scholarly journals Results from a full coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model for a Danish catchment

2014 ◽  
Vol 11 (3) ◽  
pp. 3005-3047 ◽  
Author(s):  
M. A. D. Larsen ◽  
J. C. Refsgaard ◽  
M. Drews ◽  
M. B. Butts ◽  
K. H. Jensen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Research Field ◽  
Land Surface Models ◽  
Mike She ◽  
Simulated Precipitation ◽  
Surface Models

Abstract. In recent years research on the coupling of existing regional climate models and hydrology/land surface models has emerged. A major challenge in this emerging research field is the computational interaction between the models. In this study we present results from a full two-way coupling of the HIRHAM regional climate model over a 4000 km x 2800 km domain in 11 km resolution and the combined MIKE SHE-SWET hydrology and land surface models over the 2500 km2 Skjern river catchment. A total of 26 one-year runs were performed to assess the influence of the data transfer interval (DTI) between the two models and the internal HIRHAM model variability of ten variables. In general, the coupled model simulations exhibit less accurate performance than the uncoupled simulations which is to be expected as both models prior to this study have been individually refined or calibrated to reproduce observations. Four of six output variables from HIRHAM, precipitation, relative humidity, wind speed and air temperature, showed statistically significant improvements in RMSE with a reduced DTI as evaluated in the range of 12–120 min. For these four variables the perturbation induced HIRHAM variability was shown to correspond to 47% of the RMSE improvement when using a DTI of 120 min compared to a DTI of 12 min and the variability resulted in large ranges in simulated precipitation. Also, the DTI was shown to substantially affect computation time. The MIKE SHE energy flux and discharge output variables experienced little impact from the DTI.

scholarly journals Results from a full coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model for a Danish catchment

2014 ◽  
Vol 18 (11) ◽  
pp. 4733-4749 ◽  
Author(s):  
M. A. D. Larsen ◽  
J. C. Refsgaard ◽  
M. Drews ◽  
M. B. Butts ◽  
K. H. Jensen ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Coupled Model ◽  
Research Field ◽  
Land Surface Models ◽  
Mike She ◽  
Simulated Precipitation ◽  
Surface Models

Abstract. A major challenge in the emerging research field of coupling of existing regional climate models (RCMs) and hydrology/land-surface models is the computational interaction between the models. Here we present results from a full two-way coupling of the HIRHAM RCM over a 4000 km × 2800 km domain at 11 km resolution and the combined MIKE SHE-SWET hydrology and land-surface models over the 2500 km2 Skjern River catchment. A total of 26 one-year runs were performed to assess the influence of the data transfer interval (DTI) between the two models and the internal HIRHAM model variability of 10 variables. DTI frequencies between 12 and 120 min were assessed, where the computational overhead was found to increase substantially with increasing exchange frequency. In terms of hourly and daily performance statistics the coupled model simulations performed less accurately than the uncoupled simulations, whereas for longer-term cumulative precipitation the opposite was found, especially for more frequent DTI rates. Four of six output variables from HIRHAM, precipitation, relative humidity, wind speed and air temperature, showed statistically significant improvements in root-mean-square error (RMSE) by reducing the DTI. For these four variables, the HIRHAM RMSE variability corresponded to approximately half of the influence from the DTI frequency and the variability resulted in a large spread in simulated precipitation. Conversely, DTI was found to have only a limited impact on the energy fluxes and discharge simulated by MIKE SHE.

scholarly journals Inter-comparison of two land-surface schemes applied on different scales and their feedbacks while coupled with a regional climate model

2011 ◽  
Vol 8 (4) ◽  
pp. 7091-7136 ◽  
Author(s):  
F. Zabel ◽  
W. Mauser ◽  
T. Marke ◽  
A. Pfeiffer ◽  
G. Zängl ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Regional Climate Model ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Land Surface Models ◽  
Feedback Effects ◽  
Surface Models ◽  
Vegetation Water

