scholarly journals Evaluation of SO<sub>2</sub>, SO<sub>4</sub><sup>2−</sup> and an updated SO<sub>2</sub> dry deposition parameterization in the United Kingdom Earth System Model

2021 ◽  
Vol 21 (24) ◽  
pp. 18465-18497
Author(s):  
Catherine Hardacre ◽  
Jane P. Mulcahy ◽  
Richard J. Pope ◽  
Colin G. Jones ◽  
Steven T. Rumbold ◽  
...  
Keyword(s):  
United Kingdom ◽  
Dry Deposition ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
The United Kingdom ◽  
The Usa ◽  
Simulated Surface ◽  
So2 Dry Deposition ◽  
Total Column

Abstract. In this study we evaluate simulated surface SO2 and sulfate (SO42-) concentrations from the United Kingdom Earth System Model (UKESM1) against observations from ground-based measurement networks in the USA and Europe for the period 1987–2014. We find that UKESM1 captures the historical trend for decreasing concentrations of atmospheric SO2 and SO42- in both Europe and the USA over the period 1987–2014. However, in the polluted regions of the eastern USA and Europe, UKESM1 over-predicts surface SO2 concentrations by a factor of 3 while under-predicting surface SO42- concentrations by 25 %–35 %. In the cleaner western USA, the model over-predicts both surface SO2 and SO42- concentrations by factors of 12 and 1.5 respectively. We find that UKESM1’s bias in surface SO2 and SO42- concentrations is variable according to region and season. We also evaluate UKESM1 against total column SO2 from the Ozone Monitoring Instrument (OMI) using an updated data product. This comparison provides information about the model's global performance, finding that UKESM1 over-predicts total column SO2 over much of the globe, including the large source regions of India, China, the USA, and Europe as well as over outflow regions. Finally, we assess the impact of a more realistic treatment of the model's SO2 dry deposition parameterization. This change increases SO2 dry deposition to the land and ocean surfaces, thus reducing the atmospheric loading of SO2 and SO42-. In comparison with the ground-based and satellite observations, we find that the modified parameterization reduces the model's over-prediction of surface SO2 concentrations and total column SO2. Relative to the ground-based observations, the simulated surface SO42- concentrations are also reduced, while the simulated SO2 dry deposition fluxes increase.

scholarly journals Evaluation of SO<sub>2</sub>, SO<sub>4</sub><sup>2−</sup> and an updated SO<sub>2</sub> dry deposition parameterization in UKESM1

2021 ◽  
Author(s):  
Catherine Hardacre ◽  
Jane P. Mulcahy ◽  
Richard Pope ◽  
Colin G. Jones ◽  
Steven R. Rumbold ◽  
...  
Keyword(s):  
Dry Deposition ◽  
Ozone Monitoring Instrument ◽  
Source Regions ◽  
The United Kingdom ◽  
Eastern Usa ◽  
The Usa ◽  
Simulated Surface ◽  
The Impact ◽  
So2 Dry Deposition ◽  
Total Column

Abstract. In this study we evaluate simulated surface SO2 and sulphate (SO42−) concentrations from the United Kingdom Earth System Model (UKESM1) against observations from ground based measurement networks in the USA and Europe for the period 1987 to 2014. We find that UKESM1 captures the historical trend for decreasing concentrations of atmospheric SO2 and SO42− in both Europe and the USA over the period 1987 to 2014. However, in the polluted regions of the eastern USA and Europe, UKESM1 over-predicts surface SO2 concentrations by a factor of 3, while under-predicting surface SO42− concentrations by 25–35 %. In the cleaner western USA, the model over-predicts both surface SO2 and SO42− concentrations by a factor of 12 and 1.5 respectively. We find that UKESM1’s bias in surface SO2 and SO42− concentrations is variable according to region and season. We also evaluate UKESM1 against total column SO2 from the Ozone Monitoring Instrument (OMI) using an updated data product. This comparison provides information about the model’s global performance, finding that UKESM1 over predicts total column SO2 over much of the globe, including the large source regions of India, China, the USA and Europe as well as over outflow regions. Finally, we assess the impact of a more realistic treatment of the model’s SO2 dry deposition parameterization. This change increases SO2 dry deposition to the land and ocean surfaces, thus reducing the atmospheric loading of SO2 and SO42− . In comparison with the ground-based and satellite observations, we find that the modified parameterization reduces the model’s over prediction of surface SO2 concentrations and total column SO2. Relative to the ground-based observations the simulated surface SO42− concentrations are also reduced, while the simulated SO2 dry deposition fluxes increase.

