Image Metadata File

Person Submitting Metadata/Point of Contact:

Name: Laura Stevens
Physical Address: 151 Patton Ave Asheville, NC 28801
Organization: CICSNC
Email:
Phone:

Image Info:

Image Title:
Time series of an index for the occurrence of heat waves and cold waves
Image Description:
Time series of an index for the occurrence of heat waves (top) and cold waves (bottom), defined as 4-day periods that are hotter and colder, respectively, than the threshold for a 1 in 5-year recurrence, for the Great Plains region. The dashed line is a linear fit. Based on daily COOP data from long-term stations in the National Climatic Data Center’s Global Historical Climate Network data set. Only stations with less than 10% missing daily temperature data for the period 1895-2011 are used in this analysis. Events are first identified for each individual station by ranking all 4-day period mean temperature values and choosing the highest (heat waves) and lowest (cold waves) non-overlapping N/5 events, where N is the number of years of data for that particular station. Then, event numbers for each year are averaged for all stations in each 1x1° grid box. Finally, a regional average is determined by averaging the values for the individual grid boxes. This regional average is the index. The most intense heat waves occurred in the 1930s, although there is no overall trend. There is also no statistically significant trend in cold wave events, however, the number of intense cold wave events has been very low during the last 15 years.
Attributes (variables name, description and units):
Relative number of heat spells (/ year), Relative number of cold spells ( / year)
Temporal domain:
Start Time: 1895-01-01 00:00:00.0
End Time: 2011-12-31 00:00:00.0
Spatial domain:
Max latitude: 48.9375
Min latitude: 25.9375
Max longitude: -93.5625
Min longitude: -116.063
Keywords:
Great Plains, Observed, USGHCN Daily, Temperature
Usage Limitations/Constraints:
Citation of image source:

Image Creation:

Who created the image:
Name: Laura Stevens
Physical Address: 151 Patton Ave Asheville, NC 28801
Organization: CICSNC
Email:
Phone:
When was image created (YYYY-MM-DD): 2012-08-15 00:00:00.0

Data Sources:

Dataset #1
Dataset Name: USGHCN Daily
Dataset Version:
Dataset Description: Global Historical Climatology Network - Daily
Dataset ID:
Dataset Release/Publication Date:
Affiliated Organization Name and Role: NOAA NCDC/Russ Vose
Date Accessed: 2011-06-06 00:00:00.0
Dataset Location (ftp, URL, etc): ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/
Data qualifier (QA/QC, etc):
The denominator of the scale of the source/output:
Spatial Reference system used by the source/output:
Citation to metadata:
Description of the scope of a resource, quality report, or process:
Spatial Extent of the source/output (polygon, box or region name): National
Temporal extent of the source/output: 1895-01-01 to 2011-12-31
Vertical extent of the source/output:
Identifier of the processing level of the source/input:
Spatial resolution of the source/output: 1 km

Processes:

Process #1
Input(s):
Step(s):
  • The data set is GHCN-Daily. Stations were selected by examining each station in the entire data base with a USCxxxxxxxx identifier. Only stations with less than 10% missing daily temperature data for the period 1895-2011 are used in this analysis. Days when the temperature data had a quality flag were considered missing. Daily mean temperature is the average of the maximum temperature and minimum temperature. Events are first identified for each individual station by ranking all 4-day period mean temperature values and choosing the highest (heat waves) and lowest (cold waves) non-overlapping N/5 events, where N is the number of years of data for that particular station. We require that a minimum two-day period separate all events. Thus, for example, if the highest 4-day period is July 14-17, 2011, the periods of July 12-13 and July 18-19, 2011 are excluded from being a part of lower-ranked events. A year was not included in this analysis if there were less than 300 non-missing temperature values in that year. After determining events for each station, event numbers for each year are averaged for all stations in each 1x1° grid box. Finally, a regional average is determined by averaging the values for the individual grid boxes. This regional average is the index.
Output(s):
Software:
Environment(s):
Additional Comments:

References: