The De-Icing Comparison Experiment (D-ICE): A study of broadband radiometric measurements under icing conditions in the Arctic

Abstract

Abstract. Surface-based measurements of broadband shortwave (solar) and longwave (infrared) radiative fluxes using thermopile radiometers are made regularly around the globe for scientific and operational environmental monitoring. The occurrence of ice on sensor windows in cold environments – whether snow, rime, or frost – is a common problem that is difficult to prevent as well as difficult to correct in post-processing. The Baseline Surface Radiation Network (BSRN) community recognizes radiometer icing as a major outstanding measurement uncertainty. Towards constraining this uncertainty, the De-Icing Comparison Experiment (D-ICE) was carried out at the NOAA Atmospheric Baseline Observatory in Utqiaġvik (formerly Barrow), Alaska, from August 2017 to July 2018. The purpose of D-ICE was to evaluate existing ventilation and heating technologies developed to mitigate radiometer icing. D-ICE consisted of 20 pyranometers and 5 pyrgeometers operating in various ventilator housings alongside operational systems that are part of NOAA's Barrow BSRN station and the U.S. Dept. of Energy Atmospheric Radiation Measurement (ARM) Program North Slope of Alaska and Oliktok Point observatories. To detect icing, radiometers were monitored continuously using cameras, with a total of more than 1 million images of radiometer domes archived. Ventilator and ventilator/heater performance overall was skilful with the average of the systems mitigating 77 % of icing and many being 90+ % effective. Ventilators without heating elements were also effective and capable of providing heat through roughly equal contributions of waste energy from the ventilator fan and adiabatic heating downstream of the fan. This provided ~ 0.6 C of warming, enough to subsaturate the air up to a relative humidity (w.r.t. ice) of ~ 105 %. Because the mitigation technologies performed well, a near complete record of verified ice-free radiometric fluxes were assembled for the duration of the campaign. This well-characterized data set is suitable for model evaluation, in particular for the Year of Polar Prediction (YOPP) first Special Observing Period (SOP1). We used the data set to calculate short- and long-term biases in iced sensors, finding that biases can be up to +60 W m−2 (longwave) and −211 to +188 W m−2 (shortwave). However, because of the frequency of icing, mitigation of ice by ventilators, cloud conditions, and the timing of icing relative to available sunlight, the biases in the monthly means were generally less than the aggregate uncertainty attributed to other conventional sources.

Comparison of TOA and BOA LW Radiation Fluxes Inferred From Ground‐Based Sensors, A‐Train Satellite Observations and ERA Reanalyzes at the High Arctic Station Eureka Over the 2002–2020 Period

“…Note that the BSRN screening method described in Section 2.1 and supporting S1 helps to remove suspicious measurements (184,572 cases representing about 8% of the whole data set). Cox et al., (2020) looked at the impact of filtering and they concluded that while instantaneous biases are large, biases in the long‐term means from ice are relatively small. The difference between the two BSRN data sets (unfiltered and filtered) is a combination of positive biases from ice in the version containing iced data and negative biases caused by the rejection of iced data under clear skies.…”