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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
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.
Abstract
A primitive equations dry atmospheric model is used to investigate the atmospheric response to a tropical diabatic forcing pattern and explore how the atmospheric response changes as a function of the amplitude of the forcing. The forcing anomaly represents a linear fit of the model forcing to a tropical SST pattern of an El Niño/La Niña type. The time-averaged 500-hPa geopotential height anomaly responses of two long integrations, with forcing anomalies of equal amplitudes but opposite signs, show an asymmetric feature that is similar to observations and to previous modeling results related to El Niño and La Niña. Ensemble experiments with 61 different amplitudes of this forcing pattern are conducted. An EOF analysis of the ensemble mean of the 90-day-averaged 500-hPa height for different amplitudes of forcings shows that the leading mode of the forced variability resembles the Pacific–North American (PNA) pattern, while the second mode is a wave train across the North Atlantic to Eurasia. The relationship between the amplitude of the PNA mode and the amplitude of the forcing is linear, while the amplitude of the Atlantic/Eurasian mode has a nearly parabolic relationship with the amplitude of the forcing. A set of linear experiments with forcing perturbations and eddy flux anomalies associated with the positive and negative amplitudes of forcing conditions indicates that the nonlinearity of the extratropical response primarily results from the modification of the “basic state” caused by the large-amplitude forcing and the subsequent sensitivity of the response to that modified basic flow. A La Niña–type basic state yields a stronger response in the North Atlantic to the tropical Pacific forcing than does an El Niño–type basic state.
Abstract
A primitive equations dry atmospheric model is used to investigate the atmospheric response to a tropical diabatic forcing pattern and explore how the atmospheric response changes as a function of the amplitude of the forcing. The forcing anomaly represents a linear fit of the model forcing to a tropical SST pattern of an El Niño/La Niña type. The time-averaged 500-hPa geopotential height anomaly responses of two long integrations, with forcing anomalies of equal amplitudes but opposite signs, show an asymmetric feature that is similar to observations and to previous modeling results related to El Niño and La Niña. Ensemble experiments with 61 different amplitudes of this forcing pattern are conducted. An EOF analysis of the ensemble mean of the 90-day-averaged 500-hPa height for different amplitudes of forcings shows that the leading mode of the forced variability resembles the Pacific–North American (PNA) pattern, while the second mode is a wave train across the North Atlantic to Eurasia. The relationship between the amplitude of the PNA mode and the amplitude of the forcing is linear, while the amplitude of the Atlantic/Eurasian mode has a nearly parabolic relationship with the amplitude of the forcing. A set of linear experiments with forcing perturbations and eddy flux anomalies associated with the positive and negative amplitudes of forcing conditions indicates that the nonlinearity of the extratropical response primarily results from the modification of the “basic state” caused by the large-amplitude forcing and the subsequent sensitivity of the response to that modified basic flow. A La Niña–type basic state yields a stronger response in the North Atlantic to the tropical Pacific forcing than does an El Niño–type basic state.
Abstract
Ensemble integrations using a primitive-equation dry atmospheric model were performed to investigate the atmospheric transient response to tropical thermal forcings that resemble El Niño and La Niña. The response develops in the North Pacific within 1 week after the integration. The signal in the North Atlantic and Europe is established by the end of the second week. Significant asymmetry was found between the responses in El Niño and La Niña that is similar to the observations, that is, one feature is that the 550-hPa positive height response in the North Pacific of the La Niña run is located about 30° west of the negative response of the El Niño run; another feature is that the responses in the North Atlantic and Europe for the La Niña and El Niño cases have similar patterns with the same polarity. The first feature is established within 2 weeks of the integration, while the second feature develops starting from the end of the second week. Several factors contribute to this nonlinearity of the response. In the Tropics, the shape of the Rossby wave response and the zonal extent of the Kelvin wave are not symmetric between El Niño and La Niña, which seems to be associated with the dependence of the wave property on the modified zonal mean flow. This is especially important in the equatorial region to the west of the forcing, which is likely responsible for the phase shift of the major extratropical response in the North Pacific. The transient eddy activity in the extratropics feeds back to the response and helps to maintain the nonlinearity.
