Search

The land surface supplies heat and moisture to the atmosphere influencing the regional climate during the convective season. Availability of soil moisture for evapotranspiration, vegetation phenology and atmospheric conditions influence the strength of the land surface impact on the atmosphere, and the mechanisms predominating the heat and moisture exchange. As both the synoptic conditions as well as the vegetation state vary on sub-seasonal to interannual time scales, the strength of land-atmosphere (L-A) interaction is expected to fluctuate on these time scales.Up to now, research typically either focuses on case studies to understand the mechanisms of how land surface and atmosphere interact, or on climatic time scales to quantify co-variances in the climate system based on a sufficient sample size. Timescales in between remain rarely considered in land-atmosphere feedback studies.In our study, we applied various L-A coupling measures to evaluate land surface impacts on the atmosphere and quantify interactions associated with the triggering of convective precipitation and droughts for all summers between 1991 and 2022 over Europe based on ERA5 data.Our results highlight that differently strong L-A interactions evolve in dependence of atmospheric wetness, temperature, and the circulation pattern, as well as the root zone soil moisture and vegetation cover. Under warm and dry conditions such as in 2003, 2018 and 2022, soil moisture availability imposed limits for evapotranspiration not only in Southern Europe, but also in Central and Eastern Europe, interfering with vegetation growth and atmospheric moisture supply. Limited moisture and excessive heat supply amplified the already high temperatures and low near-surface moisture, which finally aggravated the unfavorable conditions for local precipitation and caused extreme drought conditions. On the contrary, warm and wet conditions such as in 2021 provided well-suited conditions for vegetation growth, which enhanced the moisture supply to the atmosphere. Together with stronger atmospheric instability, this provided more favorable preconditions for convective precipitation. Generally, most L-A interactions perform as an intensifier of persisting anomalies, particularly under warm and dry atmospheric conditions over Europe.

In the German regional climate modeling project ReKliEs-De the existing EURO-CORDEX simulations have been systematically complemented by new simulations to derive more robust ranges of possible future climate change. The focus of the project lay on user tailored results, which are required for the planning of measures to adapt to the changing climate. Changes in temperature and precipitation indices are calculated from a multi model ensemble for the end of the 21st century. The results for the mitigation scenario RCP2.6 are compared to the results of the “business as usual” scenario RCP8.5. Averaged over Germany the increase of mean annual temperature and of the number of summer days will be around 3 times higher for RCP8.5 than for RCP2.6. In summer, the increase of dry days could be twice as high in RCP8.5 compared to RCP2.6.

Currently a strong discussion is ongoing in Germany and Europe whether to ban vehicles from downtown areas in order to lower particle concentrations of e.g. PM10 and NO2. As often only few measurements exist inside city centers, little to nothing is known about the horizontal and vertical distributions of air pollutants. Within the EU demonstration project Open Forecast (https://open-forecast.eu/), we applied the WRF-Chem model system version 4.0.3 in order to close this knowledge gap. We zoom in the urban area of Stuttgart, a hot spot of air pollution in Germany. The outermost domain with convection-permitting resolution of 1.25 km encompasses parts of Central Europe in order to provide boundary conditions for the inner two domains.The model system was improved in many ways, e.g., with respect to the representation of land cover, urban canopy, and soil properties, which turned out to be key for an acceptable performance. Furthermore, we developed a sophisticated infrastructure to ingest the required high-resolution emission data, which turned out to be very challenging.We show that this model approach is likely the best means to understand and to predict air pollution, as the distribution of their constituents depends strongly and simultaneously on the vertical mixing by turbulence, the mesoscale circulation in the complex urban environment, and orographic environment.The model system was operated and investigated for a case study of January 21, 2019 during which an alert with respect to the exceedance of PM10 was issued. We present the simulations of meteorological variables as well as PM10 and NO2 and show the complexity of their distribution in the nighttime stable and daytime shallow boundary layer in dependence of the temporal variability of the traffic in the Stuttgart metropolitan area.To the best of our knowledge, the results reveal for the first time the complex dynamics of air pollution in complex urban space of Stuttgart at a very high spatial and temporal resolution that cannot currently be achieved with measurements.

The state of the land surface can have a crucial influence on the triggering of convection. Investigations of the land-atmosphere coupling strength on the regional scale are still rare, and have been mainly performed using global climate models with coarse resolutions. Increasing the horizontal resolution and the concomitant improved representation of the land surface are expected to refine the representation of feedbacks. A strong limiting factor, especially for process-based studies of the link between surface moisture availability, land cover properties, and convection triggering, is the availability of data with sufficient vertical resolution and temporal coverage. A convenient metric to investigate this link is the ‘Convection Triggering Potential’-‘Low-Level Humidity Index’ framework, which is applied in this study. This process-based coupling metric examines the boundary layer structure based on temperature and humidity profiles to draw conclusions on the potential strength of interactions. However, increasing the resolution of a simulation usually aggravates the amount of storage capacity needed, and in practice the number of vertical levels written out is often decreased to a handful over the total column. Consequently, a comprehensive regional model intercomparison targeting land-convection coupling strength is challenging.In this study, a perturbation approach was applied as an attempt to overcome this limitation. Differences in the choice and configuration of models cause a spread in mean and variance of atmospheric temperature and humidity between models that in turn may impact the outcome of the framework. Perturbation factors of different magnitudes were added to modify summer atmospheric temperature and humidity from a WRF simulation over the entire column on a daily basis. The simulation covered the period 1986-2015 over the EURO-CORDEX domain. The perturbations were chosen to approximate a potential model spread to some extent. Sensitivity in the coupling strength was assessed in relation to the unperturbed case by applying the framework to a range of perturbation cases with differently strong combinations of temperature and humidity changes.We will present results 1) of how warmer, cooler, dryer or moister conditions in the atmosphere changed the frequency of summer days with high feedback potential, 2) how the different conditions influenced the occurrence of positive relative to negative feedbacks, and 3) of spatial differences in the sensitivity of the coupling strength to temperature or humidity modifications, respectively, over Europe.

Studies have shown the benefits of convection-permitting downscaling at the seasonal scale using limited-area models. To evaluate the performance with real forecasts as boundary conditions, four members of the SEAS5 global ensemble were dynamically downscaled over Ethiopia during June, July, and August 2018 at a 3-km resolution. We used a multi‐physics ensemble based on the WRF model to compare the effects of boundary conditions and physics parametrization producing 16 ensemble members. With ECMWF analyses as a reference, SEAS5 averaged to a +0.17°C bias over Ethiopia whereas WRF resulted in +1.14°C. With respect to precipitation, the WRF model simulated 264 mm compared to 248 mm for SEAS5 and 236 mm for GPM-IMERG. The maximum northward extension of the tropical rain belt decreased by about 2° in both models. Downscaling enhanced the ensemble spread in precipitation by 60% on average, correcting the SEAS5 underdispersion. The WRF ensemble spread over Ethiopia was mostly generated by the perturbed boundary conditions, as their effect is often 50% larger than the physics‐induced variability. The results indicate that boundary condition perturbations are necessary, although not always sufficient, to generate the right amount of ensemble spread in a limited-area model with complex topography. The next step is to use specific methods to calculate the added value provided by the downscaling.

