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Daymet: Annual Tile Summary Cross-Validation Statistics for North America, Version 3

Documentation Revision Date: 2017-04-24

Data Set Version: V3

Summary

This data set provides annual summary cross-validation statistics for minimum temperature (tmin), maximum temperature (tmax), and daily total precipitation (prcp) of "Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 3" (Thornton et al., 2016). The cross-validation statistics were generated by the Daymet model algorithm from the station-based daily observations and predictions and are summarized for each of the 2-degree by 2-degree tiles in the regimen in which Daymet is derived. Data are available for the temporal period 1980 through 2016, the most recently processed calendar year of Daymet Version 3. Summarized by tile are average and period-of-record mean absolute error (MAE) and bias statistics for the input weather observations of tmin, tmax, and prcp. Also available are tile-wide values of number of ground weather stations evaluated, total station-days evaluated, and mean observed input parameter values. Summary statistics are also available for the Gaussian distribution functions, used in the Daymet interpolation method, as mean and standard deviations of the radius of the kernel weights and x, y, and z components of the 3-dimensional regression formula.

There are a total of 114 files in this data set.  There are 111 shape files and 3 csv files.  The data are distributed as shape files that represent the 2-degree by 2-degree tile structure in which the Daymet model estimates are derived.  The annual cross-validation statistics are provided as a separate shape file for the North American domain for each of the three variables for each year of available Daymet input data (i.e., 3 files/year for 37years).

Also provided are the complete time series of annual summary cross-validation statistics for the three Daymet input parameters in comma separated files (*.csv).  There is one file for each of the three parameters for each tile.

Figure 1: Daymet V3 cross-validation tile-wide summary statistics for 2010 maximum temperature - "daymae" - mean absolute error for single day predictions.

Citation

Thornton, P.E., M.M. Thornton, and R.S. Vose. 2017. Daymet: Annual Tile Summary Cross-Validation Statistics for North America, Version 3. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1348

Table of Contents

  1. Data Set Overview
  2. Data Characteristics
  3. Application and Derivation
  4. Quality Assessment
  5. Data Acquisition, Materials, and Methods
  6. Data Access
  7. References
  8. Data Set Revisions

Data Set Overview

Project:  Daymet

This data set provides annual summary cross-validation statistics for minimum temperature (tmin), maximum temperature (tmax), and daily total precipitation (prcp) of "Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 3" (Thornton et al., 2016). The cross-validation statistics were generated by the Daymet model algorithm from the station-based daily observations and predictions and are summarized for each of the 2-degree by 2-degree tiles in the regimen in which Daymet is derived. Data are available for the temporal period 1980 through 2016, the most recently processed calendar year of Daymet Version 3.

Summarized by tile are average and period-of-record mean absolute error (MAE) and bias statistics for the input weather observations of tmin, tmax, and prcp.  Also available are tile-wide values of number of ground weather stations evaluated, total station-days evaluated, and mean observed input parameter values. Summary statistics are also available for the Gaussian distribution functions, used in the Daymet interpolation method, as mean and standard deviations of the radius of the kernel weights and x, y, and z components of the 3-dimensional regression formula.

Related Data Sets:

Thornton, P.E., M.M. Thornton, B.W. Mayer, Y. Wei, R. Devarakonda, R.S. Vose, and R.B. Cook. 2016. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 3. ORNL DAAC, Oak Ridge, Tennessee, USA. http://dx.doi.org/10.3334/ORNLDAAC/1328

 

 

Data Characteristics

The annual cross-validation statistics are provided for North America as a separate shape file for each of the three variables for each year of available Daymet input data (i.e., 3 files/year for 37 years).

Also the complete time series of annual cross-validation statistics for a variable is provided in a single comma separated file (*.csv).  There is one file for each of the three variables.

Spatial Coverage:   North America and Hawaii: including Canada, Mexico, the United States of America, Puerto Rico, and Bermuda.

Spatial Resolution:  2-degree x 2-degree

Temporal Coverage:  1980-01-01 to 2016-12-31

Temporal Resolution:  Annual

Site boundaries: (All latitudes and longitudes given in decimal degrees)

Site Westernmost Longitude Easternmost Longitude Northernmost Latitude Southernmost Latitude Geodetic Datum

North America, Puerto Rico, and Hawaii

-180 -52 84 14 WGS_1984

 

Data File Information

Shape Files

There are 111 shape files associated with this data set.  Daymet cross-validation data are available as shape files covering North America (Canada, United States, Mexico, Puerto Rico) and Hawaii – with a spatial resolution of 2 degrees. 

The shape files geometric polygon structure represents the 2 degree x 2 degree tile “grid” in which the Daymet model is processed and output.  Note that this vector file is an approximation of the Daymet 2-degree raster tile grid.

Three shape files with cross-validation statistical information for each of the three Daymet daily weather input variables minimum temperature (tmin), maximum temperature (tmax), and total precipitation (prcp) are available each year of available Daymet data.

The North American shape files are zipped for convenience and contain four files (*.dbf,*.prj,*.shp, and *.shx).

