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Variability of ice microphysical properties like crystal size and density in cirrus clouds is important for climate through its impact on radiative forcing, but challenging to represent in models. For the first time, recent laboratory experiments of particle growth (tied to crystal morphology via deposition density) are combined with a state‐of‐the‐art Lagrangian particle‐based microphysics model in large‐eddy simulations to examine sources of microphysical variability in cirrus. Simulated particle size distributions compare well against balloon‐borne observations. Overall, microphysical variability is dominated by variability in the particles' thermodynamic histories. However, diversity in crystal morphology notably increases spatial variability of mean particle size and density, especially at mid‐levels in the cloud. Little correlation between instantaneous crystal properties and supersaturation occurs even though the modeled particle morphology is directly tied to supersaturation based on laboratory measurements. Thus, the individual thermodynamic paths of each particle, not the instantaneous conditions, control the evolution of particle properties. Plain Language Summary: Thin, high‐altitude ice clouds—cirrus—are critical to climate through their interactions with incoming solar radiation and outgoing longwave radiation. With a zoomed‐in view, observations show that cirrus comprise ice crystals of diverse sizes and shapes. These crystal properties determine the bulk properties of the clouds, like their ice water content. What controls this diversity of crystal properties? To address this question, we performed numerical simulations using a state‐of‐the‐art model that tracks the growth of individual particles, informed by laboratory crystal growth experiments, in a realistic turbulent cloud flow. We show that variability in the local environmental conditions (e.g., relative humidity) that particles experience in a turbulent environment is a primary driver of crystal diversity in cirrus. Diversity is also driven by different shapes of newly formed crystals, leading to different growth characteristics. This diversity drives spatial variability of properties like mean crystal density across the cloud layer. Climate models that represent cirrus using simple relationships based on observations that are essentially snapshots of average crystal properties cannot capture this variability. Overall, our analysis indicates that the history of environmental conditions along particle trajectories, not just instantaneous conditions, are required to understand crystal growth and variability in cirrus. Key Points: Variability in the thermodynamic histories of ice crystals are a primary driver of particle variability in cirrusDiversity in crystal morphology also drives spatial variability of mean particle size and density, particularly at mid‐levels in the cloudThermodynamic histories along particle trajectories, not just local conditions, are required to understand crystal growth in cirrus [ABSTRACT FROM AUTHOR]

Cirrus clouds often contain numerous hollow ice crystals, which are distinct in scattering properties from solid ice crystals, and will be challenging to microphysical retrieval and radiative forcing assessment. Currently, hollow ice crystals have not been observed by remote sensing methods, and the estimation of their hollowness is a complex task. To address this issue, the Mixed Modal Hollow Columns (MMHC) model for hollow ice crystals is introduced, and its backscattering properties are computed using the physical optics approximation method. Through comparison with spaceborne lidar observations, we identify a specific type of cirrus associated with the MMHC model for the first time. The visible optical depth of this cirrus is less than or equal to 0.1, and the temperature is between −60 and −40°C. The MMHC characteristic cirrus clouds are prevalent in middle and high latitudes but less comm+on in low latitudes. They exhibit distinct patterns in terms of sea and land distribution as well as seasonal variation. Plain Language Summary: Cirrus clouds typically form at altitudes exceeding 6 km and consist of non‐spherical ice crystals, each with unique optical properties affecting the earth's radiation balance through scattering and absorption. Notably, these crystals include hollow formations, which are distinct in scattering properties from their solid counterparts. The coexistence of hollow and solid ice crystals presents challenges in accurately inverting ice crystal morphology in remote sensing and evaluating radiation properties in climate models. To address these complexities, we propose a MMHC model. Through analysis of spaceborne lidar observational data, we identify characteristic cirrus clouds associated with such type of ice crystals and study the global distribution and seasonal distribution of this kind of cirrus clouds. Key Points: A Mixed Modal Hollow Columns model is formulated to characterize the presence of hollow ice crystals in cirrus cloudsFor the first time, hollow characteristic cirrus clouds are observed using spaceborne lidarHollow characteristic cirrus clouds exhibit distinct global and seasonal distribution variations [ABSTRACT FROM AUTHOR]

"The Art and Science of the Atmosphere" is an article written by Alan Sealls, a retired Chief Meteorologist and author. Sealls discusses his passion for both photography and meteorology, explaining how the two disciplines complement each other. He provides tips for capturing weather phenomena, such as using the direction and altitude of the sun and the type of clouds to forecast photo opportunities. Sealls also showcases several of his own photographs, including images of crepuscular rays, a circumzenith arc, a dust storm, a fogbow, grid waves, a gust front panorama, ice storm icicles, a cumulonimbus cloud, lightning strike, and a red sky at night. [Extracted from the article]

Cirrus (Ci) clouds have an important influence on Earth's radiation budget, and they remain one of the most significant uncertainties in predicting Earth's climate. In this study, we use ground-based radiometers along with a sky imager to monitor clouds and retrieve cloud properties (cloud fraction (CF), cloud optical depth (COD) and effective radii (Re)) over a rain shadow region in south peninsular India during September and October months, 2011. Lower part of Ci clouds are identified using the thresholds pertaining to COD and cloud base height (CBH). The optical and radiative properties of Ci clouds showed large variability on temporal and diurnal scales. The CF, COD and Re varied from 7 to 100%, 0.76 to 9.99, and 2.76 to 37.92 μm, respectively. The CBH and Cloud Base Temperature (CBT) are found to vary from 7.24 to 8.99 km and − 31.99 to − 13.75 °C. The Shortwave Cloud Radiative forcing (SWCRF) exerted by the lower part of Ci clouds over the region is observed to vary from − 435 to 148.87 W m−2 on a temporal scale with an average value of − 23.06 W m−2. The relationship between SWCRF and COD revealed radiative cooling effect with increase in COD with a dependency rate of − 18.53 W m−2/τ. SWCRF is found to be more sensitive to COD as compared to other cloud characteristics (CF, CBH and CBT). The case studies depict that the observed lower part of Ci clouds are advected from the ocean indicating the influence of large scale systems. Lower part of Ci optical and radiative properties showed wide variability depending up on the source of formation and evolution. This study also suggests that the high temporal variability of optical and radiative properties of Ci clouds needs to be well considered in climate models to reduce the uncertainty of cirrus radiative effects. [ABSTRACT FROM AUTHOR]

Surface solar irradiance varies on scales as small as seconds or metres. This variability is driven mostly by wavelength‐dependent scattering by clouds, and to a lesser extent by aerosols and water vapour. The highly variable nature of solar irradiance is not resolved by most atmospheric models, yet it affects, most notably, the land–atmosphere coupling and the quality of solar energy forecasting. Characterising variability, understanding the mechanisms, and developing models capable of resolving it accurately requires spatially and spectrally resolved observational datasets of solar irradiance at high resolution, which are rare. In 2021, we deployed a network of low‐cost radiometers in the Field Experiment on submesoscale spatio‐temporal variability in Lindenberg (FESSTVaL, Germany) and Land surface Interactions with the Atmosphere over the Iberian Semi‐arid Environment (LIAISE, Spain) field campaigns to gather data on cloud‐driven surface patterns of irradiance, including spectral effects, with the aim of addressing this gap in observations and understanding. We find in case studies of cumulus, altocumulus, and cirrus clouds that these clouds generate large spatiotemporal variability in irradiance, but through different mechanisms and at different spatial scales, ranging from 50 m to 30 km. Spectral irradiance in the visible range varies at similar scales, with significant blue enrichment in cloud shadows, most strongly for cumulus, and red enrichment in irradiance peaks, particularly in the case of semitransparent clouds or near cumulus cloud edges. Under clear‐sky conditions, solar irradiance varies significantly in water‐vapour absorption bands at the minute scale, due to variability in atmospheric moisture in the boundary layer. With this study, we show that observing detailed spatiotemporal irradiance patterns is possible using a relatively small, low‐cost sensor network, and that such network observations can provide insight and validation for the development of models capable of resolving irradiance variability. [ABSTRACT FROM AUTHOR]

This study presented an analysis of the geometric and optical properties of cirrus clouds with data produced by Compact Cloud-Aerosol Lidar (ComCAL) over Koror, Palau (7.3°N, 134.5°E), in the Tropical Western Pacific region. The lidar measurement dataset covers April 2018 to May 2019 and includes data collected during March, July and August 2022. The results show that cirrus clouds occur approximately 47.9% of the lidar sampling time, predominantly between altitudes of 15 and 18 km. Seasonal variations in cirrus top height closely align with those of the cold point tropopause. Most cirrus clouds exhibit low cloud optical depth (COD < 0.1), with an annual mean depolarization ratio of 31 ± 19%. Convective-forming cirrus clouds during the summer monsoon season exhibit a larger size by notably lower values in terms of color ratio. Extremely thin cirrus clouds (COD < 0.005) constituting 1.6% of total cirrus occurrences are frequently observed at 1–2 km above the cold point, particularly during winter and summer, suggesting significant stratosphere–troposphere exchange. The coldest and highest tropopause over Palau is persistent during winter, and related to the pathway of tropospheric air entering the stratosphere through the cold trap. In summer, the extremely thin cirrus above the cold point is likely correlated with equatorial Kelvin waves induced by western Pacific monsoon convection. [ABSTRACT FROM AUTHOR]

