Comments On A Seminar “Modeling Watershed-Scale Distributions Of Snow For Present-Day And Future Climate” By Anne Nolin

There is a seminar today [August 23 2010] by Anne Nolin of the Department of Geosciences,  at Oregon State University, Corvallis

The seminar is titled “Modeling Watershed-Scale Distributions of Snow for Present-day and Future Climate in the U.S. Pacific Northwest Monday, 23 August 2010, 2:00 PM David Skaggs Research Center, Room 1D403.

After I present the abstract, I give several comments on this study, which is just one example of a type of climate study that has become common in recent years (i.e. one based on (unverifiable) multi-decadal global climate predictions).

The abstract reads

The snowmelt-dominated Cascade Mountains provide critical water supply for agriculture, hydropower, ecosystems, and municipalities throughout the Pacific Northwest. Empirical analyses and models of projected climate change show rising temperatures in the region. This temperature trend is accompanied by a shift from snowfall to rainfall at lower elevations and earlier snowmelt. In this study we model the spatial distribution of Snow Water Equivalent (SWE) in the McKenzie River Basin, Oregon (3000 km2). We use the physically based SnowModel with a grid resolution of 100 m and a daily time step. Model inputs include meteorological data, a digital elevation model, and land cover information. We compute the ratio of SWE to total winter precipitation (SWE/PRE) for the period of 2000-2009. The model is evaluated using point-based measurements of SWE, precipitation, and temperature and spatially, using snow cover extent from the MODIS instrument. SnowModel simulations are in very good agreement with measured SWE for most stations with Nash-Sutcliffe model efficiency values exceeding 0.9 in most cases. Agreement with MODIS snow cover data show a total difference of 7.1% at the time of peak SWE with the largest difference in valley bottoms (where vegetation is dense and snow cover is difficult to view with the satellite data).

For the future climate scenarios, meteorological inputs are perturbed based upon downscaled Intergovernmental Panel on Climate Change model predictions. The temperature and precipitation forcing data for 2000-2009 were perturbed to represent projected climate changes based on a composite of nineteen IPCC climate models (scenario A1B) downscaled to the Pacific Northwest region for the period 2030-2050. These perturbations were computed using the change from present-day climate to a projected future climate (delta value). The delta value was applied to daily temperature and precipitation data using a prescribed monthly value and the model was rerun using these perturbed values. Our perturbed simulations show substantial losses in SWE throughout the watershed. However, interannual variability under projected climate change can generate increases in SWE at high elevations but overall declines in basin-wide SWE. Thus, while there is a significant loss of snow covered area and volumetric water storage in the form of snow, the spatial changes in SWE are highly heterogeneous. This has important implications for runoff predictions as well as for design and implementation of snow monitoring networks.”

Here are my comments:

1. Her  evaluation of the snow distributions for the period 2000-2009 is solid science.

2. The extrapolation into the future using IPCC model predictions downscaled to the region of study, however, is not scientifically sound. First, even with current climate, the global climate models have shown no skill at predicting regional skill more than a season at most into the future. These global models are not able to skillfully simulate such regional circulation patterns as the Pacific Decadal Oscillation and ENSO, which are known to have a major effect on the weather in Oregon.

3. The packaging of her results in time periods (i.e. 2030-2050) is inappropriate and misleading to policymakers. 

4. Such unverifiable multi-decadal predictions based on the IPCC global models (as exemplified by this seminar) are  being supported by the NSF and other agencies, and are being published in the literature. Such studies, where the results are presented as forecasts rather than climate process studies,  were not funded before the last 10-15 years or so.

5. My recommended approach is to adopt the perspective that is summarized in the post

A Way Forward In Climate Science Based On A Bottom-Up Resourse-Based Perspective

where with respect to water resources the framework would read

“The vulnerability concept requires the determination of the major threats to water resources from climate, but also from other social and environmental issues. After these threats are identified for each resource, then the relative risk from natural- and human-caused climate change (estimated from the GCM projections, but also the historical, paleo-record and worst case sequences of events) can be compared with other risks in order to adopt the optimal mitigation/adaptation strategy.”

This is a much more inclusive approach than the limited narrowly focused approach presented in the second part of Anne Nolin’s seminar.

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