Hotspots of the sensitivity of the land surface hydrological cycle to climate change

Due to the shortage of the global observational data of the terrestrial hydrological variables,the understanding of how surface hydrological processes respond to climate change is still limited.In this study,the Community Land Model(CLM4.0)with high resolution atmospheric forcing data is selected to simulate the global surface hydrological quantities during the period 1948–2006and to investigate the spatial features of these quantities in response to climate change at the regional scales.The sensitivities of evaporation and runoff with respect to the dominant climate change factors(e.g.temperature and precipitation)derived from the concept of climate elasticity are introduced.Results show that evaporation has a declining trend with a rate of 0.7 mm per decade,while runoff shows a weak increasing trend of 0.15 mm per decade over the global land surface.Analyses of the hotspots in the hydrological cycle indicate that the spatial distributions for evaporation and runoff are similar over many areas in central Asia,Australia,and southern South America,but differ largely in high latitudes.It is also found that,the evaporation hotspots in arid regions are mainly associated with the changes in precipitation.Our sensitive analysis suggests that the hydrological quantities show a rather complicated spatial dependency of response of the water cycle to the different climate factors(temperature and precipitation).     

Response of forest distribution to past climate change: An insight into future predictions

Vegetation dynamics could lead to changes in the global carbon and hydrology cycle, as well as feedbacks to climate change. This paper reviews the response of forest dynamics to climate change. Based on palaeoecological studies, we summarized the features and modes of vegetation response to climate change and categorized the impacts of climate change on vegetation dynamics as three types： climate stress on vegetation, buffer effects by non-climatic factors, and perturbation of the vegetation distribution by stochastic events. Due to the openness of the vegetation system and the integrated effects of both climatic and non-climatic factors the vegetation-climate relationship deviates far from its equilibrium. The vegetation distribution shows a non-linear response to climate change, which also makes it difficult to quantify the modern vegetation distribution in terms of specific climatic factors. Past analog, space-for-time-substitution and Dynamic Global Vegetation Models （DGVMs） are three approaches to predicting the future vegetation distribution, but they have all been established on the assumption of vegetation-climate equilibrium. We propose that improving DGVMs is a future task for studies of vegetation dynamics because these are process-based models incorporating both disturbance （e.g. fire） and the variability in Plant Functional Types （PFTs）. However, palaeoecological results should be used to test the models, and issues like spatial and temporal scale, complexity of climate change, effects of non-climatic factors, vege- tation-climate feedback, and human regulation on vegetation dynamics are suggested as topics for future studies.     

Accumulation and temperature changes in Princess Elizabeth Land, Antarctica in the past 250 years

A 50 m firn core drilled in Princess Elizabeth Land, Antarctica, during the 1996/1997 Chinese First Antarctic Inland Expedition, has been measured for б18O and major ions. Based on these data, the features of the climate change in the investigated region in the past 250 years have first been studied. In the past 250 years, the change trend of climate in this region can be divided into two periods by the year 1860. Both the temperature and accumulation rate display increasing trend before 1860, while after 1860, the decreasing trend of the temperature is obvious but the change of the accumulation rate is not clear. Although both the temperature and the accumulation rate are increasing in the past 50 years, they are not the highest values in the past 250 years. So it is clear that the climate change in this region during this period does not reflect recent global wanning.     

The Impact of Climate Warming on Permafrost and Qinghai-Tibet Railway

Global wanning is an inarguable fact. Permafrost is experiencing a change due to climate warming in Qinghai-Tibet Plateau, such as the decreasing of permafrost table, the rising of permafrost temperature, etc. On the basis of analysing the permafrost change under the climate change and engineering action, the thermal regime and spatial distribution of permafrost are predicted for air temperature rising 1℃ and 2.6℃ after 50 years in this paper. The results show that climate change results in the larger change for the thermal regime and spatial distribution of permafrost. Permafrost change will produce the great effect on the Qinghai- Tibet Railway engineering, not only resulting in the decreasing of permafrost table beneath the roadbed, but also resulting in thawing settlement due to the thawing of ground ice near permafrost table. The idea of cooling roadbed and actively protecting permafrost for the Qinghai-Tibet Railway engineering could adjust and control the permafrost thermal state, some better methods are provided to ensure the engineering stability in the areas of warm permafrost and high ice content.     

