Kilometer‐Scale Simulations of Trade‐Wind Cumulus Capture Processes of Mesoscale Organization. (1st March 2023) - Saffin, Leo; Lock, Adrian; Tomassini, Lorenzo; Blyth, Alan; Böing, Steven; Denby, Leif; Marsham, John
Abstract: The EUREC 4 A (Elucidating the role of clouds–circulation coupling in climate) and ATOMIC (Atlantic Tradewind Ocean‐Atmosphere Mesoscale Interaction Campaign) joint field campaign gathered observations to better understand the links between trade‐wind cumulus clouds, their organization, and larger scales, a large source of uncertainty in climate projections. A recent large‐eddy simulation study showed a cloud transition that occurred during this field campaign, where small shallow clouds developed into larger clouds with detrainment layers, was caused by an increase in mesoscale organization generated by a dynamical feedback in mesoscale vertical velocities. We show that kilometer‐scale simulations with the Met Office's Unified Model reproduce this increase in mesoscale organization and the process generating it, despite being much lower resolution. The timing of development is associated with large‐scale convergence. Sensitivity tests with a shorter spin‐up time, to reduce initial organization, still have the same timing of development and sensitivity tests with cold pools suppressed show only a small effect on mesoscale organization. Mesoscale organization and clouds are sensitive to resolution, with higher resolution simulations producing weaker organization and less cloud, which affects changes in net radiation. The clouds also have substantial differences to observations. Therefore, while kilometer‐scale simulations can be useful for understanding processes of mesoscale organization and links with large scales, including responses to climate change, simulations will still suffer from significant errors and uncertainties in radiative budgets. Plain Language Summary: A recent field campaign made extensive measurements of shallow clouds upstream of Barbados and the surrounding region. These clouds are important because their effect on climate change is highly uncertain. Cloud patterns in satellite images in this region can vary dramatically. One example, from 2 February 2020, is when the clouds changed from a region of small clouds that looks like a scattering of sugar to larger patches of clouds that look like flowers separated by clear sky. A previous study with a very high resolution model has shown the physical mechanism behind this change in the cloud pattern. We show that lower resolution simulations can reproduce this transition and the physical mechanism associated with it. Low resolution allows for a much larger domain which can capture features of the atmospheric flow on larger scales. However, the development of individual clouds is poorly represented. The results show the model is a useful testbed for better understanding the physical mechanism behind changes in cloud patterns and what might affect it, but the impacts of clouds on climate, via reflecting sunshine and absorbing infrared radiation, will still have large errors and uncertainties in climate projections. Key Points: Kilometer‐scale Unified Model simulations capture an increase in mesoscale organization associated with an observed "flowers" cloud pattern The time during which clouds and mesoscale organization develop is associated with large‐scale convergence Initial organization and cold pools have little effect on timing and cold pools only have a small opposing effect to mesoscale organization