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The atmospheric carbon dioxide (CO2) 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 CO2, 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 CO2 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 CO2 by comparison with observed CO2 at the sites of Mauna Loa and Barrow, and the Greenhouse Gases Observing Satellite (GOSAT) CO2 product. The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO2 during the period 1850–2014, and in capturing the seasonal cycle of CO2 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. [ABSTRACT FROM AUTHOR]

Mathematical modeling of the interaction between solar radiation and the Earth's atmosphere is formalized by the radiative transfer equation (RTE), whose resolution calls for two-stream approximations among other methods. This paper proposes a new two-stream approximation of the RTE with the development of the phase function and the intensity into a third-order series of Legendre polynomials. This new approach, which adds one more term in the expression of the intensity and the phase function, allows in the conditions of a plane parallel atmosphere a new mathematical formulation of γ parameters. It is then compared to the Eddington, Hemispheric Constant, Quadrature, Combined Delta Function and Modified Eddington, and second-order approximation methods with reference to the Discrete Ordinate (Disort) method (δ–128 streams), considered as the most precise. This work also determines the conversion function of the proposed New Method using the fundamental definition of two-stream approximation (F-TSA) developed in a previous work. Notably, New Method has generally better precision compared to the second-order approximation and Hemispheric Constant methods. Compared to the Quadrature and Eddington methods, New Method shows very good precision for wide domains of the zenith angle μ0, but tends to deviate from the Disort method with the zenith angle, especially for high values of optical thickness. In spite of this divergence in reflectance for high values of optical thickness, very strong correlation with the Disort method (R ≈ 1) was obtained for most cases of optical thickness in this study. An analysis of the Legendre polynomial series for simple functions shows that the high precision is due to the fact that the approximated functions ameliorate the accuracy when the order of approximation increases, although it has been proven that there is a limit order depending on the function from which the precision is lost. This observation indicates that increasing the order of approximation of the phase function of the RTE leads to a better precision in flux calculations. However, this approach may be limited to a certain order that has not been studied in this paper. [ABSTRACT FROM AUTHOR]

Thunderstorm gusts are a common form of severe convective weather in the warm season in North China, and it is of great importance to correctly forecast them. At present, the forecasting of thunderstorm gusts is mainly based on traditional subjective methods, which fails to achieve high-resolution and high-frequency gridded forecasts based on multiple observation sources. In this paper, we propose a deep learning method called Thunderstorm Gusts TransU-net (TG-TransUnet) to forecast thunderstorm gusts in North China based on multi-source gridded product data from the Institute of Urban Meteorology (IUM) with a lead time of 1 to 6 h. To determine the specific range of thunderstorm gusts, we combine three meteorological variables: radar reflectivity factor, lightning location, and 1-h maximum instantaneous wind speed from automatic weather stations (AWSs), and obtain a reasonable ground truth of thunderstorm gusts. Then, we transform the forecasting problem into an image-to-image problem in deep learning under the TG-TransUnet architecture, which is based on convolutional neural networks and a transformer. The analysis and forecast data of the enriched multi-source gridded comprehensive forecasting system for the period 2021–23 are then used as training, validation, and testing datasets. Finally, the performance of TG-TransUnet is compared with other methods. The results show that TG-TransUnet has the best prediction results at 1–6 h. The IUM is currently using this model to support the forecasting of thunderstorm gusts in North China. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper investigates the homogeneity of United States aircraft reconnaissance data and the impact of these data on the homogeneity of the tropical cyclone (TC) best track data for the seasons 1949–1987 generated by the China Meteorological Administration (CMA). The evaluation of the reconnaissance data shows that the minimum central sea level pressure (MCP) data are relatively homogeneous, whereas the maximum sustained wind (MSW) data show both overestimations and spurious abrupt changes. Statistical comparisons suggest that both the reconnaissance MCP and MSW were well incorporated into the CMA TC best track dataset. Although no spurious abrupt changes were evident in the reconnaissance-related best track MCP data, two spurious changepoints were identified in the remainder of the best-track MCP data. Furthermore, the influence of the reconnaissance MSWs seems to extend to the best track MSWs unrelated to reconnaissance, which might reflect the optimistic confidence in making higher estimates due to the overestimated extreme wind "observations". In addition, the overestimation of either the reconnaissance MSWs or the best track MSWs was greater during the early decades compared to later decades, which reflects the important influence of reconnaissance data on the CMA TC best track dataset. The wind–pressure relationship (WPR) used in the CMA TC best track dataset is also evaluated and is found to overestimate the MSW, which may lead to inhomogeneity within the dataset between the aircraft reconnaissance era and the satellite era. [ABSTRACT FROM AUTHOR]

This paper studied a snow event over North China on 21 February 2017, using aircraft in-situ data, a Lagrangian analysis tool, and WRF simulations with different microphysical schemes to investigate the supercooled layer of warm conveyor belts (WCBs). Based on the aircraft data, we found a fine vertical structure within clouds in the WCB and highlighted a 1–2 km thin supercooled liquid water layer with a maximum Liquid Water Content (LWC) exceeding 0.5 g kg−1 during the vertical aircraft observation. Although the main features of thermodynamic profiles were essentially captured by both modeling schemes, the microphysical quantities exhibited large diversity with different microphysics schemes. The conventional Morrison two-moment scheme showed remarkable agreement with in-situ observations, both in terms of the thermodynamic structure and the supercooled liquid water layer. However, the microphysical structure of the WCB clouds, in terms of LWC and IWC, was not apparent in HUJI fast bin scheme. To reduce such uncertainty, future work may focus on improving the representation of microphysics in bin schemes with in-situ data and using similar assumptions for all schemes to isolate the impact of physics. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a crucial variable in the terrestrial water, carbon, and energy cycles. At present, a large number of multisource ET products exist. Due to sparse observations, however, great challenges exist in the evaluation and integration of ET products in remote and complex areas such as the Tibetan Plateau (TP). In this paper, the applicability of the multiple collocation (MC) method over the TP is evaluated for the first time, and the uncertainty of multisource ET products (based on reanalysis, remote sensing, and land surface models) is further analyzed, which provides a theoretical basis for ET data fusion. The results show that 1) ET uncertainties quantified via the MC method are lower in RS-based ET products (5.95 vs. 7.06 mm month−1) than in LSM ET products (10.22 vs. 17.97 mm month−1) and reanalysis ET estimates (7.27 vs. 12.26 mm month−1). 2) A multisource evapotranspiration (MET) dataset is generated at a monthly temporal scale with a spatial resolution of 0.25° across the TP during 2005–15. MET has better performance than any individual product. 3) Based on the fusion product, the total ET amount over the TP and its patterns of spatiotemporal variability are clearly identified. The annual total ET over the entire TP is approximately 380.60 mm. Additionally, an increasing trend of 1.59±0.85 mm yr−1 over the TP is shown during 2005–15. This study provides a basis for future studies on water and energy cycles and water resource management over the TP and surrounding regions. [ABSTRACT FROM AUTHOR]

Based on the TRMM dataset, this paper compares the applicability of the improved MCE (minimum circumscribed ellipse), MBR (minimum bounding rectangle), and DIA (direct indexing area) methods for rain cell fitting. These three methods can reflect the geometric characteristics of clouds and apply geometric parameters to estimate the real dimensions of rain cells. The MCE method shows a major advantage in identifying the circumference of rain cells. The circumference of rain cells identified by MCE in most samples is smaller than that identified by DIA and MBR, and more similar to the observed rain cells. The area of rain cells identified by MBR is relatively robust. For rain cells composed of many pixels (N > 20), the overall performance is better than that of MCE, but the contribution of MBR to the best identification results, which have the shortest circumference and the smallest area, is less than that of MCE. The DIA method is best suited to small rain cells with a circumference of less than 100 km and an area of less than 120 km2, but the overall performance is mediocre. The MCE method tends to achieve the highest success at any angle, whereas there are fewer "best identification" results from DIA or MBR and more of the worst ones in the along-track direction and cross-track direction. Through this comprehensive comparison, we conclude that MCE can obtain the best fitting results with the shortest circumference and the smallest area on behalf of the high filling effect for all sizes of rain cells. [ABSTRACT FROM AUTHOR]

