scholarly journals 4D-Var assimilation of MIPAS chemical observations: ozone and nitrogen dioxide analyses

2008 ◽  
Vol 8 (20) ◽  
pp. 6169-6187 ◽  
Author(s):  
Q. Errera ◽  
F. Daerden ◽  
S. Chabrillat ◽  
J. C. Lambert ◽  
W. A. Lahoz ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Nitrogen Dioxide ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Michelson Interferometer ◽  
European Space Agency ◽  
Horizontal Resolution ◽  
Space Agency ◽  
Estimated Error ◽  
Assimilation System

Abstract. This paper discusses the global analyses of stratospheric ozone (O3) and nitrogen dioxide (NO2) obtained by the Belgian Assimilation System for Chemical Observations from Envisat (BASCOE). Based on a chemistry transport model (CTM) and the 4-dimensional variational (4D-Var) method, BASCOE has assimilated chemical observations of O3, NO2, HNO3, N2O, CH4 and H2O, made between July 2002 and March 2004 by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) onboard the European Space Agency (ESA) Environment Satellite (ENVISAT). This corresponds to the entire period during which MIPAS was operating at its nominal resolution. Our analyses are evaluated against assimilated MIPAS data and independent HALOE (HALogen Occultation Experiment) and POAM-III (Polar Ozone and Aerosol Measurement) satellite data. A good agreement is generally found between the analyses and these datasets, in both cases within the estimated error bars of the observations. The benefit of data assimilation is also evaluated by comparing a BASCOE free model run with MIPAS observations. For O3, the gain from the assimilation is significant during ozone hole conditions, and in the lower stratosphere. Elsewhere, the assimilation does not provide significant improvement. For NO2, the gain from the assimilation is realized through most of the stratosphere. Using the BASCOE analyses, we estimate the differences between MIPAS data and independent data from HALOE and POAM-III, and find results close to those obtained by classical validation methods involving only direct measurement-to-measurement comparisons. Our results extend and reinforce previous MIPAS data validation efforts by taking into account a much larger variety of atmospheric states and measurement conditions. This study discusses possible further developments of the BASCOE data assimilation system; these concern the horizontal resolution, a better filtering of NO2 observations, and the photolysis calculation near the lid of the model. The ozone analyses are part of the PROMOTE project and are publicly available via the BASCOE website (http://www.bascoe.oma.be/promote/).

scholarly journals 4D-Var Assimilation of MIPAS chemical observations: ozone and nitrogen dioxide analyses

2008 ◽  
Vol 8 (2) ◽  
pp. 8009-8057 ◽  
Author(s):  
Q. Errera ◽  
F. Daerden ◽  
S. Chabrillat ◽  
J. C. Lambert ◽  
W. A. Lahoz ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Nitrogen Dioxide ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Michelson Interferometer ◽  
European Space Agency ◽  
Horizontal Resolution ◽  
Space Agency ◽  
Free Model ◽  
Assimilation System

Abstract. This paper discusses the global analyses of stratospheric ozone (O3) and nitrogen dioxide (NO2) obtained by the Belgian Assimilation System for Chemical Observations from Envisat (BASCOE). Based on a chemistry transport model (CTM) and the 4-dimensional variational (4D-Var) method, BASCOE has assimilated chemical observations of O3, NO2, HNO3, N2O, CH4 and H2O, made between July 2002 and March 2004 by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) onboard the European Space Agency (ESA) Environment Satellite (ENVISAT). This corresponds to the entire period during which MIPAS was operating at its nominal resolution. Our analyses are evaluated against assimilated MIPAS data and independent HALOE (HALogen Occultation Experiment) and POAM-III (Polar Ozone and Aerosol Measurement) satellite data. A good agreement is generally found between the analyses and these datasets, in both cases within the estimated error bars of the observations. The benefit of data assimilation is also evaluated using a BASCOE free model run. For O3, the gain from the assimilation is significant during ozone hole conditions, and in the lower stratosphere. Elsewhere, the free model run is within the MIPAS uncertainties and the assimilation does not provide significant improvement. For NO2, the gain from the assimilation is realized through most of the stratosphere. Using the BASCOE analyses, we estimate the differences between MIPAS data and independent data from HALOE and POAM-III, and find results close to those obtained by classical validation methods involving only direct measurement-to-measurement comparisons. Our results extend and reinforce previous MIPAS data validation efforts by taking account of a much larger variety of atmospheric states and measurement conditions. This study discusses possible further developments of the BASCOE data assimilation system; these concern the horizontal resolution, a better filtering of NO2 observations, and the photolysis calculation near the lid of the model. The ozone analyses are publicly available via the PROMOTE project http://www.gse-promote.org).

scholarly journals A comparative analysis of UV nadir-backscatter and infrared limb-emission ozone data assimilation

2016 ◽  
Author(s):  
Rossana Dragani
Keyword(s):  
Data Assimilation ◽  
Control Experiment ◽  
Stratospheric Ozone ◽  
Michelson Interferometer ◽  
European Space Agency ◽  
Ultra Violet ◽  
Total Column Ozone ◽  
Ozone Distribution ◽  
Ozone Data ◽  
Ozone Profile

Abstract. This paper presents a comparative assessment of ultra violet nadir-backscatter and infrared limb-emission ozone profile assimilation. The Meteorological Operational Satellite A (MetOp-A) Global Ozone Monitoring Experiment 2 (GOME-2) nadir and the ENVISAT Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) limb profiles, generated as part of the European Space Agency Climate Change Initiative, were individually added to a reference set of ozone observations and assimilated in the European Centre for Medium-Range Weather Forecasts (ECMWF) data assimilation system (DAS). The two sets of resulting analyses were compared with that from a control experiment, only constrained by the reference dataset, and independent, unassimilated observations. Comparisons with independent observations show that both datasets improve the stratospheric ozone distribution. The changes inferred by the limb-based observations are more localized and, in places, more important than those implied by the nadir profiles, albeit they have a much lower number of observations. A small degradation (up to 0.25 mg/kg for GOME-2 and 0.5 mg/kg for MIPAS) is found in the tropics between 20 and 30 hPa. In the lowermost troposphere below its vertical coverage, the limb data is found able to modify the ozone distribution with changes as large as 60 %. Comparisons of the ozone analyses with sonde data show that at those levels the assimilation of GOME-2 leads to about 1 Dobson Unit (DU) smaller root mean square error (RMSE) than that of MIPAS. However, the assimilation of MIPAS can still improve the quality of the ozone analyses, and – with a reduction in the RMSE up to about 2 DU – outperform the control experiment thanks to its synergistic assimilation with total column ozone data within the DAS. High vertical resolution ozone profile observations are essential to accurately monitor and forecast ozone concentrations in a DAS. This study demonstrates the potential and limitations of each dataset and instrument type, as well as the need for a balanced future availability of nadir and limb sensors, and long-term plans for limb-viewing instruments.

scholarly journals JRAero: the Japanese Reanalysis for Aerosol v1.0

2017 ◽  
Vol 10 (9) ◽  
pp. 3225-3253 ◽  
Author(s):  
Keiya Yumimoto ◽  
Taichu Y. Tanaka ◽  
Naga Oshima ◽  
Takashi Maki
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Horizontal Resolution ◽  
Japan Meteorological Agency ◽  
Observation Data ◽  
Aerosol Transport ◽  
Aerosol Model ◽  
Meteorological Research Institute ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. A global aerosol reanalysis product named the Japanese Reanalysis for Aerosol (JRAero) was constructed by the Meteorological Research Institute (MRI) of the Japan Meteorological Agency. The reanalysis employs a global aerosol transport model developed by MRI and a two-dimensional variational data assimilation method. It assimilates maps of aerosol optical depth (AOD) from MODIS onboard the Terra and Aqua satellites every 6 h and has a TL159 horizontal resolution (approximately 1.1°  ×  1.1°). This paper describes the aerosol transport model, the data assimilation system, the observation data, and the setup of the reanalysis and examines its quality with AOD observations. Comparisons with MODIS AODs that were used for the assimilation showed that the reanalysis showed much better agreement than the free run (without assimilation) of the aerosol model and improved under- and overestimation in the free run, thus confirming the accuracy of the data assimilation system. The reanalysis had a root mean square error (RMSE) of 0.05, a correlation coefficient (R) of 0.96, a mean fractional error (MFE) of 23.7 %, a mean fractional bias (MFB) of 2.8 %, and an index of agreement (IOA) of 0.98. The better agreement of the first guess, compared to the free run, indicates that aerosol fields obtained by the reanalysis can improve short-term forecasts. AOD fields from the reanalysis also agreed well with monthly averaged global AODs obtained by the Aerosol Robotic Network (AERONET) (RMSE  =  0.08, R = 0. 90, MFE  =  28.1 %, MFB  =  0.6 %, and IOA  =  0.93). Site-by-site comparison showed that the reanalysis was considerably better than the free run; RMSE was less than 0.10 at 86.4 % of the 181 AERONET sites, R was greater than 0.90 at 40.7 % of the sites, and IOA was greater than 0.90 at 43.4 % of the sites. However, the reanalysis tended to have a negative bias at urban sites (in particular, megacities in industrializing countries) and a positive bias at mountain sites, possibly because of insufficient anthropogenic emissions data, the coarse model resolution, and the difference in representativeness between satellite and ground-based observations.