Precipitation observations between March to May 2015 show several coherent propagating systems in an area between 10°N and 10°S with a lifetime of 3-4 weeks demonstrating the importance of simulations beyond a month. The eastward propagation speed is typically 1100 km day-1. The main origins of significant amounts of precipitation along this belt are the tropical warm pools in the Western Pacific around 158-174°E and the eastern Indian Ocean around 90°E as well as the tropical rainforest over South America around 69°W.We investigated the lifetime and propagation of tropical precipitating systems based on observations and a near-global convection permitting seasonal simulation with the Weather Research and Forecasting (WRF). The latitude-belt simulation covers an area between 57°S to 65°N with a grid increment of 0.03° over a period of 5 months forced by sea surface temperature (SST) observations.Results of this simulation with respect to tropical convection were investigated by means of comparison with satellite-based cloud and precipitation observations and ECMWF operational analysis. Wavenumber-frequency spectra of the tropical convection and the detection of various wave pattern were derived from the 3-h outgoing longwave radiation at the top of the atmosphere (TOA OLR) fields and revealed by Wheeler-Kiladis diagrams. The simulation shows the observed spectral signatures of eastward propagating EIGs and Kelvin waves.The EOF decomposition of the monthly averaged sea level pressure fields demonstrates that 65 % of the sea surface pressure fluctuations in the ECMWF analyses can be explained by the correlation pattern shown in the 1st EOF. The agreement with the 1st EOF of the WRF simulation is excellent despite a slight underestimation of the strength of the correlations. The spatial structure is very similar and 61 % of the variance are contained in first EOF. The EOF analyses provided strong evidence that the seasonal simulation with a convection permitting horizontal resolution captures the representation of the teleconnection pattern.

Land-atmosphere energy and water exchanges are fundamentally linked to soil-moisture. The distribution of the planets’ biomes hinges on the surface-atmosphere coupling since soil moisture and temperature feedbacks have a strong influence on plant transpiration and photosynthesis. Land use/land cover changes (LUC) modify locally land surface properties that control the land-atmosphere mass, energy, and momentum exchanges. The impact of these changes depends on the scale and nature of land cover modifications and is very difficult to quantify. However, large inconsistencies in the LUC impacts are observed between models, highlighting the need for common LUC across a large ensemble of models. The Flagship Pilot Study LUCAS (Land Use & Climate Across Scales) provides a coordinated effort to study LUC using an ensemble of regional climate models (RCMs). In the first phase of the project 3 experiments were performed for continental Europe: EVAL (current climate); GRASS (trees replaced by grassland) and FOREST (grasses and shrubs replaced by trees). An analysis of the energy and moisture balance for the three experiments is performed, focusing on the relationship between the fluxes partitioning, heat waves and droughts. To better asses the link between extreme temperatures and soil moisture or evapotranspiration, a new coupling metric for short time scales is proposed, the Latent Heat Flux-Temperature Coupling Magnitude (LETCM). This new metric is computed for a specific period, considering the positive temperature extremes and the negative latent heat flux extremes. Areas with positive magnitude values imply higher temperature anomaly, due to a negative latent heat flux anomaly. This new metric only considers periods of strong coupling, with positive signals in areas of high temperatures and evaporative stress, allowing for the detection of events that are extreme for energy and water cycle. Concurrently, a new decile based normalised drought index is used to examine the concurrent heat extremes and droughts. The analysis focuses on the three experiments revealing that the number, amplitude and spatial distribution of compound extreme heat and drought is highly model dependant. The impact of afforestation or deforestation is not consistent across models.Acknowledgements The authors wish to acknowledge project LEADING (PTDC/CTA-MET/28914/2017) and FCT - project UIDB/50019/2020 - Instituto Dom Luiz.

Air pollution is one of the major challenges in urban areas. It can have a major impact on human health and society and is currently a subject of several litigations in European courts. Information on the level of air pollution is based on near-surface measurements, which are often irregularly distributed along the main traffic roads and provide almost no information about the residential areas and office districts in the cities. To further enhance the process understanding and give scientific support to decision makers, we developed a prototype for an air quality forecasting system (AQFS) within the EU demonstration project “Open Forecast”. For AQFS, the Weather Research and Forecasting model together with its coupled chemistry component (WRF-Chem) is applied for the Stuttgart metropolitan area in Germany. Three model domains from 1.25 km down to a turbulence-permitting resolution of 50 m were used, and a single-layer urban canopy model was active in all domains. As a demonstration case study, 21 January 2019 was selected, which was a heavily polluted day with observed PM10 concentrations exceeding 50 µg m−3. Our results show that the model is able to reasonably simulate the diurnal cycle of surface fluxes and 2 m temperatures as well as evolution of the stable and shallow boundary layer typically occurring in wintertime in Stuttgart. The simulated fields of particulates with a diameter of less than 10 µm (PM10) and nitrogen dioxide (NO2) allow a clear statement about the most heavily polluted areas apart from the irregularly distributed measurement sites. Together with information about the vertical distribution of PM10 and NO2 from the model, AQFS will serve as a valuable tool for air quality forecasting and has the potential of being applied to other cities around the world.

