scholarly journals Flex_extract v7.1.2 – a software package to retrieve and prepare ECMWF data for use in FLEXPART

2020 ◽  
Vol 13 (11) ◽  
pp. 5277-5310
Author(s):  
Anne Tipka ◽  
Leopold Haimberger ◽  
Petra Seibert
Keyword(s):  
Software Package ◽  
Dispersion Model ◽  
Meteorological Data ◽  
Particle Dispersion ◽  
Data Sets ◽  
Weather Forecasts ◽  
Online Documentation ◽  
Open Source Software Package ◽  
The Right ◽  
Selection Of

Abstract. Flex_extract is an open-source software package to efficiently retrieve and prepare meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF) as input for the widely used Lagrangian particle dispersion model FLEXPART and the related trajectory model FLEXTRA. ECMWF provides a variety of data sets which differ in a number of parameters (available fields, spatial and temporal resolution, forecast start times, level types etc.). Therefore, the selection of the right data for a specific application and the settings needed to obtain them are not trivial. Consequently, the data sets which can be retrieved through flex_extract by both member-state users and public users as well as their properties are explained. Flex_extract 7.1.2 is a substantially revised version with completely restructured code, mainly written in Python 3, which is introduced with all its input and output files and an explanation of the four application modes. Software dependencies and the methods for calculating the native vertical velocity η˙, the handling of flux data and the preparation of the final FLEXPART input files are documented. Considerations for applications give guidance with respect to the selection of data sets, caveats related to the land–sea mask and orography, etc. Formal software quality-assurance methods have been applied to flex_extract. A set of unit and regression tests as well as code metric data are also supplied. A short description of the installation and usage of flex_extract is provided in the Appendix. The paper points also to an online documentation which will be kept up to date with respect to future versions.

scholarly journals Flex_extract v7.1 – A software to retrieve and prepare ECMWF data for use in FLEXPART

2020 ◽  
Author(s):  
Anne Philipp ◽  
Leopold Haimberger ◽  
Petra Seibert
Keyword(s):  
Dispersion Model ◽  
Meteorological Data ◽  
Particle Dispersion ◽  
Data Sets ◽  
Weather Forecasts ◽  
Medium Range ◽  
Open Source Software Package ◽  
The Right ◽  
Regression Tests ◽  
Selection Of

Abstract. Flex_extract is an open-source software package to efficiently retrieve and prepare meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF) as input for the widely-used Lagrangian particle dispersion model FLEXPART and the related trajectory model FLEXTRA. ECMWF provides a variety of data sets which differ in a number of parameters (available fields, spatial and temporal resolution, forecast start times, level types etc.). Therefore, the selection of the right data for a specific application and the settings needed to obtain them are not trivial. Therefore, the data sets which can be retrieved through flex_extract by both authorised member state users and public users and their properties are explained. Flex_extract 7.1 is a substantially revised version with completely restructured software, mainly written in Python3, which is introduced with all input and output files and for the four different application modes. Software dependencies and the methods for calculating the native vertical velocity η̇, the handling of flux data and the preparation of the final FLEXPART input files are documented. Considerations for applications give guidance with respect to the selection of data sets, caveats related to the land-sea mask and orography, etc. Formal software quality assurance methods have been applied to flex_extract. It comes with a set of unit and regression tests as well as code metric data. A short description of the installation and usage of flex_extract as well as information about available detailed documentation is also provided.

Operational evaluation of volcanic source terms (volcanic ash and SO2) from inverse modelling for aviation

2020 ◽  
Author(s):  
Mariëlle Mulder ◽  
Delia Arnold ◽  
Christian Maurer ◽  
Marcus Hirtl
Keyword(s):  
Source Term ◽  
Dispersion Model ◽  
Meteorological Data ◽  
A Priori ◽  
Radar Data ◽  
Particle Dispersion ◽  
Volcanic Emissions ◽  
Volcanic Source ◽  
Computational Resources ◽  
Different Sources

