1. Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Monitoring of IR Clear-sky Radiances over Oceans for SST (MICROS) Alexander Ignatov 1 and XingMing Liang 2 1 NOAA/NESDIS/STAR, 2 Colorado State University/CIRA References 1. Introduction MICROS is a web-based Near-Real Time tool to monitor Model (Community Radiative Transfer Model, CRTM) minus Observation (AVHRR) biases in clear-sky brightness temperatures (BT) over oceans, produced by the Advanced Clear-Sky Processor for Oceans (ACSPO). MICROS has been in routine use since July 2008 with AVHRR data from NOAA-16, -17, -18, -19 and MetOp-A. Input to MICROS is global analysis SST (Reynolds, OSTIA) and NCEP/GFS upper air fields. 3. ACSPO versions tested in MICROS since July 2008  Introduce the MICROS system (Liang et al., 2009, 2010).  Test the improvements in ACSPO versions.  Demonstrate utility of MICROS to monitor satellite radiances over clear-sky ocean for stability and cross-platform consistency.  Preliminarily evaluate CRTM daytime performance using MICROS. 2. Objectives Weekly SST AVHRR SST CRTM r577 CRTM v.1.1 CRTM r577  Warm M-O biases are due to a combined effect of not included aerosols; using bulk SST (instead of skin); using daily mean Reynolds to represent nighttime SST; residual cloud.  Cross-platform DDs (e.g, Strow et al, 2008; Wang and Wu, 2008) in BTs and SSTs cancel out many errors (CRTM errors, uncertainties in input SST, GFS, missing aerosol, etc).  DD patterns suggest that they are mainly due to errors in sensor calibration and spectral response functions. Largest systematic errors are in N-18 Ch4 and N-19 (all bands).  A simple diurnal variability and bulk-to-skin model is needed to adjust Reynolds SST at night, to help more accurately estimate the cross-sensor biases using the DD technique. CRTM v.1.1  ACSPO v1.00: uses CRTM r577 in conjunction with Reynolds 1° weekly SST and NCEP/GFS 1° 6hr fields to produce model BTs; Fresnel’s surface emissivity model; Ordinary CRTM coefficients.  ACSPO v1.02: uses CRTM v.1.1 in conjunction with Reynolds 0.25° daily SST; Wu-Smith (1997) emissivity model; Planck-Weighted CRTM coefficients.  ACSPO v1.10: uses improved cloud mask (Petrenko et al., 2009). Also, day/night flag switches now at solar zenith angle of 90° (v1.00/1.02: 85°) Using CRTM v1.1 instead of rev577 improves the satellite view zenith angle dependencies, and brings NOAA-16 Ch3B in family (Liu et al., 2009). Using daily Reynolds instead of weekly SST in ACSPO v1.02 significantly improves global STDs. Note that NOAA-16 Ch3B remains out of family. Figure 1. Global distributions, histograms and view zenith angle dependencies of the M-O biases for 24 hours of nighttime data on 14 July 2008 for MetOp-A Ch3B. CRTM r577 4. Nighttime BT and SST Biases and Double Differences (DD) BT and SST Biases Double Differences (DD) V1.00 V1.02 V1.10 V1.00 V1.02 V1.10 V1.00 V1.02 V1.10 V1.00V1.02 V1.10  Inaccurate solar reflectance model used in CRTM v1 results in unrealistic cold M-O bias ~-20 K in the sun glint areas and a smaller warm bias ~+5 K outside glint in AVHRR Ch3B band centered at 3.7 μm.  Using a physical specular reflectance model (Breon, 1993; Gordon, 1997) dramatically improves the daytime M-O biases. Figure 2. Global M-O distribution and sun glint angle dependencies for NOAA18 Ch3B on 13 Dec 2008. (top) CRTM v1; (bottom) CRTM v2. Nighttime BT and SST biases are largely consistent (except for NOAA-16). Remaining short-term variability of several tenths kelvin is likely caused by residual instabilities in Reynolds SST. Double-differencing (DD) technique can help establishing cross-sensor calibration links and contribute to the Global Satellite-based Inter-Calibration System (GSICS). Cross-platform nighttime DDs are large and variable for NOAA-16 due to sensor calibration issues. For other platforms, DDs are typically within several hundredths kelvin, except for NOAA-18 Ch4 and NOAA-19 where DD~0.10-0.15K. Work is underway to reconcile the observed nighttime cross-platform DDs by improving AVHRR calibration, and incorporating a simple diurnal variability (e.g., Kennedy et al., 2007) and bulk-to-skin model (e.g. Donlon et al., 2002). The new reflectance model was proposed based on MICROS analyses and implemented in CRTM v2. MICROS: www.star.nesdis.noaa.gov/sod/sst/micros www.star.nesdis.noaa.gov/sod/sst/micros 5. CRTM daytime performance in Ch3B 6. Conclusion and Future Work Breon, F.M., 1993, RSE, 43, 179-192. Donlon et al, 2002: JClim, 15, 353-369. Gordon, H. R., 1997, JGR, 102, 081-017. Kennedy, J.J., P. Brohan, and F.B. Tett, 2007: GRL, 34. Liang, X.-M., A. Ignatov, and Y. Kihai, 2009a: JGR, 114. Liang, X.-M and A. Ignatov, 2009b: JGR, to be submitted. Liu, Q, et al, 2009: JTech, doi:10.1175/2009JTECHA1259.1. Petrenko, B., et al, 2009: 38th AMS Annual Meeting, Phoenix, AZ, JP1.12. Strow, L., et al, 2008: EUMETSAT, 15-17 Sep 2008. (http://www.ssec.wisc.edu/hsr/meetings/2008/presentations/ Larrabee_Strow.pdf )http://www.ssec.wisc.edu/hsr/meetings/2008/presentations/ Larrabee_Strow.pdf Wang, L. and X. Wu, 2008: GSICS Quarterly, 2, 4, 4-4. Wu, X. and W. L. Smith, 1997: Appl. Opt., 36, 2609–2618. V1.00 V1.02 V1.00V1.02 V1.10 V1.00V1.02 V1.10 V1.00V1.02 V1.10