# Presentation: 782221

## Vegetation/Ecosystem Modeling and Analysis Project (VEMAP)Lessons LearnedorHow to Do It Right; How to Get What You Need

**Anthony W. King**
**Environmental Sciences Division**
**Oak Ridge National Laboratory**
**With contribution from**
**Tim Kittel**
**University of Colorado, Boulder**
***NACP Data Management Planning Workshop***
**January 25-27 2005**
**New Orleans, LA**

## Where I’m coming from...

**I’m speaking *****from***** VEMAP or *****of***** ****VEMAP not *****for***** VEMAP**
**I come to praise Caesar, not to bury him.**

## Friends, NACP investigators, fellow scientists,

***Friends, NACP investigators, fellow scientists,***
***lend me you ears;***
***I come to praise VEMAP, not to criticize;***

***The good that projects do live after them;***
***the mistakes should be lessons learned;***
***So let it be with VEMAP***

## Outline

**An overview of VEMAP**
**A few VEMAP findings**
**Lessons learned relevant to NACP data management**
**Good**
**Not so good**
**Summary/Conclusions**

## I speak not to contest what others might speak;

***I speak not to contest what others might speak;***
***But here I am to speak what I do know;***
***what I see as lessons learned from VEMAP***

## Overview of VEMAP

**The Vegetation-Ecosystem Modeling and Analysis Project (VEMAP) was a large, collaborative, international, multi-agency effort to simulate and understand ecosystem dynamics for the conterminous United States. **
**VEMAP objectives were to intercompare biogeochemistry and biogeography models and determine their sensitivity to changing climate and elevated atmospheric CO****2**** concentrations. **
**An intermodel comparison, with explicit and structured control for differences in model inputs.**

## Overview of VEMAP

**“****To accomplish [VEMAP] objectives, the models require common boundary conditions and driving variables so that differences in model results arise only from the models and their implementation rather than from differences in inputs.” **
**(p. 858, Kittel et al., 1995, *****J. Biogeography***** 22)**

## Overview of VEMAP: VEMAP had two phases

** ****Phase 1 (VEMAP 1)**** ****was structured as a sensitivity analysis, with factorial combinations of climate (current and projected under doubled CO****2****), atmospheric CO****2****, and mapped and model-generated vegetation distributions. **
**Phase 2 (VEMAP 2)**** ****compared time-dependent ecological responses of biogeochemical models and coupled biogeochemical-biogeographical models to historical and projected transient forcings (time-series) of climate and CO****2****.**

## VEMAP Datasets

**A *****lot***** of effort and resources led by Tim Kittel and Dave Schimel and the VEMAP data group at NCAR went into the creation and QA of the common model inputs.**
**VEMAP 1 database is gridded (0.5****o) ****data layers of bioclimate, climate change scenarios, soil properties, and potential natural vegetation. The set has both daily and monthly, physically consistent, representations of the same long-term climate.  **
**VEMAP 2 database added a historical (1895-1994) gridded dataset of climate and transient climate change scenarios based on coupled atmosphere-ocean GCM experiments.**

## VEMAP findings

**Strong forcing of one or a few processes does not necessarily result in large changes in ecosystem carbon because of constraints from other limiting resources (e.g., N or PAR).**
**Variation among models was “relatively modest”; the variation present was linked to differential sensitivities of hydrologic and nitrogen cycles to increases in temperature and CO****2****.**
**Understanding, modeling and predicting changes in carbon require understanding and modeling of integrated carbon, nitrogen and water cycles.**

## VEMAP findings

**Models were sensitive to disturbance; knowledge of spatial and temporal patterns of disturbance and ecosystem response to is needed for spatial modeling of ecosystems.**
**Models simulated a smaller sink than estimated by inversions, highlighting the important role of forest regrowth in a North American carbon sink. **
**Spatially extended terrestrial ecosystem models must incorporate spatial patterns of disturbance and recovery from disturbance.**
**Intermodel variability was higher at the regional scale than for the entire continent.**

## Lessons Learned

**“****To accomplish [VEMAP] *****objectives*****, the models require common boundary conditions and driving variables so that differences in model results arise only from the models and their implementation rather than from differences in inputs.” **
**(p. 858, Kittel et al., 1995, *****J. Biogeography***** 22)**

## Lessons learned: model requirements strongly guided data requirements

**[The model intercomparison required] “physical consistency among driving variables and boundary conditions...that did not violate the conceptual basis of any of the models.”**
**“****matching model requirements was...a key constraint in the development of consistent...data sets.”**
**“****Matching model requirements...played a role in the classification of vegetation types”.**

## Lessons learned: Good

**Explicit objectives**** or goals measured by tangible products generate specific requirements that in turn provide the required specifications and constraints for the data systems.**
**Assumptions**** in the data and data processing ****need to be made explicit**** and transparent to the user.**
**Need to establish and follow a clear ****protocol for QA**

## Lessons learned: Good

**A ****dissemination plan**** with considerations of version control, metadata and distribution strategy is required.**
**Need to create ****essential user tools**** but just the essentials; avoid the distraction of super-tools or toolboxes.**

## Lessons learned: Good

**It takes ****resources****, money, people, infrastructure and time to meet the data system specifications and requirements.**
**It requires close, real ****integration and dialogue**** between the modeling and data systems to both define and realize requirements.**

## Lessons learned: not so good

**Comparisons against experimental data are needed leading to ****model-data intercomparisons rather than just model intercomparisons****.**
**More common biological/ecologial parameterization****, not just common forcings and boundary conditions, are needed.**
**More attention to ****uncertainty analysis**** and error propagation.**

## Summary/Conclusions

**VEMAP was a success, both as a model intercomparison, and, inextricably, as a data system.**
**VEMAP is a model for NACP data systems.**
**NACP data systems should include data for model testing, process parameterization and provide for formal uncertainty analysis.**
**Resources are required.**
**Explicit program objectives/deliverables similar to project objectives are needed to provide the necessary specifications for a NACP data system.**

## You can't always get what you want

*You can't always get what you want*
*But if you try sometimes*
*well you might find*
*You get what you need*