Fitting microphysical observations on nonsteady convective clouds to a numerical model: An application of the adjoint technique of data assimilation to a kinematic model
- Colorado State Univ., Fort Collins, CO (United States)
Rapid advances in the quality and quantity of atmospheric observations have placed a demand for the development of techniques to assimilate these data sources into numerical forecasting models. Four-dimensional variational assimilation is a promising technique that has been applied to atmospheric and oceanic dynamical models, and to the retrieval of three-dimensional wind fields from single-Doppler radar observations. This study investigates the feasibility of using space-time variational assimilation for a complex discontinuous numerical model including cloud physics. Two test models were developed: a one-dimensional and a two-dimensional liquid physics kinematic microphysical model. These models were used in identical-twin experiments, with observations taken intermittently. Small random errors were introduced into the observations. The retrieval runs were initialized with a large perturbation of the observation run initial conditions. The models were able to retrieve the original initial conditions to a satisfactory degree when observations of all the model prognostic variables were used. Greater overdetermination of the degrees of freedom (the initial condition being retrieved) resulted in greater improvement of the errors in the observations of the initial conditions, but at a rapid increase in computational cost. Experiments where only some of the prognostic variables were observed also improved the initial conditions, but at a greater cost. To substantially improve the first guess of the field not observed, some spot observations are needed. The proper scaling of the variables was found to be important for rate of convergence. This study suggests that scaling factors related to the error variance of the observations give good convergence rates. 34 refs., 12 figs., 1 tab.
- OSTI ID:
- 5645164
- Journal Information:
- Monthly Weather Review; (United States), Vol. 121:10; ISSN 0027-0644
- Country of Publication:
- United States
- Language:
- English
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CLIMATE MODELS
COMPUTERIZED SIMULATION
CLOUDS
REMOTE SENSING
WEATHER
FORECASTING
DEGREES OF FREEDOM
EARTH ATMOSPHERE
FLUID MECHANICS
FOUR-DIMENSIONAL CALCULATIONS
METEOROLOGY
NUMERICAL ANALYSIS
PERTURBATION THEORY
MATHEMATICAL MODELS
MATHEMATICS
MECHANICS
SIMULATION
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