1. 1 Approved For Public Release; Distribution Unlimited Mr. Terry Jameson Battlefield Environment Division Army Research Laboratory, WSMR COMM 575-678-3924 terry.c.jameson.civ@mail.mil UAS Data Collection for High-resolution MET Modeling Ingest

2. 2 Approved For Public Release; Distribution Unlimited Weather Prediction Models Numerical Weather Prediction (NWP) Models Predictions of basic Met parameters (winds, temperature, pressure, humidity) Predictions of derived parameters (turbulence, visibility, cloud layers, etc.) Predictions at 3-D grid points ( ~ 30 mi. down to ~ 8 mi. horizontal spacing) Predictions out several hours - up to many days Research-grade models (one-hour predictions – 0.6 mi. grid spacing) Models require Met data observations input for initialization Surface weather stations (manned and automated) – little help for upper atmosphere Doppler weather radar (intensity and motion within storms) – good info but only when storms are present Satellite observations of winds and temps (very coarse vertical resolution) Vertically-pointing wind profiling radars – few locations even in U.S. Weather balloons (winds, pressure, temperature, humidity) ~ 70 stations in Lower 48, ~700 world-wide Twice-daily balloon launches Mainstay of NWP model input since its inception in late ‘50s-early 60’s

3. 3 Approved For Public Release; Distribution Unlimited But there’s a Problem In the U.S. all of the above are available, but….. Problem is: All of the above leave many gaps (time/space), especially for high-resolution models Problem is: In/near the battlefield, only a very few weather balloon and surface observation stations exist Problem is: Those few stations can be sporadic in their observations Bottom line: WE NEED MORE INPUT MET DATA!

4. 4 Approved For Public Release; Distribution Unlimited In-situ Obs from UAVs Data collected from UAVs - What are we up against? Certainly many UAVs have a temperature sensor/readout, plus GPS winds BUT… Are those data date/time/location-stamped? Are the data just displayed to the operator? – can’t use in modeling Are the data recorded on-board somehow? – probably not What about pressure and humidity? – need those parameters as well How to QC the data? – bad data or wrong time/place = poor performance. How to format the data? – models are very picky! Are the data recorded at the ground station? – probably not

5. 5 Approved For Public Release; Distribution Unlimited TAMDAR-What is it? TAMDAR: (Tropospheric Airborne Met DAta Reporting) Small meteorological (Met) data sensing/transmitting instrument AirDat, LLC Installed on ~150 regional commuter airliners Collects Met data for ingest into Numerical Weather Prediction (NWP) Models TAMDAR-U (TAMDAR-UAV) TAMDAR downsized for installation on UAVs Stringent restrictions on Size, Weight, and Power (SWaP) requirements

6. 6 Approved For Public Release; Distribution Unlimited AirDat’s Commercial TAMDAR ® System Know the Weather Information used with permission from AirDat, LLC

7. 7 Approved For Public Release; Distribution Unlimited The Team NMSU PSL/Technical Analysis & Applications Center (TAAC) The Aerostar-B UAV Established COA in southern NM Substantial experience in conducting instrumentation flight tests AirDat, LLC The TAMDAR Instrumentation facilities (Lakewood, CO) Data ground station and NWP modeling facilities (Florida) Substantial experience in instrumenting commercial airline fleets Substantial experience in ingesting TAMDAR data into models ARL Long-term history of DOD weather research and support High-resolution, battlefield-scale NWP model development Substantial experience in assessing model performance

8. 8 Approved For Public Release; Distribution Unlimited TAMDAR-U Sensor (Prototype) Measures and Reports -Ice presence-Relative Humidity -Median and peak turbulence-Indicated and True Airspeed -Static pressure and pressure altitude-Winds Aloft (Speed and Dir) -Air temperature (Mach corrected)-GPS Position and Time -Additional sensing possible (CBRN)-Encryption Possible Prototype TAMDAR-U CFD Analysis Mounted on Modified Aerostar Nose Cone Know the Weather Information used with permission from AirDat, LLC

9. 9 Approved For Public Release; Distribution Unlimited TAMDAR-U Sensor (Prototype) - SWaP Know the Weather LRUDimensions (Volume) WeightMax Power (Estimated) Probe (External) 2.6”x2.5”x0.7” 3.6” Pitot 2.2 oz (62 g) N/A Data Acquisition, Processing, and Communications (Internal) 40 in 3 12.2 oz (346 g) 8.4W TOTALS40 in 3 Internal (reductions possible) 14.4 oz (408 g) (reductions possible) 8.4W (reductions possible) Information used with permission from AirDat, LLC

10. 10 Approved For Public Release; Distribution Unlimited The Aerostar UAS

11. 11 Approved For Public Release; Distribution Unlimited 32 o 46.00’ N 106 o 30.00’ W 31 o 40.00’ N 106 o 30.00’ W 31 o 40.00’ N 107 o 50.00’ W 32 o 46.00’ N 107 o 50.00’ W The Airspace & Model Domain

12. 12 Approved For Public Release; Distribution Unlimited Experimental Approach  Collect TAMDAR-U data within model domain for three-hour flight  Reformat and archive data for later analyses  Run model in data-ingest mode for 3-hrs, simulating ingest during flight  Continue model run after data ingest cutoff – generate 6 hr forecast  Compare output charts with/without TAMDAR-U ingest  Compare against any available observations

13. 13 Approved For Public Release; Distribution Unlimited

14. 14 Approved For Public Release; Distribution Unlimited LRU A/P 32 o 17.21’ N 106 o 55.19’ W Point A 32 o 46.00’ N 106 o 30.00’ W 31 o 40.00’ N 106 o 30.00’ W 31 o 40.00’ N 107 o 50.00’ W 32 o 46.00’ N 107 o 50.00’ W 32 o 40.00’ N 107 o 34.00’ W Point B SOUTHERN BORDER ADIZ 305 O / 40 nm 125 O / 40 nm After T/O: Normal climb to 10,000’ MSL Course 305 o True At 10,000 MSL, normal descent to 7,000’ MSL At Point B, standard rate turn to 125 o True Return to Point A (LRU) At 65 kt IAS (approx. 75 kt TAS), the R/T to Pt. B will take approximately 1.15 hr. Example “Test Card”

15. 15 Approved For Public Release; Distribution Unlimited Example Results

16. 16 Approved For Public Release; Distribution Unlimited What did we find?  TAMDAR sensor could be adequately downsized/configured for UAV ops  TAMDAR-U data successfully assimilated, formatted, ingested given erratic flight patterns and altitudes of UAV missions  From a qualitative standpoint, wind flow patterns looked more realistic over and near mountain slopes with TAMDAR-U data ingest  Few observations within most of the domain for quantitative evaluation  Weather balloons launched at LRU airport compared against vertical profiles from the models were inconclusive  Very benign weather case-study days were not conducive to finding clear distinctions between models

17. 17 Approved For Public Release; Distribution Unlimited What’s next?  Collect TAMDAR data within a data-rich model domain (commuter fleet)  Run model ingesting or withholding data as before  Select some “bad weather” case-study days (rainfall, strong winds, etc.)  Conduct quantitative statistical analyses, observation points versus forecasts