Predictability of biomass burning in response to climate changes

Climate is an important control on biomass burning, but the sensitivity of fire to changes in temperature and moisture balance has not been quantified. We analyze sedimentary charcoal records to show that the changes in fire regime over the past 21,000 yrs are predictable from changes in regional climates. Analyses of paleo- fire data show that fire increases monotonically with changes in temperature and peaks at intermediate moisture levels, and that temperature is quantitatively the most important driver of changes in biomass burning over the past 21,000 yrs. Given that a similar relationship between climate drivers and fire emerges from analyses of the interannual variability in biomass burning shown by remote-sensing observations of month-by-month burnt area between 1996 and 2008, our results signal a serious cause for concern in the face of continuing global warming.

Scientific rationale for Saturn׳s in situ exploration

Remote sensing observations meet some limitations when used to study the bulk atmospheric composition of the giant planets of our solar system. A remarkable example of the superiority of in situ probe measurements is illustrated by the exploration of Jupiter, where key measurements such as the determination of the noble gases׳ abundances and the precise measurement of the helium mixing ratio have only been made available through in situ measurements by the Galileo probe. This paper describes the main scientific goals to be addressed by the future in situ exploration of Saturn placing the Galileo probe exploration of Jupiter in a broader context and before the future probe exploration of the more remote ice giants. In situ exploration of Saturn׳s atmosphere addresses two broad themes that are discussed throughout this paper: first, the formation history of our solar system and second, the processes at play in planetary atmospheres. In this context, we detail the reasons why measurements of Saturn׳s bulk elemental and isotopic composition would place important constraints on the volatile reservoirs in the protosolar nebula. We also show that the in situ measurement of CO (or any other disequilibrium species that is depleted by reaction with water) in Saturn׳s upper troposphere may help constraining its bulk O/H ratio. We compare predictions of Jupiter and Saturn׳s bulk compositions from different formation scenarios, and highlight the key measurements required to distinguish competing theories to shed light on giant planet formation as a common process in planetary systems with potential applications to most extrasolar systems. In situ measurements of Saturn׳s stratospheric and tropospheric dynamics, chemistry and cloud-forming processes will provide access to phenomena unreachable to remote sensing studies. Different mission architectures are envisaged, which would benefit from strong international collaborations, all based on an entry probe that would descend through Saturn׳s stratosphere and troposphere under parachute down to a minimum of 10 bar of atmospheric pressure. We finally discuss the science payload required on a Saturn probe to match the measurement requirements.

Effect of the Tiger Stripes on the water vapor distribution in Enceladus' exosphere

The jet activity emanating from Enceladus' exosphere south pole region observed by Cassini is a subject of intensive study. The in situ and remote sensing observations performed since 2005 triggered an active modeling campaign. Such modeling is essential for better understanding of the measurements performed by individual instruments as well as to link them for a more complete picture of the volatile and ice grain distribution in Enceladus' exosphere. This paper is focused on the investigation of the effect that diffuse gas sources along the Tiger Stripes have on distribution of the water vapor in Enceladus' exosphere using the updated version of our multiplume model. We have found that accounting for the gas production by Tiger Stripes is critical for interpretation of the Cassini data. According to our calculations, sources along the Tiger Stripes (apart from those originally identified by Spitale and Porco (2007)) must contribute about 23–32% to the total plume source rate, which varies in the range of (6.4–29) ×1027 s−1. The effect of the previously unidentified source suggested in the paper is found to be critical for explaining the Ultraviolet Imaging Spectrograph 2007 and 2010 observations in the whole range of the elapsed times.

