scholarly journals Validation of Satellite Rainfall Products for Western Uganda

2014 ◽  
Vol 15 (5) ◽  
pp. 2030-2038 ◽  
Author(s):  
Jeremy E. Diem ◽  
Joel Hartter ◽  
Sadie J. Ryan ◽  
Michael W. Palace
Keyword(s):  
Daily Rainfall ◽  
Summer Rainfall ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Boreal Summer ◽  
Time Step ◽  
African Rainfall ◽  
Rainfall Total ◽  
Mean Annual Rainfall ◽  
Western Uganda

Abstract Central equatorial Africa is deficient in long-term, ground-based measurements of rainfall; therefore, the aim of this study is to assess the accuracy of three high-resolution, satellite-based rainfall products in western Uganda for the 2001–10 period. The three products are African Rainfall Climatology, version 2 (ARC2); African Rainfall Estimation Algorithm, version 2 (RFE2); and 3B42 from the Tropical Rainfall Measuring Mission, version 7 (i.e., 3B42v7). Daily rainfall totals from six gauges were used to assess the accuracy of satellite-based rainfall estimates of rainfall days, daily rainfall totals, 10-day rainfall totals, monthly rainfall totals, and seasonal rainfall totals. The northern stations had a mean annual rainfall total of 1390 mm, while the southern stations had a mean annual rainfall total of 900 mm. 3B42v7 was the only product that did not underestimate boreal-summer rainfall at the northern stations, which had ~3 times as much rainfall during boreal summer than did the southern stations. The three products tended to overestimate rainfall days at all stations and were borderline satisfactory at identifying rainfall days at the northern stations; the products did not perform satisfactorily at the southern stations. At the northern stations, 3B42v7 performed satisfactorily at estimating monthly and seasonal rainfall totals, ARC2 was only satisfactory at estimating seasonal rainfall totals, and RFE2 did not perform satisfactorily at any time step. The satellite products performed worst at the two stations located in rain shadows, and 3B42v7 had substantial overestimates at those stations.

Rainfall erosivity estimation using daily rainfall amounts for South Australia

Soil Research ◽  
1996 ◽  
Vol 34 (5) ◽  
pp. 721 ◽  
Author(s):  
B Yu ◽  
CJ Rosewell
Keyword(s):  
Model Performance ◽  
South Australia ◽  
Daily Rainfall ◽  
Summer Rainfall ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
The South ◽  
Winter Rainfall ◽  
R Factor

The rainfall erosivity model relating storm erosivity to daily rainfall amounts was tested for 4 sites in South Australia where seasonal rainfall erosivity is generally out of phase with seasonal rainfall because of the predominant winter rainfall. The model worked reasonably well, with the coefficient of efficiency varying from 0.54 to 0.77, and the average discrepancy between actual and estimated monthly distribution was no more than 3%. The model performance in the winter rainfall area is similar to that in the uniform and summer rainfall areas. A set of regional parameter values estimated using a combined dataset is recommended for other sites in the agricultural and viticultural areas of South Australia where the mean annual rainfall ranges from 300 to 500 mm. The R-factor and its seasonal distribution were estimated for 99 sites in South Australia using long-term daily rainfall data. The R-factor varies mostly between 250 and 500 MJ . mm/(ha . h . year). Rainfall erosivity peaks in winter in the southern part of the western agricultural area and the south-east corner of the State, while it peaks in summer in the inland area east of the South Flinders and Mount Lofty Ranges.

scholarly journals Stochastic generation of annual, monthly and daily climate data: A review

2001 ◽  
Vol 5 (4) ◽  
pp. 653-670 ◽  
Author(s):  
R. Srikanthan ◽  
T. A. McMahon
Keyword(s):  
Climate Change ◽  
Historical Data ◽  
Southern Oscillation ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Model Parameters ◽  
Annual Data ◽  
Climate Data ◽  
Time Step ◽  
Method Of Fragments

