Downscaling future climate change projections over Puerto Rico using a non-hydrostatic atmospheric model

We present results from 20-year “high-resolution” regional climate model simulations of precipitation change for the sub-tropical island of Puerto Rico. The Japanese Meteorological Agency Non-Hydrostatic Model (NHM) operating at a 2-km grid resolution is nested inside the Regional Spectral Model (RSM) at 10-km grid resolution, which in turn is forced at the lateral boundaries by the Community Climate System Model (CCSM4). At this resolution, the climate change experiment allows for deep convection in model integrations, which is an important consideration for sub-tropical regions in general, and on islands with steep precipitation gradients in particular that strongly influence local ecological processes and the provision of ecosystem services. Projected precipitation change for this region of the Caribbean is simulated for the mid-twenty-first century (2041–2060) under the RCP8.5 climate-forcing scenario relative to the late twentieth century (1986–2005). The results show that by the mid-twenty-first century, there is an overall rainfall reduction over the island for all seasons compared to the recent climate but with diminished mid-summer drought (MSD) in the northwestern parts of the island. Importantly, extreme rainfall events on sub-daily and daily time scales also become slightly less frequent in the projected mid-twenty-first-century climate over most regions of the island.     

Perceptions of climate engineering in the South Pacific,Sub-Saharan Africa,and North American Arctic

Nearly all research on public perceptions of climate engineering has been conducted in wealthy, developed countries. However, understanding perspectives from vulnerable populations is critical to inclusive, democratic debate on both research and governance. This study utilized in-depth interviews to explore the perspectives of vulnerable populations in the South Pacific, Sub-Saharan Africa, and the North American Arctic. Interviewees in this study were desperate for solutions to climate change and therefore willing to consider climate engineering. However, their willingness to consider climate engineering could be characterized as both deeply reluctant and highly conditional. Interviewees expressed a number of concerns about potential social and political implications of engineering the climate. They also described conditions that may need to be met to ensure that future climates (engineered or otherwise) are more equitable.     

Global carbon budgets and the viability of new fossil fuel projects

Policy-makers of some fossil fuel-endowed countries wish to know if a given fossil fuel supply project is consistent with the global carbon budget that would prevent a 2 °C temperature rise. But while some studies have identified fossil fuel reserves that are inconsistent with the 2 °C carbon budget, they have not shown the effect on fossil fuel production costs and market prices. Focusing on oil, we develop an oil pricing and climate test model to which we apply future carbon prices and oil consumption from several global energy-economy-emissions models that simulate the energy supply and demand effects of the 2 °C carbon budget. Our oil price model includes key oil market attributes, notably upper and lower market share boundaries for different oil producer categories, such as OPEC. Using the distribution of the global model results as an indicator of uncertainty about future carbon prices and oil demand, we estimate the probability that a new investment of a given oil source category would be economically viable under the 2 °C carbon budget. In our case study of Canada’s oil sands, we find a less than 5% probability that oil sands investments, and therefore new oil pipelines, would be economically viable over the next three decades under the 2 °C carbon budget. Our sensitivity analysis finds that if OPEC agreed to reduce its market share to 30% by 2045, a significant reduction from its steady 40–45% of the past 25 years, then the probability of viable oil sands expansion rises to 30%.     

Is public awareness and perceived threat of climate change associated with governmental mitigation targets?

Social scientists and science communicators are concerned about the apparent discrepancy between the scientific consensus on climate change (Anderegg et al. Proc Natl Acad Sci 107:12107–12109, 2010; Doran and Zimmerman EOS Trans Am Geophys Union 90:22–3, 2009) and the general public’s views (Knight Environ Sociol 2:101–113, 2016; Lee et al. Nat Clim Chang 5:1014–1020, 2015). It is reasoned that increased public awareness and perceived threat of climate change may pressure governments to enact policy to counteract climate change (e.g. setting stringent carbon emissions targets). Despite a logical link between public awareness and government-set emissions targets, this relationship remains untested. We examined the relationship between public awareness about and perceived threat of climate change and governmental emissions targets across 71 countries and 1 region. We found a positive association between the proportions of a country’s population that are aware of climate change and the unconditional emissions reduction targets set by that country in the Paris Agreement (Rogelj et al. Nature 534:631–639, 2016). However, the proportion of people in a country who perceive climate change as a personal threat was not associated with higher emissions reduction targets. Our results suggest that public awareness may be an important part of garnering the public support required for policies designed to mitigate climate change to succeed.     

