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

Spatial variability analysis of reference evapotranspiration in Iran utilizing fine resolution gridded datasets

Monthly averages of maximum and minimum temperature, mean relative humidity, sunshine duration and wind speed at 2 m height, relative to 148 Iranian weather stations and period 1991–2005 were utilized for interpolation and gridding the variables to 1◦ in latitude and longitude. The Ordinary kriging method was used coupled with a spherical isotropic variogram. Monthly precipitation of the APHRODITE dataset was regridded to the same mesh grid for computing the aridity index jointly with the gridded variables. The required elevation for estimation of ETo at each grid node was extracted from the digital elevation map of Iran. The adequacy of gridded variables was proved through a set of statistical indicators applied to the cross-validated interpolation errors. The Penman–Monteith (PM-ETo) reference evapotranspiration (ETo) was estimated using the gridded variables and statistically compared with those of observational datasets relative to some stations covering all climatic regions of Iran. Results indicated that the PM-ETo computed using gridded variables well fitted the PM-ETo computed using observed full weather variables at those selected stations. ETo was also estimated by the Hargreaves–Samani (HS) and FAO-PM temperature (PMT) methods using gridded variables of minimum and maximum temperature (Tmin and Tmax). To estimate ETo with HS and PMT methods, appropriate kRs, an empirical radiation adjustment coefficient, were considered for each station, whereas Tmin was adjusted for estimation of the dew point temperature (Tdew) used for PMT computation. It was found that the appropriate kRs for both HS and PMT methods are identical all over the country and they are smaller in dry-sub-humid to humid areas and higher in semiarid to hyper-arid climates. The result suggested that the HS and PMT methods appropriately predict ETo all over Iran if the appropriate kRs are utilized. The spatial patterns of ETo computed with HS and PMT methods found to be identical and resemble to that of PM-ETo, all showing a gradual increasing from north to south, with the lowest ETo values observed over northern humid and sub-humid climates of Iran and larger ETo for arid and hyper-arid climates in the southern and eastern country. Results indicated that the HS and PMT methods are appropriate alternatives for estimation of ETo for all climatic regions of Iran, either when using observation or gridded dat

Estimation of ETo with Hargreaves-Samani and FAO-PM temperature methods for a wide range of climates in Iran

Monthly data records of 40 Iranian stations distributed over the country, for the period 1971–2005, were utilized for estimation of reference evapotranspiration (ETo) using Penman–Monteith (PM-ETo), Hargreaves–Samani (HS) and FAO-PM temperature (PMT) methods. To estimate ETo with HS and PMT methods, appropriate kRs, an empirical radiation adjustment coefficient, were considered for each station, whereas Tmin was adjusted for estimation of Tdew and used only for PMT computation. It was found that the appropriate kRs for both HS and PMT methods are identical for a given station and it is generally smaller in sub-humid and humid than in semi-arid to hyper-arid climates. The performance of the PMT was further improved in both arid and humid climates when Tmin was adjusted. The result suggested that the HS and PMT methods appropriately predict ETo for all climatic regions of Iran if the appropriate kRs was utilized. However, the considered methods showed weak performances for some stations in arid and hyper-arid climates of eastern and southern Iran owing to the effect of extreme and variable wind speed inherent in the PM-ETo. Thus, the role played by wind speed in ETo estimation was examined; the result indicated that the existence of extreme winds, and also the time variability of wind speed, is responsible for the observed discrepancies between PMT and PM-ETo estimates. The spatial patterns of ETo computed with HS and PMT methods found to be identical and resemble to that of PM-ETo, all showing a gradual increasing from north to south, with the lowest ETo values observed over northern humid and sub-humid climates of Iran and larger ETo for arid and hyper-arid climates in the southern and eastern country. Results indicated that the HS and PMT methods are appropriate alternatives for estimation of ETo for all climatic regions of Ira

