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  Subjects -> METEOROLOGY (Total: 112 journals)
Showing 1 - 36 of 36 Journals sorted by number of followers
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 198)
Nature Climate Change     Full-text available via subscription   (Followers: 133)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 80)
Atmospheric Environment     Hybrid Journal   (Followers: 73)
Atmospheric Research     Hybrid Journal   (Followers: 69)
Climatic Change     Open Access   (Followers: 64)
Journal of Climate     Hybrid Journal   (Followers: 54)
Bulletin of the American Meteorological Society     Open Access   (Followers: 51)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 48)
Climate Dynamics     Hybrid Journal   (Followers: 44)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 43)
Climate Policy     Hybrid Journal   (Followers: 42)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 37)
Atmospheric Science Letters     Open Access   (Followers: 36)
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 35)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 34)
Monthly Weather Review     Hybrid Journal   (Followers: 34)
International Journal of Climatology     Hybrid Journal   (Followers: 31)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 31)
American Journal of Climate Change     Open Access   (Followers: 29)
Advances in Climate Change Research     Open Access   (Followers: 29)
Journal of Hydrology and Meteorology     Open Access   (Followers: 29)
Developments in Atmospheric Science     Full-text available via subscription   (Followers: 28)
Weather and Forecasting     Hybrid Journal   (Followers: 28)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 27)
Journal of Space Weather and Space Climate     Open Access   (Followers: 27)
Atmosphere     Open Access   (Followers: 26)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 26)
Space Weather     Full-text available via subscription   (Followers: 25)
Advances in Meteorology     Open Access   (Followers: 24)
Energy & Environment     Hybrid Journal   (Followers: 24)
Tellus A     Open Access   (Followers: 22)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 21)
International Journal of Atmospheric Sciences     Open Access   (Followers: 21)
Tellus B     Open Access   (Followers: 21)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 20)
Climate Change Economics     Hybrid Journal   (Followers: 20)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Weather     Hybrid Journal   (Followers: 19)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 18)
Global Meteorology     Open Access   (Followers: 17)
Weather and Climate Extremes     Open Access   (Followers: 16)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 15)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 14)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 13)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 13)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 11)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 11)
Climate Change Responses     Open Access   (Followers: 10)
Climate Resilience and Sustainability     Open Access   (Followers: 9)
Climate law     Hybrid Journal   (Followers: 8)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 7)
Climate Change Research Letters     Open Access   (Followers: 7)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 7)
Climate     Open Access   (Followers: 6)
Open Journal of Modern Hydrology     Open Access   (Followers: 6)
Mathematics of Climate and Weather Forecasting     Open Access   (Followers: 6)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 6)
Climate Research     Hybrid Journal   (Followers: 6)
Current Climate Change Reports     Hybrid Journal   (Followers: 6)
Aeolian Research     Hybrid Journal   (Followers: 6)
The Cryosphere (TC)     Open Access   (Followers: 5)
Climate Risk Management     Open Access   (Followers: 5)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 5)
Climate of the Past (CP)     Open Access   (Followers: 5)
Change and Adaptation in Socio-Ecological Systems     Open Access   (Followers: 5)
Urban Climate     Hybrid Journal   (Followers: 4)
International Journal of Environment and Climate Change     Open Access   (Followers: 4)
Environmental and Climate Technologies     Open Access   (Followers: 4)
Carbon Balance and Management     Open Access   (Followers: 4)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
The Cryosphere Discussions (TCD)     Open Access   (Followers: 4)
Weatherwise     Hybrid Journal   (Followers: 4)
Meteorological Applications     Hybrid Journal   (Followers: 4)
Climate Services     Open Access   (Followers: 3)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 3)
Atmósfera     Open Access   (Followers: 3)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 3)
Journal of Climatology     Open Access   (Followers: 3)
Ciencia, Ambiente y Clima     Open Access   (Followers: 3)
Frontiers in Climate     Open Access   (Followers: 3)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 3)
