Climate change projections over China using regional climate models forced by two CMIP5 global models. Part II: projections of future climate

2018 ◽  
Vol 38 ◽  
pp. e78-e94 ◽  
Author(s):  
Pinhong Hui ◽  
Jianping Tang ◽  
Shuyu Wang ◽  
Xiaorui Niu ◽  
Peishu Zong ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate ◽  
Climate Change Projections ◽  
Global Models

scholarly journals Regional Climate Model Emulator based on Deep Learning: Concept and First Evaluation of a Novel Hybrid Downscaling Approach

2021 ◽  
Author(s):  
Antoine Doury ◽  
Samuel Somot ◽  
Sébastien Gadat ◽  
Aurélien Ribes ◽  
Lola Corre
Keyword(s):  
Climate Change ◽  
Network Architecture ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate ◽  
Near Surface ◽  
The Way

Abstract Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we propose a novel hybrid downscaling method combining the strengths of both empirical statistical downscaling methods and Regional Climate Models (RCMs). The aim of this tool is to enlarge the size of high-resolution RCM simulation ensembles at low cost.We build a statistical RCM-emulator by estimating the downscaling function included in the RCM. This framework allows us to learn the relationship between large-scale predictors and a local surface variable of interest over the RCM domain in present and future climate. Furthermore, the emulator relies on a neural network architecture, which grants computational efficiency. The RCM-emulator developed in this study is trained to produce daily maps of the near-surface temperature at the RCM resolution (12km). The emulator demonstrates an excellent ability to reproduce the complex spatial structure and daily variability simulated by the RCM and in particular the way the RCM refines locally the low-resolution climate patterns. Training in future climate appears to be a key feature of our emulator. Moreover, there is a huge computational benefit in running the emulator rather than the RCM, since training the emulator takes about 2 hours on GPU, and the prediction is nearly instantaneous. However, further work is needed to improve the way the RCM-emulator reproduces some of the temperature extremes, the intensity of climate change, and to extend the proposed methodology to different regions, GCMs, RCMs, and variables of interest.

scholarly journals Uncertainties in climate change projections and regional downscaling in the tropical Andes: implications for water resources management

2010 ◽  
Vol 14 (7) ◽  
pp. 1247-1258 ◽  
Author(s):  
W. Buytaert ◽  
M. Vuille ◽  
A. Dewulf ◽  
R. Urrutia ◽  
A. Karmalkar ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Resources Management ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Tropical Andes ◽  
Climate Change Projections ◽  
Resources Management

Abstract. Climate change is expected to have a large impact on water resources worldwide. A major problem in assessing the potential impact of a changing climate on these resources is the difference in spatial scale between available climate change projections and water resources management. Regional climate models (RCMs) are often used for the spatial disaggregation of the outputs of global circulation models. However, RCMs are time-intensive to run and typically only a small number of model runs is available for a certain region of interest. This paper investigates the value of the improved representation of local climate processes by a regional climate model for water resources management in the tropical Andes of Ecuador. This region has a complex hydrology and its water resources are under pressure. Compared to the IPCC AR4 model ensemble, the regional climate model PRECIS does indeed capture local gradients better than global models, but locally the model is prone to large discrepancies between observed and modelled precipitation. It is concluded that a further increase in resolution is necessary to represent local gradients properly. Furthermore, to assess the uncertainty in downscaling, an ensemble of regional climate models should be implemented. Finally, translating the climate variables to streamflow using a hydrological model constitutes a smaller but not negligible source of uncertainty.

Climate Change Projections in Latin America and the Caribbean: Review of Existing Regional Climate Models' Outputs

2016 ◽  
Author(s):  
Ramiro Alberto Ríos Flores ◽  
Alejandro Pablo Taddia ◽  
Alfred Grunwaldt ◽  
Russel Jones ◽  
Richard Streeter
Keyword(s):  
Climate Change ◽  
Latin America ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Change Projections ◽  
The Caribbean

scholarly journals Projections for the Köppen-Geiger climate classification under future climate change for the Iberian Peninsula

2021 ◽  
Author(s):  
Cristina Andrade ◽  
Joana Contente
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Classification ◽  
Dry Climates ◽  
Projected Changes

<p>Projections of the Köppen-Geiger climate classification under future climate change for the Iberian Peninsula (IP) are investigated by using a seven-ensemble mean of regional climate models (RCMs) attained from EURO-CORDEX. Maps with predicted future scenarios for temperature, precipitation and Köppen-Geiger classification are analyzed under RCP4.5 and RCP8.5 in Iberia. Widespread statistically significant shifts in temperature, precipitation and climate regimes are projected between 2041 and 2070, with higher expression under RCP8.5. An overall increase of temperatures and a decrease of precipitation in the south-southeast is predicted. Of the two climate types dry (B) and temperate (C), the dominant one was C in 86% of the Iberian territory for 1961-1990, predicted to decrease by 8.0% towards 2041-2070 under RCP4.5 (9.1% under RCP8.5). The hot-summer Mediterranean climate (CSa) will progressively replaces CSb (warm-summer) type towards north in the northwestern half of Iberia until 2070. This shift, depicted by the SSIM index, is noticeable in Portugal with a projected establishment of the CSa climate by 2041-2070. A predicted retreat of humid subtropical (Cfa) and temperate oceanic (Cfb) areas in the northeast towards Pyrenees region is noteworthy, alongside an increase of desert (BW) and semi-desert (BS) climates (7.8% and 9%) that progressively sets in the southeast (between Granada and Valencia). Climate types BSh and BWh (hot semi-desert and hot-desert, respectively), non-existent in 1961-1990 period, are projected to represent 2.8% of territory in 2041-2070 under RCP4.5 (5% under RCP8.5). The statistically significant projected changes hint at the disappearance of some vegetation species in certain regions of Iberia, with an expected increase of steppe, bush, grassland and wasteland vegetation cover, typical of dry climates in the southeast.</p><p><strong>Funding:</strong> This research was funded by National Funds by FCT - Portuguese Foundation for Science and Technology, under the project <strong>UIDB/04033/2020.</strong></p>

scholarly journals Uncertainties in climate change projections and regional downscaling: implications for water resources management

2010 ◽  
Vol 7 (2) ◽  
pp. 1821-1848 ◽  
Author(s):  
W. Buytaert ◽  
M. Vuille ◽  
A. Dewulf ◽  
R. Urrutia ◽  
A. Karmalkar ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Regional Climate Model ◽  
Water Resources Management ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Change Projections ◽  
Resources Management

Abstract. Climate change is expected to have a large impact on water resources worldwide. A major problem in assessing the potential impact of a changing climate on these resources is the difference in spatial scale between available climate change projections and water resources management. Regional climate models (RCMs) are often used for the spatial disaggregation of the outputs of global circulation models. However, RCMs are time-intensive to run and typically only a small number of model runs is available for a certain region of interest. This paper investigates the value of the improved representation of local climate processes by a regional climate model for water resources management in the tropical Andes of Ecuador. This region has a complex hydrology and its water resources are under pressure. Compared to the IPCC AR4 model ensemble, the regional climate model PRECIS does indeed capture local gradients better than global models, but locally the model is prone to large discrepancies between observed and modelled precipitation. It is concluded that a further increase in resolution is necessary to represent local gradients properly. Furthermore, to assess the uncertainty in downscaling, an ensemble of regional climate models should be implemented. Finally, translating the climate variables to streamflow using a hydrological model constitutes a smaller but not negligible source of uncertainty.

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