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 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 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.

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.

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.

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 Inter-comparison of two land-surface models applied at different scales and their feedbacks while coupled with a regional climate model

2012 ◽  
Vol 16 (3) ◽  
pp. 1017-1031 ◽  
Author(s):  
F. Zabel ◽  
W. Mauser ◽  
T. Marke ◽  
A. Pfeiffer ◽  
G. Zängl ◽  
...  
Keyword(s):  
Land Use ◽  
Land Surface ◽  
Regional Climate ◽  
Moderate Increase ◽  
Net Radiation ◽  
Land Surface Models ◽  
Near Surface ◽  
Temporal Behaviour ◽  
Surface Models ◽  
The Alps

Abstract. Downstream models are often used in order to study regional impacts of climate and climate change on the land surface. For this purpose, they are usually driven offline (i.e., 1-way) with results from regional climate models (RCMs). However, the offline approach does not allow for feedbacks between these models. Thereby, the land surface of the downstream model is usually completely different to the land surface which is used within the RCM. Thus, this study aims at investigating the inconsistencies that arise when driving a downstream model offline instead of interactively coupled with the RCM, due to different feedbacks from the use of different land surface models (LSM). Therefore, two physically based LSMs which developed from different disciplinary backgrounds are compared in our study: while the NOAH-LSM was developed for the use within RCMs, PROMET was originally developed to answer hydrological questions on the local to regional scale. Thereby, the models use different physical formulations on different spatial scales and different parameterizations of the same land surface processes that lead to inconsistencies when driving PROMET offline with RCM output. Processes that contribute to these inconsistencies are, as described in this study, net radiation due to land use related albedo and emissivity differences, the redistribution of this net radiation over sensible and latent heat, for example, due to different assumptions about land use impermeability or soil hydraulic reasons caused by different plant and soil parameterizations. As a result, simulated evapotranspiration, e.g., shows considerable differences of max. 280 mm yr−1. For a full interactive coupling (i.e., 2-way) between PROMET and the atmospheric part of the RCM, PROMET returns the land surface energy fluxes to the RCM and, thus, provides the lower boundary conditions for the RCM subsequently. Accordingly, the RCM responses to the replacement of the LSM with overall increased annual mean near surface air temperature (+1 K) and less annual precipitation (−56 mm) with different spatial and temporal behaviour. Finally, feedbacks can set up positive and negative effects on simulated evapotranspiration, resulting in a decrease of evapotranspiration South of the Alps a moderate increase North of the Alps. The inconsistencies are quantified and account for up to 30% from July to Semptember when focused to an area around Milan, Italy.

scholarly journals Evaluation of the snow regime in dynamic vegetation land surface models using field measurements

2013 ◽  
Vol 7 (3) ◽  
pp. 2333-2372
Author(s):  
E. Kantzas ◽  
M. Lomas ◽  
S. Quegan ◽  
E. Zakharova
Keyword(s):  
Land Surface ◽  
Field Data ◽  
Climate Models ◽  
Optimization Techniques ◽  
The Arctic ◽  
Surface Model ◽  
Land Surface Models ◽  
Snow Density ◽  
Data Set ◽  
Surface Models

Abstract. An increasing number of studies have demonstrated the significant climatic and ecological changes occurring in the northern latitudes over the past decades. As coupled, earth-system models attempt to describe and simulate the dynamics and complex feedbacks of the Arctic environment, it is important to reduce their uncertainties in short-term predictions by improving the description of both the systems processes and its initial state. This study focuses on snow-related variables and extensively utilizes a historical data set (1966–1996) of field snow measurements acquired across the extend of the Former Soviet Union (FSU) to evaluate a range of simulated snow metrics produced by a variety of land surface models, most of them embedded in IPCC-standard climate models. We reveal model-specific issues in simulating snow dynamics such as magnitude and timings of SWE as well as evolution of snow density. We further employ the field snow measurements alongside novel and model-independent methodologies to extract for the first time (i) a fresh snow density value (57–117 kg m–3) for the region and (ii) mean monthly snowpack sublimation estimates across a grassland-dominated western (November–February) [9.2, 6.1, 9.15, 15.25] mm and forested eastern sub-sector (November–March) [1.53, 1.52, 3.05, 3.80, 12.20] mm; we subsequently use the retrieved values to assess relevant model outputs. The discussion session consists of two parts. The first describes a sensitivity study where field data of snow depth and snow density are forced directly into the surface heat exchange formulation of a land surface model to evaluate how inaccuracies in simulating snow metrics affect important modeled variables and carbon fluxes such as soil temperature, thaw depth and soil carbon decomposition. The second part showcases how the field data can be assimilated with ready-available optimization techniques to pinpoint model issues and improve their performance.

scholarly journals Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

2015 ◽  
Vol 12 (24) ◽  
pp. 7503-7518 ◽  
Author(s):  
M. G. De Kauwe ◽  
S.-X. Zhou ◽  
B. E. Medlyn ◽  
A. J. Pitman ◽  
Y.-P. Wang ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
Soil Water Potential ◽  
Abrupt Onset ◽  
Future Climate Change ◽  
Land Surface Models ◽  
Drought Sensitivity ◽  
Coupled Climate Models ◽  
Surface Models

Abstract. Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSM and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.

Sign in / Sign up

Export Citation Format

Share Document