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Gregory S. Elsaesser

Publications and source records attributed to Gregory S. Elsaesser.

2 recordsLinked to original sources

Accurate Column Moist Static Energy Budget in Climate Models. Part 1: Conservation Equation Formulation, Methodology, and Primary Results Demonstrated Using GISS ModelE3

Column-integrated moist static energy (MSE) budgets underpin theories of tropical convection and circulation, yet in reanalyses and climate models the budget rarely closes; residuals routinely match the leading terms and mask physical insights. This study derives an MSE conservation law that is strictly consistent with GISS ModelE3 and elucidates why conventional diagnostics fail. Multiple intertwined factors -- the breakdown of the product rule upon discretization, effects of mass-filtering, mismatched flux and advective forms, numerical noise in diagnosed vertical velocity, asynchronous model output timing, and postprocessing including vertical interpolation and temporal averaging -- leave significant residuals in both annual means and daily variability, even when raw 30-min model output is used. Residuals are even larger over land and along coastlines. To tackle this obstacle, this study implements the "process increment method," which accurately computes the column MSE flux divergence by calculating the change in column-integrated internal energy, geopotential energy, and latent heats before and after applying the dynamics scheme. Furthermore, the calculated column flux divergence is decomposed into horizontal and vertical advective components. The most crucial finding is that vertical interpolation into pressure coordinates can introduce errors substantial enough to reverse the sign of vertical MSE advection in the warm-pool regions. In ModelE3, native-grid values show MSE import via vertical circulations, while values after interpolation into pressure coordinates indicate export. This discrepancy may prompt a reevaluation of vertical advection as an exporting mechanism and underscores the importance of precise MSE budget calculations.

physics.ao-ph

Towards a Climate OSSE Framework for Satellite Mission Design

The rich history of observing system simulation experiments (OSSEs) does not yet include a well-established framework for using climate models. The need for a climate OSSE is triggered by the need to quantify the value of a particular measurement for reducing the uncertainty in climate predictions, which differ from numerical weather predictions in that they depend on future atmospheric composition rather than the current state of the weather. However, both weather and climate modeling communities share a need for motivating major observing system investments. Here we outline a new framework for climate OSSEs that leverages the use of machine-learning to calibrate climate model physics against existing satellite data. We demonstrate its application using NASA's GISS-E3 model to objectively quantify the value of potential future improvements in spaceborne measurements of Earth's planetary boundary layer. A mature climate OSSE framework should be able to quantitatively compare the ability of proposed observing system architectures to answer a climate-related question, thus offering added value throughout the mission design process, which is subject to increasingly rapid advances in instrument and satellite technology. Technical considerations include selection of observational benchmarks and climate projection metrics, approaches to pinpoint the sources of model physics uncertainty that dominate uncertainty in projections, and the use of instrument simulators. Community and policy-making considerations include the potential to interface with an established culture of model intercomparison projects and a growing need to economically assess the value-driven efficiency of social spending on Earth observations.

physics.ao-ph