The NASA Langley airborne High-Spectral-Resolution Lidar – Generation 2 (HSRL-2) is used to characterize clouds and small particles in the atmosphere, called aerosols. From an airborne platform, the HSRL-2 instrument provides nadir-viewing profiles of aerosol and cloud optical and microphysical properties, which are used studies aerosol impacts on radiation, clouds, and air quality. HSRL-2 also provides measurements of the near-surface ocean, including depth-resolved subsurface backscatter and attenuation. HSRL-2 can also be configured to utilize the differential absorption (DIAL) technique for measuring profiles of ozone concentrations in addition to the above products.
P-3 Orion - WFF
Hawkeye is a combination cloud particle probe. The instrument includes four probes in one.
Probe 1: The Fast Cloud Droplet Probe (FCDP) records individual particle statistics and digitizes waveform.
Probes 2-3: 2D-S 10-µm channel and 50-µm channel also trigger CPI.
Probe 4: 400 frame per second Cloud Particle Imager (CPI).
4STAR (Spectrometers for Sky-Scanning Sun-Tracking Atmospheric Research; Dunagan et al., 2013) is an airborne sun-sky spectrophotometer measuring direct solar beam transmittance (i.e., 4STAR determines direct solar beam transmission by detecting direct solar irradiance) and narrow field-of-view sky radiance to retrieve and remotely sense column-integrated and, in some cases, vertically resolved information on aerosols, clouds, and trace gases. The 4STAR team is a world leader in airborne sun-sky photometry, building on 4STAR’s predecessor instrument, AATS-14 (the NASA Ames Airborne Tracking Sun photometers; Matsumoto et al., 1987; Russell et al. 1999, and cited in more than 100 publication) and greatly expanding aerosol observations from the ground-based AERONET network of sun-sky photometers (Holben et al., 1998) and the Pandora network of ground-based direct-sun and sky spectrometer (e.g, Herman et al., 2009).
4STAR is used to quantify the attenuated solar light (from 350 to 1650 nm) and retrieve properties of various atmospheric constituents: spectral Aerosol Optical Depth (AOD) from ultraviolet to the shortwave infrared (e.g., LeBlanc et al., 2020, Shinozuka et al., 2013); aerosol intensive properties - Single Scattering Albedo (SSA; e.g., Pistone et al., 2019), asymmetry parameter, scattering phase function, absorption angstrom exponent, size distribution, and index of refraction; various column trace gas components (NO2, Ozone, Water Vapor; e.g., Segal-Rosenheimer et al., 2014, with potential for SO2 and CH2O); and cloud optical depth, effective radius and thermodynamic phase (e.g., LeBlanc et al., 2015).
Some examples of the science questions that 4STAR have pursued in the past and will continue to address:
- What is the Direct Aerosol Radiative Effect on climate and its uncertainty? (1)
- How much light is absorbed by aerosol emitted through biomass burning? (1)
- How does heating of the atmosphere by absorbing aerosol impact large scale climate and weather patterns? (1)
- How does aerosol spatial consistency of extensive and intensive properties compare? (2)
- How does the presence of aerosol impact Earth’s radiative transfer, with co-located high concentration of trace gas? (3, 5)
- What is the impact of air quality from long-range transport of both aerosol particulates and column NO2 and Ozone, and their evolution? (3, 6)
- What are the governing properties and spatial patterns of local and transported aerosol? (1)
- How are cloud properties impacted near the sea-ice edge? (4)
- In heterogeneous environments where clouds and aerosols are present, how much solar radiation is impacted by 3D radiative transfer? And how does that impact the aerosol properties? (5)
