Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1.0)

In addition to CO2, the climate impact of aviation is strongly influenced by non-CO2 emissions, such as nitrogen oxides, influencing ozone and methane, and water vapour, which can lead to the formation of persistent contrails in ice-supersaturated regions. Because these non-CO2 emission effects are characterised by a short lifetime, their climate impact largely depends on emission location and time; that is to say, emissions in certain locations (or times) can lead to a greater climate impact (even on the global average) than the same emission in other locations (or times). Avoiding these climate-sensitive regions might thus be beneficial to climate. Here, we describe a modelling chain for investigating this climate impact mitigation option. This modelling chain forms a multi-step modelling approach, starting with the simulation of the fate of emissions released at a certain location and time (time-region grid points). This is performed with the chemistry–climate model EMAC, extended via the two submodels AIRTRAC (V1.0) and CONTRAIL (V1.0), which describe the contribution of emissions to the composition of the atmosphere and to contrail formation, respectively. The impact of emissions from the large number of time-region grid points is efficiently calculated by applying a Lagrangian scheme. EMAC also includes the calculation of radiative impacts, which are, in a second step, the input to climate metric formulas describing the global climate impact of the emission at each time-region grid point. The result of the modelling chain comprises a four-dimensional data set in space and time, which we call climate cost functions and which describes the global climate impact of an emission at each grid point and each point in time. In a third step, these climate cost functions are used in an air traffic simulator (SAAM) coupled to an emission tool (AEM) to optimise aircraft trajectories for the North Atlantic region. Here, we describe the details of this new modelling approach and show some example results. A number of sensitivity analyses are performed to motivate the settings of individual parameters. A stepwise sanity check of the results of the modelling chain is undertaken to demonstrate the plausibility of the climate cost functions.

Extraction of tidal channel networks from airborne scanning laser altimetry and aerial photography

The study of the morphodynamics of tidal channel networks is important because of their role in tidal propagation and the evolution of salt-marshes and tidal flats. Channel dimensions range from tens of metres wide and metres deep near the low water mark to only 20-30cm wide and 20cm deep for the smallest channels on the marshes. The conventional method of measuring the networks is cumbersome, involving manual digitising of aerial photographs. This paper describes a semi-automatic knowledge-based network extraction method that is being implemented to work using airborne scanning laser altimetry (and later aerial photography). The channels exhibit a width variation of several orders of magnitude, making an approach based on multi-scale line detection difficult. The processing therefore uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels using a distance-with-destination transform. Breaks in the networks are repaired by extending channel ends in the direction of their ends to join with nearby channels, using domain knowledge that flow paths should proceed downhill and that any network fragment should be joined to a nearby fragment so as to connect eventually to the open sea.

An FLIR video surveillance system to avoid bridge-ship collision

In this paper, a forward-looking infrared (FLIR) video surveillance system is presented for collision avoidance of moving ships to bridge piers. An image pre-processing algorithm is proposed to reduce clutter noises by multi-scale fractal analysis, in which the blanket method is used for fractal feature computation. Then, the moving ship detection algorithm is developed from image differentials of the fractal feature in the region of surveillance between regularly interval frames. Experimental results have shown that the approach is feasible and effective. It has achieved real-time and reliable alert to avoid collisions of moving ships to bridge piers

A bridge-ship collision avoidance system based on FLIR image sequences

In this paper, a forward-looking infrared (FLIR) video surveillance system is presented for collision avoidance of moving ships to bridge piers. An image preprocessing algorithm is proposed to reduce clutter background by multi-scale fractal analysis, in which the blanket method is used for fractal feature computation. Then, the moving ship detection algorithm is developed from image differentials of the fractal feature in the region of surveillance between regularly interval frames. When the moving ships are detected in region of surveillance, the device for safety alert is triggered. Experimental results have shown that the approach is feasible and effective. It has achieved real-time and reliable alert to avoid collisions of moving ships to bridge piers.

