Forecasting intense geomagnetic activity using interplanetary magnetic field data

NASA Astrophysics Data System (ADS)

Saiz, E.; Cid, C.; Cerrato, Y.

2008-12-01

Southward interplanetary magnetic fields are considered traces of geoeffectiveness since they are a main agent of magnetic reconnection of solar wind and magnetosphere. The first part of this work revises the ability to forecast intense geomagnetic activity using different procedures available in the literature. The study shows that current methods do not succeed in making confident predictions. This fact led us to develop a new forecasting procedure, which provides trustworthy results in predicting large variations of Dst index over a sample of 10 years of observations and is based on the value Bz only. The proposed forecasting method appears as a worthy tool for space weather purposes because it is not affected by the lack of solar wind plasma data, which usually occurs during severe geomagnetic activity. Moreover, the results obtained guide us to provide a new interpretation of the physical mechanisms involved in the interaction between the solar wind and the magnetosphere using Faraday's law.

The MSFC Solar Activity Future Estimation (MSAFE) Model

NASA Technical Reports Server (NTRS)

Suggs, Ronnie J.

2017-01-01

The MSAFE model provides forecasts for the solar indices SSN, F10.7, and Ap. These solar indices are used as inputs to many space environment models used in orbital spacecraft operations and space mission analysis. Forecasts from the MSAFE model are provided on the MSFC Natural Environments Branch's solar webpage and are updated as new monthly observations come available. The MSAFE prediction routine employs a statistical technique that calculates deviations of past solar cycles from the mean cycle and performs a regression analysis to predict the deviation from the mean cycle of the solar index at the next future time interval. The prediction algorithm is applied recursively to produce monthly smoothed solar index values for the remaining of the cycle. The forecasts are initiated for a given cycle after about 8 to 12 months of observations are collected. A forecast made at the beginning of cycle 24 using the MSAFE program captured the cycle fairly well with some difficulty in discerning the double peak that occurred at solar cycle maximum.

Space Weather Forecasting at IZMIRAN

NASA Astrophysics Data System (ADS)

Gaidash, S. P.; Belov, A. V.; Abunina, M. A.; Abunin, A. A.

2017-12-01

Since 1998, the Institute of Terrestrial Magnetism, Ionosphere, and Radio Wave Propagation (IZMIRAN) has had an operating heliogeophysical service—the Center for Space Weather Forecasts. This center transfers the results of basic research in solar-terrestrial physics into daily forecasting of various space weather parameters for various lead times. The forecasts are promptly available to interested consumers. This article describes the center and the main types of forecasts it provides: solar and geomagnetic activity, magnetospheric electron fluxes, and probabilities of proton increases. The challenges associated with the forecasting of effects of coronal mass ejections and coronal holes are discussed. Verification data are provided for the center's forecasts.

Flare forecasting at the Met Office Space Weather Operations Centre

NASA Astrophysics Data System (ADS)

Murray, S. A.; Bingham, S.; Sharpe, M.; Jackson, D. R.

2017-04-01

The Met Office Space Weather Operations Centre produces 24/7/365 space weather guidance, alerts, and forecasts to a wide range of government and commercial end-users across the United Kingdom. Solar flare forecasts are one of its products, which are issued multiple times a day in two forms: forecasts for each active region on the solar disk over the next 24 h and full-disk forecasts for the next 4 days. Here the forecasting process is described in detail, as well as first verification of archived forecasts using methods commonly used in operational weather prediction. Real-time verification available for operational flare forecasting use is also described. The influence of human forecasters is highlighted, with human-edited forecasts outperforming original model results and forecasting skill decreasing over longer forecast lead times.

An Early Prediction of Sunspot Cycle 25

NASA Astrophysics Data System (ADS)

Nandy, D.; Bhowmik, P.

2017-12-01

The Sun's magnetic activity governs our space environment, creates space weather and impacts our technologies and climate. With increasing reliance on space- and ground-based technologies that are subject to space weather, the need to be able to forecast the future activity of the Sun has assumed increasing importance. However, such long-range, decadal-scale space weather prediction has remained a great challenge as evident in the diverging forecasts for solar cycle 24. Based on recently acquired understanding of the physics of solar cycle predictability, we have devised a scheme to extend the forecasting window of solar cycles. Utilizing this we present an early forecast for sunspot cycle 25 which would be of use for space mission planning, satellite life-time estimates, and assessment of the long-term impacts of space weather on technological assets and planetary atmospheres.

AE Geomagnetic Index Predictability for High Speed Solar Wind Streams: A Wavelet Decomposition Technique

NASA Technical Reports Server (NTRS)

Guarnieri, Fernando L.; Tsurutani, Bruce T.; Hajra, Rajkumar; Echer, Ezequiel; Gonzalez, Walter D.; Mannucci, Anthony J.

2014-01-01

High speed solar wind streams cause geomagnetic activity at Earth. In this study we have applied a wavelet interactive filtering and reconstruction technique on the solar wind magnetic field components and AE index series to allowed us to investigate the relationship between the two. The IMF Bz component was found as the most significant solar wind parameter responsible by the control of the AE activity. Assuming magnetic reconnection associated to southward directed Bz is the main mechanism transferring energy into the magnetosphere, we adjust parameters to forecast the AE index. The adjusted routine is able to forecast AE, based only on the Bz measured at the L1 Lagrangian point. This gives a prediction approximately 30-70 minutes in advance of the actual geomagnetic activity. The correlation coefficient between the observed AE data and the forecasted series reached values higher than 0.90. In some cases the forecast reproduced particularities observed in the signal very well.The high correlation values observed and the high efficacy of the forecasting can be taken as a confirmation that reconnection is the main physical mechanism responsible for the energy transfer during HILDCAAs. The study also shows that the IMF Bz component low frequencies are most important for AE prediction.

Dynamo-based scheme for forecasting the magnitude of solar activity cycles

NASA Technical Reports Server (NTRS)

Layden, A. C.; Fox, P. A.; Howard, J. M.; Sarajedini, A.; Schatten, K. H.

1991-01-01

This paper presents a general framework for forecasting the smoothed maximum level of solar activity in a given cycle, based on a simple understanding of the solar dynamo. This type of forecasting requires knowledge of the sun's polar magnetic field strength at the preceding activity minimum. Because direct measurements of this quantity are difficult to obtain, the quality of a number of proxy indicators already used by other authors is evaluated, which are physically related to the sun's polar field. These indicators are subjected to a rigorous statistical analysis, and the analysis technique for each indicator is specified in detail in order to simplify and systematize reanalysis for future use. It is found that several of these proxies are in fact poorly correlated or uncorrelated with solar activity, and thus are of little value for predicting activity maxima. Also presented is a scheme in which the predictions of the individual proxies are combined via an appropriately weighted mean to produce a compound prediction. The scheme is then applied to the current cycle 22, and a maximum smoothed international sunspot number of 171 + or - 26 is estimated.

Forecasting Flare Activity Using Deep Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Hernandez, T.

2017-12-01

Current operational flare forecasting relies on human morphological analysis of active regions and the persistence of solar flare activity through time (i.e. that the Sun will continue to do what it is doing right now: flaring or remaining calm). In this talk we present the results of applying deep Convolutional Neural Networks (CNNs) to the problem of solar flare forecasting. CNNs operate by training a set of tunable spatial filters that, in combination with neural layer interconnectivity, allow CNNs to automatically identify significant spatial structures predictive for classification and regression problems. We will start by discussing the applicability and success rate of the approach, the advantages it has over non-automated forecasts, and how mining our trained neural network provides a fresh look into the mechanisms behind magnetic energy storage and release.

Analysis of regression methods for solar activity forecasting

NASA Technical Reports Server (NTRS)

Lundquist, C. A.; Vaughan, W. W.

1979-01-01

The paper deals with the potential use of the most recent solar data to project trends in the next few years. Assuming that a mode of solar influence on weather can be identified, advantageous use of that knowledge presumably depends on estimating future solar activity. A frequently used technique for solar cycle predictions is a linear regression procedure along the lines formulated by McNish and Lincoln (1949). The paper presents a sensitivity analysis of the behavior of such regression methods relative to the following aspects: cycle minimum, time into cycle, composition of historical data base, and unnormalized vs. normalized solar cycle data. Comparative solar cycle forecasts for several past cycles are presented as to these aspects of the input data. Implications for the current cycle, No. 21, are also given.

Activities of NICT space weather project

NASA Astrophysics Data System (ADS)

Murata, Ken T.; Nagatsuma, Tsutomu; Watari, Shinichi; Shinagawa, Hiroyuki; Ishii, Mamoru

NICT (National Institute of Information and Communications Technology) has been in charge of space weather forecast service in Japan for more than 20 years. The main target region of the space weather is the geo-space in the vicinity of the Earth where human activities are dominant. In the geo-space, serious damages of satellites, international space stations and astronauts take place caused by energetic particles or electromagnetic disturbances: the origin of the causes is dynamically changing of solar activities. Positioning systems via GPS satellites are also im-portant recently. Since the most significant effect of positioning error comes from disturbances of the ionosphere, it is crucial to estimate time-dependent modulation of the electron density profiles in the ionosphere. NICT is one of the 13 members of the ISES (International Space Environment Service), which is an international assembly of space weather forecast centers under the UNESCO. With help of geo-space environment data exchanging among the member nations, NICT operates daily space weather forecast service every day to provide informa-tion on forecasts of solar flare, geomagnetic disturbances, solar proton event, and radio-wave propagation conditions in the ionosphere. The space weather forecast at NICT is conducted based on the three methodologies: observations, simulations and informatics (OSI model). For real-time or quasi real-time reporting of space weather, we conduct our original observations: Hiraiso solar observatory to monitor the solar activity (solar flare, coronal mass ejection, and so on), domestic ionosonde network, magnetometer HF radar observations in far-east Siberia, and south-east Asia low-latitude ionosonde network (SEALION). Real-time observation data to monitor solar and solar-wind activities are obtained through antennae at NICT from ACE and STEREO satellites. We have a middle-class super-computer (NEC SX-8R) to maintain real-time computer simulations for solar and solar-wind, magnetosphere and ionosphere. The three simulations are directly or indirectly connected each other based on real-time observa-tion data to reproduce a virtual geo-space region on the super-computer. Informatics is a new methodology to make precise forecast of space weather. Based on new information and communication technologies (ICT), it provides more information in both quality and quantity. At NICT, we have been developing a cloud-computing system named "space weather cloud" based on a high-speed network system (JGN2+). Huge-scale distributed storage (1PB), clus-ter computers, visualization systems and other resources are expected to derive new findings and services of space weather forecasting. The final goal of NICT space weather service is to predict near-future space weather conditions and disturbances which will be causes of satellite malfunctions, tele-communication problems, and error of GPS navigations. In the present talk, we introduce our recent activities on the space weather services and discuss how we are going to develop the services from the view points of space science and practical uses.

Long-Range Solar Activity Predictions: A Reprieve from Cycle #24's Activity

NASA Technical Reports Server (NTRS)

Richon, K.; Schatten, K.

2003-01-01

We discuss the field of long-range solar activity predictions and provide an outlook into future solar activity. Orbital predictions for satellites in Low Earth Orbit (LEO) depend strongly on exospheric densities. Solar activity forecasting is important in this regard, as the solar ultra-violet (UV) and extreme ultraviolet (EUV) radiations inflate the upper atmospheric layers of the Earth, forming the exosphere in which satellites orbit. Rather than concentrate on statistical, or numerical methods, we utilize a class of techniques (precursor methods) which is founded in physical theory. The geomagnetic precursor method was originally developed by the Russian geophysicist, Ohl, using geomagnetic observations to predict future solar activity. It was later extended to solar observations, and placed within the context of physical theory, namely the workings of the Sun s Babcock dynamo. We later expanded the prediction methods with a SOlar Dynamo Amplitude (SODA) index. The SODA index is a measure of the buried solar magnetic flux, using toroidal and poloidal field components. It allows one to predict future solar activity during any phase of the solar cycle, whereas previously, one was restricted to making predictions only at solar minimum. We are encouraged that solar cycle #23's behavior fell closely along our predicted curve, peaking near 192, comparable to the Schatten, Myers and Sofia (1996) forecast of 182+/-30. Cycle #23 extends from 1996 through approximately 2006 or 2007, with cycle #24 starting thereafter. We discuss the current forecast of solar cycle #24, (2006-2016), with a predicted smoothed F10.7 radio flux of 142+/-28 (1-sigma errors). This, we believe, represents a reprieve, in terms of reduced fuel costs, etc., for new satellites to be launched or old satellites (requiring reboosting) which have been placed in LEO. By monitoring the Sun s most deeply rooted magnetic fields; long-range solar activity can be predicted. Although a degree of uncertainty in the long-range predictions remains, requiring future monitoring, we do not expect the next cycle's + 2-sigma value will rise significantly above solar cycle #23's activity level.

The NWRA Classification Infrastructure: description and extension to the Discriminant Analysis Flare Forecasting System (DAFFS)

NASA Astrophysics Data System (ADS)

Leka, K. D.; Barnes, Graham; Wagner, Eric

2018-04-01

A classification infrastructure built upon Discriminant Analysis (DA) has been developed at NorthWest Research Associates for examining the statistical differences between samples of two known populations. Originating to examine the physical differences between flare-quiet and flare-imminent solar active regions, we describe herein some details of the infrastructure including: parametrization of large datasets, schemes for handling "null" and "bad" data in multi-parameter analysis, application of non-parametric multi-dimensional DA, an extension through Bayes' theorem to probabilistic classification, and methods invoked for evaluating classifier success. The classifier infrastructure is applicable to a wide range of scientific questions in solar physics. We demonstrate its application to the question of distinguishing flare-imminent from flare-quiet solar active regions, updating results from the original publications that were based on different data and much smaller sample sizes. Finally, as a demonstration of "Research to Operations" efforts in the space-weather forecasting context, we present the Discriminant Analysis Flare Forecasting System (DAFFS), a near-real-time operationally-running solar flare forecasting tool that was developed from the research-directed infrastructure.

The Art and Science of Long-Range Space Weather Forecasting

NASA Technical Reports Server (NTRS)

Hathaway, David H.; Wilson, Robert M.

2006-01-01

Long-range space weather forecasts are akin to seasonal forecasts of terrestrial weather. We don t expect to forecast individual events but we do hope to forecast the underlying level of activity important for satellite operations and mission pl&g. Forecasting space weather conditions years or decades into the future has traditionally been based on empirical models of the solar cycle. Models for the shape of the cycle as a function of its amplitude become reliable once the amplitude is well determined - usually two to three years after minimum. Forecasting the amplitude of a cycle well before that time has been more of an art than a science - usually based on cycle statistics and trends. Recent developments in dynamo theory -the theory explaining the generation of the Sun s magnetic field and the solar activity cycle - have now produced models with predictive capabilities. Testing these models with historical sunspot cycle data indicates that these predictions may be highly reliable one, or even two, cycles into the future.

Detecting and disentangling nonlinear structure from solar flux time series

NASA Technical Reports Server (NTRS)

Ashrafi, S.; Roszman, L.

1992-01-01

Interest in solar activity has grown in the past two decades for many reasons. Most importantly for flight dynamics, solar activity changes the atmospheric density, which has important implications for spacecraft trajectory and lifetime prediction. Building upon the previously developed Rayleigh-Benard nonlinear dynamic solar model, which exhibits many dynamic behaviors observed in the Sun, this work introduces new chaotic solar forecasting techniques. Our attempt to use recently developed nonlinear chaotic techniques to model and forecast solar activity has uncovered highly entangled dynamics. Numerical techniques for decoupling additive and multiplicative white noise from deterministic dynamics and examines falloff of the power spectra at high frequencies as a possible means of distinguishing deterministic chaos from noise than spectrally white or colored are presented. The power spectral techniques presented are less cumbersome than current methods for identifying deterministic chaos, which require more computationally intensive calculations, such as those involving Lyapunov exponents and attractor dimension.

Operational Numerical Weather Prediction at the Met Office and potential ways forward for operational space weather prediction systems

NASA Astrophysics Data System (ADS)

Jackson, David

NICT (National Institute of Information and Communications Technology) has been in charge of space weather forecast service in Japan for more than 20 years. The main target region of the space weather is the geo-space in the vicinity of the Earth where human activities are dominant. In the geo-space, serious damages of satellites, international space stations and astronauts take place caused by energetic particles or electromagnetic disturbances: the origin of the causes is dynamically changing of solar activities. Positioning systems via GPS satellites are also im-portant recently. Since the most significant effect of positioning error comes from disturbances of the ionosphere, it is crucial to estimate time-dependent modulation of the electron density profiles in the ionosphere. NICT is one of the 13 members of the ISES (International Space Environment Service), which is an international assembly of space weather forecast centers under the UNESCO. With help of geo-space environment data exchanging among the member nations, NICT operates daily space weather forecast service every day to provide informa-tion on forecasts of solar flare, geomagnetic disturbances, solar proton event, and radio-wave propagation conditions in the ionosphere. The space weather forecast at NICT is conducted based on the three methodologies: observations, simulations and informatics (OSI model). For real-time or quasi real-time reporting of space weather, we conduct our original observations: Hiraiso solar observatory to monitor the solar activity (solar flare, coronal mass ejection, and so on), domestic ionosonde network, magnetometer HF radar observations in far-east Siberia, and south-east Asia low-latitude ionosonde network (SEALION). Real-time observation data to monitor solar and solar-wind activities are obtained through antennae at NICT from ACE and STEREO satellites. We have a middle-class super-computer (NEC SX-8R) to maintain real-time computer simulations for solar and solar-wind, magnetosphere and ionosphere. The three simulations are directly or indirectly connected each other based on real-time observa-tion data to reproduce a virtual geo-space region on the super-computer. Informatics is a new methodology to make precise forecast of space weather. Based on new information and communication technologies (ICT), it provides more information in both quality and quantity. At NICT, we have been developing a cloud-computing system named "space weather cloud" based on a high-speed network system (JGN2+). Huge-scale distributed storage (1PB), clus-ter computers, visualization systems and other resources are expected to derive new findings and services of space weather forecasting. The final goal of NICT space weather service is to predict near-future space weather conditions and disturbances which will be causes of satellite malfunctions, tele-communication problems, and error of GPS navigations. In the present talk, we introduce our recent activities on the space weather services and discuss how we are going to develop the services from the view points of space science and practical uses.

Forecast for solar cycle 23 activity: a progress report

NASA Astrophysics Data System (ADS)

Ahluwalia, H. S.

2001-08-01

At the 25th International Cosmic Ray Conference (ICRC) at Durban, South Africa, I announced the discovery of a three cycle quasi-periodicity in the ion chamber data string assembled by me, for the 1937 to 1994 period (Conf. Pap., v. 2, p. 109, 1997). It corresponded in time with a similar quasi-periodicity observed in the dataset for the planetary index Ap. At the 26th ICRC at Salt Lake City, UT, I reported on our analysis of the Ap data to forecast the amplitude of solar cycle 23 activity (Conf. Pap., v. 2, pl. 260, 1999). I predicted that cycle 23 will be moderate (a la cycle 17), notwithstanding the early exuberant forecasts of some solar astronomers that cycle 23, "may be one of the greatest cycles in recent times, if not the greatest." Sunspot number data up to April 2001 indicate that our forecast appears to be right on the mark. We review the solar, interplanetary and geophysical data and describe the important lessons learned from this experience. 1. Introduction Ohl (1971) was the first to realize that Sun may be sending us a subliminal message as to its intent for its activity (Sunspot Numbers, SSN) in the next cycle. He posited that the message was embedded in the geomagnetic activity (given by sum Kp). Schatten at al (1978) suggested that Ohl hypothesis could be understood on the basis of the model proposed by Babcock (1961) who suggested that the high latitude solar poloidal fields, near a minimum, emerge as the toroidal fields on opposite sides of the solar equator. This is known as the Solar Dynamo Model. One can speculate that the precursor poloidal solar field is entrained in the high speed solar wind streams (HSSWS) from the coronal holes which are observed at Earth's orbit during the descending phase of the previous cycle. The interaction

Flare Prediction Using Photospheric and Coronal Image Data

NASA Astrophysics Data System (ADS)

Jonas, E.; Shankar, V.; Bobra, M.; Recht, B.

2016-12-01

We attempt to forecast M-and X-class solar flares using a machine-learning algorithm and five years of image data from both the Helioseismic and Magnetic Imager (HMI) and Atmospheric Imaging Assembly (AIA) instruments aboard the Solar Dynamics Observatory. HMI is the first instrument to continuously map the full-disk photospheric vector magnetic field from space (Schou et al., 2012). The AIA instrument maps the transition region and corona using various ultraviolet wavelengths (Lemen et al., 2012). HMI and AIA data are taken nearly simultaneously, providing an opportunity to study the entire solar atmosphere at a rapid cadence. Most flare forecasting efforts described in the literature use some parameterization of solar data - typically of the photospheric magnetic field within active regions. These numbers are considered to capture the information in any given image relevant to predicting solar flares. In our approach, we use HMI and AIA images of solar active regions and a deep convolutional kernel network to predict solar flares. This is effectively a series of shallow-but-wide random convolutional neural networks stacked and then trained with a large-scale block-weighted least squares solver. This algorithm automatically determines which patterns in the image data are most correlated with flaring activity and then uses these patterns to predict solar flares. Using the recently-developed KeystoneML machine learning framework, we construct a pipeline to process millions of images in a few hours on commodity cloud computing infrastructure. This is the first time vector magnetic field images have been combined with coronal imagery to forecast solar flares. This is also the first time such a large dataset of solar images, some 8.5 terabytes of images that together capture over 3000 active regions, has been used to forecast solar flares. We evaluate our method using various flare prediction windows defined in the literature (e.g. Ahmed et al., 2013) and a novel per-hour time series we've constructed which more closely mimics the demands of an operational solar flare prediction system. We estimate the performance of our algorithm using the True Skill Statistic (TSS; Bloomfield et al., 2012). We find that our algorithm gives a high TSS score and predictive abilities.

Physics-based Space Weather Forecasting in the Project for Solar-Terrestrial Environment Prediction (PSTEP) in Japan

NASA Astrophysics Data System (ADS)

Kusano, K.

2016-12-01

Project for Solar-Terrestrial Environment Prediction (PSTEP) is a Japanese nation-wide research collaboration, which was recently launched. PSTEP aims to develop a synergistic interaction between predictive and scientific studies of the solar-terrestrial environment and to establish the basis for next-generation space weather forecasting using the state-of-the-art observation systems and the physics-based models. For this project, we coordinate the four research groups, which develop (1) the integration of space weather forecast system, (2) the physics-based solar storm prediction, (3) the predictive models of magnetosphere and ionosphere dynamics, and (4) the model of solar cycle activity and its impact on climate, respectively. In this project, we will build the coordinated physics-based model to answer the fundamental questions concerning the onset of solar eruptions and the mechanism for radiation belt dynamics in the Earth's magnetosphere. In this paper, we will show the strategy of PSTEP, and discuss about the role and prospect of the physics-based space weather forecasting system being developed by PSTEP.

MAG4 Versus Alternative Techniques for Forecasting Active-Region Flare Productivity

NASA Technical Reports Server (NTRS)

Falconer, David A.; Moore, Ronald L.; Barghouty, Abdulnasser F.; Khazanov, Igor

2014-01-01

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. MAG4 does not forecast that a flare will occur at a particular time in the next 24 or 48 hours; rather the probability of one occurring.

Condition of the upper atmosphere of the Earth at the final stage of flight manned orbital facility (MOF) "Mir". The modeling description

NASA Astrophysics Data System (ADS)

Boyarchuk, K. A.; Ivanov-Kholodny, G. S.; Kolomiitsev, O. P.; Surotkin, V. A.

At flooding MOF ``Mir'' the information on forecasting a condition of the upper atmosphere was used. The forecast was carried out on the basis of numerical model of an atmosphere, which was developed in IZMIRAN. This model allows reproducing and predicting a situation in an Earth space, in an atmosphere and an ionosphere, along an orbit of flight of a space vehicle in the various periods of solar-geophysical conditions. Thus preliminary forecasting solar and geomagnetic activity was carried out on the basis of an individual technique. Before the beginning of operation on flooding MOF ``Mir'' it was found out, that solar activity began to accrue catastrophically. The account of the forecast of its development has forced to speed up the moment of flooding to avoid dangerous development of events. It has allowed minimizing a risk factor - ``Mir'' was flooded successful in the commanded area of Pacific Ocean.

The Development of New Solar Indices for use in Thermospheric Density Modeling

NASA Technical Reports Server (NTRS)

Tobiska, W. Kent; Bouwer, S. Dave; Bowman, Bruce R.

2006-01-01

New solar indices have been developed to improve thermospheric density modeling for research and operational purposes. Out of 11 new and 4 legacy indices and proxies, we have selected three (F10.7, S10.7, and M10.7) for use in the new JB2006 empirical thermospheric density model. In this work, we report on the development of these solar irradiance indices. The rationale for their use, their definitions, and their characteristics, including the ISO 21348 spectral category and sub-category, wavelength range, solar source temperature region, solar source feature, altitude region of terrestrial atmosphere absorption at unit optical depth, and terrestrial atmosphere thermal processes in the region of maximum energy absorption, are described. We also summarize for each solar index, the facility and instrument(s) used to observe the solar emission, the time frame over which the data exist, the measurement cadence, the data latency, and the research as well as operational availability. The new solar indices are provided in forecast (http://SpaceWx.com) as well as real-time and historical (http://sol.spacenvironment.net/jb2006/) time frames. We describe the forecast methodology, compare results with actual data for active and quiet solar conditions, and compare improvements in F10.7 forecasting with legacy High Accuracy Satellite Drag Model (HASDM) and NOAA SEC forecasts.

An operational integrated short-term warning solution for solar radiation storms: introducing the Forecasting Solar Particle Events and Flares (FORSPEF) system

NASA Astrophysics Data System (ADS)

Anastasiadis, Anastasios; Sandberg, Ingmar; Papaioannou, Athanasios; Georgoulis, Manolis; Tziotziou, Kostas; Jiggens, Piers; Hilgers, Alain

2015-04-01

We present a novel integrated prediction system, of both solar flares and solar energetic particle (SEP) events, which is in place to provide short-term warnings for hazardous solar radiation storms. FORSPEF system provides forecasting of solar eruptive events, such as solar flares with a projection to coronal mass ejections (CMEs) (occurrence and velocity) and the likelihood of occurrence of a SEP event. It also provides nowcasting of SEP events based on actual solar flare and CME near real-time alerts, as well as SEP characteristics (peak flux, fluence, rise time, duration) per parent solar event. The prediction of solar flares relies on a morphological method which is based on the sophisticated derivation of the effective connected magnetic field strength (Beff) of potentially flaring active-region (AR) magnetic configurations and it utilizes analysis of a large number of AR magnetograms. For the prediction of SEP events a new reductive statistical method has been implemented based on a newly constructed database of solar flares, CMEs and SEP events that covers a large time span from 1984-2013. The method is based on flare location (longitude), flare size (maximum soft X-ray intensity), and the occurrence (or not) of a CME. Warnings are issued for all > C1.0 soft X-ray flares. The warning time in the forecasting scheme extends to 24 hours with a refresh rate of 3 hours while the respective warning time for the nowcasting scheme depends on the availability of the near real-time data and falls between 15-20 minutes. We discuss the modules of the FORSPEF system, their interconnection and the operational set up. The dual approach in the development of FORPSEF (i.e. forecasting and nowcasting scheme) permits the refinement of predictions upon the availability of new data that characterize changes on the Sun and the interplanetary space, while the combined usage of solar flare and SEP forecasting methods upgrades FORSPEF to an integrated forecasting solution. This work has been funded through the "FORSPEF: FORecasting Solar Particle Events and Flares", ESA Contract No. 4000109641/13/NL/AK

A Synthesis of Solar Cycle Prediction Techniques

NASA Technical Reports Server (NTRS)

Hathaway, David H.; Wilson, Robert M.; Reichmann, Edwin J.

1999-01-01

A number of techniques currently in use for predicting solar activity on a solar cycle timescale are tested with historical data. Some techniques, e.g., regression and curve fitting, work well as solar activity approaches maximum and provide a month-by-month description of future activity, while others, e.g., geomagnetic precursors, work well near solar minimum but only provide an estimate of the amplitude of the cycle. A synthesis of different techniques is shown to provide a more accurate and useful forecast of solar cycle activity levels. A combination of two uncorrelated geomagnetic precursor techniques provides a more accurate prediction for the amplitude of a solar activity cycle at a time well before activity minimum. This combined precursor method gives a smoothed sunspot number maximum of 154 plus or minus 21 at the 95% level of confidence for the next cycle maximum. A mathematical function dependent on the time of cycle initiation and the cycle amplitude is used to describe the level of solar activity month by month for the next cycle. As the time of cycle maximum approaches a better estimate of the cycle activity is obtained by including the fit between previous activity levels and this function. This Combined Solar Cycle Activity Forecast gives, as of January 1999, a smoothed sunspot maximum of 146 plus or minus 20 at the 95% level of confidence for the next cycle maximum.

SOLAR FLARE PREDICTION USING SDO/HMI VECTOR MAGNETIC FIELD DATA WITH A MACHINE-LEARNING ALGORITHM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bobra, M. G.; Couvidat, S., E-mail: couvidat@stanford.edu

2015-01-10

We attempt to forecast M- and X-class solar flares using a machine-learning algorithm, called support vector machine (SVM), and four years of data from the Solar Dynamics Observatory's Helioseismic and Magnetic Imager, the first instrument to continuously map the full-disk photospheric vector magnetic field from space. Most flare forecasting efforts described in the literature use either line-of-sight magnetograms or a relatively small number of ground-based vector magnetograms. This is the first time a large data set of vector magnetograms has been used to forecast solar flares. We build a catalog of flaring and non-flaring active regions sampled from a databasemore » of 2071 active regions, comprised of 1.5 million active region patches of vector magnetic field data, and characterize each active region by 25 parameters. We then train and test the machine-learning algorithm and we estimate its performances using forecast verification metrics with an emphasis on the true skill statistic (TSS). We obtain relatively high TSS scores and overall predictive abilities. We surmise that this is partly due to fine-tuning the SVM for this purpose and also to an advantageous set of features that can only be calculated from vector magnetic field data. We also apply a feature selection algorithm to determine which of our 25 features are useful for discriminating between flaring and non-flaring active regions and conclude that only a handful are needed for good predictive abilities.« less

Solar particle event predictions for manned Mars missions

NASA Technical Reports Server (NTRS)

Heckman, Gary

1986-01-01

Manned space missions to Mars require consideration of the effects of high radiation doses produced by solar particle events (SPE). Without some provision for protection, the radiation doses from such events can exceed standards for maximum exposure and may be life threatening. Several alternative ways of providing protection require a capability for predicting SPE in time to take some protective actions. The SPE may occur at any time during the eleven year solar cycle so that two year missions cannot be scheduled to insure avoiding them although they are less likely to occur at solar minimum. The present forecasts are sufficiently accurate to use for setting alert modes but are not accurate enough to make yes/no decisions that have major mission operational impacts. Forecasts made for one to two year periods can only be done as probabilistic forecasts where there is a chance of SPE occurring. These are current capabilities but are not likely to change significantly by the year 2000 with the exception of some improvement in the one to ten day forecasts. The effects of SPE are concentrated in solar longitudes near where their parent solar flares occur, which will require a manned Mars mission to carry its own small solar telescope to monitor the development of potentially dangerous solar activity. The preferred telescope complement includes a solar X-ray imager, a hydrogen-alpha scanner, and a solar magnetograph.

Solar flux forecasting using mutual information with an optimal delay

NASA Technical Reports Server (NTRS)

Ashrafi, S.; Conway, D.; Rokni, M.; Sperling, R.; Roszman, L.; Cooley, J.

1993-01-01

Solar flux F(sub 10.7) directly affects the atmospheric density, thereby changing the lifetime and prediction of satellite orbits. For this reason, accurate forecasting of F(sub 10.7) is crucial for orbit determination of spacecraft. Our attempts to model and forecast F(sub 10.7) uncovered highly entangled dynamics. We concluded that the general lack of predictability in solar activity arises from its nonlinear nature. Nonlinear dynamics allow us to predict F(sub 10.7) more accurately than is possible using stochastic methods for time scales shorter than a characteristic horizon, and with about the same accuracy as using stochastic techniques when the forecasted data exceed this horizon. The forecast horizon is a function of two dynamical invariants: the attractor dimension and the Lyapunov exponent. In recent years, estimation of the attractor dimension reconstructed from a time series has become an important tool in data analysis. In calculating the invariants of the system, the first necessary step is the reconstruction of the attractor for the system from the time-delayed values of the time series. The choice of the time delay is critical for this reconstruction. For an infinite amount of noise-free data, the time delay can, in principle, be chosen almost arbitrarily. However, the quality of the phase portraits produced using the time-delay technique is determined by the value chosen for the delay time. Fraser and Swinney have shown that a good choice for this time delay is the one suggested by Shaw, which uses the first local minimum of the mutual information rather than the autocorrelation function to determine the time delay. This paper presents a refinement of this criterion and applies the refined technique to solar flux data to produce a forecast of the solar activity.

Forecast and Specification of Radiation Belt Electrons Based on Solar Wind Measurements

NASA Astrophysics Data System (ADS)

Li, X.; Barker, A.; Burin Des Roziers, E.

2003-12-01

Relativistic electrons in the Earth's magnetosphere are of considerable practical importance because of their effect on spacecraft and because of their radiation hazard to astronauts who perform extravehicular activity. The good correlation between solar wind velocity and MeV electron fluxes at geosynchronous orbit has long been established. We have developed a radial diffusion model, using solar wind parameters as the only input, to reproduce the variation of the MeV electrons at geosynchronous orbit. Based on this model, we have constructed a real-time model that forecasts one to two days in advance the daily averaged >2 MeV electron flux at geosynchronous orbit using real-time solar wind data from ACE. The forecasts from this model are available on the web in real time. A natural extension of our current model is to create a system for making quantitative forecasts and specifications of radiation belt electrons at different radial distances and different local times based on the solar wind conditions. The successes and obstacles associated with this extension will be discussed in this presentation.

Forecasting the Solar Drivers of Solar Energetic Particle Events

NASA Technical Reports Server (NTRS)

Falconer, David A.; Moore, Ronald L.; Barghouty, Abdulnasser F.; Khazanov, Igor

2012-01-01

Large flares and fast CMEs are the drivers of the most severe space weather including Solar Energetic Particle Events (SEP Events). Large flares and their co-produced CMEs are powered by the explosive release of free magnetic energy stored in non-potential magnetic fields of sunspot active regions. The free energy is stored in and released from the low-beta regime of the active region's magnetic field above the photosphere, in the chromosphere and low corona. From our work over the past decade and from similar work of several other groups, it is now well established that (1) a proxy of the free magnetic energy stored above the photosphere can be measured from photospheric magnetograms, maps of the measured field in the photosphere, and (2) an active region's rate of production of major CME/flare eruptions in the coming day or so is strongly correlated with its present measured value of the free-energy proxy. These results have led us to use the large database of SOHO/MDI full-disk magnetograms spanning Solar Cycle 23 to obtain empirical forecasting curves that from an active region's present measured value of the free-energy proxy give the active region's expected rates of production of major flares, CMEs, fast CMEs, and SEP Events in the coming day or so (Falconer et al 2011, Space Weather, 9, S04003). We will present these forecasting curves and demonstrate the accuracy of their forecasts. In addition, we will show that the forecasts for major flares and fast CMEs can be made significantly more accurate by taking into account not only the value of the free energy proxy but also the active region's recent productivity of major flares; specifically, whether the active region has produced a major flare (GOES class M or X) during the past 24 hours before the time of the measured magnetogram.

Solar radio proxies for improved satellite orbit prediction

NASA Astrophysics Data System (ADS)

Yaya, Philippe; Hecker, Louis; Dudok de Wit, Thierry; Fèvre, Clémence Le; Bruinsma, Sean

2017-12-01

Specification and forecasting of solar drivers to thermosphere density models is critical for satellite orbit prediction and debris avoidance. Satellite operators routinely forecast orbits up to 30 days into the future. This requires forecasts of the drivers to these orbit prediction models such as the solar Extreme-UV (EUV) flux and geomagnetic activity. Most density models use the 10.7 cm radio flux (F10.7 index) as a proxy for solar EUV. However, daily measurements at other centimetric wavelengths have also been performed by the Nobeyama Radio Observatory (Japan) since the 1950's, thereby offering prospects for improving orbit modeling. Here we present a pre-operational service at the Collecte Localisation Satellites company that collects these different observations in one single homogeneous dataset and provides a 30 days forecast on a daily basis. Interpolation and preprocessing algorithms were developed to fill in missing data and remove anomalous values. We compared various empirical time series prediction techniques and selected a multi-wavelength non-recursive analogue neural network. The prediction of the 30 cm flux, and to a lesser extent that of the 10.7 cm flux, performs better than NOAA's present prediction of the 10.7 cm flux, especially during periods of high solar activity. In addition, we find that the DTM-2013 density model (Drag Temperature Model) performs better with (past and predicted) values of the 30 cm radio flux than with the 10.7 flux.

Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, J.; Hodge, B. M.; Florita, A.

2013-10-01

Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The resultsmore » show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.« less

Forecasting the Solar Drivers of Severe Space Weather from Active-Region Magnetograms

NASA Technical Reports Server (NTRS)

Falconer, David A.; Moore, Ronald L.; Barghouty, Abdulnasser F.; Khazanov, Igor

2012-01-01

Large flares and fast CMEs are the drivers of the most severe space weather including Solar Energetic Particle Events (SEP Events). Large flares and their co-produced CMEs are powered by the explosive release of free magnetic energy stored in non-potential magnetic fields of sunspot active regions. The free energy is stored in and released from the low-beta regime of the active region s magnetic field above the photosphere, in the chromosphere and low corona. From our work over the past decade and from similar work of several other groups, it is now well established that (1) a proxy of the free magnetic energy stored above the photosphere can be measured from photospheric magnetograms, and (2) an active region s rate of production of major CME/flare eruptions in the coming day or so is strongly correlated with its present measured value of the free-energy proxy. These results have led us to use the large database of SOHO/MDI full-disk magnetograms spanning Solar Cycle 23 to obtain empirical forecasting curves that from an active region s present measured value of the free-energy proxy give the active region s expected rates of production of major flares, CMEs, fast CMEs, and SEP Events in the coming day or so (Falconer et al 2011, Space Weather, 9, S04003). We will present these forecasting curves and demonstrate the accuracy of their forecasts. In addition, we will show that the forecasts for major flares and fast CMEs can be made significantly more accurate by taking into account not only the value of the free energy proxy but also the active region s recent productivity of major flares; specifically, whether the active region has produced a major flare (GOES class M or X) during the past 24 hours before the time of the measured magnetogram. By empirically determining the conversion of the value of free-energy proxy measured from a GONG or HMI magnetogram to that which would be measured from an MDI magnetogram, we have made GONG and HMI magnetograms useable with our MDI-based forecasting curves to forecast event rates.

ScienceCast 94: Solar Max Double Peaked

NASA Image and Video Library

2013-03-01

Something unexpected is happening on the sun. 2013 is supposed to be the year of Solar Max, but solar activity is much lower than expected. At least one leading forecaster expects the sun to rebound with a double-peaked maximum later this year.

Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheung, WanYin; Zhang, Jie; Florita, Anthony

2015-12-08

Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance,more » cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.« less

Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan

2015-10-05

Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reductionmore » in the amount of reserves that must be held to accommodate the uncertainty of solar power output.« less

Probabilistic Solar Wind and Geomagnetic Forecasting Using an Analogue Ensemble or "Similar Day" Approach

NASA Astrophysics Data System (ADS)

Owens, M. J.; Riley, P.; Horbury, T. S.

2017-05-01

Effective space-weather prediction and mitigation requires accurate forecasting of near-Earth solar-wind conditions. Numerical magnetohydrodynamic models of the solar wind, driven by remote solar observations, are gaining skill at forecasting the large-scale solar-wind features that give rise to near-Earth variations over days and weeks. There remains a need for accurate short-term (hours to days) solar-wind forecasts, however. In this study we investigate the analogue ensemble (AnEn), or "similar day", approach that was developed for atmospheric weather forecasting. The central premise of the AnEn is that past variations that are analogous or similar to current conditions can be used to provide a good estimate of future variations. By considering an ensemble of past analogues, the AnEn forecast is inherently probabilistic and provides a measure of the forecast uncertainty. We show that forecasts of solar-wind speed can be improved by considering both speed and density when determining past analogues, whereas forecasts of the out-of-ecliptic magnetic field [BN] are improved by also considering the in-ecliptic magnetic-field components. In general, the best forecasts are found by considering only the previous 6 - 12 hours of observations. Using these parameters, the AnEn provides a valuable probabilistic forecast for solar-wind speed, density, and in-ecliptic magnetic field over lead times from a few hours to around four days. For BN, which is central to space-weather disturbance, the AnEn only provides a valuable forecast out to around six to seven hours. As the inherent predictability of this parameter is low, this is still likely a marked improvement over other forecast methods. We also investigate the use of the AnEn in forecasting geomagnetic indices Dst and Kp. The AnEn provides a valuable probabilistic forecast of both indices out to around four days. We outline a number of future improvements to AnEn forecasts of near-Earth solar-wind and geomagnetic conditions.

Two-step forecast of geomagnetic storm using coronal mass ejection and solar wind condition

PubMed Central

Kim, R-S; Moon, Y-J; Gopalswamy, N; Park, Y-D; Kim, Y-H

2014-01-01

To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind criteria derived in this study (Bz ≤ −5 nT or Ey ≥ 3 mV/m for t≥ 2 h for moderate storms with minimum Dst less than −50 nT) and a Dst model developed by Temerin and Li (2002, 2006) (TL model). Using 55 CME-Dst pairs during 1997 to 2003, our solar wind criteria produce slightly better forecasts for 31 storm events (90%) than the forecasts based on the TL model (87%). However, the latter produces better forecasts for 24 nonstorm events (88%), while the former correctly forecasts only 71% of them. We then performed the two-step forecast. The results are as follows: (i) for 15 events that are incorrectly forecasted using CME parameters, 12 cases (80%) can be properly predicted based on solar wind conditions; (ii) if we forecast a storm when both CME and solar wind conditions are satisfied (∩), the critical success index becomes higher than that from the forecast using CME parameters alone, however, only 25 storm events (81%) are correctly forecasted; and (iii) if we forecast a storm when either set of these conditions is satisfied (∪), all geomagnetic storms are correctly forecasted. PMID:26213515

Two-step forecast of geomagnetic storm using coronal mass ejection and solar wind condition.

PubMed

Kim, R-S; Moon, Y-J; Gopalswamy, N; Park, Y-D; Kim, Y-H

2014-04-01

To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind criteria derived in this study ( B z  ≤ -5 nT or E y  ≥ 3 mV/m for t ≥ 2 h for moderate storms with minimum Dst less than -50 nT) and a Dst model developed by Temerin and Li (2002, 2006) (TL model). Using 55 CME- Dst pairs during 1997 to 2003, our solar wind criteria produce slightly better forecasts for 31 storm events (90%) than the forecasts based on the TL model (87%). However, the latter produces better forecasts for 24 nonstorm events (88%), while the former correctly forecasts only 71% of them. We then performed the two-step forecast. The results are as follows: (i) for 15 events that are incorrectly forecasted using CME parameters, 12 cases (80%) can be properly predicted based on solar wind conditions; (ii) if we forecast a storm when both CME and solar wind conditions are satisfied (∩), the critical success index becomes higher than that from the forecast using CME parameters alone, however, only 25 storm events (81%) are correctly forecasted; and (iii) if we forecast a storm when either set of these conditions is satisfied (∪), all geomagnetic storms are correctly forecasted.

A Tool for Empirical Forecasting of Major Flares, Coronal Mass Ejections, and Solar Particle Events from a Proxy of Active-Region Free Magnetic Energy

NASA Technical Reports Server (NTRS)

Barghouty, A. F.; Falconer, D. A.; Adams, J. H., Jr.

2010-01-01

This presentation describes a new forecasting tool developed for and is currently being tested by NASA s Space Radiation Analysis Group (SRAG) at JSC, which is responsible for the monitoring and forecasting of radiation exposure levels of astronauts. The new software tool is designed for the empirical forecasting of M and X-class flares, coronal mass ejections, as well as solar energetic particle events. Its algorithm is based on an empirical relationship between the various types of events rates and a proxy of the active region s free magnetic energy, determined from a data set of approx.40,000 active-region magnetograms from approx.1,300 active regions observed by SOHO/MDI that have known histories of flare, coronal mass ejection, and solar energetic particle event production. The new tool automatically extracts each strong-field magnetic areas from an MDI full-disk magnetogram, identifies each as an NOAA active region, and measures a proxy of the active region s free magnetic energy from the extracted magnetogram. For each active region, the empirical relationship is then used to convert the free magnetic energy proxy into an expected event rate. The expected event rate in turn can be readily converted into the probability that the active region will produce such an event in a given forward time window. Descriptions of the datasets, algorithm, and software in addition to sample applications and a validation test are presented. Further development and transition of the new tool in anticipation of SDO/HMI is briefly discussed.

The Helioseismic and Magnetic Imager (HMI) Investigation for the Solar Dynamics Observatory (SDO)

NASA Technical Reports Server (NTRS)

Scherrer, Philip Hanby; Schou, Jesper; Bush, R. I.; Kosovichev, A. G.; Bogart, R. S.; Hoeksema, J. T.; Liu, Y.; Duvall, T. L., Jr.; Zhao, J.; Title, A. M.;

Solar Eruptive Flares: from Physical Understanding to Probabilistic Forecasting

NASA Astrophysics Data System (ADS)

Georgoulis, M. K.

2013-12-01

We describe a new, emerging physical picture of the triggering of major solar eruptions. First, we discuss and aim to interpret the single distinguishing feature of tight, shear-ridden magnetic polarity inversion lines (PILs) in solar active regions, where most of these eruptions occur. Then we analyze the repercussions of this feature, that acts to form increasingly helical pre-eruption structures. Eruptions, with the CME progenitor preceding the flare, tend to release parts of the accumulated magnetic free energy and helicity that are always much smaller than the respective budgets of the source active region. These eruption-related decreases, however, are not optimal for eruption forecasting - this role is claimed by physically intuitive proxy parameters that could show increased pre-eruption sensitivity at time scales practical for prediction. Concluding, we show how reconciling this new information - jointly enabled by the exceptional resolution and quality of Hinode and cadence of SDO data - can lead to advances in understanding that outline the current state-of-the-art of our eruption-forecasting capability.

Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

DOE PAGES

Zhang, Jie; Hodge, Bri -Mathias; Lu, Siyuan; ...

2015-11-10

Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based onmore » state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.« less

Real-time forecasting of ICME shock arrivals at L1 during the "April Fool’s Day" epoch: 28 March  21 April 2001

NASA Astrophysics Data System (ADS)

Sun, W.; Dryer, M.; Fry, C. D.; Deehr, C. S.; Smith, Z.; Akasofu, S.-I.; Kartalev, M. D.; Grigorov, K. G.

2002-07-01

The Sun was extremely active during the "April Fool’s Day" epoch of 2001. We chose this period between a solar flare on 28 March 2001 to a final shock arrival at Earth on 21 April 2001. The activity consisted of two presumed helmet-streamer blowouts, seven M-class flares, and nine X-class flares, the last of which was behind the west limb. We have been experimenting since February 1997 with real-time, end-to-end forecasting of interplanetary coronal mass ejection (ICME) shock arrival times. Since August 1998, these forecasts have been distributed in real-time by e-mail to a list of interested scientists and operational USAF and NOAA forecasters. They are made using three different solar wind models. We describe here the solar events observed during the April Fool’s 2001 epoch, along with the predicted and actual shock arrival times, and the ex post facto correction to the real-time coronal shock speed observations. It appears that the initial estimates of coronal shock speeds from Type II radio burst observations and coronal mass ejections were too high by as much as 30%. We conclude that a 3-dimensional coronal density model should be developed for application to observations of solar flares and their Type II radio burst observations.

Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan

2015-08-05

Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reductionmore » in the amount of reserves that must be held to accommodate the uncertainty of solar power output. forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.« less

Prediction of global ionospheric VTEC maps using an adaptive autoregressive model

NASA Astrophysics Data System (ADS)

Wang, Cheng; Xin, Shaoming; Liu, Xiaolu; Shi, Chuang; Fan, Lei

2018-02-01

In this contribution, an adaptive autoregressive model is proposed and developed to predict global ionospheric vertical total electron content maps (VTEC). Specifically, the spherical harmonic (SH) coefficients are predicted based on the autoregressive model, and the order of the autoregressive model is determined adaptively using the F-test method. To test our method, final CODE and IGS global ionospheric map (GIM) products, as well as altimeter TEC data during low and mid-to-high solar activity period collected by JASON, are used to evaluate the precision of our forecasting products. Results indicate that the predicted products derived from the model proposed in this paper have good consistency with the final GIMs in low solar activity, where the annual mean of the root-mean-square value is approximately 1.5 TECU. However, the performance of predicted vertical TEC in periods of mid-to-high solar activity has less accuracy than that during low solar activity periods, especially in the equatorial ionization anomaly region and the Southern Hemisphere. Additionally, in comparison with forecasting products, the final IGS GIMs have the best consistency with altimeter TEC data. Future work is needed to investigate the performance of forecasting products using the proposed method in an operational environment, rather than using the SH coefficients from the final CODE products, to understand the real-time applicability of the method.

