Analysis of Spatio-temporal rainfall trends and rainfall variability in Botswana between 1958 and 2019

The present study assesses spatio-temporal rainfall variability of the most highlands to the coastal zones, comprising of eight provinces, of PNG. The variability investigation was carried out over for a period of 50 years starting from the year 1968 to 2018. After testing and checking for serial autocorrelation in the data series, Mann-Kendal non-parametric statistical evaluation was carried out to investigate rainfall trends and variability. Sen’s method was also used to investigate the magnitude of change in millimeters (mm) per year. Furthermore, the ArcGIS spatial analysis tools were used for the calculation of mean rainfall and to carry out spatial investigation. The assessments were carried out on an annual and seasonal basis within each designated study zone. CRU TS 4.03 gridded rainfall data on a 0.50 x 0.50 spatial resolution was used as an input data for trend as well as variability investigation. The CRU gridded station wise analysis was carried out to understand the variability at each specific location. From the assessments, it was found out that a higher rainfall is observed in the Eastern parts of Morobe, Southern Highlands region and central to northern part of Madang Province, while a low rainfall was observed in Goroka, the Western part of Morobe, Simbu, Western Highlands, Jiwaka and Enga province. From the trend investigation, it was observed that more grid stations show an increasing trend than a decreasing trend. On annual assessments, the significant decreasing trend is observed in the Enga and SH province, while significantly increasing trend is observed in the whole parts of Madang, and to the northern part of EH and Simbu Province. From overall assessments, it was found out that, there has been an increasing trend since 1968 up to the present.

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Rainfall spatio-temporal correlation and intermittency structure from micro-γ to meso-β scale in the Netherlands

Journal of Hydrometeorology ◽

10.1175/jhm-d-20-0311.1 ◽

2021 ◽

Author(s):

Thomas C. van Leth ◽

Hidde Leijnse ◽

Aart Overeem ◽

Remko Uijlenhoet

Keyword(s):

The Netherlands ◽

Spatial Scales ◽

Rainfall Variability ◽

Temporal Structure ◽

Temporal Correlation ◽

Exponential Model ◽

Rain Gauges ◽

Wide Range ◽

Spatio Temporal ◽

Two Parameter

AbstractWe investigate the spatio-temporal structure of rainfall at spatial scales from 7m to over 200 km in the Netherlands. We used data from two networks of laser disdrometers with complementary interstation distances in two Dutch cities (comprising five and six disdrometers, respectively) and a Dutch nationwide network of 31 automatic rain gauges. The smallest aggregation interval for which raindrop size distributions were collected by the disdrometers was 30 s, while the automatic rain gauges provided 10-min rainfall sums. This study aims to supplement other micro-γ investigations (usually performed in the context of spatial rainfall variability within a weather radar pixel) with new data, while characterizing the correlation structure across an extended range of scales. To quantify the spatio-temporal variability, we employ a two-parameter exponential model fitted to the spatial correlograms and characterize the parameters of the model as a function of the temporal aggregation interval. This widely used method allows for a meaningful comparison with seven other studies across contrasting climatic settings all around the world. We also separately analyzed the intermittency of the rainfall observations. We show that a single parameterization, consisting of a two-parameter exponential spatial model as a function of interstation distance combined with a power-law model for decorrelation distance as a function of aggregation interval, can coherently describe rainfall variability (both spatial correlation and intermittency) across a wide range of scales. Limiting the range of scales to those typically found in micro-γ variability studies (including four of the seven studies to which we compare our results) skews the parameterization and reduces its applicability to larger scales.

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Rainfall trend analysis using Mann-Kendall and Sen’s slope estimator test in West Kalimantan

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/893/1/012006 ◽

2021 ◽

Vol 893 (1) ◽

pp. 012006

Author(s):

F Aditya ◽

E Gusmayanti ◽

J Sudrajat

Keyword(s):

Climate Change ◽

Rainfall Variability ◽

Annual Rainfall ◽

Sen’S Slope Estimator ◽

West Kalimantan ◽

Rainfall Analysis ◽

Sen’S Slope ◽

Rainfall Trends ◽

Slope Estimator ◽

The Impact

Abstract Climate change has been a prominent issue in the last decade. Climate change on a global scale does not necessarily have the same effect in different regions. Rainfall is a crucial weather element related to climate change. Rainfall trends analysis is an appropriate step in assessing the impact of climate change on water availability and food security. This study examines rainfall variations and changes at West Kalimantan, focusing on Mempawah and Kubu Raya from 2000-2019. The Mann-Kendall (MK) and Sen's Slope estimator test, which can determine rainfall variability and long-term monotonic trends, were utilized to analyze 12 rainfall stations. The findings revealed that the annual rainfall pattern prevailed in all locations. Mempawah region tends to experience a downward trend, while Kubu Raya had an upward trend. However, a significant trend (at 95% confidence level) was identified in Sungai Kunyit with a slope value of -33.20 mm/year. This trend indicates that Sungai Kunyit will become drier in the future. The results of monthly rainfall analysis showed that significant upward and downward trends were detected in eight locations. Rainfall trends indicate that climate change has occurred in this region.

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

10.21203/rs.3.rs-104059/v1 ◽

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.

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Commercial microwave links instead of rain gauges: fiction or reality?

Water Science & Technology ◽

10.2166/wst.2014.466 ◽

2014 ◽

Vol 71 (1) ◽

pp. 31-37 ◽

Cited By ~ 27

Author(s):

Martin Fencl ◽

Jörg Rieckermann ◽

Petr Sýkora ◽

David Stránský ◽

Vojtěch Bareš

Keyword(s):

Rainfall Variability ◽

A Priori ◽

Rain Gauges ◽

Precipitation Estimates ◽

Spatio Temporal ◽

Areal Rainfall ◽

Quantitative Precipitation Estimates ◽

Commercial Microwave Links ◽

Unique Dataset

Commercial microwave links (MWLs) were suggested about a decade ago as a new source for quantitative precipitation estimates (QPEs). Meanwhile, the theory is well understood and rainfall monitoring with MWLs is on its way to being a mature technology, with several well-documented case studies, which investigate QPEs from multiple MWLs on the mesoscale. However, the potential of MWLs to observe microscale rainfall variability, which is important for urban hydrology, has not been investigated yet. In this paper, we assess the potential of MWLs to capture the spatio-temporal rainfall dynamics over small catchments of a few square kilometres. Specifically, we investigate the influence of different MWL topologies on areal rainfall estimation, which is important for experimental design or to a priori check the feasibility of using MWLs. In a dedicated case study in Prague, Czech Republic, we collected a unique dataset of 14 MWL signals with a temporal resolution of a few seconds and compared the QPEs from the MWLs to reference rainfall from multiple rain gauges. Our results show that, although QPEs from most MWLs are probably positively biased, they capture spatio-temporal rainfall variability on the microscale very well. Thus, they have great potential to improve runoff predictions. This is especially beneficial for heavy rainfall, which is usually decisive for urban drainage design.

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