publications

2022

1. NatGeo

   Drought self-propagation in drylands due to land–atmosphere feedbacks

   Schumacher, D. L., Keune, J., Dirmeyer, P., and Miralles, D. G.

   Nature Geoscience 2022

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   Reduced evaporation due to dry soils can affect the land surface energy balance, with implications for local and downwind precipitation. When evaporation is constrained by soil moisture, the atmospheric supply of water is depleted, and this deficit may propagate in time and space. This mechanism could theoretically result in the self-propagation of droughts, but the extent to which this process occurs is unknown. Here we isolate the influence of soil moisture drought on downwind precipitation using Lagrangian moisture tracking constrained by observations from the 40 largest recent droughts worldwide. We show that dryland droughts are particularly prone to self-propagating because evaporation tends to respond strongly to enhanced soil water stress. In drylands, precipitation can decline by more than 15% due to upwind drought during a single event and up to 30% during individual months. In light of projected widespread reductions in water availability, this feedback may further exacerbate future droughts.

2. GMD

   A unified framework to estimate the origins of atmospheric moisture and heat using Lagrangian models

   Keune, J., Schumacher, D. L., and Miralles, D. G.

   Geoscientific Model Development 2022

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   Despite the existing myriad of tools and models to assess atmospheric source–receptor relationships, their uncertainties remain largely unexplored and arguably stem from the scarcity of observations available for validation. Yet, Lagrangian models are increasingly used to determine the origin of precipitation and atmospheric heat by scrutinizing the changes in moisture and temperature along air parcel trajectories. Here, we present a unified framework for the process-based evaluation of atmospheric trajectories to infer source–receptor relationships of both moisture and heat. The framework comprises three steps: (i) diagnosing precipitation, surface evaporation, and sensible heat from the Lagrangian simulations and identifying the accuracy and reliability of flux detection criteria; (ii) establishing source–receptor relationships through the attribution of sources along multi-day backward trajectories; and (iii) performing a bias correction of source–receptor relationships. Applying this framework to simulations from the Lagrangian model FLEXPART, driven with ERA-Interim reanalysis data, allows us to quantify the errors and uncertainties associated with the resulting source–receptor relationships for three cities in different climates (Beijing, Denver, and Windhoek). Our results reveal large uncertainties inherent in the estimation of heat and precipitation origin with Lagrangian models, but they also demonstrate that a source and sink bias correction acts to reduce this uncertainty. The proposed framework paves the way for a cohesive assessment of the dependencies in source–receptor relationships.

3. SciAdv

   Soil drought can mitigate deadly heat stress thanks to a reduction of air humidity

   Wouters, H., Keune, J., Petrova, I. Y., Heerwaarden, C. C., Teuling, A. J., Pal., J. S., Arellano, J., and Miralles, D. G.

   Science Advances 2022

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   Global warming increases the number and severity of deadly heatwaves. Recent heatwaves often coincided with soil droughts that intensify air temperature but lower air humidity. Since lowering air humidity may reduce human heat stress, the net impact of soil desiccation on the morbidity and mortality of heatwaves remains unclear. Combining weather balloon and satellite observations, atmospheric modelling, and meta-analyses of heatwave mortality, we find that soil droughts—despite their warming effect—lead to a mild reduction in heatwave lethality. More specifically, morning dry soils attenuate afternoon heat stress anomaly by  5%. This occurs because of reduced surface evaporation and increased entrainment of dry air aloft. The benefit appears more pronounced during specific events, such as the Chicago 1995 and Northern U.S. 2006 and 2012 heatwaves. Our findings suggest that irrigated agriculture may intensify lethal heat stress, and question recently proposed heatwave mitigation measures involving surface moistening to increase evaporative cooling.

2020

1. ANYAS

   Atmospheric heat and moisture transport to energy-and water-limited ecosystems

   Schumacher, D. L., Keune, J., and Miralles, D. G.

   Annals of the New York Academy of Sciences 2020

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

2019

1. WRR

   A precipitation recycling network to assess freshwater vulnerability: Challenging the watershed convention

   Keune, J., and Miralles, D. G.

