scholarly journals A regional CO2 observing system simulation experiment for the ASCENDS satellite mission

2014 ◽  
Vol 14 (23) ◽  
pp. 12897-12914 ◽  
Author(s):  
J. S. Wang ◽  
S. R. Kawa ◽  
J. Eluszkiewicz ◽  
D. F. Baker ◽  
M. Mountain ◽  
...  
Keyword(s):  
Measurement Errors ◽  
Dispersion Model ◽  
A Priori ◽  
Wrf Model ◽  
Particle Dispersion ◽  
Instrument Design ◽  
Satellite Mission ◽  
Model Framework ◽  
Satellite Systems ◽  
Novel Approach

Abstract. Top–down estimates of the spatiotemporal variations in emissions and uptake of CO2 will benefit from the increasing measurement density brought by recent and future additions to the suite of in situ and remote CO2 measurement platforms. In particular, the planned NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) satellite mission will provide greater coverage in cloudy regions, at high latitudes, and at night than passive satellite systems, as well as high precision and accuracy. In a novel approach to quantifying the ability of satellite column measurements to constrain CO2 fluxes, we use a portable library of footprints (surface influence functions) generated by the Stochastic Time-Inverted Lagrangian Transport (STILT) model in combination with the Weather Research and Forecasting (WRF) model in a regional Bayesian synthesis inversion. The regional Lagrangian particle dispersion model framework is well suited to make use of ASCENDS observations to constrain weekly fluxes in North America at a high resolution, in this case at 1° latitude × 1° longitude. We consider random measurement errors only, modeled as a function of the mission and instrument design specifications along with realistic atmospheric and surface conditions. We find that the ASCENDS observations could potentially reduce flux uncertainties substantially at biome and finer scales. At the grid scale and weekly resolution, the largest uncertainty reductions, on the order of 50%, occur where and when there is good coverage by observations with low measurement errors and the a priori uncertainties are large. Uncertainty reductions are smaller for a 1.57 μm candidate wavelength than for a 2.05 μm wavelength, and are smaller for the higher of the two measurement error levels that we consider (1.0 ppm vs. 0.5 ppm clear-sky error at Railroad Valley, Nevada). Uncertainty reductions at the annual biome scale range from ~40% to ~75% across our four instrument design cases and from ~65% to ~85% for the continent as a whole. Tests suggest that the quantitative results are moderately sensitive to assumptions regarding a priori uncertainties and boundary conditions. The a posteriori flux uncertainties we obtain, ranging from 0.01 to 0.06 Pg C yr−1 across the biomes, would meet requirements for improved understanding of long-term carbon sinks suggested by a previous study.

scholarly journals A regional CO2 observing system simulation experiment for the ASCENDS Satellite Mission

2014 ◽  
Vol 14 (9) ◽  
pp. 12819-12862 ◽  
Author(s):  
J. S. Wang ◽  
S. R. Kawa ◽  
J. Eluszkiewicz ◽  
D. F. Baker ◽  
M. Mountain ◽  
...  
Keyword(s):  
Measurement Errors ◽  
Transport Model ◽  
A Priori ◽  
Instrument Design ◽  
Satellite Mission ◽  
Satellite Systems ◽  
Lagrangian Framework ◽  
Novel Approach ◽  
Scale Range ◽  
Observing System Simulation Experiment

