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Model Representation of Freezing and Melting: Anticipation of Model-Dependent Thermal Biases or

Model Representation of Freezing and Melting: Anticipation of Model-Dependent Thermal Biases or Why Melting Snow Made Me Happy as a Child (without me knowing it!). Sandy Lackmann, age 2. Cary, NC, 25 January 2000. MSC/COMET Presentation, 23 February 2001. Gary M. Lackmann

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Model Representation of Freezing and Melting: Anticipation of Model-Dependent Thermal Biases or

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  1. Model Representation of Freezing and Melting: Anticipation of Model-Dependent Thermal Biases or Why Melting Snow Made Me Happy as a Child (without me knowing it!) Sandy Lackmann, age 2. Cary, NC, 25 January 2000 MSC/COMET Presentation, 23 February 2001 Gary M. Lackmann Department of Marine, Earth, and Atmospheric Sciences North Carolina State University 1

  2. Outline I. Atmospheric Processes & Model Representation A. Thermodynamics of winter precipitation Review of p-type considerations  Cooling mechanisms in winter storms  Physical representation in NWP models B. Freezing rain  Limiting processes and other considerations  Model representations and limitations II. How Models “Do” Clouds and Precipitation A. Overview of how models represent precipitation “grid-scale precipitation” “parameterized precipitation” B. Why most models don’t represent melting and freezing 2

  3. Disclaimer I certainly do not have all the answers because: 1.) I am learning new NWP material continuously 2.) The models are “moving targets”, and are constantly changing. Today’s biases might not be tomorrow’s! 3.) NWP as a science is evolving rapidly 3

  4. Thermodynamics of Winter Precipitation Will it rain or snow? Four processes that can cool the atmosphere: 1.) Cold-air advection (CAA) Model Representation: Yes, in theory. Dependent on accuracy of synoptic-scale forecast! 2.) Evaporation/sublimation of falling precipitation Model Representation: Yes, some account of this process in all or most models (Eta, GEM, RUC, MM5 most complete physics). Proper account hinges on accurate QPF... 4

  5. Thermodynamics of Winter Precipitation Processes that can cool the atmosphere (cont.): 3.) Ascent (in stable air); a.k.a. “dynamic cooling” Model Representation: Yes, but can be problematic if strong mesoscale ascent. 4.) Melting!!! (Either in the air or on the ground) Yes/No; Often poorly handled or not represented! KNOW YOUR MODEL! Melting! (in the air) Melting! (on the ground) 0C 0C 5

  6. Consider a typical “rain” sounding (MHX, 00/01/25 00UTC): • Snow develops aloft via Bergeron-Findeisen process & may grow by agglomeration • Snow melts around 720 mb level • Latent heat of melting absorbed there- a cooling process! 6

  7. Example of isothermal layer in a sounding Maniwaki, Quebec before the big ice storm (still snowing) 7

  8. Seattle, WA 26-27 December 1974 25 cm (9.8”) snow at SEA, with 65 mm (2.56”) liquid equivalent 0 snow at BLI, with only 11 mm (0.44”) liquid A formative event in my childhood, even though we didn’t miss school! 8

  9. From First Law, for a 150 mb deep layer: • Tmelting (C)=  140.2 * [precipitation in mm] • Tmelting (C)=  5.52 * [precipitation in inches] • For 12 mm (6 h-1), Tmelting  2.8 C (6 h-1) • A 150-mb deep layer cools 2.8C (6 h-1) due to melting snow alone • Above-freezing layers can “melt out” with sufficient precipitation intensity • In terms of partial thickness: a T of 2.8C in the 1000-850 mb layer translates to a thickness change of 13 meters. • An important paper on this topic just came out in WAF: • Kain, Goss, and Baldwin, 2000: WAF 15, 700-714. 9

  10. For even modest precipitation amounts, this can have a major impact on nomogram location 10

  11. Melting and Your Favorite Model Nuts and Bolts of MELTING: Case 1: Melting in the Atmosphere Some models handle it, some don’t Eta, RUC, MM5, GEM (Sundqvist): Yes AVN, MRF, NGM: No (no ice physics at all, yet) Case 2: Melting on the ground When snow falls and melts on the ground, heat is absorbed. This process can cool the ground and lower troposphere. Models don’t account for this very well: KNOW YOUR MODEL’S LAND SURFACE MODEL; beware during heavy precipitation! 11

