data: $partialdiff sub X$ mean $partialdiff sub Z$ [ detrended-bfl detrended-bfl ( UMD Carton goa beta7 t ) climatology ]

served from IRI/LDEO Climate Data Library

∂_X mean ∂_Z [ detrended-bfl detrended-bfl ( UMD Carton goa beta7 t ) climatology ] : ∂_X ∂_Z temperature data

t adif adif adif adif partial_Z partial_Z partial_X ∂_X ∂_Z temperature from UMD Carton goa beta7: beta7 run with 16 level data assimilation (altimetry 14 level), 50-2000.

Independent Variables (Grids)

Longitude (longitude): grid: /X (degree_east) periodic (0.5E) to (0.5W) by 1.0 N= 360 pts :grid

Other Info

CE

null

CS

null

datatype

realarraytype

file_missing_value

-9.98999971E33

gridid

190064632

missing_value

NaN

pointwidth

1.0

standard_name

time

units

57.2957795130823 degree_Kelvin meter^-1 radian^-1 east

history

$partialdiff sub Z$ [ detrended-bfl detrended-bfl ( UMD Carton goa beta7 t ) climatology ]

beta7 run with 16 level data assimilation (altimetry 14 level), 50-2000
Averaged over T2[1950, 2001] minimum 0.0% data present

$partialdiff sub X$ mean $partialdiff sub Z$ [ detrended-bfl detrended-bfl ( UMD Carton goa beta7 t ) climatology ]

Averaged over Y[60.46236S, 60.46236N] Z[15.0 m, 3254.05 m] T[Jan, Dec] minimum 0.0% data present

References

Carton, J.A., G. Chepurin, X. Cao, and B.S. Giese, 2000a: A Simple Ocean Data Assimilation analysis of the global upper ocean 1950-1995, Part 1: methodology, J. Phys. Oceanogr., 30, 294-309.

Carton, J.A., G. Chepurin, and X. Cao, 2000b: A Simple Ocean Data Assimilation analysis of the global upper ocean 1950-1995 Part 2: results, J. Phys. Oceanogr., 30, 311-326

Last updated: Thu, 23 Jan 2003 21:17:59 GMT

Data Views

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$partialdiff sub X$ mean $partialdiff sub Z$ [ detrended-bfl detrended-bfl ( UMD Carton goa beta7 t ) climatology ] [ X \|]	M

Filters

Here are some filters that are useful for manipulating data. There are actually many more available, but they have to be entered manually. See Ingrid Function Documentation for more information.

Monthly Climatology calculates a monthly climatology by averaging over all years.
anomalies calculates the difference between the (above) monthly climatology and the original data.
Integrate along X
Differentiate along X
Take differences along X