scholarly journals Two-dimensional performance of MIPAS observation modes in the upper-troposphere/lower-stratosphere

2010 ◽  
Vol 3 (4) ◽  
pp. 2861-2890
Author(s):  
M. Carlotti ◽  
E. Papandrea ◽  
E. Castelli
Keyword(s):  
Lower Stratosphere ◽  
Michelson Interferometer ◽  
European Space Agency ◽  
Horizontal Resolution ◽  
Information Load ◽  
Two Dimensional ◽  
Upper Troposphere ◽  
Space Agency ◽  
Spatial Coverage ◽  
Load Analysis

Abstract. In this paper we analyze the performance of the three MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) observation modes that sound the Upper-Troposphere/Lower-Stratosphere (UT/LS) region. The two-dimensional (2-D) tomographic retrieval approach is assumed to derive the atmospheric field of geophysical parameters. For each observation mode we have calculated the 2-D distribution of the information load quantifier relative to the main MIPAS targets. The performance of the observation modes is then evaluated in terms of strength, spatial coverage and uniformity of the information-load distribution along the full orbit. The outcome of the information-load analysis has been validated with simulated retrievals based on the observational parameters of real orbits. With this strategy we have assessed the precision and the spatial (both horizontal and vertical) resolution of the retrieval products. The performance of the three observation modes has been compared for the MIPAS main products in both the UT/LS and the extended altitude range. This study shows that the two observation modes that were specifically designed for the UT/LS region are actually competitive with the third one, designed for the whole stratosphere, up to altitudes that far exceed the UT/LS. In the UT/LS the performance of the two specific observation modes is comparable even if the best performance in terms of horizontal resolution is provided by the observation mode that was excluded by the European Space Agency (ESA) from the current MIPAS duty cycle. This paper reports the first application of the information-load analysis and highlights the validity of this approach.

scholarly journals JRAero: the Japanese Reanalysis for Aerosol v1.0

2017 ◽  
Author(s):  
Keiya Yumimoto ◽  
Taichu Y. Tanaka ◽  
Naga Oshima ◽  
Takashi Maki
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Horizontal Resolution ◽  
Japan Meteorological Agency ◽  
Observation Data ◽  
Aerosol Transport ◽  
Aerosol Model ◽  
Meteorological Research Institute ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. A global aerosol reanalysis product named the Japanese Reanalysis for Aerosol (JRAero) was constructed by the Meteorological Research Institute (MRI) of the Japan Meteorological Agency. The reanalysis employs a global aerosol transport model developed by MRI and a 2-dimensional variational data assimilation method. It assimilates maps of aerosol optical depth (AOD) from MODIS onboard Terra and Aqua satellites every 6 hours and has a TL159 horizontal resolution (approximately 1.1° × 1.1°). This paper describes the aerosol transport model, the data assimilation system, the observation data, and the set-up of the reanalysis and examines its quality. Comparisons with MODIS AODs showed that the reanalysis showed much better agreement than the free run (without assimilation) of the aerosol model and improved under- and overestimation in the free run, thus confirming the accuracy of the data assimilation system. The reanalysis had a root mean square error (RMSE) = 0.05, a correlation coefficient (R) = 0.96, a mean fractional error (MFE) = 23.7 %, a mean fractional bias (MFB) = 2.8 %, and an index of agreement (IOA) = 0.98. The better agreement of the first guess, compared with the free run, indicates that aerosol fields obtained by the reanalysis can improve short-term forecasts. AOD fields from the reanalysis also agreed well with monthly averaged global AODs obtained by the Aerosol Robotic Network (AERONET) (RMSE = 0.08, R = 0.90, MFE = 28.1 %, MFB = 0.6 %, and IOA = 0.93). Site-by-site comparison showed that the reanalysis was considerably better than the free run; RMSE was  0.90 at 40.7 % of the sites, and IOA was > 0.90 at 43.4 % of the sites. However, the reanalysis tended to have a negative bias at urban sites (in particular, megacities in industrializing countries) and a positive bias at mountain sites, possibly because of insufficient anthropogenic emissions data, the coarse model resolution, and the difference in representativeness between satellite and ground-based observations.