scholarly journals Evaluation of Earth System Model and Atmospheric Inversion using Total Column CO2 Observations from GOSAT and OCO-2

2021 ◽  
Author(s):  
Prabir K Patra ◽  
Tomohiro Hajima ◽  
Ryu Saito ◽  
Naveen Chandra ◽  
Yukio Yoshida ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Greenhouse Gases ◽  
Satellite Remote Sensing ◽  
Earth System Model ◽  
System Model ◽  
Co2 Fluxes ◽  
Earth System ◽  
In Situ Data ◽  
Total Column

Abstract The measurements of one of the major greenhouse gases, carbon dioxide (CO2), are being made using dedicated satellite remote sensing since the launch of the greenhouse gases observing satellite (GOSAT) by Japan Aerospace Exploration Agency (JAXA) in 2009 and National Aeronautics and Space Administration (NASA) Orbiting Carbon Observatory-2 (OCO-2). In the past 10 years, estimation of CO2 fluxes from land and ocean using the earth system models (ESMs) and inverse modelling of in situ atmospheric CO2 data have also made significant progress. We attempt, for the first time, to evaluate the CO2 fluxes simulated by an earth system model (MIROC-ES2L) and the fluxes estimated by an inverse model (MIROC4-Inv) using in situ data by comparing with GOSAT and OCO-2 observations. Both MIROC-ES2L and MIROC4-Inv fluxes are used in the MIROC4-atmospheric chemistry transport model (referred to as ACTM_ES2LF and ACTM_InvF, respectively) for calculating total column CO2 mole fraction (XCO2) that are sampled at the time and location of the satellite measurements. Both the ACTM simulations agreed well with the GOSAT and OCO-2 satellite observations, within 2 ppm for the spatial maps and time evolutions of the zonal mean distributions. Our results suggest that the inverse model using in situ data are more consistent with the OCO-2 retrievals, compared to those of the GOSAT XCO2 data due to the higher accuracy of the former. This suggests that the MIROC4-Inv fluxes are of sufficient quality to evaluate MIROC-ES2L simulated fluxes. The ACTM_ES2LF simulation shows a slightly weaker seasonal cycle for the meridional profiles of CO2 fluxes, compared to that from the ACTM_InvF. This difference is revealed by greater XCO2 differences for ACTM_ES2LF vs GOSAT, compared to those of ACTM_InvF vs GOSAT. Using remote sensing based global products of leaf area index (LAI) and gross primary productivity (GPP) over land, we show a weaker sensitivity of MIROC-ES2L biospheric activities to the weather and climate in the tropical regions. Our results clearly suggest the usefulness of XCO2 measurements by satellite remote sensing for evaluation of large-scale ESMs, which so far remained untested by the sparse in situ data.

