Working Together on the Stratosphere: Comparisons of RO and Hyperspectral IR Data in Temperature and Radiance Space

Transcription

1 Working Together on the Stratosphere: Comparisons of RO and Hyperspectral IR Data in Temperature and Radiance Space Michelle Feltz, Robert Knuteson, Johannes Nielsen 1, Lori Borg, Thomas August 2, Tim Hultberg 2, and Antonia Gambacorta 3 UW Madison SSEC / CIMSS, ROMSAF 1, EUMETSAT DARMSTADT 2, NOAA STAR Sept. 2017, Estes Park, CO Joint COSMIC 10 th Data Users' Workshop & IROWG-6

2 Roadmap Motivations Methods Results 1] IR sounder temperature retrieval assessment 2] NASA AIRS and UCAR COSMIC 6 yr comparison 3] ROMSAF GRAS temperature assessment 4] UCAR COSMIC version assessment Conclusions Paths Forward

3 Motivations Upper-air temperature is an Essential Climate Variable according to the WMO Two technologies offer the potential for recording climate quality stratospheric benchmark measurements as defined by the NRC decadal survey (2007): 1] radio occultation (RO) 2] hyperspectral infrared sounders (IR sounders**) This work compares these two independent measurement techniques in order to assess their differences within the stratosphere **Use of IR sounder in this presentation refers to hyperspectral IR sounders

4 Methods: Matchup Scheme Individual Matchup Case IR sounder fields of view averaged to create profile GRAS RO profile location Use profile-to-profile matchup method Accounts for RO profile geometry and horizontal resolution <1 hr time criterion FOR MORE DETAILS: Feltz, M. et al. (2014), A methodology for the validation of temperature profiles from hyperspectral infrared sounders using GPS radio occultation: Experience with AIRS and COSMIC, JGR, doi: / 2013JD

5 Methods: Matchup Scheme Matchup Distributions DJF ( ) GRAS-A / CrIS GRAS-A / IASI-A (thinned) Orbital mechanic differences Method applicable to data from different platforms/processing centers Distribution and number of matchups depends on orbital mechanics Previously used datasets: RO: UCAR COSMIC, JPL COSMIC, ROMSAF GRAS, IR: NASA AIRS, EUMETSAT IASI, NOAA CrISNUCAPS,

6 Methods: Radiance Calculations Use OSS fast RTM Radiances & temperature Jacobians calculated for 15um CO 2 absorption region (represents UTLS) Inputs: ERA-Interim, NOAA CarbonTracker Temperature Jacobians are used to assign height levels to radiances Methodological uncertainty is larger for channels with more weight from above 10 hpa due to the extent of the RO profile heights Focus on channels with weight between ~ hpa

7 Result 1: IR Sounder Assessment Colored by IR instrument: NOAA CrIS NUCAPS NASA AIRS v6 EUMETSAT IASI v6 10 IR Sounder UCAR COSMIC Dry Temperature DJF Tropics ( ) Bias ( ) Stdev. (- - -) 10 Apply Averaging Kernels Pressure (hpa) RO used as a common reference to compare operational IR retrievals Averaging kernels should be applied to move products to a common vertical grid and leads to good agreement (< 0.5 K) between hpa RO successfully used to assess IR sounder error characteristics FOR MORE DETAILS: Feltz, M. L., et al. (2017), Assessment of NOAA NUCAPS upper air temperature profiles using COSMIC GPS radio occultation and ARM radiosondes, J. Geophys. Res. Atmos., 122, doi: /2017jd

