In todays news...

[slowsider]

Not pure guesses, educated guesses.

[Screwdriver]

For the obvious reason that science has to date failed to produce a workable and reliable model of the relationship between human activity, natural changes in global climate, and weather events, percentage attributions can only be pure guesses. For all we know, some (which?) changes currently being made to human activity might actually be making long term global climate changes worse. We don't know, hence the rise of the attributionists ... because they provide 'answers'.

No I think I have to disagree with the sentiment that because science does not know all the answers, it has failed.

We will never know all the answers. Even in the most extreme case of Laplace's demon, it can be shown that complete future knowledge of a system is impossible. Getting back to the real world and specifically weather systems, chaos theory also raises its head and demonstrates the extraordinary complexity of a non-linear system which again, can be shown to completely remove any possibility of accurate long range predictions.

The butterfly effect is genuinely a real phenomena. Tiny, tiny changes in any non-linear system will have gigantic effects on the long term outcome. Those effects cannot be predicted. Science will never be "right" it will always only ever be the best we can do currently.

The sharp increased level of CO2 in the atmosphere is not a tiny change. It is huge. The climate system itself though is almost unthinkably massive both in complexity and energy. It may take more than a human lifetime for any change to take effect. I am of the opinion it is already too late. There is in my view too much inertia and too much positive feedback in the system for us to turn the climate around.

It has been kicked off its delicate equilibrium and is heading off to find some other stable configuration with its increased greenhouse effect. All that extra energy has to go somewhere and if it can't reradiate back into space, it will dissipate within our delicate eco system. Into the climate system.

I say "delicate" but the recent events in La Palma demonstrate what real power is. Our planet has plenty of energy driving its climate system and if it goes "extreme" we'll know all about it. Great little factoid to finish with: how heavy is a puffy little cloud scudding gently across the sky?

Answer: about a million tons.

[Screwdriver]

Oh and while there's no direct link yet to the current level of warming, there is a link between climate and volcanic activity.

https://www.scientificamerican.com/arti ... net-warms/

I think we can predict we’re probably going to see a lot more volcanic activity in areas of the world where glaciers and volcanoes interact,” he says, listing the U.S. Pacific Northwest, southern South America and even Antarctica.

What have we done? I might have to sell that damned RG500 after all.

[irie]

For the obvious reason that science has to date failed to produce a workable and reliable model of the relationship between human activity, natural changes in global climate, and weather events, percentage attributions can only be pure guesses. For all we know, some (which?) changes currently being made to human activity might actually be making long term global climate changes worse. We don't know, hence the rise of the attributionists ... because they provide 'answers'.

No I think I have to disagree with the sentiment that because science does not know all the answers, it has failed.

Failure means "lack of success".

[Screwdriver]

Failure means "lack of success".

In which case you need to define "success". If that is "to produce a workable and reliable model of the relationship between human activity, natural changes in global climate, and weather events" then again, I would disagree and suggest that we do have a workable model. It is reliable and it does measure AGW. The natural variability in global climate and weather events is well known...

Where we may agree is that none of those successes in science are perfect (see above!) and one might even argue they are far from perfect. But it is difficult to argue they are of no use (we are using them now!) or that they are no good. Because; "no good" compared to what?

Given that we know for absolute certainty that this vastly complex system can never be perfectly modelled, how do you rate the correlation between prediction and observation? It has predicted a rise in global temperature - check. A rise in the frequency and severity of extreme weather events - check. Decrease in sea ice - check.

It has only recently been stated that global warming is, with absolute certainty, being caused by man made pollution. Largely CO2 emissions. We've known the mechanism by which increase in greenhouse gas causes temperature rise for a long time. We also know that we've been dumping a LOT of it into the atmosphere and that the concentrations of CO2 have shot up.

I think it is too much to ask that we should be able to calculate exactly how that will affect the global climate to any degree of accuracy before we accept that the science is in fact, very good.

[Saga Lout]

In which case you need to define "success". If that is "to produce a workable and reliable model of the relationship between human activity, natural changes in global climate, and weather events" then again, I would disagree and suggest that we do have a workable model. It is reliable and it does measure AGW. The natural variability in global climate and weather events is well known...

The models don't measure global warming, they predict it. And the only reliable thing about them is that they reliably predict the earth will be warmer than it subsequently turns out to be.

[slowsider]

In which case you need to define "success". If that is "to produce a workable and reliable model of the relationship between human activity, natural changes in global climate, and weather events" then again, I would disagree and suggest that we do have a workable model. It is reliable and it does measure AGW. The natural variability in global climate and weather events is well known...

