scholarly journals Mesoscale inversion: first results from the CERES campaign with synthetic data

2008 ◽  
Vol 8 (13) ◽  
pp. 3459-3471 ◽  
Author(s):  
T. Lauvaux ◽  
M. Uliasz ◽  
C. Sarrat ◽  
F. Chevallier ◽  
P. Bousquet ◽  
...  
Keyword(s):  
Mesoscale Model ◽  
Dispersion Model ◽  
Regional Scale ◽  
Error Reduction ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Co2 Fluxes ◽  
Aircraft Measurements ◽  
Imperfect Knowledge ◽  
The Impact

Abstract. We investigate the ability of a mesoscale model to reconstruct CO2 fluxes at regional scale. Formally, we estimate the reduction of error for a CO2 flux inversion at 8 km resolution in the South West of France, during four days of the CarboEurope Regional Experiment Strategy (CERES) in spring 2005. Measurements from two towers and two airplanes are available for this campaign. The lagrangian particle dispersion model LPDM was coupled to the non-hydrostatic model Meso-NH and integrated in a matrix inversion framework. Impacts of aircraft and tower measurements are quantified separately and together. We find that the configuration with both towers and aircraft is able to significantly reduce uncertainties on the 4-day averaged CO2 fluxes over about half of the 300×300 km2 domain. Most of this reduction comes from the tower measurements, even though the impact of aircraft measurements remains noticeable. Imperfect knowledge of boundary conditions does not significantly impact the error reduction for surface fluxes. We test alternative strategies to improve the impact of aircraft measurements and find that most information comes from measurements inside the boundary layer. We find that there would be a large improvement in error reduction if we could improve our ability to model nocturnal concentrations at tower sites.

scholarly journals Mesoscale inversion: first results from the CERES campaign with synthetic data

2007 ◽  
Vol 7 (4) ◽  
pp. 10439-10465 ◽  
Author(s):  
T. Lauvaux ◽  
M. Uliasz ◽  
C. Sarrat ◽  
F. Chevallier ◽  
P. Bousquet ◽  
...  
Keyword(s):  
Mesoscale Model ◽  
Dispersion Model ◽  
Regional Scale ◽  
Synthetic Data ◽  
Co2 Flux ◽  
Particle Dispersion ◽  
Co2 Fluxes ◽  
Aircraft Measurements ◽  
Imperfect Knowledge ◽  
The Impact

Abstract. We investigate the ability of a mesoscale model to reconstruct CO2 fluxes at regional scale. Formally, we estimate the reduction of error for a CO2 flux inversion at 8 km resolution in the South West of France, during four days of the CarboEurope Regional Experiment (CERES) in spring 2005. Measurements from two towers and two airplanes are available for this campaign. The lagrangian particle dispersion model LPDM was coupled to the non-hydrostatic model Meso-NH and integrated in a matrix inversion framework. Impacts of aircraft and tower measurements are quantified separately and together. We find that the configuration with both towers and aircraft is able to significantly reduce uncertainties on the 4-day averaged CO2 fluxes over about half of the 300×300 km domain. Most of this reduction comes from the tower measurements, even though the impact of aircraft measurements remains noticeable. The noise contributed by imperfect knowledge of boundary inflows does not significantly impair the resolution. We test alternative strategies to improve the impact of aircraft measurements and find that most information comes from measurements inside the boundary layer.

scholarly journals Mesoscale circulations over complex terrain in the Valencia coastal region, Spain – Part 2: Modeling CO<sub>2</sub> transport using idealized surface fluxes

2007 ◽  
Vol 7 (7) ◽  
pp. 1851-1868 ◽  
Author(s):  
G. Pérez-Landa ◽  
P. Ciais ◽  
G. Gangoiti ◽  
J. L. Palau ◽  
A. Carrara ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Transport Model ◽  
Mesoscale Model ◽  
Atmospheric Transport ◽  
Dispersion Model ◽  
Coastal Region ◽  
Net Ecosystem Exchange ◽  
Co2 Concentration ◽  
Particle Dispersion ◽  
Surface Fluxes

