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 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 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 Spatio-Temporal Variability and Trend of Rainfall and Its Association with Pacific Ocean Sea Surface Temperature in West Harerge Zone, Eastern Ethiopia

2020 ◽  
Author(s):  
Getachew Bayable Tiruneh ◽  
Gedamu Amare ◽  
Getnet Alemu ◽  
Temesgen Gashaw
Keyword(s):  
Pacific Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Temporal Variability ◽  
Rainfall Variability ◽  
Sea Surface ◽  
Annual Rainfall ◽  
Eastern Ethiopia ◽  
Spatio Temporal ◽  
Annual Time

Abstract Background: Rainfall variability is a common characteristic in Ethiopia and it exceedingly affects agriculture particularly in the eastern parts of the country where rainfall is relatively scarce. Hence, understanding the spatio-temporal variability of rainfall is indispensable for planning mitigation measures during high and low rainfall seasons. This study examined the spatio-temporal variability and trends of rainfall in the West Harerge Zone, eastern Ethiopia.Method: The coefficient of variation (CV) and standardized anomaly index (SAI) was employed to analyze rainfall variability while Mann-Kendall (MK) trend test and Sen’s slop estimator were employed to examine the trend and magnitude of the rainfall changes, respectively. The association between rainfall and Pacific Ocean Sea Surface Temperature (SST) was also evaluated by the Pearson correlation coefficient (r).Results: The annual rainfall CV ranges from 12-19.36% while the seasonal rainfall CV extends from 15-28.49%, 24-35.58%, and 38-75.9% for average Kiremt (June-September), Belg (February-May), and Bega (October-January) seasons, respectively (1983-2019). On the monthly basis, the trends of rainfall decreased in all months except in July, October, and November. However, the trends of rainfall were not statistically significant (α = 0.05), unlike November. The annual rainfall trends showed a non-significant decreasing trend. On a seasonal basis, the trend of mean Kiremt and Belg seasons rainfall was decreased. But, it increased in Bega season although it was not statistically significant. Moreover, the correlation between rainfall and Pacific Ocean SST was negative for Kiremt while positive for Belg and Bega seasons. Besides, the correlation between rainfall and Pacific Ocean SST was negative at annual time scales.Conclusions: High spatial and temporal rainfall variability on monthly, seasonal, and annual time scales was observed in the study area. Seasonal rainfall has high inter-annual variability in the dry season (Bega) than other seasons. The trends in rainfall were decreased in most of the months. Besides, the trend of rainfall was increased annually and in the Bega season rather than other seasons. Generally, the occurrence of droughts in the study area was associated with ENSO events like most other parts of Ethiopia and East Africa.

scholarly journals Spatial and Temporal Rainfall Variability over the Mountainous Central Pindus (Greece)

Climate ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 75 ◽  
Author(s):  
Stefanos Stefanidis ◽  
Dimitrios Stathis
Keyword(s):  
Multiple Regression ◽  
Rainfall Variability ◽  
Multiple Regression Model ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Spatial And Temporal Variability ◽  
Mountain Range ◽  
Rainfall Time Series ◽  
Distribution Maps ◽  
Mountainous Catchment

In this study, the authors evaluated the spatial and temporal variability of rainfall over the central Pindus mountain range. To accomplish this, long-term (1961–2016) monthly rainfall data from nine rain gauges were collected and analyzed. Seasonal and annual rainfall data were subjected to Mann–Kendall tests to assess the possible upward or downward statistically significant trends and to change-point analyses to detect whether a change in the rainfall time series mean had taken place. Additionally, Sen’s slope method was used to estimate the trend magnitude, whereas multiple regression models were developed to determine the relationship between rainfall and geomorphological factors. The results showed decreasing trends in annual, winter, and spring rainfalls and increasing trends in autumn and summer rainfalls, both not statistically significant, for most stations. Rainfall non-stationarity started to occur in the middle of the 1960s for the annual, autumn, spring, and summer rainfalls and in the early 1970s for the winter rainfall in most of the stations. In addition, the average magnitude trend per decade is approximately −1.9%, −3.2%, +0.7%, +0.2%, and +2.4% for annual, winter, autumn, spring, and summer rainfalls, respectively. The multiple regression model can explain 62.2% of the spatial variability in annual rainfall, 58.9% of variability in winter, 75.9% of variability in autumn, 55.1% of variability in spring, and 32.2% of variability in summer. Moreover, rainfall spatial distribution maps were produced using the ordinary kriging method, through GIS software, representing the major rainfall range within the mountainous catchment of the study area.