A regressive storm model for extreme space weather

NASA Astrophysics Data System (ADS)

Terkildsen, Michael; Steward, Graham; Neudegg, Dave; Marshall, Richard

2012-07-01

Extreme space weather events, while rare, pose significant risk to society in the form of impacts on critical infrastructure such as power grids, and the disruption of high end technological systems such as satellites and precision navigation and timing systems. There has been an increased focus on modelling the effects of extreme space weather, as well as improving the ability of space weather forecast centres to identify, with sufficient lead time, solar activity with the potential to produce extreme events. This paper describes the development of a data-based model for predicting the occurrence of extreme space weather events from solar observation. The motivation for this work was to develop a tool to assist space weather forecasters in early identification of solar activity conditions with the potential to produce extreme space weather, and with sufficient lead time to notify relevant customer groups. Data-based modelling techniques were used to construct the model, and an extensive archive of solar observation data used to train, optimise and test the model. The optimisation of the base model aimed to eliminate false negatives (missed events) at the expense of a tolerable increase in false positives, under the assumption of an iterative improvement in forecast accuracy during progression of the solar disturbance, as subsequent data becomes available.

Research activities at the Australian Bureau of Meteorology for the regional ionospheric specification and forecasting

NASA Astrophysics Data System (ADS)

Bouya, Zahra; Terkildsen, Michael

2016-07-01

The Australian Space Forecast Centre (ASFC) provides space weather forecasts to a diverse group of customers. Space Weather Services (SWS) within the Australian Bureau of Meteorology is focussed both on developing tailored products and services for the key customer groups, and supporting ASFC operations. Research in SWS is largely centred on the development of data-driven models using a range of solar-terrestrial data. This paper will cover some data requirements , approaches and recent SWS activities for data driven modelling with a focus on the regional Ionospheric specification and forecasting.

Multi-spacecraft testing of time-dependent interplanetary MHD models for operational forecasting of geomagnetic storms

NASA Technical Reports Server (NTRS)

Dryer, M.; Smith, Z. K.

1989-01-01

An MHD 2-1/2D, time-dependent model is used, together with observations of six solar flares during February 3-7, 1986, to demonstrate global, large-scale, compound disturbances in the solar wind over a wide range of heliolongitudes. This scenario is one that is likely to occur many times during the cruise, possibly even encounter, phases of the Multi-Comet Mission. It is suggested that a model such as this one should be tested with multi-spacecraft data (such as the MCM and earth-based probes) with several goals in view: (1) utility of the model for operational real-time forecasting of geomagnetic storms, and (2) scientific interpretation of certain forms of cometary activities and their possible association with solar-generated activity.

Solar and Wind Forecasting | Grid Modernization | NREL

Science.gov Websites

and Wind Forecasting Solar and Wind Forecasting As solar and wind power become more common system operators. An aerial photo of the National Wind Technology Center's PV arrays. Capabilities value of accurate forecasting Wind power visualization to direct questions and feedback during industry

Foretelling Flares and Solar Energetic Particle Events: the FORSPEF tool

NASA Astrophysics Data System (ADS)

Anastasiadis, Anastasios; Papaioannou, Athanasios; Sandberg, Ingmar; Georgoulis, Manolis K.; Tziotziou, Kostas; Jiggens, Piers

2017-04-01

A novel integrated prediction system, for both solar flares (SFs) and solar energetic particle (SEP) events is being presented. The Forecasting Solar Particle Events and Flares (FORSPEF) provides forecasting of solar eruptive events, such as SFs with a projection to coronal mass ejections (CMEs) (occurrence and velocity) and the likelihood of occurrence of a SEP event. In addition, FORSPEF, also provides nowcasting of SEP events based on actual SF and CME near real-time data, as well as the complete SEP profile (peak flux, fluence, rise time, duration) per parent solar event. The prediction of SFs relies on a morphological method: the effective connected magnetic field strength (Beff); it is based on an assessment of potentially flaring active-region (AR) magnetic configurations and it utilizes sophisticated analysis of a large number of AR magnetograms. For the prediction of SEP events new methods have been developed for both the likelihood of SEP occurrence and the expected SEP characteristics. In particular, using the location of the flare (longitude) and the flare size (maximum soft X-ray intensity), a reductive statistical method has been implemented. Moreover, employing CME parameters (velocity and width), proper functions per width (i.e. halo, partial halo, non-halo) and integral energy (E>30, 60, 100 MeV) have been identified. In our technique warnings are issued for all > C1.0 soft X-ray flares. The prediction time in the forecasting scheme extends to 24 hours with a refresh rate of 3 hours while the respective prediction time for the nowcasting scheme depends on the availability of the near real-time data and falls between 15-20 minutes for solar flares and 6 hours for CMEs. We present the modules of the FORSPEF system, their interconnection and the operational set up. The dual approach in the development of FORPSEF (i.e. forecasting and nowcasting scheme) permits the refinement of predictions upon the availability of new data that characterize changes on the Sun and the interplanetary space, while the combined usage of SF and SEP forecasting methods upgrades FORSPEF to an integrated forecasting solution. Finally, we demonstrate the validation of the modules of the FORSPEF tool using categorical scores constructed on archived data and we further discuss independent case studies. This work has been funded through the "FORSPEF: FORecasting Solar Particle Events and Flares", ESA Contract No. 4000109641/13/NL/AK and the "SPECS: Solar Particle Events foreCasting Studies" project of the National Observatory of Athens.

Building the Sun4Cast System: Improvements in Solar Power Forecasting

DOE PAGES

Haupt, Sue Ellen; Kosovic, Branko; Jensen, Tara; ...

2017-06-16

The Sun4Cast System results from a research-to-operations project built on a value chain approach, and benefiting electric utilities’ customers, society, and the environment by improving state-of-the-science solar power forecasting capabilities. As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this highly variable renewable resource. Thus, a team of researchers from public, private, and academic sectors partnered to develop and assess a new solar power forecasting system, Sun4Cast. The partnership focused on improving decision-making for utilities and independent system operators, ultimately resulting in improved grid stability and cost savings for consumers.more » The project followed a value chain approach to determine key research and technology needs to reach desired results. Sun4Cast integrates various forecasting technologies across a spectrum of temporal and spatial scales to predict surface solar irradiance. Anchoring the system is WRF-Solar, a version of the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model optimized for solar irradiance prediction. Forecasts from multiple NWP models are blended via the Dynamic Integrated Forecast (DICast) System, the basis of the system beyond about 6 h. For short-range (0-6 h) forecasts, Sun4Cast leverages several observation-based nowcasting technologies. These technologies are blended via the Nowcasting Expert System Integrator (NESI). The NESI and DICast systems are subsequently blended to produce short to mid-term irradiance forecasts for solar array locations. The irradiance forecasts are translated into power with uncertainties quantified using an analog ensemble approach, and are provided to the industry partners for real-time decision-making. The Sun4Cast system ran operationally throughout 2015 and results were assessed. As a result, this paper analyzes the collaborative design process, discusses the project results, and provides recommendations for best-practice solar forecasting.« less

Building the Sun4Cast System: Improvements in Solar Power Forecasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haupt, Sue Ellen; Kosovic, Branko; Jensen, Tara

The Sun4Cast System results from a research-to-operations project built on a value chain approach, and benefiting electric utilities’ customers, society, and the environment by improving state-of-the-science solar power forecasting capabilities. As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this highly variable renewable resource. Thus, a team of researchers from public, private, and academic sectors partnered to develop and assess a new solar power forecasting system, Sun4Cast. The partnership focused on improving decision-making for utilities and independent system operators, ultimately resulting in improved grid stability and cost savings for consumers.more » The project followed a value chain approach to determine key research and technology needs to reach desired results. Sun4Cast integrates various forecasting technologies across a spectrum of temporal and spatial scales to predict surface solar irradiance. Anchoring the system is WRF-Solar, a version of the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model optimized for solar irradiance prediction. Forecasts from multiple NWP models are blended via the Dynamic Integrated Forecast (DICast) System, the basis of the system beyond about 6 h. For short-range (0-6 h) forecasts, Sun4Cast leverages several observation-based nowcasting technologies. These technologies are blended via the Nowcasting Expert System Integrator (NESI). The NESI and DICast systems are subsequently blended to produce short to mid-term irradiance forecasts for solar array locations. The irradiance forecasts are translated into power with uncertainties quantified using an analog ensemble approach, and are provided to the industry partners for real-time decision-making. The Sun4Cast system ran operationally throughout 2015 and results were assessed. As a result, this paper analyzes the collaborative design process, discusses the project results, and provides recommendations for best-practice solar forecasting.« less

Seismic imaging of the Sun's far hemisphere and its applications in space weather forecasting

NASA Astrophysics Data System (ADS)

Lindsey, Charles; Braun, Douglas

2017-06-01

The interior of the Sun is filled acoustic waves with periods of about 5 min. These waves, called "p modes," are understood to be excited by convection in a thin layer beneath the Sun's surface. The p modes cause seismic ripples, which we call "the solar oscillations." Helioseismic observatories use Doppler observations to map these oscillations, both spatially and temporally. The p modes propagate freely throughout the solar interior, reverberating between the near and far hemispheres. They also interact strongly with active regions at the surfaces of both hemispheres, carrying the signatures of said interactions with them. Computational analysis of the solar oscillations mapped in the Sun's near hemisphere, applying basic principles of wave optics to model the implied p modes propagating through the solar interior, gives us seismic maps of large active regions in the Sun's far hemisphere. These seismic maps are useful for space weather forecasting. For the past decade, NASA's twin STEREO spacecraft have given us full coverage of the Sun's far hemisphere in electromagnetic (EUV) radiation from the far side of Earth's orbit about the Sun. We are now approaching a decade during which the STEREO spacecraft will lose their farside vantage. There will occur significant periods from thence during which electromagnetic coverage of the Sun's far hemisphere will be incomplete or nil. Solar seismology will make it possible to continue our monitor of large active regions in the Sun's far hemisphere for the needs of space weather forecasters during these otherwise blind periods.

Seismic imaging of the Sun's far hemisphere and its applications in space weather forecasting.

PubMed

Lindsey, Charles; Braun, Douglas

2017-06-01

The interior of the Sun is filled acoustic waves with periods of about 5 min. These waves, called " p modes," are understood to be excited by convection in a thin layer beneath the Sun's surface. The p modes cause seismic ripples, which we call "the solar oscillations." Helioseismic observatories use Doppler observations to map these oscillations, both spatially and temporally. The p modes propagate freely throughout the solar interior, reverberating between the near and far hemispheres. They also interact strongly with active regions at the surfaces of both hemispheres, carrying the signatures of said interactions with them. Computational analysis of the solar oscillations mapped in the Sun's near hemisphere, applying basic principles of wave optics to model the implied p modes propagating through the solar interior, gives us seismic maps of large active regions in the Sun's far hemisphere. These seismic maps are useful for space weather forecasting. For the past decade, NASA's twin STEREO spacecraft have given us full coverage of the Sun's far hemisphere in electromagnetic (EUV) radiation from the far side of Earth's orbit about the Sun. We are now approaching a decade during which the STEREO spacecraft will lose their farside vantage. There will occur significant periods from thence during which electromagnetic coverage of the Sun's far hemisphere will be incomplete or nil. Solar seismology will make it possible to continue our monitor of large active regions in the Sun's far hemisphere for the needs of space weather forecasters during these otherwise blind periods.

Predictions of Solar Cycle 24: How are We Doing?

NASA Technical Reports Server (NTRS)

Pesnell, William D.

2016-01-01

Predictions of solar activity are an essential part of our Space Weather forecast capability. Users are requiring usable predictions of an upcoming solar cycle to be delivered several years before solar minimum. A set of predictions of the amplitude of Solar Cycle 24 accumulated in 2008 ranged from zero to unprecedented levels of solar activity. The predictions formed an almost normal distribution, centered on the average amplitude of all preceding solar cycles. The average of the current compilation of 105 predictions of the annual-average sunspot number is 106 +/- 31, slightly lower than earlier compilations but still with a wide distribution. Solar Cycle 24 is on track to have a below-average amplitude, peaking at an annual sunspot number of about 80. Our need for solar activity predictions and our desire for those predictions to be made ever earlier in the preceding solar cycle will be discussed. Solar Cycle 24 has been a below-average sunspot cycle. There were peaks in the daily and monthly averaged sunspot number in the Northern Hemisphere in 2011 and in the Southern Hemisphere in 2014. With the rapid increase in solar data and capability of numerical models of the solar convection zone we are developing the ability to forecast the level of the next sunspot cycle. But predictions based only on the statistics of the sunspot number are not adequate for predicting the next solar maximum. I will describe how we did in predicting the amplitude of Solar Cycle 24 and describe how solar polar field predictions could be made more accurate in the future.

The scientific challenges to forecasting and nowcasting the solar origins of space weather (Invited)

NASA Astrophysics Data System (ADS)

Schrijver, C. J.; Title, A. M.

2013-12-01

With the full-sphere continuous coverage of the Sun achieved by combining SDO and STEREO imagery comes the realization that solar activity is a manifestation of local processes that respond to long-range if not global influences. Numerical experiments provide insights into these couplings, as well as into the intricacies of destabilizations of field emerging into pre-existing configurations and evolving within the context of their dynamic surroundings. With these capabilities grows an understanding of the difficulties in forecasting of the solar origins of space weather: we need assimilative global non-potential field models, but our observational resources are too limited to meet that need.

Integrating Solar Power onto the Electric Grid - Bridging the Gap between Atmospheric Science, Engineering and Economics

NASA Astrophysics Data System (ADS)

Ghonima, M. S.; Yang, H.; Zhong, X.; Ozge, B.; Sahu, D. K.; Kim, C. K.; Babacan, O.; Hanna, R.; Kurtz, B.; Mejia, F. A.; Nguyen, A.; Urquhart, B.; Chow, C. W.; Mathiesen, P.; Bosch, J.; Wang, G.

2015-12-01

One of the main obstacles to high penetrations of solar power is the variable nature of solar power generation. To mitigate variability, grid operators have to schedule additional reliability resources, at considerable expense, to ensure that load requirements are met by generation. Thus despite the cost of solar PV decreasing, the cost of integrating solar power will increase as penetration of solar resources onto the electric grid increases. There are three principal tools currently available to mitigate variability impacts: (i) flexible generation, (ii) storage, either virtual (demand response) or physical devices and (iii) solar forecasting. Storage devices are a powerful tool capable of ensuring smooth power output from renewable resources. However, the high cost of storage is prohibitive and markets are still being designed to leverage their full potential and mitigate their limitation (e.g. empty storage). Solar forecasting provides valuable information on the daily net load profile and upcoming ramps (increasing or decreasing solar power output) thereby providing the grid advance warning to schedule ancillary generation more accurately, or curtail solar power output. In order to develop solar forecasting as a tool that can be utilized by the grid operators we identified two focus areas: (i) develop solar forecast technology and improve solar forecast accuracy and (ii) develop forecasts that can be incorporated within existing grid planning and operation infrastructure. The first issue required atmospheric science and engineering research, while the second required detailed knowledge of energy markets, and power engineering. Motivated by this background we will emphasize area (i) in this talk and provide an overview of recent advancements in solar forecasting especially in two areas: (a) Numerical modeling tools for coastal stratocumulus to improve scheduling in the day-ahead California energy market. (b) Development of a sky imager to provide short term forecasts (0-20 min ahead) to improve optimization and control of equipment on distribution feeders with high penetration of solar. Leveraging such tools that have seen extensive use in the atmospheric sciences supports the development of accurate physics-based solar forecast models. Directions for future research are also provided.

Solar-Terrestrial Predictions: Proceedings of a workshop. Volume 2: Geomagnetic and space environment papers and ionosphere papers

NASA Astrophysics Data System (ADS)

Thompson, R. J.; Cole, D. G.; Wilkinson, P. J.; Shea, M. A.; Smart, D.

1990-11-01

The following subject areas were covered: a probability forecast for geomagnetic activity; cost recovery in solar-terrestrial predictions; magnetospheric specification and forecasting models; a geomagnetic forecast and monitoring system for power system operation; some aspects of predicting magnetospheric storms; some similarities in ionospheric disturbance characteristics in equatorial, mid-latitude, and sub-auroral regions; ionospheric support for low-VHF radio transmission; a new approach to prediction of ionospheric storms; a comparison of the total electron content of the ionosphere around L=4 at low sunspot numbers with the IRI model; the French ionospheric radio propagation predictions; behavior of the F2 layer at mid-latitudes; and the design of modern ionosondes.

New challenges in solar energy resource and forecasting in Greece

NASA Astrophysics Data System (ADS)

Kazantzidis, A.; Nikitidou, E.; Salamalikis, V.; Tzoumanikas, P.; Zagouras, A.

2018-05-01

Aerosols and clouds are the most important constituents in the atmosphere that affect the incoming solar radiation, either directly through absorbing and scattering processes or indirectly by changing the optical properties and lifetime of clouds. Under clear skies, aerosols become the dominant factor that affect the intensity of solar irradiance reaching the ground. Under cloudy skies, the high temporal and spatial variability of cloudiness is the key factor for the estimation of solar irradiance. In this study, recent research activities related to the climatology and the prediction of solar energy in Greece are presented with emphasis on new challenges in the climatology of global horizontal irradiance (GHI) and direct normal irradiance (DNI), the changes of DNI due to the decreasing aerosol optical depth and the short-term (15-240 min) forecasts of solar irradiance with the collaborative use of neural networks and satellite images.

Forecasting Solar Flares Using Magnetogram-based Predictors and Machine Learning

NASA Astrophysics Data System (ADS)

Florios, Kostas; Kontogiannis, Ioannis; Park, Sung-Hong; Guerra, Jordan A.; Benvenuto, Federico; Bloomfield, D. Shaun; Georgoulis, Manolis K.

2018-02-01

We propose a forecasting approach for solar flares based on data from Solar Cycle 24, taken by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) mission. In particular, we use the Space-weather HMI Active Region Patches (SHARP) product that facilitates cut-out magnetograms of solar active regions (AR) in the Sun in near-realtime (NRT), taken over a five-year interval (2012 - 2016). Our approach utilizes a set of thirteen predictors, which are not included in the SHARP metadata, extracted from line-of-sight and vector photospheric magnetograms. We exploit several machine learning (ML) and conventional statistics techniques to predict flares of peak magnitude {>} M1 and {>} C1 within a 24 h forecast window. The ML methods used are multi-layer perceptrons (MLP), support vector machines (SVM), and random forests (RF). We conclude that random forests could be the prediction technique of choice for our sample, with the second-best method being multi-layer perceptrons, subject to an entropy objective function. A Monte Carlo simulation showed that the best-performing method gives accuracy ACC=0.93(0.00), true skill statistic TSS=0.74(0.02), and Heidke skill score HSS=0.49(0.01) for {>} M1 flare prediction with probability threshold 15% and ACC=0.84(0.00), TSS=0.60(0.01), and HSS=0.59(0.01) for {>} C1 flare prediction with probability threshold 35%.

Seismic Forecasting of Solar Activity

NASA Technical Reports Server (NTRS)

Braun, Douglas; Lindsey, Charles

2001-01-01

We have developed and improved helioseismic imaging techniques of the far-side of the Sun as part of a synoptic monitor of solar activity. In collaboration with the MIDI team at Stanford University we are routinely applying our analysis to images within 24 hours of their acquisition by SOHO. For the first time, real-time seismic maps of large active regions on the Sun's far surface are publicly available. The synoptic images show examples of active regions persisting for one or more solar rotations, as well as those initially detected forming on the solar far side. Until recently, imaging the far surface of the Sun has been essentially blind to active regions more than about 50 degrees from the antipode of disk center. In a paper recently accepted for publication, we have demonstrated how acoustic travel-time perturbations may be mapped over the entire hemisphere of the Sun facing away from the Earth, including the polar regions. In addition to offering significant improvements to ongoing space weather forecasting efforts, the procedure offers the possibility of local seismic monitoring of both the temporal and spatial variations in the acoustic properties of the Sun over the entire far surface.

A Forecast of Reduced Solar Activity and Its Implications for NASA

NASA Technical Reports Server (NTRS)

Schatten, Kenneth; Franz, Heather

2005-01-01

The "Solar Dynamo" method of solar activity forecasting is reviewed. Known generically as a 'precursor" method, insofar as it uses observations which precede solar activity generation, this method now uses the Solar Dynamo Amplitude (SODA) Index to estimate future long-term solar activity. The peak amplitude of the next solar cycle (#24), is estimated at roughly 124 in terms of smoothed F10.7 Radio Flux and 74 in terms of the older, more traditional smoothed international or Zurich Sunspot number (Ri or Rz). These values are significantly smaller than the amplitudes of recent solar cycles. Levels of activity stay large for about four years near the peak in smoothed activity, which is estimated to occur near the 2012 timeflame. Confidence is added to the prediction of low activity by numerous examinations of the Sun s weakened polar field. Direct measurements are obtained by the Mount Wilson Solar Observatory and the Wilcox Solar Observatory. Further support is obtained by examining the Sun s polar faculae (bright features), the shape of coronal soft X-ray "holes," and the shape of the "source surface" - a calculated coronal feature which maps the large scale structure of the Sun s field. These features do not show the characteristics of well-formed polar coronal holes associated with typical solar minima. They show stunted polar field levels, which are thought to result in stunted levels of solar activity during solar cycle #24. The reduced levels of solar activity would have concomitant effects upon the space environment in which satellites orbit. In particular, the largest influences would affect orbit determination of satellites in LEO (Low Earth Orbit), based upon the altered thermospheric and exospheric densities. A decrease in solar activity would result in smaller satellite decay rates, as well as fewer large solar events that can destroy satellite electronic functions. Other effects of reduced solar activity upon the space environment include enhanced galactic cosmic rays and more space debris at low altitudes (from the decay of old satellite parts, etc.). The reasons are well known: namely, solar activity serves to sweep the inner heliosphere of galactic cosmic rays, and lower exospheric densities result in decreased drag on LEO debris, allowing longer lifetimes.

Transitioning the Rice Realtime Forecast Models to DSCOVR

NASA Astrophysics Data System (ADS)

Bala, R.; Reiff, P. H.

2016-12-01

The Rice realtime forecast models of global magnetospheric indices Kp, Dst and AE have been actively running at mms.rice.edu/realtime/forecast.html for nearly a decade now. These neural network models were trained using the ACE archival solar wind data while the near-realtime forecasts are provided using instantaneous upwind solar wind data stream measured at the L1 point through ACE. Additionally, the webpage also provide status of the current space weather condition as an additional resource, updating every ten minutes. Furthermore, the subscribers of our space weather alert system, called `spacalrt', have been receiving email notices based on predefined thresholds. One of the gaps that is currently seen in the Rice neural network models lies in the density dependent models using variants of the solar wind pressure. The anomalous behavior in reporting densities in ACE has been a common issue for some time now. Often such behavior is observed when the solar energetic particle that are associated with solar flares or CMEs are Earth directed. Therefore, it is understood that the subsequent measures of the density reported by ACE will be either very low or, at a minimum, contaminated. Under these circumstances, the density-based Rice models typically underpredict. However, the newly launched DSCOVR satellite will help enhance our prediction models with high-quality data; it has real time space weather data available through the NOAA's Space Weather Prediction Center as of July, 2016. We are in the process of transitioning our forecast operations to include data from DSCOVR while running the original ACE data stream in parallel until it lasts. This paper will compare and contrast the forecasted values from the two satellites. Finally, we will discuss our efforts in providing the forecast products for the Rice space weather website that will be a part of the book on "Machine Learning Techniques for Space Weather" to be published by Elsiever.

Close-up View of an Active Region of the Sun, March 23, 2007 Anaglyph

NASA Image and Video Library

2007-04-27

NASA Solar TErrestrial RElations Observatory satellites have provided the first 3-dimensional images of the Sun. This view will aid scientists ability to understand solar physics to improve space weather forecasting. 3D glasses are necessary.

