A precipitation-based regionalization for Western Iran and regional drought variability

Abstract. The spatial distribution of the seasonal and annual precipitation was analyzed in western Iran using data from 140 stations covering the period 1965–2000. Applying the Precipitation Concentration Index (PCI), the intraannual precipitation variability was also studied. Furthermore, nine precipitation-derived parameters were used to regionalize climate in western Iran using principal component analysis and clustering techniques. Results suggest that five spatially homogenous sub-regions can be identified characterized by different precipitation regimes. The spatial pattern of seasonal precipitation seems to be highly controlled by the wide latitudinal extent of the region and by the pronounced orographic relieves, and the time of occurrence of the maximum precipitation varies from spring in the north to winter in the south. The time variability of dry and wet periods in the identified sub-regions was analyzed using the Precipitation Index (PI) and the existence of any long-term trend was tested. Results show that the northern and southern regions of western Iran are characterized by different climatic variability. Furthermore, a negative long-term linear trend in the north and a weak positive trend in the south of the study area have been detected though they are not statistically significan

Space-time variability of hydrological drought and wetness in Iran using NCEP/NCAR and GPCC datasets

Abstract. Space-time variability of hydrological drought and wetness over Iran is investigated using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and the Global Precipitation Climatology Centre (GPCC) dataset for the common period 1948–2007. The aim is to complement previous studies on the detection of long-term trends in drought/wetness time series and on the applicability of reanalysis data for drought monitoring in Iran. Climate conditions of the area are assessed through the Standardized Precipitation Index (SPI) on 24-month time scale, while Principal Component Analysis (PCA) and Varimax rotation are used for investigating drought/wetness variability, and drought regionalization, respectively. Singular Spectrum Analysis (SSA) is applied to the time series of interest to extract the leading nonlinear components and compare them with linear fittings. Differences in drought and wetness area coverage resulting from the two datasets are discussed also in relation to the change occurred in recent years. NCEP/NCAR and GPCC are in good agreement in identifying four sub-regions as principal spatial modes of drought variability. However, the climate variability in each area is not univocally represented by the two datasets: a good agreement is found for southeastern and north-western regions, while noticeable discrepancies occur for central and Caspian sea regions. A comparison with NCEP Reanalysis II for the period 1979–2007, seems to exclude that the discrepancies are merely due to the introduction of satellite data into the reanalysis assimilation schem

Spatial and temporal variability of precipitation and drought in Portugal

The spatial variability of precipitation and drought are investigated for Portugal using monthly precipitation from 74 stations and minimum and maximum temperature from 27 stations, covering the common period of 1941–2006. Seasonal precipitation and the corresponding percentages in the year, as well as the precipitation concentration index (PCI), was computed for all 74 stations and then used as an input matrix for an R-mode principal component analysis to identify the precipitation patterns. The standardized precipitation index at 3 and 12 month time scales were computed for all stations, whereas the Palmer Drought Severity Index (PDSI) and the modified PDSI for Mediterranean conditions (MedPDSI) were computed for the stations with temperature data. The spatial patterns of drought over Portugal were identified by applying the S-mode principal component analysis coupled with varimax rotation to the drought indices matrices. The result revealed two distinct sub-regions in the country relative to both precipitation regimes and drought variability. The analysis of time variability of the PC scores of all drought indices allowed verifying that there is no linear trend indicating drought aggravation or decrease. In addition, the analysis shows that results for SPI-3, SPI-12, PDSI and MedPDSI are coherent among them

Spatial patterns and temporal variability of drought in Western Iran

An analysis of drought in western Iran from 1966 to 2000 is presented using monthly precipitation data observed at 140 gauges uniformly distributed over the area. Drought conditions have been assessed by means of the Standardized Precipitation Index (SPI). To study the long-term drought variability the principal component analysis was applied to the SPI field computed on 12-month time scale. The analysis shows that applying an orthogonal rotation to the first two principal component patterns, two distinct sub-regions having different climatic variability may be identified. Results have been compared to those obtained for the largescale using re-analysis data suggesting a satisfactory agreement. Furthermore, the extension of the large-scale analysis to a longer period (1948–2007) shows that the spatial patterns and the associated time variability of drought are subjected to noticeable changes. Finally, the relationship between hydrological droughts in the two sub-regions and El Niño Southern Oscillation events has been investigated finding that there is not clear evidence for a link between the two phenomen

Characterising droughts in Central America with uncertain hydro-meteorological data