scholarly journals A comparative analysis of UV nadir-backscatter and infrared limb-emission ozone data assimilation

2016 ◽  
Vol 16 (13) ◽  
pp. 8539-8557 ◽  
Author(s):  
Rossana Dragani
Keyword(s):  
Data Assimilation ◽  
Control Experiment ◽  
Stratospheric Ozone ◽  
Michelson Interferometer ◽  
European Space Agency ◽  
Total Column Ozone ◽  
Ozone Distribution ◽  
Ozone Data ◽  
Instrument Type ◽  
Ozone Profile

Abstract. This paper presents a comparative assessment of ultraviolet nadir-backscatter and infrared limb-emission ozone profile assimilation. The Meteorological Operational Satellite A (MetOp-A) Global Ozone Monitoring Experiment 2 (GOME-2) nadir and the ENVISAT Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) limb profiles, generated by the ozone consortium of the European Space Agency Climate Change Initiative (ESA O3-CCI), were individually added to a reference set of ozone observations and assimilated in the European Centre for Medium-Range Weather Forecasts (ECMWF) data assimilation system (DAS). The two sets of resulting analyses were compared with that from a control experiment, only constrained by the reference dataset, and independent, unassimilated observations. Comparisons with independent observations show that both datasets improve the stratospheric ozone distribution. The changes inferred by the limb-based observations are more localized and, in places, more important than those implied by the nadir profiles, albeit they have a much lower number of observations. A small degradation (up to 0.25 mg kg−1 for GOME-2 and 0.5 mg kg−1 for MIPAS in the mass mixing ratio) is found in the tropics between 20 and 30 hPa. In the lowermost troposphere below its vertical coverage, the limb data are found to be able to modify the ozone distribution with changes as large as 60 %. Comparisons of the ozone analyses with sonde data show that at those levels the assimilation of GOME-2 leads to about 1 Dobson Unit (DU) smaller root mean square error (RMSE) than that of MIPAS. However, the assimilation of MIPAS can still improve the quality of the ozone analyses and – with a reduction in the RMSE of up to about 2 DU – outperform the control experiment thanks to its synergistic assimilation with total-column ozone data within the DAS. High vertical resolution ozone profile observations are essential to accurately monitor and forecast ozone concentrations in a DAS. This study demonstrates the potential and limitations of each dataset and instrument type, as well as the need for a balanced future availability of nadir and limb sensors and long-term plans for limb-viewing instruments.

scholarly journals Two-dimensional performance of MIPAS observation modes in the upper-troposphere/lower-stratosphere

2011 ◽  
Vol 4 (2) ◽  
pp. 355-365 ◽  
Author(s):  
M. Carlotti ◽  
E. Castelli ◽  
E. Papandrea
Keyword(s):  
Lower Stratosphere ◽  
Michelson Interferometer ◽  
European Space Agency ◽  
Horizontal Resolution ◽  
Information Load ◽  
Two Dimensional ◽  
Upper Troposphere ◽  
Space Agency ◽  
Spatial Coverage ◽  
Load Analysis

