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The atmospheric temperature change associated with rapid sea ice loss events over the Barents–Kara Seas (BKS) is explored. Rapid sea ice loss events are defined as periods with a tendency for sea ice concentration averaged over BKS to be below the fifth percentile of the probability density function distribution during the winters of 1979–2020 for at least three consecutive days. Composite analysis shows that there is a significantly positive bottom‐amplified temperature anomaly ahead of the rapid sea ice loss, which is closely associated with a wave train composed of a Ural blocking and an upstream positive phase of the North Atlantic Oscillation. This structure is favorable for the transport of warm and moist air into the BKS, and therefore, the tropospheric temperature, including the surface air temperature, increases through horizontal warm‐temperature advection, specifically through warm advection of the climatological temperature by the anomalous wind. The cooling over the BKS due to the adiabatic effect and vertical mixing opposes the horizontal warm‐temperature advection above and below about 900 hPa, respectively. However, an increase in skin temperature prominently results from enhanced downward long‐wave radiation, which is also the main contributor to the rapid sea ice loss. [ABSTRACT FROM AUTHOR]

This article presents an analytical model for the diurnal cycle of slope‐normal profiles of potential temperature and wind speed characterizing thermally driven slope winds, generated by a daily‐periodic surface energy budget. The model extends the solution proposed by Zardi and Serafin, originally formulated for a pure sinusoidal surface forcing temperature. To account for the asymmetric features characterizing the daytime and nighttime phases, a full Fourier series expansion is derived, the coefficients and phases of which are prescribed from the surface energy budget driven by the daily‐periodic radiation model described in Part 1 of the present work. The model is applicable for any slope angle (0∘≤α≤90∘$$ {0}^{\circ}\le \alpha \le {90}^{\circ } $$) and orientation, at any latitude and elevation (up to 2500 m), and for all seasons. Despite some inherent limitations, the most remarkable being the absence of moist processes and latent heat fluxes, the model captures most key features of daily‐periodic slope wind systems, in particular the asymmetry between daytime and nighttime phases. Moreover, it allows exploration of the sensitivity of these flows to the various factors concurring in their development, and offers a basis for more realistic analytical solutions for slope winds. [ABSTRACT FROM AUTHOR]

Exploring the complex relationship between the freeze–thaw cycle and the surface energy budget (SEB) is crucial for deepening our comprehension of climate change. Drawing upon extensive field monitoring data of the Qinghai-Tibet Plateau, this study examines how surface energy accumulation influences the thawing depth. Combined with Community Land Model 5.0 (CLM5.0), a sensitivity test was designed to explore the interplay between the freeze–thaw cycle and the SEB. It is found that the freeze–thaw cycle process significantly alters the distribution of surface energy fluxes, intensifying energy exchange between the surface and atmosphere during phase transitions. In particular, an increase of 65.6% is observed in the ground heat flux during the freezing phase, which subsequently influences the sensible and latent heat fluxes. However, it should be noted that CLM5.0 has limitations in capturing the minor changes in soil moisture content and thermal conductivity during localized freezing events, resulting in an imprecise representation of the complex freeze–thaw dynamics in cold regions. Nevertheless, these results offer valuable insights and suggestions for improving the parameterization schemes of land surface models, enhancing the accuracy and applicability of remote sensing applications and climate research. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) directly heats the middle tropospheric atmosphere, and accurate simulation of its surface temperature is of great concern for improving climatic prediction and projection capabilities, but climate models always exhibit a cold bias. Based on the Coupled Model Intercomparison Project Phase 6 (CMIP6) models and in-situ observations during 1981–2014, this study elucidates the impact of the snow overestimation on the temperature simulation over the TP in CMIP6 from the perspective of local radiation processes and atmospheric circulation. On the one hand, more snow in the CMIP6 models not only directly cools the surface more, but also makes the surface receive less shortwave radiation due to the higher surface albedo, and thus has lower ground surface temperature (GST), and the more snow/albedo-low temperature process is particularly evident in the westerly region due to more uncertainty at high elevations. This process contributes 87% to the annual GST cold bias. Lower GST corresponds to less latent heat transfer and thereby lower surface air temperature (SAT). In addition, the more snow in the CMIP6 models leads to the weaker the South Asian summer monsoon and the westerlies, and brings less warm and moist air (less integrated water vapor flux), as well as less clear-sky downward longwave radiation (less water vapor amount and lower tropospheric air temperature) to the TP (contributing 58% to the annual GST cold bias). These processes will result in less both precipitation and surface latent heat loss, which offsets a 35% annual GST cold bias. Besides, the physical mechanism of snow on GST and SAT differs with season over the westerly and monsoon regions of the TP. The research highlights the importance of topography and snow parameterization schemes for optimizing CMIP6 models. [ABSTRACT FROM AUTHOR]

This study examines the annual cycle of the Surface Energy Budget (SEB) in the Beaufort‐Chukchi seas, focusing on the autumn transition. Shipboard measurements from NASA's Salinity and Stratification at the Sea Ice Edge (SASSIE) experiment (8 September–2 October 2022) and satellite flux analysis for the entire 2022 were utilized to provide a comprehensive perspective of the SEB's seasonal dynamics. An important finding is the alignment of SEB's autumnal transition with the September 22 equinox, marking the onset of prolonged Arctic darkness. This transition involved a shift from the summertime radiative heating to cooling conditions, characterized by outgoing longwave radiation surpassing incoming solar radiation and a notable increase in synoptic turbulent latent and sensible heat flux variability. The increased turbulent heat fluxes after the equinox were associated with increased occurrences of short‐duration cold air outbreaks. These outbreaks seem to originate from cold mesoscale surface winds transitioning from cooling landmasses or ice caps to the warmer seas, driven by differential cooling rates between land/ice and ocean as solar irradiance declined. Turbulent heat losses, outpacing longwave emission by more than fivefold, accelerated ocean surface cooling in the subsequent 2 months, leading to the complete freeze‐up of the Beaufort‐Chukchi seas by late November. These findings underscore the substantial influence of astronomical seasons on the SEB, emphasizing their crucial role in Arctic climate dynamics. Plain Language Summary: This study is to enhance understanding of Arctic Surface Energy Budget (SEB) patterns, focusing on energy exchanges at the open sea surface over the year. It examines autumn energy transition in the Beaufort‐Chukchi seas, using shipboard measurements from NASA's SASSIE experiment (8 September–2 October 2022) and satellite heat flux analyses for the entire year of 2022. These data sources offer insights into the energy flows and patterns in the region. An important finding is the alignment of the autumn energy transition with the September 22 equinox, marking the onset of the extended Arctic darkness and the transition from oceanic heat gain to loss. Cold air outbreaks from surrounding landmasses and ice caps increased, intensifying heat transfer from the ocean to the atmosphere through evaporation, conduction, and convection. Turbulent heat loss exceeded longwave emission by over fivefold, expediting ocean surface cooling over the subsequent 2 months, culminating in complete freezing of the Beaufort‐Chukchi seas by late November. Understanding the influence of astronomical seasons on the SEB is crucial for comprehending and predicting the Arctic climate changes. Key Points: Autumnal Equinox pivotal in ocean surface energy budget: heat loss began to surpass solar radiation gain per shipboard and satellite dataPost‐equinox, synoptic turbulent heat flux variability surged, linked to frequent cold, dry air outbreaks with a duration of a few daysTurbulent heat fluxes, five times longwave emission, accelerated ocean heat release, causing the Beaufort‐Chukchi seas freeze in November [ABSTRACT FROM AUTHOR]

Blue colour-coated steel roofs (BCCSRs) offer a lightweight and economical option to concrete and other cladding in buildings, but they are also controversial for altering the surface energy budget and water cycle. Obtaining spatial information about BCCSRs is crucial for exploring the environmental impacts of man-made landscapes. However, existing methods are not always effective due to the variety of BCCSR types and background conditions. To overcome these limitations, we proposed a new index (called BCCSI) based on Sentinel-2 multispectral images to map the commonly used BCCSRs. Five typical study areas were chosen worldwide to develop and validate the BCCSI. Based on spectral analysis, we constructed the BCCSI using the blue, red, green, and shortwave infrared 2 (SWIR2) bands to highlight the BCCSR while suppressing the background condition. Compared with five existing indices, the BCCSI was effective in the visual evaluation, separability analysis and BCCSR mapping. Moreover, the BCCSI achieved similar accuracy to the supervised classifier while avoiding the time-consuming and laborious effort of sample collection. Furthermore, the BCCSI showed its applicability in medium-resolution satellite data, such as Landsat-8 imagery. Thus, the proposed BCCSI provides a viable scheme for global BCCSR mapping and analysis.

