Weather Regimes and Forecast Errors in the Pacific Northwest

McMurdie, Lynn A.; Casola, J.H.

doi:10.1175/2008waf2222172.1

Cited by 13 publications

(10 citation statements)

References 29 publications

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“…Extratropical cyclones that originate over the Pacific Ocean can impact the West Coast of the United States with high winds and heavy precipitation and can result in the loss of life or property. Even with advances in numerical weather prediction (NWP), large errors in shortterm forecasts of strong North Pacific cyclones still occur (McMurdie and Mass 2004;McMurdie and Casola 2009;Rodwell et al 2013). For example, McMurdie and Mass (2004) observed large short-term forecast errors in position and central pressure of midlatitude cyclones along the west coast of North America and offshore.…”

Section: Introductionmentioning

confidence: 99%

Improving Winter Storm Forecasts with Observing System Simulation Experiments (OSSEs). Part I: An Idealized Case Study of Three U.S. Storms

Peevey

English

Cucurull

et al. 2018

Monthly Weather Review

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Severe weather events can have a significant impact on local communities because of the loss of life and property. Forecast busts associated with high-impact weather events have been attributed to initial condition errors over data-sparse regions, such as the Pacific Ocean. Numerous flight campaigns have found that targeted observations over these areas can improve forecasts. To better understand the impacts of measurement type and sampling domains on forecast performance, observing system simulation experiments are performed using the National Centers for Environmental Prediction Global Forecast System (GFS) with hybrid 3DEnVar data assimilation and the ECMWF T511 nature run. First, three types of simulated perfect dropsonde observations (temperature, specific humidity, and wind) are assimilated into the GFS over a large idealized sampling domain covering the Pacific Ocean. For the three winter storms studied, forecast error was found to be significantly reduced with all three types of measurements providing the most benefit (%–15% reduction in error). Instances when forecasts are not improved are investigated and concluded to be due to challenging meteorological structures, such as cutoff lows and interactions with atmospheric structures outside the sampling domain. Second, simulated dropsondes are assimilated over sensitive areas and flight tracks established using the ensemble transform sensitivity (ETS) technique. For all three winter storms, forecast error is reduced up to 5%, which is less than that found using an idealized domain. These results suggest that targeted observations over the Pacific Ocean may provide a small improvement to winter storm forecasts over the United States.

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Section: Introductionmentioning

confidence: 99%

Improving Winter Storm Forecasts with Observing System Simulation Experiments (OSSEs). Part I: An Idealized Case Study of Three U.S. Storms

Peevey

English

Cucurull

et al. 2018

Monthly Weather Review

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“…Analyses based on the 500 hPa geopotential heights performed by McMurdie and Casola [] indicate that weather regimes in the Pacific Northwest affect the forecast errors in the region. They found that the Rocky Mountain ridge regime indicates largest errors of SLP, whereas the coastal ridge indicates largest errors of 2 m temperature.…”

Section: Usefulness and Application Of Nonlinear Circulation Regimesmentioning

confidence: 99%

Low‐frequency nonlinearity and regime behavior in the Northern Hemisphere extratropical atmosphere

Hannachi

Straus

Franzke³

et al. 2017

Reviews of Geophysics

141

140

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The extratropical atmosphere is characterized by robust circulations which have time scales longer than that associated with developing baroclinic systems but shorter than a season. Such low-frequency variability is governed to a large extent by nonlinear dynamics and, hence, is chaotic. A useful aspect of this low-frequency circulation is that it can often be described by just a few quasi-stationary regime states, broadly defined as recurrent or persistent large-scale structures, that exert a significant impact on the probability of experiencing extreme surface weather conditions. We review a variety of techniques for identifying circulation regimes from reanalysis and numerical model output. While various techniques often yield similar regime circulation patterns, they offer different perspectives on the regimes. The regimes themselves are manifest in planetary scale patterns. They affect the structure of synoptic scale patterns. Extratropical flow regimes have been identified in simplified atmospheric models and comprehensive coupled climate models and in reanalysis data sets. It is an ongoing challenge to accurately model these regime states, and high horizontal resolutions are often needed to accurately reproduce them. The regime paradigm helps to understand the response to external forcing on a variety of time scales, has been helpful in categorizing a large number of weather types and their effect on local conditions, and is useful in downscaling. Despite their usefulness, there is a debate on the "nonequivocal" and systematic existence of these nonlinear circulation regimes. We review our current understanding of the nonlinear and regime paradigms and suggest future research

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“…Incorrect station elevation and imperfect assumptions about the air temperature profile extrapolated downward to sea level are generally the largest sources of error for applications of altimeter setting (Mohr 2004). Nonetheless, surface pressure and altimeter setting have been used extensively to diagnose the accuracy of numerical weather prediction model forecasts, including the position and intensity of individual cyclones and anticyclones (Colucci and Bosart 1979;Charles and Colle 2009;Mesquita et al 2010;Wheatley and Stensrud 2010) and aggregate statistics over a portion of or an entire model domain (Charles and Colle 2009;McMurdie and Casola 2009). In addition to the assessment of HRRR-AK cumulative pressure errors over the 7-month period using NWS/ FAA and TA observations, a case study of a strong downslope wind event in the lee of the Alaska Range during 12-15 February 2017 will be presented to investigate a period of low HRRR-AK forecast skill.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Experimental High-Resolution Rapid Refresh–Alaska Modeling System Using USArray Pressure Observations

McCorkle

Horel

Jacques

et al. 2018

Weather and Forecasting

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The High-Resolution Rapid Refresh–Alaska (HRRR-AK) modeling system provides 3-km horizontal resolution and 0–36-h forecast guidance for weather conditions over Alaska. This study evaluated the experimental version of the HRRR-AK system available from December 2016 to June 2017, prior to its operational deployment by the National Centers for Environmental Prediction in July 2018. Surface pressure observations from 158 National Weather Service (NWS) stations assimilated during the model’s production cycle and pressure observations from 101 USArray Transportable Array (TA) stations that were not assimilated were used to evaluate 265 complete 0–36-h forecasts of the altimeter setting (surface pressure reduced to sea level). The TA network is the largest recent expansion of Alaskan weather observations and provides an independent evaluation of the model’s performance during this period. Throughout the study period, systematic differences in altimeter setting between the HRRR-AK 0-h forecasts were larger relative to the unassimilated TA observations than relative to the assimilated NWS observations. Upon removal of these initial biases from each of the subsequent 1–36-h altimeter setting forecasts, the model’s 36-h forecast root-mean-square errors at the NWS and TA locations were comparable. The model’s treatment of rapid warming and downslope winds that developed in the lee of the Alaska Range during 12–15 February is examined. The HRRR-AK 0-h forecasts were used to diagnose the synoptic and mesoscale conditions during this period. The model forecasts underestimated the abrupt increases in the temperature and intensity of the downslope winds with smaller errors as the downslope wind events evolved.

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Weather Regimes and Forecast Errors in the Pacific Northwest

Cited by 13 publications

References 29 publications

Improving Winter Storm Forecasts with Observing System Simulation Experiments (OSSEs). Part I: An Idealized Case Study of Three U.S. Storms

Improving Winter Storm Forecasts with Observing System Simulation Experiments (OSSEs). Part I: An Idealized Case Study of Three U.S. Storms

Low‐frequency nonlinearity and regime behavior in the Northern Hemisphere extratropical atmosphere

Evaluating the Experimental High-Resolution Rapid Refresh–Alaska Modeling System Using USArray Pressure Observations

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