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The reduction of non‐gravitational accelerations through an onboard accelerometer is a vital part of accurately estimating gravity fields for Gravity Recovery and Climate Experiment (GRACE) Follow‐On (GRACE‐FO). Current accelerometer quality, specifically a defect on the GRACE‐D accelerometer, necessitates the use of extensive calibration techniques to optimally utilize the accelerometer measurements. This paper describes these techniques and correction algorithms as they are used for the official GRACE‐FO accelerometer products, which rest on the information present in the partially functional GRACE‐D accelerometer. First, transplanted data from GRACE‐C is used to remove common effects between the spacecraft. Then, GRACE‐D data is utilized to compute a correction to the transplanted data to account for solar radiation pressure (SRP) and albedo using a parity argument and to account for non‐common drag and thruster leaks in the attitude control system. The SRP and albedo term predominantly improves C3,0 while the drag and leaky thruster term improves the gravity field across the entire spectrum. Finally, some comments on alternative data usage, initial modifications to the algorithms to account for other spacecraft operational modes, and future outlook are provided. Key Points: GRACE‐D accelerometer data, while noisy, is calibrated to recover useable signals and optimize science dataUpdated accelerometer calibrations improve gravity field recovery [ABSTRACT FROM AUTHOR]

Hazy images suffer from two problems. The low contrast can be enhanced by estimating a transmission layer, and the colour cast can be restored by estimating an airlight. These two variables, together with the albedo layer, are the constitutive elements of a hazy image. The resulting quality of dehazed images is inextricably linked to the accurate estimation of these components. However, it is ill‐posed to decompose these variables from a single image. As such, this paper presents an innovative algorithm intended to facilitate the optimal decomposition of a hazy image. Using the Markov random field model, an optimal framework is established that allows the simultaneous estimation of the three components across the three‐colour channels. To improve the visual quality, three improvements are proposed in the variational solution for the optimal components. The dehazed result is recomposed from the components with the transmission enhanced to circumvent any potential artefacts or information loss. Extensive experiments on natural images corroborate that the proposed algorithm outperforms state‐of‐the‐art dehazing methods, both qualitatively and quantitatively. [ABSTRACT FROM AUTHOR]

Radiation transport codes have been an increasingly important tool for studying the space radiation environment, which includes high‐energy and high‐nuclear‐charge particles. The unique advantage of transport models lies in covering a wider range of particles, energies, and angles than would be attainable in a laboratory or measurable by an instrument. However, since there are several transport codes developed by different teams that have contributed heavily to the literature, differences are expected between such codes. In this work, we use five such radiation transport codes (FLUctuating KAscade, GEometry ANd Tracking, High‐Energy Transport Code‐Human Exploration and Development in Space, Monte Carlo N‐Particle, and Particle and Heavy Ion Transport code System) to study the radiation environment near the Moon, specifically the lunar "albedo" radiation, which is the radiation emitted by the lunar surface through interactions with incident galactic cosmic rays and solar energetic particles. The primary goal of this paper is to provide a general characterization of the lunar albedo radiation and to find the areas where the modeled transport codes agree and disagree by using almost identical input parameters. The results of this work show overall good agreement between the codes. However, some areas of discrepancies exist that are reported herein. Thus, this paper equips the space weather and radiation biology communities with a comparison between popular radiation transport models applied to lunar albedo radiation. The overall agreement and, in some cases, discrepancies between these transport codes provide fundamental insight necessary for assessing code reliability and identifying where further study and improvements are needed to advance our understanding of lunar albedo radiation. Plain Language Summary: Replicating the lunar radiation environment in a laboratory is extremely difficult for multiple reasons. One of the most effective alternatives is to use computer simulations equipped with the physical and mathematical tools to help us understand radiation in space. However, there are multiple radiation codes developed by different teams. Comparing the results from such codes and finding the areas of agreement and disagreement in their results help in improving the codes and in providing a better understanding of the space radiation environment. In this work, we studied the lunar radiation environment by comparing five different well‐known radiation codes. In general, the results show a good agreement between the codes. However, we found some areas of disagreements that are reported herein. Key Points: The lunar albedo radiation was modeled using five different radiation transport codes: FLUctuating KAscade, GEometry ANd Tracking, High‐Energy Transport Code‐Human Exploration and Development in Space, Monte Carlo N‐Particle, and Particle and Heavy Ion Transport code SystemThe results of this work show overall good agreement between the codes. However, some areas of discrepancies exist that are reported herein [ABSTRACT FROM AUTHOR]

Optical remote sensing observations have suggested that the top layer of Europa's icy surface is heavily affected by external weathering agents. To model and understand these effects, it is necessary to characterize the environment as fully as possible. In this paper, we focus on one agent in the environment (energetic electrons). We show Juno electron data from its 2022 Europa flyby and other time periods. While the Juno sensor used here (Jupiter Energetic Particle Detector Instrument) was not designed to obtain high quality electron data in an intense radiation environment, it is possible to extract information such as how Europa blocks energetic particles from accessing some of the surrounding space. The decrease in charged particle flux in Europa's wake provides an upper limit on the precipitation fluxes of the same particles. We also report that electron pitch angle distributions near Europa for the single energy channel considered here are time variable and not isotropic. Plain Language Summary: We present energetic electron data obtained when the Juno spacecraft crossed the plasma wake of the moon Europa in 2022. A major goal of this work is to estimate the amount of blockage of MeV electrons near the moon to inform radiation estimates for future Europa orbiters and landers. While the Jupiter Energetic Particle Detector Instrument does not directly detect particles between 1 and 20 MeV, using knowledge gained since the instrument began obtaining data we were able to estimate that about 80% of the particles in question are blocked by Europa in its wake at low altitude. Research on the weathering of Europa's surface by electrons is also discussed. Key Points: Jupiter Energetic Particle Detector Instrument electron data relevant to Europa are presentedWe estimate Europa's blockage causes an ∼80% reduction of ∼1–20 MeV electrons in the immediate plasma wakePitch angle distributions are computed from 70 keV electron data and show time variability [ABSTRACT FROM AUTHOR]

The estimation of cloud radiative forcing due to aerosol‐cloud interactions, RFaci (also known as the first indirect effect), relies on approximating the cloud albedo susceptibility to changes in droplet concentration, β. β depends on the cloud albedo and droplet concentration, both of which can be observed by satellites. Satellite observations are often spatially aggregated to coarser resolutions, typically 1 × 1° scenes. However, on such spatial scales, the cloud albedo tends to be heterogeneous, whereas the β approximation assumes homogeneity. Here, we demonstrate that the common practice of aggregating satellite data and neglecting cloud albedo heterogeneity results in an average overestimation of 10% in previous estimates of the RFaci. Additionally, we establish a relationship between the magnitude of the bias in β and Stratocumulus morphologies, providing a physical context for cloud heterogeneity and the associated bias. Lastly, we propose a correction method that can be applied to cloud albedo gridded data. Plain Language Summary: This paper explores the effect of cloud albedo morphology, which is a reflection of cloud heterogeneity, on radiative forcing due to aerosol‐cloud interactions (RFaci). The RFaci is estimated from satellite observations based on the assumption that clouds are homogeneous within a given scene. However, when satellite data is spatially aggregated to reduce the amount of data to a user‐friendly gridded format—a common practice—this assumption is no longer valid. Consequently, an overestimation of the RFaci occurs, particularly in heterogeneous scenes, where the overestimation can reach up to 50%. This means that the RFaci is lower than previously estimated. Our results also suggest that cloud albedo enhancement due to an increase in droplet concentrations would be most effective in homogeneous scenes. Therefore, marine cloud brightening strategies should take cloud albedo homogeneity into account to achieve the most effective albedo enhancement. Key Points: The common practice of spatial aggregation of satellite data into 1 × 1° scenes leads to an average 10% overestimation of the RFaciThe overestimation is due to neglecting cloud albedo heterogeneity, and is associated to different types of Stratocumulus morphologiesA correction is proposed, which calls for the incorporation of cloud reflectance statistics in Level 3 data [ABSTRACT FROM AUTHOR]

The Last Glacial Maximum extent of the North American Ice Sheets is well constrained empirically but has proven to be challenging to simulate with coupled Climate‐Ice Sheet models. Coupled Climate‐Ice Sheet models are often too computationally expensive to sufficiently explore uncertainty in input parameters, and it is unlikely that values calibrated to reproduce modern ice sheets will reproduce the known extent of the ice at the Last Glacial Maximum. To address this, we run an ensemble with a coupled Climate‐Ice Sheet model (FAMOUS‐ice), simulating the final stages of growth of the last North American Ice Sheets' maximum extent. Using this large ensemble approach, we explore the influence of numerous uncertain ice sheet albedo, ice sheet dynamics, atmospheric, and oceanic parameters on the ice sheet extent. We find that ice sheet albedo parameters determine the majority of uncertainty when simulating the Last Glacial Maximum North American Ice Sheets. Importantly, different albedo parameters are needed to produce a good match to the Last Glacial Maximum North American Ice Sheets than have previously been used to model the contemporary Greenland Ice Sheet due to differences in cloud cover over ablation zones. Thus, calibrating coupled climate‐ice sheet models on one ice sheet may produce strong biases when the model is applied to a new domain. Plain Language Summary: At the peak of the last ice age, an ice sheet covered much of North America. The extent of this ice sheet is well‐understood after decades of intensive data collection, but producing a computer simulation of the ice sheet which matches our observations has been a challenge. This is partly because of uncertainty about the "correct" model set‐up to create the best simulation, and partly because the computer models used in the simulations require large computing resources. In this paper, we present a series of simulations of the North American Ice Sheet at the peak of the last ice age using a fast‐running computer model in which the atmosphere and ice sheets interact. We run hundreds of simulations to tackle the uncertainty about the optimum values for unknown input parameters. We find that the model's representation of how reflective the ice sheet surface is has the most impact on the size and shape of the simulated ice sheet. Importantly, the parameter values that produce the best simulations of modern‐day Greenland produce poor simulations of the North American Ice Sheets during the last ice age, calling into question whether the parameters chosen for modern Greenland are appropriate from simulating ice sheets under different conditions. Key Points: Simulating the Last Glacial Maximum North American Ice Sheets successfully requires de‐tuning the coupled Climate‐Ice Sheet model FAMOUS‐iceAfter running a large ensemble, we identify multiple acceptable simulations of the LGM North American Ice SheetThe LGM North American cloud cover revealed overtuned albedo parameters to compensate for modern Greenland cloud biases [ABSTRACT FROM AUTHOR]