Exploring the complex relationship between the freeze–thaw cycle and the surface energy budget (SEB) is crucial for deepening our comprehension of climate change. Drawing upon extensive field monitoring data of the Qinghai-Tibet Plateau, this study examines how surface energy accumulation influences the thawing depth. Combined with Community Land Model 5.0 (CLM5.0), a sensitivity test was designed to explore the interplay between the freeze–thaw cycle and the SEB. It is found that the freeze–thaw cycle process significantly alters the distribution of surface energy fluxes, intensifying energy exchange between the surface and atmosphere during phase transitions. In particular, an increase of 65.6% is observed in the ground heat flux during the freezing phase, which subsequently influences the sensible and latent heat fluxes. However, it should be noted that CLM5.0 has limitations in capturing the minor changes in soil moisture content and thermal conductivity during localized freezing events, resulting in an imprecise representation of the complex freeze–thaw dynamics in cold regions. Nevertheless, these results offer valuable insights and suggestions for improving the parameterization schemes of land surface models, enhancing the accuracy and applicability of remote sensing applications and climate research.

The Arctic is experiencing amplified climate warming, decreasing sea ice extent, increasingly earlier springtime snowmelt, and a related increase in fire activity. The transition from cold to warm season in the Arctic strongly varies between years, but our understanding of temperature and surface energy budget changes over the springtime is limited. Here we investigate intraseasonal variability of Arctic springtime temperature and surface energy budget components and their interannual trends over 40 years (1981–2020) across the terrestrial Arctic (above 60° N) using ERA5-Land reanalysis data. We found the central and western Siberian regions to have the highest interannual variability in spring temperature anomaly among all Arctic regions during the 40-year period. Also in this region, we discovered the strength increased for heat extremes and decreased for cold extremes when comparing the first and the last 20 years of our study. Peaks in composited extreme temperature and surface energy budget anomalies were observed to occur concurrently, indicating temperature extremes are not driven by surface energy budget components. Lastly, by utilizing power spectrum analyses, we identified the primary driver of temperature anomaly interannual variability to be operating at a 1- to 2-week frequency. Based on our findings and observations in the recent literature, we hypothesize that the observed interannual variability in springtime temperature can be attributed to increased Arctic sea ice decline and an increase in the frequency and strength of associated atmospheric blocking events.

The residual found by Garratt and Pearman (2020, Boundary-Layer Meteorology 177: 613–641) in the surface energy budget of a winter wheat crop is the result of combining seven separately measured or estimated individual fluxes, each with its own uncertainty. We show that the mean hourly residual as it varies through the day is closely correlated with the rate-of-change of radiative surface temperature. Using the latter as a basis for estimating the hourly storage closes the budget to within 5% of the incident broadband shortwave irradiance, down from 10% when storage is excluded. The storage so calculated both agrees with estimates for a maize crop (Hicks et al. 2020, Agricultural and Forest Meteorology 290: 108035) and with theoretical considerations. However, for storage calculations in the field, soil and canopy temperatures are preferable to surface temperature. [ABSTRACT FROM AUTHOR]

The surface energy budget is crucial for Arctic sea ice mass balance calculation and climate systems, among which turbulent heat fluxes significantly affect the air–sea exchanges of heat and moisture in the atmospheric boundary layer. Satellite observations (e.g. CERES and APP-X) and atmospheric reanalyses (e.g., ERA5) are often used to represent components of the energy budget at regional and pan-Arctic scales. However, the uncertainties of the satellite-based turbulent heat fluxes are largely unknown, and cross-comparisons with reanalysis data and in-situ observations are limited. In this study, satellite-based turbulent heat fluxes were assessed against in-situ observations from the N-ICE2015 drifting ice station (north of Svalbard, January–June 2015) and ERA5 reanalysis. The turbulent heat fluxes were calculated by two approaches using the satellite-based ice surface temperature and radiative fluxes, surface atmospheric parameters from ERA5, and snow/sea ice thickness from the pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS). We found that the bulk-aerodynamic formula based results could better capture the variations of turbulent heat fluxes, while the maximum entropy production based estimates are comparable with ERA5 in terms of root-mean-square error (RMSE). CERES-based estimates outperform the APP-X-based ones but ERA5 performs the best in all seasons (RMSE of 18 and 7 W m−2 for sensible and latent heat flux, respectively). The air–ice temperature/humidity differences and the surface radiation budget were found the primary driving factors in the bulk-formula method and maximum entropy production (MEP) method, respectively. Furthermore, errors in the surface and near-surface temperature and humidity explain almost 50% of the uncertainties in the estimates based on the bulk-formula, whereas errors in the net radiative fluxes explain more than 50% of the uncertainties in the MEP-based results.

The surface energy budget over the Qinghai-Tibet Plateau (QTP) and the Arctic significantly influences the climate system with global consequences. The performances of 30 selected Coupled Model Intercomparison Project Phase 6 (CMIP6) models were evaluated based on six sites in the QTP and Arctic. The simulation results for latent heat flux (LE) were more accurate in the QTP, where the correlation coefficient and root mean square error (RMSE) were 0.9 and 30 W m−2, respectively. The results for sensible heat flux (H) were more accurate in the Arctic, the correlation coefficient and RMSE were 0.8 and 24 W m−2, respectively. Furthermore, the multiple models mean results revealed that the surface energy flux had seasonal variation and regional differences over the QTP and the Arctic. In the QTP, H was the lowest in winter, increased in spring, and reached the maximum in summer. However, the transitional changes in spring and autumn were not apparent in the Arctic, mainly due to seasonal net radiation difference between the two places. LE was affected by precipitation and surface soil moisture content. This work is important for understanding land-atmosphere interactions and useful for improving the accuracy of land surface models simulations.

An "inverse‐temperature layer" (ITL) of water temperature increasing with depth is predicted based on physical principles and confirmed by in situ observations. Water temperature and other meteorological data were collected from a fixed platform in the middle of a shallow inland lake. The ITL persists year‐around with its depth on the order of one m varying diurnally and seasonally and shallower during daytimes than nighttimes. Water surface heat flux derived from the ITL temperature distribution follows the diurnal cycle of solar radiation up to 300 W m−2 during daytime and down to 50 W m−2 during nighttime. Solar radiation attenuation in water strongly influences the ITL dynamics and water surface heat flux. Water surface heat flux simulated by two non‐gradient models independent of temperature gradient, wind speed and surface roughness using the data of surface temperature and solar radiation is in close agreement with the ITL based estimates. Plain Language Summary: Heat stored in water bodies resulting from the absorption of solar radiation is the energy supply of evaporation and sensible heat flux into the atmosphere from water surface. Transfer of the thermal energy from water body into the atmosphere is only possible when water temperature increasing with depth within the top water layer referred to as the "inverse temperature layer (ITL)." The existence and persistence of the theoretically predicted phenomenon are demonstrated by the field observations of water temperature profile at an inland lake. The ITL depth is found to be comparable to the penetration depth of solar radiation with evident diurnal and seasonal cycles following closely those of solar radiation. Further understanding and analysis of the ITL process require higher resolution data of water temperature and solar radiation profiles within the top‐layer than those commonly collected in previous field experiments. Key Points: Inverse temperature layer (ITL) allows transfer of heat from water into atmosphereITL has prounced diurnal seasonal cycles persisting year‐aroundWater surface heat flux is simulated using non‐gradient models [ABSTRACT FROM AUTHOR]

Solar photovoltaic (PV) generation has become the major type of solar energy utilization as the world's energy demand grows. However, the layout of large-scale public PV plants changes the original underlying conditions and has an impact on the local surface energy budget and distribution. Based on the ecohydrological model T&C, taking the fixed utility-scale PV plants as the typical object proposes a PV module, and the T&C-PV model is developed to simulate the impact of PV plants on the regional surface energy budget. Compared with the original T&C model, a substantially improvement of the simulation of energy flux in the PV plant paved underlying surface has been achieved in the T&C-PV model. This model is applied to PV power plants in Xinjiang Province, China, and the results show that the sensible heat flux increased by 12% and the latent heat flux decreased by 25%, with the percentage of transpiration decreasing from 90.1% to 74.5% and the percentage of evaporation increasing from 9.9% to 25.5% after the PV power plants are set up. • Developed a PV module to simulate the energy budget of PV panels. • Established a T&C-PV model based on the ecohydrological model T&C. • Evaluate the change of heat flux near surface under the PV panel. • Quantitively estimate the influence of the PV plant on energy balance. [ABSTRACT FROM AUTHOR]

