Chinese Academy Of Meteorological Sciences Research Articles

Guangdong Lightning Mapping Array: Errors Evaluation and Preliminary Results

AbstractThe Guangdong Lightning Mapping Array (GDLMA), as the first LMA in China, was deployed in Guangzhou, Guangdong Province, China, in November 2018 by the Chinese Academy of Meteorological Sciences and New Mexico Institute of Mining and Technology. An evaluation was conducted using Monte Carlo and an aircraft track. The average timing uncertainty of GDLMA is 35 ns based on the distributions of reduced chi‐square values. Based on the aircraft track, the average horizontal error is 13 m and the average vertical error is 41 m at an altitude of 4–5 km over the network, consistent with the Monte Carlo results. Location errors outside the network exhibit noticeable directionality. The ability to characterize lightning channels varies with different location errors. In locations that are far from the network center, only the basic structure of lightning flash can be presented, while closer to the network, the flash channel structure can be mapped well. Compared with Low‐to‐Mid Frequency E‐field Detection Array (MLFEDA), they were generally similar in overall structure, and some lightning flash characteristics such as flash duration and coverage area exhibited consistency. However, GDLMA demonstrated better flash channel structure characterization capability, while MLFEDA performed better in processes such as leader/return strokes. In addition, based on the comparison of spatial positions of one‐on‐one discharge events, we found that very high frequency sources were more located ahead of low frequency sources in the direction of lightning channel development.

A new insight into the vertical differences in NO2 heterogeneous reaction to produce HONO over inland and marginal seas

Abstract. Ship-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements were conducted along the marginal seas of China from 19 April to 16 May 2018 to measure the vertical profiles of aerosol, nitrogen dioxide (NO2), and nitrous acid (HONO). Along the cruise route, we found five hot spots with enhanced tropospheric NO2 vertical column densities (VCDs) in the Yangtze River Delta, Taiwan Strait, Guangzhou–Hong Kong–Macau Greater Bay Area, port of Zhanjiang, and port of Qingdao. Enhanced HONO concentrations could usually be observed under high-level aerosol and NO2 conditions, whereas the reverse was not always the case. To understand the impacts of relative humidity (RH), temperature, and aerosol on the heterogeneous reaction of NO2 to form HONO in different scenarios, the Chinese Academy of Meteorological Sciences (CAMS) and Southern University of Science and Technology (SUST) MAX-DOAS stations were selected as the inland and coastal cases, respectively. The RH turning points in CAMS and SUST cases were both ∼ 65 % (60 %–70 %), whereas two turning peaks (∼ 60 % and ∼ 85 %) of RH were found in the sea cases. As temperature increased, the HONO / NO2 ratio decreased with peak values appearing at ∼ 12.5∘C in CAMS, whereas the HONO / NO2 gradually increased and reached peak values at ∼ 31.5∘C in SUST. In the sea cases, when the temperature exceeded 18.0∘C, the HONO / NO2 ratio rose with increasing temperature and achieved its peak at ∼ 25.0∘C. This indicated that high temperature can contribute to the secondary formation of HONO in the sea atmosphere. In the inland cases, the correlation analysis between HONO and aerosol in the near-surface layer showed that the ground surface is more crucial to the formation of HONO via the heterogeneous reaction of NO2; however, in the coastal and sea cases, the aerosol surface contributed more. Furthermore, we discovered that the conversion rate of NO2 to HONO through heterogeneous reactions in the sea cases is larger than that in the inland cases in higher atmospheric layers (> 600 m). Three typical events were selected to demonstrate three potential contributing factors of HONO production under marine conditions (i.e., transport, NO2 heterogeneous reaction, and unknown HONO source). This study elucidates the sea–land and vertical differences in the forming mechanism of HONO via the NO2 heterogeneous reaction and provides deep insights into tropospheric HONO distribution, transforming process, and environmental effects.

Ground-Based Hyperspectral Stereoscopic Remote Sensing Network: A Promising Strategy to Learn Coordinated Control of O3 and PM2.5 over China

With the coming of the “14th Five-Year Plan”, the coordinated control of particulate matter with an aerodynamic diameter no greater than 2.5 μm (PM 2.5 ) and O 3 has become a major issue of air pollution prevention and control in China. The stereoscopic monitoring of regional PM 2.5 and O 3 and their precursors is crucial to achieve coordinated control. However, current monitoring networks are currently inadequate for monitoring the vertical profiles of both PM 2.5 and O 3 simultaneously and support air quality control. The University of Science and Technology of China (USTC) has established a nationwide ground-based hyperspectral stereoscopic remote sensing network based on multi-axis differential optical absorption spectroscopy (MAX-DOAS) since 2015. This monitoring network provides a significant opportunity for the regional coordinated control of PM 2.5 and O 3 in China. One-year vertical profiles of aerosol, NO 2 and HCHO monitored from four MAX-DOAS stations installed in four megacities (Beijing, Shanghai, Shenzhen, and Chongqing) were used to characterize their vertical distribution differences in four key regions, Jing–Jin–Ji (JJJ), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (SB), respectively. The normalized and yearly averaged aerosol vertical profiles below 400 m in JJJ and PRD exhibit a box shape and a Gaussian shape, respectively, and both show exponential shapes in YRD and SB. The NO 2 vertical profiles in four regions all exhibit exponential shapes because of vehicle emissions. The shape of the HCHO vertical profile in JJJ and PRD was Gaussian, whereas an exponential shape was shown in YRD and SB. Moreover, a regional transport event occurred at an altitude of 600–1000 m was monitored in the southwest–northeast pathway of the North China Plain (NCP) by five MAX-DOAS stations (Shijiazhuang (SJZ), Wangdu (WD), Nancheng (NC), Chinese Academy of Meteorological Sciences (CAMS), and University of Chinese Academy of Sciences (UCAS)) belonging to the above network. The aerosol optical depths (AOD) in these five stations decreased in the order of SJZ > WD > NC > CAMS > UCAS. The short-distance regional transport of NO 2 in the 700–900 m layer was monitored between WD and NC. As an important precursor of secondary aerosol, the peak of NO 2 air mass in WD and NC all occurred 1 h earlier than that of aerosol. This was also observed for the short-distance regional transport of HCHO in the 700–900 m layer between NC and CAMS, which potentially affected the O 3 concentration in Beijing. Finally, CAMS was selected as a typical site to determine the O 3 –NO x –volatile organic compounds (VOCs) sensitivities in vertical space. We found the production of O 3 changed from predominantly VOCs-limited conditions to mainly mixed VOCs–NO x -limited condition from the 0–100 m layer to the 200–300 m layer. In addition, the downward transport of O 3 could contribute to the increase of ground surface O 3 concentration. This ground-based hyperspectral stereoscopic remote sensing network provide a promising strategy to support management of PM 2.5 and O 3 and their precursors and conduct attribution of sources.

The CMIP6 Historical Simulation Datasets Produced by the Climate System Model CAMS-CSM

This paper describes the historical simulations produced by the Chinese Academy of Meteorological Sciences (CAMS) climate system model (CAMS-CSM), which are contributing to phase 6 of the Coupled Model Intercomparison Project (CMIP6). The model description, experiment design and model outputs are presented. Three members’ historical experiments are conducted by CAMS-CSM, with two members starting from different initial conditions, and one excluding the stratospheric aerosol to identify the effect of volcanic eruptions. The outputs of the historical experiments are also validated using observational data. It is found that the model can reproduce the climatological mean states and seasonal cycle of the major climate system quantities, including the surface air temperature, precipitation, and the equatorial thermocline. The long-term trend of air temperature and precipitation is also reasonably captured by CAMS-CSM. There are still some biases in the model that need further improvement. This paper can help the users to better understand the performance and the datasets of CAMS-CSM.

