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The land–atmosphere interactions play an important role in modulating climate variability at different spatial and temporal scales. In South America, two recognized hot spots of soil moisture–atmosphere coupling are located in southeastern South America (SESA) and eastern Brazil. Soil moisture variability may not only alter the climate locally but may also have nonlocal impacts through changes in the regional circulation. Here we explore how these two local coupling hot spots interact with each other, how soil moisture variability modulates the regional circulation, and what is the consequent nonlocal impact on precipitation. To this end, we analyze numerical experiments, performed with a regional climate model for the period October–March of 1983–2012, that allow us to isolate the influence of the soil moisture interannual variability on the regional climate. When the soil moisture–atmosphere interaction is enabled, we find a nonlocal coupling mechanism that links both hot spots at different temporal scales, favoring precipitation in eastern Brazil to the detriment of the precipitation in SESA through shifts in the regional circulation, when compared with a simulation with constrained soil moisture–atmosphere interaction. In northeastern Argentina, a subregion of SESA located at the exit of the South American low-level jet, it was found that the amount of nighttime precipitation is modulated by the proposed nonlocal coupling mechanism. A better understanding of the variability of precipitation due to the influence of land–atmosphere interaction processes may contribute to improving the predictability of precipitation and the interpretation of climate projections. [ABSTRACT FROM AUTHOR]

The pan-African Great Green Wall for the Sahara and the Sahel initiative (GGW) is a reforestation program to reverse the degradation of land. We investigate characteristics of mean precipitation due to proposed land-use changes to woody savannah with three hypothetical courses of the GGW, with an area between 0.8 and 1.25 million km2, and between the 100- and 400-mm isohyets. The global Model for Prediction Across Scales (MPAS) was applied for this investigation, employing ensembles with 40 members for the rainy season from June to September and 50 members for August when precipitation is at its peak. In comparison with the observational reference, the results show that a wet bias on the order of 33% in the eastern Sahel and a moderate dry bias of −41% in the western Sahel are present in the MPAS simulations. Our simulations do not provide any significant evidence for GGW-induced changes in the characteristics of the summer precipitation, for positive changes within the Sahel supporting the forestation activities, or for potentially adverse changes in the neighboring regions. Changes are present at the regional scale, but they are not significant at the 5% level. Also, changes simulated for further hydrometeorological variables such as temperature, radiation fluxes, or runoff are comparatively small. [ABSTRACT FROM AUTHOR]

We analyze the evolution of convective available potential energy (CAPE) and convective inhibition (CIN) in the days leading up to episodes of high CAPE in North America. The widely accepted theory for CAPE buildup, known as the advection hypothesis, states that high moist static energy (MSE) parcels of air moving north from the Gulf of Mexico become trapped under warm but dry parcels moving east from over elevated dry terrain. If and when the resulting CIN erodes, severe convection can occur due to the large energy difference between the boundary layer parcels and cool air aloft. However, our results, obtained via backward Lagrangian tracking of parcels at locations of peak CAPE, show that large values of CAPE are generated mainly via boundary layer moistening in the days leading up to the time of peak CAPE, and that a large portion of this moisture buildup happens on the day of peak CAPE. On the other hand, the free-tropospheric temperature above these tracked parcels rarely changes significantly over the days leading up to such occurrences. In addition, the CIN that allows for this buildup of CAPE arises mostly from unusually strong boundary layer cooling the night before peak CAPE, and has a contribution from differential advection of unusually warm air above the boundary layer to form a capping inversion. These results have important implications for the climatology of severe convective events, as it emphasizes the role of surface properties and their gradients in the frequency and intensity of high CAPE occurrences. Significance Statement: Severe convective events, such as thunderstorms, tornadoes, and hail storms, are among the most deadly and destructive weather systems. Although forecasters are quite good at predicting the probability of these events a few days in advance, there is currently no reliable seasonal prediction method of severe convection. We show that the buildup of energy for severe convection relies on both strong surface evaporation during the day of peak energy and anomalous cooling the night before. This progress represents a step toward understanding what controls the frequency of severe convective events on seasonal and longer time scales, including the effect of greenhouse gas–induced climate change. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is often referred to as 'the Third Pole' and plays an essential role in the global climate. However, it remains challenging for most global and regional models to realistically simulate the characteristics of climate over the TP. In this study, two Weather Research and Forecasting model (WRF) experiments using spectral nudging with gray-zone (GZ9) and convection-permitting (CP3) resolution are conducted for summers from 2009 to 2018. The surface air temperature (T2m) and precipitation from the two simulations and the global reanalysis ERA5 are evaluated against in-situ observations. The results show that ERA5 has a general cold bias over southern TP, especially in maximum T2m (Tmax), and wet bias over whole TP. Both experiments can successfully capture the spatial pattern and daily variation of T2m and precipitation, though cold bias for temperature and dry bias for precipitation exist especially over the regions south of 35° N. Compared with ERA5, the added value of the two WRF experiments is mainly reflected in the reduced cold bias especially for Tmax with more improvement found in CP3 and the reduced wet bias. However, the ability of the convection-permitting WRF experiment in improving the simulation of precipitation seems limited when compared to the gray-zone WRF experiment, which may be related to the biases in physical parameterization and lack of representativeness of station observation. Further investigation into surface radiation budget reveals that the underestimation of net shortwave radiation contributes a lot to the cold bias of T2m over the southeastern TP in GZ9 which is improved in CP3. Compared with GZ9, CP3 shows that larger specific humidity at low-level (mid-high level) coexists with more precipitation (clouds) over the southern TP. This improvement is achieved by better depiction of topographic details, underlying surface and atmospheric processes, land–atmosphere interactions and so on, leading to stronger northward water vapor transport (WVT) in CP3, providing more water vapor for precipitation at surface and much wetter condition in the mid-high level. [ABSTRACT FROM AUTHOR]

Tropical floodplains, such as Pantanal in Central South America, are important features for land-atmosphere interactions. Schemes to account for floodplains should therefore be included in Earth System Models, but this requires observations of flooded area for validation. Satellite data is a possible solution to estimate the flooded area but it is important to evaluate the different flood detection algorithms available in order to use the most efficient for the region. This work explores different methods to estimate the flooded area from the MODIS MOD09A1 satellite surface reflectance product using spectral indexes (mNDWI, NDMI, NDMI-NDVI) to detect the presence of water. We include the traditional threshold-based methods but also some unsupervised classification methods such as the k-means and the Principal Component Analysis applied on the water-related spectral indexes. The calibration and validation of these methods are based on the hydrological knowledge of the region, coming from land surface models, river discharge observation and from previous satellite estimations of the flooded area. The NDMI index seems too sensible to the vegetation which leads to error in the estimation of the flooded area. The other methods were spatially and temporally consistent with previous studies over the Pantanal. [ABSTRACT FROM AUTHOR]

Large-scale vegetation restoration profoundly affects ecohydrological and hydrometeorological processes with consequent effects on soil and water conservation. However, it is still unclear how revegetation affects the joint relationship between streamflow and sediment yield from the land-atmosphere interactions perspective. In this study, we combine in situ hydro-meteorological observations, satellite observed land surface characteristics, and coupled land-atmosphere model simulations to address this knowledge gap through a case study focusing on the Loess Plateau, where a megaproject of revegetation has been implemented since 2000. We find that historical annual streamflow and sediment yield have decreased over the Loess Plateau and 12 main revegetated basins, mainly due to enhanced canopy transpiration and soil conservation functions of revegetation. However, the magnitude of sediment yield reduction is much higher than that of streamflow for both mainstream and tributaries of the Yellow River. Specifically, the mean decreasing rate of sediment yield is 2.91 times of streamflow in the mainstream Yellow River, while for tributaries, the mean decline rate of sediment yield is 1.71 times of streamflow. Despite increases in total precipitation amount, erosive precipitation exhibits a clear downward trend over the Loess Plateau after the large-scale revegetation (2000–2015). This is mainly driven by enhanced local moisture recycling caused by revegetation-induced redistribution of water and energy budgets. Decreases in erosive precipitation frequency coupled with increased precipitation amount enhance streamflow availability and simultaneously mitigate soil erosion. Our findings highlight the importance of factoring in the two-way feedbacks between revegetation and erosive precipitation when planning soil and water conservation. [ABSTRACT FROM AUTHOR]