Abstract. The generation of rainfall and other climate data needs a range of models depending on the time and spatial scales involved. Most of the models used previously do not take into account year to year variations in the model parameters. Long periods of wet and dry years were observed in the past but were not taken into account. Recently, Thyer and Kuczera (1999) developed a hidden state Markov model to account for the wet and dry spells explicitly in annual rainfall. This review looks firstly at traditional time series models and then at the more complex models which take account of the pseudo-cycles in the data. Monthly rainfall data have been generated successfully by using the method of fragments. The main criticism of this approach is the repetitions of the same yearly pattern when only a limited number of years of historical data are available. This deficiency has been overcome by using synthetic fragments but this brings an additional problem of generating the right number of months with zero rainfall. Disaggregation schemes are effective in obtaining monthly data but the main problem is the large number of parameters to be estimated when dealing with many sites. Several simplifications have been proposed to overcome this problem. Models for generating daily rainfall are well developed. The transition probability matrix method preserves most of the characteristics of daily, monthly and annual characteristics and is shown to be the best performing model. The two-part model has been shown by many researchers to perform well across a range of climates at the daily level but has not been tested adequately at monthly or annual levels. A shortcoming of the existing models is the consistent underestimation of the variances of the simulated monthly and annual totals. As an alternative, conditioning model parameters on monthly amounts or perturbing the model parameters with the Southern Oscillation Index (SOI) result in better agreement between the variance of the simulated and observed annual rainfall and these approaches should be investigated further. As climate data are less variable than rainfall, but are correlated among themselves and with rainfall, multisite-type models have been used successfully to generate annual data. The monthly climate data can be obtained by disaggregating these annual data. On a daily time step at a site, climate data have been generated using a multisite type model conditional on the state of the present and previous days. The generation of daily climate data at a number of sites remains a challenging problem. If daily rainfall can be modelled successfully by a censored power of normal distribution then the model can be extended easily to generate daily climate data at several sites simultaneously. Most of the early work on the impacts of climate change used historical data adjusted for the climate change. In recent studies, stochastic daily weather generation models are used to compute climate data by adjusting the parameters appropriately for the future climates assumed.

scholarly journals Weather Types and Rainfall over Senegal. Part I: Observational Analysis

2008 ◽  
Vol 21 (2) ◽  
pp. 266-287 ◽  
Author(s):  
Vincent Moron ◽  
Andrew W. Robertson ◽  
M. Neil Ward ◽  
Ousmane Ndiaye
Keyword(s):  
Rainfall Variability ◽  
Regional Scale ◽  
Daily Rainfall ◽  
Weather Type ◽  
Seasonal Rainfall ◽  
Boreal Summer ◽  
Frequency Of Occurrence ◽  
Weather Types ◽  
Western Sahel ◽  
Type Frequency

Abstract A k-means cluster analysis is used to summarize unfiltered daily atmospheric variability at regional scale over the western Sahel and eastern tropical North Atlantic during the boreal summer season [July–September (JAS)] 1961–98. The analysis employs zonal and meridional regional wind fields at 925, 700, and 200 hPa from the European Centre for Medium-Range Weather Forecasts reanalyses. An eight-cluster solution is shown to yield an integrated view of the complex regional circulation variability, without the need for explicit time filtering. Five of the weather types identified characterize mostly typical phases of westward-moving wave disturbances, such as African easterly waves (AEWs), and persistent monsoon surges, while the three others describe mostly different stages of the seasonal cycle. Their temporal sequencing describes a systematic monsoonal evolution, together with considerable variability at subseasonal and interannual time scales. Daily rainfall occurrence at 13 gauge stations in Senegal is found to be moderately well conditioned by the eight weather types, with positive rainfall anomalies usually associated with southerly wind anomalies at 925 hPa. Interannual variability of daily rainfall frequency is shown to depend substantially on the frequency of occurrence of weather types specific to the beginning and end of the JAS season, together with the number of persistent monsoon surges over the western Sahel. In contrast, year-to-year changes in the frequency of the weather types mostly associated with westward-moving waves such as AEWs are not found to influence seasonal frequency of occurrence of daily rainfall substantially. The fraction of seasonal rainfall variability related to weather-type frequency is found to have a strong relationship with tropical Pacific sea surface temperatures (SSTs): an El Niño (La Niña) event tends to be associated with a higher (lower) frequency of dry weather types during early and late JAS season with enhanced trade winds over the western Sahel, together with lower (higher) prevalence of persistent monsoon surges. The component of seasonal rainfall variability not related to weather-type frequency is characterized by changes in rainfall probability within each weather type, especially those occurring in the core of the JAS season; it exhibits a larger decadal component that is associated with an SST pattern previously identified with recent observed trends in Sahel rainfall.

