Wednesday, December 24, 2014

Extinction is forever

Here's a study I missed when it first came out two weeks ago:

Monastersky, R. 2014. Biodiversity: Life—a status report. Nature 516:159-161.

This report compiled all known data on species status.  The results are sobering.  Thousands of species are at risk of extinction, including:
41% of all known amphibians
26% of all known mammals
13% of all known birds
Note: Those are the species currently at risk.  Today.  Not predicted to be at risk in the future.  Forty-one percent of all amphibians, 26% of all mammals, and 13% of all birds are already at risk of extinction today.  And those are the best known groups. The rest—insects, plants, fungi, fish, etc?  Unknown, as not enough species in those groups have been evaluated to even guess at the percentage currently at risk of extinction.

Saturday, December 20, 2014

The non-existant pause in global temperatures

Regular readers of this blog will know that I am skeptical of claims that global warming in atmospheric temperatures have paused since 1998, having written several posts questioning the existence of such a pause.  In this edition, I'll run down the main evidence that, in my opinion, show that the pause is a figment of the denialsphere's imagination.

Friday, December 12, 2014

What is the deal with RSS?

It's nice when a topic for a new post lands in your lap.  Or, in this case, in the comments of one of your old posts.  An anonymous commentator made several statements concerning RSS that warrant a longer explanation than is possible in a reply on the comment section.  This is going to be a long, stats-heavy post.  You've been warned.

Tuesday, December 9, 2014

Where 2014 would rank if global temperature reverted to the 1979-2013 trend

Given that 2014 is nearly over (~3 weeks to go), we're going to be hearing even more about the possibility that 2014 will be the warmest year in the instrumental record.  I myself made the pile higher and deeper with my last post.  That raised a question in my mind: Where should global temperature be in 2014 according to the warming trend since 1979 (the first full year of the satellite record)?

Monday, December 1, 2014

Hottest years-to-date on record

Back in August, I wrote a post that found the January-June period was the third hottest on record (based on the Cowtan-Way data set which corrects the coverage bias in HadCRUT4 data).  This post will revise and update that earlier article, incorporating GISS, UAH, NCDC, HadCRUT4, and Cowtan-Way data sets.  I am not including RSS, as that data set has shown false cooling since 2000.

Wednesday, November 26, 2014

Tom Luongo's multiple lies about climate change

An old friend posted an "article" by Tom Luongo, a former chemist (B.S. from the University of Florida) who now writes the Resolute Wealth Newsletter, on Facebook.  Unfortunately, that article is chock full of lies about climate science.  Since Facebook comments aren't the best forum for debunking Gish Gallops, I'm taking the liberty of debunking them here.

[Update: Since Luongo got most of his claims from John Casey, I've written something about his brand of science here.]

Wednesday, November 5, 2014

Musings after the US election

For anyone paying attention, the US election yesterday was a disaster for Democrats.  That party lost control of the US Senate (likely 53-47) and took a drubbing in US House races (242-174) and US governors' (24-8) races.  The end result as far as science, environmental policy, and climate change is that science deniers now control key oversight committees on science, as many news organizations have noted.  The likely result for at least the next two years is unending investigations, waste-of-time hearings, and other obstacles erected to make environmental regulators' working lives a living hell.  Forget about the US ratifying any environmental treaties, much less anything having to do with climate change.  On the state level, I expect rollbacks of renewable energy mandates at the least, along with attempts to repeal other environmental regulations and meaningless resolutions attempting to nullify various federal laws and/or appropriate federal lands for state and private use.

All of that, though, is in the future.  The more interesting question right now is why Democrats lost in such a spectacular fashion.  I'm sure there will be much ink spilled and numbers thrown about figuring that out but the long and short of it is this: Just like in the 2010 midterms, the Republican base voted and the Democratic base did not.  In my voting precinct, only around 30% of eligible voters actually voted yesterday.  Let that number sink in for a minute.  Thirty percent.  Seventy percent of eligible voters stayed home and let thirty percent decide the fate of this country.  That's not atypical, either.  In fact, the poll workers I spoke with thought it was a pretty good turnout for a midterm election.

We've all read stories, especially in the more liberal sectors of the Internet, about how demographic trends are working against the Republican party, about how their base is getting older and less diverse, etc.  But that base votes.  Every.  Single.  Election.  Meanwhile, the Democratic base only seems to vote in presidential elections and ignore midterm elections.  Until Democrats wake up and realize that every single election is important, not just presidential elections, we'll continue to see results like we saw yesterday.  The repercussions of yesterday's elections on science, environmental, and climate policies will be felt for years to come.  I just hope that someday, either a) Democrats wake up and vote every single time or b) Republicans wake up and realize that science is true whether or not they believe it.  I'm not holding my breath.

Monday, October 27, 2014

Trend versus cycles in global temperature data

One of the most useful features about models, both statistical and physical, is that you can examine different aspects of the system you are analyzing separate from all other other influences.  Want to see if El Niño/Southern Oscillation could be driving the trend in global temperatures?  Construct a realistic model, then isolate the ENSO term.  Want to see if a combination of natural cycles explains the trend?  Isolate the terms for the natural cycles from those for greenhouse gases, and examine the results.

Monday, October 20, 2014

Global warming: Carbon dioxide vs. Natural cycles

The recent paper by Johnstone and Mantua (2014) has certainly made the rounds in conservative circles.  It's popped up several times on my Facebook feed as various friends and acquaintances share articles about it.  Unfortunately, most of those articles get it wrong, usually twisting Johnstone and Mantua's findings to imply that 80% of ALL global warming is natural.  As I explained in my last post, that is a blatant misinterpretation of their paper, which only applies to the northeastern Pacific and coastal regions of the US Pacific Northwest.  Globally, natural cycles do not explain the trend in global temperatures.  How can I say that?  Do the statistics.

Monday, October 13, 2014

Temperature trends and natural variation in the Pacific Northwest

A recent study by Johnstone and Mantua (2014) found a high correlation (r = 0.78) between sea surface temperatures since 1900 and changes in atmospheric pressure over the Northeastern Pacific, claiming that 80% of the variance in sea surface temperatures in the Northeastern Pacific was explained by changes in the North Pacific high.

