Climate change discussion

[cancel2 2022]

Climate doesn't change. Climate has no quantity. There is nothing that can change.

You're so full of shit!

 

[cancel2 2022]

so, no proof of your religion's claims? no surprise

Monshi'ite is an ignorant arsehole with absolutely no background in science. She is an humanities graduate, in other words shit for brains.

 

[Trumpet]

Monshi'ite is an ignorant arsehole with absolutely no background in science. She is an humanities graduate, in other words shit for brains.

The renowned Lord of Cretins will set us straight with his superior expertise and intellect.

 

[cancel2 2022]

The renowned Lord of Cretins will set us straight with his superior expertise and intellect.

Thank you Queen of Quims for that fascinating post.

 

[Into the Night]

The proof abounds. It's circulated in mainstream publications every day. You are beating the Denier cultists' drum for your own amusement.
Stick to swapping idiocies with the likes of Vera and Night Soil.



Haw, haw.............................haw.

Circular argument fallacy (fundamentalism).

 

[Into the Night]

You baffle me at times, what is your point?

That the point of the OP is in error.

 

[redfish]

The proof abounds. It's circulated in mainstream publications every day. You are beating the Denier cultists' drum for your own amusement.
Stick to swapping idiocies with the likes of Vera and Night Soil.



Haw, haw.............................haw.

OK, it the proof of man made climate change is so easily available, post it here. We'll wait.

 

[Into the Night]

.
Elephant seals can only breed in sea ice-free waters. About 1,000 years ago (i.e., the Medieval Warm Period) Antarctica was warm enough (“substantially warmer than present”) and the Southern Ocean waters were ice-free enough that elephant seals could breed in the Ross Sea, or near the coast of south-central Antarctica’s Victoria Land. Today this region is so much colder and the sea ice so thick that elephant seals must travel 2,400 kilometers north of where they used to breed 1,000 years ago just to find sea ice-free waters (Koch et al., 2019; Hall et al., 2006).

Elephant seals are migratory. They do not breed and feed in the same waters. The distribution of them is not fixed. There are not seal counts from the Holocene period available. Their presence does not indicate anything like a global temperature.

 

[Into the Night]

You're so full of shit!

Inversion fallacy. It is YOU that is trying attach a quantitative value to a subjective word.

 

[Into the Night]

Monshi'ite is an ignorant arsehole with absolutely no background in science. She is an humanities graduate, in other words shit for brains.

Are you sure Moonbat graduated at all?

 

[moon]

OK, it the proof of man made climate change is so easily available, post it here. We'll wait.

You're way behind the times. Check a history book.

 

[Into the Night]

OK, it the proof of man made climate change is so easily available, post it here. We'll wait.

Wait for it...the Holy Link!

 

[Into the Night]

You're way behind the times. Check a history book.

What history book? Void reference fallacy.

 

[moon]

I'm laughing at you poor Denier dumbasses.



Haw, haw................................................haw.

 

[cancel2 2022]

New Study Finds 25-45% Of The Instrumental Warming Since The 50s Due To Urbanisation

.
Why have sea surface temperatures and proxy temperature reconstructions so strongly diverged from the instrumental land record in recent decades? Because “0.36 ± 0.04 °C” of non-climatic warming from roofs, asphalt, machines, vehicles…artificially enhances the post-1950s global temperature trend.


Detection of non‐climatic biases in land surface temperature records by comparing climatic data and their model simulations

Nicola Scafetta
Climate Dynamics (2021)Cite this article


Abstract

The 0.6 °C warming observed in global temperature datasets from 1940 to 1960 to 2000–2020 can be partially due to urban heat island (UHI) and other non-climatic biases in the underlying data, although several previous studies have argued to the contrary. Here we identify land regions where such biases could be present by locally evaluating their diurnal temperature range (DTR = TMax − TMin trends between the decades 1945–1954 and 2005–2014 and between the decades 1951–1960 and 1991–2000 versus their synthetic hindcasts produced by the CMIP5 models. Vast regions of Asia (in particular Russia and China) and North America, a significant part of Europe, part of Oceania, and relatively small parts of South America (in particular Colombia and Venezuela) and Africa show DTR reductions up to 0.5–1.5 °C larger than the hindcasted ones, mostly where fast urbanization has occurred, such as in central-east China. Besides, it is found: (1) from May to October, TMax globally warmed 40% less than the hindcast; (2) in Greenland, which appears nearly free of any non-climatic contamination, TMean warmed about 50% less than the hindcast; (3) the world macro-regions with, on average, the lowest DTR reductions and with low urbanization (60S-30N:120 W–90 E and 60 S–10 N:90 E–180 E: Central and South America, Africa, and Oceania) warmed about 20–30% less than the models’ hindcast. Yet, the world macro-region with, on average, the largest DTR reductions and with high urbanization (30 N–80 N:180 W–180 E: most of North America, Europe, and Central Asia) warmed just a little bit more (5%) than the hindcast, which indicates that the models well agree only with potentially problematic temperature records. Indeed, also tree-based proxy temperature reconstructions covering the 30°N–70°N land area produce significantly less warming than the correspondent instrumentally-based temperature record since 1980. Finally, we compare land and sea surface temperature data versus their CMIP5 simulations and find that 25–45% of the 1 °C land warming from 1940–1960 to 2000–2020 could be due to non-climatic biases. By merging the sea surface temperature record (assumed to be correct) and an adjusted land temperature record based on the model prediction, the global warming during the same period is found to be 15–25% lower than reported. The corrected warming is compatible with that shown by the satellite UAH MSU v6.0 low troposphere global temperature record since 1979. Implications for climate model evaluation and future global warming estimates are briefly addressed.

