Month: June 2017

Seven Days Of Growth

Seven Days Of Growth

via The Deplorable Climate Science Blog

The chicks are probably thirty times to fifty times the size they were on June 23.

June 23 pictures below. Barely larger than a twig.

via The Deplorable Climate Science Blog

June 30, 2017 at 07:46PM


-8.7° coldest 1st July in Canberra since 1939

-8.7° coldest 1st July in Canberra since 1939

via Errors in IPCC climate science

Previous was -5.9 in 1968 – have not yet tried other early Canberra sites.

via Errors in IPCC climate science

June 30, 2017 at 05:51PM

via Watts Up With That?

Guest Post By Walter Dnes

In continuation of my Temperature Anomaly projections, the following are my June projections, as well as last month’s projections for May, to see how well they fared.

Data Set Projected Actual Delta
HadCRUT4 2017/05 +0.770 +0.665 -0.105
HadCRUT4 2017/06 +0.583
GISS 2017/05 +0.93 +0.88 -0.05
GISS 2017/06 +0.81
UAHv6 2017/05 +0.264 +0.453 +0.189
UAHv6 2017/06 +0.384
RSS v3.3 2017/05 +0.402 +0.482 +0.080
RSS v3.3 2017/06 +0.486
RSS v4.0 2017/05 +0.497 +0.608 +0.111
RSS v4.0 2017/06 +0.539
NCEI 2017/05 +0.92 +0.83 -0.09
NCEI 2017/06 +0.76

The Data Sources

The latest data can be obtained from the following sources

The Latest 12 Months

The latest 12-month running mean (pseudo-year “9999”, highlighted in blue in the tables below) ranks anywhere from 2nd to 4th, depending on the data set. The June 2017 NCEP/NCAR anomaly is 0.10 to 0.12 lower than for June 2016 (global and satellite data sets). This implies that the June 2017 anomalies will be lower than the corresponding 2016 values, further cementing the decline of the 12-month running mean. This will make it even harder for 2017 to beat 2016 as the warmest year ever. June marks the 9th consecutive month with NCEP/NCAR global and satellite anomalies lower than 12 months ago.

The following table ranks the top 10 warmest years for earch surface data set, as well as a pseudo “year 9999” consisting of the latest available 12-month running mean of anomaly data, i.e. June 2016 to May 2017.

Year Anomaly Year Anomaly Year Anomaly
2016 +0.775 2016 +0.985 2016 +0.944
2015 +0.761 9999 +0.907 2015 +0.903
9999 +0.708 2015 +0.868 9999 +0.873
2014 +0.576 2014 +0.749 2014 +0.743
2010 +0.558 2010 +0.713 2010 +0.703
2005 +0.545 2005 +0.688 2013 +0.671
1998 +0.537 2007 +0.658 2005 +0.659
2013 +0.513 2013 +0.657 2009 +0.638
2003 +0.509 2009 +0.643 1998 +0.637
2009 +0.506 2012 +0.634 2012 +0.624
2006 +0.505 1998 +0.634 2006 +0.615

Similarly, for the satellite data sets…

UAH RSS v3.3 RSS v4.0
Year Anomaly Year Anomaly Year Anomaly
2016 +0.503 2016 +0.574 2016 +0.779
1998 +0.484 1998 +0.550 9999 +0.629
9999 +0.353 2010 +0.474 1998 +0.611
2010 +0.333 9999 +0.423 2010 +0.556
2015 +0.258 2015 +0.383 2015 +0.514
2002 +0.217 2005 +0.336 2002 +0.422
2005 +0.199 2003 +0.320 2014 +0.412
2003 +0.186 2002 +0.315 2005 +0.401
2014 +0.177 2014 +0.273 2013 +0.396
2007 +0.160 2007 +0.253 2003 +0.385
2013 +0.130 2001 +0.247 2007 +0.334

January-through-May of 2017 were all cooler, in all data sets, than the corresponding months in 2016. Therefore, June-through-December 2017 would have to be warmer than the corresponding months in 2016 to beat the 2016 annual values and make 2017 “the warmest year ever”. Here are the numbers…

  • HadCRUT4 2016 Jun-Dec was +0.664; 2017 needs to be +0.778
  • GISS 2016 Jun-Dec was +0.860; 2017 needs to be +0.995
  • UAH 2016 Jun-Dec was +0.384; 2017 needs to be +0.641
  • RSS 3.3 2016 Jun-Dec was +0.430; 2017 needs to be +0.688
  • RSS 4.0 2016 Jun-Dec was +0.674; 2017 needs to be +0.932
  • NCEI 2016 Jun-Dec was +0.837; 2017 needs to be +0.960

The Graphs

The graph immediately below is a plot of recent NCEP/NCAR daily anomalies, versus 1994-2013 base, similar to Nick Stokes’ web page. The second graph is a monthly version, going back to 1997. The trendlines are as follows…

  • Black – The longest line with a negative slope in the daily graph goes back to late May, 2015, as noted in the graph legend. On the monthly graph, it’s June 2015. This is slowly growing ever longer but nothing notable yet. Reaching back to 2005 or earlier would be a good start.
  • Green – This is the trendline from a local minimum in the slope around late 2004, early 2005. To even BEGIN to work on a “pause back to 2005”, the anomaly has to drop below the green line.
  • Pink – This is the trendline from a local minimum in the slope from mid-2001. Again, the anomaly needs to drop below this line to start working back to a pause to that date.
  • Red – The trendline back to a local minimum in the slope from late 1997. Again, the anomaly needs to drop below this line to start working back to a pause to that date.