<p>An operational framework is developed to provide timely and frequent source term updates for volcanic emissions (ash and SO<sub>2</sub>). The procedure includes running the Lagrangian particle dispersion model FLEXPART with an initial (a priori) source term, and combining the output with observations (from satellite, ground-based, etc. sources) to obtain an a posteriori source term. This work was part of the EUNADICS-AV (eunadics-av.eu), which is a continuation of the work developed in the VAST project (vast.nilu.no). The aim is to ensuring that at certain time intervals when new observational and meteorological data is available during an event, an updated source term is provided to analysis and forecasting groups. The system is tested with the Grimsvötn eruption of 2011. Based on a source term sensitivity test, one can find the optimum between a sufficiently detailed source term and computational resources. Because satellite and radar data from different sources is available at different times, the source term is generated with the data that is available the earliest after the eruption started and data that is available later is used for evaluation.</p>

scholarly journals Comparisons of polar processing diagnostics from 34 years of the ERA-Interim and MERRA reanalyses

2015 ◽  
Vol 15 (7) ◽  
pp. 3873-3892 ◽  
Author(s):  
Z. D. Lawrence ◽  
G. L. Manney ◽  
K. Minschwaner ◽  
M. L. Santee ◽  
A. Lambert
Keyword(s):  
Meteorological Data ◽  
Polar Vortex ◽  
Reanalysis Data ◽  
Cloud Formation ◽  
Data Sets ◽  
Weather Forecasts ◽  
Stratospheric Temperature ◽  
Vortex Size ◽  
Comprehensive Comparison ◽  
Modern Era

Abstract. We present a comprehensive comparison of polar processing diagnostics derived from the National Aeronautics and Space Administration (NASA) Modern Era Retrospective-analysis for Research and Applications (MERRA) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim). We use diagnostics that focus on meteorological conditions related to stratospheric chemical ozone loss based on temperatures, polar vortex dynamics, and air parcel trajectories to evaluate the effects these reanalyses might have on polar processing studies. Our results show that the agreement between MERRA and ERA-Interim changes significantly over the 34 years from 1979 to 2013 in both hemispheres and in many cases improves. By comparing our diagnostics during five time periods when an increasing number of higher-quality observations were brought into these reanalyses, we show how changes in the data assimilation systems (DAS) of MERRA and ERA-Interim affected their meteorological data. Many of our stratospheric temperature diagnostics show a convergence toward significantly better agreement, in both hemispheres, after 2001 when Aqua and GOES (Geostationary Operational Environmental Satellite) radiances were introduced into the DAS. Other diagnostics, such as the winter mean volume of air with temperatures below polar stratospheric cloud formation thresholds (VPSC) and some diagnostics of polar vortex size and strength, do not show improved agreement between the two reanalyses in recent years when data inputs into the DAS were more comprehensive. The polar processing diagnostics calculated from MERRA and ERA-Interim agree much better than those calculated from earlier reanalysis data sets. We still, however, see fairly large differences in many of the diagnostics in years prior to 2002, raising the possibility that the choice of one reanalysis over another could significantly influence the results of polar processing studies. After 2002, we see overall good agreement among the diagnostics, which demonstrates that the ERA-Interim and MERRA reanalyses are equally appropriate choices for polar processing studies of recent Arctic and Antarctic winters.

scholarly journals Open fires in Greenland: an unusual event and its impact on the albedo of the Greenland Ice Sheet

2018 ◽  
Author(s):  
Nikolaos Evangeliou ◽  
Arve Kylling ◽  
Sabine Eckhardt ◽  
Viktor Myroniuk ◽  
Kerstin Stebel ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Dispersion Model ◽  
Large Fraction ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Particle Dispersion ◽  
Data Sets ◽  
Average Value ◽  
Unusual Event ◽  
Order Of Magnitude

Abstract. Highly unusual open fires burned in Western Greenland between 31 July and 21 August 2017, after a period of warm, dry and sunny weather. The fires burned on peat lands that became vulnerable to fires by permafrost thawing. We used several satellite data sets to estimate that the total area burned was about 2345 hectares. Based on assumptions of typical burn depths and BC emission factors for peat fires, we estimate that the fires consumed a fuel amount of about 117 kt C and produced BC emissions of about 23.5 t. We used the Lagrangian particle dispersion model to simulate the atmospheric BC transport and deposition. We find that the smoke plumes were often pushed towards the Greenland Ice Sheet by westerly winds and thus a large fraction of the BC emissions (7 t or 30 %) was deposited on snow or ice covered surfaces. The calculated BC deposition was small compared to BC deposition from global sources, but not entirely negligible. Analysis of aerosol optical depth data from three sites in Western Greenland in August 2017 showed strong influence of forest fire plumes from Canada, but little impact of the Greenland fires. Nevertheless, CALIOP lidar data showed that our model captured very effectively the presence and structure of the plume from the Greenland fires. The albedo changes and instantaneous surface radiative forcing in Greenland due to the fire BC emissions were estimated with the SNICAR model and the uvspec model from the libRadtran radiative transfer software package. We estimate that the maximum albedo change due to the BC deposition was about 0.006, too small to be measured by satellites or other means. The average instantaneous surface radiative forcing over Greenland at noon on 31 August was 0.03 W m−2, with locally occurring maximum values of 0.63 W m−2. The average value is at least an order of magnitude smaller than the radiative forcing due to BC from other sources. Overall, the fires burning in Greenland in summer of 2017 had little impact on BC deposition on the Greenland Ice Sheet, causing almost negligible extra radiative forcing. This was due to the – in a global context – still rather small size of the fires. However, the very large fraction of the BC emissions deposited on the Greenland Ice Sheet makes these fires very efficient climate forcers on a per unit emission basis. If the expected further warming of Greenland produces much larger fires in the future, this could indeed cause substantial albedo changes and thus lead to accelerated melting of the Greenland Ice Sheet. The fires burning in 2017 may be a harbinger of such future changes.

scholarly journals Influence of meteorological input data on backtrajectory cluster analysis – a seven-year study for southeastern Spain

2008 ◽  
Vol 2 (1) ◽  
pp. 65-70 ◽  
Author(s):  
M. Cabello ◽  
J. A. G. Orza ◽  
V. Galiano ◽  
G. Ruiz
Keyword(s):  
Cluster Analysis ◽  
Input Data ◽  
Meteorological Data ◽  
Data Sets ◽  
Number Of Clusters ◽  
Southeastern Spain ◽  
Meteorological Input ◽  
Initial Selection ◽  
Southeast Spain ◽  
Selection Of

Abstract. Backtrajectory differences and clustering sensitivity to the meteorological input data are studied. Trajectories arriving in Southeast Spain (Elche), at 3000, 1500 and 500 m for the 7-year period 2000–2006 have been computed employing two widely used meteorological data sets: the NCEP/NCAR Reanalysis and the FNL data sets. Differences between trajectories grow linearly at least up to 48 h, showing faster growing after 72 h. A k-means cluster analysis performed on each set of trajectories shows differences in the identified clusters (main flows), partially because the number of clusters of each clustering solution differs for the trajectories arriving at 3000 and 1500 m. Trajectory membership to the identified flows is in general more sensitive to the input meteorological data than to the initial selection of cluster centroids.

scholarly journals Wind-Blown Dust Modeling Using a Backward-Lagrangian Particle Dispersion Model

2017 ◽  
Vol 56 (10) ◽  
pp. 2845-2867 ◽  
Author(s):  
Derek V. Mallia ◽  
Adam Kochanski ◽  
Dien Wu ◽  
Chris Pennell ◽  
Whitney Oswald ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Meteorological Data ◽  
Dust Emission ◽  
Particle Dispersion ◽  
Emission Model ◽  
Dust Event ◽  
Lagrangian Particle ◽  
Modeling Framework ◽  
Source Regions ◽  
Dust Modeling

AbstractPresented here is a new dust modeling framework that uses a backward-Lagrangian particle dispersion model coupled with a dust emission model, both driven by meteorological data from the Weather Research and Forecasting (WRF) Model. This new modeling framework was tested for the spring of 2010 at multiple sites across northern Utah. Initial model results for March–April 2010 showed that the model was able to replicate the 27–28 April 2010 dust event; however, it was unable to reproduce a significant wind-blown dust event on 30 March 2010. During this event, the model significantly underestimated PM2.5 concentrations (4.7 vs 38.7 μg m−3) along the Wasatch Front. The backward-Lagrangian approach presented here allowed for the easy identification of dust source regions with misrepresented land cover and soil types, which required an update to WRF. In addition, changes were also applied to the dust emission model to better account for dust emitted from dry lake basins. These updates significantly improved dust model simulations, with the modeled PM2.5 comparing much more favorably to observations (average of 30.3 μg m−3). In addition, these updates also improved the timing of the frontal passage within WRF. The dust model was also applied in a forecasting setting, with the model able to replicate the magnitude of a large dust event, albeit with a 2-h lag. These results suggest that the dust modeling framework presented here has potential to replicate past dust events, identify source regions of dust, and be used for short-term forecasting applications.

scholarly journals Ground-based FTIR and MAX-DOAS observations of formaldehyde at Réunion Island and comparisons with satellite and model data

2009 ◽  
Vol 9 (4) ◽  
pp. 15891-15957 ◽  
Author(s):  
C. Vigouroux ◽  
F. Hendrick ◽  
T. Stavrakou ◽  
B. Dils ◽  
I. De Smedt ◽  
...  
Keyword(s):  
Large Scale ◽  
Dispersion Model ◽  
Sensitivity Study ◽  
Particle Dispersion ◽  
Data Sets ◽  
Reunion Island ◽  
Source Regions ◽  
Réunion Island ◽  
Transport Patterns ◽  
Good Agreement

Abstract. Formaldehyde (HCHO) columns have been retrieved from ground-based Fourier transform infrared (FTIR) campaign measurements in 2004 and 2007 and from UV-Visible MAX-DOAS measurements in 2004–2005 at the NDACC site of Réunion Island (21° S, 55° E). The FTIR and MAX-DOAS daily mean formaldehyde total columns are intercompared in their common measurement period, from August to October 2004. The ground-based data are also compared to correlative SCIAMACHY data. The comparisons account for the vertical sensitivity differences of the data sets, by including their respective averaging kernels. Complete error budgets are also presented. The FTIR and MAX-DOAS daily mean total columns agree very well: no significant bias is observed and the standard deviation of the comparisons is only 8%. Both FTIR and MAX-DOAS HCHO total columns are in good agreement with SCIAMACHY values in the 2004–2005 period, with standard deviations of 21% and 31%, respectively. The same seasonal cycle is observed by the different instruments, with a minimum in austral winter and a maximum in February–March. The FTIR and MAX-DOAS data are confronted with HCHO columns calculated by a global CTM, the IMAGES model. The model underestimates the HCHO columns by 23–29% in comparison with FTIR, and by 15% in comparison with DOAS. This bias might have multiple causes, including an underestimation of OH concentrations in the model (as indicated by a sensitivity study using prescribed OH fields) and/or an underestimated contribution of large-scale transport of HCHO precursors from Madagascar. The latter hypothesis is comforted by the large observed day-to-day variability of HCHO columns, and by the observation that the peak values of FTIR columns can often be associated with free tropospheric transport patterns from source regions over Madagascar to Réunion Island, according to simulations performed with the Lagrangian particle dispersion model FLEXPART.

scholarly journals Ground-based FTIR and MAX-DOAS observations of formaldehyde at Réunion Island and comparisons with satellite and model data

2009 ◽  
Vol 9 (24) ◽  
pp. 9523-9544 ◽  
Author(s):  
C. Vigouroux ◽  
F. Hendrick ◽  
T. Stavrakou ◽  
B. Dils ◽  
I. De Smedt ◽  
...  
Keyword(s):  
Large Scale ◽  
Dispersion Model ◽  
Sensitivity Study ◽  
Particle Dispersion ◽  
Data Sets ◽  
Reunion Island ◽  
Source Regions ◽  
Réunion Island ◽  
Transport Patterns ◽  
Good Agreement

Abstract. Formaldehyde (HCHO) columns have been retrieved from ground-based Fourier transform infrared (FTIR) campaign measurements in 2004 and 2007 and from UV-Visible MAX-DOAS measurements in 2004–2005 at the NDACC site of Réunion Island (21° S, 55° E). The FTIR and MAX-DOAS daily mean formaldehyde total columns are intercompared in their common measurement period, from August to October 2004. The ground-based data are also compared to correlative SCIAMACHY data. The comparisons account for the vertical sensitivity differences of the data sets, by including their respective averaging kernels. Complete error budgets are also presented. The FTIR and MAX-DOAS daily mean total columns agree very well: no significant bias is observed and the standard deviation of the comparisons is only 8%. Both FTIR and MAX-DOAS HCHO total columns are in good agreement with SCIAMACHY values in the 2004–2005 period, with standard deviations of 21% and 31%, respectively. The same seasonal cycle is observed by the different instruments, with a minimum in austral winter and a maximum in February–March. The FTIR and MAX-DOAS data are confronted with HCHO columns calculated by a global CTM, the IMAGES model. The model underestimates the HCHO columns by 23–29% in comparison with FTIR, and by 15% in comparison with DOAS. This bias might have multiple causes, including an underestimation of OH concentrations in the model (as indicated by a sensitivity study using prescribed OH fields) and/or an underestimated contribution of large-scale transport of HCHO precursors from Madagascar. The latter hypothesis is comforted by the large observed day-to-day variability of HCHO columns, and by the observation that the peak values of FTIR columns can often be associated with free tropospheric transport patterns from source regions over Madagascar to Réunion Island, according to simulations performed with the Lagrangian particle dispersion model FLEXPART.

