Process‐based simulation of contrail cirrus in a global climate model

Abstract

[1] Aviation induces changes in global cirrus cloudiness by producing contrails. In the past, line shaped contrail coverage has been parameterized relying on the scaling of contrail formation frequency to observed values. Coverage due to irregularly shaped contrail cirrus, that develop from line shaped contrails, could not be estimated with this method. We introduce a process-based parameterization of contrail cirrus in a global climate model that does not rely on scaling and that is not restricted to line shaped contrails. A new prognostic cloud class, contrail cirrus, is introduced that is allowed to develop in the parameterized, fractional ice supersaturated area. Initial dimensions of the contrails and a parameter controlling their spreading in a sheared flow are constrained by observational data. In an idealized experiment contrail cirrus coverage is found to be dominated by a major contrail outbreak and scales with supersaturation rather than contrail formation frequency. The global distribution of young contrail coverage is smoothed out due to transport but overall values are similar compared to older estimates. Interannual variability of young contrail coverage can be as large as the mean coverage. The sensitivity of the model simulations to physical model parameters and to parameters concerning the comparison with observational data is studied. The associated uncertainty of global line shaped contrail coverage can be as high as 60% of the reference estimate (0.05%). The simulated coverage due to young contrails agrees reasonably well with most satellite observations of regional line shaped contrail coverage considering the sensitivity to the above parameters and the interannual variability.Citation: Burkhardt, U., and B. Kärcher (2009), Process-based simulation of contrail cirrus in a global climate model, J. Geophys.

Simulated radiative forcing from contrails and contrail cirrus

“…The forcing obtained from these online diagnostic calculations is defined as the "instantaneous effect", which represents our best estimate for linear contrail radiative forcing. These initial contrails resemble linear contrails from previous studies in which normalization (Ponater et al, 2002;Rap et al, 2010) or diagnostic lifetime constraint (Burkhardt and Kärcher, 2009) has been made towards observed linear contrail coverage, but they do not refer to the same entity.…”

Parameterization of contrails in the UK Met Office Climate Model

“…[52] The HadGEM2 GCM with the contrail parameterization described in this paper is the only other GCM with a built-in on-line contrail parameterization, apart from the ECHAM4 model, for which two contrail parameterizations have been developed, namely that of Ponater et al [2002] and the recent Burkhardt and Kärcher [2009] contrail cirrus parameterization. Although our parameterization follows a methodology inspired by Ponater et al [2002], there are some significant differences between the two schemes, since they are hosted in two very different climate models.…”

“…When estimating global contrail RF, most available models assume constant optical properties for contrails. Currently there are only two climate model approaches that 1 have the ability of considering a geographical and temporal variability for contrail optical depths, namely the Ponater et al [2002] model, with amendments by Marquart and Mayer [2002], and the Burkhardt and Kärcher [2009] contrail cirrus model, both hosted by the ECHAM4 climate model. As air traffic is expected to experience a significant increase in the future, the contrail warming effect may become stronger and therefore the development of more reliable models that can accurately estimate contrail formation and their radiative impact is considered important.…”

Global Modeling of the Contrail and Contrail Cirrus Climate Impact

“…Neither can the geometrical shapes of individual clouds be simulated in large-scale models, nor can the fraction of linear contrails to contrail cirrus, or the duration of the period for which contrails remain linear, be known from observations. Validation of linear contrail coverage and optical depth is further hampered by variable and unspecified optical depth detection thresholds of satellite sensors (Kärcher et al 2009). In situ measurements give us clues about ice water content and ice particle number concentrations, size, and shape, but statistics may be biased toward optically thicker contrails that are easily detectable.…”