ERASMUS: Campaign Summary and Highlights · ERASMUS1 2-16 August, 2015 DataHawk2 ERASMUS2 2-16...
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ERASMUS: Campaign Summary and Highlights Gijs de Boer 1,2 , Dale Lawrence 1 , Scott Palo 1 , Brian Argrow 1 , Gabe LoDolce 1 , Nathan Curry 1 , Will Finamore 1 , Doug Weibel 1 , Tevis Nichols 1 , Phillip D’Amore 1 , Ru-Shan Gao 2 , Hagen Telg 1,2 , Beat Schmid 3 , Chuck Long 1,2 , Mark Ivey 4 , Al Bendure 4 , Geoff Bland 5 , Steven Borenstein 1 , Jim Maslanik 1 , Jack Elston 6 , Terry Hock 7 , Holger Vömel 7 Introduction DataHawk Deployments (Aug. 2015, Oct. 2016) Platforms and Measurement Objectives Pilatus Deployment (Apr. 2016) Summary and Outlook Acknowledgments This work was supported by the US DOE Atmospheric Sys- tems Research (ASR) and Atmospheric Radiation Measure- ment (ARM) Programs. Additional support was provided by the National Center for Atmospheric Research (NCAR), the University of Colorado and the National Oceanographic and Atmospheric Administration (NOAA). All campaign data are publically available via the ARM data portal. References This poster presents information on unmanned-aircraft deployments to Oliktok Point, Alaska as part of the Evaluation of Routine Atmospheric Sounding Measurements using Unmanned Systems (ERASMUS) campaign. This includes an overview of the August, 2015 and October, 2016 deployments of the CU DataHawk2 aircraft. Over these two campaigns, data was collected on lower atmospher- ic thermodynamic structure, near-surface atmospheric fluxes, and surface temperature. Additionally, we provide an overview on the CU Pilatus flights completed in April, 2016. The Pilatus was configured to fly with aerosol, radiation, and thermodynamic sensors. This aircraft was flown in three configurations: 1) Aerosol+thermodynamics, which in- cludes the Printed Optical Particle Spectrometer (POPS) and NCAR-developed drop- sonde sensors; 2) Aerosol+thermodynamics+broadband longwave, which includes ev- erything in 1) in addition to up- and downward-looking Kipp and Zonen CGR4s, and 3) Aerosol+thermodynamics+broadband shortwave, which includes everything in 1) along with three Delta-T SPN-1 pyranometers and a high-accuracy IMU for attitude cor- rection. Finally, we provide a summary of lessons learned from these flight campaigns, a summary of flights and weather conditions faced, ongoing evaluation of these data sets and their use in model evaluation, and a general summary of the ERASMUS effort. de Boer, G., M. D. Ivey, B. Schmid, S. McFarlane, and R. Petty (2016a), Unmanned platforms monitor the Arctic atmosphere, EOS, 97, doi:10.1029/2016EO046441. Published on 22 February 2016. de Boer, G., S. E. Palo, B. Argrow, G. LoDolce, J. Mack, R.-S. Gao, H. Telg, C. Trussel, J. Fromm, C. N. Long, G. Bland, J. Maslanik, B. Schmid, and T. Hock (2016b), The Pilatus Unmanned Aircraft System for Lower Atmospheric Research. Atmos. Meas. Tech., 9, 1845-1857. Long, C.N., A. Bucholtz, H. HJonsson, B. Schmid, A. Vogelmann and J. Wood (2009): A method for correct- ing for tilt from horizontal in downwelling shortwave irradiance measurements on moving plat- forms, Open. Atmos. Sci. J., 4, 78-87. (1) (2) (3) (4) (5) (6) (7) Summary of Dates and Flights PTH Pod SPN-1s SPN-1 CGR-4 POPS CU Pilatus Sensor Module Pitot CU Datahawk2 Aircraft Wingspan Weight (empty) Endurance Measurement Capabilities CU DataHawk2 1 m <1 kg 75 min Temperature (fast from coldwire sensor + slow), humidity, wind estimate from local wind and aircraft state, pressure, IR surface and sky temperature, aircraft state CU Pilatus 