Four-Dimensional Model Assimilation of Data A Strategy for the Earth System Sciences (1991) / Chapter Skim
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5 Quality Control and Validation of Observations, Analyses, and Models
5 Quality Control and Validation of Observations, Analyses, and Models
Pages 48-54
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From page 48... ...
Inconsistencies between the observations and predictions are easily documented and demand explanation, providing the basis for quality control and validation of observations, analyses, and the models themselves. DATA MONITORING Significant improvements over the last decade in the use of data assimilation for numerical weather prediction (NWP)
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From page 49... ...
The relatively high accuracy of short-range forecasts is used by NWP centers to monitor systematically many types of observations. Such monitonng has successfully identified long-standing errors in radiosondes at remote stations, in reports from ships plying remote routes, in aircraft reports over the oceans, in cloud-track winds from geostationary satellites, and in temperature soundings from polar-orbiting satellites.
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From page 50... ...
Ideally, an experienced analyst would recognize a poorly observed atmospheric process that is not represented well by the background field and subjectively modify the analysis to ensure consistency with a conceptual understanding of the process or phenomenon on the scale of the model. This is an important area of research, particularly for mesoscale data assimilation where sometimes few data points are available to define important mesoscale structures.
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From page 51... ...
Early availability of real-time operational analyses will stimulate research on new satellite observations and demand for more rapid production of delayed-mode analyses. The use of EOS data in operational data assimilation will therefore be the first iteration of the research use of the data, and so the operational centers can contribute a great deal to the success of the overall research goals provided they are tasked and funded to produce research-quality assimilaiion data sets during the daily cycle.
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From page 52... ...
. A validation method of increasing importance is the use of atmospheric model-assimilated data sets ~ drive ocean circulation or ocean wave models.
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From page 53... ...
Calculations of the monthly average of a model's initial adiabatic tendency and diabetic tendency then provide three-dimensional fields of the "true" diabetic forcing and of the errors in the model's diabetic forcing. Recent applications of this methodology to model-assimilated data sets and to 1-day and 10-day forecasts have shown that there are close similarities between the mean errors (sometimes referred to in jargon as climate drift)
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From page 54... ...
This new approach to model validation provides useful insight into the sources of errors in the physical parametenzations, and it provides a valuable additional method for systematic assessment of the performance of model physics. Its effectiveness depends entirely on the availability of the model-assimilated data sets.
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