Stars4Water
climatologyMeteorologyAtmosphere
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Soil Moisture data (version 08.1) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets alongside ancillary data products. The ACTIVE and PASSIVE products have been created by fusing satellite scatterometer and radiometer soil moisture products respectively. In the case of the ACTIVE product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the PASSIVE product from the satellite instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP. The COMBINED product is generated from the Level 2 active and passive instruments. The homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the PASSIVE and COMBINED products covering the period (yyyy-mm-dd) 1978-11-01 to 2022-12-31 and the ACTIVE product covering 1991-08-05 to 2022-12-31. The soil moisture data for the PASSIVE and the COMBINED product are provided in volumetric units [m3 m-3], while the ACTIVE soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Additional documentation and information relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product User Guide. The data set should be cited using all of the following references: 1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019 2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001 3. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., "Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record," in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896.
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The FGGD CV of LGP map is a global raster datalayer with a resolution of 5 arc-minutes. Each pixel contains an average coefficient of variation of LGP for the pixel area over the period 1901-1996. The data are from FAO and IIASA, 2000, Global agro-ecological zones, as reported in FAO and IIASA, 2007, Mapping biophysical factors that influence agricultural production and rural vulnerability, by H. von Velthuizen et al.
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Derived from the Global Agro-Ecological Zones Study, Food and Agriculture Organization of the United Nations (FAO), Land and Water Development Division (AGL) with the collaboration of the International Institute for Applied Systems Analysis (IIASA), 2000. Data averaged over a period of 37 years. Raster data-set has been exported as ASCII raster file type.
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Grid with average Wet Day Frequency (rain days per month) for the period 1961-1990. This dataset is constructed from observations, backed with synthetic data derived from precipitation. Source: New, M., Lister, D., Hulme, M. and Makin, I., 2002: A high-resolution data set of surface climate over global land areas. Climate Research 21:1-25
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The Food and Agriculture Organization of the United Nations (FAO) with the collaboration of the International Institute for Applied Systems Analysis (IIASA), has developed a system that enables rational land-use planning on the basis of an inventory of land resources and evaluation of biophysical limitations and potentials. This is referred to as the Agro-ecological Zones (AEZ) methodology.
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Grid with estimated precipitation per month with a spatial resolution of 10 arc minutes. This dataset has been constructed from 27 075 stations with 1961-1990 climatological normals. The dataset consists of 12 ASCII-grids with mean monthly data in mm/day * 10, and one ASCII-grid with yearly data in mm/year. In addition, 12 ASCII-grid with monthly values at 5 arc minutes resolution are made available as input data for a global water balance model (GlobWat).
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The Food and Agriculture Organization of the United Nations (FAO) with the collaboration of the International Institute for Applied Systems Analysis (IIASA), has developed a system that enables rational land-use planning on the basis of an inventory of land resources and evaluation of biophysical limitations and potentials. This is referred to as the Agro-ecological Zones (AEZ) methodology.
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Grid with estimated yearly reference evapotranspiration with a spatial resolution of 10 arc minutes. The dataset contains average values for global land areas, excluding Antarctica, for the period 1961-1990. The dataset has been prepared according to the FAO Penman - Monteith method with limited climatic data as described in FAO Irrigation and Drainage Paper 56. The dataset consists one ASCII-grid with yearly data in mm/year. ASCII-grids with mean monthly data in mm/day * 10 are also available as described in the associated resources of this metadata.
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As part of the the World Bank's review of its rural development strategy, the Bank sought the assistance of the Food and Agriculture Organization of the United Nations (FAO) in evaluating how farming systems might change and adapt over the next thirty years. Amongst other objectives, the World Bank asked FAO to provide guidance on priorities for investment in food security, poverty reduction, and economic growth, and in particular to identify promising approaches and technologies that will contribute to these goals. The results of the study are summarized in a set of seven documents, comprising six regional reports and the global overview contained in this volume. This document, which synthesises the results of the six regional analyses as well as discussing global trends, cross-cutting issues and possible implementation modalities, presents an overview of the complete study. This document is supplemented by two case study reports of development issues of importance to farming systems globally.
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The Food and Agriculture Organization of the United Nations (FAO) with the collaboration of the International Institute for Applied Systems Analysis (IIASA), has developed a system that enables rational land-use planning on the basis of an inventory of land resources and evaluation of biophysical limitations and potentials. This is referred to as the Agro-ecological Zones (AEZ) methodology.