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- Author or Editor: Rong Zhang x
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Abstract
The amplitude asymmetry between El Niño and La Niña is investigated by diagnosing the mixed-layer heat budget during the ENSO developing phase by using the three ocean assimilation products: Simple Ocean Data Assimilation (SODA) 2.0.2, SODA 1.4.2, and the Global Ocean Data Assimilation System (GODAS). It is found that the nonlinear zonal and meridional ocean temperature advections are essential to cause the asymmetry in the far eastern Pacific, whereas the vertical nonlinear advection has the opposite effect. The zonal current anomaly is dominated by the geostrophic current in association with the thermocline depth variation. The meridional current anomaly is primarily attributed to the Ekman current driven by wind stress forcing. The resulting induced anomalous horizontal currents lead to warm nonlinear advection during both El Niño and La Niña episodes and thus strengthen (weaken) the El Niño (La Niña) amplitude. The convergence (divergence) of the anomalous geostrophic mixed-layer currents during El Niño (La Niña) results in anomalous downwelling (upwelling) in the far eastern equatorial Pacific, which leads to a cold nonlinear vertical advection in both warm and cold episodes.
Abstract
The amplitude asymmetry between El Niño and La Niña is investigated by diagnosing the mixed-layer heat budget during the ENSO developing phase by using the three ocean assimilation products: Simple Ocean Data Assimilation (SODA) 2.0.2, SODA 1.4.2, and the Global Ocean Data Assimilation System (GODAS). It is found that the nonlinear zonal and meridional ocean temperature advections are essential to cause the asymmetry in the far eastern Pacific, whereas the vertical nonlinear advection has the opposite effect. The zonal current anomaly is dominated by the geostrophic current in association with the thermocline depth variation. The meridional current anomaly is primarily attributed to the Ekman current driven by wind stress forcing. The resulting induced anomalous horizontal currents lead to warm nonlinear advection during both El Niño and La Niña episodes and thus strengthen (weaken) the El Niño (La Niña) amplitude. The convergence (divergence) of the anomalous geostrophic mixed-layer currents during El Niño (La Niña) results in anomalous downwelling (upwelling) in the far eastern equatorial Pacific, which leads to a cold nonlinear vertical advection in both warm and cold episodes.
Abstract
In this work, the variability of summer [June–August (JJA)] rainfall in northeast China is examined and its predictors are identified based on observational analyses and atmospheric modeling experiments. At interannual time scales, the summer rainfall anomaly in northeast China is significantly correlated with the rainfall anomaly over the Huang-Huai region (32°–38°N, 105°–120°E) in late spring (April–May). Compared with climatology, an earlier (later) rainy season in the Huang-Huai region favors a wet (dry) summer in northeast China. Also, this connection has strengthened since the late 1970s. In addition to the impact of the sea surface temperature anomaly (SSTA) in the tropical Indian Ocean, the local soil moisture anomalies caused by the rainfall anomaly in the Huang-Huai region in late spring generate summer general circulation anomalies, which contribute to the rainfall anomaly in northeast China. As a result, when compared with the SSTA, the rainfall anomaly in the Huang-Huai region in late spring can be used as another and even better predictor for the summer rainfall anomaly in northeast China.
The results from atmospheric general circulation model experiments forced by observed SST confirm the diagnostic results to some extent, including the connection of the rainfall anomaly between the Huang-Huai region in April–May and northeastern China in JJA as well as the influence from SSTA in the tropical Indian Ocean. It is shown that eliminating the internal dynamical processes by using the ensemble mean intensifies the connection, implying that the connection of rainfall variation in the two different seasons/regions may be partially caused by the external forcing (e.g., SSTA in the tropical Indian Ocean).
Abstract
In this work, the variability of summer [June–August (JJA)] rainfall in northeast China is examined and its predictors are identified based on observational analyses and atmospheric modeling experiments. At interannual time scales, the summer rainfall anomaly in northeast China is significantly correlated with the rainfall anomaly over the Huang-Huai region (32°–38°N, 105°–120°E) in late spring (April–May). Compared with climatology, an earlier (later) rainy season in the Huang-Huai region favors a wet (dry) summer in northeast China. Also, this connection has strengthened since the late 1970s. In addition to the impact of the sea surface temperature anomaly (SSTA) in the tropical Indian Ocean, the local soil moisture anomalies caused by the rainfall anomaly in the Huang-Huai region in late spring generate summer general circulation anomalies, which contribute to the rainfall anomaly in northeast China. As a result, when compared with the SSTA, the rainfall anomaly in the Huang-Huai region in late spring can be used as another and even better predictor for the summer rainfall anomaly in northeast China.
The results from atmospheric general circulation model experiments forced by observed SST confirm the diagnostic results to some extent, including the connection of the rainfall anomaly between the Huang-Huai region in April–May and northeastern China in JJA as well as the influence from SSTA in the tropical Indian Ocean. It is shown that eliminating the internal dynamical processes by using the ensemble mean intensifies the connection, implying that the connection of rainfall variation in the two different seasons/regions may be partially caused by the external forcing (e.g., SSTA in the tropical Indian Ocean).
Abstract
While it has generally been understood that the production of Labrador Sea Water (LSW) impacts the Atlantic meridional overturning circulation (MOC), this relationship has not been explored extensively or validated against observations. To explore this relationship, a suite of global ocean–sea ice models forced by the same interannually varying atmospheric dataset, varying in resolution from non-eddy-permitting to eddy-permitting (1°–1/4°), is analyzed to investigate the local and downstream relationships between LSW formation and the MOC on interannual to decadal time scales. While all models display a strong relationship between changes in the LSW volume and the MOC in the Labrador Sea, this relationship degrades considerably downstream of the Labrador Sea. In particular, there is no consistent pattern among the models in the North Atlantic subtropical basin over interannual to decadal time scales. Furthermore, the strong response of the MOC in the Labrador Sea to LSW volume changes in that basin may be biased by the overproduction of LSW in many models compared to observations. This analysis shows that changes in LSW volume in the Labrador Sea cannot be clearly and consistently linked to a coherent MOC response across latitudes over interannual to decadal time scales in ocean hindcast simulations of the last half century. Similarly, no coherent relationships are identified between the MOC and the Labrador Sea mixed layer depth or the density of newly formed LSW across latitudes or across models over interannual to decadal time scales.
Abstract
While it has generally been understood that the production of Labrador Sea Water (LSW) impacts the Atlantic meridional overturning circulation (MOC), this relationship has not been explored extensively or validated against observations. To explore this relationship, a suite of global ocean–sea ice models forced by the same interannually varying atmospheric dataset, varying in resolution from non-eddy-permitting to eddy-permitting (1°–1/4°), is analyzed to investigate the local and downstream relationships between LSW formation and the MOC on interannual to decadal time scales. While all models display a strong relationship between changes in the LSW volume and the MOC in the Labrador Sea, this relationship degrades considerably downstream of the Labrador Sea. In particular, there is no consistent pattern among the models in the North Atlantic subtropical basin over interannual to decadal time scales. Furthermore, the strong response of the MOC in the Labrador Sea to LSW volume changes in that basin may be biased by the overproduction of LSW in many models compared to observations. This analysis shows that changes in LSW volume in the Labrador Sea cannot be clearly and consistently linked to a coherent MOC response across latitudes over interannual to decadal time scales in ocean hindcast simulations of the last half century. Similarly, no coherent relationships are identified between the MOC and the Labrador Sea mixed layer depth or the density of newly formed LSW across latitudes or across models over interannual to decadal time scales.