The models don't measure global warming, they predict it. And the only reliable thing about them is that they reliably predict the earth will be warmer than it subsequently turns out to be.

Like the over-reading speedometer on your motor vehicles, you can still make use of the trend.

[Saga Lout]

In which case you need to define "success". If that is "to produce a workable and reliable model of the relationship between human activity, natural changes in global climate, and weather events" then again, I would disagree and suggest that we do have a workable model. It is reliable and it does measure AGW. The natural variability in global climate and weather events is well known...

The models don't measure global warming, they predict it. And the only reliable thing about them is that they reliably predict the earth will be warmer than it subsequently turns out to be.

Like the over-reading speedometer on your motor vehicles, you can still make use of the trend.

I don't have a motor vehicle. [/pedant]

The speedometer on your motor vehicle, if you have one, is designed to over-read because it isn't legally allowed to under-read. It does, however, measure your speed and indicate a slightly higher speed, climate models do not measure anything and they're about as reliable as a politician's promise.

[Cousin Jack]

Like the over-reading speedometer on your motor vehicles, you can still make use of the trend.

Perhaps we should all carry on burning fossil fuel, just a bit more carefully and frugally. Just like we all drive at an indicated 85mph when we know the limit is 70 and the speedo over-reads by 10%.

[slowsider]

The models don't measure global warming, they predict it. And the only reliable thing about them is that they reliably predict the earth will be warmer than it subsequently turns out to be.

Like the over-reading speedometer on your motor vehicles, you can still make use of the trend.

I don't have a motor vehicle. [/pedant]

The speedometer on your motor vehicle, if you have one, is designed to over-read because it isn't legally allowed to under-read. It does, however, measure your speed and indicate a slightly higher speed, climate models do not measure anything and they're about as reliable as a politician's promise.

My bad

they reliably predict the earth will be warmer than it subsequently turns out to be.

Has the temperature of the earth been falling lately? Or does the model just anticipate a little ?

[slowsider]

Like the over-reading speedometer on your motor vehicles, you can still make use of the trend.

Perhaps we should all carry on burning fossil fuel, just a bit more carefully and frugally. Just like we all drive at an indicated 85mph when we know the limit is 70 and the speedo over-reads by 10%.

You need to do you sums a bit more carefully and frugally

[Saga Lout]

Has the temperature of the earth been falling lately? Or does the model just anticipate a little ?

Has the earth warmed as much as the models predicted? No
Were the models even close? No
Should we trust the models to predict the next 10/20/50 years?

[Horse]

Like the over-reading speedometer on your motor vehicles, you can still make use of the trend.

Perhaps we should all carry on burning fossil fuel, just a bit more carefully and frugally.

Interesting item on the BBC news website this morning, suggesting roughly that.

Apparently small changes in aircraft flight paths could substantially reduce the effects of contrails.

https://www.bbc.co.uk/news/business-58769351

[Screwdriver]

Has the earth warmed as much as the models predicted? No
Were the models even close? No
Should we trust the models to predict the next 10/20/50 years?

Really? What makes you say that? Have you even looked at the data?

https://climate.nasa.gov/news/2943/stud ... ons-right/
https://skepticalscience.com/climate-models.htm
https://www.science.org/content/article ... al-warming

...and a million more if you want to look. Chances are if you only want to find evidence of poor performance they are equally easy to find but are often from spurious sources (at best). Me? I trust the science.

[irie]

Failure means "lack of success".

In which case you need to define "success"...

OK, here you are:

success
/səkˈsɛs/
noun
1.
the accomplishment of an aim or purpose.

... If that is "to produce a workable and reliable model of the relationship between human activity, natural changes in global climate, and weather events" then again, I would disagree and suggest that we do have a workable model. It is reliable and it does measure AGW. The natural variability in global climate and weather events is well known...

Where we may agree is that none of those successes in science are perfect (see above!) and one might even argue they are far from perfect. But it is difficult to argue they are of no use (we are using them now!) or that they are no good. Because; "no good" compared to what?

Given that we know for absolute certainty that this vastly complex system can never be perfectly modelled, how do you rate the correlation between prediction and observation? It has predicted a rise in global temperature - check. A rise in the frequency and severity of extreme weather events - check. Decrease in sea ice - check.

It has only recently been stated that global warming is, with absolute certainty, being caused by man made pollution. Largely CO2 emissions. We've known the mechanism by which increase in greenhouse gas causes temperature rise for a long time. We also know that we've been dumping a LOT of it into the atmosphere and that the concentrations of CO2 have shot up.

