Scientific aircraft research flights have to be planned beforehand. For that it is necessary to have model forecasts of relevant quantities such as meteorological parameters, chemical composition or particle information to guide the aircraft to the location of interest. Typically, many scintific instruments on board those aircrafts used to investigate e.g. the chemical composition of the air in order to get new insights often with the involvement of different science groups. For discussion of the possibilites of the research flights, the Mission Support System (MSS) was developed. This software helps to review a big amount of metereological and model data by viewing the forecasted parameters of interest along possible regions of a proposed flight path. Data and possible flight paths can be displayed on a hoizontal view (map projection) or on a vertical view (along the proposed flight path). Flight paths can be constructed and modified on these views. I/O through a waypoint table is also possible. The talk gives a brief insight into the MSS software development. We are using the OWS interface standard. https://geopython.github.io/OWSLib/ MSS is a client/server application. The QT client interacts with a paste wsgi server. The software is available for all platforms on conda-forge.

1. MitgliedderHelmholtz-Gemeinschaft
MSS - Software
for planning research
aircraft missions
30.10.2016 Reimar Bauer

2. About me
Forschungszentrum Jülich GmbH
http://www.fz-juelich.de/
Reimar Bauer, IEK-7
@ReimarBauer
Python Software Foundation
Python Software Verband e.V.
r.bauer@fz-juelich.de
Reimar.Bauer@python-
verband.org
dreimark@chat.freenode.net
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3. Atmospheric Research – WHAT?
Understand various
individual processes and
their interplay
Figure: NASA Earth Observatory
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4. Sketch of Atmospheric Processes
Source: SPARC Report
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5. Atmospheric Research – WHY?
Provide predictions for the atmosphere regarding
Climate
Global warming
Ozone hole
. . . and many more
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6. Atmospheric Research – HOW?
Measurements of chemical trace gas composition and other
parameters of interest that characterize these processes
Laboratory
Balloons
Aircrafts
Satellites
Simulations of the atmosphere (composition, particles) by a
variety of models
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7. Atmospheric Research – AIM
Improved understanding of the individual processes
parametrize these processes in atmospheric models, e.g.
Chemistry climate models (CCMs) and Earth system models
(ESMs)
Quality improvement of models and predictions for ozone
hole, climate,. . .
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8. Atmospheric Research – Aircraft Measurements
Flexibility to measure at locations of scientific interest
Cheap compared to satellite measurements
Research flight hours are rare and still very expensive
Collaboration with various groups and institutions that are
specialized for individual measurements
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9. Example: The Geophysica Aircraft
Top altitude: 20 km, range: 3000 km
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10. Example: The Geophysica Aircraft
Places for payload of scientific Instruments
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11. Example: The Geophysica Aircraft
Instrument Parameter P.I. Bay
FOZAN O3 Ulanovsky, CAO
FabrizioRavegnani, CNR
Bay 5
FISH H2O (total)
MartinaKraemer, JUELICH
Bay 4
FLASH H2O (gas phase)
AlexeyLykov, CAO
Under Wing
Pylon
SIOUX
NO
NOy
Particle NOy
HansSchlager, DLR
Under Wing Pod
right
HALOX t.b.d.
ClO
BrO FredStroh, JUELICH
left Wing Pod
HAGAR
N2O, CFC12
CFC11
CH4, H2
SF6
Halon 1211
CO2
MichaelVolk, BUW
Bay 8
WAS
Long lived trace gases and
isotopo-logues ThomasRoeckmann, UTRECHT
Fuselage Bay
Many more instruments for measurements of different
parameters
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12. Example: The HALO Aircraft
Top altitude: 15 km, range: 10000 km
HALO leaving the Arena Arctica. Picture by Peter Preuße, FZJ.
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13. Planning of Research Flights
Typically, scientific campaigns with more flights from a base
airport address one or more scientific questions
Model simulations provide related parameters of interest for
the near future using meteorological forecast data
Optimization of the scientific outcome by finding the best flight
path (in 4 dimensions time, latitude, longitude, altitude) in the
“model world”
Consideration of various aircraft constraints (range, flight
altitude, overflight permits. . . )
Discussion and iteration of the proposed flight plans with
pilots and aircraft representatives
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14. M
¯
ission S
¯
upport S
¯
ystem (MSS)
Software to aid scientific flight planning:
Marc Rautenhaus, formerly DLR, introduced MSS in 2012. It is
since May 2016 a git FOSS project on bitbucket.
