scholarly journals Assessing current and future spatiotemporal precipitation variability and trends over Uganda, East Africa, based on CHIRPS and regional climate model datasets

2021 ◽  
Author(s):  
Hamida Ngoma ◽  
Wang Wen ◽  
Moses Ojara ◽  
Brian Ayugi
Keyword(s):  
Regional Climate Model ◽  
East Africa ◽  
Climate Model ◽  
Regional Climate ◽  
Precipitation Variability

scholarly journals Historical evaluations and simulations of precipitation over East Africa from Rossby centre regional climate model

2020 ◽  
Vol 232 ◽  
pp. 104705 ◽  
Author(s):  
Brian Ayugi ◽  
Guirong Tan ◽  
Gnim Tchalim Gnitou ◽  
Moses Ojara ◽  
Victor Ongoma
Keyword(s):  
Regional Climate Model ◽  
East Africa ◽  
Climate Model ◽  
Regional Climate

scholarly journals The effect of topography on east African rainfall based on regional climate model

MAUSAM ◽  
2021 ◽  
Vol 67 (2) ◽  
pp. 431-440
Author(s):  
BOB ALEX OGWANG ◽  
HAISHAN CHEN ◽  
L. I. XING
Keyword(s):  
Regional Climate Model ◽  
East Africa ◽  
Climate Model ◽  
Regional Climate ◽  
Research Unit ◽  
Theoretical Physics ◽  
East African ◽  
Maximum Rainfall ◽  
Low Level ◽  
The Mean

The effect of topography on June to August (JJA) rainfall over east Africa is investigated using the International Centre for Theoretical Physics (ICTP) Regional Climate Model (RegCM4.0). Grell convection scheme with Fritsch-Chappell closure assumption is used. The control simulation is done with actual topography and sensitivity experiments are carried out with topography reduced to 75%, 25% and to zero. The model output was evaluated against Climate Research Unit (CRU) dataset, gridded at 0.5 degree resolution and ERA-interim datasets, gridded at 0.75 degree resolution. Results show that the mean JJA rainfall significantly reduces over the region when topography elevation is reduced. Based on the model, when the topography over the selected region (KTU) is reduced to 25%, the mean JJA rainfall over east Africa is reduced by roughly half. The maximum rainfall reduction is however observed around the region over which topography is reduced. The reduction in topography resulted into an anomalous moisture divergence over the region at low level (850 hPa). Divergence at low level results in vertical shrinking which suppresses convection due to subsidence. The strength of moisture transport and the zonal wind speed at 850hpa increased with decrease in topography, which may be responsible for the observed shift in moisture convergence zone from western Kenya to northern Uganda. The findings from this study would provide insight into the effect of topography on the east African climate and call for more detailed investigative research, particularly in the region. The results may motivate researchers and modeling centers to further improve on the performance of the model over the region.

GCM Model Selection Procedure for Downscaling

2021 ◽  
Author(s):  
Carolyne Pickler ◽  
Thomas Mölg
Keyword(s):  
Surface Temperature ◽  
Regional Climate Model ◽  
East Africa ◽  
Spatial Resolution ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Selection Procedure ◽  
Reanalysis Data ◽  
Local Climate

<p>Downscaling has been widely used in studies of regional and/or local climate as it yields greater spatial resolution than general circulation models (GCM) can provide.  It can approached in two distinct ways: 1) Statistical and 2) Dynamical.  Statistical downscaling utilizes mathematical relationships between large-scale and regional/local climate to transform GCM or reanalysis data to a higher spatial resolution.  Dynamical downscaling comprises forcing the lateral boundaries of a regional climate model with reanalysis or GCM data.  However, there is no set technique to select said GCM(s).</p><p>A comprehensive yet easily applicable selection procedure was created to address this.  Using reanalysis data and/or observational data, the space-time climatic anomalies and the mean state of the climate are evaluated for the region of interest.  East Africa was utilized as a case study and GISS-E2-H r6i1p3 was found to perform the strongest.  This procedure cannot, however, tell whether the models can reproduce the key processes of the region.  To examine this, the ability of the models to simulate the Indian Ocean Dipole were evaluated.  It was found that higher ranked models were better able to capture it than lower ranked ones.  Furthermore, to ensure that a higher ranked model yielded a better downscaling simulation, three 10-year regional climate model simulations over East Africa were undertaken, where they were respectively forced by the highest ranked GCM (GISS-E2-H r6i1p3), the lowest ranked GCM (IPSL-CM5A-LR r4i1p1) and the MERRA-2 reanalysis product.  The simulated surface temperature and precipitation for Equatorial East Africa were compared with a gridded observational dataset (CRU TS 4.04).  Results showed that the higher ranked GCM produced a better downscaled simulation than the lower ranked one, a result that was more evident for surface temperature than precipitation.</p>

A coupled regional climate model for the Lake Victoria basin of East Africa

2004 ◽  
Vol 24 (1) ◽  
pp. 57-75 ◽  
Author(s):  
Yi Song ◽  
Fredrick H. M. Semazzi ◽  
Lian Xie ◽  
Laban J. Ogallo
Keyword(s):  
Regional Climate Model ◽  
East Africa ◽  
Climate Model ◽  
Lake Victoria ◽  
Regional Climate ◽  
Lake Victoria Basin

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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