5.13 NOWCASTING AIRPORT WINTER WEATHER: AVISA TESTS DURING AIRS

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1 5.13 NOWCASTING AIRPORT WINTER WEATHER: AVISA TESTS DURING AIRS George A. Isaac* 1, Stewart Cober 1, Norman Donaldson 1, Norbert Driedger 1, Anna Glazer 1, Ismail Gultepe 1, David Hudak 1, Alexei Korolev 1, Janti Reid 1, Peter Rodriguez 1, J. Walter Strapp 1 and Frederic Fabry 2 1 Environment Canada, Toronto, Ontario, M3H 5T4, Canada 2 McGill University, Montreal, Quebec, H3A 2K6, Canada 1. Introduction Air traffic at airports can be considerably disrupted during winter weather such as a snowstorm and freezing precipitation. De-icing operations must commence, the total amount of traffic the airport can handle is often reduced, and delays and flight cancellations are common. Inflight icing is also a problem for aircraft on approach or taking off. MSC is developing a Nowcasting system to help provide decision makers (airport authorities, airline dispatch, ground de-icing crews, pilots, etc) with real-time, accurate, and up-to-date weather information to help alleviate the problems and to increase safety. The system is currently called the Airport Vicinity Icing and Snow Advisor (AVISA). This system uses numerical model data, pilot reports, ground sensor data (precipitation, ceiling, visibility, winds, etc) as well as remote sensing (satellite, radar, radiometer) information to provide the necessary Nowcasts out to approximately 6 hours. The limitations and strengths of some of the component inputs (e.g. model data, radar, radiometric, precipitation rate) will be presented here using experiences from the Alliance Icing Research Study II (AIRS2) which was conducted in the Ottawa-Mirabel area from 3 November 2003 to 12 February This project involved 5 research aircraft and several airport Nowcasting systems which were installed at Mirabel. Plans for future work will also be described including the difficulties associated with designing the system products, and implementing it operationally. 2. Alliance Icing Research Study II (AIRS II) The field phase of the Second Alliance Icing Research Study (AIRS II) was conducted during *Corresponding author address: George A. Isaac, Environment Canada, 4905 Dufferin Street, Toronto, Ontario, M3H 5T4, Canada; george.isaac@ec.gc.ca. the winter of 2003/2004 (see Isaac et al., 2005). AIRS II is a project endorsed by the Aircraft Icing Research Alliance (AIRA), which consists of government organizations interested in aircraft icing. It is also being supported by the World Meteorological Organization (WMO) World Weather Research Program (WWRP) project on Aircraft In-Flight Icing. The First Alliance Icing Research Study (Isaac et al., 2001a) occurred during December 1999 to February 2000 in the same area. This project used 3 aircraft stationed out of Ottawa and remote sensing hardware located at both Ottawa and Mirabel (see to investigate the remote sensing of aircraft icing and other aircraft icing issues. AIRS II, which builds on the results of AIRS I and previous icing studies (Isaac et al., 2001b), has operational objectives to: a) develop techniques/systems to remotely detect, diagnose and forecast hazardous winter conditions at airports, b) improve weather forecasts of aircraft icing conditions, c) better characterize the aircraft-icing environment and d) improve our understanding of the icing process and its effect on aircraft. In order to support the operational objectives, the following science objectives will be addressed to: a) investigate the conditions associated with supercooled large drop formation, b) determine conditions governing cloud glaciation, c) document the spatial distribution of ice crystals and supercooled water and the conditions under which they co-exist, and d) verify the response of remote sensors to various cloud particles, and determine how this can be exploited to remotely determine cloud composition. Five research aircraft were involved in the field project. The National Research Council Convair- 580 and the NASA Glenn Research Center Twin Otter operated out of Ottawa, Ontario, the National Science Foundation C-130 from the National Center