Friday, October 3, 2014

Seeing how well predictions for September Arctic sea ice did in 2014

In August, I published a post listing predictions of what the average September sea ice extent would be in 2014.  Since September 2014 is now past, we can go back and see how those predictions panned out.  First, here are the predictions again:

Month
Model
R2
Ice extent in 2014 (millions of km2)
Predicted Sept. ice extent (millions of km2)
Graph
June
-13.5300 + 1.6913x
0.7522
11.09
5.23
July
-4.80933 + 1.18618x
0.8796
8.17
4.88
August
-1.69389 + 1.12965x
0.9674
6.13
5.23

Monday, September 22, 2014

Trend since 1998—significant??

I had a question sent to me about the trend since 1998.  As many of you know, my last post included an analysis which showed that the linear regression trend since 1998 was statistically significant.

Trends versus start year.  Error bars are the 95% confidence intervals.
My questioner asked if I had accounted for autocorrelation in my analysis.  The short answer is "No, I did not."  The reason?  According to my analysis, it wasn't necessary.

Here are my methods and R code.

#Get coverage-corrected HadCRUT4 data and rename the first two columns
CW<-read.table("http://www-users.york.ac.uk/~kdc3/papers/coverage2013/had4_krig_annual_v2_0_0.txt", header=F)
names(CW)[1]<-"Year"
names(CW)[2]<-"Temp"

#Analysis for autocorrelation—I check manually as well but so far the auto.arima function has performed admirably.
library(forecast)
auto.arima(resid(lm(Temp~Year, data=CW, subset=Year>=1998)), ic=c("bic"))

The surprising result?
Series: resid(lm(Temp ~ Year, data = CW, subset = Year >= 1998))
ARIMA(0,0,0) with zero mean    

sigma^2 estimated as 0.005996:  log likelihood=18.23
AIC=-34.46   AICc=-34.18   BIC=-33.69
 I was expecting something on the order of ARIMA(1,0,1), which is the autocorrelation model for the monthly averages.  Taking the yearly average rather than the monthly average effectively removed autocorrelation from the temperature data, allowing the use of a white-noise regression model.

trend.98<-lm(Temp~Year, data=CW, subset=Year>=1998)
summary(trend.98)
Call:
lm(formula = Temp ~ Year, data = CW, subset = Year >= 1998)

Residuals:
     Min       1Q           Median        3Q          Max
-0.14007  -0.05058   0.01590    0.05696    0.11085

Coefficients:
                    Estimate       Std. Error    t value    Pr(>|t|) 
(Intercept)   -19.405126   9.003395    -2.155     0.0490 *
Year             0.009922      0.004489     2.210     0.0443 *
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.08278 on 14 degrees of freedom
Multiple R-squared: 0.2587,    Adjusted R-squared: 0.2057
F-statistic: 4.885 on 1 and 14 DF,  p-value: 0.04425
The other surprise?  That the trend since 1998 was significant even with a white-noise model.  Sixteen data points is not normally enough to reach statistical significance unless a trend is very strong.

Temperature trend since 1998

Sunday, September 21, 2014

The "no warming" claim rises from the dead yet again.

Like a movie vampire, this one keeps coming back no matter how many stakes are driven through its heart.  I've covered this one (here, here, and here).  Bluntly: There is absolutely no evidence that global warming has stopped.  For global warming to stop, the Earth's energy balance must be either zero or negative.  The most recent estimates for the energy imbalance are generally between +0.5 W/m2 and +1.0 W/m2.  The only way the Earth is not going to warm while it is gaining energy is if the laws of thermodynamics magically do not apply.  If the Earth is gaining energy, some part of it, somewhere, must be getting warmer.  The heat must go into either melting ice, warming the oceans, warming the land, or warming the atmosphere (or some combination thereof).

Tuesday, September 16, 2014

WUWT and how NOT to test the relationship between CO2 and temperature

WUWT published a piece by Danle Wolfe which purports to measure the correlation between CO2 and global temperature.  As you can probably predict, Wolfe's conclusion is that there is no relationship.
"Focusing on the most recent hiatus below, both visually and in a 1st order linear regression analysis there clearly is effectively zero correlation between CO2 levels and global mean temperature."
 Unfortunately for Wolfe, all he's produced is a fine example of mathturbation as well as an example of forming a conclusion first then warping the evidence to fit.

Thursday, September 11, 2014

James Taylor versus relative humidity and specific humidity

It appears that the relative humidity and specific humidity continues to trip some people up.  Yes, I'm thinking of the screed James Taylor wrote on Forbes.com on Aug. 20.  In his article, Taylor trumpets two "facts".  First, that relative humidity has declined and second, that specific humidity isn't rising as fast as global climate models predict.  Since climate models assume that relative humidity has stayed constant, Taylor then claims that models are overestimating global warming.  Unfortunately for Taylor, his "facts" don't check out.

Monday, September 8, 2014

R code for my Seasonal Trends graph

I had a request for the code I used to generate the graphs in my Seasonal Trends post.


While it looks complex, the R code for it is very simple IF you have the data ready.    I'm assuming that you already have the temperature dataset you want as an R object (I have several datasets in an object I simply call "monthly": GISS, Berkeley Earth, Cowtan-Way, HadCRUT4, UAH, and RSS, along with the year/decimal month Time, Year, and numeric Month).  The code I used to generate the graph is as follows:
#Create separate datasets for each season

monthly.79<-subset(monthly, Time>=1978.92 & Time<2013.91)
DJF<-subset(monthly.79, Month=="12" | Month =="1" | Month=="2")
DJF$Year_2 <- numeric (length (DJF$Year))
for (i in 1:length (DJF$Year) ) {
        if ( DJF$Month [i] == 12) {
                DJF$Year_2[i] <-   DJF$Year [i] + 1
        }
        else {
                DJF$Year_2[i] <-   DJF$Year [i]
        }
}
MAM<-subset(monthly.79, Month=="3" | Month =="4" | Month=="5")
JJA<-subset(monthly.79, Month=="6" | Month =="7" | Month=="8")
SON<-subset(monthly.79, Month=="9" | Month=="10" | Month=="11")

#Calculate the seasonal average for each year

DJF<-aggregate(DJF$BEST, by=list(DJF$Year_2), FUN=mean)
MAM<-aggregate(MAM$BEST, by=list(MAM$Year), FUN=mean)
JJA<-aggregate(JJA$BEST, by=list(JJA$Year), FUN=mean)
SON<-aggregate(SON$BEST, by=list(SON$Year), FUN=mean)

#Check for autoregression

library(forecast) #for the auto.arima function

auto.arima(resid(lm(x~Group.1, data=DJF)), ic=c("bic"))

auto.arima(resid(lm(x~Group.1, data=MAM)), ic=c("bic"))

auto.arima(resid(lm(x~Group.1, data=JJA)), ic=c("bic"))

auto.arima(resid(lm(x~Group.1, data=SON)), ic=c("bic"))

 #Construct the plot

plot(x~Group.1, data=DJF, type="l", col="blue", xlab="Year", ylab="Temperature anomaly (ºC)", main="Seasonal Climate Trends", ylim=c(-0.1, 0.8))
points(x~Group.1, data=MAM, type="l", col="green")
points(x~Group.1, data=JJA, type="l", col="red")
points(x~Group.1, data=SON, type="l", col="orange")

#Add the trend lines

abline(lm(x~Group.1, data=DJF), col="blue", lwd=2)
abline(lm(x~Group.1, data=MAM), col="green", lwd=2)
abline(lm(x~Group.1, data=JJA), col="red", lwd=2)
abline(lm(x~Group.1, data=SON), col="orange", lwd=2)

legend(1979, 0.8, c("DJF", "MAM", "JJA", "SON"), col=c("blue", "green", "red", "orange"), lwd=2)
#Get the slopes

summary(lm(x~Group.1, data=DJF)
summary(lm(x~Group.1, data=MAM)
summary(lm(x~Group.1, data=JJA)
summary(lm(x~Group.1, data=SON)
 That's all there was to it.  I just repeated this code, modifying only the period of the initial subset to create the second graph (Monthly.2002<-subset(monthly, Time>=2001.92 & Time<2013.91) and the related seasonal subsets.  To the person who requested my code: Hope this helps.

Monday, September 1, 2014

One hundred years ago today...

...the last passenger pigeon, a female named Martha, died in the Cincinnati Zoo.  A species that once had an estimated population size of 3 billion was destroyed in roughly 50 years by a combination of habitat loss and overhunting.  The story of that extinction is being told in numerous articles on this centenary (i.e. in Nature, Audubon Magazine, National Geographic) and at museums like the Smithsonian Institute which tell the story far better than I could here.  The Audubon Magazine article, in particular, is well worth reading as it details the history of the extinction.

Sunday, August 31, 2014

The Daily Fail: David Rose's newest cherry-pick.

David Rose, who is no stranger to cherry-picking climate data and then weaving artful tales based on those cherry-picks, is back with yet another example of his perversity.  This time, he's trumpeting a 2-year increase in Arctic sea ice as measured on a single day: August 25, 2012 vs. August 25, 2014, claiming a 43% increase based on those two very specific days.  This is misleading for multiple reasons, one of which he himself admits in small type under that large flashy graphic at the top of his article:
"These reveal that – while the long-term trend still shows a decline – last Monday, August 25, the area of the Arctic Ocean with at least 15 per cent ice cover was 5.62 million square kilometres." (emphasis added).
So, just what does that long-term trend show? This:

Thursday, August 28, 2014

So what if CO2 was 2400 ppmv in the Mesozoic

This is a response to those who try to claim that global warming won't be so bad.  The gist of their argument is that since life thrived in the Mesozoic when CO2 was ~2400 ppmv and temperatures 8ºC warmer, climate change today isn't anything to be worried about.  Unfortunately, this argument ignores some very basic facts about biology and physics.  Here is some of what they're ignoring.

1) First, thanks to those individuals for accidentally confirming the relationship between CO2 and global temperature, as well as modern estimates of climate sensitivity.  At modern solar radiation levels and with climate sensitivity at 0.809 W/m2, the equilibrium climate model predicts that with CO2 at 2400 ppmv, global temperatures would rise by 9.3ºC above pre-industrial temperatures.  Factor in a weaker sun back in the Mesozoic and you get the 8ºC rise experienced from 2400 ppmv CO2 back then (Royer 2006).  Got to love it when those who dismiss science score an own goal and don't even realize it.

2) The species we have living on this Earth are not the same as the species that existed during the Mesozoic.  Then, the land was dominated by various species of dinosaurs, the air by pelicosaurs, and the seas by ithyosaurs, mosasaurs, and plesiosaurs.  The dominant plants for the Triassic and Jurassic was various species of gymnosperms while the Cretaceous saw the rise of the angiosperms.  But that is largely irrelevant for today's species.  Most of today's species evolved during the Pleistocene, when global average temperatures were usually 4.5ºC colder than today.  Species are highly sensitive to changes in the normal temperature regime to which they have evolved.  Even a shift of a few tenths of a degree C is enough to make species migrate toward the poles and change their phenology.  A temperature increase of 8ºC above today's levels would be catastrophic to today's species, many of which are already at the upper limits of their normal temperature range.

3) While the total amount of warming is important, the rate at which that warming occurs is even more important.  A slow rate would allow species to evolve adaptations to the change in temperatures.  Unfortunately, the current rate of temperature change is far faster than the  rate of evolutionary adaptation to changes in temperature.  Quintero and Wiens (2013) found that vertebrate species can adapt to at most 1ºC of temperature change per million years.  The current rate of temperature change over the past 30 years is 1.6ºC per century, over 10,000x faster.

I'm sure there's more that I've left out or just didn't think of while writing this.  The bottom line is that those who try to argue that increases in CO2 is no big deal are simply ignoring most of what we know about ecology, physiology, and evolution.

Tuesday, August 26, 2014

Roy Spencer and 95% of models are wrong

Claims that 95% of climate models are wrong have been making the rounds since Spencer published it on his blog in February.  Here's the graph he created:


Take a good look.  Not only does his graph appear to show that most models are higher than both HadCRUT4 and UAH satellite temperature record but it shows that HadCRUT4 is higher than UAH as well.  That is...strange, to say the least.  IPCC AR5 (aka CMIP5) models were calibrated against 20th century temperatures (1900-1999) and have only been actually predicting temperatures since 2000.  However, Spencer's graph appears to show that their output is higher than the observed temperature records for 1983-1999—during the calibration period.  That makes no sense at all.

