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Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Analyses of the variation characteristics for aridity index (AI) can further enhance the understanding of climate change and have effect on hydrology and agriculture. In this paper, based on the data of 283 standard meteorological stations, the temporal-spatial variations and the influences of climate factors on AI were investigated and the relationship between AI and two climate indices (the Arctic Oscillation (AO); El Nino-Southern Oscillation (ENSO)) were also assessed in northern China (NC) during the period from 1961 to 2012. The results revealed that the annual mean AI decreased at the rate of −0.031 per decade in the past 52 years and the trend was statistically significant at the 0.01 level. The Mann-Kendall (M-K) test presented that the percentages of stations with positive trends and negative trends for AI were 10 and 81.9 % (22.6 % statistically significant), respectively. Spatially, in the western part of 100° E, the extremely dry area declined and the climate tended to become wet obviously. In the eastern part of 100° E, dry area moved toward the east and the south, which resulted in the enhancement of semiarid area and the shrinkage of subhumid area. The contributions of sunshine duration and precipitation to the decline of AI are more than those of other meteorological variables in NC. Moreover, the average temperature has risen significantly and AI decreased in NC, which indicated the existence of 'paradox.' Relationship between climate indices (AO and ENSO) and AI demonstrated that the influence of ENSO on AI overweight the AO on AI in NC. [ABSTRACT FROM AUTHOR]

Extreme heat events have serious effects on human daily life. Accurately capturing the dynamic variance of extreme high-temperature distributions in a timely manner is the basis for analyzing the potential impacts of extreme heat, thereby informing risk prevention strategies. This paper demonstrates the potential application of multiple source remote sensing data in mapping and monitoring the extreme heat events that occurred on Aug. 8, 2013 in Jiangsu Province, China. In combination with MODIS products, the thermal sharpening (TsHARP) method and a binary linear model are compared to downscale the original daytime FengYun 2F (FY-2F) land surface temperature (LST) imagery, with a temporal resolution of 60 min, from 5 km to 1 km. Using the meteorological measurement data from Nanjing station as the reference, the research then estimates the instantaneous air temperature by using an iterative computation based on the Surface Energy Balance Algorithm for Land (SEBAL), which is used to analyze the spatio-temporal air temperature variance. The results show that the root mean square error (RMSE) of the LST downscaled from the binary linear model is 1.30°C compared to the synchronous MODIS LST, and on this basis the estimated air temperature has the RMSE of 1.78°C. The spatial and temporal distribution of air temperature variance at each geographical location from 06:30 to 18:30 can be accurately determined, and indicates that the high temperature gradually increases and expands from the city center. For the spatial distribution, the air temperature and the defined scorching temperature proportion index increase from northern to middle, to southern part of Jiangsu, and are slightly lower in the eastern area near the Yellow Sea. In terms of temporal characteristics, the percentage of area with air temperature above 37°C in each city increase with time after 10:30 and reach the peak value at 14:30 or 15:30. Then, they decrease gradually, and the rising and falling trends become smaller from the southern cities to the northern regions. Moreover, there is a distinct positive relationship between the percentage of area above 37°C and the population density. The above results show that the spatio-temporal distributions of heat waves and their influencing factors can be determined by combining multiple sources of remotely sensed image data. [ABSTRACT FROM AUTHOR]

The parameterization of physical processes is one of the critical elements to properly simulate the regional climate over eastern China. It is essential to conduct detailed analyses on the effect of physical parameterization schemes on regional climate simulation, to provide more reliable regional climate change information. In this paper, we evaluate the 25-year (1983-2007) summer monsoon climate characteristics of precipitation and surface air temperature by using the regional spectral model (RSM) with different physical schemes. The ensemble results using the reliability ensemble averaging (REA) method are also assessed. The result shows that the RSM model has the capacity to reproduce the spatial patterns, the variations, and the temporal tendency of surface air temperature and precipitation over eastern China. And it tends to predict better climatology characteristics over the Yangtze River basin and the South China. The impact of different physical schemes on RSM simulations is also investigated. Generally, the CLD3 cloud water prediction scheme tends to produce larger precipitation because of its overestimation of the low-level moisture. The systematic biases derived from the KF2 cumulus scheme are larger than those from the RAS scheme. The scale-selective bias correction (SSBC) method improves the simulation of the temporal and spatial characteristics of surface air temperature and precipitation and advances the circulation simulation capacity. The REA ensemble results show significant improvement in simulating temperature and precipitation distribution, which have much higher correlation coefficient and lower root mean square error. The REA result of selected experiments is better than that of nonselected experiments, indicating the necessity of choosing better ensemble samples for ensemble. [ABSTRACT FROM AUTHOR]

We evaluated the potential impact of future climate change on spring maize and single-crop rice in northeastern China (NEC) by employing climate and crop models. Based on historical data, diurnal temperature change exhibited a distinct negative relationship with maize yield, whereas minimum temperature correlated positively to rice yield. Corresponding to the evaluated climate change derived from coupled climate models included in the Coupled Model Intercomparison Project Phase 5 (CMIP5) under the Representative Concentration Pathway 4.5 scenario (RCP4.5), the projected maize yield changes for three future periods [2010-39 (period 1), 2040-69 (period 2), and 2070-99 (period 3)] relative to the mean yield in the baseline period (1976-2005) were 2.92%, 3.11% and 2.63%, respectively. By contrast, the evaluated rice yields showed slightly larger increases of 7.19%, 12.39%, and 14.83%, respectively. The uncertainties in the crop response are discussed by considering the uncertainties obtained from both the climate and the crop models. The range of impact of the uncertainty became markedly wider when integrating these two sources of uncertainty. The probabilistic assessments of the evaluated change showed maize yield to be relatively stable from period 1 to period 3, while the rice yield showed an increasing trend over time. The results presented in this paper suggest a tendency of the yields of maize and rice in NEC to increase (but with great uncertainty) against the background of global warming, which may offer some valuable guidance to government policymakers. [ABSTRACT FROM AUTHOR]

The ultimate goal of climate research is to produce climate predictions on various time scales. In China, efforts to predict the climate started in the 1930s. Experimental operational climate forecasts have been performed since the late 1950s, based on historical analog circulation patterns. However, due to the inherent complexity of climate variability, the forecasts produced at that time were fairly inaccurate. Only from the late 1980s has seasonal climate prediction experienced substantial progress, when the Tropical Ocean and Global Atmosphere project of the World Climate Research program (WCRP) was launched. This paper, following a brief description of the history of seasonal climate prediction research, provides an overview of these studies in China. Processes and factors associated with the climate variability and predictability are discussed based on the literature published by Chinese scientists. These studies in China mirror aspects of the climate research effort made in other parts of the world over the past several decades, and are particularly associated with monsoon research in East Asia. As the climate warms, climate extremes, their frequency, and intensity are projected to change, with a large possibility that they will increase. Thus, seasonal climate prediction is even more important for China in order to effectively mitigate disasters produced by climate extremes, such as frequent floods, droughts, and the heavy frozen rain events of South China. [ABSTRACT FROM AUTHOR]

This paper provides a review of paleoclimate modeling activities in China. Rather than attempt to cover all topics, we have chosen a few climatic intervals and events judged to be particularly informative to the international community. In historical climate simulations, changes in solar radiation and volcanic activity explain most parts of reconstructions over the last millennium prior to the industrial era, while atmospheric greenhouse gas concentrations play the most important role in the 20th century warming over China. There is a considerable model-data mismatch in the annual and boreal winter temperature change over China during the mid-Holocene [6000 years before present (ka BP)], while coupled models with an interactive ocean generally perform better than atmospheric models. For the Last Glacial Maximum (21 ka BP), climate models successfully reproduce the surface cooling trend over China but fail to reproduce its magnitude, with a better performance for coupled models. At that time, reconstructed vegetation and western Pacific sea surface temperatures could have significantly affected the East Asian climate, and environmental conditions on the Qinghai-Tibetan Plateau were most likely very different to the present day. During the late Marine Isotope Stage 3 (30-40 ka BP), orbital forcing and Northern Hemisphere glaciation, as well as vegetation change in China, were likely responsible for East Asian climate change. On the tectonic scale, the Qinghai-Tibetan Plateau uplift, the Tethys Sea retreat, and the South China Sea expansion played important roles in the formation of the East Asian monsoon-dominant environment pattern during the late Cenozoic. [ABSTRACT FROM AUTHOR]

Meteorological disasters have increasingly become one of the important interferences limiting vegetation growth and productivity recent years, especially in ecologically fragile regions. However, it is unknown how much the impact of meteorological disaster on the vegetation in ecologically fragile area under the changing climate. This study aims to identify the spatial and temporal distribution of four meteorological disasters (drought, rainstorm, high temperature, and low temperature) as well as net primary productivity (NPP) reduction rate in Guangxi province, China, which has large ecologically fragile Karst areas. We also aim to quantify the relative impact of each disaster on NPP loss. During the last 20 years (2000–2019), there was a decreasing trend for drought indicator (drought days), but an increasing trend for rainstorm (cumulated rainfall for daily rainfall higher than 50 mm and less than 99.9 mm), high temperature (daily maximum air temperature higher than 35°C and less than 37°C days), and low temperature (cumulated thermal time for daily minimum temperature less than 0°C) indictors. In the northeast area of study region, all the intensity of rainstorm, high- and low-temperature disasters showed an increasing trend. Under the more intense and frequent meteorological disasters, 87% study sites (60 stations/69 stations in total) showed an increasing trend in terms of NPP reduction rate. Results on grey correlation between each meteorological disaster and NPP reduction rate showed that high-temperature disaster had the greatest impact (27%) on vegetation growth, followed by drought (25%) and rainstorm (25%) disaster, and then low-temperature (23%) disaster. Our results would be helpful for meteorological disasters warning, vegetation protecting as well as policies making for governments. [ABSTRACT FROM AUTHOR]

This paper describes 2007/2008 inter-annual changes in runoff from the Zhadang Glacier located on the northern slope of Nyainqêntanglha Range, Tibet, and analyzes their causes. Precipitation increased by 17.9% in summer months of 2008 compared with the same period in 2007, drainage basin runoff decreased by 33.3%, and glacial meltwater decreased by 53.8%. Change in positive accumulated air temperature explained approximately half of the inter-annual difference in glacial meltwater using a degree-day model. This suggests that the glacier is extremely sensitive to changes in air temperature. Energy balance analysis showed that change in glacier surface albedo, considered to be caused by difference in precipitation form, resulted in the large inter-annual difference in glacial meltwater. It was shown statistically that precipitation form in the summer months of 2007 was mainly rainfall which comprised 71.5% of total precipitation, while during the same period in 2008 rainfall accounted for 30.7%, with the majority of precipitation falling as snow. Precipitation form should be considered an independent factor when analyzing glacier sensitivity to climate change or forecasting the runoff from certain glaciers. [ABSTRACT FROM AUTHOR]

This paper measures the economic impacts of climate change on China's agriculture based on the Ricardian model. By using county-level cross-sectional data on agricultural net revenue, climate, and other economic and geographical data for 1275 agriculture dominated counties, we find that under most climate change scenarios both higher temperature and more precipitation would have an overall positive impact on China's agriculture. However, the impacts vary seasonally and regionally. Autumn effect is the most positive, but spring effect is the most negative. Applying the model to five climate scenarios in the year 2050 shows that the East, the Central part, the South, the northern part of the Northeast, and the Plateau would benefit from climate change, but the Southwest, the Northwest and the southern part of the Northeast may be negatively affected. In the North, most scenarios show that they may benefit from climate change. In summary, all of China would benefit from climate change in most scenarios. [ABSTRACT FROM AUTHOR]

To better understand the variation in mountainous discharge (MD) in the future, a basin case study was conducted in the upstream Taolai River Basin (UTRB) in arid northwestern China. The Blaney-Criddle (B-C) equation, Budyko framework, and water balance method were coupled for MD calculations. The outputs of 10 global climate models (GCMs) are synthesized to confirm the future changes in air temperature and precipitation under 3 selected Representative Concentration Pathway (RCP) scenarios. The climate elasticity (CE) method was used to determine the variation in MD, and the influence of climate factors on that was quantitatively analyzed. The results reveal that the coupling framework of the three methods is suitable for MD determination in the UTRB. The weight-based synthesis of the 10 GCM outputs shows overall increases in temperature (T) and precipitation (P) under the 3 scenarios during most of the time until 2099. The above climate change leads to an increase in MD. According to CE analysis, the positive effectiveness of precipitation is greater than the negative effectiveness of temperature on MD variation, and the increase in precipitation would induce more MD in the UTRB. Uncertainty analysis reveals that GCM outputs dominate in predicting precipitation, while the RCP scenarios influence temperature more. Overall, under the background of climate change, the risk of extreme floods during wet years might increase, and a water deficit will still occur during normal and dry years. The study provides a case example for better understanding MD responses to climate change in the upper reaches of inland river basins. Findings are helpful for reasonable water resource development and utilization in the middle and lower reaches of these basins in the future. As in the Taolai River Basin, considering the future water demand across the whole basin, the development of water-saving technologies and reasonable industrial structures is crucial for a sustainable future. [ABSTRACT FROM AUTHOR]

In this study, a stepwise-clustered statistical downscaling model is established to simulate future apparent temperatures based on NCEP reanalysis data and four global climate models (GCMs). AP is a metric used to quantify thermal comfort or discomfort. The model can express nonlinear relationships between variables at large scale and local scale. The model is employed for projecting future apparent temperature changes over the Pearl River Delta (PRD), on the south coast of China, under three representative concentration pathways (RCP) scenarios. The cluster tree generated for the daily apparent temperature is calibrated for the period 1971–1990 and validated for the period 1991–2000. The R2 values obtained for the validation period at eight selected cities for four GCMs (i.e., CanESM2, CNRM-CM5, CSIRO-Mk3-6-0, and IPSL-CM5A-LR) are 0.88, 0.87, 0.86, and 0.87, respectively. The results reflected that apparent temperature is projected to have a constant increment over the PRD in the future period (2035–2095). Moreover, the monthly apparent temperature in April has the largest expected increment in the future period, while the smallest increment is found in January. The results also indicated that the apparent temperature increases faster than the air temperature under the RCP4.5 and the RCP8.5 scenarios in the PRD. The findings illuminate that the expected increase in apparent temperature over the PRD can be mainly explained by increasing air temperatures and decreasing wind speeds. The results can provide decision makers with useful information for urban health risk assessments. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We performed a regional geological survey in discontinuous permafrost (PF) area along the Bei'an to Heihe Expressway between September 2009 and October 2016 to investigate the state and change of PF in northeast China. Underground resistivity changes were periodically detected along the foot of the subgrade and soil temperatures were monitored under the road foundation. We combined local meteorological and average annual air temperature data to analyze changes in PF thickness. The climate data show that the average annual temperature has gradually increased in the study area since 1980, rising to 0 °C around 1990, and the frost number has decreased to less than 0.5 since 1988. The soil temperature results show that the PF temperature in this section is higher than − 1 °C and is in a high-temperature PF zone affected by changes in seasonal air temperature. The PF under the left foot of the subgrade (LPF) and under the road central separation zone of the road (CPF) both show a decreased PF table, increased PF base, and severe PF degradation. Owing to different cover thicknesses, as well as differences in heat transfer between frozen and unfrozen soil, the base of LPF degraded faster than its table, to CPF the opposite is true. Underground resistivity measurements to verify the accuracy of the PF degradation results. The ground temperature monitoring data and climate data show good consistency. Comprehensive analysis results show that PF in the study area is in a strong degradation stage and will soon disappear. [ABSTRACT FROM AUTHOR]

Landslides result in a significant number of casualties every year in China. The frequency and intensity of extreme precipitation are expected to increase due to climate change, leading to a change in landslide occurrence. This study focuses on climate change impacts on event rainfall characteristics that are commonly linked to landslide occurrence in China. A modelling framework was proposed to quantitatively assess the spatiotemporal change in event rainfall characteristics influencing landslide occurrences in China under future scenarios. First, an algorithm was used to extract the rainfall events from observed precipitation data and the 21 Global Circulation Models dataset. Then, the cumulative event rainfall-rainfall duration (E-D) threshold was identified and used as a proxy of landslide occurrence. Finally, the historical (1971–2000) and future (2031–2060 and 2066–2095) data of 21 GCMs were then applied to determine the E-D threshold in areas highly susceptible to landslides in China to assess the impact of climate change. Landslide occurrence is projected to increase potentially under all GCMs, by amounts ranging from 19.9% to 33.2% in the late 21st century compared to the historical period under the RCP4.5 and RCP85 scenarios, respectively. There are regional differences in the impact of climate change. Future landslide increases in the Northwest region and the Qinghai-Tibet region are the most significant, with consistency among multiple GCMs. However, there is only a slight increase in the South China region with high uncertainty. The monthly variations in landslides are bimodal, with the largest increases in spring and autumn. The results indicate that using a single GCM to assess climate change impacts may have biases, and consideration of median trends and variations among multiple GCMs is suggested. However, the study is a first hint on how climate change may affect landslide occurrence in the future, as the assessment of the effect of climate change on landslides is not straightforward based on only the precipitation-related proxy. The influence on air temperature and soil moisture and the selection of projection datasets and proxies should be carefully considered when applying the presented methods for climate change impacts on landslide studies. [ABSTRACT FROM AUTHOR]

Investigating oasis effects of different oasis-town configurations is key to understanding the ecological stability of the oasis. However, previous studies have not considered the impacts of oasis–town configurations on oasis effects. In this study, the Weather Research and Forecasting (WRF) model was used to conduct a series of 1-km-resolution simulations of the Hami Oasis, Xinjiang of China, to examine how different oasis–town configurations influenced the oasis effects. The actual landscape and four hypothetical landscapes were considered. Results indicated that the WRF model effectively reproduced the trends of the surface temperature, 2-m air temperature, 2-m relative humidity, and 10-m wind speed. It was also found that the effects of the town on the oasis were substantially greater when the former was located at the center of the oasis, rather than on the margin. At 850 hPa, the center of the temperature field was downstream from that of the wind field, whereas both coincided at lower levels. When the size of the town was doubled, the convergence center over the town weakened the strength of the divergent low-level winds from the oasis. This facilitated the infiltration of dry air from the surrounding desert into the oasis, which is detrimental to the healthy development of the oasis. Placing a town at the margin of the oasis is therefore advantageous to the development of the cold island, whereas a town at the center of the oasis is beneficial to the comfort of the residents. [ABSTRACT FROM AUTHOR]

The spatial and temporal variations of the vegetation carbon flux in China from 1901 to 2005 were studied using the vegetation net primary production (NPP) values from seven Earth-system models. In addition, the temporal and spatial changes in the nitrogen deposition flux in China were studied using the NHx and NOx fluxes from 1901 to 2005. The relationship between changes in the carbon flux, nitrogen flux and climate was analyzed. The results show that (1) over the past 100 years, NPP in China has shown an upward trend. The average trend coefficient is 0.88 and the NPP distribution trend is generally low in the north and high in the south, with a gradual increase from the northwest to the southeast. Temperature, precipitation and radiation are all conducive to plant growth in the direction of the gradient. The correlation coefficients between the ensemble model mean NPP and temperature, precipitation, longwave radiation and shortwave radiation are 0.88,0.73,0.91 and 0.67, respectively. (2) In the past 100 years, the NHx and NOy fluxes in China have shown an upward trend, with trend coefficients of 0.98 and 0.98, respectively, which pass the 99.9% confidence level of the t-test. NHx and NOy fluxes are also generally low in the north and high in the south, with a gradual increase from the northwest to the southeast in a step-like pattern. (3) The spatial distribution of the correlation coefficients between the NHx and NOy fluxes and air temperature is similar, with only slight differences in values. The spatial distribution of the correlation coefficients between the NHx and NOy fluxes and precipitation is similar in overall pattern, but the pattern is relatively complicated, with a positive-negative-positive-negative-positive pattern occurring across the monsoon region from north to south, and a negative-positive-negative-positive pattern occurring beyond the monsoon region from east to west. (4) The spatial distribution of the correlation coefficients between the NHx and NOy fluxes and NPP shows a generally consistent pattern, but the pattern is relatively uneven. The average distribution of the ensemble model mean is positive correlation in northeast China and southwest China, and alternating positive and negative correlation in other regions. [ABSTRACT FROM AUTHOR]

We investigate a record-breaking heat wave in southern China (SC) and explore its association with the South China Sea (SCS) summer monsoon (SCSSM), using station observations and various reanalysis products. This heat wave event started in mid-May 2018 and persisted more than 15 days, when the maximum air temperature anomaly exceeded 6 °C. Meanwhile, the onset of the SCSSM was extremely late in 2018, primarily due to the intrusion of easterly winds over the SCS. We show that the anomalous easterlies over the SCS associated with the delayed SCSSM could block the moisture transport from the tropical oceans to SC, which led to decreased rainfall, increased surface radiation, and elevated probability of heat wave in SC during May 2018. Further analysis reveals that both SC heat waves and SCSSM were significantly affected by the Pacific subtropical high (PSH). The westward extension of the PSH can hinder the establishment of SCSSM via inducing easterly anomalies over the SCS, which reduces SC rainfall and results in a drier surface condition. Moreover, the westward displacement of the PSH may cause anomalously high pressures, descending air motions, and divergent winds over SC, which triggers above-normal air temperatures that are conducive to the occurrences of SC heat waves. This study also underlines the importance of Eurasian planetary wave trains in bridging the upstream climate variability and the changes in PSH during boreal spring, which could be used to improve the intra-seasonal predictions of SC heat wave and SCSSM onset. [ABSTRACT FROM AUTHOR]

Observational data from the Roshydromet hydrometeorological stations for 1978–2017, global meteorological network, and objective analysis and reanalysis (NOAA) are used to study the interannual variability of sea surface temperature and air temperature in the coastal and marine areas of the Okhotsk, Japan, Yellow, East China, and South China seas at the modern stage of the warming. Based on the EOF, cluster, and correlation analysis, the spatiotemporal pattern of temperature variations is analyzed and the zoning of sea areas according to the features of modern climate change is performed. The possible cause-and-effect relationships between these changes and the variations in wind components and climate indices are investigated. The studies revealed, specified, and quantified the modern trends and regional features of interannual variability of thermal conditions in the distinguished areas. [ABSTRACT FROM AUTHOR]

Gridded climatic datasets with fine spatial resolution can potentially be used to depict the climatic characteristics across the complex topography of China. In this study, we collected records of monthly temperature at 1153 stations and precipitation at 1202 stations in China and neighboring countries to construct a monthly climate dataset in China with a 0.025° resolution (~ 2.5 km). The dataset, named LZU0025, was designed by Lanzhou University and used a partial thin plate smoothing method embedded in the ANUSPLIN software. The accuracy of LZU0025 was evaluated based on three aspects: (1) Diagnostic statistics from the surface fitting model during 1951–2011. The results indicate a low mean square root of generalized cross validation (RTGCV) for the monthly air temperature surface (1.06 °C) and monthly precipitation surface (1.97 mm1/2). The method used variable square root transformation for the spline surface fitting to reduce positive skewness in the measured precipitation values and no variable transformation in air temperature case. This indicates that the surface fitting models are accurate. (2) Error statistics of comparisons between interpolated monthly LZU0025 with the withholding of climatic data from 265 stations during 1951–2011. The results show that the predicted values closely tracked the real true values with values of mean absolute error (MAE) of 0.59 °C and 70.5 mm and standard deviation of the mean error (STD) of 1.27 °C and 122.6 mm. In addition, the monthly STDs exhibited a consistent pattern of variation with RTGCV. (3) Comparison with other datasets. This was done in two ways. The first was via comparison of standard deviation, mean, and time trend derived from all datasets to a reference dataset released by the China Meteorological Administration (CMA), using Taylor diagrams. The second was to compare LZU0025 with the station dataset in the Tibetan Plateau. Taylor diagrams show that the standard deviation derived from LZU had a higher correlation with that produced by the CMA (R = 0.76 for air temperature, and R = 0.96 for precipitation) compared to those from other datasets. The standard deviation for the index derived from LZU was more close to that induced from CMA, and the centered normalized root-mean-square difference for this index derived from LZU and CMA was lower. A similar superior performance of LZU was found in the comparison of mean and time trend derived from LZU and those from other datasets. LZU0025 had high correlation with the Coordinated Energy and Water Cycle Observation Project (CEOP)—Asian Monsoon Project (CAMP) Tibet surface meteorology station dataset for air temperature, despite a non-significant correlation for precipitation at a few stations. Based on this comprehensive analysis, we conclude that LZU0025 is a reliable dataset. LZU0025, which has a fine resolution, can be used to identify a greater number of climate types, such as tundra and subpolar continental, along the Himalayan Mountain. We anticipate that LZU0025 can be used for the monitoring of regional climate change and precision agriculture modulation under global climate change. [ABSTRACT FROM AUTHOR]

Glaciers have very different dynamic characteristics during the ablation and accumulation seasons. A dynamic model to study the flow of the Koxkar Glacier is used. Ice velocity, ice viscosity, and the stress variation at different depths were studied. The aim was to compare the change in the glacier’s physical characteristics with changes in air temperature, analyze the movement mechanism at different temperatures in different seasons, and identify why temperature is the main driving force of glacier movement and change. The results show that the surface stresses have similar trends in different seasons, and that the stress in winter is larger than that in summer. This causes the ice body to break and promotes crack formation. Ice viscosity has an obvious seasonal variation, and this is especially noticeable for near-surface ice viscosity. The stress at the bottom did not change much at different temperatures. This indicates that the stress at the bottom is mainly affected by glacier morphology, hydrological characteristics, and geothermal flow. [ABSTRACT FROM AUTHOR]

The lofty and extensive Tibetan Plateau has significant mass elevation effect (MEE). In recent years, a great effort has been made to quantify MEE, with the recognition of intra-mountain basal elevation (MBE) as the main determinant of MEE. In this study, we improved the method of estimating MEE with MODIS and NECP data, by refining temperature laps rate, and dividing MBE plots, and then analyzed the spatio-temporal variation of MEE in the Plateau. The main conclusions include: 1) the highest average annual MEE of the plateau is as high as 11.5488°C in the southwest of the plateau, where exists a high-MEE core and MEE takes on a trend of decreasing from the core to the surrounding areas; 2) in the interior of the plateau, the maximum monthly MEE is 14.1108°C in the highest MBE plot (4934 m) in August; while the minimum monthly MEE appeared primarily in January and February; 3) in the peripheral areas of the plateau, annual mean MEE is relatively low, mostly between 3.0068°C-5.1972°C, where monthly MEE is high in January and December and low in June and July, completely different from the MEE time-series variation in the internal parts of the plateau. [ABSTRACT FROM AUTHOR]

China has announced plans to stabilize its pesticide use by 2020. Yet, future climate change will possibly increase the difficulty of meeting this goal. This study uses econometric estimation to explore how climate impacts Chinese pesticide usage and subsequently to project the future implications of climate change on pesticide use. The results indicate that both atmospheric temperature and precipitation increase pesticide usage. Under current climate change projections, pesticide usage will rise by +1.1 to 2.5% by 2040, +2.4 to 9.1% by 2070, and +2.6 to 18.3% by 2100. Linearly extrapolating the results to 2020 yields an approximately 0.5 to 1.2% increase. Thus, to achieve stabilization, more severe actions are needed to address this increase. Possible actions to achieve the reductions needed include using better monitoring and early warning networks so as to permit early responses to climate change-stimulated increases, enhancing information dissemination, altering crop mix, and promoting nonchemical control means. Additionally, given that increased pesticide usage generally increases health and environmental damage, there may be a need to more widely disseminate safe application procedure information while also strengthening compliance with food safety regulations. Furthermore, pest control strategies will need to be capable of evolving as climate change proceeds. Globally, efforts could be made to (1) scale up agrometeorological services, especially in developing countries; (2) use international frameworks to better align the environmental and health standards in developing countries with those in developed countries; and (3) adapt integrated pest management practices to climate change, especially for fruits and vegetables. [ABSTRACT FROM AUTHOR]

Extreme heat (EH) over North China (NC) is affected by both large scale circulations and local topography, and could be categorized into foehn favorable and no-foehn types. In this study, the performance of a regional coupled model in simulating EH over NC was examined. The effects of regional air-sea coupling were also investigated by comparing the results with the corresponding atmosphere-alone regional model. On foehn favorable (no-foehn) EH days, a barotropic cyclonic (anticyclonic) anomaly is located to the northeast (northwest) of NC, while anomalous northwesterlies (southeasterlies) prevail over NC in the lower troposphere. In the uncoupled simulation, barotropic anticyclonic bias occurs over China on both foehn favorable and no-foehn EH days, and the northwesterlies in the lower troposphere on foehn favorable EH days are not obvious. These biases are significantly reduced in the regional coupled simulation, especially on foehn favorable EH days with wind anomalies skill scores improving from 0.38 to 0.47, 0.47 to 0.61 and 0.38 to 0.56 for horizontal winds at 250, 500 and 850 hPa, respectively. Compared with the uncoupled simulation, the reproduction of the longitudinal position of Northwest Pacific subtropical high (NPSH) and the spatial pattern of the low-level monsoon flow over East Asia are improved in the coupled simulation. Therefore, the anticyclonic bias over China is obviously reduced, and the proportion of EH days characterized by anticyclonic anomaly is more appropriate. The improvements in the regional coupled model indicate that it is a promising choice for the future projection of EH over NC. [ABSTRACT FROM AUTHOR]

This study reveals the impacts of climatic variable trends on drought severity in Xinjiang, China. Four drought indices, including the self-calibrating Palmer drought severity index (sc-PDSI), Erinç's index ( I ), Sahin's index ( I ), and UNEP aridity index (AI), were used to compare drought severity. The ensemble empirical mode decomposition and the modified Mann-Kendall trend test were applied to analyze the nonlinear components and trends of the climatic variable and drought indices. Four and six climatic scenarios were generated in sc-PDSI, I , I , and AI with different combinations of the observed and detrended climatic variables, respectively. In Xinjiang, generally increasing trends in minimal, average, and maximal air temperature ( T , T , T ) and precipitation ( P) were found, whereas a decreasing trend in wind speed at 2 m height ( U ) was observed. There were significantly increasing trends in all of the four studied drought indices. Drought relief was more obvious in northern Xinjiang than in southern Xinjiang. The strong influences of increased P on drought relief and the weak influences of increased T , T , and T on drought aggravation were shown by comparing four drought indices under different climate scenarios. Decreased U had a weak influence on drought, as shown by the AI in different climate scenarios. The weak influences of T and U were considered to be masked by the strong influences of P on droughts. Droughts were expected to be more severe if P did not increase, but were likely milder without an increase in air temperature and with a decrease in U . [ABSTRACT FROM AUTHOR]

This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year) occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year) in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period. [ABSTRACT FROM AUTHOR]

Projections of changes in climate are important in assessing the potential impacts of climate change on natural and social systems. However, current knowledge on assembling different GCMs to estimate future climate change over the Pear River basin is still limited so far. This study examined the capability of BMA and arithmetic mean (AM) method in assembling precipitation and temperature from CMIP5 under RCP2.6, RCP4.5 and RCP8.5 scenarios over the Pearl River basin. Results show that the BMA outperforms the traditional AM method. Precipitation tends to increase over the basin under RCP2.6 and RCP4.5 scenarios, whereas decrease under RCP8.5. The most remarkable increase of precipitation is found in the northern region under RCP2.6 scenario. The linear trend of the monthly mean near-surface air temperature increases with the growing CO concentration. The warming trends in four seasons are distinct. The warming rate is prominent in summer and spring than that in other season, meanwhile it is larger in western region than in other parts of the basin. The findings can provide beneficial reference to water resources and agriculture management strategies, as well as the adaptation and mitigation strategies for floods and droughts under the context of global climate change. [ABSTRACT FROM AUTHOR]