Climate change and hydrologic process response in the Tarim River Basin over the past 50 years

Climate change and hydrologic process response in the Tarim River Basin over the past 50 years are the focus of more and more researchers＇ attention. In this paper, both temperature and precipitation time series were found to present a monotonic increasing trend using nonparametric tests. Noticeably, a significant step change in both temperature and precipitation time series occurred in 1986. By contrasting the trends of natural water process in headstream and mainstream, we found that it was anthropogenic activities not climate change that caused the river dried up and vegetation degenerated in the lower reaches of Tarim River. The results of gray correlation analysis show that the runoff of higher latitude distributing river is more closely associated with winter snow stocking, while that of lower latitude is more closely related to summer temperature. Runoff in the headstream is more sensitive to precipitation, while that in the mainstream is more sensitive to evaporation. The strong evaporation caused by increasing temperature weakened runoff to some extent in spite of the fact that precipitation increased over the past 50 years.     

Changes in global potential vegetation distributions from 1911 to 2000 as simulated by the Comprehensive Sequential Classification System approach

Vegetation classification models play an important role in studying the response of the terrestrial ecosystem to global climate change. In this paper, we study changes in global Potential Natural Vegetation (PNV) distributions using the Comprehensive Sequential Classification System (CSCS) approach, a technique that combines geographic information systems. Results indicate that on a global scale there are good agreements among maps produced by the CSCS method and the globally well-accepted Holdridge Life Zone (HLZ) and BIOME4 PNV models. The potential vegetation simulated by the CSCS approach has 6 major latitudinal zones in the northern hemisphere and 2 in the southern hemisphere. In mountainous areas it has obvious altitudinal distribution characteristics due to topographic effects. The distribution extent for different PNV classes at various periods has different characteristics. It had a decreasing trend for the tundra and alpine steppe, desert, sub-tropical forest and tropical forest categories, and an increasing trend for the temperate forest and grassland vegetation categories. The simulation of global CSCS-based PNV classes helps to understand climate-vegetation relationships and reveals the dynamics of potential vegetation distributions induced by global changes. Compared with existing statistical and equilibrium models, the CSCS approach provides similar mapping results for global PNV and has the advantage of improved simulation of grassland classes.     

Impacts of climate warming on plants phenophases in China for the last 40 years

Based on plant phenology data from 26 stations of the Chinese Phenology Observation Network of the Chinese Academy of Sciences and the climate data, the change of plant phenophase in spring and the impact of climate warming on the plant phenophase in China for the last 40 years are analyzed. Furthermore, the geographical distribution models of phenophase in every decade are reconstructed, and the impact of climate warming on geographical distribution model of phenophase is studied as well. The results show that (ⅰ) the response of phenophase advance or delay to temperature change is nonlinear. Since the 1980s, at the same amplitude of temperature change, phenophase delay amplitude caused by temperature decrease is greater than phenophase advance amplitude caused by temperature increase; the rate of phenophase advance days decreases with temperature increase amplitude, and the rate of phenophase delay days increases with temperature decrease amplitude. (ⅱ) The geographical distribution model between phenophase and geographical location is unstable. Since the 1980s, with the spring temperature increasing in the most of China and decreasing in the south of Qinling Mountains, phenophases have advanced in northeastern China, North China and the lower reaches of the Changjiang River, and have delayed in the eastern part of southwestern China and the middle reaches of the Changjiang River; while the rate of the phenophase difference with latitude becomes smaller.     

