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Abstract
Global teleconnections associated with the Asian summer monsoon convective activities are investigated based on monthly data of 29 Northern Hemisphere summers defined as June–September (JJAS). Two distinct teleconnection patterns are identified that are associated respectively with variabilities of the Indian summer monsoon and the western North Pacific summer monsoon. The Indian summer monsoon convective activity is associated with a global pattern that has a far-reaching connection in both hemispheres, whereas the western North Pacific summer monsoon convective activity is connected to a Southern Hemisphere wave train that influences the high-latitude South Pacific and South America. A global primitive equation model is utilized to assess the cause of the global circulation anomalies. The model responses to anomalous heatings of both monsoon systems match the general features of the observed circulation anomalies well, and they are mainly controlled by linear processes. The response patterns are largely determined by the summertime large-scale background mean flow and the location of the heating anomaly relative to the upper easterly jet in the monsoon region.
Abstract
Global teleconnections associated with the Asian summer monsoon convective activities are investigated based on monthly data of 29 Northern Hemisphere summers defined as June–September (JJAS). Two distinct teleconnection patterns are identified that are associated respectively with variabilities of the Indian summer monsoon and the western North Pacific summer monsoon. The Indian summer monsoon convective activity is associated with a global pattern that has a far-reaching connection in both hemispheres, whereas the western North Pacific summer monsoon convective activity is connected to a Southern Hemisphere wave train that influences the high-latitude South Pacific and South America. A global primitive equation model is utilized to assess the cause of the global circulation anomalies. The model responses to anomalous heatings of both monsoon systems match the general features of the observed circulation anomalies well, and they are mainly controlled by linear processes. The response patterns are largely determined by the summertime large-scale background mean flow and the location of the heating anomaly relative to the upper easterly jet in the monsoon region.
Abstract
Pentad (5-day averaged) forecast skill over the Arctic region in boreal winter is evaluated for the subseasonal to seasonal prediction (S2S) systems from three operational centers: the European Centre for Medium-Range Weather Forecasts (ECMWF), the U.S. National Centers for Environmental Prediction (NCEP), and Environment and Climate Change Canada (ECCC). The results indicate that for a lead time longer than about 10 days the forecast skill of 2-m air temperature and 500-hPa geopotential height in the Arctic area is low compared to the tropical and midlatitude regions. The three S2S systems have comparable forecast skill in the northern polar region. Relatively high skill is observed in the Arctic sector north of the Bering Strait in pentads 4–6. Possible sources of S2S predictability in the polar region are explored. The polar forecast skill is found to be dependent on the phase of the Arctic Oscillation (AO) in the initial condition; that is, forecasts initialized with the negative AO are more skillful than those starting from the positive AO. This is likely due to the influence of the stratospheric polar vortex. The tropical MJO is found to also influence the prediction skill in the polar region. Forecasts starting from MJO phases 6–7, which correspond to suppressed convection in the equatorial eastern Indian Ocean and enhanced convection in the tropical western Pacific, tend to be more skillful than those initialized from other MJO phases. To improve the polar prediction on the subseasonal time scale, it is important to have a well-represented stratosphere and tropical MJO and their associated teleconnections in the model.
Abstract
Pentad (5-day averaged) forecast skill over the Arctic region in boreal winter is evaluated for the subseasonal to seasonal prediction (S2S) systems from three operational centers: the European Centre for Medium-Range Weather Forecasts (ECMWF), the U.S. National Centers for Environmental Prediction (NCEP), and Environment and Climate Change Canada (ECCC). The results indicate that for a lead time longer than about 10 days the forecast skill of 2-m air temperature and 500-hPa geopotential height in the Arctic area is low compared to the tropical and midlatitude regions. The three S2S systems have comparable forecast skill in the northern polar region. Relatively high skill is observed in the Arctic sector north of the Bering Strait in pentads 4–6. Possible sources of S2S predictability in the polar region are explored. The polar forecast skill is found to be dependent on the phase of the Arctic Oscillation (AO) in the initial condition; that is, forecasts initialized with the negative AO are more skillful than those starting from the positive AO. This is likely due to the influence of the stratospheric polar vortex. The tropical MJO is found to also influence the prediction skill in the polar region. Forecasts starting from MJO phases 6–7, which correspond to suppressed convection in the equatorial eastern Indian Ocean and enhanced convection in the tropical western Pacific, tend to be more skillful than those initialized from other MJO phases. To improve the polar prediction on the subseasonal time scale, it is important to have a well-represented stratosphere and tropical MJO and their associated teleconnections in the model.
