Abstract:Interpreting the impacts and adaptations of food systems in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) Working Group II (WGII) is important for the scientific understanding of the frontiers of the international discipline of climate change impacts on agriculture.The newly released IPCC AR6,on the basis of further elaboration of food production capacity,planting layout,pest and disease impacts,further confirms the negative impacts of anthropogenic warming on food systems,discusses climate risks in food processing,transportation and consumption,extends the review of food impacts in complex ecosystems,and expands the analysis of climate change impacts on the entire chain of food production-processing-transportation-consumption.It extends the attribution of impacts and enriches the scientific understanding of agro-environmental impacts.As for the adaptation capacity of food systems,it emphasizes the development pathway of climate resilience based on the synergy of adaptation and mitigation,the adaptation assessment has gradually shifted from the theoretical aspects of adaptation capacity and adaptation methods to the assessment of adaptation implementation and effectiveness,and the regional specificity and effectiveness of adaptation actions are identified.This assessment emphasizes the detection and attribution of climate change impacts on crops,focuses on the impacts of climate and agro-environmental change,introduces ecosystem-based adaptation schemes and technologies,and assesses the feasibility and effectiveness of existing adaptation technologies.The contents of the report are important references for China to strengthen its capacity in agricultural impact assessment and to catch the international dynamics of the discipline.

Abstract:In this report,the IPCC Working Group Ⅱ's contribution to the Sixth Assessment Report Chapter 3 presents an assessment of the impacts of climate change on the ocean and coastal ecosystems,along with their vulnerability and the potential adaptation solutions.This report clarifies the fact that the anthropogenic greenhouse gases have and will continue to cause fundamental changes to the physical and chemical properties of our centrally important oceans,including warming,sea level rise (SLR),acidification,deoxygenation,and change in nutrients.The occurrences of the marine heatwaves have doubled since the 1980s,and will become 4-8 times more frequent in 2081—2100 compared to 1995—2014.In addition,ocean warming since the 1950s has shifted marine species poleward,at an average of 59.2±15.5 km per decade.This has resulted in reduced biomass in tropical waters,a remarkable tropicalization of mid-latitude ocean,and an earlier phytoplankton growth period in polar and sub-polar areas.Marine heatwaves are exposing species,and ecosystems approach or even exceed their tolerance,causing mass coral bleaching and mortality,and loss of seagrasses and kelp forests.Warming,acidification and hypoxia have collectively resulted in changes in the community structure and increases in the occurrence of harmful algal blooms in estuaries,and have contributed to an overall decline in phytoplankton biomass and primary production.In the meantime,phytoplankton biomass in the polar ocean will increase.Accelerating SLR has led to the degradation of coastal wetland ecosystems (e.g.,mangroves,saltmarshes and seagrass beds).Ocean conditions are projected to continue and increase risk of regional extirpations and global extinctions of marine species,especially near the Equator and in the Arctic.Coral reefs are projected to decline by a further 70%—90％ at 1.5 ℃ warming with greater losses (>99％) at 2 ℃,as early as the 2040s under SSP5-8.5.The current available adaptation options (e.g.,marine protected areas and mangrove restoration) are unable to offset the growing climate-change risk,thus exemplifying the need for transformative climate adaptation and ambitious mitigation measures.

Abstract:The second working group of the IPCC Sixth Assessment Report (IPCC AR6 WGⅡ) focuses on the impact,risk,adaptation and vulnerability of climate change.The report quantitatively assesses the impact of climate change on natural and human systems with the latest data,detailed evidence and diverse methods.Compared to AR5,the following progress has been made:Firstly,The content clarifies that the impact of climate change is attributable to three categories:anthropogenic climate forcing,non-climate factor action and weather sensitivity identification,127 key risks from climate change will become widespread or irreversible,and limiting global warming to 1.5 ℃ can greatly reduce climate change loss and damage to natural and human systems,pointing to the importance of adapting to transition.Secondly,AR6 WGⅡ adopts the latest combination of SSPs and RCPS in terms of evaluation method,which is more comprehensive.Thirdly,AR6 WGⅡ has focus on risks and solutions,and on the basis of AR5 WGⅡ,it is clarified that under different future warming scenarios,the risk level of the key risks facing the five “reasons for concern (RFCs)” will be relied on lower to very high levels of global warming.Finally,AR6 WGⅡ clarifies the urgency of climate action,combining adaptation and mitigation to support sustainable development is essential for climate resilience development pathways,pointing to the importance of immediate action to address climate risks.

