Comparison of Conventional and Constrained Variational Methods for Computing Large-Scale Budgets and Forcing Fields

Abstract

Analyses of atmospheric heat and moisture budgets serve as an effective tool to study convective characteristics over a region and to provide large-scale forcing fields for various modeling applications. This paper examines two popular methods for computing large-scale atmospheric budgets: the conventional budget method (CBM) using objectively gridded analyses based primarily on radiosonde data and the constrained variational analysis (CVA) approach which supplements vertical profiles of atmospheric fields with measurements at the top of the atmosphere and at the surface to conserve mass, water, energy, and momentum. Successful budget computations are dependent on accurate sampling and analyses of the thermodynamic state of the atmosphere and the divergence field associated with convection and the large-scale circulation that influences it. Utilizing analyses generated from data taken during Dynamics of the Madden-Julian Oscillation (DYNAMO) field campaign conducted over the central Indian Ocean from October to December 2011, we evaluate the merits of these budget approaches and examine their limitations. While many of the shortcomings of the CBM, in particular effects of sampling errors in sounding data, are effectively minimized with CVA, accurate large-scale diagnostics in CVA are dependent on reliable background fields and rainfall constraints. Finally, for the DYNAMO analyses examined, the operational model fields used as the CVA background state provided wind fields that accurately resolved the vertical structure of convection in the vicinity of Gan Island. However, biases in the model thermodynamic fields were somewhat amplified in CVA resulting in a convective environment much weaker than observed.