Spatial and temporal patterns of the sensitivity of radial growth response by Picea schrenkiana to regional climate change in the Tianshan Mountains

Climate change significantly impacts forest ecosystems in arid and semi-arid regions.However,spatiotemporal patterns of climate-sensitive changes in individual tree growth under increased climate warming and precipitation in north-west China is unclear.The dendrochronological method was used to study climate response sensitivity of radial growth of Picea schrenkiana from 158 trees at six sites during 1990-2020.The results show that climate warming and increased precipitation significantly promoted the growth of trees.The response to temperature first increased,then decreased.However,the response to increased precipitation and the self-calibrating Palmer Drought Severity Index(scPDSI)increased significantly.In most areas of the Tianshan Mountains,the proportion of trees under increased precipitation and scPDSI positive response was relatively high.Over time,small-diameter trees were strongly affected by drought stress.It is predicted that under continuous warming and increased precipitation,trees in most areas of the Tianshan Mountains,especially those with small diameters,will be more affected by precipitation.

SPARC Local Workshop on “WCRP Grand Challenges and Regional Climate Change”

1.Overview SPARC（Stratosphere-Troposphere Processes and their Role in Climate）is one of the core projects of the World Climate Research Program（WCRP）,coordinating international efforts to address relevant issues in climate and climate prediction via better understanding of the stratosphere-troposphere system.

Simulation of Effects of Land Use Change on Climate in China by a Regional Climate Model

Climate effects of land use change in China as simulated by a regional climate model (RegCM2) are investigated. The model is nested in one-way mode within a global coupled atmosphere-ocean model (CSIRO R21L9 AOGCM). Two multi-year simulations, one with current land use and the other with potential vegetation cover, are conducted. Statistically significant changes of precipitation, surface air temperature, and daily maximum and daily minimum temperature are analyzed based on the difference between the two simulations. The simulated effects of land use change over China include a decrease of mean annual precipitation over Northwest China, a region with a prevalence of arid and semi-arid areas; an increase of mean annual surface air temperature over some areas; and a decrease of temperature along coastal areas. Summer mean daily maximum temperature increases in many locations, while winter mean daily minimum temperature decreases in East China and increases in Northwest China. The upper soil moisture decreases significantly across China. The results indicate that the same land use change may cause different climate effects in different regions depending on the surrounding environment and climate characteristics.

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.

Quantitative Assessment of Impacts of Regional Climate and Human Activities on Saline-alkali Land Changes:A Case Study of Qian'an County,Jilin Province

Interdecadal and interannuat variations of saline-alkali land area in Qian＇an County, Jilin Province, China were comprehensively analyzed in this paper by means of satellite remote sensing interpretation, field flux observations and regional climate diagnosis. The results show that on the interannual scale, the impact of climate factors accounts for 71.6% of the total variation of the saline-alkali land area, and that of human activities accounts for 28.4%. Therefore the impact of climate factors is obviously greater than that of human activities. On the interdecadal scale, the impact of climate factors on the increase of the saline-alkali land area accounts for 43.2%, and that of human activities accounts for 56.8%. The impact of human activities on the variation of saline-alkali land area is very clear on the interdecadal scale, and the negative impact of human activities on the environment should not be negligible. Besides, changes in the area of heavy saline-alkali land have some indication for development of saline-alkali land in Qian＇an County.

Advancing Climate Dynamics Toward Reliable Regional Climate Projections

With a scientific consensus reached regarding the anthropogenic effect on global mean temperature, developing reliable regional climate projections has emerged as a new challenge for climate science. A national project was launched in China in 2012 to study ocean's role in regional climate change. This paper starts with a review of recent advances in the study of regional climate re-sponse to global warming, followed by a description of the Chinese project including the rationale, objectives, and plan for field ob-servations. The 15 research articles that follow in the special issue are highlighted, representing some of the initial results from the project.

