2015 Global Temperatures

[chubbs]

Can you point me to several peer-reviewed studies that discredit the accuracy of UAH?

Here are several by Q Fu and co-authors of Washington U    All based on previous versions of UAH though.

 

http://www.atmos.washington.edu/~qfu/publications.php

 

Po-Chedley, S, T.J. Thorsen, and Q. Fu, 2015: Removing Diurnal Cycle Contamination in Satellite-Derived Tropospheric Temperatures: Understanding Tropical Tropospheric Trend Discrepancies. J. Clim., 28, 2274 - 2290, doi:10.1175/JCLI-D-13-00767.1.

 

Po-Chedley, S., and Q. Fu, 2012: A Bias in the Midtropospheric Channel Warm Target Factor on the NOAA-9 Microwave Sounding Unit. J. Atmos. Oceanic Technol., 29, 646-652, doi:10.1175/JTECH-D-11-00147.1

 

Fu, Q., and C.M. Johanson, 2004: Stratospheric influences on MSU-derived tropospheric temperature trends: A direct error analysis. J. Climate, 17, 4636-4640.

 

Fu, Q., C.M. Johanson, S.G. Warren, and D.J. Seidel, 2004: Contribution of Stratospheric Cooling to Satellite-Inferred Tropspheric Temperature Trends.Nature, 429, 55-58 ( May 6, 2004 ).

[bluewave]

Several Washington U  papers  by Po-Chedly and/or Fu with co-authors going back 10+ years with a range of correction factors identified for satellite/microwave sounding units. All based on previous versions of UAH though.

 

http://www.atmos.washington.edu/~qfu/publications.php

 

This new one was an interesting read:

 

http://iopscience.iop.org/1748-9326/10/5/054007/article

 

 

Abstract

 

Temperature trends in the updated data show three noteworthy features. First, tropical warming is equally strong over both the 1959–2012 and 1979–2012 periods, increasing smoothly and almost moist-adiabatically from the surface (where it is roughly 0.14 K/decade) to 300 hPa (where it is about 0.25 K/decade over both periods), a pattern very close to that in climate model predictions. This contradicts suggestions that atmospheric warming has slowed in recent decades or that it has not kept up with that at the surface.

 

We support the findings of other recent studies (Po-Chedley et al 2015) that reports of weak tropospheric warming have likely been due to flaws in calibration and other problems and that warming patterns have proceeded in the way expected from models. Moreover our data do not show any slowdown of tropical atmospheric warming since 1998/99, an interesting finding that deserves further scrutiny using other datasets.

[The_Global_Warmer]

I don't think the CFSv2 is a bad dataset at all. I think it is better than the surface record that is for sure. Is it 100% accurate? No...but the surface record is farther off...

You are way to intelligent for this.

[The_Global_Warmer]

Global ssta for April are the warmest on record for April.

[The_Global_Warmer]

the Dragon Breathes

[chrisf97212]

 

This new one was an interesting read:

 

http://iopscience.iop.org/1748-9326/10/5/054007/article

 

 

Abstract

 

Temperature trends in the updated data show three noteworthy features. First, tropical warming is equally strong over both the 1959–2012 and 1979–2012 periods, increasing smoothly and almost moist-adiabatically from the surface (where it is roughly 0.14 K/decade) to 300 hPa (where it is about 0.25 K/decade over both periods), a pattern very close to that in climate model predictions. This contradicts suggestions that atmospheric warming has slowed in recent decades or that it has not kept up with that at the surface.

 

We support the findings of other recent studies (Po-Chedley et al 2015) that reports of weak tropospheric warming have likely been due to flaws in calibration and other problems and that warming patterns have proceeded in the way expected from models. Moreover our data do not show any slowdown of tropical atmospheric warming since 1998/99, an interesting finding that deserves further scrutiny using other datasets.

 

 

I've often wondered why tropospheric models didn't match satellite records but not sure I buy their methodology.

 

"This new radiosonde dataset Iterative Universal Kriging (IUKv2) was produced via a process of IUKv2, using the same methodology as an earlier version (Sherwood et al 2008, hereafter S08) with a few modifications. The methodology statistically corrects for incomplete sampling and step changes in bias arising from changed instrumentation or observing practises. It does this by, in effect, performing a multiple regression of the available data onto a structural model that allows simultaneously for natural and artificial changes. This preserves trends and slow variations at individual stations in an unbiased way given the structural model, a property that is essential for obtaining global trends but not yet demonstrated for other approaches that have been used (Sherwood 2007). Raw data are from the Integrated Global Radiosonde Archive (IGRA),"

 

 

"Observational records of atmospheric temperature in recent decades, however, have often failed to show the atmospheric signature expected from this warming. In particular many have not shown the local maximum of warming rate in the tropical upper troposphere (near 11–13 km) predicted by climate models and indeed expected on the basis of thermodynamic arguments fundamental to tropical meteorology (Agudelo and Curry 2004, Santer et al 2005, Mitchell et al 2013)....Satellite sounders available since 1979 can provide some constraint on the vertical variation of warming, but only in the form of broad weighted averages that span much of the troposphere and/or stratosphere. These data have been interpreted as indicating too little warming trend in the upper compared to the lower troposphere (Fu et al 2011, Po-Chedley and Fu 2012) and one satellite product shows less warming in the atmosphere than at the surface (Christy et al 2010). Caution is warranted however because the satellites suffer from uncertain changes over time in calibration and other inhomogeneities, exacerbated by the manipulations of the data necessary to extract the signals of concern here (CCSP 2006). Another problem is that warming trends in the upper troposphere are easily corrupted by the much larger cooling trends in the lower stratosphere"

[skierinvermont]

So let's get this straight:

 

1. CFSv2 is a product which has undergone no long-term quality control for surface temperature

 

2. It has an abrupt change in data assimilation and corresponding spurious cooling in 2010

 

and you insist it is remotely accurate because Ryan Maue uses it? Ryan Maue is a climate denier who works with the even more notorious climate denier Joe Bastardi, and who has no involvement whatsoever with the creation of the CFSR which is an NCEP product. Contact the NCEP. I know for a fact they will tell you that their product is not designed for nor capable of giving long-term accurate measures of surface warming.

 

 

If it were accurate, it would be 100% due to chance, since it was never designed for that purpose.

[wolfpackmet]

After peaking in December, the PDO continues to slowly drop.  April's value came in at +1.44 http://research.jisao.washington.edu/pdo/PDO.latest

[chubbs]

GISS for April came in at 75 - a little warmer than I projected a couple of weeks ago based on CFS2. The relatively cool CFS2 value for April was balanced by relatively warm SST.

 

2013    61   53   65   50   57   57   54   60   64   58   73   60     59 
2014    67   43   72   73   77   64   52   76   79   76   61   73     68
2015    76   80   85   75  **** **** **** **** ****   **** **** ****    ****
Year  Jan  Feb  Mar  Apr 

[The_Global_Warmer]

The cool pockets are at high latitudes.

The SouthernSouthern Ocean ssts are at record lows again.

But it cant compete with so much sub tropical and tropical warmth.

[chubbs]

This recent paper (open source) finds that radiosonde data show warming of the troposphere that agrees well with the distribution predicted by climate models  and with measured surface warming. Add this paper to the list which show the limitations in satellite temperature data.

 

Atmospheric changes through 2012 as shown by iteratively homogenized radiosonde temperature and wind data (IUKv2)

 

OPEN ACCESS

Steven C Sherwood and Nidhi Nishant

2015 Environ. Res. Lett. 10 054007

doi:10.1088/1748-9326/10/5/054007

 

http://iopscience.iop.org/1748-9326/10/5/054007/article

 

Warming is largest in the tropical troposphere as expected (see paper for caption)

 

Tropospheric warming (radiosonde - red symbols) is a little stronger than surface warming (HADCRUT - blue line) in the tropics and similar outside the tropics.

[nflwxman]

GISS for April came in at 75 - a little warmer than I projected a couple of weeks ago based on CFS2. The relatively cool CFS2 value for April was balanced by relatively warm SST.

