MoSST DAS: The First Working Geomagnetic Data Assimilation System

The Earth possesses an internal magnetic field (geomagnetic field) generated by convection in the outer core (geodynamo). Previous efforts have been focused along two distinct paths: (1) numerical geodynamo modeling to understand the origin of the geomagnetic field, and the mechanisms of geomagnetic secular variations (SV); and (2) geomagnetic field modeling to map the spatial/temporal variations of the field from geomagnetic data, and to derive core properties, e.g. inversion of core flow near the core-mantle boundary (CMB). Geomagnetic data assimilation is a new approach emerged over the past 5 years: surface observations are assimilated with geodynamo models for better understanding of the core dynamical state, and accurately prediction of SV. In collaboration with several geomagnetic research groups, we have developed the first working geomagnetic data assimilation system, Modular, Scalable, Self-consistent, and Three-dimensional (MoSST) DAS, that includes the MoSST numerical dynamo model; 7000 years of geomagnetic field maps from several field models utilizing satellite and ground observatory data, historical magnetic records and archeo/paleo magnetic data; and an ensemble based optimal interpolation (01) assimilation algorithm. With this system, we have demonstrated clearly that the assimilated core dynamical state is substantially different from those of pure geodynamo simulations. Ensemble assimilation runs also show the convergence of the assimilated solutions inside the core, suggesting that the simulation state is pulled closer to the truth via data assimilation. The forecasts from this system are also very accurate: the 5-year forecast of the geomagnetic field agrees very well with the observations; and the 5-year secular variation forecast is more accurate than the IGRF SV forecast models in the past. Using geomagnetic records up to 2009, we have made an SV forecast for the period from 2010-2015, and is a candidate SV model for IGRF-11

Dynamic Responses of the Earth's Outer Core to Assimilation of Observed Geomagnetic Secular Variation

Assimilation of surface geomagnetic observations and geodynamo models has advanced very quickly in recent years. However, compared to advanced data assimilation systems in meteorology, geomagnetic data assimilation (GDAS) is still in an early stage. Among many challenges ranging from data to models is the disparity between the short observation records and the long time scales of the core dynamics. To better utilize available observational information, we have made an effort in this study to directly assimilate the Gauss coefficients of both the core field and its secular variation (SV) obtained via global geomagnetic field modeling, aiming at understanding the dynamical responses of the core fluid to these additional observational constraints. Our studies show that the SV assimilation helps significantly to shorten the dynamo model spin-up process. The flow beneath the core-mantle boundary (CMB) responds significantly to the observed field and its SV. The strongest responses occur in the relatively small scale flow (of the degrees L is approx. 30 in spherical harmonic expansions). This part of the flow includes the axisymmetric toroidal flow (of order m = 0) and non-axisymmetric poloidal flow with m (is) greater than 5. These responses can be used to better understand the core flow and, in particular, to improve accuracies of predicting geomagnetic variability in future

Effect of Cross-Correlation on Geomagnetic Forecast Accuracies

Surface geomagnetic observation can determine up to degree L = 14 time-varying spherical harmonic coefficients of the poloidal magnetic field. Assimilation of these coefficients to numerical dynamo simulation could help us understand better the dynamical processes in the Earth's outer core, and to provide more accurate forecast of geomagnetic secular variations (SV). In our previous assimilation studies, only the poloidal magnetic field in the core is corrected by the observations in the analysis. Unobservable core state variables (the toroidal magnetic field and the core velocity field) are corrected via the dynamical equations of the geodynamo. Our assimilation experiments show that the assimilated core state converges near the CMB, implying that the dynamo state is strongly constrained by surface geomagnetic observations, and is pulled closer to the truth by the data. We are now carrying out an ensemble of assimilation runs with 1000 years of geomagnetic and archeo/paleo magnetic record. In these runs the cross correlation between the toroidal and the poloidal magnetic fields is incorporated into the analysis. This correlation is derived from the physical boundary conditions of the toroidal field at the core-mantle boundary (CMB). The assimilation results are then compared with those of the ensemble runs without the cross-correlation, aiming at understanding two fundamental issues: the effect of the crosscorrelation on (1) the convergence of the core state, and (2) the SV prediction accuracies. The constrained dynamo solutions will provide valuable insights on interpreting the observed SV, e.g. the near-equator magnetic flux patches, the core-mantle interactions, and possibly other geodynamic observables

Chemical Source Inversion using Assimilated Constituent Observations in an Idealized Two-dimensional System

We present a source inversion technique for chemical constituents that uses assimilated constituent observations rather than directly using the observations. The method is tested with a simple model problem, which is a two-dimensional Fourier-Galerkin transport model combined with a Kalman filter for data assimilation. Inversion is carried out using a Green's function method and observations are simulated from a true state with added Gaussian noise. The forecast state uses the same spectral spectral model, but differs by an unbiased Gaussian model error, and emissions models with constant errors. The numerical experiments employ both simulated in situ and satellite observation networks. Source inversion was carried out by either direct use of synthetically generated observations with added noise, or by first assimilating the observations and using the analyses to extract observations. We have conducted 20 identical twin experiments for each set of source and observation configurations, and find that in the limiting cases of a very few localized observations, or an extremely large observation network there is little advantage to carrying out assimilation first. However, in intermediate observation densities, there decreases in source inversion error standard deviation using the Kalman filter algorithm followed by Green's function inversion by 50% to 95%

Geomagnetic Secular Variation Prediction with Thermal Heterogeneous Boundary Conditions

