Showing papers in "Earth’s Future in 2020"

Insights from CMIP6 for Australia's future climate

Abstract: Outputs from new state‐of‐the‐art climate models under the Coupled Model Inter‐comparison Project phase 6 (CMIP6) promise improvement and enhancement of climate change projections information for Australia. Here we focus on three key aspects of CMIP6: what is new in these models, how the available CMIP6 models evaluate compared to CMIP5, and their projections of the future Australian climate compared to CMIP5 focussing on the highest emissions scenario. The CMIP6 ensemble has several new features of relevance to policymakers and others, for example the integrated matrix of socio‐economic and concentration pathways. The CMIP6 models show incremental improvements in the simulation of the climate in the Australian region, including a reduced equatorial Pacific cold‐tongue bias, slightly improved rainfall teleconnections with large‐scale climate drivers, improved representation of atmosphere and ocean extreme heat events, as well as dynamic sea level. However, important regional biases remain, evident in the excessive rainfall over the Maritime Continent and rainfall pattern biases in the nearby tropical convergence zones. Projections of Australian temperature and rainfall from the available CMIP6 ensemble broadly agree with those from CMIP5, except for a group of CMIP6 models with higher climate sensitivity and greater warming and increase in some extremes after 2050. CMIP6 rainfall projections are similar to CMIP5, but the ensemble examined has a narrower range of rainfall change in austral summer in northern Australia and austral winter in southern Australia. Overall, future national projections are likely to be similar to previous versions but perhaps with some areas of improved confidence and clarity.

Why We Can No Longer Ignore Consecutive Disasters

Abstract: In recent decades, a striking number of countries have suffered from consecutive disasters: events whose impacts overlap both spatially and temporally, while recovery is still under way. The risk of consecutive disasters will increase due to growing exposure, the interconnectedness of human society, and the increased frequency and intensity of nontectonic hazard. This paper provides an overview of the different types of consecutive disasters, their causes, and impacts. The impacts can be distinctly different from disasters occurring in isolation (both spatially and temporally) from other disasters, noting that full isolation never occurs. We use existing empirical disaster databases to show the global probabilistic occurrence for selected hazard types. Current state-of-the art risk assessment models and their outputs do not allow for a thorough representation and analysis of consecutive disasters. This is mainly due to the many challenges that are introduced by addressing and combining hazards of different nature, and accounting for their interactions and dynamics. Disaster risk management needs to be more holistic and codesigned between researchers, policy makers, first responders, and companies.

Partitioning the uncertainty of ensemble projections of global glacier mass change

Abstract: Glacier mass loss is recognized as a major contributor to current sea level rise. However, large uncertainties remain in projections of glacier mass loss on global and regional scales. We present an ensemble of 288 glacier mass and area change projections for the 21st century based on 11 glacier models using up to 10 general circulation models and four Representative Concentration Pathways (RCPs) as boundary conditions. We partition the total uncertainty into the individual contributions caused by glacier models, general circulation models, RCPs, and natural variability. We find that emission scenario uncertainty is growing throughout the 21st century and is the largest source of uncertainty by 2100. The relative importance of glacier model uncertainty decreases over time, but it is the greatest source of uncertainty until the middle of this century. The projection uncertainty associated with natural variability is small on the global scale but can be large on regional scales. The projected global mass loss by 2100 relative to 2015 (79 ± 56 mm sea level equivalent for RCP2.6, 159 ± 86 mm sea level equivalent for RCP8.5) is lower than, but well within, the uncertainty range of previous projections.

Regional Climate Sensitivity of Climate Extremes in CMIP6 Versus CMIP5 Multimodel Ensembles

Abstract: We analyze projected changes in climate extremes (extreme temperatures and heavy precipitation) in the multimodel ensembles of the fifth and sixth Coupled Model Intercomparison Projects (CMIP5 and CMIP6). The results reveal close similarity between both ensembles in the regional climate sensitivity of the projected multimodel mean changes in climate extremes, that is, their projected changes as a function of global warming. This stands in contrast to widely reported divergences in global (transient and equilibrium) climate sensitivity in the two multimodel ensembles. Some exceptions include higher warming in the South America monsoon region, lower warming in Southern Asia and Central Africa, and higher increases in heavy precipitation in Western Africa and the Sahel region in the CMIP6 ensemble. The multimodel spread in regional climate sensitivity is found to be large in both ensembles. In particular, it contributes more to intermodel spread in projected regional climate extremes compared with the intermodel spread in global climate sensitivity in CMIP6. Our results highlight the need to consider regional climate sensitivity as a distinct feature of Earth system models and a key determinant of projected regional impacts, which is largely independent of the models' response in global climate sensitivity.