Analyzing global trends of different cloud types and their potential impacts on climate by using the ISCCP D2 dataset

The International Satellite Cloud Climatology roject (ISCCP) D2 dataset is used to study the global distribution of low, middle and high cloud amounts and their rends of 1983-2001. Evidences have shown that global arming has accelerated over the past 20 a and the 1990s as the warmest decade in the instrumental records since 861. Trends of various clouds amounts over this period are nalyzed by employing the linear regression method. The esults show that global mean total cloud amounts, in general,have tended to reduce over the past 20 a. But there are lightly increasing by about 2% before 1987 and decreasing y about 4% since then. Cloudiness trends of both low and igh clouds decrease while increase for the middle cloud.And there exist remarkable discrepancies in different regions.The preliminary analyses suggest that it is likely that the loud change occurring over the past 20 a is a positive feedback to global warming.     

Spatiotemporal vegetation cover variations in the Qinghai-Tibet Plateau under global climate change

Empirical Orthogonal Function （EOF） analysis and the related Principal Components （PC） analysis are used to extract valuable vegetation cover derived information from the National Oceanic and Atmos-pheric Administration （NOAA-AVHRR）＇s Leaf Area Index （LAI） satellite images. Results suggest that from 1982 to 2000 global climate change has contributed to an increase in vegetation cover in the Qinghai-Tibet Plateau. The correlation between rainfall and LAI EOF PC1 and PC2 indicates that rainfall is the major climatic factor influencing interannual variations of average vegetation cover throughout the entire Plateau. However, annual mean vegetation cover trends in the Qinghai-Tibet Plateau are mainly out of phase with air temperature increasing, which is primarily responsible for nonsynchro-nous changes of vegetation cover. In the southern ridge of the Qinghai-Tibet Plateau, recent warming trends contribute to humid weather and favorable conditions for vegetation growth. By contrast, higher temperatures have led to arid conditions and insufficient rainfall in the northern part of the Plateau, leading to drought and other climatic conditions which are not conducive to increased vegetation cover.     

How does contemporary climate versus climate change velocity affect endemic plant species richness in China？

Climate change is considered a top threat to biodiversity, but the relative roles of contemporary climate versus the rate of climate change in determining spatial patterns of biodiversity are far from clear. China has a very diverse flora and harbors a high percentage of endemic species, but the mechanisms underlying spatial patterns of plant endemism are poorly understood. This study explores the geographical patterns of a representative sample of 555 endemic seed plant species at the scale of 0.5° latitude × 0.5°longitude. Ordinary least squares and spatial autoregressive models were compared to assess the relationship between richness of endemics and the rate of climate change in the past century, as well as a group of contemporary climate variables. In China, a high level of endemism was associated with high elevation and low rate of climate change. However, contemporary climate had a stronger impact than climate change velocity in the past century on endemic species richness patterns. Specifically,mean annual precipitation and annual range of temperature were important contemporary climatic factors. The rate of change of annual mean temperature, but not that of annual precipitation, also significantly contributed to the spatial pattern of plant endemic species richness. We found no significant relationship between topographic variation and endemic species richness, while temperature variability at multiple time scales was strongly correlated with the species richness pattern. Future work should consider the direction of climate change and incorporate higher-resolution data.     

Simulation of historical and projected climate change in arid and semiarid areas by CMIP5 models

Based on Climatic Research Unit Time Series3.1 temperature and Global Precipitation Climatology Center full data reanalysis version 6 precipitation data,the abilities of climate models from the fifth phase of the Coupled Model Intercomparison Project to simulate climate changes over arid and semiarid areas were assessed.Simulations of future climate changes under different representative concentration pathways(RCPs)were also examined.The key findings were that most of the models are able to capture the dominant features of the spatiotemporal changes in temperature,especially the geographic distribution,during the past 60 years,both globally as well as over arid and semiarid areas.In addition,the models can reproduce the observed warming trends,but with magnitudes generally less than the observations of around0.1–0.3°C/50a.Compared to temperature,the models perform worse in simulating the annual evolution of observed precipitation,underestimating both the variability and tendency,and there is a huge spread among the models in terms of their simulated precipitation results.The multimodel ensemble mean is overall superior to any individual model in reproducing the observed climate changes.In terms of future climate change,an ongoing warming projected by the multi-model ensemble over arid and semiarid areas can clearly be seen under different RCPs,especially under the high emissions scenario(RCP8.5),which is twice that of the moderate scenario(RCP4.5).Unlike the increasing temperature,precipitation changes vary across areas and are more significant under high-emission RCPs,with more precipitation over wet areas but less precipitation over dry areas.In particular,northern China is projected to be one of the typical areas experiencing significantly increased temperature and precipitation in the future.     

