scholarly journals Local-time Dependence of Chemical Species in the Venusian Mesosphere

2022 ◽  
Vol 3 (1) ◽  
pp. 3
Author(s):  
Wencheng D. Shao ◽  
Xi Zhang ◽  
João Mendonça ◽  
Thérèse Encrenaz
Keyword(s):  
Local Time ◽  
General Circulation ◽  
Transport Model ◽  
Three Dimensional ◽  
Chemical Species ◽  
Circulation Model ◽  
Chemical Transport Model ◽  
Local Maxima ◽  
Time Patterns ◽  
Time Variations

Abstract Observed chemical species in the Venusian mesosphere show local-time variabilities. SO2 at the cloud top exhibits two local maxima over local time, H2O at the cloud top is uniformly distributed, and CO in the upper atmosphere shows a statistical difference between the two terminators. In this study, we investigated these local-time variabilities using a three-dimensional (3D) general circulation model (GCM) in combination with a two-dimensional (2D) chemical transport model (CTM). Our simulation results agree with the observed local-time patterns of SO2, H2O, and CO. The two-maximum pattern of SO2 at the cloud top is caused by the superposition of the semidiurnal thermal tide and the retrograde superrotating zonal (RSZ) flow. SO2 above 85 km shows a large day–night difference resulting from both photochemistry and the subsolar-to-antisolar (SS-AS) circulation. The transition from the RSZ flows to SS-AS circulation can explain the CO difference between two terminators and the displacement of the CO local-time maximum with respect to the antisolar point. H2O is long-lived and exhibits very uniform distribution over space. We also present the local-time variations of HCl, ClO, OCS, and SO simulated by our model and compare to the sparse observations of these species. This study highlights the importance of multidimensional CTMs for understanding the interaction between chemistry and dynamics in the Venusian mesosphere.

Predictability of Total Ozone Using a Global Three-Dimensional Chemical Transport Model Coupled with the MRI/JMA98 GCM

2005 ◽  
Vol 133 (8) ◽  
pp. 2262-2274 ◽  
Author(s):  
T. T. Sekiyama ◽  
K. Shibata
Keyword(s):  
Total Ozone ◽  
General Circulation ◽  
Transport Model ◽  
Three Dimensional ◽  
Circulation Model ◽  
Chemical Transport ◽  
Japan Meteorological Agency ◽  
High Latitudes ◽  
Chemical Transport Model ◽  
Mean Square Errors

Abstract A global three-dimensional chemical transport model is being developed for forecasting total ozone. The model includes detailed stratospheric chemistry and transport and couples with a dynamical module of the Meteorological Research Institute/Japan Meteorological Agency 1998 (MRI/JMA98) general circulation model, which can yield realistic atmospheric fields through a meteorological assimilation system. Its predictability on total ozone is investigated for up to 4 weeks from 1997 to 2000. Global root-mean-square errors (rmses) of a control run are approximately 10 DU (3% of total ozone) throughout a year; the control run results are used as initial values for hindcast experiments. Rmses of the hindcast experiments globally range from 10 to 30 DU. The anomaly correlation between the 5-day forecasts and satellite measurements is approximately 0.6 throughout a year in the mid- and high latitudes of both the Northern and Southern Hemispheres. Thus, the model has potential for utilization on total ozone forecasts up to 5 days. In the northern mid- and high latitudes, the model produces better total ozone forecasts than the persistence up to 2 weeks, indicating that the deterministic limit of the total ozone forecasts is durationally comparable to that of weather forecasts. Good correlations between changes in total ozone and 100-hPa geopotential height reveal that the predictability of the dynamical field in the lower stratosphere critically affects the predictability of total ozone.

scholarly journals Meteorological modes of variability for fine particulate matter (PM2.5) air quality in the United States: implications for PM2.5 sensitivity to climate change

2012 ◽  
Vol 12 (6) ◽  
pp. 3131-3145 ◽  
Author(s):  
A. P. K. Tai ◽  
L. J. Mickley ◽  
D. J. Jacob ◽  
E. M. Leibensperger ◽  
L. Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Transport Model ◽  
Circulation Model ◽  
Multiple Linear Regression Model ◽  
The United States ◽  
Chemical Transport Model ◽  
Modes Of Variability ◽  
The Us ◽  
Cyclone Frequency