2 for Atmospheric Research (NCAR) operated out of Cleveland, Ohio, and the NASA ER-2 and the University of North Dakota Citation operated out of Bangor, Maine. These aircraft flew special flight operations over a network of ground in-situ and remote-sensing meteorological measurement systems, located at Mirabel. Data were collected to evaluate some prototype airport weather forecasting systems, which use satellite and surface-based remote sensors, PIREPS, and numerical forecast models. They include the Airport Vicinity Icing and Snow Advisor (AVISA) being developed at the Meteorological Service of Canada, the Icing Remote Sensing System (NIRSS) from NASA (Reehorst et al., 2005), and the Ground-based Remote Icing Detection System (GRIDS: Reinking et al., 2001 and Schneider et al., 2005) being developed by the National Oceanic and Atmospheric Administration. The aircraft also provided data to verify remote-sensing algorithms used to detect icing conditions. The project results will also be used in North America and Europe to further develop numerical forecast models, and forecast systems, which predict aircraft icing over large areas. 3. Airport Vicinity Icing and Snow Advisor (AVISA) The input parameters of AVISA are schematically shown in Fig. 1. Basically, model data, vertically pointing radar data, satellite data, microwave radiometer data, and surface observations are integrated into a system which can produce short term forecasts. Also included as input data are the scans from the local weather radar, pilot reports, AMDAR data where available, etc. As mentioned above, the system was tested out during AIRS II, and sample products were produced, some of which are described below. The numerical forecast models used during AIRS II have been described by Glazer and Isaac (2004). Basically, they consisted of the Canadian Meteorological Centre (CMC) Global Environmental Multiscale (GEM) model (Côté et al., 1998) run at 24 km resolution, and the High Resolution Model Application Project (HIMAP) version of the GEM model run at 10 km resolution. The mixed-phase cloud scheme of Tremblay and Glazer (2000) was used in HIMAP to forecast the occurrence of Supercooled Liquid Water (SLW). Figure 2 shows how AVISA diagnoses whether supercooled liquid water is being observed above the site. This is a rule-based approach involving satellite data (cloud top temperatures and heights), surface data (precipitation, ceiling, surface temperature), microwave radiometer data (liquid water), and model temperature data. All the current algorithms used in AVISA are rule-based, but the system is being built to allow other methods (fuzzy logic, etc) to make and improve forecasts. Figure 3 (top panel) shows how AVISA might predict precipitation at an airport site using the various sensors available. The bottom panel of Figure 3 shows how the forecasts were verified for this all-snow case. The Precipitation Occurrence Sensor System (POSS) and the Hot Plate precipitation gauge have been described by Sheppard (1990) and Rasmussen et al. (2002) respectively. Figure 4 (top panel) shows how liquid water was observed and then forecast above the site using model data. The bottom panel of Figure 4 shows the verification for this case. It should be noted that the radiometer observations are not reliable when rain is occurring at the site. The various windows get wet resulting in erroneous readings for liquid water content measurements. For this case on 6 February, it was snowing at the site and the radiometers were functioning well. Figure 5 shows some aircraft measurements during the case of 6 February. Moderate to severe icing was reported by the pilots of the Convair-580 when the aircraft was above the airport. Most of the droplets were of small size so that the percentage of spherical particles as seen by the PMS 2D probes was relatively small. However, the temperatures where supercooled liquid water was observed, and icing was occurring, was relatively cold (<-10 o C). Figure 6 shows the McGill Vertically pointing radar images (see Zawadzki et al., 2001) covering the same period on 6 February. The top panel shows a 12 hour time history of VPR reflectivities and velocities and the bottom panel shows the VPR particle typing product. The Convair-580 was over the airport site approximately between UTC. Mostly snow was identified by the particle type algorithm during this period and cloud top heights derived from the VPR echoes matched well with those from the GOES satellite over Mirabel. Figure 7 shows a sample AVISA product combining both spatial views and time history plots 2

