J11.6
Diagnosing Cumulus Cloud Updraft Characteristics and Inferring In-Cloud Parameters using 1-min GOES Observations

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Wednesday, 7 January 2015: 9:45 AM
230 (Phoenix Convention Center - West and North Buildings)
John Mecikalski, University of Alabama, Huntsville, AL; and C. P. Jewett and J. Apke

Since 2012, periodic collections of 1-min resolution super rapid scan operations for GOES-R (SRSOR) GOES-14 observations were recorded for significant weather events over the U.S. The goal of this study is to evaluate the sensitivity of the 1-min SRSOR observations of growing cumulus clouds, specifically, to determine what components of the cumulus processes occurring do these data describe. Since these SRSOR data are collected by GOES-14 at 4 km resolution in the infrared, questions arise as to the character of the signatures of cumulus cloud growth that would be expected to be seen, specifically when one examines the vertical momentum equation appropriate for moist convection. Such signatures include updraft acceleration and momentum transport as a function of the instability profile, hydrometeor loading, and latent heat release.

A total of 71 separate updrafts were collected on five dates and regions in 2012, 2013 and 2014. Cloud top temperatures (TBs) in the 10.7-µm “window” channel were cataloged as cumulus clouds evolved from the “fair weather” stage to mature cumulonimbus, or a cloud that eventually possessed a new anvil. GOES 3.9 µm channel derived reflectance (ref39) were also available every 1-minute in SRSOR. The ref39 data are used to infer cloud top glaciation, whereas reflectance values falling to below ~9% when 10.7 µm cloud top TBs are <273 K are highly correlated with the transition of cloud water particles to ice crystals (Lindsey et al. 2006). Lastly, proximity soundings of temperature, dew point, mixing ratio and of estimated convective available potential energy (CAPE) were collected from 13 km resolution NOAA Rapid Refresh (RAP) model 0000 hour analysis grids. An analyzed level of free convection (LFC) from the RAP model was used in the computation of CAPE. The profile of CAPE was first used to compute the incremental amount of CAPE (δCAPE) an updraft was penetrating through (or using) for each 1-min of cloud growth. For each updraft, a 1-min vertical motion (w, ms-1) was computed by simply noting the change in geometric height (using the RAP profile) of the updraft every 1 minute, assuming that cloud top TB is approximately the parcel temperature at cloud top (as typical for optically thick clouds), and that the parcel follows a moist adiabat. Note that the δCAPE and incremental w estimates (δw) are independent of one another, in that no information on the CAPE profile was used to determine w.

Results have shown that the correlations between δCAPE and δw often exceed 0.80, leading to the conclusion that the SRSOR observations are observing aspects of cumulus clouds which have rarely been seen by geostationary satellites (with the possible exceptions being from early 3-min observations from GOES, pre-1980, and in 2013 data collections of 2.5 min data from Meteosat Second Generation). Evidence is shown on how updrafts grow, in general, with respect to the capping inversion, the freezing level, and the equilibrium level as anvils form. Given the results, discussion is provided as to how such information can be used within products that diagnose and nowcast near-term convective storm initiation as early as possible, future storm intensity, and lightning characteristics of convective clouds.