In regional studies, reanalysis datasets can extend precipitation time series with insufficient observations. In the present study, the ERA5 precipitation dataset was compared to observational datasets from meteorological stations in nine different precipitation zones of Iran (0.125° × 0.125° grid box) for the period 2000–2018, and measurement criteria and skill detection criteria were applied to analyze the datasets. The results of the daily analysis revealed that the correlation between ERA5 and observed precipitation were larger than 0.5 at 90% of stations. Also, The daily standard relative bias indicated that precipitation was overestimated in zone 6. As detection criteria, the frequency bias index (FBI) and proportion correct (PC) showed that the ERA5 data could capture daily precipitation events. Correlation confidence comparisons between the ERA5 and observational time series at daily, monthly, and seasonal scales revealed that the correlation confidence was higher at monthly and seasonal scales. The standard relative bias results at monthly and seasonal scales followed the daily relative bias results, and most of the ERA5 underestimations during the summer belonged to zone 1 in the coastal area of the Caspian Sea with convective precipitation. In addition, some complex mountainous regions were associated with overestimated precipitation, especially in northwest Iran (zone 6) in different time scales.

The numerical weather forecast model Weather Research and Forecasting (WRF) has a range of applications because it offers multiple physical options, enabling the users to optimizing WRF for specific scales, geographical locations and applications. Summer rainfall cannot be predicted well in North West of Iran (NWI). Most of them are convective. Sometimes rainfall is heavy, so that it causes flash flood. In this research, some configurations of WRF were tested with four summer rainfall events in NWI to find the best configuration. Five cumulus, four planetary boundary layers (PBL) and two microphysical schemes were combined. Twenty-six different configurations (models) were implemented at two resolutions of 5 and 15 km for duration of 48 h. Four events, with over 20 mm convective daily rainfall total, were selected at NWI during summer season between 2010 and 2015. These events were tested by developing 26 unique models. Results were verified using several methods. The aim was to find the best results during the first 24 h. Although no single configuration can be introduced for all times, thresholds, and atmospheric system to provide reliable and accurate forecast, the best configuration for WRF can be identified. Kain-Fritsch (new Eta), Betts-Miller-Janjic, Modified Kain-Fritsch, Multi-scale Kain-Fritsch and newer Tiedtke cumulus schemes and Mellor-Yamada-Janjic, Shin-Hong ‘scale-aware’, Medium Range Forecast (MRF) and Yonsei University (YSU) Planetary Boundary Layer schemes and Kessler, WRF Single Moment 3 class simple ice (WSM3) microphysics schemes were selected. The result show that Cumulus schemes are the most sensitive and Microphysics schemes are the less sensitive. The comparison of 15 km and 5 km resolution simulations do not show obvious advantages in downscaling the results. Configuration with newer Tiedtke cumulus, Mellor-Yamada-Janjic PBL, WSM3 and Kessler microphysics schemes give the best results for the 5 and 15 km resolutions. The output image of models and statistical methods verification indexes show that WRF could not accurately simulate convective rainfall in the NWI in summer.

This study provides a comprehensive evaluation of dust events over Iran, using synoptic data from 286 meteorological stations. The dust events are classified according to synoptic dust codes as suspended dust and others (i.e., blowing dust, dust storms) and based on their intensity with horizontal visibility ≤1, 3, 5, and 10 km. Severe events (visibility ≤ 1 km) of suspended dust (code 06) occurred primarily in the western parts of Iran, while blowing dust events of moderate or severe intensity dominated over the south and eastern Iran, thus revealing a contrasting spatial distribution regarding the type and frequency of dust events. Furthermore, a distinct seasonality is revealed in the number of dust events, since suspended dust maximized in SW Iran from March to July, highly associated with Shamal winds, while blowing dust storms over south and east Iran maximized from April to August. Zabol city, east Iran, and some stations along the coast of the Arabian Sea are highly impacted by this type of dust storm throughout the year. Trend analysis revealed a notable increase in frequency of dust events during the period 1994–2023, particularly in the western part of Iran, mostly attributed to transboundary dust from the Mesopotamian plains. The large increase in dust activity during 1994–2009 was followed by a decrease during the 2010s at many stations, while notable differences were observed in the spatial distribution of the trends in suspended and blowing dust. An inverse correlation between dust events and precipitation anomalies was observed, since years with abnormal precipitation (e.g., 2019; 138% increase) were related to a substantial decrease in dust occurrence. Over an 11-year period, surface dust concentrations exceeded the annual PM₁₀ threshold of 50 µg/m³ on more than 800 days, with maximum concentrations reaching up to 1411 µg/m³. This highlights the urgent need for effective management strategies to mitigate the impacts of dust storms on air quality and public health in Iran.

