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Aquarius/SAC-D Mission Mission Simulators - Gary Lagerloef 6 th Science Meeting; Seattle, WA, USA 19-21 July 2010.

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Presentation on theme: "Aquarius/SAC-D Mission Mission Simulators - Gary Lagerloef 6 th Science Meeting; Seattle, WA, USA 19-21 July 2010."— Presentation transcript:

1 Aquarius/SAC-D Mission Mission Simulators - Gary Lagerloef 6 th Science Meeting; Seattle, WA, USA 19-21 July 2010

2 2 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA Mission Design and Sampling Strategy Global Coverage in 7 Days 4 Repeat Cycles per Month Global Coverage in 7 Days 4 Repeat Cycles per Month Sun-synchronous exact repeat orbit 6pm ascending node Altitude 657 km 3 beams 390 km wide swath. 76 x 94 km96 x 156 km 84 x 120 km Beams point toward the night side to avoid sun glint Salinity Data 150km, Monthly, 0.2 (pss) Mission Requirement Salinity Data 150km, Monthly, 0.2 (pss) Mission Requirement In Orbit Chec kout Launch

3 3 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA Data ProductDescription Level 1AReconstructed unprocessed instrument data Level 1BGeolocated, calibrated radiometer sensor units acquired at 0.12 second instrument cycle; Averaged and retained at 1.44 seconds. Geolocated, calibrated scatterometer sensor units acquired at 0.18 second instrument cycle; Averaged and retained at 1.44 seconds. Level 2AGeolocated, calibrated radiometer and scatterometer sensor units at 1.44 s sample at the surface, corrected for Faraday rotation, antenna pattern, atmosphere and sky reflections. Level 2BGeolocated SSS from L2A at 1.44 sec. Roughness correction (TB) from Scatterometer. Level 3Time-space objectively analyzed SSS on a standard Earth Projection with150 km smoothing scales; 7-days and monthly. Data Definitions Level 2 Science Data File, including ancillary data

4 4 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA Simulator Concept Simulate realistic Aquarius data including emission sources from the earth and sky. Test and improve science algorithms Test the end to end Aquarius Data Processing System (ADPS) Introduce errors and correction techniques Provide pre-launch practice data for science users

5 5 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA Simulator Approach Compute top of the atmosphere (TOA) brightness temperatures (Tb) through the radiative transfer model (RTM). Convolve TOA, sky sources (cosmic, galactic, sun, moon), and ionosphere Faraday rotation over full gain pattern to compute antenna temperature (Ta) Convert Ta to radiometer counts and telemetry stream through the radiometer calibration model and telemetry simulator. Test telemetry transmission through the ground system. Compute simulated Level 1, 2, 3 science data files through the Aquarius Data Processing System (ADPS) Analyze results

6 6 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA Two Simulator Activities Science Simulator New 12-month simulator, calendar year 2007 ocean is ready You can access the data now as Level 2 and Level 3 science data files. Operational Mission Simulator “real time” data processing of simulated data on a daily basis Daily data will be released through the Aquarius data website as if the mission were actually flying. Operational by the end of August 2010

7 7 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA Aquarius Algorithm Simulator +0.2 +0.1 0 -0.1 -0.2 -0.3 -0.4 +0.3 +0.4 38 37 36 35 34 33 32 39 Simulate surface Tb from OGCM SSS and SST fields for calendar year 2007 along the satellite orbit swath. Add the effects of the wind, atmosphere, ionosphere, solar flux, galactic reflection, rain, land and ice brightness temperatures, and the antenna gain. Add realistic errors for wind (1 m/s), SST (0.5 C) and instrument noise. Wind and SST erros have ~50 km de- correlation scale Synthesize the instrument and satellite data telemetry. Run the simulated data through the salinity retrieval algorithm, and compare with the OGCM input. Details in Frank Wentz’s talk on algorithms. 2007 mean SSS Mean input minus Retrieved Output Global mean bias is -0.014 psu. Land & ice interference (blue edge)

8 8 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA Standard Deviation Simulated Error 0.2 0.1 0 0.3 0.4 0.2 0.1 0 0.3 0.4 Weekly St Dev Error Monthly St Dev Error Global St Dev is 0.14 psu. Global St Dev is 0.07 psu. Errors increase toward high latitude (SST effect). Very favorable results that must be viewed with caution. Several unknowns are not included in the simulator: incomplete roughness model antenna gain unknowns galactic model error galactic reflection off rough surfaces heavy rain and more….. F. Wentz, Remote Sensing Systems

9 9 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA Year 2007 Simulation SSS Input To generate a realistic 2007 global SSS input field, we ran a modified HYCOM at GSFC for the 2007 calendar year, using NCEP reanalysis forcing (atmosphere fields and SST) Applied a linear SSS adjustment based on weekly Argo-based objectively analyzed SSS fields, 30-day relaxation time scale. Some Examples of monthly mean SSS after running the simulated on-orbit data through the retrieval algorithms on the processing system: –There are some spurious signals – do not take the SSS data too seriously –Seasonal variability is apparent May 2007 SimulatedOct 2007 Simulated

10 10 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA Two Level 3 Gridded Products Binned: Simple unweighted average of all data falling in a grid box Used for browsing and monitoring the data processor and sensor Smoothed: 150 km scale weighted objective analysis fields Intended to meet mission science requirements (150 km resolution, monthly average, 0.2 psu accuracy) BinnedSmoothed

11 11 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA Scatterometer Simulation PALS Airborne data, 2009, courtesy of S. Yueh, JPL Surface wind roughness is the largest single error source Aquarius includes an integrated radar scatterometer to make simultaneous ‘bore sight’ roughness measurements The simulator includes the analogous simulation of the four radar backscatter sigma-0 channels and wind speed retrieval More detail in Simon Yueh’s talk on scatterometer algorithms. January 2007 Simulated wind Speed Retrieval

12 12 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA Mission Simulator Changes and Additions from the 2007 Science Simulator New PALS high wind roughness model (see S. Yueh presentation) rather than WISE model NCEP daily 1/12 deg ice maps rather than RSS SSMI ice maps Galactic radiation is done with a finer resolution integration. CASA is now treated as a point source and is removed from the integration. Lunar reflection and solar backscatter off the sea surface are included Actual daily solar flux and ionosphere will be used rather than using 2001 values Real-time operational NRL HYCOM used for SSS input Updated SSS retrieval algorithms, data flags, and ancillary data “Real Time” processing with probably 3-4 days latency The same ancillary data fields (NCEP wind, SST, Sea Ice, etc) are used in the simulator and in the data processing algorithms

13 13 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA Ancillary Salinity The L2 Science data contains a variable called “Ancillary Sea Surface Salinity” (anc_SSS) as well as derived SSS For the simulators, anc_SSS is the SSS input, to compare with the derived SSS. The operational NRL HYCOM is being used for the new Mission Simulator. When the satellite is on-orbit, the NRL HYCOM will continue to be the source for the anc_SSS to compare with the satellite retrieved salinity. NRL HYCOM

14 14 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA Summary The 2007 Science Simulator is ready for you to use Your job is to: Download the data you need (L1, L2 or L3) Develop your software tools to read and process the data Analyze the data, and look for data anomalies, problems, errors, as well as the aspects related to your research Provide feedback to the project Do it soon! http://oceancolor.gsfc.nasa.gov/cgi/aquarius?sen=aq http://oceancolor.gsfc.nasa.gov/cgi/l3

15 15 19-21 July 2010 Mission Simulators – Lagerloef 6rh Science Meeting, Seattle, WA, USA

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