Organic‐lean and organic‐rich size‐selected soot particles were exposed to a varying O3 concentration, progressively decreasing the soot‐water contact angle (θ) to study its impact on ice nucleation (IN). The IN ability of fresh and O3‐aged soot between 218 and 233 K was observed while monitoring the particle mass and size distributions. The properties of fresh and O3‐aged bulk organic‐lean soot samples with a low and high O3‐adsorption were characterized for soot‐water θ, chemical composition, functional groups, soot‐water interaction ability and porosity. By retaining the soot porosity between aged and unaged samples, we demonstrate that a decrease in θ after O3‐aging enhances organic‐lean soot IN via pore condensation and freezing. Fresh organic‐rich soot exhibits suppressed homogeneous freezing, but after O3‐aging it freezes within uncertainty of the homogeneous freezing threshold of solution drops, because of increased hydrophilicity. Plain Language Summary: This study investigates the ice formation ability of soot exposed to O3 in the temperature range <−40°C relevant to the cirrus cloud regime for the role of surface wettability in the ice formation ability of organic‐lean and ‐rich soot. O3‐aged organic‐lean soot is more effective at forming ice crystals than unaged soot, due to an increase in soot‐water interaction ability promoting capillary condensation of water into porous structures that subsequently freeze. As the chemical functional group abundance of the organic‐lean soot does not change after O3‐exposure, the increased soot‐water interaction ability for the soot is attributed to O3‐H2O binding rather than surface oxidation. However, both water sorption isotherms and pore size distribution derived from N2 sorption measurements confirm the O3‐adsorption does not change the porosity of organic‐lean soot. This highlights the sole importance of hydrophilicity in pore water condensation prior to soot ice nucleation. O3‐aged organic‐rich soot shows poor ice formation ability because of unavailability of porous structures to condense capillary water. This study implies that organic‐lean soot will have an enhanced ice formation ability in the upper troposphere if exposed to O3 concentrations similar to that simulated in this study. Key Points: Higher O3‐concentration leads to a larger decease in water contact angle for organic‐lean soot without changing the soot porosityThe decrease in soot‐water contact angle from O3‐aging produces an ice nucleation enhancement for organic‐lean soot via PCF at T < 233 KO3‐aged organic‐rich soot freezes homogeneously at bulk droplet conditions despite increased hydrophilicity due to unavailable pores [ABSTRACT FROM AUTHOR]

Tropical-tropopause-layer cirrus clouds and their radiative effects represent a major uncertainty in the evaluation of Earth's energy budget. High-altitude aircraft offer an opportunity to provide observations at cirrus cloud altitudes, most commonly using in situ measurements of ice particle optical properties and composition. In particular, remote sensing of scattering properties and near-IR ice water absorption in the limb can provide unique insights into thin and sub-visible cirrus clouds. Here we present novel spectroscopic observations of path-averaged ice water absorptions on board NASA's Global Hawk aircraft during the Airborne Tropical TRopopause Experiment (ATTREX), which took place in 2011, 2013, and 2014. The University of California Los Angeles and University of Heidelberg mini-differential optical absorption spectroscopy (mini-DOAS) instrument provided multi-angle limb-scanning observations of scattered solar radiation in the near-IR (900–1726 nm), allowing the identification of ice and liquid water, O 2 , CO 2 , and H 2 O. The VLIDORT-QS radiative transfer (RT) code was specifically developed for this study and used to simulate high-altitude limb observations for varied cloud scenarios. We performed a comprehensive sensitivity study, developing a fundamental understanding of airborne near-IR limb observations of cirrus clouds. We identified two general distinct cases: a linear regime for optically thin clouds, where the ice absorption is proportional to ice water content (IWC), and a regime for optically thick cirrus clouds, where ice absorption is in saturation and independent of IWC. Results also demonstrate how molecular oxygen absorption can be used to infer information on optical properties of ice particles in the second regime only, with minimal information for thin cirrus clouds. We also explored the feasibility of retrieving IWC from mini-DOAS path-averaged ice water absorption (SIWP) measurements. This innovative interpolation-based approach requires a small number of RT calculations per observation to determine the sensitivity of SIWP to IWC. Spectral retrievals were applied for a particularly interesting case during Science Flight 2 over Guam in February 2014, during which the aircraft flew in circles in the same general area for an extended period of time. Retrieved IWC results are consistent with independent in situ measurements from other instruments on board. The measurements of ice particle scattering and absorption at different azimuths relative to the sun and at different altitudes represent a unique opportunity to test our approach and to infer properties of the ice particles, together with information on cirrus cloud radiative transfer. [ABSTRACT FROM AUTHOR]

The Anthropogenic Carbon Dioxide Monitoring (CO2M) mission is a constellation of satellites currently planned to be launched in 2026. CO2M is planned to be a core component of a Monitoring and Verification Support (MVS) service capacity under development as part of the Copernicus Atmosphere Monitoring Service (CAMS). The CO2M radiance measurements will be used to retrieve column-averaged dry-air mole fractions of atmospheric carbon dioxide (XCO2), methane (XCH4) and total columns of nitrogen dioxide (NO2). Using appropriate inverse modelling, the atmospheric greenhouse gas (GHG) observations will be used to derive United Nations Framework Convention on Climate Change (UNFCCC) COP 21 Paris Agreement relevant information on GHG sources and sinks. This challenging application requires highly accurate XCO2 and XCH4 retrievals. Three different retrieval algorithms to derive XCO2 and XCH4 are currently under development for the operational processing system at EUMETSAT. One of these algorithms uses the heritage of the FOCAL (Fast atmOspheric traCe gAs retrievaL) method, which has already successfully been applied to measurements from other satellites. Here, we show recent results generated using the CO2M version of FOCAL, called FOCAL-CO2M. To assess the quality of the FOCAL-CO2M retrievals, a large set of representative simulated radiance spectra has been generated using the radiative transfer model SCIATRAN. These simulations consider the planned viewing geometry of the CO2 instrument and corresponding geophysical scene data (including different types of aerosols and varying surface properties), which were taken from model data for the year 2015. We consider instrument noise and systematic errors caused by the retrieval method but have not considered additional error sources due to, for example, instrumental issues, spectroscopy or meteorology. On the other hand, we have also not taken advantage in this study of CO2M's MAP (multi-angle polarimeter) instrument, which will provide additional information on aerosols and cirrus clouds. By application of the FOCAL retrieval to these simulated data, confidence is gained that the FOCAL method is able to fulfil the challenging requirements for systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4). [ABSTRACT FROM AUTHOR]

Mineral dust, the most abundant atmospheric aerosol by mass, interacts with radiation directly and alters cloud properties indirectly. Many operational numerical weather prediction models account for aerosol direct effects by using climatological mean concentrations and neglect indirect effects. This simplification may lead to shortcomings in model forecasts during outbreaks of Saharan dust towards Europe, when climatological mean dust concentrations deviate strongly from actual concentrations. This study investigates errors in model analyses and short‐range forecasts during such events. We investigate a pronounced dust event in March 2021 using the pre‐operational ICOsahedral Nonhydrostatic weather and climate model with Aerosols and Reactive Trace gases (ICON‐ART) with prognostic calculation of dust and the operational European Centre for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) model, which deploys a dust climatology. We compare model analysis and forecast with measurements from satellite and in situ instruments. We find that inclusion of prognostic aerosol and direct radiative effects from dust improves forecasts of surface radiation during clear‐sky conditions. However, dust‐induced cirrus clouds are strongly underestimated, highlighting the importance of representing indirect effects adequately. These findings are corroborated by systematic quantification of forecast errors against satellite measurements. For this we construct an event catalogue with 49 dust days over Central Europe between January 2018 and March 2022. We classify model cells by simulated and observed cloudiness and simulated dustiness in the total atmospheric column. We find significant overestimations of brightness temperature for cases with dust compared with cases without dust. For surface shortwave radiation, we find median overestimations of 6.2% during cloudy conditions with dust optical depth greater than 0.1, however these are not significant compared with cloudy conditions without dust. Our findings show that the pre‐operational ICON‐ART and the operational IFS model still do not reproduce cloudiness adequately during events with Saharan dust over Central Europe. Missing implementations of prognostic dust, particularly of indirect effects on cloud formation, lead to significant underestimations of cloudiness and potentially overestimations of surface radiation. [ABSTRACT FROM AUTHOR]

We present a machine learning based emulator of a microphysics scheme for condensation and precipitation processes (Zhao‐Carr) used operationally in a global atmospheric forecast model (FV3GFS). Our tailored emulator architecture achieves high skill (≥94%) in predicting condensate and precipitation amounts and maintains low global‐average bias (≤4%) for 1 year of continuous simulation when replacing the Fortran scheme. The stability and success of this emulator stems from key design decisions. By separating the emulation of condensation and precipitation processes, we can better enforce physical priors such as mass conservation and locality of condensation, and the vertical dependence of precipitation falling downward, using specific network architectures. An activity classifier for condensation imitates the discrete‐continuous nature of the Fortran microphysics outputs (i.e., tendencies are identically zero where the scheme is inactive, and condensate is zero where clouds are fully evaporated). A temperature‐scaled conditional loss function ensures accurate condensate adjustments for a high dynamic range of cloud types (e.g., cold, low‐condensate cirrus clouds or warm, condensate‐rich clouds). Despite excellent overall performance, the emulator exhibits some deficiencies in the uppermost model levels, leading to biases in the stratosphere. The emulator also has short episodic skill dropouts in isolated grid columns and is computationally slower than the original Fortran scheme. Nonetheless, our challenges and strategies should be applicable to the emulation of other microphysical schemes. More broadly, our work demonstrates that with suitable physically motivated architectural choices, ML techniques can accurately emulate complex human‐designed parameterizations of fast physical processes central to weather and climate models. Plain Language Summary: In this study, we create computer code that uses machine learning to mimic a weather model's algorithm for handling how clouds form and rain falls. When used in the weather model to replace this algorithm, our machine learning code is highly accurate in simulations for a whole year. We achieve this by making smart code design choices. We split the code into two parts: one for cloud formation and one for rain and snow. This allows us to better build important aspects of these processes into the machine learning approach. For instance, clouds form where it is moist and evaporate when it gets dry, and rain and snow fall downward. Our code learns cloud behavior based on temperature to ensure it works both for cold, thin clouds high up in the sky and warm, thick clouds closer to the ground. Our work shows a path for suitably designed machine learning code to eventually replace important parts of weather and climate models, but also that this path still requires careful human design respecting known physical principles. Key Points: We build an emulator to replace the Zhao‐Carr Fortran microphysics scheme in FV3GFSThe integrated emulator sustains high skill throughout a 1‐year simulationTailoring the ML architecture to the structure of the underlying scheme greatly improves the online behavior of the emulator [ABSTRACT FROM AUTHOR]

