Abstract
The added value of using regional climate models (RCMs) to downscale data from general circulation models (GCMs) has often been questioned and researched. Although several studies have used different methods to identify (and in some cases quantify) the added value, there is still a need to find a general metric that quantifies the added value of any variable. This paper builds on past studies to propose a new metric of added value in the simulation of present-day climate which measures the difference in the probability density functions (PDFs) at each grid-cell between a model and an observation source, and then compares the results of the RCM and GCM in order to spatially compute the added value index. The same method is also adapted to quantify the climate change downscaling signal in a way that is consistent with the present-day metric. These new metrics are tested on the daily precipitation output from the EURO-CORDEX and CORDEX-CORE projection ensembles and reveal an overall positive added value of RCMs, especially at the tail-end of the distribution. Higher added value is obtained in areas of complex topography and coast-lines, as well as in tropical regions. Areas with large added value in present-day climate are consistent with areas of significant climate change downscaling signal in the RCP 8.5 far future simulations, and when the analysis is repeated at a low-resolution. The use of different resolution observations shows that the added value tends to decrease when models are compared to low-resolution observation datasets.
| Original language | English |
|---|---|
| Pages (from-to) | 1403-1424 |
| Number of pages | 22 |
| Journal | Climate Dynamics |
| Volume | 57 |
| Issue number | 5-6 |
| DOIs | |
| State | Published - Sep 2021 |
Funding
The RegCM simulations for the ICTP institute have been completed thanks to the support of the CINECA supercomputing center, Bologna, Italy and the ISCRA projects HP10BDU7TR and HP10BQCFJ2. The authors would like to thank Graziano Giuliani and Ivan Girotto for their constant support in the preparation of the simulations used in this paper. The authors would also like to thank the CMIP5 and EURO-CORDEX community, as well as the ESGF for providing access to their database where most of the data is available. The majority of the EURO-CORDEX contributions have funded by the “Producing RegIoNal ClImate Projections Leading to European Services" (PRINCIPLES, C3S_34b Lot2) as part of the Copernicus Climate Change Service (C3S). The work was also partially supported by the EUCP H2020 project (GA number: 776613). Im E-S and Nguyen-Xuan T were supported by “Research Program for Agricultural Science and Technology Development" (Project no. PJ014882) funded by the Rural Development Administration, Republic of Korea. The study was also supported by the Oak Ridge Leadership Computing Facility and the National Climate-Computing Research Center at the Oak Ridge National Laboratory, the Climate Change Research Center, Institute of Atmospheric Physics; the Chinese Academy of Sciences, Beijing, China and University of Chinese Academy of Sciences, Beijing, China; the Yingkou Meteorological Bureau, Yingkou, China; the National Center for Atmospheric Research, Boulder, CO, USA; and the Climate Service Center Germany (GERICS), Helmholtz-Zentrum Geesthacht, Hamburg, Germany; all of whom provided access to their simulation data. The observations were provided by MeteoSwiss, Santander meteorology group, Meteo-France, Met office UK, METNO Norway, SMHI, Hungarian Meteorological Service, DWD Germany, and CETEMPS University of L’Aquila. The CPC Global Unified Precipitation data was provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at https://www.esrl.noaa.gov/psd/ . The RegCM simulations for the ICTP institute have been completed thanks to the support of the CINECA supercomputing center, Bologna, Italy and the ISCRA projects HP10BDU7TR and HP10BQCFJ2. The authors would like to thank Graziano Giuliani and Ivan Girotto for their constant support in the preparation of the simulations used in this paper. The authors would also like to thank the CMIP5 and EURO-CORDEX community, as well as the ESGF for providing access to their database where most of the data is available. The majority of the EURO-CORDEX contributions have funded by the ?Producing RegIoNal ClImate Projections Leading to European Services" (PRINCIPLES, C3S_34b Lot2) as part of the Copernicus Climate Change Service (C3S). The work was also partially supported by the EUCP H2020 project (GA number: 776613). Im E-S and Nguyen-Xuan T were supported by ?Research Program for Agricultural Science and Technology Development" (Project no. PJ014882) funded by the Rural Development Administration, Republic of Korea.?The study was also supported by the Oak Ridge Leadership Computing Facility and the National Climate-Computing Research Center at the Oak Ridge National Laboratory, the Climate Change Research Center, Institute of Atmospheric Physics; the Chinese Academy of Sciences, Beijing, China and University of Chinese Academy of Sciences, Beijing, China; the Yingkou Meteorological Bureau, Yingkou, China; the National Center for Atmospheric Research, Boulder, CO, USA; and the Climate Service Center Germany (GERICS), Helmholtz-Zentrum Geesthacht, Hamburg, Germany; all of whom provided access to their simulation data. The observations were provided by MeteoSwiss, Santander meteorology group, Meteo-France, Met office UK, METNO Norway, SMHI, Hungarian Meteorological Service, DWD Germany, and CETEMPS University of L?Aquila. The CPC Global Unified Precipitation data was provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at https://www.esrl.noaa.gov/psd/.
| Funders | Funder number |
|---|---|
| CETEMPS University of L?Aquila | |
| CINECA | HP10BQCFJ2, HP10BDU7TR |
| Climate Service Center | |
| Copernicus Climate Change Service | |
| ESGF | C3S_34b Lot2 |
| EUCP H2020 | PJ014882 |
| Helmholtz-Zentrum Geesthacht | |
| Hungarian Meteorological Service | |
| Met office UK | |
| Oak Ridge National Laboratory | |
| Yingkou Meteorological Bureau | |
| National Oceanic and Atmospheric Administration | |
| National Center for Atmospheric Research | |
| Office of AIDS Research | |
| Oak Ridge National Laboratory | |
| Wisconsin Department of Workforce Development | |
| Horizon 2020 Framework Programme | 776613 |
| Earth System Research Laboratories | |
| Abdus Salam International Centre for Theoretical Physics | |
| Chinese Academy of Sciences | |
| Rural Development Administration | |
| University of Chinese Academy of Sciences |
Keywords
- Added value
- CORDEX
- CORDEX-CORE
- Downscaling signal
- EURO-CORDEX
- Regional climate model