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This text explores dilemmas faced when comparing and calculating satellite radiances in the MODIS CO2-slicing algorithm. It delves into issues with clear-sky radiance bias adjustments, zonal means, and band calculations, addressing challenges and proposed solutions.
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Dilemmas in Comparing Observations and Calculations of Satellite Radiances (in the MODIS CO2-slicing algorithm) Rich Frey, Hong Zhang, Kathy Strabala, and Paul Menzel January 5, 2005 MODIS Science Team Meeting Aqua Collection 5 Cloud Top Pressure (MOD06CT): Uses 8-day clear-sky radiance bias adjustments - separate zonal means for ocean, day and night surfaces Uses “instrument” bias adjustment - constant in each of bands 33-36
CO2-slicing equation: Rcld(1) - Rclr(1) N(1) ∫pcld (1)dB(1) dp LHS = ----------------------- = ------------------------------- = RHS + Error Rcld(2) - Rclr(2) N(2) ∫pcld (2)dB(2) dp where 1and 2 are MODIS bands 34/33, 35/34, or 36/35 Traditionally, HIRS, GOES products use observations on LHS; RHS is calculated from NCEP 1-degree T(p), q(p), and forward radiance model. Dilemma #1: MODIS processing restraints allow only 1 pass through the data; how to get Rclr ? For MODIS, Rclr(1), Rclr(2) are calculated, adding an error term on the LHS. To mitigate this, we apply clear-sky radiance biases, as functions of geographic region and band (Collection 5). Work on the CHAPS (Collocated HIRS and AVHRR Products) algorithm in the mid-1990s indicated close agreement between CTP results when calculated clear-sky radiances were used with bias corrections.
Before Clear-sky Bias Adjustment (through Collection 4) 1) Absolute amounts of high clouds were comparable to HIRS values in the tropics 2) MODIS found 5-15% less high, thin clouds than HIRS in the mid-latitudes 3) Inspection of L2 data showed thinner cirrus often retrieved as middle or low cloud Terra LWIR bands are noisy (especially band 34), so ability to retrieve CTPs for high, thin clouds is somewhat compromised. Clear-sky radiance biases were attempted, but no positive results were realized. Aqua LWIR bands are less noisy and affords an opportunity for good characterization of global cloud top pressures.
Clear-sky Radiance Bias Correction Accumulate observed minus calculated clear-sky radiances over eight days observations based on cloud mask, calculations from forward model using NCEP gridded data, 25-km resolution, bands 33-36 Form 1-degree zonal means of differences (biases) ocean, land day, land night separately, 5-point running means day and night land data combined south of 60 south, ocean ice treated as land Band 35 Clear-sky Radiances from November 23-30, 2004
Dilemma #2: Clear-sky bias adjustment alone yields non-physical results Clouds “roll up” at the edges where cloud is thinner, some obvious cirrus not retrieved, too few valid CO2-slicing retrievals Consistent with clear-sky values being too warm While correcting a known bias, we discovered a new one
Evidence … Hand-picked observed clear-sky radiances lead to non-physical results Bias-adjusted calculated clear-sky radiances lead to similar non-physical results Even in cloudy skies, many observed cloudy radiances > calculated clear MODIS LWIR (33-36) observations are significantly warmer than AIRS, SHIS (D. Tobin, C. Moeller) Solution … Subtract 0.75, 0.50, 0.25 mw/m2*str*-1 from LHS for bands 36-33, respectively
Dilemma #3: What is the “instrument bias” ? Dilemma #4: How to correct Terra data?
Channel Pair Representing the Best CTP Retrieval Pink, cyan, and green are 36/35, 35/34, 34/33, respectively Before subtracting “Instrument Bias” After subtracting “Instrument Bias”
