skip to main content


Title: Characteristics, Evolution, and Formation of Cold Air Outbreaks in the Great Plains of the United States
Abstract

Wintertime cold air outbreaks (CAOs) in the Great Plains of the United States have significant socioeconomic, environmental, and infrastructural impacts; the events of December 1983 and February 2021 are key examples of this. Previous studies have investigated CAOs in other parts of North America, particularly the eastern United States, but the development of CAOs in the Great Plains and their potential subseasonal-to-seasonal (S2S) predictability have yet to be assessed. This study first identifies 37 large-scale CAOs in the Great Plains between 1950 and 2021, before examining their characteristics, evolution, and driving mechanisms. These events occur under two dominant weather regimes at event onset: one set associated with anomalous ridging over Alaska and the other set associated with anomalous pan-Arctic ridging. Alaskan ridge CAOs evolve quickly (i.e., on synoptic time scales) and involve stratospheric wave reflection. Conversely, Arctic high CAOs are preceded by weak stratospheric polar vortex conditions several weeks prior to the event. Both categories of CAOs feature anomalous upward wave activity flux from Siberia, with downward wave activity flux over Canada seen only in the Alaskan ridge CAOs. The rapid development of the Alaskan ridge CAOs, also linked with a North Pacific wave train and anomalous wave activity flux from the central Pacific, suggests that these events could be forced by tropical modes of variability. These findings present evidence that different forcing mechanisms, with contrasting time scales, may produce distinct sources of predictability for these CAOs on the S2S time scale.

 
more » « less
Award ID(s):
1946093
NSF-PAR ID:
10368411
Author(s) / Creator(s):
 ;  ;  
Publisher / Repository:
American Meteorological Society
Date Published:
Journal Name:
Journal of Climate
Volume:
35
Issue:
14
ISSN:
0894-8755
Page Range / eLocation ID:
p. 4585-4602
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    The February 2021 cold air outbreak (CAO) was a high‐impact event in the South‐Central Plains of the United States. This study examines important precursors to the event that likely impacted its predictability in subseasonal forecasts. We use reanalysis to show that the CAO was facilitated by two distinct wave breaks—an East Siberian Sea anticyclonic wave break and a Labrador Sea cyclonic wave break. We also use European Center for Medium‐Range Weather Forecasts and National Center for Environmental Prediction subseasonal‐to‐seasonal models to investigate the impact of the wave breaks on the forecast skill of the event at a ∼2–3 weeks lead time. Ensemble members successfully simulating these features produce more negative temperature anomalies across the Great Plains, corresponding to better positioning of anomalous ridging. These results demonstrate that successfully simulating persistent anticyclones can improve central US extreme cold forecasts at long leads.

     
    more » « less
  2. Abstract

    The stratosphere can have a significant impact on winter surface weather on subseasonal to seasonal (S2S) timescales. This study evaluates the ability of current operational S2S prediction systems to capture two important links between the stratosphere and troposphere: (1) changes in probabilistic prediction skill in the extratropical stratosphere by precursors in the tropics and the extratropical troposphere and (2) changes in surface predictability in the extratropics after stratospheric weak and strong vortex events. Probabilistic skill exists for stratospheric events when including extratropical tropospheric precursors over the North Pacific and Eurasia, though only a limited set of models captures the Eurasian precursors. Tropical teleconnections such as the Madden‐Julian Oscillation, the Quasi‐Biennial Oscillation, and El Niño–Southern Oscillation increase the probabilistic skill of the polar vortex strength, though these are only captured by a limited set of models. At the surface, predictability is increased over the United States, Russia, and the Middle East for weak vortex events, but not for Europe, and the change in predictability is smaller for strong vortex events for all prediction systems. Prediction systems with poorly resolved stratospheric processes represent this skill to a lesser degree. Altogether, the analyses indicate that correctly simulating stratospheric variability and stratosphere‐troposphere dynamical coupling are critical elements for skillful S2S wintertime predictions.

