glass

Where is GLASS in GEWEX?: 

Where is GLASS in GEWEX?

GLASSGEWEX Global Land-Atmosphere System Study : 

GLASS GEWEX Global Land-Atmosphere System Study

Slide3: 

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

Split sample tests: 

Split sample tests AZ AZ to NM Arizona sites Lucky Hills Kendall Tucson New Mexico sites Sevilleta

Slide5: 

Arizona Sites

Slide6: 

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

Model Performance Before and After Multi-Criteria Calibration: 

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

Slide8: 

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

Science Questions: 

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?

Timeline for PILPS 2(g): 

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.

The Second Global Soil Wetness Project (GSWP-2): 

The Second Global Soil Wetness Project (GSWP-2)

Goals: 

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.

Implementation: 

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.

Slide14: 

Running the models Start from 1st July, 1982: Jul 1982 – Jun 1983 looping for spin up of soil moisture Jun 1983 – Dec1985 for convergence to realistic “land climate” Jan 1986 – Dec1995 for 10 year baseline run (daily output) Rerun last year with 3-hour output interval (IMP): Jan 1995 – Dec 1995 (reduced variable set) May specify subset of points for full 10-year histories at 3-hour output.

Multi-Model Analysis: 

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 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). 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.

Validation I: 

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-term monitoring – There are also long-term monitoring networks of soil moisture, radiative and turbulent fluxes that can provide local or regional validation for LSSs.

Validation II: 

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.

Conclusions: 

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.