scholarly journals Validation of temperature trends in the ENSEMBLES regional climate model runs driven by ERA40

2010 ◽  
Vol 44 (2-3) ◽  
pp. 167-177 ◽  
Author(s):  
P Lorenz ◽  
D Jacob
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Temperature Trends

scholarly journals Future Climate in the Tibetan Plateau from a Statistical Regional Climate Model

2013 ◽  
Vol 26 (24) ◽  
pp. 10125-10138 ◽  
Author(s):  
Xiuhua Zhu ◽  
Weiqiang Wang ◽  
Klaus Fraedrich
Keyword(s):  
Tibetan Plateau ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Early Summer ◽  
Maximum Temperature ◽  
Boreal Summer ◽  
The Tibetan Plateau ◽  
Temperature Trends ◽  
Precipitation Increase

Abstract The authors use a statistical regional climate model [Statistical Regional Model (STAR)] to project the Tibetan Plateau (TP) climate for the period 2015–50. Reanalysis datasets covering 1958–2001 are used as a substitute of observations and resampled by STAR to optimally fit prescribed linear temperature trends derived from the Max Planck Institute Earth System Model (MPI-ESM) simulations for phase 5 of the Coupled Model Intercomparison Project (CMIP5) under the representative concentration pathway 2.6 (RCP2.6) and RCP4.5 scenarios. To assess the related uncertainty, temperature trends from carefully selected best/worst ensemble members are considered. In addition, an extra projection is forced by observed temperature trends in 1958–2001. The following results are obtained: (i) Spatial average temperature will increase by 0.6°–0.9°C; the increase exceeds 1°C in all months except in boreal summer, thus indicating a reduced annual cycle; and daily minimum temperature rises faster than daily maximum temperature, resulting in a narrowing of the diurnal range of near-surface temperature. (ii) Precipitation increase mainly occurs in early summer and autumn possibly because of an earlier onset and later withdrawal of the Asian summer monsoon. (iii) Both frost and ice days decrease by 1–2 days in spring, early summer, and autumn, and the decrease of frost days on the annual course is inversely related to the precipitation increase. (iv) Degree-days increase all over the TP with peak amplitude in the Qaidam Basin and the southern TP periphery, which will result in distinct melting of the local seasonal frozen ground, and the annual temperature range will decrease with stronger amplitude in south TP.

scholarly journals Recent Near-surface Temperature Trends in the Antarctic Peninsula from Observed, Reanalysis and Regional Climate Model Data

2020 ◽  
Vol 37 (5) ◽  
pp. 477-493
Author(s):  
Deniz Bozkurt ◽  
David H. Bromwich ◽  
Jorge Carrasco ◽  
Keith M. Hines ◽  
Juan Carlos Maureira ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Regional Climate Model ◽  
Antarctic Peninsula ◽  
Climate Model ◽  
Regional Climate ◽  
Model Data ◽  
Near Surface ◽  
Temperature Trends ◽  
The Antarctic

Qinghai-Xizang (Tibetan) Plateau climate simulation using the regional climate model RegCM3

2013 ◽  
Vol 57 (3) ◽  
pp. 173-186 ◽  
Author(s):  
X Wang ◽  
M Yang ◽  
G Wan ◽  
X Chen ◽  
G Pang
Keyword(s):  
Tibetan Plateau ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Simulation

Evaluation of net shortwave radiation over China with a regional climate model

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Monsoon Region ◽  
Clear Sky ◽  
Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

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