The BBC say more fell up in the hills at Chiva, but that does not have a long term record, and inevitably rainfall will be much higher as the moist air rises rapidly over the hills. In other words, chalk and cheese.
Not for the first time, the BBC are using human tragedy to push their increasingly hysterical climate agenda.
Jo Nova’s article, $650 million in renewable energy didn’t save Brisbane from blackout, centers on a critical observation regarding the limitations of renewable energy in protecting urban infrastructure during extreme weather events. Nova’s story note reveals a broader critique about the reliability of renewable energy, the effectiveness of government subsidies, and the often overpromised capacity of green solutions.
According to Jo Nova, a recent storm left Brisbane, Australia, without power, despite significant investment in renewable energy—around $650 million over five years. She emphasizes that this blackout serves as a stark reminder that renewables, which rely heavily on weather conditions, do not offer the reliability needed in crisis scenarios. Nova underscores that during the storm, solar panels were rendered useless, and wind turbines also became non-functional. The renewable infrastructure could not deliver electricity when it was most needed, as stormy weather conditions forced solar and wind production offline.
The bad news is that when there is no reliable 50Hz baseload supplier of electricity, the solar panel inverters just don’t mesh well with the diesel generators. The frequency of the diesel generators varies slightly as the load changes, and these fluctuations cause issues with solar inverters, which need a stable frequency to synchronize properly.
Hence, in a blackout, the solar panels were not just useless, they were a threat to the system, so people were asked to switch them off:
Nova’s article also touches on what she sees as misplaced priorities in energy policy. She criticizes the Australian government’s allocation of funds to renewable projects while neglecting the necessary upgrades to power grids and the development of reliable backup systems. She argues that without robust energy storage solutions or alternative backup power (like coal or natural gas), heavy reliance on renewables makes cities like Brisbane vulnerable during severe weather events. Essentially, Nova suggests that renewable energy alone is not a sufficient solution to ensure energy security, particularly in emergencies.
The core message in Nova’s story note is that while renewable energy projects often receive substantial financial support, their real-world performance during high-stress situations—like storms, heatwaves, or cold snaps—remains questionable. Nova uses this incident to caution against over-reliance on renewables without adequate grid resilience planning and backup capacity.
The Silverton Wind Farm and Broken Hill Solar plant were supposed to produce enough electricity to power 117,000 homes. They’re supported by AGL’s 50MWh battery facility at Pinnacles Place, one of the largest in Australia. Yet Broken Hill, population 19,000, has been in a semi-permanent state of blackout since a storm brought down the transmission line connecting the town to the east coast grid.
Some $650m worth of renewable energy investment within a 25km radius of Broken Hill has proved to be dysfunctional. The technical challenges of operating a grid on renewable energy alone appear insurmountable using the current technology.
This example from Brisbane aligns with broader critiques of renewable energy systems worldwide, which often fail to account for their limitations in meeting constant demand, particularly during extreme weather. As policymakers continue to push for aggressive transitions to renewable energy, Nova’s article suggests the need for a more balanced approach that includes investment in grid infrastructure and reliable energy sources that can be activated when renewables falter.
Nova’s story raises critical questions about energy policy and the realistic capacity of renewables to provide energy security. While her perspective is skeptical of the efficacy of renewables in their current state, it emphasizes the importance of preparing for the unpredictability of weather-dependent energy sources. Her article serves as a reminder that in the rush to achieve net-zero targets, the reliability of power supply, especially during crises, should not be overlooked.
Instead of spending $650 million dollars on solar and wind and a battery, we could have bought two brand new useful diesel generators for every remote town in Australia, and then when transmission towers fall down, they won’t be left in the dark.
53.87458 -0.44178 Met Office Assessed CIMO Class 3 Installed 1/1/1959
There are multiple issues with this site. There are even bigger problems with the way in which its temperature readings are subsequently manipulated by government departments that is almost unbelievable.
Firstly to evaluate the site there is obviously one major problem…….
The Met office claims this is a CIMO Class 3 site. This classification has the following requirements.
Using the google satellite images measuring indicator, it is quite apparent that not only is the former taxi way well under 10 metres from the screen, the area of tarmac @ 380 square metres with a 10 metre radius exceeds the 10% maximum for artificial heat sources. This site should be at best Class 4.
