10 out of 10 based on 2 ratings
via JoNova
October 14, 2024 at 09:58AM
By Paul Homewood
Full of good ideas, aren’t they!
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The UK needs a comprehensive plan to reduce demand, reuse and recycle critical materials, such as lithium, to meet its net zero strategy goals and strengthen economic security, according to a report by the National Engineering Policy Centre, led by the Royal Academy of Engineering.
The report highlights the UK’s reliance on critical materials like lithium for batteries and magnesium for steel production, which are primarily sourced from global mining operations.
Key recommendations include reducing electric vehicle battery sizes by 30%, which could cut the UK’s lithium needs by 17%.
Professor Joan Cordiner, Chair of the National Engineering Policy Centre Working Group on Materials and Net Zero, said: “The way we extract and consume materials is unsustainable and we must address it urgently.
“Our report highlights the rising demand for critical materials, driven in part by their use in batteries, power systems and electronics.
“We are not the only country that will be competing for these finite minerals and we are calling on the new government to develop a materials strategy that addresses demand and reuse of critical materials.
“For example, if we reduced the size of the UK’s larger electric vehicle batteries by 30% we could cut our lithium demand by 17% and save 75 million tonnes of rock mined for lithium by 2040 – that’s the equivalent of 19 Wembley Stadiums full of rock.”
via NOT A LOT OF PEOPLE KNOW THAT
October 14, 2024 at 08:28AM
by Frank Bosse
Neither the trend analysis nor the model-observation comparison supports the conclusions of the attribution study that found:
“The combined change, attributable to human-induced climate change, is roughly a doubling in likelihood and a 7% increase in intensity.”
Starting September 11, there was a heavy rainfall event in parts of Austria, Poland and the Czech Republic. First assessments point to a record high value of precipitation in a wide area, as the result of a “Vb weather condition”, named after the historical classification of the tracking directions of low-pressure fields in Europe. In a Vb weather condition, a low pressure area tracks to the Mediterranean Sea, thereafter north-eastward and ends usually in the Baltic region of Europe. A Vb condition is very often associated with much rain in Mid-and Eastern Europa and flood events e.g. 1997 (River Oder) and 2002 (River Elbe).
However, an “Attribution study” appeared only a few days afterwards. It’s Core message about the event (cited in media) was:
“The combined change, attributable to human-induced climate change, is roughly a doubling in likelihood and a 7% increase in intensity.”
To evaluate the robustness of the claim, the full text of the attribution study was downloaded.
The meteorological classification of the event in question involves several atmosphere dynamics features. The triggering event was an “Arctic Outbreak”, an extreme northward displacement of the intertropical convergence zone (ITCZ) was also involved. To make the things worse, there was a stable blocking high pressure field north of the area in question, so the precipitation area was relatively stationary and could not move north towards the Baltic Sea as usual.
The key question is whether the thermodynamic element (related to warming from “climate change”) contributing to the events described can actually be quantified with some robustness, as it was claimed in the attribution study.
The attribution study describes trend analyses of observational data (E-Obs.) and (weather) model-observational reanalysis data (ERA5) for the time 1950-2023 (2024). The data used are available via the “KNMI Climate Explorer” permitting one to evaluate the numbers. The study uses the GMST GISS Dataset to describe the connection of heavy rain in Mid Europe to a warmer world. The attribution study states:
“All datasets show similar trends across the region, with increasing trends…” (see section 3.1)
The same dataset is used here, but averaged over the European area in question rather than globally. The mean temperature anomaly 1950-2023 in the region 20°W-25°E; 35°N-65°N is shown below. This region includes more land (which is faster warming than the ocean) than the roughly 30% global mean land fraction.
Fig.1: The temperature time series (GISS) in the European area. The figure was generated with the KNMI Climate Explorer.
The (not too surprising) observation: From 1950 to about 1981 the temperatures did not show any rise. Anthropogenic warming, manifested in the mean temperatures, started around 1981, not 1950.
To calculate the trends in the “RX4days” precipitation (which is the accumulation of 4 days of precipitation) the data for ERA5 were recalculated for 1950-2024:
Fig.2: The outstanding event in September 2024 is clearly visible. It makes the trendslope 1981-2024 ( green) positive (a “one year trend”), for 1981-2023 (black) it’s zero. The figure was generated with ChatGPT.
The ordinary least square (OLS)-Trend 1950-2024 (blue) is robustly positive (p=0.025) as the attribution study states. However, it did not mention that the trend become insignificant after the late 1960s when calculated to 2024. If the increasing trend from 1950 to 2024 were attributable to the “human induced climate change” after 1981, one would NOT expect that the trend slope to 2024 is completely insignificant (p=0,32) and for 1981-2023 (black) it’s zero. In the light of these findings the OLS-trends to 2024 might be more a result of internal variability. Over the period 1950-1981 with no warming (see Fig. 1), the most positive trend slope (orange) of RX4day was 2 times steeper than in 1981-2024, when the forced warming was observed.
The study evaluates the climate models used for the attribution analysis. Many models belong to the CMIP6 family. It iss well known that those models face substantial difficulties when it comes to atmosphere dynamics owing to their low resolution. The Multi Model Mean shows no skill in the study area (46°N- 52°N; 11°E- 24°E) with respect of the model-observation (E-Obs.) spatial correlation for precipitation.
Fig.3: The spatial correlation between precipitation of the CMIP6 Multi Model Mean with the Observations (E-Obs.) for the warm seasons 1975-2023. The figure was generated with the KNMI Climate Explorer.