I think it is too much to ask that we should be able to calculate exactly how that will affect the global climate to any degree of accuracy before we accept that the science is in fact, very good.

Quality obfuscation.

[Saga Lout]

Has the earth warmed as much as the models predicted? No
Were the models even close? No
Should we trust the models to predict the next 10/20/50 years?

Really? What makes you say that? Have you even looked at the data?

https://climate.nasa.gov/news/2943/stud ... ons-right/
https://skepticalscience.com/climate-models.htm
https://www.science.org/content/article ... al-warming

...and a million more if you want to look. Chances are if you only want to find evidence of poor performance they are equally easy to find but are often from spurious sources (at best). Me? I trust the science.

If the models are so accurate why are the predictions so inaccurate?
We always seem to have about 10 years to save the planet. Now that's an inconvenient truth.

[slowsider]

Failure means "lack of success".

In which case you need to define "success"...

OK, here you are:

success
/səkˈsɛs/
noun
1.
the accomplishment of an aim or purpose.

If you don't understand scientific method you should have said

a method of procedure that has characterized natural science since the 17th century, consisting in systematic observation, measurement, and experiment, and the formulation, testing, and modification of hypotheses.

[irie]

Has the earth warmed as much as the models predicted? No
Were the models even close? No
Should we trust the models to predict the next 10/20/50 years?

Really? What makes you say that? Have you even looked at the data?

https://climate.nasa.gov/news/2943/stud ... ons-right/
https://skepticalscience.com/climate-models.htm
https://www.science.org/content/article ... al-warming

...and a million more if you want to look. Chances are if you only want to find evidence of poor performance they are equally easy to find but are often from spurious sources (at best). Me? I trust the science.

If the models are so accurate why are the predictions so inaccurate?
We always seem to have about 10 years to save the planet. Now that's an inconvenient truth.

Well exactly.

If the models successfully made accurate predictions then it's obvious that there would would be no room for the fringe climate attributionists. It follows that the climate attributionists have arisen because of the failure of the climate prediction models.

I suspect our very own Screwdriver's obfuscation is still being driven by Python code of questionable origin.

Ah yes, the Python code which I guess is still a work in progress.

It's still a work in progress.

import datetime
from os import path
import urllib

import numpy as np

import ocw.data_source.local as local
import ocw.dataset_processor as dsp
import ocw.evaluation as evaluation
import ocw.metrics as metrics
import ocw.plotter as plotter

# File URL leader
FILE_LEADER = "http://zipper.jpl.nasa.gov/dist/"
# Two Local Model Files
FILE_1 = "AFRICA_KNMI-RACMO2.2b_CTL_ERAINT_MM_50km_1989-2008_tasmax.nc"
FILE_2 = "AFRICA_UC-WRF311_CTL_ERAINT_MM_50km-rg_1989-2008_tasmax.nc"
# Filename for the output image/plot (without file extension)
OUTPUT_PLOT = "wrf_bias_compared_to_knmi"

FILE_1_PATH = path.join('/tmp', FILE_1)
FILE_2_PATH = path.join('/tmp', FILE_2)

if not path.exists(FILE_1_PATH):
urllib.urlretrieve(FILE_LEADER + FILE_1, FILE_1_PATH)
if not path.exists(FILE_2_PATH):
urllib.urlretrieve(FILE_LEADER + FILE_2, FILE_2_PATH)

""" Step 1: Load Local NetCDF Files into OCW Dataset Objects """
print("Loading %s into an OCW Dataset Object" % (FILE_1_PATH,))
knmi_dataset = local.load_file(FILE_1_PATH, "tasmax")
print("KNMI_Dataset.values shape: (times, lats, lons) - %s \n" %
(knmi_dataset.values.shape,))

print("Loading %s into an OCW Dataset Object" % (FILE_2_PATH,))
wrf_dataset = local.load_file(FILE_2_PATH, "tasmax")
print("WRF_Dataset.values shape: (times, lats, lons) - %s \n" %
(wrf_dataset.values.shape,))

""" Step 2: Temporally Rebin the Data into an Annual Timestep """
print("Temporally Rebinning the Datasets to an Annual Timestep")
knmi_dataset = dsp.temporal_rebin(knmi_dataset, temporal_resolution='annual')
wrf_dataset = dsp.temporal_rebin(wrf_dataset, temporal_resolution='annual')
print("KNMI_Dataset.values shape: %s" % (knmi_dataset.values.shape,))
print("WRF_Dataset.values shape: %s \n\n" % (wrf_dataset.values.shape,))

