Effect of rainfall variability and gauge representativeness on satellite rainfall accuracy in a small upland watershed in southern Ethiopia

2020 ◽  
pp. 1-15
Author(s):  
Kassaw Beshaw Tessema ◽  
Alemseged Tamiru Haile ◽  
Negash Wagesho Amencho ◽  
Emad Habib
Keyword(s):  
Rainfall Variability ◽  
Southern Ethiopia ◽  
Satellite Rainfall ◽  
Upland Watershed

scholarly journals Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices

2014 ◽  
Vol 11 (3) ◽  
pp. 3111-3136 ◽  
Author(s):  
C. Funk ◽  
A. Hoell ◽  
S. Shukla ◽  
I. Bladé ◽  
B. Liebmann ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Rainfall Variability ◽  
Sea Surface ◽  
Southern Ethiopia ◽  
East African ◽  
Central Pacific ◽  
Boreal Spring ◽  
Central Indian Ocean

Abstract. In southern Ethiopia, Eastern Kenya, and southern Somalia, poor boreal spring rains in 1999, 2000, 2004, 2007, 2008, 2009, and 2011 contributed to severe food insecurity and high levels of malnutrition. Predicting rainfall deficits in this region on seasonal and decadal time frames can help decision makers implement disaster risk reduction measures while guiding climate-smart adaptation and agricultural development. Building on recent research that links more frequent droughts in that region to a stronger Walker Circulation, warming in the Indo-Pacific warm pool, and an increased western Pacific sea surface temperature (SST) gradient, we show that the two dominant modes of East African boreal spring rainfall variability are tied, respectively, to western-central Pacific and central Indian Ocean SST. Variations in these rainfall modes can be predicted using two previously defined SST indices – the West Pacific Gradient (WPG) and Central Indian Ocean index (CIO), with the WPG and CIO being used, respectively, to predict the first and second rainfall modes. These simple indices can be used in concert with more sophisticated coupled modeling systems and land surface data assimilations to help inform early warning and guide climate outlooks.

scholarly journals Radar-observed spatial and temporal rainfall variability near the Tapajós-Amazon confluence

2014 ◽  
Vol 29 (spe) ◽  
pp. 23-30 ◽  
Author(s):  
Julia Clarinda Paiva Cohen ◽  
David Roy Fitzjarrald ◽  
Flávio Augusto Farias D'Oliveira ◽  
Ivan Saraiva ◽  
Illelson Rafael da Silva Barbosa ◽  
...  
Keyword(s):  
Rainfall Variability ◽  
Radar Reflectivity ◽  
Amazon River ◽  
Land Breeze ◽  
Areal Extent ◽  
Convective Conditions ◽  
The South ◽  
Satellite Rainfall ◽  
Rainfall Estimates

Standard Amazonian rainfall climatologies rely on stations preferentially located near river margins. River breeze circulations that tend to suppress afternoon rainfall near the river and enhance it inland are not typically considered when reporting results. Previous studies found surprising nocturnal rainfall maxima near the rivers in some locations. We examine spatial and temporal rainfall variability in the Santarém region of the Tapajós-Amazon confluence, seeking to describe the importance of breeze effects on afternoon precipitation and defining the areal extent of nocturnal rainfall maxima.We used three years of mean S band radar reflectivity from Santarém airport with a Z-R relationship appropriate for tropical convective conditions. These data were complemented by TRMM satellite rainfall estimates. Nocturnal rainfall was enhanced along the Amazon River, consistent with the hypothesis that these are associated with the passage of instability lines, perhaps enhanced by local channeling and by land breeze convergence. In the daytime, two rainfall bands appear in mean results, along the east bank of the Tapajós River and to the south of the Amazon River, respectively.

scholarly journals High-Resolution Monthly Rainfall Database for Ethiopia: Homogenization, Reconstruction, and Gridding

2012 ◽  
Vol 25 (24) ◽  
pp. 8422-8443 ◽  
Author(s):  
G. Mengistu Tsidu
Keyword(s):  
Harmonic Analysis ◽  
Missing Values ◽  
Rainfall Variability ◽  
Singular Spectrum Analysis ◽  
Monthly Rainfall ◽  
Climatic Research Unit ◽  
Southern Ethiopia ◽  
Self Organizing Map ◽  
Global Datasets ◽  
Self Organizing

