May 10, 2004Aeronet workshop Can AERONET help with monitoring clouds? Alexander Marshak NASA/GSFC Thanks to: Y. Knyazikhin, K. Evans, W. Wiscombe, I. Slutsker.

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Presentation transcript:

May 10, 2004Aeronet workshop Can AERONET help with monitoring clouds? Alexander Marshak NASA/GSFC Thanks to: Y. Knyazikhin, K. Evans, W. Wiscombe, I. Slutsker and B. Holben Supported by: NASA Radiation Science Program

May 10, 2004Aeronet workshop AERONET Aerosol optical depth (from Cordoba-CETT, Argentina) 22 March, 2000 Clouds

May 10, 2004Aeronet workshop Outline Overview of cloud optical depth retrievals from ground- based radiometers; Main part: Cloud optical depth retrievals from Cimel’s radiances, examples, comparison with other surface retrievals at the ARM site; Surface inhomogeneity, sensitivity study; Local climatology of several Aeronet sites Testing with simulated clouds; Summary/Conclusion

May 10, 2004Aeronet workshop Ground-based retrieval downward radiance downward flux upward radiance (flux) Common approach is to use downward fluxes: broadband pyranometers (Leontieva & Stamnes, 1994; Boers, 1997) narrowband radiometers (Min and Harrison, 1996, Min et al., 2003) from Barker and Marshak, JAS 2001 computed by DISORT: g=0.85,  0 =1,  surf =0.2

May 10, 2004Aeronet workshop Clouds with Low Optical (Water) Depth “CLOWD” –Optical depth is the most fundamental cloud optical property –Solar radiation is most sensitive to changes in cloud optical depth at low optical depths –Over 50% of the warm liquid water clouds at the SGP site have LWP < 100 g m -2 –MWR’s uncertainty is g m -2 (i.e., errors of 20% to over 100%) –Aerosol indirect effect research needs accurate measurements of LWP and effective radius ARM IS UNABLE TO ADEQUATELY OBSERVE OVER HALF OF THE CLOUDS OVERHEAD !! Courtesy of Dave Turner, PNNL Presentation at the ARM STM

May 10, 2004Aeronet workshop Intercomparison between dif. retrievals for 14 March 2000 (Variable Thickness Stratus Case) Results from 14 Mar in the ARM 2000 Cloud IOP at the ARM SGP site, a day when the cloud was particularly stratiform and uniform Raman lidar backscatter Radar reflectivity comparisons among many volunteered methods for retrieving the low LWP 20:44 courtesy of Dave Turner, PNNL Presentation at the ARM STM

May 10, 2004Aeronet workshop Ground-based retrieval; zenith radiance from simulated 3D clouds

May 10, 2004Aeronet workshop Objectives from Michalski et al., 2002 Pilewskie’s SSFR within rad (640 m) from the CART site flying at 300 m on April 5, 2000 X X NIR RED X BLUE to exploit the sharp spectral contrast in vegetated surface reflect. across 0.7 µm to retrieve cloud properties from the Cimel’s measurements

May 10, 2004Aeronet workshop Cimel radiance measurements (GSFC, Bld. 33): four channels (440, 670, 870, and 1020 nm) (c) Transition between (a) and (b): sharp changes in I around cloud edges; the “order” of I between all four channels rapidly changes from cloudy to clear and back. (b) Surface and Clouds dominate: I 440 ≈ I 670 < I 870 ≈ I 1020 Cloud optical properties can be retrieved (a) Atmosphere dominates: I 440 > I 670 > I 870 > I 1020 Aerosol optical properties can be retrieved

May 10, 2004Aeronet workshop Two-channel cloud retrievals Satellite retrieval of  and r e from Nakajima-King, JAS 1990 Surface retrieval  and A c from Marshak et al., JAS 2004 points A & B are assumed to have the same cloud optical depth  but different cloud fraction A c

May 10, 2004Aeronet workshop 2D Look-Up Tables NIR vs. RED plane I RED = I RED ( , A c ) I NIR = I NIR ( , A c )  is cloud optical depth A c is “effective” cloud fraction clear cloudy

May 10, 2004Aeronet workshop Where are Cimel data points? July 28, 2002 ARM CART site Cimel measurements are taken around 13:45, 13:58 and 14:11 UT TSI is from 14:00 UT

May 10, 2004Aeronet workshop Retrieval examples August 8, 2002;18:00 UT CART site Cloud optical depth retrieved from: Cimel MWR ( Microwave Radiometer ) assuming r e = 7  m MFRSR ( Multi-Filter Rotating Shadowband Radiometer )