Introduction

There has been considerable debate in the literature over the extent (if any) to which non-climatic biases – in particular, those due to urbanization elements such as the urban heat, aerosol emissions, and other factors—have contaminated regional, hemispheric and global temperature records, and artificially raised, or in any way altered global warming trends since the 1940s (e.g.: Freitas et al. 2013; Hansen et al. 2010; McKitrick and Michaels 2007; Menne et al. 2018; Pielke et al. 2007a, b; Scafetta and Ouyang 2019; Soon et al. 2015, 2018; and many others).

The issue is of great concern because from 1950 to 2020 the world population increased from 2.5 billion to 7.5 billion (Population Division of the Department of Economic and Social Affairs of the United Nations: https://population.un.org/wup/). Urbanization did not develop uniformly. In fact, Fig. 1a shows that the world population density is not uniformly distributed on the globe, and Fig. 1b shows how the world city population has increased reporting data for the year 1950, 1990, 2015 and the projected values for 2030 (https://population.un.org/wup/). For example, from 1950 to 2015 in China the urban population increased 12 times, from 65 million to 775 million whereas in Europe it just doubled by increasing from 284 million (1950) to 547 million (2015).

https://link.springer.com/article/10.1007/s00382-021-05626-x

 

[redfish]

.
Why have sea surface temperatures and proxy temperature reconstructions so strongly diverged from the instrumental land record in recent decades? Because “0.36 ± 0.04 °C” of non-climatic warming from roofs, asphalt, machines, vehicles…artificially enhances the post-1950s global temperature trend.


Detection of non‐climatic biases in land surface temperature records by comparing climatic data and their model simulations

Nicola Scafetta
Climate Dynamics (2021)Cite this article


Abstract

The 0.6 °C warming observed in global temperature datasets from 1940 to 1960 to 2000–2020 can be partially due to urban heat island (UHI) and other non-climatic biases in the underlying data, although several previous studies have argued to the contrary. Here we identify land regions where such biases could be present by locally evaluating their diurnal temperature range (DTR = TMax − TMin trends between the decades 1945–1954 and 2005–2014 and between the decades 1951–1960 and 1991–2000 versus their synthetic hindcasts produced by the CMIP5 models. Vast regions of Asia (in particular Russia and China) and North America, a significant part of Europe, part of Oceania, and relatively small parts of South America (in particular Colombia and Venezuela) and Africa show DTR reductions up to 0.5–1.5 °C larger than the hindcasted ones, mostly where fast urbanization has occurred, such as in central-east China. Besides, it is found: (1) from May to October, TMax globally warmed 40% less than the hindcast; (2) in Greenland, which appears nearly free of any non-climatic contamination, TMean warmed about 50% less than the hindcast; (3) the world macro-regions with, on average, the lowest DTR reductions and with low urbanization (60S-30N:120 W–90 E and 60 S–10 N:90 E–180 E: Central and South America, Africa, and Oceania) warmed about 20–30% less than the models’ hindcast. Yet, the world macro-region with, on average, the largest DTR reductions and with high urbanization (30 N–80 N:180 W–180 E: most of North America, Europe, and Central Asia) warmed just a little bit more (5%) than the hindcast, which indicates that the models well agree only with potentially problematic temperature records. Indeed, also tree-based proxy temperature reconstructions covering the 30°N–70°N land area produce significantly less warming than the correspondent instrumentally-based temperature record since 1980. Finally, we compare land and sea surface temperature data versus their CMIP5 simulations and find that 25–45% of the 1 °C land warming from 1940–1960 to 2000–2020 could be due to non-climatic biases. By merging the sea surface temperature record (assumed to be correct) and an adjusted land temperature record based on the model prediction, the global warming during the same period is found to be 15–25% lower than reported. The corrected warming is compatible with that shown by the satellite UAH MSU v6.0 low troposphere global temperature record since 1979. Implications for climate model evaluation and future global warming estimates are briefly addressed.

