The AirCore Profiler. methods, challenges, applications and updates

Transcription

1 The AirCore Profiler methods, challenges, applications and updates Jonathan Bent, CIRES / NOAA Colm Sweeney, Tim Newberger, Sonja Wolter CIRES / NOAA Pieter Tans, Jack Higgs NOAA

2 Outline 1. AirCore observing strategy, challenges (10 mins) 2. AirCore Python Data Processing Package (3 mins) 3. UAS Application (1 min) 4. Mailing List (1 min)

3 1. AirCore Platform, Purpose Platform Purpose TCCON OCO2

4 1. Passive AirCore Sampling 100,000 feet Fill Gas Captured profile

5 NOAA: - 3 days (2014, 2015) profiles - CO 2, CH 4, CO Polytechnique/LSCE: 3x2 weeks ( ) 1-2 profiles CO 2, CH 4, CO, N 2 O NOAA: - 1 days (2015) - 1 profile - CO 2, CH 4, CO NOAA: - 30 days ( ) profiles - CO 2, CH 4, CO 1. AirCore Profiles Polytechnique: - Large balloon - Large AirCore - Alice Springs Groningen/FMI: 30 days ( ) 1 profiles CO 2, CH 4, CO, 14 CO 2, 17 O 2

6 1. Demonstrating trustworthiness A. Altitude registration: temperature changes, pressure drop drag can cause biases in the inferred altitude of the AirCore sample B. End-member mixing: separating push and fill gas from sample C. Surface effects, reproducibility: high surface to volume ratio in AirCore

7 1A. Altitude Registration: Comparison with in situ meas. Research Aircraft NOAA Aircraft Program CH 4 Column Mean offset CO 2 CO 2 (ppm) ± 0.04 (±0.02%)

8 1A. Tans fluid dynamics model, Temperature Correction Corrections: - Aircore temperature: actual change in temperature of air in the aircore needs to be known. - Pressure drop: AirCores rapid decent at top of profile causes large pressure drop. Validation: Now possible with high altitude bag sampler, especially valuable for CH 4, as per Joram Hooghiem

9 1A. Sampling Resolution Slug Smearing of sample: -Molecular diffusion -Taylor dispersion Altitude 4 h 12 h 24h 400 m 150 m 225 m 325 m 5000 m 200 m 350 m 500 m m 475 m 825 m 1200 m m 2400 m 4200 m N/A Based on a 100 m of x stainless steel tubing

10 Uncertainties 1A. Reproducibility Flight String 1: / ppm Flight String 2: / ppm It is important to fly multiple AirCores 2 flights with 2 AirCores on each flight string, flown 15 minutes apart. Lower column differences on order 0.8 ppm. Overall difference 0.23 ppm

11 1B. End Member Mixing, 2017 Analysis Setup 3-way Purge Through Valves Chase gas pushes sample through Picarro CRDS slowly (30 sccm) in plugflow to preserve sample with minimal mixing

12 1B. End member mixing CO is used as a neutral end member to infer mixing of CO 2 and CH 4 Ongoing Challenge: Properly representing the mixing without Underestimating the transition, hook

13 1C. Uncertainties Surface Effects CO - Water vapor CO 2 - Impurities - Age of AirCore

14 1C. Scrubbing, pigging, making coffee

15 1C. Welds and Stainless Steel Valves Location of post-silkonert Weld Upper SS Valve

16 2. Python Code Context It is a riddle, wrapped in a mystery, inside an enigma. Winston Churchill, about Russia, 1939 It is a IDL, wrapped in a Matlab, inside a Python Me, about AirCore, 2017 IDL: Pieter Tans Matlab: Colm Sweeney Anna Karion R: Huilin Chen Python: Jonathan Bent

17 2. Python Code Workflow

18 3. UAS Application Black Swift Superswift Fixed Wing Unmanned Aerial System Actively pumped to characterize point source fluxes Run by Univ. Colorado Boulder RECUV Division 5 lb (2.7kg) payload Alternative strategy to Truls s system Platform Black Swift Superswift Fixed Wing Cost $22K Cruise Speed Distance Travelled at cruise speed Flight Time AirCore Coil Length AirCore Weight 18 m/s 129 km 120 mins 100 m 0.98 kg Flow Variable as needed # of samples given mixing 266 volume of instrument cell Horiz res [m] for ten 0.25 km radius spirals spaced 120 feet apart in altitude 15 m

19 Conclusions NOAA GMD AirCore measures CO 2, CH 4, and CO between the surface and ~12 mb New lab methods have improved end member mixing calcs Surface conditions continue to be the greatest challenge, with strong evidence that cleaning AirCores leads to fewer biases Altitude registration with data processing works well, but bag sampling promises additional validation Python code (Beta release now available) will standardize approach, enable labs to improve processing, circulate it in a modular fashion UAS AirCore Active planned for 2018 to characterize point source fluxes

20 Thank you My Mailing List: