June 2012 - Recent work comparing aircraft observations and high-resolution simulations leads to useful improvements for our weather and climate models.
Stratocumulus clouds are the most prevalent cloud type across the planet, covering approximately 20% of the Earth's surface at any time. They are low-level clouds and provide a net-cooling effect to the climate system, reflecting large amounts of solar radiation back into space. Only a small increase in the global coverage of stratocumulus would be required to counteract the warming effect of increasing greenhouse gases, whilst a small decrease could significantly magnify the effect. Over land, and on a local scale, the presence of stratocumulus can have a significant effect on the surface temperature, keeping temperatures cooler during the day time and warmer at night. Therefore understanding the physical processes that control the generation and evolution of this cloud type, and modelling them accurately, is of crucial importance for both weather forecasts and climate modelling. However, many current weather forecast and climate models struggle to accurately simulate these boundary layer clouds, e.g. Wyant et al. (2010).
The VAMOS Ocean-Cloud-Atmosphere-Land Study (VOCALS) is a major international program, the goal of which is to improve the scientific understanding of the coupled ocean-atmosphere-land system in the south-east Pacific. This region is of huge importance to the climate system, in part due to the presence of the largest subtropical stratocumulus deck on the planet, covering some 107 km2 of the Pacific Ocean, roughly equivalent in size to Europe. Global satellite image with the VOCALS study area highlighted. As part of the VOCALS program, a large international field experiment was undertaken during October and November 2008. A major component of the experiment was to make high quality observations of the stratocumulus deck, in order to develop improvements to how these clouds are represented in numerical models. Many scientists from around the globe took part during the intensive observational period, which involved five research aircraft including the FAAM BAe-146, two research ships, and two surface sites in northern Chile. Based from Arica, Chile, the FAAM aircraft was used to make measurements of the structure and composition of the cloud field during 13 research flights. Flight patterns included straight-and-level runs in the cloud and sub-cloud layers, and vertical profiles through the cloud to obtain in-situ measurements from the instrumentation on the aircraft. There were also high-level legs, along which dropsondes were released from the aircraft to obtain vertical profiles through the atmosphere.
Recently, the Met Office Unified Model (MetUM) has been used for a high resolution modelling case study, incorporating two of these flights on the 12 and 13 November 2008. Typically, the global model with its 25 km grid is the highest resolution model run in this region, whilst for climate modelling the grid-length is closer to 100 km (1 degree of longitude). This study included a fine resolution model with 4 km grid and even finer resolution model with 1 km grid, both similar to the UKV model, which due to their computational expense can only be run over relatively small regions of the south-east Pacific, with boundary conditions provided by lower resolution simulations.
Comparing the model simulations with the satellite picture shows that only the 1 km grid is able to produce realistic structure in the cloud field, with the 4 km grid surrounding the edge of the domain looking like a blurred version. The first flight transited at low level from the coast out to the region near 75°W, 19°S, where one of the research vessels was located. The second flight transited at low level along the 20°S latitude, taking low-level profiles on the way out, with a high-level return leg releasing dropsondes.
Careful analysis of these simulations and comparisons to observations taken from the research flights were able to demonstrate improvements that could be made in the way the MetUM simulates the growth of cloud water droplets and their transition into rain. In stratocumulus cloud, turbulence leads to the collision and coalescence of cloud water droplets near the cloud top. As the cloud droplets grow in size, they become too heavy to be kept near the cloud top by the ascent within the cloud, and start to fall towards the surface as raindrops. As they fall, they accrete more cloud droplets and continue to grow in size, until they exit the cloud base. In the sub-saturated air below the cloud, the raindrops start to evaporate, and reduce in size until they either evaporate completely or reach the surface. The MetUM simulates these processes, but the simulations were converting the cloud water into rain too easily, and the raindrops that were created were too large, meaning that they fell to the surface very quickly with little chance to evaporate. This resulted in the cloud layer being too thin and too near the surface, and the surface rain-rate being too high. By making it harder for the model to convert cloud water into rain, and reducing the size of the raindrops to match observations better, not only was the surface rain-rate improved in the simulations, but more water was left in the cloud layer, making the cloud thicker and higher, and a better comparison to the observations.
One paper ( Boutle & Abel (2012)) describing these VOCALS comparisons has recently been published, but the insight and information gained from this observation-model comparison was able to drive developments to the global weather forecast and climate model configurations of the MetUM. Abel & Boutle (2012) showed that by improving the size of raindrops, the model representation of low-level clouds and precipitation across the globe was improved. This was useful for the forecast model, in which the improvement of cloud and precipitation processes also led to an improvement in near-surface temperatures and visibility forecasts. It was also of use for the climate model, allowing metrics such as dry-day frequency to be improved, a measure which is crucial for drought forecasting.
Abel, S.J. and Boutle, I.A., An improved representation of the raindrop size distribution for single-moment microphysics schemes, Quart. J. Roy. Meteorol. Soc., doi:10.1002/qj.1949, 2012.
Boutle, I.A. and Abel, S.J., Microphysical controls on the stratocumulus topped boundary-layer structure during VOCALS-REx, Atmos. Chem. Phys., 12, 2849-2863,, 2012.
Wyant, M.C. and coauthors, The PreVOCA experiment: modeling the lower troposphere in the Southeast Pacific, Atmos. Chem. Phys., 10, 4757-4774,, 2010.
Last updated: 14 August 2014