scholarly journals Rainfall variability and meteorological drought in the Horn of Africa

MAUSAM ◽  
2021 ◽  
Vol 68 (3) ◽  
pp. 463-474
Author(s):  
Y. WANG ◽  
Z. W. SHILENJE ◽  
P. O. SAGERO ◽  
A. M. NYONGESA ◽  
N. BANDA
Keyword(s):  
Rainfall Variability ◽  
Meteorological Drought ◽  
Research Unit ◽  
Dominant Mode ◽  
Empirical Orthogonal Functions ◽  
Seasonal Rainfall ◽  
Horn Of Africa ◽  
Standard Precipitation Index ◽  
Orthogonal Functions ◽  
Rainfall Characteristics

 Basic rainfall characteristics and drought over the Horn of Africa (HoA) is investigated, from 1901 to 2010. Standard Precipitation Index (SPI) is used to study drought variability, mainly focusing on 3-month SPI. The dominant mode of variability of seasonal rainfall was analyzed by performing Empirical orthogonal functions (EOF) analysis. Gridded data is sourced from Climate Research Unit (CRU), spanning from 1901 to 2010. The HoA experiences predominantly bimodal rainfall distribution in time; March to May (MAM) and October to December (OND). The spatial component of the first eigenvector (EOF1) shows that the MAM and OND seasonal rainfalls are dominated by negative and positive loadings, respectively. The EOF1 explain 34.5% and 58.9% variance of MAM and OND seasonal rainfall, respectively. The EOF2, 3 and 4 are predominantly positive, explaining less than 25% in total of the seasonal rainfall variance in the two seasons. The last two decades experienced the highest negative anomaly, with OND seasonal rainfall showing higher anomalies as compared to MAM season. The OND season recorded 9% more drought events as compared to MAM season. The frequency of occurrence of moderate, severe and extreme dryness was almost the same in the two seasons. These results give a good basis for regional model validation, as well as mapping out drought hotspots and projections studies in the HoA.

scholarly journals Influence of Indian Ocean dipole on rainfall variability and extremes over southern Africa

MAUSAM ◽  
2021 ◽  
Vol 71 (4) ◽  
pp. 637-648
Author(s):  
OGWANG B. A. ◽  
ONGOMA V. ◽  
SHILENJE Z. W. ◽  
RAMOTUBEI T. S. ◽  
LETUMA M. ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Southern Africa ◽  
Indian Ocean Dipole ◽  
Rainfall Variability ◽  
Dominant Mode ◽  
Empirical Orthogonal Functions ◽  
Extreme Weather Events ◽  
Orthogonal Functions ◽  
Upper Level ◽  
The Relationship

Extreme weather events; floods and droughts are common in southern Africa (SA) consisting of 8 countries (Botswana, Namibia, South Africa, Lesotho, Swaziland, Mozambique, Zimbabwe, parts of Angola and Zambia). This study examines the linkage between the SA October-December (OND) rainfall, the Indian Ocean Dipole (IOD) and the South Atlantic Oscillation Dipole (SAOD). Empirical Orthogonal Functions (EOF) technique is used to establish the dominant mode of variability of OND rainfall, as correlation analysis is applied to quantify the relationship between the indices; IOD [Dipole Mode Index (DMI)], SAOD Index (SAODI) and OND rainfall variability. Results show that the dominant mode of variability of OND rainfall exhibits a dipole pattern over SA and there exists a significant correlation at 95% confidence level between the area average OND rainfall (rainfall index (RFI)) and DMI, with a correlation coefficient of -0.3. The relationship between the mean SA OND rainfall and the positive phase of IOD varies greatly in space, ranging from one country to another. Further analysis of the dry and wet of SAOND rainfall years reveal that wet years are associated with convergence at  surface level (850 hPa) and divergence at upper level (200 hPa), depicting rising motion in the region, whereas dry years are associated with divergence at low level and convergence at upper level, implying descending motion. The study recommends further research on a reduced spatial scale, for instance at a country level to ascertain the effect of IOD on individual country’s weather. This will help in accurate monitoring of the evolution of IOD events to improve quality of seasonal weather forecasts in the region.

scholarly journals Projected effects of 1.5 °C and 2 °C global warming levels on the intra-seasonal rainfall characteristics over the Greater Horn of Africa

2020 ◽  
Vol 15 (3) ◽  
pp. 034037 ◽  
Author(s):  
Masilin Gudoshava ◽  
Herbert O Misiani ◽  
Zewdu T Segele ◽  
Suman Jain ◽  
Jully O Ouma ◽  
...  
Keyword(s):  
Global Warming ◽  
Seasonal Rainfall ◽  
Horn Of Africa ◽  
Rainfall Characteristics ◽  
Greater Horn Of Africa

Understanding the role of water vapor and temperature in easterly wave-related convection

2020 ◽  
Author(s):  
Rosa Vargas Martes ◽  
Angel Adames Corraliza
Keyword(s):  
Water Vapor ◽  
Rainfall Variability ◽  
Large Fraction ◽  
Deep Convection ◽  
Linear Regression Analysis ◽  
Empirical Orthogonal Functions ◽  
Specific Humidity ◽  
Coupling Mechanism ◽  
Orthogonal Functions ◽  
The Relationship

<p>Easterly Waves (EW) in the Pacific Ocean (PEW) and over Africa (AEW) account for a large fraction of rainfall variability in their respective regions. Although multiple studies have been conducted to better understand EWs, many questions remain regarding their structure, development, and coupling to deep convection. Recent studies have highlighted the relationship between water vapor and precipitation in tropical motion systems. However, EW have not been studied within this context. On the basis of Empirical Orthogonal Functions (EOFs) and a novel plume-buoyancy framework, the thermodynamic processes associated with EW-related convection are elucidated. A linear regression analysis reveals the relationship between temperature, moisture, and precipitation in EW. Temperature anomalies are found to be highly correlated in space and time with anomalies in specific humidity. However, this coupling between temperature and moisture is more robust in AEWs than PEWs. In PEWs moisture accounts for a larger fraction of precipitation variability. Results suggest that the convective coupling mechanism in AEW may differ from the coupling mechanism of PEWs.</p>

scholarly journals Geospatial Trends and Decadal Anomalies in Extreme Rainfall over Uganda, East Africa

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Charles Onyutha
Keyword(s):  
North Atlantic Ocean ◽  
Rainfall Variability ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Empirical Orthogonal Functions ◽  
Orthogonal Functions ◽  
Indicator Method ◽  
Significance Level ◽  
Modes Of Variability ◽  
In Series

Trends and variability in series comprising the mean of fifteen highest daily rainfall intensities in each year were analyzed considering entire Uganda. The data were extracted from high-resolution (0.5° × 0.5°) gridded daily series of the Princeton Global Forcings covering the period 1948–2008. Variability was analyzed using nonparametric anomaly indicator method and empirical orthogonal functions. Possible drivers of the rainfall variability were investigated. Trends were analyzed using the cumulative rank difference approach. Generally, rainfall was above the long-term mean from the mid-1950s to the late 1960s and again in the 1990s. From around 1970 to the late 1980s, rainfall was characterized by a decrease. The first and second dominant modes of variability correspond with the variation in Indian Ocean Dipole and North Atlantic Ocean index, respectively. The influence of Niño 3 on the rainfall variability of some parts of the country was also evident. The southern and northern parts had positive and negative trends, respectively. The null hypothesisH0(no trend) was collectively rejected at the significance level of 5% in the series from 7 out of 168 grid points. The insights from the findings of this study are vital for planning and management of risk-based water resources applications.

scholarly journals An Empirical Seasonal Rainfall Forecasting Model for the Northeast Region of Brazil

Water ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1613
Author(s):  
Rodrigo Lins da Rocha Júnior ◽  
David Duarte Cavalcante Pinto ◽  
Fabrício Daniel dos Santos Silva ◽  
Heliofábio Barros Gomes ◽  
Helber Barros Gomes ◽  
...  
Keyword(s):  
Time Series ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Northern Region ◽  
Empirical Orthogonal Functions ◽  
Rainfall Forecasting ◽  
Orthogonal Functions ◽  
Northeast Region ◽  
Teleconnection Patterns ◽  
The North

The Northeast region of Brazil (NEB) is characterized by large climate variability that causes extreme and long unseasonal wet and dry periods. Despite significant model developments to improve seasonal forecasting for the NEB, the achievement of a satisfactory accuracy often remains a challenge, and forecasting methods aimed at reducing uncertainties regarding future climate are needed. In this work, we implement and assess the performance of an empirical model (EmpM) based on a decomposition of historical data into dominant modes of precipitation and seasonal forecast applied to the NEB domain. We analyzed the model’s performance for the February-March-April quarter and compared its results with forecasts based on data from the North American Multi-model Ensemble (NMME) project for the same period. We found that the first three leading precipitation modes obtained by empirical orthogonal functions (EOF) explained most of the rainfall variability for the season of interest. Thereby, this study focuses on them for the forecast evaluations. A teleconnection analysis shows that most of the variability in precipitation comes from sea surface temperature (SST) anomalies in various areas of the Pacific and the tropical Atlantic. The modes exhibit different spatial patterns across the NEB, with the first being concentrated in the northern half of the region and presenting remarkable associations with the El Niño-Southern Oscillation (ENSO) and the Atlantic Meridional Mode (AMM), both linked to the latitudinal migration of the intertropical convergence zone (ITCZ). As for the second mode, the correlations with oceanic regions and its loading pattern point to the influence of the incursion of frontal systems in the southern NEB. The time series of the third mode implies the influence of a lower frequency mode of variability, probably related to the Interdecadal Pacific Oscillation (IPO). The teleconnection patterns found in the analysis allowed for a reliable forecast of the time series of each mode, which, combined, result in the final rainfall prediction outputted by the model. Overall, the EmpM outperformed the post-processed NMME for most of the NEB, except for some areas along the northern region, where the NMME showed superiority.

scholarly journals Statistical Analysis of Seasonal Rainfall Variability and Characteristics in Ahmednagar District of Maharashtra, India

2020 ◽  
pp. 125-136
Author(s):  
Gadekar Deepak Janardhan ◽  
Soniya Sonkar
Keyword(s):  
Statistical Analysis ◽  
Rainfall Variability ◽  
Rainfall Data ◽  
Seasonal Rainfall ◽  
Rainfall Characteristics ◽  
Prone Area ◽  
Drought Prone Area

The three major characteristics of rainfall are mainly its amount, frequency and intensity. The value of rainfall varies greatly from day to day, place to place, month and year to year. Generally Akole tehsil receives the highest rainfall and Karjat and Jamkhed tehsils receives the least rainfall. The main reason for the highest rainfall in Akole tehsil is orographic type rainfall. The rainfall characteristics and distribution in drought prone area in study area. The research covers rainfall data from 1981 to 2014 and the rainfall data is taken from the statistical department website of Ahmednagar district.

scholarly journals DAMPAK VARIABILITAS IKLIM MUSIMAN PADA PRODUKSI PADI SAWAH TADAH HUJAN DI PULAU LOMBOK (IMPACT OF INTERANNUAL CLIMATE VARIABILITY ON RAINFED PADDY PRODUCTION IN LOMBOK ISLAND)

Agromet ◽  
2006 ◽  
Vol 20 (2) ◽  
pp. 38
Author(s):  
I. Yasin ◽  
M. Ma'shum
Keyword(s):  
Agricultural Land ◽  
Rainfall Variability ◽  
Storage System ◽  
Cropping System ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Rain Event ◽  
Rainfall Characteristics ◽  
Rainfall Variation ◽  
Wide Range

<p>Variability of inter-anuual rainfall has great impact on agricultural production. The inter-annual rainfall variability mainly causes cropping and harvest failure in rainfed land due to drought and flood. Although the onset of season is usully known, the characteristic of in coming rainfall is usually not predictable. Thus the understanding of the cause of rainfall variability may lead to establishment of new system to forecast seasonal rainfall characteristics. The aims of this research are to study water availibity for dry direct seeding rice by considering water balance in southern Lombok and understanding the relationship between ENSO phenomena with rain event in Lombok as well using SOI for predicting seasonal rainfall events. The results of this research showed that average rainfall in southern Lombok is 1450 mm with 950 mm the lowest and 2460 the highest. Southern Lombok has three water surplus months (with rainfall >200 mm), and 5 to 6 water deficit months (with less than 100 mm rainfall).. Inter annual rainfall variation is closely correlated to ENSO phenomena where the rainfall tend to be obove normal in La Niña years and below normal in El Niño years. The short term wet months and wide range of rainfall varibility lead to the need to establishment of water storage system and the application of water and cropping management which suitable to rainfall characteristics and local environmental conditions. The use of ENSO and SOI value to forecast seasonal rain events may be suitable and may reduce the risks of cropping system in rainfed agricultural land.</p>

scholarly journals On the Differences in the Intraseasonal Rainfall Variability between Western and Eastern Central Africa: Case of 10–25-Day Oscillations

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Alain Tchakoutio Sandjon ◽  
Armand Nzeukou ◽  
Clément Tchawoua ◽  
Tengeleng Siddi
Keyword(s):  
Time Series ◽  
Rainfall Variability ◽  
Intraseasonal Variability ◽  
Central Africa ◽  
Power Spectra ◽  
Correlation Coefficients ◽  
Empirical Orthogonal Functions ◽  
Orthogonal Functions ◽  
Intraseasonal Oscillations ◽  
Cross Correlations

In this paper, we analyze the space-time structures of the 10–25 day intraseasonal variability of rainfall over Central Africa (CA) using 1DD GPCP rainfall product for the period 1996–2009, with an emphasis on the comparison between the western Central Africa (WCA) and the eastern Central Africa (ECA) with different climate features. The results of Empirical Orthogonal Functions (EOFs) analysis have shown that the amount of variance explained by the leading EOFs is greater in ECA than WCA (40.6% and 48.1%, for WCA and ECA, resp.). For the two subregions, the power spectra of the principal components (PCs) peak around 15 days, indicating a biweekly signal. The lagged cross-correlations computed between WCA and ECA PCs time series showed that most of the WCA PCs lead ECA PCs time series with a time scale of 5–8 days. The variations of Intraseasonal Oscillations (ISO) activity are weak in WCA, when compared with ECA where the signal exhibits large annual and interannual variations. Globally, the correlation coefficients computed between ECA and WCA annual mean ISO power time series are weak, revealing that the processes driving the interannual modulation of ISO signal should be different in nature or magnitude in the two subregions.

Interannual Tasmanian Rainfall Variability Associated with Large-Scale Climate Modes

2009 ◽  
Vol 22 (16) ◽  
pp. 4383-4397 ◽  
Author(s):  
Khalia J. Hill ◽  
Agus Santoso ◽  
Matthew H. England
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Southern Annular Mode ◽  
Reanalysis Data ◽  
Empirical Orthogonal Functions ◽  
Orthogonal Functions ◽  
Climate Modes ◽  
Interannual Rainfall Variability ◽  
East West

Abstract Interannual rainfall variability over Tasmania is examined using observations and reanalysis data. Tasmanian rainfall is dominated by an east–west gradient of mean rainfall and variability. The Pacific–South American mode (PSA), El Niño–Southern Oscillation (ENSO), and the southern annular mode (SAM) each show clear influences on the interannual variability of Tasmanian rainfall. Composites of rainfall during each phase of ENSO and the PSA suggest a notable islandwide influence of these climate modes on Tasmanian rainfall. In contrast, the positive phase of the SAM is associated with drier conditions over the west of the island. The PSA and the SAM project most prominently over the southwest of the island, whereas the ENSO signature is strongest in the north. Empirical orthogonal functions (EOFs) of rainfall over Tasmania show a leading mode (explaining 72% of total variance) of coherent islandwide in-phase anomalies with dominant periods of 2 and 5 yr. The second EOF accounts for ∼14% of total variation, characterized by out-of-phase east–west anomalies, which is likely a combination of all three modes. The EOF1 mode can be attributed to ENSO, the PSA, and to a lesser extent the SAM.

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