Identification

Title

Correcting for position errors in variational data assimilation

Abstract

The Feature Calibration and Alignment technique (FCA) has been developed to characterize errors that a human would ascribe to a change in the position or intensity of a coherent feature, such as a hurricane. Here the feature alignment part of FCA is implemented in the Weather Research and Forecasting Data Assimilation system (WRFDA) to correct position errors in background fields and tested in simulation for the case of Hurricane Katrina (2005). The displacement vectors determined by feature alignment can be used to explain part of the background error and make the residual background errors smaller and more Gaussian. Here a set of 2D displacement vectors to improve the alignment of features in the forecast and observations is determined by solving the usual variational data assimilation problem--simultaneously minimizing the misfit to observations and a constraint on the displacements. This latter constraint is currently implemented by hijacking the usual background term for the midlevel u- and υ-wind components. The full model fields are then aligned using a procedure that minimizes dynamical imbalances by displacing only conserved or quasi-conserved quantities. Simulation experiments show the effectiveness of these procedures in correcting gross position errors and improving short-term forecasts. Compared to earlier experiments, even this initial implementation of feature alignment produces improved short-term forecasts. Adding the calculation of displacements to WRFDA advances the key contribution of FCA toward mainstream implementation since all observations with a corresponding observation operator may be used and the existing methodology for estimating the background error covariances may be used to refine the displacement error covariances.

Resource type

document

Resource locator

Unique resource identifier

code

http://n2t.net/ark:/85065/d7ht2qh7

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

Resource Type

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

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Temporal reference

Temporal extent

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Dataset reference date

date type

publication

effective date

2015-04-01T00:00:00Z

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Copyright 2015 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be "fair use" under Section 107 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Law (17 USC, as revised by P.L. 94-553) does not require the Society's permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statements, requires written permission or license from the AMS. Additional details are provided in the AMS Copyright Policies, available from the AMS at 617-227-2425 or amspubs@ametsoc.org. Permission to place a copy of this work on this server has been provided by the AMS. The AMS does not guarantee that the copy provided here is an accurate copy of the published work.

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact