Anthropogenic warming induced intensification of summer monsoon frontal precipitation over East Asia.

Summer monsoon frontal rainfall in East Asia (EA) is crucial for water resources and flood hazards in densely populated areas. Recent studies have documented the increasing intensity of summer frontal rainfall over recent decades. However, the extent of ongoing climate change on the intensification of the EA frontal precipitation system remains uncertain. Using an objective method for detecting frontal systems, we found a 17 ± 3% increase in observed frontal rainfall intensity during 1958 to 2015. Climate model simulations with and without greenhouse gases suggest that anthropogenic warming plays a key role in the intensification of EA summer frontal precipitation by 5.8% from 1991 to 2015. The analysis highlights that enhanced water vapor convergence and reinforced western North Pacific subtropical High collectively increased moisture transport to the region, resulting in intensified EA frontal precipitation. The results lend support to the anthropogenic warming-induced enhancement of the EA frontal precipitation and its persistence in the future.

Enhancement of river flooding due to global warming.

Human-induced climate change has increased the frequency and intensity of heavy precipitation1. Due to the complexity of runoff generation and the streamflow process, the historical impact of human-induced climate change on river flooding remains uncertain. Here, we address the question of whether anthropogenic climate change has altered the probability of the extreme river flood events for the period 1951-2010 based on simulated river discharge derived from large ensemble climate experiments with and without human-induced climate change. The results indicate that human-induced climate change altered the probabilities of 20 of the 52 analyzed flood events. Fourteen of these 20 flood events, which occurred mainly in Asia and South America, were very likely to have been enhanced by human-induced climate change due to an increase in heavy precipitation. Conversely, two flood events in North/South America and two flood events in Asia and two flood events in Europe were suppressed by human-induced climate change, perhaps as a result of lower snowfall. Human-induced climate change has enhanced flooding more prominently in recent years, providing important insights into potential adaptation strategies for river flooding.

The timing of unprecedented hydrological drought under climate change.

Droughts that exceed the magnitudes of historical variation ranges could occur increasingly frequently under future climate conditions. However, the time of the emergence of unprecedented drought conditions under climate change has rarely been examined. Here, using multimodel hydrological simulations, we investigate the changes in the frequency of hydrological drought (defined as abnormally low river discharge) under high and low greenhouse gas concentration scenarios and existing water resource management measures and estimate the time of the first emergence of unprecedented regional drought conditions centered on the low-flow season. The times are detected for several subcontinental-scale regions, and three regions, namely, Southwestern South America, Mediterranean Europe, and Northern Africa, exhibit particularly robust results under the high-emission scenario. These three regions are expected to confront unprecedented conditions within the next 30 years with a high likelihood regardless of the emission scenarios. In addition, the results obtained herein demonstrate the benefits of the lower-emission pathway in reducing the likelihood of emergence. The Paris Agreement goals are shown to be effective in reducing the likelihood to the unlikely level in most regions. However, appropriate and prior adaptation measures are considered indispensable when facing unprecedented drought conditions. The results of this study underscore the importance of improving drought preparedness within the considered time horizons.

Emergent constraints on future precipitation changes.

Future projections of global mean precipitation change (ΔP) based on Earth-system models have larger uncertainties than projections of global mean temperature changes (ΔT)1. Although many observational constraints on ΔT have been proposed, constraints on ΔP have not been well studied2-5 and are often complicated by the large influence of aerosols on precipitation4. Here we show that the upper bound (95th percentile) of ΔP (2051-2100 minus 1851-1900, percentage of the 1980-2014 mean) is lowered from 6.2 per cent to 5.2-5.7 per cent (minimum-maximum range of sensitivity analyses) under a medium greenhouse gas concentration scenario. Our results come from the Coupled Model Intercomparison Project phase 5 and phase 6 ensembles6-8, in which ΔP for 2051-2100 is well correlated with the global mean temperature trends during recent decades after 1980 when global anthropogenic aerosol emissions were nearly constant. ΔP is also significantly correlated with the recent past trends in precipitation when we exclude the tropical land areas with few rain-gauge observations. On the basis of these significant correlations and observed trends, the variance of ΔP is reduced by 8-30 per cent. The observationally constrained ranges of ΔP should provide further reliable information for impact assessments.

Event-to-event intensification of the hydrologic cycle from 1.5 °C to a 2 °C warmer world.

