Abstract. Improvements to climate model results in polar regions require improvedknowledge of cloud properties. Surface-based infrared (IR) radiancespectrometers have been used to retrieve cloud properties in polar regions,but measurements are sparse. Reductions in cost and power requirements toallow more widespread measurements could be aided by reducing instrumentresolution. Here we explore the effects of errors and instrument resolutionon cloud property retrievals from downwelling IR radiances for resolutionsof 0.1 to 20 cm−1. Retrievals are tested on 336 radiance simulationscharacteristic of the Arctic, including mixed-phase, verticallyinhomogeneous, and liquid-topped clouds and a variety of ice habits.Retrieval accuracy is found to be unaffected by resolution from 0.1 to 4 cm−1, after which it decreases slightly. When cloud heights areretrieved, errors in retrieved cloud optical depth (COD) and ice fractionare considerably smaller for clouds with bases below 2 km than for higherclouds. For example, at a resolution of 4 cm−1, with errors imposed(noise and radiation bias of 0.2 mW/(m2 sr cm−1) and biases intemperature of 0.2 K and in water vapor of −3 %), using retrieved cloudheights, root-mean-square errors decrease from 1.1 to 0.15 for COD, 0.3 to0.18 for ice fraction (fice), and 10 to 7 µm for iceeffective radius (errors remain at 2 µm for liquid effective radius).These results indicate that a moderately low-resolution, surface-based IRspectrometer could provide cloud property retrievals with accuracycomparable to existing higher-resolution instruments and that such aninstrument would be particularly useful for low-level clouds.
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Toward autonomous surface-based infrared remote sensing of polar clouds: cloud-height retrievals
Abstract. Polar regions are characterized by their remoteness, making measurements challenging, but an improved knowledge of clouds and radiation is necessary to understand polar climate change. Infrared radiance spectrometers can operate continuously from the surface and have low power requirements relative to active sensors. Here we explore the feasibility of retrieving cloud height with an infrared spectrometer that would be designed for use in remote polar locations. Using a wide variety of simulated spectra of mixed-phase polar clouds at varying instrument resolutions, retrieval accuracy is explored using the CO2 slicing/sorting and the minimum local emissivity variance (MLEV) methods. In the absence of imposed errors and for clouds with optical depths greater than ∼ 0.3, cloud-height retrievals from simulated spectra using CO2 slicing/sorting and MLEV are found to have roughly equivalent high accuracies: at an instrument resolution of 0.5cm−1, mean biases are found to be ∼ 0.2km for clouds with bases below 2 and −0.2km for higher clouds. Accuracy is found to decrease with coarsening resolution and become worse overall for MLEV than for CO2 slicing/sorting; however, the two methods have differing sensitivity to different sources of error, suggesting an approach that combines them. For expected errors in the atmospheric state as well as both instrument noise and bias of 0.2mW/(m2srcm−1), at a resolution of 4cm−1, average retrieval errors are found to be less than ∼ 0.5km for cloud bases within 1km of the surface, increasing to ∼ 1.5km at 4km. This sensitivity indicates that a portable, surface-based infrared radiance spectrometer could provide an important complement in remote locations to satellite-based measurements, for which retrievals of low-level cloud are challenging.
more » « less- Award ID(s):
- 1543236
- NSF-PAR ID:
- 10083501
- Date Published:
- Journal Name:
- Atmospheric Measurement Techniques
- Volume:
- 9
- Issue:
- 8
- ISSN:
- 1867-8548
- Page Range / eLocation ID:
- 3641 to 3659
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/amt-9-3641-2016
