A new paper out this week in PLOS Biology uses some CMIP5 simulations of daily mean surface air temperature as part of a larger analysis on the change to future plant growing days. The description of the analysis suggests they have not used the simulations appropriately to arrive at their conclusions. Here I highlight a couple of possible pitfalls in using such data in impact studies. Continue reading How not to use daily CMIP5 data for impact studies
Current global temperatures are often discussed in terms of their unprecedented nature when compared to the last few thousand years. An interesting paper in Nature Climate Change by Steven J Smith and colleagues examines the rate of warming projected by the CMIP5 ensemble and suggests that the rate of warming is unprecedented also. However, we note here that their projections are not constrained by the current observations which do not show such strong warming rates at present, and are unlikely to do so in the next few years. Continue reading Hiatus delays unprecedented warming rates
Imagine a ball bouncing down a bumpy hill. Gravity will ensure that the ball will head downwards. But, if the ball hits a bump at a certain angle it might move horizontally or even upwards for a time, before resuming its inevitable downward trajectory. This bouncing ball is an analogy for the behaviour of Arctic sea-ice.
Post based on Swart et al., Nature Climate Change, or see a less technical summary. Continue reading Arctic sea-ice decline erratic as expected
2014 was a warm year for much of Europe and the globe, and may end up being the warmest year on record globally. But, no-one experiences a global mean temperature directly, so how about more locally? Can the signal of a warming climate be seen?
Model projections of heavy precipitation and temperature extremes include large uncertainties. However, disagreement between individual simulations primarily arises from internal variability, whereas models agree remarkably well on the forced signal.
Post based on Fischer et al., 2014, Geophys. Res. Lett.
Continue reading Projected changes of precipitation and temperature extremes
Investigations into the recent observed slower rate of global warming have largely been focussed on variability in the Pacific basin. Climate models also show similar slowdowns focussed in the Pacific (e.g. Meehl et al. 2011).
But, is this the only type of simulated slowdown? How different can regional patterns of temperature change be for the same global change? Continue reading The slowdown zoo
Global surface air temperatures have risen less rapidly over the past 15 years than the previous few decades. The causes of this ‘hiatus’ have been much debated. However, just considering surface temperatures does not tell the whole story – a new analysis using satellite & ocean observations confirms that the Earth is still gaining energy overall. Continue reading Earth’s energy imbalance
A prevailing paradigm of how rainfall patterns will change on a warming Earth is that the hydrological cycle strengthens causing wet regions to get wetter and dry regions to get drier.
However, this is not always the case: Hawkins, Joshi & Frame (2014) highlight one particular effect – the movement of the Inter-Tropical Convergence Zone (ITCZ) – as a key long-term driver of rainfall changes that do not follow this ‘wet get wetter’ paradigm. Continue reading Wet get drier (eventually)?
How will UK summer temperatures change in future? And, how might we best communicate the possibilities? This is a short post describing one effort in visualising the possible outcomes. Continue reading Visualising UK summer temperatures – what are the odds?
As the attention received by the ‘global warming hiatus’ demonstrates, global mean surface temperature (T) variability on decadal timescales is of great interest to both the general public and to scientists. Here, I will discuss a recently published paper (Brown et al., 2014) that attempts to contribute to this scientific discussion by investigating the impact of unforced (internal) changes in the earth’s top-of-atmosphere (TOA) energy budget on decadal T variability.
Guest post by Patrick Brown (Duke University) Continue reading Top-of-atmosphere contribution to unforced variability in global temperature
A previous post discussed the recent Comment on Mora et al., which considered mainly methodological & statistical errors. However, the erroneous assumptions regarding uncertainty in the Mora et al. study have further implications for their results on population and income.
Yesterday saw the publication of our Comment on Mora et al., along with Mora et al.’s Reply and an associated ‘News & Views’ piece. Although the Editors deserve credit for commissioning a News & Views piece on this exchange – a first for a Comment in Nature – there are still errors in Mora et al.’s Reply. A previous post summarised the issues with the original paper, and Doug McNeall also discusses the main issues. Continue reading On Mora et al.’s Reply
The paper was highlighted by Nature with an associated News & Views article and received widespread media attention (e.g. Climate Central, National Geographic, Guardian, Grist, amongst many). The paper was also in the top 100 most discussed papers from 2013 according to Altmetric.
Unfortunately, it has since emerged that the analysis has some serious flaws. A ‘Brief Communication Arising’ (or Comment) has now been published by Hawkins et al. in Nature (freely available for one month), written by a large group which includes several IPCC Lead Authors, from both WG1 and WG2. There is also a ‘Reply’ from Mora et al., and a new News & Views (N&V) piece by Scott Power discussing the continuing disagreement between the author teams. This is the first ever N&V on a Comment in Nature.
This post provides a slightly less technical description of the issues with Mora et al.’s analysis. The errors in Mora et al.’s Reply are summarised in a separate post. The Carbon Brief blog has also produced some videos on the topic. Continue reading Uncertainties in the timing of unprecedented climates
Ideally, we would have observations of past weather everywhere for several centuries to reconstruct the state of the atmosphere and learn about its variability. But, we don’t.
Instead, all the observations ever taken would, ideally, be available digitally for everyone to use. But, they aren’t. Many past observations are buried in hand-written journals and logbooks, gathering dust in libraries and archives all over the world. Rescuing this data would be of great benefit to reconstructing past weather, as this example will show. Continue reading Improving the weather from 96 years ago
Lewis & Crok have circulated a report, published by the Global Warming Policy Foundation (GWPF), criticising the assessment of equilibrium climate sensitivity (ECS) and transient climate response (TCR) in both the AR4 and AR5 IPCC assessment reports.
Climate sensitivity remains an uncertain quantity. Nevertheless, employing the best estimates suggested by Lewis & Crok, further and significant warming is still expected out to 2100, to around 3°C above pre-industrial climate, if we continue along a business-as-usual emissions scenario (RCP 8.5), with continued warming thereafter. However, there is evidence that the methods used by Lewis & Crok result in an underestimate of projected warming. Continue reading Comments on the GWPF climate sensitivity report
Climate projections have demonstrated the need to adapt to a changing climate, but have been less helpful (so far) in guiding how to effectively adapt. Part of the reason is the ‘cascade of uncertainty’ going from assumptions about future global emissions of greenhouse gases to what that means for the climate to real decisions on a local scale. Each of the steps in the process contains uncertainty, but which step is the most important? And, how might this be visualised? Continue reading The cascade of uncertainty in climate projections
The recent IPCC AR5 includes a discussion on the sources of uncertainty in climate projections (Fig. 11.8, section 18.104.22.168), which updates previous analyses using CMIP3 (temperature, precipitation) to the latest CMIP5 simulations. The dominant source of uncertainty depends on lead time, variable and spatial scale. Continue reading Sources of uncertainty in CMIP5 projections
The ‘signal’ of a warming climate is emerging against a background ‘noise’ of natural internal variability. Both the magnitude of the signal and the noise vary spatially and seasonally. As society and ecosystems tend to be somewhat adapted to natural variability, some of the impacts of any change will be felt when the signal becomes large relative to the noise. So, it is important to note where and when this might occur. Continue reading Time of emergence of a warming signal
The final version of the IPCC AR5 WG1 assessment on the physical basis for climate change has now been published. The AR5 includes, for the first time, a specific chapter and assessment on ‘near-term’ climate change, which covers the period up to 2050, but with a specific focus on the 2016-2035 period.
What are the possible regional temperature trends over the coming few decades? Globally, on average, there is expected to be a long-term warming, but this is not necessarily true for any particular location or period. What are the probabilities of a local warming or cooling? Continue reading Near-term regional climate: the range of possibilities
The Science Media Centre recently held a briefing for journalists on the recent slowdown in global surface temperature rise, and published an accompanying briefing note. The Met Office also released three reports on the topic.
The key points were: (1) recent changes need to be put in longer term context & other climate indicators such as sea level, Arctic sea ice, snow cover, glacier melt etc are also important; (2) the explanation for recent slowdown is partly additional ocean heat uptake & partly negative trends in natural radiative forcing (due to solar changes and small volcanic eruptions) which slightly counteract the positive forcing from GHGs; (3) the quantification of the relative magnitude of these causes is still work in progress; (4) climate models simulate similar pauses. Continue reading Recent slowdown in global surface temperature rise
The recent WMO press release on the climate of the 2001-2010 period highlighted that global temperature change was accelerating. Although this could be a misleading statement, should we even be expecting global temperature changes to be accelerating at present? Continue reading Rates of change in global temperatures
A recent comparison of global temperature observations and model simulations on this blog prompted a rush of media and wider interest, notably in the Daily Mail, The Economist & in evidence to the US House of Representatives. Given the widespread misinterpretation of this comparison, often without the correct attribution or links to the original source, a more complete description & update is needed. Continue reading Comparing global temperature observations and simulations, again
Climate information for the future is usually presented in the form of scenarios: plausible and consistent descriptions of future climate without probability information. This suffices for many purposes, but for the near term, say up to 2050, scenarios of emissions of greenhouse gases do not diverge much and we could work towards climate forecasts: calibrated probability distributions of the climate in the future. Continue reading Reliability of regional climate trends
Can past observations be used to help constrain future temperature projections? This question is particularly relevant given the last decade which has shown relatively less warming than expected. Continue reading Constraining projections with observations
Now that 2012 is over, it is time to update a comparison of simulations and observations of global mean temperatures.
A new analysis by Clara Deser and colleagues (accepted for Nature Climate Change), provides some fantastic visualisations of the crucial role of natural variability in how we will experience climate. Continue reading Visualising the role of natural variability