The Paris agreement was adopted to hold the global average temperature increase to well below 2 °C and pursue efforts to limit it to 1.5 °C. Here, we investigate the event-to-event hydroclimatic intensity, where an event is a pair of adjacent wet and dry spells, under future warming scenarios. According to a set of targeted multi-model large ensemble experiments, event-wise intensification will significantly increase globally for an additional 0.5 °C warming beyond 1.5 °C. In high latitudinal regions of the North American continent and Eurasia, this intensification is likely to involve overwhelming increases in wet spell intensity. Western and Eastern North America will likely experience more intense wet spells with negligible changes of dry spells. For the Mediterranean region, enhancement of dry spells seems to be dominating compared to the decrease in wet spell strength, and this will lead to an overall event-wise intensification. Furthermore, the extreme intensification could be 10 times stronger than the mean intensification. The high damage potential of such drastic changes between flood and drought conditions poses a major challenge to adaptation, and the findings suggest that risks could be substantially reduced by achieving a 1.5 °C target.

Extreme heat-related mortality avoided under Paris Agreement goals.

In key European cities, stabilizing climate warming at 1.5 °C would decrease extreme heat-related mortality by 15-22% per summer compared with stabilization at 2 °C.

How do climate-related uncertainties influence 2 and 1.5 °C pathways?

We investigate how uncertainties in key parameters in the carbon cycle and climate system propagate to the costs of climate change mitigation and adaptation needed to achieve the 2 and 1.5 °C targets by 2100 using a stochastic version of the simple climate model for optimization (SCM4OPT), an integrated assessment model. For the 2 °C target, we find a difference in 2100 CO2 emission levels of 20.5 GtCO2 (- 1.2 GtCO2 to 19.4 GtCO2), whereas this difference is 12.0 GtCO2 (- 6.9 GtCO2 to 5.1 GtCO2) for the 1.5 °C target (17-83% range). Total radiative forcing in 2100 is estimated to be 3.3 (2.7-3.9) Wm-2 for the 2 °C case and 2.5 (2.0-3.0) Wm-2 for the 1.5 °C case. Carbon prices in 2100 are 482 (181-732) USD(2005)/tCO2 and 713 (498-1014) USD(2005)/tCO2 for the 2 and 1.5 °C targets, respectively. We estimate GDP losses in 2100 that correspond to 1.9 (1.2-2.5)% of total gross output for the 2 °C target and 2.0 (1.5-2.7)% for the 1.5 °C target.

The value of knowledge accumulation on climate sensitivity uncertainty: comparison between perfect information, single stage and act then learn decisions.

In COP21 followed by the Paris Agreement, the world is now seriously planning actions to mitigate greenhouse gas emissions toward a "below 2 °C above preindustrial levels" future. Currently, we are still far from identifying the emission pathways to achieve this target because of the various uncertainties in both climate science and the human behavior. As a part of the ICA-RUS project, conducted by Dr. Seita Emori of the National Institute for Environmental Studies we have studied how these uncertainties are eliminated by the accumulation of scientific knowledge and the decision-making processes. We consider the following three questions: first, when and how will the uncertainty range on the global temperature rise be eliminated, second which global emission pathway should be chosen before we get the perfect information, and third how much expenditure is justified in reducing the climate uncertainties. The first question has been investigated by one of the authors. Shiogama et al. (Sci Rep 6:18903, 2016) developed the Allen-Stott-Kettleborough (ASK) method further to estimate how quickly and in what way the uncertainties in future global mean temperature changes can decline when the current observation network of surface air temperature is maintained. Fourteen global climate model results in CMIP5 (CMIP http://cmip-pcmdi.llnl.gov/, 2017) are used as virtual observations of surface air temperature. The purpose of this study is to answer the remaining two questions. Based on the ASK research outcomes, we apply the multi stage decision-making known as Act Then Learn (ATL) process to an integrated assessment model MARIA which includes energy technologies, economic activities, land use changes and a simple climate model block. We reveal how accumulating observations helps to mitigate economic losses by expanding the existing ATL method to deal with the uncertainty eliminating process by ASK. The primary findings are as follows. First, the value of information largely increases as the climate target policy is more stringent. Second, even if the uncertainties in the equilibrium climate sensitivity are not fully resolved, scientific knowledge is still valuable. In other words, the expenditure for scientific researches is rationalized when we really concern the global climate changes.

Biogeophysical Impacts of Land-Use Change on Climate Extremes in Low-Emission Scenarios: Results From HAPPI-Land.