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 3)
Atmospheric Environment : X     Open Access   (Followers: 3)
npj Climate and Atmospheric Science     Open Access   (Followers: 3)
Journal of Weather Modification     Full-text available via subscription   (Followers: 2)
Open Atmospheric Science Journal     Open Access   (Followers: 2)
GeoHazards     Open Access   (Followers: 2)
Journal of Climate Change     Full-text available via subscription   (Followers: 2)
Climate and Energy     Full-text available via subscription   (Followers: 2)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
Climate Summary of South Africa     Full-text available via subscription   (Followers: 2)
Meteorological Monographs     Hybrid Journal   (Followers: 1)
气候与环境研究     Full-text available via subscription   (Followers: 1)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 1)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 1)
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
International Journal of Biometeorology     Hybrid Journal   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Mediterranean Marine Science     Open Access   (Followers: 1)
Large Marine Ecosystems     Full-text available via subscription   (Followers: 1)
Weather and Climate Dynamics     Open Access  
Journal of Agricultural Meteorology     Open Access  
Nīvār     Open Access  
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access  
Mètode Science Studies Journal : Annual Review     Open Access  
Earth Perspectives - Transdisciplinarity Enabled     Open Access  
Climate of the Past Discussions (CPD)     Open Access  
Revista Brasileira de Meteorologia     Open Access  
Studia Geophysica et Geodaetica     Hybrid Journal  

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Similar Journals
Journal Cover
Advances in Atmospheric Sciences
Journal Prestige (SJR): 0.956
Citation Impact (citeScore): 2
Number of Followers: 43  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1861-9533 - ISSN (Online) 0256-1530
Published by Springer-Verlag Homepage  [2653 journals]
  • Intermodel Diversity of Simulated Long-term Changes in the Austral Winter
           Southern Annular Mode: Role of the Southern Ocean Dipole
    • Abstract: The Southern Annular Mode (SAM) plays an important role in regulating Southern Hemisphere extratropical circulation. State-of-the-art models exhibit intermodel spread in simulating long-term changes in the SAM. Results from Atmospheric Model Intercomparison Project (AMIP) experiments from 28 models archived in CMIP5 show that the intermodel spread in the linear trend in the austral winter (June–July–August) SAM is significant, with an intermodel standard deviation of 0.28 (10 yr)−1, larger than the multimodel ensemble mean of 0.18 (10 yr)−1. This study explores potential factors underlying the model difference from the aspect of extratropical sea surface temperature (SST). Extratropical SST anomalies related to the SAM exhibit a dipole-like structure between middle and high latitudes, referred to as the Southern Ocean Dipole (SOD). The role of SOD-like SST anomalies in influencing the SAM is found in the AMIP simulations. Model performance in simulating the SAM trend is linked with model skill in reflecting the SOD-SAM relationship. Models with stronger linkage between the SOD and the SAM tend to simulate a stronger SAM trend. The explained variance is about 40% in the AMIP runs. These results suggest improved simulation of the SOD-SAM relationship may help reproduce long-term changes in the SAM.
      PubDate: 2021-03-01
  • Numerical Simulation to Evaluate the Effects of Upward Lightning
           Discharges on Thunderstorm Electrical Parameters
    • Abstract: A theoretical discussion of the discharge effects of upward lightning simulated with a fine-resolution 2D thunderstorm model is performed in this paper, and the results reveal that the estimates of the total induced charge on the upward lightning discharge channels range from 0.67 to 118.8 C, and the average value is 19.0 C, while the ratio of the induced charge on the leader channels to the total opposite-polarity charge in the discharge region ranges from 5.9% to 47.3%, with an average value of 14.7%. Moreover, the average value of the space electrostatic energy consumed by upward lightning is 1.06×109 J. The above values are lower than those related to intracloud lightning discharges. The density of the deposited opposite-polarity charge is comparable in magnitude to that of the preexisting charge in the discharge area, and the deposition of these opposite-polarity charges rapidly destroys the original space potential well in the discharge area and greatly reduces the space electric field strength. In addition, these opposite-polarity charges are redistributed with the development of thunderstorms. The space charge redistribution caused by lightning discharges partly accounts for the complexity of the charge structures in a thunderstorm, and the complexity gradually decreases with the charge neutralization process.
