scholarly journals Best Practice Strategies for Process Studies Designed to Improve Climate Modeling

2020 ◽  
Vol 101 (10) ◽  
pp. E1842-E1850
Author(s):  
Janet Sprintall ◽  
Victoria J. Coles ◽  
Kevin A. Reed ◽  
Amy H. Butler ◽  
Gregory R. Foltz ◽  
...  
Keyword(s):  
Best Practice ◽  
Climate Models ◽  
Climate Modeling ◽  
Scientific Data ◽  
Career Stage ◽  
Scientific Data Management ◽  
Process Study ◽  
Quantitative Understanding ◽  
Process Studies

AbstractProcess studies are designed to improve our understanding of poorly described physical processes that are central to the behavior of the climate system. They typically include coordinated efforts of intensive field campaigns in the atmosphere and/or ocean to collect a carefully planned set of in situ observations. Ideally the observational portion of a process study is paired with numerical modeling efforts that lead to better representation of a poorly simulated or previously neglected physical process in operational and research models. This article provides a framework of best practices to help guide scientists in carrying out more productive, collaborative, and successful process studies. Topics include the planning and implementation of a process study and the associated web of logistical challenges; the development of focused science goals and testable hypotheses; and the importance of assembling an integrated and compatible team with a diversity of social identity, gender, career stage, and scientific background. Guidelines are also provided for scientific data management, dissemination, and stewardship. Above all, developing trust and continual communication within the science team during the field campaign and analysis phase are key for process studies. We consider a successful process study as one that ultimately will improve our quantitative understanding of the mechanisms responsible for climate variability and enhance our ability to represent them in climate models.

scholarly journals SAM-CAAM: A Concept for Acquiring Systematic Aircraft Measurements to Characterize Aerosol Air Masses

2017 ◽  
Vol 98 (10) ◽  
pp. 2215-2228 ◽  
Author(s):  
Ralph A. Kahn ◽  
Tim A. Berkoff ◽  
Charles Brock ◽  
Gao Chen ◽  
Richard A. Ferrare ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Modeling ◽  
Chemical Properties ◽  
Aircraft Measurements ◽  
Air Masses ◽  
Aerosol Forcing ◽  
Aerosol Mass ◽  
Aerosol Property ◽  
Species Specific

Abstract A modest operational program of systematic aircraft measurements can resolve key satellite aerosol data record limitations. Satellite observations provide frequent global aerosol amount maps but offer only loose aerosol property constraints needed for climate and air quality applications. We define and illustrate the feasibility of flying an aircraft payload to measure key aerosol optical, microphysical, and chemical properties in situ. The flight program could characterize major aerosol airmass types statistically, at a level of detail unobtainable from space. It would 1) enhance satellite aerosol retrieval products with better climatology assumptions and 2) improve translation between satellite-retrieved optical properties and species-specific aerosol mass and size simulated in climate models to assess aerosol forcing, its anthropogenic components, and other environmental impacts. As such, Systematic Aircraft Measurements to Characterize Aerosol Air Masses (SAM-CAAM) could add value to data records representing several decades of aerosol observations from space; improve aerosol constraints on climate modeling; help interrelate remote sensing, in situ, and modeling aerosol-type definitions; and contribute to future satellite aerosol missions. Fifteen required variables are identified and four payload options of increasing ambition are defined to constrain these quantities. “Option C” could meet all the SAM-CAAM objectives with about 20 instruments, most of which have flown before, but never routinely several times per week, and never as a group. Aircraft integration and approaches to data handling, payload support, and logistical considerations for a long-term, operational mission are discussed. SAM-CAAM is feasible because, for most aerosol sources and specified seasons, particle properties tend to be repeatable, even if aerosol loading varies.

scholarly journals Comparing multiple model-derived aerosol optical properties to spatially collocated ground-based and satellite measurements

