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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Exploring the Capabilities of a Machine Learning Algorithm to Detect Space Weather-Significant Emerging Active Regions

Active regions are a source of various phenomena responsible for Space Weather disturbances; therefore, developing a technology for early warning about upcoming magnetic activity is crucial to mitigate its impact. However, observational limitations and the high nonlinearity of processes associated with the accumulation of magnetic flux and its interaction with the surrounding plasma during the emergence through the convection zone make early activity detection a challenging problem. To address these challenges, we developed a physics-driven machine learning model that allows us to detect active regions (ARs) before they become visible on the solar surface by analyzing the power spectra of acoustic oscillations observed by the SDO/HMI instrument. This study is based on a time series of Doppler shift maps of 31x31-degree areas tracked with the Carrington rotation rate for four days before and after the emergence. The Doppler shift time series are processed into the oscillation power maps for four frequency ranges and accompanied by line-of-sight magnetograms and the continuum intensity maps from SDO/HMI. The resulting data are converted into a 1D time series representing the mean temporal variations of these quantities. The redacted time series are used as input to predict AR emergence using the Long Short Term Memory (LSTM) method. The training of the LSTM model is based on 40 ARs, which includes an independent analysis for each sub region that exhibits AR emergence or remains quiet. The emergence of magnetic flux (defined as a decrease of the continuum intensity) was detected with the developed LSTM algorithm from 5 to 48 hours before the reported time by NOAA. The developed model is capable of pointing to the time and location of active region formation. In this presentation, we discuss reasons that impact how early in advance the model can identify the upcoming activity and the possibility of improving the current predictive skills and steps to transition to the operational forecast.

Heliophysics↗
NASA NTRS2014

Integration of RGB "Dust" Imagery to Operations at the Albuquerque Forecast Office

The NASA/Short‐term Prediction, Research, and Transition (SPoRT) Program has been providing unique Red‐Green‐Blue (RGB) composite imagery to its operational partners since 2005. In the early years of activity these RGB products were related to a True Color RGB, showing what one's own eyes would see if looking down at earth from space, as well as a Snow‐Cloud RGB (i.e. False Color), separating clouds from snow on the ground. More recently SPoRT has used the EUMETSAT Best Practices standards for RGB composites to transition a wide array of imagery for multiple uses. A "Dust" RGB product has had particular use at the Albuquerque, New Mexico WFO. Several cases have occurred where users were able to isolate dust plume locations for mesoscale and microscale events during day and night time conditions. In addition the "Dust" RGB can be used for more than just detection of dust as it is sensitive to the changes in density due to atmospheric moisture content. Hence low‐level dry boundaries can often be discriminated. This type of imagery is a large change from the single channel imagery typically used by operational forecast staff and hence, can be a challenge to interpret. This presentation aims to discuss the integration of such new imagery into operational use as well as the benefits assessed by the Albuquerque WFO over several documented events.

Fuell, Kevin↗
NASA NTRS2014

Integration of RGB "Dust" Imagery to Operations at the Albuqueque Forecast Office

The NASA/Short‐term Prediction, Research, and Transition (SPoRT) Program has been providing unique Red‐Green‐Blue (RGB) composite imagery to its operational partners since 2005. In the early years of activity these RGB products were related to a True Color RGB, showing what one's own eyes would see if looking down at earth from space, as well as a Snow‐Cloud RGB (i.e. False Color), separating clouds from snow on the ground. More recently SPoRT has used the EUMETSAT Best Practices standards for RGB composites to transition a wide array of imagery for multiple uses. A "Dust" RGB product has had particular use at the Albuquerque, New Mexico WFO. Several cases have occurred where users were able to isolate dust plume locations for mesoscale and microscale events during day and night time conditions. In addition the "Dust" RGB can be used for more than just detection of dust as it is sensitive to the changes in density due to atmospheric moisture content. Hence low‐level dry boundaries can often be discriminated. This type of imagery is a large change from the single channel imagery typically used by operational forecast staff and hence, can be a challenge to interpret. This presentation aims to discuss the integration of such new imagery into operational use as well as the benefits assessed by the Albuquerque WFO over several documented events.

