Search Results

You are looking at 1 - 10 of 15 items for

  • Author or Editor: Yehui Chang x
  • All content x
Clear All Modify Search
Siegfried Schubert and Yehui Chang

Abstract

A restricted statistical correction (RSC) approach is introduced to assess the sources of error in general circulation models (GCMs). RSC models short-term forecast error by considering linear transformations of the GCM's forcing terms, which produce a “best” model in a restricted least squares sense. The results of RSC provide 1) a partitioning of the systematic error among the various GCM's forcing terms, and 2) a consistent partitioning of the nonsystematic error among the GCM forcing terms, which maximize the explained variance. In practice, RSC requires a substantial reduction in the dimensionality of the resulting regression problem: the approach described here projects the fields on the eigenvectors of the error covariance matrix.

An example of RSC is presented for the Goddard Earth Observing System (GEOS) GCM's vertically integrated moisture equation over the continental United States during spring. The results are based on the history of analysis increments (“errors”) from a multiyear data assimilation experiment employing the GEOS model. The RSC analysis suggests that during early spring the short-term systematic forecast errors in the vertically integrated moisture are dominated by errors in the evaporation field, while during late spring the errors are large in both the precipitation and evaporation fields. The RSC results further suggest that one-quarter to one-half of the nonsystematic forecast errors in the vertically integrated moisture may be attributable to GCM deficiencies.

Limitations of the method resulting from ambiguities in the nature of the analysis increments are discussed. While the RSC approach was specifically developed to take advantage of data assimilation experiments, it should also be useful for analysing sequences of somewhat longer GCM forecasts (∼1 day) as long as they are short enough to consider the errors approximately local.

Full access
Yehui Chang, Siegfried Schubert, and Max Suarez

Abstract

This study examines the cause of the extreme snowstorm activity along the U.S. East Coast during the winter of 2009/10 with a focus on the role of sea surface temperature (SST) anomalies. The study employs the Goddard Earth Observing System, version 5 (GEOS-5) atmospheric general circulation model (AGCM) run at high resolution and forced with specified observed or idealized SST. Comparisons are made with the winter of 1999/2000, a period that is characterized by SST anomalies that are largely of opposite sign.

When forced with observed SSTs, the AGCM response consists of a band of enhanced storminess extending from the central subtropical North Pacific, across the southern United States, across the North Atlantic, and across southern Eurasia, with reduced storminess to the north of these regions. Positive precipitation and cold temperature anomalies occur over the eastern United States, reflecting a propensity for enhanced snowstorm activity. Additional idealized SST experiments show that the anomalies over the United States are, to a large extent, driven by the ENSO-related Pacific SST. The North Atlantic SSTs contribute to the cooler temperatures along the East Coast of the United States, while the Indian Ocean SSTs act primarily to warm the central part of the country.

It is further shown that the observed upper-tropospheric height anomalies have a large noise (unforced) component over the Northern Hemisphere, represented over the North Atlantic by a North Atlantic Oscillation (NAO)-like structure. The signal-to-noise ratios of the temperature and precipitation fields nevertheless indicate a potential for predicting the unusual storm activity along the U.S. East Coast several months in advance.

Full access
Yoo-Geun Ham, Siegfried Schubert, and Yehui Chang

Abstract

An initialization strategy, tailored to the prediction of the Madden–Julian oscillation (MJO), is evaluated using the Goddard Earth Observing System Model, version 5 (GEOS-5), coupled general circulation model (CGCM). The approach is based on the empirical singular vectors (ESVs) of a reduced-space statistically determined linear approximation of the full nonlinear CGCM. The initial ESV, extracted using 10 years (1990–99) of boreal winter hindcast data, has zonal wind anomalies over the western Indian Ocean, while the final ESV (at a forecast lead time of 10 days) reflects a propagation of the zonal wind anomalies to the east over the Maritime Continent—an evolution that is characteristic of the MJO.

A new set of ensemble hindcasts are produced for the boreal winter season from 1990 to 1999 in which the leading ESV provides the initial perturbations. The results are compared with those from a set of control hindcasts generated using random perturbations. It is shown that the ESV-based predictions have a systematically higher bivariate correlation skill in predicting the MJO compared to those using the random perturbations. Furthermore, the improvement in the skill depends on the phase of the MJO. The ESV is particularly effective in increasing the forecast skill during those phases of the MJO in which the control has low skill (with correlations increasing by as much as 0.2 at 20–25-day lead times), as well as during those times in which the MJO is weak.

