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NASA NTRS2009

Tools and Products of Real-Time Modeling: Opportunities for Space Weather Forecasting

The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second CCMC activity is to support Space Weather forecasting at national Space Weather Forecasting Centers. This second activity involves model evaluations, model transitions to operations, and the development of draft Space Weather forecasting tools. This presentation will focus on the last element. Specifically, we will discuss present capabilities, and the potential to derive further tools. These capabilities will be interpreted in the context of a broad-based, bootstrapping activity for modern Space Weather forecasting.

Hesse, Michael↗

NASA NTRS2013

How MAG4 Improves Space Weather Forecasting

Dangerous space weather is driven by solar flares and Coronal Mass Ejection (CMEs). Forecasting flares and CMEs is the first step to forecasting either dangerous space weather or All Clear. MAG4 (Magnetogram Forecast), developed originally for NASA/SRAG (Space Radiation Analysis Group), is an automated program that analyzes magnetograms from the HMI (Helioseismic and Magnetic Imager) instrument on NASA SDO (Solar Dynamics Observatory), and automatically converts the rate (or probability) of major flares (M- and X-class), Coronal Mass Ejections (CMEs), and Solar Energetic Particle Events.

Falconer, David↗

NASA NTRS2017

Transforming Satellite Data into Weather Forecasts

A NASA project spans the gap between research and operations, introducing new composites of satellite imagery to weather forecasters to prepare for the next generation of satellites. Satellite imagery has been an immense benefit to weather forecasters. With it, they can assess aviation hazards such as low clouds, monitor thunderstorms, and track the evolution of dust plumes. Satellite sensors are continually evolving to provide ever greater imaging capabilities, and researchers continue to develop advanced techniques to identify hazards in satellite imagery. However, barriers can prevent experimental products from reaching forecasters in the operational environment. A NASA project has developed an interactive process whereby weather forecasters learn to interpret the latest satellite imagery and apply it to their operations. Forecasters then provide feedback to the researchers who are developing algorithms and products to further improve future products. This effort has taken on greater importance with the anticipated launch of a new series of satellites that will provide substantially greater amounts of data than are currently available.

Emily Berndt↗

DOE OSTI2025

Enhancing Short-Range Weather Forecasts through Temporal Variation Encoding: A Multiperiod Embedding Approach

Machine learning (ML) techniques have emerged as promising approaches to improve regional weather forecast accuracy and reliability through data-driven methods. We propose a novel ML-based weather forecasting model, the Multiperiod Embed Net (MPENet). A key distinguishing feature of MPENet is its explicit utilization of the inherent cyclic nature in weather dynamics, unlike the autoregressive strategies commonly used in other ML weather forecasting approaches. Critical cyclic structures are identified via Fourier analyses of dynamic time series. Cyclicity in the convolutional representation is achieved by transforming one-dimensional time series of meteorological variables into two-dimensional tensors based on identified periods. This approach enables the model to leverage intrinsic weather patterns, enhancing regional forecast performance. To demonstrate the effectiveness of MPENet, we conduct a comparative analysis with Nvidia’s FourCastNet. Both models are trained on High-Resolution Rapid Refresh (HRRR) data from 2015 to 2022, over a 192 km × 192 km region in Tennessee. The comparisons are performed locally at two specific locations known to have different weather dynamics due to orographic effects: Crossville, on the relatively flat Cumberland Plateau with fewer topographic airflow disruptions, and Oak Ridge, in the ridge-and-valley region, where airflow is heavily influenced by surrounding valleys and mountains. Our results indicate that FourCastNet achieves strong accuracy at very short lead times, while MPENet maintains competitive skill and shows advantages in capturing temporal evolution over longer periods. Cross-correlation analyses of MPENet and FourCastNet predictions with the HRRR data suggest that encoding critical cyclicity into the network architecture leads to improvements in the forecasting skill.