Fuell, Kevin↗
NASA NTRS2022

Operational maize yield forecasts for Sub-Saharan Africa using Earth observation data and machine learning

Food insecurity continues to grow in Sub-Saharan Africa (SSA). In 2019, chronically malnourished people numbered nearly 240 million, or 20% of the population in SSA. Globally, numerous efforts have been made to anticipate potential droughts, crop conditions, and food shortages to foster improved food insecurity early warning and risk management. To support this goal, we develop an Earth Observation (EO) and machine-learning-based operational, subnational maize yield forecast system and evaluate its out-of-sample forecast skills during the growing seasons for Kenya, Somalia, Malawi, and Burkina Faso. In general, forecast skills improve substantially during the vegetative growth period (VP) and gradually during the reproductive development period (RP). Thus, mid-season assessment can provide effective early warning months before harvest. Skillful forecasts (Nash Sutcliffe Efficiency (NSE) > 0.6 and Mean Absolute Percentage Error (MAPE) < 20%) appear approximately two dekads after the VP; for example, they appear in May in Kenya and Somalia, January in Malawi, and July in Burkina Faso.

Donghoon Lee↗
NASA NTRS2017

Meteor Shower Forecasting for Spacecraft Operations

Although sporadic meteoroids are a much greater hazard to spacecraft than shower meteoroids in general, meteor showers can significantly increase the risk of damage over short time periods. Because showers are brief, it is sometimes possible to mitigate the risk operationally, which requires accurate predictions of shower activity. NASA's Meteoroid Environment Office generates an annual meteor shower forecast that describes the variations in the near-Earth meteoroid flux produced by meteor showers, which presents the shower flux both in absolute terms and relative to the sporadic ux. The shower forecast incorporates model predictions of annual variations in shower activity and quotes fluxes to several limiting particle kinetic energies. In this work, we describe our forecasting methods, compare them to actual observations, and highlight recent improvements to the temporal pro les based on flux measurements from the Canadian Meteor Orbit Radar (CMOR).

Moorhead, Althea V.↗
NASA NTRS2017

Meteor Shower Forecasting for Spacecraft Operations

Although sporadic meteoroids generally pose a much greater hazard to spacecraft than shower meteoroids, meteor showers can significantly increase the risk of damage over short time periods. Because showers are brief, it is sometimes possible to mitigate the risk operationally, which requires accurate predictions of shower activity. NASA's Meteoroid Environment Office (MEO) generates an annual meteor shower forecast that describes the variations in the near-Earth meteoroid flux produced by meteor showers, and presents the shower flux both in absolute terms and relative to the sporadic flux. The shower forecast incorporates model predictions of annual variations in shower activity and quotes fluxes to several limiting particle kinetic energies. In this work, we describe our forecasting methods and present recent improvements to the temporal profiles based on flux measurements from the Canadian Meteor Orbit Radar (CMOR).

Moorhead, Althea V.↗
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 NTRS1980

The program of the Techniques Development Laboratory in aviation weather forecasting

Some operational and experimental products developed for aviation weather forecasting are briefly described. Experimental products include surface dew point, obstructions to vision, boundary layer model, computer-worded terminal forecasts, terminal alerting procedure, generalized equivalent Markov, and radar forecasts (0-2 hours).

Klein, W. H.↗
NASA NTRS2015

Development and Application of Hyperspectral Infrared Ozone Retrieval Products for Operational Meteorology

