2021 Vol. 27, No. 4
2021, 27(4): .
Abstract:
2021, 27(4): 319-329.
doi: 10.46267/j.1006-8775.2021.028
Abstract:
To support short-range weather forecasts, a high-resolution model (1km) is developed and technically upgraded in the South China Regional Center, including the improvement of the 3D reference scheme and the predictor-corrector method for semi-implicit semi-Lagrangian (SISL) in model dynamical core, as well as the improvement of physical parameterization. Furthermore, the multi-process parallel I/O and parallel nudging techniques are developed and have facilitated rapid updating in the assimilation prediction system and fast-output post processing process. The experimental results show that the improved 3D reference scheme and upgraded physic schemes can effectively improve the prediction accuracy and stability with a longer integration time step. The batch test shows that the precipitation forecast performance of 1-km model is significantly better than that of 3-km model. The 1-km model is in operation with a rapidly updating cycle at 12-minute intervals, which can be applied to short-range forecasts and nowcasting.
To support short-range weather forecasts, a high-resolution model (1km) is developed and technically upgraded in the South China Regional Center, including the improvement of the 3D reference scheme and the predictor-corrector method for semi-implicit semi-Lagrangian (SISL) in model dynamical core, as well as the improvement of physical parameterization. Furthermore, the multi-process parallel I/O and parallel nudging techniques are developed and have facilitated rapid updating in the assimilation prediction system and fast-output post processing process. The experimental results show that the improved 3D reference scheme and upgraded physic schemes can effectively improve the prediction accuracy and stability with a longer integration time step. The batch test shows that the precipitation forecast performance of 1-km model is significantly better than that of 3-km model. The 1-km model is in operation with a rapidly updating cycle at 12-minute intervals, which can be applied to short-range forecasts and nowcasting.
2021, 27(4): 330-345.
doi: 10.46267/j.1006-8775.2021.029
Abstract:
Large-scale atmospheric information plays an important role in the regional model for the forecasts of weather such as tropical cyclone (TC). However, it is difficult to be fully represented in regional models due to domain size and a lack of observation data, particularly at sea used in regional data assimilation. Blending analysis has been developed and implemented in regional models to reintroduce large-scale information from global model to regional analysis. Research of the impact of this large-scale blending scheme for the Global/Regional Assimilation and PrEdiction System (CMA-MESO) regional model on TC forecasting is limited and this study attempts to further progress by examining the adaptivity of the blending scheme using the two-dimensional Discrete Cosine Transform (2D-DCT) filter on the model forecast of Typhoon Haima over Shenzhen, China in 2016 and considering various cut-off wavelengths. Results showed that the error of the 24-hour typhoon track forecast can be reduced to less than 25 km by applying the scale-dependent blending scheme, indicating that the blending analysis is effectively able to minimise the large-scale bias for the initial fields. The improvement of the wind forecast is more evident for u-wind component according to the reduced root mean square errors (RMSEs) by comparing the experiments with and without blending analysis. Furthermore, the higher equitable threat score (ETS) provided implications that the precipitation prediction skills were increased in the 24h forecast by improving the representation of the large-scale feature in the CMA-MESO analysis. Furthermore, significant differences of the track error forecast were found by applying the blending analysis with different cut-off wavelengths from 400 km to 1200 km and the track error can be reduced less than by 10 km with 400 km cut-off wavelength in the first 6h forecast. It highlighted that the blending scheme with dynamic cut-off wavelengths adapted to the development of different TC systems is necessary in order to optimally introduce and ingest the large-scale information from global model to the regional model for improving the TC forecast. In this paper, the methods and data applied in this study will be firstly introduced, before discussion of the results regarding the performance of the blending analysis and its impacts on the wind and precipitation forecast correspondingly, followed by the discussion of the effects of different blending scheme on TC forecasts and the conclusion section.
