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Gilbert P. Compo
,
Jeffrey S. Whitaker
, and
Prashant D. Sardeshmukh

Climate variability and global change studies are increasingly focused on understanding and predicting regional changes of daily weather statistics. Assessing the evidence for such variations over the last 100 yr requires a daily tropospheric circulation dataset. The only dataset available for the early twentieth century consists of error-ridden hand-drawn analyses of the mean sea level pressure field over the Northern Hemisphere. Modern data assimilation systems have the potential to improve upon these maps, but prior to 1948, few digitized upper-air sounding observations are available for such a “reanalysis.” We investigate the possibility that the additional number of newly recovered surface pressure observations is sufficient to generate useful weather maps of the lower-tropospheric extratropical circulation back to 1890 over the Northern Hemisphere, and back to 1930 over the Southern Hemisphere. Surprisingly, we find that by using an advanced data assimilation system based on an ensemble Kalman filter, it would be feasible to produce high-quality maps of even the upper troposphere using only surface pressure observations. For the beginning of the twentieth century, the errors of such upper-air circulation maps over the Northern Hemisphere in winter would be comparable to the 2-3-day errors of modern weather forecasts.

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Matthew Newman
,
Prashant D. Sardeshmukh
, and
John W. Bergman

Three very different views of the mean structure and variability of deep convection over the tropical east Indian and west Pacific Oceans, provided by three different reanalysis datasets for 1980–93, are highlighted. The datasets were generated at the National Centers for Environmental Prediction, the National Aeronautics and Space Administration's Goddard Laboratory for Atmospheres, and the European Centre for Medium-Range Weather Forecasts (ECMWF). Precipitation, outgoing longwave radiation (OLR), and 200-mb wind divergence fields from the three datasets are compared with one another and with satellite observations. Climatological means as well as interannual and intraseasonal (30–70 day) variability are discussed. For brevity the focus is restricted to northern winter (DJF).

The internal consistency of the datasets is high, in the sense that the geographical extremes of rainfall, OLR, and divergence in each dataset correspond closely to one another. On the other hand, the external consistency, that is, the agreement between the datasets, is so low as to defy a simple summary. Indeed, the differences are such as to raise fundamental questions concerning 1) whether there is a single or a split ITCZ over the west Pacific Ocean with a strong northern branch, 2) whether there is more convection to the west or the east of Sumatra over the equatorial Indian Ocean, and 3) whether there is a relative minimum of convection near New Guinea. Geographical maps of interannual and intraseasonal variances also show similar order 1 uncertainties, as do regressions against the principal component time series of the Madden–Julian oscillation. The annual cycle of convection is also different in each reanalysis. Overall, the ECMWF reanalysis compares best with observations in this region, but it too has important errors.

Finally, it is noted that although 200-mb divergence fields in the three datasets are highly inconsistent with one another, the 200-mb vorticity fields are highly consistent. This reaffirms the relevance of diagnosing divergence from knowledge of the vorticity using the method described in Sardeshmukh (1993). This would yield divergence fields from the three datasets that are not only more consistent with each other, but also more consistent with the 200-mb vorticity balance. Further, as proxies of deep convection, they would help resolve many of the issues raised above.

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Christopher R. Winkler
,
Matthew Newman
, and
Prashant D. Sardeshmukh

Abstract

A linear inverse model (LIM) suitable for studies of atmospheric extratropical variability on longer than weekly timescales is constructed using observations of the past 30 years. Notably, it includes tropical diabatic heating as an evolving model variable rather than as a forcing, and also includes, in effect, the feedback of the extratropical weather systems on the more slowly varying circulation. Both of these features are shown to be important contributors to the model's realism.

Forecast skill is an important test of any model's usefulness as a diagnostic tool. The LIM is better at forecasting week 2 anomalies than a dynamical model based on the linearized baroclinic equations of motion (with many more than the LIM's 37 degrees of freedom) that is forced with observed (as opposed to the LIM's predicted) tropical heating throughout the forecast. Indeed, at week 2 the LIM's skill is competitive with that of the global nonlinear medium-range forecast (MRF) model with nominally O(106) degrees of freedom in use at the National Centers for Environmental Prediction (NCEP). Importantly, this encouraging model performance is not limited to years of El Niño or La Niña episodes. This suggests that accurate prediction of tropical diabatic heating, rather than of tropical sea surface temperatures per se, is key to enhancing extratropical predictability.