scholarly journals Recent Trends in the Daily Rainfall Regime in Southern West Africa

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 741 ◽  
Author(s):  
Francis Nkrumah ◽  
Théo Vischel ◽  
Geremy Panthou ◽  
Nana Ama Browne Klutse ◽  
David C. Adukpo ◽  
...  
Keyword(s):  
West Africa ◽  
Rainy Season ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Large Set ◽  
Mean Intensity ◽  
Mean Annual Rainfall ◽  
Recent Trends ◽  
The Mean ◽  
Climate Events

Extreme climate events, either being linked to dry spells or extreme precipitation, are of major concern in Africa, a region in which the economy and population are highly vulnerable to climate hazards. However, recent trends in climate events are not often documented in this poorly surveyed continent. This study makes use of a large set of daily rain gauge data covering Southern West Africa (extending from 10° W to 10° E and from 4° N to 12° N) from 1950 to 2014. The evolution of the number and the intensity of daily rainfall events, especially the most extremes, were analyzed at the annual and seasonal scales. During the first rainy season (April–July), mean annual rainfall is observed to have a minor trend due to less frequent but more intense rainfall mainly along the coast of Southern West Africa (SWA) over the last two decades. The north–south seasonal changes exhibit an increase in mean annual rainfall over the last decade during the second rainy season (September–November) linked by both an increase in the frequency of occurrence of rainy days as well as an increase in the mean intensity and extreme events over the last decade. The study also provides evidence of a disparity that exists between the west and east of SWA, with the east recording a stronger increase in the mean intensity of wet days and extreme rainfall during the second rainy season (September–November).

scholarly journals Evaluation and Application of Multi-Source Satellite Rainfall Product CHIRPS to Assess Spatio-Temporal Rainfall Variability on Data-Sparse Western Margins of Ethiopian Highlands

2019 ◽  
Vol 11 (22) ◽  
pp. 2688 ◽  
Author(s):  
Ashebir Sewale Belay ◽  
Ayele Almaw Fenta ◽  
Alemu Yenehun ◽  
Fenta Nigate ◽  
Seifu A. Tilahun ◽  
...  
Keyword(s):  
Rainfall Variability ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Integration Time ◽  
Spatial And Temporal Variability ◽  
Rainfall Events ◽  
Rainfall Characteristics ◽  
Mean Annual Rainfall ◽  
Time Space ◽  
Spatio Temporal

The spatio-temporal characteristic of rainfall in the Beles Basin of Ethiopia is poorly understood, mainly due to lack of data. With recent advances in remote sensing, satellite derived rainfall products have become alternative sources of rainfall data for such poorly gauged areas. The objectives of this study were: (i) to evaluate a multi-source rainfall product (Climate Hazards Group Infrared Precipitation with Stations: CHIRPS) for the Beles Basin using gauge measurements and (ii) to assess the spatial and temporal variability of rainfall across the basin using validated CHIRPS data for the period 1981–2017. Categorical and continuous validation statistics were used to evaluate the performance, and time-space variability of rainfall was analyzed using GIS operations and statistical methods. Results showed a slight overestimation of rainfall occurrence by CHIRPS for the lowland region and underestimation for the highland region. CHIRPS underestimated the proportion of light daily rainfall events and overestimated the proportion of high intensity daily rainfall events. CHIRPS rainfall amount estimates were better in highland regions than in lowland regions, and became more accurate as the duration of the integration time increases from days to months. The annual spatio-temporal analysis result using CHIRPS revealed: a mean annual rainfall of the basin is 1490 mm (1050–2090 mm), a 50 mm increase of mean annual rainfall per 100 m elevation rise, periodical and persistent drought occurrence every 8 to 10 years, a significant increasing trend of rainfall (~5 mm year−1), high rainfall variability observed at the lowland and drier parts of the basin and high coefficient of variation of monthly rainfall in March and April (revealing occurrence of bimodal rainfall characteristics). This study shows that the performance of CHIRPS product can vary spatially within a small basin level, and CHIRPS can help for better decision making in poorly gauged areas by giving an option to understand the space-time variability of rainfall characteristics.

scholarly journals Precipitation characteristics over Paradeep

MAUSAM ◽  
2021 ◽  
Vol 49 (3) ◽  
pp. 321-324
Author(s):  
T. R. SIVARAMAKRISHNAN ◽  
J. R. PRASAD
Keyword(s):  
Monsoon Season ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Monsoon Period ◽  
Mean Annual Rainfall ◽  
Precipitation Characteristics ◽  
The Mean ◽  
Rainfall Climatology