Land evapotranspiration has a notable impact on the continental precipitation of India during monsoons. Given the heterogeneous land use and climate, India hosts many transition zones, which are hotspots for land-atmosphere interactions. This work aims to study the soil moisture-precipitation feedbacks over India by quantifying recycled precipitation using the Eulerian water vapor-tagging technique incorporated in the Weather Research and Forecasting model. Eulerian vapor tagging techniques provide the most accurate information on recycled precipitation. We tracked the vapor originating at two spatial scales—entire India and six homogeneous monsoon regions. The latter analysis is conducted to assess inter-regional vapor exchanges. In this process, we determined the seasonal, monthly, and diurnal variations of recycling ratio and assessed its behavior during active and monsoon break periods. We considered three contrasting monsoon seasons (surplus, normal, and deficit rainfall years) for analysis. Results show a high recycling ratio in Central India, Gangetic plain, and Northeast India. Recycling ratio increases with monsoon progression and peaks in September (∼0.30). The Himalaya and transient low-pressure systems originating from the Bay of Bengal are vital for precipitation recycling in India. The contrasting monsoons exhibit changes in recycling ratio only at monthly scale. Regional analysis indicates West Central India is the most significant vapor contributor, while Northeast India is the highest recipient of recycled precipitation. High recycling (∼20%) shifts from central India during the active period to the foothills of Himalaya during the break period. Diurnal scale analysis reveals high afternoon recycling due to enhanced convective activity. [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]

Measurements of atmosphere-surface exchange are largely limited by the availability of fast-response gas analyzers; this limitation hampers our understanding of the role of terrestrial ecosystems in atmospheric chemistry and global change. Current micrometeorological methods, compatible with slow-response gas analyzers, are difficult to implement, or rely on empirical parameters that introduce large systematic errors. Here, we develop a new micrometeorological method, optimized for slow-response gas analyzers, that directly measures exchange rates of different atmospheric constituents, with minimal requirements. The new method requires only the sampling of air at a constant rate and directing it into one of two reservoirs, depending on the direction of the vertical wind velocity. An integral component of the new technique is an error diffusion algorithm that minimizes the biases in the measured fluxes and achieves direct flux estimates. We demonstrate that the new method provides an unbiased estimate of the flux, with accuracy within 0.1% of the reference eddy covariance flux, and importantly, allows for significant enhancements in the signal-to-noise ratio of measured scalars without compromising accuracy. Our new method provides a simple and reliable way to address complex environmental questions and offers a promising avenue for advancing our understanding of ecological systems and atmospheric chemistry. • New method for atmospheric exchange measurements with slow-response gas analyzers. • Minimal implementation requirements similar to relaxed eddy accumulation. • Error diffusion algorithm developed to minimize flux biases to less than 0.1%. • Enables increasing the signal-to-noise ratio without losing accuracy. [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]

• Study on forest heterogeneity's impact on water/energy partitioning in boreal forest. • A process-based model and local forcing were used to quantify land-surface fluxes. • Soil water content dynamic is shaped by physiographic factors and less by climate. • An insightful case study on CLASS's local-scale physical processes reliability. • Total evapotranspiration stays uniform but shows great variation in its partitioning. High latitude regions, including the circumpolar boreal biome, are experiencing important changes in the availability of usable surface water because of climate change. In this context, an adequate representation of the land-atmosphere interaction is critical to ensure optimal management of current and future water resources, forest management, and climate prediction. However, the task is particularly intricate in high-latitude boreal forest, as land surface model faces several challenges due to the unique environmental conditions and ecological characteristics. The objective of this study is to quantify the impact of forest landscape heterogeneity, specifically stand leaf-area index (LAI), soil texture, and drainage regime, on surface water and energy balance in a small boreal high-latitude sub-catchment. To this end, hydrometeorological conditions at seventeen 20×20 m plots in a 1-km2 boreal forest sub-basin are simulated using the Canadian Land Surface Scheme (CLASS), a land surface model, at the point scale. The subplot-scale soil texture, drainage regime, and vegetation characteristics and type are based as closely as possible on field measurements and observations for the 17 plots. The model-driven experiment comprises two sets of simulations using CLASS, each employing the same model setup and run for the 17 experimental plots. The main set employs meteorological forcing from a local micrometeorological tower within the sub-basin to investigate the plot-to-plot variability of albedo, energy fluxes, and soil state variables. A second set of simulations is conducted using meteorological forcing from the ERA5-Land reanalysis, which spans from 1986 to 2022. This data provides a longer time series, enabling a more accurate representation of the interannual climatic variability in the sub-basin. The results of the main and secondary sets of CLASS simulations are used to assess the plot-to-plot and temporal variability of several key hydrometeorological variables by calculating a monthly spread. In brief, the following conclusions and broader implications can be drawn from the findings: i) The simulated total annual evapotranspiration remains relatively uniform between plots despite notable variation in its partitioning from plot to plot. ii) In the presence of a full snowpack, the albedo exhibits substantial heterogeneity at the subplot scale, linked to the canopy's LAI. iii) Local soil properties, drainage regime, and vegetation structure and type exhibit substantial influence on the plot-to-plot variability in soil water content. iv) When parameterized with localized observations and measurements, CLASS can represent and be responsive to the complex dynamics of energy and water fluxes at the plot scale within the heterogeneous surface of boreal forests. [ABSTRACT FROM AUTHOR]

Abstract Diverse urban‐induced rainfall anomalies across different cities highlight the need for additional insights into land‐atmosphere interactions over complex urban environments. Based on empirical analyses of 144 warm‐season storms and high‐resolution numerical simulations over Nanjing, China, we show divergent patterns of urban‐induced rainfall anomalies for storms with contrasting synoptic conditions, despite of rainfall enhancement over downtown from a climatological perspective. We propose two simple gage‐based metrics to characterize both the thermal and turbulent conditions in pre‐storm environment, and classify storms into different groups. Our results show that elevated rainfall magnitudes and heavy rainfall frequency are equally expected in either downtown or suburb regions (upwind or downwind). This is mainly dictated by the relative dominance of urban‐induced thermal perturbations and mechanical turbulence (i.e., related to surface roughness) under different synoptic conditions. We develop four paradigms of urban rainfall modification, and thus provide a predictive understanding of rainfall anomalies in urban environments.

Recent studies using global climate models have suggested that irrigation, assuming unlimited water supply and that all crops can be irrigated, may be an option for regional cooling in southeast Australia. In this paper, using idealised simulations, we aim to quantify the maximum possible benefits of irrigation in southeast Australia during a record breaking summer. By limiting the amount of irrigation applied to the actual amount used, and only to areas which are equipped for it, our study provides much needed practical context on the maximum potential benefits of irrigation for southeast Australia. We conduct simulations with the Weather Research and Forecasting regional atmospheric model to investigate the sensitivity to both land surface models and irrigation parameters (start hour, duration and frequency). All simulations used the same total amount of irrigation water. Our results show that irrigation could potentially reduce the mean seasonal maximum temperature during the Angry summer of 2012/2013 by −1.44°C to −2.13°C over irrigated regions. Maximum possible cooling was achieved by applying irrigation during the middle of the day, over 4 h, with daily application. During early hours of the morning, increasing the number of hours that irrigation is on has little to no effect on maximum cooling, but longer duration of irrigation later during the day leads to larger cooling. Similar results were found when decreasing irrigation frequency. The amount of cooling was strongly dependent on the land surface model, with use of the CLM model resulting in 2.32 to 2.66 times more cooling as compared to the Noah and Noah-MP land surface models, highlighting the importance of using multiple land surface models. Our results also highlight that considering realistic irrigation volumes and equipped-areas leads to cooling benefits that are largely local, and studies using global models that do not take this into consideration are likely over-estimating the potential cooling benefits of irrigation.

