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Development of a Real-Time Boundary Layer Analysis

Jeff McQueen, Caterina Tassone, MarinaTsidulko, Yanqui Zhu, Lidia Cucurull, Shun Liu, Geoff Manikin and Geoff DiMego

NOAA/NWS/NCEP/EMC

May 14, 2023

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Collaborators• ACARS estimates:

– Marina Tsidulko and Caterina Tassone, NCEP/EMC

• MPLNET:– Judd Welton, Larry Belcher, NASA/GSFC

• COSMIC:– UCAR , Sharome Goode

• NexRad Radars: – Laurie Bianco/Pam Heinselmenn (OAR/NSSL)

• NCAS lidars & CALIPSO : – Everette Joseph, Michael Hicks, Belay (Howard U. - DC)– Ray Hoff, Ruben Delgado, Wallace McMillan (U. Maryland-Baltimore Campus)

• Dispersion model impacts: – Roland Draxler, W. Pendergrass, C. Vogel (NOAA/ARL)– Kyle Dedrick (DTRA)– Matt Simpson (DHS/IMAAC)

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•NOAA-NASA-NCAS High Resolution

Boundary Layer Analysis Project •

NOAA-NASA-NCAS High Resolution Boundary Layer Analysis Project

                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                

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Program Tasks

• Derivation of PBL heights from: – RAOB and ACARS Aircraft profiles – MPLNET LIDAR measurements– ESRL/CAP Profilers– COSMIC Radio Occultation Measurements– NWS NEXRAD radars ( w/ NOAA/NSSL)– CALIPSO backscatter profiles for evaluation (UMBC)– NCAS LIDAR measurements for evaluation

• Evaluation of RUC model 1st guess fields used for RTMA– Modified bulk Richardson number based PBL

• Assimilation of PBL heights into RTMA• Evaluation of plume dispersion models with RTMA

analyses• Evaluation of low-level RTMA winds and stability products

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Observations RAOBS and ACARS: Bulk Richardson Number (RIB) approach (Vogelezang and Holtslag): PBL height is defined as the level where the RIB exceeds the Richardson

Critical Number (0.25)

Derivation of PBL height from Aircraft observations (M.Tsidulko)

-ACARS level data (U,V,T and P)-Surface Observation attached-Moisture analysis from model-QC

2shsh

))()((g/

bu)v(v)u(uhθθθ

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vsvhvs

sRIBz

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Radar comparison to raobs Shun Liu & Caterina Tassone

•Current estimates are too low•Compared to nearby airports within 30 minutes•Radar PBL Z computed by looking at maximum reflectivity

•Include VAD wind profiles also ?•Limit computations to below 4 km

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COSMIC GPS Radio Occultation Lidia Cucurull and Caterina Tassone

• All data collected during August-September 2009 over CONUS• Very few observations per day

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Other data sources

Bianco, et al. 2008Automated algorithmFor PBLH detection

915 MHZ, boundary Layer profilersCloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)

NASA Micro-Pulse Lidar NETwork (MPLNET)

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NCEP Real-Time Mesoscale AnalysisYanqui Zhu

• 5 km hourly analysis 10 m winds, 2m temperature and dew point, cloud cover and precip

• 2-D variational Assimilation (NCEP GSI)• RUC 13 km 1 hour forecast used as background analysis

• NCEP format PREPBUFR PBL Height files for ingest:– ACARS– RAOBS– Radar– COSMIC– MPLNET– Boundary Layer Profilers

• Background Errors: NMC Method• Determine weighting functions:

– By stability, low level temperature ???

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Evaluation of RUC first guess PBLH

PBL depth - Using a vertical profile of virtual potential temperature from RUC native levels, find the height above surface at which theta-v (virtual potential temperature) again exceeds theta-v at surface (lowest native level - 5 m above surface). Surface theta-v is boosted by an additional 0.5 K.

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RTMA 5 km PBL Analysis Yanqiu Zhu, NCEP/EMC

-Background field: RUC 13 km 1h forecast-Observations: ACARS and RAOBS

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PBL Variability Experiment DC-Baltimore Area Sept 14-15 and 19-20 2009 Purpose:

Investigate the evolution and spatial variability of the urban atmospheric PBL height

Evaluate various instrument platforms for detecting PBL height Data collected:

Radiosondes: HU-Downtown, RFK stadium, Beltsville, Baltimore Raman lidar: Beltsville Elastic Lidar Facility: Baltimore Sodar: DOE Forrestal Bldng, DC Microwave radiometer: Beltsville Wind lidar: Baltimore, Navy Annex MPLNET COSMIC CALIPSO

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Evaluation of ACARS withday-time radiosondes

Good agreement;ACARS underestimates PBL height in early afternoon

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Different methods for deriving PBL height from ACARS: Local Richardson Number Parcel method Modified RIB (unstable)

14 September 2009

0.5Kθvsθ'vs

Evaluation of Various methods to determine PBLH

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At 20z:-RUC PBL height at 1800m-Lidar PBL height at 1500m-RS PBL height at 1600-1800m-ACARS PBL height 200m: stable THV profile - Observed clouds at 21z

Modify surface temperature for all cases

Evaluation of Various methods to determine PBLH

15 September 2009

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HU-Beltsville Raman Lidar (HURL) comparisons

A Raman lidar system is designed to make both daytime and nighttime measurements of atmospheric water vapor and aerosols

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UMD Baltimore Campus Elastic Lidar Facility (ELF) comparisons

• ACARS Bulk RI number estimate under-estimates PBLH for clear sky case.

• Very late on estimating growth of PBL compared to sondes and lidar

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Possible Additional Products

• Hourly analyses of the following 2.5 km PBL products are expected from this project: – PBL height – Ventilation index – Boundary layer transport wind – Pasquill-Gifford stability – Sigma-Theta stability profiles

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Summary & Future Work• DC PBL experiment

– RUC background PBLH agrees well w/ daytime convective PBL measurements (radiosondes, lidar) but too low at night

– ACARS PBLH estimates improved with sfc temperature adjustments

• ACARS PBLH: – good diurnal pattern– Under-estimates PBLH in late afternoon– use closest surface observation at flight level to compute PBLH

• COSMIC, radar : quantify biases for assimilation

Additional PBLH estimates from: CAP, MPLNET, multi-level towers, ceiliometers &, sfc flux sites

Begin RTMA PBL evaluation w/ lidars, CALIPSO Evaluate Impact on dispersion model simulations

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BACKUPS

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ATDD Radiosondes

Howard U. Downtown RFK Stadium

09, 11,13,14,15,17 EDT

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Micro-wave profilers,NCAS/Howard U. - Beltsville,MD)