An official website of the United States government
The Unidata Program Center dedicates two software engineers to the development and maintenance of a science gateway meant to serve the members of the Earth Systems Science community. Unidata collaborated with one such community member, Dr. Greg Blumberg of the Department of Earth Sciences at Millerville University, in order to provide three undergraduate courses in atmospheric science with access to a custom JupyterHub cluster on the Jetstream2 Cloud boasting preconfigured environments, a shared network drive, and the capability to enable machine learning education and the execution of the Weather Research and Forecasting (WRF) model. The implementation of these features through the Kubernetes orchestration engine is discussed in detail, including initial failures of the Unidata Science Gateway team and the resolution of the issues that arose as a result. The performance of WRF executed at scale using JupyterHub is discussed at a surface level, with more study necessary to make further conclusions. Finally, feedback from Dr. Blumberg, both positive and constructive, is discussed along with specific use cases for the cyberinfrastructure.
more »
« less
The I-WRF Framework: Containerized Weather Modeling, Validation, and Verification
We describe the I-WRF project for the NSF Cyberinfrastructure for Sustained Scientific Innovation program, which provides a framework for application containers that allow the Weather Research and Forecasting Model (WRF) software and accompanying MET and METplus validation software to be run on a wide range of resources with minimal installation requirements. I-WRF will support three major science use cases that quantify impacts of environmental or human developments together with climate change on critical outcomes. I-WRF is also intended to facilitate outreach by making it easier to provide training and demonstrations to build understanding and interest for new potential atmospheric scientists.
more »
« less
- Award ID(s):
- 2209711
- PAR ID:
- 10527497
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9781450399852
- Page Range / eLocation ID:
- 206 to 210
- Format(s):
- Medium: X
- Location:
- Portland OR USA
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract The computational fluid dynamics of hurricane rapid intensification (RI) is examined through idealized simulations using two codes: a community‐based, finite‐difference/split‐explicit model (WRF) and a spectral‐element/semi‐implicit model (NUMA). The focus of the analysis is on the effects of implicit numerical dissipation (IND) in the energetics of the vortex response to heating, which embodies the fundamental dynamics in the hurricane RI process. The heating considered here is derived from observations: four‐dimensional, fully nonlinear, latent heating/cooling rates calculated from airborne Doppler radar measurements collected in a hurricane undergoing RI. The results continue to show significant IND in WRF relative to NUMA with a reduction in various intensity metrics: (a) time‐integrated, mean kinetic energy values in WRF are ∼20% lower than NUMA and (b) peak, localized wind speeds in WRF are ∼12 m/s lower than NUMA. Values of the eddy diffusivity in WRF need to be reduced by ∼50% from those in NUMA to produce a similar intensity time series. Kinetic energy budgets demonstrate that the pressure contribution is the main factor in the model differences with WRF producing smaller energy input to the vortex by ∼23%, on average. The low‐order spatial discretization of the pressure gradient in WRF is implicated in the IND. In addition, the eddy transport term is found to have a largely positive impact on the vortex intensification with a mean contribution of ∼20%. Overall, these results have important implications for the research and operational forecasting communities that use WRF and WRF‐like numerical models.more » « less
-
The objective of this study was to assess feasibility of integrating a coupled fire-atmosphere model within an air-quality forecast system to create a multiscale air-quality modeling framework designed to simulate wildfire smoke. For this study, a coupled fire-atmosphere model, WRF-SFIRE, was integrated, one-way, with the AIRPACT air-quality modeling system. WRF-SFIRE resolved local meteorology, fire growth, the fire plume rise, and smoke dispersion, and provided AIRPACT with fire inputs. The WRF-SFIRE-forecasted fire area and the explicitly resolved vertical smoke distribution replaced the parameterized BlueSky fire inputs used by AIRPACT. The WRF-SFIRE/AIRPACT integrated framework was successfully tested for two separate wildfire events (2015 Cougar Creek and 2016 Pioneer fires). The execution time for the WRF-SFIRE simulations was <3 h for a 48 h-long forecast, suggesting that integrating coupled fire-atmosphere simulations within the daily AIRPACT cycle is feasible. While the WRF-SFIRE forecasts realistically captured fire growth 2 days in advance, the largest improvements in the air quality simulations were associated with the wildfire plume rise. WRF-SFIRE-estimated plume tops were within 300-m of satellite-estimated plume top heights for both case studies analyzed in this study. Air quality simulations produced by AIRPACT with and without WRF-SFIRE inputs were evaluated with nearby PM 2 . 5 measurement sites to assess the performance of our multiscale smoke modeling framework. The largest improvements when coupling WRF-SFIRE with AIRPACT were observed for the Cougar Creek Fire where model errors were reduced by ∼50%. For the second case (Pioneer fire), the most notable change with WRF-SFIRE coupling was that the probability of detection increased from 16 to 52%.more » « less
-
This is the Masters thesis of Badrul Hasan from UMBC in the Department of Mechanical Engineering. The co-main advisors are Meilin Yu (UMBC) and Stephen Guimond (UMBC, now with Hampton University). Numerous aspects of human existence, both material and immaterial, can be disrupted by a hurricane. In this work, the computational fluid dynamics of hurricane rapid intensification (RI) are studied by running idealized simulations with two different codes: a community-based, finite-difference/split-explicit model (WRF) and a spectral-element/semi-implicit model (NUMA). Rapid intensification is what RI stands for, how a hurricane gets stronger quickly. The main goal of this study is to find out how implicit numerical dissipation (IND) affects the energy of the vortex's response to heating, which describes the fundamental dynamics of the hurricane RI process. The heating that is taken into account here is derived from data. These observations include four-dimensional, fully nonlinear, latent heating/cooling rates estimated using airborne Doppler radar readings acquired during RI in a hurricane. The results show that WRF has more IND than NUMA, with a decrease in several intensity parameters, such as (1) the time-integrated mean kinetic energy values that WRF predicts are 20% lower than those that NUMA predicts and (2) the peak, localized wind speeds that WRF predicts are 12 meters per second slower than those that NUMA predicts. To make a time series of intensity similar to NUMA, the eddy diffusivity values in WRF need to be less than those in NUMA by about 50%. Various analyses are conducted comparing WRF with NUMA. Kinetic energy budgets reveal that the pressure contribution is the primary cause in the model variations, with WRF generating an average 23% lower vortex energy input. The IND is associated with the low-order spatial discretization of the pressure gradient in WRF. In addition, the mean contribution of the eddy transport term to the vortex intensification is determined to be 20% positive. These findings have significant implications for the academic and operational forecasting communities that employ WRF and similar numerical methods.more » « less
-
Background Accurate simulation of wildfires can benefit pre-ignition mitigation and preparedness, and post-ignition emergency response management. Aims We evaluated the performance of Weather Research and Forecast-Fire (WRF-Fire), a coupled fire-atmosphere wildland fire simulation platform, in simulating a large historic fire (2018 Camp Fire). Methods A baseline model based on a setup typically used for WRF-Fire operational applications is utilised to simulate Camp Fire. Simulation results are compared to high-temporal-resolution fire perimeters derived from NEXRAD observations. The sensitivity of the model to a series of modelling parameters and assumptions governing the simulated wind field are then investigated. Results of WRF-Fire for Camp Fire are compared to FARSITE. Key results Baseline case shows non-negligible discrepancies between the simulated fire and the observations on rate of spread (ROS) and spread direction. Sensitivity analysis results show that refining the atmospheric grid of Camp Fire’s complex terrain improves fire prediction capabilities. Conclusions Sensitivity studies show the importance of refined atmosphere modelling for wildland fire simulation using WRF-Fire in complex terrains. Compared to FARSITE, WRF-Fire agrees better with the observations in terms of fire propagation rate and direction. Implications The findings suggest the need for further investigation of other possible sources of wildfire modelling uncertainties and errors.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3569951.3597547
