scholarly journals Spatial and temporal variability of rainfall in the Nile Basin

2014 ◽  
Vol 11 (10) ◽  
pp. 11945-11986 ◽  
Author(s):  
C. Onyutha ◽  
P. Willems
Keyword(s):  
Indian Ocean ◽  
Temporal Variability ◽  
Driving Forces ◽  
Equatorial Region ◽  
Annual Rainfall ◽  
Climate Indices ◽  
Spatial And Temporal Variability ◽  
Nile Basin ◽  
The North ◽  
Group A

Abstract. Spatio-temporal variability in annual and seasonal rainfall totals were assessed at 37 locations of the Nile Basin in Africa using quantile perturbation method. To get insight into the spatial difference in rainfall statistics, the stations were grouped based on the pattern of the long-term mean of monthly rainfall and that of temporal variability. To find the origin of the driving forces for the temporal variability in rainfall, correlation analyses were carried out using global monthly sea level pressure and surface temperature. Further investigations to support the obtained correlations were made using a total of 10 climate indices. It was possible to obtain 3 groups of stations; those within the equatorial region (A), Sudan and Ethiopia (B), and Egypt (C). For group A, annual rainfall was found to be below (above) the reference during the late 1940s to 1950s (1960s to mid 1980s). Conversely for groups B and C, the period 1930s to late 1950s (1960s to 1980s) was characterized by anomalies being above (below) the reference. For group A, significant linkages were found to Niño 3, Niño 3.4 and the North Atlantic and Indian Ocean drivers. Correlations of annual rainfall of group A with Pacific Ocean-related climate indices were inconclusive. With respect to the main wet seasons, the June to September rainfall of group B has strong connection to the influence from the Indian Ocean. For the March to May (October to February) rainfall of group A (C), possible links to the Atlantic and Indian Oceans were found.

scholarly journals Spatial and temporal variability of rainfall in the Nile Basin

2015 ◽  
Vol 19 (5) ◽  
pp. 2227-2246 ◽  
Author(s):  
C. Onyutha ◽  
P. Willems
Keyword(s):  
Indian Ocean ◽  
Temporal Variability ◽  
Driving Forces ◽  
Equatorial Region ◽  
Spatiotemporal Variability ◽  
Annual Rainfall ◽  
Climate Indices ◽  
Spatial And Temporal Variability ◽  
Nile Basin ◽  
Group A

Abstract. Spatiotemporal variability in annual and seasonal rainfall totals were assessed at 37 locations of the Nile Basin in Africa using quantile perturbation method (QPM). To get insight into the spatial difference in rainfall statistics, the stations were grouped based on the pattern of the long-term mean (LTM) of monthly rainfall and that of temporal variability. To find the origin of the driving forces for the temporal variability in rainfall, correlation analyses were carried out using global monthly sea level pressure (SLP) and sea surface temperature (SST). Further investigations to support the obtained correlations were made using a total of 10 climate indices. It was possible to obtain three groups of stations; those within the equatorial region (A), Sudan and Ethiopia (B), and Egypt (C). For group A, annual rainfall was found to be below (above) the reference during the late 1940s to 1950s (1960s to mid-1980s). Conversely for groups B and C, the period from 1930s to late 1950s (1960s to 1980s) was characterized by anomalies being above (below) the reference. For group A, significant linkages were found to Niño 3, Niño 3.4, and the North Atlantic Ocean and Indian Ocean drivers. Correlations of annual rainfall of group A with Pacific Ocean-related climate indices were inconclusive. With respect to the main wet seasons, the June–September rainfall of group B has strong connection to the influence from the Indian Ocean. For the March–May (October–February) rainfall of group A (C), possible links to the Atlantic and Indian oceans were found.

Temperature and precipitation projections for Poland based on downscaled EuroCORDEX ensemble

2020 ◽  
Author(s):  
Joanna Struzewska ◽  
Maciej Jefimow ◽  
Paulina Jagiełło ◽  
Maria Kłeczek ◽  
Anahita Sattari ◽  
...  
Keyword(s):  
Regional Climate ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Climate Indices ◽  
Climate Projections ◽  
Spatial And Temporal Variability ◽  
Climate Change Scenarios ◽  
North East ◽  
The North ◽  
Temperature And Precipitation

<p>Regional climate projections are necessary to assess possible changes in the exposure and risk to allow planning the adaptation strategies.</p><p>Projections of temperature and precipitation trends were developed using a consistent methodology and homogeneous datasets to address the needs of up-to-date climate change scenarios for Poland.</p><p>The Euro-Cordex results with the resolution of 0.11deg (about 12.5km) for RCP4.5 and RCP8.5 were downscaled based on various historical gridded datasets (EOBS, ERA5, UERRA and data from IMWM).</p><p>Ensemble analysis was undertaken to assess the projection uncertainty and ensemble mean were calculated for base parameters (daily average, minimum, and maximum temperature and daily precipitation sum) as well as for the number of climate indices.</p><p>We will present spatial and temporal variability of selected climate indices over Poland for subsequent decades. Increase of the annual average temperature is due to the rise in the number of hot days and the reduction of the number of frost days. All temperature indices are characterized by statistically significant trends, strongest for RCP8.5. The most pronounced changes in the frequency and amount of precipitation occur in the north-east of Poland. The total number of days with precipitation increases slightly. The increase in the annual rainfall is due to the increase in the number of days with extreme precipitation.</p><p>Results are presented via an interactive web portal. Further analysis includes the development of projection for solar radiation, wind speed, humidity and snow cover.</p>

scholarly journals Rainfall Characteristics in Ahmednagar District of Maharashtra State