File names follow this syntax:   DaymetV3_xval_pppp_yyyy.shp  (*.zip)

Where:

xval distinguishes these as Daymet tile summary cross-validation data files;

pppp is the respective Daymet input meteorological variable (tmin, tmax, and prcp); and

yyyy is year. 

 

Data Dictionary:

Fields within each shape file contain the tile-wide summary cross-validation statistics. 

Shape files for temperature (tmin and tmax) Cross-Validation Statistics have these attributes.

Field

Units/format

Description

Xmin

decimal degrees

Approximate minimum longitude of tile

Xmax

decimal degrees

Approximate maximum longitude of tile

Ymin

decimal degrees

Approximate minimum latitude of tile

Ymax

decimal degrees

Approximate maximum latitude of tile

year

YYYY

Daymet processing year

tileid

 

Daymet Tile ID

nstns

stations

number of stations evaluated (tileid)

nstndays

days

number of station-days evaluated (tileid)

rad90mean

meter

mean: radius capturing 90% of filter kernel weight

rad90std

meter

standard deviation: radius capturing 90% of filter kernel weight

daymae

degrees Celsius

mean absolute error for single-day predictions

pormae

degrees Celsius

mean absolute error for period-of-record predictions

bias

degrees Celsius

mean prediction bias

tamean

degrees Celsius

mean observed temperature (tmin and tmax)

xlrmean

degrees C/meter

3-d regression: mean x-component

xlrstdv

degrees C/meter

3-d regression: among-station std dev of x-component

ylrmean

degrees C/meter

3-d regression: mean y-component

ylrstdv

degrees C/meter

3-d regression: among-station std dev of y-component

zlrmean

degrees C/meter

3-d regression: mean z-component

zlrstdv

degrees C/meter

3-d regression: among-station std dev of z-component

 

Shape files for precipitation (prcp) Cross-Validation Statistics have these attributes.

Field

Units/format

Description

Xmin

decimal degrees

Approximate minimum longitude of tile

Xmax

decimal degrees

Approximate maximum longitude of tile

Ymin

decimal degrees

Approximate minimum latitude of tile

Ymax

decimal degrees

Approximate maximum latitude of tile

year

YYYY

Daymet processing year

tileid

 

Daymet Tile ID

nstns

stations

number of stations evaluated (tileid)

nstndays

days

number of station-days evaluated (tileid)

rad90mean

meter

mean: radius capturing 90% of filter kernel weight

rad90std

meter

standard deviation:  radius capturing 90% of filter kernel weight

daymae

cm/day

mean absolute error for single-day predictions

pormae

cm/day

mean absolute error for period-of-record predictions

pormpae

%

mean absolute error as a percentage, for period of record predictions

bias

cm/day

mean prediction bias

ppmean

cm/day

mean observed daily total precipitation

xlrmean

1/meter

3-d regression: mean x-component

xlrstdv

1/meter

3-d regression: among-station std dev of x-component

ylrmean

1/meter

3-d regression: mean y-component

ylrstdv

1/meter

3-d regression: among-station std dev of y-component

zlrmean

1/meter

3-d regression: mean z-component

zlrstdv

1/meter

3-d regression: among-station std dev of z-component

User’s Notes

  • When “nstns” is zero (0), no input weather station data are available within that tile.  All attributes are recorded as nodata (-9999) or "nan".
  • When “nstns” have very low values (e.g. 1, 2, or 3) denoting limited input data available for that tile, values for the 3-dimensional regression components may be set to “nan” where the regressions algorithm failed.
  • Floating point precision has been carried forward from the Daymet model for all attributes.

 

Spatial Data Properties

Spatial Representation:  vector

Vector Format:  shape file

Nodata Value:  -9999

Spatial Reference Properties

Type:  Geographic

"GEOGCS['GCS_WGS_1984',  

                DATUM['WGS_1984',      

                SPHEROID['WGS_84',6378137.0,298.257223563]],  

                PRIMEM['Greenwich',0.0],  

                UNIT['Degree',0.0174532925199433]]"

 

Comma Separated Files

There are 3 comma separated files with this data set.  The complete time series (1980-2016) of annual cross-validation statistics for a variable is provided in a single comma separated file (*.csv) -- one file for each of the three variables.

File names follow this syntax:   DaymetV3_xval_pppp_yyyy-yyyy.csv

Where:

xval distinguishes these as Daymet cross-validation data files;

pppp is the respective Daymet input meteorological variable (tmin, tmax, and prcp); and

yyyy-yyyy is the range of annual summary statistics included in the file. 

User’s Notes

  • When “nstns” is zero (0), no input weather station data are available within that tile.  All attributes are recorded as nodata (-9999) or "nan".
  • When “nstns” have very low values (e.g. 1, 2, or 3) denoting limited input data available for that tile, values for the 3-dimensional regression components may be set to “nan” where the regressions algorithm failed.
  • Floating point precision has been carried forward from the Daymet model for all attributes.

