Monthly Technical Report PROJECT TITLE

Investigation of surface layer parameterization of the WRF model and its impact on the observed nocturnal wind speed bias: Period of investigation focuses on the Second Texas Air Quality Study (TexAQS II) in 2006

PROJECT # 12-TN1

PROJECT PARTICIPANTS

University of Maryland (UMD), College Park Air Resources Laboratory, NOAA

DATE SUBMITTED

7/8/2013

REPORTING PERIOD

From: June 1, 2013 To: June 30, 2013

REPORT # 4

University of Maryland (UMD)

Invoice # #2

Amount $0.00

A Financial Status Report (FSR) and Invoice will be submitted separately from each of the Project Participants reflecting charges for this Reporting Period. I understand that the FSR and Invoice are due to the AQRP by the 15th of the month following the reporting period shown above. Detailed Accomplishments by Task Motivation We continued the effort from last month to rerun the simulation with WRF Model version 3.4.1 for the innermost nest for Eastern Texas. This effort stemmed from a relevant decision that this upgraded version included two bug fixes from version 3.2 that we used in a previous TCEQ-funded project addressing the wind-bias problem described in the title of this project. The fixes dealt with the Yonsei University (YSU) planetary boundary layer (PBL) under stable atmospheric conditions. The first introduced an adjustment of convective velocity scale that results in reduced mixing in the upper layers of the stable layer. The second reduced the minimum turbulence eddy diffusivity in the stable layer. Last month we did the simulation with the newer version ofWRF coupling the YSU PBL with the U.S. National Centers for Environmental Prediction; Oregon State University; Air Force; Hydrological Research Laboratory (Noah) land surface model (LSM). This month we did another simulation choosing again YSU PBL but with the MM5 5-layer slab LSM. The results of these runs are compared to the corresponding runs with WRF version 3.2 performed in the previous wind bias project. Model set up The geometric and physics package configuration used in this study is identical to that used in the previous wind-bias project (Lee et al., 2012). The simulation was conducted over the period between June 4 and June 12,2006. For the sake of convenient reference, a domain configuration diagram (Fig. 1) a physics package selections (Table 1), and measurements from the Continuous Air Monitoring Site (CAMS) used to verify the model results (Fig. 2) are included here.

Fig. 1. WRF domains used for model simulations in three different spatial resolutions: 36-km (NA36), 12-km(SUS12) and 4-km (TX04).

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fi d' h' dTable 1. Model con Igurattons use lD t IS stu IV

Domain name NA36 SUS12 TX04Resolution (km) 36 12 4Domain coverage Continental U.S. Texas and neighboring states Eastern TexasHorizontal grid dimensions 162 x 128 174 x 138 216x288 ,Initialization NAM + NCEP daily SST Nest-down ofSUS12

run in 2-way nestingMicrophysics WSMS" WSM6b

Cloud Scheme KFc NoneRadiation scheme RRTMo for longwave radiation MMS (Dudhia)" for shortwave radiationPBL scheme YSUt schemeLand surface model S-Iayer slab model'' or Noah LSMNudging 3D grid nudging (no nudging of mass fields within PBL)a b cWRF Single-Moment S-class (Hong et al., 2004). WRF Single-Moment 6-class (Hong and Lim, 2006). Kain and

d eFritsch scheme (Kain, 2004). Rapid Radiative Transfer Model scheme (Mlawer et a1. 1997). Dudhia (1989).f gYonsei University scheme (Hong et aI., 2006). S-layer soil temperature model (Grell et aI., 1994).

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Verification against UHCC and CAMS data

Figures 3a to 3d show the time series for 2 meter temperature, sensible heat flux, 10 meter windspeed, and 10 meter wind direction comparing model results between June 4 and June 13 2006,using MM5 5-layer LSM (red) with using NOAH LSM (blue) against UH Coastal Centermeasurements (black), respectively. The exact corresponding figures based on WRF version 3.2

AQPR Monthly Technical Report TemplateRevised January 2011

are given in Appendix (Figs. Ala to AId). There is not large differences between thecorresponding figures between Fig. 3 and Fig. AI. The general rankings between the Slab LSMand NOAH LSM runs stayed the same between these figures implying that the upgrade of WRFto version 3.4 did not dramatically impact 2 m temperature, 10 m wind speed and wind direction,and sensible heat flux at the UH Coastal Center. Similar to Figs. AI, sensible heat flux showedrather encouraging benefits of using the more sophisticated NOAH LSM. (Figs. 4a and 4b) wereproduced with model results verified against CAM sites (See Fig.2) for 2 m temperature and 10m wind speed, respectively. Again their counterparts from results based on WRF version 3.2 areincluded in Appendix (Figs. A2a and A2b). Over the 46 CAMS sites (Fig. 2), 2 m temperatureprediction improvement using NOAH LSM is quite noticeable. The next challenging task is tolink this with the governing tunable parameters in PBL and surface layer schemes that delineatethe CAMS sites behavior with that of the coastal site.

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AQPR Monthly Technical Report TemplateRevised January 2011

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Fig 4. Comparison of model results between Slab LSM (red) and NOAH LSM (blue) simulaitonsbetween June 4 and June 13 2006 over 46 CAMS sites (Fig. 2) for (a) 2 m temperature, and (b)10m wind speed.

