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SUMMARY:Climate Physics Journal Club – Artificial Intelligence and Machine Learning seminar
DESCRIPTION:IARC’s Climate Physics Journal Club is starting a seminar series on the use of Artificial Intelligence and Machine Learning in scientific applications. Contributions are invited from all fields of science. The series will launch with climate-related applications developed by scientists from the Los Alamos National Lab.\n\nCircumpolar observations of ice wedge melting and thermokarst pool expansion\n\nPresenter: Chuck Aboldt\, Director’s Postdoc at Los Alamos National Lab\, Earth and Environmental Sciences Division\n\nAbstract: Recent permafrost thaw has progressed at rates that far exceed predictions from Earth system models (ESMs)\, which are the primary tools used to project interactions between the global carbon cycle and climate. Accurate simulations of permafrost degradation are vital to forecasting climate change\, because vast stocks of carbon may be mobilized as frozen sediments thaw. One of the key sources of error in pan-Arctic scale simulations of permafrost thaw is the absence of a fine-scale\, but ubiquitous process: the melting of ice wedges\, or meter-scale bodies of ice buried at the top of the permafrost. Ice wedge melting accelerates thaw\, because it tends to create small ponds\, or thermokarst pools\, which absorb heat more efficiently than the tundra they replace. Building this process into ESMs is challenging\, due to incomplete knowledge of the highly variable extent to which ice wedges across the Arctic have responded to climate change thus far. To address this challenge\, my research analyzes an enormous dataset of submeter-resolution satellite imagery\, available from 2008-present. My workflow\, based on a convolutional neural network\, measures the area of individual ponds and tracks their growth at twenty-five landscapes spanning the Arctic. The results reveal highly uneven decadal-scale trends\, which vary from no expansion at some sites in Siberia\, to a nearly fourfold increase in the area of thermokarst pools near Prudhoe Bay\, Alaska. These results comprise a unique and geographically extensive dataset\, which will permit parameterization and validation of the pan-Arctic simulations of ice wedge melting. The incorporation of this key process into Earth system models will improve the realism of simulated permafrost thaw\, enabling more accurate projections of changes of climate change and carbon cycling over the 21st century.\n\nBehind the curtain: the messiness of machine learning\n\nPresenter: Jon Schwenk\, Scientist at Los Alamos National Lab\, Earth and Environmental Sciences Division\n\nAbstract: While many machine learning applications produce seemingly magical results\, we often neglect the messy details of data provenance\, acquisition\, and curation that can account for more than 75% of the effort required to build a machine learned model. Large training datasets are often required to train robust models\, which can result in focusing on data quantity over quality. Satellite imagery and derived products often serve as a primary source of this data\, but can pose major technical challenges that are often overlooked. Here I will present two data-driven machine learning modeling efforts. The first is an attempt to model riverbank erosion rates globally using primarily watershed-averaged characteristics. I will show a tool we developed (RaBPro) to aid in generating spatially-relevant predictors and some preliminary modeling results. The second project aims to fuse millions of in-situ ocean observations with MODIS satellite imagery in order to create a temporally- and spatially-continuous dataset of sea surface temperatures\, salinities\, and turbidities that will aid Earth System Model development. I will highlight some of the technical challenges of both efforts as well as present (some of) our solutions to overcome them. I will close by presenting an InteRFACE-generated dataset that could serve as a collaborative machine-learning project.\n\nWatch the recording [Passcode: AJGBiM?6]\n\nAbout the Climate physics journal club: Exchanging ideas and findings in an informal atmosphere– scientific discussion welcome!
URL:https://uaf-iarc.org/event/climate-physics-journal-club-circumpolar-observations-of-ice-wedge-melting-and-thermokarst-pool-expansion/
CATEGORIES:Climate Physics Journal Club
ATTACH;FMTTYPE=image/jpeg:https://uaf-iarc.org/wp-content/uploads/2021/02/ice_wedge_polygons_north_slope_Alaska_7-23-2010_Chris_Zimmerman.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Anchorage:20191015T130000
DTEND;TZID=America/Anchorage:20191015T140000
DTSTAMP:20260515T004233
CREATED:20191010T194743Z
LAST-MODIFIED:20191010T201845Z
UID:17673-1571144400-1571148000@uaf-iarc.org
SUMMARY:Climate Physics Journal Club - Dynamical downscaling for Southeast Alaska: A look at precipitation metrics
DESCRIPTION:Presenter: Rick Lader\, Postdoctoral Fellow\, Alaska Climate Adaptation Science Center \nSoutheast Alaska has been under drought conditions for the past two years\, with precipitation deficits of greater than 100 cm in some locations. These conditions have impacted hydropower electricity generation\, fish habitat and forest health. Given the region’s extreme topographical gradients\, newly produced dynamically downscaled datasets are used to help resolve and study changes on this landscape. \nThis seminar looks at historical precipitation trends\, rain/snow partitioning and precipitation intensities from the downscaled Climate Forecast System Reanalysis (CFSR). These data are at 4-km spatial resolution across Southeast Alaska from 1981-2018. Future projections (2031-2060) of these indices are also investigated using downscaled simulations from the Geophysical Fluid Dynamics Laboratory Climate Model version 3 (GFDL-CM3). Bias correction methods for the climate model simulations are also considered.
URL:https://uaf-iarc.org/event/climate-physics-journal-club-dynamical-downscaling-for-southeast-alaska-a-look-at-precipitation-metrics/
LOCATION:Akasofu 501\, 2160 Koyukuk Dr\, Fairbanks\, AK\, 99775\, United States
CATEGORIES:Climate Physics Journal Club
ATTACH;FMTTYPE=image/jpeg:https://uaf-iarc.org/wp-content/uploads/2019/10/P6180639.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Anchorage:20190612T130000
DTEND;TZID=America/Anchorage:20190612T140000
DTSTAMP:20260515T004233
CREATED:20190521T195330Z
LAST-MODIFIED:20190523T232922Z
UID:6132-1560344400-1560348000@uaf-iarc.org
SUMMARY:Climate Physics Journal Club- Climate-scale predictability and variability of Alaska wildfire
DESCRIPTION:Alaska fires\, 1940-2015.\n\n\n\nPresenter: Peter Bieniek\, IARC Research Assistant Professor \n\n\n\nWildfire in Interior Alaska is a key natural driver of the landscape and can be a hazard at the wildland-urban interface. Years with extreme wildfire activity in Alaska have increased in frequency in recent decades and are projected to continue to increase under climate change.  \n\n\n\nFire danger estimates and lightning-ignition risk derived from existing seasonal forecast models are being assessed to see if they can effectively inform fire management decisions. Work is also underway to evaluate the current suite of fire weather indices to determine if indices used in the CONUS and the research community might be adopted in the unique Alaska landscape.  \n\n\n\nFinally\, the role of long-term climate variability and change in Alaska fire danger is being further examined. It is the goal of these projects to provide Alaska fire managers with guidance from the next season to the next 80+ years.
URL:https://uaf-iarc.org/event/climate-physics-journal-club-climate-scale-predictability-and-variability-of-alaska-wildfire/
LOCATION:Akasofu 401\, 2160 Koyukuk Dr\, Fairbanks\, AK\, 99775\, United States
CATEGORIES:Climate Physics Journal Club
ATTACH;FMTTYPE=image/jpeg:https://uaf-iarc.org/wp-content/uploads/2019/05/JR-16-5048-165.jpg
ORGANIZER;CN="Vladimir Alexeev":MAILTO:valexeev@alaska.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Anchorage:20190515T143000
DTEND;TZID=America/Anchorage:20190515T153000
DTSTAMP:20260515T004233
CREATED:20190521T224059Z
LAST-MODIFIED:20190523T183027Z
UID:6159-1557930600-1557934200@uaf-iarc.org
SUMMARY:Climate Physics Journal Club- Arctic warming amplification & arctic-lower latitude linkages
DESCRIPTION:Xiangdong Zhang\n\n\n\nPresenter: Xiangdong Zhang\,\nIARC Professor\, climate & global change \n\n\n\nSurface air temperature increase has been amplified in the Arctic. However\, the sparse observational network limits accurate estimates of Arctic warming. There is uncertainty in global warming rate\, including the period of so-called “hiatus” from 1998-2012 as indicated by the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5).  \n\n\n\nWe reconstructed a new global dataset with improved spatial\nand temporal representations of the Arctic SAT observations. The analysis\nsuggests that Arctic SAT has increased at a rate of 0.755°C/decade during\n1998-2012\, more than 6 times the global average. Rather than a hiatus\, the\namplification significantly contributed to the global warming trend.  \n\n\n\nWe also examined changes in Arctic storms and atmospheric\ncirculation and their roles in linking Arctic and lower latitudes and causing\noccurrence of extreme events. The results indicate that changes in the\nlarge-scale atmospheric circulation build up a shortcut for warm and moist air\nflowing into the Arctic and circulate the polar cold air to the lower\nlatitudes\, causing an amplified Arctic warming and midlatitude cooling.
URL:https://uaf-iarc.org/event/climate-physics-journal-club-arctic-warming-amplification-arctic-lower-latitude-linkages/
CATEGORIES:Climate Physics Journal Club
ATTACH;FMTTYPE=image/jpeg:https://uaf-iarc.org/wp-content/uploads/2019/04/zhang3.jpg
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