49 research outputs found
Application and Evaluation of an Explicit Prognostic Cloud Cover Scheme in GRAPES Global Forecast System
An explicit prognostic cloudâcover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middleârange numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloudâcover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and largeâscale stratiform condensation processes. Our simulation results show that clouds in midâhigh latitudes arise mainly from largeâscale stratiform condensation processes, while cumulus convection and largeâscale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERAâInterim reanalysis data. The low, high, and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850 hPa and above 400 hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloudâcover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast
Acute and chronic health impacts of PM2.5 in China and the influence of interannual meteorological variability
High concentrations of PM2.5 in China have an adverse impact on human health and present a major problem for air quality control. Here we evaluate premature deaths attributable to chronic and acute exposure to ambient PM2.5 at different scales in China over 2013-2017 with an air quality model at 5âŻkm resolution and integrated exposure-response methods. We estimate that 1,210,000 (95% Confidence Interval: 720,000-1,750,000) premature deaths annually are attributable to chronic exposure to PM2.5 pollution. Chongqing exhibits the largest chronic per capita mortality (1.4â°) among all provinces. A total of 116,000 (64,000-170,000) deaths annually are attributable to acute exposure during pollution episodes over the period, with Hubei province showing the highest acute per capita mortality (0.15â°). We also find that in urban areas premature deaths are 520,000 (320,000-760,000) due to chronic and 55,000 (3,000-81,000) due to acute exposure, respectively. At a provincial level, the annual mean PM2.5 concentration varies by ±20% due to interannual variability in meteorology, and PM2.5-attributable chronic mortality varies by ±8%, and by >±5% and ±1% at a national level. Meteorological variability shows larger impacts on interannual variations in acute risks than that in chronic exposure at both provincial (>±20%) and national (±4%) levels. These findings emphasize that tighter controls of PM2.5 and precursor emissions are urgently needed, particularly under unfavorable meteorological conditions in China
Global-regional nested simulation of particle number concentration by combing microphysical processes with an evolving organic aerosol module
Aerosol microphysical processes are essential for the next generation of global and regional climate and air quality models to determine particle size distribution. The contribution of organic aerosols (OAs) to particle formation, mass, and number concentration is one of the major uncertainties in current models. A new globalâregional nested aerosol model was developed to simulate detailed microphysical processes. The model combines an advanced particle microphysics (APM) module and a volatility basis set (VBS) OA module to calculate the kinetic condensation of low-volatility organic compounds and equilibrium partitioning of semi-volatile organic compounds in a 3-D framework using globalâregional nested domain. In addition to the condensation of sulfuric acid, the equilibrium partitioning of nitrate and ammonium, and the coagulation process of particles, the microphysical processes of the OAs are realistically represented in our new model. The model uses high-resolution size bins to calculate the size distribution of new particles formed through nucleation and subsequent growth. The multi-scale nesting enables the model to perform high-resolution simulations of the particle formation processes in the urban atmosphere in the background of regional and global environments. By using the nested domains, the model reasonably reproduced the OA components obtained from the analysis of aerosol mass spectrometry measurements through positive matrix factorization and the particle number size distribution in the megacity of Beijing during a period of approximately a month. Anthropogenic organic species accounted for 67â% of the OAs of secondary particles formed by nucleation and subsequent growth, which is considerably larger than that of biogenic OAs. On the global scale, the model well predicted the particle number concentration in various environments. The microphysical module combined with the VBS simulated the universal distribution of organic components among the different aerosol populations. The model results strongly suggest the importance of anthropogenic organic species in aerosol particle formation and growth at polluted urban sites and over the whole globe.Aerosol microphysical processes are essential for the next generation of global and regional climate and air quality models to determine particle size distribution. The contribution of organic aerosols (OAs) to particle formation, mass, and number concentration is one of the major uncertainties in current models. A new global-regional nested aerosol model was developed to simulate detailed microphysical processes. The model combines an advanced particle microphysics (APM) module and a volatility basis set (VBS) OA module to calculate the kinetic condensation of low-volatility organic compounds and equilibrium partitioning of semi-volatile organic compounds in a 3-D framework using global-regional nested domain In addition to the condensation of sulfuric acid, the equilibrium partitioning of nitrate and ammonium, and the coagulation process of particles, the microphysical processes of the OAs are realistically represented in our new model. The model uses high-resolution size bins to calculate the size distribution of new particles formed through nucleation and subsequent growth. The multi-scale nesting enables the model to perform high-resolution simulations of the particle formation processes in the urban atmosphere in the background of regional and global environments. By using the nested domains, the model reasonably reproduced the OA components obtained from the analysis of aerosol mass spectrometry measurements through positive matrix factorization and the particle number size distribution in the megacity of Beijing during a period of approximately a month. Anthropogenic organic species accounted for 67 % of the OAs of secondary particles formed by nucleation and subsequent growth, which is considerably larger than that of biogenic OAs. On the global scale, the model well predicted the particle number concentration in various environments. The microphysical module combined with the VBS simulated the universal distribution of organic components among the different aerosol populations. The model results strongly suggest the importance of anthropogenic organic species in aerosol particle formation and growth at polluted urban sites and over the whole globe.Peer reviewe
Application and Evaluation of an Explicit Prognostic Cloud Cover Scheme in GRAPES Global Forecast System
An explicit prognostic cloudâcover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middleârange numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloudâcover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and largeâscale stratiform condensation processes. Our simulation results show that clouds in midâhigh latitudes arise mainly from largeâscale stratiform condensation processes, while cumulus convection and largeâscale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERAâInterim reanalysis data. The low, high, and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850 hPa and above 400 hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloudâcover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast
A 3D study on the amplification of regional haze and particle growth by local emissions
The role of new particle formation (NPF) events and their contribution to haze formation through subsequent growth in polluted megacities is still controversial. To improve the understanding of the sources, meteorological conditions, and chemistry behind air pollution, we performed simultaneous measurements of aerosol composition and particle number size distributions at ground level and at 260 m in central Beijing, China, during a total of 4 months in 2015-2017. Our measurements show a pronounced decoupling of gas-to-particle conversion between the two heights, leading to different haze processes in terms of particle size distributions and chemical compositions. The development of haze was initiated by the growth of freshly formed particles at both heights, whereas the more severe haze at ground level was connected directly to local primary particles and gaseous precursors leading to higher particle growth rates. The particle growth creates a feedback loop, in which a further development of haze increases the atmospheric stability, which in turn strengthens the persisting apparent decoupling between the two heights and increases the severity of haze at ground level. Moreover, we complemented our field observations with model analyses, which suggest that the growth of NPF-originated particles accounted up to similar to 60% of the accumulation mode particles in the Beijing-Tianjin-Hebei area during haze conditions. The results suggest that a reduction in anthropogenic gaseous precursors, suppressing particle growth, is a critical step for alleviating haze although the number concentration of freshly formed particles (3-40 nm) via NPF does not reduce after emission controls.Peer reviewe
Analogue Ensemble Averaging Method for Bias Correction of 2-m Temperature of the Medium-Range Forecasts in China
The 2-m temperature is one of the important meteorological elements, and improving the accuracy of medium- and long-term forecasts of the 2-m temperature is important. The similarity forecasting method is widely used as a calibration technique in the statistical postprocessing of numerical weather prediction (NWP). In this study, the analogue ensemble averaging method is used to correct the deterministic forecast of the 2-m temperature with a forecast lead time from 180 h to 348 h using the CMA-GEPS model. The bias, mean absolute error (MAE), and root mean square error (RMSE) are used as the evaluation metrics. In comparison with NWP, the systematic error of the model for 2-m temperature is effectively reduced during each forecast period when using the analogue ensemble averaging method. In addition, the differences in forecast errors between regions are reduced, and the accuracy of 2-m temperature forecasts over complex terrain, especially in Southwest China, Northwest China, and North China, is improved using this method. In the future, there is certainly potential to apply the analogue ensemble averaging method to the bias correction of medium- and long-term forecasts of more meteorological elements
Analogue Ensemble Averaging Method for Bias Correction of 2-m Temperature of the Medium-Range Forecasts in China
The 2-m temperature is one of the important meteorological elements, and improving the accuracy of medium- and long-term forecasts of the 2-m temperature is important. The similarity forecasting method is widely used as a calibration technique in the statistical postprocessing of numerical weather prediction (NWP). In this study, the analogue ensemble averaging method is used to correct the deterministic forecast of the 2-m temperature with a forecast lead time from 180 h to 348 h using the CMA-GEPS model. The bias, mean absolute error (MAE), and root mean square error (RMSE) are used as the evaluation metrics. In comparison with NWP, the systematic error of the model for 2-m temperature is effectively reduced during each forecast period when using the analogue ensemble averaging method. In addition, the differences in forecast errors between regions are reduced, and the accuracy of 2-m temperature forecasts over complex terrain, especially in Southwest China, Northwest China, and North China, is improved using this method. In the future, there is certainly potential to apply the analogue ensemble averaging method to the bias correction of medium- and long-term forecasts of more meteorological elements
A Comparative Study on the Construction Model of Traditional Chinese Medicine Tourism in Sichuan Province - Based on the Perspective of Industrial Integration
Traditional Chinese medicine (TCM) tourism is a new industry formed by the integration and development of Chinese herbal medicine industry and tourism industry, and an in-depth analysis of its model is helpful to explore its general development law. In this paper, the commonalities, differences and development effects of two TCM tourism construction modes, namely, characteristic town construction type and industry platform construction type in Sichuan Province, are compared and analyzed. The study concludes that three points are needed to promote the development of TCM tourism: (1) correctly understanding the basic conditions of construction subjects and promote the development of TCM tourism according to local conditions; (2) taking diversified organizational structure as a breakthrough point and build a cluster of TCM tourism development enterprises; (3) Being focus on the four-dimensional organic integration of industry, city and humanities to form a unique cultural expression of TCM tourism
The Influence of the Configuration Effect of Social Capital and Knowledge Absorptive Capacity on the Cooperation Intensity of Cooperatives Participating in Agricultural Industrialization Consortia
Agricultural industrialization consortia fully realize the organizational advantages of division of labor, risk sharing, and benefit sharing, which mainly rely on close cooperation of members under integrated governance, but the current influence mechanism on the intensity of cooperation is yet to be explored in depth. Using 40 member cooperatives of agricultural industrialization consortia in Sichuan Province as research samples, this paper explores the mechanism by which the configuration effects of five conditional factors at the levels of social capital and knowledge absorptive capacity can generate different cooperative intensity of cooperative participation in consortia using fuzzy set qualitative comparative analysis. It was found that (1) the driving mechanism of high cooperative intensity of cooperatives was divided into three paths; (2) the driving mechanism of non-high cooperative intensity of cooperatives was divided into two paths and had an asymmetric relationship with the driving mechanism of high cooperative intensity of cooperatives. The findings of this paper help to expand the research perspective on cooperative intensity at the level of social capital and knowledge absorptive capacity configuration, and provide useful insights for improving the cooperative intensity of cooperative participation in consortia and the cooperative tightness among consortium members