scholarly journals Precipitation extremes and anomalies of the Indian Sundarban 1984-2018

MAUSAM ◽  
2021 ◽  
Vol 72 (4) ◽  
pp. 847-858
Author(s):  
PRIYANKA DAS ◽  
PABITRA BANIK ◽  
KRISHNA CHANDRA RATH
Keyword(s):  
Climatic Variability ◽  
Grid Point ◽  
Critical Evaluation ◽  
Research Unit ◽  
Precipitation Pattern ◽  
Gridded Data ◽  
Precipitation Concentration Index ◽  
Data Variability ◽  
Data Products ◽  
Context Data

Gridded precipitation data products of 0.5º × 0.5º spatial resolution were analysed to understand the climatic variability in a spatial and temporal context. Data reliability of processed gridded data products were examined in the absence of gauge station data observations in the study area. However, the implementations of comparative analysis of the spatial and temporal data products in this study area are missing. The NASA Power Data (NPD) and Climate Research Unit (CRU TS 4.03) Data were scrutinized from 1984-2018. The data products were selected, compared, and interpreted grid wise. Annual and monsoonal precipitation pattern was also studied. Data variability has been analyzed using the Coefficient of Variation (CV), Anomaly, and Precipitation Concentration Index (PCI). The statistical analysis of R2, MAE, RMSE, MAPE and BIAS was performed to quantify the error and differences. Considering the independent grid point, the MAPE and BIAS indicate that only grid 4 performed better than the rest with 12.7% and 17%, respectively. The results regarding the data products illustrate significant differences both in averaged and grid wise context. The NPD shows an increasing trend, whereas CRU represents a decreasing trend from the year 1984-2018. Before the implementation of any processed secondary gridded data products in complex terrain, the critical evaluation and quantification of the magnitude of error is a prerequisite, like the Sundarbans, where the gauge stationed data is unavailable.  

scholarly journals A robust method to identify cyclone tracks from gridded data

2010 ◽  
Vol 4 (1) ◽  
pp. 105-114 ◽  
Author(s):  
F. Kreienkamp ◽  
A. Spekat ◽  
W. Enke
Keyword(s):  
Input Data ◽  
Grid Point ◽  
Storm Track ◽  
Atmospheric Dynamics ◽  
Storm Tracks ◽  
Second Step ◽  
Small Scale ◽  
Gridded Data ◽  
Robust Method ◽  
Space Order

Abstract. A system to derive tracks of barometric minima is presented. It is deliberately using coarse input data in space (order of 2°×2°) and time (6-hourly to daily) as well as information from just one geopotential level. It is argued that the results are, for one robust in the sense of an assumption of the IMILAST Project that the use of as simple as possible metrics should be strived for and for two tailored to the input from reanalyses and GCMs. The methodology presented is a necessary first step towards an automated storm track recognition scheme which will be employed in a second paper to study the future development of atmospheric dynamics in a changing climate. The process towards obtaining storm tracks is two-fold. In its first step cyclone centers are being identified. The performance of this step requires the existence of closed isolines, i.e., a topology in which a grid-point is surrounded by neighbours which all exhibit higher geopotential. The usage of this topology requirement as well as the constraint of coarse data may lead, though, to limitations in identifying centers in geopotential fields with shallow gradients that may occur in the summer months; moreover, some centers may potentially be missed in case of a configuration in which a small scale storm is located at the perimeter of a deep and very large low (a kind of "dent in a crater wall"). The second step of the process strings the identified cyclone centers together in a meaningful way to form tracks. By way of several examples the capability to identify known storm tracks is shown.

scholarly journals Comparison of Various Reanalyses Gridded Data with Observed Data from Meteorological Stations over India

10.29007/c1sf ◽  
2018 ◽  
Author(s):  
Arnab Bandyopadhyay ◽  
Grace Nengzouzam ◽  
W. Rahul Singh ◽  
Nemtinkim Hangsing ◽  
Aditi Bhadra
Keyword(s):  
Observational Data ◽  
General Circulation ◽  
Promising Result ◽  
Meteorological Data ◽  
Circulation Model ◽  
India Meteorological Department ◽  
Gridded Data ◽  
Statistical Parameters ◽  
Data Product ◽  
Data Products