Drought hazard is the main restrictive factor in the field of food production in China, and climate change may aggravate it over the long run. The present study aims to assess the potential drought hazard at present, as well as determine future different climate change scenarios based on the data of monthly precipitation and temperature. Drought is defined using the Standardized Precipitation-Evapotranspiration Index. The probability density function of SPEI was used to create the drought hazard index (DH), which provides a comprehensive overview of the frequency and intensity of drought events. The statistical downscale method was used to convert the regional climate model output grid data into meteorological station data for the near future (2020-2050) under three Representative Concentration Pathways (RCPs). The results showed that in the baseline (1981-2010), DH is much serious in Jilin compared with Henan. In the near future (2020-2050), DH increases in the case of RCP8.5, and the increased scale is larger in Henan. In the case of RCP4.5, the DH will be flat with baseline in Jilin and slightly increase in Henan. DH may relieve in case of RCP2.6. The results can help to optimize agriculture allocation and policy making with regard to climate change adaptation. [ABSTRACT FROM AUTHOR]

Alpine wetlands are considered to be very sensitive to future climate warming. Understanding changes in decomposition rates ( Rs) of soil organic matter (SOM) and temperature sensitivity ( Q) in alpine wetlands, under the scenarios of a warming climate and decreasing soil moisture, is important for predicting their carbon (C) budget. Here, we established three sampling transects from wetland edge to meadow in the Zoige alpine wetlands in China, which represented the gradients of decreasing soil moisture. We conducted an incubation experiment (5-25 °C) to explore changes in Q with the degradation process from alpine wetland to alpine meadow. The results showed that temperature significantly influenced Rs in all locations. Rs first increased from site I to site IV and then decreased from site IV to site V. However, Q and activation energy ( E) showed no apparent trends with soil coming from sites along a moisture gradient. Overall, the Q values in the wetland (sites 1.50) were significantly lower than that of the meadow (1.83); similar trends were observed for E. In addition, E exhibited a negative logarithmic relationship with C quality indices in all locations, which suggested that the C quality-temperature hypothesis is applicable to both alpine wetlands and meadows. These findings provide a theoretical foundation for predicting the potential influences of warming climate on soil C turnover and storage in alpine wetlands. [ABSTRACT FROM AUTHOR]

Both inter- and intra-annual changes in air temperature are impacted by global climate change. Sine curves, such as T = Asin(ω t + φ), adjust the 10-day mean air temperature T contributed by the corresponding number of 10-day t within a year. Based on the curve, relative indices were defined as follows: A, indicating the annual maximum 10-day air temperature; t and t, representing the starting and ending time of the warm season; t and t, indicating the starting and ending time of the growing season; l and l, denoting the length of the warm and growing seasons. The objective of this study was to evaluate the inter- and intra-annual distribution characteristics of the 10-day mean air temperature and the associated spatial patterns, changing trends, and abrupt points in 128 meteorological stations across Northwestern China during 1961 to 2010 by using the selected indices. The results showed that the 2010s had the fastest increase in air temperature during the study period across the study area. Altitude was an important factor affecting the selected indices. Annual mean air temperature ( T) and A were high in low-altitude areas, where the warm and growing season came earlier and ended later, and vice versa. The values of T and A had increased by 1.65 and 0.65 °C during the past 50 years, respectively. The warm and growing season had come earlier by 9 and 7.5 days and ended later by 7.5 and 6 days during the past 50 years, respectively. Therefore, the warm season has gotten longer by 16 days and the growing season by 14 days in the study area during the past 50 years. The abrupt increase of T, A, t, t, t, t, l, and l detected at the 0.05 significance level took place in the late 1960s and that of A occurred in the late 1980s. The inter- and intra-annual distribution of air temperature in Northwestern China has changed during the last five decades, and it is reasonable to expect those changes to continue for a period under global climate change. [ABSTRACT FROM AUTHOR]

Based on the nonlinear Lyapunov exponent and nonlinear error growth dynamics, the spatiotemporal distribution and decadal change of the monthly temperature predictability limit (MTPL) in China is quantitatively analyzed. Data used are daily temperature of 518 stations from 1960 to 2011 in China. The results are summarized as follows: (1) The spatial distribution of MTPL varies regionally. MTPL is higher in most areas of Northeast China, southwest Yunnan Province, and the eastern part of Northwest China. MTPL is lower in the middle and lower reaches of the Yangtze River and Huang-huai Basin. (2) The spatial distribution of MTPL varies distinctly with seasons. MTPL is higher in boreal summer than in boreal winter. (3) MTPL has had distinct decadal changes in China, with increase since the 1970s and decrease since 2000. Especially in the northeast part of the country, MTPL has significantly increased since 1986. Decadal change of MTPL in Northwest China, Northeast China and the Huang-huai Basin may have a close relationship with the persistence of temperature anomaly. Since the beginning of the 21st century, MTPL has decreased slowly in most of the country, except for the south. The research provides a scientific foundation to understand the mechanism of monthly temperature anomalies and an important reference for improvement of monthly temperature prediction. [ABSTRACT FROM AUTHOR]

National Centers for Environmental Prediction recently upgraded its operational seasonal forecast system to the fully coupled climate modeling system referred to as CFSv2. CFSv2 has been used to make seasonal climate forecast retrospectively between 1982 and 2009 before it became operational. In this study, we evaluate the model's ability to predict the summer temperature and precipitation over China using the 120 9-month reforecast runs initialized between January 1 and May 26 during each year of the reforecast period. These 120 reforecast runs are evaluated as an ensemble forecast using both deterministic and probabilistic metrics. The overall forecast skill for summer temperature is high while that for summer precipitation is much lower. The ensemble mean reforecasts have reduced spatial variability of the climatology. For temperature, the reforecast bias is lead time-dependent, i.e., reforecast JJA temperature become warmer when lead time is shorter. The lead time dependent bias suggests that the initial condition of temperature is somehow biased towards a warmer condition. CFSv2 is able to predict the summer temperature anomaly in China, although there is an obvious upward trend in both the observation and the reforecast. Forecasts of summer precipitation with dynamical models like CFSv2 at the seasonal time scale and a catchment scale still remain challenge, so it is necessary to improve the model physics and parameterizations for better prediction of Asian monsoon rainfall. The probabilistic skills of temperature and precipitation are quite limited. Only the spatially averaged quantities such as averaged summer temperature over the Northeast China of CFSv2 show higher forecast skill, of which is able to discriminate between event and non-event for three categorical forecasts. The potential forecast skill shows that the above and below normal events can be better forecasted than normal events. Although the shorter the forecast lead time is, the higher deterministic prediction skill appears, the probabilistic prediction skill does not increase with decreased lead time. The ensemble size does not play a significant role in affecting the overall probabilistic forecast skill although adding more members improves the probabilistic forecast skill slightly. [ABSTRACT FROM AUTHOR]

