scholarly journals The constraint of CO<sub>2</sub> measurements made onboard passenger aircraft on surface-atmosphere fluxes: the impact of transport model errors in vertical mixing

2016 ◽  
Author(s):  
Shreeya Verma ◽  
Julia Marshall ◽  
Christoph Gerbig ◽  
Christian Roedenbeck ◽  
Kai Uwe Totsche
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
Vertical Mixing ◽  
Synthetic Data ◽  
Vertical Profiles ◽  
Model Errors ◽  
Transport Models ◽  
Boundary Layer Height ◽  
Temporal Sampling ◽  
The Impact

Abstract. Inaccurate representation of atmospheric processes by transport models is a dominant source of uncertainty in inverse analyses and can lead to large discrepancies in the retrieved flux estimates. We investigate the impact of uncertainties in vertical transport as simulated by atmospheric transport models on fluxes retrieved using vertical profiles from aircraft as an observational constraint. Our numerical experiments are based on synthetic data with realistic spatial and temporal sampling of aircraft measurements. The impact of such uncertainties on the flux retrieved using the ground-based network with those retrieved using the aircraft profiles are compared. We find that the posterior flux retrieved using aircraft profiles is less susceptible to errors in boundary layer height as compared to the ground- based network. This highlights the benefit of utilizing atmospheric observations made onboard aircraft over surface measurements for flux estimation using inverse methods. We further use synthetic vertical profiles of CO2 in an inversion to estimate the potential of these measurements, which will be made available through the IAGOS (In-Service Aircraft for a Global Observing System) project in future, in constraining the regional carbon budget. Our results show that the regions tropical Africa and temperate Eurasia, that are under constrained by the existing surface based network, will benefit the most from these measurements, the reduction of posterior flux uncertainty being about 7 to 10 %.

scholarly journals The constraint of CO<sub>2</sub> measurements made onboard passenger aircraft on surface–atmosphere fluxes: the impact of transport model errors in vertical mixing

2017 ◽  
Vol 17 (9) ◽  
pp. 5665-5675 ◽  
Author(s):  
Shreeya Verma ◽  
Julia Marshall ◽  
Christoph Gerbig ◽  
Christian Rödenbeck ◽  
Kai Uwe Totsche
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
Vertical Mixing ◽  
Synthetic Data ◽  
Vertical Profiles ◽  
Model Errors ◽  
Transport Models ◽  
Boundary Layer Height ◽  
Temporal Sampling ◽  
The Impact

Abstract. Inaccurate representation of atmospheric processes by transport models is a dominant source of uncertainty in inverse analyses and can lead to large discrepancies in the retrieved flux estimates. We investigate the impact of uncertainties in vertical transport as simulated by atmospheric transport models on fluxes retrieved using vertical profiles from aircraft as an observational constraint. Our numerical experiments are based on synthetic data with realistic spatial and temporal sampling of aircraft measurements. The impact of such uncertainties on the flux retrieved using the ground-based network and those retrieved using the aircraft profiles are compared. We find that the posterior flux retrieved using aircraft profiles is less susceptible to errors in boundary layer height, compared to the ground-based network. This finding highlights a benefit of utilizing atmospheric observations made onboard aircraft over surface measurements for flux estimation using inverse methods. We further use synthetic vertical profiles of CO2 in an inversion to estimate the potential of these measurements, which will be made available through the IAGOS (In-service Aircraft for a Global Observing System) project in the future, in constraining the regional carbon budget. Our results show that the regions of tropical Africa and temperate Eurasia, that are under-constrained by the existing surface-based network, will benefit the most from these measurements, with a reduction of posterior flux uncertainty of about 7 to 10 %.

scholarly journals The importance of transport model uncertainties for the estimation of CO<sub>2</sub> sources and sinks using satellite measurements

2010 ◽  
Vol 10 (20) ◽  
pp. 9981-9992 ◽  
Author(s):  
S. Houweling ◽  
I. Aben ◽  
F.-M. Breon ◽  
F. Chevallier ◽  
N. Deutscher ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
A Priori ◽  
Model Errors ◽  
Tracer Transport ◽  
Satellite Measurements ◽  
Transport Models ◽  
Sources And Sinks ◽  
The Impact ◽  
Ppm Level

