Recent Progress in Studies of Climate Change in China

An overview of basic research on climate change in recent years in China is presented. In the past 100 years in China, average annual mean surface air temperature （SAT） has increased at a rate ranging from 0.03℃ （10 yr）-1 to 0.12℃ （10 yr）-1. This warming is more evident in northern China and is more significant in winter and spring. In the past 50 years in China, at least 27% of the average annual warming has been caused by urbanization. Overall, no significant trends have been detected in annual and/or summer precipitation in China on a whole for the past 100 years or 50 years. Both increases and decreases in frequencies of major extreme climate events have been observed for the past 50 years. The frequencies of extreme temperature events have generally displayed a consistent pattern of change across the country, while the frequencies of extreme precipitation events have shown only regionally and seasonally significant trends. The frequency of tropical cyclone landfall decreased slightly, but the frequency of sand/dust storms decreased significantly. Proxy records indicate that the annual mean SAT in the past a few decades is the highest in the past 400-500 years in China, but it may not have exceeded the highest level of the Medieval Warm Period （1000 1300 AD）. Proxy records also indicate that droughts and floods in eastern China have been characterized by continuously abnormal rainfall periods, with the frequencies of extreme droughts and floods in the 20th century most likely being near the average levels of the past 2000 years. The attribution studies suggest that increasing greenhouse gas （GHG） concentrations in the atmosphere are likely to be a main factor for the observed surface warming nationwide. The Yangtze River and Huaihe River basins underwent a cooling trend in summer over the past 50 years, which might have been caused by increased aerosol concentrations and cloud cover. However, natural climate variability might have been a main driver for the mean and extreme precipitation variations observed over the past century. Climate models generally perform well in simulating the variations of annual mean SAT in China. They have also been used to project future changes in SAT under varied GHG emission scenarios. Large uncertainties have remained in these model-based projections, however, especially for the projected trends of regional precipitation and extreme climate events.

Multi-year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model (RegCM_NCC). Part Ⅰ: Sensitivity Study

A modified version of the NCAR/RegCM2 has been developed at the National Climate Center （NCC）, China Meteorological Administration, through a series of sensitivity experiments and multi-year simulations and hindcasts, with a special emphasis on the adequate choice of physical parameterization schemes suitable for the East Asian monsoon climate. This regional climate model is nested with the NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM to make an experimental seasonal prediction for China and East Asia. The four-year （2001 to 2004） prediction results are encouraging. This paper is the first part of a two-part paper, and it mainly describes the sensitivity study of the physical process paraxneterization represented in the model. The systematic errors produced by the different physical parameterization schemes such as the land surface processes, convective precipitation, cloud-radiation transfer process, boundary layer process and large-scale terrain features have been identified based on multi-year and extreme flooding event simulations. A number of comparative experiments has shown that the mass flux scheme （MFS） and Betts-Miller scheme （BM） for convective precipitation, the LPMI （land surface process model I） and LPMII （land surface process model Ⅱ） for the land surface process, the CCM3 radiation transfer scheme for cloud-radiation transfer processes, the TKE （turbulent kinetic energy） scheme for the boundary layer processes and the topography treatment schemes for the Tibetan Plateau are suitable for simulations and prediction of the East Asia monsoon climate in rainy seasons. Based on the above sensitivity study, a modified version of the RegCM2 （RegCM_NCC） has been set up for climate simulations and seasonal predictions.

A Modeling Study of the Effects of Direct Radiative Forcing Due to Carbonaceous Aerosol on the Climate in East Asia

The study investigated the effects of global direct radiative forcing due to carbonaceous aerosol on the climate in East Asia, using the CAM3 developed by NCAR. The results showed that carbonaceous aerosols cause negative forcing at the top of the atmosphere （TOA） and surface under clear sky conditions, but positive forcing at the TOA and weak negative forcing at the surface under all sky conditions. Hence, clouds could change the sign of the direct radiative forcing at the TOA, and weaken the forcing at the surface. Carbonaceous aerosols have distinct effects on the summer climate in East Asia. In southern China and India, it caused the surface temperature to increase, but the total cloud cover and precipitation to decrease. However, the opposite effects are caused for most of northern China and Bangladesh. Given the changes in temperature, vertical velocity, and surface streamflow caused by carbonaceous aerosol in this simulation, carbonaceous aerosol could also induce summer precipitation to decrease in southern China but increase in northern China.

