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At least 19 records

Going to Extremes: Architecting Holographic Microscopes for Extreme Environments

Bacterial life exists on earth in extreme environments. These are environments described by large temperature excur- sions, large pressure excursions, and large radiation excursions from the nominal conditions near sea level which are largely populated by humans. These extreme locales represent such places as the ocean ice, the briny pools of Death Valley and deep mines, the acidic hot springs of the High Sierra or Yellowstone, or even the clouds of our upper atmosphere. The preponderance of bacterial life in these extreme environments here on earth suggests that bacterial life might likely exist in the extreme environments of our own solar system, such as the icy moons of Europa or Enceladus. Thus, architecting instruments for detect- ing life in these extreme environments on earth builds confidence that we can architect such instruments for flight missions. In this paper, we discuss our experience with designing digital holo- graphic microscope instruments to enable detection of bacteria in several extreme environments. In particular we discuss three different instruments. The first is our field instrument which is a small, portable instrument for examination of remote sites. The second is submersible instrument which enables exploration of deep aquatic environments and is deployed on a ocean-going drone. The third is a balloon-borne instrument to examine the bacterial content of the upper atmosphere. We will provide a review of each instrument and discuss aspects of instrument engineering for each particular application.

Ramirez, Alex

NPCC4: Tail Risk, Climate Drivers of Extreme Heat, and New Methods for Extreme Event Projections

We summarize historic New York City (NYC) climate change trends and provide the latest scientific analyses on projected future changes based on a range of global greenhouse gas emissions scenarios. Building on previous NPCC assessment reports, we describe new methods used to develop the projections of record for sea level rise, temperature, and precipitation for NYC, across multiple emissions pathways and analyze the issue of the “hot models” associated with the 6th phase of the Coupled Model Intercomparison Project (CMIP6) and their potential impact on NYC's climate projections. We describe the state of the science on temperature variability within NYC and explain both the large-scale and regional dynamics that lead to extreme heat events, as well as the local physical drivers that lead to inequitable distributions of exposure to extreme heat. We identify three areas of tail risk and potential for its mischaracterization, including the physical processes of extreme events and the effects of a changing climate. Finally, we review opportunities for future research, with a focus on the hot model problem and the intersection of spatial resolution of projections with gaps in knowledge in the impacts of the climate signal on intraurban heat and heat exposure.

NPCC4

MSD CoP Webinar: AI and Extreme Events - Overcoming Data Challenges for Improved Characterization of Climate Extremes

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Artificial Intelligence (AI) models require large volumes of data for training and testing. Data requirements present challenges for using AI to explore extreme events with limited observational data. This webinar will showcase two innovative methods developed by part of the European Climate Intelligence (CLINT) project to overcome data challenges and harness AI to improve our understanding of climate extremes. Dr. Ascenso will present his research on data augmentation methods to improve estimates of tropical cyclones using satellite data. His presentation will review established methods for data augmentation and explore opportunities and challenges for using generative AI to generate images of extreme, life-threatening tropical cyclones. Next, Dr. Plesiat will present his research on deep learning techniques to overcome limited observational data sets. His presentation will illustrate deep learning methods to develop AI reconstructions of four climate indices across Europe. Presenters : Dr. Guido Ascenso (post-doctoral researcher, Politecnico di Milano); Dr. Étienne Plésiat (German Climate Computing Centre - DKRZ) Moderator(s): Stefano Galelli (MSD CoP WG Co-Lead), David Gold (MSD CoP WG Co-Lead), Jillian Sturtevant (MSD CoP WG Communications Officer), Matteo Giuliani (Politecnico di Milano, MSD CoP WG Member, Moderator and Organizer) This webinar was held on: October 11, 2024 from 11AM - 1PM ET

AI

Detecting Climate Signals in Precipitation Extremes from TRMM (1998-2013) - Increasing Contrast Between Wet and Dry Extremes During the "Global Warming Hiatus"

We investigate changes in daily precipitation extremes using Tropical Rainfall Measuring Mission (TRMM) data (1998-2013), which coincides with the "global warming hiatus." Results show a change in probability distribution functions of local precipitation events (LPEs) during this period consistent with previous global warming studies, indicating increasing contrast between wet and dry extremes, with more intense LPE, less moderate LPE, and more dry (no rain) days globally. Analyses for land and ocean separately reveal more complex and nuanced changes over land, characterized by a strong positive trend (+12.0% per decade, 99% confidence level (c.l.)) in frequency of extreme LPEs over the Northern Hemisphere extratropics during the wet season but a negative global trend (−6.6% per decade, 95% c.l.) during the dry season. A significant global drying trend (3.2% per decade, 99% c.l.) over land is also found during the dry season. Regions of pronounced increased dry events include western and central U.S., northeastern Asia, and Southern Europe/Mediterranean.

