30 Arc-Second Historical and Future Scenario Climate Surfaces for Western Honduras

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Llanos Herrera, Lizeth; Navarro Racines, Carlos E.; Valencia, Jefferson; Monserrate, Fredy; Quintero, Marcela, 2017, "30 Arc-Second Historical and Future Scenario Climate Surfaces for Western Honduras", https://doi.org/10.7910/DVN/YR7QYP, Harvard Dataverse, V1

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Description	In order to characterize the historical climate for the Western Honduras region, it was developed monthly surfaces by years through spatial interpolation and available records of weather stations. The interpolated surfaces were generated at 1-km of spatial resolution (30 arc-seconds) for monthly precipitation (1981-2015), and minimum and maximum temperature (1990-2014). It was followed the method described by Hijmans et al. (2005), using data from: (1) the DGRH (General Direction of Water Resources of the Honduran Ministry of Natural Resources); (2) the National Oceanic and Atmospheric Administration (NOAA), including data from the Global Historical Climatology Network (GHCN) and the Global Surface Summary of the Day (GSOD); and (3) the ENEE (National Electric Power Company of Honduras). In some areas with low weather station density, it was added pseudo-stations from CFSR (Climate Forecast System Reanalysis) for temperature (Ruane et al., 2015) and CHIRPS (Climate Hazards Group InfraRed Precipitation with Station; Funk et al., 2015) for precipitation. For future climates, it was performed a statistical downscaling (delta method or change factor) process based on the sum of the anomalies of GCMs (General Circulation Models), to the high resolution baseline surface (the 20-yr normal) at monthly scale (Ramirez & Jarvis, 2010). It was used data from ~20 GCMs from the IPCC AR5 (CMIP5 Archive) run across two Representative Concentration Pathways (RCP 2.6 and 8.5), for the reported IPCC future 20-year periods (IPCC, 2013): 2026-2045 (2030s) and 2046-2065 (2050s).
Subject	Earth and Environmental Sciences; Agricultural Sciences
Keyword	Downscaling, Interpolation, Weather stations, Climate change, Honduras, Precipitation, Rainfall, Maximum temperature, Minimum temperature, Latin America and the Caribbean, Decision and Policy Analysis - DAPA
Related Publication	Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., Jarvis, A., & others. (2005). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25(15), 1965–1978. doi: 10.1002/joc.1276
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	01. historical_monthly_30s_tif.zip ZIP Archive - 842.7 KB Published Nov 15, 2017 158 Downloads MD5: 11b6aa762286e82a04881156eb0e8679 Historical 20-yr average monthly surfaces interpolated from Honduras’ weather station datasets of precipitation, maximum and minimum temperature. Data	Preview "01. historical_monthly_30s_tif.zip" Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	02. historical_monthly_ts_30s_tif.zip ZIP Archive - 21.1 MB Published Nov 15, 2017 108 