Abstract

The influence of six CAM5.1 cloud microphysical parameters on the variance of phase partitioning in mixed-phase clouds is determined by application of a variance-based sensitivity analysis. The sensitivity analysis is based on a generalized linear model that assumes a polynomial relationship between the six parameters and the two-way interactions between them. The parameters, bounded such that they yield realistic cloud phase values, were selected by adopting a quasi–Monte Carlo sampling approach. The sensitivity analysis is applied globally, and to 20°-latitude-wide bands, and over the Southern Ocean at various mixed-phase cloud isotherms and reveals that the Wegener–Bergeron–Findeisen (WBF) time scale for the growth of ice crystals single-handedly accounts for the vast majority of the variance in cloud phase partitioning in mixed-phase clouds, while its interaction with the WBF time scale for the growth of snowflakes plays a secondary role. The fraction of dust aerosols active as ice nuclei in latitude bands, and the parameter related to the ice crystal fall speed and their interactions with the WBF time scale for ice are also significant. All other investigated parameters and their interactions with each other are negligible (<3%). Further analysis comparing three of the quasi–Monte Carlo–sampled simulations with spaceborne lidar observations by CALIOP suggests that the WBF process in CAM5.1 is currently parameterized such that it occurs too rapidly due to failure to account for subgrid-scale variability of liquid and ice partitioning in mixed-phase clouds.

Abstract

A new treatment of mixed-phase cloud microphysics has been implemented in the general circulation model, Community Atmosphere Model (CAM)-Oslo, which combines the NCAR CAM2.0.1 and a detailed aerosol module. The new treatment takes into account the aerosol influence on ice phase initiation in stratiform clouds with temperatures between 0° and −40°C. Both supersaturation and cloud ice fraction, that is, the fraction of cloud ice compared to the total cloud water in a given grid box, are now determined based on a physical reasoning in which not only temperature but also the ambient aerosol concentration play a role. Included in the improved microphysics treatment is also a continuity equation for ice crystal number concentration. Ice crystal sources are heterogeneous and homogeneous freezing processes and ice multiplication. Sink terms are collection processes and precipitation formation, that is, melting and sublimation. Instead of using an idealized ice nuclei concentration for the heterogeneous freezing processes, a common approach in global models, the freezing processes are here dependent on the ability of the ambient aerosols to act as ice nuclei. Additionally, the processes are dependent on the cloud droplet number concentration and hence the aerosols’ ability to act as cloud condensation nuclei. Sensitivity simulations based on the new microphysical treatment of mixed-phase clouds are presented for both preindustrial and present-day aerosol emissions. Freezing efficiency is found to be highly sensitive to the amount of sulphuric acid available for ice nuclei coating. In the simulations, the interaction of anthropogenic aerosols and freezing mechanisms causes a warming of the earth–atmosphere system, counteracting the cooling effect of aerosols influencing warm clouds. The authors find that this reduction of the total aerosol indirect effect amounts to 50%–90% for the specific assumptions on aerosol properties used in this study. However, many microphysical processes in mixed-phase clouds are still poorly understood and the results must be interpreted with that in mind.

Abstract

Shortwave radiative feedbacks from Southern Ocean clouds are a major source of uncertainty in climate projections. Much of this uncertainty arises from changes in cloud scattering properties and lifetimes that are caused by changes in cloud thermodynamic phase. Here we use satellite observations to infer the scattering component of the cloud-phase feedback mechanism and determine its relative importance by comparing it with an estimate of the overall temperature-driven cloud feedback. The overall feedback is dominated by an optical thinning of low-level clouds. In contrast, the scattering component of cloud-phase feedback is an order of magnitude smaller and is primarily confined to free-tropospheric clouds. The small magnitude of this feedback component is a consequence of counteracting changes in albedo from cloud optical thickening and enhanced forward scattering by cloud particles. These results indicate that shortwave cloud feedback is likely positive over the Southern Ocean and that changes in cloud scattering properties arising from phase changes make a small contribution to the overall feedback. The feedback constraints shift the projected 66% confidence range for the global equilibrium temperature response to doubling atmospheric CO₂ by about +0.1 K relative to a recent consensus estimate of cloud feedback.

Abstract

In-cloud icing is a major hazard for aviation traffic and forecasting of these events is an important task for weather agencies worldwide. A common tool utilized by aviation forecasters is an icing intensity index based on supercooled liquid water from numerical weather prediction models. We seek to validate the modified microphysics scheme, ICE-T, in the HARMONIE-AROME numerical weather prediction model with respect to aircraft icing. Icing intensities and supercooled liquid water derived from two 3-month winter season simulations with the original microphysics code, CTRL, and ICE-T are compared with pilot reports of icing and satellite retrieved values of liquid and ice water content from CloudSat–CALIPSO and liquid water path from AMSR-2. The results show increased supercooled liquid water and higher icing indices in ICE-T. Several different thresholds and sizes of neighborhood areas for icing forecasts were tested out, and ICE-T captures more of the reported icing events for all thresholds and nearly all neighborhood areas. With a higher frequency of forecasted icing, a higher false alarm ratio cannot be ruled out, but is not possible to quantify due to the lack of no-icing observations. The increased liquid water content in ICE-T shows a better match with the retrieved satellite observations, yet the values are still greatly underestimated at lower levels. Future studies should investigate this issue further, as liquid water content also has implications for downstream processes such as the cloud radiative effect, latent heat release, and precipitation.

Abstract

In the winter, orographic precipitation falls as snow in the mid- to high latitudes where it causes avalanches, affects local infrastructure, or leads to flooding during the spring thaw. We present a technique to validate operational numerical weather prediction model simulations in complex terrain. The presented verification technique uses a combined retrieval approach to obtain surface snowfall accumulation and vertical profiles of snow water at the Haukeliseter test site, Norway. Both surface observations and vertical profiles of snow are used to validate model simulations from the Norwegian Meteorological Institute’s operational forecast system and two simulations with adjusted cloud microphysics. Retrieved surface snowfall is validated against measurements conducted with a double-fence automated reference gauge (DFAR). In comparison, the optimal estimation snowfall retrieval produces +10.9% more surface snowfall than the DFAR. The predicted surface snowfall from the operational forecast model and two additional simulations with microphysical adjustments (CTRL and ICE-T) are overestimated at the surface with +41.0%, +43.8%, and +59.2%, respectively. Simultaneously, the CTRL and ICE-T simulations underestimate the mean snow water path by −1071.4% and −523.7%, respectively. The study shows that we would reach false conclusions only using surface accumulation or vertical snow water content profiles. These results highlight the need to combine ground-based in situ and vertically profiling remote sensing instruments to identify biases in numerical weather prediction.

The Dominica Experiment (DOMEX) took place in the eastern Caribbean from 4 April to 10 May 2011 with 21 research flights of the Wyoming King Air and several other observing systems. The goal was an improved understanding of the physics of convective orographic precipitation in the tropics. Two types of convection were found. During a period of weak trade winds, diurnal thermal convection was seen over Dominica. This convection caused little precipitation but carried aloft air with island-derived aerosol and depleted CO₂. During periods of strong trades, mechanically forced convection over the windward slopes brought heavy rain to the high terrain. This convection was “seeded” by trade-wind cumuli or neutrally buoyant cool wet patches of air. In this mechanically forced convection, air parcels did not touch the island surface to gain buoyancy so no island-derived tracers were lofted. With fewer aerosols, the mean cloud droplet diameter increased from 15 to 25 μm. Plunging airflow and a wake were found in the lee of Dominica. The DOMEX dataset will advance our understanding and test our theories of cumulus triggering and aerosol influence on precipitation.