Climate continues to change.

Status
Not open for further replies.


Here's the data; where's the warming?

http://www.woodfortrees.org/data/uah/from:1988/normalise


Code:
#Data from UAH National Space Science and Technology Center
#http://vortex.nsstc.uah.edu/public/msu/t2lt/
#----------------------------------------------------
#
#File: tltglhmam_5.5
#
#Time series (uah) from 1978.92 to 2014.67
#Selected data from 1988
#Normalised to -0.5..0.5
1988	0.0607394
1988.08	-0.15757
1988.17	0.0184859
1988.25	-0.123239
1988.33	-0.0757042
1988.42	-0.0536972
1988.5	0.0202465
1988.58	-0.00880282
1988.67	0.0528169
1988.75	-0.0836268
1988.83	-0.245599
1988.92	-0.275528
1989	-0.46831
1989.08	-0.341549
1989.17	-0.354754
1989.25	-0.271127
1989.33	-0.351232
1989.42	-0.323944
1989.5	-0.234155
1989.58	-0.202465
1989.67	-0.139965
1989.75	-0.152289
1989.83	-0.237676
1989.92	-0.100352
1990	-0.183979
1990.08	-0.301056
1990.17	-0.0889085
1990.25	-0.168134
1990.33	-0.0713028
1990.42	-0.0536972
1990.5	-0.107394
1990.58	-0.127641
1990.67	-0.196303
1990.75	-0.0748239
1990.83	0.100352
1990.92	0.0316901
1991	-0.0651408
1991.08	-0.0352113
1991.17	0.0721831
1991.25	-0.0598592
1991.33	-0.0105634
1991.42	0.158451
1991.5	0.0211268
1991.58	0.0413732
1991.67	-0.133803
1991.75	-0.229754
1991.83	-0.269366
1991.92	-0.267606
1992	-0.203345
1992.08	-0.290493
1992.17	-0.18838
1992.25	-0.330986
1992.33	-0.319542
1992.42	-0.305458
1992.5	-0.440141
1992.58	-0.492077
1992.67	-0.5
1992.75	-0.307218
1992.83	-0.31162
1992.92	-0.353873
1993	-0.385563
1993.08	-0.34419
1993.17	-0.483275
1993.25	-0.368838
1993.33	-0.31162
1993.42	-0.18838
1993.5	-0.183979
1993.58	-0.303697
1993.67	-0.450704
1993.75	-0.248239
1993.83	-0.234155
1993.92	-0.0862676
1994	-0.169894
1994.08	-0.297535
1994.17	-0.293134
1994.25	-0.220951
1994.33	-0.208627
1994.42	-0.0889085
1994.5	-0.111796
1994.58	-0.198944
1994.67	-0.140845
1994.75	-0.301937
1994.83	-0.056338
1994.92	-0.056338
1995	-0.0633803
1995.08	-0.106514
1995.17	-0.193662
1995.25	0.00792254
1995.33	-0.0994718
1995.42	-0.0255282
1995.5	-0.0607394
1995.58	0.0977113
1995.67	0.00528169
1995.75	-0.0985915
1995.83	-0.0457746
1995.92	-0.267606
1996	-0.253521
1996.08	-0.0889085
1996.17	-0.110915
1996.25	-0.221831
1996.33	-0.255282
1996.42	-0.245599
1996.5	-0.158451
1996.58	-0.0457746
1996.67	-0.0633803
1996.75	-0.119718
1996.83	-0.0748239
1996.92	-0.153169
1997	-0.238556
1997.08	-0.168134
1997.17	-0.205986
1997.25	-0.356514
1997.33	-0.204225
1997.42	-0.138204
1997.5	-0.0695423
1997.58	-0.0607394
1997.67	-0.113556
1997.75	-0.0713028
1997.83	-0.00880282
1997.92	0.111796
1998	0.330986
1998.08	0.490317
1998.17	0.286972
1998.25	0.5
1998.33	0.411972
1998.42	0.362676
1998.5	0.304577
1998.58	0.308099
1998.67	0.206866
1998.75	0.173415
1998.83	-0.0105634
1998.92	0.084507
1999	-0.0660211
1999.08	0.0316901
1999.17	-0.178697
1999.25	-0.104754
1999.33	-0.141725
1999.42	-0.243838
1999.5	-0.148768
1999.58	-0.194542
1999.67	-0.0783451
1999.75	-0.131162
1999.83	-0.158451
1999.92	-0.159331
2000	-0.383803
2000.08	-0.169014
2000.17	-0.138204
