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  • 1
    Online Resource
    Online Resource
    Atmospheric circulation influences on seasonal precipitation patterns in Alaska during the latter 20th century : ATMOSPHERIC CIRCULATION AND PRECIPITATION
    American Geophysical Union (AGU) ; 2004
    In:  Journal of Geophysical Research: Atmospheres Vol. 109, No. D6 ( 2004-03-27), p. n/a-n/a
    Details
    In: Journal of Geophysical Research: Atmospheres, American Geophysical Union (AGU), Vol. 109, No. D6 ( 2004-03-27), p. n/a-n/a
    Type of Medium: Online Resource
    ISSN: 0148-0227
    URL: Article
    DOI: 10.1029/2003JD003845
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2004
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  • 2
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    The International Surface Pressure Databank version 2
    Wiley ; 2015
    In:  Geoscience Data Journal Vol. 2, No. 1 ( 2015-07), p. 31-46
    Details
    In: Geoscience Data Journal, Wiley, Vol. 2, No. 1 ( 2015-07), p. 31-46
    Abstract: The International Surface Pressure Databank ( ISPD ) is the world's largest collection of global surface and sea‐level pressure observations. It was developed by extracting observations from established international archives, through international cooperation with data recovery facilitated by the Atmospheric Circulation Reconstructions over the Earth ( ACRE ) initiative, and directly by contributing universities, organizations, and countries. The dataset period is currently 1768–2012 and consists of three data components: observations from land stations, marine observing systems, and tropical cyclone best track pressure reports. Version 2 of the ISPD ( ISPD v2) was created to be observational input for the Twentieth Century Reanalysis Project (20 CR ) and contains the quality control and assimilation feedback metadata from the 20 CR . Since then, it has been used for various general climate and weather studies, and an updated version 3 ( ISPD v3) has been used in the ERA ‐20C reanalysis in connection with the European Reanalysis of Global Climate Observations project ( ERA ‐ CLIM ). The focus of this paper is on the ISPD v2 and the inclusion of the 20 CR feedback metadata. The Research Data Archive at the National Center for Atmospheric Research provides data collection and access for the ISPD v2, and will provide access to future versions.
    Type of Medium: Online Resource
    ISSN: 2049-6060 , 2049-6060
    URL: Article
    DOI: 10.1002/gdj3.25
    Language: English
    Publisher: Wiley
    Publication Date: 2015
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  • 3
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    The Global Historical Climatology Network Monthly Temperature Dataset, Version 4
    American Meteorological Society ; 2018
    In:  Journal of Climate Vol. 31, No. 24 ( 2018-12), p. 9835-9854
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 31, No. 24 ( 2018-12), p. 9835-9854
    Abstract: We describe a fourth version of the Global Historical Climatology Network (GHCN)-monthly (GHCNm) temperature dataset. Version 4 (v4) fulfills the goal of aligning GHCNm temperature values with the GHCN-daily dataset and makes use of data from previous versions of GHCNm as well as data collated under the auspices of the International Surface Temperature Initiative. GHCNm v4 has many thousands of additional stations compared to version 3 (v3) both historically and with short time-delay updates. The greater number of stations as well as the use of records with incomplete data during the base period provides for greater global coverage throughout the record compared to earlier versions. Like v3, the monthly averages are screened for random errors and homogenized to address systematic errors. New to v4, uncertainties are calculated for each station series, and regional uncertainties scale directly from the station uncertainties. Correlated errors in the station series are quantified by running the homogenization algorithm as an ensemble. Additional uncertainties associated with incomplete homogenization and use of anomalies are then incorporated into the station ensemble. Further uncertainties are quantified at the regional level, the most important of which is for incomplete spatial coverage. Overall, homogenization has a smaller impact on the v4 global trend compared to v3, though adjustments lead to much greater consistency than between the unadjusted versions. The adjusted v3 global mean therefore falls within the range of uncertainty for v4 adjusted data. Likewise, annual anomaly uncertainties for the other major independent land surface air temperature datasets overlap with GHCNm v4 uncertainties.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    DOI: 10.1175/JCLI-D-18-0094.1
    RVK:
    UA 4548
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2018
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  • 4
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    An overview of the Global Historical Climatology Network monthly mean temperature data set, version 3
    American Geophysical Union (AGU) ; 2011