Abstract. In this paper we analyze the performance of the three MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) observation modes that sound the Upper-Troposphere/Lower-Stratosphere (UT/LS) region. The two-dimensional (2-D) tomographic retrieval approach is assumed to derive the atmospheric field of geophysical parameters. For each observation mode we have calculated the 2-D distribution of the information load quantifier relative to the main MIPAS targets. The performance of the observation modes has been evaluated in terms of strength and spatial coverage of the information-load distribution along the full orbit. The indications of the information-load analysis has been validated with simulated retrievals based on the observational parameters of real orbits. In the simulation studies we have assessed the precision and the spatial (both horizontal and vertical) resolution of the retrieval products. The performance of the three observation modes has been compared for the MIPAS main products in both the UT/LS and the extended altitude range. This study shows that the two observation modes that were specifically designed for the UT/LS region are actually competitive with the third one, designed for the whole stratosphere, up to altitudes that far exceed the UT/LS. In the UT/LS the performance of the two specific observation modes is comparable even if the best performance in terms of horizontal resolution is provided by the observation mode that was excluded by the European Space Agency (ESA) from the current MIPAS duty cycle. This paper reports the first application of the information-load analysis and highlights the worthiness of this approach to make qualitative considerations about retrieval potential and selection of retrieval grid.

scholarly journals Validation of MIPAS IMK/IAA methane profiles

2015 ◽  
Vol 8 (12) ◽  
pp. 5251-5261 ◽  
Author(s):  
A. Laeng ◽  
J. Plieninger ◽  
T. von Clarmann ◽  
U. Grabowski ◽  
G. Stiller ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Michelson Interferometer ◽  
European Space Agency ◽  
Trace Gas ◽  
Mixing Ratios ◽  
Air Sampler ◽  
Solar Occultation ◽  
Space Agency ◽  
Scanning Imaging ◽  
Satellite Instruments

Abstract. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) is an infrared (IR) limb emission spectrometer on the Envisat platform. It measures trace gas distributions during day and night, pole-to-pole, over an altitude range from 6 to 70 km in nominal mode and up to 170 km in special modes, depending on the measurement mode, producing more than 1000 profiles day−1. We present the results of a validation study of methane, version V5R_CH4_222, retrieved with the IMK/IAA (Institut für Meteorologie und Klimaforschung, Karlsruhe/Instituto de Astrofisica de Andalucia, Grenada) MIPAS scientific level 2 processor. The level 1 spectra are provided by the ESA (European Space Agency) and version 5 was used. The time period covered is 2005–2012, which corresponds to the period when MIPAS measured trace gas distributions at a reduced spectral resolution of 0.0625 cm−1. The comparison with satellite instruments includes the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), the HALogen Occultation Experiment (HALOE), the Solar Occultation For Ice Experiment (SOFIE) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). Furthermore, comparisons with MkIV balloon-borne solar occultation measurements and with air sampling measurements performed by the University of Frankfurt are presented. The validation activities include bias determination, assessment of stability, precision validation, analysis of histograms and comparison of corresponding climatologies. Above 50 km altitude, MIPAS methane mixing ratios agree within 3 % with ACE-FTS and SOFIE. Between 30 and 40 km an agreement within 3 % with SCIAMACHY has been found. In the middle stratosphere, there is no clear indication of a MIPAS bias since comparisons with various instruments contradict each other. In the lower stratosphere (below 25 km) MIPAS CH4 is biased high with respect to satellite instruments, and the most likely estimate of this bias is 14 %. However, in the comparison with CH4 data obtained from cryogenic whole-air sampler (cryosampler) measurements, there is no evidence of a high bias in MIPAS between 20 and 25 km altitude. Precision validation is performed on collocated MIPAS–MIPAS pairs and suggests a slight underestimation of its uncertainties by a factor of 1.2. No significant evidence of an instrumental drift has been found.

scholarly journals CTDAS-Lagrange v1.0: A high-resolution data assimilation system for regional carbon dioxide observations

2017 ◽  
Author(s):  
Wei He ◽  
Ivar R. van der Velde ◽  
Arlyn E. Andrews ◽  
Colm Sweeney ◽  
John Miller ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Transport Model ◽  
Lateral Boundary ◽  
Lateral Boundary Conditions ◽  
Sensitivity Tests ◽  
Lagrange System ◽  
Data Assimilation System ◽  
Flux Adjustment ◽  
Assimilation System

