2018 Vol. 35, No. 4
Display Method:
2018, 35(4): 376-388.
doi: 10.1007/s00376-017-6269-1
Abstract:
Future changes in the 50-yr return level for temperature and precipitation extremes over mainland China are investigated based on a CMIP5 multi-model ensemble for RCP2.6, RCP4.5 and RCP8.5 scenarios. The following indices are analyzed: TXx and TNn (the annual maximum and minimum of daily maximum and minimum surface temperature), RX5day (the annual maximum consecutive 5-day precipitation) and CDD (maximum annual number of consecutive dry days). After first validating the model performance, future changes in the 50-yr return values and return periods for these indices are investigated along with the inter-model spread. Multi-model median changes show an increase in the 50-yr return values of TXx and a decrease for TNn, more specifically, by the end of the 21st century under RCP8.5, the present day 50-yr return period of warm events is reduced to 1.2 yr, while extreme cold events over the country are projected to essentially disappear. A general increase in RX5day 50-yr return values is found in the future. By the end of the 21st century under RCP8.5, events of the present RX5day 50-yr return period are projected to reduce to <10 yr over most of China. Changes in CDD-50 show a dipole pattern over China, with a decrease in the values and longer return periods in the north, and vice versa in the south. Our study also highlights the need for further improvements in the representation of extreme events in climate models to assess the future risks and engineering design related to large-scale infrastructure in China.
Future changes in the 50-yr return level for temperature and precipitation extremes over mainland China are investigated based on a CMIP5 multi-model ensemble for RCP2.6, RCP4.5 and RCP8.5 scenarios. The following indices are analyzed: TXx and TNn (the annual maximum and minimum of daily maximum and minimum surface temperature), RX5day (the annual maximum consecutive 5-day precipitation) and CDD (maximum annual number of consecutive dry days). After first validating the model performance, future changes in the 50-yr return values and return periods for these indices are investigated along with the inter-model spread. Multi-model median changes show an increase in the 50-yr return values of TXx and a decrease for TNn, more specifically, by the end of the 21st century under RCP8.5, the present day 50-yr return period of warm events is reduced to 1.2 yr, while extreme cold events over the country are projected to essentially disappear. A general increase in RX5day 50-yr return values is found in the future. By the end of the 21st century under RCP8.5, events of the present RX5day 50-yr return period are projected to reduce to <10 yr over most of China. Changes in CDD-50 show a dipole pattern over China, with a decrease in the values and longer return periods in the north, and vice versa in the south. Our study also highlights the need for further improvements in the representation of extreme events in climate models to assess the future risks and engineering design related to large-scale infrastructure in China.
2018, 35(4): 389-397.
doi: 10.1007/s00376-017-6320-2
Abstract:
In previous work, a significant relationship was identified between the meridional displacement of the Asian westerly jet (JMD) and the Silk Road Pattern (SRP) in summer. The present study reveals that this relationship is robust in northward JMD years but absent in southward JMD years. In other words, the amplitude of the SRP increases with northward displacement of the jet but shows little change with southward displacement. Further analysis indicates that, in northward JMD years, the Rossby wave source (RWS) anomalies, which are primarily contributed by the planetary vortex stretching, are significantly stronger around the entrance of the Asian jet, i.e., the Mediterranean Sea-Caspian Sea area, with the spatial distribution being consistent with that related to the SRP. By contrast, in southward JMD years, the RWS anomalies are much weaker. Therefore, this study suggests that the RWS plays a crucial role in inducing the asymmetry of the JMD-SRP relationship. The results imply that climate anomalies may be stronger in strongly northward-displaced JMD years due to the concurrence of the JMD and SRP, and thus more attention should be paid to these years.
