UPDATE ON WRF-ARW END-TO-END MULTI-SCALE FDDA SYSTEM
Aijun Deng, David Stauffer, Brian GaudetPenn State University
Jimy Dudhia, Joshua Hacker, Cindy Bruyere, Wanli Wu, Francois Vandenberghe, Yubao Liu and Al Bourgeois NCAR
10th Annual WRF Users’ Workshop
June 23-26, 2009, Boulder, CO
2
Objectives
• Current status of the nudging FDDA capabilities in WRF-ARW, and status of the end-to-end FDDA system.
• Test results of WRF nudging FDDA in a multiscale FDDA framework, using a model configuration with typical vertical resolution.
• Test results of the end-to-end FDDA system, using a model configuration with very high vertical resolution.
• Future Plans
3
Two Approaches to Nudging (Newtonian Relaxation)
• Nudge to gridded analyses of observations• Nudge to individual observations(multi-scale FDDA, Stauffer and Seaman 1990, 1994)
( ) ...obGt
t t
0 0
( ) computed in grid space analysis nudging( ) computed in obs space obs nudging
( ) ( ) ( )t
1 folding-time
ob
ob
Gtob o ob obdt G dt t e
eG
O(1 )h
5
• CAPTEX-83 Case
48-h model simulation, 36-km/12-km/4-km domains, 32 vertical layers with the first half layer at ~30 m
Starting: 1200 UTC, 18 Sept. 1983Ending: 1200 UTC, 20 Sept. 1983(IC/LBC/FDDA inputs based on MM5 RAWINS)Physics: MYJ PBL, KF CPS on 36- and 12-km grids,
Dudhia SW and RRTM LW, etc
7
Experimental Design for Multi-scale FDDA
CAPTEX-83 (36/12/4-km grids)
YESNOYESYESYESYESMFDDA
NONONOYESNOYESGFDDA
YESNOYESNOYESNOOFDDA
NONONONONONONOFDDA
OBS Nudging
3D Analysis Nudging
OBS Nudging
3D Analysis Nudging
OBS Nudging
3D Analysis Nudging
4-km12-km36-kmExp. name
8
222N/AN/AN/ATWINDO (hr)
2060180N/AN/AN/Adt (sec)
1042N/AN/AN/AIONF
100100150N/AN/AN/ARINXY (km)
Nudging above PBL
Nudging above PBL
Nudging above PBLN/ANudging
above PBLNudging above PBLMass field
Nudging all layers
Nudging all layers
Nudging all layersN/ANudging all
layersNudging all layersWind field
4*10-44*10-44*10-4N/A1*10-43*10-4G (1/sec)
4-km12-km36-km4-km12-km36-km
OBS Nudging3D Analysis Nudging
FDDA Experimental Design and ParametersCAPTEX-83 (36/12/4-km grids)
9
CAPTEX-83: MAE of WRF-Simulated Fields Averaged Over 48-h Time Period and All Model Layers
MAE of Vector Wind Difference
0
0.5
1
1.5
2
2.5
3
3.5
4
36-km 12-km 4-km
m/s
NOFDDAOFDDAGFDDAMFDDA
MAE of Wind Direction
0
5
10
15
20
25
36-km 12-km 4-km
Degr
ee
NOFDDAOFDDAGFDDAMFDDA
MAE of Temperature
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
36-km 12-km 4-km
K
NOFDDAOFDDAGFDDAMFDDA
MAE of Water Vapor Mixing Ratio
0
0.2
0.4
0.6
0.8
1
1.2
36-km 12-km 4-km
g/kg
NOFDDAOFDDAGFDDAMFDDA
10
CAPTEX-83: MAE of WRF-Simulated Surface Layer Fields Averaged Over 48-h Time Period
MAE of Surface-layer Vector Wind Difference
0
0.5
1
1.5
2
2.5
3
3.5
4
36-km 12-km 4-km
m/s
NOFDDAOFDDAGFDDAMFDDA
MAE of Surface-layer Wind Direction
0
5
10
15
20
25
30
35
40
36-km 12-km 4-km
Degr
ee
NOFDDAOFDDAGFDDAMFDDA
MAE of Surface-layer Temperature
0
0.5
1
1.5
2
2.5
3
36-km 12-km 4-km
K
NOFDDAOFDDAGFDDAMFDDA
MAE of Surface-layer Water Vapor Mixing Ratio
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
36-km 12-km 4-km
g/k
NOFDDAOFDDAGFDDAMFDDA
11
• Alaska-08 Case
72-h model run, 12-km/4-km domains, 45 model layers very high vertical resolution, with half-layer heights of 2 m, 6m, 10m, etc.
