Predictability of Recurrent Weather Regimes over North America during Winter from Submonthly Reforecasts

Vigaud, Nicolas; Robertson, Andrew W.; Tippett, Michael K.

doi:10.1175/mwr-d-18-0058.1

Cited by 55 publications

(99 citation statements)

References 74 publications

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“…All days are then assigned to a regime based on their minimum Euclidean distance to the cluster centroids; we do not employ “no‐regime” days (Grams et al, ). The resultant regimes are very similar to those found in Vigaud et al (); they show that these regimes are a significant representation based on the classifiability index of Michelangeli et al (), so we do not repeat that calculation here. Our four regimes remain largely unchanged as a subset when five or six clusters are used, further indicating they are dominant patterns and form a concise characterization with reasonably large individual sample sizes.…”

Section: Methodssupporting

confidence: 76%

“…Although some prior work has described regimes across North America in a similar sense to the Atlantic regimes (Amini & Straus, 2019;Riddle et al, 2013;Robertson & Ghil, 1999;Straus et al, 2007;Vigaud et al, 2018), the use of regimes is not as common in this region. The number of regimes and the westward and eastward extent of the region used to define the regimes varies between studies, capturing different aspects of Pacific and Atlantic variability.…”

Section: Introductionmentioning

confidence: 99%

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Wintertime North American Weather Regimes and the Arctic Stratospheric Polar Vortex

Lee

Furtado

Charlton‐Perez

2019

Geophysical Research Letters

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The impact of the Arctic stratospheric polar vortex on persistent weather regimes over North America is so far underexplored. Here we show the relationship between four wintertime North American weather regimes and the stratospheric vortex strength using reanalysis data. We find that the strength of the vortex significantly affects the behavior of the regimes. While a regime associated with Greenland blocking is strongly favored following weak vortex events, it is not the primary regime associated with a widespread, elevated risk of extreme cold in North America. Instead, we find that the regime most strongly associated with widespread extremely cold weather does not show a strong dependency on the strength of the lower stratospheric zonal mean zonal winds. We also suggest that stratospheric vortex morphology may be particularly important for cold air outbreaks during this regime.Plain Language Summary During winter, the strength of the winds 10-50 km above the Arctic can affect the weather patterns at the surface. Generally, this influence is strongest over the North Atlantic and Europe. However, we show that the strength of stratospheric winds has a significant impact on weather patterns across North America. Our results indicate that knowledge of the stratospheric winds can provide a greater understanding of the evolution of likely weather in this region on longer time periods, including both severely cold weather (and its associated impacts on energy consumption, transport, and human health) and an unusual absence of severe cold.

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Section: Methodssupporting

confidence: 76%

Section: Introductionmentioning

confidence: 99%

Wintertime North American Weather Regimes and the Arctic Stratospheric Polar Vortex

Lee

Furtado

Charlton‐Perez

2019

Geophysical Research Letters

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“…Weather regimes can be viewed as "low-frequency envelopes" of synoptic weather variability (Cassou, 2008), with lifetimes ranging from several days to a few weeks. At the same time, regimes are accompanied by typical surface weather conditions and enhance the likelihood of large-scale weather extremes (e.g., Yiou and Nogaj, 2004;Della-Marta et al, 2007;Stefanon et al, 2012;Ferranti et al, 2018;Schaller et al, 2018;Vigaud et al, 2018). Weather regimes are commonly identified using clustering techniques applied to geopotential height.…”

Section: Weather Regimesmentioning

confidence: 99%

Stratospheric modulation of the large‐scale circulation in the Atlantic–European region and its implications for surface weather events