A meaningful correlation should be a prerequisite for blaming the anthropogenic warming as simulated in the CMIP6 models, for a distinct extreme precipitation event based on model comparisons with the real world.
In Table 4.1 of the attribution study the models were evaluated, some of them (only a few) were labelled as “good” when it comes to precipitation. The “IPSL-CM6A-LR” model was labelled as “reasonable”. The spatial correlation 1950-2023 to E-OBS observations during months where Vb-events were observed is shown below, also for the “good” model “EC Earth 3”, both with below 20%, indistinguishable from random noise:
Fig. 4: There is no skill (white for the zero- correlation) in selected models of the study. The figure was generated with the KNMI Climate Explorer.
Neither “IPSL-CM6A-LR” (left) nor in “EC Earth3” (right), labelled as “good” in the study, have any skill when it comes to the spatial correlation of precipitation with the real world. Nor does the model MPI-ESM1-2LR (“reasonable” in Table 4.1 of the study), but not shown here.
In the end it seems dubious to attribute an extreme precipitation event to climate change when using the CMIP6 models. The ocean warming is for sure a source for more evaporation and also for more rain, although the proportional rise in precipitation with warming is only a fraction of the rise in evaporation.
However, the influence of atmosphere dynamics is overwhelming and hampers the attribution of single extreme weather events based on thermodynamics arguments.
Conclusion
After a closer look, neither the trend analysis nor the model-observation comparison supports the conclusions of the attribution study.
The issue of unsound extreme weather event attribution studies is not limited to extreme precipitation. As this recent article by Roger Pielke Jr explains, attribution studies for all types of extreme weather event are in general highly dubious, and appear to be undertaken more for “political” than for scientific purposes.
via Watts Up With That?
October 14, 2024 at 08:05AM
51.20408 0.13458 (Actual location) – Met Office quoted wrong co-ordinates 51.20346 0.1362 Real Elevation 42 metres amsl – Met Office (wrong location) 45 metres amsl. Met Office assessed Class 1 or 4 depending when they assessed it and “Excellent” dependent on who input (or didn’t ) the data. Installed 1/1/1973.
During my research into the CIMO classification of Hastings weather station I received the following admission from Angus Bruce BSc MIET (Regional Network Officer South east England- Met Office)
“The default CIMO rating is 1 on our site visit application (and Met O ‘Excellent’), so it looks like the class hasn’t been entered correctly, human error.”
A clear admission that the Met Office has a database that (by default) records all their sites as Class 1 and “Excellent” unless manually altered downwards – excellence assumed. So is this yet another case of “Human Error”? Well I did ask…….
Firstly to clarify the position, the Met office co-ordinates given on the CEDA archive do not accurately locate the site which is, in reality, 120 metres away from the quoted co-ordinates. The relevance of this inaccuracy takes on significant importance when the site is viewed from aspects of elevation and wider perspective.
“Edenbridge” weather station is actually 5 radial kilometres from Edenbridge railway station but just a few metres from the dam wall of its former site name of “Bough Beech” and best known for its artificial reservoir.
The Met Office quoted location claims an elevation of 45 metres amsl, however the actual location is lower at 41.5 metres. This difference becomes all them more relevant considering the unnatural curve of the lake above is the dam wall which tops at 55 metres. Edenbridge weather stations sits at the bottom of an artificial slope clearly evident from the Ordnance Survey map.
This Youtube clip below gives good panoramic views of this very attractive area showing the typical Kent Weald countryside and also the somewhat unnatural and unrepresentative nature of the lake. There really are no large natural lakes in any part of Kent. I have been unable to catch any glimpse of the station as it is hidden by the ridge of the dam wall.
In more specific close detail, the Screen is just 30 metres from the start of a large area of hard-standing which clearly rules out any possibility of meeting CIMO Class 1 on that count alone.
So how did the Met Office assess this site, compromised by external heat sources and lying at the foot of the steep slope up to the dam of an artificial body of water not representative of the natural region as Class 1?
Well they probably didn’t! Under Freedom of Information request I obtained Met Office CIMO assessments for England for 2021 as Class 4,
The same for 2022
But then in 2023 and with no amendments to the site…..
Almost miraculously this site improved itself from a lowly Class 4 (inaccuracy due to siting of 2°C) to a perfect Class 1 and the Met Office’s unique rating system of “EXCELLENT”
A further worrying point for this manually reporting site is that readings are not regularly taken. Again from FOI, in 2021 80 day’s readings were absent, in 2022 61 missing and in 2023 there were 134 missing day’s readings – not excellent at all.
Obviously this is yet another “Human Error” but it seems the Met Office no longer likes to admit to me that they are wrong. Following the revelation of the Hastings error, I queried the CIMO Class 1 rating given to the Cassley station. As I noted then, despite an initial offer to discuss issues with me by Angus Bruce’s national manager, Karl Shepherdson, the latter then reneged on the offer, declined to discuss anything at all with me and directed me to the “gatekeepers” on their enquiry desk. I was, however, somewhat cryptically assured that the Met Office current assessment of Cassley was “correct” but not confirmation that it was Class 1.
Unfortunately the Met Office enquiry desk also now seems somewhat unwilling to answer many of my enquiries. I have raised all the above issues regarding Edenbridge with the enquiry desk plus copying in my email request to the responsible area manager (Angus Bruce) but only to be met with a wall of silence and no reply.
Edenbridge is not Class 1 nor Excellent but until independent assessment or oversight is allowed how will we ever know? The Met Office seems to feel it is optional whether to openly reveal information so yet another, needless, Freedom of information request.
via Tallbloke’s Talkshop
October 14, 2024 at 07:59AM