Abstract. We have implemented a regional carbon dioxide data assimilation system based on the CarbonTracker Data Assimilation Shell (CTDAS) and a high-resolution Lagrangian transport model, the Stochastic Time-Inverted Lagrangian Transport model driven by the Weather Forecast and Research meteorological fields (WRF-STILT). With this system, named as CTDAS‑Lagrange, we simultaneously optimize terrestrial biosphere fluxes and four parameters that adjust the lateral boundary conditions (BCs) against CO2 observations from the NOAA ESRL North America tall tower and aircraft Programmable Flask Packages (PFPs) sampling program. Least-squares optimization is performed with a time-stepping ensemble Kalman smoother, over a time window of 10 days and assimilating sequentially a time series of observations. Because the WRF-STILT footprints are pre-computed, it is computationally efficient to run the CTDAS-Lagrange system. To estimate the uncertainties of the optimized fluxes from the system, we performed sensitivity tests with various a priori biosphere fluxes (SiBCASA, SiB3, CT2013B) and BCs (optimized mole fraction fields from CT2013B and CTE2014, and an empirical data set derived from aircraft observations), as well as with a variety of choices on the ways that fluxes are adjusted (additive or multiplicative), covariance length scales, biosphere flux covariances, BC parameter uncertainties, and model-data mismatches. In pseudo-data experiments, we show that in our implementation the additive flux adjustment method is more flexible in optimizing NEE than the multiplicative flux adjustment method, and that the CTDAS-Lagrange system has the ability to correct for the potential biases in the lateral boundary conditions and to resolve large biases in the prior biosphere fluxes. Using real observations, we have derived a range of estimates for the optimized carbon fluxes from a series of sensitivity tests, which places the North American carbon sink for the year 2010 in a range from −0.92 to −1.26 PgC/yr. This is comparable to the TM5-based estimates of CarbonTracker (version CT2016, −0.91 ± 1.10 PgC/yr) and CarbonTracker Europe (version CTE2016, −0.91 ± 0.31 PgC/yr). We conclude that CTDAS-Lagrange can offer a versatile and computationally attractive alternative to these global systems for regional estimates of carbon fluxes, which can take advantage of high-resolution Lagrangian footprints that are increasingly easy to obtain.

scholarly journals The CarbonTracker Data Assimilation System for CO<sub>2</sub> and <i>δ</i><sup>13</sup>C (CTDAS-C13 v1.0): retrieving information on land–atmosphere exchange processes

2018 ◽  
Vol 11 (1) ◽  
pp. 283-304 ◽  
Author(s):  
Ivar R. van der Velde ◽  
John B. Miller ◽  
Michiel K. van der Molen ◽  
Pieter P. Tans ◽  
Bruce H. Vaughn ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Carbon Balance ◽  
Modular Design ◽  
Transport Model ◽  
Co2 Exchange ◽  
Severe Drought ◽  
Terrestrial Biosphere ◽  
Global Carbon ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. To improve our understanding of the global carbon balance and its representation in terrestrial biosphere models, we present here a first dual-species application of the CarbonTracker Data Assimilation System (CTDAS). The system's modular design allows for assimilating multiple atmospheric trace gases simultaneously to infer exchange fluxes at the Earth surface. In the prototype discussed here, we interpret signals recorded in observed carbon dioxide (CO2) along with observed ratios of its stable isotopologues 13CO2∕12CO2 (δ13C). The latter is in particular a valuable tracer to untangle CO2 exchange from land and oceans. Potentially, it can also be used as a proxy for continent-wide drought stress in plants, largely because the ratio of 13CO2 and 12CO2 molecules removed from the atmosphere by plants is dependent on moisture conditions.The dual-species CTDAS system varies the net exchange fluxes of both 13CO2 and CO2 in ocean and terrestrial biosphere models to create an ensemble of 13CO2 and CO2 fluxes that propagates through an atmospheric transport model. Based on differences between observed and simulated 13CO2 and CO2 mole fractions (and thus δ13C) our Bayesian minimization approach solves for weekly adjustments to both net fluxes and isotopic terrestrial discrimination that minimizes the difference between observed and estimated mole fractions.With this system, we are able to estimate changes in terrestrial δ13C exchange on seasonal and continental scales in the Northern Hemisphere where the observational network is most dense. Our results indicate a decrease in stomatal conductance on a continent-wide scale during a severe drought. These changes could only be detected after applying combined atmospheric CO2 and δ13C constraints as done in this work. The additional constraints on surface CO2 exchange from δ13C observations neither affected the estimated carbon fluxes nor compromised our ability to match observed CO2 variations. The prototype presented here can be of great benefit not only to study the global carbon balance but also to potentially function as a data-driven diagnostic to assess multiple leaf-level exchange parameterizations in carbon-climate models that influence the CO2, water, isotope, and energy balance.

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