New Record Ocean Temperatures and Related Climate Indicators in 2023

The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human activities.In 2023,the sea surface temperature(SST)and upper 2000 m ocean heat content(OHC)reached record highs.The 0–2000 m OHC in 2023 exceeded that of 2022 by 15±10 ZJ(1 Zetta Joules=1021 Joules)(updated IAP/CAS data);9±5 ZJ(NCEI/NOAA data).The Tropical Atlantic Ocean,the Mediterranean Sea,and southern oceans recorded their highest OHC observed since the 1950s.Associated with the onset of a strong El Niño,the global SST reached its record high in 2023 with an annual mean of~0.23℃ higher than 2022 and an astounding>0.3℃ above 2022 values for the second half of 2023.The density stratification and spatial temperature inhomogeneity indexes reached their highest values in 2023.

Moisture Transport and Associated Background Circulation for the Regional Extreme Precipitation Events over South China in Recent 40 Years

Based on the hourly precipitation data at 176 observational stations over south China and the hourly ERA5reanalysis data during the 40-yr period of 1981-2020, we analyzed the universal characteristics of moisture transport and their associated background circulations for four types of regional extreme precipitation events(REPEs) over south China. Main findings are shown as follow.(i) The wind that transported moisture for the REPEs over south China featured a notable diurnal variation, which was consistent with the variations of the precipitation.(ii) Four types of REPEs could be determined, among which the southwest type(SWT) and the southeast type(SET) accounted for ~92%and ~5.7%, respectively, ranking the first and second, respectively.(iii) Trajectory analyses showed that the air particles of the SWT-REPEs had the largest specific humidity and experienced the most intense ascending motion, and therefore their precipitation was the strongest among the four types.(iv) South China was dominated by notable moisture flux convergence for the four types of REPEs, but their moisture transport was controlled by different flow paths.(v)Composite analyses indicated that the background circulation of the four types of REPEs showed different features,particularly for the intensity, location and coverage of a western Pacific subtropical high. For the SWT-REPEs, their moisture transport was mainly driven by a lower-tropospheric strong southwesterly wind band in the low-latitude regions. Air particles for this type of REPEs mainly passed over the Indochina Peninsula and South China Sea. For the SET-REPEs, their moisture transport was mainly steered by a strong low-tropospheric southeasterly wind northeast of a transversal trough. Air particles mainly passed over the South China Sea for this type of REPEs.

El Niño and the AMO Sparked the Astonishingly Large Margin of Warming in the Global Mean Surface Temperature in 2023

In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.

Severe Global Environmental Issues Caused by Canada’s Record-Breaking Wildfires in 2023

Due to the record-breaking wildfires that occurred in Canada in 2023,unprecedented quantities of air pollutants and greenhouse gases were released into the atmosphere.The wildfires had emitted more than 1.3 Pg CO_(2)and 0.14 Pg CO_(2)equivalent of other greenhouse gases(GHG)including CH4 and N_(2)O as of 31 August.The wildfire-related GHG emissions constituted more than doubled Canada’s planned cumulative anthropogenic emissions reductions in 10 years,which represents a significant challenge to climate mitigation efforts.The model simulations showed that the Canadian wildfires impacted not only the local air quality but also that of most areas in the northern hemisphere due to long-range transport,causing severe PM_(2.5)pollution in the northeastern United States and increasing daily mean PM_(2.5)concentration in northwestern China by up to 2μg m-3.The observed maximum daily mean PM_(2.5)concentration in New York City reached 148.3μg m-3,which was their worst air quality in more than 50 years,nearly 10 times that of the air quality guideline(i.e.,15μg m-3)issued by the World Health Organization(WHO).Aside from the direct emissions from forest fires,the peat fires beneath the surface might smolder for several months or even longer and release substantial amounts of CO_(2).The substantial amounts of greenhouse gases from forest and peat fires might contribute to the positive feedback to the climate,potentially accelerating global warming.To better understand the comprehensive environmental effects of wildfires and their interactions with the climate system,more detailed research based on advanced observations and Earth System Models is essential.