Climate change is expected to have long-term impacts on drought and wildfire risks in Oregon as summers continue to become warmer and drier. This paper investigates the projected changes in drought characteristics and drought propagation in the Umatilla River Basin in northeastern Oregon for mid-century (2030–2059) and late-century (2070–2099) climate scenarios. Drought characteristics for projected climates were determined using downscaled CMIP5 climate datasets from ten climate models and Soil and Water Assessment Tool to simulate effects on hydrologic processes. Short-term (three months) drought characteristics (frequency, duration, and severity) were analyzed using four drought indices, including the Standardized Precipitation Index (SPI-3), Standardized Precipitation-Evapotranspiration Index (SPEI-3), Standardized Streamflow Index (SSI-3), and the Standardized Soil Moisture Index (SSMI-3). Results indicate that short-term meteorological droughts are projected to become more prevalent, with up to a 20% increase in the frequency of SPI-3 drought events. Short-term hydrological droughts are projected to become more frequent (average increase of 11% in frequency of SSI-3 drought events), more severe, and longer in duration (average increase of 8% for short-term droughts). Similarly, short-term agricultural droughts are projected to become more frequent (average increase of 28% in frequency of SSMI-3 drought events) but slightly shorter in duration (average decrease of 4%) in the future. Historically, drought propagation time from meteorological to hydrological drought is shorter than from meteorological to agricultural drought in most sub-basins. For the projected climate scenarios, the decrease in drought propagation time will likely stress the timing and capacity of water supply in the basin for irrigation and other uses. [ABSTRACT FROM AUTHOR]

Atmospheric chemistry research has been growing rapidly in China in the last 25 years since the concept of the "air pollution complex" was first proposed by Professor Xiaoyan TANG in 1997. For papers published in 2021 on air pollution (only papers included in the Web of Science Core Collection database were considered), more than 24 000 papers were authored or co-authored by scientists working in China. In this paper, we review a limited number of representative and significant studies on atmospheric chemistry in China in the last few years, including studies on (1) sources and emission inventories, (2) atmospheric chemical processes, (3) interactions of air pollution with meteorology, weather and climate, (4) interactions between the biosphere and atmosphere, and (5) data assimilation. The intention was not to provide a complete review of all progress made in the last few years, but rather to serve as a starting point for learning more about atmospheric chemistry research in China. The advances reviewed in this paper have enabled a theoretical framework for the air pollution complex to be established, provided robust scientific support to highly successful air pollution control policies in China, and created great opportunities in education, training, and career development for many graduate students and young scientists. This paper further highlights that developing and low-income countries that are heavily affected by air pollution can benefit from these research advances, whilst at the same time acknowledging that many challenges and opportunities still remain in atmospheric chemistry research in China, to hopefully be addressed over the next few decades. [ABSTRACT FROM AUTHOR]

Existing studies contend that latent heating (LH) will replace sensible heating (SH) to become the dominant factor affecting the development of the Tibetan Plateau vortex (TPV) after it moves off the Tibetan Plateau (TP). However, in the process of the TPV moving off the TP requires that the airmass traverse the eastern slope of the Tibetan Plateau (ESTP) where the topography and diabatic heating (DH) conditions rapidly change. How LH gradually replaces SH to become the dominant factor in the development of the TPV over the ESTP is still not very clear. In this paper, an analysis of a typical case of a TPV with a long life history over the ESTP is performed by using multi-sourced meteorological data and model simulations. The results show that SH from the TP surface can change the TPV-associated precipitation distribution by temperature advection after the TPV moves off the TP. The LH can then directly promote the development of the TPV and has a certain guiding effect on the track of the TPV. The SH can control the active area of LH by changing the falling area of the TPV-associated precipitation, so it still plays a key role in the development and tracking of the TPV even though it has moved out of the main body of the TP. [ABSTRACT FROM AUTHOR]

This paper provides a systematic evaluation of the ability of 12 Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate the spatial inhomogeneity of the atmospheric carbon dioxide (CO2) concentration. The multi-model ensemble mean (MME) can reasonably simulate the increasing trend of CO2 concentration from 1850 to 2014, compared with the observation data from the Scripps CO2 Program and CMIP6 prescribed data, and improves upon the CMIP5 MME CO2 concentration (which is overestimated after 1950). The growth rate of CO2 concentration in the northern hemisphere (NH) is higher than that in the southern hemisphere (SH), with the highest growth rate in the mid-latitudes of the NH. The MME can also reasonably simulate the seasonal amplitude of CO2 concentration, which is larger in the NH than in the SH and grows in amplitude after the 1950s (especially in the NH). Although the results of the MME are reasonable, there is a large spread among ESMs, and the difference between the ESMs increases with time. The MME results show that regions with relatively large CO2 concentrations (such as northern Russia, eastern China, Southeast Asia, the eastern United States, northern South America, and southern Africa) have greater seasonal variability and also exhibit a larger inter-model spread. Compared with CMIP5, the CMIP6 MME simulates an average spatial distribution of CO2 concentration that is much closer to the site observations, but the CMIP6-inter-model spread is larger. The inter-model differences of the annual means and seasonal cycles of atmospheric CO2 concentration are both attributed to the differences in natural sources and sinks of CO2 between the simulations. [ABSTRACT FROM AUTHOR]

Variability in the East Asian summer monsoon (EASM) brings the risk of heavy flooding or drought to the Yangtze River basin, with potentially devastating impacts. Early forecasts of the likelihood of enhanced or reduced monsoon rainfall can enable better management of water and hydropower resources by decision-makers, supporting livelihoods and major economic and population centres across eastern China. This paper demonstrates that the EASM is predictable in a dynamical forecast model from the preceding November, and that this allows skilful forecasts of summer mean rainfall in the Yangtze River basin at a lead time of six months. The skill for May–June–July rainfall is of a similar magnitude to seasonal forecasts initialised in spring, although the skill in June–July–August is much weaker and not consistently significant. However, there is some evidence for enhanced skill following El Niño events. The potential for decadal-scale variability in forecast skill is also examined, although we find no evidence for significant variation. [ABSTRACT FROM AUTHOR]

In recent years, China has implemented several measures to improve air quality. The Beijing-Tianjin-Hebei (BTH) region is one area that has suffered from the most serious air pollution in China and has undergone huge changes in air quality in the past few years. How to scientifically assess these change processes remain the key issue in further improving the air quality over this region in the future. To evaluate the changes in major air pollutant emissions over this region, this paper employs ensemble Kalman filtering (EnKF) for integrating the national ground monitoring pollutant observation data and the Nested Air Quality Prediction Modeling System (NAQPMS) simulation data to inversely estimate the emission rates of SO2, NOX, CO, and primary PM2.5 over BTH region in February from 2014 to 2019. The results show that SO2, NOX, CO, and primary PM2.5 emissions in the BTH region decreased in February from 2014 to 2019 by 83%, 37%, 41%, and 42%, while decreases in Beijing during this period were 86%, 67%, 59%, and 65%, respectively. Compared with the prior emission inventory, the inversion emission inventory reduces the uncertainty of multi-pollutant simulation in the BTH region, with simulated root mean square errors of the monthly average concentrations of SO2, NOX, PM2.5, and CO reduced by 41%, 30%, 31%, and 22%, respectively. The average uncertainties of SO2, NOX, PM2.5, and CO inversion emissions in 2014–19 are ±14.03% yr−1, ±28.91% yr−1, ±126.15% yr−1, and ±43.58% yr−1. Compared with the uncertainty of MEIC emission, the uncertainties of all species changed by +2% yr−1, −2% yr−1, −26% yr−1, and −4% yr−1, respectively. The spatial distribution results illustrate that air pollutant emissions are mainly distributed over the eastern and southern BTH regions. The spatial gap between the inversion emissions and MEIC emissions was further closed in 2019 compared to 2014. The results of this paper can provide a new reference for assessing changes in air pollution emissions over the BTH region in recent years and validating a bottom-up emission inventory. [ABSTRACT FROM AUTHOR]