      PubDate: 2021-03-01
  • Understanding the Soil Temperature Variability at Different Depths:
           Effects of Surface Air Temperature, Snow Cover, and the Soil Memory
    • Abstract: The soil temperature (ST) is closely related to the surface air temperature (AT), but their coupling may be affected by other factors. In this study, significant effects of the AT on the underlying ST were found, and the time taken to propagate downward to 320 cm can be up to 10 months. Besides the AT, the ST is also affected by memory effects—namely, its prior thermal conditions. At deeper depth (i.e., 320 cm), the effects of the AT from a particular season may be exceeded by the soil memory effects from the last season. At shallower layers (i.e., < 80 cm), the effects of the AT may be blocked by the snow cover, resulting in a poorly synchronous correlation between the AT and the ST. In northeastern China, this snow cover blockage mainly occurs in winter and then vanishes in the subsequent spring. Due to the thermal insulation effect of the snow cover, the winter ST at layers above 80 cm in northeastern China were found to continue to increase even during the recent global warming hiatus period. These findings may be instructive for better understanding ST variations, as well as land-atmosphere interactions.
      PubDate: 2021-03-01
  • Integrative Monsoon Frontal Rainfall Experiment (IMFRE-I): A Mid-Term
    • Abstract: The mei-yu season, typically occurring from mid-June to mid-July, on average, contributes to 32% of the annual precipitation over the Yangtze–Huai River Valley (YHRV) and represents one of the three heavy-rainfall periods in China. Here, we briefly review the large-scale background, synoptic pattern, moisture transport, and cloud and precipitation characteristics of the mei-yu frontal systems in the context of the ongoing Integrative Monsoon Frontal Rainfall Experiment (IMFRE) field campaign. Phase one of the campaign, IMFRE-I, was conducted from 10 June to 10 July 2018 in the middle reaches of the YHRV. Led by the Wuhan Institute of Heavy Rain (IHR) with primary support from the National Natural Science Foundation of China, IMFRE-I maximizes the use of our observational capacity enabled by a suite of ground-based and remote sensing instruments, most notably the IHR Mesoscale Heavy Rainfall Observing System (MHROS), including different wavelengths of radars, microwave radiometers, and disdrometers. The KA350 (Shanxi King-Air) aircraft participating in the campaign is equipped with Ka-band cloud radar and different probes. The comprehensive datasets from both the MHROS and aircraft instruments are combined with available satellite observations and model simulations to answer the three scientific questions of IMFRE-I. Some highlights from a previously published special issue are included in this review, and we also briefly introduce the IMFRE-II field campaign, conducted during June–July 2020, where the focus was on the spatiotemporal evolutions of the mei-yu frontal systems over the middle and lower reaches of the YHRV.
      PubDate: 2021-03-01
  • A New Global Solar-induced Chlorophyll Fluorescence (SIF) Data Product
           from TanSat Measurements
    • Abstract: The Chinese Carbon Dioxide Observation Satellite Mission (TanSat) is the third satellite for global CO2 monitoring and is capable of detecting weak solar-induced chlorophyll fluorescence (SIF) signals with its advanced technical characteristics. Based on the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing (IAPCAS) platform, we successfully retrieved the TanSat global SIF product spanning the period of March 2017 to February 2018 with a physically based algorithm. This paper introduces the new TanSat SIF dataset and shows the global seasonal SIF maps. A brief comparison between the IAPCAS TanSat SIF product and the data-driven SVD (singular value decomposition) SIF product is also performed for follow-up algorithm optimization. The comparative results show that there are regional biases between the two SIF datasets and the linear correlations between them are above 0.73 for all seasons. The future SIF data product applications and requirements for SIF space observation are discussed.
      PubDate: 2021-03-01
  • Hybrid Method to Identify Second-trip Echoes Using Phase Modulation and
           Polarimetric Technology
    • Abstract: For pulse Doppler radars, the widely used method for identifying second-trip echoes (STs) in the signal processing level yields significant misidentification in regions of high turbulence and severe wind shear. In the data processing level, although the novel algorithm for ST identification does not yield significant misidentification in specific regions, its overall identification performance is not ideal. Therefore, this paper proposes a hybrid method for the identification of STs using phase modulation (signal processing) and polarimetric technology (data processing). Through this approach, most of the STs are removed, whereas most of the first-trip echoes (FTs) remain untouched. Compared with the existing method using a signal quality index filter with an optimized threshold, the hybrid method exhibits superior performance (Heidke skill scores of 0.98 versus 0.88) on independent test datasets, especially in high-turbulence and severe-wind-shear regions, for which misidentification is significantly reduced.
