Challenges in Linking Atmospheric CO2 Concentrations to Fluxes at Local and Regional Scales

1992 ◽  
Vol 40 (5) ◽  
pp. 697 ◽  
Author(s):  
MR Raupach ◽  
OT Denmead ◽  
FX Dunin
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Co2 Flux ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Wheat Crop ◽  
Turbulent Transfer ◽  
Near Surface ◽  
Scalar Dispersion ◽  
Source Sink

We describe relationships between atmospheric CO2 concentration variations and CO2 source-sink distributions, at two important scales between the single plant and the whole earth: the vegetation canopy and the atmospheric planetary boundary layer. For both these scales, it is shown how knowledge of turbulence and scalar dispersion can be applied to infer CO2 source-sink distributions or fluxes from concentration measurements. At the canopy scale, the turbulent transfer of CO2 and other scalars is non-diffusive close to any point source or sink in the canopy, but diffusive at greater distances. This distinction leads to a physically tenable description of turbulent transfer, and thence to an 'inverse method' for finding the vertical profiles of sources and sinks in the canopy from measured concentration profiles. The method is tested with data from a wheat crop. At the scale of the planetary boundary layer, we consider the daily CO2 concentration drawdown (the depression of the near-surface CO2 concentration below the free-atmosphere value) of typically 20-40 ppm. This is determined by both the regionally averaged CO2 uptake at the surface and the growth of the daytime convective boundary layer (CBL). It is shown that, for a column of air which fills the CBL and is moved across the landscape by the mean wind, the net cumulative surface CO2 flux (in mol m-2) is given to a good approximation by h(t)[Cm(t) - C+]/V, where h(t) is CBL depth, Cm(t) the CO2 concentration in the CBL column in mol mol-1, C+ the concentration above the CBL, V the molar volume and time t is measured from the time at which Cm = C+ in the morning, typically about 0800 hours local time. The resulting CO2 flux estimates are regionally averaged over the trajectory followed by the column. This 'CBL budget method' for inferring surface fluxes is compared with direct measurements of CO2 fluxes, with satisfactory results. The technique has application to scalars other than CO2.

scholarly journals Impact of physical parameterizations and initial conditions on simulated atmospheric transport and CO<sub>2</sub> mole fractions in the US Midwest

2018 ◽  
Vol 18 (20) ◽  
pp. 14813-14835 ◽  
Author(s):  
Liza I. Díaz-Isaac ◽  
Thomas Lauvaux ◽  
Kenneth J. Davis
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Boundary Conditions ◽  
Planetary Boundary Layer ◽  
Initial Conditions ◽  
Atmospheric Transport ◽  
Atmospheric Co2 ◽  
The Us ◽  
Physics Parameterizations ◽  
Physical Parameterizations

Abstract. Atmospheric transport model errors are one of the main contributors to the uncertainty affecting CO2 inverse flux estimates. In this study, we determine the leading causes of transport errors over the US upper Midwest with a large set of simulations generated with the Weather Research and Forecasting (WRF) mesoscale model. The various WRF simulations are performed using different meteorological driver datasets and physical parameterizations including planetary boundary layer (PBL) schemes, land surface models (LSMs), cumulus parameterizations and microphysics parameterizations. All the different model configurations were coupled to CO2 fluxes and lateral boundary conditions from the CarbonTracker inversion system to simulate atmospheric CO2 mole fractions. PBL height, wind speed, wind direction, and atmospheric CO2 mole fractions are compared to observations during a month in the summer of 2008, and statistical analyses were performed to evaluate the impact of both physics parameterizations and meteorological datasets on these variables. All of the physical parameterizations and the meteorological initial and boundary conditions contribute 3 to 4 ppm to the model-to-model variability in daytime PBL CO2 except for the microphysics parameterization which has a smaller contribution. PBL height varies across ensemble members by 300 to 400 m, and this variability is controlled by the same physics parameterizations. Daily PBL CO2 mole fraction errors are correlated with errors in the PBL height. We show that specific model configurations systematically overestimate or underestimate the PBL height averaged across the region with biases closely correlated with the choice of LSM, PBL scheme, and cumulus parameterization (CP). Domain average PBL wind speed is overestimated in nearly every model configuration. Both planetary boundary layer height (PBLH) and PBL wind speed biases show coherent spatial variations across the Midwest, with PBLH overestimated averaged across configurations by 300–400 m in the west, and PBL winds overestimated by about 1 m s−1 on average in the east. We find model configurations with lower biases averaged across the domain, but no single configuration is optimal across the entire region and for all meteorological variables. We conclude that model ensembles that include multiple physics parameterizations and meteorological initial conditions are likely to be necessary to encompass the atmospheric conditions most important to the transport of CO2 in the PBL, but that construction of such an ensemble will be challenging due to ensemble biases that vary across the region.