Meteorological data such as precipitation and temperature are important for hydrological modelling. In areas where there is sparse observational data, an alternate means for obtaining information for different impact modelling and monitoring activities is provided by reanalysis products. Evaluating their behaviour is crucial to know their uncertainties. Therefore, we evaluated two reanalyses gridded data products, viz., Coordinated Regional Climate Downscaling Experiment (CORDEX) and National Centers for Environment Predictors and GCM (General Circulation Model) predictor variables (NCEP); two station based gridded data products, viz., Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) and India Meteorological Department (IMD) gridded data; one satellite based gridded data product i.e., Tropical Rainfall Measuring Mission (TRMM); and one merged data product, i.e., Global Precipitation Climatology Project (GPCP). These products were compared with IMD observed station data for 1971 to 2010 to evaluate their behaviour in terms of fitness by using statistical parameters such as NSE, CRM and R2. APHRODITE and TRMM gridded data showed overall good results for precipitation followed by IMD, GPCP, CORDEX and NCEP. APHRODITE also showed good agreement for mean temperature. CORDEX and NCEP gave a promising result for minimum and maximum temperatures with NCEP better than CORDEX.

Topographic and Atmospheric Influences on Precipitation Variability over a Mountainous Watershed

1995 ◽  
Vol 34 (1) ◽  
pp. 68-87 ◽  
Author(s):  
Gregory L. Johnson ◽  
Clayton L. Hanson
Keyword(s):  
General Circulation ◽  
Grid Point ◽  
Geographic Location ◽  
Circulation Model ◽  
Principal Component ◽  
Precipitation Pattern ◽  
Storm Events ◽  
Local Climate ◽  
Radiosonde Station ◽  
Mountainous Watershed

Abstract Using rotated principal component analysis (PCA), unique, orthogonal spatial patterns of daily and monthlyprecipitation on a well-instrumented, mountainous watershed in Idaho are examined for their relationship totopography, geographic location, and atmospheric variability. Precipitation pattern and homogeneous precipitationregion differences between daily and monthly timescales and between winter and summer Seasons were identifiedusing the rotated PCA procedure. In general, monthly data produced regional boundaries more closely alignedwith topography, reflecting the integration of many storm events on monthly timescales. Spatial fields, derivedfrom mapping rotated component loadings at 46 precipitation stations on a 234-kmz watershed, were found tobe highly correlated with topography and geographic location. The eight-year time series of the components forspecific watershed regions were found to be moderately related to linear combinations of meteorological variablesderived from a single radiosonde station approximately 50 km from the waterhed. This would indicate thepotential usefulness of data from a single location, such as a general circulation model grid point, to provideclues about spatial pattern changes and regional precipitation fluctuations even on a small watershed, if sufficientinformation about local climate (i.e., topographic influences) is first established.

scholarly journals Rankings of extreme and widespread dry and wet events in the Iberian Peninsula between 1901–2016

2020 ◽  
Author(s):  
Margarida L. R. Liberato ◽  
Irene Montero ◽  
Célia Gouveia ◽  
Ana Russo ◽  
Alexandre M. Ramos ◽  
...  
Keyword(s):  
Iberian Peninsula ◽  
Time Scales ◽  
Extreme Events ◽  
Potential Evapotranspiration ◽  
Grid Point ◽  
Research Unit ◽  
Climatic Research Unit ◽  
The Impact ◽  
Monteith Equation