Begun modifying the WRF Model for extra outputs

We are at an initial stage to decide what extra output within the MM5 surface layer similarityschemes (see April 20 13 report) to be generated to facilitate investigation of the nocturnal nearsurface high wind-speed biases. There are two approaches to generate extra output: (1) Forexisting variables and parameters within the model code, one can simply activate thecorresponding output switches in the registry file of the model and no re-compilation is required.Create a text file such as "myoutfields.txt" and include a pointer in the "namelist.input" file tothat text file, such as "iofields filename=' myoutfields.txt' "; (2) For intermediate values ordiagnostic quantities desired to be investigated, one can define the new quantities in the registryand modify the code to achieve that. Recompile the code and execute it. Table 2 shows a samplesegment of the registry file.

AQPR Monthly Technical Report Tempi teRevised January 2011

Table 2. A segment ofthe Registry file of WRF: the second line refers to the u component ofwind and third line refers to rate of convective rainfall

Entry Type Sym Dims Use TLev Stagger I/O Name

State real u ikjb dyn_em 2 x iOrhusdf "U"

State real RAINC IJ rmsc 1 - rhdu "PRECIP"

Appendix:

Herein we recite old results using the exact simulation setting as prescribed above but usingWRF version 3.2 in the wind-bias project we conducted for TCEQ last year. Figures Ala to AIdare corresponding to Figs. 3a to 3d, and Figs. A2a and A2b are corresponding to Figs. 4a and 4b.

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References:

Chen, F, and 1. Dudhia, 2001: Coupling and advanced land surface-hydrology model with the Penn State-NCARMM5 modeling system. Part I: model implementation and sensitivity. Mon. Wea. Rev" 129, 569-585.

Dudhia, 1., 1989: Numerical Study of Convection observed during the Winter Monsoon Experiment using amesoscale two-dimensional model, J. Atmos. Sci., 46, 3077-3107,

Hong, S.-Y., and 1,-0.1. Lim, 2006: The WRF Single-Moment 6-Class Microphysics Scheme (WSM6), J. KoreanMeteor, Soc. 42, 129-151.

Grell, G,A" Dudhia, 1., Stauffer, D., 1994, A description of the fifth-generation Penn StatelNCAR mesoscale model(MM5), NCAR Technical Note: NCARlTN-398pSTR.

Hong, S, Y., Y. Noh, and 1. Dudhia, 2006: A new vertical diffusion package with an explicit treatment ofentraimnent processes, Man. Wea. Rev" 134,2318-2341.

Kain, 1, S., 2004: The Kain-Fritsch convective parameterization: An update. J. Appl. Meteor., 43,170-181.

Lee, P., F, Ngan, and H. C, Kim, 2012: Final Report submitted to TCEQ: Investigation ofnoctumal surface windbias by the WRF-ARW meteorological model for TexAQS-II in 2006. pp. 1-22,

Mlawer, E. 1" S. 1. Taubman, P. D. Brown, M. 1, Iacono and S. A. Clough, 1997: Radiative transfer forinhomogeneous atmosphere: RTTM, a validated correlated-k model for the longwave, J. Geophys. Res.,102,16663-16682.

Hong, S,-Y., 1. Dudhia, and S.-H. Chen, 2004: A Revised Approach to Ice Microphysical Processes for the BulkParameterization of Clouds and Precipitation, Mon. Wea, Rev., 132, 103-120.

Hong, S.-Y., and Y. Noh, and 1. Dudhia, 2006: A new vertical diffusion package with an explicit treatment ofentrainment processes, Mon. Wea. Rev" 134, 2318-2341,

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WRF Model Version 3.4.1 (2012): WRF model update. Availablehttp://www .mmm. ucar. edulwrf/users/wrfv3 .4/updates- 3.4 .l.html

Preliminary Analysis

No preliminary analysis available at this point.

Data Collected

NIA

Identify Problems of Issues Encountered and Proposed Solutions of Adjustments

There is a necessity to rerun the WRF model with version 3A.1 using two physics packagespecifications for PBL and LSM options: YSU coupled with MM5 5-1ayer LSM, and YSU PBLwith the NOAH LSM. These sensitivities were also done with version 3.2 in the previous wind-bias project we performed for TCEQ (Lee et al., 2012). In theory, the NOAH LSM is morecapable to rectify the wind bias deficiency as it has a sophisticated vegetation model includingfour soil layers for soil temperature and moisture prediction (Chen and Dudhia, 2001).

Goals and Anticipated Issues for the Succeeding Reporting Period

1. Further evaluate some of the model rerun results.2. Compare the new model results with those conducted last year (Lee et al. 2012) and

examine the performance statistics to confirm improvements by the upgraded WRFmodel.

3. Study the surface layer similarity code further to decide what to be added to the outputfiles to facilitate the wind bias problem investigation.

Detailed Analysis of the Progress of the Task Order to Date

Significant progress has been made on this fifth scheduled technical reporting period as aliterature survey on the subject and rerun the WRF model with one of the latest versions hasresulted in guidance as which are likely the largest uncertainties in the linkage between a PBLscheme and a surface layer scheme.

All other Project Tasks are on schedule as presented in the Task Order.

Submitted to AQRP by:

Principal Investigator: Daniel Tong

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