Stable isotope geochemistry of terrestrial carbonates provides important opportunities to answer questions about climates, environments, and ecosystems both in the present day and the geologic past. Here we present a case study from the Cretaceous Newark Canyon Formation (NCF) type section (~98–113 Ma), where we explore how climate and depositional settings influence the stable isotope record in highly variable lacustrine and palustrine carbonates. The NCF was deposited within the hinterland of the Sevier orogenic belt and allows us to examine how North American terrestrial climate changed during the mid-Cretaceous, a time of potentially significant regional surface uplift and increasing global temperatures related to the Cretaceous Thermal Maximum (Di Fiori et al., 2020; Huber et al., 2018). In this study, we find substantial inter- and intra-facies heterogeneity, despite having formed in the same overall climate setting, highlighting the differences between lacustrine and palustrine environments. Stable carbon, oxygen, and clumped isotopes (δ13C, δ18Ocarbonate, and Δ47) paired with optical and cathodoluminescence petrography from along-strike lateral and vertical stratigraphic sections show significant isotopic variability between and within seven carbonate facies (Fetrow et al., 2020). Palustrine deposition is interpreted to have occurred along a spectrum of shallow water depths preserved in two key palustrine sub-facies endmembers – shallower mottled micrite and deeper pebbly, peloid-rich micrite. These record mean Δ47 temperatures of 51ºC and 44°C, respectively. The mottled micrite has heavier calculated δ18O of formation water (δ18Owater) values indicating increased evaporative enrichment, which suggests more intense desiccation during deposition. Lacustrine sediments preserved in laminated biomicrite to massive micrite have mean Δ47 temperatures of 50ºC and 37°C, respectively. Elevated temperatures and δ13C, δ18Ocarb, and δ18Owater values more similar to values from NCF secondary spar veins indicate that the biomicrite sub-facies underwent diagenetic alteration. We will discuss the implications of these results for the NCF and the Cretaceous western USA paleoclimate record, as well as general lessons learned for interpreting mixed terrestrial carbonate facies records.

The astrogeodetic or Helmert deflection of the vertical (DoV) data, as opposed to data obtained through other geodetic instruments (e.g., GNSS (geodetic coordinates), levelling (normal or orthometric heights) and gravimeters (gravity data)), cannot be readily obtained by astrogeodetic instruments. In order to obtain these data, geodetic and astronomical latitude and longitude information is required. Currently, geodetic latitude and longitude (φ, λ) are measured with GNSS receivers, while astronomical latitude and longitude (Φ, Λ) are observed with Digital Zenith Camera Systems (DZCSs) or the QDaedalus system. The result of these observations are the astrogeodetic North-South (ξ=Φ-φ) and East-West (η=(Λ-λ)cosφ) DoV components. This study investigates the precision and accuracy of the newly installed tachymeter-based (multi station (MS) 60) QDaedalus astrogeodetic measurement system’s DoV data with the aid of promising DoV data from the Compact Digital Astronomical Camera (CODIAC) DZCS. For this study, we used the CODIAC (accuracy of ∼0.05″) and QDaedalus (accuracy of ~0.20″) systems to conduct parallel measurements over 2 nights (measurement duration of more than 20 hours) at the Zimmerwald Observatory in Switzerland. Both the CODIAC and QDaedalus systems were developed at ETH Zurich. CODIAC has the standard DZCS components seen in other DZCSs in Germany, Latvia, Turkey and China: telescope, charge-coupled device (CCD) camera, tiltmeters, focuser, single frequency GNSS receiver and antenna, laptop, and substructure. While each DZCS has a unique design, CODIAC has upgraded hardware components (such as the use of four tiltmeters-two Wyler and two Lipmann High-Resolution Tiltmeters) as well as advanced software and processing technology. The key components of the QDaedalus which differ from the DZCS are tachymeter, interface box, and mountable meniscus lens. Also, the measurement principle and data evaluation processes of these two systems differ; therefore, we also describe the data evaluation methods for both the CODIAC and QDaedalus systems. Finally, we discuss the results of the parallel measurements and their implications for further astrogeodetic work.

