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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
The output of two global atmospheric models participating in the second phase of the Canadian Historical Forecasting Project (HFP2) is utilized to assess the forecast skill of the Madden–Julian oscillation (MJO). The two models are the third generation of the general circulation model (GCM3) of the Canadian Centre for Climate Modeling and Analysis (CCCma) and the Global Environmental Multiscale (GEM) model of Recherche en Prévision Numérique (RPN). Space–time spectral analysis of the daily precipitation in near-equilibrium integrations reveals that GEM has a better representation of the convectively coupled equatorial waves including the MJO, Kelvin, equatorial Rossby (ER), and mixed Rossby–gravity (MRG) waves. An objective of this study is to examine how the MJO forecast skill is influenced by the model’s ability in representing the convectively coupled equatorial waves.
The observed MJO signal is measured by a bivariate index that is obtained by projecting the combined fields of the 15°S–15°N meridionally averaged precipitation rate and the zonal winds at 850 and 200 hPa onto the two leading empirical orthogonal function (EOF) structures as derived using the same meridionally averaged variables following a similar approach used recently by Wheeler and Hendon. The forecast MJO index, on the other hand, is calculated by projecting the forecast variables onto the same two EOFs.
With the HFP2 hindcast output spanning 35 yr, for the first time the MJO forecast skill of dynamical models is assessed over such a long time period with a significant and robust result. The result shows that the GEM model produces a significantly better level of forecast skill for the MJO in the first 2 weeks. The difference is larger in Northern Hemisphere winter than in summer, when the correlation skill score drops below 0.50 at a lead time of 10 days for GEM whereas it is at 6 days for GCM3. At lead times longer than about 15 days, GCM3 performs slightly better. There are some features that are common for the two models. The forecast skill is better in winter than in summer. Forecasts initialized with a large amplitude for the MJO are found to be more skillful than those with a weak MJO signal in the initial conditions. The forecast skill is dependent on the phase of the MJO at the initial conditions. Forecasts initialized with an MJO that has an active convection in tropical Africa and the Indian Ocean sector have a better level of forecast skill than those initialized with a different phase of the MJO.
Abstract
The output of two global atmospheric models participating in the second phase of the Canadian Historical Forecasting Project (HFP2) is utilized to assess the forecast skill of the Madden–Julian oscillation (MJO). The two models are the third generation of the general circulation model (GCM3) of the Canadian Centre for Climate Modeling and Analysis (CCCma) and the Global Environmental Multiscale (GEM) model of Recherche en Prévision Numérique (RPN). Space–time spectral analysis of the daily precipitation in near-equilibrium integrations reveals that GEM has a better representation of the convectively coupled equatorial waves including the MJO, Kelvin, equatorial Rossby (ER), and mixed Rossby–gravity (MRG) waves. An objective of this study is to examine how the MJO forecast skill is influenced by the model’s ability in representing the convectively coupled equatorial waves.
The observed MJO signal is measured by a bivariate index that is obtained by projecting the combined fields of the 15°S–15°N meridionally averaged precipitation rate and the zonal winds at 850 and 200 hPa onto the two leading empirical orthogonal function (EOF) structures as derived using the same meridionally averaged variables following a similar approach used recently by Wheeler and Hendon. The forecast MJO index, on the other hand, is calculated by projecting the forecast variables onto the same two EOFs.
With the HFP2 hindcast output spanning 35 yr, for the first time the MJO forecast skill of dynamical models is assessed over such a long time period with a significant and robust result. The result shows that the GEM model produces a significantly better level of forecast skill for the MJO in the first 2 weeks. The difference is larger in Northern Hemisphere winter than in summer, when the correlation skill score drops below 0.50 at a lead time of 10 days for GEM whereas it is at 6 days for GCM3. At lead times longer than about 15 days, GCM3 performs slightly better. There are some features that are common for the two models. The forecast skill is better in winter than in summer. Forecasts initialized with a large amplitude for the MJO are found to be more skillful than those with a weak MJO signal in the initial conditions. The forecast skill is dependent on the phase of the MJO at the initial conditions. Forecasts initialized with an MJO that has an active convection in tropical Africa and the Indian Ocean sector have a better level of forecast skill than those initialized with a different phase of the MJO.
