Search Results
A Technique for Estimating Liquid Droplet Diameter and Liquid Water Content in Stratocumulus Clouds Using Radar and Lidar Measurementsspectra collected by in situ cloud and drizzle probes on the NSF–NCAR C-130 aircraft during VAMOS in the southeastern Pacific Ocean were used as input to the simulations of radar and lidar observations. The simulated radar and lidar observations were used for developing a retrieval method for estimating cloud microphysical products, namely, characteristic particle diameter and LWC. The practical applicability of the retrieval method was demonstrated using the radar and lidar measurements from CSET
spectra collected by in situ cloud and drizzle probes on the NSF–NCAR C-130 aircraft during VAMOS in the southeastern Pacific Ocean were used as input to the simulations of radar and lidar observations. The simulated radar and lidar observations were used for developing a retrieval method for estimating cloud microphysical products, namely, characteristic particle diameter and LWC. The practical applicability of the retrieval method was demonstrated using the radar and lidar measurements from CSET
Merged Cloud and Precipitation Dataset from the HIAPER GV for the Cloud System Evolution in the Trades (CSET) Campaignsampling strategies and the mean conditions observed during CSET can be found within Albrecht et al. (2019) , Mohrmann et al. (2019, manuscript submitted to Mon. Wea. Rev .), and Bretherton et al. (2019) . A notable feature of the CSET campaign was the first deployment of the HIAPER W-band Doppler cloud radar (HCR), together with the high-spectral-resolution lidar (HSRL). These systems were included on the CSET GV deployment to remotely sense cloud and precipitation. A cloud and precipitation data
sampling strategies and the mean conditions observed during CSET can be found within Albrecht et al. (2019) , Mohrmann et al. (2019, manuscript submitted to Mon. Wea. Rev .), and Bretherton et al. (2019) . A notable feature of the CSET campaign was the first deployment of the HIAPER W-band Doppler cloud radar (HCR), together with the high-spectral-resolution lidar (HSRL). These systems were included on the CSET GV deployment to remotely sense cloud and precipitation. A cloud and precipitation data
evaluating the simulations against a range of observations, including in situ measurements, aircraft-borne radar and lidar, and satellite-based remote sensing, the model cannot be tuned to match a particular observation. In addition to the initial exploration of these cases in the present paper, we hope that these Lagrangian case studies will be used by other researchers to illuminate the processes that control real cloudiness transitions. The CSET field campaign ( Albrecht et al. 2019 ) took place over
evaluating the simulations against a range of observations, including in situ measurements, aircraft-borne radar and lidar, and satellite-based remote sensing, the model cannot be tuned to match a particular observation. In addition to the initial exploration of these cases in the present paper, we hope that these Lagrangian case studies will be used by other researchers to illuminate the processes that control real cloudiness transitions. The CSET field campaign ( Albrecht et al. 2019 ) took place over
Clarifying Remotely Retrieved Precipitation of Shallow Marine Clouds from the NSF/NCAR Gulfstream Vquantity, robust observations of precipitation remain necessary for untangling subtle cause and effect relationships using modeling studies (e.g., vanZanten et al. 2011 ; Blossey et al. 2021 ). During the Cloud System Evolution in the Trades (CSET; Albrecht et al. 2019 ) campaign in 2015, precipitating stratocumulus and cumulus clouds were observed by in situ probes as well as by a 94-GHz Doppler radar, and a 532-nm-wavelength high spectral resolution lidar (HSRL) over the northeastern Pacific Ocean
quantity, robust observations of precipitation remain necessary for untangling subtle cause and effect relationships using modeling studies (e.g., vanZanten et al. 2011 ; Blossey et al. 2021 ). During the Cloud System Evolution in the Trades (CSET; Albrecht et al. 2019 ) campaign in 2015, precipitating stratocumulus and cumulus clouds were observed by in situ probes as well as by a 94-GHz Doppler radar, and a 532-nm-wavelength high spectral resolution lidar (HSRL) over the northeastern Pacific Ocean
potential cloud-controlling factors, inversion stability and cloud droplet number concentration. Section 6 compares observations from an illustrative CSET flight with reanalysis and a weather-nudged climate model, followed by a summary in section 7 . 2. CSET observations and analysis methods a. Measurements used in this study The G-V instrumentation used for CSET was described in detail by A19 . It included a 94-GHz cloud radar, a high spectral resolution lidar, dropsondes, and in situ probes for
