An exploration of the aerosol indirect effects in East Asia using a regional climate model

A regional climate model (RegCM4) was used to project the potential evapotranspiration (PET) of Egypt under two future scenarios: RCP45 and RCP85. Spatially, the RegCM4 has a higher PET under the RCP85 than the RCP45. Among all locations, the RegCM4 was able to capture the monthly variability in PET with respect to the Climate Research Unit (CRU). In addition, the simulated PET was notably improved when a linear regression model (LRM) was used. Further, future PET projects a strong increased trend under the RCP85; meanwhile, future PET projects a weak increased trend under the RCP45.

Large concentrations of air-suspended particulate matter (PM) in megacities represent an important health risk for their populations, but PM time series are often missing or too short to quantify the associated burden of diseases. In this study, we propose a model for retrieving the surface PM in Cairo (Egypt) and Delhi (India) from the automated measurements of aerosol optical depth (AOD), precipitable water (PW), and Angström exponent (AE) performed by the sunphotometers of the Aerosol Robotics Network (AERONET). For this we exploit the (1) synchronous measurements performed from 2010 to 2015 at the headquarters of the Egyptian Meteorological Authority and in 2009 at the Gual Pahari station (25 km south of Delhi) and (2) the ERA5 estimate of the planetary boundary layer height (H). The correlation between the surface PM10 and the AOD is primarily controlled by the variations of PW and secondarily by those of H: for similar surface PM10 concentrations, the AOD tends to be the largest in summer because of the hygroscopic enhancement of the mass extinction efficiency (σ) of the particles and their dilution in the more developed mixing layer. The variations of composition also play a significant role in Cairo. This effect, particularly marked in spring (coinciding with the dust season), can be parameterized as a linear function of AE. Finally, we show that the variations of the surface PM10 concentration at the two sites can be retrieved simply from those of the AOD, PW, AE and H. At the weekly temporal resolution, the agreement between the model and the observations is very good at the two locations (correlation coefficient > 0.81, relative mean absolute error < 15%). This validates indirectly the assumption made in the development of the model, namely that the aerosols are mostly confined to the mixing layer of the two megacities and not transported in the free atmosphere. Provided a few years of surface PM measurements are available, the methodology proposed in this study could be easily applied to any other AERONET station.

The Weather Research and Forecasting model (WRF) offers a number of physical options that let users modify it to different scales, regions, and applications. The aim of this study is to test the sensitivity of different physics schemes in the WRF model for rainfall events over Iraq. In this study, six different physics configurations of the climate version of WRF were evaluated for simulation of a rainfall event in Iraq. Possible combinations among two Planetary Boundary Layers (PBL), three Cumulus (CUM) and two Microphysics (MIC) schemes were tested. The study area is the region surrounded by the longitudes 35o E-55o E and latitudes 290o N–38o N, which typically includes the Iraq region. The WRF model is installed on a Linux platform with a 10 km grid size in the zonal and meridional directions. For the six different simulations and the process of choosing the best performing configuration for the Iraq region, the model outputs tested for a single grid point (Baghdad station) of the atmospheric parameters (temperature, pressure and total precipitation) with modeled data and ECMWF. Model outputs using statistical methods: Bias Error (BE), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The results show All the simulations predict rainfall with values close to the actual but it was discovered that the cloud microphysics setup had the greatest impact on temperature biases, whereas the cumulus parameterization setup has the greatest impact on precipitation.

Background: Snow forms when tiny ice crystals in clouds stick together to become snowflakes. If enough crystals stick together, they become heavy enough to fall to the ground. Where background includes Precipitation falls as snow when the air temperature is below 2 °C (275.15 K). The falling snow does begin to melt as soon as the temperature rises above freezing, but as the melting process begins, the air around the snowflake is cold. Objective: It is a myth that it needs to be below 0 °C (273.15) K to snow. In Iraq, the heaviest snowfalls tend to occur when the air temperature is between (273.15-275.15) K (0-2) °C. Methods: The data for this study, which includes Temperature (T), Snow Albedo (SA), and Snow Density (SD) as monthly-daily mean, taken from the European Center for Medium-Range Weather Forecasts (ECMWF) for fifteen years from 2008 to 2022 for several selected stations over northern Iraq. The method was to take the monthly rates of snow density, snow albedo, and temperature for the stations of Erbil, Sulaymaniyah, Zakho, Dohuk, and Amadiyah, and the type of relationship and strength of the connection between them was also known. Results: The study found an inverse relationship between snow albedo and snow density across the selected stations, indicating that an increase in snow density leads to a decrease in snow albedo. Notably, Duhok City exhibited the strongest relationship between snow albedo and density, with a regression coefficient of 0.9699 compared to other regions. Conclusions: This study highlights the complex relationship between snow albedo and density in northern Iraq. The strong correlation observed in Duhok City suggests the importance of further research to understand the factors influencing snow properties in this region.