Abstract
Ensemble integrations using a primitive-equation dry atmospheric model were performed to investigate the atmospheric transient response to tropical thermal forcings that resemble El Niño and La Niña. The response develops in the North Pacific within 1 week after the integration. The signal in the North Atlantic and Europe is established by the end of the second week. Significant asymmetry was found between the responses in El Niño and La Niña that is similar to the observations, that is, one feature is that the 550-hPa positive height response in the North Pacific of the La Niña run is located about 30° west of the negative response of the El Niño run; another feature is that the responses in the North Atlantic and Europe for the La Niña and El Niño cases have similar patterns with the same polarity. The first feature is established within 2 weeks of the integration, while the second feature develops starting from the end of the second week. Several factors contribute to this nonlinearity of the response. In the Tropics, the shape of the Rossby wave response and the zonal extent of the Kelvin wave are not symmetric between El Niño and La Niña, which seems to be associated with the dependence of the wave property on the modified zonal mean flow. This is especially important in the equatorial region to the west of the forcing, which is likely responsible for the phase shift of the major extratropical response in the North Pacific. The transient eddy activity in the extratropics feeds back to the response and helps to maintain the nonlinearity.
Abstract
A primitive equation dry atmospheric model is used to perform ensemble seasonal predictions. The predictions are done for 51 winter seasons [December–January–February (DJF)] from 1948 to 1998. Ensembles of 24 forecasts are produced, with initial conditions of 1 December plus small perturbations. The model uses a forcing field that is calculated empirically from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalyses. The forcing used to forecast a given winter is the sum of its winter climatological forcing plus an anomaly. The anomalous forcing is obtained as that of the month prior to the start of the forecast (November), which is also calculated from NCEP data. The predictions are thus made without using any information about the season to be predicted.
The ensemble-mean predictions for the 51 winters are verified against the NCEP–NCAR reanalyses. Comparisons are made with the results obtained with a full GCM. It is found that the skill of the simple GCM is comparable in many ways to that of the full GCM. The skill in predicting the amplitude of the main patterns of Northern Hemisphere mean-seasonal variability, the Arctic Oscillation (AO) and the Pacific–North American (PNA) pattern is also discussed. The simple GCM has skill not only in predicting the PNA pattern during winters with strong ENSO forcing, but it also has skill in predicting the AO in winters without appreciable ENSO forcing.
Abstract
A primitive equation dry atmospheric model is used to perform ensemble seasonal predictions. The predictions are done for 51 winter seasons [December–January–February (DJF)] from 1948 to 1998. Ensembles of 24 forecasts are produced, with initial conditions of 1 December plus small perturbations. The model uses a forcing field that is calculated empirically from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalyses. The forcing used to forecast a given winter is the sum of its winter climatological forcing plus an anomaly. The anomalous forcing is obtained as that of the month prior to the start of the forecast (November), which is also calculated from NCEP data. The predictions are thus made without using any information about the season to be predicted.
The ensemble-mean predictions for the 51 winters are verified against the NCEP–NCAR reanalyses. Comparisons are made with the results obtained with a full GCM. It is found that the skill of the simple GCM is comparable in many ways to that of the full GCM. The skill in predicting the amplitude of the main patterns of Northern Hemisphere mean-seasonal variability, the Arctic Oscillation (AO) and the Pacific–North American (PNA) pattern is also discussed. The simple GCM has skill not only in predicting the PNA pattern during winters with strong ENSO forcing, but it also has skill in predicting the AO in winters without appreciable ENSO forcing.
Abstract
The mei-yu onset over the middle to lower reaches of the Yangtze River Valley (MLYRV) varies considerably from early June to mid-July, which leads to large interannual changes in rainy-season length, total summer rainfall, and flooding potential. Previous studies have investigated the impact of El Niño–Southern Oscillation (ENSO) on the mei-yu onset. This study shows that a strong (weak) East Asian and western North Pacific (EAWNP) intraseasonal oscillation (ISO) in spring leads to an early (late) onset of the mei-yu over the MLYRV, and this ISO–mei-yu relationship is attributed to different types of ENSO in the preceding winter. A strong EAWNP ISO in spring is related to an eastern Pacific El Niño (EP El Niño) in the previous winter, and negative sea surface temperature (SST) anomalies in the eastern Indian Ocean and the South China Sea (SCS) in May, which can cause an early onset of the South China Sea summer monsoon that also favors an early mei-yu onset. In contrast, a weak EAWNP ISO in spring is associated with a central Pacific El Niño (CP El Niño) before April, but with an EP El Niño after April, and positive SST anomalies in both the eastern Indian Ocean and the SCS in May. A statistical forecast model combining the intensity of spring EAWNP ISO, CP ENSO, and EP ENSO indices shows a high prediction skill of the observed mei-yu onset date.