The outputs of the Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System (FGOALS-f3-L) model for the decadal climate prediction project (DCPP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) are described in this paper. The FGOALS-f3-L was initialized through the upgraded, weakly coupled data assimilation scheme, referred to as EnOI-IAU, which assimilates observational anomalies of sea surface temperature (SST) and upper-level (0–1000-m) ocean temperature and salinity profiles into the coupled model. Then, nine ensemble members of 10-year hindcast/forecast experiments were conducted for each initial year over the period of 1960–2021, based on initial conditions produced by three initialization experiments. The hindcast and forecast experiments follow the experiment designs of the Component-A and Component-B of the DCPP, respectively. The decadal prediction output datasets contain a total of 44 monthly mean atmospheric and oceanic variables. The preliminary evaluation indicates that the hindcast experiments show significant predictive skill for the interannual variations of SST in the north Pacific and multi-year variations of SST in the subtropical Pacific and the southern Indian Ocean. [ABSTRACT FROM AUTHOR]

Seamless prediction is a weather–climate integrated prediction covering multiple time scales that include days, weeks, months, seasons, years, and decades. Seamless prediction can provide different industries with information such as weather conditions and climate variations from the next few days to years, which have important impacts on economic and social development and important reference value for short-, medium- and long-term decision-making and planning of the country. Therefore, seamless prediction has received widespread attention from the international scientific community recently. As Chinese scientists have also carried out relevant research, this paper reviews the research in China on developments and applications of seamless prediction methods and prediction systems in recent years. Among them, the main progress of seamless prediction methods studies is reviewed from four aspects: short- and medium-range weather forecasting, subseasonal-to-seasonal, seasonal-to-interannual, and decadal climate prediction. In terms of development and application of seamless prediction systems, the main achievements made by meteorological operational departments, scientific institutes, and universities in China in recent years are reviewed. Finally, some of the issues in seamless prediction that need further study are discussed. [ABSTRACT FROM AUTHOR]

The influences of human activity on regional climate over China have been widely reported and drawn great attention from both the scientific community and governments. This paper reviews the evidence of the anthropogenic influence on regional climate over China from the perspectives of surface air temperature (SAT), precipitation, droughts, and surface wind speed, based on studies published since 2018. The reviewed evidence indicates that human activities, including greenhouse gas and anthropogenic aerosol emissions, land use and cover change, urbanization, and anthropogenic heat release, have contributed to changes in the SAT trend and the likelihood of regional record-breaking extreme high/low temperature events over China. The anthropogenically forced SAT signal can be detected back to the 1870s in the southeastern Tibetan Plateau region. Although the anthropogenic signal of summer precipitation over China is detectable and anthropogenic forcing has contributed to an increased likelihood of regional record-breaking heavy/low precipitation events, the anthropogenic precipitation signal over China is relatively obscure. Moreover, human activities have also contributed to a decline in surface wind speed, weakening of monsoon precipitation, and an increase in the frequency of droughts and compound extreme climate/weather events over China in recent decades. This review can serve as a reference both for further understanding the causes of regional climate changes over China and for sound decision-making on regional climate mitigation and adaptation. Additionally, a few key or challenging scientific issues associated with the human influence on regional climate changes are discussed in the context of future research. [ABSTRACT FROM AUTHOR]

Studies of the multi-scale climate variability of the Asian monsoon are essential to an advanced understanding of the physical processes of the global climate system. In this paper, the progress achieved in this field is systematically reviewed, with a focus on the past several years. The achievements are summarized into the following topics: (1) the onset of the South China Sea summer monsoon; (2) the East Asian summer monsoon; (3) the East Asian winter monsoon; and (4) the Indian summer monsoon. Specifically, new results are highlighted, including the advanced or delayed local monsoon onset tending to be synchronized over the Arabian Sea, Bay of Bengal, Indochina Peninsula, and South China Sea; the basic features of the record-breaking mei-yu in 2020, which have been extensively investigated with an emphasis on the role of multi-scale processes; the recovery of the East Asian winter monsoon intensity after the early 2000s in the presence of continuing greenhouse gas emissions, which is believed to have been dominated by internal climate variability (mostly the Arctic Oscillation); and the accelerated warming over South Asia, which exceeded the tropical Indian Ocean warming, is considered to be the main driver of the Indian summer monsoon rainfall recovery since 1999. A brief summary is provided in the final section along with some further discussion on future research directions regarding our understanding of the Asian monsoon variability. [ABSTRACT FROM AUTHOR]

During the recent four decades since 1980, a series of modern climate satellites were launched, allowing for the measurement and record-keeping of multiple climate parameters, especially over the polar regions where traditional observations are difficult to obtain. China has been actively engaging in polar expeditions. Many observations were conducted during this period, accompanied by improved Earth climate models, leading to a series of insightful understandings concerning Arctic and Antarctic climate changes. Here, we review the recent progress China has made concerning Arctic and Antarctic climate change research over the past decade. The Arctic temperature increase is much higher than the global-mean warming rate, associated with a rapid decline in sea ice, a phenomenon called the Arctic Amplification. The Antarctic climate changes showed a zonally asymmetric pattern over the past four decades, with most of the fastest changes occurring over West Antarctica and the Antarctic Peninsula. The Arctic and Antarctic climate changes were driven by anthropogenic greenhouse gas emissions and ozone loss, while tropical-polar teleconnections play important roles in driving the regional climate changes and extreme events over the polar regions. Polar climate changes may also feedback to the entire Earth climate system. The adjustment of the circulation in both the troposphere and the stratosphere contributed to the interactions between the polar climate changes and lower latitudes. Climate change has also driven rapid Arctic and Southern ocean acidification. Chinese researchers have made a series of advances in understanding these processes, as reviewed in this paper. [ABSTRACT FROM AUTHOR]

Atmospheric electricity is composed of a series of electric phenomena in the atmosphere. Significant advances in atmospheric electricity research conducted in China have been achieved in recent years. In this paper, the research progress on atmospheric electricity achieved in China during 2019–22 is reviewed focusing on the following aspects: (1) lightning detection and location techniques, (2) thunderstorm electricity, (3) lightning forecasting methods and techniques, (4) physical processes of lightning discharge, (5) high energy emissions and effects of thunderstorms on the upper atmosphere, and (6) the effect of aerosol on lightning. [ABSTRACT FROM AUTHOR]