Abstract. Top-down estimates of the spatiotemporal variations in emissions and uptake of CO2 will benefit from the increasing measurement density brought by recent and future additions to the suite of in situ and remote CO2 measurement platforms. In particular, the planned NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) satellite mission will provide greater coverage in cloudy regions, at high latitudes, and at night than passive satellite systems, as well as high precision and accuracy. In a novel approach to quantifying the ability of satellite column measurements to constrain CO2 fluxes, we use a portable library of footprints (surface influence functions) generated by the WRF-STILT Lagrangian transport model in a regional Bayesian synthesis inversion. The regional Lagrangian framework is well suited to make use of ASCENDS observations to constrain fluxes at high resolution, in this case at 1° latitude × 1° longitude and weekly for North America. We consider random measurement errors only, modeled as a function of mission and instrument design specifications along with realistic atmospheric and surface conditions. We find that the ASCENDS observations could potentially reduce flux uncertainties substantially at biome and finer scales. At the 1° × 1°, weekly scale, the largest uncertainty reductions, on the order of 50%, occur where and when there is good coverage by observations with low measurement errors and the a priori uncertainties are large. Uncertainty reductions are smaller for a 1.57 μm candidate wavelength than for a 2.05 μm wavelength, and are smaller for the higher of the two measurement error levels that we consider (1.0 ppm vs. 0.5 ppm clear-sky error at Railroad Valley, Nevada). Uncertainty reductions at the annual, biome scale range from ∼40% to ∼75% across our four instrument design cases, and from ∼65% to ∼85% for the continent as a whole. Our uncertainty reductions at various scales are substantially smaller than those from a global ASCENDS inversion on a coarser grid, demonstrating how quantitative results can depend on inversion methodology. The a posteriori flux uncertainties we obtain, ranging from 0.01 to 0.06 Pg C yr−1 across the biomes, would meet requirements for improved understanding of long-term carbon sinks suggested by a previous study.

Estimates of anthropogenic CO2 emissions from satellite and ground based measurements

2020 ◽  
Author(s):  
Yury Timofeyev ◽  
George Nerobelov ◽  
Sergey Smyshlyaev ◽  
Ivan Berezin ◽  
Yana Virolainen ◽  
...  
Keyword(s):  
Measurement Errors ◽  
Numerical Models ◽  
Dispersion Model ◽  
A Priori ◽  
Three Dimensional ◽  
Atmospheric Model ◽  
Experimental Information ◽  
Anthropogenic Emissions ◽  
Plume Dispersion ◽  
Satellite Measurements

<p>In recent years, satellite methods have played an important role in CO<sub>2</sub> monitoring. Various satellite instruments (SCIAMACHY, AIRS, GOSAT, OCO-2, etc.) validated by ground-based and aircraft measurements allow to retrieving the column averaged CO<sub>2</sub> mixing ratio (X<sub>CO2</sub>) with high accuracy (0.25–1.0%). The relatively high spatial resolution of a number of instruments (for example, OCO-2) allows studies of spatial and temporal CO<sub>2</sub> variations, that, under appropriate conditions, makes it possible to estimate anthropogenic emissions from different cities.</p><p>Various techniques (source pixel mass balance method, plume dispersion model and atmospheric inversion system) for determining anthropogenic greenhouse gas emissions from data of satellite measurements are considered.</p><p>On the basis of three-dimensional modeling and comparison with the results of various local and remote measurements, numerical models of the atmosphere were adapted to different megacities of Russia. Based on numerical experiments, the errors of various satellite techniques for determining emissions caused by various factors (measurement errors, quality of used a priori and additional experimental information, adequacy of used numerical atmospheric model, etc.) were evaluated. Anthropogenic CO<sub>2</sub> emissions in St. Petersburg, Moscow and other cities of Russia are estimated using various satellite measurements. These estimates of anthropogenic emissions are compared with data obtained by different methods and for different cities.</p>

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 Impact of optimized mixing heights on simulated regional atmospheric transport of CO<sub>2</sub>

2014 ◽  
Vol 14 (14) ◽  
pp. 7149-7172 ◽  
Author(s):  
R. Kretschmer ◽  
C. Gerbig ◽  
U. Karstens ◽  
G. Biavati ◽  
A. Vermeulen ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Synthetic Data ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Particle Dispersion ◽  
Random Errors ◽  
Tracer Transport ◽  
European Continent ◽  
Co2 Transport ◽  
The Impact