Abstract. We applied a multiple linear regression model to understand the relationships of PM2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM2.5 to climate change. We used 2004–2008 PM2.5 observations from ~1000 sites (~200 sites for PM2.5 components) and compared to results from the GEOS-Chem chemical transport model (CTM). All data were deseasonalized to focus on synoptic-scale correlations. We find strong positive correlations of PM2.5 components with temperature in most of the US, except for nitrate in the Southeast where the correlation is negative. Relative humidity (RH) is generally positively correlated with sulfate and nitrate but negatively correlated with organic carbon. GEOS-Chem results indicate that most of the correlations of PM2.5 with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling PM2.5 variability, and show that 20–40% of the observed PM2.5 day-to-day variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. These and other synoptic transport modes drive most of the overall correlations of PM2.5 with temperature and RH except in the Southeast. We show that interannual variability of PM2.5 in the US Midwest is strongly correlated with cyclone frequency as diagnosed from a spectral-autoregressive analysis of the dominant meteorological mode. An ensemble of five realizations of 1996–2050 climate change with the GISS general circulation model (GCM) using the same climate forcings shows inconsistent trends in cyclone frequency over the Midwest (including in sign), with a likely decrease in cyclone frequency implying an increase in PM2.5. Our results demonstrate the need for multiple GCM realizations (because of climate chaos) when diagnosing the effect of climate change on PM2.5, and suggest that analysis of meteorological modes of variability provides a computationally more affordable approach for this purpose than coupled GCM-CTM studies.

scholarly journals GCAP 2.0: A global 3-D chemical-transport model framework for past, present, and future climate scenarios

2021 ◽  
Author(s):  
Lee Thomas Murray ◽  
Eric M. Leibensperger ◽  
Clara Orbe ◽  
Loretta J. Mickley ◽  
Melissa Sulprizio
Keyword(s):  
General Circulation ◽  
Transport Model ◽  
Coupled Model ◽  
Circulation Model ◽  
Chemical Transport ◽  
Recent Past ◽  
Chemical Transport Model ◽  
Model Framework ◽  
Intercomparison Project ◽  
Goddard Institute

Abstract. This manuscript describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the preindustrial and recent past. In addition, meteorology is available for the near future and end-of-the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) product and with observational constraints.

scholarly journals Projected effect of 2000–2050 changes in climate and emissions on aerosol levels in China and associated transboundary transport

2013 ◽  
Vol 13 (3) ◽  
pp. 6501-6551
Author(s):  
H. Jiang ◽  
H. Liao ◽  
H. O. T. Pye ◽  
S. Wu ◽  
L. J. Mickley ◽  
...  
Keyword(s):  
Climate Change ◽  
South Asia ◽  
General Circulation ◽  
Transport Model ◽  
Large Fraction ◽  
Eastern China ◽  
Circulation Model ◽  
Western China ◽  
Valuable Insight ◽  
Chemical Transport Model

Abstract. We investigate the 2000–2050 changes in concentrations of aerosols in China and the associated transboundary aerosol transport by using the chemical transport model GEOS-Chem driven by the Goddard Institute for Space Studies (GISS) general circulation model (GCM) 3 at 4° × 5° resolution. Future changes in climate and emissions projected by the IPCC A1B scenario are imposed separately and together through sensitivity simulations. Accounting for sulfate, nitrate, ammonium, black carbon (BC), and organic carbon (OC) aerosols, concentrations of individual aerosol species change by −2.3 to +1.7 μg m−3 and PM2.5 levels are projected to change by about 10–20% in eastern China as a result of 2000–2050 change in climate alone. With future changes in anthropogenic emissions alone, concentrations of sulfate, BC, and OC are simulated to decrease because of reductions in emissions, and those of nitrate are predicted to increase because of higher NOx emissions combined with decreases in sulfate. The net result is a reduction of seasonal mean PM2.5 concentrations in eastern China by 2–9.5 μg m−3 (or 10–30%) over 2000–2050. It is noted that current emission inventories for BC and OC over China are found to be inadequate at present. Transboundary fluxes of different aerosol species show different sensitivities to future changes in climate and emissions. The annual outflow of PM2.5 from eastern China to the western Pacific is estimated to change by −6.0%, −1.5%, and −9.0% over 2000–2050 owing to climate change alone, changes in emissions alone, and changes in both climate and emissions, respectively. The fluxes of nitrate and ammonium aerosols from Europe and Central Asia into western China increase over 2000–2050 by changes in emissions, leading to a 15% increase in annual inflow of PM2.5 to western China with future changes in both emissions and climate. Fluxes of BC and OC from South Asia to China in spring contribute to a large fraction of the annual inflow of PM2.5. The annual inflow of PM2.5 from South Asia and Southeast Asia to China is estimated to change by −55%, +133%, and +63% over 2000–2050 owing to climate change alone, changes in emissions alone, and changes in both climate and emissions, respectively. While the 4° × 5° spatial resolution is a limitation of the present study, the direction of predicted changes in aerosol levels and transboundary fluxes still provides valuable insight into future air quality.