Diversity of arbuscular mycorrhizal fungal spore communities and its relations to plants under increased temperature and precipitation in a natural grassland

Arbuscular mycorrhizal fungi(AMF)form mutualisms with most plant species,and therefore,understanding how AMF communities will respond to climate change is essential for predictions of changes in plant communities.To evaluate the impact of global climate change on AMFs and plant-AMF interactions in a natural grassland in Inner Mongolia,both artificial warming and watering treatments were assigned to experimental plots.Our results indicate that(1)warming and precipitation significantly affected the relative spore abundance of abundant sporulating AMF species;(2)the relative abundance of weak sporulating AMF species and AMF diversity decreased under experimental warming;(3)evidence was found that the composition of the AMF community in a given year might be correlated with plant community composition in the following year;and(4)grasses and forbs showing different preferences to Claroideoglomus etunicatum or Ambispora gerdemannii dominated plots.Our results imply that climate change appears to induce changes in AMF assemblages with knock-on effects on grassland plant communities.AMF communities may play a much more important role than we have thought in the responses of ecosystem to global climate changes.     

Sensitivity of pollen factors in the climate transfer function

Constructing a mathematic transfer function of pollen and climatic factors is one of the most important approaches in the quantitative reconstruction of paleoclimate elements.In the function building,the key point is the response sensitivity to the climate change for different pollen families and categories. As an example in this paper,the pollen samples from the surface and stratum in Dajiuhu basin,Shennongjia are used to estimate the sensitivity of pollen factor-temperature in the transfer function by the EOF analysis,multiple regression and stepwise regression techniques.Thereafter,the selection methods of pollen factors are discussed and compared with other results from different researchers. The results show that in the pollen samples,the quantity of woody plants is larger than others,but the woody plants have relatively lower sensitivity and slow responses to the climate evolution and abrupt climate change.While the pollens from lower grade plants(herb and fern)have a relatively high sensi- tivity to the temperature change and fast response to the abrupt climate changes.Therefore,the pollen of herb and fern may significantly record the extreme events in the climate change.Also in different regions,the pollen samples have different sensitivity and optimum combination in the transfer functions.Final conclusion is that the stepwise regression is one of the best methods for transfer function building since it can obtain the maximum multiple correlation coefficients and optimum combination of sensitive pollen factors.     

Runoff sensitivity to climate changes in the Longitudinal Range-Gorge Region （LRGR）： An example of the Longchuan Basin in the Upper Yangtze

The sensitivity of runoff to the climate change in the Longitudinal Range-Gorge Region （LRGR） in southwest China was investigated with a case study in the Longchuan Basin of the upper Yangtze River, where the climate change is more complex due to the influences from both global warming and local topography. Non-updating artificial neural networks were calibrated and validated at the baseline condition and were used to predict the response of runoff under 25 hypothetical climate scenarios, which were generated by adjusting the baseline temperature by -1, 0, 1, 2 and 3℃ and by scaling rainfall by 0%, ± 10% and ± 20%, The results indicated that runoff is more sensitive to the increase in rainfall. The annual and seasonal runoff changes were determined by the interaction between temperature and rainfall. At seasonal scale, the direction of change in runoff is more determined by temperature in winter and spring; whereas it is more determined by rainfall in summer and autumn. The LRGR in southwest China may experience a higher frequency of floods in the wet season and more serious droughts in the dry season, if a wetter summer and warmer winter is the trend of future climate change, as predicted by many GCMs.     