Abstract Recent heightened concern regarding possible consequences of anthropogenically induced global warming has spurred analyses of data aimed at detection of climate change and more thorough characterization of the natural climate variability. However, there is greater concern regarding the extent and especially quality of the historical climate data. In this paper, rainfall records of 233 gauge stations over Ethiopia for the 1978–2007 period are employed in an analysis that involves homogenization, reconstruction, and gridding onto a regular 0.5° × 0.5° resolution grid. Inhomogeneity is detected and adjusted based on quantile matching. The regularized expectation-maximization and multichannel singular spectrum analysis algorithms are then utilized for imputation of missing values, and the latter has been determined to have a marginal advantage. Ordinary kriging is used to create a gridded monthly rainfall dataset. The spatial and temporal coherence of this dataset are assessed using harmonic analysis, self-organizing maps, and intercomparison with global datasets. The self-organizing map delineates Ethiopia into nine homogeneous rainfall regimes, which is consistent with seasonal and interannual rainfall variations. The harmonic analysis of the dataset reveals that the annual mode accounts for 55%–85% of the seasonal rainfall variability over western Ethiopia while the semiannual mode accounts for up to 40% over southern Ethiopia. The dataset is also intercompared with Global Precipitation Climatology Project (GPCP), Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP), Climatic Research Unit time series version 3 (CRUTS3.0), Tropical Rainfall Measuring Mission (TRMM), and interim ECMWF Re-Analysis (ERA-Interim) rainfall. The correlation of the dataset with global datasets ranges from 0.52 to 0.95 over sparse to dense rain gauge regions. The GPCP rainfall has a small bias and good correlation with the new dataset whereas TRMM and ERA-Interim have relatively large dry and wet biases, respectively.

scholarly journals Spatio-temporal analysis of remotely sensed rainfall datasets retrieved for the transboundary basin of the Madeira River in Amazonia

Atmósfera ◽  
2020 ◽  
Author(s):  
Vinicius Alexandre Sikora de Souza ◽  
Daniel Medeiros Moreira ◽  
Otto Corrêa Rotunno Filho ◽  
Anderson Paulo Rudke ◽  
Claudia Daza Andrade ◽  
...  
Keyword(s):  
River Basin ◽  
Rainfall Variability ◽  
Temporal Analysis ◽  
Remotely Sensed ◽  
Rain Gauges ◽  
Madeira River ◽  
Satellite Rainfall ◽  
Climate Hazards ◽  
Spatio Temporal ◽  
Madeira River Basin

Rainfall is recognized as the most important driving force of the hydrologic cycle. To accurately represent the spatio-temporal rainfall variability continues to be an enormous hydrological task when using commonly sparse, if available, rain gauges networks. Therefore, the present study devoted a special effort to analyze the robustness of some satellite rainfall products, notably the datasets hereafter named as (i) CHIRP (Climate Hazards Group InfraRed Precipitation), (ii) CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), (iii) 3B42, and (iv) 3B42RT of the Tropical Rainfall Measuring Mission (TRMM), to adequately represent the pluviometric regime in the Madeira river basin. To assess the accuracy of acquired remotely sensed rainfall products, comparisons to observational available rain gauges usually taken as ground-truth in the literature, despite their well-known limitations, were performed. Wavelet analysis was also used to validate the performance of the referred satellite products by means of extracting the corresponding cycles, frequencies, and tendencies along the available time series across the studied basin. The results showed that the data sources CHIRPS and CHIRP better represent the pluviometric phenomenon by means of their monthly accumulated rainfall in the Madeira river basin when compared to the 3B42 and 3B42RT products taking into account rain gauges as baseline information. The CHIRPS product performed the best among the selected rainfall estimators for the Madeira river basin. Further analysis brought up also another very interesting result related to non-rainfall periods, which is usually not reported. However, such evaluation is quite important in hydrology when examining run sequences of droughts and consequent effects in the water balance at the watershed scale. Highly accurate estimates in the sense of identifying non-rainfall periods by remotely sensed information was achieved, which represents an additional and valuable asset of satellite rainfall products. It is worthwhile to say that this perspective deserves to receive much more attention in the literature in order to deeply discuss the water-energy-food nexus.

scholarly journals Evaluating Climate Change Impact of Rainfed Maize Production Yield in Southern Ethiopia

2022 ◽  
Author(s):  
Kinde Negessa Disasa ◽  
Haofang Yan
Keyword(s):  
Climate Change ◽  
Time Horizon ◽  
Crop Production ◽  
Rainfall Variability ◽  
Maximum Temperature ◽  
Yield Response ◽  
Southern Ethiopia ◽  
Maize Production ◽  
Mitigation And Adaptation ◽  
Study Results

Abstract A developing country like Ethiopia suffers a lot from the effects of climate change due to its limited economic capability to build irrigation projects to combat climate change's impact on crop production. This study evaluates climate change's impact on rainfed maize production in the Southern part of Ethiopia. AquaCrop, developed by FAO that simulates the crop yield response to water deficit conditions, is employed to assess potential rainfed maize production in the study area with and without climate change. The Stochastic weather generators model LARS-WG of the latest version is used to simulate local-scale level climate variables based on low-resolution GCM outputs. The expected monthly percentage change of rainfall during these two-time horizons (2040 and 2060) ranges from -23.18 to 20.23% and -14.8 to 36.66 respectively. Moreover, the monthly mean of the minimum and maximum temperature are estimated to increase in the range of 1.296 0C to 2.192 0C and 0.98 0C to 1.84 0C for the first time horizon (2031-2050) and from 1.860C to 3.40C and 1.560C to 3.180C in the second time horizon (2051-2070), respectively. Maize yields are expected to increase with the range of 4.13–7% and 6.36–9.32% for the respective time horizon in the study area provided that all other parameters were kept the same. In conclusion, the study results suggest that rainfed maize yield responds positively to climate change if all field management, soil fertility, and crop variety improve were kept the same to baseline; but since there is intermodal rainfall variability among the seasons planting date should be scheduled well to combat water stress on crops. The authors believe that this study is very likely important for regional development agents (DA) and policymakers to cope up with the climate change phenomenon and take some mitigation and adaptation strategies.