Land-Use and Land Cover Changes (LULCC) play a fundamental role in land-atmosphere interactions, since they mainly regulate the exchange of latent and sensible heat between the ground and the upper air, while they control the amount of shortwave radiation absorbed by the ground. In this study, we make an attempt to investigate the biogeophysical effects of extreme land cover changes on soil variables, such as soil temperature and soil moisture. In particular, we analyze a multi-model ensemble of nine different regional climate model simulations, which had been performed over the Euro-CORDEX domain in the frame of the WCRP CORDEX Flagship Pilot Study LUCAS (Land Use and Climate Across Scales). We compare two idealized experiments: a maximally forested (called FOREST) and a fully grassed Europe (called GRASS). According to our results, the soil temperature response to forestation varies among the climate models. They show a profound seasonality and dependence by latitude. In winter, the magnitude of soil temperature changes is considered weak, showing a warming in high latitudes (around +1oC on average) and a weak cooling over the Mediterranean region. During the summertime, in contrast, soil temperatures are higher in the GRASS experiment, especially in Central and Southern Europe (ranging from +1oC to +3oC depending to the model), underlying the essential role of soil moisture in determining the land-atmosphere feedbacks during the summer. In our contribution, we will present in detail the role of forest and grass characteristics and its effects on seasonal soil conditions across Europe[DR1] .

The evaluation of the first of its kind multi-model convection permitting - regional climate model (CP-RCM) ensemble, produced within the framework of the international CORDEX - Flagship Pilot Study on Convective phenomena over the Mediterranean (CORDEX-FPS-CEM), showed the improved spatial representation, frequency and extremes of precipitation compared to coarser resolution counterparts (Ban et al., submitted 2019). It is important, though, to keep in mind that the quality of each of such high resolution simulations strongly depend on the quality of the forcing used to drive the model.In this work we investigate the impact of the land-surface forcing on the model representation of land-atmosphere (LA) feedback. For that we used the 2 Weather Research and Forecasting (WRF) settings from the CORDEX-FPS-CEM ensemble to run 4 simulations for 2 seasons (summer and fall), combining 2 sets of data for the land cover (MODIS and CORINE) and the top soil texture (FAO and HWSD). In such a way we generated two ensembles with 8 simulations for each season. Additionally we run 4 simulations with perturbed starting date for the summer season to obtain an additional 5-member ensemble to investigate the impact of the internal variability on the final results.The objective of this study is to investigate the model sensitivity to (1) land-surface static forcing, (2) season, and (3) the model configuration. To quantify the strength of LA coupling for each grid, we use coupling metrics appropriate for seasonal time scales. We applied mixing diagram approach to investigate the impact of the land-surface changes on the boundary layer evolution. We also investigate the impact of these changes on the potential for convection triggering, and we calculate correlation matrices to quantify the impact on the strength of the land-atmosphere coupling.Preliminary results show evident effects of the land surface changes on surface variables, boundary layer evolution, atmospheric stability and humidity in the lower atmosphere. Strength of the sensitivity to a specific change in the land-surface forcing depend on the model configuration: WRF with less sophisticated parameterization schemes is more sensitive to land use changes, while more sophisticated configuration shows higher sensitivity to the soil texture changes in representing boundary layer evolution. Furthermore, the WRF shows stronger coupling and therefore stronger sensitivity to the land surface changes in the summer season.Acknowledgement: This work is partially funded by the Spanish Government R+D programme through grant INSIGNIA (CGL2016-79210-R) co-funded by the ERDF/FEDER.References: Ban N., and coauthors: The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, Part I: Evaluation of precipitation, (submitted to Climate Dynamics, 2019)

