Item talk:Q253519
From geokb
{
"USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "Article", "additionalType": "Journal Article", "name": "Holocene paleoclimate change in the western US: The importance of chronology in discerning patterns and drivers", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70215537", "url": "https://pubs.usgs.gov/publication/70215537" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70215537 }, { "@type": "PropertyValue", "propertyID": "DOI", "value": "10.1016/j.quascirev.2020.106487", "url": "https://doi.org/10.1016/j.quascirev.2020.106487" } ], "journal": { "@type": "Periodical", "name": "Quaternary Science Reviews", "volumeNumber": "246", "issueNumber": null }, "inLanguage": "en", "isPartOf": [ { "@type": "CreativeWorkSeries", "name": "Quaternary Science Reviews" } ], "datePublished": "2020", "dateModified": "2020-10-22", "abstract": "Sediment in lakes and meadows forms a powerful archive that can be used to reconstruct environmental change through time. Reconstructions of lake level, of chemical, biological, and hydrological conditions, and of surrounding vegetation provide detailed information about past climate conditions, both locally and regionally. Indeed, most of our current knowledge of centennial- to millennial-scale climate variability in the arid western United States, where information about past hydroclimate is particularly important, comes from such sediment-based reconstructions. The pressing need for robust, precise predictions of future conditions is a significant motivation for paleoclimate science, and current research questions frequently require Holocene reconstructions to be resolved at sub-centennial timescales. Increasingly, regional syntheses seek to identify synoptic-scale patterns similar to those defined from modern observations (seasonal, interannual, multi-decadal, etc.) or to compare with the output of climate model simulations. However, the age control on existing records, especially those more than about 20 years old, is often sufficient only for millennial-scale interpretation. Here we assess the age control for 84 published and unpublished records from lakes and meadows in the Great Basin, California, and desert southwest, and use Bayesian modeling to evaluate the 95% uncertainty ranges for the 42 best-dated records. In the Late Holocene, about half of the 42 records have <400-year mean uncertainty ranges; however, high-precision age control is especially critical for young records, used to develop an accurate understanding of a proxy\u2019s response to known climate variations. In the Middle Holocene, records vary from 400 to >800-year mean uncertainty and records of the Early Holocene have 600- to >1400-year mean uncertainty ranges. We find that the largest control on modeled uncertainties is dating density, with at least 2 dates/kyr being optimal and suggest obtaining \u201crange-finder\u201d dates at the onset of a study to better predict the total number of dates needed for an adequate age model. Such a density avoids a commonly observed phenomenon of significant peaks in uncertainty arising in gaps between age control points. Analysis of the uncertainties associated with proxy shifts reveal that more than half are >400 years. Although such large uncertainties currently prevent sub-centennial interpretations in most cases, increased dating density, strategic use of limited funds (including budgeting for a 2 date/kyr minimum at the proposal stage), construction of age-depth models with Bayesian methods, and critical evaluation of chronological uncertainty will shed light on past climate variability at finer timescales, enhancing our understanding of global and regional drivers of western U.S. climate.", "description": "106487, 26 p.", "publisher": { "@type": "Organization", "name": "Elsevier" }, "author": [ { "@type": "Person", "name": "Zimmerman, Susan", "givenName": "Susan", "familyName": "Zimmerman", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0002-1320-1878", "url": "https://orcid.org/0000-0002-1320-1878" }, "affiliation": [ { "@type": "Organization", "name": "CAMS, LLNL" } ] }, { "@type": "Person", "name": "Wahl, David", "givenName": "David", "familyName": "Wahl", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0002-0451-3554", "url": "https://orcid.org/0000-0002-0451-3554" }, "affiliation": [ { "@type": "Organization", "name": "Geology, Minerals, Energy, and Geophysics Science Center", "url": "https://www.usgs.gov/centers/gmeg" } ] } ], "funder": [ { "@type": "Organization", "name": "Geology, Minerals, Energy, and Geophysics Science Center", "url": "https://www.usgs.gov/centers/gmeg" } ], "spatialCoverage": [ { "@type": "Place", "additionalType": "country", "name": "United States", "url": "https://geonames.org/4074035" }, { "@type": "Place", "additionalType": "state", "name": "California" }, { "@type": "Place", "additionalType": "state", "name": "Idaho" }, { "@type": "Place", "additionalType": "state", "name": "Nevada" }, { "@type": "Place", "additionalType": "state", "name": "Oregon" }, { "@type": "Place", "additionalType": "state", "name": "Utah" }, { "@type": "Place", "geo": [ { "@type": "GeoShape", 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"uncertainty": [ 189, 209, 246, 258, 316, 382 ], "ranges": [ 190 ], "42": [ 193, 204 ], "best-dated": [ 194 ], "records.": [ 195 ], "In": [ 196, 235 ], "Late": [ 198 ], "Holocene,": [ 199, 238 ], "half": [ 201, 336 ], "have": [ 206, 253 ], "<400-year": [ 207 ], "mean": [ 208, 245, 257 ], "ranges;": [ 210 ], "however,": [ 211 ], "high-precision": [ 212 ], "critical": [ 217, 378 ], "young": [ 219 ], "develop": [ 223 ], "an": [ 224, 300 ], "accurate": [ 225 ], "understanding": [ 226, 395 ], "proxy\u2019s": [ 229 ], "response": [ 230 ], "known": [ 232 ], "variations.": [ 234 ], "Middle": [ 237 ], "vary": [ 240 ], "400": [ 242 ], ">800-year": [ 244 ], "Early": [ 251 ], "600-": [ 254 ], ">1400-year": [ 256 ], "ranges.": [ 259 ], "We": [ 260 ], "find": [ 261 ], "largest": [ 264 ], "modeled": [ 267 ], "uncertainties": [ 268, 327, 343 ], "dating": [ 270, 352 ], "density,": [ 271, 353 ], "least": [ 274 ], "2": [ 275, 363 ], "dates/kyr": [ 276 ], "being": [ 277 ], "optimal": [ 278 ], "suggest": [ 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