 

Application and Derivation

The Daymet cross-validation analysis are used to characterize the sensitivity of Daymet model methods to the variation of parameters and to estimate the prediction errors associated with the final selected parameters.  The general cross-validation protocol is to withhold one observation at a time from a sample, generating a prediction error for the withheld case by comparing with the observed value, and repeating over all observations in the sample to generate an average prediction error.  The mean absolute error and bias are the basic error prediction error statistics.  MAE does not exaggerate the influence of outliers as would a root mean square error and provides a more robust parameterization framework.  Both the absolute value and sign of the prediction are considered in the generation of MAE and bias, respectively.

Quality Assessment

Occurrence of No Data and Not A Number (nan) field values

For tiles that had no input weather stations located within the 2 degree by 2 degree tile processing extent (e.g. nstns = 0), there are no cross-validation data available.  For these tiles, the nodata values are represented with -9999  or "nan" values.  For tiles with very low weather station inputs (e.g. nstns <= 3), it is often the case that the 3-dimensional regression components calculations failed.  In those cases, the regression values are represented with “nan” values in the attribute fields.

Data Acquisition, Materials, and Methods

Cross-validation Protocol

The Daymet cross-validation summary statistics are used to test the sensitivity of Daymet model methods to the variation of parameters and to estimate the prediction errors associated with the final selected parameters (Thornton, 1999). 

The general cross-validation protocol is to withhold one observation at a time from the sample, generating a prediction error for the withheld case by comparing with the observed value, and repeating over all observations in the sample to generate an average prediction error.  The mean absolute error and bias are the basic error prediction error statistics.  MAE does not exaggerate the influence of outliers as would a root mean square error and provides a more robust parameterization framework.  Both the absolute value and sign of the prediction are considered in the generation of MAE and bias, respectively.

The mean absolute error for single prediction days, or "daymae" is determined as below:

The bias for the single prediction days is determined as below:

The mean absolute error for the period of record predictions, or pormae, is determined as below:

 

Version 3.0 Daymet model inputs of spatially referenced ground observations of daily maximum and minimum temperature and precipitation were obtained from the NOAA National Centers for Environmental Information's Global Historical Climatology Network (GHCN)-Daily data set from Version 3.22 of the data distribution (Menne et al., 2012).  The sparse network of Mexican stations available through the GHCN-Daily network was augmented with additional stations provided by the Servicio Meteorológico Nacional of Mexico.  These data were obtained through an agreement with NOAA/GHCN-Daily in which GHCN-D acquired the station data directly from the Servicio Meteorológico Nacional and processed this data through the same QA/QC measures as all GHCN-D data are subject ensuring credibility to the data provenance of these additional data.  The additional Mexican data were then provided to the NASA Daymet processing group. 

Data Access

These data are available through the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Daymet: Annual Tile Summary Cross-Validation Statistics for North America, Version 3

Contact for Data Center Access Information:

References

Menne, M.J., I. Durre, R.S. Vose, B.E. Gleason, and T.G. Houston, 2012:  An overview of the Global Historical Climatology Network-Daily Database.  Journal of Atmospheric and Oceanic Technology, 29, 897-910, doi:10.1175/JTECH-D-11-00103.1. http://dx.doi.org/10.1175/JTECH-D-11-00103.1

Menne, M.J., I. Durre, B. Korzeniewski, S. McNeal, K. Thomas, X. Yin, S. Anthony, R. Ray, R.S. Vose, B.E.Gleason, and T.G. Houston, 2012: Global Historical Climatology Network -Daily (GHCN-Daily), Version 3.22.  NOAA National Climatic Data Center. http://doi.org/10.7289/V5D21VHZ February 29, 2016.

Thornton, P.E. and S.W. Running. 1999. An improved algorithm for estimating incident daily solar radiation from measurements of temperature, humidity, and precipitation. Agriculture and Forest Meteorology. 93:211 - 228. http://dx.doi.org/10.1016/S0168-1923(98)00126-9

Thornton, P.E., M.M. Thornton, B.W. Mayer, Y. Wei, R. Devarakonda, R.S. Vose, and R.B. Cook. 2016. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 3. ORNL DAAC, Oak Ridge, Tennessee, USA. http://dx.doi.org/10.3334/ORNLDAAC/1328

Data Set Revisions

The ORNL DAAC will update the Daymet V3.0 products annually. Version and change history documentation are provided.

ORNL DAAC Version Record for Version 3.0:

Daymet Product Version

ORNL DAAC Release Date Description
Version 3, Tile Summary Cross Validation for 1980-2016 April 20, 2017 ORNL DAAC archived and released the 2016 data for Version 3 of Daymet Tile Summary Cross Validation Statistics
Version 3, Tile Summary Cross Validation for 1980-2015 September 30, 2016 ORNL DAAC archived and released Version 3 of Daymet Tile Summary Cross Validation Statistics

  ORNL DAAC Version Record for Version 2.0:

Daymet Product Version ORNL DAAC Release Date Description
Version 2, Tile Summary Cross Validation Revision July 6, 2016 ORNL DAAC released the final revision of the Version 2 Daymet Tile Summary Cross Validation Statistics
Version 2, Tile Summary Cross Validation April 29, 2016 ORNL DAAC released the Version 2 Daymet Tile Summary Cross Validation Statistics