Korea Institute of

Atmospheric Prediction Systems (KIAPS)

(재)한국형수치예보모델개발사업단

LETKF Data Assimilation System for KIAPS AGCM: Progress and Plan

Ji-Sun Kang, Jong-Im Park,

Hyo-Jong Song, Ji-Hye Kwun,

Seoleun Shin, and In-Sun Song

UMD Weather-Chaos Group Meeting June 17, 2013

Korea Institute of Atmospheric Prediction Systems

Goal – To develop a global NWP system optimized to the topographic &

meteorological features of Korean peninsula

Period – 2011~2019 (total 9 years)

Total fund – About $ 100 million

Korea Institute of Atmospheric Prediction Systems

There are 14 researchers in a group for data assimilation (DA)

– 7 for observation pre-processing (QC, bias correction for observation data)

– 7 for DA system development

(12)

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(31) (22)

Computing Facilities

Haenam (Cray XE6, AMD 2.1G, 16.9Tflops) – One of KMA’s supercomputers – 2016 cores

Gaon1 (Dell, AMD Opteron 2.3G*4cpu, 2.9 Tflops) – Belongs to KIAPS – 5 nodes with 320 cores (64 cores per node)

Gaon2 (IBM, Intel Xeon 2.9G 2cpu, 11.5 Tflops) – Belongs to KIAPS – 36 nodes with 576 cores (16 cores per node)

Gaon3 – Will be purchased this year or early next year – Expected a similar one with Gaon2 (576 cores)

Total 3,488 cores (5325 cores normalized by the performance of Haenam)

Backup & Archiving system – 210 TB for backup & 330 TB for archiving

KIAPS Data Assimilation Systems

Plans for KIAPS Data Assimilation System

Ensemble Data Assimilation ─ LETKF would be the first system to be constructed as an operational system

Hybrid(3D-Var/LETKF) ─ 3D hybrid assimilation systems of which components consist of the

ensemble assimilation system, descent algorithm for minimization of 3D-Var cost function

Variational data assimilation (3D/4D-Var) ─ KIAPS also plan to develop a 4-d variational data assimilation system

Framework of EnKF data assimilation system

LETKF – CAM_SE (Kang)

We are implementing LETKF to NCAR CAM_SE (Community Atmospheric Model-Spectral Element) model, because it has the same horizontal/vertical coordinates as HOMME/KIAPS that will be released as the first version at the end of this year.

LETKF implemented to NCAR CAM-SE model can be immediately used for the HOMME/KIAPS when released

LETKF – SPEEDY (Park)

While developing LETKF-CAM_SE(HOMME/KIAPS), we would develop or/and test many essential methods to advance the current LETKF DA system, using the simplified model as a testbed.

Model

HOMME/KIAPS & NCAR CAM-SE – Spectral Element dynamic core

– The SE dycore uses accurate, high-order numerical methods on rectangular elements in a cubed-sphere geometry (six faces)

Each face has Ne*Ne elements (Ne: # of elements in one side of a face)

Each element has Np*Np grid points (Np: # of points in one side of a element)

Horizontal resolution can be addressed by neXnpY (e.g. ne16np4~2° resolution, ne120np4~0.25°, ne240np4~0.125°)

5

LETKF implemented to NCAR CAM-SE Model

– NCAR CAM 5.2 with Spectral Element dynamic core

– Horizontal resolution: ne16np4 (~ 2°)

– 30 vertical levels with hybrid sigma-pressure coordinate

Major modifications of LETKF

– I/O of the model

– Data search process

The original LETKF codes (from Dr. Miyoshi) compute (ri, rj) for a location of each observation which is a relative position to the model grid (i, j).

Since (ri, rj) requires too much consideration near the boundary for cubed-sphere domain when LETKF searches for data within local area, I modified this part so that just (lon, lat) is used instead of (ri, rj).

vs.

Test of LETKF-CAM_SE

Observing System Simulation Experiments

– Simulated observations for U, V, T, q

Radiosonde distribution

– Simulated observations for Ps

Surface stations

Observation distribution has been determined by real observation data (NCEP bufr)

Observation errors: 1m/s for (U, V), 1K for T, 1g/kg for q, 1hPa for Ps

64 ensembles (cam, clm2, and cice)

Random initial condition

– States at 64 arbitrary timesteps from a nature run + perturbations

Preliminary Result

Reduced RMS difference after the first analysis step

It seems working well.

– I’ll make an analysis cycle with ensemble forecast right after getting back to Korea

RMS difference of background (red) and analysis (blue) to observations in the observation space

Progress

Understanding the model with special horizontal grid of Spectral Element dynamic core on rectangular elements in a cubed-sphere geometry

– Installing and running CAM-SE (coupled with CLM2 & CICE components) with every 6-hour restart

Modifying standard LETKF codes for the model HOMME/KIAPS (NCAR CAM-SE)

– Analysis system of LETKF-CAM_SE assimilating radiosonde and surface station data has been developed.

– Preliminary result looks good

Plans

We plan to include satellite data of AMSU-A & IASI, and GPS radio occultation data into LETKF data assimilation system. – Takemasa (radiance DA) & Shu-Chih (GPS RO DA) will visit KIAPS

in August for giving us an advice.

AIRS retrieval data can be also assimilated and compared.

Target resolution of HOMME/KIAPS is ne240np4 (~0.125°, very high) with 70 vertical layers – Ensemble forecast may have coarser resolution than ne240np4.

If the resolution for ensemble forecast is too coarse, we may not be able to get comparable results with others.

It would be good to incorporate a mixed resolution of background (Rainwater and Hunt, 2013)? I can test it using CAM!

We plan to test many useful techniques in EnKF, especially forecast sensitivity to observations (Kalnay et al. 2012) which KMA is very interested in.

Carbon cycle data assimilation (LETKF-C) will be also tested using CAM5.2 with SE, or CAM3.5 with FV

Thank you very much for your attention!