  12. Case 1: Representation of melting-induced cooling in air NGM Eta AVN MRF GEM No Yes No No Yes • Currently, NGM and AVN/MRF lack ice physics • These models have no account of ice or melting whatsoever! • Explains why NGM RH often greater than Eta at sub-freezing temps- NGM doesn't “know” about saturation with respect to ice!! • Thus, the Eta, GEM may have clouds with RHliquid water < 100% at subfreezing temperatures • MRF/AVN will soon upgrade physics package, will account for this (Peter Caplan, NCEP, personal communication 8/00) 12

  13. Example: 24 January 2000 • Model forecast soundings (6h) valid 1800 UTC 24 January 2000: • Eta develops isothermal layer, NGM does not • NGM has significantly warmer lower-tropospheric sounding • (NGM shows RH = 100% well above freezing level) 13

  14. Case 2: Representation of melting on the ground Eta Model (Michael Ek, personal communication & other sources): Eta land surface model uses lowest AIR temp to determine precipitation type. If < 0°C, snow assumed, if > 0°C, rain. Eta will account for melting of snow if lowest air temperature < 0°C AND GROUND TEMPERATURE > 0°C THIS IS VERY UNUSUAL (usually ground, air temp same sign) Consider situation where Tground = 1°C, T2-meters = 1°C, and heavy, wet snow is falling. Will Eta land surface model know to absorb latent heat due to melting snow at ground? 12

  15. Example: Eta-NGM Comparison12Z Sunday, 11/19/00 [RDU Wet Snow] Blue: Eta 24-h forecast sounding for RDU Red/green: NGM 24-h forecast sounding for RDU

  16. Model Comparisons • Expect Eta or GEM to be colder relative to NGM, AVN during snow (all else being equal): • account for melting of falling snow • best microphysics, most realistic account of evaporational cooling • In at least several recent NC cases, Eta TOO cold! (12/19/00) … WHY?? 14

  17. Anticipation of Isothermal Layer Development • Be wary in borderline rain/snow situations: 1.) if precipitation persistent, heavy, & radar indicates model QPF too light [Even models with more complete physics packages can err] 2.) melting can change rain or sleet to snow in spite of weak WAA 3.) if you anticipate large mesoscale ascent due to elevated convection or orographic lifting 4.) will not generally change rain to snow in “progressive” warm frontal situations 15

  18. January 30 2000 • Case summary by • Phil Badgett RDU maximum: 0C (32 F), RDU precipitation: 28 mm (1.09”) Only 3 mm (1/8”) ice in Wake Co. Why not more??? 16

  19. Freezing Rain and Sleet • Three Limiting Processes for Freezing Rain: 1.) Downward IR from warm clouds (only if PBL clear) 2.) Freezing!!! (Latent heat release can quickly send the temperature to 0°C (32°F), with subsequent runoff in lieu of additional ice buildup) 3.) Warm rain drops (sensible heat transfer) • For Major [e.g, 12-25 mm (0.5” - 1”)] Icing: 1.) must be transport of colder or drier air, or 2.) initial low-level air mass must be extremely cold or dry, or 3.) upslope wind component can also cool air! Advection of equivalent potential temperature (e) allows examination of thermal & moisture advection 17

  20. Thermodynamics From the isobaric First Law of Thermodynamics for a 100-mb layer, with consideration of latent heat of freezing alone: T( C, freezing) = + 8.2865*R (“ FZRA) Thus, for 25 mm (1.0”) of freezing rain, a 100 mb deep layer will warm by 8.3C (14.9 F). Neglecting all else, the initial temperature would have to be -8C (17F) for a 25 mm (1”) ice storm  A COOLING MECHANISM IS REQUIRED TO MAINTAIN FZRA We often *do* have such a mechanism! 18

  21. A Monumental Ice Storm: Quebec 1/98 Eta analysis (with apologies), surface observations 19

  22. A Monumental Ice Storm: Quebec 1/98 Eta analysis (with apologies), surface observations 20

  23. A Monumental Ice Storm: Quebec 1/98 Maniwaki, Quebec rawinsonde, 00 UTC 4 January 1998 21

  24. Freezing Rain: In the Air (Sleet Situation) NONE of the operational models account for the freezing of rain drops in the air (not even GEM or Eta). The net effect would be to generate a negative bias in near-surface temperatures (or in lowest partial thickness) For melting, expect a warm bias in the model temperature or partial thickness forecast for the layers where melting is active, least so in the GEM or Eta Both of these effects are most significant for heavy precipitation Biases may be “significant” (i.e., sufficient to change interpretations of forecast sounding or nomogram) 22