Multi-Year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model (RegCM_NCC) Part Ⅱ:The Experimental Seasonal Prediction

A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center （NCC） since 2001. The NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM （CGCM） provides the boundary and initial conditions for driving the regional climate model （RegCM_NCC）. The latter has a 60-km horizontal resolution and improved physical parameterization schemes including the mass flux cumulus parameterization scheme, the turbulent kinetic energy closure scheme （TKE） and an improved land process model （LPM）. The large-scale terrain features such as the Tibetan Plateau are included in the larger domain to produce the topographic forcing on the rain-producing systems. A sensitivity study of the East Asian climate with regard to the above physical processes has been presented in the first part of the present paper. This is the second part, as a continuation of Part Ⅰ. In order to verify the performance of the nested regional climate model, a ten-year simulation driven by NCEP reanalysis datasets has been made to explore the performance of the East Asian climate simulation and to identify the model＇s systematic errors. At the same time, comparative simulation experiments for 5 years between the RegCM2 and RegCM_NCC have been done to further understand their differences in simulation performance. Also, a ten-year hindcast （1991-2000） for summer （June-August）, the rainy season in China, has been undertaken. The preliminary results have shown that the RegCM_NCC is capable of predicting the major seasonal rain belts. The best predicted regions with high anomaly correlation coefficient （ACC） are located in the eastern part of West China, in Northeast China and in North China, where the CGCM has maximum prediction skill as well. This fact may reflect the importance of the largescale forcing. One significant improvement of the prediction derived from RegCM_NCC is the increase of ACC in the Yangtze River valley where the CGCM has a very low, even a negative, ACC. The reason behind this improvement is likely to be related to the more realistic representation of the large-scale terrain features of the Tibetan Plateau. Presumably, many rain-producing systems may be generated over or near the Tibetan Plateau and may then move eastward along the Yangtze River basin steered by upper-level westerly airflow, thus leading to enhancement of rainfalls in the mid and lower basins of the Yangtze River. The real-time experimental predictions for summer in 2001, 2002, 2003 and 2004 by using this nested RegCM-NCC were made. The results are basically reasonable compared with the observations.

A Modeling Study of Effective Radiative Forcing and Climate Response Due to Tropospheric Ozone

This study simulates the effective radiative forcing （ERF） of tropospheric ozone from 1850 to 2013 and its effects on global climate using an aerosol-climate coupled model, BCC_AGCM2.0. I_CUACE/Aero, in combination with OMI （Ozone Monitoring Instrument） satellite ozone data. According to the OMI observations, the global annual mean tropospheric col- umn ozone （TCO） was 33.9 DU in 2013, and the largest TCO was distributed in the belts between 30°N and 45°N and at approximately 30°S; the annual mean TCO was higher in the Northern Hemisphere than that in the Southern Hemisphere; and in boreal summer and autumn, the global mean TCO was higher than in winter and spring. The simulated ERF due to the change in tropospheric ozone concentration from 1850 to 2013 was 0.46 W m-2, thereby causing an increase in the global annual mean surface temperature by 0.36°C, and precipitation by 0.02 mm d-1 （the increase of surface temperature had a significance level above 95%）. The surface temperature was increased more obviously over the high latitudes in both hemispheres, with the maximum exceeding 1.4°C in Siberia. There were opposite changes in precipitation near the equator, with an increase of 0.5 mm d- 1 near the Hawaiian Islands and a decrease of about -0.6 mm d- 1 near the middle of the Indian Ocean.

