scholarly journals HCOOH measurements from space: TES retrieval algorithm and observed global distribution

2014 ◽  
Vol 7 (7) ◽  
pp. 2297-2311 ◽  
Author(s):  
K. E. Cady-Pereira ◽  
S. Chaliyakunnel ◽  
M. W. Shephard ◽  
D. B. Millet ◽  
M. Luo ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Transport Model ◽  
A Priori ◽  
Optimal Estimation ◽  
Initial Guess ◽  
Global Distribution ◽  
Retrieval Algorithm ◽  
Vertical Resolution ◽  
Chemical Transport Model ◽  
Thermal Contrast

Abstract. Presented is a detailed description of the TES (Tropospheric Emission Spectrometer)-Aura satellite formic acid (HCOOH) retrieval algorithm and initial results quantifying the global distribution of tropospheric HCOOH. The retrieval strategy, including the optimal estimation methodology, spectral microwindows, a priori constraints, and initial guess information, are provided. A comprehensive error and sensitivity analysis is performed in order to characterize the retrieval performance, degrees of freedom for signal, vertical resolution, and limits of detection. These results show that the TES HCOOH retrievals (i) typically provide at best 1.0 pieces of information; (ii) have the most vertical sensitivity in the range from 900 to 600 hPa with ~ 2 km vertical resolution; (iii) require at least 0.5 ppbv (parts per billion by volume) of HCOOH for detection if thermal contrast is greater than 5 K, and higher concentrations as thermal contrast decreases; and (iv) based on an ensemble of simulated retrievals, are unbiased with a standard deviation of ±0.4 ppbv. The relative spatial distribution of tropospheric HCOOH derived from TES and its associated seasonality are broadly correlated with predictions from a state-of-the-science chemical transport model (GEOS-Chem CTM). However, TES HCOOH is generally higher than is predicted by GEOS-Chem, and this is in agreement with recent work pointing to a large missing source of atmospheric HCOOH. The model bias is especially pronounced in summertime and over biomass burning regions, implicating biogenic emissions and fires as key sources of the missing atmospheric HCOOH in the model.

scholarly journals HCOOH measurements from space: TES retrieval algorithm and observed global distribution

2014 ◽  
Vol 7 (2) ◽  
pp. 1975-2015 ◽  
Author(s):  
K. E. Cady-Pereira ◽  
S. Chaliyakunnel ◽  
M. W. Shephard ◽  
D. B. Millet ◽  
M. Luo ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Transport Model ◽  
A Priori ◽  
Optimal Estimation ◽  
Initial Guess ◽  
Global Distribution ◽  
Retrieval Algorithm ◽  
Vertical Resolution ◽  
Chemical Transport Model ◽  
Thermal Contrast

Abstract. Presented is a detailed description of the TES-Aura satellite formic acid (HCOOH) retrieval algorithm and initial results quantifying the global distribution of tropospheric HCOOH. The retrieval strategy, including the optimal estimation methodology, spectral microwindows, a priori constraints, and initial guess information, are provided. A comprehensive error and sensitivity analysis is performed in order to characterize the retrieval performance, degrees of freedom for signal, vertical resolution, and limits of detection. These results show that the TES HCOOH retrievals: (i) typically provide at best 1.0 pieces of information, (ii) have the most vertical sensitivity in the range from 900 to 600 hPa with ~ 2 km vertical resolution, (iii) require at least 0.5 ppbv of HCOOH for detection if thermal contrast is greater than 10 K, and higher concentrations as thermal contrast decreases; and (iv) based on an ensemble of simulated retrievals, are unbiased with a standard deviation of ±0.3 ppbv. Globally, the spatial distribution of tropospheric HCOOH derived from TES is broadly consistent with that simulated by a state-of-the-science chemical transport model (GEOS-Chem CTM). However, TES HCOOH is frequently higher than is predicted by GEOS-Chem, and this is in agreement with recent work pointing to a large missing source of atmospheric HCOOH. The model bias is especially pronounced over biomass burning regions, suggesting that fires are one key source of the missing atmospheric HCOOH in the model.

scholarly journals Methanol from TES global observations: retrieval algorithm and seasonal and spatial variability

2012 ◽  
Vol 12 (5) ◽  
pp. 11823-11859 ◽  
Author(s):  
K. E. Cady-Pereira ◽  
M. W. Shephard ◽  
D. B. Millet ◽  
M. Luo ◽  
K. C. Wells ◽  
...  
Keyword(s):  
Large Scale ◽  
Transport Model ◽  
A Priori ◽  
Lower Troposphere ◽  
Initial Guess ◽  
Retrieval Algorithm ◽  
Atmospheric Conditions ◽  
Chemical Transport Model ◽  
Model Retrieval ◽  
Peak Sensitivity

Abstract. We present a detailed description of the TES methanol (CH3OH) retrieval algorithm, along with initial global results showing the seasonal and spatial distribution of methanol in the lower troposphere. The full development of the TES methanol retrieval is described, including microwindow selection, error analysis, and the utilization of a priori and initial guess information provided by the GEOS-Chem chemical transport model. Retrieval simulations and a sensitivity analysis using the developed retrieval strategy show that TES: (i) generally provides between 0.5 and 1.0 pieces of information, (ii) is sensitive in the lower troposphere with peak sensitivity typically occurring between ~900–700 hPa (~1–3 km) at a vertical resolution of ~5 km, (iii) has a limit of detectability between 0.5 and 1.0 ppbv Representative Volume Mixing Ratio (RVMR) depending on the atmospheric conditions, corresponding roughly to a profile with a maximum concentration of at least 1 to 2 ppbv, and (iv) in a simulation environment has a mean bias of 0.16 ppbv and a standard deviation of 0.34 ppbv. Applying the newly-derived TES retrieval globally and comparing the results with corresponding GEOS-Chem output, we find generally consistent large-scale patterns between the two. However, TES often reveals higher methanol concentrations than predicted in the Northern Hemisphere spring, summer and fall. In the Southern Hemisphere, the TES methanol observations indicate a model overestimate over the bulk of South America from December through July, and a model underestimate during the biomass burning season.

scholarly journals Methanol from TES global observations: retrieval algorithm and seasonal and spatial variability

2012 ◽  
Vol 12 (17) ◽  
pp. 8189-8203 ◽  
Author(s):  
K. E. Cady-Pereira ◽  
M. W. Shephard ◽  
D. B. Millet ◽  
M. Luo ◽  
K. C. Wells ◽  
...  
Keyword(s):  
Large Scale ◽  
Transport Model ◽  
A Priori ◽  
Lower Troposphere ◽  
Initial Guess ◽  
Retrieval Algorithm ◽  
Atmospheric Conditions ◽  
Chemical Transport Model ◽  
Model Retrieval ◽  
Peak Sensitivity

Abstract. We present a detailed description of the TES methanol (CH3OH) retrieval algorithm, along with initial global results showing the seasonal and spatial distribution of methanol in the lower troposphere. The full development of the TES methanol retrieval is described, including microwindow selection, error analysis, and the utilization of a priori and initial guess information provided by the GEOS-Chem chemical transport model. Retrieval simulations and a sensitivity analysis using the developed retrieval strategy show that TES: (i) generally provides less than 1.0 piece of information, (ii) is sensitive in the lower troposphere with peak sensitivity typically occurring between ~900–700 hPa (~1–3 km) at a vertical resolution of ~5 km, (iii) has a limit of detectability between 0.5 and 1.0 ppbv Representative Volume Mixing Ratio (RVMR) depending on the atmospheric conditions, corresponding roughly to a profile with a maximum concentration of at least 1 to 2 ppbv, and (iv) in a simulation environment has a mean bias of 0.16 ppbv with a standard deviation of 0.34 ppbv. Applying the newly derived TES retrieval globally and comparing the results with corresponding GEOS-Chem output, we find generally consistent large-scale patterns between the two. However, TES often reveals higher methanol concentrations than simulated in the Northern Hemisphere spring, summer and fall. In the Southern Hemisphere, the TES methanol observations indicate a model overestimate over the bulk of South America from December through July, and a model underestimate during the biomass burning season.

scholarly journals Evaluation of potential sources of a priori ozone profiles for TEMPO tropospheric ozone retrievals

2018 ◽  
Vol 11 (6) ◽  
pp. 3457-3477 ◽  
Author(s):  
Matthew S. Johnson ◽  
Xiong Liu ◽  
Peter Zoogman ◽  
John Sullivan ◽  
Michael J. Newchurch ◽  
...  
Keyword(s):  
Air Quality ◽  
Tropospheric Ozone ◽  
Transport Model ◽  
A Priori ◽  
Retrieval Algorithm ◽  
Chemical Transport Model ◽  
Diurnal Variability ◽  
Potential Sources ◽  
Tropospheric O3 ◽  
Lidar Observations

Abstract. Potential sources of a priori ozone (O3) profiles for use in Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite tropospheric O3 retrievals are evaluated with observations from multiple Tropospheric Ozone Lidar Network (TOLNet) systems in North America. An O3 profile climatology (tropopause-based O3 climatology (TB-Clim), currently proposed for use in the TEMPO O3 retrieval algorithm) derived from ozonesonde observations and O3 profiles from three separate models (operational Goddard Earth Observing System (GEOS-5) Forward Processing (FP) product, reanalysis product from Modern-era Retrospective Analysis for Research and Applications version 2 (MERRA2), and the GEOS-Chem chemical transport model (CTM)) were: (1) evaluated with TOLNet measurements on various temporal scales (seasonally, daily, and hourly) and (2) implemented as a priori information in theoretical TEMPO tropospheric O3 retrievals in order to determine how each a priori impacts the accuracy of retrieved tropospheric (0–10 km) and lowermost tropospheric (LMT, 0–2 km) O3 columns. We found that all sources of a priori O3 profiles evaluated in this study generally reproduced the vertical structure of summer-averaged observations. However, larger differences between the a priori profiles and lidar observations were calculated when evaluating inter-daily and diurnal variability of tropospheric O3. The TB-Clim O3 profile climatology was unable to replicate observed inter-daily and diurnal variability of O3 while model products, in particular GEOS-Chem simulations, displayed more skill in reproducing these features. Due to the ability of models, primarily the CTM used in this study, on average to capture the inter-daily and diurnal variability of tropospheric and LMT O3 columns, using a priori profiles from CTM simulations resulted in TEMPO retrievals with the best statistical comparison with lidar observations. Furthermore, important from an air quality perspective, when high LMT O3 values were observed, using CTM a priori profiles resulted in TEMPO LMT O3 retrievals with the least bias. The application of near-real-time (non-climatological) hourly and daily model predictions as the a priori profile in TEMPO O3 retrievals will be best suited when applying this data to study air quality or event-based processes as the standard retrieval algorithm will still need to use a climatology product. Follow-on studies to this work are currently being conducted to investigate the application of different CTM-predicted O3 climatology products in the standard TEMPO retrieval algorithm. Finally, similar methods to those used in this study can be easily applied by TEMPO data users to recalculate tropospheric O3 profiles provided from the standard retrieval using a different source of a priori.

scholarly journals A geostationary thermal infrared sensor to monitor the lowermost troposphere: O<sub>3</sub> and CO retrieval studies

2010 ◽  
Vol 3 (4) ◽  
pp. 3489-3534 ◽  
Author(s):  
M. Claeyman ◽  
J.-L. Attié ◽  
V.-H. Peuch ◽  
L. El Amraoui ◽  
W. A. Lahoz ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Transport Model ◽  
Weather Prediction ◽  
High Surface ◽  
Thermal Infrared ◽  
Added Value ◽  
Spatial And Temporal Variability ◽  
Chemical Transport Model ◽  
Statistical Parameters ◽  
Thermal Contrast