Abstract. Feedback effects between the land surface and the atmosphere are an important issue in modelling the climate system. Therefore, in order to take land surface heterogeneity adequately into account, a representation of the land surface in sufficient spatial resolution is necessary. In order to analyze the impact of different land surface models on the atmosphere, we analyzed the differences of two physically based land surface models, which evolved from different disciplinary backgrounds, both fully coupled with the regional climate model MM5, providing the atmospheric drivers. While the NOAH-LSM originally was developed for atmosphere applications, PROMET is primarily used as a hydrological land surface model. Both use different physical approaches and different spatial resolutions of 45 km (NOAH) and 1 km (PROMET) respectively, to represent the land surface processes. The parameterization of soil and plant properties in terms of phenological behaviour and water-stress is treated with a higher level of detail in PROMET. Used with same atmospheric drivers over a four-year period for Central Europe, the model differences have strong impacts on simulated evapotranspiration and soil moisture both spatially and temporally. Regions with high proportion of impervious surfaces show the highest differences in simulated evapotranspiration (up to 30 %). Further, PROMET simulations show lower evapotranspiration rates e.g. in the Po Valley, caused mainly by a higher level of vegetation water stress. In order to study feedback effects, PROMET was then bilaterally coupled with MM5. The feedbacks result in increasing near surface air temperature and decreasing precipitation especially in Southern Europe and are a result of regional self-amplification effects due to decreasing soil moisture and increasing vegetation water stress.

scholarly journals A multivariate comparison of two land-surface models integrated into an Arctic Regional Climate System model

1997 ◽  
Vol 25 ◽  
pp. 127-131
Author(s):  
Amanda Lynch ◽  
David McGinnis ◽  
William L. Chapman ◽  
Jeffrey S. Tilley
Keyword(s):  
Regional Climate Model ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Climate System ◽  
System Model ◽  
Small Scale ◽  
Land Surface Models ◽  
Climate System Model ◽  
Surface Models

Different vegetation models impact the atmospheric response of a regional climate model in different ways, and hence have an impact upon the ability of that model to match an observed climatology. Using a multivariate principal-component analysis, we investigate the relationships between several land-surface models (BATS, LSM) coupled to a regional climate model, and observed climate parameters over the North Slope of Alaska. In this application, annual cycle simulations at 20 km spatial resolution are compared with European Centre for Medium-Range Weather Forecasts (ECMWF) climatology. Initial results demonstrate broad agreement between all models; however, small-scale regional variations between land-surface models indicate the strengths and weaknesses of the land-surface treatments in a climate system model. Specifically, we found that the greater surface-moisture availability and temperature-dependent albedo formulation of the LSM model allow for a higher proportion of low-level cloud, and a later, more rapid transition from the winter to the summer regime. Crucial to this transition is the seasonal cycle of incoming solar radiation. These preliminary results indicate the importance of the land-surface hydrologic cycle in modelling the seasonal transitions.

scholarly journals A multivariate comparison of two land-surface models integrated into an Arctic Regional Climate System model

1997 ◽  
Vol 25 ◽  
pp. 127-131
Author(s):  
Amanda Lynch ◽  
David McGinnis ◽  
William L. Chapman ◽  
Jeffrey S. Tilley
Keyword(s):  
Regional Climate Model ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Climate System ◽  
System Model ◽  
Small Scale ◽  
Land Surface Models ◽  
Climate System Model ◽  
Surface Models

Different vegetation models impact the atmospheric response of a regional climate model in different ways, and hence have an impact upon the ability of that model to match an observed climatology. Using a multivariate principal-component analysis, we investigate the relationships between several land-surface models (BATS, LSM) coupled to a regional climate model, and observed climate parameters over the North Slope of Alaska. In this application, annual cycle simulations at 20 km spatial resolution are compared with European Centre for Medium-Range Weather Forecasts (ECMWF) climatology. Initial results demonstrate broad agreement between all models; however, small-scale regional variations between land-surface models indicate the strengths and weaknesses of the land-surface treatments in a climate system model. Specifically, we found that the greater surface-moisture availability and temperature-dependent albedo formulation of the LSM model allow for a higher proportion of low-level cloud, and a later, more rapid transition from the winter to the summer regime. Crucial to this transition is the seasonal cycle of incoming solar radiation. These preliminary results indicate the importance of the land-surface hydrologic cycle in modelling the seasonal transitions.

scholarly journals Land-atmosphere interactions in sub-polar and alpine climates in the CORDEX FPS LUCAS models: Part II. The role of changing vegetation

2021 ◽  
Author(s):  
Priscilla A. Mooney ◽  
Diana Rechid ◽  
Edouard L. Davin ◽  
Eleni Katragkou ◽  
Natalie de Noblet-Ducoudré ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Climate Models ◽  
Regional Climate ◽  
Model Development ◽  
Regional Climate Models ◽  
Sensitivity Index ◽  
Land Surface Models ◽  
Snow Albedo ◽  
Surface Models