2021 ◽  
pp. 355-362
Author(s):  
Dr. Vasudev S. Salunke ◽  
Pramila. P. Zaware
Keyword(s):  
Temporal Variability ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Agricultural Activity ◽  
Spatial And Temporal Variability ◽  
Agricultural Activities ◽  
Short Term ◽  
Rainfall Distribution ◽  
Rainfall Characteristics ◽  
Average Annual Rainfall

Rainfall is one of the vital form of precipitation which affects not only agricultural activity but also entire ecology in any region. Hence rainfall distribution and its trends in district is important to understand water availability and to take decisions for the agricultural activities in area. This research paper is an effort to assess the spatial and temporal rainfall variability of Ahmednagar district of Maharashtra State. Ahmednagar is popularly known as the largest district of Maharashtra with fourteen Talukas. The average annual rainfall of this district is 621 mm with an average of 46 rainy days. In this study the spatial and temporal rainfall distribution of this district is taken in to account. Short-term annual rainfall data are considered from 1998 to 2014. The daily rainfalls of monsoon months of all the fourteen Taluka are analyzed for the year 2015.It was found that spatial and temporal variability is high in the District.

scholarly journals Statistical prediction of seasonal cyclonic activity over North Indian Ocean

MAUSAM ◽  
2021 ◽  
Vol 63 (1) ◽  
pp. 17-28
Author(s):  
S. BALACHANDRAN ◽  
B. GEETHA
Keyword(s):  
Indian Ocean ◽  
Regression Model ◽  
North Indian Ocean ◽  
Statistical Prediction ◽  
Quantitative Prediction ◽  
Climate Indices ◽  
Bias Error ◽  
Northeast Monsoon ◽  
Cyclonic Activity ◽  
The North

The Northeast monsoon season of October to December (OND) is the primary season of cyclonic activity over the North Indian Ocean (NIO). The mean number of days of cyclonic activity over NIO during this season is about 20 days. In the present study, statistical prediction for seasonal cyclonic activity over the North Indian Ocean during the cyclone season of October to December is attempted using well known climate indices and regional circulation features during the recent 30 years of 1971-2000.Potential predictors are identified using correlation analysis and optimum numbers of predictors are chosen using screening regression technique. A qualitative prediction for number of Cyclonic Disturbance (CD) days is attempted by analysing the conditional means of the number of CD days during OND over NIO for different intervals of each predictor based on the 30 year data of 1971-2000. Predictions and their validations for the subsequent test period of 2001 to 2009, based on this scheme, are discussed. An attempt for quantitative prediction is also made by developing a multiple regression model for prediction of number of CD days over the NIO during OND using the same predictors. The regression model accounts for 70% of the inter annual variance. The root mean square error of estimate is 5 days and the bias error is 0.36 days. The regression model is cross validated by Jackknife method for each individual year using the data of 29 years from the sample excluding the year under consideration. The model is also tested for independent dataset for the years 2001 to 2009. Salient features of the model performance are discussed.

scholarly journals Contribution of TRMM 3B42 Data to Improve Knowledge on Rainfall in the Kayanga/Geba River Basin (Republic of Guinea, Senegal and GuineaBissau)

2018 ◽  
Vol 14 (9) ◽  
pp. 260
Author(s):  
Saly Sambou ◽  
Honore Dacosta ◽  
Abdoulaye Deme ◽  
Ibrahima Diouf
Keyword(s):  
Temporal Variability ◽  
Statistical Study ◽  
Correlation Coefficients ◽  
Tropical Rainfall Measuring Mission ◽  
Spatial And Temporal Variability ◽  
Rainfall Gradient ◽  
Republic Of Guinea ◽  
The North ◽  
Average Monthly Rainfall ◽  
Trmm 3B42

The use of Tropical Rainfall Measuring Mission (TRMM) data is an option for counteracting challenge of the lack of ground based observations, particularly in Kayanga/Gêba. This paper undertakes validation of monthly TRMM rainfall estimates before using it to understand the spatial and temporal variability in the Basin. This validation based on application of statistical study, made it possible to obtain interesting results with correlation coefficients varying from 0.92 to 0.96 and Nash indices close to 1. The analysis of the seasonal rainfall pattern shows consistence with ground based observations. The study of the annual cycle reveals that their interannual variability is similar to that of ground based observations. Finally, the interpolation of average monthly rainfall in the basin highlights the NorthSouth rainfall gradient, which shows that the South is wetter than the North, with differences more pronounced in August and September.

Sign in / Sign up

Export Citation Format

Share Document