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11 results for “Volcanism and Climate”
Climatic and societal impacts of a "forgotten" cluster of volcanic eruptions in 1108-1110 CE
<p>This repository contains all the tree-ring and historical archives used by Guillet et al. (2020) to assess the climatic impacts of the 1108-1110 CE volcanic eruptions</p> <p>For more information, we refer the user to the readme file entitled "Guillet_et_al_SciReports2020_Readme.txt"</p> <p>We note that investigations of European historical archives are still carried ongoing. The file entitled "Guillet_et_al_SciReports2020_Supp_Info_Table_S1_S2_Historical_Sources.xlsx" will be updated as new material is discovered.</p> <p>We welcome every addition or contribution that may help to extend the number of historical sources available and better document the climatic and societal response to the 1108-1110 CE cluster of eruptions. Thank you ;-)!</p>
Intital simulation of Hunga-Tonga volcanic aerosol cloud with the UM-UKCA composition-climate model
<p>This dataset is from a series of “forward projection” interactive stratospheric aerosol simulations of the Jan 2022 Hunga-Tonga volcanic aerosol cloud with the UM-UKCA composition-climate model. The model experiments predict how the cloud will disperse through 2022, and apply the UM-UKCA model at GA4 (Walters et al., 2014), with GLOMAP v8.2, as applied for the “MajorVolc” datasets for Agung, El Chichon and Pinatubo (Dhomse et al., 2020), those runs aligned with the Historical Eruption SO2 emissions Assessment experiment within ISA-MIP (Timmreck et al., 2018).</p> <p>The “standard” Hunga-Tonga GA4 UM-UKCA experiment emits 0.4Tg of SO2 at 29-31km, within a 24-hour period, matching the detrainment duration specified for the ISA-MIP HErSEA experiment protocol. Following the stronger than expected mid-visible backscatter ratios (BSR) measured by CALIOP satellite-borne lidar, and from ground-based lidar from Reunion Island (very high BSR values > 200), we also ran UM-UKCA simulations with “scaled-up Hunga-Tonga SO2 emission”, at 0.8, 1.2 and 1.6 Tg of SO2 emitted.</p> <p>Unexpectedly strong stratospheric AOD observed from the OMPS satellite months after the eruption further strengthens the motivation for these simulations.</p> <p>Several hypotheses for the high AOD from Hunga-Tonga have been suggested:<br> 1) an unusual amount of (or influence from) co-emitted ultra-fine ash particles<br> 2) “in-plume oxidised sulphate” already converted from SO2 at the time of detrainment<br> (e.g. via aqueous-phase oxidation within water droplets within the eruptive plume).<br> 3) co-emitted marine aerosol (e.g. sea-salt aerosol) from seawater vaporized in the plume<br> </p> <p>There are 4 types of netcdf files, Stratospheric AOD (saod), Effective Radius (reff), Extinction (ext) and sulphate aerosol surface area density (sad).</p> <p><br> <br> For e.g. <br> saod550_HT_0pt4Tg_T2Mz-20220101-20230831.nc contains<br> Stratospheric aerosol optical depth (sAOD) at 550nm (2D-monthly dataset vs latitude and time) with 0.4 Tg SO2 injection Jan2022 to August 2023<br> Whereas other files<br> reff_HT_0pt4Tg_T2Mz_20220101-20230831.nc,<br> sad_HT_0pt4Tg_T2Mz_20220101-20230831.nc<br> ext550_HT_0pt4Tg_T2Mz-20220101-20230831.nc</p> <p>contain particle effective radius (reff), aerosol surface area density, aerosol extinction as 3D-monthly fields (altitude, latitude , time) from the same simulation.<br> Other saod and extinction files are also available at 870 and 1020 nm.</p> <p> </p> <p>Note that these are preliminary simulations, hence we do not expect good match with the observations. We plan to perform additional UM-UKCA simulations, comparing to the satellite and ground-based lidar measurements, and to in-situ balloon observations from Reunion Island rapid response campaign & upcoming high-altitude balloon sampling flights in Brazil.</p> <p> </p> <p>References :<br> Dhomse SS, Mann GW, Antuña Marrero JC, Shallcross SE, Chipperfield MP, Carslaw KS, Marshall L, Abraham NL, Johnson CE. 2020. Evaluating the simulated radiative forcings, aerosol properties, and stratospheric warmings from the 1963 Mt Agung, 1982 El Chichón, and 1991 Mt Pinatubo volcanic aerosol clouds. Atmospheric Chemistry and Physics. 20(21), pp. 13627-13654</p> <p><br> Timmreck, C., Mann, G. W., Aquila, V., Hommel, R., Lee, L. A., Schmidt, A., Brühl, C., Carn, S., Chin, M., Dhomse, S. S., Diehl, T., English, J. M., Mills, M. J., Neely, R., Sheng, J., Toohey, M., and Weisenstein, D.: The Interactive Stratospheric Aerosol Model Intercomparison Project (ISA-MIP): motivation and experimental design, Geosci. Model Dev., 11, 25812608, https://doi.org/10.5194/gmd-11-2581-2018, 2018.</p> <p> </p>
Data for recreating figures of scientific paper by Hermanson et al on volcanic impacts on climate
<p>This data is the data necessary to recreate the figures that appear in a draft manuscript submitted to the AGU journal Journal of Geophysical Research - Atmospheres for peer review. When / if the manuscript is accepted then the article will be linked from here. The data is in netcdf files. The data was created by processing (mainly averaging) data from five different institutions. It was given to the authors for the purpose of scientific research only.</p>
Lunar eclipses illuminate timing and climate impact of medieval volcanism
<p>This repository contains all the data and codes needed to reproduce the results and figures from the article "Lunar Eclipses Illuminate Timing and Climate Impacts of the Middle Ages" published in Nature.<br> <br> For more information, we refer the user to the readme file entitled "Guillet_et_al_Nature2023_Readme.txt".<br> <br> If you have any queries, please feel free to contact us: sebastien.guillet@unige.ch<br> <br> Thank you very much ;-)</p>
Lunar eclipses illuminate timing and climate impact of medieval volcanism
<p>This repository contains all the data and codes needed to reproduce the results and figures from the article "Lunar Eclipses Illuminate Timing and Climate Impacts of the Middle Ages" published in Nature.<br> <br> For more information, we refer the user to the readme file entitled "Guillet_et_al_Nature2023_Readme.txt".<br> <br> If you have any queries, please feel free to contact us: sebastien.guillet@unige.ch<br> <br> Thank you very much ;-)</p>
GEOSCCM Simulations for Thresholds for Volcanic Climate Warming 4
<p>Selected output in NetCDF format from simulations performed with the GEOSCCM global climate model. </p>
GEOSCCM Simulations for Thresholds for Volcanic Climate Warming 3
<p>Selected output in NetCDF format from simulations performed with the GEOSCCM global climate model. </p>
ModelE simulation output used in the study "Severe Global Cooling After Volcanic Supereruptions? The Answer Hinges on Unknown Aerosol Size" in Journal of Climate (2024)
<p>The included files are the GISS ModelE output needed to replicate the figures in McGraw et al 2023, "Severe Global Cooling After Volcanic Supereruptions? The Answer Hinges on Unknown Aerosol Size"</p> <p>Most of the data herein is output from GISS ModelE2.2 simulations that did not include interactive aerosol microphysics and chemistry. Instead, aerosol extinction and effective radius were input into the model from scaled Easy Volcanic Aerosol [Toohey et al, GMD 2016] output, as described in this study's Methods section. To calculate volcanic temperature impacts and forcings at combinations of injected sulfur mass and peak effective radius (Reff) that were not simulated, we used 2D linear interpolation with the scipy function 'Rbf'.</p> <p>Separately included is output from GISS ModelE2.1 with MATRIX interactive aerosol microphysics and chemistry [Bauer et al, ACP 2008]. Note that the injections were scaled to match that a 6.5 Tg sulfur (S) injection in ModelE2.1/MATRIX best replicated the aerosol optical depth (AOD) and effective radius observations of the 1991 Pinatubo event despite this injection being most commonly considered an 9 Tg S injection. Hence, to produce the 1000 Tg S eruption, a 722 Tg S injected was simulated. Such a mismatch has been found in other GCMs (eg Mills et al, JGRA 2016) and may be due to aerosol quick-removal processes not represented in these models.</p> <p>Please note that simulated eruption masses are in this dataset listed in units of Tg S, but in the publication are in Tg SO2 (Tg S x 2).</p> <p>Data from other modeling studies included in Fig. 1 and tree ring estimates in Figs. S2 & S4 can be found within the cited studies.</p> <p>For additional information, please contact zachary.mcgraw@columbia.edu</p>
Enhancing Climate Model Performance through Improving Volcanic Aerosol Representation Dataset and model source codes
<p>Enhancing Climate Model Performance through Improving Volcanic Aerosol Representation: Dataset and codes used in the study</p> <p> </p>
Data from: Phylogeography and population differentiation in the Psittacanthus calyculatus (Loranthaceae) mistletoe: a complex scenario of climate-volcanism interaction along the Trans-Mexican Volcanic Belt
Aim The formation of the Trans-Mexican Volcanic Belt (TMVB) played an important role in driving inter- and intraspecific diversification at high elevations. However, Pleistocene climate changes and ecological factors might also contribute to plant genetic structuring along the volcanic belt. Here, we analysed phylogeographic patterns of the parrot-mistletoe Psittacanthus calyculatus to determine the relative contribution of these different factors. Location Trans-Mexican Volcanic Belt Methods Using nuclear and chloroplast DNA sequence data for 370 individuals, we investigate the genetic differentiation of 35 populations across the species range. We conducted phylogenetic, population and spatial genetic analyses of P. calyculatus sequences along with ecological niche modelling and Bayesian inference methods to gain insight into the structuring of genetic variation of these populations. Results Our analyses revealed population structure with three genetic groups corresponding to individuals from Oaxaca and those from the central-eastern and western TMVB regions. A significant genetic signal of demographic expansion, an east-to-west expansion predicted by species distribution modelling, and approximate Bayesian computation analyses strongly supported a scenario of habitat isolation and invasion of TMVB by P. calyculatus during the late-Pleistocene. Main conclusions The genetic differentiation of P. calyculatus may be explained by the combined effects of (i) geographical isolation linked to the effects of the glacial/interglacial cycles and environmental factors, driving genetic differentiation from congeners into more xeric vegetation and (ii) the invasion of TMVB from east to west, suggesting a role for both colonization and glacial/interglacial cycles models.
Data from: Phylogeography and population differentiation in the Psittacanthus calyculatus (Loranthaceae) mistletoe: a complex scenario of climate-volcanism interaction along the Trans-Mexican Volcanic Belt
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