Abstract. This study presents a synthetic model intercomparison to investigate the importance of transport model errors for estimating the sources and sinks of CO2 using satellite measurements. The experiments were designed for testing the potential performance of the proposed CO2 lidar A-SCOPE, but also apply to other space borne missions that monitor total column CO2. The participating transport models IFS, LMDZ, TM3, and TM5 were run in forward and inverse mode using common a priori CO2 fluxes and initial concentrations. Forward simulations of column averaged CO2 (xCO2) mixing ratios vary between the models by σ=0.5 ppm over the continents and σ=0.27 ppm over the oceans. Despite the fact that the models agree on average on the sub-ppm level, these modest differences nevertheless lead to significant discrepancies in the inverted fluxes of 0.1 PgC/yr per 106 km2 over land and 0.03 PgC/yr per 106 km2 over the ocean. These transport model induced flux uncertainties exceed the target requirement that was formulated for the A-SCOPE mission of 0.02 PgC/yr per 106 km2, and could also limit the overall performance of other CO2 missions such as GOSAT. A variable, but overall encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen, although systematic differences are found exceeding the 0.5 ppm level. Because of this, our estimate of the impact of transport model uncerainty is likely to be conservative. It is concluded that to make use of the remote sensing technique for quantifying the sources and sinks of CO2 not only requires highly accurate satellite instruments, but also puts stringent requirements on the performance of atmospheric transport models. Improving the accuracy of these models should receive high priority, which calls for a closer collaboration between experts in atmospheric dynamics and tracer transport.

scholarly journals Sensitivity of simulated CO<sub>2</sub> concentration to sub-annual variations in fossil fuel CO<sub>2</sub> emissions

2016 ◽  
Vol 16 (4) ◽  
pp. 1907-1918 ◽  
Author(s):  
Xia Zhang ◽  
Kevin R. Gurney ◽  
Peter Rayner ◽  
David Baker ◽  
Yu-ping Liu
Keyword(s):  
Fossil Fuel ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Vertical Mixing ◽  
Grid Cell ◽  
Co2 Concentration ◽  
Tracer Transport ◽  
Annual Variations ◽  
Atmospheric Co2 Concentrations ◽  
The Impact

Abstract. Recent advances in fossil fuel CO2 (FFCO2) emission inventories enable sensitivity tests of simulated atmospheric CO2 concentrations to sub-annual variations in FFCO2 emissions and what this implies for the interpretation of observed CO2. Six experiments are conducted to investigate the potential impact of three cycles of FFCO2 emission variability (diurnal, weekly and monthly) using a global tracer transport model. Results show an annual FFCO2 rectification varying from −1.35 to +0.13 ppm from the combination of all three cycles. This rectification is driven by a large negative diurnal FFCO2 rectification due to the covariation of diurnal FFCO2 emissions and diurnal vertical mixing, as well as a smaller positive seasonal FFCO2 rectification driven by the covariation of monthly FFCO2 emissions and monthly atmospheric transport. The diurnal FFCO2 emissions are responsible for a diurnal FFCO2 concentration amplitude of up to 9.12 ppm at the grid cell scale. Similarly, the monthly FFCO2 emissions are responsible for a simulated seasonal CO2 amplitude of up to 6.11 ppm at the grid cell scale. The impact of the diurnal FFCO2 emissions, when only sampled in the local afternoon, is also important, causing an increase of +1.13 ppmv at the grid cell scale. The simulated CO2 concentration impacts from the diurnally and seasonally varying FFCO2 emissions are centered over large source regions in the Northern Hemisphere, extending to downwind regions. This study demonstrates the influence of sub-annual variations in FFCO2 emissions on simulated CO2 concentration and suggests that inversion studies must take account of these variations in the affected regions.

scholarly journals Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling

2013 ◽  
Vol 13 (4) ◽  
pp. 10961-11021
Author(s):  
R. Locatelli ◽  
P. Bousquet ◽  
F. Chevallier ◽  
A. Fortems-Cheney ◽  
S. Szopa ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
Spatial Scales ◽  
Global Scale ◽  
Methane Emissions ◽  
Inverse Modelling ◽  
Model Errors ◽  
Inverse Systems ◽  
Set Up ◽  
The Impact