Two-Step Forecast of Geomagnetic Storm Using Coronal Mass Ejection and Solar Wind Condition

NASA Technical Reports Server (NTRS)

Kim, R.-S.; Moon, Y.-J.; Gopalswamy, N.; Park, Y.-D.; Kim, Y.-H.

2014-01-01

To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind criteria derived in this study (Bz = -5 nT or Ey = 3 mV/m for t = 2 h for moderate storms with minimum Dst less than -50 nT) (i.e. Magnetic Field Magnitude, B (sub z) less than or equal to -5 nanoTeslas or duskward Electrical Field, E (sub y) greater than or equal to 3 millivolts per meter for time greater than or equal to 2 hours for moderate storms with Minimum Disturbance Storm Time, Dst less than -50 nanoTeslas) and a Dst model developed by Temerin and Li (2002, 2006) (TL [i.e. Temerin Li] model). Using 55 CME-Dst pairs during 1997 to 2003, our solar wind criteria produce slightly better forecasts for 31 storm events (90 percent) than the forecasts based on the TL model (87 percent). However, the latter produces better forecasts for 24 nonstorm events (88 percent), while the former correctly forecasts only 71 percent of them. We then performed the two-step forecast. The results are as follows: (i) for 15 events that are incorrectly forecasted using CME parameters, 12 cases (80 percent) can be properly predicted based on solar wind conditions; (ii) if we forecast a storm when both CME and solar wind conditions are satisfied (n, i.e. cap operator - the intersection set that is comprised of all the elements that are common to both), the critical success index becomes higher than that from the forecast using CME parameters alone, however, only 25 storm events (81 percent) are correctly forecasted; and (iii) if we forecast a storm when either set of these conditions is satisfied (?, i.e. cup operator - the union set that is comprised of all the elements of either or both), all geomagnetic storms are correctly forecasted.

The Second NWRA Flare-Forecasting Comparison Workshop: Methods Compared and Methodology

NASA Astrophysics Data System (ADS)

Leka, K. D.; Barnes, G.; the Flare Forecasting Comparison Group

2013-07-01

The Second NWRA Workshop to compare methods of solar flare forecasting was held 2-4 April 2013 in Boulder, CO. This is a follow-on to the First NWRA Workshop on Flare Forecasting Comparison, also known as the ``All-Clear Forecasting Workshop'', held in 2009 jointly with NASA/SRAG and NOAA/SWPC. For this most recent workshop, many researchers who are active in the field participated, and diverse methods were represented in terms of both the characterization of the Sun and the statistical approaches used to create a forecast. A standard dataset was created for this investigation, using data from the Solar Dynamics Observatory/ Helioseismic and Magnetic Imager (SDO/HMI) vector magnetic field HARP series. For each HARP on each day, 6 hours of data were used, allowing for nominal time-series analysis to be included in the forecasts. We present here a summary of the forecasting methods that participated and the standardized dataset that was used. Funding for the workshop and the data analysis was provided by NASA/Living with a Star contract NNH09CE72C and NASA/Guest Investigator contract NNH12CG10C.

3D cloud detection and tracking system for solar forecast using multiple sky imagers

DOE PAGES

Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...

2015-06-23

We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

Recent Trends in Variable Generation Forecasting and Its Value to the Power System

DOE PAGES

Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; ...

2014-12-23

We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value ofmore » adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.« less

Have We Entered a 21st Century Prolonged Minimum of Solar Activity? Updated Implications of a 1987 Prediction

NASA Astrophysics Data System (ADS)

Shirley, James H.

2009-05-01

Fairbridge and Shirley (1987) predicted that a new prolonged minimum of solar activity would be underway by the year 2013 (Solar Physics 110, 191). While it is much too early to tell if this prediction will be fully realized, recent observations document a striking reduction in the Sun's general level of activity. While other forecasts of reduced future activity levels on decadal time scales have appeared, the Fairbridge-Shirley (FS) prediction is unique in pinpointing the current epoch. We are unaware of any forecast method that shows a better correspondence with the actual behavior of the Sun to this point. The FS prediction was based on the present-day recurrence of two physical indicators that were correlated in time with the occurrence of the Wolf, Sporer, and Maunder Minima. The amplitude of the inertial revolution of the axis of symmetry of the Sun's orbital motion about the solar system barycenter, and the direction in space of that axis, each bear a relationship to the occurrence of the prolonged minima of the historic record. The FS prediction appeared before the importance of solar meridional flows was generally appreciated, and before the existence and role of the tachocline was suspected. We will update and restate some of the physical implications of the FS results, along with those of some more recent investigations, particularly with reference to orbit-spin coupling hypotheses (Shirley, 2006: M.N.R.A.S. 368, 280). New investigations combining and integrating modern dynamo models with physical solutions describing key aspects of the variability of the solar motion may lead to significant advances in our ability to forecast future changes in the Sun. Acknowledgement: This work was supported by the resources of the author. No part of this work was performed at the Jet Propulsion Laboratory under a contract from NASA.

Ground-based Observations of Large Solar Flares Precursors

NASA Astrophysics Data System (ADS)

Sheyner, Olga; Smirnova, Anna; Snegirev, Sergey

2010-05-01

The importance problem of Solar-terrestrial physics is regular forecasting of solar activity phenomena, which negatively influence the human's health, operating safety, communication, radar sets and others. The opportunity of development of short-term forecasting technique of geoeffective solar flares is presented in this study. This technique is based on the effect of growth of pulsations of horizontal component of geomagnetic field before the solar proton flares. The long-period (30-60 minutes) pulsations of H-component of geomagnetic field are detected for the events of different intensity on March 22, 1991, November 4, 2001, and November 17, 2001 using the method of wavelet-analysis. Amplitudes of fluctuations of horizontal component of geomagnetic field with the 30-60 minute's periods grow at the most of tested stations during 0.5-3.5 days before the solar flares. The particularities of spectral component are studied for the stations situated on different latitudes. The assumptions about the reason of such precursors-fluctuations appearance are made.

Solar EUV irradiance for space weather applications

NASA Astrophysics Data System (ADS)

Viereck, R. A.

2015-12-01

Solar EUV irradiance is an important driver of space weather models. Large changes in EUV and x-ray irradiances create large variability in the ionosphere and thermosphere. Proxies such as the F10.7 cm radio flux, have provided reasonable estimates of the EUV flux but as the space weather models become more accurate and the demands of the customers become more stringent, proxies are no longer adequate. Furthermore, proxies are often provided only on a daily basis and shorter time scales are becoming important. Also, there is a growing need for multi-day forecasts of solar EUV irradiance to drive space weather forecast models. In this presentation we will describe the needs and requirements for solar EUV irradiance information from the space weather modeler's perspective. We will then translate these requirements into solar observational requirements such as spectral resolution and irradiance accuracy. We will also describe the activities at NOAA to provide long-term solar EUV irradiance observations and derived products that are needed for real-time space weather modeling.

Customization of Discriminant Function Analysis for Prediction of Solar Flares

DTIC Science & Technology

2005-03-01

lives such as telecommunication, commercial airlines, electrical power , wireless services, and terrestrial weather tracking and forecasting...the 1800’s can wreak havoc on today’s power , fuel, and telecommunication lines and finds its origin in solar activity. Enormous amounts of solar...inducing potential differences across large areas of the surface. Earth-bound power , fuel, and telecommunication lines grounded to the Earth provide an

Forecasting Wind and Solar Generation: Improving System Operations, Greening the Grid (Spanish Version)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tian, Tian; Chernyakhovskiy, Ilya; Brancucci Martinez-Anido, Carlo

This document is the Spanish version of 'Greening the Grid- Forecasting Wind and Solar Generation Improving System Operations'. It discusses improving system operations with forecasting with and solar generation. By integrating variable renewable energy (VRE) forecasts into system operations, power system operators can anticipate up- and down-ramps in VRE generation in order to cost-effectively balance load and generation in intra-day and day-ahead scheduling. This leads to reduced fuel costs, improved system reliability, and maximum use of renewable resources.

How MAG4 Improves Space Weather Forecasting

NASA Technical Reports Server (NTRS)

Falconer, David; Khazanov, Igor; Barghouty, Nasser

2013-01-01

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.

Forecasting of global solar radiation using anfis and armax techniques

NASA Astrophysics Data System (ADS)

Muhammad, Auwal; Gaya, M. S.; Aliyu, Rakiya; Aliyu Abdulkadir, Rabi'u.; Dauda Umar, Ibrahim; Aminu Yusuf, Lukuman; Umar Ali, Mudassir; Khairi, M. T. M.

2018-01-01

Procurement of measuring device, maintenance cost coupled with calibration of the instrument contributed to the difficulty in forecasting of global solar radiation in underdeveloped countries. Most of the available regressional and mathematical models do not capture well the behavior of the global solar radiation. This paper presents the comparison of Adaptive Neuro Fuzzy Inference System (ANFIS) and Autoregressive Moving Average with eXogenous term (ARMAX) in forecasting global solar radiation. Full-Scale (experimental) data of Nigerian metrological agency, Sultan Abubakar III international airport Sokoto was used to validate the models. The simulation results demonstrated that the ANFIS model having achieved MAPE of 5.34% outperformed the ARMAX model. The ANFIS could be a valuable tool for forecasting the global solar radiation.

Forecasts and Warnings of Extreme Solar Storms at the Sun

NASA Astrophysics Data System (ADS)

Lundstedt, H.

2015-12-01

The most pressing space weather forecasts and warnings are those of the most intense solar flares and coronal mass ejections. However, in trying to develop these forecasts and warnings, we are confronted to many fundamental questions. Some of those are: How to define an observable measure for an extreme solar storm? How extreme can a solar storm become and how long is the build up time? How to make forecasts and warnings? Many have contributed to clarifying these general questions. In his presentation we will describe our latest results on the topological complexity of magnetic fields and the use of SDO SHARP parameters. The complexity concept will then be used to discuss the second question. Finally we will describe probability estimates of extreme solar storms.

Impacts of Short-Term Solar Power Forecasts in System Operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ibanez, Eduardo; Krad, Ibrahim; Hodge, Bri-Mathias

2016-05-05

Solar generation is experiencing an exponential growth in power systems worldwide and, along with wind power, is posing new challenges to power system operations. Those challenges are characterized by an increase of system variability and uncertainty across many time scales: from days, down to hours, minutes, and seconds. Much of the research in the area has focused on the effect of solar forecasting across hours or days. This paper presents a methodology to capture the effect of short-term forecasting strategies and analyzes the economic and reliability implications of utilizing a simple, yet effective forecasting method for solar PV in intra-daymore » operations.« less

Intra-Hour Dispatch and Automatic Generator Control Demonstration with Solar Forecasting - Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coimbra, Carlos F. M.

2016-02-25

In this project we address multiple resource integration challenges associated with increasing levels of solar penetration that arise from the variability and uncertainty in solar irradiance. We will model the SMUD service region as its own balancing region, and develop an integrated, real-time operational tool that takes solar-load forecast uncertainties into consideration and commits optimal energy resources and reserves for intra-hour and intra-day decisions. The primary objectives of this effort are to reduce power system operation cost by committing appropriate amount of energy resources and reserves, as well as to provide operators a prediction of the generation fleet’s behavior inmore » real time for realistic PV penetration scenarios. The proposed methodology includes the following steps: clustering analysis on the expected solar variability per region for the SMUD system, Day-ahead (DA) and real-time (RT) load forecasts for the entire service areas, 1-year of intra-hour CPR forecasts for cluster centers, 1-year of smart re-forecasting CPR forecasts in real-time for determination of irreducible errors, and uncertainty quantification for integrated solar-load for both distributed and central stations (selected locations within service region) PV generation.« less

A stochastic post-processing method for solar irradiance forecasts derived from NWPs models

NASA Astrophysics Data System (ADS)

Lara-Fanego, V.; Pozo-Vazquez, D.; Ruiz-Arias, J. A.; Santos-Alamillos, F. J.; Tovar-Pescador, J.

2010-09-01

Solar irradiance forecast is an important area of research for the future of the solar-based renewable energy systems. Numerical Weather Prediction models (NWPs) have proved to be a valuable tool for solar irradiance forecasting with lead time up to a few days. Nevertheless, these models show low skill in forecasting the solar irradiance under cloudy conditions. Additionally, climatic (averaged over seasons) aerosol loading are usually considered in these models, leading to considerable errors for the Direct Normal Irradiance (DNI) forecasts during high aerosols load conditions. In this work we propose a post-processing method for the Global Irradiance (GHI) and DNI forecasts derived from NWPs. Particularly, the methods is based on the use of Autoregressive Moving Average with External Explanatory Variables (ARMAX) stochastic models. These models are applied to the residuals of the NWPs forecasts and uses as external variables the measured cloud fraction and aerosol loading of the day previous to the forecast. The method is evaluated for a set one-moth length three-days-ahead forecast of the GHI and DNI, obtained based on the WRF mesoscale atmospheric model, for several locations in Andalusia (Southern Spain). The Cloud fraction is derived from MSG satellite estimates and the aerosol loading from the MODIS platform estimates. Both sources of information are readily available at the time of the forecast. Results showed a considerable improvement of the forecasting skill of the WRF model using the proposed post-processing method. Particularly, relative improvement (in terms of the RMSE) for the DNI during summer is about 20%. A similar value is obtained for the GHI during the winter.

The Origin of the "Seasons" in Space Weather

NASA Astrophysics Data System (ADS)

Dikpati, Mausumi; Cally, Paul S.; McIntosh, Scott W.; Heifetz, Eyal

2017-11-01

Powerful `space weather' events caused by solar activity pose serious risks to human health, safety, economic activity and national security. Spikes in deaths due to heart attacks, strokes and other diseases occurred during prolonged power outages. Currently it is hard to prepare for and mitigate the impact of space weather because it is impossible to forecast the solar eruptions that can cause these terrestrial events until they are seen on the Sun. However, as recently reported in Nature, eruptive events like coronal mass ejections and solar flares, are organized into quasi-periodic "seasons", which include enhanced bursts of eruptions for several months, followed by quiet periods. We explored the dynamics of sunspot-producing magnetic fields and discovered for the first time that bursty and quiet seasons, manifested in surface magnetic structures, can be caused by quasi-periodic energy-exchange among magnetic fields, Rossby waves and differential rotation of the solar interior shear-layer (called tachocline). Our results for the first time provide a quantitative physical mechanism for forecasting the strength and duration of bursty seasons several months in advance, which can greatly enhance our ability to warn humans about dangerous solar bursts and prevent damage to satellites and power stations from space weather events.

The Origin of the "Seasons" in Space Weather.

PubMed

Dikpati, Mausumi; Cally, Paul S; McIntosh, Scott W; Heifetz, Eyal

2017-11-07

Powerful 'space weather' events caused by solar activity pose serious risks to human health, safety, economic activity and national security. Spikes in deaths due to heart attacks, strokes and other diseases occurred during prolonged power outages. Currently it is hard to prepare for and mitigate the impact of space weather because it is impossible to forecast the solar eruptions that can cause these terrestrial events until they are seen on the Sun. However, as recently reported in Nature, eruptive events like coronal mass ejections and solar flares, are organized into quasi-periodic "seasons", which include enhanced bursts of eruptions for several months, followed by quiet periods. We explored the dynamics of sunspot-producing magnetic fields and discovered for the first time that bursty and quiet seasons, manifested in surface magnetic structures, can be caused by quasi-periodic energy-exchange among magnetic fields, Rossby waves and differential rotation of the solar interior shear-layer (called tachocline). Our results for the first time provide a quantitative physical mechanism for forecasting the strength and duration of bursty seasons several months in advance, which can greatly enhance our ability to warn humans about dangerous solar bursts and prevent damage to satellites and power stations from space weather events.

Assessment of Predictive Capabilities of L1 Orbiters using Realtime Solar Wind Data

NASA Astrophysics Data System (ADS)

Holmes, J.; Kasper, J. C.; Welling, D. T.

2017-12-01

Realtime measurements of solar wind conditions at L1 point allow us to predict geomagnetic activity at Earth up to an hour in advance. These predictions are quantified in the form of geomagnetic indices such as Kp and Ap, allowing for a concise, standardized prediction and measurement system. For years, the Space Weather Prediction Center used ACE realtime solar wind data to develop its one and four-hour Kp forecasts, but has in the past year switched to using DSCOVR data as its source. In this study, the performance of both orbiters in predicting Kp over the course of one month was assessed in an attempt to determine whether or not switching to DSCOVR data has resulted in improved forecasts. The period of study was chosen to encompass a time when the satellites were close to each other, and when moderate to high activity was observed. Kp predictions were made using the Geospace Model, part of the Space Weather Modeling Framework, to simulate conditions based on observed solar wind parameters. The performance of each satellite was assessed by comparing the model output to observed data.

Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoff, Thomas Hoff; Kankiewicz, Adam

Four major research objectives were completed over the course of this study. Three of the objectives were to evaluate three, new, state-of-the-art solar irradiance forecasting models. The fourth objective was to improve the California Independent System Operator’s (ISO) load forecasts by integrating behind-the-meter (BTM) PV forecasts. The three, new, state-of-the-art solar irradiance forecasting models included: the infrared (IR) satellite-based cloud motion vector (CMV) model; the WRF-SolarCA model and variants; and the Optimized Deep Machine Learning (ODML)-training model. The first two forecasting models targeted known weaknesses in current operational solar forecasts. They were benchmarked against existing operational numerical weather prediction (NWP)more » forecasts, visible satellite CMV forecasts, and measured PV plant power production. IR CMV, WRF-SolarCA, and ODML-training forecasting models all improved the forecast to a significant degree. Improvements varied depending on time of day, cloudiness index, and geographic location. The fourth objective was to demonstrate that the California ISO’s load forecasts could be improved by integrating BTM PV forecasts. This objective represented the project’s most exciting and applicable gains. Operational BTM forecasts consisting of 200,000+ individual rooftop PV forecasts were delivered into the California ISO’s real-time automated load forecasting (ALFS) environment. They were then evaluated side-by-side with operational load forecasts with no BTM-treatment. Overall, ALFS-BTM day-ahead (DA) forecasts performed better than baseline ALFS forecasts when compared to actual load data. Specifically, ALFS-BTM DA forecasts were observed to have the largest reduction of error during the afternoon on cloudy days. Shorter term 30 minute-ahead ALFS-BTM forecasts were shown to have less error under all sky conditions, especially during the morning time periods when traditional load forecasts often experience their largest uncertainties. This work culminated in a GO decision being made by the California ISO to include zonal BTM forecasts into its operational load forecasting system. The California ISO’s Manager of Short Term Forecasting, Jim Blatchford, summarized the research performed in this project with the following quote: “The behind-the-meter (BTM) California ISO region forecasting research performed by Clean Power Research and sponsored by the Department of Energy’s SUNRISE program was an opportunity to verify value and demonstrate improved load forecast capability. In 2016, the California ISO will be incorporating the BTM forecast into the Hour Ahead and Day Ahead load models to look for improvements in the overall load forecast accuracy as BTM PV capacity continues to grow.”« less

Predictability of Solar Radiation for Photovoltaics systems over Europe: from short-term to seasonal time-scales

NASA Astrophysics Data System (ADS)

De Felice, Matteo; Petitta, Marcello; Ruti, Paolo

2014-05-01

Photovoltaic diffusion is steadily growing on Europe, passing from a capacity of almost 14 GWp in 2011 to 21.5 GWp in 2012 [1]. Having accurate forecast is needed for planning and operational purposes, with the possibility to model and predict solar variability at different time-scales. This study examines the predictability of daily surface solar radiation comparing ECMWF operational forecasts with CM-SAF satellite measurements on the Meteosat (MSG) full disk domain. Operational forecasts used are the IFS system up to 10 days and the System4 seasonal forecast up to three months. Forecast are analysed considering average and variance of errors, showing error maps and average on specific domains with respect to prediction lead times. In all the cases, forecasts are compared with predictions obtained using persistence and state-of-art time-series models. We can observe a wide range of errors, with the performance of forecasts dramatically affected by orography and season. Lower errors are on southern Italy and Spain, with errors on some areas consistently under 10% up to ten days during summer (JJA). Finally, we conclude the study with some insight on how to "translate" the error on solar radiation to error on solar power production using available production data from solar power plants. [1] EurObserver, "Baromètre Photovoltaïque, Le journal des énergies renouvables, April 2012."

Forecasting Geomagnetic Activity Using Kalman Filters

NASA Astrophysics Data System (ADS)

Veeramani, T.; Sharma, A.

2006-05-01

The coupling of energy from the solar wind to the magnetosphere leads to the geomagnetic activity in the form of storms and substorms and are characterized by indices such as AL, Dst and Kp. The geomagnetic activity has been predicted near-real time using local linear filter models of the system dynamics wherein the time series of the input solar wind and the output magnetospheric response were used to reconstruct the phase space of the system by a time-delay embedding technique. Recently, the radiation belt dynamics have been studied using a adaptive linear state space model [Rigler et al. 2004]. This was achieved by assuming a linear autoregressive equation for the underlying process and an adaptive identification of the model parameters using a Kalman filter approach. We use such a model for predicting the geomagnetic activity. In the case of substorms, the Bargatze et al [1985] data set yields persistence like behaviour when a time resolution of 2.5 minutes was used to test the model for the prediction of the AL index. Unlike the local linear filters, which are driven by the solar wind input without feedback from the observations, the Kalman filter makes use of the observations as and when available to optimally update the model parameters. The update procedure requires the prediction intervals to be long enough so that the forecasts can be used in practice. The time resolution of the data suitable for such forecasting is studied by taking averages over different durations.

Forecasting Safe or Dangerous Space Weather from HMI Magnetograms

NASA Technical Reports Server (NTRS)

Falconer, David; Barghouty, Abdulnasser F.; Khazanov, Igor; Moore, Ron

2011-01-01

We have developed a space-weather forecasting tool using an active-region free-energy proxy that was measured from MDI line-of-sight magnetograms. To develop this forecasting tool (Falconer et al 2011, Space Weather Journal, in press), we used a database of 40,000 MDI magnetograms of 1300 active regions observed by MDI during the previous solar cycle (cycle 23). From each magnetogram we measured our free-energy proxy and for each active region we determined its history of major flare, CME and Solar Particle Event (SPE) production. This database determines from the value of an active region s free-energy proxy the active region s expected rate of production of 1) major flares, 2) CMEs, 3) fast CMEs, and 4) SPEs during the next few days. This tool was delivered to NASA/SRAG in 2010. With MDI observations ending, we have to be able to use HMI magnetograms instead of MDI magnetograms. One of the difficulties is that the measured value of the free-energy proxy is sensitive to the spatial resolution of the measured magnetogram: the 0.5 /pixel resolution of HMI gives a different value for the free-energy proxy than the 2 /pixels resolution of MDI. To use our MDI-database forecasting curves until a comparably large HMI database is accumulated, we smooth HMI line-of-sight magnetograms to MDI resolution, so that we can use HMI to find the value of the free-energy proxy that MDI would have measured, and then use the forecasting curves given by the MDI database. The new version for use with HMI magnetograms was delivered to NASA/SRAG (March 2011). It can also use GONG magnetograms, as a backup.

A Solar Time-Based Analog Ensemble Method for Regional Solar Power Forecasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, Brian S; Zhang, Xinmin; Li, Yuan

This paper presents a new analog ensemble method for day-ahead regional photovoltaic (PV) power forecasting with hourly resolution. By utilizing open weather forecast and power measurement data, this prediction method is processed within a set of historical data with similar meteorological data (temperature and irradiance), and astronomical date (solar time and earth declination angle). Further, clustering and blending strategies are applied to improve its accuracy in regional PV forecasting. The robustness of the proposed method is demonstrated with three different numerical weather prediction models, the North American Mesoscale Forecast System, the Global Forecast System, and the Short-Range Ensemble Forecast, formore » both region level and single site level PV forecasts. Using real measured data, the new forecasting approach is applied to the load zone in Southeastern Massachusetts as a case study. The normalized root mean square error (NRMSE) has been reduced by 13.80%-61.21% when compared with three tested baselines.« less

Increasing the temporal resolution of direct normal solar irradiance forecasted series

NASA Astrophysics Data System (ADS)

Fernández-Peruchena, Carlos M.; Gastón, Martin; Schroedter-Homscheidt, Marion; Marco, Isabel Martínez; Casado-Rubio, José L.; García-Moya, José Antonio

2017-06-01

A detailed knowledge of the solar resource is a critical point in the design and control of Concentrating Solar Power (CSP) plants. In particular, accurate forecasting of solar irradiance is essential for the efficient operation of solar thermal power plants, the management of energy markets, and the widespread implementation of this technology. Numerical weather prediction (NWP) models are commonly used for solar radiation forecasting. In the ECMWF deterministic forecasting system, all forecast parameters are commercially available worldwide at 3-hourly intervals. Unfortunately, as Direct Normal solar Irradiance (DNI) exhibits a great variability due to the dynamic effects of passing clouds, 3-h time resolution is insufficient for accurate simulations of CSP plants due to their nonlinear response to DNI, governed by various thermal inertias due to their complex response characteristics. DNI series of hourly or sub-hourly frequency resolution are normally used for an accurate modeling and analysis of transient processes in CSP technologies. In this context, the objective of this study is to propose a methodology for generating synthetic DNI time series at 1-h (or higher) temporal resolution from 3-h DNI series. The methodology is based upon patterns as being defined with help of the clear-sky envelope approach together with a forecast of maximum DNI value, and it has been validated with high quality measured DNI data.

