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 Modeling Rainfall Variability over Urban Areas: A Case Study for Kuwait

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Jaber Almedeij
Keyword(s):  
Urban Areas ◽  
Rainfall Variability ◽  
Rainfall Data ◽  
Point Estimate ◽  
Spatial And Temporal Variability ◽  
Time Duration ◽  
Reliable Model ◽  
Monthly Total ◽  
Seasonal Basis

This study examines the spatial and temporal variability of monthly total rainfall data obtained from weather stations located in the urban areas of Kuwait. The rainfall data are analyzed by considering statistics on a seasonal basis and by means of periodogram technique to reveal the periods responsible for the variable pattern. The results demonstrate similarity implying that a point estimate of rainfall data can be considered spatially representative over the urban areas of Kuwait. A sinusoidal model triggering the influence of the detected periods is developed accordingly for the time duration from January 1965 to December 2009. The model is capable of describing the rainfall data with some discrepancies between the actual and calculated values resulting from hidden periods that have not been taken into account. This finding suggests that the ability to construct a more reliable model would require a wider range of historical data to detect the other periods affecting the rainfall pattern.

scholarly journals Climatologia da pluviometria do município de Teresina, Piauí, Brasil

2016 ◽  
Vol 11 (4) ◽  
pp. 135
Author(s):  
Hudson Ellen Alencar Menezes ◽  
Raimundo Mainar de Medeiros ◽  
José Lucas Guilherme Santos
Keyword(s):  
Water Resources ◽  
Rainfall Variability ◽  
Intertropical Convergence Zone ◽  
Atmospheric Dynamics ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Convergence Zone ◽  
Northeast Brazil ◽  
Urban Structures ◽  
Urbanized Areas

<p>As variações nas precipitações refletem claramente a dinâmica atmosférica da região, marcada pela intensa variabilidade, onde se observa a atuação da Zona de Convergência Intertropical (ZCIT) com sua atuação entre os meses de janeiro a março, sendo esse período mais chuvoso. As variabilidades espaço temporal no comportamento das chuvas tem sido analisadas e diagnosticadas por vários autores no Nordeste do Brasil (NEB), portanto objetivou-se diagnosticar a variabilidade dos índices pluviométricos em Teresina no Estado do Piauí no período de 1913 a 2010. A análise do comportamento da precipitação nas cidades de grande e médio porte é de extrema importância para o gerenciamento dos recursos hídricos, uma vez que se trata de áreas densamente urbanizadas. Muitas vezes, sem uma estruturação urbana adequada, estas cidades se encaixam perfeitamente nesse contexto. Foram utilizados dados mensais observados e anuais de precipitação pluviométrica no período de 1913 a 2010, com 97 anos de observações. Os resultados mostraram a recorrência de valores máximos de precipitação anual dentro de um intervalo de 18, 11 e 8 anos. Na análise dos desvios-padrões, os resultados mostraram predominância dos desvios negativos em relação aos desvios positivos.</p><p align="center"><strong><em>Climatology of rainfall in the Teresina city, Piauí state, Brazil</em></strong></p><p>Variations in precipitation clearly reflect the atmospheric dynamics of the region, marked by intense variability, where we observe the performance of the Intertropical Convergence Zone (ITCZ) with his performance in the months of January-March, this being more rain tem period. The timeline of rainfall variability in behavior has been analyzed and diagnosed by several authors in Northeast Brazil (NEB), so let's study this variability between the periods 1913 to 2010 of Teresina city.  The behavior of rainfall in cities large and medium sized is of utmost importance to the managerial of water resources, since it is densely urbanized areas. Often without adequate urban structures these cities fit perfectly in this context. We used observed monthly and annual rainfall data for the period 1913-2010, 97 years of observations. The results showed recurrence of maximum values of annual precipitation an interval of 18, 11 and 8 years. In the analysis of standard deviations, the results showed a predominance of negative deviations from the positive deviations.<strong></strong></p><p align="center"><strong><em><br /></em></strong></p>

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 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 Identification of a Representative Stationary Period for Rainfall Variability Description in the Sudano-Sahelian Zone of West Africa during the 1901–2018 Period

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 716
Author(s):  
Boubacar Ibrahim ◽  
Yahaya Nazoumou ◽  
Tazen Fowe ◽  
Moussa Sidibe ◽  
Boubacar Barry ◽  
...  
Keyword(s):  
West Africa ◽  
Rainfall Variability ◽  
Baseline Period ◽  
Rainfall Amount ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
Variability Analysis ◽  
The Mean ◽  
The Difference ◽  
Stationary Period