Land surface and hydrologic models (LSM/HM) are used at diverse spatial resolutions ranging from 1–10 km in catchment-scale applications to over 50 km in global-scale applications. Application of the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the model resolution and fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent and realistic parameter fields for land surface geophysical properties. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB and WaterGAP models are conducted to demonstrate the pitfalls of poor parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. We provide a short review of existing parameter regionalization techniques and discuss a method for obtaining seamless hydrological predictions of water fluxes and states across multiple spatial resolutions. The multiscale parameter regionalization (MPR) technique is a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. A general model protocol is presented to describe how MPR can be applied to a specific model, with an example of this application using the PCR-GLOBWB model. Applying MPR to PCR-GLOBWB substantially improves the flux-matching condition. Estimation of evapotranspiration without MPR at 5 arcmin and 30 arcmin spatial resolutions for the Rhine river basin results in a difference of approximately 29 %. Applying MPR reduce this difference to 9 %. For total soil water, the differences without and with MPR are 25 % and 7 %, respectively.

A 10 × 10 km irrigated biomass plantation was simulated in an arid region of Israel to simulate diurnal energy balances during the summer of 2012 (JJA). The goal is to examine daytime horizontal flux gradients between plantation and desert. Simulations were carried out within the coupled WRF-NOAH atmosphere/land surface model. MODIS land surface data was adjusted by prescribing tailored land surface and soil/plant parameters, and by adding a controllable sub-surface irrigation scheme to NOAH. Two model cases studies were compared – Impact and Control. Impact simulates the irrigated plantation. Control simulates the existing land surface, where the predominant land surface is bare desert soil. Central to the study is parameter validation against land surface observations from a desert site and from a 400 ha Simmondsia chinensis (jojoba) plantation. Control was validated with desert observations, and Impact with Jojoba observations. Model evapotranspiration was validated with two Penman–Monteith estimates based on the observations. Control simulates daytime desert conditions with a maximum deviation for surface 2 m air temperatures (T2) of 0.2 °C, vapour pressure deficit (VPD) of 0.25 hPa, wind speed (U) of 0.5 m s−1, surface radiation (Rn) of 25 W m−2, soil heat flux (G) of 30 W m−2 and 5 cm soil temperatures (ST5) of 1.5 °C. Impact simulates irrigated vegetation conditions with a maximum deviation for T2 of 1–1.5 °C, VPD of 0.5 hPa, U of 0.5 m s−1, Rn of 50 W m−5, G of 40 W m−2 and ST5 of 2 °C. Latent heat curves in Impact correspond closely with Penman–Monteith estimates, and magnitudes of 160 W m−2 over the plantation are usual. Sensible heat fluxes, are around 450 W m−2 and are at least 100–110 W m−2 higher than the surrounding desert. This surplus is driven by reduced albedo and high surface resistance, and demonstrates that high evaporation rates may not occur over Jojoba if irrigation is optimized. Furthermore, increased daytime T2 over plantations highlight the need for hourly as well as daily mean statistics. Daily mean statistics alone may imply an overall cooling effect due to surplus nocturnal cooling, when in fact a daytime warming effect is observed.