3.2 m 16 kg 25 min Temperature (slow), humidity, pressure, aerosol size distribution (Gao et al., 2015), up/downwelling broadband shortwave irradiance (albedo), up/downwelling broadband longwave irradiance, aircraft state, auto-pilot-derived wind estimates Left: Surface temperature measured during low-altitude flight. Tundra is slightly colder than water around it (ponds, river, ocean). Right: Near-surface air temperature distributions. AMF3 DH2 DH2 cold T sfc DH2 mid T sfc DH2 warm T sfc Information on Airspace at Oliktok Point 149.95° W 149.85° W 70.48° N 70.5° N 70.52° N 70.54° N 1 nm 2 nm AMF-3 R-2204 4 nm diameter circle centered on Oliktok Point. This airspace is split into two sections, low (up to 1500’ MSL) and high (up to 7000’ MSL). Barrow Oliktok Point A B C D E F G H 80° N 75° N 70° N 130° W 140° W 150° W 160° W 170° W 50 nm 100 nm 173 nm W-220 20 nm on either side of 149.86° W, bounded to the south by 70.78° N, and to the north by 82° N. The warning area is divided into 16 sections of various lengths (A-H on map, including a low portion between 0’ and 2000’ MSL and a high portion between 2000’ and 10000’ MSL). Two areas of controlled airspace exist at Oliktok Point, including restricted area R-2204 and warning area W-220. ERASMUS was conducted entirely within R-2204. COALA (10/14) DH (8/15) Pilatus (4/16) DH (10/16) Details on the dates and flight patterns executed during each ERASMUS deployment. The photographs demonstrate some of the conditions faced by the flight crews. Campaign Dates Aircraft COALA 7-19 October, 2014 DataHawk ERASMUS1 2-16 August, 2015 DataHawk2 ERASMUS2 2-16 April, 2016 Pilatus ERASMUS3 10-22 October, 2016 DataHawk2 Temperature structure during October 2016 at Oliktok Point, as simulated by the Regional Arctic System Model (RASM) being used by NOAA PSD for sea ice forecasting. Dots represent DataHawk measurements and radiosonde measurements (denoted by “R”). The bottom figure shows DataHawk measurements plotted over the AERIoe retrieval of temperature. Model and Retrieval Evaluation Examples Hour (UTC) 17 19 21 23 25 27 0 100 200 300 400 0 100 200 300 400 500 Altitude (m) Date (UTC) 10/18 10/19 10/20 10/21 R R R R R R R R 285 280 275 270 265 260 0 -5 -10 -15 T (K) T (C) Spatial Variability Turbulent Fluxes Profiling 18:00 00:00 06:00 12:00 18:00 00:00 Time (UTC) 0 100 200 300 400 0 100 200 300 400 Altitude (m) 272 268 264 100 80 60 40 T (K) RH (%) 262 266 270 274 Theta (K) Altitude (m) 400 0 70.498 70.490 70.494 -149.91 -149.89 Latitude (deg) Longitude (deg) 70.498 70.488 70.490 70.492 70.494 70.496 Latitude (deg) -149.92 -149.90 -149.88 Longitude (deg) 0.74 0.72 0.69 0.67 0.65 0.62 Surface Albedo LW Irradiance Qs (W m -2 ) w’θ’ (K m s -1 ) θ’ (K) w’ (m s -1 ) Temperature and relative humidity profiles from 10/2016. Note the stable boundary layer and its evolution over time under a transition from clear to cloudy conditions. Left: An example flight targeting estimation of turbulent surface fluxes in the near-shore environment from 10/2016. Right: Compar- ison between Datahawk-derived sensible and latent heat fluxes and those measured by the Eddy-Covariance system at Oliktok Point from 10/2016. Both over-water (blue) and over-land (Green) flights are shown. Broadband Radiation 18:25 Time -500 0 500 1000 Flux Density (W m -2 ) 18:30 18:35 Down Up Net 18:25 Time 0 100 200 300 400 500 600 Flux Density (W m -2 ) 18:30 18:35 Total Direct Diffuse SW Albedo 0.55 Surface SW Albedo 0 0.2 0.4 0.6 0.8 1 Relative Frequency 0.65 0.75 Sea Ice SE Land NW Land Aerosols The Printed Optical Particle Spectrom- eter (POPS) was de- ployed on Pilatus to obtain profiles of aerosol size distri- bution. Delta-T SPN-1 pyranom- eters were deployed to measure broadband SW radiation and estimate surface albedo. Down- welling measurements were corrected using the technique from Long et al. 2009. 