May 10, 2004Aeronet workshop Retrievals SZA=16.3 Time: 17:50 SZA=52.3 Time: 14:36 MFRSR data is courtesy of Q. Min

May 10, 2004Aeronet workshop Independent retrieval from BLUE and RED SZA: 29 Time: 20:36 SZA: 19 Time: 19:32 SZA: 64 Time: 14:00 SZA: 30 Time: 16:24 SZA: 47 Time: 15:17 MODIS surface albedo: BLUE: RED: NIR: Scatter-plot of RED_vs_NIR against BLUE_vs_NIR retrievals

May 10, 2004Aeronet workshop Local Climatology (broadleaf cropland: Bondville, IL) MODIS srf. albedo 670 nm MODIS srf. albedo 870 nm

May 10, 2004Aeronet workshop Local Climatology (Santa Barbara, CA: 2003) Version 0 cloud optical depth product Cloud optical depth “Effective”cloud fraction RED&NIR vs. BLUE&NIR retrievals

May 10, 2004Aeronet workshop Local climatology ARM CART cite Version 0 optical depth product RED&NIR vs. BLUE&NIR retrievals

May 10, 2004Aeronet workshop Seasonal applicability ARM CART site, OK Bondville, IL Surface albedo NDVI

May 10, 2004Aeronet workshop How good is the retrieval? Sensitivity to Surface Albedo July 3, 2002, ARM CART site If the uncertainties in surface albedo have the same sign, the algorithm performs well. If the NIR albedo is overestim. but the RED albedo is underestim., errors in the retrieved  are not severe. In the opp. case, the algorithm underestim. multiple refl. in the bright band and greatly overestim. . + + in % courtesy of A. Trishchenko from LANDSAT

May 10, 2004Aeronet workshop How good is the retrieval? Simulations using stochastic cloud models

May 10, 2004Aeronet workshop Results scatter plots of “retr.” vs. “true”  Total STATISTICS (A c =81%)  (true)  (retr) mean std pixel-by-pixel error:3.0

May 10, 2004Aeronet workshop Cumulative error histograms 3 75% pixels have errors < 3

May 10, 2004Aeronet workshop Summary The Main Ideas Cimel measures zenith radiance when the Sun is blocked by clouds; use two wavelengths: one in RED (670 nm) [or in BLUE (440 nm)], where vegetation albedo is low, and one in NIR (870 nm), where vegetation albedo is high retrieve cloud optical depth (and cloud fraction) using the NIR vs. RED plane The Results (so far) looks promising; it largely removes 3D effects; it is not the final answer but a big improvement against single- wavelength retrievals; can fill (cloud) gaps in AERONET aerosol optical depth retrievals and estimate (effective) cloud fraction; version 0 cloud optical depth product will be soon available for distribution

May 10, 2004Aeronet workshop Can AERONET help with monitoring clouds? Alexander Marshak NASA/GSFC Thanks to: Y. Knyazikhin, K. Evans, W. Wiscombe, I. Slutsker and B. Holben Supported by: NASA Radiation Science Program

May 10, 2004Aeronet workshop Dates with the cloud mode data Bondville: July present Cartel:July May 2002 Egbert: July Jan GSFC:Dec Dec Harvard Forest:July Dec SGP CART:Oct March 2004 Shirahama: Oct May 2002 UCSB:May present

May 10, 2004Aeronet workshop NDCI Normalized Difference Cloud Index

May 10, 2004Aeronet workshop 1D Calculations

May 10, 2004Aeronet workshop Cloud observations Normalized radiance, NDCI and cloud optical depth zoom 1D retrieval

May 10, 2004Aeronet workshop How good is the retrieval? Surface Albedo at the ARM SGP site from Li et al., JGR from Michalski et al., 2002 Pilewskie’s SSFR within rad (640 m) from the CART site flying at 300 m on April 5, 2000 courtesy of A. Trishchenko from LANDSAT

May 10, 2004Aeronet workshop Local Climatology ( a few other locations) optical depth (effective) cloud fraction Egbert (2001) Cartel ( )

May 10, 2004Aeronet workshop Encouraging? LWP comparisons for March 14 th and 15 th Comparison of the Miller microbase algorithm for LWP (based on combining microwave and radar data) against all other volunteered results, for two days in the ARM 2000 Cloud IOP at the ARM SGP site. The cloud was very uniform and stratiform on both days. 20:44 courtesy of Dave Turner, PNNL