Abstract. Vertical profiles of CO2 concentration were collected during an intensive summer campaign in a coastal complex-terrain region within the frame of the European Project RECAB (Regional Assessment and Modelling of the Carbon Balance in Europe). The region presents marked diurnal mesoscale circulation patterns. These circulations result in a specific coupling between atmospherically transported CO2 and its surface fluxes. To understand the effects of this interaction on the spatial variability of the observed CO2 concentrations, we applied a high-resolution transport simulation to an idealized model of land biotic fluxes. The regional Net Ecosystem Exchange fluxes were extrapolated for different land-use classes by using a set of eddy-covariance measurements. The atmospheric transport model is a Lagrangian particle dispersion model, driven by a simulation of the RAMS mesoscale model. Our simulations were able to successfully reproduce some of the processes controlling the mesoscale transport of CO2. A semi-quantitative comparison between simulations and data allowed us to characterize how the coupling between mesoscale transport and surface fluxes produced CO2 spatial gradients in the domain. Temporal averages in the simulated CO2 field show a covariance between flux and transport consisting of: 1) horizontally, a CO2 deficit over land, mirrored by a CO2 excess over the sea and 2) vertically, the prevalence of a mean CO2 depletion between 500 and 2000 m, and a permanent build-up of CO2 in the lower levels.

scholarly journals Regional-scale geostatistical inverse modeling of North American CO<sub>2</sub> fluxes: a synthetic data study

2010 ◽  
Vol 10 (13) ◽  
pp. 6151-6167 ◽  
Author(s):  
S. M. Gourdji ◽  
A. I. Hirsch ◽  
K. L. Mueller ◽  
V. Yadav ◽  
A. E. Andrews ◽  
...  
Keyword(s):  
North America ◽  
Flux Distribution ◽  
Regional Scale ◽  
Measurement Data ◽  
Synthetic Data ◽  
Surface Fluxes ◽  
Co2 Fluxes ◽  
Actual Measurement ◽  
Diurnal Variability ◽  
The Impact

Abstract. A series of synthetic data experiments is performed to investigate the ability of a regional atmospheric inversion to estimate grid-scale CO2 fluxes during the growing season over North America. The inversions are performed within a geostatistical framework without the use of any prior flux estimates or auxiliary variables, in order to focus on the atmospheric constraint provided by the nine towers collecting continuous, calibrated CO2 measurements in 2004. Using synthetic measurements and their associated concentration footprints, flux and model-data mismatch covariance parameters are first optimized, and then fluxes and their uncertainties are estimated at three different temporal resolutions. These temporal resolutions, which include a four-day average, a four-day-average diurnal cycle with 3-hourly increments, and 3-hourly fluxes, are chosen to help assess the impact of temporal aggregation errors on the estimated fluxes and covariance parameters. Estimating fluxes at a temporal resolution that can adjust the diurnal variability is found to be critical both for recovering covariance parameters directly from the atmospheric data, and for inferring accurate ecoregion-scale fluxes. Accounting for both spatial and temporal a priori covariance in the flux distribution is also found to be necessary for recovering accurate a posteriori uncertainty bounds on the estimated fluxes. Overall, the results suggest that even a fairly sparse network of 9 towers collecting continuous CO2 measurements across the continent, used with no auxiliary information or prior estimates of the flux distribution in time or space, can be used to infer relatively accurate monthly ecoregion scale CO2 surface fluxes over North America within estimated uncertainty bounds. Simulated random transport error is shown to decrease the quality of flux estimates in under-constrained areas at the ecoregion scale, although the uncertainty bounds remain realistic. While these synthetic data inversions do not consider all potential issues associated with using actual measurement data, e.g. systematic transport errors or problems with the boundary conditions, they help to highlight the impact of inversion setup choices, and help to provide a baseline set of CO2 fluxes for comparison with estimates from future real-data inversions.

scholarly journals Mesoscale circulations over complex terrain in the Valencia coastal region, Spain, Part 2: linking CO<sub>2</sub> surface fluxes with observed concentrations

2006 ◽  
Vol 6 (2) ◽  
pp. 2853-2895 ◽  
Author(s):  
G. Pérez-Landa ◽  
P. Ciais ◽  
G. Gangoiti ◽  
J. L. Palau ◽  
A. Carrara ◽  
...  
Keyword(s):  
Diurnal Cycle ◽  
Complex Terrain ◽  
Mesoscale Model ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Rectification Effect ◽  
Mesoscale Circulations ◽  
Area Of Interest ◽  
Co2 Concentrations

