An evaluation of COSMO‐CLM regional climate model in simulating precipitation over Central Africa

2020 ◽  
Vol 40 (5) ◽  
pp. 2891-2912 ◽  
Author(s):  
Gabriel Fotso‐Kamga ◽  
Thierry C. Fotso‐Nguemo ◽  
Ismaila Diallo ◽  
Zéphirin D. Yepdo ◽  
Wilfried M. Pokam ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Central Africa

On the added value of the regional climate model REMO in the assessment of climate change signal over Central Africa

2017 ◽  
Vol 49 (11-12) ◽  
pp. 3813-3838 ◽  
Author(s):  
Thierry C. Fotso-Nguemo ◽  
Derbetini A. Vondou ◽  
Wilfried M. Pokam ◽  
Zéphirin Yepdo Djomou ◽  
Ismaïla Diallo ◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Central Africa ◽  
Added Value ◽  
Climate Change Signal

Assessment of simulated rainfall and temperature from the regional climate model REMO and future changes over Central Africa

2016 ◽  
Vol 48 (11-12) ◽  
pp. 3685-3705 ◽  
Author(s):  
Thierry C. Fotso-Nguemo ◽  
Derbetini A. Vondou ◽  
Clément Tchawoua ◽  
Andreas Haensler
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Central Africa ◽  
Simulated Rainfall

scholarly journals Influence of slab-ocean parametrization in a regional climate model (RegCM4) over Central Africa

2021 ◽  
Author(s):  
Francois Xavier Mengouna ◽  
Derbetini A. Vondou ◽  
A. J. Komkoua Mbienda ◽  
Thierry C. Fotso-Nguemo ◽  
Denis Sonkoué ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Central Africa ◽  
Slab Ocean

Impact of anthropogenic aerosols on climate variability over Central Africa by using a regional climate model

2016 ◽  
Vol 37 (1) ◽  
pp. 249-267 ◽  
Author(s):  
A. J. Komkoua Mbienda ◽  
C. Tchawoua ◽  
D. A. Vondou ◽  
P. Choumbou ◽  
C. Kenfack Sadem ◽  
...  
Keyword(s):  
Climate Variability ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Central Africa ◽  
Anthropogenic Aerosols

Boundary layer schemes in the regional climate model RegCM4.6 over Central Africa

2021 ◽  
Author(s):  
A. J. Komkoua Mbienda ◽  
G. M. Guenang ◽  
S. Kaissassou ◽  
A. Tchakoutio Sandjon ◽  
R. S. Tanessong ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Central Africa

scholarly journals Possible influence of the convection schemes in regional climate model RegCM4.6 for climate services over Central Africa

2021 ◽  
Vol 28 (2) ◽  
Author(s):  
A. J. Komkoua Mbienda ◽  
G. M. Guenang ◽  
R. S. Tanessong ◽  
S. V. Ashu Ngono ◽  
S. Zebaze ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Central Africa ◽  
Climate Services ◽  
Convection Schemes

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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