   Water Resources Research 2019

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   Water resources and water scarcity are usually regarded as local aspects for which a watershed-based management appears adequate. However, precipitation, as a main source of freshwater, may depend on moisture supplied through land evaporation from outside the watershed. This notion of evaporation as a local “green water” supply to precipitation is typically not considered in hydrological water assessments. Here we propose the concept of a watershed precipitation recycling network, which establishes atmospheric pathways and links land surface evaporation as a moisture supply to precipitation, hence contributing to local but also remote freshwater resources. Our results show that up to 74% of summer precipitation over European watersheds depends on moisture supplied from other watersheds, which contradicts the conventional consideration of autarkic watersheds. The proposed network approach illustrates atmospheric pathways and enables the objective assessment of freshwater vulnerability and water scarcity risks under global change. The illustrated watershed interdependence emphasizes the need for global water governance to secure freshwater availability.

2. NGeo

   Amplification of mega-heatwaves through heat torrents fuelled by upwind drought

   Schumacher, D. L., Keune, J., Van Heerwaarden, C. C., Arellano, J., Teuling, A. J., and Miralles, D. G.

   Nature Geoscience 2019

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   Mega-heatwaves are among the deadliest natural disasters in midlatitudes. During such events, the atmospheric circulation is typically governed by persistent anticyclones, enabling cloud-free conditions and advection of hot air. Dry soils in heatwave regions are also known to further contribute to the escalation of air temperatures. However, while local land–atmosphere feedbacks are well studied, the same does not apply to the influence of upwind areas, from where heat is advected. Here we investigate reanalysis data using a Lagrangian heat-tracking model to unravel the role of upwind land–atmosphere feedbacks during the two European mega-heatwaves of this century: the events in 2003 and 2010. Our analysis indicates that advected sensible heat can come in torrents, suddenly and intensely, leading to abrupt increases in air temperatures that further strengthen local land–atmosphere feedbacks via soil desiccation. During both mega-heatwaves, about 30% of the advected sensible heat was caused by the drought upwind. Since subtropical droughts are projected to aggravate during this century, in light of our results, this may be accompanied by consequent intensification of midlatitude mega-heatwaves. We therefore recommend considering not only local, but also upwind land cover and land-use management in the design of adaptation strategies against compound drought–heatwave events.

3. AFM

   Incorporating a root water uptake model based on the hydraulic architecture approach in terrestrial systems simulations

   Sulis, M., Couvreur, V., Keune, J., Cai, G., Trebs, I., Junk, J., Shrestha, P., Simmer, C., Kollet, S., Vereecken, H., and others,

   Agricultural and Forest Meteorology 2019

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   A detailed representation of plant hydraulic traits and stomatal closure in land surface models (LSMs) is a prerequisite for improved predictions of ecosystem drought response. This work presents the integration of a macroscopic root water uptake (RWU) model based on the hydraulic architecture approach in the LSM of the Terrestrial Systems Modeling Platform. The novel RWU approach is based on three parameters derived from first principles that describe the root system equivalent conductance, the compensatory RWU conductance, and the leaf water potential at stomatal closure, which defines the water stress condition for the plants. The developed RWU model intrinsically accounts for changes in the root density as well as for the simulation of the hydraulic lift process. The standard and the new RWU approach are compared by performing point-scale simulations for cropland over a sheltered minirhizotron facility in Selhausen, Germany, and validated against transpiration fluxes estimated from sap flow and soil water content measurements at different depths. Numerical sensitivity experiments are carried out using different soil textures and root distributions in order to evaluate the interplay between soil hydrodynamics and plant characteristics, and the impact of assuming time-constant plant physiological properties. Results show a good agreement between simulated and observed transpiration fluxes for both RWU models, with a more distinct response under water stress conditions and with uncertainty in the soil parameterization prevailing to the differences due to changes in the model formulation. The hydraulic RWU model exhibits also a lower sensitivity to the root distributions when simulating the onset of the water stress period. Finally, an analysis of variability across the soil and root scenarios indicates that differences in soil water content are mainly influenced by the root distribution, while the transpiration flux in both RWU models is additionally determined by the soil characteristics.