NCEP/NCAR Daily Anomalies:

NCEP/NCAR Monthly Anomalies:

Miscellaneous Notes
At the time of posting, the 6 monthly data sets were available through May 2017. The NCEP/NCAR re-analysis data runs 2 days behind real-time. Therefore, real daily data from May 31st through June 28th is used, and June the 29th is assumed to have the same anomaly as the 28th. For RSS and UAH, subsets of global NCEP/NCAR data are used, to match the latitude coverage provided by the satellites.

In search of better results, I’ve tweaked the data set projection algorithm again. The monthly anomaly difference (current month minus previous month) in the corresponding NCEP/NCAR subset anomalies is multiplied by 0.5 and added to the previous month’s anomaly for that data set. This applies to all 6 data sets.

via Watts Up With That?

June 30, 2017 at 05:32PM

NASA: Global acreage burned by fire has dropped 24% since 1998

NASA: Global acreage burned by fire has dropped 24% since 1998

via Watts Up With That?

NASA detects drop in global fires

Shifting livelihoods across the tropical forest frontiers of South America, the Eurasian Steppe, and the savannas of Africa are altering landscapes and leading to a significant decline in the amount of land burned by fire, a trend that NASA’s satellites have detected from space.

The global area of land burned each year declined by 24 percent between 1998 and 2015, according to analysis of satellite data by NASA scientists and their colleagues. The largest decline was seen across savannas in Africa, and due to changing livelihoods. CREDIT Credits: Joshua Stevens/NASA’s Earth Observatory

The ongoing transition from nomadic cultures to settled lifestyles and intensifying agriculture has led to a steep drop not only in the use of fire on local lands, but in the prevalence of fire worldwide, researchers at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, and colleagues found.

Globally, the total acreage burned by fires each year declined by 24 percent between 1998 and 2015, according to a new paper in Science that analyzes NASA’s satellite data, as well as population and socioeconomic information. The decline in burned lands was largest in savannas and grasslands, where fires are essential for maintaining healthy ecosystems and habitat conservation.

Across Africa, fires typically burn an area about half the size of the continental United States every year, said Niels Andela, a research scientist at Goddard and lead author on the paper. In traditional savanna cultures with common lands, people often set fires to keep grazing lands productive and free of shrubs. As many of these communities have shifted to cultivate more permanent fields and to build more houses, roads and villages, the use of fire declines. As economic development continues, the landscape becomes more fragmented, communities often enact legislation to control fires and the burned area declines even more.

By 2015, savanna fires in Africa had declined by 270,000 square miles (700,000 square kilometers) — an area the size of Texas.

“When land use intensifies on savannas, fire is used less and less as a tool,” Andela said. “As soon as people invest in houses, crops and livestock, they don’t want these fires close by anymore. The way of doing agriculture changes, the practices change, and fire slowly disappears from the grassland landscape.”

Andela and an international team of scientists analyzed the fire data, derived from the Moderate Resolution Imaging Spectrometer (MODIS) instruments on NASA’s Terra and Aqua satellites, as well as other sources. They compared these datasets with trends in population, agriculture, livestock density and gross domestic product.

The scientists found a different pattern in the rainforests and other humid regions close to the equator. Natural fires are rare in tropical forests, but as people settle an area they often burn to clear land for cropland and pastures. After the land is first cleared, as more people move into the area and increase the investments in agriculture, they set fewer fires and the burned area declines again.

The impact of human-caused changes in savannas, grasslands and tropical forests is so large that it offsets much of the increased risk of fire caused by warming global temperatures, said Doug Morton, a research scientist at Goddard and a co-author of the study. Still, the impact of a warming and drying climate is seen at higher latitudes, where fire has increased in parts of Canada and the American west. Regions of China, India, Brazil and southern Africa also show an increase in burned area. But the expansiveness of savannas and grasslands puts the global trend in decline.

“Climate change has increased fire risk in many regions, but satellite burned area data show that human activity has effectively counterbalanced that climate risk, especially across the global tropics,” Morton said. “We’ve seen a substantial global decline over the satellite record, and the loss of fire has some really important implications for the Earth system.”

Fewer and smaller fires on the savanna favors trees and shrubs instead of open grasslands, altering habitat for the region’s iconic mammals, like elephants, rhinoceroses and lions.

“Humans are interrupting the ancient, natural cycle of burning and regrowth in these areas,” senior author Jim Randerson, a professor of Earth system science at the University of California, Irvine, said of the African savannas. “Fire had been instrumental for millennia in maintaining healthy savannas, keeping shrubs and trees at bay and eliminating dead vegetation.”

There are benefits to fewer fires as well. Regions with less fire also saw a drop in carbon monoxide emissions and an improvement in air quality during the peak of the fire season, confirming the burned area trends using data from other NASA satellites. With less fire, the vegetation in savannas is also able to build up — taking up carbon dioxide from the atmosphere, instead of releasing it into the atmosphere during fires. The 24 percent decline in burned area may have contributed about 7 percent to the ability of global vegetation to absorb the increase in carbon dioxide emissions from burning fossil fuels and land use change.

The decline in burned area from human activity raises some difficult questions, Morton said: “For fire-dependent ecosystems like savannas, the challenge is to balance the need for frequent burning to maintain habitat for large mammals and biodiversity, while reducing fire on the landscape to improve air quality and protect people’s property and agriculture.”

As these savannas and grasslands continue to develop and agriculture intensifies, however, the researchers expect the global decline in fires to continue. It’s a trend that should be incorporated into computer models that forecast climate and carbon dynamics, Morton said.

“The loss of fire from agricultural landscapes has a big impact on communities and ecosystems. Looking ahead, models that account for changes in fire activity from human management will help us understand the feedbacks from fewer fires on vegetation, air quality and climate,” he said.


For more information and to explore the data:

via Watts Up With That?

June 30, 2017 at 04:43PM