2017 ◽  
Vol 17 (7) ◽  
pp. 4451-4475 ◽  
Author(s):  
Ilissa B. Ocko ◽  
Paul A. Ginoux
Keyword(s):  
Climate Models ◽  
Climate Modeling ◽  
Global Climate ◽  
Measurement Techniques ◽  
Global Climate Models ◽  
Orthogonal Polarization ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Multiple Model ◽  
Anthropogenic Aerosols ◽  
Aerosol Properties

Abstract. Anthropogenic aerosols are a key factor governing Earth's climate and play a central role in human-caused climate change. However, because of aerosols' complex physical, optical, and dynamical properties, aerosols are one of the most uncertain aspects of climate modeling. Fortunately, aerosol measurement networks over the past few decades have led to the establishment of long-term observations for numerous locations worldwide. Further, the availability of datasets from several different measurement techniques (such as ground-based and satellite instruments) can help scientists increasingly improve modeling efforts. This study explores the value of evaluating several model-simulated aerosol properties with data from spatially collocated instruments. We compare aerosol optical depth (AOD; total, scattering, and absorption), single-scattering albedo (SSA), Ångström exponent (α), and extinction vertical profiles in two prominent global climate models (Geophysical Fluid Dynamics Laboratory, GFDL, CM2.1 and CM3) to seasonal observations from collocated instruments (AErosol RObotic NETwork, AERONET, and Cloud–Aerosol Lidar with Orthogonal Polarization, CALIOP) at seven polluted and biomass burning regions worldwide. We find that a multi-parameter evaluation provides key insights on model biases, data from collocated instruments can reveal underlying aerosol-governing physics, column properties wash out important vertical distinctions, and improved models does not mean all aspects are improved. We conclude that it is important to make use of all available data (parameters and instruments) when evaluating aerosol properties derived by models.

Multistage Openhole Completion Using Integrated Dynamic Diversion Frac Technique in Highly Depleted Well: First Successful Application in West Kuwait Field

2021 ◽  
Author(s):  
Abdullah Abu-Eida ◽  
Salem Al-Sabea ◽  
Milan Patra ◽  
Bader Akbar ◽  
Kutbuddin Bhatia ◽  
...  
Keyword(s):  
Best Practice ◽  
Treatment Options ◽  
High Energy ◽  
Lessons Learned ◽  
High Potential ◽  
Fracture Plane ◽  
Fluid Loss ◽  
Field Development ◽  
Two Fluids

Abstract The Minagish field in West Kuwait is a high potential field which poses several challenges in terms of hydrocarbon flow assurance through highly depleted tight carbonate intervals with uneven reservoir quality and curtailed mobility. These conditions have shifted the field development from vertical to horizontal wellbore completions. Achieving complete wellbore coverage is a challenge for any frac treatment performed in a long openhole lateral with disparities in reservoir characteristics. The fluid will flow into the path of least resistance leaving large portions of the formation untreated. As a result, economic fracturing treatment options dwindle significantly, thus reservoir stimulation results are not always optimum. A multistage fracturing technique using Integrated Dynamic Diversion (IDD) has been performed first time in West Kuwait field well. The process uses active fluid energy to divert flow into a specific fracture point in the lateral, which can initiate and precisely place a fracture. The process uses two self-directed fluid streams: one inside the pipe and one in the annulus. The process mixes the two fluids downhole with high energy to form a consistent controllable mixture. The technique includes pinpoint fluid jetting at the point of interest, followed by in-situ HCL based crosslinked systems employed for improving individual stage targets. The IDD diversion shifts the fracture to unstimulated areas to create complex fractures which increases reservoir contact volume and improved overall conductivity in the lateral. The kinetic and chemical diversion of the IDD methodology is highly critical to control fluid loss in depleted intervals and results in enhanced stimulation. Pumping a frac treatment in openhole without control would tend to initiate a longitudinal fracture along the wellbore and may restrict productivity. By using specialized completion tools with nozzles at the end of the treating string, a new pinpoint process has been employed to initiate a transverse fracture plane in IDD applications. Proper candidate selection and fluid combination with in-situ crosslink acid effectively plug the fracture generated previously and generate pressure high enough to initiate another fracture for further ramification. By combining these processes into one continuous operation, the use of wireline/coiled tubing for jetting, plug setting and milling is eliminated, making the new multistage completion technology economical for these depleted wells. The application of the IDD methodology is a fit-for-purpose solution to address the unique challenges of openhole operations, formation technical difficulties, high-stakes economics, and untapped high potential from intermittent reservoirs. The paper will present post-operation results of this completion from all fractured zones along the lateral and will describe the lessons learned in implementation of this methodology which can be considered as best practice for application in similar challenges in other fields.

