New research from last week 46/2011
Posted by Ari Jokimäki on November 21, 2011
Here is the new research published last week. I’m not including everything that was published but just some papers that got my attention. Those who follow my Facebook page (and/or Twitter) have already seen most of these, as I post these there as soon as they are published. Here, I’ll just put them out in one batch. Sometimes I might also point out to some other news as well, but the new research will be the focus here. Here’s the archive for the news of previous weeks. By the way, if this sort of thing interests you, be sure to check out A Few Things Illconsidered, they have a weekly posting containing lots of links to new research and other climate related news.
There will still be cold months in warmer climate
Cold months in a warming climate – Räisänen & Ylhäisi (2011) “The frequency of cold months in the 21st century is studied using the CMIP3 ensemble of climate model simulations, using month-, location- and model-specific threshold temperatures derived from the simulated 20th century climate. Unsurprisingly, cold months are projected to become less common, but not non-existent, under continued global warming. As a multi-model mean over the global land area excluding Antarctica and under the SRES A1B scenario, 14% of the months during the years 2011–2050 are simulated to be colder than the 20th century median for the same month, 1.3% colder than the 10th percentile, and 0.1% record cold. The geographic and seasonal variations in the frequency of cold months are strongly modulated by variations in the magnitude of interannual variability. Thus, for example, cold months are most infrequently simulated over the tropical oceans where the variability is smallest, not over the Arctic where the warming is largest.” Räisänen, J. and J. S. Ylhäisi (2011), Geophys. Res. Lett., 38, L22704, doi:10.1029/2011GL049758.
You need at least 17 years of TLT data to detect anthropogenic warming signal
Separating signal and noise in atmospheric temperature changes: The importance of timescale – Santer et al. (2011) “We compare global-scale changes in satellite estimates of the temperature of the lower troposphere (TLT) with model simulations of forced and unforced TLT changes. While previous work has focused on a single period of record, we select analysis timescales ranging from 10 to 32 years, and then compare all possible observed TLT trends on each timescale with corresponding multi-model distributions of forced and unforced trends. We use observed estimates of the signal component of TLT changes and model estimates of climate noise to calculate timescale-dependent signal-to-noise ratios (S/N). These ratios are small (less than 1) on the 10-year timescale, increasing to more than 3.9 for 32-year trends. This large change in S/N is primarily due to a decrease in the amplitude of internally generated variability with increasing trend length. Because of the pronounced effect of interannual noise on decadal trends, a multi-model ensemble of anthropogenically-forced simulations displays many 10-year periods with little warming. A single decade of observational TLT data is therefore inadequate for identifying a slowly evolving anthropogenic warming signal. Our results show that temperature records of at least 17 years in length are required for identifying human effects on global-mean tropospheric temperature.” Santer, B. D., et al. (2011), Separating signal and noise in atmospheric temperature changes: The importance of timescale, J. Geophys. Res., 116, D22105, doi:10.1029/2011JD016263. [Full text]
Climate model shows skill in predicting decadal trends in global surface temperature
Skillful predictions of decadal trends in global mean surface temperature – Fyfe et al. (2011) “We compare observed decadal trends in global mean surface temperature with those predicted using a modelling system that encompasses observed initial condition information, externally forced response (due to anthropogenic greenhouse gases and aerosol precursors), and internally generated variability. We consider retrospective decadal forecasts for nine cases, initiated at five year intervals, with the first beginning in 1961 and the last in 2001. Forecast ensembles of size thirty are generated from differing but similar initial conditions. We concentrate on the trends that remain after removing the following natural signals in observations and hindcasts: dynamically induced atmospheric variability, El Nino-Southern Oscillation (ENSO), and the effects of explosive volcanic eruptions. We show that ensemble mean errors in the decadal trend hindcasts are smaller than in a parallel set of uninitialized free running climate simulations. The ENSO signal, which is skillfully predicted out to a year or so, has little impact on our decadal trend predictions, and our modelling system possesses skill, independent of ENSO, in predicting decadal trends in global mean surface temperature.” Fyfe, J. C., W. J. Merryfield, V. Kharin, G. J. Boer, W.-S. Lee, and K. von Salzen (2011), Geophys. Res. Lett., doi:10.1029/2011GL049508, in press.
