Objective Analysis of ARM IOP Data: Method and Sensitivity

Abstract

Motivated by the need to obtain accurate objective analysis of field experimental data to force physical parameterizations in numerical models, this paper first reviews the existing objective analysis methods and interpolation schemes that are used to derive atmospheric wind divergence, vertical velocity, and advective tendencies. Advantages and disadvantages of different methods are discussed. It is shown that considerable uncertainties in the analyzed products can result from the use of different analysis. The paper then describes a hybrid approach to combine the strengths of the regular grid and the line-integral methods, together with a variational constraining procedure for the analysis of field experimental data. In addition to the use of upper-air data, measurements at the surface and at the top of the atmosphere (TOA) are used to constrain the upper-air analysis to conserve column-integrated mass, water, energy, and momentum. Analyses are shown for measurements taken in the Atmospheric Radiation Measurement Program July 1995 intensive observational period. Sensitivity experiments are carried out to test the robustness of the analyzed data and to reveal uncertainties in the analysis. These include sensitivities to the interpolation schemes, to the types of input data sources, and to the variational constraining procedures. It is shown that the constraining process of using additional surface and TOA data significantly reduces the sensitivity of the final data products.