potential cloud-controlling factors, inversion stability and cloud droplet number concentration. Section 6 compares observations from an illustrative CSET flight with reanalysis and a weather-nudged climate model, followed by a summary in section 7 . 2. CSET observations and analysis methods a. Measurements used in this study The G-V instrumentation used for CSET was described in detail by A19 . It included a 94-GHz cloud radar, a high spectral resolution lidar, dropsondes, and in situ probes for
Wisconsin high spectral resolution lidar . Opt. Eng. , 30 , 6 – 12 , https://doi.org/10.1117/12.55766 . 10.1117/12.55766 Guzman , R. , and Coauthors , 2017 : Direct atmosphere opacity observations from CALIPSO provide new constraints on cloud-radiation interactions . J. Geophys. Res. Atmos. , 122 , 1066 – 1085 , https://doi.org/10.1002/2016JD025946 . 10.1002/2016JD025946 Hindman , E. E. , W. M. Porch , J. G. Hudson , and P. A. Durkee , 1994 : Ship-produced cloud lines of 13 July
Wisconsin high spectral resolution lidar . Opt. Eng. , 30 , 6 – 12 , https://doi.org/10.1117/12.55766 . 10.1117/12.55766 Guzman , R. , and Coauthors , 2017 : Direct atmosphere opacity observations from CALIPSO provide new constraints on cloud-radiation interactions . J. Geophys. Res. Atmos. , 122 , 1066 – 1085 , https://doi.org/10.1002/2016JD025946 . 10.1002/2016JD025946 Hindman , E. E. , W. M. Porch , J. G. Hudson , and P. A. Durkee , 1994 : Ship-produced cloud lines of 13 July
Pincus 1995 ; Bretherton et al. 1995 ). The ASTEX Lagrangian studies, however, were not made in classic trade wind flow conditions and lacked the aircraft-based lidar and radar observations needed to provide a detailed mapping of cloud and precipitation structures. Fig . 1. (top left) Photo of NSF–NCAR GV and (top right) GOES visible image with aircraft path on 27 Jul 2015 RF10 during CSET. The red points indicate where dropsonde launches were made. (bottom) Photos from this flight were taken by a
Pincus 1995 ; Bretherton et al. 1995 ). The ASTEX Lagrangian studies, however, were not made in classic trade wind flow conditions and lacked the aircraft-based lidar and radar observations needed to provide a detailed mapping of cloud and precipitation structures. Fig . 1. (top left) Photo of NSF–NCAR GV and (top right) GOES visible image with aircraft path on 27 Jul 2015 RF10 during CSET. The red points indicate where dropsonde launches were made. (bottom) Photos from this flight were taken by a
( RWC i υ i L υ , i ) − ( RWC i − 1 υ i − 1 L υ , i − 1 ) . The rainwater content at cloud base is set equal to that from the in-cloud leg. Although collision–coalescence will increase the rainwater content between in-cloud leg and cloud base, the assumption that the raindrop size distribution measured during in-cloud leg scales well with cloud-base precipitation is supported by observations ( Wood 2005a ). The mean cloud base height is derived from lidar measurements from the nearest 150-m level
( RWC i υ i L υ , i ) − ( RWC i − 1 υ i − 1 L υ , i − 1 ) . The rainwater content at cloud base is set equal to that from the in-cloud leg. Although collision–coalescence will increase the rainwater content between in-cloud leg and cloud base, the assumption that the raindrop size distribution measured during in-cloud leg scales well with cloud-base precipitation is supported by observations ( Wood 2005a ). The mean cloud base height is derived from lidar measurements from the nearest 150-m level
was empirically chosen to balance the competing interests in reducing noise in box-averaged quantities while avoiding including observations from regions subject to significantly different large-scale forcings; a comparison of the GOES cloud fraction estimate to that derived from a radar-lidar cloud mask can be found in Bretherton et al. (2019) . Supplemental data are drawn from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis, version 5 (ERA5) [ Copernicus Climate Change
was empirically chosen to balance the competing interests in reducing noise in box-averaged quantities while avoiding including observations from regions subject to significantly different large-scale forcings; a comparison of the GOES cloud fraction estimate to that derived from a radar-lidar cloud mask can be found in Bretherton et al. (2019) . Supplemental data are drawn from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis, version 5 (ERA5) [ Copernicus Climate Change