Thursday, August 21, 2014

More predictions of September Arctic sea ice extent

I published a prediction of Arctic sea ice extent on July 1 that was based on September sea ice extent from 1979 to 2013.  That model yielded a prediction that the average extent for September 2014 would be 4.135 million square kilometers.  However, that model does not take into consideration any other information we have on Arctic sea ice, such as the ice extent in previous months of the year.  It just gives the general trend of sea ice in September from year to year.  You cannot use it to predict ice extent based on current ice extent or conditions.

Wednesday, August 20, 2014

Where does 2014 rank in the hottest years on record so far?

While we're closing in on September, several of the global temperature datasets are still stuck on June and haven't released the July data yet.  Just for fun, let's compare how the first six months of 2014 stack up to previous years.  To answer the question in the title, I  averaged the first six months of each year in the Cowtan-Way global temperature dataset.

Sunday, August 10, 2014

IPCC models versus actual trends

This is an extension of my previous post comparing IPCC models and actual temperature data.  I had a request to directly compare the observed rates of temperature rise with the predicted rise from the average of the AR5 models.  First, my methods:  I averaged all 81 IPCC AR5 8.5 models.  I then calculated the rate of change for the average of the models as well as Berkeley Earth's Land + Ocean dataset, the new Cowtan-Way coverage-corrected version of HadCRUT4, and GISS.  All rates were calculated after compensating for autocorrelation.  With that out of the way, here's the rates of temperature rise for the last 30 full years (1984-2013) in three surface datasets that cover the entire globe versus the average of all 81 IPCC AR5 8.5 scenarios:

Monday, July 21, 2014

Risbey et al. 2014

It seems the canard about how IPCC models are inaccurate just won't go away.  I've covered it before on this blog.  The newest incarnation of that canard revolves around a new paper by Risbey et al. (2014).  It seems that many just don't understand what Risbey et al. did and they definitely don't understand the results of that paper.

Sunday, July 20, 2014

Seasonal trends by hemisphere

A reader raised a good question about my last post.  One of the confirmed predictions of climate change is that winters will warm faster than summers, yet my analysis showed that December-February warmed the least.  The question was why that would be.  The answer is simple: I used global temperature data.  December-February may be winter in the Northern Hemisphere but it is summer in the Southern.  The seasons largely cancel out.  The reason we see faster warming in the June-August  (Northern Hemisphere summer) versus December-February (Southern Hemisphere summer) is due to the position of land masses.  There's a greater proportion of ocean in the Southern Hemisphere and the ocean doesn't change temperature very readily compared to landmasses whereas the Northern Hemisphere has more landmass and consequently a larger response to seasonal changes in insolation.

Saturday, July 19, 2014

Seasonal trends

It is almost comical how people will grasp at any straw they can come up with to claim that global warming isn't happening.  The most recent bit of hilarity?  A claim that the winter trend since 2002 is cooling, therefore we're in global cooling, not global warming.  Let's check that one out to see just how ridiculous it is.

Friday, July 11, 2014

What will summers be in AD 2100?

While I'm working on a longer post, here is an interesting interactive graphic from Climate Central.  Just type in the city you are interested in and see what the summers will be for that city in AD 2100. It shows which US city (or world city) currently experiences average summer temperatures as hot as those predicted for selected US cities and gives you an idea of how far north the climate bands will have shifted over the next 86 years.



Average summer highs in my current hometown are predicted to warm up by nearly 6.5ºC from the current average high of 29.4ºC to a predicted average high of 35.9ºC.  How much will your closest city warm?

Thursday, July 3, 2014

NewsMax, Ambler, and BS about Antarctic sea ice

NewsMax.com printed a poorly writen story about Antarctic sea ice intended to sow confusion amongst its readers which was unfortunately shared on my Facebook timeline by an acquaintance.  However, the article is even worse than being merely poorly written.  The "author," Sandy Fitzgerald, extensively plagiarizes a blog post by Harold Ambler while leaving out nearly everything Ambler wrote about why Antarctic sea ice is increasing.  Fitzgerald manages to make it sound like a new record extent in Antarctic sea ice somehow contradicts global warming.  Ambler's original is a far more nuanced argument.

Tuesday, July 1, 2014

How low will it go?

This is the time of year all eyes start turning toward the Arctic, specifically how rapidly and/or much the multiyear sea ice will melt this particular year.  Here is the average sea ice extent for September since 1979:


I've added a loess regression line along with 95% confidence intervals to highlight the trend.  Despite last year's rebound from the 2012 low, the overall trend is decidedly down, with less multiyear ice remaining as time goes by.

Now on to my prediction of what the ice will do this year.  What I did was simply to extrapolate based on the loess regression, which yielded a prediction of 4.135 million km2.  I also fitted a polynomial regression to the data, which produced a prediction of 4.085 million km2.  Both are well above the record low in 2012 (3.58 million km2), showing how anomalous the 2012 low was.  If the loess curve holds, I wouldn't expect the trend to fall below the 2012 low until 2018.

So, what is your prediction of what the September low will hold for Arctic sea ice?

Monday, June 30, 2014

Is it a requirement...

for GOP politicians to be completely ignorant of science?  You have Phil Broun, a former physician who called evolution, embryology, and the Big Bang "lies straight from the pit of Hell."  It's enough to make one wonder how he reacted to bacteria who have evolved antibiotic resistance and/or cared for any potentially pregnant patients, given that an understanding of embryology is rather integral to caring for such patients.  Then there's Ralph Hall, who claimed that climate scientists are essentially committing fraud for grant money, Dana Rohrabacher once claiming that dinosaur farts caused climate cycles in the past, and Phil Gingrey's claims that women's bodies can resist pregnancy arising from rape because a woman's body shuts down ovulation if she is stressed out.  Gingrey is a former OB/GYN.  Who believes that a woman's body can magically shut down its reproductive system if subjected to the stress of being raped....  My irony meter just broke.  Now get ready to add one more science illiterate to the GOP circus.