In this paper, a method previously developed for reconstructing daily erythemal ultraviolet (UVery) doses in Novi Sad (Serbia) was improved and used for estimating daily UVery over the period 1971–2018. The proposed new method uses reanalysed total ozone column (TOC) data and snow cover as an input and is based on the empirical relationship between relative sunshine duration and relative UVery doses. Introducing reanalysed TOC data and snow cover data significantly improved the quality and accuracy of the reconstructed UVery time series, particularly in the winter season. The reconstructed time series revealed the statistically significant increase in summer and winter UVery in the 1980s and the first half of the 1990s (+8.78% and + 13.14% per decade, respectively), which was linked to the statistically significant decline in TOC (−4.13 and −7.36% per decade, respectively). The study focuses on days with high erythemal UV dose (highUVery), which is defined based on the 90th percentile of the daily UVery for each month. Moreover, the influence of low TOC, low cloud cover conditions, and high surface albedo on highUVery was analysed on a seasonal basis. The results of this study show that highUVery days increased from the 1980s, particularly strongly in the period of TOC depletion. A fraction of highUVery days in the last two decades was large (12.29%), which is higher than in the previous periods (6.97 and 8.68% in the period before and during TOC depletion, respectively). The occurrence of highUVery days was influenced mostly by low cloud cover (89.71% of days), and low TOC (82.23% of days). In the winter season, high surface albedo influenced the appearance of 19.18% of highUVery days. However, overall the interaction of low cloud cover and low TOC in all seasons most often led to the appearance of highUVery days. [ABSTRACT FROM AUTHOR]

The SMART‐s (Spectral Measurements for Atmospheric Radiative Transfer—spectroradiometer) acquires Sun/sky observations for retrieving optimal information on trace gases and aerosols with minimal assumptions. Overall, the algorithm of SMART‐s incorporates a series of retrievals, from fundamental quantities (i.e., column abundance of trace gases and aerosol loading) to higher‐order geophysical parameters (e.g., aerosol physicochemical properties and vertical profiles), utilizing Sun/sky spectral radiance measurements. This paper describes the theoretical basis for column retrievals of trace gases and aerosols. Associated profile retrievals will be presented in follow‐up papers. The current algorithm retrieves the fine/coarse mode of the particle size distribution and spectral complex index of refraction and, thereby, the spectral aerosol single‐scattering albedo ω0. SMART‐s retrieval is unique particularly in its high spectral resolution of the complex index of refraction and ω0 from near‐ultraviolet to near‐infrared wavelengths, which is pivotal information for atmospheric chemistry, climate and other inversions. We theoretically assessed information content and retrieval accuracy of the algorithm and compared different type of measurements including the Aerosol Robotic Network (AERONET) and standard Pandora. For the same levels of radiometric accuracy, SMART‐s measurements provide the most informative aerosol retrievals based on theoretical error analyses. Higher spectral resolution measurements are particularly beneficial for particle size distribution and fine‐mode refractive index retrievals. We applied this algorithm to the AERONET Sun/sky measurements at Kanpur, India, in 2016 to assess algorithm consistency. Even with different assumptions and numerical methods for the inversion, SMART‐s retrieved aerosol parameters agreed well with the AERONET operational products (e.g., absolute mean bias errors less than 0.01 for ω0). Key Points: The SMART‐s algorithm retrieves aerosol particle size distributions and spectral complex index of refraction from about 310 to 800 nmWe applied the SMART‐s algorithm to the AERONET Sun/sky measurements and the retrievals were consistent with the operational products of AERONETHigh spectral resolution of the SMART‐s retrievals can provide unique information for atmospheric chemistry, air quality, and climate studies [ABSTRACT FROM AUTHOR]

This paper presents a methodology to build multipath models for aviation use of new Global Positioning System (GPS) and Galileo signals. The estimation of airframe multipath errors makes use of carrier phase measurements; thus, it is affected by the integer ambiguities. A new method for removing the ambiguities from the multipath estimation is presented. The method is suitable for measurements from flight data and is able to exclude measurements highly affected by multipath from the estimation by using a derived standard deviation based on the receiver thermal noise only. Next, an overview of the error sources relevant for the multipath estimation is given, and a first concept to separate the receiver antenna errors from the multipath errors is proposed. Finally, the paper discusses overbounding of the observed multipath errors to safely bound the tail risks and the inflation needed to account for uncertainty due to limited amounts of data. [ABSTRACT FROM AUTHOR]

Land surface temperature anomalies can be linked to changes in local surface energy balance, although the relationship between surface temperature variability and individual radiative processes remains unclear. In this paper, we quantify the contributions of surface radiative effects and non‐radiative heat fluxes to the variance of monthly land surface temperature using European Centre for Medium‐Range Weather Forecasts Reanalysis v5 data and Coupled Model Intercomparison Project Phase 6 simulations. The surface energy budget equation is used to link changes in surface radiation, surface heat fluxes and land surface temperature. Subsequently, surface radiation is decomposed into the radiative effects of clouds, air temperature, surface albedo and relative humidity using radiative kernels. The contributions of these radiative processes, including their coupling effects, are quantified using covariance matrices. The results reveal the air temperature radiative effect to be the most significant contributor to the variability of land surface temperature. In addition, the covariance terms reveal important coupling effects. For example, the contribution from the cloud radiative effect is found to be substantially dampened by its coupling with surface heat fluxes. The air temperature radiative effect is further decomposed into a forcing component and a feedback component using different regression methods, in an attempt to separate the air temperature radiative effect as the driver of the surface temperature variability. The cloud radiative effect becomes the primary contributor to the variance of surface temperature after separating the air temperature feedback, while the contribution of the air temperature radiative forcing remains important. Plain Language Summary: Land surface temperature is critical environmental variable. Through a statistical analysis of the European Centre for Medium‐Range Weather Forecasts Reanalysis v5 data and Coupled Model Intercomparison Project Phase 6 multi‐model simulations, we have explained the land surface temperature variability in relation to the surface energy fluxes. Specifically, we have attributed the variability of monthly surface radiation to the effects of different meteorological variables such as clouds, air temperature, surface albedo and relative humidity. Our findings suggest that the radiative effect of air temperature is the primary contributor to the variance of land surface temperature in most regions, although this effect includes a strong feedback effect of air temperature to surface temperature changes. After separating this feedback effect, the cloud radiative effect becomes the primary contributor. On the other hand, the contribution from cloud radiative effect is significantly counteracted by its coupling with surface heat fluxes. Key Points: The variance of land surface temperature is decomposed to contributions from surface radiative effects and heat fluxesThe radiative effect of air temperature is found to contribute the most to surface temperature variabilityThe cloud radiative effect is found to be the primary contributor after decoupling the air and surface temperature variations [ABSTRACT FROM AUTHOR]

The relative importance of radiative feedbacks and emissions scenarios in controlling surface warming patterns is challenging to quantify across model generations. We analyze three variants of the Community Earth System Model (CESM) with differing equilibrium climate sensitivities under identical CMIP5 historical and high‐emissions scenarios. CESM1, our base model, exhibits Arctic‐amplified warming with the least warming in the Southern Hemisphere middle latitudes. A variant of CESM1 with enhanced extratropical shortwave cloud feedbacks shows slightly increased late‐21st century warming at all latitudes. In the next‐generation model, CESM2, global‐mean warming is also slightly greater, but the warming is zonally redistributed in a pattern mirroring cloud and surface albedo feedbacks. However, if the nominally equivalent CMIP6 scenario is applied to CESM2, the redistributed warming pattern is preserved, but global‐mean warming is significantly greater. These results demonstrate how model structural differences and scenario differences combine to produce differences in climate projections across model generations. Plain Language Summary: Earth System Models are used to project climate change through the 21st century. Such projections are constrained by a range of assumptions about emissions of greenhouse gases as well as other climate‐relevant human activities like deforestation and emissions of aerosols. These assumptions are carefully evaluated and represented in an emissions scenario. In a coordinated set of experiments, a given emissions scenario is applied to a number of different Earth System Models to test differences in climate projections that arise from physical (or "structural") differences among the models. However, over time, models are updated and improved, and emissions scenarios are updated as well. This continuous updating makes it difficult to track whether a new set of climate projections is different from its predecessor due to model changes or due to scenario changes. In this paper, we disentangle these two factors, clarifying the role of each. For the Earth System Model that we use, the emissions scenario largely controls the amount of global‐mean warming projected for the 21st century, but the model or structural differences matter greatly for the regional patterns of warming. Key Points: Higher equilibrium climate sensitivity, from more positive cloud feedbacks, only slightly increases 21st century transient warmingCloud and surface albedo feedbacks redistribute warming from the middle and high northern latitudes to lower latitudesThese warming pattern differences result from feedback differences, not CMIP5 to CMIP6 forcing scenario differences [ABSTRACT FROM AUTHOR]

Shadow removal from a single image is an ill‐posed problem because shadow generation is affected by the complex interactions of geometry, albedo, and illumination. Most recent deep learning‐based methods try to directly estimate the mapping between the non‐shadow and shadow image pairs to predict the shadow‐free image. However, they are not very effective for shadow images with complex shadows or messy backgrounds. In this paper, we propose a novel end‐to‐end depth‐aware shadow removal method without using depth images, which estimates depth information from RGB images and leverages the depth feature as guidance to enhance shadow removal and refinement. The proposed framework consists of three components, including depth prediction, shadow removal, and boundary refinement. First, the depth prediction module is used to predict the corresponding depth map of the input shadow image. Then, we propose a new generative adversarial network (GAN) method integrated with depth information to remove shadows in the RGB image. Finally, we propose an effective boundary refinement framework to alleviate the artifact around boundaries after shadow removal by depth cues. We conduct experiments on several public datasets and real‐world shadow images. The experimental results demonstrate the efficiency of the proposed method and superior performance against state‐of‐the‐art methods. [ABSTRACT FROM AUTHOR]

Most of previous studies utilized the surface parameters from LANDSAT images to construct the feature space monitoring index model of salinisation (salinization), and a few studies that have combined the feature space model with SENTINEL‐2B MSI images have been reported. In addition, the red edge index derived from SENTINEL‐2B MSI images can provide more detailed information to indicate the vegetation condition when monitoring salinized land ecosystems. Based on SENTINEL‐2B MSI images, this paper introduces seven typical parameters, namely NDVI, MSAVI, SI, Albedo, NDre1, NDre2, and NDre3 (red edge index) to construct two category features space models (point‐to‐line type and point‐to‐point type), and then, a novel salinisation monitoring index for use in the Yellow River Delta (YRD). Our main conclusions showed that: (1) the monitoring index model based on SENTINEL‐2B MSI images and a feature space model has high applicability for the salinisation monitoring in the YRD, with an average precision of R2 = 0.8499; (2) the point‐to‐point monitoring index of soil salinisation based on the NDre1‐SI feature space model has the best inversion accuracy of R2 = 0.9305 and RMSE = 0.9926; (3) the red edge index can better indicate the state and evolution process of soil salinisation. The salinisation monitoring models that included the red edge indexes have higher inversion accuracy with an average value of R2 = 0.8650; (4) the soil salinisation in the YRD was more serious in its eastern and northeastern regions than other parts. The results provide a new technical and methodological approach for the prevention and treatment of regional salinisation. [ABSTRACT FROM AUTHOR]