Quantifying the Cloud Water Resource: Methods Based on Observational Diagnosis and Cloud Model Simulation

Based on the concepts of cloud water resource (CWR) and related variables proposed in the first part of this study, this paper provides details of two methods to quantify the CWR. One is diagnostic quantification (CWR-DQ) based on satellite observations, precipitation products, and atmospheric reanalysis data; and the other is numerical quantification (CWR-NQ) based on a cloud resolving model developed at the Chinese Academy of Meteorological Sciences (CAMS). The two methods are applied to quantify the CWR in April and August 2017 over North China, and the results are evaluated against all available observations. Main results are as follows. (1) For the CWR-DQ approach, reference cloud profiles are firstly derived based on the CloudSat/CALIPSO joint satellite observations for 2007–2010. The NCEP/NCAR reanalysis data in 2000–2017 are then employed to produce three-dimensional cloud fields. The budget/balance equations of atmospheric water substance are lastly used, together with precipitation observations, to retrieve CWR and related variables. It is found that the distribution and vertical structure of clouds obtained by the diagnostic method are consistent with observations. (2) For the CWR-NQ approach, it assumes that the cloud resolving model is able to describe the cloud microphysical processes completely and precisely, from which four-dimensional distributions of atmospheric water vapor, hydrometeors, and wind fields can be obtained. The data are then employed to quantify the CWR and related terms/quantities. After one-month continuous integration, the mass of atmospheric water substance becomes conserved, and the tempospatial distributions of water vapor, hydrometeors/cloud water, and precipitation are consistent with observations. (3) Diagnostic values of the difference in the transition between hydrometeors and water vapor (Cvh − Chv) and the surface evaporation (Es) are well consistent with their numerical values. (4) Correlation and bias analyses show that the diagnostic CWR contributors are well correlated with observations, and match their numerical counterparts as well, indicating that the CWR-NQ and CWR-DQ methods are reasonable. (5) Underestimation of water vapor converted from hydrometeors (Chv) is a shortcoming of the CWR-DQ method, which may be rectified by numerical quantification results or by use of advanced observations on higher spatiotemporal resolutions.

Development of a coupled atmosphere–ocean typhoon regional assimilation and prediction system for operational typhoon forecasting by the Chinese Academy of Meteorological Sciences—part I: experiments of Western North Pacific typhoons in 2016

Typhoons can interact intensely with oceans, and the atmosphere–ocean interaction has an enormous impact on the intensity and structure of typhoons. To consider the impact of typhoon–ocean interactions, a regional coupled atmosphere–ocean system for operational forecasting of Western North Pacific typhoons is established in this paper based on a public coupled atmosphere–ocean framework and in accordance with the operational typhoon forecasting conditions and system settings of the Chinese Academy of Meteorological Sciences. The new coupled system is fully validated and used for hindcasting experiments on all typhoons in 2016. The results show that the computational cost associated with the proposed coupled system is approximately 5.33 times that of the atmosphere-only system. A comparison of the hindcasts of the 2016 typhoons using the atmosphere-only system and the proposed coupled system reveals that the use of the coupled system can obviously reduce the forecasted intensity error by approximately 10–20% but not the typhoon track error. In addition, some of the intrinsic structural characteristics of typhoons influence the effectivity of the coupled system. Specifically, when typhoons have a high intensity and a low translational speed, move in an East-West or turning direction, and are at 20°N–25°N latitude, the forecasts can be relatively significantly improved by the coupled system; otherwise, the improvement is not obvious.

Responses of Cloud-Radiative Forcing to Strong El Niño Events over the Western Pacific Warm Pool as Simulated by CAMS-CSM

Cloud-radiative forcing (CRF) at the top of the atmosphere (TOA) over the western Pacific warm pool (WP) shows unique characteristics in response to El Nino events. In this region, the responses of CRF to El Nino events have been a useful metric for evaluating climate models. Satellite data are used to analyze the CRF anomalies to El Nino events simulated by the new and old versions of the Climate System Model of the Chinese Academy of Meteorological Sciences (CAMS-CSM), which has participated in the Atmospheric Model Intercomparison Project (AMIP). Here, simulations for super El Nino years, El Nino years, and normal years are compared with observations. The results show that the mean values of both longwave CRF (LWCRF) and shortwave CRF (SWCRF) in CAMS-CSM are weaker than the observations for each category of El Nino events. Compared with the old version of CAMS-CSM, the decrease in LWCRF during El Nino events is well simulated by the new version of CAMS-CSM. However, both new and old models cannot reproduce the anomalous SWCRF in El Nino events. The biases in the CRF response to El Nino events are attributed to the biases in the cloud vertical structure because of a weaker crash of the Walker circulation in CAMS-CSM. Due to the modification of the conversion rate from cloud droplets to raindrops in the cumulus convection scheme, the new version of CAMS-CSM has better CRF skills in normal years, but biases in El Nino events still exist in the new version. Improving the response of the Walker circulation to El Nino events is key to higher skills in simulating the cloud radiative responses.

