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At least 163 records · Page 9

MERRA Analytic Services: Meeting the Big Data Challenges of Climate Science Through Cloud-enabled Climate Analytics-as-a-service

Climate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however, we it see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a service. These elements are essential because in the aggregate they lead to generativity, a capacity for self-assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Services (MERRAAS) is an example of cloud-enabled CAaaS built on this principle. MERRAAS enables MapReduce analytics over NASAs Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing importance to scientists doing climate change research and a wide range of decision support applications. MERRAAS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capabilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRAAS has been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to organizational change, fosters innovation and experimentation, facilitates technology transfer, and provides the agility required to meet our customers' increasing and changing needs. Cloud Computing is providing a new tier in the data services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. For climate science, Cloud Computing's capacity to engage communities in the construction of new capabilies is perhaps the most important link between Cloud Computing and Big Data.

Data Analytics↗

New parameterizations and sensitivities for simple climate models

This paper presents a reexamination of the earth radiation budget parameterization of energy balance climate models in light of data collected over the last 12 years. The study consists of three parts: (1) an examination of the infrared terrestrial radiation to space and its relationship to the surface temperature field on time scales from 1 month to 10 years; (2) an examination of the albedo of the earth with special attention to the seasonal cycle of snow and clouds; (3) solutions for the seasonal cycle using the new parameterizations with special attention to changes in sensitivity. While the infrared parameterization is not dramatically different from that used in the past, the albedo in the new data suggest that a stronger latitude dependence be employed. After retuning the diffusion coefficient the simulation results for the present climate generally show only a slight dependence on the new parameters. Also, the sensitivity parameter for the model is still about the same (1.25 C for a 1 percent increase of solar constant) for the linear models and for the nonlinear models that include a seasonal snow line albedo feedback (1.34 C). One interesting feature is that a clear-sky planet with a snow line albedo feedback has a significantly higher sensitivity (2.57 C) due to the absence of smoothing normally occurring in the presence of average cloud cover.

Graves, Charles E.↗

The Corfu Landslide: Analog to Giant Landslides on Mars

In an analog to the great landslides of the Vales Marineris, Mars, a detailed study was made of the Corfu Landslide in south-central Washington. This prehistoric slide is located on the northern flank of the Saddle Mountains, southwest of Othello, Washington. The slide covers a 13 square km area centered on section 11 of T.15N., R.27E., Willamette Meridian, adjacent to the Corfu townsite. Approximately 1 cubic km of material is involved in sliding that was probably initiated by Missoula flooding through the Channeled Scabland. It is concluded that there were four primary factors involved in the initiation of the Corfu landsliding: (1) A slip surface was present at the right orientation; (2) Glacial flooding undercut the slope; (3) Wetter climatic conditions prevailed during that time period; and (4) Some seismic vibrations, known to occur locally, probably acted as a trigger. These factors show that special conditions were required in conjunction to produce landsliding. Studies in progress of the Vales Marieneris suggest that the same factors probably contributed to landsliding there.

Scott W. Lewis↗

Geophysics, Oceanography

Development of decade-long time series of global surface wind measurements for studies ofseasonal-to-interannual climate variability presents unique challenges for space- borne instrumentationbecause of the necessity to combine data sets of 3- to 5-year lifetimes. Before the first Special SensorMicrowave Imager (SSMI), which was launched on the Defence Meteorological Satellite Program(DMSP) F8 spacecraft in July 1987, stopped recording wind speed in December 1991, another SSMIwas launched on DMSP F10 in December 1991. Interpretation of the 1987 - 1993 composite timeseries is dependent upon the space and time characteristics of the differences between concurrent F8and F10 SSMI measurements. This paper emphasizes large geographical regions and 1-month timescale. The F8-F10 area-weighted difference between 60 degrees S and 60 degrees S during 305 daysof 1991 (-0.12 m s^(-1)) was comparable to the year-to-year wind speed variations during 1988-1991. The 10 degree-zonal averaged monthly mean F8-F10 difference was negative (positive) forwind speeds less (greater) than 7.9 m s^(-1), reaching - 0.43(0.32) m s^(-1) at 5(10) m s^(-1). The10 degree-zonal averaged monthly mean F8-F10 bias had considerable variations throughout the yearand between 60 degrees S - 60 degrees N, with the largest temporal variation (1.4 m s^(-1)) in the 50degrees - 60 degrees N region from February to April. The 1991 average value of the monthly meanroot-mean-square (rms) difference between F8 and F10 daily wind speeds in 10 degree-longitudinalbands was 2.0 m s^(-1) over 60 degrees S - 60 degrees N, the amplitude of the annual cycle of therms difference was largest in the northern hemisphere middle latitudes, and the rms difference wasrelated to the wind speed (e.g., at 6 and 10 m s^(-1), the rms difference was 1.7 and 2.7 m s^(-1),respectively). The relationship between monthly mean 1/3 degrees x 1/3 degrees F8-F10 SSMI windspeed differences and integrated water vapor and liquid water content in the atmosphere is discussed.