Evidence from Arrokoth and comets strongly suggests a very low density for this and similar small Kuiper belt objects. Plausible compositions imply high porosities, in excess of 70%, and low compaction crush strengths. If so, impact craters on Arrokoth (especially Sky, its largest) formed largely by compaction of pore space and material displacement. This is consistent with geological evidence from New Horizons imaging. High porosity reduces cratering efficiency in the gravity regime whereas compaction moves it toward crush strength scaling and increased efficiency. Compaction also guarantees that most impactor kinetic energy is taken up as waste heat near the impact point, with momentum transferred to the rest of the body by elastic waves only. Monte Carlo simulations of Sky‐forming conditions indicate that the momentum imparted likely separated Arrokoth's two lobes, but displacement was limited by dissipation at the neck between them. Unusual strength properties are not required to preserve Arrokoth's bilobate configuration. Plain Language Summary: It has become apparent over the last few years that small asteroids and comets are very underdense compared with the materials they are made of. This means that their total porosities are likely quite high, in excess of 70%, both as tiny voids within particles (so‐called microscopic porosity) and spaces between particles (macroscopic porosity). But none are likely as porous as the distant denizens of the Kuiper belt such as Arrokoth (visited by the New Horizons spacecraft in 2019). This paper concerns impact craters on Arrokoth and similar small bodies, and the rather unusual effects expected. Imagine a fluffy (fine powder) snowball striking a much larger fluffy snowball, only that the snow is not pure ice but a mixture of porous icy, rocky, and carbon‐rich particles. Even at high velocities (>100 s of m/s) craters should mostly form by compacting pore space and pushing material away from the impact point, not the traditional blasting of ejecta back into space. Similar to crush‐up of an automobile bumper, compaction helps to protect from the potentially catastrophic effects of large impacts, such as complete disruption of the target or breakup of bilobate bodies like Arrokoth, and should be incorporated in future collisional evolution studies. Key Points: Arrokoth is likely a low density, highly porous, contact binary planetesimalImpact craters on Arrokoth, and particularly its largest, likely formed as compaction craters, with modest or little ejectaHigh porosity acted to protect Arrokoth from catastrophic disruption, ejecta recoil, and lobe dislocation and rearrangement [ABSTRACT FROM AUTHOR]

Boreal coniferous forests decrease climate forcing by sequestering carbon from the atmosphere. However, they also increase climate forcing through their effect on surface albedo, as coniferous forests make Earth's surface darker. Ignoring the warming effect of albedo can lead to a flawed climate policy that overstates the benefits of forest carbon sequestration. In this paper, we examine how these climate externalities affect the socially optimal harvest rotations and the social land value of a forest stand that is managed for timber, carbon, and albedo under changing economic and ecological conditions. We also examine how the relative importance of these externalities changes over time. We show that the rotations and the land value are sensitive to the changing external conditions, especially in the long run. Hence, for policy‐ relevance, stand‐level analyses with long examination horizons should account for these changes. In general, the carbon externality increases land value and lengthens rotations, whereas the albedo externality decreases land value and shortens rotations. At our study site in Finland, the positive effect of carbon on land value is stronger than the negative effect of albedo. The opposite effects of the two externalities on the timing of harvests are currently of equal strength, which means that they cancel out. More generally, inferences regarding the impacts of the externalities vary depending on climatic conditions, the incidence of solar irradiance, and the shadow prices of carbon and albedo. We discuss the extrapolation of our results throughout the boreal region based on variation in these factors. [ABSTRACT FROM AUTHOR]

Absorbing aerosols uniquely impact radiation, aerosol transport, and meteorology. This paper quantifies black carbon core and sulphate shell size and mass using decadal measurements of multi‐spectral aerosol optical depth, single scattering albedo, and angstrom exponent from Aerosol Robotic Network stations located throughout East, Southeast, and South Asia, in connection with a MIE model. All sites are uniquely characterized into four types: urban, biomass burning, long‐range transport, and clean. Unique size and mass probability distributions of both the core and shell are calculated within each classification. Well known urban, biomass burning, and clean sites are all properly identified. Furthermore, two unique sites previously thought to not have multiple characteristics are identified, with urban and biomass burning significant in Beijing and long‐range transport significant in the otherwise clean South China Sea at Taiping Island. It is hoped that these results will allow for advances in attribution and radiative forcing studies. Plain Language Summary: Black Carbon strongly absorbs visible radiation, leading to unique impacts on atmospheric radiation, climate, the water cycle, and PM2.5. This work attributes different aerosol source characteristics, and further specifies the size distribution and concentration of aerosol black carbon cores and refractive shells. This work uses measurements of aerosol optical depth, single scatter albedo, and angstrom exponent, across multiple different wavelengths of light, in combination with statistics and a MIE model (physical model of aerosol/radiation interaction) using a Core‐Shell approximation. The results show that aerosols observed in East, Southeast, and South Asia can be uniquely classified into four types: urban, biomass burning, long‐range transport, and clean. These results are consistent in terms of aerosol size and mass at each site within each type of characterization. Furthermore, two unique sites are identified in which a second characteristic occurs some significant fraction of every year, which otherwise was not known or previously identified in the literature. These results are expected to help enhance the understanding of attribution of aerosols, as well as provide specific size and mass details of the aerosols useful to improve radiative forcing models and aerosol impacts on climate change. Key Points: Aerosols are categorized into biomass burning, urban, and long‐range types over Asia using decadal long multi‐spectral measurementsBased on multiple Aerosol Robotic Network Single Scatter Albedo measurements and a MIE model, physical characteristics of different aerosol types are deducedMost aerosols are found to be mixed, with two sites having different characteristics during different times of the year [ABSTRACT FROM AUTHOR]

Orbital Earth Radiation Budget measurement comparisons to models, are critical for climate prediction confidence. Satellite systems must reduce calibration drifts for this purpose. NASA Clouds and the Earth's Radiant Energy System (CERES) measures Earth albedo reductions that if correct, would increase solar forcing and suggest greater sunlight absorption is driving much of recent temperature increases. Such results are presented, alongside those from the Moon and Earth Radiation Budget Experiment (MERBE). MERBE uses constant lunar reflectivity for tracking and compensation of instrument telescope degradation, undetectable by CERES. MERBE finds Earth albedo constant compared to that of the Moon, because Arctic solar warming effects are balanced by solar cooling elsewhere, likely due to negative feedbacks. Contrary to NASA, this shows the Sun is not increasing warming and that CERES results are not as stable as claimed and assumed. Furthermore, MERBE can actually resolve Cloud Radiative Forcing (CRF) signals from the existing record, rather than in decades with official observations. Plain Language Summary: In contrast to NASA Clouds and the Earth's Radiant Energy System results, this paper shows that the Earth reflectivity has not changed since the year 2000, by comparing the sunlight bouncing off it to that from the Moon. Disagreeing with NASA, this provides physical evidence that global warming is not being increased by the Sun. It also immediately brings data to the standard requested by the climate community for cloud forcing/feedback signal detection. The Moon and Earth Radiation Budget Experiment data is being staged for free on the FAIR compliant website Pangaea for climate scientists. Key Points: The Sun is not causing climate change and Cloud Radiative Forcing (CRF) signals can now be detected immediatelyArctic heating is being balanced by reflectivity increases elsewhereThe calibration accuracy of data is sufficient to detect uncertain cloud feedback signals immediately, rather than in decades [ABSTRACT FROM AUTHOR]

The moon Ganymede has a strong internally generated magnetic field that separates the surface into two regions, with the polar surface magnetically connected to the Jovian environment. Consequently, the weathering of Ganymede's surface by plasma and energetic charged particles trapped in the Jovian magnetosphere is not uniform. At the same time, optical data suggest differences in the surface ice between the poles and the equator, with further refinements in the equatorial surface that have a longitudinal dependence. Here, we use Juno spacecraft data to characterize the charged particle environment along Ganymede's orbit (from about 50 eV to 1 MeV for electrons and 10 eV to 6 MeV for protons). These results put us into a better position to test the hypothesis that space weathering by electrons causes the brighter poles of Ganymede, given that electron fluxes are likely to be more clearly separated between the polar and equatorial regions. Plain Language Summary: Electron weathering of ice may be the reason Ganymede's poles are brighter. These particles are well separated by the two magnetic topologies of Ganymede, whereas ions are not as well separated. We suggest ions may be converted to energetic neutral atoms near Ganymede and reach the surface despite the magnetic barrier. We quantify the environmental inputs in this paper. Key Points: Juno orbital evolution has allowed better characterization of the region near Jupiter's magnetic equator and Ganymede's orbital distanceElectron and proton energy spectra from that region derived from Jovian Auroral Distributions Experiment (JADE) and Jupiter Energetic‐particle Detector Instrument (JEDI) data are presentedWe propose that polar versus equatorial albedo differences on Ganymede are due to changes resulting from electron precipitation [ABSTRACT FROM AUTHOR]

We present a differentiable ray‐tracing based novel face reconstruction approach where scene attributes – 3D geometry, reflectance (diffuse, specular and roughness), pose, camera parameters, and scene illumination – are estimated from unconstrained monocular images. The proposed method models scene illumination via a novel, parameterized virtual light stage, which in‐conjunction with differentiable ray‐tracing, introduces a coarse‐to‐fine optimization formulation for face reconstruction. Our method can not only handle unconstrained illumination and self‐shadows conditions, but also estimates diffuse and specular albedos. To estimate the face attributes consistently and with practical semantics, a two‐stage optimization strategy systematically uses a subset of parametric attributes, where subsequent attribute estimations factor those previously estimated. For example, self‐shadows estimated during the first stage, later prevent its baking into the personalized diffuse and specular albedos in the second stage. We show the efficacy of our approach in several real‐world scenarios, where face attributes can be estimated even under extreme illumination conditions. Ablation studies, analyses and comparisons against several recent state‐of‐the‐art methods show improved accuracy and versatility of our approach. With consistent face attributes reconstruction, our method leads to several style – illumination, albedo, self‐shadow – edit and transfer applications, as discussed in the paper. [ABSTRACT FROM AUTHOR]

The necessary reduction of greenhouse gas (GHG) emissions may lead in the future to an increase in solar irradiance (solar brightening). Anthropogenic aerosols (and their precursors) that cause solar dimming are in fact often co‐emitted with GHGs. While the reduction of GHG emissions is expected to slow down the ongoing increase in the greenhouse effect, an increased surface irradiance due to reduced atmospheric aerosol load might occur in the most populated areas of the earth. Increased irradiance may lead to air warming, favour the occurrence of heatwaves and increase the evaporative demand of the atmosphere. This is why effective and sustainable solar radiation management strategies to reflect more light back to space should be designed, tested and implemented together with GHG emission mitigation. Here we propose that new plants (crops, orchards and forests) with low‐chlorophyll (Chl) content may provide a realistic, sustainable and relatively simple solution to increase surface reflectance of large geographical areas via changes in surface albedo. This may finally offset all or part of the expected local solar brightening. While high‐Chl content provides substantial competitive advantages to plants growing in their natural environment, new plants with low‐Chl content may be successfully used in agriculture and silviculture and be as productive as the green wildtypes (or even more). The most appropriate strategies to obtain highly productive and highly reflective plants are discussed in this paper and their mitigation potential is examined together with the challenges associated with their introduction in agriculture. [ABSTRACT FROM AUTHOR]