scholarly journals Rainfall statistics changes in Sicily

2013 ◽  
Vol 10 (2) ◽  
pp. 2323-2352 ◽  
Author(s):  
E. Arnone ◽  
D. Pumo ◽  
F. Viola ◽  
L. V. Noto ◽  
G. La Loggia
Keyword(s):  
Extreme Events ◽  
Daily Rainfall ◽  
Negative Trend ◽  
Rainfall Series ◽  
Annual Maximum ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Rainfall Characteristics ◽  
Annual Maximum Rainfall ◽  
Rainfall Statistics

Abstract. Changes in rainfall characteristics are one of the most relevant signs of current climate alterations. Many studies have demonstrated an increase in rainfall intensity and a reduction of frequency in several areas of the world, including Mediterranean areas. Rainfall characteristics may be crucial for vegetation patterns formation and evolution in Mediterranean ecosystems, with important implications, for example, in vegetation water stress or coexistence and competition dynamics. At the same time, characteristics of extreme rainfall events are fundamental for the estimation of flood peaks and quantiles which can be used in many hydrological applications, such as design of the most common hydraulic structures, or planning and management of flood prone areas. In the past, Sicily has been screened for several signals of possible climate change. Annual, seasonal and monthly rainfall data in the entire Sicilian region have been analyzed, showing a global reduction of total annual rainfall. Moreover, annual maximum rainfall series for different durations have been rarely analyzed in order to detect the presence of trends. Results indicated that for short durations, historical series generally exhibit increasing trends while for longer durations the trends are mainly negative. Starting from these premises, the aim of this study is to investigate and quantify changes in rainfall statistics in Sicily, during the second half of the last century. Time series of about 60 stations over the region have been processed and screened by using the non parametric Mann–Kendall test. Particularly, extreme events have been analyzed using annual maximum rainfall series at 1, 3, 6, 12 and 24 h duration while daily rainfall properties have been analyzed in term of frequency and intensity, also characterizing seasonal rainfall features. Results of extreme events analysis confirmed an increasing trend for rainfall of short durations, especially for one hour rainfall duration. Instead, precipitation of long durations have exhibited a decreased trend. With regard to the spatial distribution, increase in short duration precipitation has been observed especially in stations located along the coastline; however, no clear and well-defined spatial pattern have been outlined by the results. Outcomes of analysis for daily rainfall properties have showed that heavy-torrential precipitation tends to be more frequent at regional scale, while light rainfall events exhibited a negative trend at some sites. Values of total annual precipitations confirmed a significant negative trend, mainly due to the reduction during the winter season.

scholarly journals Spatio-temporal variability of climatic parameters across different altitudes of North- Western Himalaya

2021 ◽  
Vol 21 (3) ◽  
pp. 297-306
Author(s):  
PANKAJ PANWAR ◽  
SHARMISTHA PAL ◽  
NANCY LORIA ◽  
MED RAM VERMA ◽  
N.M. ALAM ◽  
...  
Keyword(s):  
Rainfall Variability ◽  
Management Strategies ◽  
Extreme Rainfall ◽  
Western Himalaya ◽  
Farming System ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Rainfall Occurrence ◽  
Spatio Temporal ◽  
Different Altitudes