Abstract. Several consecutive vertical profiles of CO2 concentration and meteorological parameters were collected during an intensive summer campaign in a coastal complex terrain region within the frame of the European Project RECAB (Regional Assessment and Modelling of the Carbon Balance in Europe). The region presents a marked diurnal cycle in the wind flow (analyzed in detail in a companion paper) as a consequence of the development of mesoscale circulations. In terms of the different stages of the diurnal cycle in the meteorology, these circulations result in an important coupling between atmospheric transport and surface CO2 fluxes. To understand the effects of this interaction on the spatial variability of the observed CO2 concentrations, we conduct a high-resolution simulation with a coupled biosphere-atmosphere model in the area of interest during a representative case study. Our model approach consists of estimating the regional NEE distribution by using a set of eddy-covariance measurements that are transported by a mesoscale model coupled to a Lagrangian particle dispersion model. Our simulations were able to successfully reproduce crucial processes controlling the mesoscale transport of CO2. Availability of both simulations and observations for our analysis allowed us to characterize the influence of the coupling between mesoscale circulations and biological processes in the spatial gradients of the CO2 concentrations. Temporal averages in the simulated CO2 distribution show a 3-D rectification effect consisting of: 1) horizontally, a CO2 deficit over land, mirrored by a CO2 excess over the sea and 2) vertically, the prevalence of mean CO2 depletion between 500 and 2000 m, and the permanent build-up of CO2 in the lower levels.

scholarly journals On using radon-222 and CO<sub>2</sub> to calculate regional-scale CO<sub>2</sub> fluxes

2007 ◽  
Vol 7 (14) ◽  
pp. 3737-3747 ◽  
Author(s):  
A. I. Hirsch
Keyword(s):  
Dispersion Model ◽  
Regional Scale ◽  
Radioactive Decay ◽  
Weighted Average ◽  
Co2 Flux ◽  
Particle Dispersion ◽  
Spatial Average ◽  
Co2 Fluxes ◽  
Tracer Method ◽  
Average Flux

Abstract. Because of its ubiquitous release on land and well-characterized atmospheric loss, radon-222 has been very useful for deducing fluxes of greenhouse gases such as CO2, CH4, and N2O. It is shown here that the radon-tracer method, used in previous studies to calculate regional-scale greenhouse gas fluxes, returns a weighted-average flux (the flux field F weighted by the sensitivity of the measurements to that flux field, f) rather than an evenly-weighted spatial average flux. A synthetic data study using a Lagrangian particle dispersion model and modeled CO2 fluxes suggests that the discrepancy between the sensitivity-weighted average flux and evenly-weighted spatial average flux can be significant in the case of CO2, due to covariance between F and f for biospheric CO2 fluxes during the growing season and also for anthropogenic CO2 fluxes in general. A technique is presented to correct the radon-tracer derived fluxes to yield an estimate of evenly-weighted spatial average CO2 fluxes. A new method is also introduced for correcting the CO2 flux estimates for the effects of radon-222 radioactive decay in the radon-tracer method.

scholarly journals On using radon-222 and CO<sub>2</sub> to calculate regional-scale CO<sub>2</sub> fluxes

2006 ◽  
Vol 6 (6) ◽  
pp. 10929-10958 ◽  
Author(s):  
A. I. Hirsch
Keyword(s):  
Dispersion Model ◽  
Regional Scale ◽  
Radioactive Decay ◽  
Weighted Average ◽  
Co2 Flux ◽  
Particle Dispersion ◽  
Spatial Average ◽  
Co2 Fluxes ◽  
Tracer Method ◽  
Average Flux

Abstract. Because of its ubiquitous release on land and well-characterized atmospheric loss, radon-222 has been very useful for deducing fluxes of greenhouse gases such as CO2, CH4, and N2O. It is shown here that the radon-tracer method, used in previous studies to calculate regional-scale greenhouse gas fluxes, returns a weighted-average flux (the flux field F weighted by the sensitivity of the measurements to that flux field, f) rather than an evenly-weighted spatial average flux. A synthetic data study using a Lagrangian particle dispersion model and modeled CO2 fluxes suggests that the discrepancy between the sensitivity-weighted average flux and evenly-weighted spatial average flux can be significant in the case of CO2, due to covariance between F and f for biospheric CO2 fluxes during the growing season and also for anthropogenic CO2 fluxes in general. A technique is presented to correct the radon-tracer derived fluxes to yield an estimate of evenly-weighted spatial average CO2 fluxes. A new method is also introduced for correcting the CO2 flux estimates for the effects of radon-222 radioactive decay in the radon-tracer method.