Beerli

Grams

2019

Quart J Royal Meteoro Soc

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Extreme states of the stratospheric polar vortex can have long‐lasting impacts on extratropical circulation patterns, such as the North Atlantic Oscillation (NAO). This provides windows of subseasonal predictability beyond the typical weather forecast horizon of about 10 days. Subseasonal forecasts of surface weather are of significant interest in weather‐dependent socio‐economic sectors. For example, demand and supply for electricity and gas are weather dependent and therefore accurate forecasts are important for the energy industry and energy trading. Here we investigate the subseasonal impact of stratospheric conditions on surface weather events relevant to the energy industry in five subregions of Europe in winter. We use a definition of seven Atlantic–European weather regimes to describe the variability of the large‐scale circulation on subseasonal time scales. Results indicate that weather events are often associated with more than one preferred weather regime. In turn, some weather regimes project onto a specific NAO phase, while others are independent of the NAO. As expected, anomalous stratospheric polar vortex states predominantly modulate the occurrence of regimes related to the NAO and affect the likelihood of their associated weather events. In contrast, the occurrence of weather regimes which do not project well onto the NAO is not affected by anomalous stratospheric polar vortex states. These regimes provide pathways to unexpected weather events in extreme stratospheric polar vortex states. For example, weak stratospheric polar vortex states enhance the likelihood of negative NAO. High wind events in Central Europe predominantly occur during the zonal regime, strongly projecting onto positive NAO. However, these events also occur during the Atlantic trough regime, which is unaffected by anomalous stratospheric polar vortex states and thus provides a pathway to Central European high wind events during weak stratospheric polar vortex states. A correct NAO prediction alone is therefore not sufficient to correctly predict surface weather after extreme stratospheric polar vortex states. Moreover, weather regime life cycles independent of the NAO also need to be forecast accurately.

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“…Model output statistics (MOS) has been shown to improve probabilistic weather forecasts (Hamill et al 2004), but fewer analyses have been yet done at subseasonal time scales. Submonthly forecasts based on extended logistic regression (ELR; Wilks 2009) have recently provided probabilistic precipitation forecast skill estimates on S2S time scales over different parts of the globe including North America (Vigaud et al 2017a(Vigaud et al ,b, 2018, but such approaches have yet to be applied to surface temperatures. In the ELR methodology proposed in Vigaud et al (2017a), calibration is done at the gridpoint level (i.e., a separate regression model is constructed for every location without using information from neighboring grid points).…”

Section: Introductionmentioning

confidence: 99%

“…Submonthly forecasts based on extended logistic regression (ELR; Wilks 2009) have recently provided probabilistic precipitation forecast skill estimates on S2S time scales over different parts of the globe including North America (Vigaud et al 2017a(Vigaud et al ,b, 2018, but such approaches have yet to be applied to surface temperatures. In the ELR methodology proposed in Vigaud et al (2017a), calibration is done at the gridpoint level (i.e., a separate regression model is constructed for every location without using information from neighboring grid points). Since gridpoint regressions are prone to sampling uncertainties that can translate into spatially noisy forecasts, there might be potential for improvements by including spatial information.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Skill of Subseasonal Surface Temperature Forecasts over North America

Vigaud¹,

Tippett

Yuan³

et al. 2019

Weather and Forecasting

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The skill of surface temperature forecasts up to 4 weeks ahead is examined for weekly tercile category probabilities constructed using extended logistic regression (ELR) applied to three ensemble prediction systems (EPSs) from the Subseasonal-to-Seasonal (S2S) project (ECMWF, NCEP, and CMA), which are verified over the common period 1999-2010 and averaged with equal weighting to form a multimodel ensemble (MME). Over North America, the resulting forecasts are characterized by good reliability and varying degrees of sharpness. Skill decreases after two weeks and from winter to summer. Multimodel ensembling damps negative skill that is present in individual forecast systems, but overall, does not lead to substantial skill improvement compared to the best (ECMWF) model. Spatial pattern correction is implemented by projecting the ensemble mean temperatures neighboring each grid point onto Laplacian eigenfunctions, and then using those amplitudes as new predictors in the ELR. Forecasts and skill improve beyond week 2, when the ELR model is trained on spatially averaged temperature (i.e., the amplitude of the first Laplacian eigenfunction) rather than the gridpoint ensemble mean, but not at shorter leads. Forecasts are degraded when adding more Laplacian eigenfunctions that encode additional spatial details as predictors, likely due to the short reforecast sample size. Forecast skill variations with ENSO are limited, but MJO relationships are more pronounced, with the highest skill during MJO phase 3 up to week 3, coinciding with enhanced forecast probabilities of above-normal temperatures in winter.

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Predictability of Recurrent Weather Regimes over North America during Winter from Submonthly Reforecasts

Cited by 55 publications

References 74 publications

Wintertime North American Weather Regimes and the Arctic Stratospheric Polar Vortex

Wintertime North American Weather Regimes and the Arctic Stratospheric Polar Vortex

Stratospheric modulation of the large‐scale circulation in the Atlantic–European region and its implications for surface weather events

Probabilistic Skill of Subseasonal Surface Temperature Forecasts over North America

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