2023 Vol. 40, No. 5
Display Method:
2023, 40(5): 1-1.
Abstract:
2023, 40(5): 747-790.
doi: 10.1007/s00376-022-2077-3
Abstract:
Cloud microphysical processes occur at the smallest end of scales among cloud-related processes and thus must be parameterized not only in large-scale global circulation models (GCMs) but also in various higher-resolution limited-area models such as cloud-resolving models (CRMs) and large-eddy simulation (LES) models. Instead of giving a comprehensive review of existing microphysical parameterizations that have been developed over the years, this study concentrates purposely on several topics that we believe are understudied but hold great potential for further advancing bulk microphysics parameterizations: multi-moment bulk microphysics parameterizations and the role of the spectral shape of hydrometeor size distributions; discrete vs “continuous” representation of hydrometeor types; turbulence–microphysics interactions including turbulent entrainment–mixing processes and stochastic condensation; theoretical foundations for the mathematical expressions used to describe hydrometeor size distributions and hydrometeor morphology; and approaches for developing bulk microphysics parameterizations. Also presented are the spectral bin scheme and particle-based scheme (especially, super-droplet method) for representing explicit microphysics. Their advantages and disadvantages are elucidated for constructing cloud models with detailed microphysics that are essential to developing processes understanding and bulk microphysics parameterizations. Particle-resolved direct numerical simulation (DNS) models are described as an emerging technique to investigate turbulence–microphysics interactions at the most fundamental level by tracking individual particles and resolving the smallest turbulent eddies in turbulent clouds. Outstanding challenges and future research directions are explored as well.
Cloud microphysical processes occur at the smallest end of scales among cloud-related processes and thus must be parameterized not only in large-scale global circulation models (GCMs) but also in various higher-resolution limited-area models such as cloud-resolving models (CRMs) and large-eddy simulation (LES) models. Instead of giving a comprehensive review of existing microphysical parameterizations that have been developed over the years, this study concentrates purposely on several topics that we believe are understudied but hold great potential for further advancing bulk microphysics parameterizations: multi-moment bulk microphysics parameterizations and the role of the spectral shape of hydrometeor size distributions; discrete vs “continuous” representation of hydrometeor types; turbulence–microphysics interactions including turbulent entrainment–mixing processes and stochastic condensation; theoretical foundations for the mathematical expressions used to describe hydrometeor size distributions and hydrometeor morphology; and approaches for developing bulk microphysics parameterizations. Also presented are the spectral bin scheme and particle-based scheme (especially, super-droplet method) for representing explicit microphysics. Their advantages and disadvantages are elucidated for constructing cloud models with detailed microphysics that are essential to developing processes understanding and bulk microphysics parameterizations. Particle-resolved direct numerical simulation (DNS) models are described as an emerging technique to investigate turbulence–microphysics interactions at the most fundamental level by tracking individual particles and resolving the smallest turbulent eddies in turbulent clouds. Outstanding challenges and future research directions are explored as well.
2023, 40(5): 791-803.
doi: 10.1007/s00376-022-2136-9
Abstract:
Valuable dropsonde data were obtained from multiple field campaigns targeting tropical cyclones, namely Higos, Nangka, Saudel, and Atsani, over the western North Pacific by the Hong Kong Observatory and Taiwan Central Weather Bureau in 2020. The conditional nonlinear optimal perturbation (CNOP) method has been utilized in real-time to identify the sensitive regions for targeting observations adhering to the procedure of real-time field campaigns for the first time. The observing system experiments were conducted to evaluate the effect of dropsonde data and CNOP sensitivity on TC forecasts in terms of track and intensity, using the Weather Research and Forecasting model. It is shown that the impact of assimilating all dropsonde data on both track and intensity forecasts is case-dependent. However, assimilation using only the dropsonde data inside the sensitive regions displays unanimously positive effects on both the track and intensity forecast, either of which obtains comparable benefits to or greatly reduces deterioration of the skill when assimilating all dropsonde data. Therefore, these results encourage us to further carry out targeting observations for the forecast of tropical cyclones according to CNOP sensitivity.