Extreme weather and climate events in China under changing climate.

In the summer of 2003, a heat wave swept Europe and caused more than 70 000 additional fatalities [J.-M. Robine et al., C. R. Biologies331 (2008)]. Global warming and climate change is no longer a prophecy to be fulfilled, as strong heat waves and typhoons, as well as severe rainfalls, are becoming more severe. Extreme weather and climate events in the world, especially over Europe and North America, are widely studied and frequently reported in the media. These events may be related to the ongoing climate change. In this NSR forum, active researchers specialized in this field gather to discuss the climate and weather changes in China. They present the current changes, identify knowledge gaps, discuss the research difficulties, and propose ways forward to better serve the society with climate science. Ying Sun Professor at the National Climate Center of the China Meteorological Administration, China Qiuhong Tang Professor at the Institute of Geographic Sciences and Natural Resources Research of the Chinese Academy of Sciences, China Zhongwei Yan Professor at the Institute of Atmospheric Physics of the Chinese Academy of Sciences, China Jing Yang Professor at the Academy of Disaster Reduction and Emergency Management, faculty of Geographic Science of Beijing Normal University, China Panmao Zhai Professor at the Chinese Academy of Meteorological Sciences of the China Meteorological Administration, and the current Co-Chair of the IPCC Working Group I, China Tianjun Zhou Professor at the Institute of Atmospheric Physics of the Chinese Academy of Sciences, China Deliang Chen (Chair) Professor at the University of Gothenburg, NSR Editorial Board member, Sweden

Observation of the Whole Discharge Process During a Multi-stroke Triggered Lightning by Continuous Interferometer

The discharge process is often discussed in the lightning physics. VHF (very high frequency) observations play an important role in studying lightning discharge processes, because they show where air breakdown occurs. Triggered lightning flashes are ideal research objects, because they are generated in a fixed time and place. Regular experiments of triggering lightning have been conducted by Chinese Academy of Meteorological Sciences since 2006, and 189 lightning flashes are triggered successfully. Besides regular observations, such as fast/slow antenna, channel-based current and high-speed video, the continuous interferometer (CINTF) is developed and deployed at the site for triggered lightning after 2016 in order to observe detailed discharge processes. The CINTF can provide high-precision location with time resolution of around 1 μs.A multi-stroke triggered lightning with 8 return strokes is observed by a self-developed lightning continuous interferometer during Guangdong Comprehensive Observation Experiment on Lightning Discharge on 11 June 2019. The whole discharge processes, including precursor current pulse, initial precursor current pulse, initial continuous current and return strokes, last for about 1600 ms. The channel-based current, electric field change and radiation source positions are obtained. CINTF results show that the radiation signal generated from discrete precursor current pulse with a minimum value of about 8 A can be detected. The average transfer charge of initial precursor current pulse is twice as much as that of the precursor current pulse. During the initial continuous current stage after continuously developing of the upward positive leader, the obviously forward channel extension is the main discharge form at the beginning, and then the extension can be accompanied by discontinuously backward propagation, and recoil leader often occurs in the following stage. M-component in the ICC stage is caused by two discharge processes:Forward positive streamer (or leader) or recoil leader generated in the existing channel. Multi recoil leaders occur during the whole M process, which maintain M discharge. The main discharge form in return stroke stage is recoiling discharge. There are multi recoil leaders before return strokes, however, most of them cannot develop to ground, keep as an attempted leader until the last leader-stroke occurs. Adjacent two strokes with a short duration time of 4.5 ms have the same optical channel in optical images, but they are obviously different in development paths, which lead to a very short RS interval.

