scholarly journals Coupled modeling of land hydrology–regional climate including human carbon emission and water exploitation

2017 ◽  
Vol 8 (2) ◽  
pp. 68-79 ◽  
Author(s):  
Zheng-Hui Xie ◽  
Yu-Jin Zeng ◽  
Jun Xia ◽  
Pei-Hua Qin ◽  
Bing-Hao Jia ◽  
...  
2021 ◽  
Vol 17 (4) ◽  
pp. 1645-1664
Author(s):  
Yiling Huo ◽  
William Richard Peltier ◽  
Deepak Chandan

Abstract. Proxy records suggest that the Northern Hemisphere during the mid-Holocene (MH), to be assumed herein to correspond to 6000 years ago, was generally warmer than today during summer and colder in the winter due to the enhanced seasonal contrast in the amount of solar radiation reaching the top of the atmosphere. The complex orography of both South and Southeast Asia (SA and SEA), which includes the Himalayas and the Tibetan Plateau (TP) in the north and the Western Ghats mountains along the west coast of India in the south, renders the regional climate complex and the simulation of the intensity and spatial variability of the MH summer monsoon technically challenging. In order to more accurately capture important regional features of the monsoon system in these regions, we have completed a series of regional climate simulations using a coupled modeling system to dynamically downscale MH global simulations. This regional coupled modeling system consists of the University of Toronto version of the Community Climate System Model version 4 (UofT-CCSM4), the Weather Research and Forecasting (WRF) regional climate model, and the 3D Coastal and Regional Ocean Community model (CROCO). In the global model, we have taken care to incorporate Green Sahara (GS) boundary conditions in order to compare with standard MH simulations and to capture interactions between the GS and the monsoon circulations in India and SEA. Comparison of simulated and reconstructed climates suggest that the dynamically downscaled simulations produce significantly more realistic anomalies in the Asian monsoon than the global climate model, although they both continue to underestimate the inferred changes in precipitation based upon reconstructions using climate proxy information. Monsoon precipitation over SA and SEA is also greatly influenced by the inclusion of a GS, with a large increase particularly being predicted over northern SA and SEA, and a lengthening of the monsoon season. Data–model comparisons with downscaled simulations outperform those with the coarser global model, highlighting the crucial role of downscaling in paleo data–model comparison.


2013 ◽  
Vol 57 (3) ◽  
pp. 173-186 ◽  
Author(s):  
X Wang ◽  
M Yang ◽  
G Wan ◽  
X Chen ◽  
G Pang

2015 ◽  
Vol 64 (2) ◽  
pp. 123-140 ◽  
Author(s):  
P Zanis ◽  
E Katragkou ◽  
C Ntogras ◽  
G Marougianni ◽  
A Tsikerdekis ◽  
...  

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  

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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