2000.25	-0.0536972
2000.33	-0.0440141
2000.42	-0.0897887
2000.5	-0.159331
2000.58	-0.18838
2000.67	-0.0871479
2000.75	-0.108275
2000.83	-0.0897887
2000.92	-0.12588
2001	-0.131162
2001.08	-0.0466549
2001.17	-0.056338
2001.25	0.0739437
2001.33	0.0809859
2001.42	-0.0950704
2001.5	-0.0290493
2001.58	0.136444
2001.67	-0.00792254
2001.75	0.0757042
2001.83	0.0677817
2001.92	0.0642606
2002	0.0880282
2002.08	0.0748239
2002.17	0.125
2002.25	0.12588
2002.33	0.185739
2002.42	0.18838
2002.5	0.109155
2002.58	0.0748239
2002.67	0.131162
2002.75	0.0272887
2002.83	0.137324
2002.92	0.0466549
2003	0.169894
2003.08	0.068662
2003.17	-0.00440141
2003.25	0.0501761
2003.33	0.112676
2003.42	-0.0580986
2003.5	0.0158451
2003.58	0.0193662
2003.67	0.084507
2003.75	0.176056
2003.83	0.107394
2003.92	0.240317
2004	0.0792254
2004.08	0.100352
2004.17	0.199824
2004.25	0.0519366
2004.33	-0.0387324
2004.42	-0.0660211
2004.5	-0.245599
2004.58	-0.127641
2004.67	0.0237676
2004.75	0.133803
2004.83	0.0580986
2004.92	-0.000880282
2005	0.179577
2005.08	0.0792254
2005.17	0.115317
2005.25	0.241197
2005.33	0.0994718
2005.42	0.116197
2005.5	0.162852
2005.58	0.0457746
2005.67	0.205986
2005.75	0.231514
2005.83	0.197183
2005.92	0.0818662
2006	0.0889085
2006.08	0.12412
2006.17	0.096831
2006.25	0.0466549
2006.33	-0.103873
2006.42	0.0334507
2006.5	0.0528169
2006.58	0.0994718
2006.67	0.136444
2006.75	0.193662
2006.83	0.0924296
2006.92	0.111796
2007	0.285211
2007.08	0.142606
2007.17	0.173415
2007.25	0.096831
2007.33	0.0959507
2007.42	0.0889085
2007.5	0.102993
2007.58	0.105634
2007.67	0.0616197
2007.75	0.0774648
2007.83	0.00352113
2007.92	-0.0880282
2008	-0.300176
2008.08	-0.261444
2008.17	-0.103873
2008.25	-0.0739437
2008.33	-0.235915
2008.42	-0.175176
2008.5	-0.0748239
2008.58	-0.0994718
2008.67	0.0633803
2008.75	0.0536972
2008.83	0.0871479
2008.92	0.0290493
2009	0.0739437
2009.08	0.0889085
2009.17	0.0369718
2009.25	0.00264085
2009.33	-0.0167254
2009.42	-0.068662
2009.5	0.242958
2009.58	0.102113
2009.67	0.28081
2009.75	0.161092
2009.83	0.273768
2009.92	0.133803
2010	0.428697
2010.08	0.394366
2010.17	0.425176
2010.25	0.283451
2010.33	0.3125
2010.42	0.248239
2010.5	0.21919
2010.58	0.248239
2010.67	0.295775
2010.75	0.161972
2010.83	0.100352
2010.92	0.0413732
2011	-0.0633803
2011.08	-0.0853873
2011.17	-0.140845
2011.25	-0.0096831
2011.33	0.00616197
2011.42	0.146127
2011.5	0.21919
2011.58	0.181338
2011.67	0.172535
2011.75	-0.0184859
2011.83	-0.00880282
2011.92	-0.0246479
2012	-0.200704
2012.08	-0.201585
2012.17	-0.0378521
2012.25	0.121479
2012.33	0.0748239
2012.42	0.12412
2012.5	0.0316901
2012.58	0.100352
2012.67	0.215669
2012.75	0.210387
2012.83	0.165493
2012.92	0.0985915
2013	0.360915
2013.08	0.0713028
2013.17	0.0783451
2013.25	0.00792254
2013.33	-0.0149648
2013.42	0.154049
2013.5	0.0211268
2013.58	0.0246479
2013.67	0.176056
2013.75	0.117077
2013.83	0.0149648
2013.92	0.0757042
2014	0.125
2014.08	0.0290493
2014.17	0.0378521
2014.25	0.0792254
2014.33	0.159331
2014.42	0.162852
2014.5	0.111796
2014.58	0.0211268
#Data ends
#Number of samples: 320