Abstract. This paper describes the capabilities of a nadir thermal infrared (TIR) sensor proposed for embarkation onboard a geostationary platform to monitor ozone (O3) and carbon monoxide (CO) for air quality (AQ) purposes. To assess the capabilities of this sensor we perform idealized retrieval studies considering typical atmospheric profiles of O3 and CO over Europe with different instrument configurations (signal to noise ratio and spectral sampling interval) using the KOPRA forward model and the KOPRA-fit retrieval scheme based on the Tikhonov-Phillips regularization. We then select a configuration, referred to as GEO-TIR, optimized for providing information in the lowermost troposphere (LmT; 0–3 km in height). For the GEO-TIR configuration we obtain around 1.5 degrees of freedom for O3 and 2 for CO at altitudes between 0 and 15 km. The error budget of GEO-TIR, calculated taking account of the principal contributions to the error (namely, temperature, measurement error, smoothing error) shows that information in the LmT can be achieved by GEO-TIR. We also retrieve analogous profiles from another geostationary infrared instrument with characteristics similar to the Meteosat Third Generation Infrared Sounder (MTG-IRS) which is dedicated to numerical weather prediction, referred to as GEO-TIR2. Comparison between GEO-TIR and GEO-TIR2 allows us to quantify the added value of GEO-TIR, a mission complementing the AQ observing system. To better characterize the information provided by GEO-TIR and GEO-TIR2 in the LmT, we retrieve two typical profiles of O3 and CO for different thermal contrast ranging from –10 K to 10 K. The shape of the first averaging kernel (corresponding to the surface level) confirms that GEO-TIR has good sensitivity to CO in the LmT and also to O3 for high positive thermal contrast. GEO-TIR2 has very low sensitivity in the LmT to O3 but can have sensitivity to CO with high positive thermal contrast. To quantify these results for a realistic atmosphere, we simulate it using the chemical transport model MOCAGE (MOdèle de Chimie Atmospherique à Grande Echelle) – this is the nature run. We simulate the O3 and CO spatial and temporal distributions from GEO-TIR observations in the LmT in July 2009 over Europe by sampling the nature run. Results show that GEO-TIR is able to capture well the spatial and temporal variability in the LmT for both O3 and CO, particularly during periods with high positive thermal contrast near the ground and high surface temperature, which results in active photochemistry and a raised planetary boundary layer. These results also provide evidence of the significant added value in the LmT of GEO-TIR compared to GEO-TIR2 by showing GEO-TIR is closer to the nature run than GEO-TIR2 for various statistical parameters (correlation, bias, standard deviation).

scholarly journals Tropospheric methanol observations from space: retrieval evaluation and constraints on the seasonality of biogenic emissions

2012 ◽  
Vol 12 (13) ◽  
pp. 5897-5912 ◽  
Author(s):  
K. C. Wells ◽  
D. B. Millet ◽  
L. Hu ◽  
K. E. Cady-Pereira ◽  
Y. Xiao ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Degrees Of Freedom ◽  
Transport Model ◽  
A Priori ◽  
Global Scale ◽  
Biogenic Emissions ◽  
Chemical Transport Model ◽  
Area Index ◽  
New Information

Abstract. Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model:TES regressions are generally consistent with the model:aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS >0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1–2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 0.26, 0.12 and 3.0 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.5 for expanding canopies with leaf area index <1.2) provide a more realistic simulation of seasonal methanol concentrations in midlatitudes on the basis of both the IASI and TES measurements.

scholarly journals Glyoxal vertical columns from GOME-2 backscattered light measurements and comparisons with a global model

2010 ◽  
Vol 10 (24) ◽  
pp. 12059-12072 ◽  
Author(s):  
C. Lerot ◽  
T. Stavrakou ◽  
I. De Smedt ◽  
J.-F. Müller ◽  
M. Van Roozendael
Keyword(s):  
Transport Model ◽  
Total Error ◽  
A Priori ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Chemical Transport Model ◽  
Vertical Column ◽  
Air Mass ◽  
Tropical Regions

Abstract. Glyoxal vertical column densities have been retrieved from nadir backscattered radiances measured from 2007 to 2009 by the spaceborne GOME-2/METOP-A sensor. The retrieval algorithm is based on the DOAS technique and optimized settings have been used to determine glyoxal slant columns. The liquid water absorption is accounted for using a two-step DOAS approach, leading to a drastic improvement of the fit quality over remote clear water oceans. Air mass factors are calculated by means of look-up tables of weighting functions pre-calculated with the LIDORT v3.3 radiative transfer model and using a priori glyoxal vertical distributions provided by the IMAGESv2 chemical transport model. The total error estimate comprises random and systematic errors associated to the DOAS fit, the air mass factor calculation and the cloud correction. The highest glyoxal vertical column densities are mainly observed in continental tropical regions, while the mid-latitude columns strongly depend on the season with maximum values during warm months. An anthropogenic signature is also observed in highly populated regions of Asia. Comparisons with glyoxal columns simulated with IMAGESv2 in different regions of the world generally point to a missing glyoxal source, most probably of biogenic origin.

