scholarly journals VHR-REA_IT Dataset: Very High Resolution Dynamical Downscaling of ERA5 Reanalysis over Italy by COSMO-CLM

Data ◽  
2021 ◽  
Vol 6 (8) ◽  
pp. 88
Author(s):  
Mario Raffa ◽  
Alfredo Reder ◽  
Gian Franco Marras ◽  
Marco Mancini ◽  
Gabriella Scipione ◽  
...  
Keyword(s):  
High Resolution ◽  
Applied Research ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Horizontal Resolution ◽  
Climatological Data ◽  
Recent Climate ◽  
Very High ◽  
Italian Territory

This work presents a new dataset for recent climate developed within the Highlander project by dynamically downscaling ERA5 reanalysis, originally available at ≃31 km horizontal resolution, to ≃2.2 km resolution (i.e., convection permitting scale). Dynamical downscaling was conducted through the COSMO Regional Climate Model (RCM). The temporal resolution of output is hourly (like for ERA5). Runs cover the whole Italian territory (and neighboring areas according to the necessary computation boundary) to provide a very detailed (in terms of space–time resolution) and comprehensive (in terms of meteorological fields) dataset of climatological data for at least the last 30 years (01/1989-12/2020). These types of datasets can be used for (applied) research and downstream services (e.g., for decision support systems).

scholarly journals Very high resolution regional climate model simulations over Greenland: Identifying added value

2012 ◽  
Vol 117 (D2) ◽  
pp. n/a-n/a ◽  
Author(s):  
Philippe Lucas-Picher ◽  
Maria Wulff-Nielsen ◽  
Jens H. Christensen ◽  
Guðfinna Aðalgeirsdóttir ◽  
Ruth Mottram ◽  
...  
Keyword(s):  
High Resolution ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Added Value ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
Very High

scholarly journals Streamflow Data from Small Basins: A Challenging Test to High-Resolution Regional Climate Modeling

2011 ◽  
Vol 12 (5) ◽  
pp. 900-912 ◽  
Author(s):  
Kerstin Stahl ◽  
Lena M. Tallaksen ◽  
Lukas Gudmundsson ◽  
Jens H. Christensen
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Temporal Dynamics ◽  
Model Simulation ◽  
Regional Climate ◽  
Regional Scale ◽  
Climate Simulation ◽  
Change Scenario

Abstract Land surface models and large-scale hydrological models provide the basis for studying impacts of climate and anthropogenic changes on continental- to regional-scale hydrology. Hence, there is a need for comparison and validation of simulated characteristics of spatial and temporal dynamics with independent observations. This study introduces a novel validation framework that relates to common hydrological design measures. The framework is tested by comparing anomalies of runoff from a high-resolution climate-model simulation for Europe with a large number of streamflow observations from small near-natural basins. The regional climate simulation was performed as a “poor man’s reanalysis,” involving a dynamical downscaling of the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) with the Danish “HIRHAM5” model. For 19 different anomaly levels, two indices evaluate the temporal agreement (i.e., the occurrence and frequency of dry and wet events based on daily anomalies), whereas two other indices compare the interannual variability and trends based on annual anomalies. Benchmarks on each index facilitated a comparison across indices, anomaly levels, and basins. The lowest agreement of observed and simulated anomalies was found for dry anomalies. Weak to moderately wet anomalies agreed best, but agreement dropped again for the wettest anomalies. The results could guide the decision on thresholds if this regional climate model were used for the assessment of climate change scenario impacts on flood and drought statistics. Indices vary across Europe, but a gradient with decreasing correspondence between observed and simulated runoff characteristics from west to east, from lower to higher elevations, and from fast to slowly responding basins can be distinguished. The suggested indices can easily be adapted to other study areas and model types to assist in assessing the reliability of predictions of hydrological change.

