# Lake Surprise, California Plesitocene Lake Level Radiocarbon Data #----------------------------------------------------------------------- # World Data Service for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # Template Version 4.0 # Encoding: UTF-8 # NOTE: Please cite original publication, NOAA Landing Page URL, dataset and publication DOIs (where available), and date accessed when using downloaded data. # If there is no publication information, please cite investigator, study title, NOAA Landing Page URL, and date accessed. # # Description/Documentation lines begin with '#' followed by a space # Data lines have no '#' # # NOAA_Landing_Page: https://www.ncei.noaa.gov/access/paleo-search/study/39182 # Landing_Page_Description: NOAA Landing Page of this file's parent study, which includes all study metadata. # # Study_Level_JSON_Metadata: https://www.ncei.noaa.gov/pub/data/metadata/published/paleo/json/noaa-lakelevel-39182.json # Study_Level_JSON_Description: JSON metadata of this data file's parent study, which includes all study metadata. # # Data_Type: Lake Levels # # Dataset_DOI: # # Science_Keywords: #--------------------------------------- # Resource_Links # # Data_Download_Resource: https://www.ncei.noaa.gov/pub/data/paleo/paleolimnology/northamerica/usa/california/ibarra2024/ibarra2014-surprise-c14.txt # Data_Download_Description: NOAA Template File; Surprise Valley Tufa Ages Data # #--------------------------------------- # Contribution_Date # Date: 2024-03-21 #--------------------------------------- # File_Last_Modified_Date # Date: 2024-03-21 #--------------------------------------- # Title # Study_Name: Lake Surprise, California Plesitocene Lake Level Radiocarbon Data #--------------------------------------- # Investigators # Investigators: Ibarra, D.E. (https://orcid.org/0000-0002-9980-4599); Tripati, A. (https://orcid.org/0000-0002-1695-1754); Egger, A. (https://orcid.org/0000-0001-5686-4375) #--------------------------------------- # Description_Notes_and_Keywords # Description: Compilation of radiocarbon ages from latest Pleistocene shoreline tufa from Lake Surprise, California previously published across numerous publications. #--------------------------------------- # Publication # Authors: Ibarra, D.E., Egger, A.E., Weaver, K.L., Harris, C.R., and Maher, K. # Published_Date_or_Year: 2014 # Published_Title: Rise and fall of late Pleistocene pluvial lakes in response to reduced evaporation and precipitation: Evidence from Lake Surprise, California # Journal_Name: GSA Bulletin # Volume: 126 # Edition: # Issue: 11-12 # Pages: 1387-1415 # Report_Number: # DOI: 10.1130/B31014.1 # Online_Resource: # Full_Citation: # Abstract: Widespread late Pleistocene lake systems of the Basin and Range Province indicate substantially greater moisture availability during glacial periods relative to modern times, but the climatic factors that drive changes in lake levels are poorly constrained. To better constrain these climatic factors, we present a new lacustrine paleoclimate record and precipitation estimates for Lake Surprise, a closed basin lake in northeastern California. We combine a detailed analysis of lake hydrography and constitutive relationships describing the water balance to determine the influence of precipitation, evaporation, temperature, and seasonal insolation on past lake levels. At its maximum extent, during the last deglaciation, Lake Surprise covered 1366 km2(36%) of the terminally draining Surprise Valley watershed. Using paired radiocarbon and 230Th-U analyses, we dated shoreline tufa deposits from wave-cut lake terraces in Surprise Valley, California, to determine the hydrography of the most recent lake cycle. This new lake hydrograph places the highest lake level 176 m above the present-day playa at 15.19 ± 0.18 calibrated ka (14C age). This significantly postdates the Last Glacial Maximum (LGM), when Lake Surprise stood at only moderate