      PubDate: 2021-03-01
  • Skill Assessment of Copernicus Climate Change Service Seasonal Ensemble
           Precipitation Forecasts over Iran
    • Abstract: Medium to long-term precipitation forecasting plays a pivotal role in water resource management and development of warning systems. Recently, the Copernicus Climate Change Service (C3S) database has been releasing monthly forecasts for lead times of up to three months for public use. This study evaluated the ensemble forecasts of three C3S models over the period 1993–2017 in Iran’s eight classified precipitation clusters for one- to three-month lead times. Probabilistic and non-probabilistic criteria were used for evaluation. Furthermore, the skill of selected models was analyzed in dry and wet periods in different precipitation clusters. The results indicated that the models performed best in western precipitation clusters, while in the northern humid cluster the models had negative skill scores. All models were better at forecasting upper-tercile events in dry seasons and lower-tercile events in wet seasons. Moreover, with increasing lead time, the forecast skill of the models worsened. In terms of forecasting in dry and wet years, the forecasts of the models were generally close to observations, albeit they underestimated several severe dry periods and overestimated a few wet periods. Moreover, the multi-model forecasts generated via multivariate regression of the forecasts of the three models yielded better results compared with those of individual models. In general, the ECMWF and UKMO models were found to be appropriate for one-month-ahead precipitation forecasting in most clusters of Iran. For the clusters considered in Iran and for the long-range system versions considered, the Météo France model had lower skill than the other models.
      PubDate: 2021-03-01
  • Phase Two of the Integrative Monsoon Frontal Rainfall Experiment
    • Abstract: Phase Two of the Integrative Monsoon Frontal Rainfall Experiment (IMFRE-II) was conducted over the middle and lower reaches of the Yangtze River during the period 16 June to 19 July 2020. This paper provides a brief overview of the IMFRE-II field campaign, including the multiple ground-based remote sensors, aircraft probes, and their corresponding measurements during the 2020 mei-yu period, as well as how to use these numerous datasets to answer scientific questions. The highlights of IMFRE-II are: (1) to the best of our knowledge, IMFRE-II is the first field campaign in China to use ground-based, airborne, and spaceborne platforms to conduct comprehensive observations over the middle and lower reaches of the Yangtze River; and (2) seven aircraft flights were successfully carried out, and the spectra of ice particles, cloud droplets, and raindrops at different altitudes were obtained. These in-situ measurements will provide a “cloud truth” to validate the ground-based and satellite-retrieved cloud and precipitation properties and quantitatively estimate their retrieval uncertainties. They are also crucial for the development of a warm (and/or cold) rain conceptual model in order to better understand the cloud-to-rain conversion and accretion processes in mei-yu precipitation events. Through an integrative analysis of ground-based, aircraft, and satellite observations and model simulations, we can significantly improve our cloud and precipitation retrieval algorithms, investigate the microphysical properties of cloud and precipitation, understand in-depth the formation and dissipation mechanisms of mei-yu frontal systems, and improve cloud microphysics parameterization schemes and model simulations.