 

2013    61   53   65   50   57   57   54   60   64   58   73   60     59 

2014    67   43   72   73   77   64   52   76   79   76   61   73     68

2015    76   80   85   75  **** **** **** **** ****   **** **** ****    ****

Year  Jan  Feb  Mar  Apr 

interestingly enough, it appears as if 2014 and the beginning of 2015 was revised upwards.

[ORH_wxman]

interestingly enough, it appears as if 2014 and the beginning of 2015 was revised upwards.

 

 

They did a lot of adjustments this update...they cooled a lot of the 2000s years, and even years like 2011-2013 were all cooled.

[nflwxman]

They did a lot of adjustments this update...they cooled a lot of the 2000s years, and even years like 2011-2013 were all cooled.

Nothing big though.  It seems like the largest annual adjustment was 2013 at 0.02C.

[ORH_wxman]

Nothing big though.  It seems like the largest annual adjustment was 2013 at 0.02C.

 

It was a pretty uniform drop though which is a bit unusual. GISS typically has a lot of random adjustments, but most of the years from 2001-2013 were adjusted colder. It looks like 2010 was adjusted up 0.01, I think that was the only one that went positive before you reach 2014.

 

At any rate, just another example of how a few hundreths doesn't really mean anything on these datasets.

[StudentOfClimatology]

This recent paper (open source) finds that radiosonde data show warming of the troposphere that agrees well with the distribution predicted by climate models and with measured surface warming. Add this paper to the list which show the limitations in satellite temperature data.

Atmospheric changes through 2012 as shown by iteratively homogenized radiosonde temperature and wind data (IUKv2)

OPEN ACCESS

Steven C Sherwood and Nidhi Nishant

2015 Environ. Res. Lett. 10 054007

doi:10.1088/1748-9326/10/5/054007

http://iopscience.iop.org/1748-9326/10/5/054007/article

Warming is largest in the tropical troposphere as expected (see paper for caption)

sherwoodfig1.jpg

Tropospheric warming (radiosonde - red symbols) is a little stronger than surface warming (HADCRUT - blue line) in the tropics and similar outside the tropics.

sherwood2.jpg

It's generally agreed within the RS community that the error potential in the radiosonde datasets is larger than that of the satellite data. It also takes three times as long to homogenize and spatially interpolate the data. We did some basic sonde integration back in February..it was a living nightmare.

When it comes to this sort of research, I don't know why they're used at all, to be honest. If you're not going to trust the satellite data, there's no reason to trust the sondes.

[LakeEffectKing]

It was a pretty uniform drop though which is a bit unusual. GISS typically has a lot of random adjustments, but most of the years from 2001-2013 were adjusted colder. It looks like 2010 was adjusted up 0.01, I think that was the only one that went positive before you reach 2014.

 

At any rate, just another example of how a few hundreths doesn't really mean anything on these datasets.

.....unless there are adjustments before....and after the current "few hundreths" adjustments....that end up being additive....

 

[nflwxman]

.....unless there are adjustments before....and after the current "few hundreths" adjustments....that end up being additive....

Here we go again...

[chubbs]

It's generally agreed within the RS community that the error potential in the radiosonde datasets is larger than that of the satellite data. It also takes three times as long to homogenize and spatially interpolate the data. We did some basic sonde integration back in February..it was a living nightmare.

When it comes to this sort of research, I don't know why they're used at all, to be honest. If you're not going to trust the satellite data, there's no reason to trust the sondes.

 

On the contrary additional datasets are always valuable particularly when the measurements are independent.  This paper and the recent UWash paper show that the satellite temperature trend data is too imprecise to be of much value in evaluating climate models forecasts in the middle and upper troposphere, and not surprisingly, the atmosphere is behaving as expected.

[chubbs]

NOAA updated estimates of GHG from 2013 to 2014 at the site below. Consistent with recent trends, man-made forcing increased by 1.6% last year from 478 to 481 ppm CO2 equivalent - while CO2 alone was just below 400 ppm. Most of the forcing increase was due to CO2,  which increased at a typical rate. The most notable GHG was methane which had an unusually large increase last year. Time will tell if this is just a short-term fluctuation.

