Building the Global Adaptation Community

Given the severe impacts of hot summers on human and natural systems, we attempt to quantify future changes in extreme hot summer frequency in China using the Coupled Model Intercomparison Project Phase 5 (CMIP5) projections. Unlike previous studies focusing on fixed future time slices, we investigate the changes as a function of global mean temperature (GMT) rise. Analyses show that extreme hot summers (June-July-August mean temperature higher than 90 % quantile of 1971–2000 climatology) are projected to occur at least 80 % of the time across China with a GMT rise of 2 °C. The fraction of land area with extreme hot summers becoming the norm (median of future summer temperatures exceed the extreme) will increase from ~15 % with 0.5 °C of GMT rise to ~97 % with 2.5 °C GMT rise, which is much greater than for the global land surface as a whole. A distinct spatial pattern of the GMT rise threshold over which the local extreme hot summer first becomes the norm is revealed. When averaged over the country, the GMT rise threshold is 0.96 °C. Earth system models exhibit comparable results to climate system models, but with a relatively larger spread. Further analysis shows that the concurrence of hot and dry summers will increase significantly with the spatial structure of responses depending on the definition of drying. The increase of concurrent hot and dry conditions will induce potential droughts which would be more severe than those induced by only precipitation deficits.

Abstract. The Mekong River Basin is a key regional resource in Southeast Asia for sectors that include agriculture, fisheries and electricity production. Here we explore the potential impacts of climate change on freshwater resources within the river basin. We quantify uncertainty in these projections associated with GCM structure and climate sensitivity, as well as from hydrological model parameter specification. This is achieved by running pattern-scaled GCM scenarios through a semi-distributed hydrological model (SLURP) of the basin. Pattern-scaling allows investigation of specific thresholds of global climate change including the postulated 2 °C threshold of "dangerous" climate change. Impacts of a 2 °C rise in global mean temperature are investigated using seven different GCMs, providing an implicit analysis of uncertainty associated with GCM structure. Analysis of progressive changes in global mean temperature from 0.5 to 6 °C above the 1961–1990 baseline (using the HadCM3 GCM) reveals a relatively small but non-linear response of annual river discharge to increasing global mean temperature, ranging from a 5.4 % decrease to 4.5 % increase. Changes in mean monthly river discharge are greater (from −16 % to +55 %, with greatest decreases in July and August, greatest increases in May and June) and result from complex and contrasting intra-basin changes in precipitation, evaporation and snow storage/melt. Whilst overall results are highly GCM dependent (in both direction and magnitude), this uncertainty is primarily driven by differences in GCM projections of future precipitation. In contrast, there is strong consistency between GCMs in terms of both increased potential evapotranspiration and a shift to an earlier and less substantial snowmelt season. Indeed, in the upper Mekong (Lancang sub-basin), the temperature-related signal in discharge is strong enough to overwhelm the precipitation-related uncertainty in the direction of change in discharge, with scenarios from all GCMs leading to increased river flow from April–June and decreased flow from July–August.

Temperature-related excess mortality in German cities at 2 °C and higher degrees of global warming

Recent studies based on the ensemble mean of Coupled Model Intercomparison Project 6 (CMIP6) General Circulation Models (GCMs, CMIP6‐GCMs hereafter) reported a decline in drought frequency over South Asia in the projected future climate. Here using the simulations from 16 CMIP6‐GCMs, we examine the potential causes of declining droughts in South Asia. We show that the projections based on the multimodel ensemble mean CMIP6‐GCMs are not reliable over South Asia. The multimodel ensemble mean is influenced mainly by the low‐skill GCMs, which show high bias in simulating the monsoon (June–September) season precipitation during the observed period (1951–2014). The low‐skill GCMs show a higher (20–30%) increase in the convective precipitation with a rise in the global mean temperature under the warming (1.5°C, 2.0°C, and 2.5°C worlds) climate. The GCMs with less bias (BEST‐GCMs) in the monsoon season precipitation and better seasonal cycle representation show lower sensitivity of convective precipitation to rise in global mean temperature. BEST‐GCMs exhibit significantly different projections in comparison to the multimodel ensemble mean from all 16 GCMs (ALL‐GCMs). In contrast to ALL‐GCMs, BEST‐GCMs project an increase in the frequency of droughts in South Asia under the future climate. Therefore, the projected risk of droughts over South Asia under the 1.5°C, 2.0°C, and 2.5°C warming levels is higher than previously reported based on the ensemble mean of CMIP6‐GCMs. A projected increase in the drought frequency in South Asia will have considerable implications for agricultural production and water availability.