In this study, a method for assimilating FY4A advanced geostationary radiance imager (AGRI) cirrus‐effected radiances (CER) is investigated, and the impact of this method on water vapor analysis and rainstorm forecasting is examined through observing system simulation experiments and actual case experiments. The high proportion of inverted humidity profiles in the cirrus‐effected pixels is the main reason for the negative effect of assimilation in the mid‐to‐lower troposphere. To address this, relevant constraint conditions are incorporated into the cost function. The statistical results reveal that the addition of a CER assimilation improves the analysis increment of water vapor, with pattern correlation coefficients of 0.33, 0.35, and 0.20 at 200, 300, and 400 hPa, respectively, which are greater than those of a clear‐sky radiance assimilation (0.28, 0.33, and 0.17, respectively). Moreover, the inclusion of a CER assimilation greatly improves data utilization, and has a neutral to positive effect on precipitation forecasting. Plain Language Summary: Infrared all‐sky radiance assimilation is an attractive but challenging problem in satellite data assimilation. Is there an alternative approach to achieve the assimilation of infrared radiance for a certain type of cloud? It is found that cirrus clouds, which are loose ice clouds composed of ice crystals, can partially transmit infrared radiance and are large in number. Considering these advantages, a new direct assimilation method for FY4A advanced geostationary radiance imager (AGRI) cirrus‐effected radiances is proposed in this paper. The method addresses the uncertainty in the assimilation of cirrus‐effected radiances by adding weak constraints of inverse humidity. This research highlights the substantial increase in AGRI data usage when incorporating cirrus‐effected radiance data, as well as the neutral‐to‐positive impact on water vapor analysis and precipitation forecasting. This study also suggests that future endeavors could combine infrared channels with lower‐level microwave channels, which may have a more significant contribution to infrared radiance assimilation. Key Points: A high percentage of inverse humidity exists in the atmospheric profile corresponding to cirrus cloud fields of view over landThe assimilation of cirrus cloud pixels greatly improves the utilization rateAssimilating advanced geostationary radiance imager cirrus‐effected radiances has a neutral to positive effect on water vapor analysis and precipitation forecasting [ABSTRACT FROM AUTHOR]

Remote sensing satellite monitoring involving the use of shortwave infrared (SWIR) solar backscatter radiation to measure atmospheric CH4 column concentrations provides wide−ranging and accurate data for quantitatively determining atmospheric CH4 emissions and is highly important for human studies of atmospheric composition and environmental protection. The ESA−launched Sentinel−2 satellite equipped with a tropospheric monitoring instrument (TROPOMI) can provide the concentration of CH4 columns in every piece of the global atmosphere every day. However, these data may be affected by surface albedo, SWIR, aerosols, cirrus cloud scattering, and other factors. The greenhouse gas observing satellite (GOSAT) launched by Japan has fairly accurate data that are minimally affected by the aforementioned factors; however, its data density is much less than that of the TROPOMI. In this study, we propose a CH4 model that combines the TROPOMI and GOSAT data. We construct the model by analyzing the data from the TROPOMI and GOSAT at the same location at the same time. Then, we apply the proposed model to a certain location at a certain time with TROPOMI data but without GOSAT data to obtain a large range of high−precision CH4 data. The most developed urban agglomeration in the Yangtze River Delta in China was selected for model construction and the correlations between the TROPOMI and GOSAT data and their spatial and temporal trends were analyzed. First, we analyzed the CH4 concentrations in the same area measured by both models. The results revealed a high degree of temporal and spatial correlation in the YRD region. The correlation coefficient reached 0.71 in the metropolitan area of the YRD. At the small−city scale, the correlation is much more significant, with the correlation reaching 0.80, 0.79, and 0.71 for Nanjing, Shanghai, and Ningbo, respectively. The most accurate model was screened through comparative construction to calibrate the TROPOMI data and high−precision and high−coverage CH4 concentration information was obtained for the study area. Five models (linear model, quadratic term model, cubic term model, lognormal model, and logistic model) were used to select the best−fitting model. The magnitudes of the differences in the CH4 concentrations calculated by each model were compared. The final results showed that the linear model, as the prediction model, had the highest accuracy, with a coefficient of determination (R22) of 0.542. To avoid the specificity of the constructed model, we used the same method in several simulations to validate. The coefficient of determination of the model constructed with different stochastic data was greater than 0.5. Subsequently, we used Nanjing as the study area and applied the same method to construct the model. The coefficient of determination of the model (R22) was approximately 0.601. The model constructed in this research can be used not only for data conversion between the same products from different sensors to obtain high−precision data products but also for calibrating newly developed satellite data products that utilize mature data products. [ABSTRACT FROM AUTHOR]

Large amounts of tropical precipitation have been observed as significantly concentrated over the western coast of Sumatra Island. In the present study, we used a cloud-resolving model to perform 14-day numerical simulations and reproduce the distinctive precipitation distributions over western Sumatra Island and adjacent areas. The control experiment, in which the warmer sea surface temperature (SST) near the coast was incorporated and the terminal velocity and effective radius of ice clouds were parameterized to be temperature dependent, adequately reproduced the precipitation concentration as well as the diurnal cycles of precipitation. We then used the column-integrated frozen moist static energy budget equation, which is virtually equivalent to the column-integrated moisture budget equation under the weak temperature gradient assumption, to formulate sensitivity experiments focusing on the effects of coastal SST and upper-level ice clouds. Analysis of the time-averaged fields revealed that the column-integrated moisture and precipitation in the coast were significantly reduced when a cooler coastal SST or larger ice cloud particle size was assumed. Based on the comparison of the sensitivity experiments and in situ observations, we speculate that ice clouds, which are exported from inland convection that is strictly regulated by solar radiation, promote the accumulation of moisture in the coastal region by mitigating radiative cooling. Together with the moisture and heat supplied by the warm ocean surface, they contribute to the large amounts of precipitation here. [ABSTRACT FROM AUTHOR]

Organized deep convective activity has been routinely monitored by satellite precipitation radar from the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM). Organized deep convective activity is found to increase not only with sea surface temperature (SST) above 27°C, but also with low-level wind shear. Precipitation shows a similar increasing relationship with both SST and low-level wind shear, except for the highest low-level wind shear. These observations suggest that the threshold for organized deep convection and precipitation in the tropics should consider not only SST, but also vertical wind shear. The longwave cloud radiative feedback, measured as the tropospheric longwave cloud radiative heating per amount of precipitation, is found to generally increase with stronger organized deep convective activity as SST and low-level wind shear increase. Organized deep convective activity, the longwave cloud radiative feedback, and cirrus ice cloud cover per amount of precipitation also appear to be controlled more strongly by SST than by the deviation of SST from its tropical mean. This study hints at the importance of non-thermodynamic factors such as vertical wind shear for impacting tropical convective structure, cloud properties, and associated radiative energy budget of the tropics. Significance Statement: This study uses tropical satellite observations to demonstrate that vertical wind shear affects the relationship between sea surface temperature and tropical organized deep convection and precipitation. Shear also affects associated cloud properties and how clouds affect the flow of radiation in the atmosphere. Although how vertical wind shear affects convective organization has long been studied in the mesoscale community, the study attempts to apply mesoscale theory to explain the large-scale mean organization of tropical deep convection, cloud properties, and radiative feedbacks. The study also provides a quantitative observational baseline of how vertical wind shear modifies cloud radiative effects and convective organization, which can be compared to numerical simulations. [ABSTRACT FROM AUTHOR]

In this paper a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. First, a review of the literature on the two-way transmittance method is presented. This method is a well-known lidar inversion method used to retrieve the optical properties of an aerosol–cloud layer between two molecular (i.e. aerosol and cloud-free) regions below and above, without the need to make any a priori assumptions about their optical and/or microphysical properties. Second, a simple mathematical expression of the two-way transmittance method is proposed for both ground-based and spaceborne lidar systems. This approach of the method allows the retrieval of the cloud optical depth, the cloud column lidar ratio and the vertical profile of the cloud backscatter coefficient. The method is illustrated for a cirrus cloud using measurements from the ground-based MPL and from the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Third, the database is then filtered with a cirrus identification criterion based on (and compared to) the literature using only lidar and radiosonde data. During the period from November 2018 to September 2022, 367 high-altitude cirrus clouds were identified at 00:00 and 12:00 UTC, of which 203 were successfully inverted with the two-way transmittance method. The statistical results of these 203 high-altitude cirrus clouds show that the cloud thickness is 1.8 ± 1.1 km, the mid-cloud temperature is - 51 ± 8 ∘ C and the linear cloud depolarization ratio is 0.32 ± 0.13. The application of the transmittance method yields an average cloud optical depth (COD) of 0.36 ± 0.45 and a mean effective column lidar ratio of 30 ± 19 sr. Statistical results of the errors associated with the two-way transmittance method retrievals are also provided. The highest occurrence of cirrus is observed in spring and the majority of cirrus clouds (48 %) are visible (0.03 < COD < 0.3), followed by opaque (COD > 0.3) with a percentage of 38 %. Together with results from other sites, possible latitudinal dependencies have been analysed together with correlations between cirrus cloud properties. For example, we noted that in Barcelona the COD correlates positively with the cloud base temperature, effective column lidar ratio and linear cloud depolarization ratio and negatively with the cloud base height. [ABSTRACT FROM AUTHOR]