Comparison of the profiler HT ht to that from radiosonde data in Fig. Figure 1 shows the synoptic-forcing terms in the equation for HT ht time tendency, 1 HT ht Graph where HT ht represents CBL growth due to entrainment and the last two terms represent horizontal advection, assuming HT ht is parallel to the plane described by the three sounding sites. 11 of LeMone et al. ([2]) confirms strong subsidence starting around 1700 UTC (1100 LST), with HT ht decreasing with time between 1630 and 1900 UTC. [Extracted from the article]

Knowledge of the difference between soil and air temperatures (ΔT) is helpful to improve our understanding on the land‐atmosphere thermal interactions and temperature‐dependent soil processes. Based on 272 stations across China, this study investigated the spatiotemporal variations of the annual and seasonal ΔT (difference between soil temperature at a depth of 0.4 m and air temperature) from 1981 to 2014, and quantified the relative contributions of multiple environmental variables (snow cover, precipitation, vegetation, soil moisture, and solar radiation) to ΔT variation for the first time. Air temperature primarily controls soil temperature dynamics, but the asynchronous trends of soil and air temperatures may lead to the complexity of the land‐atmosphere relationship. Almost no apparent trends in ΔT were detected for the entire China (except in summer), but the spatial heterogeneity of trends was evident. Snow cover conditions greatly dominated the ΔT dynamics both annually and seasonally (except in summer). The relative contribution of snow cover duration to ΔT variation was significantly greater than that of mean snow depth for the entire China, but the regional differences in the contributions of the two variables were noticeable at different seasons. The greening of vegetation closely associated with the ΔT variation in annual, autumn and winter, and soil moisture exerted a great influence on summer ΔT, associated with sunshine duration (a proxy for surface solar radiation). The amount of precipitation made a slight impact on ΔT at either seasonal or annual scales. [ABSTRACT FROM AUTHOR]

We implement the GEOS-Chem chemistry module as a chemical mechanism in version 2 of the Community Earth System Model (CESM). Our implementation allows the state-of-the-science GEOS-Chem chemistry module to be used with identical emissions, meteorology, and climate feedbacks as the CAM-chem chemistry module within CESM. We use coupling interfaces to allow GEOS-Chem to operate almost unchanged within CESM. Aerosols are converted at each time step between the GEOS-Chem bulk representation and the size-resolved representation of CESM's Modal Aerosol Model (MAM4). Land-type information needed for dry-deposition calculations in GEOS-Chem is communicated through a coupler, allowing online land–atmosphere interactions. Wet scavenging in GEOS-Chem is replaced with the Neu and Prather scheme, and a common emissions approach is developed for both CAM-chem and GEOS-Chem in CESM. We compare how GEOS-Chem embedded in CESM (C-GC) compares to the existing CAM-chem chemistry option (C-CC) when used to simulate atmospheric chemistry in 2016, with identical meteorology and emissions. We compare the atmospheric composition and deposition tendencies between the two simulations and evaluate the residual differences between C-GC and its use as a stand-alone chemistry transport model in the GEOS-Chem High Performance configuration (S-GC). We find that stratospheric ozone agrees well between the three models, with differences of less than 10 % in the core of the ozone layer, but that ozone in the troposphere is generally lower in C-GC than in either C-CC or S-GC. This is likely due to greater tropospheric concentrations of bromine, although other factors such as water vapor may contribute to lesser or greater extents depending on the region. This difference in tropospheric ozone is not uniform, with tropospheric ozone in C-GC being 30 % lower in the Southern Hemisphere when compared with S-GC but within 10 % in the Northern Hemisphere. This suggests differences in the effects of anthropogenic emissions. Aerosol concentrations in C-GC agree with those in S-GC at low altitudes in the tropics but are over 100 % greater in the upper troposphere due to differences in the representation of convective scavenging. We also find that water vapor concentrations vary substantially between the stand-alone and CESM-implemented version of GEOS-Chem, as the simulated hydrological cycle in CESM diverges from that represented in the source NASA Modern-Era Retrospective analysis for Research and Applications (Version 2; MERRA-2) reanalysis meteorology which is used directly in the GEOS-Chem chemistry transport model (CTM). Our implementation of GEOS-Chem as a chemistry option in CESM (including full chemistry–climate feedback) is publicly available and is being considered for inclusion in the CESM main code repository. This work is a significant step in the MUlti-Scale Infrastructure for Chemistry and Aerosols (MUSICA) project, enabling two communities of atmospheric researchers (CESM and GEOS-Chem) to share expertise through a common modeling framework, thereby accelerating progress in atmospheric science. [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]

Drought can develop rapidly over a short period, the so‐called "flash drought". The widely used standardized precipitation evapotranspiration index (SPEI), with traditional time scales longer than 1 month, cannot easily capture flash drought signals. Here, the SPEI with a 5‐day (pentad) time scale was proposed to investigate flash droughts in China from 1980 to 2017. New criteria for flash droughts based on the high‐resolution index were also developed. Flash droughts were stronger and longer in western and northern China. The intensity and duration of mild, moderate, and severe flash droughts increased during the study period, while severe flash droughts showed the largest increase. The high‐resolution SPEI permits us to examine the process of a drought event, that is, how a mild flash drought develops into a severe flash drought. The contribution of precipitation deficit to the duration of mild flash droughts was 50%. As the intensity of flash droughts increased, the contribution of high temperature and increased net radiation to flash drought duration increased from 50% (mild flash droughts) to 74% (severe flash droughts). When flash droughts occurred, Northwestern China and Southwestern China were dominated by unusually weak water vapor transport, while Northeastern China, Northern China, Southern China ,and Middle‐Lower Yangtze were mainly dominated by abnormal downward motion. The downward motion was generally accompanied by clear sky conditions with fewer clouds, higher air temperature, and higher surface solar radiation, which accelerated and amplified flash droughts triggered by initial precipitation deficits. Plain Language Summary: In recent years, a rapidly developing drought has attracted widespread attention, and it is known as the "flash drought". However, existing drought indices do not capture the signals of flash drought event life cycles. In this study, the existing drought index (SPEI) was upgraded to a higher temporal resolution to explore the spatial distribution and temporal changes in flash droughts in China. The results showed that the flash drought was intense and long‐lasting in western and northern China. In the past 38 yr, flash droughts have become more intense and more difficult to recover from, especially severe flash droughts. As the intensity of flash droughts increased, the impact of precipitation decreased, while temperature and net radiation gradually played leading roles. Flash droughts in Northwestern China and Southwestern China were mainly related to weak water vapor transport, while they were affected by strong downward motion in Northeastern China, Northern China, Southern China, and Middle‐Lower Yangtze. The downward motion was generally accompanied by clear sky conditions with fewer clouds, higher air temperature, and higher surface solar radiation, which accelerated and amplified flash droughts triggered by initial precipitation deficits. Key Points: A high temporal resolution drought index and new criteria were developed to identify flash droughts over ChinaThe intensity and duration of the flash drought increased significantly from 1980 to 2017 over China, especially the severe flash droughtThe precipitation deficit initiated a mild flash drought, and interactions with air temperature and net radiation amplified the drought intensity [ABSTRACT FROM AUTHOR]

Future projections of global meteorological drought are evaluated in the Multi‐Model Large Ensemble Archive, including an evaluation of the atmospheric moisture budget, conditioned on drought years. Drought is defined as 5‐year running‐mean annual precipitation below some threshold, for example, 10th percentile. Drought increases in frequency over the subtropics, in addition to certain tropical regions, consistent with previous studies. The moisture‐budget decomposition allows drought to be defined as mean‐flow, eddy, or feedback droughts, depending on which term in the equation contributes the largest negative interannual anomaly. In the historical climate, mean‐flow droughts constitute most droughts at low latitudes; eddy droughts are equally common at higher latitudes; feedback droughts (i.e., droughts exacerbated by land–atmosphere feedbacks) constitute almost all droughts in water‐limited subtropical/Mediterranean regions. The future drought increases are predominantly due to increases in feedback droughts in regions where these droughts are common historically but also over the Amazon. However, over most Mediterranean‐type regions mean‐flow droughts are also large contributors, resulting from dynamics. Eddy droughts also contribute to future increases along the equatorward flanks of historical eddy‐driven jets, likely reflecting poleward shifts therein. Model uncertainty is particularly large over the Amazon and Australia, a reflection of model diversity in processes associated with land‐atmosphere interaction. Based on these results, an availability of 3‐D atmospheric data from a wider swath of global climate model large ensembles could help constrain global drought projections based on the representation of drought mechanisms in the historical climate. Plain Language Summary: Around the globe, drought is projected to intensify and increase in frequency in the future. However, the mechanisms by which drought increases have not been shown from a global perspective. Here we show that drought, defined as a 5‐year period of extremely low precipitation, may fall under three categories. One is where the monthly average conditions in the atmosphere are conducive to drought; one is where there is an absence of individual storms over some region that depends on isolated events for its annual precipitation; one is where drought is made worse by a drying of the surface, which in turn further dries the atmosphere. In the future, climate models project an increase of drought mostly over regions where historically the latter category is prevalent. However, there are large disagreements between climate models over these regions, particularly over the Amazon and Australia. This reflects disagreements between the models in the interaction between the atmosphere and the Earth's surface. The results of this study help us to understand how climate models agree/disagree on drought intensification and why. Key Points: Multiple single‐model large ensembles can assess low‐frequency meteorological drought projections and model uncertainty thereinDroughts over global land increase mostly in regions where land‐atmosphere feedbacks exacerbate droughtModel uncertainty is largest in the Amazon and Australia, due to land‐atmosphere feedbacks and changes to atmospheric circulation [ABSTRACT FROM AUTHOR]

