Precipitation Data in a Mountainous Catchment in Honduras: Quality Assessment and Spatiotemporal Characteristics

Theor Appl Climatol (2010) 101:381–396 DOI 10.1007/s00704-009-0222-x ORIGINAL PAPER Precipitation data in a mountainous catchment in Honduras: quality assessment and spatiotemporal characteristics I. Westerberg & A. Walther & J-L. Guerrero & Z. Coello & S. Halldin & C-Y. Xu & D. Chen & L-C. Lundin Received: 25 April 2008 /Accepted: 1 October 2009 /Published online: 24 October 2009 # Springer-Verlag 2009 Abstract An accurate description of temporal and spatial provided the best results for gap-filling and the universal precipitation variability in Central America is important for kriging method for spatial interpolation. In-homogeneity in local farming, water supply and flood management. Data the time series was the main quality problem, and 22% of quality problems and lack of consistent precipitation data the daily precipitation data were too poor to be used. Spatial impede hydrometeorological analysis in the 7,500 km2 autocorrelation for monthly precipitation was low during Choluteca River basin in central Honduras, encompassing the dry season, and correlation increased markedly when the capital Tegucigalpa. We used precipitation data from 60 data were temporally aggregated from a daily time scale to daily and 13 monthly stations in 1913–2006 from five local 4–5 days. The analysis manifested the high spatial and authorities and NOAA's Global Historical Climatology temporal variability caused by the diverse precipitation- Network. Quality control routines were developed to tackle generating mechanisms and the need for an improved the specific data quality problems. The quality-controlled monitoring network. data were characterised spatially and temporally, and compared with regional and larger-scale studies. Two gap- filling methods for daily data and three interpolation 1 Introduction methods for monthly and mean annual precipitation were compared. The coefficient-of-correlation-weighting method In Central America, large socio-economic interests, such as hydropower generation, agriculture and flood prevention are dependent on the characteristics of the precipitation regime * : : : : I. Westerberg: ( ) J.-L. Guerrero Z. Coello S. Halldin (Alfaro 2002;Magañaetal.1999). An accurate description C.-Y. Xu L.-C. Lundin of the features of this regime, specifically on a local scale, is Department of Earth Sciences, Uppsala University, dependent on the quality of the database. The creation of Uppsala, Sweden e-mail: [email protected] such a database takes many years of data collection. In addition, a thorough quality control and analysis are needed I. Westerberg before the station data records can be transformed into IVL Swedish Environmental Research Institute, estimates of areal precipitation useful for hydrometeorological Stockholm, Sweden analysis. In Central America in general, and Honduras in A. Walther : D. Chen particular, the need for properly quality controlled precipita- Department of Earth Sciences, University of Gothenburg, tion data has been stated in several previous studies (Aguilar et Gothenburg, Sweden al. 2005; Balairón Pérez et al. 2004; Flambard 2003)of J.-L. Guerrero : Z. Coello which some have been limited by poor quality data. High Universidad Nacional Autónoma de Honduras, quality precipitation data are specifically needed for water Tegucigalpa, Honduras management in the Choluteca River basin in Honduras, encompassing the capital Tegucigalpa. C.-Y. Xu Department of Geosciences, University of Oslo, Precipitation data of high quality are important not only Oslo, Norway for describing the precipitation regime; hydrological models 382 I. Westerberg et al. are sensitive to input data errors, and errors in precipitation 2 Study area data have been shown to be more important than errors in evaporation (Paturel et al. 1995; Xu and Vandewiele 1994; The 7,500 km2 Choluteca River basin is situated in the Xu et al. 2006). There are both random and systematic southern part of Honduras, with a small part of the basin errors in point precipitation measurements (Sevruk 1986); located in Nicaragua (Fig. 1). Elevation in this mountainous random errors can be caused by micro-climatic variations catchment ranges from 0 to 2,300 m above sea level with a around the gauge while systematic errors are related to mean elevation of 890 m. The capital of Honduras, wind, wetting and evaporation losses, etc. On top of these Tegucigalpa, is located in the upper parts and the water errors are human-induced errors like misread and mistyped supply reservoirs for the city affect the hydrological regime records and database inconsistencies. In previous studies on in the basin. This region is also where the precipitation- precipitation-quality control, errors have been identified in monitoring network