Current Icing Potential: Algorithm Description and Comparison with Aircraft Observations

Abstract The “current icing potential” (CIP) algorithm combines satellite, radar, surface, lightning, and pilot-report observations with model output to create a detailed three-dimensional hourly diagnosis of the potential for the existence of icing and supercooled large droplets. It uses a physically based situational approach that is derived from basic and applied cloud physics, combined with forecaster and onboard flight experience from field programs. Both fuzzy logic and decision-tree logic are applied in this context. CIP determines the locations of clouds and precipitation and then estimates the potential for the presence of supercooled liquid water and supercooled large droplets within a given airspace. First developed in the winter of 1997/98, CIP became an operational National Weather Service and Federal Aviation Administration product in 2002, providing real-time diagnoses that allow users to make route-specific decisions to avoid potentially hazardous icing. The CIP algorithm, its individual c...

[1]  A. Glazer,et al.  An Improved Modeling Scheme for Freezing Precipitation Forecasts , 2000 .

[2]  R. Rasmussen,et al.  Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model , 1998 .

[3]  G. Isaac,et al.  Aircraft Icing Measurements in East Coast Winter Storms , 1995 .

[4]  A. Tafferner,et al.  ADWICE: Advanced Diagnosis and Warning System for Aircraft Icing Environments , 2003 .

[5]  R. Rogers,et al.  A short course in cloud physics , 1976 .

[6]  G. Isaac,et al.  An Example of Supercooled Drizzle Drops Formed through a Collision-Coalescence Process , 1996 .

[7]  George A. Isaac,et al.  Characterizations of Aircraft Icing Environments that Include Supercooled Large Drops , 2001 .

[8]  Wayne Sand,et al.  Icing Conditions Encountered by a Research Aircraft , 1984 .

[9]  George G. Koenig,et al.  Overview of Mount Washington Icing Sensors Project , 2000 .

[10]  C. G. Wade A Multisensor Approach to Detecting Drizzle on ASOS , 2003 .

[11]  Thomas F. Lee,et al.  Derivation and Applications of Near-Infrared Cloud Reflectances from GOES-8 and GOES-9 , 1998 .

[12]  M. Ramamurthy,et al.  The Relative Importance of Warm Rain and Melting Processes in Freezing Precipitation Events , 2000 .

[13]  Thomas P. Ratvasky,et al.  NASA/FAA/NCAR Supercooled Large Droplet Icing Flight Research: Summary of Winter 1996-1997 Flight Operations , 1998 .

[14]  B. Bernstein,et al.  Production and Depletion of Supercooled Liquid Water in a Colorado Winter Storm , 1995 .

[15]  R. Stewart,et al.  The Mesoscale and Microscale Structure of a Severe Ice Pellet Storm , 1995 .

[16]  Ben C. Bernstein,et al.  Meteorological Conditions Associated with the ATR72 Aircraft Accident near Roselawn, Indiana, on 31 October 1994 , 1997 .

[17]  Barry E. Schwartz,et al.  An Hourly Assimilation–Forecast Cycle: The RUC , 2004 .

[18]  Marcia K. Politovich,et al.  Conditions associated with large-drop regions , 1994 .

[19]  H. Guan,et al.  Verification of Supercooled Cloud Water Forecasts with In Situ Aircraft Measurements , 2001 .

[20]  Roy Rasmussen,et al.  Winter Icing and Storms Project (WISP). , 1992 .

[21]  Linda S. Wharton,et al.  Comparing PIREPs with NAWAU Turbulence and Icing Forecasts: Issues and Results , 1996 .

[22]  Barbara G. Brown,et al.  Intercomparison of In-Flight Icing Algorithms. Part II: Statistical Verification Results , 1997 .

[23]  F. Joseph Turk,et al.  Stratus and Fog Products Using GOES-8–9 3.9-μm Data , 1997 .

[24]  Gregory Thompson,et al.  Using Satellite Data to Reduce Spatial Extent of Diagnosed Icing , 1997 .

[25]  Sergey Y. Matrosov,et al.  Identification of Hydrometeors with Elliptical and Linear Polarization Ka-Band Radar , 1997 .

[26]  Alexander V. Ryzhkov,et al.  Cloud Microphysics Retrieval Using S-Band Dual-Polarization Radar Measurements , 1999 .

[27]  A. Korolev,et al.  Microphysical characterization of mixed‐phase clouds , 2003 .

[28]  Marcia K. Politovich,et al.  Toward the Improvement of Aircraft-Icing Forecasts for the Continental United States , 1992 .

[29]  William L. Woodley,et al.  Deep convective clouds with sustained supercooled liquid water down to -37.5 °C , 2000, Nature.

[30]  Jean-Marie Carrière,et al.  Statistical verification of forecast icing risk indices , 1997 .

[31]  B. Bernstein,et al.  The Relationship between Aircraft Icing and Synoptic-Scale Weather Conditions , 1997 .

[32]  R. Rasmussen,et al.  The 1990 Valentine's Day Arctic Outbreak. Part I: Mesoscale and Microscale Structure and Evolution of a Colorado Front Range Shallow Upslope Cloud , 1995 .

[33]  Christine Le Bot SIGMA : System of Icing Geographic identification in Meteorology for Aviation , 2003 .

[34]  R. Rasmussen,et al.  Sensitivity of freezing drizzle formation in stably stratified clouds to ice processes , 2005 .

[35]  Kevin W. Manning,et al.  Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part I: Description and Sensitivity Analysis , 2004 .

[36]  B. Brown,et al.  Intercomparison of In-Flight Icing Algorithms. Part I: WISP94 Real-Time Icing Prediction and Evaluation Program , 1997 .