The flow and deformation of glacier ice in response to stress is often described using Glen’s Flow Law, a power-law relation that compactly represents ice rheology with a prefactor, A, and stress exponent, n. For natural ice, these parameters (and the parameters subsumed within them) come with large uncertainties that have not been robustly quantified with observations. Modern remote sensing technologies that collect data with finer resolutions and broader coverage provide us with an opportunity to robustly calibrate these rheological parameters for certain environments. Here, we utilize publicly available observations of ice sheet surface velocity and elevation acquired with remote sensing platforms to calibrate the flow law parameters over select Antarctic ice shelves. We build upon recent work that used remote sensing observations to quantify the relationship between ice stress and strain rate in extensional flow to infer an exponent of n = 4.1 +/- 0.4 for Antarctica. Here, we model two-dimensional flow and perform parameter calibration by constructing and training physics-informed neural networks (PINNs) to learn spatially-varying A and uniform n for each ice shelf. We cast the parameter estimation problem as a neural network optimization problem through minimization of a cost function that includes both data reconstruction errors and momentum balance residuals derived from the 2D shallow-shelf approximation. Additionally, we formulate the networks to predict spatially-varying uncertainties for A by using variational inference techniques, which approximate Bayesian inference (traditionally a computationally-intensive procedure) as an additional optimization objective. Finally, we demonstrate the use of time-dependent surface velocities, which are becoming increasingly more available over the ice sheets, to independently constrain the stress exponent n, confirming the appropriateness of n = 4 derived from previous work. Overall, calibration of these parameters with robust uncertainties are critical for placing observational constraints on prognostic ice flow model parameters and to improve our understanding of flow and fracture processes on ice shelves in Antarctica.

Nowadays, the time evolution of ITRF station positions is described by piece-wise linear models extended with exponential and logarithmic functions to account for post-seismic displacements. The ITRF2020 will also account for seasonal deformation by means of annual and semi-annual sine waves. However, part of the Earth’s surface deformation is not captured by those deterministic functions, such as inter-annual hydrological loading deformation, or high-frequency atmospheric loading deformation. To account for such aperiodic displacements, a reference frame in the form of a time series could be considered. This would require aperiodic motions of the different space geodetic stations to be tied in a common frame by means of co-motion constraints. The relevance of such constraints is however debatable. Indeed, common aperiodic movements between co-located space geodetic stations have thus far not been evidenced. This presentation describes the comparison of station position time series from the different space geodetic techniques in order to highlight whether or not common aperiodic movements can be detected at co-location sites. Those time series are extracted from the solutions provided by the techniques international services for the ITRF2014. They are first carefully aligned to a common reference frame in order to minimize differential network effect. Then, they are cleaned from linear, post-seismic and periodic signals (including seasonal deformation and technique systematic errors). Residual time series from co-located stations are finally confronted with each other.

To stabilize global warming within the 1.5-2.0°C Paris Agreement goal, greenhouse gas (GHG) emissions need to reach net-zero. Offsetting is required for net-zero emissions (emissions minus offsets), as achieving zero emissions is unrealistic. Offset schemes differ widely in their capacity to mitigate anthropogenic global warming (AGW). Rayer et al. (2021) provide offsetting guidelines to strengthen their long-term climate benefit, this chapter further develops this topic. We propose a framework for rating different offset types based on their climate risk, moving beyond the usual criteria of verification, audit, and additionality. We apply our offset climate ratings to some offsetting types and case studies including the sorts of schemes proposed by major oil companies, and the PAS 2060 carbon-neutrality standard. Some offsets provide little more than economic nudges towards emissions reduction. Climate offsetting requirements are more exacting. The proposed framework grades offsets from most to least benefit. Grades help classify offsets’ climate risks based on: helping terminate it, slowing warming, or only offering economic incentives with little climate benefit. Ultimately, to stabilize global warming, it will be necessary for policy to encourage the highest rated offsets under the proposed framework. Reference Rayer, Q. G., Jenkins, S., & Walton, P. (2021). Defining net-zero and climate recommendations for carbon offsetting. In Walker, T., Wendt, S., Goubran, S., & Schwartz, T. (Eds.), Beyond the 2ºC: Business and Policy Trajectories to Climate Change Adaptation (chapter 2). Palgrave Macmillan.

