Comparison of Aircraft Observations With Surface Observations from R/V POINT SUR Dominick Vincent OC 3570 18 March 2003

Operational Motivation: Naval Oceanography Program Operational Concept - Guiding Principles (2002): “…We will employ a doctrinal Rapid Environmental Assessment (REA) process, using both dynamic and static data to characterize the battlespace environment and reflect it in the 4D Cube as part of deliberate and contingency military operations.” - Page 6

Rapid Environmental Assessment Aircraft: Rapid (Synoptic) In-situ (Atmosphere) Remote (Surface Obs) Ship: Slower In-situ (Surface) In-situ (Atmosphere)

Question for Investigation: Can Aircraft provide comparable or superior observational data for environmental assessment?

Method of Investigation: Compare aircraft and ship data as used in the following: - Determining surface fluxes based on a bulk method calculation, and - Determining the spatial variability of wind field over a given area.

Data and Methods of Collection: Data were collected during the 8 day OC 3570 Operational Oceanography cruise from 27 Jan 2003 to 03 Feb 2003 aboard the R/V POINT SUR. Additionally, the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) provided aircraft data collection support for 27 Jan and 1 Feb.

Area of Collection: Area of investigation for the R/V POINT SUR covered a box off the coast of Central California and was bounded by California Cooperative Oceanic Fisheries Investigations (CalCOFI) line 67 to station 67-70, alongshore to station 77-70, and inshore to Port San Luis along line 77. Additional CalCOFI Hydrography lines were covered within the outer box by both the R/V POINT SUR and the CIRPAS Aircraft.

Ship Plane – 27 Jan Plane – 1 Feb CalCOFI Line 67 CalCOFI Line 77

Ship Plane – 27 Jan Plane – 1 Feb

Collection Platforms: R/V POINT SUR Data Collected every 54 seconds (SAIL): Position Time (UTC) Wind Direction Wind Speed Air Temperature Relative Humidity Pressure Sea Surface Temperature

Collection Platforms: UV-18A “Twin Otter” Data Collected every second: Position Time (UTC) Wind Direction Wind Speed Air Temperature Relative Humidity Pressure Sea Surface Temperature Altitude

Bulk Method-derived Surface Fluxes: Comparison of Bulk Method-derived Surface Fluxes: Calculated using a Matlab program, sfcfluxoc3570, by Guest (1997) using a bulk method formulation based on Smith (1990) and requiring the following inputs: - Wind speed - Air temperature - Relative humidity - Sea Surface Temperature - Pressure

Bulk Method-derived Surface Fluxes: Comparison of Bulk Method-derived Surface Fluxes: Measurements needed to be spatially and temporally coincident to achieve a valid comparison. One window, approximately 15 minutes in length, was found for each day.

Ship Plane

Ship Plane

Bulk Method-derived Surface Fluxes: Comparison of Bulk Method-derived Surface Fluxes: Ship Data: - Averaged over the 15 minute window. Aircraft Data: - Input parameters taken at lowest altitude, - Winds averaged over lowest 10 meters in window.

Data Comparison - 27 January 2003

Data Comparison - 27 January 2003

Data Comparison - 1 February 2003

Data Comparison - 1 February 2003

Results of Comparison of Bulk Method-derived Surface Fluxes: 27 January 2003: Differing total heat flux values likely due to difference in in relative humidity and wind speed measurements. Differing wind stress values likely due to 10-meter wind speed difference. τ = cDu102

10-Meter Normalized Parameters Bulk Method Derived Surface Fluxes 27 January 2003 Input Parameters 10-Meter Normalized Parameters Bulk Method Derived Surface Fluxes   Ship Plane Air Temp (C) 14.1 14.9 Temperature 14.8 Sensible Heat Flux (W/m2) -2.3 -4.3 Pressure (mbar) 1018.7 1012.2 Potential Temp (K) 287.4 288.0 Latent Heat Flux 3.0 20.9 Relative Humidity (%) 94.4 66.3 Wind Speed (m/s) 5.0 3.5 Total Heat Flux 0.7 16.6 Sea Surface Temp (C) 13.8 13.6 Specific Humidity (g/kg) 9.4 7.4 Drag Coefficient 0.0010 0.0008 5.2 4.2 Wind Stress (N/m2) 0.0304 0.0118 Height of Ob (m) 14 20.7

Results of Comparison of Bulk Method-derived Surface Fluxes: 1 February 2003: Valid comparison impossible due to height of aircraft data.

10-Meter Normalized Parameters Bulk Method Derived Surface Fluxes 1 February 2003 Input Parameters 10-Meter Normalized Parameters Bulk Method Derived Surface Fluxes   Ship Plane Air Temp (C) 12.9 12.4 Temperature 13.0 Sensible Heat Flux (W/m2) 5.2 -6.3 Pressure (mbar) 1015.6 985.8 Potential Temp (K) 286.2 286.3 Latent Heat Flux 142.7 394.8 Relative Humidity (%) 77.7 39.9 Wind Speed (m/s) 18.7 22.0 Total Heat Flux 147.9 388.5 Sea Surface Temp (C) 13.3 Specific Humidity (g/kg) 7.2 4.3 Drag Coefficient 0.0017 0.0019 19.3 26.9 Wind Stress (N/m2) 0.7466 1.115 Height of Ob (m) 14 81

Comparison of Measured Wind Fields: Ship Data: - Plotted every 15 minutes Aircraft Data: - Plotted every minute

Ship Plane

Ship Plane

Ship Plane

Ship Plane

Ship Plane

Ship Plane

Ship Plane

Ship Plane

Results of Comparison of Measured Wind Fields: - Offshore winds show clockwise turning with increasing elevation consistent with Ekman Theory as described in Holton (1992). - Nearshore winds show terrain effects. - Ship data likely a combination of spatial and temporal variability.

Recommendations for Future Studies: - Specifically design an experiment to collect a significant amount of temporally and spatially coincident data sufficient to quantitatively describe biases. - Ensure careful calibration of sensors before experiment. - Ensure aircraft flies at a consistently low altitude to ensure collection of data within the surface layer.

Conclusions: - Aircraft data are a powerful tool for REA but must have some ground truth. - Biases must be carefully studied for data to have any validity for data assimilation purposes.

References Guest, P., sfcfluxoc3570.m, 1997. Matlab program.   Guest, P., windvector.m, 2003. Matlab program. Holton, J. R., An Introduction to Dynamic Meteorology. Academic Press, San Diego, 1992. Naval Oceanography Program Operational Concept, March 2002, 48 pp. Smith, S.D. 1988: Coefficients of sea surface wind stress, heat flux, and wind profiles as a function of wind speed and temperature. J. Geophys. Res, 93, 15,467-15,472.