Regional Variability of Climate Change Hot-Spots in East Asia

The regional climate change index （RCCI） is employed to investigate hot-spots under 21st century global warming over East Asia. The RCCI is calculated on a 1-degree resolution grid from the ensemble of CMIP3 simulations for the B1, AIB, and A2 IPCC emission scenarios. The RCCI over East Asia exhibits marked sub-regional variability. Five sub-regional hot-spots are identified over the area of investigation： three in the northern regions （Northeast China, Mongolia, and Northwest China）, one in eastern China, and one over the Tibetan Plateau. Contributions from different factors to the RCCI are discussed for the sub-regions. Analysis of the temporal evolution of the hot-spots throughout the 21st century shows different speeds of response time to global warming for the different sub-regions. Hot-spots firstly emerge in Northwest China and Mongolia. The Northeast China hot-spot becomes evident by the mid of the 21st century and it is the most prominent by the end of the century. While hot-spots are generally evident in all the 5 sub-regions for the A1B and A2 scenarios, only the Tibetan Plateau and Northwest China hot-spots emerge in the B1 scenario, which has the lowest greenhouse gas （GHG） concentrations. Our analysis indicates that subregional hot-spots show a rather complex spatial and temporal dependency on the GHG concentration and on the different factors contributing to the RCCI.

Impacts of climate change on the potential forest productivity based on a climate-driven biophysical model in northeastern China

Climate warming is expected to influence forest growth,composition and distribution.However,accurately estimating and predicting forest biomass,potential productivity or forest growth is still a challenge for forest managers dealing with land-use at the stand to regional levels.In the present study,we predicted the potential productivity(PP)of forest under current and future climate scenarios(RCP2.6,RCP4.5,RCP6.0 and RCP8.5)in Jilin province,northeastern China by using Paterson’s Climate Vegetation and Productivity(CVP)index model.The PP was validated by comparing it with the mean and maximum net primary production calculated from light energy utilization(GLM_PEM).Our results indicated that using the CVP index model is partially valid for predicting the potential forest productivity in northeastern China.PP exhibited obvious spatial heterogeneity varying from 4.6 to 8.9 m3 ha-1 year-1 with an increasing tendency from northwest to southeast driven by the precipitation across the region.The number of vegetation-active months,precipitation and insolation coefficient were identified as the primary factors affecting PP,but no significant relationship was found for warmest temperature or temperature fluctuation.Under future climate scenarios,PP across the Jilin Province is expected to increase from 1.38%(RCP2.6 in 2050)to 15.30%(RCP8.5 in 2070),especially in the eastern Songnen Plain(SE)for the RCP8.5 scenarios.

Evaluation on Climate Suitability in Main Growth Stages of Zhaotong Apple in Recent 60 Years

Based on daily average temperature,precipitation and sunshine hours during 1961-2018 from two meteorological stations of Zhaoyang District and Ludian County at Zhaolubazi,Zhaotong City,Yunnan Province,using the freezing injury index at flowering stage(Ha),climatic suitability index during expansion period(Pa),climatic suitability index during coloring period(Dy)and climatic suitability index during fruit growing period(Si),etc.,the climatic suitability of Zhaotong apple during the main growth stages was evaluated.The results showed that the annual average temperature was 11.8-12.3℃at Zhaolu Bazi in recent 60 years,and the climate was the most suitable for Fuji apple planting both in the south and north;the average annual precipitation was 674.8-852.6 mm,and the climate was suitable in the north and sub-suitable in the south;the annual average sunshine hours was between 1845.4 and 1851.1 h,and the climate was sub-suitable in both areas.The Ha was between 0.42-0.50,serious in the north and moderate in the south;the Pa was between 0.92 and 1.02,and both the south and the north were suitable areas;the Dy was between 0.95 and 1.00,and the climate in the south was suitable,while it was sub-suitable in the north;the Si was between 1.38 and 1.59,and the climate was suitable in the south and sub-suitable in the north.There was a 4-year cycle in the interannual variation of Ha,Pa,Dy and Si.After the 1980s,the Ha decreased by 0.56-0.59,the Pa,Dy and Si respectively increased by 0.10-0.16,0.14-0.15 and 0.78-0.84 with the temperature rise,and the changes of these four indexes were all favorable for Fuji apple's fruits growth.It can be seen that under the background of the global warming,the climatic conditions in Zhaolu Bazi are becoming more and more favorable for popularizing the planting of Fuji apple.