Surface albedo is a crucial parameter in land surface radiation budget. As bias exists between the model simulated and observed surface albedo, data assimilation is an important method to improve the simulation results. Moreover, surface albedo is associated with the wavelength of the sunlight. So, solar radiation partitioning is important to parameterize the surface albedo. In this paper, the moderate resolution imaging spectroradiometer- (MODIS-) retrieved direct visible, direct near-infrared, diffuse visible, and diffuse near-infrared surface albedos were assimilated into the integrated urban land model (IUM). The solar radiation partitioning method was introduced to parameterize the surface albedo. Based on the albedo data from MODIS and the solar radiation partitioning method, the surface albedo data set for the Beijing municipal area was generated. Based on the surface albedo data set and the IUM, the impacts of the surface albedo on the surface radiation budget were discussed quantitatively. Surface albedo is inversely proportional to the net radiation. For urban areas, after assimilation, the annual average net radiation decreases about 5.6%. For cropland, grassland, and forest areas, after assimilation, the annual average net radiations increase about 20.2%, 24.3%, and 18.7%, respectively. [ABSTRACT FROM AUTHOR]

The aim of this paper is to biosynthesize NiFe2O4/SiO2/Au (NiFe/Si/Au) magnetic nanocatalyst using the sonochemical method. This is the first study to synthesize this compound using this method. To obtain optimum morphology and size of products, the synthesis was performed in the presence of polyvinylpyrrolidone, maltose, glucose, and fructose as capping agents and Crataegus pentagyna leaf extract and NaBH4 as reducing agents. Vibrating‐sample magnetometer, field‐emission scanning electron microscopy, Fourier‐transform infrared, transmission electron microscopy, X‐ray diffraction, energy‐dispersive X‐ray spectroscopy, and differential reflectance spectroscopy techniques were performed to confirm the preparation of magnetic products. The as‐synthesized magnetic samples were used to enhance the photocatalytic degradation and antibacterial activity. The NiFe/Si/Au nanocatalysts exhibited an excellent photocatalytic activity by degradation of rhodamine b, methylene blue, and erythrosine as organic contaminants under ultraviolet and visible light irradiation. The degradation curves illustrate that the degradation of anionic dyes is more than that of cationic dyes. In addition, antibacterial activity of as‐prepared nanocatalyst against seven bacterial species was investigated. Because of their antibacterial effects, as‐synthesized products show a high antibacterial activity against various bacteria. Consequently, the NiFe/Si/Au nanocatalysts with high antibacterial activity and excellent potential photocatalyst activity can be used in environmental and medical sciences for wastewater treatment. [ABSTRACT FROM AUTHOR]

Increasing the albedo of urban surfaces, through strategies like white roof installations, has emerged as a promising approach for urban climate adaptation. Yet, modeling these strategies on a large scale is limited by the use of static urban surface albedo representations in the Earth system models. In this study, we developed a new transient urban surface albedo scheme in the Community Earth System Model and evaluated evolving adaptation strategies under varying urban surface albedo configurations. Our simulations model a gradual increase in the urban surface albedo of roofs, impervious roads, and walls from 2015 to 2099 under the SSP3‐7.0 scenario. Results highlight the cooling effects of roof albedo modifications, which reduce the annual‐mean canopy urban heat island intensity from 0.8°C in 2015 to 0.2°C by 2099. Compared to high‐density and medium‐density urban areas, higher albedo configurations are more effective in cooling environments within tall building districts. Additionally, urban surface albedo changes lead to changes in building energy consumption, where high albedo results in more indoor heating usage in urban areas located beyond 30°N and 25°S. This scheme offers potential applications like simulating natural albedo variations across urban surfaces and enables the inclusion of other urban parameters, such as surface emissivity. Plain Language Summary: Higher albedo surfaces reflect more sunlight, which helps cool down cities. Yet, research into how altering the albedo of urban surfaces on a global scale can aid climate adaptation is limited. It either relies on empirical analysis, oversimplifying urban physical processes, or assumes that urban surface albedo remains constant over time. These limitations hinder our understanding of how changes in urban surfaces can impact the urban thermal environment. In this study, we developed a new option that allows urban surface albedo to vary over time within a global climate model. By gradually increasing global urban surface albedo, we quantified the cooling effects of implementing high urban albedo in a more realistic way. This new option sets the stage for future exploration of scenarios like painting roofs white or how materials age, shedding light on effective urban climate adaptation strategies. Key Points: We developed a new representation scheme of transient urban surface albedo in Community Earth System Model (CESM) to improve urban climate adaptation modelingThe new scheme enables CESM to assess evolving adaptation strategies for roofs, impervious roads, and walls over timeSimulations show increasing roof albedo cools cities more effectively than increasing wall or impervious road albedo [ABSTRACT FROM AUTHOR]

Surface albedo is one of the key parameters of land surface radiation and energy balance. As surface albedoes for visible and near-infrared solar radiation are quite different, solar radiation partitioning is important to parameterize the total surface albedo and upward solar radiation. In this paper, a surface albedo parameterization scheme was introduced and a solar radiation partitioning method was developed to improve the simulation of the upward solar radiation. The simulation results were validated in a hinterland site of the Taklimakan Desert. The surface albedo is not only associated with the soil moisture, but associated with the solar zenith angle. The solar radiation partitioning method considers the joint influences of cloud cover, near-surface air pressure, and solar zenith angle and was compared with the method using the Simple Biosphere Model version 3 (SiB3). The total albedo depends on the partitioning of the total visible and near-infrared radiations. The results indicate the surface albedo parameterization scheme is important to parameterize the upward solar radiation. The new solar radiation partitioning method could improve the simulation result. [ABSTRACT FROM AUTHOR]

As a widespread landscape, rugged terrain significantly distorts the land surface albedo. Simply neglecting the topographic effects in the land surface albedo modeling and retrievals can lead to large biases and uncertainties over rugged terrain. In spite of gradually increasing research about the topographic effects on the albedo, the albedo sensitivities over rugged terrain to different variables remain unclear. In this paper, the sensitivities of coarse‐scale snow‐free albedo to topography were quantitatively investigated using the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface albedo data and the variance‐based global sensitivity analysis based on a well‐established mechanistically‐based land surface albedo parameterized model over rugged terrain. The results based on the MODIS data revealed that MODIS land surface albedo over the Tibetan Plateau was highly sensitive to the topographic distribution, and the differences of the spatially averaged snow‐free black‐sky albedos over grasslands induced by different terrain could reach up to 0.10 in winter. The topographic effects on MODIS albedo are tightly relevant to the land cover type, solar illumination geometries, and vegetation characteristics. The global sensitivity analysis results underscored that topography was an important driving factor of the snow‐free albedo, and it accounted for more than 30% of the total variance, respectively. These results highlight the necessities for the topographic consideration in the land surface albedo modeling and retrievals even though the terrain is gentle (10–20°) and advance our understanding of the albedo sensitivities to different variables over rugged terrain, which will facilitate the improvement of land surface albedo parameterization in the land surface models. Key Points: We quantitatively investigated the sensitivities of coarse‐scale snow‐free albedo to topography using MODIS data and global sensitivity analysis methodMODIS land surface albedo over the Tibetan Plateau is highly sensitive to the topographic distributionThe mean slope and aspect anisotropic index account for about 16.7% and 14% of the total variance, respectively [ABSTRACT FROM AUTHOR]

Abstract: In situ albedo measurement over sloped surfaces is pivotal to a wide range of remote sensing applications, such as the estimation and evaluation of surface energy budget at regional and global scales. However, existing albedo measurements over rugged terrain are limited and controversial and remain a major challenge. In this paper, two commonly measured broadband albedos, which depend on incoming/outgoing geometric conditions, were characterized over sloped surfaces and illustrated. These albedos are the horizontal/horizontal sloped surface albedo (HHSA) and inclined/inclined sloped surface albedo (IISA). The 3‐D Discrete Anisotropic Radiative Transfer (DART) model simulations over varying slopes were utilized to quantify differences in the albedos. In particular, the effects of the slope, aspect, the solar zenith angle, and the proportion of diffuse skylight were investigated. The results show that absolute (relative) biases between HHSA and IISA are significant, reaching up to 0.026 (61.8%), 0.134 (62.4%), and 0.114 (62.3%) in the visible, near‐infrared, and shortwave broadbands, respectively. In addition, the diurnal cycle differences between HHSA and IISA were also compared using DART simulations and in situ observations over four typical slopes. Comparisons reveal that topographic parameters (e.g., slope and aspect) and atmospheric conditions (e.g., diffuse skylight and atmospheric visibility) are the primary factors, while the optical and structural parameters have a smaller effect. [ABSTRACT FROM AUTHOR]

Earth's Northern and Southern Hemispheres reflect essentially equal amounts of sunlight. How—and whether—this hemispheric albedo symmetry is maintained remains a mystery. We decompose Earth's hemispheric albedo symmetry into components associated with the surface, clear‐sky atmosphere, and different cloud types as defined by cloud effective pressure and optical thickness. Climatologically, greater reflection by the surface, aerosols, and high clouds in the Northern Hemisphere is balanced by greater low and mid‐level cloudiness in the Southern Hemisphere. Both hemispheres have darkened at similar rates over the past two decades; whether the darkening from more rapidly declining aerosol in the Northern Hemisphere is causing a departure from all‐sky symmetry remains uncertain. Natural experiments including long‐term trends, sea ice loss, and volcanic eruptions provide strong evidence against the hypothesis that extratropical low clouds compensate changing clear‐sky asymmetries on annual‐to‐decadal timescales but some evidence that tropical high cloud shifts may do so. Plain Language Summary: Mysteriously, the Northern and Southern Hemispheres reflect the same amount of sunlight as each other, but scientists are not yet sure why, how, or even whether this phenomenon is sustained by the Earth system. The Northern Hemisphere is brighter in clear skies because it contains more pollution particles in the atmosphere and has more land area, whereas the Southern Hemisphere is cloudier. We break down this cloudiness contrast into components related to different cloud types defined by their height and thickness. Tropical high‐altitude clouds increase reflection preferentially in the Northern Hemisphere but are overcompensated by low‐ and mid‐level clouds in the Southern Hemisphere, especially in the subtropics and midlatitudes. Both hemispheres have darkened over the past two decades, but whether the Northern Hemisphere is darkening faster than the Southern Hemisphere due to decreasing particulate pollution or if they are darkening at the exact same rate remains uncertain. Based on long‐term trends and "natural experiments" like sea ice loss and volcanic eruptions, we can rule out the hypothesis that low‐level clouds in the Southern Ocean act to balance out clear‐sky asymmetries at yearly‐to‐decadal timescales, but we cannot rule out the hypothesis that high‐altitude tropical clouds do so. Key Points: Greater reflection from Northern Hemisphere clear‐skies and high clouds is balanced by Southern Hemisphere low and mid‐level cloudsEvidence points against extratropical low cloud adjustments compensating for clear‐sky albedo changes on decadal timescalesLimited and conflicting evidence for whether shifts in tropical high clouds compensate clear‐sky changes at annual to decadal timescales [ABSTRACT FROM AUTHOR]