Advancing solar energy forecasting through the underlying physics

NASA Astrophysics Data System (ADS)

Yang, H.; Ghonima, M. S.; Zhong, X.; Ozge, B.; Kurtz, B.; Wu, E.; Mejia, F. A.; Zamora, M.; Wang, G.; Clemesha, R.; Norris, J. R.; Heus, T.; Kleissl, J. P.

2017-12-01

As solar power comprises an increasingly large portion of the energy generation mix, the ability to accurately forecast solar photovoltaic generation becomes increasingly important. Due to the variability of solar power caused by cloud cover, knowledge of both the magnitude and timing of expected solar power production ahead of time facilitates the integration of solar power onto the electric grid by reducing electricity generation from traditional ancillary generators such as gas and oil power plants, as well as decreasing the ramping of all generators, reducing start and shutdown costs, and minimizing solar power curtailment, thereby providing annual economic value. The time scales involved in both the energy markets and solar variability range from intra-hour to several days ahead. This wide range of time horizons led to the development of a multitude of techniques, with each offering unique advantages in specific applications. For example, sky imagery provides site-specific forecasts on the minute-scale. Statistical techniques including machine learning algorithms are commonly used in the intra-day forecast horizon for regional applications, while numerical weather prediction models can provide mesoscale forecasts on both the intra-day and days-ahead time scale. This talk will provide an overview of the challenges unique to each technique and highlight the advances in their ongoing development which come alongside advances in the fundamental physics underneath.

Probabilistic Solar Wind Forecasting Using Large Ensembles of Near-Sun Conditions With a Simple One-Dimensional "Upwind" Scheme

NASA Astrophysics Data System (ADS)

Owens, Mathew J.; Riley, Pete

2017-11-01

Long lead-time space-weather forecasting requires accurate prediction of the near-Earth solar wind. The current state of the art uses a coronal model to extrapolate the observed photospheric magnetic field to the upper corona, where it is related to solar wind speed through empirical relations. These near-Sun solar wind and magnetic field conditions provide the inner boundary condition to three-dimensional numerical magnetohydrodynamic (MHD) models of the heliosphere out to 1 AU. This physics-based approach can capture dynamic processes within the solar wind, which affect the resulting conditions in near-Earth space. However, this deterministic approach lacks a quantification of forecast uncertainty. Here we describe a complementary method to exploit the near-Sun solar wind information produced by coronal models and provide a quantitative estimate of forecast uncertainty. By sampling the near-Sun solar wind speed at a range of latitudes about the sub-Earth point, we produce a large ensemble (N = 576) of time series at the base of the Sun-Earth line. Propagating these conditions to Earth by a three-dimensional MHD model would be computationally prohibitive; thus, a computationally efficient one-dimensional "upwind" scheme is used. The variance in the resulting near-Earth solar wind speed ensemble is shown to provide an accurate measure of the forecast uncertainty. Applying this technique over 1996-2016, the upwind ensemble is found to provide a more "actionable" forecast than a single deterministic forecast; potential economic value is increased for all operational scenarios, but particularly when false alarms are important (i.e., where the cost of taking mitigating action is relatively large).

Probabilistic Solar Wind Forecasting Using Large Ensembles of Near-Sun Conditions With a Simple One-Dimensional "Upwind" Scheme.

PubMed

Owens, Mathew J; Riley, Pete

2017-11-01

Long lead-time space-weather forecasting requires accurate prediction of the near-Earth solar wind. The current state of the art uses a coronal model to extrapolate the observed photospheric magnetic field to the upper corona, where it is related to solar wind speed through empirical relations. These near-Sun solar wind and magnetic field conditions provide the inner boundary condition to three-dimensional numerical magnetohydrodynamic (MHD) models of the heliosphere out to 1 AU. This physics-based approach can capture dynamic processes within the solar wind, which affect the resulting conditions in near-Earth space. However, this deterministic approach lacks a quantification of forecast uncertainty. Here we describe a complementary method to exploit the near-Sun solar wind information produced by coronal models and provide a quantitative estimate of forecast uncertainty. By sampling the near-Sun solar wind speed at a range of latitudes about the sub-Earth point, we produce a large ensemble (N = 576) of time series at the base of the Sun-Earth line. Propagating these conditions to Earth by a three-dimensional MHD model would be computationally prohibitive; thus, a computationally efficient one-dimensional "upwind" scheme is used. The variance in the resulting near-Earth solar wind speed ensemble is shown to provide an accurate measure of the forecast uncertainty. Applying this technique over 1996-2016, the upwind ensemble is found to provide a more "actionable" forecast than a single deterministic forecast; potential economic value is increased for all operational scenarios, but particularly when false alarms are important (i.e., where the cost of taking mitigating action is relatively large).

Probabilistic Solar Wind Forecasting Using Large Ensembles of Near‐Sun Conditions With a Simple One‐Dimensional “Upwind” Scheme

PubMed Central

Riley, Pete

2017-01-01

Abstract Long lead‐time space‐weather forecasting requires accurate prediction of the near‐Earth solar wind. The current state of the art uses a coronal model to extrapolate the observed photospheric magnetic field to the upper corona, where it is related to solar wind speed through empirical relations. These near‐Sun solar wind and magnetic field conditions provide the inner boundary condition to three‐dimensional numerical magnetohydrodynamic (MHD) models of the heliosphere out to 1 AU. This physics‐based approach can capture dynamic processes within the solar wind, which affect the resulting conditions in near‐Earth space. However, this deterministic approach lacks a quantification of forecast uncertainty. Here we describe a complementary method to exploit the near‐Sun solar wind information produced by coronal models and provide a quantitative estimate of forecast uncertainty. By sampling the near‐Sun solar wind speed at a range of latitudes about the sub‐Earth point, we produce a large ensemble (N = 576) of time series at the base of the Sun‐Earth line. Propagating these conditions to Earth by a three‐dimensional MHD model would be computationally prohibitive; thus, a computationally efficient one‐dimensional “upwind” scheme is used. The variance in the resulting near‐Earth solar wind speed ensemble is shown to provide an accurate measure of the forecast uncertainty. Applying this technique over 1996–2016, the upwind ensemble is found to provide a more “actionable” forecast than a single deterministic forecast; potential economic value is increased for all operational scenarios, but particularly when false alarms are important (i.e., where the cost of taking mitigating action is relatively large). PMID:29398982

Near-term Forecasting of Solar Total and Direct Irradiance for Solar Energy Applications

NASA Astrophysics Data System (ADS)

Long, C. N.; Riihimaki, L. D.; Berg, L. K.

2012-12-01

Integration of solar renewable energy into the power grid, like wind energy, is hindered by the variable nature of the solar resource. One challenge of the integration problem for shorter time periods is the phenomenon of "ramping events" where the electrical output of the solar power system increases or decreases significantly and rapidly over periods of minutes or less. Advance warning, of even just a few minutes, allows power system operators to compensate for the ramping. However, the ability for short-term prediction on such local "point" scales is beyond the abilities of typical model-based weather forecasting. Use of surface-based solar radiation measurements has been recognized as a likely solution for providing input for near-term (5 to 30 minute) forecasts of solar energy availability and variability. However, it must be noted that while fixed-orientation photovoltaic panel systems use the total (global) downwelling solar radiation, tracking photovoltaic and solar concentrator systems use only the direct normal component of the solar radiation. Thus even accurate near-term forecasts of total solar radiation will under many circumstances include inherent inaccuracies with respect to tracking systems due to lack of information of the direct component of the solar radiation. We will present examples and statistical analyses of solar radiation partitioning showing the differences in the behavior of the total/direct radiation with respect to the near-term forecast issue. We will present an overview of the possibility of using a network of unique new commercially available total/diffuse radiometers in conjunction with a near-real-time adaptation of the Shortwave Radiative Flux Analysis methodology (Long and Ackerman, 2000; Long et al., 2006). The results are used, in conjunction with persistence and tendency forecast techniques, to provide more accurate near-term forecasts of cloudiness, and both total and direct normal solar irradiance availability and variability. This new system could be a long term economical solution for solar energy applications.xample of SW Flux Analysis global hemispheric (light blue) and direct (yellow) clear-sky shortwave (SW) along with corresponding actual global hemispheric (blue) and direct (red) SW, and the corresponding fractional sky cover (black, right Y-axis). Note in afternoon about 40-50% of the global SW is available, yet most times there is no direct SW.

Space weather: Why are magnetospheric physicists interested in solar explosive phenomena

NASA Astrophysics Data System (ADS)

Koskinen, H. E. J.; Pulkkinen, T. I.

That solar activity drives magnetospheric dynamics has for a long time been the basis of solar-terrestrial physics. Numerous statistical studies correlating sunspots, 10.7 cm radiation, solar flares, etc., with various magnetospheric and geomagnetic parameters have been performed. However, in studies of magnetospheric dynamics the role of the Sun has often remained in the background and only the actual solar wind impinging the magnetosphere has gained most of the attention. During the last few years a new applied field of solar-terrestrial physics, space weather, has emerged. The term refers to variable particle and field conditions in our space environment, which may be hazardous to space-borne or ground-based technological systems and can endanger human life and health. When the modern society is becoming increasingly dependent on space technology, the need for better modelling and also forecasting of space weather becomes urgent. While for post analysis of magnetospheric phenomena it is quite sufficient to include observations from the magnetospheric boundaries out to L1 where SOHO is located, these observations do not provide enough lead-time to run space weather forecasting models and to distribute the forecasts to potential customers. For such purposes we need improved physical understanding and models to predict which active processes on the Sun will impact the magnetosphere and what their expected consequences are. An important change of view on the role of the Sun as the origin of magnetospheric disturbances has taken place during last 10--20 years. For a long time, the solar flares were thought to be the most geoeffective solar phenomena. Now the attention has shifted much more towards coronal mass ejections and the SOHO coronal observations seem to have turned the epoch irreversibly. However, we are not yet ready to make reliable perdictions of the terrestrial environment based on CME observations. From the space weather viewpoint, the key questions are when a CME will be ejected, will it hit the Earth, what will its density and speed be, and how the magnetic field will be wrapped around the plasma cloud. This is clearly an enormous modelling task, but very forthwhile to carry further. Also forecasting of the solar energetic particle events would be very usefule as they form the most hazardous single effect on spaceflight, be that on the Space Station, on the Moon, or even further. We illustrate the chain of effects from the solar atmosphere to near-Earth space using some of the CME-associated magnetic storm events from the SOHO era.

Novel approaches to mid-long term weather and climate forecast based on the solar-geomagnetic signal

NASA Astrophysics Data System (ADS)

Avakyan, Sergey; Baranova, Lubov

Two possibilities are discussed concerning the use of data on solar-geomagnetic activity for meteorological forecasting (cloudiness, temperature and precipitation). The first possibility is consideration of quasicyclic recurrence of large solar flares and geomagnetic storms with periods of 2 - 5 years. For the periods shorter than one year the second possibility is taking into account: the negative correlation of total global cloud cover with the number of solar spots and positive correlation with the total solar irradiance (TSI) - the contribution of short wave radiation of faculae fields. To justify the mechanism of solar-tropospheric links, it is obviously necessary to provide explanation for the observed dependence of weather and climate on usual cyclic activity of the Sun. Meteorologists and even geophysicists have found no significant correlation between atmospheric parameters and either number of solar spots or variations of solar constant. It was found that temperature did not display any variability with the 11-year period (the basic solar cycle). Instead stable quasi-periodic variations of temperature of air within 2 - 5.5 years and also for the precipitation periods in the interval 2 to 6 years were observed. Each 11-year cycle displays two maxima for the probability of solar X-ray and extreme UV flares and for probability of medium and strong geomagnetic storms (2 to 4 years for the flares and 2 to 6 years for significant magnetic storms), and those induced by solar flares, the latter, as a rule, between the maximum points of the number of geomagnetic storms. On a timescale of about a year or shorter, a correlation is revealed between the occurrence of the total cloudiness and the sunspot and faculae activity (number of solar spots and the value of the solar constant - TSI). From the number of sunspots and the data concerning faculae fields, on the basis of the known statistics for the lifetime of these formation in the solar photosphere, it is possible to forecasting the variation in the area of cloud and consequently the thermal radiative balance of the Earth (the temperature anomalies) for several months ahead. The physics of these manifestations of the effect of the "solar signal" on the troposphere is also related with our radio-optical three-stage trigger mechanism. The microwave radiation generated by ionosphere under the influence of the enhanced solar and geomagnetic activity (increased fluxes of the ionizing solar radiation during solar flares and of electrons precipitated from radiation belts during magnetic storms) affects the cluster condensation process of origination and further evolution of optically thin cloudiness, including the formation of precipitation in the course of «sowing» by crystals from upper-layer clouds. These clouds cause a net warming due to their relative transparence at short wavelengths but opacity in the infrared region (where there is flux of the thermal radiation coming out from the underlying surface).

Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle.

PubMed

Deo, Ravinesh C; Downs, Nathan; Parisi, Alfio V; Adamowski, Jan F; Quilty, John M

2017-05-01

Exposure to erythemally-effective solar ultraviolet radiation (UVR) that contributes to malignant keratinocyte cancers and associated health-risk is best mitigated through innovative decision-support systems, with global solar UV index (UVI) forecast necessary to inform real-time sun-protection behaviour recommendations. It follows that the UVI forecasting models are useful tools for such decision-making. In this study, a model for computationally-efficient data-driven forecasting of diffuse and global very short-term reactive (VSTR) (10-min lead-time) UVI, enhanced by drawing on the solar zenith angle (θ s ) data, was developed using an extreme learning machine (ELM) algorithm. An ELM algorithm typically serves to address complex and ill-defined forecasting problems. UV spectroradiometer situated in Toowoomba, Australia measured daily cycles (0500-1700h) of UVI over the austral summer period. After trialling activations functions based on sine, hard limit, logarithmic and tangent sigmoid and triangular and radial basis networks for best results, an optimal ELM architecture utilising logarithmic sigmoid equation in hidden layer, with lagged combinations of θ s as the predictor data was developed. ELM's performance was evaluated using statistical metrics: correlation coefficient (r), Willmott's Index (WI), Nash-Sutcliffe efficiency coefficient (E NS ), root mean square error (RMSE), and mean absolute error (MAE) between observed and forecasted UVI. Using these metrics, the ELM model's performance was compared to that of existing methods: multivariate adaptive regression spline (MARS), M5 Model Tree, and a semi-empirical (Pro6UV) clear sky model. Based on RMSE and MAE values, the ELM model (0.255, 0.346, respectively) outperformed the MARS (0.310, 0.438) and M5 Model Tree (0.346, 0.466) models. Concurring with these metrics, the Willmott's Index for the ELM, MARS and M5 Model Tree models were 0.966, 0.942 and 0.934, respectively. About 57% of the ELM model's absolute errors were small in magnitude (±0.25), whereas the MARS and M5 Model Tree models generated 53% and 48% of such errors, respectively, indicating the latter models' errors to be distributed in larger magnitude error range. In terms of peak global UVI forecasting, with half the level of error, the ELM model outperformed MARS and M5 Model Tree. A comparison of the magnitude of hourly-cumulated errors of 10-min lead time forecasts for diffuse and global UVI highlighted ELM model's greater accuracy compared to MARS, M5 Model Tree or Pro6UV models. This confirmed the versatility of an ELM model drawing on θ s data for VSTR forecasting of UVI at near real-time horizon. When applied to the goal of enhancing expert systems, ELM-based accurate forecasts capable of reacting quickly to measured conditions can enhance real-time exposure advice for the public, mitigating the potential for solar UV-exposure-related disease. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Image-based optimization of coronal magnetic field models for improved space weather forecasting

NASA Astrophysics Data System (ADS)

Uritsky, V. M.; Davila, J. M.; Jones, S. I.; MacNeice, P. J.

2017-12-01

The existing space weather forecasting frameworks show a significant dependence on the accuracy of the photospheric magnetograms and the extrapolation models used to reconstruct the magnetic filed in the solar corona. Minor uncertainties in the magnetic field magnitude and direction near the Sun, when propagated through the heliosphere, can lead to unacceptible prediction errors at 1 AU. We argue that ground based and satellite coronagraph images can provide valid geometric constraints that could be used for improving coronal magnetic field extrapolation results, enabling more reliable forecasts of extreme space weather events such as major CMEs. In contrast to the previously developed loop segmentation codes designed for detecting compact closed-field structures above solar active regions, we focus on the large-scale geometry of the open-field coronal regions up to 1-2 solar radii above the photosphere. By applying the developed image processing techniques to high-resolution Mauna Loa Solar Observatory images, we perform an optimized 3D B-line tracing for a full Carrington rotation using the magnetic field extrapolation code developed S. Jones at al. (ApJ 2016, 2017). Our tracing results are shown to be in a good qualitative agreement with the large-scale configuration of the optical corona, and lead to a more consistent reconstruction of the large-scale coronal magnetic field geometry, and potentially more accurate global heliospheric simulation results. Several upcoming data products for the space weather forecasting community will be also discussed.

Nonlinear solar cycle forecasting: theory and perspectives

NASA Astrophysics Data System (ADS)

Baranovski, A. L.; Clette, F.; Nollau, V.

2008-02-01

In this paper we develop a modern approach to solar cycle forecasting, based on the mathematical theory of nonlinear dynamics. We start from the design of a static curve fitting model for the experimental yearly sunspot number series, over a time scale of 306 years, starting from year 1700 and we establish a least-squares optimal pulse shape of a solar cycle. The cycle-to-cycle evolution of the parameters of the cycle shape displays different patterns, such as a Gleissberg cycle and a strong anomaly in the cycle evolution during the Dalton minimum. In a second step, we extract a chaotic mapping for the successive values of one of the key model parameters - the rate of the exponential growth-decrease of the solar activity during the n-th cycle. We examine piece-wise linear techniques for the approximation of the derived mapping and we provide its probabilistic analysis: calculation of the invariant distribution and autocorrelation function. We find analytical relationships for the sunspot maxima and minima, as well as their occurrence times, as functions of chaotic values of the above parameter. Based on a Lyapunov spectrum analysis of the embedded mapping, we finally establish a horizon of predictability for the method, which allows us to give the most probable forecasting of the upcoming solar cycle 24, with an expected peak height of 93±21 occurring in 2011/2012.

Improved Modeling Tools Development for High Penetration Solar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Washom, Byron; Meagher, Kevin

2014-12-11

One of the significant objectives of the High Penetration solar research is to help the DOE understand, anticipate, and minimize grid operation impacts as more solar resources are added to the electric power system. For Task 2.2, an effective, reliable approach to predicting solar energy availability for energy generation forecasts using the University of California, San Diego (UCSD) Sky Imager technology has been demonstrated. Granular cloud and ramp forecasts for the next 5 to 20 minutes over an area of 10 square miles were developed. Sky images taken every 30 seconds are processed to determine cloud locations and cloud motionmore » vectors yielding future cloud shadow locations respective to distributed generation or utility solar power plants in the area. The performance of the method depends on cloud characteristics. On days with more advective cloud conditions, the developed method outperforms persistence forecasts by up to 30% (based on mean absolute error). On days with dynamic conditions, the method performs worse than persistence. Sky Imagers hold promise for ramp forecasting and ramp mitigation in conjunction with inverter controls and energy storage. The pre-commercial Sky Imager solar forecasting algorithm was documented with licensing information and was a Sunshot website highlight.« less

Ionospheric Data Assimilation and Targeted Observation Strategies: Proof of Concept Analysis in a Geomagnetic Storm Event

NASA Astrophysics Data System (ADS)

Kostelich, Eric; Durazo, Juan; Mahalov, Alex

2017-11-01

The dynamics of the ionosphere involve complex interactions between the atmosphere, solar wind, cosmic radiation, and Earth's magnetic field. Geomagnetic storms arising from solar activity can perturb these dynamics sufficiently to disrupt radio and satellite communications. Efforts to predict ``space weather,'' including ionospheric dynamics, require the development of a data assimilation system that combines observing systems with appropriate forecast models. This talk will outline a proof-of-concept targeted observation strategy, consisting of the Local Ensemble Transform Kalman Filter, coupled with the Thermosphere Ionosphere Electrodynamics Global Circulation Model, to select optimal locations where additional observations can be made to improve short-term ionospheric forecasts. Initial results using data and forecasts from the geomagnetic storm of 26-27 September 2011 will be described. Work supported by the Air Force Office of Scientific Research (Grant Number FA9550-15-1-0096) and by the National Science Foundation (Grant Number DMS-0940314).

Topside Equatorial Ionospheric Density and Composition During and After Extreme Solar Minimum

NASA Technical Reports Server (NTRS)

Klenzing, J.; Simoes, F.; Ivanov, S.; Heelis, R. A.; Bilitza, D.; Pfaff, R.; Rowland, D.

2011-01-01

During the recent solar minimum, solar activity reached the lowest levels observed during the space age. This extremely low solar activity has accompanied a number of unexpected observations in the Earth s ionosphere-thermosphere system when compared to previous solar minima. Among these are the fact that the ionosphere is significantly contracted beyond expectations based on empirical models. Altitude profiles of ion density and composition measurements near the magnetic dip equator are constructed from the Communication/Navigation Outage Forecast System (C/NOFS) satellite to characterize the shape of the topside ionosphere during the recent solar minimum and into the new solar cycle. The variation of the profiles with respect to local time, season, and solar activity are compared to the IRI-2007 model. Building on initial results reported by Heelis et al. (2009), here we describe the extent of the contracted ionosphere, which is found to persist throughout 2009. The shape of the ionosphere during 2010 is found to be consistent with observations from previous solar minima.

Comparative Validation of Realtime Solar Wind Forecasting Using the UCSD Heliospheric Tomography Model

NASA Technical Reports Server (NTRS)

MacNeice, Peter; Taktakishvili, Alexandra; Jackson, Bernard; Clover, John; Bisi, Mario; Odstrcil, Dusan

2011-01-01

The University of California, San Diego 3D Heliospheric Tomography Model reconstructs the evolution of heliospheric structures, and can make forecasts of solar wind density and velocity up to 72 hours in the future. The latest model version, installed and running in realtime at the Community Coordinated Modeling Center(CCMC), analyzes scintillations of meter wavelength radio point sources recorded by the Solar-Terrestrial Environment Laboratory(STELab) together with realtime measurements of solar wind speed and density recorded by the Advanced Composition Explorer(ACE) Solar Wind Electron Proton Alpha Monitor(SWEPAM).The solution is reconstructed using tomographic techniques and a simple kinematic wind model. Since installation, the CCMC has been recording the model forecasts and comparing them with ACE measurements, and with forecasts made using other heliospheric models hosted by the CCMC. We report the preliminary results of this validation work and comparison with alternative models.