Cirrus thinning, as one kind of geoengineering approach, not only cools our planet but also enhances the amount of sunlight reaching the Earth's surface (brightening effect). This study delves into the brightening effect induced by cirrus thinning with a flexible seeding method. The thinning of cirrus clouds alone leads to a considerable globally averaged cooling effect (−2.46 W m−2), along with a notable globally averaged brightening effect (2.19 W m−2). Cirrus thinning also results in substantial reductions in the cloud radiative effects of the lower mixed-phase and liquid clouds. While these reductions counteract the cooling effect from cirrus clouds, they enhance the brightening effect from cirrus clouds. Consequently, the brightening effect caused by cirrus seeding (4.69 W m−2) is considerably stronger than its cooling effect (−1.21 W m−2). Furthermore, due to the more pronounced changes from the mixed-phase and liquid clouds at low and mid-latitudes, the cooling effect is primarily concentrated at high latitudes. In contrast, the brightening effect is stronger over most low- and mid-latitude regions. Overall, cirrus thinning could lead to a notable brightening effect, which can be leveraged to offset the dimming effect (the opposite of the brightening effect) of other geoengineering approaches. [ABSTRACT FROM AUTHOR]

Observations and measurements show that crystals remain relatively compact at low ice supersaturations, but become increasingly hollowed and complex as the ice supersaturation rises. Prior measurements at temperatures >−25°C indicate that the transition from compact, solid ice to morphologically complex crystals occurs when the excess vapor density exceeds a threshold value of about 0.05 g m−3. A comparable threshold is not available at low temperatures. A temperature-dependent criterion for the excess vapor density threshold (Δρthr) that defines morphological transformations to complex ice is derived from laboratory measurements of vapor grown ice at temperatures below −40°C. This criterion depends on the difference between the equilibrium vapor density of liquid ( ρ e l ) and ice (ρei) multiplied by a measurement-determined constant, Δ ρ thr ≃ 0.27 (ρ e l − ρ e i ) . The new criterion is consistent with prior laboratory measurements, theoretical estimates, and it reproduces the classical result of about 0.05 g m−3 above −25°C. Since Δρthr defines the excess vapor density above which crystals transition to a morphologically complex (lower density) growth mode, we can estimate the critical supersaturation (scrit) for step nucleation during vapor growth. The derived values of scrit are consistent with previous measurements at temperatures above −20°C. No direct measurements of scrit are available for temperatures below −40°C; however, our derived values suggest some measurement-based estimates may be too high while estimates from molecular dynamics simulations may be too low. [ABSTRACT FROM AUTHOR]

An energy budget combining atmospheric moist static energy (MSE) and upper ocean heat content (OHC) is used to examine the processes impacting day-to-day convective variability in the tropical Indian and western Pacific Oceans. Feedbacks arising from atmospheric and oceanic transport processes, surface fluxes, and radiation drive the cyclical amplification and decay of convection around suppressed and enhanced convective equilibrium states, referred to as shallow and deep convective discharge–recharge (D–R) cycles, respectively. The shallow convective D–R cycle is characterized by alternating enhancements of shallow cumulus and stratocumulus, often in the presence of extensive cirrus clouds. The deep convective D–R cycle is characterized by sequential increases in shallow cumulus, congestus, narrow deep precipitation, wide deep precipitation, a mix of detached anvil and altostratus and altocumulus, and once again shallow cumulus cloud types. Transitions from the shallow to deep D–R cycle are favored by a positive "column process" feedback, while discharge of convective instability and OHC by mesoscale convective systems (MCSs) contributes to transitions from the deep to shallow D–R cycle. Variability in the processes impacting MSE is comparable in magnitude to, but considerably more balanced than, variability in the processes impacting OHC. Variations in the quantity of atmosphere–ocean coupled static energy (MSE + OHC) result primarily from atmospheric and oceanic transport processes, but are mainly realized as changes in OHC. MCSs are unique in their ability to rapidly discharge both lower-tropospheric convective instability and OHC. [ABSTRACT FROM AUTHOR]

We present an asymptotic approach for the systematic investigation of the effect of gravity waves (GWs) on ice clouds formed through homogeneous nucleation. In particular, we consider high- and midfrequency GWs in the tropopause region driving the formation of ice clouds, modeled with a double-moment bulk ice microphysics scheme. The asymptotic approach allows for identifying reduced equations for self-consistent description of the ice dynamics forced by GWs including the effects of diffusional growth and nucleation of ice crystals. Further, corresponding analytical solutions for a monochromatic GW are derived under a single-parcel approximation. The results provide a simple expression for the nucleated number of ice crystals in a nucleation event. It is demonstrated that the asymptotic solutions capture the dynamics of the full ice model and accurately predict the nucleated ice crystal number. The present approach is extended to allow for superposition of GWs, as well as for variable ice crystal mean mass in the deposition. Implications of the results for an improved representation of GW variability in cirrus parameterizations are discussed. [ABSTRACT FROM AUTHOR]

Based on the high-resolution data from April to October (the warm season) during the 2010 to 2020 timeframe provided by the FY-2F geostationary meteorological satellite, the classification and application evaluation of the eastward-moving southwest vortex cloud system affecting Zhejiang Province was conducted using cloud classification (CLC) and black body temperature (TBB) products. The results show that: (1) when the intensity of the eastward-moving southwest vortex is strong, the formed precipitation is predominantly regional convective precipitation. The cloud system in the center and southeast quadrant of the southwest vortex is dominated by cumulonimbus and dense cirrus clouds with convective precipitation, while the other quadrants are mainly composed of stratiform clouds, resulting in stable precipitation; (2) The original text is modified as follows: By using the TBB threshold method to identify stratiform and mixed cloud rainfall, we observed a deviation of one order of magnitude. This deviation is advantageous for moderate rain. However, the precipitation results from mixed clouds identified by the TBB threshold method are being overestimated; By means of the application of stratiform and mixed cloud rainfall identified by the TBB threshold method, an order of magnitude deviation was identified (3) The TBB can be consulted to estimate the precipitation, above which there is a large error. Moreover, the dispersion of precipitation produced by deep convective clouds is the largest, while the dispersion of precipitation produced by stratiform clouds is the smallest and has better predictability. Compared to CLC products, cloud type results based on TBB identification are better for convective cloud precipitation application. [ABSTRACT FROM AUTHOR]

The application of differential optical absorption spectroscopy (DOAS) for the diagnostics of localized methane emission based on data from satellite spectral measurements is discussed. It is shown that the application of DOAS in a scattering atmosphere can lead to significant errors in estimates of the concentration of methane. It is proposed that it be supplemented by a filtering procedure for signals distorted by atmospheric scattering effects which takes into account the correlation of the errors in the recovered concentrations of methane and water vapor owing to the uncertainty in the trajectory of the photons propagating in a scattering atmosphere. This correlation has been estimated by numerical calculations of these errors for a model atmosphere that includes cirrus clouds and two types of surface aerosols. [ABSTRACT FROM AUTHOR]

This work evaluates the quality of the satellite-based GLobal radiation model version 1.2 (GL1.2) estimates for four cloud classes. The GL1.2 calculates the global solar irradiance at ground level using images from a single visible band channel (VIS) of the Geostationary Operational Environmental Satellite -- GOES (GOES-East). The model´s performance was assessed by comparing hourly mean GL1.2 values with groundbased hourly measurements from the Brazilian National Institute of Meteorology (INMET, 354 automatic weather stations), for the entire year 2017. A satellite-based cloud classifier was adopted to discriminate the datasets according to prevailing cloud conditions (cumulus, stratus, cirrus and multilayer), but the clear sky behaviour was presented. The results were analysed for the five Brazilian regions. In the first analysis, we selected days with a predominance for five stations. It was found that the diurnal cycle was well reproduced. Then the regional investigation for the cloud types reveals that the best results are found for the Center West region over multilayer cloud (mean bias error, MBEannual = -2 ± 91 Wm-2 and root mean squared error, RMSE = 91 Wm-2), while the worst ones are in the North over cumulus fields (MBEannual = 101.5 ± 136.4 Wm-2). When considering all cloud types, the MBEannual is lower than 5 Wm-2 for the Northeast, Southeast and South regions, but it reaches 101 Wm-2 in the North. It is noteworthy that winter has the highest MBE in all classes analysed in the North, as well as cirrus situations in other regions. Although the inhomogeneities of cumulus and the semitransparent cirrus clouds tend to propagate errors to the model, the quality of GL1.2 data has a high degree of agreement with the observations. Improvements including an updated monthly minimum reflectance (Rmin) and water vapour column (H2Ovapour), and a better spatial resolution of the Advanced Baseline Imager (ABI) of GOES-16 (ABI/GOES-16) VIS imagery will allow refinement, especially for cumulus clouds. [ABSTRACT FROM AUTHOR]