Parametric modeling of downwelling longwave irradiance under all‐sky conditions (LW↓) typically involves "correcting" a clear‐ (or non‐overcast) sky model estimate using solar‐irradiance‐based proxies of cloud cover in lieu of actual cloud cover given uncertainties and measurement challenges of the latter. While such approaches are deemed sound, their application in time and space is inherently limited. We report on a correction model free of solar irradiance‐derived cloud proxies that is applicable at the true daily (24 hr) and global scales. The new "cloud‐free" correction model demonstrates superior performance in a range of environments relative to existing cloud‐free modeling approaches and to corrections based on solar‐derived cloudiness proxies. Literature‐based performance benchmarking indicates a performance that is often comparable to—and in some cases superior to—performances yielded by conventional parametric modeling approaches employing locally or regionally calibrated parameters, as well as to performances of satellite‐based algorithms. Plain Language Summary: Downwelling longwave irradiance (LW↓) is a major component of Earth's surface energy budget and is often modeled indirectly using routinely measured surface meteorological variables. In overcast (or "all‐sky") conditions, LW↓ is typically estimated by correcting an estimate valid for non‐overcast (or "clear‐sky") conditions using information about cloud cover or cloudiness proxies derived from solar irradiance variables. Cloud cover information is often unavailable and uncertain, and proxies based on solar irradiance variables inherently limit the correction to the daytime. Here, we present a correction model that circumvents the dependence on cloud variables or their proxies and document its performance when applied under a variety of conditions. Key Points: A model free of cloud variables or their solar‐based proxies is proposed to correct clear‐sky longwave irradiances under all‐sky conditionsModel performance is weakly sensitive to the underlying clear‐sky model when jointly parameterizedThe model yields daily errors of 3.9%–4.5% over ocean and 5.5%–7% over land, depending on the error metric and underlying clear‐sky model [ABSTRACT FROM AUTHOR]

The land surface energy exchange indirectly describes the energy forcing effect of solar radiation on the atmospheric system. Exploring the exchange process is of great significance to understand the formation and change of weather and climate. Based on the ERA5 reanalysis data and a process‐based land surface model (the Ecosystem‐Atmosphere Simulation Scheme), this study analysed the spatiotemporal variations and influencing factors in the energy budget in the Loess Plateau (LP). The results showed that from 1990 to 2017, the average annual surface net radiation (Rn) and latent heat (LE) in the LP showed a decreasing trend. The Rn and LE presented an increased spatial pattern from northwest to southeast. On a monthly scale, the Grain for Green (GFG) project amplified the negative effect in the period of November to February and September, but diminished the negative effect in other months. Climate change contributed more to energy exchange than land cover change during the study period. Our results provide useful information for developing adaptive strategies for the region to adapt to global climate change. [ABSTRACT FROM AUTHOR]

The presence of taliks (perennially unfrozen zones in permafrost areas) adversely affects the thermal stability of infrastructure in cold regions, including roads. The role of heat advection on talik development and feedback on permafrost degradation has not been quantified methodically in this context. We incorporate a surface energy balance model into a coupled groundwater flow and energy transport numerical model (SUTRA‐ice). The model, calibrated with long‐term observations (1997–2018 on the Alaska Highway), is used to investigate and quantify the role of heat advection on talik initiation and development under a road embankment. Over the 25‐year simulation period, the new model is driven by reconstructed meteorological data and has a good agreement with near surface soil temperatures. The model successfully reproduces the increasing depth to the permafrost table (mean absolute error <0.2 m), and talik development. The results demonstrate that heat advection provides an additional energy source that expedites the rate of permafrost thaw and roughly doubles the rate of permafrost table deepening, compared to purely conductive thawing. Talik initially formed and grew over time under the combined effect of water flow, snow insulation, road construction and climate warming. Talik formation creates a new thermal state under the road embankment, resulting in acceleration of underlying permafrost degradation, due to the positive feedback of heat accumulation created by trapped unfrozen water. In a changing climate, mobile water flow will play a more important role in permafrost thaw and talik development under road embankments, and is likely to significantly increase maintenance costs and reduce the long‐term stability of the infrastructure. Plain Language Summary: Formation of taliks (perennially unfrozen zones in permafrost areas) affects the thermal, hydrological, and biogeochemical processes at and below the land surface. The presence of taliks beneath or adjacent to constructed structures has been reported in many permafrost settings, but the processes controlling the initiation, formation, and extent of a talik under a road embankment remains largely unknown. In this study, a fully coupled groundwater flow and energy transport model integrated with a surface energy budget model is developed and validated with field observations from a Canadian sub‐Arctic discontinuous permafrost zone. Our results show that positive feedback mechanisms related to mobile porewater flow through the taliks greatly increased permafrost degradation. Talik formation creates a new hydrothermal state under the road embankment and poses a serious threat to overlying infrastructure. Additionally, dispatching the snow from the road pavement onto the embankment slopes may initiate an irreversible permafrost thaw feedback through the creation of taliks. With a warming climate, subsurface water flow will have a more important role in permafrost thaw and talik development. The results from our research highlight the importance of adequate drainage systems below road embankments to preserve permafrost. Key Points: A fully coupled groundwater flow and energy transport model integrated with a surface energy budget model is developed and validated with field observationsTalik formation is triggered by the combined effect of snow cover, mobile porewater flow, road construction, and atmospheric warmingConnectivity of two isolated taliks located up‐gradient and down‐gradient of the road embankment led to accelerated permafrost thaw [ABSTRACT FROM AUTHOR]

Surface downward longwave radiation (SDLR) is significant with regard to surface energy budgets and climate research. The uncertainty of cloud base height (CBH) retrieval by remote sensing induces the vast majority of SDLR estimation errors under cloudy conditions; reliable CBH observation and estimation are crucial for determining the cloud radiative effect. This study presents a CBH retrieval methodology built from 10 thermal spectral data from Himawari-8 (H-8) observations, utilizing the random forest (RF) algorithm to fully account for each band's contribution to CBH. The algorithm utilizes only infrared band data, making it possible to obtain CBH 24 h a day. Considering some factors that can significantly affect the CBH estimation, RF models are trained for different clouds using inputs from multiple H-8 channels together with geolocation information to target CBH derived from CloudSat/CALIPSO combined measurements. The validation results reveal that the new methodology performs well, with a root-mean-square error (RMSE) of only 1.17 km for all clouds. To evaluate the effect of CBH on SDLR estimation, an all-sky SDLR estimation algorithm based on previous CBH predictions is proposed. The new SDLR product not only has a resolution that is noticeably higher than that of benchmark products of the SDLR, such as the Clouds and the Earth's Radiant Energy System (CERES) and the next-generation reanalysis (ERA5) of the European Centre for Medium-Range Weather Forecasts (ECMWF), but it also has greater accuracy, with an RMSE of 21.8 W m−2 for hourly surface downward longwave irradiance (SDLI). [ABSTRACT FROM AUTHOR]

Due to its latitude and ample year‐round rainfall, Ireland is typically an energy‐limited regime in the context of soil moisture availability and evapotranspiration. However, during the summer of 2018, regions within the country displayed significant soil moisture deficits, associated with anomalous atmospheric forcing conditions, with consequent impacts on the surface energy balance. Here, we explore the utility of a physically based land surface scheme coupled with observational, global gridded reanalysis and satellite‐derived data products to analyse the spatial and temporal evolution of the 2018 summer drought event in Ireland over grassland, which represents the dominant agricultural land‐cover. While the surface–air energy exchanges were initially dominated by atmospheric anomalies, soil moisture constraints became increasingly important in regulating these exchanges, as the accumulated rainfall deficit increased throughout the summer months. This was particularly evident over the freer draining soils in the east and southeast of the country. From late June 2018, we identify a strong linear coupling between soil moisture and both evapotranspiration and vegetation response, suggesting a shift from an energy‐limited evapotranspiration regime into a dry or soil water‐limited regime. Applying segmented regression models, the study quantifies a critical soil moisture threshold as a key determinant of the transition from wet to dry evaporative regimes. These findings are important to understand the soil moisture context under which land–atmosphere couplings are strongest in water‐limited regimes across the country and should help improve the treatment of soil parameters in weather prediction models, required for subseasonal and seasonal forecasts, consequently enhancing early warning systems of summer climate extremes in the future. [ABSTRACT FROM AUTHOR]

Blue colour-coated steel roofs (BCCSRs) offer a lightweight and economical option to concrete and other cladding in buildings, but they are also controversial for altering the surface energy budget and water cycle. Obtaining spatial information about BCCSRs is crucial for exploring the environmental impacts of man-made landscapes. However, existing methods are not always effective due to the variety of BCCSR types and background conditions. To overcome these limitations, we proposed a new index (called BCCSI) based on Sentinel-2 multispectral images to map the commonly used BCCSRs. Five typical study areas were chosen worldwide to develop and validate the BCCSI. Based on spectral analysis, we constructed the BCCSI using the blue, red, green, and shortwave infrared 2 (SWIR2) bands to highlight the BCCSR while suppressing the background condition. Compared with five existing indices, the BCCSI was effective in the visual evaluation, separability analysis and BCCSR mapping. Moreover, the BCCSI achieved similar accuracy to the supervised classifier while avoiding the time-consuming and laborious effort of sample collection. Furthermore, the BCCSI showed its applicability in medium-resolution satellite data, such as Landsat-8 imagery. Thus, the proposed BCCSI provides a viable scheme for global BCCSR mapping and analysis. [ABSTRACT FROM AUTHOR]

