1. Profiling Clouds with Satellite Imager Data and Potential Applications William L. Smith Jr. 1, Douglas A. Spangenberg 2, Cecilia Fleeger 2, Patrick Minnis 1, Mandana Khaiyer 2 1 Science Directorate, NASA LaRC, Hampton, VA 2 SSAI, Inc., Hampton, VA Background Accurate cloud characterizations are needed for weather and climate applications. Satellite cloud retrievals (e.g.cloud top height, CTH; cloud base height, CBH; ice & liquid water path, IWP & LWP) are not being used advantageously. Objectives Develop a cloud water content profiling technique for application to satellite imager cloud retrievals of all cloud types Use method to resolve the Aircraft Icing Potential in deep cloud systems (e.g. winter storms and convection) Validate method (i.e. ice and liquid water content profiles, icing potential) with active sensor retrievals and in situ aircraft observations in single-layer, optically thick ice over water clouds Summary Satellite imager cloud retrievals combined with empirical characterizations of cloud vertical structure from NWP and active sensors provide an unprecedented resolution of clouds for: 1. Weather applications: 4-D cloud properties for nowcasting and assimilation and improved diagnoses of aircraft icing potential 2. Climate applications: Improved global estimates of cloud water budgets and radiative impacts Real-time satellite imager cloud retrievals constrain the vertical distribution of cloud water High resolution cloud properties from satellite imagers The total water path (TWP) is estimated empirically from the satellite cloud retrievals for ice over water clouds. TWP parameterization based on correlations between GOES cloud properties and ARM MICROBASE (Radar/MWR) TWP estimates Note that TWP nearly twice as large as satellite IWP for densest clouds GOES Cloud Analysis 26 Feb 2013 (1745 UTC) Cloud top information currently used in operations but more information is available Daytime optical depth retrievals provide information on cloud mass (total water path) and thickness Assumes single-layer but multi-layer info and retrievals are also available (future work) GOES IWP (gm -2 ) TWP (gm -2 ) TWP Parameterization Example for R e =40 μm * SLIOW clouds Relationships describing the typical vertical distribution of total cloud water content (TWC) as a function of cloud top temperature (T t ) and total water path (TWP) Novel applications for cloud profiling method Cloud vertical structure information from NWP, CloudSat and CALIPSO data are assessed climatologically and employed in a satellite imager profiling method Cloud vertical structure information from NWP, CloudSat and CALIPSO data are assessed climatologically and employed in a satellite imager profiling method Temperature (K) SLW Mass Fraction (%) TWP <= 50 gm -2 50-200 200-500 1000-2000 500-1000 2000-3000 3000-4000 TWP > 4000 gm -2 Temperature (K) SLW Probability (%) Relationships to partition liquid from ice in mixed phase clouds (from NOAA RUC) Example for clouds with tops < 233K 245 <= T t < 253 K Normalized TWC 253 <= T t < 263 K Normalized TWC 263 <= T t < 273 K Normalized TWC T t >= 273 K Normalized TWC 225 <= T t < 230 K Normalized TWC 230 <= T t < 235 K Normalized TWC 235 <= T t < 240 K Normalized TWC 240 <= T t < 245 K Normalized TWC T t < 220 K Normalized TWC 220 <= T t < 225 K Normalized TWC TWP Normalized TWC profiles derived from the NOAA Rapid Update Cycle (RUC). Similar functions are derived from CloudSat/CALIPSO data (not shown). These information are constrained with satellite imager retrievals of TWP and cloud boundaries to derive ice and liquid water content profiles at the pixel resolution of the imager. Validation High Res 4-D Clouds from GEO Pilot Reports Improved Resolution of Aircraft Icing Conditions GOES-13 Icing Analysis Probability Profiling method provides estimates of SLW probability and LWC (icing conditions) in overlapping clouds Combined with Smith et al (2012) method to determine icing threat in all cloud types Accuracy in winter storm clouds similar to low cloud method Compared to satellite observations, cloud water path in NWP only accurate on scales of ~ 10 2 km Improved Global Estimates of Cloud IWP and LWP The global distribution of CWP is not well known  CMIP5 models show factor of 4 differences  No consensus from observations »CloudSat+CALIPSO good for IWC/IWP in upper troposphere »Microwave good for LWP (oceans only) »Not much available in mixed phase regime »Remote sensing retrievals highly uncertain in overlapping and precipitating conditions  Profiling method provides »Consensus between active sensor and imager IWP »Consensus between imager and microwave LWP »Consistency over land and ocean »Largest uncertainty due to ML clouds? Backups CERES Ed4 MODIS IWP (April 2013) CERES Ed4 MODIS LWP (April 2013) Profile method minus CERES IWP Profile method minus CERES LWP Profiling method helps to overcome poor assumptions in standard methods (e.g. CERES Ed4) (i.e. accounts for mixed phase in overlapping clouds) GOES IWC Validation with Aircraft Data NASA SEAC4RS Campaign DC-8 2D-S probe GOES-13 DC-8 Altitude DC-8 2D-S probe GOES-13 Sept 13 2013 Sept 21 2013 GOES IWC tracks Aircraft in-situ during ascents and descents thru thick clouds MODIS IWC and IWP Comparison with CloudSat+CALIPSO IWC (g/m 3 ) IWP (g/m 2 ) Assessed at altitudes above -20C level Monthly Means stratified by MODIS COD IWC (g/m 3 ) IWP (g/m 3 ) COD BIN CALIPSO+Clo udSat MODISBIASN 10-200.0510.047-8%5083 20-400.0870.083-5%4149 40-800.1540.1615%2635 80-1500.2970.3259%730 1500.5680.480-15%965 ALL0.1410.1431%13562 COD BIN CALIPSO+Cl oudSat MODISBIASN 10-20191169-12%5083 20-40333324-3%4149 40-8066876715%2635 80-1501231150722%730 150254926885%965 ALL5515836%13562 GOES Icing (SLW) Validation Icing Detection Icing Intensity (Light vs MOG) Icing PIREPS corroborate icing diagnosis capability from satellite Jan-Mar 2013, CONUS LWP difference expressed as a fraction of the TWP GOES Cloud Optical Depth LWP Difference (%) GOES Cloud Optical Depth LWP (gm -2 ) x – GOES embedded LWP - ARM MWR relationship GOES LWP Validation GOES retrieval matches MWR observations w.r.t retrieved COD Suggests NWP cloud phase partitioning is pretty good Single-layer ice over water clouds Contact: william.L.smith@nasa.gov