scholarly journals Seasonal features of the spatial distribution of rainfall in pre-partitioned India

MAUSAM ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 47-56
Author(s):  
K. L. SINHA
Keyword(s):  
Spatial Distribution ◽  
India Meteorological Department ◽  
Rainfall Distribution ◽  
Common Features ◽  
Four Seasons ◽  
Rainy Days

The spatial distribution of rainfall in accordance with the practice prevalent in the India Meteorological Department, viz., "few falls", "local" and "widespread" during the four seasons and the whole in the different meteorological subdivisions of the pre-partitioned India have been studied with a view, to find any common features that may exist between the three types of rainfall distribution. Distribution of total number of rainy days in the various meteorological subdivisions during the four seasons and the year have been discussed.

scholarly journals Rainfall distribution over Delhi State during monsoon

MAUSAM ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 57-66
Author(s):  
D. A. MOOLEY
Keyword(s):  
Spatial Distribution ◽  
Heavy Rainfall ◽  
Extreme Values ◽  
Monsoon Season ◽  
The State ◽  
Rainfall Distribution ◽  
Mean Values ◽  
The Mean ◽  
Rainy Days

Based on the data for the period 1939-1954, the mean values of rainfall and number of rainy days during the, monsoon season at the various raingauge stations as well as the extreme values of these have been given; spatial distribution of heavy, rainfall over the State and the incidence of heavy rainfall at the various location have been studied. From a study of the synoptic charts on days prior to the days on which local heavy rainfall over was reported, an attempt has been made to indicate the topical synoptic situations which usually lead to local heavy rainfall over Delhi State during the next 24hours.Typical situation ‘have been illustrated by charts.  

scholarly journals Some hydrometeorological studies over Teesta basin in north Bengal

MAUSAM ◽  
2021 ◽  
Vol 42 (4) ◽  
pp. 385-392
Author(s):  
S. K. PRASAD ◽  
A. K. DAS ◽  
I. SENGUPTA
Keyword(s):  
Spatial Distribution ◽  
Extreme Rainfall ◽  
Monthly Rainfall ◽  
Rainfall Distribution ◽  
Precipitation Depth ◽  
Areal Precipitation ◽  
Rainy Days ◽  
North Bengal

Based on data of 40 rainfall stations located within and in the neighbourhood of Teesta basin in north Bengal for period ranging between 7 & 23 years, hydrometeorological informations of the spatial distribution of monthly rainfall, umber of rainy days and extreme rainfall distribution over Teesta basin have been determined and presented on basin maps for the months of May to October.  The average monthly areal precipitation depth as wi1l as extreme areal precipitation depth for a day have been discussed for 6 sectors of the basin. The pentads rainfall for 22 selected stations in the catchment during May to October have also been evaluated and discussed.

scholarly journals Development of 1961-1990 monthly surface climatology of India and patterns of differences of some meteorological parameters with respect to the 1951-1980 climatology

MAUSAM ◽  
2022 ◽  
Vol 63 (3) ◽  
pp. 377-390
Author(s):  
A.K. JASWAL ◽  
S.R. BHAMBAK ◽  
M.K. GUJAR ◽  
S.H. MOHITE ◽  
S. ANANTHARAMAN ◽  
...  
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Spatial Patterns ◽  
Large Scale ◽  
India Meteorological Department ◽  
Cloud Amount ◽  
Climatic Conditions ◽  
Maximum Temperature ◽  
Annual Means ◽  
Rainy Days