The pre-ALPACA (Alaskan Layered Pollution And Chemical Analysis) 2019 winter campaign took place in Fairbanks, Alaska, in November–December 2019. One objective of the campaign was to study the life-cycle of surface-based temperature inversions and the associated surface energy budget changes. Several instruments, including a 4-component radiometer and sonic anemometer were deployed in the open, snow-covered University of Alaska Fairbanks (UAF) Campus Agricultural Field. A local flow from a connecting valley occurs at this site. This flow is characterized by locally elevated wind speeds (greater than 3 m s - 1 ) under clear-sky conditions and a north-westerly direction. It is notably different to the wind observed at the airport more than 3.5 km to the south-west. The surface energy budget at the UAF Field site exhibits two preferential modes. In the first mode, turbulent sensible heat and net longwave fluxes are close to 0 W m - 2 , linked to the presence of clouds and generally low winds. In the second, the net longwave flux is around − 50 W m - 2 and the turbulent sensible heat flux is around 15 W m - 2 , linked to clear skies and elevated wind speeds. The development of surface-based temperature inversions at the field is hindered compared to the airport because the local flow sustains vertical mixing. In this second mode the residual of the surface energy budget is large, possibly due to horizontal temperature advection. [ABSTRACT FROM AUTHOR]

Mount Emei is located on the eastern edge of the Tibetan Plateau, on the transition zone between the main body of the Tibetan Plateau and the Sichuan Basin in China. It is not only the necessary place for the eastward movement of the plateau system but also the place where the southwest vortex begins to develop. Its special geographical location makes it particularly important to understand the turbulence characteristics and surface energy balance of this place. Based on the Atmospheric Boundary Layer (ABL) tower data, radiation observation data and surface flux data of Mount Emei station on the eastern edge of the Tibetan Plateau from December 2019 to February 2022, the components of surface equilibrium are estimated by the eddy correlation method and Thermal Diffusion Equation and Correction (TDEC) method, the characteristics of surface energy exchange in the Mount Emei area are analyzed, and the aerodynamic and thermodynamic parameters are estimated. The results show that the annual average value of zero-plane displacement d is 10.45 m, the annual average values of aerodynamic roughness Z 0 m and aerothermal roughness Z 0 h are 1.61 and 1.67 m, respectively, and the annual average values of momentum flux transport coefficient C D and sensible heat flux transport coefficient C H are 1.58 × 10 − 2 and 3.79 × 10 − 3 , respectively. The dimensionless vertical wind fluctuation variance in the Mount Emei area under unstable conditions can better conform to the 1/3rd power law of the Monin–Obukhov similarity theory, while the dimensionless horizontal wind fluctuation variance under unstable lamination and the dimensionless 3D wind fluctuation variance under stable condition does not conform to this law. In the near-neutral case, the dimensionless velocity variance in the vertical direction in this area is 1.314. The daytime dominance of sensible and latent heat fluxes varied seasonally, with latent heat fluxes dominating in summer and sensible heat transport dominating in winter. he surface albedo of Mount Emei in four seasons is between 0.04 and 0.08. The surface albedo in summer and autumn is higher than that in Mount Emei. The influence of the underlying surface on surface reflectance is much greater than other factors, such as altitude, longitude and latitude. The non-closure phenomenon is significant in the Mount Emei area. The energy closure rates before and after considering canopy thermal storage are 46% and 48%, respectively. The possible reason for the energy non-closure in this area is that the influence of horizontal advection and vertical advection on the energy closure is not considered. [ABSTRACT FROM AUTHOR]

Heat transport through short and closed vegetation such as grass is modelled by a simple diffusion process. The grass is treated as a homogeneous 'sponge layer' with uniform thermal diffusivity and conductivity, placed on top of the soil. The temperature and heat-flux dynamics in both vegetation and soil are described using harmonic analysis. All thermal properties have been determined by optimization against observations from the Haarweg climatological station in The Netherlands. Our results indicate that both phase and amplitude of soil temperatures can be accurately reproduced from the vegetation surface temperature. The diffusion approach requires no specific tuning to, for example, the daily cycle, but instead responds to all frequencies present in the input data, including quick changes in cloud cover and day–night transitions. The newly determined heat flux at the atmosphere–vegetation interface is compared with the other components of the surface energy balance at this interface. The budget is well-closed, particularly in the most challenging cases with varying cloud cover and during transition periods. We conclude that the diffusion approach (either implemented analytically or numerically) is a physically consistent alternative to more ad hoc methods, like 'skin resistance' approaches for vegetation and bulk correction methods for upper soil heat storage. However, more work is needed to evaluate parameter variability and robustness under different climatological conditions. From a numerical perspective, the present representation of vegetation allows for both slow and rapid feedbacks between the atmosphere and the surface. As such, it would be interesting to couple the present surface parametrization to turbulence-resolving models, such as large-eddy simulations. [ABSTRACT FROM AUTHOR]

Modern urban climatology is a part of boundary-layer climatology with a focus on the urban effects on the atmosphere. The best known of these effects is the urban heat island (UHI), which has been a subject of study for more than 200 years and may be categorised into air, surface and substrate types. Progress on this topic has occurred in various phases associated with theoretical developments, improvements in technology (instruments and computing) and study design, to isolate the causative drivers. The history of the field can be categorised into response-based (descriptive) and process-based (analytic) periods associated with hypothesis generation and testing, respectively. Myrup's paper on simulating the UHI, published in 1969, is at the forefront of this shift in approach and is the first application of numerical modelling to the topic. Its computational methods place the UHI within the context of the surface energy budget and the exchanges of energy, urban characteristics, and the substrate as well as overlying air. The paper is a classic that had considerable impact on the approach that geographical climatology took to examining the UHI; however, it is not without its limitations Careful reading of Myrup's work provides insights into how the field has evolved in the last 50 years. In particular the recurring issues associated with conceputalising the urban thermal effect and challenge of comparing models results with field observations. Remarkably, key urban climate questions on how to cool cities, how to plan cities for future climate, and the factors that impact UHI are still being studied, albeit with more sophisticated models. A numerical model of the urban heat island is part of a rich literature on the UHI that illustrates the development of the urban climate science that deserves to be read and cited. [ABSTRACT FROM AUTHOR]

While most Arctic amplification research is focused on sea ice reduction and its feedbacks onto the climate system, the impacts of permafrost degradation in high latitudes and subsequent land–atmosphere interactions potentially resulting in terrestrial-based amplification are still unclear. Previous work has shown that thermodynamics plays a large part in surface air temperature increases over continuous and discontinuous permafrost at the end of the lengthening warm season. Here, a novel information flow methodology is applied to determine the specific land surface drivers of autumn surface air temperatures over different frozen ground regions in Eurasia. The influences of a changing surface energy balance are particularly apparent in the continuous and discontinuous permafrost regions. There, autumn surface air temperatures transition from being driven by summer and autumn sensible heat flux in the late twentieth century to a combination of latent and ground heat flux as the twenty-first century progresses. Changing seasonal snow patterns aid this transition, whereby continued thermodynamically influenced warming initially occurs through early-year insulation and subsurface hydrothermal heat transport. Later in the twenty-first century, a likely switch to late-season soil heat gain due to direct atmospheric exposure occurs as less snow remains in autumn. This role of evolving surface-atmosphere energy exchange reinforces the importance of the terrestrial contribution to Arctic amplification, as the high latitudes become a hot spot for increasing land–atmosphere interactions. [ABSTRACT FROM AUTHOR]

Studies of land‐atmosphere interactions under a clear sky and low cumulus cloud conditions are common from long‐term observatories like at the southern great plains. How well the relationships and responses of surface radiative and turbulent heat fluxes determined from these investigations hold for more heterogeneous surfaces in other climate regimes, however, is uncertain. In this study, detailed observations of the surface energy budget and daytime boundary layer properties are analyzed using measurements from the Chequamegon Heterogenous Ecosystem Energy‐Balance Study Enabled by a High‐Density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign, July‐October 2019, across a heterogeneous forested landscape of northern Wisconsin. A cloud regime framework is employed to classify consecutive periods of clear skies from lower atmosphere stratiform and cumulus clouds. A seasonal transition from low cumulus to low stratiform periods occurred, together with a diurnal pattern in cloudy or clear sky period dominance. Radiative forcing was highly dependent on sky conditions, leading to changes in the redistribution efficiency of radiative energy by the surface turbulent heat fluxes. During CHEESEHEAD19, small Bowen ratios dominated with daytime latent heat fluxes three times as large as sensible heat fluxes for all sky conditions studied; the forested region, therefore, falls within an energy‐limited regime. The depth of the daytime mixed layer depended upon the sky condition and thermodynamic setting; deeper mixed layers occurred during periods of low cumulus and not clear skies. Profiles of vertical velocity were found to have enhanced variance under low cumulus compared to clear sky periods, suggesting potential for cloud feedbacks on boundary layer structure and surface energy fluxes. Plain Language Summary: This study investigates how different cloud regimes influence the exchange of energy at Earth's surface over a highly heterogeneous forested landscape in northern Wisconsin. Clouds directly modify the solar and infrared radiation reaching the surface. In turn, the modifications to radiation affect how turbulence near the surface is generated and its magnitude. The net result of these energy fluxes determines the warming and cooling processes at the surface, with direct implications on the development of local weather systems. From the observations in northern Wisconsin, an apparent partition in energy fluxes between two commonly observed lower atmosphere cloud types is found. A seasonal pattern in the occurrence of these cloud types was observed. Because of these cloud‐specific preferences, turbulence generated near the surface was larger during the first half of the 3‐month field campaign. Enhanced surface fluxes supported a deeper boundary layer for the shallow cumulus cloud conditions compared to overcast conditions. These fluxes were even larger than periods when skies were clear; however clear sky conditions were most frequent during the morning when surface energy fluxes were generally increasing with time during this development stage of the convective mixed layer. Turbulent fluxes associated with evaporation at the surface dominated over dry fluxes, regardless of the overhead sky conditions. These findings represent important differences to heavily study climatological regions where grasslands make up the primary surface characteristics. Key Points: Detailed surface energy fluxes and boundary layer structure responses to three boundary layer sky conditions are examined: low stratiform, low cumulus, clearTurbulent and radiative flux relationships were separable by cloud regime; latent fluxes dominated over sensible fluxes by a factor of 3 (low Bowen ratios dominated)Boundary layers were deeper during low cumulus compared to clear sky periods; surface‐atmosphere interactions are complex over the heterogenous forest landscape [ABSTRACT FROM AUTHOR]