Abstract
The mei-yu onset over the middle to lower reaches of the Yangtze River Valley (MLYRV) varies considerably from early June to mid-July, which leads to large interannual changes in rainy-season length, total summer rainfall, and flooding potential. Previous studies have investigated the impact of El Niño–Southern Oscillation (ENSO) on the mei-yu onset. This study shows that a strong (weak) East Asian and western North Pacific (EAWNP) intraseasonal oscillation (ISO) in spring leads to an early (late) onset of the mei-yu over the MLYRV, and this ISO–mei-yu relationship is attributed to different types of ENSO in the preceding winter. A strong EAWNP ISO in spring is related to an eastern Pacific El Niño (EP El Niño) in the previous winter, and negative sea surface temperature (SST) anomalies in the eastern Indian Ocean and the South China Sea (SCS) in May, which can cause an early onset of the South China Sea summer monsoon that also favors an early mei-yu onset. In contrast, a weak EAWNP ISO in spring is associated with a central Pacific El Niño (CP El Niño) before April, but with an EP El Niño after April, and positive SST anomalies in both the eastern Indian Ocean and the SCS in May. A statistical forecast model combining the intensity of spring EAWNP ISO, CP ENSO, and EP ENSO indices shows a high prediction skill of the observed mei-yu onset date.
Abstract
Subseasonal variability of surface air temperature (SAT) over East Asia is analyzed using the NCEP–NCAR reanalysis of 34 Northern Hemisphere extended summers. An empirical orthogonal function (EOF) analysis is performed with pentad SAT data to identify the leading modes of subseasonal SAT variability. The first (EOF1) and second (EOF2) modes, which together account for about 35% of the total variance, correspond to a monopole structure of SAT anomaly in the whole East Asian region and a dipole structure with opposite signs of variability over the north and south East Asian continent, respectively. Lead–lag regressions are calculated in order to analyze how the large-scale atmospheric circulation evolves in association with the development of the leading SAT modes. An eastward propagation of the Rossby wave from the midlatitude Atlantic Ocean is observed about three pentads before EOF1. EOF2 is influenced by both the tropical Madden–Julian oscillation (MJO) and a midlatitude wave train. These results indicate that there is potential for prediction of the dominant SAT modes on the subseasonal time scale. The subseasonal prediction of the two dominant modes is further evaluated in the operational monthly forecasting system of Environment and Climate Change Canada (ECCC). The model shows a better forecast skill than the persistence forecast. The strength of the subseasonal signal in initial conditions impacts the forecast skill. The forecasts starting with strong EOF in the initial condition are more skillful than those initialized with weak EOF. The findings in the study contribute to improving the understanding of the subseasonal variability and SAT subseasonal forecasting in East Asia.
Abstract
Subseasonal variability of surface air temperature (SAT) over East Asia is analyzed using the NCEP–NCAR reanalysis of 34 Northern Hemisphere extended summers. An empirical orthogonal function (EOF) analysis is performed with pentad SAT data to identify the leading modes of subseasonal SAT variability. The first (EOF1) and second (EOF2) modes, which together account for about 35% of the total variance, correspond to a monopole structure of SAT anomaly in the whole East Asian region and a dipole structure with opposite signs of variability over the north and south East Asian continent, respectively. Lead–lag regressions are calculated in order to analyze how the large-scale atmospheric circulation evolves in association with the development of the leading SAT modes. An eastward propagation of the Rossby wave from the midlatitude Atlantic Ocean is observed about three pentads before EOF1. EOF2 is influenced by both the tropical Madden–Julian oscillation (MJO) and a midlatitude wave train. These results indicate that there is potential for prediction of the dominant SAT modes on the subseasonal time scale. The subseasonal prediction of the two dominant modes is further evaluated in the operational monthly forecasting system of Environment and Climate Change Canada (ECCC). The model shows a better forecast skill than the persistence forecast. The strength of the subseasonal signal in initial conditions impacts the forecast skill. The forecasts starting with strong EOF in the initial condition are more skillful than those initialized with weak EOF. The findings in the study contribute to improving the understanding of the subseasonal variability and SAT subseasonal forecasting in East Asia.