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- Author or Editor: Stephen Baxter x
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Abstract
The 2013/14 boreal winter (December 2013–February 2014) brought extended periods of anomalously cold weather to central and eastern North America. The authors show that a leading pattern of extratropical variability, whose sea level pressure footprint is the North Pacific Oscillation (NPO) and circulation footprint the West Pacific (WP) teleconnection—together, the NPO–WP—exhibited extreme and persistent amplitude in this winter. Reconstruction of the 850-hPa temperature, 200-hPa geopotential height, and precipitation reveals that the NPO–WP was the leading contributor to the winter climate anomaly over large swaths of North America. This analysis, furthermore, indicates that NPO–WP variability explains the most variance of monthly winter temperature over central-eastern North America since, at least, 1979. Analysis of the NPO–WP related thermal advection provides physical insight on the generation of the cold temperature anomalies over North America. Although NPO–WP’s origin and development remain to be elucidated, its concurrent links to tropical SSTs are tenuous. These findings suggest that notable winter climate anomalies in the Pacific–North American sector need not originate, directly, from the tropics. More broadly, the attribution of the severe 2013/14 winter to the flexing of an extratropical variability pattern is cautionary given the propensity to implicate the tropics, following several decades of focus on El Niño–Southern Oscillation and its regional and far-field impacts.
Abstract
The 2013/14 boreal winter (December 2013–February 2014) brought extended periods of anomalously cold weather to central and eastern North America. The authors show that a leading pattern of extratropical variability, whose sea level pressure footprint is the North Pacific Oscillation (NPO) and circulation footprint the West Pacific (WP) teleconnection—together, the NPO–WP—exhibited extreme and persistent amplitude in this winter. Reconstruction of the 850-hPa temperature, 200-hPa geopotential height, and precipitation reveals that the NPO–WP was the leading contributor to the winter climate anomaly over large swaths of North America. This analysis, furthermore, indicates that NPO–WP variability explains the most variance of monthly winter temperature over central-eastern North America since, at least, 1979. Analysis of the NPO–WP related thermal advection provides physical insight on the generation of the cold temperature anomalies over North America. Although NPO–WP’s origin and development remain to be elucidated, its concurrent links to tropical SSTs are tenuous. These findings suggest that notable winter climate anomalies in the Pacific–North American sector need not originate, directly, from the tropics. More broadly, the attribution of the severe 2013/14 winter to the flexing of an extratropical variability pattern is cautionary given the propensity to implicate the tropics, following several decades of focus on El Niño–Southern Oscillation and its regional and far-field impacts.
Abstract
The Pacific–North American (PNA) teleconnection is a major mode of Northern Hemisphere wintertime climate variability, with well-known impacts on North American temperature and precipitation. To assess whether the PNA teleconnection has extended predictability, comprehensive data analysis is conducted to elucidate PNA evolution, with an emphasis on patterns of PNA development and decay. These patterns are identified using extended empirical orthogonal function (EEOF) and linear regression analyses on pentad-resolution atmospheric circulation data from the new Climate Forecast System Reanalysis (CFSR). Additionally, dynamical links between the PNA and another important mode of wintertime variability, the North Atlantic Oscillation (NAO), are analyzed both in the presence and absence of notable tropical convections, for example, the Madden–Julian oscillation (MJO), which is known to be influential on both. The relationship is analyzed using EEOF and regression techniques.
It is shown that the PNA structure is similar in both space and time when the MJO is linearly removed from the dataset. Furthermore, there is a small but significant lag between the NAO and PNA, with the NAO leading a PNA of opposite phase on time scales of one to three pentads. It is suggested from barotropic vorticity analysis that this relationship may result in part from excitation of Rossby waves by the NAO in the Asian waveguide.
Abstract
The Pacific–North American (PNA) teleconnection is a major mode of Northern Hemisphere wintertime climate variability, with well-known impacts on North American temperature and precipitation. To assess whether the PNA teleconnection has extended predictability, comprehensive data analysis is conducted to elucidate PNA evolution, with an emphasis on patterns of PNA development and decay. These patterns are identified using extended empirical orthogonal function (EEOF) and linear regression analyses on pentad-resolution atmospheric circulation data from the new Climate Forecast System Reanalysis (CFSR). Additionally, dynamical links between the PNA and another important mode of wintertime variability, the North Atlantic Oscillation (NAO), are analyzed both in the presence and absence of notable tropical convections, for example, the Madden–Julian oscillation (MJO), which is known to be influential on both. The relationship is analyzed using EEOF and regression techniques.