3 of observations, model data and forecasts for 6 February at 20 UTC. The spatial view gives an impression of potential errors involved in tracking a simple time history for one point, and it gives an idea of what an aircraft can encounter on approach or takeoff from the airport. 4. Discussion The AIRS II project provided an excellent opportunity to collect data for development and verification of algorithms being used in AVISA. In addition, an evaluation was made of some new sensors such as the hot plates and the profiling radiometer. The ability of the models to predict parameters of interest to AVISA was also tested. The types of products now being tested for AVISA are prototypes only. It will be necessary to engage users and to optimize products that will be useful for their requirements. This step has not yet been done. Ultimately, AVISA will be turned into an all season HUB Forecast System for use at major airports. Although winter weather problems associated with icing and precipitation was a useful way to commence building an airport Nowcasting system, it is recognized that progress should be made on other problems associated with poor visibility, low ceilings, blowing snow, frost, wind shifts, thunderstorms and lightning, etc. 5. Acknowledgments Besides our own organizations, the authors wish to acknowledge the help and sponsorship of the following institutions within Canada and the U.S. For Canada, Transport Canada, the National Search and Rescue Secretariat, the Canadian Foundation for Climate and Atmospheric Sciences, the Natural Sciences and Engineering Research Council, the Defense Research Development Centre, and the Communication Research Centre contributed. For the U.S. the efforts and support of NASA, NOAA, FAA, NSF, NCAR, and the Desert Research Institute must be acknowledged. There were 25 different organizations involved in AIRS II from North America and Europe. 6. References Côté, J., J.G. Desmarais, S. Gravel, A. Méthot, A. Patoine, M. Roch and A. Staniforth, 1988: The operational CMC-NRB Global Environmental Multiscale (GEM) Model. Part 1: Design considerations and formulation. Mon. Wea. Rev., 126, Glazer, A., G.A. Isaac, 2004: Forecasting icing conditions during the Alliance Icing Research Study II with the Canadian Meteorological Centre Global environmental Multiscale Model. Proceedings 14th Intl. Conf. on Clouds and Precipitation, Bologna, July 2004, Isaac, G.A., S.G. Cober, J.W. Strapp, D. Hudak, T.P. Ratvasky, D.L. Marcotte, and F. Fabry 2001a: Preliminary results from the Alliance Icing Research Study (AIRS). AIAA 39th Aerospace Sci. Meeting and Exhibit, Reno Nevada, 8-11 January 2001, AIAA Isaac, G.A., S.G. Cober, J.W. Strapp, A.V. Korolev, A. Tremblay, and D.L. Marcotte, 2001b: Recent Canadian research on aircraft in-flight icing. Canadian Aeronautics and Space Journal, 47, Isaac, G.A., J.K. Ayers, M. Bailey, L. Bissonnette, B.C. Bernstein, S.G. Cober, N. Driedger, W.F.J. Evans, F. Fabry, A. Glazer, I. Gultepe, J. Hallett, D. Hudak, A.V. Korolev, D. Marcotte, P. Minnis, J. Murray, L. Nguyen, T.P. Ratvasky, A. Reehorst, J. Reid, P. Rodriguez, T. Schneider, B.E. Sheppard, J.W. Strapp, and M. Wolde, 2005: First results from the Alliance Icing Research Study II. AIAA 43rd Aerospace Sci. Meeting and Exhibit, Reno Nevada, January 2005, AIAA Rasmussen, R.M.,J. Hallett, R. Purcell, J. Cole, and M. Tryhane, 2002: The hot plate snowgauge 11 th AMS Conference on Cloud Physics, 3-7 June 2002, P1.6. Reehorst, A.L., D.J. Brinker and T. Ratvasky, 2005: NASA Icing Remote Sensing System comparisons from AIRS II. AIAA 43 rd Aerospace Sciences Meeting and Exhibit, Reno, NV, January 2005, Paper AIAA Reinking, R.F., R.A. Kropfli, S.Y. Matrosov, W.C. Campbell, M.J. Post, D.A. Hazen, J.S. Gibson, K.P. Moran and B.E. Martner, 2001: Concept and Design for a Pilot Demonstration Ground-Based Remote Icing Detection System. 30th International Conference on Radar Meteorology, Munich, Germany, July 2001, P5.2. Schneider, T.L., B.C. Bernstein and R.A. Reinking, 2005: Forecasting and ground-based remote icing 3

4 detection system (GRIDS): Documentation of the transition from a glaciated environment to an SLD icing environment. AIAA 43 rd Aerospace Sciences Meeting and Exhibit, Reno, NV, January 2005, Paper AIAA Sheppard, B.E., 1990: The measurement of raindrop size distributions using a small Doppler radar. J. Atmos. Oceanic Technol. 7, Tremblay, A. and A. Glazer, 2000: An improved modeling scheme for freezing precipitation forecasts. Mon. Wea Rev., 128, Zawadzki, I., F. Fabry and W. Szymer, 2001: Observations of supercooled water and secondary ice generation by a vertically pointing X-band Doppler radar. Atmos. Res., 59-60, Radiometers HIMAP & GEM Models AVISA Input Parameters GOES Satellite POSS, HP & Met Station Vertically Pointing Radar (VPR) Fig. 1: Airport Vicinity and Snow Advisor (AVISA) input parameters. 4

