scholarly journals 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

2021 ◽  
Author(s):  
Philipp Franke ◽  
Anne Caroline Lange ◽  
Hendrik Elbern
Keyword(s):  
Particle Filter ◽  
Wind Shear ◽  
Volcanic Ash ◽  
Strong Wind ◽  
Mass Loading ◽  
Stochastic Integration ◽  
Minimization Method ◽  
Emission Fluxes ◽  
Weak Wind ◽  
Atmospheric Simulations

Abstract. 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.

scholarly journals A model sensitivity study of the impact of clouds on satellite detection and retrieval of volcanic ash

2015 ◽  
Vol 8 (5) ◽  
pp. 1935-1949 ◽  
Author(s):  
A. Kylling ◽  
N. Kristiansen ◽  
A. Stohl ◽  
R. Buras-Schnell ◽  
C. Emde ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Liquid Water ◽  
Volcanic Ash ◽  
Spectral Band ◽  
Sensitivity Study ◽  
Transfer Model ◽  
Mass Loading ◽  
Ice Clouds ◽  
Medium Range Weather Forecast ◽  
The Impact

Abstract. Volcanic ash is commonly observed by infrared detectors on board Earth-orbiting satellites. In the presence of ice and/or liquid-water clouds, the detected volcanic ash signature may be altered. In this paper the sensitivity of detection and retrieval of volcanic ash to the presence of ice and liquid-water clouds was quantified by simulating synthetic equivalents to satellite infrared images with a 3-D radiative transfer model. The sensitivity study was made for the two recent eruptions of Eyjafjallajökull (2010) and Grímsvötn (2011) using realistic water and ice clouds and volcanic ash clouds. The water and ice clouds were taken from European Centre for Medium-Range Weather Forecast (ECMWF) analysis data and the volcanic ash cloud fields from simulations by the Lagrangian particle dispersion model FLEXPART. The radiative transfer simulations were made both with and without ice and liquid-water clouds for the geometry and channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The synthetic SEVIRI images were used as input to standard reverse absorption ash detection and retrieval methods. Ice and liquid-water clouds were on average found to reduce the number of detected ash-affected pixels by 6–12%. However, the effect was highly variable and for individual scenes up to 40% of pixels with mass loading >0.2 g m−2 could not be detected due to the presence of water and ice clouds. For coincident pixels, i.e. pixels where ash was both present in the FLEXPART (hereafter referred to as "Flexpart") simulation and detected by the algorithm, the presence of clouds overall increased the retrieved mean mass loading for the Eyjafjallajökull (2010) eruption by about 13%, while for the Grímsvötn (2011) eruption ash-mass loadings the effect was a 4% decrease of the retrieved ash-mass loading. However, larger differences were seen between scenes (standard deviations of ±30 and ±20% for Eyjafjallajökull and Grímsvötn, respectively) and even larger ones within scenes. The impact of ice and liquid-water clouds on the detection and retrieval of volcanic ash, implies that to fully appreciate the location and amount of ash, hyperspectral and spectral band measurements by satellite instruments should be combined with ash dispersion modelling.

scholarly journals Modeling volcanic ash resuspension – application to the 14–18 October 2011 outbreak episode in central Patagonia, Argentina

2014 ◽  
Vol 14 (1) ◽  
pp. 119-133 ◽  
Author(s):  
A. Folch ◽  
L. Mingari ◽  
M. S. Osores ◽  
E. Collini
Keyword(s):  
Air Quality ◽  
Volcanic Ash ◽  
Suspended Particle ◽  
Dust Emission ◽  
Vegetation Coverage ◽  
Weather Research And Forecasting ◽  
Test Case ◽  
Arid Environments ◽  
Strong Wind ◽  
Near Future

Abstract. Volcanic fallout deposits from the June 2011 Cordón Caulle eruption on central Patagonia were remobilized in several occasions months after their emplacement. In particular, during 14–18 October 2011, an intense outbreak episode generated widespread volcanic clouds that were dispersed across Argentina, causing multiple impacts in the environment, affecting the air quality and disrupting airports. Fine ash particles in volcanic fallout deposits can be resuspended under favorable meteorological conditions, particularly during strong wind episodes in arid environments with low soil moisture and poor vegetation coverage. As opposed to eruption-formed ash clouds, modeling of resuspension-formed ash clouds has received little attention. In consequence, there are no emission schemes specially developed and calibrated for resuspended volcanic ash, and few operational products exists to model and forecast the formation and dispersal of resuspension ash clouds. Here we implement three dust emission schemes of increasing complexity in the FALL3D tephra dispersal model and use the 14–18 October 2011 outbreak episode as a model test case. We calibrate the emission schemes and validate the results of the coupled WRF–ARW (Weather Research and Forecasting – Advanced Research WRF)/FALL3D modeling system using satellite imagery and measurements of visibility (a quantity related to total suspended particle concentration at the surface) and particulate matter (PM10) concentration at several meteorological and air quality stations located at Argentina and Uruguay. Our final goal is to test the capability of the modeling system to become, in the near future, an operational forecast product for volcanic ash resuspension events.