263 264 265 266 267 W m -2 Kipp and Zonen CGR-4s were de- ployed to measure up- and down- welling LW irradiance. These sen- sors were found to have too slow of a response time for this application. - Two different unmanned aircraft systems (CU DataHawk and CU Pilatus) were deployed to Oliktok Point, Alaska (OLI) over the course of three deployments to make measurements of the lower atmosphere and surface. - OLI was found to be a challenging operating environment for unmanned air- craft. This was the result of two major issues: 1) Electromagnetic Interference re- sulting from the US Air Force Dew Line radar station, which impacted aircraft con- trol systems and instrumentation; and 2) The weather conditions presented by the Arctic, which included a historically anomolous wind event (April 2016), cold temperatures, icing conditions, and low clouds and fog. While the weather condi- tions were not surprising, it is nearly impossible to prepare for them without ex- periencing them firsthand. The radar interference is a less well-understood issue that will likely impact systems operating at OLI in one way or another and its po- tential influence should be carefully weighed by operators. - Despite the challenges, a substantial data was collected over a variety of seasons and meteorological regimes. We are beginning to analyze the datasets collected in order to improve our measurement capabilities and conduct scientific evalua- tion of surface fluxes, temperature structure, surface albedo and more. - Knowledge gained through these deployments continues to be integrated into the ARM infrastructure through close collaboration with the ARM Aerial Facility (AAF) and the Tethered balloon team. Work conducted to improve the ability of the DataHawks to handle the radar interference has been integrated into the ARM-owned DataHawks
Transcript of ERASMUS: Campaign Summary and Highlights · ERASMUS1 2-16 August, 2015 DataHawk2 ERASMUS2 2-16...
ERASMUS: Campaign Summary and HighlightsGijs de Boer1,2, Dale Lawrence1, Scott Palo1, Brian Argrow1, Gabe LoDolce1, Nathan Curry1, Will Finamore1, Doug Weibel1, Tevis Nichols1, Phillip D’Amore1, Ru-Shan Gao2, Hagen Telg1,2, Beat Schmid3, Chuck Long1,2, Mark Ivey4, Al Bendure4, Geoff Bland5, Steven Borenstein1,Jim Maslanik1, Jack Elston6, Terry Hock7, Holger Vömel7
Introduction
DataHawk Deployments (Aug. 2015, Oct. 2016)
Platforms and Measurement Objectives
Pilatus Deployment (Apr. 2016)
Summary and Outlook
AcknowledgmentsThis work was supported by the US DOE Atmospheric Sys-tems Research (ASR) and Atmospheric Radiation Measure-ment (ARM) Programs. Additional support was provided by the National Center for Atmospheric Research (NCAR), the University of Colorado and the National Oceanographic and Atmospheric Administration (NOAA). All campaign data are publically available via the ARM data portal.
References
This poster presents information on unmanned-aircraft deployments to Oliktok Point, Alaska as part of the Evaluation of Routine Atmospheric Sounding Measurements using Unmanned Systems (ERASMUS) campaign.
This includes an overview of the August, 2015 and October, 2016 deployments of the CU DataHawk2 aircraft. Over these two campaigns, data was collected on lower atmospher-ic thermodynamic structure, near-surface atmospheric fluxes, and surface temperature.