Abstract. Extensive, longstanding dry and wet episodes are one of the most frequent climatic extreme events in the Iberian Peninsula. Here, we present a method for ranking regional extremes of persistent, widespread drought and wet events, considering different time scales. The method is based on the multiscalar Standardized Precipitation Evapotranspiration Index (SPEI) gridded dataset for the Iberian Peninsula. SPEI was computed using the Climatic Research Unit (CRU) between 1901 and 2016 using a log-logistic probability distribution function. The Potential Evapotranspiration (PET) was computed through the Penmann-Monteith equation. The ranking classification method is based on the evaluation of the magnitude of an event, which is obtained after considering both the area affected respectively by the dryness or wetness – defined by SPEI values over a certain threshold – and its intensity in each grid point. A sensitivity analysis on the impact of different thresholds to define dry and wet events is performed. A comprehensive dataset of rankings of the most extreme, prolonged, widespread dry and wet periods in the Iberian Peninsula is presented, for aggregated time scales of 6, 12, 18 and 24 months. Results show that in the Iberian Peninsula there is not a region more prone to the occurrence of any of these long-term (dry and/or wet) most extreme events.

scholarly journals Climatic Variability and Estimation of Supplementary Irrigation Water Needs of Selected Food Crops in the Sokoto-Rima River Basin, Nigeria

2019 ◽  
Vol 3 (1) ◽  
pp. 86-104 ◽  
Author(s):  
C. N. Emeribe ◽  
E. T. Ogbomida ◽  
J. O. Enoma-Calus
Keyword(s):  
River Basin ◽  
Irrigation Water ◽  
Potential Evapotranspiration ◽  
Climatic Variability ◽  
Research Unit ◽  
Climatic Research Unit ◽  
Food Crops ◽  
Water Requirements ◽  
Irrigation Project ◽  
Supplementary Irrigation

The study investigated the effects of rainfall and temperature variability on crop water requirements of selected food crops in the Sokoto-Rima River Basin, Northwest of Nigeria. Rainfall and temperature datasets were obtained from the Climatic Research Unit (CRU) TS 3.21 of the University of East Anglia, Norwich, for a period of 70 years (1943-2012). The suitability of CRU datasets were verified by correlating the datasets with measured rainfall data of Yelwa synoptic station, from the Nigerian Meteorological Agency. Selected food crops were used for estimating supplementary irrigation water needs in the River basin. Results of Mann-Kendal, Spearman’s Rho and linear regression tests showed strong evidence of increasing annual temperature and potential evapotranspiration with corresponding decrease in rainfall amounts, especially in the northern parts of the basin which houses big irrigation projects and dams such as the Goronyo Irrigation and the Bakolori Dam and Bakolori Irrigation Project. This will impact on the water availability within the basin, through reduction in surface and ground water supply for ongoing irrigation and other water resources projects. Water requirements for selected crops were modeled to ascertain crop sensitivity to climatic variability which will aid in the design of supplementary irrigation water needs models. Results showed that even in the rainfall months, supplementary irrigation of varying quantity is required to complement rainfall, most especially, in the northeast of the basin. Surprisingly, the month of May which marks commencement of rainfall, recorded the highest water need and this has implication for agriculture yields in the region.

scholarly journals Precipitation anomalies in the Brazilian southern coast related to the SAM and ENSO climate variability modes

RBRH ◽  
2018 ◽  
Vol 23 (0) ◽  
Author(s):  
Venisse Schossler ◽  
Jefferson Cardia Simões ◽  
Francisco Eliseu Aquino ◽  
Denilson Ribeiro Viana
Keyword(s):  
Climate Variability ◽  
Southern Oscillation ◽  
Statistical Significance ◽  
Climatic Variability ◽  
Rio Grande ◽  
Precipitation Pattern ◽  
Rio Grande Do Sul ◽  
Geographical Differences ◽  
South Central ◽  
Precipitation Anomalies