CAS-ESM2.0 Dataset for the Carbon Dioxide Removal Model Intercomparison Project(CDRMIP)

Understanding the response of the Earth system to varying concentrations of carbon dioxide(CO_(2))is critical for projecting possible future climate change and for providing insight into mitigation and adaptation strategies in the near future.In this study,we generate a dataset by conducting an experiment involving carbon dioxide removal(CDR)—a potential way to suppress global warming—using the Chinese Academy of Sciences Earth System Model version 2.0(CASESM2.0).A preliminary evaluation is provided.The model is integrated from 200–340 years as a 1%yr^(−1) CO_(2) concentration increase experiment,and then to~478 years as a carbon dioxide removal experiment until CO_(2) returns to its original value.Finally,another 80 years is integrated in which CO_(2) is kept constant.Changes in the 2-m temperature,precipitation,sea surface temperature,ocean temperature,Atlantic meridional overturning circulation(AMOC),and sea surface height are all analyzed.In the ramp-up period,the global mean 2-m temperature and precipitation both increase while the AMOC weakens.Values of all the above variables change in the opposite direction in the ramp-down period,with a delayed peak relative to the CO_(2) peak.After CO_(2) returns to its original value,the global mean 2-m temperature is still~1 K higher than in the original state,and precipitation is~0.07 mm d^(–1) higher.At the end of the simulation,there is a~0.5°C increase in ocean temperature and a 1 Sv weakening of the AMOC.Our model simulation produces similar results to those of comparable experiments previously reported in the literature.

CAS-ESM2.0 Successfully Reproduces Historical Atmospheric CO_(2) in a Coupled Carbon−Climate Simulation

The atmospheric carbon dioxide(CO_(2))concentration has been increasing rapidly since the Industrial Revolution,which has led to unequivocal global warming and crucial environmental change.It is extremely important to investigate the interactions among atmospheric CO_(2),the physical climate system,and the carbon cycle of the underlying surface for a better understanding of the Earth system.Earth system models are widely used to investigate these interactions via coupled carbon-climate simulations.The Chinese Academy of Sciences Earth System Model version 2(CAS-ESM2.0)has successfully fixed a two-way coupling of atmospheric CO_(2)with the climate and carbon cycle on land and in the ocean.Using CAS-ESM2.0,we conducted a coupled carbon-climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment.This paper examines the modeled CO_(2)by comparison with observed CO_(2)at the sites of Mauna Loa and Barrow,and the Greenhouse Gases Observing Satellite(GOSAT)CO_(2)product.The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO_(2)during the period 1850-2014,and in capturing the seasonal cycle of CO_(2)at the two baseline sites,as well as over northern high latitudes.These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon-climate interactions,even though uncertainties remain in the processes involved.This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate,which will provide significant scientific support for climate research and China’s goal of carbon neutrality.

Probabilistic Automatic Outlier Detection for Surface Air Quality Measurements from the China National Environmental Monitoring Network

Although quality assurance and quality control procedures are routinely applied in most air quality networks, outliers can still occur due to instrument malfunctions, the influence of harsh environments and the limitation of measuring methods. Such outliers pose challenges for data-powered applications such as data assimilation, statistical analysis of pollution characteristics and ensemble forecasting. Here, a fully automatic outlier detection method was developed based on the probability of residuals, which are the discrepancies between the observed and the estimated concentration values. The estimation can be conducted using filtering—or regressions when appropriate—to discriminate four types of outliers characterized by temporal and spatial inconsistency, instrument-induced low variances, periodic calibration exceptions, and less PM_(10) than PM_(2.5) in concentration observations, respectively. This probabilistic method was applied to detect all four types of outliers in hourly surface measurements of six pollutants(PM_(2.5), PM_(10),SO_2,NO_2,CO and O_3) from 1436 stations of the China National Environmental Monitoring Network during 2014-16. Among the measurements, 0.65%-5.68% are marked as outliers. with PM_(10) and CO more prone to outliers. Our method successfully identifies a trend of decreasing outliers from 2014 to 2016,which corresponds to known improvements in the quality assurance and quality control procedures of the China National Environmental Monitoring Network. The outliers can have a significant impact on the annual mean concentrations of PM_(2.5),with differences exceeding 10 μg m^(-3) at 66 sites.