  25. Freezing Rain: On the Ground FREEZING on the ground: Eta Model Eta land surface model uses lowest AIR temp to determine precip type. If < 0°C, snow assumed, if > 0°C, rain. Eta will account for freezing of rain if lowest air temperature > 0°C AND GROUND TEMPERATURE < 0°C THIS IS VERY UNUSUAL (usually ground, air temp same sign) Consider situation where Tground = -3°C, T2-meters = -2°C, and heavy, freezing rain is falling. Will Eta land surface model know to release latent heat due to freezing of rain on ground? 23

  26. Summary For the case of melting snow (in air), what would the sign of the bias in NGM or AVN forecast temperature (or partial thickness) be? For a case of melting snow (in air), where the Eta underpredicted the QPF by a factor of two, what would be the sign of the bias? What about for the case of freezing rain (with any of the models)? For melting snow on ground, what is expected bias? For freezing rain, what is expected bias? 24

  27. Summary For the case of heavy melting snow, what would the sign of the bias in NGM or AVN forecast temperature (or partial thickness) be? [positive- model forecasts would be too warm for the layer containing the melting.] For the case of melting snow, where the Eta underpredicted the QPF by a factor of two, what would be the sign of the bias? [positive- model forecast would be too warm] What about for the case of freezing rain (with any of the models)? [negative- model forecast would be too cold (for the near-surface temperature or 1000-850 thickness)] 25

  28. II. Why Most Models Don’t Account for Freezing and Melting Two “kinds” of precipitation in most models: • Grid Scale (a.k.a. “stratiform”) • Parameterized (a.k.a. “convective”) Processes that are sufficiently large relative to the grid spacing of the model can be explicitly (directly) accounted for by model, or “resolved”. We must also account for (“parameterize”) processes that are too small in spatial scale to be resolved, yet that are important to the atmosphere 26

  29. Why Most Models…. A very important process that it is not always resolved in operational models is convection (scales .1 to 50 km) What does convection do? Transports heat, moisture, and momentum in the vertical stabilizes the atmosphere and generates precipitation affects radiation budget (anvil shading, etc) may generate mid-level vortices and outflow boundaries, either of which may trigger new convection Models must account for convective elements to prevent very bad forecasts (Molinari and Dudek, 1992 MWR); there are a variety of “convective parameterization schemes” (CPSs) used in models... 27

  30. How Models “Do” Cloud and Precipitation on the Grid Scale NGM, AVN, MRF DO NOT HAVE EXPLICIT PREDICTION OF CLOUDS OR RAIN WATER! (GEM, Eta do) These models remove vapor diagnostically by computing the excess vapor above a threshold or saturation value (e.g., 95% in NGM). NGM, AVN, and MRF do not consider saturation w.r.t. ice in this process, Eta, GEM do Once precipitation generated, it “falls” in the model, (may evaporate on the way down), “instantly” 28

  31. How Models “Do” Cloud and Precipitation Also, model CPS can generate precipitation of its own, in the absence of grid scale precipitation This “kind” of precipitation is generally much less reliable in the model forecast relative to grid scale The split of precipitation between grid scale and CPS for a given system depends on CPS and model resolution (important paper by Gallus WAF 1999) Running models at 5-20 km resolution is dangerous- parameterize and resolve convective scales! 29

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  34. Conclusions To use NWP effectively as a forecast tool, we must • be aware of how models represent physical processes • stay abreast of changes in model configurations and physics • strive to anticipate model biases and use knowledge of model limitations to “stay a step ahead” of models 32

  35. Some of my sources... Gallus, W. A., 1999: Eta simulations of three extreme precipitation events: Sensitivity to resolution and convective parameterization. Wea. Forecasting,14, 405–426. Rogers et al. 1995: The regional analysis system for the operational “early” Eta model: Original 80-km configuration and recent changes. Wea. Forecasting,10, 810 – 825. Zhao and Carr, 1997: A prognostic cloud scheme for operational NWP models. Mon. Wea. Rev.,125, 1931 – 1953. Zhao et al. 1997: Implementation of the cloud prediction scheme in the Eta model at NCEP. Wea. Forecasting,12, 697 – 712. Stewart and King, 1987:Rain-snow boundaries over southern Ontario. Mon. Wea. Rev.,115, 1894 – 1907. Past and upcoming model changes: http://www.ncep.noaa.gov/NCO/PMB Eta model change log: http://www.emc.ncep.noaa.gov/mmb/research/eta.log.html METED operational model matrix: [See also the meted NWP Section!] http://meted.ucar.edu/nwp/pcu2/index.htm 33

  36. Some of my sources… (cont.) Kain et al. WAF, December 2000 Peter Caplan, NCEP Michael Ek, NCEP Cote et al. 1997: The Operational CMC/MRF Global Environmental Multiscale (GEM) Model Sundqvist, 1989 MWR. 34

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