Evaluation of regression and neural network models for solar forecasting over different short-term horizons

DOE PAGES

Inanlouganji, Alireza; Reddy, T. Agami; Katipamula, Srinivas

2018-04-13

Forecasting solar irradiation has acquired immense importance in view of the exponential increase in the number of solar photovoltaic (PV) system installations. In this article, analyses results involving statistical and machine-learning techniques to predict solar irradiation for different forecasting horizons are reported. Yearlong typical meteorological year 3 (TMY3) datasets from three cities in the United States with different climatic conditions have been used in this analysis. A simple forecast approach that assumes consecutive days to be identical serves as a baseline model to compare forecasting alternatives. To account for seasonal variability and to capture short-term fluctuations, different variants of themore » lagged moving average (LMX) model with cloud cover as the input variable are evaluated. Finally, the proposed LMX model is evaluated against an artificial neural network (ANN) model. How the one-hour and 24-hour models can be used in conjunction to predict different short-term rolling horizons is discussed, and this joint application is illustrated for a four-hour rolling horizon forecast scheme. Lastly, the effect of using predicted cloud cover values, instead of measured ones, on the accuracy of the models is assessed. Results show that LMX models do not degrade in forecast accuracy if models are trained with the forecast cloud cover data.« less

Evaluation of regression and neural network models for solar forecasting over different short-term horizons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Inanlouganji, Alireza; Reddy, T. Agami; Katipamula, Srinivas

Forecasting solar irradiation has acquired immense importance in view of the exponential increase in the number of solar photovoltaic (PV) system installations. In this article, analyses results involving statistical and machine-learning techniques to predict solar irradiation for different forecasting horizons are reported. Yearlong typical meteorological year 3 (TMY3) datasets from three cities in the United States with different climatic conditions have been used in this analysis. A simple forecast approach that assumes consecutive days to be identical serves as a baseline model to compare forecasting alternatives. To account for seasonal variability and to capture short-term fluctuations, different variants of themore » lagged moving average (LMX) model with cloud cover as the input variable are evaluated. Finally, the proposed LMX model is evaluated against an artificial neural network (ANN) model. How the one-hour and 24-hour models can be used in conjunction to predict different short-term rolling horizons is discussed, and this joint application is illustrated for a four-hour rolling horizon forecast scheme. Lastly, the effect of using predicted cloud cover values, instead of measured ones, on the accuracy of the models is assessed. Results show that LMX models do not degrade in forecast accuracy if models are trained with the forecast cloud cover data.« less

Neural net forecasting for geomagnetic activity

NASA Technical Reports Server (NTRS)

Hernandez, J. V.; Tajima, T.; Horton, W.

1993-01-01

We use neural nets to construct nonlinear models to forecast the AL index given solar wind and interplanetary magnetic field (IMF) data. We follow two approaches: (1) the state space reconstruction approach, which is a nonlinear generalization of autoregressive-moving average models (ARMA) and (2) the nonlinear filter approach, which reduces to a moving average model (MA) in the linear limit. The database used here is that of Bargatze et al. (1985).

Evaluating the spatio-temporal performance of sky imager based solar irradiance analysis and forecasts

NASA Astrophysics Data System (ADS)

Schmidt, T.; Kalisch, J.; Lorenz, E.; Heinemann, D.

2015-10-01

Clouds are the dominant source of variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the world-wide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a shortest-term global horizontal irradiance (GHI) forecast experiment based on hemispheric sky images. A two month dataset with images from one sky imager and high resolutive GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series in different cloud scenarios. Overall, the sky imager based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depend strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1-2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

A Real-time 3D Visualization of Global MHD Simulation for Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Murata, K.; Matsuoka, D.; Kubo, T.; Shimazu, H.; Tanaka, T.; Fujita, S.; Watari, S.; Miyachi, H.; Yamamoto, K.; Kimura, E.; Ishikura, S.

2006-12-01

Recently, many satellites for communication networks and scientific observation are launched in the vicinity of the Earth (geo-space). The electromagnetic (EM) environments around the spacecraft are always influenced by the solar wind blowing from the Sun and induced electromagnetic fields. They occasionally cause various troubles or damages, such as electrification and interference, to the spacecraft. It is important to forecast the geo-space EM environment as well as the ground weather forecasting. Owing to the recent remarkable progresses of super-computer technologies, numerical simulations have become powerful research methods in the solar-terrestrial physics. For the necessity of space weather forecasting, NICT (National Institute of Information and Communications Technology) has developed a real-time global MHD simulation system of solar wind-magnetosphere-ionosphere couplings, which has been performed on a super-computer SX-6. The real-time solar wind parameters from the ACE spacecraft at every one minute are adopted as boundary conditions for the simulation. Simulation results (2-D plots) are updated every 1 minute on a NICT website. However, 3D visualization of simulation results is indispensable to forecast space weather more accurately. In the present study, we develop a real-time 3D webcite for the global MHD simulations. The 3-D visualization results of simulation results are updated every 20 minutes in the following three formats: (1)Streamlines of magnetic field lines, (2)Isosurface of temperature in the magnetosphere and (3)Isoline of conductivity and orthogonal plane of potential in the ionosphere. For the present study, we developed a 3-D viewer application working on Internet Explorer browser (ActiveX) is implemented, which was developed on the AVS/Express. Numerical data are saved in the HDF5 format data files every 1 minute. Users can easily search, retrieve and plot past simulation results (3D visualization data and numerical data) by using the STARS (Solar-terrestrial data Analysis and Reference System). The STARS is a data analysis system for satellite and ground-based observation data for solar-terrestrial physics.

Forecast Method of Solar Irradiance with Just-In-Time Modeling

NASA Astrophysics Data System (ADS)

Suzuki, Takanobu; Goto, Yusuke; Terazono, Takahiro; Wakao, Shinji; Oozeki, Takashi

PV power output mainly depends on the solar irradiance which is affected by various meteorological factors. So, it is required to predict solar irradiance in the future for the efficient operation of PV systems. In this paper, we develop a novel approach for solar irradiance forecast, in which we introduce to combine the black-box model (JIT Modeling) with the physical model (GPV data). We investigate the predictive accuracy of solar irradiance over wide controlled-area of each electric power company by utilizing the measured data on the 44 observation points throughout Japan offered by JMA and the 64 points around Kanto by NEDO. Finally, we propose the application forecast method of solar irradiance to the point which is difficulty in compiling the database. And we consider the influence of different GPV default time on solar irradiance prediction.

Tools, Resources, and Innovations for Active Learning of Solar and Geospace Environment Content in the Undergraduate Classrooms

NASA Astrophysics Data System (ADS)

Knipp, D. J.

2013-12-01

An undergraduate course in solar and geospace (helio) physics should link fundamental principles from introductory physics and astronomy courses to concepts that appear unique, or are uniquely named in the heliophysics course. This paper discusses short topics and activities that can be addressed in an approximately 15-min class segment, that introduce students to aspects of solar, solar wind, and geospace storms that are a step beyond, or a special application of, an introductory physics concept. Some of these activities could be assigned as pre- or post- class activities as well. Many of the actives are aligned with images or diagrams in textbook, "Understanding Space Weather and the Physics Behind It," but could be easily adapted to other texts. We also address activities that link to information from space weather forecasting and/or modeling websites.

Solar cycles: A tutorial

NASA Astrophysics Data System (ADS)

Moussas, X.; Polygiannakis, J. M.; Preka-Papadema, P.; Exarhos, G.

The Sun is the nearest stellar and astrophysical laboratory, available for detailed studies in several fields of physics and astronomy. It is a sphere of hot gas with a complex and highly variable magnetic field which plays a very important role. The Sun shows an unprecedented wealth of phenomena that can be studied extensively and to the greatest detail, in a way we will never be in a position to study in other stars. Humans have studied the Sun for millennia and after the discovery of the telescope they realized that the Sun varies with time, i.e., solar activity is highly variable, in tune scales of millennia to seconds. The study of these variabilities helps us to understand how the Sun works and how it affects the interplanetary medium, Earth and the other planets. Solar power varies substantially and greatly affects the Earth and humans. Solar activity has several important periodicities, and quasi-periodicities. Knowledge of these periodicities helps us to forecast, to an extent, solar events that affect our planet. The most prominent periodicity of solar activity is the one of 11 years. The actual period is in fact 22 years because the magnetic field polarity of the Sun has to be taken into account. The Sun can be considered as a non-linear RLC electric circuit with a period of 22 years. The RLC equivalent circuit of the Sun is a van der Pol oscillator and such a model can explain many solar phenomena, including the variability of solar energy with time. Other quasi-periodicities such as the ones of 154 days, the 1.3, 1.7 to 2 years, etc., some of which might be harmonics of the 22 year cycle are also present in solar activity, and their study is very interesting and important since they affect the Earth and human activities. The period of 27 days related to solar rotation plays also a very important role in geophysical phenomena. It is noticeable that almost all periodicities are highly variable with time as wavelet analysis reveals. It is very important for humans to be in a position to forecast solar activity during the next hour, day, year, decade and century, because solar phenomena affect life on Earth and such predictions will help politicians and policy makers to better serve their countries and our planet.

Forbush Decrease Prediction Based on Remote Solar Observations

NASA Astrophysics Data System (ADS)

Dumbovic, Mateja; Vrsnak, Bojan; Calogovic, Jasa

2016-04-01

We study the relation between remote observations of coronal mass ejections (CMEs), their associated solar flares and short-term depressions in the galactic cosmic-ray flux (so called Forbush decreases). Statistical relations between Forbush decrease magnitude and several CME/flare parameters are examined. In general we find that Forbush decrease magnitude is larger for faster CMEs with larger apparent width, which is associated with stronger flares that originate close to the center of the solar disk and are (possibly) involved in a CME-CME interaction. The statistical relations are quantified and employed to forecast expected Forbush decrease magnitude range based on the selected remote solar observations of the CME and associated solar flare. Several verification measures are used to evaluate the forecast method. We find that the forecast is most reliable in predicting whether or not a CME will produce a Forbush decrease with a magnitude >3 %. The main advantage of the method is that it provides an early prediction, 1-4 days in advance. Based on the presented research, an online forecast tool was developed (Forbush Decrease Forecast Tool, FDFT) available at Hvar Observatory web page: http://oh.geof.unizg.hr/FDFT/fdft.php. We acknowledge the support of Croatian Science Foundation under the project 6212 "Solar and Stellar Variability" and of European social fond under the project "PoKRet".

[Medium-term forecast of solar cosmic rays radiation risk during a manned Mars mission].

PubMed

Petrov, V M; Vlasov, A G

2006-01-01

Medium-term forecasting radiation hazard from solar cosmic rays will be vital in a manned Mars mission. Modern methods of space physics lack acceptable reliability in medium-term forecasting the SCR onset and parameters. The proposed estimation of average radiation risk from SCR during the manned Mars mission is made with the use of existing SCR fluence and spectrum models and correlation of solar particle event frequency with predicted Wolf number. Radiation risk is considered an additional death probability from acute radiation reactions (ergonomic component) or acute radial disease in flight. The algorithm for radiation risk calculation is described and resulted risk levels for various periods of the 23-th solar cycle are presented. Applicability of this method to advance forecasting and possible improvements are being investigated. Recommendations to the crew based on risk estimation are exemplified.

Evaluating the spatio-temporal performance of sky-imager-based solar irradiance analysis and forecasts

NASA Astrophysics Data System (ADS)

Schmidt, Thomas; Kalisch, John; Lorenz, Elke; Heinemann, Detlev

2016-03-01

Clouds are the dominant source of small-scale variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the worldwide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a very short term global horizontal irradiance (GHI) forecast experiment based on hemispheric sky images. A 2-month data set with images from one sky imager and high-resolution GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series into different cloud scenarios. Overall, the sky-imager-based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depends strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1-2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability, which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

Comparative Analysis of NOAA REFM and SNB3GEO Tools for the Forecast of the Fluxes of High-Energy Electrons at GEO

NASA Technical Reports Server (NTRS)

Balikhin, M. A.; Rodriguez, J. V.; Boynton, R. J.; Walker, S. N.; Aryan, Homayon; Sibeck, D. G.; Billings, S. A.

2016-01-01

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB3GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB3GEO forecasts use solar wind density and interplanetary magnetic field B(sub z) observations at L1. The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB3GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB3GEO forecast.

Comparative analysis of NOAA REFM and SNB3GEO tools for the forecast of the fluxes of high-energy electrons at GEO.

PubMed

Balikhin, M A; Rodriguez, J V; Boynton, R J; Walker, S N; Aryan, H; Sibeck, D G; Billings, S A

2016-01-01

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB 3 GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB 3 GEO forecasts use solar wind density and interplanetary magnetic field B z observations at L1.The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB 3 GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB 3 GEO forecast.

Practice of Meteorological Services in Turpan Solar Eco-City in China (Invited)

NASA Astrophysics Data System (ADS)

Shen, Y.; Chang, R.; He, X.; Jiang, Y.; Zhao, D.; Ma, J.

2013-12-01

Turpan Solar Eco-City is located in Gobi in Northwest China, which is one of the National New Energy Demonstration Urban. The city was planed and designed from October of 2008 and constructed from May of 2010, and the first phase of the project has been completed by October of 2013. Energy supply in Turpan Solar Eco-City is mainly from PV power, which is installed in all of the roof and the total capacity is 13.4MW. During the planning and designing of the city, and the running of the smart grid, meteorological services have played an important role. 1) Solar Energy Resource Assessment during Planning Phase. According to the observed data from meteorological stations in recent 30 years, solar energy resource was assessed and available PV power generation capacity was calculated. The results showed that PV power generation capacity is 1.3 times the power consumption, that is, solar energy resource in Turpan is rich. 2) Key Meteorological Parameters Determination for Architectural Design. A professional solar energy resource station was constructed and the observational items included Global Horizontal Irradiance, Inclined Total Solar Irradiance at 30 degree, Inclined Total Solar Irradiance at local latitude, and so on. According these measured data, the optical inclined angle for PV array was determined, that is, 30 degree. The results indicated that the annual irradiation on inclined plane with optimal angle is 1.4% higher than the inclined surface with latitude angle, and 23.16% higher than the horizontal plane. The diffuse ratio and annual variation of the solar elevation angle are two major factors that influence the irradiation on inclined plane. 3) Solar Energy Resource Forecast for Smart Grid. Weather Research Forecast (WRF) model was used to forecast the hourly solar radiation of future 72 hours and the measured irradiance data was used to forecast the minutely solar radiation of future 4 hours. The forecast results were submitted to smart grid and used to regulate the local grid and the city gird.

Advances in Predicting Magnetic Fields on the Far Side of the Sun

NASA Astrophysics Data System (ADS)

Lindsey, C. A.

2016-12-01

Techniques in local solar seismology applied to observations of seismic oscillations in the Sun's near hemisphere allow us to map large magnetic regions in the Sun's far hemisphere. Seismic signatures are not nearly as sensitive to magnetic flux as observations in electromagnetic radiation. However, they clearly identify and locate the 400 or so largest active regions in a typical solar cycle, i.e., those of most concern for space-weather forecasting. By themselves, seismic observations are insensitive to magnetic polarity. However, the Hale polarity law offers tantalizing avenues for guessing polarity distributions from seismic signatures as they evolve. I will review what we presently know about the relationship between seismic signatures of active regions and their magnetic and radiative properties, and offer a preliminary assessment of the potential of far-side seismic maps for space-weather forecasting in the coming decade.

A Multi-scale, Multi-Model, Machine-Learning Solar Forecasting Technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamann, Hendrik F.

The goal of the project was the development and demonstration of a significantly improved solar forecasting technology (short: Watt-sun), which leverages new big data processing technologies and machine-learnt blending between different models and forecast systems. The technology aimed demonstrating major advances in accuracy as measured by existing and new metrics which themselves were developed as part of this project. Finally, the team worked with Independent System Operators (ISOs) and utilities to integrate the forecasts into their operations.

Solar energy market penetration models - Science or number mysticism

NASA Technical Reports Server (NTRS)

Warren, E. H., Jr.

1980-01-01

The forecast market potential of a solar technology is an important factor determining its R&D funding. Since solar energy market penetration models are the method used to forecast market potential, they have a pivotal role in a solar technology's development. This paper critiques the applicability of the most common solar energy market penetration models. It is argued that the assumptions underlying the foundations of rigorously developed models, or the absence of a reasonable foundation for the remaining models, restrict their applicability.

Forecasting the peak of the present solar activity cycle 24

NASA Astrophysics Data System (ADS)

Hamid, R. H.; Marzouk, B. A.

2018-06-01

Solar forecasting of the level of sun Activity is very important subject for all space programs. Most predictions are based on the physical conditions prevailing at or before the solar cycle minimum preceding the maximum in question. Our aim is to predict the maximum peak of cycle 24 using precursor techniques in particular those using spotless event, geomagnetic aamin. index and solar flux F10.7. Also prediction of exact date of the maximum (Tr) is taken in consideration. A study of variation over previous spotless event for cycles 7-23 and that for even cycles (8-22) are carried out for the prediction. Linear correlation between maximum of solar cycles (RM) and spotless event around the preceding minimum gives R24t = 88.4 with rise time Tr = 4.6 years. For the even cycles R24E = 77.9 with rise time Tr = 4.5 y's. Based on the average aamin. index for cycles (12-23), we estimate the expected amplitude for cycle 24 to be Raamin = 99.4 and 98.1 with time rise of Traamin = 4.04 & 4.3 years for both the total and even cycles in consecutive. The application of the data of solar flux F10.7 which cover only cycles (19-23) was taken in consideration and gives predicted maximum amplitude R24 10.7 = 126 with rise time Tr107 = 3.7 years, which are over estimation. Our result indicating to somewhat weaker of cycle 24 as compared to cycles 21-23.

Hilbert-Huang transform analysis of long-term solar magnetic activity

NASA Astrophysics Data System (ADS)

Deng, Linhua

2018-04-01

Astronomical time series analysis is one of the hottest and most important problems, and becomes the suitable way to deal with the underlying dynamical behavior of the considered nonlinear systems. The quasi-periodic analysis of solar magnetic activity has been carried out by various authors during the past fifty years. In this work, the novel Hilbert-Huang transform approach is applied to investigate the yearly numbers of polar faculae in the time interval from 1705 to 1999. The detected periodicities can be allocated to three components: the first one is the short-term variations with periods smaller than 11 years, the second one is the mid- term variations with classical periods from 11 years to 50 years, and the last one is the long-term variations with periods larger than 50 years. The analysis results improve our knowledge on the quasi-periodic variations of solar magnetic activity and could be provided valuable constraints for solar dynamo theory. Furthermore, our analysis results could be useful for understanding the long-term variations of solar magnetic activity, providing crucial information to describe and forecast solar magnetic activity indicators.

Future mission studies: Preliminary comparisons of solar flux models

NASA Technical Reports Server (NTRS)

Ashrafi, S.

1991-01-01

The results of comparisons of the solar flux models are presented. (The wavelength lambda = 10.7 cm radio flux is the best indicator of the strength of the ionizing radiations such as solar ultraviolet and x-ray emissions that directly affect the atmospheric density thereby changing the orbit lifetime of satellites. Thus, accurate forecasting of solar flux F sub 10.7 is crucial for orbit determination of spacecrafts.) The measured solar flux recorded by National Oceanic and Atmospheric Administration (NOAA) is compared against the forecasts made by Schatten, MSFC, and NOAA itself. The possibility of a combined linear, unbiased minimum-variance estimation that properly combines all three models into one that minimizes the variance is also discussed. All the physics inherent in each model are combined. This is considered to be the dead-end statistical approach to solar flux forecasting before any nonlinear chaotic approach.

Machine Learning Based Multi-Physical-Model Blending for Enhancing Renewable Energy Forecast -- Improvement via Situation Dependent Error Correction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Siyuan; Hwang, Youngdeok; Khabibrakhmanov, Ildar

With increasing penetration of solar and wind energy to the total energy supply mix, the pressing need for accurate energy forecasting has become well-recognized. Here we report the development of a machine-learning based model blending approach for statistically combining multiple meteorological models for improving the accuracy of solar/wind power forecast. Importantly, we demonstrate that in addition to parameters to be predicted (such as solar irradiance and power), including additional atmospheric state parameters which collectively define weather situations as machine learning input provides further enhanced accuracy for the blended result. Functional analysis of variance shows that the error of individual modelmore » has substantial dependence on the weather situation. The machine-learning approach effectively reduces such situation dependent error thus produces more accurate results compared to conventional multi-model ensemble approaches based on simplistic equally or unequally weighted model averaging. Validation over an extended period of time results show over 30% improvement in solar irradiance/power forecast accuracy compared to forecasts based on the best individual model.« less

Ensemble flare forecasting: using numerical weather prediction techniques to improve space weather operations

NASA Astrophysics Data System (ADS)

Murray, S.; Guerra, J. A.

2017-12-01

One essential component of operational space weather forecasting is the prediction of solar flares. Early flare forecasting work focused on statistical methods based on historical flaring rates, but more complex machine learning methods have been developed in recent years. A multitude of flare forecasting methods are now available, however it is still unclear which of these methods performs best, and none are substantially better than climatological forecasts. Current operational space weather centres cannot rely on automated methods, and generally use statistical forecasts with a little human intervention. Space weather researchers are increasingly looking towards methods used in terrestrial weather to improve current forecasting techniques. Ensemble forecasting has been used in numerical weather prediction for many years as a way to combine different predictions in order to obtain a more accurate result. It has proved useful in areas such as magnetospheric modelling and coronal mass ejection arrival analysis, however has not yet been implemented in operational flare forecasting. Here we construct ensemble forecasts for major solar flares by linearly combining the full-disk probabilistic forecasts from a group of operational forecasting methods (ASSA, ASAP, MAG4, MOSWOC, NOAA, and Solar Monitor). Forecasts from each method are weighted by a factor that accounts for the method's ability to predict previous events, and several performance metrics (both probabilistic and categorical) are considered. The results provide space weather forecasters with a set of parameters (combination weights, thresholds) that allow them to select the most appropriate values for constructing the 'best' ensemble forecast probability value, according to the performance metric of their choice. In this way different forecasts can be made to fit different end-user needs.

Forecasting Global Horizontal Irradiance Using the LETKF and a Combination of Advected Satellite Images and Sparse Ground Sensors

NASA Astrophysics Data System (ADS)

Harty, T. M.; Lorenzo, A.; Holmgren, W.; Morzfeld, M.

2017-12-01

The irradiance incident on a solar panel is the main factor in determining the power output of that panel. For this reason, accurate global horizontal irradiance (GHI) estimates and forecasts are critical when determining the optimal location for a solar power plant, forecasting utility scale solar power production, or forecasting distributed, behind the meter rooftop solar power production. Satellite images provide a basis for producing the GHI estimates needed to undertake these objectives. The focus of this work is to combine satellite derived GHI estimates with ground sensor measurements and an advection model. The idea is to use accurate but sparsely distributed ground sensors to improve satellite derived GHI estimates which can cover large areas (the size of a city or a region of the United States). We use a Bayesian framework to perform the data assimilation, which enables us to produce irradiance forecasts and associated uncertainties which incorporate both satellite and ground sensor data. Within this framework, we utilize satellite images taken from the GOES-15 geostationary satellite (available every 15-30 minutes) as well as ground data taken from irradiance sensors and rooftop solar arrays (available every 5 minutes). The advection model, driven by wind forecasts from a numerical weather model, simulates cloud motion between measurements. We use the Local Ensemble Transform Kalman Filter (LETKF) to perform the data assimilation. We present preliminary results towards making such a system useful in an operational context. We explain how localization and inflation in the LETKF, perturbations of wind-fields, and random perturbations of the advection model, affect the accuracy of our estimates and forecasts. We present experiments showing the accuracy of our forecasted GHI over forecast-horizons of 15 mins to 1 hr. The limitations of our approach and future improvements are also discussed.

Advanced Cloud Forecasting for Solar Energy Production

NASA Astrophysics Data System (ADS)

Werth, D. W.; Parker, M. J.

2017-12-01

A power utility must decide days in advance how it will allocate projected loads among its various generating sources. If the latter includes solar plants, the utility must predict how much energy the plants will produce - any shortfall will have to be compensated for by purchasing power as it is needed, when it is more expensive. To avoid this, utilities often err on the side of caution and assume that a relatively small amount of solar energy will be available, and allocate correspondingly more load to coal-fired plants. If solar irradiance can be predicted more accurately, utilities can be more confident that the predicted solar energy will indeed be available when needed, and assign solar plants a larger share of the future load. Solar power production is increasing in the Southeast, but is often hampered by irregular cloud fields, especially during high-pressure periods when rapid afternoon thunderstorm development can occur during what was predicted to be a clear day. We are currently developing an analog forecasting system to predict solar irradiance at the surface at the Savannah River Site in South Carolina, with the goal of improving predictions of available solar energy. Analog forecasting is based on the assumption that similar initial conditions will lead to similar outcomes, and involves the use of an algorithm to look through the weather patterns of the past to identify previous conditions (the analogs) similar to those of today. For our application, we select three predictor variables - sea-level pressure, 700mb geopotential, and 700mb humidity. These fields for the current day are compared to those from past days, and a weighted combination of the differences (defined by a cost function) is used to select the five best analog days. The observed solar irradiance values subsequent to the dates of those analogs are then combined to represent the forecast for the next day. We will explain how we apply the analog process, and compare it to existing solar forecasts.

Using Heliospheric Imaging for Storm Forecasting - SMEI CME Observations as a Tool for Operational Forecasting at AFWA

NASA Astrophysics Data System (ADS)

Webb, D. F.; Johnston, J. C.; Fry, C. D.; Kuchar, T. A.

