Not exact matches
So scientists have been finding innovative new ways of peering beneath the swells, conscripting everything from seals to
climate models to
improve their grasp of marine temperature trends.
The results
so far show only a correlation between fires and water cycle indicators, but the data gathered from the study is allowing scientists to
improve climate models to be able to establish a more direct relationship between biomass burning and its impacts on drought.
But for journalists and others who are not
climate scientists, some narrative would help, as inline text and more clarification as footnotes if needed including, cover for example: — being very clear for a graph what was being forecast (people play silly games with Hansen, confusing which was BAU)-- Perhaps showing original graph first «This is what was predicted...» in [clearly a] sidebar THEN annotated / overlayed graph with «And this is how they did...» sidebar — placing the prediction in context of the evolving data and science (e.g. we'd reached 3xx ppm and trajectory was; or «used
improved ocean
model»; or whatever)-- perhaps a nod to the successive IPCC reports and links to their narrative,
so the historical evolution is clear, and also perhaps, how the confidence level has evolved.
Of course, there are some differences — the butterfly effect has a basis in physical reality,
so as our understanding of physical processes and the ability to mathematically
model them
improves,
so will our ability to bridge the gap between predicting weather and
climate.
The missing variability in the
models highlights the critical need to
improve cloud
modeling in the tropics
so that prediction of tropical
climate on interannual and decadal time scales can be
improved.»
So... the
models don't give better answers to questions like
climate sensitivity despite getting larger, faster, and using smaller grid sizes... and your conclusion is that because they have not
improved, we should trust them?
It's a global
model so it doesn't tell us anything about
climate equity or the distribution of mitigation efforts, wealth or
improved lifestyles.
As such data
improve,
so will the calculated
models of
climate.
Various approaches to
improve the precision of multi-model projections have been explored, but there is still no agreed strategy for weighting the projections from different
models based on their historical performance
so that there is no direct means of translating quantitative measures of past performance into confident statements about fidelity of future
climate projections.
For independent realisations, the natural variability noise is reduced by the ensemble averaging (averaging to zero for a large enough ensemble)
so that -LCB- T -RCB- is an
improved estimate of the
model s forced
climate change Tf.