Starting: 0000 UTC 23 Jan 2008Ending: 0000 UTC 26 Jan 2008(IC/LBC/FDDA inputs based on WRF OBSGRID)
Physics: MYJ PBL, KF CPS on 12- km grid,Dudhia SW and RRTM LW, Noah LSM, etc
14
YESNOYESYESMFDDA/MFDDAS
YESNONOYESGFDDA/GFDDAS
NONOYESNOOFDDA
NONONONONOFDDA
OBS Nudging3D/Sfc Analysis NudgingOBS Nudging3D/Sfc Analysis
NudgingExp. Name
4-km12-km
Experimental Design for Multi-scale FDDAAlaska-08 Jan 2008 (12/4-km grids)
15
22N/AN/ATWINDO (hr)
824N/AN/Adt (sec)
124N/AN/AIONF
100100N/AN/ARINXY (km)
Nudging all layersNudging all layersN/ANudging all layersMass field
Nudging all layersNudging all layersN/ANudging all layersWind field
4*10-44*10-4N/A3*10-4G (1/sec)
4-km12-km4-km12-km
OBS Nudging3D/Sfc Analysis Nudging
FDDA Experimental Design and ParametersAlaska-08 Jan 2008 (12/4-km grids)
16
Alaska-08: RMSE of WRF-Simulated Fields Averaged Over Three 12 UTC (3 LST) Times and All Model Layers below 750 hPa
RMSE of U-component
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
12-km 4-km
m/s
NOFDDAOFDDAGFDDAGFDDASMFDDAMFDDAS
RMSE of V-component
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
12-km 4-km
m/s
NOFDDAOFDDAGFDDAGFDDASMFDDAMFDDAS
RMSE of Temperature
0
0.5
1
1.5
2
2.5
3
3.5
4
12-km 4-km
K
NOFDDAOFDDAGFDDAGFDDASMFDDAMFDDAS
RMSE of Relative Humidity
0
5
10
15
20
25
30
12-km 4-km
%
NOFDDAOFDDAGFDDAGFDDASMFDDAMFDDAS
17
Alaska-08: RMSE of WRF-Simulated Surface Fields Averaged Over Three 12 UTC (3 LST) Times
RMSE of Surface U-component
0
0.5
1
1.5
2
2.5
3
3.5
4
12-km 4-km
m/s
NOFDDAOFDDAGFDDAGFDDASMFDDAMFDDAS
RMSE of Surface V-component
0
0.5
1
1.5
2
2.5
3
3.5
12-km 4-km
m/s
NOFDDAOFDDAGFDDAGFDDASMFDDAMFDDAS
RMSE of Surface Temperature
0
1
2
3
4
5
6
12-km 4-km
K
NOFDDAOFDDAGFDDAGFDDASMFDDAMFDDAS
RMSE of Surface Relative Humidity
0
5
10
15
20
25
12-km 4-km
%
NOFDDAOFDDAGFDDAGFDDASMFDDAMFDDAS
18
PBL Depth at 60 h, 3 LST
PBL Depth at Fairbanks
Model Sounding at Fairbanks
WRF-Simulated PBL Depth (m)
*
19
A Simple Weighting Function Used for the Vertical Spreading of Surface Innovation
35 m
23 m
12.5 m
8 m
4 m
0.0 1.0
velo
city
wei
ghtin
g fu
nctio
n 35 m
23 m
12.5 m
8 m
4 m
0.0 1.0
velo
city
wei
ghtin
g fu
nctio
n 35 m
23 m
12.5 m
8 m
4 m
0.0 1.0
tem
pera
ture
wei
ghtin
g fu
nctio
n
35 m
23 m
12.5 m
8 m
4 m
0.0 1.0
tem
pera
ture
wei
ghtin
g fu
nctio
n
Wind Fields Mass Fields
20
Alaska-08: RMSE of WRF-Simulated Fields Averaged Over All Three 12 UTC Times and All Model Layers below 750 hPa
RMSE of U-component
00.5
11.5
22.5
33.5
44.5
5
12-km 4-km
m/s
NOFDDAMFDDAOMFDDAS
RMSE of Temperature
0
0.5
1
1.5
2
2.5
3
3.5
12-km 4-km
K
NOFDDAMFDDAOMFDDAS
RMSE of Relative Humidity
0
5
10
15
20
25
30
12-km 4-km
%
NOFDDAMFDDAOMFDDAS
RMSE of V-component
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
12-km 4-km
m/s
NOFDDAMFDDAOMFDDAS
21
Alaska-08: RMSE of WRF-Simulated Surface Fields Averaged All Three 12 UTC Times
RMSE of Surface U-component
0
0.5
1
1.5
2
2.5
3
3.5
12-km 4-km
m/s
NOFDDAMFDDAOMFDDAS
RMSE of Surface V-component
0
0.5
1
1.5
2
2.5
3
3.5
12-km 4-km
m/s
NOFDDAMFDDAOMFDDAS
RMSE of Surface Temperature
0
1
2
3
4
5
6
12-km 4-km
K
NOFDDAMFDDAOMFDDAS
RMSE of Surface Relative Humidity
0
5
10
15
20
25
12-km 4-km
%
NOFDDAMFDDAOMFDDAS
22
Alaska-08: RMSE of WRF-Simulated Surface Fields Averaged Over All 3-h Times
RMSE of Surface U-component
0
0.5
1
1.5
2
2.5
3
3.5
4
12-km 4-km
m/s
NOFDDAMFDDAOMFDDAS
RMSE of Surface V-component
0
0.5
1
1.5
2
2.5
3
3.5
12-km 4-km
m/s
NOFDDAMFDDAOMFDDAS
RMSE of Surface Temperature
0
1
2
3
4
5
6
12-km 4-km
K
NOFDDAMFDDAOMFDDAS
RMSE of Surface Relative Humidity
15.5
16
16.5
17
17.5
18
18.5
19
19.5
20
12-km 4-km
%
NOFDDAMFDDAOMFDDAS
24
Surface Observations
2-m (k=1) Model Temperature and 10-m (k=3) Wind
(MFDDAS)
4-km Grid, 0600 UTC 25 Jan 2008
2-m (k=1) Model Temperature and 10-m (k=3) Wind
(NOFDDA)
25
Summary and Conclusions
• PSU leads the DTRA-funded nudging FDDA implementation in WRF, and has recently released its surface analysis nudging in WRFV3.1.
• PSU has been working with NCAR to improve observation nudging and to build an end-to-end FDDA system.
• The end-to-end FDDA system involves observation preprocessing, objective analysis with OBSGRID (or VAR), and observation QC.
26
Summary and Conclusions –CAPTEX-83 Multiscale FDDA
• Multiscale FDDA results for the 48-h CAPTEX dynamic analysis case, both 3D analysis-nudging only and obs-nudging only significantly reduce model error.
• Analysis nudging shows closer fit to obs than obs nudging on the coarser 36-km grid, and obs nudging better fits the obs than analysis nudging on the 12-km grid, as expected due to stronger obs nudging strength.
• Multiscale FDDA produces the best fit to the obs over all three domains.
• On the 4-km grid, multiscale FDDA (combined both 3D analysis nudging and obs nudging on coarser domains, and only obs nudging on finer domains) produces comparable or slightly better fit to the obs compared to using obs-nudging only.
27
Summary and Conclusions –Alaska End-to-End FDDA System
• First multiscale WRF FDDA application using the end-to-end FDDA system.
• Multiscale FDDA (combined 3D analysis and obsnudging on 12-km domain, obs nudging on 4-km domain) is the best overall in fitting the observations.
• Degradation while using surface-data nudging is caused by spreading surface innovations throughout the high PBL depths predicted by WRF MYJ PBL scheme.
• Using simplified vertical weights near the surface for surface-data nudging caused large improvement in all variables compared to NOFDDA control, and also slight improvement with the addition of surface analysis nudging when verified at all 3-hourly times throughout the 72-h period.
28
FUTURE WORK
• Improving the nudging strategy so that the vertical spreading of the surface obs is not solely dependent on the PBL depth. Other factors such as PBL Regime should be used in addition to the PBL depth.
• Implement improved strategies for applications with very high vertical resolution.
• Expand the flexibility of the WRF observation nudging to include options often used at Penn State for MM5 obs nudging (e.g. height-level based observations, additional space and time weighting factors for surface observations, additional options for vertical spreading of surface data and anisotropic horizontal weighting functions in the vicinity of terrain, improved QC at finer vertical resolution for FDDA observation data sets, etc).
29
FUTURE WORK
• Transition hybrid nudging – EnKF from Lorenz and shallow water model (Lei and Stauffer 2008,2009) to WRF.
30
ACKNOWLEDGEMENTS
• WRF nudging FDDA implementation is supported by the Defense Threat Reduction Agency under contract no. HDTRA-1-07-C-0076 through Penn State under the supervision of Dr. John Hannan.
• The Alaska WRF modeling study is also supported by US EPA under contract no. EP08D000663 through Penn State under the supervision of Drs. Ken Schere and Jon Pleim.
• We also acknowledge Jeff Zielonka and Brian Reen of Penn State for their help in WRF verification for the Alaska case study