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2011 - Cooperative Institute for Research in Environmental Sciences ...

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Milestone 1. Exam<strong>in</strong>e the transitional probability of<br />

drought/pluvial conditions over the United States at different<br />

phases of sea surface temperature (SST) evolution<br />

<strong>in</strong> the tropical Pacific Ocean based on observational data<br />

and multi-model ensemble simulations.<br />

Two sets of analyses are carried out with focus on<br />

the predictability at seasonal timescale. First, the transitional<br />

probability of drought/pluvial conditions is<br />

exam<strong>in</strong>ed at various regional scales <strong>for</strong> observations;<br />

AMIP-type (Atmospheric Model Intercomparison Project)<br />

ensemble simulations from multiple atmospheric global<br />

circulation models (AGCMs) <strong>for</strong>ced with observed evolution<br />

of global sea-surface temperature (SST); and the<br />

ensemble <strong>for</strong>ecasts/h<strong>in</strong>dcasts from a fully coupled <strong>for</strong>ecast<br />

system with realistic <strong>in</strong>itializations. The transitional<br />

probability <strong>in</strong> the dynamic model’s simulations/<strong>for</strong>ecasts<br />

are compared to the transitional probability seen <strong>in</strong> the<br />

observations. A diagnostic/<strong>for</strong>ecast tool is developed <strong>for</strong><br />

probabilistic <strong>for</strong>ecast of seasonal drought/pluvial conditions.<br />

Our <strong>in</strong>itial test <strong>in</strong>dicates that this tool, built upon a<br />

larger number of ensembles of dynamic model output, is<br />

capable of produc<strong>in</strong>g more stable and realistic probability<br />

<strong>for</strong>ecasts than other exist<strong>in</strong>g <strong>for</strong>ecasts that have smaller<br />

ensemble size.<br />

The second set of the analyses focuses on the predictability<br />

of change of an exist<strong>in</strong>g meteorological drought<br />

condition. A method is developed to comb<strong>in</strong>e <strong>for</strong>ecasts<br />

with the measures of exist<strong>in</strong>g conditions to <strong>for</strong>m a universal<br />

drought <strong>in</strong>dex, which gives an objective estimate<br />

on the severity of future drought and allows <strong>for</strong> quantitative<br />

verification. Further analyses are be<strong>in</strong>g pursued <strong>in</strong><br />

collaboration with scientists at the International <strong>Research</strong><br />

<strong>Institute</strong> <strong>for</strong> Climate and Society (IRI) and the Climate<br />

Prediction Center (CPC).<br />

Milestone 2. Evaluation of statistical and dynamical<br />

down-scaled climate projections <strong>for</strong> the Colorado River<br />

Bas<strong>in</strong>, <strong>in</strong>clud<strong>in</strong>g data from North American Regional<br />

Climate Change Assessment Program (NARCCAP), particularly<br />

as it relates to hydroclimatic processes and variability.<br />

Work with stakeholders through Western Water<br />

Assessment, WWA, <strong>in</strong> evaluat<strong>in</strong>g needs and approaches<br />

<strong>for</strong> apply<strong>in</strong>g regional climate change <strong>in</strong><strong>for</strong>mation to water<br />

and land resource management.<br />

Hydrologic-model runs compar<strong>in</strong>g statistical and dynamical<br />

downscal<strong>in</strong>g NARCCAP methods were completed.<br />

Work with Bureau of Reclamation researchers to complete<br />

runs of the reservoir-operations model cont<strong>in</strong>ues. Additionally,<br />

scientific study to clarify some confus<strong>in</strong>g model<strong>in</strong>g<br />

results found <strong>in</strong> Reclamation’s Colorado River Bas<strong>in</strong><br />

Study were designed, and sources of model bias are be<strong>in</strong>g<br />

isolated.<br />

A project with The Nature Conservancy and University of<br />

Wash<strong>in</strong>gton was <strong>in</strong>itiated to calibrate Variable Infiltration<br />

Capacity (VIC) hydrologic model <strong>for</strong> the purposes of better<br />

model<strong>in</strong>g flows relevant to ecological applications. NARC-<br />

CAP temperature and precipitation data over the Upper<br />

Colorado River Bas<strong>in</strong> and the San Juan Mounta<strong>in</strong>s were<br />

analyzed (publication has been submitted). The team participated<br />

<strong>in</strong> the Gunnison Bas<strong>in</strong> Climate Vulnerability Group,<br />

and climate <strong>in</strong><strong>for</strong>mation to assist a species- and habitat-based<br />

vulnerability assessment was provided.<br />

Figure 1<br />

Milestone 3. Cont<strong>in</strong>ue programmatic development and<br />

impact assessments of climate, weather and water services<br />

<strong>in</strong> conjunction with the National Integrated Drought<br />

In<strong>for</strong>mation Service (NIDIS) and other programs.<br />

The Colorado Water Availability Task Force, as well as the<br />

Colorado Water Conservation Board (CWCB), Colorado<br />

Bas<strong>in</strong> River Forecast Center (Salt Lake City) and Upper<br />

Colorado Assessments (NIDIS Pilot), were briefed on seasonal<br />

to two-year expectations regard<strong>in</strong>g runoff prospects<br />

<strong>in</strong> Colorado. This was partially funded through CWCB.<br />

Figure 2 illustrates two-year runoff behavior <strong>for</strong> naturalized<br />

annual streamflow dur<strong>in</strong>g long-last<strong>in</strong>g La Niña events,<br />

as a possible scenario <strong>for</strong> the current La Niña situation.<br />

Water managers <strong>in</strong> the southeastern U.S. (Apalachicola-<br />

Chattahoochee-Fl<strong>in</strong>t bas<strong>in</strong>: ACF NIDIS pilot) were briefed<br />

on develop<strong>in</strong>g drought situation and l<strong>in</strong>kages to La Niña.<br />

Work cont<strong>in</strong>ues on an ongo<strong>in</strong>g project with the Department<br />

of Water Resources <strong>in</strong> Cali<strong>for</strong>nia to predict seasonal climate<br />

<strong>in</strong> that state, with a particular focus on the Sacramento and<br />

San Joaqu<strong>in</strong> river bas<strong>in</strong>s. Additionally, a project with the<br />

Bureau of Reclamation to help with its seasonal-prediction<br />

ef<strong>for</strong>ts was <strong>in</strong>itiated.<br />

Figure 2<br />

CIRES Annual Report <strong>2011</strong> 121

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