The household production function approach to valuing climate: the case of Japan

According to household production function theory households combine marketed goods and nonmarket environmental goods to produce service flows of direct value to the household. This readily explains why, as an input to household production activities, households might have preferences over the climate. Using techniques more frequently employed to account for differences in the demographic composition of households we use household production function theory to estimate climate equivalence scales using household expenditure data drawn from 51 Japanese cities over the period 2000–2009. Our results indicate that warmer temperatures result in a small but statistically highly significant reduction in the cost of living. Combining these estimates with climate change scenarios associated with the IPCC A2, A1B, and B1 emissions scenarios other things being equal points to a slight reduction in Japanese households’ cost of living.     

The challenge to detect and attribute effects of climate change on human and natural systems

Future scenarios of the energy system under greenhouse gas emission constraints depict dramatic growth in a range of energy technologies. Technological growth dynamics observed historically provide a useful comparator for these future trajectories. We find that historical time series data reveal a consistent relationship between how much a technology’s cumulative installed capacity grows, and how long this growth takes. This relationship between extent (how much) and duration (for how long) is consistent across both energy supply and end-use technologies, and both established and emerging technologies. We then develop and test an approach for using this historical relationship to assess technological trajectories in future scenarios. Our approach for “learning from the past” contributes to the assessment and verification of integrated assessment and energy-economic models used to generate quantitative scenarios. Using data on power generation technologies from two such models, we also find a consistent extent - duration relationship across both technologies and scenarios. This relationship describes future low carbon technological growth in the power sector which appears to be conservative relative to what has been evidenced historically. Specifically, future extents of capacity growth are comparatively low given the lengthy time duration of that growth. We treat this finding with caution due to the low number of data points. Yet it remains counter-intuitive given the extremely rapid growth rates of certain low carbon technologies under stringent emission constraints. We explore possible reasons for the apparent scenario conservatism, and find parametric or structural conservatism in the underlying models to be one possible explanation.     

A tale of two population crises in recent Chinese history

The fall of the Ming dynasty in the first half of the 17th century and the Taiping Rebellion from 1851–1864 were two of the most chaotic periods in Chinese history, and each was accompanied by large-scale population collapses. The ‘Kang-Qian Golden Age’ (also known as ‘High Qing’), during which population size expanded rapidly, falls in between the two. Scholars remain divided in their opinions concerning the above alternation of population growth and decline as to whether variations in population size or climate change should be identified as the root cause. In either case, the synergistic impact of population growth and climate change upon population growth dynamics is overlooked. In the present study, we utilized high-resolution empirical data, qualitative survey, statistical comparison and time-series analysis to investigate how the two factors worked synergistically to drive population cycles in 1600–1899. To facilitate our research, we posited a set of simplified pathways for population growth in historical agrarian China. Our results confirm that the interrelation between population growth, climate change and population crises in recent Chinese history basically followed our posited pathways. The recurrences of population crises were largely determined by the combination of population growth and climate change. Our results challenge classic Malthusian/post-Malthusian interpretations and historians’ views of historical Chinese population cycles.     

Climate change and infectious diseases: Can we meet the needs for better prediction?

The next generation of climate-driven, disease prediction models will most likely require a mechanistically based, dynamical framework that parameterizes key processes at a variety of locations. Over the next two decades, consensus climate predictions make it possible to produce forecasts for a number of important infectious diseases that are largely independent of the uncertainty of longer-term emissions scenarios. In particular, the role of climate in the modulation of seasonal disease transmission needs to be unravelled from the complex dynamics resulting from the interaction of transmission with herd immunity and intervention measures that depend upon previous burdens of infection. Progress is also needed to solve the mismatch between climate projections and disease projections at the scale of public health interventions. In the time horizon of seasons to years, early warning systems should benefit from current developments on multi-model ensemble climate prediction systems, particularly in areas where high skill levels of climate models coincide with regions where large epidemics take place. A better understanding of the role of climate extremes on infectious diseases is urgently needed.     

From desert to Mediterranean rangelands: will increasing drought and inter-annual rainfall variability affect herbaceous annual primary productivity?

Climate change is predicted to alter the rainfall regime in the Eastern Mediterranean Basin: total annual rainfall will decrease, while seasonal and inter-annual variation in rainfall will increase. Such changes in the rainfall regime could potentially lead to large-scale changes in aboveground net primary productivity (ANPP) in the region. We conducted a data-driven evaluation of herbaceous ANPP along an entire regional rainfall gradient, from desert (90 mm MAR [Mean Annual Rainfall]) to Mesic-Mediterranean (780 mm MAR) ecosystems, using the largest database ever collated for herbaceous ANPP in Israel, with the aim of predicting consequences of climate change for rangeland productivity. This research revealed that herbaceous ANPP increases with increasing rainfall along the gradient, but strong dependence on rainfall was only apparent within dry sites. Rain Use Efficiency peaks at mid-gradient in Mediterranean sites without woody vegetation (560 and 610 mm MAR). Inter-annual coefficients of variation in rainfall and herbaceous ANPP decrease along the rainfall gradient up to ca. 500 mm MAR. Climate change is more likely to affect herbaceous ANPP of rangelands in the arid end of the rainfall gradient, requiring adaptation of rangeland management, while ANPP of rangelands in more mesic ecosystems is less responsive to variation in rainfall. We conclude that herbaceous ANPP in most Mediterranean rangelands is less vulnerable to climate change than generally predicted.     

