scholarly journals Modelling Mediterranean heavy precipitation events at climate scale: an object-oriented evaluation of the CNRM-AROME convection-permitting regional climate model

2021 ◽  
Author(s):  
Cécile Caillaud ◽  
Samuel Somot ◽  
Antoinette Alias ◽  
Isabelle Bernard-Bouissières ◽  
Quentin Fumière ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Object Oriented ◽  
Heavy Precipitation ◽  
Horizontal Resolution ◽  
Added Value ◽  
Continuous Simulation ◽  
Climate Scale ◽  
Precipitation Events

AbstractModelling the rare but high-impact Mediterranean Heavy Precipitation Events (HPEs) at climate scale remains a largely open scientific challenge. The issue is adressed here by running a 38-year-long continuous simulation of the CNRM-AROME Convection-Permitting Regional Climate Model (CP-RCM) at a 2.5 km horizontal resolution and over a large pan-Alpine domain. First, the simulation is evaluated through a basic Eulerian statistical approach via a comparison with selected high spatial and temporal resolution observational datasets. Northwestern Mediterranean fall extreme precipitation is correctly represented by CNRM-AROME at a daily scale and even better at an hourly scale, in terms of location, intensity, frequency and interannual variability, despite an underestimation of daily and hourly highest intensities above 200 mm/day and 40 mm/h, respectively. A comparison of the CP-RCM with its forcing convection-parameterised 12.5 km Regional Climate Model (RCM) demonstrates a clear added value for the CP-RCM, confirming previous studies. Secondly, an object-oriented Lagrangian approach is proposed with the implementation of a precipitating system detection and tracking algorithm, applied to the model and the reference COMEPHORE precipitation dataset for twenty fall seasons. Using French Mediterranean HPEs as objects, CNRM-AROME’s ability to represent the main characteristics of fall convective systems and tracks is highlighted in terms of number, intensity, area, duration, velocity and severity. Further, the model is able to simulate long-lasting and severe extreme fall events similar to observations. However, it fails to reproduce the precipitating systems and tracks with the highest intensities (maximum intensities above 40 mm/h) well, and the model’s tendency to overestimate the cell size increases with intensity.

scholarly journals Atmospheric Rivers in CMIP5 climate ensembles downscaled with a high resolution regional climate model

2021 ◽  
Author(s):  
Matthias Gröger ◽  
Christian Dieterich ◽  
Cyril Dutheil ◽  
Markus Meier ◽  
Dmitry Sein
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Eastern Europe ◽  
Central Europe ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Atmospheric Rivers ◽  
Precipitation Events

Abstract. Atmospheric rivers (AR) are important drivers of heavy precipitation events in western and central Europe and often associated with intense floods. So far, the ARs response to climate change in Europe has been investigated by global climate models within the CMIP5 framework. However, their spatial resolution between 1 and 3° is too coarse for an adequate assessment of local to regional precipitation patterns. Using a regional climate model with 0.22° resolution we downscale an ensemble of 24 global climate simulations following the greenhouse gas scenarios RCP2.6, RCP4.5, RCP8.5. The performance of the model was tested against ER-I reanalysis data. The downscaled simulation notably better represents small-scale spatial characteristics which is most obvious over the terrain of the Iberian Peninsula where the AR induced precipitation pattern clearly reflect eat-west striking topographical elements resulting in zonal bands of high and low AR impact. Over central Europe the model simulates a less far propagation of ARs toward eastern Europe compared to ERA-I but a higher share of AR forced heavy precipitation events especially Norway where 60 % of annual precipitation maxima are related to ARs. We find ARs more frequent and more intense in a future warmer climate especially in the higher emission scenarios whereas the changes are mostly mitigated under the assumption of RCP2.6. They also propagate further inland to eastern Europe in a warmer climate. In the high emission scenario RCP8.5 AR induced precipitation rates increase between 20 and 40 % in western central Europe while mean precipitation rates increase by maximal 12 %. Over the Iberian Peninsula AR induced precipitation rates slightly decrease around −6 % but mean rates decrease around −15 %. The result of these changes is an overall increased contribution of ARs to heavy precipitation with greatest impact over Iberia (15–30 %). Over Norway average AR precipitation rates decline between −5 to −30 %. These reductions most likely the originate from regional dynamical changes. In fact, over Norway we find ARs originating from > 60° N are reduced by up to 20 % while those originating south of 45° N are increased. Also, no clear climate change signal is seen for AR related heavy precipitation and annual maximum precipitation over Norway where the uncertainty of the ensemble is quite large.