scholarly journals Best Paper Selection

2017 ◽  
Vol 26 (01) ◽  
pp. 212-213
Keyword(s):  
Logistic Regression ◽  
Private Information ◽  
Statistical Models ◽  
Heart Sound ◽  
Information Leakage ◽  
Scientific Data ◽  
Training Data ◽  
Genotype Data ◽  
Scientific Data Management ◽  
Heart Sound Segmentation

Agarwal V, Podchiyska T, Banda JM, Goel V, Leung TI, Minty EP, Sweeney TE, Gyang E, Shah NH. Learning statistical models of phenotypes using noisy labeled training data. J Am Med Inform Assoc 2016;23(6):1166-73 https://academic.oup.com/jamia/article-lookup/doi/10.1093/jamia/ocw028 Harmanci A, Gerstein M. Quantification of private information leakage from phenotype-genotype data: linking attacks. Nat Methods 2016;13(3):251-6 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4834871/ Pfiffner PB, Pinyol I, Natter MD, Mandl KD. C3-PRO: Connecting ResearchKit to the Health System Using i2b2 and FHIR. PloS One 2016;11(3):e0152722 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4816293/ Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten JW, da Silva Santos LB, Bourne PE, Bouwman J, Brookes AJ, Clark T, Crosas M, Dillo I, Dumon O, Edmunds S, Evelo CT, Finkers R, Gonzalez-Beltran A, Gray AJ, Groth P, Goble C, Grethe JS, Heringa J, ‘t Hoen PA, Hooft R, Kuhn T, Kok R, Kok J, Lusher SJ, Martone ME, Mons A, Packer AL, Persson B, Rocca-Serra P, Roos M, van Schaik R, Sansone SA, Schultes E, Sengstag T, Slater T, Strawn G, Swertz MA, Thompson M, van der Lei J, van Mulligen E, Velterop J, Waagmeester A, Wittenburg P, Wolstencroft K, Zhao J, Mons B. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 2016;3:160018 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4792175/ Springer DB, Tarassenko L, Clifford GD. Logistic regression-HSMM-based heart sound segmentation. IEEE Trans Biomed Eng 2016 Apr;63(4):822-32

scholarly journals Precipitation at Dumont d'Urville, Adélie Land, East Antarctica: the APRES3 field campaigns dataset

2018 ◽  
Vol 10 (3) ◽  
pp. 1605-1612 ◽  
Author(s):  
Christophe Genthon ◽  
Alexis Berne ◽  
Jacopo Grazioli ◽  
Claudio Durán Alarcón ◽  
Christophe Praz ◽  
...  
Keyword(s):  
Climate Models ◽  
Data Repository ◽  
X Band ◽  
Intensive Observation ◽  
Radar Measurements ◽  
Scientific Results ◽  
Antarctic Precipitation ◽  
Severe Shortage ◽  
Observation Period