Abstract. The mixing height (MH) is a crucial parameter in commonly used transport models that proportionally affects air concentrations of trace gases with sources/sinks near the ground and on diurnal scales. Past synthetic data experiments indicated the possibility to improve tracer transport by minimizing errors of simulated MHs. In this paper we evaluate a method to constrain the Lagrangian particle dispersion model STILT (Stochastic Time-Inverted Lagrangian Transport) with MH diagnosed from radiosonde profiles using a bulk Richardson method. The same method was used to obtain hourly MHs for the period September/October 2009 from the Weather Research and Forecasting (WRF) model, which covers the European continent at 10 km horizontal resolution. Kriging with external drift (KED) was applied to estimate optimized MHs from observed and modelled MHs, which were used as input for STILT to assess the impact on CO2 transport. Special care has been taken to account for uncertainty in MH retrieval in this estimation process. MHs and CO2 concentrations were compared to vertical profiles from aircraft in situ data. We put an emphasis on testing the consistency of estimated MHs to observed vertical mixing of CO2. Modelled CO2 was also compared with continuous measurements made at Cabauw and Heidelberg stations. WRF MHs were significantly biased by ~10–20% during day and ~40–60% during night. Optimized MHs reduced this bias to ~5% with additional slight improvements in random errors. The KED MHs were generally more consistent with observed CO2 mixing. The use of optimized MHs had in general a favourable impact on CO2 transport, with bias reductions of 5–45% (day) and 60–90% (night). This indicates that a large part of the found CO2 model–data mismatch was indeed due to MH errors. Other causes for CO2 mismatch are discussed. Applicability of our method is discussed in the context of CO2 inversions at regional scales.

scholarly journals A meteorological overview of the ARCTAS 2008 mission

2009 ◽  
Vol 9 (5) ◽  
pp. 18417-18478 ◽  
Author(s):  
H. E. Fuelberg ◽  
D. L. Harrigan ◽  
W. Sessions
Keyword(s):  
Large Scale ◽  
Dispersion Model ◽  
Wrf Model ◽  
Particle Dispersion ◽  
Meteorological Conditions ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Transport Pathways ◽  
Large Scale Flow ◽  
June July

Abstract. The Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) mission was a multi-aircraft project whose major objective was to investigate the factors driving changes in the Arctic's atmospheric composition and climate. It was conducted during April and June–July 2008. The summer ARCTAS deployment was preceded by a week of flights over and around California to address state issues of air quality and climate forcing. This paper focuses on meteorological conditions during the ARCTAS Spring and Summer campaigns. We examine mission averaged large-scale flow patterns at the surface, 500 hPa, and 300 hPa and determine their departures from climatology. Results from runs of the Weather Research and Forecasting (WRF) model are used to describe meteorological conditions on individual days. Our WRF configuration included a nested grid approach that provided horizontal spacing as small as 5 km. Trajectories calculated from the WRF output are used to determine transport pathways to the Arctic, including their origins and the altitudes at which they reach 70° N. We also present backward trajectories from selected legs of individual ARCTAS flights. Finally, the FLEXPART particle dispersion model, with the high resolution WRF data as input, is used to determine the paths of anthropogenic and biomass burning-derived CO. Results show that there was frequent and widespread transport to the Arctic during both phases of ARCTAS and that the three ARCTAS aircraft sampled air having a multitude of origins, following a myriad of paths, and experiencing many types of meteorological conditions.

scholarly journals Precipitation Efficiency and Water Budget of Typhoon Fitow (2013): A Particle Trajectory Study

2017 ◽  
Vol 18 (9) ◽  
pp. 2331-2354 ◽  
Author(s):  
Huiyan Xu ◽  
Guoqing Zhai ◽  
Xiaofan Li
Keyword(s):  
Water Vapor ◽  
Dispersion Model ◽  
Wrf Model ◽  
Particle Dispersion ◽  
Precipitation Efficiency ◽  
Accumulated Rainfall ◽  
Torrential Rainfall ◽  
High Precipitation ◽  
Particles Trajectories ◽  
Water Vapor Convergence

Abstract In this study, the WRF Model is used to simulate the torrential rainfall of Typhoon Fitow (2013) over coastal areas of east China during its landfall. Data from the innermost model domain are used to trace trajectories of particles in three major 24-h accumulated rainfall centers using the Lagrangian flexible particle dispersion model (FLEXPART). Surface rainfall budgets and cloud microphysical budgets as well as precipitation efficiency are analyzed along the particles’ trajectories. The rainfall centers with high precipitation efficiency are associated with water vapor convergence, condensation, accretion of cloud water by raindrops, and raindrop loss/convergence. The raindrop loss/convergence over rainfall centers is supported by the raindrop gain/divergence over the areas adjacent to rainfall centers. Precipitation efficiency is mainly determined by hydrometeor loss/convergence. Hydrometeor loss/convergence corresponds to the hydrometeor flux convergence, which may be related to the increased vertical advection of hydrometeors in response to the upward motions and upward decrease of hydrometeors, whereas hydrometeor gain/divergence corresponds to the reduction in hydrometeor flux convergence, which may be associated with the decreased horizontal advection of hydrometeors in response to the zonal decrease in hydrometeors and easterly winds and the meridional increase in hydrometeors and southerly winds. The water vapor convergence and associated condensation do not show consistent relationships with orographic lifting all the time.

