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Calibration Scenarios for PICASSO-CENA J. A. REAGAN, X. WANG, H. FANG University of Arizona, ECE Dept., Bldg. 104, Tucson, AZ 85721 MARY T. OSBORN SAIC,

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Presentation on theme: "Calibration Scenarios for PICASSO-CENA J. A. REAGAN, X. WANG, H. FANG University of Arizona, ECE Dept., Bldg. 104, Tucson, AZ 85721 MARY T. OSBORN SAIC,"— Presentation transcript:

1 Calibration Scenarios for PICASSO-CENA J. A. REAGAN, X. WANG, H. FANG University of Arizona, ECE Dept., Bldg. 104, Tucson, AZ MARY T. OSBORN SAIC, NASA Langley Research Center, M.S. 475, Hampton, VA Objective This poster presents scenarios for calibration of the PICASSO-CENA 532 nm and 1064 nm lidar channels. The calibration approaches are presented, including uncertainty assessments and demonstrated calibrations obtained from LITE data.

2 Background and Strategy PICASSO-CENA is being developed as a partnership between NASA and the French space agency CNES and is planned for launch in early Calibration of the lidar is very essential to the quantitative retrieval of the aerosol and cloud properties in the PICASSO-CENA mission. Following the procedures employed for LITE, in situ calibration of the 532 nm lidar channel will be accomplished via normalization to high altitude, nearly molecular scattering regions. The molecular backscatter will likely be too weak and/or too aerosol contaminated to permit such calibration for the longer wavelength 1064 nm channel. Rather, calibration of the 1064 nm relative to the 532 nm channel calibration will be obtained via comparisons of the 532 nm and 1064 nm backscatter and integrated attenuated backscatter from known/quantifiable scatters such as cirrus clouds.

3 The lidar calibration factor or constant, C, appears in the lidar equation and normalized equation as follows: where E 0 = transmitted laser pulse energy r = range or distance from the lidar to the point of scattering P(r) = instantaneous lidar signal from range r  (r) = atmospheric backscatter coefficient (m -1 sr -1 ) T(r) = atmospheric transmittance through range r Molecular Normalization Calibration

4 The calibration constant may be extracted from the lidar signal P(r c ) obtained at a reference calibration range, r c, by where, in addition to the terms defined above,  m (r c )= molecular (Rayleigh) atmospheric backscatter (for the lidar wavelength) at range r c R(r c ) =  (r c ) /  m (r c ); total to molecular backscattering mixing ratio at range r c For r c selected to be around 30 km above ground, R(r c ) = 1 and T 2 (r c )  0.99 are reasonable approximations for 532 nm enabling accurate retrievals of C providing the signal uncertainty is sufficiently small and  m (r c ) can be accurately computed(driven by how accurately the air density can be determined). Using ancillary meteorological data along the satellite track, it is estimated that  m (r c ) can be determined within  3% uncertainty. PICASSO-CENA simulations predict that the shot-noise limited uncertainty in P(r) and X(r) for nighttime, negligible

5 background conditions and a pure molecular atmosphere at a height of 30 km above ground should be less than 2% for vertical averaging over 3 km and horizontal averaging of about 750 km. This should permit C 532 to be determined within  5% uncertainty. Results from LITE demonstrate that horizontal averaging over 1000 km and more without significant horizontal inhomogeneity biases is quite feasible. This is demonstrated in Fig.1 which shows retrievals of C 532 from LITE data for 300 m vertical averaging and 100 shot (~70 km) sequential horizontal averaging over a total horizontal extent of ~1000 km. The standard deviation of the mean for the total horizontal extent is less than 1%.

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7 Fig.2. The cloud image of orbit 24 from NASA, Langley Research Center.

8 1064/532 Ratio Calibration from Cirrus Cloud Returns Cirrus clouds offer good candidate targets by which the calibration ratio C 1064 /C 532 can be estimated from the ratio of the normalized returns for the two wavelengths, because, to first order, the backscatter and extinction should be nearly the same for both wavelengths. Also, as cirrus occurs at high altitudes, corrections for 1064/532 spectral transmittance differences between the satellite and the cloud top are relatively small and fairly predictable. The normalized cloud return, X c, defined as the total normalized return minus the non-cloud background normalized return, is given approximately by X c = CT 2 cT  c T 2 c where C = lidar calibration factor T 2 cT = round-trip transmittance to cloud top at range r cT  c = cloud backscatter for r > r cT T 2 c = cloud round-trip transmittance from r cT to r > r cT

9 Assuming  c T 2 c is the same for 532 nm and 1064 nm, the ratio of X c for the two wavelengths at any r within the cloud, or the ratio of the integrals of X c through the cloud for the two wavelengths, will be approximately For r cT at about 12 km above ground, the round-trip transmittance ratio is given approximately by Cirrus cloud returns from LITE, Orbit 24, have been analyzed to assess the feasibility of the cirrus cloud calibration approach. Orbit 24 was chosen because the C 1064 /C 532 calibration ratio was estimated from ground returns at Edwards AFB, thereby providing something to compare against. Figure 2 shows the LITE cloud image data used for this analysis. Example X c profiles for 532 nm and 1064 nm obtained from 10 shot averages and 150 m vertical and

10 averaging are shown in Figs. 3 and 4. The background for 532 nm follows a molecular scattering line, while the 1064 nm background is a vertical, system noise defined line. Also, the ratio X C1064 /X C532 ( normRatio) and the ratio of the integrals of X c ( intRatio) for this cloud example are shown in Fig. 5. The plots in Figs. 5 and 6 display the expected ideal behavior of both the normalized X c ratio and the ratio of the integrals at X c being equal and constant with height, with the integral smoothing removing some of the fluctuations exhibited in the X c ratio. Not all cases were so ideal and screening was required to identify other useable segments and useable height ranges within a segment. Other acceptable cases are shown in Figs. 7 and 8. Table 1 also lists the results for some 18 cloud cases (segments), where each numerical listing is the average over a useable height range identified for the particular segment (some segments have multiple useable height ranges). The averages for all cases yield little difference between the results for the X c ratio versus the ratio of the integrals of X c approaches. Multiplying these averages by 0.9 yields the estimates for C 1064 /C 532, as shown in the table, including the  one standard deviation limits from the averaging.

11 Table 2 shows a comparison of the LITE C 1064 /C 532 calibration ratios obtained by the cirrus cloud approach (mean of the two values in Table 1), pre-launch instrument specifications/measurements, and surface returns from the Rogers dry lake bed at Edwards AFB, CA. Table 2. LITE 1064/532 Calibration Determinations Calibration Determinations C 1064 /C 532 From Instrument Specifications 93 From Edwards Surface Returns 79  10 From Cirrus Cloud Returns 89  12

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18 Conclusions Calibration of the PICASSO-CENA 532 nm channel by molecular normalization, analogous to what was done for the LITE shuttle mission, is quite feasible and should yield calibrations with uncertainties of  5% or less. Calibration of the PICASSO-CENA 1064 nm channel in terms of, or as a ratio to, the 532 nm calibration factor by using cirrus cloud returns appears quite feasible. The accuracy with which this can be achieved is still open to question, but the results presented here suggest that it may be possible to reduce the uncertainty to ± 10% or less.


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