 


Here's the data; where's the warming?

http://www.woodfortrees.org/data/uah/from:1988/normalise


Code:
#Data from UAH National Space Science and Technology Center
#http://vortex.nsstc.uah.edu/public/msu/t2lt/
#----------------------------------------------------
#
#File: tltglhmam_5.5
#
#Time series (uah) from 1978.92 to 2014.67
#Selected data from 1988
#Normalised to -0.5..0.5
1988	0.0607394
1988.08	-0.15757
1988.17	0.0184859
1988.25	-0.123239
1988.33	-0.0757042
1988.42	-0.0536972
1988.5	0.0202465
1988.58	-0.00880282
1988.67	0.0528169
1988.75	-0.0836268
1988.83	-0.245599
1988.92	-0.275528
1989	-0.46831
1989.08	-0.341549
1989.17	-0.354754
1989.25	-0.271127
1989.33	-0.351232
1989.42	-0.323944
1989.5	-0.234155
1989.58	-0.202465
1989.67	-0.139965
1989.75	-0.152289
1989.83	-0.237676
1989.92	-0.100352
1990	-0.183979
1990.08	-0.301056
1990.17	-0.0889085
1990.25	-0.168134
1990.33	-0.0713028
1990.42	-0.0536972
1990.5	-0.107394
1990.58	-0.127641
1990.67	-0.196303
1990.75	-0.0748239
1990.83	0.100352
1990.92	0.0316901
1991	-0.0651408
1991.08	-0.0352113
1991.17	0.0721831
1991.25	-0.0598592
1991.33	-0.0105634
1991.42	0.158451
1991.5	0.0211268
1991.58	0.0413732
1991.67	-0.133803
1991.75	-0.229754
1991.83	-0.269366
1991.92	-0.267606
1992	-0.203345
1992.08	-0.290493
1992.17	-0.18838
1992.25	-0.330986
1992.33	-0.319542
1992.42	-0.305458
1992.5	-0.440141
1992.58	-0.492077
1992.67	-0.5
1992.75	-0.307218
1992.83	-0.31162
1992.92	-0.353873
1993	-0.385563
1993.08	-0.34419
1993.17	-0.483275
1993.25	-0.368838
1993.33	-0.31162
1993.42	-0.18838
1993.5	-0.183979
1993.58	-0.303697
1993.67	-0.450704
1993.75	-0.248239
1993.83	-0.234155
1993.92	-0.0862676
1994	-0.169894
1994.08	-0.297535
1994.17	-0.293134
1994.25	-0.220951
1994.33	-0.208627
1994.42	-0.0889085
1994.5	-0.111796
1994.58	-0.198944
1994.67	-0.140845
1994.75	-0.301937
1994.83	-0.056338
1994.92	-0.056338
1995	-0.0633803
1995.08	-0.106514
1995.17	-0.193662
1995.25	0.00792254
1995.33	-0.0994718
1995.42	-0.0255282
1995.5	-0.0607394
1995.58	0.0977113
1995.67	0.00528169
1995.75	-0.0985915
1995.83	-0.0457746
1995.92	-0.267606
1996	-0.253521
1996.08	-0.0889085
1996.17	-0.110915
1996.25	-0.221831
1996.33	-0.255282
1996.42	-0.245599
1996.5	-0.158451
1996.58	-0.0457746
1996.67	-0.0633803
1996.75	-0.119718
1996.83	-0.0748239
1996.92	-0.153169
1997	-0.238556
1997.08	-0.168134
1997.17	-0.205986
1997.25	-0.356514
1997.33	-0.204225
1997.42	-0.138204
1997.5	-0.0695423
1997.58	-0.0607394
1997.67	-0.113556
1997.75	-0.0713028
1997.83	-0.00880282
1997.92	0.111796
1998	0.330986
1998.08	0.490317
1998.17	0.286972
1998.25	0.5
1998.33	0.411972
1998.42	0.362676
1998.5	0.304577
1998.58	0.308099
1998.67	0.206866
1998.75	0.173415
1998.83	-0.0105634
1998.92	0.084507
1999	-0.0660211
1999.08	0.0316901
1999.17	-0.178697
1999.25	-0.104754
1999.33	-0.141725
1999.42	-0.243838
1999.5	-0.148768
1999.58	-0.194542
1999.67	-0.0783451
1999.75	-0.131162
1999.83	-0.158451
1999.92	-0.159331
2000	-0.383803
2000.08	-0.169014
2000.17	-0.138204
2000.25	-0.0536972
2000.33	-0.0440141
2000.42	-0.0897887
2000.5	-0.159331
2000.58	-0.18838