The daily rainfall records since 1976 and the SRRG records after its installation in 1982 at Paradeep have been analysed and rainfall climatology has been worked out. The heaviest 24-hour rainfall recorded at the station is 264 mm on 4 June 1982. The mean annual rainfall is 1475 mm. January and December are near dry months while August is the wettest month getting about 339 mm rainfall. The variability of annual rainfall here is 20 %. Light rainspells giving a total rain of 10 mm or less form about 50% occasions in pre-monsoon period and 63% of occasions in monsoon period. The extended rainspells lasting for more than 4 hours form about 10% of occasions in pre-monsoon season and 6% occasions in monsoon season. While morning (04-08 hr IST) period gets the rainfall in both pre-monsoon and monsoon months, early night gets the peak rainfall activity during the pre-monsoon months.

scholarly journals Monitoring Water Resources over the Kotmale Reservoir in Sri Lanka Using ENSO Phases

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Sewwandhi Chandrasekara ◽  
Venkatraman Prasanna ◽  
Hyun-Han Kwon
Keyword(s):  
Sri Lanka ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Southern Oscillation ◽  
Daily Rainfall ◽  
Sea Surface ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Average Rainfall ◽  
Enso Phases

In this study, the El Nino Southern Oscillation (ENSO) phase index is used for water management over the Kotmale reservoir in Sri Lanka. Daily rainfall data of 9 stations over the Kotmale catchment during 1960–2005 June-September (JJAS) season is investigated over the Kotmale catchment. The ENSO phases are identified based on the 0.5°C sea surface temperature (SST) anomaly over Nino 3 region. The study has brought out few stations showing increasing and a few decreasing seasonal rainfall trends for JJAS season, while there is no change in the annual rainfall for the catchment. Monthly and seasonal rainfall of all the selected stations showed negative correlation with the sea surface temperature (SST) over the Nino-3 region index during JJAS season with varying magnitudes. During the warm phase of ENSO, below average rainfall is prominent for JJAS season over many stations. The rainfall especially during early September showed a significant below average rainfall during the warm ENSO phase. The seasonal rainfall during neutral and cold ENSO phases does not experience similar significant changes as seen during warm ENSO phase. Inflow of the Kotmale reservoir shows decreasing trend for the period of 1960–2005 in the observation from all stations collectively.

scholarly journals Rainfall-Runoff Modeling Using the HEC-HMS Model for the Al-Adhaim River Catchment, Northern Iraq

Hydrology ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 58
Author(s):  
Ahmed Naseh Ahmed Hamdan ◽  
Suhad Almuktar ◽  
Miklas Scholz
Keyword(s):  
Geographical Information Systems ◽  
Hydrological Model ◽  
Daily Rainfall ◽  
Curve Number ◽  
Geographical Information ◽  
Coefficient Of Determination ◽  
Rainfall Runoff ◽  
Time Step ◽  
River Catchment ◽  
Northern Iraq

It has become necessary to estimate the quantities of runoff by knowing the amount of rainfall to calculate the required quantities of water storage in reservoirs and to determine the likelihood of flooding. The present study deals with the development of a hydrological model named Hydrologic Engineering Center (HEC-HMS), which uses Digital Elevation Models (DEM). This hydrological model was used by means of the Geospatial Hydrologic Modeling Extension (HEC-GeoHMS) and Geographical Information Systems (GIS) to identify the discharge of the Al-Adhaim River catchment and embankment dam in Iraq by simulated rainfall-runoff processes. The meteorological models were developed within the HEC-HMS from the recorded daily rainfall data for the hydrological years 2015 to 2018. The control specifications were defined for the specified period and one day time step. The Soil Conservation Service-Curve number (SCS-CN), SCS Unit Hydrograph and Muskingum methods were used for loss, transformation and routing calculations, respectively. The model was simulated for two years for calibration and one year for verification of the daily rainfall values. The results showed that both observed and simulated hydrographs were highly correlated. The model’s performance was evaluated by using a coefficient of determination of 90% for calibration and verification. The dam’s discharge for the considered period was successfully simulated but slightly overestimated. The results indicated that the model is suitable for hydrological simulations in the Al-Adhaim river catchment.

