30 Arc-Second Historical and Future Scenario Climate Surfaces for Western Honduras (doi:10.7910/DVN/YR7QYP)

View:

Part 1: Document Description
Part 2: Study Description
Part 5: Other Study-Related Materials
Entire Codebook

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

doi:10.7910/DVN/YR7QYP

Harvard Dataverse

2017-11-15

1

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

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

doi:10.7910/DVN/YR7QYP

Llanos Herrera, Lizeth (International Center for Tropical Agriculture - CIAT)

Navarro Racines, Carlos E. (International Center for Tropical Agriculture - CIAT)

Valencia, Jefferson (International Center for Tropical Agriculture - CIAT)

Monserrate, Fredy (International Center for Tropical Agriculture - CIAT)

Quintero, Marcela (International Center for Tropical Agriculture - CIAT)

International Center for Tropical Agriculture

Dirección General de Recursos Hídricos

Empresa Nacional de Energía Eléctrica

2017

Water Planning System

Harvard Dataverse

International Center for Tropical Agriculture

CIAT Data and Research Methods

Garcia, Carolina

2017-11-01

https://doi.org/10.7910/DVN/YR7QYP

Agricultural Sciences, Earth and Environmental Sciences, Downscaling, Interpolation, Weather stations, Climate change, Honduras, Precipitation, Rainfall, Maximum temperature, Minimum temperature, Latin America and the Caribbean, Decision and Policy Analysis - DAPA

Climatic data

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. <br> 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).

1990-2014

Honduras

Interpolated Data

Aggregate Data

Climate Data

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. <BR/><BR/> By using the CIAT Dataverse, the user expressly acknowledges that the Data may contain some nonconformities, defects, or errors. No warranty is given that the data will meet the user's needs or expectations or that all nonconformities, defects, or errors can or will be corrected. <BR/><BR/> The user should always verify actual data; therefore the user bears all responsibility in determining whether the data is fit for the user’s intended use. The user of the data should use the related publications as a baseline for their analysis whenever possible. Doing so will be an added safeguard against misinterpretation of the data. Related publications are listed in the metadata section of the Dataverse study.

<P><a rel="license" href="http://creativecommons.org/licenses/by/4.0/" target="_blank"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br /> These data and documents are licensed under a <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank"> Creative Commons Attribution 4.0 International license.</a> You may copy, distribute and transmit the data as long as you acknowledge the source through proper <a href="http://best-practices.dataverse.org/data-citation/" target="_blank">data citation</a>.</P> <Strong>Disclaimer</Strong> <P> 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. <BR/><BR/> By using the CIAT Dataverse, the user expressly acknowledges that the Data may contain some nonconformities, defects, or errors. No warranty is given that the data will meet the user's needs or expectations or that all nonconformities, defects, or errors can or will be corrected. <BR/><BR/> The user should always verify actual data; therefore the user bears all responsibility in determining whether the data is fit for the user’s intended use. The user of the data should use the related publications as a baseline for their analysis whenever possible. Doing so will be an added safeguard against misinterpretation of the data. Related publications are listed in the metadata section of the Dataverse study. </P>

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

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.

10.1002/joc.1276

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.

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.

10.1016/j.agrformet.2014.09.016

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.

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.

10.1038/sdata.2015.66

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.

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:

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:

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.

10.1017/CBO9781107415324

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.

Label:

01. historical_monthly_30s_tif.zip

Text:

Historical 20-yr average monthly surfaces interpolated from Honduras’ weather station datasets of precipitation, maximum and minimum temperature.

application/zip

Label:

02. historical_monthly_ts_30s_tif.zip

Text:

Historical 20-yr time-series monthly surfaces interpolated from Honduras’ weather station datasets of precipitation, maximum and minimum temperature.

application/zip

Label:

03. historical_seasonal_30s_tif.zip

Text:

Historical 20-yr average seasonal surfaces interpolated from Honduras’ weather station datasets of precipitation, maximum and minimum temperature.

application/zip

Label:

04. historical_seasonal_ts_30s_tif.zip

Text:

Historical 20-yr time-series seasonal surfaces interpolated from Honduras’ weather station datasets of precipitation, maximum and minimum temperature.

application/zip

Label:

05. rcp26_2026_2045_monthly_30s_tif.zip

Text:

Future 20-yr average downscaled monthly surfaces by 2030s using RCP 2.6.

application/zip

Label:

06. rcp26_2026_2045_seasonal_30s_tif.zip

Text:

Future 20-yr average downscaled seasonal surfaces by 2030s using RCP 2.6.

application/zip

Label:

07. rcp26_2046_2065_monthly_30s_tif.zip

Text:

Future 20-yr average downscaled monthly surfaces by 2050s using RCP 2.6.

application/zip

Label:

08. rcp26_2046_2065_seasonal_30s_tif.zip

Text:

Future 20-yr average downscaled seasonal surfaces by 2050s using RCP 2.6.

application/zip

Label:

09. rcp85_2026_2045_monthly_30s_tif.zip

Text:

Future 20-yr average downscaled monthly surfaces by 2030s using RCP 8.5.

application/zip

Label:

10. rcp85_2026_2045_seasonal_30s_tif.zip

Text:

Future 20-yr average downscaled seasonal surfaces by 2030s using RCP 8.5.

application/zip

Label:

11. rcp85_2046_2065_monthly_30s_tif.zip

Text:

Future 20-yr average downscaled monthly surfaces by 2050s using RCP 8.5.

application/zip

Label:

12. rcp85_2046_2065_seasonal_30s_tif.zip

Text:

Future 20-yr average downscaled seasonal surfaces by 2050s using RCP 8.5.

application/zip