ABSTRACT The precipitation pattern of the State of Rio Grande do Sul (RS) is changing, indicating an increase, although there are long periods of drought. Several studies indicate the influence of climate variability modes on RS precipitation. This work analyzes the influence of the Southern Annular Mode (SAM) and the El Niño - Southern Oscillation (ENSO) on precipitation anomalies (PP) of the Rio Grande do Sul Coastal Plain (RGSCP), dividing it into three regions: south, central and north. Contingency tables were used to correlate the indices, classifying them as neutral, below ou above the mean. To statistical significance we used percentage correctly classified with which the Student’s t was aplied for each region. The PP of the RGSCP and the south coast have correlation with the ENSO and SAM; the central only with SAM. The PP of the north is not correlated to either index. Periods with more than 5 months of PP, SAM and ENSO anomalies were identified. Below average events were majority. The results indicate greater influence of SAM + and La Niña. The trend towards SAM+ and intensification of ENSO, could increase the frequency of droughts in RGSCP. In addition, it was possible to interpret that the geographical differences of the RGSCP can influence the results of precipitation totals. This work contributes to the understanding of the effects of the new trends of climatic variability under regional and geographical aspects.

scholarly journals Are Temperature and Precipitation Extremes Increasing over the U.S. High Plains?

2012 ◽  
Vol 16 (16) ◽  
pp. 1-20 ◽  
Author(s):  
Di Long ◽  
Bridget R. Scanlon ◽  
D. Nelun Fernando ◽  
Lei Meng ◽  
Steven M. Quiring
Keyword(s):  
Climatic Variability ◽  
Standardized Precipitation Index ◽  
Extreme Temperature ◽  
Climate Extremes ◽  
Precipitation Extremes ◽  
Semiarid Region ◽  
High Plains ◽  
Gridded Data ◽  
Temperature And Precipitation ◽  
The U.S

Abstract Large-scale environmental, social, and economic impacts of recent weather and climate extremes are raising questions about whether the frequency and intensity of these extremes have been increasing. Here, the authors evaluate trends in climate extremes during the past half century using the U.S. High Plains as a case study. A total of eight different extreme indices and the standardized precipitation index (SPI) were evaluated using daily maximum and minimum temperature and precipitation data from 207 stations and 0.25° gridded data. The 1958–2010 time period was selected to exclude the 1950s and 2011 droughts. Results show general consistency between the station data and gridded data. The annual extreme temperature range (ETR) decreased significantly (p < 0.05) in ~54% of the High Plains, with a spatial mean rate of −0.7°C decade−1. Decreases in ETR result primarily from increases in annual lowest temperature in ~63% of the stations at a mean rate of ~0.9°C decade−1, whereas increases in annual highest temperature were much less. Approximately 43% of the stations showed increasing warm nights (Tmin90) with a spatial mean rate of 0.5% decade−1. Precipitation intensity generally did not vary significantly in most grid cells and stations. Significant decreasing trends in consecutive dry days (CDD) were restricted to 21% of the stations in the northern High Plains with a spatial mean of −0.8 days decade−1. Areas experiencing severe dry periods (1-month SPI < −1.5) decreased over time from 8% to 4%. The number of dry months (SPI < 0) in each year also decreased. In summary, the ETR is decreasing and low temperatures are increasing. Precipitation extremes are generally not changing in the High Plains; however, high natural climatic variability in this semiarid region makes it difficult to assess climate extremes.

scholarly journals A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901–present

2012 ◽  
Vol 5 (2) ◽  
pp. 921-998 ◽  
Author(s):  
A. Becker ◽  
P. Finger ◽  
A. Meyer-Christoffer ◽  
B. Rudolf ◽  
K. Schamm ◽  
...  
Keyword(s):  
Data Base ◽  
Land Surface ◽  
Data Sets ◽  
Gridded Data ◽  
Surface Precipitation ◽  
Global Precipitation Climatology Centre ◽  
Global Land ◽  
Data Products ◽  
Precipitation Analysis ◽  
Global Precipitation