levels, 65–99 m above modern playa, similar to nearby Lake Lahontan. To evaluate the climatic factors associated with lake-level changes, we use an oxygen isotope mass balance model combined with an analysis of predictions from the Paleoclimate Model Intercomparison Project 3 (PMIP3) climate model ensemble. Our isotope mass balance model predicts minimal precipitation increases of only 2%–18% during the LGM relative to modern, compared to an ~75% increase in precipitation during the 15.19 ka highstand. LGM PMIP3 climate model simulations corroborate these findings, simulating an average precipitation increase of only 6.5% relative to modern, accompanied by a 28% decrease in total evaporation driven by a 7 °C decrease in mean annual temperature. LGM PMIP3 climate model simulations also suggest a seasonal decoupling of runoff and precipitation, with peak runoff shifting to the late spring–early summer from the late winter–early spring. Our coupled analyses suggest that moderate lake levels during the LGM were a result of reduced evaporation driven by reduced summer insolation and temperatures, not by increased precipitation. Reduced evaporation primed Basin and Range lake systems, particularly smaller, isolated basins such as Surprise Valley, to respond rapidly to increased precipitation during late-Heinrich Stadial 1 (HS1). Post-LGM highstands were potentially driven by increased rainfall during HS1 brought by latitudinally extensive and strengthened midlatitude westerly storm tracks, the effects of which are recorded in the region’s lacustrine and glacial records. These results suggest that seasonal insolation and reduced temperatures have been underinvestigated as long-term drivers of moisture availability in the western United States. #--------------------------------------- # Publication # Authors: Ibarra, D.E. # Published_Date_or_Year: 2013 # Published_Title: Applying Uranium-series Isotope Geochemistry and Geochronology to Great Basin Pleistocene Paleohydrology # Journal_Name: Thesis # Volume: # Edition: # Issue: # Pages: # Report_Number: # DOI: # Online_Resource: # Full_Citation: Ibarra, D. E. (2013). Applying Uranium-series Isotope Geochemistry and Geochronology to Great Basin Pleistocene Paleohydrology. M.S. Thesis Stanford University. # Abstract: #--------------------------------------- # Publication # Authors: Egger, A.E., Ibarra, D.E., Weldon, R., Langridge, R.M., Marion, B., and Hall, J. # Published_Date_or_Year: 2021 # Published_Title: Influence of pluvial lake cycles on earthquake recurrence in the northwestern Basin and Range, USA. # Journal_Name: GSA Special paper # Volume: 538 # Edition: # Issue: # Pages: 28 # Report_Number: # DOI: 10.1130/2018.2536(07) # Online_Resource: # Full_Citation: # Abstract: The Basin and Range hosted large pluvial lakes during the Pleistocene, which generally reached highstands following the Last Glacial Maximum and then regressed rapidly to near-modern levels. These lakes were large and deep enough to profoundly affect the crust through flexure; they filled basins formed by faults, and they locally modified pore pressure and groundwater conditions. A compilation of geochronologic constraints on paleoshorelines and paleoseismicity suggests temporal correlations between lake level and earthquake recurrence, with changes in earthquake rates as lakes regressed. In the northwestern Basin and Range, climatic and tectonic conditions differ from the rest of the province: The modern and glacial climate is/was cooler and wetter, glacial lakes were proportionally larger, and the crustal strain rate is lower. Numerous valleys host late Pleistocene and Holocene fault scarps and evidence of >Mw 7 earthquakes in the last 15,000 yr. We compiled detailed lake hydrographs, timing of earthquakes and slip on faults, and other climatic and crustal data from Surprise Valley, Summer Lake, and the Fort Rock basin, along with additional data from