Sublimation of ice–tholins mixtures: A morphological and spectro-photometric study

Sublimation, the direct transition from solid to gas phase, is a process responsible for shaping and changing the reflectance properties of many Solar System surfaces. In this study, we have characterized the evolution of the structure/texture and of the visible and near-infrared (VIS–NIR) spectral reflectance of surfaces made of water ice mixed with analogues of complex extraterrestrial organic matter, named tholins, under low temperature (<-70° C) and pressure (10-⁵mbar) conditions. The experiments were carried out in the SCITEAS simulation setup recently built as part of the Laboratory for Outflow Studies of Sublimating Materials (LOSSy) at the University of Bern (Pommerol, A. et al. [2015a]. Planet. Space Sci. 109–110, 106–122). As the water ice sublimated, we observed in situ the formation of a sublimation lag deposit made of a water-free porous (>90% porosity) network of organic filaments on top of the ice. The temporal evolution of the tholins and water ice spectral features (reflectance at the absorption bands wavelengths, red slope, from 0.40 to 1.90lm) are analyzed throughout the sublimation of the samples. We studied how different mixtures of tholins with water (0.1 wt.% tholins as coating or inclusions within the water particles), and different ice particle sizes (4.5 ± 2.5 or 67 ± 31lm) influence the morphological and spectral evolutions of the samples. The sublimation of the ice below the mantle produces a gas flow responsible for the ejection of mm to cm-sized fragments of the deposit in outbursts-like events. The results show remarkable differences between these samples in term of mantle structure, speed of mantle building, rates and surface area of mantle ejections. These data provide useful references for interpreting remote-sensing observations of icy Solar System surfaces, in particular the activity of comet nuclei where sublimation of organic-rich ices and deposition of organic-dust particles likely play a major role. Consequently, the data presented here could be of high interest for the interpretation of Rosetta, and also New Horizons, observations.

Sublimation of water ice mixed with silicates and tholins: Evolution of surface texture and reflectance spectra, with implications for comets

The surfaces of many objects in the Solar System comprise substantial quantities of water ice sometimes mixed with minerals and/or organic molecules. The sublimation of the ice changes the structural and optical properties of these objects. We present laboratory data on the evolution of the structure and the visible and near-infrared spectral reflectance of icy surface analogues of cometary ices, made of water ice, complex organic matter (tholins) and silicates, as they undergo sublimation under low temperature (<-70°C) and pressure (10-⁵mbar) conditions inside the SCITEAS simulation chamber. As the water ice sublimated, we observed in situ the formation of a porous sublimation lag deposit, or sublimation mantle, at the top of the ice. This mantle is a network of filaments made of the non-volatile particles. Organics or phyllosilicates grains, able to interact via stronger inter-particulate forces than olivine grains, can form a foam-like structure having internal cohesiveness, holding olivine grains together. As this mantle builds-up, the band depths of the sub-surface water ice are attenuated until complete extinction under only few millimeters of mantle. Optically thick sublimation mantles are mainly featureless in the near infrared. The absorption bands of the minerals present in the mantle are weak, or even totally absent if minerals are mixed with organics which largely dominate the VIS–NIR reflectance spectrum. During sublimation, ejections of large fragments of mantle, triggered by the gas flow, expose ice particles to the surface. The contrast of brightness between mantled and ice-exposed areas depends on the wavelength range and the dust/ice ratio considered. We describe how the chemical nature of the non-volatiles, the size of their particles, the way they are mixed with the ice and the dust/ice mass ratio influence the texture, activity and spectro-photometric properties of the sublimation mantles. These data provide useful references for interpreting remote-sensing observations of comets and also icy satellites or trans-neptunian objects.

Ice and snow measurements during Nathaniel B. Palmer cruise NBP0709 (SIMBA experiment)

The Sea Ice Mass Balance in the Antarctic (SIMBA) experiment was conducted from the RVIB N.B. Palmer in September and October 2007 in the Bellingshausen Sea in an area recently experiencing considerable changes in both climate and sea ice cover. Snow and ice properties were observed at 3 short-term stations and a 27-day drift station (Ice Station Belgica, ISB) during the winter-spring transition. Repeat measurements were performed on sea ice and snow cover at 5 ISB sites, each having different physical characteristics, with mean ice (snow) thicknesses varying from 0.6 m (0.1 m) to 2.3 m (0.7 m). Ice cores retrieved every five days from 2 sites and measured for physical, biological, and chemical properties. Three ice mass-balance buoys (IMBs) provided continuous records of snow and ice thickness and temperature. Meteorological conditions changed from warm fronts with high winds and precipitation followed by cold and calm periods through four cycles during ISB. The snow cover regulated temperature flux and controlled the physical regime in which sea ice morphology changed. Level thin ice areas had little snow accumulation and experienced greater thermal fluctuations resulting in brine salinity and volume changes, and winter maximum thermodynamic growth of ~0.6 m in this region. Flooding and snow-ice formation occurred during cold spells in ice and snow of intermediate thickness. In contrast, little snow-ice formed in flooded areas with thicker ice and snow cover, instead nearly isothermal, highly permeable ice persisted. In spring, short-lived cold air episodes did not effectively penetrate the sea ice nor overcome the effect of ocean heat flux, thus favoring net ice thinning from bottom melt over ice thickening from snow-ice growth, in all cases. These warm ice conditions were consistent with regional remote sensing observations of earlier ice breakup and a shorter sea ice season, more recently observed in the Bellingshausen Sea.

