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HWRF PHYSICS Young C. Kwon EMC/NCEP/NOAA Hurricane WRF Tutorial NCWCP College Park, MD Jan 14 2014 1.

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Presentation on theme: "HWRF PHYSICS Young C. Kwon EMC/NCEP/NOAA Hurricane WRF Tutorial NCWCP College Park, MD Jan 14 2014 1."— Presentation transcript:

1 HWRF PHYSICS Young C. Kwon EMC/NCEP/NOAA Hurricane WRF Tutorial NCWCP College Park, MD Jan

2 Contents 1.Overview 2.Land surface model 3.Surface layer physics (air-sea interaction) 4.Planetary Boundary Layer 5.Convective parameterization 6.Micro-physics 7.Radiation 8.Physics upgrade plan for FY2014 2

3 Overview 1.At the initial operational implementation, HWRF physics suite was closely following as GFDL hurricane model physics. 2.Some physics are from GFS (PBL, convection), some are originated from NCEP mesoscale model (Micro-Physics) and others are from GFDL (radiation, surface physics, Land surface), and modify to tropical environment. 3.Many aspects of physics have been upgraded, and the 2013 HWRF physics will be covered in this presentation. The proposed 2014 physics upgrades will also introduced briefly. 3

4 SchemeDescriptions Ocean model POM-TC(Princeton Ocean Model) is coupled to Atm. Model, HWRF 3D POM in ATL; 1D POM in EP and uncoupled other basins Land modelGFDL slab model* Surface layer physics M-O similarity theory. GFDL based but C d and C h upgraded Planetary Boundary Layer GFS scheme with modification of diffusivity and Ri c Convective parameterization Simplified Arakawa-Schubert scheme with modifications Explicit MPFerrier scheme* RadiationGFDL LW/SW radiation scheme* *: plan to upgrade at 2014 HWRF model Physics suite 4

5 5

6 where, Thermodynamic equation Time tendency horizontal advection vertical advec. + adiabatic heating diabatic heating Diabatic heating : phase change of water – convection, microphysics Radiative absorption/emission – radiation Subgrid vertical mixing – PBL, convection Surface fluxes – air-sea interaction, land surface H. diffusion 6

7 subgrid scale mixing micro-physical processes Radiative cooling/warming subgrid scale convection Horizontal/vertical advections, horizontal diffusion Dynamics physics 7

8 Land surface model GFDL hurricane model slab ∂T*/∂t = (-σT * 4 - Shfx - Levp + (S+F ))/ρ s c s d) 8

9 Verification of HWRF Skin temperature over CONUS (compare to GFS analysis) 9

10 10 OCEAN Hurricane Low level inflow Upper level outflow Energy gain from sea surface (sensible and latent heat) C h Energy loss by surface friction C d Hurricane intensity is proportional to sqrt(Ch/Cd) over ocean – Emanuel(1995) Air-sea interactions

11 Modified GFS Scheme Original GFS Scheme C d : Surface exchange coefficient for momentum C k : Surface exchange coefficient for moisture & heat K m : Eddy diffusivity for momentum Same Observations C h before modification 10m Wind speed (m/s) Cd and Ch profile in the current HWRF model (gray dots) 11

12 HEXOS data(1996, Decosmo et al) CBLAST data (2007) Original HWRF/GFDL model 12

13 PBL scheme: Parameterize subgrid-scale vertical turbulence mixing of momentum, heat and moisture in the boundary layer. There are two main categories of PBL schemes: local vs non-local mixing scheme. Local mixing scheme: vertical mixing is proportional to the local gradient., e.g. Mellor-Yamada-Janjic scheme, Blackadar scheme Non-local mixing scheme: vertical mixing is not only proportional to local gradient but also counter-gradient mixing due to large scale eddy, e.g., GFS scheme, YSU scheme. HWRF model uses GFS PBL scheme, which is non-local mixing scheme. GFS PBL has shown to good performance outside of hurricane regions while PBL height in hurricane area is too deep and too strong mixing compare to observational data. Recent PBL scheme upgrades address this issue significantly. 13

14 1. First guess PBL height 4. Momentum diffusivity (K m ) is calculated under PBLh 5. Moist diffusivity (K t ) is calculated using Prandtl number Procedures in the operational HWRF PBL scheme 14

15 15 Hong and Pan (1996)

16 CdCh Km Gopalakrishnan et al (2012) 16

17 Reduction of momentum diffusivity led to shallower PBL height and inflow depth Gopalakrishnan et al (2012) 17

18 Variable Critical Richardson number (Vickers & Mahrt, 2003) PBL z (1 - z/h) p Motivation: The GFS PBL scheme used in HWRF model has been known to produce too diffusive boundary layer in hurricane condition. Thanks to HRD’s effort to improve the hurricane PBL in HWRF model, the diffusivity and PBL height of HWRF model greatly improved based on composite dropsonde observations (e.g., Gopalakrishnan et al. 2013, JAS; Zhang et al. 2013, TCRR) However, outside of hurricanes, the GFS PBL behaves quite well and some underestimation of PBL height is reported (Jongil Han, personal communication). Therefore, it may worth trying to revise the current PBL scheme to work well in both inside and outside of hurricane area seamlessly. 18

19 Critical Richardson number function of Ro (Vickers and Mahrt, 2003) Hurricane cases Vickers and Mahrt(2003) Critical Richardson number is not a constant but varies with case by case. R ic = 0.16(10 −7 ) −0.18 The magnitude of R ic modifies the depth of PBL and diffusivity, so the R ic varying with conditions would fit both hurricane condition and environments. 19

20 20 PBL height difference (new PBL scheme with var Ric – PBL scheme in 2012 HWRF with constant Ric=0.25) PBL height over the ocean and hurricane area becomes shallower while that over land area becomes deeper Both configurations have  set to 0.5 Hurricane Katia ( hr)

21 Convective parameterization: When grid resolution of a numerical model is too coarse to resolve individual convection, there are need to parameterize the impact of convection to grid scale. Convection does stabilized the atmospheric column by vertical transportation of heat, moisture and momentum. There are two main categories in convective parameterization scheme. One is an adjustment scheme and the other is a mass flux scheme. HWRF model uses Simplified Arakawa Shubert (SAS) which is one of the mass flux scheme. Grid point value 21

22 22 SAS deep convection scheme SL DL LFC CTOP h hshs Environmental moist static energy mb A hshs hchc 0.1A Updated SAS scheme Courtesy from Jongil Han (EMC)

23 Spurious? No momentum mixing momentum mixing analysis Too intense ? Han and Pan 2006 Mean sea level pressure (hPa) 132-h forecasts with various amounts of momentum mixing 27 Sep 2000, 12 UTC 23

24 Microphysics scheme: While convective parameterization scheme is parameterizing subgrid/unresolvable moist processes, microphysics scheme predict the behavior of hydrometeo species explicitly. Hence, microphysics scheme are called explicit moisture scheme, grid scale precipitation scheme or large scale precipitation scheme. There are bulk microphysics schemes (which are widely used in NWP models) and bin microphysics scheme. HWRF uses Ferrier microphysics scheme which is a single moment bulk scheme. 24

25 Cloud Microphysics Tropical Ferrier scheme mp_physics=85 Very similar to current NAM general Ferrier scheme Differences in RH condensation onset, number concentration, etc Designed for efficiency Advection only of total condensate (CWM) and vapor Diagnostic cloud water, rain, & ice (cloud ice, snow/graupel) from storage arrays (F_*) Assumes fractions of water & ice within the column are fixed during advection Supercooled liquid water & ice melt Variable density for precipitation ice (snow/graupel/sleet) – “rime factor” (F_rime) 25

26 Q t =Q i +Q r +Q c (CWM = ice mixing ratio+rain mixing ratio + cloud water mixing ratio) Q i = Fice * Q t Q l = (1-Fice) * Q t Q r = Q l * Frain = (1-Fice) * Frain * Q t Q c = (1-Frain)* Q l =(1-Fice) * (1-Frain) * Q t F_rime should be always bigger than 1. Based on F_rime value, ice species are defined like, snow/sleet/grauple 26

27 RACW Cloud Water GROUND REVP Rain Water Vapor RAUT Sfc Rain CND ICND DEP Sfc Snow/Graupel/Sleet Cloud Ice Precip Ice (Snow/ Graupel/ Sleet) IACWR IEVP IACW IACR IMLT T < 0 o C T > 0 o C Flowchart of Ferrier Microphysics From Ferrier,

28 SW Clear sky: net ~ -2 o /day SW LW absorption reflection sensible latent emissivity albedo Land..low heat capacity, rapid temperature Changes… diurnal variability Sea … high heat capacity, slow changes except for TC wake effects ~ -10+ o /day TC’s & Radiation Effects Low clouds 28

29 GFDL radiation Long wave ra_lw_physics=98 Used in Eta/NMM Default code is used with Ferrier microphysics Spectral scheme from global model Also uses tables Interacts with clouds (cloud fraction) Ozone profile based on season, latitude CO 2 fixed Short wave ra_sw_physics=98 Used in Eta/NMM model Default code is used with Ferrier Microphysics (see GFDL longwave) Interacts with clouds (and cloud fraction) Ozone/CO 2 profile as in GFDL longwave 29

30 Potential physics upgrades 30

31 Noah land model 31

32 Upgraded Land Surface model (GFDL slab to NOAH) 1.GFDL slab has shown large negative temperature bias over SW CONUS 2.NOAH LSM has more down-stream application potential (e.g. storm surge, inland flooding) on top of reducing negative temperature bias 3.Track errors of land-falling storms seem to be improved according to preliminary tests ~18% improvement with NOAH LSM GFS anlHWRF fcst HWRF - GFS Cold bias of HWRF sfc T 32

33 Upgraded Ferrier Microphysics 1.New ice nucleation scheme to reduce no. concentration of small ice crystals 2.New, simpler closure for diagnosing small ice crystals and large, precipitating ice particles from ice mixing ratios 3.Advection of mass-weighted rime factor (i.e. “graupel”) 4.Slightly slower fall speeds of rimed ice 5.Increase the maximum (minimum) number concentration of small (large) ice in order to simulate better anvil cloud operation upgraded obs Before upgrades 33

34 Upgraded SW/LW radiation schemes (GFDL radiation to RRTMG) 1.GFDL radiation schemes have problems of proper representations of cloud- radiation interactions, especially net cloud top cooling and net cloud base warming. 2.Although the use of RRTMG radiations degraded the intensity forecast skills of HWRF model, we are going to test again with tuning of some key parameters. Cloud top cooling due to radiation 34

35 MESO SAS convection scheme convective updraft area fundamental assumption of SAS The convective updraft area(Ac) is much smaller than grid box(Ae) σ = Ac/Ae << 1.0 : updraft fraction When grid resolution becomes finer, the assumption will not be valid anymore (<~10km). The explicit MP scheme may also have a problem 10km or finer resolution to create moist adiabatic profile smoothly, which lead to grid-point storms. Meso- SAS scheme is designed to resolve this issue of the original SAS scheme by removing the assumption of σ << 1.0 (Hualu Pan) 35

36 IMPORTANT: We need closure assumption for the MESO SAS, which is the specification of the convective updraft fraction σ. The current MESO SAS scheme determines σ based on the ratio of grid point vertical velocity and convective updraft vertical velocity as followed: 36


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