Artificial intelligence↗

NASA NTRS1962

THE UTILITY OF WEATHER FORECASTS TO THE RAISIN INDUSTRY

Utility of weather forecasts to the raisin industry

METEOROLOGY↗

NASA NTRS2006

Using Satellite Data in Weather Forecasting: I

The GOES Product Generation System (GPGS) is a set of computer codes and scripts that enable the assimilation of real-time Geostationary Operational Environmental Satellite (GOES) data into regional-weather-forecasting mathematical models. The GPGS can be used to derive such geophysical parameters as land surface temperature, the amount of precipitable water, the degree of cloud cover, the surface albedo, and the amount of insolation from satellite measurements of radiant energy emitted by the Earth and its atmosphere. GPGS incorporates a priori information (initial guesses of thermodynamic parameters of the atmosphere) and radiometric measurements from the geostationary operational environmental satellites along with mathematical models of physical principles that govern the transfer of energy in the atmosphere. GPGS solves the radiative-transfer equation and provides the resulting data products in formats suitable for use by weather-forecasting computer programs. The data-assimilation capability afforded by GPGS offers the potential to improve local weather forecasts ranging from 3 hours to 2 days - especially with respect to temperature, humidity, cloud cover, and the probability of precipitation. The improvements afforded by GPGS could be of interest to news media, utility companies, and other organizations that utilize regional weather forecasts.

Jedlovec, Gary J.↗

NASA NTRS2019

Space Weather Forecasting Capabilities at the Community Coordinated Modeling Center (CCMC)

The Community Coordinated Modeling Center (CCMC) provides a variety of services to the space science community. The mission for the CCMC's Space Weather Forecasting team is to address the space weather needs of NASA's robotic mission by conducting customized space weather services to NASA end-users. The team leverages CCMC tools/resources, carries out prototyping activities for the next generation space weather tools and follows communications/interactions with the users. We provide space weather forecasts, notifications, analysis and also education. This presentation will describe the team's concepts of operations, notification processes, anomaly analysis, and the tools used for space weather forecasting. The tools include a system that are completely open and available to the public's use like the Integrated Space Weather Analysis (iSWA) tool and the Database of Notifications, Knowledge and Information (DONKI). We will also discuss the education and training activities and how events like solar eclipses are important for the improvement and validation of different space weather models.

Collado-Vega, Yaireska↗

NASA NTRS2012

Development of a High Resolution Weather Forecast Model for Mesoamerica Using the NASA Ames Code I Private Cloud Computing Environment

Two projects at NASA Marshall Space Flight Center have collaborated to develop a high resolution weather forecast model for Mesoamerica: The NASA Short-term Prediction Research and Transition (SPoRT) Center, which integrates unique NASA satellite and weather forecast modeling capabilities into the operational weather forecasting community. NASA's SERVIR Program, which integrates satellite observations, ground-based data, and forecast models to improve disaster response in Central America, the Caribbean, Africa, and the Himalayas.

Molthan, Andrew↗

NASA NTRS1969

The value of weather forecasts

Economic and social benefits from weather forecasting developments, noting expenditures on satellites and high speed computers

Thompson, J. C.↗

NASA NTRS2002

Smooth Sailing for Weather Forecasting

Through a cooperative venture with NASA's Stennis Space Center, WorldWinds, Inc., developed a unique weather and wave vector map using space-based radar satellite information and traditional weather observations. Called WorldWinds, the product provides accurate, near real-time, high-resolution weather forecasts. It was developed for commercial and scientific users. In addition to weather forecasting, the product's applications include maritime and terrestrial transportation, aviation operations, precision farming, offshore oil and gas operations, and coastal hazard response support. Target commercial markets include the operational maritime and aviation communities, oil and gas providers, and recreational yachting interests. Science applications include global long-term prediction and climate change, land-cover and land-use change, and natural hazard issues. Commercial airlines have expressed interest in the product, as it can provide forecasts over remote areas. WorldWinds, Inc., is currently providing its product to commercial weather outlets.

Source record↗

NASA NTRS2012

Community Coordinated Modeling Center: Addressing Needs of Operational Space Weather Forecasting

Models are key elements of space weather forecasting. The Community Coordinated Modeling Center (CCMC, http://ccmc.gsfc.nasa.gov) hosts a broad range of state-of-the-art space weather models and enables access to complex models through an unmatched automated web-based runs-on-request system. Model output comparisons with observational data carried out by a large number of CCMC users open an unprecedented mechanism for extensive model testing and broad community feedback on model performance. The CCMC also evaluates model's prediction ability as an unbiased broker and supports operational model selections. The CCMC is organizing and leading a series of community-wide projects aiming to evaluate the current state of space weather modeling, to address challenges of model-data comparisons, and to define metrics for various user s needs and requirements. Many of CCMC models are continuously running in real-time. Over the years the CCMC acquired the unique experience in developing and maintaining real-time systems. CCMC staff expertise and trusted relations with model owners enable to keep up to date with rapid advances in model development. The information gleaned from the real-time calculations is tailored to specific mission needs. Model forecasts combined with data streams from NASA and other missions are integrated into an innovative configurable data analysis and dissemination system (http://iswa.gsfc.nasa.gov) that is accessible world-wide. The talk will review the latest progress and discuss opportunities for addressing operational space weather needs in innovative and collaborative ways.

Kuznetsova, M.↗

NASA NTRS1971

How some nonmeteorological professionals view meteorology and weather forecasting.

The results of a questionnaire designed to gather information on how nonmeteorological scientists and engineers view meteorology and weather forecasting are summarized in this paper. The respondents were from two organizations, Texas A & M University and NASA's Marshall Space Flight Center, the first representing the academic community and the latter the engineering community. While there were some differences between the groups, in most cases answers expressed in the opinionnaire by the two groups were essentially identical. The results revealed the following: Approximately three-fourths of the respondents use meteorological data and/or weather forecasts in their profession; the meaning of probability forecasts is very unclear with only 13% indicating the correct answer; television is the main source of weather information; approximately half of the respondents had never heard of the Global Atmospheric Research Program; and the opinion was almost unanimous that satellites had contributed significantly to weather observations and/or forecasts. Also, the results indicated a number of other ?problem' areas where some improvements are desired.

Scoggins, J. R.↗

NASA NTRS2004

The Effect of NEXRAD Image Looping and National Convective Weather Forecast Product on Pilot Decision Making in the Use of a Cockpit Weather Information Display

This experiment investigated improvements to cockpit weather displays to better support the hazardous weather avoidance decision-making of general aviation pilots. Forty-eight general aviation pilots were divided into three equal groups and presented with a simulated flight scenario involving embedded convective activity. The control group had access to conventional sources of pre-flight and in-flight weather products. The two treatment groups were provided with a weather display that presented NEXRAD mosaic images, graphic depiction of METARs, and text METARs. One treatment group used a NEXRAD image looping feature and the second group used the National Convective Weather Forecast (NCWF) product overlaid on the NEXRAD display. Both of the treatment displays provided a significant increase in situation awareness but, they provided incomplete information required to deal with hazardous convective weather conditions, and would require substantial pilot training to permit their safe and effective use.

Burgess, Malcolm A.↗

NASA NTRS1992

Weather forecasting support for AASE-2

The AFEAS Contract and NASA Grant were awarded to Penn State in order to obtain real-time weather forecasting support for the NASA AASE-II Project, which was conducted between October 1991 and March 1992. Because of the special weather sensitivities of the NASA ER-2 aircraft, AASE-II planners felt that public weather forecasts issued by the National Weather Service would not be adequate for mission planning purposes. A likely consequence of resorting to that medium would have been that scientists would have had to be at work by 4 AM day after day in the hope that the aircraft could fly, only to be frustrated by a great number of 'scrubbed' missions. Thus, the Pennsylvania State University was contracted to provide real-time weather support to the AASE-II mission.

Forbes, Gregory S.↗

NASA NTRS2012

Development of a High Resolution Weather Forecast Model for Mesoamerica Using the NASA Nebula Cloud Computing Environment

Over the past two years, scientists in the Earth Science Office at NASA fs Marshall Space Flight Center (MSFC) have explored opportunities to apply cloud computing concepts to support near real ]time weather forecast modeling via the Weather Research and Forecasting (WRF) model. Collaborators at NASA fs Short ]term Prediction Research and Transition (SPoRT) Center and the SERVIR project at Marshall Space Flight Center have established a framework that provides high resolution, daily weather forecasts over Mesoamerica through use of the NASA Nebula Cloud Computing Platform at Ames Research Center. Supported by experts at Ames, staff at SPoRT and SERVIR have established daily forecasts complete with web graphics and a user interface that allows SERVIR partners access to high resolution depictions of weather in the next 48 hours, useful for monitoring and mitigating meteorological hazards such as thunderstorms, heavy precipitation, and tropical weather that can lead to other disasters such as flooding and landslides. This presentation will describe the framework for establishing and providing WRF forecasts, example applications of output provided via the SERVIR web portal, and early results of forecast model verification against available surface ] and satellite ]based observations.

Molthan, Andrew L.↗

NASA NTRS2016

Earth Remote Sensing for Weather Forecasting and Disaster Applications

NASA's constellation of current missions provide several opportunities to apply satellite remote sensing observations to weather forecasting and disaster response applications. Examples include: Using NASA's Terra and Aqua MODIS, and the NASA/NOAA Suomi-NPP VIIRS missions to prepare weather forecasters for capabilities of GOES-R; Incorporating other NASA remote sensing assets for improving aspects of numerical weather prediction; Using NASA, NOAA, and international partner resources (e.g. ESA/Sentinel Series); and commercial platforms (high-res, or UAV) to support disaster mapping.

Molthan, Andrew↗

NASA NTRS2014

Development and Implementation of Dynamic Scripts to Support Local Model Verification at National Weather Service Weather Forecast Offices

Local modeling with a customized configuration is conducted at National Weather Service (NWS) Weather Forecast Offices (WFOs) to produce high-resolution numerical forecasts that can better simulate local weather phenomena and complement larger scale global and regional models. The advent of the Environmental Modeling System (EMS), which provides a pre-compiled version of the Weather Research and Forecasting (WRF) model and wrapper Perl scripts, has enabled forecasters to easily configure and execute the WRF model on local workstations. NWS WFOs often use EMS output to help in forecasting highly localized, mesoscale features such as convective initiation, the timing and inland extent of lake effect snow bands, lake and sea breezes, and topographically-modified winds. However, quantitatively evaluating model performance to determine errors and biases still proves to be one of the challenges in running a local model. Developed at the National Center for Atmospheric Research (NCAR), the Model Evaluation Tools (MET) verification software makes performing these types of quantitative analyses easier, but operational forecasters do not generally have time to familiarize themselves with navigating the sometimes complex configurations associated with the MET tools. To assist forecasters in running a subset of MET programs and capabilities, the Short-term Prediction Research and Transition (SPoRT) Center has developed and transitioned a set of dynamic, easily configurable Perl scripts to collaborating NWS WFOs. The objective of these scripts is to provide SPoRT collaborating partners in the NWS with the ability to evaluate the skill of their local EMS model runs in near real time with little prior knowledge of the MET package. The ultimate goal is to make these verification scripts available to the broader NWS community in a future version of the EMS software. This paper provides an overview of the SPoRT MET scripts, instructions for how the scripts are run, and example use cases.

Zavordsky, Bradley↗

NASA NTRS2014

Development and Implementation of Dynamic Scripts to Support Local Model Verification at National Weather Service Weather Forecast Offices

Zavodsky, Bradley↗