It has long been conjectured that thermal heterogeneity at the core-mantle boundary (CMB) affects the geodynamo substantially. The observed two pairs of steady and strong magnetic flux lobes near the Polar Regions and the low secular variation in the Pacific over the past 400 years (and perhaps longer) are likely the consequences of this CMB thermal heterogeneity. There are several studies on the impact of the thermal heterogeneity with numerical geodynamo simulations. However, direct correlation between the numerical results and the observations is found very difficult, except qualitative comparisons of certain features in the radial component of the magnetic field at the CMB. This makes it difficult to assess accurately the impact of thermal heterogeneity on the geodynamo and the geomagnetic secular variation. We revisit this problem with our MoSST_DAS system in which geomagnetic data are assimilated with our geodynamo model to predict geomagnetic secular variations. In this study, we implement a heterogeneous heat flux across the CMB that is chosen based on the seismic tomography of the lowermost mantle. The amplitude of the heat flux (relative to the mean heat flux across the CMB) varies in the simulation. With these assimilation studies, we will examine the influences of the heterogeneity on the forecast accuracies, e.g. the accuracies as functions of the heterogeneity amplitude. With these, we could be able to assess the model errors to the true core state, and thus the thermal heterogeneity in geodynamo modeling

Assimilation of SCIAMACHY Total Column CO Observations: Regional Analysis of Data Impact

Carbon monoxide (CO) total column observations from the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartography (SCIAMACHY) on board ENVISAT are assimilated into the Global Modeling and Assimilation Office (GMAO) constituent assimilation system for the period July 18-October 31, 2004. This is the first assimilation of CO observations from a near infrared sounder. The impact of the assimilation on CO distribution is evaluated using independent Measurement of Ozone and Water vapor by Airbus In-service Aircraft (MOZAIC) in-situ CO profiles. Assimilation of satellite data improves agreement with MOZAIC CO globally, especially in the upper troposphere

International Geomagnetic Reference Field: the 12th generation

The 12th generation of the International Geomagnetic Reference Field (IGRF) was adopted in December 2014 by the Working Group V-MOD appointed by the International Association of Geomagnetism and Aeronomy (IAGA). It updates the previous IGRF generation with a definitive main field model for epoch 2010.0, a main field model for epoch 2015.0, and a linear annual predictive secular variation model for 2015.0-2020.0. Here, we present the equations defining the IGRF model, provide the spherical harmonic coefficients, and provide maps of the magnetic declination, inclination, and total intensity for epoch 2015.0 and their predicted rates of change for 2015.0-2020.0. We also update the magnetic pole positions and discuss briefly the latest changes and possible future trends of the Earth’s magnetic fiel

The Effect of Glaciers on Streamflow Variations

The effect of temperate glaciers on runoff variations is examined for the North Cascade Mountains of Washington State. The principal influences of glaciers on streamflow are often unexpected contributions to streamflow volume, a delay of the maximum seasonal flow, and a decrease in annual and monthly variation of runoff. The delay of maximum flow is caused by temporary englacial storage of spring meltwater and by peak meltwater production occurring in midsummer. The englacial storage, for one case, is 54% of the potential May runoff. An algorithm is presented that calculates the coefficient of variation of runoff for any arbitrary glacier cover. The results suggest that a minimum in year-to-year vanatlon occurs for basms about 36% glacierized. On a month-to-month basis, maximum variation occurs in July and August for basins with less than 10% glacier cover but is a minimum for basins with glacier covers greater than 30%

Impact of Archeomagnetic Field Model Data on Modern Era Geomagnetic Forecasts

A series of geomagnetic data assimilation experiments have been carried out to demonstrate the impact of assimilating archeomagnetic data via the CALS3k.4 geomagnetic field model from the period between 10 and 1590 CE. The assimilation continues with the gufm1 model from 1590 to 1990 and CM4 model from 1990 to 2000 as observations, and comparisons between these models and the geomagnetic forecasts are used to determine an optimal maximum degree for the archeomagnetic observations, and to independently estimate errors for these observations. These are compared with an assimilation experiment that uses the uncertainties provided with CALS3k.4. Optimal 20 year forecasts in 1990 are found when the Gauss coefficients up to degree 3 are assimilated. In addition we demonstrate how a forecast and observation bias correction scheme could be used to reduce bias in modern era forecasts. Initial experiments show that this approach can reduce modern era forecast biases by as much as 50 percent

Constraining Numerical Geodynamo Modeling with Surface Observations

Numerical dynamo solutions have traditionally been generated entirely by a set of self-consistent differential equations that govern the spatial-temporal variation of the magnetic field, velocity field and other fields related to dynamo processes. In particular, those solutions are obtained with parameters very different from those appropriate for the Earth s core. Geophysical application of the numerical results therefore depends on correct understanding of the differences (errors) between the model outputs and the true states (truth) in the outer core. Part of the truth can be observed at the surface in the form of poloidal magnetic field. To understand these differences, or errors, we generate new initial model state (analysis) by assimilating sequentially the model outputs with the surface geomagnetic observations using an optimal interpolation scheme. The time evolution of the core state is then controlled by our MoSST core dynamics model. The final outputs (forecasts) are then compared with the surface observations as a means to test the success of the assimilation. We use the surface geomagnetic data back to year 1900 for our studies, with 5-year forecast and 20-year analysis periods. We intend to use the result; to understand time variation of the errors with the assimilation sequences, and the impact of the assimilation on other unobservable quantities, such as the toroidal field and the fluid velocity in the core