Land biosphere processes are of central importance to the climate system. Specifically, ecosystems interact with the atmosphere through a variety of feedback loops that modulate energy, water, and CO2 fluxes between the land surface and the atmosphere across a wide range of temporal and spatial scales. Human land use and land cover modification add a further level of complexity to land–atmosphere interactions. Dynamic global vegetation models (DGVMs) attempt to capture land ecosystem processes and are increasingly incorporated into Earth system models (ESMs), which makes it possible to study the coupled dynamics of the land biosphere and the climate. In this work we describe a number of modifications to the LPJ-GUESS DGVM, aimed at enabling direct integration into an ESM. These include energy balance closure, the introduction of a sub-daily time step, a new radiative transfer scheme, and improved soil physics. The implemented modifications allow the model (LPJ-GUESS/LSM) to simulate the diurnal exchange of energy, water, and CO2 between the land ecosystem and the atmosphere and thus provide surface boundary conditions to an atmospheric model over land. A site-based evaluation against FLUXNET2015 data shows reasonable agreement between observed and modelled sensible and latent heat fluxes. Differences in predicted ecosystem function between standard LPJ-GUESS and LPJ-GUESS/LSM vary across land cover types. We find that the emerging ecosystem composition and carbon fluxes are sensitive to both the choice of stomatal conductance model and the response of plant water uptake to soil moisture. The new implementation described in this work lays the foundation for using the well-established LPJ-GUESS DGVM as an alternative land surface model (LSM) in coupled land–biosphere–climate studies, where an accurate representation of ecosystem processes is essential. [ABSTRACT FROM AUTHOR]

The Earth's land surface features spatial and temporal heterogeneity over a wide range of scales below those resolved by current Earth system models (ESMs). State-of-the-art land and atmosphere models employ parameterizations to represent their subgrid heterogeneity, but the land–atmosphere coupling in ESMs typically operates on the grid scale. Communicating the information on the land surface heterogeneity with the overlying atmospheric boundary layer (ABL) remains a challenge in modeling land–atmosphere interactions. In order to account for the subgrid-scale heterogeneity in land–atmosphere coupling, we implement a new coupling scheme in the Energy Exascale Earth system model version 1 (E3SMv1) that uses adjusted surface variances and covariance of potential temperature and specific water content as the lower boundary condition for the atmosphere model. The new lower boundary condition accounts for both the variability of individual subgrid land surface patches and the inter-patch variability. The E3SMv1 single-column model (SCM) simulations over the Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) site were performed to assess the impacts. We find that the new coupling parameterization increases the magnitude and diurnal cycle of the temperature variance and humidity variance in the lower ABL on non-precipitating days. The impacts are primarily attributed to subgrid inter-patch variability rather than the variability of individual patches. These effects extend vertically from the surface to several levels in the lower ABL on clear days. We also find that accounting for surface heterogeneity increases low cloud cover and liquid water path (LWP). These cloud changes are associated with the change in cloud regime indicated by the skewness of the probability density function (PDF) of the subgrid vertical velocity. In precipitating days, the inter-patch variability reduces significantly so that the impact of accounting for surface heterogeneity vanishes. These results highlight the importance of accounting for subgrid heterogeneity in land–atmosphere coupling in next-generation ESMs. [ABSTRACT FROM AUTHOR]

In the present study, the structures and mechanisms of the heatwaves (HWs) associated with the quasi-biweekly (QBW; 10–20-day period) variability (QBW-HW) over southern China (SC; 106°–120°E, 21°–30°N) are investigated by using observation data from surface stations in China and the related gridded dataset (CN05.1), and the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis. We found that the strongest anticyclonic anomaly and subsidence appear over SC during the developing phase of QBW-HW, and then induced excess solar radiation at surface and significant diabatic heating lead to a positive surface air temperature change, thus favoring occurrence of QBW-HW over SC. In addition, we found a wet near-surface atmosphere in the QBW-HW events over SC, and further confirmed that near-surface moisture should play an important role in the occurrence of QBW-HW, via absorptions of longwave and shortwave radiation. This result is quite different from previous studies since they did not pay attention to the near-surface moisture. On the other hand, warmer SAT favors more water vapor evaporated from the moist soil when considering the Clausius–Clapeyron relationship. Then, the positive feedback processes promote the occurrence of QBW-HW over SC. In contrast, during the developing and warm phases of QBW-HW over SC, except for the near-surface level, the troposphere is in a dry condition, even at 850 and 700 hPa. In the QBW-HW events over SC, the factor responsible for the wet near-surface atmosphere is the enhanced surface evaporation, which is attributed to strengthened surface wind speed and background moist soil. Significance Statement: Under the background of global warming, heatwaves over Southern China are experiencing an increasing trend. In this study, we want to understand the structures and mechanisms of the heatwaves related to 10–20-day (quasi-biweekly) variability. We that found some structures of heatwaves (e.g., anticyclonic anomalies along with subsidence) are consistent with previous studies. In addition, we also show that the moist soil and increased induced near-surface moisture play a key role in the occurrence of heatwaves over Southern China, via enhanced absorptions of longwave and shortwave radiation. This study is helpful for understanding the processes and prediction of heatwaves over Southern China. Future work should examine the findings by some numerical experiments with a climate model. [ABSTRACT FROM AUTHOR]

Extreme heat events are a threat to human health, productivity, and food supply, so understanding their drivers is critical to adaptation and resilience. Anticyclonic circulation and certain quasi-stationary Rossby wave patterns are well known to coincide with heatwaves, and soil moisture deficits amplify extreme heat in some regions. However, the relative roles of these two factors in causing heatwaves is still unclear. Here we use constructed circulation analogs to estimate the contribution of atmospheric circulation to heatwaves in the United States in the Community Earth System Model version 1 (CESM1) preindustrial control simulations. After accounting for the component of the heatwaves explained by circulation, we explore the relationship between the residual temperature anomalies and soil moisture. We find that circulation explains over 85% of heatwave temperature anomalies in the eastern and western United States but only 75%–85% in the central United States. In this region, there is a significant negative correlation between soil moisture the week before the heatwave and the strength of the heatwave that explains additional variance. Further, for the hottest central U.S. heatwaves, positive temperature anomalies and negative soil moisture anomalies are evident over a month before heatwave onset. These results provide evidence that positive land–atmosphere feedbacks may be amplifying heatwaves in the central United States and demonstrate the geographic heterogeneity in the relative importance of the land and atmosphere for heatwave development. Analysis of future circulation and soil moisture in the CESM1 Large Ensemble indicates that, over parts of the United States, both may be trending toward greater heatwave likelihood. [ABSTRACT FROM AUTHOR]

The land–atmosphere interactions play an important role in the South American climate system. Previous studies have explored the coupling between soil moisture (SM), surface heat fluxes and atmospheric variables such as temperature and precipitation; however, the SM–precipitation feedback is still debated, especially at the diurnal scale. We computed three diurnal local coupling diagnostics between spatial, temporal and heterogeneity morning SM anomalies and the occurrence of afternoon precipitation events. We analyse South America in the period October–March 1983–2012 with the ERA5 reanalysis and the RCA4 regional climate model. Two 30‐year climate simulations are performed: a control and an uncoupled simulation where the SM is prescribed with daily climatological values, limiting the SM–atmosphere interaction. Comparing both simulations we isolate the effect of SM variability, allowing us to confirm that the diagnostics are indeed showing the contribution of the SM–precipitation coupling. We test different methods of calculating the morning SM anomalies and observe that all diagnostics show some methodological sensitivity, especially the spatial and temporal diagnostics. Despite the differences, in eastern Brazil we find a preference for afternoon precipitation to develop when the soil is wetter and heterogeneous, over points that are wetter than their surroundings. Towards southeastern South America, there is a spatial and temporal preference for drier or average conditions, depending on the method, with heterogeneity preference, and the same is observed in southwestern Amazonia in RCA4. Ultimately, it is important that future studies disentangle the spatiotemporal coupling mechanisms that may act simultaneously into its distinct components to avoid erroneous assumptions and contradictory results. [ABSTRACT FROM AUTHOR]