Projections of Wind Changes for 21st Century in China by Three Regional Climate Models

This paper examines the capability of three regional climate models (RCMs), i.e., RegCM3 (the International Centre for Theoretical Physics Regional Climate Model), PRECIS (Providing Regional Climates for Impacts Studies) and CMM5 (the fifth-generation Pennsylvania State University-the National Center for Atmospheric Research of USA, NCAR Mesoscale Model) to simulate the near-surface-layer winds (10 m above surface) all over China in the late 20th century. Results suggest that like global climate models (GCMs), these RCMs have the certain capability of imitating the distribution of mean wind speed and fail to simulate the greatly weakening wind trends for the past 50 years in the country. However, RCMs especially RegCM3 have the better capability than that of GCMs to simulate the distribution and change feature of mean wind speed. In view of their merits, these RCMs were used to project the variability of near-surface-layer winds over China for the 21st century. The results show that 1) summer mean wind speed for 2020-2029 will be lower compared to those in 1990-1999 in most area of China; 2) annual and winter mean wind speed for 2081-2100 will be lower than those of 1971-1990 in the whole China; and 3) the changes of summer mean wind speed for 2081-2100 are uncertain. As a result, although climate models are absolutely necessary for projecting climate change to come, there are great uncertainties in projections, especially for wind speed, and these issues need to be further explored.

CLIMATE PREDICTION EXPERIMENT FOR TROPICAL CYCLONE GENESIS FREQUENCY USING THE LARGE-SCALE CIRCULATION FORECAST BY A COUPLED GLOBAL CIRCULATION MODEL

Based on an analysis of the relationship between the tropical cyclone genesis frequency and large-scale circulation anomaly in NCEP reanalysis, large-scale atmosphere circulation information forecast by the JAMSTEC SINTEX-F coupled model is used to build a statistical model to predict the cyclogenesis frequency over the South China Sea and the western North Pacific. The SINTEX-F coupled model has relatively good prediction skill for some circulation features associated with the cyclogenesis frequency including sea level pressure, wind vertical shear, Intertropical Convergence Zone and cross-equatorial air flows. Predictors derived from these large-scale circulations have good relationships with the cyclogenesis frequency over the South China Sea and the western North Pacific. A multivariate linear regression(MLR) model is further designed using these predictors. This model shows good prediction skill with the anomaly correlation coefficient reaching, based on the cross validation, 0.71 between the observed and predicted cyclogenesis frequency. However, it also shows relatively large prediction errors in extreme tropical cyclone years(1994 and 1998, for example).

Downscaled climate change projections for the Hindu Kush Himalayan region using CORDEX South Asia regional climate models

This study assessed the regional climate models (RCMs) employed in the Coordinated Regional climate Downscaling Experiment (CORDEX) South Asia framework to investigate the qualitative aspects of future change in seasonal mean near surface air temperature and precipitation over the Hindu Kush Himalayan (HKH) region. These RCMs downscaled a subset of atmosphere ocean coupled global climate models (AOGCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5) to higher 50 km spatial resolution over a large domain covering South Asia for two representation concentration pathways (RCP4.5 and RCP8.5) future scenarios. The analysis specifically examined and evaluated multi-model and multi-scenario climate change projections over the hilly sub-regions within HKH for the near-future (2036e2065) and far-future (2066e2095) periods. The downscaled multi-RCMs provide relatively better confidence than their driving AOGCMs in projecting the magnitude of seasonal warming for the hilly sub-region within the Karakoram and northwestern Himalaya, with higher projected change of 5.4
C during winter than of 4.9
C during summer monsoon season by the end of 21st century under the high-end emissions (RCP8.5) scenario. There is less agreement among these RCMs on the magnitude of the projected warming over the other sub-regions within HKH for both seasons, particularly associated with higher RCM uncertainty for the hilly sub-region within the central Himalaya. The downscaled multi-RCMs show good consensus and low RCM uncertainty in projecting that the summer monsoon precipitation will intensify by about 22% in the hilly subregion within the southeastern Himalaya and Tibetan Plateau for the far-future period under the RCP8.5 scenario. There is low confidence in the projected changes in the summer monsoon and winter season precipitation over the central Himalaya and in the Karakoram and northwestern Himalaya due to poor consensus and moderate to high RCM uncertainty among the downscaled multi-RCMs. Finally, the RCM related uncertainty is found to be large for the projected changes in seasonal temperature and precipitation over the hilly sub-regions within HKH by the end of this century, suggesting that improving the regional processes and feedbacks in RCMs are essential for narrowing the uncertainty, and for providing more reliable regional climate change projections suitable for impact assessments in HKH region.