Parametric Reconstruction Method for the Long Time-Series Return-Stroke Current of Triggered Lightning Based on the Particle Swarm Optimization Algorithm

The lightning research group of the Chinese Academy of Meteorological Sciences has carried out observations and experiments with artificially triggered lightning for more than ten years, and it accumulated thousands of examples of channel base current data on the return stroke of artificially triggered lightning prior to 2020. Based on the current data, this paper explores ways of improving the constructed function of a long time-series (400 μs) return stroke and the parametric reconstruction of the current waveform. The long time-series current can be divided into three components: the breakdown pulse current, corona current and quasi-uniform current. The corona current and quasi-uniform current are constructed by a Heidler function, while the breakdown pulse current is determined by the waveform characteristics of the current peak, which can be divided into the Heidler type and high-order exponential type. According to the three-component model of the return-stroke current, a two-step parametric reconstruction method for the long time-series lightning return-stroke current based on the particle swarm optimization (PSO) algorithm is proposed. In this paper, the results of the parameterized reconstruction of 14 return strokes are given, and the results of the multidimensional error analysis of 13 long time-series return strokes are given to illustrate the accuracy of the improved parameterized model of the return-stroke current and the effectiveness of the two-step reconstruction method based on the PSO algorithm.

Comparison of the effects of soil moisture and El Niño on summer precipitation in eastern China

The effects of spring soil moisture over the vast region from the lower and middle reaches of the Yangtze River valley to North China (YRNC) and El Nino on the East Asian summer monsoon (EASM) and precipitation in eastern China, as well as the relevant mechanisms, are investigated using the modified atmospheric model ECHAM5 coupled with the Common Land Model. These models are the atmospheric and land components of the climate system model developed at the Chinese Academy of Meteorological Sciences (CAMS-CSM). The simulations show that both soil moisture anomalies in eastern China and El Nino sea surface temperature (SST) anomalies have significant influences on the EASM, with the effect of soil moisture being slightly greater than that of the El Nino. However, the impacts of soil moisture on EASM and rainfall in eastern China are markedly different from those of the El Nino. Wetter (drier) soil over the YRNC corresponds to less (more) precipitation over northern and southeastern China, and more (less) precipitation over the Yangtze River basin and northeastern China, as well as a strengthened (weakened) and westward-shifted (eastward-shifted) West Pacific Subtropical High and a deepened (shallower) East Asian trough, representing a weakened (strengthened) EASM pattern. During El Nino developing summers, an anomalous anticyclone extends from northeastern to northern China, and an anomalous cyclone occupies the middle and lower reaches of the Yangtze River and southern China. Concurrently, the West Pacific Subtropical High is anomalously weaker than normal. As a result, rainfall anomalously increases over the lower reaches of the Yangtze River and southern China, and decreases over northern and northeastern China. In El Nino decaying summers, there is an anomalous cyclone over northeastern China and an anomalous anticyclone over southern China. The convergence of southerly airflow and northerly winds leads to enhanced rainfall around northern China and the middle reaches of the Yangtze River, and reduced rainfall over other regions.

Convectively Coupled Equatorial Waves Simulated by CAMS-CSM

The Chinese Academy of Meteorological Sciences developed a Climate System Model (CAMS-CSM) to participate in the upcoming Coupled Model Intercomparison Project phase 6 (CMIP6). In this study, we assessed the model performance in simulating the convectively coupled equatorial waves (CCEWs) by comparing the daily output of precipitation from a 23-yr coupled run with the observational precipitation data from Global Precipitation Climatology Project (GPCP). Four dominant modes of CCEWs including the Kelvin, equatorial Rossby (ER), mixed Rossby–gravity (MRG), tropical depression-type (TD-type) waves, and their annual mean and seasonal cycle characteristics are investigated respectively. It is found that the space–time spectrum characteristics of each wave mode represented by tropical averaged precipitation could be very well simulated by CAMS-CSM, including the magnitudes and the equivalent depths. The zonal distribution of wave associated precipitation is also well simulated, with the maximum centers over the Indian Ocean and the Pacific Ocean. However, the meridional distribution of the wave activities is poorly simulated, with the maximum centers shifted from the Northern Hemisphere to the Southern Hemisphere, especially the Kelvin, MRG, and TD waves. The seasonal cycle of each wave mode is generally captured by the model, but their amplitudes over the Southern Hemisphere during boreal winter are grossly overestimated. The reason for the excessive wave activity over the southern Pacific Ocean in the simulation is discussed.

