Byron E. Gleason

Global observed changes in daily climate extremes of temperature and precipitation

A suite of climate change indices derived from daily temperature and precipitation data, with a primary focus on extreme events, were computed and analyzed. By setting an exact formula for each index and using specially designed software, analyses done in different countries have been combined seamlessly. This has enabled the presentation of the most up-to-date and comprehensive global picture of trends in extreme temperature and precipitation indices using results from a number of workshops held in data-sparse regions and high-quality station data supplied by numerous scientists world wide. Seasonal and annual indices for the period 1951-2003 were gridded. Trends in the gridded fields were computed and tested for statistical significance. Results showed widespread significant changes in temperature extremes associated with warming, especially for those indices derived from daily minimum temperature. Over 70% of the global land area sampled showed a significant decrease in the annual occurrence of cold nights and a significant increase in the annual occurrence of warm nights. Some regions experienced a more than doubling of these indices. This implies a positive shift in the distribution of daily minimum temperature throughout the globe. Daily maximum temperature indices showed similar changes but with smaller magnitudes. Precipitation changes showed a widespread and significant increase, but the changes are much less spatially coherent compared with temperature change. Probability distributions of indices derived from approximately 200 temperature and 600 precipitation stations, with near-complete data for 1901-2003 and covering a very large region of the Northern Hemisphere midlatitudes (and parts of Australia for precipitation) were analyzed for the periods 1901-1950, 1951-1978 and 1979-2003. Results indicate a significant warming throughout the 20th century. Differences in temperature indices distributions are particularly pronounced between the most recent two periods and for those indices related to minimum temperature. An analysis of those indices for which seasonal time series are available shows that these changes occur for all seasons although they are generally least pronounced for September to November. Precipitation indices show a tendency toward wetter conditions throughout the 20th century.

An Overview of the Global Historical Climatology Network-Daily Database

AbstractA 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...

Comprehensive Automated Quality Assurance of Daily Surface Observations

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 falsepositive 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%22%, and is effective at detecting both the grossest errors as well as more subtle inconsistencies among elements.

Meteorological Causes of the Secular Variations in Observed Extreme Precipitation Events for the Conterminous United States

AbstractDaily extreme precipitation events, exceeding a threshold for a 1-in-5-yr occurrence, were identified from a network of 935 Cooperative Observer stations for the period of 1908–2009. Each event was assigned a meteorological cause, categorized as extratropical cyclone near a front (FRT), extratropical cyclone near center of low (ETC), tropical cyclone (TC), mesoscale convective system (MCS), air mass (isolated) convection (AMC), North American monsoon (NAM), and upslope flow (USF). The percentage of events ascribed to each cause were 54% for FRT, 24% for ETC, 13% for TC, 5% for MCS, 3% for NAM, 1% for AMC, and 0.1% for USF. On a national scale, there are upward trends in events associated with fronts and tropical cyclones, but no trends for other meteorological causes. On a regional scale, statistically significant upward trends in the frontal category are found in five of the nine regions. For ETCs, there are statistically significant upward trends in the Northeast and east north central. For the ...

NOAA's Merged Land–Ocean Surface Temperature Analysis

This paper describes the new release of the Merged Land–Ocean Surface Temperature analysis (MLOST version 3.5), which is used in operational monitoring and climate assessment activities by the NOAA National Climatic Data Center. The primary motivation for the latest version is the inclusion of a new land dataset that has several major improvements, including a more elaborate approach for addressing changes in station location, instrumentation, and siting conditions. The new version is broadly consistent with previous global analyses, exhibiting a trend of 0.076°C decade−1 since 1901, 0.162°C decade−1 since 1979, and widespread warming in both time periods. In general, the new release exhibits only modest differences with its predecessor, the most obvious being very slightly more warming at the global scale (0.004°C decade−1 since 1901) and slightly different trend patterns over the terrestrial surface.

U.S. temperature and drought: Recent anomalies and trends

The spring and summer (March through August) of 2011–2012 set many new climatological records across the contiguous United States, including the hottest month in the instrumental record: July 2012. Various measures of temperature extremes and drought severity serve to put this period into historical perspective (1895 to present) and to assess to what extent the recent anomalies are consistent with observed trends. During spring and summer, anomalously high temperatures can combine with unusually dry conditions to amplify temperature and drought feedbacks. Observational data from 2011 and 2012 are strongly suggestive of such an amplification and reveal a number of significant trends for various measures of high temperatures in the United States.

Spatial heterogeneity of albedo over a snow‐covered agricultural landscape

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.

NOAA CIRES Twentieth Century Global Reanalysis Version 2

The Twentieth Century Reanalysis Project, supported by the Earth System Research Laboratory Physical Sciences Division from NOAA and the University of Colorado CIRES Climate Diagnostics Center, is an effort to produce a global reanalysis dataset spanning a portion of the nineteenth century and the entire twentieth century (1871 - near present), assimilating only surface observations of synoptic pressure, monthly sea surface temperature and sea ice distribution. Products include 6-hourly ensemble mean and spread analysis fields on a 2 by 2 degree global latitude-longitude grid, and 3 and 6-hourly ensemble mean and spread forecast (first guess) fields on a global Gaussian T62 grid. Fields are accessible in yearly time series (1 file per parameter) and monthly synoptic time (all parameters per synoptic hour) files. Ensemble grids, spectral coefficients, and other information will available by offline request in the future.\n\n The Twentieth Century Reanalysis Project used resources of the National Energy Research Scientific Computing Center managed by Lawrence Berkeley National Laboratory and of the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, which are supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 and Contract No. DE-AC05-00OR22725, respectively.\n\nNote: Version 2c of this reanalysis (running from 1851 - 2011) is the recommended research version. Please see ds131.2 to access Version 2c.

International Surface Pressure Databank (ISPDv2)

The International Surface Pressure Databank (ISPD; Cram et al. 2015) [http://reanalyses.org/observations/international-surface-pressure-databank] is the worlds largest collection of pressure observations. It has been gathered through international cooperation with data recovery facilitated by the ACRE Initiative and the other contributing organizations and assembled under the auspices of the GCOS Working Group on Surface Pressure and the WCRP/GCOS Working Group on Observational Data Sets for Reanalysis by NOAA Earth System Research Laboratory (ESRL), NOAAs National Climatic Data Center (NCDC), and the Climate Diagnostics Center (CDC) of the University of Colorados Cooperative Institute for Research in Environmental Sciences (CIRES). The ISPDv2 consists of three components: station, marine, and tropical cyclone best track pressure observations. The station component is a blend of many national and international collections.\n\nNOTE: A newer version of this dataset, the International Surface Pressure Databank version 3, is available in RDA dataset ds132.1 [http://rda.ucar.edu/datasets/ds132.1/]. Users are recommended to access this updated dataset.\n\nThe Twentieth Century Reanalysis Project used resources of the National Energy Research Scientific Computing Center [http://www.nersc.gov/] and of the Oak Ridge Leadership Computing Facility [http://www.olcf.ornl.gov/] at Oak Ridge National Laboratory, which are supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 and Contract No. DE-AC05-00OR22725, respectively.

The Global Historical Climatology Network Monthly Temperature Dataset, Version 4

AbstractWe 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 w...