The surface energy budget over the Antarctic sea ice from 8 April 2016 through 26 November 2016 are presented. From April to October, Sensible heat flux (SH) and subsurface conductive heat flux (G) were the heat source of surface while latent heat flux (LE) and net radiation flux (Rn) were the heat sink of surface. Our results showed larger downward SH (due to the warmer air in our site) and upward LE (due to the drier air and higher wind speed in our site) compared with SHEBA data. However, the values of SH in N-ICE2015 campaign, which located at a zone with stronger winds and more advection of heat in the Arctic, were comparable to our results under clear skies. The values of aerodynamic roughness length (z0m) and scalar roughness length for temperature (z0h), being 1.9 × 10−3 m and 3.7 × 10−5 m, were suggested in this study. It is found that snow melting might increase z0m. Our results also indicate that the value of log(z0h/z0m) was related to the stability of stratification. In addition, several representative parameterization schemes for z0h have been tested and a couple of schemes were found to make a better performance.

The surface energy budget over the Qinghai-Tibet Plateau (QTP) and the Arctic significantly influences the climate system with global consequences. The performances of 30 selected Coupled Model Intercomparison Project Phase 6 (CMIP6) models were evaluated based on six sites in the QTP and Arctic. The simulation results for latent heat flux (LE) were more accurate in the QTP, where the correlation coefficient and root mean square error (RMSE) were 0.9 and 30 W m−2, respectively. The results for sensible heat flux (H) were more accurate in the Arctic, the correlation coefficient and RMSE were 0.8 and 24 W m−2, respectively. Furthermore, the multiple models mean results revealed that the surface energy flux had seasonal variation and regional differences over the QTP and the Arctic. In the QTP, H was the lowest in winter, increased in spring, and reached the maximum in summer. However, the transitional changes in spring and autumn were not apparent in the Arctic, mainly due to seasonal net radiation difference between the two places. LE was affected by precipitation and surface soil moisture content. This work is important for understanding land-atmosphere interactions and useful for improving the accuracy of land surface models simulations. [ABSTRACT FROM AUTHOR]

We use in situ environmental measurements by the Mars Science Laboratory (MSL) mission to obtain the surface energy budget (SEB) across Curiosity's traverse during the first 2500 sols of the mission. This includes values of the downwelling shortwave solar radiation, the upwelling solar radiation reflected by the surface, the downwelling longwave radiation from the atmosphere, the upwelling longwave radiation emitted by the surface, the sensible heat flux associated with turbulent motions, and the latent heat flux associated with water phase changes. We then analyze their temporal variation on different timescales and relate this to the mechanisms causing these variations. Through its Rover Environmental Monitoring Station, MSL allows for a more accurate determination of the SEB than its predecessors on Mars. Moreover, the unprecedented duration, cadence, and frequency of MSL environmental observations allow for analyses of the SEB from diurnal to interannual timescales. The results presented in this article can be used to evaluate the consistency with predictions from atmospheric numerical models, to validate aerosol radiative properties under a range of dust conditions, to understand the energy available for solar‐powered missions, and to enable comparisons with measurements of the SEB by the Perseverance rover at Jezero crater. Plain Language Summary: The primary energy input at the Martian surface is the solar radiation, which depends on the time of the day and season, geographical location (latitude and altitude), and atmospheric dust and gas abundances. Another energy input is the thermal atmospheric forcing, which depends on the vertical distribution of dust and water ice aerosols as well as CO2 and H2O molecules. Together with the reflected solar radiation and the thermal radiation emitted by the surface, these four terms make up the net radiative forcing of the surface. In response to it, energy outputs as turbulent motions and water phase changes emerge to cool down/warm up the ground. The remaining energy is available to control the thermal environment in the surface and shallow subsurface through conduction into the soil. By using first‐of‐their‐kind measurements from the Mars Science Laboratory mission, we calculate the energy inputs and outputs across Curiosity's traverse over the first 2500 Martian days of the mission. We then analyze their temporal variations and relate this to the mechanisms causing such variations. An accurate determination of the surface energy budget is key to preparing for the human exploration of Mars because it contributes to improvements in the predictive capabilities of numerical models. Key Points: We have calculated each term of the surface energy budget during the first 2500 sols of the Mars Science Laboratory missionWe have analyzed the variation of each term from diurnal to interannual timescales in relation to the mechanisms causing the variationsOur results are important in preparation for the human exploration of Mars to evaluate the consistency with predictions from models [ABSTRACT FROM AUTHOR]

• The increase in withered grass stems (WGS) area over the Tibetan Plateau reduces the winter snow depth and snow cover fraction by up to 6 mm and 3 %, respectively. • The increase in WGS area results in a reduction in surface albedo, causing an increase in net radiation absorption by up to 1.6 W/m2 and a rise in ground temperature by up to 0.1 °C. • Ground temperature rise caused by the increment of WGS area promotes snow decline, such negative impacts seem more obvious with heavier snow cover. Along with climate change, the coverage of short vegetation, such as alpine grass over the Tibetan Plateau (TP), has significantly increased in the past decades. However, the changes in non-growing season alpine grass—withered grass stems (WGS), as well as their impact on snow cover and surface energy budget, still remain unclear. In this study, we derived vegetation stem area index (L s) data by using GLASS's leaf area index (LAI) as a way to analyze the impacts of WGS on snow depth, snow cover fraction, surface temperature and surface albedo in winter (December-January-February) over the TP during the period 1982–2018, and numerical experiments were conducted by the Community Land Model version 5.0 (CLM5.0) to investigate physical mechanism behind impacts of WGS. The results reveal that an increment in WGS coverage significantly increases net radiation at the surface, as well as the net radiation arrived at the ground due to the enhancing downward longwave radiation to the ground from the WGS, raising the ground temperature by up to 0.1 °C in winter. On average, ground warming reduces snow depth (up to about 6 mm) and snow cover fraction (up to about 3 %). This negative impact of WGS on snow cover seems more obvious in areas with heavier snow cover. Overall, this study highlights the feedback of changes in non-growing season vegetation cover to climate change in cold regions. [ABSTRACT FROM AUTHOR]

Surface heat fluxes from four atmospheric reanalyses in the Southern Ocean are evaluated using air–sea measurements obtained from the Aurora Australis during off-winter seasons in 2010–12. The icebreaker tracked between Hobart, Tasmania (ca. 42°S), and the Antarctic continent, providing in situ benchmarks for the surface energy budget change in the Subantarctic Southern Ocean (58–42°S) and the eastern Antarctic marginal ice zone (MIZ, 68–58°S). We find that the reanalyses show a high-level agreement among themselves, but this agreement reflects a universal bias, not a “truth.” Downward shortwave radiation (SW↓) is overestimated (warm biased) and downward longwave radiation (LW↓) is underestimated (cold biased), an indication that the cloud amount in all models is too low. The ocean surface in both regimes shows a heat gain from the atmosphere when averaged over the seven months (October–April). However, the ocean heat gain in reanalyses is overestimated by 10–36 W m−2 (80–220%) in the MIZ but underestimated by 6–20 W m−2 (7–25%) in the Subantarctic. The biases in SW↓ and LW↓ cancel out each other in the MIZ, causing the surface heat budget to be dictated by the underestimation bias in sensible heat loss. These reanalyses biases affect the surface energy budget in the Southern Ocean by meaningfully affecting the timing of the seasonal transition from net heat gain to net heat loss at the surface and the relative strength of SW↓ at different regimes in summer, when the length-of-day effect can lead to increased SW↓ at high latitudes.