We analyze cirrus cloud measurements from two dual-instrument cloud spectrometers, two hygrometers and a backscattersonde with the goal of connecting cirrus optical parameters usually accessible by remote sensing with microphysical size-resolved and bulk properties accessible in situ. Specifically, we compare the particle backscattering coefficient and depolarization ratio to the particle size distribution, effective and mean radius, surface area density, particle aspherical fraction, and ice water content. Data were acquired by instruments on board the M55 Geophysica research aircraft in July and August 2017 during the Asian Monsoon campaign based in Kathmandu, Nepal, in the framework of the StratoClim (Stratospheric and upper tropospheric processes for better climate predictions) project. Cirrus clouds have been observed over the Himalayan region between 10 km and the tropopause, situated at 17–18 km. The observed particle number densities varied between 10 and 10-4 cm -3 in the dimensional range from 1.5 to 468.5 µm in radius. Correspondingly, backscatter ratios from 1.1 up to 50 have been observed. Optical-scattering theory has been used to compare the backscattering coefficients computed from the measured particle size distribution with those directly observed by the backscattersonde. The aspect ratio of the particles, modeled as spheroids for the T-matrix approach, was left as a free parameter to match the calculations to the optical measures. The computed backscattering coefficient can be brought into good agreement with the observed one, but the match between simulated and measured depolarization ratios is insufficient. Relationships between ice particle concentration, mean and effective radius, surface area density, and ice water content with the measured backscattering coefficient are investigated for an estimate of the bulk microphysical parameters of cirrus clouds from remote sensing lidar data. The comparison between particle depolarization and aspherical fraction as measured by one of the cloud spectrometers equipped with a detector for polarization represents a novelty since it was the first time the two instruments were operated simultaneously on an aircraft. The analysis shows the difficulty of establishing an univocal link between depolarization values and the presence and amount of aspherical scatterers. This suggests the need for further investigation that could take into consideration not only the fraction of aspheric particles but also their predominant morphology. [ABSTRACT FROM AUTHOR]

Cirrus clouds are highly reflective clouds that play an important role in the atmospheric radiative balance and contribute to climate change. We present the seasonal distribution of cirrus cloud occurrence, characteristics and evolution over a coastal station (Goa, 15.4°N, 73.8°E, 40 m above MSL) in India using ground-based micro pulse lidar and radiosonde observations from July 2013 to June 2015. The frequency of cirrus occurrence was approximately 44%, 33%, 17% and 6% in winter (JF), premonsoon (MAM), southwest monsoon (JJAS) and postmonsoon season (OND), respectively. Thicker cirrus was more frequent in September, with an average value of > 1.7 ± 0.89 km. The frequency of cirrus descent occurs almost similarly in monsoon and postmonsoon (42% and 43% respectively). Two extreme cirrus descending cases were observed during the monsoon: (1) on 22 August 2014 with a displacement of 9.6 km from the initial height of 14 km with a descending rate and geometrical thickness of 0.4 ms−1 and 1.5 km, respectively, and (2) on 14 September 2013 with a displacement of 7.8 km with descending rate and thickness of 0.2 ms−1 and 2.3 km respectively. Relatively high humidity (> 60%) and low (< − 20 °C) ambient temperature caused thick cirrus formation in September 2013. However, during August 2014 event, relatively thinner cirrus was observed, and the same is attributed to lower humidity conditions (45 to 60%). The wind shear associated with the tropical easterly jet (TEJ) plays a major role in cirrus displacement by modifying their vertical velocity. The positive and negative vertical velocity fields cause cirrus to have a descending shape. The gradual descending pattern of cirrus is moving parallel to the vertical velocity contour, while the rapid descending in 2014 was mainly due to the occurrence of cirrus perpendicular to the velocity contour. Overall, this study highlights the descending nature of cirrus clouds over a coastal station in India, which can impact surface radiative characteristics. [ABSTRACT FROM AUTHOR]

The Anthropogenic Carbon Dioxide Monitoring (CO2M) mission is a constellation of satellites currently planned to be launched in 2026. CO2M is planned to be a core component of a Monitoring and Verification Support (MVS) service capacity under development as part of the Copernicus Atmosphere Monitoring Service (CAMS). The CO2M radiance measurements will be used to retrieve column-averaged dry-air mole fractions of atmospheric carbon dioxide (XCO2), methane XCH4) and total columns of nitrogen dioxide (NO2). Using appropriate inverse modelling, the atmospheric greenhouse gas GHG) observations will be used to derive United Nations Framework Convention on Climate Change (UNFCCC) COP 21 Paris Agreement relevant information on GHG sources and sinks. This challenging application requires highly accurate XCO2 and XCH4 retrievals. Three different retrieval algorithms to derive XCO2 and XCH4 are currently under development for the operational processing system at EUMETSAT. One of these algorithms uses the heritage of the FOCAL (Fast atmOspheric traCe gAs retrievaL) method, which has already successfully been applied to measurements from other satellites. Here, we show recent results generated using the CO2M version of FOCAL, called FOCAL-CO2M. To assess the quality of the FOCAL-CO2M retrievals, a large set of representative simulated radiance spectra has been generated using the radiative transfer model SCIATRAN. These simulations consider the planned viewing geometry of the CO2 instrument and corresponding geophysical scene data (including different types of aerosols and varying surface properties) which were taken from model data for the year 2015. We consider instrument noise and systematic errors due to the retrieval method but have not considered additional error sources due to e.g. instrumental issues, spectroscopy, or meteorology. On the other hand, we have also not taken advantage in this study of CO2M's MAP (Multi Angle Polarimeter) instrument, which will provide additional information on aerosols and cirrus clouds. By application of the FOCAL retrieval to these simulated data confidence is gained that the FOCAL method is able to fulfil the challenging requirements on systematic errors for the CO2M mission (spatio-temporal bias = 0.5 ppm for XCO2 and = 5 ppb for XCH4). [ABSTRACT FROM AUTHOR]

A methodology for the computation of spectrally resolved upwelling radiances in the presence of atmospheric diffusive layers is presented. The algorithm, called MAMA (Martinazzo–Maestri), provides fast simulations over the whole longwave spectrum, with high accuracy, particularly for optically thin scattering layers like cirrus clouds. The solution is obtained through a simplification of the multiple-scattering term in the general equation of the radiative transfer in a plane-parallel assumption. The scattering contribution is interpreted as a linear combination of the mean ambient radiances involved in the forward and back-scatter processes, which are multiplied by factors derived from the diffusive features of the layer. For this purpose, a fundamental property of the layer is introduced, named the angular back-scattering coefficient, which describes the fraction of radiation coming from a hemisphere and back-scattered into a specific direction (the observer in our case). This property, easily derived from the phase function of the particle size distribution, can be calculated from any generic single-scattering properties database, which allows for simple upgrades of the reference optical properties within the code. The paper discusses the solutions for mean upward and downward ambient radiances and their use in the simplification of the general radiative transfer equation for thermal infrared. To assess the algorithm performance, the results obtained with the MAMA code are compared with those derived with a discrete ordinate-based radiative transfer model for a large range of physical and optical properties of ice and liquid water clouds and for multiple atmospheric conditions. It is demonstrated that, for liquid water clouds, the MAMA code accuracy is mostly within 0.4 mW / (m 2 cm − 1 sr) with respect to the reference code both at far- and mid-infrared wavelengths. Ice cloud spectra are also accurately simulated at mid-infrared for all realistic cloud cases, which makes the MAMA code suitable for the analysis of any spectral measurements of current satellite infrared sounders. At far infrared, the MAMA accuracy is excellent when ice clouds with an optical depth of less than 2 are considered, which is particularly valuable since cirrus clouds are one of the main targets of the future mission FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) of the European Space Agency. In summary, the MAMA method allows computations of cloudy sky high-resolution radiances over the full longwave spectrum (4–100 μ m ) in less than a second (for pre-computed gas optical depths and on a standard personal computer). The algorithm exploits the fundamental properties of the scattering layers, and the code can be easily updated in relation to new scattering properties. [ABSTRACT FROM AUTHOR]

It remains challenging to accurately classify complicated clouds owing to the various types of clouds and their distribution on multiple layers. In this paper, multi-band radiation information from the geostationary satellite Himawari-8 and the cloud classification product of the polar orbit satellite CloudSat from June to September 2018 are investigated. Based on sample sets matched by two types of satellite data, a random forest (RF) algorithm was applied to train a model, and a retrieval method was developed for cloud classification. With the use of this method, the sample sets were inverted and classified as clear sky, low clouds, middle clouds, thin cirrus, thick cirrus, multi-layer clouds and deep convection (cumulonimbus) clouds. The results indicate that the average accuracy for all cloud types during the day is 88.4%, and misclassifications mainly occur between low and middle clouds, thick cirrus clouds and cumulonimbus clouds. The average accuracy is 79.1% at night, with more misclassifications occurring between middle clouds, multi-layer clouds and cumulonimbus clouds. Moreover, Typhoon Muifa from 2022 was selected as a sample case, and the cloud type (CLT) product of an FY-4A satellite was used to examine the classification method. In the cloud system of Typhoon Muifa, a cumulonimbus area classified using the method corresponded well with a mesoscale convective system (MCS). Compared to the FY-4A CLT product, the classifications of ice-type (thick cirrus) and multi-layer clouds are effective, and the location, shape and size of these two varieties of cloud are similar. [ABSTRACT FROM AUTHOR]

