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Consistent MSU Radiance Dataset for Reanalysis Cheng-Zhi Zou

Consistent MSU Radiance Dataset for Reanalysis Cheng-Zhi Zou. NOAA/NESDIS/Center for Satellite Applications and research. CFSRR First Advisory Board Meeting, NOAA Science Center, November 7, 2007. NOAA MSU Satellites. 4 channels to measure the atmospheric temperature profiles

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Consistent MSU Radiance Dataset for Reanalysis Cheng-Zhi Zou

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  1. Consistent MSU Radiance Dataset for Reanalysis Cheng-Zhi Zou NOAA/NESDIS/Center for Satellite Applications and research CFSRR First Advisory Board Meeting, NOAA Science Center, November 7, 2007

  2. NOAA MSU Satellites • 4 channels to measure the atmospheric temperature profiles • No cloud contamination • Each satellite has a life cycle of a few years • Each satellite overlaps With other satellites—good for bias correction • LECT gradually changes With time– orbital drift phenomenon Satellite Local Equator Crossing Time (LECT) vs time MSU Scan Pattern and footprint sizes

  3. Time series based on pre-launch calibrated radiance data • Different bias correction yield different trend results (Christy and Spenser, Mears and Wentz, Vinnikov and Grody, Zou et al.) • Reanalysis has its own bias correction procedure, how to ensure the reanalysis trend to represent the real atmospheric trend?

  4. Simultaneous Nadir Overpass Method to find SNO matchups: • Use Cao’s (2004) method to find the orbits that have intersections • Use time and location information in the 1B file to determine simultaneity between two pixels Schematic viewing the overpasses between two NOAA satellites

  5. SNO Locations

  6. MSU In-Orbit Calibration Process Cold Space T=2.73K MSU Sensor Warm Target Temperature is measured by PRT Earth Conceptual diagram of MSU observational procedure

  7. Level 0 Calibration (Cw, Rw) (Ce, Re) Radiance (R) Onboard Warm Target (Ce, RL) Earth View (Cc , 2.73K) Cosmic Cold Target Digital Counts (C)

  8. SNO Radiance Error Model k j Radiance Error Model for SNO Matchup K and J : • Consider colinearity between Zk and Zj • choose the coefficients that completely remove the warm target temperature contamination

  9. Tb comparison for SNO matchups After pre-launch calibration After SNO calibration

  10. Comparison Between Pre-launch and SNO calibration Time series differences for pre-launch calibration Std=0.1K Inter-satellite differences after SNO calibration std=0.04K

  11. Anomaly time series

  12. Independent validation dataset for reanalysis Website address: http://www.orbit.nesdis.noaa.gov/smcd/emb/mscat/mscatmain.htm • Datasets available: • Level 2 radiance:  pre-launch (operationally) calibrated •  SNO calibrated • Level 3 SNO calibrated gridded products: 2.502.50  pentad T2, T3, and T4, 1987-present  pentad anomaly T2, T3, and T4, 1987-present  monthly T2, T3, and T4, 1987-present  monthly anomaly T2, T3, and T4,1987-present

  13. Trend patterns T3 trend T23, Mid-tropospheric temperature trend, 1987-2006 T4, Lower Stratospheric temperature trend 1987-2006

  14. Remaining issues • Efforts needed to resolve short overlap problem • between NOAA 10 and 9 for accurate bias removal • more calibration coefficients (higher order calibration • equation) maybe needed to solve Channel 3 for • NOAA 11 and 12 • Different frequencies between MSU and AMSU

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