Precipitation

Anthropogenic extremely low volatility organics (ELVOCs) Govern the Growth of Molecular Clusters over the Southern Great Plains during the Springtime

New particle formation (NPF) and growth govern cloud condensation nuclei (CCN) concentrations in many regions. The mechanisms governing the nucleation of molecular clusters vary substantially in different regions of the atmosphere. Additionally, the growth of these clusters from ~2 to 20 nm sizes is often governed by the availability of extremely low volatility organic vapours (ELVOCs). While the pathways to ELVOC formation from the oxidation of biogenic monoterpenes with ozone is better understood, the chemical and mechanistic pathways for ELVOC formation from oxidation of anthropogenic organics are not well understood. We integrate measurements and three-dimensional regional model simulations with the Weather Research and Forecasting Model coupled to chemistry (WRF-Chem) to understand the processes governing new particle formation and growth and secondary organic aerosol (SOA) formation during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign at the Southern Great Plains (SGP) observatory in Oklahoma, and contrast it with a site within the Bankhead National Forest (BNF), Alabama in Southeast USA, where 5-year long measurements will begin in 2024. Simulations show that nucleation rates are at least an order of magnitude higher at SGP compared to BNF during the springtime days (April 28 and May 14, 2016), largely due to lower H2SO4 concentrations at BNF, which are needed for nucleation. In addition, the larger CS at BNF (compared to SGP) increase the loss of molecular clusters by coagulation to pre-existing particles. Among the 8 different nucleation mechanisms in WRF-Chem, we find that the amine+H2SO4 nucleation mechanism dominates at the SGP site, while the pure organic ion induced nucleation mechanism dominates over BNF. Through various WRF-Chem sensitivity simulations, we find that anthropogenic ELVOCs are critical for explaining the growth of newly formed particles and the resulting number size distribution observed near the surface at the SGP site during the daytime. In addition, we show that treating organic particles as semisolid, with strong diffusion-limited uptake of organic vapours, brings model predictions into closer agreement with the observed evolution of particle size distribution. Simulations also predict that anthropogenic SOA, formed by the oxidation of aromatic volatile organic compounds (VOCs), is the dominant organic aerosol component at SGP, while biogenic SOA dominates particle composition at the BNF site in Southeast USA on these days.

Shrivastava, ManishKumar B.

Simulation of the 23 July 2012 Extreme Space Weather Event: What if This Extremely Rare CME Was Earth Directed?

Extreme space weather events are known to cause adverse impacts on critical modern day technological infrastructure such as high-voltage electric power transmission grids. On 23 July 2012, NASA's Solar Terrestrial Relations Observatory-Ahead (STEREO-A) spacecraft observed in situ an extremely fast coronal mass ejection (CME) that traveled 0.96 astronomical units (approx. 1 AU) in about 19 h. Here we use the SpaceWeather Modeling Framework (SWMF) to perform a simulation of this rare CME.We consider STEREO-A in situ observations to represent the upstream L1 solar wind boundary conditions. The goal of this study is to examine what would have happened if this Rare-type CME was Earth-bound. Global SWMF-generated ground geomagnetic field perturbations are used to compute the simulated induced geoelectric field at specific ground-based active INTERMAGNET magnetometer sites. Simulation results show that while modeled global SYM-H index, a high-resolution equivalent of the Dst index, was comparable to previously observed severe geomagnetic storms such as the Halloween 2003 storm, the 23 July CME would have produced some of the largest geomagnetically induced electric fields, making it very geoeffective. These results have important practical applications for risk management of electrical power grids.

SPACE WEATHER

Extreme Ultraviolet and Beyond Extreme Ultraviolet Lithography Using Amorphous Zeolitic Imidazolate Resists Deposited by Atomic/Molecular Layer Deposition

Amorphous zinc-imidazolate (aZnMIm) resists show potential to meet the demands for next-generation high-numerical aperture (high-NA) metal-containing extreme ultraviolet (EUV) resist materials, given their ease of deposition by atomic/molecular layer deposition (ALD/MLD) at thicknesses of 20 nm and below. Here, this study demonstrates that aZnMIm thin films, previously identified as high-resolution electron beam resists, can also function as negative-tone EUV photoresists. Water development achieves high sensitivity (5 mJ/cm 2 ) but leaves significant residue, while acetic acid development results in poor contrast. A hybrid approach─water followed by acetic acid─enables residue-free development with a sensitivity of 181 mJ/cm 2 . Dry development using 1,1,1,5,5,5-hexafluoroacetylacetone (hfacH) is also possible but shows lower sensitivity (375 mJ/cm 2 ) compared to wet development methods. EUV photoelectron spectroscopy (PES), reflectometry/EUV absorption, total electron yield (TEY), residual gas analysis (RGA), and time-of-flight secondary ion mass spectrometry (TOF-SIMS) were used to investigate the effects of EUV irradiation on aZnMIm resists. Reflectometry experiments reveal an aZnMIm EUV absorption coefficient of 6.2 μm –1 , while PES and TEY analyses show that, compared to poly(4-hydroxystyrene) (PHS), a polymer-based reference resist, aZnMIm emits more primary and secondary electrons but generates fewer slow electrons relative to its primary electron emission; its total electron yield is similar to that of poly(methyl methacrylate) (PMMA) resists. When exposed to EUV, aZnMIm predominantly outgasses H 2 , as determined by RGA. TOF-SIMS measurements demonstrate that high-dose EUV exposure only partially fragments the 2-methylimidazole (2MIm) organic linkers, unlike high-dose electron beam exposure, which is known to completely degrade them. Additionally, aZnMIm resists show promise for potential beyond EUV lithography (BEUVL) due to the presence of Zn, which provides higher sensitivity at a wavelength of 6.7 nm compared to other metal ions, such as Sn, that are currently used in the best-performing EUV metal–organic resists. TEY measurements demonstrate that aZnMIm emits nearly twice as many electrons as PHS at 6.7 nm. The BEUV TEY of aZnMIm also surpasses that of PMMA, poly(pentafluorostyrene), and poly(4-iodostyrene), with the latter two being known for their high EUV TEYs. This work provides insight into zeolitic imidazolate framework (ZIF)-based EUV and BEUV resists and highlights their potential for both wet and dry development.