Abstract
The predictability of atmospheric mean-seasonal conditions in the absence of externally varying forcing is examined. A perfect-model approach is adopted, in which a global T21 three-level quasigeostrophic atmospheric model is integrated over 21 000 days to obtain a reference atmospheric orbit. The model is driven by a time-independent forcing, so that the only source of time variability is the internal dynamics. The forcing is set to perpetual winter conditions in the Northern Hemisphere (NH) and perpetual summer in the Southern Hemisphere.
A significant temporal variability in the NH 90-day mean states is observed. The component of that variability associated with the higher-frequency motions, or climate noise, is estimated using a method developed by Madden. In the polar region, and to a lesser extent in the midlatitudes, the temporal variance of the winter means is significantly greater than the climate noise, suggesting some potential predictability in those regions.
Forecast experiments are performed to see whether the presence of variance in the 90-day mean states that is in excess of the climate noise leads to some skill in the prediction of these states. Ensemble forecast experiments with nine members starting from slightly different initial conditions are performed for 200 different 90-day means along the reference atmospheric orbit. The serial correlation between the ensemble means and the reference orbit shows that there is skill in the 90-day mean predictions. The skill is concentrated in those regions of the NH that have the largest variance in excess of the climate noise. An EOF analysis shows that nearly all the predictive skill in the seasonal means is associated with one mode of variability with a strong axisymmetric component.
Abstract
The predictability of atmospheric mean-seasonal conditions in the absence of externally varying forcing is examined. A perfect-model approach is adopted, in which a global T21 three-level quasigeostrophic atmospheric model is integrated over 21 000 days to obtain a reference atmospheric orbit. The model is driven by a time-independent forcing, so that the only source of time variability is the internal dynamics. The forcing is set to perpetual winter conditions in the Northern Hemisphere (NH) and perpetual summer in the Southern Hemisphere.
A significant temporal variability in the NH 90-day mean states is observed. The component of that variability associated with the higher-frequency motions, or climate noise, is estimated using a method developed by Madden. In the polar region, and to a lesser extent in the midlatitudes, the temporal variance of the winter means is significantly greater than the climate noise, suggesting some potential predictability in those regions.
Forecast experiments are performed to see whether the presence of variance in the 90-day mean states that is in excess of the climate noise leads to some skill in the prediction of these states. Ensemble forecast experiments with nine members starting from slightly different initial conditions are performed for 200 different 90-day means along the reference atmospheric orbit. The serial correlation between the ensemble means and the reference orbit shows that there is skill in the 90-day mean predictions. The skill is concentrated in those regions of the NH that have the largest variance in excess of the climate noise. An EOF analysis shows that nearly all the predictive skill in the seasonal means is associated with one mode of variability with a strong axisymmetric component.
Abstract
In this study, a new index is defined to capture the prominent northward propagation of the intraseasonal oscillation (ISO) in boreal summer in the East Asian and western North Pacific (EAWNP) region. It is based on the first two modes of empirical orthogonal function (EOF) analysis of the combined fields of daily anomalies of zonally averaged outgoing longwave radiation (OLR) and 850-hPa zonal wind (U850) in the EAWNP region. These two EOFs are well separated from the rest of the modes, and their principal components (PCs) capture the intraseasonal variability. They are nearly in quadrature in both space and time and their combination reasonably well represents the northward propagation of the ISO. As no future information beyond the current date is required as in conventional time filtering, this ISO index can be used in real-time applications. This index is applied to the output of the 24-yr historical hindcast experiment using the Global Environmental Multiscale (GEM) model of Environment Canada to evaluate the forecast skill of the ISO of the EAWNP summer monsoon.