• Proposed an extended change detection methodology for soil moisture retrieval of croplands using Dual-pol Radar Vegetation Index for GRD data, DpRVIc. • DpRVIc outperforms NDVI for soil moisture estimation over croplands and shrublands. • Provides new insights into using dual-pol GRD SAR data to retrieve soil moisture for vegetated soils, an important finding for future missions like NISAR and ROSE-L. Soil moisture is a critical land variable that controls the energy and mass balance in land–atmosphere interactions. Spaceborne Synthetic Aperture Radar (SAR) sensors offer an efficient way to map and monitor soil moisture because of their sensitivity towards the dielectric and geometric properties of the target. In addition, SAR acquisitions are weather-independent, providing a significant advantage over optical imaging during periods of cloud cover. However, vegetation cover makes these processes more complex and influences the interaction of SAR backscatter resulting from combined soil matrix and vegetation cover. Therefore, using SAR data, it is necessary to compensate for vegetation contribution in total backscatter while estimating soil moisture over the vegetated soil surface. This study presents a technique that utilizes a vegetation index derived from SAR data to generate high-resolution soil moisture maps. It is noteworthy that this proposed soil moisture retrieval method uses only the dual-polarimetric Ground Range Detected (GRD) SAR product, i.e., only backscatter intensities. Hence, the proposed method has a high potential for operational soil moisture monitoring globally. We validated over 34 soil moisture stations of the Texas Soil Observation Network (TxSON) using time-series Sentinel-1 SAR data. The Root Mean Square Error (RMSE) values for estimated volumetric soil moisture are within the range of 0.048 m3 m−3 to 0.055 m3 m−3 with the Pearson correlation coefficient r > 0.79. The code to generate DpRVI c in Google Earth Engine is available at: https://github.com/Narayana-Rao/dual_pol_descriptors. [ABSTRACT FROM AUTHOR]

Elevated atmospheric CO2 (eCO2) influences the carbon assimilation rate and stomatal conductance of plants, thereby affecting the global cycles of carbon and water. Yet, the detection of these physiological effects of eCO2 in observational data remains challenging, because natural variations and confounding factors (e.g., warming) can overshadow the eCO2 effects in observational data of real‐world ecosystems. In this study, we aim at developing a method to detect the emergence of the physiological CO2 effects on various variables related to carbon and water fluxes. We mimic the observational setting in ecosystems using a comprehensive process‐based land surface model QUINCY to simulate the leaf‐level effects of increasing atmospheric CO2 concentrations and their century‐long propagation through the terrestrial carbon and water cycles across different climate regimes and biomes. We then develop a statistical method based on the signal‐to‐noise ratio to detect the emergence of the eCO2 effects. The eCO2 effect on gross primary productivity (GPP) emerges at relatively low CO2 increase (∆[CO2] ~ 20 ppm) where the leaf area index is relatively high. Compared to GPP, the eCO2 effect causing reduced transpiration water flux (normalized to leaf area) emerges only at relatively high CO2 increase (∆[CO2] >> 40 ppm), due to the high sensitivity to climate variability and thus lower signal‐to‐noise ratio. In general, the response to eCO2 is detectable earlier for variables related to the carbon cycle than the water cycle, when plant productivity is not limited by climatic constraints, and stronger in forest‐dominated rather than in grass‐dominated ecosystems. Our results provide a step toward when and where we expect to detect physiological CO2 effects in in‐situ flux measurements, how to detect them and encourage future efforts to improve the understanding and quantification of these effects in observations of terrestrial carbon and water dynamics. [ABSTRACT FROM AUTHOR]

Compound drought and heatwaves (DHW) events have much attention due to their notable impacts on socio-ecological systems. However, studies on the mechanisms of DHW related to land-atmosphere interaction are not still fully understood in regional aspects. Here, we investigate drastic increases in DHW from 1980 to 2019 over northern East Asia, one of the strong land-atmosphere interaction regions. Heatwaves occurring in severely dry conditions have increased after the late 1990s, suggesting that the heatwaves in northern East Asia are highly likely to be compound heatwaves closely related to drought. Moreover, the soil moisture–temperature coupling strength increased in regions with strong increases in DHW through phase transitions of both temperature and heat anomalies that determine the coupling strength. As the soil moisture decreases, the probability density of low evapotranspiration increases through evaporative heat absorption. This leads to increase evaporative stress and eventually amplify DHW since the late 1990s. In particular, seasonal changes in soil moisture and evapotranspiration between spring and summer contributed to the amplification of DHW by enhancing land-atmosphere interaction. [ABSTRACT FROM AUTHOR]

Weather forecasting over complex terrain with diverse land cover is challenging. Utilizing the high-resolution observations from New York State Mesonet (NYSM), we are able to evaluate the surface processes of the Weather Research Forecast (WRF) Model in a detailed, scale-dependent manner. In the study, possible impacts of land–atmosphere interaction on surface meteorology and boundary layer cloud development are investigated with different model resolutions, land surface models (LSMs), and planetary boundary layer (PBL) physical parameterizations. The High-Resolution Rapid Refresh, version 3 (HRRR), forecasting model is used as a reference for the sensitivity evaluation. Results show that over complex terrain, the high-resolution simulations (1 km × 60 vertical levels) generally perform better compared to low-resolution (3 km × 50 levels) in both surface meteorology and cloud fields. LSMs play a more important role in surface meteorology compared to PBL schemes. The NoahMP land surface model exhibits daytime warmer and drier biases compared to the Rapid Update Cycle (RUC) due to better prediction of the Bowen ratio in RUC. The PBL schemes would affect the convective strength in the boundary layer. The Shin–Hong (SH) scale-aware scheme tends to produce the strongest convective strength in the PBL, while the ACM2 PBL scheme rarely resolved convection even at 1-km resolution. By considering the radiation effect of subgrid-scale (SGS) clouds, the Mellor–Yamada–Nakanishi–Niino eddy diffusivity mass flux (MYNN-EDMF) predicted the highest cloud coverage and lowest surface solar radiation bias. The configuration of SGS clouds in MYNN-EDMF would not only significantly reduce shortwave radiation bias, but also affect the convection behaviors through land surface–cloud–radiation interaction. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) possesses the largest cryosphere in the world outside of the Arctic and Antarctic, and is the source of nine major rivers in Asia. The surface environment of the TP has undergone significant changes against the background of global warming. It is projected that the continuation of climate change in the future will result in most of the glaciers and frozen soil disappearing by the end of this century, and freshwater resources will be greatly reduced, on which 22% of the world's population depends. These environmental changes are of great concern to global society given the influences of the TP on the climate at the global scale. However, great uncertainties exist in global climate simulations over the TP, which affects our ability to properly understand the associated water security crisis. Based on atmospheric dynamics and physical processes, dynamical downscaling can characterize surface conditions more accurately than global simulations, and better simulate and predict regional or local weather and climate situations. With advances in supercomputing, the grid spacing of dynamical downscaling simulations has been continuously increasing, marching the technique into the kilometer-scale era. In this paper, the origin and development of dynamical downscaling in the TP region from the quarter-degree to kilometer scale is firstly introduced, including an assessment of the advantages and disadvantages of dynamical downscaling at the kilometer scale over the TP. Then, the main land surface factors affecting the performance of dynamical downscaling over the TP are described, as well as a brief introduction to a land surface model with specific plateau characteristics. Specifically, it has emerged that perfecting the land surface model and improving the performance of land-atmosphere interaction are the most effective ways to advance the performance of dynamic downscaling in this region. Finally, the challenges and some recommended future research directions are discussed and proposed. [ABSTRACT FROM AUTHOR]

