International Journal of Climatology (10970088)42(4)pp. 2039-2064
Satellite remote-sensing products with high spatial and temporal resolution are viable sources of precipitation information, especially for data-sparse and remote regions. The aim of this study is to examine the performance of four precipitation products including Integrated Multi-satellite Retrievals for GPM (GPM IMERG), Tropical Rainfall Measuring Mission (TRMM 3B43), Climate Hazards Centre InfraRed Precipitation with Station data (CHIRPS), and European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) in estimating precipitation and capturing meteorological droughts over Iran for the time span from 2001 to 2019. For this aim, a ground-based gridded precipitation dataset was constructed over the country using a dense network of quality-controlled rain gauges as a reference dataset. Different statistical metrics including the correlation coefficient (CC), the bias, the relative bias, and the root mean square error (RMSE) were applied to evaluate the performance of the products. The results suggest that GPM IMERG and TRMM 3B43 outperform CHIRPS and ERA5 in capturing the spatial distribution of precipitation and meteorological drought events across the country. The estimates of precipitation from the four products are seasonally influenced, with the least accurate precipitation estimates during summer season over the southern shores of the Caspian Sea. The GPM IMERG and TRMM 3B43, with higher CC and lower RMSE, show better performance in detecting drought events at both short and long time scales while the CHIRPS demonstrates the least accuracy. Spatially, all of the products show the best performance in identifying drought events over western and southwestern regions. © 2021 Royal Meteorological Society
Theoretical and Applied Climatology (14344483)150(1-2)pp. 389-403
The recent droughts in Iran have contributed to declining runoff, diminishing lake water levels, and rising salt levels due to lower runoff. This study aims to quantify how the recent changes affected to investigate the trend of land surface albedo in Iran between 2000 and 2018. Accessing field data from the Iran is difficult, and thus the common understanding of climate change in the region is strongly based on satellite data. We use remotely sensed data of land surface albedo, land surface temperature (LST), number of snow-covered days (SCDs), normalized difference vegetation index (NDVI), and the land cover type, obtained from Moderate Resolution Imaging Spectroradiometer (MODIS). The results show decreasing trends in albedo and SCDs by − 0.02 and − 0.52, respectively, and upward trends in the LST and NDVI data by 0.07 °C and 0.009, respectively. Due to the recent drought condition in Iran, SCDs decreased significantly, which might explain the reason behind the albedo decreases in winter time in Iran. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
Climate Research (16161572)84pp. 59-73
Climate change can manifest in many ways, including impacts on the start, end, and duration of the frost-free season. We examined the climatology and variability of the first fall frost day (FFFD), last spring frost day (LSFD), and length of the frost-free season (LFFS) across Iran for the period 1978-2017. Trend analysis revealed that FFFD shifted later by 6.4 d over the study period while LSFD shifted earlier by slightly over 2 wk, and LFFS is now >3 wk longer than it was only 4 decades ago. Since land-use changes around meteorological stations may affect the temperature measured at these stations (especially the magnitudes of nocturnal cooling rates), atmospheric thickness changes, which reflect temperature changes and are independent of stationbased measurements, were used as a secondary dataset to investigate minimum temperature trends. The analysis revealed a very strong relationship between frost-related indices and atmospheric thickness. Sequential Mann-Kendall statistical analysis revealed abrupt changes in the applied frost-related indices, minimum temperatures, and atmospheric thicknesses. The first abrupt changes in FFFD and LFFS occurred around 1996, which matched the timing of abrupt changes in atmospheric thickness over Iran. Interestingly, seasonal trend analyses of minimum temperature over the Northern Hemisphere using Era5 reanalysis data indicated consistent regional patterns of warming over the last 4 decades. The results suggest that the increase in LFFS is largely driven by regional-scale warming as opposed to local urbanization and/or land-use changes. Our results document an important and ongoing change of potentially considerable interest to agriculturalists in Iran and elsewhere. © 2021 Inter-Research. All rights reserved.
Advances in Space Research (02731177)66(9)pp. 2094-2112
The goal of this study is to examine the capability of the TRMM 3B42 product to detect spatial and temporal patterns in extreme precipitation events over southwestern Iran during the period of 1998–2016. A ground-based gridded precipitation dataset was created using a dense network of surface observations for the evaluation process. Various extreme precipitation indices in the three categories of fixed threshold indices, grid-related threshold indices, and non-threshold indices were examined and compared with the ground-based gridded precipitation dataset. The findings suggest that the TRMM 3B42 product is able to capture the spatial and temporal behavior of many extreme indices especially for fixed and non-threshold indices. In terms of the spatial error metrics, the satellite product has better performance over mid-elevated areas in the south and southeastern parts of the study region. © 2020 COSPAR
Climate Research (16161572)82pp. 55-73
Characterizing the errors in satellite-based precipitation estimations for drought monitoring is of great importance, as these estimations provide both spatially and temporally complete records. The aim of this study was to evaluate satellite-based quantitative precipitation estimates to monitor meteorological drought in southwestern Iran. The reliability of the Tropical Rainfall Measuring Mission Version 7 products (3B42 and 3B43) in estimating the standardized precipitation index (SPI) was evaluated against a ground-based gridded precipitation dataset at 0.25° spatial resolution for 1998−2016. The analysis conducted for the SPI at various time scales revealed that both products (3B42 and 3B43) are capable of capturing the spatial and temporal behavior of drought events over the study region, with the best performance at SPI6. 3B43 is also more efficient in the identification of shorter severe drought events compared to 3B42. The findings suggest that both satellite products, particularly 3B43, are suitable to be used directly for SPI computation in the region for drought monitoring and early warning in terms of the accuracy and the spatial and temporal resolutions they provide. © Inter-Research 2020 · www.int-res.com
Iranian Journal of Geophysics (20080336)13(2)pp. 26
All objects whose temperature exceeds absolute zero (-273°C) can emit energy. The amount of energy emitted from the objects depends on their temperature and can be measured according to Stephan-Boltzmann's law. The maximum emission of this energy is at a certain wavelength defined by Planck's law. Regarding the surface temperature of the sun, it emits maximum energy at a wavelength of 0.48 microns, in the middle of visible waves, while the Earth emits its maximum energy at 10 microns (infrared) wavelengths. This radiation which starts from 3 microns and continues to 100 microns (infrared), is known as Outgoing Long Radiation (OLR). Measuring this radiation is very important for understanding the energy balance and the temperature of the Earth. Because of the difficulties in measuring this radiation, the use of remote sensing data can effectively help in understanding the tempo-spatial variations of OLR. The purpose of this study is to estimate the seasonal trend of Iran's outgoing longwave radiation by using National Oceanic and Atmospheric Administration (NOAA) satellites. In this study, the daily mean outgoing longwave radiation data for the period 1988/3/21 to 2018/3/20, with 1° spatial coverage, was extracted on a global scale from the United States Climate Data Record (CDR) database. Then, based on nearly 700 million pixels, the seasonal mean of Iran's outgoing longwave radiation was calculated for each year, and a time-space matrix was obtained with dimensions of 154*30, for each season. The rows of the matrix are locations (pixels) and the columns are the time (season). For each season of the year, the nonparametric test of Mann-Kendall was calculated at a confidence level of %90 for each individual pixel. The results showed that there was no negative trend in different seasons in Iran, and only in winter, Iran's territory has an extensive positive trend. Hence, the outgoing longwave radiation does not show trends in other seasons of the year. The positive trend of the outgoing longwave radiation during winter is due to cloudiness and snow in most of Iran. Also, in this study, the long-term mean outgoing longwave radiation pattern of Iran was calculated for each season, separately. Findings of the long-term mean of the seasons showed that outgoing longwave radiation depends on latitude and topography of the earth. So, the highest outgoing longwave radiation is seen in low and flat latitudes (especially in summer) and the lowest one is seen in high and uneven latitudes(especially in winter). © 2019 Iranian Geophyisical Society. All rights reserved.