2000.67	-0.0871479
2000.75	-0.108275
2000.83	-0.0897887
2000.92	-0.12588
2001	-0.131162
2001.08	-0.0466549
2001.17	-0.056338
2001.25	0.0739437
2001.33	0.0809859
2001.42	-0.0950704
2001.5	-0.0290493
2001.58	0.136444
2001.67	-0.00792254
2001.75	0.0757042
2001.83	0.0677817
2001.92	0.0642606
2002	0.0880282
2002.08	0.0748239
2002.17	0.125
2002.25	0.12588
2002.33	0.185739
2002.42	0.18838
2002.5	0.109155
2002.58	0.0748239
2002.67	0.131162
2002.75	0.0272887
2002.83	0.137324
2002.92	0.0466549
2003	0.169894
2003.08	0.068662
2003.17	-0.00440141
2003.25	0.0501761
2003.33	0.112676
2003.42	-0.0580986
2003.5	0.0158451
2003.58	0.0193662
2003.67	0.084507
2003.75	0.176056
2003.83	0.107394
2003.92	0.240317
2004	0.0792254
2004.08	0.100352
2004.17	0.199824
2004.25	0.0519366
2004.33	-0.0387324
2004.42	-0.0660211
2004.5	-0.245599
2004.58	-0.127641
2004.67	0.0237676
2004.75	0.133803
2004.83	0.0580986
2004.92	-0.000880282
2005	0.179577
2005.08	0.0792254
2005.17	0.115317
2005.25	0.241197
2005.33	0.0994718
2005.42	0.116197
2005.5	0.162852
2005.58	0.0457746
2005.67	0.205986
2005.75	0.231514
2005.83	0.197183
2005.92	0.0818662
2006	0.0889085
2006.08	0.12412
2006.17	0.096831
2006.25	0.0466549
2006.33	-0.103873
2006.42	0.0334507
2006.5	0.0528169
2006.58	0.0994718
2006.67	0.136444
2006.75	0.193662
2006.83	0.0924296
2006.92	0.111796
2007	0.285211
2007.08	0.142606
2007.17	0.173415
2007.25	0.096831
2007.33	0.0959507
2007.42	0.0889085
2007.5	0.102993
2007.58	0.105634
2007.67	0.0616197
2007.75	0.0774648
2007.83	0.00352113
2007.92	-0.0880282
2008	-0.300176
2008.08	-0.261444
2008.17	-0.103873
2008.25	-0.0739437
2008.33	-0.235915
2008.42	-0.175176
2008.5	-0.0748239
2008.58	-0.0994718
2008.67	0.0633803
2008.75	0.0536972
2008.83	0.0871479
2008.92	0.0290493
2009	0.0739437
2009.08	0.0889085
2009.17	0.0369718
2009.25	0.00264085
2009.33	-0.0167254
2009.42	-0.068662
2009.5	0.242958
2009.58	0.102113
2009.67	0.28081
2009.75	0.161092
2009.83	0.273768
2009.92	0.133803
2010	0.428697
2010.08	0.394366
2010.17	0.425176
2010.25	0.283451
2010.33	0.3125
2010.42	0.248239
2010.5	0.21919
2010.58	0.248239
2010.67	0.295775
2010.75	0.161972
2010.83	0.100352
2010.92	0.0413732
2011	-0.0633803
2011.08	-0.0853873
2011.17	-0.140845
2011.25	-0.0096831
2011.33	0.00616197
2011.42	0.146127
2011.5	0.21919
2011.58	0.181338
2011.67	0.172535
2011.75	-0.0184859
2011.83	-0.00880282
2011.92	-0.0246479
2012	-0.200704
2012.08	-0.201585
2012.17	-0.0378521
2012.25	0.121479
2012.33	0.0748239
2012.42	0.12412
2012.5	0.0316901
2012.58	0.100352
2012.67	0.215669
2012.75	0.210387
2012.83	0.165493
2012.92	0.0985915
2013	0.360915
2013.08	0.0713028
2013.17	0.0783451
2013.25	0.00792254
2013.33	-0.0149648
2013.42	0.154049
2013.5	0.0211268
2013.58	0.0246479
2013.67	0.176056
2013.75	0.117077
2013.83	0.0149648
2013.92	0.0757042
2014	0.125
2014.08	0.0290493
2014.17	0.0378521
2014.25	0.0792254
2014.33	0.159331
2014.42	0.162852
2014.5	0.111796
2014.58	0.0211268
#Data ends
#Number of samples: 320





I see you had to "normalize" the data to hide the incline. Every one of those figures is far above what should be normal.
 
