1. RO Winds, Reanalysis, PPE Stephen Leroy 1, Chi Ao 2, Olga Verkhoglyadova 2 CLARREO SDT Meeting, April 16-18, 2013 NASA Langley Research Center 1 Harvard School of Engineering and Applied Sciences 2 Jet Propulsion Laboratory, California Institute of Technology

2. On-going activity RO Winds: Balance winds? Anchoring reanalysis: BAMS reviews Developing a perturbed physics ensemble with climateprediction.net 17 April 2013Leroy: RO Winds, Reanalysis, PPE2

3. Geostrophic Winds 17 April 2013Leroy: RO Winds, Reanalysis, PPE3 Leroy and Anderson, 2007: Geophys. Res. Lett., 34, doi:10.1029/2006GL028263.

4. COSMIC Geostrophic Winds 17 April 2013Leroy: RO Winds, Reanalysis, PPE4 At dry pressure 100, 125, 150, 175, 200, 225, 250, 275, 300 hPa.

5. Balance winds 17 April 2013Leroy: RO Winds, Reanalysis, PPE5 First order correction to geostrophic winds. In order to follow path of geostrophic winds, air parcels must accelerate. Include cyclostrophic acceleration terms. Randel, W.J., 1987: The evaluation of winds from geopotential height data in the stratosphere. J. Atmos. Sci., 44, 3097-3120.

6. Improvement with balance winds… 17 April 2013Leroy: RO Winds, Reanalysis, PPE6 Error, geostrophic winds from gridded ERA Interim Error, balance winds from gridded ERA Interim 200 hPa

7. Improvement with balance winds? 17 April 2013Leroy: RO Winds, Reanalysis, PPE7 Error, geostrophic winds after Bayesian mapping Error, balance winds after Bayesian mapping 200 hPa

8. Actual windGeostrophic wind Jet Stream 17 April 2013Leroy: RO Winds, Reanalysis, PPE8 Jet stream location and strength, January 2007

9. Actual windGeostrophic wind Jet Stream Strength 17 April 2013Leroy: RO Winds, Reanalysis, PPE9

10. RO Winds: Conclusions No benefit at this point in computing balance winds rather than geostrophic winds – Does this change with denser RO sampling? – Is data assimilation absolutely necessary? What impact does RO provide on winds in assimilation? Jet stream position seems well determined by geostrophic winds but strength is overestimated by ~10%. – Is accuracy in jet stream position sufficient for monitoring? – What influence does it have on North American weather? 17 April 2013Leroy: RO Winds, Reanalysis, PPE10

11. Data Assimilation Diagnostics 17 April 2013Leroy: RO Winds, Reanalysis, PPE11 + Analysis Increment Next Analysis = ‘Evolution’ Process order in each timestep (e.g.) Temperature Dynamics + Radiation + Vertical diffusion (&GWD) + Convection + L.S. Precip + Other * numerics etc ‘First guess’ Analysis * Deduced as a residual Observation + Bias adj. Departure + Analysis Increment Next Analysis = ‘Evolution’ Dynamics + Radiation + Vertical diffusion (&GWD) + Convection + L.S. Precip + Other * numerics etc ‘First guess’ Analysis * Deduced as a residual Observation + Bias adj. Departure + Analysis Increment Next Analysis = ‘Evolution’ Process order in each timestep (e.g.) Temperature Dynamics + Radiation + Vertical diffusion (&GWD) + Convection + L.S. Precip + Other * numerics etc ‘First guess’ Analysis * Deduced as a residual Observation + Bias adj. Departure + Analysis Increment Next Analysis = ‘Evolution’ Dynamics + Radiation + Vertical diffusion (&GWD) + Convection + L.S. Precip + Other * numerics etc ‘First guess’ Analysis * Deduced as a residual Observation + Bias adj. Departure

12. Numerical experiments at ECMWF Investigate upper tropospheric (specific) humidity Four runs, 4 April – 31 May 2011, 37r2 T511, 91 levels, 15min – Control – Perturb HIRS channel 12 radiative transfer (q @ 300 hPa) – Perturb AIRS channel 1783 & IASI channel 3645 radiative transfer (q @ 350 hPa) – Perturb vertical diffusion Monitor multiple data types – Conventional in situ data: radiosondes T, q, u, v; aircraft T, u, v; – Satellite water vapor: AIRS and IASI humidity channels (1556 cm -1 ), AMSU-B channel 3, HIRS channel 12 – Other satellite data: AMSU-A, HIRS channel 11, scatterometer winds, atmospheric motion winds, radio occultation bending angles, SSM/I channel 14 Mistakes – AIRS and IASI passively assimilated – Bias correction remained dynamic 17 April 2013Leroy: RO Winds, Reanalysis, PPE12

13. Reanalysis 17 April 2013Leroy: RO Winds, Reanalysis, PPE13 Perturbed HIRS channel 12 Perturbed vertical diffusion physics

14. BAMS Review 17 April 2013Leroy: RO Winds, Reanalysis, PPE14 “In general the paper was well received by the reviewers, but …” Improve “crispness” of the ideas in the introduction; Strengthen the claim that RO is anchoring the bias correction. Perform two new runs: 1)Control run without GPS RO 2)Perturbed diffusion without GPS RO

15. Bayesian Information on Data Types 17 April 2013Leroy: RO Winds, Reanalysis, PPE15 Form joint PDF P(x,y) using an ensemble of climate models. For each model, need (1) observation kernel to simulate data x from hindcast run, and (2) emissions scenario run to generate prediction variables y. Internal variability in x and y and uncertain physics will both be accounted for. With data d, set x = d and P(y|x=d ) is the projection PDF with data incorporated. P(x) is a normalization constant that guarantees a unit integral of P(y|x) over y.

16. Ranking Data Types 17 April 2013Leroy: RO Winds, Reanalysis, PPE16 Satellite Measurements In Situ Measurements

17. Toward a Climate OSSE Use a perturbed physics ensemble (PPE) with a radiance and refractivity simulator – Consider atmospheric variable retrieval – Consider inference of radiative feedbacks and forcing Take advantage of accumulated expertise – Knowledge base of model sensitivity to changing parameters – Knowledge base of calibration of ensemble – Gain access to massive computing Collaboration with climateprediction.net – Based on HadAM3, Unified Model 4.5 of Met. Office – Legal agreement is in place – Embed PCRTM, specify sampling frequency – Specify initialization, boundary conditions 17 April 2013Leroy: RO Winds, Reanalysis, PPE17

18. GPS RO Processing (1) Tool developed by Gorbunov (NOAA, CLARREO SDT) – Use 2-parameter ionospheric fitting – Initialization at 100 km – Canonical transform type 2 – Truncate lower troposphere when canonical transform signal drops below 50% Build on Harvard FAS cluster “odyssey” – 8.6 core-seconds per level1b calibration – 83% of CHAMP passes quality contro l Begin research – Systematic error from precise orbit determination (?) – Detectible climate signals in UTLS, stratosphere 17 April 2013Leroy: RO Winds, Reanalysis, PPE18

19. GPS RO Processing (2) 17 April 2013Leroy: RO Winds, Reanalysis, PPE19 7,902,055 total occultations, ~83% of which pass quality control (CHAMP).