Lenar Whitney, a Republican state representative from Louisiana, claims that climate change is nothing more than a massive fraud.  Why?  First, because, according to Whitney, the planet "has done nothing but get colder each year since [An Inconvenient Truth's] release."  An Inconvenient Truth was released in 2006.  Here's what the planet has done since then:


An ARMA(1,0) regression reveals that global temperature has risen slightly since 2006:
+0.084 ± 0.322ºC per decade, p = 0.6086
Now, it's not a statistically significant rise.  Nowhere near.  In fact, statistically, the global temperature rise since 2006 is not any different from zero—yet.  It takes at least 17 years of data to detect climate trends.  Whitney is only considering 8 years.  But even 8 years of data shows that the planet is not getting colder, as Whitney so ignorantly claimed.

Second, Whitney cites the increase in sea ice around Antarctica.  Never mind that the decline in Arctic sea ice has been greater Antarctica's gain (-1.458 million km2 versus +0.924 million km2 as measured by annual averages, -2.764 million km2 vs +0.715 million km2 as measured by the total Arctic loss in September from 1979 to 2013 versus the total Antarctic gain in March from 1979 to 2014).  Never mind that Antarctic land ice has been decreasing by an average of -71 billion metric tons of land ice per year for the past 20 years (Shepherd et al. 2012).  Never mind that Antarctic sea ice is growing in part because of the melt water flowing off the continent diluting the top layer of the Southern Ocean and making it fresher (Bintanja et al. 2013), which makes the surface of the ocean easier to freeze.  Never mind anything scientists have discovered about either the Arctic or Antarctic.  All that matters to Whitney is that somewhere, somehow, sea ice is increasing and in her simplistic view of the world, that means the world cannot be warming.

Quite frankly, the ability of Republican politicians to show rank scientific ignorance (and be proud of that ignorance) should be a national embarrassment.  At best, it allows other nations to laugh at "our" ignorance.  At worst, government policies that impact current and future generations are being based, not on reality, but on ignorance and wishful, magical thinking.  And that is a situation that no American should desire.

Wednesday, April 9, 2014

A prediction of global surface temperatures if an El Niño forms this year.

There are increasing evidence that we'll have our first El Niño since 2010 sometime within the next year.  Just for fun, I thought it would be interesting to try to predict what the annual global average temperature would be if an El Niño developed as expected.

I took Berkeley Earth land + ocean annual temperature data starting in 1970 and categorized each year as El Niño, La Niña, or neutral using average MEI data for each year.  Any year with an MEI average  ≥ +0.5 was classed as an El Niño year.  La Niña years had MEI values ≤ -0.5, whereas neutral years were between -0.5 and +0.5.  I then performed a separate linear regression on each category.


Monday, March 31, 2014

The danger of anecdotal evidence

Anecdotal evidence is one of the most common forms of evidence.  We encounter it frequently in life, from those stories about the relative who tried some new cure to reports of children developing autism after receiving vaccines to stories on Fox News about how some snowstorm somehow disproves global warming.  However common, anecdotal evidence is the worst and most misleading form of evidence.


Tuesday, March 25, 2014

The myth that Mars has more CO2 than Earth

One would hope that a patently false claim would just die rather than being continuously resurrected.  Such is the case with the "Mars has more CO2 than Earth and is colder than Earth so CO2 can't be causing global warming" claim.  This one is usually based on the fact that Mars has an atmosphere that is 95.32% CO2 by volume whereas Earth's atmosphere is only 0.04% CO2.  Unfortunately, all that claim reveals is that whoever is making it didn't get very far in a science class.


Wednesday, March 12, 2014

Another denier trying to baffle with BS

On Huffington Post, I was challenged by a denier going by the screen name "Shuman the Human".  You can read the exchange here.  It's incomplete as for some reason my attempts to reply to his comment keep getting zapped.  Update: Looks like HuffPost zapped his last comment as well.

Monday, March 10, 2014

Yet another invasive insect.

I've written before about the impact of the Emerald Ash Borer on forests in southwestern Ohio.  My introduction to the pest I'm profiling this time came last summer when I found my tomato, pumpkin, cucumber, acorn squash, watermelon, and summer squash vines infested with a strange brown bug with an oddly shaped abdomen: Halyomorpha halys (Stål), the brown mamorated stink bug.

Picture from http://www.stopbmsb.org/stopBMSB/assets/Image/BMSB-on-bark-istock350w.png

Friday, March 7, 2014

New Berkeley Earth temperature dataset vs existing datasets

The Berkeley Earth team released a new temperature analysis that includes both land and ocean surface temperatures.  They used their existing land data and merged it with HadSST data (note: not HadSST3 as I originally wrote), using kriging to interpolate temperatures where data did not directly exist.  In this, their methodology is similar to the recent Cowtan and Way (2013) paper, however, Cowtan and Way used HadSST3 for their ocean data.  I've compared their new results over the past 30 years (Jan 1984-Dec 2013) to GISS, HadCRUT4, NCDC, UAH, and Cowtan and Way's results, first standardizing all temperature anomalies to the 1981-2010 baseline.  Why the past 30 years?  Thirty years is generally considered the standard time period for measuring climate.  All trends mentioned in this article are calculated using linear regression corrected for autocorrelation.

Friday, February 28, 2014

Monckton, RSS, and no warming since September 1996

While browsing a climate change article on Huffington Post, I noticed a global warming denier using a Watts Up With That post by Lord Monckton as "evidence" that global temperatures haven't changed since September 1996.  In it, Monckton uses least squares regression to show that satellite data from RSS is flat (trend: -0.0001394ºC per year) between September 1996 and January 2014.

Sunday, February 23, 2014

Charles Krauthammer and settled science

An op-ed in my local paper caught my eye yesterday.  By Charles Krauthammer, it's largely a fact-free repetition of talking points trying to dispute whether or not climate change is settled science.  While my hometown paper has the editorial paywalled, it's available at the Washington Post.  Some of his points are utterly unrelated, some are badly outdated, and some are out-right lies.