Abstract. Land cover in sub-polar and alpine regions of northern and eastern Europe have already begun changing due to natural and anthropogenic changes such as afforestation. This will impact the regional climate and hydrology upon which societies in these regions are highly reliant. This study aims to identify the impacts of afforestation/reforestation (hereafter afforestation) on snow and the snow-albedo effect, and highlight potential improvements for future model development. The study uses an ensemble of nine regional climate models for two different idealised experiments covering a 30-year period; one experiment replaces most land cover in Europe with forest while the other experiment replaces all forested areas with grass. The ensemble consists of nine regional climate models composed of different combinations of five regional atmospheric models and six land surface models. Results show that afforestation reduces the snow-albedo sensitivity index and enhances snow melt. While the direction of change is robustly modelled, there is still uncertainty in the magnitude of change. Greatest differences between models emerge in the snowmelt season. One regional climate model uses different land surface models which shows consistent changes between the three simulations during the accumulation period but differs in the snowmelt season. Together these results point to the need for further model development in representing both grass-snow and forest-snow interactions during the snowmelt season. Pathways to accomplishing this include 1) a more sophisticated representation of forest structure, 2) kilometer scale simulations, and 3) more observational studies on vegetation-snow interactions in Northern Europe.

Evaluation of the regional climate model RegCM4.7 over the Carpathian region for very wet and average years

2020 ◽  
Author(s):  
Tímea Kalmár ◽  
Ildikó Pieczka ◽  
Rita Pongrácz
Keyword(s):  
Soil Moisture ◽  
Regional Climate Model ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Cloud Microphysics ◽  
Mountainous Area ◽  
Model Version ◽  
Carpathian Region

<p>Precipitation is one of the most important climate variables in many aspects due to its key impact on agriculture, water management, etc. However, it remains a challenge for climate models to realistically simulate the regional patterns, temporal variations, and intensity of precipitation. The difficulty arises from the complexity of precipitation processes within the atmosphere stemming from cloud microphysics, cumulus convection, large-scale circulations, planetary boundary layer (PBL) processes, and many others. This is especially true for heterogeneous surfaces with complex orography such as the Carpathian region.  Thus, the Carpathian Basin, with its surrounding mountains, requires higher model resolution, along with different parameterizations, compared to more homogenous regions. The aim of the study is to reproduce the historical precipitation pattern through testing the parameterization of surface processes. The appropriate representations of land surface component in climate models are essential for the simulation of surface and subsurface runoff, soil moisture, and evapotranspiration. Furthermore, PBL strongly influences temperature, moisture, and wind through the turbulent transfer of air mass. The current study focuses on the newest model version of RegCM (RegCM4.7), with which we carry out simulations using different parameterization schemes over the Carpathian region. We investigate the effects of land-surface schemes (i.e. BATS - Biosphere-Atmosphere Transfer Scheme and CLM4.5 - Community Land Model version 4.5) in the regional climate model. Studies over different regions have shown that CLM offers improvements in terms of land–atmosphere exchanges of moisture and energy and associated surface climate feedbacks compared with BATS. Our aim includes evaluating whether this is the case for the Carpathian region.</p><p>Four 1-year-long experiments both for 1981 and 2010 (excluding the spin-up time) are completed using the same domain, initial and lateral atmospheric boundary data conditions (i.e. ERA-Interim), with a 10 km spatial resolution. These years were chosen because 1981 was a normal year in terms of precipitation, while 2010 was the wettest year in Hungary from the beginning of the 20th century. We carry out a detailed analysis of RegCM outputs focusing not only on standard climatological variables (precipitation and temperature), but also on additional meteorological variables, which have important roles in the water cycle (e.g. soil moisture, evapotranspiration). The simulations are compared with the CARPATCLIM observed, homogenised, gridded dataset and other databases (ESA CCI Soil Moisture Product New Version Release (v04.5) and Surface Solar Radiation Data Set - Heliosat (SARAH)). It is found that the simulated near-surface temperature and precipitation are better represented in the CLM scheme than in the BATS when compared with observations, both over the lowland and mountainous area. The model simulations also show that the precipitation is overestimated more over mountainous area in 2010 than in 1981.  </p>

scholarly journals Validating the water vapour content from a reanalysis product and a regional climate model over Europe based on GNSS observations

2018 ◽  
Author(s):  
Julie Berckmans ◽  
Roeland Van Malderen ◽  
Eric Pottiaux ◽  
Rosa Pacione ◽  
Rafiq Hamdi
Keyword(s):  
Regional Climate Model ◽  
Water Vapour ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Horizontal Resolution ◽  
Global Navigation Satellite Systems ◽  
Surface Model ◽  
Water Vapour Content