Aerosols can enhance terrestrial productivity through increased absorption of solar radiation by the shaded portion of the plant canopy—the diffuse radiation fertilization effect. Although this process can, in principle, alter surface evaporation due to the coupling between plant water loss and carbon uptake, with the potential to change the surface temperature, aerosol‐climate interactions have been traditionally viewed in light of the radiative effects within the atmosphere. Here, we develop a modeling framework that combines global atmosphere and land model simulations with a conceptual diagnostic tool to investigate these interactions from a surface energy budget perspective. Aerosols increase the terrestrial evaporative fraction, or the portion of net incoming energy consumed by evaporation, by over 4% globally and as much as ∼40% regionally. The main mechanism for this is the increase in energy allocation from sensible to latent heat due to global dimming (reduction in global shortwave radiation) and slightly augmented by diffuse radiation fertilization. In regions with moderately dense vegetation (leaf area index >2), the local surface cooling response to aerosols is dominated by this evaporative pathway, not the reduction in incident radiation. Diffuse radiation fertilization alone has a stronger impact on gross primary productivity (+2.18 Pg C y−1 or +1.8%) than on land evaporation (+0.18 W m−2 or +0.48%) and surface temperature (−0.01 K). Our results suggest that it is important for land surface models to distinguish between quantity (change in total magnitude) and quality (change in diffuse fraction) of radiative forcing for properly simulating surface climate. Plain Language Summary: Atmospheric particles or aerosols are known to enhance plant growth by increasing photosynthesis in leaves that are normally shaded from direct sunlight, a phenomenon known as the diffuse radiation fertilization effect. Since photosynthesis and water vapor released from plants are linked, this would imply that there is more evaporative cooling at the surface under polluted skies, a mechanism of aerosol‐induced cooling that has not been explicitly considered in past studies. In the present study, we test this hypothesis on a global scale by combining a modeling framework with an offline energy balance method. We show that the surface cooling due to the evaporative pathway is stronger than due to the radiative effect of aerosols for moderately dense vegetation. Traditionally, aerosol‐climate interactions are viewed in light of their radiation impacts on the atmospheric energy budget. Our study provides a new, surface energy budget perspective on these interactions and highlight the importance of differentiating between the quantity and quality of radiative forcing at the Earth's surface when examining the impact of aerosols on the surface climate. Key Points: A modeling framework from the terrestrial surface energy budget perspective is used to investigate aerosol‐climate interactionsAerosols enhance primary productivity and reduce terrestrial Bowen ratio, causing evaporative cooling over vegetated surfacesDiffuse radiation fertilization effect is important for primary productivity while global dimming controls the evaporative cooling [ABSTRACT FROM AUTHOR]

Drylands are an important component of Earth's carbon, water, and energy budgets. Changes in hydroclimatic conditions can significantly alter land surface fluxes in these ecosystems. In regions with groundwater‐river water exchange, land surface fluxes are strongly modulated by groundwater table fluctuations in response to river stage variations; however, interactions between fluxes and groundwater remain poorly understood in drylands. Here, we use eddy covariance data collected in paired upland and riparian semiarid ecosystems (AmeriFlux sites US‐Hn1 and US‐Hn2) during 4 years with contrasting river flow conditions to examine interactions among river stage, water table dynamics, meteorological drivers, and ecosystem fluxes. Elevated groundwater availability resulting from groundwater‐surface water exchange at the riparian site enhanced the latent heat flux (LE, the energy form of evapotranspiration), which was sustained longer in the growing season. Interannual variation of dry season LE was small at the upland site, while at the riparian site contrasting river flow conditions resulted in large interannual variability in LE, with June LE of high‐flow years being 2.3 times that of low‐flow years. The 4‐year mean summer LE at the riparian site was 2.1 times larger than that at the upland site. Carbon uptake (NEP) and LE were well correlated at the upland site at the monthly and annual timescales, but at the riparian site enhanced LE due to shallow water table depth did not correspond to enhanced NEP. Our results demonstrate that enhanced groundwater availability modulated by river stage is a critical driver of land surface fluxes in semiarid riparian ecosystems. Key Points: In an upland ecosystem without groundwater access, interannual variability in evapotranspiration was primarily driven by precipitationGroundwater‐river water exchange enhances interannual variability and regulates dynamics of evapotranspiration in the riparian ecosystemHigh river stage and shallow groundwater table led to sustained large evapotranspiration over drought summers in the riparian ecosystem [ABSTRACT FROM AUTHOR]

An understanding of the surface albedo of high latitudes is crucial for climate change studies. MODIS albedo retrievals flagged as high-quality compare well with in situ Greenland Climate Network (GC-Net) measurements but cover too small an area to fully characterize Greenland's albedo in nonsummer months. In contrast, poor quality MODIS retrievals provide adequate spatiotemporal coverage, but are not recommended for use at large solar zenith angles (SZAs) where they have a systematic low bias. We introduce an empirical adjustment to the poor quality data based on high-quality reference albedos and constrained by GC-Net data and theory, and use the adjusted data to improve estimates and fill in gaps of the year-round, Greenland-wide, albedo and surface energy budget. For observations made with SZAs between 55° and 75°, the mean differences (MODIS minus GC-Net) between our adjusted MODIS albedo and GC-Net measurements are −0.02 and −0.03 at Saddle and Summit, respectively, compared to −0.05 and −0.08 between the unadjusted MODIS albedo and GC-Net measurements. The adjusted MODIS snow albedos are usually between 0.75 and 0.87 over dry snow when SZA is larger than 55°, and they reduce unrealistic seasonal and meridional trends associated with MODIS retrievals at large SZA, defined as SZA > 55° and 70°, respectively, for low- and high-quality retrievals. The impact of the adjusted albedo on the surface energy budget, relative to the unadjusted albedo from all MODIS data, is smallest (−0.7 ± 0.1W/m2) in June, and largest (−6.2 ± 0.9 W/m2) in September for the black-sky albedo (BSA). The mean annual absorbed solar radiation (ASR) reduction by the adjusted MODIS albedo in Greenland from 2003 to 2005 is 3.1 ± 0.2 and 4.3 ± 0.2 W/m2 for BSA and white-sky albedo (WSA), respectively, about 8.0 ± 0.5% and 10.8 ± 0.4% of ASR based on the raw BSA and WSA. The ASR reduction by the adjusted blue-sky (actual) albedo is between 2.9 and 4.5 W/m2, enough to annually melt 27.1 to 41.7 cm snow water equivalent (SWE), or to sublimate 3.2 to 4.9 cm SWE. The ASR difference between the adjusted MODIS BSA and CERES albedo in March from 2003 to 2005 is only −0.1 ± 0.9 W/m2, much less than the difference (4.9 ± 1.4 W/m2) between the unadjusted MODIS BSA and CERES. The albedo adjustments exceed the likely direct anthropogenic radiative forcing experienced by Greenland due to greenhouse gases or aerosols. The proposed adjustment preserves most of the zonal and meridional structure of raw MODIS albedo, and extends its usefulness as a cryospheric climate record in times and regions of Greenland with large SZA.

Warm and dry föhn winds on the Antarctic Peninsula (AP) cause surface melt that can destabilize vulnerable ice shelves. Topographic funneling of these downslope winds through mountain passes and canyons can produce localized wind‐induced melt that is difficult to quantify without direct measurements. Our Föhn Detection Algorithm (FöhnDA) identifies the surface föhn signature that causes melt from measurement by 12 Automatic Weather Stations on the AP, that train a machine learning model to detect föhn in 5 km Regional Atmospheric Climate Model 2 (RACMO2.3p2) simulations and in the ERA5 reanalysis model. We estimate the fraction of AP surface melt attributed to föhn and possibly katabatic winds and identify the drivers of melt, temporal variability, and long‐term trends and evolution from 1979–2018. We find that föhn wind‐induced melt accounts for 3.1% of the total melt on the AP and can be as high at 18% close to the mountains where the winds funnel through mountain canyons. Föhn‐induced surface melt does not significantly increase from 1979–2018, despite a warmer atmosphere and more positive Southern Annular Mode. However, a significant increase (+0.1 Gt y‐1) and subsequent decrease/stabilization occur in 1979–1998 and 1999–2018, consistent with the AP warming and cooling trends during the same time periods. Föhn occurrence, more than föhn strength, drives the annual variability in föhn‐induced melt. Long‐term föhn‐induced melt trends and evolution are attributable to seasonal changes in föhn occurrence, with increased occurrence in summer, and decreased occurrence in fall, winter, and early spring over the past 20 years. Plain Language Summary: Surface melt on the glaciers and floating ice shelves of the Antarctic Peninsula can contribute to sea‐level rise via run‐off to the ocean and by ice‐shelf destabilization and reduced buttressing against glacier flow to the ocean. Surface melt on the Antarctic Peninsula has traditionally been attributed to sunlight melting snow although more recent studies demonstrate significant contributions in all seasons from warm, downslope winds called föhn winds. It is important to understand where these winds cause melt, when they cause melt, how much melt, and are they changing through time? We use weather stations on the Antarctic Peninsula, model data, and Machine‐Learning techniques to characterize these warm winds. We find they occur in every season, including winter when there is no sunlight to melt the snow surface. Föhn wind‐induced melt accounts for 3.1% of the total melt on the Antarctic Peninsula and can be as high as 18% close to the mountains where the winds funnel through mountain canyons. Overall there has not been a significant increase in melt caused by föhn winds in the past 40 years, although the seasonality of the winds and associated melt are changing. Key Points: We use machine learning, trained with surface observations to identify föhn winds on the Antarctic Peninsula and their impact on meltFöhn‐induced melt trends mirror surface temperature trends with increased melt from 1979 to 1998 and stable/decreased melt from 1999 to 2018Föhn occurrence, or the number of hours föhn melt occurs, drives annual föhn‐induced melt variability and evolution [ABSTRACT FROM AUTHOR]