The impacts of land use have been shown to have considerable influence on regional climate. With the recent international commitment to limit global warming to well below 2°C, emission reductions need to be ambitious and could involve major land-use change (LUC). Land-based mitigation efforts to curb emissions growth include increasing terrestrial carbon sequestration through reforestation, or the adoption of bioenergy crops. These activities influence local climate through biogeophysical feedbacks, however, it is uncertain how important they are for a 1.5° climate target. This was the motivation for HAPPI-Land: the half a degree additional warming, prognosis, and projected impacts-land-use scenario experiment. Using four Earth system models, we present the first multimodel results from HAPPI-Land and demonstrate the critical role of land use for understanding the characteristics of regional climate extremes in low-emission scenarios. In particular, our results show that changes in temperature extremes due to LUC are comparable in magnitude to changes arising from half a degree of global warming. We also demonstrate that LUC contributes to more than 20% of the change in temperature extremes for large land areas concentrated over the Northern Hemisphere. However, we also identify sources of uncertainty that influence the multimodel consensus of our results including how LUC is implemented and the corresponding biogeophysical feedbacks that perturb climate. Therefore, our results highlight the urgent need to resolve the challenges in implementing LUC across models to quantify the impacts and consider how LUC contributes to regional changes in extremes associated with sustainable development pathways.

Detecting latitudinal and altitudinal expansion of invasive bamboo Phyllostachys edulis and Phyllostachys bambusoides (Poaceae) in Japan to project potential habitats under 1.5°C-4.0°C global warming.

Rapid expansion of exotic bamboos has lowered species diversity in Japan's ecosystems by hampering native plant growth. The invasive potential of bamboo, facilitated by global warming, may also affect other countries with developing bamboo industries. We examined past (1975-1980) and recent (2012) distributions of major exotic bamboos (Phyllostachys edulis and P. bambusoides) in areas adjacent to 145 weather stations in central and northern Japan. Bamboo stands have been established at 17 sites along the latitudinal and altitudinal distributional limit during the last three decades. Ecological niche modeling indicated that temperature had a strong influence on bamboo distribution. Using mean annual temperature and sun radiation data, we reproduced bamboo distribution (accuracy = 0.93 and AUC (area under the receiver operating characteristic curve) = 0.92). These results infer that exotic bamboo distribution has shifted northward and upslope, in association with recent climate warming. Then, we simulated future climate data and projected the climate change impact on the potential habitat distribution of invasive bamboos under different temperature increases (i.e., 1.5°C, 2.0°C, 3.0°C, and 4.0°C) relative to the preindustrial period. Potential habitats in central and northern Japan were estimated to increase from 35% under the current climate (1980-2000) to 46%-48%, 51%-54%, 61%-67%, and 77%-83% under 1.5°C, 2.0°C, 3.0°C, and 4.0°C warming levels, respectively. These infer that the risk areas can increase by 1.3 times even under a 1.5°C scenario and expand by 2.3 times under a 4.0°C scenario. For sustainable ecosystem management, both mitigation and adaptation are necessary: bamboo planting must be carefully monitored in predicted potential habitats, which covers most of Japan.

Downscaling Global Emissions and Its Implications Derived from Climate Model Experiments.

In climate change research, future scenarios of greenhouse gas and air pollutant emissions generated by integrated assessment models (IAMs) are used in climate models (CMs) and earth system models to analyze future interactions and feedback between human activities and climate. However, the spatial resolutions of IAMs and CMs differ. IAMs usually disaggregate the world into 10-30 aggregated regions, whereas CMs require a grid-based spatial resolution. Therefore, downscaling emissions data from IAMs into a finer scale is necessary to input the emissions into CMs. In this study, we examined whether differences in downscaling methods significantly affect climate variables such as temperature and precipitation. We tested two downscaling methods using the same regionally aggregated sulfur emissions scenario obtained from the Asian-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model. The downscaled emissions were fed into the Model for Interdisciplinary Research on Climate (MIROC). One of the methods assumed a strong convergence of national emissions intensity (e.g., emissions per gross domestic product), while the other was based on inertia (i.e., the base-year remained unchanged). The emissions intensities in the downscaled spatial emissions generated from the two methods markedly differed, whereas the emissions densities (emissions per area) were similar. We investigated whether the climate change projections of temperature and precipitation would significantly differ between the two methods by applying a field significance test, and found little evidence of a significant difference between the two methods. Moreover, there was no clear evidence of a difference between the climate simulations based on these two downscaling methods.

Comparing regional precipitation and temperature extremes in climate model and reanalysis products.

A growing field of research aims to characterise the contribution of anthropogenic emissions to the likelihood of extreme weather and climate events. These analyses can be sensitive to the shapes of the tails of simulated distributions. If tails are found to be unrealistically short or long, the anthropogenic signal emerges more or less clearly, respectively, from the noise of possible weather. Here we compare the chance of daily land-surface precipitation and near-surface temperature extremes generated by three Atmospheric Global Climate Models typically used for event attribution, with distributions from six reanalysis products. The likelihoods of extremes are compared for area-averages over grid cell and regional sized spatial domains. Results suggest a bias favouring overly strong attribution estimates for hot and cold events over many regions of Africa and Australia, and a bias favouring overly weak attribution estimates over regions of North America and Asia. For rainfall, results are more sensitive to geographic location. Although the three models show similar results over many regions, they do disagree over others. Equally, results highlight the discrepancy amongst reanalyses products. This emphasises the importance of using multiple reanalysis and/or observation products, as well as multiple models in event attribution studies.