Climate change impact varies across different altitudinal ranges and demands local specific management strategies for water resource and farming system management. The present study analyses spacio-temporal climate parameters across different altitudes of Himachal Pradesh a hilly state of India. Analysis shows that annually, minimum temperature has significantly decreased by -0.09°C at altitude I (350 - 400 m) while maximum temperature has significantly increased by 0.05°C at altitudes I and II (1400-1500 m) and decreased significantly by -0.08°C at altitude III (2000- 2100 m). Higher regions Altitude – IV (2900-3000 m) received lowest rainfall (746.1 mm) with 30.2 % variation. Seasonal rainfall variability was higher in post monsoon (102 - 174%) and least in monsoon (21 - 57%). Annual rainfall at altitude I is strongly irregular (PCI 20.1 to 22.3), followed by altitude – IV (PCI 15-25); altitude – II irregular (PCI 15-20) and altitude – III moderate to irregular (PCI 12 -19) rainfall. Seasonal Index values for four altitudes fall between 0.91-0.96 revealed that rainfall is irregular and markedly seasonal with longer drier season. Higher wavelet powers in altitude - I and II after 2005 suggests frequency of extreme rainfall occurrence had increased.

Less rain and rainy days - lessons from 45 years of rainfall data (1971 to 2015) in the Kathmandu Valley, Nepal

2021 ◽  
Author(s):  
Rajaram Prajapati ◽  
Rocky Talchabhadel ◽  
Priya Silwal ◽  
Surabhi Upadhyay ◽  
Brandon Ertis ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Temporal Trends ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Kathmandu Valley ◽  
Light Rain ◽  
Mk Test ◽  
Spatio Temporal ◽  
Rainy Days

Abstract Understanding spatio-temporal variability in rainfall patterns is crucial for evaluating water balances needed for water resources planning and management. This paper investigates spatio-temporal variability in rainfall and assesses the frequency of daily rainfall observations from seven stations in the Kathmandu Valley, Nepal, from 1971–2015. Daily rainfall totals were classified into five classes, namely, A (light rain, daily rainfall < 10 mm in a day), B (between 10–50 mm), C (between 50–100 mm), D (between 100–150 mm) and E (> 150 mm). The relationship between daily rainfall and rainfall frequency of various rainfall rate classes were analysed. Kriging method was used for interpolation in interpreting seasonal and annual rainfall data and spatial maps were generated using QGIS. The Mann-Kendall (MK) test was performed to determine the temporal trends and Theil-Sen’s (TS) slope estimator was used in quantifying the magnitude of trends. Mountain stations showed a decreasing trend in rainfall for all seasons, ranging from − 8.4 mm/year at Sankhu to -21.8 mm/year at Thankot, whereas, a mixed pattern was found on the Valley floor. Mean annual rainfall in the Valley was 1610 mm. Both annual rainfall and the number of rainy days decreased in the Kathmandu Valley over the study period. The study indicated a significant reduction in rainfall after 2000. Since springs and shallow groundwater are the primary sources of water supply for residents in the Kathmandu Valley, it is apparent that decreasing rainfall will have (and is already having) an adverse impact on domestic, industrial, and agricultural water supplies, and the livelihoods of people.

The Impact of Climate Change and Variability on Small-Scale Peri-Urban Horticultural Farmers in Domboshawa, Zimbabwe

2019 ◽  
pp. 46-69
Author(s):  
Vincent Itai Tanyanyiwa
Keyword(s):  
Climate Change ◽  
Smallholder Farmers ◽  
Climate Change Impacts ◽  
Annual Rainfall ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Clear Understanding ◽  
Rainfall Events ◽  
Climate Change And Variability ◽  
Dry Spells

Zimbabwe is a semi-arid country reliant on regular rains (November-April). Mean annual rainfall is low, and many rivers in the drier parts of the country are not perennial. In the small-scale horticultural sector, irrigation becomes handy. Rainfall exhibits spatial and temporal variability. This scenario is characterized by shifts in the onset of rains, increases in frequency and intensity of heavy rainfall events, increases in the proportion of low rainfall years, decreases in low-intensity rainfall events, and increases in the frequency and intensity of mid-season dry spells. Drought have increased in frequency and intensity. Agriculture is the main source of income for most smallholder farmers who depend on rain-fed cropping and livestock rearing. Adaptation of agriculture to climate variability and change impacts is vital for livelihood. To develop appropriate strategies and institutional responses to climate change adaptation, a clear understanding of climate change impacts on smallholder farmers at farm-level is vital.