Central America is frequently affected by droughts that cause significant socio-economic and environmental problems. Drought characterisation, monitoring and forecasting are potentially useful to support water resource management. Drought indices are designed for these purposes, but their ability to characterise droughts depends on the characteristics of the regional climate and the quality of the available data. Local comprehensive and high-quality observational networks of meteorological and hydrological data are not available, which limits the choice of drought indices and makes it important to assess available datasets. This study evaluated which combinations of drought index and meteorological dataset were most suitable for characterising droughts in the region. We evaluated the standardised precipitation index (SPI), a modified version of the deciles index (DI), the standardised precipitation evapotranspiration index (SPEI) and the effective drought index (EDI). These were calculated using precipitation data from the Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS), the CRN073 dataset, the Climate Research Unit (CRU), ECMWF Reanalysis (ERA-Interim) and a regional station dataset, and temperature from the CRU and ERA-Interim datasets. The gridded meteorological precipitation datasets were compared to assess how well they captured key features of the regional climate. The performance of all the drought indices calculated with all the meteorological datasets was then evaluated against a drought index calculated using river discharge data. Results showed that the selection of database was more important than the selection of drought index and that the best combinations were the EDI and DI calculated with CHIRPS and CRN073. Results also highlighted the importance of including indices like SPEI for drought assessment in Central America.Universidad de Costa Rica/[805-B0-810]/UCR/Costa RicaUniversidad de Costa Rica/[805-A9-532]/UCR/Costa RicaUniversidad de Costa Rica/[805-B3-600]/UCR/Costa RicaUniversidad de Costa Rica/[805-B0-065]/UCR/Costa RicaUniversidad de Costa Rica/[805-B3-413]/UCR/Costa RicaUniversidad de Costa Rica/[805-B4-227]/UCR/Costa RicaUniversidad de Costa Rica/[805-B4-228]/UCR/Costa RicaUniversidad de Costa Rica/[805-B5-295]/UCR/Costa RicaUppsala University/[54100006]//SueciaMarie Curie Intra-European Fellowship/[No.329762]//EuropaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI)UCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de Físic

Development of high-resolution gridded datasets of monthly temperature in Portugal

High-resolution gridded datasets of monthly minimum and maximum temperature with 0.2˚ × 0.2˚ spatial resolution (approximately 20 km) are generated for Portugal covering the period 1950–2003. At the purpose of their application in a wide range of climatological and hydrological studies over Portugal and the Iberian Peninsula, the time period and the spatial resolution are intentionally set to be the same of the daily gridded datasets recently developed for Portugal (PT02, only precipitation) and Spain (Spain02, precipitation, and minimum and maximum temperature). The Ordinary Kriging method is used to produce the temperature fields interpolated from 36 meteorological stations regularly distributed over Portugal. The performance and accuracy of the interpolation method are evaluated using a cross-validation approach and the estimated errors. The correlation analysis is performed to assess the degree of agreement between observations and the gridded outputs, represented by the grid points surrounding the stations. Furthermore, the representativeness of the new datasets for the study area is evaluated analyzing the capability of the gridded data in reproducing the seasonal time variability and spatial patterns of the temperature variables over Portugal

Variants of the Palmer Drought Severity Index for Portugal using fine resolution gridded datasets

Monthly time series of the Self-Calibrating Palmer Drought Severity Index (SC-PDSI) and SC-MedPDSI, a modified PDSI for the Mediterranean environment, are computed for Portugal using high-resolution gridded datasets of monthly precipitation totals retrieved from the PT02 daily gridded dataset, and monthly averages of maximum and minimum temperature purposefully developed. The datasets have 0.2˚ × 0.2˚ spatial resolution and cover the period 1950–2003. The effects of the weighing and self-calibrating (SC) methods are studied by comparing the SC-PDSI and SC-MedPDSI with the corresponding indices computed using the original calibration for Portugal. Particular attention is given to the frequency of wet and dry events. The two indices are compared with the SPI on 9-month time scale (SPI-9) computed using the PT02 dataset. Results show that extreme events are less frequent when using the SC indices, and that there is a significant agreement between the SPI-9 and the SC-PDSI or the SC-MedPDSI. Moreover, the space and time variability of the indices are analysed using the Principal Component Analysis (PCA). The spatial patterns identify two sub-regions consistently with previous studies. The Modified Mann-Kendal test is applied to the PC score time serie

Spatial modes of drought variability in Portugal using a high-resolution gridded dataset.

Regional drought modes in Portugal are identified applying the Principal Component Analysis (PCA) and Varimax rotation to the Standardized Precipitation Index (SPI) computed on different time scales at grid points regularly distributed over the country. The high-resolution (0.2 degree, approximately 20 km) gridded precipitation dataset provided by the Portuguese Meteorological Institute, which is based on a dense network of 400 quality-controlled stations covering the period 1950–2003, is used in the present study. The analysis aims to identify the spatial modes of drought variability in Portugal as well as to investigate their stability as a function of the SPI time scale used for monitoring the different kinds of drought. The identified spatial modes consist of two sub-regions with independent climate time variability, and they appear to remain relatively stable when the SPI time scale is varied from 1- to 36-month. As it is reasonable to expect, the wider extension over latitude than over longitude of the country (37–42N, 7–9W), controls the north-south character of the regionalization. Moreover, for long time scales it was found a third sub-region in central-eastern Portugal characterized by a prevailing downward trend in the SPI time series; this deserves further checks against observations and/or other precipitation datasets. The regionalization of drought herein proposed appears of particular interest for a rationale water resources management in the major Portuguese river basins (i.e., Douro, Tagus and Guadiana)