We have found that a spatial interpolation of mean annual temperature (MAT) in China can be accomplished using a global ordinary least squares regression model since the relationship between temperature and its environmental determinants is constant. Therefore the estimation of MAT does not very across space and thus exhibits spatial stationarity. The interpolation of mean annual precipitation (MAP), however, is more complex and changes spatially as a function of topographic variation. Therefore, MAP shows spatial non-stationarity and must be estimated with a geographically weighted regression. A statistical transfer function (STF) of MAT was formulated using minimized residuals output from a high accuracy and high speed method for surface modeling (HASM) with an ordinary least squares (OLS) linear equation that uses latitude and elevation as independent variables, abbreviated as HASM-OLS. The STF of MAP under a BOX-COX transformation is derived as a combination of minimized residuals output by HASM with a geographically weighted regression (GWR) using latitude, longitude, elevation, impact coefficient of aspect and sky view factor as independent variables, abbreviated as HASM-GWR-BC. In terms of HASM-OLS and HASM-GWR-BC, MAT had an increasing trend since the 1960s in China, with an especially accelerated increasing trend since 1980. Overall, our data show that MAT has increased by 1.44 °C since the 1960s. The warming rates increase from the south to north in China, except in the Qinghai-Xizang plateau. Specifically, the 2,100 °C · d contour line of annual accumulated temperature (AAT) of ≥10 °C shifted northwestward 255 km in the Heilongjiang province since the 1960s. MAP in Qinghai-Xizang plateau and in arid region had a continuously increasing trend. In the other 7 regions of China, MAP shows both increasing and decreasing trends. On average, China became wetter from the 1960s to the 1990s, but drier from the 1990s to 2000s. The Qinghai-Xizang Plateau and Northern China experienced more climatic extremes than Southern China since the 1960s. [ABSTRACT FROM AUTHOR]

Based on runoff, air temperature, and precipitation data from 1960 to 2010, the effects of climate change on water resources in the arid region of the northwestern China were investigated. The long-term trends of hydroclimatic variables were studied by using both Mann-Kendall test and distributed-free cumulative sum (CUSUM) chart test. Results indicate that the mean annual air temperature increases significantly from 1960 to 2010. The annual precipitation exhibits an increasing trend, especially in the south slope of the Tianshan Mountains and the North Uygur Autonomous Region of Xinjiang in the study period. Step changes occur in 1988 in the mean annual air temperature time series and in 1991 in the precipitation time series. The runoff in different basins shows different trends, i.e., significantly increasing in the Kaidu River, the Aksu River and the Shule River, and decreasing in the Shiyang River. Correlation analysis reveals that the runoff in the North Xinjiang (i.e., the Weigan River, the Heihe River, and the Shiyang River) has a strong positive relationship with rainfall, while that in the south slope of the Tianshan Mountains, the middle section of the north slope of the Tianshan Mountains and the Shule River has a strong positive relationship with air temperature. The trends of runoff have strong negative correlations with glacier coverage and the proportion of glacier water in runoff. From the late 1980s, the climate has become warm and wet in the arid region of the northwestern China. The change in runoff is interacted with air temperature, precipitation and glacier coverage. The results show that streamflow in the arid region of the northwestern China is sensitive to climate change, which can be used as a reference for regional water resource assessment and management. [ABSTRACT FROM AUTHOR]

The modern atmospheric observation and literatural historical drought-flood records were used to extract the inter-decadal signals of dry-wet modes in eastern China and reveal the possible relationship of global and China temperature changes associated with the East Asian summer monsoon advances. A climate pattern of 'wet-north and dry-south' in eastern China and cool period in China and globe are associated with the strong summer monsoon that can advance further to the northernmost part in the East Asian monsoon region. On the contrary, a climate pattern of 'dry-north and wet-south' in eastern China and a warm period in China and globe are associated with the weaker summer monsoon that only reaches the southern part in the region. An interdecadal oscillation with the timescale about 60 years was found dominating in both the dry-wet mode index series of the East Asian summer monsoon and the global temperature series after the secular climate states and long-term trend over inter-centennial timescales have been removed. [ABSTRACT FROM AUTHOR]

Recent progress in the study of nonlinear atmospheric dynamics and related predictability of weather and climate in China (2007-2011) are briefly introduced in this article. Major achievements in the study of nonlinear atmospheric dynamics have been classified into two types: (1) progress based on the analysis of solutions of simplified control equations, such as the dynamics of NAO, the optimal precursors for blocking onset, and the behavior of nonlinear waves, and (2) progress based on data analyses, such as the nonlinear analyses of fluctuations and recording-breaking temperature events, the long-range correlation of extreme events, and new methods of detecting abrupt dynamical change. Major achievements in the study of predictability include the following: (1) the application of nonlinear local Lyapunov exponents (NLLE) to weather and climate predictability; (2) the application of condition nonlinear optimal perturbation (CNOP) to the studies of El Niño-Southern Oscillation (ENSO) predictions, ensemble forecasting, targeted observation, and sensitivity analysis of the ecosystem; and (3) new strategies proposed for predictability studies. The results of these studies have provided greater understanding of the dynamics and nonlinear mechanisms of atmospheric motion, and they represent new ideas for developing numerical models and improving the forecast skill of weather and climate events. [ABSTRACT FROM AUTHOR]