Charcoal records of two sediment cores off SW Africa

We analyze sedimentary charcoal records to show that the changes in fire regime over the past 21,000 yrs are predictable from changes in regional climates. Analyses of paleo- fire data show that fire increases monotonically with changes in temperature and peaks at intermediate moisture levels, and that temperature is quantitatively the most important driver of changes in biomass burning over the past 21,000 yrs. Given that a similar relationship between climate drivers and fire emerges from analyses of the interannual variability in biomass burning shown by remote-sensing observations of month-by-month burnt area between 1996 and 2008, our results signal a serious cause for concern in the face of continuing global warming.

Global LAI uncertainty and relative uncertainty datasets derived from a Triple Collocation Error Model (TCEM)

Uncertainty information for global leaf area index (LAI) products is important for global modeling studies but usually difficult to systematically obtain at a global scale. Here, we present a new method that cross-validates existing global LAI products and produces consistent uncertainty information. The method is based on a triple collocation error model (TCEM) that assumes errors among LAI products are not correlated. Global monthly absolute and relative uncertainties, in 0.05° spatial resolutions, were generated for MODIS, CYCLOPES, and GLOBCARBON LAI products, with reasonable agreement in terms of spatial patterns and biome types. CYCLOPES shows the lowest absolute and relative uncertainties, followed by GLOBCARBON and MODIS. Grasses, crops, shrubs, and savannas usually have lower uncertainties than forests in association with the relatively larger forest LAI. With their densely vegetated canopies, tropical regions exhibit the highest absolute uncertainties but the lowest relative uncertainties, the latter of which tend to increase with higher latitudes. The estimated uncertainties of CYCLOPES generally meet the quality requirements (± 0.5) proposed by the Global Climate Observing System (GCOS), whereas for MODIS and GLOBCARBON only non-forest biome types have met the requirement. Nevertheless, none of the products seems to be within a relative uncertainty requirements of 20%. Further independent validation and comparative studies are expected to provide a fair assessment of uncertainties derived from TCEM. Overall, the proposed TCEM is straightforward and could be automated for the systematic processing of real time remote sensing observations to provide theoretical uncertainty information for a wider range of land products.

Planetary Penetrators for Sample Return Missions

Thesis (Master's)--University of Washington, 2016-06

Probabilistic uncertainty in an interoperable framework

This thesis provides an interoperable language for quantifying uncertainty using probability theory. A general introduction to interoperability and uncertainty is given, with particular emphasis on the geospatial domain. Existing interoperable standards used within the geospatial sciences are reviewed, including Geography Markup Language (GML), Observations and Measurements (O&M) and the Web Processing Service (WPS) specifications. The importance of uncertainty in geospatial data is identified and probability theory is examined as a mechanism for quantifying these uncertainties. The Uncertainty Markup Language (UncertML) is presented as a solution to the lack of an interoperable standard for quantifying uncertainty. UncertML is capable of describing uncertainty using statistics, probability distributions or a series of realisations. The capabilities of UncertML are demonstrated through a series of XML examples. This thesis then provides a series of example use cases where UncertML is integrated with existing standards in a variety of applications. The Sensor Observation Service - a service for querying and retrieving sensor-observed data - is extended to provide a standardised method for quantifying the inherent uncertainties in sensor observations. The INTAMAP project demonstrates how UncertML can be used to aid uncertainty propagation using a WPS by allowing UncertML as input and output data. The flexibility of UncertML is demonstrated with an extension to the GML geometry schemas to allow positional uncertainty to be quantified. Further applications and developments of UncertML are discussed.

