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.

Evaluation of Temperature Simulation over Northern Thailand from Regional Climate Model Coupled with Land Surface Model

2017 ◽  
Vol 866 ◽  
pp. 108-111
Author(s):  
Theerapan Saesong ◽  
Pakpoom Ratjiranukool ◽  
Sujittra Ratjiranukool
Keyword(s):  
Regional Climate Model ◽  
Land Surface ◽  
Climate Model ◽  
Global Analysis ◽  
Regional Climate ◽  
Land Surface Model ◽  
Analysis Data ◽  
Surface Model ◽  
Northern Thailand ◽  
Weather Model

Numerical Weather Model called The Weather Research and Forecasting model, WRF, developed by National Center for Atmospheric Research (NCAR) is adapted to be regional climate model. The model is run to perform the daily mean air surface temperatures over northern Thailand in 2010. Boundery dataset provided by National Centers for Environmental Prediction, NCEP FNL, (Final) Operational Global Analysis data which are on 10 x 10. The simulated temperatures by WRF with four land surface options, i.e., no land surface scheme (option 0), thermal diffusion (option 1), Noah land-surface (option 2) and RUC land-surface (option 3) were compared against observational data from Thai Meteorological Department (TMD). Preliminary analysis indicated WRF simulations with Noah scheme were able to reproduce the most reliable daily mean temperatures over northern Thailand.

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 Assessment of the Urban Impact on Surface and Screen-Level Temperature in the ALADIN-Climate Driven SURFEX Land Surface Model for Budapest

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 709
Author(s):  
Gabriella Zsebeházi ◽  
Sándor István Mahó
Keyword(s):  
Surface Temperature ◽  
Regional Climate Model ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Land Surface Model ◽  
Surface Model ◽  
Urban Impact ◽  
Model Driven ◽  
The Impact

Land surface models with detailed urban parameterization schemes provide adequate tools to estimate the impact of climate change in cities, because they rely on the results of the regional climate model, while operating on km scale at low cost. In this paper, the SURFEX land surface model driven by the evaluation and control runs of ALADIN-Climate regional climate model is validated over Budapest from the aspect of urban impact on temperature. First, surface temperature of SURFEX with forcings from ERA-Interim driven ALADIN-Climate was compared against the MODIS land surface temperature for a 3-year period. Second, the impact of the ARPEGE global climate model driven ALADIN-Climate was assessed on the 2 m temperature of SURFEX and was validated against measurements of a suburban station for 30 years. The spatial extent of surface urban heat island (SUHI) is exaggerated in SURFEX from spring to autumn, because the urbanized gridcells are generally warmer than their rural vicinity, while the observed SUHI extent is more variable. The model reasonably simulates the seasonal means and diurnal cycle of the 2 m temperature in the suburban gridpoint, except summer when strong positive bias occurs. However, comparing the two experiments from the aspect of nocturnal UHI, only minor differences arose. The thorough validation underpins the applicability of SURFEX driven by ALADIN-Climate for future urban climate projections.

scholarly journals Land Surface Model influence on the simulated climatologies of temperature and precipitation extremes in the WRF v.3.9 model over North America

2020 ◽  
Author(s):  
Almudena García-García ◽  
Francisco José Cuesta-Valero ◽  
Hugo Beltrami ◽  
J. Fidel González-Rouco ◽  
Elena García-Bustamante ◽  
...  
Keyword(s):  
North America ◽  
Regional Climate Model ◽  
Extreme Events ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Temperature And Precipitation

Abstract. The representation and projection of extreme temperature and precipitation events in regional and global climate models are of major importance for the study of climate change impacts. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensity, duration and frequency of these extremes. Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) model to determine the influence of the land surface model (LSM) component on uncertainties associated with extreme events. First, we evaluate land-atmosphere interactions within four simulations performed by the WRF model using three different LSMs from 1980 to 2012 over North America. Results show LSM-dependent differences at regional scales in the frequency of occurrence of events when surface conditions are altered by atmospheric forcing or land processes. The inter-model range of extreme statistics across the WRF simulations is large, particularly for indices related to the intensity and duration of temperature and precipitation extremes. Areas showing large uncertainty in WRF simulated extreme events are also identified in a model ensemble from three different Regional Climate Model (RCM) simulations participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project, revealing the implications of these results for other model ensembles. This study illustrates the importance of the LSM choice in climate simulations, supporting the development of new modeling studies using different LSM components to understand inter-model differences in simulating temperature and precipitation extreme events, which in turn will help to reduce uncertainties in climate model projections.

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.

Evaluation of agricultural-related extreme events in hindcast COSMO-CLM simulations over Central Europe 

2021 ◽  
Author(s):  
Huan Zhang ◽  
Merja Tölle
Keyword(s):  
Regional Climate Model ◽  
Central Europe ◽  
Extreme Events ◽  
Climate Models ◽  
Climate Model ◽  
Crop Yields ◽  
Regional Climate ◽  
Extreme Weather ◽  
Horizontal Resolution ◽  
Extreme Weather Events

<p>Convection-permitting regional climate model simulations may serve as driving data for crop and dynamic vegetation models. It is thus possible to generate physically consistent scenarios for the future-concerning effects of climate change on crop yields and pollinators. Here, we performed convection-permitting hindcast simulations with the regional climate model COSMO5.0-CLM16 (CCLM) from 1980 to 2015 with a spin-up starting at 1979. The model was driven with hourly ERA5 data, which is the latest climate reanalysis product by ECMWF and directly downscaled to 3 km horizontal resolution over central Europe. The land-use classes are described by ECOCLIMAP, and the soil type and depth by HWSD. The evaluation is carried out in terms of temperature, precipitation, and extreme weather indices, comparing CCLM output with the gridded observational dataset HYRAS from the German Weather Service. While CCLM inherits a warm/cold and dry/wet summer/winter bias found in its parent model, it reproduces the main features of the present climate of the study domain, including the distribution, the seasonal mean climate patterns, and probability density distributions. The bias for precipitation ranges between ±20 % and the bias for temperature between ±1 °C compared to the observations over most of the regions. This is in the range of the bias between observational data. Furthermore, the model catches extreme weather events related to droughts, floods, heat/cold waves, and agriculture-specific events. The results highlight the possibility to directly downscale ERA5 data with regional climate models avoiding the multiple nesting approach and high computational costs. This study adds confidence to convection-permitting climate simulations of future changes in agricultural extreme events.</p>

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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