scholarly journals Observations and Regional Climate Model Simulations of Heavy Precipitation Events and Seasonal Anomalies: A Comparison

2002 ◽  
Vol 3 (3) ◽  
pp. 322-334 ◽  
Author(s):  
Kenneth E. Kunkel ◽  
Karen Andsager ◽  
Xin-Zhong Liang ◽  
Raymond W. Arritt ◽  
Eugene S. Takle ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
Precipitation Events

Importance of Regional Climate Model Grid Spacing for the Simulation of Heavy Precipitation in the Colorado Headwaters

2013 ◽  
Vol 26 (13) ◽  
pp. 4848-4857 ◽  
Author(s):  
Andreas F. Prein ◽  
Gregory J. Holland ◽  
Roy M. Rasmussen ◽  
James Done ◽  
Kyoko Ikeda ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Colorado River ◽  
Climate Model ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Grid Spacing ◽  
Climate Simulations ◽  
Horizontal Grid ◽  
Precipitation Events

Abstract Summer and winter daily heavy precipitation events (events above the 97.5th percentile) are analyzed in regional climate simulations with 36-, 12-, and 4-km horizontal grid spacing over the headwaters of the Colorado River. Multiscale evaluations are useful to understand differences across horizontal scales and to evaluate the effects of upscaling finescale processes to coarser-scale features associated with precipitating systems. Only the 4-km model is able to correctly simulate precipitation totals of heavy summertime events. For winter events, results from the 4- and 12-km grid models are similar and outperform the 36-km simulation. The main advantages of the 4-km simulation are the improved spatial mesoscale patterns of heavy precipitation (below ~100 km). However, the 4-km simulation also slightly improves larger-scale patterns of heavy precipitation.

An Assessment of Observed and Simulated Temperature Variability in Sierra de Guadarrama (Spain)

2021 ◽  
Author(s):  
Cristina Vegas Cañas ◽  
J. Fidel González Rouco ◽  
Jorge Navarro Montesinos ◽  
Elena García Bustamante ◽  
Etor E. Lucio Eceiza ◽  
...  
Keyword(s):  
Western Europe ◽  
Climate Model ◽  
Regional Climate ◽  
Monitoring Network ◽  
Horizontal Resolution ◽  
Temperature Variability ◽  
Added Value ◽  
Seasonal Temperature ◽  
Temperature Trends ◽  
Highly Correlated

<p>This work provides a first assessment of temperature variability from interannual to multidecadal timescales in Sierra de Guadarrama, located in central Spain, from observations and regional climate model (RCM) simulations. Observational data are provided by the Guadarrama Monitoring Network (GuMNet; www.ucm.es/gumnet) at higher altitudes, up to 2225 masl, and by the Spanish Meteorological Agency (AEMet) at lower sites. An experiment at high horizontal resolution of 1 km using the Weather Research and Forecasting (WRF) RCM, feeding from ERA Interim inputs, is used. Through model-data comparison, it is shown that the simulations are annually and seasonally highly representative of the observations, although there is a tendency in the model to underestimate observational temperatures, mostly at high altitudes. Results show that WRF provides an added value in relation to the reanalysis, with improved correlation and error metrics relative to observations.</p><p>The analysis of temperature trends shows a warming in the area during the last 20 years, very significant in autumn. When spanning the analysis to the whole observational period, back to the beginning of the 20th century at some sites, significant annual and seasonal temperature increases of 1℃/decade develop, most of them happening during de 1970s, although not as intense as during the last 20 years.</p><p>The temporal variability of temperature anomalies in the Sierra de Guadarrama is highly correlated with the temperatures in the interior of the Iberian Peninsula. This relationship can be extended broadly over south-western Europe.</p>

On the added value of the regional climate model REMO in the assessment of climate change signal over Central Africa

2017 ◽  
Vol 49 (11-12) ◽  
pp. 3813-3838 ◽  
Author(s):  
Thierry C. Fotso-Nguemo ◽  
Derbetini A. Vondou ◽  
Wilfried M. Pokam ◽  
Zéphirin Yepdo Djomou ◽  
Ismaïla Diallo ◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Central Africa ◽  
Added Value ◽  
Climate Change Signal

scholarly journals Global Radiative Flux and Cloudiness Variability for the Period 1959–2010 in Belgium: A Comparison between Reanalyses and the Regional Climate Model MAR