Then there is the obvious issue with the newly built solar farm, a part of Project Prometheus. As detailed in reviews of both Chertsey and Wallington, solar farms have been shown to create their own heat island effect that artificially raises local temperatures. The 4,248 panels start at just 80 metres from the screen. Construction of solar farms in the vicinity of weather stations is a growing issue that the Met Office seems to avoid discussing.
Another highly relevant concern is the site history. Archives show an initial installation date of 1959. This may indicate a long term temperature record but closer inspection reveals multiple site re-locations. The original station (WMO 03383) was located over 700 metres away at 502600E , 443800N from 1959 to 1969 as shown below.
Between 1969 to 1991 there were no records archived at all from any station at Leconfield. From 1991 to 2002 a separate station (WMO 03384) was at an unspecified location, however, unique WMO numbering indicates it was at a site that was subject to significantly different meteorological conditions. As a result the only representative and comparative record runs from 2002 to 2021 when the solar panels then corrupted the site from its prior low ranking.
Thus the Leconfield site is a low grade site with no genuinely comparative long term archived data.
So why is my headline about “Doubled Dubious Data”
The Met Office has an interesting web page on CIMO ratings detailing how grading indicates wider area representation. N.B. this is a complete misrepresentation of the CIMO guidance – using terminology such as “holistic” is highly indicative.
“the WMO classification simply informs the data user of the geographical scale of a site’s representativity of the surrounding environment – the smaller the siting class, the higher the representativeness of the measurement for a wide area. Indeed, it should be noted that WMO Class 5 is not the same as a Met Office ‘Unsatisfactory’ inspection assessment, which ultimately determines the ongoing use of a site. We use the Met Office grading system to determine record verification because; it has historical relevance, covering a wide range of long-standing criteria at UK observation sites, the equipment, and the exposure in a holistic manner and has clear meaning to what is acceptable or not. It tells us how much confidence we have in the data and permits comparisons.”
I interpret the above as the Met Office accepts that a Class 1 represents a wide area whilst a Class 5 only represents its immediate surroundings though they notably fail to mention the WMO inaccuracy by siting statements.
This is all very relevant to producing area and historic comparisons. The Department for Science, Innovation and Technology is responsible for the Met Office and provides data to the Department of Energy Security and Net Zero to assist in decisions the latter makes on energy information and policy.
This below is the government’s weather station statistics page.
There are over 380 Met Office CIMO assessed weather stations in the UK. For some truly bizarre reason just 17 were chosen with a totally unrepresentative geographic spread, and 4 of those sites simply had their data “doubled” to “produce the national averages for temperature correction”. Leconfield was one of those select 4.
From the above perversely selected site data “Climate Averages” are somehow produced running specifically for the period 1981 to 2020 as here.
What are the rankings of the chosen stations? These quite clearly should be representative of both their wider area (i.e. Class 1 or 2 ) and the historic period for which their data was accumulated (i.e. from before 1981 to present).
Leuchars, CIMO Class 5 and data from 1921, Durham Class 5 from 1851, St Athan Class 5 from 1997, Boscombe Down Class 5 from 1930, Glasgow Bishopton Class 4 from 1998, Bingley (by a substation) Class 4 from 1972, Crosby Class 4 from 1983, Nottingham:Watnall (doubled) Class 4 from 1941, Coleshill Class 4 from 1997, Aberporth Class 4 from 1941, Hurn (doubled) Class 4 from 1951 , Plymouth:Mountbatten Class 4 from 1920, Heathrow (falsely claimed to be Class 3) from 1947, Leconfield (falsely claimed to be Class 3 and doubled) from 2002, Leeming Class 2 from 1944, Weybourne Class 1 from 1991 and Rostherne No 2 (doubled) Class 1 from 2012.
So of 17 (which should really be 21) there are just 2 Class 1 sites neither of which existed in 1981. Just 1 Class 2 site. 2 sites are alleged to be Class 3 (inaccuracy by siting of up to 1°C) but clearly are not, 1 being doubled and not reporting from 1981. 8 are Class 4 (inaccuracy by siting up to 2°C) with 2 doubled and 3 non existent in 1981. 4 are Class 5 (inaccuracy by siting of up to 5°C) with one none existent in 1981.
This concoction of historic averages is reminiscent of Dungeness and Lowestoft where stations that do not actually exist are attributed averages by what are no better than mathematical conjuring tricks. The unrepresentative nature of these sites for their area is reminiscent of the absurdities demonstrated by Sheffield and Copley. The DSIT, DESNZ as well as the DWP are all using what can only be described as worthless number concoctions manipulated from unreliable prime data.