Seasonal Prediction of Monthly Precipitation in China Using Large-Scale Climate Indices

In this study, seasonal predictions were applied to precipitation in China on a monthly basis based on a multivariate linear regression with an adaptive choice of predictors drawn from regularly updated climate indices with a two to twelve month lead time. A leave-one-out cross validation was applied to obtain hindcast skill at a 1% significance level. The skill of forecast models at a monthly scale and their significance levels were evaluated using Anomaly Correlation Coefficients （ACC） and Coefficients Of Determination （COD）. The monthly ACC skill ranged between 0.43 and 0.50 in Central China, 0.41-0.57 in East China, and 0.41 0.60 in South China. The dynamic link between large-scale climate indices with lead time and the precipitation in China is also discussed based on Singular Value Decomposition Analysis （SVDA） and Correlation Analysis （CA）.

Analysis of the Correlation between Tourism and Climate in the Ancient City of Langzhong

Based on the meteorological data of Langzhong from 1981 to 2016,a comprehensive comfort index model of tourism climate suitable for Langzhong is established by calculating the meteorological and climatic factors affecting tourism in the ancient city of Langzhong.The model is used to evaluate the climate comprehensive comfort of Langzhong,and its grades and suitable tourism periods are divided.Based on the monthly index of passenger flow volume in the ancient city of Langzhong from 2013 to 2015,a mathematical model is established through OLS regression analysis to analyze the correlation between changes in monthly passenger flow volume in a year and the comprehensive comfort of tourism climate in the ancient city of Langzhong.The results show that the climate in Langzhong is suitable for tourism in spring and autumn.It is suitable for tourism from February to June and from September to December,of which it is most suitable for tourism from April to May and from September to October.It is less suitable for tourism in only January and from July to August,and there is no unsuitable period.The changes in monthly passenger flow volume in a year are mainly affected by the meteorology and climate.The changes of climate comprehensive comfort in various month have an extremely significant impact on passenger flow volume.The elastic coefficient of impact of climate comprehensive comfort index on the monthly index of passenger flow volume is 0.9614%.

Perceiving the Trend of Terrestrial Climate Change during the Past 40 year(1978-2018)

In past few decades,climate has manifested numerous shifts in its trend.Various natural and anthropogenic factors have influenced the dynamics and the trends of climate change at longer time scale.To understand the long term climate fluctuations,we have analyzed forty years(1978-2018)data of ten climatic parameters that are responsible to influence the climate dynamics.The parameters involved in the present study are total solar irradiance(TSI),ultra violet(UV)index,cloud cover,carbon dioxide(CO2)abundances,multivariate(ENSO)index,volcanic explosivity index(VEI),global surface temperature(GST)anomaly,global sea ice extent,global mean sea level and global precipitation anomaly.Using the above mentioned climate entities;we have constructed a proxy index to study the quantitative measure of the climate change.In this process these indicators were aggregated to a single proxy index as global climate index(GCI)that has measured the strength of present climate change in semblance with the past natural variability.To construct GCI,the principal component analysis(PCA)has been used on yearly based data for the period 1978-2018.Actually PCA is a statistical tool with which we can reduce the dimensionality of the data and it retains most of the variation in the new data set.Further,we have confined our study to natural climate drivers and anthropogenic climate drivers.Our result has indicated that the strongest climate change has been occurred globally by the end of the year 2018 in comparison to late 1970’s natural variability.

Ranking Regional Drought Events in China for 1960-2009

The spatiotemporal variations of the site and regional droughts in China during 1960–2009 were analyzed by applying a daily composite-drought index （CDI） to 722 stations in China's Mainland. Droughts frequently happened in a zone extended from Southwest China to the Yellow River, North China, and the southwestern part of Northeast China, with two centers of high frequency in North China and Southwest China. In Southwest and South China, droughts tend to happen during the winter. In North China and along the Yellow River, droughts mainly occur during the winter and during May–June. During the past 50 years, the geographical distribution of site drought events showed high frequencies （0.9–1.3 times per year） in the upper Yellow River basin and North China, comparing with moderate frequencies （0.6–0.9 times per year） in Southwest China and the southwestern part of Northeast China and with lower frequencies over the middle and lower Yangtze River basin. And the frequencies increased over China's Mainland except for the upper reaches of the Yangtze River. A regional drought （RD） event is a widespread and persistent event that covers at least five adjacent sites and lasts for at least 10 days. There were 252 RD events in the past 50 years—five times per year. Most RD events lasted for 100 days and covered 100 stations, but the longest and largest RD event lasted for 307 days from 6 September 1998 to 9 July 1999 and covered 327 stations from North to Southwest China.

