Rainfall and rainfall variability

2014 ◽  
Author(s):  
International Food Policy Research Institute (IFPRI)
Keyword(s):  
Rainfall Variability

Predicted consequences of increased rainfall variability on soil carbon stocks in a semiarid environment

2016 ◽  
Vol 67 (1) ◽  
pp. 61-69
Author(s):  
M Forouzangohar ◽  
R Setia ◽  
DD Wallace ◽  
CR Nitschke ◽  
LT Bennett
Keyword(s):  
Soil Carbon ◽  
Rainfall Variability ◽  
Carbon Stocks ◽  
Semiarid Environment ◽  
Soil Carbon Stocks

scholarly journals Differential Influences of Teleconnections from the Indian and Pacific Oceans on Rainfall Variability in Southeast Asia

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 886
Author(s):  
Abdul Azim Amirudin ◽  
Ester Salimun ◽  
Fredolin Tangang ◽  
Liew Juneng ◽  
Muhamad Zuhairi
Keyword(s):  
Indian Ocean ◽  
Southeast Asia ◽  
El Niño ◽  
El Nino ◽  
Rainfall Variability ◽  
June July August ◽  
Rainfall Patterns ◽  
Negative Impacts ◽  
The Individual ◽  
June July

This study investigates the individual and combined impacts of El Niño and the positive Indian Ocean Dipole (IOD) on the Southeast Asia (SEA) rainfall variability. Using composite and partial correlation techniques, it is shown that both inter-annual events have individually distinct impacts on the SEA rainfall anomaly distribution. The results showed that the impacts of the co-occurrence of El Niño and IOD events are significant compared to the individual effects of pure El Niño or pure IOD. During June-July-August and September-October-November, the individual impacts of the pure El Niño and IOD events are similar but less significant. Both events caused negative impacts over the southern part of SEA during June-July-August (JJA) and propagated northeastward/eastward during September-October-November (SON). Thus, there are significant negative impacts over the southern part of SEA during the co-occurrence of both events. The differential impacts on the anomalous rainfall patterns are due to the changes in the sea surface temperature (SST) surrounding the region. Additionally, the differences are also related to the anomalous regional atmospheric circulations that interact with the regional SST. The anomalous Walker circulation that connects the Indian Ocean and tropical Pacific Ocean also plays a significant role in determining the regional anomalous rainfall patterns.

scholarly journals Land Use/Cover Response to Rainfall Variability: A Comparing Analysis between NDVI and EVI in the Southwest of Burkina Faso

Climate ◽  
2014 ◽  
Vol 3 (1) ◽  
pp. 63-77 ◽  
Author(s):  
Benewinde Zoungrana ◽  
Christopher Conrad ◽  
Leonard Amekudzi ◽  
Michael Thiel ◽  
Evariste Da
Keyword(s):  
Land Use ◽  
Burkina Faso ◽  
Rainfall Variability

scholarly journals Understanding the variability of the rainfall dipole in West Africa using the EC-Earth last millennium simulation

2021 ◽  
Author(s):  
Qiong Zhang ◽  
Ellen Berntell ◽  
Qiang Li ◽  
Fredrik Charpentier Ljungqvist
Keyword(s):  
West Africa ◽  
Model Simulation ◽  
Rainfall Variability ◽  
Low Pressure ◽  
Last Millennium ◽  
Tropical Atlantic ◽  
Gulf Of Guinea ◽  
Dipole Pattern ◽  
Sahel Region ◽  
Heat Low

AbstractThere is a well-known mode of rainfall variability associating opposite hydrological conditions over the Sahel region and the Gulf of Guinea, forming a dipole pattern. Previous meteorological observations show that the dipole pattern varies at interannual timescales. Using an EC-Earth climate model simulation for last millennium (850–1850 CE), we investigate the rainfall variability in West Africa over longer timescales. The 1000-year-long simulation data show that this rainfall dipole presents at decadal to multidecadal and centennial variability and long-term trend. Using the singular value decomposition (SVD) analysis, we identified that the rainfall dipole present in the first SVD mode with 60% explained variance and associated with the variabilities in tropical Atlantic sea surface temperature (SST). The second SVD mode shows a monopole rainfall variability pattern centred over the Sahel, associated with the extra-tropical Atlantic SST variability. We conclude that the rainfall dipole-like pattern is a natural variability mode originated from the local ocean–atmosphere-land coupling in the tropical Atlantic basin. The warm SST anomalies in the equatorial Atlantic Ocean favour an anomalous low pressure at the tropics. This low pressure weakens the meridional pressure gradient between the Saharan Heat Low and the tropical Atlantic. It leads to anomalous northeasterly, reduces the southwesterly moisture flux into the Sahel and confines the Gulf of Guinea's moisture convergence. The influence from extra-tropical climate variability, such as Atlantic multidecadal oscillation, tends to modify the rainfall dipole pattern to a monopole pattern from the Gulf of Guinea to Sahara through influencing the Sahara heat low. External forcing—such as orbital forcing, solar radiation, volcanic and land-use—can amplify/dampen the dipole mode through thermal forcing and atmosphere dynamical feedback.

scholarly journals Evaluation of the Performance of CMIP6 Models in Reproducing Rainfall Patterns over North Africa

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 475
Author(s):  
Hassen Babaousmail ◽  
Rongtao Hou ◽  
Brian Ayugi ◽  
Moses Ojara ◽  
Hamida Ngoma ◽  
...  
Keyword(s):  
North Africa ◽  
Rainfall Variability ◽  
Coupled Model ◽  
Cumulative Distribution ◽  
Climatic Research Unit ◽  
Model Ensemble ◽  
Empirical Cumulative Distribution Function ◽  
Cycle Simulation ◽  
Taylor Diagram ◽  
Statistical Metrics

This study assesses the performance of historical rainfall data from the Coupled Model Intercomparison Project phase 6 (CMIP6) in reproducing the spatial and temporal rainfall variability over North Africa. Datasets from Climatic Research Unit (CRU) and Global Precipitation Climatology Centre (GPCC) are used as proxy to observational datasets to examine the capability of 15 CMIP6 models’ and their ensemble in simulating rainfall during 1951–2014. In addition, robust statistical metrics, empirical cumulative distribution function (ECDF), Taylor diagram (TD), and Taylor skill score (TSS) are utilized to assess models’ performance in reproducing annual and seasonal and monthly rainfall over the study domain. Results show that CMIP6 models satisfactorily reproduce mean annual climatology of dry/wet months. However, some models show a slight over/under estimation across dry/wet months. The models’ overall top ranking from all the performance analyses ranging from mean cycle simulation, trend analysis, inter-annual variability, ECDFs, and statistical metrics are as follows: EC-Earth3-Veg, UKESM1-0-LL, GFDL-CM4, NorESM2-LM, IPSL-CM6A-LR, and GFDL-ESM4. The mean model ensemble outperformed the individual CMIP6 models resulting in a TSS ratio (0.79). For future impact studies over the study domain, it is advisable to employ the multi-model ensemble of the best performing models.

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