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.

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.

Impact of planetary waves on infrasound propagation uncertainties

2021 ◽  
Author(s):  
Elisabeth Blanc ◽  
Patrick Hupe ◽  
Bernd Kaifler ◽  
Natalie Kaifler ◽  
Alexis Le Pichon ◽  
...  
Keyword(s):  
Wave Activity ◽  
Atmospheric Dynamics ◽  
Planetary Waves ◽  
Data Sets ◽  
Atmospheric Models ◽  
Period Range ◽  
Weather Forecasts ◽  
Atmospheric Disturbances ◽  
Medium Range ◽  
Model Improvement

<p>The uncertainties in the infrasound technology arise from the middle atmospheric disturbances, which are partly underrepresented in the atmospheric models such as in the European Centre for Medium-Range Weather Forecasts (ECMWF) products used for infrasound propagation simulations. In the framework of the ARISE (Atmospheric dynamics Research InfraStructure in Europe) project, multi-instrument observations are performed to provide new data sets for model improvement and future assimilations. In an unexpected way, new observations using the autonomous CORAL lidar showed significant differences between ECMWF analysis fields and observations in Argentina in the period range between 0.1 and 10 days. The model underestimates the wave activity, especially in the summer. During the same season, the infrasound bulletins of the IS02 station in Argentina indicate the presence of two prevailing directions of the detections, which are not reflected by the simulations. Observations at the Haute Provence Observatory (OHP) are used for comparison in different geophysical conditions. The origin of the observed anomalies are discussed in term of planetary waves effect on the infrasound propagation.</p>

scholarly journals Errors in top-down estimates of emissions using a known source

2020 ◽  
Author(s):  
Wayne M. Angevine ◽  
Jeff Peischl ◽  
Alice Crawford ◽  
Christopher P. Loughner ◽  
Ilana B. Pollack ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Random Errors ◽  
Top Down ◽  
Weather Forecasts ◽  
Medium Range ◽  
Research Aircraft ◽  
Lagrangian Dispersion ◽  
Types Of Error

Abstract. Air pollutant emissions estimates by top-down methods are subject to a variety of errors and uncertainties. This work uses a known source, a coal-fired power plant, to explore those errors. The known emissions amount and location remove two major types of error, facilitating understanding of other types. Biases and random errors are distinguished. A Lagrangian dispersion model (HYSPLIT) is run forward in time from the known source, and virtual measurements of the resulting tracer plume are compared to actual measurements from research aircraft. Four flights in different years are used to illustrate a variety of conditions. The measurements are analyzed by a mass-balance method, and the assumptions of that method are discussed. Some of those assumptions can be relaxed in analysis of the modeled plume, allowing testing of their validity. Meteorological fields to drive HYSPLIT are provided by the European Center for Medium Range Weather Forecasts Fifth Reanalysis (ERA5). A unique feature of this work is the use of an ensemble of meteorological fields intrinsic to ERA5. This analysis supports reasonably large (30–40 %) uncertainties on top-down analyses.

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 Trajectory matching of ozonesondes and MOZAIC measurements in the UTLS – Part 2: Application to the global ozonesonde network

2014 ◽  
Vol 7 (1) ◽  
pp. 241-266 ◽  
Author(s):  
J. Staufer ◽  
J. Staehelin ◽  
R. Stübi ◽  
T. Peter ◽  
F. Tummon ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Data Sets ◽  
Wind Fields ◽  
Concentration Cell ◽  
Weather Forecasts ◽  
Long Term Stability ◽  
Medium Range ◽  
The Difference ◽  
Long Term Trend