Scale-dependent Regional Climate Predictability over North America Inferred from CMIP3 and CMIP5 Ensemble Simulations

Through the analysis of ensembles of coupled model simulations and projections collected from CMIP3 and CMIP5, we demonstrate that a fundamental spatial scale limit might exist below which useful additional refinement of climate model predictions and projections may not be possible. That limit varies among climate variables and from region to region. We show that the uncertainty（noise） in surface temperature predictions（represented by the spread among an ensemble of global climate model simulations） generally exceeds the ensemble mean（signal） at horizontal scales below 1000 km throughout North America, implying poor predictability at those scales. More limited skill is shown for the predictability of regional precipitation. The ensemble spread in this case tends to exceed or equal the ensemble mean for scales below 2000 km. These findings highlight the challenges in predicting regionally specific future climate anomalies, especially for hydroclimatic impacts such as drought and wetness.

A Simulation Study on Climatic Effects of Land Cover Change in China

The regional climate model RegCM4 was used to investigate the regional climate effects of land cover change over China. Two 24-year simulations （1978-2001）, one with the land cover derived from the MODIS data and the other with the CLCV （Chinese land cover derived from vegetation map） data, were conducted for a region encompassing China. The differences between the MODIS and CLCV data reflect characteristics of desertification and degradation of vegetation in China. Results indicate that the land cover change has important impacts on local climate through mechanisms related to changes in surface energy, water budgets and macro-scale circulation. In summer, the land cover change leads to a decrease in surface air temperature over southern China, a reduction in precipitation and an increase in surface air temperature in the transitional climate zone and the northern Tibetan Plateau, and an increase in inter-annual variability of surface air temperature in the marginal monsoon zone and northwestern China. Strengthened southwesterly winds increase precipitation to some extent in central and eastern Inner Mongolia by enhancing water vapor transport. In winter, enhanced northerly winds, bringing more dry and cold air, lead to a reduction in precipitation and temperature over areas south of the Yellow River.

Spatial variability of glacial changes and their effects on water resources in the Chinese Tianshan Mountains during the last five decades

Changes in glaciers in the Chinese Tianshan Mountains have been analyzed previously. However, most previous studies focused on individual glaciers and/or decentralized glacial basins. Moreover, a majority of these studies were published only in Chinese, which limited their usefulness at the international level. With this in mind, the authors reviewed the previous studies to create an overview of glacial changes in the Chinese Tianshan Mountains over the last five decades and discussed the effects of glacial changes on water resources. In response to climate change, glaciers in the Tianshan Mountains are shrinking rapidly and are ca. 20% smaller on average in the past five decades. Overall, the area reduction of glacial basins in the central part of the Chinese Tianshan Mountains is larger than that in the eastern and western parts. The spatial differentiation in glacial changes are caused by both differences in regional climate and in glacial factors. The effects of glacial changes on water resources vary in different river basins due to the differences in glacier distribution, characteristics of glacial change and proportion of the glacier meltwater in river runoff.

Agricultural Land Use Effects on Climate over China as Simulated by a Regional Climate Model

The Abdus Salam International Centre for Theoretical Physics（ICTP） Regional Climate Model version 3（RegCM3） is used to investigate the climate effects of land use change related to agriculture over China.The model is driven by the European Center for Medium-range Weather Forecast 40-yr Re-Analysis（ERA40） data.Two sets of experiments for 15 yr（1987-2001） are conducted,one with the potential vegetation cover and the other the agricultural land use（AG）.The results show that the AG effects on temperature are weak over northern China while in southern China a significant cooling is found in both winter（DecemberJanuary-February） and summer（June-July-August）.The mean cooling in the sub-regions of South China（SC） in winter and the sub-regions of Southeast（SE） China in summer are found to be the greatest,up to 0.5°and 0.8 ℃ ,respectively.In general,the change of AG leads to a decrease of annual mean temperature by 0.5-1 ℃ in southern China.Slight change of precipitation in western China and a decrease of precipitation in eastern China are simulated in winter,with the maximum reduction reaching-7.5% over SE.A general decrease of precipitation over northern China and an increase over southern China are simulated in summer,in particular over SE where the increase of precipitation can be up to 7.3%.The AG effects on temperature and precipitation show strong interannual variability.Comparison of the climate effects between AG and the present-day land use（LU） is also performed.In southern China,the ratio of temperature（precipitation） changes caused by AG and LU is greater than（closer to） the ratio of the number of grid cells with changed vegetation cover due to AG and LU variations.