4. ERL

   Land use change impacts on European heat and drought: remote land-atmosphere feedbacks mitigated locally by shallow groundwater

   Zipper, S. C., Keune, J., and Kollet, S.

   Environmental Research Letters 2019

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   Heat and drought are projected to increase globally but may be mitigated or exacerbated by land use/land cover (LULC) change. Here, we show that remote land-atmosphere feedbacks caused by historical European LULC change led to widespread changes in the energy and water balances, drought, and heat. Using a continental-scale bedrock-to-atmosphere model, we find that LULC change following the Soviet Union collapse and European Union formation may have substantially increased cloud cover and decreased incoming shortwave radiation in western Europe, even in locations where LULC did not change. These changes to the water and energy balances had spatially heterogeneous impacts on drought and heat, including drying in the Mediterranean and Eastern Europe regions. The response of the water and energy balances to remote feedbacks was lessened in areas with shallow groundwater, indicating that local- and continental-scale responses to LULC change are influenced by the coupling between the subsurface, land surface, and atmosphere.

5. JG

   Evidence of daily hydrological loading in GPS time series over Europe

   Springer, A., Karegar, M. A., Kusche, J., Keune, J., Kurtz, W., and Kollet, S.

   Journal of geodesy 2019

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   Loading deformations from atmospheric, oceanic, and hydrological mass changes mask geophysical processes such as land subsidence and tectonic or volcanic deformation. While it is known that hydrological loading plays a role at seasonal time scales, here we demonstrate evidence that also fast water storage changes contribute to daily Global Positioning System (GPS) height time series. So far, no clear strategy, i.e., no single conventional hydrological model, has been proposed for removing hydrological deformation from daily GPS height time series. Hydrological model predictions of total water storage anomalies tend to diverge and (substantially) deviate from Gravity Recovery and Climate Experiment (GRACE) observations, which however have a limited spatial and temporal resolution. Here, we suggest to overcome these limitations by assimilating GRACE data into a high-resolution (12.5 km) hydrological model. We tested this approach over Europe, and we found that accounting for daily hydrological mass changes reduces the root mean square scatter of GPS height time series almost by a factor of two when compared to monthly hydrological mass changes. We suggest that a GRACE-assimilating hydrological model would provide a promising option for removing hydrology-induced vertical deformation from GPS time series also at the global scale.

6. HESS

   Improving soil moisture and runoff simulations at 3 km over Europe using land surface data assimilation

   Naz, B. S., Kurtz, W., Montzka, C., Sharples, W., Goergen, K., Keune, J., Gao, H., Springer, A., Hendricks-Franssen, H., and Kollet, S.

   Hydrology and Earth System Sciences 2019

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   iAccurate and reliable hydrologic simulations are important for many applications such as water resources management, future water availability projections and predictions of extreme events. However, the accuracy of water balance estimates is limited by the lack of large-scale observations, model simulation uncertainties and biases related to errors in model structure and uncertain inputs (e.g., hydrologic parameters and atmospheric forcings). The availability of long-term and global remotely sensed soil moisture offers the opportunity to improve model estimates through data assimilation with complete spatiotemporal coverage. In this study, we assimilated the European Space Agency (ESA) Climate Change Initiative (CCI) derived soil moisture (SM) information to improve the estimation of continental-scale soil moisture and runoff. The assimilation experiment was conducted over a time period 2000–2006 with the Community Land Model, version 3.5 (CLM3.5), integrated with the Parallel Data Assimilation Framework (PDAF) at a spatial resolution of 0.0275∘ (∼3 km) over Europe. The model was forced with the high-resolution reanalysis COSMO-REA6 from the Hans Ertel Centre for Weather Research (HErZ). The performance of assimilation was assessed against open-loop model simulations and cross-validated with independent ESA CCI-derived soil moisture (CCI-SM) and gridded runoff observations. Our results showed improved estimates of soil moisture, particularly in the summer and autumn seasons when cross-validated with independent CCI-SM observations. The assimilation experiment results also showed overall improvements in runoff, although some regions were degraded, especially in central Europe. The results demonstrated the potential of assimilating satellite soil moisture observations to produce downscaled and improved high-resolution soil moisture and runoff simulations at the continental scale, which is useful for water resources assessment and monitoring.