Abstract. The use of ground-based observations is suitable for the assessment of atmospheric water vapour in climate models. Global Navigation Satellite Systems (GNSS) provide information on the Integrated Water Vapour (IWV), at a high temporal and spatial resolution. We used IWV observations at 100 European GNSS sites to evaluate the regional climate model ALARO running at 20 km horizontal resolution and coupled to the land surface model SURFEX, driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) data. The observations recorded in the selected stations span from 1996 to 2014 (with minimum 10 years) and were homogeneously reprocessed during the second reprocessing campaign of the EUREF Permanent Network (EPN Repro2). The outcome of the reprocessing was then used to compute IWV time series at these stations. The yearly cycle of the IWV for the 19-year period from 1996 to 2014 reveals that the model simulates well the seasonal variation. Although the model overestimates IWV during winter and spring, it is consistent with the driving field of ERA-Interim. However, the agreement with ERA-Interim is less in summer, when the model demonstrates an underestimation of the IWV. The model presents a cold and dry bias in summer that feedbacks to a lower evapotranspiration and results in too few water vapour. The spatial variability among the sites is high and shows a dependence on the altitude of the stations which is strongest in summer and by ALARO-SURFEX. The IWV diurnal cycle presents best results with ERA-Interim in the morning, whereas ALARO-SURFEX presents best results at midnight.

Use of Satellite-Based Precipitation Observation in Improving the Parameterization of Canopy Hydrological Processes in Land Surface Models

2005 ◽  
Vol 6 (5) ◽  
pp. 745-763 ◽  
Author(s):  
Dagang Wang ◽  
Guiling Wang ◽  
Emmanouil N. Anagnostou
Keyword(s):  
Land Surface ◽  
Rain Rate ◽  
Climate Models ◽  
Climate Model ◽  
Model Simulation ◽  
Heat Fluxes ◽  
Land Surface Models ◽  
Canopy Interception ◽  
Surface Models ◽  
Rain Rates

Abstract Precipitation exhibits significant spatial variability at scales much smaller than the typical size of climate model grid cells. Neglecting such subgrid-scale variability in climate models causes unrealistic representation of land–atmosphere flux exchanges. It is especially problematic over densely vegetated land. This paper addresses this issue by incorporating satellite-based precipitation observations into the representation of canopy interception processes in land surface models. Rainfall data derived from passive microwave (PM) observations are used to obtain realistic estimates of 1) conditional mean rain rates, which together with the modeled rain rate are used to estimate the rainfall coverage fraction at each model grid cell in this study, and 2) the probability density function (pdf) of rain rates within the rain-covered areas. Both of these properties significantly impact the land–atmosphere water vapor exchanges. Based on the above information, a statistical–dynamical approach is taken to incorporate the representation of precipitation subgrid variability into canopy interception processes in land surface models. The results reveal that incorporation of precipitation subgrid variability significantly alters the partitioning between runoff and total evapotranspiration as well as the partitioning among the three components of evapotranspiration (i.e., canopy interception loss, ground evaporation, and plant transpiration). This further influences soil water, surface temperature, and surface heat fluxes. It is shown that the choice of the rain-rate pdf within rain-covered areas has an effect on the model simulation of land–atmosphere flux exchanges. This study demonstrates that land surface and climate models can substantially benefit from the fine-resolution remotely sensed rainfall observations.

REMOLAND: New high-resolution surface boundary data for the regional climate model REMO and their impacts

2020 ◽  
Author(s):  
Katrin Ziegler ◽  
Felix Pollinger ◽  
Daniel Abel ◽  
Heiko Paeth
Keyword(s):  
High Resolution ◽  
Regional Climate Model ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Data Sets ◽  
Surface Boundary ◽  
Local Climate

<p class="western" align="justify"><span lang="en-US">In cooperation with the Climate Service Center Germany (GERICS) we want to improve the land surface module in the regional climate model REMO. Due to the need of high-resolution regional climate models to get information about local climate change, new data and new processes have to be integrated in these models.</span></p> <p class="western" align="justify"><span lang="en-US">Based on the REMO2015 version and focusing on EUR-CORDEX region we included and compared five different high-resolution topographic data sets. To improve the thermal and hydrological processes in the model’s soil we also tested three new soil data sets with a much higher spatial resolution and with new parameters for a new soil parameterization.</span></p>

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