In this paper, we describe and analyze two datasets entitled "Homogenised monthly and daily temperature and precipitation time series in China during 1960–2021" and "Homogenised monthly and daily temperature and precipitation time series in Greece during 1960–2010". These datasets provide the homogenised monthly and daily mean (TG), minimum (TN), and maximum (TX) temperature and precipitation (RR) records since 1960 at 366 stations in China and 56 stations in Greece. The datasets are available at the Science Data Bank repository and can be downloaded from https://doi.org/10.57760/sciencedb.01731 and https://doi.org/10.57760/sciencedb.01720. For China, the regional mean annual TG, TX, TN, and RR series during 1960–2021 showed significant warming or increasing trends of 0.27°C (10 yr)−1, 0.22°C (10 yr)−1, 0.35°C (10 yr)−1, and 6.81 mm (10 yr)−1, respectively. Most of the seasonal series revealed trends significant at the 0.05 level, except for the spring, summer, and autumn RR series. For Greece, there were increasing trends of 0.09°C (10 yr)−1, 0.08°C (10 yr)−1, and 0.11°C (10 yr)−1 for the annual TG, TX, and TN series, respectively, while a decreasing trend of −23.35 mm (10 yr)−1 was present for RR. The seasonal trends showed a significant warming rate for summer, but no significant changes were noted for spring (except for TN), autumn, and winter. For RR, only the winter time series displayed a statistically significant and robust trend [−15.82 mm (10 yr)−1]. The final homogenised temperature and precipitation time series for both China and Greece provide a better representation of the large-scale pattern of climate change over the past decades and provide a quality information source for climatological analyses. [ABSTRACT FROM AUTHOR]

Convolutional neural networks (CNNs) have been widely studied and found to obtain favorable results in statistical downscaling to derive high-resolution climate variables from large-scale coarse general circulation models (GCMs). However, there is a lack of research exploring the predictor selection for CNN modeling. This paper presents an effective and efficient greedy elimination algorithm to address this problem. The algorithm has three main steps: predictor importance attribution, predictor removal, and CNN retraining, which are performed sequentially and iteratively. The importance of individual predictors is measured by a gradient-based importance metric computed by a CNN backpropagation technique, which was initially proposed for CNN interpretation. The algorithm is tested on the CNN-based statistical downscaling of monthly precipitation with 20 candidate predictors and compared with a correlation analysis-based approach. Linear models are implemented as benchmarks. The experiments illustrate that the predictor selection solution can reduce the number of input predictors by more than half, improve the accuracy of both linear and CNN models, and outperform the correlation analysis method. Although the RMSE (root-mean-square error) is reduced by only 0.8%, only 9 out of 20 predictors are used to build the CNN, and the FLOPs (Floating Point Operations) decrease by 20.4%. The results imply that the algorithm can find subset predictors that correlate more to the monthly precipitation of the target area and seasons in a nonlinear way. It is worth mentioning that the algorithm is compatible with other CNN models with stacked variables as input and has the potential for nonlinear correlation predictor selection. [ABSTRACT FROM AUTHOR]

In this paper, the evolution of the microphysical characteristics in different regions (eyewall, inner core, and outer rainbands) and different quadrants [downshear left (DL), downshear right (DR), upshear left (UL), and upshear right (UR)] during the final landfall of Typhoon Ewiniar (2018) is analyzed using two-dimensional video disdrometer and S-band polarimetric radar data collected in Guangdong, China. Due to the different types of underlying surfaces, the periods before landfall (mainly dominated by underlying sea surface) and after landfall (mainly dominated by underlying land surface) are also analyzed. Both before landfall and after landfall, the downshear quadrants had the dominate typhoon precipitation. The outer rainbands had more graupel than the inner core, resulting in a larger radar reflectivity, differential reflectivity, specific differential phase shift, and mass-weighted mean diameter below the melting layer. Compared with other regions, the eyewall region had the smallest mean logarithmic normalized intercept parameter before landfall and the smallest mean mass-weighted mean diameter and the largest mean logarithmic normalized intercept parameter after landfall. The hydrometeor size sorting was obvious in the eyewall and inner core (especially in the eyewall) after landfall. A high concentration of large raindrops fell in the DL quadrant, and more small raindrops fell in the UR quadrant. Although the ice-phase process and warm rain process were both important in the formation of tropical cyclone precipitation, the warm rain process (ice-phase process) contributed more liquid water before landfall (after landfall). This investigation provides a reference for improving the microphysical parameterization scheme in numerical models. [ABSTRACT FROM AUTHOR]

Ensemble forecasting systems have become an important tool for estimating the uncertainties in initial conditions and model formulations and they are receiving increased attention from various applications. The Regional Ensemble Prediction System (REPS), which has operated at the Beijing Meteorological Service (BMS) since 2017, allows for probabilistic forecasts. However, it still suffers from systematic deficiencies during the first couple of forecast hours. This paper presents an integrated probabilistic nowcasting ensemble prediction system (NEPS) that is constructed by applying a mixed dynamic-integrated method. It essentially combines the uncertainty information (i.e., ensemble variance) provided by the REPS with the nowcasting method provided by the rapid-refresh deterministic nowcasting prediction system (NPS) that has operated at the Beijing Meteorological Service (BMS) since 2019. The NEPS provides hourly updated analyses and probabilistic forecasts in the nowcasting and short range (0–6 h) with a spatial grid spacing of 500 m. It covers the three meteorological parameters: temperature, wind, and precipitation. The outcome of an evaluation experiment over the deterministic and probabilistic forecasts indicates that the NEPS outperforms the REPS and NPS in terms of surface weather variables. Analysis of two cases demonstrates the superior reliability of the NEPS and suggests that the NEPS gives more details about the spatial intensity and distribution of the meteorological parameters. [ABSTRACT FROM AUTHOR]

Precipitation detection is an essential step in radiance assimilation because the uncertainties in precipitation would affect the radiative transfer calculation and observation errors. The traditional precipitation detection method for microwave only detects clouds and precipitation horizontally, without considering the three-dimensional distribution of clouds. Extending precipitation detection from 2D to 3D is expected to bring more useful information to the data assimilation without using the all-sky approach. In this study, the 3D precipitation detection method is adopted to assimilate Microwave Temperature Sounder-2 (MWTS-II) onboard the Fengyun-3D, which can dynamically detect the channels above precipitating clouds by considering the near-real-time cloud parameters. Cycling data assimilation and forecasting experiments for Typhoons Lekima (2019) and Mitag (2019) are carried out. Compared with the control experiment, the quantity of assimilated data with the 3D precipitation detection increases by approximately 23%. The quality of the additional MWTS-II radiance data is close to the clear-sky data. The case studies show that the average root-mean-square errors (RMSE) of prognostic variables are reduced by 1.7% in the upper troposphere, leading to an average reduction of 4.53% in typhoon track forecasts. The detailed diagnoses of Typhoon Lekima (2019) further show that the additional MWTS-II radiances brought by the 3D precipitation detection facilitate portraying a more reasonable circulation situation, thus providing more precise structures. This paper preliminarily proves that 3D precipitation detection has potential added value for increasing satellite data utilization and improving typhoon forecasts. [ABSTRACT FROM AUTHOR]

In this paper, we first review the research advancements in blocking dynamics and highlight the merits and drawbacks of the previous theories of atmospheric blocking. Then, the dynamical mechanisms of atmospheric blocking are presented based on a nonlinear multi-scale interaction (NMI) model. Previous studies suggested that the eddy deformation (e.g., eddy straining, wave breaking, and eddy merging) might lead to the formation and maintenance of atmospheric blocking. However, the results were speculative and problematic because the previous studies, based on the time-mean eddy-mean flow interaction model, cannot identify the causal relationship between the evolution of atmospheric blocking and the eddy deformation. Based on the NMI model, we indicate that the onset, growth, maintenance, and decay of atmospheric blocking is mainly produced by the spatiotemporal evolution of pre-existing upstream synoptic-scale eddies, whereas the eddy deformation is a concomitant phenomenon of the blocking formation. The lifetime of blocking is mainly determined by the meridional background potential vorticity gradient (PVy) because a small PVy favors weak energy dispersion and strong nonlinearity to sustain the blocking. But the zonal movement of atmospheric blocking is associated with the background westerly wind, PVy, and the blocking amplitude. Using this NMI model, a bridge from the climate change to sub-seasonal atmospheric blocking and weather extremes might be established via examining the effect of climate change on PVy. Thus, it is expected that using the NMI model to explore the dynamics of atmospheric blocking and its change is a new direction in the future. [ABSTRACT FROM AUTHOR]

An extremely heavy rainfall event occurred in Zhengzhou, China, on 20 July 2021 and produced an hourly rainfall rate of 201.9 mm, which broke the station record for mainland China. Based on radar observations and a convection-permitting simulation using the WRF-ARW model, this paper investigates the multiscale processes, especially those at the mesoscale, that support the extreme observed hourly rainfall. Results show that the extreme rainfall occurred in an environment characteristic of warm-sector heavy rainfall, with abundant warm moist air transported from the ocean by an abnormally northward-displaced western Pacific subtropical high and Typhoon In-Fa (2021). However, rather than through back building and echo training of convective cells often found in warm-sector heavy rainfall events, this extreme hourly rainfall event was caused by a single, quasi-stationary storm in Zhengzhou. Scale separation analysis reveals that the extreme-rain-producing storm was supported and maintained by the dynamic lifting of low-level converging flows from the north, south, and east of the storm. The low-level northerly flow originated from a mesoscale barrier jet on the eastern slope of the Taihang Mountain due to terrain blocking of large-scale easterly flows, which reached an overall balance with the southerly winds in association with a low-level meso-β-scale vortex located to the west of Zhengzhou. The large-scale easterly inflows that fed the deep convection via transport of thermodynamically unstable air into the storm prevented the eastward propagation of the weak, shallow cold pool. As a result, the convective storm was nearly stationary over Zhengzhou, resulting in record-breaking hourly precipitation. [ABSTRACT FROM AUTHOR]

In weather sciences, the two specific terms "storm" and "cyclone" frequently appear in literature and usually refer to the violent nature of a number of weather systems characterized by central low pressure, strong winds, large precipitation amounts in the form of rain, freezing rain, or snow, as well as thunder and lightning. But what is the connection between these two specific terms? In this paper, the historic evolutions of the terms "storm" and "cyclone" are reviewed from the perspective of weather science. The earliest recorded storms in world history are also briefly introduced. Then, the origin of the term "meteorological bomb", which is the nickname of the "explosive cyclone" is introduced. Later, the various definitions of explosive cyclones given by several researchers are discussed. Also, the climatological features of explosive cyclones, as well as the future trends of explosive cyclones under global climate change, are discussed. [ABSTRACT FROM AUTHOR]

In this paper, a statistical method called Generalized Equilibrium Feedback Analysis (GEFA) is used to investigate the responses of the North Pacific Storm Track (NPST) in the cold season to the multi-scale oceanic variations of the Kuroshio Extension (KE) system, including its large-scale variation, oceanic front meridional shift, and mesoscale eddy activity. Results show that in the cold season from the lower to the upper troposphere, the KE large-scale variation significantly weakens the storm track activity over the central North Pacific south of 30°N. The northward shift of the KE front significantly strengthens the storm track activity over the western and central North Pacific south of 40°N, resulting in a southward shift of the NPST. In contrast, the NPST response to KE mesoscale eddy activity is not so significant and relatively shallow, which only shows some significant positive signals near the dateline in the lower and middle troposphere. Furthermore, it is found that baroclinicity and baroclinic energy conversion play an important role in the formation of the NPST response to the KE multi-scale oceanic variations. [ABSTRACT FROM AUTHOR]

Forecasting tropical cyclone track and intensity is a great challenge for the meteorological community, and safeguarding the life and property of people living near the coast is an important issue. One major reason for challenging forecasts is the lack of observations over the vast oceans. During tropical cyclone Mulan between 8 and 10 August 2022 over the northern part of the South China Sea, the meteorological authority and research institutes of Chinese mainland collaborated with the meteorological service in Hong Kong on conducting the first-ever ground-space-sky observing system experiment on tropical cyclone Mulan. The enhanced targeted observations collected during the experiment include Geostationary Interferometric Infrared Sounder, round-trip radiosondes, and aircraft-launched dropsondes. This paper describes the campaign, technical details of the meteorological models used, and impact of the additional targeted observation data on the tropical cyclone forecast. Ideally, similar enhanced observation campaigns could be conducted in the future, not only in the northern part of the South China Sea, but also in other ocean basins. [ABSTRACT FROM AUTHOR]

Landfalling typhoons can cause disasters over large regions. The government and emergency responders need to take measures to mitigate disasters according to the forecast of landfall position, while slight timing error can be ignored. The reliability of operational model forecasts of typhoon landfall position needs to be evaluated beforehand, according to the forecasts and observation of historical cases. In the evaluation of landfalling typhoon track, the traditional method based on point-to-point matching methods could be influenced by the predicted typhoon translation speed. Consequently, the traditional track evaluation method may result in a large track error even if the predicted landfall position is close to observation. The purpose of this paper is to address the above issue using a simple evaluation method of landfalling typhoon track forecast based on the time neighborhood approach. In this new method, the timing error was lessened to highlight the importance of the position error during the landfall of typhoon. The properties of the time neighborhood method are compared with the traditional method based on numerical forecast results of 12 landfalling typhoon cases. Results demonstrated that the new method is not sensitive to the sampling frequency, and that the difference between the time neighborhood and traditional method will be more obvious when the moving speed of typhoon is moderate (between 15–30 km h−1). The time neighborhood concept can be easily extended to a broader context when one attempts to examine the position error more than the timing error. [ABSTRACT FROM AUTHOR]

In this paper, a scheme of dual-Doppler radar wind analysis based on a three-dimensional variational method is proposed and performed in two steps. First, the horizontal wind field is simultaneously recovered through minimizing a cost function defined as a radial observation term with the standard conjugate gradient method, avoiding a weighting parameter specification step. Compared with conventional dual-Doppler wind synthesis approaches, this variational method minimizes errors caused by interpolation from radar observation to analysis grid in the iterative solution process, which is one of the main sources of errors. Then, through the accelerated Liebmann method, the vertical velocity is further re-estimated as an extra step by solving the Poisson equation with impermeable conditions imposed at the ground and near the tropopause. The Poisson equation defined by the second derivative of the vertical velocity is derived from the mass continuity equation. Compared with the method proposed by O'Brien, this method is less sensitive to the uncertainty of the boundary conditions and has better stability and reliability. Furthermore, the method proposed in this paper is applied to Doppler radar observation of a squall line process. It is shown that the retrieved vertical wind profile agrees well with the vertical profile obtained with the velocity—azimuth display (VAD) method, and the retrieved radial velocity as well as the analyzed positive and negative velocity centers and horizontal wind shear of the squall line are in accord with radar observations. There is a good correspondence between the divergence field of the derived wind field and the vertical velocity. And, the horizontal and vertical circulations within and around the squall line, as well as strong updrafts, the associated downdrafts, and associated rear inflow of the bow echo, are analyzed well. It is worth mentioning that the variational method in this paper can be applied to simultaneously synthesize the three-dimensional wind field from multiple-Doppler radar observations. [ABSTRACT FROM AUTHOR]