A new soil moisture index for monitoring drought occurrence and intensity is presented. The index is based on the integration of different remote sensing products and in situ observations. Due to a shortage of precipitation, droughts reduce vegetation productivity, and thus, aggravate the impact of moisture stress on pastureland. The spatial distribution of soil moisture index with high-resolution images in Mongolia is still being one of the essential goals in the remote sensing and rangeland community. Specifically, we examined a new composite Gobi soil moisture index (GI) based on the combination of Ocean Salinity (SMOS) Soil Moisture, several products from the MODIS satellite, and in situ Soil Moisture (SM) observations. A multiple linear regression method was used for the estimation of GI soil moisture index. The former includes the surface soil moisture from the Soil Moisture and Ocean Salinity (SMOS) mission, the Moderate Resolution Imaging Spectroradiometer (MODIS) derived land surface temperature (LST), normalized difference vegetation index (NDVI), potential evapotranspiration (PET). The latter includes a standardized precipitation index (SPI) from in-situ data. The validation of the approach is based on the relationship between SPI and in-situ soil moisture (SM) observations, and their comparison to remote sensing (RS) – derived indices. The results show that the correlation was statistically significant between GI and in-situ SM observations from the meteorological stations at 10 – 15 cm depths (p < 0.0001). The correlation between GI and SPI, as represented by the correlation coefficient (r) was 0.64. The GI empirical equations that utilize at least three key atmospheric variables are (a) NDVI, (b) land surface temperature, and (c) potential evapotranspiration. The established new GI soil moisture index was retrieved at the 1 km spatial resolution for Southwest Mongolia from 2000 to 2018, and their two summer months (July, August) were used for monitoring drought and vegetation response to the varying soil/climatic conditions. Now, based on the assessment of drought severity, the new soil moisture index allowed us to assess a large-scale spatial coherence of droughts across the Southwestern part of Mongolia.

One of the most worrisome aspects of anthropogenic climate change is its potential to enhance the frequency and severity of extreme weather events and seasonality (van der Wiel et al., 2021). More accurate reconstructions of short-term climate variability in past warm climates help improve our projections of this type of variability in future climate (IPCC, 2013). Here, we apply our recently developed clumped isotope methodology for absolute seasonal sea surface temperature and salinity reconstructions (de Winter et al., 2021a; b) on fossil mollusk shells from the Pliocene Warm Period (3.0 – 3.3 Ma) of northwestern Europe, an important analogue for equilibrium climate under present-day radiative forcing (pCO2 ≈ 400 ppmV; Haywood et al., 2016). Isotope records from well-preserved shells of four different bivalve species (Arctica islandica, Glycymeris radiolyrata, Angulus benedeni and Ostrea edulis) reveal warm sea surface temperatures and high seasonal variability during the key mid-Pliocene PRISM interval, allowing detailed comparison with long-term geological climate reconstructions and an ensemble of model simulations (Haywood et al., 2016). Moreover, our results shed light on sub-annual variability in water chemistry in the shallow European epicontinental seas during this crucial period. These new findings highlight the effect of a warming climate on shallow marine ecosystems and shed light on the seasonal response to global warming. Haywood, A. M. et al. Integrating geological archives and climate models for the mid-Pliocene warm period. Nat Commun 7, 10646 (2016). IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, 1535 pp. (Cambridge Univ. Press, Cambridge, UK, and New York, 2013). van der Wiel, K. & Bintanja, R. Contribution of climatic changes in mean and variability to monthly temperature and precipitation extremes. Commun Earth Environ 2, 1–11 (2021). de Winter, N. J. et al. Optimizing sampling strategies in high-resolution paleoclimate records. Climate of the Past 17, 1315–1340 (2021a). de Winter, N. J. et al. Absolute seasonal temperature estimates from clumped isotopes in bivalve shells suggest warm and variable greenhouse climate. Commun Earth Environ 2, 1–8 (2021b).

