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- Author or Editor: Yun-Young Lee x
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Abstract
California Central Valley (CCV) heat waves are grouped into two types based on the temporal and spatial evolution of the large-scale meteorological patterns (LSMPs) prior to onset. The k-means clustering of key features in the anomalous temperature and zonal wind identifies the two groups. Composite analyses show different evolution prior to developing a similar ridge–trough–ridge pattern spanning the North Pacific at the onset of CCV hot spells. Backward trajectories show adiabatic heating of air enhanced by anomalous sinking plus horizontal advection as the main mechanisms to create hot lower-tropospheric air just off the Northern California coast, although the paths differ between clusters.
The first cluster develops the ridge at the west coast on the day before onset, consistent with wave activity flux traveling across the North Pacific. Air parcels that arrive at the maximum temperature anomaly (just off the Northern California coast) tend to travel a long distance across the Pacific from the west. The second cluster has the ridge in place for several days prior to extreme CCV heat, but this ridge is located farther north, with heat anomaly over the northwestern United States. This ridge expands south as air parcels at midtropospheric levels descend from the northwest while lower-level parcels over land tend to bring hot air from directions ranging from the hot area to the northeast to the desert areas to the southeast. These two types reveal unexpected dynamical complexity, hint at different remote associations, and expand the assessment needed of climate models’ simulations of these heat waves.
Abstract
California Central Valley (CCV) heat waves are grouped into two types based on the temporal and spatial evolution of the large-scale meteorological patterns (LSMPs) prior to onset. The k-means clustering of key features in the anomalous temperature and zonal wind identifies the two groups. Composite analyses show different evolution prior to developing a similar ridge–trough–ridge pattern spanning the North Pacific at the onset of CCV hot spells. Backward trajectories show adiabatic heating of air enhanced by anomalous sinking plus horizontal advection as the main mechanisms to create hot lower-tropospheric air just off the Northern California coast, although the paths differ between clusters.
The first cluster develops the ridge at the west coast on the day before onset, consistent with wave activity flux traveling across the North Pacific. Air parcels that arrive at the maximum temperature anomaly (just off the Northern California coast) tend to travel a long distance across the Pacific from the west. The second cluster has the ridge in place for several days prior to extreme CCV heat, but this ridge is located farther north, with heat anomaly over the northwestern United States. This ridge expands south as air parcels at midtropospheric levels descend from the northwest while lower-level parcels over land tend to bring hot air from directions ranging from the hot area to the northeast to the desert areas to the southeast. These two types reveal unexpected dynamical complexity, hint at different remote associations, and expand the assessment needed of climate models’ simulations of these heat waves.
Abstract
The structure and dynamics of stratospheric northern annular mode (SNAM) events in CMIP5 simulations are studied, emphasizing (i) stratosphere–troposphere coupling and (ii) disparities between high-top (HT) and low-top (LT) models. Compared to HT models, LT models generally underrepresent SNAM amplitude in stratosphere, consistent with weaker polar vortex variability, as demonstrated by Charlton-Perez et al. Interestingly, however, this difference does not carry over to the associated zonal-mean SNAM signature in troposphere, which closely resembles observations in both HT and LT models. Nonetheless, a regional analysis illustrates that both HT and LT models exhibit anomalously weak and eastward shifted (compared to observations) storm track and sea level pressure anomaly patterns in association with SNAM events.
Dynamical analyses of stratosphere–troposphere coupling are performed to further examine the distinction between HT and LT models. Variability in stratospheric planetary wave activity is reduced in LT models despite robust concomitant tropospheric variability. A meridional heat flux analysis indicates relatively weak vertical Rossby wave coupling in LT models consistent with the excessive damping events discussed by Shaw et al. Eliassen–Palm flux cross sections reveal that Rossby wave propagation is anomalously weak above the tropopause in LT models, suggesting that weak polar vortex variability in LT models is due, at least in part, to the inability of tropospheric planetary wave activity to enter the stratosphere. Although the results are consistent with anomalously weak vertical dynamical coupling in LT models during SNAM events, there is little impact upon attendant tropospheric variability. The physical reason behind this apparent paradox represents an important topic for future study.
Abstract
The structure and dynamics of stratospheric northern annular mode (SNAM) events in CMIP5 simulations are studied, emphasizing (i) stratosphere–troposphere coupling and (ii) disparities between high-top (HT) and low-top (LT) models. Compared to HT models, LT models generally underrepresent SNAM amplitude in stratosphere, consistent with weaker polar vortex variability, as demonstrated by Charlton-Perez et al. Interestingly, however, this difference does not carry over to the associated zonal-mean SNAM signature in troposphere, which closely resembles observations in both HT and LT models. Nonetheless, a regional analysis illustrates that both HT and LT models exhibit anomalously weak and eastward shifted (compared to observations) storm track and sea level pressure anomaly patterns in association with SNAM events.
Dynamical analyses of stratosphere–troposphere coupling are performed to further examine the distinction between HT and LT models. Variability in stratospheric planetary wave activity is reduced in LT models despite robust concomitant tropospheric variability. A meridional heat flux analysis indicates relatively weak vertical Rossby wave coupling in LT models consistent with the excessive damping events discussed by Shaw et al. Eliassen–Palm flux cross sections reveal that Rossby wave propagation is anomalously weak above the tropopause in LT models, suggesting that weak polar vortex variability in LT models is due, at least in part, to the inability of tropospheric planetary wave activity to enter the stratosphere. Although the results are consistent with anomalously weak vertical dynamical coupling in LT models during SNAM events, there is little impact upon attendant tropospheric variability. The physical reason behind this apparent paradox represents an important topic for future study.
