7.3. Cell Methods
To describe the characteristic of a field that
is represented by cell values, we define the
attribute of the variable. This
is a string attribute comprising a list
of blank-separated words of the form "name:
method". Each "name: method" pair indicates that
for an axis identified by name, the cell values
representing the field have been determined or
derived by the specified method. For example, if data
values have been generated by computing time means, then this could be
cell_methods="t: mean", assuming here that
the name of the time
dimension variable is "t".
The token name
can be a dimension of the variable, a scalar
coordinate variable, or a valid standard name.
In the specification of this attribute,
name can be a dimension of the variable, a scalar
coordinate variable, a valid standard name, or the word "
(See Section 7.3.4, “Cell methods when there are no coordinates” concerning the use
of standard names in cell_methods.) The
values of method should be selected from the list
Appendix E, Cell Methods,
Case is not
significant in the method name. Some methods
imply a change of units of
the variable, as is indicated in
Appendix E, Cell Methods.
It must be remembered that the
method applies only to the axis designated in
cell_methods by name, and
different methods may apply to other axes. If, for instance,
a precipitation value in a longitude-latitude
cell is given the method
maximum for these axes,
it means that it is the maximum
within these spatial cells, and does not imply
that it is also the maximum in time.
Furthermore, it should be noted that if any method
other than "
point" is specified for a given axis,
cell_bounds should also be provided for that
axis (except for the relatively rare exceptions described in
Section 7.3.4, “Cell methods when there are no coordinates”).
The default interpretation for variables that
do not have the
specified depends on whether the quantity is
extensive (which depends on the size of the cell)
or intensive (which does not). Suppose, for example,
the quantities "accumulated precipitation"
and "precipitation rate" each have a time axis.
A variable representing accumulated precipitation
is extensive in time because it depends on the length
of the time interval over which it is accumulated.
For correct interpretation, it therefore
requires a time interval
to be completely specified via a boundary variable
(i.e., via a
cell_bounds attribute for the time axis).
In this case the default
interpretation is that the cell method is a sum over the specified time interval.
This can be (optionally) indicated explicitly by setting the cell method
sum. A precipitation rate on the other hand is
intensive in time and could equally well represent either
an instantaneous value or a mean value over the
time interval specified by the cell. In this case the
default interpretation for the quantity would be "instantaneous" (which,
optionally, can be indicated explicitly by setting the cell method to
point). More often, however, cell values for
intensive quantities are means, and this should be indicated explicitly
by setting the cell method to
mean and specifying the cell bounds.
Because the default interpretation for an intensive
quantity differs from that of an extensive quantity and because this distinction
may not be understood by some users of the data, it is recommended that every data
variable include for each of its dimensions and each of its scalar coordinate
cell_methods information of interest
(unless this information would
not be meaningful). It is especially recommended that
cell_methods be explicitly
specified for each spatio-temporal dimension and each spatio-temporal scalar
Example 7.4. Methods applied to a timeseries
Consider 12-hourly timeseries of pressure, temperature and precipitation from a number of stations, where pressure is measured instantaneously, maximum temperature for the preceding 12 hours is recorded, and precipitation is accumulated in a rain gauge. For a period of 48 hours from 6 a.m. on 19 April 1998, the data is structured as follows:
dimensions: time = UNLIMITED; // (5 currently) station = 10; nv = 2; variables: float pressure(station,time)(time,station); pressure:long_name = "pressure"; pressure:units = "kPa"; pressure:cell_methods = "time: point"; float maxtemp(station,time)(time,station); maxtemp:long_name = "temperature"; maxtemp:units = "K"; maxtemp:cell_methods = "time: maximum"; float ppn(station,time)(time,station); ppn:long_name = "depth of water-equivalent precipitation"; ppn:units = "mm"; ppn:cell_methods = "time: sum"; double time(time); time:long_name = "time"; time:units = "h since 1998-4-19 6:0:0"; time:bounds = "time_bnds"; double time_bnds(time,nv); data: time = 0., 12., 24., 36., 48.; time_bnds = -12.,0., 0.,12., 12.,24., 24.,36., 36.,48.;
Note that in this example the
time axis values coincide with
the end of each interval. It is
sometimes desirable, however, to
use the midpoint of intervals as
coordinate values for variables
that are representative of an
interval. An application may
simply obtain the midpoint values
by making use of the boundary
If more than one cell method is to be indicated, they should be
arranged in the order they were applied. The left-most operation
is assumed to have been applied first. Suppose, for example, that
within each grid cell a quantity varies
in both longitude and time and that these dimensions are named "lon" and "time",
respectively. Then values representing the time-average of the zonal
maximum are labeled
cell_methods="lon: maximum time: mean"
(i.e. find the largest value at each instant of time over all
longitudes, then average these maxima over time); values of the
zonal maximum of time-averages are labeled
cell_methods="time: mean lon: maximum". If the methods could
have been applied in any order without affecting the outcome,
they may be put in any order in the
If a data value is representative of variation over a combination
of axes, a single method should be prefixed by the names of all
the dimensions involved (listed in any order, since in this case
the order must be immaterial). Dimensions
should be grouped in this way only if there is an essential
difference from treating the dimensions individually. For instance, the
standard deviation of topographic height within a
longitude-latitude gridbox could
cell_methods="lat: lon: standard_deviation".