In this paper a statistical study of cirrus geometrical and optical properties based on 5 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. First, a review of the literature on the two-way transmittance method is presented. This method is a well-known lidar inversion method used to retrieve the optical properties of an aerosol/cloud layer between two molecular (i.e. aerosol/cloud-free) regions below and above, without the need to make any a priori assumptions about their optical and/or microphysical properties. Second, a simple mathematical expression of the two-way transmittance method is proposed for both ground-based and spaceborne lidar systems. This approach of the method allows the retrieval of the cloud optical depth, the columnar cloud lidar ratio and the vertical profile of the cloud backscatter coefficient. The method is illustrated for a cirrus cloud using measurements from a ground-based MPL and from the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Third, the data base is then filtered with a cirrus identification criterion based on (and compared to) the literature using only lidar and radiosonde data. During the period from November 2018 to September 2022, 367 high-altitude cirrus clouds have been identified at 00 and 12 UTC, of which 203 were successfully inverted with the two-way transmittance method. The statistical results of these 203 high-altitude cirrus clouds show that the cloud thickness is 1.8 ± 1.1 km, the mid-cloud temperature is -51 ± 8 °C and linear cloud depolarization ratio is 0.32 ± 0.13. The application of the transmittance method yields an average cloud optical depth (COD) of 0.36 ± 0.45 and a mean lidar ratio of 30 ± 19 sr. It is observed that the highest occurrence of cirrus is in spring and the majority of cirrus clouds (48 %) are visible (0.03 < COD < 0.3), followed by opaque (COD > 0.3) with a percentage of 38 %. Together with results from other sites, a possible latitudinal dependence of lidar ratio is detected: the lidar ratio increases with increasing latitude. We also note that in Barcelona the COD correlates positively with the cloud base temperature, lidar ratio and linear cloud depolarization ratio and negatively with the cloud base height. On the one hand, the decrease of the cloud base temperature and COD associated to an increase of the cloud base height occurs because clouds located at higher altitudes are formed from air masses with a lower water vapour content and, therefore, their geometric and optical thickness are smaller. On the other hand, the lidar ratio increases with increasing cloud optical depth, as the complexity and diversity of ice crystal shapes increases, due to collisions and turbulence. Lastly, the linear cloud depolarization ratio has a slightly positive tendency with the cloud optical depth, because as the cloud optical depth increases, the number of ice crystals increases and, as a consequence, the randomly aggregation of ice crystals within the cloud occurs more frequently, making ice crystals rougher and thus more depolarizing. [ABSTRACT FROM AUTHOR]

Using multi‐satellite observations, the cloud dynamic and microphysical characteristics were revealed during the rapid intensification (RI) of super‐typhoon Nanmadol (2022). As the storm intensifies, the eyewall contracts, the upper‐level divergence strengthens, and the cirrus cloud increases, leading to stronger upper‐level radial outflow and the vertical updraft. Meanwhile, it is found that there exists a dynamically attractive area in the outer rainbands, where particles grow effectively and form "a small amount of large particles" around 300 km from the eye. A theory of cloud dynamics‐microphysics interaction, called "tunnel theory," is further proposed to explain the generation, accumulation, and concentrated downflow of large particles in the outer rainbands during RI. Results suggest the unique feature of particle distribution in the outer rainbands could be a potential indicator for RI. Plain Language Summary: The rapid intensification (RI) of tropical cyclones (TCs) becomes more frequent in recent years, but the TC RI forecasts still remain challenging. Better understanding of the physical processes associated with RI of TCs would essentially improve its forecasting capability. The cloud dynamical and microphysical processes, especially their interactions that respond to RI are not well explored. In this study, the cloud macro and micro characteristics associated with RI of a super‐typhoon Nanmadol (2022) over the western Pacific are investigated using multiple satellites observations. The storm underwent RI during 15–16 September 2022, and it has wreaked havoc on Japan's most cities as it moved across the Japanese island afterward with a track length of about 1,120 km. It is found inside Nanmadol as well as other typhoons that a few large particles tend to occur in the outer rainbands during RI, due to the interaction of cloud dynamical and microphysical processes. Such unique feature of particle distribution in the outer rainbands could be a potential indicator for RI, and should also be paid attention to in model forecasting of typhoon precipitation. Key Points: First satellite‐based observational study on the interaction of cloud dynamics and microphysics during typhoon rapid intensification (RI)The eyewall contracts, the upper‐level divergence strengthens, and the convection column increases, providing kinetic energy for typhoon RIA "tunnel theory" is proposed for the generation, accumulation, and downflow of large particles in the outer rainbands during typhoon RI [ABSTRACT FROM AUTHOR]

Satellite observations of dry-column methane mixing ratios (XCH 4) from shortwave infrared (SWIR) solar backscatter radiation provide a powerful resource to quantify methane emissions in service of climate action. The TROPOspheric Monitoring Instrument (TROPOMI), launched in October 2017, provides global daily coverage at a 5.5 × 7 km 2 (nadir) pixel resolution, but its methane retrievals can suffer from biases associated with SWIR surface albedo, scattering from aerosols and cirrus clouds, and across-track variability (striping). The Greenhouse gases Observing SATellite (GOSAT) instrument, launched in 2009, has better spectral characteristics and its methane retrieval is much less subject to biases, but its data density is 250 times sparser than TROPOMI. Here, we present a blended TROPOMI + GOSAT methane product obtained by training a machine learning (ML) model to predict the difference between TROPOMI and GOSAT co-located measurements, using only predictor variables included in the TROPOMI retrieval, and then applying the correction to the complete TROPOMI record from April 2018 to present. We find that the largest corrections are associated with coarse aerosol particles, high SWIR surface albedo, and across-track pixel index. Our blended product corrects a systematic difference between TROPOMI and GOSAT over water, and it features corrections exceeding 10 ppb over arid land, persistently cloudy regions, and high northern latitudes. It reduces the TROPOMI spatially variable bias over land (referenced to GOSAT data) from 14.3 to 10.4 ppb at a 0.25 ∘ × 0.3125 ∘ resolution. Validation with Total Carbon Column Observing Network (TCCON) ground-based column measurements shows reductions in variable bias compared with the original TROPOMI data from 4.7 to 4.4 ppb and in single-retrieval precision from 14.5 to 11.9 ppb. TCCON data are all in locations with a SWIR surface albedo below 0.4 (where TROPOMI biases tend to be relatively low), but they confirm the dependence of TROPOMI biases on SWIR surface albedo and coarse aerosol particles, as well as the reduction of these biases in the blended product. Fine-scale inspection of the Arabian Peninsula shows that a number of hotspots in the original TROPOMI data are removed as artifacts in the blended product. The blended product also corrects striping and aerosol/cloud biases in single-orbit TROPOMI data, enabling better detection and quantification of ultra-emitters. Residual coastal biases can be removed by applying additional filters. The ML method presented here can be applied more generally to validate and correct data from any new satellite instrument by reference to a more established instrument. [ABSTRACT FROM AUTHOR]

Tropical upper-level clouds (TUCs) control the radiation budget in a climate system and strongly influence surface temperatures. This study examines global mean surface temperature changes due to the percent change in TUC cover, which is referred to as the tropical upper-level cloud radiative effect (TUCRE, in units of Kelvin per %). We use a radiative-convective equilibrium model that can control both upper- and lower-level cloud layers separately in three idealized regions (extratropics, tropical moist, and tropical dry regions) and two sub-regions (clear-moist and cloudy-moist regions) within the tropical moist regions. In the simulation, tropical reflectivity based on the TUC fraction assumes a primary role in determining the TUCRE. Accurate estimate of the TUCRE requires careful prescriptions according to actual satellite observations. We use the extent of TUC fraction and reflectivity obtained from 18 years (2003–2020) of satellite data on daily MODIS cloud properties. Our results show that the estimated net TUCRE ranges from 0.19 to 0.33 K/%, with a higher TUC fraction leading to higher temperatures (a warming effect) in the climate system. This means that a longwave TUCRE dominates over a shortwave TUCRE. When upper- and lower-level clouds interplay in the model, the range of the TUCRE was greater with a combination of two cloud layers, although all values were positive. The TUCRE is greater by 0.22 to 0.40 K/% when upper- and lower-level clouds are negatively coupled, because the Earth warms due to a decline in the reflectance of solar radiation. When upper- and lower-level clouds are positively coupled, the TUCRE is lower by 0.14 to 0.30 K/%, as less radiation reaches the Earth through combined cloud layers. Finally, we test the sensitivity of the TUCRE with five TUC fractions and 15 combinations of tropical reflectivity. Comparing our results with the TUCREs estimated from climate models will help us understand how TUC cover affects climate, and should greatly reduce uncertainty associated with cloud feedback. [ABSTRACT FROM AUTHOR]

The relationship of cirrus clouds and areas of increased relative humidity in the upper troposphere with symmetric instability developing on the subtropical (anticyclonic) side of jet streams are explored. Theoretical arguments are supplemented by case studies related to the Northern and Southern hemispheres. Using satellite images of cirrus clouds and reanalysis data, the values of the vertical eddy viscosity, which compensates for the inviscid growth of disturbances in case of symmetric instability, are estimated. At the levels of 250 and 200 hPa, a significant correlation between high relative humidity and potential vorticity characteristic of symmetric instability is confirmed. [ABSTRACT FROM AUTHOR]

Atmospheric lidars can simultaneously measure clouds and aerosols with high temporal and spatial resolution and hence help understand cloud–aerosol interactions, which are the source of major uncertainties in future climate projections. However, atmospheric lidars are typically custom-built, with significant differences between them. In this sense, lidar networks play a crucial role as they coordinate the efforts of different groups, provide guidelines for quality-assured routine measurements and opportunities for side-by-side instrument comparisons, and enforce algorithm validation, all aiming to homogenize the physical retrievals from heterogeneous instruments in a network. Here we provide a high-level overview of the Lidar Processing Pipeline (LPP), an ongoing, collaborative, and open-source coordinated effort in Latin America. The LPP is a collection of tools with the ultimate goal of handling all the steps of a typical analysis of lidar measurements. The modular and configurable framework is generic enough to be applicable to any lidar instrument. The first publicly released version of the LPP produces data files at levels 0 (raw and metadata), 1 (averaging and layer mask), and 2 (aerosol optical properties). We assess the performance of the LPP through quantitative and qualitative analyses of simulated and measured elastic lidar signals. For noiseless synthetic 532 nm elastic signals with a constant lidar ratio (LR), the root mean square error (RMSE) in aerosol extinction within the boundary layer is about 0.1 %. In contrast, retrievals of aerosol backscatter from noisy elastic signals with a variable LR have an RMSE of 11 %, mostly due to assuming a constant LR in the inversion. The application of the LPP for measurements in São Paulo, further constrained by co-located AERONET data, retrieved a lidar ratio of 69.9 ± 5.2 sr at 532 nm, in agreement with reported values for urban aerosols. Over the Amazon, analysis of a 6 km thick multi-layer cirrus found a cloud optical depth of about 0.46, also in agreement with previous studies. From this exercise, we identify the need for new features and discuss a roadmap to guide future development, accommodating the needs of our community. [ABSTRACT FROM AUTHOR]

Cirrus clouds provide a significant radiative forcing on the Earth's climate system. This paper looks at the connection in space and time between monthly mean lightning activity observed from the Lightning Imaging Sensor on board the International Space Station, and the global monthly mean cirrus cloud cover obtained from the MERRA‐2 reanalysis product. The correlation coefficient between the global monthly mean cloud optical thickness of the cirrus clouds (clouds at altitudes above the 400 hPa pressure levels) with the monthly mean lightning flash counts is 0.84, implying that monthly mean lightning can explain 70% of monthly variability of the global high cloud optical thickness. In addition, lightning amount explains nearly 60% of the monthly mean global area coverage of cirrus clouds. Given these statistically significant connections between lightning and cirrus clouds, we propose using global lightning data as an additional tool for monitoring monthly variability of cirrus clouds. Plain Language Summary: Cirrus clouds are one of the most important components maintaining the Earth's radiation budget. They reflect shortwave radiation from the Sun while absorbing the longwave radiation from the Earth. The net cloud radiative forcing for cirrus clouds results a warming of the climate. More/less cirrus clouds result in more/less warming of the planet. The moisture for the formation of cirrus clouds in the upper atmosphere is transported there in large part via deep convective storms, many associated with lightning activity and hence defined as thunderstorms. An increasing in cirrus clouds in a warmer atmosphere will amplify the initial warming. We explored in this study the relationship between global cirrus cloud coverage and global lightning activity. The results of the research show that 60%–70% of the monthly variability in global cirrus clouds can be explained by mean global lightning activity. Key Points: Cirrus clouds are one of the essential components in the atmosphere, with many important feedbacks on the radiation balance of EarthMonthly mean lightning can explain 70% of the monthly variability of the global high cloud optical thicknessLightning explains nearly 60% of the monthly mean global area coverage of cirrus clouds [ABSTRACT FROM AUTHOR]

This analysis presents the results of observation episodes for high-level clouds consisting of ice crystals with different orientations in space, using the EARLINET lidar network and MODIS data over Europe from 2015 to 2022. The technique used involves identifying specular reflecting layers through ground-based laser soundings of the atmosphere and finding synchronous images from space, followed by the retrieval of cirrus cloud parameters. The study considers several properties of high-level clouds, including reflection ratio (ρ), effective emissivity (ε), optical thickness, effective particle radius, water path, and top height, according to MODIS data. The results of retrieving these properties for cirrus clouds with different orientations of ice crystals over individual EARLINET lidar stations and over Europe as a whole are discussed. The study indicates that high-level clouds with ρ ≥ 0.15 and ε ≥ 0.4 definitely contain specular reflecting layers. [ABSTRACT FROM AUTHOR]

This paper presents the light-scattering matrices of atmospheric-aggregated hexagonal ice particles that appear in cirrus clouds. The aggregates consist of the same particles with different spatial orientations and numbers of these particles. Two types of particle shapes were studied: (1) hexagonal columns; (2) hexagonal plates. For both shapes, we studied compact and non-compact cases of particle arrangement in aggregates. As a result, four sets of aggregates were made: (1) compact columns; (2) non-compact columns; (3) compact plates; and (4) non-compact plates. Each set consists of eight aggregates with a different number of particles from two to nine. For practical reasons, the bullet-rosette and the aggregate of hexagonal columns with different sizes were also calculated. The light scattering matrices were calculated for the case of arbitrary spatial orientation within the geometrical optics approximation for sets of compact and non-compact aggregates and within the physical optics approximation for two additional aggregates. It was found that the light-scattering matrix elements for aggregates depend on the arrangement of particles they consist of. [ABSTRACT FROM AUTHOR]

The stability of ice crystal orientation is studied by modeling the airflow around ice crystals at moderate Reynolds number, where an ice crystal is approximated by a cylinder with three parameters: diameter D, length L, and zenith angle of the axis θ. In this paper, the torque acting on ice crystals is simulated at different θ first, and then a special θ with zero horizontal torque, denoted as θe, is sought as an equilibrium of ice crystal orientation. The equilibrium is classified into two kinds: stable and unstable. Ice crystals rotate to θe of stable equilibriums while deviating from θe of unstable ones once they are released into quiet air. Multiple equilibriums of ice crystal orientation are found via numerical simulations. A cylinder with D/L close to one has three equilibriums, two of which are stable (i.e., θe = 0° and 90°). A cylinder with D/L away from one has only two equilibriums, one of which is stable (i.e., either θe = 0° or 90°). In addition, an asymmetric cylinder has two, three, or five equilibriums, and their θe is sensitive to the distance between its geometrical center and its center of gravity. The sensitivity of θe to crystal asymmetry suggests large symmetric ice crystals tend to become asymmetric (or irregular) and subsequently oriented randomly. Significance Statement: Ice crystal orientation impacts high-cloud reflectance and satellite-based observations of high clouds significantly. However, its laboratory and field observations look dissimilar: the percentage of horizontally oriented ice crystals (HOICs) observed in the laboratory is quite high, while in the field it is often low and varies greatly in space and time. The motivation for this study is to elucidate what causes the difference between the laboratory and field observations. The torque acting on ice crystals are computed by modeling the airflow around ice crystals, revealing the conditions for nonhorizontal orientations of ice crystals. In quiet air, an ice crystal is oriented either horizontally or vertically when its shape is close to sphere. When its shape is elongated in one direction, its orientation depends on its asymmetry in density and shape. The sensitivity of ice crystal orientation to ice crystal asymmetry explains the low percentage of HOICs in the field, because asymmetric ice crystals are common in clouds. As an application, this sensitivity together with the observed percentage of HOICs can be used to infer the processes of ice crystal growth in clouds, providing clues to better representation of ice crystals in weather and climate models. [ABSTRACT FROM AUTHOR]

The EarthCARE (Earth Clouds, Aerosols and Radiation Explorer) satellite mission will provide new insights into aerosol–cloud–radiation interactions by means of synergistic observations of the Earth's atmosphere from a collection of active and passive remote sensing instruments, flying on a single satellite platform. The Multi-Spectral Imager (MSI) will provide visible and infrared images in the cross-track direction with a 150 km swath and a pixel sampling at 500 m. The suite of MSI cloud algorithms will deliver cloud macro- and microphysical properties complementary to the vertical profiles measured from the Atmospheric Lidar (ATLID) and the Cloud Profiling Radar (CPR) instruments. This paper provides an overview of the MSI cloud mask algorithm (M-CM) being developed to derive the cloud flag, cloud phase and cloud type products, which are essential inputs to downstream EarthCARE algorithms providing cloud optical and physical properties (M-COP) and aerosol optical properties (M-AOT). The MSI cloud mask algorithm has been applied to simulated test data from the EarthCARE end-to-end simulator and satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as from the Spinning Enhanced Visible InfraRed Imager (SEVIRI). Verification of the MSI cloud mask algorithm to the simulated test data and the official cloud products from SEVIRI and MODIS demonstrates a good performance of the algorithm. Some discrepancies are found, however, for the detection of thin cirrus clouds over bright surfaces like desert or snow. This will be improved by tuning of the thresholds once real observations are available. [ABSTRACT FROM AUTHOR]

Most climate models still suffer large warm and dry summer biases in the central United States (CUS). As a solution, we improved cumulus parameterization to represent 1) the lifting effect of small-scale rising motions associated with Great Plains low-level jets and midtropospheric perturbations by defining the cloud base at the level of condensation, 2) the constraint of the cumulus entrainment rate depending on the boundary layer depth, and 3) the temperature-dependent cloud-to-rainwater conversion rate. These improvements acted to (i) trigger mesoscale convective systems in unfavorable environmental conditions to enhance total rainfall amount, (ii) lower cloud base and increase cloud depth to increase low-level clouds and reduce surface shortwave radiation, (iii) suppress penetrative cumuli from shallow boundary layers to remedy the overestimation of precipitation frequency, and (iv) increase water detrainment to form sufficient cirrus clouds and balanced outgoing longwave radiation. Much of these effects were nonlocal and nonlinear, where more frequent but weaker convective rainfall led to stronger (and sometimes more frequent) large-scale precipitation remotely. Together, they produced consistently heavier precipitation and colder temperature with a realistic atmospheric energy balance, essentially eliminating the CUS warm and dry biases through robust physical mechanisms. [ABSTRACT FROM AUTHOR]

The National Institute for Environmental Studies has provided the column-averaged dry-air mole fraction of carbon dioxide and methane (XCO 2 and XCH 4) products (L2 products) obtained from the Greenhouse gases Observing SATellite (GOSAT) for more than a decade. Recently, we updated the retrieval algorithm used to produce the new L2 product, V03.00. The main changes from the previous version (V02) of the retrieval algorithm are the treatment of cirrus clouds, the degradation model of the Thermal And Near-infrared Spectrometer for carbon Observation–Fourier Transform Spectrometer (TANSO–FTS), solar irradiance spectra, and gas absorption coefficient tables. The retrieval results from the updated algorithm showed improvements in fitting accuracies in the O 2 A, weak CO 2 , and CH 4 bands of TANSO–FTS, although the residuals increase in the strong CO 2 band over the ocean. The direct comparison of the new product obtained from the updated (V03) algorithm with the previous version V02.90/91 and the validations using the Total Carbon Column Observing Network revealed that the V03 algorithm increases the amount of data without diminishing the data qualities of XCO 2 and XCH 4 over land. However, the negative bias of XCO 2 is larger than that of the previous version over the ocean, and bias correction is still necessary. Additionally, the V03 algorithm resolves the underestimation of the XCO 2 growth rate compared with the in situ measurements over the ocean recently found using V02.90/91 and V02.95/96. [ABSTRACT FROM AUTHOR]