Projecting Exposure to Extreme Climate Impact Events Across Six Event Categories and Three Spatial Scales

Abstract: The extent and impact of climate-related extreme events depend on the underlying meteorological, hydrological, or climatological drivers as well as on human factors such as land use or population density. Here we quantify the pure effect of historical and future climate change on the exposure of land and population to extreme climate impact events using an unprecedentedly large ensemble of harmonized climate impact simulations from the Inter-Sectoral Impact Model Intercomparison Project phase 2b. Our results indicate that global warming has already more than doubled both the global land area and the global population annually exposed to all six categories of extreme events considered: river floods, tropical cyclones, crop failure, wildfires, droughts, and heatwaves. Global warming of 2°C relative to preindustrial conditions is projected to lead to a more than fivefold increase in cross-category aggregate exposure globally. Changes in exposure are unevenly distributed, with tropical and subtropical regions facing larger increases than higher latitudes. The largest increases in overall exposure are projected for the population of South Asia.

Increased flood exposure due to climate change and population growth in the United States

Abstract: Precipitation extremes are increasing globally due to anthropogenic climate change. However, there remains uncertainty regarding impacts upon flood occurrence and subsequent population exposure. Here, we quantify changes in population exposure to flood hazard across the contiguous United States. We combine simulations from a climate model large ensemble and a high‐resolution hydrodynamic flood model—allowing us to directly assess changes across a wide range of extreme precipitation magnitudes and accumulation timescales. We report a mean increase in the 100‐year precipitation event of ~20% (magnitude) and >200% (frequency) in a high warming scenario, yielding a ~30–127% increase in population exposure. We further find a nonlinear increase for the most intense precipitation events—suggesting accelerating societal impacts from historically rare or unprecedented precipitation events in the 21st century. Plain Language Summary Heavy rainfall is increasing globally due to human‐caused global warming. However, it is still unclear how these increases in heavy rainfall might affect flood risk. In this paper, we investigate how global warming and population changes together may be affecting the number of people at risk from floods in the United States. We combine simulations from a climatemodel and flood model—allowing us to consider a wide range of heavy rainfall events. We report a ~20% increase in the size and a >200% increase in the frequency of very heavy and rare rainfall events, which leads to a ~30–127% increase in the number of people at risk from floods. Finally, we find that the heaviest rainfall events increase by the widest margin—suggesting the possibility of major increases in damage and disruption caused by severe floods in the 21st century.

Integrating the Water Planetary Boundary With Water Management From Local to Global Scales

Abstract: The planetary boundaries framework defines the "safe operating space for humanity" represented by nine global processes that can destabilize the Earth System if perturbed. The water planetary boundary attempts to provide a global limit to anthropogenic water cycle modifications, but it has been challenging to translate and apply it to the regional and local scales at which water problems and management typically occur. We develop a cross-scale approach by which the water planetary boundary could guide sustainable water management and governance at subglobal contexts defined by physical features (e.g., watershed or aquifer), political borders (e.g., city, nation, or group of nations), or commercial entities (e.g., corporation, trade group, or financial institution). The application of the water planetary boundary at these subglobal contexts occurs via two approaches: (i) calculating fair shares, in which local water cycle modifications are compared to that context's allocation of the global safe operating space, taking into account biophysical, socioeconomic, and ethical considerations; and (ii) defining a local safe operating space, in which interactions between water stores and Earth System components are used to define local boundaries required for sustaining the local water system in stable conditions, which we demonstrate with a case study of the Cienaga Grande de Santa Marta wetlands in Colombia. By harmonizing these two approaches, the water planetary boundary can ensure that water cycle modifications remain within both local and global boundaries and complement existing water management and governance approaches.

Iran's Agriculture in the Anthropocene

Abstract: The anthropogenic impacts of development and frequent droughts have limited Iran's water availability. This has major implications for Iran's agricultural sector which is responsible for about 90% ...