Arctic sea ice has substantially changed over the past four decades, with a large decrease in sea-ice area and volume. The exact causes of these changes are not entirely known. In our study, we make use of the Swedish Meteorological and Hydrological Institute Large Ensemble (SMHI-LENS). This ensemble consists of 50 members realized with the EC-Earth3 global climate model and covers the period 1970-2100. We apply the Liang-Kleeman information flow method to analyze the cause-effect relationships between Arctic sea ice and its potential drivers. We show that recent and future changes in Arctic sea ice are mainly driven by air and sea-surface temperatures and ocean heat transport. Conversely, changes in Arctic sea ice also considerably impact temperature and ocean heat transport. Finally, we find a progressive decrease in the influence of sea-ice area and volume on air temperature and ocean heat transport through the twenty-first century.

Thunderstorms are very violent and short-lived weather phenomena associated with thunder, rain, heavy wind, lightning and dense clouds. These storms are persistent and intense during the pre-monsoon (March-May) season over Eastern and North-eastern India, leading to catastrophic destruction over the regions. These thunderstorms are locally known as Kal-Baishakhi, Bordoichila or Nor’westers, which are short-lived events able to make changes in the thermodynamic properties of the environment. In this work, thermodynamic indices were calculated and analysed to evaluate the spatial and temporal variations of thunderstorms over Eastern India (Odisha, Jharkhand and West Bengal). The present study also investigated the influence of climate change on thermodynamic indices thresholds over Eastern India by using radiosonde data and ERA-5. The thermodynamic indices considered in the study are Boyden index, bulk Richardson’s number, convective available potential energy, convective inhibition, cross totals index, dew point temperature at 850hPa, humidity Index, K index, lifted index, relative humidity at 700hPa, Showalter index, severe weather threat index, total totals index, vertical totals index. After calculating these indices, with the information of thunderstorm occurrence over the region, skill score analysis has been accomplished based on the contingency table. The work discussed the change in the thermodynamic indices pattern with every 5-year interval time for temporal variations and the climatological variation of thermodynamic indices by using spatial plots to differentiate the thunderstorm and non-thunderstorm days for spatial variations. In the temporal variation, some thermodynamic indices show a noticeable shift of threshold values over time, while some indices do not exhibit any apparent change in the pattern. The trend analysis of these thermodynamic indices shows evident changes in trends over the different regions of Eastern India for thunderstorm and non-thunderstorm days. Keywords: Thunderstorm, Climate Change, Thermodynamic indices, Radiosonde data, Skill score

Banded Iron Formations (BIFs) are archives of Precambrian seawater composition. Presence or absence of negative Ce anomaly (Ce/Ce*) in BIFs has been widely used to understand paleo-redox conditions on the Earth’s surface in the Precambrian. However, whether the extremely negative Ce anomaly associated with the BIFs reflects a primarily depositional signature or not has been questioned and it has been suggested that such signatures could also arise from secondary alterations.1 We report elemental and Nd isotopic data for BIFs and associated clastic rocks from the Sirsi region in southern India. Major and trace element compositions of these BIFs were measured using an Inductively Coupled Plasma Mass Spectrometer (ICP-MS, X series II) while Nd isotope ratio (143Nd/144Nd) measurements were performed using a Thermal Ionization Mass Spectrometer (TIMS, Triton Plus), both at the Centre for Earth Sciences (CEaS), Indian Institute of Science Bangalore, India. The BIF samples are sub-divided into two groups based on their REE+Y (REY) compositions. The group-1 BIFs show seawater-like REY pattern with HREE enrichment over LREEs and super-chondritic Y/Ho (41-52). These BIF samples also lack significant negative Ce anomalies. In contrast, group-2 BIFs show high LREE/HREE enrichment, negative Ce anomaly, and sub-chondritic Y/Ho. Very high values of La/Yb in the group-2 BIFs cannot be explained by simple two-component mixing of basement rock (Dharwar TTG) and pristine Sirsi BIFs. Instead, fluid-rock alteration by LREE enriched, and Ce depleted fluid could explain the observed REY variations. We further utilized Sm-Nd isotope systematics to calculate the timing of this alteration event. These BIFs show lowest RSD (%) in their initial 143Nd/144Nd composition around 0.6 Ga, which we consider as the time of alteration event which affected the Sm/Nd of these rocks. The timing of alteration event coincides with the Pan-African orogeny which had regionally affected the Greater Dharwar Craton. The associated red shales are also characterized by high LREE/HREE ratios and negative Ce anomalies. These shales also show very high Chemical Index of Alteration (CIA) values (83-99) suggesting high degree of chemical weathering. [1] Bonnand et al, (2020) Earth and Planetary Science Letters

