Improvement of Soil Moisture Simulation in Eurasia by the Beijing Climate Center Climate System Model from CMIP5 to CMIP6

This study provides a comprehensive evaluation of historical surface soil moisture simulation(1979-2012)over Eurasia at annual and seasonal time scales between two medium-resolution versions of the Beijing Climate Center Climate System Model(BCC-CSM)—one that is currently participating in phase 6 of the Coupled Model Intercomparison Project(CMIP6),i.e.,BCC-CSM2-MR,and the other,BCC-CSM1.1m,which participated in CMIP5.We show that BCC-CSM2-MR is more skillful in reproducing the climate mean states and standard deviations of soil moisture,with pattern correlations increased and biases reduced significantly.BCC-CSM2-MR performs better in capturing the first two primary patterns of soil moisture anomalies,where the period of the corresponding time series is closer to that of reference data.Comparisons show that BCC-CSM2-MR performs at a high level among multiple models of CMIP6 in terms of centered pattern correlation and“amplitude of variation”(relative standard deviation).In general,the centered pattern correlation of BCC-CSM2-MR,ranging from 0.61 to 0.87,is higher than the multi-model mean of CMIP6,and the relative standard deviation is 0.75,which surmounts the overestimations in most of the CMIP6 models.Due to the vital role played by precipitation in land-atmosphere interaction,possible causes of the improvement of soil moisture simulation are further related to precipitation in BCC-CSM2-MR.The results indicate that a better description of the relationship between soil moisture and precipitation and a better reproduction of the climate mean precipitation by the model may result in the improved performance of soil moisture simulation.

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.

Introduction of CMIP5 Experiments Carried out with the Climate System Models of Beijing Climate Center

The climate system models from Beijing Climate Center, BCC_CSM1.1 and BCC_CSM1.1-M, are used to carry out most of the CMIP5 experiments. This study gives a general introduction of these two models, and provides main information on the experiments including the experiment purpose, design, and the external forcings. The transient climate responses to the CO2 concentration increase at 1% per year are presented in the simulation of the two models. The BCC_CSM1.1-M result is closer to the CMIP5 multiple models ensemble. The two models perform well in simulating the historical evolution of the surface air temperature, globally and averaged for China. Both models overestimate the global warming and underestimate the warming over China in the 20th century. With higher horizontal resolution, the BCC_CSM1.1-M has a better capability in reproducing the annual evolution of surface air temperature over China.

EU and international policies for hydrometeorological risks:Operational aspects and link to climate action

Changes in hydrometeorological characteristics and risks have been observed and are projected to increase under climate change. These considerations are scientifically well studied and led to the development of a complex policy framework for adaptation and mitigation for hydrometeorological risks. Awareness for policy actions is growing worldwide but no legal framework is in place to tackle climate change impacts on water at a global scale. With the example of international frameworks and the legislation on EU-level, this article elaborates that hydrometeorological risks are not considered in the framework of one single policy. However, various policy instruments are directly or indirectly considering these risks at different operational levels. It is discussed that a tailor-made framework for hydrometeorological risks would improve coordination at international or national level. A major drawback for a single operational framework is that hydrometeorological risks are scientifically tackled in two large communities: the disaster risk reduction community and the climate change adaptation community, both of which are bound to different research and operational funding budgets. In future, disaster risk reduction and climate change adaptation will need been seen as a complementary set of actions that requires collaboration.

Climate state of the Three Gorges Region in the Yangtze River basin in 2022–2023

Based on daily observation data of the Three Gorges Region(TGR)of the Yangtze River basin and global reanalysis data,the climate characteristics,climate events,and meteorological disasters of the TGR in 2022 and 2023 were analyzed.For the TGR,the average annual temperature for 2022 and 2023 was 0.8℃ and 0.4℃ higher than normal,respectively,making them the two warmest years in the past decade.In 2022,the TGR experienced its warmest summer on record.The average air temperature was 2.4℃ higher than the average,and there were 24.8 days of above-average high temperature days during summer.Rainfall in the TGR varied significantly between 2022 and 2023.Annual rainfall was 18.4%below normal and drier than normal in most parts of the region.In contrast,the precipitation in 2023 was considerably higher than the long-term average,and above normal for almost the entire year.The average wind speed exhibited minimal variation between the two years.However,the number of foggy days and relative humidity increased in 2023 compared to 2022.In 2022–2023,the TGR mainly experienced meteorological disasters such as extreme high temperatures,regional heavy rain and flooding,overcast rain,and inverted spring chill.Analysis indicates that the abnormal western Pacific subtropical high and the abnormal persistence of the eastward-shifted South Asian high were the two important drivers of the durative enhancement of record-breaking high temperature in the summer of 2022.