Abstract
In the second phase of the Canadian Historical Forecasting Project (HFP2), four global atmospheric general circulation models (GCMs) were used to perform seasonal forecasts over the period of 1969–2003. Little predictive skill was found from the uncalibrated GCM ensemble seasonal predictions for the Canadian winter precipitation. This study is an effort to improve the precipitation forecasts through a postprocessing approach.
Canadian winter precipitation is significantly influenced by two of the most important atmospheric large-scale patterns: the Pacific–North American pattern (PNA) and the North Atlantic Oscillation (NAO). The time variations of these two patterns were found to be significantly correlated with those of the leading singular value decomposition (SVD) modes that relate the ensemble mean forecast 500-mb geopotential height over the Northern Hemisphere and the tropical Pacific SST in the previous month (November). A statistical approach to correct the ensemble forecasts was formulated based on the regression of the model’s leading forced SVD patterns and the observed seasonal mean precipitation. The performance of the corrected forecasts was assessed by comparing its cross-validated skill with that of the original GCM ensemble mean forecasts. The results show that the corrected forecasts predict the Canadian winter precipitation with statistically significant skill over the southern prairies and a large area of Québec–Ontario.
Abstract
In the second phase of the Canadian Historical Forecasting Project (HFP2), four global atmospheric general circulation models (GCMs) were used to perform seasonal forecasts over the period of 1969–2003. Little predictive skill was found from the uncalibrated GCM ensemble seasonal predictions for the Canadian winter precipitation. This study is an effort to improve the precipitation forecasts through a postprocessing approach.
Canadian winter precipitation is significantly influenced by two of the most important atmospheric large-scale patterns: the Pacific–North American pattern (PNA) and the North Atlantic Oscillation (NAO). The time variations of these two patterns were found to be significantly correlated with those of the leading singular value decomposition (SVD) modes that relate the ensemble mean forecast 500-mb geopotential height over the Northern Hemisphere and the tropical Pacific SST in the previous month (November). A statistical approach to correct the ensemble forecasts was formulated based on the regression of the model’s leading forced SVD patterns and the observed seasonal mean precipitation. The performance of the corrected forecasts was assessed by comparing its cross-validated skill with that of the original GCM ensemble mean forecasts. The results show that the corrected forecasts predict the Canadian winter precipitation with statistically significant skill over the southern prairies and a large area of Québec–Ontario.
Abstract
A statistical postprocessing approach is applied to seasonal forecasts of surface air temperatures (SAT) over North America in fall, when the original uncalibrated predictions have little skill. The data used are ensemble-mean seasonal forecasts from four atmospheric general circulation models (GCMs) in the Canadian Historical Forecasting Project (HFP2) during the period 1969–2001. The statistical postprocessing uses the relationship between the predicted 500-hPa geopotential height (Z500) and the observed SAT to calibrate the SAT forecasts. The dimensions of the predicted Z500 fields are reduced to three modes with fixed spatial structures but time-dependent amplitudes. The latter are obtained through a singular value decomposition (SVD) analysis linking the variability of the ensemble-mean predicted Z500 to the tropical Pacific sea surface temperatures (SSTs). Results show that the postprocessing significantly improves the predictive skill of North American SAT in fall. The distributions of the SAT temporal standard deviation and the skill of the postprocessed ensemble forecasts are consistent among the GCMs, indicating that the approach is effective in reducing the model-dependent part of the errors associated with GCMs.