An overview of studies of observed climate change in the Hindu Kush Himalayan (HKH) region

The Hindu Kush Himalayan (HKH hereafter) region is characterized by mountainous environments and a variety of regional climatic conditions. High-altitude regions in the HKH have the recent warming amplifications, especially during the global warming hiatus period. The rapid warming cause solid state water (snow, ice, glacier, and permafrost) to shrink, leading to increase in meltwater and there have been found more frequent incidences of flash floods, landslides, livestock diseases, and other disasters in the HKH region. Increasing awareness of climate change over the HKH region is reached a consensus. Meanwhile, the HKH region is often referred to as the water towers of Asia as many highaltitude regions store its water in the form of snow and/or glacier, feeding ten major large rivers in Asia. Therefore, the impacts of climate change on water availability in these river basins have huge influences on the livelihood of large number of population, especially in downstream regions. However, the scarcity of basic hydro-meteorological observations particularly in high-altitude regions of HKH limits rigorous analysis of climate change. Most studies used reanalysis data and/or model-reconstructed products to explore the spatial and temporal characteristics of hydro-meteorological processes, especially for extreme events. In this study, we review recent climate change in the HKH region, and the scientific challenges and research recommendations are suggested for this high-altitude area.

A review of progress in coupled ocean-atmosphere model developments for ENSO studies in China

El Nino-Southern Oscillation(ENSO) is the strongest interannual signal that is producedby basinscale processes in the tropical Pacific,with significant effects on weather and climate worldwide.In the past,extensive and intensive international efforts have been devoted to coupled model developments for ENSO studies.A hierarchy of coupled ocean-atmo sphere models has been formulated;in terms of their complexity,they can be categorized into intermediate coupled models(ICMs),hybrid coupled models(HCMs),and fully coupled general circulation models(CGCMs).ENSO modeling has made significant progress over the past decades,reaching a stage where coupled models can now be used to successfully predict ENSO events 6 months to one year in advance.Meanwhile,ENSO exhibits great diversity and complexity as observed in nature,which still cannot be adequately captured by current state-of-the-art coupled models,presenting a challenge to ENSO modeling.We primarily reviewed the long-term efforts in ENSO modeling continually and steadily made at different institutions in China;some selected representative examples are presented here to review the current status of ENSO model developments and applications,which have been actively pursued with noticeable progress being made recently.As ENSO simulations are very sensitive to model formulations and process representations etc.,dedicated efforts have been devoted to ENSO model developments and improvements.Now,different ocean-atmosphere coupled models have been available in China,which exhibit good model performances and have already had a variety of applications to climate modeling,including the Coupled Model Intercomparison Project Phase 6(CMIP6).Nevertheless,large biases and uncertainties still exist in ENSO simulations and predictions,and there are clear rooms for their improvements,which are still an active area of researches and applications.Here,model performances of ENSO simulations are assessed in terms of advantages and disadvantages with these differently formulated coupled models,pinpointing to the areas where they need to be further improved for ENSO studies.These analyses provide valuable guidance for future improvements in ENSO simulations and predictions.

A modeling study of effective radiative forcing and climate response due to increased methane concentration

An atmospheric general circulation model BCC_AGCM2.0 and observation data from ARIS were used to calculate the effective radiative forcing（ERF） due to increased methane concentration since pre-industrial times and its impacts on climate. The ERF of methane from 1750 to2011 was 0.46 W m^-2 by taking it as a well-mixed greenhouse gas, and the inhomogeneity of methane increased its ERF by about 0.02 W m^-2.The change of methane concentration since pre-industrial led to an increase of 0.31 ℃ in global mean surface air temperature and 0.02 mm d 1in global mean precipitation. The warming was prominent over the middle and high latitudes of the Northern Hemisphere（with a maximum increase exceeding 1.4℃）. The precipitation notably increased（maximum increase of 1.8 mm d^-1） over the ocean between 10°N and 20° N and significantly decreased（maximum decrease 〉-0.6 mm d^-1） between 10° S and 10° N. These changes caused a northward movement of precipitation cell in the Intertropical Convergence Zone（ITCZ）. Cloud cover significantly increased（by approximately 4%） in the high latitudes in both hemispheres, and sharply decreased（by approximately 3%） in tropical areas.