Steep rise in the earth’s atmospheric CO2 concentration is the main concerned problem nowadays. Presently, the earth’s atmosphere contains nearly 397.34 ppmv of CO2 which is much higher than the natural range of CO2 (180–300 ppmv) that existed over millions of years. Anthropogenic CO2 emission exceeds the natural sink of CO2 such as CO2 solubility in ocean, photosynthetic removal of CO2 by ocean phytoplanktons, and terrestrial plants. Increase in CO2 may be correlating with the rise in global mean temperature. This in turn is associated with melting of glaciers, rise in sea level, ocean acidification, unpredicted climate changes, etc. Rise in sea level and temperatures has been observed in the past also, but the rates of increase in these parameters are the main indicator of the effect of corresponding increase in CO2 concentration. The present chapter summarizes the role of various biological processes available for CO2 mitigation. Use of terrestrial plants, algae, cyanobacteria, carbonic anhydrase (CA) enzyme, and various other bacteria in CO2 sequestration has been extensively discussed. Chemical fixation of CO2 in the form of carbonates is a safe and permanent natural process. CA catalyzes the CO2 hydration reaction and accelerates the transformation of CO2 into solid carbonates manifold. Terrestrial plants for CO2 sequestration are limited only to lower range of CO2 concentration. Forest fertilization has been found to increase the CO2 mitigation two- to threefold. Contrary to terrestrial plants, algae and cyanobacteria can be used at higher CO2 concentration with higher photosynthetic efficiency.KeywordsCarbonic AnhydraseThylakoid MembraneDissolve Inorganic CarbonCalvin CyclePurple BacteriumThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The validity of the manmade global warming alarm requires the support of scientific forecasts of (1) a substantive long-term rise in global mean temperatures in the absence of regulations, (2) serious net harmful effects due to global warming, and (3) cost-effective regulations that would produce net beneficial effects versus alternatives policies, including doing nothing. Without scientific forecasts for all three aspects of the alarm, there is no scientific basis to enact regulations. In effect, the warming alarm is like a three-legged stool: Each leg needs to be strong. Despite repeated appeals to global warming alarmists, we have been unable to find scientific forecasts for any of the three legs. We drew upon scientific (evidence-based) forecasting principles to audit the forecasting procedures used to forecast global mean temperatures by the Intergovernmental Panel on Climate Change (IPCC) — leg “1” of the stool. This audit found that the IPCC procedures violated 81% of the 89 relevant forecasting principles. We also audited forecasting procedures, used in two papers, that were written to support regulation regarding the protection of polar bears from global warming — leg “3” of the stool. On average, the forecasting procedures violated 85% of the 90 relevant principles. The warming alarmists have not demonstrated the predictive validity of their procedures. Instead, their argument for predictive validity is based on their claim that nearly all scientists agree with the forecasts. This count of “votes” by scientists is not only an incorrect tally of scientific opinion, it is also, and most importantly, contrary to the scientific method. We conducted a validation test of the IPCC forecasts that were based on the assumption that there would be no regulations. The errors for the IPCC model long-term forecasts (for 91 to 100 years in the future) were 12.6 times larger than those from an evidence-based “no change” model. Based on our own analyses and the documented unscientific behavior of global warming alarmists, we concluded that the global warming alarm is the product of an anti-scientific political movement. Having come to this conclusion, we turned to the “structured analogies” method to forecast the likely outcomes of the warming alarmist movement. In our ongoing study we have, to date, identified 26 similar historical alarmist movements. None of the forecasts behind the analogous alarms proved correct. Twenty-five alarms involved calls for government intervention and the government imposed regulations in 23. None of the 23 interventions was effective and harm was caused by 20 of them. Our findings on the scientific evidence related to global warming forecasts lead to the following recommendations: End government funding for climate change research. End government funding for research predicated on global warming (e.g., alternative energy; CO2 reduction; habitat loss). End government programs and repeal regulations predicated on global warming. End government support for organizations that lobby or campaign predicated on global warming.