Climate normals are used to describe the average climatic conditions of a particular place and are computed by National Meteorological Services of all countries. The World Meteorological Organization (WMO) recommends that all countries prepare climate normals for the 30-year periods ending in 1930, 1960, 1990 and so on, for which the WMO World Climate Normals are published. Recently, Climatological Normals for the period 1961-1990 have been prepared by India Meteorological Department (IMD) which will change the baseline of comparison from 1951-1980. In this paper, preparation of the 30-year Climatological Normals of India for the period 1961 to 1990 and spatial patterns of differences of annual means of temperatures, relative humidity, clouds, rainfall and wind speed from the previous normals (1951-1980) are documented.The changes from earlier climatological normals indicate increase in annual means of maximum temperature, relative humidity and decrease in annual means of minimum temperature, cloud amount, rainfall, rainy days and wind speed over large parts of the country during 1961-1990. The spatial patterns of changes in dry bulb temperatures and relative humidity are complementary over most parts of the country. Compared with 1951-1980 climatology, there are large scale decreases in annual mean rainfall, rainy days and wind speed over most parts of the country during 1961-1990. The decrease in wind speed may be partly due to changes in exposure conditions of observatories due to urbanization.

scholarly journals The Precipitation Variations in the Qinghai-Xizang (Tibetan) Plateau during 1961-2015

2017 ◽  
Author(s):  
Guoning Wan ◽  
Meixue Yang ◽  
Zhaochen Liu ◽  
Xuejia Wang ◽  
Xiaowen Liang
Keyword(s):  
Spatial Distribution ◽  
Tibetan Plateau ◽  
Precipitation Variability ◽  
Annual Precipitation ◽  
The Tibetan Plateau ◽  
Four Seasons ◽  
Winter Half ◽  
Summer Half ◽  
Surrounding Areas ◽  
Autumn And Winter

The Tibetan Plateau(TP) is known as ‘the water tower of Asian’, its precipitation variation play an important role in the eco-hydrological processes and water resources regimes. based on the monthly mean precipitation data of 65 meteorological stations over the Tibetan Plateau and the surrounding areas from 1961-2015,variations, trends and temporal-spatial distribution were analyzed, furthermore, the possible reasons were also discussed preliminarily. The main results are summarized as follows: the annual mean precipitation in the TP is 465.54mm during 1961-2015, among four seasons, the precipitation in summer accounts for 60.1% of the annual precipitation, the precipitation in summer half year (May.- Oct.) accounts for 91.0% while that in winter half year (Nov.- Apr.) only accounts for 9.0%; During 1961-2015, the annual precipitation variability is 0.45mm/a and the seasonal precipitation variability is 0.31mm/a, 0.13mm/a, -0.04mm/a and 0.04mm/a in spring, summer, autumn and winter respectively on the TP; The spatial distribution of precipitation can be summarized as decreasing from southeast to northwest in the TP, the trend of precipitation is decreasing with the increase of altitude, but the correlation is not significant. The rising of air temperature and land cover changes may cause the precipitation by changing the hydrologic cycle and energy budget, furthermore, different pattern of atmospheric circulation can also influence on precipitation variability in different regions.

scholarly journals The assessment of annual rainfall field by applying different interpolation methods in the state of Rio Grande do Sul, Brazil

2021 ◽  
Vol 3 (7) ◽  
Author(s):  
Denis Rafael Silveira Ananias ◽  
Gilberto Rodrigues Liska ◽  
Luiz Alberto Beijo ◽  
Geraldo José Rodrigues Liska ◽  
Fortunato Silva de Menezes
Keyword(s):  
Spatial Distribution ◽  
Mean Squared Error ◽  
Rio Grande ◽  
The State ◽  
Annual Rainfall ◽  
Rio Grande Do Sul ◽  
Rainfall Distribution ◽  
Interpolation Methods ◽  
Squared Error ◽  
Rainfall Spatial Distribution