scholarly journals The potential for regional-scale bias in top-down CO<sub>2</sub> flux estimates due to atmospheric transport errors

2014 ◽  
Vol 14 (16) ◽  
pp. 23681-23709
Author(s):  
S. M. Miller ◽  
I. Fung ◽  
J. Liu ◽  
M. N. Hayek ◽  
A. E. Andrews
Keyword(s):  
Boundary Layer ◽  
Atmospheric Transport ◽  
Regional Scale ◽  
Co2 Flux ◽  
Atmospheric Co2 ◽  
Co2 Fluxes ◽  
Atmospheric Measurements ◽  
Meteorological Model ◽  
Co2 Transport

Abstract. Estimates of CO2 fluxes that are based on atmospheric data rely upon a meteorological model to simulate atmospheric CO2 transport. These models provide a quantitative link between surface fluxes of CO2 and atmospheric measurements taken downwind. Therefore, any errors in the meteorological model can propagate into atmospheric CO2 transport and ultimately bias the estimated CO2 fluxes. These errors, however, have traditionally been difficult to characterize. To examine the effects of CO2 transport errors on estimated CO2 fluxes, we use a global meteorological model-data assimilation system known as "CAM–LETKF" to quantify two aspects of the transport errors: error variances (standard deviations) and temporal error correlations. Furthermore, we develop two case studies. In the first case study, we examine the extent to which CO2 transport uncertainties can bias CO2 flux estimates. In particular, we use a common flux estimate known as CarbonTracker to discover the minimum hypothetical bias that can be detected above the CO2 transport uncertainties. In the second case study, we then investigate which meteorological conditions may contribute to month-long biases in modeled atmospheric transport. We estimate 6 hourly CO2 transport uncertainties in the model surface layer that range from 0.15 to 9.6 ppm (standard deviation), depending on location, and we estimate an average error decorrelation time of ∼2.3 days at existing CO2 observation sites. As a consequence of these uncertainties, we find that CarbonTracker CO2 fluxes would need to be biased by at least 29%, on average, before that bias were detectable at existing non-marine atmospheric CO2 observation sites. Furthermore, we find that persistent, bias-type errors in atmospheric transport are associated with consistent low net radiation, low energy boundary layer conditions. The meteorological model is not necessarily more uncertain in these conditions. Rather, the extent to which meteorological uncertainties manifest as persistent atmospheric transport biases appears to depend, at least in part, on the energy and stability of the boundary layer. Existing CO2 flux studies may be more likely to estimate inaccurate regional fluxes under those conditions.

scholarly journals Forecasting global atmospheric CO<sub>2</sub>

2014 ◽  
Vol 14 (9) ◽  
pp. 13909-13962 ◽  
Author(s):  
A. Agustí-Panareda ◽  
S. Massart ◽  
F. Chevallier ◽  
S. Boussetta ◽  
G. Balsamo ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Real Time ◽  
Diurnal Cycle ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Physical Models ◽  
Atmospheric Co2 ◽  
Co2 Fluxes ◽  
Near Surface ◽  
Forecasting System