An objective separation of rainfall classes in the high tropical Andes by using a clustering analysis.

2021 ◽  
Author(s):  
Gabriela Urgilés ◽  
Rolando Célleri ◽  
Katja Trachte ◽  
Jörg Bendix ◽  
Johanna Orellana-Alvear
Keyword(s):  
Clustering Analysis ◽  
Rainfall Variability ◽  
Tropical Andes ◽  
Mountain Area ◽  
Rainfall Events ◽  
Rainfall Characteristics ◽  
Melting Layer ◽  
Tropical Mountain ◽  
Layer Characteristic ◽  
Using Data

&lt;p&gt;Information about the temporal rainfall variability at high-resolution is scarce, especially in regions with complex topography as the Tropical Andes, and this hinders the study rainfall dynamics. The identification of rainfall types is usually determined using thresholds of some rainfall characteristics as rain rate and velocity. Nevertheless, these thresholds are identified for a specific study area and thus they cannot be extrapolated to other places to identify rainfall classes. Thus, the aim of this study is to investigate rainfall-event classes based on a clustering approach by using the k-means algorithm. The clustering analysis is used to group objects (i.e., rainfall-events) based on its characteristics (e.g., duration, intensity, drop size distribution, melting layer identification). This study was carried out using data retrieved from a vertically pointing Micro Rain Radar (MRR) and a laser disdrometer. The instruments were located in the tropical Andes, at 2600 m a.s.l., in the city of Cuenca, Ecuador.&amp;#160; Three years of data were available for the study. Firstly, the rainfall events were selected by using the criteria: minimum inter-event, minimum total accumulation and minimum duration. Then, by using the k-means algorithm, two principal rainfall classes were identified in the study area. These rainfall classes (i.e., convective, stratiform) showed marked differences in their rainfall characteristics. Besides, a third rainfall class (mixed class) was identified as a subclass of the stratiform class. The stratiform class was more common during the year in the study area. Also, short duration rainfall events (less than 70 min) were dominant. Furthermore, the melting layer characteristic &amp;#8211; that is used to determine rainfall classes &amp;#8211; did not influence the rainfall class identification using the clustering analysis, especially in two classes; thus, its prior study is not necessary, and this makes the clustering analysis highly beneficial. Finally, this clustering analysis ensured an objective separation of rainfall classes in the tropical high Andes. This rainfall classification provided new insights about the rainfall dynamics in this tropical mountain area.&lt;/p&gt;

The Impact of Climate Change and Variability on Small-Scale Peri-Urban Horticultural Farmers in Domboshawa, Zimbabwe

2022 ◽  
pp. 1535-1553
Author(s):  
Vincent Itai Tanyanyiwa
Keyword(s):  
Climate Change ◽  
Smallholder Farmers ◽  
Climate Change Impacts ◽  
Annual Rainfall ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Clear Understanding ◽  
Rainfall Events ◽  
Climate Change And Variability ◽  
Dry Spells

Zimbabwe is a semi-arid country reliant on regular rains (November-April). Mean annual rainfall is low, and many rivers in the drier parts of the country are not perennial. In the small-scale horticultural sector, irrigation becomes handy. Rainfall exhibits spatial and temporal variability. This scenario is characterized by shifts in the onset of rains, increases in frequency and intensity of heavy rainfall events, increases in the proportion of low rainfall years, decreases in low-intensity rainfall events, and increases in the frequency and intensity of mid-season dry spells. Drought have increased in frequency and intensity. Agriculture is the main source of income for most smallholder farmers who depend on rain-fed cropping and livestock rearing. Adaptation of agriculture to climate variability and change impacts is vital for livelihood. To develop appropriate strategies and institutional responses to climate change adaptation, a clear understanding of climate change impacts on smallholder farmers at farm-level is vital.

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