2021, 27(4): 346-354.
doi: 10.46267/j.1006-8775.2021.030
Abstract:
The global three-dimensional variational (3D-Var) data assimilation is implemented on a new quasi-uniform overset (Yin-Yang) grid on sphere. As a quasi-uniform spherical grid, it covers the sphere by overlapping two perpendicularly oriented grid components which is nothing but low latitude region of the usual latitude-longitude grid. Based on this characteristic of the Yin-Yang grid, it enables us to implement the regional 3D-Var system efficiently and accurately on the Yin or Yang component grid, respectively. The global analysis could update directly from the regional analysis since they have the same configurations like the precondition of eigenvalue decomposition for vertical direction, recursive filtering for horizontal direction, minimization method and observation operator and so on. However, the balance equation and vector wind are needed to be paid more attention on the Yin grid analysis due to its coordinate transformation. How to spread the observation information near the boundary of Yin and Yang grid is a key to the 3D-Var analysis. Extending double the horizontal correlation length distance in the overset boundary of Yin and Yang grid has successfully solved the problem. The results show that the analysis on the Yin-Yang grid is reasonable and similar to the result on the latitude-longitude (LAT-LON) grid. This paper provides a promising strategy for the development of a 3D-Var global system for overset grids.
The global three-dimensional variational (3D-Var) data assimilation is implemented on a new quasi-uniform overset (Yin-Yang) grid on sphere. As a quasi-uniform spherical grid, it covers the sphere by overlapping two perpendicularly oriented grid components which is nothing but low latitude region of the usual latitude-longitude grid. Based on this characteristic of the Yin-Yang grid, it enables us to implement the regional 3D-Var system efficiently and accurately on the Yin or Yang component grid, respectively. The global analysis could update directly from the regional analysis since they have the same configurations like the precondition of eigenvalue decomposition for vertical direction, recursive filtering for horizontal direction, minimization method and observation operator and so on. However, the balance equation and vector wind are needed to be paid more attention on the Yin grid analysis due to its coordinate transformation. How to spread the observation information near the boundary of Yin and Yang grid is a key to the 3D-Var analysis. Extending double the horizontal correlation length distance in the overset boundary of Yin and Yang grid has successfully solved the problem. The results show that the analysis on the Yin-Yang grid is reasonable and similar to the result on the latitude-longitude (LAT-LON) grid. This paper provides a promising strategy for the development of a 3D-Var global system for overset grids.
2021, 27(4): 355-367.
doi: 10.46267/j.1006-8775.2021.031
Abstract:
The role of sea surface temperature (SST) forcing in the development and predictability of tropical cyclone (TC) intensity is examined using a large set of idealized numerical experiments in the Weather Research and Forecasting (WRF) model. The results indicate that the onset time of rapid intensification of TC gradually decreases, and the peak intensity of TC gradually increases, with the increased magnitude of SST. The predictability limits of the maximum 10 m wind speed (MWS) and minimum sea level pressure (MSLP) are ~72 and ~84 hours, respectively. Comparisons of the analyses of variance for different simulation time confirm that the MWS and MSLP have strong signal-to-noise ratios (SNR) from 0-72 hours and a marked decrease beyond 72 hours. For the horizontal and vertical structures of wind speed, noticeable decreases in the magnitude of SNR can be seen as the simulation time increases, similar to that of the SLP or perturbation pressure. These results indicate that the SST as an external forcing signal plays an important role in TC intensity for up to 72 hours, and it is significantly weakened if the simulation time exceeds the predictability limits of TC intensity.
The role of sea surface temperature (SST) forcing in the development and predictability of tropical cyclone (TC) intensity is examined using a large set of idealized numerical experiments in the Weather Research and Forecasting (WRF) model. The results indicate that the onset time of rapid intensification of TC gradually decreases, and the peak intensity of TC gradually increases, with the increased magnitude of SST. The predictability limits of the maximum 10 m wind speed (MWS) and minimum sea level pressure (MSLP) are ~72 and ~84 hours, respectively. Comparisons of the analyses of variance for different simulation time confirm that the MWS and MSLP have strong signal-to-noise ratios (SNR) from 0-72 hours and a marked decrease beyond 72 hours. For the horizontal and vertical structures of wind speed, noticeable decreases in the magnitude of SNR can be seen as the simulation time increases, similar to that of the SLP or perturbation pressure. These results indicate that the SST as an external forcing signal plays an important role in TC intensity for up to 72 hours, and it is significantly weakened if the simulation time exceeds the predictability limits of TC intensity.
2021, 27(4): 368-377.
doi: 10.46267/j.1006-8775.2021.032
Abstract:
Blacklist methods are used in the CMA Global Forecasting System (CMA-GFS) to improve the application of aircraft temperature data to numerical weather prediction in the Northern Hemisphere and the tropics. In this paper, the ERA5 re-analysis data are used to analyze aircraft temperature observation errors of each aircraft and a blacklist is established using pre-quality controls and threshold methods. The blacklist-filtered and blacklisted aircraft temperature data are then applied to the four-dimensional variational assimilation system, respectively, and an assimilation cycle forecast for the period from September 1 to 30, 2019 is carried out. The results show an uneven distribution in the global aircraft blacklist data. After the application of the blacklist methods, the RMSE of geopotential height and temperature analysis field decrease in the vertical direction by a maximum of ~ 1.5 gpm at 200 hPa and ~ 0.15 K at 250 hPa, respectively. Overall, the blacklist methods of aircraft temperature data improve the analysis and forecast in the CMA-GFS.
Blacklist methods are used in the CMA Global Forecasting System (CMA-GFS) to improve the application of aircraft temperature data to numerical weather prediction in the Northern Hemisphere and the tropics. In this paper, the ERA5 re-analysis data are used to analyze aircraft temperature observation errors of each aircraft and a blacklist is established using pre-quality controls and threshold methods. The blacklist-filtered and blacklisted aircraft temperature data are then applied to the four-dimensional variational assimilation system, respectively, and an assimilation cycle forecast for the period from September 1 to 30, 2019 is carried out. The results show an uneven distribution in the global aircraft blacklist data. After the application of the blacklist methods, the RMSE of geopotential height and temperature analysis field decrease in the vertical direction by a maximum of ~ 1.5 gpm at 200 hPa and ~ 0.15 K at 250 hPa, respectively. Overall, the blacklist methods of aircraft temperature data improve the analysis and forecast in the CMA-GFS.
2021, 27(4): 378-392.
doi: 10.46267/j.1006-8775.2021.033
Abstract:
The surface flux exchange associated with the exchange coefficients and upper ocean conditions is essential to the development of tropical cyclones (TCs). Using the Weather Research and Forecasting (WRF) model, the present study has investigated the impact of exchange coefficients and ocean coupling during Super Typhoon Saomai (2006). Firstly, two experiments with different formula of roughness are conducted. The experiment with the Donelan formula for drag coefficient (Cd) and ramped formula for enthalpy coefficient (Ck) can simulate stronger intensity compared to other experiments due to the increased surface wind and enthalpy fluxes. That is because the new formulas allows for a smaller Cd and larger Ck in the high wind regime than the former formulas did. Moreover, two coupled simulations between WRF and a one-dimensional ocean model are conducted to examine the feedback of sea surface cooling to the TC. In the experiments with a horizontal uniform mixed layer depth of 70 m, the sea surface cooling is too weak to change the evolution of TC. While in the experiment with an input mixed layer calculated using the Hybrid Coordinate Ocean Model (HYCOM) data, the significant sea surface cooling induces obvious impact on TC intensity and structure. Under the negative feedback of sea surface cooling, the sensible and latent heat fluxes decreases, especially in the right part of Saomai (2006). The negative feedback with coupled ocean model plays a vital role in simulating the intensity and structure of TC.
The surface flux exchange associated with the exchange coefficients and upper ocean conditions is essential to the development of tropical cyclones (TCs). Using the Weather Research and Forecasting (WRF) model, the present study has investigated the impact of exchange coefficients and ocean coupling during Super Typhoon Saomai (2006). Firstly, two experiments with different formula of roughness are conducted. The experiment with the Donelan formula for drag coefficient (Cd) and ramped formula for enthalpy coefficient (Ck) can simulate stronger intensity compared to other experiments due to the increased surface wind and enthalpy fluxes. That is because the new formulas allows for a smaller Cd and larger Ck in the high wind regime than the former formulas did. Moreover, two coupled simulations between WRF and a one-dimensional ocean model are conducted to examine the feedback of sea surface cooling to the TC. In the experiments with a horizontal uniform mixed layer depth of 70 m, the sea surface cooling is too weak to change the evolution of TC. While in the experiment with an input mixed layer calculated using the Hybrid Coordinate Ocean Model (HYCOM) data, the significant sea surface cooling induces obvious impact on TC intensity and structure. Under the negative feedback of sea surface cooling, the sensible and latent heat fluxes decreases, especially in the right part of Saomai (2006). The negative feedback with coupled ocean model plays a vital role in simulating the intensity and structure of TC.
