Determination of the Thresholds of the Climatic Classification According to the Discharges in the Upper Senegal River Basin

Floods are the most common type of natural disaster in the world and one of the most damaging.Changes in weather conditions such as precipitation and temperature result in changes in discharge.To better understand the floods and eventually develop a system to predict them,we must analyze in more detail the flow of rivers.The purpose of this article is to analyze the discharges in the upper Senegal River Basin by focusing on determining the limits of the climatic classification according to past discharges.The daily discharges from May 1,1950 to April 30,2018 were chosen as the study period.These flow data have been grouped into annual discharges and classified as very wet,moist,medium,dry and very dry each year.Then,the flow data were divided into two seasons or periods each year:high water and low water.The statistical variables used in this study are the average,the standard deviation,the coefficient of variation and the skewness.The results of the climate classification that corresponds to a log-normal distribution indicate a total of 17 years classified as averages(25%of the series),14 classified as wet(20.6%),29 classified as dry(42.6%)and 8 classified as very wet(11.8%),very dry classifications being nil.Seasonal analysis showed that the months of the high water period,such as September,had the highest flow,and the period of low water,such as May,had the lowest flow.The results of the flow analysis were then compared with changes in rainfall.The results obtained show similar climatic classifications between rainfall and flow in the basin.

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.

Projected Shifts in Kppen Climate Zones over China and Their Temporal Evolution in CMIP5 Multi-Model Simulations

Previous studies have examined the projected climate types in China by 2100. This study identified the emergence time of climate shifts at a 1 o scale over China from 1990 to 2100 and investigated the temporal evolution of Koppen-Geiger climate classifications computed from CMIP5 multi-model outputs. Climate shifts were detected in transition regions （7%-8% of China＇s land area） by 2010, including rapid replacement of mixed forest （Dwb） by deciduous forest （Dwa） over Northeast China, strong shrinkage of alpine climate type （ET） on the Tibetan Plateau, weak northward expansion of subtropical winter- dry climate （Cwa） over Southeast China, and contraction of oceanic climate （Cwb） in Southwest China. Under all future RCP （Representative Concentration Pathway） scenarios, the reduction of Dwb in Northeast China and ET on the Tibetan Plateau was projected to accelerate substantially during 2010-30, and half of the total area occupied by ET in 1990 was projected to be redistributed by 2040. Under the most severe scenario （RCP8.5）, sub-polar continental winter dry climate over Northeast China would disappear by 2040-50, ET on the Tibetan Plateau would disappear by 2070, and the climate types in 35.9% and 50.8% of China＇s land area would change by 2050 and 2100, respectively. The results presented in this paper indicate imperative impacts of anthropogenic climate change on China＇s ecoregions in future decades.

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.

Global Land Surface Climate Analysis Based on the Calculation of a Modified Bowen Ratio

A modified Bowen ratio(BRm),the sign of which is determined by the direction of the surface sensible heat flux,was used to represent the major divisions in climate across the globe,and the usefulness of this approach was evaluated. Five reanalysis datasets and the results of an offline land surface model were investigated. We divided the global continents into five major BRm zones using the climatological means of the sensible and latent heat fluxes during the period 1980–2010:extremely cold,extremely wet,semi-wet,semi-arid and extremely arid. These zones had BRm ranges of(-∞,0),(0,0.5),(0.5,2),(2,10) and(10,+∞),respectively. The climatological mean distribution of the Bowen ratio zones corresponded well with the K ¨oppen-like climate classification,and it reflected well the seasonal variation for each subdivision of climate classification. The features of climate change over the mean climatological BRm zones were also investigated. In addition to giving a map-like classification of climate,the BRm also reflects temporal variations in different climatic zones based on land surface processes. An investigation of the coverage of the BRm zones showed that the extremely wet and extremely arid regions expanded,whereas a reduction in area was seen for the semi-wet and semi-arid regions in boreal spring during the period 1980–2010. This indicates that the arid regions may have become drier and the wet regions wetter over this period of time.

Detection of Changes on Temperature and Precipitation Features in Istanbul(Turkey)

In this study, the changes in the data of Istanbul’s precipitation and temperature and the features of these changes were analyzed by different methods. In the analyses the daily precipitation and temperature data sets of Florya and Goztepe Meteorological Stations which have similar locational features were used. These sets were recorded between 1960 and 2013 (for 54 years). In order to emphasize the differentiations in the last 15 years the analyses were conducted comparatively both for the 15-year and for the 54-year periods and then the results were evaluated. The changes in the monthly, annual and seasonal quantity, type and frequency of the precipitation in the form of rain and the features of the temperature’s monthly, annual and seasonal changes, the De Martonne aridity index and the Thornthwaite climate classification were carried out. The results showed that during the years from 1999 to 2013 the climate type of Istanbul changed from semi-humid climate to arid and less-humid climate. Most notably the precipitation during the warm periods has decreased, but the frequency of the intense rain has increased and the majority of these episodes of intense rain coincided with the warm periods. Other determinations were the rise in the annual average temperature and the extension of the warm periods in a year. This differentiation of the temperature features can lead to the aggravation of the evaporation and it can be effective for a longer period during the year. Being aware of this differentiation in the features of precipitation and temperature and taking these data into consideration in all sorts of planning and managing strategies have a special importance for the 14 million or more people living in Istanbul.

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.

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.