Integrating features for man-made target tracking from FLIR image sequence using particle filter

A new man-made target tracking algorithm integrating features from (Forward Looking InfraRed) image sequence is presented based on particle filter. Firstly, a multiscale fractal feature is used to enhance targets in FLIR images. Secondly, the gray space feature is defined by Bhattacharyya distance between intensity histograms of the reference target and a sample target from MFF (Multi-scale Fractal Feature) image. Thirdly, the motion feature is obtained by differencing between two MFF images. Fourthly, a fusion coefficient can be automatically obtained by online feature selection method for features integrating based on fuzzy logic. Finally, a particle filtering framework is developed to fulfill the target tracking. Experimental results have shown that the proposed algorithm can accurately track weak or small man-made target in FLIR images with complicated background. The algorithm is effective, robust and satisfied to real time tracking.

Landscape, regional and global estimates of nitrogen flux from land to sea: errors and uncertainties

Regional to global scale modelling of N flux from land to ocean has progressed to date through the development of simple empirical models representing bulk N flux rates from large watersheds, regions, or continents on the basis of a limited selection of model parameters. Watershed scale N flux modelling has developed a range of physically-based approaches ranging from models where N flux rates are predicted through a physical representation of the processes involved, through to catchment scale models which provide a simplified representation of true systems behaviour. Generally, these watershed scale models describe within their structure the dominant process controls on N flux at the catchment or watershed scale, and take into account variations in the extent to which these processes control N flux rates as a function of landscape sensitivity to N cycling and export. This paper addresses the nature of the errors and uncertainties inherent in existing regional to global scale models, and the nature of error propagation associated with upscaling from small catchment to regional scale through a suite of spatial aggregation and conceptual lumping experiments conducted on a validated watershed scale model, the export coefficient model. Results from the analysis support the findings of other researchers developing macroscale models in allied research fields. Conclusions from the study confirm that reliable and accurate regional scale N flux modelling needs to take account of the heterogeneity of landscapes and the impact that this has on N cycling processes within homogenous landscape units.

Aerosol impacts on drizzle properties in warm clouds from ARM Mobile Facility maritime and continental deployments

We have extensively evaluated the response of cloud-base drizzle rate (Rcb; mm day–1) in warm clouds to liquid water path (LWP; g m–2) and to cloud condensation nuclei (CCN) number concentration (NCCN; cm–3), an aerosol proxy. This evaluation is based on a 19-month long dataset of Doppler radar, lidar, microwave radiometers and aerosol observing systems from the Atmospheric Radiation Measurement (ARM) Mobile Facility deployments at the Azores and in Germany. Assuming 0.55% supersaturation to calculate NCCN, we found a power law , indicating that Rcb decreases by a factor of 2–3 as NCCN increases from 200 to 1000 cm–3 for fixed LWP. Additionally, the precipitation susceptibility to NCCN ranges between 0.5 and 0.9, in agreement with values from simulations and aircraft measurements. Surprisingly, the susceptibility of the probability of precipitation from our analysis is much higher than that from CloudSat estimates, but agrees well with simulations from a multi-scale high-resolution aerosol-climate model. Although scale issues are not completely resolved in the intercomparisons, our results are encouraging, suggesting that it is possible for multi-scale models to accurately simulate the response of LWP to aerosol perturbations.

Urban integrated meteorological observations: practice and experience in Shanghai, China

Observations of atmospheric conditions and processes in citiesare fundamental to understanding the interactions between the urban surface and weather/climate, improving the performance of urban weather, air quality and climate models, and providing key information for city end-users (e.g. decision-makers, stakeholders, public). In this paper, Shanghai's urban integrated meteorological observation network (SUIMON) and some examples of intended applications are introduced. Its characteristics include being: multi- purpose (e.g. forecast, research, service), multi-function (high impact weather, city climate, special end-users), multi-scale (e.g. macro/meso-, urban-, neighborhood, street canyon), multi-variable (e.g. thermal, dynamic, chemical, bio-meteorological, ecological), and multi- platform (e.g. radar, wind profiler, ground-based, satellite based, in-situ observation/ sampling). Underlying SUIMON is a data management system to facilitate exchange of data and information. The overall aim of the network is to improve coordination strategies and instruments; to identify data gaps based on science and user driven requirements; and to intelligently combine observations from a variety of platforms by using a data assimilation system that is tuned to produce the best estimate of the current state of the urban atmosphere.

Anticipatory governance for social-ecological resilience

Anticipation is increasingly central to urgent contemporary debates, from climate change to the global economic crisis. Anticipatory practices are coming to the forefront of political, organizational, and citizens’ society. Research into anticipation, however, has not kept pace with public demand for insights into anticipatory practices, their risks and uses. Where research exists, it is deeply fragmented. This paper seeks to identify how anticipation is defined and understood in the literature and to explore the role of anticipatory practice to address individual, social, and global challenges. We use a resilience lens to examine these questions. We illustrate how varying forms of anticipatory governance are enhanced by multi-scale regional networks and technologies and by the agency of individuals, drawing from an empirical case study on regional water governance of Mälaren, Sweden. Finally, we discuss how an anticipatory approach can inform adaptive institutions, decision making, strategy formation, and societal resilience.

Terahertz spectroscopy and imaging at the nanoscale for biological and security applications

The chemical specificity of terahertz spectroscopy, when combined with techniques for sub-wavelength sensing, is giving new understanding of processes occurring at the nanometre scale in biological systems and offers the potential for single molecule detection of chemical and biological agents and explosives. In addition, terahertz techniques are enabling the exploration of the fundamental behaviour of light when it interacts with nanoscale optical structures, and are being used to measure ultrafast carrier dynamics, transport and localisation in nanostructures. This chapter will explain how terahertz scale modelling can be used to explore the fundamental physics of nano-optics, it will discuss the terahertz spectroscopy of nanomaterials, terahertz near-field microscopy and other sub-wavelength techniques, and summarise recent developments in the terahertz spectroscopy and imaging of biological systems at the nanoscale. The potential of using these techniques for security applications will be considered.

Spatial interaction among nontoxic phytoplankton, toxic phytoplankton and zooplankton: emergence in space and time

In homogeneous environments, by overturning the possibility of competitive exclusion among phytoplankton species, and by regulating the dynamics of overall plankton population, toxin-producing phytoplankton (TPP) potentially help in maintaining plankton diversity—a result shown recently. Here, I explore the competitive effects of TPP on phytoplankton and zooplankton species undergoing spatial movements in the subsurface water. The spatial interactions among the species are represented in the form of reaction-diffusion equations. Suitable parametric conditions under which Turing patterns may or may not evolve are investigated. Spatiotemporal distributions of species biomass are simulated using the diffusivity assumptions realistic for natural planktonic systems. The study demonstrates that spatial movements of planktonic systems in the presence of TPP generate and maintain inhomogeneous biomass distribution of competing phytoplankton, as well as grazer zooplankton, thereby ensuring the persistence of multiple species in space and time. The overall results may potentially explain the sustainability of biodiversity and the spatiotemporal emergence of phytoplankton and zooplankton species under the influence of TPP combined with their physical movement in the subsurface water.

On the reprocessing and reanalysis of observations for climate

The long observational record is critical to our understanding of the Earth’s climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. The purpose of this paper is to both review recent progress in reprocessing and reanalyzing observations, and summarize the challenges that must be overcome in order to improve our understanding of climate and variability. Reprocessing improves data quality through more scrutiny and improved retrieval techniques for individual observing systems, while reanalysis merges many disparate observations with models through data assimilation, yet both aim to provide a climatology of Earth processes. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Oceanic reanalyses have made significant advances in recent years, but will only be discussed here in terms of progress toward integrated Earth system analyses. Climate data sets are generally adequate for process studies and large-scale climate variability. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. It must be emphasized that careful investigation of the data and processing methods are required to use the observations appropriately.