scholarly journals An extended Kalman-filter for regional scale inverse emission estimation

2011 ◽  
Vol 11 (10) ◽  
pp. 29195-29249 ◽  
Author(s):  
D. Brunner ◽  
S. Henne ◽  
C. A. Keller ◽  
S. Reimann ◽  
M. K. Vollmer ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Dispersion Model ◽  
Regional Scale ◽  
Estimation Method ◽  
Particle Dispersion ◽  
Montreal Protocol ◽  
Correlated Noise ◽  
Temporal Correlations ◽  
Emission Estimation ◽  
Hfc 152A

Abstract. A Kalman-filter based inverse emission estimation method for long-lived trace gases is presented for use in conjunction with a Lagrangian particle dispersion model like FLEXPART. The sequential nature of the approach allows tracing slow seasonal and interannual changes rather than estimating a single period-mean emission field. Other important features include the estimation of a slowly varying concentration background at each measurement station, the possibility to constrain the solution to non-negative emissions, the quantification of uncertainties, the consideration of temporal correlations in the residuals, and the applicability to potentially large inversion problems. The method is first demonstrated for a set of synthetic observations created from a prescribed emission field with different levels of (correlated) noise, which closely mimics true observations. It is then applied to real observations of the three halocarbons HFC-125, HFC-152a and HCFC-141b at the remote research stations Jungfraujoch and Mace Head for the quantification of emissions in Western European countries from 2006 to 2010. Estimated HFC-125 emissions are mostly consistent with national totals reported to the Kyoto protocol and show a generally increasing trend over the considered period. Results for HFC-152a are much more variable with estimated emissions being both higher and lower in different countries. The highest emissions of the order of 1000 Mg yr−1 are estimated for Italy which so far does not report HFC-152a emissions. Emissions of HCFC-141b show a continuing strong decrease as expected due to its ban under the Montreal Protocol. Emissions from France, however, were still rather large (near 1000 Mg yr−1) in the years 2006 and 2007 but strongly declined thereafter.

scholarly journals Identification of Aerosol Sources in Siberia and Study of Aerosol Transport at Regional Scale by Airborne and Space-Borne Lidar Measurement

2020 ◽  
Vol 237 ◽  
pp. 02014
Author(s):  
Antonin Zabukovec ◽  
Gérard Ancellet ◽  
Jacques Pelon ◽  
J.D. Paris ◽  
Iogannes E. Penner ◽  
...  
Keyword(s):  
Forest Fires ◽  
Dispersion Model ◽  
Regional Scale ◽  
Particle Dispersion ◽  
Airborne Lidar ◽  
Orthogonal Polarization ◽  
Lidar Measurement ◽  
Imaging Spectrometer ◽  
Modis Aod ◽  
Moderate Resolution

Airborne lidar measurements were carried out over Siberia in July 2013 and June 2017. Aerosol optical properties are derived using the Lagrangian FLEXible PARTicle dispersion model (FLEXPART) simulations and Moderate Resolution Imaging Spectrometer (MODIS) AOD. Comparison with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol products is used to validate the CALIOP aerosol type identification above Siberia. Two case studies are discussed : a mixture of dust and pollution from Northern Kazakhstan and smoke plumes from forest fires. Comparisons with the CALIOP backscatter ratio show that CALIOP algorithm may overestimate the LR for a dusty mixture if not constrained by an independent AOD measurement.

scholarly journals Greenhouse gas network design using backward Lagrangian particle dispersion modelling − Part 1: Methodology and Australian test case

2014 ◽  
Vol 14 (17) ◽  
pp. 9363-9378 ◽  
Author(s):  
T. Ziehn ◽  
A. Nickless ◽  
P. J. Rayner ◽  
R. M. Law ◽  
G. Roff ◽  
...  
Keyword(s):  
Network Design ◽  
Fossil Fuel ◽  
Dispersion Model ◽  
Surface Flux ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Test Case ◽  
Lagrangian Particle ◽  
Gas Network ◽  
Australian Continent

