GLASS GEWEX Global Land-Atmosphere System Study

1. GSWP GLASSGEWEX Global Land-Atmosphere System Study

2. Proposal for a PILPS Experiment in semi-arid sites L. A. Bastidas B. Nijssen, H. Gupta,W. Emmerich, and E. Small Photo National Geographic

3. 1997 1998 1999 2000 Split sample tests AZ AZ to NM • New Mexico sites • Sevilleta • Arizona sites • Lucky Hills • Kendall • Tucson

4. Arizona Sites

5. New Mexico Sites Larrea tridentada Creosotebush Bouteloua eriopoda Black Grama 1 m

6. After Calibration Model Performance Before and After Multi-Criteria Calibration Energy Partition? Sw ? Before Calibration

7. How much improvement is possible ? 20 – 50 % 20 – 50 % ~ 30 % Estimated using Neural Networks

8. Science Questions • What is the ability of the models to reproduce the water, energy, and carbon exchanges in semi-arid environments? • Are the current (usually single) representations of semi-arid lands in the models enough to reproduce the different environments that exist in those areas? • Does model calibration reduce the among-model range in the model simulations? • How much influence does the model parameterization have on the parameter estimations of “physically meaningful” parameters? • Do current carbon representations, developed for forests, properly reproduce carbon exchanges over vegetated arid lands?

9. Timeline for PILPS 2(g) • October 2002 • Submission of experimental protocol • January 2003 • Distribution of forcing data to the participants • February 2003 • Workshop for training of participants in the use of the multi-criteria procedures • April 2003 • Deadline for submission of results • July 2003 • Workshop for analysis of preliminary results.

10. The SecondGlobalSoil Wetness Project (GSWP-2)

11. Goals • Produce state-of-the-art global data sets of soil moisture, surface fluxes, and related hydrologic quantities (1986-1995). • Develop and test in situ and remote sensing validation, calibration, and assimilation techniques over land. • Provide a large-scale validation and quality check of the ISLSCP Initiative II data sets. • Compare LSSs, and conduct sensitivity analyses of specific parameterizations.

12. Implementation • Input data access • DODS server via the internet • Magnetic or optical media (if necessary) The model output will go to the Inter-Comparison Center (ICC) in Japan for consistency checks and preliminary analysis. Output data from base runs and sensitivity studies will also be available for further analysis and validation.

13. Multi-Model Analysis A major product of GSWP2 will be a multi-model land surface analysis for the ISLSCP II period. This will be a land surface analog to the atmospheric reanalyses. There will be a climatological annual cycle data set, and a larger data set for the entire series. Compiling the results of multiple LSSs to produce a single analysis will provide a model-independent result. Of particular value, uncertainty estimates can be put on all of the fields, based on inter-model spread. Additional uncertainties regarding forcing data can be quantified, based on the results of the sensitivity studies. Example of the multi-model mean (inset) and spread in evapotranspiration over North America during one decad from GSWP1. Over some regions the models are in good agreement (e.g., the mid-Atlantic coast), but in others (e.g., New England) the spread among models exceeds the mean of the models (color scale is the same for both plots).

14. Validation I • There will be three main modes of in situ validation of participating LSSs: • Field campaigns – The ISLSCP2/GSWP2 period overlaps a number of relevant field campaigns, which can provide validation data. Comparison of measured meteorological variables with the reanalysis-based forcing data will also provide a validation of those products. 2. Observational networks and long-termmonitoring – There are also long-term monitoring networks of soil moisture, radiative and turbulent fluxes that can provide local or regional validation for LSSs.

15. Validation II • There will be three main modes of in situ validation of participating LSSs: • Streamflow – Runoff fluxes from LSSs will be routed with a common river model to compare with streamflow measurements across a large portion of the globe. This analysis can also uncover problems in the forcing data at basin scales. Also large basin comparison of water storage change with observed ∫V∇•q – Runoff. Validation data will be converted to the ALMA data convention to aid in comparison with LSS output, and to make it readily available for other uses within GLASS and the broader land surface modeling community.

16. Conclusions • GLASS has modeling infrastructure, and GLASS programs have timelines – NAME may leverage off them where there is mutual interest & benefit. • PILPS-2(g) may be leveraged by NAME, and findings/improvements to LSSs that are also participating in NAME (GCMs or MMs) can feedback to the NAME modeling team. NAME should be sure these LSSs are involved in PILPS-2(g). • GLASS open to input and new ideas for land surface modeling initiatives.