With shore-fast sea ice disappearing along the coast of the Chukchi Sea causing winds with deep snow drifts, variable snowpack in Bristol Bay in Alaska, and winters without snow in West Central Montana, youth from these areas have personal stories of environmental changes witnessed firsthand. In a virtual “Dirty Snow” citizen science STEM engagement program that met weekly for 5-weeks, middle and high school youth across different time zones and cultures shared such snow stories, implemented a protocol to measure light absorbing particles (LAPs) in snow, and conducted their own Global Learning and Observations to Benefit the Environment (GLOBE) snowpack and pH investigations. Teachers, parents and researchers teamed up to support students as they asked their own questions about how LAPs affect their local communities and measured, collected, filtered, and analyzed snow samples. Students learned that LAPs in snow affect the Earth’s climate system by reducing snow reflectivity, affecting albedo. On a local scale, LAPs capture heat energy leading to snow loss. Students wondered if LAPs also affect water quality. Middle school students from Shishmaref, Alaska (located on an island in the Chukchi Sea) selected snow sampling locations in areas important to their community’s resilience to climate change, such as the sole water supply lagoon. The Shishmaref students shared their results with their community, showcased their project in both the GLOBE International Virtual Science Symposium and a tribal climate resilience webinar, and have been featured in the July 2021 Association of Women in Science Magazine issue on sustainability and innovation. In this session, we will share the lessons learned from multiple perspectives - including surveyed youth participants - on conducting a remote synchronous and asynchronous STEM and climate resilience engagement on a short timescale.

The stated mission of the International Arctic Research Center (IARC) at the University of Alaska Fairbanks (UAF) is ”to foster Arctic research to help the nation and the world understand, prepare for, and adapt to the pan-Arctic impacts of climate change.” IARC’s work and collaborations are everywhere in the Arctic and beyond. One of IARC’s core values is actively cultivating an environment of diversity and inclusion where all individuals and groups feel welcomed and are heard. Through the work of the IARC Diversity and Inclusion Working Group, we affirm that our different experiences, expertise, and ways of knowing are our strength, fostering diverse thoughts and ideas. Collaborative science and administrative support by people from diverse backgrounds and knowledge systems helps IARC build a professional culture of inclusion, listening, caring and respect. We face challenges in DEI work and are actively addressing them. For example, in addressing the challenge of time constraints by the all-volunteer membership, a DEI coordinator position to spearhead our efforts is being created and funding sought. We highlight efforts from the IARC Diversity and Inclusivity Working Group to cultivate a culture of inclusion, equity and access: 1) collaboratively developing an institutional diversity and inclusivity statement and land acknowledgement statement, 2) creating safe spaces for conversation and action through open biweekly working group meetings and discussions, 3) elevating awareness through relevant workshops, trainings and discussions, 4) collectively incorporating diversity and inclusion values into the IARC strategic plan, 5) making presentations and documents accessible, and 6) actively collaborating on inclusion efforts within UAF, Alaska and beyond. We welcome new members with their ideas and perspectives to the working group. At IARC, we recognize that inclusion is an ongoing process that has to be woven into all that we do in research, education and outreach.