This paper presents a new water and energy budget-based glacier mass balance model. Enthalpy, rather than temperature, is used in the energy balance equations to simplify the computation of the energy transfers through the water phase change and the movement of liquid water in the snow. A new parameterization for albedo estimation and state-of-the-art parameterization schemes for rainfall/snowfall type identification and surface turbulent heat flux calculations are implemented in the model. This model was driven with meteorological data and evaluated using mass balance and turbulent flux data collected during a field experiment implemented in the ablation zone of the Parlung No. 4 Glacier on the Southeast Tibetan Plateau during 2009 and 2015-2016. The evaluation shows that the model can reproduce the observed glacier ablation depth, surface albedo, surface temperature, sensible heat flux, and latent heat flux with high accuracy. Comparing with a traditional energy budget-based glacier mass balance model, this enthalpy-based model shows a superior capacity in simulation accuracy. Therefore, this model can reasonably simulate the energy budget and mass balance of glacier melting in this region and be used as a component of land surface models and hydrological models. [ABSTRACT FROM AUTHOR]

The Empty Quarter Desert, one of Earth's major dust sources, frequently experiences dust storms due to wind erosion. Despite its significance as a primary dust source on a global scale, in‐situ observations from this region had not been reported until very recently. In summer 2022, the WInd‐blown Sand Experiment (WISE) Phase‐1 was initiated in the Empty Quarter Desert of the United Arab Emirates, and continued until 7 February 2023. Utilizing a diverse array of instruments, we measured winds, temperature, humidity, radiation fluxes, saltation, and the physical and optical properties of dust aerosols, atmospheric electric fields, and soil characteristics. A total of 38 distinct sand‐saltation events were recorded from September 2022 to February 2023, with activity peaking between 13:00 and 14:00 local time. Key findings include the identification of dominant wind patterns, and the measurement of the average aerodynamic roughness length (z0) at 0.8 ± 0.6 mm, and the thermal roughness length (zh) at 0.3 ± 0.5 mm—the first estimation of zh for this area. In‐situ observations revealed that dust particle concentrations near the surface increased 1.7‐fold on days with saltation compared to days without it. Moreover, we determined a wind‐speed threshold for initiating saltation at 7.70 m s−1. This comprehensive data set significantly advances our understanding of atmospheric‐soil interactions and sand movement dynamics, providing invaluable insights for ongoing research into desert environments and the global dust cycle. Plain Language Summary: The Empty Quarter Desert, one of the Earth's major dust sources, frequently experiences dust storms due to wind erosion. Despite its importance as a main dust source on a global scale, no in‐situ observations from this region have been reported until very recently. In the summer of 2022, the WInd‐blown Sand Experiment (WISE) Phase‐1 provided crucial data on the arid environment of the Empty Quarter Desert in the United Arab Emirates. Lasting until February 2023, this experiment focused on quantifying environmental and soil characteristics through an array of measurements, including wind direction and speed, temperature, humidity, radiation fluxes, and dust particle concentrations. The study revealed dominant wind patterns, quantified the aerodynamic and thermal roughness of the desert soil, and recorded 38 distinct sand movement events, noting a peak in activity during early afternoon hours. This research is significant for its detailed analysis of particle concentration changes during these events and its establishment of a specific wind speed threshold for sand movement in this region. These findings are invaluable for researchers studying desert environments, particularly in terms of understanding atmospheric‐soil interactions and the dynamics of sand movement. Key Points: First‐of‐its kind experiment in the Empty Quarter Desert to characterize environmental dynamicsThe first estimation of the thermal roughness length (zh) for this desert and is found to be 0.3 mmThe derived wind‐speed threshold for saltation at the Empty Quarter Desert is 7.70 m s−1 [ABSTRACT FROM AUTHOR]

Research on albedo enhancement by stratospheric sulfur injection inspired by Paul Crutzen's paper a decade ago has made clear that it may present serious risks and concerns as well as benefits if used to address the global warming problem. While volcanic eruptions were suggested as innocuous examples of stratospheric aerosols cooling the planet, the volcano analog also argues against stratospheric geoengineering because of ozone depletion and regional hydrologic responses. Continuous injection of SO2 into the lower stratosphere would reduce global warming and some of its negative impacts, and would increasing the uptake of CO2 by plants, but research in the past decade has pointed out a number of potential negative impacts of stratospheric geoengineering. More research is needed to better quantify the potential benefits and risks so that if society is tempted to implement geoengineering in the future it will be able to make an informed decision. [ABSTRACT FROM AUTHOR]

The main focus of this paper is calculation of the diameters of asteroids belonging to five families (Vesta, Eos, Eunomia, Koronis, and Themis). To do that, we used the HCM algorithm applied for a data set containing 292,003 numbered asteroids, and a numerical procedure for choosing the crucial parameter of the HCM, called 'the cutting velocity' vcut. It was established with a precision as high as 1 m s−1. Thereafter, we used the WISE (Wide-field Infrared Survey Explorer) catalog to set a range of albedo for the largest members of each family considered. The albedo data were supported by the data concerning color classification ( SDSS MOC4). The asteroids with albedo out of this range were classified as interlopers and were therefore disqualified as family members. Sizes were calculated for the asteroids with albedo within the acceptable range. For the other asteroids (those chosen by means of the HCM, but with albedo not listed in the WISE), the value of albedo of the largest member of the family was adopted. Results are given in a set of figures showing the families on the planes ( a, e), ( a, i), ( e, i). Diameters and volumes of the asteroids that are the individual members of a family were calculated on the basis of their known or assumed albedo and on their absolute magnitude. Volumes of the parent bodies of the families were found on the basis of the cumulative volume distribution of these families. We also studied the secular resonances of the family members. We have shown that the locations of members of the considered asteroid families are related to the lines of secular resonances z1, z2, and z3 with Saturn. [ABSTRACT FROM AUTHOR]

Accurate simulations of freshwater lake ice are integral for the study of climatic variability in northern environments. Surface albedo, a component often parameterized in lake ice models, has been shown to affect the timing of ice break-up during the melt season. In situ snow and ice albedo measurements were taken over a partially snow-covered freshwater lake near Churchill, Manitoba for the evaluation of the albedo parameterization of the Canadian Lake Ice Model (CLIMo) and the Moderate Resolution Imaging Spectrometer (MODIS) albedo products (MOD10A1/MYD10A1 and MCD43A3). The albedo simulations using CLIMo were performed with and without snow integrated into the model and evaluated against in situ albedo measurements recorded over clear ice, snow ice and snow-covered ice. The simulated snow albedo from CLIMo for the entire ice growth season evaluated against snow albedo observations had a root mean square error of 0.07, a mean absolute error of 0.06, and a mean bias error (MBE) of −0.01. With snow removed from CLIMo, the albedo parameterization overestimated albedo values measured in the field over snow-free clear ice and snow ice with MBE values of 0.13 and 0.10, respectively. These findings suggest that CLIMo's bare ice albedo parameterization needs to be revised to account for albedo differences between ice types. The evaluation of the MODIS albedo products with in situ snow and ice albedo observations and the comparison of these satellite products with CLIMo's albedo parameterization during the melt period, when in situ radiation measurement stations needed to be removed from the lake-ice surface, are addressed in paper Part II (this issue). Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The current discussion regarding global warming (or "climate change") centers on managing the contribution of carbon dioxide (CO2) to incremental warming due to enhanced absorption of infrared radiation. If we are concerned about the warming, what is most important is the atmospheric heating regardless of cause. The incremental effect of CO2 may enhance this, but it is not the dominant mechanism of atmospheric warming, which is solar irradiance and the net absorption compared with reflection. This paper analyzes the large energy flows from the sun, human‐generated heat and CO2 emissions, several alternative energy conversion and generation strategies, and the resulting contributions to atmospheric heating. It is shown that increasing terrestrial albedo can offset the effects of fossil fuel combustion on both direct heating and incremental heating from CO2 emissions, and represents a viable alternative to replacing fossil‐fuel combustion with solar power. [ABSTRACT FROM AUTHOR]

This paper synthesizes 10-years' worth of interannual time-series space-borne ERS-1 and RADARSAT-1 synthetic aperture radar (SAR) data collected coincident with daily measurement of snow-covered, land-fast first-year sea ice (FYI) geophysical and surface radiation data collected from the Seasonal Sea Ice Monitoring and Modeling Site, Collaborative-Interdisciplinary Cryospheric Experiment and 1998 North Water Polynya study over the period 1992 to 2002. The objectives are to investigate the seasonal co-relationship of the SAR time-series dataset with selected surface mass (bulk snow thickness) and climate state variables (surface temperature and albedo) measured in situ for the purpose of measuring the interannual variability of sea ice spring melt transitions and validating a time-series SAR methodology for sea ice surface mass and climate state parameter estimation. We begin with a review of the salient processes required for our interpretation of time-series microwave backscatter from land-fast FYI. Our results suggest that time-series SAR data can reliably measure the timing and duration of surface albedo transitions at daily to weekly time-scales and at a spatial scales that are on the order of hundreds of metres. Snow thickness on FYI immediately prior to melt onset explains a statistically significant portion of the variability in timing of SAR-detected melt onset to pond onset for SAR time-series that are made up of more than 25 images. Our results also show that the funicular regime of snowmelt, resolved in time-series SAR data at a temporal resolution of approximately 2.5 images per week, is not detectable for snow covers less than 25 cm in thickness. [ABSTRACT FROM AUTHOR]

Observed reduction in recent sea ice areal extent and thickness has focused attention on the fact that the Arctic marine system appears to be responding to global-scale climate variability and change. Passive microwave remote-sensing data are the primary source underpinning these reports, yet problems remain in geophysical inversion of information on ice type and concentration. Uncertainty in sea-ice concentration (SIC) retrievals is highest in the summer and fall, when water occurs in liquid phase within the snow-sea-ice system. Of particular scientific interest is the timing and rate of new ice formation due to the control that this form of sea ice has on mass, energy and gas fluxes across the ocean-sea-ice-atmosphere interface. In this paper we examine the critical fall freeze-up period using in situ data from a ship-based and aerial survey programme known as the Canadian Arctic Shelf Exchange study combined with microwave and optical Earth observations data. Results show that: (1) the overall physical conditions observed from aerial survey photography were well matched with coincident moderate-resolution imaging spectroradiometer data and Radarsat ScanSAR imagery; (2) the shortwave albedo was linearly related to old ice concentration derived from survey photography; (3) the three SSM/I SIC algorithms (NASA Team (NT), NASA Team 2 (NT2), and Bootstrap (BT)) showed considerable discrepancies in pixel-scale comparison with the Radarsat ScanSAR SICs well calibrated by the aerial survey data. The major causes of the discrepancies are attributed to (1) the inherent inability to detect the new thin ice in the NT and BT algorithms, (2) mismatches of the thin-ice tie point of the NT2 algorithm, and (3) sub-pixel ambiguity between the thin ice and the mixture of open water and sea ice. These results suggest the need for finer resolution of passive microwave sensors, such as AMSR-E, to improve the precision of the SSM/I SIC algorithms in the marginal ice zone during early fall freeze-up. [ABSTRACT FROM AUTHOR]