2021, 27(4): 393-405.
doi: 10.46267/j.1006-8775.2021.034
Abstract:
During the movement of Typhoon Hato (2017) over land, heavy rainfall occurred when the spiral rainband which was about 100 km distance away from the center of the typhoon passed the Dayao Mountain (with an elevation of 1.2 km). In this study, the structures and forming mechanism of the heavy rainband along the mountain range are investigated by using high-resolution model simulations. The results show the importance of topography in causing the heavy rainband. Upslope of the steep terrain lifts the cyclonic flow to produce strong upward motion when the rainband passes across with high wind speed. At the same time, the warm and humid air is lifted to the steep slope, causing unstable energy to accumulate over the windward slope, which is conducive to the occurrence of rainfall. In particular, the convective cells generated upstream of rainband will further strengthen and develop due to the uplift when they move close to the mountain foot. Some precipitation particles in the convective cells fall to the ground while others move downstream with the intense updrafts, forming heavy rainfall near the summit. As a result, the largest accumulative rainfall coincides well with the orientation of the mountain ridge.
During the movement of Typhoon Hato (2017) over land, heavy rainfall occurred when the spiral rainband which was about 100 km distance away from the center of the typhoon passed the Dayao Mountain (with an elevation of 1.2 km). In this study, the structures and forming mechanism of the heavy rainband along the mountain range are investigated by using high-resolution model simulations. The results show the importance of topography in causing the heavy rainband. Upslope of the steep terrain lifts the cyclonic flow to produce strong upward motion when the rainband passes across with high wind speed. At the same time, the warm and humid air is lifted to the steep slope, causing unstable energy to accumulate over the windward slope, which is conducive to the occurrence of rainfall. In particular, the convective cells generated upstream of rainband will further strengthen and develop due to the uplift when they move close to the mountain foot. Some precipitation particles in the convective cells fall to the ground while others move downstream with the intense updrafts, forming heavy rainfall near the summit. As a result, the largest accumulative rainfall coincides well with the orientation of the mountain ridge.
2021, 27(4): 406-417.
doi: 10.46267/j.1006-8775.2021.035
Abstract:
In the present study, the performances of the NWP models on two heavy rainfalls on 20 July and 22 August 2021 over Henan Province were investigated. The impacts of the water vapor transport to the extreme rainfall were further discussed. The results showed that the regional model system in the Guangzhou Meteorological Service generally showed high scores on the extreme rainfall over Henan. The maximum 24h accumulative rainfall by the 24h forecasts by the CMA-GD reached 556 mm over Henan Province. The 24-h and 48-h Threat Score (TS) of heavy rainfall reached 0.56 and 0.64. The comparisons of the Fraction Skill Score (FSS) verifications of the heavy rainfall by CMA-GD and CMA-TRAMS at the radium of 40km reached 0.96 and 0.87. The water vapor transport to the extreme rainfall showed that the vertically integrated water vapor transport (IVT) of the whole layer before the occurrence of the heavy rainfall exhibited a double-eyes distribution in case 7 · 20. The north eye over Henan reached the same magnitude of IVT as the typhoon eye (Cempaka) over south China. The IVT over the lower troposphere (< 500 hPa) showed an overwhelming magnitude than the upper level, especially in the planetary boundary layer (< 700 hPa). More practical technique needs to be developed to improve its performances on the forecasting of extreme rainfall, as well as more experiments need to be conducted to examine the effects of the specific terrain and physical schemes on the extreme rainfall.