Collaborative Modeling With Fine-Resolution Data Enhances Flood Awareness, Minimizes Differences in Flood Perception, and Produces Actionable Flood Maps

Abstract: Author(s): Sanders, BF; Schubert, JE; Goodrich, KA; Houston, D; Feldman, DL; Basolo, V; Luke, A; Boudreau, D; Karlin, B; Cheung, W; Contreras, S; Reyes, A; Eguiarte, A; Serrano, K; Allaire, M; Moftakhari, H; AghaKouchak, A; Matthew, RA | Abstract: ©2019. The Authors. Existing needs to manage flood risk in the United States are underserved by available flood hazard information. This contributes to an alarming escalation of flood impacts amounting to hundreds of billions of dollars per year and countless disrupted lives and affected communities. Making information about flood hazards useful for the range of decisions that dictate the consequences of flooding poses many challenges. Here, we describe collaborative flood modeling, whereby researchers and end-users at two coastal sites co-develop fine-resolution flood hazard models and maps responsive to decision-making needs. We find, first of all, that resident perception and awareness of flooding are enhanced more by fine-resolution depth contour maps than Federal Emergency Management Agency (FEMA) flood hazard classification maps and that viewing fine-resolution depth contour maps helps to minimize differences in flood perception across subgroups within the community, generating a shared understanding. We also find that collaborative flood modeling supports the engagement of a wide range of end-users in contemplating the risks of flooding and provides strong evidence that the co-produced knowledge can be readily adopted and applied for Flood Risk Management (FRM). Overall, collaborative flood modeling advances FRM by providing multiple points of entry for diverse groups of end-users to contemplate the spatial extent, intensity, timing, chance, and consequences of flooding, thus enabling the web of decision-making related to flooding to be better informed with the best available science. This transdisciplinary approach emphasizes vulnerability reduction and is complementary to FEMA Flood Insurance Rate Maps used for flood insurance administration.

The Role of Urban Growth in Resilience of Communities Under Flood Risk

Abstract: Flood risk to urban communities is increasing significantly as a result of the integrated effects of climate change and socioeconomic development. The latter effect is one of the main drivers of rising flood risk has received less attention in comparison to climate change. Economic development and population growth are major causes of urban expansion in flood-prone areas, and a comprehensive understanding of the impact of urban growth on flood risk is an essential ingredient of effective flood risk management. At the same time, planning for community resilience has become a national and worldwide imperative in recent years. Enhancements to community resilience require well-integrated and enormous long-term public and private investments. Accordingly, comprehensive urban growth plans should take rising flood risk into account to ensure future resilient communities through careful collaboration between engineers, geologists, socialists, economists, and urban planners within the framework of life-cycle analysis. This paper highlights the importance of including urban growth in accurate future flood risk assessment and how planning for future urbanization should include measurement science-based strategies in developing policies to achieve more resilient communities.

Future Drought in the Dry Lands of Asia Under the 1.5 and 2.0 °C Warming Scenarios

Abstract: Drought has become a major threat to local sustainable development in dryland Asia, one of the largest grassland ecosystems in the world. However, empirical- and science-based evidence regarding the extent of drought changes and the future trends of these changes in dryland Asia is variable and incomplete. Here, we first investigate the historical variations in drought conditions in dryland Asia, as measured by the drought intensity and arid area, using three widely used drought indices (the Palmer Drought Severity Index, the Standardized Precipitation Index, and the Standardized Precipitation Evapotranspiration Index). Then, we use Bayesian model averaging to reproduce the future drought conditions under two representative concentration pathways (RCP2.6 and RCP4.5) from the Coupled Model Intercomparison Project Phase 5 Earth system models. The Palmer Drought Severity Index, Standardized Precipitation Index, and Standardized Precipitation Evapotranspiration Index illustrate that dryland Asia has experienced an overall drying trend and an expansion of arid areas over the past 100 years (1901–2016). Both temperature and precipitation are projected to increase under both the 1.5 and 2.0 °C warming scenarios compared with the values from the reference period (1986–2005). The projected drought conditions in the 1.5 and 2.0 °C warming scenarios will worsen, especially across Kazakhstan and Northwest China. We found that the drought conditions under the 2.0 °C warming conditions will not be as severe as those under the 1.5 °C warming conditions due to the mitigating effect of the projected precipitation increase under RCP4.5. These results call for short-term and long-term mitigation and adaptation measurements for drought events in dryland Asia.

