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Massive irrigation across eastern China (EC) could reduce extreme heat by altering energy and water budgets. However, the irrigation effect on increasing humidity has often been missed, especially in humid regions, leaving its effect and mechanism on extreme humid heat (EHH) poorly characterized. We analyzed assemblies of observations and performed regional simulations with more detailed irrigation scheme to explore the irrigation impacts and potential mechanisms on EHH. We find that irrigation in EC, despite having a cooling effect of about 0.2–0.6° ${}^{\circ}$C, leads to an increase of about 0.4–0.8° ${}^{\circ}$C in EHH, with a more intense impact on the Middle‐Lower Yangtze Plain (MLYP) by 0.9° ${}^{\circ}$C. Cooling effect induced by increased latent heat fluxes through irrigation contributes to air deposition, which lowers boundary layer height, raises near‐surface moist enthalpy, and ultimately exacerbates the EHH. Results mechanistically emphasized irrigation impacts on EHH and highlighted the necessity of improving irrigation modeling reality. Plain Language Summary: Eastern China (EC) distributes the North China Plain (NCP, semi‐arid climate) and MLYP (humid climate), the first and third largest irrigated areas of China. Large‐scale irrigation mitigates extreme dry heat (EDH) while moistening surface air, which is more dangerous to humans with EDH and high humidity combined. Recently, the advantages of irrigation on summer EDH have been widely explored, whereas the influence of irrigation on compound extreme humid heat (EHH) remains unclear. Hence, we studied the impacts of irrigation on EDH and EHH in EC and its potential driving mechanisms based on in situ observations and simulations of WRF‐Noah model coupled with a subgrid demand‐driven irrigation scheme. The comprehensive analysis supports that although irrigation reduces temperature, it raises the integrated measure of temperature and humidity, exacerbating deadly heat stress. The decline in the height of planetary boundary layer induced by the irrigation cooling effect could have played an important role. We argue that heat wave mitigation measures in MLYP and other regions with dominantly moist climates that ignore the moistening power of irrigation, overestimate irrigation's advantages for EDH but underestimate the risks of tens of millions of outdoor workers in the region experiencing compound EHH. Key Points: Effects of irrigation on summer extreme dry and humid heat stress in eastern China are investigated through observations and simulationsIrrigation decreases summer dry‐bulb temperatures but increases heat index and wet‐bulb temperatures, especially in the Middle‐Lower Yangtze Plain.Reduction in planetary boundary layer height induced by cooling effects of irrigation could contribute to deteriorating humid heat extremes [ABSTRACT FROM AUTHOR]

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Land use and land cover changes (LULCCs) can influence surface temperature through local and nonlocal biophysical processes, which remain inadequately addressed. In this study, we separate the local and nonlocal effects of historical (1850–2014) LULCCs based on model outputs from the Coupled Model Intercomparison Project Phase 6. We also attempt to explore the sources of intermodel differences in the effects of LULCCs. The multimodel mean shows a cooling effect of −0.05°C (with an intermodel range of −0.24–0.06°C) at the global scale due to cropland and pastureland expansion, consisting of dominant nonlocal cooling of −0.06°C (with an intermodel range of −0.26–0.06°C) and slight local warming of 0.01°C (with an intermodel range of −0.01–0.05°C). The modeling results show some clear consistency in the effects of LULCCs despite considerable intermodel uncertainties. The local effects cause warming at low latitudes and cooling in boreal regions via changes in upward shortwave radiation and sensible and latent heat fluxes. The nonlocal effects mainly cause cooling via decreases in downward longwave radiation and increases in upward shortwave radiation. Intermodel differences in the total effects are dominated by those in the nonlocal effects, which are further attributed to divergent changes in downward longwave radiation and sensible heat flux across the models. This study highlights the importance of the nonlocal effects of LULCCs in terms of strength and intermodel uncertainty, with implications for designing land‐based solutions aimed at climate change mitigation. Plain Language Summary: Land use and land cover changes (LULCCs) can alter surface properties and thereby influence surface temperature through land–atmosphere interactions. LULCCs influence the climate not only at the location of LULCCs (local effects) but also elsewhere (nonlocal effects) through atmospheric and oceanic feedbacks. However, the local and nonlocal effects of realistic LULCCs still lack explicit investigation. In this study, we quantify the local and nonlocal effects of historical (1850–2014) LULCCs and their intermodel differences based on a set of simulations from four earth system models. The multimodel mean suggests that historical cropland and pastureland expansion has caused a nonlocal cooling effect of −0.06°C and a local warming effect of 0.01°C, creating a net cooling effect of −0.05°C at the global scale. The local and nonlocal effects of LULCCs can be attributed to changes in surface fluxes and atmospheric feedbacks, whereas the strength and sign vary substantially across the models. Large intermodel differences in the total effects of LULCCs mostly result from those in the nonlocal effects. This study highlights the importance of the nonlocal effects of LULCCs and has implications for developing land‐use strategies aimed at climate change mitigation. Key Points: The local and nonlocal biophysical effects of historical land use and land cover changes (LULCCs) are investigated using CMIP6 modelsThe multimodel mean shows that, overall, historical LULCCs cool the land surface through nonlocal processesThe intermodel divergence in the total effects of historical LULCCs mainly results from low intermodel agreement on the nonlocal effects [ABSTRACT FROM AUTHOR]

Latent and sensible heat flux observations are essential for understanding land–atmosphere interactions. Measurements from the eddy covariance technique are widely used but suffer from systematic energy imbalance problems, partly due to missing large eddies from sub‐mesoscale transport. Because available energy drives the development of large eddies, we propose an available energy based correction method for turbulent flux measurements. We apply our method to 172 flux tower sites and show that we can reduce the energy imbalance from −14.99 to −0.65 W m−2 on average, together with improved consistency between turbulent fluxes and available energy and associated increases in r2 at individual sites and across networks. Our results suggest that our method is conceptually and empirically preferable over the method implemented in the ONEFlux processing. This can contribute to the efforts in understanding and addressing the energy imbalance issue, which is crucial for the evaluation and calibration of land surface models. Plain Language Summary: Eddy covariance measurements are key to understanding the exchange of energy and water between the Earth's surface and the atmosphere, which helps us validate Earth system models that predict how the land interacts with the atmosphere. However, these measurements often show an energy imbalance problem, meaning that the measured turbulent energy does not fully account for all the energy entering the system. For two decades, scientists have been using advanced simulations and multi‐tower measurements to find out why this happens, and have found that the movements of airflow in a horizontal direction play a large role. Taking this knowledge into account, we propose a simple, data‐driven method to make these measurements more accurate. This new approach reduces the error not just at one eddy covariance site, but at multiple sites around the globe, and it's also effective at reflecting the energy changes that occur with daily weather events like rain. Key Points: Observed systematic imbalance of energy flux (∼17%) across the network of eddy covariance sitesA theoretically motivated correction method based on available energy variations is proposedThe available energy correction method has conceptual and empirical advantages compared to the method implemented in the ONEFlux pipeline [ABSTRACT FROM AUTHOR]

In the Energy Exascale Earth System Model (E3SM) Multi-scale Modeling Framework (MMF), where parameterizations of convection and turbulence are replaced by a 2-D cloud-resolving model (CRM), there are multiple options to represent land–atmosphere interactions. Here, we propose three different coupling strategies, namely the (1) coupling of a single land surface model to the global grid (MMF), (2) coupling a single land copy directly to the embedded CRM (SFLX2CRM), and (3) coupling a single copy of land model to each column of the CRM grid (MAML). In the MAML (Multi-Atmosphere Multi-Land) framework, a land model is coupled to CRM at the CRM-grid scale by coupling an individual copy of a land model to each CRM grid. Therefore, we can represent intra-CRM heterogeneity in the land–atmosphere interaction processes. There are 5-year global simulations run using these three coupling strategies, and we find some regional differences but overall small changes with respect to whether a land model is coupled to CRM or a global atmosphere. In MAML, the spatial heterogeneity within CRM induces stronger turbulence, which leads to the changes in soil moisture, surface heat fluxes, and precipitation. However, the differences in the MAML from the other two cases are rather weak, suggesting that the impact of using MAML does not justify the increase in cost. [ABSTRACT FROM AUTHOR]

Realistic initialization of the land surface is important to produce accurate NWP forecasts. Therefore, making use of available observations is essential when estimating the surface state. In this work, sequential land surface data assimilation of soil variables is replaced with an offline cycling method. To obtain the best possible initial state for the lower boundary of the NWP system, the land surface model is rerun between forecasts with an analyzed atmospheric forcing. We found a relative reduction of 2-m temperature root-mean-square errors and mean errors of 6% and 12%, respectively, and 4.5% and 11% for 2-m specific humidity. During a convective event, the system was able to produce useful (fractions skill score greater than the uniform forecast) forecasts [above 30 mm (12 h)−1] down to a 100-km length scale where the reference failed to do so below 200 km. The different precipitation forcing caused differences in soil moisture fields that persisted for several weeks and consequently impacted the surface fluxes of heat and moisture and the forecasts of screen level parameters. The experiments also indicate diurnal- and weather-dependent variations of the forecast errors that give valuable insight on the role of initial land surface conditions and the land–atmosphere interactions in southern Scandinavia. [ABSTRACT FROM AUTHOR]

