Climate sensitivity uncertainty : When is good news bad?

Climate change is real and dangerous. Exactly how bad it will get, however, is uncertain. Uncertainty is particularly relevant for estimates of one of the key parameters: equilibrium climate sensitivity—how eventual temperatures will react as atmospheric carbon dioxide concentrations double. Despite significant advances in climate science and increased confidence in the accuracy of the range itself, the “likely” range has been 1.5-4.5°C for over three decades. In 2007, the Intergovernmental Panel on Climate Change (IPCC) narrowed it to 2-4.5°C, only to reverse its decision in 2013, reinstating the prior range. In addition, the 2013 IPCC report removed prior mention of 3°C as the “best estimate.” We interpret the implications of the 2013 IPCC decision to lower the bottom of the range and excise a best estimate. Intuitively, it might seem that a lower bottom would be good news. Here we ask: When might apparently good news about climate sensitivity in fact be bad news in the sense that it lowers societal wellbeing? The lowered bottom value also implies higher uncertainty about the temperature increase, a definite bad. Under reasonable assumptions, both the lowering of the lower bound and the removal of the “best estimate” may well be bad news

Intercomparison of the northern hemisphere winter mid-latitude atmospheric variability of the IPCC models

We compare, for the overlapping time frame 1962-2000, the estimate of the northern hemisphere (NH) mid-latitude winter atmospheric variability within the XX century simulations of 17 global climate models (GCMs) included in the IPCC-4AR with the NCEP and ECMWF reanalyses. We compute the Hayashi spectra of the 500hPa geopotential height fields and introduce an integral measure of the variability observed in the NH on different spectral sub-domains. Only two high-resolution GCMs have a good agreement with reanalyses. Large biases, in most cases larger than 20%, are found between the wave climatologies of most GCMs and the reanalyses, with a relative span of around 50%. The travelling baroclinic waves are usually overestimated, while the planetary waves are usually underestimated, in agreement with previous studies performed on global weather forecasting models. When comparing the results of various versions of similar GCMs, it is clear that in some cases the vertical resolution of the atmosphere and, somewhat unexpectedly, of the adopted ocean model seem to be critical in determining the agreement with the reanalyses. The GCMs ensemble is biased with respect to the reanalyses but is comparable to the best 5 GCMs. This study suggests serious caveats with respect to the ability of most of the presently available GCMs in representing the statistics of the global scale atmospheric dynamics of the present climate and, a fortiori, in the perspective of modelling climate change.Comment: 39 pages, 8 figures, 2 table

Dominant role of greenhouse-gas forcing in the recovery of Sahel rainfall

Sahelian summer rainfall, controlled by the West African monsoon, exhibited large-amplitude multidecadal variability during the twentieth century. Particularly important was the severe drought of the 1970s and 1980s, which had widespread impacts1–6. Research into the causes of this drought has identified anthropogenic aerosol forcing3,4,7 and changes in sea surface temperatures (SSTs; refs 1,2,6,8–11) as the most important drivers. Since the 1980s, there has been some recovery of Sahel rainfall amounts2–6,11–14, although not to the pre-drought levels of the 1940s and 1950s. Here we report on experiments with the atmospheric component of a state-of-the-art global climate model to identify the causes of this recovery. Our results suggest that the direct influence of higher levels of greenhouse gases in the atmosphere was the main cause, with an additional role for changes in anthropogenic aerosol precursor emissions. We find that recent changes in SSTs, although substantial, did not have a significant impact on the recovery. The simulated response to anthropogenic greenhouse-gas and aerosol forcing is consistent with a multivariate fingerprint of the observed recovery, raising confidence in our findings. Although robust predictions are not yet possible, our results suggest that the recent recovery in Sahel rainfall amounts is most likely to be sustained or amplified in the near term

Relationship between the expansion of drylands and the intensification of Hadley circulation during the late twentieth century

The changes in coverage by arid climate and intensity of the Hadley circulation during the second half of the twentieth century were examined using observations and the multi-model ensemble (MME) mean of Twentieth-Century Coupled Climate Model (20C3M) simulations. It was found that the area of dry climate, which comprises steppe and desert climates following the Köppen climate classification, expanded to an appreciable extent in observation and, to a lesser degree, in MME simulation. The areal extent of steppe climate (the outer boundary of arid climate) tends to encroach on the surrounding climate groups, which, in turn, feeds desert climate (the inner part of arid climate) and causes it to grow. This result indicates the importance of accurate prediction for climate regimes that border steppe climate. Concomitant with the expansion of drylands, the observed intensity of the Hadley cell is persistently enhanced, particularly during boreal winter, suggesting the validity of a self-induction of deserts through a positive biogeophysical feedback (also known as Charney’s cycle). In comparison, the simulated Hadley circulation in the MME mean remains invariant in time. The current climate models, therefore, disagree with the observation in the long-term linkage between desertification and Hadley cell. Finally, the implication of such discrepancy is discussed as a possible guidance to improve models