Many studies have been undertaken on climate variability in West Africa since the drastic drought of 1970s. These studies rely in many cases on different baseline periods chosen with regard to the reference periods defined by the World Meteorological Organization. A method is developed in this study to determine a stationary baseline period for rainfall variability analysis. The method is based on an application of three statistic tests (on deviation and trend) and a test of shifts detection in rainfall time series. The application of this method on six different gridded rainfall data and observations from 1901 to 2018 shows that the 1917–1946 period is the longest stationary period. An assessment of the significance of the difference between the mean annual rainfall amount during this baseline period and the annual rainfall amount during the other years shows that the “Normal” annual rainfall amount is defined by an interval delineated by ±the standard deviation (STD). With regard to this interval, a very wet/dry year is defined with a surplus/gap over/below the STD. Overall the 1901–2018 period, the 1950–1970 period presents the most important number of significant wet years and the 1971–1990 period presents the most important number of significant dry years.

scholarly journals Automated convective and stratiform precipitation estimation in a small mountainous catchment using X-band radar data in Central Spain

2016 ◽  
Vol 19 (2) ◽  
pp. 315-330 ◽  
Author(s):  
Carolina Guardiola-Albert ◽  
Carlos Rivero-Honegger ◽  
Robert Monjo ◽  
Andrés Díez-Herrero ◽  
Carlos Yagüe ◽  
...  
Keyword(s):  
Rainfall Variability ◽  
Radar Data ◽  
Rain Gauge ◽  
Spatial And Temporal Variability ◽  
Central Spain ◽  
Small Catchment ◽  
Mountainous Catchment ◽  
X Band ◽  
Precipitation Estimation ◽  
Spatio Temporal

For the purposes of weather nowcasting, flood risk monitoring and water resources assessment, it is often difficult to achieve a reliable spatio-temporal representation of rainfall due to a low rain gauge network density. However, quantitative precipitation estimation (QPE) has acquired new prospects with the introduction of weather radars, thanks to their higher spatio-temporal resolution. Although a wide number of QPE algorithms are available for using C-band radar data, only a few studies have employed X-band radar. In this study the microscale rainfall variability in a small catchment is automatically measured using short-range X-band radar variograms and classifying precipitation into convective and stratiform types with a recently published index. The aim is to apply a straightforward geostatistical algorithm, named ordinary kriging of radar errors (OKRE), to integrate X-band radar and rain gauge measurements in a mountainous catchment (15 km2) in central Spain. As expected, convective events presented higher estimation errors due to their complex spatial and temporal variability. Despite this fact, errors are sufficiently small and results are reliable rainfall estimations. The two main contributions of this work are the adaptation of the OKRE method to small spatial scales and its application automatically differentiating between convective and stratiform events.

scholarly journals Spatiotemporal Rainfall Distribution of Soan River Basin, Pothwar Region, Pakistan

2021 ◽  
Vol 2021 ◽  
pp. 1-24
Author(s):  
Fiaz Hussain ◽  
Ghulam Nabi ◽  
Ray-Shyan Wu
Keyword(s):  
River Basin ◽  
Water Resource Management ◽  
Monsoon Season ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Mountainous Areas ◽  
Distribution Maps ◽  
Annual Basis ◽  
Rational Management ◽  
Rainfall Patterns

This study evaluates the spatiotemporal rainfall variability over the semimountainous Soan River Basin (SRB) of sub-Himalayan Pothwar region, Pakistan. The temporal rainfall trend analysis of sixteen rain gauges was performed on annual basis with long-term (1981–2016) data. The results depicted that there is substantial year-to-year and season-to-season variability in rainfall patterns, and rainfall patterns are generally erratic in nature. The results highlight that most of the highland rainfall stations showed decreasing trends on annual basis. The central and lowland stations of the study area recorded an increasing trend of rainfall except for Talagang station. The average annual rainfall of the study area ranges between 492 mm and 1710 mm in lowland and high-altitude areas, respectively. Of the whole year’s rainfall, about 70 to 75% fall during the monsoon season. The rainfall spatial distribution maps obtained using the inverse distance weighting (IDW) method, through the GIS software, revealed the major rainfall range within the study area. There is a lack of water during postmonsoon months (November–February) and great differences in rainfall amounts between the mountainous areas and the lowlands. There is a need for the rational management of mountainous areas using mini and check dams to increase water production and stream regulation for lowland areas water availability. The spatiotemporal rainfall variability is crucial for better water resource management schemes in the study area of Pothwar region, Pakistan.

scholarly journals Taluka Wise Study of Rainfall Pattern in Nanded District of Marthwada Region (Maharashtra) Using Rainfall Data

2021 ◽  
Vol 10 (9) ◽  
pp. 333-350
Author(s):  
Ramesh Bethala B. V. Asewar ◽  
M. S. Peneke K. K. Dakhore ◽  
M. G. Jadhav A. M. Khobragade
Keyword(s):  
Crop Production ◽  
Rainfall Variability ◽  
Winter Season ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Monsoon Period ◽  
Annual Basis ◽  
Rainy Days ◽  
Onset Of Monsoon