GROOPS: An open-source software package for GNSS processing and gravity field recovery

2021 ◽  
Author(s):  
Andreas Kvas ◽  
Saniya Behzadpour ◽  
Annette Eicker ◽  
Matthias Ellmer ◽  
Beate Koch ◽  
...  
Keyword(s):  
Gravity Field ◽  
Software Package ◽  
Satellite System ◽  
Object Oriented Programming ◽  
Satellite Orbits ◽  
Data Sets ◽  
Programming System ◽  
Gravity Field Recovery ◽  
Open Source Software Package ◽  
Global Navigation Satellite

<p>The Gravity Recovery Object Oriented Programming System (GROOPS) is a software package written in C++ that enables the user to perform core geodetic tasks. The software features gravity field recovery from satellite and terrestrial data, the determination of low-earth-orbiting satellite orbits from global navigation satellite system (GNSS) measurements, and the computation of GNSS constellations and ground station networks. For an easy and intuitive setup of complex workflows, GROOPS contains a graphical user interface to create and edit configuration files. The source code of GROOPS is released under the GPL v3 license and is available on GitHub (https://github.com/groops-devs/groops) together with documentation, a cookbook with guided examples, and installation instructions for different platforms. In this contribution we give a software overview and present results of different applications and data sets computed with GROOPS.</p>

scholarly journals Methodology to obtain highly resolved SO<sub>2</sub> vertical profiles for representation of volcanic emissions in climate models

2021 ◽  
Vol 14 (11) ◽  
pp. 7153-7165
Author(s):  
Oscar S. Sandvik ◽  
Johan Friberg ◽  
Moa K. Sporre ◽  
Bengt G. Martinsson
Keyword(s):  
Dispersion Model ◽  
Meteorological Data ◽  
Potential Temperature ◽  
Particle Dispersion ◽  
Orthogonal Polarization ◽  
Height Distribution ◽  
Vertical Profiles ◽  
Vertical Resolution ◽  
Volcanic Emissions ◽  
High Vertical Resolution

Abstract. In this study we describe a methodology to create high-vertical-resolution SO2 profiles from volcanic emissions. We demonstrate the method's performance for the volcanic clouds following the eruption of Sarychev in June 2009. The resulting profiles are based on a combination of satellite SO2 and aerosol retrievals together with trajectory modelling. We use satellite-based measurements, namely lidar backscattering profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite instrument, to create vertical profiles for SO2 swaths from the Atmospheric Infrared Sounder (AIRS) aboard the Aqua satellite. Vertical profiles are created by transporting the air containing volcanic aerosol seen in CALIOP observations using the FLEXible PARTicle dispersion model (FLEXPART) while preserving the high vertical resolution using the potential temperatures from the MERRA-2 (Modern-Era Retrospective analysis for Research and Application) meteorological data for the original CALIOP swaths. For the Sarychev eruption, air tracers from 75 CALIOP swaths within 9 d after the eruption are transported forwards and backwards and then combined at a point in time when AIRS swaths cover the complete volcanic SO2 cloud. Our method creates vertical distributions for column density observations of SO2 for individual AIRS swaths, using height information from multiple CALIOP swaths. The resulting dataset gives insight into the height distribution in the different sub-clouds of SO2 within the stratosphere. We have compiled a gridded high-vertical-resolution SO2 inventory that can be used in Earth system models, with a vertical resolution of 1 K in potential temperature, 61 ± 56 m, or 1.8 ± 2.9 mbar.

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