Dried lake beds are some of the largest sources of dust in the world and have caused environmental problems in the surrounding areas in recent decades. In the present work, we studied the monthly and annual occurrence of dust storms at selected weather stations around Urmia Lake in northwestern (NW) Iran. Furthermore, we investigated the variations in the daily aerosol optical depth (AOD at 550 nm) and the Ångström exponent (at 412/470 nm), as well as the vertical profile of the total aerosol extinction coefficient and AOD at 532 nm, using space-borne MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua and CALIPSO Satellite LiDAR data over the Urmia Lake region (36–39°N, 44–47°E). The monthly variations of AOD₅₅₀ and AOD₅₃₂ for the regions 37–39°N and 46–59°E were compared, and it was found that the CALIPSO AOD₅₃₂ and MODIS AOD₅₃₂ (reconstructed using the Ångström exponent) were in good agreement. In general, the dust storms during 2000–2021 increased the AOD₅₅₀ above average around the Urmia Lake. The vertical profile of aerosols showed that the largest contribution to total aerosol loading over the Urmia Lake was from 1.5–3 km, 1.5–4 km, 1.5–5 km, and 1.5–3 km during winter, spring, summer, and autumn seasons, respectively.

Drying lakes have become a new source of dust, causing severe problems in surrounding areas. From 2000 to 2017, a statistical study was conducted on Lake Urmia in Iran in the Middle East. The results indicated a significant increase in the annual number of dusty days in stations around the lake and the mean annual aerosol optical depth (AOD) at 550 nm. The sharp decrease in annual snowfall rate over the Lake Urmia area since 2007 has been linked to the lake’s decreasing water level and drying. During a dust storm event from 27 October to 31 October 2017, a local dust storm originated from Lake Urmia before another large-scale dust storm originated from the An-Nafud desert. According to MODIS true-color images, dust particles were lifted from Lake Urmia and transported eastward to the Caspian Sea and the HYSPLIT model. The comparison of the four models under the Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) revealed that the models overestimated surface dust concentrations compared to ground-based PM₁₀ measurements. Nevertheless, the NOAA/WRF-Chem and DREAMABOL models simulated higher dust concentrations during the dust period. More emphasis should be placed on the development of dust models for SDS-WAS models in Lake Urmia.

Dust storms create some of the most critical air quality problems in the world; the Middle East, located in the dust belt, suffers substantially from dust storms. Iran, as a country in the Middle East, is affected by dust storms from multiple internal and external sources that mostly originate from deserts in Iraq and Syria (especially the Mesopotamia region). To determine the highest dust loadings in the south and west of Iran, dust frequencies were investigated in the eight most polluted stations in the west, southwest, and southern Iran for a period of 21 years from 2000 to 2021. During the study’s duration, the dust frequency was much higher from 2008 to 2012, which coincided with severe droughts reported in Iraq and Syria; from which, we investigated two severe dust storms (as well as the dust sources and weather condition effects) that took place on 15–17 September 2008 and 1–3 June 2012; we used secondary data from ground measurement stations, and satellite and modeling products. In both cases, horizontal visibility was reduced to less than 1 km at most weather stations in Iran. The measured $P{M}_{10}$ in the first case reached 834 μg m⁻³ at Ilam station in west Iran and the Iran–Iraq borders while the measured $P{M}_{10}$ in the second case reached 4947 μg m⁻³ at Bushehr station in the northern shore of the Persian Gulf. The MODIS true color images and MODIS AOD detected the dust mass over Iraq, southern Iran, and Saudi Arabia in both cases; the AOD value reached 4 in the first case and 1.8 in the second case over the Persian Gulf. During these two severe dust storms, low-level jets were observed at 930 hPa atmospheric levels in north Iraq (2008 case) and south Iraq (2012 case). The output of the NAPPS model and CALIPSO satellite images show that the dust rose to higher than 5 km in these dust storm cases, confirming the influence of Shamal wind on the dust storm occurrences.