Tropical cyclone climatology in a 10-km global atmospheric GCM: toward weather-resolving climate modeling

Northern Hemisphere tropical cyclone (TC) activity is investigated in multiyear global climate simulations with theECMWFIntegrated Forecast System (IFS) at 10-km resolution forced by the observed records of sea surface temperature and sea ice. The results are compared to analogous simulationswith the 16-, 39-, and 125-km versions of the model as well as observations. In the North Atlantic, mean TC frequency in the 10-km model is comparable to the observed frequency, whereas it is too low in the other versions. While spatial distributions of the genesis and track densities improve systematically with increasing resolution, the 10-km model displays qualitatively more realistic simulation of the track density in the western subtropical North Atlantic. In the North Pacific, the TC count tends to be too high in thewest and too low in the east for all resolutions. These model errors appear to be associated with the errors in the large-scale environmental conditions that are fairly similar in this region for all model versions. The largest benefits of the 10-km simulation are the dramatically more accurate representation of the TC intensity distribution and the structure of the most intense storms. The model can generate a supertyphoon with a maximum surface wind speed of 68.4 m s21. The life cycle of an intense TC comprises intensity fluctuations that occur in apparent connection with the variations of the eyewall/rainband structure. These findings suggest that a hydrostatic model with cumulus parameterization and of high enough resolution could be efficiently used to simulate the TC intensity response (and the associated structural changes) to future climate change.

Tree species diversity interacts with elevated CO2 to induce a greater root system response

As a consequence of land use change and the burning of fossil fuels, atmospheric concentrations of CO2 are increasing and altering the dynamics of the carbon cycle in forest ecosystems. In a number of studies using single tree species, fine root biomass has been shown to be strongly increased by elevated CO2. However, natural forests are often intimate mixtures of a number of co-occurring species. To investigate the interaction between tree mixture and elevated CO2, Alnus glutinosa, Betula pendula and Fagus sylvatica were planted in areas of single species and a three species polyculture in a free-air CO2 enrichment study (BangorFACE). The trees were exposed to ambient or elevated CO2 (580 µmol mol-1) for four years. Fine and coarse root biomass, together with fine root turnover and fine root morphological characteristics were measured. Fine root biomass, and morphology responded differentially to elevated CO2 at different soil depths in the three species when grown in monocultures. In polyculture, a greater response to elevated CO2 was observed in coarse roots to a depth of 20 cm, and fine root area index to a depth of 30 cm. Total fine root biomass was positively affected by elevated CO2 at the end of the experiment, but not by species diversity. Our data suggest that existing biogeochemical cycling models parameterised with data from species grown in monoculture may be underestimating the belowground response to global change.

The proportionality of global warming to cumulative carbon emissions

The global temperature response to increasing atmospheric CO2 is often quantified by metrics such as equilibrium climate sensitivity and transient climate response1. These approaches, however, do not account for carbon cycle feedbacks and therefore do not fully represent the net response of the Earth system to anthropogenic CO2 emissions. Climate–carbon modelling experiments have shown that: (1) the warming per unit CO2 emitted does not depend on the background CO2 concentration2; (2) the total allowable emissions for climate stabilization do not depend on the timing of those emissions3, 4, 5; and (3) the temperature response to a pulse of CO2 is approximately constant on timescales of decades to centuries3, 6, 7, 8. Here we generalize these results and show that the carbon–climate response (CCR), defined as the ratio of temperature change to cumulative carbon emissions, is approximately independent of both the atmospheric CO2 concentration and its rate of change on these timescales. From observational constraints, we estimate CCR to be in the range 1.0–2.1 °C per trillion tonnes of carbon (Tt C) emitted (5th to 95th percentiles), consistent with twenty-first-century CCR values simulated by climate–carbon models. Uncertainty in land-use CO2 emissions and aerosol forcing, however, means that higher observationally constrained values cannot be excluded. The CCR, when evaluated from climate–carbon models under idealized conditions, represents a simple yet robust metric for comparing models, which aggregates both climate feedbacks and carbon cycle feedbacks. CCR is also likely to be a useful concept for climate change mitigation and policy; by combining the uncertainties associated with climate sensitivity, carbon sinks and climate–carbon feedbacks into a single quantity, the CCR allows CO2-induced global mean temperature change to be inferred directly from cumulative carbon emissions.

How difficult is it to recover from dangerous levels of global warming?

