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Estimation of evapotranspiration, representing a highly sensitive variable to global warming, is often required in water resources and agricultural studies. This study explores the possible effects of climate change on evapotranspiration (ETo) across Iran. The ETo was computed using the Penman‐Monteith Temperature (PMT) method that requires only minimum and maximum temperature (Tmin and Tmax), provided by the NASA Earth Exchange Global Daily Downscaled Projections dataset (NEX‐GDDP) with a 0.25° × 0.25° spatial resolution. Accuracy of the NEX‐GDDP Tmin and Tmax were evaluated against ground truth observations at 41 synoptic weather stations distributed across the country using a set of statistical measures, including the coefficient of determination (R2) and Nash‐Sutcliffe Efficiency (NSE). Similarly, the PMT estimated evapotranspiration based on the NEX‐GDDP Tmin and Tmax (ETo‐GDDP) were statistically evaluated against the ETo computed with observed variables at selected stations (ETo‐obs). Then, at each grid cell, the 45‐years ETo‐GDDP time series was partitioned into three 15‐years subperiods such that the differences between three subperiods were computed and inter‐compared. Furthermore, annual, seasonal, and monthly ETo time series trends of each cell were evaluated using the Mann–Kendall trend test (MK) while the corresponding change rates were estimated using Theil–Sen's slope estimator (TSSE). The results demonstrated a good agreement between ETo‐GDDP and ETo‐obs with R2 greater than 0.8 and NSE greater than 0.7 in 90.2% and 65.8% of the stations, respectively. The maps of differences between the three subperiods showed negligible changes in ETo between 1975–1990 and 1950–1975 subperiods. The spatial patterns of annual and seasonal MK statistics showed a significant increasing trend in most parts of Iran. On seasonal scale, the highest and lowest ETo changes were observed in spring (0.00035–0.0045) and in autumn (0.0005–0.0015), respectively. [ABSTRACT FROM AUTHOR]

Monthly precipitation time series of 155 synoptic stations distributed over Iran, covering 1990–2014 time period, were used to identify areas with different precipitation time variability and regimes utilizing S-mode principal component analysis (PCA) and cluster analysis (CA) preceded by T-mode PCA, respectively. Taking into account the maximum loading values of the rotated components, the first approach revealed five sub-regions characterized by different precipitation time variability, while the second method delineated eight sub-regions featured with different precipitation regimes. The sub-regions identified by the two used methods, although partly overlapping, are different considering their areal extent and complement each other as they are useful for different purposes and applications. Northwestern Iran and the Caspian Sea area were found as the two most distinctive Iranian precipitation sub-regions considering both time variability and precipitation regime since they were well captured with relatively identical areas by the two used approaches. However, the areal extents of the other three sub-regions identified by the first approach were not coincident with the coverage of their counterpart sub-regions defined by the second approach. Results suggest that the precipitation sub-region identified by the two methods would not be necessarily the same, as the first method which accounts for the variance of the data grouped stations with similar temporal variability while the second one which considers a fixed climatology defined by the average over the period 1990–2014 clusters stations having a similar march of monthly precipitation. [ABSTRACT FROM AUTHOR]

Large-scale atmospheric circulations associated with 133 moderate to heavy cold-weather precipitation events recorded at Mehrabad station in Tehran, Iran, during the period 1951–2013 are analysed. To this end, the performance of un-rotated, orthogonally rotated and obliquely rotated solutions of T-mode principal component analysis (PCA) is examined in classifying the atmospheric circulations into a few representative circulation types (CTs). The T-mode PCAs were applied to the 500-hPa geopotential height for the events in a domain from 10∘E to 70∘E and from 20∘N to 50∘N. The first six leading principal components were retained and then orthogonally and obliquely rotated using varimax and promax solutions, respectively. Statistical inter-comparison of the CTs obtained using the three solutions suggests that the obliquely rotated solution is the better choice for circulation classification in the present study. The six CTs obtained using the oblique rotation were then linked to the daily total precipitation and daily mean temperature variability at Tehran station as well as to the standardized anomalies of the daily total precipitation and mean daily temperature of a dense network of stations distributed across Iran. It is found that the CTs identified, though generally comparable in producing significant precipitation in Tehran, vary in their potential to bring cold weather and generate snowfall in Tehran specifically and in the country in general. While the first three CTs give rise to regional patterns of standardized precipitation anomalies centred in Tehran, the next three CTs leave a pronounced precipitation signature almost across the whole country. As regards the standardized temperature anomalies, with the exception of one CT that causes deep and widespread negative standardized anomalies over most parts of the country, the other CTs are characterized with a dipolar structure of a deep intrusion of cold weather to the west and prevailing warm weather to the east of the country. [ABSTRACT FROM AUTHOR]

ABSTRACT Computing crop reference evapotranspiration ( ETo) with the FAO Penman-Monteith method ( PM-ETo) requires maximum and minimum air temperature, shortwave radiation, relative air humidity and wind speed. These data are often not available, thus requiring alternative computation procedures. Although some proposed approximations may provide ETo values with small estimation errors, the physics of the ET processes may then not be well described. The use of reanalysis data, which is common in climate studies, represents an alternative to observation data for the weather variables referred above, when these are not available. This study focuses on the use of the National Center for Environmental Prediction/National Center for Atmospheric Research ( NCEP/ NCAR) blended reanalysis products with gridded data sets for the computation of PM-ETo in the Iberian Peninsula. A monthly time step was adopted. The PM-ETo time series computed with the blended reanalysis data sets were compared with those obtained using observations for 130 weather stations in the Iberian Peninsula. Results show that the PM-ETo computed with blended reanalysis compares well with the series computed from observation data (average root mean square error, RMSE = 0.49 mm day−1). The weather variables derived from reanalysis were also compared with observation data. Results supported the quality of ETo computations because, overall, there was a good match between solar radiation (average RMSE = 1.76 MJm−2 day−1) and maximum temperature (average RMSE = 1.48 °C) derived from reanalysis and in situ observations. By contrast, the wind speed from reanalysis highly overestimated observations and this is likely a reason for the slight overestimation of ETo computed from reanalysis (percentage bias, PBIAS>20% in 89% of cases). In addition, the reanalysis products are apparently influenced by modelled warming, which contributes to overestimation of the minimum temperature and, to a lesser extent, of the relative humidity. The spatial pattern of accuracy indicators reveals that poorer results correspond to the southern and south-eastern coastal areas of Iberia, where climate is semi-arid. The compatibility of the PM-ETo computed with monthly inputs and of the daily ETo cumulated to the month using the PM-ETo equation was confirmed, thus allowing to extend conclusions of this study to daily computations. Alternative reanalysis products were also assessed. Tests for ERA-Interim reanalysis products revealed overestimation of ETo and those for NCEP/ NCAR Reanalysis II have shown large underestimation. Results suggest that the blended reanalysis products are suitable for the estimation of ETo in Iberia since they integrate an appropriate correction of radiation and temperature, which proved essential for the good estimation results obtained. [ABSTRACT FROM AUTHOR]