An Investigation of the Formation of the Heat Wave in Southern China in Summer 2013 and the Relevant Abnormal Subtropical High Activities

In the summer of 2013, an unprecedented heat wave was experienced over a vast area of southern China. The great areal extent, duration, and strength of this high temperature are very rare. For the 2013 hot spell, the major and direct influence mostly came from the anomaly of the western Pacific subtropical high(WPSH). The abnormally strong and stable WPSH was associated with specific surrounding circulations. The eastward extension of a stronger Qinghai-Xizang high favored the westward extension of the WPSH. The weaker cold air activity from the polar region led to the northward shift of the WPSH and helped it to remain stable. In the tropics, the western segment of the ITCZ was abnormally strong in the period, and supported the maintenance of the WPSH from the south. In addition, the interdecadal variation of the WPSH provided a decadal background for the anomaly variation of the WPSH that summer.

An Ocean Reanalysis System for the Joining Area of Asia and Indian-Pacific Ocean

An ocean reanalysis system for the joining area of Asia and Indian-Pacific Ocean (AIPO) has been developed and is currently delivering reanalysis data sets for study on the air-sea interaction over AIPO and its climate variation over China in the inter-annual time scale.This system consists of a nested ocean model forced by atmospheric reanalysis,an ensemble-based multivariate ocean data assimilation system and various ocean observations.The following report describes the main components of the data assimilation system in detail.The system adopts an ensemble optimal interpolation scheme that uses a seasonal update from a free running model to estimate the background error covariance matrix.In view of the systematic biases in some observation systems,some treatments were performed on the observations before the assimilation.A coarse resolution reanalysis dataset from the system is preliminarily evaluated to demonstrate the performance of the system for the period 1992 to 2006 by comparing this dataset with other observations or reanalysis data.

The El Ni?o-Southern Oscillation cycle simulated by the climate system model of Chinese Academy of Sciences

On the basis of more than 200-year control run, the performance of the climate system model of Chinese Academy of Sciences （CAS-ESM-C） in simulating the E1 Nifio-Southern Oscillation （ENSO） cycle is evalu- ated, including the onset, development and decay of the ENSO. It is shown that, the model can reasonably simulate the annual cycle and interannual variability of sea surface temperature （SST） in the tropical Pacif- ic, as well as the seasonal phase-locking of the ENSO. The model also captures two prerequisites for the E1 Nino onset, i.e., a westerly anomaly and a warm SST anomaly in the equatorial western Pacific. Owing to too strong forcing from an extratropical meridional wind, however, the westerly anomaly in this region is largely overestimated. Moreover, the simulated thermocline is much shallower with a weaker slope. As a result, the warm SST anomaly from the western Pacific propagates eastward more quickly, leading to a faster develop- ment of an E1 Nino. During the decay stage, owing to a stronger E1Nino in the model, the secondary Gill-type response of the tropical atmosphere to the eastern Pacific warming is much stronger, thereby resulting in a persistent easterly anomaly in the western Pacific. Meanwhile, a cold anomaly in the warm pool appears as a result of a lifted thermocline via Ekman pumping. Finally, an E1 Nino decays into a La Nina through their interactions. In addition, the shorter period and larger amplitude of the ENSO in the model can be attribut- ed to a shallower thermocline in the equatorial Pacific, which speeds up the zonal redistribution of a heat content in the upper ocean.

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.

