1. LHS are the linear terms. First 2 terms on the RHS are nonlinear terms in the bias. The group THF are transient heat advection bias. Q^ is the bias in diabatic heating. The vorticity bias equation is Observational “Era” data (DJF) We use ERA-40 reanalysis 4x daily data from 12/1979 to 2/2002. Data are imported at full resolution then regridded to match the CAM3 model resolution when constructing the bias. P s is from NCEP/DOE AMIP II reanalysis. CAM3 data (DJF) On the UCD cluster we ran a 20 year AMIP T42, 26 level, simulation from 1979-1998 of CAM3.0. Northern Hemisphere Winter CAM3 Bias Analysis Richard Grotjahn and Lin Lin Pan Department of Land, Air, and Water Resources, University of California, Davis 1. Introduction NCAR climate models have similar winter simulation bias in Arctic surface climate (e.g. sea level pressure, SLP and low-level wind). The bias creates unrealistic extent and thickness of Arctic sea ice. Local and remote mechanisms affect the Arctic surface bias in both observations and model output. We used uncoupled (CAM 3.0) model output, since (DJF) SLP bias is similar in both CCSM3 and CAM3. Previously we showed: 1.The 3-D structure of the CAM3 model bias in the Arctic and surrounding region. 2.The forcing of the bias using a model of the linearized CAM3 dynamics. (With friction and heating to control nonlinear instability the model treats CAM3 bias as a stationary ‘solution’.) 3.The forcing needed to produce the structures and nearly all the amplitude of the Arctic region bias are either localized to the Arctic region or in the midlatitude storm tracks. 4.Some of temperature and vorticity bias equations analyses This poster summarizes new results and the more important conclusions from this work. 2. Data Used A. Analyze how bias develops in NAST (and to lesser extent NPST). Ensembles of ‘forecast model’ runs of CAM Composites of short forecasts (e.g. all at 12hr, all at 24hr, etc.) term by term in T and ζ equations. B. Consider forcing CAM with LSW forcings from pieces of the bias C. Analyze why long waves have much less KE’ and Ens’ in CAM D. Further investigate the friction (residual) bias magnitude and sign 8. Future Work (not yet funded) 3. Temperature and Vorticity Bias Equations Define time average with overbar and use a prime for the deviation from that average. Subscript “C” denotes CAM3 data; subscript “E” denotes ERA-40 data. Define a ^ notation for the bias. The Temperature bias equation is: 1.Nonlinear terms small except for ICZ & some midlatitude surface locations 2.Diabatic and Linear advection terms are the largest 3.NAST: Linear advection terms dipolar pattern (due to storm track shift, negative NW of positive) 4.NAST: Transient advection terms larger in upper troposphere, postitive. 5.NPST: Transient terms >0 upper troposphere, <0 mid & lower troposphere 6.Diabatic heating large in tropics, CAM3 emphasizes NH ICZ 7.NAST: Diabatic heating bias large, mainly from precipitation, second by vertically averaged net radiation. 8.NAST: downstream end shifted too far south (~10-15 degrees latitude) 9.Shift of NAST makes SLP bias that autocorrelates with Barents SLP bias 10. LSW links Arctic bias to local and NAST region forcing 5. Main results from Vorticity (ζ) Bias Eqn (2) 1.Nonlinear terms small except a few locations, near Greenland & notably, Iberia. 2.Terms in ERA-40 & CAM3 rank similar at σ=0.3, but lower levels different (see table) 3.Linear horizontal advection terms largest, but have much cancelation (upper levels) 4.Bias in velocity field is largely geostrophic. 5.Friction (residual) stronger (or opposite sign) in CAM3 along NPST and NAST (Fig. 2) 6.Ens’ and KE’ smaller amplitude in CAM3 along both storm tracks, even for most long waves. (Fig 2) 4. Main results from Temperature (T) Bias Eqn (1) Figure 1, at right A) Vertically-integral latent heating (L*P) bias B) Surface sensible heat flux (SHF) bias C) Top of atmosphere net radiation (R) bias D) Total heating: Q1 = R+SHF+LP E) Q2=L*(P-E) implied heating in moisture eqn, see Trenberth & Smith (2008) F) Q1 – Q2 is total energy equation heating 6. Vertically-integrated heating7. Storm track bias v’T’ weights early stage, Ens’, KE’ weight mature stages 1.Storm track proxies biases also seen in jet stream 2.NAST start is similar in ERA and CAM3, but end is 15 o latitude south in CAM3 and extends further east. 3.Ens’ in ERA is >2x CAM3 data. (fig 3) 4.KE’ in ERA ~1.25x CAM3 5.Track better for NPST 6.KE’ & Ens’ have secondary max in Mediterranean (mainly v’) not in ERA data 7.Ens’, KE’, v’T’ narrower tracks in CAM3 8.CAM3 has much more P but much less KE & ζ in NAST! 9.CAM3 NPST starts too weak 1.Q1 dominated by heating bias (>0) over Atlantic, Pacific, W. coast 2.Net radiative (R) cooling bias over Arctic Ocean, 3.Over NAST & Russia Q1>0 mainly from Precipitation (P), also R. 4.NPST: SHF too weak at start ( 0 at end. Ens’ Transient vorticity squared (2-8 day band pass enstrophy) ICZ Intertropical Convergence Zone KE’ Transient kinetic energy per unit mass (2-8 day band pass) LSW Branstator (1990) model linearizes CAM primitive equations about the winter (DJF) time mean. NAST North Atlantic Storm Track NH Northern Hemisphere NPST North Pacific Storm Track P precipitation R net radiation (short & long) at top of atmosphere SHF Sensible heat flux from the surface v’T’ meridional heat flux by transients (2-8 day band pass) 9. Acronyms and Abbreviations used Figure 2. Vorticity spectrum at 40N, table ranking terms, and ζ friction for CAM, ERA-40, and bias Figure 3. Left column: KE’ for ERA- 40, CAM, and bias. Right column: Ens’ for ERA-40, CAM, and bias. e) f) Peek-a-boo Canyon, Utah Photo © Richard Grotjahn