Landfalling typhoons can cause disasters over large regions. The government and emergency responders need to take measures to mitigate disasters according to the forecast of landfall position, while slight timing error can be ignored. The reliability of operational model forecasts of typhoon landfall position needs to be evaluated beforehand, according to the forecasts and observation of historical cases. In the evaluation of landfalling typhoon track, the traditional method based on point-to-point matching methods could be influenced by the predicted typhoon translation speed. Consequently, the traditional track evaluation method may result in a large track error even if the predicted landfall position is close to observation. The purpose of this paper is to address the above issue using a simple evaluation method of landfalling typhoon track forecast based on the time neighborhood approach. In this new method, the timing error was lessened to highlight the importance of the position error during the landfall of typhoon. The properties of the time neighborhood method are compared with the traditional method based on numerical forecast results of 12 landfalling typhoon cases. Results demonstrated that the new method is not sensitive to the sampling frequency, and that the difference between the time neighborhood and traditional method will be more obvious when the moving speed of typhoon is moderate (between 15–30 km h−1). The time neighborhood concept can be easily extended to a broader context when one attempts to examine the position error more than the timing error. [ABSTRACT FROM AUTHOR]

China's first carbon dioxide (CO2) measurement satellite mission, TanSat, was launched in December 2016. This paper introduces the first attempt to detect anthropogenic CO2 emission signatures using CO2 observations from TanSat and NO2 measurements from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (S5P) satellite. We focus our analysis on two selected cases in Tangshan, China and Tokyo, Japan. We found that the TanSat XCO2 measurements have the capability to capture the anthropogenic variations in the plume and have spatial patterns similar to that of the TROPOMI NO2 observations. The linear fit between TanSat XCO2 and TROPOMI NO2 indicates the CO2-to-NO2 ratio of 0.8 × 10−16 ppm (molec cm−2)−1 in Tangshan and 2.3 × 10−16 ppm (molec cm−2)−1 in Tokyo. Our results align with the CO2-to-NOx emission ratios obtained from the EDGAR v6 emission inventory. [ABSTRACT FROM AUTHOR]

In the traditional incremental analysis update (IAU) process, all analysis increments are treated as constant forcing in a model's prognostic equations over a certain time window. This approach effectively reduces high-frequency oscillations introduced by data assimilation. However, as different scales of increments have unique evolutionary speeds and life histories in a numerical model, the traditional IAU scheme cannot fully meet the requirements of short-term forecasting for the damping of high-frequency noise and may even cause systematic drifts. Therefore, a multi-scale IAU scheme is proposed in this paper. Analysis increments were divided into different scale parts using a spatial filtering technique. For each scale increment, the optimal relaxation time in the IAU scheme was determined by the skill of the forecasting results. Finally, different scales of analysis increments were added to the model integration during their optimal relaxation time. The multi-scale IAU scheme can effectively reduce the noise and further improve the balance between large-scale and small-scale increments in the model initialization stage. To evaluate its performance, several numerical experiments were conducted to simulate the path and intensity of Typhoon Mangkhut (2018) and showed that: (1) the multi-scale IAU scheme had an obvious effect on noise control at the initial stage of data assimilation; (2) the optimal relaxation time for large-scale and small-scale increments was estimated as 6 h and 3 h, respectively; (3) the forecast performance of the multi-scale IAU scheme in the prediction of Typhoon Mangkhut (2018) was better than that of the traditional IAU scheme. The results demonstrate the superiority of the multi-scale IAU scheme. [ABSTRACT FROM AUTHOR]

The positive phase of the subtropical Indian Ocean dipole (SIOD) is one of the climatic modes in the subtropical southern Indian Ocean that influences the austral summer inter-annual rainfall variability in parts of southern Africa. This paper examines austral summer rain-bearing circulation types (CTs) in Africa south of the equator that are related to the positive SIOD and the dynamics through which specific rainfall regions in southern Africa can be influenced by this relationship. Four austral summer rain-bearing CTs were obtained. Among the four CTs, the CT that featured (i) enhanced cyclonic activity in the southwest Indian Ocean; (ii) positive widespread rainfall anomaly in the southwest Indian Ocean; and (iii) low-level convergence of moisture fluxes from the tropical South Atlantic Ocean, tropical Indian Ocean, and the southwest Indian Ocean, over the south-central landmass of Africa, was found to be related to the positive SIOD climatic mode. The relationship also implies that positive SIOD can be expected to increase the amplitude and frequency of occurrence of the aforementioned CT. The linkage between the CT related to the positive SIOD and austral summer homogeneous regions of rainfall anomalies in Africa south of the equator showed that it is the principal CT that is related to the inter-annual rainfall variability of the south-central regions of Africa, where the SIOD is already known to significantly influence its rainfall variability. Hence, through the large-scale patterns of atmospheric circulation associated with the CT, the SIOD can influence the spatial distribution and intensity of rainfall over the preferred landmass through enhanced moisture convergence. [ABSTRACT FROM AUTHOR]

Radiative transfer simulations and remote sensing studies fundamentally require accurate and efficient computation of the optical properties of non-spherical particles. This paper proposes a deep learning (DL) scheme in conjunction with an optical property database to achieve this goal. Deep neural network (DNN) architectures were obtained from a dataset of the optical properties of super-spheroids with extensive shape parameters, size parameters, and refractive indices. The dataset was computed through the invariant imbedding T-matrix method. Four separate DNN architectures were created to compute the extinction efficiency factor, single-scattering albedo, asymmetry factor, and phase matrix. The criterion for designing these neural networks was the achievement of the highest prediction accuracy with minimal DNN parameters. The numerical results demonstrate that the determination coefficients are greater than 0.999 between the prediction values from the neural networks and the truth values from the database, which indicates that the DNN can reproduce the optical properties in the dataset with high accuracy. In addition, the DNN model can robustly predict the optical properties of particles with high accuracy for shape parameters or refractive indices that are unavailable in the database. Importantly, the ratio of the database size (∼127 GB) to that of the DNN parameters (∼20 MB) is approximately 6810, implying that the DNN model can be treated as a highly compressed database that can be used as an alternative to the original database for real-time computing of the optical properties of non-spherical particles in radiative transfer and atmospheric models. [ABSTRACT FROM AUTHOR]

This study reveals a significant positive connection between autumn non-tropical-cyclone heavy rainfall on Hainan Island and the intensity of Eastern Pacific (EP) El Niño events. That is, the amount of rainfall in super EP El Niño years is more than that in normal EP El Niño years. Comparing EP El Niño years of different intensities, the cooler sea surface temperature in the northwestern Pacific during super EP El Niño years stimulates a negative surface latent heat flux (LHF) anomaly and abnormal anticyclonic circulation at 850 hPa. Under these conditions, an abnormal zonal vertical circulation develops in the northern South China Sea once a positive LHF anomaly and abnormal cyclonic circulation (ACC) at 850 hPa occur in the Beibu Gulf. The abnormal zonal vertical circulation further strengthens the ascending motion over Hainan Island, as the critical factor that leads to excessive rainfall. Further analysis shows that the positive LHF anomaly, which can be attributed to the increased latent heat transfer which resulted from the increased surface wind speed, is an important trigger for the ACC. However, the ACC is also the supplier of favorable moisture conditions because it intensifies vapor convergence over Hainan Island and meridionally transports moisture from the South China Sea to northeastern Hainan Island, thereby generating heavy rainfall. This paper emphasizes that the impact of El Niño events, especially super El Niño events, on rainfall over Hainan Island cannot be ignored, even if the traditional view is that frequent rainfall occurs mainly in La Niña years. [ABSTRACT FROM AUTHOR]