The LIM assumes that the dynamics of extratropical low-frequency variability are linear, stable, and stochastically forced. The approximate validity of these assumptions is demonstrated through several tests. A potentially limiting aspect of such a stable linear model with decaying eigenmodes concerns its ability to predict anomaly growth. It is nevertheless found, through a singular vector analysis of the model's propagator, that predictable anomaly growth can and does occur in this dynamical system through constructive modal interference. Examination of the dominant growing singular vectors further confirms the importance of tropical heating anomalies associated with El Niño/La Niña as well as Madden–Julian oscillation episodes in the predictable dynamics of the extratropical circulation. The relative contribution of initial streamfunction and heating perturbations to the development of amplifying anomalies is similarly examined. This analysis suggests that without inclusion of the effects of tropical heating, extratropical weekly averages may be predictable about two weeks ahead, but with tropical heating included, they may be predictable as far as seven weeks ahead.

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Prashant D. Sardeshmukh
,
Gilbert P. Compo
, and
Cécile Penland

Abstract

Away from the tropical Pacific Ocean, an ENSO event is associated with relatively minor changes of the probability distributions of atmospheric variables. It is nonetheless important to estimate the changes accurately for each ENSO event, because even small changes of means and variances can imply large changes of the likelihood of extreme values. The mean signals are not strictly symmetric with respect to El Niño and La Niña. They also depend upon the unique aspects of the SST anomaly patterns for each event. As for changes of variance and higher moments, little is known at present. This is a concern especially for precipitation, whose distribution is strongly skewed in areas of mean tropospheric descent.

These issues are examined here in observations and GCM simulations of the northern winter (January–March, JFM). For the observational analysis, the 42-yr (1958–99) reanalysis data generated at NCEP are stratified into neutral, El Niño, and La Niña winters. The GCM analysis is based on NCEP atmospheric GCM runs made with prescribed seasonally evolving SSTs for neutral, warm, and cold ENSO conditions. A large number (180) of seasonal integrations, differing only in initial atmospheric states, are made each for observed climatological mean JFM SSTs, the SSTs for an observed warm event (JFM 1987), and the SSTs for an observed cold event (JFM 1989). With such a large ensemble, the changes of probability even in regions not usually associated with strong ENSO signals are ascertained.

The results suggest a substantial asymmetry in the remote response to El Niño and La Niña, not only in the mean but also the variability. In general the remote seasonal mean geopotential height response in the El Niño experiment is stronger, but also more variable, than in the La Niña experiment. One implication of this result is that seasonal extratropical anomalies may not necessarily be more predictable during El Niño than La Niña. The stronger seasonal extratropical variability during El Niño is suggested to arise partly in response to stronger variability of rainfall over the central equatorial Pacific Ocean. The changes of extratropical variability in these experiments are large enough to affect substantially the risks of extreme seasonal anomalies in many regions. These and other results confirm that the remote impacts of individual tropical ENSO events can deviate substantially from historical composite El Niño and La Niña signals. They also highlight the necessity of generating much larger GCM ensembles than has traditionally been done to estimate reliably the changes to the full probability distribution, and especially the altered risks of extreme anomalies, during those events.

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Gilbert P. Compo
,
Prashant D. Sardeshmukh
, and
Cécile Penland

Abstract

This paper is concerned with assessing the impact of the El Niño–Southern Oscillation (ENSO) on atmospheric variability on synoptic, intraseasonal, monthly, and seasonal timescales. Global reanalysis data as well as atmospheric general circulation model (AGCM) simulations are used for this purpose. For the observational analysis, 53 yr of NCEP reanalyses are stratified into El Niño, La Niña, and neutral winters [Jan–Feb–Mar (JFM)]. The AGCM analysis is based on three sets of 180 seasonal integrations made with prescribed global sea surface temperatures corresponding to an observed El Niño event (JFM 1987), an observed La Niña event (JFM 1989), and climatological mean JFM conditions. These ensembles are large enough to estimate the ENSO-induced changes of variability even in regions not usually associated with an ENSO effect. The focus is on the anomalous variability of precipitation and 500-mb heights.

The most important result from this analysis is that the patterns of the anomalous extratropical height variability change sharply from the synoptic to the intraseasonal to monthly timescales, but are similar thereafter. In contrast, the patterns of the anomalous tropical rainfall variability are nearly identical across these timescales. On the synoptic and monthly scales, the anomalous extratropical height variability is generally opposite for El Niño and La Niña, and is also roughly symmetric about the equator. On the intraseasonal scale, however, the anomalous height variability is of the same sign for El Niño and La Niña in the Atlantic sector, and is antisymmetric about the equator in the Pacific sector. In the North Pacific, these intraseasonal variance anomalies (which are consistent with a decrease of blocking activity during El Niño and an increase during La Niña) are of opposite sign to the monthly and seasonal variance anomalies.

The sharp differences across timescales in the ENSO-induced changes of extratropical variability suggest that different dynamical mechanisms dominate on different timescales. They also have implications for the predictability of extreme events on those timescales. Finally, there is evidence here that these impacts on extratropical variability may differ substantially from ENSO event to event, especially in the northern Atlantic and over Europe.

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Sang-Ik Shin
,
Prashant D. Sardeshmukh
,
Robert S. Webb
,
Robert J. Oglesby
, and
Joseph J. Barsugli

Abstract

Paleoclimatic evidence suggests that during the mid-Holocene epoch (about 6000 yr ago) North America and North Africa were significantly drier and wetter, respectively, than at present. Modeling efforts to attribute these differences to changes in orbital parameters and greenhouse gas (GHG) levels have had limited success, especially over North America. In this study, the importance of a possibly cooler tropical Pacific Ocean during the epoch (akin to a permanent La Niña–like perturbation to the present climate) in causing these differences is emphasized. Systematic sets of atmospheric general circulation model experiments, with prescribed sea surface temperatures (SSTs) in the tropical Pacific basin and an interactive mixed layer ocean elsewhere, are performed. Given the inadequacies of current fully coupled climate models in simulating the tropical Pacific climate, this intermediate coupling model configuration is argued to be more suitable for quantifying the contributions of the altered orbital forcing, GHG levels, and tropical Pacific SST conditions to the different mid-Holocene climates. The simulated responses in this configuration are in fact generally more consistent with the available evidence from paleovegetation and sedimentary records.

Coupling to the mixed layer ocean enhances the wind–evaporation–SST feedback over the tropical Atlantic Ocean. The net response to the orbital changes is to shift the North Atlantic intertropical convergence zone (ITCZ) northward, and make North Africa wetter. The response to the reduced GHG levels opposes, but does not eliminate, these changes. The northward-shifted ITCZ also blocks the moisture supply from the Gulf of Mexico into North America. This drying tendency is greatly amplified by the local response to La Niña–like conditions in the tropical Pacific. Consistent with the paleoclimatic evidence, the simulated North American drying is also most pronounced in the growing (spring) season.

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Prashant D. Sardeshmukh
,
Jih-Wang Aaron Wang
,
Gilbert P. Compo
, and
Cécile Penland

Abstract

It is well known that randomly perturbing an atmospheric model’s diabatic tendencies can increase its probabilistic forecast skill, mainly by increasing the spread of ensemble forecasts and making it more consistent with the errors of ensemble-mean forecasts. Less obvious and less well established is that such perturbations can also reduce the errors of the ensemble-mean forecasts and improve the model’s mean climate, variability, and sensitivity to forcing. A clear reduction in ensemble-mean forecast errors is demonstrated here in large ensembles of 15-day forecasts made with NOAA’s Global Forecast System model. The nearly ubiquitous reduction around the globe, obtained throughout the forecast range, is interpreted as arising in effect from a modification of the model’s deterministic evolution operator by a stochastic noise-induced drift. The effect is general in systems with state-dependent noise, and occurs even if the noise is not white. In the atmospheric context considered here, the effect is suggested to arise largely from noise-induced reductions of mechanical and thermal damping by chaotic boundary layer and cloud-radiative processes, which also tend to increase model sensitivity to forcing. The results presented here are consistent with many previous studies performed with models ranging from simple stochastically forced models to comprehensive global weather and climate models. They suggest that the diabatic interactions in most current global atmospheric models may not be sufficiently chaotic and this deficiency could be partly remedied by specifying additional stochastic terms. Using some empirical guidance in such specifications may be unavoidable, given the generally intractable complexity of the diabatic interactions.