Land use and land cover (LULC) changes have some implications on land–atmosphere interactions, surface energy budget, and hydrological cycle. The understanding of LULC changes and their interactions with the environment provide better management of agriculture, forests, and water resources. LULC changes are frequently observed in developing countries such as Türkiye and much research has been conducted in this field. However, few studies investigated the countrywide LULC changes and their interactions with energy fluxes and precipitation. In this paper, LULC changes in Türkiye over the last two decades have been evaluated by utilizing an Enhanced Vegetation Index (EVI) derived from the Terra satellite. The latent and sensible heat fluxes were obtained from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis datasets. Precipitation data were acquired from the Tropical Rainfall Measuring Mission (TRMM) satellite. The results showed that EVI has an increasing trend over Türkiye between 2000 and 2021, while climate change–induced desertification, droughts, and forest fires have threatened the vegetative cover in some portions of the country. The latent heat flux has a rising trend due to increasing vegetative cover and irrigated areas. A slight reduction was observed in sensible heat flux, while a sharp increase was witnessed in specific humidity. EVI represented a high positive correlation (R = 0.84) with sensible heat flux and a moderate positive correlation (R = 0.69) with latent heat flux. No significant relation was determined between EVI and precipitation on a monthly basis. [ABSTRACT FROM AUTHOR]

Land–atmosphere interactions are influenced by the earth's complex underlying subsurface, which in turn indirectly affects atmospheric motion and climate change. Human activities are increasingly exerting an influence on desert ecosystems, and artificial green land with clear functional orientation has been established in many desert areas. Consequently, the previously dominant, shifting, sand-covered, underlying surface in these desert regions is gradually transforming. This transformation has significant implications for the characteristics of land–atmosphere interactions, causing them to deviate from their original state. At present, existing studies still have not presented a systematic understanding of this change and have ignored the impact of human activities on land–atmosphere interactions in artificial green land. To address these research gaps, this study specifically targets artificial green land in the Tazhong region of Taklamakan Desert. We carried out observation experiments on land–atmosphere interactions in three different functional units from outside to inside: natural shifting sands, the shelter forest, and the living area. We also analyzed the differences and attribution of land–atmosphere interactions characteristics of different functional units. Compared with the natural shifting sands, the daily average maximum values of wind speed in the shelter forest decreased by 78%, and the daily average maximum air temperature and soil (0 cm) temperature decreased by 2.6 °C and 7 °C, respectively. Additionally, the soil moisture level was significantly increased throughout the green land due to the shelter forest. The surface albedo experienced a decrease, with an annual average of 0.21. Furthermore, the aerodynamic roughness and bulk transport coefficient increased by two orders of magnitude. The daily average maximum values of sensible heat flux and soil heat flux (G05) decreased by 18.7% and 75%, respectively, and the daily average maximum value of latent heat flux increased by 70.3%. This effectively improved the microclimate environment of the green land. The living area was greatly reduced by the shelter forest coverage and influenced by the buildings. Consequently, the environmental improvement was not as large as it was inside the shelter forest. However, it still provided a good shelter for production and living in the desert area. Throughout the year, a total of 4.60 × 105 t water was consumed through evapotranspiration in the artificial green land. The findings of this study have the potential to enhance our comprehension of land–atmosphere interactions in desert regions, thereby offering valuable insights for the establishment and effective management of artificial desert green lands. [ABSTRACT FROM AUTHOR]

Evidence has been provided that land‐cover changes such as deforestation can have an impact on cloudiness and precipitation. However, conflicting results have been obtained at different scales and places, highlighting our poor understanding of the physical processes involved. Here we focus on mesoscale summer cloudiness in a temperate region, as influenced by a large forest massif (the Landes forest in France). Our study is based on an up‐to‐date atmosphere‐surface mesoscale model (Meso‐NH coupled with SURFEX). Based on observational data, we first optimize the model configuration for our purpose, and show that with a 500 m horizontal resolution we can successfully simulate the higher summer cloud cover observed over the forest, compared to its surroundings. Second, we investigate the physical processes leading to cloud formation in a representative case study. Based on a comparative analysis of diagnostics and budgets over forest and non‐forest areas, we find that the larger sensible heat flux over the forest and its higher roughness are the main drivers of cloudiness, enhancing vertical velocity and boundary‐layer mixing. Third, we simulate the impact of the 2009 Klaus storm that led to the loss of about one third of the trees. Considering 15 representative convective summer days, we show that the model simulates well the resulting decrease in summer cloudiness that was reported in a previous study based on satellite observations. As a complementary tool, the mesoscale simulations allow to quantify the impacts of the Klaus storm windthrow on the diurnal cycle of the boundary layer. Plain Language Summary: Previous studies have shown that land‐cover changes such as deforestation can have an impact on cloud cover and precipitation. But the results can be contradictory depending on the region of the world studied. Here, we focus on the temperate Landes forest in southwest France, during the summer period with boundary‐layer clouds. The surface and the atmosphere are represented by two coupled models operating at a 500 m horizontal resolution. We show that, when properly configured, the system can represent boundary‐layer clouds forming over the forest. We then investigate the link between the forest and the generated clouds, highlighting the prominent role of the larger sensible heat flux and roughness over forested areas. These key factors generate vertical motions and mixing that enable cloud formation. Finally, the damage caused by Klaus storm, which destroyed a third of the Landes forest in 2009, is considered. Fifteen summer days with clouds over the Landes are simulated and show that the damage leads to a decrease in cloudiness, in agreement with the results of a previous study based on satellite image analysis. At the regional scale, recent models can thus be used to study and quantify the impact of deforestation on cloudiness. Key Points: A mesoscale model successfully simulates cloud enhancement by a temperate forest and provides realistic cloud fields at hectometric resolutionA comparison of the physical processes over forested and non‐forested areas shows that sensible heat flux and surface roughness are the key drivers of cloudinessThe model helps to understand and quantify the substantial decrease in forest‐induced cloudiness that was observed after storm Klaus [ABSTRACT FROM AUTHOR]

Soil moisture feedbacks that initiate, enhance, or suppress convection initiation and precipitation are important components of regional hydroclimatology. However, soil moisture feedbacks and the processes through which they operate are notoriously challenging to observe and study outside of model environments. In this study, we combine a climatological assessment of event frequency‐based measurements of soil moisture‐precipitation coupling in the central United States with a process‐based analysis of the mechanisms by which wet‐ and dry‐soil feedbacks may operate in the region. We use the Thunderstorm Observation by Radar algorithm to identify the location of convection initiation, circumventing the issue of using precipitation accumulation as a proxy for convection initiation. Results show substantial spatial variability in the climatological sign and strength of soil moisture‐precipitation coupling in the central United States, including regions that exhibit signs of both wet‐ and dry‐soil feedbacks. Within the regions with the strongest feedback signals, we find consistently strong coupling between soil moisture and the partitioning of surface heat flux, and strong coupling between surface heat flux—particularly sensible heat flux—and diurnal change in planetary boundary layer height. In all three regions assessed, the process‐based metrics confirmed the potential of wet‐ and/or dry‐soil feedbacks leading to convection initiation. Plain Language Summary: Soil moisture can affect the occurrence, location, and intensity of precipitation in many global regions. Observations of the drivers of so‐called soil moisture feedbacks are important for constraining models; however, feedbacks are challenging to observe and study outside of model environments. We use a data set of thousands of thunderstorm initiation locations with model‐based soil moisture to measure the sign, strength, and variability in soil moisture feedback to precipitation in the central United States. We denote three regions with strong evidence of both wet‐soil and dry‐soil feedbacks to precipitation. Key Points: The sign and strength of soil moisture‐precipitation coupling was assessed using thousands of convection events points in the central USMultiple regions show signs of both wet and dry soil feedbacks, with strong coupling between soil moisture and surface heat fluxClimatological assessment and process‐based metrics confirmed wet‐ and/or dry‐soil feedbacks leading to convection in the central US [ABSTRACT FROM AUTHOR]

In E3SM-MMF, where parameterizations of convection and turbulence are replaced by 2-D CRM, there are multiple options to represent land-atmosphere interactions. Here, we propose 3 different coupling strategies: 1) coupling of a single land surface model to the global grid (MMF), 2) coupling a single land instance directly to the embedded CRM (SFLX2CRM), and 3) coupling multiple land instances to each column of the CRM grid (MAML). In MAML (Multi-Atmosphere Multi-Land) framework, a land model is coupled to CRM at CRM grid scale by coupling an individual copy of a land model to each CRM grid. Therefore, we can represent intra-CRM heterogeneity in the land-atmosphere interaction processes. 5-year global simulations are run using these 3 coupling strategies and we find that there are little to no difference whether a land model is coupled to CRM or a global atmosphere. In MAML, spatial heterogeneity within CRM induces stronger turbulence, which leads to the changes in soil moisture, surface heat fluxes and precipitation. However, the differences of MAML from the other two cases are rather weak, suggesting that the impact of using MAML does not justify the increase in cost. [ABSTRACT FROM AUTHOR]

This study uses semi-idealized simulations to investigate multiscale processes induced by the heterogeneity of soil moisture observed during the 2016 Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) field campaign. The semi-idealized simulations have realistic land heterogeneity, but large-scale winds are removed. Analysis on isentropic coordinates enables the tracking of circulation that transports energy vertically and facilitates the identification of the primary convective processes induced by realistic land heterogeneity. The isentropes associated with upward motion are found to connect the ground characterized by high latent heat flux to cloud bases directly over the ground with high sensible heat flux, while isentropes associated with downward motion connect precipitation to the ground characterized by high sensible heat fluxes. The mixing of dry, warm parcels ascending from the ground with high sensible heat fluxes and moist parcels from high latent heat regions leads to cloud formation. This new mechanism explains how soil moisture heterogeneity provides the key ingredients such as buoyancy and moisture for shallow cloud formation. We also found that the submesoscale dominates upward energy transport in the boundary layer, while mesoscale circulations contribute to vertical energy transport above the boundary layer. Our novel method better illustrates and elucidates the nature of land atmospheric interactions under irregular and realistic soil moisture patterns. Significance Statement: Models that resolve boundary layer turbulence and clouds have been used extensively to understand processes controlling land–atmosphere interactions, but many of their configurations and computational expense limit the use of variable land properties. This study aims to understand how heterogeneous land properties over multiple spatial scales affect energy redistribution by moist convection. Using a more realistic land representation and isentropic analyses, we found that high sensible heat flux regions are associated with relatively higher vertical velocity near the surface, and the high latent heat flux regions are associated with relatively higher moist energy. The mixing of parcels rising from these two regions results in the formation of shallow clouds. [ABSTRACT FROM AUTHOR]

The processes underlying heavy rainfall in the higher elevations of the Himalayas are still not well known despite their importance. Here, we examine the detailed process causing a heavy rainfall event, observed by our rain gauge network in the Rolwaling valley, eastern Nepal Himalayas, using ERA5 and a regional cloud-resolving numerical simulation. Heavy precipitation (112 mm day−1) was observed on 8 July 2019 at Dongang (2790 m above sea level). Most of the precipitation (81 mm) occurred during 1900–2300 local time (LT). The synoptic-scale environment is characterized by a monsoon low pressure system (LPS) over northeastern India. The LPS lifted moisture upward from the lower troposphere and then horizontally transported it into the eastern Nepal Himalayas within the middle troposphere, increasing the content of the water vapor around Dongang. A mesoscale convective system passed over Dongang around the time of the intense precipitation. The numerical simulation showed that surface heat fluxes prevailed under the middle tropospheric (∼500 hPa) southeasterly flow associated with the LPS around a mountain ridge on the upwind side of Dongang until 1900 LT, enhancing convective instability. Topographic lifting led to the release of the enhanced instability, which triggered the development of a mesoscale precipitation system. The southeasterly flow pushed the precipitation system northward, which then passed over Dongang during 2000–2200 LT, resulting in heavy precipitation. Thus, we conclude that the heavy precipitation came from the multiscale processes such as three-dimensional moisture transport driven by the LPS and the diurnal variation in heat fluxes from the land surface. SIGNIFICANCE STATEMENT: Precipitation in the Himalayas is closely related to the hydrological cycle, floods, and landslide disasters in South Asia. Thus, elucidating the features of precipitation in the Himalayas is important. This study explored multiscale processes leading to a heavy precipitation event that was observed on 8 July 2019 at Dongang in the Rolwaling valley of the eastern Nepal Himalayas. We identified new processes producing heavy precipitation in the Himalayas: the three-dimensional synoptic-scale moisture transport driven by a monsoon low pressure system and the effect of the diurnal variation in heat fluxes from the land surface on the development and movement of a mesoscale precipitation system causing heavy precipitation. These findings broaden our understanding of heavy precipitation in the Himalayas. [ABSTRACT FROM AUTHOR]

The calculation of surface sensible heat (SH) and latent heat (LE) fluxes using the bulk transfer models for complex terrains, tall vegetation regions, and morning and evening transition periods remains a challenging problem in numerical weather and climate models. The maximum entropy production (MEP) model, a new method of calculating surface heat fluxes, is coupled with the Noah land surface model (LSM) in the Weather Research and Forecasting (WRF) model. Surface heat fluxes and meteorological variables including air temperature, relative humidity, soil temperature, and precipitation data at nine intensive observation stations and 453 routine meteorological operational observation stations in the Tibetan Plateau (TP) from 1 June to 31 August 2015 are used to evaluate the coupled model. The results show that the MEP method improves the nonclosure of the surface energy balance in the WRF (with an energy residual from 24.3 to 1.9 W m−2), reducing the overestimations of SH and LE and the underestimation of the surface ground heat flux over the complex terrain of TP (with the bias decreases of 50.6% and 117.1% for SH and LE in turn), especially during the daytime. The improved SH and LE reduce the cold and wet biases in the TP by 29.4% and 51.7%, respectively. The MEP model also reduces the overestimated soil temperature by 63%. Moreover, the overestimated daily precipitation is reduced by 3% over the TP. The successful application of the MEP method demonstrates its advantage over the bulk transfer method, providing a new approach for reducing the overestimation of surface heat fluxes and wet and cold biases in numerical forecast models in complex terrains. Plain Language Summary: In this study, the maximum entropy production (MEP) model, as a new promising method of calculating surface heat fluxes, is coupled to the Weather Research and Forecasting Noah land surface model to replace the original bulk transfer model. The coupled MEP model improves the predictions of surface sensible and latent heat fluxes, air temperature and humidity, precipitation, and soil temperature when compared to observations in the Tibetan Plateau (TP) and the adjacent areas. Overall, the coupled MEP model overcomes some drawbacks of modeling surface heat fluxes with bulk transfer models in numerical forecast models and improves the understanding of land‐atmosphere interactions in the TP and their impacts. Key Points: We use the maximum entropy production (MEP) method instead of the bulk transfer method to calculate surface heat fluxes in the Weather Research and Forecasting (WRF) Noah land surface modelThe MEP method improves the nonclosure of the surface energy budget in the WRF, reducing the overestimation of sensible heat and latent heat over the Tibetan Plateau (TP)The MEP method reduces the cold and wet biases around the TP, leading to an improved understanding of land‐atmosphere interactions [ABSTRACT FROM AUTHOR]

The characteristics of diurnal variation of the surface sensible heat flux (SH) over the Tibetan Plateau (TP) are comprehensively investigated by using the long-term dataset of integrated land–atmosphere interaction observations (2006–2016) on the TP. Results show that the diurnal variation of SH shows obvious seasonal variabilities in terms of amplitude, duration, and peak time. At the Muztagh Ata Westerly Observation and Research Station (MAWORS), the Ngari Desert Observation and Research Station (NADORS), and the Qomolangma Atmospheric and Environmental Observation and Research Station (QOMS), the SH diurnal amplitude is consistently the largest in spring, followed by summer and autumn, and the smallest in winter, with a peak at 15:00. However, for the Southeast Tibet Observation and Research Station (SETORS), the amplitude in winter is rather violent with the peak at 12:00. We find that positive SH at most stations has the longest duration from May to August. Moreover, the peak time fluctuates from month to month, even showing a shift at the QOMS before and after 2015, and the double-peak phenomenon of SH mainly occurs in spring and autumn. Additionally, magnitudes of calculated SH with the conventional heat transfer coefficient (CDH) of 0.004 are about 64% to 100% larger than those of directly observed SH at the QOMS and the Nam Co Monitoring and Research Station (NAMORS). We here additionally recommend a new CDH values of about 2.24 × 10−3 in spring and 2.78 × 10−3 in summer, respectively, to more accurately calculate the TP SH. [ABSTRACT FROM AUTHOR]

Improving our understanding of the energy and water exchanges between the land surface and the lower atmosphere (i.e. land–atmosphere interactions), and how climate change may affect them, is crucial to predict changes in temperature and precipitation extremes. Observations of energy and water fluxes at the land surface are typically retrieved from the eddy covariance method, which presents limitations related to spatial and temporal gaps, and the non-closure of the energy and water balances. Meanwhile, soil moisture (SM) products derived from satellite data have been widely used at regional and global scales, but they are limited to capture only surface soil water content and variations. The combination of remote sensing (RS) data and modelling frameworks is called to be the solution to improve the spatial coverage and vertical resolution of land–atmosphere interactions data, ensuring the energy and water balance closure. Here, we explore the combination of remote sensing and meteorological data with a physical-based modelling framework, the High resOlution Land Atmosphere Parameters from Space (HOLAPS). We used HOLAPS to produce hourly consistent estimates of energy and water fluxes over Europe at 5 km resolution. HOLAPS and other satellite-based evapotranspiration and sensible heat flux products from the literature are evaluated against the water balance method and eddy covariance measurements. HOLAPS SM estimates together with other RS-modelling products are also evaluated against ground-based measurements at the surface and in the root zone. The evaluation of HOLAPS ET estimates show similar performance to the other products with Kling–Gupta efficiency (KGE) ¿ -0.41 in comparison with eddy covariance measurements from FLUXNET in all seasons but in boreal winter. The simulation of H is more uncertain than for ET with KGE values ranging from -2.5 to 0.8 along the products and stations at monthly scales. HOLAPS reaches slightly better results than the rest of ET and H products at daily scales in summer (KGE ¿ 0.3 for ET and KGE ¿ 0.0 for H) and during hot conditions (KGE ¿ 0.2 for ET and KGE ¿-0.2 for H), while the state-of-the-art products show KGE ¿ 0.1 for ET and KGE ¿ -0.41 for H in summer and KGE ¿ -0.1 for ET and KGE ¿ -0.6 for H during hot conditions. All products evaluated here yield a reasonable performance (KGE ¿-0.41 at most sites) in simulating SM at the surface and in the root zone. Our results expose the need for further investigating and improving product performances during extreme conditions. The good performance of HOLAPS together with its inherent advantages (RS data driven, high temporal and spatial resolution, spatial and temporal continuity, soil moisture at different depths and long-term consistent evapotranspiration and sensible heat flux estimates) support its use for agricultural and forest management activities as well as to study land–atmosphere interactions based on Earth Observations. • No SM/ET/H single product outperforms others in all conditions for all variables. • The performance of ET products is worse during hot extremes than in summer. • The HOLAPS product can be used to study land–atmosphere interactions based on EO. • HOLAPS ET provides a satellite-based reference independent from SM satellite products. [ABSTRACT FROM AUTHOR]

• Based on the energy cycle framework introducing a metric to diagnose VPD and heat fluxes coupling during heat waves. • Coupling between VPD and sensible heat fluxes rather than VPD and latent heat fluxes has more significant differences. • Max temperature and land cover types determine VPD coupling direction with latent and sensible heat fluxes, respectively. Vapor pressure deficit (VPD) plays an essential role in determining land-atmospheric interaction by proving a gradient for moisture transport and modulating the biophysical process of plants. Land-atmosphere interaction has been suggested to affect the evolution of heatwave, including its intensification and propagation. However, the role of VPD dynamics in this interaction during heat waves remains unclear. Here, we apply the Pearson correlation coefficient between VPD and energy fluxes to diagnose VPD-induced land-atmospheric interaction over different climate regions and ecosystems, and then evaluate key factors' contributions to this interaction through machine learning. The result shows a nonlinear coupling between VPD and sensible heat fluxes (H) or latent heat fluxes (LE) during heat waves with both strong positive and negative coupling. This coupling exhibits climate and species-dependent. there is a considerable positive coupling between VPD and LE in all climate regions. However, the coupling of VPD and H is more climate-sensitive which shows positive correlations in arid and cold regions and negative coupling in temperate region. Across various vegetation types, LE consistently demonstrates a positive correlation with VPD. In contrast, the coupling between VPD and H tends to be negative in short vegetation whereas positive in forests. In addition, we discovered that the coupling between VPD and LE or H is significantly influenced by the heat wave duration (HWD) at (p < 0.01). Specifically, the land-atmospheric interaction turns decoupling when the HWD extends beyond 8 days. Furthermore, the coupling direction between VPD and energy will change as heat waves evolve. The coupling direction between VPD and LE is considerably affected by maximum temperature. The direction of VPD and H coupling is intimately related to plant functional characteristics. Our research suggests that the VPD impacts should be imperative for accurately simulating land-atmospheric interaction during heat waves. [ABSTRACT FROM AUTHOR]

• Multi-year mean turbulent fluxes accounted for 75 ± 8 % of available energy. • Latent heat flux (LE) comprised 72 ± 10 % of available energy. • 7.8 ± 2.8 % of LE was induced by higher sensible heat advection. • Large differences exist between the oasis and surrounding deserts. • Differences in vegetation cover, soil moisture, and temperature cause advection. Surface energy fluxes, mainly encompassing the net radiation (R n), latent heat flux (LE), sensible heat flux (H s), and soil heat flux (G s), play an important role in the land-atmosphere interactions. However, almost all sites face the problem of energy imbalance, and advection fluxes associated with large inhomogeneous surfaces have been ignored, especially in arid oasis areas. In this study, a three-year continuous measurement of energy fluxes with an eddy covariance system was conducted in a drip-irrigated oasis agroecosystem in Northwest China. Reanalysis data including air temperature (T a), soil moisture (θ), and leaf area index (LAI) in our cropland and surrounding deserts were also collected. The results showed that multi-year mean turbulent fluxes (LE+ H s) accounted for 75 ± 8 % (mean ± standard deviation) of available energy (R n – G s). To be precise, LE took up 72 ± 10 % of available energy, and 7.8 ± 2.8 % of it was induced by higher sensible heat advection, proving a pronounced advection effect in this study. When advection was present, most likely during the heading stage, the threshold value for the Priestley–Taylor parameter α , an indicator to reflect the advection effect, fell in the range of 0.88–1.34. Additionally, after a significant irrigation event, α showed a good linear relationship with differences in air temperature (ΔT a), soil moisture (Δθ), and leaf area index (ΔLAI) between our cropland and surrounding deserts. It's worth mentioning that Δθ was the most significant factor, showing a negative correlation with the advection effect. This study has deepened our understanding of the energy balance in oasis agriculture, emphasizing that the advection effect should not be overlooked. [ABSTRACT FROM AUTHOR]

• Transect measurements in an alfalfa field showed the importance of horizontal advection. • Spatiotemporal heterogeneity induced advection via non-local eddies, which affected the surface energy balance. • Advective fluxes of heat and moisture explained energy budget non-closure. Orbiting around the non-closure problem in eddy covariance, a new generation of high-resolution thermal imagery has revealed that advection may be more common than previously expected. To investigate this, we conducted an extensive study over an irrigated alfalfa field that experienced heat and moisture advection. Over the course of five analysis periods (37 days total), multiple tower arrays and profile measurements were deployed to measure the horizontal advection and vertical heat flux divergence. Latent heat flux (λE) measured at the anchor tower showed an enhancement (i.e., increase) due to both local and non-local processes. Locally, as a result of the upwind λE, advection humidified the atmosphere and increased stomatal opening, enhancing the downwind λE. Simultaneously, with lowered atmospheric demand, λE was suppressed downwind. Our results suggest that stomatal regulation played a dominant role in the enhancement, but not by itself. Spectral analysis revealed that low frequency (i.e., large) eddies contributed high heat and moisture via advection. In combination with thermal remote sensing observations from ECOSTRESS and Landsat 8/9, we found that these large eddies were generated over the upwind surface, and they were independent of the local boundary layer conditions. Consequently, spatiotemporal heterogeneity in land-surface conditions induced large eddies, further enhancing λE through non-local transport of heat and moisture. Lastly, by conditionally including the advective fluxes, the energy balance closure improved from 89 % to 97 % (r2 = 0.97, p < 0.001) over the five analysis periods. Results from this improved energy balance closure suggest an alternative approach for developing validation datasets for remote sensing evapotranspiration (ET) models rather than forcing closure with Bowen-ratio. Furthermore, our findings provide insights for algorithms that may improve remote sensing ET products that treat pixels as isolated columns rather than also considering the lateral effects of heat and moisture transport. [ABSTRACT FROM AUTHOR]

Land–atmosphere interactions have been investigated at daily or longer timescales due to limited data availability and large errors for measuring high-frequency variations. Yet coupling at the subdaily timescale is characterized by the diurnal cycle of incoming solar radiation and surface fluxes. Based on flux tower observations, this study investigates the climatology of observed land–atmosphere interactions on subdaily timescales during the warm season. Process-based multivariate metrics are employed to quantitatively measure segmented coupling processes, and mixing diagrams are adopted to demonstrate the integrative moist and thermal energy budget evolution in the atmospheric mixed layer. The land, atmosphere, and combined couplings for the entire daily mean, midday, and midnight periods show different situations to which surface latent and sensible heat fluxes are relevant, and they also reveal the climate sensitivity to soil moisture and surface air temperature. The 24 h coevolution of the moist and thermal energy within the boundary layer traces a particular path on mixing diagrams, exhibiting different degrees of asymmetry (time shifts) in water- and energy-limited locations. Water- and energy-limited processes also show opposing long tails of low humidity during the daytime and nighttime, related to the impact on land and atmospheric couplings of latent heat flux and other diabatic processes like radiative cooling. This study illustrates the necessity of considering the entire diurnal cycle to understand land–atmosphere coupling processes comprehensively in observations and models. [ABSTRACT FROM AUTHOR]

Bowen ratio reflects the partitioning between sensible and latent heat fluxes and plays a crucial role in land–atmosphere interaction. In this study, the spatiotemporal variations of Bowen ratio among 12 vegetation types were analyzed using observations from 203 FLUXNET sites and compared against Community Land Model (CLM) simulations. Results showed that the annual mean Bowen ratio across all sites was 1.48 ± 1.20 (mean ± SD). Sites with Bowen ratios less than 1 were found across all continents, and the ones with a higher Bowen ratio appeared in dry and warm areas. Open shrublands showed the highest Bowen ratio (3.04 ± 0.58), whereas wetlands showed the lowest (0.74 ± 0.09). In terms of seasonality, Bowen ratio generally showed lower values in local summer and higher in spring and autumn in the northern hemisphere; the opposite occurred in the southern hemisphere. The spatiotemporal variations in Bowen ratio can be explained by climatic, geographical, and biological factors, with climate factors having the greatest impact. The spatial correlation analyses suggested Bowen ratio increased under higher VPD (R = 0.45, p < 0.001) and hotter (R = 0.14, p < 0.05) conditions and decreased with higher precipitation (R = −0.34, p < 0.001), albedo (R = −0.16, p > 0.05), and leaf area index (R = −0.25, p < 0.001). Compared to FLUXNET observations, CLM well reproduced the global annual mean Bowen ratio (1.48 for CLM vs. 1.56 for FLUXNET) but showed larger differences for certain vegetation types. Our results could enhance our understanding of biotic and environmental controls on land surface energy fluxes and help improve the land surface and climate models. Key Points: Open shrublands showed the highest Bowen ratio, followed by savannas, grasslands, forests, and croplands, and the lowest in wetlandsThe spatiotemporal variations in Bowen ratio can be explained by climatic, geographical, and biological factors, especially climate factorsCommunity Land Model well captured the global annual mean Bowen ratio but showed large differences for certain vegetation types [ABSTRACT FROM AUTHOR]

A benchmark dataset of radiation, heat, and CO 2 fluxes is crucial to land–atmosphere interaction research. Due to rapid urbanization and the development of agriculture, the land–atmosphere interaction processes over the Yangtze River Delta (YRD) of China, which is a typical East Asian monsoon region, are becoming various and complex. To understand the effects of various land cover changes on land–atmosphere interactions in this region, a comprehensive long-term (2011–2019) in situ observation campaign, including 30 min resolution meteorological variables (air temperature, humidity, pressure, wind speed, and wind direction), surface radiative flux, turbulent heat flux, and CO 2 flux, was conducted at four sites with two typical surface types (i.e., croplands and suburbs) in the YRD. Analysis of the dataset showed that all four radiation components, latent heat flux, sensible heat flux, soil heat flux, and CO 2 flux varied seasonally and diurnally at the four sites. Surface energy fluxes exhibited great differences among the four sites. On an annual basis, for the two cropland sites, the dominant consumer of net radiation was latent heat flux. For the two suburban sites, in contrast, latent heating dominated from April to November, whereas sensible heating dominated during the other months. Our present work provides convincing evidence that the dataset has potential for multiple research fields, including studying land–atmosphere interactions, improving boundary layer parameterization schemes, evaluating remote sensing algorithms, validating carbon flux modeling and inversion, and developing climate models for typical East Asian monsoon regions. The dataset is publicly available at 10.5281/zenodo.6552301 (Duan et al., 2022). [ABSTRACT FROM AUTHOR]