Root-zone soil moisture (RZSM) is an important variable in land–atmosphere interactions, notably affecting the global climate system. Contrary to satellite-based acquisition of surface soil moisture, RZSM is generally obtained from model-based simulations. In this study, in situ observations from the Naqu and Pali networks that represent different climatic conditions over the Tibetan Plateau (TP) and a triple collocation (TC) method are used to evaluate model-based RZSM products, including Global Land Evaporation Amsterdam Model (GLEAM) (versions 3.5a and 3.5b), Global Land Data Assimilation System (GLDAS) (versions 2.1 and 2.2), and the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis (ERA5). The evaluation results based on in situ observations indicate that all products tend to overestimate but could generally capture the temporal variation, and ERA5 exhibits the best performance with the highest R (0.875) and the lowest unbiased RMSE (ubRMSE; 0.015 m3 m−3) against in situ observations in the Naqu network. In the TC analysis, similar results are obtained: ERA5 has the best performance with the highest TC-derived R (0.785) over the entire TP, followed by GLEAM v3.5a (0.746) and GLDAS-2.1 (0.682). Meanwhile, GLEAM v3.5a and GLDAS-2.1 outperform GLEAM v3.5b and GLDAS-2.2 over the entire TP, respectively. Besides, possible error causes in evaluating these RZSM products are summarized, and the effectiveness of TC method is also evaluated with two dense networks, finding that TC method is reliable since TC-derived R is close to ground-derived R, with only 6.85% mean relative differences. These results using both in situ observations and TC method may provide a new perspective for the soil moisture product developers to further enhance the accuracy of model-based RZSM over the TP. Significance Statement: The purpose of this study is to better understand the quality and applicability of GLEAM, GLDAS, and ERA5 RZSM products over the TP using both in situ observations and the triple collocation (TC) method, making it better applied to climate and hydrological research. This study provides four standard statistical metrics evaluation based on in situ observations, as well as the reliable metric, that is, correlation coefficient (R) derived from TC method, and highlights that TC-based evaluation could supplement the ground-based validation, especially over the data-scarce TP region. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is an atmosphere-land interaction, which represents the first thermal reaction of the environmental changes occurring in the earth surface, being one of the most important factors used in the earth sciences. Jazmourian basin, in the southeast of Iran, is a fertile agricultural land with diverse topography and unique climatic conditions. Due to its significance as one of the most important agricultural poles of Iran, the LST variations are of great interest due to their high impact on the environmental processes, especially in the land cover. In recent years, Moderate Resolution Imaging Spectroradiometer images have been extensively used to estimate the LST due to their spatial and temporal homogeneity and freely available showing improved capabilities of climate analysis in the areas with scarce observation networks. We used a combination of MOD11C3 and MYD11C3 products of daytime and nighttime LST, covering the complete circadian cycle over Jazmourian basin, from 2003 to 2019. Results showed varied trends by months with a significantly positive increase in January. The spatial distribution revealed a generalized positive anomaly in the whole study area, with the highest values in central lowlands and lowest at eastern high elevations of the basin. The temporal and spatial analyses indicated high temperature differences between months and seasons as well as a wide range from −10°C to 65°C. [ABSTRACT FROM AUTHOR]

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Copyright of SDU Journal of Engineering Sciences & Design / Mühendislik Bilimleri ve Tasarım Dergisi is the property of Journal of Engineering Sciences & Design and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Extreme heat is investigated in a series of high‐resolution time‐slice global simulations comparing the current and late‐21st century climates. An increase in climate‐relative extreme heat is found in the region surrounding the Black Sea. Similarities between the synoptic‐scale flows in current and future heat events combined with a decrease in future summer precipitation suggests that the increased future severity stems from strengthened land‐atmosphere feedbacks driven primarily by the changes in precipitation. The resulting intensification of heat events beyond the mean warming driven by climate change could generate significant future heat hazards in vulnerable regions. Given the continental cool bias in the present‐day simulations, the resulting estimates of future extreme heat are likely to be conservative. Plain Language Summary: Increases in extreme heat are a direct consequence of global warming. In some regions, however, the frequency and severity of heat waves can exceed what is expected given the rise in mean temperature alone. We examine this issue using data from a high‐resolution climate model run for 10 simulated summers under current and future (late 21st century) climate conditions. In the future simulations, extreme heat events, relative to the baseline of a much warmer climate, become more frequent and severe in a region surrounding the Black Sea. The weather patterns that lead to heat waves are very similar in the current and future climates. This similarity suggests that land‐atmosphere interactions during atmospheric heat waves amplify these events more in the future. Under warmer baseline conditions, the land dries out more rapidly during a heat event, reducing cooling from evaporation, and thus creating more severe and dangerous heat. Additionally, these model simulations are too cold over land areas, likely weakening the land‐atmosphere interactions so our projections of increased extreme heat are probably conservative. Key Points: Climate‐relative extreme heat events in certain regions are substantially amplified in a set of high‐resolution future climate simulationsThis regional amplification of extreme heat does not depend on changes in flow regimesResults suggest amplified heat may be due to stronger regional/local land surface feedbacks, resulting in faster drying in a warmer climate [ABSTRACT FROM AUTHOR]

Heavy precipitation and associated flood hazards can cause enormous socioeconomic losses. The advances in atmospheric modeling enable great promise in accurately predicting precipitation. However, the representation of land‐atmosphere exchange processes in atmospheric models and its impacts on precipitation evolution remain high uncertainties. This study investigated the sensitivity of convective precipitation to land‐atmosphere exchanges and examined the improvements in precipitation simulations by a dynamic vegetation‐type‐dependent exchange scheme. We conducted 3‐km‐resolution convection‐permitting modeling for three heavy precipitation events that occurred over areas with different dominant land‐cover types. The results showed that land‐atmosphere exchange efficiency significantly altered the precipitation intensity as well as the onset and peak time of precipitation but hardly affected the precipitation pattern. Strong exchange simulations could agree better with the observed precipitation in the 21 July 2012 Beijing and the 19 June 2010 Jiangxi heavy precipitation events occurring over humid and semihumid zones, while weak exchange simulations could attain higher consistencies with the observations in the 30 July 2012 Ningxia heavy precipitation event occurring over arid and semiarid zones. As a more physical alternative, the dynamic exchange simulations could achieve the closest agreement with the field observations, especially the intensity and location of the heaviest rainfall. The dynamic scheme modifies land‐atmosphere exchange efficiency to match local land cover conditions and could provide promising applications in heavy precipitation modeling studies. Plain Language Summary: Over recent decades, the frequent occurrence of heavy precipitation events has caused devastating ecological and socioeconomic impacts, such as agriculture losses, infrastructure damage, and casualties. High‐resolution atmospheric modeling at a convection‐permitting grid spacing (≤4 km) provides valuable applications for predicting heavy precipitation. Precipitation can be strongly affected by the energy and moisture exchanges between land surface and atmosphere. However, the representation of land‐atmosphere interactions in atmospheric models and the responses of precipitation to land‐atmosphere exchange efficiency remain great uncertainties. This study performed 3‐km high‐resolution atmospheric modeling with a dynamic vegetation‐type‐dependent land‐atmosphere exchange scheme for three typical heavy precipitation events that occurred over areas with different dominant land‐cover types. The results showed that land‐atmosphere exchange efficiency mainly affected the precipitation intensity as well as the onset and peak time of precipitation. The dynamic exchange scheme modifies the efficiency of land‐atmosphere exchanges to match local land cover conditions and could reproduce well the field observations, especially the intensity and location of the heaviest rainfall which usually serve as the most concerned variable in a major rainstorm event. Our findings show that the dynamical scheme could help achieve more accurate precipitation simulations. Key Points: A dynamic vegetation‐type‐dependent land‐atmosphere exchange scheme was applied into convection‐permitting atmospheric modelsLand‐atmosphere exchange efficiency mainly affected the precipitation intensity as well as the onset and peak time of precipitationThe dynamic exchange simulations agreed well with the field observations, especially the intensity and location of the heaviest rainfall [ABSTRACT FROM AUTHOR]