I see you had to "normalize" the data to hide the incline. Every one of those figures is far above what should be normal.

If ever there was proof that you have absolutely no idea what you're talking about, this is it.


 
Everyone is missing the big point

It doesn't matter if the climate is changing. What matters is, who or what is responsible and what do do about it. Should we punish everyone with higher energy prices because "maybe" humans are responsible? If the change is due to natural volcanic pollution and sun spots nothing can be done. So, all that is left is to punish the human race with high evergy prices and dubious "Green Energy". We are our own worst enemy.
 
Last edited:
It doesn't matter if the climate is changing. What matters is, who or what is responsible and what do do about it. Should we punish everyone with higher energy prices because "maybe" humans are responsible? If the change is due to natural volcanic pollution and sun spots nothing can be done. So, all that is left is to punish the human race with high evergy prices and dubious "Green Energy". We are our own worst enemy.
We are being punished with a degraded and shrinking environment. That's bad enough.

The problem will eventually correct itself, when the population dwindles to the point where it can't cause global effects anymore.
 


Since we've now had eighteen (18) years of no significant warming, extreme weather events are now attributable to the global warming (that we haven't had).

Got that?

It's a new and very special branch of logic.


So according to your statement there have been no record high temperatures in the past 18 years .

If you really believe in it I have a matched pair of toll bridges I would like to sell you .
 
We are being punished with a degraded and shrinking environment. That's bad enough.

The problem will eventually correct itself, when the population dwindles to the point where it can't cause global effects anymore.

Are we really being punished? Obesity is more of a threat than hunger. We have a surplus of food. People live longer than ever. Where is the population dwindling? Most suffering is caused political and religious domination of those unable to defend themselves. How can there be starving in Africa, with some of the most fertile land in the world? The climate is not the problem.
 
Are we really being punished? Obesity is more of a threat than hunger. We have a surplus of food. People live longer than ever. Where is the population dwindling? Most suffering is caused political and religious domination of those unable to defend themselves. How can there be starving in Africa, with some of the most fertile land in the world? The climate is not the problem.
Africa? That's the continent most susceptible to damage from climate change.

https://www.e-education.psu.edu/drupal6/files/geog030/climate/m4_ciesin.jpg
 
From a true believer

"If the religion of environmentalism is correct & the world is really as old as it says...the amount of time that weather has even been measured is NOT EVEN A BLIP IN TIME. But when you are your own god, you can imagine that you really do influence the weather & can "fix" it. The worship of the created rather than the Creator. Were we to actually all practice the Good Stewardship that God entrusted us to perform over this beautiful earth He GAVE TO US...it would be better. Tell that to the evil DICTATORS & TYRANTS. Not even bleeding heart liberal elites of the environmentalist religion want to give up the standard of living we all enjoy.....they just want YOU to GIVE UP YOURS. You go first."
 
Climate change forcing fish stocks north: study

Bob Weber, The Canadian Press
Published Friday, October 10, 2014 12:56PM EDT
Last Updated Friday, October 10, 2014 2:28PM EDT

A study has produced the strongest evidence yet that climate change is forcing hundreds of valuable fish species toward the poles.

The paper, published in the ICES Journal of Marine Science on Friday, concludes that Canadian and Arctic waters may end up with more species and greater abundance.

But fisheries in the tropics, where people depend more heavily on seafood, may become hollowed out.

"The variety of species available for fisheries in the tropics will decrease," said co-author William Cheung of the University of British Columbia. "It may be good news for the Arctic -- our projections are that the Arctic will be a hot spot for species invasion. There will be more variety of fish species available for the Arctic region."

Previous studies have suggested that warming ocean waters will affect the distribution of fish stocks. Cheung's paper gives the clearest and broadest picture yet of those effects.

Using a combination of three different mathematical models and the latest climate data, he forecast the probable distribution of 802 commercially exploited fish species. Those species include commonly harvested fish such as cod, tuna, herring and halibut.

