Added Value of EURO-CORDEX downscaling over the complex orography region of the Pyrenees-Reference-Cited by-同舟云学术

Added Value of EURO-CORDEX downscaling over the complex orography region of the Pyrenees

Published:2024-01-15 Issue: Volume: Page:
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Author:

Bilbao-Barrenetxea Nerea¹,Santolaria-Otín Maria²,Teichmann Claas³,Faria Sergio Henrique¹,Máñez-Costa María³

Affiliation:

1. BC3: BC3 Basque Centre for Climate Change

2. UB: Universitat de Barcelona

3. HZG GERICS: Helmholtz-Zentrum Hereon GERICS - Deutsches Institut fur Klimaservices

Abstract

Abstract This study presents an assessment of the added value of downscalling utilizing Regional Climate Models (RCMs) compared to Global Climate Models (GCMs) in the high mountain region of the Pyrenees, characterized by complex topography. We investigate the EURO-CORDEX ensemble, employing a gridded high-resolution observational database as a reference. A recently proposed method is applied to quantify the performance gains or losses associated with dynamic downscalling. Our analysis focuses on calculating the added value by exploring the extremes of the probability density function (PDF), spatial distribution patterns, and its relationship with elevation. Overall, our findings reveal improvements in the representation of precipitation, minimum temperature, and maximum temperature. RCMs demonstrate enhanced performance in capturing maximum precipitation events; however, they struggle to represent low precipitation rates, particularly in the Mediterranean area of the mountain range. Regarding temperature, dynamical downscalling exhibits improvements in capturing maximum events. Nevertheless, deficiencies are observed in the RCMs' representation of minimum temperature events for both minimum and maximum temperature variables, as well as in representing near-freezing temperatures.

Publisher

Research Square Platform LLC

Reference51 articles.

1. Ciarlo, James M. and Coppola, Erika and Fantini, Adriano and Giorgi, Filippo and Gao, Xue Jie and Tong, Yao and Glazer, Russell H. and {Torres Alavez}, Jose Abraham and Sines, Taleena and Pichelli, Emanuela and Raffaele, Francesca and Das, Sushant and Bukovsky, Melissa and Ashfaq, Moetasim and Im, Eun Soon and Nguyen-Xuan, Thanh and Teichmann, Claas and Remedio, Armelle and Remke, Thomas and B{\"{u}}low, Katharina and Weber, Torsten and Buntemeyer, Lars and Sieck, Kevin and Rechid, Diana and Jacob, Daniela (2021) {A new spatially distributed added value index for regional climate models: the EURO-CORDEX and the CORDEX-CORE highest resolution ensembles}. Climate Dynamics 57(5-6): 1403--1424 https://doi.org/10.1007/s00382-020-05400-5, Springer Berlin Heidelberg, GERICS, Added value,CORDEX,CORDEX-CORE,Downscaling signal,EURO-CORDEX,Regional climate model, 14320894, 0038202005400, :home/nerea/Deskargak/Ciarlo2021_Article_ANewSpatiallyDistributedAddedV.pdf:pdf

2. Careto, Jo{\ {a}}o Ant{\'{o}}nio Martins and Soares, Pedro Miguel Matos and Cardoso, Rita Margarida and Herrera, Sixto and Guti{\'{e}}rrez, Jos{\'{e}} Manuel (2022) {Added value of EURO-CORDEX high-resolution downscaling over the Iberian Peninsula revisited - Part 1: Precipitation}. Geoscientific Model Development 15(6): 2635--2652 https://doi.org/10.5194/gmd-15-2635-2022, GERICS/Intro,GERICS, 19919603, :home/nerea/Deskargak/gmd-15-2635-2022.pdf:pdf, Over the years, higher-resolution regional climate model simulations have emerged owing to the large increase in computational resources. The 12km resolution from the Coordinated Regional Climate Downscaling Experiment for the European domain (EURO-CORDEX) is a reference, which includes a larger multi-model ensemble at a continental scale while spanning at least a 130-year period. These simulations are computationally demanding but do not always reveal added value. In this study, a recently developed regular gridded dataset and a new metric for added value quantification, the distribution added value (DAV), are used to assess the precipitation of all available EURO-CORDEX hindcast (1989-2008) and historical (1971-2005) simulations. This approach enables a direct comparison between the higher-resolution regional model runs against their forcing global model or ERA-Interim reanalysis with respect to their probability density functions. This assessment is performed for the Iberian Peninsula. Overall, important gains are found for most cases, particularly in precipitation extremes. Most hindcast models reveal gains above 15%, namely for wintertime, while for precipitation extremes values above 20% are reached for the summer and autumn. As for the historical models, although most pairs display gains, regional models forced by two general circulation models (GCMs) reveal losses, sometimes around -5% or lower, for the entire year. However, the spatialization of the DAV is clear in terms of added value for precipitation, particularly for precipitation extremes with gains well above 100%. Copyright:

3. Reder, Alfredo and Raffa, Mario and Montesarchio, Myriam and Mercogliano, Paola (2020) {Performance evaluation of regional climate model simulations at different spatial and temporal scales over the complex orography area of the Alpine region}. Natural Hazards 102(1): 151--177 https://doi.org/10.1007/s11069-020-03916-x, Springer Netherlands, GERICS/Intro,GERICS, Climate model evaluation,Convection permitting models,Distribution added value,Extremes,High resolution,Sub-daily precipitation, 15730840, 1106902003916, :home/nerea/Deskargak/Reder_etal_2020(1).pdf:pdf, This work provides a significant contribution on the open debate in the climate community to establish the added value of very high-resolution configurations, characterized by a horizontal resolution below 4 km with respect to current state-of-the-art climate simulations (10 –15 km). Specifically, it aims at assessing quantitative gains and losses in the performance of climate models caused by an enhancement in temporal and spatial resolution by evaluating the capability of different climate simulations in reproducing daily and sub-daily present precipitation dynamics over a complex orographic context such as the Alpine region. In this perspective, the results of three experiments (EURO-CORDEX ensemble mean, CCLM 8 and CCLM 2.2) at different spatial ($$\sim$$ 12, 8 and 2.2 km) and temporal (daily, 6 h and 3 h) scales are compared to gridded and point-scale observational datasets. Precipitation data are analyzed by mean of the Expert Team on Climate Change Detection and Indices indicators, as well as with statistical models able to evaluate the precipitation distribution and the extreme values for different durations of precipitation events. To objectively assess gains and losses in adopting high-resolution RCMs, data are elaborated assuming the distribution added value as metric, particularly focusing on the role of orography. The work returns, at daily scale, a gain in climate model performances moving from lower to higher horizontal resolution. At the same time, investigating the effect of the orography the simulation with the finest grid proves to better capture local precipitation dynamics at higher altitudes in terms of both sub-daily precipitation and extreme events.

4. Perkins, S. E. and Pitman, A. J. and Holbrook, N. J. and McAneney, J. (2007) {Evaluation of the AR4 climate models' simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions}. Journal of Climate 20(17): 4356--4376 https://doi.org/10.1175/JCLI4253.1, GERICS/Intro,GERICS, 08948755, :home/nerea/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Perkins et al. - 2007 - Evaluation of the AR4 climate models' simulated daily maximum temperature, minimum temperature, and precipitatio.pdf:pdf, The coupled climate models used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change are evaluated. The evaluation is focused on 12 regions of Australia for the daily simulation of precipitation, minimum temperature, and maximum temperature. The evaluation is based on probability density functions and a simple quantitative measure of how well each climate model can capture the observed probability density functions for each variable and each region is introduced. Across all three variables, the coupled climate models perform better than expected. Precipitation is simulated reasonably by most and very well by a small number of models, although the problem with excessive drizzle is apparent in most models. Averaged over Australia, 3 of the 14 climate models capture more than 80% of the observed probability density functions for precipitation. Minimum temperature is simulated well, with 10 of the 13 climate models capturing more than 80% of the observed probability density functions. Maximum temperature is also reasonably simulated with 6 of 10 climate models capturing more than 80% of the observed probability density functions. An overall ranking of the climate models, for each of precipitation, maximum, and minimum temperatures, and averaged over these three variables, is presented. Those climate models that are skillful over Australia are identified, providing guidance on those climate models that should be used in impacts assessments where those impacts are based on precipitation or temperature. These results have no bearing on how well these models work elsewhere, but the methodology is potentially useful in assessing which of the many climate models should be used by impacts groups. {\textcopyright} 2007 American Meteorological Society.

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