Wednesday, February 19, 2014

A Republican Meteorologist on climate change

This one is too good not to share.  It's the response of Paul Douglas, a meteorologist who happens to be a registered Republican, to a question on why more climate scientists do not enter the public debate (full response found here).  His take-home line?
"To the heart of your question, why don’t more climate scientists enter into the public debate? Because the debate is over. It’s the moral and scientific equivalent of debating gravity."
As readers who peruse the archives of this blog know, I've spent quite a bit of time detailing why the scientific debate is over.  However, I have one quibble with Douglas' response: He fails to distinguish between the scientific debate and the public debate.  The question concerned the public debate—and the public debate is far from over.  Given the scientific illiteracy of many American voters (26% of whom don't even know that the Earth revolves around the sun), it's been easy for fossil fuel interests to spread misinformation.  And it's going to take scientists who understand both the science and how to communicate that science to set the public debate straight so we can solve the knotty issue of how to take the carbon out of our economy.  While debating climate change may be the moral and scientific equivalent of debating gravity, we need scientists willing to enter the fray so that Americans can understand why it's the equivalent of debating gravity.

Tuesday, February 18, 2014

California's drought

California's drought has been in the news quite a bit lately, complete with dire predictions for agriculture and food prices across the US.  The one question I had after reading several articles is "Just how bad is it?"  The answer: Really bad.

Monday, February 10, 2014

Answering a Gish Galloping critic, part 2

In case you missed it, the original comments I'm answering are found at the end of my bibliography of hockey sticks found here.  Part 1 of my response is here.  Now on to the second comment.

Answering a Gish Galloping critic, Part 1

Apparently my post listing 36 publications that all show a "hockey-stick" has attracted some attention, including from a self-proclaimed paleogeneticist who claims that he's an expert in climate models.  I'm putting my response here, as responding to the Gish Gallop of BS he wrote would take far too much space in the comments section of that post.  If he doesn't like it?  Too bad.

Sunday, February 9, 2014

2013 climate review

2013 was notable in several ways, from the record warmth in Australia to the polar vortex that gripped the Eastern US in November and December due to a weakened Arctic polar jet stream and record drought in the US state of California, along with numerous extreme weather events around the globe.

Tuesday, February 4, 2014

Keystone cops

After digging through the recent State Department Environmental Impact Statement for the Keystone XL Pipeline, I am quite disappointed.  While right-wingers are cheering the fact that the State Department found that building Keystone XL won't have an impact on greenhouse gas emissions, that is the wrong conclusion.  In reality, the State Department found that the tar sand oil flowing through Keystone XL will generate the equivalent of 147 to 168 million metric tons of CO2 emission per year (Executive Summary, page 15).  That is a sizable contribution to greenhouse gas emission from one single project.  It's between 57% and 65% of the average total CO2 emissions from all the world's volcanoes combined (average combined volcanic emissions per year: 260 million metric tons, see Gerlach 2011) and enough to raise atmospheric CO2 levels by 0.021 ppmv per year.  And the State Department somehow thinks that isn't going to impact greenhouse gas emissions?

So, how could the State Department conclude that Keystone XL won't have an impact on greenhouse gas emissions?  Simple.  They assumed that the Canadian tar sands will get developed regardless of whether or not the pipeline is built, then compared expected emissions from transporting that oil via train versus transporting it via Keystone XL (ES page 28).  They didn't even consider the possibility that the tar sands won't be developed without the pipeline.  And that, IMO, is a mistake worthy of the Keystone Cops.

Update

 The Carbon Tracker Initiative released a report today that questioned the State Department's assumption that rail and pipeline emissions would be the same.  They found that oil production could be 525,000 barrels per day higher with Keystone than without.  The reason for the difference?  Carbon Tracker found that transporting oil via the pipeline would be cheaper than via rail and calculated how that price difference would influence tar sands development.  The additional oil would result in up to 5.3 billion metric tons of CO2 emissions per year through AD 2050, far higher than the State Department's estimate that didn't account for the difference in transportation cost.  That amount of emissions is equivalent to what the entire US produces each year.  If the Carbon Tracker analysis is verified, then it appears that the State Department lowballed the impacts of Keystone XL.

Thursday, January 30, 2014

The problem with "All of the above"

President Obama in his State of the Union address praised his "all of the above" energy strategy.  What he left out is that "all of the above" is a recipe for disastrous climate change.

The 12-month running mean for Mauna Loa CO2 levels is currently at 396.18 ppmv.


With a climate sensitivity of 0.809ºC/W/m2 (3ºC per doubling CO2), that translates to warming of
ΔT = λΔF = λ*[5.35 W/m2 * ln(C/C0)]
ΔT = 0.809ºC/W/m2 * [5.35 W/m2 * ln(396.18 ppmv/280 ppmv)]
ΔT = 1.50ºC above pre-industrial levels
with just the CO2 levels of today.  However, that climate sensitivity value is just the 100-year value.  At longer time spans (i.e. 1,000 years), sensitivity is actually closer 1.618ºC/W/m2.  That means that at today's CO2 levels, we're already committed to 3ºC of warming over the next millennium.  The key phrase?  "At today's CO2 levels."  And that's the main problem I have with how President Obama is approaching the whole issue.

The "all of the above" approach sounds good—and partially insulates the president from right-wing attacks—but it does little to stabilize CO2 levels.  We're still pumping out fossil fuels, still burning them for energy, still dumping the waste CO2 into the atmosphere.  CO2 levels have been climbing at an average +1.484 ppmv per year since 1958 and that rate has been accelerating by an average of +0.01196 ppmv per year2.  If we continue accumulating CO2 at the same rate, CO2 levels by AD 2100 will be 670.81 ppmv and we'll be locked into 3.78ºC of warming by AD 2200 and 7.56ºC of warming over the next millennium.  Considering the observed consequences of just the 0.8ºC of warming we've already experienced and the projected consequences of future warming (i.e. Sherwood and Huber. 2010; Chapter 14 of the IPCC AR5 report; Levermann et al. 2013), to say nothing of methylmercury emissions, landuse changes, etc associated with fossil fuels, any energy plan that does not phase out fossil fuels (yes, ALL fossil fuels) and quickly is simply irresponsible to future generations.  That is the main issue I have with the president's approach—it does little to phase out fossil fuels.  While I realize that nothing will get through the current do-nothing Congress, we need to at least start a serious conversation on phasing out fossil fuels by whatever means necessary.  And the longer we wait to have that national conversation and phase out fossil fuels, the more expensive it will be.  The science on climate change is clear.  The Earth is warming and technology is the reason.  Now we need to ignore the squawks of the flat-earth science deniers and act on the science.