(1) ORACLES: Zuidema et al., doi:10.1175/BAMS-D-15-00082.1., 2016; LeBlanc et al., doi:10.5194/acp-20-1565-2020, 2020; Pistone et al., https://doi.org/10.5194/acp-2019-142, 2019;Cochrane et al., https://doi.org/10.5194/amt-12-6505-2019, 2019; Shinozuka et al., https://doi.org/10.5194/acp-20-11275-2020, 2020; Shinozuka et al., https://doi.org/10.5194/acp-20-11491-2020, 2020
(2) KORUS-AQ: LeBlanc et al., doi:https://doi.org/10.5194/acp-22-11275-2022, 2022
(3) KORUS-AQ: Herman et al., doi:10.5194/amt-11-4583-2018, 2018
(4) ARISE: Smith et al., https://doi.org/10.1175/BAMS-D-14-00277.1, 2017; Segal-Rosenheimer et al., doi:10.1029/2018JD028349, 2018
(5) SEAC4RS: Song et al., doi: 10.5194/acp-16-13791-2016, 2016; Toon et al., https://doi.org/10.1002/2015JD024297, 2016
(6) TCAP: Shinozuka et al., doi:10.1002/2013JD020596, 2013; Segal-Rosenheimer et al., doi:10.1002/2013JD020884, 2014
The Advanced Vertical Atmospheric Profiling System (AVAPS) is the dropsonde system for the Global Hawk. The Global Hawk dropsonde is a miniaturized version of standard RD-93 dropsondes based largely on recent MIST driftsondes deployed from balloons. The dropsonde provides vertical profiles of pressure, temperature, humidity, and winds. Data from these sondes are transmitted in near real-time via Iridium or Ku-band satellite to the ground-station, where additional processing will be performed for transmission of the data via the Global Telecommunications System (GTS) for research and operational use. The dispenser is located in zone 61 in the Global Hawk tail and is capable of releasing up to 88 sondes in a single flight.
The NASA GISS Research Scanning Polarimeter (RSP) is a passive, downward-facing polarimeter that makes total radiance and linear polarization measurements in nine spectral bands ranging from the visible/near-infrared (VNIR) to the shortwave infrared (SWIR). The band centers are: 410 (30), 470 (20), 550 (20), 670 (20), 865 (20), 960 (20), 1590 (60), 1880 (90) and 2250 (130) nm where the full width at half maximum (FWHM) bandwidths of each channel is shown in parenthesis. Noise is minimized in the SWIR channels by cooling the detectors to less than 165K using a dewar of liquid nitrogen. The RSP measures the degree of linear polarization (DoLP) with an uncertainty of <0.2%. The polarimetric and radiometric intensity measurement uncertainties are each <3%. A full set of RSP’s design parameters are shown in Table 1 and more details on design and calibration can be found in Cairns et al. (1999) and Cairns et al. (2003).
The RSP is an along track scanning instrument that can make up to 152 measurements sweeping ± 60° from nadir along the aircraft's track every 0.8 seconds with each measurement having a 14 mrad (~0.8°) field-of-view. Each scan includes stability, dark reference and calibration checks. As the RSP travels aboard an aircraft, the same nadir footprint is viewed from multiple angles. Consecutive scans are aggregated into virtual scans that are reflectances of a single nadir footprint from multiple viewing angles. This format comprises the RSP’s Level 1C data.
RSP’s high-angular resolution and polarimetric accuracy enables numerous aerosol, cloud and ocean properties to be retrieved. These are Level 2 data products. A summary of the primary L2 aerosol, cloud and ocean data products retrieved by the RSP are shown in Table 3.
The RSP’s data archive is publicly available and organized by air campaign, each of which contain ReadMe files provided by the RSP team for their Level 1C and Level 2 data products, including important details about biases and uncertainties that data users should consult.