Climate change impacts and implications towards ecosystems and biodiversity, water resources, food production, and infrastructures can be mitigated through adapting, reducing or avoiding adverse impacts and maximizing positive consequences. It can have numerous effects on the world’s natural ecosystems and their functions. IPCC projections showed approximately 10% of species to be at an increasing high risk of extinction for every 1 °C rise in global mean temperature and recommended to limit global temperatures below 1.5 °C. To identify consequences of climate change, impacts, and implications, data collected from different sources, reviewed, assessed and analyzed, discussing dimensional impacts and mitigation strategies adopted. Nepal’s 118 major ecosystems and 75 vegetation types with 44.74% forestland comprising 0.1% of global landmass harboring 3.2% flora and 1.1% fauna of the world’s biodiversity critically influenced by the regional climate change and intervention of developmental projects. Since 2000, Nepal lost forest area by 2.1% including several endangered and threatened species. Nepal is highly vulnerable towards natural disasters like GLOF, Glacier retreat, flooding, landslide and global warming. Therefore, it is crucial to plan climate resilience infrastructures adopting effective environmental management tools, formulation of strong plan, policy and strategy, mitigation of greenhouse gases, climate resilient adaptation and restoration of degraded ecosystems.

Summer outdoor temperature and occupational heat-related illnesses in Quebec (Canada)

The salient feature of anthropogenic climate change over the last century has been the rise in global mean temperature. However, global mean temperature is not used as an explanatory variable in studies of population-level response to climate change, perhaps because the signal-to-noise ratio of this gross measure makes its effect difficult to detect in any but the longest of datasets. Using a population of Leach's storm-petrels breeding in the Bay of Fundy, we tested whether local, regional, or global temperature measures are the best index of reproductive success in the face of climate change in species that travel widely between and within seasons. With a 56-year dataset, we found that annual global mean temperature (AGMT) was the single most important predictor of hatching success, more so than regional sea surface temperatures (breeding season or winter) and local air temperatures at the nesting colony. Storm-petrel reproductive success showed a quadratic response to rising temperatures, in that hatching success increased up to some critical temperature, and then declined when AGMT exceeded that temperature. The year at which AGMT began to consistently exceed that critical temperature was 1988. Importantly, in this population of known-age individuals, the impact of changing climate was greatest on inexperienced breeders: reproductive success of inexperienced birds increased more rapidly as temperatures rose and declined more rapidly after the tipping point than did reproductive success of experienced individuals. The generality of our finding that AGMT is the best predictor of reproductive success in this system may hinge on two things. First, an integrative global measure may be best for species in which individuals move across an enormous spatial range, especially within seasons. Second, the length of our dataset and our capacity to account for individual- and age-based variation in reproductive success increase our ability to detect a noisy signal.

