ALBERT

Description: 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 locations, for single-layer, mixed-phase polar clouds, 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 0.5 cm−1, mean biases are found to be ∼0.2 km for low clouds (bases below 2 km) and −0.2 km for medium-to-high clouds (hereafter “high clouds”). Accuracy is found to decrease with decreasing cloud signal and increasing cloud height (independent of signal). Accuracy also decreases with coarsening resolution and becomes 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. In the presence of errors, the dependence of retrieval accuracy on resolution is weakened. Further, errors have a small effect on retrievals of low clouds but a large effect on high clouds. Expected errors in the atmospheric state indicate that at a resolution of 0.5 cm−1, instrument noise level and bias of 0.1 mW/(m2 sr cm−1) would permit a retrieval accuracy of −2 ± 2 km for high clouds and ∼0.2 ± 0.5 km for low clouds, for both methods. This study highlights the sensitivity of surface-based infrared spectrometers to low clouds prevalent in polar regions.