Associated content: 
ORACLES
Sub-categories: 
ORACLES Background, ORACLES-4

Site Visit Namibia #2

Date: 
Saturday, October 10, 2015 (All day) - Saturday, October 17, 2015 (All day)

Composite CALIPSO backscatter curtains

Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research

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

Instrument Type: 
Spectrometer
Measurements: 
NO2, O3, H2O, Spectral Aerosol Optical Depth, Aerosol Extinction Angstrom Exponent, Aerosol Single Scattering Albedo, Aerosol Asymmetry Parameter, Aerosol Scattering phase function, Aerosol Size Distribution, Aerosol Complex Refractive Index, Cloud Optical Depth, Cloud droplet effective radius, Cloud Thermodynamic Phase, Cloud Liquid Water Content
Aircraft: 
P-3 Orion - WFF, C-130H - WFF, Convair 580 NRC, Gulfstream G-1 (DOE), DC-8 - AFRC
Point(s) of Contact: 
Meloe S. Kacenelenbogen (Co-I)

Research Scanning Polarimeter

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
 

Table 1: RSP Design Parameters
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

 

Table 2: RSP Spectral Channels
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

 

Table 3: Summary of L2 Data Products
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

 

Table 4: References
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.
Instrument Type: 
Polarimeter
Measurements: 
Imagery
Aircraft: 
ER-2 - AFRC, P-3 Orion - WFF, C-130- WFF, King Air B-200 - LaRC, J-31
Point(s) of Contact: 
Brian Cairns (PI)

Enhanced MODIS Airborne Simulator

The Enhanced MODIS Airborne Simulator (EMAS) is a multispectral scanner configured to approximate the Moderate-Resolution Imaging Spectrometer (MODIS), an instrument orbiting on the NASA Terra and Aqua satellites. MODIS is designed to measure terrestrial and atmospheric processes. The EMAS was a joint development project of Daedalus Enterprises, Berkeley Camera Engineering, the USU Space Dynamics Laboratory, and Ames Research Center. The EMAS system acquires 50-meter spatial resolution imagery, in 38 spectral bands, of cloud and surface features from the vantage point of the NASA ER-2 high-altitude research aircraft.

Instrument Type: Multispectral Imager
Measurements: VNIR/SWIR/LWIR Imagery
 

Instrument Type: 
Spectrometer
Measurements: 
Imagery
Aircraft: 
ER-2 - AFRC
Point(s) of Contact: 
Steve Platnick (Co-I)

Turbulent Air Motion Measurement System

The TAMMS is composed of several subsystems including: (1) distributed pressure ports coupled with absolute and differential pressure transducers and temperature sensors, (2) aircraft inertial and satellite navigation systems, (3) a central data acquisition/processing system, and (4) water vapor instruments and potentially other trace gas or aerosol sensors.

Instrument Type: 
Navigation recorder
Measurements: 
Aircraft position, Temperature, Pressure, H2O
Aircraft: 
P-3 Orion - WFF
Point(s) of Contact: 
Lee Thornhill (PI)

Solar Spectral Flux Radiometer

In early 2000, the Ames Atmospheric Radiation Group completed the design and development of an all new Solar Spectral Flux Radiometer (SSFR). The SSFR is used to measure solar spectral irradiance at moderate resolution to determine the radiative effect of clouds, aerosols, and gases on climate, and also to infer the physical properties of aerosols and clouds. Additionally, the SSFR was used to acquire water vapor spectra using the Ames 25-meter base-path multiple-reflection absorption cell in a laboratory experiment. The Solar Spectral Flux Radiometer is a moderate resolution flux (irradiance) spectrometer with 8-12 nm spectral resolution, simultaneous zenith and nadir viewing. It has a radiometric accuracy of 3% and a precision of 0.5%. The instrument is calibrated before and after every experiment, using a NIST-traceable lamp. During field experiments, the stability of the calibration is monitored before and after each flight using portable field calibrators. Each SSFR consists of 2 light collectors, which are either fix-mounted to the aircraft fuselage, or on a stabilizing platform which counteracts the movements of the aircraft. Through fiber optic cables, the light collectors are connected to 2 identical pairs of spectrometers, which cover the wavelength range from (a) 350 nm-1000 nm (Zeiss grating spectrometer with Silicon linear diode array) and (b) 950 nm - 2150 nm (Zeiss grating spectrometer with InGaAs linear diode array). Each spectrometer pair covers about 95% of the incoming solar incident irradiance spectrum.

Instrument Type: 
Radiometer
Measurements: 
Solar flux, Irradiance
Aircraft: 
Altair, DC-8 - AFRC, ER-2 - AFRC, Global Hawk - AFRC, J-31, P-3 Orion - WFF, C-130H - WFF, Twin Otter - CIRPAS - NPS
Point(s) of Contact: 
Peter Pilewskie (Co-I)

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