Simulation of the Northern and Southern Hemisphere Annular Modes by CAMS-CSM

As leading modes of the planetary-scale atmospheric circulation in the extratropics, the Northern Hemisphere (NH) annular mode (NAM) and Southern Hemisphere (SH) annular mode (SAM) are important components of global circulation, and their variabilities substantially impact the climate in mid−high latitudes. A 35-yr (1979−2013) simulation by the climate system model developed at the Chinese Academy of Meteorological Sciences (CAMS-CSM) was carried out based on observed sea surface temperature and sea ice data. The ability of CAMS-CSM in simulating horizontal and vertical structures of the NAM and SAM, relation of the NAM to the East Asian climate, and temporal variability of the SAM is examined and validated against the observational data. The results show that CAMS-CSM captures the zonally symmetric and out-of-phase variations of sea level pressure anomaly between the midlatitudes and polar zones in the extratropics of the NH and SH. The model has also captured the equivalent barotropic structure in tropospheric geopotential height and the meridional shifts of the NH and SH jet systems associated with the NAM and SAM anomalies. Furthermore, the model is able to reflect the variability of northern and southern Ferrel cells corresponding to the NAM and SAM anomalies. The model reproduces the observed relationship of the boreal winter NAM with the East Asian trough and air temperature over East Asia. It also captures the upward trend of the austral summer SAM index during recent decades. However, compared with the observation, the model shows biases in both the intensity and center locations of the NAM’s and SAM’s horizontal and vertical structures. Specifically, it overestimates their intensities.

Coupling the Common Land Model to ECHAM5 Atmospheric General Circulation Model

The ECHAM5 model is coupled with the widely used Common Land Model (CoLM). ECHAM5 is a state-of-the-art atmospheric general circulation model incorporated into the integrated weather and climate model of the Chinese Academy of Meteorological Sciences (CAMS-CSM). Land surface schemes in ECHAM5 are simple and do not provide an adequate representation of the vegetation canopy and snow/frozen soil processes. Two AMIP (Atmosph-eric Model Intercomparison Project)-type experiments using ECHAM5 and ECHAM5-CoLM are run over 30 yr and the results are compared with reanalysis and observational data. It is found that the pattern of land surface temperature simulated by ECHAM5-CoLM is significantly improved relative to ECHAM5. Specifically, the cold bias over Eurasia is removed and the root-mean-square error is reduced in most regions. The seasonal variation in the zonal mean land surface temperature and the in situ soil temperature at 20- and 80-cm depths are both better simulated by ECHAM5-CoLM. ECHAM5-CoLM produces a more reasonable spatial pattern in the soil moisture content, whereas ECHAM5 predicts much drier soils. The seasonal cycle of soil moisture content from ECHAM5-CoLM is a better match to the observational data in six specific regions. ECHAM5-CoLM reproduces the observed spatial patterns of both sensible and latent heat fluxes. The strong positive bias in precipitation over land is reduced in ECHAM5-CoLM, especially over the southern Tibetan Plateau and middle–lower reaches of the Yangtze River during the summer monsoon rainy season.

Boreal Summer Intraseasonal Oscillation in the Asian–Pacific Monsoon Region Simulated in CAMS-CSM

The boreal summer intraseasonal oscillation (BSISO) is simulated by the Climate System Model (CSM) developed at the Chinese Academy of Meteorological Sciences (CAMS), China Meteorological Administration. Firstly, the results indicate that this new model is able to reasonably simulate the annual cycle and seasonal mean of the precipitation, as well as the vertical shear of large-scale zonal wind in the tropics. The model also reproduces the eastward and northward propagating oscillation signals similar to those found in observations. The simulation of BSISO is generally in agreement with the observations in terms of variance center, periodicity, and propagation, with the exception that the magnitude of BSISO anomalous convections are underestimated during both its eastward propagation along the equator and its northward propagation over the Asian–Pacific summer monsoon region. Our preliminary evaluation of the simulated BSISO by CAMS-CSM suggests that this new model has the capability, to a certain extent, to capture the BSISO features, including its propagation zonally along the equator and meridionally over the Asian monsoon region.