The RSP data archive is available at: https://data.giss.nasa.gov/pub/rsp/
A visualizer showing the times and locations of NASA Airborne Campaigns the RSP has taken part in is available at: http://rsp.apam.columbia.edu:3000
Parameter | Performance |
---|---|
Degree of Linear Polarization Uncertainty (%) | <0.2 |
Polarization Uncertainty (%) | <3.0 |
Radiometric Uncertainty (%) | <3.0 |
Dynamic Range | >104 |
Signal-to-Noise Ratio | >2000 (with R=0.3) |
Spectral Characteristics | See table |
Field of View | >90o |
Instantaneous FOV | 14 mrad |
Photodiode Detector Type: · Visible/NIR · Shortwave IR (temperature) |
Silicon HgCdTe (165K) |
SWIR Detector Cooling | LN2 dewar |
Data Rate | <20 kbytes/sec |
Size, W x L x H (cm) | 40 x 64 x 34 |
Mass (kg) | <20 |
Power (watts) | <20 w/o heaters |
Band ID | λc (nm) | Δλ (nm) | Wavelength Type |
---|---|---|---|
V1 | 410 | 27 | Visible |
V2 | 470 | 20 | Visible |
V3 | 555 | 20 | Visible |
V4 | 670 | 20 | Visible |
V5 | 865 | 20 | Near-IR |
V6 | 960 | 20 | Near-IR |
S1 | 1590 | 60 | Shortwave-IR |
S2 | 1880 | 90 | Shortwave-IR |
S3 | 2250 | 130 | Shortwave-IR |
Property Type | Property | Uncertainty | Reference |
---|---|---|---|
Aerosol | Aerosol Optical Depth for fine & coarse modes (column) | 0.02/7% | Stamnes et al., 2018 |
Aerosol | Aerosol Size: effective radius for fine and coarse modes (column) | 0.05 µm/10% | Stamnes et al., 2018 |
Aerosol | Aerosol Size: effective variance for fine and coarse modes (column) | 0.3/50% | Stamnes et al., 2018 |
Aerosol | Aerosol Single Scatter Albedo (column) | 0.03 | Stamnes et al., 2018 |
Aerosol | Aerosol Refractive Index (column) | 0.02 | Stamnes et al., 2018 |
Aerosol | Aerosol Number Concentration | 50% | Schlosser et al., 2022 |
Aerosol | Aerosol Top Height | < 1 km | Wu et al., 2016 |
Aerosol | Surface Wind Speed | 0.5 m s-1 | Stamnes et al., 2018 |
Ocean | Chlorophyll-A Concentration | 0.7 mg m-3 | Stamnes et al., 2018 |
Ocean | Ocean diffuse attenuation coefficient | 40% | Stamnes et al., 2018 |
Ocean | Ocean hemispherical backscatter coefficient | 10% | Stamnes et al., 2018 |
Cloud | Cloud Flag | 10% | |
Cloud | Cloud Albedo | 10% | |
Cloud | Cloud Top Phase Index | 10% | van Diedenhoven et al., 2012 |
Cloud | Cloud Top Effective Radius | 1 um/10% | Alexandrov et al., 2012a/b |
Cloud | Cloud Top Effective Variance | 0.05/50% | Alexandrov et al., 2012a/b |
Cloud | Cloud Mean Effective Radius | 20% | Alexandrov et al., 2012a/b |
Cloud | Cloud Optical Depth | 10% | Nakajima & King, 1990 |
Cloud | Liquid Water Path | 25% | Sinclair et al., 2021 |
Cloud | Columnar Water Vapor (Above Surface or Cloud) | 10% | Nielsen et al., 2023 (to be submitted) |
Cloud | Cloud Top Height | 15% | Sinclair et al., 2017 |
Cloud | Cloud Droplet Number Concentration | 25% | Sinclair et al., 2021; Sinclair et al., 2019 |
Alexandrov, M. D., Cairns, B., & Mishchenko, M. I. (2012). Rainbow fourier transform. Journal of Quantitative Spectroscopy and Radiative Transfer, 113(18), 2521-2535. |
Alexandrov, M. D., Cairns, B., Emde, C., Ackerman, A. S., & van Diedenhoven, B. (2012). Accuracy assessments of cloud droplet size retrievals from polarized reflectance measurements by the research scanning polarimeter. Remote Sensing of Environment, 125, 92-111. |
Cairns, B., E.E. Russell, and L.D. Travis, 1999: The Research Scanning Polarimeter: Calibration and ground-based measurements. In Polarization: Measurement, Analysis, and Remote Sensing II, 18 Jul. 1999, Denver, Col., Proc. SPIE, vol. 3754, pp. 186, doi:10.1117/12.366329. |
