Nested simulations of a downslope windstorm over Cangshan mountain,Yunnan,China,have been used to demonstrate a method of topographic smoothing that preserves a relatively large amount of terrain detail compared to ty...Nested simulations of a downslope windstorm over Cangshan mountain,Yunnan,China,have been used to demonstrate a method of topographic smoothing that preserves a relatively large amount of terrain detail compared to typical smoothing procedures required for models with terrain-following grids to run stably.The simulations were carried out using the Met Office Unified Model(MetUM)to investigate downslope winds.The smoothing method seamlessly blends two terrain datasets to which uniform smoothing has been applied—one with a minimum of smoothing,the other smoothed more heavily to remove gradients that would cause model instabilities.The latter dataset dominates the blend where the steepest slopes exist,but this is localised and recedes outside these areas.As a result,increased detail is starkly apparent in depictions of flow simulated using the blend,compared to one using the default approach.This includes qualitative flow details that were absent in the latter,such as narrow shooting flows emerging from roughly 1-2 km wide leeside channels.Flow separation is more common due to steeper lee slopes.The use of targeted smoothing also results in increased lee side temporal variability at a given point during the windstorm,including over flat areas.Low-/high-pass filtering of the wind perturbation field reveals that relative spatial variability above 30 km in scale(reflecting the background flow)is similar whether or not targeting is used.Beneath this scale,when smoothing is targeted,relative flow variability decreases at the larger scales,and increases at lower scales.This seems linked to fast smaller scale flows disturbing more coherent flows(notably an along-valley current over Erhai Lake).Spatial variability of winds in the model is unsurprisingly weaker at key times than is observed across a local network sampling mesoscale variation,but results are compromised due to relatively few observation locations sampling the windstorm.Only when targeted smoothing is applied does the model capture the downslope windstorm's 展开更多
The air pollution in Urumqi which is located on the northern slope of the Tianshan Mountains in northwestern China,is very serious in winter.Of particular importance is the influence of terrain-induced shallow foehn,k...The air pollution in Urumqi which is located on the northern slope of the Tianshan Mountains in northwestern China,is very serious in winter.Of particular importance is the influence of terrain-induced shallow foehn,known locally as elevated southeasterly gale(ESEG).It usually modulates atmospheric boundary layer structure and wind field patterns and produces favorable meteorological conditions conducive to hazardous air pollution.During 2013-17,Urumqi had an average of 50 d yr-1 of heavy pollution(daily average PM2.5 concentration>150μg m-3),of which 41 days were in winter.The majority(71.4%)of heavy pollution processes were associated with the shallow foehn.Based on microwave radiometer,wind profiler,and surface observations,the surface meteorological fields and boundary layer evolution during the worst pollution episode in Urumqi during 16-23 February 2013 are investigated.The results illustrate the significant role of shallow foehn in the building,strengthening,and collapsing of temperature inversions.There were four wind field patterns corresponding to four different phases during the whole pollution event.The most serious pollution phase featured shallow foehn activity in the south of Urumqi city and the appearance of an intense inversion layer below 600 m.Intense convergence caused by foehn and mountain-valley winds was sustained during most of the phase,resulting in pollutants sinking downward to the lower boundary layer and accumulating around urban area.The key indicators of such events identified in this study are highly correlated to particulate matter concentrations and could be used to predict heavy pollution episodes in the feature.展开更多
Significant changes have occurred in the Antarctic Peninsula(AP) including warmer temperatures, accelerated melting of glaciers, and breakup of ice shelves. This study uses the Weather Research and Forecasting model(W...Significant changes have occurred in the Antarctic Peninsula(AP) including warmer temperatures, accelerated melting of glaciers, and breakup of ice shelves. This study uses the Weather Research and Forecasting model(WRF)forced by the Community Climate System Model 4(CCSM) simulations to study foehn wind warming in AP. Weather systems responsible for generating the foehn events are two cyclonic systems that move toward and/or cross over AP. WRF simulates the movement of cyclonic systems and the resulting foehn wind warming that is absent in CCSM. It is found that the warming extent along a transect across the central AP toward Larsen C Ice Shelf(LCIS) varies during the simulation period and the maximum warming moves from near the base of leeward slopes to over 40 km away extending