Public engagement on solar radiation management and why it needs to happen now

There have been a number of calls for public engagement in geoengineering in recent years. However, there has been limited discussion of why the public should have a say or what the public can be expected to contribute to geoengineering discussions. We explore how public engagement can contribute to the research, development, and governance of one branch of geoengineering, solar radiation management (SRM), in three key ways: 1. by fulfilling ethical requirements for the inclusion of affected parties in democratic decision making processes; 2. by contributing to improved dialogue and trust between scientists and the public; and 3. by ensuring that decisions about SRM research and possible deployment are informed by a broad set of societal interests, values, and framings. Finally, we argue that, despite the nascent state of many SRM technologies, the time is right for the public to participate in engagement processes.     

Multi-factor impact analysis of agricultural production in Bangladesh with climate change

Diverse vulnerabilities of Bangladesh's agricultural sector in 16 sub-regions are assessed using experiments designed to investigate climate impact factors in isolation and in combination. Climate information from a suite of global climate models (GCMs) is used to drive models assessing the agricultural impact of changes in temperature, precipitation, carbon dioxide concentrations, river floods, and sea level rise for the 2040–2069 period in comparison to a historical baseline. Using the multi-factor impacts analysis framework developed in Yu et al. (2010), this study provides new sub-regional vulnerability analyses and quantifies key uncertainties in climate and production. Rice (aman, boro, and aus seasons) and wheat production are simulated in each sub-region using the biophysical Crop Environment REsource Synthesis (CERES) models. These simulations are then combined with the MIKE BASIN hydrologic model for river floods in the Ganges-Brahmaputra-Meghna (GBM) Basins, and the MIKE21 Two-Dimensional Estuary Model to determine coastal inundation under conditions of higher mean sea level. The impacts of each factor depend on GCM configurations, emissions pathways, sub-regions, and particular seasons and crops. Temperature increases generally reduce production across all scenarios. Precipitation changes can have either a positive or a negative impact, with a high degree of uncertainty across GCMs. Carbon dioxide impacts on crop production are positive and depend on the emissions pathway. Increasing river flood areas reduce production in affected sub-regions. Precipitation uncertainties from different GCMs and emissions scenarios are reduced when integrated across the large GBM Basins’ hydrology. Agriculture in Southern Bangladesh is severely affected by sea level rise even when cyclonic surges are not fully considered, with impacts increasing under the higher emissions scenario.     

The High-Resolution Coronal Imager (Hi-C)

The High-Resolution Coronal Imager (Hi-C) was flown on a NASA sounding rocket on 11 July 2012. The goal of the Hi-C mission was to obtain high-resolution (≈?0.3?–?0.4′′), high-cadence (≈?5 seconds) images of a solar active region to investigate the dynamics of solar coronal structures at small spatial scales. The instrument consists of a normal-incidence telescope with the optics coated with multilayers to reflect a narrow wavelength range around 19.3 nm (including the Fe xii 19.5-nm spectral line) and a 4096×4096 camera with a plate scale of 0.1′′?pixel^?1. The target of the Hi-C rocket flight was Active Region 11520. Hi-C obtained 37 full-frame images and 86 partial-frame images during the rocket flight. Analysis of the Hi-C data indicates the corona is structured on scales smaller than currently resolved by existing satellite missions.     

Comparative Analysis of a Transition Region Bright Point with a Blinker and Coronal Bright Point Using Multiple EIS Emission Lines

Since their discovery 20 year ago, transition region bright points have never been observed spectroscopically. Bright point properties have not been compared with similar transition region and coronal structures. In this work we have investigated three transient quiet Sun brightenings including a transition region bright point (TR BP), a coronal bright point (CBP) and a blinker. We use time-series observations of the extreme-ultraviolet emission lines of a wide range of temperature T (logT=5.3?–?6.4) from the EUV Imaging Spectrometer (EIS) onboard the Hinode satellite. We present the EIS temperature maps and Doppler maps, which are compared with magnetograms from the Michelson Doppler Imager (MDI) onboard the SOHO satellite. Doppler velocities of the TR BP and blinker are ≤?25 km?s^?1, which is typical of transient TR phenomena. The Doppler velocities of the CBP were found to be ≤?20 km?s^?1 with exception of those measured at logT=6.2 where a distinct bi-directional jet is observed. From an EM loci analysis we find evidence of single and double isothermal components in the TR BP and CBP, respectively. TR BP and CBP loci curves are characterized by broad distributions suggesting the existence of unresolved structure. By comparing and contrasting the physical characteristics of the events we find that the BP phenomena are an indication of multi-scaled self-similarity, given the similarities in both their underlying magnetic field configuration and evolution in relation to EUV flux changes. In contrast, the blinker phenomena and the TR BP are sufficiently dissimilar in their observed properties as to constitute different event classes. Our work is an indication that the measurement of similar characteristics across multiple event types holds class-predictive power, and is a significant step towards automated solar atmospheric multi-class classification of unresolved transient EUV sources. Finally, the analysis performed here establishes a connection between solar quiet region CBPs and jets.