An Analysis of Subseasonal Variability in the NCEP

An Analysis of Subseasonal Variability in the NCEP CFS and NASA NSIPP Coupled GCMs Myong-In Lee 1, 2, Siegfried Schubert 2, Max Suarez 2, Phil Pegion 2, Ben Kirtman 3, Kathy Pegion 3, Arun Kumar 4, Bhaskar Jha 4, and Duane Waliser 4 1 Goddard Earth Sciences and Technology Center/ UMBC 2 NASA/GSFC Global Modeling and Assimilation Office 3 COLA/George Mason University 4 NCEP/ Climate Prediction Center 5 NASA/Jet Propulsion Laboratory/Cal. Tech The 30 th Annual Climate Diagnostics & Prediction Workshop The Pennsylvania State University October 24 -28, 2005

Questions ? ? n How well do the current coupled models reproduce the leading patterns of extratropical subseasonal variability? n n n CGCM intercomparisons ( CFS and NSIPP CGCM) Coupling versus prescribed (comparison with AMIP) How well do the current coupled models reproduce the changes in subseasonal variability associated with ENSO ? n n ENSO simulation in CGCMs Subseasonal variance changes

Model Descriptions n NCEP CFS T 62 L 64 n n n NCEP Global Forecast System (GFS) for the atmospheric component GFDL Modular Ocean Model version 3 (MOM 3) for the ocean component NASA NSIPP CGCM v. 1 n n NSIPP 1 AGCM (1 x 1. 25) Poseidon v 4 (1/3 x 5/8 x. L 27) OGCM

Datasets n 50 years of NCEP/NCAR Reanalysis-1 n n n 1951 -2000 Daily and monthly GPH 200 Monthly U 200 n 50 years of monthly Had. ISST n 50 years coupled runs n n n NCEP CFS (T 62 L 64) NSIPP CGCM (1 x 1. 25) 50 years of AMIP (1951 -2000) Runs n n NCEP GFS T 62 L 64 (T 62 L 64) 9 -member NSIPP AGCM ensemble runs (2 x 2. 5)

n Principal patterns of monthly 200 mb height (Rotated EOFs)

ENSO AO AAO PNA meters per STDV

ENSO AO AAO PNA

NAO

Variance of Leading Patterns (Unit: meter 2)

ENSO CFS (coupled) Reanalysis NSIPP (coupled) (var. =252 m 2) GFS AMIP (var. =340 m 2) NSIPP AMIP (var. =364± 9 m 2) (var. =341 m 2) (var. =134 m 2)

AO CFS(coupled) (var. =217 m 2) GFS AMIP (var. =371 m 2) (var. =339 m 2) NSIPP AMIP (var. =308± 33 m 2) Reanalysis (var. =314 m 2) NSIPP(coupled)

AAO CFS (var. =242 m 2) GFS AMIP (var. =283 m 2) (var. =282 m 2) NSIPP AMIP (var. =231± 25 m 2) Reanalysis (var. =224 m 2) NSIPP

PNA CFS (var. =180 m 2) GFS AMIP (var. =193 m 2) (var. =197 m 2) NSIPP AMIP (var. =176± 14 m 2) Reanalysis (var. =215 m 2) NSIPP

NAO CFS (var. =109 m 2) GFS AMIP (var. =164 m 2) (var. =109 m 2) NSIPP AMIP (var. =128± 26 m 2) Reanalysis (var. =172 m 2) NSIPP

n Ensemble spreads in NSIPP AMIP runs (spaghetti diagram of EOFs) - contours from each ensemble members - compared with the reanalysis (shading)

ENSO response from NSIPP 9 AMIPs

AO from NSIPP 9 AMIPs AAO from NSIPP 9 AMIPs

PNA from NSIPP 9 AMIPs NAO from NSIPP 9 AMIPs

n ENSO simulations in the CGCMs

Time-Longitude SSTA (5 S-5 N)

Nino 3 SSTA (5 S-5 N, 150 -90 W) Reanalysis CFS NSIPP Warm SST Composite (> 1σ) Cold SST Composite (< -1σ)

n Subseasonal Variance Analysis - GPH 200 daily - remove seasonal cycle (0 -3 harmonics of 50 year-averaged daily climatology) - 10 -60 day band-pass filtered - variance in NH winter (DJF)

