- About CDIAC
- Observing Programs
Like politics, you might say that all climate is local. As researchers seek to help the public better understand climate and climate change, a sensible approach would include helping people know more about changes in their own backyards. High and low temperatures are something that all of us pay attention to each day; when they are extreme (flirting with or setting records) they generate tremendous interest, largely because of the potential for significant impacts on human health, the environment, and built infrastructure.
Changes through time in record high and low temperatures (extremes) are also an important manifestation of climate change (Sect. 3.8 in Trenberth et al. 2007; Peterson et al. 2008; Peterson et al. 2012). Meehl et al. (2009) found that currently, about twice as many high temperature records are being set as low temperature records over the conterminous U.S. (lower 48 states) as a whole. As the climate warms further, this ratio is expected to multiply, mainly because when the whole temperature distribution for a location or region shifts, it changes the "tails" of the distribution (in the case of warming this means fewer extreme cold temperatures and more extreme hot temperatures; see Page 2, Figure ES.1 of Karl et al. 2008). The Meehl et al. (2009) findings were covered pretty well by the online media, but, as is the case for all types of scientifc studies, it's safe to say that most of the public are not aware of these basic findings, and they would benefit from additional ways to get climate extremes information for their own areas and assess it. One such way is the National Climatic Data Center's (NCDC) U.S. Records Look-Up page.
But how do most people typically hear about their area's high and low temperature records? Likely via the evening news, when their local on-air meteorologist notes the high/low for the day at a nearby airport then gives the years when the all-time high and low for the date were set (perhaps not at that same airport). The year of the record is an interesting bit of infotrmation on its own but it doesn't do much to place things in context. What about the local history of record temperatures and how things may be changing?
Here we present a daily temperature records data product that we hope will serve the scientist and non-scientist alike in exploring and analyzing high and low temperature records and trends at hundreds of locations across the U.S.
Data and Methods
Analysis of temperature extremes over time requires daily maximum and minimum temperature data from stations with records of sufficient length, quality, completeness, and temporal homogeneity. Homogeneity of the daily temperature record is an especially difficult challenge due to stations experiencing varying degrees of change over time in location, instrumentation, observing practices, and siting conditions.
The DayRec interface uses daily maximum temperature (Tmax) and minimum temperature (Tmin) observations from the National Climatic Data Center's (NCDC) Global Historical Climatology Network (GHCN) - Daily database (Durre et al. 2010; Menne et al. 2012). As the name implies, GHCN contains data from countries around the globe, including thousands of stations in the U.S. A special subset of these stations are the 1218 stations in the U.S. Historical Climatology Network (USHCN) (Menne et al. 2009), which has been used as the main dataset for monitoring U.S. climate since the 1980s. The periods of record for USHCN stations vary somewhat, but most extend from the early 1900s through the current year. Most USHCN stations are located in non-urbanized areas and are operated by unpaid cooperative observers as part of the National Weather Service's Cooperatuve Observer Program (COOP). Compared to city or airport stations (often referred to as "first-order stations"), these COOP stations have experienced fewer significant station moves and are considered more homogeneous over time, although not perfectly so. Still, thanks to rigorous qaulity assurance efforts at NCDC, these daily station records are considered to be the best available for analyzing and monitoring changes in extremes for the U.S. One can obtain station history information (metadata) from NCDC's Historical Observing Metadata Repository (HOMR).
In deciding what stations were suitable for DayRec, the first step was identifying all Tmax and Tmin observations in the 1218 USHCN station records having any of the quality flag assigments described on the quality control page of the GHCN documentation (see also Durre et al. 2010). These flags indicate that the accuracy and reliability of data are questionable, so these observations were set to the missing indicator ("-999") matching the one already used in the database for actual missing observations. Next, an assessment of the amount of missing data at each station was performed. Instead of subjectively assigning an acceptable percentage threshold, it was desired that the allowable volume of missing data not only be quite small, but also that missing observations be spread out relatively evenly over time (both seasonally and over the full period of record), so as to avoid time-dependent bias that could on its own give misleading impressions of changes in the frequency of record-setting temperatures over time at a given station. This was done via 3 steps:
- For each station and each day of the year (1-365; Feb. 29 data from leap years was discarded), determine the number of years having data for each decade over 1911-2010;
- flag any day of the year that had one or more decades with less than Nyears observations (see below); and
- discard any station with more than Ndays (see below) such flagged days over any month for Tmax or Tmin values.