Full access
Siegfried Schubert, Yehui Chang, Hailan Wang, Randal Koster, and Max Suarez

Abstract

This study examines the causes and predictability of the spring 2011 U.S. extreme weather using the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and Goddard Earth Observing System Model, version 5, (GEOS-5) atmospheric general circulation model simulations. The focus is on assessing the impact on precipitation of sea surface temperature (SST) anomalies, land conditions, and large-scale atmospheric modes of variability. A key result is that the April record-breaking precipitation in the Ohio River valley was primarily the result of the unforced development of a positive North Atlantic Oscillation (NAO)-like mode of variability with unusually large amplitude, limiting the predictability of the precipitation in that region at 1-month leads. SST forcing (La Niña conditions) contributed to the broader continental-scale pattern of precipitation anomalies, producing drying in the southern plains and weak wet anomalies in the northeast, while the impact of realistic initial North American land conditions was to enhance precipitation in the upper Midwest and produce deficits in the Southeast. It was further found that 1) the 1 March atmospheric initial condition was the primary source of the ensemble mean precipitation response over the eastern United States in April (well beyond the limit of weather predictability), suggesting an influence on the initial state of the previous SST forcing and/or tropospheric–stratospheric coupling linked to an unusually persistent and cold polar vortex; and 2) stationary wave model experiments suggest that the SST-forced base state for April enhanced the amplitude of the NAO response compared to that of the climatological state, though the impact is modest and can be of either sign.

Full access
Hailan Wang, Siegfried D. Schubert, Randal D. Koster, and Yehui Chang
Open access
Young-Kwon Lim, Siegfried D. Schubert, Yehui Chang, and Hailan Wang

Abstract

This study examines the within-season monthly variation of the El Niño response over North America during December–March using the NASA/GEOS model. In agreement with previous studies, the skill of 1-month-lead GEOS coupled model forecasts of precipitation over North America is largest (smallest) for February (January), with similar results in uncoupled mode. A key finding is that the relatively poor January skill is the result of the model placing the main circulation anomaly over the northeast Pacific slightly to the west of the observed, resulting in precipitation anomalies that lie off the coast instead of over land as observed. In contrast, during February the observed circulation anomaly over the northeast Pacific shifts westward, lining up with the predicted anomaly, which is essentially unchanged from January, resulting in both the observed and predicted precipitation anomalies remaining off the coast. Furthermore, the largest precipitation anomalies occur along the southern tier of states associated with an eastward extended jet—something that the models capture reasonably well. Simulations with a stationary wave model indicate that the placement of January El Niño response to the west of the observed over the northeast Pacific is the result of biases in the January climatological stationary waves, rather than errors in the tropical Pacific El Niño heating anomalies in January. Furthermore, evidence is provided that the relatively poor simulation of the observed January climatology, characterized by a strengthened North Pacific jet and enhanced ridge over western North America, can be traced back to biases in the January climatology heating over the Tibet region and the tropical western Pacific.

Restricted access
Randal D. Koster, Yehui Chang, Hailan Wang, and Siegfried D. Schubert

Abstract

A series of stationary wave model (SWM) experiments are performed in which the boreal summer atmosphere is forced, over a number of locations in the continental United States, with an idealized diabatic heating anomaly that mimics the atmospheric heating associated with a dry land surface. For localized heating within a large portion of the continental interior, regardless of the specific location of this heating, the spatial pattern of the forced atmospheric circulation anomaly (in terms of 250-hPa eddy streamfunction) is largely the same: a high anomaly forms over west-central North America and a low anomaly forms to the east. In supplemental atmospheric general circulation model (AGCM) experiments, similar results are found; imposing soil moisture dryness in the AGCM in different locations within the U.S. interior tends to produce the aforementioned pattern, along with an associated near-surface warming and precipitation deficit in the center of the continent. The SWM-based and AGCM-based patterns generally agree with composites generated using reanalysis and precipitation gauge data. The AGCM experiments also suggest that dry anomalies imposed in the lower Mississippi River valley have remote surface impacts of particularly large spatial extent, and a region along the eastern half of the U.S.–Canadian border is particularly sensitive to dry anomalies in a number of remote areas. Overall, the SWM and AGCM experiments support the idea of a positive feedback loop operating over the continent: dry surface conditions in many interior locations lead to changes in atmospheric circulation that act to enhance further the overall dryness of the continental interior.