So, what could we do to phase out fossil fuels?  The policy I favor is to put a price on carbon emissions via a tax-and-rebate system on fossil fuels but I know that isn't everyone's preference.

Tuesday, January 28, 2014

The last time the Earth had a 15-year cooling trend of any kind...

I was asked by a friend to identify the last time the Earth experienced a 15-year cooling trend.  The way I answered this was to use a rolling regression on GISS surface data (R code at the bottom).  Turns out that the last time was before I was born.  The period from February 1958-January 1973 (cooling of -0.00188ºC per decade) was the last 15-year cooling trend in GISS surface data.  Every 15-year period since has shown a warming trend of some magnitude—and yes, that even includes trends starting in 1998.
 
Figure 1.  Graph of temperature trends over each 15-year period.  Each point represents the trend over the preceding 15-year period.

Now as to the last time the Earth showed a statistically significant 15-year cooling trend, well, that's a bit tougher to answer.  The code I'm using cannot account for autocorrelation, which means that it is biased toward showing significant time series trends when in reality the trends are not significant.  The original code also didn't compensate for multiple comparisons.  Even using that extremely lenient standard of significance, however, the last time the Earth experienced a statistically significant cooling trend was from August 1957 to July 1972 (trend: -0.00424ºC per year, p-value = 0.0425).  So at the very least, it's been 41 years since the Earth last had a 15-year cooling trend of any sort—and 41.5 years since the Earth had a statistically significant 15-year cooling trend.

Update
 I realized that I made a mistake in not compensating for multiple comparisons.  Since I was computing every possible 15-year trend, 5% of the trends would be statistically significant by chance alone.  With 1,416 computed trends, that means around 71 of them would be statistically significant by chance.  To compensate for multiple comparisons, I used the p.adjust function in R to use the Benjamini & Yekutieli (2001) method for compensating for fake positives.  When I did that, the last statistically significant cooling trend was pushed back in time to the 15 years between February 1943 and January 1958 (trend: -0.06929ºC per decade, p = 0.04).  Again, this is without autocorrelation, so it's very likely that even that cooling was not actually statistically significant.  But it's been at least 56 years since the last statistically significant 15-year cooling trend.  And my guess is that if I could incorporate autocorrelation in to my code, it would be far longer than that.  The current warming really started in 1910, so the safe bet would be 1910 or before.

If any of my readers know how to incorporate ARMA into a rolling regression in R, please leave a comment with the code and I'll update my analysis.

Thanks.

Updated R code used for this analysis
Climate=read.csv("monthly.csv", header=T)
install.packages("zoo")
library(zoo)
Climate.1880=subset(Climate, Year>=1880)
GISS=ts(Climate.1880$GISS, start=c(1880,1), frequency=12)
GISS=as.zoo(GISS)
GISS=merge(GISS=GISS, time=time(GISS))
func=function(z) {
    co=coef(summary(lm(GISS~time, data=as.data.frame(z))))
    c(Est=co[,1], SE=co[,2], t=co[,3], p=co[,4])
    }
rr=rollapply(GISS, width=180, FUN=func, by.column=FALSE, align="right")
rr$p.time.adj=p.adjust(rr$p.time, method="BY", n=length(rr$p.time))
rr
plot(rr[,2], type="l", xlab="Years", ylab="15-year trend (ºC/year)", main="15-year trends in GISS surface temperature data")
curve(0+x*0, add=T)
text(1950, 0.03, "Warming Trend", col="Red", lwd=2)
text(1950, -0.02, "Cooling Trend", col="Blue", lwd=2)

Saturday, January 25, 2014

Ignorance, blindness, and outright misinformation

A childhood acquaintance on Facebook posted a link to a CBN News article that serves as a good example of what is wrong with conservative news media.  Written by Dale Hurd, it is a mash-up of science denier canards with little in the way of actual science or evidence.

The first paragraph sets the tone, making fun of the scientists who were trapped in Antarctic ice.  Nowhere does Hurd mention HOW the scientists were trapped: A storm packed sea ice into the bay their ship was in.  Now this can happen at any time of the year but it doesn't mean that the ice is growing.  It's summer down in Antarctica, a time when Antarctic sea ice melts from ~19 million km2 in September down to ~2-3 million km2 by March.  That leaves plenty of broken pack ice for winds to blow around, especially in the early part of the melt season such as December when the ship was trapped.  So the irony is that those scientists were trapped by MELTING sea ice, an irony completely lost on Hurd.

Hurd's claim: "Ice is not only growing in the South Pole, but in parts of the North Pole, too."

While satellite data shows that Antarctic sea ice is growing, there's reason to believe that some of that growth is not real.  Eisenman et al. (2014) showed that part of the reported growth in Antarctic sea ice is due to how the satellite data is processed rather than actual ice growth.  The most likely source of that error is a change in the type of sensor used to measure ice extent in December 1991 which made the ice appear more extensive than the previous sensor (see their figure 2).  Eisenman and his co-authors suggest subtracting 150,000 km2 from all monthly Antarctic sea ice averages after December 1991 to calibrate the data and factor out the shift due to the change in sensors.  When I do that, the trend in Antarctic sea ice changes +17,961 km2/year (± 2,427 km2/year 1σ standard error) down to +11,819 km2/year (± 2,689 km2/year 1σ standard error).  Still statistically significant but 1/3 less than the trend of the uncalibrated data.  Hurd also ignores the research that shows Antarctica lost an average of -71 billion metric tons of land ice per year for the past 20 years (Shepherd et al. 2012) and that Antarctic sea ice is growing because of the melt water flowing off the continent diluting the top layer of the Southern Ocean and making it fresher (Bintanja et al. 2013).

The only way his claim about growing ice in parts of the North Pole works is if you start your trend in September 2012, the lowest point on record, and completely ignore everything else.  Yes, Arctic sea ice "rebounded" in 2013—to the 6th lowest extent on record.  And Arctic sea ice in December 2013 was "only" the 4th lowest on record.  One years worth of random fluctuation doesn't change the long-term trend, a statistical concept that is apparently lost on Hurd.


