GLAS Team Member Quarterly Report

Transcription

1 GLAS Team Member Quarterly Report Thomas A. Herring, Katherine J. Quinn, An Nguyen, Monchaya Piboon Massachusetts Institute of Technology Period: 4/1/2002 to 6/30/2002 Options for Estimating Multiple Scattering Effects for ICESat Altimetry K. J. Quinn Simulations performed by the GLAS Atmospheric Data Products team members have shown that cloud multiple scattering (MS) of the laser pulse will stretch the return pulse, producing an apparent delay in the altimetry measurement. This bias may be as large as tens of cm [Duda et al, 2001]. The MS biases are potentially large enough such that we must have a way of detecting those laser returns which are significantly effected by MS, and hopefully be able to estimate the size of the bias. Based on the scattering simulations performed by Duda et al [2001], the magnitude of the MS biases are primarily dependent on cloud height, cloud optical depth, particle size, particle shape, and receiver field of view. Delays are largest for low altitude clouds (< 2 km) with particle radii 3-20 microns. The Duda paper examines mean path delay as a function of all the above mentioned parameters, it is the primary reference for GLAS multiple scattering calculations. There are some points to keep in mind when considering the delays reported in the Duda study. It should be noted that the delays are calculated using the offset in the pulse centroid. Centroid analysis is sensitive to the asymmetric long tail that multiple scattering produces in the return pulse. The GLAS ranges will be calculated using a gaussian fit to the transmitted and received pulses. Section 4 of Duda et al [2001] does examine the effect of using a gaussian fit and finds that such an analysis greatly reduces the effect of multiple scattering, down by a factor of 3-5, maybe more depending on the cloud height and particle radius. There may be other ways of analyzing the return pulse shape that will help detect MS (e.g. skewness) or reduce its effect. The scattering phase function used also has a significant effect on the MS delays, especially for low cloud heights. The scattering phase function is primarily determined by particle shape.

2 Duda et al [2001] examined this effect, the differences in path delay can range from 2 to 20 cm for 1 km high clouds (optical depth 0.5 and cloud thickness 750 m). The scattering phase function used for the simulations on other the parameters was that for ice spheres, this is the phase function which has the largest delay for low clouds. Determining which phase function is appropriate will require further study, it may be possible that different phase functions will be appropriate given different conditions. Given the parameters that effect the magnitude of the multiple scattering bias, i.e. cloud height, cloud optical depth, particle size, and particle shape, we require a method of measuring these parameters. The ideal method is to use the ICESat atmospheric data products, as calculated using the green channel of the GLAS instrument. These atmospheric measurements are made at the same time and location as the altimetry laser pulses and contain most of the information needed to estimate the MS bias, except for explicit particle size and shape. The multiple scattering code designed for GLAS uses a climatological model of particle size which depends on location, time of year, and cloud height. However, there is some concern about the reliability of the green channel detectors. Therefore we require secondary methods for determining the MS cloud parameters. We believe second best option for determining cloud properties is the Moderate Resolution Imaging Spectroradiometer (MODIS). This instrument is on the EOS Terra and Aqua satellites, launched in 1999 and 2002, respectively. MODIS covers the entire globe approximately once per day and uses 36 spectral bands from the visible to thermal infra-red. The spatial resolution of the spectral bands is 1000m, except for a few higher resolution bands (250m and 500m). A detailed description of the instrument and its characteristics is given in Barnes et al [1998]. MODIS is designed to measure cloud, aerosol and water vapor properties. These atmospheric data products of MODIS are described by King et al [2002] and the cloud algorithms are described in detail by Platnick et al [2002]. The MODIS cloud measurements contain most of the information required to calculate the multiple scattering bias using the methods described in Duda et al [2001]. There is a well validated cloud mask algorithm that will allow us to determine whether multiple scattering will be present, i.e. no cloud, no multiple scattering. For night time scenes MODIS can measure cloud top pressure, temperature, and effective emissivity, as well as whether the cloud is ice, water, or a combination. By using NCEP atmospheric analyses we may convert cloud top pressure into

3 heights. For day time scenes MODIS also measures optical thickness and effective particle radius. The difference in night and day time measurements is due to the fact that MODIS is a passive sensor, as opposed to the active sensing of the GLAS atmospheric channel. The biggest drawback is that the measurements are not at the same time and location as the ICESat altimetry measurements. The MODIS Level 2 swath data is at relatively high spatial resolution, 1-5 km, however there is only a remote chance the MODIS and ICESat will be coincident during the operational phase of the ICESat mission. The MODIS Level 3 data will be aggregated to daily, 8 day, and monthly grids at 1 by 1 degree resolution. We will be using the daily grids. Note that there is a concern the optical thickness derived over polar regions may be anomalously large due to problems with the MODIS algorithms over snow and ice. Further study of the accuracy of MODIS measurements of polar regions needs to be done. If the GLAS atmospheric channel measurements and the MODIS cloud data are both unavailable we might be able to use the cloud data produced by the NCEP global analyses. NCEP reports three different cloud layers, high, mid, and low, and for each layer gives percentage coverage, top and bottom pressure, and top and bottom temperature. The accuracy of the NCEP cloud data will need to be studied, it may only be useful for determining whether multiple scattering is likely to significantly effect a return pulse but not for estimating the scattering bias. The 90 day validation phase of the ICESat mission will be essential for clarifying the issues surrounding the multiple scattering bias. As part of the GLAS atmospheric products validation there is already a plan to have some coincident orbit tracks with either the Terra or Aqua satellites, allowing direct comparisons with MODIS. The 8 day repeat track provides a perfect set of data for studying the multiple scattering effect. Hopefully different repeat tracks will have different cloud conditions. Given that there will be negligible elevation changes over an eight day period, any changes in height will be primarily due to changes in the multiple scattering delay. We may even collect enough data during the validation phase to create empirical algorithms that correct for the multiple scattering delay, using MODIS measurements and NCEP model data. Barnes, W. L., T. S. Pagano, and V. V. Salomonson, Prelaunch characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AM1, IEEE Trans. Geosci. & Rem. Sens., 36, Duda, D. P., J. D. Spinhirne, E. W. Eloranta, Atmospheric multiple scattering effects on GLAS

4 altimetry - Part 1: Calculations of single pulse bias, IEEE Trans. Geosci. & Rem. Sens., 39, , King, M. D., W. P. Menzel, Y. J. Kaufman, D. Tanre, Bo-Cai Gao, S. Platnick, S. A. Ackerman, L. A. Remer, R. P. Pincus, and P. A. Hubanks, Cloud, aerosol and water vapor properties from MODIS: preliminary results from Terra, IEEE Trans. Geosci. & Rem. Sens., submitted May, Platnick, S. M. D. King, S. A. Ackerman, W. P. Menzel, B. A. Baum, R. A. Frey, The MODIS cloud products: Algorithms and examples from Terra, IEEE Trans. Geosci. & Rem. Sens., submitted April, 2002.

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13 4000 Variogram and Model 3000 =0.4 2 h 0.26 (m 2 ) Distance ( o ) (m 2 ) Distance ( o )

14 A Latitude ( o ) o ) B Latitude ( o ) o )

15 0.5 dhdt profiles over Martian poles Nk Nm Sk Sm dh(m) o ) 1 North pole dhdt profiles with trend dh (m) o ) 1 South pole dhdt profiles with trend dh (m) o )