On the Rooftop Micrometeorology and Heat Islands of

On the Rooftop Micrometeorology and Heat Islands of Washington and New York City William R. Pendergrass, Bruce B. Hicks*, and Christoph A. Vogel NOAA/ARL/ATDD P. O. Box 2456 Oak Ridge, TN 37831 * Metcorps P. O. Box 1510 Norris, TN 36828

SSG DCNet sites in DC. Not all sites have been operating at all times. Major attention: NAX SSG 60 m AGL NAX 30 m AGL 2 km

The DCNet tower on the H. C. Hoover Department of Commerce building (DOC) in the Federal Triangle area of Washington, DC. All DCNet towers are similar. Key instrumentation: 3 -d sonic anemometer Standard meteorological state variables.

Data analysis steps: 1. Use all data (15 minute averages) from January 2004 onwards. 2. Reject all data sets with missing records. 3. Apply coordinate rotation to drive to zero. 4. Reject all data for which the angle of attack after rotation exceeds 10°. 5. Reject all data for which || > 1 (m/s)2 or || > 1 °C. m/s. 6. Compute -1/L = k. g. /(<-w’u’>3/2. T). 7. For each month and for |1/L| < 0. 005, assume neutrality and compute ln((z – d)/z 0) = k/Cf = 0. 41*u/<-u’w’>½. 8. For assumed values of d (0. 7 h, 0. 8 h, 0. 9 h) compute z 0.

NAS – The National Academy of Sciences. Displacement height (d) and roughness length (z 0) vary with direction and season. Winds from the north pass over the State Department. Elsewhere, there are many trees. We see the seasonal “greening” of Washington. Smoother E W Rougher S Near-neutral only N k/Cf = ln((z – d)/z 0) Z = 25 m h ~ 15 m

DOC – The Department of Commerce H. C. Hoover Building. The White House is to the northwest. Winds from the south pass over the Mall. To the north and east, there are large buildings. Westward is the Ellipse, with trees between it and the DCNet tower. S E N Near-neutral only k/Cf = ln((z – d)/z 0) W Z = 40 m h ~ 30 m

Washington a c Washington New York b d New York Spatial averages of downtown roughness lengths. The left hand diagrams show the differences according to wind quadrant. The right hand diagrams show the overall geometric mean values. The points in (b) and (d) assume d = 0. 8 h. The lines assume d = 0. 7 h and 0. 9 h.

Now look at heat fluxes (actually, ). The first five steps, as before. . . 1. Use all data (15 minute averages) from January 2004 onwards. 2. Reject all data sets with missing records. 3. Apply coordinate rotation to drive to zero. 4. Reject all data for which the angle of attack after rotation exceeds 10°. 5. Reject all data for which || > 1 (m/s)2 or || > 1 °C. m/s. 6. Then, for each hour construct monthly averages of and of T.

Average covariances, 2004/5/6/7 – Silver Spring M J J O S D + -- Middle months, Feb, May, Aug, Nov

Average covariances, 2004/5/6/7 – Times Square, NYC A J J + -- Middle months, Feb, May, Aug, Nov O

NAS DOC DOE NAX NRL FMC SSG EML TSQ Nighttime (2200 – 0500 hrs) average changes in and temperature, for all sites with a sufficiently long data record.

Averages, 2200 to 0500 hours, DOC and DOE, Washington

Averages over 2200 to 0500 hours, TSQ And EML, New York

Conclusions: • The roughness length for the city center of Washington varies with season. Roughness correlates with the leafing of deciduous trees. Mean z 0 ~ 0. 6 m. • New York does not have the seasonal variation. Mean z 0 ~ 0. 8 m. • The effects of air conditioning heating and cooling of buildings is strongly evident in areas with old and large buildings. • For nighttime situations, sensible heat fluxes tend to be directly related to air temperatures. The relationship is well described by the slope of a plot of against T, with a dependence strongest for New York (TSQ: 0. 47 cm/s; EML: 0. 15 cm/s). The most significant Washington sites are DOC (0. 24 cm/s) and DOE (0. 12 cm/s). These values indicate the wintertime increment in associated with a 1 °C drop in air temperature, below about 25 °C.