Filters

2018 - 201912020 - 20221

More filters

20232
Reset filters

Settings

search.filters.applied.f.access: openAccess × Author: Rosenfeld, Daniel × End date: 2024 × Start date: 2020 × DDC: 550 × Has files: Yes × Publisher: Hoboken, NJ : Wiley × WGL Institute: TROPOS ×

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Detrainment Dominates CCN Concentrations Around Non-Precipitating Convective Clouds Over the Amazon
    (Hoboken, NJ : Wiley, 2022) Braga, Ramon C.; Rosenfeld, Daniel; Andreae, Meinrat O.; Pöhlker, Christopher; Pöschl, Ulrich; Voigt, Christiane; Weinzierl, Bernadett; Wendisch, Manfred; Pöhlker, Mira L.; Harrison, Daniel
    We investigated the relationship between the number concentration of cloud droplets (Nd) in ice-free convective clouds and of particles large enough to act as cloud condensation nuclei (CCN) measured at the lateral boundaries of cloud elements. The data were collected during the ACRIDICON-CHUVA aircraft campaign over the Amazon Basin. The results indicate that the CCN particles at the lateral cloud boundaries are dominated by detrainment from the cloud. The CCN concentrations detrained from non-precipitating convective clouds are smaller compared to below cloud bases. The detrained CCN particles from precipitating cloud volumes have relatively larger sizes, but lower concentrations. Our findings indicate that CCN particles ingested from below cloud bases are activated into cloud droplets, which evaporate at the lateral boundaries and above cloud base and release the CCN again to ambient cloud-free air, after some cloud processing. These results support the hypothesis that the CCN around the cloud are cloud-processed.
  • Thumbnail Image
    Item
    Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives
    (Hoboken, NJ : Wiley, 2018) Grosvenor, Daniel P.; Sourdeval, Odran; Zuidema, Paquita; Ackerman, Andrew; Alexandrov, Mikhail D.; Bennartz, Ralf; Boers, Reinout; Cairns, Brian; Chiu, J. Christine; Christensen, Matthew; Deneke, Hartwig; Diamond, Michael; Feingold, Graham; Fridlind, Ann; Hünerbein, Anja; Knist, Christine; Kollias, Pavlos; Marshak, Alexander; McCoy, Daniel; Merk, Daniel; Painemal, David; Rausch, John; Rosenfeld, Daniel; Russchenberg, Herman; Seifert, Patric; Sinclair, Kenneth; Stier, Philip; van Diedenhoven, Bastiaan; Wendisch, Manfred; Werner, Frank; Wood, Robert; Zhang, Zhibo; Quaas, Johannes
    The cloud droplet number concentration (Nd) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol-cloud interactions. Current standard satellite retrievals do not operationally provide Nd, but it can be inferred from retrievals of cloud optical depth (τc) cloud droplet effective radius (re) and cloud top temperature. This review summarizes issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel-level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. Nd uncertainty is dominated by errors in re, and therefore, improvements in re retrievals would greatly improve the quality of the Nd retrievals. Recommendations are made for how this might be achieved. Some existing Nd data sets are compared and discussed, and best practices for the use of Nd data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative Nd estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high-quality ground-based observations are examined.