(Note also, that in accordance with the recommendation of the following paragraph,
this could be equivalently and preferably indicated by
This is not the same as
cell_methods="lon: standard_deviation lat: standard_deviation",
which would mean finding the standard deviation along each
parallel of latitude within the zonal extent of the gridbox,
and then the standard deviation of these values over latitude.
To indicate variation over horizontal area, it is recommended
that instead of specifying the combination of horizontal dimensions, the special
area" be used. The common case of an area-mean can thus
be indicated by
(rather than, for example, "
lon: lat: mean").
The horizontal coordinate variables to which "
area" refers are
in this case not explicitly indicated in
cell_methods but can be
identified, if necessary, from attributes attached to the coordinate variables,
scalar coordinate variables, or auxiliary coordinate variables, as described in
To indicate more precisely how the cell method was applied,
extra information may be included in parentheses () after the
identification of the method. This information includes
standardized and non-standardized parts. Currently the only
standardized information is to provide the typical interval
between the original data values to which the method was applied,
in the situation where the present data values are statistically
representative of original data values which had a finer spacing.
The syntax is (
interval: value unit),
where value is a numerical
value and unit
is a string that can be recognized by UNIDATA's
Udunits package [UDUNITS].
The unit will usually be
dimensionally equivalent to the unit of the corresponding
dimension, but this is not required (which allows, for example,
the interval for a standard deviation calculated from points evenly
spaced in distance along a parallel to be reported in units of length
even if the zonal coordinate of the cells is given in degrees). Recording the original
interval is particularly important for standard deviations.
For example, the standard deviation of daily values could be
cell_methods="time: standard_deviation (interval: 1 day)"
and of annual values by
cell_methods="time: standard_deviation (interval: 1 year)".
If the cell method applies to a combination of axes, they may
have a common original interval
cell_methods="lat: lon: standard_deviation (interval: 10 km)".
Alternatively, they may have separate intervals, which are
matched to the names of axes by position
cell_methods="lat: lon: standard_deviation (interval: 0.1 degree_N interval: 0.2 degree_E)",
in which 0.1 degree applies to latitude and 0.2 degree to longitude.
If there is both standardized and non-standardized information,
the non-standardized follows the standardized information and
comment:. If there is no
standardized information, the keyword
comment: should be omitted.
For instance, an area-weighted mean over
latitude could be indicated as
lat: mean (area-weighted)
lat: mean (interval: 1 degree_north comment: area-weighted).
A dimension of size one may be the result of "collapsing" an
axis by some statistical operation, for instance by calculating
a variance from time series data. We strongly recommend that
dimensions of size one be retained (or scalar coordinate variables be
defined) to enable documentation of the method (through the
cell_methods attribute) and its domain (through the
Example 7.5. Surface air temperature variance
The variance of the diurnal cycle on 1 January 1990 has been calculated from hourly instantaneous surface air temperature measurements. The time dimension of size one has been retained.
dimensions: lat=90; lon=180; time=1; nv=2; variables: float TS_var(time,lat,lon); TS_var:long_name="surface air temperature variance" TS_var:units="K2"; TS_var:cell_methods="time: variance (interval: 1 hr comment: sampled instantaneously)"; float time(time); time:units="days since 1990-01-01 00:00:00"; time:bounds="time_bnds"; float time_bnds(time,nv); data: time=.5; time_bnds=0.,1.;
Notice that a parenthesized comment in the
cell_methods attribute provides
the nature of the samples used to calculate the variance.
By default, the statistical method indicated by
cell_methods is assumed to
have been evaluated over the entire horizontal area of the cell. Sometimes, however, it is
useful to limit consideration to only a portion of a cell (e.g. a mean over the sea-ice area).
To indicate this, one of two conventions may be used.
The first convention is a method that can be used for the common case of a single area-type.
In this case, the
cell_methods attribute may include a string of the form
Here name could, for example, be
type may be any of the strings permitted for a variable with a
area_type. As an example,
if the method were
mean and the
sea_ice, then the data would represent a mean over only the sea
ice portion of the grid cell. If the data writer expects type to be
interpreted as one of the standard
area_type strings, then none of
the variables in the netCDF file should be given a name identical to that of the string
(because the second convention, described in the next paragraph, takes precedence).
The second convention is the more general. In this case, the
entry is of the form "name: method
Here typevar is a string-valued auxiliary coordinate variable or string-valued
scalar coordinate variable (see Section 6.1, “Labels”) with a
area_type. The variable typevar contains the name(s)
of the selected portion(s) of the grid cell to which the method is applied.