Abstract
In this study, a new index is defined to capture the prominent northward propagation of the intraseasonal oscillation (ISO) in boreal summer in the East Asian and western North Pacific (EAWNP) region. It is based on the first two modes of empirical orthogonal function (EOF) analysis of the combined fields of daily anomalies of zonally averaged outgoing longwave radiation (OLR) and 850-hPa zonal wind (U850) in the EAWNP region. These two EOFs are well separated from the rest of the modes, and their principal components (PCs) capture the intraseasonal variability. They are nearly in quadrature in both space and time and their combination reasonably well represents the northward propagation of the ISO. As no future information beyond the current date is required as in conventional time filtering, this ISO index can be used in real-time applications. This index is applied to the output of the 24-yr historical hindcast experiment using the Global Environmental Multiscale (GEM) model of Environment Canada to evaluate the forecast skill of the ISO of the EAWNP summer monsoon.
Abstract
Using the homogenized Canadian historical daily surface air temperature (SAT) for 210 relatively evenly distributed stations across Canada, the lagged composites and probability of the above- and below-normal SAT in Canada for different phases of the Madden–Julian oscillation (MJO) in the winter season are analyzed. Significant positive SAT anomalies and high probability of above-normal events in the central and eastern Canada are found 5–15 days following MJO phase 3, which corresponds to an enhanced precipitation over the Indian Ocean and Maritime Continent and a reduced convective activity near the tropical central Pacific. On the other hand, a positive SAT anomaly appears over a large part of northern and northeastern Canada about 5–15 days after the MJO is detected in phase 7. An analysis of the evolution of the 500-hPa geopotential height and sea level pressure anomalies indicates that the Canadian SAT anomaly is a result of a Rossby wave train associated with the tropical convection anomaly of the MJO. Hence, the MJO phase provides useful information for the extended-range forecast of Canadian winter surface air temperature. This result also provides an important reference for numerical model verifications.
Abstract
Using the homogenized Canadian historical daily surface air temperature (SAT) for 210 relatively evenly distributed stations across Canada, the lagged composites and probability of the above- and below-normal SAT in Canada for different phases of the Madden–Julian oscillation (MJO) in the winter season are analyzed. Significant positive SAT anomalies and high probability of above-normal events in the central and eastern Canada are found 5–15 days following MJO phase 3, which corresponds to an enhanced precipitation over the Indian Ocean and Maritime Continent and a reduced convective activity near the tropical central Pacific. On the other hand, a positive SAT anomaly appears over a large part of northern and northeastern Canada about 5–15 days after the MJO is detected in phase 7. An analysis of the evolution of the 500-hPa geopotential height and sea level pressure anomalies indicates that the Canadian SAT anomaly is a result of a Rossby wave train associated with the tropical convection anomaly of the MJO. Hence, the MJO phase provides useful information for the extended-range forecast of Canadian winter surface air temperature. This result also provides an important reference for numerical model verifications.
Abstract
The seasonality of the influence of the tropical Pacific sea surface temperature (SST)-forced large-scale atmospheric patterns on the surface air temperature (SAT) over China is investigated for the period from 1969 to 2001. Both observations and output from four atmospheric general circulation models (GCMs) involved in the second phase of the Canadian Historical Forecasting Project (HFP) are used. The large-scale atmospheric patterns are obtained by applying a singular value decomposition (SVD) analysis between 500-hPa geopotential height (Z500) in the Northern Hemisphere and SST in the tropical Pacific Ocean. Temporal correlations between the SAT over China and the expansion coefficients of the leading SVD modes show that SAT over China can be significantly influenced by these large-scale atmospheric patterns, especially by the second SVD mode. The relationship between the SAT over China and the leading atmospheric patterns in the observations is partly captured by the HFP models.
Furthermore, seasonal forecasts of SAT over China are postprocessed using a statistical approach. This statistical approach is designed based on the relationship between the forecast Z500 and the observed SST to calibrate the SAT forecasts. Results show that the forecast skill of the postprocessed SAT over China can be improved in all seasons to some extent, with that in fall having the most significant improvement. Possible mechanisms behind the improvement of the forecast are investigated.
Abstract
The seasonality of the influence of the tropical Pacific sea surface temperature (SST)-forced large-scale atmospheric patterns on the surface air temperature (SAT) over China is investigated for the period from 1969 to 2001. Both observations and output from four atmospheric general circulation models (GCMs) involved in the second phase of the Canadian Historical Forecasting Project (HFP) are used. The large-scale atmospheric patterns are obtained by applying a singular value decomposition (SVD) analysis between 500-hPa geopotential height (Z500) in the Northern Hemisphere and SST in the tropical Pacific Ocean. Temporal correlations between the SAT over China and the expansion coefficients of the leading SVD modes show that SAT over China can be significantly influenced by these large-scale atmospheric patterns, especially by the second SVD mode. The relationship between the SAT over China and the leading atmospheric patterns in the observations is partly captured by the HFP models.