     
    more » « less
  3. Abstract

    The Mississippi River basin drains nearly one-half of the contiguous United States, and its rivers serve as economic corridors that facilitate trade and transportation. Flooding remains a perennial hazard on the major tributaries of the Mississippi River basin, and reducing the economic and humanitarian consequences of these events depends on improving their seasonal predictability. Here, we use climate reanalysis and river gauge data to document the evolution of floods on the Missouri and Ohio Rivers—the two largest tributaries of the Mississippi River—and how they are influenced by major modes of climate variability centered in the Pacific and Atlantic Oceans. We show that the largest floods on these tributaries are preceded by the advection and convergence of moisture from the Gulf of Mexico following distinct atmospheric mechanisms, where Missouri River floods are associated with heavy spring and summer precipitation events delivered by the Great Plains low-level jet, whereas Ohio River floods are associated with frontal precipitation events in winter when the North Atlantic subtropical high is anomalously strong. Further, we demonstrate that the El Niño–Southern Oscillation can serve as a precursor for floods on these rivers by mediating antecedent soil moisture, with Missouri River floods often preceded by a warm eastern tropical Pacific (El Niño) and Ohio River floods often preceded by a cool eastern tropical Pacific (La Niña) in the months leading up peak discharge. We also use recent floods in 2019 and 2021 to demonstrate how linking flood hazard to sea surface temperature anomalies holds potential to improve seasonal predictability of hydrologic extremes on these rivers.

     
    more » « less
  4. Abstract

    Boreal summer intraseasonal oscillation (BSISO) is a primary source of predictability for summertime weather and climate on the subseasonal-to-seasonal (S2S) time scale. Using the GFDL SPEAR S2S prediction system, we evaluate the BSISO prediction skills based on 20-yr (2000–19) hindcast experiments with initializations from May to October. It is revealed that the overall BSISO prediction skill using all hindcasts reaches out to 22 days as measured by BSISO indices before the bivariate anomalous correlation coefficient (ACC) drops below 0.5. Results also show that the northeastward-propagating canonical BSISO (CB) event has a higher prediction skill than the northward dipole BSISO (DB) event (28 vs 23 days). This is attributed to CB’s more periodic nature, resulting in its longer persistence, while DB events are more episodic accompanied by a rapid demise after reaching maximum enhanced convection over the equatorial Indian Ocean. From a forecaster’s perspective, a precursory strong Kelvin wave component in the equatorial western Pacific signifies the subsequent development of a CB event, which is likely more predictable. Investigation of individual CB events shows a large interevent spread in terms of their prediction skills. For CB, the events with weaker and fluctuating amplitude during their lifetime have relatively lower prediction skills likely linked to their weaker convection–circulation coupling. Interestingly, the prediction skills of individual CB events tend to be relatively higher and less scattered during late summer (August–October) than those in early summer (May–July), suggestive of the seasonal modulation on the evolution and predictability of BSISO.

    Significance Statement

    The advance of subseasonal-to-seasonal (S2S) prediction largely depends on dynamical models’ ability to predict some major intrinsic modes in the climate system, including the boreal summer intraseasonal oscillation (BSISO). Using a newly developed S2S prediction system, we thoroughly evaluated its performance in predicting BSISO, and revealed the skill dependence on the BSISO propagation diversity. Here we provide physical explanations of what influences the BSISO predictions and identify different precursory signals for two types of BSISO, which have important implications for operational forecasts.

     
    more » « less
  5. Abstract

    Extreme stratospheric wave activity has been suggested to be connected to surface temperature anomalies, but some key processes are not well understood. Using observations, we show that the stratospheric events featuring weaker‐than‐normal wave activity are associated with increased North American (NA) cold extreme risks before and near the event onset, accompanied by less frequent atmospheric river (AR) events on the west coast of the United States. Strong stratospheric wave events, on the other hand, exhibit a tropospheric weather regime transition. They are preceded by NA warm anomalies and increased AR frequency over the west coast, followed by increased risks of NA cold extremes and north‐shifted ARs over the Atlantic. Moreover, these links between the stratosphere and troposphere are attributed to the vertical structure of wave coupling. Weak wave events show a wave structure of westward tilt with increasing altitudes, while strong wave events feature a shift from westward tilt to eastward tilt during their life cycle. This wave phase shift indicates vertical wave coupling and likely regional planetary wave reflection. Further examinations of CMIP6 models show that models with a degraded representation of stratospheric wave structure exhibit biases in the troposphere during strong wave events. Specifically, models with a stratospheric ridge weaker than the reanalysis exhibit a weaker tropospheric signal. Our findings suggest that the vertical coupling of extreme stratospheric wave activity should be evaluated in the model representation of stratosphere‐troposphere coupling.

     
    more » « less