黔西南优质烤烟种植分区农业气象关键因子研究(英文)

[Objective] This research was to provide technical guidance for the cultivation of high-quality tobacco in Qianxinan area.[Method] Through analyzing the conditions of main tobacco cultivation areas in Qianxinan including temperature,precipitation and sunshine,the influence factors of tobacco yield and quality in Qianxinan were investigated.[Result] The altitude of Division I was 450-1 650 m,its days with temperature equal to or higher than 20℃ were about 80 d,its active accumulated temperature was 1 200-2 100℃ and its annual average temperature was 13.5-14.6℃.The altitude of Division II was 1 300-1 450 m,its days with temperature equal to or higher than 20℃ were about 110 d,its active accumulated temperature was 2 100-2 700℃ and its annual average temperature was 14.6-16.3℃.The altitude of Division III was 1 050-1 300 m,its days with temperature equal to or higher than 20℃ were about 150 d,its active accumulated temperature was 2 700-3 600℃ and its annual average temperature was 16.3-17.0℃.Division IV was divided into 2 areas,the altitude of Area 1 was lower than 1 000 m,its days with temperature equal to or higher than 20℃ were more than 160 d,its active accumulated temperature was higher than 3 600℃ and its annual average temperature was higher than 17.5℃;the altitude of Area 2 was higher than 1 700 m,its days with temperature equal to or higher than 20℃ were basically none and its annual average temperature was lower than 1.30℃.[Conclusion] In this research,the agricultural climate index conditions for cultivation of high-quality tobacco in areas at different altitudes were suggested and some references were provided for developing tobacco production in Guizhou.

Seasonal and inter-annual variations of Arctic cyclones and their linkage with Arctic sea ice and atmospheric teleconnections

The seasonal and inter-annual variations of Arctic cyclone are investigated. An automatic cyclone tracking algorithm developed by University of Reading was applied on the basis of European Center for Medium-range Weather Forecasts（ECMWF） ERA-interim mean sea level pressure field with 6 h interval for 34 a period. The maximum number of the Arctic cyclones is counted in winter, and the minimum is in spring not in summer.About 50% of Arctic cyclones in summer generated from south of 70°N, moving into the Arctic. The number of Arctic cyclones has large inter-annual and seasonal variabilities, but no significant linear trend is detected for the period 1979–2012. The spatial distribution and linear trends of the Arctic cyclones track density show that the cyclone activity extent is the widest in summer with significant increasing trend in CRU（central Russia）subregion, and the largest track density is in winter with decreasing trend in the same subregion. The linear regressions between the cyclone track density and large-scale indices for the same period and pre-period sea ice area indices show that Arctic cyclone activities are closely linked to large-scale atmospheric circulations, such as Arctic Oscillation（AO）, North Atlantic Oscillation（NAO） and Pacific-North American Pattern（PNA）. Moreover,the pre-period sea ice area is significantly associated with the cyclone activities in some regions.

Analysis on Climatic and Synoptic Characteristics of Thunderstorm Gale Weather in Jiangsu

By using observation and sounding data at 68 artificial observatories of Jiangsu Province during 2009- 2013,thunderstorm gale weather and its climatic characteristics in Jiangsu were conducted statistics. The characteristics of some instability indexes and strong convection parameters were analyzed,and environmental parameters of dry and wet thunderstorm gales were contrasted. Results showed that thunderstorm gale in Jiangsu had the characteristics of high occurrence frequency,local feature and stronger intensity. It was mostly accompanied by precipitation,and had obvious seasonal and daily change characteristics. Synoptics analysis showed that temperature-humidity profile characteristics before thunderstorm gale appeared in Jiangsu mainly had four types： bell mouth type,inverted V type,dry unstable type and wet unstable type. Before thunderstorm gale occurred,atmospheric instability was stronger,and some strong convection parameters all had certain instructions. But the forecasts of some thunderstorm gale processes were easy to be missed by only considering CAPE. Environmental condition difference of generating dry and wet thunderstorm gale was that instability of dry thunderstorm gale was stronger than that of wet thunderstorm gale. Before dry thunderstorm gale occurred,environmental temperature at middle-low layer was lower; lapse rate was larger; humidity was small. Before wet thunderstorm gale occurred,environmental temperature was higher; lapse rate was small; humidity was large. At dynamic structure,vertical wind shear at 0- 6 km of dry thunderstorm gale was significantly stronger than that of wet thunderstorm gale.

