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In this paper, we employed an autoregressive integrated moving average (ARIMA) model to simulate aerosol optical depth time series from the ground-based AErosol RObotic NETwork (AERONET) from 2012 to 2021. To test the validity and applicability of the developed ARIMA model, we correlated the ARIMA predicted for 2021 with AERONET network data and obtained a correlation coefficient of ~ 0.9. Additionally, we compared the results with the space-based Moderate Resolution Imaging Spectroradiometer (MODIS) data for the Middle East and obtained a considerable correlation coefficient of ~ 0.5. We employ the threshold of the Angstrom exponent (AE) as a measure of the spectral dependence of aerosol optical depth (AOD), which ranges between 0 and 1, to characterize aerosol types. The results show weighted averages of AOD ≥ 0.2 and AE ≥ 1.0 for fine-mode aerosol spray in IASBS (36.705 N, 48.507 E), AOD > 0.2 and AE < 1.0 for dust aerosols in Nes_Ziona (31.922 N, 34.789 E), AOD > 0.4, 0.5 < AE < 1.0 for dust and maritime aerosol for Masdar _Institute station (24.442 N, 54.617 E) and AE < 1, AOD ≤ 0.5 for dust and maritime aerosol in Hada_El-Sham (21.802 N, 39.729E). [ABSTRACT FROM AUTHOR]

Yemen is one of the most vulnerable states to climate change impact in the Middle East. The main objective of this study is to evaluate temperature variability of the city of Al-Hodeidah over the period 1985 to 2019 for monthly, seasonal, and annual data. These were collected from the ground station as well as from the Meteoblue dataset. The time series were analyzed using parametric and non-parametric methods to detect the trend. The annual means of temperature during the past period (1985–2019) were between 26.9 and 30.1 °C. The trend rate between 1985 and 2019 showed an increase in temperature toward a warmer climate for all months and seasons. The increasing rate of annual mean temperature is about + 0.075 °C/year, with an actual increase of about + 0.37 °C/year and + 0.75 °C/decade. At a monthly and seasonal timescale, there is a similar trend rate from December to September, with the greatest rate in November of about + 0.13; 0.11 °C/year. These significantly increasing trends are confirmed by MK statistics (significant at 0.05 level where Z1-α/2 > 1.96). This general trend obviously is related to global warming. In general, the trend across Al-Hodeidah towards a warmer climate demands more effective actions from the Yemeni government and also from the local people to be prepared for increased heat stress, increased water demand, and related adaptation needs. [ABSTRACT FROM AUTHOR]

In many parts of the world, teleconnection patterns are one of the climate phenomena that significantly change the causative climate anomalies, especially temperature and precipitation. Thus, statistical analysis and modeling of their effects are of great importance in order to understand the fluctuations and climate variability in a region. In this study, 52 teleconnection indices were utilized to perform statistical analysis and conceptual modeling as well as simulation of temperature and precipitation fluctuations in Iran. For this purpose, temperature and precipitation data of 36 synoptic stations in Iran and 52 teleconnection indices for the period 1951–2019 were used. For the analysis, the relevant data were classified into four groups of global (GLB), regional (RGN), El Niño–Southern Oscillation (ENSO), and all indices (ALL). Then, the correlation of the aforementioned indices with temperature and precipitation was calculated using the teleconnectional–statistical model (TSM). Afterward, 5 years with the highest correlation coefficient was selected and considered as the forecasting parameters. The results revealed that the local temperature forecasting using RGN indices and the precipitation forecasting using GLB and ALL indices were more accurate than those using other indices. Our findings highlighted the prominent role of the indices with broader geographical regions that mainly were evolved across the oceans. Moreover, the effect of ENSO teleconnection on Iran climate was explained by the dynamic mechanism of the atmospheric bridge. Comparing TSM outputs and the Climate Forecast System Version 2 (CFSV2), TSM outperformed CFSV2 in the conducting experiment. Overall, the findings of this study emphasized on the existence of coincided synergy in the fluctuation or trend within almost all indices and atmospheric parameters, and most of the fluctuations in the indices occurred simultaneously or right after the ENSO events, including specific super El Niño in 1997–1998 (turning point). Also, the dramatic effect of sunspots on the average temperature of Iran is shown in inverse harmony, which is not easily revealed by correlation analysis. Also, the influence of global warming and especially synchronization with El Niño event on climatic change was briefly discussed in the Middle East. In this work, for the first time in the Middle East, physical mechanisms of how linkages affect Iran's climate and rainfall were proposed in a synoptic conceptual model. [ABSTRACT FROM AUTHOR]

Temperature and precipitation are among the most important climatic elements in the study of climate change due to significant temporal and spatial changes, and the projection of their changes is very important in environmental hazards and planning. Therefore, in this study, the future of temperature and precipitation changes in the Middle East and North Africa (MENA) region was projected. For this purpose, the data of 23 global circulation models (GCMs) from Coupled Model Intercomparison Project phase 6 (CMIP6) were used as networks under the influence of two scenarios SSP3–7.0 and SSP5–8.5 for temperature and precipitation changes in the two future periods (2020–2049 and 2050–2079) were investigated comparing to the base period (1985–2014). The results showed that the temperature will increase in both periods, which will be between 0.8 and 3.3 °C in the period 2020–2079 compared to the base period. The highest and lowest temperature changes are related to the eastern and northern regions of the study area, respectively. Projection of precipitation changes also showed that the precipitation in most of the study area will decrease in the next two periods compared to the base period, which will be between 5 and 133 mm on average. Most of its changes are related to the northern regions and in the form of a strip from Morocco to the northwest of Iran. In both studied periods, the SSP5–8.5 scenario shows the highest temperature and precipitation changes in the study area. [ABSTRACT FROM AUTHOR]