Full access
Siegfried D. Schubert, Max J. Suarez, Yehui Chang, and Grant Branstator

Abstract

This study examines the variability in forecasts of the January–February–March (JFM) mean extratropical circulation and how that variability is modulated by the El Niño–Southern Oscillation. The analysis is based on ensembles of seasonal simulations made with an atmospheric general circulation model (AGCM) forced with sea surface temperatures observed during the 1983 El Niño and 1989 La Niña events. The AGCM produces pronounced interannual differences in the magnitude of the extratropical seasonal mean noise (intraensemble JFM variability). The North Pacific, in particular, shows extensive regions in which the 1989 seasonal mean noise kinetic energy (SKE), which is dominated by a “Pacific–North American (PNA)–like” spatial structure, is more than 2 times that of the 1983 forecasts. The larger SKE in 1989 is associated with a larger-than-normal barotropic conversion of kinetic energy from the mean Pacific jet to the seasonal mean noise. The generation of SKE by submonthly transients also shows substantial interannual differences, though these are much smaller than the differences in the mean flow conversions. An analysis of the generation of monthly mean noise kinetic energy and its variability suggests that the seasonal mean noise is predominantly a statistical residue of variability resulting from dynamical processes operating on monthly and shorter timescales.

A stochastically forced barotropic model (linearized about the AGCM's 1983 and 1989 seasonal and ensemble mean states) is used to further assess the role of the basic state, submonthly transients, and tropical forcing in modulating the uncertainties in the seasonal AGCM forecasts. When forced globally with spatially white noise, the linear model generates much larger variance for the 1989 basic state, consistent with the AGCM results. The extratropical variability for the 1989 basic state is dominated by a single eigenmode and is strongly coupled with forcing over the tropical western Pacific and the Indian Ocean. Linear calculations that include forcing from the AGCM variance of the tropical forcing and submonthly transients show a small impact on the variability over the PNA region as compared with that of the basic-state differences.

Full access
Randal D. Koster, Yehui Chang, and Siegfried D. Schubert

Abstract

While the ability of land surface conditions to influence the atmosphere has been demonstrated in various modeling and observational studies, the precise mechanisms by which land–atmosphere feedback occurs are still largely unknown: particularly the mechanisms that allow land moisture state in one region to affect atmospheric conditions in another. Such remote impacts are examined here in the context of atmospheric general circulation model (AGCM) simulations, leading to the identification of one potential mechanism: the phase locking and amplification of a planetary wave through the imposition of a spatial pattern of soil moisture at the land surface. This mechanism, shown here to be relevant in the AGCM, apparently also operates in nature, as suggested by supporting evidence found in reanalysis data.

Full access
Hailan Wang, Siegfried D. Schubert, Randal D. Koster, and Yehui Chang

Abstract

Past modeling simulations, supported by observational composites, indicate that during boreal summer, dry soil moisture anomalies in very different locations within the U.S. continental interior tend to induce the same upper-tropospheric circulation pattern: a high anomaly forms over west-central North America and a low anomaly forms to the east. The present study investigates the causes of this apparent phase locking of the upper-level circulation response and extends the investigation to other land regions in the Northern Hemisphere. The phase locking over North America is found to be induced by zonal asymmetries in the local basic state originating from North American orography. Specifically, orography-induced zonal variations of air temperature, those in the lower troposphere in particular, and surface pressure play a dominant role in placing the soil moisture–forced negative Rossby wave source (dominated by upper-level divergence anomalies) over the eastern leeside of the Western Cordillera, which subsequently produces an upper-level high anomaly over west-central North America, with the downstream anomalous circulation responses phase locked by continuity. The zonal variations of the local climatological atmospheric circulation, manifested as a climatological high over central North America, help shape the spatial pattern of the upper-level circulation responses. Considering the rest of the Northern Hemisphere, the northern Middle East exhibits similar phase locking, also induced by local orography. The Middle Eastern phase locking, however, is not as pronounced as that over North America; North America is where soil moisture anomalies have the greatest impact on the upper-tropospheric circulation.

Full access