      PubDate: 2021-03-01
  • Increases in Anthropogenic Heat Release from Energy Consumption Lead to
           More Frequent Extreme Heat Events in Urban Cities
    • Abstract: With economic development and rapid urbanization, increases in Gross Domestic Product and population in fast-growing cities since the turn of the 21st Century have led to increases in energy consumption. Anthropogenic heat flux released to the near-surface atmosphere has led to changes in urban thermal environments and severe extreme temperature events. To investigate the effects of energy consumption on urban extreme temperature events, including extreme heat and cold events, a dynamic representation scheme of anthropogenic heat release (AHR) was implemented in the Advanced Research version of the Weather Research and Forecasting (WRF) model, and AHR data were developed based on energy consumption and population density in a case study of Beijing, China. Two simulations during 1999–2017 were then conducted using the developed WRF model with 3-km resolution with and without the AHR scheme. It was shown that the mean temperature increased with the increase in AHR, and more frequent extreme heat events were produced, with an annual increase of 0.02–0.19 days, as well as less frequent extreme cold events, with an annual decrease of 0.26–0.56 days, based on seven extreme temperature indices in the city center. AHR increased the sensible heat flux and led to surface energy budget changes, strengthening the dynamic processes in the atmospheric boundary layer that reduce AHR heating efficiency more in summer than in winter. In addition, it was concluded that suitable energy management might help to mitigate the impact of extreme temperature events in different seasons.
      PubDate: 2021-03-01
  • Future Precipitation Extremes in China under Climate Change and Their
           Physical Quantification Based on a Regional Climate Model and CMIP5 Model
    • Abstract: The atmospheric water holding capacity will increase with temperature according to Clausius-Clapeyron scaling and affects precipitation. The rates of change in future precipitation extremes are quantified with changes in surface air temperature. Precipitation extremes in China are determined for the 21st century in six simulations using a regional climate model, RegCM4, and 17 global climate models that participated in CMIP5. First, we assess the performance of the CMIP5 models and RCM runs in their simulation of extreme precipitation for the current period (RF: 1982–2001). The CMIP5 models and RCM results can capture the spatial variations of precipitation extremes, as well as those based on observations: OBS and XPP. Precipitation extremes over four subregions in China are predicted to increase in the mid-future (MF: 2039–58) and far-future (FF: 2079–98) relative to those for the RF period based on both the CMIP5 ensemble mean and RCM ensemble mean. The secular trends in the extremes of the CMIP5 models are predicted to increase from 2008 to 2058, and the RCM results show higher interannual variability relative to that of the CMIP5 models. Then, we quantify the increasing rates of change in precipitation extremes in the MF and FF periods in the subregions of China with the changes in surface air temperature. Finally, based on the water vapor equation, changes in precipitation extremes in China for the MF and FF periods are found to correlate positively with changes in the atmospheric vertical wind multiplied by changes in surface specific humidity (significant at the p < 0.1 level).
      PubDate: 2021-03-01
  • Classification of Northeast China Cold Vortex Activity Paths in Early
           Summer Based on K -means Clustering and Their Climate Impact
    • Abstract: The classification of the Northeast China Cold Vortex (NCCV) activity paths is an important way to analyze its characteristics in detail. Based on the daily precipitation data of the northeastern China (NEC) region, and the atmospheric circulation field and temperature field data of ERA-Interim for every six hours, the NCCV processes during the early summer (June) seasons from 1979 to 2018 were objectively identified. Then, the NCCV processes were classified using a machine learning method (k-means) according to the characteristic parameters of the activity path information. The rationality of the classification results was verified from two aspects, as follows: (1) the atmospheric circulation configuration of the NCCV on various paths; and (2) its influences on the climate conditions in the NEC. The obtained results showed that the activity paths of the NCCV could be divided into four types according to such characteristics as the generation origin, movement direction, and movement velocity of the NCCV. These included the generation-eastward movement type in the east of the Mongolia Plateau (eastward movement type or type A); generation-southeast longdistance movement type in the upstream of the Lena River (southeast long-distance movement type or type B); generation-eastward less-movement type near Lake Baikal (eastward less-movement type or type C); and the generation-southward less-movement type in eastern Siberia (southward less-movement type or type D). There were obvious differences observed in the atmospheric circulation configuration and the climate impact of the NCCV on the four above-mentioned types of paths, which indicated that the classification results were reasonable.
