Abstract
Abstract. Observations made during late summer in the central Arctic Ocean, as part of the Arctic Summer Cloud Ocean Study (ASCOS), are used to evaluate cloud and vertical temperature structure in the Met Office Unified Model (MetUM). The observation period can be split into 5 regimes; the first two regimes had a large number of frontal systems, which were associated with deep cloud. During the remainder of the campaign a layer of low-level cloud occurred, typical of central Arctic summer conditions, along with two periods of greatly reduced cloud cover. The short-range operational NWP forecasts could not accurately reproduce the observed variations in near-surface temperature. A major source of this error was found to be the temperature-dependant surface albedo parameterisation scheme. The model reproduced the low-level cloud layer, though it was too thin, too shallow, and in a boundary-layer that was too frequently well-mixed. The model was also unable to reproduce the observed periods of reduced cloud cover, which were associated with very low cloud condensation nuclei (CCN) concentrations (<1 cm−3). As with most global NWP models, the MetUM does not have a prognostic aerosol/cloud scheme but uses a constant CCN concentration of 100 cm−3 over all marine environments. It is therefore unable to represent the low CCN number concentrations and the rapid variations in concentration frequently observed in the central Arctic during late summer. Experiments with a single-column model configuration of the MetUM show that reducing model CCN number concentrations to observed values reduces the amount of cloud, increases the near-surface stability, and improves the representation of both the surface radiation fluxes and the surface temperature. The model is shown to be sensitive to CCN only when number concentrations are less than 10–20 cm−3.
Highlights
Arctic temperatures are increasing faster than the global mean (Manabe and Wetherald, 1975; Serreze and Barry, 2011) and this is projected to continue through the 21st century (ACIA, 2004; Holland et al, 2006; Solomon et al, 2007)
Birch et al (2009) present a general evaluation of a recent version of the Met Office Unified Model (MetUM) using data from the Arctic Ocean Experiment (AOE) 2001 (Tjernstrom et al, 2004). They concluded that the occurrence and radiative properties of deeper clouds, which are associated with frontal systems, are represented more accurately than the low-level cloud that is ubiquitous to the summer central Arctic boundary layer
There are few, if any, insitu observations from the central Arctic Ocean assimilated into the operational forecasts, satellite retrievals of wind and radiance are assimilated at very low vertical resolution
Summary
Arctic temperatures are increasing faster than the global mean (Manabe and Wetherald, 1975; Serreze and Barry, 2011) and this is projected to continue through the 21st century (ACIA, 2004; Holland et al, 2006; Solomon et al, 2007). Clouds have a pronounced influence on the Arctic surface energy budget (Curry et al, 1996; Shupe and Intrieri, 2004; Sedlar et al, 2011) and on the melting and freezing of the Arctic perennial sea ice (Kay and Gettelman, 2009; Persson, 2011) In spite of this importance, clouds remain an Achilles heel in our understanding of the climate system and in climate modelling Birch et al (2009) present a general evaluation of a recent version of the Met Office Unified Model (MetUM) using data from the Arctic Ocean Experiment (AOE) 2001 (Tjernstrom et al, 2004) They concluded that the occurrence and radiative properties of deeper clouds, which are associated with frontal systems, are represented more accurately than the low-level cloud that is ubiquitous to the summer central Arctic boundary layer. Regime is used to highlight one possible reason why models over-predict low-level cloudiness
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