For the past two decades RAL scientists have worked to improve diagnoses and forecasts of icing conditions that impact aviation. Our largest program is the FAA's Aviation Weather Research Program, which is focused on providing operationally-available, automated in-flight icing forecasts over the CONUS and Alaska. At this time, the Current and Forecast Icing Products (CIP and FIP), developed at RAL, are running at the National Weather Service's Aviation Weather Center (AWC) and are approved for unrestricted supplementary use. The outputs include expected icing severity, probability of encounter, and potential for supercooled large drop (SLD, those drops with diameters exceeding 50 microns) at 20-km resolution over the CONUS for 0-12 h. A new version with 13-km resolution has been delivered and is being tested at AWC.
In 2013 RAL continued work on these projects within the FAA program: 1) MICRO (Model for Icing Conditions in Real-time Operations), which will incorporate a high-resolution NWP model and improved use of sensor data to output the full drop size distribution (DSD) for icing prediction and severity calculations, 2) IPA (Icing Product-Alaska) which will revise CIP and FIP for the Alaska weather and data environments, and 3) evaluations of improvements to icing diagnosis using NEXRAD dual-polarization data.
Preliminary studies of the Icing Hazard Level Algorithm (developed in 2012) applied to NEXRAD dual-polarization data show very favorable results. Versions of the IHLA with and without the dual-pol data were compared with pilot reports of inflight icing conditions.
This image shows from left to right: 0.5o reflectivity from KCLE (Cleveland, OH NEXRAD); corresponding IHLA product with dual-polarization; IHLA with a new supercooled liquid water module; and without the module. For algorithm output, red and brown indicate likely icing, green is possible, and blue is no icing. The pink cross is a pilot report of mixed icing near the radar image altitude; the dual-polarized version of the algorithm correctly diagnosed icing conditions while the non-polarized versions did not. NCAR has also been working with NSSL on a winter hydrometeor classification algorithm pertinent to aviation hazards; the new output fields should be included in test versions of NSSL’s Multi-Radar-Multi-Sensor mosaic in early CY2014.
A draft Concept of Operations was completed for MICRO, describing the planned outputs and their intended use by pilots, dispatchers and meteorologists. This was written in conjunction with FAA and their support staff, and input from the FAA’s Icing Steering Committee was particularly helpful in defining the end use of the products and how they fit into current and future regulations. Additionally, NCAR staff worked with FAA, NASA, NOAA, and private industry representatives on an InFlight Icing Research Evolution Plan to define a pathway from basic research to implementation and use of icing products.
The High Ice Water Content (HIWC) project conducted a Real Time Nowcasting Experiment (RTNE) in Darwin, Australia in spring 2013. Staff travelled to Darwin to install their ALPHA (Algorithm for Prediction of High Ice Water Content (HIWC) Areas) workstation and collaborate with Australian Bureau of Meteorology staff to forecast HIWC conditions in the area. The RTNE was a “dress rehearsal” for a larger experiment, with a research aircraft, scheduled for spring 2014. ALPHA will be part of the flight planning process to guide the aircraft into HIWC regions to sample their microphysical characteristics and effect on engine performance. During the RTNE, internet connections were thoroughly tested, data set availability was determined, and a good collaboration with BOM meteorologists was established, all which will increase the chances of success of the 2014 field campaign. The ALPHA concept uses NWP output combined with satellite and radar data to diagnose cold cloud tops, warm atmosphere (compared to a standard sounding), high radar reflectivity below typical flight cruise altitudes, and other factors to determine regions conducive to the HIWC hazard.
The Terminal-Area Icing Weather Information System (TAIWIS) focused on defining user requirements for icing information in the airport terminal area. This somewhat arduous task was needed to insure that research and development activities truly addressed the needs of the community. Two reports were generated: one described current capabilities in icing detection, diagnosis and forecasting applicable for the terminal area; the other presented a high-level description of a TAIWIS incorporating elements from WSDDM (Weather Support for Deicing Decision Making), NIRSS (NASA Icing Remote Sensing System) and MICRO (Model for icing Conditions in Real-time Operations).
The NASA Icing Remote Sensing System (NIRSS) is being converted from a upward-looking system to a scanning system, providing potential support for an airport terminal area. Preliminary data processing was accomplished to determine how to apply the vertically pointing-based algorithms to different elevation angles, and how best to display the data. NIRSS has also been incorporated into the dual-polarization studies to help developers better understand the icing environment and include new features in the icing detection algorithm.
In 2014 we will continue to upgrade our automated icing algorithms to use higher resolution numerical weather prediction model and observational data, and to better interpret those data in terms of their effect on the diagnosed and predicted icing environment.
TAIWIS will conduct a small experiment at Denver International Airport to assess the variability of snowfall rate across the airfield. Five shielded snowgauges will be deployed and data will be collected at 1-min intervals. Deicing “holdover times” are usually determined by a single measurement at the airfield; if this varies considerably safety could be compromised as higher snowfall rates cause deicing fluids to fail more quickly. Variability in surface winds and in radar reflectivity aloft will also be analyzed to evaluate whether these could be used as predictors for snowfall rate variability at the surface.
Modules to use dual-polarization NEXRAD to detect high Zdr bands within precipitation and to detect negative Zdr in graupel will be tested and implemented in the upcoming year to augment our radar-based icing detection algorithm. There is also the possibility of a research flight campaign in 2014-2015 in the Great Lakes Region to further test the ground based remote sensing algorithms discussed within.
Our work on a Global Forecast Icing Severity (GFIS) algorithm will resume in FY2014 in collaboration with NCEP’s Meteorological Development Laboratory. The GFIS is scheduled for implementation and testing at NCEP in early CY2014.