    In:  Journal of Geophysical Research Vol. 116, No. D19 ( 2011-10-15)
    Details
    In: Journal of Geophysical Research, American Geophysical Union (AGU), Vol. 116, No. D19 ( 2011-10-15)
    Type of Medium: Online Resource
    ISSN: 0148-0227
    URL: Article
    DOI: 10.1029/2011JD016187
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2011
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  • 5
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    An Overview of the Global Historical Climatology Network-Daily Database
    American Meteorological Society ; 2012
    In:  Journal of Atmospheric and Oceanic Technology Vol. 29, No. 7 ( 2012-07-01), p. 897-910
    Details
    In: Journal of Atmospheric and Oceanic Technology, American Meteorological Society, Vol. 29, No. 7 ( 2012-07-01), p. 897-910
    Abstract: A database is described that has been designed to fulfill the need for daily climate data over global land areas. The dataset, known as Global Historical Climatology Network (GHCN)-Daily, was developed for a wide variety of potential applications, including climate analysis and monitoring studies that require data at a daily time resolution (e.g., assessments of the frequency of heavy rainfall, heat wave duration, etc.). The dataset contains records from over 80 000 stations in 180 countries and territories, and its processing system produces the official archive for U.S. daily data. Variables commonly include maximum and minimum temperature, total daily precipitation, snowfall, and snow depth; however, about two-thirds of the stations report precipitation only. Quality assurance checks are routinely applied to the full dataset, but the data are not homogenized to account for artifacts associated with the various eras in reporting practice at any particular station (i.e., for changes in systematic bias). Daily updates are provided for many of the station records in GHCN-Daily. The dataset is also regularly reconstructed, usually once per week, from its 20+ data source components, ensuring that the dataset is broadly synchronized with its growing list of constituent sources. The daily updates and weekly reprocessed versions of GHCN-Daily are assigned a unique version number, and the most recent dataset version is provided on the GHCN-Daily website for free public access. Each version of the dataset is also archived at the NOAA/National Climatic Data Center in perpetuity for future retrieval.
    Type of Medium: Online Resource
    ISSN: 0739-0572 , 1520-0426
    URL: Article
    DOI: 10.1175/JTECH-D-11-00103.1
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2012
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  • 6
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    Uncertainty Estimates for Sea Surface Temperature and Land Surface Air Temperature in NOAAGlobalTemp Version 5
    American Meteorological Society ; 2020
    In:  Journal of Climate Vol. 33, No. 4 ( 2020-02-15), p. 1351-1379
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 33, No. 4 ( 2020-02-15), p. 1351-1379
    Abstract: This analysis estimates uncertainty in the NOAA global surface temperature (GST) version 5 (NOAAGlobalTemp v5) product, which consists of sea surface temperature (SST) from the Extended Reconstructed SST version 5 (ERSSTv5) and land surface air temperature (LSAT) from the Global Historical Climatology Network monthly version 4 (GHCNm v4). Total uncertainty in SST and LSAT consists of parametric and reconstruction uncertainties. The parametric uncertainty represents the dependence of SST/LSAT reconstructions on selecting 28 (6) internal parameters of SST (LSAT), and is estimated by a 1000-member ensemble from 1854 to 2016. The reconstruction uncertainty represents the residual error of using a limited number of 140 (65) modes for SST (LSAT). Uncertainty is quantified at the global scale as well as the local grid scale. Uncertainties in SST and LSAT at the local grid scale are larger in the earlier period (1880s–1910s) and during the two world wars due to sparse observations, then decrease in the modern period (1950s–2010s) due to increased data coverage. Uncertainties in SST and LSAT at the global scale are much smaller than those at the local grid scale due to error cancellations by averaging. Uncertainties are smaller in SST than in LSAT due to smaller SST variabilities. Comparisons show that GST and its uncertainty in NOAAGlobalTemp v5 are comparable to those in other internationally recognized GST products. The differences between NOAAGlobalTemp v5 and other GST products are within their uncertainties at the 95% confidence level.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    DOI: 10.1175/JCLI-D-19-0395.1
    RVK:
    UA 4548
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2020
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  • 7
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    Comprehensive Automated Quality Assurance of Daily Surface Observations
    American Meteorological Society ; 2010
    In:  Journal of Applied Meteorology and Climatology Vol. 49, No. 8 ( 2010-08-01), p. 1615-1633
    Details
