On the 2m temperature and dew point diagnostics in the COSMO model
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1 Eidgenössisches Departement des Innern EDI Bundesamt für Meteorologie und Klimatologie MeteoSchweiz On the 2m temperature and dew point diagnostics in the COSMO model Matteo Buzzi and M.W. Rotach MeteoSwiss
2 Overview Introduction Surface layer Operational 2m temperature and dew point diagnostics Possible sources of error The role of subgrid scale orography Alternatives: new interpolation formulas or profiles Case studies Intercomparison: verification results Conclusions 2
3 Surface layer 0.1z i z * Inertial sublayer (ISL) constant turbulent fluxes Roughness sublayer (RSL) NWP models first model layer z * = 2h can h can 2m 0 Θ'w' surf or Qv'w' surf inconstant fluxes Θ'w' sensible heat flux Qv'w' latent heat flux 3
4 COSMO 2m temperature and dew point diagnostics: 3 cases h can RC r H H H H r + ( ) lam r + tur lam rtur log rlam = H z 0 +h(ke-1) T(ke-1), Q(ke-1) H2=z 0 +h(ke) T(ke), Q(ke) H1=z 0 h can 0 T s,q s EXP LOG LOG INTERP skin layer! 4
5 2m temperature: possible sources of error Surface temperature: soil model (surface energy balance, LH, SH, GF, SW bal, LW bal ) Atmosphere temperature: dynamics (e.g. advection), convection, turbulence scheme Interpolation profile in the diagnostics: choice of wrong profile function Surface description: Roughness length: canopy height 5
6 COSMO-7 roughness length (7 km) [m] 6
7 COSMO-7 roughness length: local and orographic component (7 km) z 0,loc [m] z 0,oro [m] z 0 = z 0,loc + z 0,oro h can 7
8 Unrealistic canopy height (7km) UTC UTC ( hcan = RC r H lam hcan +r H tur ) H rlam + rturh log H r lam [m] z0, loc = 0.1 exp profile is too often used! matteo.buzzi@meteoswiss.ch 8
9 Averaged diurnal cycle: z 0,oro < 0.2 m 0.2 m < z 0,oro < 0.5 m COSMO-7 over the alpine region 9
10 Phase error COSMO-7- Swiss SYNOP stations 10
11 Comparison of different diagnostics Problem: 2 m temperature is too close to the surface temperature Solution: introduction of a local roughness length and try others diagnostics 0. Introduce a realistic h can in operational diagnostics But inconsistent with resistances (option only possible if surface transfer scheme and turbulence scheme are called twice) 1. Use a simple logarithmic interpolation as used for wind (newlog) But not consistent with RSL (z 0,loc >0.2m)! 2. ECMWF IFS diagnostics (logarithmic interpolation based on Monin- Obuchov similarity) (ecmwf) But not consistent with RSL (z 0,loc >0.2m)! 3. New approach (new): New logarithmic profile (as 1.) only for gridcells with z 0,loc < 0.2m z 0,loc > 0.2m new RSL profiles independent from surface temperature 4. Diagnostics for a SYNOP garden (by Matthias R.) (dwdnew) But not consistent with RSL (z 0,loc >0.2m)! 5. As 4. but with z 0,loc instead of typical SYNOP z0 (dwdnew z0loc) 11
12 New profiles: general aspects Approach for large z 0,loc : derive temperature and specific humidity profile from turbulent flux profiles and atmospheric values 0.1z i H2 z* First model atmospheric level Inertial sublayer ISL Roughness sublayer RSL T,QV,H 0, LH 0, Mo 0 T*, ISL fluxes h can d H2 = H(ke) + z 0,loc + d h can = z 0,loc 0.1 z* = 2h can 0 Temperature d = 2 3 h can 12
13 New profiles: 3 cases newlog 13
14 New profiles: formulation dθ dz = θ * (z) α (z z 0,loc ) θ * (z) = w'θ'(z) u * (z) = w'θ'(z) ( u'w'(z) 2 + v'w'(z) 2 ) 1/4 RSL: local scaling θ(z) = θ(z * ) z z0 θ * (z) α (z z 0,loc ) dz Integration Profile matching at z * θ * (z * ) α (z * z 0,loc ) = φ h RSL θ * k(z * d) α = k(z z ) * 0,loc φ h (z * d) ISL φ h ( z L ) 14
15 Sensible heat flux and vertical temperature derivative 15
16 Temperature and specific humidity 16
17 Case studies and model settings 5 cases 24h forecast COSMO 7km (fairly good weather) , , , , COMSO 3.20, Runge-Kutta, IFS Analysis as BC, COSMO analysis as IC Verification with SYNOP stations for the domain covering the alpine region (COSMO-2) (for all 6 variants) 17
18 Variants compared with operational diagnostics 1. Simple logarithmic interpolation as used for wind (newlog) 2. ECMWF IFS diagnostics (ecmwf) 3. New approach (new): RSL profiles z 0,loc > 0.2m 4. Diagnostics for a SYNOP garden (dwdnew) 5. As 4. but with z 0,loc instead of typical SYNOP z 0 (dwdnew z0loc) 18
19 Results: diurnal cycle
20 Averaged diurnal cycle:
21 Comparison of the vertical profiles 21
22 Comparison of the vertical profiles 22
23 Verification: SYNOP alpine region 2m temperature
24 Verification: SYNOP alpine region 2m dew point (RMSE) 24
25 2m temperature: results summary COSMO-7 verified on COMSO-2 domain (only 5 days)! RMSE [ C] ME [ C] STDEV ME [ C] Operational new RSL newlog dwdnew dwdnew z 0,loc ecmwf
26 Conclusions 2 m temperature and 2m dew point: multiple sources of error (soil, atmosphere, choice of the interpolation profile) Unrealistic canopy height (from subgridscale orography) is a significant source of error (choice between EXP and LOG profile) Operational diagnostics compared to 5 options based on local roughness length or on SYNOP garden 26
27 Conclusions Better verification results for all the 5 options: Phase shift improved Cold bias in winter significantly reduced but still important! Logarithmic interpolation: the best results, BUT inconsistent with the RSL (for z 0,loc >0.2)! The new RSL profiles perform comparably well and are consistent with the RSL Local roughness length necessary for diagnostics: should be introduced in COSMO Downscaling on a SYNOP garden: inconsistent with the mean gridbox conditions in the model but gives better verification results (better DWD) 27
28 Eidgenössisches Departement des Innern EDI Bundesamt für Meteorologie und Klimatologie MeteoSchweiz Thank you for your attention!
29 Verification: SYNOP Switzerland 2m temperature
30 New profiles: turbulent fluxes Momentum fluxes z z0 u'w' = c u'w'isl zs z0 z z0 v'w' = c v'w'isl zs z0 u'w'(z*) = u'w'isl 2 2 exp a(1 z z0 zs z0 exp a(1 z z0 zs z0 v'w'(z*) = v'w'isl c = z * z0 zs z0 2 Kaster-Klein and Rotach (2004) a=2 exp a(1 z * z0 zs z0 Sensible heat flux z z0 w'θ' = w'θ'isl z s z0 2 exp ch z s z z < z s z s ch=1.2 w'θ' = w'θ'isl z z s Modified from Christen (2005) 30
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