Abstract
A statistical postprocessing approach is applied to seasonal forecasts of surface air temperatures (SAT) over North America in fall, when the original uncalibrated predictions have little skill. The data used are ensemble-mean seasonal forecasts from four atmospheric general circulation models (GCMs) in the Canadian Historical Forecasting Project (HFP2) during the period 1969–2001. The statistical postprocessing uses the relationship between the predicted 500-hPa geopotential height (Z500) and the observed SAT to calibrate the SAT forecasts. The dimensions of the predicted Z500 fields are reduced to three modes with fixed spatial structures but time-dependent amplitudes. The latter are obtained through a singular value decomposition (SVD) analysis linking the variability of the ensemble-mean predicted Z500 to the tropical Pacific sea surface temperatures (SSTs). Results show that the postprocessing significantly improves the predictive skill of North American SAT in fall. The distributions of the SAT temporal standard deviation and the skill of the postprocessed ensemble forecasts are consistent among the GCMs, indicating that the approach is effective in reducing the model-dependent part of the errors associated with GCMs.
Abstract
Based on the adjusted daily total precipitation data at Canadian stations and the Climate Prediction Center Merged Analysis of Precipitation (CMAP) data during the most recent 30 Northern Hemisphere winters, the connection between the tropical convection of the Madden–Julian oscillation (MJO) and the intraseasonal variability of precipitation in Canada is investigated. The dominant convection patterns associated with the MJO are represented by the two leading modes of the empirical orthogonal function (EOF) analysis that is applied to the pentad outgoing longwave radiation (OLR) in the equatorial Indian Ocean and western Pacific. The first EOF mode is characterized by a single convection center near the Maritime Continent, whereas the second EOF has an east–west dipole structure with enhanced precipitation over the Indian Ocean and reduced convective activity over the tropical western Pacific. Lagged regression analysis reveals significant precipitation anomalies in Canada associated with the tropical convection of the MJO. Above-normal precipitation starts to occur in the west coast of Canada one pentad after a positive EOF2 phase. In the next two pentads, positive precipitation anomalies extend to a large area of south Canada. At the same time, the northeast region experiences reduced precipitation. For strong MJO events when the principal component of EOF2 exceeds its standard deviation, the precipitation anomaly in the west coast of Canada can reach about 20%–30% of its standard deviation of pentad-to-pentad variability. A linearized global primitive equation model is utilized to assess the cause of the intraseasonal variability in the Northern Hemisphere extratropics and its influence on North American weather associated with the tropical heating of the MJO.
Abstract
Based on the adjusted daily total precipitation data at Canadian stations and the Climate Prediction Center Merged Analysis of Precipitation (CMAP) data during the most recent 30 Northern Hemisphere winters, the connection between the tropical convection of the Madden–Julian oscillation (MJO) and the intraseasonal variability of precipitation in Canada is investigated. The dominant convection patterns associated with the MJO are represented by the two leading modes of the empirical orthogonal function (EOF) analysis that is applied to the pentad outgoing longwave radiation (OLR) in the equatorial Indian Ocean and western Pacific. The first EOF mode is characterized by a single convection center near the Maritime Continent, whereas the second EOF has an east–west dipole structure with enhanced precipitation over the Indian Ocean and reduced convective activity over the tropical western Pacific. Lagged regression analysis reveals significant precipitation anomalies in Canada associated with the tropical convection of the MJO. Above-normal precipitation starts to occur in the west coast of Canada one pentad after a positive EOF2 phase. In the next two pentads, positive precipitation anomalies extend to a large area of south Canada. At the same time, the northeast region experiences reduced precipitation. For strong MJO events when the principal component of EOF2 exceeds its standard deviation, the precipitation anomaly in the west coast of Canada can reach about 20%–30% of its standard deviation of pentad-to-pentad variability. A linearized global primitive equation model is utilized to assess the cause of the intraseasonal variability in the Northern Hemisphere extratropics and its influence on North American weather associated with the tropical heating of the MJO.
Abstract
Results from two simulations using the Global Environmental Multiscale (GEM) model in a variable-resolution modeling approach are evaluated. Simulations with a highly resolved domain positioned over North America and over the tropical Pacific–eastern Indian Ocean are assessed against the GEM uniform grid control run, 40-yr ECMWF Re-Analysis (ERA-40), and available observations in terms of regional and global climate and interannual variability.