Halpern, D.↗

Comparison of NASA Team2 and AES-York Ice Concentration Algorithms Against Operational Ice Charts From the Canadian Ice Service

Ice concentration retrieved from spaceborne passive-microwave observations is a prime input to operational sea-ice-monitoring programs, numerical weather prediction models, and global climate models. Atmospheric Environment Service (AES)- York and the Enhanced National Aeronautics and Space Administration Team (NT2) are two algorithms that calculate ice concentration from Special Sensor Microwave/Imager observations. This paper furnishes a comparison between ice concentrations (total, thin, and thick types) output from NT2 and AES-York algorithms against the corresponding estimates from the operational analysis of Radarsat images in the Canadian Ice Service (CIS). A new data fusion technique, which incorporates the actual sensor's footprint, was developed to facilitate this study. Results have shown that the NT2 and AES-York algorithms underestimate total ice concentration by 18.35% and 9.66% concentration counts on average, with 16.8% and 15.35% standard deviation, respectively. However, the retrieved concentrations of thin and thick ice are in much more discrepancy with the operational CIS estimates when either one of these two types dominates the viewing area. This is more likely to occur when the total ice concentration approaches 100%. If thin and thick ice types coexist in comparable concentrations, the algorithms' estimates agree with CIS'S estimates. In terms of ice concentration retrieval, thin ice is more problematic than thick ice. The concept of using a single tie point to represent a thin ice surface is not realistic and provides the largest error source for retrieval accuracy. While AES-York provides total ice concentration in slightly more agreement with CIS'S estimates, NT2 provides better agreement in retrieving thin and thick ice concentrations.

Shokr, Mohammed↗

Climate change–induced stress disrupts ectomycorrhizal interaction networks at the boreal–temperate ecotone

The interaction networks formed by ectomycorrhizal fungi (EMF) and their tree hosts, which are important to both forest recruitment and ecosystem carbon and nutrient retention, may be particularly susceptible to climate change at the boreal–temperate forest ecotone where environmental conditions are changing rapidly. Here, we quantified the compositional and functional trait responses of EMF communities and their interaction networks with two boreal ( Pinus banksiana and Betula papyrifera ) and two temperate ( Pinus strobus and Quercus macrocarpa ) hosts to a factorial combination of experimentally elevated temperatures and reduced rainfall in a long-term open-air field experiment. The study was conducted at the B4WarmED (Boreal Forest Warming at an Ecotone in Danger) experiment in Minnesota, USA, where infrared lamps and buried heating cables elevate temperatures (ambient, +3.1 °C) and rain-out shelters reduce growing season precipitation (ambient, ~30% reduction). EMF communities were characterized and interaction networks inferred from metabarcoding of fungal-colonized root tips. Warming and rainfall reduction significantly altered EMF community composition, leading to an increase in the relative abundance of EMF with contact-short distance exploration types. These compositional changes, which likely limited the capacity for mycelial connections between trees, corresponded with shifts from highly redundant EMF interaction networks under ambient conditions to less redundant (more specialized) networks. Further, the observed changes in EMF communities and interaction networks were correlated with changes in soil moisture and host photosynthesis. Collectively, these results indicate that the projected changes in climate will likely lead to significant shifts in the traits, structure, and integrity of EMF communities as well as their interaction networks in forest ecosystems at the boreal–temperate ecotone.