Construction and Application of a Climate Risk Index for China

In the context of global warming,China is facing with increasing climate risks.It is imperative to develop quantitative indices to reflect the climate risks caused by extreme weather/climate events and adverse climatic conditions in association with different industries.Based on the observations at 2288 meteorological stations in China and the meteorological disasters data,a set of indices are developed to measure climate risks due to water-logging,drought,high temperature,cryogenic freezing,and typhoon.A statistical method is then used to construct an overall climate risk index(CRI)for China from these individual indices.There is a good correspondence between these indices and historical climatic conditions.The CRI,the index of water-logging by rain,and the high temperature index increase at a rate of 0.28,0.37,and 0.65 per decade,respectively,from 1961 to 2016.The cryogenic freezing index is closely related to changes in the consumer price index for food.The high temperature index is correlated with the consumption of energy and electricity.The correlation between the yearly growth in claims on household property insurance and the sum of the water-logging index and the typhoon index in the same year is as high as 0.70.Both the growth rate of claims on agricultural insurance and the annual growth rate of hospital inpatients are positively correlated with the CRI.The year-on-year growth in the number of domestic tourists is significantly negatively correlated with the CRI in the same year.More efforts are needed to develop regional CRIs.

Notes on Business Climate Index and Entrepreneur Confidence Index

To better demonstrate the economic forecasting function of business climate survey,China Economic Monitoring and Analysis Center(CEMAC) revised the calculation methodology of Business Climate Index(BCI) and Entrepreneur Confidence Index(ECI) from 2012Q 1.The details are as below:

Notes on Business Climate Index and Entrepreneur Confidence Index

To better demonstrate the economic forecasting function of business climate survey,China Economic Monitoring and Analysis Center(CEMAC)revised the calculation methodology of Business Climate Index(BCI)and Entrepreneur Confidence Index(ECI)from 2012Q1.The details are as below: Calculation methodology:Business Climate Index(BCI)is a weighted-average of current situation index (mainly reflects entrepreneurs’judgment on the business operation in the current situation)and expectation index (mainly reflects entrepreneurs’judgment on the business operation in the future),where current situation

Changes in Temporal Concentration Property of Summer Precipitation in China during 1961–2010 Based on a New Index

Based on the property of entropy,a new index Q was defined to measure the temporal concentration property of summertime daily rainfall in China,based on daily precipitation data collected at 553 observation stations in China during 1961–2010.Furthermore,changes in the temporal concentration property of summer precipitation in China were investigated.The results indicate that the regions with larger Q values were located in most parts of Northwest China and the north of the Yellow River,where daily precipitation tended to become temporally concentrated during the study period.On the contrary,smaller Q values were found in eastern Tibetan Plateau,southeastern Northwest China,and most parts of Southwest and South China.The most obvious increasing trend of Q index was found in South China and most parts of Southwest China,where precipitation showed a temporal concentration trend.However,a decreasing trend of Q index was found in Northwest China,the Tibetan Plateau,and the north of the Huaihe River.Variations of the Q index and the summer rainfall total during 1961–2010 in China both exhibited an increasing trend,implying larger temporal variability in rainfall attributes.It is illustrated that the summer precipitation in general became more temporally concentrated with more intense rainfall events and wetter days.

Changes in thermal comfortable condition in the Qinghai‒Tibet Plateau from 1979 to 2020

Qinghai‒Tibet Plateau(QTP)is one of the most sensitive regions to climate change in the world.As a result,people in the QTP are more likely to be sensitively affected by climate change than those in other regions,particularly in the poverty area.Using the Universal Thermal Climate Index(UTCI)derived from ERA5 and population data,changes in annual thermal comfort condition and population under such condition in the QTP are systematically analyzed.The results reveal that there is considerable regional heterogeneity in the distribution of UTCI and the number of comfortable days(CDs),mainly due to the complex geographic features.In most areas of the QTP,the increase in UTCI leads to an increased number of comfortable days.Spatial distribution and temporal change in the number of comfortable days are found to be principally related to altitude.In areas within altitudes of 3000–4500 m,the number of comfortable days increases by up to 6 d per decade,which is faster than that in higher elevation areas above 4500 m.Results also indicate that thermal comfortable condition has improved in areas of 2500–5000 m(medium to high altitude),particularly in spring and autumn.Further research indicates that population distribution also shows a regional clustering feature,with the majority of residents residing in cities and their vicinities,where a higher number of comfortable days were observed.Most areas with a greater number of comfortable days have experienced a more significant increase in population under thermal comfortable conditions.It implies that climate change more likely has a large influence on population in the QTP.These findings are expected to enhance tourism development and the assessment of the impact on the living environment.The findings can be helpful for optimizing of tourism development and better understanding how climate change affects population distribution.