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Langley Cloud Probes

The LARGE group operates a suite of probes to measure in-situ cloud microphysical properties. Probes are typically mounted at an under-wing or wing-tip position in unperturbed air. The package of probes can be tailored to specific science objectives or mounting-point availability considerations. The following probes are available:

CAPS (Cloud, Aerosol, Precipitation Spectrometer), Droplet Measurement Technologies.  The CAPS contains individual sensors.  The CAS (Cloud Aerosol Spectrometer) measures size distributions of clouds and aerosols between 0.5-50µm diameter using forward-scattered light intensity from a 658nm laser. Response is calibrated with glass beads. The CIP (Cloud Imaging Spectrometer) measures size distributions of droplet and precipitation particles between 15-150µm diameter recording shadows on an optical array. The CIP is calibrated using a spinning disk. A hotwire is also used to measure total liquid-water-content. Each probe utilizes a local measurment of airspeed, temperature, and static pressure for quantification and has de-icing capability.
CDP (Cloud Droplet Probe), Droplet Measurement Technologies. The CDP measures droplet and aerosol size distributions between 2-50µm diameter using forward-scattering from a 658nm laser.  The probe is calibrated with glass beads and has de-icing capability.
WCM-2000 (Science Engineering Associates).  Measures Liquid Water Content (LWC) using two independent hotwire elements, Total Water Content (TWC) using a scoop sensor, and an element oriented parallel with the airstream as a control to establish the background response at that specific airspeed, temperature, and pressure.  Ice Water Content (IWC) is calculated as the difference between TWC and LWC. Each element operates by maintaining a constant temperature, and the current necessary to maintain that temperature is related directly with water content.  
 

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Langley Aerosol Mass Spectrometer

Aerodyne High-Resolution Time-of-Flight Aerosol Mass Spectrometer (AMS) operated by the Langley Aerosol Research Group Experiment (LARGE).  Provides fast-response non-refractory submicron aerosol mass concentrations (e.g., organics, sulfate, nitrate, ammonium, and chloride) and tracer m/z fragments (e.g., m/z44, m/z55, etc.).   

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HU25 ACTIVATE Upper Probes

Aerosol Cloud Meteorology Interactions Over the Western Atlantic Experiment (ACTIVATE)

NASA’s Aerosol Cloud me

Probing the Hazy Mysteries of Marine Clouds

A new NASA airborne science mission will take researchers on coordinated flights above, through and below the clouds over the western North Atlantic Ocean.

NASA Embarks on Five U.S. Expeditions Targeting Air, Land and Sea

NASA is sending five airborne campaigns across the United States in 2020 to investigate fundamental processes that ultimately impact human lives and the environment, from snowstorms along the East Coast to ocean eddies off the coast of San Francisco.

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: 
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ER-2 - AFRC, P-3 Orion - WFF, C-130- WFF, King Air B-200 - LaRC, J-31
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Langley Aerosol Research Group Experiment

Langley Aerosol Research Group Experiment (LARGE).  The "classic" suite of instrumenation measures in-situ aerosol micrphysical and optical properties. The package can be tailored for specific science objectives and to operate on a variety of aircraft. Depending on the aircraft, measurments are made from either a shrouded single-diffuser "Clarke" inlet, from a BMI (Brechtel Manufacturing Inc.) isokinetic inlet, or from a HIML inlet. Primary measurements include:

1.) total and non-volatile particle concentrations (3nm and 10nm nominal size cuts),
2.) dry size distributions from 3nm to 5µm diameter using a combination of mobilty-optical-aerodynamic sizing techniques,
3.) dry and humidified scattering coefficients (at 450, 550, and 700nm wavelength), and
4.) dry absorption coefficients (470, 532, and 670nm wavelength). 

LARGE derived products include particle size statistics (integrated number, surface area, and volume concentrations for ultrafine, accumulation, and coarse modes), dry and ambient aerosol extinction coefficients, single scattering albedo, angstrom exponent coefficients, and scattering hygroscopicity parameter f(RH).

Aircraft: 
DC-8 - AFRC, C-130H - WFF, P-3 Orion - WFF, HU-25 Falcon - LaRC, King Air B-200 - LaRC, Twin Otter - CIRPAS - NPS
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Diode Laser Hygrometer

The DLH has been successfully flown during many previous field campaigns on several aircraft, most recently ACTIVATE (Falcon); FIREX-AQ, ATom, KORUS-AQ, and SEAC4RS (DC-8); POSIDON (WB-57); CARAFE (Sherpa); CAMP2Ex and DISCOVER-AQ (P-3); and ATTREX (Global Hawk). This sensor measures water vapor (H2O(v)) via absorption by one of three strong, isolated spectral lines near 1.4 μm and is comprised of a compact laser transceiver and a sheet of high grade retroflecting road sign material to form the optical path. Optical sampling geometry is aircraft-dependent, as each DLH instrument is custom-built to conform to aircraft geometric constraints. Using differential absorption detection techniques, H2O(v) is sensed along the external path negating any potential wall or inlet effects inherent in extractive sampling techniques. A laser power normalization scheme enables the sensor to accurately measure water vapor even when flying through clouds. An algorithm calculates H2O(v) concentration based on the differential absorption signal magnitude, ambient pressure, and temperature, and spectroscopic parameters found in the literature and/or measured in the laboratory. Preliminary water vapor mixing ratio and derived relative humidities are provided in real-time to investigators.

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Continuous Flow Streamwise Thermal Gradient CCN Counter

Developed by Droplet Measurement Technologies, the CFSTGC is based on a concept by Roberts and Nenes [2005]. The instrument counts the fraction of aerosol particles that become droplets when exposed to a given water vapor supersaturation (RH > 100%).

As with all CCN counters, a temperature gradient is applied to produce a supersaturation of water vapor. However, the mechanism for generating supersaturation is not the same for all CCN counters. For example, for continuous flow parallel plate diffusion chambers, the temperature gradient is perpendicular to the flow, and supersaturation is a result of the nonlinear dependence of vapor pressure upon temperature. The same mechanism applies for static diffusion cloud chambers, where there is no flow at all.

However, as the name implies, for the Continuous Flow Streamwise Thermal Gradient CCN Counter, the temperature gradient is in the streamwise direction (maintained by thermoelectric coolers). In this case, supersaturation results as a consequence of the greater rate of mass transfer over heat transfer.

With laminar flow, heat and water vapor are transferred to the centerline of the column from the walls only by diffusion.

Since molecular diffusivity is greater than thermal diffusivity, the distance downstream that a water molecule travels before reaching the centerline is less than the distance the heat travels downstream before reaching the centerline. If you pick a point at the centerline, the heat originated from a greater distance upstream than the water vapor.

There are four facts that are necessary to explain how supersaturation is generated within the CFSTGC:

1) Assuming that the inner surface of the column is saturated with water vapor at all points, since the temperature is greater at point B than at point A, the water vapor partial pressure is also greater at point B than at point A.

2) The actual partial pressure of water vapor at point C is equal to the partial pressure of water vapor at point B.

3) However, since the temperature at point C is the same as at point A, the equilibrium water vapor pressure at point C is equal to the water vapor partial pressure at point A.

4) The saturation ratio is the ratio between the actual partial pressure of water vapor and the equilibrium vapor pressure. This is equivalent to the partial pressure at point B divided by the partial pressure at point A, which is always greater than one. Thus supersaturation is generated through a dynamic equilibrium.

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Aircraft: 
Balloon, P-3 Orion - WFF, C-130H - WFF, DC-8 - AFRC, HU-25 Falcon - LaRC
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