7. JAMES

   Potential added value of incorporating human water use on the simulation of evapotranspiration and precipitation in a continental-scale bedrock-to-atmosphere modeling system: A validation study considering observational uncertainty

   Keune, J., Sulis, M., and Kollet, S.

   Journal of Advances in Modeling Earth Systems 2019

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   Human activities, such as human water use, have been shown to directly influence terrestrial water fluxes and states. Simulations of soil moisture, river discharge, evapotranspiration, and groundwater storage are significantly improved, if human interactions, such as irrigation and groundwater abstraction, are incorporated. Yet improvements through the incorporation of human water use on the simulation of local and remote precipitation are rarely studied but may contribute to the skill of land surface fluxes. In this study, we evaluate the impact of human water use on the skill of evapotranspiration and precipitation in a fully coupled bedrock-to-atmosphere modeling platform. The results show that human water use can potentially increase the skill of the simulations across scales. However, observational uncertainty at the watershed scale limits the identification of model deficiencies and added value related to human water use. Locally, daily precipitation statistics potentially benefit from the incorporation of human water use. Although the incorporation of human water use does not remove the wet bias, it can increase the model skill.

8. SciData

   Pan-European groundwater to atmosphere terrestrial systems climatology from a physically consistent simulation

   Furusho-Percot, C., Goergen, K., Hartick, C., Kulkarni, K., Keune, J., and Kollet, S.

   Scientific Data 2019

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   Applying the Terrestrial Systems Modeling Platform, TSMP, this study provides the first simulated long-term (1996–2018), high-resolution ( 12.5 km) terrestrial system climatology over Europe, which comprises variables from groundwater across the land surface to the top of the atmosphere (G2A). The data set offers an unprecedented opportunity to test hypotheses related to short- and long- range feedback processes in space and time between the different interacting compartments of the terrestrial system. The physical consistency of simulated states and fluxes in the terrestrial system constitutes the uniqueness of the data set: while most regional climate models (RCMs) have a tendency to simplify the soil moisture and groundwater representation, TSMP explicitly simulates a full 3D soil- and groundwater dynamics, closing the terrestrial water cycle from G2A. As anthopogenic impacts are excluded, the dataset may serve as a near-natural reference for global change simulations including human water use and climate change. The data set is available as netCDF files for the pan-European EURO-CORDEX domain.

2018

1. GRL

   Human water use impacts on the strength of the continental sink for atmospheric water

   Keune, J., Sulis, M., Kollet, S., Siebert, S., and Wada, Y.

   Geophysical Research Letters 2018

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   In the hydrologic cycle, continental landmasses constitute a sink for atmospheric moisture as annual terrestrial precipitation commonly exceeds evapotranspiration. Simultaneously, humans intervene in the hydrologic cycle and pump groundwater to sustain, for example, drinking water and food production. Here we use a coupled groundwater-to-atmosphere modeling platform, set up over the European continent, to study the influence of groundwater pumping and irrigation on the net atmospheric moisture import of the continental landmasses, which defines the strength of the continental sink. Water use scenarios are constructed to account for uncertainties of atmospheric feedback during the heatwave year 2003. We find that human water use induces groundwater-to-atmosphere feedback, which potentially weaken the continental sink over arid watersheds in southern Europe. This feedback is linked to groundwater storage, which suggests that atmospheric feedbacks to human water use may contribute to drying of watersheds, thereby raising water resources and socio-economic concerns beyond local sustainability considerations.

2. JGR

   Quantifying the impact of subsurface-land surface physical processes on the predictive skill of subseasonal mesoscale atmospheric simulations

   Sulis, M., Keune, J., Shrestha, P., Simmer, C., and Kollet, S.