The Unprecedented Extreme Anticyclonic Anomaly over Northeast Asia in July 2021 and Its Climatic Impacts

This study investigates the evolution of an extreme anomalous anticyclone(AA)event over Northeast Asia,which was one of the dominant circulation systems responsible for the catastrophic extreme precipitation event in July 2021 in Henan,and further explores the significant impact of this AA on surface temperatures beneath it.The results indicate that this AA event over Northeast Asia was unprecedented in terms of intensity and duration.The AA was very persistent and extremely strong for 10 consecutive days from 13 to 22 July 2021.This long-lived and unprecedented AA led to the persistence of warmer surface temperatures beyond the temporal span of the pronounced 500-hPa anticyclonic signature as the surface air temperatures over land in Northeast Asia remained extremely warm through 29 July 2021.Moreover,the sea surface temperatures in the Sea of Japan/East Sea were extremely high for 30 consecutive days from 13 July to 11 August 2021,persisting well after the weakening or departure of this AA.These results emphasize the extreme nature of this AA over Northeast Asia in July 2021 and its role in multiple extreme climate events,even over remote regions.Furthermore,possible reasons for this long-lasting AA are explored,and it is suggested to be a byproduct of a teleconnection pattern over extratropical Eurasia during the first half of its life cycle,and of the Pacific-Japan teleconnection pattern during the latter half.

Detection,Causes and Projection of Climate Change over China:An Overview of Recent Progress

This article summarizes the main results and findings of studies conducted by Chinese scientists in the past five years. It is shown that observed climate change in China bears a strong similarity with the global average. The country-averaged annual mean surface air temperature has increased by 1.1℃ over the past 50 years and 0.5-0.8℃ over the past 100 years, slightly higher than the global temperature increase for the same periods. Northern China and winter have experienced the greatest increases in surface air temperature. Although no significant trend has been found in country-averaged annual precipitation, interdecadal variability and obvious trends on regional scales are detectable, with northwestern China and the mid and lower Yangtze River basin having undergone an obvious increase, and North China a severe drought. Some analyses show that frequency and magnitude of extreme weather and climate events have also undergone significant changes in the past 50 years or so. Studies of the causes of regional climate change through the use of climate models and consideration of various forcings, show that the warming of the last 50 years could possibly be attributed to an increased atmospheric concentration of greenhouse gases, while the temperature change of the first half of the 20th century may be due to solar activity, volcanic eruptions and sea surface temperature change. A significant decline in sunshine duration and solar radiation at the surface in eastern China has been attributed to the increased emission of pollutants. Projections of future climate by models of the NCC （National Climate Center, China Meteorological Administration） and the IAP （Institute of Atmospheric Physics, Chinese Academy of Sciences）, as well as 40 models developed overseas, indicate a potential significant warming in China in the 21st century, with the largest warming set to occur in winter months and in northern China. Under varied emission scenarios, the country-averaged annual mean temperature is projected to increase by 1.5 2.1℃ by 2020, 2.3 3.3℃ by 2050, and by 3.9-6.0℃ by 2100, in comparison to the 30-year average of 1961-1990. Most models project a 10% 12% increase in annual precipitation in China by 2100, with the trend being particularly evident in Northeast and Northwest China, but with parts of central China probably undergoing a drying trend. Large uncertainty exists in the projection of precipitation, and further studies are needed. Furthermore, anthropogenic climate change will probably lead to a weaker winter monsoon and a stronger summer monsoon in eastern Asia.