Challenging UKESM1 with SO2 and sulphate observational data to evaluate the aerosol sulphur cycle 

2021 ◽  
Author(s):  
Catherine Hardacre ◽  
Jane P. Mulcahy ◽  
Richard Pope ◽  
Can Li ◽  
Steve Rumbold ◽  
...  
Keyword(s):  
Dry Deposition ◽  
Cold Bias ◽  
Good Representation ◽  
Earth System ◽  
Ozone Monitoring Instrument ◽  
Radiative Balance ◽  
The Earth ◽  
Sulphur Cycle ◽  
The Usa ◽  
So2 Dry Deposition

&lt;div&gt; &lt;p&gt;UKESM1 is the latest generation Earth system model to be developed in the UK. It simulates the core physical and dynamical processes of land, atmosphere, ocean and sea ice systems which are extended to incorporate key marine and terrestrial biogeochemical cycles. These include the carbon and nitrogen cycles and interactive stratosphere-troposphere trace gas chemistry. Feedbacks between these components that have an important amplifying or dampening effect on the physical climate, and/or change themselves in response to changes in the physical climate are also included. One focus for the future development of UKESM1 is improved treatment of sulphur processes, including emission, chemical processing and deposition in the aerosol-chemistry scheme, UKCA-Mode. These processes span land-atmosphere and ocean-atmosphere boundaries and can therefore impact feedbacks between these systems. Emissions of SO2 can be oxidised to form sulphate aerosol, which plays a key role in both acid deposition, atmospheric aerosol loading and cloud properties, thereby directly contributing to the Earth&amp;#8217;s radiative balance. Good representation of sulphur processes in UKESM1 is therefore essential for constraining uncertainties associated with the impacts of aerosols on the Earth system and thus understanding the global climate. Here we challenge UKESM1 with observations of SO2 and&amp;#160;sulphate&amp;#160;from ground-based measurement networks in Europe and the USA, and of SO2 from the Ozone Monitoring Instrument (OMI). We use these to evaluate temporal and spatial biases in the model&amp;#8217;s simulation of SO2 and sulphate.&amp;#160;&amp;#160;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;We find that UKESM1 captures the historical trend for decreasing concentrations of atmospheric SO2 and&amp;#160;sulphate&amp;#160;in both Europe and the USA over the period 1987 to 2014. However, in the polluted regions of the Eastern USA and Europe, UKESM1 over-predicts surface SO2 concentrations by an average of 320-340%, while under-predicting surface&amp;#160;sulphate&amp;#160;concentrations by 25-35%. In the cleaner Western USA, the model over-predicts both surface SO2 and&amp;#160;sulphate&amp;#160;concentrations by 1200% and 150% respectively. The variability in the direction of UKESM1&amp;#8217;s bias according to species and region suggests that the model bias may be driven differently depending on species and region. These drivers likely result from uncertainty in aspects of the sulphur cycle, including SO2 emission, loss processes (oxidation and deposition) or transport. To evaluate UKESM1 at the global scale we use a newly available data product for total column SO2 (TCSO2) from OMI. We find that UKESM1 over-predicts TCSO2 over much of the globe, particularly the large source regions of India, China, the USA and Europe as well as over background regions, including much of the ocean.&amp;#160;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;In this study we also assess changes to UKESM1&amp;#8217;s SO2 dry deposition parameterization. These changes increase SO2 dry deposition to land and ocean surfaces, thus reducing atmospheric SO2 and sulphate concentrations, and ultimately reducing cold bias in UKESM1's simulation of mid 20th C global mean surface temperatures. In comparison with the ground based and satellite observations, we find that the changes reduce UKESM1's over prediction of surface SO2 concentrations and TCSO2&lt;/p&gt; &lt;/div&gt;

scholarly journals Earth System Music: the methodology and reach of music generated from the United Kingdom Earth System Model

2020 ◽  
Author(s):  
Lee de Mora ◽  
Alistair A. Sellar ◽  
Andrew Yool ◽  
Julien Palmieri ◽  
Robin S. Smith ◽  
...  
Keyword(s):  
United Kingdom ◽  
Time Series Data ◽  
Climate Science ◽  
Practical Aspect ◽  
Scientific Data ◽  
Earth System Model ◽  
System Model ◽  
Series Data ◽  
Earth System ◽  
Science Outreach

