The Adjoint Sensitivity Guidance to Diagnosis and Tuning of Error Covariance Parameters - Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications - page 199

Chapter 9
The Adjoint Sensitivity Guidance to Diagnosis
and Tuning of Error Covariance Parameters

Dacian N. Daescu and Rolf H. Langland

Abstract Adjoint techniques are effective tools for the analysis and optimization
of the observation performance on reducing the errors in the forecasts produced
by atmospheric data assimilation systems (DASs). This chapter provides a detailed
exposure of the equations that allow the extension of the adjoint-DAS applications
from observation sensitivity and forecast impact assessment to diagnosis and tuning
of parameters in the observation and background error covariance representation.
The error covariance sensitivity analysis allows the identification of those param-
eters of potentially large impact on the forecast error reduction and provides a
first-order diagnostic to parameter specification. A proof-of-concept is presented
together with comparative results of observation impact assessment and sensitivity
analysis obtained with the adjoint versions of the Naval Research Laboratory
Atmospheric Variational Data Assimilation System - Accelerated Representer
(NAVDAS-AR) and the Navy Operational Global Atmospheric Prediction System
(NOGAPS).

9.1 Introduction

Advanced measurement capabilities and algorithms for operational retrieval of
atmospheric parameters from data acquired by remote sensing instruments have
increased at a fast pace the amount of information provided by the global observing
system ( Thepaut and Andersson 2010 ; Lahoz 2010 ).Asthedatavolumehas