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In this study, a shipborne 95 GHz Doppler cloud radar mounted on a stabilized platform is used to retrieve vertical profiles of three-dimensional (3D) winds by sequentially pointing the stabilized platform in different directions. A specific challenge is that the maximum angle off zenith is 8 ∘ , which implies that the projection of the horizontal wind components onto the radar beam directions is a small component of Doppler velocity in most cases. A variational 3D wind retrieval technique is then described, allowing for 1 min 3D wind profiles to be retrieved. Statistical comparisons with 3-hourly radiosonde launches from the ship indicate that horizontal wind profiles can be obtained from such cloud radar observations at small off-zenith angles with biases less than 0.2 m s -1 and standard deviations of differences with radiosonde winds less than 2.5 m s -1. [ABSTRACT FROM AUTHOR]

In this study, a shipborne 95 GHz Doppler cloud radar mounted on a stabilized platform is used to retrieve vertical profiles of three-dimensional (3D) winds by sequentially pointing the stabilized platform in different directions. A specific challenge is that the maximum angle off zenith is 8°, which implies that the projection of the horizontal wind components onto the radar beam directions is a small component of Doppler velocity in most cases. A variational 3D wind retrieval technique is then described, allowing for 1-minute resolution 3D wind profiles to be retrieved. Statistical comparisons with 3-hourly radiosonde launches and qualitative comparisons with ship-level horizontal winds demonstrate that accurate 3D wind profiles can be obtained from such cloud radar observations at small off-zenith angles. [ABSTRACT FROM AUTHOR]

Oceans cover over 70 % of the Earth's surface. Ship-based measurements are an important component in developing an understanding of atmosphere of this vast region. A common problem that impacts the quality of atmospheric data collected from marine research vessels is exhaust from both diesel combustion and waste incineration from the ship itself. Described here is an algorithm, developed for the recently commissioned Australian blue-water research vessel (RV) Investigator , that identifies exhaust periods in sampled air. The RV Investigator , with two dedicated atmospheric laboratories, represents an unprecedented opportunity for high-quality measurements of the marine atmosphere. The algorithm avoids using ancillary data such as wind speed and direction, and instead utilises components of the exhaust itself – aerosol number concentration, black carbon concentration, and carbon monoxide and carbon dioxide mixing ratios. The exhaust signal is identified within each of these parameters individually before they are combined and an additional window filter is applied. The algorithm relies heavily on statistical methods, rather than setting thresholds that are too rigid to accommodate potential temporal changes. The algorithm is more effective than traditional wind-based filters in removing exhaust data without removing exhaust-free data, which commonly occurs with traditional filters. In application to the current dataset, the algorithm identifies 26 % of the wind filter's "clean" data as exhaust, and recovers 5 % of data falsely removed by the wind filter. With suitable testing, the algorithm has the potential to be applied to other ship-based atmospheric measurements where suitable measurements exist. [ABSTRACT FROM AUTHOR]

Ship-based measurements are an important component in developing an understanding of the global atmosphere. A common problem that impacts the quality of atmospheric data collected from marine research vessels is exhaust from both diesel combustion and waste incineration from the ship itself. Described here is an algorithm, developed for the recently commissioned Australian blue-water Research Vessel (RV) Investigator, that identifies exhaust periods in sampled air. The RV Investigator, with two dedicated atmospheric laboratories, represents an unprecedented opportunity for high quality measurements of the marine atmosphere. The algorithm avoids using ancillary data such as wind speed and direction, and instead utilises components of the exhaust itself - aerosol number concentration, black carbon concentration, and carbon monoxide and carbon dioxide mixing ratios. The exhaust signal is identified within each of these parameters individually before they are combined and an additional window filter is applied. The algorithm relies heavily on statistical methods, rather than setting thresholds that are too rigid to accommodate potential temporal changes. The algorithm is more effective than traditional wind-based filters in removing exhaust data without removing exhaust-free data which commonly occurs with traditional filters. With suitable testing, the algorithm has the potential to be applied to other ship-based atmospheric measurements where suitable measurements exist. [ABSTRACT FROM AUTHOR]