54 ENVIRONMENTAL SCIENCES↗

Estimation of monthly rainfall over Japan and surrounding waters from a combination of low-orbit microwave and geosynchronous IR data

A method is described for estimating the mean monthly rainfall data for climate studies by combining the geosynchronous IR and low-orbit microwave data. The microwave technique uses the brightness temperature at 37 and 86 GHz from the Special Sensor Microwave/Imager instrument on board the DMSP satellite to define raining areas over water and land, and the 86-GHz scattering signal to assign rain rate based on cloud model-microwave calculations. The IR estimates are initially computed separately, using hourly data from the Japanese Geostationary Meteorological Satellite. Results show that, in areas where the microwave technique performs well, the combined microwave-IR monthly total estimates have better error statistics than either the microwave of the IR techniques individually.

Adler, Robert F.↗

Better Weather Prediction and Climate Diagnostics Using Rainfall Measurements from Space

Progress in understanding of the role of water in global weather and climate is currently limited by our knowledge of the spatial and temporal variability of primary hydrological fields such as precipitation and evaporation. The Tropical Rainfall Measuring Mission (TRMM) has recently demonstrated that use of microwave-based rainfall observations from space in data assimilation can provide better climate data sets and improve short-range weather forecasting. At NASA, we have been exploring non-traditional approaches to assimilating TRMM Microwave Imager (TMI) and Special Sensor Microwavehager (SSM/I) surface rain rate and latent heating profile information in global systems. In this talk we show that assimilating microwave rain rates using a continuous variational assimilation scheme based on moisture tendency corrections improves quantitative precipitation estimates (QPE) and related clouds, radiation energy fluxes, and large-scale circulations in the Goddard Earth Observing System (GEOS) reanalyses. Short-range forecasts initialized with these improved analyses also yield better QPE scores and storm track predictions for Hurricanes Bonnie and Floyd. We present a status report on current efforts to assimilate convective and stratiform latent heating profile information within the general variational framework of model parameter estimation to seek further improvements. Within the next 5 years, there will be a gradual increase in microwave rain products available from operational and research satellites, culminating to a target constellation of 9 satellites to provide global rain measurements every 3 hours with the proposed Global Precipitation Measurement (GPM) mission in 2007/2008. Based on what has been learned from TRMM, there is a high degree of confidence that these observations can play a'major role in improving weather forecasts and producing better global datasets for understanding the Earth's water and energy cycle. The key to success is to adopt an integrated approach to retrieval, validation, modeling, and data assimilation in a coordinated end-to-end observation-application program.

Hou, Arthur↗

Identification of Human-Induced Changes in Atmospheric Moisture Content

Data from the satellite-based Special Sensor Microwave Imager (SSM/I) show that the total atmospheric moisture content over oceans has increased by 0.41 kg/sq m per decade since 1988. Results from current climate models indicate that water vapor increases of this magnitude cannot be explained by climate noise alone. In a formal detection and attribution analysis using the pooled results from 22 different climate models, the simulated "fingerprint" pattern of anthropogenically caused changes in water vapor is identifiable with high statistical confidence in the SSM/I data. Experiments in which forcing factors are varied individually suggest that this fingerprint "match" is primarily due to human-caused increases in greenhouse gases and not to solar forcing or recovery from the eruption of Mount Pinatubo. Our findings provide preliminary evidence of an emerging anthropogenic signal in the moisture content of earth's atmosphere.

