Engineering topics
Publications and source records attributed to Pierce, Roger.
Supplementary material to "Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Project Goals and Experimental Design"
A two-day workshop with participants from various U.S. federal agencies/programs, national and international universities, and U.S. national labs met to discuss progress with the Atmospheric River Tracking Method Intercomparison Project (ARTMIP). ARTMIP aims to quantify the uncertainty in AR climatology, precipitation, and related impacts that arise from a wide range of AR tracking methods developed by the community, and how these AR-related metrics may change in the future.
The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification and tracking algorithms in the literature with a wide range of techniques and conclusions. ARTMIP strives to provide the community with information on different methodologies and provide guidance on the most appropriate algorithm for a given science question or region of interest. All ARTMIP participants will implement their detection algorithms on a specified common dataset for a defined period of time. The project is divided into two phases: Tier 1 will utilize the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis from January 1980 to June 2017 and will be used as a baseline for all subsequent comparisons. Participation in Tier 1 is required. Tier 2 will be optional and include sensitivity studies designed around specific science questions, such as reanalysis uncertainty and climate change. High-resolution reanalysis and/or model output will be used wherever possible. Proposed metrics include AR frequency, duration, intensity, and precipitation attributable to ARs. Here, we present the ARTMIP experimental design, timeline, project requirements, and a brief description of the variety of methodologies in the current literature. Furthermore, we also present results from our 1-month proof-of-concept trial run designed to illustrate the utility and feasibility of the ARTMIP project.
Atmospheric rivers (ARs) have for the last decade been broadly recognized for their global and regional significance in mediating energy and water cycles. As a distinct large-scale circulation feature, ARs can be characterized by long, narrow bands of atmospheric moisture transport from the tropics to higher latitudes. They are both an important source of water supply to coastal regions as well as a hazard because of their predisposition to increase flood risk. However, predicting ARs poses a significant challenge to the scientific community, as they exhibit large variability from subseasonal-to-interannual time scales. On multi-decadal and longer time scales, it is unclear how the frequency and intensity of ARs will change with a warming climate. Hence ARs play a significant role in understanding predictability of water cycle variability and extremes as well as becoming a factor in assessing risks to future infrastructures. There is a large body of literature that has explored ARs from both global and regional perspectives and from timescales spanning hourly to centennial. Despite significant progress in understanding ARs, significant gaps remain, e.g., in characterizing the dynamical and thermodynamical processes associated with ARs, improving predictions of ARs at weather and subseasonal-to-seasonal timescales, and understanding and quantifying the impacts of ARs on the design and management of built infrastructures. Furthermore, the consensus definition of ARs remains essentially qualitative, and investigators have had to rely on heuristic definitions of ARs for quantitative studies. In the First Atmospheric River Tracking Method Intercomparison Project (ARTMIP) workshop held in May 2017, it was recognized that (1) there are many heuristic AR tracking algorithms employed in the literature, (2) our quantitative—and possibly qualitative— understanding of ARs and their impacts may depend on the details of the algorithm used, (3) no data set yet exists to systematically explore the impact of AR tracking algorithm choice on scientific results, and (4) the broader scientific community therefore lacks any formal guidance on the advantages and disadvantages of different AR tracking methods. The First ARTMIP workshop defined and launched a multi-tiered intercomparison experiment designed to fill this community need. The first tier of ARTMIP was aimed at understanding the impact of AR algorithms on quantitative baseline statistics and characteristics of ARs, and the second tier includes sensitivity studies designed around specific science questions, such as reanalysis uncertainty and influences associated with climate change. The Second ARTMIP workshop was convened on April 23-24, 2018, as a two-day event, and following the completion of Tier 1 of the ARTMIP effort: an experiment in which most existing AR tracking algorithms were run on a standardized data set of reanalyzed weather conditions.
UMAP is a system utility library which provides an application-specific buffer of pages cashed from a large file, i.e. out-of-core execution using memory map.
EMPRESS (Expert Mission Planning and REplanning Scheduling System) is an expert system created to assist payload mission planners at Kennedy in the long range planning and scheduling of horizontal payloads for space shuttle flights. Using the current flight manifest, these planners develop mission and payload schedules detailing all processing to be performed in the Operations and Checkout building at Kennedy. With the EMPRESS system, schedules are generated quickly using standard flows that represent the tasks and resources required to process a specific horizontal carrier. Resources can be tracked and resource conflicts can be determined and resolved interactively. Constraint relationships between tasks are maintained and can be enforced when a task is moved or rescheduled. The domain, structure, and functionality of the EMPRESS system is briefly designed. The limitations of the EMPRESS system are described as well as improvements expected with the EMPRESS-2 development.