Design and Implementation of National Meteorological Service Platform

In order to change the distributed status of the meteorological service platform,based on the integration of the self-built service platforms including meteorology,climate,observation and service,National Meteorological Information Center( NMIC) constructs National Meteorological Service Platform( NMSP). NMSP is a unified national meteorological service platform to provide browsing,searching and displaying of observation,weather forecasting,warning information,historical climate data and network information. NMSP uses the MVC design pattern.For adapting the characteristics of meteorological application,above J2 EE application framework( Struts + Spring + Hibernate),NMSP encapsulates data exchange module which improves flexibility and efficiency of the system development. On March 2015,NMSP( version 2. 0)has been on operational running,which covers six core sections,nearly 100 sub-modules,2000 kinds of service products. It plays an effective supporting role on various types of meteorological service.

Construction and Application of a Regional Kilometer-Scale Carbon Source and Sink Assimilation Inversion System(CCMVS-R)

CO_(2)is one of the most important greenhouse gases(GHGs)in the earth’s atmosphere.Since the industrial era,anthropogenic activities have emitted excessive quantities of GHGs into the atmosphere,resulting in climate warming since the 1950s and leading to an increased frequency of extreme weather and climate events.In 2020,China committed to striving for carbon neutrality by 2060.This commitment and China’s consequent actions will result in significant changes in global and regional anthropogenic carbon emissions and therefore require timely,comprehensive,and objective monitoring and verification support(MVS)systems.The MVS approach relies on the top-down assimilation and inversion of atmospheric CO_(2)concentrations,as recommended by the Intergovernmental Panel on Climate Change(IPCC)Inventory Guidelines in 2019.However,the regional high-resolution assimilation and inversion method is still in its initial stage of development.Here,we have constructed an inverse system for carbon sources and sinks at the kilometer level by coupling proper orthogonal decomposition(POD)with four-dimensional variational(4DVar)data assimilation based on the weather research and forecasting-greenhouse gas(WRF-GHG)model.Our China Carbon Monito ring and Verification Support at the Regional level(CCMVS-R)system can continuously assimilate information on atmospheric CO_(2)and other related information and realize the inversion of regional and local anthropogenic carbon emissions and natural terrestrial ecosystem carbon exchange.Atmospheric CO_(2)data were collected from six ground-based monito ring sites in Shanxi Province,China to verify the inversion effect of regio nal anthropogenic carbon emissions by setting ideal and real experiments using a two-layer nesting method(at 27 and 9 km).The uncertainty of the simulated atmospheric CO_(2)decreased significantly,with a root-mean-square error of CO_(2)concentration values between the ideal value and the simulated after assimilation was close to 0.The total anthropogenic carbon emissions in Shanxi Province in 2019 from the assimilated inversions were approximately 28.6%(17%-38%)higher than the mean of five emission inventories using the bottomup method,showing that the top-down CCMVS-R system can obtain more comprehensive information on anthropogenic carbon emissions.

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.

A New Method for Deriving High-Vertical-Resolution Wind Vector Data from the L-Band Radar Sounding System in China

High-vertical-resolution radiosonde wind data are highly valuable for describing the dynamics of the meso-and microscale atmosphere. However, the current algorithm used in China's L-band radar sounding system for calculating highvertical-resolution wind vectors excessively smooths the data, resulting in significant underestimation of the calculated kinetic energy of gravity waves compared to similar products from other countries, which greatly limits the effective utilization of the data. To address this issue, this study proposes a novel method to calculate high-vertical-resolution wind vectors that utilizes the elevation angle, azimuth angle, and slant range from L-band radar. In order to obtain wind data with a stable quality, a two-step automatic quality control procedure, including the RMSE-F(root-mean-square error F) test and elemental consistency test are first applied to the slant range data, to eliminate continuous erroneous data caused by unstable signals or radar malfunctions. Then, a wind calculation scheme based on a sliding second-order polynomial fitting is utilized to derive the high-vertical-resolution radiosonde wind vectors. The evaluation results demonstrate that the wind data obtained through the proposed method show a high level of consistency with the high-resolution wind data observed using the Vaisala Global Positioning System and the data observed by the new Beidou Navigation Sounding System. The calculation of the kinetic energy of gravity waves in the recalculated wind data also reaches a level comparable to the Vaisala observations.