2008-12-01

Observations of coronal mass ejections (CMEs) from heliospheric imagers such as the Solar Mass Ejection Imager (SMEI) can lead to significant improvements in operational space weather forecasting. We are working with the Air Force Weather Agency (AFWA) to ingest SMEI all-sky imagery with appropriate tools to help forecasters improve their operational space weather forecasts. We describe two approaches: 1) Near- real time analysis of propagating CMEs from SMEI images alone combined with near-Sun observations of CME onsets and, 2) Using these calculations of speed as a mid-course correction to the HAFv2 solar wind model forecasts. HAFv2 became operational at AFWA in late 2006. The objective is to determine a set of practical procedures that the duty forecaster can use to update or correct a solar wind forecast using heliospheric imager data. SMEI observations can be used inclusively to make storm forecasts, as recently discussed in Webb et al. (Space Weather, in press, 2008). We have developed a point-and-click analysis tool for use with SMEI images and are working with AFWA to ensure that timely SMEI images are available for analyses. When a frontside solar eruption occurs, especially if within about 45 deg. of Sun center, a forecaster checks for an associated CME observed by a coronagraph within an appropriate time window. If found, especially if the CME is a halo type, the forecaster checks SMEI observations about a day later, depending on the apparent initial CME speed, for possibly associated CMEs. If one is found, then the leading edge is measured over several successive frames and an elongation-time plot constructed. A minimum of three data points, i.e., over 3-4 orbits or about 6 hours, are necessary for such a plot. Using the solar source location and onset time of the CME from, e.g., SOHO observations, and assuming radial propagation, a distance-time relation is calculated and extrapolated to the 1 AU distance. As shown by Webb et al., the storm onset time is then expected to be about 3 hours after this 1 AU arrival time (AT). The prediction program is updated as more SMEI data become available. Currently when an appropriate solar event occurs, AFWA routinely runs the HAFv2 model to make a forecast of the shock and ejecta arrival times at Earth. SMEI data can be used to improve this prediction. The HAFv2 model can produce synthetic sky maps of predicted CME brightness for comparison with SMEI images. The forecaster uses SMEI imagery to observe and track the CME. The forecaster then measures the CME location and speed using the SMEI imagery and the HAFv2 synthetic sky maps. After comparing the SMEI and HAFv2 results, the forecaster can adjust a key input to HAFv2, such as the initial speed of the disturbance at the Sun or the mid-course speed. The forecaster then iteratively runs HAFv2 until the observed and forecast sky maps match. The final HAFv2 solution becomes the new forecast. When the CME/shock arrives at (or does not reach) Earth, the forecaster verifies the forecast and updates the forecast skill statistics. Eventually, we plan to develop a more automated version of this procedure.

Project for Solar-Terrestrial Environment Prediction (PSTEP): Towards Predicting Next Solar Cycle

NASA Astrophysics Data System (ADS)

Imada, S.; Iijima, H.; Hotta, H.; Shiota, D.; Kanou, O.; Fujiyama, M.; Kusano, K.

2016-10-01

It is believed that the longer-term variations of the solar activity can affect the Earth's climate. Therefore, predicting the next solar cycle is crucial for the forecast of the "solar-terrestrial environment". To build prediction schemes for the activity level of the next solar cycle is a key for the long-term space weather study. Although three-years prediction can be almost achieved, the prediction of next solar cycle is very limited, so far. We are developing a five-years prediction scheme by combining the Surface Flux Transport (SFT) model and the most accurate measurements of solar magnetic fields as a part of the PSTEP (Project for Solar-Terrestrial Environment Prediction),. We estimate the meridional flow, differential rotation, and turbulent diffusivity from recent modern observations (Hinode and Solar Dynamics Observatory). These parameters are used in the SFT models to predict the polar magnetic fields strength at the solar minimum. In this presentation, we will explain the outline of our strategy to predict the next solar cycle. We also report the present status and the future perspective of our project.

Real-Time CME Forecasting Using HMI Active-Region Magnetograms and Flare History

NASA Technical Reports Server (NTRS)

Falconer, David; Moore, Ron; Barghouty, Abdulnasser F.; Khazanov, Igor

2011-01-01

We have recently developed a method of predicting an active region s probability of producing a CME, an X-class Flare, an M-class Flare, or a Solar Energetic Particle Event from a free-energy proxy measured from SOHO/MDI line-of-sight magnetograms. This year we have added three major improvements to our forecast tool: 1) Transition from MDI magnetogram to SDO/HMI magnetogram allowing us near-real-time forecasts, 2) Automation of acquisition and measurement of HMI magnetograms giving us near-real-time forecasts (no older than 2 hours), and 3) Determination of how to improve forecast by using the active region s previous flare history in combination with its free-energy proxy. HMI was turned on in May 2010 and MDI was turned off in April 2011. Using the overlap period, we have calibrated HMI to yield what MDI would measure. This is important since the value of the free-energy proxy used for our forecast is resolution dependent, and the forecasts are made from results of a 1996-2004 database of MDI observations. With near-real-time magnetograms from HMI, near-real-time forecasts are now possible. We have augmented the code so that it continually acquires and measures new magnetograms as they become available online, and updates the whole-sun forecast from the coming day. The next planned improvement is to use an active region s previous flare history, in conjunction with its free-energy proxy, to forecast the active region s event rate. It has long been known that active regions that have produced flares in the past are likely to produce flares in the future, and that active regions that are nonpotential (have large free-energy) are more likely to produce flares in the future. This year we have determined that persistence of flaring is not just a reflection of an active region s free energy. In other words, after controlling for free energy, we have found that active regions that have flared recently are more likely to flare in the future.

Solar Photovoltaic and Liquid Natural Gas Opportunities for Command Naval Region Hawaii

DTIC Science & Technology

2014-12-01

Utilities Commission xii PV Photovoltaic Pwr Power RE Renewable Energy Re-gas Regasification RFP Request For Proposal RMI Rocky... forecasted LS diesel price and the forecasted LNG delivered-to-the- power -plant cost. The forecast for LS diesel by FGE from year 2020–2030 is seen...annual/html/epa_08_01.html Electric Power Research Institute. (July, 2010). Addressing solar photovoltaic operations and maintenance challenges: A

Using the Solar Polar Magnetic Field for Longterm Predictions of Solar Activity, Solar Cycles 21-25

NASA Astrophysics Data System (ADS)

Pesnell, W. D.; Schatten, K. H.

2017-12-01

We briefly review the dynamo and geomagnetic precursor methods of long-term solar activity forecasting. These methods depend upon the most basic aspect of dynamo theory to predict future activity, future magnetic field arises directly from the amplification of pre-existing magnetic field. We then generalize the dynamo technique, allowing the method to be used at any phase of the solar cycle, to the Solar Dynamo Amplitude (SODA) index. This index is sensitive to the magnetic flux trapped within the Sun's convection zone but insensitive to the phase of the solar cycle. Since magnetic fields inside the Sun can become buoyant, one may think of the acronym SODA as describing the amount of buoyant flux. We will show how effective the SODA Index has been in predicting Solar Cycles 23 and 24, and present a unified picture of earlier estimates of the polar magnetic configuration in Solar Cycle 21 and 22. Using the present value of the SODA index, we estimate that the next cycle's smoothed peak activity will be about 125 ± 30 solar flux units for the 10.7 cm radio flux and a sunspot number of 70 ± 25. This suggests that Solar Cycle 25 will be comparable to Solar Cycle 24. Since the current approach uses data prior to solar minimum, these estimates may improve when the upcoming solar minimum is reached.

The solar magnetic activity band interaction and instabilities that shape quasi-periodic variability

NASA Astrophysics Data System (ADS)

McIntosh, Scott W.; Leamon, Robert J.; Krista, Larisza D.; Title, Alan M.; Hudson, Hugh S.; Riley, Pete; Harder, Jerald W.; Kopp, Greg; Snow, Martin; Woods, Thomas N.; Kasper, Justin C.; Stevens, Michael L.; Ulrich, Roger K.

2015-04-01

Solar magnetism displays a host of variational timescales of which the enigmatic 11-year sunspot cycle is most prominent. Recent work has demonstrated that the sunspot cycle can be explained in terms of the intra- and extra-hemispheric interaction between the overlapping activity bands of the 22-year magnetic polarity cycle. Those activity bands appear to be driven by the rotation of the Sun's deep interior. Here we deduce that activity band interaction can qualitatively explain the `Gnevyshev Gap'--a well-established feature of flare and sunspot occurrence. Strong quasi-annual variability in the number of flares, coronal mass ejections, the radiative and particulate environment of the heliosphere is also observed. We infer that this secondary variability is driven by surges of magnetism from the activity bands. Understanding the formation, interaction and instability of these activity bands will considerably improve forecast capability in space weather and solar activity over a range of timescales.

Sensitivity analysis of numerical weather prediction radiative schemes to forecast direct solar radiation over Australia

NASA Astrophysics Data System (ADS)

Mukkavilli, S. K.; Kay, M. J.; Taylor, R.; Prasad, A. A.; Troccoli, A.

2014-12-01

The Australian Solar Energy Forecasting System (ASEFS) project requires forecasting timeframes which range from nowcasting to long-term forecasts (minutes to two years). As concentrating solar power (CSP) plant operators are one of the key stakeholders in the national energy market, research and development enhancements for direct normal irradiance (DNI) forecasts is a major subtask. This project involves comparing different radiative scheme codes to improve day ahead DNI forecasts on the national supercomputing infrastructure running mesoscale simulations on NOAA's Weather Research & Forecast (WRF) model. ASEFS also requires aerosol data fusion for improving accurate representation of spatio-temporally variable atmospheric aerosols to reduce DNI bias error in clear sky conditions over southern Queensland & New South Wales where solar power is vulnerable to uncertainities from frequent aerosol radiative events such as bush fires and desert dust. Initial results from thirteen years of Bureau of Meteorology's (BOM) deseasonalised DNI and MODIS NASA-Terra aerosol optical depth (AOD) anomalies demonstrated strong negative correlations in north and southeast Australia along with strong variability in AOD (~0.03-0.05). Radiative transfer schemes, DNI and AOD anomaly correlations will be discussed for the population and transmission grid centric regions where current and planned CSP plants dispatch electricity to capture peak prices in the market. Aerosol and solar irradiance datasets include satellite and ground based assimilations from the national BOM, regional aerosol researchers and agencies. The presentation will provide an overview of this ASEFS project task on WRF and results to date. The overall goal of this ASEFS subtask is to develop a hybrid numerical weather prediction (NWP) and statistical/machine learning multi-model ensemble strategy that meets future operational requirements of CSP plant operators.

Solar power satellite system definition study. Volume 1, phase 1: Executive summary

NASA Technical Reports Server (NTRS)

1979-01-01

A systems definition study of the solar satellite system (SPS) is presented. The technical feasibility of solar power satellites based on forecasts of technical capability in the various applicable technologies is assessed. The performance, cost, operational characteristics, reliability, and the suitability of SPS's as power generators for typical commercial electricity grids are discussed. The uncertainties inherent in the system characteristics forecasts are assessed.

Solar Energetic Particle Forecasting Algorithms and Associated False Alarms

NASA Astrophysics Data System (ADS)

Swalwell, B.; Dalla, S.; Walsh, R. W.

2017-11-01

Solar energetic particle (SEP) events are known to occur following solar flares and coronal mass ejections (CMEs). However, some high-energy solar events do not result in SEPs being detected at Earth, and it is these types of event which may be termed "false alarms". We define two simple SEP forecasting algorithms based upon the occurrence of a magnetically well-connected CME with a speed in excess of 1500 km s^{-1} (a "fast" CME) or a well-connected X-class flare and analyse them with respect to historical datasets. We compare the parameters of those solar events which produced an enhancement of {>} 40 MeV protons at Earth (an "SEP event") and the parameters of false alarms. We find that an SEP forecasting algorithm based solely upon the occurrence of a well-connected fast CME produces fewer false alarms (28.8%) than an algorithm which is based solely upon a well-connected X-class flare (50.6%). Both algorithms fail to forecast a relatively high percentage of SEP events (53.2% and 50.6%, respectively). Our analysis of the historical datasets shows that false-alarm X-class flares were either not associated with any CME, or were associated with a CME slower than 500 km s^{-1}; false-alarm fast CMEs tended to be associated with flare classes lower than M3. A better approach to forecasting would be an algorithm which takes as its base the occurrence of both CMEs and flares. We define a new forecasting algorithm which uses a combination of CME and flare parameters, and we show that the false-alarm ratio is similar to that for the algorithm based upon fast CMEs (29.6%), but the percentage of SEP events not forecast is reduced to 32.4%. Lists of the solar events which gave rise to {>} 40 MeV protons and the false alarms have been derived and are made available to aid further study.

Automated flare forecasting using a statistical learning technique

NASA Astrophysics Data System (ADS)

Yuan, Yuan; Shih, Frank Y.; Jing, Ju; Wang, Hai-Min

2010-08-01

We present a new method for automatically forecasting the occurrence of solar flares based on photospheric magnetic measurements. The method is a cascading combination of an ordinal logistic regression model and a support vector machine classifier. The predictive variables are three photospheric magnetic parameters, i.e., the total unsigned magnetic flux, length of the strong-gradient magnetic polarity inversion line, and total magnetic energy dissipation. The output is true or false for the occurrence of a certain level of flares within 24 hours. Experimental results, from a sample of 230 active regions between 1996 and 2005, show the accuracies of a 24-hour flare forecast to be 0.86, 0.72, 0.65 and 0.84 respectively for the four different levels. Comparison shows an improvement in the accuracy of X-class flare forecasting.

Massive Solar Storms Inflict Little Damage on Earth

NASA Astrophysics Data System (ADS)

Simpson, Sarah

2003-11-01

The face of the Sun had been peaceful and blemish-free for much of 2003. But space weather forecasters knew trouble was brewing on 24 October when Jupiter-sized sunspot 486 rotated into full view. Combined with two other unusually large spots, number 486 would kick up the most intense solar activity in 30 years according to several NOAA and NASA officials who were interviewed during the accompanying flurry of media coverage.

Short-Term Solar Forecasting Performance of Popular Machine Learning Algorithms: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Florita, Anthony R; Elgindy, Tarek; Hodge, Brian S

A framework for assessing the performance of short-term solar forecasting is presented in conjunction with a range of numerical results using global horizontal irradiation (GHI) from the open-source Surface Radiation Budget (SURFRAD) data network. A suite of popular machine learning algorithms is compared according to a set of statistically distinct metrics and benchmarked against the persistence-of-cloudiness forecast and a cloud motion forecast. Results show significant improvement compared to the benchmarks with trade-offs among the machine learning algorithms depending on the desired error metric. Training inputs include time series observations of GHI for a history of years, historical weather and atmosphericmore » measurements, and corresponding date and time stamps such that training sensitivities might be inferred. Prediction outputs are GHI forecasts for 1, 2, 3, and 4 hours ahead of the issue time, and they are made for every month of the year for 7 locations. Photovoltaic power and energy outputs can then be made using the solar forecasts to better understand power system impacts.« less

Geodetic Space Weather Monitoring by means of Ionosphere Modelling

NASA Astrophysics Data System (ADS)

Schmidt, Michael

2017-04-01

The term space weather indicates physical processes and phenomena in space caused by radiation of energy mainly from the Sun. Manifestations of space weather are (1) variations of the Earth's magnetic field, (2) the polar lights in the northern and southern hemisphere, (3) variations within the ionosphere as part of the upper atmosphere characterized by the existence of free electrons and ions, (4) the solar wind, i.e. the permanent emission of electrons and photons, (5) the interplanetary magnetic field, and (6) electric currents, e.g. the van Allen radiation belt. It can be stated that ionosphere disturbances are often caused by so-called solar storms. A solar storm comprises solar events such as solar flares and coronal mass ejections (CMEs) which have different effects on the Earth. Solar flares may cause disturbances in positioning, navigation and communication. CMEs can effect severe disturbances and in extreme cases damages or even destructions of modern infrastructure. Examples are interruptions to satellite services including the global navigation satellite systems (GNSS), communication systems, Earth observation and imaging systems or a potential failure of power networks. Currently the measurements of solar satellite missions such as STEREO and SOHO are used to forecast solar events. Besides these measurements the Earth's ionosphere plays another key role in monitoring the space weather, because it responses to solar storms with an increase of the electron density. Space-geodetic observation techniques, such as terrestrial GNSS, satellite altimetry, space-borne GPS (radio occultation), DORIS and VLBI provide valuable global information about the state of the ionosphere. Additionally geodesy has a long history and large experience in developing and using sophisticated analysis and combination techniques as well as empirical and physical modelling approaches. Consequently, geodesy is predestinated for strongly supporting space weather monitoring via modelling the ionosphere and detecting and forecasting its disturbances. At present a couple of nations, such as the US, UK, Japan, Canada and China, are taken the threats from extreme space weather events seriously and support the development of observing strategies and fundamental research. However, (extreme) space weather events are in all their consequences on the modern highly technologized society, causative global problems which have to be treated globally and not regionally or even nationally. Consequently, space weather monitoring must include (1) all space-geodetic observation techniques and (2) geodetic evaluation methods such as data combination, real-time modelling and forecast. In other words, geodetic space weather monitoring comprises the basic ideas of GGOS and will provide products such as forecasts of severe solar events in order to initiate necessary activities to protect the infrastructure of modern society.

Forecasting E > 50-MeV Proton Events with the Proton Prediction System (PPS)

NASA Astrophysics Data System (ADS)

Kahler, S. W.; White, S. M.; Ling, A. G.

2017-12-01

Forecasting solar energetic (E > 10 MeV) particle (SEP) events is an important element of space weather. While several models have been developed for use in forecasting such events, satellite operations are particularly vulnerable to higher-energy (> 50 MeV) SEP events. Here we validate one model, the proton prediction system (PPS), which extends to that energy range. We first develop a data base of E > 50-MeV proton events > 1.0 proton flux units (pfu) events observed on the GOES satellite over the period 1986 to 2016. We modify the PPS to forecast proton events at the reduced level of 1 pfu and run PPS for four different solar input parameters: (1) all > M5 solar X-ray flares; (2) all > 200 sfu 8800-MHz bursts with associated > M5 flares; (3) all > 500 sfu 8800-MHz bursts; and (4) all > 5000 sfu 8800-MHz bursts. For X-ray flare inputs the forecasted event peak intensities and fluences are compared with observed values. The validation contingency tables and skill scores are calculated for all groups and used as a guide to use of the PPS. We plot the false alarms and missed events as functions of solar source longitude.

Forecast of solar wind parameters according to STOP magnetograph observations

NASA Astrophysics Data System (ADS)

Tlatov, A. G.; Pashchenko, M. P.; Ponyavin, D. I.; Svidskii, P. M.; Peshcherov, V. S.; Demidov, M. L.

2016-12-01

The paper discusses the results of the forecast of solar wind parameters at a distance of 1 AU made according to observations made by the STOP telescope magnetograph during 2014-2015. The Wang-Sheeley-Arge (WSA) empirical model is used to reconstruct the magnetic field topology in the solar corona and estimate the solar wind speed in the interplanetary medium. The proposed model is adapted to STOP magnetograph observations. The results of the calculation of solar wind parameters are compared with ACE satellite measurements. It is shown that the use of STOP observations provides a significant correlation of predicted solar wind speed values with the observed ones.

Cost-Loss Analysis of Ensemble Solar Wind Forecasting: Space Weather Use of Terrestrial Weather Tools

NASA Astrophysics Data System (ADS)

Henley, E. M.; Pope, E. C. D.

2017-12-01

This commentary concerns recent work on solar wind forecasting by Owens and Riley (2017). The approach taken makes effective use of tools commonly used in terrestrial weather—notably, via use of a simple model—generation of an "ensemble" forecast, and application of a "cost-loss" analysis to the resulting probabilistic information, to explore the benefit of this forecast to users with different risk appetites. This commentary aims to highlight these useful techniques to the wider space weather audience and to briefly discuss the general context of application of terrestrial weather approaches to space weather.

a system approach to the long term forecasting of the climat data in baikal region

NASA Astrophysics Data System (ADS)

Abasov, N.; Berezhnykh, T.

2003-04-01

The Angara river running from Baikal with a cascade of hydropower plants built on it plays a peculiar role in economy of the region. With view of high variability of water inflow into the rivers and lakes (long-term low water periods and catastrophic floods) that is due to climatic peculiarities of the water resource formation, a long-term forecasting is developed and applied for risk decreasing at hydropower plants. Methodology and methods of long-term forecasting of natural-climatic processes employs some ideas of the research schools by Academician I.P.Druzhinin and Prof. A.P.Reznikhov and consists in detailed investigation of cause-effect relations, finding out physical analogs and their application to formalized methods of long-term forecasting. They are divided into qualitative (background method; method of analogs based on solar activity), probabilistic and approximative methods (analog-similarity relations; discrete-continuous model). These forecasting methods have been implemented in the form of analytical aids of the information-forecasting software "GIPSAR" that provides for some elements of artificial intelligence. Background forecasts of the runoff of the Ob, the Yenisei, the Angara Rivers in the south of Siberia are based on space-time regularities that were revealed on taking account of the phase shifts in occurrence of secular maxima and minima on integral-difference curves of many-year hydrological processes in objects compared. Solar activity plays an essential role in investigations of global variations of climatic processes. Its consideration in the method of superimposed epochs has allowed a conclusion to be made on the higher probability of the low-water period in the actual inflow to Lake Baikal that takes place on the increasing branch of solar activity of its 11-year cycle. The higher probability of a high-water period is observed on the decreasing branch of solar activity from the 2nd to the 5th year after its maximum. Probabilistic method of forecasting (with a year in advance) is based on the property of alternation of series of years with increase and decrease in the observed indicators (characteristic indices) of natural processes. Most of the series (98.4-99.6%) are represented by series of one to three years. The problem of forecasting is divided into two parts: 1) qualitative forecast of the probability that the started series will either continue or be replaced by a new series during the next year that is based on the frequency characteristics of series of years with increase or decrease of the forecasted sequence); 2) quantitative estimate of the forecasted value in the form of a curve of conditional frequencies is made on the base of intra-sequence interrelations among hydrometeorological elements by their differentiation with respect to series of years of increase or decrease, by construction of particular curves of conditional frequencies of the runoff for each expected variant of series development and by subsequent construction a generalized curve. Approximative learning methods form forecasted trajectories of the studied process indices for a long-term perspective. The method of analog-similarity relations is based on the fact that long periods of observations reveal some similarities in the character of variability of indices for some fragments of the sequence x (t) by definite criteria. The idea of the method is to estimate similarity of such fragments of the sequence that have been called the analogs. The method applies multistage optimization of both external parameters (e.g. the number of iterations of the sliding averaging needed to decompose the sequence into two components: the smoothed one with isolated periodic oscillations and the residual or random one). The method is applicable to current terms of forecasts and ending with the double solar cycle. Using a special procedure of integration, it separates terms with the best results for the given optimization subsample. Several optimal vectors of parameters obtained are tested on the examination (verifying) subsample. If the procedure is successful, the forecast is immediately made by integration of several best solutions. Peculiarities of forecasting extreme processes. Methods of long-term forecasting allow the sufficiently reliable forecasts to be made within the interval of xmin+Δ_1, xmax - Δ_2 (i.e. in the interval of medium values of indices). Meanwhile, in the intervals close to extreme ones, reliability of forecasts is substantially lower. While for medium values the statistics of the100-year sequence gives acceptable results owing to a sufficiently large number of revealed analogs that correspond to prognostic samples, for extreme values the situation is quite different, first of all by virtue of poverty of statistical data. Decreasing the values of Δ_1,Δ_2: Δ_1,Δ_2 rightarrow 0 (by including them into optimization parameters of the considered forecasting methods) could be one of the ways to improve reliability of forecasts. Partially, such an approach has been realized in the method of analog-similarity relations, giving the possibility to form a range of possible forecasted trajectories in two variants - from the minimum possible trajectory to the maximum possible one. Reliability of long-term forecasts. Both the methodology and the methods considered above have been realized as the information-forecasting system "GIPSAR". The system includes some tools implementing several methods of forecasting, analysis of initial and forecasted information, a developed database, a set of tools for verification of algorithms, additional information on the algorithms of statistical processing of sequences (sliding averaging, integral-difference curves, etc.), aids to organize input of initial information (in its various forms) as well as aids to draw up output prognostic documents. Risk management. The normal functioning of the Angara cascade is periodically interrupted by risks of two types that take place in the Baikal, the Bratsk and Ust-Ilimsk reservoirs: long low-water periods and sudden periods of extremely high water levels. For example, low-water periods, observed in the reservoirs of the Angara cascade can be classified under four risk categories : 1 - acceptable (negligible reduction of electric power generation by hydropower plants; certain difficulty in meeting environmental and navigation requirements); 2 - significant (substantial reduction of electric power generation by hydropower plants; certain restriction on water releases for navigation; violation of environmental requirements in some years); 3 - emergency (big losses in electric power generation; limited electricity supply to large consumers; significant restriction of water releases for navigation; threat of exposure of drinkable water intake works; violation of environmental requirements for a number of years); 4 - catastrophic (energy crisis; social crisis exposure of drinkable water intake works; termination of navigation; environmental catastrophe). Management of energy systems consists in operative, many-year regulation and perspective planning and has to take into account the analysis of operative data (water reserves in reservoirs), long-term statistics and relations among natural processes and also forecasts - short-term (for a day, week, decade), long-term and/or super-long-term (from a month to several decades). Such natural processes as water inflow to reservoirs, air temperatures during heating periods depend in turn on external factors: prevailing types of atmospheric circulation, intensity of the 11- and 22-year cycles of solar activity, volcanic activity, interaction between the ocean and atmosphere, etc. Until recently despite the formed scientific schools on long-term forecasting (I.P.Druzhinin, A.P.Reznikhov) the energy system management has been based on specially drawn dispatching schedules and long-term hydrometeorological forecasts only without attraction of perspective forecasted indices. Insertion of a parallel block of forecast (based on the analysis of data on natural processes and special methods of forecasting) into the scheme can largely smooth unfavorable consequences from the impact of natural processes on sustainable development of energy systems and especially on its safe operation. However, the requirements to reliability and accuracy of long-term forecasts significantly increase. The considered approach to long term forecasting can be used for prediction: mean winter and summer air temperatures, droughts and wood fires.