On the potential of ground-based GPS measurements for monitoring dry/wet events

Half-hourly ground-based GPS measurements of precipitable water vapor (PWV) from January 2009 to December 2012 are analyzed to investigate the potential of such data for hydrological applications at basin level. In particular, the usefulness of these high temporal resolution data for monitoring extreme weather conditions such as floods and meteorological dry/wet spells is discussed. Two sample GPS stations in U.S. from the SoumiNet network are considered that have continuous data for the last four years and a few missing values. Results suggest that: (i) A flood event is characterized by an anomalous increase of PWV and surface pressure lowering; (ii) Precipitable water tendency (DPWV) becomes increasingly small moving from half-hour to monthly time scales, but not negligible compared with both the moisture flux divergence div(Q) and the unbalance between evapotraspiration and precipitation (E–P), especially during spring and fall; (iii) GPS observations, jointly with other meteorological data, can provide an accurate estimate of the unbalance (E–P) that is of interest for drought assessment, and the rate of change of the terrestrial water storage that is known to be difficult to measure; (iii) the availability of on-site precipitation observations allow the computation of the precipitation efficiency, which is a key variable for estimating the water availability in a given area and monitoring drought. It appears that for a comprehensive monitoring of a river basin, a GPS network that encloses the area of concern, equipped with meteorological ground sensors, is suitable and desirable

Regional Drought Modes in Iran Using the SPI: The Effect of Time Scale and Spatial Resolution

In the present paper, regional drought modes in Iran are identified applying the Principal Component Analysis (PCA) and Varimax rotation to the Standardized Precipitation Index (SPI) computed on different time scales. Data used include gridded monthly precipitation covering the period 1951-2007 retrieved from the Global Precipitation Climatology Centre (GPCC) archive with different spatial resolutions (2. 5, 1 and 0. 5° resolution). The objective of the study is twofold: (i) Investigate the stability of drought spatial modes as a function of the SPI time scales used for monitoring the different kinds of drought, (ii) Evaluate the impact of the spatial resolution of gridded data on drought regionalization. For the coarse spatial resolution of 2. 5°, results show four drought modes of distinct variability, which remain quite stable when the SPI time scale is varied from 1- to 24-month. Differently, for higher spatial resolutions drought modes appear more sensitive to the index time scale and become less spatially homogeneous as the time scale is increased. Moreover, the number of identified modes (sub-regions) may reduce to three or two, but in all cases the most well defined sub-region appears to be the southern one. This suggests that both the spatial resolution of precipitation data and the time scale may affect drought regionalization, i. e. the number of drought modes and their spatial homogeneity. © 2012 Springer Science+Business Media B.V

An Application of GPCC and NCEP/NCAR Datasets for Drought Variability Analysis in Iran

The lack of reliable and updated precipitation datasets is the most important limitation that hinders establishing a drought monitoring and early warning system in Iran. To overcome this obstacle, we have evaluated the applicability of GPCC and NCEP/NCAR precipitation datasets for drought analysis in Iran. For this purpose, drought variability across the country has been analyzed through the standardized precipitation index (SPI) on 12-month time scale based on the common period 1951-2005. For each dataset, by applying the principal component analysis (PCA) to the SPI field and Varimax rotation, the studied area has been regionalized into a few distinctive sub-regions characterized by independent climatic variability. Results have been checked against observations at 32 rain gauge stations having reliable data for the study period. Both GPCC and NCEP/NCAR datasets identify the same sub-regions of drought variability and they are in good agreement with observations. However, the NCEP rotated principal component scores associated with the sub-regions show different time variability with respect to the behaviours captured by GPCC, on one hand, and observations, on the other hand. It seems that, in central Iran such differences concern mainly the period before the seventies. Thus, the results suggest that GPCC dataset is a useful tool for drought monitoring in Iran and it can be used to complement the information provided by rain gauge observations. The NCEP/NCAR reanalysis dataset shows a better agreement with observations for the period 1970-2005 than for 1951-2005, and its discrepancies in the regional time variability of drought with respect to GPCC and observations should be taken into account when periods before the seventies are considered

Annual Rainfall Trend Analysis in Arid and Semi-arid Regions of Central and Eastern Iran

Climate variability is the main reason for drought and water scarcity. Annual rainfall trend was investigated in arid and semi-arid regions of Iran using 79 climatology and synoptic stations with 36 years of data records. Monthly and annual precipitation data from homogeneity tests were applied and discontinuities were adjusted in non-homogeneous stations using the annual nonparametric Mann-Kendal statistic test. The results showed no evidence of climate change in the study area. Although many stations showed negative trends indicating decreasing precipitation, this trend was not statistically significant at 95 percent significant level. The results indicate that the southeastern part of Iran has recently experienced a climate change of negative precipitation trend. Mapping trend statistics did not show any geographical orientation. Considering the global warming and rising temperatures, evident in the study area, the adverse effects of decreasing precipitation on temperature, the adverse effects of decreasing precipitation in conjunction with significant positive trends in temperature rise may lead to severe ecological and economic problems in the study area. The frequently occurring droughts in this region can be due to increasing temperature and decreasing precipitation