The past three decades have seen an unprecedented increase in world living standards and a fall in poverty across many fundamental dimensions. Increased confidence in what was possible together with greater acceptance of moral responsibilities led to the adoption of the Millennium Development Goals (MDGs) at the turn of the century. They provided a real basis for international cooperation and development. In the Sustainable Development Goals (SDGs), agreed in September 2015, there is now a common platform for the next phase of the fight against poverty. The SDGs make it clear that environmental protection will be a key feature of this next phase and increasingly intertwined with poverty reduction. Thirteen of the 17 SDGs are directly concerned with the natural environment, climate or sustainability. Environment, climate and sustainability were not prominent in the MDGs. With hindsight we can now see that this was a mistake. A key factor in all this is climate change. Climate change is not the only environmental problem we face, nor is it the only threat to global prosperity. But climate change is unique in its magnitude and the vast risks it poses. It is a potent threat-multiplier for other urgent concerns, such as habitat loss, disease and global security (IPCC 2014) and puts at risk the development achievements of the past decades (World Bank 2016). If unchecked, climate change could fundamentally redraw the map of the planet, and where and how humans and other species can live. Climate change is also unique in the scale of the response that is needed. Reducing climate risks requires cooperation from all countries, developed and developing, to reorient their economic systems away from fossil fuels and harmful land-use practices. This reorientation is urgent. Our activities in the next two decades will determine whether our successes in development will be sustained or advanced, or whether they will be undermined or reversed in a hostile environment. The nature of the climate problem has implications for economic analysis. Economics has much to offer, and indeed continues to provide important insights, but there has been a dangerous tendency to force climate change into narrow existing ways of thinking. This must change. We need to construct theories and models that reflect the structure and scale of the problem and the contexts in which it occurs. Climate change also has implications for development policy. In the Paris Agreement, negotiated at the end of 2015,there is now an international platform through which global climate action can be advanced and coordinated. The Paris Agreement sets out a process through which the rise in global mean temperatures may be curtailed to 'well below' 2oC above pre-industrial levels and perhaps as low as 1.5oC. These are the central long-term objectives of the agreement. Meeting the Paris objectives requires sustained action over many decades. It also requires the reorientation of investment. At least US$ 100 trillion will be invested over the next two or three decades into buildings and urban infrastructure, roads, railways, ports and into new energy systems. It is imperative that these investment decisions are taken with climate change in mind. If they are there will be substantial benefits for development and poverty reduction – living spaces where we can move, breathe and be productive, better protection for fragile ecosystems, as well as the fundamental reduction of the risks of climate change. Putting the SDGs and Paris together, the agreements of 2015 have given us, for the first time, a global agenda for sustainable development applying to all countries. This paper sets out the implications of this agenda, and climate change in particular, for development economics and development policy. It emphasizes the nature of the required changes and their implications. We start with an examination of what economics has had to say about the link between economic prosperity and the environment. We then explain why climate change is a different kind of problem and why it requires a new approach to both analysis and policy. The final two sections explore how this new approach might look.

Beyond water vapor, the three most important greenhouse gases (GHGs) in terms of their radiative forcing are carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Increasing concentrations of these gases driven by human activities are the primary cause of the observed climate change according to the Intergovernmental Panel on Climate Change (ref AR6 WG1). The Paris Agreement, adopted by 196 countries at the UNFCCC Conference of the Parties in 2015, sets specific targets for maximum rise in global mean temperature and identifies reduction in net greenhouse emissions as the primary means to achieve this target.However, even very accurate estimates of anthropogenic emissions alone will not be enough to design meaningful mitigation efforts or to monitor their effectiveness. Greenhouse gas concentrations are influenced by both natural and anthropogenic processes, and some of the natural carbon sources and sinks in particular are associated with very large uncertainties, both as they currently operate and as they may change in the future in response to climate change. Sustained, routine monitoring of greenhouse gas concentrations, using monitoring of weather and climate as a paradigm and role model, will provide a wealth of quantitative data to help constrain the modelling of all parts of the carbon cycle. This will be extremely valuable for the work of the World Climate Research Programme (WCRP) and IPCC, it will complement and supplement existing methodologies used to estimate anthropogenic emissions, and it will help put mitigation steps taken by Parties to the Paris Agreement on a solid scientific footing. This presentation introduces a WMO-coordinated effort to establish an operational Global Greenhouse Monitoring Infrastructure to directly observe and model greenhouse gas concentrations in the atmosphere, and thereby support/enable estimates of net greenhouse gas fluxes between atmosphere, land, and oceans. The atmospheric component of this infrastructure builds on the research infrastructure for greenhouse gas observations and modelling supported by WMO since 1975, and promotes its operationalization and further advancement by utilizing the existing infrastructure and methodologies employed for more than 50 years for operational weather forecasting. 