Hurd's claim: "And the coldest arctic temperatures in decades have descended upon North America."

Just because it's cold in your backyard doesn't mean that it's colder everywhere.  Look beyond your nose:

Average surface temperature anomaly December 2013
 Notice anything?  And you can't claim that it's just GISS, either.  UAH satellite temperature anomaly maps for December 2013 shows the same pattern:



Hurd's claim: "There are signs that the Earth is entering a very unpleasant cooling period. Sunspot activity remains very low."

Sunspot activity has been falling since 1957.  If global temperatures depended solely on sunspot activity, then global temperatures would have peaked in the late 1950s/early 1960s.  As it is, there's plenty of research available that shows that solar activity has had little to no impact on global temperatures over the past 40+ years (i.e. Usoskin et al. 2005; Foster and Rahmstorf 2011; Huber and Knutti 2011).  Scientists have also examined the impact of a new Maunder Minimum (the lowest solar activity on record) and found that it will have minimal impact, with global temperatures rising by "only" 3.7ºC by AD 2100 rather than the 4ºC rise currently forecast (Feulner and Rahmstorf 2010).

Hurd's claim: 'The last time the sun was this quiet, North America and Europe suffered through a weather event from the 1600s to the 1800s known as "Little Ice Age..."'

First, Hurd might want to check his dates.  The Little Ice Age began around AD 1300 with a series of volcanic eruptions (Miller et al. 2012), NOT in the 1600s.  Second, once again, just because it's colder in your backyard does not mean that it's colder everywhere.

Average temperature anomaly (1961-1990 baseline) during the Little Ice Age.  Taken from Mann et al. 2009.
Hurd's claim: "Pedersen said climate scientists know the Earth stopped warming 15 years ago."

If this statement is true, Jens Pedersen should be ashamed of himself for spouting a blatant lie and for botching his calender to boot (1998 was 16 years ago, not 15).  I've dealt with this one extensively before.  There's no evidence that the Earth stopped warming in 1998.  In fact, as I've already shown here, you can't even conclude that the rate of temperature rise has even changed.  Most of the apparent "pause" in global warming is due to problems with the current surface data sets (HadCRUT4 doesn't include the polar regions, GISS doesn't calibrate buoy-based sea surface temperature measurements to ship-based measurements).  As Cowtan and Way (2013) showed, once you correct those problems, warming since 1998 continues at a 0.1ºC per decade clip—and the underlying rate of rise after factoring out ENSO, volcanic activity, and the solar cycle is running at 0.18ºC per decade.

Hurd's claim: '"In particular one of the issues has been why global warming has stopped during the last 15 years, and climate scientists were very frank that the climate models do not match the climate we observe," Pedersen said.'

Leaving out the fact that Pedersen repeats his lie about global warming stopping 15 years ago, the more interesting question is WHY climate models do not match observations.  I've already considered this one as well and shown that much of the mismatch is due to a combination of errors in the observations and changes in ENSO, volcanic activity, and solar activity.

Hurd's claim: "It has become a political movement, a cash cow for climate scientists and environmental groups, and a way for world leaders to control economies and people."

Ah yes, when all else fails, pull out the conspiracy theories.  Does Hurd also doubt the moon landing as well?

Hurd's claim: "Climate change skeptics have been censored and compared to Holocaust deniers and even child molesters."

 Actually, it was science deniers who compared a climate scientist to a child molester.

In short, Hurd's article is very short on actual facts and analysis, long on debunked talking points, and really just serves to keep his intended audience ignorant while thinking that they know far more than they actually do.  Which appears to be the entire point.

Tuesday, January 7, 2014

Polar vortex and global warming

I've had several people to use the current cold weather in the US as "proof" that global warming isn't happening. Unfortunately for those arguments, they're pure bunk.

First, the Eastern US and Canada do not represent the entire planet. The December 2013 global map of average temperature anomalies show this:


While the eastern US and Canada are cold, the rest of the planet is relatively warm, with only a few areas (e.g. the Middle East) colder than the 1951-1980 average.  This same pattern has been in place since November 2013 and I expect that the January 2014 map won't change much.   [As expected, it did not.  Here's the January 2014 map:]



Again, the Eastern US was far below average whereas the rest of the planet, especially much of the Arctic was far above average.]  This demonstrates the importance of looking at the global temperature data, rather than just the weather in your backyard when contemplating global warming.


Second, the current weather pattern fits a trend that has been tied to global warming.  The rapid warming in the Arctic and loss of Arctic sea ice has been tied to negative phases of  the Arctic Oscillation (i.e. Francis and Vavrus 2012, Jaiser et al. 2012, Liu et al. 2012, Tang et al. 2013).  The Arctic has warmed at a rate of 0.4345ºC per decade since 1980 whereas September sea ice has melted at a rate of -850,560 km2 per decade.


The Arctic Oscillation (AO) measures the pressure difference between the Azores High and the Icelandic Low.  When the AO is negative, the pressure difference is low.  That low pressure difference weakens and slows the polar jet stream, allowing waves to develop.  The more negative the AO, the larger those waves become, allowing cold polar air to spill southward in the troughs and drawing warm air northward along the peaks.  When the AO is positive, the polar jet stream is faster and straighter, bottling cold polar air further north.  Large waves in the jet stream have become more frequent as the ice has melted (Cohen et al. 2013, Francis and Vavrus 2015), making the wintertime pattern of a warm Arctic coupled with cold temperatures over the continents much more frequent.  What does that mean for us?  Toss in the increase in water vapor in the atmosphere (i.e. Santer et al. 2007) and we get colder, snowier winters if in a trough of the jet stream and warm, snow-less winters if in a peak.  Looking at the temperature anomalies map I posted above, it's pretty obvious where the trough in the jet stream is this winter.

One of the other effects of a warming Actic is also evident.  Because the jet stream move slower, storm systems and weather patterns move slower.  Once a particular pattern is in place, it tends to stay that way.  And the more extreme the pattern, the more likely it is to get stuck in place (see Petoukhov et al. 2013).  So buckle up, USA.  It's going to stay colder than normal for a while this winter.  While we're shivering in -20ºC temperatures, just think of Siberia and Europe enjoying their warmer-than-average winter.