Python 2.7.x Client / Server application
OGC web map service based
conda-forge - anaconda application
License: Apache 2.0
Docs: mss.rtfd.io
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15. Documented in GMT
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16. Basic principle of the OGC Web Map Service standard
A client (left) sends a GetMap request, encoded as an HTTP
URL to the server (right). The server creates an image file and
sends it to the client.
Rautenhaus et al., GMD, 5, 55-71, 2012
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17. Description MSS
A data center can install the MSS server component and
configure it to provide data.
The client is a QT 4 GUI application which can access many
MSS Servers.
The client accesses the server and requests vertical,
horizontal views and receives generated images.
Scientists interactively design a flight route in direct relation to
atmospheric prediction data.
Way points of a proposed flight route are overlayed on any
view of requested data.
All the information could be exchanged and manipulated by
others.
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18. Architecture of MSS WMS Server
Rautenhaus et al., GMD, 5, 55-71, 2012
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19. Architecture of MSS GUI
Rautenhaus et al., GMD, 5, 55-71, 2012
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20. Installing MSS and running Client or/and Server
$ conda create -n mssenv python=2
$ source activate mssenv
$ conda install -c conda-forge mss
$ mss
$ #mswms #standalone wsgi server
MSS Launcher:
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21. Top View
Rautenhaus et al., GMD, 5, 55-71, 2012
A) map projection
B) zoom/pan
C) way points
D) appearance
E) open controls
F) layer
G) time setup
H) new request
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22. Vertical Flight Profile
Rautenhaus et al., GMD, 5, 55-71, 2012
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23. Table View
Rautenhaus et al., GMD, 5, 55-71, 2012
Listing way points of the flight track
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24. Example: NAWDEX, Sept/Oct 2016 Keflavik, Iceland
Pictures: Marc Rautenhaus, TU München
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25. Example: HALO flight from Kiruna to
Oberpfaffenhofen
Top view: Mixing ratios of N2O and O3:
Source: POLSTRACC flight planning team
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26. Example: HALO flight from Kiruna to
Oberpfaffenhofen
Side view: Mixing ratios of N2O and Ozone loss:
Source: POLSTRACC flight planning team
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27. Example: HALO flight from Kiruna to
Oberpfaffenhofen
Top view: Cloud cover and tropopause height:
Source: POLSTRACC flight planning team
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28. Example: HALO flight from Kiruna to
Oberpfaffenhofen
Side view: Clouds and Potential Vorticity:
Source: POLSTRACC flight planning team
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29. Documentation
http://mss.rtfd.io
https://bitbucket.org/wxmetvis/mss
https://anaconda.org/conda-forge/mss
http://www.geosci-model-dev.net/5/55/2012/gmd-5-55-
2012.pdf
http://www.geosci-model-dev.net/5/55/2012/gmd-5-55-2012-
supplement.pdf
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30. Examples of campaigns using MSS
ML-CIRRUS 2014 Oberpfaffenhofen
http://www.pa.op.dlr.de/ML-CIRRUS/
POLSTRACC 2016 Kiruna
https://www.polstracc.kit.edu/polstracc
STRATOCLIM 2016-17 Kalamata and India
http://www.stratoclim.org/
NAWDEX 2016 Iceland
http://nawdex.org/
WISE 2017 Ireland
https://www.blogs.uni-mainz.de/fb08-ipa/wise/
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31. Summary
Scientific aircraft research flights have to be planned
beforehand. For that it is necessary to have model forecasts of
relevant quantities such as meteorological parameters, chemical
composition or particle information to guide the aircraft to the
location of interest.
For discussion of the possibilites of the research flights, the
Mission Support System (MSS) was developed. This software
helps to review a big amount of metereological and model data
by viewing the forecasted parameters of interest along possible
regions of a proposed flight path.
30.10.2016 Reimar Bauer Folie 31