Adaptation pathways of global wheat production: Importance of strategic adaptation to climate change.

Agricultural adaptation is necessary to reduce the negative impacts of climate change on crop yields and to maintain food production. However, few studies have assessed the course of adaptation along with the progress of climate change in each of the current major food producing countries. Adaptation pathways, which describe the temporal sequences of adaptations, are helpful for illustrating the timing and intensity of the adaptation required. Here we present adaptation pathways in the current major wheat-producing countries, based on sequential introduction of the minimum adaptation measures necessary to maintain current wheat yields through the 21st century. We considered two adaptation options: (i) expanding irrigation infrastructure; and (ii) switching crop varieties and developing new heat-tolerant varieties. We find that the adaptation pathways differ markedly among the countries. The adaptation pathways are sensitive to both the climate model uncertainty and natural variability of the climate system, and the degree of sensitivity differs among countries. Finally, the negative impacts of climate change could be moderated by implementing adaptations steadily according to forecasts of the necessary future adaptations, as compared to missing the appropriate timing to implement adaptations.

Observational constraints indicate risk of drying in the Amazon basin.

Climate warming due to human activities will be accompanied by hydrological cycle changes. Economies, societies and ecosystems in South America are vulnerable to such water resource changes. Hence, water resource impact assessments for South America, and corresponding adaptation and mitigation policies, have attracted increased attention. However, substantial uncertainties remain in the current water resource assessments that are based on multiple coupled Atmosphere Ocean General Circulation models. This uncertainty varies from significant wetting to catastrophic drying. By applying a statistical method, we characterized the uncertainty and identified global-scale metrics for measuring the reliability of water resource assessments in South America. Here, we show that, although the ensemble mean assessment suggested wetting across most of South America, the observational constraints indicate a higher probability of drying in the Amazon basin. Thus, over-reliance on the consensus of models can lead to inappropriate decision making.

Pacific decadal oscillation hindcasts relevant to near-term climate prediction.

Decadal-scale climate variations over the Pacific Ocean and its surroundings are strongly related to the so-called Pacific decadal oscillation (PDO) which is coherent with wintertime climate over North America and Asian monsoon, and have important impacts on marine ecosystems and fisheries. In a near-term climate prediction covering the period up to 2030, we require knowledge of the future state of internal variations in the climate system such as the PDO as well as the global warming signal. We perform sets of ensemble hindcast and forecast experiments using a coupled atmosphere-ocean climate model to examine the predictability of internal variations on decadal timescales, in addition to the response to external forcing due to changes in concentrations of greenhouse gases and aerosols, volcanic activity, and solar cycle variations. Our results highlight that an initialization of the upper-ocean state using historical observations is effective for successful hindcasts of the PDO and has a great impact on future predictions. Ensemble hindcasts for the 20th century demonstrate a predictive skill in the upper-ocean temperature over almost a decade, particularly around the Kuroshio-Oyashio extension (KOE) and subtropical oceanic frontal regions where the PDO signals are observed strongest. A negative tendency of the predicted PDO phase in the coming decade will enhance the rising trend in surface air-temperature (SAT) over east Asia and over the KOE region, and suppress it along the west coasts of North and South America and over the equatorial Pacific. This suppression will contribute to a slowing down of the global-mean SAT rise.

Precipitation extreme changes exceeding moisture content increases in MIROC and IPCC climate models.

Precipitation extreme changes are often assumed to scale with, or are constrained by, the change in atmospheric moisture content. Studies have generally confirmed the scaling based on moisture content for the midlatitudes but identified deviations for the tropics. In fact half of the twelve selected Intergovernmental Panel on Climate Change (IPCC) models exhibit increases faster than the climatological-mean precipitable water change for high percentiles of tropical daily precipitation, albeit with significant intermodel scatter. Decomposition of the precipitation extreme changes reveals that the variations among models can be attributed primarily to the differences in the upward velocity. Both the amplitude and vertical profile of vertical motion are found to affect precipitation extremes. A recently proposed scaling that incorporates these dynamical effects can capture the basic features of precipitation changes in both the tropics and midlatitudes. In particular, the increases in tropical precipitation extremes significantly exceed the precipitable water change in Model for Interdisciplinary Research on Climate (MIROC), a coupled general circulation model with the highest resolution among IPCC climate models whose precipitation characteristics have been shown to reasonably match those of observations. The expected intensification of tropical disturbances points to the possibility of precipitation extreme increases beyond the moisture content increase as is found in MIROC and some of IPCC models.