The Probability Distribution of Land Surface Wind Speeds

2011 ◽  
Vol 24 (15) ◽  
pp. 3892-3909 ◽  
Author(s):  
Adam H. Monahan ◽  
Yanping He ◽  
Norman McFarlane ◽  
Aiguo Dai
Keyword(s):  
Boundary Layer ◽  
Weibull Distribution ◽  
Land Surface ◽  
Wind Shear ◽  
Surface Wind ◽  
Nocturnal Boundary Layer ◽  
Global Network ◽  
Strong Wind ◽  
Wind Speeds ◽  
Tropospheric Wind

Abstract The probability density function (pdf) of land surface wind speeds is characterized using a global network of observations. Daytime surface wind speeds are shown to be broadly consistent with the Weibull distribution, while nighttime surface wind speeds are generally more positively skewed than the corresponding Weibull distribution (particularly in summer). In the midlatitudes, these strongly positive skewnesses are shown to be generally associated with conditions of strong surface stability and weak lower-tropospheric wind shear. Long-term tower observations from Cabauw, the Netherlands, and Los Alamos, New Mexico, demonstrate that lower-tropospheric wind speeds become more positively skewed than the corresponding Weibull distribution only in the shallow (~50 m) nocturnal boundary layer. This skewness is associated with two populations of nighttime winds: (i) strongly stably stratified with strong wind shear and (ii) weakly stably or unstably stratified with weak wind shear. Using an idealized two-layer model of the boundary layer momentum budget, it is shown that the observed variability of the daytime and nighttime surface wind speeds can be accounted for through a stochastic representation of intermittent turbulent mixing at the nocturnal boundary layer inversion.

scholarly journals A Case Study of Low-level Wind Shear in Xining Airport

2019 ◽  
Vol 131 ◽  
pp. 01037
Author(s):  
Ting Xu ◽  
Wei Niu
Keyword(s):  
High Pressure ◽  
Wind Shear ◽  
Strong Wind ◽  
Low Level ◽  
Weather Pattern ◽  
Wind Distribution

Low-level wind shear is a hazardous phenomenon for aircraft, a low-level wind shear case of Xining airport selected from pilot reports is analysed in this paper. Using ERA-Interim data, the weather pattern and characteristics of wind distribution are discussed. The result indicates cold high pressure accompanied by strong wind and terrain is the main reason of this low-level wind shear case.

scholarly journals A Velocity Dealiasing Scheme Based on Minimization of Velocity Differences between Regions

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yue Yuan ◽  
Ping Wang ◽  
Di Wang ◽  
Junzhi Shi
Keyword(s):  
Radial Velocity ◽  
Wind Shear ◽  
Doppler Radar ◽  
Heavy Precipitation ◽  
Probability Of Detection ◽  
Strong Wind ◽  
Velocity Data ◽  
Step Velocity ◽  
Noise Data ◽  
Radial Velocity Data

The velocity dealiasing is an essential work of automatic weather phenomenon identification, nowcasting, and disaster monitoring based on radial velocity data. The noise data, strong wind shear, and isolated echo region in the Doppler radar radial velocity data severely interfere with the velocity dealiasing algorithm. This paper proposes a two-step velocity dealiasing algorithm based on the minimization of velocity differences between regions to solve this problem. The first step is to correct aliased velocities by minimizing the sum of gradients in every region to eliminate abnormal velocity gradients between points. The interference of noise data and strong wind shear can be reduced by minimizing the whole gradients in a region. The second step is to dealiase velocities by the velocity differences between different isolated regions. The velocity of an unknown isolated region is determined by the velocities of all known regions. This step improves the dealiasing results of isolated regions. In this paper, 604 volume scan samples, including typhoons, squall lines, and heavy precipitation, were used to test the algorithm. The statistical results and analysis show that the proposed algorithm can dealiase the velocity field with a high probability of detection and a low false alarm rate.

A DOCUMENTED EXAMPLE OF STRONG WIND-SHEAR

Weather ◽  
1982 ◽  
Vol 37 (1) ◽  
pp. 19-22 ◽  
Author(s):  
D. A. Membery
Keyword(s):  
Wind Shear ◽  
Strong Wind

Aircraft Behaviour in a Vertical Gradient of Wind Velocity

1963 ◽  
Vol 14 (3) ◽  
pp. 265-278 ◽  
Author(s):  
J. K. Zbrożek
Keyword(s):  
Theoretical Analysis ◽  
Wind Velocity ◽  
Wind Shear ◽  
Wind Profile ◽  
Numerical Study ◽  
Vertical Gradient ◽  
Jet Stream ◽  
Strong Wind ◽  
Aircraft Motion ◽  
The Stability

SummaryThe stability of the phugoid motion of an aircraft in the presence of wind shear is investigated. The effect of the wind shear on the phugoid frequency increases with increasing aircraft speed and can be stabilising or destabilising, depending on the aircraft orientation relative to the wind shear. The destabilising effect of wind shear is alleviated by the stabilising effect of the density gradient of the atmosphere. At the most critical combination of speed and altitude a strong wind shear may lead to divergence, with a time to double amplitude of the order of 10-15 seconds.A numerical study of the aircraft motion with controls fixed when descending through a wind profile similar to that in a jet stream indicates that the increase in the aircraft indicated speed can be of the same magnitude as, or larger than, the maximum wind velocity increment in the jet stream core. However, as the time to reach the excess speed is of the order of one minute, the actual behaviour of the aircraft strongly depends on the pilot's action and thus is not fully predictable by theoretical analysis.

scholarly journals Should we use a simple or complex model for moisture recycling and atmospheric moisture tracking?

2013 ◽  
Vol 17 (12) ◽  
pp. 4869-4884 ◽  
Author(s):  
R. J. van der Ent ◽  
O. A. Tuinenburg ◽  
H.-R. Knoche ◽  
H. Kunstmann ◽  
H. H. G. Savenije
Keyword(s):  
West Africa ◽  
Wind Shear ◽  
Climate Model ◽  
Research Question ◽  
Strong Wind ◽  
Atmospheric Moisture ◽  
A Posteriori ◽  
Layer Model ◽  
Moisture Recycling ◽  
Release Height

Abstract. This paper compares state-of-the-art atmospheric moisture tracking models. Such models are typically used to study the water component of coupled land and atmosphere models, in particular quantifying moisture recycling and the source-sink relations between evaporation and precipitation. There are several atmospheric moisture tracking methods in use. However, depending on the level of aggregation, the assumptions made and the level of detail, the performance of these methods may differ substantially. In this paper, we compare three methods. The RCM-tag method uses highly accurate 3-D water tracking (including phase transitions) directly within a regional climate model (online), while the other two methods (WAM and 3D-T) use a posteriori (offline) water vapour tracking. The original version of WAM is a single-layer model, while 3D-T is a multi-layer model, but both make use the "well-mixed" assumption for evaporation and precipitation. The a posteriori models are faster and more flexible, but less accurate than online moisture tracking with RCM-tag. In order to evaluate the accuracy of the a posteriori models, we tagged evaporated water from Lake Volta in West Africa and traced it to where it precipitates. It is found that the strong wind shear in West Africa is the main cause of errors in the a posteriori models. The number of vertical layers and the initial release height of tagged water in the model are found to have the most significant influences on the results. With this knowledge small improvements have been made to the a posteriori models. It appeared that expanding WAM to a 2-layer model, or a lower release height in 3D-T, led to significantly better results. Finally, we introduced a simple metric to assess wind shear globally and give recommendations about when to use which model. The "best" method, however, very much depends on the research question, the spatial extent under investigation, as well as the available computational power.

scholarly journals Data Assimilation of Volcanic Aerosols using FALL3D+PDAF

2021 ◽  
Author(s):  
Leonardo Mingari ◽  
Arnau Folch ◽  
Andrew T. Prata ◽  
Federica Pardini ◽  
Giovanni Macedonio ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Volcanic Ash ◽  
Volcanic Eruptions ◽  
Column Height ◽  
Model Parameters ◽  
Eruption Column ◽  
Mass Loading ◽  
Multiple Model ◽  
Volcanic Aerosols ◽  
Forecast Quality

Abstract. Modelling atmospheric dispersal of volcanic ash and aerosols is becoming increasingly valuable for assessing the potential impacts of explosive volcanic eruptions on infrastructures, air quality, and aviation. Management of volcanic risk and reduction of aviation impacts can strongly benefit from quantitative forecasting of volcanic ash. However, an accurate prediction of volcanic aerosol concentrations using numerical modelling relies on proper estimations of multiple model parameters which are prone to errors. Uncertainties in key parameters such as eruption column height, physical properties of particles or meteorological fields, represent a major source of error affecting the forecast quality. The availability of near-real-time geostationary satellite observations with high spatial and temporal resolutions provides the opportunity to improve forecasts in an operational context by incorporating observations into numerical models. Specifically, ensemble-based filters aim at converting a prior ensemble of system states into an analysis ensemble by assimilating a set of noisy observations. Previous studies dealing with volcanic ash transport have demonstrated that a significant improvement of forecast skill can be achieved by this approach. In this work, we present a new implementation of an ensemble-based Data Assimilation (DA) method coupling the FALL3D dispersal model and the Parallel Data Assimilation Framework (PDAF). The FALL3D+PDAF system runs in parallel, supports online-coupled DA and can be efficiently integrated into operational workflows by exploiting high-performance computing (HPC) resources. Two numerical experiments are considered: (i) a twin experiment using an incomplete dataset of synthetic observations of volcanic ash and, (ii) an experiment based on the 2019 Raikoke eruption using real observations of SO2 mass loading. An ensemble-based Kalman filtering technique based on the Local Ensemble Transform Kalman Filter (LETKF) is used to assimilate satellite-retrieved data of column mass loading. We show that this procedure may lead to nonphysical solutions and, consequently, conclude that LETKF is not the best approach for the assimilation of volcanic aerosols. However, we find that a truncated state constructed from the LETKF solution approaches the real solution after a few assimilation cycles, yielding a dramatic improvement of forecast quality when compared to simulations without assimilation.

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