Santer, B.D.↗

The Virtual Climate Data Server (vCDS): An iRODS-Based Data Management Software Appliance Supporting Climate Data Services and Virtualization-as-a-Service in the NASA Center for Climate Simulation

Scientific data services are becoming an important part of the NASA Center for Climate Simulation's mission. Our technological response to this expanding role is built around the concept of a Virtual Climate Data Server (vCDS), repetitive provisioning, image-based deployment and distribution, and virtualization-as-a-service. The vCDS is an iRODS-based data server specialized to the needs of a particular data-centric application. We use RPM scripts to build vCDS images in our local computing environment, our local Virtual Machine Environment, NASA s Nebula Cloud Services, and Amazon's Elastic Compute Cloud. Once provisioned into one or more of these virtualized resource classes, vCDSs can use iRODS s federation capabilities to create an integrated ecosystem of managed collections that is scalable and adaptable to changing resource requirements. This approach enables platform- or software-asa- service deployment of vCDS and allows the NCCS to offer virtualization-as-a-service: a capacity to respond in an agile way to new customer requests for data services.

Schnase, John L.↗

Special relativity effects for space-based coherent lidar experiments

There is a great need to develop a system that can measure accurately atmospheric wind profiles because an accurate data of wind profiles in the atmosphere constitutes single most input for reliable simulations of global climate numerical methods. Also such data helps us understand atmospheric circulation and climate dynamics better. Because of this need for accurate wind measurements, a space-based Laser Atmospheric Winds Sounder (LAWS) is being designed at MSFC to measure wind profiles in the lower atmosphere of the earth with an accuracy of 1 m/s at lower altitudes to 5m/s at higher altitudes. This system uses an orbiting spacecraft with a pulsed laser source and measures the Doppler shift between the transmitted and received frequencies to estimate the atmospheric wind velocities. If a significant return from the ground (sea) is possible, the spacecraft speed and height are estimated from it and these results and the Doppler shift are then used to estimate the wind velocities in the atmosphere. It is expected that at the proposed wavelengths, there will be enough backscatter from the aerosols but there may no be significant return from the ground. So a coherent (heterodyne) detection system is being proposed for signal processing because it can provide high signal to noise ratio and sensitivity and thus make the best use of low ground return. However, for a heterodyne detection scheme to provide the best results, it is important that the receiving aperture be aligned properly for the proposed wind sounder, this amounts to only a few microradians tolerance in alignment. It is suspected that the satellite motion relative to the ground may introduce errors in the order of a few microradians because of special relativity. Hence, the problem of laser scattering off a moving fixed target when the source and receiver are moving, which was not treated in the past in the literature, was analyzed in the following, using relativistic electrodynamics and applied to the case of the space-based coherent lidar, assuming flat ground. Here an interest in developing analytical expression for the location of the receiving point for the return with respect to the satellite, receiving angle and Doppler shift in frequency and amount of tip, all as measured in the satellite moving coordinate system and the diffuse scattering angle at the ground which does not require any compensation. All the three cases of retro-reflection, specular reflection and diffuse scattering by the ground should be treated though retro-reflection and diffuse scattering are more important.

Raogudimetla, V. S.↗

Understanding the Global Water and Energy Cycle Through Assimilation of Precipitation-Related Observations: Lessons from TRMM and Prospects for GPM

Understanding the Earth's climate and how it responds to climate perturbations relies on what we know about how atmospheric moisture, clouds, latent heating, and the large-scale circulation vary with changing climatic conditions. The physical process that links these key climate elements is precipitation. Improving the fidelity of precipitation-related fields in global analyses is essential for gaining a better understanding of the global water and energy cycle. In recent years, research and operational use of precipitation observations derived from microwave sensors such as the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and Special Sensor Microwave/Imager (SSM/I) have shown the tremendous potential of using these data to improve global modeling, data assimilation, and numerical weather prediction. We will give an overview of the benefits of assimilating TRMM and SSM/I rain rates and discuss developmental strategies for using space-based rainfall and rainfall-related observations to improve forecast models and climate datasets in preparation for the proposed multi-national Global Precipitation Mission (GPM).

Hou, Arthur↗

The status and prospects of materials for carbon capture technologies

In order to combat climate change, carbon dioxide (CO 2 ) emissions from industry, transportation, buildings, and other sources need to be captured and long-term stored. Decarbonization of these sources requires special types of materials that have high affinities for CO 2 . Potassium hydroxide is a benchmark aqueous sorbent that reacts with CO 2 to convert it into K 2 CO 3 and subsequently precipitated as CaCO 3 . Another class of carbon capture materials is solid sorbents that are usually functionalized with amines or have natural affinities for CO 2 . The next wave of materials for carbon capture under investigation includes activated carbon, metal–organic frameworks, zeolites, carbon nanotubes, and ionic liquids. In this issue of MRS Bulletin, some of these materials are highlighted, including solvents and sorbents, membranes, ionic liquids, and hydrides. Other materials that can capture CO2 from low concentrations of gas streams, such as air (direct air capture) are also discussed. Also covered in this issue are machine learning-based computer algorithms developed with the goal to speed up the progress of carbon capture materials development, and to design advanced materials with high CO 2 capacity, improved capture and release kinetics, and improved cyclic durability.

36 MATERIALS SCIENCE↗

Climate Impact of Primary Plastic Production

Plastics show the strongest production growth of all bulk materials over the last decade. The industry’s current growth trajectory is exponential and plastic production is expected to double or triple by 2050. The rapidly increasing production of plastics and the continued reliance on fossil fuels for production, have contributed to numerous environmental problems and health harms. As a result, plastic pollution has become an increasing threat to natural ecosystems, human health and climate. However, there is a lack of granularity on the contribution of the primary plastics specifically to greenhouse gas (GHG) emissions and their impact on the remaining global carbon budget needed to stay below a 1.5°C or 2°C global average temperature rise. In this report, we explore the contribution of primary plastic production to climate change disaggregated by polymer and technology. To this end, we have developed comprehensive bottom-up modeling of GHG emissions from global primary plastic production, with a special focus on polymer value chains. We have analyzed the results under various growth scenarios in the context of carbon budgets compatible with a 1.5°C global trajectory. Modeling includes the material flows of all production stages, processes and technologies used in primary plastic production value chains, including from the extraction of fossil fuels required for production to shaping the final product. We specifically focus on nine major types of fossil fuelbased plastic polymers that are produced and consumed in large quantities: three types of polyethylene (PE) – low-density (LDPE), linear low-density (LLDPE), and high-density (HDPE) – as well as polypropylene (PP); polyethylene terephthalate (PET); polyvinyl chloride (PVC); polystyrene (PS) and other key styrene-based plastics such as styrene acrylonitrile (SAN) and acrylonitrile butadiene styrene (ABS), and polyurethane (PU). Together these account for about 80% of plastics production.

54 ENVIRONMENTAL SCIENCES↗

Climate Impact of Primary Plastic Production

Plastics show the strongest production growth of all bulk materials over the last decade. The industry’s current growth trajectory is exponential and plastic production is expected to double or triple by 2050. The rapidly increasing production of plastics and the continued reliance on fossil fuels for production, have contributed to numerous environmental problems and health harms. As a result, plastic pollution has become an increasing threat to natural ecosystems, human health and climate. However, there is a lack of granularity on the contribution of the primary plastics specifically to greenhouse gas (GHG) emissions and their impact on the remaining global carbon budget needed to stay below a 1.5°C or 2°C global average temperature rise. In this report, we explore the contribution of primary plastic production to climate change disaggregated by polymer and technology. To this end, we have developed comprehensive bottom-up modeling of GHG emissions from global primary plastic production, with a special focus on polymer value chains. We have analyzed the results under various growth scenarios in the context of carbon budgets compatible with a 1.5°C global trajectory. Modeling includes the material flows of all production stages, processes and technologies used in primary plastic production value chains, including from the extraction of fossil fuels required for production to shaping the final product. We specifically focus on nine major types of fossil fuel-based plastic polymers that are produced and consumed in large quantities: three types of polyethylene (PE) – low-density (LDPE), linear low-density (LLDPE), and high-density (HDPE) – as well as polypropylene (PP); polyethylene terephthalate (PET); polyvinyl chloride (PVC); polystyrene (PS) and other key styrene-based plastics such as styrene acrylonitrile (SAN) and acrylonitrile butadiene styrene (ABS), and polyurethane (PU). Together these account for about 80% of plastics production.