 

http://www.esrl.noaa.gov/gmd/aggi/aggi.html

[skierinvermont]

On the contrary additional datasets are always valuable particularly when the measurements are independent.  This paper and the recent UWash paper show that the satellite temperature trend data is too imprecise to be of much value in evaluating climate models forecasts in the middle and upper troposphere, and not surprisingly, the atmosphere is behaving as expected.

 

SOC doesn't need peer-reviewed papers to tell him what to think.. he's genius AND a graduate student!

[StudentOfClimatology]

On the contrary additional datasets are always valuable particularly when the measurements are independent. This paper and the recent UWash paper show that the satellite temperature trend data is too imprecise to be of much value in evaluating climate models forecasts in the middle and upper troposphere, and not surprisingly, the atmosphere is behaving as expected.

Using a wildly imprecise dataset to claim another dataset is imprecise? Those radiosonde aggregations have potential errors on the order of 0.15C/decade or more. They're also a pain in the arse to homogenize and spatially interpolate. The sonde networks are dinosaurs in this age.

Either way, the UAH upgrade has yet to be formally reviewed. I'll wait for the verification paper(s) on v6.0 before making any judgements.

[skierinvermont]

Using a wildly imprecise dataset to claim another dataset is imprecise? Those radiosonde aggregations have potential errors on the order of 0.15C/decade or more. They're also a pain in the arse to homogenize and spatially interpolate. The sonde networks are dinosaurs in this age.

Either way, the UAH upgrade has yet to be formally reviewed. I'll wait for the verification paper(s) on v6.0 before making any judgements.

 

This is false information.

 

First, the UWash paper provides criticism of the UAH method itself, independent of radiosonde data.

 

Second, the error bars on radiosonde data are on the order of +/-.04C/decade, not .15C/decade. You are making up numbers unsupported by the literature. If you are going to make up numbers on your own, at least have the decency to state the fact that these are YOUR numbers, NOT the numbers found in the literature.

 

The error bars for radiosonde data can be seen on this chart below. This is from the recent Sherwood paper. Sherwood is probably the most published author in this field.

 

[StudentOfClimatology]

You're not analyzing the radiosonde data correctly.

Aside from the fact that it's analyzing an old version of UAH, the UWash paper uses a four-cycle overfill to obtain globally aggregated temperature measurements with height. That's basically pleading for a time-of-day relativity bias to the satellite data. You can't even adjust for that.

Give this a read: http://www.atmos-meas-tech.net/8/463/2015/amt-8-463-2015.html

Radiosondes provide one of the primary sources of upper troposphere and stratosphere temperature data for numerical weather prediction, the assessment of long-term trends in atmospheric temperature, study of atmospheric processes and provide intercomparison data for other temperature sensors, e.g. satellites. When intercomparing different temperature profiles it is important to include the effect of temporal mismatch between the measurements. To help quantify this uncertainty the atmospheric temperature variation through the day needs to be assessed, so that a correction and uncertainty for time difference can be calculated. Temperature data from an intensive radiosonde campaign, at Manus Island in Papua New Guinea, were analysed to calculate the hourly rate of change in temperature at different altitudes and provide recommendations and correction factors for different launch schedules. Using these results, three additional longer term data sets were analysed (Lindenberg 1999 to 2008; Lindenberg 2009 to 2012; and Southern Great Plains 2006 to 2012) to assess the diurnal variability of temperature as a function of altitude, time of day and season of the year. This provides the appropriate estimation of temperature differences for given temporal separation and the uncertainty associated with them. A general observation was that 10 or more repeat measurements would be required to get a standard error of the mean of less than 0.1 K per hour of temporal mismatch.

[LakeEffectKing]

Here we go again...

Not quite...just a factual comment on what Will stated...a few hundredths here, a few hundreds there, and there....when done over time, it does become "more meaningful"....am I wrong??

[skierinvermont]

You're not analyzing the radiosonde data correctly.

Aside from the fact that it's analyzing an old version of UAH, the UWash paper uses a four-cycle overfill to obtain globally aggregated temperature measurements with height. That's basically pleading for a time-of-day relativity bias to the satellite data. You can't even adjust for that.

Give this a read: http://www.atmos-meas-tech.net/8/463/2015/amt-8-463-2015.html

 

 

I'm not the one "analyzing the radiosonde data." The Sherwood paper is. They find error bars of +/- .04C/decade. This is the peer-reviewed estimate. If you want to make up your own, that's fine, but make sure for the sake of objectivity that you clearly state this is your own unpublished estimate (which has no credibility as far as I'm concerned).

 

Go ahead and publish your results for that, and your criticism of the UWash paper. Until I see a peer-reviewed criticism of the UWash paper, I'll remain doubtful especially coming from someone with as little credibility as you. 

[skierinvermont]

Not quite...just a factual comment on what Will stated...a few hundredths here, a few hundreds there, and there....when done over time, it does become "more meaningful"....am I wrong??

 

No, the major revision that is showing has a peer reviewed explanation for why it was necessary.

 

The revisions Will was pointing out actually cooled the present. Not sure if you caught that.

[StudentOfClimatology]

I'm not the one "analyzing the radiosonde data." The Sherwood paper is. They find error bars of +/- .04C/decade. This is the peer-reviewed estimate. If you want to make up your own, that's fine, but make sure for the sake of objectivity that you clearly state this is your own unpublished estimate (which has no credibility as far as I'm concerned).

You either seriously need to work on your reading comprehension, or have not read the paper. The Sherwood et al 2015 sonde aggregation does little in the way of homogenization and performs no extrapolated correction for diurnal bias because it's not a validation study..there are no quantitative error bars given. The error analysis is limited to the measurement intervals only.

I'm sick of explaining what you should be able to figure out with 5 minutes of reading. It's honestly annoying.

[StudentOfClimatology]

So, now you disagree with the conclusions drawn by Mears et al 2012? Just a few weeks ago you were arguing in favor of their stated limitations regarding time-extrapolated homogenization.

http://onlinelibrary.wiley.com/doi/10.1029/2012JD017710/full

Abstract

[1] Multidecadal-scale changes in atmospheric temperature have been measured by both radiosondes and the satellite-borne microwave sounding unit (MSU). Both measurement systems exhibit substantial time varying biases that need to removed to the extent possible from the raw data before they can be used to assess climate trends. A number of methods have been developed for each measurement system, leading to the creation of several homogenized data sets. In this work, we evaluate the agreement between MSU and homogenized radiosonde data sets on multiyear (predominantly 5-year) time scales and find that MSU data sets are often more similar to each other than to radiosonde data sets and vice versa. Furthermore, on these times scales the differences between MSU data sets are often not larger than published internal uncertainty estimates for the RSS product alone and therefore may not be statistically significant when the internal uncertainty in each data set is taken into account. Given the data limitations it is concluded that using radiosondes to validate multidecadal-scale trends in MSU data, or vice versa, or trying to use such metrics alone to pick a ‘winner’ is an ill-conditioned approach and has limited utility without one or more of additional independent measurements, or methodological, or physical analysis.

You need to actually read through the literature you're referring to, before posting it.

[skierinvermont]

You either seriously need to work on your reading comprehension, or have not read the paper. The Sherwood et al 2015 sonde aggregation does little in the way of homogenization and performs no extrapolated correction for diurnal bias because it's not a validation study..there are no quantitative error bars given. The error analysis is limited to the measurement intervals only.

I'm sick of explaining what you should be able to figure out with 5 minutes of reading. It's honestly annoying.

 

You are not reading correctly. The graph very clearly provides error bars for trend estimates. The Sherwood paper says the trend for 300hpa from 1959-2015 is +.25C/decade +/-.04C/decade. 

 

It's funny how you managed to throw all those big words in there to try and sound smart, but end up being wrong.

 

The Sherwood paper is quite clear, the trend at 300hpa is +.25C/decade +/-.04C/decade.

 

This is in contrast with satellite derived estimates for TLT which have published error bars and/or discrepancy between research group of +/-.1C/decade.