Abstract. A modelling experiment has been conceived to assess the impact of transport model errors on the methane emissions estimated by an atmospheric inversion system. Synthetic methane observations, given by 10 different model outputs from the international TransCom-CH4 model exercise, are combined with a prior scenario of methane emissions and sinks, and integrated into the PYVAR-LMDZ-SACS inverse system to produce 10 different methane emission estimates at the global scale for the year 2005. The same set-up has been used to produce the synthetic observations and to compute flux estimates by inverse modelling, which means that only differences in the modelling of atmospheric transport may cause differences in the estimated fluxes. In our framework, we show that transport model errors lead to a discrepancy of 27 Tg CH4 per year at the global scale, representing 5% of the total methane emissions. At continental and yearly scales, transport model errors have bigger impacts depending on the region, ranging from 36 Tg CH4 in north America to 7 Tg CH4 in Boreal Eurasian (from 23% to 48%). At the model gridbox scale, the spread of inverse estimates can even reach 150% of the prior flux. Thus, transport model errors contribute to significant uncertainties on the methane estimates by inverse modelling, especially when small spatial scales are invoked. Sensitivity tests have been carried out to estimate the impact of the measurement network and the advantage of higher resolution models. The analysis of methane estimated fluxes in these different configurations questions the consistency of transport model errors in current inverse systems. For future methane inversions, an improvement in the modelling of the atmospheric transport would make the estimations more accurate. Likewise, errors of the observation covariance matrix should be more consistently prescribed in future inversions in order to limit the impact of transport model errors on estimated methane fluxes.

scholarly journals Error characterization of CO<sub>2</sub> vertical mixing in the atmospheric transport model WRF-VPRM

2012 ◽  
Vol 12 (5) ◽  
pp. 2441-2458 ◽  
Author(s):  
R. Kretschmer ◽  
C. Gerbig ◽  
U. Karstens ◽  
F.-T. Koch
Keyword(s):  
Transport Model ◽  
Vertical Mixing ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Model Errors ◽  
Simple Method ◽  
European Continent ◽  
Mixing Ratios ◽  
Error Characterization ◽  
The Impact

Abstract. One of the dominant uncertainties in inverse estimates of regional CO2 surface-atmosphere fluxes is related to model errors in vertical transport within the planetary boundary layer (PBL). In this study we present the results from a synthetic experiment using the atmospheric model WRF-VPRM to realistically simulate transport of CO2 for large parts of the European continent at 10 km spatial resolution. To elucidate the impact of vertical mixing error on modeled CO2 mixing ratios we simulated a month during the growing season (August 2006) with different commonly used parameterizations of the PBL (Mellor-Yamada-Janjić (MYJ) and Yonsei-University (YSU) scheme). To isolate the effect of transport errors we prescribed the same CO2 surface fluxes for both simulations. Differences in simulated CO2 mixing ratios (model bias) were on the order of 3 ppm during daytime with larger values at night. We present a simple method to reduce this bias by 70–80% when the true height of the mixed layer is known.

scholarly journals Using boundary layer equilibrium to reduce uncertainties in transport models and CO<sub>2</sub> flux inversions

2011 ◽  
Vol 11 (18) ◽  
pp. 9631-9641 ◽  
Author(s):  
I. N. Williams ◽  
W. J. Riley ◽  
M. S. Torn ◽  
J. A. Berry ◽  
S. C. Biraud
Keyword(s):  
Boundary Layer ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Vertical Mixing ◽  
Systematic Errors ◽  
Surface Fluxes ◽  
Concentration Gradients ◽  
Layer Depth ◽  
Transport Models ◽  
Mixing Rates

Abstract. This paper reexamines evidence for systematic errors in atmospheric transport models, in terms of the diagnostics used to infer vertical mixing rates from models and observations. Different diagnostics support different conclusions about transport model errors that could imply either stronger or weaker northern terrestrial carbon sinks. Conventional mixing diagnostics are compared to analyzed vertical mixing rates using data from the US Southern Great Plains Atmospheric Radiation Measurement Climate Research Facility, the CarbonTracker data assimilation system based on Transport Model version 5 (TM5), and atmospheric reanalyses. The results demonstrate that diagnostics based on boundary layer depth and vertical concentration gradients do not always indicate the vertical mixing strength. Vertical mixing rates are anti-correlated with boundary layer depth at some sites, diminishing in summer when the boundary layer is deepest. Boundary layer equilibrium concepts predict an inverse proportionality between CO2 vertical gradients and vertical mixing strength, such that previously reported discrepancies between observations and models most likely reflect overestimated as opposed to underestimated vertical mixing. However, errors in seasonal concentration gradients can also result from errors in modeled surface fluxes. This study proposes using the timescale for approach to boundary layer equilibrium to diagnose vertical mixing independently of seasonal surface fluxes, with applications to observations and model simulations of CO2 or other conserved boundary layer tracers with surface sources and sinks. Results indicate that frequently cited discrepancies between observations and inverse estimates do not provide sufficient proof of systematic errors in atmospheric transport models. Some previously hypothesized transport model biases, if found and corrected, could cause inverse estimates to further diverge from carbon inventory estimates of terrestrial sinks.