Impact of ECMWF ERA-Interim and ERA5 reanalysis on the simulated tracer transport and polar ozone loss using a chemical transport model TOMCAT/SLIMCAT 

2020 ◽  
Author(s):  
Wuhu Feng ◽  
Martyn Chipperfield ◽  
Sandip Dhmose ◽  
Florence Goutail ◽  
Michelle Santee ◽  
...  
Keyword(s):  
Transport Model ◽  
Three Dimensional ◽  
Chemical Species ◽  
Chemical Transport ◽  
Tropospheric Chemistry ◽  
Tracer Transport ◽  
Chemical Transport Model ◽  
Ozone Loss ◽  
The Impact ◽  
Polar Ozone

<div> <p>Three-dimensional chemical transport models (CTMs) have been widely used in a wide variety of scientific studies (e.g., to obtain a better understanding of tracer transport and to study the dynamical and chemical processes which control polar ozone losses etc). However, there are still some uncertainties in the model simulations and indeed in our understanding. For example, the accuracy of ozone simulations largely depends on the transport, chemistry and treatment of PSCs in the model as well as the forcing files. </p> <p>Here we have used a  CTM model TOMCAT/SLIMCAT with a detailed description of stratospheric and tropospheric chemistry forced by differnt wind fields (ECMWF ERA-Interim and <span>ERA5</span> reanalysis datasets) to investigate the different dynamical fields on the simulated tracer transport, ozone and other chemical species. Both simulations have been run from 1979 to 2018. First we will assess the impact of different reanalysis data on the idealised tracers when the model includes additional process of the gravitational separation of gases (e.g., Ar/N2) and compare the model results with dataset of gravitational fractionation of Ar/N2 and AoA observations made on flask samples from three airborne research projects. Modelled AoA will be also compared with MIPAS data.  Then we will focus on the polar ozone loss from late 1990 to 2018 and quntify<br>the amount of chemical ozone loss using both models and satellite observations as well as  SAOZ measurements. The year-to-year variation of polar ozone depletion will also be discussed, in particular for the recent years of decreasing stratospheric chlorine loading. </p> </div>

scholarly journals GCAP 2.0: a global 3-D chemical-transport model framework for past, present, and future climate scenarios

2021 ◽  
Vol 14 (9) ◽  
pp. 5789-5823
Author(s):  
Lee T. Murray ◽  
Eric M. Leibensperger ◽  
Clara Orbe ◽  
Loretta J. Mickley ◽  
Melissa Sulprizio
Keyword(s):  
General Circulation ◽  
Transport Model ◽  
Coupled Model ◽  
Circulation Model ◽  
Chemical Transport ◽  
Recent Past ◽  
Chemical Transport Model ◽  
Model Framework ◽  
Intercomparison Project ◽  
Goddard Institute

Abstract. This paper describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the pre-industrial era and the recent past. In addition, meteorology is available for the near future and end of the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport, and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) product and with observational constraints.

scholarly journals Projected effect of 2000–2050 changes in climate and emissions on aerosol levels in China and associated transboundary transport

2013 ◽  
Vol 13 (16) ◽  
pp. 7937-7960 ◽  
Author(s):  
H. Jiang ◽  
H. Liao ◽  
H. O. T. Pye ◽  
S. Wu ◽  
L. J. Mickley ◽  
...  
Keyword(s):  
Climate Change ◽  
South Asia ◽  
General Circulation ◽  
Transport Model ◽  
Large Fraction ◽  
Eastern China ◽  
Circulation Model ◽  
Western China ◽  
Valuable Insight ◽  
Chemical Transport Model

Abstract. We investigate projected 2000–2050 changes in concentrations of aerosols in China and the associated transboundary aerosol transport by using the chemical transport model GEOS-Chem driven by the Goddard Institute for Space Studies (GISS) general circulation model (GCM) 3 at 4° × 5° resolution. Future changes in climate and emissions projected by the IPCC A1B scenario are imposed separately and together through sensitivity simulations. Accounting for sulfate, nitrate, ammonium, black carbon (BC), and organic carbon (OC) aerosols, concentrations of individual aerosol species change by −1.5 to +0.8 μg m−3, and PM2.5 levels are projected to change by about 10–20% in eastern China as a result of 2000–2050 change in climate alone. With future changes in anthropogenic emissions alone, concentrations of sulfate, BC, and OC are simulated to decrease because of assumed reductions in emissions, and those of nitrate are predicted to increase because of higher NOx emissions combined with decreases in sulfate. The net result is a predicted reduction of seasonal mean PM2.5 concentrations in eastern China by 1–8 μg m−3 (or 10–40%) over 2000–2050. It is noted that current emission inventories for BC and OC over China are judged to be inadequate at present. Transboundary fluxes of different aerosol species show different sensitivities to future changes in climate and emissions. The annual outflow of PM2.5 from eastern China to the western Pacific is estimated to change by −7.0%, −0.7%, and −9.0% over 2000–2050 owing to climate change alone, changes in emissions alone, and changes in both climate and emissions, respectively. The fluxes of nitrate and ammonium aerosols from Europe and Central Asia into western China increase over 2000–2050 in response to projected changes in emissions, leading to a 10.5% increase in annual inflow of PM2.5 to western China with future changes in both emissions and climate. Fluxes of BC and OC from South Asia to China in spring contribute a large fraction of the annual inflow of PM2.5. The annual inflow of PM2.5 from South Asia and Southeast Asia to China is estimated to change by −8%, +281%, and +227% over 2000–2050 owing to climate change alone, changes in emissions alone, and changes in both climate and emissions, respectively. While the 4° × 5° spatial resolution is a limitation of the present study, the direction of predicted changes in aerosol levels and transboundary fluxes still provides valuable insight into future air quality.