Unstructured grid modelling of offshore wind farm impacts on seasonally stratified shelf seas

Shelf seas comprise approximately 7% of the world’s oceans and host enormous economic activity. Development of energy installations (e.g. Offshore Wind Farms (OWFs), tidal turbines) in response to increased demand for renewable energy requires a careful analysis of potential impacts. Recent remote sensing observations have identified kilometrescale impacts from OWFs. Existing modelling evaluating monopile impacts has fallen into two camps: small-scale models with individually resolved turbines looking at local effects; and large-scale analyses but with sub-grid scale turbine parameterisations. This work straddles both scales through a 3D unstructured grid model (FVCOM): wind turbine monopiles in the eastern Irish Sea are explicitly described in the grid whilst the overall grid domain covers the south-western UK shelf. Localised regions of decreased velocity extend up to 250 times the monopile diameter away from the monopile. Shelf-wide, the amplitude of the M2 tidal constituent increases by up to 7%. The turbines enhance localised vertical mixing which decreases seasonal stratification. The spatial extent of this extends well beyond the turbines into the surrounding seas. With significant expansion of OWFs on continental shelves, this work highlights the importance of how OWFs may impact coastal (e.g. increased flooding risk) and offshore (e.g. stratification and nutrient cycling) areas.

Unstructured grid modelling of offshore wind farm impacts on seasonally stratified shelf seas

Shelf seas comprise approximately 7% of the world’s oceans and host enormous economic activity. Development of energy installations (e.g. Offshore Wind Farms (OWFs), tidal turbines) in response to increased demand for renewable energy requires a careful analysis of potential impacts. Recent remote sensing observations have identified kilometrescale impacts from OWFs. Existing modelling evaluating monopile impacts has fallen into two camps: small-scale models with individually resolved turbines looking at local effects; and large-scale analyses but with sub-grid scale turbine parameterisations. This work straddles both scales through a 3D unstructured grid model (FVCOM): wind turbine monopiles in the eastern Irish Sea are explicitly described in the grid whilst the overall grid domain covers the south-western UK shelf. Localised regions of decreased velocity extend up to 250 times the monopile diameter away from the monopile. Shelf-wide, the amplitude of the M2 tidal constituent increases by up to 7%. The turbines enhance localised vertical mixing which decreases seasonal stratification. The spatial extent of this extends well beyond the turbines into the surrounding seas. With significant expansion of OWFs on continental shelves, this work highlights the importance of how OWFs may impact coastal (e.g. increased flooding risk) and offshore (e.g. stratification and nutrient cycling) areas.

Point-and-shoot: rapid quantitative detection methods for on-site food fraud analysis – moving out of the laboratory and into the food supply chain

Major food adulteration and contamination events occur with alarming regularity and are known to be episodic, with the question being not if but when another large-scale food safety/integrity incident will occur. Indeed, the challenges of maintaining food security are now internationally recognised. The ever increasing scale and complexity of food supply networks can lead to them becoming significantly more vulnerable to fraud and contamination, and potentially dysfunctional. This can make the task of deciding which analytical methods are more suitable to collect and analyse (bio)chemical data within complex food supply chains, at targeted points of vulnerability, that much more challenging. It is evident that those working within and associated with the food industry are seeking rapid, user-friendly methods to detect food fraud and contamination, and rapid/high-throughput screening methods for the analysis of food in general. In addition to being robust and reproducible, these methods should be portable and ideally handheld and/or remote sensor devices, that can be taken to or be positioned on/at-line at points of vulnerability along complex food supply networks and require a minimum amount of background training to acquire information rich data rapidly (ergo point-and-shoot). Here we briefly discuss a range of spectrometry and spectroscopy based approaches, many of which are commercially available, as well as other methods currently under development. We discuss a future perspective of how this range of detection methods in the growing sensor portfolio, along with developments in computational and information sciences such as predictive computing and the Internet of Things, will together form systems- and technology-based approaches that significantly reduce the areas of vulnerability to food crime within food supply chains. As food fraud is a problem of systems and therefore requires systems level solutions and thinking.