Furthermore, seasonal forecasts of SAT over China are postprocessed using a statistical approach. This statistical approach is designed based on the relationship between the forecast Z500 and the observed SST to calibrate the SAT forecasts. Results show that the forecast skill of the postprocessed SAT over China can be improved in all seasons to some extent, with that in fall having the most significant improvement. Possible mechanisms behind the improvement of the forecast are investigated.
Abstract
Previous studies have shown that the Madden–Julian oscillation (MJO) has a global impact that may provide an important source of skill for subseasonal predictions. The extratropical response was found to be the strongest when the tropical diabatic heating has a dipole structure with convection anomaly centers of opposite sign in the eastern Indian Ocean and the western Pacific. A positive (negative) MJO dipole heating refers to that with heating (cooling) in the eastern Indian Ocean and cooling (heating) in the western Pacific. In this study, two aspects of the extratropical response to the MJO are examined: 1) nonlinearity, which answers the question of whether the response to a positive MJO dipole heating is the mirror image of that to a negative MJO, and 2) sensitivity to the initial state, which explores the dependence of the extratropical response on the initial condition of the westerly jet.
Ensemble integrations using a primitive-equation global atmospheric circulation model are performed with anomalous tropical thermal forcings that resemble a positive MJO (+MJO) and a negative MJO (−MJO). The response in the first week is largely linear. After that, significant asymmetry is found between the response in the positive MJO and the negative MJO. The 500-hPa negative geopotential height response in the North Pacific of the −MJO run is located about 30° east of the positive height response of the +MJO run. There is also an eastward shift of the extratropical wave train in the Pacific–North American region. This simulated nonlinearity is in agreement with the observations. The two leading response patterns among the ensemble members are identified by an empirical orthogonal function (EOF) analysis. EOF1 represents an eastward shift of the wave train, which is positively correlated with strengthening of the East Asian subtropical upper-troposphere westerly jet in the initial condition. On the other hand, EOF2 represents an amplification of the response, which is associated with a southward shift of the westerly jet in the initial state.
Abstract
Previous studies have shown that the Madden–Julian oscillation (MJO) has a global impact that may provide an important source of skill for subseasonal predictions. The extratropical response was found to be the strongest when the tropical diabatic heating has a dipole structure with convection anomaly centers of opposite sign in the eastern Indian Ocean and the western Pacific. A positive (negative) MJO dipole heating refers to that with heating (cooling) in the eastern Indian Ocean and cooling (heating) in the western Pacific. In this study, two aspects of the extratropical response to the MJO are examined: 1) nonlinearity, which answers the question of whether the response to a positive MJO dipole heating is the mirror image of that to a negative MJO, and 2) sensitivity to the initial state, which explores the dependence of the extratropical response on the initial condition of the westerly jet.
Ensemble integrations using a primitive-equation global atmospheric circulation model are performed with anomalous tropical thermal forcings that resemble a positive MJO (+MJO) and a negative MJO (−MJO). The response in the first week is largely linear. After that, significant asymmetry is found between the response in the positive MJO and the negative MJO. The 500-hPa negative geopotential height response in the North Pacific of the −MJO run is located about 30° east of the positive height response of the +MJO run. There is also an eastward shift of the extratropical wave train in the Pacific–North American region. This simulated nonlinearity is in agreement with the observations. The two leading response patterns among the ensemble members are identified by an empirical orthogonal function (EOF) analysis. EOF1 represents an eastward shift of the wave train, which is positively correlated with strengthening of the East Asian subtropical upper-troposphere westerly jet in the initial condition. On the other hand, EOF2 represents an amplification of the response, which is associated with a southward shift of the westerly jet in the initial state.
Abstract
This study examines the evolution of the interannual warm Arctic–cold continents (WACC) pattern over the North American sector, which refers to the warm Arctic–cold North American pattern (WACNA), and explores its driving mechanism. WACNA features a pair of opposite surface air temperature anomalies centered over the Chukchi–Bering Seas and the North American Great Plains. A negative phase of the warm Arctic–cold Eurasia (WACE) pattern tends to lead a positive phase of the WACNA pattern by about 25 days. Negative Asian–Bering–North American (ABNA)- and Pacific–North American (PNA)-like atmospheric circulation patterns also appear upstream and precede a positive WACNA by about 25 days, gradually develop, reach their peaks when both circulation patterns lead the WACNA by 5 days, and weaken afterward. The negative ABNA-like pattern can be driven by the Siberian snow decline that is related to a negative WACE pattern and its featured Eurasian warming, whereas the negative PNA-like pattern is influenced by negative SST anomalies over the tropical central-eastern Pacific Ocean that resemble the tropical ENSO variability. The surface signatures of both patterns highlight a horseshoe-shaped high pressure anomaly straddling over the Gulf of Alaska, Alaska, and northwestern Canada. The anomalous warm advection from the North Pacific and cold advection from the Arctic that follow the circulation anomalies, as well as sea ice declines over the Chukchi–Bering Seas and growth over Hudson Bay, lead to the formation of the positive WACNA pattern. Processes with circulation anomalies of opposite signs will likewise lead to the negative WACNA pattern.
Abstract
This study examines the evolution of the interannual warm Arctic–cold continents (WACC) pattern over the North American sector, which refers to the warm Arctic–cold North American pattern (WACNA), and explores its driving mechanism. WACNA features a pair of opposite surface air temperature anomalies centered over the Chukchi–Bering Seas and the North American Great Plains. A negative phase of the warm Arctic–cold Eurasia (WACE) pattern tends to lead a positive phase of the WACNA pattern by about 25 days. Negative Asian–Bering–North American (ABNA)- and Pacific–North American (PNA)-like atmospheric circulation patterns also appear upstream and precede a positive WACNA by about 25 days, gradually develop, reach their peaks when both circulation patterns lead the WACNA by 5 days, and weaken afterward. The negative ABNA-like pattern can be driven by the Siberian snow decline that is related to a negative WACE pattern and its featured Eurasian warming, whereas the negative PNA-like pattern is influenced by negative SST anomalies over the tropical central-eastern Pacific Ocean that resemble the tropical ENSO variability. The surface signatures of both patterns highlight a horseshoe-shaped high pressure anomaly straddling over the Gulf of Alaska, Alaska, and northwestern Canada. The anomalous warm advection from the North Pacific and cold advection from the Arctic that follow the circulation anomalies, as well as sea ice declines over the Chukchi–Bering Seas and growth over Hudson Bay, lead to the formation of the positive WACNA pattern. Processes with circulation anomalies of opposite signs will likewise lead to the negative WACNA pattern.
Abstract
The relationship between the interannual wintertime variability of the North Atlantic Oscillation (NAO) and tropical heating anomalies is examined using the NCEP–NCAR reanalysis and observation-based sea surface temperature (SST) and precipitation data for the period from 1980 to 2011. The NAO is found to be significantly correlated with the precipitation anomalies in the tropical Indian Ocean and tropical American–Atlantic region, but not with the underlying SST anomalies. The tropical heating impact on the NAO is examined and the evolution process of the influence is explored by numerical experiments using a primitive equation atmospheric model forced by atmospheric heating perturbations. Results from the reanalysis data and numerical experiments suggest that the atmospheric heating in the tropical Indian Ocean appears to be a driving force for the NAO variability. The atmospheric response to the tropical heating involves the combined effects of Rossby wave dispersion, normal mode instability, and transient eddy feedback. The remote forcing influence on the NAO tends to be organized and achieved by the circumglobal teleconnection pattern. By contrast, the influence of the tropical American–Atlantic heating on the NAO is weak. The linkage between the NAO and the tropical American–Atlantic heating is likely through the anomalously meridional atmospheric circulation over the Atlantic Ocean.
