scholarly journals Assessing spatio-temporal rainfall variability in a tropical mountain area (Ethiopia) using NOAA’s rainfall estimates

2013 ◽  
Vol 34 (23) ◽  
pp. 8319-8335 ◽  
Author(s):  
Miro Jacob ◽  
Amaury Frankl ◽  
Mitiku Haile ◽  
Ann Zwertvaegher ◽  
Jan Nyssen
Keyword(s):  
Rainfall Variability ◽  
Mountain Area ◽  
Tropical Mountain ◽  
Spatio Temporal ◽  
Rainfall Estimates

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

<p>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.  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 – that is used to determine rainfall classes – 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.</p>

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

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.

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.

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

2014 ◽  
Vol 71 (1) ◽  
pp. 31-37 ◽  
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.

Relevance of spatio-temporal rainfall variability regarding groundwater management challenges under global change: case study in Doñana (SW Spain)

2020 ◽  
Vol 34 (9) ◽  
pp. 1289-1311 ◽  
Author(s):  
N. Naranjo-Fernández ◽  
C. Guardiola-Albert ◽  
H. Aguilera ◽  
C. Serrano-Hidalgo ◽  
M. Rodríguez-Rodríguez ◽  
...  
Keyword(s):  
Global Change ◽  
Groundwater Management ◽  
Rainfall Variability ◽  
Sw Spain ◽  
Spatio Temporal

scholarly journals Evaluation of spatio‐temporal rainfall variability and performance of a stochastic rainfall model in Bangladesh

2019 ◽  
Vol 39 (11) ◽  
pp. 4256-4273 ◽  
Author(s):  
AFM Kamal Chowdhury ◽  
Kanak Kanti Kar ◽  
Shamsuddin Shahid ◽  
Rezaul Chowdhury ◽  
Md. Mamunur Rashid
Keyword(s):  
Rainfall Variability ◽  
Rainfall Model ◽  
Spatio Temporal ◽  
And Performance

Land cover changes as impacted by spatio-temporal rainfall variability along the Ethiopian Rift Valley escarpment

2016 ◽  
Vol 17 (2) ◽  
pp. 451-463 ◽  
Author(s):  
Sofie Annys ◽  
Biadgilgn Demissie ◽  
Amanuel Zenebe Abraha ◽  
Miro Jacob ◽  
Jan Nyssen
Keyword(s):  
Land Cover ◽  
Rift Valley ◽  
Rainfall Variability ◽  
Ethiopian Rift ◽  
Land Cover Changes ◽  
Spatio Temporal

Spatio-temporal analysis and estimation of rainfall variability in and around upper Godavari River basin, India

2019 ◽  
Vol 12 (22) ◽  
Author(s):  
Sainath Aher ◽  
Sambhaji Shinde ◽  
Praveen Gawali ◽  
Pragati Deshmukh ◽  
Lakshmi B. Venkata
Keyword(s):  
River Basin ◽  
Rainfall Variability ◽  
Temporal Analysis ◽  
Godavari River ◽  
Spatio Temporal

Assessing the potential of using telecommunication microwave links in urban drainage modelling

2013 ◽  
Vol 68 (8) ◽  
pp. 1810-1818 ◽  
Author(s):  
M. Fencl ◽  
J. Rieckermann ◽  
M. Schleiss ◽  
D. Stránský ◽  
V. Bareš
Keyword(s):  
Urban Areas ◽  
Rainfall Variability ◽  
Rain Gauge ◽  
Urban Drainage ◽  
Rainfall Runoff ◽  
Urban Catchment ◽  
Flow Prediction ◽  
Spatial Coverage ◽  
Spatio Temporal

The ability to predict the runoff response of an urban catchment to rainfall is crucial for managing drainage systems effectively and controlling discharges from urban areas. In this paper we assess the potential of commercial microwave links (MWL) to capture the spatio-temporal rainfall dynamics and thus improve urban rainfall-runoff modelling. Specifically, we perform numerical experiments with virtual rainfall fields and compare the results of MWL rainfall reconstructions to those of rain gauge (RG) observations. In a case study, we are able to show that MWL networks in urban areas are sufficiently dense to provide good information on spatio-temporal rainfall variability and can thus considerably improve pipe flow prediction, even in small subcatchments. In addition, the better spatial coverage also improves the control of discharges from urban areas. This is especially beneficial for heavy rainfall, which usually has a high spatial variability that cannot be accurately captured by RG point measurements.

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