This convention can accommodate cases in which a method is applied to more than one area type
and the result is stored in a single data variable (with a dimension which ranges across the
various area types). It provides a convenient way to store output from land surface models,
for example, since they deal with many area types within each surface gridbox
Example 7.6. Mean surface temperature over land and sensible heat flux averaged separately over land and sea.
dimensions: lat=73; lon=96; maxlen=20; ls=2; variables: float surface_temperature(lat,lon); surface_temperature:cell_methods="area: mean where land"; float surface_upward_sensible_heat_flux(ls,lat,lon); surface_upward_sensible_heat_flux:coordinates="land_sea"; surface_upward_sensible_heat_flux:cell_methods="area: mean where land_sea"; char land_sea(ls,maxlen); land_sea:standard_name="area_type"; data: land_sea="land","sea";
If the method is
mean, various ways of calculating
the mean can be distinguished in the
cell_methods attribute with a string
of the form
mean where type1 [
Here, type1 can be any of the possibilities allowed for
typevar or type (as specified in the two paragraphs
preceding above Example). The same options apply to type2, except it is not
allowed to be the name of an auxiliary coordinate variable with a dimension greater than one
(ignoring the dimension accommodating the maximum string length). A
attribute with a string of the form
mean where type1
indicates the mean is calculated by summing over the type1 portion of the cell and
dividing by the area of the type2 portion. In particular,
cell_methods string of the form
mean where all_area_types over type2" indicates the mean is
calculated by summing over all types of area within the cell and dividing by the area of the
type2 portion. (Note that "
all_area_types" is one of the
valid strings permitted for a variable with the
over type2" is omitted, the mean is calculated by
summing over the type1 portion of the cell and dividing by the area of this portion.
Example 7.7. Thickness of sea-ice and snow on sea-ice averaged over sea area.
variables: float sea_ice_thickness(lat,lon); sea_ice_thickness:cell_methods="area: mean where sea_ice over sea"; sea_ice_thickness:standard_name="sea_ice_thickness"; sea_ice_thickness:units="m"; float snow_thickness(lat,lon); snow_thickness:cell_methods="area: mean where sea_ice over sea"; snow_thickness:standard_name="lwe_thickness_of_surface_snow_amount"; snow_thickness:units="m";
In the case of sea-ice thickness, the phrase
where sea_ice" could be replaced by "
without changing the meaning since the integral of sea-ice thickness over all area
types is obviously the same as the integral over the sea-ice area only.
In the case of snow thickness, "
where sea_ice" differs from
where all_area_types" because "
excludes snow on land from the average.
To provide an indication that a particular cell method is relevant
to the data without having to provide a precise description of the corresponding cell,
the "name" that appears in a
"name: method" pair may be an appropriate
standard_name (which identifies the dimension) or the string,
"area" (rather than the name of a scalar coordinate variable or a dimension
with a coordinate variable). This convention cannot be used, however, if the
name of a dimension or scalar coordinate variable is identical to name.
There are two situations where this convention is useful.
First, it allows one to provide some indication of the method when the cell
coordinate range cannot be precisely defined. For example, a climatological
mean might be based on any data that exists, and, in general, the data might
not be available over the same time periods everywhere. In this case, the
time range would not be well defined (because it would vary, depending on location),
and it could not be precisely specified through a time dimension's bounds.
Nevertheless, useful information can be conveyed by a
cell_methods entry of "
time, it should be noted, is a valid
(As required by this convention, it is assumed here that for the data referred
to by this
cell_methods attribute, "time" is not a dimension or coordinate
Second, for a few special dimensions, this convention allows one to indicate (without explicitly defining the coordinates) that the method applies to the domain covering the entire permitted range of those dimensions. This is allowed only for longitude, latitude, and area (indicating a combination of horizontal coordinates). For longitude, the domain is indicated according to this provision by the string "longitude" (rather than the name of a longitude coordinate variable), and this implies that the method applies to all possible longitudes (i.e., from 0E to 360E). For latitude, the string "latitude" is used and implies the method applies to all possible latitudes (i.e., from 90S to 90N). For area, the string "area" is used and implies the method applies to the whole world.
In the second case if, in addition, the data variable has a dimension with
a corresponding labeled axis that specifies a geographic region
(Section 6.1.1, “Geographic Regions”), the implied range of longitude and
latitude is the valid range for each specified region, or in the case of
area the domain is the geographic region. For example, there could be
cell_methods entry of "
longitude is not the
name of a dimension or coordinate variable (but is one of the special
cases given above). That would indicate a mean over all longitudes.
Note, however, that if in addition the data variable had a scalar coordinate
variable with a
and a value of
would indicate a mean over longitudes that lie within the Atlantic Ocean,
not all longitudes.
We recommend that whenever possible, cell bounds should be supplied by giving the variable a dimension of size one and attaching bounds to the associated coordinate variable.