Geoscience Reference
In-Depth Information
Chapter 6
Quantifying Observation Impact for a Limited
Area Atmospheric Forecast Model
Clark Amerault, Keith Sashegyi, Patricia Pauley, and James Doyle
Abstract
Adjoint models calculate the first order sensitivity of a scalar output
parameter to an input vector. Adjoint numerical weather prediction models have
been used for a variety of sensitivity and data assimilation studies to provide a
gradient for a measure of error with respect to the model's analysis variables.
Recent work has shown that the adjoint of the data assimilation system can map
the gradient information in analysis space onto individual observations to provide
a quantitative estimate of an observation's influence on short-term forecast error.
This chapter will review the framework of an adjoint observation impact system
and some reported applications. Aspects of the framework particular to limited
area atmospheric models will be the main focus of this chapter and results from a
specific system will be presented. Issues discussed include: the effect of horizontal
grid spacing on observation impact, the influence of lateral boundaries on forecast
error, the relative importance of observations for different physical locations, and
appropriate error metrics for limited area forecast models.
6.1
Adjoint Sensitivities
This chapter investigates the application of a limited area adjoint observation impact
system. The adjoint operators of a numerical weather prediction (NWP) model and
data assimilation (DA) system are combined to quantify the influence an observation
has on short-term forecast error. This section reviews the previously developed
framework of the system and its components, beginning with the adjoint NWP
model. A description of the components of the limited area modeling system utilized
for this work is given in Sect.
6.2
, and observation impacts for the system are
presented in Sect.
6.3
. Future considerations are discussed in Sect.
6.4
.
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