Improving Estuarine Transport Models using Satellite Measurements

2013 ◽  
Author(s):  
Stefan A. Talke
Keyword(s):  
Satellite Measurements ◽  
Transport Models

scholarly journals The STRatospheric Estimation Algorithm from Mainz (STREAM): estimating stratospheric NO<sub>2</sub> from nadir-viewing satellites by weighted convolution

2016 ◽  
Vol 9 (7) ◽  
pp. 2753-2779 ◽  
Author(s):  
Steffen Beirle ◽  
Christoph Hörmann ◽  
Patrick Jöckel ◽  
Song Liu ◽  
Marloes Penning de Vries ◽  
...  
Keyword(s):  
Input Data ◽  
Polar Vortex ◽  
Chemical Transport ◽  
Estimation Algorithm ◽  
Satellite Observations ◽  
Satellite Measurements ◽  
Transport Models ◽  
Verification Algorithm ◽  
Chemical Transport Models ◽  
Total Column

Abstract. The STRatospheric Estimation Algorithm from Mainz (STREAM) determines stratospheric columns of NO2 which are needed for the retrieval of tropospheric columns from satellite observations. It is based on the total column measurements over clean, remote regions as well as over clouded scenes where the tropospheric column is effectively shielded. The contribution of individual satellite measurements to the stratospheric estimate is controlled by various weighting factors. STREAM is a flexible and robust algorithm and does not require input from chemical transport models. It was developed as a verification algorithm for the upcoming satellite instrument TROPOMI, as a complement to the operational stratospheric correction based on data assimilation. STREAM was successfully applied to the UV/vis satellite instruments GOME 1/2, SCIAMACHY, and OMI. It overcomes some of the artifacts of previous algorithms, as it is capable of reproducing gradients of stratospheric NO2, e.g., related to the polar vortex, and reduces interpolation errors over continents. Based on synthetic input data, the uncertainty of STREAM was quantified as about 0.1–0.2 × 1015 molecules cm−2, in accordance with the typical deviations between stratospheric estimates from different algorithms compared in this study.

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 Aerosol optical depth over the Arctic: a comparison of ECHAM-HAM and TM5 with ground-based, satellite and reanalysis data

2012 ◽  
Vol 12 (15) ◽  
pp. 6953-6967 ◽  
Author(s):  
J. von Hardenberg ◽  
L. Vozella ◽  
C. Tomasi ◽  
V. Vitale ◽  
A. Lupi ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Reanalysis Data ◽  
The Arctic ◽  
Model Resolution ◽  
Satellite Measurements ◽  
Transport Models ◽  
Aerosol Dynamics ◽  
Good Reproduction ◽  
Wet Scavenging

Abstract. We compare ground-based measurements of aerosol optical depth and Ångström parameter at six Arctic stations in the period 2001–2006 with the results from two global aerosol dynamics and transport models, ECHAM-HAM and TM5. Satellite measurements from MODIS and the MACC reanalysis product are used to examine the spatial distribution and the seasonality of these parameters and to compare them with model results. We find that both models provide a good reproduction of the Ångström parameter but significantly underestimate the observed AOD values. We also explore the effects of changes in emissions, model resolution and the parametrization of wet scavenging.

scholarly journals Aerosol optical depth over the Arctic: a comparison of ECHAM-HAM and TM5 with ground-based, satellite and reanalysis data

2012 ◽  
Vol 12 (3) ◽  
pp. 8319-8353
Author(s):  
J. von Hardenberg ◽  
L. Vozella ◽  
V. Vitale ◽  
A. Lupi ◽  
M. Mazzola ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Reanalysis Data ◽  
The Arctic ◽  
Model Resolution ◽  
Satellite Measurements ◽  
Transport Models ◽  
Aerosol Dynamics ◽  
Good Reproduction ◽  
Wet Scavenging

Abstract. We compare ground-based measurements of aerosol optical depth and Ångström parameter at six Arctic stations in the period 2001–2006 with the results from two global aerosol dynamics and transport models, ECHAM-HAM and TM5. Satellite measurements from MODIS and the MACC reanalysis product are used to examine the spatial distribution and the seasonality of these parameters and to compare them with model results. We find that both models provide a good reproduction of the Ångström parameter but significantly underestimate the observed AOD values. We also explore the effects of changes in emissions, model resolution and the parametrization of wet scavenging.

scholarly journals A simple and quick sensitivity analysis method for methane isotopologues detection with GOSAT-TANSO-FTS

2020 ◽  
Author(s):  
Edward Malina ◽  
Jan-Peter Muller ◽  
David Sellers Walton
Keyword(s):  
Surface Albedo ◽  
Analysis Method ◽  
Satellite Measurements ◽  
School Students ◽  
Transport Models ◽  
Analysis Technique ◽  
Sensitivity Analysis Method ◽  
Total Column ◽  
Limited Sensitivity

Measurements of methane isotopologues can differentiate between different source types, be they biogenic (e.g. marsh lands) or abiogenic (e.g. industry). Global measurements of these isotopologues would greatly benefit the current disconnect between top-down (knowledge from Chemistry Transport Models and satellite measurements) and bottom-up (in situ measurement inventories) methane measurements. However, current measurements of these isotopologues are limited to a small number of in situ studies and airborne studies. In this paper we investigate the potential for detecting the second most common isotopologue of methane ( 13 CH 4 ) from space using the Japanese Greenhouse Gases Observation Satellite (GOSAT) applying a quick and simple residual radiance analysis technique. The method allows for a rapid analysis of spectral regions, and can be used to teach University students or advanced school students about radiative transfer analysis. Using this method we find limited sensitivity to 13 CH 4 , with detections limited to total column methane enhancements of >6%, assuming a desert surface albedo of >0.3.

scholarly journals A simple and quick sensitivity analysis method for methane isotopologues detection with GOSAT-TANSO-FTS

2021 ◽  
Vol 2 ◽  
Author(s):  
Edward Malina ◽  
Jan-Peter Muller ◽  
David Walton
Keyword(s):  
Surface Albedo ◽  
Analysis Method ◽  
Satellite Measurements ◽  
School Students ◽  
Transport Models ◽  
Analysis Technique ◽  
Sensitivity Analysis Method ◽  
Total Column ◽  
Limited Sensitivity

Measurements of methane isotopologues can differentiate between different source types, be they biogenic (e.g. marsh lands) or abiogenic (e.g. industry). Global measurements of these isotopologues would greatly benefit the current disconnect between ‘top-down’ (knowledge from chemistry transport models and satellite measurements) and ‘bottom-up’ (in situ measurement inventories) methane measurements. However, current measurements of these isotopologues are limited to a small number of in situ studies and airborne studies. In this paper we investigate the potential for detecting the second most common isotopologue of methane (13CH4) from space using the Japanese Greenhouse Gases Observing Satellite applying a quick and simple residual radiance analysis technique. The method allows for a rapid analysis of spectral regions, and can be used to teach university students or advanced school students about radiative transfer analysis. Using this method we find limited sensitivity to 13CH4, with detections limited to total column methane enhancements of >6%, assuming a desert surface albedo of >0.3.

scholarly journals A simple and quick sensitivity analysis method for methane isotopologues detection with GOSAT-TANSO-FTS

2019 ◽  
Author(s):  
Edward Malina ◽  
Jan-Peter Muller ◽  
David Walton
Keyword(s):  
Surface Albedo ◽  
Analysis Method ◽  
Satellite Measurements ◽  
School Students ◽  
Transport Models ◽  
Analysis Technique ◽  
Sensitivity Analysis Method ◽  
Total Column ◽  
Limited Sensitivity

Measurements of methane isotopologues can differentiate between different source types, be they biogenic (e.g. marsh lands) or abiogenic (e.g. industry). Global measurements of these isotopologues would greatly benefit the current disconnect between top-down (knowledge from Chemistry Transport Models and satellite measurements) and bottom-up (in situ measurement inventories) methane measurements. However, current measurements of these isotopologues are limited to a small number of in situ studies and airborne studies. In this paper we investigate the potential for detecting the second most common isotopologue of methane ( 13 CH 4 ) from space using the Japanese Greenhouse Gases Observation Satellite (GOSAT) applying a quick and simple residual radiance analysis technique. The method allows for a rapid analysis of spectral regions, and can be used to teach University students or advanced school students about radiative transfer analysis. Using this method we find limited sensitivity to 13 CH 4 , with detections limited to total column methane enhancements of >6%, assuming a desert surface albedo of >0.3.

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 (6) ◽  
pp. 14737-14769 ◽  
Author(s):  
S. Houweling ◽  
I. Aben ◽  
F.-M. Breon ◽  
F. Chevallier ◽  
N. Deutscher ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
Model Errors ◽  
Satellite Measurements ◽  
Transport Models ◽  
Sources And Sinks ◽  
Remote Sensing Technique ◽  
Mixing Ratios ◽  
Further Development ◽  
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 CO2 fluxes and initial concentrations. Simulated column averaged CO2 (xCO2) mixing ratios vary between the models by σ=0.5 ppm over the continents and σ=0.27 ppm over sea. A variable, but overall quite encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen. 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 Pg C/yr per 106 km2 over land and 0.03 Pg C/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 Pg C/yr per 106 km2, and could also limit the overall performance of other CO2 missions such as GOSAT. 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. Further development of these models should receive high priority.

scholarly journals The STRatospheric Estimation Algorithm from Mainz (STREAM): Estimating stratospheric NO<sub>2</sub> from nadir-viewing satellites by weighted convolution

2016 ◽  
Author(s):  
S. Beirle ◽  
C. Hörmann ◽  
P. Jöckel ◽  
M. Penning de Vries ◽  
A. Pozzer ◽  
...  
Keyword(s):  
Input Data ◽  
Polar Vortex ◽  
Chemical Transport ◽  
Estimation Algorithm ◽  
Satellite Observations ◽  
Satellite Measurements ◽  
Transport Models ◽  
Verification Algorithm ◽  
Chemical Transport Models ◽  
Total Column

Abstract. Abstract. The STRatospheric Estimation Algorithm from Mainz (STREAM) determines stratospheric columns of NO2 which are needed for the retrieval of tropospheric columns from satellite observations. It is based on the total column measurements over clean, remote regions as well as over clouded scenes where the tropospheric column is effectively shielded. The contribution of individual satellite measurements to the stratospheric estimate is controlled by various weighting factors. STREAM is a flexible and robust algorithm and does not require input from chemical transport models. It was developed as verification algorithm for the upcoming satellite instrument TROPOMI, as complement to the operational stratospheric correction based on data assimilation. STREAM was successfully applied to the UV/vis satellite instruments GOME 1/2, SCIAMACHY, and OMI. It overcomes some of the artefacts of previous algorithms, as it is capable of reproducing gradients of stratospheric NO2, e.g. related to the polar vortex, and reduces interpolation errors over continents. Based on synthetic input data, the uncertainty of STREAM was quantified as about 0.1–0.2 × 1015 molecules cm−2, in accordance to the typical deviations between stratospheric estimates from different algorithms compared in this study.

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