The Stratospheric Wind Interferometer for Transport Studies SWIFT SWIFT I. McDade, C. Haley, J. Drummond, K. Strong, B. Solheim, T. Shepherd, Y. Rochon, and the SWIFT Team

What is SWIFT ? © ESA

SWIFT is the SWITS S tratospheric W ind I nterferometer for T ransport S tudies it is a Canadian satellite instrument designed to make global stratospheric wind measurements between 15 and 55 km and provide simultaneous co-located ozone profiles. Very few satellite measurements of stratospheric winds exist, so this is something quite unique and of great interest to the international atmospheric science community SWIFT Chinook SWIFT is just about to start Mission Phase B/C for implementation on a Canadian Space Agency Small Sat mission called Chinook scheduled for launch in late 2010

SCIENCE OBJECTIVES OF SWIFT To provide global maps of wind profiles in the stratosphere in order to study: Atmospheric dynamics and stratospheric circulation Ozone transport from SWIFT’s co-located wind and ozone density measurements The potential of stratospheric wind measurements for improving medium range weather forecasts

Observational goals and required performance  Obtain global vector winds to an accuracy of 3-5 m/s between 15 km and 55 km  Simultaneously obtain ozone number densities to an accuracy of 5 % (15-30 km)  Vertical resolution 1.5 km  Horizontal sampling ~400 km along track  Continuous near-global coverage

SWIFT How does SWIFT work?

SWIFT SWIFT is based on the ‘Doppler Imaging Michelson’ concept already used by the WINDII instrument on UARS. visible WINDII measured Doppler shifts in the wavelengths of airglow emission lines in the visible region of the spectrum to determine winds in the upper mesosphere and thermosphere and made remarkable discoveries about atmospheric tides and mesosphere and thermosphere dynamics SWIFT mid IR SWIFT will do the same thing but use a single thermal emission line from ozone in the mid IR region to push this technique down into the stratosphere

SWIFT The Doppler Imaging Michelson concept as applied on SWIFT The wind produces a Doppler shift in the emission line A Michelson interferometer produces the Fourier transform (right) of the input line spectrum (left) The phase shift of a single fringe gives the ‘Line of Sight’ (LOS) wind speed as illustrated on the next slide Using etalon filters, a single thermal emission line (an ozone rotation-vibration line near 9  m ) is isolated as shown in the left panel

Phase measurement and the LOS wind speed The interferometer is phase- stepped through four positions, yielding I 1, I 2, I 3 and I 4 From these the phase is computed, and from this the apparent LOS wind speed This analysis is performed for each tangent height in the image field

SWIFT viewing geometry SWIFT viewing geometry (side view) Image field 1X2 degree (~ 50 km x 100 km)

SWIFT will take ‘pictures’ of bright line emission from ozone in the IR region

SWIFT Sample simulated SWIFT images for phase steps 1,2,3 & 4 without noise

SWIFT viewing geometry SWIFT viewing geometry (top view)

SWIFT For each tangent height in the limb image SWIFT obtains a LOS wind speed (after correcting for the satellite velocity and Earth rotation components) SWIFT By observing at two orthogonal (or near orthogonal) directions as shown in the next slide, SWIFT can resolve the wind speed and direction – i.e., measure the vector wind profiles

SWIFT SWIFT viewing geometry SWIFT measures ‘line of sight ’ wind speeds in two orthogonal directions Image field 1° x 2° (50 km x 100 km) made up of 81x 162 pixels each 0.64 km high/wide. Stratospheric coverage from 15 km to 65 km SWIFT on Chinook FOV 1 and 2 Orthogonal FOVs resolve full horizontal wind vector Spacecraft velocity means ~8 minute delay between orthogonal components

SWIFT SWIFT Retrieval algorithm Uses iterative Optimal Estimation with a forward model based on a SWIFT Instrument Simulator (SIS) and an atmospheric Radiative Transfer model, together with the Maximum a Posteriori (MAP) solver of Rodgers (2000), to find the FOV wind profile and ozone density profile most consistent with the observed phase-stepped images

MAP+DR MAP Unconstrained SWIFT SWIFT Illustrative retrieval noise standard deviations Wind and ozone random error standard deviations (lines) and sample retrieval errors from a single Monte Carlo realization/simulation (points) with measurement noise

Principal Investigator Ian McDade, York University, Toronto, Canada Assistant to P.I Craig Haley (York U.) Co.I. Co.I. Co.I. Co.I. Co.I Lead ID&C Lead GDR&SOC Lead GDV Lead GDA&M Lead ECUI&DA J.Drummond B. Solheim K. Strong T. Shepherd Y. Rochon (Dal. U. ) (York U.) (U. of T.) (U. of T.) (E. C.) Plus the other Co-Investigators and student members listed below: G. Shepherd, C. McLandress, W. Ward, D. Degenstein, R. Sica, W. Lahoz, C. Camy-Peyret, P. Rahnama, B. Quine, J. McConnell, E. Llewellyn, S. Turner, etc. ID&C = Instrument Development, Characterization and calibration GDR&SOC = Geophysical Data Retrieval and Science Operations Centre GDV = Geophysical Data Validation GDA&M = Geophysical Data Analysis and Modelling ECUI&DA = Environment Canada User Interface & Data Assimilation SWIFT SWIFT Science Team

SWIFT on Chinook in 2010

Extra slides

SWIFT SWIFT Solid model