      PubDate: 2021-03-01
  • Anthropogenic Effects on Biogenic Secondary Organic Aerosol Formation
    • Abstract: Anthropogenic emissions alter biogenic secondary organic aerosol (SOA) formation from naturally emitted volatile organic compounds (BVOCs). We review the major laboratory and field findings with regard to effects of anthropogenic pollutants (NOx, anthropogenic aerosols, SO2, NH3) on biogenic SOA formation. NOx participate in BVOC oxidation through changing the radical chemistry and oxidation capacity, leading to a complex SOA composition and yield sensitivity towards NOx level for different or even specific hydrocarbon precursors. Anthropogenic aerosols act as an important intermedium for gas—particle partitioning and particle-phase reactions, processes of which are influenced by the particle phase state, acidity, water content and thus associated with biogenic SOA mass accumulation. SO2 modifies biogenic SOA formation mainly through sulfuric acid formation and accompanies new particle formation and acid-catalyzed heterogeneous reactions. Some new SO2-involved mechanisms for organosulfate formation have also been proposed. NH3/amines, as the most prevalent base species in the atmosphere, influence biogenic SOA composition and modify the optical properties of SOA. The response of SOA formation behavior to these anthropogenic pollutants varies among different BVOCs precursors. Investigations on anthropogenic—biogenic interactions in some areas of China that are simultaneously influenced by anthropogenic and biogenic emissions are summarized. Based on this review, some recommendations are made for a more accurate assessment of controllable biogenic SOA formation and its contribution to the total SOA budget. This study also highlights the importance of controlling anthropogenic pollutant emissions with effective pollutant mitigation policies to reduce regional and global biogenic SOA formation.
      PubDate: 2021-02-15
  • Estimations of Land Surface Characteristic Parameters and Turbulent Heat
           Fluxes over the Tibetan Plateau Based on FY-4A/AGRI Data
    • Abstract: Accurate estimates of land surface characteristic parameters and turbulent heat fluxes play an important role in the understanding of land-atmosphere interaction. In this study, Fengyun-4A (FY-4A) Advanced Geostationary Radiation Imager (AGRI) satellite data and the China Land Data Assimilation System (CLDAS) meteorological forcing dataset CLDAS-V2.0 were applied for the retrieval of broadband albedo, land surface temperature (LST), radiation flux components, and turbulent heat fluxes over the Tibetan Plateau (TP). The FY-4A/AGRI and CLDAS-V2.0 data from 12 March 2018 to 30 April 2018 were first used to estimate the hourly turbulent heat fluxes over the TP. The time series data of in-situ measurements from the Tibetan Observation and Research Platform were divided into two halves—one for developing retrieval algorithms for broadband albedo and LST based on FY-4A, and the other for the cross validation. Results show the root-mean-square errors (RMSEs) of the FY-4A retrieved broadband albedo and LST were 0.0309 and 3.85 K, respectively, which verifies the applicability of the retrieval method. The RMSEs of the downwelling/upwelling shortwave radiation flux and downwelling/upwelling longwave radiation flux were 138.87/32.78 W m−2 and 51.55/17.92 W m−2, respectively, and the RMSEs of net radiation flux, sensible heat flux, and latent heat flux were 58.88 W m−2, 82.56 W m−2 and 72.46 W m−2, respectively. The spatial distributions and diurnal variations of LST and turbulent heat fluxes were further analyzed in detail.
      PubDate: 2021-02-12
  • Comprehensive Marine Observing Experiment Based on High-Altitude Large
           Unmanned Aerial Vehicle (South China Sea Experiment 2020 of the “Petrel
    • Abstract: In collaboration with 12 other institutions, the Meteorological Observation Center of the China Meteorological Administration undertook a comprehensive marine observation experiment in the South China Sea using the Yilong-10 high-altitude large unmanned aerial vehicle (UAV). The Yilong-10 UAV carried a self-developed dropsonde system and a millimeter-wave cloud radar system. In addition, a solar-powered unmanned surface vessel and two drifting buoys were used. The experiment was further supported by an intelligent, reciprocating horizontal drifting radiosonde system that was deployed from the Sansha Meteorological Observing Station, with the intent of producing a stereoscopic observation over the South China Sea. Comprehensive three-dimensional observations were collected using the system from 31 July to 2 August, 2020. This information was used to investigate the formation and development processes of Typhoon Sinlaku (2020). The data contain measurements of 21 oceanic and meteorological parameters acquired by the five devices, along with video footage from the UAV. The data proved very helpful in determining the actual location and intensity of Typhoon Sinlaku (2020). The experiment demonstrates the feasibility of using a high-altitude, large UAV to fill in the gaps between operational meteorological observations of marine areas and typhoons near China, and marks a milestone for the use of such data for analyzing the structure and impact of a typhoon in the South China Sea. It also demonstrates the potential for establishing operational UAV meteorological observing systems in the future, and the assimilation of such data into numerical weather prediction models.