Intercomparison of Magnitudes and Trends in Anthropogenic Surface Emissions From Bottom-Up Inventories, Top-Down Estimates, and Emission Scenarios

Abstract: This study compares recent CO, NOx, NMVOC, SO2, BC, and OC anthropogenic emissions from several state-of-the-art top-down estimates to global and regional bottom-up inventories and projections from five Shared Socioeconomic Pathways (SSPs) in several regions. Results show that top-down emissions derived in several recent studies exhibit similar uncertainty as bottom-up inventories in some regions for certain species and even less in the case of Chinese CO emissions. In general, the largest discrepancies are found outside of regions such as the United States, Europe, and Japan where the most accurate and detailed information on emissions is available. In some regions such as China, which has recently undergone dynamical economic growth and changes in air quality regulations, the top-down estimates better capture recent emission trends than global bottom-up inventories. These results show the potential of top-down estimates to complement bottom-up inventories and to aide in the development of emission scenarios, particularly in regions where global inventories lack the necessary up-to-date and accurate information regarding regional activity data and emission factors such as Africa and India. Areas of future work aimed at quantifying and reducing uncertainty are also highlighted. A regional comparison of recent CO and NOx trends in the five SSPs indicate that SSP126, a strong pollution control scenario, best represents the trends from the top-down and regional bottom-up inventories in the United States, Europe, and China, while SSP460, a low-pollution control scenario, lies closest to actual trends in West Africa. This analysis can be useful for air quality forecasting and near-future pollution control/mitigation policy studies.

Robustness of CMIP6 Historical Global Mean Temperature Simulations: Trends, Long-Term Persistence, Autocorrelation, and Distributional Shape

Abstract: Multi‐model climate experiments carried out as part of different phases of the Coupled Model Intercomparison Project (CMIP) are crucial to evaluate past and future climate change. The reliability of models' simulations is often gauged by their ability to reproduce the historical climate across many time scales. This study compares the global mean surface air temperature from 29 CMIP6 models with observations from three datasets. We examine (1) warming and cooling rates in five subperiods from 1880 to 2014, (2) autocorrelation and long‐term persistence, (3) models' performance based on probabilistic and entropymetrics, and (4) the distributional shape of temperature. All models simulate the observed long‐term warming trend from 1880 to 2014. The late twentieth century warming (1975–2014) and the hiatus (1942–1975) are replicated by most models. The post‐1998 warming is overestimated in 90% of the simulations. Only six out of 29 models reproduce the observed long‐term persistence. All models show differences in distributional shape when compared with observations. Varying performance across metrics reveals the challenge to determine the “best” model. Thus, we argue that models should be selected, based on case‐specific metrics, depending on the intended use. Metrics proposed here facilitate a comprehensive assessment for various applications.

Future Transboundary Water Stress and Its Drivers Under Climate Change: A Global Study

Abstract: Various transboundary river basins are facing increased pressure on water resources in near future. However, little is known ab out the future drivers globally, namely, changes in natural local runoff and natural inflows from upstream parts of a basin, as well as local and upstream water consumption. Here we use an ensemble of four global hydrological models forced by five global climate models and the latest greenhouse-gas concentration (RCP) and socioeconomic pathway (SSP) scenarios to assess the impact of these drivers on transboundary water stress in the past and future. Our results show that population under water stress is expected to increase by 50% under a low population growth and emissions scenario (SSP1-RCP2.6) and double under a high population growth and emission scenario (SSP3-RCP6.0), compared to the year 2010. As changes in water availability have a smaller effect when water is not yet scarce, changes in water stress globally are dominated by local water consumption-managing local demand is thus necessary in order to avoid future stress. Focusing then on the role of upstream changes, we identified upstream availability (i.e., less natural runoff or increased water consumption) as the dominant driver of changes in net water availability in most downstream areas. Moreover, an increased number of people will be living in areas dependent on upstream originating water in 2050. International water treaties and management will therefore have an increasingly crucial role in these hot spot regions to ensure fair management of transboundary water resources.