Meta-analysis and its application in global change research

Meta-analysis is a quantitative synthetic research method that statistically integrates results from in- dividual studies to find common trends and differences. With increasing concern over global change, meta-analysis has been rapidly adopted in global change research. Here, we introduce the methodolo- gies, advantages and disadvantages of meta-analysis, and review its application in global climate change research, including the responses of ecosystems to global warming and rising CO2 and O3 concentrations, the effects of land use and management on climate change and the effects of distur- bances on biogeochemistry cycles of ecosystem. Despite limitation and potential misapplication, meta-analysis has been demonstrated to be a much better tool than traditional narrative review in synthesizing results from multiple studies. Several methodological developments for research synthe- sis have not yet been widely used in global climate change researches such as cumulative meta-analysis and sensitivity analysis. It is necessary to update the results of meta-analysis on a given topic at regular intervals by including newly published studies. Emphasis should be put on multi-factor interaction and long-term experiments. There is great potential to apply meta-analysis to global climate change research in China because research and observation networks have been established (e.g. ChinaFlux and CERN), which create the need for combining these data and results to provide support for governments’ decision making on climate change. It is expected that meta-analysis will be widely adopted in future climate change research.     

Response of tree-ring width to rainfall gradient along the Tianshan Mountains of northwestern China

By comparing the long-term tree-ring growths at various geographic scales, we can make clear the effects of environmental variations on tree growth, and get an understanding of the responses of forest ecosystems to the possible changes in global and regional climate. Radial tree-ring growth of Picea schrenkiana and its relationship to air temperature and precipitation were investigated across longi- tude transects on the north slopes of the Tianshan Mountains in northwestern China. Tree-ring samples were collected and residual chronologies were developed for three different regions along a gradient of decreasing precipitation from west to east. Response-function analysis was conducted to quantify the relationships between tree-ring chronologies and climate variables, such as monthly mean temperature and monthly precipitation from 1961 to 1998, using the PRECON software program. The statistical characteristics of the chronologies showed that the three chronologies constructed in this study con- tained significant environmental signals and were well suitable to reveal the impacts of climatic change on tree growth and forest productivity. Annual ring-width variations were similar among the three sites, but the variability was greatest in the east. This research showed that the growth trends of Picea schrenkiana in the Tianshan Mountains have not followed a uniform pattern. Response-function analy- sis indicated that there were significant correlations between tree growth and climatic factors in all the three regions, among which precipitation was the principal. With decreasing precipitation, the response of tree-ring widths to increasing temperature changed from a positive to a negative correlation. As for precipitation, the positive relationship to tree-ring width always dominates. It could be expected that with increased temperature and decreased precipitation, the importance of precipitation to tree growth would increase, and the response of tree growth to environmental changes would also increase. This study emphasizes the importance of regional-scale investigations into the biosphere-climate interac- tions. The results of this research indicated a substantial increment of tree-ring radial growth as a re- sult of warmer and wetter climate in the eastern regions. However, climate change will have less effect on forest growth and primary production in the western regions.     

Debating about the climate warming

Debating about the climate warming is reviewed. Discussions have focused on the validity of the temperature reconstruction for the last millennium made by Mann et al. Arguments against and for the reconstruction are introduced. Temperature reconstructions by other authors are examined, including the one carried out by Wang et al. in 1996. It is concluded that: (1) Ability of reproducing temperature variability of time scale less than 10 a is limited, so no sufficient evidence proves that the 1990s was the warmest decade, and 1998 was the warmest year over the last millennium. (2) All of the temperature reconstructions by different authors demonstrate the occurrence of the MWP (Medieval Warm Period) and LIA (Little Ice Age) in low frequency band of temperature variations, though the peak in the MWP and trough in LIA varies from one reconstruction to the others. Therefore, terms of MWP and LIA can be used in studies of climate change. (3) The warming from 1975 to 2000 was significant, but we do not know if it was the strongest for the last millennium, which needs to be proved by more evidence.     