AbstractAn accurate analysis of spatial rainfall distribution is of great importance for managing watershed water resources, in addition to giving support to meteorological studies and agricultural planning. This work compares the performance of two interpolation methods: Inverse distance weighted (IDW) and Kriging, in the analysis of annual rainfall spatial distribution. We use annual rainfall data for the state of Rio Grande do Sul (Brazil) from 1961 to 2017. To determine which proportion of the sample results in more accurate rainfall distribution maps, we use a certain amount of points close to the estimated point. We use mean squared error (MSE), coefficient of determination (R2), root mean squared error (RMSE) and modified Willmott's concordance index (md). We conduct random fields simulations study, and the performance of the geostatistics and classic methods for the exposed case was evaluated in terms of precision and accuracy obtained by Monte Carlo simulation to support the results. The results indicate that the co-ordinary Kriging interpolator showed better goodness of fit, assuming altitude as a covariate. We concluded that the geostatistical method of Kriging using nine closer points (50% of nearest neighbors) was the one that better represented annual rainfall spatial distribution in the state of Rio Grande do Sul.

Trend and spatial distribution of rainfall & rainy days over Andaman & Nicobar Islands

2012 ◽  
Vol 63 (2) ◽  
pp. 575-587 ◽  
Author(s):  
Naresh Kumar ◽  
B. P. Yadav ◽  
Ajit Tyagi ◽  
A. K. Jaswal
Keyword(s):  
Spatial Distribution ◽  
Nicobar Islands ◽  
Rainy Days

scholarly journals Evaluation of TRMM Precipitation Dataset over Himalayan Catchment: The Upper Ganga Basin, India

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 613 ◽  
Author(s):  
Anoop Shukla ◽  
Chandra Ojha ◽  
Rajendra Singh ◽  
Lalit Pal ◽  
Dafang Fu
Keyword(s):  
Spatial Distribution ◽  
Lake Victoria ◽  
Monsoon Season ◽  
Winter Season ◽  
India Meteorological Department ◽  
Statistical Parameters ◽  
Ganga Basin ◽  
Dual Nature ◽  
Post Monsoon ◽  
Trmm Precipitation

Satellite based rainfall estimation techniques have emerged as a potential alternative to ground based rainfall measurements. The Tropical Rainfall Measuring Mission (TRMM) precipitation, in particular, has been used in various climate and hydrology based studies around the world. While having wide possibilities, TRMM rainfall estimates are found to be inconsistent with the ground based rainfall measurements at various locations such as the southwest coast and Himalayan region of India, northeast parts of USA, Lake Victoria in Africa, La Plata basin in South America, etc. In this study, the applicability of TRMM estimates is evaluated over the Upper Ganga Basin (Himalayan catchment) by comparing against gauge-based India Meteorological Department (IMD) gridded precipitation records. Apart from temporal evaluation, the ability of TRMM in capturing spatial distribution is also examined using three statistical parameters namely correlation coefficient (r), mean absolute error (MAE) and relative bias (RBIAS). In the results, the dual nature of bias is evident in TRMM precipitation with rainfall magnitude falling in the range from 100 to 370 mm representing positive bias, whereas, rainfall magnitude above 400 mm, approximately, representing negative bias. The Quantile Mapping (QM) approach has been used to correct the TRMM dataset from these biases. The raw TRMM precipitation is found to be fairly correlated with IMD rainfall for post-monsoon and winter season with R2 values of 0.65 and 0.57, respectively. The R2 value of 0.41 is obtained for the monsoon season, whereas least correlation is found for the pre-monsoon season with an R2 value of 0.24. Moreover, spatial distribution of rainfall during post-monsoon and winter season is captured adequately; however, the limited efficiency of TRMM is reflected for pre-monsoon and monsoon season. Bias correction has satisfactorily enhanced the spatial distribution of rainfall obtained from TRMM for almost all the seasons except for monsoon. Overall, the corrected TRMM precipitation dataset can be used for various climate analyses and hydrological water balance based studies in the Himalayan river basins.

scholarly journals Influence of Radar and Gauge Rainfall Data Sources on the Analysis of Spatial Distribution of Traffic Accidents and Rainfall Events