It is shown that the PNA structure is similar in both space and time when the MJO is linearly removed from the dataset. Furthermore, there is a small but significant lag between the NAO and PNA, with the NAO leading a PNA of opposite phase on time scales of one to three pentads. It is suggested from barotropic vorticity analysis that this relationship may result in part from excitation of Rossby waves by the NAO in the Asian waveguide.
Abstract
Variability of springtime tornadic activity over the United States is assessed through the connectivity of preferred modes of North American low-level jet (NALLJ) variability to the local thermodynamic environment and remote SST variations. The link between regional tornado activity and NALLJ variability as diagnosed from a consistent reanalysis system (i.e., NCEP–NCAR) serves as dynamical corroboration in light of the inhomogeneous tornado database. The analysis reveals a multidecadal variation in the strength of the NALLJ–tornado connection, highlighted by tornado activity in the southern Great Plains region nearly doubling its correlation with NALLJ principal component 1 (PC 1) in recent decades. Locally, this is a result of a southward shift of NALLJ variability modes during the recent period. Motivated by these epochal shifts in NALLJ activity, a comparison of the early (1950–78) and late (1979–2010) tornado and NALLJ SST linkages indicates an Atlantic decadal SST variability influence during the early epoch, with Pacific decadal variability thereafter, highlighting the remote SST influence on the shifts in geographic placement and strength of NALLJ variability. The remote SST variability linkages further reveal that the observed global-scale SST trend pattern over the last 61 years may be contributing to a shift toward weaker tornadoes during spring in the northern Great Plains region. Tornado activity over the southeast region of the United States shows no such relationship to the SST trend pattern during spring, an immunity that is unexpected if spurious trends in the tornado database were influencing the SST linkage.
Abstract
Variability of springtime tornadic activity over the United States is assessed through the connectivity of preferred modes of North American low-level jet (NALLJ) variability to the local thermodynamic environment and remote SST variations. The link between regional tornado activity and NALLJ variability as diagnosed from a consistent reanalysis system (i.e., NCEP–NCAR) serves as dynamical corroboration in light of the inhomogeneous tornado database. The analysis reveals a multidecadal variation in the strength of the NALLJ–tornado connection, highlighted by tornado activity in the southern Great Plains region nearly doubling its correlation with NALLJ principal component 1 (PC 1) in recent decades. Locally, this is a result of a southward shift of NALLJ variability modes during the recent period. Motivated by these epochal shifts in NALLJ activity, a comparison of the early (1950–78) and late (1979–2010) tornado and NALLJ SST linkages indicates an Atlantic decadal SST variability influence during the early epoch, with Pacific decadal variability thereafter, highlighting the remote SST influence on the shifts in geographic placement and strength of NALLJ variability. The remote SST variability linkages further reveal that the observed global-scale SST trend pattern over the last 61 years may be contributing to a shift toward weaker tornadoes during spring in the northern Great Plains region. Tornado activity over the southeast region of the United States shows no such relationship to the SST trend pattern during spring, an immunity that is unexpected if spurious trends in the tornado database were influencing the SST linkage.
Abstract
Intensification of regional springtime precipitation variability over the United States and the role of North American low-level jets (NALLJs) are investigated for the 1950–2010 period. The analysis reveals that the primary modes of NALLJ fluctuations are related to the strengthening of AMJ precipitation variability over the northern Great Plains and southeastern United States during the last 60 years. Examination of the epochal change in NALLJ variations shows a stronger connectivity to SST variability during 1980–2010 than in the 1950–79 period. In the context of the first three NALLJ variability modes it appears that the role of decadal SST variations (NALLJ mode 1) and the recent emergence of tropical Pacific connectivity (NALLJ modes 1 and 2) via SST-induced atmospheric heating and large-scale circulation changes may act to strengthen and spatially shift the NALLJ variability modes southward and/or eastward, intensifying regional precipitation variability in the recent epoch. Although notable NALLJ variability also exists in the earlier epoch, the upper-level height field is significantly lacking in meridional gradients, leading to weak upper-level zonal wind anomalies over the United States and diminished NALLJ variability. Conversely, the intensified and spatially shifted upper-level height anomaly in the recent epoch produces enhanced meridional height gradients in all three modes, strengthening NALLJ variability—highlighting that seemingly subtle shifts in hemispheric-scale atmospheric circulation changes can have important impacts on regional climate variability and change.