Condensation and desublimation are important processes of nocturnal land–atmosphere interactions, energy transfer, and the water cycle, and have important ecological and hydrological roles in mitigating physiological water deficits caused by low temperatures and reducing the risk of frost damage to plants, animals, and microorganisms near the surface in the Alpine Region. The aim of the present study is to evaluate the spatial and temporal variations of condensation and desublimation from 1950 to 2020 based on Penman model using hourly ERA5-Land and ERA5 reanalysis datasets on the Qinghai–Tibet Plateau (QTP), where condensation and desublimation occur frequently but lack quantitative evaluation. The results showed that: (1) Condensation showed a decreasing trend from southeast to northwest, with annual mean condensation ranging from 0 mm to 72.8 mm, while desublimation showed regional enrichment rather than zonal variation, with the annual mean desublimation ranging from 0 mm to 23.6 mm; (2) At 95% confidence level, condensation showed a significant increasing trend in the central and western QTP, while desublimation showed a significant decreasing trend in most regions of the QTP, and the decreasing trend of desublimation was more obvious than the increasing trend of condensation; (3) Both condensation and desublimation showed significant seasonal characteristics; the maximum monthly condensation was 2.37 mm and the monthly mean condensation was 0.70 mm, while the maximum monthly desublimation was 1.45 mm and the monthly mean desublimation was 0.95 mm; (4) The annual mean condensation was 8.45 mm, with an increasing trend of 0.24 mm/10a, the annual mean desublimation was 11.45 mm, with a decreasing trend of −0.26 mm/10a, and the total annual mean condensation and desublimation was 19.89 mm, with a weak decreasing trend on the QTP; (5) The increase in condensation is most associated with the increase in precipitation, while the decrease in desublimation is most associated with the increase in air temperature on the QTP. [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]

Comprehensive characterization of turbulent fluxes and land‐atmosphere interactions at a semi‐arid region in the Deccan Plateau of peninsular India is presented using 2‐year eddy covariance measurements. Contrary to previously reported results over the Indian region, surface energy partitioning is more into sensible heat flux than latent heat flux, even during the monsoon season. Irrespective of the seasons, the soil moisture and its response to rainfall drive the land‐atmosphere interactions and along with the net radiation, play crucial roles in deciding the surface fluxes and its partitioning. Time series comparison with ERA5 reanalysis data reveals the inadequate representation of land‐atmosphere interactions in ERA5 reanalysis over the peninsular Indian region, particularly the intensity and duration of rainfall and the feedbacks of soil moisture to the atmosphere. The surface energy balance closure improves by ∼3% when the soil heat storage term is considered and is the highest when the height and scatter of the roughness elements around the measurement site are the lowest. The influence of rainfall on energy balance closure is lower as compared to land surface heterogeneity. The present study also fills an existing gap of validating the surface fluxes and its partitioning in ERA5 reanalysis in the tropics and will provide deeper insights on the land‐atmosphere interactions in tropical semi‐arid regions. Plain Language Summary: The interactions between the surface of the Earth and the atmosphere above it controls the weather and climate of a region to a large extent. Accurately capturing such interactions in weather and climate models is arduous due to (a) the limited measurements on the partitioning of solar energy that reaches the surface and (b) the surface heterogeneities. Such measurements over different terrains and its comparison with various global data sets are essential to improve the climate predictions. Making use of 2‐year observations, we report the anomalous partitioning of surface energy at a semi‐arid region in India and how the rainfall and soil moisture play crucial roles in regulating it. Large differences between the observations and a modeled data set in the duration and intensity of rainfall and the energy partitioning at the surface are delineated along with the significant influence of the vegetation and soil heat storage. These results will be helpful in improving the weather and climate model simulations over the semi‐arid regions in the tropics. Key Points: Contrary to previous reports over the Indian region, partitioning of surface fluxes is more to sensible heat flux than latent heat fluxMeasurements reveal large differences in the rainfall duration and intensity and land‐atmosphere interactions compared to reanalysis dataEnergy balance closure is inversely proportional to the height of the roughness elements and their scatter around the measurement site [ABSTRACT FROM AUTHOR]

Fog plays a vital role in maintaining ecosystems in montane cloud forests. In these forests, a large amount of water on the surface of leaves and canopy (hereafter canopy water) evaporates during the morning. This biophysical process plays a critical factor in regulating afternoon fog formation. Recent studies have found that alterations in precipitation, temperature, humidity, and CO2 concentrations associated with future climate changes may affect terrestrial hydroclimatology, but the responses in cloud forests remain unclear. Utilizing numerical experiments with the Community Land Model, we explored changes in surface evaporative fluxes in Chi-Lan Mountain cloud forests in northeastern Taiwan under the RCP8.5 scenario with changes in the aforementioned various atmospheric variables. The results showed that increased rainfall intensity in climate change runs decreased the accumulation of canopy water, while larger water vapor concentrations led to more nighttime condensation on leaves. Elevated CO2 concentrations did not greatly impact canopy water amounts, but photosynthesis was enhanced, while transpiration was reduced and contributed to decreased latent heat fluxes, implying the importance of forest plant physiology in modulating land evaporative fluxes. Evapotranspiration decreased in Chi-Lan due to multiple combined factors, in contrast to the expected intensification in the global water cycle under global warming. The study, however, is restricted to an offline land surface model without land–atmosphere interactions and the interactions with adjacent grids, which deserves further analyses for the water cycle changes in the montane cloud forest regions. [ABSTRACT FROM AUTHOR]

A new high-resolution Regional Earth System Model, namely ROM, has been implemented over CORDEX-SA towards examining the impact of air–sea coupling on the Indian summer monsoon characteristics. ROM's simulated mean ISM rainfall and associated dynamical and thermodynamical processes, including the representation of northward and eastward propagating convention bands, are closer to observation than its standalone atmospheric model component (REMO), highlighting the advantage of air–sea coupling. However, the value addition of air–sea coupling varies spatially with more significant improvements over regions with large biases. Bay of Bengal and the eastern equatorial Indian Ocean are the most prominent region where the highest added value is observed with a significant reduction up to 50–500% precipitation bias. Most of the changes in precipitation over the ocean are associated with convective precipitation (CP) due to the suppression of convective activity caused by the negative feedback due to the inclusion of air–sea coupling. However, CP and large-scale precipitation (LP) improvements show east–west asymmetry over the Indian land region. The substantial LP bias reduction is noticed over the wet bias region of western central India due to its suppression, while enhanced CP over eastern central India contributed to the reduction of dry bias. An insignificant change is noticed over Tibetan Plateau, northern India, and Indo Gangetic plains. The weakening of moisture-laden low-level Somalia Jets causes the diminishing of moisture supply from the Arabian Sea (AS) towards Indian land regions resulting in suppressed precipitation, reducing wet bias, especially over western central India. The anomalous high kinetic energy over AS, wind shear, and tropospheric temperature gradient in REMO compared to observation is substantially reduced in the ROM, facilitating the favourable condition for suppressing moisture feeding and hence the wet bias over west-central India in ROM. The warmer midlatitude in ROM than REMO over eastern central India strengthens the convection, enhancing precipitation results in reducing the dry bias. Despite substantially improved ROM'performance, it still exhibits some systematic biases (wet/dry) partially associated with the persistent warm/cold SST bias and land–atmosphere interaction. [ABSTRACT FROM AUTHOR]

This study investigates the contributing factors of East Asian heatwaves (EAHWs) linked to the Arctic-Siberian Plain (ASP) over the past 42 years (1979–2020). EAHWs are mainly affected by two time scales of variabilities: long-term externally forced and interannual variabilities. The externally forced EAHWs are attributed to the increasing global warming trend, while their interannual variability is related to the circumglobal teleconnection (CGT) and the ASP teleconnection patterns. In addition to the CGT, the Rossby wave energy originating from the ASP propagates to East Asia through the upper troposphere, amplifying the EAHWs. The stationary high pressure in the ASP is generated by vorticity advection in the upper troposphere. Enhanced surface radiative heating and evaporation on the ASP surface increase the specific humidity and temperature, amplifying the thermal high pressure via positive water vapor feedback. Thermal high-pressure amplified by land–atmosphere interactions in the ASP during the peak summer season leads to EAHWs by the propagation of stationary Rossby wave energy. The results indicate that our enhanced understanding of the ASP teleconnection can improve forecasting of the EAHWs not only on a sub-seasonal time scale but also in future projections of global climate models. [ABSTRACT FROM AUTHOR]

