Data are stored in ASCII
Temperatures are stored as degrees C
Land squares and missing data are set to -99.99
The month and year are stored at the start of each month.
Data Array (72x36)
Item ( 1, 1) stores the value for the 5-deg-area centred at 177.5W and 87.5N
Item (72, 36) stores the value for the 5-deg-area centred at 177.5E and 87.5S
----- -----
| | |
| MON | YR |
|_____|_____|__________________________________
90N |(1,1) |
| |
| |
| |
| |
|(1,18) |
Equ | |
|(1,19) |
| |
| |
| |
| |
90S |(1,36)_________________________________(72,36)|
180W 0 180E
Monthly version of HadSST2 based on the ICOADS
Data generated by MDS2.2 from in situ observations held in the International
Comprehensive Ocean Atmosphere Data Set, ICOADS (see http://www.cdc.noaa.gov/coads/).
Reference: Improved analyses of changes and uncertainties in sea surface temperature
measured in situ since the mid-nineteenth century: the HadSST2 dataset. N.A.Rayner,
P.Brohan, D.E.Parker, C.K.Folland, J.J.Kennedy, M.Vanicek, T.Ansell and S.F.B.Tett.
In press J.Clim.
Data restrictions: for academic research use only. Data are Crown copyright see
(http://www.opsi.gov.uk/advice/crown-copyright/copyright-guidance/index.htm)
Updates and supplementary information will be available from http://www.hadobs.org
HadSST2_SST_1850_2004.txt.gz
============================
Monthly 5degree resolution SST anomalies wrt 1961-90 climatology
The observations that make up this dataset are taken from the International
Comprehensive Ocean-Atmosphere DataSet, ICOADS (see http://www.cdc.noaa.gov/coads/),
until 1997 and from the NCEP GTS archive thereafter. Individual observations must
first pass a series of quality checks (track check, reality check, positional check,
climatology check, buddy check, duplicate check). The quality-checked observations
in each 1degree longitude X 1degree latitude X pentad gridbox are then averaged
using a winsorised average. The pentad climatology is then subtracted from these
pentad superobs and the resulting anomalies are averaged to 5degree X 5degree X
monthly resolution. The data are then bias-corrected for the use of buckets in the
period 1850-1941.
HadSST2_m_and_s_errors_1850-2004.txt.gz
=======================================
Measurement and sampling error, 1 standard error
Measurement and sampling error refers to the random error caused by estimating an
area-averaged quantity from a finite number of noisy observations. These errors are
calculated directly from the gridded data. Measurement and sampling errors are
uncorrelated between gridboxes.
HadSST2_2.5_pct_bias_1850-2004.txt.gz
=====================================
2.5 percent bias bound, equivalent to 2 standard errors
The bias bound represents the low (2.5 percent) error bound on the bias corrected
data as calculated from 1000 physically plausible realisations of the bias corrected
dataset. The bias errors are completely correlated between gridboxes.
HadSST2_97.5_pct_bias_1850-2004.txt.gz
======================================
97.5 percent bias bound, equivalent to 2 standard errors
The bias bound represents the high (97.5 percent) error bound on the bias corrected
data as calculated from 1000 physically plausible realisations of the bias corrected
dataset. The bias errors are completely correlated between gridboxes.
A note on combining errors
==========================
If you would like to create combined 2 sigma uncertainties at each gridbox, it is
suggested that you subtract the "low_bias" field from the "high_bias"field, divide
by two and then add to two times the sampling and measurement errors in quadrature,
as they are independent uncertainties. This is because the bias uncertainties are
95% confidence intervals, but the sampling and measurement errors are 1 standard error.
Note that, although the sampling and measurement errors are uncorrelated between grid
boxes, the bias correction uncertainties are completely correlated between grid boxes.
This will have implications for the way youcalculate average uncertainties for any
averaged time series that youcreate, e.g. your Nino3.4 index.