Long-term trend and abrupt changes of major climate variables in the Taihu Basin were investigated based on the mean, maximum and minimum air temperature, diurnal temperature range (DTR), precipitation, relative humidity and sunshine duration at six meteorological stations from 1954 to 2006. Results showed that the long-term trend for annual precipitation was not statistically significant during the past 53 years, but a wetter tendency was detected and the increasing centre for annual precipitation was located in the southeast of the study area. Mean air temperature has increased by 1.43°C, similar trends were also identified for maximum and minimum air temperature, which have increased by 1.06 and 1.54°C, respectively, while DTR exhibited a slight decreasing trend with a rate of about −0.09°C/(10 year). The annual mean relative humidity and sunshine duration exhibited a decreasing trend, with Kendall slope values of −0.99%/10 year and −7.797 h/10 year, respectively. Examination of long-range dependence showed that all climate variables exhibited strong persistence at annual scale except minimum air temperature. Detection of abrupt changes using nonparametric Mann-Kendall and Pettitt methods showed different results. Abrupt changes occurred in the 1980s and 2000s for annual precipitation using the nonparametric Mann-Kendall method, while no abrupt changes were detected using the Pettitt method. Abrupt changes of temperature and relative humidity took place in the early 1990s using the nonparametric Mann-Kendall method, which occurred in the late and mid 1980s using the Pettitt method, while abrupt changes of sunshine duration and DTR detected by two methods occurred in the similar period. The result will be helpful for local flood control and drought relief in urban planning and construction under future global climate change. [ABSTRACT FROM AUTHOR]

dataset of air temperature and precipitation time series (1959-2008) from 61 stations across Shanxi, China is used to analyze the climate change. The monotonic trends and step (abrupt) trends for annual and seasonal series data of mean air temperature and total precipitation are tested by using Mann-Kendall test and Mann-Whitney test, respectively. The results show that annual mean air temperature has increased by 1.20°C during the past 50 years. Winter, spring, and autumn have experienced a significant increase in air temperature. The step trend for annual mean air temperature is different from, but closely related with, those for seasonal mean air temperature. Spatially, there is an enhanced warming trend from south to north in Shanxi, and the most remarkable warming occurs in northern Shanxi. Annual precipitation has decreased by 99.20 mm during the past half century. The decrease is mainly caused by precipitation decline in rainy season (June-September), though precipitation in post-rainy season (October-November) also tended to decrease. An abrupt decrease in precipitation has occurred since late 1970s. Decrease in precipitation is highest in central Shanxi and in the area along the west fringe between Sanchuan River and Fenhe River in western Shanxi. [ABSTRACT FROM AUTHOR]

Using historical records on first and last frost and snow, spring cultivation, David peach blossom, autumn crop harvest, grade of sea freeze and change in northern citrus boundary, we reconstructed temperature change during 601-920 AD. The mean temperature of the winter half-year (October to April) over Central East China during this period was about -0.22°C higher than that of the present (1961-2000 AD mean). During 601-820 AD, mean temperature was about -0.52°C higher than the present. During 821-920 AD, the mean temperature was 0.42°C lower than the present. The temperature fluctuations were characterized by a maximum amplitude of 1.05°C at the centennial scale, 1.38°C at the 50-year scale, 2.02°C at the 30-year scale, and 2.3°C at the 20-year scale. There were four peaks warmer than today (601-620 AD, mean of 1°C higher temperature; 641-660 AD, 1.44°C; 701-720 AD, 0.88°C; 781-800 AD, 0.65°C). Three cold periods were in 741-760, 821-840, and 881-900 AD, the mean temperature of which was 0.37-0.87°C lower than the present. [ABSTRACT FROM AUTHOR]

Understanding the role of aerosols in global and regional climate change requires the long-term measurements of aerosol optical properties. We use an indirect method to infer aerosol optical depths (AODs) based on atmospheric visibility and water vapor pressure measured at 504 key climate stations in eastern China (east of 100° E) over 1951–2002. Inferred AODs are compared with the MODIS satellite measurements for year of 2002. Results show that AODs averaged over 1951–2000 exhibit large values in Sichuan Basin and Changjiang River Delta, and there are two belts of high AODs, one from Beijing to South China by the middle reaches of Changjiang River and the other from Beijing to Changjiang Delta. Inferred AODs in eastern China show the lowest value in 1960s, increase dramatically in 1980s, and reach maximum in 1990s. The ratios of the regional and decadal mean AOD in 1950s, 1960s, 1970s, 1980s, and 1990s to that in 1960s are 1.085, 1.0, 1.066, 1.195, and 1.22, respectively. Statistical analysis shows that variations in AODs correlate with the changes in precipitation and air temperature in eastern China over the past 50 years. Correlation coefficients between annual mean AOD and precipitation are 0.39, 0.37, and 0.57 in the upper (Sichuan Basin), middle, and lower reaches of the Changjiang River, respectively. In the Sichuan Basin, the increase in annual mean AOD correlates with the reduction in air temperature with a correlation coefficient of −0.33 at 95% confidence level. [ABSTRACT FROM AUTHOR]

The reconstructed temperature anomalies in the eastern China were compared with the output from a 1000-year model simulation in an attempt to evaluate the model's regional simulation skills and to understand the causes of climate change in China over the last millennium. The reconstructed data are the winter half-year temperature anomalies in the central region of eastern China (25°–40°N, east of 105°E) for the last 1000 years with a 30-year resolution. The model used is the global atmosphere-ocean coupled climate model, ECHO-G, which was driven by time-varying external forcings including solar radiation, volcanic eruptions, and greenhouse gas concentrations (CO2 and CH4) for the same period. The correlation coefficient between the simulated and reconstructed time series is 0.37, which is statistically significant at a confidence level of 97.5%. The Medieval Warm Period (MWP) during 1000–1300 A.D., the Little Ice Age (LIA) during 1300–1850 A.D. and the modern warming period after 1900 A.D. are all recognizable from both the simulated and reconstructed temperatures. The anomalies associated with the LIA and the modern warming simulated by the model are in good consistency with the reconstructed counterpart. In particular during the Maunder sun-spot minimum (1670–1710 A.D.), both the simulated and reconstructed temperature anomalies reach their minima without any phase difference. But in the earlier MWP, significant discrepancies exist between the simulation and the reconstruction, which might reflect the degrading quality of the reconstruction data. The range of the simulated anomalies (1.62 K) is comparable with that of reconstructed (2.0 K). Diagnosis of the model results indicates that, during the last millennium, variations in solar radiation and volcanic activity are the main controlling factors on regional temperature change, while in the recent 100 years, the change of the concentration of greenhouse gases plays most important role in explaining the rapid temperature rising. [ABSTRACT FROM AUTHOR]