Search Results
You are looking at 1 - 5 of 5 items for :
- Author or Editor: Gilbert Brunet x
- Journal of Climate x
- Refine by Access: All Content x
Abstract
Based on the bivariate Madden–Julian oscillation (MJO) index defined by Wheeler and Hendon and 25 yr (1979–2004) of pentad data, the association between the North Atlantic Oscillation (NAO) and the MJO on the intraseasonal time scale during the Northern Hemisphere winter season is analyzed. Time-lagged composites and probability analysis of the NAO index for different phases of the MJO reveal a statistically significant two-way connection between the NAO and the tropical convection of the MJO. A significant increase of the NAO amplitude happens about 5–15 days after the MJO-related convection anomaly reaches the tropical Indian Ocean and western Pacific region. The development of the NAO is associated with a Rossby wave train in the upstream Pacific and North American region. In the Atlantic and African sector, there is an extratropical influence on the tropical intraseasonal variability. Certain phases of the MJO are preceded by the occurrence of strong NAOs. A significant change of upper zonal wind in the tropical Atlantic is caused by a modulated transient westerly momentum flux convergence associated with the NAO.
Abstract
Based on the bivariate Madden–Julian oscillation (MJO) index defined by Wheeler and Hendon and 25 yr (1979–2004) of pentad data, the association between the North Atlantic Oscillation (NAO) and the MJO on the intraseasonal time scale during the Northern Hemisphere winter season is analyzed. Time-lagged composites and probability analysis of the NAO index for different phases of the MJO reveal a statistically significant two-way connection between the NAO and the tropical convection of the MJO. A significant increase of the NAO amplitude happens about 5–15 days after the MJO-related convection anomaly reaches the tropical Indian Ocean and western Pacific region. The development of the NAO is associated with a Rossby wave train in the upstream Pacific and North American region. In the Atlantic and African sector, there is an extratropical influence on the tropical intraseasonal variability. Certain phases of the MJO are preceded by the occurrence of strong NAOs. A significant change of upper zonal wind in the tropical Atlantic is caused by a modulated transient westerly momentum flux convergence associated with the NAO.
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
Based on the database of the Subseasonal to Seasonal (S2S) Prediction project of the World Weather Research Programme (WWRP)/World Climate Research Programme (WCRP), the influence of the North Atlantic Oscillation (NAO) on the Madden–Julian oscillation (MJO) and its forecast skill is investigated. It is found that most models can capture the MJO phase changes following positive and negative NAO events. About 20 days after initializing with a positive (negative) NAO, the forecast MJO appears most frequently in phase 7 (3), which corresponds to reduced (enhanced) convection in the tropical Indian Ocean and enhanced (suppressed) convection in the western Pacific. In most S2S models the MJO prediction skill is dependent on the NAO amplitude and phase in the initial condition. A strong NAO leads to a better MJO forecast skill than a weak NAO. The MJO skill tends to be higher when the forecast starts from a negative NAO than a positive NAO. These results indicates that there is a strong northern extratropical influence on the MJO and its forecast skill. It is important for numerical models to better represent the NAO influence to improve the simulation and prediction of the MJO.
Abstract
Based on the database of the Subseasonal to Seasonal (S2S) Prediction project of the World Weather Research Programme (WWRP)/World Climate Research Programme (WCRP), the influence of the North Atlantic Oscillation (NAO) on the Madden–Julian oscillation (MJO) and its forecast skill is investigated. It is found that most models can capture the MJO phase changes following positive and negative NAO events. About 20 days after initializing with a positive (negative) NAO, the forecast MJO appears most frequently in phase 7 (3), which corresponds to reduced (enhanced) convection in the tropical Indian Ocean and enhanced (suppressed) convection in the western Pacific. In most S2S models the MJO prediction skill is dependent on the NAO amplitude and phase in the initial condition. A strong NAO leads to a better MJO forecast skill than a weak NAO. The MJO skill tends to be higher when the forecast starts from a negative NAO than a positive NAO. These results indicates that there is a strong northern extratropical influence on the MJO and its forecast skill. It is important for numerical models to better represent the NAO influence to improve the simulation and prediction of the MJO.
Abstract
The statistical model proposed by Vautard et al. is applied to the seasonal prediction of surface air temperatures over North America (Canada and the United States). This model is based on sea surface temperature predictors filtered by multichannel singular spectrum analysis (MSSA), which is equivalent here to a nonseasonal version of extended EOF analysis. Several versions of the MSSA model are proposed. The most successful one is based on a two-step procedure consisting in a prior prediction of filtered sea surface temperatures followed by a predictand specification stage.
The MSSA model is compared with the recent prediction technique based on canonical correlation analysis (CCA). The former model turns out, in this application, to be more skillful in most seasons than the latter. The differences are, however, marginal. The authors argue that these differences are due to the nonseasonal nature of the MSSA model and to overfitting problems inherent to CCA. Another advantage of the MSSA model relative to CCA is the possibility of easily transforming deterministic continuous forecasts into probabilistic categorical forecasts.
The geographical distribution of prediction skill across North America is studied. Canada turns out to be the country where skill is most significant. During winter, high skill values are also found over the southeastern United States.
Abstract
The statistical model proposed by Vautard et al. is applied to the seasonal prediction of surface air temperatures over North America (Canada and the United States). This model is based on sea surface temperature predictors filtered by multichannel singular spectrum analysis (MSSA), which is equivalent here to a nonseasonal version of extended EOF analysis. Several versions of the MSSA model are proposed. The most successful one is based on a two-step procedure consisting in a prior prediction of filtered sea surface temperatures followed by a predictand specification stage.
The MSSA model is compared with the recent prediction technique based on canonical correlation analysis (CCA). The former model turns out, in this application, to be more skillful in most seasons than the latter. The differences are, however, marginal. The authors argue that these differences are due to the nonseasonal nature of the MSSA model and to overfitting problems inherent to CCA. Another advantage of the MSSA model relative to CCA is the possibility of easily transforming deterministic continuous forecasts into probabilistic categorical forecasts.
The geographical distribution of prediction skill across North America is studied. Canada turns out to be the country where skill is most significant. During winter, high skill values are also found over the southeastern United States.
