With this update to GHCN - M, the Merged Land and
Ocean Surface Temperature dataset also is subsequently revised as MLOST version 3.5.3.
Both NASA GISS and NOAA NCEI use NOAA's ERSST.v4 «pause buster» data for the ocean surface temperature components of their combined land -
ocean surface temperature datasets, and, today, both agencies are holding a multi-agency press conference to announce their «warmest ever» 2016 global surface temperature findings.
Not exact matches
The East Pacific
Ocean (90S - 90N, 180 - 80W) has not warmed since the start of the satellite - based Reynolds OI.v2 sea
surface temperature dataset, yet the multi-model mean of the CMIP3 (IPCC AR4) and CMIP5 (IPCC AR5) simulations of sea
surface temperatures say, if they were warmed by anthropogenic forcings, they should have warmed approximately 0.42 to 0.44 deg C.
That solar activity is largely underestimated was a topic at the SORCE meeting last October: «Widespread empirical evidence from the extensive Earth climate
datasets suggests the presence of an 11 - year solar signal of order 0.1 K in
surface, atmospheric, and
ocean temperatures.
A known problem with that
dataset is that GISS Deletes Arctic And Southern
Ocean Sea
Surface Temperature (SST) Data.
And the lower troposphere
temperatures also show warming in the Southern
Ocean (latitudes 65S - 55S) while the
surface temperature - based
datasets both show cooling.
Let's compare the warming and cooling patterns for lower troposphere
temperatures over the
oceans to a spatially complete, satellite - enhanced sea
surface temperature dataset, Reynolds OI.v2.
Surface warming / ocean warming: «A reassessment of temperature variations and trends from global reanalyses and monthly surface climatological datasets» «Estimating changes in global temperature since the pre-industrial period» «Possible artifacts of data biases in the recent global surface warming hiatus» «Assessing the impact of satellite - based observations in sea surface temperature trends
Surface warming /
ocean warming: «A reassessment of
temperature variations and trends from global reanalyses and monthly
surface climatological datasets» «Estimating changes in global temperature since the pre-industrial period» «Possible artifacts of data biases in the recent global surface warming hiatus» «Assessing the impact of satellite - based observations in sea surface temperature trends
surface climatological
datasets» «Estimating changes in global
temperature since the pre-industrial period» «Possible artifacts of data biases in the recent global
surface warming hiatus» «Assessing the impact of satellite - based observations in sea surface temperature trends
surface warming hiatus» «Assessing the impact of satellite - based observations in sea
surface temperature trends
surface temperature trends»
«Estimating changes in global
temperature since the pre-industrial period» «A reassessment of
temperature variations and trends from global reanalyses and monthly
surface climatological
datasets» «Deducing Multidecadal Anthropogenic Global Warming Trends Using Multiple Regression Analysis» «Early onset of industrial - era warming across the
oceans and continents»
The three major groups calculating the average
surface temperature of the earth (land and
ocean combined) all are currently indicating that 2014 will likely nudge out 2010 (by a couple hundredths of a degree Celsius) to become the warmest year in each
dataset (which begin in mid-to-late 1800s).
Phil Jones and Tom Wigley (the second Director of the Climatic Research Unit) devoted significant portions of their scientific careers to the construction of the land component of the so - called «HadCRUT»
dataset of land and
ocean surface temperatures.
I know that around the US there are coastal moorings and stations in river mouths and harbours which report water
surface temperatures that aren't comparable to nearby open
ocean temperature measurements used in SST
datasets.
Introduction: The NOAA Global (Land and
Ocean)
Surface Temperature Anomaly
dataset is a product of the National Climatic Data Center (NCDC).
Figure 12: Annual mean
temperature anomalies (departure from mean) for Australia (1911 — 2014), using the ACORN - SAT
dataset and a range of other local and international land - only (LO) and blended (BL) land /
ocean datasets based upon
surface - based instruments.
These
datasets include: NOAA Optimum Interpolation 1/4 Degree Daily Sea
Surface Temperature (OISST) Analysis, Version 2 AVHRR Pathfinder Version 5.2 Level 3 Collated (L3C) Global 4 km Sea
Surface Temperature (SST) Climate Data Record (CDR) for 1981 - 2010 NOAA Climate Data Record (CDR) of Gridded Satellite Data from ISCCP B1 (GridSat - B1) 11 micron Brightness
Temperature, Version 2 NCDC Storm Events Database Coastal Economic Trends for Coastal Geographies Demographic Trends (1970 - 2010) for Coastal Geographies FEMA HAZUS Critical Facilities for Coastal Geographies Time - Series Data for Self - Employed Economic Activity Dependent on the
Ocean and Great Lakes Economy for Counties, States, and the Nation between 2005 and 2012 Time - Series Data on the
Ocean and Great Lakes Economy for Counties, States, and the Nation between 2005 and 2012 (Sector and Industry Level) Time - Series Data on the
Ocean and Great Lakes Economy for Counties, States, and the Nation between 2005 and 2012 (Sector Level)... Continued
NOAA: «The globally averaged
temperature over land and
ocean surfaces for September 2017 was the fourth highest for the month of September in the NOAA global
temperature dataset record, which dates back 138 years to 1880.