Global warming might have inreased potato yield in Scotland
Attribution of climate change: a methodology to estimate the potential contribution to increases in potato yield in Scotland since 1960 – Gregory & Marshall (2011) “Maincrop potato yields in Scotland have increased by 30-35 t ha−1 since 1960 as a result of many changes, but has changing climate contributed anything to this? The purpose of this work was to answer this question. Daily weather data for the period 1960 to 2006 were analysed for five locations covering the zones of potato growing on the east coast of Scotland (between 55.213 and 57.646 N) to determine trends in temperature, rainfall and solar radiation. A physiologically-based potato yield model was validated using data obtained from a long-term field trial in eastern Scotland, and then employed to simulate crop development and potential yield at each of the five sites. Over the 47 years, there were significant increases in annual air and 30 cm soil temperatures (0.27 K decade−1 and 0.30 K decade−1 respectively), but no significant changes in annual precipitation or in the timing of the last frost in spring and the first frost of autumn. There was no evidence of any north to south gradient of warming. Simulated emergence and canopy closure became earlier at all five sites over the period with the advance being greater in the north (3.7 and 3.6 days decade−1 respectively) than the south (0.5 and 0.8 days decade−1 respectively). Potential yield increased with time, generally reflecting the increased duration of the green canopy, at average rates of 2.8 t ha−1 decade−1 for chitted seed (sprouted prior to planting) and 2.5 t ha−1 decade−1 for unchitted seed. The measured warming could contribute potential yield increases of up to 13.2 t ha−1 for chitted potato (range 7.1 – 19.3 t ha−1) and 11.5 t ha−1 for unchitted potato (range 7.1 – 15.5 t ha−1) equivalent to 34-39% of the increased potential yield over the period or 23-26% of the increase in actual measured yields.” P J Gregory, B Marshall, Global Change Biology, DOI: 10.1111/j.1365-2486.2011.02601.x.
Do tropical plant species experience cold-ward range shifts with global warming?
Distributional migrations, expansions, and contractions of tropical plant species as revealed in dated herbarium records – Feeley (2011) “Species are predicted to respond to global warming through “cold-ward” shifts in their geographic distributions due to encroachment into newly suitable habitats and/or dieback in areas that become climatically unsuitable. I conduct one of the first ever tests of this hypothesis for tropical plant species. I test for changes in the thermal distributions of 239 South American tropical plant species using dated herbarium records for specimens collected between 1970 and 2009. Supporting a priori predictions, many species (59%) exhibit some evidence of significant cold-ward range shifts even after correcting for collection biases. Over 1/3 of species (35%) show significant cold-ward movement in their hot thermal limits (mean rate of change = 0.022°C yr−1). Most of these species (85%; 30% of all study species) show no corresponding shift in their cold thermal limits. These unbalanced changes in the species’ thermal range limits may indicate species that are experiencing dieback due to their intolerance of rising temperatures coupled with an inability to expand into newly climatically-suitable habitats. On the other hand, 25% of species show significant cold-ward shifts in their cold thermal range limits (mean rate of change = 0.003°C yr−1), but 80% of these species (20% of all study species) show no corresponding shift in their hot thermal range limits. In these cases, the unbalanced shifts may indicate species that are able to “benefit” under global warming, at least temporally, by both tolerating rising temperatures and expanding into new suitable habitat. An important ancillary result of this study is that the number of species exhibiting significant range shifts was greatly influenced by shifting collector biases. This highlights the need to account for biases when analyzing natural history records or other long-term records.” Kenneth J. Feeley, Global Change Biology, DOI: 10.1111/j.1365-2486.2011.02602.x.
New study says semi-empirical sea level projections are robust
Testing the robustness of semi-empirical sea level projections – Rahmstorf et al. (2011) “We determine the parameters of the semi-empirical link between global temperature and global sea level in a wide variety of ways, using different equations, different data sets for temperature and sea level as well as different statistical techniques. We then compare projections of all these different model versions (over 30) for a moderate global warming scenario for the period 2000–2100. We find the projections are robust and are mostly within ±20% of that obtained with the method of Vermeer and Rahmstorf (Proc Natl Acad Sci USA 106:21527–21532, 2009), namely ~1 m for the given warming of 1.8°C. Lower projections are obtained only if the correction for reservoir storage is ignored and/or the sea level data set of Church and White (Surv Geophys, 2011) is used. However, the latter provides an estimate of the base temperature T 0 that conflicts with the constraints from three other data sets, in particular with proxy data showing stable sea level over the period 1400–1800. Our new best-estimate model, accounting also for groundwater pumping, is very close to the model of Vermeer and Rahmstorf (Proc Natl Acad Sci USA 106:21527–21532, 2009).” Stefan Rahmstorf, Mahé Perrette and Martin Vermeer, Climate Dynamics, DOI: 10.1007/s00382-011-1226-7.