Spatial patterns and regimes of daily precipitation in Iran in relation to large-scale atmospheric circulation

The relationships between large-scale atmospheric circulation types and seasonal regimes of daily precipitation over Iran are assessed using daily precipitation from a high-resolution gridded dataset provided by the Asian Precipitation-Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE) Project. Regional spatial modes of daily precipitation variability were identified by S-mode Principal Component Analysis (PCA) with Varimax rotation, applied to the subset of days when at least 10% of all grid-points over Iran received precipitation ≥ 5 mm. The study refers to the period 1961-2004 and is carried out for each season (excluding summer) separately. To characterize the dynamical features associated with each regional precipitation regime (PR), composites of daily atmospheric fields are computed by only averaging days with rotated PCA scores ≥ 1.5 (strong positive phase). In autumn and winter, Iran is divided into five PRs, while four PRs are identified in spring. Results suggest that the spatial distribution of precipitation over Iran is largely governed by the geographical position of both the mid-tropospheric trough over the Middle East and the Arabian anticyclone. In fact, in almost all PRs, the trough, as a pre-conditioning factor, leads to regional-scale ascending motions, whereas the Arabian anticyclone induces low-tropospheric moisture transports from southern water bodies into the cyclonic systems near Iran, triggering rain-generating conditions. © 2011 Royal Meteorological Society

Atmospheric circulation types and winter daily precipitation in Iran

The relationship between daily large-scale atmospheric circulation types (CTs) and wintertime daily precipitation over Iran during the period 1965-2000 is investigated. Twelve atmospheric CTs identified in a previous study, which applied the K-means clustering technique to the rotated principal components (RPCs) of the 500 hPa geopotential height fields, are also considered in this study. The leading spatial modes of daily precipitation variability over Iran are extracted by a PC analysis, with Varimax rotation, applied to the APHRODITE (Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of the Water Resources) gridded precipitation dataset; six Iranian sub-regions with independent precipitation variability are identified. The relationships between the CTs and the daily precipitation are investigated by computing: (1) the spatial patterns of the performance index (PI) for each CT and (2) the cross tabulations between the frequencies of occurrence of the CTs and the RPC scores of the daily precipitation, associated with each of the six sub-regions. Results suggest that two particular CTs affect the precipitation occurrence over most of the country, while the remaining ten provide more regional or negligible contributions to precipitation. The more (less) influencing CTs in each precipitation sub-region are then identified and a characterization of the main large-scale atmospheric features governing the winter precipitation fields is provided

Spatial patterns and temporal trends of precipitation in Iran

Spatial patterns of monthly, seasonal and annual precipitation over Iran and the corresponding long-term trends for the period 1951-2009 are investigated using the Global Precipitation Climatology Centre gridded dataset. Results suggest that the spatial patterns of annual, winter and spring precipitation and the associated coefficients of variation reflect the role of orography and latitudinal extent between central-southern arid and semi-arid regions and northern and western mountainous areas. It is also shown that precipitation occurrence is almost regularly distributed within the year in northern areas while it is more concentrated in a few months in southern Iran. The spatial distribution of Mann-Kendal trend test (Z statistics) for annual precipitation showed downward trend in north-western and south-eastern Iran, whereas western, central and north-eastern exhibited upward trend, though not statistically significant in most regions. Results for winter and autumn revealed upward trend in most parts of the country, with the exception of north-western and south-eastern where a downward trend is observed; in spring and summer, a downward trend seems to prevail in most of Iran. However, for all seasons the areas where the detected trend is statistically significant are limited to a few spot regions. The overall results suggest that the precipitation is decreasing in spring and summer and increasing in autumn and winter in most of Iran, i.e. less precipitation during the warm season with a consequent intensification of seasonality and dryness of the country. However, since the detected trends are often not statistically significant, any stringent conclusion cannot be done on the future tendencies. © 2013 Springer-Verlag Wien