Characterizing urban boundary layer dynamics using radar, lidar, sodar, surface observations and predictions from numerical models Mark Arend Optical Remote Sensing Lab City College of New York NOAA CREST with E. Gutierrez *, B. Madhavan, C. M. Gan, S. Abdelazim, B. Gross, D. Santoro, F. Moshary, J. Gonzalez *, and S. Ahmed Collaborators: R. D. Bornstein**, A. Martilli***, *Mechanical Engineering Department, City College of New York **Meteorology Department, San Jose State University *** Research Centre for Energy, Environment and Technology (CIEMAT), Spain. This research was supported, in part, by grants from NOAA Through the NOAA Coperative Science Centers NOAA ISET and NOAA CREST and computer time from the City University of New York High Performance Computing Center under NSF Grants CNS-0855217 and CNS - 0958379.

GOAL APPROACH Observe and model the growth of the convective boundary layer during “bad air days” e.g. boundary layer mixing is dominated by thermal fluxes from the surface as opposed to synoptic scale disturbances (fronts producing wind shears) APPROACH Operate ground based surface and unique remote sensing meteorological instrumentation for New York City (our test bed for an Urban/Coastal megacity). Ingest data in a continuous and automated fashion Pick selected meteorological events Characterize vertical wind, temperature and mixing layer height Develop regional high resolution Urban/Coastal mesoscale model, compare to observations and other models

NYCMetNet Vertical Profiling Assets and Surface Station Ingest

Available from NYC MetNet Web site http://nycmetnet.ccny.cuny.edu

Available from NYC MetNet Web site http://nycmetnet.ccny.cuny.edu

Synoptic scale condition :Warm summer days 2010 Focus on Aug 30,31 and Sept1 (from NCEP Daily Weather maps 07:00 EST) Expect Geostrophic Winds from the NW initially Aug 30 Aug 31 Sept 1 Sept 2

Observed RWP Wind Speed vs. Time stacked every 80m 2 km Scale 10 m/sec surface

Observed RWP Wind Direction vs. Time All vertical levels (degrees from N) Modulo (-60,300)

Wind direction in degrees from N at 650m height 3rd day First 2 days

Signature of thermal fluxes Vertical Velocity from all sodar levels (20 to 200 m above building tops)

WRF and uWRF Setup (** see poster 790 tomorrow) Coarse WRF for input in to CMAQ WRF-NMM - NCEP 0Z 24 –h forecast data. 12 km grid resolution Mellor-Yamada-Janjic (MYJ) 2.5 local (TKE) PBL scheme. First level 27 m NOAH Land Surface Module (Bulk Parameterization) CMAQ version 4.6 Nested 12km x 12km Eddy Vertical Diffusion “K-coefficient” aero3 aerosol mechanism uWRF with Multi-layer urban canopy surface layer parameterization* A 24-h forecast was performed (12-h spin up) for NYC Aug 30,31, Sept1. Four two-way nested domains grid spacing of 9, 3, 1 and 0.333 km Initial and boundary conditions from NAM (resolution: 12 km). Vertical resolution of 51 terrain Following sigma levels (33 levels in the lowest 1.5 km, first level ~10m. PBL Parameterization: Bougeault and Lacarrère (BouLac). Urban classes were derived from the National Land Cover Data (NLCD)** (** see poster 790 tomorrow) * Martilli A., Clappier A., and Rotach M. W., 2002: An urban surface exchange parameterization for mesoscale models, Boundary-Layer Meteorol., 104, 26, 304.

Typically see temperature profile gradient discrepancy between MWR and coarse WRF MODEL --May affect how CMAQ interprets mixing layer height-- MWR Significant differences in Air Temperature envelope can test Urban Heat Island Mechanisms.

August 30, 2010 MWR Temperature and Relative Humidity Profiles WRF Temperature and Relative Humidity Profiles

MWR and WRF Temperature profiles Difference plot and constant difference time evolution August 30, 2010

Lidar Return Signal Range Corrected, 1064 nm

August 31, 2010 MWR Temperature and Relative Humidity Profiles WRF Temperature and Relative Humidity Profiles

MWR and WRF Temperature profiles Difference plot and constant difference time evolution August 31, 2010

Lidar Return Signal Range Corrected, 1064 nm

September 1, 2010 MWR Temperature and Relative Humidity Profiles

MWR and WRF Temperature profiles Difference plot and constant difference time evolution September 1, 2010

Lidar Return Signal Range Corrected, 1064 nm

Wavelet transform analysis of PBL height. K. J. Davis, N *Wavelet transform analysis of PBL height. K. J. Davis, N. Gamageb, et al., “An objective method for deriving atmospheric structure from airborne lidar observations,” J. Atmos. Oceanic Technol. 17, 1455–1468 (2000).

Conclusion Vertical profilers are used to characterize coastal/urban boundary layer dynamics and to test urban surface parameterization schemes Outcome: Improvements have been made to properly represent surface and boundary layer interactions Further investigation is needed to appropriately resolve discrepancies between observations and models