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Winter Weather Refresher

Winter Weather Refresher Stephen Jascourt and Bill Bua COMET NWP resources Stephen.Jascourt@noaa.gov Bill.Bua@noaa.gov at NCEP OUTLINE 1. Global Forecast System – what did we learn last winter? 2. Global Forecast System – what’s new for 2003-2004?

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Winter Weather Refresher

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  1. Winter Weather Refresher Stephen Jascourt and Bill Bua COMET NWP resources Stephen.Jascourt@noaa.gov Bill.Bua@noaa.gov at NCEP

  2. OUTLINE 1. Global Forecast System – what did we learn last winter? 2. Global Forecast System – what’s new for 2003-2004? 3. Eta Model – what did we learn last two winters? 4. Eta Model – what’s new? 5. Nonhydrostatic Mesoscale Model (NMM) 6. Short range ensembles (SREF) 7. RUC-20 8. COMET Slides with this blue background indicate transition to next item in above outline

  3. Global Forecast System: What did we learn last winter?

  4. October 2002 and August 2003 Implementations • Increased resolution from T170L42 to T254L64 for first 84 hours of forecast (10/02) • Replaced long wave radiation scheme 8/02 (now called RRTM) • Results in warmer troposphere, colder stratosphere • Should mitigate the GFS cold bias in troposphere • Colder stratosphere may impact data assimilation of satellite radiances

  5. Anecdotal evidence about the GFS • GFS deepens mid-tropospheric troughs too much in eastern North America, particularly past day 3-4 • Evidence that the GFS prefers positive PNA pattern (ridge west, trough east North America) • GFS often has better storm tracks along the Gulf and Atlantic coasts than the Eta-12 • Reasons for above are unknown and may be regime-dependent • Likely will continue in winter 2003-04 • Forecasters should assess anew this winter

  6. Contrasting Winter Regimes: ‘01-’02 vs ‘02-’03 Negative PNA in winter 2001-02 (positive height anomalies over eastern US) Positive PNA in winter 2002-03 (positive height anomalies over Alaska/Yukon, negative over east coast)

  7. Comparison of 5 day 500-hPa height error: DJF 01-02 to DJF 02-03 Too much troughing over eastern US, not enough across north Pacific and Hudson Bay Too much ridging over northern oceans, too much trough over NH mid-latitude continents

  8. GFS lower tropospheric cold bias in cold season 00 UTC GFS analysis and forecast biases for 850-hPa temperatures at 12-h intervals for January 2002 0ºC 24-h analysis Cold bias over west, spreads across northern plains during forecast. 36-h Magnitude may depend on flow regime 12-h 48-h

  9. Compare January 2002 to 2003850-hPa for 1st 48 hrs of forecast 00 UTC GFS analysis and forecast biases for 850-hPa temperatures at 12-h intervals for January 2003 0ºC 24-h analysis Overall forecast bias still gets colder with time but pattern of bias different under different regime 36-h PNA regime changes biases in upper Midwest by about 1-2ºC? 12-h 48-h

  10. Model topo. (m) Cold air damming and propagation along barrierbad due to sigma coordinate: 2001-02 at T170 Contours=temperature error (surface, deg C) Colors=model terrain height 24-hour GFS fcst of 2-m temperature was 8°C too warm over High Plains during start of arctic outbreak (T170)!

  11. Cold air damming and propagation along barrierbad due to sigma coordinate: 2002-03 at T254 Contours=temperature error (surface, deg C) Colors=model terrain height Model topo. (m) At T254, 10ºC too warm at 2-m in GFS 48-hr forecast near DEN!

  12. AVN generally too wettoo large precip area and with a generally wet bias AVN 36-h forecast of 24-h precipitation verifying 12z 3 March 2002 24-h gage analysis of precipitation verifying 12z 3 March 2002

  13. T254 still has same precipitation bias Grid 211: 24, 48, 72-hr fcsts of 24-hr accum prec ECMWF ECMWF 0.4 0.4 UKMET UKMET GFS GFS 0.2 0.2 Equitable Threat Score Equitable Threat Score JAN 2003: Dry month FEB 2003: Wet month UKMET GFS ECMWF UKMET ECMWF GFS 1.0 1.0 BIAS BIAS

  14. GFS tends not to be able to remove enough elevated CAPE Why do we care about this in the cold season? • Can result in overdevelopment of frontal waves • Waves move too far into the cold air • Overdevelopment results in problems with amount (too much), location, and type of precipitation • Example follows from winter 2001-2002 • Note: This problem is not expected to improve with resolution increase on October 29, 2002 • The source of the problem is physics, rather than dynamics