Introduction

There has been considerable debate in the literature over the extent (if any) to which non-climatic biases – in particular, those due to urbanization elements such as the urban heat, aerosol emissions, and other factors—have contaminated regional, hemispheric and global temperature records, and artificially raised, or in any way altered global warming trends since the 1940s (e.g.: Freitas et al. 2013; Hansen et al. 2010; McKitrick and Michaels 2007; Menne et al. 2018; Pielke et al. 2007a, b; Scafetta and Ouyang 2019; Soon et al. 2015, 2018; and many others).

The issue is of great concern because from 1950 to 2020 the world population increased from 2.5 billion to 7.5 billion (Population Division of the Department of Economic and Social Affairs of the United Nations: https://population.un.org/wup/). Urbanization did not develop uniformly. In fact, Fig. 1a shows that the world population density is not uniformly distributed on the globe, and Fig. 1b shows how the world city population has increased reporting data for the year 1950, 1990, 2015 and the projected values for 2030 (https://population.un.org/wup/). For example, from 1950 to 2015 in China the urban population increased 12 times, from 65 million to 775 million whereas in Europe it just doubled by increasing from 284 million (1950) to 547 million (2015).

https://link.springer.com/article/10.1007/s00382-021-05626-x

not one of the resident libs will bother to read this. but thanks for posting the truth.

 

[Trumpet]

Thank you Queen of Quims for that fascinating post.

I certainly appreciate your gratitude, and if I can be of help in the future, just let me know.

 

[moon]

Here's an opportunity for JPP's Denier meteorologists to explain why the established US/Canada low-pressure front should suddenly collapse.

US cold snap: Why is Texas seeing Arctic temperatures?

According to the US National Weather Service (NWS), this is down to an "Arctic outbreak" that originated just above the US-Canada border, bringing a winter snow storm as well as plummeting temperatures.

Cold air outbreaks such as these are normally kept in the Arctic by a series of low-pressure systems, the NWS said. However, this one moved through Canada and spilled out into the US last week.

Temperatures in the city of Dallas for example will reach a high of 14F (-10C) on Monday when it should be more like 59F (15C) at this time of year.

For the first time in the US state, all 254 counties are under a winter storm warning, US media report. The temperature in Dallas is already colder than in Anchorage, Alaska, CBS News reports.

https://www.bbc.co.uk/news/world-us...bHjCXLbwCUdpWomN4bGh9NKjFdkg7cEgU_IOg86jvFrDw

Take it away, dumbasses.

Haw, haw..............................................haw.

 

[cancel2 2022]

.
Peer-Reviewed Study Confirms Antarctica Has Not Warmed in Last Seven Decades

Abstract

The Antarctic continent has not warmed in the last seven decades, despite a monotonic increase in the atmospheric concentration of greenhouse gases. In this paper, we investigate whether the high orography of the Antarctic ice sheet (AIS) has helped delay warming over the continent. To that end, we contrast the Antarctic climate response to CO2-doubling with present-day orography to the response with a flattened AIS. To corroborate our findings, we perform this exercise with two different climate models. We find that, with a flattened AIS, CO2-doubling induces more latent heat transport toward the Antarctic continent, greater moisture convergence over the continent and, as a result, more surface-amplified condensational heating. Greater moisture convergence over the continent is made possible by flattening of moist isentropic surfaces, which decreases humidity gradients along the trajectories on which extratropical poleward moisture transport predominantly occurs, thereby enabling more moisture to reach the pole. Furthermore, the polar meridional cell disappears when the AIS is flattened, permitting greater CO2-forced warm temperature advection toward the Antarctic continent. Our results suggest that the high elevation of the present AIS plays a significant role in decreasing the susceptibility of the Antarctic continent to CO2-forced warming.

https://www.nature.com/articles/s41612-020-00143-w

 

[Into the Night]

.
Why have sea surface temperatures

It is not possible to measure the temperature of the ocean.

.
and proxy temperature reconstructions

Proxies do not indicate temperature. These are speculations.

.
so strongly diverged from the instrumental land record

There is no land record. It is not possible to measure the temperature of the Earth.

.
in recent decades?

Irrelevant. It has never been possible to measure the temperature of the Earth.

.
Because “0.36 ± 0.04 °C” of non-climatic warming from roofs, asphalt, machines, vehicles…artificially enhances the post-1950s global temperature trend.

Speculation. Argument from randU fallacy. You can't have a trend with absolute measurements AND specified starting and ending times of those measurements.