State of China’s climate in 2023

China witnessed a warm and dry climate in 2023.The annual surface air temperature reached a new high of 10.71℃,with the hottest autumn and the second hottest summer since 1961.Meanwhile,the annual precipitation was the second lowest since 2012,at 615.0 mm.Precipitation was less than normal from winter to summer,but more in autumn.Consistent with the annual condition,precipitation in the flood season from May to September was also the second lowest since 2012,which was 4.3%less than normal,with the anomalies in the central and eastern parts of China being higher in central areas and lower in the north and south.On the contrary,the West China Autumn Rain brought much more rainfall than normal,with an earlier start and later end.Although there was less annual precipitation in 2023,China suffered seriously from heavy precipitation events and floods.In particular,from the end of July to the beginning of August,a rare,extremely strong rainstorm caused by Typhoon Dussuri hit Beijing,Tianjin,and Hebei,causing an abrupt alteration from drought to flood conditions in North China.By contrast,Southwest China experienced continuous drought from the previous autumn to current spring.In early summer,North China and the Huanghuai region experienced the strongest high-temperature process since 1961.Nevertheless,there were more cold-air processes than normal impacting China,with the most severe of the year occurring in mid-January.Unexpectedly,in spring,there were more sand and dust occurrences in northern China.

Analysis of Dry-Wet Climate Change Characteristics and Main Influencing Factors in Main Grain Producing Area of Tibet from 1980 to 2021

Based on the daily meteorological observation data of seven meteorological stations in southern Tibet from 1980 to 2021 (April-October), the temporal and spatial variation characteristics and influencing factors of aridity index ( AI ) in the growing season of major grain producing areas in Tibet were studied by using climate tendency rate, Mann-Kendal test, Morlet wavelet analysis, GIS hybrid interpolation method, Pearson correlation coefficient, contribution rate analysis and other methods. The results showed that the average AI in the main grain producing areas of Tibet was 1.7, which belonged to the semi-arid area, and the overall trend was decreasing (humidifying) (-0.036/10 a). The linear decreasing trend was different in different regions, and the area around Lhatse County was the most significant (-0.26/10 a). AI had no obvious abrupt change, and had long- and medium-term fluctuation characteristics of 24 years, 6 years. The spatial distribution was uneven, and had the characteristics of ‘shrinking arid area and expanding humid area . The contribution rates of the main climate influencing factors of AI varied in different regions. In general, the contribution rates after quantification was as follows: precipitation (34.9%)>relative humidity (28.4%)>sunshine (19.9%)>maximum temperature (12.4%).

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.

Climate Change over China in the 21st Century as Simulated by BCC_CSM1.1-RegCM4.0

Driven by the global model,Beijing Climate Center Climate System Model version 1.1(BCC_CSM1.1),climate change over China in the 21st century is simulated by a regional climate model(RegCM4.0)under the new emission scenarios of the Representative Concentration Pathways—RCP4.5 and RCP8.5.This is based on a period of transient simulations from 1950 to2099,with a grid spacing of 50 km.The present paper focuses on the annual mean temperature and precipitation in China over this period,with emphasis on their future changes.Validation of model performance reveals marked improvement of the RegCM4.0 model in reproducing present day temperature and precipitation relative to the driving BCC_CSM1.1 model.Significant warming is simulated by both BCC_CSM1.1 and RegCM4.0,however,spatial distribution and magnitude differ between the simulations.The high emission scenario RCP8.5 results in greater warming compared to RCP4.5.The two models project different precipitation changes,characterized by a general increase in the BCC_CSM1.1,and broader areas with decrease in the RegCM4.0 simulations.

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 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.

Surface Turbulent Flux Measurements over the Loess Plateau for a Semi-Arid Climate Change Study

In order to provide high quality data for climate change studies, the data quality of turbulent flux measurements at the station of SACOL （Semi-Arid Climate ＆ Environment Observatory of Lanzhou University）, which is located on a semi-arid grassland over the Loess Plateau in China, has been analyzed in detail. The effects of different procedures of the flux corrections on CO2, momentum, and latent and sensible heat fluxes were assessed. The result showed that coordinate rotation has a great influence on the momentum flux but little on scalar fluxes. For coordinate rotation using the planar fit method, different regression planes should be determined for different wind direction sectors due to the heterogeneous nature of the ground surface. Sonic temperature correction decreased the sensible heat flux by about 9%, while WPL correction （correction for density fluctuations） increased the latent heat flux by about 10%. WPL correction is also particularly important for CO2 fluxes. Other procedures of flux corrections, such as the time delay correction and frequency response correction, do not significantly influence the turbulent fluxes. Furthermore, quality tests on stationarity and turbulence development conditions were discussed. Parameterizations of integral turbulent characteristics （ITC） were tested and a specific parameterization scheme was provided for SACOL. The ITC test on turbulence development conditions was suggested to be applied only for the vertical velocity. The combined results of the quality tests showed that about 62%-65% of the total data were of high quality for the latent heat flux and CO2 flux, and as much as about 76% for the sensible heat flux. For the momentum flux, however, only about 35% of the data were of high quality.