  15. GFS tends not to be able to remove enough elevated CAPE - example FORECAST versus ANALYSISlow positions and pressures at 6 hour intervals from 00z7Dec01 through 12z9Dec01from GFS run of 00 UTC 7 Dec 2001 996 1003 1006! 1008 1012! 1011 12z09Dec01 12z08Dec01 (lows collocated)

  16. GFS tends not to be able to remove enough elevated CAPE - example Verification, 12z8Dec01 Verification, 12z9Dec01 Low tracks Forecast Analysis

  17. GFS tends not to be able to remove enough elevated CAPE Reasons for overdevelopment in this GFS forecast: • Deep, moist, conditionally unstable elevated layer • Convective scheme cannot remove this instability (or enough of it) • Grid-scale scheme convects instead, which results in too much: • Latent heating in 850-500 hPa layer • Vorticity spin-up at low- and mid-levels • Frontal wave intensification • Moisture convergence in lower troposphere (results in even more moisture entering the grid column!)

  18. Ensembles more consistent run to run than operational higher-resolution GFS Yellow = operational MRF, same valid times Initial=00 UTC 8 April 2002 Initial=00 UTC 9 April 2002

  19. 3-day forecast from 00 UTC 11/2/01, spaghetti diagram for ensemble global Ensembles help assess forecast confidence and range of scenarios Uncertain location of incoming western trough Uncertain amplitude of eastern trough From CDC web site: http://www.cdc.noaa.gov/map/images/ens/ens.html

  20. Relative Measure of Predictability (RMOP)measure of how likely the ensemble mean ishttp://wwwt.emc.ncep.noaa.gov/gmb/ens/index.html (note: wwwt may become www) • Based on last 30 days of ensemble performance to take into account regime predictability and general model performance • Ensemble mean and each ensemble member placed in equally likely climatological bins (bins vary seasonally and geographically to account for typical variability) • RMOP colors with percentage below color bar show the percentile rank of today’s forecast compared to the last 30 days for number of ensemble members agreeing with their ensemble means (“agreeing with” = in the same bin) • For example, red (90%) means the ensemble distribution has more members in the same bin as the mean than 90% of the cases in the past 30 days, suggesting this is among the most predictable forecasts in the last month • RMOP probability numbers (above the color bar) • Calibrated probability that ensemble mean will verify based on how often the ensemble mean verified when the same number of ensemble members were in the bin containing the ensemble mean during the past 30 days

  21. Unpredictable heights in Strong gradient Ridge/Trough Highly predictable

  22. Global Forecast System: What’s new for 2003-2004?

  23. Resolution through boreal winter 2003-04 GFS 00, 06, 12, 18 UTC “MRF” are same as fields labeled “AVN”. MRF fields to be discontinued T254 L64 T170 L42 T126 L28 84h 180h 384h 3½d 7½d 16d 2003 until …. Planned change (may only be resolution) by 12/6/03 T126 L28 T126 L28 Ensembles T62 L28 T62 L28 84h 180h 384h 3½d 7½d 16d 84h 180h 384h 3½d 7½d 16d 11 members (1 control, 10 perturbations) 11 members (1 cont., 10 pert) 00 UTC, 12 UTC 00 UTC, 06 UTC, 12 UTC, 18 UTC

  24. Topography comparisonT254 topography (0-3.5 days)

  25. Resolution of topography affects precip forecast Verification T170 T254 Sharper precipitation maxima, slightly better placement of precipitation as a consequence of increased horizontal resolution (first 3 1/2 days only!)

  26. Topography comparisonT170 topography (3.5-7.5 days)

  27. Topography comparisonT126 topography (7.5-16 days), also ensembles 0-3.5 days until 12/06/03, then 0-7.5 days

  28. Topography comparisonT62 topography(ensembles 3.5-16 days until 12/06/03, then 7.5-16 days)

  29. New Long Wave Radiation Scheme and Changes to Cloud-Long Wave Radiation Interaction • More efficient (runs twice as fast) • More accurate (by a factor of 5 to 10!) • Decreased lower tropospheric cold bias and upper tropospheric/lower stratospheric warm bias in parallel experiments • High stratosphere cold bias occurs (may affect data assimilation of radiances?) Details at: http://meted.ucar.edu/nwp/pcu2/avclrad2c.htm and http://meted.ucar.edu/nwp/pcu2/avradtr4.htm

  30. GFS warmer with new long wave scheme Skin T Skin and 2-meter temperatures with RRTM long wave are higher than old GFS LW radiation early in the forecast at high latitudes 2-meter T

  31. GFS warmer with new long wave scheme Near-surface temperature increase in RRTM over old GFS LW radiationincreases through 5 days (average difference around 1oC)

  32. Eta Model:What did we learn last two winters? Model has been stable (no major changes, several minor fixes) from December 2001 through June 2003

  33. Examine the analysis! • Compare against satellite, radar, surface data, etc.! • Large scale features set the forecast scenario • Model details and high resolution topography and coastlines will not help forecast accuracy if the large-scale winds are not well forecast or the cyclone track or intensity is off. • Look off the coasts – is the Atlantic ridge too weak in the model? Is the trough off the west coast sharp enough? Is the jet core, where parcels are peeling anticyclonically into, through, and out of, in the right position? How do you expect errors in such features will affect the strength of a cold surface high or the amplitude and timing of a major wave in the model forecast?