.
Detection of non‐climatic biases in land surface temperature records by comparing climatic data and their model simulations

Comparing one set of random number to another set of random number is pointless.

.
Nicola Scafetta
Climate Dynamics (2021)Cite this article


Abstract

The 0.6 °C warming observed in global temperature datasets from 1940 to 1960 to 2000–2020

There is no global temperature dataset. It is not possible to measure the temperature of the Earth. We have nowhere near enough thermometers to even begin a sensible statistical summary of this type. The ones we do have are biased by location grouping and time.

.
can be partially due to urban heat island (UHI) and other non-climatic biases in the underlying data,

Speculation. There is no reference point. Base rate fallacy.

.
although several previous studies have argued to the contrary.

Irrelevant.

.
Here we identify land regions where such biases could be present by locally evaluating their diurnal temperature range (DTR = TMax − TMin trends between the decades 1945–1954 and 2005–2014 and between the decades 1951–1960 and 1991–2000 versus their synthetic hindcasts produced by the CMIP5 models.

Argument from randU fallacy. It is not possible to measure the temperature of the Earth. Base rate fallacy.

.
Vast regions of Asia (in particular Russia and China) and North America, a significant part of Europe, part of Oceania, and relatively small parts of South America (in particular Colombia and Venezuela) and Africa show DTR reductions up to 0.5–1.5 °C larger than the hindcasted ones, mostly where fast urbanization has occurred, such as in central-east China. Besides, it is found: (1) from May to October, TMax globally warmed 40% less than the hindcast; (2) in Greenland, which appears nearly free of any non-climatic contamination, TMean warmed about 50% less than the hindcast; (3) the world macro-regions with, on average, the lowest DTR reductions and with low urbanization (60S-30N:120 W–90 E and 60 S–10 N:90 E–180 E: Central and South America, Africa, and Oceania) warmed about 20–30% less than the models’ hindcast. Yet, the world macro-region with, on average, the largest DTR reductions and with high urbanization (30 N–80 N:180 W–180 E: most of North America, Europe, and Central Asia) warmed just a little bit more (5%) than the hindcast, which indicates that the models well agree only with potentially problematic temperature records. Indeed, also tree-based proxy temperature reconstructions covering the 30°N–70°N land area produce significantly less warming than the correspondent instrumentally-based temperature record since 1980. Finally, we compare land and sea surface temperature data versus their CMIP5 simulations and find that 25–45% of the 1 °C land warming from 1940–1960 to 2000–2020 could be due to non-climatic biases. By merging the sea surface temperature record (assumed to be correct) and an adjusted land temperature record based on the model prediction, the global warming during the same period is found to be 15–25% lower than reported. The corrected warming is compatible with that shown by the satellite UAH MSU v6.0 low troposphere global temperature record since 1979. Implications for climate model evaluation and future global warming estimates are briefly addressed.

Argument from randU fallacies. These are made up numbers. It is not possible to measure the temperature of the Earth.

.
Introduction

There has been considerable debate in the literature over the extent (if any) to which non-climatic biases – in particular, those due to urbanization elements such as the urban heat, aerosol emissions, and other factors—have contaminated regional, hemispheric and global temperature records, and artificially raised, or in any way altered global warming trends since the 1940s (e.g.: Freitas et al. 2013; Hansen et al. 2010; McKitrick and Michaels 2007; Menne et al. 2018; Pielke et al. 2007a, b; Scafetta and Ouyang 2019; Soon et al. 2015, 2018; and many others).

The issue is of great concern because from 1950 to 2020 the world population increased from 2.5 billion to 7.5 billion (Population Division of the Department of Economic and Social Affairs of the United Nations: https://population.un.org/wup/). Urbanization did not develop uniformly. In fact, Fig. 1a shows that the world population density is not uniformly distributed on the globe, and Fig. 1b shows how the world city population has increased reporting data for the year 1950, 1990, 2015 and the projected values for 2030 (https://population.un.org/wup/). For example, from 1950 to 2015 in China the urban population increased 12 times, from 65 million to 775 million whereas in Europe it just doubled by increasing from 284 million (1950) to 547 million (2015).
...deleted Holy Link...

Math errors: attempt to predict using statistical or probability math. Failure to publish unbiased raw data. Failure conduct selection. Failure to declare and justify variance. Failure to calculate margin of error. Synthetic averages. Use of random numbers as data.

Why are you cutting and pasting? This is not your argument, this is the argument from someone else. They are not here to debate the issue. You are stealing their argument as your own. This is weak thinking. and in some cases not even thinking at all.

You are making the SAME mistakes as those you oppose. Don't fall into their trap. You're better than this.