      PubDate: 2021-02-12
  • Diversity of the Coupling Wheels in the East Asian Summer Monsoon on the
    • Abstract: Two types of three-dimensional circulation of the East Asian summer monsoon (EASM) act as the coupling wheels determining the seasonal rainfall anomalies in China during 1979–2015. The first coupling mode features the interaction between the Mongolian cyclone over North Asia and the South Asian high (SAH) anomalies over the Tibetan Plateau at 200 hPa. The second mode presents the coupling between the anomalous low-level western Pacific anticyclone and upper-level SAH via the meridional flow over Southeast Asia. These two modes are responsible for the summer rainfall anomalies over China in 24 and 7 out of 37 years, respectively. However, the dominant SST anomalies in the tropical Pacific, the Indian Ocean, and the North Atlantic Ocean fail to account for the first coupling wheel’s interannual variability, illustrating the challenges in forecasting summer rainfall over China.
      PubDate: 2021-02-12
  • Satellite Observations of Reflectivity Maxima above the Freezing Level
           Induced by Terrain
    • Abstract: Previous studies have recognized reflectivity maxima above the freezing level (RMAF) within stratiform precipitation over mountain slopes, however, quantitative studies are limited due to the lack of adequate identification criteria. Here, we establish an identification method for RMAF precipitation and apply it to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) observations. Using the TRMM 2A25 product from 1998 to 2013, we show that the RMAF structure in reflectivity profiles can be effectively identified. RMAF exists not only in stratiform precipitation but also in convective precipitation. RMAF frequency is positively correlated with elevation, which is thought to be caused by enhanced updrafts in the middle layers of stratiform precipitation, or in the low to middle layers of convective precipitation over mountains. The average RMAF heights in stratiform and convective precipitation were 1.35 and 2.01 km above the freezing level, respectively, which is lower than previous results. In addition, our results indicate that the RMAF structure increased the echo top height and enhanced precipitation processes above the RMAF height, but it suppressed the downward propagation of ice particles and the near-surface rain rate. Future studies of orographic precipitation should take into account the impact of the RMAF structure and its relevant dynamic triggers.
      PubDate: 2021-02-12
  • The 2020/21 Extremely Cold Winter in China Influenced by the Synergistic
           Effect of La Niña and Warm Arctic
    • Abstract: In the first half of winter 2020/21, China has experienced an extremely cold period across both northern and southern regions, with record-breaking low temperatures set in many stations of China. Meanwhile, a moderate La Niña event which exceeded both oceanic and atmospheric thresholds began in August 2020 and in a few months developed into its mature phase, just prior to the 2020/21 winter. In this report, the mid-high-latitude large-scale atmospheric circulation anomalies in the Northern Hemisphere, which were forced by the negative phase of Arctic Oscillation, a strengthened Siberian High, an intensified Ural High and a deepened East Asian Trough, are considered to be the direct reason for the frequent cold surges in winter 2020/21. At the same time, the synergistic effect of the warm Arctic and the cold tropical Pacific (La Niña) provided an indispensable background, at a hemispheric scale, to intensify the atmospheric circulation anomalies in middle-to-high latitudes. In the end, a most recent La Niña prediction is provided and the on-coming evolution of climate is discussed for the remaining part of the 2020/21 winter for the purpose of future decision-making and early warning.
