Tanya L. Otte and Robert C. Gilliam

NOAA Air Resources Laboratory, Research Triangle Park, NC (In partnership with U.S. EPA National Exposure Research Laboratory)

6th Annual CMAS Conference Chapel Hill, NC2 October 2007

A Nudging Strategy for Mesobeta-Scale WRF Simulations Suitable

for Retrospective Air Quality Modeling:Preliminary Results

What is “Nudging”?

• Formally, “Newtonian relaxation”• Method of dynamically relaxing model toward observed state

Includes non-physical forcing term in prognostic equations Uses difference between model and best estimate of observation in

space and time• Used throughout retrospective simulations (i.e., a “dynamic

analysis”) to keep meteorology as close to observed as possible Extends run length of “usable” meteorology for AQ modeling

• One method of FDDA in MM5 and WRF• Typically applied to:

Horizontal wind components (U and V) Temperature (T) above the PBL Water vapor mixing ratio (Q) above the PBL

Motivation

• Current nudging strategies for MM5 and WRF typically based on four papers: Stauffer and Seaman, MWR, 1990

• Initial MM5 nudging paper; both analysis and obs nudging Stauffer, Seaman, and Binkowski, MWR, 1991

• Nudging in PBL…OK for wind, restrict for mass and moisture Stauffer and Seaman, JAM, 1994

• Multiscale approach to phase from analysis to obs nudgingas horizontal grid spacing decreases

Seaman, Stauffer, and Lario-Gibbs, JAM, 1995• Define nudging coefficients for multiscale approach• Use 36/12/4 km nesting for air quality modeling

Motivation (continued)

• Seaman et al. (1995) used input analyses derived from 12-h, 2.5-deg 3D analyses and 3-h, 2.5-deg surface analyses Analysis to observations done in MM5 with “RAWINS” toward

conventional surface observations and rawinsondes

• Current archived analyses are often as fine as 3-h, 12-km (e.g., NAM218) for 3D and surface Analyses include combination of conventional and remote-

sensed observations Can use “RAWINS” with MM5; only 3DVar in WRF (for now)

• Is nudging strategy (coefficients and multiscale approach) in Seaman et al. (1995) too restrictive given today’s data availability?

WRFv2.2+ Setup

Input Analyses NARR (32-km) grid, 3-hourly

Explicit Microphysics WSM 6

Convective Parameterization Kain-Fritsch

PBL Model ACM2*

Land-Surface Model Pleim-Xiu LSM*

Radiation RRTM LW & Dudhia SW

* Not in released code; to be included in WRFv3

WRF Domain12 km, 290 x 251 x 34 layers

Sensitivity Overview

Low: Typical nudging coefficients for 12-km 1.0 x 10-4 s-1 for U,V,T; 1.0 x 10-5 s-1 for Q From Seaman et al., JAM, 1995 for analysis nudging with obs nudging @12-km

Std: Typical nudging coefficients for 36-km 3.0 x 10-4 s-1 for U,V,T,Q ~1-h e-folding time for physical processes

High: Nudging coefficients with half e-folding time of Std 5.5 x 10-4 s-1 for U,V,T,Q ~0.5-h e-folding time for physical processes

Std+PBL: Same as Std, but with nudging toward temperature and moisture in PBL

High+PBL: Same as High, but with nudging toward temperature and moisture in PBL

12 UTC 4 Aug – 00 UTC 25 Aug 2006

Four 5.5-day overlapping run segments

Preliminary Analysis

• Show mean error (“bias”) from 20-day runs Keep it simple, for now MAE and RMSE do not change “bottom line”

• Verify against ~700 NWS surface stations Includes T, “Q”, wind, surface pressure Included in analyses (i.e., nudged) Includes urban, suburban, and rural sites

• Verify against 67 CASTNET observations Includes T, RH, wind, SW radiation Independent of analyses (i.e., not considered in nudging) Largely rural sites

2-m Temperature vs. CASTNETDaily By Day in WRF Run

2-m Dew Point vs. CASTNETDaily By Day in WRF Run

SW Radiation vs. CASTNETDaily By Day in WRF Run

10-m Wind Speed vs. CASTNETDaily By Day in WRF Run

Diurnal 2-m TemperatureNudged Not Nudged

Diurnal 2-m Mixing Ratio

2-m Q for CASTNET not included because CASTNET does not report surface pressure, which is required to convert RH to Q.

Nudged Not Nudged

Diurnal 10-m Wind SpeedNudged Not Nudged

Diurnal 10-m Wind DirectionNudged Not Nudged

Summary

• Preliminary results suggest: Nudging coefficients for wind, temperature, and moisture can be

increased over Seaman et al. (1995), i.e., “Low” values, *if not obs nudging*

Stronger nudging, i.e., “High” values, reduces bias in 10-m wind speed, but has little impact on 2-m temperature and dew point.

Nudging toward moisture may still need to be weaker than towards temperature and wind.

Nudging toward temperature and moisture in the PBL increases the bias for 2-m temperature, 2-m dew point, 10-m wind speed, and shortwave radiation at CASTNET sites (not nudged).

As expected, statistics vs. NWS observations are better than statistics vs. CASTNET sites, which are independent of the analyses.

Model behavior with and without nudging in the PBL is vastly different during stable (nighttime) regime than convective (daytime) regime

Next Steps

• Further evaluation with current runs Evaluation against upper-air observations,

PBL heights, precipitation, etc. Additional methods

• Repeat sensitivities with NAM-218 (12-km) input• Vary nudging strength “by variable”• Use observation nudging with analysis nudging• Test with analysis (e.g., RAWINS) in WRF

0

0.5

1

1.5

2

2.5

3

3.5

4

8/4/

2006

8/5/

2006

8/6/

2006

8/7/

2006

8/8/

2006

8/9/

2006

8/10

/200

6

8/11

/200

6

8/12

/200

6

8/13

/200

6

8/14

/200

6

8/15

/200

6

8/16

/200

6

8/17

/200

6

8/18

/200

6

8/19

/200

6

8/20

/200

6

8/21

/200

6

8/22

/200

6

8/23

/200

6

8/24

/200

6

8/25

/200

6

wrf_ACMPX_12km (RMSE)

NARR_StdCoeffs (RMSE)wrf_ACMPX_12km (MAE)

NARR_StdCoeffs (MAE)

Looking Ahead…2-m Temp. using NARR and NAM218 vs. CASTNET

Uses 12-km NAM218 analyses; initialized 00 UTC 20 Jul

Uses 32-km NARR analyses; initialized 12 UTC 4 Aug

MA

E a

nd R

MS

E [

K]

Acknowledgments

• Jonathan Pleim (NOAA)

• Lara Reynolds (CSC)

Disclaimer: The research presented here was performed under the Memorandum of Understanding between the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Commerce's National Oceanic and Atmospheric Administration (NOAA) and under agreement number DW13921548. This work constitutes a contribution to the NOAA Air Quality Program. Although it has been reviewed by EPA and NOAA and approved for publication, it does not necessarily reflect their policies or views.