P2 (63) Innovative New Canister-type Auto Balloon Launcher aiming for Uninterrupted Observations Kensaku Shimizu, Ryota Maeda, and Norio Nagahama Meisei s new auto balloon launcher is designed to use multiple modularized canisters arranged in the balloon inflating area, Canister-type. Advantages: Allows variety of selection in number of sondes (Min.4 to Max.40) to meet user s requirements. Simple structure with minimal moving mechanism allows steady and assured operations Multiple modularized canisters which can be inflated respective balloons achieve continue observations with a minimum of human intervention.
Aircraft Derived Wind and Temperature Observations on a Global Scale Edmund Stone and Malcolm Kitchen Introduction Mode-S enhanced surveillance (Mode-S EHS) derived meteorological data have the potential to be a very valuable source of high quality wind observations from aircraft [1,2,3]. Mode-S EHS is an air traffic management standard where an aircraft transmits a set of messages about their current situation. These messages provide both the aircrafts vector through the air and the vector along the ground. The difference between these two vectors is the wind acting on the aircraft. It is also possible to derive temperature observations using the reported Mach number and the true airspeed [3]. Global Satellite Reception There have been several advances in the detection of ADS-B data using satellites to enable Air Traffic Control (ATC) to track aircraft with no breaks in coverage [4]. Recently, the European Space Agency (ESA) and GomSpace have completed a mission to demonstrate the potential to use a cubesat (GomX-3, shown in figure 4) to detect ADS-B data to track aircraft from space. These advances have opened up the possibility of considering global Mode-S EHS data coverage without the need to deploy 100 s of ground stations. As such, the Met Office, ESA and GomSpace are currently working together to map the potential coverage of Mode-S EHS data across the globe and to assess the economic value of collecting the data using a satellite platform. Figure 4. The GomX-3 CubeSat. Wind Ground Vector Air Vector Figure 1. Vector diagram demonstrating how aircraft movement vectors can be used to calculate wind observations. Figure 5. Map showing the location of derived wind and temperature observations (red dots) received using the GomX-3 satellite. The blue lines show the path of the satellite during the data collection period. Figure 2. Observation-background (o-b) statistics for Mode-S EHS derived (solid black circles) and AMDAR (solid gray triangles). Heading corrections were introduced on 28 th August. Figure 3. Mode-S antenna installation at the Channel Islands Radar. So far,13 days of data have been collected from the GomX-3 satellite. These have provided 19353 observations across the globe, with the wide availability of data being shown in Figure 5 as the red dots. The blue lines represent the path of the satellite. For regions where data is received from cruse altitudes, some profile data is also available. There is potentially significant value in this data, although location specific heading corrections will need to be made. Further work on the collection efficiency and cross section will need to be made for operational cubesat collection to be feasible. UK Network Network of 6 receivers. The receivers gather Mode-S EHS messages and Automated Dependent Surveillance Broadcast (ADS-B) (position data) messages. The network derives around 5.5 million wind observations every day around the UK, and around 900 profiles. Observation Background statistics (UK-V 1.5 km) of a similar quality to those generated for AMDAR. Acknowledgements We would like to thank GomSpace and the European Space Agency for listening to our idea and reprogramming their satellite on a very tight timescale to provide data for this poster and for their ongoing support. References [1] Siebren de Haan. High-resolution wind and temperature observations from aircraft tracked by Mode-S air tracked by air traffic control radar. Journal of Geophysical Research: Atmospheres (1984{2012), 116(D10), 2011. [2] Heiner Lange and Janjić Tijana. Assimilation of mode-s EHS aircraft observations in COSMO-KENDA. Monthly Weather Review 144.5 (2016): 1697-1711. [3] Edmund Keith Stone and Gary Pearce. A network of mode-s receivers for routine acquisition of aircraft-derived meteorological data. Journal of Atmospheric and Oceanic Technology, 33(4):757{768, 2016. [4] Igor Alonso Portillo1, David Gerhardt, and Morten Bisgaard. Launch and early operations phase for the gomx-3 mission. 2016. Met Office FitzRoy Road, Exeter, Devon, EX1 3PB United Kingdom Tel: +44 1392 885680 Fax: +44 1392 885681 Email: ed.stone@metoffice.gov.uk Crown copyright Met Office and the Met Office logo are registered trademarks
P2(68) JMA s C band dual polarization Doppler weather radar with SSPAs Solid State Dual Pol Low Peak Power Narrow Band High speed 1min Low elevation 5min Volume scan High quality Severe Phenomena Detection
P2 (72) A smart framework for weather awareness Motivation 72WSG8 Aeronautical MET information is pivotal ICAO MET services, especially for terminal area, are not enough and climate change / traffic / safety / environment will influence the future MET information and service content. Consistent, interoperable, concise and fit-for-purpose weather information is a fundamental ingredient to improve global situational awareness. Drivers ICAO/GANP * ASBU * SWIM * SESAR * SESAR2020 ICAO/WMO CAeM: Restructure of Annex 3 / new Procedures for Air Navigation Services for MET National: German Federal Aeronautical Research Programme 2016-2019 Poster presents R&D on inter alia visibility detection (3D ceilometer/infrared camera), turbulence and wind shear (radar and lidar), glide slope related information for TMA, cross wind impact, Microburst radar overhead assessment Solution for web-based and human centric decision support framework R&D on translation ATM MET information to ATM impact metrics 2016 Selex ES GmbH - All rights reserved Poster P2(72), CIMO TECO 2016 Madrid, Think smart