Downloads MD5: 77e8569aa0d87c08f8335c82c96881fd Historical 20-yr time-series monthly surfaces interpolated from Honduras’ weather station datasets of precipitation, maximum and minimum temperature. Data	Preview "02. historical_monthly_ts_30s_tif.zip" Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	03. historical_seasonal_30s_tif.zip ZIP Archive - 395.9 KB Published Nov 15, 2017 105 Downloads MD5: 0005c2a074e19087f16ba4da580dd277 Historical 20-yr average seasonal surfaces interpolated from Honduras’ weather station datasets of precipitation, maximum and minimum temperature. Data	Preview "03. historical_seasonal_30s_tif.zip" Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	04. historical_seasonal_ts_30s_tif.zip ZIP Archive - 9.9 MB Published Nov 15, 2017 103 Downloads MD5: 4adae637ecf2c4c4fa936b961e19126c Historical 20-yr time-series seasonal surfaces interpolated from Honduras’ weather station datasets of precipitation, maximum and minimum temperature. Data	Preview "04. historical_seasonal_ts_30s_tif.zip" Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	05. rcp26_2026_2045_monthly_30s_tif.zip ZIP Archive - 10.6 MB Published Nov 15, 2017 95 Downloads MD5: dac64a547fdf8fbbdb6287b486d2175d Future 20-yr average downscaled monthly surfaces by 2030s using RCP 2.6. Data	Preview "05. rcp26_2026_2045_monthly_30s_tif.zip" Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	06. rcp26_2026_2045_seasonal_30s_tif.zip ZIP Archive - 3.5 MB Published Nov 15, 2017 93 Downloads MD5: 58f4e7503bc05a7ec0f125abbc007a30 Future 20-yr average downscaled seasonal surfaces by 2030s using RCP 2.6. Data	Preview "06. rcp26_2026_2045_seasonal_30s_tif.zip" Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	07. rcp26_2046_2065_monthly_30s_tif.zip ZIP Archive - 10.6 MB Published Nov 15, 2017 93 Downloads MD5: 60cc8f813c052ec7d3dcd32b5d4051df Future 20-yr average downscaled monthly surfaces by 2050s using RCP 2.6. Data	Preview "07. rcp26_2046_2065_monthly_30s_tif.zip" Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	08. rcp26_2046_2065_seasonal_30s_tif.zip ZIP Archive - 3.5 MB Published Nov 15, 2017 94 Downloads MD5: 42ccbb6a56d313f305018ee2adc3ac77 Future 20-yr average downscaled seasonal surfaces by 2050s using RCP 2.6. Data	Preview "08. rcp26_2046_2065_seasonal_30s_tif.zip" Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	09. rcp85_2026_2045_monthly_30s_tif.zip ZIP Archive - 10.6 MB Published Nov 15, 2017 93 Downloads MD5: cb1a7754daa99bacb139c4685d9b8c0f Future 20-yr average downscaled monthly surfaces by 2030s using RCP 8.5. Data	Preview "09. rcp85_2026_2045_monthly_30s_tif.zip" Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX
	10. rcp85_2026_2045_seasonal_30s_tif.zip ZIP Archive - 3.5 MB Published Nov 15, 2017 94 Downloads MD5: 21135ea9f500e3b97c6fb80c7686f43a Future 20-yr average downscaled seasonal surfaces by 2030s using RCP 8.5. Data	Preview "10. rcp85_2026_2045_seasonal_30s_tif.zip" Access File File Access Public Download Options ZIP Archive Download Metadata Data File Citation EndNote XML RIS BibTeX