Abstract
Intensification of regional springtime precipitation variability over the United States and the role of North American low-level jets (NALLJs) are investigated for the 1950–2010 period. The analysis reveals that the primary modes of NALLJ fluctuations are related to the strengthening of AMJ precipitation variability over the northern Great Plains and southeastern United States during the last 60 years. Examination of the epochal change in NALLJ variations shows a stronger connectivity to SST variability during 1980–2010 than in the 1950–79 period. In the context of the first three NALLJ variability modes it appears that the role of decadal SST variations (NALLJ mode 1) and the recent emergence of tropical Pacific connectivity (NALLJ modes 1 and 2) via SST-induced atmospheric heating and large-scale circulation changes may act to strengthen and spatially shift the NALLJ variability modes southward and/or eastward, intensifying regional precipitation variability in the recent epoch. Although notable NALLJ variability also exists in the earlier epoch, the upper-level height field is significantly lacking in meridional gradients, leading to weak upper-level zonal wind anomalies over the United States and diminished NALLJ variability. Conversely, the intensified and spatially shifted upper-level height anomaly in the recent epoch produces enhanced meridional height gradients in all three modes, strengthening NALLJ variability—highlighting that seemingly subtle shifts in hemispheric-scale atmospheric circulation changes can have important impacts on regional climate variability and change.
Abstract
Lagged pentad composites of surface air temperature and precipitation are analyzed for the winter season (December–February) to assess the influence of the Madden–Julian oscillation (MJO) on the climate of the contiguous United States. Composites are based on the Wheeler and Hendon MJO index as well as an index developed and maintained at NOAA’s Climate Prediction Center (CPC), which is based on extended empirical orthogonal function analysis of upper-level velocity potential. Significant positive temperature anomalies develop in the eastern United States 5–20 days following Wheeler and Hendon MJO index phase 3, which corresponds to enhanced convection centered over the eastern Indian Ocean. At the same lag, positive precipitation anomalies are observed from the southern Plains to the Great Lakes region. Negative temperature anomalies appear in the central and eastern United States 10–20 days following Wheeler and Hendon MJO phase 7. These impacts are supported by an analysis of the evolution of 200-hPa geopotential height and zonal wind anomalies. Composites based on the CPC velocity potential MJO index generally yield similar results; however, they capture more cases since the index contains both interannual and subseasonal variability. There are some cases where the CPC index differs from that of WH in both MJO phase identification and its North American impacts, especially near the West Coast. This analysis suggests that MJO-related velocity potential anomalies can be used without the Wheeler and Hendon MJO index to predict MJO impacts.
Abstract
Lagged pentad composites of surface air temperature and precipitation are analyzed for the winter season (December–February) to assess the influence of the Madden–Julian oscillation (MJO) on the climate of the contiguous United States. Composites are based on the Wheeler and Hendon MJO index as well as an index developed and maintained at NOAA’s Climate Prediction Center (CPC), which is based on extended empirical orthogonal function analysis of upper-level velocity potential. Significant positive temperature anomalies develop in the eastern United States 5–20 days following Wheeler and Hendon MJO index phase 3, which corresponds to enhanced convection centered over the eastern Indian Ocean. At the same lag, positive precipitation anomalies are observed from the southern Plains to the Great Lakes region. Negative temperature anomalies appear in the central and eastern United States 10–20 days following Wheeler and Hendon MJO phase 7. These impacts are supported by an analysis of the evolution of 200-hPa geopotential height and zonal wind anomalies. Composites based on the CPC velocity potential MJO index generally yield similar results; however, they capture more cases since the index contains both interannual and subseasonal variability. There are some cases where the CPC index differs from that of WH in both MJO phase identification and its North American impacts, especially near the West Coast. This analysis suggests that MJO-related velocity potential anomalies can be used without the Wheeler and Hendon MJO index to predict MJO impacts.