Atmosphere ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 262 ◽  
Author(s):  
Coraline Wyard ◽  
Sébastien Doutreloup ◽  
Alexandre Belleflamme ◽  
Martin Wild ◽  
Xavier Fettweis
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Horizontal Resolution ◽  
Radiative Flux ◽  
Added Value ◽  
Historical Trends ◽  
The Mean

The use of regional climate models (RCMs) can partly reduce the biases in global radiative flux (Eg↓) that are found in reanalysis products and global models, as they allow for a finer spatial resolution and a finer parametrisation of surface and atmospheric processes. In this study, we assess the ability of the MAR («Modèle Atmosphérique Régional») RCM to reproduce observed changes in Eg↓, and we investigate the added value of MAR with respect to reanalyses. Simulations were performed at a horizontal resolution of 5 km for the period 1959–2010 by forcing MAR with different reanalysis products: ERA40/ERA-interim, NCEP/NCAR-v1, ERA-20C, and 20CRV2C. Measurements of Eg↓ from the Global Energy Balance Archive (GEBA) and from the Royal Meteorological Institute of Belgium (RMIB), as well as cloud cover observations from Belgocontrol and RMIB, were used for the evaluation of the MAR model and the forcing reanalyses. Results show that MAR enables largely reducing the mean biases that are present in the reanalyses. The trend analysis shows that only MAR forced by ERA40/ERA-interim shows historical trends, which is probably because the ERA40/ERA-interim has a better horizontal resolution and assimilates more observations than the other reanalyses that are used in this study. The results suggest that the solar brightening observed since the 1980s in Belgium has mainly been due to decreasing cloud cover.

scholarly journals Panama’s Current Climate Replicability in a Non-Hydrostatic Regional Climate Model Nested in an Atmospheric General Circulation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1543
Author(s):  
Reinhardt Pinzón ◽  
Noriko N. Ishizaki ◽  
Hidetaka Sasaki ◽  
Tosiyuki Nakaegawa
Keyword(s):  
Regional Climate Model ◽  
Air Temperature ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Horizontal Resolution ◽  
Temperature And Precipitation ◽  
Current Climate

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation.

scholarly journals Assessing the Effects of Spatial Resolution on Regional Climate Model Simulated Summer Temperature and Precipitation in China: A Case Study

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Xin-Min Zeng ◽  
Ming Wang ◽  
Yujian Zhang ◽  
Yang Wang ◽  
Yiqun Zheng
Keyword(s):  
Regional Climate Model ◽  
South China ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Northern China ◽  
Horizontal Resolution ◽  
Vertical Resolution ◽  
Humid Climate ◽  
Entire Area

The regional climate model, RegCM3, is used to simulate the 2004 summer surface air temperature (SAT) and precipitation at different horizontal (i.e., 30, 60, and 90 km) and vertical resolutions (i.e., 14, 18, and 23 layers). Results showed that increasing resolution evidently changes simulated SATs with regional characteristics. For example, simulated SATs are apparently better produced when horizontal resolution increases from 60 to 30 km under the 23 layers. Meanwhile, the SATs over the entire area are more sensitive to vertical resolution than horizontal resolution. The subareas present higher sensitivities than the total area, with larger horizontal resolution effects than those of vertical resolution. For precipitation, increasing resolution shows higher impact compared to SAT, with higher sensitivity induced by vertical resolution than by horizontal resolution, especially in rainy South China. The best SAT/precipitation can be produced only when the horizontal and vertical resolutions are reasonably configured. This indicates that different resolutions lead to different atmospheric thermodynamic states. Because of the dry climate and low soil heat capacity in Northern China, resolution changes easily modify surface energy fluxes, hence the SAT; due to the rainy and humid climate in South China, resolution changes likely strongly influence grid-scale structure of clouds and therefore precipitation.

Adaptation and Application of the large LAERTES-EU RCM Ensemble for Hydrological Modeling

2021 ◽  
Author(s):  
Florian Ehmele ◽  
Lisa-Ann Kautz ◽  
Hendrik Feldmann ◽  
Yi He ◽  
Martin Kadlec ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Central Europe ◽  
Hydrological Modeling ◽  
Climate Model ◽  
Regional Climate ◽  
Added Value ◽  
Data Set ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
Rhine Catchment

<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>

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