Performance of the Seasonal Forecasting of the Asian Summer Monsoon by BCC_CSM1.1(m)

This paper provides a comprehensive assessment of Asian summer monsoon prediction skill as a function of lead time and its relationship to sea surface temperature prediction using the seasonal hindcasts of the Beijing Climate Center Climate System Model, BCC_CSM1. l（m）. For the South and Southeast Asian summer monsoon, reasonable skill is found in the model＇s forecasting of certain aspects of monsoon climatology and spatiotemporal variability. Nevertheless, deficiencies such as significant forecast errors over the tropical western North Pacific and the eastern equatorial Indian Ocean are also found. In particular, overestimation of the connections of some dynamical monsoon indices with large-scale circulation and precipitation patterns exists in most ensemble mean forecasts, even for short lead-time forecasts. Variations of SST, measured by the first mode over the tropical Pacific and Indian oceans, as well as the spatiotemporal features over the Nifio3.4 region, are overall well predicted. However, this does not necessarily translate into successful forecasts of the Asian summer monsoon by the model. Diagnostics of the relationships between monsoon and SST show that difficulties in predicting the South Asian monsoon can be mainly attributed to the limited regional response of monsoon in observations but the extensive and exaggerated response in predictions due partially to the application of ensemble average forecasting methods. In contrast, in spite of a similar deficiency, the Southeast Asian monsoon can still be forecasted reasonably, probably because of its closer relationship with large-scale circulation patterns and E1 Nifio-Southern Oscillation.

The Soil Moisture of China in a High Resolution Climate-Vegetation Model

The spatial distribution of soil moisture, especially the temporal variation at seasonal and interannual scales, is difficult for many land surface models （LSMs） to capture partly due to the deficiencies of the LSMs and the highly spatial variability of soil moisture, which makes it problematic to simulate the moisture for climate studies. However the soil moisture plays an important role in influencing the energy and hydrological cycles between the land and air, so it should be considered in land surface models. In this paper, a soil moisture simulation in China with a T213 resolution （about 0.5625°× 0.5625°） is compared to the observational data, and its relationship to precipitation is explored. The soil moisture distribution agrees roughly with the observations, and the soil moisture pattern reflects the variation and intensity of the precipitation. In particular, for the 1998 summer catastrophic floods along the Yangtze River, the soil moisture remains high in this region from July to August and represents the flood well. The seasonal cycle of soil moisture is roughly consistent with the observed data, which is a good calibration for the ground simulation capacity of the Atmosphere-Vegetation Interaction Model （AVIM） with respect to this tough problem for land surface models.

Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios: A Case Study of Swedish Precipitation

There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.

Decreasing Reference Evapotranspiration in a Warming Climate-A Case of Changjiang (Yangtze) River Catchment During 1970-2000

This study deals with temporal trends in the Penman-Monteith reference evapotranspiration estimated from standard meteorological observations, observed pan evaporation, and four related meteorological variables during 1970-2000 in the Yangtze River catchment. Relative contributions of the four meteorological variables to changes in the reference evapotranspiration are quantified. The results show that both the reference evapotranspiration and the pan evaporation have significant decreasing trends in the upper, the middle as well as in the whole Changjiang （Yangtze） River catchment at the 5% significance level, while the air temperature shows a significant increasing trend. The decreasing trend detected in the reference evapotranspiration can be attributed to the significant decreasing trends in the net radiation and the wind speed.

Climate change in Mt. Qomolangma region since 1971

Using monthly average, maximum, minimum air temperature and monthly precipitation data from 5 weather stations in Mt. Qomolangma region in China from 1971 to 2004, climatic linear trend, moving average, low-pass filter and accumulated variance analysis methods, the spatial and temporal patterns of the climatic change in this region were analyzed. The main findings can be summarized as follows： （1） There is obvious ascending tendency for the interannual change of air temperature in Mt. Qomolangma region and the ascending tendency of Tingri, the highest station, is the most significant. The rate of increasing air temperature is 0.234℃/decade in Mt. Qomolangma region, 0.302 ℃/decade in Tingxi. The air temperature increases more strongly in non-growing season. （2） Compared with China and the global average, the warming of Mt. Qomolangma region occurred early. The linear rates of temperature increase in Mt. Qomolangma region exceed those for China and the global average in the same period. This is attributed to the sensitivity of mountainous regions to climate change. （3） The southern and northern parts of Mt. Qomolangma region are quite different in precipitation changes. Stations in the northern part show increasing trends but are not statistically significant. Nyalam in the southern part shows a decreasing trend and the sudden decreasing of precipitation occurred in the early 1990s. （4） Compared with the previous studies, we find that the warming of Mt. Qomolangma high-elevation region is most significant in China in the same period. The highest automatic meteorological comprehensive observation station in the world set up at the base camp of Mt. Qomolangma with a height of 5032 m a.s.l will play an important role in monitoring the global climate change.