Satellite observations of dry column methane mixing ratios (XCH4) from shortwave infrared (SWIR) solar backscatter radiation provide a powerful resource to quantify methane emissions in service of climate action. The TROPOMI instrument launched in October 2017 provides global daily coverage at 5.5 x 7 km² nadir pixel resolution but its retrievals can suffer from biases associated with SWIR surface albedo, scattering from aerosols and cirrus clouds, and across-track variability (striping). The GOSAT instrument launched in 2009 uses a retrieval method that is less subject to biases, but its data density is 200 times sparser than TROPOMI. Here we present a blended TROPOMI+GOSAT methane product obtained by training a machine learning (ML) model to predict the difference between TROPOMI and GOSAT co-located measurements, using only predictor variables included in the TROPOMI retrieval, and then applying the correction to the complete TROPOMI record from January 2018 to present. We find that the largest corrections are associated with coarse aerosol particles, high SWIR surface albedo, and across-track pixel index. Our blended product corrects a systematic difference between TROPOMI and GOSAT over water, and it features corrections exceeding 10 ppb over arid land, persistently cloudy regions, and high northern latitudes. It reduces the TROPOMI spatially variable bias over land (referenced to GOSAT data) from 14.0 to 10.7 ppb at 0.25° x 0.3125° resolution. Validation with TCCON ground-based column measurements shows reductions in variable bias compared to the original TROPOMI data from 6.0 to 5.2 ppb and in single-retrieval precision from 13.8 to 11.7 ppb. TCCON data are all in locations of SWIR surface albedo below 0.4 (where TROPOMI biases tend to be relatively low), but they confirm the dependence of TROPOMI biases on SWIR surface albedo and coarse aerosol particles, as well as the reduction of these biases in the blended product. Fine-scale inspection of the Arabian Peninsula shows that a number of hotspots in the original TROPOMI data are removed as artifacts in the blended product. The blended product also corrects striping and aerosol/cloud biases in single-orbit TROPOMI data, enabling better detection and quantification of ultra-emitters. Residual coastal biases can be removed by applying additional filters. The ML method presented here can be applied more generally to validate and correct data from any new satellite instrument by reference to a more established instrument. [ABSTRACT FROM AUTHOR]

This study investigates the possible mechanisms related to the wide range of relative humidity in cirrus clouds (RHi). Under the closed adiabatic assumption, the impacts of vertical motion and ice crystal deposition/sublimation on RHi are investigated through in situ observations and parcel model simulations. Vertical motion is an active external force that changes the RHi, and ice crystal deposition/sublimation plays a role in mitigating the change in the RHi. They are the two most important mechanisms involved in controlling the RHi fluctuation during cirrus evolution and could well explain the wide range of RHi in wave-related cirrus clouds. Furthermore, a comparison of statistical cloud characteristics from both observations and simulations shows that a very low value (e.g., 0.001) for the water vapor ice deposition coefficient is highly unlikely. [ABSTRACT FROM AUTHOR]

A typhoon or hurricane is one of the most destructive high-impact weather events. In this study, the genesis and development processes of Typhoon Nangka (2015), which occurred over the Western Pacific in 2015, were investigated based on the comprehensive observation data from three satellites, i.e., the Himawari-8 satellite, the CloudSat satellite and the Global Precipitation Measurement mission satellite (GPM), focusing on the characteristics of typhoon structure, precipitation and cloud. The results (Results) show that during the developing stage of Typhoon Nangka, the cloud system was relatively complex and changed significantly, with large raindrops dominating the precipitation around the eyewall in the first quadrant, and the convection in the eyewall and outer rainband burst upward to 17 km. In addition, three features were obvious: stratiform precipitation was dominant in the inner rainband, both the precipitation type (stratiform or convective) and intensity were distributed unevenly in the outer rainband, and large water content was located in the warm layer of clouds. Moreover, the collision growth and breakup of water droplets tended to be stable. The precipitation in the typhoon eyewall, inner rainband and outer rainband was significantly different; stratiform precipitation mainly occurred in the inner rainband, while convective precipitation mainly appeared in the eyewall and outer rainband. The cloud system was distributed asymmetrically, and the upper-layer and lower-layer clouds were closely related, dominated by single-layer clouds. There were deep convective clouds in the eyewall, and cirrus clouds with the broadest range across the eyewall. The coverage range of cirrus clouds was close to the radius of the typhoon. There were stratocumulus, altostratus and cumulus in the low levels. [ABSTRACT FROM AUTHOR]

The interaction between tropical clouds and radiation is studied in the context of the weak temperature gradient approximation, using very low order systems (e.g., a two-column two-layer model) as a zeroth-order approximation. Its criteria for the instability are derived in the systems. Owing to the connection between the instability (unstable fixed point) and the oscillation (limit cycle) in physics (phase) space, the systems suggest that the instability of tropical clouds and radiation leads to the atmospheric oscillations with distinct timescales observed. That is, the instability of the boundary layer quasi-equilibrium leads to the quasi-two-day oscillation, the instability of the radiative convective equilibrium leads to the Madden–Julian oscillation (MJO), and the instability of the radiative convective flux equilibrium leads to the El Niño–southern oscillation. In addition, a linear model as a first-order approximation is introduced to reveal the zonal asymmetry of the atmospheric response to a standing convective/radiative heating oscillation. Its asymmetric resonance conditions explain why a standing ~45-day oscillation in the systems brings about a planetary-scale eastward travelling vertical circulation like the MJO. The systems, despite of their simplicity, replicate the oscillations with the distinct timescales observed, providing a novel cloud parameterization for weather and climate models. Their instability criteria further suggests that the models can successfully predict the oscillations if they properly represent cirrus clouds and convective downdrafts in the tropics. [ABSTRACT FROM AUTHOR]

The assimilation of hyperspectral infrared sounders (HIS) observations aboard Earth-observing satellites has become vital to numerical weather prediction, yet this assimilation is predicated on the assumption of clear-sky observations. Using collocated assimilated observations from the Atmospheric Infrared Sounder (AIRS) and the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP), it is found that nearly 7.7% of HIS observations assimilated by the Naval Research Laboratory Variational Data Assimilation System–Accelerated Representer (NAVDAS-AR) are contaminated by cirrus clouds. These contaminating clouds primarily exhibit visible cloud optical depths at 532 nm (COD532nm) below 0.10 and cloud-top temperatures between 240 and 185 K as expected for cirrus clouds. These contamination statistics are consistent with simulations from the Radiative Transfer for TOVS (RTTOV) model showing a cirrus cloud with a COD532nm of 0.10 imparts brightness temperature differences below typical innovation thresholds used by NAVDAS-AR. Using a one-dimensional variational (1DVar) assimilation system coupled with RTTOV for forward and gradient radiative transfer, the analysis temperature and moisture impact of assimilating cirrus-contaminated HIS observations is estimated. Large differences of 2.5 K in temperature and 11 K in dewpoint are possible for a cloud with COD532nm of 0.10 and cloud-top temperature of 210 K. When normalized by the contamination statistics, global differences of nearly 0.11 K in temperature and 0.34 K in dewpoint are possible, with temperature and dewpoint tropospheric root-mean-squared errors (RMSDs) as large as 0.06 and 0.11 K, respectively. While in isolation these global estimates are not particularly concerning, differences are likely much larger in regions with high cirrus frequency. [ABSTRACT FROM AUTHOR]

We analyze cirrus cloud measurements from two dual-instrument cloud spectrometers, two hygrometers and a backscattersonde in view to connect cirrus optical parameters usually accessible by remote sensing with microphysical size resolved and bulk properties accessible in situ. Specifically, we compare the particle backscattering coefficient and depolarization ratio to the particle size distribution, effective and mean radius, surface area density, particle aspherical fraction and ice water content. Data have been acquired by instruments on board the M55 Geophysica research aircraft during July and August 2017 during the Asian Monsoon campaign based in Kathmandu, Nepal, in the framework of the StratoClim (Stratospheric and upper tropospheric processes for better climate predictions) project. Cirrus have been observed over the Hymalaian region between 10 km and the tropopause, situated at 17-18 km. The observed particle number densities varied between 10 and 10-4 cm-3 in the dimensional range from 1.5 to 468.5 μm in radius. Correspondingly, backscatter ratios from one tenth up to 50 have been observed. Optical scattering theory has been used to compare the backscattering coefficient computed from measured particle size distribution with those directly observed by the backscattersonde. The aspect ratio of the particles, modeled as spheroids for the T-matrix approach, was left as a free parameter to match the calculations to the optical measures. The computed backscattering coefficient can be set in good agreement with the observed one, but the match between simulated and determined depolarization ratios is insufficient, however. Relationships between ice particle concentration, mean and effective radius, surface area density and ice water content with the measured backscattering coefficient are investigated for an estimate of the bulk microphysical parameters of cirrus clouds from remote sensing lidar data. The comparison between particle depolarization and aspherical fraction as measured by one of the cloud spectrometers equipped with a detector for polarization, represents a novelty since it was the first time the two instruments are operated simultaneously on aircraft. The analysis shows the difficulty of establishing an univocal link between depolarization values and the presence and amount of aspherical scatterers. This suggests the need of further investigation that could take into consideration not only the fraction of aspheric particles but also their predominant morphology. [ABSTRACT FROM AUTHOR]