Toward reduced transport errors in a high resolution urban CO2 inversion system

Aijun Deng, Thomas Lauvaux, Kenneth J. Davis, Brian J. Gaudet, Natasha Miles, Scott J. Richardson, Kai Wu, Daniel P. Sarmiento, R. Michael Hardesty, Timothy A. Bonin, W. Alan Brewer, Kevin R. Gurney

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

We present a high-resolution atmospheric inversion system combining a Lagrangian Particle Dispersion Model (LPDM) and the Weather Research and Forecasting model (WRF), and test the impact of assimilating meteorological observation on transport accuracy. A Four Dimensional Data Assimilation (FDDA) technique continuously assimilates meteorological observations from various observing systems into the transport modeling system, and is coupled to the high resolution CO2 emission product Hestia to simulate the atmospheric mole fractions of CO2. For the Indianapolis Flux Experiment (INFLUX) project, we evaluated the impact of assimilating different meteorological observation systems on the linearized adjoint solutions and the CO2 inverse fluxes estimated using observed CO2 mole fractions from 11 out of 12 communications towers over Indianapolis for the Sep.-Nov. 2013 period. While assimilating WMO surface measurements improved the simulated wind speed and direction, their impact on the planetary boundary layer (PBL) was limited. Simulated PBL wind statistics improved significantly when assimilating upper-air observations from the commercial airline program Aircraft Communications Addressing and Reporting System (ACARS) and continuous ground-based Doppler lidar wind observations. Wind direction mean absolute error (MAE) decreased from 26 to 14 degrees and the wind speed MAE decreased from 2.0 to 1.2 m s-1, while the bias remains small in all configurations (< 6 degrees and 0.2 m s-1). Wind speed MAE and ME are larger in daytime than in nighttime. PBL depth MAE is reduced by ∼10%, with little bias reduction. The inverse results indicate that the spatial distribution of CO2 inverse fluxes were affected by the model performance while the overall flux estimates changed little across WRF simulations when aggregated over the entire domain. Our results show that PBL wind observations are a potent tool for increasing the precision of urban meteorological reanalyses, but that the impact on inverse flux estimates is dependent on the specific urban environment.

Original languageEnglish (US)
Article number20
JournalElementa
Volume5
DOIs
StatePublished - Jan 1 2017

Fingerprint

boundary layer
wind velocity
Fluxes
Boundary layers
wind direction
communication
Doppler lidar
weather
data assimilation
Aircraft communication
aircraft
spatial distribution
Surface measurement
Optical radar
inversion
air
Towers
Spatial distribution
modeling
simulation

All Science Journal Classification (ASJC) codes

  • Oceanography
  • Environmental Engineering
  • Ecology
  • Geotechnical Engineering and Engineering Geology
  • Geology
  • Atmospheric Science

Cite this

Deng, Aijun ; Lauvaux, Thomas ; Davis, Kenneth J. ; Gaudet, Brian J. ; Miles, Natasha ; Richardson, Scott J. ; Wu, Kai ; Sarmiento, Daniel P. ; Hardesty, R. Michael ; Bonin, Timothy A. ; Brewer, W. Alan ; Gurney, Kevin R. / Toward reduced transport errors in a high resolution urban CO2 inversion system. In: Elementa. 2017 ; Vol. 5.
@article{7721f569d87741fab232f6c9f8c279a1,
title = "Toward reduced transport errors in a high resolution urban CO2 inversion system",
abstract = "We present a high-resolution atmospheric inversion system combining a Lagrangian Particle Dispersion Model (LPDM) and the Weather Research and Forecasting model (WRF), and test the impact of assimilating meteorological observation on transport accuracy. A Four Dimensional Data Assimilation (FDDA) technique continuously assimilates meteorological observations from various observing systems into the transport modeling system, and is coupled to the high resolution CO2 emission product Hestia to simulate the atmospheric mole fractions of CO2. For the Indianapolis Flux Experiment (INFLUX) project, we evaluated the impact of assimilating different meteorological observation systems on the linearized adjoint solutions and the CO2 inverse fluxes estimated using observed CO2 mole fractions from 11 out of 12 communications towers over Indianapolis for the Sep.-Nov. 2013 period. While assimilating WMO surface measurements improved the simulated wind speed and direction, their impact on the planetary boundary layer (PBL) was limited. Simulated PBL wind statistics improved significantly when assimilating upper-air observations from the commercial airline program Aircraft Communications Addressing and Reporting System (ACARS) and continuous ground-based Doppler lidar wind observations. Wind direction mean absolute error (MAE) decreased from 26 to 14 degrees and the wind speed MAE decreased from 2.0 to 1.2 m s-1, while the bias remains small in all configurations (< 6 degrees and 0.2 m s-1). Wind speed MAE and ME are larger in daytime than in nighttime. PBL depth MAE is reduced by ∼10{\%}, with little bias reduction. The inverse results indicate that the spatial distribution of CO2 inverse fluxes were affected by the model performance while the overall flux estimates changed little across WRF simulations when aggregated over the entire domain. Our results show that PBL wind observations are a potent tool for increasing the precision of urban meteorological reanalyses, but that the impact on inverse flux estimates is dependent on the specific urban environment.",
author = "Aijun Deng and Thomas Lauvaux and Davis, {Kenneth J.} and Gaudet, {Brian J.} and Natasha Miles and Richardson, {Scott J.} and Kai Wu and Sarmiento, {Daniel P.} and Hardesty, {R. Michael} and Bonin, {Timothy A.} and Brewer, {W. Alan} and Gurney, {Kevin R.}",
year = "2017",
month = "1",
day = "1",
doi = "10.1525/elementa.133",
language = "English (US)",
volume = "5",
journal = "Elementa",
issn = "2325-1026",
publisher = "BioOne",