Valuable dropsonde data were obtained from multiple field campaigns targeting tropical cyclones, namely Higos, Nangka, Saudel, and Atsani, over the western North Pacific by the Hong Kong Observatory and Taiwan Central Weather Bureau in 2020. The conditional nonlinear optimal perturbation (CNOP) method has been utilized in real-time to identify the sensitive regions for targeting observations adhering to the procedure of real-time field campaigns for the first time. The observing system experiments were conducted to evaluate the effect of dropsonde data and CNOP sensitivity on TC forecasts in terms of track and intensity, using the Weather Research and Forecasting model. It is shown that the impact of assimilating all dropsonde data on both track and intensity forecasts is case-dependent. However, assimilation using only the dropsonde data inside the sensitive regions displays unanimously positive effects on both the track and intensity forecast, either of which obtains comparable benefits to or greatly reduces deterioration of the skill when assimilating all dropsonde data. Therefore, these results encourage us to further carry out targeting observations for the forecast of tropical cyclones according to CNOP sensitivity.
2023, 40(5): 804-823.
doi: 10.1007/s00376-022-2029-y
Abstract:
A statistical analysis of the initial vortexes leading to tropical cyclone (TC) formation in the western North Pacific (WNP) is conducted with the ECMWF ERA5 reanalysis data from 1999 to 2018. It is found that TCs in the WNP basically originate from three kinds of vortexes, i.e., a mid-level vortex (MV), a low-level vortex (LV), and a relatively deep vortex with notable vorticity in both the lower and middle troposphere (DV). Among them, LV and DV account for 47.9% and 24.2% of tropical cyclogenesis events, respectively, while only 27.9% of TCs develop from the MV, which is much lower than that which occurs in the North Atlantic and eastern Pacific. Such a difference might be ascribed to the active monsoon systems in the WNP all year round. Due to the nearly upright structure of mid-level convergence in the early pre-genesis stage, TC genesis efficiency is the highest in DV. Compared with MV, LV generally takes a shorter time to intensify to a TC because of the higher humidity and the stronger low-level cyclonic circulation, which is related to air-sea interaction and boundary-layer convergence. Further examination of the relationship between tropical cyclogenesis and large-scale flow patterns indicate that the TC genesis events associated with LV are primarily related to the monsoon shear line, monsoon confluence region, and monsoon gyre, while those associated with MV are frequently connected with easterly waves and wave energy dispersion of preexisting TC. Compared with other flow patterns, tropical cyclones usually form and intensify faster in the monsoon confluence region.
A statistical analysis of the initial vortexes leading to tropical cyclone (TC) formation in the western North Pacific (WNP) is conducted with the ECMWF ERA5 reanalysis data from 1999 to 2018. It is found that TCs in the WNP basically originate from three kinds of vortexes, i.e., a mid-level vortex (MV), a low-level vortex (LV), and a relatively deep vortex with notable vorticity in both the lower and middle troposphere (DV). Among them, LV and DV account for 47.9% and 24.2% of tropical cyclogenesis events, respectively, while only 27.9% of TCs develop from the MV, which is much lower than that which occurs in the North Atlantic and eastern Pacific. Such a difference might be ascribed to the active monsoon systems in the WNP all year round. Due to the nearly upright structure of mid-level convergence in the early pre-genesis stage, TC genesis efficiency is the highest in DV. Compared with MV, LV generally takes a shorter time to intensify to a TC because of the higher humidity and the stronger low-level cyclonic circulation, which is related to air-sea interaction and boundary-layer convergence. Further examination of the relationship between tropical cyclogenesis and large-scale flow patterns indicate that the TC genesis events associated with LV are primarily related to the monsoon shear line, monsoon confluence region, and monsoon gyre, while those associated with MV are frequently connected with easterly waves and wave energy dispersion of preexisting TC. Compared with other flow patterns, tropical cyclones usually form and intensify faster in the monsoon confluence region.
