Investigation of aerosol–cloud interactions using a chemical transport model constrained by satellite observations

Tellus B ◽  
2010 ◽  
Vol 62 (1) ◽  
Author(s):  
Yan Feng ◽  
V. Ramanathan
Keyword(s):  
Transport Model ◽  
Chemical Transport ◽  
Satellite Observations ◽  
Chemical Transport Model ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions

scholarly journals Aerosol-cloud interactions in the NASA GMI: model development and indirect forcing assessments

2007 ◽  
Vol 7 (5) ◽  
pp. 14295-14330 ◽  
Author(s):  
N. Meskhidze ◽  
R. E. P. Sotiropoulou ◽  
A. Nenes ◽  
J. Kouatchou ◽  
B. Das ◽  
...  
Keyword(s):  
Transport Model ◽  
Model Development ◽  
Cloud Droplet ◽  
Chemical Transport Model ◽  
Remotely Sensed Data ◽  
Liquid Water Path ◽  
Model Framework ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions ◽  
Indirect Forcing

Abstract. This study uses the NASA Global Modeling Initiative (GMI) 3-D chemical transport model (CTM) for assessments of indirect forcing and its sensitivity to the treatment of aerosol, aerosol-cloud interactions and meteorological fields. Three different meteorological datasets from NASA Data Assimilation Office (DAO), NASA finite volume GCM (FVGCM) and the Goddard Institute for Space Studies version II' (GISS II') GCM were used. GMI is ideal for this study as different model components (such as meteorological fields and chemical mechanisms) can easily be interchanged under the same model framework to capture the first aerosol indirect effect (AIE), and its sensitivity to parameterizations and meteorological fields. Cloud droplet number concentration was calculated by implementing both diagnostic and physically based droplet parameterizations. Derived cloud properties, such as cloud optical thickness and effective radius were compared with the remotely sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS). GMI was able to capture the spatial variability and the land-ocean contrast observed in the satellite record. Depending on the meteorological field and droplet parameterization used, the annual mean first AIE ranged from −0.99 to −1.48 W m−2. It is found that, roughly 80% of the variation is attributed to changes in the meteorology (primarily from variations in liquid water path), while the remaining 20% is attributed to different cloud droplet parameterizations.

scholarly journals Interpretation of Measured Aerosol Mass Scattering Efficiency Over North America Using a Chemical Transport Model

2018 ◽  
Author(s):  
Robyn N. C. Latimer ◽  
Randall V. Martin
Keyword(s):  
North America ◽  
Transport Model ◽  
Chemical Transport ◽  
Satellite Observations ◽  
Climate Forcing ◽  
Size Distributions ◽  
Positive Bias ◽  
Chemical Transport Model ◽  
Scattering Efficiency ◽  
Aerosol Mass

Abstract. Aerosol mass scattering efficiency affects climate forcing calculations, atmospheric visibility, and the interpretation of satellite observations of aerosol optical depth. We evaluated the representation of aerosol mass scattering efficiency (αsp) in the GEOS-Chem chemical transport model over North America using collocated measurements of aerosol scatter and mass from IMPROVE network sites between 2000–2015. We found a positive bias in mass scattering efficiency given current assumptions of aerosol size distributions and particle hygroscopicity in the model. We found that overestimation of mass scattering efficiency was most significant in dry (RH 

scholarly journals Multi sensor reanalysis of total ozone

2010 ◽  
Vol 10 (22) ◽  
pp. 11277-11294 ◽  
Author(s):  
R. J. van der A ◽  
M. A. F. Allaart ◽  
H. J. Eskes
Keyword(s):  
Data Assimilation ◽  
Total Ozone ◽  
Transport Model ◽  
Chemical Transport ◽  
Satellite Observations ◽  
Chemical Transport Model ◽  
Model Driven ◽  
Near Ultraviolet ◽  
Time Period ◽  
Sample Frequency

Abstract. A single coherent total ozone dataset, called the Multi Sensor Reanalysis (MSR), has been created from all available ozone column data measured by polar orbiting satellites in the near-ultraviolet Huggins band in the last thirty years. Fourteen total ozone satellite retrieval datasets from the instruments TOMS (on the satellites Nimbus-7 and Earth Probe), SBUV (Nimbus-7, NOAA-9, NOAA-11 and NOAA-16), GOME (ERS-2), SCIAMACHY (Envisat), OMI (EOS-Aura), and GOME-2 (Metop-A) have been used in the MSR. As first step a bias correction scheme is applied to all satellite observations, based on independent ground-based total ozone data from the World Ozone and Ultraviolet Data Center. The correction is a function of solar zenith angle, viewing angle, time (trend), and effective ozone temperature. As second step data assimilation was applied to create a global dataset of total ozone analyses. The data assimilation method is a sub-optimal implementation of the Kalman filter technique, and is based on a chemical transport model driven by ECMWF meteorological fields. The chemical transport model provides a detailed description of (stratospheric) transport and uses parameterisations for gas-phase and ozone hole chemistry. The MSR dataset results from a 30-year data assimilation run with the 14 corrected satellite datasets as input, and is available on a grid of 1× 1 1/2° with a sample frequency of 6 h for the complete time period (1978–2008). The Observation-minus-Analysis (OmA) statistics show that the bias of the MSR analyses is less than 1% with an RMS standard deviation of about 2% as compared to the corrected satellite observations used.

scholarly journals Multi sensor reanalysis of total ozone

2010 ◽  
Vol 10 (4) ◽  
pp. 11401-11448 ◽  
Author(s):  
R. J. van der A ◽  
M. A. F. Allaart ◽  
H. J. Eskes
Keyword(s):  
Data Assimilation ◽  
Total Ozone ◽  
Transport Model ◽  
Chemical Transport ◽  
Satellite Observations ◽  
Chemical Transport Model ◽  
Model Driven ◽  
Stratospheric Temperature ◽  
Near Ultraviolet ◽  
Time Period

Abstract. A single coherent total ozone dataset, called the Multi Sensor Reanalysis (MSR), has been created from all available ozone column data measured by polar orbiting satellites in the near-ultraviolet Huggins band in the last thirty years. Fourteen total ozone satellite retrieval datasets from the instruments TOMS (on the satellites Nimbus-7 and Earth Probe), SBUV (Nimbus-7, NOAA-9, NOAA-11 and NOAA-16), GOME (ERS-2), SCIAMACHY (Envisat), OMI (EOS-Aura), and GOME-2 (Metop-A) have been used in the MSR. As first step a bias correction scheme is applied to all satellite observations, based on independent ground-based total ozone data from the World Ozone and Ultraviolet Data Center. The correction is a function of solar zenith angle, viewing angle, time (trend), and stratospheric temperature. As second step data assimilation was applied to create a global dataset of total ozone analyses. The data assimilation method is a sub-optimal implementation of the Kalman filter technique, and is based on a chemical transport model driven by ECMWF meteorological fields. The chemical transport model provides a detailed description of (stratospheric) transport and uses parameterisations for gas-phase and ozone hole chemistry. The MSR dataset results from a 30-year data assimilation run with the 14 corrected satellite datasets as input, and is available on a grid of 1×1½ degrees with a sample frequency of 6 h for the complete time period (1978–2008). The Observation-minus-Analysis (OmA) statistics show that the bias of the MSR analyses is less than 1 percent with an RMS standard deviation of about 2 percent as compared to the corrected satellite observations used.

scholarly journals The UIUC three-dimensional stratospheric chemical transport model: Description and evaluation of the simulated source gases and ozone

1999 ◽  
Vol 104 (D9) ◽  
pp. 11755-11781 ◽  
Author(s):  
Eugene V. Rozanov ◽  
Vladimir A. Zubov ◽  
Michael E. Schlesinger ◽  
Fanglin Yang ◽  
Natalia G. Andronova
Keyword(s):  
Transport Model ◽  
Three Dimensional ◽  
Chemical Transport ◽  
Model Description ◽  
Chemical Transport Model ◽  
Simulated Source

scholarly journals Record-breaking ozone loss in the Arctic winter 2010/2011: comparison with 1996/1997

2012 ◽  
Vol 12 (15) ◽  
pp. 7073-7085 ◽  
Author(s):  
J. Kuttippurath ◽  
S. Godin-Beekmann ◽  
F. Lefèvre ◽  
G. Nikulin ◽  
M. L. Santee ◽  
...  
Keyword(s):  
Transport Model ◽  
Chemical Transport ◽  
The Arctic ◽  
Altitude Range ◽  
Chemical Transport Model ◽  
Model Simulations ◽  
Ozone Loss ◽  
Elevated Ozone ◽  
Record Value ◽  
First Time

Abstract. We present a detailed discussion of the chemical and dynamical processes in the Arctic winters 1996/1997 and 2010/2011 with high resolution chemical transport model (CTM) simulations and space-based observations. In the Arctic winter 2010/2011, the lower stratospheric minimum temperatures were below 195 K for a record period of time, from December to mid-April, and a strong and stable vortex was present during that period. Simulations with the Mimosa-Chim CTM show that the chemical ozone loss started in early January and progressed slowly to 1 ppmv (parts per million by volume) by late February. The loss intensified by early March and reached a record maximum of ~2.4 ppmv in the late March–early April period over a broad altitude range of 450–550 K. This coincides with elevated ozone loss rates of 2–4 ppbv sh−1 (parts per billion by volume/sunlit hour) and a contribution of about 30–55% and 30–35% from the ClO-ClO and ClO-BrO cycles, respectively, in late February and March. In addition, a contribution of 30–50% from the HOx cycle is also estimated in April. We also estimate a loss of about 0.7–1.2 ppmv contributed (75%) by the NOx cycle at 550–700 K. The ozone loss estimated in the partial column range of 350–550 K exhibits a record value of ~148 DU (Dobson Unit). This is the largest ozone loss ever estimated in the Arctic and is consistent with the remarkable chlorine activation and strong denitrification (40–50%) during the winter, as the modeled ClO shows ~1.8 ppbv in early January and ~1 ppbv in March at 450–550 K. These model results are in excellent agreement with those found from the Aura Microwave Limb Sounder observations. Our analyses also show that the ozone loss in 2010/2011 is close to that found in some Antarctic winters, for the first time in the observed history. Though the winter 1996/1997 was also very cold in March–April, the temperatures were higher in December–February, and, therefore, chlorine activation was moderate and ozone loss was average with about 1.2 ppmv at 475–550 K or 42 DU at 350–550 K, as diagnosed from the model simulations and measurements.

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