Regional drying and wetting trends over Central Asia based on Koppen climate classification in 1961—2015

Central Asia(CA)is one of the most drought-prone regions in the world with complex climate regimes,it is extremely vulnerable to water scarcity.Many studies on drought in CA,as a whole,have been carried out,whereas there is a lack of studies on the drying and wetting trends of different climatic zones within CA.In this study,CA was divided into three different climatic zones based on the Koppen climate classification method,precipitation climatology,and aridity index.These were the temperate continental(Df),dry arid desert(BW),and Mediterranean continental(Ds)climatic zones.The regional drying and wetting trends during the years 1961—2015 were investigated using the monthly gridded Standardized Precipitation Evapotranspiration Index(SPEI).The empirical orthogonal function(EOF)was applied to analyze spatial and temporal variation patterns.EOF mode 1(EOF1)analysis found increasingly wet conditions throughout CA over the duration of the study,and EOF mode 2(EOF2)analysis found a contrast between northern and southern CA:as Df became drier and BW and Ds became wetter.EOF mode 3(EOF3)analysis found a western and eastern inverse phase distribution.The SPEI displayed a decreasing trend from 1961 to 1974 for CA as a whole,before increasing from 1975 to 2015,with a particularly significant increase over the first seven years of that period.On a regional scale,the BW and Ds zones experienced a wetting trend due to increased precipitation during 1961—2015,but the Df zone experienced a drying trend due to reduced evapotranspiration and an increasing temperature,particularly from 1961 to 1978.Thus,the spatio-temporal patterns in dryness and wetness across CA can be categorized according to climatic regions.

Evaluation of the integrated multi-satellite retrievals for global precipitation measurement over the Tibetan Plateau

The availability of high-resolution satellite precipitation measurement products provides an opportunity to monitor precipitation over large and complex terrain and thus accurately evaluate the climatic,hydrological and ecological conditions in those regions.The Global Precipitation Measurement(GPM)mission is an important new program designed for global satellite precipitation estimation,but little information has been reported on the applicability of the GPM’s products for the Tibetan Plateau(TP).The object of this study is to evaluate the accuracy of the Integrated Multi-Satellite Retrievals for GPM(IMERG)Final Run product under different terrain and climate conditions over the TP by using 78 ground gauges from April 2014 to December 2017.The results showed the following:(1)the 3-year average daily precipitation estimation in the IMERG agrees well with the rain gauge observations(R^2=0.58,P<0.01),and IMERG also has a considerable ability to detect precipitation,as indicated by a high probability of detection(78%-98%)and critical success index(65%-85%);(2)IMERG performed better at altitudes from 3000 m to 4000 m with a small relative bias(RB)of 6.4%.Precipitation change was not significantly affected by local relief;(3)the climate system of the TP was divided into four climate groups with a total of 12 climate types based on the K?ppen climate classification system,and IMERG performed well in all climate types with the exception of the arid-desert-cold climate(Bwk)type.Furthermore,although IMERG showed the potential to detect snowfall,it still exhibits deficiencies in identifying light and moderate snow.These results indicate that IMERG could provide more accurate precipitation data if its retrieval algorithm was improved for complex terrain and arid regions.

An Assessment of Changes in Bioclimatic Types in Sichuan Province, 1961-2010

Assessing the impact of climate change is important for ecosystem conservation and plant recovery, especially in climate sensitive regions. Various studies suggested that the KSppen classification is an effective method to depict climate change. However, these studies were restricted to large scales or of limited accuracy due to uncertainties in climate model projections. In addition, the impact of elevation on the shift of climate zones, as compared with other factors, is less emphasized. To address these issues we compiled the KSppen Climate Classification （period 1961-2olo） for the study area, Sichuan Province, China. The spatial resolution was selected as x km x x km. Sichuan Province may be characterized by 3 main climate classes and 1o subtypes. The east-west gradient of the climatic regimes in Siehuan is represented by the main climate classes, warm temperate climates （C）, snow climates （D） and polar climates （E）, at which the most abundant class is C. The most abundant subtype is snow climate with dry winter and cool summer （Dwe）. Shifts in K/Sppen climate classes reflect the observed trend of increasing temperature. Finally, the elevation showed an obvious impact on the distribution and the change of climate classes in Siehuan Province. The shift of areas covered by KSppen climate classes increases with elevation.

Epidemiological features of seasonal influenza transmission among 11 climate zones in Chinese mainland

Background Previous studies provided some evidence of meteorological factors influence seasonal influenza transmission patterns varying across regions and latitudes. However, research on seasonal influenza activities based on climate zones are still in lack. This study aims to utilize the ecological-based Koppen Geiger climate zones classification system to compare the spatial and temporal epidemiological characteristics of seasonal influenza in Chinese mainland and assess the feasibility of developing an early warning system.Methods Weekly influenza cases number from 2014 to 2019 at the county and city level were sourced from China National Notifiable Infectious Disease Report Information System. Epidemic temporal indices, time series seasonality decomposition, spatial modelling theories including Moran’s/ and local indicators of spatial association were applied to identify the spatial and temporal patterns of influenza transmission.Results All climate zones had peaks in Winter-Spring season. Arid, desert, cold (BWk) showed up the first peak. Only Tropical, savannah (Aw) and Temperate, dry winter with hot summer (Cwa) zones had unique summer peak. Temperate, no dry season and hot summer (Cfa) zone had highest average incidence rate (IR) at 1.047/100,000. The Global Moran’s/ showed that average IR had significant clustered trend (z = 53.69,P < 0.001), with local Moran’s/ identified high-high cluster in Cfa and Cwa. IR differed among three age groups between climate zones (0-14 years old:F = 26.80,P < 0.001;15-64 years old:F = 25.04,P < 0.001;Above 65 years old:F = 5.27,P < 0.001). Age group 0-14 years had highest average IR in Cwa and Cfa (IR= 6.23 and 6.21) with unique dual peaks in winter and spring season showed by seasonality decomposition.Conclusions Seasonal influenza exhibited distinct spatial and temporal patterns in different climate zones. Seasonal influenza primarily emerged in BWk, subsequently in Cfa and Cwa. Cfa, Cwa and BSk pose high risk for seasonal influenza epidemics. The research finds will provide scientific evidence for developing seasonal influenza early warning system based on climate zones.