Abstract
The skill and reliability of forecasts of winter and summer temperature, wind speed, and irradiance over China are assessed using the Met Office Global Seasonal Forecast System, version 5 (GloSea5). Skill in such forecasts is important for the future development of seasonal climate services for the energy sector, allowing better estimates of forthcoming demand and renewable electricity supply. It was found that, although overall the skill from the direct model output is patchy, some high-skill regions of interest to the energy sector can be identified. In particular, winter mean wind speed is skillfully forecast around the coast of the South China Sea, related to skillful forecasts of the El Niño–Southern Oscillation. Such information could improve seasonal estimates of offshore wind-power generation. In a similar way, forecasts of winter irradiance have good skill in eastern central China, with possible use for solar-power estimation. Skill in predicting summer temperatures, which derives from an upward trend, is shown over much of China. The region around Beijing, however, retains this skill even when detrended. This temperature skill could be helpful in managing summer energy demand. While both the strengths and limitations of the results presented here will need to be considered when developing seasonal climate services in the future, the outlook for such service development in China is promising.
Abstract
The skill and reliability of forecasts of winter and summer temperature, wind speed, and irradiance over China are assessed using the Met Office Global Seasonal Forecast System, version 5 (GloSea5). Skill in such forecasts is important for the future development of seasonal climate services for the energy sector, allowing better estimates of forthcoming demand and renewable electricity supply. It was found that, although overall the skill from the direct model output is patchy, some high-skill regions of interest to the energy sector can be identified. In particular, winter mean wind speed is skillfully forecast around the coast of the South China Sea, related to skillful forecasts of the El Niño–Southern Oscillation. Such information could improve seasonal estimates of offshore wind-power generation. In a similar way, forecasts of winter irradiance have good skill in eastern central China, with possible use for solar-power estimation. Skill in predicting summer temperatures, which derives from an upward trend, is shown over much of China. The region around Beijing, however, retains this skill even when detrended. This temperature skill could be helpful in managing summer energy demand. While both the strengths and limitations of the results presented here will need to be considered when developing seasonal climate services in the future, the outlook for such service development in China is promising.
Abstract
Airborne microphysical measurements of a frontal precipitation event in North China were used to evaluate five microphysics schemes for predicting the bulk properties of ice particles. They are the Morrison and Thompson schemes, which use predetermined categories, the 1-ice- and 2-ice-category configurations of the Predicted Particle Properties (P3) scheme and the Ice-Spheroids Habit Model with Aspect-Ratio Evolution (ISHMAEL) scheme, which model the evolution of particle properties, and the spectral bin fast version (SBM_fast) microphysics scheme within the Weather Research and Forecasting (WRF) Model. WRF simulations with these schemes successfully reproduced the observed temperature and the liquid and total water content profiles at corresponding times and locations, allowing for a credible comparison of the predictions of particle properties with the aircraft measurements. The simulated results with the 1-ice-category P3 scheme are in good agreement with the observations for all the particle properties we examined. The 2-ice-category P3 scheme overestimates the spectrum width and underestimates the number concentration, which can be alleviated by reducing the ice collection efficiency. The simulation with the SBM_fast scheme deviates from the observed ice particle size distributions since the mass–diameter relationship of snow-sized particles adopted in this scheme may not be applicable to this stratiform cloud case.
Abstract
Airborne microphysical measurements of a frontal precipitation event in North China were used to evaluate five microphysics schemes for predicting the bulk properties of ice particles. They are the Morrison and Thompson schemes, which use predetermined categories, the 1-ice- and 2-ice-category configurations of the Predicted Particle Properties (P3) scheme and the Ice-Spheroids Habit Model with Aspect-Ratio Evolution (ISHMAEL) scheme, which model the evolution of particle properties, and the spectral bin fast version (SBM_fast) microphysics scheme within the Weather Research and Forecasting (WRF) Model. WRF simulations with these schemes successfully reproduced the observed temperature and the liquid and total water content profiles at corresponding times and locations, allowing for a credible comparison of the predictions of particle properties with the aircraft measurements. The simulated results with the 1-ice-category P3 scheme are in good agreement with the observations for all the particle properties we examined. The 2-ice-category P3 scheme overestimates the spectrum width and underestimates the number concentration, which can be alleviated by reducing the ice collection efficiency. The simulation with the SBM_fast scheme deviates from the observed ice particle size distributions since the mass–diameter relationship of snow-sized particles adopted in this scheme may not be applicable to this stratiform cloud case.
