TAFTS: Atmospheric Profile Uncertainty and Continuum Contribution

1. TAFTS: Atmospheric Profile Uncertainty and Continuum Contribution Ralph Beeby Paul Green, Juliet Pickering 29th September 2010

2. Outline • Introduction • Atmospheric profiles • Uncertainty in profiles; calculating equivalent uncertainty in radiance • Comparison: uncertainty in profiles from B400 against simulated changes in continuum strength • Conclusions

3. Introduction • TAFTS (Tropospheric Airborne Fourier Transform Spectrometer) used to measure in-situ far-infrared atmospheric radiances during CAVIAR field campaigns • Aim: to use TAFTS measurements to measure the water vapour continuum as part of CAVIAR • Need to compare TAFTS spectra with simulations based on existing line databases • LBLRTM (Line by Line Radiative Transfer Model): • - can easily adjust strength of continuum absorption within this model • - can use real atmospheric measurements as input to model • - includes Analytic Jacobian routine – calculating sensitivity of simulation to uncertainties in profile • Would a change in continuum absorption be greater or smaller than the change in radiance due to uncertainties in profile?

4. Atmospheric Profiles • LBLRTM takes a 1D atmospheric profile as input • Radiosondes, dropsondes and ECMWF data used to generate a ‘best estimate’ of profile for Camborne flights • Basic measurement uncertainty of ±2%RH and ±0.2oC from sonde measurements • Additional uncertainty due to separation of sondes from aircraft, i.e., • Separation of sonde from aircraft • Variation of profile with time and space  “Representation Error” • Other instruments onboard FAAM aircraft can be used to measure temperature and water vapour content

5. Variability of Atmospheric Profiles • 2 x Rosemount Temperature Probes (T), General Eastern Dewpoint Hygrometer (RH) • How does relative humidity vary over the course of a level run? • Have hygrometer data for five levels in model atmosphere – what about the other 144? • Standard deviation of RH appears to be roughly proportional to magnitude RH in profile – use this to extrapolate standard deviation for all levels in profile • Have since calculated similar standard deviations for all flights in Camborne campaign – correlation seems to hold!

6. dR/d log[vmr(H2O)] / mWm2sr.cm-1/log[vmr] Wavenumber / cm-1 Calculating Equivalent Uncertainty • Analytic Jacobian: calculates ∂R/∂x for each level and each wavelength, where R is radiance and x is the parameter of interest (RH or T in this case) • Indicates how sensitive the spectrum will be to a given change in parameter x at each level • So to calculate error: multiply ∂R/∂x by randomised RH/T uncertainty at each level, sum contribution from all levels between boundary (surface or TOA) and observer • Compare with LBLRTM spectra in which the foreign continuum absorption strength has been adjusted

7. Comparison: Upwelling Radiance

8. Comparison: Downwelling Radiance

9. Conclusions • Compared uncertainty in atmospheric profiles with uncertainty in continuum strength • Equivalent change in radiance simulated using LBLRTM (continuum) and calculated from Jacobian routine using flight data (profile) • Longer wavelengths less sensitive both to profile uncertainty and changes in continuum in terms of radiance • Profile uncertainty more significant in drier region of atmosphere around 20,000ft at higher wavenumbers (shorter wavelengths) • Continuum contribution more sensitive in wetter regions, particularly for downwelling radiation • Use this as a guide to which TAFTS data to use to look for continuum signal, e.g., 34,000ft run, around 238cm-1 downwelling, 5,500ft around 365cm-1 downwelling