Abstract. Compared to the other continents and lands, Antarctica suffers from a severe shortage of in situ observations of precipitation. APRES3 (Antarctic Precipitation, Remote Sensing from Surface and Space) is a program dedicated to improving the observation of Antarctic precipitation, both from the surface and from space, to assess climatologies and evaluate and ameliorate meteorological and climate models. A field measurement campaign was deployed at Dumont d'Urville station at the coast of Adélie Land in Antarctica, with an intensive observation period from November 2015 to February 2016 using X-band and K-band radars, a snow gauge, snowflake cameras and a disdrometer, followed by continuous radar monitoring through 2016 and beyond. Among other results, the observations show that a significant fraction of precipitation sublimates in a dry surface katabatic layer before it reaches and accumulates at the surface, a result derived from profiling radar measurements. While the bulk of the data analyses and scientific results are published in specialized journals, this paper provides a compact description of the dataset now archived in the PANGAEA data repository (https://www.pangaea.de, https://doi.org/10.1594/PANGAEA.883562) and made open to the scientific community to further its exploitation for Antarctic meteorology and climate research purposes.

scholarly journals Upper urinary tract draining in acute gestational pyelonephritis: What for? When? For how long?

2019 ◽  
Vol 7 (3) ◽  
pp. 35-40 ◽  
Author(s):  
K. L. Lokshin
Keyword(s):  
Urinary Tract ◽  
Upper Urinary Tract ◽  
Scientific Data ◽  
Optimal Treatment ◽  
Evidence Based

Diagnosis and optimal treatment of urological conditions in pregnant have lots of controversy due to a lack of objective and evidence-based data. This is equally true in for acute gestational pyelonephritis patients, particularly in the context of indications for upper urinary tract ‘de-obstruction’/ draining, and catheter stay in situ time. This review is a compilation of current scientific data concerning upper urinary tract draining in patients with acute gestational pyelonephritis, as well analysis of our own data and results.

scholarly journals Model cascade from meteorological drivers to river flood hazard: flood-cascade v1.0

2021 ◽  
Vol 14 (8) ◽  
pp. 4865-4890
Author(s):  
Peter Uhe ◽  
Daniel Mitchell ◽  
Paul D. Bates ◽  
Nans Addor ◽  
Jeff Neal ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
River Flow ◽  
Climate Model ◽  
Climate Modeling ◽  
Flood Hazard ◽  
Spatial Scales ◽  
Computational Cost ◽  
Data Sets ◽  
Flood Inundation

Abstract. Riverine flood hazard is the consequence of meteorological drivers, primarily precipitation, hydrological processes and the interaction of floodwaters with the floodplain landscape. Modeling this can be particularly challenging because of the multiple steps and differing spatial scales involved in the varying processes. As the climate modeling community increases their focus on the risks associated with climate change, it is important to translate the meteorological drivers into relevant hazard estimates. This is especially important for the climate attribution and climate projection communities. Current climate change assessments of flood risk typically neglect key processes, and instead of explicitly modeling flood inundation, they commonly use precipitation or river flow as proxies for flood hazard. This is due to the complexity and uncertainties of model cascades and the computational cost of flood inundation modeling. Here, we lay out a clear methodology for taking meteorological drivers, e.g., from observations or climate models, through to high-resolution (∼90 m) river flooding (fluvial) hazards. Thus, this framework is designed to be an accessible, computationally efficient tool using freely available data to enable greater uptake of this type of modeling. The meteorological inputs (precipitation and air temperature) are transformed through a series of modeling steps to yield, in turn, surface runoff, river flow, and flood inundation. We explore uncertainties at different modeling steps. The flood inundation estimates can then be related to impacts felt at community and household levels to determine exposure and risks from flood events. The approach uses global data sets and thus can be applied anywhere in the world, but we use the Brahmaputra River in Bangladesh as a case study in order to demonstrate the necessary steps in our hazard framework. This framework is designed to be driven by meteorology from observational data sets or climate model output. In this study, only observations are used to drive the models, so climate changes are not assessed. However, by comparing current and future simulated climates, this framework can also be used to assess impacts of climate change.

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