Impact of land surface degradation in northern China and southern Mongolia on regional climate

Clear evidence provided by the singular value decomposition (SVD) analysis to the normalized difference vegetation index (NDVI) and precipitation data identifies that there exists a sensitive region of vegetation-climate interaction located in the transitional zone over northern China and its surrounding areas, where the vegetation cover change has the most significant influence on summer precipitation over China.““ Comparison of reanalysis data with station data provides a good method to assess the impacts of land use change on surface temperature, and the most obvious contribution of land use change may be to lead to notable warming over northern China in the interdecadal time scale. Based on the new statistical results, a high-resolution regional integrated environmental model system (RIEMS) is employed to investigate the effects of land surface degradation over the transitional zone and its surrounding areas (northern China and southern Mongolia) on the regional climate. Land degradation results in the decreases in precipitation over northern and southern China, and the increase in between, and increased and decreased temperature over vegetation change areas and the adjacent area to the south, respectively. Not only would it change the surface climate, but also bring the significant influence on the atmospheric circulation. Both the surface climate and circulation changes generally agree to the observed interdecadal anomalies over the last five decades. These integrated statistical and simulated results imply that land surface degradation over the transitional zone in northern China and its surrounding areas could be one of the main causes responsible for the climate anomalies over China, especially the drought over northern China.     

The climatic suitability for maize cultivation in China

To provide scientific support for planning maize production and designing countermeasures against the effects of climate change on the national maize crop, we analyzed the climatic suitability for cultivating maize across China. These analyses were based on annual climate indices at the Chinese national level; these indices influence the geographical distribution of maize cultivation. The annual climate indices, together with geographical information on the current cultivation sites of maize, the maximum entropy (MaxEnt) model, and the ArcGIS spatial analysis technique were used to analyze and predict maize distribution. The results show that the MaxEnt model can be used to study the climatic suitability for maize cultivation. The eight key climatic factors affecting maize cultivation areas were the frost-free period, annual average temperature, ≥0°C accumulated temperature, ≥10°C accumulated temperature continuous days, ≥10°C accumulated temperature, annual precipitation, warmest month average temperature, and humidity index. We classified climatic zones in terms of their suitability for maize cultivation, based on the existence probability determined using the MaxEnt model. Furthermore, climatic thresholds for a potential maize cultivation zone were determined based on the relationship between the dominant climatic factors and the potential maize cultivation area. The results indicated that the importance and thresholds of main climate controls differ for different maize species and maturities, and their specific climatic suitability should be studied further to identify the best cultivation zones. The MaxEnt model is a useful tool to study climatic suitability for maize cultivation.     

Testing the ability of RIEMS2.0 to simulate multi-year precipitation and air temperature in China

RIEMS2.0 （Regional Integrated Environment Modeling System, Version 2.0） is now being developed starting from RIEMS1.0 by the Key Laboratory of Regional Climate Environment Research for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, China. In order to test RIEMS2.0’s ability to simulate long-term climate and its changes, as well as provide a basis for further development and applications, we compare simulated precipitation and air temperature from 1980 to 2007 （simulation duration from Jan. 1, 1979 to Dec. 31, 2007） under different cumulus parameterization schemes with the observed data. The results show that RIEMS2.0 can reproduce the spatial distribution of precipitation and air temperature, but that the model overestimates precipitation with the rainfall center moving northwestward and underestimates air temperature for annual simulations. Annual and interannual variations in precipitation and air temperature for different climate subregions are well captured by the model. Further analysis of summer and winter simulations shows that precipitation is overestimated, except for the Jianghuai-Jiangnan subregions in the winter, and the air temperature bias in the summer is weaker than in the winter. There are larger biases for precipitation and air temperature in semiarid subregions. Anomalies in precipitation and air temperature are also well captured by the model. Although a similar distribution can be found between observed data and simulated results under different cumulus parameterization schemes, these show differences in intensity and location. In sum, RIEMS2.0 shows good stability and does well in simulating the long-term climate and its changes in China.