This paper analyzed observations from the Great Plains Irrigation Experiment (GRAINEX) to better understand land–atmosphere (L–A) interactions and PBL evolution. This study is focused on a day when the largest forcing on the boundary layer originated from the land surface/land use. To examine these impacts, we also applied the Weather Research and Forecasting (WRF) Model. Results from the observations show that compared to nonirrigated areas, air temperature, wind speed, and PBL height (PBLH) were lower while dewpoint temperature and latent heat flux were higher over irrigated areas. Findings suggest that entrainment layer drying and differences in energy partitioning over irrigated and nonirrigated areas played an important role in PBL evolution. In the final hours of the day, the PBL collapsed faster over nonirrigated areas compared to irrigated. The WRF Model simulations agree with these observations. They also show that the extent of irrigation [expressed as irrigation fraction (IF)] in an area impacts L–A response. Under ∼60% IF, the latent heat flux and mixing ratio reach their highest value while temperature and PBLH are at their lowest, and sensible heat flux is near its lowest value. Results are reversed for ∼2% IF. It is concluded that irrigation notably impacts L–A interactions and PBL evolution. [ABSTRACT FROM AUTHOR]

Based on the comprehensive data from the land-atmosphere interaction observation station in Ali of Tibetan in 2019, the characteristics of land-atmosphere energy exchange processes in Ali were analyzed. The results indicated that the timing of the mean intraday net radiation peak in Ali over the past 20 years has been delayed, and the month when the maximum monthly mean net radiation occurred has been delayed by about 2 months; the maximum daily mean, maximum monthly mean, minimum monthly mean, and annual mean sensible heat were 99.63 w/m2, 76.53 w/m2, 17.47 w/m2, and 46.74 w/m2, respectively, and the maximum daily mean, maximum monthly mean, minimum monthly mean, and annual mean latent heat flux were 73.27 w/m2, 36.13 w/m2, 0.67 w/m2, and 8.32 w/m2, respectively; and the monthly mean sensible heat was greater than the latent heat in all months. [ABSTRACT FROM AUTHOR]

Following potential reforestation in the Amazon Basin, changes in the biophysical characteristics of the land surface may affect the fluxes of heat and moisture behavior. This research examines the impacts of potential tropical reforestation on surface energy and moisture budgets, including precipitation and temperature. The study is novel in that while most studies look at the opposite driver (deforestation), this one examines the impact of potential forest rehabilitation on atmospheric behavior using WRF.V3.9 (weather research and forecast model). We found that forest rehabilitation across the Amazon Basin can make the atmosphere cooler with more moisture and latent heat (LH), especially during May-November. For instance, the mean seasonal temperature decreased significantly by about 1.2 °C, indicating the cooling effects of reforestation. Also, the seasonal precipitation increased by 5 mm/day in reforested areas. By reforestation, the mean monthly LH also increased as much as 50 W m−2 in August in certain areas, while available moisture to the atmosphere increased by 27%, indicating possible causal mechanisms between increased LH and precipitation and emphasizing the mechanisms that were identified between the onset of the wet season and forest cover. Therefore, it is likely that forest regrowth across the basin leads to, if not reverses regional climate change, at least slowing down the rate of changes in the climate. [ABSTRACT FROM AUTHOR]

Ebullition, the release of gas bubbles, is an important pathway of methane emission in many ecosystems, yet its high spatio–temporal variability makes it challenging to quantify. In this work, a methane-flux partitioning method based on scalar similarity in the wavelet domain is applied to eddy-covariance data collected at two flooded rice fields. Inspection of initial results indicates that several modifications are needed for robust ebullition detection. With these modifications, our objectives are to compare the original and modified methods, conduct a sensitivity analysis of the program's empirical parameters, characterize the importance of ebullition in rice across growth stages, and identify the primary drivers of ebullition. The modified method's ebullitive fluxes are significantly lower and show lower variance than those from the original method. Furthermore, the two methods produce distinct patterns of diel variation. While partitioning estimates show non-trivial sensitivity to the program parameters, this sensitivity is lower in magnitude than the random error in the ebullitive flux estimates. Ebullitive fluxes make up 9% of the total flux on average, with ebullition increasing in importance as plants develop. Ebullitive fluxes are best predicted by wind speed (negative effect), ecosystem respiration (positive effect), and sensible heat flux (positive effect), suggesting an indirect effect of plant-mediated transport, a link with temperature and methane production, and a potential effect of water column turnover, respectively. In addition to validating the method with independent ebullition observations, we recommend its application at more natural and managed wetlands to improve understanding of this highly variable transport pathway. [ABSTRACT FROM AUTHOR]

The control of latent heat flux (LE) by soil moisture (SM) is a key process affecting the moisture and energy budgets at the land--atmosphere interface. SM--LE coupling relationships are conventionally examined using metrics involving temporal correlation. However, such a traditional linear approach, which fits a straight line across the full SM--LE space to evaluate the dependency, leaves out certain critical information: nonlinear SM--LE relationships and the long-recognized thresholds that lead to dramatically different behavior in different ranges of soil moisture, delineating a dry regime, a transitional regime of high sensitivity, and a wet (energy-limited) regime. Using data from climate models, reanalyses, and observationally constrained datasets, global patterns of SM--LE regimes are determined by segmented regression. Mutual information analysis is applied only for days when SM is in the transitional regime between critical points defining high sensitivity of LE to SM variations. Sensitivity is further decomposed into linear and nonlinear components. Results show discrepancies in the global patterns of existing SM regimes, but general consistencies among the linear and nonlinear components of SM--LE coupling. This implies that although models simulate differing surface hydroclimates, once SM is in the transitional regime, the locations where LE closely interacts with SM are well captured and resemble the conventional distribution of "hotspots" of land--atmosphere interactions. This indicates that only the transitional SM regime determines the strength of coupling, and attention should focused on when this regime occurs. This framework can also be applied to investigate extremes and the shifting surface hydroclimatology in a warming climate. [ABSTRACT FROM AUTHOR]

Although desertification has greatly increased across the Mongolian Plateau during the last decades of the 20th century, recent satellite records documented increasing vegetation growth since the 21st century in some areas of the Mongolian Plateau. Compared to the study of desertification, the opposite characteristics of land use and vegetation cover changes and their different effects on regional land–atmosphere interaction factors still lack enough attention across this vulnerable region. Using long-term time-series multi-source satellite records and regional climate model, this study investigated the climate feedback to the observed land surface changes from the 1990s to the 2010s in the Mongolia Plateau. Model simulation suggests that vegetation greening induced a local cooling effect, while the warming effect is mainly located in the vegetation degradation area. For the typical vegetation greening area in the southeast of Inner Mongolia, latent heat flux increased over 2 W/m2 along with the decrease of sensible heat flux over 2 W/m2, resulting in a total evapotranspiration increase by 0.1~0.2 mm/d and soil moisture decreased by 0.01~0.03 mm/d. For the typical vegetation degradation area in the east of Mongolia and mid-east of Inner Mongolia, the latent heat flux decreased over 2 W/m2 along with the increase of sensible heat flux over 2 W/m2 obviously, while changes in moisture cycling were spatially more associated with variations of precipitation. It means that precipitation still plays an important role in soil moisture for most areas, and some areas would be at potential risk of drought with the asynchronous increase of evapotranspiration and precipitation. [ABSTRACT FROM AUTHOR]

A benchmark dataset of radiation, heat and CO2 fluxes is crucial to land-atmosphere interaction research. Due to the rapid urbanization and the development of agriculture, land-atmosphere interaction process over the Yangtze River Delta YRD) of China, which is the typical East Asian monsoon region, is becoming various and complex. To understand the effects of various land cover changes on land-atmosphere interaction in this region, a comprehensive long-term (2011-2019) in situ observation including 30-min meteorology (air temperature, humidity, pressure, wind speed, and wind direction), surface radiative flux, turbulent heat flux, and CO2 flux was conducted at four sites with two typical surface types (i.e., croplands and suburbs) in the YRD. The dataset shows that all four component radiation components, latent heat flux, sensible heat flux, soil heat flux, and CO2 fluxes varied seasonally and diurnally at four sites. Surface energy fluxes exhibited great differences among the four sites. On an annual basis, for two cropland sites, the dominant consumer of net radiation was latent heat flux. At two suburb sites, latent heating dominates from April to November, whereas sensible heating dominates the other months. This dataset will contribute to multiple research fields, including studying land-atmosphere interaction, improving the boundary-layer parameterization schemes, evaluating remote sensing algorithms, and developing climate models in the typical East Asian monsoon region. The dataset is publicly available at https://doi.org/10.5281/zenodo.6552301, last access: 10 May 2022 (Duan et al., 2022). [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]