lithography

Negative extreme events in gross primary productivity and their drivers in China during the past three decades

Climate extremes have remarkable impacts on ecosystems and are expected to increase with future global warming. However, only few studies have focused on the ecological extreme events and their drivers in China. In this study, we carried out an analysis of negative extreme events in gross primary productivity (GPP) in China and the sub-regions during 1982–2015, using monthly GPP simulated by 12 process-based models (TRENDYv6) and an observation-based model (Yao-GPP). Extremes were defined as the negative 5th percentile of GPP anomalies, which were further merged into individual extreme events using a three-dimensional contiguous algorithm. Spatio-temporal patterns of negative GPP anomalies were analyzed by taking the 1000 largest extreme events into consideration. Results showed that the effects of extreme events decreased annual GPP by 2.8% (i.e. 208 TgC/year) in TRENDY models and 2.3% (i.e. 151 TgC/year) in Yao-GPP. Hotspots of extreme GPP deficits were mainly observed in North China (−53 gC/sq.m year) in TRENDY models and Northeast China (−42 gC/sq.m year) in Yao-GPP. For China as a whole, attribution analyses suggested that extreme low precipitation was associated with 40%–50% of extreme negative GPP events. Most events in northern and western China could be explained by meteorological droughts (i.e. low precipitation) while GPP extreme events in southern China were more associated with temperature extremes, in particular with cold spells. GPP was revealed to be much more sensitive to heat/drought than to cold/wet extreme events. Combined with projected changes in climate extremes in China, GPP negative anomalies caused by drought events in northern China and by temperature extremes in southern China might be more prominent in the future.

Climate change

Statistic analysis of annual total ozone extremes for the period 1964-1988

Annual extremes of total column amount of ozone (in the period 1964-1988) from a network of 29 Dobson stations have been examined using the extreme value analysis. The extremes have been calculated as the highest deviation of daily mean total ozone from its long-term monthly mean, normalized by the monthly standard deviations. The extremes have been selected from the direct-Sun total ozone observations only. The extremes resulting from abrupt changes in ozone (day to day changes greater than 20 percent) have not been considered. The ordered extremes (maxima in ascending way, minima in descending way) have been fitted to one of three forms of the Fisher-Tippet extreme value distribution by the nonlinear least square method (Levenberg-Marguard method). We have found that the ordered extremes from a majority of Dobson stations lie close to Fisher-Tippet type III. The extreme value analysis of the composite annual extremes (combined from averages of the annual extremes selected at individual stations) has shown that the composite maxima are fitted by the Fisher-Tippet type III and the composite minima by the Fisher-Tippet type I. The difference between the Fisher-Tippet types of the composite extremes seems to be related to the ozone downward trend. Extreme value prognoses for the period 1964-2014 (derived from the data taken at: all analyzed stations, the North American, and the European stations) have revealed that the prognostic extremes are close to the largest annual extremes in the period 1964-1988 and there are only small regional differences in the prognoses.

Krzyscin, Janusz W.

A New Metric for Indian Monsoon Rainfall Extremes

Extreme monsoon rainfall in India has disastrous consequences, including significant socio- economic impacts. However, little is known about the overall trends and climate factors associated with extreme rainfall because rainfall greatly varies across India and because few appropriate methods are available to measure extreme rainfall in the context of such heterogeneity. To provide a comprehensive assessment of extreme monsoon rainfall, we developed a metric using record rainfall data to measure the changes in the likelihood of extreme high and extreme low rainfall over time; this metric is independent of the characteristics of the underlying rainfall distributions. Hence, the metric is ideally suited to aggregate extreme rainfall information across heterogeneous regions covering India. We found that from 1930 to 2013, the likelihood of extreme high and extreme low rainfall increases 2-fold and 4-fold, respectively. These overall trend increases are driven by anomalous increases, particularly in the early 2000s; the likelihood of extreme high and extreme low rainfall increases 5-fold and 18-fold in 2005 and 2002, respectively. These findings imply a broadening of the underlying monsoon rainfall distribution over the past century. We also show that the time patterns of the likelihood of extreme rainfall in recent decades are correlated with the El Nino Southern Oscillation, Indian Ocean Dipole, and surface air temperature in the Northern Hemisphere.

Rain