2023, 40(5): 824-842.
doi: 10.1007/s00376-021-1172-1
Abstract:
The dominant frequency modes of pre-summer extreme precipitation events (EPEs) over South China (SC) between 1998 and 2018 were investigated. The 67 identified EPEs were all characterized by the 3–8-d (synoptic) frequency band. However, multiscale combined modes of the synoptic and three low-frequency bands [10 – 20-d (quasi-biweekly, QBW); 15–40-d (quasi-monthly, QM); and 20–60-d (intraseasonal)] accounted for the majority (63%) of the EPEs, and the precipitation intensity on the peak wet day was larger than that of the single synoptic mode. It was found that EPEs form within strong southwesterly anomalous flows characterized by either lower-level cyclonic circulation over SC or a deep trough over eastern China. Bandpass-filtered disturbances revealed the direct precipitating systems and their life cycles. Synoptic-scale disturbances are dominated by mid–high latitude troughs, and the cyclonic anomalies originate from downstream of the Tibetan Plateau (TP). Given the warm and moist climate state, synoptic-scale northeasterly flows can even induce EPEs. At the QBW and QM scales, the disturbances originate from the tropical Pacific, downstream of the TP, or mid–high latitudes (QBW only). Each is characterized by cyclonic–anticyclonic wave trains and intense southwesterly flows between them within a region of large horizontal pressure gradient. The intraseasonal disturbances are confined to tropical regions and influence SC by marginal southwesterly flows. It is concluded that low-frequency disturbances provide favorable background conditions for EPEs over SC and synoptic-scale disturbances ultimately induce EPEs on the peak wet days. Both should be simultaneously considered for EPE predictions over SC.
The dominant frequency modes of pre-summer extreme precipitation events (EPEs) over South China (SC) between 1998 and 2018 were investigated. The 67 identified EPEs were all characterized by the 3–8-d (synoptic) frequency band. However, multiscale combined modes of the synoptic and three low-frequency bands [10 – 20-d (quasi-biweekly, QBW); 15–40-d (quasi-monthly, QM); and 20–60-d (intraseasonal)] accounted for the majority (63%) of the EPEs, and the precipitation intensity on the peak wet day was larger than that of the single synoptic mode. It was found that EPEs form within strong southwesterly anomalous flows characterized by either lower-level cyclonic circulation over SC or a deep trough over eastern China. Bandpass-filtered disturbances revealed the direct precipitating systems and their life cycles. Synoptic-scale disturbances are dominated by mid–high latitude troughs, and the cyclonic anomalies originate from downstream of the Tibetan Plateau (TP). Given the warm and moist climate state, synoptic-scale northeasterly flows can even induce EPEs. At the QBW and QM scales, the disturbances originate from the tropical Pacific, downstream of the TP, or mid–high latitudes (QBW only). Each is characterized by cyclonic–anticyclonic wave trains and intense southwesterly flows between them within a region of large horizontal pressure gradient. The intraseasonal disturbances are confined to tropical regions and influence SC by marginal southwesterly flows. It is concluded that low-frequency disturbances provide favorable background conditions for EPEs over SC and synoptic-scale disturbances ultimately induce EPEs on the peak wet days. Both should be simultaneously considered for EPE predictions over SC.
2023, 40(5): 843-855.
doi: 10.1007/s00376-022-2133-z
Abstract:
The Sichuan-Tibet Railway, mainly located in the southeastern Qinghai-Tibet Plateau, is affected by summertime extreme precipitation (SEP). Using daily rain-gauge observations and ERA5 reanalysis data for the summers of 1979–2020, the spatiotemporal distribution characteristics of SEP in the key region of the Sichuan-Tibet Railway (28°–33°N, 90°–105°E, hereafter KR) are revealed, and the mechanism for SEP amount (SEPA) variation in the KR is investigated. The results show that SEPA in the KR contributes nearly 30% to the total summer precipitation. Regional differences are evident in SEP, justifying thresholds higher in the plateau-dominated central-western KR (CWKR) and lower in the basin-dominated eastern KR (EKR). In addition, SEP in the CWKR is less intense but more frequent than SEP in the EKR. During 1979–2020, the SEPA in the KR increased slightly while the SEPA in the CWKR increased significantly and peaked in the last decade. When anticyclonic circulation (AC) anomalies dominate the 500 hPa pattern over the Bay of Bengal and Mongolia, the southerly flow and cyclonic shear over the southeastern plateau will be strengthened, favoring more SEPA in the CWKR. When an AC anomaly dominates the 500 hPa pattern over the Bohai Sea, the low-level easterly wind over the basin will be strengthened, favoring more SEPA in the EKR. The strengthening of the ascent, water vapor convergence, and convective instability is conducive to more SEPA in the KR. Our results deepen the understanding of the characteristics and the physical mechanisms responsible for extreme precipitation in the KR.
The Sichuan-Tibet Railway, mainly located in the southeastern Qinghai-Tibet Plateau, is affected by summertime extreme precipitation (SEP). Using daily rain-gauge observations and ERA5 reanalysis data for the summers of 1979–2020, the spatiotemporal distribution characteristics of SEP in the key region of the Sichuan-Tibet Railway (28°–33°N, 90°–105°E, hereafter KR) are revealed, and the mechanism for SEP amount (SEPA) variation in the KR is investigated. The results show that SEPA in the KR contributes nearly 30% to the total summer precipitation. Regional differences are evident in SEP, justifying thresholds higher in the plateau-dominated central-western KR (CWKR) and lower in the basin-dominated eastern KR (EKR). In addition, SEP in the CWKR is less intense but more frequent than SEP in the EKR. During 1979–2020, the SEPA in the KR increased slightly while the SEPA in the CWKR increased significantly and peaked in the last decade. When anticyclonic circulation (AC) anomalies dominate the 500 hPa pattern over the Bay of Bengal and Mongolia, the southerly flow and cyclonic shear over the southeastern plateau will be strengthened, favoring more SEPA in the CWKR. When an AC anomaly dominates the 500 hPa pattern over the Bohai Sea, the low-level easterly wind over the basin will be strengthened, favoring more SEPA in the EKR. The strengthening of the ascent, water vapor convergence, and convective instability is conducive to more SEPA in the KR. Our results deepen the understanding of the characteristics and the physical mechanisms responsible for extreme precipitation in the KR.
2023, 40(5): 856-873.
doi: 10.1007/s00376-022-1435-5
Abstract:
Research on vertical motion in mesoscale systems is an extraordinarily challenging effort. Allowing for fewer assumptions, a new form of generalized vertical motion equation and a generalized Omega equation are derived in the Cartesian coordinate system (nonhydrostatic equilibrium) and the isobaric coordinate system (hydrostatic equilibrium), respectively. The terms on the right-hand side of the equations, which comprise the Q vector, are composed of three factors: dynamic, thermodynamic, and mass. A heavy rain event that occurred from 18 to 19 July 2021 in southern Xinjiang was selected to analyze the characteristics of the diagnostic variable in the generalized vertical motion equation (\begin{document}${{\boldsymbol{Q}}_z}$\end{document} ![]()
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Research on vertical motion in mesoscale systems is an extraordinarily challenging effort. Allowing for fewer assumptions, a new form of generalized vertical motion equation and a generalized Omega equation are derived in the Cartesian coordinate system (nonhydrostatic equilibrium) and the isobaric coordinate system (hydrostatic equilibrium), respectively. The terms on the right-hand side of the equations, which comprise the Q vector, are composed of three factors: dynamic, thermodynamic, and mass. A heavy rain event that occurred from 18 to 19 July 2021 in southern Xinjiang was selected to analyze the characteristics of the diagnostic variable in the generalized vertical motion equation (
2023, 40(5): 874-886.