Alpine grassland is the main ecosystem of the Tibetan Plateau (TP), thus accurate simulation of water and heat exchange in the grassland will significantly enhance the understanding of the land-atmosphere interaction process on the TP. In this study, we assessed and improved the ensemble numerical simulations of the community Noah land surface model with multiparameterization options (Noah-MP) by using observations collected from four alpine grassland observation sites. The four observation sites belong to the upper Heihe River Basin Integrated Observatory Network located in the northeastern part of the TP. First, an ensemble of 1008 numerical simulation experiments, based on multiparameterization options of seven physical processes/variables in the Noah-MP, was carried out for the vegetation growing season. The Taylor skill score was then used to assess the model performance and select the optimal combination of parameterization options for a more exact simulation of the water and heat exchange in alpine grassland. The accuracy of Noah-MP simulation was further improved by introducing new parameterizations of thermal roughness length, soil hydraulic properties, and vertical root distribution. It was found that: (1) Simulation of water and heat exchange over alpine grassland in the growing season was mainly affected by the parameterizations of dynamic vegetation, canopy stomatal resistance, runoff and groundwater dynamics, and surface exchange coefficient for heat transfer. Selection of different parameterization options for these four physical processes/variables led to large differences in the simulation of water and heat fluxes. (2) The optimal combination of parameterization options selected in the current Noah-MP framework suffered from significant overestimation of sensible heat flux (H) and underestimation of soil moisture (θ) at all observation sites. (3) The overestimation of H was significantly improved by introducing a new parameterization of thermal roughness length. Furthermore, the underestimation of θ was resolved by introducing a new parameterization of soil hydraulic properties that considered the organic matter effect and a new vertical distribution function for the vegetation root system. The results of this study provide an important reference for further improving the simulation of water and heat exchange by using the land surface model in alpine grassland. [ABSTRACT FROM AUTHOR]

The intra-seasonal variation in precipitation isotopes shows a characteristic declining trend over northeast India. As of now, no mechanism offers a consistent explanation of this trend. We have performed the isotopic analysis of precipitation (rain) and estimated net ecosystem exchange and latent heat fluxes using an eddy-covariance system in northeast India. Additionally, we have used a diagnostic model to determine the recycled rainfall in this region. We find a strong link between the enhanced ecosystem productivity and isotopic enrichment in rainwater during the premonsoon season. Subsequently, on the advent of monsoon, the Bay of Bengal generated moisture enters this region and depletes the isotopic values. Additionally, the regional-scale convective activities produce periodic lows in the precipitation isotopes. Contrary to the general understanding, our study shows that the internal factors, such as the local land-atmosphere interactions, rather than the external influences, play a significant role in governing the precipitation isotopes in northeast India. [ABSTRACT FROM AUTHOR]

The planetary boundary layer (PBL) plays an essential role in climate and air quality simulations. Nevertheless, large uncertainties remain in understanding the drivers for long-termtrends of PBL height (PBLH) and its simulation. Herewe combine the radiosonde data and reanalysis datasets to analyze PBLHlong-termtrends over China, and to further explore the performance of CMIP6 climate models in simulating these trends. Results show that the observed long-term "positive-tonegative" trend shift of PBLH is related to the variation in the surface upward sensible heat flux (SHFLX), and the SHFLX is further controlled by the synergistic effect of low cloud cover (LCC) and soil moisture (SM) changes. Variabilities in LCC and SM directly influence the energy balance via surface net downward shortwave flux (SWF) and the latent heat flux (LHFLX), respectively. The CMIP6 climate models, however, cannot reproduce the observed PBLH long-term trend shift over China. The CMIP6 results illustrate an overwhelming continuous downward PBLH trend during the 1979-2014 period, which is largely caused by the poor capability in simulating long-term variations of cloud radiative effect. Our results reveal that the long-term cloud radiative effect simulation is critical for CMIP6 models in reproducing the long-term trend of PBLH. This study highlights the importance of processes associated with LCC and SM in modulating PBLH long-term variations and calls attention to improve these processes in climate models in order to improve the PBLH long-term trend simulations. SIGNIFICANCE STATEMENT: Investigating the long-term variations of the planetary boundary layer height (PBLH) is of great importance in understanding the complicated interactions between climate change and the planetary boundary layer. The availability of long-term radiosonde observations, along with reanalysis data and data from phase 6 of the Coupled Model Intercomparison Project, provides an excellent opportunity for us to analyze the long-term variability of PBLH and explore the capability of global climate models in reproducing the observed trend of PBLH. We argue that variations of cloud cover and soil moisture dominate the long-term variability of PBLH over China, given their key role in modifying the surface energy partition and balance. More importantly, whether cloud processes can be well simulated or not is key to reproducing the observed PBLH variations in global climate models, which merits further process-based observation in the future. [ABSTRACT FROM AUTHOR]

Accurate estimates of land surface characteristic parameters and turbulent heat fluxes play an important role in the understanding of land-atmosphere interaction. In this study, Fengyun-4A (FY-4A) Advanced Geostationary Radiation Imager (AGRI) satellite data and the China Land Data Assimilation System (CLDAS) meteorological forcing dataset CLDAS-V2.0 were applied for the retrieval of broadband albedo, land surface temperature (LST), radiation flux components, and turbulent heat fluxes over the Tibetan Plateau (TP). The FY-4A/AGRI and CLDAS-V2.0 data from 12 March 2018 to 30 April 2018 were first used to estimate the hourly turbulent heat fluxes over the TP. The time series data of in-situ measurements from the Tibetan Observation and Research Platform were divided into two halves—one for developing retrieval algorithms for broadband albedo and LST based on FY-4A, and the other for the cross validation. Results show the root-mean-square errors (RMSEs) of the FY-4A retrieved broadband albedo and LST were 0.0309 and 3.85 K, respectively, which verifies the applicability of the retrieval method. The RMSEs of the downwelling/upwelling shortwave radiation flux and downwelling/upwelling longwave radiation flux were 138.87/32.78 W m−2 and 51.55/17.92 W m−2, respectively, and the RMSEs of net radiation flux, sensible heat flux, and latent heat flux were 58.88 W m−2, 82.56 W m−2 and 72.46 W m−2, respectively. The spatial distributions and diurnal variations of LST and turbulent heat fluxes were further analyzed in detail. [ABSTRACT FROM AUTHOR]

Warm-season precipitation in the Lower Mississippi River Alluvial Valley (LMRAV) is heavily dominated by the rates of evapotranspiration and surface heat fluxes and is a primary water resource for agriculture. However, the stochastic nature of LMRAV warm-season thunderstorms makes precipitation forecasts challenging. The Weather Research and Forecasting Hydrologic (WRF-Hydro) model, coupled with the multi-parameter Noah land surface (Noah-MP) model, has improved estimates of important warm-season precipitation process. Given the widespread agriculture and dominance of crop and forested landscapes over the region, proper assessment of land use / land cover (LULC) is critical in predicting warm-season precipitation patterns. The objective of this study is to quantify simulated latent heat flux sensitivity (important for warm-season precipitation) to temporally updated LULC datasets. Both the model default and annually updated LULC conditions were used to initialize a 16-year WRF-Hydro simulation from which warm-season latent heat flux estimates were obtained. Annual root mean square difference was computed at each gridpoint. Cluster analysis preprocessed with kernel principal component analysis was used to identify spatial RMSD structures that quantified sensitivity to updated LULC conditions. Results showed the largest impacts occurred directly in the LMRAV and for points slightly east and revealed a meteorological link between these regions. [ABSTRACT FROM AUTHOR]

Increased heat-wave frequency across the United States has led to the need for improved predictability of heat-wave events. A detailed understanding of land–atmosphere interactions and the relationship between soil moisture and temperature extremes could provide useful information for prediction. This study identifies, for many locations, a threshold of soil moisture below which there is an increase in the sensitivity of atmospheric temperature to declining soil moisture. This shift to a hypersensitive regime causes the atmosphere to be more susceptible to atmospherically driven heat-wave conditions. The soil moisture breakpoint where the regime shift occurs is estimated using segmented regression applied to observations and reanalysis data. It is shown that as the soil gets drier, there is a concomitant change in the rate of decrease in latent heat flux and increase in sensible heat flux leading to a strong positive feedback of increased air temperature near the surface, which further dries out the soil. Central, southwestern, and southeastern parts of the United States seem to have regions of clear regime shifts, while the eastern part of the United States generally does not get dry enough to reveal significant breakpoints. Sensible heat flux is seen to be a primary driver of this increased temperature sensitivity aided by the drop in latent heat flux. An investigation of flux tower sites verifies the breakpoint–flux relationships found in reanalysis data. Accurate estimation of these breakpoints can contribute to improved heat-wave prediction. [ABSTRACT FROM AUTHOR]

One of the critical components in understanding the climate system is the interaction between the land and the atmosphere. Whereas previous studies on land–atmosphere coupling mostly focus on its spatial hotspots, we explore the temporal evolution of land surface coupling strength (LCS) during a large-scale flood event in a semiarid region in northern Australia. The LCS indicates the relationship between soil moisture and latent heat flux, and the spatiotemporal variability in precipitation and soil water strongly affects the variability of LCS. The LCS is usually positive in the semiarid climate, where evapotranspiration (ET) occurs under the soil moisture–limited regime and thus increases with soil moisture. However, our analyses of combined land surface modeling and observational datasets show high temporal variability of LCS in the course of the extreme flood event followed by a drying period. The wet regions transferred the ET regime from the soil moisture–limited to the transition section, weakening the linear growth of ET with soil moisture, which resulted in the decline of LCS. The LCS remained weak until the flood retreated and the soil water approached the prestorm average state. Such temporal variation of the LCS has important implications for realistic parameterization of the land–atmosphere coupling and consequently improving subseasonal to seasonal climate forecast. [ABSTRACT FROM AUTHOR]