On average, Cheung found the fish are slowly moving toward the South and North poles at a rate of between 15 and 26 kilometres a decade. The effect is more pronounced in the Arctic, where warming is happening the quickest.

He checked his conclusions by using the same method to model the past movements of fish. When Cheung compared the modelling results with actual fisheries data, the two matched up.

"We found that, overall, our projections are consistent with the observations in the last 30 years."

Cheung warns that the finding means challenges as well as opportunity. How the invasive species will interact with existing species and ecosystems is unknown. Their movements are also likely to create problems for international fisheries management, as stocks shift across different jurisdictions.

Read more: http://www.ctvnews.ca/sci-tech/clim...sh-stocks-north-study-1.2048783#ixzz3G2oYkJlh
 
Mathmatical model based on assumptions about FUTURE climate change PREDICTS that in the FUTURE fish will migrate.

Not "study' of actual, observed statistically relevent climate change in the present tense.

Boats are pretty good at following the fish.

You want to worry about the fishies then I suggest to worry about overfishing which is a much bigger problem.

I realize your religion doesn't allow blasphemous scientific studies...

... consider that when co2 levels go up so will the levels of ocean algae. Guess what's on the bottom rung of food chain for the fishies?
 
Last edited:
Mathmatical model based on assumptions about FUTURE climate change PREDICTS that in the FUTURE fish will migrate.

Not "study' of actual, observed statistically relevent climate change in the present tense.

Boats are pretty good at following the fish.

You want to worry about the fishies then I suggest to worry about overfishing which is a much bigger problem.

I realize your religion doesn't allow blasphemous scientific studies...

... consider that when co2 levels go up so will the levels of ocean algae. Guess what's on the bottom rung of food chain for the fishies?
There's plenty of algae in the Gulf of Mexico, just off the Mississippi delta. They call it the Dead Zone.

Learn your topic before you post next time, OK?
 
There's plenty of algae in the Gulf of Mexico, just off the Mississippi delta. They call it the Dead Zone.

Learn your topic before you post next time, OK?

That would mean that he would have to think .
 


The great cat catastrophe

by "Bishop Hill" (Andrew W. Montford)
http://bishophill.squarespace.com/blog/2014/10/14/the-great-cat-catastrophe.html



It has been observed many times in the past that there are many aspects of the global warming debate that reasonable people should be able to agree on: carbon dioxide is a greenhouse gas, the temperature has gone up a bit, that sort of thing.

I think we can now add to the list the idea that Naomi Oreskes and Erik Conway are a few cherries short of the full Bakewell, right down there with Peter Wadhams as representatives of the full-on-bonkers wing of the green scientivist academy. I say this after reading a review of their latest opus by Martin Lewis, a confirmed global warming believer. Here's an excerpt:


As the book claims to outline the “not only predictable but predicted” (p. 1) consequences of a fossil-fuel-based energy system, I will begin by examining the author’s actual foretelling. As it turns out, most of it is hyperbolic, going far behind even the most extreme warnings provided by climatologists. Consider, for example, Oreskes and Conway’s most grimly amusing nightmare: the mass die-off of dogs and cats in the early 2020s. Lest one conclude that I am exaggerating here, a direct quotation should suffice:

ut in 2023, the infamous “year of perpetual summer,” lived up to its name, taking 500,000 lives worldwide and costing nearly $500 billion in losses due to fires, crop failures, and the deaths of livestock and companion animals. The loss of pet cats and dogs garnered particular attention among wealthy Westerners, but what was anomalous in 2023 soon became the new normal (p. 8-9).

Within a mere nine years, global warning could produce temperature spikes so elevated as to generate massive cat mortality? The idea is so ludicrous that I hardly know where to begin. Domestic cats, as anyone who has spent any time around them surely understands, are heat-seeking creatures; native to the Middle East and North Africa, they thrive in the world’s hottest environments. Yet Oreskes and Conway expect us to believe that within a few decades “normal” temperatures across much of “the West” will exceed the tolerance threshold of the house cat? ...


The great cat catastrophe of 2023 is by no means the only instance of risible fear-mongering found in the book. It would seem that there is no limit to the horrors that global warming will spawn, including a resurgence of bubonic plague (p. 30) and the creation of “viral and retroviral agents never before seen” (p. 25). Even typhus is predicted to make a major comeback owing to “explosive increases in insect populations.”


The review is magnificent. Do read the whole thing ( http://www.geocurrents.info/physica...al-deluded-vision-naomi-oreskes-erik-m-conway )

 
Status
Not open for further replies.
Back
Top