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PNNL-13501 - Pacific Northwest National Laboratory

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wide variety of parallel computing platforms using twodimensional<br />

decomposition with shared or distributed<br />

memory. This effort also contributes toward the<br />

development of a community regional climate model<br />

based on MM5.<br />

Figure 1 shows the speedup attained with the twodimensional<br />

decomposition parallel version of MM5 with<br />

and without subgrid orographic precipitation. Results are<br />

based on benchmarks on the EMSL IBM-SP computer. A<br />

number of 1-day simulations have been performed using<br />

different configurations of the model domain. Higher<br />

speedup is achieved with larger domain sizes. When the<br />

subgrid orographic precipitation scheme is applied, a<br />

simple load-balancing algorithm is needed to improve the<br />

performance. Figure 2 shows the two-dimensional<br />

domain decomposition when the load-balancing algorithm<br />

is applied. Because computational burden increases with<br />

an increasing number of subgrid elevation bands, smaller<br />

domains are assigned to processors that are required to<br />

handle a larger number of subgrid elevation bands.<br />

Speed-up<br />

100<br />

10<br />

B Perfect parallelization<br />

J L-domain (200x200x23) B<br />

H M-domain (70x70x23)<br />

J<br />

F S-domain (37x37x23)<br />

B S-domain (subgrid + load bal) B H<br />

J S-domain (subgrid, no load bal) J<br />

H<br />

B J<br />

H<br />

F<br />

F<br />

B JH<br />

F<br />

B B<br />

F B J J<br />

B J<br />

J<br />

B B J<br />

JH<br />

H F<br />

B F<br />

B J<br />

J<br />

1<br />

1 10<br />

Number of processors<br />

100<br />

Figure 1. Speedup of the two-dimensional decomposition<br />

parallel RCM on the <strong>PNNL</strong> EMSL IBM-SP machine.<br />

Results are based on 1-day simulations with the RCM<br />

applied to different geographical domains.<br />

Hydrologic Modeling<br />

Assessments of fisheries management conducted by<br />

various federal, state, and tribal agencies (including<br />

Bonneville Power Administration) are driven to the<br />

spatial scale of the 6th-level Hydrologic Unit Code<br />

(HUC6). The channel system in each hydrologic unit<br />

code is subdivided into a number of geo-referenced river<br />

1 2 3 4 5 6 7 8 9 10 11 12<br />

number of subgrid bands per grid<br />

Figure 2. Two-dimensional domain decomposition when the<br />

<strong>PNNL</strong> subgrid orographic precipitation is applied. Smaller<br />

domains are assigned to processors that cover regions with a<br />

large number of subgrid elevation bands.<br />

reaches. More than 7500, 6th-level hydrologic unit codes<br />

exist in the Columbia Basin, of which less than 1% has<br />

gauged streamflows. The Distributed Hydrology-Soil-<br />

Vegetation Model has been enhanced to operate either on<br />

the original square-grid domain or a more generic<br />

watershed/channel representation that allows direct<br />

application at the HUC6 level. Linkage with the<br />

<strong>Laboratory</strong>’s regional climate model has been maintained.<br />

Support utilities have been developed to subdivide each<br />

HUC6 into elevation bands with a simplified<br />

representation of subband topography. Each band is<br />

mapped to the appropriate River Reach(s). The model is<br />

currently being run for the entire Columbia River basin at<br />

the HUC6 level using five elevation bands per hydrologic<br />

unit code.<br />

Development of a Hydrosystem Management Tool<br />

The developments under the hydrology task enable us to<br />

provide estimates of natural streamflows. However, dams<br />

and diversions significantly alter these natural streamflow<br />

patterns. Any adaptation to changes in the future climate<br />

will involve changes to the operating policies of dams and<br />

diversions. A numerical procedure to express the<br />

multiple-objective tradeoffs for a single reservoir system<br />

had been developed. The procedure linked a niched<br />

Pareto genetic algorithm with a simple reservoir model.<br />

This method has been modified to consider a system of<br />

multiple reservoirs. The system has been implemented on<br />

massively parallel computer platforms.<br />

Earth System Science 239

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