1. Isotopic constraints on moist processes over the tropics in NASA GISS ModelE2 Robert Field, Daehyun Kim, Gavin Schmidt, John Worden, Allegra LeGrande, Max Kelley JPL

2. Motivation Climate projections with ModelE form a major part of the GISS contribution to IPCC. Are measurements of the isotopic composition of water vapor useful for model evaluation? Can we use them to identify compensation errors in the parameterizations? What physical processes might they be constraining, especially those that are hard to measure?

3. Moisture in lower free troposphere ERA-I ModelE

4. Model performance across different metrics Pattern correlation OceanLand

5. Aura TES HDO/H 2 O Simulator Varying TES retrieval quality and vertical sensitivity must be taken into account. See: Field, R.D., C. Risi, G.A. Schmidt, J. Worden, A. Voulgarakis, A.N. LeGrande, A.H. Sobel, R.J. Healy, A Tropospheric Emission Spectrometer HDO/H 2 O retrieval simulator for climate models, Atmospheric Chemistry and Physics, 12, doi:10.5194/acp-12- 10485-2012, 10485-10504, 2012. Retrieval quality (%) Height of peak HDO retrieval sensitivity (hPa)

6. Effects of TES operator on modeled δD fields Raw model δD (‰) Change to raw model δD after applying ‘standard’ TES operator. Only works for prescribed meteorology. Change to raw model δD after applying new TES operator. Works for arbitrary, free-running model configurations.

7. δD over lower free troposphere TES ModelE with operator

8. Pattern correlation Model performance across different metrics OceanLand

9. Model performance across different metrics Pattern correlation OceanLand

10. q as a constraint on convective recycling Pattern correlation Convective recycling ratio OceanLand

11. δD as a constraint on convective recycling Pattern correlation Convective recycling ratio OceanLand

12. Key points Isotopic measurements provide a stronger constraint than moisture amount or precipitation, especially over the ocean. They can provide guidance on the fidelity of hard- to-measure processes within the model. Next up: – Mechanistic constraints on model variability: MJO & ENSO – Land surface fluxes: evaporation / transpiration partitioning – Observational error

13. Convective moisture recycling Ratio of re-evaporated to total convective condensate Not well constrained

14. q and δD over lower free troposphere HDO concentrations are expressed relative to an ocean water standard, in units of permil (‰). q ERA-I δD TES

15. Capturing variation in vertical sensitivity More complicated categorizations Obs.

16. GPCP ModelE Precipitation

19. TES vs. ModelE δD δD Raw - δD TES δD TES δD RetrAK - δD TES δD CatAK - δD TES

20. Stable isotopes (isotopologues) of water 16 O 1H1H 1H1H 99.73% 18 O 1H1H 1H1H 0.20% 16 O 2H2H 1H1H 0.03% The heavy isotopes of water evaporate less readily and condense preferentially. There are now sufficient HDO measurements in the troposphere against which to evaluate models. We are currently working with HDO/H2O retrievals from the Tropospheric Emission Spectrometer (TES).