Abstract
During boreal winter, anomalous temperature regimes (ATRs), including cold air outbreaks (CAOs) and warm waves (WWs), provide important societal influences upon the United States. The current study analyzes reanalysis and model data for the period from 1949 to 2011 to assess (i) long-term variability in ATRs, (ii) interannual modulation of ATRs by low-frequency modes, and (iii) the representation of ATR behavior in models from phase 5 of the Coupled Model Intercomparison Project (CMIP5).
No significant trends in either WWs or CAOs are identified for the continental United States. On interannual time scales, CAOs are modulated by the (i) North Atlantic Oscillation (NAO) over the U.S. Southeast and (ii) the Pacific–North American (PNA) pattern over the Northwest. WW frequency is modulated by (i) the NAO over the eastern United States and (ii) the combined influence of the PNA, Pacific decadal oscillation (PDO), and ENSO over the southern United States. In contrast to previous studies of seasonal-mean temperature, the influence of ENSO upon ATRs is found to be mainly limited to a modest modulation of WWs over the southern United States. Multiple linear regression analysis reveals that the regional collective influence of low-frequency modes accounts for as much as 50% of interannual ATR variability. Although similar behavior is observed in CMIP5 models, WW (CAO) frequency is typically overestimated (underestimated). All models considered are unable to replicate observed associations between ATRs and the PDO. Further, the collective influence of low-frequency modes upon ATRs is generally underestimated in CMIP5 models. The results indicate that predictions of future ATR behavior are limited by climate model ability to represent the evolving behavior of low-frequency modes of variability.
Abstract
During boreal winter, anomalous temperature regimes (ATRs), including cold air outbreaks (CAOs) and warm waves (WWs), provide important societal influences upon the United States. The current study analyzes reanalysis and model data for the period from 1949 to 2011 to assess (i) long-term variability in ATRs, (ii) interannual modulation of ATRs by low-frequency modes, and (iii) the representation of ATR behavior in models from phase 5 of the Coupled Model Intercomparison Project (CMIP5).
No significant trends in either WWs or CAOs are identified for the continental United States. On interannual time scales, CAOs are modulated by the (i) North Atlantic Oscillation (NAO) over the U.S. Southeast and (ii) the Pacific–North American (PNA) pattern over the Northwest. WW frequency is modulated by (i) the NAO over the eastern United States and (ii) the combined influence of the PNA, Pacific decadal oscillation (PDO), and ENSO over the southern United States. In contrast to previous studies of seasonal-mean temperature, the influence of ENSO upon ATRs is found to be mainly limited to a modest modulation of WWs over the southern United States. Multiple linear regression analysis reveals that the regional collective influence of low-frequency modes accounts for as much as 50% of interannual ATR variability. Although similar behavior is observed in CMIP5 models, WW (CAO) frequency is typically overestimated (underestimated). All models considered are unable to replicate observed associations between ATRs and the PDO. Further, the collective influence of low-frequency modes upon ATRs is generally underestimated in CMIP5 models. The results indicate that predictions of future ATR behavior are limited by climate model ability to represent the evolving behavior of low-frequency modes of variability.
Abstract
This study presents the ability of seasonal forecast models to represent the observed midlatitude teleconnection associated with El Niño–Southern Oscillation (ENSO) events over the North American region for the winter months of December, January, and February. Further, the impacts of the associated errors on regional forecast performance for winter temperatures are evaluated, with a focus on 1-month-lead-time forecasts. In most models, there exists a strong linear relationship of temperature anomalies with ENSO, and, thus, a clear anomaly sign separation between both ENSO phases persists throughout the winter, whereas linear relationships are weak in observations. This leads to a difference in the temperature forecast performance between the two ENSO phases. Forecast verification scores show that the winter-season warming events during El Niño in northern North America are more correctly forecast in the models than the cooling events during La Niña and that the winter-season cooling events during El Niño in southern North America are also more correctly forecast in the models than warming events during La Niña. One possible reason for this result is that the remote atmospheric teleconnection pattern in the models is almost linear or symmetric between the El Niño and La Niña phases. The strong linear atmospheric teleconnection appears to be associated with the models’ failure in simulating the westward shift of the tropical Pacific Ocean rainfall response for the La Niña phase as compared with that for the El Niño phase, which is attributed to the warmer central tropical Pacific in the models. This study highlights that understanding how the predictive performance of climate models varies according to El Niño or La Niña phases is very important when utilizing predictive information from seasonal forecast models.
Abstract
This study presents the ability of seasonal forecast models to represent the observed midlatitude teleconnection associated with El Niño–Southern Oscillation (ENSO) events over the North American region for the winter months of December, January, and February. Further, the impacts of the associated errors on regional forecast performance for winter temperatures are evaluated, with a focus on 1-month-lead-time forecasts. In most models, there exists a strong linear relationship of temperature anomalies with ENSO, and, thus, a clear anomaly sign separation between both ENSO phases persists throughout the winter, whereas linear relationships are weak in observations. This leads to a difference in the temperature forecast performance between the two ENSO phases. Forecast verification scores show that the winter-season warming events during El Niño in northern North America are more correctly forecast in the models than the cooling events during La Niña and that the winter-season cooling events during El Niño in southern North America are also more correctly forecast in the models than warming events during La Niña. One possible reason for this result is that the remote atmospheric teleconnection pattern in the models is almost linear or symmetric between the El Niño and La Niña phases. The strong linear atmospheric teleconnection appears to be associated with the models’ failure in simulating the westward shift of the tropical Pacific Ocean rainfall response for the La Niña phase as compared with that for the El Niño phase, which is attributed to the warmer central tropical Pacific in the models. This study highlights that understanding how the predictive performance of climate models varies according to El Niño or La Niña phases is very important when utilizing predictive information from seasonal forecast models.