other basins in the northwestern Basin and Range. We also present new mapping and topographic analysis of fault scarps that provides relative age constraints on the timing of slip events. Our results confirm temporal correlations, but the limited length of the paleoseismic record prevents definitive causation on the scale of the individual fault or lake basin. Taken together, however, data from all basins suggest that the faults in the northwestern Basin and Range could be acting as a system, with pluvial lake cycles affecting elastic strain accumulation and release across the region. #--------------------------------------- # Publication # Authors: Marion, B.N. # Published_Date_or_Year: 2016 # Published_Title: Spatiotemporal Slip Rate Variations Along Surprise Valley Fault in Relation to Pleistocene Pluvial Lakes # Journal_Name: Thesis # Volume: # Edition: # Issue: # Pages: # Report_Number: # DOI: # Online_Resource: # Full_Citation: Marion, B. N. (2016). Spatiotemporal Slip Rate Variations Along Surprise Valley Fault in Relation to Pleistocene Pluvial Lakes. M.S. Thesis, Central Washington University # Abstract: #--------------------------------------- # Publication # Authors: Santi, L., Ibarra, D.E., Mering, J., Arnold, A., Tripati, A., Whicker, C., and Oviatt, C.G. # Published_Date_or_Year: 2019 # Published_Title: Lake level fluctuations in the Northern Great Basin for the last 25,000 years # Journal_Name: Desert Symposium Field Guide and Proceedings: Exploring Ends of Eras in the eastern Mojave Desert # Volume: # Edition: # Issue: # Pages: 176-186 # Report_Number: # DOI: 10.31223/osf.io/6as7t # Online_Resource: # Full_Citation: # Abstract: During the Last Glacial Maximum (LGM; ~23,000 to 19,000 years ago or ka) and through the last deglaciation, the Great Basin physiographic region in the western United States was marked by multiple extensive lake systems, as recorded by proxy evidence and lake sediments. However, temporal constraints on the growth, desiccation, and timing of lake highstands remain poorly constrained. Studies aimed at disentangling hydroclimate dynamics have offered multiple hypotheses to explain the growth of post-LGM lakes; however, a more robust understanding is currently impeded by a general paucity of spatially and temporally robust data. In this study, we present new data constraining the timing and extent of lake highstands at three post-LGM age pluvial lakes: Lake Newark, Lake Surprise, and Lake Franklin. This data is used in concert with previously published data for these basins and others from the Northern Great Basin including Lakes Bonneville, Chewaucan, and Lahontan to compare the timings of lake growth and decay over a large spatial scale and constrain how regional hydroclimate evolved through the deglaciation. #--------------------------------------- # Publication # Authors: Santi, L.M. # Published_Date_or_Year: 2019 # Published_Title: Stable and Clumped Isotope Analyses of Last Glacial Maximum Pluvial Lakes to Constrain Past Hydroclimate # Journal_Name: Thesis # Volume: # Edition: # Issue: # Pages: # Report_Number: # DOI: # Online_Resource: # Full_Citation: Santi, L. M. (2019).Stable and Clumped Isotope Analyses of Last Glacial Maximum Pluvial Lakes to Constrain Past Hydroclimate. M.S. Thesis, University of California, Los Angeles. # Abstract: #--------------------------------------- # Publication # Authors: Santi, L. M., Arnold, A. J., Ibarra, D. E., Whicker, C. A., Mering, J. A., Lomarda, R. B., Lora, J. M., and Tripati, A. # Published_Date_or_Year: 2020 # Published_Title: Clumped isotope constraints on changes in latest Pleistocene hydroclimate in the northwestern Great Basin: Lake Surprise, California. # Journal_Name: GSA Bulletin # Volume: 132 # Edition: # Issue: 11-12 # Pages: 2669-2683 # Report_Number: # DOI: 10.1130/B35484.1 # Online_Resource: # Full_Citation: # Abstract: During the Last Glacial Maximum (LGM) and subsequent