Abstract
Over the last two decades, the Central Weather Bureau of Taiwan and the U.S. National Severe Storms Laboratory have been involved in a research and development collaboration to improve the monitoring and prediction of river flooding, flash floods, debris flows, and severe storms for Taiwan. The collaboration resulted in the Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPESUMS) system. The QPESUMS system integrates observations from multiple mixed-band weather radars, rain gauges, and numerical weather prediction model fields to produce high-resolution (1 km) and rapid-update (10 min) rainfall and severe storm monitoring and prediction products. The rainfall products are widely used by government agencies and emergency managers in Taiwan for flood and mudslide warnings as well as for water resource management. The 3D reflectivity mosaic and QPE products are also used in high-resolution radar data assimilation and for the verification of numerical weather prediction model forecasts. The system facilitated collaborations with academic communities for research and development of radar applications, including quantitative precipitation estimation and nowcasting. This paper provides an overview of the operational QPE capabilities in the Taiwan QPESUMS system.
Abstract
Over the last two decades, the Central Weather Bureau of Taiwan and the U.S. National Severe Storms Laboratory have been involved in a research and development collaboration to improve the monitoring and prediction of river flooding, flash floods, debris flows, and severe storms for Taiwan. The collaboration resulted in the Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPESUMS) system. The QPESUMS system integrates observations from multiple mixed-band weather radars, rain gauges, and numerical weather prediction model fields to produce high-resolution (1 km) and rapid-update (10 min) rainfall and severe storm monitoring and prediction products. The rainfall products are widely used by government agencies and emergency managers in Taiwan for flood and mudslide warnings as well as for water resource management. The 3D reflectivity mosaic and QPE products are also used in high-resolution radar data assimilation and for the verification of numerical weather prediction model forecasts. The system facilitated collaborations with academic communities for research and development of radar applications, including quantitative precipitation estimation and nowcasting. This paper provides an overview of the operational QPE capabilities in the Taiwan QPESUMS system.
Abstract
A polarimetric radar quantitative precipitation estimation to estimate rain rate (R) from specific attenuation (A) has been applied in Taiwan's operational Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPESUMS) system since 2016. A 3-yrs' (2016-2018) drop size distribution dataset from an operational Parsivel network was used to derive a localized coefficient as well as the α(K) function in the R(A) scheme for S-band radar, where α is a key parameter in the estimation of A and K is the linear fitted slope of differential reflectivity (ZDR) versus reflectivity (Z).
The local DSD data was also used to derive localized R(Z) and R(KDP) relationships, and the relationships were evaluated using radar observations in heavy rain cases. A synthetic QPE combining the localized R(A), R(Z), and R(KDP) relationships is compared to its operational counterpart and showed about 8 % reduction in normalized mean error for the Mei-Yu cases. Typhoon cases exhibited similar improvements by the localized QPE relationships, but showed higher uncertainties than in the Mei-Yu cases. The higher uncertainties in the typhoon QPE verification was likely due to the stronger winds in typhoons than in the Mei-Yu events that caused greater mismatches between the radar observations at an altitude and the gauges at the ground. Overall, the results demonstrated advantages of localized radar rainfall relationships derived from the disdrometer data to improve the accuracy of the operational rainfall estimation products.
Abstract
A polarimetric radar quantitative precipitation estimation to estimate rain rate (R) from specific attenuation (A) has been applied in Taiwan's operational Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPESUMS) system since 2016. A 3-yrs' (2016-2018) drop size distribution dataset from an operational Parsivel network was used to derive a localized coefficient as well as the α(K) function in the R(A) scheme for S-band radar, where α is a key parameter in the estimation of A and K is the linear fitted slope of differential reflectivity (ZDR) versus reflectivity (Z).
