An Evaluation of Cloud Microphysics and Radiation Calculations at the NSA Matthew D. Shupe a, David D. Turner b, Eli Mlawer c, Timothy Shippert d a CIRES.

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An Evaluation of Cloud Microphysics and Radiation Calculations at the NSA Matthew D. Shupe a, David D. Turner b, Eli Mlawer c, Timothy Shippert d a CIRES – University of Colorado and NOAA/ESRL, b University of Wisconsin, c Atmospheric and Environmental Research, Inc., d Pacific Northwest National Laboratory BBHRP Surface Radiative Closure Analysis Dependence on Cloud and Environment Properties “ShupeTurner” Cloud Properties Dataset [1-min, IWC/Rei, NSA for 3/2004 – 2/2005] Funded by: ARM Grant DE-FG02-05ER63965 Summary BBHRP Radiative Closure Analysis Cloud phase dependence and comparison with BNL Microbase Methods A Multi-Algorithm Collaboration Phase Classification – combines phase signatures from radar, lidar, radiosonde, and lwp Retrieval Classification – conditional based on phase type and measurement availability Liquid Retrievals – aeri+mwr or mwr+radar or adiabatic (radiosonde, radar, lidar) or climatology Ice Retrievals – radar+aeri or radar Cloud Phase Characteristics – Key Findings 1) Cloud ice occurs most of the time that clouds are present. 2) Liquid–containing clouds occur throughout the year with occurrence fractions greater than 20% in the winter. 3) Late summer cloud fractions are very high. 4) Low-level clouds of all types are most prevalent Microphysical Properties – Key Findings 1) Highest LWC and largest liquid droplets in summer 2) IWC is approx. 1 order of magnitude less than LWC, on average 3) Re_ice shows little annual variation. Key Findings 1)ShupeTurner shows significant, all around improvements (both StdDev and Bias) for cloud scenes containing liquid water. 2)Ice clouds show similar results (both are based on radar reflectivity). 3)SW TOA closure is better when clouds are present than under clear skies!? 4)Surface closure is usually better than TOA closure 5)Key discrepancies in cloud classification. ST identifies many cases as “mixed” that BNL calls “ice.” ST identifies more clear sky than BNL. Surface LW – Key Findings 1) StDev and Bias decrease as LWP increases. 2) Quality of radiative closure is not dependent on IWP. 3) StDev slightly decreases as T surf increases and as the total downwelling LW increases. 4) Quality of LW closure appears to be independent of cloud phase Surface SW– Key Findings 1) SW closure becomes worse as SZA decreases and insolation increases 2) SW closure appears to be insensitive to LWP and IWP 3) SW closure is better for ice clouds than for other cloud types * These statistics are at 20-min resolution. Phase class is for the full column. Comparison of Scene Identification # of occurrences ShupeTurner and BNL microphysics products are incorporated into the Broadband Heating Rate Profiles algorithm to compute radiative fluxes at the surface and TOA. These are compared with similar flux measurements to evaluate the quality of the microphysics products. Reasons for Improvement 1)Cloud classification (improved location of liquid) 2)LWP retrieval  A new “ShupeTurner” cloud microphysics product has been implemented for 1 year at the NSA site, and will soon be expanded to more years and sites  ShupeTurner shows improvement over BNL Microbase in terms of radiative closure, especially in liquid-containing cases.  Ice cloud cases are similar between ST and BNL products  Some issue other than cloud microphysics adversely affects the SW closure analyses (clear sky closure is no better than cloudy sky).  LW closure may be improved through further improvements to the characterization of low LWP clouds (StDev and Bias increase as LWP decreases). SW closure is great when there is no sun!