Deputatskaya st.1; e Institution of Russian Academy of Sciences Dorodnicyn Computing Centre of RAS, , Moscow, Russia, Vavilov st.

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1 Testing results of remote sensing method by using microwave temperature profiler for detection of icing conditions aloft in Novosibirsk and Tomsk International Airports Vladimir V. Zuev a,b,c, Daria P. Nakhtigalova a,d, Alexander P. Shelekhov a, Nikolay A. Baranov e a Institute of Monitoring of Climatic and Ecological Systems SB RAS, 63455, Tomsk, Akademichesky Ave., 1/3; b National Research Tomsk State University, 6345, Tomsk, Lenin Ave., 36; c National Research Tomsk Polytechnic University, 6345, Tomsk, Lenin ave., 3; d West Siberian Branch FSBI Aviamettelecom Roshydromet 6399, Novosibirsk, Deputatskaya st.1; e Institution of Russian Academy of Sciences Dorodnicyn Computing Centre of RAS, , Moscow, Russia, Vavilov st., 4 Testing results of remote sensing method by using microwave temperature profiler for detection of icing conditions aloft [1-3] in Novosibirsk and Tomsk International Airports are presented in the paper. Analysis of the results obtained during the field campaign at Novosibirsk and Tomsk International Airports shows that using Schultz and Politovich method and Minus 8D technique coupled with data of MTP- 5 profiler and AMIS-RF give similar results for detection of spatial areas of aircraft icing. Testing results of remote sensing method received using only Schultz and Politovich method completely agree with on-board weather data. Using MTP-5 together with data form AMIS-RF allows us for detection of the icing conditions aloft with high spatial and temporal resolution. For the Novosibirsk International Airport the maximum number of icing events is observed at a height from to 1 km. For the Tomsk International Airport the maximum number of icing events is at a height from 1 to 2 km. A significant number of events are also observed in a height layer from 1 to 2 km for both airports. With the increasing height icing phenomenon is less common and it is not recorded higher than 6 km. 1. Remote sensing theory Let us consider remote sensing method by using MTP-5 microwave temperature profiler for detection of icing conditions aloft [1-3]. In practice for detection of these conditions are used the approach based on the knowledge of the temperature and humidity of the ambient air and one effective way to forecast icing is the Schultz and Politovich method [4] or the Minus 8D technique [5]. a. Schultz and Politovich method It is shown [4] that the risk and severity of aircraft icing are extremely high if o z o 16 C T C, (1) z 63% R H, (2) where altitude. T z and z b. Minus 8D technique R H - are profiles of temperature and relative humidity respectively, z is In the case of the Minus 8D technique [5] conditions favorable for icing defined as follows

2 T z T zt z 8 d, (3) T d z is the profile of dew point temperature, D TzT z where d is the dew point depression. The Minus 8D technique is commonly used to forecast icing conditions aloft at the airports in the Russian Federation, including Novosibirsk and Tomsk International Airports. It is seen from equations (1) - (3) that the aircraft icing areas depend on the behavior of the temperature profile and humidity profile. We use MTP-5 microwave temperature profiler for measurements of temperature profile and data of Automatic Weather Observing System (AMIS- RF) for humidity profile retrieval. c. Humidity profile retrieval The relative humidity profile was retrieved through analytical extrapolation using data of AMIS-RF: surface value relative humidity and height of cloud base. The equation for retrieval of relative humidity profile R H z has the form [1-3] 1 R H, R z R, H, z z H H H (4) 1, in clouds where H, base. R is surface value of relative humidity, i.e. H RH, R, and H is height of a cloud Eq. 4 and the well-known formula [6] which relates dew point temperature with temperature and relative humidity allows us to retrieve T d z profile. As a result, the equation for retrieval of dew point temperature profile can be written in the form R ( z) A ( ) ln 1T z B H 1 1 B1 T( z) T ( z) d, (5) R ( z) A ( ) ln 1T z A H 1 1 B1 T ( z) where A and B C [6]. Eqs. 1 5 are the basic formulas for remote sensing method by using MTP-5 microwave temperature profiler for detection of icing conditions aloft [1-3]. 2. Testing results of remote sensing method Testing results of remote sensing method was carried out during the field campaign at Novosibirsk and Tomsk International Airports. In this paper we consider testing results of remote sensing method at Novosibirsk International Airport on 17 January 215 and at Tomsk International Airport on 17 March 213. a. Novosibirsk International Airport Icing intensity was varying from weak to strong within a kilometer layer during that day 17 January 215. Figure 1 shows testing results of remote sensing method by using the Schultz

3 and Politovich method and Minus 8D technique at Novosibirsk International Airport on 17 January 215. Green, yellow and red colors mark spatial areas of aircraft icing; white-colored areas are those where weather conditions do not result in icing. Red and yellow colors correspond to the spatial areas of aircraft icing in the clouds and in snow, respectively. Green color refers to spatial areas of icing to be encountered in the absence of significant weather conditions and in cloud free sky. Grey dashed lines mark spatial areas of actual aircraft icing obtained from on-board reports (pireps) during the study time period. Signs plus () and minus () represent calculations based on radiosonde data corresponding to aircraft icing and its absence, respectively a) Schultz and Politovich method b) Minus 8D technique Fig. 1. Testing results of remote sensing method at Novosibirsk International Airport on 17 January 215. b. Tomsk International Airport According to pireps 17 March 213, moderate icing existed on that day in clouds during the period from : to 2:3 UTC, in clouds at altitudes from 7 to 2 m during the period from 8:15 to 1: UTC, and in clouds and precipitation at altitudes from to 24 m during the period from 11:6 to 13: UTC. Figure 2 shows testing results of remote sensing method by using the Schultz and Politovich method and Minus 8D technique at Tomsk International Airport on 17 March 213.

4 a) Schultz and Politovich method b) Minus 8D technique Fig. 2. Testing results of remote sensing method at Tomsk International Airport on 17 March 213. c. Discussion It follows from Figures 1a and 2a testing results of remote sensing method are in agreement with on-board weather data for Novosibirsk and Tomsk International Airports. It is seen from Figure 1a, remote sensing data for Schultz and Politovich method and calculation results based on radiosonde data agree with each other. Also, calculation results based on the radiosonde data (. UTC) agree with on-board weather reports. For Novosibirsk and Tomsk International Airports remote sensing data by using Minus 8D technique (see: Figures 1b and 2b) show that they agree in part with on-board weather data. For example, the difference is observed during 3:38-5:37 UTC and 7:41-1:5 UTC at altitudes below 2 and 3 m for Novosibirsk International Airport. According to on-board weather data, weak icing is observed during that time period, and remote sensing data by using Minus 8D technique are showed that weather conditions did not lead to aircraft icing close to the surface. Also calculation results based on radiosonde data (. UTC) and Minus 8D technique partly agree with on-board weather data close to the surface. Thus analysis of the results obtained during the field campaign at Novosibirsk and Tomsk International Airports shows that using Schultz and Politovich method and Minus 8D technique coupled with data of MTP- 5 profiler and AMIS-RF give similar results for detection of spatial areas of aircraft icing. Testing results of remote sensing method received using only Schultz and Politovich method completely agree with on-board weather data. Using MTP-5 together with data form AMIS-RF allows us for detection of the icing conditions aloft with high spatial and temporal resolution. 3. Frequency distribution of icing pireps The frequency distributions of icing pireps as a function of altitude for Novosibirsk and Tomsk International Airports are presented at Figure 3. These frequency distributions are received by AMIS-RF data over the years

5 Percent Percent Novosibirsk International Airport Tomsk International Airport It is clear from Figure 3a that for the Novosibirsk International Airport the maximum number of icing events (34.7% of the total) is observed at a height from to 1 km. For the Tomsk International Airport the maximum number of icing events (37.5% of the total) is at a height from 1 to 2 km. A significant number of events are also observed in a height layer from 1 to 2 km for both airports. With the increasing height icing phenomenon is less common and it is not recorded higher than 6 km. Icing occurrence in Novosibirsk and Tomsk International Airports is significantly different from those in the continental United States [4] and from the results published in [5]. For example, we can see from [4] that icing is not actually observed in the layer from to 1.5 km. However, there is a maximum number of icing pireps at these heights for in International Novosibirsk and Tomsk Airports. In the continental US maximum of icing pireps is registered in a layer from 1.5 km to 4 km, while in International Tomsk and Novosibirsk airports only a few numbers of icing events are observed. References 1. Pat. of the Russian Federation , G1W 1/1, B64D 15/2. 2. Zuev V.V., Nakhtigalova D.P., Shelekhov A.P., Shelekhova E.A., Pavlinskii A.V., Baranov N.A., Kizhner L.I. Application of MTP-5PE meteorological temperature profiler in an airport for determining spatial zones of possible aircraft icing. Atmospheric and Oceanic Optics, 29(2), (216). 3. Zuev V. V., Nakhtigalova D. P., Shelekhov A. P., Shelekhova E. A., Baranov N. A., Kizhner L. I. Remote sensing of potential aircraft icing areas. Proc. of SPIE, 215. V P. 9686Q Schultz P., Politovich M.K., "Toward the Improvement of Aircraft-Icing Forecasts for the Continental United States," Wea. and Forecasting (1992). 5. Baranov A.M. and Solonin S.V., [Aeronautical Meterology], Gidrometeoizdat, Leningrad, (1981). 6. M. G. Lawrence, The relationship between relative humidity and the dewpoint temperature in moist air: A simple conversion and applications, Bull. Amer. Meteorol. Soc. 86 (2), (25).