Articles
Theoretical and Applied Climatology (14344483)156(1)
This study analyzed Iran's trends and variations in annual precipitation (AP) from 1971 to 2015. The findings indicate that 80.9% of the nation’s territory has experienced a declining trend in AP, while only 19% has exhibited an increase. Notably, the pronounced decreasing trend is observed in approximately 33.53% of the country. Regions demonstrating statistically significant increasing trends represent merely 2.93% of the total area and appear as dispersed patches. The correlation coefficients (CC) between precipitation trends and geographical coordination-topographic variables (GCTV) were found to be relatively low. In contrast, the CC between AP trends and the amount of AP was more significant; suggesting that large-scale atmospheric forcing predominantly influences long-term trends. Furthermore, a slight decrease in the long-term trend of days with normal and extreme precipitation was identified. These types of precipitation, particularly those below the 10th and 25th percentile, appear to be more influenced by local geographic features than by large-scale atmospheric systems, resulting in a negligible relationship between their trends and the overarching trends in AP. The analysis delineates three distinct phases within the AP time series—1971–1982, 1983–1999, and 2000–2015—highlighting a recorded decline in national AP from the first phase to the final phase. Additionally, a decrease in the month-to-month coefficient of variation (MCV) of precipitation, which indicates a reduction in precipitation during the wet months, generally aligns with the spatial pattern of AP; however, some variability in the CC between GCTV and MCV was observed. The study suggests large-scale atmospheric forcing and the local features (e.g., elevation) play a significant role in Iran's AP trends and phases of AP in Iran. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024.
Rezaee, R.,
Maleki, A.,
Aboubakri, O.,
Safari, M.,
Masoodian, S.A.,
Darand, M.,
Godini, K.,
Goudarzi, G.,
Khosravi, A.,
Zarei, M. Air Quality, Atmosphere and Health (18739326)18(1)pp. 29-41
Satellite-based data has been currently considered as an important exposure in projection studies of climate change impact on mortality. We projected all-cause mortality attributable to heat and cold by 2099 under adaptation, population change and climate scenarios using the data, in addition to ground-based exposure. Air temperature was estimated using Land Surface Temperature (LST) in a city-specific regression model. The predicted temperature was corrected for the bias using Bland–Altman approach and observed data in each city. The bias-corrected and observed predictors were then used in a two-stage time series regression to estimate baseline city-specific and pooled associations across five cities. Combination of the dose–response association and projected temperature by RCPs and GCMs along mortality data were used in the projection analysis. The temperature was estimated to increase by 6 °C in all of the regions under the worst scenario. Based on station data and under all scenarios, the Attributable Fraction (AF) and number of deaths due to cold were higher than heat in all decades in future. Also, the uncertainty in the heat effect was low if there is no adaptation to heat especially during 2020–2050 (e.g., AF for the worst scenario of RCPs and population variant was 0.07 (Empirical CI: 0.01, 0.12)). However, both exposures showed an increasing impact (Attributable Fraction (AF) and number of deaths) of heat and decreasing impact of cold in future. Compared to station-based data, the uncertainty in heat impact using the predicted data was lower under all scenarios in all decades. Along the observed data measured by weather stations the satellite-based exposure should be addressed in the studies of the projection of climate change impact on mortality. Our findings specifically highlight the urgent need for adaptive strategies to mitigate the impacts of extreme heat events, particularly in the cities like Ilam where adaptation scenario had an important role on the projection analysis. © The Author(s), under exclusive licence to Springer Nature B.V. 2024.
Theoretical and Applied Climatology (14344483)155(1)pp. 273-288
In the present study, the precipitation regime (PR) was investigated as a feature of the structure of Iran’s climate and its relationship with spatial-topographic variables and its spatial pattern. Spatial patterns of the indices of the PR used in the present study exhibited significant agreement in illustrating the diverse PRs of Iran. The diversity of spatial factors provided the spatial diversity of precipitation characteristics, including PR. Harmonic analysis (HA) results confirmed the country’s diverse PRs, which were attributed to different mechanisms affecting Iran’s precipitation patterns throughout the year. Using multiple methods in the present study, four PRs were identified. According to the methods used, the increase in precipitation in each location was associated with a reduction in the month-to-month difference in precipitation and an enhancement in the uniform distribution of precipitation. All indices indicated that the northern regions of Iran, including the Iranian coast of the Caspian Sea (ICCS), exhibited a uniform PR. The northwestern (NWI) and southeastern (SEI) regions displayed a relatively uniform regime, while the remaining parts of the country experienced a seasonal regime characterized by a longer dry season. Furthermore, there was a notable correlation between the PR and latitude, particularly from approximately 35 degrees northward. Moreover, there was a notable correlation between the PR and latitude, particularly from approximately 35 degrees northward. As for the southern regions of the country, beyond the latitude of 35 degrees, the spatial distribution of PRs was influenced not only by latitude but also by other variables such as longitude, altitude, and the shape and length of the Persian Gulf coast adjacent to the eastern deserts. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
Theoretical and Applied Climatology (14344483)155(2)pp. 1103-1112
One of the parameters affecting albedo is snow. Therefore, the effects of snow on albedo can be a tool to understand environmental changes. Moderate Resolution Imaging Spectroradiometer (MODIS) continuously produces snow and albedo products of the land surface on a global scale and with appropriate spatial resolution and makes them available to researchers. In this study, to investigate the relationship between albedo and snow in Iran, first, the daily data of the MODIS sensor MCD43A4 and MOD10A1 products in the area of Iran in the period of 1/1/2001 to 12/30/2021 for 6770 days were downloaded from the NASA website. Since the temperature conditions for snowfall are provided from an altitude of 1700 m, was calculated the seasonal and long-term correlation between albedo and snow at altitudes above 1700 m. These altitudes, which cover 27% of Iran’s area, were known as Iran’s Mountains (Mts.). The results showed that in the winter and autumn seasons, which are known as Iran’s snowy seasons, the land surface albedo also increases with the increase in snow cover. Therefore, in these seasons, the correlation between albedo and snow over Iran’s Mts. is strongly positive. In these seasons, positive correlation covers 91 and 81% of Iran’s Mts., respectively. In spring, there is a strong positive correlation in high altitudes and a weak positive/negative correlation in low altitudes. The negative correlation in the spring season is due to the delay in the measuring time of the sensor and the conversion of precipitation from solid to liquid. In the summer season, due to the establishment of Subtropical High-Pressure Systems Azores and the increase in air temperature, the snow cover of the Mts. disappears and the albedo was expected to decrease. But with the reduction of snow cover, albedo has increased. As a result, in these seasons, the correlation between albedo and snow over Iran’s Mts. is negative. It seems that the increase in albedo in spring and especially summer is caused by the increase in the land surface temperature (LST), which requires separate research. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
