High-resolution satellite-gauge merged precipitation climatologies of the tropical Andes
Cite this dataset as:
Manz, B.; Buytaert, W.; Zulkafli, Z.; Lavado, W.; Willems, B.; Robles, L.A.; Rodríguez Sánchez, J.-. (2016). High-resolution satellite-gauge merged precipitation climatologies of the tropical Andes. NERC Environmental Information Data Centre. https://doi.org/10.5285/74a588cc-723c-4a35-ac0c-223f5b92ee36
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© NERC/ Bastian Manz
This dataset is made available under the terms of the Open Government Licence 
https://doi.org/10.5285/74a588cc-723c-4a35-ac0c-223f5b92ee36
A set of 130 digital precipitation maps of the tropical Andes, covering Colombia, Ecuador and Peru at a 5km resolution. The maps represent different realizations of mean precipitation totals of the period 1981-2010 using different satellite-gauge merging methods. The work draws on a large database of 723 rain gauges and the full 5km Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (TPR) record from 1998 to 2014. Each map is approximately 1MB
Publication date: 2016-01-14
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Format
TIFF
Spatial information
Study area
Spatial representation type
Raster
Spatial reference system
WGS 84
Temporal information
Temporal extent
1981-01-01 to 2014-12-31
Provenance & quality
TRMM Precipitation Radar data, product 2A25, was obtained from NASA for the period Jan 1998 to Oct 2014. Individual orbital scans were converted into time-series and re-projected onto a regular UTM grid (5 km) in R (statistical software), which allowed averaging over time to obtain mean monthly and annual climatological rainfall fields (regular raster grids) from the TPR (in R). Monthly or daily rain gauge time-series for the period 1981-2010 were obtained from IDEAM (Colombia), INAMHI (Ecuador), SENAMHI (Peru), SENAMHI (Bolivia) and NOAA (USA) and mean monthly and annual climatological values were determined for every gauge using a bespoke R script. Gauging station coordinates are re-projected into UTM (in R). Satellite-gauge merging as described in the supporting information was conducted using bespoke R scripts. Following generation of the final merged climatological precipitation fields (regular raster grids) these are converted from R to GeoTIFF (.tif).
Licensing and constraints
This dataset is made available under the terms of the Open Government Licence
Cite this dataset as:
Manz, B.; Buytaert, W.; Zulkafli, Z.; Lavado, W.; Willems, B.; Robles, L.A.; Rodríguez Sánchez, J.-. (2016). High-resolution satellite-gauge merged precipitation climatologies of the tropical Andes. NERC Environmental Information Data Centre. https://doi.org/10.5285/74a588cc-723c-4a35-ac0c-223f5b92ee36
© NERC/ Bastian Manz
Citations
Manz, B., W. Buytaert, Z. Zulkafli, W. Lavado, B. Willems, L.-A. Robles, and J.-P. Rodriguez-Sanchez (2016) High-resolution satellite-gauge merged precipitation climatologies of the tropical Andes, Journal of Geophysical Research: Atmospheres https://doi.org/10.1002/2015JD023788
Cruz-Roa, A.F., & Barrios, M.I. (2018). Estimación de datos faltantes de lluvia mensual a través de la asimilación de información satelital y pluviométrica en una cuenca andina tropical. Idesia (Arica), (ahead), 0–0. https://doi.org/10.4067/s0718-34292018005001601
Ulloa, J., Ballari, D., Campozano, L., & Samaniego, E. (2017). Two-Step Downscaling of Trmm 3b43 V7 Precipitation in Contrasting Climatic Regions With Sparse Monitoring: The Case of Ecuador in Tropical South America. Remote Sensing, 9(7), 758. https://doi.org/10.3390/rs9070758
Paul, J.D., Buytaert, W., Allen, S., Ballesteros‐Cánovas, J.A., Bhusal, J., Cieslik, K., … Supper, R. (2017). Citizen science for hydrological risk reduction and resilience building. WIREs Water, 5(1). https://doi.org/10.1002/wat2.1262
Bai, P., & Liu, X. (2018). Evaluation of Five Satellite-Based Precipitation Products in Two Gauge-Scarce Basins on the Tibetan Plateau. Remote Sensing, 10(8), 1316. https://doi.org/10.3390/rs10081316
Ochoa-Tocachi, B.F., Buytaert, W., Antiporta, J., Acosta, L., Bardales, J.D., Célleri, R., … De Bièvre, B. (2018). High-resolution hydrometeorological data from a network of headwater catchments in the tropical Andes. Scientific Data, 5(1). https://doi.org/10.1038/sdata.2018.80
Correspondence/contact details
Manz, B.
Imperial College London
Department of Civil and Environmental Engineering
London
SW7 2AZ
bastian.manz10@imperial.ac.uk
London
SW7 2AZ
Other contacts
Custodian
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
Publisher
NERC Environmental Information Data Centre
info@eidc.ac.uk