scholarly journals A high resolution reference data set of German wind velocity 19512001 and comparison with regional climate model results

2006 ◽  
Vol 15 (6) ◽  
pp. 585-596 ◽  
Author(s):  
Andreas Walter ◽  
Klaus Keuler ◽  
Daniela Jacob ◽  
Richard Knoche ◽  
Alexander Block ◽  
...  
SOLA ◽  
2020 ◽  
Vol 16 (0) ◽  
pp. 132-139
Author(s):  
Sheau Tieh Ngai ◽  
Hidetaka Sasaki ◽  
Akihiko Murata ◽  
Masaya Nosaka ◽  
Jing Xiang Chung ◽  
...  

2021 ◽  
Author(s):  
Florian Ehmele ◽  
Lisa-Ann Kautz ◽  
Hendrik Feldmann ◽  
Yi He ◽  
Martin Kadlec ◽  
...  

<p>Enduring and extensive heavy precipitation associated with widespread river floods are among the main natural hazards affecting Central Europe. Since such events are characterized by long return periods, it is difficult to adequately quantify their frequency and intensity solely based on the available observations of precipitation. Furthermore, long-term observations are rare, not homogeneous in space and time, and thus not suitable to run hydrological models (HMs). To overcome this issue, we make use of the recently introduced LAERTES-EU (LArge Ensemble of Regional climaTe modEl Simulations for EUrope) data set, which is an ensemble of regional climate model simulations providing 12.000 simulated years. LAERTES-EU is adapted and applied for the use in an HM to calculate discharges for large river catchments in Central Europe, where the Rhine catchment serves as the pilot area for calibration and validation. Quantile mapping with a fixed density function is used to correct the bias in model precipitation. The results show clear improvements in the representation of both precipitation (e.g., annual cycle and intensity distributions) and simulated discharges by the HM after the bias correction. Furthermore, the large size of LAERTES-EU improves the statistical representativeness also for high return values of precipitation and discharges. While for the Rhine catchment a clear added value is identified, the results are more mixed for other catchments (e.g., the Upper Danube).</p>


2019 ◽  
Vol 101 ◽  
pp. 03004
Author(s):  
Rohit Srivastava ◽  
Ruchita Shah

Global warming is an increase in average global temperature of the earth which lead to climate change. Heterogeneity in the earth-atmosphere system becomes difficult to capture at low resolution (1°x1°) by satellite. Such features may be captured by using high resolution model such as regional climate model (0.5°x 0.5°). This type of study is quite important for a monsoon dominated country like India where Indo-Gangetic Plains (IGP) faces highest heterogeneity due to its geographic location. Present study compares high resolution model features with satellite data over IGP for monsoon season during a normal rainfall year 2010 to understand the actual performance of model. Almost whole IGP simulates relative humidity (RH) with wide range (~50-100%), whereas satellite shows it with narrow range (~60-80%) during September, 2010. Thus model is able to pick the features which were missed by satellite. Hence further model simulation extends over India and adjoining oceanic regions which simulates data of southwest monsoon with high (~70-100%) RH, high (~0.4-0.7) cloud fraction (CF) and low (~80-200 W/m2) outgoing longwave radiation (OLR) over Arabian Sea during June, 2010. Such type of study can be useful to understand heterogeneity at regional scale with the help of high resolution model generated data.


2010 ◽  
Vol 23 (7) ◽  
pp. 1854-1873 ◽  
Author(s):  
E-S. Im ◽  
E. Coppola ◽  
F. Giorgi ◽  
X. Bi

Abstract A mosaic-type parameterization of subgrid-scale topography and land use (SubBATS) is applied for a high-resolution regional climate simulation over the Alpine region with a regional climate model (RegCM3). The model coarse-gridcell size in the control simulation is 15 km while the subgridcell size is 3 km. The parameterization requires disaggregation of atmospheric variables from the coarse grid to the subgrid and aggregation of surface fluxes from the subgrid to the coarse grid. Two 10-yr simulations (1983–92) are intercompared, one without (CONT) and one with (SUB) the subgrid scheme. The authors first validate the CONT simulation, showing that it produces good quality temperature and precipitation statistics, showing in particular a good performance compared to previous runs of this region. The subgrid scheme produces much finer detail of temperature and snow distribution following the topographic disaggregation. It also tends to form and melt snow more accurately in response to the heterogeneous characteristics of topography. In particular, validation against station observations shows that the SUB simulation improves the model simulation of the surface hydrologic cycle, in particular snow and runoff, especially at high-elevation sites. Finally, two experiments explore the model sensitivity to different subgrid disaggregation assumptions, namely, the temperature lapse rate and an empirical elevation-based disaggregation of precipitation.


2017 ◽  
Vol 8 (3) ◽  
pp. 199-211 ◽  
Author(s):  
Rupak Rajbhandari ◽  
Arun Bhakta Shrestha ◽  
Santosh Nepal ◽  
Shahriar Wahid ◽  
Guo-Yu Ren

2008 ◽  
Vol 17 (4) ◽  
pp. 467-476 ◽  
Author(s):  
Martin Suklitsch ◽  
Andreas Gobiet ◽  
Armin Leuprecht ◽  
Christoph Frei

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