Multi-model study of HTAP II on sulfur and nitrogen deposition

Tan, Jiani; Fu, Joshua S.; Dentener, Frank; Sun, Jian; Emmons, L. K.; Tilmes, Simone; Sudo, Kengo; Flemming, Johannes; Jonson, Jan Eiof; Gravel, Sylvie; Bian, Huisheng; Davila, Yanko; Henze, D. K.; Lund, Marianne T.; Kucsera, Tom; Keating, Terry

doi:10.5194/acp-18-6847-2018

Cited by 59 publications

(52 citation statements)

References 54 publications

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“…SOCOL-AERv1 is a model with a sectional scheme that divides the sulfate aerosol size distribution into 40 bins (Sheng et al, 2015). The model succeeded in reproducing the observed background stratospheric aerosol extinctions compared to the Stratospheric Aerosol and Gas Experiment II (SAGE II) and Halogen Occultation Experiment (HALOE) measurements (Thomason, 2012), as well as the particle size distributions measured by optical particle counters (OPCs) in the midlatitudes (Deshler et al, 2003;Deshler, 2008). The SOCOL-AERv1-simulated aerosol burden of 109 Gg sulfur (S) also matched the stratospheric burden calculated from SAGE-4λ data (112 Gg S).…”

mentioning

confidence: 98%

Improved tropospheric and stratospheric sulfur cycle in the aerosol–chemistry–climate model SOCOL-AERv2

et al. 2019

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SOCOL-AERv1 was developed as an aerosolchemistry-climate model to study the stratospheric sulfur cycle and its influence on climate and the ozone layer. It includes a sectional aerosol model that tracks the sulfate particle size distribution in 40 size bins, between 0.39 nm and 3.2 µm. Sheng et al. (2015) showed that SOCOL-AERv1 successfully matched observable quantities related to stratospheric aerosol. In the meantime, SOCOL-AER has undergone significant improvements and more observational datasets have become available. In producing SOCOL-AERv2 we have implemented several updates to the model: adding interactive deposition schemes, improving the sulfate mass and particle number conservation, and expanding the tropospheric chemistry scheme. We compare the two versions of the model with background stratospheric sulfate aerosol observations, stratospheric aerosol evolution after Pinatubo, and ground-based sulfur deposition networks. SOCOL-AERv2 shows similar levels of agreement as SOCOL-AERv1 with satellite-measured extinctions and in situ optical particle counter (OPC) balloon flights. The volcanically quiescent total stratospheric aerosol burden simulated in SOCOL-AERv2 has increased from 109 Gg of sulfur (S) to 160 Gg S, matching the newly available satellite estimate of 165 Gg S. However, SOCOL-AERv2 simulates too high cross-tropopause transport of tropospheric SO 2 and/or sulfate aerosol, leading to an overestimation of lower stratospheric aerosol. Due to the current lack of upper tropospheric SO 2 measurements and the neglect of organic aerosol in the model, the lower stratospheric bias of SOCOL-AERv2 was not further improved. Model performance under volcanically perturbed conditions has also undergone some changes, resulting in a slightly shorter volcanic aerosol lifetime after the Pinatubo eruption. With the improved deposition schemes of SOCOL-AERv2, simulated sulfur wet deposition fluxes are within a factor of 2 of measured deposition fluxes at 78 % of the measurement stations globally, an agreement which is on par with previous model intercomparison studies. Because of these improvements, SOCOL-AERv2 will be better suited to studying changes in atmospheric sulfur deposition due to variations in climate and emissions.

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confidence: 98%

Improved tropospheric and stratospheric sulfur cycle in the aerosol–chemistry–climate model SOCOL-AERv2

et al. 2019

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“…Ground-based monitoring of N r deposition can be divided into two parts: wet and dry (Tan et al, 2018;Vet et al, 2014). The detailed scientific objectives of the wet N r deposition observation networks vary, but most of the observation networks mainly concentrate on the spatiotemporal variation of wet deposition of ions including N r compounds, the long-term trends of ions in precipitation, and the evaluation of ACTMs.…”

Section: Ground-based Monitoringmentioning

confidence: 99%

Reviewing Global Estimates of Surface Reactive Nitrogen Concentration and Deposition Using Satellite Observation