54 ENVIRONMENTAL SCIENCES↗

Conference Summary: First International Conference on Global Warming and the Next Ice Age

The First International Conference on Global Warming and the Next Ice Age was convened in Halifax, Nova Scotia, August 19-24, 2001. The conference program began each day with a 30 minute live classical music performances of truly international quality before the beginning business. Ample time for panel discussions was also scheduled. The general public was invited to attend and participate in a special evening panel session on the last day of the conference. The unusual and somewhat provocative title of the conference was designed to attract diverse views on global climate change. This summary attempts to accurately reflect the tone and flavor of the lively discussions which resulted. Presentations ranged from factors forcing current climate to those in effect across the span of time from the Proterozoic "snowball Earth" epoch to 50,000 years in the future. Although, as should be expected, attendees at the conference arrived with opinions on some of the controversial issues regarding climate change, and no-one openly admitted to a 'conversion' from their initial point of view, the interdisciplinary nature of the formal presentations, poster discussions, panels, and abundant informal discourse helped to place the attendees' personal perspectives into a broader, more diversified context.

Wetzel, Peter J.↗

Satellite Observation Systems for Polar Climate Change Studies

The key observational tools for detecting large scale changes of various parameters in the polar regions have been satellite sensors. The sensors include passive and active satellite systems in the visible, infrared and microwave frequencies. The monitoring started with Tiros and Nimbus research satellites series in the 1970s but during the period, not much data was stored digitally because of limitations and cost of the needed storage systems. Continuous global data came about starting with the launch of ocean color, passive microwave, and thermal infrared sensors on board Nimbus-7 and Synthetic Aperture Radar, Radar Altimeter and Scatterometer on board SeaSat satellite both launched in 1978. The Nimbus-7 lasted longer than expected and provided about 9 years of useful data while SeaSat quit working after 3 months but provided very useful data that became the baseline for follow-up systems with similar capabilities. Over the years, many new sensors were launched, some from Japan Aeronautics and Space Agency (JAXA), some from the European Space Agency (ESA) and more recently, from RuSSia, China, Korea, Canada and India. For polar studies, among the most useful sensors has been the passive microwave sensor which provides day/night and almost all weather observation of the surface. The sensor provide sea surface temperature, precipitation, wind, water vapor and sea ice concentration data that have been very useful in monitoring the climate of the region. More than 30 years of such data are now available, starting with the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7, the Special Scanning Microwave/Imager (SSM/I) on board a Defense Meteorological Satellite Program (DMSP) and the Advanced Microwave Scanning Radiometer on board the EOS/ Aqua satellite. The techniques that have been developed to derive geophysical parameters from data provided by these and other sensors and associated instrumental and algorithm errors and validation techniques will be discussed. An important issue is the organization and storage of hundreds of terabytes of data collected by even just a few of these satellite sensors. Advances in mass storage and computer technology have made it possible to overcome many of the collection and archival problems and the availability of comprehensive satellite data sets put together by NASA's Earth Observing System project will be discussed.

Comiso, Josefino C.↗

Editorial: North Pacific Environment and Paleoclimate from the Late Pleistocene to Present

The vast area of the North Pacific, spanning ~55° longitude, represents a challenge for documenting and understanding the geologic history of ocean, atmosphere, and terrestrial environmental change. This special issue highlights site-specific analyses to address various questions and provides clues that arise in response to continued North Pacific warming today in a rapidly changing climate (Figure 1). The emergence of new methods and novel application of existing methods serve to enhance our fundamental understanding of natural modes of climate variability driven by ocean and atmospheric circulation patterns, including the role of external (e.g., insolation) vs. internal forcing [e.g., El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO)]. Included in this volume are geographically diverse studies that present new and traditional methods for the interpretation of climate records drawn from pollen, macrofossils, tree rings, diatoms, grain size, and glacial studies. Many provide new geographic comparisons, such as Kamchatka and Hawaii, or emerge from novel geologic archives and environments, such as the marine shelf, a thermokarst lake, and a fossil forest.

Jones, Miriam C.↗