5 ARE SKIES CLEAR? NO YES SLW IS ASSUMED FALSE FOR ALL HEIGHTS DERIVE BEST GUESS CLOUD TOP DERIVE BEST GUESS CLOUD BASE IS THERE LIQUID PRECIPITATION? YES SLW IS INCONCLUSIVE NO IS THE RADIOMETER LWP > 0 mm AND GEM MODEL TEMP < 0ºC? YES SLW IS ASSUMED TRUE FOR THAT HEIGHT NO SLW IS ASSUMED FALSE AT THAT HEIGHT Fig. 2: Shows a rule-based algorithm for determining if supercooled liquid water (SLW) is above the site. Other methods for detecting and forecasting SLW include a GOES satellite icing detection algorithm, the GEM and HIMAP model data alone, and the Vertically Pointing Radar (VPR) liquid water content (LWC) and precipitation typing algorithms. For Supercooled Large Droplet (SLD) detection and forecasting, the VPR LWC and precipitation typing algorithms, and/or the POSS precipitation typing and surface observations can be used. 5

6 Precip Rate [mm/hr] HIMAP RR GEM RR Hot Plate 1 Hot Plate 2 POSS RR WMN Snow HIMAP RR - Future GEM RR - Future WMN Snow Pt Fcst Current Time: :00Z Precip Rate [mm/hr] Observed Data: :00Z to :00Z HIMAP RR GEM RR Hot Plate 1 Hot Plate 2 POSS RR WMN Snow Figure 3: The top panel shows a time history of precipitation rates from the models (HIMAP and GEM), the two Hot Plates, the Precipitation Occurrence Sensor System (POSS), and the McGill Weather Radar (WMN) up to the observation time of 19 UTC. After that time, the predictions of the models and the translated radar pattern are shown as short term predictions. The bottom panel shows the observations for the entire time period along with the model results. 6

7 Integrated Liquid Water [cm] Current Time: :00Z 0.10 HIMAP IC GEM IC 0.09 TP3000 Radiometer 0.08 WVR1100 Radiometer 0.07 HIMAP IC - Future 0.06 GEM IC - Future Integrated Liquid Water [cm] Observed Data: :00Z to :00Z HIMAP IC GEM IC 0.08 TP3000 Radiometer 0.07 WVR1100 Radiometer Figure 4: The top panel shows a time history of integrated liquid water path from the models (HIMAP and GEM), and the two radiometers up to the observation time of 19 UTC. After that time, only the predictions of the models are shown. The bottom panel shows the observations for the entire time period along with the model projections. 7

8 Altitude (km) Temperature Nevz IWC Nevz LWC 2D Sphere Frac 5 Aircraft Temp Sounding 1949Z HIMAP Temp Avg TPR Temp Avg HIMAP LWC Avg VPR LWC Avg TPR LWC Avg LWC [g/m3] and Sphere Particle Fraction LWC [g/m3] or [g/kg] for HIMAP Figure 5: The left panel shows profiles of LWC, IWC, spherical particle fraction and temperature as measured using the Convair-580 on 6 February 2004, along with soundings from the balloon, radiometer, and HIMAP model. The right panel shows averaged LWC profiles from the HIMAP model, VPR and profiling radiometer for the period when the aircraft was over Mirabel ( UTC). 8

9 Figure 6: The upper panel shows the VPR reflectivities (left) and velocities (right) for a 12 hour period covering the Convair-580 flight on 6 February ( UTC). The lower panel shows the VPR particle identification product for the same period. 9

10 February 6, UTC in the vicinity of YMX HIMAP Total Precipitation Rate and Radar HIMAP Supercooled LWP & GOES Icing 0.05 cm 0.2 mm/hr 0.03 cm 0.03 cm 0.6 mm/hr YMX > 1 mm/hr > 1 mm/hr YMX 20 km 0.05 cm GOES 2002 Precip Rate [mm/hr] Precipitation Observations & Forecast at YMX Current Time: :00Z 3.5 HIMAP RR 3.0 GEM RR Hot Plate Hot Plate POSS ZR POSS Snow Type 1.5 WMN Snow HIMAP RR - Future 1.0 GEM RR - Future 0.5 WMN Snow Pt Fcst Integrated Liquid Water [cm] LWP Observations & Forecast at YMX Current Time: :00Z HIMAP IC GEM IC TP3000 Radiometer WVR1100 Radiometer HIMAP IC - Future GEM IC - Future Figure 7: This shows a sample display combining the spatial views of radar, satellite and forecast model data near Mirabel with the time history plots of precipitation and LWP observations and predictions for 20 UTC on 6 February. The top left panel shows the McGill Observatory S-band precipitation rate estimates overlaid with the HIMAP model predictions for the same time period. The top right panel shows the satellite icing algorithm (yes for icing is indicated in grey) with the LWP predictions from HIMAP plotted on top. The bottom right and left panels are similar to Figures 3 and 5, except for 20 UTC on 6 February. 10