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Land use changes have great potential to influence temperature extremes. However, contradictory summer daytime temperature responses to deforestation are reported between observations and climate models. Here we present a pertinent comparison between multiple satellite-based datasets and climate model deforestation experiments. Observationally-based methods rely on a space-for-time assumption, which compares neighboring locations with contrasting land covers as a proxy for land use changes over time without considering possible atmospheric feedbacks. Offline land simulations or subgrid-level analyses agree with observed warming effects only when the space-for-time assumption is replicated. However, deforestation-related cloud and radiation effects manifest in coupled climate simulations and observations at larger scales, which show that a reduction of hot extremes with deforestation – as simulated in a number of CMIP5 models – is possible. Our study provides a design and analysis methodology for land use change studies and highlights the importance of including land-atmosphere coupling, which can alter deforestation-induced temperature changes. Models show a cooler surface temperature response to deforestation than observations which has been attributed to uncertainties in the models. A comparison of satellite observations and model experiments shows that the disagreement is due to the role of atmospheric feedbacks, which are not well captured in the observational space-for-time approach.

When soil moisture (SM) content falls within a transitional regime between dry and wet conditions, it controls evaporation, affecting atmospheric heat and humidity. Accordingly, different SM regimes correspond to different gears of land-atmosphere coupling, affecting climate. Determining patterns of SM regimes and their future evolution is imperative. Here, we examine global SM regime distributions from ten climate models. Under increasing CO 2 , the range of SM extends into unprecedented coupling regimes in many locations. Solely wet regime areas decline globally by 15.9%, while transitional regimes emerge in currently humid areas of the tropics and high latitudes. Many semiarid regions spend more days in the transitional regime and fewer in the dry regime. These imply that a larger fraction of the world will evolve to experience multiple gears of land-atmosphere coupling, with the strongly coupled transitional regime expanding the most. This could amplify future climate sensitivity to land-atmosphere feedbacks and land management. When soil moisture is within the transitional regime that is neither too dry nor too wet, its variation affects evaporation and thus climate. This study shows that, under global warming, more areas will experience a transitional regime.

High temperature extremes accompanied by drought have led to serious ramifications for environmental and socio‐economic systems. Thus, improving the predictability of heat‐wave events is a high priority. One key to achieving this is to better understand land‐atmosphere interactions. Recent studies have documented a hypersensitive regime in the soil moisture‐temperature relationship: when soil dries below a critical low threshold, called the soil moisture breakpoint, air temperatures increase at a greater rate as soil moisture declines. Whether such a hypersensitive regime is rooted in land surface processes and whether this soil moisture breakpoint corresponds to a known plant critical value, the permanent wilting point (WP), below which latent heat flux almost ceases, remains unclear. In this study, we explore the mechanisms linking low soil moisture to high air temperatures. From in situ observations, we confirm that the hypersensitive regime acts throughout the chain of energy processes from land to atmosphere. A simple energy‐balance model indicates that the hypersensitive regime occurs when there is a dramatic drop in evaporative cooling, which happens when soil moisture dries toward the permanent WP, suggesting that the soil moisture breakpoint is slightly above the permanent WP. Precisely how a model represents the relationship between evapotranspiration and soil moisture is found to be essential to describe the occurrence of the hypersensitive regime. Thus, we advocate that weather and climate models should ensure a realistic representation of land‐atmosphere interactions to obtain reliable forecasts of extremes and climate projections, aiding the assessment of heatwave vulnerability and adaptation. Plain Language Summary Hot temperature extremes combined with droughts have caused significant problems for the environment and economies. Improving prediction of heat‐wave events is of utmost importance. This can be achieved by a better understanding of how land conditions affect near surface atmosphere and vice versa. Recent evidences have shown that when the soil becomes very dry and below a certain threshold, even a slight decrease in soil moisture yields a substantial increase in air temperature. However, the behind mechanism remains unclear. In this study, we validate that hypersensitive regimes indeed result from energy transmission from land to atmosphere by using observations. Subsequently, we built a simple model to explore how air temperature correlates to land wetness conditions. Our model indicates that hypersensitive regime occurs when there is a dramatic drop in evaporation when soil moisture dries to the permanent wilting point, below which water is no longer drawn from the soil by plant roots. The diminished evaporation significantly curtails the cooling effect on the atmosphere. Notably, the model’s representation of evaporation behavior fundamentally governs the occurrence of hypersensitive regimes. To achieve reliable forecasts of climate extremes and projections, a realistic depiction of land‐atmosphere interactions is indispensable. Key Points Hypersensitive regime acts throughout the chain of energy processes from land to atmosphere Hypersensitive regime occurs when soil moisture dries to the permanent wilting point Model’s representation of evapotranspiration fundamentally governs the occurrence of hypersensitive regimes

To assess the biogeophysical impacts of land cover land use change (LCLUC) on surface temperature, two observation-based metrics and their applicability in climate modeling were explored in this study. Both metrics were developed based on the surface energy balance, and provided insight into the contribution of different aspects of land surface change (such as albedo, surface roughness, net radiation and surface heat fluxes) to changing climate. A revision of the first metric, the intrinsic biophysical mechanism, can be used to distinguish the direct and indirect effects of LCLUC on surface temperature. The other, a decomposed temperature metric, gives a straightforward depiction of separate contributions of all components of the surface energy balance. These two metrics well capture observed and model simulated surface temperature changes in response to LCLUC. Results from paired FLUXNET sites and land surface model sensitivity experiments indicate that surface roughness effects usually dominate the direct biogeophysical feedback of LCLUC, while other effects play a secondary role. However, coupled climate model experiments show that these direct effects can be attenuated by large scale atmospheric changes (indirect feedbacks). When applied to real-time transient LCLUC experiments, the metrics also demonstrate usefulness for assessing the performance of climate models and quantifying land-atmosphere interactions in response to LCLUC.

There is high demand and a growing expectation for predictions of environmental conditions that go beyond 0–14-day weather forecasts with outlooks extending to one or more seasons and beyond. This is driven by the needs of the energy, water management, and agriculture sectors, to name a few. There is an increasing realization that, unlike weather forecasts, prediction skill on longer time scales can leverage specific climate phenomena or conditions for a predictable signal above the weather noise. Currently, it is understood that these conditions are intermittent in time and have spatially heterogeneous impacts on skill, hence providing strategic windows of opportunity for skillful forecasts. Research points to such windows of opportunity, including El Niño or La Niña events, active periods of the Madden–Julian oscillation, disruptions of the stratospheric polar vortex, when certain large-scale atmospheric regimes are in place, or when persistent anomalies occur in the ocean or land surface. Gains could be obtained by increasingly developing prediction tools and metrics that strategically target these specific windows of opportunity. Across the globe, reevaluating forecasts in this manner could find value in forecasts previously discarded as not skillful. Users’ expectations for prediction skill could be more adequately met, as they are better aware of when and where to expect skill and if the prediction is actionable. Given that there is still untapped potential, in terms of process understanding and prediction methodologies, it is safe to expect that in the future forecast opportunities will expand. Process research and the development of innovative methodologies will aid such progress.

Land–atmosphere (L-A) interactions are a main driver of Earth’s surface water and energy budgets; as such, they modulate near-surface climate, including clouds and precipitation, and can influence the persistence of extremes such as drought. Despite their importance, the representation of L-A interactions in weather and climate models remains poorly constrained, as they involve a complex set of processes that are difficult to observe in nature. In addition, a complete understanding of L-A processes requires interdisciplinary expertise and approaches that transcend traditional research paradigms and communities. To address these issues, the international Global Energy and Water Exchanges project (GEWEX) Global Land–Atmosphere System Study (GLASS) panel has supported “L-A coupling” as one of its core themes for well over a decade. Under this initiative, several successful land surface and global climate modeling projects have identified hot spots of L-A coupling and helped quantify the role of land surface states in weather and climate predictability. GLASS formed the Local Land–Atmosphere Coupling (LoCo) project and working group to examine L-A interactions at the process level, focusing on understanding and quantifying these processes in nature and evaluating them in models. LoCo has produced an array of L-A coupling metrics for different applications and scales and has motivated a growing number of young scientists from around the world. This article provides an overview of the LoCo effort, including metric and model applications, along with scientific and programmatic developments and challenges.

The ability of soil moisture to affect precipitation (SM‐P) can be dissected into the ability of soil moisture to affect evapotranspiration (ET; SM‐ET) and the ability of ET to affect precipitation (ET‐P). SM‐ET is a local process that is relatively easy to quantify, but ET‐P includes nonlocal atmospheric processes and is more complex. Here, ET‐P is quantified both locally and remotely with a back‐trajectory method for water vapor transport, using corrected reanalysis data. It is found that, for SM‐P and ET‐P, local impact is greater than that from remote for most land areas with significant local impacts. By examining the responses of the three metrics (SM‐ET, ET‐P, and SM‐P) to climate variations over different climate regimes, we show that SM‐ET is the principal factor that determines the spatial pattern and variation of SM‐P. For climatologically wet regions, SM‐ET and SM‐P are higher during dry periods, and vice versa for climatologically dry regions. All three metrics show highest values over the transitional zones. Key Points The impact of soil moisture on precipitation is dissected into two segments Land segment dominants over atmospheric segment in the impact Local impact dominants over nonlocal impacts over a majority of impact areas

When initial soil moisture is perturbed among ensemble members in the operational NWS global forecast model, surface latent and sensible fluxes are immediately affected much more strongly, systematically, and over a greater area than conventional land–atmosphere coupling metrics suggest. Flux perturbations are likewise transmitted to the atmospheric boundary layer more formidably than climatology-based metrics would indicate. Impacts are not limited to the traditional land–atmosphere coupling hot spots, but extend over nearly all ice-free land areas of the globe. Key to isolating this effect is that initial atmospheric states are identical among quantities correlated, pinpointing soil moisture and snow cover. A consequence of this high sensitivity is that significant positive impacts of realistic land surface initialization on the skill of deterministic near-surface temperature and humidity forecasts are also immediate and nearly universal during boreal spring and summer (the period investigated) and persist for at least 3 days over most land areas. Land surface initialization may be more broadly important for weather forecasts than previously realized, as the research focus historically has been on subseasonal-to-seasonal time scales. This study attempts to bridge the gap between climate studies with their associated coupling assessments and weather forecast time scales. Furthermore, errors in land surface initialization and shortcomings in the parameterization of atmospheric processes sensitive to surface fluxes may have greater consequences than previously recognized, the latter exemplified by the lack of impact on precipitation forecasts even though the simulation of boundary layer development is shown to be greatly improved with realistic soil moisture initialization.

The 2018 drought and heatwave over northern Europe were exceptional, with unprecedented forest fires in Sweden, searing heat in Germany and water restrictions in England. Monthly, daily, and hourly data from ERA5, verified with in situ soil water content and surface flux measurements, are examined to investigate the subseasonal‐to‐seasonal progression of the event and the diurnal evolution of tropospheric profiles over Britain to quantify the anomalous land surface contribution to heat and drought. Data suggest the region entered an unprecedented condition of becoming a “hot spot” for land‐atmosphere coupling, which exacerbated the heatwave across much of northern Europe. Land‐atmosphere feedbacks were prompted by unusually low soil water over wide areas, which generated moisture limitations on surface latent heat fluxes, suppressing cloud formation, increasing surface net radiation, and driving temperatures higher during several multiweek episodes of extreme heat. We find consistent evidence in field data and reanalysis of a threshold of soil water content at most locations, below which surface fluxes and daily maximum temperatures become hypersensitive to declining soil water. Similar recent heatwaves over various parts of Europe in 2003, 2010, and 2019, combined with dire climate change projections, suggest such events could be on the increase. Land‐atmosphere feedbacks may play an increasingly important role in exacerbating extremes, but could also contribute to their predictability on subseasonal time scales. Plain Language Summary This study uses a combination of environmental observations, atmospheric, and land surface analyses over northern Europe to examine the exceptional drought and heatwave during the summer of 2018. Results suggest the region entered a state of positive feedback between the land and atmosphere, exacerbating the heatwave over the area. This is a situation that is common over southern Europe and many other places in the world, but not for northern Europe. Dry soils and vegetation led to reduced evaporation, increased heating of the surface, warming and drying of the air, contributing to less cloud cover and rain. Particularly, a threshold value of soil water content has been found for most locations, below which evaporation, heating, and daily maximum temperatures become significantly more sensitive to declining soil water. This is both a worrying indicator for the region in a warming climate and a potential source of additional predictability for the intensification of future heatwave events. Key Points Unprecedented dry soil contributed to the 2018 European heatwave and drought by altering surface fluxes, heating, and drying the atmosphere Threshold values of soil water content are found below which air temperature becomes much more sensitive to increased drying Field observations corroborate reanalysis depictions of heatwave sensitivity, suggesting land feedbacks amplified heat over much of Europe

Recent studies have shown the impacts of historical land-use land-cover changes (i.e., deforestation) on hot temperature extremes; contradictory temperature responses have been found between studies using observations and climatemodels. However, different characterizations of surface temperature are sometimes used in the assessments: land surface skin temperature Ts is more commonly used in observation-based studies while nearsurface air temperature T2m is more often used in model-based studies. The inconsistent use of temperature variables is not inconsequential, and the relationship between deforestation and various temperature changes can be entangled,which complicates comparisons between observations and model simulations. In this study, the responses in the diurnal cycle of summertime Ts and T2m to deforestation are investigated using the Community Earth System Model. For the daily maximum, opposite responses are found in Ts and T2m . Due to decreased surface roughness after deforestation, the heat at the land surface cannot be efficiently dissipated into the air, leading to a warmer surface but cooler air. For the daily minimum, strong warming is found in T2m , which exceeds daytime cooling and leads to overall warming in daily mean temperatures. After comparing several climate models, we find that the models agree in daytime land surface (Ts ) warming, but different turbulent transfer characteristics produce discrepancies in T2m . Our work highlights the need to investigate the diurnal cycles of temperature responses carefully in land-cover change studies. Furthermore, consistent consideration of temperature variables should be applied in future comparisons involving observations and climate models.