For the initial version of the DayRec interface, released in 2012, Nyears was set to 8, and Ndays was set to 5. These thresholds resulted in 200 stations being retained for use in the interface, with several areas (especially the southwest) being underrepresented. The corresponding average percentage of missing data for these stations was about 1.5%, a very low/stringent value relative to most climatological studies. In November of 2013 the Nyears and Ndays values were both changed to 7, resulting in an additional 224 stations being retained (for a total of 424), with the average percentage of missing data per station only increasing to about 2.4% across all 424 stations. These stringent missing data criteria are necessary to give a relatively reliable picture of changes in record-setting Tmax and Tmin occurrences (realizing that non-climatic factors likely still have important effects, depending on the station). The 200- and 224-station datasets are referred to as Class 1 and Class 2 stations, respectively, in the DayRec interface, and are distinguished from each other using different-colored map markers.
Many USHCN stations do not have century-scale daily records. Obviously this makes them less useful for exploring longer-term changes, but a 2014 version of the DayRec interface will include additional stations so as to allow for examination of record-setting temperatures at most of the 1218 USHCN stations for decades starting with 1951-1960, paralleling the analysis of Meehl et al. (2009).
Data for four types of daily temperature records can be explored:
- Record-high maximum ("Hot Tmax")
- Record-low maximum ("Cool Tmax")
- Record-high minimum ("Warm Tmin")
- Record-low minimum ("Cold Tmin")
These extremes can be thought of as reflecting the hottest/coolest days and the warmest/coldest nights. Examples of the main types of plots that are available are shown below.
Scatter plot for Urbana, Illinois showing the years that record Hot Tmax's were set for each day of the year. Note the large number of summertime records set in the 1930's (including long runs of record-setting temperature), and the relative lack of summertime records in the last several decades.
Decadal frequency of record-setting Tmax's and Tmin's for Fort Collins, Colorado. The plot reflects record temperatures set over all days of the year. Note that over 2001-2010 there were just three record-low Tmin's set, while there were 104 record-high Tmax's set.
Record Hot Tmax and Cool Tmax values for each day of the year at Watertown, New York. At a glance you can determine things like: the hottest/coolest Tmax ever recorded; the three all-time high Tmax's in January exceeded any that have occurred in February ("January Thaws"?) and whether any temperatures appear to be extreme outliers warranting further investigation.
Data behind all plots, along with all daily Tmax and Tmin data for a given station, are readily available through the interface to enable detailed data exploration.
Click on the map below to go to the DayRec Interface.
- Durre, I., M.J. Menne, B.E. Gleason, T.G. Houston, and R.S. Vose, 2010: Comprehensive automated quality assurance of daily surface observations. Journal of Applied Meteorology and Climatology, 49, 1615-1633, doi: 10.1175/2010JAMC2375.1.
- Karl, T.R., G.A. Meehl, T.C. Peterson, K.E. Kunkel, W.J. Gutowski, Jr., D.R. Easterling, 2008: Executive Summary in Weather and Climate Extremes in a Changing Climate. Regions of Focus: North America, Hawaii, Caribbean, and U.S. Pacific Islands. T.R. Karl, G.A. Meehl, C.D. Miller, S.J. Hassol, A.M. Waple, and W.L. Murray (eds.). A Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research, Washington, DC.
- Meehl, G.A., C. Tebaldi, G. Walton, D. Easterling, and L. McDaniel, 2009: Relative increase of record high maximum temperatures compared to record low minimum temperatures in the U.S. Geophysical Research Letters, 36, L23701, doi:10.1029/2009GL040736.
- Menne, Matthew J., Imke Durre, Russell S. Vose, Byron E. Gleason, Tamara G. Houston, 2012: An Overview of the Global Historical Climatology Network-Daily Database. J. Atmos. Oceanic Technol., 29, 897–910. doi:10.1175/JTECH-D-11-00103.1.
- Menne, M. J., C. N. Williams, and R. S. Vose, 2009: The United States Historical Climatology Network Monthly Temperature Data - Version 2. Bull. Amer. Meteor. Soc., 90, 993-1007, doi: 10.1175/2008BAMS2613.1.
- Peterson, T. C., and Coauthors, 2008: Why weather and climate extremes matter. Weather and Climate Extremes in a Changing Climate. Regions of Focus: North America, Hawaii, Caribbean, and U.S. Pacific Islands, T. R. Karl et al., Eds. U.S. Climate Change Science Program and the Subcommittee on Global Change Research, 11–33.
- Peterson, T. C., P. A. Stott and S. Herring, Editors, 2012: Explaining extreme events of 2011 from a climate perspective. Bull. Amer. Meteorol. Soc., 93, 1041–1067, doi:10.1175/BAMS-D-12-00021.1.
- Trenberth, K.E., P.D. Jones, P. Ambenje, R. Bojariu, D. Easterling, A. Klein Tank, D. Parker, F. Rahimzadeh, J.A. Renwick, M. Rusticucci, B. Soden and P. Zhai, 2007: Observations: Surface and Atmospheric Climate Change. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Questions? Please contact D. Kaiser (email@example.com).