Evaluation of the Tropical Variability from the Beijing Climate Center's Real-Time Operational Global Ocean Data Assimilation System

The second-generation Global Ocean Data Assimilation System of the Beijing Climate Center （BCC_GODAS2.0） has been run daily in a pre-operational mode. It spans the period 1990 to the present day. The goal of this paper is to introduce the main components and to evaluate BCC_GODAS2.0 for the user community. BCC_GODAS2.0 consists of an observational data preprocess, ocean data quality control system, a three-dimensional variational （3DVAR） data assimilation, and global ocean circulation model [Modular Ocean Model 4 （MOM4）]. MOM4 is driven by six-hourly fluxes from the National Centers for Environmental Prediction. Satellite altimetry data, SST, and in-situ temperature and salinity data are assimilated in real time. The monthly results from the BCC_GODAS2.0 reanalysis are compared and assessed with observations for 1990-201 I. The climatology of the mixed layer depth of BCC_GODAS2.0 is generally in agreement with that of World Ocean Atlas 2001. The modeled sea level variations in the tropical Pacific are consistent with observations from satellite altimetry on interannual to decadal time scales. Performances in predicting variations in the SST using BCC_GODAS2.0 are evaluated. The standard deviation of the SST in BCC_GODAS2.0 agrees well with observations in the tropical Pacific. BCC_GODAS2.0 is able to capture the main features of E1 Nifio Modoki I and Modoki II, which have different impacts on rainfall in southern China. In addition, the relationships between the Indian Ocean and the two types of E1 Nino Modoki are also reproduced.

Estimation of ground heat flux and its impact on the surface energy budget for a semi-arid grassland

Three approaches, i.e., the harmonic analysis （HA） technique, the thermal diffusion equation and correction （TDEC） method, and the calorimetric method used to estimate ground heat flux, are evaluated by using observations from the Semi-Arid Climate and Environment Observatory of Lanzhou University （SACOL） in July, 2008. The calorimetric method, which involves soil heat flux measurement with an HFP01SC self-calibrating heat flux plate buried at a depth of 5 cm and heat storage in the soil between the plate and the surface, is here called the ITHP approach. The results show good linear relationships between the soil heat fluxes measured with the HFP01SC heat flux plate and those calculated with the HA technique and the TDEC method, respectively, at a depth of 5 cm. The soil heat fluxes calculated with the latter two methods well follow the phase measured with the HFP01SC heat flux plate. The magnitudes of the soil heat flux calculated with the HA technique and the TDEC method are close to each other, and they are about 2 percent and 6 percent larger than the measured soil heat flux, respectively, which mainly occur during the nighttime. Moreover, the ground heat fluxes calculated with the TDEC method and the HA technique are highly correlated with each other （R2= 0.97）, and their difference is only about 1 percent. The TDEC-calculated ground heat flux also has a good linear relationship with the ITttP-calculated ground heat flux （R2 = 0.99）, but their difference is larger （about 9 percent）. Furthermore, compared to the HFP01SC direct measurements at a depth of 5 cm, the ground heat flux calculated with the HA technique, the TDEC method, and the ITHP approach can improve the surface energy budget closure by about 6 percent, 7 percent, and 6 percent at SACOL site, respectively. Therefore, the contribution of ground heat flux to the surface energy budget is very important for the semi-arid grassland over the Loess Plateau in China. Using turbulent heat fluxes with common corrections, soil heat storage between the surface and the heat flux plate can improve the surface energy budget closure by about 6 to 7 percent, resulting in a closure of 82 to 83 percent at the SACOL site.