In the present study, the performances of the NWP models on two heavy rainfalls on 20 July and 22 August 2021 over Henan Province were investigated. The impacts of the water vapor transport to the extreme rainfall were further discussed. The results showed that the regional model system in the Guangzhou Meteorological Service generally showed high scores on the extreme rainfall over Henan. The maximum 24h accumulative rainfall by the 24h forecasts by the CMA-GD reached 556 mm over Henan Province. The 24-h and 48-h Threat Score (TS) of heavy rainfall reached 0.56 and 0.64. The comparisons of the Fraction Skill Score (FSS) verifications of the heavy rainfall by CMA-GD and CMA-TRAMS at the radium of 40km reached 0.96 and 0.87. The water vapor transport to the extreme rainfall showed that the vertically integrated water vapor transport (IVT) of the whole layer before the occurrence of the heavy rainfall exhibited a double-eyes distribution in case 7 · 20. The north eye over Henan reached the same magnitude of IVT as the typhoon eye (Cempaka) over south China. The IVT over the lower troposphere (< 500 hPa) showed an overwhelming magnitude than the upper level, especially in the planetary boundary layer (< 700 hPa). More practical technique needs to be developed to improve its performances on the forecasting of extreme rainfall, as well as more experiments need to be conducted to examine the effects of the specific terrain and physical schemes on the extreme rainfall.
2021, 27(4): 418-427.
doi: 10.46267/j.1006-8775.2021.036
Abstract:
Extreme rainfall is common from May to October in south China. This study investigates the key deviation of initial fields on ensemble forecast of a persistent heavy rainfall event from May 20 to 22, 2020 in Guangdong Province, south China by comparing ensemble members with different performances. Based on the rainfall distribution and pattern, two types are selected for analysis compared with the observed precipitation. Through the comparison of the thermal and dynamic fields in the middle and lower layers, it can be found that the thermal difference between the middle and lower layers was an important factor which led to the deviation of precipitation distribution. The dynamic factors also have some effects on the precipitation area although they were not as important as the thermal factors in this case. Correlating accumulated precipitation with atmospheric state variables further corroborates the above conclusion. This study suggests that the uncertainty of the thermal and dynamic factors in the numerical model can have a strong impact on the quantitative skills of heavy rainfall forecasts.
Extreme rainfall is common from May to October in south China. This study investigates the key deviation of initial fields on ensemble forecast of a persistent heavy rainfall event from May 20 to 22, 2020 in Guangdong Province, south China by comparing ensemble members with different performances. Based on the rainfall distribution and pattern, two types are selected for analysis compared with the observed precipitation. Through the comparison of the thermal and dynamic fields in the middle and lower layers, it can be found that the thermal difference between the middle and lower layers was an important factor which led to the deviation of precipitation distribution. The dynamic factors also have some effects on the precipitation area although they were not as important as the thermal factors in this case. Correlating accumulated precipitation with atmospheric state variables further corroborates the above conclusion. This study suggests that the uncertainty of the thermal and dynamic factors in the numerical model can have a strong impact on the quantitative skills of heavy rainfall forecasts.
2021, 27(4): 428-436.
doi: 10.46267/j.1006-8775.2021.037
Abstract:
This paper proposes a simple and powerful optimal integration (OPI) method for improving hourly quantitative precipitation forecasts (QPFs, 0-24 h) of a single-model by integrating the benefits of different biascorrected methods using the high-resolution CMA-GD model from the Guangzhou Institute of Tropical and Marine Meteorology of China Meteorological Administration (CMA). Three techniques are used to generate multi-method calibrated members for OPI: deep neural network (DNN), frequency-matching (FM), and optimal threat score (OTS). The results are as follows: (1) The QPF using DNN follows the basic physical patterns of CMA-GD. Despite providing superior improvements for clear-rainy and weak precipitation, DNN cannot improve the predictions for severe precipitation, while OTS can significantly strengthen these predictions. As a result, DNN and OTS are the optimal members to be incorporated into OPI. (2) Our new approach achieves state-of-the-art performances on a single model for all magnitudes of precipitation. Compared with the CMA-GD, OPI improves the TS by 2.5%, 5.4%, 7.8%, 8.3%, and 6.1% for QPFs from clear-rainy to rainstorms in the verification dataset. Moreover, OPI shows good stability in the test dataset. (3) It is also noted that the rainstorm pattern of OPI relies heavily on the original model and that OPI cannot correct for deviations in the location of severe precipitation. Therefore, improvements in predicting severe precipitation using this method should be further realized by improving the numerical model's forecasting capability.
