Sentences with phrase «sst data»

In my view only meaningful graph to start from is the N.A. SST which tells what the Atlantic Multidecadal Oscillation — AMO is doing SST or from Bob Tisdale: The SST data is available here: http://www.esrl.noaa.gov/psd/data/correlation/amon.us.long.mean.data if you whish to look at it a bit closer.

Are you aware that the annual variations in monthly land surface data are at least 4 times greater than the TLT data and about 35 times greater than the annual variations in monthly SST data?

Overall the SST data are less variable in each hemisphere in these rather poorly observed periods.

Also, I believe the Kaplan SST data has been using the Reynolds OI.v2 data since 2003, and like the HADISST data, the Reynolds OI.v2 is satellite based.

But I just discussed with links to the GISS paper that the GISS dTs is obsolete: If their «current» analysis uses SST data, then the dataset you referred to in the post is «not current», meaning it is outdated, or obsolete.

The point I was trying to make is that there are shorelines that separate the oceans from the land and that SST data and land surface data are measuring two completely different variables.

They start with HADISST, and in December 1981 they switch to Reynolds OI.v2 SST data.

You are now saying that all of the «extra-heat» in land surface temperatures could result from «UHI + possibly faulty adjustments of data and siting problems» as you wrote in the post, - PLUS - the methods used to infill missing data, - PLUS - the deletion of SST data in the Arctic and Southern Oceans, etc..

Also, I'd check the source of your Kaplan SST data.

HADSST2 reaches into areas with seasonal sea ice, but Kaplan does not, meaning there is very little Arctic and Southern Ocean SST data in the Kaplan dataset.

However, compensation for a different potential source of bias in SST data in the past decade — the transition from ship - to buoy - derived SSTs — might increase the century - long trends by raising recent SSTs as much as ~ 0.1 deg C, as buoy - derived SSTs are biased cool relative to ship measurements [10 — Worley et al 2005]

I believe that David Smith has made comparisons of two of the commonly used SST data sets and presented the results here.

The bias estimates are used to adjust the SST data to create a new, more homogeneous data set of anomalies relative to the 1961 - 1990 average.

In order to trace adjustments, for example, an SST data set, one would have to start with the preliminary adjustments made by the providers of data to ICOADS and those performed by ICOADS and then follow on with those made in the finished data sets such as Kaplan, Rayner and Smith and Reynolds.

In summary, I would not rely on SST data obtained from merchant vessels — too many variables.

Neither are directly measuring the flow but use either SST data & modelling (there is an illustrative animation of their modelling in this RC post) or proxy paleo - data to infer the past strength of the AMOC.

Any opinions whether they have made a mistake in the analysis by using the SST data model from Hadley rather than that of NOAA?

How good is SST data from 1850 anyway?

Yes, SST data sets have warts as well, albeit somewhat smaller warts than the cyclone data.

But the important issue, ignored by Landsea et al. is that the tropical cyclone data and the SST data is absolutely independent.

Also, his SST data (see our Fig. 2 above) go back to 1930, thus covering the whole previous warm phase of the AMO.

These tools support the regridding of the SST data products to a coarser raster and the regional averaging of data for a selectable time interval.

The results shown here are based on the current version of the UK Met Office Hadley Centre SST data set (HadSST2; ref.

AR5 3.2.2.3 says of it «Overall, the SST data should be regarded as more reliable because averaging of fewer samples is needed for SST than for HadMAT to remove synoptic weather noise.

GISSTEMP uses the NOAAv4.01 SST data set (ERSST4).

I'll take a look at the Reynolds OI.v2 SST data when they update it next, hopefully tomorrow, to see what it looks like... if it shows up.

I would like to address the following question / concern to Judith Curry and the Climate Etc community, regarding calculation of SST data.

It seems to me that this dataset exhibits the same attributes as the SST data set that I wrote an article about, whereby the provenance of the original data can be as dubious or unlikely as is possible, but researchers seem prepared to disregard its accuracy in order to analyse and parse it and then make profound pronouncements.

Looking at SST data (HADSST2 time series available at woodfortrees.org for instance), one can observe that global SST is actually calculated as the true average between Northern Hemisphere SST and Southern Hemisphere SST.

With due respect, I consider that it is completely and absolutely inappropriate to present any temperature statistic that combines land and SST data.

«At all sites and during warm as well as cold climatic intervals SST values are well above 0 °C (i.e., ranging between about 5 and 12 °C), suggesting that the SST data represent more the summer situation with ice - free conditions.»

With averages over the full array extent based on a minimum of 40 % valid data points, SAT and SST data are available for 1993 - 2015.

So, will the author's proposed cycles from the land record fit your SST data over the available 160 time period; and if it does fit, what is «their» near - term prediction for the next 60 years?

To add even more cooks in the kitchen, which may or may not improve the soup, does Willis» combined 60 + 22 year cycle fit the SST data shown in your ppt?

The raw SST data is in ICOADS which is freely available on line: http://icoads.noaa.gov/

OI.v2 SST data is still available.

The effect of the newly released SST data by Hadley looks to me by eye like it would enhance the 60 yr signal, but I only learned of it last week.

Bob Tisdale's SST data makes this overwhelmingly obvious, and he identifies ENSO events as a trigger for the jumps, but that still doesn't yet predict the direction of the jumps or their magnitude (that is, the long term underlying trend in the local equilibria the jumps move between).

The SST data used here comprise over 80 million observations from the UK Main Marine Data Bank, the United States Comprehensive Ocean Atmosphere Data Set (COADS) and recent information telecommunicated from ships and buoys from the World Weather Watch.

Overall, however, the SST data should be regarded as more reliable, though the relative changes in NMAT since 1991 may be partly real (Christy et al., 2001).

It is not pure residual SST data like the AMO.

Figure 2.4 (Folland et al., 2001) shows simulations of global land - surface air temperature anomalies in model runs forced with SST, with and without bias adjustments to the SST data before 1942.

was in apparent reference to SST data from the WWII era when engine intake readings were preferred by merchant mariners to the bucket method for some fairly obvious reasons.

Here's a link to Smith and Reynolds» instructions for downloading their SST data from NOAA's NOMADS system, based on user - defined months, years, and coordinates.

And also the AMO index back to 1854 as well the Raw data [red line] it comes from (the AMO is the detrended version of this raw SST data).

A combined physical - empirical method (Folland and Parker, 1995) is used, as in the SAR, to estimate adjustments to ships SST data obtained up to 1941 to compensate for heat losses from uninsulated (mainly canvas) or partly - insulated (mainly wooden) buckets (see Box 2.2).

Jim — The Wigley speculations you cite are similar to points I made in my above comment, It's necessary for any adjusted SST data, if it is to accurately reflect reality, to be reconcilable with land data that also shows a 1940's peak and dip.

Thanks go to Dale Bailey and the Royal North Shore Hospital for CT scanning, Mark Ohman for laboratory space and use of the Iatroscan MK - 5, and Scott Heron of NOAA Coral Reef Watch for providing the satellite - derived SST data.

Because of this, Folland and Parker were careful only to use NMAT data which hadn't previously been adjusted using SST data in order to constrain the SST adjustments in the period 1856 - 1920 for their 1995 paper.

At that time the value of SST data was short lived, and lasted hardly longer than for the next few days weather forecasting.