The local DSD data was also used to derive localized R(Z) and R(KDP) relationships, and the relationships were evaluated using radar observations in heavy rain cases. A synthetic QPE combining the localized R(A), R(Z), and R(KDP) relationships is compared to its operational counterpart and showed about 8 % reduction in normalized mean error for the Mei-Yu cases. Typhoon cases exhibited similar improvements by the localized QPE relationships, but showed higher uncertainties than in the Mei-Yu cases. The higher uncertainties in the typhoon QPE verification was likely due to the stronger winds in typhoons than in the Mei-Yu events that caused greater mismatches between the radar observations at an altitude and the gauges at the ground. Overall, the results demonstrated advantages of localized radar rainfall relationships derived from the disdrometer data to improve the accuracy of the operational rainfall estimation products.
Abstract
Retrospective predictions of multiyear North Atlantic Ocean hurricane frequency are explored by applying a hybrid statistical–dynamical forecast system to initialized and noninitialized multiyear forecasts of tropical Atlantic and tropical-mean sea surface temperatures (SSTs) from two global climate model forecast systems. By accounting for impacts of initialization and radiative forcing, retrospective predictions of 5- and 9-yr mean tropical Atlantic hurricane frequency show significant correlations relative to a null hypothesis of zero correlation. The retrospective correlations are increased in a two-model average forecast and by using a lagged-ensemble approach, with the two-model ensemble decadal forecasts of hurricane frequency over 1961–2011 yielding correlation coefficients that approach 0.9. These encouraging retrospective multiyear hurricane predictions, however, should be interpreted with care: although initialized forecasts have higher nominal skill than uninitialized ones, the relatively short record and large autocorrelation of the time series limits confidence in distinguishing between the skill caused by external forcing and that added by initialization. The nominal increase in correlation in the initialized forecasts relative to the uninitialized experiments is caused by improved representation of the multiyear tropical Atlantic SST anomalies. The skill in the initialized forecasts comes in large part from the persistence of a mid-1990s shift by the initialized forecasts, rather than from predicting its evolution. Predicting shifts like that observed in 1994/95 remains a critical issue for the success of multiyear forecasts of Atlantic hurricane frequency. The retrospective forecasts highlight the possibility that changes in observing system impact forecast performance.
Abstract
Retrospective predictions of multiyear North Atlantic Ocean hurricane frequency are explored by applying a hybrid statistical–dynamical forecast system to initialized and noninitialized multiyear forecasts of tropical Atlantic and tropical-mean sea surface temperatures (SSTs) from two global climate model forecast systems. By accounting for impacts of initialization and radiative forcing, retrospective predictions of 5- and 9-yr mean tropical Atlantic hurricane frequency show significant correlations relative to a null hypothesis of zero correlation. The retrospective correlations are increased in a two-model average forecast and by using a lagged-ensemble approach, with the two-model ensemble decadal forecasts of hurricane frequency over 1961–2011 yielding correlation coefficients that approach 0.9. These encouraging retrospective multiyear hurricane predictions, however, should be interpreted with care: although initialized forecasts have higher nominal skill than uninitialized ones, the relatively short record and large autocorrelation of the time series limits confidence in distinguishing between the skill caused by external forcing and that added by initialization. The nominal increase in correlation in the initialized forecasts relative to the uninitialized experiments is caused by improved representation of the multiyear tropical Atlantic SST anomalies. The skill in the initialized forecasts comes in large part from the persistence of a mid-1990s shift by the initialized forecasts, rather than from predicting its evolution. Predicting shifts like that observed in 1994/95 remains a critical issue for the success of multiyear forecasts of Atlantic hurricane frequency. The retrospective forecasts highlight the possibility that changes in observing system impact forecast performance.