Tibetan Plateau (TP) snow cover is featured by sub‐seasonal changes, affecting weather and climate in surrounding and downstream areas. Previous studies emphasize the effect of background atmospheric circulation on rapid changes of TP snow cover as a whole. However, spatial discrepant changes of snow cover over the TP with complex topography and uneven snowfall remain unaddressed. Our research indicates that snow cover fraction dominates the rapid changes of surface albedo across the TP, and snow depth also significantly influences surface albedo changes through modulating snow albedo in central and eastern TP with shallow snow. However, the excessive snow amount and empirical snow cover fraction schemes introduce spatially divergent biases of surface albedo changes in simulations. Our research highlights the instant response of TP surface albedo to both snow coverage and depth in snow season, and provides a promising perspective for improving TP snow and surface albedo simulations. Plain Language Summary: Tibetan Plateau (TP) snow cover is characterized not only by obvious seasonal changes, but also by rapid sub‐seasonal changes, which has a significant impact on the weather and climate of the downstream areas by affecting the surface albedo over the TP. Previous studies have generally concluded that the background atmospheric circulation dominates rapid changes of overall TP snow cover. However, rapid changes of snow cover exhibit spatial discrepancies over the TP with complex topography and uneven snowfall. Our study finds that snow coverage and depth both contribute to rapid changes of surface albedo and energy budget over the TP, which further lead to rapid changes of snow cover. However, current numerical models tend to overestimate the snow and fail to simulate spatial different changes of snow coverage and depth, leading to spatially divergent simulation biases in surface albedo, surface energy balance and local atmospheric circulation over the TP. Therefore, there is an urgent need to improve the snow parameterization in models to enhance the intra‐seasonal simulation of snow cover and surface albedo over the TP. Key Points: Observed surface albedo over the Tibetan Plateau (TP) has significant weekly scale fluctuations during winterSnow cover fraction and snow depth jointly dominate observed rapid changes of surface albedo over the TPExcessive snow amount and empirical snow cover fraction schemes lead to spatially divergent bias of surface albedo change [ABSTRACT FROM AUTHOR]

The accuracy of snow density in land surface model (LSM) simulations impacts the accuracy of simulated terrestrial water and energy budgets. However, there has been little research that has focused on enhancing snow compaction in operationally used LSMs. A baseline snow simulation with the widely used Noah‐MP LSM systematically overestimates snow depth by 55 mm even after removing daily snow water equivalent (SWE) biases. To reduce uncertainties associated with snow compaction, we enhance the most sensitive Noah‐MP snow compaction parameter—the empirical parameter for compaction due to overburden (Cbd)—such that Cbd is calculated as a function of surface air temperature as opposed to a fixed value in the baseline simulation. This enhancement improves accuracy in simulated snow compaction across the majority of western U.S. (WUS) SNOTEL test sites (biases reduced at 88% of test sites), with modest bias reductions in cooler accumulation periods (biases reduced at 70% of test sites) and substantial improvements during warmer ablation periods (biases reduced at 99% of test sites). Relatively larger improvements during warm conditions are attributable to the default Cbd value being reasonable for cold temperatures (≤−5°C). Improvements in simulated snow depth and density with observations outside of the training sites and optimization periods support that the snow compaction enhancement is transferable in space and time. Differences between enhanced and baseline gridded simulations across the total WUS support that the enhancement can have important impacts on snowpack evolution, snow albedo feedback, and snow hydrology. Plain Language Summary: Snow density, the ratio of water in the snowpack to the snow depth, is a fundamental property of snow that is important to accurately represent in snow simulations. In this research, we develop and evaluate a model enhancement designed to more accurately simulate the snow densification process in a widely used land surface model, Noah‐MP. Evaluations of the baseline snow compaction scheme, without model enhancements, reveals reasonable performance during cold conditions but substantial errors during warm conditions. We update the Noah‐MP snow compaction scheme to calculate the most sensitive snow compaction parameter as a function of surface air temperature. This enhancement provides substantially more accurate representations of snow compaction during warm conditions and provides similar performance relative to the baseline simulation during cold conditions. Improved accuracy in simulating snow densification is consistent between training sites the enhancement was optimized over and sites that were only used for validation both within and outside of the time period of optimization, supporting that improvements associated with using our model update can be expected at places and times distinct from the optimization locations and time periods. Key Points: Noah‐MP snow compaction parameterization is enhanced using SNOTEL snow observationsThe snow compaction enhancement provides substantial improvements in snow density and depth particularly during warm conditionsThe enhanced snow compaction scheme can have notable effects on snowpack evolution and snow albedo feedback [ABSTRACT FROM AUTHOR]

We enhance the Community Land Model (CLM) snow albedo modeling by implementing several new features with more realistic and physical representations of snow‐aerosol‐radiation interactions. Specifically, we incorporate the following model enhancements: (a) updating ice and aerosol optical properties with more realistic and accurate data sets, (b) adding multiple dust types, (c) adding multiple surface downward solar spectra to account for different atmospheric conditions, (d) incorporating a more accurate adding‐doubling radiative transfer solver, (e) adding nonspherical snow grain representations, (f) adding black carbon‐snow and dust‐snow internal mixing representations, and (g) adding a hyperspectral (480‐band vs. the default 5‐band) modeling capability. These model features/enhancements are included as new CLM physics/namelist options, which allows for quantification of model sensitivity to snow albedo processes and for multi‐physics model ensemble analyses for uncertainty assessment. The model updates have been included in the latest released CLM version. Sensitivity analyses reveal strong impacts of using the new adding‐doubling solver, nonspherical snow grains, aerosol‐snow internal mixing, updated aerosol optics, and different dust types. These enhanced snow albedo representations improve the CLM simulated global snowpack evolution and land surface conditions, with reduced biases in simulated snow surface albedo, snow cover, snow water equivalent, snow depth, and surface (2‐m) air temperature over many mid‐latitude mountainous regions and seasonal snowpacks but degraded performance in some northern high‐latitude regions. Plain Language Summary: Snow albedo plays a critical role in the Earth system, affecting land surface energy and water balance and also serving as an important land process that feeds back to the atmosphere. Several recent studies have identified new or improved physical representations of snow albedo processes. In this study, we leverage recent advances in snow albedo modeling to implement a number of relevant new features into the widely used Community Land Model (CLM), which is the land component of the Community Earth System Model (CESM). Specifically, we improve the ice and aerosol optical properties, the treatment of dust types and downward sunlight energy distribution at different wavelength bands, the albedo computation algorithm, and the representations of snow grain shape and how aerosol is mixed with snow grains. These model updates have been included in the latest released CLM version. Overall, the enhanced snow albedo representations improve the simulated snowpack evolution and related land surface conditions in many parts of the globe. Key Points: We enhance CLM5 snow albedo modeling by including more realistic and physical representations of snow‐aerosol‐radiation interactionsThe new adding‐doubling solver, nonspherical snow grains, aerosol‐snow internal mixing, and updated aerosol optics show strong impactsThe enhanced snow albedo representation improves the CLM simulated snowpack evolution and land surface conditions in many global regions [ABSTRACT FROM AUTHOR]

Existing land surface models still have large error in the simulation of surface albedo. At present, introducing the influence of meteorological factors into the albedo parameterization scheme is an effective way to improve the albedo simulation. However, the improvement of the vegetation canopy surface albedo parameterization scheme is still insufficient. Therefore, based on the radiation and meteorological observation data during 1 November 2015–30 April 2018 from a land‐atmosphere interaction observation tower in a typical secondary evergreen broadleaved forest in Southern China, this study firstly analyzed the influencing factors of canopy surface albedo. It was found that the solar elevation angle and air relative humidity are two key factors influencing the canopy surface albedo, and the impact of the solar elevation angle on canopy surface albedo is not exactly the same on diurnal and seasonal scales. Then, two new canopy surface albedo parameterization schemes of additive form and multiplicative form were proposed and introduced into CLM5 model for single point simulation. Results show that the adoption of newly developed canopy surface albedo parameterization schemes can improve the simulation of diurnal and seasonal variations of albedo and reduce the overestimation of the simulation of near‐infrared radiation albedo and visible radiation albedo in the CLM5 model, then significantly reduce the root mean square errors of reflected solar radiation and net radiation simulation. Plain Language Summary: Surface albedo is an important factor affecting the heat exchange between land and atmosphere, and is critical for weather forecasting and regional climate modeling. At present, even in some complex land surface models, the canopy surface albedo parameterization scheme only considers the variation of leaf and stem index and the cosine of the solar zenith angle over time but does not take into account the effect of meteorological factors. In this study, two newly developed canopy albedo schemes that take into account the effects of solar elevation angle and air relative humidity were developed, and then introduced into the CLM5 model for single point simulation. The results show that the new canopy albedo scheme can indeed improve the simulation skills of the reflected solar radiation. The results emphasize the important influence of meteorological factors on the surface albedo, and the findings may provide a base to further develop and improve the CLM5 model. Key Points: Two new canopy surface albedo schemes considering the influence of solar elevation angle and air relative humidity are proposedThe new canopy surface albedo schemes can reduce the canopy surface albedo of evergreen broad‐leaved forest overestimated by CLM5 model [ABSTRACT FROM AUTHOR]

Dark (low albedo) surface ice on the Greenland Ice Sheet enhances melting and subsequent runoff, a major mass loss contributor during the ablation season. The accumulation of both biological (e.g., glacier ice algae) and abiotic (e.g., mineral dust) light‐absorbing particulates are important darkening factors, that are potentially influenced by the duration of snow‐free, bare ice (a phenological factor), and other geo‐topographical factors such as elevation, slope, aspect and the distance from the ice margin. Here, we present the first medium‐resolution (30 m) analysis of the phenological and geo‐topographical controls on the distribution of dark ice in SE and SW Greenland from statistical analysis of data derived from a harmonized satellite albedo product and ArcticDEM. The duration of bare ice primarily controls the distribution of dark surface ice, allowing for algae growth on inland ice surfaces in particular, whereas geo‐topographical factors are only secondary controls. Plain Language Summary: Meltwater that runs off the Greenland Ice Sheet is currently the largest single glaciological contributor to global sea level rise. Recent darkening of the surface ice has contributed significantly to increased melt rates. We used medium resolution (30m) satellite data to link ice surface darkness (albedo) to the topography (elevation, slope, and aspect) of the ice sheet surface, the distance from the ice margin, and the duration of bare or snow‐free surface ice. Our analysis shows that the duration of bare ice or snow‐free conditions was the most significant factor in driving the darkening of ice. We also found that the impact of topographic factors on the ice darkening varied depending on whether abiotic or biological processes were driving the darkening. This information helps us to better explain where the ice sheet is melting fastest and to predict the loss of ice mass, particularly considering the expected increase in the area of bare, snow‐free ice in our warming climate. Key Points: The duration of snow‐free, bare ice is the primary control on the distribution of dark iceLonger durations of bare ice (median = 40 days) are prerequisites for ice to become darkSurface slope and aspect influence darkening by modulating the duration of bare ice and glacier ice algae growth [ABSTRACT FROM AUTHOR]