“Certain uncertainty: The role of internal climate variability in projections of regional climate change and risk management”

Abstract: Internal climate variability co‐exists with anthropogenic climate change and places limits on the accuracy of regional climate projections due to its inherent unpredictability. This “certain” uncertainty in regional projections introduced by internal variability contrasts with uncertainty resulting from structural differences amongst climate models, which is potentially reducible as climate models improve. Initial‐condition “Large Ensembles” of simulations with individual climate models provide a new perspective on the expected range of future climate change outcomes. Their value for climate risk assessment, adaptation management, and decision‐making has yet to be fully realized.

Exploring the Drivers of Global and Local Sea-Level Change Over the 21st Century and Beyond

Abstract: We present a new set of global and local sea-level projections at example tide gauge locations under the RCP26, RCP45 and RCP85 emissions scenarios Compared to the CMIP5-based sealevel projections presented in IPCC AR5, we introduce a number of methodological innovations, including: (i) more comprehensive treatment of uncertainties; (ii) direct traceability between global and local projections; (iii) exploratory extended projections to 2300 based on emulation of individual CMIP5 models Combining the projections with observed tide gauge records, we explore the contribution to total variance that arises from sea-level variability, different emissions scenarios and model uncertainty For the period out to 2300 we further breakdown the model uncertainty by sea-level component and consider the dependence on geographic location, time horizon and emissions scenario Our analysis highlights the importance of variability for sea-level change in the coming decades and the potential value of annual-to-decadal predictions of local sea-level change Projections to 2300 show a substantial degree of committed sea-level rise under all emissions scenarios considered and highlights the reduced future risk associated with RCP26 and RCP45 compared to RCP85 Tide gauge locations can show large (> 50%) departures from the global average, in some cases even reversing the sign of the change While uncertainty in projections of the future Antarctic ice dynamic response tends to dominate post2100, we see a substantial differences in the breakdown of model variance as a function of location, timescale and emissions scenario

The state of the art in modeling waterlogging impacts on plants: what do we know and what do we need to know

Abstract: Models are key tools in our quest to better understand the impacts of soil waterlogging on plant growth and crop production. Here, we reviewed the state of the art of modeling approaches and compared the conceptual design of these models with recent experimental findings. We show that many models adopt an aeration stress (AS) principle where surplus water reduces air‐filled porosity, with implications for root growth. However, subsequent effects of AS within each model vary considerably. In some cases, AS inhibits biomass accumulation (e.g. AquaCrop), altering processes prior to biomass accumulation such as light interception (e.g. APSIM), or photosynthesis and carbohydrate accumulation (e.g. SWAGMAN Destiny). While many models account for stage‐dependent waterlogging effects, few models account for experimentally observed delays in phenology caused by waterlogging. A model intercomparison specifically designed for long‐term waterlogged conditions (APSIM‐Oryza) with models developed for dryland conditions with transient waterlogging would advance our understanding of the current fitness for purpose of exsiting frameworks for simulating transient waterlogging in dryland cropping systems. Of the point‐based dynamic models examined here, APSIM‐Soybean and APSIM‐Oryza simulations most closely matched with the observed data, while GLAM‐WOFOST achieved the highest performance of the spatial‐regional models examined. We conclude that future models should incorporate waterlogging effects on genetic tolerance parameters such as (1) phenology of stress onset, (2) aerenchyma, (3) root hydraulic conductance, (4) nutrient‐use efficiency, and (5) plant ion (e.g. Fe/Mn) tolerance. Incorporating these traits/effects into models, together with a more systematic model intercomparison using consistent initialization data, will significantly improve our understanding of the relative importance of such factors in a systems context, including feedbacks between biological factors, emergent properties, and sensitive variables responsible for yield losses under waterlogging.

Projected Changes in Reference Evapotranspiration in California and Nevada: Implications for Drought and Wildland Fire Danger

Abstract: Author(s): McEvoy, Daniel J; Pierce, David W; Kalansky, Julie F; Cayan, Daniel R; Abatzoglou, John T

Implications of CMIP6 Projected Drying Trends for 21st Century Amazonian Drought Risk

Abstract: Recent exceptionally hot droughts in Amazonia have highlighted the potential role of global warming in driving elevated fire risk and forest dieback. The previous generation of global climate model...