Cyclogenesis is a key forecast challenge at operational forecasting centers such as WPC and OPC, so these centers have a particular interest in unique products that can identify key storm features. In some cases, explosively developing extratropical cyclones can produce hurricane force, non-convective winds along the East Coast and north Atlantic as well as the Pacific Ocean, with the potential to cause significant damage to life and property. Therefore, anticipating cyclogenesis for these types of storms is crucial for furthering the NOAA goal of a "Weather Ready Nation". Over the last few years, multispectral imagery (i.e. RGB) products have gained popularity among forecasters. The GOES-R satellite champion at WPC/OPC has regularly evaluated the Air Mass RGB products from GOES Sounder, MODIS, and SEVIRI to aid in forecasting cyclogenesis as part of ongoing collaborations with SPoRT within the framework of the GOES-R Proving Ground. WPC/OPC has used these products to identify regions of stratospheric air associated with tropopause folds that can lead to cyclogenesis and hurricane force winds. RGB products combine multiple channels or channel differences into multi-color imagery in which different colors represent a particular cloud or air mass type. Initial interaction and feedback from forecasters evaluating the legacy Air Mass RGBs revealed some uncertainty regarding what physical processes the qualitative RGB products represent and color interpretation. To enhance forecaster confidence and interpretation of the Air Mass RGB, NASA SPoRT has transitioned a total column ozone product from AIRS retrievals to the WPC/OPC. The use of legacy AIRS demonstrates future JPSS capabilities possible with CrIS or OMPS. Since stratospheric air can be identified by anomalous potential vorticity and warm, dry, ozone-rich air, hyperspectral infrared sounder ozone products can be used in conjunction with the Air Mass RGB for identifying the role of stratospheric air in explosive cyclogenesis and hurricane force wind events. Currently, forecasters at WPC/OPC are evaluating the Air Mass RGB imagery in conjunction with the AIRS total column ozone to aid forecasting cyclogenesis and high wind forecasts. One of the limitations of the total ozone product is that it is difficult for forecasters to determine whether elevated ozone concentrations are related to stratospheric air or climatologically high values of ozone in certain regions. To address this limitation, SPoRT created an AIRS ozone anomaly product which calculates the percent of normal ozone based on a global stratospheric ozone mean climatology. With the knowledge that ozone values 125 percent of normal and greater typically represent stratospheric air; the anomaly product can be used with the total column ozone product to confirm regions of stratospheric air on the Air Mass RGB. This presentation describes the generation of these products along with forecaster feedback concerning the use of the AIRS ozone products in conjunction with the Air Mass RGB product for the unique forecast challenges WPC/OPC face. Additionally examples of CrIS ozone and anomaly products will be shown to further demonstrate the utility and capability of JPSS in forecasting unique events.

Berndt, Emily↗
NASA NTRS2012

A Comparison of Perturbed Initial Conditions and Multiphysics Ensembles in a Severe Weather Episode in Spain

Ensembles of numerical model forecasts are of interest to operational early warning forecasters as the spread of the ensemble provides an indication of the uncertainty of the alerts, and the mean value is deemed to outperform the forecasts of the individual models. This paper explores two ensembles on a severe weather episode in Spain, aiming to ascertain the relative usefulness of each one. One ensemble uses sensible choices of physical parameterizations (precipitation microphysics, land surface physics, and cumulus physics) while the other follows a perturbed initial conditions approach. The results show that, depending on the parameterizations, large differences can be expected in terms of storm location, spatial structure of the precipitation field, and rain intensity. It is also found that the spread of the perturbed initial conditions ensemble is smaller than the dispersion due to physical parameterizations. This confirms that in severe weather situations operational forecasts should address moist physics deficiencies to realize the full benefits of the ensemble approach, in addition to optimizing initial conditions. The results also provide insights into differences in simulations arising from ensembles of weather models using several combinations of different physical parameterizations.

severe weather↗
NASA NTRS1985

Use of wind data in global modelling

The European Centre for Medium Range Weather Forecasts (ECMWF) is producing operational global analyses every 6 hours and operational global forecasts every day from the 12Z analysis. How the wind data are used in the ECMWF golbal analysis is described. For each current wind observing system, its ability to provide initial conditions for the forecast model is discussed as well as its weaknesses. An assessment of the impact of each individual system on the quality of the analysis and the forecast is given each time it is possible. Sometimes the deficiencies which are pointed out are related not only to the observing system itself but also to the optimum interpolation (OI) analysis scheme; then some improvements are generally possible through ad hoc modifications of the analysis scheme and especially tunings of the structure functions. Examples are given. The future observing network over the North Atlantic is examined. Several countries, coordinated by WMO, are working to set up an 'Operational WWW System Evaluation' (OWSE), in order to evaluate the operational aspects of the deployment of new systems (ASDAR, ASAP). Most of the new systems are expected to be deployed before January 1987, and in order to make the best use of the available resources during the deployment phase, some network studies are carried out at the present time, by using simulated data for ASDAR and ASAP systems. They are summarized.

Pailleux, J.↗