Abstract. Scientific data is almost always represented graphically either in figures or in videos. With the ever-growing interest from the general public towards understanding climate science, it is becoming increasingly important that we present this information in ways accessible to non-experts. In this pilot study, we use time series data from the first United Kingdom Earth System model (UKESM1) to create six procedurally generated musical pieces and use them to test whether we can use music to engage with the wider community. Each of these pieces is based around a unique part of UKESM1's ocean component model, either in terms of a scientific principle or a practical aspect of modelling. In addition, each piece is arranged using a different musical progression, style and tempo. These pieces were performed by the digital piano synthesizer, TiMidity++, and were published on the lead author's YouTube channel. The videos all show the time progression of the data in time with the music and a brief description of the methodology is posted below the video. To disseminate these works, a link to each piece was published on the lead authors personal and professional social media accounts. The reach of these works was analysed using YouTube's channel monitoring toolkit for content creators, YouTube studio. In the first ninety days after the first video was published, the six pieces reached at least 251 unique viewers, and have 553 total views. We found that most of the views occurred in the fourteen days immediately after each video was published. In effect, once the concept had been demonstrated to an audience, there was reduced enthusiasm from that audience to return to it immediately. This suggests that to use music effectively as an science outreach tool, the works needs to reach new audiences or new and unique content needs to be delivered to a returning audience.

scholarly journals Earth system music: music generated from the United Kingdom Earth System Model (UKESM1)

2020 ◽  
Vol 3 (2) ◽  
pp. 263-278 ◽  
Author(s):  
Lee de Mora ◽  
Alistair A. Sellar ◽  
Andrew Yool ◽  
Julien Palmieri ◽  
Robin S. Smith ◽  
...  
Keyword(s):  
United Kingdom ◽  
Pilot Study ◽  
Time Series Data ◽  
Musical Instrument ◽  
Practical Aspect ◽  
Scientific Data ◽  
Earth System Model ◽  
System Model ◽  
Series Data ◽  
Earth System

Abstract. Scientific data are almost always represented graphically in figures or in videos. With the ever-growing interest from the general public in understanding climate sciences, it is becoming increasingly important that scientists present this information in ways that are both accessible and engaging to non-experts. In this pilot study, we use time series data from the first United Kingdom Earth System Model (UKESM1) to create six procedurally generated musical pieces. Each of these pieces presents a unique aspect of the ocean component of the UKESM1, either in terms of a scientific principle or a practical aspect of modelling. In addition, each piece is arranged using a different musical progression, style and tempo. These pieces were created in the Musical Instrument Digital Interface (MIDI) format and then performed by a digital piano synthesiser. An associated video showing the time development of the data in time with the music was also created. The music and video were published on the lead author's YouTube channel. A brief description of the methodology was also posted alongside the video. We also discuss the limitations of this pilot study and describe several approaches to extend and expand upon this work.

Earth System Music: music generated from the first United Kingdom Earth System model

2020 ◽  
Author(s):  
Lee de Mora ◽  
Alistair Sellar ◽  
Andrew Yool ◽  
Julien Palmieri ◽  
Robin S. Smith ◽  
...  
Keyword(s):  
United Kingdom ◽  
Time Series Data ◽  
Scientific Data ◽  
Earth System Model ◽  
System Model ◽  
Series Data ◽  
Historical Period ◽  
System Modelling ◽  
Earth System ◽  
Model Data