    In: Journal of Applied Meteorology and Climatology, American Meteorological Society, Vol. 49, No. 8 ( 2010-08-01), p. 1615-1633
    Abstract: This paper describes a comprehensive set of fully automated quality assurance (QA) procedures for observations of daily surface temperature, precipitation, snowfall, and snow depth. The QA procedures are being applied operationally to the Global Historical Climatology Network (GHCN)-Daily dataset. Since these data are used for analyzing and monitoring variations in extremes, the QA system is designed to detect as many errors as possible while maintaining a low probability of falsely identifying true meteorological events as erroneous. The system consists of 19 carefully evaluated tests that detect duplicate data, climatological outliers, and various inconsistencies (internal, temporal, and spatial). Manual review of random samples of the values flagged as errors is used to set the threshold for each procedure such that its false-positive rate, or fraction of valid values identified as errors, is minimized. In addition, the tests are arranged in a deliberate sequence in which the performance of the later checks is enhanced by the error detection capabilities of the earlier tests. Based on an assessment of each individual check and a final evaluation for each element, the system identifies 3.6 million (0.24%) of the more than 1.5 billion maximum/minimum temperature, precipitation, snowfall, and snow depth values in GHCN-Daily as errors, has a false-positive rate of 1%−2%, and is effective at detecting both the grossest errors as well as more subtle inconsistencies among elements.
    Type of Medium: Online Resource
    ISSN: 1558-8432 , 1558-8424
    URL: Article
    DOI: 10.1175/2010JAMC2375.1
    RVK:
    UA 4547
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2010
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  • 8
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    AusTraits, a curated plant trait database for the Australian flora
    Springer Science and Business Media LLC ; 2021
    In:  Scientific Data Vol. 8, No. 1 ( 2021-09-30)
    Details
    In: Scientific Data, Springer Science and Business Media LLC, Vol. 8, No. 1 ( 2021-09-30)
    Abstract: We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge.
    Type of Medium: Online Resource
    ISSN: 2052-4463
    URL: Article
    DOI: 10.1038/s41597-021-01006-6
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
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  • 9
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    Spatial heterogeneity of albedo over a snow‐covered agricultural landscape
    American Geophysical Union (AGU) ; 1999
    In:  Journal of Geophysical Research: Atmospheres Vol. 104, No. D16 ( 1999-08-27), p. 19551-19557
    Details
    In: Journal of Geophysical Research: Atmospheres, American Geophysical Union (AGU), Vol. 104, No. D16 ( 1999-08-27), p. 19551-19557
    Abstract: Measurements of albedo were obtained along a 100 km transect in east central Illinois using a combination of airborne and ground‐based radiometers. Analysis of the measurements focused on three different land use categories: agricultural cropland, prairie grass, and woodland. The value of albedo over the woodland after a fresh snowfall was 0.30, which is somewhat higher than what has been measured in a previous experiment over an aspen forest but similar to previous measurements over a deciduous forest in the eastern United States. The albedo values over the grassland were similar to past experiments and similar to the values over cropland. The drifting that accompanied one of the snow events caused large differences in albedo during snowmelt compared to another event with minimal drifting but similar average snow depth. The albedo was lower over the melting wind‐blown snow cover than for a snow cover of similar average depth that fell under light wind conditions. These large differences suggest that inclusion of meteorological conditions during snowfall in snow parameterizations may appreciably increase their accuracy. Different tillage practices used in the agricultural fields also caused measurable differences in albedo during the snowmelt phase.
    Type of Medium: Online Resource
    ISSN: 0148-0227
    URL: Article
    DOI: 10.1029/1999JD900050
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 1999
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    SSG: 16,13
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  • 10
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    Recent increases in U.S. heavy precipitation associated with tropical cyclones : HEAVY PRECIPITATION AND TROPICAL CYCLONES
    American Geophysical Union (AGU) ; 2010
    In:  Geophysical Research Letters Vol. 37, No. 24 ( 2010-12), p. n/a-n/a
    Details
    In: Geophysical Research Letters, American Geophysical Union (AGU), Vol. 37, No. 24 ( 2010-12), p. n/a-n/a
    Type of Medium: Online Resource
    ISSN: 0094-8276
    URL: Article
    DOI: 10.1029/2010GL045164
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2010
    detail.hit.zdb_id: 2021599-X
    detail.hit.zdb_id: 7403-2
    SSG: 16,13
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