}

Deng, A, Lauvaux, T, Davis, KJ, Gaudet, BJ, Miles, N, Richardson, SJ, Wu, K, Sarmiento, DP, Hardesty, RM, Bonin, TA, Brewer, WA & Gurney, KR 2017, 'Toward reduced transport errors in a high resolution urban CO2 inversion system', Elementa, vol. 5, 20. https://doi.org/10.1525/elementa.133

Toward reduced transport errors in a high resolution urban CO2 inversion system. / Deng, Aijun; Lauvaux, Thomas; Davis, Kenneth J.; Gaudet, Brian J.; Miles, Natasha; Richardson, Scott J.; Wu, Kai; Sarmiento, Daniel P.; Hardesty, R. Michael; Bonin, Timothy A.; Brewer, W. Alan; Gurney, Kevin R.

In: Elementa, Vol. 5, 20, 01.01.2017.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Toward reduced transport errors in a high resolution urban CO2 inversion system

AU - Deng, Aijun

AU - Lauvaux, Thomas

AU - Davis, Kenneth J.

AU - Gaudet, Brian J.

AU - Miles, Natasha

AU - Richardson, Scott J.

AU - Wu, Kai

AU - Sarmiento, Daniel P.

AU - Hardesty, R. Michael

AU - Bonin, Timothy A.

AU - Brewer, W. Alan

AU - Gurney, Kevin R.

PY - 2017/1/1

Y1 - 2017/1/1

N2 - We present a high-resolution atmospheric inversion system combining a Lagrangian Particle Dispersion Model (LPDM) and the Weather Research and Forecasting model (WRF), and test the impact of assimilating meteorological observation on transport accuracy. A Four Dimensional Data Assimilation (FDDA) technique continuously assimilates meteorological observations from various observing systems into the transport modeling system, and is coupled to the high resolution CO2 emission product Hestia to simulate the atmospheric mole fractions of CO2. For the Indianapolis Flux Experiment (INFLUX) project, we evaluated the impact of assimilating different meteorological observation systems on the linearized adjoint solutions and the CO2 inverse fluxes estimated using observed CO2 mole fractions from 11 out of 12 communications towers over Indianapolis for the Sep.-Nov. 2013 period. While assimilating WMO surface measurements improved the simulated wind speed and direction, their impact on the planetary boundary layer (PBL) was limited. Simulated PBL wind statistics improved significantly when assimilating upper-air observations from the commercial airline program Aircraft Communications Addressing and Reporting System (ACARS) and continuous ground-based Doppler lidar wind observations. Wind direction mean absolute error (MAE) decreased from 26 to 14 degrees and the wind speed MAE decreased from 2.0 to 1.2 m s-1, while the bias remains small in all configurations (< 6 degrees and 0.2 m s-1). Wind speed MAE and ME are larger in daytime than in nighttime. PBL depth MAE is reduced by ∼10%, with little bias reduction. The inverse results indicate that the spatial distribution of CO2 inverse fluxes were affected by the model performance while the overall flux estimates changed little across WRF simulations when aggregated over the entire domain. Our results show that PBL wind observations are a potent tool for increasing the precision of urban meteorological reanalyses, but that the impact on inverse flux estimates is dependent on the specific urban environment.

AB - We present a high-resolution atmospheric inversion system combining a Lagrangian Particle Dispersion Model (LPDM) and the Weather Research and Forecasting model (WRF), and test the impact of assimilating meteorological observation on transport accuracy. A Four Dimensional Data Assimilation (FDDA) technique continuously assimilates meteorological observations from various observing systems into the transport modeling system, and is coupled to the high resolution CO2 emission product Hestia to simulate the atmospheric mole fractions of CO2. For the Indianapolis Flux Experiment (INFLUX) project, we evaluated the impact of assimilating different meteorological observation systems on the linearized adjoint solutions and the CO2 inverse fluxes estimated using observed CO2 mole fractions from 11 out of 12 communications towers over Indianapolis for the Sep.-Nov. 2013 period. While assimilating WMO surface measurements improved the simulated wind speed and direction, their impact on the planetary boundary layer (PBL) was limited. Simulated PBL wind statistics improved significantly when assimilating upper-air observations from the commercial airline program Aircraft Communications Addressing and Reporting System (ACARS) and continuous ground-based Doppler lidar wind observations. Wind direction mean absolute error (MAE) decreased from 26 to 14 degrees and the wind speed MAE decreased from 2.0 to 1.2 m s-1, while the bias remains small in all configurations (< 6 degrees and 0.2 m s-1). Wind speed MAE and ME are larger in daytime than in nighttime. PBL depth MAE is reduced by ∼10%, with little bias reduction. The inverse results indicate that the spatial distribution of CO2 inverse fluxes were affected by the model performance while the overall flux estimates changed little across WRF simulations when aggregated over the entire domain. Our results show that PBL wind observations are a potent tool for increasing the precision of urban meteorological reanalyses, but that the impact on inverse flux estimates is dependent on the specific urban environment.

UR - http://www.scopus.com/inward/record.url?scp=85020874580&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85020874580&partnerID=8YFLogxK

U2 - 10.1525/elementa.133

DO - 10.1525/elementa.133

M3 - Article

AN - SCOPUS:85020874580

VL - 5

JO - Elementa

JF - Elementa

SN - 2325-1026

M1 - 20

ER -