&lt;p&gt;With the ever-growing interest from the general public towards understanding climate science, it is becoming increasingly important that we present this information in ways accessible to non-experts. In this pilot study, we use time series data from the first United Kingdom Earth System model (UKESM1) to create six procedurally generated musical pieces and use them to explain the process of modelling the earth system and to engage with the wider community.&amp;#160;&lt;/p&gt;&lt;p&gt;Scientific data is almost always represented graphically either in figures or in videos. By adding audio to the visualisation of model data, the combination of music and imagery provides additional contextual clues to aid in the interpretation. Furthermore, the audiolisation of model data can be employed to generate interesting and captivating music, which can not&amp;#160; only reach a wider audience, but also hold the attention of the listeners for extended periods of time.&lt;/p&gt;&lt;p&gt;Each of the six pieces presented in this work was themed around either a scientific principle or a practical aspect of earth system modelling. These pieces demonstrate the concepts of a spin up, a pre-industrial control run, multiple historical experiments, and the use of several future climate scenarios to a wider audience. They also show the ocean acidification over the historical period, the changes in circulation, the natural variability of the pre-industrial simulations, and the expected rise in sea surface temperature over the 20th century.&amp;#160;&lt;/p&gt;&lt;p&gt;Each of these pieces were arranged using different musical progression, style and tempo. All six pieces were performed by the digital piano synthesizer, TiMidity++, and were published on the lead author's YouTube channel. The videos all show the progression of the data in time with the music and a brief description of the methodology is posted alongside the video.&amp;#160;&lt;/p&gt;&lt;p&gt;To disseminate these works, links to each piece were published on the lead author's personal and professional social media accounts. The reach of these works was also analysed using YouTube's channel monitoring toolkit for content creators, YouTube studio.&lt;/p&gt;

scholarly journals Evaluation of earth system model and atmospheric inversion using total column CO2 observations from GOSAT and OCO-2

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Prabir K. Patra ◽  
Tomohiro Hajima ◽  
Ryu Saito ◽  
Naveen Chandra ◽  
Yukio Yoshida ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Greenhouse Gases ◽  
Satellite Remote Sensing ◽  
Inverse Model ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
In Situ Data ◽  
Total Column

AbstractThe measurements of one of the major greenhouse gases, carbon dioxide (CO2), are being made using dedicated satellite remote sensing since the launch of the greenhouse gases observing satellite (GOSAT) by a three-way partnership between the Japan Aerospace Exploration Agency (JAXA), the Ministry of Environment (MoE) and the National Institute for Environmental Studies (NIES), and the National Aeronautics and Space Administration (NASA) Orbiting Carbon Observatory-2 (OCO-2). In the past 10 years, estimation of CO2 fluxes from land and ocean using the earth system models (ESMs) and inverse modelling of in situ atmospheric CO2 data have also made significant progress. We attempt, for the first time, to evaluate the CO2 fluxes simulated by an earth system model (MIROC-ES2L) and the fluxes estimated by an inverse model (MIROC4-Inv) using in situ data by comparing with GOSAT and OCO-2 observations. Both MIROC-ES2L and MIROC4-Inv fluxes are used in the MIROC4-atmospheric chemistry transport model (referred to as ACTM_ES2LF and ACTM_InvF, respectively) for calculating total column CO2 mole fraction (XCO2) that are sampled at the time and location of the satellite measurements. Both the ACTM simulations agreed well with the GOSAT and OCO-2 satellite observations, within 2 ppm for the spatial maps and time evolutions of the zonal mean distributions. Our results suggest that the inverse model using in situ data is more consistent with the OCO-2 retrievals, compared with those of the GOSAT XCO2 data due to the higher accuracy of the former. This suggests that the MIROC4-Inv fluxes are of sufficient quality to evaluate MIROC-ES2L simulated fluxes. The ACTM_ES2LF simulation shows a slightly weaker seasonal cycle for the meridional profiles of CO2 fluxes, compared with that from the ACTM_InvF. This difference is revealed by greater XCO2 differences for ACTM_ES2LF vs GOSAT, compared with those of ACTM_InvF vs GOSAT. Using remote sensing–based global products of leaf area index (LAI) and gross primary productivity (GPP) over land, we show a weaker sensitivity of MIROC-ES2L biospheric activities to the weather and climate in the tropical regions. Our results clearly suggest the usefulness of XCO2 measurements by satellite remote sensing for evaluation of large-scale ESMs, which so far remained untested by the sparse in situ data.

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