Abstract. A new global atmospheric carbon dioxide (CO2) real-time forecast is now available as part of the pre-operational Monitoring of Atmospheric Composition and Climate – Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO2 forecasting system is that the land surface, including vegetation CO2 fluxes, is modelled online within the IFS. Other CO2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO2 fluxes also lead to accumulating errors in the CO2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO2 fluxes compared to total optimized fluxes and the atmospheric CO2 compared to observations. The largest biases in the atmospheric CO2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO2 analyses based on the assimilation of CO2 satellite retrievals, as they become available in near-real time. In this way, the accumulation of errors in the atmospheric CO2 forecast will be reduced. Improvements in the CO2 forecast are also expected with the continuous developments in the operational IFS.

scholarly journals Carbon balance of China constrained by CONTRAIL aircraft CO<sub>2</sub> measurements

2014 ◽  
Vol 14 (6) ◽  
pp. 7683-7709
Author(s):  
F. Jiang ◽  
H. M. Wang ◽  
J. M. Chen ◽  
T. Machida ◽  
L. X. Zhou ◽  
...  
Keyword(s):  
Transport Model ◽  
Carbon Sink ◽  
Terrestrial Ecosystem ◽  
Co2 Flux ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Inversion Method ◽  
Climate Factors ◽  
Mean Climate ◽  
Atmospheric Co2 Concentrations

Abstract. Terrestrial CO2 flux estimates in China using atmospheric inversion method are beset with considerable uncertainties because very few atmospheric CO2 concentration measurements are available. In order to improve these estimates, nested atmospheric CO2 inversion during 2002–2008 is performed in this study using passenger aircraft-based CO2 measurements over Eurasia from the Comprehensive Observation Network for Trace gases by Airliner (CONTRAIL) project. The inversion system includes 43 regions with a focus on China, and is based on the Bayesian synthesis approach and the TM5 transport model. The terrestrial ecosystem carbon flux modeled by the BEPS model and the ocean exchange simulated by the OPA-PISCES-T model are considered as the prior fluxes. The impacts of CONTRAIL CO2 data on inverted China terrestrial carbon fluxes are quantified, the improvement of the inverted fluxes after adding CONTRAIL CO2 data are rationed against climate factors and evaluated by comparing the simulated atmospheric CO2 concentrations with three independent surface CO2 measurements in China. Results show that with the addition of CONTRAIL CO2 data, the inverted carbon sink in China increases while those in South and Southeast Asia decrease. Meanwhile, the posterior uncertainties over these regions are all reduced. CONTRAIL CO2 data also have a large effect on the inter-annual variation of carbon sinks in China, leading to a better correlation between the carbon sink and the annual mean climate factors. Evaluations against the CO2 measurements at three sites in China also show that the CONTRAIL CO2 measurements have improved the inversion results.

scholarly journals Sensitivity of the air–sea CO<sub>2</sub> exchange in the Baltic Sea and Danish inner waters to atmospheric short term variability

2014 ◽  
Vol 11 (12) ◽  
pp. 16993-17042
Author(s):  
A. S. Lansø ◽  
J. Bendtsen ◽  
J. H. Christensen ◽  
L. L. Sørensen ◽  
H. Chen ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Co2 Flux ◽  
Co2 Concentration ◽  
Co2 Exchange ◽  
Atmospheric Co2 ◽  
The Baltic Sea ◽  
Short Term ◽  
Transfer Velocity ◽  
The Baltic ◽  
Short Term Variability

Abstract. Minimising the uncertainties in estimates of air–sea CO2 exchange is an important step toward increasing the confidence in assessments of the CO2 cycle. Using an atmospheric transport model makes it possible to investigate the direct impact of atmospheric parameters on the air–sea CO2 flux along with its sensitivity to e.g. short-term temporal variability in wind speed, atmospheric mixing height and the atmospheric CO2 concentration. With this study the importance of high spatiotemporal resolution of atmospheric parameters for the air–sea CO2 flux is assessed for six sub-basins within the Baltic Sea and Danish inner waters. A new climatology of surface water partial pressure of CO2 (pCO2) has been developed for this coastal area based on available data from monitoring stations and underway pCO2 measuring systems. Parameterisations depending on wind speed were applied for the transfer velocity to calculate the air–sea CO2 flux. Two model simulations were conducted – one including short term variability in atmospheric CO2 (VAT), and one where it was not included (CAT). A seasonal cycle in the air–sea CO2 flux was found for both simulations for all sub-basins with uptake of CO2 in summer and release of CO2 to the atmosphere in winter. During the simulated period 2005–2010 the average annual net uptake of atmospheric CO2 for the Baltic Sea, Danish Straits and Kattegat was 287 and 471 Gg C yr-1 for the VAT and CAT simulations, respectively. The obtained difference of 184 Gg C yr-1 was found to be significant, and thus ignoring short term variability in atmospheric CO2 does have a sizeable effect on the air–sea CO2 exchange. The combination of the atmospheric model and the new pCO2 fields has also made it possible to make an estimate of the marine part of the Danish CO2 budget for the first time. A net annual uptake of 2613 Gg C yr-1 was found for the Danish waters. A large uncertainty is connected to the air–sea CO2 flux in particular caused by the transfer velocity parameterisation and the applied pCO2 climatology. However, the present study underlines the importance of including short term variability in the atmospheric CO2 concentration in future model studies of the air–sea exchange in order to minimise the uncertainty.

Potential CO2-Enhanced Carbon Storage by the Terrestrial Biosphere

1992 ◽  
Vol 40 (5) ◽  
pp. 641 ◽  
Author(s):  
PJ Polglase ◽  
YP Wang
Keyword(s):  
Carbon Storage ◽  
Net Primary Production ◽  
Co2 Concentration ◽  
Carbon Accumulation ◽  
Atmospheric Co2 ◽  
Terrestrial Biosphere ◽  
Tropical Regions ◽  
Geochemical Models ◽  
Increasing Temperature ◽  
Source Sink

Geochemical models that deduce latitudinal source/sink relationships of atmospheric CO2 suggest that, in tropical regions, there is almost zero net exchange of CO2 between the atmosphere and the terrestrial biosphere. The implication is that CO2-enhanced carbon storage (CO2-ECS) by tropical biomes is negating the output of CO2 from deforestation. We describe here a 10-biome model for CO2-ECS, in which carbon accumulation in living vegetation is coupled to the Rothamsted soil carbon model. A biotic growth factor (β) was used to describe the relationship between literature estimates of net primary production (NPP) and atmospheric CO2 concentration. Using β = 0.3 as a reference state, CO2-ECS by the global biosphere in 1990 was 1.1 Gt. When more appropriate values of β were used (derived from a theoretical response of vegetation to increasing temperature and CO2), CO2-ECS was 1.3 Gt, of which tropical biomes accounted for 0.7 Gt. There are many uncertainties in this (and other) models; total CO2-ECS is particularly sensitive to changes in NPP. Unless published surveys have underestimated tropical NPP by a factor of about 2, then it is unlikely that CO2-ECS could have negated the 1.5-3.0 Gt of carbon that are estimated to have been emitted by tropical deforestation in 1990.

Simulations of the Urban Planetary Boundary Layer in an Arid Metropolitan Area

2008 ◽  
Vol 47 (3) ◽  
pp. 752-768 ◽  
Author(s):  
Susanne Grossman-Clarke ◽  
Yubao Liu ◽  
Joseph A. Zehnder ◽  
Jerome D. Fast
Keyword(s):  
Boundary Layer ◽  
Land Use ◽  
Planetary Boundary Layer ◽  
Mesoscale Model ◽  
Potential Temperature ◽  
Surface Flux ◽  
Metropolitan Region ◽  
Radiosonde Data ◽  
Near Surface ◽  
Better Than

Abstract A modified version of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) was applied to the arid Phoenix, Arizona, metropolitan region. The ability of the model to simulate characteristics of the summertime urban planetary boundary layer (PBL) was tested by comparing model results with observations from two field campaigns conducted in May/June 1998 and June 2001. The modified MM5 included a refined land use/cover classification and updated land use data for Phoenix and bulk approaches of characteristics of the urban surface energy balance. PBL processes were simulated by a version of MM5’s Medium-Range Forecast Model (MRF) scheme that was enhanced by new surface flux and nonlocal mixing approaches. Simulated potential temperature profiles were tested against radiosonde data, indicating that the modified MRF scheme was able to simulate vertical mixing and the evolution and height of the PBL with good accuracy and better than the original MRF scheme except in the late afternoon. During both simulation periods, it is demonstrated that the modified MM5 simulated near-surface air temperatures and wind speeds in the urban area consistently and considerably better than the standard MM5 and that wind direction simulations were improved slightly.

scholarly journals The climatology of planetary boundary layer height in China derived from radiosonde and reanalysis data

2016 ◽  
Author(s):  
Jianping Guo ◽  
Yucong Miao ◽  
Yong Zhang ◽  
Huan Liu ◽  
Zhanqing Li ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Reanalysis Data ◽  
Near Surface ◽  
Layer Height ◽  
Boundary Layer Height ◽  
Early Afternoon ◽  
Fine Resolution

Abstract. The important roles of planetary boundary layer (PBL) in climate, weather and air quality have long been recognized, but little has been known about the PBL climatology in China. Using the fine-resolution sounding observations made across China and a reanalysis data, we conducted a comprehensive investigation of the PBL in China from January 2011 to July 2015. The boundary layer height (BLH) is found to be generally higher in spring and summer than that in fall and winter. The comparison of seasonally averaged BLH derived from observations and reanalysis shows good agreement. The BLH derived from three- or four-times-daily soundings in summer tends to peak in the early afternoon, and the diurnal amplitude of BLH is higher in the northern and western sub-regions of China than other sub-regions. The meteorological influence on the annual cycle of BLH are investigated as well, showing that BLH at most sounding sites is negatively associated with the surface pressure and lower tropospheric stability, but positively associated with the near-surface wind speed and temperature. This indicates that meteorology plays a significant role in the PBL processes. Overall, the key findings obtained from this study lay a solid foundation for us to gain a deep insight into the fundamentals of PBL in China, which helps understand the roles of PBL playing in the air pollution, weather and climate of China.

scholarly journals Relationships between the planetary boundary layer height and surface pollutants derived from lidar observations over China: regional pattern and influencing factors

2018 ◽  
Vol 18 (21) ◽  
pp. 15921-15935 ◽  
Author(s):  
Tianning Su ◽  
Zhanqing Li ◽  
Ralph Kahn
Keyword(s):  
Boundary Layer ◽  
Air Pollution ◽  
Planetary Boundary Layer ◽  
North China Plain ◽  
North China ◽  
Strong Wind ◽  
Planetary Boundary Layer Height ◽  
Near Surface ◽  
Layer Height ◽  
Boundary Layer Height

Abstract. The frequent occurrence of severe air pollution episodes in China has been a great concern and thus the focus of intensive studies. Planetary boundary layer height (PBLH) is a key factor in the vertical mixing and dilution of near-surface pollutants. However, the relationship between PBLH and surface pollutants, especially particulate matter (PM) concentration across China, is not yet well understood. We investigate this issue at ∼1600 surface stations using PBLH derived from space-borne and ground-based lidar, and discuss the influence of topography and meteorological variables on the PBLH–PM relationship. Albeit the PBLH–PM correlations are roughly negative for most cases, their magnitude, significance, and even sign vary considerably with location, season, and meteorological conditions. Weak or even uncorrelated PBLH–PM relationships are found over clean regions (e.g., Pearl River Delta), whereas nonlinearly negative responses of PM to PBLH evolution are found over polluted regions (e.g., North China Plain). Relatively strong PBLH–PM interactions are found when the PBLH is shallow and PM concentration is high, which typically corresponds to wintertime cases. Correlations are much weaker over the highlands than the plains regions, which may be associated with lighter pollution loading at higher elevations and contributions from mountain breezes. The influence of horizontal transport on surface PM is considered as well, manifested as a negative correlation between surface PM and wind speed over the whole nation. Strong wind with clean upwind air plays a dominant role in removing pollutants, and leads to obscure PBLH–PM relationships. A ventilation rate is used to jointly consider horizontal and vertical dispersion, which has the largest impact on surface pollutant accumulation over the North China Plain. As such, this study contributes to improved understanding of aerosol–planetary boundary layer (PBL) interactions and thus our ability to forecast surface air pollution.

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