Cairns, B., E.E. Russell, J.D. LaVeigne, and P.M.W. Tennant, 2003: Research scanning polarimeter and airborne usage for remote sensing of aerosols. In Polarization Science and Remote Sensing, 3 Aug. 2003, San Diego, Cal., Proc. SPIE, vol. 5158, pp. 33, doi:10.1117/12.518320. |
Nakajima, T., & King, M. D. (1990). Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements. Part I: Theory. Journal of Atmospheric Sciences, 47(15), 1878-1893. |
Schlosser, J. S., Stamnes, S., Burton, S. P., Cairns, B., Crosbie, E., Van Diedenhoven, B., ... & Sorooshian, A. (2022). Polarimeter+ lidar derived aerosol particle number concentration. CHARACTERIZATION OF REMOTELY SENSED, MODELED, AND IN-SITU DERIVED AMBIENT AEROSOL PROPERTIES. |
Sinclair, K., Van Diedenhoven, B., Cairns, B., Yorks, J., Wasilewski, A., & McGill, M. (2017). Remote sensing of multiple cloud layer heights using multi-angular measurements. Atmospheric Measurement Techniques, 10(6), 2361-2375. |
Sinclair, K., Van Diedenhoven, B., Cairns, B., Alexandrov, M., Moore, R., Crosbie, E., & Ziemba, L. (2019). Polarimetric retrievals of cloud droplet number concentrations. Remote Sensing of Environment, 228, 227-240. |
Sinclair, K., van Diedenhoven, B., Cairns, B., Alexandrov, M., Dzambo, A. M., & L'Ecuyer, T. (2021). Inference of precipitation in warm stratiform clouds using remotely sensed observations of the cloud top droplet size distribution. Geophysical Research Letters, 48(10), e2021GL092547. |
Stamnes, S., et al. "Simultaneous polarimeter retrievals of microphysical aerosol and ocean color parameters from the “MAPP” algorithm with comparison to high-spectral-resolution lidar aerosol and ocean products." Applied optics 57.10 (2018): 2394-2413. |
van Diedenhoven, B., Fridlind, A. M., Ackerman, A. S., & Cairns, B. (2012). Evaluation of hydrometeor phase and ice properties in cloud-resolving model simulations of tropical deep convection using radiance and polarization measurements. Journal of the Atmospheric Sciences, 69(11), 3290-3314. |
Wu, L., Hasekamp, O., van Diedenhoven, B., Cairns, B., Yorks, J. E., & Chowdhary, J. (2016). Passive remote sensing of aerosol layer height using near‐UV multiangle polarization measurements. Geophysical research letters, 43(16), 8783-8790. |
The DASH-SP providse rapid measurements of size-resolved aerosol sub-saturated hygroscopic growth factors and the real part of aerosol refractive index. It has been deployed aboard the NASA DC-8 during the DC3 and SEAC4RS field campaign and also on the P3 during ARCSIX (May-Aug 2024).
The continuous flow diffusion chambers are oriented for vertical flow through an annular space. They are constructed of two cylindrical, thin, ebonized copper walls that are separated by approximately 1.1 cm. The walls of the CFDC are force-cooled either by circulating coolant through copper tubing coils surrounding the outer wall and inside the inner wall (laboratory CFDC) or by using these same coolant coils as evaporators for refrigeration compressor units (aircraft CFDC). In operation, the walls are coated with ice, achieved by flooding the chamber with water. An inlet manifold directs sample air containing aerosol particles into the center of a laminar flow field where the sample is surrounded on either side by particle-free sheath air (or N2). By varying the set temperatures of the two walls, the warm wall provides a vapor source to the cold wall so that water vapor and temperature fields are created. These fields and airflow determine the conditions of exposure for the aerosols during their typical 5 to 20 s residence time in the CFDC. Ice particles grow to relatively large sizes compared to aerosol particles and are distinguished from them using an optical particle counter (0.4 to 20 mm) at the base of the CFDC.