  34. Sensitivity to multiple factors B, F (in) A,C, D, E, G, H (mm) Initial conditions • GFS vs. Eta initial state in same model: • compare B vs. F • compare D vs. G B C D A Physics • Different convective parameterizations in same model: • compare C vs. D vs. H Resolution F H • Different resolutions in same model: • compare A vs. C vs. B E G • Also, different models with same initial condition: • compare E vs. F Look at: different models and ensembles! Check for: bad init. cond. and unphysical behavior in forecast

  35. Remember, saturation for ice occurs at much lower RH with respect to water • Affects your interpretation of cloud base/top and cloud coverage (new 32 km SREF is between brown and pink curves) Model cloud top of overcast deck Forecast sounding (new 32 km SREF is between brown and pink curves) Ice saturation threshold in 12 km Eta model Model is saturated with respect to ice Model cloud base

  36. Drying trend during forecast • precipitable water becomes steadily drier during forecast compared to verification • QPF also dries up at increasing forecast range compared to verification • Monthly total 24-h forecast minus observed precipitation for Feb 2003 • lower (or more negative) values at later times into forecast period Valid at 36 h Valid at 60 h Valid at 84 h

  37. Watch for moisture stream getting intercepted by convection • Convective scheme drops too little precip, leaving moisture stream free to reach area where dynamics are causing grid-scale lift in colder air. • In reality, convection intercepts moisture stream. Moist inflow =7inches =5inches =1inch Moist inflow Moist inflow

  38. Snow drifting downwind while falling Most falls on upwind side but some advects downwind of ridges

  39. Snow drifting downwind while falling Most falls on upwind side but some advects downwind of ridges

  40. Lake Effect • Lake-effect band placement excellent • precip intensity too weak by factor of at least 3 overall and 10 for peak local amounts • can’t resolve multiple bands and waves

  41. Isothermal layers form at 0 oC Hourly BUFR sounding 0oC

  42. Precipitation Type: microphysics vs. diagnostic output Hourly BUFR sounding now in BUFKIT

  43. Precip type grids are not from model microphysics Baldwin-Schichtel diagnostic algorithm • Tends to have bias against SN in Eta; overforecasts ZR • Purpose is to alert forecaster to potential hazardous weather (ZR is most hazardous) so that forecaster inspects situation carefully and determines for him/herself the precip type

  44. Precipitation Type: microphysics vs. diagnostic output Overrunning case at LEX (Kentucky) Hourly BUFR sounding Both all liquid 0oC

  45. Precipitation Type: microphysics vs. diagnostic output Overrunning case at LEX (Kentucky) Hourly BUFR sounding Microphysics=72% frozen precip Baldwin=rain 0oC

  46. Precipitation Type: microphysics vs. diagnostic output Overrunning case at LEX (Kentucky) Hourly BUFR sounding Microphysics=mix of 21% frozen Baldwin=rain 0oC

  47. Precipitation Type: microphysics vs. diagnostic output Overrunning case at MSL (Alabama) Hourly BUFR sounding Microphysics=94% frozen Baldwin=rain 0oC

  48. Precipitation Type: microphysics vs. diagnostic output Overrunning case at MSL (Alabama) Hourly BUFR sounding Microphysics=mix with only 13% frozen Baldwin=rain 0oC

  49. Patchy snow cover with bare ground spots changed 26 Feb 2002 • Before model fix: (as in soundings to the left) • 2-meter temperatures too cold over snow • 850 temperatures too warm over Canada • arctic boundary layer poorly handled • After model fix (as in schematic below): • 2-meter temps warmer, 850 temps cooler so verifies better • arctic boundary layer structure still poor, seldom makes very stable even when it should Too warm (before fix) Too cold

  50. Land surface upgrade summer 2001 Cold season processes (Koren et al 1999) • Patchy snow cover • Frozen soil (new state variable) • Variable snow pack density (new state variable) • Soil heat flux under snowpack (Lunardini 1981) • New maximum snow albedo database (Robinson & Kukla 1985) • Takes into account observed effect of vegetation on the albedo of grid box

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