Meteorology is a major driving force to poor urban air quality. This is due to its ability to influence the emissions, transport, formation, and deposition of air pollutants. In this study, the relationship between meteorological parameters including temperature, relative humidity, wind speed and direction and ambient air pollutants concentrations such as PM2.5 in the capital city of Ghana was carried out for a continuous period of 12 months from March 2020 to February 2021. Clear seasonality was observed for PM2.5, meteorological parameters and the air quality index. Maximum concentrations of PM2.5 were recorded in winter leading to poor air quality. Wind speed and relative humidity reversely correlated with the air pollutant while temperature showed a positive correlation with PM2.5. north-easterly winds led to highest concentrations during the winter season while south-westerly winds prevail over Accra in summer. The results from air quality index (AQI) indicated that severely poor air prevails during the winter period. These results justify the crucial role of meteorological parameters in air pollution formation with large variations in different seasons. These findings can be employed to enhance the understanding of processes that lead to air pollution and improve the accuracy of air quality forecast under different meteorological conditions.

The conduct of reproducible science improves when computations are portable and verifiable. A container provides an isolated environment for running computations and thus is useful for porting applications on new machines. Current container engines, such as Linux Containers (LXC) and Docker, however, have a high learning curve, are resource-intensive, and do not address the entire reproducibility spectrum consisting of portability, repeatability, and replicability. As part of EarthCube, we have developed Sciunit (https://sciunit.run) which encapsulates application dependencies i.e, system binaries, code, data, environment, along with application provenance. The resulting research object can be easily shared and reused amongst collaborators. Sciunit can be used with HydroShare’s JupyterHub CUAHSI notebook environment, and available to the entire community for use. In this poster, we will present three new features in Sciunit which have emerged based on community-provided use cases and discussion. Sciunit is available as a command-line utility. We will: (1) showcase the new Sciunit API. This will allow data facilities to integrate Sciunit as a reproducible environment on portals, (2) show how a Sciunit container can transition to a Docker container and vice versa, and finally, (3) demonstrate the ability to contrast two containers in terms of content and metadata. We will show these capabilities with the Hydrology use case of pySUMMA, a Python API for the Structure for Unifying Multiple Modeling Alternative (SUMMA) hydrologic model.

Land evapotranspiration (ET) and lake evaporation are important water budget components, representing the main processes of energy and water exchange between the earth and the atmosphere, and thus can influence the regional-scale hydrological cycles. Based on several long-term and comprehensive land-atmosphere interaction measurements over the Tibetan Plateau, the total amounts of land ET and lake evaporation are estimated by a combination of satellite products and meteorological data, the results show that: (1) the total ET amount has an average annual value of 1.238±0.058×103 km3. The trends of annual ET amount show high variable in spatial distributions, with an increasing trend in the east plateau and a decreasing trend in the west plateau. (2) As for the lake surface, lake ice phenology are clearly presented by MODIS 8-day snow cover products, and they show large spatial variability in the duration of ice-free season. The estimated Bowen ratio and evaporation amounts show acceptable accuracies, and display opposite spatial distributions, with the latter being higher in the southern part than in the northern part. On the TP, a lake with a higher elevation, a smaller area and a larger latitude mostly corresponds to a shorter ice-free season (a lower total net radiation), a larger Bowen ratio and finally a lower evaporation amount. The multi-year average evaporation amounts are listed, with the total water evaporated from lake surface being approximately 29.4±1.2 km3 year-1 for the studied 75 lakes and 51.7±2.1 km3 year-1 for all Plateau lakes included. (3) To further explore the land/lake-atmosphere interaction processes in detail over data-limited regions of the TP and supported by the “Third Pole Environment (TPE) program, 16 comprehensive observation and research stations have been constructed over all kinds of landscapes and in different regions of the TP in 2021. These data have provided significance for future research on plateau- and regional-scale water budget, hydrological cycle and water resources management.

