# Presentation: 658774

## Incorporation of Stable Water Isotopes in GSM and Spectrum-Nudged 28-year Simulation

**Incorporation of Stable Water Isotopes in GSM and ****Spectrum-Nudged 28-year Simulation**

**Kei YOSHIMURA****1,2**** **1: Scripps Institution of Oceanography, University of California San Diego2: Institute of Industrial Science, The University of TokyoEmail: *k1yoshimura@ucsd.edu, *HP: **http://meteora.ucsd.edu/~kyoshimura**

**2. Results of Global Isotope Simulation with Spectral Nudging**

**1. Introduction**

**3. Comparison with in-situ observations.**

**Summary**

- NOAA 32nd Annual Climate Diagnostics and Prediction Workshop, October 22-26, 2007, Tallahassee, FL, USA

**References:****	**
- Majoube, J., Fractionation factor of 18O between water vapor and ice, Nature, 299, 1242, 1970.
- Merlivat, L., Molecular diffusivities of H216O, HD16O, and H218O in gases, J.Chim.Phys., 69, 2864-2871, 1978.
- Merlivat, L., and J. Jouzel, Global climatic interpretation of the deuterium oxygen 18 relationship for precipitation, J.Geophys.Res., 84, 5029-5033, 1979.
- Jouzel, J., and L. Merlivat, Deuterium and oxygen 18 in precipitation: modeling of the isotopic effects during snow formation, J. Geophys.Res., 89, 11749-11757, 1984.
- Stewart, M.K., Stable isotope fractionation due to evaporation and isotopic exchange of falling waterdrops: Applications to atmospheric processes and evaporation of lakes, J.Geophys.Res., 80, 1133-1146, 1975.
- Yoshimura, K. and M. Kanamitsu, Dynamical global downscaling of global reanalysis, submitted to Mon.Wea.Rev. (In revision)
**Acknowledgment:** This research is funded by JSPS and CEC.

-   Right figure shows observation (GNIP), model mean by SWING, and IsoGSM annual climatology and seasonal departure (DFJ-JJA) of d18O and d-excess (dD-8*d18O) in precipitation.  The model mean and IsoGSM agree quite well with lower d18O values in high latitudinal regions (“latitude effect”), in high elevation regions (“altitude effect”) and in inland region (“continent effect”). d-excess also shows good correspondence with observations.

**Right figure********:** dD in column vapor and the seasonal  variation, and the same of d-excess.
**Bottom figure********:** Worden’s (2007) result showing the isotopic evidence of evaporation from raindrop. It is caused by kinetic fractionation processes. Right figure shows simulated result for same criteria.

- Stable water isotopes are incorporated into NCEP/ECPC’s global spectral model in a manner similar to other isotope models.  In addition, a newly developed spectral nudging technique (Yoshimura et al., 2007) is used, which allows to reproduce the actual spatial and temporal distribution of water and isotopes distributions.  Divergence, vorticity, and temperature in NCEP/NCAR Reanalysis 2 data are the base fields that are nudged for more than 1000 km scales. Specific humidity remains unnudged in order to close the water budget.  A T62L28 large-scale nudging simulation for 1979-2006 has now been simulated and the results show much more realistic precipitation isotope variations in comparison to other free-forecast simulations.

**a. What are Stable Water Isotopes (SWI)?**

**b. Why should SWI incorporated into GCMs?**

**c. What is merit of using NCEP/ECPC G-RSM?**

**d. Isotopic and other physics in Iso-GSM**

**a. Global Climatology of SWI in Precipitation compared with GNIP data**

**b. Global Climatology of SWI in Vapor  compared with TES Observation.**

**a. Typhoon event (2006/09/14-16)**

**c. Seasonality of SWI in Precipitation**

**Top right figure********:** Correlation coefficient distributions of all monthly precipitation d18O compared with GNIP dataset for three SWING models and IsoGSM. Closer to one (blue) is better.
**Further right figure********: **Climatologic seasonality in selected GNIP observation sites (only 12 are shown among 660 sites).  Precipitation of ECHAM4, IsoGSM, and observation are also shown.
**Right figure********:** The anomaly of d18O is shown. It is calculated by removing climatologic seasonality. All free forecast models have difficulty to simulate such second order variations.

- Physical processes

- Isotopic Physical processes

**Figures:** from left to right, annual climatology of precipitation d18O, its seasonal differences, annual climatology of d-excess, and its seasonal differences.  From top to bottom, GNIP, Model mean, and IsoGSM results are shown.

- From Worden et al., 2007

- In the table below, by taking simple average of correlation coefficients of monthly d18O and its anomalies over all available sites (about 200), IsoGSM with nudging has the best number. All other models are enable to simulate seasonality of isotopic climatology, but they all failed to produce accurate interannual variability, whereas IsoGSM is capable to do so.

**IsoGSM results****	**

**Cyclonic field ****emerges**

**b. Traverse Observation over Antarctic Sea (2006/01)**

- Spectral Nudging Scheme