deglaciation, the Great Basin in the southwestern United States was covered by numerous extensive closed-basin lakes, in stark contrast with the predominately arid climate observed today. This transition from lakes in the Late Pleistocene to modern aridity implies large changes in the regional water balance. Whether these changes were driven by increased precipitation rates due to changes in atmospheric dynamics, decreased evaporation rates resulting from temperature depression and summer insolation changes, or some combination of the two remains uncertain. The factors contributing to these large-scale changes in hydroclimate are critical to resolve, given that this region is poised to undergo future anthropogenic-forced climate changes with large uncertainties in model simulations for the 21st century. Furthermore, there are ambiguous constraints on the magnitude and even the sign of changes in key hydroclimate variables between the Last Glacial Maximum and the present day in both proxy reconstructions and climate model analyses of the region. Here we report thermodynamically derived estimates of changes in temperature, precipitation, and evaporation rates, as well as the isotopic composition of lake water, using clumped isotope data from an ancient lake in the northwestern Great Basin, Lake Surprise (California). Compared to modern climate, mean annual air temperature at Lake Surprise was 4.7 °C lower during the Last Glacial Maximum, with decreased evaporation rates and similar precipitation rates to modern. During the mid-deglacial period, the growth of Lake Surprise implied that the lake hydrologic budget briefly departed from steady state. Our reconstructions indicate that this growth took place rapidly, while the subsequent lake regression took place over several thousand years. Using models for precipitation and evaporation constrained from clumped isotope results, we determine that the disappearance of Lake Surprise coincided with a moderate increase in lake temperature, along with increasing evaporation rates outpacing increasing precipitation rates. Concomitant analysis of proxy data and climate model simulations for the Last Glacial Maximum are used to provide a robust means to understand past climate change, and by extension, predict how current hydroclimates may respond to expected future climate forcings. We suggest that an expansion of this analysis to more basins across a larger spatial scale could provide valuable insight into proposed climate forcings, and aid in climate model process depiction. Ultimately, our analysis highlights the importance of temperature-driven evaporation as a mechanism for lake growth and retreat in this region. #--------------------------------------- # Funding_Agency # Funding_Agency_Name: US National Science Foundation # Grant: EAR-0921134, EAR-1352212 #--------------------------------------- # Funding_Agency # Funding_Agency_Name: US National Aeronautic and Space Administration (NASA) # Grant: 10-UAS10-0021 #--------------------------------------- # Funding_Agency # Funding_Agency_Name: US Geological Survey # Grant: G14AS00036 #--------------------------------------- # Funding_Agency # Funding_Agency_Name: US Department of Energy # Grant: DE-FG02-13ER16402 #--------------------------------------- # Site_Information # Site_Name: Surprise Valley, California # Location: California # Northernmost_Latitude: 41.8624 # Southernmost_Latitude: 40.9764 # Easternmost_Longitude: -119.8747 # Westernmost_Longitude: -120.07695 # Elevation_m: 1469 #--------------------------------------- # Data_Collection # Collection_Name: Surprise Valley Tufa Ages Ibarra2024 # First_Year: 20970 # Last_Year: 7810 # Time_Unit: radiocarbon year before present # Core_Length_m: # Parameter_Keywords: lake levels # Notes: #--------------------------------------- # Chronology_Information # Chronology: # # Labcode sample identification used by 14C laboratory # sample_name sample name in publication # sample_group sample group in publications # latitude latitude in degrees north # longitude longtitude in degrees west # elevation elevation in meters # elevation_method method used for determining sample elevation; see publications for details # 14C.raw conventional radiocarbon age, years before 1950AD # 14C.raw_err radiocarbon age, standard error # datemeth Dating method # reservoir Reservoir correction # calib.14C Calibrated age # calib.14C_2sig_lo Calibrated age, 2-sigma lower confidence bound # calib.14C_2sig_up Calibrated age, 2-sigma upper confidence bound # calib_method Calibration method # rejected Rejected sample (yes/no) # notes Notes # publication NaN # # Labcode sample_name sample_group latitude longitude elevation elevation_method 14C.raw 14C.raw_err datemeth reservoir calib.14C calib.14C_2sig_lo calib.14C_2sig_up calib_method rejected notes publication # Beta - 342012 SVDI11-T2-1 Inner Rind Larskpur Hills Shoreline Set 41.5936621092259 120.070257335901 1453.5 LIDAR 15930 70 14C AMS IntCal20 19234 19003 19451 Calib 8.2 NaN NaN Ibarra et al. (2014) # Beta - 342013 SVDI11-T3-2 Larskpur Hills Shoreline Set 41.5932929702103 120.070955632254 1437.689941 LIDAR 17580 70 14C AMS IntCal20 21221 20967 21433 Calib 8.2 NaN NaN Ibarra et al. (2014) # Beta - 340102 SVDI11-T4-1b Larskpur Hills Shoreline Set 41.5929377451539 120.070912297815 1430.550048 LIDAR 17280 60 14C AMS IntCal20 20856 20622 20982 Calib 8.2 NaN NaN Ibarra et al. (2014) # Beta - 342014 SVDI11-T14-1c Larskpur Hills Shoreline Set 41.5911399945616 120.052265999838 1478.430053 LIDAR 10790 50 14C AMS IntCal20 12744 12705 12785 Calib 8.2 NaN NaN Ibarra et al. (2014) # Beta - 340103 SVDI11-T18-1c Larskpur Hills Shoreline Set 41.5962409693747 120.049038967117 1555.650024 LIDAR 13310 40 14C AMS IntCal20 16000 15826 16165 Calib 8.2 NaN NaN Ibarra et al. (2014) # Beta - 342017 SVDI12-T10-b Middle Lake Shoreline Set 41.4268650021404 119.970569014549 1516.829956 LIDAR 12600 50 14C AMS IntCal20 15011 14823 15190 Calib 8.2 NaN NaN Ibarra et al. (2014) # Beta - 340106 SVDI12-T12-1 Middle Lake Shoreline Set 41.4283999800682 119.967793012037 1576.930053 LIDAR 7810 40 14C AMS IntCal20 8582 8453 8650 Calib 8.2 YES rejected based on U systematics Ibarra et al. (2014) # Beta - 340104 SVDI12-T1-a Middle Lake Shoreline Set 41.4299160148948 119.975594971328 1419.47998 LIDAR 17560 60 14C AMS IntCal20 21200 20980 21401 Calib 8.2 NaN NaN Ibarra et al. (2014) # Beta - 342015 SVDI12-T2-b Middle Lake Shoreline Set 41.4299160148948 119.975594971328 1419.47998 LIDAR 18270 70 14C AMS IntCal20 22228 22064 22377 Calib 8.2 NaN NaN Ibarra et al. (2014) # UCI AMS SVDI12-T3A Middle Lake Shoreline Set 41.4298519771546 119.975166991353 1427.800048 LIDAR 18030 280 14C AMS IntCal20 21861 21045 22444 Calib 8.2 NaN NaN Ibarra et al. (2014)/Santi et al., (2019; 2020) # UCI AMS SVDI12-T3B Middle Lake Shoreline Set 41.4298519771546 119.975166991353 1427.800048 LIDAR 16590 290 14C AMS IntCal20 20032 19361 20785 Calib 8.2 NaN NaN Ibarra et al. (2014)/Santi et al., (2019; 2020) # UCI AMS SVDI12-T4A Middle Lake Shoreline Set 41.4298290107399 119.974638009443 1439 LIDAR 18780 270 14C AMS IntCal20 22704 22136 23282 Calib 8.2 NaN NaN Ibarra et al. (2014)/Santi et al., (2019; 2020) # UCI AMS SVDI12-T4B Middle Lake Shoreline Set 41.4298290107399 119.974638009443 1439 LIDAR 18350 270 14C AMS IntCal20 22262 21677 22923 Calib 8.2 NaN NaN Ibarra et al. (2014)/Santi et al., (2019; 2020) # Beta - 342016 SVDI12-T5-b Middle Lake Shoreline Set 41.429868992418 119.974454026669 1444.270019 LIDAR 9470 40 14C AMS IntCal20 10711 10577 10795 Calib 8.2 NaN NaN Ibarra et al. (2014) # UCI AMS SVDI12-T7 Middle Lake Shoreline Set 41.4280419889837 119.972520992159 1472.540039 LIDAR 14460 170 14C AMS IntCal20 17654 17268 18165 Calib 8.2 NaN NaN Ibarra et al. (2014)/Santi et al., (2019; 2020) # Beta - 340105 SVDI12-T9-1 Middle Lake Shoreline