Additionally, we provide an overview on the CU Pilatus flights completed in April, 2016. The Pilatus was configured to fly with aerosol, radiation, and thermodynamic sensors. This aircraft was flown in three configurations: 1) Aerosol+thermodynamics, which in-cludes the Printed Optical Particle Spectrometer (POPS) and NCAR-developed drop-sonde sensors; 2) Aerosol+thermodynamics+broadband longwave, which includes ev-erything in 1) in addition to up- and downward-looking Kipp and Zonen CGR4s, and 3) Aerosol+thermodynamics+broadband shortwave, which includes everything in 1) along with three Delta-T SPN-1 pyranometers and a high-accuracy IMU for attitude cor-rection. Finally, we provide a summary of lessons learned from these flight campaigns, a summary of flights and weather conditions faced, ongoing evaluation of these data sets and their use in model evaluation, and a general summary of the ERASMUS effort.
de Boer, G., M. D. Ivey, B. Schmid, S. McFarlane, and R. Petty (2016a), Unmanned platforms monitor the Arctic atmosphere, EOS, 97, doi:10.1029/2016EO046441. Published on 22 February 2016.
de Boer, G., S. E. Palo, B. Argrow, G. LoDolce, J. Mack, R.-S. Gao, H. Telg, C. Trussel, J. Fromm, C. N. Long, G. Bland, J. Maslanik, B. Schmid, and T. Hock (2016b), The Pilatus Unmanned Aircraft System for Lower Atmospheric Research. Atmos. Meas. Tech., 9, 1845-1857.
Long, C.N., A. Bucholtz, H. HJonsson, B. Schmid, A. Vogelmann and J. Wood (2009): A method for correct-ing for tilt from horizontal in downwelling shortwave irradiance measurements on moving plat-forms, Open. Atmos. Sci. J., 4, 78-87.
(1) (2) (3) (4)
(5) (6) (7)
Summary of Dates and Flights
PTH Pod
SPN-1s
SPN-1
CGR-4
POPS
CU Pilatus
Sensor Module
Pitot
CU Datahawk2Aircraft Wingspan Weight (empty) Endurance Measurement Capabilities
CU DataHawk2 1 m <1 kg 75 min Temperature (fast from coldwire sensor + slow), humidity, wind estimate from local wind and aircraft state, pressure, IR surface and sky temperature, aircraft state
CU Pilatus 3.2 m 16 kg 25 min Temperature (slow), humidity, pressure, aerosol size distribution (Gao et al., 2015), up/downwelling broadband shortwave irradiance (albedo), up/downwelling broadband longwave irradiance, aircraft state, auto-pilot-derived wind estimates
Left: Surface temperature measured during low-altitude flight. Tundra is slightly colder than water around it (ponds, river, ocean). Right: Near-surface air temperature distributions.
AMF3
DH2 DH2 cold TsfcDH2 mid TsfcDH2 warm Tsfc
Information on Airspace at Oliktok Point
149.95° W 149.85° W70.48° N
70.5° N
70.52° N
70.54° N
1 nm
2 nm
AMF-3
R-22044 nm diameter circle centered on Oliktok Point. This airspace is split into two sections, low (up to 1500’ MSL) and high (up to 7000’ MSL).
Barrow
Oliktok Point
ABCD
E
F
G
H 80° N
75° N
70° N
130° W140° W150° W160° W
170° W
50 nm
100 nm
173 nm
W-22020 nm on either side of 149.86° W, bounded to the south by 70.78° N, and to the north by 82° N. The warning area is divided into 16 sections of various lengths (A-H on map, including a low portion between 0’ and 2000’ MSL and a high portion between 2000’ and 10000’ MSL).
Two areas of controlled airspace exist at Oliktok Point, including restricted area R-2204 and warning area W-220. ERASMUS was conducted entirely within R-2204.
COALA (10/14)DH (8/15)Pilatus (4/16)DH (10/16)
Details on the dates and flight patterns executed during each ERASMUS deployment. The photographs demonstrate some of the conditions faced by the flight crews.
Campaign Dates Aircraft
COALA 7-19 October, 2014 DataHawk
ERASMUS1 2-16 August, 2015 DataHawk2
ERASMUS2 2-16 April, 2016 Pilatus
ERASMUS3 10-22 October, 2016 DataHawk2
Temperature structure during October 2016 at Oliktok Point, as simulated by the Regional Arctic System Model (RASM) being used by NOAA PSD for sea ice forecasting. Dots represent DataHawk measurements and radiosonde measurements (denoted by “R”). The bottom figure shows DataHawk measurements plotted over the AERIoe retrieval of temperature.
