Aviation Weather Hazards Nowcasting Based on Remote Temperature Sensing Data

Transcription

1 Aviation Weather Hazards Nowcasting Based on Remote Temperature Sensing Data Mikhail Kanevsky*, Evgeny Miller**, Nikolay Baranov*** *International Aeronavigation Systems, **RPO ATTEX, ***Dorodnicyn Computing Centre, FRC CSC RAS

2 2(30) In 2017 has been started the new project in Pulkovo (ULLI) for investigation of the Aviation Weather Hazards Nowcasting Based on Remote Temperature Sensing Data

3 Aviation Weather Hazards Nowcasting Based on Remote Temperature Sensing Data ensures automated temperature observations in the boundary layer of the atmosphere, as well as provision and visualization of observation data up to 10 km and automatic calculations for forecasts of the current weather phenomena and conditions at the airport, such as: 1) Fog probability, 2) Low altitude wind shear and wake vortex flight safety, 3) Probability of freezing precipitation, 4) Icing. San Francisco, USA, 2014 Enhancing the short-term forecasting system for the weather phenomena and conditions with the greatest impact on aviation operations represents an important endeavor for improvement of the air navigation meteorological support which contributes to the safe, efficient and regular aircraft flights. One way of developing nowcasting systems is to integrate the existing observation data and mesoscale highresolution models for the tasks of airport forecasting to support air traffic control during take-off/approach and airport service operations. This report describes a nowcasting subsystem based on an automated remote 3 temperature sensing and nowcasting complex using the microwave profiler (MTP-5).

4 1. Introduction 4(30)

5 5(30) Comparison of radiosonde sounding (black) and NWP model (red) profiles of temperature (solid lines) MWRnet - An International Network of Ground-based Microwave Radiometers Radiosonde-Measurements-White-Paper-B211548EN.pdf 1) Radiosonde Is limited for using in airport (not continuous) 2) MetroTower Is impossible in airport 3) Tethered Balloons Unavailable at airports 4) RASS is depend on weather condition and there are no data on the first 100m 5) MultiChannel padiometer No profile without radiosondes (pos.1)

6 6(30) 24/7

7 7(30) Boulder м Obninsk м Tsukuba и м

8 8(30) 25 years experience

9

10 10(30) Parma Italy 1995,1997 Zurich Swiss 2004 Pert Australia 2009 Begishevo Russia 2008 Rome Italy 2009 Bolzano Italy 2011 JFK USA 2012 Tomsk Russia 2012 NASA Memphis IA 2013 Sochi Russia 2014 Tolmachevo 2014 IANS 2015 SFO USA 2015 LAX USA 2015 Pulkovo (ULLI) 2017

11 The blending technology has been developed and implemented for aviation application through utilizing high-resolution weather forecast models and direct measurements in PBL by using MTP-5 data each 5 minutes. This technology ensures on-line temperature profiling with the data measurement height of up to 10 km and complete monitoring of the temperature dynamics in the troposphere. Moreover, the users have an opportunity to reliably assess the altitudes of typical isotherms that can be effectively used to identify meteorological phenomena in radar observations. 11(30) St-Petersburg Airport «Pulkovo» (ULLI) 2017

12 Example of the temperature field up to 10 km (with a part up to 1 km) resulting from blending MTP-5 data and GFS data measured on April 29-30, 2017, when advection was present, and, as a result, fog has been observed.

13 1) Fog probability, 2) Low altitude wind shear and wake vortex flight safety, 3) Probability of freezing precipitation, 4) Icing.

14 14(30)

15 The temperature profile determines the vertical transport of air masses, as well as the condensation of atmospheric water vapor. Knowledge of the temperature profile dynamics can provides early warning of developing and disappearance of fogs. The method based on MTP-5 technology is the only remote method that works reliably in conditions of fog. 15(30) Parma Italy 1995,1997 Rome Italy 2009 Bolzano Italy 2011 SFO USA 2015 LAX USA 2015 Diagram and photo of the MTP-5 installation in Pulkovo (ULLI) airport in March 17, To solve task of nowcasting, numerical models data (GFS) and meteorological data from Pulkovo meteorological station (METAR) have been applied. Data from the standard set of sensors (air temperature, humidity, wind, and etc.) provided by НМР155D (as a part of «KRAMS-4») have been used for calculations. The final solution for nowcasting taking account all sets of data has been implemented through using specialized software developed together with IANS Concern (