scholarly journals Sensitivity of simulated CO2 concentration to sub-annual variations in fossil fuel CO2 emissions

2015 ◽  
Vol 15 (14) ◽  
pp. 20679-20708 ◽  
Author(s):  
X. Zhang ◽  
K. R. Gurney ◽  
P. Rayner ◽  
D. Baker ◽  
Y.-P. Liu
Keyword(s):  
Fossil Fuel ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Vertical Mixing ◽  
Grid Cell ◽  
Co2 Concentration ◽  
Tracer Transport ◽  
Annual Variations ◽  
Atmospheric Co2 Concentrations ◽  
The Impact

Abstract. Recent advances in fossil fuel CO2 (FFCO2) emission inventories enable sensitivity tests of simulated atmospheric CO2 concentrations to sub-annual variations in FFCO2 emissions and what this implies for the interpretation of observed CO2. Six experiments are conducted to investigate the potential impact of three cycles of FFCO2 emission variability (diurnal, weekly and monthly) using a global tracer transport model. Results show an annual FFCO2 rectification varying from −1.35 to +0.13 ppm from the combination of all three cycles. This rectification is driven by a large negative diurnal FFCO2 rectification due to the covariation of diurnal FFCO2 emissions and diurnal vertical mixing, and a smaller positive seasonal FFCO2 rectification driven by the covariation of monthly FFCO2 emissions and monthly atmospheric transport. The diurnal FFCO2 emissions are responsible for a diurnal FFCO2 concentration amplitude of up to 9.12 ppm at the grid cell scale. Similarly, the monthly FFCO2 emissions are responsible for a simulated seasonal CO2 amplitude of up to 6.11 ppm at the grid cell scale. The impact of the diurnal FFCO2 emissions, when only sampled in the local afternoon is also important, causing an increase of +1.13 ppmv at the grid cell scale. The simulated CO2 concentration impacts from the diurnally and seasonally-varying FFCO2 emissions are centered over large source regions in the Northern Hemisphere, extending to downwind regions. This study demonstrates the influence of sub-annual variations in FFCO2 emissions on simulated CO2 concentration and suggests that inversion studies must take account of these variations in the affected regions.

scholarly journals Error characterization of CO2 vertical mixing in the atmospheric transport model WRF-VPRM

2011 ◽  
Vol 11 (10) ◽  
pp. 28169-28217
Author(s):  
R. Kretschmer ◽  
C. Gerbig ◽  
U. Karstens ◽  
F.-T. Koch
Keyword(s):  
Transport Model ◽  
Vertical Mixing ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Model Errors ◽  
Simple Method ◽  
European Continent ◽  
Mixing Ratios ◽  
Error Characterization ◽  
The Impact

Abstract. One of the dominant uncertainties in inverse estimates of regional CO2 surface-atmosphere fluxes is related to model errors in vertical transport within the planetary boundary layer (PBL). In this study we present the results from a synthetic experiment using the atmospheric model WRF-VPRM to realistically simulate transport of CO2 for large parts of the European continent at 10 km spatial resolution. To elucidate the impact of vertical mixing error on modeled CO2 mixing ratios we simulated a month during the growing season (August 2006) with different commonly used parameterizations of the PBL (Mellor-Yamada-Janjic (MYJ) and Yonsei-University (YSU) scheme). To isolate the effect of transport errors we prescribed the same CO2 surface fluxes for both simulations. Differences in simulated CO2 mixing ratios (model bias) were on the order of 3 ppm during daytime with larger values during night. We present a simple method to reduce this bias by 70–80% when the true height of the mixed layer is known.

scholarly journals Using boundary layer equilibrium to reduce uncertainties in transport models and CO<sub>2</sub> flux inversions

2011 ◽  
Vol 11 (4) ◽  
pp. 11455-11495 ◽  
Author(s):  
I. N. Williams ◽  
W. J. Riley ◽  
M. S. Torn ◽  
J. A. Berry ◽  
S. C. Biraud
Keyword(s):  
Boundary Layer ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Vertical Mixing ◽  
Co2 Flux ◽  
Surface Fluxes ◽  
Layer Depth ◽  
Transport Models ◽  
Mixing Rates ◽  
Systematic Biases