Abstract. Both balloon-borne electrochemical ozonesondes and MOZAIC (measurements of ozone, water vapour, carbon monoxide and nitrogen oxides by in-service Airbus aircraft) provide very valuable data sets for ozone studies in the upper troposphere/lower stratosphere (UTLS). Although MOZAIC's highly accurate UV-photometers are regularly inspected and recalibrated annually, recent analyses cast some doubt on the long-term stability of their ozone analysers. To investigate this further, we perform a 16 yr comparison (1994–2009) of UTLS ozone measurements from balloon-borne ozonesondes and MOZAIC. The analysis uses fully three-dimensional trajectories computed from ERA-Interim (European Centre for Medium-Range Weather Forecasts Re-analysis) wind fields to find matches between the two measurement platforms. Although different sensor types (Brewer-Mast and Electrochemical Concentration Cell ozonesondes) were used, most of the 28 launch sites considered show considerable differences of up to 25% compared to MOZAIC in the mid-1990s, followed by a systematic tendency to smaller differences of around 5–10% in subsequent years. The reason for the difference before 1998 remains unclear, but observations from both sondes and MOZAIC require further examination to be reliable enough for use in robust long-term trend analyses starting before 1998. According to our analysis, ozonesonde measurements at tropopause altitudes appear to be rather insensitive to changing the type of the Electrochemical Concentration Cell ozonesonde, provided the cathode sensing solution strength remains unchanged. Scoresbysund (Greenland) showed systematically 5% higher readings after changing from Science Pump Corporation sondes to ENSCI Corporation sondes, while a 1.0% KI cathode electrolyte was retained.

scholarly journals Errors in top-down estimates of emissions using a known source

2020 ◽  
Vol 20 (20) ◽  
pp. 11855-11868
Author(s):  
Wayne M. Angevine ◽  
Jeff Peischl ◽  
Alice Crawford ◽  
Christopher P. Loughner ◽  
Ilana B. Pollack ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Random Errors ◽  
Top Down ◽  
Weather Forecasts ◽  
Medium Range ◽  
Research Aircraft ◽  
Lagrangian Dispersion ◽  
Types Of Error

Abstract. Air pollutant emissions estimates by top-down methods are subject to a variety of errors and uncertainties. This work uses a known source, a coal-fired power plant, to explore those errors. The known emissions amount and location remove two major types of error, facilitating understanding of other types. Biases and random errors are distinguished. A Lagrangian dispersion model (HYSPLIT) is run forward in time from the known source, and virtual measurements of the resulting tracer plume are compared to actual measurements from research aircraft. Four flights in different years are used to illustrate a variety of conditions. The measurements are analyzed by a mass-balance method, and the assumptions of that method are discussed. Some of those assumptions can be relaxed in analysis of the modeled plume, allowing testing of their validity. Meteorological fields to drive HYSPLIT are provided by the European Centre for Medium-Range Weather Forecasts Fifth Reanalysis (ERA5). A unique feature of this work is the use of an ensemble of meteorological fields intrinsic to ERA5. This analysis supports reasonably large (30 %–40 %) uncertainties on top-down analyses.

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 HOAPS and ERA-Interim precipitation over sea: Validation against shipboard in-situ measurements

2016 ◽  
Author(s):  
Karl Bumke ◽  
Gert König-Langlo ◽  
Julian Kinzel ◽  
Marc Schröder
Keyword(s):  
Reanalysis Data ◽  
Data Sets ◽  
Weather Forecasts ◽  
Rain Gauges ◽  
Medium Range ◽  
Temporal And Spatial ◽  
The Tropics ◽  
Along Track ◽  
Spatial Threshold

Abstract. The satellite derived HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite data) and ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-Interim reanalysis data sets have been validated against in-situ precipitation measurements from ship rain gauges and optical disdrometers over the open-ocean by applying a statistical analysis for binary forecasts. For this purpose collocated pairs of data were merged within a certain temporal and spatial threshold into single events, according to the satellites' overpass, the observation and the forecast times. HOAPS detects the frequency of precipitation well, while ERA-Interim strongly overestimates it, especially in the tropics and subtropics. Although precipitation rates are difficult to compare because along-track point measurements are collocated with areal estimates and the numbers of available data are limited, we find that HOAPS underestimates precipitation rates, while ERA-Interim's Atlantic-wide average precipitation rate is close to measurements. However, regionally averaged over latitudinal belts, there are deviations between the observed mean precipitation rates and ERA-Interim. The most obvious ERA-Interim feature is an overestimation of precipitation in the area of the intertropical convergence zone and the southern sub-tropics over the Atlantic Ocean. For a limited number of snow measurements by optical disdrometers it can be concluded that both HOAPS and ERA-Interim are suitable to detect the occurrence of solid precipitation.

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