The roles of static stability and tropical – extratropical interactions in the summer interannual variability of the North Atlantic sector

Summer seasonal forecast skill in the North Atlantic sector is lower than winter skill. To identify potential controls on predictability, the sensitivity of North Atlantic baroclinicity to atmospheric drivers is quantified. Using ERA-INTERIM reanalysis data, North Atlantic storm-track baroclinicity is shown to be less sensitive to meridional temperature-gradient variability in summer. Static stability shapes the sector’s interannual variability by modulating the sensitivity of baroclinicity to variations in meridional temperature gradients and tropopause height and by modifying the baroclinicity itself. High static stability anomalies at upper levels result in more zonal extratropical cyclone tracks and higher eddy kinetic energy over the British Isles in the summertime. These static stability anomalies are not strongly related to the summer NAO; but they are correlated with the suppression of convection over the tropical Atlantic and with a poleward-shifted subtropical jet. These results suggest a non-local driver of North Atlantic variability. Furthermore, they imply that improved representations of convection over the south-eastern part of North America and the tropical Atlantic might improve summer seasonal forecast skill

The resolution sensitivity of the Asian summer monsoon and its inter-model comparison between MRI-AGCM and MetUM

In this study, we compare the resolution sensitivity of the Asian Summer Monsoon (ASM) in two Atmospheric General Circulation Models (AGCMs): the MRI-AGCM and the MetUM. We analyze the MetUM at three different resolutions, N96 (approximately 200-km mesh on the equator), N216 (90-km mesh) and N512 (40-km mesh), and the MRI-AGCM at TL95 (approximately 180-km mesh on the equator), TL319 (60-km mesh), and TL959 (20-km mesh). The MRI-AGCM and the MetUM both show decreasing precipitation over the western Pacific with increasing resolution, but their precipitation responses differ over the Indian Ocean. In MRI-AGCM, a large precipitation increase appears off the equator (5–20°N). In MetUM, this off-equatorial precipitation increase is less significant and precipitation decreases over the equator. Moisture budget analysis demonstrates that a changing in moisture flux convergence at higher resolution is related to the precipitation response. Orographic effects, intra-seasonal variability and the representation of the meridional thermal gradient are explored as possible causes of the resolution sensitivity. Both high-resolution AGCMs (TL959 and N512) can represent steep topography, which anchors the rainfall pattern over south Asia and the Maritime Continent. In MRI-AGCM, representation of low pressure systems in TL959 also contributes to the rainfall pattern. Furthermore, the seasonal evolution of the meridional thermal gradient appears to be more accurate at higher resolution, particularly in the MRI-AGCM. These findings emphasize that the impact of resolution is only robust across the two AGCMs for some features of the ASM, and highlights the importance of multi-model studies of GCM resolution sensitivity

Assimilating Seizure Dynamics

Observability of a dynamical system requires an understanding of its state—the collective values of its variables. However, existing techniques are too limited to measure all but a small fraction of the physical variables and parameters of neuronal networks. We constructed models of the biophysical properties of neuronal membrane, synaptic, and microenvironment dynamics, and incorporated them into a model-based predictor-controller framework from modern control theory. We demonstrate that it is now possible to meaningfully estimate the dynamics of small neuronal networks using as few as a single measured variable. Specifically, we assimilate noisy membrane potential measurements from individual hippocampal neurons to reconstruct the dynamics of networks of these cells, their extracellular microenvironment, and the activities of different neuronal types during seizures. We use reconstruction to account for unmeasured parts of the neuronal system, relating micro-domain metabolic processes to cellular excitability, and validate the reconstruction of cellular dynamical interactions against actual measurements. Data assimilation, the fusing of measurement with computational models, has significant potential to improve the way we observe and understand brain dynamics

Environmental controls, oceanography and population dynamics of pathogens and harmful algal blooms: connecting sources to human exposure

© 2008 Author et al. This is an open access article distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Environmental Health 7 (2008): S5, doi:10.1186/1476-069X-7-S2-S5.Coupled physical-biological models are capable of linking the complex interactions between environmental factors and physical hydrodynamics to simulate the growth, toxicity and transport of infectious pathogens and harmful algal blooms (HABs). Such simulations can be used to assess and predict the impact of pathogens and HABs on human health. Given the widespread and increasing reliance of coastal communities on aquatic systems for drinking water, seafood and recreation, such predictions are critical for making informed resource management decisions. Here we identify three challenges to making this connection between pathogens/HABs and human health: predicting concentrations and toxicity; identifying the spatial and temporal scales of population and ecosystem interactions; and applying the understanding of population dynamics of pathogens/HABs to management strategies. We elaborate on the need to meet each of these challenges, describe how modeling approaches can be used and discuss strategies for moving forward in addressing these challenges.The authors acknowledge the financial support for the NSF/NIEHS and NOAA Centers for Oceans and Human Healt