Development and Evaluation of In-Flight Icing Index Forecast for Aviation

<p>Hindcasts from the United Kingdom Met Office weather model are used as inputs to an in-flight icing index from the literature. This index uses information about model-predicted temperature, relative humidity, vertical velocity and cloud liquid water content. Parts of the icing index formulation are then modified slightly, in the light of comparisons between hindcast model data and ground-based remote sensing observations. Firstly, the link to relative humidity is replaced with a link to model-predicted cloud cover. Secondly, although super-cooled liquid water icing is due to cloud condensate in the liquid phase, the model may not always correctly partition its condensate into the correct phase. So the second modification is to consider all condensate irrespective of phase when calculating the icing index. The skill of the original and new index are then assessed quantitatively against satellite-derived icing potential. We show that the new indices have substantially better reliability than the operational index used up until recently. Finally, we present a case study, when icing was reported, and discuss ways of presenting the likelihood and severity information.</p>

Sensitivity of Cloud Liquid Water Content Estimates to the Temperature-Dependent Thermodynamic Phase: A Global Study Using CloudSat Data

The main purpose of this study is to underline the sensitivity of cloud liquid water content (LWC) estimates purely to 1) the shape of computationally simplified temperature-dependent thermodynamic phase and 2) the range of subzero temperatures covered to partition total cloud condensate into liquid and ice fractions. Linear, quadratic, or sigmoid-shaped functions for subfreezing temperatures (down to −20° or −40°C) are often used in climate models and reanalysis datasets for partitioning total condensate. The global vertical profiles of clouds obtained from CloudSat for the 4-yr period June 2006–May 2010 are used for sensitivity analysis and the quantitative estimates of sensitivities based on these realistic cloud profiles are provided. It is found that three cloud regimes in particular—convective clouds in the tropics, low-level clouds in the northern high latitudes, and middle-level clouds over the midlatitudes and Southern Ocean—are most sensitive to assumptions on thermodynamic phase. In these clouds, the LWC estimates based purely on quadratic or sigmoid-shaped functions with a temperature range down to −20°C can differ by up to 20%–40% over the tropics (in seasonal means), 10%–30% over the midlatitudes, and up to 50% over high latitudes compared to a linear assumption. When the temperature range is extended down to −40°C, LWC estimates in the sigmoid case can be much higher than the above values over high-latitude regions compared to the commonly used case with quadratic dependency down to −20°C. This sensitivity study emphasizes the need to critically investigate radiative impacts of cloud thermodynamic phase assumptions in simplified climate models and reanalysis datasets.