Abstract
The relationship between the interannual wintertime variability of the North Atlantic Oscillation (NAO) and tropical heating anomalies is examined using the NCEP–NCAR reanalysis and observation-based sea surface temperature (SST) and precipitation data for the period from 1980 to 2011. The NAO is found to be significantly correlated with the precipitation anomalies in the tropical Indian Ocean and tropical American–Atlantic region, but not with the underlying SST anomalies. The tropical heating impact on the NAO is examined and the evolution process of the influence is explored by numerical experiments using a primitive equation atmospheric model forced by atmospheric heating perturbations. Results from the reanalysis data and numerical experiments suggest that the atmospheric heating in the tropical Indian Ocean appears to be a driving force for the NAO variability. The atmospheric response to the tropical heating involves the combined effects of Rossby wave dispersion, normal mode instability, and transient eddy feedback. The remote forcing influence on the NAO tends to be organized and achieved by the circumglobal teleconnection pattern. By contrast, the influence of the tropical American–Atlantic heating on the NAO is weak. The linkage between the NAO and the tropical American–Atlantic heating is likely through the anomalously meridional atmospheric circulation over the Atlantic Ocean.
Abstract
Predicting surface air temperature (T) is a major task of North American (NA) winter seasonal prediction. It has been recognized that variations of the NA winter T’s can be associated with El Niño–Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). This study presents observed evidence that variability in snow cover over the Tibetan Plateau (TP) and its adjacent areas in prior autumn (September–November) is significantly correlated with the first principal component (PC1) of the NA winter T’s, which features a meridional seesaw pattern over the NA continent. The autumn TP snow cover anomaly can persist into the following winter through a positive feedback between snow cover and the atmosphere. A positive TP snow cover anomaly may induce a negative sea level pressure and geopotential height anomaly over the eastern North Pacific, a positive geopotential height anomaly over Canada, and a negative anomaly over the southeastern United States—a structure very similar to the positive phase of the Pacific–North America (PNA) pattern. This pattern usually favors the occurrence of a warm–north, cold–south winter over the NA continent. When a negative snow cover anomaly occurs, the situation tends to be opposite. Since the autumn TP snow cover shows a weak correlation with ENSO, it provides a new predictability source for NA winter T’s.
Based on the above results, an empirical model is constructed to predict PC1 using a combination of autumn TP snow cover and other sea surface temperature anomalies related to ENSO and the NAO. Hindcasts and real forecasts are performed for the 1972–2003 and 2004–09 periods, respectively. Both show a promising prediction skill. As far as PC1 is concerned, the empirical model hindcast performs better than the ensemble mean of four dynamical models from the Canadian Meteorological Centre. Particularly, the real forecast of the empirical model exhibits a better performance in predicting the extreme phases of PC1—that is, the extremely warm winter over Canada in 2009/10—should the model include the autumn TP snow cover impacts. Since all these predictors can be readily monitored in real time, this empirical model provides a real-time forecast tool for NA winter climate.
Abstract
Predicting surface air temperature (T) is a major task of North American (NA) winter seasonal prediction. It has been recognized that variations of the NA winter T’s can be associated with El Niño–Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). This study presents observed evidence that variability in snow cover over the Tibetan Plateau (TP) and its adjacent areas in prior autumn (September–November) is significantly correlated with the first principal component (PC1) of the NA winter T’s, which features a meridional seesaw pattern over the NA continent. The autumn TP snow cover anomaly can persist into the following winter through a positive feedback between snow cover and the atmosphere. A positive TP snow cover anomaly may induce a negative sea level pressure and geopotential height anomaly over the eastern North Pacific, a positive geopotential height anomaly over Canada, and a negative anomaly over the southeastern United States—a structure very similar to the positive phase of the Pacific–North America (PNA) pattern. This pattern usually favors the occurrence of a warm–north, cold–south winter over the NA continent. When a negative snow cover anomaly occurs, the situation tends to be opposite. Since the autumn TP snow cover shows a weak correlation with ENSO, it provides a new predictability source for NA winter T’s.
Based on the above results, an empirical model is constructed to predict PC1 using a combination of autumn TP snow cover and other sea surface temperature anomalies related to ENSO and the NAO. Hindcasts and real forecasts are performed for the 1972–2003 and 2004–09 periods, respectively. Both show a promising prediction skill. As far as PC1 is concerned, the empirical model hindcast performs better than the ensemble mean of four dynamical models from the Canadian Meteorological Centre. Particularly, the real forecast of the empirical model exhibits a better performance in predicting the extreme phases of PC1—that is, the extremely warm winter over Canada in 2009/10—should the model include the autumn TP snow cover impacts. Since all these predictors can be readily monitored in real time, this empirical model provides a real-time forecast tool for NA winter climate.