doi: 10.1007/s00376-022-1319-8
Abstract:
During the pre-summer rainy season, heavy rainfall occurs frequently in South China. Based on polarimetric radar observations, the microphysical characteristics and processes of convective features associated with extreme rainfall rates (ERCFs) are examined. In the regions with high ERCF occurrence frequency, sub-regional differences are found in the lightning flash rate (LFR) distributions. In the region with higher LFRs, the ERCFs have larger volumes of high reflectivity factor above the freezing level, corresponding to more active riming processes. In addition, these ERCFs are more organized and display larger spatial coverage, which may be related to the stronger low-level wind shear and higher terrain in the region. In the region with lower LFRs, the ERCFs have lower echo tops and lower-echo centroids. However, no clear differences of the most unstable convective available potential energy (MUCAPE) exist in the ERCFs in the regions with different LFR characteristics. Regardless of the LFRs, raindrop collisional coalescence is the main process for the growth of raindrops in the ERCFs. In the ERCFs within the region with lower LFRs, the main mechanism for the rapid increase of liquid water content with decreasing altitude below 4 km is through the warm-rain processes converting cloud drops to raindrops. However, in those with higher LFRs, the liquid water content generally decreases with decreasing altitude.
During the pre-summer rainy season, heavy rainfall occurs frequently in South China. Based on polarimetric radar observations, the microphysical characteristics and processes of convective features associated with extreme rainfall rates (ERCFs) are examined. In the regions with high ERCF occurrence frequency, sub-regional differences are found in the lightning flash rate (LFR) distributions. In the region with higher LFRs, the ERCFs have larger volumes of high reflectivity factor above the freezing level, corresponding to more active riming processes. In addition, these ERCFs are more organized and display larger spatial coverage, which may be related to the stronger low-level wind shear and higher terrain in the region. In the region with lower LFRs, the ERCFs have lower echo tops and lower-echo centroids. However, no clear differences of the most unstable convective available potential energy (MUCAPE) exist in the ERCFs in the regions with different LFR characteristics. Regardless of the LFRs, raindrop collisional coalescence is the main process for the growth of raindrops in the ERCFs. In the ERCFs within the region with lower LFRs, the main mechanism for the rapid increase of liquid water content with decreasing altitude below 4 km is through the warm-rain processes converting cloud drops to raindrops. However, in those with higher LFRs, the liquid water content generally decreases with decreasing altitude.
2023, 40(5): 887-899.
doi: 10.1007/s00376-022-2082-6
Abstract:
Convective storms and lightning are among the most important weather phenomena that are challenging to forecast. In this study, a novel multi-task learning (MTL) encoder-decoder U-net neural network was developed to forecast convective storms and lightning with lead times for up to 90 min, using GOES-16 geostationary satellite infrared brightness temperatures (IRBTs), lightning flashes from Geostationary Lightning Mapper (GLM), and vertically integrated liquid (VIL) from Next Generation Weather Radar (NEXRAD). To cope with the heavily skewed distribution of lightning data, a spatiotemporal exponent-weighted loss function and log-transformed lightning normalization approach were developed. The effects of MTL, single-task learning (STL), and IRBTs as auxiliary input features on convection and lightning nowcasting were investigated. The results showed that normalizing the heavily skew-distributed lightning data along with a log-transformation dramatically outperforms the min-max normalization method for nowcasting an intense lightning event. The MTL model significantly outperformed the STL model for both lightning nowcasting and VIL nowcasting, particularly for intense lightning events. The MTL also helped delay the lightning forecast performance decay with the lead times. Furthermore, incorporating satellite IRBTs as auxiliary input features substantially improved lightning nowcasting, but produced little difference in VIL forecasting. Finally, the MTL model performed better for forecasting both lightning and the VIL of organized convective storms than for isolated cells.
Convective storms and lightning are among the most important weather phenomena that are challenging to forecast. In this study, a novel multi-task learning (MTL) encoder-decoder U-net neural network was developed to forecast convective storms and lightning with lead times for up to 90 min, using GOES-16 geostationary satellite infrared brightness temperatures (IRBTs), lightning flashes from Geostationary Lightning Mapper (GLM), and vertically integrated liquid (VIL) from Next Generation Weather Radar (NEXRAD). To cope with the heavily skewed distribution of lightning data, a spatiotemporal exponent-weighted loss function and log-transformed lightning normalization approach were developed. The effects of MTL, single-task learning (STL), and IRBTs as auxiliary input features on convection and lightning nowcasting were investigated. The results showed that normalizing the heavily skew-distributed lightning data along with a log-transformation dramatically outperforms the min-max normalization method for nowcasting an intense lightning event. The MTL model significantly outperformed the STL model for both lightning nowcasting and VIL nowcasting, particularly for intense lightning events. The MTL also helped delay the lightning forecast performance decay with the lead times. Furthermore, incorporating satellite IRBTs as auxiliary input features substantially improved lightning nowcasting, but produced little difference in VIL forecasting. Finally, the MTL model performed better for forecasting both lightning and the VIL of organized convective storms than for isolated cells.
2023, 40(5): 900-919.
doi: 10.1007/s00376-022-1252-x
Abstract:
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.
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.
2023, 40(5): 920-936.
doi: 10.1007/s00376-022-1380-3
Abstract:
Assimilation of the Advanced Geostationary Radiance Imager (AGRI) clear-sky radiance in a regional model is performed. The forecasting effectiveness of the assimilation of two water vapor (WV) channels with conventional observations for the “21·7” Henan extremely heavy rainfall is analyzed and compared with a baseline test that assimilates only conventional observations in this study. The results show that the 24-h cumulative precipitation forecast by the assimilation experiment with the addition of the AGRI exceeds 500 mm, compared to a maximum value of 532.6 mm measured by the national meteorological stations, and that the location of the maximum precipitation is consistent with the observations. The results for the short periods of intense precipitation processes are that the simulation of the location and intensity of the 3-h cumulative precipitation is also relatively accurate. The analysis increment shows that the main difference between the two sets of assimilation experiments is over the ocean due to the additional ocean observations provided by FY-4A, which compensates for the lack of ocean observations. The assimilation of satellite data adjusts the vertical and horizontal wind fields over the ocean by adjusting the atmospheric temperature and humidity, which ultimately results in a narrower and stronger WV transport path to the center of heavy precipitation in Zhengzhou in the lower troposphere. Conversely, the WV convergence and upward motion in the control experiment are more dispersed; therefore, the precipitation centers are also correspondingly more dispersed.
Assimilation of the Advanced Geostationary Radiance Imager (AGRI) clear-sky radiance in a regional model is performed. The forecasting effectiveness of the assimilation of two water vapor (WV) channels with conventional observations for the “21·7” Henan extremely heavy rainfall is analyzed and compared with a baseline test that assimilates only conventional observations in this study. The results show that the 24-h cumulative precipitation forecast by the assimilation experiment with the addition of the AGRI exceeds 500 mm, compared to a maximum value of 532.6 mm measured by the national meteorological stations, and that the location of the maximum precipitation is consistent with the observations. The results for the short periods of intense precipitation processes are that the simulation of the location and intensity of the 3-h cumulative precipitation is also relatively accurate. The analysis increment shows that the main difference between the two sets of assimilation experiments is over the ocean due to the additional ocean observations provided by FY-4A, which compensates for the lack of ocean observations. The assimilation of satellite data adjusts the vertical and horizontal wind fields over the ocean by adjusting the atmospheric temperature and humidity, which ultimately results in a narrower and stronger WV transport path to the center of heavy precipitation in Zhengzhou in the lower troposphere. Conversely, the WV convergence and upward motion in the control experiment are more dispersed; therefore, the precipitation centers are also correspondingly more dispersed.
2023, 40(5): 937-951.
doi: 10.1007/s00376-022-2056-8
Abstract:
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.
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.
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