The aircraft CFDC transitions to a hydrphobic warm wall surface in the lower third of the device so that liquid water drops formed at RH>100% will evaporate, leaving only ice crystals as large particles. The only other physical differences between the two devices is the fact that the laboratory CFDC is approximately 50% longer, providing additional ice crystal growth time at ambient lab pressures and the laboratory device has associated equipment for aerosol generation and preconditioning.
An impactor is sometimes used following the optical counter to collect ice crystals onto specialized transmission electron microscope (TEM) grids for analysis of the residual particles. Calculations of air flow, temperature, and humidity are made assuming steady-state conditions (Rogers, 1988). The temperature and supersaturation range are determined by wall temperatures and air flow.
The RICE is a magnetostrictive oscillation probe with a sensing cylinder 6.35 mm in diameter and 2.54 cm in length. Ice buildup on the sensing cylinder causes the frequency of oscillation to change, which can be related to the rate of ice accretion and hence the cloud liquid water content (LWC). When approximately 0.5 mm of ice has accumulated, a heater melts the ice, which is shed into the air stream. The heater cycle is approximately 5 s, and the cylinder normally requires an additional 5–10 s to cool down to a temperature where it can begin accreting ice again.
PTR-MS is a chemical ionization mass spectrometry technique that allows for fast measurements of organic trace gases. In combination with the CHARON inlet, it measures the organic composition of submicrometer aerosol particles.
The DFGAS instrument utilizes a room temperature infrared (IR) laser source based upon non-linear difference frequency generation (DFG) in the measurement of CH2O.
Mid-IR laser light is generated in the DFG system by mixing the output of two near-IR room temperature laser sources (one at 1562-nm and the other at 1083-nm) in a periodically poled lithium niobate (PPLN) non-linear wavelength conversion crystal. The mid-IR difference frequency at 2831.6 cm-1 (3.53-μm) is generated at the PPLN output and directed through a multipass astigmatic Herriott cell (100-m pathlength using ~ 4-liter sampling volume) and ultimately onto IR detectors employing a number of optical elements. A portion of the IR beam is split off by a special beam splitter (BS) before the multipass cell and focused onto an Amplitude Modulation Detector (AMD) to capture and remove optical noise from various components in the difference frequency generation process. A third detection channel from light emanating out the back of the beam splitter is directed through a low pressure CH2O reference cell and onto a reference detector (RD) for locking the center of the wavelength scan to the absorption line center. The mid-IR DFG output is simultaneously scanned and modulated over the CH2O absorption feature, and the second harmonic signals at twice the modulation frequency from the 3 detectors are processed using a computer lock-in amplifier [Weibring et al. [2006].
Ambient air is continuously drawn through a heated rear-facing inlet at flow rates around 9 standard liters per minute (slm), through a pressure controller, and through the multipass Herriott cell maintained at a constant pressure around 50-Torr. Ambient measurements are acquired in 1-second increments for time periods as long as 60 to 120-seconds (to be determined during the campaign), and this will be followed by 15-seconds of background zero air acquisition, using an onboard CH2O scrubbing unit. The zero air is added back to the inlet a few centimeters from the tip at flow rates ~ 2 to 3 slm higher than the cell flow. This frequent zeroing procedure very effectively captures and removes optical noise as well as residual outgassing from inlet line and cell contaminants. Retrieved CH2O mixing ratios are determined for each 1-second ambient spectrum by fitting to a reference spectrum, obtained by introducing high concentration calibration standards (~ 3 to 7-ppbv) from an onboard permeation calibration system into the inlet approximately every hour. The calibration outputs for the two permeation tubes employed are determined before and after the field campaign using multiple means, including direct absorption employing the Beer-Lambert Law relationship. The 1-second ambient CH2O results can be further averaged into longer time intervals for improved precision. However, in all cases the 1-second results are retained. This flexibility allows one to further study pollution plumes with high temporal resolution, and at the same time study more temporally constant background CH2O levels in the upper troposphere using longer integration times.
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