- Related Research Areas
- Climate Variability & Change, Water & Energy Cycles
Marine boundary layer clouds have a strong cooling effect on Earth's climate because they reflect more solar radiation back to space than does the dark ocean while exerting nearly the same greenhouse effect as the cloud-free atmosphere. One major climate change question is how marine boundary layer clouds will respond to global warming produced by anthropogenic greenhouse gases, and whether the cloud response will exacerbate (positive feedback) or mitigate (negative feedback) the global warming. Marine boundary layer clouds are incorrectly and inconsistently simulated in current global climate models, and some models predict an increase in cloud cover during the 21st century whereas other models predict a decrease. Differences in marine boundary layer cloud simulation are one of the biggest contributors to uncertainty in estimates of future global warming. It is therefore crucial to better understand how meteorological processes control cloud properties, better evaluate how global climate models correctly or incorrectly simulate clouds, and better project how the cloud properties will change with global warming and what feedback this will have on Earth's climate. Many previous studies and model cloud evaluations have examined relationships between meteorological parameters and marine boundary layer cloud properties, but almost all of these have focused on cloud and meteorological data obtained for the same time point. One great disadvantage of this approach is that the boundary layer has a finite time response to a change in external forcing such that cloud properties are often more correlated to meteorological conditions experienced one day earlier than meteorological conditions at the time of observation. The proposed research addresses this problem by introducing a new technique that considers cloud dynamics from a Lagrangian perspective, using parcel trajectories. Satellite-observed cloud properties and reanalysis meteorological parameters will be interpolated onto back trajectory locations to document how cloud properties and meteorological conditions (e.g., lower tropospheric stability, humidity, radiative flux, subsidence rate, surface divergence, surface fluxes, etc.) vary over a three-day period and how cloudiness at t = 0 is related to previous meteorological forcing along the back trajectory. Compositing techniques will be applied to hold some meteorological parameters constant while allowing another to vary in order to determine how each parameter independently affects cloudiness. The back trajectory and compositing techniques will then be applied to global climate model output to evaluate the how well the model simulates specific relationships between cloud properties and meteorological parameters. The characterization of model cloud simulation errors will provide insight into how to improve cloud parameterizations. Examination of the connections between errors in the cloud simulation at synoptic time scales and at climate time scales will enable an assessment of the accuracy of marine boundary layer cloud feedbacks in the models.
Project PI: Joel Norris/University of California, San Diego
Scripps Institution of Oceanography, UCSD 9500 Gilman Drive La Jolla CA, 92093 Mail Code: 0224
Phone: (858) 822-4420
Fax: (858) 534-8561
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