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Land‐atmospheric interactions are complex and variable in space and time. On average soil moisture‐temperature coupling is expected to be stronger in transition zones between wet and dry climates. During heatwaves anomalously high coupling may be found in areas of soil moisture deficit and high atmospheric demand of water. Here a new approach is applied to satellite andin situobservations towards the characterization of regions of intense soil moisture‐temperature coupling, both in terms of climatology and anomalies during heatwaves. The resulting average summertime couplinghot spotsreflect intermediate climatic regions in agreement with previous studies. Results at heatwave‐scale suggest a minor role of soil moisture deficit during the heatwave of 2006 in California but an important one in the 2003 event in Western Europe. Progress towards near‐real time satellite products may allow the application of the approach to aid prediction and management of warm extremes. Key Points Soil moisture‐temperature coupling at different timescales using new diagnostic New field of global satellite evaporation to study land‐atmosphere interaction Transitional climate zones as hotspots and variable coupling during heatwaves

Quantification of global land evapotranspiration (ET) has long been associated with large uncertainties due to the lack of reference observations. Several recently developed products now provide the capacity to estimate ET at global scales. These products, partly based on observational data, include satellite ]based products, land surface model (LSM) simulations, atmospheric reanalysis output, estimates based on empirical upscaling of eddycovariance flux measurements, and atmospheric water balance datasets. The LandFlux-EVAL project aims to evaluate and compare these newly developed datasets. Additionally, an evaluation of IPCC AR4 global climate model (GCM) simulations is presented, providing an assessment of their capacity to reproduce flux behavior relative to the observations ]based products. Though differently constrained with observations, the analyzed reference datasets display similar large-scale ET patterns. ET from the IPCC AR4 simulations was significantly smaller than that from the other products for India (up to 1 mm/d) and parts of eastern South America, and larger in the western USA, Australia and China. The inter-product variance is lower across the IPCC AR4 simulations than across the reference datasets in several regions, which indicates that uncertainties may be underestimated in the IPCC AR4 models due to shared biases of these simulations.

This study investigates the difference in land–atmosphere interactions between grassland and forest during typical heatwave conditions in order to understand the controversial results of Teuling et al. (2010) (hereafter T10), who found the systematic occurrence of higher sensible heat fluxes over forest than over grassland during heatwaves. With a simple but accurate coupled land–atmosphere model, we show that existing parametrizations are able to reproduce the findings of T10 for normal summer and heatwave conditions. Furthermore, we demonstrate the sensitivity of the coupled system to changes in incoming radiation and early-morning temperature typical for European heatwaves. Our results suggest that the fast atmospheric control of stomatal resistance can explain the observed differences between grassland and forest. The atmospheric boundary layer has a buffering function therein: increases in stomatal resistance are largely compensated for by increases in the potential evaporation due to atmospheric warming and drying. In order to disentangle the contributions of differences in several static and dynamic properties between forest and grassland, we have performed a virtual experiment with artificial land-use types that are equal to grassland, but with one of its properties replaced by that of forest. From these, we confirm the important role of the fast physiological processes that lead to the closure of stomata. Nonetheless, for a full explanation of T10's results, the other properties (albedo, roughness and the ratio of minimum stomatal resistance to leaf-area index) play an important but indirect role; their influences mainly consist of strengthening the feedback that leads to the closure of the stomata by providing more energy that can be converted into sensible heat. The model experiment also confirms that, in line with the larger sensible heat flux, higher atmospheric temperatures occur over forest. As our parametrization for stomatal resistance is empirical rather than mechanical, our study stresses the demand for a better mechanistic understanding of physiological processes in plants.

Evapotranspiration (ET)$(ET)$is a key process in the hydrological cycle that can help mitigate urban heat. ET$ET$depends on the surface cover, as the surface affects the partitioning of precipitation between runoff and evapotranspiration. In urban neighborhoods, this surface cover is highly heterogeneous. The resulting neighborhood‐scale ET$ET$can be observed with eddy‐covariance systems. However, these observations represent the signal from wind‐ and stability‐dependent footprints resulting in a continuously changing contribution of surface cover types to the observation. This continuous change prevents quantifying the contribution of the surface cover types to neighborhood ET$ET$and their hourly dynamics. Here, we disentangle this neighborhood‐scale ET$ET$at two sites in Berlin attributing the patch‐scale ET$ET$dynamics to the four major surface cover types in the footprint: impervious surfaces, low vegetation, high vegetation, and open water. From the bottom‐up, we reconstruct neighborhood ET$ET$based on patch‐scale observations and conceptual models. Alternatively, we start top‐down and attribute neighborhood ET$ET$to the surface cover types solving a system of equations for three eddy‐covariance systems. Although data requirements for the bottom‐up approach are met more frequently, both approaches indicate that vegetation is responsible for more ET$ET$than proportional to its surface fraction in the footprint related to the large evaporating surface compared to the ground surface. Evaporation from impervious surfaces cannot be neglected, although it is less than from vegetation due to limited water availability. The limited water availability causes impervious surfaces to cease evaporation hours after rainfall, while vegetation and open water sustain ET$ET$for extended periods. Plain Language Summary Different types of surfaces, like grass, trees, pavement, and open water, affect how rainwater is divided between evaporation and runoff. In cities with lots of pavement and buildings, more water runs off than in natural areas leaving less water for evaporation. Measurement towers have been observing the evaporation from whole neighborhoods, but separating the effects of different surfaces is hard. In our study, we figure out how much each surface type contributes to evaporation with two methods: one starting from the separate surfaces and rebuilding the neighborhood evaporation, and the other starting with the neighborhood evaporation and breaking it down into evaporation from each surface. Both ways showed that plants evaporate more than proportionally to their surface area, but even built surfaces like pavement evaporate. Our findings confirm that more plants lead to more evaporation, but built surfaces cannot be ignored. This information can help urban planners create cities that manage water better, making cities nicer places to live. Key Points Neighborhood ET is reconstructed from patch‐scale data (bottom‐up) and disentangled attributing ET to four surface types (top‐down) The neighborhood and patch scale are connected through half‐hourly‐varying eddy‐covariance footprints ET dynamics after rainfall reveal that water limitation drives differences between surface cover types

Enhanced surface runoff in urban environments reduces water availability and limits the evaporative cooling potential. We evaluate surface runoff in 18 urban land surface models (ULSM) in Urban‐PLUMBER for 6,570 rainfall events across 21 urban sites. Surface runoff occurs when rainfall exceeds the infiltration, saturation, or interception capacity. Ten models omit at least one of these processes, while seven fail to increase runoff with increasing imperviousness. Surprisingly, some models lack any runoff during intense (>50mmh−1${50\\text{mmh}}^{-1}$ ) or prolonged (>20 mm) rainfall. Urban land surface models (ULSMs) turn 0%–86% rainfall into runoff. Most models produce runoff in agreement with an empirical comparison offered by the CN method, especially for high imperviousness. However, ULSM runoff exceeds CN runoff estimates for low impervious fraction, particularly by models with incomplete process description and for low‐intensity rainfall. The large discrepancy between ULSMs calls for advancing the urban hydrology representation in ULSMs, which is essential for correct simulation of evaporative cooling in cities.

Climate models suggest that enhanced greenhouse gas concentrations and aerosols have major impacts on the land energy and water cycles, and in particular on evapotranspiration (ET). Here we analyze how the main external drivers of ET (incident solar radiation and precipitation) vary regionally, using recent data from a eddy‐covariance flux tower network (FLUXNET) and a multi‐model re‐analysis (GSWP‐2). Trends in radiation (global “dimming” and “brightening”) are expected to impact ET only in regions where ET correlates with radiation. In central Europe this correlation is particularly strong, and trends derived from weighing lysimeters and river‐basin water budgets follow trends in radiation. In central North America the correlation is weak, and trends in precipitation rather than radiation explain trends in ET. Our results reconcile previous hypotheses by demonstrating the strongly regional and temporal differentiation of trends in evaporation.

Urban Land Surface Models (ULSMs) simulate energy and water exchanges between the urban surface and atmosphere. However, earlier systematic ULSM comparison projects assessed the energy balance but ignored the water balance, which is coupled to the energy balance. Here, we analyze the water balance representation in 19 ULSMs participating in the Urban‐PLUMBER project using results for 20 sites spread across a range of climates and urban form characteristics. As observations for most water fluxes are unavailable, we examine the water balance closure, flux timing, and magnitude with a score derived from seven indicators expecting better scoring models to capture the latent heat flux more accurately. We find that the water budget is only closed in 57% of the model‐site combinations assuming closure when annual total incoming fluxes (precipitation and irrigation) fluxes are within 3% of the outgoing (all other) fluxes. Results show the timing is better captured than magnitude. No ULSM has passed all water balance indicators for any site. Models passing more indicators do not capture the latent heat flux more accurately refuting our hypothesis. While output reporting inconsistencies may have negatively affected model performance, our results indicate models could be improved by explicitly verifying water balance closure and revising runoff parameterizations. By expanding ULSM evaluation to the water balance and related to latent heat flux performance, we demonstrate the benefits of evaluating processes with direct feedback mechanisms to the processes of interest. Plain Language Summary Urban environments have their own local climates including typically higher nocturnal temperatures compared with rural areas. Ideally, modeling cities should capture their influences on the atmosphere above them. As the energy and water balances are linked by evaporation, a good water balance representation will support a good energy balance simulation. Focusing on the water balance, we find the water balance in models could be improved by paying attention to closure and runoff. Key Points We evaluate the water balance in 19 urban land surface models (ULSM) from the Urban‐PLUMBER project ULSMs capture the timing of water fluxes more accurately than their magnitude The water balance appears unclosed in 43% of the model runs (19 models at 20 sites)