In previous work, a significant relationship was identified between the meridional displacement of the Asian westerly jet (JMD) and the Silk Road Pattern (SRP) in summer. The present study reveals that this relationship is robust in northward JMD years but absent in southward JMD years. In other words, the amplitude of the SRP increases with northward displacement of the jet but shows little change with southward displacement. Further analysis indicates that, in northward JMD years, the Rossby wave source (RWS) anomalies, which are primarily contributed by the planetary vortex stretching, are significantly stronger around the entrance of the Asian jet, i.e., the Mediterranean Sea-Caspian Sea area, with the spatial distribution being consistent with that related to the SRP. By contrast, in southward JMD years, the RWS anomalies are much weaker. Therefore, this study suggests that the RWS plays a crucial role in inducing the asymmetry of the JMD-SRP relationship. The results imply that climate anomalies may be stronger in strongly northward-displaced JMD years due to the concurrence of the JMD and SRP, and thus more attention should be paid to these years.
2018, 35(4): 397-409.
doi: 10.1007/s00376-017-6322-0
Abstract:
The "summer prediction barrier" (SPB) of SST anomalies (SSTA) over the Kuroshio-Oyashio Extension (KOE) refers to the phenomenon that prediction errors of KOE-SSTA tend to increase rapidly during boreal summer, resulting in large prediction uncertainties. The fast error growth associated with the SPB occurs in the mature-to-decaying transition phase, which is usually during the August-September-October (ASO) season, of the KOE-SSTA events to be predicted. Thus, the role of KOE-SSTA evolutionary characteristics in the transition phase in inducing the SPB is explored by performing perfect model predictability experiments in a coupled model, indicating that the SSTA events with larger mature-to-decaying transition rates (Category-1) favor a greater possibility of yielding a more significant SPB than those events with smaller transition rates (Category-2). The KOE-SSTA events in Category-1 tend to have more significant anomalous Ekman pumping in their transition phase, resulting in larger prediction errors of vertical oceanic temperature advection associated with the SSTA events. Consequently, Category-1 events possess faster error growth and larger prediction errors. In addition, the anomalous Ekman upwelling (downwelling) in the ASO season also causes SSTA cooling (warming), accelerating the transition rates of warm (cold) KOE-SSTA events. Therefore, the SSTA transition rate and error growth rate are both related with the anomalous Ekman pumping of the SSTA events to be predicted in their transition phase. This may explain why the SSTA events transferring more rapidly from the mature to decaying phase tend to have a greater possibility of yielding a more significant SPB.
The "summer prediction barrier" (SPB) of SST anomalies (SSTA) over the Kuroshio-Oyashio Extension (KOE) refers to the phenomenon that prediction errors of KOE-SSTA tend to increase rapidly during boreal summer, resulting in large prediction uncertainties. The fast error growth associated with the SPB occurs in the mature-to-decaying transition phase, which is usually during the August-September-October (ASO) season, of the KOE-SSTA events to be predicted. Thus, the role of KOE-SSTA evolutionary characteristics in the transition phase in inducing the SPB is explored by performing perfect model predictability experiments in a coupled model, indicating that the SSTA events with larger mature-to-decaying transition rates (Category-1) favor a greater possibility of yielding a more significant SPB than those events with smaller transition rates (Category-2). The KOE-SSTA events in Category-1 tend to have more significant anomalous Ekman pumping in their transition phase, resulting in larger prediction errors of vertical oceanic temperature advection associated with the SSTA events. Consequently, Category-1 events possess faster error growth and larger prediction errors. In addition, the anomalous Ekman upwelling (downwelling) in the ASO season also causes SSTA cooling (warming), accelerating the transition rates of warm (cold) KOE-SSTA events. Therefore, the SSTA transition rate and error growth rate are both related with the anomalous Ekman pumping of the SSTA events to be predicted in their transition phase. This may explain why the SSTA events transferring more rapidly from the mature to decaying phase tend to have a greater possibility of yielding a more significant SPB.
2018, 35(4): 410-422.
doi: 10.1007/s00376-017-7109-z
Abstract:
Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational (4D-Var) data assimilation system was developed for an intermediate coupled model (ICM) and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer (T e), which is empirically and explicitly related to sea level (SL) variation. The strength of the thermocline effect on SST (referred to simply as "the thermocline effect") is represented by an introduced parameter, αT e. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Var data assimilation system implemented in the ICM are also discussed.
Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational (4D-Var) data assimilation system was developed for an intermediate coupled model (ICM) and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer (T e), which is empirically and explicitly related to sea level (SL) variation. The strength of the thermocline effect on SST (referred to simply as "the thermocline effect") is represented by an introduced parameter, αT e. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Var data assimilation system implemented in the ICM are also discussed.
2018, 35(4): 423-434.
doi: 10.1007/s00376-017-7060-z
Abstract:
Variations in the high-frequency oscillations of tropical cyclones (TCs) over the western North Pacific (WNP) are studied in numerical model simulations. Power spectrum analysis of maximum wind speeds at 10 m (MWS10) from an ensemble of 15 simulated TCs shows that oscillations are significant for all TCs. The magnitudes of oscillations in MWS10 are similar in the WNP and South China Sea (SCS); however, the mean of the averaged significant periods in the SCS (1.93 h) is shorter than that in the open water of the WNP (2.83 h). The shorter period in the SCS is examined through an ensemble of simulations, and a case simulation as well as a sensitivity experiment in which the continent is replaced by ocean for Typhoon Hagupit (2008). The analysis of the convergence efficiency within the boundary layer suggests that the shorter periods in the SCS are possibly due to the stronger terrain effect, which intensifies convergence through greater friction. The enhanced convergence strengthens the disturbance of the gradient and thermal wind balances, and then contributes to the shorter oscillation periods in the SCS.
Variations in the high-frequency oscillations of tropical cyclones (TCs) over the western North Pacific (WNP) are studied in numerical model simulations. Power spectrum analysis of maximum wind speeds at 10 m (MWS10) from an ensemble of 15 simulated TCs shows that oscillations are significant for all TCs. The magnitudes of oscillations in MWS10 are similar in the WNP and South China Sea (SCS); however, the mean of the averaged significant periods in the SCS (1.93 h) is shorter than that in the open water of the WNP (2.83 h). The shorter period in the SCS is examined through an ensemble of simulations, and a case simulation as well as a sensitivity experiment in which the continent is replaced by ocean for Typhoon Hagupit (2008). The analysis of the convergence efficiency within the boundary layer suggests that the shorter periods in the SCS are possibly due to the stronger terrain effect, which intensifies convergence through greater friction. The enhanced convergence strengthens the disturbance of the gradient and thermal wind balances, and then contributes to the shorter oscillation periods in the SCS.
2018, 35(4): 435-444.
doi: 10.1007/s00376-017-7118-y
Abstract:
This study identifies the atmospheric circulation features that are favorable for the occurrence of low-level turbulence at Hong Kong International Airport [below 1600 feet (around 500 m)]. By using LIDAR data at the airport, turbulence and nonturbulence cases are selected. It is found that the occurrence of turbulence is significantly related to the strength of the southerly wind at 850 hPa over the South China coast. On the other hand, the east-west wind at this height demonstrates a weak relation to the occurrence. This suggests that turbulence is generated by flow passing Lantau Island from the south. The southerly wind also transports moisture from the South China Sea to Hong Kong, reducing local stability. This is favorable for the development of strong turbulence. It is also noted that the strong southerly wind during the occurrence of low-level turbulence is contributed by an anomalous zonal gradient of geopotential in the lower troposphere over the South China Sea. This gradient is caused by the combination of variations at different timescales. These are the passage of synoptic extratropical cyclones and anticyclones and the intraseasonal variation in the western North Pacific subtropical high. The seasonal variation in geopotential east of the Tibetan Plateau leads to a seasonal change in meridional wind, by which the frequency of low-level turbulence is maximized in spring and minimized in autumn.