Decadal Variation of the Aleutian Low-Icelandic Low Seesaw Simulated by a Climate System Model(CAS-ESM-C)

Based on a simulation using a newly developed climate system model(Chinese Academy of Sciences-Earth System Model-Climate system component, CAS-ESM-C), the author investigated the Aleutian Low- Icelandic Low Seesaw(AIS) and its decadal variation. Results showed that the CAS-ESM-C can reasonably reproduce not only the spatial distribution of the climatology of sea level pressure(SLP) in winter, but also the AIS and its decadal variation. The period 496–535 of the integration by this model was divided into two sub-periods: 496–515(P1) and 516–535(P2) to further investigate the decadal weakening of the AIS. It was shown that this decadal variation of the AIS is mainly due to the phase transition of the Pacific Decadal Oscillation(PDO), from its positive phase to its negative phase. This transition of the PDO causes the sea surface temperature(SST) in the equatorial eastern(northern) Pacific to cool(warm), resulting in the decadal weakening of mid-latitude westerlies over the North Pacific and North Atlantic. This may be responsible for the weakening of the inverse relation between the Aleutian Low(AL) and the Icelandic Low(IL).

Contrasting the Skills and Biases of Deterministic Predictions for the Two Types of El Nio

The tropical Pacific has begun to experience a new type of El Nio, which has occurred particularly frequently during the last decade, referred to as the central Pacific(CP) El Nio. Various coupled models with different degrees of complexity have been used to make real-time El Nio predictions, but high uncertainty still exists in their forecasts. It remains unknown as to how much of this uncertainty is specifically related to the new CP-type El Nio and how much is common to both this type and the conventional Eastern Pacific(EP)-type El Nio. In this study, the deterministic performance of an El Nio–Southern Oscillation(ENSO) ensemble prediction system is examined for the two types of El Nio. Ensemble hindcasts are run for the nine EP El Nio events and twelve CP El Nio events that have occurred since 1950. The results show that(1) the skill scores for the EP events are significantly better than those for the CP events, at all lead times;(2) the systematic forecast biases come mostly from the prediction of the CP events; and(3) the systematic error is characterized by an overly warm eastern Pacific during the spring season, indicating a stronger spring prediction barrier for the CP El Nio. Further improvements to coupled atmosphere–ocean models in terms of CP El Nio prediction should be recognized as a key and high-priority task for the climate prediction community.

Possible Sources of Forecast Errors Generated by the Global/Regional Assimilation and Prediction System for Landfalling Tropical Cyclones. Part Ⅱ: Model Uncertainty

This paper investigates the possible sources of errors associated with tropical cyclone(TC) tracks forecasted using the Global/Regional Assimilation and Prediction System(GRAPES). In Part I, it is shown that the model error of GRAPES may be the main cause of poor forecasts of landfalling TCs. Thus, a further examination of the model error is the focus of Part II.Considering model error as a type of forcing, the model error can be represented by the combination of good forecasts and bad forecasts. Results show that there are systematic model errors. The model error of the geopotential height component has periodic features, with a period of 24 h and a global pattern of wavenumber 2 from west to east located between 60?S and 60?N. This periodic model error presents similar features as the atmospheric semidiurnal tide, which reflect signals from tropical diabatic heating, indicating that the parameter errors related to the tropical diabatic heating may be the source of the periodic model error. The above model errors are subtracted from the forecast equation and a series of new forecasts are made. The average forecasting capability using the rectified model is improved compared to simply improving the initial conditions of the original GRAPES model. This confirms the strong impact of the periodic model error on landfalling TC track forecasts. Besides, if the model error used to rectify the model is obtained from an examination of additional TCs, the forecasting capabilities of the corresponding rectified model will be improved.