8 Result 2: UCAR COSMIC v2010 vs. AIRSv6 (6-years) 35 hpa: AK*(COSMIC Dry-AIRS) Temp bias cm -1 : AIRS calc AIRS obs. BT bias COSMIC calc AIRS obs. BT bias Robust-Lowess Filtered Time Series AIRS calc - obs BT bias within 0.5K for all lat. zones à implies no large methodological errors COSMIC calc AIRS obs BT bias within 1K in tropics/mid-lats and 2K at poles seasonal dependence similar magnitude to AK*(COSMIC-AIRS) temp à suggests COSMIC temp is dominating contributor to 35 hpa AK smoothed temp diff IR radiances have ~0.5 K systematic uncertainty (Tobin, JGR, 2014) further investigation needed in attribution of seasonal differences Feltz, M. et al. (2017), Assessment of COSMIC radio occultation and AIRS hyperspectral IR sounder temperature products in the stratosphere using observed radiances, J. Geophys. Res. Atmos., 122, doi: /2017jd

9 Result 3: ROMSAF GRAS vs. IASI, CrIS BTs ROMSAF GRAS BTs compared to IASI and CrIS observations GRAS-A vs. IASI-A GRAS-B vs. IASI-B GRAS-A vs. CrIS GRAS-B vs. CrIS Results from four matchup datasets were consistent (w/in ~0.25 K, shared general characteristics) Total BT uncertainty estimated to assess agreement of RO and IR BTs Based on IR stochastic uncertainty RO stochastic uncertainty Methodological uncertainty

10 Result 3: ROMSAF GRAS vs. IASI, CrIS BTs Wet and background (bg) BT stats show similarity Wet and bg temp difference may have too high vertical resolution Dry BT bias often larger than wet/bg bias, reach largest values at ~20 hpa negative minima in summer solstices, positive maxima in winter solstices GRAS-B IASI-B observed BTs ( ) Bias (bold markers) Stdev (light markers) Stochastic Unc. (error bars) JJA DJF Wet/bg BT stdev. typically constant with height, roughly 0.5 K agrees with BT unc. in mid-lats/polar winters slightly smaller than expected in polar summers (by ~0.1 K), slightly larger in tropics (by ~0.1 K) Dry BT stdev. grows with hgt. over hpa larger than BT unc. for all zones for channels with contributions from above 70 hpa à BT uncertainty estimate does not account for stochastic error sources of the dry temperature

11 Result 4: RO Processing Version Assessment UCAR COSMIC v2013 UCAR COSMIC v2010 *Vertical lines represent span of WF COSMIC AIRS observed BT Bias (2011) DJF BT Bias: - decreased in Arctic btwn hpa by up to 0.5 K - increased slightly in Tropics by max of ~0.2 K btwn 10 1hPa Update improves bias through most seasons, heights, and lat. zones with exception for Tropics where cold bias is increased in some seasons When 0.5 K used as systematic uncertainty for IR sounder, then conclusion that UCAR v2013 dry temp is an improvement upon v2010 can be made

12 Conclusions Result 1: UCAR COSMIC dry temp used as common reference to assess IR sounder retrieval errors. Result 2: 6 year comparison of UCAR COSMIC vs. AIRS observed BT bias showed seasonal dependency at 35 hpa. COSMIC BT bias was similar magnitude as temp difference and reached over the 0.5 K IR measurement unc in some regions à further investigation on attribution of seasonal variations is needed. Result 3: ROMSAF GRAS BTs were compared to IASI and CRIS observations using an estimated BT uncertainty. Overall reasonable agreement seen between GRAS and IR BTs. Largest inconsistency seen in increased dry temp standard deviation above 70 hpa à need investigation. Regions of increased biases, in particular polar regions around solstices and lower stratospheric tropical channels should be investigated. Result 4: AIRS observations used to assess UCAR COSMIC processing version update. COSMIC v2013 showed improved BT bias agreement with AIRS over large majority of seasons, particularly the poles.

13 Paths Forward Investigate areas of concern and interest as noted from previous studies e.g. seasonal dependent biases in polar zones, increased dry temperature standard deviations, Take into account challenges of radiative transfer, IR and RO measurement difficulties à What can we attribute the differences of IR and RO to?? Look at other IR channels which represent the lower atmosphere Continued collaboration between hyperspectral IR sounder and RO communities in hopes for fruitful insights

14 Working Together on the Stratosphere: Comparisons of RO and Hyperspectral IR Data in Temperature and Radiance Space M. Feltz

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