Long‐term efforts have sought to extend global model resolution to smaller scales enabling more accurate descriptions of gravity wave (GW) sources and responses, given their major roles in coupling and variability throughout the atmosphere. Such studies reveal significant improvements accompanying increasing resolution, but no guidance on what is sufficient to approximate reality. We take the opposite approach, using a finite‐volume model solving the Navier‐Stokes equations exactly. The reference simulation addresses mountain wave (MW) generation and responses over the Southern Andes described using isotropic 500 m, central resolution by Fritts et al. (2021),
Hydroelectric power (hydropower) is unique in that it can function as both a conventional source of electricity and as backup storage (pumped hydroelectric storage and large reservoir storage) for providing energy in times of high demand on the grid (S. Rehman, L M Al-Hadhrami, and M M Alam), (2015
- NSF-PAR ID:
- 10368734
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Environmental Research Communications
- Volume:
- 4
- Issue:
- 7
- ISSN:
- 2515-7620
- Page Range / eLocation ID:
- Article No. 075003
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract https://doi.org/10.1175/JAS-D-20-0207.1 and Lund et al. (2020),https://doi.org/10.1175/JAS-D-19-0356.1 . Reductions of horizontal resolution to 1 and 2 km result in (a) systematic increases in initial MW breaking altitudes, (b) weaker, larger‐scale generation of secondary GWs and acoustic waves accompanying these dynamics, and (c) significantly weaker and less extended responses in the mesosphere in latitude and longitude. Horizontal resolution of 4 km largely suppresses instabilities, but allows weak, sustained mean‐flow interactions. Responses for 8 km resolution are very weak and fail to capture any aspects of the high‐resolution responses. The chosen mean winds allow efficient MW penetration into the mesosphere and lower thermosphere, hence only exhibit strong pseudo‐momentum deposition and mean wind decelerations at higher altitudes. A companion paper by Fritts et al. (2022),https://doi.org/10.1029/2021JD036035 explores the impacts of decreasing resolution on responses in the thermosphere. -
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Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022.
Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance.
Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models.
Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks.
Funding: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 (
https://www.nfdi4health.de/task-force-covid-19-2 ) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z). -
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Abstract Computational workflows are widely used in data analysis, enabling automated tracking of steps and storage of provenance information, leading to innovation and decision-making in the scientific community. However, the growing popularity of workflows has raised concerns about reproducibility and reusability which can hinder collaboration between institutions and users. In order to address these concerns, it is important to standardize workflows or provide tools that offer a framework for describing workflows and enabling computational reusability. One such set of standards that has recently emerged is the Common Workflow Language (CWL), which offers a robust and flexible framework for data analysis tools and workflows. To promote portability, reproducibility, and interoperability of AI/ML workflows, we developed
geoweaver_cwl geoweaver_cwl geoweaver_cwl https://pypi.org/project/geoweaver-cwl/0.0.1/ and exemplar results are accessible at:https://github.com/amrutakale08/geoweaver_cwl-usecases . -
Exploring sustainable electricity system development pathways in South America’s MERCOSUR sub-regionWe explore sustainable electricity system development pathways in South America’s MERCOSUR sub-region under a range of techno-economic, infrastructural, and policy forces. The MERCOSUR sub-region includes Argentina, Brazil, Chile, Uruguay, and Paraguay, which represent key electricity generation, consumption, and trade dynamics on the continent. We use a power system planning model to co-optimize investment and operations of generation, storage, and transmission facilities out to 2050. Our results show that, under business-as-usual conditions, wind and solar contribute more than half of new generation capacity by 2050, though this requires substantial expansion of natural gas-based capacity. While new hydropower appears to be less cost-competitive, the existing high capacity of hydropower provides critically important flexibility to integrate the wind and solar and to avoid further reliance on more expensive or polluting resources (e.g., natural gas). Over 90% emission cut by 2050 could be facilitated mostly by enhanced integration (predominantly after 2040) of wind, solar, and battery storage with 11%–28% additional cost, whereas enhanced expansion of hydropower reduces the cost of low-carbon transition, suggesting trade-off opportunities between saving costs and environment in selecting the clean energy resources. Achieving high emission reduction goals will also require enhanced sub-regional electricity trade, which could be mostly facilitated by existing interconnection capacities.more » « less
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Abstract Roll vortices are a series of large-scale turbulent eddies that nearly align with the mean wind direction and prevail in the hurricane boundary layer. In this study, the one-way nested WRF-LES model simulation results from Li et al. (J Atmos Sci 78(6):1847–1867,
https://doi.org/10.1175/JAS-D-20-0270.1 , 2021) are used to examine the structure and generation mechanism of roll vortices and associated coherent turbulence in the hurricane boundary layer during the landfall of Hurricane Harvey from 00 UTC 25 to 18 UTC 27 August 2017. Results indicate that roll vortices prevail in the hurricane boundary layer. The intense roll vortices and associated large turbulent eddies above them (at a height of ~ 200 to 3000 m) accumulate within a hurricane radius of 20–40 km. Their intensity is proportional to hurricane intensity during the simulation period. Before and during hurricane landfall, strong inflow convergence leads to horizontal advection of roll vortices throughout the entire hurricane boundary layer. Combined with the strong wind shear, the strongest roll vortices and associated large turbulent eddies are generated near the eyewall with suitable thermodynamic (Richardson number at around − 0.2 to 0.2) and dynamic conditions (strong negative inflow wind shear). After landfall, the decayed inflow weakens the inflow convergence and quickly reduces the strong roll vortices and associated large turbulent eddies. Diagnosis of vertical turbulent kinetic energy indicates that atmospheric pressure perturbation, caused by horizontal convergence, transfers the horizontal component of turbulence to the vertical component with a mean wavelength of about 1 km. The buoyancy term is weak and negative, and the large turbulent eddies are suppressed.
