WRF- Hydro Development and Performance Tes9ng
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1 WRF- Hydro Development and Performance Tes9ng Wei Yu, David Gochis, David Yates Research Applica9ons Laboratory Na9onal Center for Atmospheric Research Boulder, CO USA
2 Scien9fic Mo9va9on How does terrain features affect the spa9al and temporal distribu9on of moisture availability? How does the spa9al distribu9on of soil moisture in complex terrain impact land- atmosphere fluxes and convec9ve circula9ons? Flash flooding forecast?
3 Hydrologically- enhanced Land Surface Models (Gochis and Chen, 2003, NCAR Tech Note) Single Column Land Rou9ng Channel Rou9ng Explicit diffusive wave overland flow Dynamical Routing Methodologies Explicit channel routing 1-D Land Surface ModelS (e.g. Noah ) Explicit saturated subsurface flow fully distributed flow/head reservoir levels distributed soil moisture distributed land/atmo fluxes distributed snow depth/swe
4 System Func9on Overview WRF- Hydro offline data assimila9on/spin- up Forecas9ng WRF- Hydro fully coupled system WRF model LIS system CESM
5 Conceptualiza9on of WRF- Hydro Off- line Mul9- scale/mul9- physics modeling Gridded Forcing Data Output From Nowcas9ng, Weather and Climate Models Column Land Surface Model & Hydro Data Assimila9on WRF- Hydro Driver/Coupler w/ conserva9ve regridders Subsurface Flow Rou9ng Channel & Overland Flow Rou9ng Water Management
6 Conceptualiza9on of WRF- Hydro Coupling Mul9- scale/mul9- physics modeling WRF LIS CESM Column Land Surface Model WRF- Hydro Driver/Coupler w/ conserva9ve regridders Overland & Subsurface Flow Rou9ng Channel Flow Rou9ng Water Management
7 Parallel Implementa,on
8 Data Grids Three Types of Data Grids Land Grids: (ix, jx), (ix, jx, n_soil_layer) Land Rou9ng: (ixrt, jxrt), (ixrt, jxrt, n_soil_layer) Channel Rou9ng: (n_nodes), (n_lakes) Parallel Scheme Two dimensional domain decomposi9on Distributed system (MPI) only
9 WRF- Hydro Mul9- Grids Domain Decomposi9on 1 km Land grid Land rou9ng grid cell: regridding One CPU: Land grid, land rou9ng grid cell, and channel rou9ng nodes.
10 Distributed Memory Communica9ons Land Grid P1 P2 No overlap of the grids. No memory communica9on between neighbor processors.
11 Land Rou9ng Grid Memory Communica9ons (1) * * * V(i) = V(i+1) V(i) = V(i-1) P1 P2 * * * 1) Replace the hello variables
12 Land Rou9ng Grid Memory Communica9ons (2) * * * F(i) à V(i+1) F(i) à V(i-1) P1 P2 * * * * + * 2) Update the inflow/outflow variables in boundary: P1 + P2
13 Distributed Memory Communica9ons Channel Rou9ng * * * * * * * * P1 ** ** * * * * P2 * * Update of red and black nodes for both P1 and P2: inflow/outflow to red and black nodes in P1 + value from P2
14 Implementa9on of Coupling WRF Calling WRF_Drv_Hydro WRF_cpl_Hydro (from Hydro module) (Coupling interface) Ini9alize Hydro (first 9me call) Passing data to Hydro (data mapping) Run Hydro model Passing data back to WRF (data mapping) Land Rou9ng Channel Rou9ng
15 Compiling and Run Configure Choose compiler op9ons When coupled with WRF, WRF- Hydro will be controlled from WRF side. Compiling WRF- Hydro will always be compiled as a library and called by other components as an external func9on. Run (constant files and one namelist file) Offline Coupled with other systems
16 D1: 16 km (90 X 100) D2: 4 km (181 X 161) D3: 1 km (269 X 261) Tes9ng Domain
17 MPI Tasks WRF- Hydro Performance Tes9ng Offline 6 hours forecast (wall clock 9me: seconds) Land & Channel RT Wall Clock: Seconds Scalabilit y 1 WRF (Fully Coupled) 2 hours forecast (wall clock 9me: seconds) Land RT Only WRF Only WRF Fully Coupled Wall Clock: Seconds Scalabilit y 1 Wall Clock: Seconds Scalability 1 Wall Clock: Seconds Scalability
18 WRF- Hydro Performance Speedup Time of Sequen9al Run Time of Parallel Run Ideal Land RT Hydro WRF- CPL WRF Only MPI Tasks
19 Scientific Application First formal release with WRF3.5 Real 9me forecast Offline WRF fully coupled system Regional Climate research Offline LIS and CESM (CLM) Coupling
20 Ini9al Results: WRF- Hydro Simula9ons Evalua9on of simulated streamflow using mul9ple precipita9on products: Aug. 8, 2008
21 Ini9al Results: WRF- Hydro Simula9ons Evalua9on of simulated streamflow using mul9ple precipita9on products: Aug. 8, 2008 Peak lags 15 minutes Here the QPE is provided by the CSU- CHILL dual- polarimetric radar. Noah and CHILL QPE precipita9on on a 1km grid, NDHMS rou9ng executed on a 100m NDHMS- Noah is un- calibrated LIS- NDHMS coupling near complete
22 July 13, 2011 Fourmile Canyon Flood Event: Hydrologic Simula9on
23 July 13, 2011 Fourmile Canyon Flood Event: Coupled WRF- Hydro/RTFDDA model predic9on ~12 hour lead 9me 10.4km
24 WRF- Hydro Somware Features Modularized F90 and integrated in the WRF, HLDAS, CESM systems and NASA- LIS Coupling op9ons are specified at compila9on and WRF- Hydro is compiled as a new library in WRF Physics op9ons are switch- ac9vated though a namelist Fully- parallelized to HPC systems (e.g. NCAR supercomputer) and very good scaling performance Ported to different systems and a variety of compilers WRF- Hydro model can represent beper the important hydrological process over complicated topography and facilitate the streamflow forecas9ng, as well as the regional climate research
25 Future Work Model Scheme Load balance IO for large area applica9on Implicit 9me integra9on scheme for channel rou9ng Data Assimila9on Surface radar data
26 Thank you!
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