scholarly journals Mechanisms Associated with Large Daily Rainfall Events in Northeast Brazil

2011 ◽  
Vol 24 (2) ◽  
pp. 376-396 ◽  
Author(s):  
Brant Liebmann ◽  
George N. Kiladis ◽  
Dave Allured ◽  
Carolina S. Vera ◽  
Charles Jones ◽  
...  
Keyword(s):  
Daily Rainfall ◽  
Annual Rainfall ◽  
Northeast Brazil ◽  
Kelvin Wave ◽  
Rainfall Events ◽  
Independent Events ◽  
Precipitation Anomalies ◽  
Wave Trains ◽  
Using Data ◽  
Forcing Mechanisms

Abstract The mechanisms resulting in large daily rainfall events in Northeast Brazil are analyzed using data filtering to exclude periods longer than 30 days. Composites of circulation fields that include all independent events do not reveal any obvious forcing mechanisms as multiple patterns contribute to Northeast Brazil precipitation variability. To isolate coherent patterns, subsets of events are selected based on anomalies that precede the Northeast Brazil precipitation events at different locations. The results indicate that at 10°S, 40°W, the area of lowest annual rainfall in Brazil, precipitation occurs mainly in association with trailing midlatitude synoptic wave trains originating in either hemisphere. Closer to the equator at 5°S, 37.5°W, an additional convection precursor is found to the west, with a spatial structure consistent with that of a Kelvin wave. Although these two sites are located within only several hundred kilometers of each other and the midlatitude patterns that induce precipitation appear to be quite similar, the dates on which large precipitation anomalies occur at each location are almost entirely independent, pointing to separate forcing mechanisms.

scholarly journals The Wet and Dry Spells across India during 1951–2007

2010 ◽  
Vol 11 (1) ◽  
pp. 26-45 ◽  
Author(s):  
Nityanand Singh ◽  
Ashwini Ranade
Keyword(s):  
Climate Change ◽  
Rainfall Intensity ◽  
Total Duration ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Change Scenario ◽  
Monsoon Period ◽  
Northwestern India ◽  
Area Of Interest ◽  
Dry Spells

Abstract Characteristics of wet spells (WSs) and intervening dry spells (DSs) are extremely useful for water-related sectors. The information takes on greater significance in the wake of global climate change and climate-change scenario projections. The features of 40 parameters of the rainfall time distribution as well as their extremes have been studied for two wet and dry spells for 19 subregions across India using gridded daily rainfall available on 1° latitude × 1° longitude spatial resolution for the period 1951–2007. In a low-frequency-mode, intra-annual rainfall variation, WS (DS) is identified as a “continuous period with daily rainfall equal to or greater than (less than) daily mean rainfall (DMR) of climatological monsoon period over the area of interest.” The DMR shows significant spatial variation from 2.6 mm day−1 over the extreme southeast peninsula (ESEP) to 20.2 mm day−1 over the southern-central west coast (SCWC). Climatologically, the number of WSs (DSs) decreases from 11 (10) over the extreme south peninsula to 4 (3) over northwestern India as a result of a decrease in tropical and oceanic influences. The total duration of WSs (DSs) decreases from 101 (173) to 45 (29) days, and the duration of individual WS (DS) from 12 (18) to 7 (11) days following similar spatial patterns. Broadly, the total rainfall of wet and dry spells, and rainfall amount and rainfall intensity of actual and extreme wet and dry spells, are high over orographic regions and low over the peninsula, Indo-Gangetic plains, and northwest dry province. The rainfall due to WSs (DSs) contributes ∼68% (∼17%) to the respective annual total. The start of the first wet spell is earlier (19 March) over ESEP and later (22 June) over northwestern India, and the end of the last wet spell occurs in reverse, that is, earlier (12 September) from northwestern India and later (16 December) from ESEP. In recent years/decades, actual and extreme WSs are slightly shorter and their rainfall intensity higher over a majority of the subregions, whereas actual and extreme DSs are slightly (not significantly) longer and their rainfall intensity weaker. There is a tendency for the first WS to start approximately six days earlier across the country and the last WS to end approximately two days earlier, giving rise to longer duration of rainfall activities by approximately four days. However, a spatially coherent, robust, long-term trend (1951–2007) is not seen in any of the 40 WS/DS parameters examined in the present study.

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