""" Step 3: Spatially Regrid the Dataset Objects to a 1 degree grid """
# The spatial_boundaries() function returns the spatial extent of the dataset
print("The KNMI_Dataset spatial bounds (min_lat, max_lat, min_lon, max_lon) are: \n"
"%s\n" % (knmi_dataset.spatial_boundaries(), ))
print("The KNMI_Dataset spatial resolution (lat_resolution, lon_resolution) is: \n"
"%s\n\n" % (knmi_dataset.spatial_resolution(), ))

min_lat, max_lat, min_lon, max_lon = knmi_dataset.spatial_boundaries()

# Using the bounds we will create a new set of lats and lons on 1 degree step
new_lons = np.arange(min_lon, max_lon, 1)
new_lats = np.arange(min_lat, max_lat, 1)

# Spatially regrid datasets using the new_lats, new_lons numpy arrays
print("Spatially Regridding the KNMI_Dataset...")
knmi_dataset = dsp.spatial_regrid(knmi_dataset, new_lats, new_lons)
print("Final shape of the KNMI_Dataset: \n"
"%s\n" % (knmi_dataset.values.shape, ))
print("Spatially Regridding the WRF_Dataset...")
wrf_dataset = dsp.spatial_regrid(wrf_dataset, new_lats, new_lons)
print("Final shape of the WRF_Dataset: \n"
"%s\n" % (wrf_dataset.values.shape, ))

""" Step 4: Build a Metric to use for Evaluation - Bias for this example """
# You can build your own metrics, but OCW also ships with some common metrics
print("Setting up a Bias metric to use for evaluation")
bias = metrics.Bias()

""" Step 5: Create an Evaluation Object using Datasets and our Metric """
# The Evaluation Class Signature is:
# Evaluation(reference, targets, metrics, subregions=None)
# Evaluation can take in multiple targets and metrics, so we need to convert
# our examples into Python lists. Evaluation will iterate over the lists
print("Making the Evaluation definition")
bias_evaluation = evaluation.Evaluation(knmi_dataset, [wrf_dataset], [bias])
print("Executing the Evaluation using the object's run() method")
bias_evaluation.run()

""" Step 6: Make a Plot from the Evaluation.results """
# The Evaluation.results are a set of nested lists to support many different
# possible Evaluation scenarios.
#
# The Evaluation results docs say:
# The shape of results is (num_metrics, num_target_datasets) if no subregion
# Accessing the actual results when we have used 1 metric and 1 dataset is
# done this way:
print("Accessing the Results of the Evaluation run")
results = bias_evaluation.results[0][0]
print("The results are of type: %s" % type(results))

# From the bias output I want to make a Contour Map of the region
print("Generating a contour map using ocw.plotter.draw_contour_map()")

lats = new_lats
lons = new_lons
fname = OUTPUT_PLOT
gridshape = (4, 5) # 20 Years worth of plots. 20 rows in 1 column
plot_title = "TASMAX Bias of WRF Compared to KNMI (1989 - 2008)"
sub_titles = range(1989, 2009, 1)

plotter.draw_contour_map(results, lats, lons, fname,
gridshape=gridshape, ptitle=plot_title,
subtitles=sub_titles)

So. How does that help?

[Cousin Jack]

You need to do you sums a bit more carefully and frugally

I've done my sums.

If I stop all my CO2 producing activities now, and everyone else in the UK does the same (at huge cost/inconvenience) the USA/Russia/India/China and Brazil will make a token effort, and global warming (if it is driven by human activity) will continue. If it is a natural cycle thing it will happen anyway, whatever Homo Sapiens does.

Why should I bother, except to make David Attenborough and Greta Thunberg happy and make assorted politicians (who will be largely immune to the consequences) look good? Better to be a follower, WHEN and IF the rest of the world goes green we can follow. Not much sign of the major polluters making anything except token efforts at the moment.

IMO the earth is probably warming up, bad (for us) stuff is happening, and we had better get used to it.

[Screwdriver]

Failure means "lack of success".

In which case you need to define "success"...

OK, here you are:

success
/səkˈsɛs/
noun
1.
the accomplishment of an aim or purpose.

Then you need to understand what the aim of science is and the purpose for developing models. It is ongoing...

Like I said, it is impossible to produce a perfect model so if you want to suggest the entire science of climatology is "a failure" because it is not perfect, what do you propose to replace it with?