Impacts of Rossby Wave Packets on Impacts of Rossby Wave Packets on Forecast Uncertainties and ErrorsForecast Uncertainties and Errors

Brian A. Colle, Edmund K.M. Chang, and Minghua ZhengBrian A. Colle, Edmund K.M. Chang, and Minghua ZhengSchool of Marine and Atmospheric SciencesSchool of Marine and Atmospheric Sciences

Stony Brook UniversityStony Brook UniversityStony Brook, New York, USAStony Brook, New York, USA

NROW 1410 December 2013

OutlineOutline

MotivationMotivation

Relationship between RWPs and Forecast ErrorsRelationship between RWPs and Forecast Errors

-- for relatively large East coast medium range errors-- for relatively large East coast medium range errors

-- evolution of errors relative to a moving RWP-- evolution of errors relative to a moving RWP

-- ensemble spread starting with RWP over Pacific-- ensemble spread starting with RWP over Pacific

Ensemble Wave Packet Page and Updates to Ensemble Wave Packet Page and Updates to Ensemble Sensitivity PageEnsemble Sensitivity Page

Summary and Ongoing ResearchSummary and Ongoing Research

What are Rossby Wave Packets? An example (adapted from Chang 1993)

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Contours: 300 hPa Z

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Contours: 300 hPa ZShades: 300 hPa v

Hovmoller (Time-Longitude) diagram

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Unit: m/s

Climatology of RWPA(Souders et al. 2013 –submitted to MWR)

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Max: ~18m/s across NAMin: < 8m/s central Asia

From THORPEX International Science Plan(Shapiro and Thorpe, 2004)

Cyclogenesis near Japan

Flooding over Europe

RWPs have frequently been linked to high impact weather downstream

Taken from U.S. TPARC science plan. Adopted from Hakim (2005)

Initial analysis error structure

12-hr forecast uncertainty

24-hr forecast uncertainty

Another example showing the similarity between RWPs and Another example showing the similarity between RWPs and ensemble sensitivity signals (2010 Christmas snowstorm)ensemble sensitivity signals (2010 Christmas snowstorm)

Downstream development

Group V > Phase V

Magenta: region for calculating EOF of ensemble meridional wind v300.State field: v300

Unit: m/s

Sensitivity

Wave packet

From Zheng et al. (2013)

Data 1:Data 1: GFS analysis and 7-day GFS analysis and 7-day

control run forecast for 5 cool control run forecast for 5 cool seasons (2007-2012)seasons (2007-2012)

Parameters: geopotential Parameters: geopotential height at 300 hPa (Z300)height at 300 hPa (Z300)

Data 2: Data 2: RWP amplitude: calculated by RWP amplitude: calculated by

Matthew Souders using u,v Matthew Souders using u,v and Z at 300 hPaand Z at 300 hPa

MethodMethod Composite methodComposite method RMSE of Z300RMSE of Z300

NN: total grids number: total grids number Absolute error Absolute error

Forecast ErrorsForecast Errors

Preliminary results: verification region and large error cases Preliminary results: verification region and large error cases selectionsselections

Verification region (VR): 22°N-63°N, 99°W-46°W

Inter Quartile Range (IQR): Third Quartile - First Quartile

Drop-out cases: RMSE>=mean+1.2*IQR (75 cases) Good forecasts: RMSE<=mean-1.0*IQR (79 cases)

Composited RWPA anomaly for large error casesComposited RWPA anomaly for large error cases

Initial Positive RWPA Anomaly Develop and Propagate into VR

Unit: m/s

The purplepurple contour corresponds to 95% significance level

For 46 most robust wave packets over NAmer (2007-2013):

Composited RWPA (shaded, [m/s]) and the normalized 300 Z forecast error (Magenta Contours, forecast error divided by maximum error,[%]). Errors at day -3 to +3 correspond to 0.5 day to 6.5 day forecast errors.

For 46 most robust wave packets over NAmer (2007-2013):

Composited RWPA (shaded, [m/s]) and the normalized 300 Z forecast error (Magenta Contours, forecast error divided by maximum error,[%]). Errors at day -3 to +3 correspond to 0.5 day to 6.5 day forecast errors.

Wave packet relative errors for same 46 cases, which includes the composited RWPA and errors with the centers representing the weighted wave packet centers at each step.

Wave packet amplitude (shaded, [m/s]) and forecast errors (magenta contour, [%]). The composites are centered at the weighted centers of RWPA at each step.

25 coherent RWPS starting from central Pacific are selected to calculate the RWPA mean and 300Z normalized spread divided by max spread (%) using the 20-member GEFS from day 0 to day 6.5

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Days 6-6.5

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Unit: m/s

Very strong Positive RWPA Anomaly Develop and Propagate into VR

Discussions: sensitivity to VR―composited RWPA anomaly for large error cases (EUROPE)

The greengreen contour corresponds to 95% significance level

Day 0

(http://wavy.somas.stonybrook.edu/wavepackets/home.html). Figure 8 shows the cover of the page, in which users can

http://dendrite.somas.stonybrook.edu/CSTAR/Ensemble_Sensitivity/EnSense_Main.html). Figure 8 shows the cover of the page, in which users can

Updates to Ensemble Sensitivity Web Page

SummarySummaryComposited RWPA for GFS large error cases over U.S. East Composited RWPA for GFS large error cases over U.S. East Coast shows a positive RWPA anomaly originating from eastern Coast shows a positive RWPA anomaly originating from eastern Asia and propagating across the Pacific into the verification box. Asia and propagating across the Pacific into the verification box. Large error cases over Europe also show a propagating RWPA Large error cases over Europe also show a propagating RWPA positive anomaly upstream. positive anomaly upstream.

-- These results suggest that large error cases are associated with -- These results suggest that large error cases are associated with the presence of aenhanced RWPA upstream. the presence of aenhanced RWPA upstream.

Early in the forecast over the Pacific, the largest errors tend to be Early in the forecast over the Pacific, the largest errors tend to be in the middle of the RWP, but as the packet spreads across North in the middle of the RWP, but as the packet spreads across North America in the medium range, the largest errors (and ensemble America in the medium range, the largest errors (and ensemble spread) occur more around the leading edge of the packet spread) occur more around the leading edge of the packet (**Could be an important signal to look for while forecasting…)(**Could be an important signal to look for while forecasting…)

Ongoing ResearchOngoing Research

Examine ensemble forecasts using TIGGE dataExamine ensemble forecasts using TIGGE dataTo study the relationship between RWPs and forecast uncertaintiesTo study the relationship between RWPs and forecast uncertainties

Study how forecast uncertainties and errors grow in multi-modelStudy how forecast uncertainties and errors grow in multi-modelCompare ensemble outputs from different operational modelsCompare ensemble outputs from different operational models