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Tomoko Matsuo

Publications and source records attributed to Tomoko Matsuo.

Exploring Earth's Interface with Space: The Scientific Case for a Satellite Mission to the Lower Thermosphere-Ionosphere Transition Region

The ESA-NASA Lower Thermosphere-Ionosphere Science (ENLoTIS) Working Group was formed in May 2022 to cooperatively explore future lower thermosphere-ionosphere (LTI) satellite mission concepts, targeting very low altitudes (100-200 km) with in situ sampling of relevant geophysical parameters associated with the neutral atmosphere, the ionosphere’s plasma, electromagnetic fields, and energetic particles, which, together with modeling, would enable significant advancements in the understanding of neutral-ion interactions and other related science and space weather topics in this critical region of Geospace. The LTI region has been identified as one of considerable interest to both NASA and ESA. Most recently, the Daedalus mission study was carried out under the remit of ESA’s Earth Observation Programmes (EOP) Directorate competitive Earth Explorer 10 pre-feasibility (Phase 0) activities. Furthermore, many NASA studies have also focused on the LTI region, including both directed missions with dipping spacecraft, such as the initial TIMED dual-satellites and the GEC constellation, as well as numerous highly-rated Explorer proposals targeting the LTI. Although the Daedalus mission was not selected, the ESA Advisory Committee on Earth Observation (ACEO) ranked it highly on scientific grounds and encouraged further study activities to mature the concept, exploring potential international collaboration. Subsequent bilateral discussions with NASA’s Science Mission Directorate (SMD) noted that such a concept was in alignment with the 2020 SMD science plan – Science 2020-2024: A Vision for Scientific Excellence – along with other complimentary activities within the NASA Heliophysics Division. Building on NASA’s and ESA’s long history of very successful collaborations, this mutual interest in LTI science led to the establishment of a new inter-agency and cross-discipline science connection, linking the ESA EOP Climate Action, Sustainability and Science Department and the NASA Heliophysics Division. Initial exploratory discussions led to the formation of the ENLoTIS Working Group, which was directed to explore the science case behind a potential joint LTI mission. Members of the ENLoTIS Working Group are listed below, consisting of 7 scientists from ESA Member and Cooperating States and 7 scientists from the United States. The working group held 3 “in person” meetings over the course of 18 months, interspersed with regular virtual meetings on a more frequent basis. This report constitutes their chief findings and recommendations.

thermosphere

Continuum Covariance Propagation for Understanding Variance Loss in Advective Systems

Motivated by the spurious variance loss encountered during covariance propagation in atmospheric and other large-scale data assimilation systems, we consider the problem for state dynamics governed by the continuity and related hyperbolic partial differential equations. This loss of variance has been attributed to reduced-rank representations of the covariance matrix, as in ensemble methods for example, or else to the use of dissipative numerical methods. Through a combination of analytical work and numerical experiments, we demonstrate that significant variance loss, as well as gain, typically occurs during covariance propagation, even at full rank. The cause of this unusual behavior is a discontinuous change in the continuum covariance dynamics as correlation lengths become small, for instance in the vicinity of sharp gradients in the velocity field. This discontinuity in the covariance dynamics arises from hyperbolicity: the diagonal of the kernel of the covariance operator is a characteristic surface for advective dynamics. Our numerical experiments demonstrate that standard numerical methods for evolving the state are not adequate for propagating the covariance, because16they do not capture the discontinuity in the continuum covariance dynamics as correlations lengths tend to zero. Our analytical and numerical results show that this leads to significant, spurious variance loss in certain regions, and gain in others. The results suggest that developing local covariance propagation methods designed specifically to capture covariance evolution near the diagonal may prove a useful alternative to current methods of covariance propagation.

covariance propagation

Day-to-Day Variability of Ionosphere Electron Density During Solar Minimum Derived From FORMOSAT-7/COSMIC-2 Measurements

This study examines the day-to-day variability of low-latitude ionosphere using global ionospheric specification (GIS) electron density profiles derived from FORMOSAT-7/COSMIC-2 radio occultation measurements during a deep solar minimum period of August 2019 to July 2020. The measurements reveal significant daily variations over dayside low latitudes, yielding about 10-20% standard deviation in equinoxes, 20-30% in solstices, reaching 40-50% in winter. The nighttime deviations could be 30-60%, being largest in solstices. Day-to-day variations are also observed in the longitudinal wave-4 structures. The period mostly remained geomagnetically quiet except for some moderate disturbances on a few days. Tidal decomposition of the GIS electron density shows that in-situ forced migrating diurnal (DW1) terdiurnal (TW3) oscillations and the background zonal mean yield only ~25% of the daily variations despite accounting for almost 75-90% of the observed electron density. Thus, forcing from lower atmosphere dominates the contribution (~75%) to the observed daily variations. Only about one third of this lower atmospheric forcing comes from the migrating semidiurnal SW2 and the usually investigated non-migrating diurnal eastward DE2, DE3, stationary planetary wave SPW3, SPW4, and semidiurnal eastward SE1, and SE2 components. The residual tides other than those mentioned above, including secondary waves through non-linear interactions and other planetary waves, thus significantly influence the day-to-day variations in electron density and modify the longitudinal wave structures.