scholarly journals Simulation of SEVIRI infrared channels: a case study from the Eyjafjallajökull April/May 2010 eruption

2012 ◽  
Vol 5 (5) ◽  
pp. 7783-7813 ◽  
Author(s):  
A. Kylling ◽  
R. Buras ◽  
S. Eckhardt ◽  
C. Emde ◽  
B. Mayer ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Satellite Images ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Model Framework ◽  
Brightness Temperatures ◽  
Retrieval Technique ◽  
Infrared Radiances

Abstract. Infrared satellite images are widely and successfully used to detect and follow atmospheric ash from erupting volcanoes. We describe a new radiative transfer model framework for the simulation of infrared radiances, which can be compared directly with satellite images. This can be helpful to get insight into the processes that affect the satellite retrievals. As input to the radiative transfer model, the distribution of ash is provided by simulations with the FLEXPART Lagrangian particle dispersion model, meteorological cloud information is adopted from the ECMWF analysis and the radiative transfer modelling is performed with the MYSTIC 3-D radiative transfer model. The model framework is used to study an episode during the Eyjafjallajökull eruption in 2010. It is found that to detect ash by the reverse absorption retrieval technique, accurate representation of the ash particle size distribution is required. Detailed investigation of individual pixels displays the radiative effects of various combinations of ash, liquid water and ice clouds. In order to be clearly detectable, the ash clouds need to be located at some distance above other clouds. If ash clouds are mixed with water clouds or are located only slightly above water clouds, detection of the ash becomes difficult. Simulations were also made using the so-called independent pixel approximation (IPA) instead of the fully 3-D radiative transfer modeling. A comparison between these IPA simulations and the 3-D simulations revealed differences in brightness temperatures of up to ±25 K due to shadow effects. The presented model framework is useful for further studies of the processes that affect satellite imagery and may be used to test both new and existing ash retrieval algorithms.

scholarly journals A meteorological overview of the ARCTAS 2008 mission

2010 ◽  
Vol 10 (2) ◽  
pp. 817-842 ◽  
Author(s):  
H. E. Fuelberg ◽  
D. L. Harrigan ◽  
W. Sessions
Keyword(s):  
Large Scale ◽  
Dispersion Model ◽  
Wrf Model ◽  
Particle Dispersion ◽  
Meteorological Conditions ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Transport Pathways ◽  
Large Scale Flow ◽  
June July

Abstract. The Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) mission was a multi-aircraft project whose major objective was to investigate the factors driving changes in the Arctic's atmospheric composition and climate. It was conducted during April and June–July 2008. The summer ARCTAS deployment was preceded by a week of flights over and around California to address state issues of air quality and climate forcing. This paper focuses on meteorological conditions during the ARCTAS Spring and Summer campaigns. We examine mission averaged large-scale flow patterns at the surface, 500 hPa, and 300 hPa and determine their departures from climatology. Results from runs of the Weather Research and Forecasting (WRF) model are used to describe meteorological conditions on individual days. Our WRF configuration included a nested grid approach that provided horizontal spacing as small as 5 km. Trajectories calculated from the WRF output are used to determine transport pathways to the Arctic, including their origins and the altitudes at which they reach 70° N. We also present backward trajectories from selected legs of individual ARCTAS flights. Finally, the FLEXPART Lagrangian particle dispersion model, with the high resolution WRF data as input, is used to determine the paths of anthropogenic and biomass burning-derived CO. Results show that there was frequent and widespread transport to the Arctic during both phases of ARCTAS and that the three ARCTAS aircraft sampled air having a multitude of origins, following a myriad of paths, and experiencing many types of meteorological conditions.