   Journal of Geophysical Research: Atmospheres 2018

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   Integrated terrestrial system modeling platforms, which simulate the 3-D flow of water both in the subsurface and the atmosphere, are expected to improve the realism of predictions through a more detailed physics-based representation of hydrometeorological processes and feedbacks. We test this expectation by evaluating simulation results from different configurations of an atmospheric model with increasing complexity in the representation of land surface and subsurface physical processes. The evaluation is performed using observations during the (HD(CP)2) Observational Prototype Experiment field campaign in April–May 2013 over western Germany. The augmented model physics do not improve the prediction of daily cumulative precipitation and minimum temperature during this period. Moreover, a cold bias is introduced in the simulated daily maximum temperature, which decreases the performance of the atmospheric model with respect to its standard configuration. The decreased performance in the maximum temperature is traced in part to a higher simulated soil moisture, which shifts surface flux partitioning toward higher latent and lower sensible heat fluxes. The better reproduced air temperature profiles simulated by the standard atmospheric model comes, however, with an overestimated heat flux at the land surface caused by a warm bias in the simulated soil temperature. Simulated atmospheric states do not correlate significantly with differences in soil moisture and temperature; thus, different turbulent flux parameterizations dominate the propagation of the subsurface signal into the atmosphere. The strong influence of the lateral synoptic forcings on the results suggests, however, the need for further investigations encompassing different weather situations or regions with stronger land-atmosphere coupling conditions.

3. WATER

   Introduction of an experimental terrestrial forecasting/monitoring system at regional to continental scales based on the terrestrial systems modeling platform (v1. 1.0)

   Kollet, S., Gasper, F., Brdar, S., Goergen, K., Hendricks-Franssen, H., Keune, J., Kurtz, W., Küll, V., Pappenberger, F., Poll, S., and others,

   Water 2018

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   Operational weather and flood forecasting has been performed successfully for decades and is of great socioeconomic importance. Up to now, forecast products focus on atmospheric variables, such as precipitation, air temperature and, in hydrology, on river discharge. Considering the full terrestrial system from groundwater across the land surface into the atmosphere, a number of important hydrologic variables are missing especially with regard to the shallow and deeper subsurface (e.g., groundwater), which are gaining considerable attention in the context of global change. In this study, we propose a terrestrial monitoring/forecasting system using the Terrestrial Systems Modeling Platform (TSMP) that predicts all essential states and fluxes of the terrestrial hydrologic and energy cycles from groundwater into the atmosphere. Closure of the terrestrial cycles provides a physically consistent picture of the terrestrial system in TSMP. TSMP has been implemented over a regional domain over North Rhine-Westphalia and a continental domain over Europe in a real-time forecast/monitoring workflow. Applying a real-time forecasting/monitoring workflow over both domains, experimental forecasts are being produced with different lead times since the beginning of 2016. Real-time forecast/monitoring products encompass all compartments of the terrestrial system including additional hydrologic variables, such as plant available soil water, groundwater table depth, and groundwater recharge and storage.

2016

1. JGR

   Studying the influence of groundwater representations on land surface-atmosphere feedbacks during the European heat wave in 2003

   Keune, J., Gasper, F., Goergen, K., Hense, A., Shrestha, P., Sulis, M., and Kollet, S.

   Journal of Geophysical Research: Atmospheres 2016

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   The impact of 3D groundwater dynamics as part of the hydrologic cycle is rarely considered in regional climate simulation experiments. However, there exists a spatial and temporal connection between groundwater and soil moisture near the land surface, which can influence the land surface-atmosphere feedbacks during heat waves. This study assesses the sensitivity of bedrock-to-atmosphere simulations to groundwater representations at the continental scale during the European heat wave 2003 using an integrated fully coupled soil-vegetation-atmosphere model. The analysis is based on the comparison of two groundwater configurations: (1) 3D physics-based variably saturated groundwater dynamics and (2) a 1D free drainage (FD) approach. Furthermore, two different subsurface hydrofacies distributions (HFD) account for the uncertainty of the subsurface hydraulic characteristics, and ensemble simulations address the uncertainty arising from different surface-subsurface initial conditions. The results show that the groundwater representation significantly impacts land surface-atmosphere processes. Differences between the two groundwater configurations follow subsurface patterns, and the largest differences are observed for shallow water table depths. While the physics-based setup is less sensitive to the HFD, the parameterized FD simulations are highly sensitive to the hydraulic characteristics of the subsurface. An analysis of variance shows that both, the groundwater configuration and the HFD, induce variability across all compartments with decreasing impact from the subsurface to the atmosphere, while the initial condition has only a minor impact.

2015

1. HYP

   Hyper-resolution global hydrological modelling: what is next? “Everywhere and locally relevant”

   Bierkens, M. F. P., Keune, J., and others,

   Hydrological Processes 2015

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2. QJRMS

   Towards a high-resolution regional reanalysis for the European CORDEX domain

   Bollmeyer, C., Keller, J. D., Ohlwein, C., Wahl, S., Crewell, S., Friederichs, P., Hense, A., Keune, J., Kneifel, S., Pscheidt, I., Redl, S., and Steinke, S.

   Quarterly Journal of the Royal Meteorological Society 2015

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   Atmospheric reanalyses covering the European region are mainly available as part of relatively coarse global reanalyses. The aim of this article is to present the development and evaluation of a next generation regional reanalysis for the European CORDEX EUR-11 domain with a horizontal grid spacing of approximately 6 km. In this context, a reanalysis is understood to be an assimilation of heterogeneous observations with a physical model such as a numerical weather prediction (NWP) model. The reanalysis system presented here is based on the NWP model COSMO by the German Meteorological Service (Deutscher Wetterdienst) using a continuous nudging scheme. In order to assess the added value of data assimilation, a dynamical downscaling experiment has been conducted, i.e. an identical model set-up but without data assimilation. Both systems have been evaluated for a 1 year test period, employing standard measures such as analysis increments, biases, or log-odds ratios, as well as tests for distributional characteristics. An important aspect is the evaluation from different perspectives and with independent measurements such as satellite infrared brightness temperatures using forward operators, integrated water vapour from GPS stations, and ceilometer cloud cover. It can be shown that the reanalysis better resolves local extreme events; this is basically an effect of the higher spatio-temporal resolution, as known from dynamical downscaling approaches. However, an important criterion for regional reanalyses is the coherence with independent observations of high temporal and spatial resolution, resulting in significant improvement over dynamical downscaling. The system is intended to become operational within a year, continuously reprocessing and evaluating longer time periods. The reanalysis data are planned to become available to the research community within a year.

2014

1. MWR

   Multivariate probabilistic analysis and predictability of medium-range ensemble weather forecasts

   Keune, J., Ohlwein, C., and Hense, A.

   Monthly Weather Review 2014

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   Ensemble weather forecasting has been operational for two decades now. However, the related uncertainty analysis in terms of probabilistic postprocessing still focuses on single variables, grid points, or stations. Inevitable dependencies in space and time and between variables are often ignored. To address this problem, two probabilistic postprocessing methods are presented, which are multivariate versions of Gaussian fit and kernel dressing, respectively. The multivariate case requires the estimation of a full rank, invertible covariance matrix. For this purpose, a Graphical Least Absolute Shrinkage and Selection Operators (GLASSO) estimator has been employed that is based on sparse undirected graphical models regularized by an L1 penalty term in order to parameterize the full rank inverse covariance. In all cases, the result is a multidimensional probability density. The forecasts used to test the approach are station forecasts of 2-m temperature and surface pressure from four main global ensemble prediction systems (EPS) with medium-range weather forecasts: the NCEP Global Ensemble Forecast System (GEFS), the Met Office Global and Regional Ensemble Prediction System (MOGREPS), the Canadian Meteorological Centre (CMC) Global Ensemble Prediction System (GEPS), and the ECMWF EPS. To evaluate the multivariate probabilistic postprocessing, especially the uncertainty estimates, common verification methods such as the analysis rank histogram and the continuous ranked probability score (CRPS) are applied. Furthermore, a multivariate extension of the CRPS, the energy score, allows for the verification of a complete medium-range forecast as well as for determining its predictability. It is shown that the predictability is similar for all of the examined ensemble prediction systems, whereas the GLASSO proved to be a useful tool for calibrating the commonly observed underdispersion of ensemble forecasts during the first few lead days by using information from the full covariance matrix.