Thermal Tracking and Estimation for Microprocessors

Due to increasing integration density and operating frequency of today's high performance processors, the temperature of a typical chip can easily exceed 100 degrees Celsius. However, the runtime thermal state of a chip is very hard to predict and manage due to the random nature in computing workloads, as well as the process, voltage and ambient temperature variability (together called PVT variability). The uneven nature (both in time and space) of the heat dissipation of the chip could lead to severe reliability issues and error-prone chip behavior (e.g. timing errors). Many dynamic power/thermal management techniques have been proposed to address this issue such as dynamic voltage and frequency scaling (DVFS), clock gating and etc. However, most of such techniques require accurate knowledge of the runtime thermal state of the chip to make efficient and effective control decisions. In this work we address the problem of tracking and managing the temperature of microprocessors which include the following sub-problems: (1) how to design an efficient sensor-based thermal tracking system on a given design that could provide accurate real-time temperature feedback; (2) what statistical techniques could be used to estimate the full-chip thermal profile based on very limited (and possibly noise-corrupted) sensor observations; (3) how do we adapt to changes in the underlying system's behavior, since such changes could impact the accuracy of our thermal estimation. The thermal tracking methodology proposed in this work is enabled by on-chip sensors which are already implemented in many modern processors. We first investigate the underlying relationship between heat distribution and power consumption, then we introduce an accurate thermal model for the chip system. Based on this model, we characterize the temperature correlation that exists among different chip modules and explore statistical approaches (such as those based on Kalman filter) that could utilize such correlation to estimate the accurate chip-level thermal profiles in real time. Such estimation is performed based on limited sensor information because sensors are usually resource constrained and noise-corrupted. We also took a further step to extend the standard Kalman filter approach to account for (1) nonlinear effects such as leakage-temperature interdependency and (2) varying statistical characteristics in the underlying system model. The proposed thermal tracking infrastructure and estimation algorithms could consistently generate accurate thermal estimates even when the system is switching among workloads that have very distinct characteristics. Through experiments, our approaches have demonstrated promising results with much higher accuracy compared to existing approaches. Such results can be used to ensure thermal reliability and improve the effectiveness of dynamic thermal management techniques.

Observations of volcanic emissions using satellite remote sensing

Volcanoes pose a threat to the human population at regional and global scales and so efficient monitoring is essential in order to effectively manage and mitigate the risks that they pose. Volcano monitoring from space has been possible for over thirty years and now, more than ever, a suite of instruments exists with the capability to observe emissions of gas and ash from a unique perspective. The goal of this research is to demonstrate the use of a range of satellite-based sensors in order to detect and quantify volcanic sulphur dioxide, and to assess the relative performances of each sensor against one another. Such comparisons are important in order to standardise retrievals and permit better estimations of the global contribution of sulphur dioxide to the atmosphere from volcanoes for climate modelling. In this work, retrievals of volcanic sulphur dioxide from a number of instruments are compared, and the individual performances at quantifying emissions from large, explosive volcanic eruptions are assessed. Retrievals vary widely from sensor to sensor, and often the use of a number of sensors in synergy can provide the most complete picture, rather than just one instrument alone. Volcanic emissions have the ability to result significant economic loses by grounding aircraft due to the high risk associated with ash encountering aircraft. As sulphur dioxide is often easier to measure than ash, it is often used as a proxy. This work examines whether this is a reasonable assumption, using the Icelandic eruption in early 2010 as a case study. Results indicate that although the two species are for the most part collocated, separation can occur under some conditions, meaning that it is essential to accurately measure both species in order to provide effective hazard mitigation. Finally, the usefulness of satellite remote sensing in quantifying the passive degassing from Turrialba, Costa Rica is demonstrated. The increase in activity from 2005 – 2010 can be observed in satellite data prior to the phreatic phase of early 2010, and can therefore potentially provide a useful indication of changing activity at some volcanoes.