      PubDate: 2021-02-12
  • Characterization of Organic Aerosol at a Rural Site in the North China
           Plain Region: Sources, Volatility and Organonitrates
    • Abstract: The North China Plain (NCP) is a region that experiences serious aerosol pollution. A number of studies have focused on aerosol pollution in urban areas in the NCP region; however, research on characterizing aerosols in rural NCP areas is comparatively limited. In this study, we deployed a TD-HR-AMS (thermodenuder high-resolution aerosol mass spectrometer) system at a rural site in the NCP region in summer 2013 to characterize the chemical compositions and volatility of submicron aerosols (PM1). The average PM1 mass concentration was 51.2 ± 48.0 µg m−3 and organic aerosol (OA) contributed most (35.4%) to PM1. Positive matrix factorization (PMF) analysis of OA measurements identified four OA factors, including hydrocarbon-like OA (HOA, accounting for 18.4%), biomass burning OA (BBOA, 29.4%), less-oxidized oxygenated OA (LO-OOA, 30.8%) and more-oxidized oxygenated OA (MO-OOA, 21.4%). The volatility sequence of the OA factors was HOA > BBOA > LO-OOA > MO-OOA, consistent with their oxygen-to-carbon (O:C) ratios. Additionally, the mean concentration of organonitrates (ON) was 1.48–3.39 µg m−3, contributing 8.1%–19% of OA based on cross validation of two estimation methods with the high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) measurement. Correlation analysis shows that ON were more correlated with BBOA and black carbon emitted from biomass burning but poorly correlated with LO-OOA. Also, volatility analysis for ON further confirmed that particulate ON formation might be closely associated with primary emissions in rural NCP areas.
      PubDate: 2021-02-10
  • Sensitivity of Snowfall Characteristics to Meteorological Conditions in
           the Yeongdong Region of Korea
    • Abstract: This study investigates the characteristics of cold clouds and snowfall in both the Yeongdong coastal and mountainous regions under different meteorological conditions based on the integration of numerical modeling and three-hourly rawinsonde observations with snow crystal photographs for a snowfall event that occurred on 29–30 January 2016. We found that rimed particles predominantly observed turned into dendrite particles in the latter period of the episode when the 850 hPa temperature decreased at the coastal site, whereas the snow crystal habits at the mountainous site were largely needle or rimed needle. Rawinsonde soundings showed a well-defined, two-layered cloud structure along with distinctive wind-directional shear, and an inversion in the equivalent potential temperature above the low-level cloud layer. The first experiment with a decrease in lower-layer temperature showed that the low-level cloud thickness was reduced to less than 1.5 km, and the accumulated precipitation was decreased by 87% compared with the control experiment. The difference in precipitation amount between the single-layered experiment and control experiment (two-layered) was not so significant to attribute it to the effect of the seeder-feeder mechanism. The precipitation in the last experiment by weakening wind-directional shear was increased by 1.4 times greater than the control experiment specifically at the coastal site, with graupel particles accounting for the highest proportion (∼62%). The current results would improve snowfall forecasts in complicated geographical environments such as Yeongdong in terms of snow crystal habit as well as snowfall amount in both time and space domains.
      PubDate: 2021-01-14
      DOI: 10.1007/s00376-020-0157-9
  • Determination of Surface Precipitation Type Based on the Data Fusion
    • Abstract: Hazardous events related to atmospheric precipitation depend not only on the intensity of surface precipitation, but also on its type. Uncertainty related to determination of the precipitation type (PT) leads to financial losses in many areas of human activity, such as the power industry, agriculture, transportation, and many more. In this study, we use machine learning (ML) algorithms with the data fusion approach to more accurately determine surface PT. Based on surface synoptic observations, ERA5 reanalysis, and radar data, we distinguish between liquid, mixed, and solid precipitation types. The study domain considers the entire area of Poland and a period from 2015 to 2017. The purpose of this work is to address the question: “How can ML techniques applied in observational and NWP data help to improve the recognition of the surface PT'” Despite testing 33 parameters, it was found that a combination of the near-surface air temperature and the depth of the warm layer in the 0–1000 m above ground level (AGL) layer contains most of the signal needed to determine surface PT. The accrued probability of detection for liquid, solid, and mixed PTs according to the developed Random Forest model is 98.0%, 98.8%, and 67.3%, respectively. The application of the ML technique and data fusion approach allows to significantly improve the robustness of PT prediction compared to commonly used baseline models and provides promising results for operational forecasters.
      PubDate: 2021-01-14
      DOI: 10.1007/s00376-020-0165-9
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Heriot-Watt University
Edinburgh, EH14 4AS, UK
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