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Sang-Ik Shin
,
Prashant D. Sardeshmukh
,
Matthew Newman
,
Cecile Penland
, and
Michael A. Alexander

Abstract

Low-order linear inverse models (LIMs) have been shown to be competitive with comprehensive coupled atmosphere–ocean models at reproducing many aspects of tropical oceanic variability and predictability. This paper presents an extended cyclostationary linear inverse model (CS-LIM) that includes the annual cycles of the background state and stochastic forcing of tropical sea surface temperature (SST) and sea surface height (SSH) anomalies. Compared to a traditional stationary LIM that ignores such annual cycles, the CS-LIM is better at representing the seasonal modulation of ENSO-related SST anomalies and their phase locking to the annual cycle. Its deterministic as well as probabilistic hindcast skill is comparable to the skill of the North American Multimodel Ensemble (NMME) of comprehensive global coupled models. The explicit inclusion of annual-cycle effects in the CS-LIM improves the forecast skill of both SST and SSH anomalies through SST–SSH coupling. The impact on the SSH skill is particularly marked at longer forecast lead times over the western Pacific and in the vicinity of the Pacific North Equatorial Countercurrent (NECC), consistent with westward propagating oceanic Rossby waves that reflect off the western boundaries as eastward propagating Kelvin waves and influence El Niño development in the region. The higher CS-LIM skill is thus associated with the improved representation of both ENSO phase-locking and Pacific NECC variations. These improvements result from explicitly accounting for not only the annual cycle of the background state, but also that of the stochastic forcing.

Open access
Matthew Newman
,
George N. Kiladis
,
Klaus M. Weickmann
,
F. Martin Ralph
, and
Prashant D. Sardeshmukh

Abstract

The relative contributions to mean global atmospheric moisture transport by both the time-mean circulation and by synoptic and low-frequency (periods greater than 10 days) anomalies are evaluated from the vertically integrated atmospheric moisture budget based on 40 yr of “chi corrected” NCEP–NCAR reanalysis data. In the extratropics, while the time-mean circulation primarily moves moisture zonally within ocean basins, low-frequency and synoptic anomalies drive much of the mean moisture transport both from ocean to land and toward the poles. In particular, during the cool-season low-frequency variability is the largest contributor to mean moisture transport into southwestern North America, Europe, and Australia. While some low-frequency transport originates in low latitudes, much is of extratropical origin due to large-scale atmospheric anomalies that extract moisture from the northeast Pacific and Atlantic Oceans. Low-frequency variability is also integral to the Arctic (latitudes > 70°N) mean moisture budget, especially during summer, when it drives mean poleward transport from relatively wet high-latitude continental regions. Synoptic variability drives about half of the mean poleward moisture transport in the midlatitudes of both hemispheres, consistent with simple “lateral mixing” arguments. Extratropical atmospheric transport is also particularly focused within “atmospheric rivers” (ARs), relatively narrow poleward-moving moisture plumes associated with frontal dynamics. AR moisture transport, defined by compositing fluxes over those locations and times where column-integrated water vapor and poleward low-level wind anomalies are both positive, represents most of the total extratropical meridional moisture transport. These results suggest that understanding potential anthropogenic changes in the earth ’s hydrological cycle may require understanding corresponding changes in atmospheric variability, especially on low-frequency time scales.

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Joseph J. Barsugli
,
Jeffrey S. Whitaker
,
Andrew F. Loughe
,
Prashant D. Sardeshmukh
, and
Zoltan Toth

Can an individual weather event be attributed to El Niño? This question is addressed quantitatively using ensembles of medium-range weather forecasts made with and without tropical sea surface temperature anomalies. The National Centers for Environmental Prediction (NCEP) operational medium-range forecast model is used. It is found that anomalous tropical forcing affects forecast skill in midlatitudes as early as the fifth day of the forecast. The effect of the anomalous sea surface temperatures in the medium range is defined as the synoptic El Niño signal. The synoptic El Niño signal over North America is found to vary from case to case and sometimes can depart dramatically from the pattern classically associated with El Niño. This method of parallel ensembles of medium-range forecasts provides information about the changing impacts of El Niño on timescales of a week or two that is not available from conventional seasonal forecasts.

Knowledge of the synoptic El Niño signal can be used to attribute aspects of individual weather events to El Niño. Three large-scale weather events are discussed in detail: the January 1998 ice storm in the northeastern United States and southeastern Canada, the February 1998 rains in central and southern California, and the October 1997 blizzard in Colorado. Substantial impacts of El Nino are demonstrated in the first two cases. The third case is inconclusive.

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