Abstract. This paper reexamines evidence for previously hypothesized errors in atmospheric transport models and CO2 flux inversions by evaluating the diagnostics used to infer vertical mixing rates from observations. Several conventional mixing diagnostics are compared to analyzed mixing using data from the US Southern Great Plains Atmospheric Radiation Measurement Climate Research Facility, the CarbonTracker data assimilation system based on Transport Model version 5 (TM5), and atmospheric reanalyses. The results demonstrate that previous diagnostics based on boundary layer depth and vertical concentration gradients are unreliable indicators of vertical mixing. Vertical mixing rates are anti-correlated with boundary layer depth at some sites, diminishing in summer when the boundary layer is deepest. Vertical CO2 gradients between the boundary layer and free-troposphere are strongly affected by seasonal surface fluxes and therefore do not accurately reflect vertical mixing rates. The finite timescale over which vertical tracer gradients relax toward equilibrium is proposed as an improved mixing diagnostic, which can be applied to observations and model simulations of CO2 or other conserved boundary layer tracers with surface sources and sinks. This diagnostic does not require dynamical variables from the transport models, and is independent of possible systematic biases in prior- and post-inversion seasonal surface fluxes. Results indicate that observations frequently cited as evidence for systematic biases in atmospheric transport models are insufficient to prove that such biases exist. Some previously hypothesized transport model biases, if found and corrected, could cause inverse estimates to further diverge from land-based estimates.

scholarly journals Evaluation of the boundary layer dynamics of the TM5 model

2016 ◽  
Author(s):  
E. N. Koffi ◽  
P. Bergamaschi ◽  
U. Karstens ◽  
M. Krol ◽  
A. Segers ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Activity Concentration ◽  
Transition Period ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Vertical Mixing ◽  
Activity Concentrations ◽  
Boundary Layer Dynamics ◽  
Relative Differences ◽  
The Impact

Abstract. We evaluate the capability of the global atmospheric transport model TM5 to reproduce observations of the boundary layer dynamics and the associated variability of trace gases close to the surface, using radon (222Rn), which is an excellent tracer for vertical mixing owing to its short lifetime (half-life) of 3.82 days. Focusing on the European scale, we compare the boundary layer height (BLH) in the TM5 model with observations from the NOAA Integrated Global Radiosonde Archive (IGRA) and in addition with ceilometer measurements at Cabauw (The Netherlands) and lidar BLH retrievals at Trainou (France). Furthermore, we compare TM5 simulations of 222Rn activity concentrations, using a novel, process-based 222Rn flux map over Europe (Karstens et al., 2015), with quasi-continuous 222Rn measurements from 10 European monitoring stations. The TM5 model reproduces relatively well the daytime BLH (within ~ 10–20 % for most of the stations), except for coastal sites, for which differences are usually larger due to model representation errors. During night, TM5 overestimates the shallow nocturnal BLHs, especially for the very low observed BLHs (< 100 m) during summer. The 222Rn activity concentration simulations based on the new 222Rn flux map show significant improvements especially regarding the average seasonal variability, compared to simulations using constant 222Rn fluxes. Nevertheless, the (relative) differences between simulated and observed daytime minimum 222Rn activity concentrations are larger for several stations (on the order of 50 %) compared to the (relative) differences between simulated and observed BLH at noon. Although the nocturnal BLH is often higher in the model than observed, simulated 222Rn nighttime maxima are larger at several continental stations, which points to potential deficiencies of TM5 to correctly simulate the vertical gradients within the nocturnal boundary layer, limitations of the 222Rn flux map, or issues related to the definition of the nocturnal BLH. At several stations the simulated decrease of 222Rn activity concentrations in the morning is faster than observed. In addition, simulated vertical 222Rn activity concentration gradients at Cabauw decrease faster than observations during the morning transition period, and are in general lower than observed gradients during daytime, which points to too fast vertical mixing in the TM5 boundary layer during daytime. Furthermore, the capability of the TM5 model to simulate the diurnal BLH cycle is limited due to the current coarse temporal resolution (3 hr/6 hr) of the TM5 input meteorology. Additionally, we analyze the impact of a new treatment of convection in TM5, based on the ECMWF reanalysis, leading to overall significantly lower (on the order of ~ 20 %) surface 222Rn activity concentrations during daytime compared to the current default convection scheme based on Tiedtke (1989). However, the performance of the model simulations compared to the 222Rn observations is very similar in terms of root mean square and correlation coefficient for both convection schemes.

Sign in / Sign up

Export Citation Format

Share Document