Last week Dr. John Reagan gave a seminar talk about the CALIPSO Lidar and Airborne HSRL aerosol measurements. He presented an overview of the satellite, covered its launch, and discussed its products. CALIPSO is a satellite remote sensing instrument in a polar sun-syncronous orbit designed to measure aerosols and aerosol influences in the atmosphere. CALIPSO carries aboard the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. This is an active remote sensing device. A passive system which measures the reflected sunlight or emitted thermal infrared radiation. Therefore, an active system directs radiation towards the ground and measures the attenuated backscatter. This works good during the nighttime hours, but not so well during the daytime. This is due to thermal instability; when the sun’s radiation hits the satellite, it heats up and causes unknown changes in the optics, sensor, or electronics. This leads to issues with calibrating the sensor.

Dr. Reagan showed several of the “images” obtained from the CALIOP instrument. The instrument provides two dimensions of data: vertical and along-track. There is no cross-track information. In areas where there are clouds or other obstructions, the instrument is obviously unable to provide data below the obstruction. He talked about using the parallel and perpendicular channels of the 532nm band to do a rough classification of smoke versus dust particles. Dust particles are non-spherical, while smoke particles are smaller and more spherical in nature. This means that due to the radiative properties of non-spherical objects and the relative size between the aerosol and 532nm (the wavelength of CALIOP), the dust-like particles will provide a signal in both the parallel and perpendicular channels while the smoke will only show up in one.

There were several attempts to calibrate/validate the CALIPSO data. The first was using the AERONET [Holben et al., 1988] instrument network. AERONET is a ground-based aerosol measuring tool which can provide aerosol optical depth and has applications for radiative transfer modeling and validation of satellite aerosol retrievals. It is the last which was talked about in the seminar. Dr. Reagan talked about using the ratio of the backscatter ratio to the extinction ratio (hereafter Sa), using a technique called CRAM, to classify aersols into one of several large categories. Examples of these categories were sea salts and urban aerosols. He also spent time talking about validation with the HSRL, which is an airborne Lidar system.

One thing that Dr. Reagan mentioned, but did not discuss at length, was that MODIS has an aerosols product. There have been studies in the past that have attempted to compare MODIS data with an active remote sensing technique [e.g. He et al., 2006]. MODIS provides a product with a nadir GIFOV [groud instantaneous field of view] and GSI [ground sample interval] of 1km; CALIOP has a GIFOV of around 100m and a GSI of 333m. Also, MODIS provides no vertical information about the aerosols - it only provides aerosol optical depth information. The accuracy of the MODIS aerosol retrievals is not great over land; it experiences similar problems as CALIOP. The errors in the optical depth (dAOD) over land were found to be dAOD=±0.05±0.2*AOD [Chu et al., 2002]. These errors seem especially large for small optical depths, and the use of validating other retrievals will this product are questionable. Another satellite which is soon to go into orbit is Glory. Aboard Glory will be the Aerosol Polarimetry Sensor (APS) that will “help understand the climate-relevant chemical, microphysical, and optical properties and spatial and temporal distributions of human-caused and naturally occurring aerosols” [Mishchenko et al., 2004]. The APS aboard Glory will be another passive remote sensing system that will be able to be used for validation and calibration of current aerosol products.

References:

Chu, D. A., Y. J. Kaufman, C. Ichoku, L. A. Remer, D. Tanré, and B. N Holben, 2002, Validation of MODIS aerosol optical depth retrieval over land, Geophys. Res. Lett., 29(12), 8007, doi:10.1029/2001GL013205.

He, Q.S., Li, C.C., Mao, J.T., Lau, A.K.H., Li, P.R., 2006, A study on the aerosol extinction-to-backscatter ratio with combination of micro-pulse LIDAR and MODIS over Hong Kong, Atmospheric Chemistry and Physics, Volume 6, Issue 11, 2006, pp.3243-3256.

Holben, B.N., T.F. Eck, I. Slutsker, D. Tanre, J.P. Buis, A. Setzer, E. Vermote, J.A. Reagan, Y.J. Kaufman, T. Nakajima, F. Lavenu, I. Jankowiak and A. Smirnov, 1988, AERONET–A Federated Instrument Network and Data Archive for Aerosol Characterization, Remote Sensing of Environment, 66, 1-16.

Mishchenko, M.I., B. Cairns, J.E. Hansen, L.D. Travis, R. Burg, Y.J. Kaufman, J.V. Martins and E.P. Shettle, 2004, Monitoring of aerosol forcing of climate from space: analysis of measurement requirements, Journal of Quantitative Spectroscopy and Radiative Transfer, 88, Photopolarimetry in remote sensing, 149-161.

(No Ratings Yet)

 Loading ...

Related Posts:

Trackback URI |