Climate models provide compelling evidence that if greenhouse gas emissions continue at present rates, then key global temperature thresholds (such as the European Union limit of two degrees of warming since pre-industrial times) are very likely to be crossed in the next few decades. However, there is relatively little attention paid to whether, should a dangerous temperature level be exceeded, it is feasible for the global temperature to then return to safer levels in a usefully short time. We focus on the timescales needed to reduce atmospheric greenhouse gases and associated temperatures back below potentially dangerous thresholds, using a state-of-the-art general circulation model. This analysis is extended with a simple climate model to provide uncertainty bounds. We find that even for very large reductions in emissions, temperature reduction is likely to occur at a low rate. Policy-makers need to consider such very long recovery timescales implicit in the Earth system when formulating future emission pathways that have the potential to 'overshoot' particular atmospheric concentrations of greenhouse gases and, more importantly, related temperature levels that might be considered dangerous.

Microsaccades distinguish between global and local visual processing

Much is known about the functional mechanisms involved in visual search. Yet, the fundamental question of whether the visual system can perform different types of visual analysis at different spatial resolutions still remains unsettled. In the visual-attention literature, the distinction between different spatial scales of visual processing corresponds to the distinction between distributed and focused attention. Some authors have argued that singleton detection can be performed in distributed attention, whereas others suggest that even such a simple visual operation involves focused attention. Here we showed that microsaccades were spatially biased during singleton discrimination but not during singleton detection. The results provide support to the hypothesis that some coarse visual analysis can be performed in a distributed attention mode.

An earth-system prediction initiative for the twenty-first century

The necessity and benefits for establishing the international Earth-system Prediction Initiative (EPI) are discussed by scientists associated with the World Meteorological Organization (WMO) World Weather Research Programme (WWRP), World Climate Research Programme (WCRP), International Geosphere–Biosphere Programme (IGBP), Global Climate Observing System (GCOS), and natural-hazards and socioeconomic communities. The proposed initiative will provide research and services to accelerate advances in weather, climate, and Earth system prediction and the use of this information by global societies. It will build upon the WMO, the Group on Earth Observations (GEO), the Global Earth Observation System of Systems (GEOSS) and the International Council for Science (ICSU) to coordinate the effort across the weather, climate, Earth system, natural-hazards, and socioeconomic disciplines. It will require (i) advanced high-performance computing facilities, supporting a worldwide network of research and operational modeling centers, and early warning systems; (ii) science, technology, and education projects to enhance knowledge, awareness, and utilization of weather, climate, environmental, and socioeconomic information; (iii) investments in maintaining existing and developing new observational capabilities; and (iv) infrastructure to transition achievements into operational products and services.

Sensitivity of an Earth system climate model to idealized radiative forcing

We diagnose forcing and climate feedbacks in benchmark sensitivity experiments with the new Met Office Hadley Centre Earth system climate model HadGEM2-ES. To identify the impact of newly-included biogeophysical and chemical processes, results are compared to a parallel set of experiments performed with these processes switched off, and different couplings with the biogeochemistry. In abrupt carbon dioxide quadrupling experiments we find that the inclusion of these processes does not alter the global climate sensitivity of the model. However, when the change in carbon dioxide is uncoupled from the vegetation, or when the model is forced with a non-carbon dioxide forcing – an increase in solar constant – new feedbacks emerge that make the climate system less sensitive to external perturbations. We identify a strong negative dust-vegetation feedback on climate change that is small in standard carbon dioxide sensitivity experiments due to the physiological/fertilization effects of carbon dioxide on plants in this model.

Deriving global flood hazard maps of fluvial floods through a physical model cascade

Global flood hazard maps can be used in the assessment of flood risk in a number of different applications, including (re)insurance and large scale flood preparedness. Such global hazard maps can be generated using large scale physically based models of rainfall-runoff and river routing, when used in conjunction with a number of post-processing methods. In this study, the European Centre for Medium Range Weather Forecasts (ECMWF) land surface model is coupled to ERA-Interim reanalysis meteorological forcing data, and resultant runoff is passed to a river routing algorithm which simulates floodplains and flood flow across the global land area. The global hazard map is based on a 30 yr (1979–2010) simulation period. A Gumbel distribution is fitted to the annual maxima flows to derive a number of flood return periods. The return periods are calculated initially for a 25×25 km grid, which is then reprojected onto a 1×1 km grid to derive maps of higher resolution and estimate flooded fractional area for the individual 25×25 km cells. Several global and regional maps of flood return periods ranging from 2 to 500 yr are presented. The results compare reasonably to a benchmark data set of global flood hazard. The developed methodology can be applied to other datasets on a global or regional scale.

