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Lidar Study: HSRL Instrument Option

Lidar Study: HSRL Instrument Option. Study Team: Chris Hostetler, Matt McGill, Pete Colarco, Zia Ahmad Contributors: Rich Ferrare, Judd Welton, Brian Cairns, Jim Coakley, Graham Feingold, Detlef Müller. Multiwavelength HSRL: 3 β +2 α +3 δ

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Lidar Study: HSRL Instrument Option

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  1. Lidar Study: HSRL Instrument Option Study Team: Chris Hostetler, Matt McGill, Pete Colarco, Zia Ahmad Contributors: Rich Ferrare, Judd Welton, Brian Cairns, Jim Coakley, Graham Feingold, Detlef Müller

  2. Multiwavelength HSRL: 3β+2α+3δ Backscatter at 3 wavelengths (3β) : 355, 532, 1064 nm Extinction at 2 wavelengths (2α) : 355, 532 nm Depolarization at 3 wavelengths (3δ): 355, 532, and 1064 3β+2α technique enables retrievals of layer-resolved, aerosol microphysical and optical properties (Müller et al., 1999, 2000, 2001; Veselovskii et al.,2002,2004) Effective and mean particle radius Concentration (volume, surface) Complex index of refraction Single scatter albedo Retrievals involve several assumptions … but have been validated against in situ measurements in several case studies Anticipate that 3β+2α+3δ HSRL data extremely powerful in combined lidar-polarimeter retrieval Multiwavelength HSRL Option

  3. Lidar Study: HSRL Option Our charge: Assess value of the ACE HSRL instrument option in CTM and climate model improvement

  4. Dilemma • The kind of questions we would like to address are • To what extent will HSRL data improve • Estimates of forcing at TOA? • Estimates of forcing a the surface and throughout the column? • To what extent does the information on the profile of aerosol absorption improve • Modeling of the semi-direct effect (suppression of clouds and precipitation)? • Modeling of effect of absorbing aerosol on dynamics and stability? • To what extent will HSRL data enable • Assessment of model predictions of aerosol-cloud interactions? • Improvement of model predictions of aerosol-cloud interactions? • But modelers currently don’t have the tools or the funding to provide quantitative answers to these questions (at least not in the near term) • And these questions should be addressed in the context of the full ACE data set, not lidar only.

  5. Fallback So, what questions can we answer???I’m not sure, but what follows are some ideas for debate….

  6. Aerosol environment: sources, transport, removal processes • CTM predictions of global average AOT currently show good agreement among models and between models and observations • This was not the case before modelers had access to MODIS and MISR data. Prior to that models diverged widely on AOT. • However, models still diverge widely on partitioning of AOT among aerosol type: getting the right AOT for the different reasons. Questions: • Will global profile information on aerosol backscatter, extinction, effective radius, refractive index, and SSA enable modelers to improve prediction of vertical distribution of aerosol type, optical properties, and microphysics to uncertainty levels commensurate with the uncertainties in the HSRL profile retrievals? • If so, how much will uncertainties in model predictions of direct and indirect forcing decrease?

  7. Aerosol-Cloud Interactions • Assumption: climate models of the future will have much higher resolution and advanced capability for modeling aerosol-cloud interaction – i.e., effectively implementing global cloud-resolving models Questions: • At vertical and horizontal resolutions achievable from satellite, will the HSRL data contribute significantly to assessment of aerosol-cloud interactions in future models? • Will the data be useful in estimating the uncertainties in the models? • Will the HSRL data enable reduction in the uncertainties in the model? • Which parameters? • Is it possible to say by roughly how much? 2X? 5X? 10X?

  8. Aerosol-Cloud Interactions Question: • In broken cloud systems, can multi-wavelength HSRL data be effectively composited by distance from cloud to assess • Variation in aerosol microphysics as a function of distance from cloud? • Assessment of cloud edge effects for correcting biases in polarimeter and radiometer retrievals? Aerosol Extensive Parameters Aerosol Intensive Parameters

  9. Basic Aerosol Measurements • HSRL inherently more accurate than backscatter lidar • Internal calibration (airborne HSRL calibrated to ~1-2%) • Daytime calibration a significant issue for CALIPSO • Extinction and backscatter are measured independently: does not require assumption of extinction-to-backscatter ratio • Extinction more accurate • Backscatter also more accurate • Retrievals are more straightforward (relatively accurate Level-2 products can be computed in real-time) Questions: • How much more accurate are retrievals of backscatter, extinction, and depolarization from HSRL vs. backscatter lidar? • How much more accurate are inferences of aerosol type? • To what degree does HSRL improve layer detection? • Better calibration and more straightforward retrieval will enable improvement in layer finding and determination of layer top/bottom.

  10. Combined Retrievals • Our most accurate aerosol retrievals will likely be combined lidar-polarimeter retrievals Questions: • To what degree are vertically resolved microphysical retrievals improved • More robust in autonomous mode • More accurate • Reduce reliance on assumptions in 3β + 2αretrievals • Reduce horizontal or vertical averaging requirements • What conditions are required for combined retrievals? • Solar elevation angle • Near clouds • Surface types • Multi-layer cloud systems

  11. Discussion • We are soliciting ideas and priorities on the HSRL study. • We won’t get all of these ideas covered by the March deadline and are probably missing some other very good ones. • Modelers should be leading some aspects of this study: e.g., providing guidance on the use and value of the measurements in improving CTMs and climate models. • Modelers could indicate which aerosol parameters and which sampling strategies would have the most impact to reduce uncertainties in estimates and predictions of direct and indirect forcing, clouds, precipitation • Most modelers don’t have the time, funding, or tools to answer many of the questions we raise • We don’t have the power to commit the appropriate experts from the modeling community to these studies • Possible outcome: ROSES NRA element or directed funding for modeling and analyses of past data sets needed for ACE mission definition

  12. Backups

  13. Sampling vs. Information Content Question: • For improving CTMs and climate models which is more important • Improved statistics from MBL (reduction of sampling noise)? • Reduction of sampling biases via MBL? • Increase information content from multi-wavelength HSRL?

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