This paper evaluates the microwave instruments onboard the latest Chinese polar-orbiting satellite, Feng-Yun 3D (FY-3D). Comparing three months of observations from the Microwave Temperature Sounder 2 (MWTS-2), the Microwave Humidity Sounder 2 (MWHS-2), and the Microwave Radiation Imager (MWRI) to Met Office short-range forecasts, we characterize the instrumental biases, show how those biases have changed with respect to their predecessors onboard FY-3C, and how they compare to the Advanced Technology Microwave Sounder (ATMS) onboard NOAA-20 and the Global Precipitation Measurement Microwave Imager (GMI). The MWTS-2 global bias is much reduced with respect to its predecessor and compares well to ATMS at equivalent channel frequencies, differing only by 0.36 ± 0.28 K (1σ) on average. A suboptimal averaging of raw digital counts is found to cause an increase in striping noise and an ascending—descending bias. MWHS-2 benefits from a new calibration method improving the 183-GHz humidity channels with respect to its predecessor and biases for these channels are within ± 1.9 K to ATMS. MWRI presents the largest improvements, with reduced global bias and standard deviation with respect to FY-3C; although, spurious, seemingly transient, brightness temperatures have been detected in the observations at 36.5 GHz (vertical polarization). The strong solar-dependent bias that affects the instrument on FY-3C has been reduced to less than 0.2 K on average for FY-3D MWRI. Experiments where radiances from these instruments were assimilated on top of a full global system demonstrated a neutral to positive impact on the forecasts, as well as on the fit to the background of independent instruments. [ABSTRACT FROM AUTHOR]

This paper includes a comprehensive assessment of 40 models from the Coupled Model Intercomparison Project phase 5 (CMIP5) and 33 models from the CMIP phase 6 (CMIP6) to determine the climatological and seasonal variation of ocean salinity from the surface to 2000 m. The general pattern of the ocean salinity climatology can be simulated by both the CMIP5 and CMIP6 models from the surface to 2000-m depth. However, this study shows an increased fresh bias in the surface and subsurface salinity in the CMIP6 multimodel mean, with a global average of −0.44 g kg−1 for the sea surface salinity (SSS) and −0.26 g kg−1 for the 0–1000-m averaged salinity (S1000) compared with the CMIP5 multimodel mean (−0.25 g kg−1 for the SSS and −0.07 g kg−1 for the S1000). In terms of the seasonal variation, both CMIP6 and CMIP5 models show positive (negative) anomalies in the first (second) half of the year in the global average SSS and S1000. The model-simulated variation in SSS is consistent with the observations, but not for S1000, suggesting a substantial uncertainty in simulating and understanding the seasonal variation in subsurface salinity. The CMIP5 and CMIP6 models overestimate the magnitude of the seasonal variation of the SSS in the tropics in the region 20°S–20°N but underestimate the magnitude of the seasonal change in S1000 in the Atlantic and Indian oceans. These assessments show new features of the model errors in simulating ocean salinity and support further studies of the global hydrological cycle. [ABSTRACT FROM AUTHOR]

Marine heatwaves (MHWs) are prolonged high-temperature extreme events in the ocean that can be devastating to marine life and seriously impact climate systems and economies. This paper describes the accessibility, content, characteristics, and potential applications of an MHW dataset to facilitate its use in scientific research. Daily intensities of global MHWs from 1982 to 2020 were analyzed using gridded SST data sourced from the National Oceanic and Atmospheric Administration (NOAA) Optimum Interpolation (OI) SST V2 high-resolution (0.25°) dataset. The analysis shows a linear increase in the frequency of MHWs in most ocean regions of the world as well as significant interdecadal changes. This data product can be used as a basic dataset to study the seasonal to decadal changes in extreme ocean events and explore the effects of global warming on the surface layers of oceans during the last 40 years. [ABSTRACT FROM AUTHOR]

Three types of previously used numerical methods are revisited for computing the streamfunction ψ and velocity potential χ from the horizontal velocity v in limited domains. The first type, called the SOR-based method, uses a classical successive over-relaxation (SOR) scheme to compute ψ (or χ) first with an arbitrary boundary condition (BC) and then χ (or ψ) with the BC derived from ν. The second type, called the spectral method, uses spectral formulations to construct the inner part of (ψ, χ)—the inversion of (vorticity, divergence) with a homogeneous BC, and then the remaining harmonic part of (ψ, χ) with BCs from ν. The third type, called the integral method, uses integral formulas to compute the internally induced (ψ, χ)—the inversion of domain-internal (vorticity, divergence) using the free-space Green's function without BCs and then the remaining harmonic ψ (or χ) with BCs from v minus the internally-induced part. Although these methods have previously been successfully applied to flows in large-scale and synoptic-scale domains, their accuracy is compromised when applied to complex flows over mesoscale domains, as shown in this paper. To resolve this problem, two hybrid approaches, the integral-SOR method and the integral-spectral method, are developed by combining the first step of the integral method with the second step adopted from the SOR-based and spectral methods, respectively. Upon testing these methods on real-case complex flows, the integral-SOR method is significantly more accurate than the integral-spectral method, noting that the latter is still generally more accurate than the three previously-used methods. The integral-SOR method is recommended for future applications and diagnostic studies of complex flows. [ABSTRACT FROM AUTHOR]

The 26th Conference of the Parties (COP26) to the United Nations Framework Convention on Climate Change (UNFCCC) was held in Glasgow a year later than scheduled, with expected outcomes achieved under a post-pandemic background. Based on the Issue-Actor-Mechanism Framework, this paper systematically evaluates the outcomes achieved at COP26 and analyzes the tendency of post-COP26 climate negotiations. Overall, with the concerted efforts of all parties, COP26 has achieved a balanced and inclusive package of outcomes and concluded six years of negotiations on the Paris Rulebook. It is fair to say that COP26 is another milestone in climate governance following the implementation of the Paris Agreement. Meanwhile, the Glasgow Climate Pact has cemented the consensus on a global commitment to accelerating climate action over the next decade and reached a breakthrough consensus on reducing coal, controlling methane, and halting deforestation. In the post-COP26 era, we still need to take concrete actions to implement the outcomes of the Paris Agreement and the Glasgow Climate Pact, innovate ways to speed up CO2 emissions reduction, and continue to strive for breakthroughs in important issues such as finance, technology, adaptation, and collaboration. In addition to avoiding the escalation of international conflicts, we need to collectively and properly handle the relationship between energy security, carbon reduction, and development and facilitate the efforts of countries to achieve their Sustainable Development Goals (SDGs), including climate-related goals. China will continue to maintain the existing multilateral mechanisms and processes for climate governance, unremittingly take concrete actions to address climate change, promote a domestic comprehensive green transition and global cooperation on carbon neutrality, and contribute constructively to global climate governance. [ABSTRACT FROM AUTHOR]

China's recently announced directive on tackling climate change, namely, to reach carbon peak by 2030 and to achieve carbon neutrality by 2060, has led to an unprecedented nationwide response among the academia and industry. Under such a directive, a rapid increase in the grid penetration rate of solar in the near future can be fully anticipated. Although solar radiation is an atmospheric process, its utilization, as to produce electricity, has hitherto been handled by engineers. In that, it is thought important to bridge the two fields, atmospheric sciences and solar engineering, for the common good of carbon neutrality. In this überreview, all major aspects pertaining to solar resource assessment and forecasting are discussed in brief. Given the size of the topic at hand, instead of presenting technical details, which would be overly lengthy and repetitive, the overarching goal of this review is to comprehensively compile a catalog of some recent, and some not so recent, review papers, so that the interested readers can explore the details on their own. [ABSTRACT FROM AUTHOR]