ADVANCES IN REGIONAL CLIMATE MODELING SINCE 1990

Due to the close relationship between regional climate anomalies and social-economy and society development,climatologists worldwide paid great attention to the regional climate anomalies over a long period of time and the corresponding investigation of regional climate modeling has made great progresses.Since 1990 the regional climate simulations have made a more substantial achievement.This paper will focus on the reliability and uncertainties of regional climate modeling by global climate models,the advances on regional climate modeling in the world and the outlook of regional climate modeling.

Sea Surface Temperature Extremes of Different Intensity in the China Seas During the Global Warming Acceleration and Hiatus Periods

Based on the daily OISST V2 with 0.25ohorizontal resolutions, the present study looks into the variations of sea surface temperature (SST) extremes in the China Seas for different segments of the period 1982-2013. The two segments include the warming acceleration period from 1982 to 1997 and the hiatus period from 1998 to 2013 when the global mean surface temperature (GMST) did not significantly increase as expected, or even decreased in some areas.First, we construct the regional average time series over the entire China Seas (15°-45°N, 105°-130°E) for these SST extremes. During the hiatus period, the regionally averaged 10th, 1th and 0.1th percentile of SSTs in each year decreased significantly by 0.40℃, 0.56℃ and 0.58℃ per decade, respectively. The regionally averaged 90th, 99th and 99.9th percentile of SSTs in each year decreased slightly or insignificantly. Our work confirm that the regional hiatus was primarily reflected by wintertime cold extremes. Spatially, the trends of cold extremes in different intensity were nonuniformly distributed. Cold extremes in the near-shore areas were much more sensitive to the global warming hiatus. Hot extremes exhibited non-significant trend in the China Seas during the hiatus period. In short, the variations of the SST extremes in the two periods were non-uniform spatially and asymmetric seasonally. It is unexpected that the hot and cold extremes of each year during 1998-2013 were still higher than those extremes during 1982-1997. It is obvious that compared with the warming acceleration period, hot extremes were far more likely to occur in the recent hiatus as a result of a 0.3℃ warmer shift in the mean temperature distribution. Moreover, hot extremes in the China Seas will be sustained or amplified with the end of warming hiatus and the continuous anthropogenic warming.

Intercomparison of multi-model ensemble-processing strategies within a consistent framework for climate projection in China

Climate change adaptation and relevant policy-making need reliable projections of future climate.Methods based on multi-model ensemble are generally considered as the most efficient way to achieve the goal.However,their efficiency varies and inter-comparison is a challenging task,as they use a variety of target variables,geographic regions,time periods,or model pools.Here,we construct and use a consistent framework to evaluate the performance of five ensemble-processing methods,i.e.,multimodel ensemble mean(MME),rank-based weighting(RANK),reliability ensemble averaging(REA),climate model weighting by independence and performance(ClimWIP),and Bayesian model averaging(BMA).We investigate the annual mean temperature(Tav)and total precipitation(Prcptot)changes(relative to 1995–2014)over China and its seven subregions at 1.5 and 2℃warming levels(relative to pre-industrial).All ensemble-processing methods perform better than MME,and achieve generally consistent results in terms of median values.But they show different results in terms of inter-model spread,served as a measure of uncertainty,and signal-to-noise ratio(SNR).ClimWIP is the most optimal method with its good performance in simulating current climate and in providing credible future projections.The uncertainty,measured by the range of 10th–90th percentiles,is reduced by about 30%for Tav,and 15%for Prcptot in China,with a certain variation among subregions.Based on ClimWIP,and averaged over whole China under 1.5/2℃global warming levels,Tav increases by about 1.1/1.8℃(relative to 1995–2014),while Prcptot increases by about 5.4%/11.2%,respectively.Reliability of projections is found dependent on investigated regions and indices.The projection for Tav is credible across all regions,as its SNR is generally larger than 2,while the SNR is lower than 1 for Prcptot over most regions under 1.5℃warming.The largest warming is found in northeastern China,with increase of 1.3(0.6–1.7)/2.0(1.4–2.6)℃(ensemble’s median and range of the 10th–90th percentiles)under 1.5/2℃warming,followed by northern and northwestern China.The smallest but the most robust warming is in southwestern China,with values exceeding 0.9(0.6–1.1)/1.5(1.1–1.7)℃.The most robust projection and largest increase is achieved in northwestern China for Prcptot,with increase of 9.1%(–1.6–24.7%)/17.9%(0.5–36.4%)under 1.5/2℃warming.Followed by northern China,where the increase is 6.0%(–2.6–17.8%)/11.8%(2.4–25.1%),respectively.The precipitation projection is of large uncertainty in southwestern China,even with uncertain sign of variation.For the additional half-degree warming,Tav increases more than 0.5℃throughout China.Almost all regions witness an increase of Prcptot,with the largest increase in northwestern China.

Variations in soil moisture over the ‘Huang-Huai-Hai Plain＇ in China due to temperature change using the CNOP-P method and outputs from CMIP5

In this study, the variations in surface soil liquid water(SSLW) due to future climate change are explored in the‘Huang-Huai-Hai Plain'(‘3H') region in China with the Common Land Model(CoLM). To evaluate the possible maximum response of SSLW to climate change, the combination of the conditional nonlinear optimal perturbation related to the parameter(CNOP-P) approach and projections from 10 general circulation models(GCMs) of the Coupled Model Intercomparison Project5(CMIP5) are used. The CNOP-P-type temperature change scenario, a new type of temperature change scenario, is determined by using the CNOP-P method and constrained by the temperature change projections from the 10 GCMs under a high-emission scenario(the Representative Concentration Pathway 8.5 scenario). Numerical results have shown that the response of SSLW to the CNOP-P-type temperature scenario is stronger than those to the 11 temperature scenarios derived from the 10 GCMs and from their ensemble average in the entire ‘3H' region. In the northern region, SSLW under the CNOP-P-type scenario increases to0.1773 m^3 m^(-3); however, SSLW in the scenarios from the GCMs fluctuates from 0.1671 to 0.1748 m^3 m^(-3). In the southern region,SSLW decreases, and its variation(–0.0070 m^3 m^(-3)) due to the CNOP-P-type scenario is higher than each of the variations(–0.0051 to –0.0026 m^3 m^(-3)) due to the scenarios from the GCMs.

不同全球变暖目标下中国气候变化风险区域格局

Climate change will bring huge risks to human society and the economy.Regional climate change risk assessment is an important basic analysis for addressing climate change,which can be expressed as a regional system of comprehensive climate change risk.This study establishes regional systems of climate change risks under the proposed global warming targets.Results of this work are spatial patterns of climate change risks in China,indicated by the degree of climate change and the status of the risk receptors.Therefore,the risks show significant spatial differences.The high-risk regions are mainly distributed in East,South,and central China,while the medium-high risk regions are found in North and southwestern China.Under the 2℃warming target,more than 1/4 of China’s area would be at high and medium-high risk,which is more severe than under the 1.5℃warming target,and would extend to the western and northern regions.This work provides regional risk characteristics of climate change under different global warming targets as a foundation for dealing with climate change.

Interpreting the sea surface temperature warming trend in the Yellow Sea and East China Sea

Previous studies have demonstrated that the low-frequency sea surface temperature(SST) variability in the Yellow Sea and East China Sea(YECS) is linked to large-scale climate variability, but explanations on the mechanisms vary. This study examines the low-frequency variability and trends of some atmospheric and oceanic variables to discuss their different effects on the YECS warming. The increasing temperature trend is also observed at a hydrographic section transecting the Kuroshio.The increasing rate of ocean temperature decreases with depth, which might result in an increase in vertical stratification and a decrease in vertical mixing, and thus plays a positive role on the YECS warming. The surface net heat flux(downward positive)displays a decreasing trend, which is possibly a result of the YECS warming, and, in turn, inhibits it. Wind speeds show different trends in different datasets, such that its role in the YECS warming is uncertain. The trends in wind stress divergence and curl have large uncertainties, so their effects on SST warming are still unclear. The Kuroshio heat transport calculated in this study,displays no significantly increasing trend, so is an unlikely explanation for the SST warming. Limited by sparse ocean observations,sophisticated assimilative climate models are still needed to unravel the mechanisms behind the YECS warming.