Nancy L. Baker

Estimation of observation impact using the NRL atmospheric variational data assimilation adjoint system

An adjoint-based procedure for assessing the impact of observations on the short-range forecast error in numerical weather prediction is described. The method is computationally inexpensive and allows observation impact to be partitioned for any set or subset of observations, by instrument type, observed variable, geographic region, vertical level or other category. The cost function is the difference between measures of 24-h and 30-h global forecast error in the Navy Operational Global Atmospheric Prediction System (NOGAPS) during June and December 2002. Observations are assimilated at 00UTC in the Naval Research Laboratory (NRL) Atmospheric Variational Data Assimilation System (NAVDAS). The largest error reductions in the Northern Hemisphere are produced by rawinsondes, satellite wind data, and aircraft observations. In the Southern Hemisphere, the largest error reductions are produced by Advanced TIROS Operational Vertical Sounder (ATOVS) temperature retrievals, satellite wind data and rawinsondes. Approximately 60% (40%) of global observation impact is attributed to observations below (above) 500 hPa. A significant correlation is found between observation impact and cloud cover at the observation location. Currently, without consideration of moisture observations and moist processes in the forecast model adjoint, the observation impact procedure accounts for about 75% of the actual reduction in 24-h forecast error.

Comparison of Hybrid Ensemble/4DVar and 4DVar within the NAVDAS-AR Data Assimilation Framework

AbstractThe effect on weather forecast performance of incorporating ensemble covariances into the initial covariance model of the four-dimensional variational data assimilation (4D-Var) Naval Research Laboratory Atmospheric Variational Data Assimilation System-Accelerated Representer (NAVDAS-AR) is investigated. This NAVDAS-AR-hybrid scheme linearly combines the static NAVDAS-AR initial background error covariance with a covariance derived from an 80-member flow-dependent ensemble. The ensemble members are generated using the ensemble transform technique with a (three-dimensional variational data assimilation) 3D-Var-based estimate of analysis error variance. The ensemble covariances are localized using an efficient algorithm enabled via a separable formulation of the localization matrix. The authors describe the development and testing of this scheme, which allows for assimilation experiments using differing linear combinations of the static and flow-dependent background error covariances. The tests are ...

An Observational Study of the "Interstate 5" Dust Storm Case

On 29 November 1991 a series of collisions involving 164 vehicles occurred on Interstate 5 in the San Joaquin Valley in California in a dust storm that reduced the visibility to near zero. The accompanying high surface winds are hypothesized to result from intense upper-tropospheric downward motion that led to the formation of a strong upper front and tropopause fold and that transported high momentum air downward to midlevels where boundary layer processes could then mix it to the surface. The objectives of the research presented in this paper are to document the event, to provide support for the hypothesis that both upper-level and boundary layer processes were important, and to determine the structure of the mesoscale circulations in this case for future use in evaluating the navys mesoscale data assimilation system. The strong upper-level descent present in this case is consistent with what one would expect for jet streak and frontal circulations in combination with quasigeostrophic processes. During...

Rifting history of the northern Mariana Trough: SeaMARC II and seismic reflection surveys

SeaMARC II sidescan sonar data and seismic reflection profiles of the northernmost portion of the Mariana Trough suggest a rifting rather than a seafloor-spreading origin for lithosphere within this active backarc basin of the western Pacific. Variations in morphology along the strike of the backarc basin suggest both a spatial and a temporal variation in the style of extension of the basin. The northern Mariana Trough widens from 70 km near 23°N to 135 km near 21°30′N. Major active fault zones bound both sides of the backarc basin. Active rifting and volcanism are predominant in a roughly 20-km-wide active rift zone along the eastern (arc) side of the basin from 24°N to 22°N. The locus of active rifting has remained near the volcanic front of the arc during extension and is probably controlled by lithospheric weakness, which is greatest at the volcanic front. The zone of rifting intersects the active volcanic arc at Nikko Seamount. The distinction between the mechanism for formation of the Mariana Trough proposed here and that of slow mid-ocean ridge spreading is that no true plate boundary has developed in the northernmost Mariana Trough. Rather, the backarc basin is composed of arc lithosphere intruded by arc and backarc basin magmas. Volcanism both in the rift zone and throughout the basin is fault-controlled. South of 22°N, the zone of active rifting diverges westward from the arc as the transition to true seafloor spreading is approached. The transition to true mid-ocean ridge spreading occurs to the south of the survey area described here.