toward the attached LCIS. Our analysis suggests that the foehn wind warming is negatively correlated with the incoming air temperature and the mountain top temperature during periods without significant precipitation, in which isentropic drawdown is the dominant heating mechanism. On the other hand, when significant precipitation occurs along the windward side of AP, latent heating is the major heating mechanism evidenced by positive relations between the foehn wind warming and 1) incoming air temperature, 2) windward precipitation, and 3)latent heating. Foehn wind warming caused by isentropic drawdown also tends to be stronger than that caused by latent heating. Comparison of WRF simulations forced by original and corrected CCSM data indicates that foehn wind warming is stronger in the original CCSM forced simulation when no significant windward precipitation is present.The foehn wind warming becomes weaker in both simulations when there is significant windward precipitation. This suggests that model’s ability to resolve the foehn warming varies with the forcing data, but the precipitation impact on the leeward warming is consistent.展开更多
Zonda wind is a typical downslope windstorm over the eastern slopes of the Central Andes in Argentina,which produces extremely warm and dry conditions and creates substantial socioeconomic impacts.The aim of this work...Zonda wind is a typical downslope windstorm over the eastern slopes of the Central Andes in Argentina,which produces extremely warm and dry conditions and creates substantial socioeconomic impacts.The aim of this work is to obtain an index for predicting the probability of Zonda wind occurrence.The Principal Component Analysis(PCA)is applied to the vertical sounding data on both sides of the Andes.Through the use of a binary logistic regression,the PCA is applied to discriminate those soundings associated with Zonda wind events from those that are not,and a probabilistic forecasting tool for Zonda occurrence is obtained.This index is able to discriminate between Zonda and non-Zonda events with an effectiveness close to 91%.The best model consists of four variables from each side of the Andes.From an eventbased statistical perspective,the probability of detection of the mixed model is above 97%with a probability of false detection lower than 7%and a missing ratio below 1%.From an alarm-based perspective,models exhibit false alarm rate below 7%,a missing alarm ratio lower than 1.5%and higher than 93%for the correct alarm ratio.The zonal component of the wind on both sides of the Andes and the windward temperature are the key variables in class discrimination.The vertical structure of Zonda wind includes two wind maximums and an unstable lapse rate at midlevels on the lee side and a wind maximum at 700 h Pa accompanied by a relatively stable layer near the mountain top.展开更多
基金supported by the UK–China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund
文摘Nested simulations of a downslope windstorm over Cangshan mountain,Yunnan,China,have been used to demonstrate a method of topographic smoothing that preserves a relatively large amount of terrain detail compared to typical smoothing procedures required for models with terrain-following grids to run stably.The simulations were carried out using the Met Office Unified Model(MetUM)to investigate downslope winds.The smoothing method seamlessly blends two terrain datasets to which uniform smoothing has been applied—one with a minimum of smoothing,the other smoothed more heavily to remove gradients that would cause model instabilities.The latter dataset dominates the blend where the steepest slopes exist,but this is localised and recedes outside these areas.As a result,increased detail is starkly apparent in depictions of flow simulated using the blend,compared to one using the default approach.This includes qualitative flow details that were absent in the latter,such as narrow shooting flows emerging from roughly 1-2 km wide leeside channels.Flow separation is more common due to steeper lee slopes.The use of targeted smoothing also results in increased lee side temporal variability at a given point during the windstorm,including over flat areas.Low-/high-pass filtering of the wind perturbation field reveals that relative spatial variability above 30 km in scale(reflecting the background flow)is similar whether or not targeting is used.Beneath this scale,when smoothing is targeted,relative flow variability decreases at the larger scales,and increases at lower scales.This seems linked to fast smaller scale flows disturbing more coherent flows(notably an along-valley current over Erhai Lake).Spatial variability of winds in the model is unsurprisingly weaker at key times than is observed across a local network sampling mesoscale variation,but results are compromised due to relatively few observation locations sampling the windstorm.Only when targeted smoothing is applied does the model capture the downslope windstorm's
基金supported by Central Scientific Research and Operational Project (IDM2020001)National Natural Science Foundation of China (Grant No. 41575011)China Desert Funds (Sqj2017013, Sqj2019004)