The impact of a convection permitting (CP) northern hemisphere latitude-belt simulation with the Weather Research and Forecasting (WRF) model was investigated during the July and August 2013. For this application, the WRF model together with the NOAH land-surface model (LSM) was applied at two different horizontal resolutions, 0.03° (HIRES) and 0.12° (LOWRES). The set-up as a latitude-belt domain avoids disturbances that originate from the western and eastern boundaries and therefore allows to study the impact of model resolution and physical parameterizations on the results. Both simulations were forced by ECMWF operational analysis data at the northern and southern domain boundaries and the high-resolution Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data at the sea surface. The simulations are compared to the operational ECMWF analysis for the representation of large scale features. To compare the simulated precipitation, the operational ECMWF forecast, the CPC MORPHing (CMORPH), and the ENSEMBLES gridded observation precipitation data set (E-OBS) were used. Compared to the operational high-resolution ECMWF analysis, both simulations are able to capture the large scale circulation pattern though the strength of the Pacific high is considerably overestimated in the LOWRES simulation. Major differences between ECMWF and WRF occur during July 2013 when the lower resolution simulation shows a significant negative bias over the North Atlantic which is not observed in the CP simulation. The analysis indicates deficiencies in the applied combinations of cloud microphysics and convection parametrization on the coarser grid scale in subpolar regions. The overall representation of the 500 hPa geopotential height surface is also improved by the CP simulation compared to the LOWRES simulation apart across Newfoundland where the geopotential height is higher than in the LOWRES simulation due to a northward shift of the location of the Atlantic high pressure system. Both simulations show higher wind speeds in the boundary layer by about 1.5 m s−1 compared to the the ECMWF analysis. Due to the higher surface evaporation, this results in a moist bias of 0.5 g kg−1 at 925 hPa in the planetary boundary layer compared to the ECMWF analysis. Major differences between ECMWF and WRF occur in the simulation of the 2-m temperatures over the Asian desert and steppe regions. They are significantly higher in WRF by about 5 K both during day- and night-time presumably as a result of different soil hydraulic parameters used in the NOAH land surface model for steppe regions. The precipitation of the HIRES simulation shows a better spatial agreement with CMORPH especially over mountainous terrain. The overall bias reduces from 80 mm at the coarser resolution to 50 mm in the HIRES simulation and the root mean square error is reduced by about 35 % when compared to the CMORPH precipitation analysis. The precipitation distribution agrees much better with the CMORPH data than the LOWRES simulation which tends to overestimate precipitation, mainly caused by the convection parametrization. Especially over Europe the CP resolution reduces the precipitation bias by about 30 % to 20 mm as a result of a better terrain representation and due to the avoidance of the convection parameterization.

Despite considerable progress in recent years, output of both global and regional circulation models is still afflicted with biases to a degree that precludes its direct use, especially in climate change impact studies. This is well known, and to overcome this problem, bias correction (BC; i.e. the correction of model output towards observations in a post-processing step) has now become a standard procedure in climate change impact studies. In this paper we argue that BC is currently often used in an invalid way: it is added to the GCM/RCM model chain without sufficient proof that the consistency of the latter (i.e. the agreement between model dynamics/model output and our judgement) as well as the generality of its applicability increases. BC methods often impair the advantages of circulation models by altering spatiotemporal field consistency, relations among variables and by violating conservation principles. Currently used BC methods largely neglect feedback mechanisms, and it is unclear whether they are time-invariant under climate change conditions. Applying BC increases agreement of climate model output with observations in hindcasts and hence narrows the uncertainty range of simulations and predictions without, however, providing a satisfactory physical justification. This is in most cases not transparent to the end user. We argue that this hides rather than reduces uncertainty, which may lead to avoidable forejudging of end users and decision makers. We present here a brief overview of state-of-the-art bias correction methods, discuss the related assumptions and implications, draw conclusions on the validity of bias correction and propose ways to cope with biased output of circulation models in the short term and how to reduce the bias in the long term. The most promising strategy for improved future global and regional circulation model simulations is the increase in model resolution to the convection-permitting scale in combination with ensemble predictions based on sophisticated approaches for ensemble perturbation. With this article, we advocate communicating the entire uncertainty range associated with climate change predictions openly and hope to stimulate a lively discussion on bias correction among the atmospheric and hydrological community and end users of climate change impact studies.