Abstract
This study applies Fourier filtering to a combination of rainfall estimates from TRMM and forecasts from the CFSv2. The combined data are filtered for low-frequency (LF, ≥120 days) variability, the MJO, and convectively coupled equatorial waves. The filtering provides insight into the sources of skill for the CFSv2. The LF filter, which encapsulates persistent anomalies generally corresponding with SSTs, has the largest contribution to forecast skill beyond week 2. Variability within the equatorial Pacific is dominated by its response to ENSO, such that both the unfiltered and the LF-filtered forecasts are skillful over the Pacific through the entire 45-day CFSv2 forecast. In fact, the LF forecasts in that region are more skillful than the unfiltered forecasts or any combination of the filters. Verifying filtered against unfiltered observations shows that subseasonal variability has very little opportunity to contribute to skill over the equatorial Pacific. Any subseasonal variability produced by the model is actually detracting from the skill there. The MJO primarily contributes to CFSv2 skill over the Indian Ocean, particularly during March–May and MJO phases 2–5. However, the model misses opportunities for the MJO to contribute to skill in other regions. Convectively coupled equatorial Rossby waves contribute to skill over the Indian Ocean during December–February and the Atlantic Ocean during September–November. Convectively coupled Kelvin waves show limited potential skill for predicting weekly averaged rainfall anomalies since they explain a relatively small percent of the observed variability.
Abstract
This study applies Fourier filtering to a combination of rainfall estimates from TRMM and forecasts from the CFSv2. The combined data are filtered for low-frequency (LF, ≥120 days) variability, the MJO, and convectively coupled equatorial waves. The filtering provides insight into the sources of skill for the CFSv2. The LF filter, which encapsulates persistent anomalies generally corresponding with SSTs, has the largest contribution to forecast skill beyond week 2. Variability within the equatorial Pacific is dominated by its response to ENSO, such that both the unfiltered and the LF-filtered forecasts are skillful over the Pacific through the entire 45-day CFSv2 forecast. In fact, the LF forecasts in that region are more skillful than the unfiltered forecasts or any combination of the filters. Verifying filtered against unfiltered observations shows that subseasonal variability has very little opportunity to contribute to skill over the equatorial Pacific. Any subseasonal variability produced by the model is actually detracting from the skill there. The MJO primarily contributes to CFSv2 skill over the Indian Ocean, particularly during March–May and MJO phases 2–5. However, the model misses opportunities for the MJO to contribute to skill in other regions. Convectively coupled equatorial Rossby waves contribute to skill over the Indian Ocean during December–February and the Atlantic Ocean during September–November. Convectively coupled Kelvin waves show limited potential skill for predicting weekly averaged rainfall anomalies since they explain a relatively small percent of the observed variability.
Abstract
Over the past 40 years, the Arctic sea ice minimum in September has declined. The period between 2007 and 2012 showed accelerated melt contributed to the record minima of 2007 and 2012. Here, observational and model evidence shows that the changes in summer sea ice since the 2000s reflect a continuous anthropogenically forced melting masked by interdecadal variability of Arctic atmospheric circulation. This variation is partially driven by teleconnections originating from sea surface temperature (SST) changes in the east-central tropical Pacific via a Rossby wave train propagating into the Arctic [herein referred to as the Pacific–Arctic teleconnection (PARC)], which represents the leading internal mode connecting the pole to lower latitudes. This mode has contributed to accelerated warming and Arctic sea ice loss from 2007 to 2012, followed by slower declines in recent years, resulting in the appearance of a slowdown over the past 11 years. A pacemaker model simulation, in which we specify observed SST in the tropical eastern Pacific, demonstrates a physically plausible mechanism for the PARC mode. However, the model-based PARC mechanism is considerably weaker and only partially accounts for the observed acceleration of sea ice loss from 2007 to 2012. We also explore features of large-scale circulation patterns associated with extreme melting periods in a long (1800 yr) CESM preindustrial simulation. These results further support that remote SST forcing originating from the tropical Pacific can excite significant warm episodes in the Arctic. However, further research is needed to identify the reasons for model limitations in reproducing the observed PARC mode featuring a cold Pacific–warm Arctic connection.
Abstract
Over the past 40 years, the Arctic sea ice minimum in September has declined. The period between 2007 and 2012 showed accelerated melt contributed to the record minima of 2007 and 2012. Here, observational and model evidence shows that the changes in summer sea ice since the 2000s reflect a continuous anthropogenically forced melting masked by interdecadal variability of Arctic atmospheric circulation. This variation is partially driven by teleconnections originating from sea surface temperature (SST) changes in the east-central tropical Pacific via a Rossby wave train propagating into the Arctic [herein referred to as the Pacific–Arctic teleconnection (PARC)], which represents the leading internal mode connecting the pole to lower latitudes. This mode has contributed to accelerated warming and Arctic sea ice loss from 2007 to 2012, followed by slower declines in recent years, resulting in the appearance of a slowdown over the past 11 years. A pacemaker model simulation, in which we specify observed SST in the tropical eastern Pacific, demonstrates a physically plausible mechanism for the PARC mode. However, the model-based PARC mechanism is considerably weaker and only partially accounts for the observed acceleration of sea ice loss from 2007 to 2012. We also explore features of large-scale circulation patterns associated with extreme melting periods in a long (1800 yr) CESM preindustrial simulation. These results further support that remote SST forcing originating from the tropical Pacific can excite significant warm episodes in the Arctic. However, further research is needed to identify the reasons for model limitations in reproducing the observed PARC mode featuring a cold Pacific–warm Arctic connection.
Abstract
The Pacific–North American pattern (PNA), North Atlantic Oscillation (NAO), and Arctic Oscillation (AO) are three dominant teleconnection patterns known to strongly affect December–February surface weather in the Northern Hemisphere. A partial least squares regression (PLSR) method is adopted in this study to generate wintertime two-week statistical forecasts of these three teleconnection pattern indices for lead times of up to five weeks over the 1980–2013 period. The PLSR approach generates forecasts for the teleconnection pattern indices by maximizing the variance explained by predictor indices determined as linear combinations of predictor fields, which include gridded outgoing longwave radiation (OLR), 300-hPa geopotential height (Z300), and 50-hPa geopotential height (Z50). Overall, the PLSR models yield statistically significant skill at all lead times up to five weeks. In particular, cross-validated correlations between the combined weeks 3–4 PLSR forecasts and verification for the PNA, NAO, and AO indices are 0.34, 0.28, and 0.41, respectively. The PLSR approach also allows the authors to isolate a small number of predictor patterns that help shed light on the sources of prediction skill for each teleconnection pattern. As expected, the results reveal the importance of tropical convection (OLR) for forecast skill in weeks 3–4, but the initial atmospheric flow (Z300) accounts for a substantial fraction of the skill as well. Overall, the results of this study provide promise for improving subseasonal-to-seasonal (S2S) forecasts and the physical understanding of predictability on these time scales.
Abstract
The Pacific–North American pattern (PNA), North Atlantic Oscillation (NAO), and Arctic Oscillation (AO) are three dominant teleconnection patterns known to strongly affect December–February surface weather in the Northern Hemisphere. A partial least squares regression (PLSR) method is adopted in this study to generate wintertime two-week statistical forecasts of these three teleconnection pattern indices for lead times of up to five weeks over the 1980–2013 period. The PLSR approach generates forecasts for the teleconnection pattern indices by maximizing the variance explained by predictor indices determined as linear combinations of predictor fields, which include gridded outgoing longwave radiation (OLR), 300-hPa geopotential height (Z300), and 50-hPa geopotential height (Z50). Overall, the PLSR models yield statistically significant skill at all lead times up to five weeks. In particular, cross-validated correlations between the combined weeks 3–4 PLSR forecasts and verification for the PNA, NAO, and AO indices are 0.34, 0.28, and 0.41, respectively. The PLSR approach also allows the authors to isolate a small number of predictor patterns that help shed light on the sources of prediction skill for each teleconnection pattern. As expected, the results reveal the importance of tropical convection (OLR) for forecast skill in weeks 3–4, but the initial atmospheric flow (Z300) accounts for a substantial fraction of the skill as well. Overall, the results of this study provide promise for improving subseasonal-to-seasonal (S2S) forecasts and the physical understanding of predictability on these time scales.