Most studies of land‐atmosphere coupling have focused on bivariate linear statistics like correlation. However, more complex dependencies exist, including nonlinear relationships between components of land‐atmosphere coupling and the transmutability of relationships between soil moisture and surface heat fluxes under different environmental conditions. In this study, a technique called multivariate mutual information, based on information theory, is proposed to quantify how surface heat fluxes depend on both surface energy and wetness conditions, that is, net radiation and soil moisture, seasonally across the globe using reanalysis data. Such interdependency is then decomposed into linear and nonlinear contributions, which are further decomposed as different components explainable as the unique contribution from individual surface conditions, redundant contributions shared by both surface conditions, and the synergistic contribution from the concurrent action of net radiation and soil moisture. In reanalysis data, the dependency linearly contributed from soil moisture bears a similar global pattern to previously identified hot spots of coupling. The linear unique contributions of net radiation and soil moisture are mainly nonoverlapping, which suggests two separate regimes are governed by either energy or water limitations. These patterns persist when the nonlinearity is superimposed, thus reinforcing the validity of the land‐atmospheric coupling hot spot paradigm and the spatial division of energy‐limited as well as water‐limited regions. Nevertheless, strong nonlinear relationships are detected, particularly over subtropical regions. Synergistic components are found across the globe, implying widespread multidimensional physical relationships among net radiation, soil moisture, and surface heat fluxes that previously had only been inferred locally. Plain Language Summary: Most of our knowledge of how land surface states affect weather and climate around the world is based on common statistical methods that assume straight lines can be fitted to determine how evaporation and heating of the air can be controlled by soil moisture. Furthermore, studies have historically looked one‐at‐a‐time at a single cause affecting a single response. But local studies have shown that coupling between land and atmosphere can be more complex, involving multiple factors working simultaneously and often nonlinearly. This study uses a novel combination of techniques to discern how variations in processes like evaporation are driven by multiple factors such as soil moisture and available soil and thermal energy at the land surface that can make separately unique contributions, redundant contributions, and compound contributions due to factor interaction. Each of these contributions is also broken down into simple linear and other nonlinear components, helping show how much land‐atmosphere interaction the previous methods were missing, and suggesting which regions, seasons and potential physical processes need further study. Key Points: Nonlinear and multivariate dependencies in land‐atmospheric coupling are diagnosed using multivariate mutual information (MMI)Integrated MMI method decomposes drivers of surface flux variability into linear versus nonlinear; unique, redundant, and synergistic componentsNonlinear and synergistic dependencies of surface heat fluxes on soil moisture and net radiation are widespread across the globe [ABSTRACT FROM AUTHOR]

Subgrid horizontal variations of land surface heat fluxes to the atmosphere resulting from subgrid land cover heterogeneity are important in land‐atmosphere interaction in global climate models (GCMs). To incorporate it, a parameterization using stochastic sampling based on truncated normal distributions diagnosed from the land model and internal ensemble mean of multiple calls to the planetary boundary layer and deep convection schemes is developed. After its implementation in the National Center for Atmospheric Research (NCAR) Community Earth System Model version 1.2 (CESM1.2), large changes of simulated land precipitation are found to occur in regions where large subgrid variations of surface heat fluxes exist. The simulated precipitation is improved in boreal summer, especially over eastern China and the coastal areas of the Bay of Bengal. The improved precipitation is mainly a result of improved large‐scale moisture convergence and advection by altered vertical diffusion and convection. Plain Language Summary: Many recent studies show that the horizontal variations of land surface heat fluxes play an important role in land precipitation. The horizontal grid scale of global climate models (GCMs) is typically ∼100–200 km within which various land cover types may coexist, leading to significant variations of surface heat fluxes in the model grid. However, GCMs only utilize the grid‐averaged surface heat fluxes to drive the atmosphere, while neglecting the variations within each grid. To address this shortcoming, a method feeding these missing variations to the atmosphere is proposed and implemented in the National Center for Atmospheric Research Community Earth System Model version 1.2 (CESM1.2). The results show that the method overall improves the simulated rainfall on land, especially in boreal summer. Key Points: A parameterization scheme for the subgrid variations of land surface heat fluxes to the atmosphere in global climate model is developedBoreal summer precipitation simulation in the Community Earth System Model version 1.2 with the new scheme is improvedImproved large‐scale moisture convergence and advection are mainly responsible for the improved precipitation simulation [ABSTRACT FROM AUTHOR]

The diurnal cycle of solar radiation represents the strongest energetic forcing and dominates the exchange of heat and mass of the land surface with the atmosphere. This diurnal heat redistribution represents a core of land–atmosphere coupling that should be accurately represented in land surface models (LSMs), which are critical parts of weather and climate models. We employ a diagnostic model evaluation approach using a signature-based metric that describes the diurnal variation of heat fluxes. The metric is obtained by decomposing the diurnal variation of surface heat fluxes into their direct response and the phase lag to incoming solar radiation. We employ the output of 13 different LSMs driven with meteorological forcing of 20 FLUXNET sites (PLUMBER dataset). All LSMs show a poor representation of the evaporative fraction and thus the diurnal magnitude of the sensible and latent heat flux under cloud-free conditions. In addition, we find that the diurnal phase of both heat fluxes is poorly represented. The best performing model only reproduces 33% of the evaluated evaporative conditions across the sites. The poor performance of the diurnal cycle of turbulent heat exchange appears to be linked to how models solve for the surface energy balance and redistribute heat into the subsurface. We conclude that a systematic evaluation of diurnal signatures is likely to help to improve the simulated diurnal cycle, better represent land–atmosphere interactions, and therefore improve simulations of the near-surface climate. [ABSTRACT FROM AUTHOR]

The evaluation and characteristics of land-surface processes over the Indian Summer Monsoon (ISM) region are studied using Dirmeyer's two-legged land-atmosphere coupling metrics in regional climate modelling system. Different land-atmosphere coupling metrics are used for assessing the "hot-spots" of land atmosphere feedback over the Indian subcontinent. The model simulations are performed using regional climate model (RCM)—RegCMv4.0, 4.2 and 4.4.5.10 at different horizontal resolutions. The monthly soil wetness climatology over India is calculated using European Space Agency (ESA) datasets. Maximum soil moisture(SM) is found over the western part of central India during June–September. The results from RCM simulations (RegCMv4.0, 4.2 and 4.4.5.10) indicate more soil wetness, systematically (over-predicted) over North India, Indo-Gangetic plains and central India during June, July, August and September, implying that model soil wetness is driven by precipitation minus evapotranspiration (P-E). The role of aerosols in land–atmosphere interactions along with the impact of mixed convective parameterization schemes over ocean and land on modelling SM and land–atmosphere interactions is also addressed. The spatial and temporal variation of atmospheric and terrestrial coupling indices during ISM regime concludes that May, June, July and August are the prime months of land–atmosphere interactions over central and north-west India reiterating results from previous GLACE (The Global Land–Atmosphere Coupling Experiment) studies. Model simulations also indicate that during the ISM season the terrestrial segment of land–atmosphere coupling (i.e. terrestrial coupling index of soil moisture, SM) from SM to latent heat flux varies around 35–40 W m−2, while the atmospheric segment of coupling (i.e. atmospheric coupling index of precipitation) from latent heat flux to precipitation modulates around 4–6 mm/day. Aerosols are found to influence land-atmosphere interactions over north-west India by modulating net radiation. More in-situ observations of land surface variables are required for verification of land-atmospheric interactions (along with impact of aerosols) using RCMs. [ABSTRACT FROM AUTHOR]

Land surface heat and evaporative fluxes exchanged between the land and atmosphere play a crucial role in the terrestrial water and energy balance. Regional mapping of these fluxes is hampered by the lack of in situ measurements (with the required coverage and duration) and the high spatial heterogeneity. In this paper, we propose a Land Integrated Data Assimilation framework (LIDA) based on the variational data assimilation technique to estimate the key parameters of surface heat and evaporative fluxes by jointly assimilating Soil Moisture Active Passive (SMAP) data and Geostationary Operational Environmental Satellite (GOES) surface temperature data into a coupled parsimonious land water and energy balance model. The method is implemented over an area of 31,500 km2 in the U.S. Southern Great Plains, and its performance is evaluated through consistency tests, comparison tests, and uncertainty analyses. The maps of retrieved heat and evaporative fluxes are used to analyze a range of feedback mechanisms in land‐atmosphere interaction, such as the dependence of evapotranspiration on vegetation and water availability. Key Points: A Land Integrated Data Assimilation framework (LIDA) based on the variational data assimilation technique is proposedLIDA maps surface heat and evaporative fluxes over the U.S. Southern Great Plains by assimilating GOES LST and SMAP SMLIDA estimates the uncertainty of estimated parameters, hence fluxes, by calculating the error covariance matrix of parameters [ABSTRACT FROM AUTHOR]

The land biosphere is a crucial component of the Earth system that interacts with the atmosphere in a complex manner throughmanifold feedback processes. These relationships are bidirectional, as climate affects our terrestrial ecosystems, which, in turn, influence climate. Great progress has beenmade in understanding the local interactions between the terrestrial biosphere and climate, but influences fromremote regions through energy andwater influxes to downwind ecosystems remain less explored. Using a Lagrangian trajectorymodel driven by atmospheric reanalysis data, we show how heat and moisture advection affect gross carbon production at interannual scales and in different ecoregions across the globe. For water-limited regions, results show a detrimental effect on ecosystem productivity during periods of enhanced heat and reduced moisture advection. These periods are typically associated with winds that disproportionately come from continental source regions, as well as positive sensible heat flux and negative latent heat flux anomalies in those upwind locations. Our results underline the vulnerability of ecosystems to the occurrence of upwind climatic extremes and highlight the importance of the latter for the spatiotemporal propagation of ecosystem disturbances. [ABSTRACT FROM AUTHOR]