Acetone is an abundant volatile organic compound with important influence on ozone and atmospheric self-cleaning processes. The budget of acetone is influenced by various sources and sinks. Direct sources include anthropogenic, terrestrial vegetation, oceanic, and biomass burning emissions, while chemistry forms acetone from other compounds. Sinks include deposition onto the land and ocean surfaces, as well as chemical loss. The GISS Earth System Model, ModelE, is capable of simulating a variety of Earth system interactions. Previously, acetone had a very simplistic representation in the ModelE chemical scheme. This study assesses a greatly improved acetone tracer scheme, in which acetone's sources, sinks and atmospheric transport are now tracked in 3 dimensions. Extensive research was conducted to assess how well past literature supported the new global acetone budget. Anthropogenic, vegetation, biomass burning, and deposition schemes fit well with previous studies. While their net fluxes were well-supported, source and sink terms for chemistry and the ocean were overestimated and underestimated, respectively. In iterations of the chemistry scheme, it was found that the production of acetone from hydrocarbon oxidation is a strong leverage to the overall chemical source. Spatial distributions reveal that ocean uptake of acetone dominates northern latitudes, while production is mainly in mid-southern latitudes. Ocean surface conditions influence ocean-acetone interactions and will be considered when modifying the ocean scheme in future work. The seasonality of acetone-related processes was also studied in conjunction with field measurements around the world. These comparisons show promising results, but have shortcomings at urban locations, since the model's resolution is too coarse to capture high-emission areas. Overall, an analysis of the acetone budget aids the development of the tracer in the GISS ModelE, a crucial step to parameterizing the role of acetone in the atmosphere.

Self-propelled motion is an agnostic biosignature that is observed widely, yet motility of microbes in their natural environments is sparsely studied. In this study we use a Digital Holographic Microscope (DHM) for in situ imaging of aquatic samples in extreme environments to investigate motility and morphology as biosignatures. Samples were collected from glaciovolcanic ice caves, glacial runoff, hot springs, and mixed glacial and hot spring samples.The transport and deposition of materials and heat from the volcanic subsurface in glaciovolcanic caves may be similar in some respects to the eruption processes of the plumes of Enceladus. Through different tracking methods, we identified concentrations of organisms, morphologies, swimming patterns, speeds, and turn angles. In every type of sample we looked we were able to identify motile organisms. Methods for distinguishing active swimming from Browian motion and drift are considered. Field work was done over two deployments in collaboration with the Thermal High-voltage Ocean-penetrating Research platform (THOR) science team and EELS robotics team. This work and these collaborations intend to inform future off-world extant life detection missions of the utility of DHM and motility as an investigation tool and biosignature, respectively.

Because climate change is both a physical and social phenomenon, personal experience has been considered the first step to entail how individuals perceive climate change risk and which actions can be promoted to reduce their vulnerability. Considering that agriculture is affected by climate change in several ways, farmers can provide first-hand observations of climate change impacts and suggest better adaptation options. However, modeling farmers’ behavior is a non-trivial task: personal experience is well recognized as a complex non-linear, multi-variate process due to the high heterogeneity and uncertainties in human cognition and decision-making processes. Furthermore, individual understandings of climate change are always contextualized within broader considerations, meaning that farmers are not ‘blank slates’ receiving information about climate change, but that information is always and inevitably filtered through values and worldviews. Despite the burgeoning of research on climate change, information about farmers’ awareness and risk perception is not geographically homogenized and varies substantially among countries and regions. For example, studies from Global North regions are scarce and emphasize how farmers characterize themselves rather than how they perceive and react to climate change. Drawing on farmers’ surveys in the Lombardy region (Italy), we provide an empirical study to pre-test the triple-loop analysis of farmers’ behavior regarding climate change: awareness, perceived impacts, and adaptation measures and barriers. Applying descriptive statistics and considering socio-economic data and farm characteristics, we address two main research questions: 1) What are farmers’ perceptions of climatic impacts and which responses do they promote? 2) How do personal experience and attitude change is conditioning farmers’ adaptation capacity? Obtained results from accurate bottom-up knowledge on farmers’ behavior may increase policy-makers’ and managers’ understanding of climate change and re-think local policies, which is essential to address agricultural risks in climate change hotspots.