Changes in Mean and Extreme Temperature and Precipitation over the Arid Region of Northwestern China： Observation and Projection

This paper reports a comprehensive study on the observed and projected spatiotemporal changes in mean and extreme climate over the arid region of northwestern China, based on gridded observation data and CMIP5 simulations under the RCP4.5 and RCP8.5 scenarios. The observational results reveal an increase in annual mean temperature since 1961, largely attributable to the increase in minimum temperature. The annual mean precipitation also exhibits a significant increasing tendency. The precipitation amount in the most recent decade was greater than in any preceding decade since 1961. Seasonally,the greatest increase in temperature and precipitation appears in winter and in summer, respectively. Widespread significant changes in temperature-related extremes are consistent with warming, with decreases in cold extremes and increases in warm extremes. The warming of the coldest night is greater than that of the warmest day, and changes in cold and warm nights are more evident than for cold and warm days. Extreme precipitation and wet days exhibit an increasing trend, and the maximum number of consecutive dry days shows a tendency toward shorter duration. Multi-model ensemble mean projections indicate an overall continual increase in temperature and precipitation during the 21 st century. Decreases in cold extremes, increases in warm extremes, intensification of extreme precipitation, increases in wet days, and decreases in consecutive dry days, are expected under both emissions scenarios, with larger changes corresponding to stronger radiative forcing.

Preface to Special Issue on Climate Science for Service Partnership China

This special issue of Advances in Atmospheric Sciences provides a selection of research highlights from the Climate Science for Service Partnership China(CSSP China).This pioneering partnership between China and UK based researchers has broken new ground in the development of climate science for services.By accelerating and enhancing collaborative science,CSSP China has built a strong foundation for services to support climate and weather resilient economic

Stable classi?cation with limited sample: transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017

As the world strives to reduce the impact of population growth, urbanization, agricultural expansion, and climate change on food security, energy and water shortage, resource over-exploration, biodiversity loss, environmental pollution, and ultimately human health, timely and higher resolution land cover information is urgently needed to achieve the sustainable development goals of the United Nations.

Prediction of Primary Climate Variability Modes at the Beijing Climate Center

Climate variability modes, usually known as primary climate phenomena, are well recognized as the most important predictability sources in subseasonal–interannual climate prediction. This paper begins by reviewing the research and development carried out, and the recent progress made, at the Beijing Climate Center(BCC) in predicting some primary climate variability modes. These include the El Ni?o–Southern Oscillation(ENSO), Madden–Julian Oscillation(MJO), and Arctic Oscillation(AO), on global scales, as well as the sea surface temperature(SST) modes in the Indian Ocean and North Atlantic, western Pacific subtropical high(WPSH), and the East Asian winter and summer monsoons(EAWM and EASM, respectively), on regional scales. Based on its latest climate and statistical models, the BCC has established a climate phenomenon prediction system(CPPS) and completed a hindcast experiment for the period 1991–2014. The performance of the CPPS in predicting such climate variability modes is systematically evaluated. The results show that skillful predictions have been made for ENSO, MJO, the Indian Ocean basin mode, the WPSH, and partly for the EASM, whereas less skillful predictions were made for the Indian Ocean Dipole(IOD) and North Atlantic SST Tripole, and no clear skill at all for the AO, subtropical IOD, and EAWM. Improvements in the prediction of these climate variability modes with low skill need to be achieved by improving the BCC's climate models, developing physically based statistical models as well as correction methods for model predictions.Some of the monitoring/prediction products of the BCC-CPPS are also introduced in this paper.

Re-Assessing Climatic Warming in China since 1900

The regional mean surface air temperature(SAT)in China has risen with a rate of 1.3–1.7℃(100 yr)^-1 since 1900,based on the recently developed homogenized observations.This estimate is larger than those[0.5–0.8℃(100 yr)^-1]adopted in the early National Reports of Climate Change in China.The present paper reviews the studies of the longterm SAT series of China,highlighting the homogenization of station observations as the key progress.The SAT series of China in early studies showed a prominent warm peak in the 1940s,mainly due to inhomogeneous records associated with site-moves of a number of stations from urban to outskirts in the early 1950s,thus leading to underestimates of the centennial warming trend.Parts of China were relatively warm around the 1940s but with differentphase interdecadal variations,while some parts were even relatively cool.This fact is supported by proxy data and could partly be explained by interdecadal changes in large-scale circulation.The effect of urbanization should have a minor contribution to the observed warming in China,although the estimates of such contributions for individual urban stations remain controversial.Further studies relevant to the present topic are discussed.

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.

A Possible Abrupt Change in Summer Precipitation over Eastern China around 2009

Historical studies have shown that summer rainfall in eastern China undergoes decadal variations,with three apparent changes in the late 1970s,1992,and the late 1990s.The present observational study indicates that summer precipitation over eastern China likely underwent a change in the late 2000s,during which the main spatial pattern changed from negative–positive–negative to positive–negative in the meridional direction.This change in summer precipitation over eastern China may have been associated with circulation anomalies in the middle/upper troposphere.A strong trough over Lake Baikal created a southward flow of cold air during 2009–15,compared with 1999–2008,while the westward recession of the western Pacific subtropical high strengthened the moisture transport to the north,creating conditions that were conducive for more rainfall in the north during this period.The phase shift of the Pacific Decadal Oscillation in the late 2000s led to the Pacific–Japan-type teleconnection wave train shifting from negative to positive phases,resulting in varied summer precipitation over eastern China.

Climate Services for Water Resource Management in China: The Case Study of Danjiangkou Reservoir

The efficiencies and effectiveness of water resource management are inextricably linked to climate services. This study demonstrates a climate information service for Danjiangkou Reservoir, which is the largest artificial lake in Asia, facing mounting challenges for flood control, water storage, and water diversion. Unlike traditional water resource management on the basis of short-term weather forecast and runoff monitoring, subseasonal to seasonal(S2S)and annual climate predictions as well as long-term climate change projections were well used to support the decision makers in Danjiangkou Reservoir. The National Climate Center(NCC) has projected the changes of future climate and extreme events by dynamically downscaling the Coupled Model Intercomparison Project phase 5(CMIP5)projections to 25-km resolution for the long-term planning of water resource management in Danjiangkou Reservoir.Real-time climate predictions based on climate models and downscaling interpretation and application methods at different timescales were also provided to meet the specific needs of earlier predictions and spatial refinement for the short-term diversion of the reservoir. Our results show that such climate services facilitated the Diversion Center of Danjiangkou Reservoir(DCDR) to reasonably control the operational water level, increased the ecological water supply to the northern portion of China by 844 million m^(3), and reduced as much as 1.67 billion m^(3) of abandoned water in 2019. In the future, it is necessary to develop climate prediction methods to increase spatial and temporal resolutions and prediction skills, and enhance interactions between providers and users.