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Water 2019, 11(1), 70; https://doi.org/10.3390/w11010070

Generation of Monthly Precipitation Climatologies for Costa Rica Using Irregular Rain-Gauge Observational Networks

1
Instituto Tecnológico de Costa Rica, Escuela de Ingeniería en Construcción, Cartago 159-7050, Costa Rica
2
Instituto Tecnológico de Costa Rica, Escuela de Ingeniería en Computación, Cartago 159-7050, Costa Rica
3
Department of Water Resources, Faculty of Geo-Information Science and Earth Observation (UT-I-ITC-WCC), University of Twente, Enschede Hengelosestraat 99 7514 AE, The Netherlands
4
Departamento de Climatología e Investigaciones Aplicadas, Instituto Meteorológico Nacional, San José 5383-1000, Costa Rica
*
Author to whom correspondence should be addressed.
Received: 14 December 2018 / Revised: 24 December 2018 / Accepted: 27 December 2018 / Published: 3 January 2019
(This article belongs to the Section Water Resources Management and Governance)
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Abstract

Precipitation climatologies for the period 1961–1990 were generated for all climatic regions of Costa Rica using an irregular rain-gauge observational network comprised by 416 rain-gauge stations. Two sub-networks were defined: a high temporal resolution sub-network (HTR), including stations having at least 20 years of continuous records during the study period (157 in total); and a high spatial resolution sub-network (HSR), which includes all HTR-stations plus those stations with less than 20 years of continuous records (416 in total). Results from the kriging variance reduction efficiency (KRE) objective function between the two sub-networks, show that ordinary kriging (OK) is unable to fully explain the spatio-temporal variability of precipitation within most climatic regions if only stations from the HTR sub-network are used. Results also suggests that in most cases, it is beneficial to increase the density of the rain-gauge observational network at the expense of temporal fidelity, by including more stations even though their records may not represent the same time step. Thereafter, precipitation climatologies were generated using seven deterministic (IDW, TS2, TS2PARA, TS2LINEAR, TPS, MQS and NN) and two geostatistical (OK and KED) interpolation methods. Performance of the various interpolation methods was evaluated using cross validation technique, selecting the mean absolute error (MAE) and the root-mean square error (RMSE) as agreement metrics. Results suggest that IDW is marginally superior to OK and KED for most climatic regions. The remaining deterministic methods however, considerably deviate from IDW, which suggests that these methods are incapable of properly capturing the true-nature of spatial precipitation patterns over the considered climatic regions. The final generated IDW climatology was then validated against the Global Precipitation Climatology Centre (GPCC), Climate Research Unit (CRU) and WorldClim datasets, in which overall spatial and temporal coherence is considered satisfactory, giving assurance about the use this new climatology in the development of local climate impact studies. View Full-Text
Keywords: climatology; interpolation; irregular; kriging; precipitation; rain-gauge network; variance climatology; interpolation; irregular; kriging; precipitation; rain-gauge network; variance
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Mendez, M.; Calvo-Valverde, L.-A.; Maathuis, B.; Alvarado-Gamboa, L.-F. Generation of Monthly Precipitation Climatologies for Costa Rica Using Irregular Rain-Gauge Observational Networks. Water 2019, 11, 70.

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