Abstract. This paper describes the generation of optimal atmospheric measurement networks for determining carbon dioxide fluxes over Australia using inverse methods. A Lagrangian particle dispersion model is used in reverse mode together with a Bayesian inverse modelling framework to calculate the relationship between weekly surface fluxes, comprising contributions from the biosphere and fossil fuel combustion, and hourly concentration observations for the Australian continent. Meteorological driving fields are provided by the regional version of the Australian Community Climate and Earth System Simulator (ACCESS) at 12 km resolution at an hourly timescale. Prior uncertainties are derived on a weekly timescale for biosphere fluxes and fossil fuel emissions from high-resolution model runs using the Community Atmosphere Biosphere Land Exchange (CABLE) model and the Fossil Fuel Data Assimilation System (FFDAS) respectively. The influence from outside the modelled domain is investigated, but proves to be negligible for the network design. Existing ground-based measurement stations in Australia are assessed in terms of their ability to constrain local flux estimates from the land. We find that the six stations that are currently operational are already able to reduce the uncertainties on surface flux estimates by about 30%. A candidate list of 59 stations is generated based on logistic constraints and an incremental optimisation scheme is used to extend the network of existing stations. In order to achieve an uncertainty reduction of about 50%, we need to double the number of measurement stations in Australia. Assuming equal data uncertainties for all sites, new stations would be mainly located in the northern and eastern part of the continent.

Assimilation of GPS Radio Occultation Refractivity Data from CHAMP and SAC-C Missions over High Southern Latitudes with MM5 4DVAR

2008 ◽  
Vol 136 (8) ◽  
pp. 2923-2944 ◽  
Author(s):  
Tae-Kwon Wee ◽  
Ying-Hwa Kuo ◽  
David H. Bromwich ◽  
Andrew J. Monaghan
Keyword(s):  
Radio Occultation ◽  
Ross Sea ◽  
Mesoscale Model ◽  
Positive Impact ◽  
Extended Period ◽  
Error Reduction ◽  
Specific Humidity ◽  
Subtle Change ◽  
Gps Radio Occultation ◽  
The Impact

Abstract In this study, the GPS radio occultation (RO) data from the Challenging Minisatellite Payload (CHAMP) and Satellite de Aplicaciones Cientificas-C (SAC-C) missions are assimilated. An updated version of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) four-dimensional variational data assimilation system (4DVAR) is used to assess the impact of the GPS RO data on analyses and short-range forecasts over the Antarctic. The study was performed during the period of intense cyclonic activity in the Ross Sea, 9–19 December 2001. On average 66 GPS RO soundings were assimilated daily. For the assimilation over a single 12-h period, the impact of GPS RO data was only marginally positive or near neutral, and it varied markedly from one 12-h period to another. The large case-to-case variation was attributed to the low number of GPS RO soundings and a strong dependency of forecast impact on the location of the soundings relative to the rapidly developing cyclone. Despite the moderate general impact, noticeable reduction of temperature error in the upper troposphere and lower stratosphere was found, which demonstrates the value of GPS RO data in better characterizing the tropopause. Significant error reduction was also noted in geopotential height and wind fields in the stratosphere. Those improvements indicate that early detection of the upper-level precursors for storm development is a potential benefit of GPS RO data. When the assimilation period was extended to 48 h, a considerable positive impact of GPS RO data was found. All parameters that were investigated (i.e., temperature, pressure, and specific humidity) showed the positive impact throughout the entire model atmosphere for forecasts extending up to 5 days. The impact increased in proportion to the length of the assimilation period. Although the differences in the analyses as a result of GPS RO assimilation were relatively small initially, the subtle change and subsequent nonlinear growth led to noticeable forecast improvements at longer ranges. Consequently, the positive impact of GPS RO data was more evident in longer-range (e.g., greater than 2 days) forecasts. A correlation coefficient is introduced to quantify the linear relationship between the analysis errors without GPS RO assimilation and the analysis increments induced by GPS RO assimilation. This measure shows that the growth of GPS RO–induced modifications over time is related to the prominent error reduction observed in GPS RO experiments. The measure may also be useful for understanding how cycling analysis accumulates the positive impact of GPS RO data for an extended period of assimilation.

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