Comparative Analysis of the Mechanisms of Intensified Summer Warming over Europe-West Asia and Northeast Asia since the Mid-1990s through a Process-based Decomposition Method

Previous studies have found amplified warming over Europe-West Asia and Northeast Asia in summer since the mid- 1990s relative to elsewhere on the Eurasian continent, but the cause of the amplification in these two regions remains unclear. In this study, we compared the individual contributions of influential factors for amplified warming over these two regions through a quantitative diagnostic analysis based on CFRAM (climate feedback-response analysis method). The changes in surface air temperature are decomposed into the partial changes due to radiative processes (including CO2 concentration, incident solar radiation at the top of the atmosphere, surface albedo, water vapor content, ozone concentration, and clouds) and non-radiative processes (including surface sensible heat flux, surface latent heat flux, and dynamical processes). Our results suggest that the enhanced warming over these two regions is primarily attributable to changes in the radiative processes, which contributed 0.62 and 0.98 K to the region-averaged warming over Europe-West Asia (1.00 K) and Northeast Asia (1.02 K), respectively. Among the radiative processes, the main drivers were clouds, CO2 concentration, and water vapor content. The cloud term alone contributed to the mean amplitude of warming by 0.40 and 0.85 K in Europe-West Asia and Northeast Asia, respectively. In comparison, the non-radiative processes made a much weaker contribution due to the combined impact of surface sensible heat flux, surface latent heat flux, and dynamical processes, accounting for only 0.38 K for the warming in Europe-West Asia and 0.05 K for the warming in Northeast Asia. The resemblance between the influential factors for the amplified warming in these two separate regions implies a common dynamical origin. Thus, this validates the possibility that they originate from the Silk Road pattern.

Investigating the Effect of Climatic Factors of Roshtkhar Town (Khorasan Razavi, Iran) on the Development and Cultivation of Pistachio Using GIS Software

The use of Geographic Information System (GIS) has significantly helped managers provide optimal models of sustainable agricultural development, identify local features related to agricultural production and their proper zoning, identify agricultural needs and constraints and finally provide the appropriate structure of land use. The main purpose of this study was to determine areas capable of cultivating Pistachio according to the parameters affecting the Pistachio cultivation in Roshtkhar town. Statistics of meteorological stations of the town were taken from Meteorology Organization of Khorasan Razavi for the period of 1989-2010 in order to determine climatic parameters required to cultivate Pistachio. For mapping surface elevation, slope, aspect, and TIN of the geographic organization of armed forces with a scale of 1:250,000 topographic maps were used. For mapping vegetation and land use in the area under study, land capability map of the area on a scale of 1:250,000 from the institute of soil and water was used. Also information on cultivation and annual production of agricultural statistics, published by Agriculture was used. Finally, it was concluded that the northeast and southwest of Roshtkhar town are the most prone areas to cultivate Pistachio.

Assessing 10 Satellite Precipitation Products in Capturing the July 2021 Extreme Heavy Rain in Henan, China

On 20 July 2021,a sudden rainstorm happened in central and northern Henan Province,China,killing at least 302people.This extreme precipitation event incurred substantial socioeconomic impacts and resulted in serious losses.Accurate monitoring of such rainstorm events is crucial.In this study,qualitative and quantitative methods are used to comprehensively evaluate the abilities of 10 high-resolution satellite precipitation products[CMORPH-Raw(Climate Prediction Center morphing technique),CMORPH-RT,PERSIANN-CCS(Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks),GPM IMERG-Early(Integrated Multisatellite Retrievals for Global Precipitation Measurement),GPM IMERG-Late,GSMaP-Now(Global Satellite Mapping of Precipitation),GSMaP-NRT,FY-2F,FY-2G,and FY-2H]in capturing this extreme rainstorm event,as well as their performances in monitoring different precipitation intensities.The results show that these satellite precipitation products are able to capture the spatial distributions of the rainstorm(e.g.,its location in central and northern Henan),but all products have underestimated the amount of precipitation in the rainstorm center.With the increase in precipitation intensity,the hit rate decreases,the threat score decreases,and the false alarm rate increases.CMORPH-RT is better at capturing the rainstorm than CMORPH-Raw,and it depictes the rainstorm process well;GPM IMERG-Late is more accurate than GPM IMERG-Early;GSMaP-NRT has performed better than GSMaP-Now;and PERSIANNCCS and FY-2F perform poorly.Among the products,CMORPH-RT performs the best,which has accurately captured the center of the rainstorm,and is also the closest to the station-based observations.In general,the satellite precipitation products that integrate infrared and passive microwave data are found to be better than those that only make use of infrared data.The satellite precipitation retrieval algorithm and the amount of passive microwave data have a relatively greater impact on the accuracy of satellite precipitation products.