Abstract:Attribution studies include climate change attribution,impact attribution and identification of weather sensitivity.IPCC Sixth Assessment Report Working Group Ⅱ (AR6 WGⅡ) follows the definition of climate change impact attribution in the Fifth Assessment Report Working Group Ⅱ (AR5 WGⅡ),and considers that climate change impact attribution assesses the contribution of climate system changes to observed natural,human or managed system changes.IPCC AR6 WGⅡ sets up a “no-climate change baseline” in the impact attribution studies,and summarizes most recent achievements on the impact attribution of climate change on terrestrial ecosystems,marine ecosystems,coastal systems,water systems,food systems and human society.Compared with the AR5 WGⅡ,the AR6 WGⅡ more specifically describes the impact of climate change on nature,human or managed systems,improves the reliability of some assessment conclusions,and gives more evidence on the social impact of climate change.Although some progresses have been made in climate change impact attribution,the AR6 WGⅡ points out that more high-quality data,more effective methods for quantifying climate change impacts and more comprehensive understanding on the mechanisms of systematic change are still needed to deepen the research on climate change impact attribution.

Abstract:Chapter 7 of the IPCC Sixth Assessment Report (AR6),Working Group II (WG II),entitled'Health,well-being and the changing structure of communities’,assessed the current impacts and projected risks of climate change on health and well-being,and proposed strategies and constraints for health adaptation.Evidence has increased since AR5 that climate change has had negative impacts on human physical health,including mental health,through direct or indirect way,and that climate-sensitive diseases,malnutrition,premature death,and threats to mental health are increasing,and that climate-related hazards are increasingly affecting a growing number of health outcomes (including communicable and non-communicable diseases) and geographical areas.Cascading and compounding risks affecting health due to extreme weather events have been observed in all regions and risks are expected to increase with further warming.Key adaptation measures for health risks include increasing investment in health and other systems,strengthening integration and collaboration across sectors and systems,building climate-resilient development pathways,and integrating adaptation and mitigation in the goal of sustainable development and so on,which will bring huge co-benefits for health and well-being.

Abstract:The chapter of Working Group Ⅱ Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6 WGⅡ) entitled,“Key Risks Across Sectors and Regions”,synthesizes observed climate change impacts,adaptation-related responses,limits to adaptation,and the key risks identified across sectors and regions.Compared to AR5,AR6 WGⅡ provides additional and stronger evidence for impacts of climate change;emphasizes the effect of adaptation to reducing risk;differentiates soft and hard limits to adaptation;raises the concept of residual risk in the conceptual framework of risk evaluation;and updates the dependence of risk associated with the Reasons for Concern on the level of climate change.The impacts of changes in climate-related systems have been identified in a wide range of natural,human,and managed systems (very high confidence).The responses in ecosystems may not be adaptive enough or sufficient to cope with the rate of climate changes (high confidence).There is negligible evidence that adaptation in human systems is adequate to reduce climate risk (high confidence).Maladaptation is increasing (high confidence).Limits to adaptation stem from interactions between soft and hard limits (high confidence).The report of AR6 WGⅡ identified 127 Key Risks and risk cascades,which will enhance eight Representative Key Risks across sectors and regions to a certain extent.Representative Key Risks increase the challenges in achieving global sustainability goals (high confidence).Increasing evidence now supports the five major Reasons for Concern regarding climate change.Assuming low to no adaptation,risks for all five Reasons for Concern increase to high and very high levels under global warming (high confidence).