ENSO Features, Dynamics, and Teleconnections to East Asian Climate as Simulated in CAMS-CSM

This study evaluates the performance of CAMS-CSM (the climate system model of the Chinese Academy of Meteorological Sciences) in simulating the features, dynamics, and teleconnections to East Asian climate of the El Nino–Southern Oscillation (ENSO). In general, fundamental features of ENSO, such as its dominant patterns and phase-locking features, are reproduced well. The two types of El Nino are also represented, in terms of their spatial distributions and mutual independency. However, the skewed feature is missed in the model and the simulation of ENSO is extremely strong, which is found—based on Bjerknes index assessment—to be caused by underestimation of the shortwave damping effect. Besides, the modeled ENSO exhibits a regular oscillation with a period shorter than observed. By utilizing the Wyrtki index, it is suggested that this periodicity bias results from an overly quick phase transition induced by feedback from the thermocline and zonal advection. In addition to internal dynamics of ENSO, its external precursors—such as the North Pacific Oscillation with its accompanying seasonal footprinting mechanism, and the Indian Ocean Dipole with its 1-yr lead correlation with ENSO—are reproduced well by the model. Furthermore, with respect to the impacts of ENSO on the East Asian summer monsoon, although the anomalous Philippine anticyclone is reproduced in the post-El Nino summer, it exhibits an eastward shift compared with observation; and as a consequence, the observed flooding of the Yangtze River basin is poorly represented, with unrealistic air–sea interaction over the South China Sea being the likely physical origin of this bias. The response of wintertime lower-tropospheric circulation to ENSO is simulated well, in spite of an underestimation of temperature anomalies in central China. This study highlights the dynamic processes that are key for the simulation of ENSO, which could shed some light on improving this model in the future.

Climate Sensitivity and Feedbacks of a New Coupled Model CAMS-CSM to Idealized CO2 Forcing: A Comparison with CMIP5 Models

Climate sensitivity and feedbacks are basic and important metrics to a climate system. They determine how large surface air temperature will increase under CO2 forcing ultimately, which is essential for carbon reduction policies to achieve a specific warming target. In this study, these metrics are analyzed in a climate system model newly developed by the Chinese Academy of Meteorological Sciences (CAMS-CSM) and compared with multi-model results from the Coupled Model Comparison Project phase 5 (CMIP5). Based on two idealized CO2 forcing scenarios, i.e., abruptly quadrupled CO2 and CO2 increasing 1% per year, the equilibrium climate sensitivity (ECS) and transient climate response (TCR) in CAMS-CSM are estimated to be about 2.27 and 1.88 K, respectively. The ECS is near the lower bound of CMIP5 models whereas the TCR is closer to the multi-model ensemble mean (MME) of CMIP5 due to compensation of a relatively low ocean heat uptake (OHU) efficiency. The low ECS is caused by an unusually negative climate feedback in CAMS-CSM, which is attributed to cloud shortwave feedback (λSWCL) over the tropical Indo-Pacific Ocean. The CMIP5 ensemble shows that more negative λSWCL is related to larger increase in low-level (925–700 hPa) cloud over the tropical Indo-Pacific under warming, which can explain about 90% of λSWCL in CAMS-CSM. Static stability of planetary boundary layer in the pre-industrial simulation is a critical factor controlling the low-cloud response and λSWCL across the CMIP5 models and CAMS-CSM. Evidently, weak stability in CAMS-CSM favors lowcloud formation under warming due to increased low-level convergence and relative humidity, with the help of enhanced evaporation from the warming tropical Pacific. Consequently, cloud liquid water increases, amplifying cloud albedo, and eventually contributing to the unusually negative λSWCL and low ECS in CAMS-CSM. Moreover, the OHU may influence climate feedbacks and then the ECS by modulating regional sea surface temperature responses.