scholarly journals Impact of optimized mixing heights on simulated regional atmospheric transport of CO<sub>2</sub>

2014 ◽  
Vol 14 (4) ◽  
pp. 4627-4685
Author(s):  
R. Kretschmer ◽  
C. Gerbig ◽  
U. Karstens ◽  
G. Biavati ◽  
A. Vermeulen ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Synthetic Data ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Particle Dispersion ◽  
Random Errors ◽  
Tracer Transport ◽  
European Continent ◽  
Co2 Transport ◽  
The Impact

Abstract. The mixing height (MH) is a crucial parameter in commonly used transport models that proportionally affects air concentrations of trace gases with sources/sinks near the ground and on diurnal scales. Past synthetic data experiments indicated the possibility to improve tracer transport by minimizing errors of simulated MHs. In this paper we evaluate a method to constrain the Langrangian particle dispersion model STILT (Stochastic Time-Inverted Lagrangian Transport) with MH diagnosed from radiosonde profiles using a bulk Richardson method. The same method was used to obtain hourly MHs for the period September/October 2009 from the Weather Research and Forecasting (WRF) model, which covers the European continent at 10 km horizontal resolution. Kriging with External Drift (KED) was applied to estimate optimized MHs from observed and modelled MHs, which were used as input for STILT to assess the impact on CO2 transport. Special care has been taken to account for uncertainty in MH retrieval in this estimation process. MHs and CO2 concentrations were compared to vertical profiles from aircraft in-situ data. We put an emphasis on testing the consistency of estimated MHs to observed vertical mixing of CO2. Modelled CO2 was also compared with continuous measurements made at Cabauw and Heidelberg stations. WRF MHs were significantly biased by ~10–20% during day and ~40–60% during night. Optimized MHs reduced this bias to ~5% with additional slight improvements in random errors. The KED MHs were generally more consistent with observed CO2 mixing. The use of optimized MHs had in general a favourable impact on CO2 transport, with bias reductions of 5–45% (day) and 60–90% (night). This indicates that a large part of the found CO2 model-data mismatch was indeed due to MH errors. Other causes for CO2 mismatch are discussed. Applicability of our method is discussed in the context of CO2 inversions at regional scales.

scholarly journals Simulation of SEVIRI infrared channels: a case study from the Eyjafjallajökull April/May 2010 eruption

2013 ◽  
Vol 6 (3) ◽  
pp. 649-660 ◽  
Author(s):  
A. Kylling ◽  
R. Buras ◽  
S. Eckhardt ◽  
C. Emde ◽  
B. Mayer ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Satellite Images ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Model Framework ◽  
Retrieval Technique ◽  
Transfer Modelling ◽  
Infrared Radiances

Abstract. Infrared satellite images are widely and successfully used to detect and follow atmospheric ash from erupting volcanoes. We describe a new radiative transfer model framework for the simulation of infrared radiances, which can be compared directly with satellite images. This can be helpful to get insight into the processes that affect the satellite retrievals. As input to the radiative transfer model, the distribution of ash is provided by simulations with the FLEXPART Lagrangian particle dispersion model, meteorological cloud information is adopted from the ECMWF analysis and the radiative transfer modelling is performed with the MYSTIC 3-D radiative transfer model. The model framework is used to study an episode during the Eyjafjallajökull eruption in 2010. It is found that to detect ash by the reverse absorption retrieval technique, accurate representation of the ash particle size distribution is required. Detailed investigation of individual pixels displays the radiative effects of various combinations of ash, liquid water and ice clouds. In order to be clearly detectable, the ash clouds need to be located at some distance above other clouds. If ash clouds are mixed with water clouds or are located only slightly above water clouds, detection of the ash becomes difficult. Simulations were also made using the so-called independent pixel approximation (IPA) instead of the fully 3-D radiative transfer modelling. In the two simulations, different clouds (or different parts of the clouds) or the ground are effectively emitting radiation towards the instrument, thus causing differences in the brightness temperature of up to ± 25 K. The presented model framework is useful for further studies of the processes that affect satellite imagery and may be used to test both new and existing ash retrieval algorithms.

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