Abstract:Based on the daily precipitation data of 60 stations in South China and NCEP reanalysis data,the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT_4.9) are used to analyze the difference of water vapor transport trajectories of frontal and monsoon precipitation in the pre-flood season in South China,main water vapor sources and precipitation contribution rates of water vapor in main sources during different Pacific Decadal Oscillation (PDO) phases from 1960 to 2012.Results show that:(1)In the frontal precipitation stage,there is more water vapor in the Western Pacific-the South China Sea-the Bay of Bengal during the positive PDO phase.In the summer monsoon precipitation stage,the water vapor in the northern Indian Ocean-the Bay of Bengal-the South China Sea is more during the positive PDO phase.(2)In the frontal precipitation stage,the water vapor mainly comes from the Northwest Pacific and the South China Sea.During the positive PDO phase,the subtropical high is located to the north,which makes the water vapor transport path in the Western Pacific to the north and transports more water vapor to South China.It is conducive to the formation of monsoon precipitation in South China.There is a significant positive correlation between precipitation and PDO.(3)In the monsoon precipitation stage,during the positive PDO phase,although the water vapor content in the whole layer from the northern Indian Ocean-the Bay of Bengal-the South China Sea is large,it is not completely transported to South China,so the effective monsoon precipitation is less,and there is a significant negative correlation between precipitation and PDO.

Abstract:Solar forcing has an important impact on the formation and evolution of the Earth's climate.Under the influence of quasi-11-year solar cycle,the global climate changes with heterogeneity.The details of the response of the tropical Pacific sea surface temperature (SST) to solar 11-year variability and how it amplifies this response are important matters of discussion.Sunspot numbers (SSN) are used to represent the intensity of solar forcing.When the SSN increases,then the solar forcing strengthens.Positive and negative Niño3 indices are used to characterize the El Niño-like and La Niña-like SSTs.Bootstrap methods are used to verify the statistical significance of each signal.Next,based on the historical experiment from 24 CMIP5 (Coupled Model Intercomparison Project Phase 5),this paper evaluates the ability of models to simulate the observed significant La Niña-like SST anomalies in the tropical Pacific,which is stimulated by quasi-11-year solar cycle.By analyzing the reanalysis data,the “bottom-up” mechanism explains that the significant La Niña-like SST anomalies in the eastern tropical Pacific are likelier to occur in years with high solar activity.The results illustrate that two fifths of the CMIP5 models can effectively demonstrate the negative SST anomalies in the tropical eastern Pacific during the high solar forcing,which are segmented into the La Niña-like group.Meanwhile,another three fifths of the models can even simulate the opposite signal,which are known as the El Niño-like group.In order to explore the different simulation capabilities of the CMIP5 models,this paper analyzes the “bottom-up” mechanism in the model.The “bottom-up” mechanism is divided into two processes:evaporation process and thermostat process.The results show that whether or not the models can simulate the La Niña-like SST response depends on the strength of the thermostat process,and the thermostat process in La Niña-like group is stronger.However,it is observed that the evaporation process is not a key factor.

Abstract:Based on three centennial SST data,this paper investigated the interdecadal variation of the interannual transition from Indian Ocean Dipole (IOD) to Indian Ocean Basin Mode (IOB) by using statistical analysis and interannual signal removal methods.Results show that there is almost no such transition from 1940 to 1970,but it is very significant after 1970.It is found that the interdecadal variation of air-sea coupling between IOD and ENSO is the main reason for this transition.The occurrence and development of IOD and ENSO are independent from 1940 to 1970,but they are closely related after 1970.Through further diagnostic analysis of physical quantity fields,this paper reveals the main dynamic mechanism.Before 1970,the anomalous monsoon circulation over the tropical Indian Ocean could not be coupled with the anti-walker circulation over the tropical Pacific Ocean,and the IOD event cannot be connected with the tropical Pacific when it occurs.On the contrary,after 1970,the coupling effect between the two latitudinal circulation anomalies over the two tropical oceans is strong.When the positive (negative) IOD event occurs,it promotes the development of El Niño (La Niña) through air-sea interaction,and the Indian Ocean will receive the positive feedback from ENSO.Therefore,this “geared-like” coupling model can last until winter and the following spring,and the tropical Indian Ocean is continuously affected by the easterly (westerly) anomaly and guided by the low-level circulation.There is an inflow (outflow) of subsurface warm water in the western Indian Ocean,coupled with the small basin size of the Indian Ocean itself,so the western warm (cold) water area increases significantly,the difference between the east and west SST anomalies rapidly decreases,and it changes to the uniform warming (cold) of the basin,which leads to the occurrence of positive (negative) IOB events in the late winter and spring.

Abstract:During the “21·7” extreme rainstorm in Henan,the precipitation of mutil-model showed great differences and divergence.This paper uses multiple spatial verification methods (such as CRA,neighborhood TS score and FSS) to comprehensively evaluate the forecast performance of multiple numerical models during the “21·7” Henan extreme rainstorm process,and diagnoses the cause of model deviation from the aspects of low-level jet,water vapor convergence and thermal conditions.Results show that:(1)For the position forecast deviation of precipitation over 100 mm,the forecast performance of WARMS is the best,followed by GRAPES_3 km.When the heavy rain area predicted by RMAPS is comparable to the observation,the predicted precipitation intensity is obviously stronger,and the predicted rain area continues to appear westward compared with the observation.(2)The position deviation of 3 h cumulative precipitation predicted by GRAPES_3 km and WARMS is more manifested in the meridional direction and has large dispersion.The meridional deviation decreases obviously when the forecast time is nearer,while the zonal deviation changes slightly with the forecast time.The position forecast deviation of RMAPS is mainly manifested in the zonal direction,with 86.7％,91.3％ and 72.7％ of the individual forecasts of precipitation being westward from the 19th to the 21st,respectively.(3)The weak forecast of low-level jet and water vapor convergence by WARMS leads to the underestimation of precipitation intensity from 19th to 20th.The main reason for the location deviation of precipitation area is that the low-level jet predicted by EC and RMAPS is obviously westward from the 19th to 20th.MESO has a good forecast of the occurrence time and location of jet stream and water vapor convergence on the 20th,but it lacks the ability to predict extreme heavy precipitation due to the obviously weak thermal conditions.(4)On the 21st,too many easterly components of low-level jet predicted by MESO and RMAPS leads to the strong terrain increasing precipitation forecast at the steep terrain of Taihang Mountain.The wind direction of low-level jet stream forecasted by EC and WARMS is closer to the observation,but the forecast deviation of intensity and time of low-level water vapor convergence leads to the obvious meridional position deviation of individual precipitation forecast.

Abstract:Global atmospheric models have been continuously improved in the development process,and have gradually adopted unstructured computing grids,such as the atmospheric component of Model for Prediction Across Scales (MPAS-A) characterized by the spherical centroid Voronoi mesh.In order to improve the initial value of MPAS-A model,relevant data assimilation research is actively carried out simultaneously.In order to meet the needs of rapid assimilation of multi-source observation data by using variational method,this paper takes the Gridpoint Statistical Interpolation (GSI) system used in NCEP business in the United States as the assimilation module,handles transformations between unstructured and structured spherical grids based on conservation remapping method,constructs the GSI-MPAS assimilation and prediction framework,and carries out grid transformation experiments and assimilation prediction experiments.The grid transformation tests show that the transformation errors of model physical quantities are closely related to their distribution patterns,and the second-order precision conservative remapping transformation results are better than the first-order precision transformation results.The continuous rolling cycle assimilation and prediction experiment for one week shows that the GSI-MPAS assimilation and prediction framework based on the conservation remapping method can effectively assimilate multi-source observation data,improve the quality of initial value field,make each variable obtained by MPAS-A prediction more accurate,and have a positive effect on precipitation prediction.Further analysis shows that the improvements in the Northern Hemisphere are obviously better than those in the Southern Hemisphere and the equatorial region due to the assimilation of more observation data in the Northern Hemisphere.