This study identifies the atmospheric circulation features that are favorable for the occurrence of low-level turbulence at Hong Kong International Airport [below 1600 feet (around 500 m)]. By using LIDAR data at the airport, turbulence and nonturbulence cases are selected. It is found that the occurrence of turbulence is significantly related to the strength of the southerly wind at 850 hPa over the South China coast. On the other hand, the east-west wind at this height demonstrates a weak relation to the occurrence. This suggests that turbulence is generated by flow passing Lantau Island from the south. The southerly wind also transports moisture from the South China Sea to Hong Kong, reducing local stability. This is favorable for the development of strong turbulence. It is also noted that the strong southerly wind during the occurrence of low-level turbulence is contributed by an anomalous zonal gradient of geopotential in the lower troposphere over the South China Sea. This gradient is caused by the combination of variations at different timescales. These are the passage of synoptic extratropical cyclones and anticyclones and the intraseasonal variation in the western North Pacific subtropical high. The seasonal variation in geopotential east of the Tibetan Plateau leads to a seasonal change in meridional wind, by which the frequency of low-level turbulence is maximized in spring and minimized in autumn.
2018, 35(4): 445-456.
doi: 10.1007/s00376-017-7006-5
Abstract:
Soil enthalpy (H) contains the combined effects of both soil moisture (w) and soil temperature (T) in the land surface hydrothermal process. In this study, the sensitivities of H to w and T are investigated using the multi-linear regression method. Results indicate that T generally makes positive contributions to H, while w exhibits different (positive or negative) impacts due to soil ice effects. For example, w negatively contributes to H if soil contains more ice; however, after soil ice melts, w exerts positive contributions. In particular, due to lower w interannual variabilities in the deep soil layer (i.e., the fifth layer), H is more sensitive to T than to w. Moreover, to compare the potential capabilities of H, w and T in precipitation (P) prediction, the Huanghe-Huaihe Basin (HHB) and Southeast China (SEC), with similar sensitivities of H to w and T, are selected. Analyses show that, despite similar spatial distributions of H-P and T-P correlation coefficients, the former values are always higher than the latter ones. Furthermore, H provides the most effective signals for P prediction over HHB and SEC, i.e., a significant leading correlation between May H and early summer (June) P. In summary, H, which integrates the effects of T and w as an independent variable, has greater capabilities in monitoring land surface heating and improving seasonal P prediction relative to individual land surface factors (e.g., T and w).
Soil enthalpy (H) contains the combined effects of both soil moisture (w) and soil temperature (T) in the land surface hydrothermal process. In this study, the sensitivities of H to w and T are investigated using the multi-linear regression method. Results indicate that T generally makes positive contributions to H, while w exhibits different (positive or negative) impacts due to soil ice effects. For example, w negatively contributes to H if soil contains more ice; however, after soil ice melts, w exerts positive contributions. In particular, due to lower w interannual variabilities in the deep soil layer (i.e., the fifth layer), H is more sensitive to T than to w. Moreover, to compare the potential capabilities of H, w and T in precipitation (P) prediction, the Huanghe-Huaihe Basin (HHB) and Southeast China (SEC), with similar sensitivities of H to w and T, are selected. Analyses show that, despite similar spatial distributions of H-P and T-P correlation coefficients, the former values are always higher than the latter ones. Furthermore, H provides the most effective signals for P prediction over HHB and SEC, i.e., a significant leading correlation between May H and early summer (June) P. In summary, H, which integrates the effects of T and w as an independent variable, has greater capabilities in monitoring land surface heating and improving seasonal P prediction relative to individual land surface factors (e.g., T and w).