Mêdog and Nagqu are two typical regions of the Tibetan Plateau with different geographical locations and climate regimes. These differences may lead to discrepancies in the raindrop size distributions (DSDs) and precipitation microphysical processes between the two regions. This paper investigates discrepancies in the DSDs using disdrometer data obtained during the rainy season in Mêdog and Nagqu. The DSD characteristics are studied under five different rainfall rate categories and two precipitation types (stratiform and convective). For the total datasets, the number concentrations of drops with diameters D > 0.6 (D < 0.6) mm are higher (lower) in Nagqu than in Mêdog. The fitted normalized gamma distributions of the averaged DSDs for the five rainfall rate categories show that Nagqu has a larger (lower) mass-weighted mean diameter Dm (normalized intercept parameter, lgNw) than does Mêdog. The difference in Dm between Nagqu and Mêdog increases with the rainfall rate. Convective clusters in Nagqu could be identified as continental-like, while convective precipitation in Mêdog could be classified as maritime-like. The relationships between the shape factor μ and slope parameter Λ of the gamma distribution model, the radar reflectivity Z, and the rainfall rate R are also derived. Furthermore, the possible causative mechanism for the notable DSD variation between the two regions during the rainy season is illustrated using reanalysis data and automated weather station observations. Cold rain processes are mainly responsible for the lower concentrations of larger drops observed in Nagqu, whereas warm rain prevails in Mêdog, producing abundant small drops. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the influence of the winter NAO on the multidecadal variability of winter East Asian surface air temperature (EASAT) and EASAT decadal prediction. The observational analysis shows that the winter EASAT and East Asian minimum SAT (EAmSAT) display strong in-phase fluctuations and a significant 60–80-year multidecadal variability, apart from a long-term warming trend. The winter EASAT experienced a decreasing trend in the last two decades, which is consistent with the occurrence of extremely cold events in East Asia winters in recent years. The winter NAO leads the detrended winter EASAT by 12–18 years with the greatest significant positive correlation at the lead time of 15 years. Further analysis shows that ENSO may affect winter EASAT interannual variability, but does not affect the robust lead relationship between the winter NAO and EASAT. We present the coupled oceanic-atmospheric bridge (COAB) mechanism of the NAO influences on winter EASAT multidecadal variability through its accumulated delayed effect of ∼15 years on the Atlantic Multidecadal Oscillation (AMO) and Africa–Asia multidecadal teleconnection (AAMT) pattern. An NAO-based linear model for predicting winter decadal EASAT is constructed on the principle of the COAB mechanism, with good hindcast performance. The winter EASAT for 2020–34 is predicted to keep on fluctuating downward until ∼2025, implying a high probability of occurrence of extremely cold events in coming winters in East Asia, followed by a sudden turn towards sharp warming. The predicted 2020/21 winter EASAT is almost the same as the 2019/20 winter. [ABSTRACT FROM AUTHOR]

Starting in mid-November, China was hit by several cold events during the early winter of 2020/21. The lowest temperature observed at Beijing station on 7 January reached −19.6°C. In this paper, we show that the outbreak of the record-breaking extreme cold event can be attributed to a huge merging Ural blocking (UB) ridge over the Eurasian region. The sea-ice cover in the Kara and East Siberia Seas (KESS) in autumn was at its lowest value since 1979, which could have served as a precursor signal. Further analysis shows that several successive UB episodes occurred from 1 September 2020 to 10 January 2021. The persistent UB that occurred in late September/early October 2020 may have made an important contribution to the October historical minimum of sea ice in the KESS region. Our results also show that, after each UB episode in winter, significant upward propagation of wave activity occurred around 60°E, which resulted in weakening the stratospheric vortex. Meanwhile, each UB episode also caused a significant reduction in sea-ice extent in KESS and a significant weakening of the westerly jet in mid–high-latitude Eurasia. Results suggest that the Arctic vortex, which is supposed to enhance seasonally, became weaker and more unstable than the climatic mean under the seasonal cumulative effects of UB episodes, KESS warming, and long-lasting negative-phase North Atlantic Oscillation (NAO–). Those seasonal cumulative effects, combined with the impact of La Niña winter, led to the frequent occurrence of extreme cold events. [ABSTRACT FROM AUTHOR]

A physical retrieval approach based on the one-dimensional variational (1D-Var) algorithm is applied in this paper to simultaneously retrieve atmospheric temperature and humidity profiles under both clear-sky and partly cloudy conditions from FY-4A GIIRS (geostationary interferometric infrared sounder) observations. Radiosonde observations from upper-air stations in China and level-2 operational products from the Chinese National Satellite Meteorological Center (NSMC) during the periods from December 2019 to January 2020 (winter) and from July 2020 to August 2020 (summer) are used to validate the accuracies of the retrieved temperature and humidity profiles. Comparing the 1D-Var-retrieved profiles to radiosonde data, the accuracy of the temperature retrievals at each vertical level of the troposphere is characterized by a root mean square error (RMSE) within 2 K, except for at the bottom level of the atmosphere under clear conditions. The RMSE increases slightly for the higher atmospheric layers, owing to the lack of temperature sounding channels there. Under partly cloudy conditions, the temperature at each vertical level can be obtained, while the level-2 operational products obtain values only at altitudes above the cloud top. In addition, the accuracy of the retrieved temperature profiles is greatly improved compared with the accuracies of the operational products. For the humidity retrievals, the mean RMSEs in the troposphere in winter and summer are both within 2 g kg−1. Moreover, the retrievals performed better compared with the ERA5 reanalysis data between 800 hPa and 300 hPa both in summer and winter in terms of RMSE. [ABSTRACT FROM AUTHOR]

An observational study focusing on the contribution of tropical cyclones (TCs) that form over the western North Pacific (WNP) to the synoptic-scale transient eddy activity (STEA) over the North Pacific during the boreal autumn and early winter in the period 1979–2019 is presented in this paper. Statistical results show that WNP TCs entering the mid-latitudinal North Pacific provide significant positive effects on the pentad mean strength of STEA, which is primarily concentrated over the Kuroshio/Oyashio Extensions (KOE) and regions from east of Japan to 160°W in the lower and mid-to-upper troposphere, respectively. TC intensity is highly indicative of the subsequent STEA with a correlation coefficient of 0.37/0.33/0.45 at 300 hPa/500 hPa/850 hPa exceeding the 99% confidence level for the period 1979–2019. The strength of STEA in the upper troposphere associated with TCs presents a more significant linear growth with TC intensity than that at the mid-to-lower levels after the cyclones enter the KOE region, suggesting that the impact of TCs on STEA gradually increases with height. Further analyses reveal that the contribution of TCs accounts for 4%–6% of the total STEA change over the KOE region during the late autumn and early winter. In addition, the influence of TCs on STEA experienced an interdecadal decrease from the early 2000s through the early 2010s. [ABSTRACT FROM AUTHOR]

Before 2008, the number of surface observation stations in China was small. Thus, the surface observation data were too sparse to effectively support the High-resolution China Meteorological Administration's Land Assimilation System (HRCLDAS) which ultimately inhibited the output of high-resolution and high-quality gridded products. This paper proposes a statistical downscaling model based on a deep learning algorithm in super-resolution to research the above problem. Specifically, we take temperature as an example. The model is used to downscale the 0.0625° × 0.0625°, 2-m temperature data from the China Meteorological Administration's Land Data Assimilation System (CLDAS) to 0.01° × 0.01°, named CLDASSD. We performed quality control on the paired data from CLDAS and HRCLDAS, using data from 2018 and 2019. CLDASSD was trained on the data from 31 March 2018 to 28 February 2019, and then tested with the remaining data. Finally, extensive experiments were conducted in the Beijing-Tianjin-Hebei region which features complex and diverse geomorphology. Taking the HRCLDAS product and surface observation data as the "true values" and comparing them with the results of bilinear interpolation, especially in complex terrain such as mountains, the root mean square error (RMSE) of the CLDASSD output can be reduced by approximately 0.1°C, and its structural similarity (SSIM) was approximately 0.2 higher. CLDASSD can estimate detailed textures, in terms of spatial distribution, with greater accuracy than bilinear interpolation and other sub-models and can perform the expected downscaling tasks. [ABSTRACT FROM AUTHOR]