Particle filter based volcanic ash emission inversion applied to a hypothetical sub-Plinian Eyjafjallajökull eruption using the chemical component of the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem) version 1.0

A particle filter based inversion system to derive time- and altitude-resolved volcanic ash emission fluxes along with its uncertainty is presented. For the underlying observation information only vertically integrated ash load data as provided by retrievals from nadir looking imagers mounted on geostationary satellites is assimilated. We aim to estimate the temporally varying emission profile with error margins, along with evidence of its dependencies on wind driven transport patterns within variable observation intervals. Thus, a variety of observation types, although not directly related to volcanic ash, can be utilized to constrain the probabilistic volcanic ash estimate. The system validation addresses the special challenge of ash cloud height analyses in case of observations restricted to bulk column mass loading information, mimicking the typical case of geostationary satellite data. The underlying method rests on a linear-combination of height-time emission finite elements of arbitrary resolution, each of which is assigned to a model run subject to ensemble-based space-time data assimilation. Employing a modular concept, this setup builds the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem) that comprises a particle smoother in combination with a discrete-grid ensemble extension of the Nelder-Mead minimization method. The ensemble version of the EURopean Air pollution Dispersion – Inverse Model (EURAD-IM) is integrated into ESIAS-chem but can be replaced by other models. The performance of ESIAS-chem is tested by identical twin experiments. The application of the inversion system to two notional sub-Plinian eruptions of the Eyjafjallajökull with strong ash emission changes with time and injection heights demonstrate the ability of ESIAS-chem to retrieve the volcanic ash emission fluxes from the assimilation of column mass loading data only. However, the analysed emission profiles strongly differ in their levels of accuracy depending of the strength of wind shear conditions. Under strong wind shear conditions at the volcano the temporal and vertical varying volcanic emissions are analyzed up to an error of only 10 % for the estimated emission fluxes. For weak wind shear conditions, however, analysis errors are larger and ESIAS-chem is less able to determine the ash emission flux variations. This situation, however, can be remedied by extending the assimilation window. In the performed test cases, the ensemble predicts the location of high volcanic ash column mass loading in the atmosphere with a very high probability of > 95 %. Additionally, the ensemble is able to provide a vertically resolved probability map of high volcanic ash concentrations to a high accuracy for both, high and weak wind shear conditions.

Analysis of Different Gray Zone Treatments in WRF-LES Real Case Simulations

When conducting meso-micro scale coupled atmospheric simulations, it is crucial to ensure an adequate treatment of gray zone or terra incognita resolutions in which a large portion of the kinetic energy is naturally produced by the momentum balance equations in the model, while the remaining part still needs to be parameterized. In this work, we conduct three multi-day, real case, full-physics atmospheric simulations that are fully coupled from the meso to the micro scale and in which the only difference is the treatment of boundary layer physics at the gray zone domain. One simulation uses a well-established parameterization, another uses its scale-aware version previously modified to accommodate gray zone resolutions, and a final one uses no parameterization at all and assumes that the gray zone domain can be run in large-eddy simulation (LES) mode. The simulated fields are cross-compared, and further compared to measurements collected during the Prince Edward Island Wind Energy Experiment. Use of LES in the gray zone domain influences the flow fields in a manner that is robust to temporal averaging. The best predictions of vertical wind shear were found for the simulations in which the gray zone is parameterized, and the inclusion of a micro scale nest run in LES mode within the gray zone domains increased the model errors by producing overly homogeneous flow fields. The parameterized simulations also produced better agreement in terms of kinetic energy spectra at the two innermost simulation domains. In the gray zone domain, the energy decays as f−3 throughout most of the spectral range considered. In the micro scale domain, the same is only seen in the low-frequency end of the gray zone spectral range. In the high-frequency end, the energy decay follows a f−1 slope. Outside the gray zone spectral range, the micro scale simulated spectra follow the expected f−5/3 slope and produce good agreement with measurements.