Abstract
Abstract. Improvements to climate model results in polar regions require improved knowledge of cloud properties. Surface-based infrared (IR) radiance spectrometers have been used to retrieve cloud properties in polar regions, but measurements are sparse. Reductions in cost and power requirements to allow more widespread measurements could be aided by reducing instrument resolution. Here we explore the effects of errors and instrument resolution on cloud property retrievals from downwelling IR radiances for resolutions of 0.1 to 20 cm−1. Retrievals are tested on 336 radiance simulations characteristic of the Arctic, including mixed-phase, vertically inhomogeneous, 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 are retrieved, errors in retrieved cloud optical depth (COD) and ice fraction are considerably smaller for clouds with bases below 2 km than for higher clouds. 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 in temperature of 0.2 K and in water vapor of −3 %), using retrieved cloud heights, root-mean-square errors decrease from 1.1 to 0.15 for COD, 0.3 to 0.18 for ice fraction (fice), and 10 to 7 µm for ice effective radius (errors remain at 2 µm for liquid effective radius). These results indicate that a moderately low-resolution, surface-based IR spectrometer could provide cloud property retrievals with accuracy comparable to existing higher-resolution instruments and that such an instrument would be particularly useful for low-level clouds.
Highlights
Knowledge of polar cloud properties is critical for understanding climate change in polar regions
Improving the representation of cloud processes in climate models requires observational constraints, including ice and liquid water paths, particle size, and thermodynamic phase (Komurcu et al, 2014; Winker et al, 2017). This is true for the polar regions, where clouds and cloud processes are distinctly different from lower lati
Gaseous layer optical depths computed by Line-By-Line Radiative Transfer Model (LBLRTM) are at monochromatic or perfect resolution and a fine wavenumber spacing, and DIScrete Ordinates Radiative Transfer (DISORT) must be run for each wavenumber, after which the radiance must be convolved to instrument resolution
Summary
Knowledge of polar cloud properties is critical for understanding climate change in polar regions. In the Antarctic, there have been only short-term surface-based IR spectrometer measurements, including measurements made at Amundsen–Scott South Pole Station in 1992 (Mahesh et al, 2001) and 2001 (Rowe et al, 2008), at Dome C during Austral summer 2003 (Walden et al, 2005) and 2012–2014 (Palchetti et al, 2015), and at McMurdo (as part of the Atmospheric Radiation measurement (ARM) West Antarctic Radiation Experiment, or AWARE; Silber et al, 2018) These measurements are crucial, but represent only very sparse coverage of the polar regions. There is the potential for portable, low-cost, autonomous IR spectrometers that could be deployed to remote locations to make widespread IR radiance measurements across the polar regions from which cloud properties could be retrieved Such measurements would be beneficial in a number of ways: First, they could be used to fill gaps in satellite measurements. We examine the sensitivity of retrieved results to noise and bias imposed on the radiance as well as to errors in specified input parameters, especially the atmospheric state and cloud height
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