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Clear-sky dry bias and its implications in the cloud forcing determination

Clear-sky dry bias and its implications in the cloud forcing determination. B.J. Sohn Seoul National University, Seoul, Korea (with T. Nakajima and M. Satoh, Univ of Tokyo). Sohn (1999, JAS). ERBE. Slingo et al. (1998) Eq-20 ° , ocean only 1985-89 mean.

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Clear-sky dry bias and its implications in the cloud forcing determination

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  1. Clear-sky dry bias and its implications in the cloud forcing determination B.J. Sohn Seoul National University, Seoul, Korea (with T. Nakajima and M. Satoh, Univ of Tokyo)

  2. Sohn (1999, JAS) ERBE Slingo et al. (1998) Eq-20°, ocean only 1985-89 mean Simulated with ISCCP plus ECMWF w Definition of CRF CRF = Clear-sky OLR – All-sky OLR SST Allan and Ringer (2003)

  3. All Sky Cloud-free Sky T’(z), q’(z) T(z), q(z) -- drier Different definitions of the clear-sky flux Satellite cloud-free sky: OLR = f(T(z), q(z), ….) Model clear sky: OLR = f(T’(z), q’(z), ..) q(z), T(z)

  4. Determination of 'clear-sky' UTW from SSM/T2 UTWmea = a + bAl + cAm + dAh UTW: Integrated water vapor amount for 200-500 mb UTWmea: UTW measured (all-sky) UTWclr: clear-sky UTW a, b, c: regression coefficients Ah, Am, Al: high, middle, and low cloud amounts 1. 'ERBE-like' Clear-sky UTW: UTWclr = a, if Al=Am=Ah=0 2. All-sky UTW: UTWmea (representing all-sky condition)

  5. JJA 1997/98

  6. CERES CRF and Clear-Sky Flux Difference (a) CERES CRF (b) UTW forced CRF Sohn et al. (2005, J Clim)

  7. AMSR-E water vapor path measurements Sohn and Bennartz (2008, JGR)

  8. NCIAM Simulations (one month from Dec to Jan) All-sky TPW Cloud-free minus All-sky TPW All-sky UTH Cloud-free minus All-sky UTH

  9. Lapse rate = T(surface-500 hPa) – T(500 hPa-200 hPa) All-sky Cloud-free minus All-sky

  10. Clear-sky OLR and water-vapor contributed CRF Clear-sky OLR Cloud-free OLR minus Clear-sky OLR

  11. NICAM Simulations Satellite-suggested UTH only contribution to CRF (Sohn et al., 2005)

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