An Assessment of CAMS-CSM in Simulating Land–Atmosphere Heat and Water Exchanges

The Chinese Academy of Meteorological Sciences (CAMS) has been devoted to developing a climate system model (CSM) to meet demand for climate simulation and prediction for the East Asian region. In this study, we evaluated the performance of CAMS-CSM in regard to sensible heat flux (H), latent heat flux (LE), surface temperature, soil moisture, and snow depth, focusing on the Atmospheric Model Intercomparison Project experiment, with the aim of participating in the Coupled Model Intercomparison Project phase 6. We systematically assessed the simulation results achieved by CAMS-CSM for these variables against various reference products and ground observations, including the FLUXNET model tree ensembles H and LE data, Climate Prediction Center soil moisture data, snow depth climatology data, and Chinese ground observations of snow depth and winter surface temperature. We compared these results with data from the ECMWF Interim reanalysis (ERA-Interim) and Global Land Data Assimilation System (GLDAS). Our results indicated that CAMS-CSM simulations were better than or comparable to ERAInterim reanalysis for snow depth and winter surface temperature at regional scales, but slightly worse when simulating total column soil moisture. The root-mean-square differences of H in CAMS-CSM were all greater than those from the ERA-Interim reanalysis, but less than or comparable to those from GLDAS. The spatial correlations for H in CAMS-CSM were the lowest in nearly all regions, except for North America. CAMS-CSM LE produced the lowest bias in Siberia, North America, and South America, but with the lowest spatial correlation coefficients. Therefore, there are still scopes for improving H and LE simulations in CAMS-CSM, particularly for LE.

The CAMS Climate System Model and a Basic Evaluation of Its Climatology and Climate Variability Simulation

A new coupled climate system model (CSM) has been developed at the Chinese Academy of Meteorological Sciences (CAMS) by employing several state-of-the-art component models. The coupled CAMS-CSM consists of the modified atmospheric model [ECmwf-HAMburg (ECHAM5)], ocean model [Modular Ocean Model (MOM4)], sea ice model [Sea Ice Simulator (SIS)], and land surface model [Common Land Model (CoLM)]. A detailed model description is presented and both the pre-industrial and “historical” simulations are preliminarily evaluated in this study. The model can reproduce the climatological mean states and seasonal cycles of the major climate system quantities, including the sea surface temperature, precipitation, sea ice extent, and the equatorial thermocline. The major climate variability modes are also reasonably captured by the CAMS-CSM, such as the Madden–Julian Oscillation (MJO), El Nino–Southern Oscillation (ENSO), East Asian Summer Monsoon (EASM), and Pacific Decadal Oscillation (PDO). The model shows a promising ability to simulate the EASM variability and the ENSO–EASM relationship. Some biases still exist, such as the false double-intertropical convergence zone (ITCZ) in the annual mean precipitation field, the overestimated ENSO amplitude, and the weakened Bjerknes feedback associated with ENSO; and thus the CAMS-CSM needs further improvements.

How Well Can a Climate Model Simulate an Extreme Precipitation Event: A Case Study Using the Transpose-AMIP Experiment

AbstractA high-impact extreme precipitation event over the Yangtze River valley (YRV) in the midsummer of 2016 is simulated using the Climate System Model of Chinese Academy of Meteorological Sciences (CAMS-CSM). After validation of the model’s capability in reproducing the climatological features of precipitation over the YRV, the Transpose Atmospheric Model Intercomparison Project (T-AMIP)–type experiment, which runs the climate model in the weather forecast mode, is applied to investigate the performance of the climate model in simulating the spatial and temporal distribution of rainfall and the related synoptic circulation. Analyses of T-AMIP results indicate that the model realistically reproduces the heavy rainfall centers of accumulated precipitation amount along the YRV, indicating that the climate model has the ability to simulate the severity of the extreme event. However, the frequency–intensity structure shows similar biases as in the AMIP experiment, especially the underestimation of the maximum hourly intensity. The simulation of two typical heavy rainfall periods during the extreme event is further evaluated. The results illustrate that the model shows different performances during periods dominated by circulation systems of different spatial scales. The zonal propagation of heavy rainfall centers during the first two days, which is related to the eastward movement of the southwest vortex, is well reproduced. However, for another period with a smaller vortex, the model produces an artificial steady heavy rainfall center over the upwind slope of the mountains rather than the observed eastward movement of the precipitation centers.