Evaluation of SSMIS Upper Atmosphere Sounding Channels for High-Altitude Data Assimilation

AbstractUpper atmosphere sounding (UAS) channels of the Special Sensor Microwave Imager/Sounder (SSMIS) were assimilated using a high-altitude version of the Navy Global Environmental Model (NAVGEM) in order to investigate their potential for operational forecasting from the surface to the mesospause. UAS radiances were assimilated into NAVGEM using the new Community Radiative Transfer Model (CRTM) that accounts for Zeeman line splitting by geomagnetic fields. UAS radiance data from April 2010 to March 2011 are shown to be in good agreement with coincident temperature measurements from the Sounding of the Atmosphere Using Broadband Emission Radiometry (SABER) instrument that were used to simulate UAS brightness temperatures. Four NAVGEM experiments were performed during July 2010 that assimilated (i) no mesospheric observations, (ii) UAS data only, (iii) SABER and Microwave Limb Sounder (MLS) mesospheric temperatures only, and (iv) SABER, MLS, and UAS data. Zonal mean temperatures and observation − foreca...

Accounting for Correlated Observation Error in a Dual-Formulation 4D Variational Data Assimilation System

AbstractAppropriate specification of the error statistics for both observational data and short-term forecasts is necessary to produce an optimal analysis. Observation error stems from instrument error, forward model error, and error of representation. All sources of observation error, particularly error of representation, can lead to nonzero correlations. While correlated forecast error has been accounted for since the early days of atmospheric data assimilation, observation error has typically been treated as uncorrelated until relatively recently. Thinning, averaging, and/or inflation of the assigned observation error variance have been employed to compensate for unaccounted error correlations, especially for high-resolution satellite data.In this study, the benefits of accounting for nonzero vertical (interchannel) correlation for both the Advanced Technology Microwave Satellite (ATMS) and Infrared Atmospheric Sounding Interferometer (IASI) in the NRL Atmospheric Variational Data Assimilation System-A...

Diagnostics for Evaluating the Impact of Satellite Observations

The adjoints of the numerical weather prediction (NWP) model and data assimilation system may be used together to objectively determine the observation impact – or whether a given observation platform or observing system improves or degrades the subsequent NWP forecast.

High-Altitude (0-100 km) Global Atmospheric Reanalysis System: Description and Application to the 2014 Austral Winter of the Deep Propagating Gravity-Wave Experiment (DEEPWAVE)

AbstractA data assimilation system (DAS) is described for global atmospheric reanalysis from 0- to 100-km altitude. We apply it to the 2014 austral winter of the Deep Propagating Gravity Wave Exper...

Recent Applications in Representer-Based Variational Data Assimilation

Data assimilation with representer-based algorithms (also called “dual space” algorithms) are currently being used for weak-constraint four-dimensional variational data assimilation (W4D-Var) atmospheric prediction, distributed parameter estimation, and other hydrodynamic data assimilation problems. The iterative linear solvers at the core of these systems may display non-monotonic convergence in the norm defined by the primal objective function, and this behavior makes problematic the development of practical stopping criteria. One approach to this problem is described, namely an implementation of the inner solver using the generalized conjugate residual(GCR) algorithm. Additional elements of data assimilation systems are error model for the background, model forcings, and observations. An implementation of a posterior analysis method for diagnosing the error variances is described, and representative results from an atmospheric data assimilation systems are shown.

Information Quantification for Data Assimilation

In this paper we discuss the application of observability as a measurement of observation quality for data assimilation in numerical weather prediction (NWP ). Observability is a measure of well-posedness of a dynamical system and provides a flexible framework to address questions in data assimilation. We review the concept of observability for differential equations and high dimensional numerical models. We discuss the relationship of observability to observation impact . We conclude with a discussion of various applications of observability to data assimilation including optimal sensor placement and data thinning .