16 Temperature profiles for minimum visibility in fog Vis<0.3km :00 Vis<0.1km :30 Vis<0.8km 200m 50m To applying FSI with continues data (T-T850) has been changed to (T-T200) and W850 to Ft (2m). The analysis carried out on the available data series (16 days with events) showed that the short-term fog forecasting problem can be successfully solved through the complex using set of observation data: - the dynamics of the dewpoint depression (trend to and/or stand at a level close to 0), - data on temperature profiles sounding of PBL (dt[0-200m], dtinversion and height of the inversion base), - wind speed on 2m. By using these data set we have: - justifiability of up to 98%, - forecasting on a short term period of up to 5-9 hours for fog formation, - for dissipations the forecasting period was up to 2 hours. To ensure high justifiability of algorithms for the short-term fog forecasting, it is necessary to adapt the criterion parameters on the all-season data set.

17 1) Fog probability, 2) Low altitude wind shear and wake vortex flight safety, 3) Probability of freezing precipitation, 4) Icing.

18 WHY WE NEED TEMPERATURE PROFILE for Wind shear? 18(30) MTP-5 has been developed for temperature inversion measurements! Christian Pagé D. Cimini et al. (eds.), Integrated Ground-Based Observing Systems

19 Wake vortex safety system and Wind shear 19(30) Sochi. RU h Profile 1 Profile 2 Profile 3 Profile 4 125y Profile 1 Profile 2 Profile 3 Profile 4 Adiabatic Wake turbulence is turbulence that forms behind an aircraft as it passes through the air. В , 100sec, Profile 1 next is B (wings 28.88m, speed 77m/sec). Wind 0m/s T z

20 20(30) Fast-time wake vortex models typically require inputs of an estimate of the vertical profiles of the wind, potential temperature, and ambient turbulence (Greene, 1986; Robins and Delisi, 2002; Proctor, 2009; Ahmad et al., 2014). San Francisco - Airport (SFO). USA. 2015

21 1) Fog probability, 2) Low altitude wind shear and wake vortex flight safety, 3) Probability of freezing precipitation, 4) Icing. 21

22 22(30) :35 Moscow

23 :20 GMT By using radars data we can the expected rainfall amount and intensity. Moreover, we can see how fast is coming to us these precipitation.

24 dto=to_isot-tinv

25 1) Fog probability, 2) Low altitude wind shear and wake vortex flight safety, 3) Probability of freezing precipitation, 4) Icing.

26 Icing (heights hazardous for icing ) While the icing can occur over a wide range of negative temperatures, the probability is maximum in a relatively narrow range of temperatures and relative humidity ( C and> 85% respectively). Outside these intervals icing probability decreases rapidly. ( 7/sh_ice.pdf)

27 27(30) Icing (+ weather forecast + meteorological data)

28 INVISIBLE WATER «Orlovka» 2015/01/22 09:43 Icing (heights hazardous for icing ) While the icing can occur over a wide range of negative temperatures, the probability is maximum in a relatively narrow range of temperatures and relative humidity ( C and> 85% respectively). Outside these intervals icing probability decreases rapidly. (

29 29(30) Complex is based on 3 microwave radiometric receivers with operating frequencies: 20.7, 31.4 and 56,7 GHz. The complex has following features: 1 - Temperature profile 1-10 km, 2 - Water vapor content, 3 - Liquid water content, 4 - Humidity profile.

30 30(30) Conclusions. The first step shown the good potential of the blending data NWP, in-situ data and state-ofthe-art remote sensing of the temperature stratification in solving task of the Aviation Weather Hazards Nowcasting; By using the tested algorithms have been solved problem with limitation NWP in accuracy in PBL and with height for temperature profiling at 56.6GHz (1 km usually), On the base of such implementation the NEW algorithms have been tested for Nowcasting: 1) Fog probability, 2) Low altitude wind shear and wake vortex flight safety, 3) Probability of freezing precipitation, 4) In-flight Icing To confirm and develop these results the work will be continue with development of userfriendly software, hardware and testing in local airports. to be continue

31 Thank you I wanted to thank everybody who is involved in this project. Merci beaucoup! Evgeny Miller, Mikhail Kanevsky, Nikolay Baranov