Model and Retrieval Evaluation Examples
Hour (UTC)17 19 21 23 25 27
0
100
200
300
400
0
100
200
300
400
500
Altit
ude
(m)
Date (UTC)10/18 10/19 10/20 10/21
R R R R R R R R 285
280
275
270
265
260
0
-5
-10
-15
T (K)
T (C)
Spatial Variability
Turbulent Fluxes
Profiling
18:00 00:00 06:00 12:00 18:00 00:00Time (UTC)
0
100
200
300
400
0
100
200
300
400Altit
ude
(m)
272
268
264
100
80
60
40
T (K)
RH (%)
262 266 270 274Theta (K)
Altit
ude
(m)
400
0
70.498
70.490
70.494
-149.91 -149.89
Latit
ude
(deg
)
Longitude (deg)
70.498
70.488
70.490
70.492
70.494
70.496
Latit
ude
(deg
)
-149.92 -149.90 -149.88Longitude (deg)
0.740.72
0.690.670.65
0.62
Surface Albedo
LW Irradiance
Qs (W m-2)
w’θ’ (K m s-1)
θ’ (K)
w’ (m s-1)
Temperature and relative humidity profiles from 10/2016. Note the stable boundary layer and its evolution over time under a transition from clear to cloudy conditions.
Left: An example flight targeting estimation of turbulent surface fluxes in the near-shore environment from 10/2016. Right: Compar-ison between Datahawk-derived sensible and latent heat fluxes and those measured by the Eddy-Covariance system at Oliktok Point from 10/2016. Both over-water (blue) and over-land (Green) flights are shown.
Broadband Radiation
18:25Time
-500
0
500
1000
Flux
Den
sity
(W m
-2)
18:30 18:35
Down Up Net
18:25Time
0
100
200
300
400
500
600
Flux
Den
sity
(W m
-2)
18:30 18:35
Total Direct Diffuse
SW Albedo
0.55Surface SW Albedo
0
0.2
0.4
0.6
0.8
1
Rela
tive
Freq
uenc
y
0.65 0.75
Sea Ice SE Land NW Land
Aerosols
The Printed Optical Particle Spectrom-eter (POPS) was de-ployed on Pilatus to obtain profiles of aerosol size distri-bution.
Delta-T SPN-1 pyranom-eters were deployed to measure broadband SW radiation and estimate surface albedo. Down-welling measurements were corrected using the technique from Long et al. 2009.
263
264
265
266
267
W m-2
Kipp and Zonen CGR-4s were de-ployed to measure up- and down-welling LW irradiance. These sen-sors were found to have too slow of a response time for this application.
- Two different unmanned aircraft systems (CU DataHawk and CU Pilatus) were deployed to Oliktok Point, Alaska (OLI) over the course of three deployments to make measurements of the lower atmosphere and surface.- OLI was found to be a challenging operating environment for unmanned air-craft. This was the result of two major issues: 1) Electromagnetic Interference re-sulting from the US Air Force Dew Line radar station, which impacted aircraft con-trol systems and instrumentation; and 2) The weather conditions presented by the Arctic, which included a historically anomolous wind event (April 2016), cold temperatures, icing conditions, and low clouds and fog. While the weather condi-tions were not surprising, it is nearly impossible to prepare for them without ex-periencing them firsthand. The radar interference is a less well-understood issue that will likely impact systems operating at OLI in one way or another and its po-tential influence should be carefully weighed by operators.- Despite the challenges, a substantial data was collected over a variety of seasons and meteorological regimes. We are beginning to analyze the datasets collected in order to improve our measurement capabilities and conduct scientific evalua-tion of surface fluxes, temperature structure, surface albedo and more.- Knowledge gained through these deployments continues to be integrated into the ARM infrastructure through close collaboration with the ARM Aerial Facility (AAF) and the Tethered balloon team. Work conducted to improve the ability of the DataHawks to handle the radar interference has been integrated into the ARM-owned DataHawks