Summer Atmospheric Water Cycle under the Transition Influence of the Westerly and Summer Monsoon over the Yarlung Zangbo River Basin in the Southern Tibetan Plateau

This study compares the summer atmospheric water cycle,including moisture sources and consumption,in the upstream,midstream,and downstream regions of the Yarlung Zangbo River Basin in the southern Tibetan Plateau.The evolutions of moisture properties under the influence of the westerly and summer southerly monsoon are examined using 5-yr multi-source measurements and ERA5 reanalysis data.Note that moisture consumption in this study is associated with clouds,precipitation,and diabatic heating.Compared to the midstream and downstream regions,the upstream region has less moisture,clouds,and precipitation,where the moisture is brought by the westerly.In early August,the vertical wet advection over this region becomes enhanced and generates more high clouds and precipitation.The midstream region has moisture carried by the westerly in June and by the southerly monsoon from July to August.The higher vertical wet advection maximum here forms more high clouds,with a precipitation peak in early July.The downstream region is mainly affected by the southerly-driven wet advection.The rich moisture and strong vertical wet advection here produce the most clouds and precipitation among the three regions,with a precipitation peak in late June.The height of the maximum moisture condensation is different between the midstream region(325 hPa)and the other two regions(375 hPa),due to the higher upward motion maximum in the midstream region.The diabatic heating structures show that stratiform clouds dominate the upstream region,stratiform clouds and deep convection co-exist in the midstream region,and deep convection systems characterize the downstream region.

Assimilating FY-4A AGRI Radiances with a Channel-Sensitive Cloud Detection Scheme for the Analysis and Forecasting of Multiple Typhoons

This paper presents an attempt at assimilating clear-sky FY-4A Advanced Geosynchronous Radiation Imager(AGRI)radiances from two water vapor channels for the prediction of three landfalling typhoon events over the West Pacific Ocean using the 3DVar data assimilation(DA)method along with the WRF model.A channel-sensitive cloud detection scheme based on the particle filter(PF)algorithm is developed and examined against a cloud detection scheme using the multivariate and minimum residual(MMR)algorithm and another traditional cloud mask–dependent cloud detection scheme.Results show that both channel-sensitive cloud detection schemes are effective,while the PF scheme is able to reserve more pixels than the MMR scheme for the same channel.In general,the added value of AGRI radiances is confirmed when comparing with the control experiment without AGRI radiances.Moreover,it is found that the analysis fields of the PF experiment are mostly improved in terms of better depicting the typhoon,including the temperature,moisture,and dynamical conditions.The typhoon track forecast skill is improved with AGRI radiance DA,which could be explained by better simulating the upper trough.The impact of assimilating AGRI radiances on typhoon intensity forecasts is small.On the other hand,improved rainfall forecasts from AGRI DA experiments are found along with reduced errors for both the thermodynamic and moisture fields,albeit the improvements are limited.

Quality Information Management and Application of AWS

This paper has designed a unified storage model of Automatic Weather Station Quality Information Inquiries and Feedback( AWSQIF),and has developed an AWSQIF automatic management system,which implements the storage of AWSQIF automatically in national quality information two-way feedback process. Based on the unified storage,AWSQIF data have important application in real-time data management,data quality assessment and quality control effect analysis. The results show that the data quality has been improved significantly,and the data assessment has achieved online operating. In addition,AWSQIF can assist the improvement of the quality control effect.

Workflow-Based Platform Design and Implementation for Numerical Weather Prediction Models and Meteorological Data Service

In this paper, we present a set of best practices for workflow design and implementation for numerical weather prediction models and meteorological data service, which have been in operation in China Meteorological Administration (CMA) for years and have been proven effective in reliably managing the complexities of large-scale meteorological related workflows. Based on the previous work on the platforms, we argue that a minimum set of guidelines including workflow scheme, module design, implementation standards and maintenance consideration during the whole establishment of the platform are highly recommended, serving to reduce the need for future maintenance and adjustment. A significant gain in performance can be achieved through the workflow-based projects. We believe that a good workflow system plays an important role in the weather forecast service, providing a useful tool for monitoring the whole process, fixing the errors, repairing a workflow, or redesigning an equivalent workflow pattern with new components.

Vertical structure of predictability and information transport over the Northern Hemisphere

Based on nonlinear prediction and information theory, vertical heterogeneity of predictability and information loss rate in geopotential height field are obtained over the Northern Hemisphere. On a seasonal-to-interannual time scale, the predictability is low in the lower troposphere and high in the mid-upper troposphere. However, within mid-upper troposphere over the subtropics ocean area, there is a relatively poor predictability. These conclusions also fit the seasonal time scale. Moving to the interannual time scale, the predictability becomes high in the lower troposphere and low in the mid-upper troposphere, contrary to the former case. On the whole the interannual trend is more predictable than the seasonal trend. The average information loss rate is low over the mid-east Pacific, west of North America, Atlantic and Eurasia, and the atmosphere over other places has a relatively high information loss rate on all-time scales. Two channels are found steadily over the Pacific Ocean and Atlantic Ocean in subtropics. There are also unstable channels. The four- season influence on predictability and information communication are studied. The predictability is low, no matter which season data are removed and each season plays an important role in the existence of the channels, except for the winter. The predictability and teleconnections are paramount issues in atmospheric science, and the teleconnections may be established by communication channels. So, this work is interesting since it reveals the vertical structure of predictability distribution, channel locations, and the contributions of different time scales to them and their variations under different seasons.

Development of Operational Technology for Meteorological High Performance Computing

As an important branch of information technology, high-performance computing has expanded its application field and its influence has been expanding. High-performance computing is always a key area of application in meteorology. We used field research and literature review methods to study the application of high performance computing in China’s meteorological department, and obtained the following results: 1) China Meteorological Department gradually established the first high-performance computer system since 1978. High-performance computing services can support operational numerical weather prediction models. 2) The Chinese meteorological department has always used the relatively advanced high-performance computing technology, and the business system capability has been continuously improved. The computing power has become an important symbol of the level of meteorological modernization. 3) High-performance computing technology and meteorological numerical forecasting applications are increasingly integrated, and continue to innovate and develop. 4) In the future, high-performance computing resource management will gradually transit from the current local pre-allocation mode to the local remote unified scheduling and shared use. In summary, we have come to the conclusion that the performance calculation business of the meteorological department will usher in a better tomorrow.

Study and Analysis of the High Performance Computing Failures in China Meteorological Field

China Meteorological Administration (CMA) has a long history of using High Performance Computing System (HPCS) for over three decades. CMA HPCS investment provides reliable HPC capabilities essential to run Numerical Weather Prediction (NWP) models and climate models, generating millions of weather guidance products daily and providing support for Coupled Model Inter-comparison Project Phase 5 (CMIP5). Monitoring the HPCS and analyzing the resource usage can improve the performance and reliability for our users, which require a good understanding of failure characteristics. Large-scale studies of failures in real production systems are scarce. This paper collects, analyzes and studies all the failures occurring during the HPC operation period, especially focusing on studying the relationship between HPCS and NWP applications. Also, we present the challenges for a more effective monitoring system development and summarize the useful maintenance strategies. This step may have considerable effects on the performance of online failure prediction of HPC and better performance in future.

Evaluation of the Application Benefit of Meteorological High Performance Computing Resources

The meteorological high-performance computing resource is the support platform for the weather forecast and climate prediction numerical model operation. The scientific and objective method to evaluate the application of meteorological high-performance computing resources can not only provide reference for the optimization of active resources, but also provide a quantitative basis for future resource construction and planning. In this paper, the concept of the utility value B and index compliance rate E of the meteorological high performance computing system are presented. The evaluation process, evaluation index and calculation method of the high performance computing resource application benefits are introduced.

Elucidating Dominant Factors Affecting Land Surface Hydrological Simulations of the Community Land Model over China

In order to compare the impacts of the choice of land surface model(LSM)parameterization schemes,meteorological forcing,and land surface parameters on land surface hydrological simulations,and explore to what extent the quality can be improved,a series of experiments with different LSMs,forcing datasets,and parameter datasets concerning soil texture and land cover were conducted.Six simulations are run for the Chinese mainland on 0.1°×0.1°grids from 1979 to 2008,and the simulated monthly soil moisture(SM),evapotranspiration(ET),and snow depth(SD)are then compared and assessed against observations.The results show that the meteorological forcing is the most important factor governing output.Beyond that,SM seems to be also very sensitive to soil texture information;SD is also very sensitive to snow parameterization scheme in the LSM.The Community Land Model version 4.5(CLM4.5),driven by newly developed observation-based regional meteorological forcing and land surface parameters(referred to as CMFD_CLM4.5_NEW),significantly improved the simulations in most cases over the Chinese mainland and its eight basins.It increased the correlation coefficient values from 0.46 to 0.54 for the SM modeling and from 0.54 to 0.67 for the SD simulations,and it decreased the root-mean-square error(RMSE)from 0.093 to 0.085 for the SM simulation and reduced the normalized RMSE from 1.277 to 0.201 for the SD simulations.This study indicates that the offline LSM simulation using a refined LSM driven by newly developed observation-based regional meteorological forcing and land surface parameters can better model reginal land surface hydrological processes.

A Daily Temperature Dataset over China and Its Application in Validating a RCM Simulation

This paper describes the construction of a 0.5°× 0.5° daily temperature dataset for the period of 1961- 2005 over China's Mainland for the purpose of climate model validation. The dataset is based on the interpolation from 751 observing stations in China and comprises 3 variables： daily mean, minimum, and maximum temperature. The ＂anomaly approach＂ is applied in the interpolation. The gridded climatology of 1971-2000 is first calculated and then a gridded daily anomaly for 1961-2005 is added to the climatology to obtain the final dataset. Comparison of the dataset with CRU （Climatic Research Unit） observations at the monthly scale shows general agreement between the two datasets. The differences found can be largely attributed to the introduction of observations at new stations. The dataset shows similar interannual variability as does CRU data over North China and eastern part of the Tibetan Plateau, but with a slightly larger linear trend. The dataset is employed to validate the simulation of three extreme indices based on daily mean, minimum, and maximum temperature by a high-resolution regional climate model. Results show that the model reproduces these indices well. The data are available at the National Climate Center of China Meteorological Administration, and a coarser resolution （1°× 1°） version can be accessed via the World Wide Web.

Comparative analysis of GF-1,HJ-1,and Landsat-8 data for estimating the leaf area index of winter wheat

Using simultaneously collected remote sensing data and field measurements, this study firstly assessed the consistency and applicability of China high-resolution earth observation system satellite 1 （GF-1） wide field of view （WFV） camera, environment and disaster monitoring and forecasting satellite （H J-l） charge coupled device （CCD）, and Landsat-8 opera- tional land imager （OLI） data for estimating the leaf area index （LAI） of winter wheat via reflectance and vegetation indices （VIs）. The accuracies of these LAI estimates were then assessed through comparison with an empirical model and the PROSAIL radiative transfer model. The effects of radiation calibration, spectral response functions, and spatial resolution on discrepancies in the LAI estimates between the different sensors were also analyzed. The results yielded the following observations： （1） The correlation between reflectance from different sensors is relative good, with the adjusted coefficients of determination （R2） between 0.375 to 0.818. The differences in reflectance are ranging from 0.002 to 0.054. The correlation between VIs from different sensors is high with the R2 between 0.729 and 0.933. The differences in the VIs are ranging from 0.07 to 0.156. These results show the three sensors＇ images can all be used for cross calibration of the reflectance and VIs. （2） The four VIs from the three sensors are all demonstrated to be highly correlated with LAI （R2 between 0.703 and 0.849）. The linear models associated with the 2-band enhanced vegetation index （EVI2）, which feature the highest R2 （higher than 0.746） and the lowest root mean square errors （RMSE） （less than 0.21）, were selected to estimate the winter wheat LAI. The accuracy of the estimated LAI from Landsat-8 was the highest, with the relative errors （RE） of 2.18% and an RMSE of 0.13, while the H J-1 was the lowest, with the RE of 2.43% and the RMSE of 0.15. （3） The inversion errors in the different sensors＇ LAI estimates using the PROSAIL model are small. The accuracy of the GF-1 is the highest with the RE of 3.44%, and the RMSE of 0.22, whereas that of the H J-1 is the lowest with the RE of 4.95%, and the RMSE of 0.26. （4） The effects of the spectral response function and radiation calibration for the different sensors are small and can be ignored, but the effects of spatial resolution are significant and must be taken into consideration in practical applications.

Detection and Adjustment of Undocumented Discontinuities in Chinese Temperature Series Using a Composite Approach

Annually averaged daily maximum and minimum surface temperatures from southeastern China were evaluated for artificial discontinuities using three different tests for undocumented changepoints. Changepoints in the time series were identified by comparing each target series to a reference calculated from values observed at a number of nearby stations. Under the assumption that no trend was present in the sequence of target-reference temperature differences, a changepoint was assigned to the target series when at least two of the three tests rejected the null hypothesis of no changepoint at approximately the same position in the difference series. Each target series then was adjusted using a procedure that accounts for discontinuities in average temperature values from nearby stations that otherwise could bias estimates of the magnitude of the target series step change. A spatial comparison of linear temperature trends in the adjusted annual temperature series suggests that major relative discontinuities were removed in the homogenization process. A greater number of relative change points were detected in annual average minimum than in average maximum temperature series. Some evidence is presented which suggests that minimum surface temperature fields may be more sensitive to changes in measurement practice than maximum temperature fields. In addition, given previous evidence of urban heat island （i.e., local） trends in this region, the assumption of no slope in a target-reference difference series is likely to be violated more frequently in minimum than in maximum temperature series. Consequently, there may be greater potential to confound trend and step changes in minimum temperature series.

Homogenized Daily Relative Humidity Series in China during 1960?2017

Surface relative humidity(RH)is a key element for weather and climate monitoring and research.However,RH is not as commonly applied in studying climate change,partly because the observation series of RH are prone to inhomogeneous biases due to non-climate changes in the observation system.A homogenized dataset of daily RH series from 746 stations in Chinese mainland for the period 1960–2017,ChinaRHv1.0,has been developed.Most(685 or 91.82%of the total)station time series were inhomogeneous with one or more break points.The major breakpoints occurred in the early 2000s for many stations,especially in the humid and semi-humid zones,due to the implementation of automated observation across the country.The inhomogeneous biases in the early manual records before this change are positive relative to the recent automatic records,for most of the biased station series.There are more break points detected by using the MASH(Multiple Analysis of Series for Homogenization)method,with biases mainly around?0.5%and 0.5%.These inhomogeneous biases are adjusted with reference to the most recent observations for each station.Based on the adjusted observations,the regional mean RH series of China shows little long-term trend during 1960–2017[0.006%(10 yr)^?1],contrasting with a false decreasing trend[?0.414%(10 yr)?1]in the raw data.It is notable that ERA5 reanalysis data match closely with the interannual variations of the raw RH series in China,including the jump in the early 2000s,raising a caveat for its application in studying climate change in the region.

