Jacques Derome

A System Simulation Approach to Ensemble Prediction

Abstract For many aspects of numerical weather prediction it is important to have good error statistics. Here one can think of applications as diverse as data assimilation, model improvement, and medium-range forecasting. In this paper, a method for producing these statistics from a representative ensemble of forecast states at the appropriate forecast time is proposed and examined. To generate the ensemble, an attempt is made to simulate the process of error growth in a forecast model. For different ensemble members the uncertain elements of the forecasts are perturbed in different ways. First the authors attempt to obtain representative initial perturbations. For each perturbation, an independent 6-h assimilation cycle is performed. For this the available observations are randomly perturbed. The perturbed observations are input to the statistical interpolation assimilation scheme, giving a perturbed analysis. This analysis is integrated for 6 h with a perturbed version of the T63 forecast model, using p...

An Observed Connection between the North Atlantic Oscillation and the Madden–Julian Oscillation

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 ...

The Differences between Early and Midwinter Atmospheric Responses to Sea Surface Temperature Anomalies in the Northwest Atlantic

Abstract Using an atmospheric global spectral model, it is shown that the winter atmosphere in the midlatitudes is capable of reacting to prescribed sea surface temperature (SST) anomalies in the northwest Atlantic with two very different responses. The nature of the response is determined by the climatological conditions of the winter regime. Experiments are performed using either the perpetual November or January conditions with or without the prescribed SST anomalies. Warm SST anomalies in November result in a highly significant anomalous ridge downstream over the Atlantic with a nearly equivalent barotropic structure; in January, the response is a statistically less significant trough. The presence of the SST anomalies also causes a northward (southward) shift of the Atlantic storm track in the November (January) cases. A diagnostic analysis of the anomalous heat advection in the simulations reveals that in the January cases, the surface heating is offset primarily by the strong horizontal cold advect...

Methods for ensemble prediction

Abstract It is desirable to filter the unpredictable components from a medium-range forecast. Such a filtered forecast can be obtained by averaging an ensemble of predictions that started from slightly different initial atmospheric states. Different strategies have been proposed to generate the initial perturbations for such an ensemble. “Optimal” perturbation give the largest error at a prespecified forecast time. “Bred” perturbations have grown during a period prior to the analysis. “OSSE-MC” perturbations are obtained using a Monte Carlo-like observation system simulation experiment (OSSE). In the current pilot study, the properties of the different strategies are compared. A three-level quasigeostrophic model is used to describe the evolution of the errors. The tangent linear version of this model and its adjoint version are used to generate the optimal perturbations, while bred perturbations are generated using the full nonlinear model. In the OSSE-MC method, random perturbations of model states are ...

Forecast Skill of the Madden-Julian Oscillation in Two Canadian Atmospheric Models

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 Prevision Numerique (RPN). Space–time spectral analysis of the daily precipitation in nearequilibrium 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.

Seasonal predictions based on two dynamical models

Abstract Two dynamical models are used to perform a series of seasonal predictions. One model, referred to as GCM2, was designed as a general circulation model for climate studies, while the second one, SEF, was designed for numerical weather prediction. The seasonal predictions cover the 26‐year period 1969–1994. For each of the four seasons, ensembles of six forecasts are produced with each model, the six runs starting from initial conditions six hours apart. The sea surface temperature (SST) anomaly for the month prior to the start of the forecast is persisted through the three‐month prediction period, and added to a monthly‐varying climatological SST field. The ensemble‐mean predictions for each of the models are verified independently, and the two ensembles are blended together in two different ways: as a simple average of the two models, denoted GCMSEF, and with weights statistically determined to minimize the mean‐square error (the Best Linear Unbiased Estimate (BLUE) method). The GCMSEF winter and spring predictions show a Pacific/North American (PNA) response to a warm tropical SST anomaly. The temporal anomaly correlation between the zero‐lead GCMSEF mean‐seasonal predictions and observations of the 500‐hPa height field (Z500) shows statistically significant forecast skill over parts of the PNA area for all seasons, but there is a notable seasonal variability in the distribution of the skill. The GCMSEF predictions are more skilful than those of either model in winter, and about as skilful as the better of the two models in the other seasons. The zero‐lead surface air temperature GCMSEF forecasts over Canada are found to be skilful (a) over the west coast in all seasons except fall, (b) over most of Canada in summer, and (c) over Manitoba, Ontario and Quebec in the fall. In winter the skill of the BLUE forecasts is substantially better than that of the GCMSEF predictions, while for the other seasons the difference in skill is not statistically significant. When the Z500 forecasts are averaged over months two and three of the seasons (one‐month lead predictions), they show skill in winter over the north‐eastern Pacific, western Canada and eastern North America, a skill that comes from those years with strong SST anomalies of the El Niño/La Niña type. For the other seasons, predictions averaged over months two and three show little skill in Z500 in the mid‐latitudes. In the tropics, predictive skill is found in Z500 in all seasons when a strong SST anomaly of the El Niño/La Niña type is observed. In the absence of SST anomalies of this type, tropical forecast skill is still found over much of the tropics in months two and three of the northern hemisphere spring and summer, but not in winter and fall.

Linking Arctic sea‐ice and atmospheric circulation anomalies on interannual and decadal timescales

Abstract The relationship between Arctic sea‐ice concentration anomalies, particularly those associated with the “Great Salinity Anomaly” of 1968–1982, and atmospheric circulation anomalies north of 45°N is investigated. Empirical orthogonal function (EOF) analyses are performed on winter Arctic ice concentration from 1954 to 1990, sea level pressure and 500‐hPa heights from 1947 to 1994, and 850‐hPa temperatures from 1963 to 1994. Variability on both interannual and decadal timescales is apparent in the time series of the leading winter EOFs of all variables. The first EOF of winter sea‐ice concentration was found to characterize the patterns of ice variability associated with the Great Salinity Anomaly in the northern North Atlantic from 1968–82. Spatial maps of temporal correlation coefficients between the time series of the first EOF of winter sea‐ice concentration and the winter atmospheric anomaly fields are calculated at lags of 0 and ±7 year. Maximum correlations were found to exist when the time‐...

Intraseasonal Variability in a Dry Atmospheric Model

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 ot...

Nonlinearity of the Extratropical Response to Tropical Forcing

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 Nino/La Nina 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 Nino and La Nina. 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 r...

The Extratropical Signal Generated by a Midlatitude SST Anomaly. Part I: Sensitivity at Equilibrium

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