# Global Holocene Paleodust Database #----------------------------------------------------------------------- # World Data Service for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program # National Centers for Environmental Information (NCEI) #----------------------------------------------------------------------- # Template Version 2.0 # NOTE: Please cite Publication, and Online_Resource and date accessed when using these data. # If there is no publication information, please cite Investigators, Title, and Online_Resource and date accessed. # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/20529 # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/loess/albani2015/albani2015-pc72-mar.txt # # Original_Source_URL: # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Loess # # Parameter_Keywords: #-------------------- # Contribution_Date # Date: 2016-09-16 #-------------------- # Title # Study_Name: Global Holocene Paleodust Database #-------------------- # Investigators # Investigators: Albani, S.; Mahowald, N.M.; Winckler, G.; Anderson, R.F.; Bradtmiller, L.I.; Delmonte, B.; François, R.; Goman, M.; Heavens, N.G.; Hesse, P.P; Hovan, S.A.; Kang, S.G.; Kohfeld, K.E.; Lu, H.; Maggi, V.; Mason, J.A.; Mayewski, P.A.; McGee, D.; Miao, X.; Otto-Bliesner, B.L.; Perry, A.T.; Pourmand, A.; Roberts, H.M.; Rosenbloom, N.; Stevens, T.; Sun, J. #-------------------- # Description_and_Notes # Description: Mineral dust data (dust mass accumulation rates and particle grain size distributions) derived from a global set of 45 # ice core, marine sediment, loess-paleosol, lake sediment, and peat bog records. # Provided Keywords: Dust Mass Accumulation Rate (DMAR), grain size #-------------------- # Publication # Authors: S. Albani, N.M. Mahowald, G. Winckler, R.F. Anderson, L.I. Bradtmiller, B. Delmonte, R. François, M. Goman, N.G. Heavens, P.P. Hesse, S.A. Hovan, S.G. Kang, K.E. Kohfeld, H. Lu, V. Maggi, J.A. Mason, P.A. Mayewski, D. McGee, X. Miao, B.L. Otto-Bliesner, A.T. Perry, A. Pourmand, H.M. Roberts, N. Rosenbloom, T. Stevens, and J. Sun # Published_Date_or_Year: 2015-06-11 # Published_Title: Twelve thousand years of dust: the Holocene global dust cycle constrained by natural archives # Journal_Name: Climate of the Past # Volume: 11 # Edition: # Issue: 6 # Pages: 869-903 # Report_Number: # DOI: 10.5194/cp-11-869-2015 # Online_Resource: http://www.clim-past.net/11/869/2015/cp-11-869-2015.html # Full_Citation: # Abstract: Mineral dust plays an important role in the climate system by interacting with radiation, clouds, and biogeochemical cycles. In addition, natural archives show that the dust cycle experienced variability in the past in response to global and local climate change. The compilation of the DIRTMAP (Dust Indicators and Records from Terrestrial and MArine Palaeoenvironments) paleodust data sets in the last 2 decades provided a benchmark for paleoclimate models that include the dust cycle, following a time slice approach. We propose an innovative framework to organize a paleodust data set that builds on the positive experience of DIRTMAP and takes into account new scientific challenges by providing a concise and accessible data set of temporally resolved records of dust mass accumulation rates and particle grain size distributions. We consider data from ice cores, marine sediments, loess-paleosol sequences, lake sediments, and peat bogs for this compilation, with a temporal focus on the Holocene period. This global compilation allows the investigation of the potential, uncertainties, and confidence level of dust mass accumulation rate reconstructions and highlights the importance of dust particle size information for accurate and quantitative reconstructions of the dust cycle. After applying criteria that help to establish that the data considered represent changes in dust deposition, 45 paleodust records have been identified, with the highest density of dust deposition data occurring in the North Atlantic region. Although