Errors and Correction of Precipitation Measurements in China

In order to discover the range of various errors in Chinese precipitation measurements and seek a correction method, 30 precipitation evaluation stations were set up countrywide before 1993. All the stations are reference stations in China. To seek a correction method for wind-induced error, a precipitation correction instrument called the ＂horizontal precipitation gauge＂ was devised beforehand. Field intercomparison observations regarding 29,000 precipitation events have been conducted using one pit gauge, two elevated operational gauges and one horizontal gauge at the above 30 stations. The range of precipitation measurement errors in China is obtained by analysis of intercomparison measurement results. The distribution of random errors and systematic errors in precipitation measurements are studied in this paper. A correction method, especially for wind-induced errors, is developed. The results prove that a correlation of power function exists between the precipitation amount caught by the horizontal gauge and the absolute difference of observations implemented by the operational gauge and pit gauge. The correlation coefficient is 0.99. For operational observations, precipitation correction can be carried out only by parallel observation with a horizontal precipitation gauge. The precipitation accuracy after correction approaches that of the pit gauge. The correction method developed is simple and feasible.

Influence of the Asian-Pacific Oscillation on Spring Precipitation over Central Eastern China

The linkage between the Asian-Pacific oscillation （APO） and the precipitation over central eastern China in spring is preliminarily addressed by use of the observed data. Results show that they correlate very well, with the positive （negative） phase of APO tending to increase （decrease） the precipitation over central eastern China. Such a relationship can be explained by the atmospheric circulation changes over Asia and the North Pacific in association with the anomalous APO. A positive phase of APO, characterized by a positive anomaly over Asia and a negative anomaly over the North Pacific in the upper-tropospheric temperature, corresponds to decreased low-level geopotential height （H） and increased high-level H over Asia, and these effects are concurrent with increased low-level H and decreased high-level H over the North Pacific. Meanwhile, an anticyclonic circulation anomaly in the upper troposphere and a cyclonic circulation anomaly in the lower troposphere are introduced in East Asia, and the low-level southerly wind is strengthened over central eastern China. These changes provide advantageous conditions for enhanced precipitation over central eastern China. The situation is reversed in the negative phase of APO, leading to reduced precipitation in this region.

A New Method for Quality Control of Chinese Rawinsonde Wind Observations

In 2006,the National Meteorological Information Center （NMIC） of the China Meteorological Administration （CMA） developed its real-time quality control （QC） system of rawinsonde observations coming from the Global Telecommunications System （GTS） and established the Global Upper-air Report Dataset,which,with the NMIC B01 format,is generally referred to as the B01 dataset and updated on a daily basis.However,when the B01 dataset is applied in climate analysis,some wind errors as well as some accurate values with incorrect error marks are found.To improve the quality and usefulness of Chinese rawinsonde wind observations,a new QC method （NewQC） is proposed in this paper.Different from the QC approach used for B01 datasets,the NewQC includes two vertical-wind-shear checks to analyze the vertical consistency of winds,in which the constant height level winds are used as reference data for the QC of mandatory pressure level winds.Different threshold values are adopted in the wind shear checks for different stations and different vertical levels.Several typical examples of QC of different error types by the new algorithm are shown and its performance with respect to 1980-2008 observational data is statistically evaluated.Compared with the radiosonde QC algorithms used in both the Meteorological Assimilation Data Ingest System （MADIS,http：//madis.noaa.gov/madis_raob_qc.html） of the National Oceanic and Atmospheric Administration （NOAA） and the B01 dataset,the NewQC shows higher accuracy and better reliability,particularly when used to judge successive observation errors.