Anthropogenic heat (AH) is an important part of urban surface energy balance. Although AH affects regional climates through changing land-atmosphere interactions, the climate forcing from AH are not usually calculated in state-of-the-art regional climate simulations. In this paper, the spatial pattern of AH in 20 automatic weather station sites in the Beijing municipal administrative area is parameterized by employing nighttime light data. Two experiments were designed and performed to quantify the influence of AH on the surface balance of energy and water through running the Integrated urban Land Model (IUM). The results show that due to accounting for AH, the simulated LST increases; the net radiation decreases around noon; the absolute value of the ground heat flux increases around noon; the sensible heat flux increases in the daytime; the evapotranspiration decreases around noon and increases in the morning and evening; volumetric soil moisture and soil water storage decrease; aggregated evapotranspiration increases. [ABSTRACT FROM AUTHOR]

The aerodynamic roughness length is a crucial parameter that controls surface variables including the horizontal wind, surface temperature, and heat fluxes. Despite its importance, in the Weather Research and Forecasting (WRF) model, this parameter is typically assigned a predefined value, mostly based on the dominant land‐use type. In this work, the roughness length is first estimated from eddy‐covariance measurements at Al Ain in the United Arab Emirates (UAE), a hyper‐arid region, and then ingested into WRF. The estimated roughness length is in the range 1.3–2.2 mm, one order smaller than the default value used in WRF. In line with previous studies, and from WRF model simulations during the warm and cold seasons, it is concluded that, when the roughness length is decreased by an order of magnitude, the horizontal wind speed increases by up to 1 m s−1, the surface temperature rises by up to 2.5°C, and the sensible heat flux decreases by as much as 10 W m−2. In comparison with in situ station and eddy covariance data, and when forced with the updated roughness length, WRF gives more accurate 2‐m air temperature and sensible heat flux predictions. For prevailing wind speeds >6 m s−1, the model underestimates the strength of the near‐surface wind, a tendency that can be partially corrected, typically by 1–3 m s−1, when the updated roughness length is considered. For low wind speeds (<4 m s−1), however, WRF generally overestimates the strength of the wind. Key Points: For the first time, aerodynamic roughness length is estimated from in the United Arab Emirates, and it is one order smaller than the default value used in WRFWRF model 2‐m air temperature and sensible heat simulations are more accurate with the updated roughness lengthFor wind speeds >6 m s−1, the model underestimates the strength of the surface wind, and it is corrected by 1–3 m s−1, when the updated roughness length is considered [ABSTRACT FROM AUTHOR]

Correct understanding of the land-surface processes and cloud-precipitation processes in the Tibetan Plateau (TP) is an important prerequisite for the study and forecast of the downstream activities of weather systems and one of the key points for understanding the global atmospheric movement. In order to show the achievements that have been made, this paper reviews the progress on the observations for the atmospheric boundary layer, land-surface heat fluxes, cloud-precipitation distributions and vertical structures by using ground- and space-based multiplatform, multisensor instruments and the effect of the cloud system in the TP on the downstream weather. The results show that the form drag related to the topography, land–atmosphere momentum and scalar fluxes is an important part of the parameterization process. The sensible heat flux decreased especially in the central and northern TP caused by the decrease in wind speeds and the differences in the ground-air temperatures. Observations show that the cloud and precipitation over the TP have a strong diurnal variation. Studies also show the compressed-air column in the troposphere by the higher-altitude terrain of the TP makes particles inside clouds vary at a shorter distance in the vertical direction than those in the non-plateau area so that precipitation intensity over the TP is usually small with short duration, and the vertical structure of the convective precipitation over the TP is obviously different from that in other regions. In addition, the influence of the TP on severe weather downstream is preliminarily understood from the mechanism. It is necessary to use model simulations and observation techniques to reveal the difference between cloud precipitation in the TP and non-plateau areas in order to understand the cloud microphysical parameters over the TP and the processes of the land boundary layer affecting cloud, precipitation and weather in the downstream regions. [ABSTRACT FROM AUTHOR]

Driven by the strength in local land–atmosphere coupling, inter‐annual variability of larger‐scale atmospheric circulations primarily determines a glacier's response to warming in high Asia. In this study, micrometeorological measurements in conjunction with regional reanalysis data set were analysed to examine seasonal land–atmosphere coupling strength at a typical central Himalayan (CH) glacier where the influence of Indian summer monsoon (ISM) predominates relative to winter‐westerlies. Energy–water (E–W) exchange and coupling behaviour were studied for the Pindari glacier based on sub‐hourly measurements of radiative–convective flux, state parameters, and sub‐surface thermal profiles using cross‐correlations between various E–W balance components. Coupling was positive in summer and winter accumulation seasons. However, it remained strongest during ISM. Coupling reversed during seasonal transition phases concurrent with distinct seasonality in E–W components. Lead–lag relation between some variables showed strong association at diurnal‐scale (VPD–Rn; VPD–LE; Rn–G), whereas some persisted beyond months (Rn–LE; Bowen ratio–precipitation; surface–air temperature). Weak association of variation of latent heat flux (LE) and rainfall was found during ISM at local scale than at regional scale, but with a lag, which was more prominent at regional scale. These observations indicate a seasonally variable coupling between E–W balance components through response–feedback mechanisms. Cross‐correlations of daily mean values of energy fluxes and meteorological variables reveal that Rn and air temperature are the prime drivers of energy balance. Net radiative energy (Rn) dominates energy exchanges at the glacier–atmosphere interface (governed primarily by the variation in net shortwave radiation), contributed on average 62% of the melt energy. However, sub‐surface heat flux along with the turbulent fluxes was the energy sinks of 24 and 15%, respectively. This study would help understand and parameterize E–W exchange pathways for ISM dominated CH glaciers in coupled glacier–climate models. [ABSTRACT FROM AUTHOR]

This study evaluated the Noah land-surface model performance to simulate the land-surface process during different weather conditions in the hinterland of the Taklimakan Desert. This study is based on observation data from the Taklimakan Desert Meteorology Field Experiment Station in 2014. The results illustrated that the energy-exchange process between the land surface and the atmosphere in the drifting desert can be simulated by Noah effectively. However, the effects of soil moisture and latent heat flux were very poor. For sunny days, the soil temperature and heat flux were underestimated significantly in the nighttime and overestimated in the daytime. The simulation results are very good in sand-dust weather. The simulation of heat flux and net radiation is very consistent with the observation during cloudy days. For rainy days, the model can successfully model the diurnal variation of soil moisture, but it has obvious deviations in the net radiation, heat flux, and soil heat flux. [ABSTRACT FROM AUTHOR]

Reliable simulation of turbulent heat fluxes needed for modeling land‐atmosphere interactions remains a challenge over the humid tropical region. This may be connected with the inadequate parameterization of the roughness lengths for momentum (z0m) and heat (z0h) transfer usually expressed in terms of excess resistance factor (κB−1). This paper assesses the performance of existing κB−1 schemes developed for high wind speed conditions over the humid tropical region. Thereafter, a more appropriate κB−1 suitable for low wind speed condition is developed for use in the aerodynamic resistance parameterization. Based on observed surface heat fluxes and profile measurements of wind speed and temperature from Nigeria Micrometeorological Experimental site, new κB−1 parameterization was derived through the application of the Monin‐Obukhov similarity theory and Brutsaert theoretical model for heat transfer. The derived κB−1=6.66Re*0.02−5.47, where Re* is the Reynolds number. Turbulent flux parameterization with this new formula provides better estimates of heat fluxes with reference to results from existing κB−1 schemes. The R2 increased by about 85%, while mean bias error and root‐mean‐square error in the parameterized QH based on the derived κB−1 reduced by about 63% and 66.7%, respectively. Similarly, the R2 increased by about 38%, while mean bias error and root‐mean‐square error in the parameterized QE based on the derived κB−1 reduced by about 47.8% and 52.6%, respectively. The derived κB−1 gave better estimates of QH than QE during the daytime. The derived κB−1 scheme corrects a well‐documented, large overestimation of turbulent heat fluxes, and it is therefore recommended for use in regions where low wind speed is prevalent. Key Points: There is an improvement (bias reduction) on the estimated heat fluxes when κB−1 term is incorporated to the ARAThe Brutsaert exponent (0.25) seems to be valid for neutral cases of stable conditions in an equatorial atmosphereA complete neglect of this resistance may give rise to more than 50% overestimation of heat flux during the daytime [ABSTRACT FROM AUTHOR]

Uncertainties in representing land–atmosphere interactions can substantially influence regional climate simulations. Among these uncertainties, the surface exchange coefficient Ch is a critical parameter, controlling the total energy transported from the land surface to the atmosphere. Although it directly impacts the coupling strength between the surface and atmosphere, it has not been properly evaluated for regional climate models. This study assesses the representation of surface coupling strength in a stand-alone Noah-MP land surface model and in coupled 4-km Weather Research and Forecasting (WRF) model simulations. The data collected at eight FLUXNET sites of the Canadian Carbon Program and seven AMRIFLUX sites are used to evaluate the offline Noah-MP simulations. Nine of these FLUXNET sites are used for the evaluation of the coupled WRF simulations. These sites are categorized into three land use types: grassland, cropland, and forest. The surface exchange coefficients derived using three formulations in Noah-MP simulations are compared to those calculated from observations. Then, the default C zil = 0 and new canopy-height dependent C zil are used in coupled WRF simulations over the spring and summer in 2006 to compare their effects on surface heat flux, temperature, and precipitation. When the new canopy-height dependent C zil scheme is used, the simulated Ch exchange coefficient agrees better with observation and improves the daily maximum air temperature and heat flux simulation over grassland and cropland in the US Great Plains. Over grassland, the modeled Ch shows a different diurnal cycle than that for observed Ch, which makes WRF lag behind the observed diurnal cycle of sensible heat flux and temperature. The difference in precipitation between the two schemes is not as clear as the temperature difference because the impact of changing Ch is not local. [ABSTRACT FROM AUTHOR]