Estimations of Hazardous Convective Weather in the United States Using Dynamical Downscaling

2014 ◽  
Vol 27 (17) ◽  
pp. 6581-6589 ◽  
Author(s):  
Vittorio A. Gensini ◽  
Thomas L. Mote
Keyword(s):  
United States ◽  
High Resolution ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate Model ◽  
Regional Climate ◽  
The United States ◽  
Regional Model ◽  
Severe Weather ◽  
Convective Weather

Abstract High-resolution (4 km; hourly) regional climate modeling is utilized to resolve March–May hazardous convective weather east of the U.S. Continental Divide for a historical climate period (1980–90). A hazardous convective weather model proxy is used to depict occurrences of tornadoes, damaging thunderstorm wind gusts, and large hail at hourly intervals during the period of record. Through dynamical downscaling, the regional climate model does an admirable job of replicating the seasonal spatial shifts of hazardous convective weather occurrence during the months examined. Additionally, the interannual variability and diurnal progression of observed severe weather reports closely mimic cycles produced by the regional model. While this methodology has been tested in previous research, this is the first study to use coarse-resolution global climate model data to force a high-resolution regional model with continuous seasonal integration in the United States for purposes of resolving severe convection. Overall, it is recommended that dynamical downscaling play an integral role in measuring climatological distributions of severe weather, both in historical and future climates.

scholarly journals Realism of Rainfall in a Very High-Resolution Regional Climate Model

2012 ◽  
Vol 25 (17) ◽  
pp. 5791-5806 ◽  
Author(s):  
Elizabeth J. Kendon ◽  
Nigel M. Roberts ◽  
Catherine A. Senior ◽  
Malcolm J. Roberts
Keyword(s):  
United Kingdom ◽  
High Resolution ◽  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Heavy Rain ◽  
Spatial Extent ◽  
Hourly Rainfall ◽  
Very High

Abstract The realistic representation of rainfall on the local scale in climate models remains a key challenge. Realism encompasses the full spatial and temporal structure of rainfall, and is a key indicator of model skill in representing the underlying processes. In particular, if rainfall is more realistic in a climate model, there is greater confidence in its projections of future change. In this study, the realism of rainfall in a very high-resolution (1.5 km) regional climate model (RCM) is compared to a coarser-resolution 12-km RCM. This is the first time a convection-permitting model has been run for an extended period (1989–2008) over a region of the United Kingdom, allowing the characteristics of rainfall to be evaluated in a climatological sense. In particular, the duration and spatial extent of hourly rainfall across the southern United Kingdom is examined, with a key focus on heavy rainfall. Rainfall in the 1.5-km RCM is found to be much more realistic than in the 12-km RCM. In the 12-km RCM, heavy rain events are not heavy enough, and tend to be too persistent and widespread. While the 1.5-km model does have a tendency for heavy rain to be too intense, it still gives a much better representation of its duration and spatial extent. Long-standing problems in climate models, such as the tendency for too much persistent light rain and errors in the diurnal cycle, are also considerably reduced in the 1.5-km RCM. Biases in the 12-km RCM appear to be linked to deficiencies in the representation of convection.

scholarly journals Long-Term Atmospheric Changes in a Convection-Permitting Regional Climate Model Hindcast Simulation over Northern Germany and the German Bight

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 283
Author(s):  
Benjamin Schaaf ◽  
Frauke Feser ◽  
Insa Meinke
Keyword(s):  
High Resolution ◽  
Regional Climate Model ◽  
German Bight ◽  
Climate Model ◽  
Regional Climate ◽  
Meteorological Variables ◽  
Northern Germany ◽  
Atmospheric Changes ◽  
Very High

Long-term atmospheric changes are a result of complex interactions on various spatial scales. In this study, we examine the long-term variability of the most important meteorological variables in a convection-permitting regional climate model simulation. A consistent, gridded data set from 1948 to 2014 was computed using the regional climate model COSMO-CLM with a very high convection-permitting resolution at a grid distance of 2.8 km, for a region encompassing the German Bight and Northern Germany. This is one of the very first atmospheric model simulations with such high resolution, and covering several decades. Using a very high-resolution hindcast, this study aims to extend knowledge of the significance of regional details for long-term variability and multi-decadal trends of several meteorological variables such as wind, temperature, cloud cover, precipitation, and convective available potential energy (CAPE). This study demonstrates that most variables show merely large decadal variability and no long-term trends. The analysis shows that the most distinct and significant positive trends occur in temperature and in CAPE for annual mean values as well as for extreme events. No clear and no significant trend is detectable for the annual sum of precipitation and for extreme precipitation. However, spatial structures in the trends remain weak.

Sign in / Sign up

Export Citation Format

Share Document