Recent advances in global electric circuit coupling between the space environment and the troposphere

The global atmospheric electric circuit is driven by thunderstorms and electrified rain/shower clouds and is also influenced by energetic charged particles from space. The global circuit maintains the ionosphere as an equipotential at∼+250 kV with respect to the good conducting Earth (both land and oceans). Its “load” is the fair weather atmosphere and semi-fair weather atmosphere at large distances from the disturbed weather “generator” regions. The main solar-terrestrial (or space weather) influence on the global circuit arises from spatially and temporally varying fluxes of galactic cosmic rays (GCRs) and energetic electrons precipitating from the magnetosphere. All components of the circuit exhibit much variability in both space and time. Global circuit variations between solar maximum and solar minimum are considered together with Forbush decrease and solar flare effects. The variability in ion concentration and vertical current flow are considered in terms of radiative effects in the troposphere, through infra-red absorption, and cloud effects, in particular possible cloud microphysical effects from charging at layer cloud edges. The paper identifies future research areas in relation to Task Group 4 of the Climate and Weather of the Sun-Earth System (CAWSES-II) programme.

What is the climate system able to do ‘on its own’?

The climate of the Earth, like planetary climates in general, is broadly controlled by solar irradiation, planetary albedo and emissivity as well as its rotation rate and distribution of land (with its orography) and oceans. However, the majority of climate fluctuations that affect mankind are internal modes of the general circulation of the atmosphere and the oceans. Some of these modes, such as El Nino-Southern Oscillation (ENSO), are quasi-regular and have some longer-term predictive skill; others like the Arctic and Antarctic Oscillation are chaotic and generally unpredictable beyond a few weeks. Studies using general circulation models indicate that internal processes dominate the regional climate and that some like ENSO events have even distinct global signatures. This is one of the reasons why it is so difficult to separate internal climate processes from external ones caused, for example, by changes in greenhouse gases and solar irradiation. However, the accumulation of the warmest seasons during the latest two decades is lending strong support to the forcing of the greenhouse gases. As models are getting more comprehensive, they show a gradually broader range of internal processes including those on longer time scales, challenging the interpretation of the causes of past and present climate events further.

The global atmospheric water cycle

Water vapour plays a key role in the Earth's energy balance. Almost 50% of the absorbed solar radiation at the surface is used to cool the surface, through evaporation, and warm the atmosphere, through release of latent heat. Latent heat is the single largest factor in warming the atmosphere and in transporting heat from low to high latitudes. Water vapour is also the dominant greenhouse gas and contributes to a warming of the climate system by some 24°C (Kondratev 1972). However, water vapour is a passive component in the troposphere as it is uniquely determined by temperature and should therefore be seen as a part of the climate feedback system. In this short overview, we will first describe the water on planet Earth and the role of the hydrological cycle: the way water vapour is transported between oceans and continents and the return of water via rivers to the oceans. Generally water vapour is well observed and analysed; however, there are considerable obstacles to observing precipitation, in particular over the oceans. The response of the hydrological cycle to global warming is far reaching. Because different physical processes control the change in water vapour and evaporation/precipitation, this leads to a more extreme distribution of precipitation making, in general, wet areas wetter and dry areas dryer. Another consequence is a transition towards more intense precipitation. It is to be expected that the changes in the hydrological cycle as a consequence of climate warming may be more severe that the temperature changes.

Integration of Space and In Situ Observations to Study Global Climate Change

The currently available model-based global data sets of atmospheric circulation are a by-product of the daily requirement of producing initial conditions for numerical weather prediction (NWP) models. These data sets have been quite useful for studying fundamental dynamical and physical processes, and for describing the nature of the general circulation of the atmosphere. However, due to limitations in the early data assimilation systems and inconsistencies caused by numerous model changes, the available model-based global data sets may not be suitable for studying global climate change. A comprehensive analysis of global observations based on a four-dimensional data assimilation system with a realistic physical model should be undertaken to integrate space and in situ observations to produce internally consistent, homogeneous, multivariate data sets for the earth's climate system. The concept is equally applicable for producing data sets for the atmosphere, the oceans, and the biosphere, and such data sets will be quite useful for studying global climate change.

A complex system perspective on the emergence and spread of infectious diseases: integrating economic and ecological aspects

The emergence and spread of infectious diseases reflects the interaction of ecological and economic factors within an adaptive complex system. We review studies that address the role of economic factors in the emergence and spread of infectious diseases and identify three broad themes. First, the process of macro-economic growth leads to environmental encroaching, which is related to the emergence of infectious diseases. Second, there are a number of mutually reinforcing processes associated with the emergence/spread of infectious diseases. For example, the emergence and spread of infectious diseases can cause significant economic damages, which in turn may create the conditions for further disease spread. Also, the existence of a mutually reinforcing relationship between global trade and macroeconomic growth amplifies the emergence/spread of infectious diseases. Third, microeconomic approaches to infectious disease point to the adaptivity of human behavior, which simultaneously shapes the course of epidemics and responds to it. Most of the applied research has been focused on the first two aspects, and to a lesser extent on the third aspect. With respect to the latter, there is a lack of empirical research aimed at characterizing the behavioral component following a disease outbreak. Future research should seek to fill this gap and develop hierarchical econometric models capable of integrating both macro and micro-economic processes into disease ecology.