Abstract. The availability of highly accessible and reliable monthly gridded data sets of the global land-surface precipitation is a need that has already been identified in the mid-80s when there was a complete lack of a globally homogeneous gauge based precipitation analysis. Since 1989 the Global Precipitation Climatology Centre (GPCC) has built up a unique capacity to assemble, quality assure, and analyse rain gauge data gathered from all over the world. The resulting data base has exceeded 200 yr in temporal coverage and has acquired data from more than 85 000 stations world-wide. This paper provides the reference publication for the four globally gridded monthly precipitation products of the GPCC covering a 111-yr analysis period from 1901–present, processed from this data base. As required for a reference publication, the content of the product portfolio, as well as the underlying methodologies to process and interpolate are detailed. Moreover, we provide information on the systematic and statistical errors associated with the data products. Finally, sample applications provide potential users of GPCC data products with suitable advice on capabilities and constraints of the gridded data sets. In doing so, the capabilities to access ENSO and NAO sensitive precipitation regions and to perform trend analysis across the past 110 yr are demonstrated. The four gridded products, i.e. the Climatology V2011 (CLIM), the Full Data Reanalysis (FD) V6, the Monitoring Product (MP) V4, and the First Guess Product (FG) are public available on easy accessible latitude longitude grids encoded in zipped clear text ASCII files for subsequent visualization and download through the GPCC download gate hosted on ftp://ftp.dwd.de/pub/data/gpcc/html/download_gate.html by the Deutscher Wetterdienst (DWD), Offenbach, Germany. Depending on the product four (0.25°, 0.5°, 1.0°, 2.5° for CLIM), three (0.5°, 1.0°, 2.5°, for FD), two (1.0°, 2.5° for MP) or one (1.0° for FG) resolutions are provided, and for each product a DOI reference is provided allowing for public user access to the products. A preliminary description of the scope of a fifth product – the Homogenized Precipitation Analysis (HOMPRA) – is also provided. Its comprehensive description will be handed later in an extra paper upon completion of this data product. DOIs of the gridded datasets examined: doi:10.5676/DWD_GPCC/CLIM_M_V2011_025, doi:10.5676/DWD_GPCC/CLIM_M_V2011_050, doi:10.5676/DWD_GPCC/CLIM_M_V2011_100, doi:10.5676/DWD_GPCC/CLIM_M_V2011_250, doi:10.5676/DWD_GPCC/FD_M_V6_050, doi:10.5676/DWD_GPCC/FD_M_V6_100, doi:10.5676/DWD_GPCC/FD_M_V6_250, doi:10.5676/DWD_GPCC/MP_M_V4_100, doi:10.5676/DWD_GPCC/MP_M_V4_250, doi:10.5676/DWD_GPCC/FG_M_100

scholarly journals A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901–present

2013 ◽  
Vol 5 (1) ◽  
pp. 71-99 ◽  
Author(s):  
A. Becker ◽  
P. Finger ◽  
A. Meyer-Christoffer ◽  
B. Rudolf ◽  
K. Schamm ◽  
...  
Keyword(s):  
Land Surface ◽  
Data Sets ◽  
Monthly Precipitation ◽  
Gridded Data ◽  
Surface Precipitation ◽  
Precipitation Climatology ◽  
Global Precipitation Climatology Centre ◽  
Global Land ◽  
Data Products ◽  
Global Precipitation