Forecasts with the European Centre for Medium-Range Weather Forecasts’ numerical weather prediction model are evaluated using an extensive set of observations from the Arctic Ocean 2018 expedition on the Swedish icebreaker Oden. The atmospheric model (Cy45r1) is similar to that used for the ERA5 reanalysis (Cy41r2). The evaluation covers 1 month,with the icebreaker moored to drifting sea ice near the North Pole; a total of 125 forecasts issued four times per day were used. Standard surface observations and 6-hourly soundings were assimilated to ensure that the initial model error is small. Model errors can be divided into two groups. First, variables related to dynamics feature errors that grow with forecast length; error spread also grows with time. Initial errors are small, facilitating a robust evaluation of the second group; thermodynamic variables. These feature fast error growth for 6–12 hr, after which errors saturates; error spread is roughly constant. Both surface and near-surface air temperatures are too warm in the model. During the summer both are typically above zero in spite of the ongoing melt; however, the warm bias increases as the surface freezes. The warm bias is due to a too warm atmosphere; errors in surface sensible heat flux transfer additional heat from the atmosphere to the surface. The lower troposphere temperature error has a distinct vertical structure: a substantial warm bias in the lowest few 100m and a large cold bias around 1 km; this structure features a significant diurnal cycle and is tightly coupled to errors in themodelled clouds. Clouds appear too often and in a too deep layer of the lower atmosphere; the lowest clouds essentially never break up. The largest error in cloud presence is aligned with the largest cold bias at around 1 km. [ABSTRACT FROM AUTHOR]

Hurricane Maria drastically altered the landscape across the island of Puerto Rico. This article investigates modifications to surface‐atmospheric interactions due to Hurricane Maria induced land damage and the associated impacts on local convective dynamics. Herein, we employed LANDSAT‐8 image mosaics to quantify the hurricane induced land modification. Results of the analysis indicate that the island suffered significant forest damage—much of which registered as a 28.35% increase in barren land and a 10.85% increase in pasture. Smaller changes included a decrease in cultivated agricultural land cover by 0.76%, along with wetland and water increases of 0.62% and 0.25%, respectively. Pre and postMaria land classifications were then assimilated into the Regional Atmospheric Modeling System cloud resolving model for the simulation of the June 23 to July 2, 2018 period under two land conditions. Results of the numerical experiments indicate that surface to atmosphere interactions were significantly modified when the land cover was altered, and that the highest deviations between pre and postMaria convection occurred over elevated areas with extreme hurricane induced land changes, such as the Cordillera Central mountain range and the El Yunque rainforest. Key Points: Hurricane Maria significantly altered the landscape of Puerto RicoHurricane induced land modification altered surface‐atmosphere interactionsThe highest deviations between pre and postMaria land cover convection occur over the western mountains, and El Yunque [ABSTRACT FROM AUTHOR]

The presence of clouds in the Arctic regulates the surface energy budget (SEB) over the sea‐ice surface and the ice‐free ocean. Following several previous field campaigns, the cloud‐radiation relationship, including cloud vertical structure and phase, has been elucidated; however, modeling of this relationship has matured slowly. In recognition of the recent decline in the Arctic sea‐ice extent, representation of the cloud system in numerical models should consider the effects of areas covered by sea ice and ice‐free areas. Using an in situ stationary meteorological observation data set obtained over the ice‐free Arctic Ocean by the Japanese Research Vessel Mirai (September 2014), coordinated evaluation of six regional climate models (RCMs) with nine model runs was performed by focusing on clouds and the SEB. The most remarkable findings were as follows: (1) reduced occurrence of unstable stratification with low‐level cloud water in all models in comparison to the observations, (2) significant differences in cloud water representations between single‐ and double‐moment cloud schemes, (3) extensive differences in partitioning of hydrometeors including solid/liquid precipitation, and (4) pronounced lower‐tropospheric air temperature biases. These issues are considered as the main sources of SEB uncertainty over ice‐free areas of the Arctic Ocean. The results from a coupled RCM imply that the SEB is constrained by both the atmosphere and the ocean (and sea ice) with considerable feedback. Coordinated improvement of both stand‐alone atmospheric and coupled RCMs would promote a more comprehensive and improved understanding of the Arctic air‐ice‐sea coupled system. Key Points: Discrepancies remain in surface energy budget (SEB) and cloud properties despite constrained boundary conditionsModels underestimate occurrence of unstable stratification with low‐level water cloudsBiases in hydrometeor partitioning essentially contribute to limited skill in SEB simulation [ABSTRACT FROM AUTHOR]

We apply well-established flux–gradient relationships to deduce the aerodynamic and radiative properties of a winter wheat crop, using a neglected 1971 dataset (hourly averages), only recently resurrected as part of a historical review of precision CO2 measurements in Australia (Pearman et al. in Hist Rec Aust Sci 28:111–125, 2017). The aerodynamic roughness length (seasonal variation between 0.07 and 0.14 of the mean crop height) and broadband albedo (seasonal variation between 0.13 and 0.23) are consistent with values published in the literature over the past 50 years. Net radiation at night is found to agree with the net longwave flux only when the dry-bulb temperature exceeds 10 °C, probably the result of dewfall on one or both of the two instruments. During the day, the sum of the four individual radiative flux components (upwards and downwards shortwave and longwave)—the composite net radiation—exceeds the directly measured net radiation, from near zero at sunrise to approximately 100 W m−2 at maximum net radiation ≈ 600 W m−2, viz. an underestimate in the directly measured net radiation of close to 15%. Again, this is in line with instrument comparisons made in the USA and Europe 15–25 years ago. A novel approach is used in the analysis of terms in the surface energy budget, viz., normalization of all terms by the downwelling shortwave flux. Normalization reveals, (1) near-normal frequency distributions of both the total turbulent heat flux (sensible plus latent) and the implied total storage (the residual); (2) significant diurnal variations in the total turbulent heat flux, whose standard deviations of individual values about any hourly mean during daytime are reduced significantly on those for either the sensible or latent heat flux; (3) an implied storage term with a well-defined diurnal variation, but with an overall mean value of 1% of the shortwave input. Overall, with the above results in mind, the computed momentum and heat fluxes (and also the CO2 flux) during the daytime, at small to moderate gradient Richardson numbers, provide support for the profile approach when eddy-correlation fluxes are unavailable. Even so, possible errors due to, (1) uncertainties in the zero-plane displacement, and (2) influences of the roughness sublayer, must be borne in mind. [ABSTRACT FROM AUTHOR]

This study examined the historical (1980–2005) austral summer precipitation in Tropical South America (SA) simulated by five Earth System Models (ESM) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). All simulations show a band of maximum precipitation eastward of the observed one and without typical NW‐SE orientation. This displacement suggests models have trouble in reproducing the South Atlantic Convergence Zone (SACZ). Due to this and additional model problems in simulating the Atlantic Intertropical Convergence Zone (ITCZ), all models exhibit negative precipitation biases at the extreme northern SA, including Guianas, Suriname, and north of Brazil and positive precipitation biases at part of northeastern Brazil. For extreme northern SA, models, in general, underestimate intense precipitation and overestimate weak rainfall. Analysis of the moisture flux divergence over the northern coast of SA in models suggested that the precipitation bias could primarily stem from model misrepresentations of moisture availability for convection. Further analyses indicate that the moisture flux biases are, in turn, tied to a negative sea surface temperature (SST) bias in the tropical North Atlantic, inducing stronger northeasterly trade winds. Thus, more intense moisture flux goes to the inner continent. Consequently, an anomalous divergence of moisture flux and less precipitation occur near the coast. Despite some differences in energy budget and cloudiness, models results for wind, precipitation, SST, and latent heat flux suggest problems at WES feedback. In the GFDL‐ESM and MIROC‐ESM models, the negative SST bias was also partly associated with a lower incident shortwave (SW) radiation over the tropical North Atlantic. This SW bias was tied to a positive bias of cloud cover over tropical North Atlantic, at least in the GFDL‐ESM. [ABSTRACT FROM AUTHOR]