The impact of a thermodynamic sea-ice module in the COSMO numerical weather prediction model on simulations for the Laptev Sea, Siberian Arctic

Previous versions of the Consortium for Small-scale Modelling (COSMO) numerical weather prediction model have used a constant sea-ice surface temperature, but observations show a high degree of variability on sub-daily timescales. To account for this, we have implemented a thermodynamic sea-ice module in COSMO and performed simulations at a resolution of 15 km and 5 km for the Laptev Sea area in April 2008. Temporal and spatial variability of surface and 2-m air temperature are verified by four automatic weather stations deployed along the edge of the western New Siberian polynya during the Transdrift XIII-2 expedition and by surface temperature charts derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. A remarkable agreement between the new model results and these observations demonstrates that the implemented sea-ice module can be applied for short-range simulations. Prescribing the polynya areas daily, our COSMO simulations provide a high-resolution and high-quality atmospheric data set for the Laptev Sea for the period 14-30 April 2008. Based on this data set, we derive a mean total sea-ice production rate of 0.53 km3/day for all Laptev Sea polynyas under the assumption that the polynyas are ice-free and a rate of 0.30 km3/day if a 10-cm-thin ice layer is assumed. Our results indicate that ice production in Laptev Sea polynyas has been overestimated in previous studies.

Quantifying polynya ice production in the Laptev Sea with the COSMO model

Arctic flaw polynyas are considered to be highly productive areas for the formation of sea-ice throughout the winter season. Most estimates of sea-ice production are based on the surface energy balance equation and use global reanalyses as atmospheric forcing, which are too coarse to take into account the impact of polynyas on the atmosphere. Additional errors in the estimates of polynya ice production may result from the methods of calculating atmospheric energy fluxes and the assumption of a thin-ice distribution within polynyas. The present study uses simulations using the mesoscale weather prediction model of the Consortium for Small-scale Modelling (COSMO), where polynya area is prescribed from satellite data. The polynya area is either assumed to be ice-free or to be covered with thin ice of 10 cm. Simulations have been performed for two winter periods (2007/08 and 2008/09). When using a realistic thin-ice thickness of 10 cm, sea-ice production in Laptev polynyas amount to 30 km3 and 73 km3 for the winters 2007/08 and 2008/09, respectively. The higher turbulent energy fluxes of open-water polynyas result in a 50-70% increase in sea-ice production (49 km3 in 2007/08 and 123 km3 in 2008/09). Our results suggest that previous studies have overestimated ice production in the Laptev Sea.

Impact of Laptev Sea flaw polynyas on the atmospheric boundary layer and ice production using idealized mesoscale simulations

The interaction between polynyas and the atmospheric boundary layer is examined in the Laptev Sea using the regional, non-hydrostatic Consortium for Small-scale Modelling (COSMO) atmosphere model. A thermodynamic sea-ice model is used to consider the response of sea-ice surface temperature to idealized atmospheric forcing. The idealized regimes represent atmospheric conditions that are typical for the Laptev Sea region. Cold wintertime conditions are investigated with sea-ice–ocean temperature differences of up to 40 K. The Laptev Sea flaw polynyas strongly modify the atmospheric boundary layer. Convectively mixed layers reach heights of up to 1200 m above the polynyas with temperature anomalies of more than 5 K. Horizontal transport of heat expands to areas more than 500 km downstream of the polynyas. Strong wind regimes lead to a more shallow mixed layer with strong near-surface modifications, while weaker wind regimes show a deeper, well-mixed convective boundary layer. Shallow mesoscale circulations occur in the vicinity of ice-free and thin-ice covered polynyas. They are forced by large turbulent and radiative heat fluxes from the surface of up to 789 W m−2, strong low-level thermally induced convergence and cold air flow from the orographic structure of the Taimyr Peninsula in the western Laptev Sea region. Based on the surface energy balance we derive potential sea-ice production rates between 8 and 25 cm d−1. These production rates are mainly determined by whether the polynyas are ice-free or covered by thin ice and by the wind strength.