Subseasonal Variance Changes (La Nina-El Nino) contour: 200 mb u-wind difference

n Rotated EOFs from daily band-pass (1060 d) filtered 200 mb height

Variance of PCs (daily 200 mb height) CFS (coupled) A O PN AA O NSIPP AMIP A PN O NA A O AA O PN A NH pattern SH pattern Total variance(*0. 1) A NA O O NSIPP (coupled) AA O P NA NA AO O A NA PN Reanalysis GFS AMIP

Pattern 1 Pattern 4 Pattern 3 Pattern 2 Reanalysis #2 #1 #6 #20 GFS AMIP r=0. 88 #4 r=0. 80 #5 #1 r=0. 97 r=0. 73 #7 NSIPP AMIP r=0. 97 #1 #3 r=0. 94 #2 r=0. 83 #8 CFS (coupled) r=0. 96 #4 r=0. 85 #1 #13 NSIPP (coupled) r=0. 96 r=0. 83 r=0. 95 #8 r=0. 79 r=0. 94 r=0. 72 PNA NAO

Pattern 6 Pattern 5 Pattern 8 Pattern 7 Reanalysis GFS AMIP #4 #13 #5 r=0. 94 r=0. 95 #3 #2 #9 r=0. 68 #6 r=0. 81 #12 NSIPP AMIP r=0. 92 r=0. 94 CFS (coupled) #11 #5 r=0. 91 #5 #9 r=0. 90 r=0. 80 AO r=0. 71 #2 #3 r=0. 89 r=0. 78 #7 #9 r=0. 95 NSIPP (coupled) r=0. 93 r=0. 47 r=0. 96

Pattern 9 Pattern 10 Pattern 11 Pattern 12 Reanalysis #10 #7 #8 GFS AMIP r=0. 92 #8 r=0. 87 #14 #13 #9 r=0. 80 r=0. 96 #10 NSIPP AMIP r=0. 92 CFS (coupled) #6 #13 r=0. 95 NSIPP (coupled) #7 #4 r=0. 92 r=0. 95 #22 r=0. 82 #14 #6 r=0. 84 r=0. 96 r=0. 89 #11 r=0. 96 r=0. 94

Variance difference (cold-warm) – CFS (coupled) reconstructed from EOFs GFS AMIP Reanalysis NSIPP (coupled) NSIPP AMIP (*1000 m 2)

Variance difference (cold-warm) - Reanalysis NAO PNA p 1 p 5 p 9 AO p 2 p 3 p 4 p 6 p 7 p 8 p 10 p 11 p 12

Variance difference (cold-warm) – GFS AMIP NAO PNA p 1 p 5 p 9 AO p 2 p 3 p 4 p 6 p 7 p 8 p 10 p 11 p 12

Variance difference (cold-warm) – NSIPP AMIP NAO PNA p 1 p 5 p 9 AO p 2 p 3 p 4 p 6 p 7 p 8 p 10 p 11 p 12

Variance difference (cold-warm) – CFS coupled NAO PNA p 1 p 5 p 9 AO p 2 p 3 p 4 p 6 p 7 p 8 p 10 p 11 p 12

Variance difference (cold-warm) – NSIPP coupled NAO PNA p 1 p 5 p 9 AO p 2 p 3 p 4 p 6 p 7 p 8 p 10 p 11 p 12

Summary 1. Current models reproduce the leading wintertime extratropical patterns of monthly variability reasonably well n REOFs identify the patterns of ENSO, AAO, PNA and NAO n an assessment of the spread of the NSIPP AMIP ensemble shows these patterns to be robust in samples of 50 years n there are, however, large differences in the variance of individual patterns n total monthly variance is in general weaker in the simulations

Summary 2. An assessment of the full subseasonal (10 -60 day) variance shows the following: n n n 3. (continued) the variance is weak in the coupled runs, whereas it is comparable to the reanalysis in the AMIP runs but, all models have a sign of variance increase over the northern reach of Pacific and Alaska region and decrease over the arctic and northern Atlantic region REOFs from daily band-pass 200 mb height show a much richer spectrum of patterns compared with the monthly results, apparently a variation of several leading principal patterns interannual changes in the subseasonal variance associated with ENSO have realistic patterns (but are weak, especially in the coupled runs) changes in the PNA and NAO are robust, though not so for other leading patterns Future work will focus on furthering our understanding of the nature of the various subseasonal patterns and their underlying dynamics

Thank You !