About 60 per cent of the total cultivable area of the country is rainfed. However, prolonged dry periods affect the final crop production. Monsoon is an important season for water supplies, from surface reservoir. Uneven distribution of rainfall, affect the agricultural production remarkably. The daily rainfall data was collected for each taluka of Nanded district for the period of 20 years (1998-2017) and it was to be summed up on meteorological weekly, monthly, seasonally, annual basis for each taluka of Nanded district basis for the study of rainfall characterization. The results indicated that weekly mean annual basis total rainfall was ranged between 720.0 mm in Deglur and 1009.9 mm in Mahur. The weekly highest rainfall on annual basis was recorded in Himayat Nagar (53.7 mm) in the 30th MW amongst all the taluka considering monsoon period (23 to 42 MW). The monthly mean rainfall indicated that the lowest and highest monthly mean rainfall amongst all the taluka was observed in Nanded, Kandhar, Loha, Hadgaon, Bhokar, Kinwat, Mahur, Dharmabad, Ardhapur, Naigaon talukas (0.0 mm) in the December month and in the Mahur taluka (283.1 mm) in July month. The seasonal distribution of Nanded district was obtained in winter season (6.1 mm), in summer (15.5 mm), in monsoon (578.3 mm), in post monsoon (216.6 mm). The annual rainfall data is statistical analyzed for Nanded district and within the year and taluka to taluka ranged C.V. (%) were between 25.0 to 46.9 %. The data of taluka-wise annual normal of weather parameter (i.e. rainfall and rainy days) calculated. Here, the results indicated that the onset of monsoon was observed in 23th MW and withdrawal in 43rd MW in Nanded district. It showed that average rainfall of Nanded district is 816.4 mm with 45.0 rainy days per year. The results clearly indicated the onset of monsoon in 23th MW and withdrawal of monsoon in 43rd MW for the Nanded district should be considered. The statistical analysis for rainfall variability was worked out and it was intra-annual as well as intra-taluka variation in Nanded district. It was ranged between 19.0 to 51.0 per cent with annual mean 45.0 rainy days per year.

Spatial Variability of the Hurst Exponent for the Daily Scale Rainfall Series in the State of Zacatecas, Mexico

2013 ◽  
Vol 52 (12) ◽  
pp. 2771-2780 ◽  
Author(s):  
M. A. Velásquez Valle ◽  
G. Medina García ◽  
Ignacio Sánchez Cohen ◽  
L. Klaudia Oleschko ◽  
J. A. Ruiz Corral ◽  
...  
Keyword(s):  
Time Series ◽  
Hurst Exponent ◽  
Fractal Theory ◽  
Daily Rainfall ◽  
The State ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
Wavelet Techniques ◽  
Hurst Exponents

AbstractThe structural pattern of rainfall data exhibits random fluctuations over time and space. Utilizing concepts of fractal theory, it has been possible to identify characteristics of rainfall data beyond simple statistical indicators of their randomness. The objective of this research was to identify the spatial variation of the Hurst exponent, extracted through standard wavelet techniques from time series of daily rainfall data in the state of Zacatecas, Mexico. The Hurst exponent was extracted for 26 locations using the reference techniques for auto-affine traces—in particular, the wavelets method. Results have shown that the Hurst exponents of rainfall time series are negatively influenced by altitude; thus, stations located at higher altitudes were characterized by Hurst exponents indicating more nonpersistent behavior. The trends among geographical variables (west longitude and latitude) and climatic parameters (annual rainfall and number of rainy days) and their relationship with the Hurst exponent were also analyzed.

scholarly journals The Impact of Work Characteristics on Social Distancing: Implications at the Time of COVID-19

2021 ◽  
Vol 18 (10) ◽  
pp. 5074
Author(s):  
Keisuke Kokubun ◽  
Yoshinori Yamakawa
Keyword(s):  
Information Processing ◽  
Multiple Regression ◽  
Explanatory Power ◽  
Work Conditions ◽  
Multiple Regression Model ◽  
Social Characteristics ◽  
Work Characteristics ◽  
Social Distancing ◽  
Using Data ◽  
The Impact

The coronavirus disease (COVID-19) continues to spread globally. While social distancing has attracted attention as a measure to prevent the spread of infection, some occupations find it difficult to implement. Therefore, this study aims to investigate the relationship between work characteristics and social distancing using data available on O*NET, an occupational information site. A total of eight factors were extracted by performing an exploratory factor analysis: work conditions, supervisory work, information processing, response to aggression, specialization, autonomy, interaction outside the organization, and interdependence. A multiple regression analysis showed that interdependence, response to aggression, and interaction outside the organization, which are categorized as ”social characteristics,” and information processing and specialization, which are categorized as “knowledge characteristics,” were associated with physical proximity. Furthermore, we added customer, which represents contact with the customer, and remote working, which represents a small amount of outdoor activity, to our multiple regression model, and confirmed that they increased the explanatory power of the model. This suggests that those who work under interdependence, face aggression, and engage in outside activities, and/or have frequent contact with customers, little interaction outside the organization, and little information processing will have the most difficulty in maintaining social distancing.

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