Abstract:With the development of automatic meteorological observation technology in China,approximately 70,000 automatic observation stations have been constructed across the country,and the automation of meteorological observation has been fully realized.Automatic observation technology causes the amount of meteorological observation data to increase rapidly,but how to improve the utilization rate of automatic observation data through quality control is of particular importance.This study uses a total of 168 temperature observation data of automatic ground stations,beginning from 00:00 to 23:00 BST on December 1,2019,provided by Jiangsu meteorological bureau,along with the temperature grid data in the ECMWF Reanalysis V5 (ERA5) Reanalysis data of European Centre for Medium-range Weather Forecasts (ECMWF).Next,by combining the general quality control method and Empirical Orthogonal Function (EOF) quality control method,this paper establishes a quality control method for surface temperature data with high spatial and temporal resolution.Next,real data quality control experiments on surface temperature observation of automatic stations in central and eastern China are conducted to verify the effectiveness of the new method.The results show that,according to the characteristics of the automatic station high density,by choosing the appropriate analysis area,the EOF analysis method can effectively extract organized observation system information,so as to ensure that the remaining information better meet the random distribution characteristics.After this,abnormal observations can be effectively removed according to the probability distributions,which in turn can help avoid the impact of changes in the weather.

Abstract:The accurate spatial-temporal distribution of soil moisture,which is one of the important parameters of the Earth System Simulation,is the basis for land-atmosphere interaction.Both reanalysis data and the land data assimilation system (LDAS) can provide global or regional high-resolution soil moisture products.However,validation of the simulation data is required before application.In this study,the fidelity of soil moisture products,including four reanalyzed soil moisture products (ERA5,ERA5-Land,NCEP-DOE R2 and CRA40) and three LDAS soil moisture products (GLDAS-Noah,GLDAS-CLSM and CLDAS) are examined using the in situ datasets via several statistical indexes (e.g.,median,deviation,and correlation coefficient) in northern China.The results show that CRA40 achieves the best correlation with observations,while ERA5 and ERA5-Land respectively provide better simulation for dry and wet centers.In addition,GLDAS-Noah shows a slightly positive bias for drier soil areas,and CLDAS presents a negative bias for wet soil areas.In general,NCEP-DOE R2 and GLDAS-CLSM exhibit poor simulation in northern China.ERA5-Land,ERA5-Land,NCEP-DOE R2,GLDAS-Noah and CLDAS show simulated positive bias in all seasons.The better simulation results in spring are CRA40 and ERA5-Land,along with ERA5-Land,ERA5 and CRA40 in summer and autumn.In winter,the correlation between the soil moisture simulated by different products and the observed value is the smallest throughout the year.In arid regions,different soil moisture products exhibited positive deviations,with the GLDAS-Noah simulation being the best,but the peak and valley values of soil moisture in the simulated products appeared earlier than observed.GLDAS-Noah,CRA40 and ERA5 can more effectively simulate the duration of dry and wet soils and the amplitude of soil moisture changes in the monsoon region.Most of the products can simulate the occurrence of drier soils and wetter soils in the transition zone that is affected by the summer monsoon.

Abstract:Cloud droplet spectral relative dispersion is critical to the aerosol-cloud-radiation interaction and the formation of surface precipitation.This study discusses the relationship between relative dispersion of cloud droplet size distributions and volume-mean radius by analyzing the observation data from April to July 2008,May to August 2009 and May to September 2011 at Guangming Peak of Mount Huangshan.This relationship is often used to parameterize relative dispersion.The results show that the relationship between relative dispersion and volume-mean radius changes from positive to negative with the increase of the volume-mean radius,which is mainly related to activation,condensation,evaporation and deactivation,and this is consistent with previous studies.It is further found that the negative correlation is relatively weak,mainly due to collision-coalescence.In addition,when the autoconversion threshold function increases,the correlation between relative dispersion and volume-mean radius turns from negative to positive,and the degree of positive correlation gradually increases due to enhanced collision-coalescence.The positive correlation caused by collision-coalescence offsets the negative correlation caused by condensation and evaporation.In addition,although some cloud droplet size distributions have double peaks,the first bin strength (i.e.,the first bin number concentration divided by the total number concentration) is still able to effectively distinguish their positive and negative correlations.These results will enhance the theoretical understanding of the influencing factors of relative dispersion,which is conducive to the improvement of relative dispersion parameterizations.