It is found that the variable-resolution configurations realistically simulate global and regional climate over North America with seasonal means and variability generally closer to ERA-40 or observations than the control run. Systematic errors of the control run are still present within the variable-resolution simulations but alleviated to some extent over their respective highly resolved domains. Additionally, there is some evidence of performance deterioration due to the increased resolution.
There is little evidence that an increased resolution over the tropical Pacific–eastern Indian Ocean, with better-resolved local processes (e.g., convection and equatorial waves), has a significant impact on the extratropical time mean fields. However, in terms of simulating the Northern Hemisphere atmospheric flow anomaly associated with the dominant mode of sea surface temperature interannual variability in the equatorial eastern Pacific (i.e., El Niño), both stretched configurations have more realistic teleconnection patterns than the control run.
Abstract
Results from two simulations using the Global Environmental Multiscale (GEM) model in a variable-resolution modeling approach are evaluated. Simulations with a highly resolved domain positioned over North America and over the tropical Pacific–eastern Indian Ocean are assessed against the GEM uniform grid control run, 40-yr ECMWF Re-Analysis (ERA-40), and available observations in terms of regional and global climate and interannual variability.
It is found that the variable-resolution configurations realistically simulate global and regional climate over North America with seasonal means and variability generally closer to ERA-40 or observations than the control run. Systematic errors of the control run are still present within the variable-resolution simulations but alleviated to some extent over their respective highly resolved domains. Additionally, there is some evidence of performance deterioration due to the increased resolution.
There is little evidence that an increased resolution over the tropical Pacific–eastern Indian Ocean, with better-resolved local processes (e.g., convection and equatorial waves), has a significant impact on the extratropical time mean fields. However, in terms of simulating the Northern Hemisphere atmospheric flow anomaly associated with the dominant mode of sea surface temperature interannual variability in the equatorial eastern Pacific (i.e., El Niño), both stretched configurations have more realistic teleconnection patterns than the control run.
Abstract
A multivariable linear regression model is constructed based on the status of the Madden–Julian oscillation (MJO) and persistence in order to forecast wintertime surface air temperature anomalies over North America out to 4 pentads (20 days). The current and previous states of the MJO are utilized as predictors, based on the Real-time Multivariate (RMM) indices of Wheeler and Hendon. Beyond the persistence-driven first pentad, potentially useful skill is mainly observed during strong MJO events in phases 3, 4, 7, and 8, which correspond to a dipole diabatic heating anomaly in the tropical Indian Ocean and western Pacific. This skill is largely centered over the eastern United States and the Great Lakes region during pentads 2 and 3.
Abstract
A multivariable linear regression model is constructed based on the status of the Madden–Julian oscillation (MJO) and persistence in order to forecast wintertime surface air temperature anomalies over North America out to 4 pentads (20 days). The current and previous states of the MJO are utilized as predictors, based on the Real-time Multivariate (RMM) indices of Wheeler and Hendon. Beyond the persistence-driven first pentad, potentially useful skill is mainly observed during strong MJO events in phases 3, 4, 7, and 8, which correspond to a dipole diabatic heating anomaly in the tropical Indian Ocean and western Pacific. This skill is largely centered over the eastern United States and the Great Lakes region during pentads 2 and 3.
Abstract
A new statistical–dynamical downscaling procedure is developed and then applied to high-resolution (regional) time series generation and wind resource assessment. The statistical module of the new procedure uses empirical orthogonal function (EOF) analysis for the generation of large-scale atmospheric component patterns. The dominant atmospheric patterns (associated with the EOF modes explaining most of the statistical variance) are then dynamically downscaled or adjusted to high-resolution terrain and surface roughness by using the Global Environmental Multiscale–Limited Area Model (GEM-LAM). Regional time series are constructed using the model outputs. The new method is applied to the Gaspé region of Québec in Canada. The dataset used is the NCEP–NCAR reanalysis of wind, temperature, humidity, and geopotential height during the period 1958–2004. Regional time series of wind speed and temperature are constructed, and a numerical wind atlas of the Gaspé region is generated. The generated time series and the numerical wind atlas are compared with observations at different masts located in the Gaspé Peninsula and are also compared with a numerical wind atlas for the same region generated in Yu et al. The results suggest that the newly developed procedure can be useful to generate regional time series and reasonably accurate numerical wind atlases using large-scale data with much less computational effort than previous techniques.