The feedback between soil moisture and precipitation has long been a topic of interest due to its potential for improving weather and seasonal forecasts. The generally proposed mechanism assumes a control of soil moisture on precipitation via the partitioning of the surface turbulent heat fluxes, as assessed via the evaporative fraction (EF), i.e., the ratio of latent heat to the sum of latent and sensible heat, in particular under convective conditions. Our study investigates the poorly understood link between EF and precipitation by relating the before-noon EF to the frequency of afternoon precipitation over the contiguous US, through statistical analyses of multiple EF and precipitation data sets. We analyze remote-sensing data products (Global Land Evaporation: the Amsterdam Methodology (GLEAM) for EF, and radar precipitation from the NEXt generation weather RADar system (NEXRAD)), FLUXNET station data, and the North American Regional Reanalysis (NARR). Data sets agree on a region of positive relationship between EF and precipitation occurrence in the southwestern US. However, a region of strong positive relationship over the eastern US in NARR cannot be confirmed with observation-derived estimates (GLEAM, NEXRAD and FLUXNET). The GLEAM–NEXRAD data set combination indicates a region of positive EF–precipitation relationship in the central US. These disagreements emphasize large uncertainties in the EF data. Further analyses highlight that much of these EF–precipitation relationships could be explained by precipitation persistence alone, and it is unclear whether EF has an additional role in triggering afternoon precipitation. This also highlights the difficulties in isolating a land impact on precipitation. Regional analyses point to contrasting mechanisms over different regions. Over the eastern US, our analyses suggest that the EF–precipitation relationship in NARR is either atmospherically controlled (from precipitation persistence and potential evaporation) or driven by vegetation interception rather than soil moisture. Although this aligns well with the high forest cover and the wet regime of that region, the role of interception evaporation is likely overestimated because of low nighttime evaporation in NARR. Over the central and southwestern US, the EF–precipitation relationship is additionally linked to soil moisture variations, owing to the soil-moisture-limited climate regime.

The Wageningen Lowland Runoff Simulator (WALRUS) is a new parametric (conceptual) rainfall–runoff model which accounts explicitly for processes that are important in lowland areas, such as groundwater-unsaturated zone coupling, wetness-dependent flowroutes, groundwater–surface water feedbacks, and seepage and surface water supply (see companion paper by Brauer et al., 2014). Lowland catchments can be divided into slightly sloping, freely draining catchments and flat polders with controlled water levels. Here, we apply WALRUS to two contrasting Dutch catchments: the Hupsel Brook catchment and the Cabauw polder. In both catchments, WALRUS performs well: Nash–Sutcliffe efficiencies obtained after calibration on 1 year of discharge observations are 0.87 for the Hupsel Brook catchment and 0.83 for the Cabauw polder, with values of 0.74 and 0.76 for validation. The model also performs well during floods and droughts and can forecast the effect of control operations. Through the dynamic division between quick and slow flowroutes controlled by a wetness index, temporal and spatial variability in groundwater depths can be accounted for, which results in adequate simulation of discharge peaks as well as low flows. The performance of WALRUS is most sensitive to the parameter controlling the wetness index and the groundwater reservoir constant, and to a lesser extent to the quickflow reservoir constant. The effects of these three parameters can be identified in the discharge time series, which indicates that the model is not overparameterised (parsimonious). Forcing uncertainty was found to have a larger effect on modelled discharge than parameter uncertainty and uncertainty in initial conditions.

Many climate models have difficulties in properly reproducing climate extremes, such as heat wave conditions. Here we use the Weather Research and Forecasting (WRF) regional climate model with a large combination of different atmospheric physics schemes, in combination with the NOAH land-surface scheme, with the goal of detecting the most sensitive physics and identifying those that appear most suitable for simulating the heat wave events of 2003 in western Europe and 2010 in Russia. In total, 55 out of 216 simulations combining different atmospheric physical schemes have a temperature bias smaller than 1 °C during the heat wave episodes, the majority of simulations showing a cold bias of on average 2–3 °C. Conversely, precipitation is mostly overestimated prior to heat waves, and shortwave radiation is slightly overestimated. Convection is found to be the most sensitive atmospheric physical process impacting simulated heat wave temperature across four different convection schemes in the simulation ensemble. Based on these comparisons, we design a reduced ensemble of five well performing and diverse scheme configurations, which may be used in the future to perform heat wave analysis and to investigate the impact of climate change during summer in Europe.