This paper proposes a simple and powerful optimal integration (OPI) method for improving hourly quantitative precipitation forecasts (QPFs, 0-24 h) of a single-model by integrating the benefits of different biascorrected methods using the high-resolution CMA-GD model from the Guangzhou Institute of Tropical and Marine Meteorology of China Meteorological Administration (CMA). Three techniques are used to generate multi-method calibrated members for OPI: deep neural network (DNN), frequency-matching (FM), and optimal threat score (OTS). The results are as follows: (1) The QPF using DNN follows the basic physical patterns of CMA-GD. Despite providing superior improvements for clear-rainy and weak precipitation, DNN cannot improve the predictions for severe precipitation, while OTS can significantly strengthen these predictions. As a result, DNN and OTS are the optimal members to be incorporated into OPI. (2) Our new approach achieves state-of-the-art performances on a single model for all magnitudes of precipitation. Compared with the CMA-GD, OPI improves the TS by 2.5%, 5.4%, 7.8%, 8.3%, and 6.1% for QPFs from clear-rainy to rainstorms in the verification dataset. Moreover, OPI shows good stability in the test dataset. (3) It is also noted that the rainstorm pattern of OPI relies heavily on the original model and that OPI cannot correct for deviations in the location of severe precipitation. Therefore, improvements in predicting severe precipitation using this method should be further realized by improving the numerical model's forecasting capability.
2021, 27(4): 437-446.
doi: 10.46267/j.1006-8775.2021.038
Abstract:
Based on the daily maximum air temperature (Tmax) data from the China Meteorological Data Network and the NCEP/DOE reanalysis data, the intra-seasonal circulation and evolution of an extreme high temperature event (EHTE) in the middle reaches of the Yangtze River (MYR) from August 9-21, 2011 were explored, as well as the influence of diabatic heating on the position variation of the Western Pacific subtropical high (WPSH). Results show that the daily Tmax in the MYR exhibits a vigorous intraseasonal oscillation (ISO) of 10-25 days in the extended summer of 1980-2018. The main factors affecting the EHTE in the summer of 2011 are the low-frequency wave train propagating southeastward in the mid-latitude of the upper troposphere and the low-frequency anticyclone moving northwestward in the lowlatitude of the mid-lower troposphere. The diagnosis of 925hPa thermodynamic equation indicates that the ISO features of the Tmax in the core region is determined by the intra-seasonal variation of the adiabatic variation. In addition, the variations of the WPSH correspond well to the distribution of apparent heat source. In the early stage of the high temperature process, the apparent heat source in the north of the Bay of Bengal is a certain indicator for the westward extension of the WPSH.
Based on the daily maximum air temperature (Tmax) data from the China Meteorological Data Network and the NCEP/DOE reanalysis data, the intra-seasonal circulation and evolution of an extreme high temperature event (EHTE) in the middle reaches of the Yangtze River (MYR) from August 9-21, 2011 were explored, as well as the influence of diabatic heating on the position variation of the Western Pacific subtropical high (WPSH). Results show that the daily Tmax in the MYR exhibits a vigorous intraseasonal oscillation (ISO) of 10-25 days in the extended summer of 1980-2018. The main factors affecting the EHTE in the summer of 2011 are the low-frequency wave train propagating southeastward in the mid-latitude of the upper troposphere and the low-frequency anticyclone moving northwestward in the lowlatitude of the mid-lower troposphere. The diagnosis of 925hPa thermodynamic equation indicates that the ISO features of the Tmax in the core region is determined by the intra-seasonal variation of the adiabatic variation. In addition, the variations of the WPSH correspond well to the distribution of apparent heat source. In the early stage of the high temperature process, the apparent heat source in the north of the Bay of Bengal is a certain indicator for the westward extension of the WPSH.
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