scholarly journals Glyoxal vertical columns from GOME-2 backscattered light measurements and comparisons with a global model

2010 ◽  
Vol 10 (9) ◽  
pp. 21147-21188 ◽  
Author(s):  
C. Lerot ◽  
T. Stavrakou ◽  
I. De Smedt ◽  
J.-F. Müller ◽  
M. Van Roozendael
Keyword(s):  
Transport Model ◽  
Total Error ◽  
A Priori ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Chemical Transport Model ◽  
Vertical Column ◽  
Air Mass ◽  
Tropical Regions

Abstract. Glyoxal vertical column densities have been retrieved from nadir backscattered radiances measured from 2007 to 2009 by the spaceborne GOME-2/METOP-A sensor. The retrieval algorithm is based on the DOAS technique and optimized settings have been used to determine glyoxal slant columns. The liquid water absorption is accounted for using a two-step DOAS approach, leading to a drastic improvement of the fit quality over remote clear water oceans. Air mass factors are calculated by means of look-up tables of weighting functions pre-calculated with the LIDORT v3.3 radiative transfer model and using a priori glyoxal vertical distributions provided by the IMAGESv2 chemical transport model. The total error estimate comprises random and systematic errors associated to the DOAS fit, the air mass factor calculation and the cloud correction. The highest glyoxal vertical column densities are mainly observed in continental tropical regions, while the mid-latitude columns strongly depend on the season with maximum values during warm months. An anthropogenic signature is also observed in highly populated regions of Asia. Comparisons with glyoxal columns simulated with IMAGESv2 in different regions of the world generally point to a missing glyoxal source, most probably of biogenic origin.

scholarly journals Satellite observations of peroxyacetyl nitrate from the Aura Tropospheric Emission Spectrometer

2014 ◽  
Vol 7 (6) ◽  
pp. 5347-5379 ◽  
Author(s):  
V. H. Payne ◽  
M. J. Alvarado ◽  
K. E. Cady-Pereira ◽  
J. R. Worden ◽  
S. S. Kulawik ◽  
...  
Keyword(s):  
Detection Limit ◽  
Transport Model ◽  
A Priori ◽  
Initial Guess ◽  
Chemical Transport Model ◽  
Peroxyacetyl Nitrate ◽  
Cloud Optical Depth ◽  
Spatial Features ◽  
Instrument Noise ◽  
Global Chemical Transport Model

Abstract. We present a description of the algorithm used to retrieve peroxyacetyl nitrate (PAN) concentrations from the Aura Tropospheric Emission Spectrometer (TES). We describe the spectral microwindows, error analysis and the utilization of a priori and initial guess information provided by the GEOS-Chem global chemical transport model. The TES PAN retrievals contain up to one degree of freedom for signal. Estimated single-measurement uncertainties are 30 to 50%. The detection limit for a single TES measurement is dependent on the atmospheric and surface conditions as well as on the instrument noise. For observations where the cloud optical depth is less than 0.5, we find that the TES detection limit for PAN is in the region of 200 to 300 pptv. We show that PAN retrievals over the Northern Hemisphere Pacific in springtime show spatial features that are qualitatively consistent with the expected distribution of PAN in outflow of Asian pollution.

scholarly journals Tropospheric methanol observations from space: retrieval evaluation and constraints on the seasonality of biogenic emissions

2012 ◽  
Vol 12 (2) ◽  
pp. 3941-3982 ◽  
Author(s):  
K. C. Wells ◽  
D. B. Millet ◽  
L. Hu ◽  
K. E. Cady-Pereira ◽  
Y. Xiao ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Degrees Of Freedom ◽  
Transport Model ◽  
A Priori ◽  
Global Scale ◽  
Biogenic Emissions ◽  
Chemical Transport Model ◽  
Area Index ◽  
Model Aircraft

Abstract. Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model : TES regressions are generally consistent with the model : aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS > 0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1–2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 1.0, 0.05 and 8.6 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.75 for expanding canopies with leaf area index < 2.0) provide a more realistic simulation of seasonal methanol concentrations in midlatitudes on the basis of IASI, TES, and ground-based measurements.

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