North America Climate Extremes Monitoring


  Spatial Mapping: 
 Station Time Series: 
Map of trends of greatest 3-day total rainfall for North America Time Series Graph for Number of frost days Tmin<0°C index for G HOMER WSO AIRPORT station
  
      
       
 

Go to top of page Background

      The Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report (TAR) concluded that most of the observed warming of the last 50 years is likely to have been due to an increase in greenhouse gas concentrations (IPCC, 2001). This report also concluded that other aspects of climate such as precipitation, arctic sea ice extent, sea level, and snow cover were also influenced by changingclimate conditions.

      However, findings with regard to changes in extreme events such as heat waves, drought, and heavy precipitation events were far less conclusive than those for changes in mean conditions. This web site is being established in an effort to improve the scientific understanding of observed changes in extreme climate conditions.

 

Go to top of page Data and Indices

      The analysis of climate extremes on this website is possible through the calculation of a set of extremes indices which was developed by the World Meteorological Organization (WMO) Commission for Climatology/CLIVAR Expert Team on Climate Change Detection Monitoring and Indices (ETCCDMI). The indices, which have also been used in global analyses by Alexander et al. (2005), are based on daily temperature values or daily precipitation amount. Some are based on fixed thresholds that are of relevance to particular applications. In these cases, thresholds are the same for all stations. Other indices are based on thresholds that vary from location to location. In these cases, thresholds are typically defined as a percentile of the relevant data series.

      From a set of 27 core indices defined by the ETCCDMI, a subset of 12 of the most important indices to climate change study is being provided at this time.

      The software for calculating these indices was provided on behalf of the ETCCDMI by Xuebin Zhang of Environment Canada ( http://cccma.seos.uvic.ca/ETCCDMI/index.shtml) and has been used to calculate the indices for a set of stations in the US, Canada and Mexico.

 
Number of Frost Days Annual count of days with daily minimum temperature < 0°C (days).
Number of Summer Days Annual count of days with daily maximum temperature > 25°C (days).
Number of Icing Days Annual count of days with daily maximum temperature < 0°C (days).
Number of Tropical Nights Annual count of days with daily minimum temperature > 20°C (days).
Growing Season Length Annual count of days between first span of at least 6 days with daily mean temperature >5°C and first span after having 6 days with mean temperature <5°C (days);
Much below average minimums Percentage of days when daily minimum temperature was < 10th percentile (%).
Much below average maximums Percentage of days when daily maximum temperature was < 10th percentile (%).
Much above average minimums Percentage of days when daily minimum temperature was > 90th percentile (%).
Much above average maximums Percentage of days when daily maximum temperature was > 90th percentile (%).
Greatest 5-day Total Rainfall Maximum amount of rainfall falling within any consecutive 5-day period (mm).
Simple Precipitation Intensity Index Amount of precipitation that fell on days with any amount of precipitation (mm/day).
Maximum Length of Dry Spell Maximum number of consecutive days without precipitation (days).
 

      The indices were calculated from a variety of data sources. When possible, only data that had been adjusted to remove the effects of non-climatic influences have been used.

Canadian Data

     A set of 210 stations with homogeneity adjusted daily temperature data are provided (Vincent et al. 2002) as well as a set of 493 adjusted precipitation stations for Canada (Mekis and Hogg, 1999). The data have been adjusted through the year 2003. Data in the years following 2003 are unadjusted and are also available in NCDC's GHCN Daily dataset at ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/
     Temperature Station Inventory:      View |  Download
     Precipitation Station Inventory:      View |  Download

US Data

     Adjustments have not been applied to U.S. daily data. Stations used for CONUS were those stations that passed the Menne and Williams (2005) statistical homogeneity tests. Stations for Alaska, Hawaii, Puerto Rico and the US Virgin Islands are a subset of the most homogenous stations for temperaure and precipitation as identified using a 4-phased process that involved 1) visual inspections of various graphs of the station data, 2) examination of the metadata, both digital and scanned in paper archive metadata, 3) the homogeneity test described by Wang (2003), and 4) consultation with State Climatologists for the respective states and regions. From this analysis, a set of approximately 750 stations with the fewest moves and instrument changes were identified.
     Station Inventory:      View |  Download

Mexican Data

     No adjustments or estimates of the most homogenous daily temperature and precipitation records have been applied to Mexican stations, so station selection was based on length of record and reporting frequency. The inventory for Mexico consists of approximately 300 temperature and precipitation stations.
      Station Inventory:      View |  Download

 

Go to top of page Graphing Options

      Trend maps and anomaly maps can be produced for North America as a whole, Canada, Mexico, or the United States. Station trends can be calculated and displayed for subsets of stations based on station elevation, significance level of the resulting trends, and percent of available data. Any set of years and seasons from 1955 to present can be selected for analysis and mapping.

      Each station's trend is displayed as a colored dot with the legend corresponding to appropriate bins. The underlying values for the trend analysis period can be viewed in time series format by clicking on the dot for any station on the map. Using this click and point action enables the user to view a time series graph of the station of interest.Graphing of individual station index values can also be accomplished through the station selection feature which provides access to the full station inventory for each country.

      For any map produced, the corresponding data are available for download in flat ASCII format. The data values are also provided via a scrolling table.


Go to top of page References

Alexander,L. V.X.Zhang, T.C.Peterson, J.Caesar, B.Gleason, A.Klein Tank, M.Haylock, D.Collins, B.Trewin, F.Rahimzadeh, A.Tagipour, P.Ambenje, K.Rupa Kumar, J.Revadekar, G.Griffiths, L.Vincent,D.Stephenson, J.Burn, E.Aguilar, M.Brunet, M.Taylor, M.New, P.Zhai, M.Rusticucci, J.L.Vazquez-Aguirre, 2005: Global observed changes in daily climate extremes of temperature and precepitation. Journal of Geophysical Research - Atmospheres, in press

IPCC, 2001: Climate Change 2001: the Scientific Basis, Contribution of Working Group 1 to the Third Assessment Report of the Intergovernmental Panel on Climate Change. J.T.Houghton, Y.Ding, D.J.Griggs, M.Noguer, P.J.van der Linden, X.Dai, K.Maskell, and C.A.Johnson (Eds.), Cambridge University Press, 881 pp.

Mekis,E. and W.Hogg, 1999: Rehabilitation and Analysis of Canadian Daily Precipitation Time Series. Atmosphere-Ocean, 37, 1, 53-85.

Menne,M.J. and C.N.Williams (2005), Detection of undocumented change points: On the use of multiple test statistics and composite reference series, J.Climate, in press.

Vincent,L.A, X.Zhang, B.R.Bonsal and W.D.Hogg, 2002: Homogenization of daily temperatures over Canada. Journal of Climate, 15, 1322-1344.