day-to-day variability

Continuum covariance propagation for understanding variance loss in advective systems

At the heart of modern data assimilation schemes is covariance propagation.Loss of variance experienced in large-scale applications such as numerical weather prediction is problematic, and the development of auxiliary methods to mitigate this issue is an active research area. The focus of this work is to understand the root causes of variance loss and show that for advective dynamics, the covariance propagation by itself typically causes significant, spurious loss of variance, even at full rank. To demonstrate this, we first study continuum covariance propagation by analyzing the covariance evolution equation for advective dynamics. The behavior of this evolution equation changes abruptly as the correlation length tends to zero, for example in the vicinity of sharp gradients in the advection field. This happens because the diagonal of the kernel of the covariance operator is a characteristic surface for advective dynamics. Our numerical experiments then confirm that the variance lost during numerical propagation greatly exceeds that due to numerical dissipation alone. The variance loss is driven primarily by inaccurate variance propagation resulting from standard, full-rank covariance propagation schemes, which have difficulty capturing the abrupt change in dynamics as the correlation length tends to zero. These results suggest that developing local covariance propagation methods may prove useful in ameliorating the variance loss observed in data assimilation schemes

Covariance Propagation

Continuum Covariance Propagation for Understanding Variance Loss in Advective Systems

We demonstrate for state dynamics governed by the continuity equation and related hyperbolic partial differential equations that significant, spurious variance loss occurs during covariance propagation by traditional methods used in data assimilation, even at full rank. This inaccurate variance evolution is caused not by numerical dissipation, but rather by a discontinuous change in the continuum covariance dynamics as correlation lengths tend to zero.

Shay Gilpin

A Generalized, Compactly-Supported Correlation Function for Data Assimilation Applications

Correlation functions play an essential role in modern data assimilation, where they are used to model covariances given a set of tunable parameters or applied as tapering functions to localize covariances in ensemble-based schemes. One of the most widely-used correlation functions in data assimilation is the Gaspari and Cohn (1999) piecewise-rational, compactly-supported parametric correlation function (hereafter referred to as GC99). The GC99 correlation function is useful due to its tunable cut-off parameter c and Gaussian-like shape achieved when the parameter a is set to one-half. These properties are attractive for tapering functions in data assimilation applications. However, the GC99 correlation function is homogeneous over Euclidean 3-space and isotropic when restricted to the sphere, properties that may be less than ideal for some geophysical applications. GC99 is also compactly-supported on a sphere of fixed radius, which requires tuning of the cut-off parameter c that can depend on the specific application. This work presents a generalization of the GC99 correlation function that allows the cut-off parameter c and shape parameter a to vary over space to gain more flexibility in shape while maintaining its compact support property. The function, which we call the Generalized Gaspari Cohn (GenGC) correlation function, introduces inhomogeneity in Euclidean 3-space and anisotropy when restricted to the sphere by allowing both parameters c and a to vary, as functions, over the spatial domain. The GC99 correlation function is a special case of GenGC where the functions c and a are held constant, as fixed parameters rather than functions. The GenGC correlation function also generalizes the follow-on to the work of Gaspari and Cohn (1999) presented in Gaspari et al. (2006), which allowed a to vary while keeping c fixed. We illustrate through simple one- and two-dimensional examples the variety of inhomogeneous and anisotropic correlation functions GenGC can produce by varying c and a over space, and suggest applications where they may be useful in data assimilation, such as covariance modeling or localization. In particular, we describe how the GenGC correlation function can be used to construct covariances using correlation length and variance fields derived from dynamics. For example, the correlation length field for advective dynamics is governed by a partial differential equation (PDE) in N spatial dimensions, where N is the number of space dimensions of the state. Correlation length fields can be determined from this PDE and used with GenGC to construct the corresponding correlations. We can then approximate the full covariance by rescaling by the variance, which also satisfies a PDE in N spatial dimensions for advective dynamics. Thus we can approximate the full covariance without solving the covariance PDE, which is in 2N spatial dimensions, by solving just two PDEs each in only N spatial dimensions. This approach to evolving the correlation length and variance fields, then reconstructing the correlations using GenGC, is suggested as an alternative to current methods of covariance modeling in data assimilation algorithms.

GC99