#4 Temperature too – not just rain – ongoing BoM utter incompetence – month after month after month

Just in case anybody thinks temperature Outlooks are reliable – take a look at these disparate results for the last three months period. Also note that the BoM seems to have the overall calibration of their models wrong – the Outlooks are overall far too warm – which has been an error for years now. To scan through my BoM articles.
First maximum or daytime temperatures – huge areas of Australia turned out way cooler than normal – a fact which the BoM models utterly failed to predict.
Max T BoM model failure Oct 2010
If you live in city where the home office of that brand is located, they will most likely be paying for it out of your own home. generic vs viagra Causes of Impotence Male impotence affects more than 30 million in order cheap levitra the U.S. alone. Consequently, erectile dysfunction outcome from several different mechanisms. bulk generic viagra Bayesian tadalafil super active filtering analyzes single words and computes a score for each mail message. Minimum or night time temperatures – predicted to be even hotter relative to norms compared to daytime – yet once again huge areas of Australia turned out way cooler than normal – a fact which the BoM models utterly failed to predict.
Min T BoM model failure Oct 2010
But what would you expect from an organization pushing the notion of man caused global warming. The Govt. must tell the BoM to stop wasting our taxes to produce this useless rubbish.

8 thoughts on “#4 Temperature too – not just rain – ongoing BoM utter incompetence – month after month after month”

  1. Gee whiz!

    If they can massage another “hottest record” into this somewhere without admitting UHI or dodgy thermometer locations they should all be selling used cars while standing for parliament.

  2. and here’s a fascinating link (thanks el gordo)
    www.holtonweather.com/WHAT%20IS%20THE%20MAIN%20FACTOR%20CONTROLLING%20THE%20MURRAY%20DARLING%20BASIN%20SYSTEM%20RAINFALL.pdf
    conclusions:
    The results show that the Sinusoidal Solar-Lunar Cycles have controlled the general Murray Darling Basin (South QLD-NSW-VIC-SA) Rainfall Trends from 1900 to 2006….During the critical Autumn to Spring & River- Dam inflow- Irrigation and Dry-land farming period….And the most helpful information about this close connection, is that we are able, from the Copeland and Watts Sinusoidal Model, to forecast with a high degree of confidence the next 30 years or so Murray Darling Basin General Rainfall & Dam Inflow Trends…As the future plotted Sinusoidal Model Trace is based on regular and recurring cycles that have not altered significantly in the past, and should not alter significantly in the future…..Therefore, any general Murray Darling Basin Southern Wet Season General Rainfall Trends that we can forecast from the Sinusoidal Solar-Lunar Model are highly likely to be accurate general trend rainfall & dam inflow forecasts.

    It is the firm opinion of the author that weather, ocean and rainfall patterns are cyclic. They always have been, and always will continue to do so…….And that any dire predictions of continuing & worsening drought in the Murray Darling Basin, and in fact in any region of Australia, are entirely unfounded.

  3. huge areas of Australia turned out way cooler than normal – a fact which the BoM models utterly failed to predict.

    And from “Negating climate change policy”, Dr David RB Stockwell:

    But the SoC says CSIRO/BoM use scientific modeling based on the laws of physics

    So the real world is not in agreement with the SoC and neither are physicists. From G&T 2009:

    In global climatology temperatures are computed from given radiation intensities, and this exchanges cause and effect. The current local temperatures determine the radiation intensities and not vice versa.

    Also heat conduction at the ocean-atmosphere interface is ignored in the current model configurations. The AGW hypothesis is in direct contravention of the laws of physics to start with despite the efforts of the proponents to modify the law so that cool objects transfer heat to warm objects. The bizarre extension of their reasoning is that in their view, the suns temperature is higher due to the presence of the earth than it would be if the earth was non-existent.

    From “Negating climate change policy” again:

    and thoroughly tested against recorded observations.

    Yes they have been “tested against recorded observations” and apart from the apparent correlation of the 70’s, 80’s and 90’s, the models have not got the foggiest clue in hindcast, particularly the 30’s, 40’s, 50’s, 60’s warm-cool phase change and the last decade since 2000. Not that it’s the model’s fault, they’ve been hard-wired with bogus CO2 forcing datasets.

    So in the absence of solar-lunar natural cycles built into the model parameters they still fail when CO2 forcing is removed for the IPCC version of “natural forcings only” simulations.

    That the performance of the CSIRO ACCESS and POAMA models is less than useful comes as no surprise given that they opted for the UKMO core of “barbeque summer” infamy. NZ’s NIWA in me-too group-think fashion saw CSIRO’s adoption of UKMO software and in turn opted for off-the-shelf UKMO UM, so NIWA’s forecasts are equally predestined to fail.

    It is disappointing that a great deal of work has gone into V&V for say, AER’s Radiative Transfer Model (RRTMG) which is the module that is then inserted into NCAR’s CESM1 GCM only for the whole atmospheric component (CAM) to then be distorted by the same old familiar Law Dome ice core – Mauna Loa splice, CO2 ppm spin-up dataset.

    And still the climate modeling community ignore natural cycles that are the real climate drivers in favour of consensus science that churns out reality defying predictions.

    Commercial operators are not so silly. From

    “Inquiry into long-term meteorological forecasting in Australia”

    2.69
    The Committee was astounded to learn that private enterprises are apparently able to forecast particular seasonal conditions and events, which may not necessarily have been forecast by our leading national agencies. The question that came to the mind of Committee members when this issue came to light was “how did you forecast these events and why didn’t anyone else?” When considering the skills, knowledge and expertise in our national agencies, the question that came to mind was “what do they know that CSIRO and the Bureau don’t?”

    [H/T David Stockwell, Niche Modeling]

  4. BOM are predicting 22 cyclones for the tropics this season, nearly double the average. With warmer waters in the north they may get this right, however last year, the sea was also warm, but there were few cyclones. Any thoughts?
    Our temperature in Broome is strongly associated with sea surface temps in the NWest, resulting in above average minimum and maximum temperatures since June 2009. The Oct 2009 minimum and the August 2009 and Jan 2010 maximums, are the only periods where there was a below average record in this 17 month period. Great weather!

  5. Another reason for the warm bias in the models may be the way they handle numerical imbalances in the energy budget. If I understand it correctly, for any particular grid square, if there is a net energy imbalance at the end of the day, the net imbalance is uniformly redistributed over all the grid squares. This maintains the energy balance, but perhaps it is not realistic. Instead of retaining energy in the Earth, perhaps it escapes to space, in whole or in part. Allowing such escape would allow for long-term oscillations in climate. Suppressing such escape will suppress natural climate variability and lead to a larger net warming.

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