Typical Circulation Patterns and Associated Mechanisms for Persistent Heavy Rainfall Events over Yangtze–Huaihe River Valley during 1981–2020

Persistent heavy rainfall events(PHREs)over the Yangtze–Huaihe River Valley(YHRV)during 1981–2020 are classified into three types(type-A,type-B and type-C)according to pattern correlation.The characteristics of the synoptic systems for the PHREs and their possible development mechanisms are investigated.The anomalous cyclonic disturbance over the southern part of the YHRV during type-A events is primarily maintained and intensified by the propagation of Rossby wave energy originating from the northeast Atlantic in the mid–upper troposphere and the northward propagation of Rossby wave packets from the western Pacific in the mid–lower troposphere.The zonal propagation of Rossby wave packets and the northward propagation of Rossby wave packets during type-B events are more coherent than those for type-A events,which induces eastward propagation of stronger anomaly centers of geopotential height from the northeast Atlantic Ocean to the YHRV and a meridional anomaly in geopotential height over the Asian continent.Type-C events have“two ridges and one trough”in the high latitudes of the Eurasian continent,but the anomalous intensity of the western Pacific subtropical high(WPSH)and the trough of the YHRV region are weaker than those for type-A and type-B events.The composite synoptic circulation of four PHREs in 2020 is basically consistent with that of the corresponding PHRE type.The location of the South Asian high(SAH)in three of the PHREs in 2020 moves eastward as in the composite of the three types,but the position of the WPSH of the four PHREs is clearly westward and northward.Two water vapor conveyor belts and two cold air conveyor belts are tracked during the four PHREs in 2020,but the water vapor path from the western Pacific is not seen,which may be caused by the westward extension of the WPSH.

The Predictability of Ocean Environments that Contributed to the 2020/21 Extreme Cold Events in China:2020/21 La Niña and 2020 Arctic Sea Ice Loss

Several consecutive extreme cold events impacted China during the first half of winter 2020/21,breaking the low-temperature records in many cities.How to make accurate climate predictions of extreme cold events is still an urgent issue.The synergistic effect of the warm Arctic and cold tropical Pacific has been demonstrated to intensify the intrusions of cold air from polar regions into middle-high latitudes,further influencing the cold conditions in China.However,climate models failed to predict these two ocean environments at expected lead times.Most seasonal climate forecasts only predicted the 2020/21 La Niña after the signal had already become apparent and significantly underestimated the observed Arctic sea ice loss in autumn 2020 with a 1-2 month advancement.In this work,the corresponding physical factors that may help improve the accuracy of seasonal climate predictions are further explored.For the 2020/21 La Niña prediction,through sensitivity experiments involving different atmospheric-oceanic initial conditions,the predominant southeasterly wind anomalies over the equatorial Pacific in spring of 2020 are diagnosed to play an irreplaceable role in triggering this cold event.A reasonable inclusion of atmospheric surface winds into the initialization will help the model predict La Niña development from the early spring of 2020.For predicting the Arctic sea ice loss in autumn 2020,an anomalously cyclonic circulation from the central Arctic Ocean predicted by the model,which swept abnormally hot air over Siberia into the Arctic Ocean,is recognized as an important contributor to successfully predicting the minimum Arctic sea ice extent.

The Influence of Land Surface Changes on Regional Climate in Northwest China

Land surface changes effect the regional climate due to the complex coupling of land-atmosphere interactions. From 1995 to 2000, a decrease in the vegetation density and an increase in ground-level thermodynamic activity has been documented by multiple data sources in Northwest China, including meteorological, reanalysis from European Centre for Medium-Range Weather Forecasts （ECMWF）, National Oceanic and Atmospheric Administration＇s （NOAA） Advanced Very High Resolution Radiometer （AVHRR） and TIROS Operational Vertical Sounder （TOVS） satellite remote sensing data. As the ground-level thermodynamic activity increases, humid air from the surrounding regions converge toward desert （and semi-desert） regions, causing areas with high vegetation cover to become gradually more arid. Furthermore, land surface changes in Northwest China are responsible for a decrease in total cloud cover, a decline in the fraction of low and middle clouds, an increase in high cloud cover （due to thermodynamic activity） and other regional climatic adaptations. It is proposed that, beginning in 1995, these cloud cover changes contributed to a ＂green- house＂ effect, leading to the rapid air temperature increases and other regional climate impacts that have been observed over Northwest China.