the temporal evolution of dust in the North Atlantic appears consistent across several cores and suggests that minimum dust fluxes are likely observed during the early to mid-Holocene period (6000-8000 years ago), the magnitude of dust fluxes in these observations is not fully consistent, suggesting that more work needs to be done to synthesize data sets for the Holocene. Based on the data compilation, we used the Community Earth System Model to estimate the mass balance of and variability in the global dust cycle during the Holocene, with dust loads ranging from 17.2 to 20.8 Tg between 2000 and 10 000 years ago and with a minimum in the early to mid-Holocene (6000-8000 years ago). #------------------ # Funding_Agency # Funding_Agency_Name: US National Science Foundation # Grant: 0932946, 1003509, AGS-1003505 #------------------ # Funding_Agency # Funding_Agency_Name: US Department of Energy # Grant: SC00006735 #------------------ # Funding_Agency # Funding_Agency_Name: Dote ricercatori # Grant: FSE, Regione Lombardia #------------------ # Site_Information # Site_Name: TT013-PC72 # Location: Ocean>Pacific Ocean>North Pacific Ocean # Country: # Northernmost_Latitude: 0.0 # Southernmost_Latitude: 0.0 # Easternmost_Longitude: -140.0 # Westernmost_Longitude: -140.0 # Elevation: m #------------------ # Data_Collection # Collection_Name: Albani2015-PC72-MAR # Earliest_Year: 11465 # Most_Recent_Year: 5000 # Time_Unit: Cal. Year BP # Core_Length: m # Notes: #------------------ # Chronology_Information # Chronology: # #---------------- # Variables # # Data variables follow are preceded by "##" in columns one and two. # Data line variables format: Variables list, one per line, shortname-tab-longname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) # ## age_calkaBP age, , , calendar Kyears before present, , , , ,N ## dustMAR dust mass accumulation rate, , , g/m2/a, , , , ,N ## age_err age error, , , calendar Kyears, , , , ,N ## dustMARerr dust mass accumulation rate error, , , g/m2/a, , , , ,N ## depth_top depth top, , , cm, , , , ,N ## depth_bot depth bottom, , , cm, , , , ,N ## depth_cm depth center, , , cm, , , , ,N ## age_top age top, , , calendar Kyears before present, , , , ,N ## age_bot age bottom, , , calendar Kyears before present, , , , ,N ## age_calkaBP age center, , , calendar Kyears before present, , , , ,N ## SBMAR Sediment bulk mass accumulation rate, , , g/m2/a, , , , ,N ## SBMARerr Sediment bulk mass accumulation rate relative error, , , g/m2/a, , , , ,N ## SDBD Sediment dry bulk density, , , g/cm3, , , , ,N ## SDBDerr Sediment dry bulk density relative error, , , g/cm3, , , , ,N ## SR Sedimentation Rate, , , cm/ka, , , , ,N ## SRerr Sedimentation Rate relative error, , , cm/ka, , , , ,N ## EC Eolian Content, , , , , , fraction, ,N ## ECppm Eolian Content, , , ppm, , , fraction, ,N ## ECerr Eolian Content relative error, , , cm/ka, , , , ,N # #---------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: NA # age_calkaBP dustMAR age_err dustMARerr depth_top depth_bot depth_cm age_top age_bot age_calkaBP SBMAR SBMARerr SDBD SDBDerr SR SRerr EC ECppm ECerr 5 0.2271 0.34 0.031 5 6 5.5 NA NA 5 6.779 0.014 NA NA NA NA NA 0.034 0.14 5.569 0.1653 0.379 0.0193 7 8 7.5 NA NA 5.569 6.647 0.007 NA NA NA NA NA 0.025 0.12 5.66 0.213 0.385 0.0305 10 11 10.5 NA NA 5.6596 7.359 0.014 NA NA NA NA NA 0.029 0.14 5.72 0.1691 0.389 0.0223 12 13 12.5 NA NA 5.72 6.884 0.007 NA NA NA NA NA 0.025 0.13 5.811 0.191 0.395 0.0293 15 16 15.5 NA NA 5.8106 8.526 0.012 NA NA NA NA NA 0.022 0.15 7.368 0.1951 0.501 0.023 18.5 19.5 19 NA NA 7.368 9.201 0.007 NA NA NA NA NA 0.021 0.12 8.314 0.1955 0.565 0.0304 20 21 20.5 NA NA 8.313529412 9.673 0.017 NA NA NA NA NA 0.02 0.15 9.574 0.1943 0.651 0.0253 22 23 22.5 NA NA 9.574235294 9.592 0.007 NA NA NA NA NA 0.02 0.13 10.52 0.1706 0.715 0.0163 23.5 24.5 24 NA NA 10.51976471 10.001 0.011 NA NA NA NA NA 0.017 0.09 11.465 0.2738 0.78 0.0375 25 26 25.5 NA NA 11.46529412 10.129 0.014 NA NA NA NA NA 0.027 0.14