文摘The air pollution in Urumqi which is located on the northern slope of the Tianshan Mountains in northwestern China,is very serious in winter.Of particular importance is the influence of terrain-induced shallow foehn,known locally as elevated southeasterly gale(ESEG).It usually modulates atmospheric boundary layer structure and wind field patterns and produces favorable meteorological conditions conducive to hazardous air pollution.During 2013-17,Urumqi had an average of 50 d yr-1 of heavy pollution(daily average PM2.5 concentration>150μg m-3),of which 41 days were in winter.The majority(71.4%)of heavy pollution processes were associated with the shallow foehn.Based on microwave radiometer,wind profiler,and surface observations,the surface meteorological fields and boundary layer evolution during the worst pollution episode in Urumqi during 16-23 February 2013 are investigated.The results illustrate the significant role of shallow foehn in the building,strengthening,and collapsing of temperature inversions.There were four wind field patterns corresponding to four different phases during the whole pollution event.The most serious pollution phase featured shallow foehn activity in the south of Urumqi city and the appearance of an intense inversion layer below 600 m.Intense convergence caused by foehn and mountain-valley winds was sustained during most of the phase,resulting in pollutants sinking downward to the lower boundary layer and accumulating around urban area.The key indicators of such events identified in this study are highly correlated to particulate matter concentrations and could be used to predict heavy pollution episodes in the feature.
基金sponsored by the US NSF Grants OPP-1649713 and OPP-1543445
文摘Significant changes have occurred in the Antarctic Peninsula(AP) including warmer temperatures, accelerated melting of glaciers, and breakup of ice shelves. This study uses the Weather Research and Forecasting model(WRF)forced by the Community Climate System Model 4(CCSM) simulations to study foehn wind warming in AP. Weather systems responsible for generating the foehn events are two cyclonic systems that move toward and/or cross over AP. WRF simulates the movement of cyclonic systems and the resulting foehn wind warming that is absent in CCSM. It is found that the warming extent along a transect across the central AP toward Larsen C Ice Shelf(LCIS) varies during the simulation period and the maximum warming moves from near the base of leeward slopes to over 40 km away extending toward the attached LCIS. Our analysis suggests that the foehn wind warming is negatively correlated with the incoming air temperature and the mountain top temperature during periods without significant precipitation, in which isentropic drawdown is the dominant heating mechanism. On the other hand, when significant precipitation occurs along the windward side of AP, latent heating is the major heating mechanism evidenced by positive relations between the foehn wind warming and 1) incoming air temperature, 2) windward precipitation, and 3)latent heating. Foehn wind warming caused by isentropic drawdown also tends to be stronger than that caused by latent heating. Comparison of WRF simulations forced by original and corrected CCSM data indicates that foehn wind warming is stronger in the original CCSM forced simulation when no significant windward precipitation is present.The foehn wind warming becomes weaker in both simulations when there is significant windward precipitation. This suggests that model’s ability to resolve the foehn warming varies with the forcing data, but the precipitation impact on the leeward warming is consistent.
文摘Zonda wind is a typical downslope windstorm over the eastern slopes of the Central Andes in Argentina,which produces extremely warm and dry conditions and creates substantial socioeconomic impacts.The aim of this work is to obtain an index for predicting the probability of Zonda wind occurrence.The Principal Component Analysis(PCA)is applied to the vertical sounding data on both sides of the Andes.Through the use of a binary logistic regression,the PCA is applied to discriminate those soundings associated with Zonda wind events from those that are not,and a probabilistic forecasting tool for Zonda occurrence is obtained.This index is able to discriminate between Zonda and non-Zonda events with an effectiveness close to 91%.The best model consists of four variables from each side of the Andes.From an eventbased statistical perspective,the probability of detection of the mixed model is above 97%with a probability of false detection lower than 7%and a missing ratio below 1%.From an alarm-based perspective,models exhibit false alarm rate below 7%,a missing alarm ratio lower than 1.5%and higher than 93%for the correct alarm ratio.The zonal component of the wind on both sides of the Andes and the windward temperature are the key variables in class discrimination.The vertical structure of Zonda wind includes two wind maximums and an unstable lapse rate at midlevels on the lee side and a wind maximum at 700 h Pa accompanied by a relatively stable layer near the mountain top.