From April through June in 2019 and 2022, we monitored snow melt at three sites near Utqiaġvik, Alaska. Along 200‐m lines we measured snow depth, density, stratigraphy, snow‐covered area, and spectral albedo. Site 1 (ARM) was sloped tundra drained by water tracks. Site 2 (BEO) was flat polygonal tundra. Site 3 (ICE) was on undeformed landfast sea ice. All three sites were within a 6 km radius. Despite similar pre‐melt snow distributions and weather, the melt progression differed markedly between sites. In 2019, by mid‐melt, there was 40% less snow‐covered area at ARM versus ICE, and 34% less snow‐covered area at ARM versus BEO. The 2022 melt started 2 weeks later than in 2019 and was rapid, so smaller differences in snow‐covered areas developed. In both years meltout dates varied by up to 25 days between sites, and more than 20 days within sites, with melt rates at locations only meters apart differing by up to a factor of seven. This melt diachroneity led to highly heterogeneous meltout patterns at all three sites. Our measurements and observations indicate that, in addition to reductions in snow reflective properties and wind‐driven heat advection, the fate of meltwater plays a key role in producing melt diachroneity. We identify seven snow‐water mechanisms that can enhance or inhibit melt rates, all largely controlled by the local topography and the nature of the substrate. These mechanisms are important because the most rapid changes in albedo coincide with the peak of water‐snow melt interactions. Plain Language Summary: We observed in detail snow melt on two different tundra locations and one sea ice location in Arctic Alaska in the spring of 2019 and 2022. During the melt season, these landscapes go from reflecting over 80% of the sunlight to less than 20%, a transition that impacts the global climate. Our observations showed that while warming weather is what ultimately controls snowmelt, the re‐freezing and flow of meltwater within the snowpack, plays a crucial role in controlling local melt rates of individual snow patches. These water‐related melt mechanisms, together with wind‐driven laterally advected air and the reflective properties of the snow, largely control the date individual snow patches disappear, and therefore, when the most rapid changes in solar reflectivity will take place. Key Points: Water‐related processes in snow can promote or impede lateral advection of heat and mass, enhancing or inhibiting melt in the ArcticThe composition and topography of the substrate govern the nature of the water‐snow interactions and thereby influence meltout patternsThe most rapid and largest changes in surface albedo happen just prior to the snow‐free date when water‐snow melt mechanisms reach a peak [ABSTRACT FROM AUTHOR]

In a database of lunar fractured boulders (Rüsch & Bickel, 2023, https://doi.org/10.3847/psj/acd1ef), we found boulders with reflectance features dissimilar to previously known morphologies. We performed a photo‐geologic investigation and determined that the features correspond to a dust mantling on top of boulders with a unique photometric behavior. We next performed a photometric model inversion on the dust mantling using Bayesian inference sampling. Modeling indicates that the dust photometric anomaly is most likely due to a reduced opposition effect, whereas the single scattering albedo is not significantly different from that of the nearby background regolith. This implies a different structure of the dust mantling relative to the normal regolith. We identified and discussed several potential processes to explain the development of such soil. None of these mechanisms can entirely explain the multitude of observational constraints unless evoking anomalous boulder properties. Further study of these boulders can shed light on the workings of a natural dust sorting process potentially involving dust dynamics, a magnetic field, and electrostatic dust transport. The presence of these boulders appears to be limited to the Reiner K crater near the Reiner Gamma magnetic and photometric anomaly. This close spatial relationship further highlights that poorly understood processes occur in this specific region of the Moon. Plain Language Summary: The study of rocks on the surface of the Moon is important to understand the processes forming and modifying the lunar crust as well as the processes modifying rocks after their formation. The lunar rocks resting on the surface can be studied by imaging them with an orbital camera and analyzing their shape and reflectance. Here we report on the finding of a new type of brightness feature on rocks. This finding was made possible by scrutinizing a catalog of split lunar rocks. The brightness feature is found to be unique because of its rare occurrence, localization limited to near the Rainer Gamma magnetic anomaly, and association with some but not all rocks of the crater Reiner K. The feature is a dust deposit with a potentially uncommon physical structure. Key Points: In a catalog of lunar boulder images, we find a new type of reflectance feature associated with bouldersThe feature is likely a dust mantling with unique photometric propertiesSeveral formation scenarios are discussed [ABSTRACT FROM AUTHOR]

Almost all current climate models simplify the ocean surface albedo (OSA) by assuming the reflected solar energy without the ocean interior contribution. In this study, an improved ocean surface albedo scheme is incorporated into the Community Earth System Model version 2 (CESM2) to assess the sensitivity of Arctic surface temperature to including ocean interior reflectance to the OSA. Fully coupled CESM2 simulations with and without ocean interior reflectance are subsequently performed, we focus on the analysis of Arctic surface temperature responses. Incorporating ocean interior reflectance increases absorbed solar radiation and warms the ocean, enhancing seasonal heat storage and release across the Arctic Ocean, and increasing sea ice reduction and positive climate feedbacks that elevates Arctic surface temperature. Seasonal variations in air‐surface temperature differences induce changes in turbulent heat flux patterns, concurrently modifying dynamic advection and moisture processes that affect boundary layer humidity and low clouds, especially in winter. Based on partitioning physical processes in the thermodynamic energy equation, surface air warming is induced primarily through positive heating anomalies of vertical advection, latent heat release, and longwave radiative forcing. Through an examination of the surface energy budget, skin temperature warming is driven predominantly by increased downward longwave radiation, positive surface albedo feedback in summer, and increased conductive heat transport from the ocean particularly in winter. Significant effects of ocean interior reflectance on the Arctic Ocean, including sea surface warming and sea ice reduction, justify the importance of ocean interior reflectance in climate models for better understanding of ongoing Arctic climate changes. Plain Language Summary: The penetrated sunlight across the ocean surface is attenuated through the light absorption and scattering processes associated with oceanic optical constituents. The ocean attenuation of sunlight not only modifies the amount of solar energy reflected back to the atmosphere but also warms the seawater. Many climate models neglect the contribution of ocean interior reflectance to the ocean surface albedo (OSA) and hence simulate less accurate net heat flux through the air‐sea interface. In this study, sensitivity simulations were performed with and without ocean interior reflectance in the OSA calculation, respectively. When ocean interior reflectance is included, the Arctic surface shows warmings in both summer and winter, and the warming is stronger in winter, due to complex feedback mechanisms in the fully coupled model. The warmer Arctic surface is predominantly caused by changes in near‐surface vertical air motion, latent heat released during cloud formation, longwave radiative energy budget, and conductive heat transport from the ocean especially in winter. The changes in the drivers are related to seasonal variations in air‐surface temperature differences and heat storage‐release of the Arctic Ocean. To get a better understanding of climate responses associated with including ocean interior reflectance to the OSA, further investigations are necessary. Key Points: Arctic surface temperature changes are simulated to better understand the implication of the ocean interior reflectance in climate modelSimulation‐based increase in Arctic surface temperature is attributed to complex feedbacks inherent in the fully coupled modelClimate responses due to integrating ocean interior reflectance in the ocean surface albedo need more attention in earth system modeling [ABSTRACT FROM AUTHOR]

Entrainment‐mixing modulates the number and size of cloud droplets, and thus affects the optical properties of clouds and their role in the climate system. Using a statistical turbulence model coupled with Lagrangian cloud microphysics, we analyze the role of aerosol in the entrainment‐mixing process, which, for instance, prevent the full evaporation of cloud droplets, leaving behind haze particles. To test a commonly applied indicator for inhomogeneous mixing, a set of different mixing scenarios is simulated. We conclude that if a hard separation radius between cloud droplets and haze particles is chosen, the typical classification into homogeneous and inhomogeneous mixing can be wrong because larger haze particles might be misidentified as cloud droplets, making the mixing appear more homogeneous. Furthermore, we show that the growth of cloud droplets on the expense of other hydrometeors due to differences in aerosol loading and particle curvature (Ostwald ripening) can produce cloud microphysical signatures indistinguishable from inhomogeneous mixing. Finally, we investigate how the consideration of haze particles can mitigate the previously reported negative impacts of inhomogeneous mixing on the cloud albedo. These findings should be considered when interpreting observations and simulations of small‐scale entrainment‐mixing. Plain Language Summary: The mixing of clouds with their environment can change the size and number of cloud droplets, two important parameters to understand the role of clouds in the climate system. Because these changes are determined by the specific way a cloud mixes with its environment, they have traditionally been used to characterize the mixing process. Using a highly detailed numerical cloud modeling framework, we show that the adequate consideration of aerosol particles from which cloud droplets grow can alter the actual and apparent changes of cloud droplets during mixing. We identify biases that need to be considered when mixing is analyzed in observations and simulations. Key Points: Because sufficiently large haze particles can be misinterpreted as droplets, mixing can appear more homogeneousSolute and curvature effects initiate microphysical changes (Ostwald ripening) that can be confounded with inhomogeneous mixingHaze particles are shown to buffer the negative impacts of inhomogeneous mixing on the cloud albedo [ABSTRACT FROM AUTHOR]

The deployment of bifacial photovoltaic (PV) modules for utility‐scale PV plants has quickly proliferated in recent years. As they can harness the irradiance received at the rear side of bifacial generators—which depends on the albedo of the reflector ground—bifacial modules provide higher productivity than monofacial modules, in exchange for a low increase in manufacturing costs. However, the reduction of PV performance estimations uncertainty still represents a main concern for both PV and financial actors, which seek to reduce financial risks of bifacial PV systems. The aim of this work is to provide a better understanding of the impact that albedo measurements have on PV yield estimations uncertainty. We analysed the albedo sensitivity coefficient relating albedo measurement and subsequent energy yield estimations' uncertainties through a representative yield simulation exercise performed for three different sites (Chile, Spain and Sweden) and two types of PV plants: static and single‐axis tracker. A formula considering the impact of Ground Coverage Ratio and Inverter Loading Ratio is proposed for this coefficient. We performed an experimental campaign to evaluate the uncertainty associated to different albedo measurement conditions. Surface reflectance of five different ground surfaces has been measured using four sensors, which allowed to obtain three useful types of albedos that we defined and described. A series of recommendations for short‐term ground‐based albedo measurements that entail a maximum of 1.5% yield uncertainty contribution in the frame of commercial PV plants are then derived. A representative case of actual albedo measurement practices at the current PV market scene is also presented in the form of a commercial albedo measurement project for a future 50 MW bifacial PV plant. Despite being a local characteristic, the most relevant uncertainty source found is associated to the non‐homogeneity of the future PV plant's surface. An important consideration is that changes in the use of land caused by the construction of a PV plant lead to an albedo uncertainty that predominates over all the uncertainty sources associated to the albedo measurement conditions. This can also be the case for long‐term seasonal variations, which can become the dominant uncertainty source for high latitude locations. [ABSTRACT FROM AUTHOR]