scholarly journals ASIS v1.0: an adaptive solver for the simulation of atmospheric chemistry

2017 ◽  
Vol 10 (4) ◽  
pp. 1467-1485 ◽  
Author(s):  
Daniel Cariolle ◽  
Philippe Moinat ◽  
Hubert Teyssèdre ◽  
Luc Giraud ◽  
Béatrice Josse ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
General Circulation ◽  
Transport Model ◽  
Circulation Model ◽  
Implicit Scheme ◽  
Chemical Transport Model ◽  
Time Stepping ◽  
Implicit Solvers ◽  
One Step ◽  
Phase Chemistry

Abstract. This article reports on the development and tests of the adaptive semi-implicit scheme (ASIS) solver for the simulation of atmospheric chemistry. To solve the ordinary differential equation systems associated with the time evolution of the species concentrations, ASIS adopts a one-step linearized implicit scheme with specific treatments of the Jacobian of the chemical fluxes. It conserves mass and has a time-stepping module to control the accuracy of the numerical solution. In idealized box-model simulations, ASIS gives results similar to the higher-order implicit schemes derived from the Rosenbrock's and Gear's methods and requires less computation and run time at the moderate precision required for atmospheric applications. When implemented in the MOCAGE chemical transport model and the Laboratoire de Météorologie Dynamique Mars general circulation model, the ASIS solver performs well and reveals weaknesses and limitations of the original semi-implicit solvers used by these two models. ASIS can be easily adapted to various chemical schemes and further developments are foreseen to increase its computational efficiency, and to include the computation of the concentrations of the species in aqueous-phase in addition to gas-phase chemistry.

scholarly journals Meteorological modes of variability for fine particulate matter (PM<sub>2.5</sub>) air quality in the United States: implications for PM<sub>2.5</sub> sensitivity to climate change

2011 ◽  
Vol 11 (11) ◽  
pp. 31031-31066 ◽  
Author(s):  
A. P. K. Tai ◽  
L. J. Mickley ◽  
D. J. Jacob ◽  
E. M. Leibensperger ◽  
L. Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Transport Model ◽  
Circulation Model ◽  
Multiple Linear Regression Model ◽  
The United States ◽  
Chemical Transport Model ◽  
Modes Of Variability ◽  
The Us ◽  
Cyclone Frequency

Abstract. We applied a multiple linear regression model to understand the relationships of PM2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM2.5 to climate change. We used 2004–2008 PM2.5 observations from ~1000 sites (~200 sites for PM2.5 components) and compared to results from the GEOS-Chem chemical transport model (CTM). All data were deseasonalized to focus on synoptic-scale correlations. We find strong positive correlations of PM2.5 components with temperature in most of the US, except for nitrate in the Southeast where the correlation is negative. Relative humidity (RH) is generally positively correlated with sulfate and nitrate but negatively correlated with organic carbon. GEOS-Chem results indicate that most of the correlations of PM2.5 with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling PM2.5 variability, and show that 20–40% of the observed PM2.5 day-to-day variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. These and other synoptic transport modes drive most of the overall correlations of PM2.5 with temperature and RH except in the Southeast. We show that interannual variability of PM2.5 in the US Midwest is strongly correlated with cyclone frequency as diagnosed from a spectral-autoregressive analysis of the dominant meteorological mode. An ensemble of five realizations of 1996–2050 climate change with the GISS general circulation model (GCM) using the same climate forcings shows inconsistent trends in cyclone frequency over the Midwest (including in sign), with a likely decrease in cyclone frequency implying an increase in PM2.5. Our results demonstrate the need for multiple GCM realizations (because of climate chaos) when diagnosing the effect of climate change on PM2.5, and suggest that analysis of meteorological modes of variability provides a computationally more affordable approach for this purpose than coupled GCM-CTM studies.

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