Engineering topics
Flynn, Connor
Publications and source records attributed to Flynn, Connor.
Shape-Morphing Nanocomposite Origami
Explore the source record for details and available documents.
Atmospheric Sounder Spectrometer for Infrared Spectral Technology (ASSIST): summary data
This datastream encapsulates the contents of the ASSIST "ExtraCSV" files. The ExtraCSV files contain an array of defined system constants, quantities derived from the calibrated radiances including brightness temperatures and noise estimates. It also contains most values from both the housekeeping (hkp) and annotator (ann) files except at coarser temporal resolution so represents a virtual one-stop-shop for determining the ASSIST system status.
Atmospheric Sounder Spectrometer for Infrared Spectral Technology (ASSIST): engineering data
This datastream encapsulates the contents of the ASSIST "hkp" (housekeeping) files. The reported values are from one-wire sensors that capture and report a variety of system measurements including T, RH, and voltages.
Atmospheric Sounder Spectrometer for Infrared Spectral Technology (ASSIST): channel 1 data
This datastream encapsulates the contents of the ASSIST "cha" files of calibrated sky radiances, brightness temperatures and noise equivalent radiance files.
Atmospheric Sounder Spectrometer for Infrared Spectral Technology (ASSIST): channel 2 data
This datastream encapsulates the contents of the ASSIST "chb" files of calibrated sky radiances, brightness temperatures and noise equivalent radiance files.
aospsap3w1s.b1
The aospsap3w1m process reads in data from the aospsap3w.b1 datastream and applies a dilution correction to the aerosol sample flow rate, and a filter loading correction to the absorption coefficients. The filter loading is corrected by multiplying by the Weiss transfer function f_w = 1/1.031 * 1/1.22 * (1/(1.0796 Tr + 0.71)) = 1 / (1.3579 Tr + 0.8931) where Tr is the transmittance for a given wavelength. This form incorporates the initial PSAP transfer function with modifications in Bond 1999 and subsequently in Ogren 2010. The one second (1s) data stream is only created for BNL psap3w instruments where the 1 second samples are available. The one minute (1m) data streams contain the averages of the one second data.
A13K-0336: Airborne Multi-Wavelength High Spectral Resolution Lidar for Process Studies and Assessment of Future Satellite Remote Sensing Concepts
NASA Langley recently developed the world's first airborne multi-wavelength high spectral resolution lidar (HSRL). This lidar employs the HSRL technique at 355 and 532 nm to make independent, unambiguous retrievals of aerosol extinction and backscatter. It also employs the standard backscatter technique at 1064 nm and is polarization-sensitive at all three wavelengths. This instrument, dubbed HSRL-2 (the secondgeneration HSRL developed by NASA Langley), is a prototype for the lidar on NASA's planned Aerosols- Clouds-Ecosystems (ACE) mission. HSRL-2 completed its first science mission in July 2012, the Two-Column Aerosol Project (TCAP) conducted by the Department of Energy (DOE) in Hyannis, MA. TCAP presents an excellent opportunity to assess some of the remote sensing concepts planned for ACE: HSRL-2 was deployed on the Langley King Air aircraft with another ACE-relevant instrument, the NASA GISS Research Scanning Polarimeter (RSP), and flights were closely coordinated with the DOE's Gulfstream-1 aircraft, which deployed a variety of in situ aerosol and trace gas instruments and the new Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR). The DOE also deployed their Atmospheric Radiation Measurement Mobile Facility and their Mobile Aerosol Observing System at a ground site located on the northeastern coast of Cape Cod for this mission. In this presentation we focus on the capabilities, data products, and applications of the new HSRL-2 instrument. Data products include aerosol extinction, backscatter, depolarization, and optical depth; aerosol type identification; mixed layer depth; and rangeresolved aerosol microphysical parameters (e.g., effective radius, index of refraction, single scatter albedo, and concentration). Applications include radiative closure studies, studies of aerosol direct and indirect effects, investigations of aerosol-cloud interactions, assessment of chemical transport models, air quality studies, present (e.g., CALIPSO) and future (e.g., EarthCARE) satellite calibration/validation, and development/assessment of advanced retrieval techniques for future satellite applications (e.g., lidar+polarimeter retrievals of aerosol and cloud properties). We will also discuss the relevance of HSRL-2 measurement capabilities to the ACE remote sensing concept.
Use of In Situ Cloud Condensation Nuclei, Extinction, and Aerosol Size Distribution Measurements to Test a Method for Retrieving Cloud Condensation Nuclei Profiles From Surface Measurements
If the aerosol composition and size distribution below cloud are uniform, the vertical profile of cloud condensation nuclei (CCN) concentration can be retrieved entirely from surface measurements of CCN concentration and particle humidification function and surface-based retrievals of relative humidity and aerosol extinction or backscatter. This provides the potential for long-term measurements of CCN concentrations near cloud base. We have used a combination of aircraft, surface in situ, and surface remote sensing measurements to test various aspects of the retrieval scheme. Our analysis leads us to the following conclusions. The retrieval works better for supersaturations of 0.1% than for 1% because CCN concentrations at 0.1% are controlled by the same particles that control extinction and backscatter. If in situ measurements of extinction are used, the retrieval explains a majority of the CCN variance at high supersaturation for at least two and perhaps five of the eight flights examined. The retrieval of the vertical profile of the humidification factor is not the major limitation of the CCN retrieval scheme. Vertical structure in the aerosol size distribution and composition is the dominant source of error in the CCN retrieval, but this vertical structure is difficult to measure from remote sensing at visible wavelengths.