Abstract. The availability of highly accessible and reliable monthly gridded data sets of global land-surface precipitation is a need that was already identified in the mid-1980s when there was a complete lack of globally homogeneous gauge-based precipitation analyses. Since 1989, the Global Precipitation Climatology Centre (GPCC) has built up its unique capacity to assemble, quality assure, and analyse rain gauge data gathered from all over the world. The resulting database has exceeded 200 yr in temporal coverage and has acquired data from more than 85 000 stations worldwide. Based on this database, this paper provides the reference publication for the four globally gridded monthly precipitation products of the GPCC, covering a 111-yr analysis period from 1901–present. As required for a reference publication, the content of the product portfolio, as well as the underlying methodologies to process and interpolate are detailed. Moreover, we provide information on the systematic and statistical errors associated with the data products. Finally, sample applications provide potential users of GPCC data products with suitable advice on capabilities and constraints of the gridded data sets. In doing so, the capabilities to access El Niño–Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) sensitive precipitation regions and to perform trend analyses across the past 110 yr are demonstrated. The four gridded products, i.e. the Climatology (CLIM) V2011, the Full Data Reanalysis (FD) V6, the Monitoring Product (MP) V4, and the First Guess Product (FG), are publicly available on easily accessible latitude/longitude grids encoded in zipped clear text ASCII files for subsequent visualization and download through the GPCC download gate hosted on ftp://ftp.dwd.de/pub/data/gpcc/html/download_gate.html by the Deutscher Wetterdienst (DWD), Offenbach, Germany. Depending on the product, four (0.25°, 0.5°, 1.0°, 2.5° for CLIM), three (0.5°, 1.0°, 2.5°, for FD), two (1.0°, 2.5° for MP) or one (1.0° for FG) resolution is provided, and for each product a DOI reference is provided allowing for public user access to the products. A preliminary description of the scope of a fifth product – the Homogenized Precipitation Analysis (HOMPRA) – is also provided. Its comprehensive description will be submitted later in an extra paper upon completion of this data product. DOIs of the gridded data sets examined are as follows: doi:10.5676/DWD_GPCC/CLIM_M_V2011_025, doi:10.5676/DWD_GPCC/CLIM_M_V2011_050, doi:10.5676/DWD_GPCC/CLIM_M_V2011_100, doi:10.5676/DWD_GPCC/CLIM_M_V2011_250, doi:10.5676/DWD_GPCC/FD_M_V6_050, doi:10.5676/DWD_GPCC/FD_M_V6_100, doi:10.5676/DWD_GPCC/FD_M_V6_250, doi:10.5676/DWD_GPCC/MP_M_V4_100, doi:10.5676/DWD_GPCC/MP_M_V4_250, doi:10.5676/DWD_GPCC/FG_M_100.

scholarly journals Assessing Agricultural Vulnerability in India using NDVI Data Products

2014 ◽  
Vol XL-8 ◽  
pp. 39-46 ◽  
Author(s):  
R. Kaushalya ◽  
V. Praveen Kumar ◽  
S. Shubhasmita
Keyword(s):  
Climate Change ◽  
Agricultural Land ◽  
Climatic Variability ◽  
Central India ◽  
Western India ◽  
Resource Base ◽  
Noaa Avhrr ◽  
Agricultural Vulnerability ◽  
Data Products ◽  
Natural Resource Base

Impact of climate change on Indian rainfed agriculture was assessed using temporal NDVI data products from AVHRR and MODIS. Agricultural vulnerability was analysed using CV of Max NDVI from NOAA-AVHRR (15-day, 8 km) and MODIS-TERRA (16-day, 250 m) NDVI data products from 1982–2012. AVHRR dataset was found suitable for estimating regional vulnerability at state and agro-eco-sub-region (AESR) level while MODIS dataset was suitable for drawing district-level strategy for adaptation and mitigation. Methodology was developed to analyse NDVI variations with spatial pattern of rainfall using 10 X 10 girded data and spatially interpolating it to estimate Standard Precipitation Index. Study indicated large variations in vegetation dynamics across India owing to bio-climate and natural resource base. IPCC framework of vulnerability and exposure was used to identify vulnerable region extending from arid western India to semi-arid and dry sub-humid regions in central India and southern peninsula. This is a major agricultural region in the country with sizable human and livestock population with millions of marginal and small farm holdings. Exposure to climatic variability at local and regional levels have national implications and study indicated that over 122 districts extending over 110 mha was vulnerable to climate change that spread across 26 typical AESR in 11 states in India. Of the 74 mha under agriculture in the region, MODIS dataset indicated 47 mha as agriculturally vulnerable while coarser resolution of AVHRR dataset indicated a conservative estimate of 29 mha. First ever estimates of agricultural vulnerability for India indicates 20.4 to 33.1 % agricultural land under risk from climate change.

Sign in / Sign up

Export Citation Format

Share Document