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 25-yr dataset is used to investigate the role of transient eddies in the dynamics of the Pacific–North American (PNA) pattern. Monthly mean vorticity and sensible heat flux divergences associated with submonthly transients are computed over the Northern Hemisphere for each winter month. These fields are composited over months with strong PNA patterns, and the average over all winter months is subtracted to obtain anomaly fields. The vorticity flux divergence anomaly is found to be well correlated with the PNA height field, particularly in the upper troposphere, where an eddy vorticity flux convergence (divergence) is found in the low (high) height regions of the PNA anomaly. The sensible heat flux divergence, on the other hand, is negatively correlated with the PNA temperature anomaly, so that the transient eddies produce a sensible heat flux out of the warm regions of the PNA and into the cold regions, thus tending to destroy the temperature anomaly.

A linear quasi-nondivergent global steady-state model is constructed using the observed climatology. The eddy vorticity and sensible heat flux divergence anomalies are treated as empirical forcing functions to simulate the response of the atmosphere. The model response to the transient-eddy forcing is found to be qualitatively similar to the PNA pattern. The amplitude of the response is weaker than observed over the North Pacific but nearly as observed over North America. The wave-activity flux computed from the model response is in reasonable agreement with that obtained from the observed PNA, except that the model shows a weaker wave activity and a spurious flux southward from the main cell of the PNA in the North Pacific. A possible explanation for this deficiency, as for the underestimation of the response in the North Pacific, is the absence of tropical forcing in the model. The results clearly show the crucial role of the transient eddies in the dynamics of the PNA, particularly over North America.

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

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

This study investigates the North Atlantic Oscillation (NAO) on an intraseasonal time scale. The authors investigate the question of how the characteristics of NAO events are influenced by the choice of its definitions using daily NCEP–NCAR reanalysis data spanning 51 boreal winters. Four different NAO indexes are used in this study, including one station/gridpoint–based index and three pattern-based indexes.

It is found that the NAO events obtained using pattern–based indexes are quite similar to each other, while some notable differences are observed when the NAO is defined using the station/gridpoint–based index (NAO1). The characteristics of the pattern-based NAO are found to be more antisymmetric for its two phases, including its time-averaged spatial structures, its lifetime distributions, and time-evolving spatial structures. The NAO1, on the other hand, reveals some asymmetric characteristics between the two phases. Emphasis is placed on comparing the characteristics of the NAO events obtained using the NAO1 index and one of the pattern-based indices, that is, NAO2. The time-averaged spatial structures for the NAO2 expand across more of the polar region than the NAO1. The positive NAO1 shows a wave train signal over the Pacific–North American region during the setup phase, while the negative NAO1 is found to develop more locally over northern Europe and the North Atlantic. The wave activity flux for the NAO2 is primarily in the zonal direction while for the NAO1, on the other hand, it is mostly concentrated over the North Atlantic with a pronounced southward component. The barotropic vorticity equation is used to examine the physical mechanisms that drive the life cycle of the NAO.

Abstract

A simple GCM (SGCM) is constructed by adding empirically derived time-independent forcing terms to a dry primitive equation model. This yields a model with realistic time-mean jets and storm tracks. The SGCM is then used to study the equilibrium response to an imposed heating anomaly in the midlatitude Pacific, meant to represent an anomaly in the sea surface temperature. Using the SGCM’s own climatology as a basic state, the same model is then used to find the time-independent linear response to the same heating anomaly. The difference between the two responses is clearly attributed to the forcing due to anomalous transient eddies.

The sensitivity of the response to the strength and vertical profile of the heating, and to the presence of the wind speed in the surface flux parameterization, is explored. It is found that for a reasonable range of heating amplitude the transient eddy forcing is proportional to the heating and the responses to heating and cooling are almost antisymmetric. The antisymmetry breaks down at large amplitude. The vertical profile of heating has a small but systematic effect on the response: deeper heating leads to stronger equivalent barotropic features. The inclusion of wind speed in the surface flux parameterization alters the response mainly by virtue of altering the basic model climatology, rather than by any local effect on the heating.

The position of the heating anomaly is varied in both latitude and longitude to gain insight into the possible effects of systematic errors in GCMs. The time-independent linear response tends to move with the heating, but the eddy-driven nonlinear part remains relatively fixed and varies only in amplitude. The heating perturbation slightly modifies the first empirical orthogonal function of the model’s internal low frequency variability. The response projects strongly onto this pattern and the probability distribution function of the projection is significantly skewed.

Abstract

In this study, ensemble seasonal predictions of the Arctic Oscillation (AO) were conducted for 51 winters (1948–98) using a simple global atmospheric general circulation model. A means of estimating a priori the predictive skill of the AO ensemble predictions was developed based on the relative entropy (R) of information theory, which is a measure of the difference between the forecast and climatology probability density functions (PDFs). Several important issues related to the AO predictability, such as the dominant precursors of forecast skill and the degree of confidence that can be placed in an individual forecast, were addressed. It was found that R is a useful measure of the confidence that can be placed on dynamical predictions of the AO. When R is large, the prediction is likely to have a high confidence level whereas when R is small, the prediction skill is more variable. A small R is often accompanied by a relatively weak AO index. The value of R is dominated by the predicted ensemble mean. The relationship identified here, between model skills and the R of an ensemble prediction, offers a practical means of estimating the confidence level of a seasonal forecast of the AO using the dynamical model.

Through an analysis of the global sea surface temperature (SST) forcing, it was found that the winter AO-related R is correlated significantly with the amplitude of the SST anomalies over the tropical central Pacific and the North Pacific during the previous October. A large value of R is usually associated with strong SST anomalies in the two regions, whereas a poor prediction with a small R indicates that SST anomalies are likely weak in these two regions and the observed AO anomaly in the specific winter is likely caused by atmospheric internal dynamics.

Abstract

The prediction skill of the North Atlantic Oscillation (NAO) in boreal winter is assessed in the operational models of the WCRP/WWRP Subseasonal-to-Seasonal (S2S) prediction project. Model performance in representing the contribution of different processes to the NAO forecast skill is evaluated. The S2S models with relatively higher stratospheric vertical resolutions (high-top models) are in general more skillful in predicting the NAO than those models with relatively lower stratospheric resolutions (low-top models). Comparison of skill is made between different groups of forecasts based on initial condition characteristics: phase and amplitude of the NAO, easterly and westerly phases of the quasi-biennial oscillation (QBO), warm and cold phases of ENSO, and phase and amplitude of the Madden–Julian oscillation (MJO). The forecasts with a strong NAO in the initial condition are more skillful than with a weak NAO. Those with negative NAO tend to have more skillful predictions than positive NAO. Comparisons of NAO skill between forecasts during easterly and westerly QBO and between warm and cold ENSO show no consistent difference for the S2S models. Forecasts with strong initial MJO tend to be more skillful in the NAO prediction than weak MJO. Among the eight phases of MJO in the initial condition, phases 3–4 and phase 7 have better NAO forecast skills compared with the other phases. The results of this study have implications for improving our understanding of sources of predictability of the NAO. The situation dependence of the NAO prediction skill is likely useful in identifying “windows of opportunity” for subseasonal to seasonal predictions.

Abstract

A simple GCM based on a primitive equation model with empirically derived time-independent forcing is used to make forecasts in the extended to seasonal range. The results are analyzed in terms of the response to a midlatitude Pacific sea surface temperature anomaly (SSTA), represented here by a heating perturbation. A set of 90-day, 30-member ensemble forecasts is made with 54 widely differing initial conditions, both with and without the SSTA. The development of the response, defined as the difference between ensemble means, is split into three 30-day averages: month 1, month 2, and month 3.

During month 1, ensemble members separate, and the local response and remote teleconnections are established. The local response is not very sensitive to the initial condition.

In month 2, the extended range, the responses are relatively strong and vary greatly from one initial condition to another. However, a linear analysis reveals that large variations in the response do not correlate strongly with large variations in the initial condition. The initial perturbations required to generate the observed variations in the response are relatively small, and may be difficult to isolate in a real forecasting situation.

In month 3, the seasonal range, variations between responses are much smaller. The initial condition loses its influence and the responses all start to resemble the equilibrium response discussed in Part I.