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Inspiration for REMOTE SENSING satellites

Inspiration for REMOTE SENSING satellites. Or What could have happened to lidar if Nov. 2000 had turned out differently. R. A. Brown 2005 EGU; Lidar Mt. Hood. Evolution and current Status of Surface Pressure Fields from Scatterometer data. And maybe from radiosonde (WindSat) data.

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Inspiration for REMOTE SENSING satellites

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  1. Inspiration for REMOTE SENSING satellites Or What could have happened to lidar if Nov. 2000 had turned out differently R. A. Brown 2005 EGU; Lidar Mt. Hood

  2. Evolution and current Status of Surface Pressure Fields from Scatterometer data And maybe from radiosonde (WindSat) data R. A. Brown 2005 EGU; Lidar Mt. Hood

  3. State of The analytic solution for a PBL fV + K Uzz - pz / = 0 fU - K Vzz + pz /  = 0 The solution, U (f, K,p ) was found by Ekman in 1904. Unfortunately, this was almost never observed. fV + K Uzz - pz/ = 0 fU - K Vzz + pz/ = A(v2w2) Solution, U (f, K,p ) found in 1970. OLE are part of solution for 80% of observed conditions (near-neutral to convective). Unfortunately, this scale was difficult to observe. The complete nonlinear solution for OLE exists, including 8th order instability solution, variable roughness, stratification and baroclinicity, 1996. Being integrated into MM5, NCEP (2005) R. A. Brown 2005 EGU

  4. Geostrophic Wind VG=P / ( f ) The nonlinear Ekman layer mean wind Mid- PBL V = P / ( f) - Fviscous Geostrophic Wind direction 25° (Stable strat.) 18° (neutral stratification) Surface wind 5° (Unstable strat.) -10° to 40° (Thermal Wind Effect) R. A. Brown 2003 U. ConcepciÓn

  5. The Dinosaur Cartoon (next slide) This Gary Larson cartoon struck me for some reason, probably because it is very close to how I feel these days, simply changing a couple of words. R. A. Brown 2005 EGU; Lidar Mt. Hood

  6. The dinosaur lecturer says: The picture’s pretty bleak, Gentlemen…..the world’s climates are changing, the mammals are taking over, and we have a brain about the size of a walnut. R. A. Brown 2005; EGU Lidar Mt. Hood

  7. The analytic PBL modeller says: The picture’s pretty bleak, Gentlemen…..the world’s climates are changing, the numerical modellers are taking over, and we have a brain about the size of a coconut. R. A. Brown 2005 EGU; Lidar Mt. Hood

  8. The dinosaurs successfully morphed into birds, and I successfully morphed into a satellite remote sensing specialist. R. A. Brown 2005 EGU; Lidar Mt. Hood

  9. Surface Pressures from Space 1. The indirect model connects surface winds to gradient winds and hence to surface pressure gradients through the PBL model (analytically) 2. The Direct Pressure Model Function, (PMF) connects scatterometer backscatter to NCEP surface pressure gradient directly (empirically) R. A. Brown 2004

  10. The nonlinear solution applied to satellite surface winds yields accurate surface pressure fields when compared to numerical models. These results show: * Agreement between satellite and ECMWF pressure fields indicate that both Scatterometer winds and the nonlinear PBL model (VG/U10) are accurate within  2 m/s. * A 3-month, zonally averaged offset angle <VG, U10> of 19° from scatterometer data suggests the mean PBL state is near neutral (the angle predicted by the nonlinear PBL model). * Swath deviation angle observations successfully infer thermal wind and stratification. * When pressure gradients are used as surface truth (rather than GCM or buoy winds) higher winds are obtained . * VG (pressure gradients) rather than U10 could be used to initialize GCMs R. A. Brown 2005 EGU

  11. R. A. Brown 2004 EGU

  12. Surface Pressures QuikScat analysis ECMWF analysis J. Patoux & R. A. Brown

  13. Surface Pressures: verification & applications Note: A special tropical PBL is patched at the equator R. A. Brown 2004

  14. Applications Better Storms Definition Dealiasing wind direction with SeaWinds Better GCM Progs (initialization with P) Higher Winds (& heat fluxes) in Climate models Evolution of Fronts & Cyclones R. A. Brown 2004 WRAGU

  15. (JPL) Raw scatterometer winds UW Pressure field smoothed JPL Project Local GCM nudge; smoothed (with ECMWF fields) = Dirth R. A. Brown 2005 EGU

  16. Producing smooth wind fields Gap from rain Direction information is poor R. A. Brown 2003 U. ConcepciÓn

  17. The quikScat scatterometer real-time data is currently being used at NCEP in the forecasters' display as surface pressure fields. They are more comfortable with these than wind fields — it is more compatible with other data. R. A. Brown 2005 EGU; Lidar Mt. Hood

  18. Dashed: ECMWF R. A. Brown 2005 EGU

  19. The application of scatterometer data to storms and frontal development using divergence and pressure fields R. A. Brown, J. Patoux R. A. Brown 2005 EGU

  20. Programs and Fields available onhttp://pbl.atmos.washington.eduQuestionsto rabrown, neal or jerome@atmos.washington.edu • Direct PBL model: PBL_LIB. (’75 -’00) An analytic solution for the PBL flow with rolls, U(z) = f( P, To , Ta , ) • The Inverse PBL model: Takes U10 field and calculates surface pressure field P (U10 , To , Ta , ) (1986 - 2000) • Pressure fields directly from the PMF: P (o) along all swaths (exclude 0 -  5° lat.?) (2001) (dropped in favor of I-PBL) • Global swath pressure fields for QuikScat swaths (with global I-PBL model) (2004) • Surface stress fields from PBL_LIB corrected for stratification effects along all swaths (2005) R. A. Brown 2005 EGU

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