Past studies quantifying the burden of heat-related mortality attributable to climate change have mostly focused on specific extreme events or considered multi-decadal averages. Here, we contribute to the scarce literature on the attribution of observed temporal trends in heat-related mortality to climate change. Our study is based on daily all-cause mortality time-series from 15 major German cities over 1993-2020. Counterfactual climate data is derived from century-long measurement series of daily mean temperatures by removing trends related to the observed rise in global mean temperature according to the ATTRICI method. We use quasi-Poisson regression models including distributed lag non-linear models and multivariate meta-regression models to estimate temperature mortality associations. Our results corroborate previous model-based estimates, suggesting that, averaged over the entire study period, 28% (95%CI: 17%, 42%) of warm-season (May-Sep) heat-related excess mortality across all German cities were attributable to climate change. Considering linear temporal trends suggests that this proportion has increased by 4.0±1.0% per decade. Under observed climate change, we find a linear increase of 174 (SE: ±151) heat-associated deaths per decade across cities. By contrast, our results suggest that without climate change there would not have been a significant increase in heat associated deaths. Overall, our study provides evidence of increasing impacts of climate change on heat-related mortality in Germany since the 1990s. As temperatures keep rising in the future, climate change is expected to drive further increases in heat-related excess mortality unless additional adaptive measures are taken.

21st century climate change is projected to result in an intensification of the global hydrological cycle, but there is substantial uncertainty in how this will impact freshwater availability. A relatively overlooked aspect of this uncertainty pertains to how different methods of estimating potential evapotranspiration (PET) respond to changing climate. Here we investigate the global response of six different PET methods to a 2°C rise in global mean temperature. All methods suggest an increase in PET associated with a warming climate. However, differences in PET climate change signal of over 100% are found between methods. Analysis of a precipitation/PET aridity index and regional water surplus indicates that for certain regions and GCMs, choice of PET method can actually determine the direction of projections of future water resources. As such, method dependence of the PET climate change signal is an important source of uncertainty in projections of future freshwater availability.

Climate models vary widely in their projections of both global mean temperature rise and regional climate changes, but are there any systematic differences in regional changes associated with different levels of global climate sensitivity? This paper examines model projections of climate change over the twenty-first century from the Intergovernmental Panel on Climate Change Fourth Assessment Report which used the A2 scenario from the IPCC Special Report on Emissions Scenarios, assessing whether different regional responses can be seen in models categorized as 'high-end' (those projecting 4°C or more by the end of the twenty-first century relative to the preindustrial). It also identifies regions where the largest climate changes are projected under high-end warming. The mean spatial patterns of change, normalized against the global rate of warming, are generally similar in high-end and 'non-high-end' simulations. The exception is the higher latitudes, where land areas warm relatively faster in boreal summer in high-end models, but sea ice areas show varying differences in boreal winter. Many continental interiors warm approximately twice as fast as the global average, with this being particularly accentuated in boreal summer, and the winter-time Arctic Ocean temperatures rise more than three times faster than the global average. Large temperature increases and precipitation decreases are projected in some of the regions that currently experience water resource pressures, including Mediterranean fringe regions, indicating enhanced pressure on water resources in these areas.

Chapter 7 - Impacts of Climate Change on Agriculture and Food Security