On the Variation of Divergent Flow： An Eddy-flux Form Equation Based on the Quasi-geostrophic Balance and Its Application

Based on basic equations in isobaric coordinates and the quasi-geostrophic balance,an eddy-flux form budget equation of the divergent wind has been derived. This newly derived budget equation has evident physical significance. It can show the intensity of a weather system,the variation of its flow pattern,and the feedback effects from smaller-scale systems(eddy flows). The usefulness of this new budget equation is examined by calculating budgets for the strong divergent-wind centers associated with the South Asian high,and the strong divergence centers over the Tibetan Plateau,during summer(June–August) 2010. The results indicate that the South Asian high significantly interacts with eddy flows. Compared with effects from the mean flow(background circulation),the eddy flows’ feedback influences are of greater importance in determining the flow pattern of the South Asian high. Although the positive divergence centers over the Tibetan Plateau intensify through different mechanisms,certain similarities are also obvious. First,the effects from mean flow are dominant in the rapid intensification process of the positive divergence center. Second,an intense offsetting mechanism exists between the effects associated with the eddy flows’ horizontal component and the effects related to the eddy flows’ convection activities,which weakens the total effects of the eddy flows significantly. Finally,compared with the effects associated with the convection activities of the mean flow,the accumulated effects of the eddy flows’ convection activities may be more favorable for the enhancement of the positive-divergence centers.

System of Multigrid Nonlinear Least-squares Four-dimensional Variational Data Assimilation for Numerical Weather Prediction(SNAP):System Formulation and Preliminary Evaluation

A new forecasting system-the System of Multigrid Nonlinear Least-squares Four-dimensional Variational(NLS-4DVar)Data Assimilation for Numerical Weather Prediction(SNAP)-was established by building upon the multigrid NLS-4DVar data assimilation scheme,the operational Gridpoint Statistical Interpolation(GSI)−based data-processing and observation operators,and the widely used Weather Research and Forecasting numerical model.Drawing upon lessons learned from the superiority of the operational GSI analysis system,for its various observation operators and the ability to assimilate multiple-source observations,SNAP adopts GSI-based data-processing and observation operator modules to compute the observation innovations.The multigrid NLS-4DVar assimilation framework is used for the analysis,which can adequately correct errors from large to small scales and accelerate iteration solutions.The analysis variables are model state variables,rather than the control variables adopted in the conventional 4DVar system.Currently,we have achieved the assimilation of conventional observations,and we will continue to improve the assimilation of radar and satellite observations in the future.SNAP was evaluated by case evaluation experiments and one-week cycling assimilation experiments.In the case evaluation experiments,two six-hour time windows were established for assimilation experiments and precipitation forecasts were verified against hourly precipitation observations from more than 2400 national observation sites.This showed that SNAP can absorb observations and improve the initial field,thereby improving the precipitation forecast.In the one-week cycling assimilation experiments,six-hourly assimilation cycles were run in one week.SNAP produced slightly lower forecast RMSEs than the GSI 4DEnVar(Four-dimensional Ensemble Variational)as a whole and the threat scores of precipitation forecasts initialized from the analysis of SNAP were higher than those obtained from the analysis of GSI 4DEnVar.

Heat waves in summer 2022 and increasing concern regarding heat waves in general

The year 2022 featured an unprecedented hot summer that has attracted worldwide attention.Abnormal warming spread over most of the Eurasian continent and North America(Fig.1),with Europe and China especially suffering from extraordinarily long-lasting extreme heat events.In addition,severe droughts,which are a common accompaniment to heat waves,attacked Europe and the Yangtze River basin in China.Droughts in Sichuan Province,which is in the upstream region of the Yangtze River basin and is proud of its water resources and hydro power,led to power shortages and adverse effects on the lives and productivity of local people.Extremely high temperatures and severe drought induced massive wildfires in Europe,North America,and Asia,including Chongqing(Fig.2),a neighboring municipality of Sichuan Province.