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

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

The Influence of Vegetation Cover on Summer Precipitation in China: a Statistical Analysis of NDVI and Climate Data

This study provides new evidence for the feedback effects of vegetation cover on summer precipitation in different regions of China by calculating immediate (same season), and one-and two-season lagged correlations between the normalized difference vegetation index (NDVI) and summer precipitation. The results show that the correlation coefficients between NDVI in spring and the previous winter and precipitation in summer are positive in most regions of China, and they show significant difference between regions. The stronger one-and two-season lagged correlations occur in the eastern arid/semi-arid region, Central China, and Southwest China out of the eight climatic regions of China, and this implies that vegetation cover change has more sensitive feedback effects on summer precipitation in the three regions. The three regions are defined as sensitive regions. Spatial analyses of correlations between spring NDVI averaged over each sensitive region and summer precipitation of 160 stations suggest that the vegetation cover strongly affects summer precipitation not only over the sensitive region itself but also over other regions, especially the downstream region.

SIMULATION OF PRESENT CLIMATE OVER EAST ASIA BY A REGIONAL CLIMATE MODEL

A 15-year simulation of climate over East Asia is conducted with the latest version of a regional climate model RegCM3 nested in one-way mode to the ERA40 Re-analysis data. The performance of the model in simulating present climate over East Asia and China is investigated. Results show that RegCM3 can reproduce well the atmospheric circulation over East Asia. The simulation of the main distribution patterns of surface air temperature and precipitation over China and their seasonal cycle/evolution, are basically agree with that of the observation. Meanwhile a general cold bias is found in the simulation. As for the precipitation, the model tends to overestimate the precipitation in northern China while underestimate it in southern China, particularly in winter. In general, the model has better performance in simulating temperature than precipitation.

Regional Variability of Climate Change Hot-Spots in East Asia

The regional climate change index （RCCI） is employed to investigate hot-spots under 21st century global warming over East Asia. The RCCI is calculated on a 1-degree resolution grid from the ensemble of CMIP3 simulations for the B1, AIB, and A2 IPCC emission scenarios. The RCCI over East Asia exhibits marked sub-regional variability. Five sub-regional hot-spots are identified over the area of investigation： three in the northern regions （Northeast China, Mongolia, and Northwest China）, one in eastern China, and one over the Tibetan Plateau. Contributions from different factors to the RCCI are discussed for the sub-regions. Analysis of the temporal evolution of the hot-spots throughout the 21st century shows different speeds of response time to global warming for the different sub-regions. Hot-spots firstly emerge in Northwest China and Mongolia. The Northeast China hot-spot becomes evident by the mid of the 21st century and it is the most prominent by the end of the century. While hot-spots are generally evident in all the 5 sub-regions for the A1B and A2 scenarios, only the Tibetan Plateau and Northwest China hot-spots emerge in the B1 scenario, which has the lowest greenhouse gas （GHG） concentrations. Our analysis indicates that subregional hot-spots show a rather complex spatial and temporal dependency on the GHG concentration and on the different factors contributing to the RCCI.

Climate Change due to Greenhouse Effects in China as Simulated by a Regional Climate Model

Impacts of greenhouse effects (2 × CO2) upon climate change over China as simulated by a regional climate model over China (RegCM / China) have been investigated. The model was based on RegCM2 and was nested to a global coupled ocean-atmosphere model (CSIRO R21L9 AOGCM model). Results of the control run (1 × CO2) indicated that simulations of surface air temperature and precipitation in China by RegCM are much better than that by the global coupled model because of a higher resolution. Results of sensitive experiment by RegCM with 2 × CO2 showed that the surface air temperature over China might increase remarkably due to greenhouse effect, especially in winter season and in North China. Precipitation might also increase in most parts of China due to the CO2 doubling. Key words Regional climate model - Greenhouse effect This research was supported by National Key Programme for Developing Basic Sciences (G1998040900 — Part I), Chinese Academy of Sciences Key Program KZCX2-203 and KZ981-B1-108.

South Asian High and Asian-Pacific-American Climate Teleconnection

Growing evidence indicates that the Asian monsoon plays an important role in affecting the weather and climate outside of Asia. However, this active role of the monsoon has not been demonstrated as thoroughly as has the variability of the monsoon caused by various impacting factors such as sea surface temperature and land surface. This study investigates the relationship between the Asian monsoon and the climate anomalies in the Asian-Pacific-American （APA） sector. A hypothesis is tested that the variability of the upper-tropospheric South Asian high （SAH）, which is closely associated with the overall heating of the large-scale Asian monsoon, is linked to changes in the subtropical western Pacific high （SWPH）, the midPacific trough, and the Mexican high. The changes in these circulation systems cause variability in surface temperature and precipitation in the APA region. A stronger SAH is accompanied by a stronger and more extensive SWPH. The enlargement of the SWPH weakens the mid-Pacific trough. As a result, the southern portion of the Mexican high becomes stronger. These changes are associated with changes in atmospheric teleconnections, precipitation, and surface temperature throughout the APA region. When the SAH is stronger, precipitation increases in southern Asia, decreases over the Pacific Ocean, and increases over the Central America. Precipitation also increases over Australia and central Africa and decreases in the Mediterranean region. While the signals in surface temperature are weak over the tropical land portion, they are apparent in the mid latitudes and over the eastern Pacific Ocean.

A Review of Seasonal Climate Prediction Research in China

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 1930 s. Experimental operational climate forecasts have been performed since the late 1950 s,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 1980 s 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.

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.