Abstract
A new statistical–dynamical downscaling procedure is developed and then applied to high-resolution (regional) time series generation and wind resource assessment. The statistical module of the new procedure uses empirical orthogonal function (EOF) analysis for the generation of large-scale atmospheric component patterns. The dominant atmospheric patterns (associated with the EOF modes explaining most of the statistical variance) are then dynamically downscaled or adjusted to high-resolution terrain and surface roughness by using the Global Environmental Multiscale–Limited Area Model (GEM-LAM). Regional time series are constructed using the model outputs. The new method is applied to the Gaspé region of Québec in Canada. The dataset used is the NCEP–NCAR reanalysis of wind, temperature, humidity, and geopotential height during the period 1958–2004. Regional time series of wind speed and temperature are constructed, and a numerical wind atlas of the Gaspé region is generated. The generated time series and the numerical wind atlas are compared with observations at different masts located in the Gaspé Peninsula and are also compared with a numerical wind atlas for the same region generated in Yu et al. The results suggest that the newly developed procedure can be useful to generate regional time series and reasonably accurate numerical wind atlases using large-scale data with much less computational effort than previous techniques.
Abstract
A long integration of a primitive equation dry atmospheric model with time-independent forcing under boreal winter conditions is analyzed. A variety of techniques such as time filtering, space–time spectral analysis, and lag regressions are used to identify tropical waves. It is evident that oscillations with intraseasonal time scales and a Kelvin wave structure exist in the model tropical atmosphere. Coherent eastward propagations in the 250-hPa velocity potential and zonal wind are found, with a speed of about 15 m s−1. The oscillation is stronger in the Eastern Hemisphere than in the Western Hemisphere.
Interactions between the tropical and extratropical flows are found to be responsible for the simulated intraseasonal variability. Wave activity flux analysis reveals that a tropical influence occurs in the North Pacific region where a northeastward wave activity flux is found associated with the tropical divergent flow in the western and central Pacific. In the North Atlantic sector, on the other hand, a strong extratropical influence is observed with a southward wave activity flux into the Tropics. The extratropical low-frequency variability develops by extracting kinetic energy from the basic mean flow and through interactions with synoptic-scale transient eddies. Linear experiments show that the tropical atmospheric response to the extratropical forcing in the North Atlantic leads to an eastward-propagating wave in the tropical easterly mean flow of the Eastern Hemisphere.
Abstract
A long integration of a primitive equation dry atmospheric model with time-independent forcing under boreal winter conditions is analyzed. A variety of techniques such as time filtering, space–time spectral analysis, and lag regressions are used to identify tropical waves. It is evident that oscillations with intraseasonal time scales and a Kelvin wave structure exist in the model tropical atmosphere. Coherent eastward propagations in the 250-hPa velocity potential and zonal wind are found, with a speed of about 15 m s−1. The oscillation is stronger in the Eastern Hemisphere than in the Western Hemisphere.
Interactions between the tropical and extratropical flows are found to be responsible for the simulated intraseasonal variability. Wave activity flux analysis reveals that a tropical influence occurs in the North Pacific region where a northeastward wave activity flux is found associated with the tropical divergent flow in the western and central Pacific. In the North Atlantic sector, on the other hand, a strong extratropical influence is observed with a southward wave activity flux into the Tropics. The extratropical low-frequency variability develops by extracting kinetic energy from the basic mean flow and through interactions with synoptic-scale transient eddies. Linear experiments show that the tropical atmospheric response to the extratropical forcing in the North Atlantic leads to an eastward-propagating wave in the tropical easterly mean flow of the Eastern Hemisphere.
