New Satellite Energy and Water Balance and Water Cycle Products for the Study of Interactions between Atmospheric Hydrology and the ERB T. S. L’Ecuyer ( email@example.com ) , G. L. Stephens ( firstname.lastname@example.org ) , and Z. Luo ( email@example.com ).
New Satellite Energy and Water Balance and Water Cycle Products for the Study of Interactions between Atmospheric Hydrology and the ERB
T. S. L’Ecuyer (firstname.lastname@example.org), G. L. Stephens (email@example.com),
and Z. Luo (firstname.lastname@example.org)
Science issue:The implications of cloud-induced changes in the vertical distribution of atmospheric radiative heating is not well understood due to a lack of accurate global QR(z) obs.
Approach: Combine cloud, precipitation, atmospheric, and surface property information from mutliple sensors to estimate profiles of LW and SW fluxes and heating rates
Satellite-based data: PMW and IR radiances from TRMM and the A-Train, CloudSat reflectivity profiles, CERES TOA fluxes, and AIRS T and q profiles
Study Particulars: QR(z) products covering the TRMM and A-Train eras at 0.25 degree spatial and daily time resolution
Left: September 2007 Arctic sea ice extent (courtesy NSIDC) illustrating the largest polar ice melt on record.
Below: 2007-2006 differences in cloud fraction (left) and corresponding modeled downwelling SW radiation averaged over the three months preceding the sea ice minimum in each year.
Estimates of surface radiative fluxes from A-Train obs. reveal that anomalously high SW heating at the surface may have contributed to the record Arctic ice sheet minimum observed in September 2007.
Kay et al, GRL (2008)
Year 1 (complete) – refined TRMM-based QR(z) estimates and apply first few years of data to examine radiative heating in IPCC-AR4 models (L’Ecuyer and Stephens, 2007)
Year 2 (nearly complete) – processing 10 year TRMM product and completing error (preparing manuscript for J. Climate special issue on diabatic heating); initial A-Train-based algorithm also nearing completion
Year 3 (plan) – analyze profiles of heating in GCMs and MMF in the context of large-scale circulations and known modes of atmospheric variability (eg. ENSO); generate and evaluate A-Train products
NEWS linkages: (pull, push, collaborate, external)
Fetzer – AIRS T and q profiles provide input to A-Train QR product
McFarlane/Dong – QR profiles from ARM sites to evaluate products and export regional information to global scales
Olson - analyze total diabatic heating from TRMM on various space/time scales
Analysis of vertical heating associated with MJO (Waliser)
Important component of TRMM LH intercomparison project
Integration with similar CloudSat product to improve vertical representation of clouds
Updated: April 10, 2008