Citation Metadata

Persistent Identifier	doi:10.7910/DVN/YR7QYP
Publication Date	2017-11-15
Title	30 Arc-Second Historical and Future Scenario Climate Surfaces for Western Honduras
Author	Llanos Herrera, Lizeth (International Center for Tropical Agriculture - CIAT) - ORCID: 0000-0003-3540-7348 Navarro Racines, Carlos E. (International Center for Tropical Agriculture - CIAT) - ORCID: 0000-0002-8692-6431 Valencia, Jefferson (International Center for Tropical Agriculture - CIAT) - ORCID: 0000-0002-6774-6996 Monserrate, Fredy (International Center for Tropical Agriculture - CIAT) - ORCID: 0000-0003-4669-9614 Quintero, Marcela (International Center for Tropical Agriculture - CIAT) - ORCID: 0000-0001-8107-7744
Point of Contact	Use email button above to contact. CIAT Data and Research Methods (International Center for Tropical Agriculture - CIAT)
Description	In order to characterize the historical climate for the Western Honduras region, it was developed monthly surfaces by years through spatial interpolation and available records of weather stations. The interpolated surfaces were generated at 1-km of spatial resolution (30 arc-seconds) for monthly precipitation (1981-2015), and minimum and maximum temperature (1990-2014). It was followed the method described by Hijmans et al. (2005), using data from: (1) the DGRH (General Direction of Water Resources of the Honduran Ministry of Natural Resources); (2) the National Oceanic and Atmospheric Administration (NOAA), including data from the Global Historical Climatology Network (GHCN) and the Global Surface Summary of the Day (GSOD); and (3) the ENEE (National Electric Power Company of Honduras). In some areas with low weather station density, it was added pseudo-stations from CFSR (Climate Forecast System Reanalysis) for temperature (Ruane et al., 2015) and CHIRPS (Climate Hazards Group InfraRed Precipitation with Station; Funk et al., 2015) for precipitation. For future climates, it was performed a statistical downscaling (delta method or change factor) process based on the sum of the anomalies of GCMs (General Circulation Models), to the high resolution baseline surface (the 20-yr normal) at monthly scale (Ramirez & Jarvis, 2010). It was used data from ~20 GCMs from the IPCC AR5 (CMIP5 Archive) run across two Representative Concentration Pathways (RCP 2.6 and 8.5), for the reported IPCC future 20-year periods (IPCC, 2013): 2026-2045 (2030s) and 2046-2065 (2050s).
Subject	Earth and Environmental Sciences; Agricultural Sciences
Keyword	Downscaling Interpolation Weather stations (AGROVOC) http://aims.fao.org/aos/agrovoc/c_4781 Climate change (AGROVOC) http://aims.fao.org/aos/agrovoc/c_1666 Honduras (AGROVOC) http://aims.fao.org/aos/agrovoc/c_3651 Precipitation (AGROVOC) http://aims.fao.org/aos/agrovoc/c_6161 Rainfall (AGROVOC) http://aims.fao.org/aos/agrovoc/c_6435 Maximum temperature Minimum temperature Latin America and the Caribbean (CIAT Region) Decision and Policy Analysis - DAPA (CIAT Research Area)
Topic Classification	Climatic data (AGROVOC) http://aims.fao.org/aos/agrovoc/c_29553
Related Publication	Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., Jarvis, A., & others. (2005). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25(15), 1965–1978. doi: 10.1002/joc.1276 https://dx.doi.org/10.1002/joc.1276 Ruane, A. C., Goldberg, R., & Chryssanthacopoulos, J. (2015). Climate forcing datasets for agricultural modeling: Merged products for gap-filling and historical climate series estimation. Agricultural and Forest Meteorology, 200, 233–248. doi: 10.1016/j.agrformet.2014.09.016 http://dx.doi.org/10.1016/j.agrformet.2014.09.016 Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., & Michaelsen, J. (2015). The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Scientific Data, 2, 150066. doi: 10.1038/sdata.2015.66 http://dx.doi.org/10.1038/sdata.2015.66 Ramirez, J., & Jarvis, A. (2010). Downscaling Global Circulation Model Outputs: The Delta Method Decision and Policy Analysis Working Paper No. 1. International Center for Tropical Agriculture. Available at: url: http://ccafs-climate.org/documentation IPCC. (2013). Climate Change 2013 The Physical Science Basis Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. B. Cambridge University Press United Kingdom and New York, NY, USA, 1535 pp. doi: 10.1017/CBO9781107415324 http://dx.doi.org/10.1017/CBO9781107415324
Producer	International Center for Tropical Agriculture (CIAT) http://ciat.cgiar.org/ Dirección General de Recursos Hídricos (DGRH) Empresa Nacional de Energía Eléctrica (ENEE)
Production Date	2017
Funding Information	United States Agency for International Development - USAID: Water Planning System
Distributor	International Center for Tropical Agriculture (CIAT) http://ciat.cgiar.org/
Depositor	Garcia, Carolina
Deposit Date	2017-11-01
Date of Collection	Start Date: 1990 ; End Date: 2014
Data Type	Interpolated Data; Aggregate Data; Climate Data
Related Dataset	Da Silva, Mayesse; Monserrate, Fredy; Valencia, Jefferson; Quintero, Marcela; Jarvis, Andy, 2016, "Digital mapping of soil properties in the West of Honduras, Central America.", doi:10.7910/DVN/QVXA7U, Harvard Dataverse, V2

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Geographic Coverage	Honduras

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Disclaimer Whilst utmost care has been taken by CIAT and data authors while collecting and compiling the data, the data is however offered "as is" with no express or implied warranty. In no event shall the data authors, CIAT, or relevant funding agencies be liable for any actual, incidental or consequential damages arising from use of the data.

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