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오류신고를 진행 하실 데이터 정보를 담은 표입니다. 제목(Main) Agroclimatic Indices Dataset for Characterizing Crop Water Requirements, Dry and Wet Spells, Heatwaves, and Water Balance in Agricultural Regions of Angola 제목(Sub) 저자 Barrios-Perez, Camilo;Sotelo Betancurt, Humberto Steven;Chilambe, Pedro Anglaze;Ramirez-Villegas, Julian; 제공처 HARVARD Dataverse 리포지터리 HARVARD Dataverse
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2023
해외
공개
English
Agroclimatic Indices Dataset for Characterizing Crop Water Requirements, Dry and Wet Spells, Heatwaves, and Water Balance in Agricultural Regions of Angola
Agroclimatic Indices Dataset for Characterizing Crop Water Requirements, Dry and Wet Spells, Heatwaves, and Water Balance in Agricultural Regions of Angola Barrios-Perez, Camilo;Sotelo Betancurt, Humberto Steven;Chilambe, Pedro Anglaze;Ramirez-Villegas, Julian;
This database contains spatial information with a 0.05° grid resolution of specific agroclimatic indices for maize, dry beans, soybeans, and coffee regions in Angola. In total, the database comprises 13 agroclimatic indices for each crop, grouped as follows:
1. Dry Conditions Indices:
• Number of Dry Days
• Number of Dry Spells
• Average Length of Dry Spells
2. Wet Conditions Indices:
• Number of Wet Days
• Number of Wet Spells
• Average Length of Wet Spells
• Total Precipitation
3. Heatwave Indices:
• Number of Hot Days
• Number of Heatwaves
• Maximum Length of Heatwaves
4. Crop Water Requirement Index:
• Potential Evapotranspiration (ETo)
5. Water Balance Index:
• Standardized Precipitation and Evapotranspiration Index (SPEI)
These indices were calculated using historical climatic data for the period 1981 to 2020, considering the typical growth and development periods of each crop of interest, detailed as follows:
• Maize: September - April
• Beans: November - March
• Soybeans: October - April
• Coffee: September - August
Additionally, six El Niño events (1982-1983, 1987-1988, 1991-1992, 1997-1998, 2009-2010, 2015-2016) and six La Niña events (1984-1985, 1988-1989, 1998-1999) were considered to characterize the behavior of each indicator under the influence of different phases of the ENSO phenomenon.
Metodology:Regarding the climatic data used to calculate each of the indices, the following information is provided:
1. Dry and Wet Conditions Indices: Historical daily rainfall data from the Climate Hazards Group InfraRed Precipitation Measurement (CHIRPS) dataset (https://www.chc.ucsb.edu/data) were used.
2. Heatwave Indices: Historical daily maximum temperature data were obtained from the AgERA5 database (https://cds.climate.copernicus.eu/cdsapp#!/dataset/sis-agrometeorological-indicators?tab=overview), and a resampling process was applied to reduce the spatial scale of the original maps from 0.1° to 0.05°.
3. Crop Water Requirement Indices: The Priestley-Taylor equation was used to calculate Potential Evapotranspiration (ETo) due to its simplicity and suitability for tropical conditions. Daily maximum and minimum temperature data, as well as solar radiation, were obtained from the AgERA5 database. A resampling process was also applied to reduce the spatial scale of the original maps from 0.1° to 0.05°.
4. Water Balance Indices: The SPEI indicator calculation was based on daily precipitation data from CHIRPS and ETo calculated using daily maximum and minimum temperature data, as well as solar radiation, from the AgERA5 database. This database provides a valuable tool for understanding and managing agroclimatic aspects in key crop-producing regions in Angola, which can have a significant impact on the country's agriculture and food security.
1. Dry Conditions Indices:
• Number of Dry Days
• Number of Dry Spells
• Average Length of Dry Spells
2. Wet Conditions Indices:
• Number of Wet Days
• Number of Wet Spells
• Average Length of Wet Spells
• Total Precipitation
3. Heatwave Indices:
• Number of Hot Days
• Number of Heatwaves
• Maximum Length of Heatwaves
4. Crop Water Requirement Index:
• Potential Evapotranspiration (ETo)
5. Water Balance Index:
• Standardized Precipitation and Evapotranspiration Index (SPEI)
These indices were calculated using historical climatic data for the period 1981 to 2020, considering the typical growth and development periods of each crop of interest, detailed as follows:
• Maize: September - April
• Beans: November - March
• Soybeans: October - April
• Coffee: September - August
Additionally, six El Niño events (1982-1983, 1987-1988, 1991-1992, 1997-1998, 2009-2010, 2015-2016) and six La Niña events (1984-1985, 1988-1989, 1998-1999) were considered to characterize the behavior of each indicator under the influence of different phases of the ENSO phenomenon.
Metodology:Regarding the climatic data used to calculate each of the indices, the following information is provided:
1. Dry and Wet Conditions Indices: Historical daily rainfall data from the Climate Hazards Group InfraRed Precipitation Measurement (CHIRPS) dataset (https://www.chc.ucsb.edu/data) were used.
2. Heatwave Indices: Historical daily maximum temperature data were obtained from the AgERA5 database (https://cds.climate.copernicus.eu/cdsapp#!/dataset/sis-agrometeorological-indicators?tab=overview), and a resampling process was applied to reduce the spatial scale of the original maps from 0.1° to 0.05°.
3. Crop Water Requirement Indices: The Priestley-Taylor equation was used to calculate Potential Evapotranspiration (ETo) due to its simplicity and suitability for tropical conditions. Daily maximum and minimum temperature data, as well as solar radiation, were obtained from the AgERA5 database. A resampling process was also applied to reduce the spatial scale of the original maps from 0.1° to 0.05°.
4. Water Balance Indices: The SPEI indicator calculation was based on daily precipitation data from CHIRPS and ETo calculated using daily maximum and minimum temperature data, as well as solar radiation, from the AgERA5 database. This database provides a valuable tool for understanding and managing agroclimatic aspects in key crop-producing regions in Angola, which can have a significant impact on the country's agriculture and food security.
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특성 정보
- 주제분류 = Agricultural Sciences;Earth and Environmental Sciences;climate variability;dry spells;Angola;wet spells;Heat waves;water balance;maize;coffee;dry beans;soybeans;ENSO;Americas;Lever3: Climate Action
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