scholarly journals Analysis of Climate Variability and Trends in Southern Ethiopia

Climate ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 96
Author(s):  
Abrham Belay ◽  
Teferi Demissie ◽  
John W. Recha ◽  
Christopher Oludhe ◽  
Philip M. Osano ◽  
...  
Keyword(s):  
Rainfall Variability ◽  
Rate Of Change ◽  
Mitigation Strategies ◽  
Annual Rainfall ◽  
Southern Ethiopia ◽  
Drought Indices ◽  
Trend Test ◽  
Rainfall Trends ◽  
Slope Estimator ◽  
Normal Rainfall

This study investigated the trends and variability of seasonal and annual rainfall and temperature data over southern Ethiopia using time series analysis for the period 1983–2016. Standard Anomaly Index (SAI), Coefficient of Variation (CV), Precipitations Concentration Index (PCI), and Standard Precipitation Index (SPI) were used to examine rainfall variability and develop drought indices over southern Ethiopia. Temporal changes of rainfall trends over the study period were detected using Mann Kendall (MK) trend test and Sen’s slope estimator. The results showed that the region experienced considerable rainfall variability and change that resulted in extended periods of drought and flood events within the study period. Results from SAI and SPI indicated an inter-annual rainfall variability with the proportions of years with below and above normal rainfall being estimated at 56% and 44% respectively. Results from the Mann Kendall trend test indicated an increasing trend of annual rainfall, Kiremt (summer) and Bega (dry) seasons whereas the Belg (spring) season rainfall showed a significant decreasing trend (p < 0.05). The annual rate of change for mean, maximum and minimum temperatures was found to be 0.042 °C, 0.027 °C, and 0.056 °C respectively. The findings from this study can be used by decision-makers in taking appropriate measures and interventions to avert the risks posed by changes in rainfall and temperature variability including extremes in order to enhance community adaptation and mitigation strategies in southern Ethiopia.

scholarly journals Investigating Spatial Downscaling of Satellite Rainfall Data for Streamflow Simulation in a Medium-Sized Basin

2009 ◽  
Vol 10 (4) ◽  
pp. 1063-1079 ◽  
Author(s):  
Sayma Rahman ◽  
Amvrossios C. Bagtzoglou ◽  
Faisal Hossain ◽  
Ling Tang ◽  
Lance D. Yarbrough ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Rainfall Variability ◽  
Tropical Rainfall Measuring Mission ◽  
Hydrologic Model ◽  
Rainfall Data ◽  
Streamflow Prediction ◽  
Satellite Rainfall ◽  
Spatial Downscaling ◽  
Streamflow Simulation

Abstract The objective of this study was to investigate spatial downscaling of satellite rainfall data for streamflow prediction in a medium-sized (970 km2) river basin prone to flooding. The spatial downscaling scheme used in the study was based on the principle of scale invariance. It reproduced the rainfall variability at finer scales while being conditioned on the large-scale rainfall. Two Tropical Rainfall Measuring Mission (TRMM)-based real-time global satellite rainfall products were analyzed: 1) the infrared (IR)-based 3B41RT product available at 1 hourly and 0.25° scales and 2) the combined passive microwave (PMW) and IR-based 3B42RT product available at 3 hourly and 0.25° scales. The conceptual Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) was used for the simulation of streamflow. It was found that propagation of spatially downscaled satellite rainfall in the hydrologic model increased simulation uncertainty in streamflow as rainfall grid scales became smaller than 0.25°. The streamflow simulation uncertainty for satellite downscaling was found to be very similar to that for ground validation Next Generation Weather Radar (NEXRAD) downscaling at any given scale, indicating that the effectiveness of the spatial downscaling scheme is not influenced by rainfall data type. Closer inspection at the subbasin level revealed that the limitation of the selected spatial downscaling scheme to preserve the mean rainfall intensity for irregularly sized drainage units was responsible for the increase in simulation uncertainty as scales became smaller. Although the findings should not be construed as a generalization for spatial downscaling schemes, there is a need for more rigorous hydrometeorological assessment of downscaled satellite rainfall data prior to institutionalizing its use for real-time streamflow simulation over ungauged basins.

Sign in / Sign up

Export Citation Format

Share Document