Liu¹,

Zhang²,

Xu³

et al. 2020

Preprint

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Abstract. Since the industrial revolution, human activities have dramatically changed the nitrogen (N) cycle in natural systems. Anthropogenic emissions of reactive nitrogen (Nr) can return to the earth's surface through atmospheric Nr deposition. Increased Nr deposition may improve ecosystem productivity. However, excessive Nr deposition can cause a series of negative effects on ecosystem health, biodiversity, soil, and water. Thus, accurate estimations of Nr deposition are necessary for evaluating its environmental impacts. The United States, Canada and Europe have successively launched a number of satellites with sensors that allow retrieval of atmospheric NO2 and NH3 column density, and therefore estimation of surface Nr concentration and deposition at an unprecedented spatiotemporal scale. Atmosphere NH3 column can be retrieved from atmospheric infra-red emission measured by IASI, AIRS, CrIS or TES, while atmospheric NO2 column can be retrieved from reflected solar radiation measured by GOME, GOME-2, SCIAMACHY, OMI, TEMPO, Sentinel and GEMS. In recent years, scientists attempted to estimate surface Nr concentration and deposition using satellite retrieval of atmospheric NO2 and NH3 columns. In this study, we give a thorough review on recent advances of estimating surface Nr concentration and deposition using the satellite retrievals of NO2 and NH3, present a framework of using satellite data to estimate surface Nr concentration and deposition based on recent works, and summarize the existing challenges for estimating surface Nr concentration and deposition using the satellite-based methods. We believe that exploiting satellite data to estimate Nr deposition has a broad and promising prospect.

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“…We interpolated modelled annual mean deposition to the coordinates of the measurements stations. Several previous model intercomparison projects that simulated deposition (Dentener et al, 2006a;Lamarque et al, 2013;Vet et al, 2014;Tan et al, 2018) will be used as benchmarks for the performance of SOCOL-AER compared with observations.…”

Section: Evaluation Of Socol-aer Deposition In Transient Simulationsmentioning

confidence: 99%

“…Since errors in emission inventories and model precipitation fields impact the evaluation of the deposition field, it is difficult to attribute errors to the deposition scheme itself. Table 3 compares the performance of SOCOL-AERv2 to past model intercomparison studies, including Photocomp (Dentener et al, 2006a), ACCMIP (Lamarque et al, 2013), HTAP I (Vet et al, 2014), and HTAP II (Tan et al, 2018). These intercomparison projects used observational data from the same networks as in the WMO database to evaluate their results.…”

Section: Wet Depositionmentioning

confidence: 99%

Improved tropospheric and stratospheric sulfur cycle in the aerosol-chemistry-climate model SOCOL-AERv2

Feinberg¹,

Sukhodolov²,

Luo³

et al. 2019

Preprint

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Abstract. SOCOL-AERv1 was developed as an aerosol-chemistry-climate model to study the stratospheric sulfur cycle and its influence on climate and the ozone layer. It includes a sectional aerosol model that tracks the sulfate particle size distribution in 40 size bins, between 0.39 nm to 3.2 µm. Sheng et al. (2015) showed that SOCOL-AERv1 successfully matched observable quantities related to stratospheric aerosol, including a simulated stratospheric aerosol burden of 109 Gg of sulfur (S), very close to the satellite-derived estimate available in 2015, 112 Gg S. In the meantime, both the satellite retrieval and SOCOL-AER have undergone significant improvements. In producing SOCOL-AERv2 we have implemented several updates to the model: adding interactive deposition schemes, improving the sulfate mass and particle number conservation, and expanding the tropospheric chemistry scheme. We compare the two versions of the model with background stratospheric sulfate aerosol observations, stratospheric aerosol evolution after Pinatubo, and ground-based sulfur deposition networks. SOCOL-AERv2 shows similar levels of agreement as SOCOL-AERv1 with satellite-measured extinctions and in situ optical particle counter (OPC) balloon flights. Also, the volcanically quiescent total stratospheric aerosol burden simulated in SOCOL-AERv2, 160 Gg S, agrees very well with the new satellite estimate of 165 Gg S. However, SOCOL-AERv2 simulates too high cross-tropopause transport of tropospheric SO2 and/or sulfate aerosol, leading to an overestimation of lower stratospheric aerosol. Due to the current lack of upper tropospheric SO2 measurements and the neglect of organic aerosol in the model, the lower stratospheric bias of SOCOL-AERv2 was not further improved. Model performance under volcanically perturbed conditions has also undergone some changes, resulting in a slightly lower shorter volcanic aerosol lifetime after the Pinatubo eruption. With the improved deposition schemes of SOCOL-AERv2, simulated sulfur wet deposition fluxes are within a factor of 2 of measured deposition fluxes at 78 % of the measurement stations globally, an agreement which is on par with previous model intercomparison studies. Because of these improvements, SOCOL-AERv2 will be better suited to studying changes to atmospheric sulfur deposition due to variations in climate and emissions.

show abstract

Multi-model study of HTAP II on sulfur and nitrogen deposition

Cited by 59 publications

References 54 publications

Improved tropospheric and stratospheric sulfur cycle in the aerosol–chemistry–climate model SOCOL-AERv2

Improved tropospheric and stratospheric sulfur cycle in the aerosol–chemistry–climate model SOCOL-AERv2

Reviewing Global Estimates of Surface Reactive Nitrogen Concentration and Deposition Using Satellite Observation

Improved tropospheric and stratospheric sulfur cycle in the aerosol-chemistry-climate model SOCOL-AERv2

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