As a key parameter for indicating the fraction of surface-reflected solar incident radiation, land surface albedo plays an important role in the Earth's surface energy budget (SEB). Since the Sanjiang Plain has been severely affected by human activities (e.g., reclamation and shrinking of wetlands), it is important to assess the spatiotemporal variations of surface albedo in this region using a long-term remote sensing dataset. In order to investigate the surface albedo climatology, trends, and mechanisms of change, we evaluated the surface albedo variations in the Sanjiang Plain, China from 1982 to 2015 using the Global LAnd Surface Satellite (GLASS) broadband surface albedo product. The results showed that: 1) an increasing annual trend (+0.000 58/yr) of surface albedo was discovered in the Sanjiang Plain based on the GLASS albedo dataset, with a much stronger increasing trend (+0.001 26/yr) occurring during the winter. Most of the increasing trends occurred over the cultivated land, unused land, and land use conversion types located in the northeastern Sanjiang Plain. 2) The increasing trend of land surface albedo in Sanjiang Plain can be largely explained by the changes of both snow cover extent and land use. The surface albedo in winter is highly correlated with the snow cover extent in the Sanjiang Plain, and the increasing trend of surface albedo can be further enhanced by the land use changes. [ABSTRACT FROM AUTHOR]

Recent ice shelf retreat on the east coast of the Antarctic Peninsula has been principally attributed to atmospherically driven melt. However, previous studies on the largest of these ice shelves—Larsen C—have struggled to reconcile atmospheric forcing with observed melt. This study provides the first comprehensive quantification and explanation of the atmospheric drivers of melt across Larsen C, using 31‐months' worth of observations from Cabinet Inlet, a 6‐month, high‐resolution atmospheric model simulation and a novel approach to ascertain the surface energy budget (SEB) regime. The dominant meteorological controls on melt are shown to be the occurrence, strength, and warmth of mountain winds called foehn. At Cabinet Inlet, foehn occurs 15% of the time and causes 45% of melt. The primary effect of foehn on the SEB is elevated turbulent heat fluxes. Under typical, warm foehn conditions, this means elevated surface heating and melting, the intensity of which increases as foehn wind speed increases. Less commonly—due to cooler‐than‐normal foehn winds and/or radiatively warmed ice—the relationship between wind speed and net surface heat flux reverses. This explains the seemingly contradictory results of previous studies. In the model, spatial variability in cumulative melt across Larsen C is largely explained by foehn, with melt maxima in inlets reflecting maxima in foehn wind strength. However, most accumulated melt (58%) occurs due to solar radiation in the absence of foehn. A broad north‐south gradient in melt is explained by the combined influence of foehn and non‐foehn conditions. Plain Language Summary: The recent rapid retreat and collapse of ice shelves on the east coast of the Antarctic Peninsula is known to be primarily a result of enhanced surface melt due to climate warming and changing atmospheric circulation patterns. However, previous studies have struggled to reconcile observed melt patterns with meteorological conditions. Here we provide the first quantification and explanation of the atmospheric drivers of melt across Larsen C, the largest ice shelf on the Antarctic Peninsula. We find that variability in melt across Larsen C is primarily governed by mountain winds known as foehn, with melt maxima in ice shelf inlets coinciding with the strongest foehn winds. Foehn air is usually much warmer than the ice below, resulting in elevated heating and melting of the ice, the intensity of which increases with increasing wind speed. However, in rare cases where the foehn air is not significantly warmer than the ice, the relationship between melt and foehn wind speed reverses, which explains the seemingly contradictory results of previous studies. While foehn causes the highest melt rates, non‐foehn‐driven melt is more common and, via summertime solar heating, is responsible for most of the accumulation of melt across the ice shelf as a whole. Key Points: Spatial variability and maxima in Larsen C melt are chiefly due to foehn‐driven sensible heating, though most melt is due to solar radiationLow static stability reverses the usual positive correlation between melt and foehn wind speed, explaining conflicting results in previous studiesA high‐resolution atmospheric model capably reproduces melt patterns across Larsen C but has notable biases in the surface radiative fluxes [ABSTRACT FROM AUTHOR]

The surface energy budget over the Antarctic sea ice from 8 April 2016 through 26 November 2016 are presented. From April to October, Sensible heat flux (SH) and subsurface conductive heat flux (G) were the heat source of surface while latent heat flux (LE) and net radiation flux (Rn) were the heat sink of surface. Our results showed larger downward SH (due to the warmer air in our site) and upward LE (due to the drier air and higher wind speed in our site) compared with SHEBA data. However, the values of SH in N-ICE2015 campaign, which located at a zone with stronger winds and more advection of heat in the Arctic, were comparable to our results under clear skies. The values of aerodynamic roughness length (z0m) and scalar roughness length for temperature (z0h), being 1.9 × 10−3 m and 3.7 × 10−5 m, were suggested in this study. It is found that snow melting might increase z0m. Our results also indicate that the value of log(z0h/z0m) was related to the stability of stratification. In addition, several representative parameterization schemes for z0h have been tested and a couple of schemes were found to make a better performance. [ABSTRACT FROM AUTHOR]

Remote sensing data are abundant, whereas surface in situ verification of atmospheric conditions is rare on Mars. Earth-based analogs could help gain an understanding of soil and atmospheric processes on Mars and refine existing models. In this work, we evaluate the applicability of the Weather Research and Forecasting (WRF) model against measurements from the Mars analog High Andes-Atacama Desert. Validation focuses on the surface conditions and on the surface energy budget. Measurements show that the average daily net radiation, global radiation, and latent heat flux amount to 131, 273, and about 10 W/m2, respectively, indicating extremely dry atmospheric conditions. Dynamically, the effect of topography is also well simulated. One of the main modeling problems is the inaccurate initial soil and surface conditions in the area. Correction of soil moisture based on in situ and satellite soil moisture measurements, as well as the removal of snow coverage, reduced the surface skin temperature root mean square error from 9.8°C to 4.3°C. The model, however, has shortcomings when soil condition modeling is considered. Sensible heat flux estimations are on par with the measurements (daily maxima around 500 W/m2), but surface soil heat flux is greatly overestimated (by 150–500 W/m2). Soil temperature and soil moisture diurnal variations are inconsistent with the measurements, partially due to the lack of water vapor representation in soil calculations. [ABSTRACT FROM AUTHOR]

Two-wavelength scintillometer systems can provide much needed measurements of area-averaged sensible and latent heat fluxes. However, these devices rarely have been deployed on canopy-covered complex terrain, and never in the circumpolar boreal biome, where large-scale fluxes are essential to hydroclimate modellers. We present a comparison of fluxes measured above a boreal-forested valley with a two-wavelength scintillometer and an eddy covariance system. Instruments were deployed in late summer 2017, and 19 days of data were retained for the analysis. The scintillometer path was 1347-m long and projected across the valley between 5 and 100 m above the ground, with an effective height of ≈ 88 m. The limitations of deriving surface fluxes using scintillometry in complex terrain are discussed, and the effects of atmospheric conditions on the flux comparison are quantified. Fluxes are calculated with the scintillometer only, and using a number of atmospheric variables from the eddy-covariance system; impacts of these calculation methods on the correlation between instrumental systems are assessed. Despite a weak agreement of structure parameters between instruments, the comparison of scintillometer and eddy-covariance fluxes yields good correlation ( R 2 up to 0.82). Scintillometry correlates best with eddy-covariance data when the atmospheric surface-layer top is above the scintillometer effective height, but R 2 only drops slightly otherwise (average decrease of 0.11). The validity of scintillometer fluxes appears dubious during night-time and stable periods. We show that area-averaged flux measurements using two-wavelength scintillometers are possible in hilly forests, but more studies are needed to pinpoint the best methodological framework. [ABSTRACT FROM AUTHOR]

• Research on land-atmosphere interactions covers a large breadth of disciplines. • Silos between research areas are reinforced by increasingly complex approaches. • This issue integrates research across the soil-vegetation-atmosphere continuum. • New funding opportunities are needed to support this trans-disciplinary work. • Coordinated networks are expensive but will facilitate transformational knowledge. To help bridge science topics related to land-atmosphere interactions, we organized a virtual special issue in this journal (Agricultural and Forest Meteorology [AFM]) entitled, "Land-Atmosphere Interactions: Integrating Surface Flux with Boundary Layer Measurements." The motivation for the special issue was driven by existing disciplinary barriers between research areas that all address land-atmosphere interactions. In particular, it addressed research silos between those who study features of the land surface, surface fluxes (including water, energy, and trace gases), atmospheric boundary layer growth and thermodynamics, and atmospheric composition and aerosols. The special issue sought to bring these communities together to integrate multiple observations across the soil-vegetation-atmosphere continuum with the aim of 1) improving broader understanding of land-atmosphere interactions, feedbacks, and coupling, 2) fostering new collaborations between atmospheric and surface flux scientists, and 3) identifying new paths for integrative research. Here, we provide an overview and synthesis of the special issue. [ABSTRACT FROM AUTHOR]