Advances in Space Research (02731177)62(9)pp. 2418-2430
We analyzed three-hourly TRMM precipitation data for Iran over the period 1998–2013. During the winter season when cyclonic storms dominate the precipitation, 66% of the country does not display a significant diurnal cycle in precipitation; however, the more mountainous portions of the country display a diurnal cycle with the time of maximum occurring near 12.50 LST. During the spring season when convective precipitation dominates, 55% of the country has a significant diurnal cycle in precipitation with a time of maximum near 15.50 LST; the result clearly shows the convective nature of the precipitation in this season. In summer season, only the northern and southern regions of the country receive much precipitation with most of it occurring between 15.50 and 18.50 LST, with the pattern being strongest in the southern areas. In fall season 42% of the country displays a significant diurnal cycle in precipitation. In this season, south regions of the country have their maximum precipitation frequency between 12.50 and 15.50 LST. Nearly identical patterns exist for precipitation amounts when compared to frequency. © 2018 COSPAR
Water (Switzerland) (20734441)9(12)
The Karoon River Basin, with an area of about 67,000 km2, is located in the southern part of Iran and has a complex mountainous terrain. No comprehensive study has been done on the spatial and temporal variations of snow cover in this region to date. In this paper, daily snow data of Moderate Resolution Imaging Spectroradiometer MODIS Terra (MOD10A1) and MODIS Aqua (MYD10A1) were examined from 1 January 2003 to 31 December 2015, to analyze snow cover variations. Due to difficulties created by cloud cover effects, it was crucial to reduce cloud contamination in the daily time series. Therefore, two common cloud removal methods were applied on the daily data. The results suggested that in winter nearly 43% of the Basin's area experienced a negative trend, while only 1.4% of the Basin had a positive trend for snow-covered days (SCD); trends in fall and spring were less evident in the data. Using a digital elevation model of the Basin, the trends of SCD in 100 m elevation intervals were calculated, indicating a significant positive trend in SCD during the fall season above 3500 m. © 2017 by the authors.
Atmospheric Research (01698095)169pp. 96-101
We analyzed spatial and temporal patterns in temperature extremes from 31 stations located throughout Iran for the period 1961 to 2010. As with many other parts of the globe, we found that the number of days (a) with high maximum temperatures was rising, (b) with high minimum temperatures was rising, and (c) with low minimum temperatures was declining; all of these trends were statistically significant at the 0.05 level of confidence. Population records from 1956 to 2011 at the station locations allowed us to reveal that the rate of human population growth was positively related to the increase in the number of days with high maximum temperatures and negatively related to days with low maximum temperatures. Our research shows a number of identifiable anthropogenic signals in the temperature records from Iran, but unlike most other studies, the signals are stronger with indices related to maximum, not minimum, temperatures. © 2015 Elsevier B.V.
Indian Journal of Science and Technology (discontinued) (09746846)9(40)
Objectives: The purpose of this study is to find the relationships of snow-covered days (SCDs) with topographic variables such as elevation, slope and aspect by using MODIS data. Methods/Statistical Analysis: MODIS data were used from 1 January 2003 to 31 December 2015. Due to cloud contamination in the daily data of MODIS snow products, it is not reasonable to use the data without any processing aimed at reducing cloud blockage. To reduce cloud cover effect, the daily data of MOD10A1 and MYD10A1 were combined and a three day filtering technique was applied to further reduce cloud cover effect. Findings: 1) The relationship of SCDs with elevation is not necessarily a linear relation; 2) The slope value of 22° is the critical slope in the Basin above which the snow accumulation decreases; and 3) The most SCDs are on the N and NE facing slopes and the least SCDs are on the SW facing slopes. Application/Improvements: The study showed that the slopes steeper than 22 degree are not suitable for snow accumulation. So in a country like Iran that is 3 degree Celsius warmer than the globe and snowfall frequency is dramatically low and this may be considered as a new restriction to accumulation of snow in high altitudes of the country.
Advances In Meteorology (16879317)2016
We investigate trends in extreme precipitation in Iran for 1951-2007 using the recently released APHRODITE daily rainfall time series. We find that seven different indices of extreme precipitation all show an upward trend through the study period. The seven different precipitation indices include annual precipitation total, number of days above a certain threshold, maximum precipitation received over a certain period of time, maximum one-day precipitation, and number of days with precipitation above the 90th percentile. A principal components analysis reveals one eigenvector explaining much of the variance in the seven indices and reveals that this component exhibits a strong upward trend for the whole of Iran. On a regional level, we find that the upward trend in extreme precipitation has a strong southwest-to-northeast gradient across the country for all the indices. We repeated all the analyses for 42 stations across the country to compare with the results from the gridded data; trends in extreme rainfall generated from the station data compare favorably with the results from the APHRODITE daily rainfall time series thereby reinforcing the robustness of our conclusions. Copyright © 2016 Robert C. Balling Jr. et al.