2018, 35(4): 457-468.
doi: 10.1007/s00376-017-7082-6
Abstract:
The application of numerical weather prediction (NWP) products is increasing dramatically. Existing reports indicate that ensemble predictions have better skill than deterministic forecasts. In this study, numerical ensemble precipitation forecasts in the TIGGE database were evaluated using deterministic, dichotomous (yes/no), and probabilistic techniques over Iran for the period 2008-16. Thirteen rain gauges spread over eight homogeneous precipitation regimes were selected for evaluation. The Inverse Distance Weighting and Kriging methods were adopted for interpolation of the prediction values, downscaled to the stations at lead times of one to three days. To enhance the forecast quality, NWP values were post-processed via Bayesian Model Averaging. The results showed that ECMWF had better scores than other products. However, products of all centers underestimated precipitation in high precipitation regions while overestimating precipitation in other regions. This points to a systematic bias in forecasts and demands application of bias correction techniques. Based on dichotomous evaluation, NCEP did better at most stations, although all centers overpredicted the number of precipitation events. Compared to those of ECMWF and NCEP, UKMO yielded higher scores in mountainous regions, but performed poorly at other selected stations. Furthermore, the evaluations showed that all centers had better skill in wet than in dry seasons. The quality of post-processed predictions was better than those of the raw predictions. In conclusion, the accuracy of the NWP predictions made by the selected centers could be classified as medium over Iran, while post-processing of predictions is recommended to improve the quality.
The application of numerical weather prediction (NWP) products is increasing dramatically. Existing reports indicate that ensemble predictions have better skill than deterministic forecasts. In this study, numerical ensemble precipitation forecasts in the TIGGE database were evaluated using deterministic, dichotomous (yes/no), and probabilistic techniques over Iran for the period 2008-16. Thirteen rain gauges spread over eight homogeneous precipitation regimes were selected for evaluation. The Inverse Distance Weighting and Kriging methods were adopted for interpolation of the prediction values, downscaled to the stations at lead times of one to three days. To enhance the forecast quality, NWP values were post-processed via Bayesian Model Averaging. The results showed that ECMWF had better scores than other products. However, products of all centers underestimated precipitation in high precipitation regions while overestimating precipitation in other regions. This points to a systematic bias in forecasts and demands application of bias correction techniques. Based on dichotomous evaluation, NCEP did better at most stations, although all centers overpredicted the number of precipitation events. Compared to those of ECMWF and NCEP, UKMO yielded higher scores in mountainous regions, but performed poorly at other selected stations. Furthermore, the evaluations showed that all centers had better skill in wet than in dry seasons. The quality of post-processed predictions was better than those of the raw predictions. In conclusion, the accuracy of the NWP predictions made by the selected centers could be classified as medium over Iran, while post-processing of predictions is recommended to improve the quality.
2018, 35(4): 469-478.
doi: 10.1007/s00376-017-7101-7
Abstract:
The effects of sea-surface waves and ocean spray on the marine atmospheric boundary layer (MABL) at different wind speeds and wave ages were investigated. An MABL model was developed that introduces a wave-induced component and spray force to the total surface stress. The theoretical model solution was determined assuming the eddy viscosity coefficient varied linearly with height above the sea surface. The wave-induced component was evaluated using a directional wave spectrum and growth rate. Spray force was described using interactions between ocean-spray droplets and wind-velocity shear. Wind profiles and sea-surface drag coefficients were calculated for low to high wind speeds for wind-generated sea at different wave ages to examine surface-wave and ocean-spray effects on MABL momentum distribution. The theoretical solutions were compared with model solutions neglecting wave-induced stress and/or spray stress. Surface waves strongly affected near-surface wind profiles and sea-surface drag coefficients at low to moderate wind speeds. Drag coefficients and near-surface wind speeds were lower for young than for old waves. At high wind speeds, ocean-spray droplets produced by wind-tearing breaking-wave crests affected the MABL strongly in comparison with surface waves, implying that wave age affects the MABL only negligibly. Low drag coefficients at high wind caused by ocean-spray production increased turbulent stress in the sea-spray generation layer, accelerating near-sea-surface wind. Comparing the analytical drag coefficient values with laboratory measurements and field observations indicated that surface waves and ocean spray significantly affect the MABL at different wind speeds and wave ages.
The effects of sea-surface waves and ocean spray on the marine atmospheric boundary layer (MABL) at different wind speeds and wave ages were investigated. An MABL model was developed that introduces a wave-induced component and spray force to the total surface stress. The theoretical model solution was determined assuming the eddy viscosity coefficient varied linearly with height above the sea surface. The wave-induced component was evaluated using a directional wave spectrum and growth rate. Spray force was described using interactions between ocean-spray droplets and wind-velocity shear. Wind profiles and sea-surface drag coefficients were calculated for low to high wind speeds for wind-generated sea at different wave ages to examine surface-wave and ocean-spray effects on MABL momentum distribution. The theoretical solutions were compared with model solutions neglecting wave-induced stress and/or spray stress. Surface waves strongly affected near-surface wind profiles and sea-surface drag coefficients at low to moderate wind speeds. Drag coefficients and near-surface wind speeds were lower for young than for old waves. At high wind speeds, ocean-spray droplets produced by wind-tearing breaking-wave crests affected the MABL strongly in comparison with surface waves, implying that wave age affects the MABL only negligibly. Low drag coefficients at high wind caused by ocean-spray production increased turbulent stress in the sea-spray generation layer, accelerating near-sea-surface wind. Comparing the analytical drag coefficient values with laboratory measurements and field observations indicated that surface waves and ocean spray significantly affect the MABL at different wind speeds and wave ages.
2018, 35(4): 479-492.
doi: 10.1007/s00376-017-6275-3
Abstract:
Few studies have specifically focused on the validation and spatiotemporal distribution of planetary boundary layer height (PBLH) and relative humidity (RH) data in China. In this analysis, continuous PBLH and surface-level RH data simulated from GEOS-5 between 2004 and 2012, were validated against ground-based observations. Overall, the simulated RH was consistent with the statistical data from meteorological stations, with a correlation coefficient of 0.78 and a slope of 0.9. However, the simulated PBLH was underestimated compared to LIDAR data by a factor of approximately two, which was primarily because of poor simulation in late summer and early autumn. We further examined the spatiotemporal distribution characteristics of two factors in four regions——North China, South China, Northwest China, and the Tibetan Plateau. The results showed that the annual PBLH trends in all regions were fairly moderate but sensitive to solar radiation and precipitation, which explains why the PBLH values were ranked in order from largest to smallest as follows: Tibetan Plateau, Northwest China, North China, and South China. Strong seasonal variation of the PBLH exhibited high values in summer and low values in winter, which was also consistent with the turbulent vertical exchange. Not surprisingly, the highest RH in South China and the lowest RH in desert areas of Northwest China (less than 30%). Seasonally, South China exhibited little variation, whereas Northwest China exhibited its highest humidity in winter and lowest humidity in spring, the maximum values in the other regions were obtained from July to September.
Few studies have specifically focused on the validation and spatiotemporal distribution of planetary boundary layer height (PBLH) and relative humidity (RH) data in China. In this analysis, continuous PBLH and surface-level RH data simulated from GEOS-5 between 2004 and 2012, were validated against ground-based observations. Overall, the simulated RH was consistent with the statistical data from meteorological stations, with a correlation coefficient of 0.78 and a slope of 0.9. However, the simulated PBLH was underestimated compared to LIDAR data by a factor of approximately two, which was primarily because of poor simulation in late summer and early autumn. We further examined the spatiotemporal distribution characteristics of two factors in four regions——North China, South China, Northwest China, and the Tibetan Plateau. The results showed that the annual PBLH trends in all regions were fairly moderate but sensitive to solar radiation and precipitation, which explains why the PBLH values were ranked in order from largest to smallest as follows: Tibetan Plateau, Northwest China, North China, and South China. Strong seasonal variation of the PBLH exhibited high values in summer and low values in winter, which was also consistent with the turbulent vertical exchange. Not surprisingly, the highest RH in South China and the lowest RH in desert areas of Northwest China (less than 30%). Seasonally, South China exhibited little variation, whereas Northwest China exhibited its highest humidity in winter and lowest humidity in spring, the maximum values in the other regions were obtained from July to September.
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