CrIMSS EDR Algorithm Improvements NGAS A&DP March 21, 2013

1. CrIMSS EDR Algorithm Improvements NGAS A&DP March 21, 2013

2. Summary of Current Status of CrIMSS Profile Retrievals • Retrievals generally good at this early stage of algorithm maturity • Global stats show retrievals meeting specification over much of the profile and most scene classifications • Yields for QC(1&4) (e.g. combined IR/MW) close to 50% • Some systematic biases observed in global stats • Microwave-only biased warmer and dryer than truth over land surfaces • IR/MW biased slightly cooler in clear sky conditions over ocean with larger cooler bias in partly cloudy conditions • IR/MW retrievals better than microwave-only over land and ice surfaces • In partly cloudy conditions, IR/MW bias typically diverges from microwave-only retrievals below 500 mb, especially for temperature retrievals

3. Focus Day Retrieval Results Suggest Following Areas Require Additional Tuning • Microwave and IR surface emissivity • Largest differences in retrievals relative to truth are near surface • Cloud-clearing • Largest differences in retrievals relative to truth for IR/MW occur below 500 mb • Largest divergence between IR/MW and microwave generally occur below 500 mb for partly cloudy conditions • Scene classification • Biases suggest some misclassification of clear and cloudy conditions

4. Near-term Plan (1/3) • Test with new IR and microwave noise LUTs using G-ADA Mx7.1 and evaluate impact for Sept 20 focus day • Expect reduction in yields especially for QC(1) retrievals • May require additional tuning of other LUTs and parameters to increase yields • Verify MW-only and MW+IR retrievals are the same under the cloudy scenes • Perform bias analysis for the partly cloudy land or ice mass scenes to understand reason(s) for larger bias

5. Near-term Plan (2/3) • Update Mx7.1 code with ‘quick’ code fixes as described in LaRC talk: • Fix cloud noise amplification factor (NAF) when NAF < 1 • Fix scene identification logic • Fix error in altitude calculation during post processing • Add precipitation algorithm from Ferraro’s group • Test additional code fixes within G-ADA environment

6. Near-term Plan (3/3) • Re-process all focus days using Mx7.1 G-ADA and evaluate consistency of performance • Re-process focus day with updated ATMS SDR antenna beam efficiency and scan angle bias correction coefficients • Expect minor performance impacts • Compare and evaluate performance using RAOB prep-BUFR data as well as ECMWF

7. Long-term Plan (1/2) • Improve scene classification module • Test logic/tuning parameters using VIIRS cloud mask data • Some work in this area already initiated • Improve retrievals over land surfaces • Get global land surface emissivity dataset and perform retrieval analysis with various hinge points • Investigate use of more cloud-clearing channels • Test with additional shortwave channels • Investigate channel sub-setting to avoid spectral regions that degrade retrieval accuracy

8. Long-term Plan (2/2) • Restore trace gases to retrieval, such as CH4 and N2O, using existing code which scales to tropopause height • Need to check which channels sensitive to trace gases are included in the current channel selection • Fix cloud fraction sometimes >1 • Difficult to fix under cloudy scene • Related to cloud temperature, height and temp & water vapor mixing retrievals above cloud • This part of code bypassed since 2006, with MW-only retrievals as the final product