2020 ◽  
Vol 10 (20) ◽  
pp. 7327
Author(s):  
Seong-Sim Yoon ◽  
Un Ji ◽  
Inhyeok Bae
Keyword(s):  
Spatial Distribution ◽  
Traffic Accidents ◽  
Reference Value ◽  
Radar Data ◽  
Rainfall Data ◽  
Assessment Tools ◽  
Severe Injury ◽  
Rainfall Distribution ◽  
Rainfall Events ◽  
Study Results

The records of 24,797 traffic accidents (9039 involving fatalities or severe injury) during rainy conditions from 2007 to 2017 in Seoul, South Korea, were used to analyze the spatial distribution of the traffic accidents and rainfall events based on radar and gauge rainfall data. According to the spatial correspondence analysis between rainfall distribution and accident locations for localized and stratiform rain events, radar data in a two-dimensional grid (250 by 250 m) of 10 min temporal resolution benefited the localized rainfall distribution concerning the accident location. The relative accident rate (RAR) from radar data, which was used as a quantitative reference value for the effect of rainfall on traffic accidents, was about 18% higher than that from gauge rainfall. The radar data more clearly classified the number of traffic accidents during rainy conditions because its spatial distribution was more precise for all accidents. In addition, the RAR estimation of accidents involving fatalities and severe injury during rainfall could provide information on the district in which traffic accidents increase due to rainfall. The study results support the adoption of radar-derived rainfall data to analyze the influence of rainfall on accidents and the development of more accurate risk-assessment tools for drivers and planners.

scholarly journals Statistical analysis of monsoon rainfall distribution over West Bengal, India

MAUSAM ◽  
2021 ◽  
Vol 61 (4) ◽  
pp. 487-498
Author(s):  
AVIK GHOSH DASTIDAR ◽  
SARBARI GHOSH ◽  
U. K. DE ◽  
S. K. GHOSH
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
West Bengal ◽  
Monsoon Rainfall ◽  
Daily Rainfall ◽  
India Meteorological Department ◽  
Seasonal Rainfall ◽  
Rainfall Distribution ◽  
Rainfall Characteristics ◽  
Plain Region

Seasonal, monthly and daily rainfall characteristics of meteorological sub-divisions of Sub Himalayan West Bengal (SHWB) and Gangetic West Bengal (GWB) have been studied using rainfall data of 23 stations of India Meteorological Department (IMD) over the state of West Bengal. The two subdivisions have distinctive characteristics, though two stations lying in the plain region of SHWB have behaviour more alike the stations of GWB.  Krishnagar is a station with least seasonal rainfall in the entire state. Kurtosis and Skewness of the seasonal rainfall distribution have been studied and found that, for most of the stations they lie within reasonable limits. From the time series analysis, it is found that the seasonal rainfall has no trend.     

scholarly journals Some aspects of daily rainfall distribution over a high range river basin in central Kerala

MAUSAM ◽  
2021 ◽  
Vol 48 (1) ◽  
pp. 71-76
Author(s):  
V. JAYASREE ◽  
K.G. ANIL KUMAR
Keyword(s):  
River Basin ◽  
Frequency Distribution ◽  
Coefficient Of Variation ◽  
Daily Rainfall ◽  
Seasonal Rainfall ◽  
Total Rainfall ◽  
Rainfall Distribution ◽  
Low Intensity ◽  
Rainy Days ◽  
High Range

ABSTRACT. The daily rainfall distribution of twelve stations in the Chalakudy river basin of central Kerala is studied. Normalised rainfall curve (NRC) is constructed and various parameters of the daily rainfall distribution are derived. The number of rainy days and mean rain intensities at each 10% rain amounts are calculated from the NRC. It has been found that the coefficient of variation (CY) is the most important parameter of the daily rainfall distribution which determines the shape of NRC. Frequency distribution of CY values reveals that the CY is highest in the range of 100-120%. Rainfall contributions by non-rainy days and significant rainfall days are calculated. About half of the seasonal rainfall which contributes 80% of the total rainfall are of low intensity. However, the remaining 20% due to higher intensity rainfall are of considerable significance for floods, erosion, etc.    

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