is most dense. data series as outliers, in-homogeneities and inconsistencies There is a distinct seasonal precipitation variation in the as well as erroneous information about station metadata, area with a marked dry and rainy season; the climate is e.g., coordinates and codes (Aguilar et al. 2005; Eischeid et classified as tropical wet-and-dry in the lowlands and as al. 1995; Feng et al. 2004; Gonzalez-Rouco et al. 2001). In highland climate in the mountainous upper parts of the the Honduran national water-balance study (Balairón Pérez basin (McGregor and Nieuwolt 1998). The regional climate et al. 2004), problems such as non-consistent coding of of Central America is strongly influenced by the surrounding data, erroneous station coordinates, time series data with no oceans, but it also shows a greater spatial and temporal associated codes, and incomplete data were identified. A precipitation variability than might be expected in such a case monitoring network must be carefully designed and (Hastenrath 1967;Portig1976). Orographic lifting that takes managed to prevent these types of errors. Except for place at the high mountain range stretching through the organisational weaknesses in the Honduran hydrometeoro- region, and the orientation of the coastline in relation to logical monitoring network, Flambard (2003) identifies seasonal atmospheric flow patterns (e.g. the trade winds) some technical limiting aspects such as lack of calibration explain a large part of this variability (Hastenrath 1967). The of the equipment, lack of quality control of data and loss of region is located in the North Atlantic trade-wind belt and is sub-daily data as only daily values are stored. In addition to affected by the northward migration of the inter-tropical errors in measured data, the interpolation of point-measured convergence zone (ITCZ), which reaches its maximum precipitation into estimates of the spatial precipitation latitude of about 10°N, in the vicinity of Panama (Amador distribution also introduces uncertainty, especially in et al. 2006;Hastenrath1967). Average annual wind speeds mountainous terrain and if the station density varies over are small and significant seasonal changes in wind direction time. only occur in the western and southern parts of Central The precipitation regime in the Choluteca River basin America, which are affected by the Pacific Ocean (Portig has been addressed in earlier hydrological studies and the 1976). The ITCZ is at its southernmost position, and the need for quality control and a unified approach to easterly trade winds dominate the lower levels of the monitoring has been stressed in most studies (Balairón atmosphere during winter (Hastenrath 1967). The trade Pérez et al. 2004; Díaz Chávez 1984; Flambard 2003; winds are, at times, interrupted by northerly “Nortes” winds Lardizábal Becerra 1976). The majority of the studies have in the first half of winter. The “Nortes” are associated with been made with monthly precipitation data with varying cold-air outbreaks from the North American continent and degrees of quality control performed on the data set. produce precipitation on the windward sides of the mountains Interpolation of precipitation have been made by hand or (Hastenrath 1967;Portig1976). There are large differences with subjectively set weights—in some studies, the effect of in the precipitation regimes of the Caribbean and Pacific quality problems, such as too-low values, can be seen in coasts; there is no distinct dry season on the Caribbean coast isohyetal maps (e.g. Lardizábal Becerra 1976). while the leeward position with respect to the trade winds The aim of this study was to describe the characteristics and the “Nortes” gives little precipitation on the Pacific coast of the precipitation regime in the Choluteca River basin, during winter (Hastenrath 1967). The rainy season starts and to produce a quality controlled precipitation database around May on the Pacific side and transient weather for future hydrologic modelling and water-resource studies. disturbances such as hurricanes, tropical storms and depres- The objectives were achieved through; (1) gathering and sions, easterly waves and meridional displacements of merging the available data from the different data providers the ITCZ explain the largest part of the synoptic variability in a single database, (2) quality control and a description of in precipitation during this season (Peña and Douglas the temporal characteristics of the data and (3) spatial 2002). Wet spells occur most frequently in May–June and interpolation and analysis of the spatial characteristics of September–October, when the atmospheric influences pre- the precipitation data for different time scales. dominantly come from the Pacific Ocean (Hastenrath 1967), Precipitation

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