Uncertainties in projected runoff over the conterminous United States

Projections of runoff from global multi-model ensembles provide a valuable basis for the estimation of future hydrological extremes. However, projections suffer from uncertainty that originates from different error sources along the modeling chain. Hydrological impact studies have generally partitioned these error sources into global impact and global climate model (GIM and GCM, respectively) uncertainties, neglecting other sources, including scenarios and internal variability. Using a set of GIMs driven by GCMs under different representative concentration pathways (RCPs), this study aims to partition the uncertainty of future flows coming from GIMs, GCMs, RCPs, and internal variability over the CONterminous United States (CONUS). We focus on annual maximum, median, and minimum runoff, analyzed decadally over the twenty-first century. Results indicate that GCMs and GIMs are responsible for the largest fraction of uncertainty over most of the study area, followed by internal variability and to a smaller extent RCPs. To investigate the influence of the ensemble setup on uncertainty, in addition to the full ensemble, three ensemble configurations are studied using fewer GIMs (excluding least credible GIMs in runoff representation and GIMs accounting for vegetation and CO₂ dynamics), and excluding intermediate RCPs. Overall, the use of fewer GIMs has a minor impact on uncertainty for low and medium flows, but a substantial impact for high flows. Regardless of the number of pathways considered, RCPs always play a very small role, suggesting that improvement of GCMs and GIMs and more informed ensemble selections can yield a reduction of projected uncertainties.     

Using species traits to guide conservation actions under climate change

Few assessments of species vulnerability to climate change used to inform conservation management consider the intrinsic traits that shape species’ capacity to respond to climate change. This omission is problematic as it may result in management actions that are not optimised for the long-term persistence of species as climates shift. We present a tool for explicitly linking data on plant species’ life history traits and range characteristics to appropriate management actions that maximise their capacity to respond to climate change. We deliberately target data on easily measured and widely available traits (e.g. dispersal syndrome, height, longevity) and range characteristics (e.g. range size, climatic/soil niche breadth), to allow for rapid comparison across many species. We test this framework on 1237 plants, categorising species on the basis of their potential climate change risk as related to four factors affecting their response capacity: reproduction, movement capability, abiotic niche specialisation and spatial coverage. Based on these four factors, species were allocated risk scores, and these were used to test the hypothesis that the current protection status under national legislation and related management actions capture species response capacity to climate change. Our results indicate that 20% of the plant species analysed (242 species) are likely to have a low capacity to respond to climate change based on the traits assessed, and are therefore at high risk. Of the 242 high risk species, only 10% (24 species) are currently listed for protection under conservation legislation. Importantly, many management plans for these listed species fail to address the capacity of species to respond to climate change with appropriate actions: 70% of approved management plans do not include crucial actions which may improve species’ ability to adapt to climate change. We illustrate how the use of easily attainable traits associated with ecological and evolutionary responses to changing environmental conditions can inform conservation actions for plant species globally.     

Regionalisation of population growth projections in coastal exposure analysis

Large-area coastal exposure and impact analysis has focussed on using sea-level rise (SLR) scenarios and has placed little emphasis on socioeconomic scenarios, while neglecting spatial variations of population dynamics. We use the Dynamic Interactive Vulnerability Assessment (DIVA) Framework to assess the population exposed to 1 in 100-year coastal flood events under different population scenarios, that are consistent with the shared socioeconomic pathways (SSPs); and different SLR scenarios, derived from the representative concentration pathways (RCPs); and analyse the effect of accounting for regionalised population dynamics on population exposure until 2100. In a reference approach, we use homogeneous population growth on national level. In the regionalisation approaches, we test existing spatially explicit projections that also account for urbanisation, coastal migration and urban sprawl. Our results show that projected global exposure in 2100 ranges from 100 million to 260 million, depending on the combination of SLR and population scenarios and method used for regionalising the population projections. The assessed exposure based on the regionalised approaches is higher than that derived from the reference approach by up to 60 million people (39%). Accounting for urbanisation and coastal migration leads to an increase in exposure, whereas considering urban sprawl leads to lower exposure. Differences between the reference and the regionalised approaches increase with higher SLR. The regionalised approaches show highest exposure under SSP5 over most of the twenty-first century, although total population in SSP5 is the second lowest overall. All methods project the largest absolute growth in exposure for Asia and relative growth for Africa.     

Real Data Assimilation Using the Local Ensemble Transform Kalman Filter (LETKF) System for a Global Non-hydrostatic NWP model on the Cubed-sphere

An ensemble data assimilation system using the 4-dimensional Local Ensemble Transform Kalman Filter is implemented to a global non-hydrostatic Numerical Weather Prediction model on the cubed-sphere. The ensemble data assimilation system is coupled to the Korea Institute of Atmospheric Prediction Systems Package for Observation Processing, for real observation data from diverse resources, including satellites. For computational efficiency in a parallel computing environment, we employ some advanced software engineering techniques in the handling of a large number of files. The ensemble data assimilation system is tested in a semi-operational mode, and its performance is verified using the Integrated Forecast System analysis from the European Centre for Medium-Range Weather Forecasts. It is found that the system can be stabilized effectively by additive inflation to account for sampling errors, especially when radiance satellite data are additionally used.     

Joint Impacts of SSTA in Tropical Pacific and Indian Oceans on Variations of the WPSH

Using the NCEP/NCAR reanalysis and HadISST sea surface temperature (SST) data, the joint effects of the tropical Indian Ocean and Pacific on variations of area of the summertime western Pacific subtropical high (WPSH) for period 1980–2016 are investigated. It is demonstrated that the central tropical Indian Ocean (CTI) and central equatorial Pacific (CEP) are two key oceanic regions that affect the summertime WPSH. During autumn and winter, warm SST anomalies (SSTAs) in CEP force the Walker circulation to change anomalously, resulting in divergence anomalies over the western Pacific and Maritime Continent (MC). Due to the Gill-type response, the abnormal anticyclonic circulation is generated over the western Pacific and South China Sea (SCS). In the subsequent spring, the warm SSTAs in CEP weaken, while the SST over CTI demonstrates a lagged response to Pacific SSTA. The warm CTISSTA and CEP-SSTA cooperate with the eastward propagation of cold Kelvin waves in the western Pacific, leading to the eastward shift of the abnormal divergence center that originally locates at the western Pacific and MC. The anticyclone forced by this divergence subsequently moves eastward, leading to the intensification of the negative vorticity there. Meanwhile, warm SSTA in CTI triggers eastward propagating Kelvin waves, which lead to easterly anomalies over the equatorial Indian Ocean and Indonesia, being favorable for maintenance and intensification of the anticyclone over the SCS and western Pacific. The monsoonal meridional–vertical circulation strengthens, which is favorable for the intensification of the WPSH. Using SSTA over the two key oceanic regions as predictors, a multiple regression model is successfully constructed for prediction of WPSH area. These results are useful for our better understanding the variation mechanisms of WPSH and better predicting summer climate in East Asia.     

Influence of the Boreal Summer Intraseasonal Oscillation on Extreme Temperature Events in the Northern Hemisphere

The impact of the boreal summer intraseasonal oscillation (BSISO) on extreme hot and cool events was investigated, by analyzing the observed and reanalysis data for the period from 1983 to 2012. It is found that the frequency of the extreme events in middle and high latitudes is significantly modulated by the BSISO convection in the tropics, with a 3–9-day lag. During phases 1 and 2 when the BSISO positive rainfall anomaly is primarily located over a northwest–southeast oriented belt extending from India to Maritime Continent and a negative rainfall anomaly appears in western North Pacific, the frequency of extreme hot events is 40% more than the frequency of non-extreme hot events. Most noticeable increase appears in midlatitude North Pacific (north of 40°N) and higher-latitude polar region.Two physical mechanisms are primarily responsible for the change of the extreme frequency. First, an upper-tropospheric Rossby wave train (due to the wave energy propagation) is generated in response to a negative heating anomaly over tropical western North Pacific in phases 1 and 2. This wave train consists of a strong high pressure anomaly center northeast of Japan, a weak low pressure anomaly center over Alaska, and a strong high pressure anomaly center over the western coast of United States. Easterly anomalies to the south of the two strong midlatitude high pressure centers weaken the climatological subtropical jet along 40°N, which is accompanied by anomalous subsidence and warming in North Pacific north of 40°N. Second, an enhanced monsoonal heating over South Asia and East Asia sets up a transverse monsoonal overturning circulation, with large-scale ascending (descending) anomalies over tropical Indian (Pacific) Ocean. Both the processes favor more frequent extreme hot events in higher-latitude Northern Hemisphere. An anomalous atmospheric general circulation model is used to confirm the tropical heating effect.