Set 41.426983019337 119.970856010913 1508.939941 LIDAR 12420 50 14C AMS IntCal20 14548 14260 14918 Calib 8.2 NaN NaN Ibarra et al. (2014) # Beta - 342018 SVDI12-T13 Lower Lake Shoreline Set 41.2174879945814 119.970070039853 1437.150024 LIDAR 17490 90 14C AMS IntCal20 21122 20893 21388 Calib 8.2 NaN NaN Ibarra et al. (2014) # Beta - 342019 SVDI12-T14 Lower Lake Shoreline Set 41.2190849985927 119.965077023953 1530.71997 LIDAR 12750 50 14C AMS IntCal20 15206 15022 15371 Calib 8.2 NaN NaN Ibarra et al. (2014) # Beta - 342020 SVDI12-T15-b Upper Lake Shoreline Set 41.7179639730602 120.07005399093 1433.089965 LIDAR 16150 70 14C AMS IntCal20 19492 19222 19628 Calib 8.2 NaN NaN Ibarra et al. (2014) # Beta - 342021 SVDI12-T18 Upper Lake Shoreline Set 41.7139349598437 120.062480019405 1564.189941 LIDAR 20970 110 14C AMS IntCal20 25302 25042 25638 Calib 8.2 YES rejected based on U systematics Ibarra et al. (2014) # D-AMS 012850 SV15AE01 Poison Springs Shoreline Set 41.8608 120.07464 1462 5m DEM 15551 62 14C AMS IntCal20 18840 18733 18941 Calib 8.2 NaN NaN Marion (2016)/Egger et al. (2021) # D-AMS 012851 SV15AE02 Poison Springs Shoreline Set 41.8612 120.07488 1470 5m DEM 14858 56 14C AMS IntCal20 18194 18023 18273 Calib 8.2 NaN NaN Marion (2016)/Egger et al. (2021) # D-AMS 012843 SV15AE03 Poison Springs Shoreline Set 41.8616 120.07452 1491 5m DEM 12089 46 14C AMS IntCal20 13934 13808 13960 Calib 8.2 NaN NaN Marion (2016)/Egger et al. (2021) # D-AMS 012844 SV15AE05 Poison Springs Shoreline Set 41.8611 120.07574 1443 5m DEM 17703 59 14C AMS IntCal20 21457 21160 21780 Calib 8.2 NaN NaN Marion (2016)/Egger et al. (2021) # D-AMS 012845 SV15AE06 Poison Springs Shoreline Set 41.8624 120.07695 1437 5m DEM 18201 97 14C AMS IntCal20 22161 21948 22367 Calib 8.2 NaN NaN Marion (2016)/Egger et al. (2021) # D-AMS 012846 SV15BM03 Hays Volcano Shoreline Set 41.319 120.01203 1440.2 LIDAR 14129 60 14C AMS IntCal20 17196 17043 17361 Calib 8.2 NaN NaN Marion (2016)/Egger et al. (2021) # D-AMS 012847 SV15BM04 Hays Volcano Shoreline Set 41.3189 120.00957 1458.5 LIDAR 16199 60 14C AMS IntCal20 19541 19398 19654 Calib 8.2 NaN NaN Marion (2016)/Egger et al. (2021) # D-AMS 012852 SV15AE12 Hays Volcano Shoreline Set 41.3213 119.99765 1545 5m DEM 13290 46 14C AMS IntCal20 15969 15791 16147 Calib 8.2 NaN NaN Marion (2016)/Egger et al. (2021) # D-AMS 012852 SV15BM08 Coppersmith Hills Shoreline Set 41.1445 119.98698 1441 5m DEM 17725 65 14C AMS IntCal20 21527 21202 21817 Calib 8.2 NaN NaN Marion (2016)/Egger et al. (2021) # D-AMS 012849 SV15BM09 Coppersmith Hills Shoreline Set 41.144 119.9865 1456 5m DEM 16427 62 14C AMS IntCal20 19798 19583 20012 Calib 8.2 NaN NaN Marion (2016)/Egger et al. (2021) # UCI AMS SVCW17-PT1 Duck Flat Shoreline Set 40.9771 119.8755 1475 Google Earth Elevation 13520 340 14C AMS IntCal20 16317 15345 17290 Calib 8.2 NaN NaN Santi et al. (2019; 2020) # UCI AMS SVCW17-PT2 Duck Flat Shoreline Set 40.977 119.8755 1475 Google Earth Elevation 13390 160 14C AMS IntCal20 16119 15651 16598 Calib 8.2 NaN NaN Santi et al. (2019; 2020) # UCI AMS SVCW17-PT3 Duck Flat Shoreline Set 40.9764 119.8747 1477 Google Earth Elevation 13890 190 14C AMS IntCal20 16839 16311 17362 Calib 8.2 NaN NaN Santi et al. (2019; 2020) # #--------------------------------------- # Variables # PaST_Thesaurus_Download_Resource: https://www.ncei.noaa.gov/access/paleo-search/skos/past-thesaurus.rdf # PaST_Thesaurus_Download_Description: Paleoenvironmental Standard Terms (PaST) Thesaurus terms, definitions, and relationships in SKOS format. # # Data variables follow that are preceded by "##" in columns one and two. # Variables list, one per line, shortname-tab-var components: what, material, error, units, seasonality, data type, detail, method, C or N for Character or Numeric data) # #------------------------ # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing_Values: NA # NOTE: All Data is in the Chronology table above.