Previous studies have primarily focused on the hydrological response of snowpack during rain‐on‐snow (ROS) events, with limited attention given to their subsequent stages, despite the significance of these stages. Therefore, this study selected two snow plots with similar initial parameters in the Qilian Mountains at an altitude of 4151 m. One of the snow plots underwent artificial rainfall simulation, and the changes in snow albedo, liquid water content, and snow depth of two snow plots were observed and analysed during the rainfall experiment and for a period of 7 days thereafter. The results indicate that ROS events significantly accelerate the rate of decrease in snow albedo and snow depth, increase the liquid water content within the snowpack, and these effects persist for several days after the rainfall event. Furthermore, the input of liquid water leads to rapid saturation of the snowpack, altering the transport mechanism of water within the snowpack, and transforming a process that would otherwise take a long time to complete into a short time. The decrease in snow albedo enhances the absorption of more energy by the snow, thereby accelerating snowmelt. Compared to natural snowmelt, ROS events cause the snowpack with high liquid water content to rapidly melt over a short period, resulting in a rapid increase in river flow, which may be one of the causes of ROS‐induced flooding. These research findings provide scientific insights for a better understanding of the disaster mechanisms associated with ROS events. [ABSTRACT FROM AUTHOR]

Images of Venusian clouds taken at ultraviolet (UV) wavelengths frequently exhibit mesoscale cellular structures at low latitudes. To obtain clues regarding the origin of these structures, we studied the temporal variation of the mesoscale UV contrast using 283‐ and 365‐nm images taken by the ultraviolet imager (UVI) onboard the Akatsuki spacecraft. The 283‐nm channel is mostly affected by SO2 at the cloud top and the 365‐nm channel is mostly affected by an unknown absorber, though both absorbers are thought to influence both wavelengths. We defined the mesoscale as a spatial scale roughly below 1,000 km, where the effect of large‐scale streaky patterns is not significant according to the spatial spectra of 283‐nm images taken by UVI and 2.02‐μm images taken by the near‐infrared camera (IR2) onboard Akatsuki. We found that the temporal variation of the standard deviation of the mesoscale UV contrast is dominated by quasi‐periodic oscillations with amplitudes of 30%–50% relative to the mean value and periods of around 4–5 Earth days. Oscillations of the planetary‐scale UV contrast with similar periods were also observed, suggesting that the mesoscale structures are influenced by planetary‐scale waves. The mesoscale contrast tends to be enhanced when the background albedo decreases in the course of the propagation of planetary‐scale waves. This correlation suggests that the solar heating near the cloud top level feeds the mesoscale dynamics. An enhancement of the mesoscale contrast in the afternoon was seen at a wavelength of 365 nm. Plain Language Summary: On Venus, the brightness pattern of the cloud top shows signs of convection, where heat is transported either upward or horizontally through the fluid motion. These processes could have a large impact on material and energy transportation on the planet. We examined ultraviolet (UV) cloud images captured by the Akatsuki Venus orbiter to track changes in contrast over time at both a planetary and mesoscale (below 1,000 km). Unlike visible wavelengths, Venus' clouds display changes in brightness over time and space when viewed at UV wavelengths. The UV contrast at the mesoscale was found to oscillate with periods of around 4–5 Earth days. Similar periods of oscillation are observed in the planetary‐scale brightness variation, suggesting that planetary‐scale waves influence the motion at a scale below 1,000 km. The contrast at this scale tends to be enhanced when the background becomes darker. This relation implies that the heating of clouds by the Sun enhances vertical or horizontal inhomogeneity of the temperature and then powers the observed convection. Key Points: The temporal variation of the mesoscale ultraviolet (UV) contrast of Venusian clouds was studied using images taken by the UV camera on AkatsukiThe mesoscale contrast was found to oscillate with periods of 4–5 Earth days, which are also the periods of planetary‐scale wavesThe mesoscale contrast tends to be enhanced when the background becomes darker, suggesting that solar heating feeds the mesoscale dynamics [ABSTRACT FROM AUTHOR]

"Land radiative management" (LRM)—intentionally increasing land surface albedo to reduce regional temperatures—has been proposed as a form of geoengineering. Its effects on local precipitation and soil moisture over long timescales are not well understood. We use idealized cloud‐permitting simulations and a conceptual model to understand the response of precipitation and soil moisture to a mesoscale albedo anomaly at equilibrium. Initially, differential heating between a high‐albedo anomaly and the lower‐albedo surrounding environment drives mesoscale circulations, increasing precipitation and soil moisture in the surrounding environment. However, over time, increasing soil moisture reduces the differential heating, eliminating the mesoscale circulations. At equilibrium, the fractional increase in simulated soil moisture is up to 1.3 times the fractional increase in co‐albedo (one minus albedo). Thus, LRM may increase precipitation and soil moisture in surrounding regions, enhancing evaporative cooling and spreading the benefits of LRM over a wider region than previously recognized. Plain Language Summary: One way to reduce temperatures in a warming world is to increase the fraction of sunlight reflected by the land surface back to space (the "albedo"), for example, by painting surfaces white. However, changing albedo does not only change temperatures; it can also impact rainfall and soil moisture. Here, we show that increasing a region's albedo leads to increased rainfall and soil moisture in surrounding regions, where the albedo has not been changed, spreading the cooling effect over a wider area than previously recognized. Key Points: Land radiative management (LRM)—increasing land surface albedo to reduce temperatures—has been proposed as a form of geoengineeringWe use idealized cloud‐permitting simulations and a conceptual model to understand the hydrologic response to LRMLRM increases rainfall and soil moisture in surrounding regions, potentially extending its cooling benefits [ABSTRACT FROM AUTHOR]

The use of standard aerosol models for atmospheric correction over inland and nearshore coastal waters generates large uncertainties due to their inability to appropriately characterize aerosols in those regions. To address this problem, we developed new aerosol models using data acquired from 1,475 Aerosol Robotic Network (AERONET) sites distributed in inland and coastal regions throughout the globe. We established spatially gridded (5° × 5°) aerosol models on a climatological monthly scale, with a total of 3,207 new aerosol models developed for 310 grid cells worldwide. The monthly aerosol model for each grid was derived using mean monthly values of microphysical aerosol properties from AERONET data. The optical properties (i.e., single scattering albedo and Ångström coefficient) of our global gridded aerosol models demonstrated considerable spatial and seasonal dynamics and deviated substantially from the aerosol models currently utilized by the National Aeronautics and Space Administration (NASA). We built associated lookup tables for all aerosol models and incorporated them into two atmospheric correction algorithms: the combined near‐infrared and shortwave infrared algorithm (NIR‐SWIR) and the Atmospheric Correction algorithm for inLand and Nearshore Coastal waters (ACLANC). For both algorithms, the accuracies of atmospherically corrected satellite remote sensing reflectance (Rrs) improved markedly when the new aerosol models were used, and improvements were noted across all spectral bands and across all six inland and nearshore water bodies used in this study. Our new aerosol models can be easily applied to all ocean color satellite missions to obtain accurate Rrs products for inland and coastal waters worldwide. Plain Language Summary: The use of standard aerosol models for atmospheric correction over inland and nearshore coastal waters generates large uncertainties due to their inability to characterize aerosols in those regions appropriately. This issue also represents the most challenging task of quantitative remote sensing of the inland and coastal environments. To address this problem, we developed new aerosol models using data acquired from 1,475 Aerosol Robotic Network sites distributed in inland and coastal regions throughout the globe. We established spatially gridded (5° × 5°) aerosol models on a climatological monthly scale, with a total of 3,207 new aerosol models developed for 310 grid cells worldwide. Key Points: Develop new aerosol models using data from 1,475 global Aerosol Robotic Network sitesEstablish spatially gridded aerosol models on a climatological monthly scaleAccuracies of the Rrs product improved markedly using new aerosol models [ABSTRACT FROM AUTHOR]

The Antarctica Peninsula (AP) has experienced more frequent and intense surface melting recently, jeopardizing the stability of ice shelves and ultimately leading to ice loss. Among the key phenomena that can initiate surface melting are atmospheric rivers (ARs) and leeside foehn; the combined impact of ARs and foehn led to moderate surface warming over the AP in December 2018 and record‐breaking surface melting in February 2022. Focusing on the more intense 2022 case, this study uses high‐resolution Polar WRF simulations with advanced model configurations, Reference Elevation Model of Antarctica topography, and observed surface albedo to better understand the relationship between ARs and foehn and their impacts on surface warming. With an intense AR (AR3) intrusion during the 2022 event, weak low‐level blocking and heavy orographic precipitation on the upwind side resulted in latent heat release, which led to a more deep‐foehn like case. On the leeside, sensible heat flux associated with the foehn magnitude was the major driver during the night and the secondary contributor during the day due to a stationary orographic gravity wave. Downward shortwave radiation was enhanced via cloud clearance and dominated surface melting during the daytime, especially after the peak of the AR/foehn events. However, due to the complex terrain of the AP, ARs can complicate the foehn event by transporting extra moisture to the leeside via gap flows. During the peak of the 2022 foehn warming, cloud formation on the leeside hampered the downward shortwave radiation and slightly increased the downward longwave radiation. Plain Language Summary: On the Antarctic Peninsula (AP), when ice shelves break up, glaciers flow faster from the land into the sea, leading to ice loss and increasing sea level rise. Surface warming is projected to double by 2050 over Antarctica and may have led to ice shelf collapse. Two phenomena that enhance surface warming are atmospheric rivers, (long corridors of moisture in the atmosphere) and leeside foehn effects (cooler and moist air advection on the upwind side that becomes warmer and drier when descending on the leeside). Here we study two combined atmospheric river and foehn events that led to surface warming on the AP, occurring in December 2018 and February 2022. The main warming mechanism in the northeastern AP during the nighttime was transfer of heat from the air to the ice surface (sensible heat flux), while the main mechanism during the daytime was intense sunlight, which was able to reach the surface because of clear skies on the opposite (lee) side caused by foehn. However, complicating the picture, there are gaps in the AP mountain range that let the atmospheric river through, allowing clouds to form on the other side, which then blocked some of the sunlight. Key Points: This study investigates the atmospheric river and foehn warming over the Antarctic Peninsula via observations and model simulationsAtmospheric rivers led to stronger precipitation on the upwind side and favored the foehn‐related sensible heat transfer on the leesideUnder the combined atmospheric rivers and foehn, shortwave radiation contributed the most to the ice surface warming, followed by sensible heat flux [ABSTRACT FROM AUTHOR]