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Richard J. Vong and David S. Covert


Simultaneous field measurements of aerosol and cloud droplet concentrations and droplet diameter were performed at a maritime site on the coast of Washington State. The aerosol and droplet spectra were compared for estimating cloud condensation nucleus concentration (N ccn) as the number of particles with diameters greater than 80 nm, that is, N ccnN(D p > 80 nm). Several analytical approaches were developed and applied to the data, including a stratification of the observations into periods of high and low liquid water content (LWC) based on a threshold value of 0.25 g m−3. The aerosol data were corrected for inertial losses of cloud droplets at the inlet using wind speed and droplet size; this correction improved the measured relationships between N ccn and droplet number concentration (N d). These measurements, when coupled with the range of possible aerosol chemical compositions, imply a cloud supersaturation of 0.24%–0.31% at the Cheeka Peak sampling site during periods of high LWC.

The observations of droplet and aerosol spectra supported Twomey’s cloud brightening hypothesis in that N ccn was highly correlated (r 2 = 0.8) with N d in apparent 1:1 proportions. For the investigated range (50 cm−3 < N d < 600 cm−3) droplet effective diameter (D eff) was very sensitive to variation in N ccn for 50 cm−3 < N ccn < 200 cm−3, somewhat sensitive for 200 cm−3 < N ccn < 400 cm−3, but not very sensitive to variation in aerosol number for N ccn > 400 cm−3. A model was applied to the aerosol and droplet data to predict droplet size, as D eff, from N−0.33ccn and LWC. Predicted values for D eff agreed (r 2 = 0.8) with D eff determined directly from the cloud droplet spectra, suggesting that this approach should be useful in climate modeling for predicting cloud droplet size from knowledge of N ccn and LWC.

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Andrew S. Kowalski, Peter M. Anthoni, Richard J. Vong, Anthony C. Delany, and Gordon D. Maclean


Direct interception of windblown cloud water by forests has been dubbed “occult deposition” because it represents a hydrological input that is hidden from rain gauges. Eddy correlation studies of this phenomenon have estimated cloud water fluxes to vegetation yet have lacked estimates of error bounds. This paper presents an evaluation of instrumental and methodological errors for cloud liquid water fluxes to put such eddy correlation measurements in context. Procedures for data acquisition, processing (including correction factors), and calibration testing of the particulate volume monitor (PVM) and forward-scattering spectrometer probe (FSSP) are detailed. Nearly 200 h of in-cloud data are analyzed for intercomparison of these instruments. Three methods of coordinate system rotation are investigated; the flux shows little sensitivity to the method used, and the difference between fluxes at different stations is even less sensitive to this choice. Side-by-side intercomparison of two PVMs and one FSSP leads to error bounds of 0.01–0.035 g m−3 on half-hour mean cloud liquid water content (relative to typical values of 0.35 g m−3) and 2–3.5 mg m−2 s−1 on the surface-normal liquid water flux (typical magnitude of 7 mg m−2 s−1 for these data), depending on which instruments are compared.

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