Despite some recent improvements, major deficiencies remain in model simulations using parameterised convection in capturing both the phase and amplitude of the daily cycle of precipitation in tropical regions. The difficulties are particularly acute in regions of heterogeneous surface conditions, since the simulations need not only to respond appropriately to the local forcing from surface fluxes but also to capture the interactions with near‐surface mesoscale circulations. Here, we examine such a situation by means of idealised cloud‐resolving simulations of deep convection over a heterogeneous surface, performed using the cloud‐resolving simulation known as the Met Office NERC Cloud model (MONC). In these simulations, we show that precipitation forms preferentially over dry and warm patches ("DRY") compared with wet and cold patches ("WET"), with the peak precipitation rates differing by a factor of approximately 4. The initiation of precipitation occurs approximately 1.5 hr earlier in the DRY patches compared with the WET patches. Moreover, within the WET and DRY patches there are marked differences in the spatial distribution of the precipitation. These cloud‐resolving simulations are then used as a benchmark to assess the behaviour of simulations using parameterised convection, performed using the idealised configuration of the Met Office Unified Model (MetUM). The MetUM simulations produce a response with some qualitative similarities to the cloud‐resolving simulations. In particular, although the simulations with parameterised convection initiate precipitation too early, they are capable of capturing the relative amounts of daily‐mean precipitation in the DRY and WET patches. We propose that the cloud‐resolving simulations could be used further to investigate the impact of fully interactive surface schemes and as benchmark simulations to evaluate new parameterisation schemes. [ABSTRACT FROM AUTHOR]

The diurnal variations of surface and air temperature are closely related, but their different responses to evaporative conditions can inform us about land–atmosphere interactions. Here, we evaluate the responses of the diurnal ranges in surface (ΔTs) and air (ΔTa) temperature to evaporative fraction at 160 FLUXNET sites and in the ERA5 reanalysis. We show that the sensitivity of ΔTs to evaporative fraction depends on vegetation type, whereas ΔTa does not. On days with low evaporative fraction, ΔTs in FLUXNET is enhanced by up to ∼20 K (∼30 K in ERA5) in short vegetation, but only by up to ∼10 K (∼10 K in ERA5) in forests. Note that ΔTa responds rather similarly to evaporative fraction irrespective of vegetation type (∼5 K in FLUXNET, ∼10 K in ERA5). We find a systematic bias in ERA5's ΔT response to evaporative conditions, showing a stronger sensitivity to evaporative fraction than in FLUXNET. We then demonstrate with a simple atmospheric boundary layer (SABL) model that the weak response of ΔTa to evaporative fraction can be explained by greater boundary layer growth under dry conditions, which increases the heat storage capacity and reduces the response of air temperature to evaporative fraction. Additionally, using a simplified surface energy balance (SSEB) model we show that ΔTs mainly responds to solar radiation, evaporative fraction, and aerodynamic conductance. We conclude that the dominant patterns of diurnal temperature variations can be explained by fundamental physical concepts, which should help us to better understand the main controls of land–atmosphere interactions. Significance Statement: Generally, air temperature is used more widely than the surface temperature, and often they are assumed to be equivalent. However, we show that their responses to changes in vegetation type and evaporative conditions are quite different. Using FLUXNET observations, ERA5 reanalysis, and two simple physical models, we found that these responses are much stronger in surface temperature, especially in short vegetation, and relatively weaker in air temperature. Despite being measured just 2 m above the surface, air temperature carries lesser imprints of evaporation and vegetation than the surface temperature because of boundary layer dynamics. These findings suggest the importance of coupled land–atmosphere processes in shaping surface and air temperature differently and provide insights on their distinctive responses to global changes. [ABSTRACT FROM AUTHOR]

Dynamical forecasting talks included IRI's calibrated subseasonal forecasts based on the Subseasonal Experiment (SubX; [8]) and calibrated seasonal forecasts based on the North American Multi-Model Experiment (NMME; [7]), which provide seamless prediction capabilities starting from 1 day to 6 months in advance. The low prediction skill of winter precipitation is attributed largely to model shortcomings in simulating the ENSO-independent, anomalous Pacific circulation, which is an important driver of year-to-year California precipitation variability. For drought preparedness, state and local water managers would like to rely on skillful forecasts on time scales that span the spectrum between weather forecasts and climate predictions. Keywords: Forecasting; Seasonal variability; Subseasonal variability; Communications/decision making; Decision support; Water resources EN Forecasting Seasonal variability Subseasonal variability Communications/decision making Decision support Water resources E2168 E2175 8 11/14/22 20221001 NES 221001 Virtual Workshop on Subseasonal to Seasonal Climate Forecasting for Water Management in the W... What: Scientists and stakeholders came together to discuss forecast priorities for western U.S. water resource management and to review existing and emerging methodologies that can improve prediction of precipitation, circulation regimes, and atmospheric rivers at lead times of weeks to months. [Extracted from the article]

Global monsoon system is a major component of the Earth's climate system and carries about two‐thirds of the world's population. How large‐scale deforestation induced changes in water cycle and energy balance may modify global monsoon system and its underlying mechanisms are not well understood. Here, we use simulations of 11 models participating in the Land Use Model Intercomparison Project in the framework of the Coupled Model Intercomparison Project, phase 6 to study the response of global monsoon precipitation and atmospheric circulation to large‐scale deforestation. Global deforestation of about 38% induces annual precipitation reduction of about −15.01 mm yr−1 (Multi‐Model Ensemble) in global monsoon regions and −26.15 mm yr−1 in land monsoon regions. The precipitation reduction is particularly pronounced in the Northern Hemisphere Summer Monsoon (NHSM) regions with decreased precipitation by 16.83 mm in the summer monsoon season from May to September along with weakened circulation intensity. Deforestation causes asymmetrical temperature response in the northern high latitudes and Southern Hemisphere Tropics, leading to decreased hemispheric thermal contrast, which reduces the meridional pressure gradient and weakens the convergence of cross‐equatorial flows into the NHSM trough regions, thereby decreasing the NHSM circulation and precipitation intensity. The deforestation‐induced hemispheric temperature asymmetry also increases the northward cross‐equatorial atmosphere heat transport (c‐eq AHT) that drives southward shift of Intertropical Convergence Zone, which suppresses the NHSM precipitation. Our results show that the drying monsoon region in response to deforestation is fairly consistent among the models implying the adverse effects of large‐scale deforestation beyond the region of land use change. Plain Language Summary: The global monsoon system carries about two‐thirds of the world's population. The changes in monsoon precipitation have enormous impacts on social and economic development over the monsoon regions. Human activities will change the characteristics of the land surface, and then affect the weather and climate through the process of land‐atmosphere interaction. Our work aims to study the impact of human activities such as large‐scale deforestation activities on global monsoon region, and its impact mechanism, which have not been systematically studied yet. Using multiple models participating in the Coupled Model Intercomparison Project, phase 6, our results show that large scale deforestation induces precipitation weakening of global Monsoon, particularly the Northern Hemisphere Summer Monsoon (NHSM). The different temperature response in the northern high latitudes and Southern Hemisphere tropics to deforestation cause hemispheric thermal contrast. This temperature asymmetry induces atmospheric energy asymmetry between the two hemispheres and drives the shifts of tropical rainbelt, there by suppressing the NHSM precipitation. Key Points: Deforestation induces circulation and precipitation weakening of global monsoon, particularly the Northern Hemisphere Summer Monsoon (NHSM)Deforestation‐induced hemispheric thermal asymmetry weakens the convergence of cross‐equatorial flows into the NHSM trough regionsHemispheric thermal asymmetry drives southward shift of the Intertropical Convergence Zone, thereby suppressing the NHSM precipitation [ABSTRACT FROM AUTHOR]

The highly interactive and variable nature of scales of space and time featured in components of the Earth system imparts enormous complexity to land‐atmosphere interactions. Here, we introduce an open special collection on Advances in Scaling and Modeling of Land‐Atmosphere Interactions that features articles in JGR: Biogeosciences, JGR: Atmospheres, Journal of Advances in the Modeling of Earth Systems, and Earth & Space Science. Collectively, these articles identify interactions across multiple processes, in field experiments, long‐term observations, and numerical simulations, which are then used to advance theories of scale interaction to improve predictive models. Plain Language Summary: Scale refers to the patterns in space and oscillations in time of features in our universe. The Earth system features a wide range of scales. Understanding the processes that explain the size, shape, regularity, and changes in those scales looms large in our science. Land‐atmosphere interaction refers to the ways that organisms and elements of the land surface influence the structure and evolution of the atmosphere and in turn, how weather and climate processes influence the ground. Numerous studies through coordinated field experiments and computer simulations have helped us advance understanding of how scale influences land‐atmosphere interaction. We introduce a special collection that documents many of those. Key Points: Scaling in space and time is an essential foundation for understanding land‐atmosphere interactionsA series of papers in this collection demonstrate scale‐related advances in a number of areasCoordination of research across disciplines is needed [ABSTRACT FROM AUTHOR]