Toward the Probabilistic Forecasting of High-latitude GPS Phase Scintillation

NASA Technical Reports Server (NTRS)

Prikryl, P.; Jayachandran, P.T.; Mushini, S. C.; Richardson, I. G.

2012-01-01

The phase scintillation index was obtained from L1 GPS data collected with the Canadian High Arctic Ionospheric Network (CHAIN) during years of extended solar minimum 2008-2010. Phase scintillation occurs predominantly on the dayside in the cusp and in the nightside auroral oval. We set forth a probabilistic forecast method of phase scintillation in the cusp based on the arrival time of either solar wind corotating interaction regions (CIRs) or interplanetary coronal mass ejections (ICMEs). CIRs on the leading edge of high-speed streams (HSS) from coronal holes are known to cause recurrent geomagnetic and ionospheric disturbances that can be forecast one or several solar rotations in advance. Superposed epoch analysis of phase scintillation occurrence showed a sharp increase in scintillation occurrence just after the arrival of high-speed solar wind and a peak associated with weak to moderate CMEs during the solar minimum. Cumulative probability distribution functions for the phase scintillation occurrence in the cusp are obtained from statistical data for days before and after CIR and ICME arrivals. The probability curves are also specified for low and high (below and above median) values of various solar wind plasma parameters. The initial results are used to demonstrate a forecasting technique on two example periods of CIRs and ICMEs.

The "Sigmoid Sniffer” and the "Advanced Automated Solar Filament Detection and Characterization Code” Modules

NASA Astrophysics Data System (ADS)

Raouafi, Noureddine; Bernasconi, P. N.; Georgoulis, M. K.

2010-05-01

We present two pattern recognition algorithms, the "Sigmoid Sniffer” and the "Advanced Automated Solar Filament Detection and Characterization Code,” that are among the Feature Finding modules of the Solar Dynamic Observatory: 1) Coronal sigmoids visible in X-rays and the EUV are the result of highly twisted magnetic fields. They can occur anywhere on the solar disk and are closely related to solar eruptive activity (e.g., flares, CMEs). Their appearance is typically synonym of imminent solar eruptions, so they can serve as a tool to forecast solar activity. Automatic X-ray sigmoid identification offers an unbiased way of detecting short-to-mid term CME precursors. The "Sigmoid Sniffer” module is capable of automatically detecting sigmoids in full-disk X-ray images and determining their chirality, as well as other characteristics. It uses multiple thresholds to identify persistent bright structures on a full-disk X-ray image of the Sun. We plan to apply the code to X-ray images from Hinode/XRT, as well as on SDO/AIA images. When implemented in a near real-time environment, the Sigmoid Sniffer could allow 3-7 day forecasts of CMEs and their potential to cause major geomagnetic storms. 2)The "Advanced Automated Solar Filament Detection and Characterization Code” aims to identify, classify, and track solar filaments in full-disk Hα images. The code can reliably identify filaments; determine their chirality and other relevant parameters like filament area, length, and average orientation with respect to the equator. It is also capable of tracking the day-by-day evolution of filaments as they traverse the visible disk. The code was tested by analyzing daily Hα images taken at the Big Bear Solar Observatory from mid-2000 to early-2005. It identified and established the chirality of thousands of filaments without human intervention.

The real-time SEP forecasting tools of the 'HESPERIA' HORIZON 2020 project

NASA Astrophysics Data System (ADS)

Malandraki, Olga E.; Nunez, Marlon; Heber, Bernd; Labrenz, Johannes; Posner, Arik; Milas, Nick; Tsiropoula, Georgia; Pavlos, Evgenios; Sarlanis, Christos

2017-04-01

In this study, we describe the two real-time prediction tools, that have been developed in the framework of the HESPERIA project based upon the proven concepts UMASEP and REleASE. A major impact on human and robotic space exploration activities is the sudden and prompt occurrence of solar energetic ion events. The fact that near-relativistic electrons (1 MeV electrons have 95% of the speed of light) travel faster than ions (30 MeV protons have 25% of the speed of light) and are always present in Solar Energetic Particle (SEP) events can be used to forecast the arrival of protons from SEP events with real-time measurements of near relativistic electrons. The faster electrons arrive at L1 30 to 90 minutes before the slower protons. The Relativistic Electron Alert System for Exploration (REleASE) forecasting scheme (Posner, 2007) uses this effect to predict the proton flux by utilizing the actual electron flux and the increase of the electron flux in the last 60 minutes. In the framework of the HESPERIA project, a clone of the REleASE system was built in the open source programming language PYTHON. The same forecasting principle with use of the same forecasting matrices were in addition adapted to real-time electron flux measurements from the Electron, Proton & Alpha Monitor (EPAM) onboard the Advanced Composition Explorer (ACE). It is shown, that the REleASE forecasting scheme can be adapted to work with any near relativistic electron flux measurements. Solar energetic particles (SEPs) are sometimes energetic enough and the flux is high enough to cause air showers in the stratosphere and in the troposphere, which are an important ionization source in the atmosphere. >500 MeV solar protons are so energetic that they usually have effects on the ground, producing what is called a Ground Level Enhancement (GLE) event. Within the HESPERIA project a predictor of >500 SEP proton events at the near-earth (e.g. at geostationary orbit) has been developed. In order to predict these events, the UMASEP scheme (Núñez, 2011, 2015) has been used. UMASEP makes a lag-correlation of solar electromagnetic (EM) flux with the particle flux at near-earth. If the correlation is high, the model infers that there is a magnetic connection through which particles are arriving. If, additionally, the intensity of the flux of the associated solar event is also high, then the UMASEP scheme issues a SEP prediction. In the case of the prediction of >500 MeV SEP events, the implemented system, called UMASEP-500, correlates X-ray flux with each of the differential proton fluxes measured by the GOES satellites, and with each of the neutron density fluxes collected by neutron monitor stations around the world. When the correlation estimation surpasses a threshold, and the associated flare is greater than a specific X-ray peak flux, a >500 MeV SEP forecast is issued. Both forecasting tools are operational under the HESPERIA server maintained at the National Observatory of Athens. Acknowledgement: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 637324 (HESPERIA project).

A Comparative Verification of Forecasts from Two Operational Solar Wind Models

DTIC Science & Technology

2010-12-16

knowing how much confidence to place on predicted parameters. Cost /benefit information is provided to administrators who decide to sustain or...components of the magnetic field vector in the geocentric solar magnetospheric (GSM) coordinate system at each hour of forecast time. For an example of a

Solar Storm GIC Forecasting: Solar Shield Extension Development of the End-User Forecasting System Requirements

NASA Technical Reports Server (NTRS)

Pulkkinen, A.; Mahmood, S.; Ngwira, C.; Balch, C.; Lordan, R.; Fugate, D.; Jacobs, W.; Honkonen, I.

2015-01-01

A NASA Goddard Space Flight Center Heliophysics Science Division-led team that includes NOAA Space Weather Prediction Center, the Catholic University of America, Electric Power Research Institute (EPRI), and Electric Research and Management, Inc., recently partnered with the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) to better understand the impact of Geomagnetically Induced Currents (GIC) on the electric power industry. This effort builds on a previous NASA-sponsored Applied Sciences Program for predicting GIC, known as Solar Shield. The focus of the new DHS S&T funded effort is to revise and extend the existing Solar Shield system to enhance its forecasting capability and provide tailored, timely, actionable information for electric utility decision makers. To enhance the forecasting capabilities of the new Solar Shield, a key undertaking is to extend the prediction system coverage across Contiguous United States (CONUS), as the previous version was only applicable to high latitudes. The team also leverages the latest enhancements in space weather modeling capacity residing at Community Coordinated Modeling Center to increase the Technological Readiness Level, or Applications Readiness Level of the system http://www.nasa.gov/sites/default/files/files/ExpandedARLDefinitions4813.pdf.

Impact of the 4 April 2014 Saharan dust outbreak on the photovoltaic power generation in Germany

NASA Astrophysics Data System (ADS)

Rieger, Daniel; Steiner, Andrea; Bachmann, Vanessa; Gasch, Philipp; Förstner, Jochen; Deetz, Konrad; Vogel, Bernhard; Vogel, Heike

2017-11-01

The importance for reliable forecasts of incoming solar radiation is growing rapidly, especially for those countries with an increasing share in photovoltaic (PV) power production. The reliability of solar radiation forecasts depends mainly on the representation of clouds and aerosol particles absorbing and scattering radiation. Especially under extreme aerosol conditions, numerical weather prediction has a systematic bias in the solar radiation forecast. This is caused by the design of numerical weather prediction models, which typically account for the direct impact of aerosol particles on radiation using climatological mean values and the impact on cloud formation assuming spatially and temporally homogeneous aerosol concentrations. These model deficiencies in turn can lead to significant economic losses under extreme aerosol conditions. For Germany, Saharan dust outbreaks occurring 5 to 15 times per year for several days each are prominent examples for conditions, under which numerical weather prediction struggles to forecast solar radiation adequately. We investigate the impact of mineral dust on the PV-power generation during a Saharan dust outbreak over Germany on 4 April 2014 using ICON-ART, which is the current German numerical weather prediction model extended by modules accounting for trace substances and related feedback processes. We find an overall improvement of the PV-power forecast for 65 % of the pyranometer stations in Germany. Of the nine stations with very high differences between forecast and measurement, eight stations show an improvement. Furthermore, we quantify the direct radiative effects and indirect radiative effects of mineral dust. For our study, direct effects account for 64 %, indirect effects for 20 % and synergistic interaction effects for 16 % of the differences between the forecast including mineral dust radiative effects and the forecast neglecting mineral dust.

Spring-fall asymmetry of substorm strength, geomagnetic activity and solar wind: Implications for semiannual variation and solar hemispheric asymmetry

USGS Publications Warehouse

Marsula, K.; Tanskanen, E.; Love, J.J.

2011-01-01

We study the seasonal variation of substorms, geomagnetic activity and their solar wind drivers in 1993–2008. The number of substorms and substorm mean duration depict an annual variation with maxima in Winter and Summer, respectively, reflecting the annual change of the local ionosphere. In contradiction, substorm mean amplitude, substorm total efficiency and global geomagnetic activity show a dominant annual variation, with equinoctial maxima alternating between Spring in solar cycle 22 and Fall in cycle 23. The largest annual variations were found in 1994 and 2003, in the declining phase of the two cycles when high-speed streams dominate the solar wind. A similar, large annual variation is found in the solar wind driver of substorms and geomagnetic activity, which implies that the annual variation of substorm strength, substorm efficiency and geomagnetic activity is not due to ionospheric conditions but to a hemispherically asymmetric distribution of solar wind which varies from one cycle to another. Our results imply that the overall semiannual variation in global geomagnetic activity has been seriously overestimated, and is largely an artifact of the dominant annual variation with maxima alternating between Spring and Fall. The results also suggest an intimate connection between the asymmetry of solar magnetic fields and some of the largest geomagnetic disturbances, offering interesting new pathways for forecasting disturbances with a longer lead time to the future.

A Semi-Empirical Model for Forecasting Relativistic Electrons at Geostationary Orbit

NASA Technical Reports Server (NTRS)

Lyatsky, Wladislaw; Khazanov, George V.

2008-01-01

We developed a new prediction model for forecasting relativistic (>2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/Interplanetary Magnetic Field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is about 0.9. The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible. The correlation coefficient between predicted and actual electron fluxes is stable and incredibly high.

Short-term solar flare prediction using image-case-based reasoning

NASA Astrophysics Data System (ADS)

Liu, Jin-Fu; Li, Fei; Zhang, Huai-Peng; Yu, Da-Ren

2017-10-01

Solar flares strongly influence space weather and human activities, and their prediction is highly complex. The existing solutions such as data based approaches and model based approaches have a common shortcoming which is the lack of human engagement in the forecasting process. An image-case-based reasoning method is introduced to achieve this goal. The image case library is composed of SOHO/MDI longitudinal magnetograms, the images from which exhibit the maximum horizontal gradient, the length of the neutral line and the number of singular points that are extracted for retrieving similar image cases. Genetic optimization algorithms are employed for optimizing the weight assignment for image features and the number of similar image cases retrieved. Similar image cases and prediction results derived by majority voting for these similar image cases are output and shown to the forecaster in order to integrate his/her experience with the final prediction results. Experimental results demonstrate that the case-based reasoning approach has slightly better performance than other methods, and is more efficient with forecasts improved by humans.

Solar Resource Assessment with Sky Imagery and a Virtual Testbed for Sky Imager Solar Forecasting

NASA Astrophysics Data System (ADS)

Kurtz, Benjamin Bernard

In recent years, ground-based sky imagers have emerged as a promising tool for forecasting solar energy on short time scales (0 to 30 minutes ahead). Following the development of sky imager hardware and algorithms at UC San Diego, we present three new or improved algorithms for sky imager forecasting and forecast evaluation. First, we present an algorithm for measuring irradiance with a sky imager. Sky imager forecasts are often used in conjunction with other instruments for measuring irradiance, so this has the potential to decrease instrumentation costs and logistical complexity. In particular, the forecast algorithm itself often relies on knowledge of the current irradiance which can now be provided directly from the sky images. Irradiance measurements are accurate to within about 10%. Second, we demonstrate a virtual sky imager testbed that can be used for validating and enhancing the forecast algorithm. The testbed uses high-quality (but slow) simulations to produce virtual clouds and sky images. Because virtual cloud locations are known, much more advanced validation procedures are possible with the virtual testbed than with measured data. In this way, we are able to determine that camera geometry and non-uniform evolution of the cloud field are the two largest sources of forecast error. Finally, with the assistance of the virtual sky imager testbed, we develop improvements to the cloud advection model used for forecasting. The new advection schemes are 10-20% better at short time horizons.

STEREO as a "Planetary Hazards" Mission

NASA Technical Reports Server (NTRS)

Guhathakurta, M.; Thompson, B. J.

2014-01-01

NASA's twin STEREO probes, launched in 2006, have advanced the art and science of space weather forecasting more than any other spacecraft or solar observatory. By surrounding the Sun, they provide previously-impossible early warnings of threats approaching Earth as they develop on the solar far side. They have also revealed the 3D shape and inner structure of CMEs-massive solar storms that can trigger geomagnetic storms when they collide with Earth. This improves the ability of forecasters to anticipate the timing and severity of such events. Moreover, the unique capability of STEREO to track CMEs in three dimensions allows forecasters to make predictions for other planets, giving rise to the possibility of interplanetary space weather forecasting too. STEREO is one of those rare missions for which "planetary hazards" refers to more than one world. The STEREO probes also hold promise for the study of comets and potentially hazardous asteroids.

A COMPARISON OF FLARE FORECASTING METHODS. I. RESULTS FROM THE “ALL-CLEAR” WORKSHOP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnes, G.; Leka, K. D.; Dunn, T.

2016-10-01

Solar flares produce radiation that can have an almost immediate effect on the near-Earth environment, making it crucial to forecast flares in order to mitigate their negative effects. The number of published approaches to flare forecasting using photospheric magnetic field observations has proliferated, with varying claims about how well each works. Because of the different analysis techniques and data sets used, it is essentially impossible to compare the results from the literature. This problem is exacerbated by the low event rates of large solar flares. The challenges of forecasting rare events have long been recognized in the meteorology community, butmore » have yet to be fully acknowledged by the space weather community. During the interagency workshop on “all clear” forecasts held in Boulder, CO in 2009, the performance of a number of existing algorithms was compared on common data sets, specifically line-of-sight magnetic field and continuum intensity images from the Michelson Doppler Imager, with consistent definitions of what constitutes an event. We demonstrate the importance of making such systematic comparisons, and of using standard verification statistics to determine what constitutes a good prediction scheme. When a comparison was made in this fashion, no one method clearly outperformed all others, which may in part be due to the strong correlations among the parameters used by different methods to characterize an active region. For M-class flares and above, the set of methods tends toward a weakly positive skill score (as measured with several distinct metrics), with no participating method proving substantially better than climatological forecasts.« less

The Next Level in Automated Solar Flare Forecasting: the EU FLARECAST Project

NASA Astrophysics Data System (ADS)

Georgoulis, M. K.; Bloomfield, D.; Piana, M.; Massone, A. M.; Gallagher, P.; Vilmer, N.; Pariat, E.; Buchlin, E.; Baudin, F.; Csillaghy, A.; Soldati, M.; Sathiapal, H.; Jackson, D.; Alingery, P.; Argoudelis, V.; Benvenuto, F.; Campi, C.; Florios, K.; Gontikakis, C.; Guennou, C.; Guerra, J. A.; Kontogiannis, I.; Latorre, V.; Murray, S.; Park, S. H.; Perasso, A.; Sciacchitano, F.; von Stachelski, S.; Torbica, A.; Vischi, D.

2017-12-01

We attempt an informative description of the Flare Likelihood And Region Eruption Forecasting (FLARECAST) project, European Commission's first large-scale investment to explore the limits of reliability and accuracy achieved for the forecasting of major solar flares. We outline the consortium, top-level objectives and first results of the project, highlighting the diversity and fusion of expertise needed to deliver what was promised. The project's final product, featuring an openly accessible, fully modular and free to download flare forecasting facility will be delivered in early 2018. The project's three objectives, namely, science, research-to-operations and dissemination / communication, are also discussed: in terms of science, we encapsulate our close-to-final assessment on how close (or far) are we from a practically exploitable solar flare forecasting. In terms of R2O, we briefly describe the architecture of the FLARECAST infrastructure that includes rigorous validation for each forecasting step. From the three different communication levers of the project we finally focus on lessons learned from the two-way interaction with the community of stakeholders and governmental organizations. The FLARECAST project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 640216.

Sensor network based solar forecasting using a local vector autoregressive ridge framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, J.; Yoo, S.; Heiser, J.

2016-04-04

The significant improvements and falling costs of photovoltaic (PV) technology make solar energy a promising resource, yet the cloud induced variability of surface solar irradiance inhibits its effective use in grid-tied PV generation. Short-term irradiance forecasting, especially on the minute scale, is critically important for grid system stability and auxiliary power source management. Compared to the trending sky imaging devices, irradiance sensors are inexpensive and easy to deploy but related forecasting methods have not been well researched. The prominent challenge of applying classic time series models on a network of irradiance sensors is to address their varying spatio-temporal correlations duemore » to local changes in cloud conditions. We propose a local vector autoregressive framework with ridge regularization to forecast irradiance without explicitly determining the wind field or cloud movement. By using local training data, our learned forecast model is adaptive to local cloud conditions and by using regularization, we overcome the risk of overfitting from the limited training data. Our systematic experimental results showed an average of 19.7% RMSE and 20.2% MAE improvement over the benchmark Persistent Model for 1-5 minute forecasts on a comprehensive 25-day dataset.« less

Spatial Pattern Classification for More Accurate Forecasting of Variable Energy Resources

NASA Astrophysics Data System (ADS)

Novakovskaia, E.; Hayes, C.; Collier, C.

2014-12-01

The accuracy of solar and wind forecasts is becoming increasingly essential as grid operators continue to integrate additional renewable generation onto the electric grid. Forecast errors affect rate payers, grid operators, wind and solar plant maintenance crews and energy traders through increases in prices, project down time or lost revenue. While extensive and beneficial efforts were undertaken in recent years to improve physical weather models for a broad spectrum of applications these improvements have generally not been sufficient to meet the accuracy demands of system planners. For renewables, these models are often used in conjunction with additional statistical models utilizing both meteorological observations and the power generation data. Forecast accuracy can be dependent on specific weather regimes for a given location. To account for these dependencies it is important that parameterizations used in statistical models change as the regime changes. An automated tool, based on an artificial neural network model, has been developed to identify different weather regimes as they impact power output forecast accuracy at wind or solar farms. In this study, improvements in forecast accuracy were analyzed for varying time horizons for wind farms and utility-scale PV plants located in different geographical regions.

Possibilities of the forecast of generation of the high energy solar protons for the safety of Mars mission

NASA Astrophysics Data System (ADS)

Avakyan, S. V.; Gaponov, V. A.; Nicol'skii, G. A.; Solov'ev, A. A.

2017-06-01

During interplanetary flight, after large solar flares, astronauts are subject to the impact of relativistic solar protons. These particles produce an especially strong effect during extravehicular activity or landing on Mars (in the future). The relativistic protons reach the orbits of the Earth and Mars with a delay of several hours relative to solar X-rays and UV radiation. In this paper, we discuss a new opportunity to predict the most dangerous events caused by Solar Cosmic Rays with protons of maximum (relativistic) energy, known in the of solar-terrestrial physics asGround Level Enhancements or Ground Level Events (GLEs). This new capability is based on a close relationship between the dangerous events and decrease ofTotal Solar Irradiance (TSI)which precedes these events. This important relationship is revealed for the first time.

Understanding Solar Eruptions with SDO/HMI Measuring Photospheric Flows, Testing Models, and Steps Towards Forecasting Solar Eruptions

NASA Technical Reports Server (NTRS)

Schuck, Peter W.; Linton, Mark; Muglach, Karin; Welsch, Brian; Hageman, Jacob

2010-01-01

The imminent launch of Solar Dynamics Observatory (SDO) will carry the first full-disk imaging vector magnetograph, the Helioseismic and Magnetic Imager (HMI), into an inclined geosynchronous orbit. This magnetograph will provide nearly continuous measurements of photospheric vector magnetic fields at cadences of 90 seconds to 12 minutes with I" resolution, precise pointing, and unfettered by atmospheric seeing. The enormous data stream of 1.5 Terabytes per day from SDO will provide an unprecedented opportunity to understand the mysteries of solar eruptions. These ground-breaking observations will permit the application of a new technique, the differential affine velocity estimator for vector magnetograms (DAVE4VM), to measure photospheric plasma flows in active regions. These measurements will permit, for the first time, accurate assessments of the coronal free energy available for driving CMEs and flares. The details of photospheric plasma flows, particularly along magnetic neutral-lines, are critical to testing models for initiating coronal mass ejections (CMEs) and flares. Assimilating flows and fields into state-of-the art 3D MHD simulations that model the highly stratified solar atmosphere from the convection zone to the corona represents the next step towards achieving NASA's Living with a Star forecasting goals of predicting "when a solar eruption leading to a CME will occur." This talk will describe these major science and predictive advances that will be delivered by SDO /HMI.

Understanding Solar Eruptions with SDO/HMI Measuring Photospheric Flows, Testing Models, and Steps Towards Forecasting Solar Eruptions

NASA Technical Reports Server (NTRS)

Schuck, Peter W.; Linton, M.; Muglach, K.; Hoeksema, T.

2010-01-01

The Solar Dynamics Observatory (SDO) is carrying the first full-disk imaging vector magnetograph, the Helioseismic and Magnetic Imager (HMI), into an inclined geosynchronous orbit. This magnetograph will provide nearly continuous measurements of photospheric vector magnetic fields at cadences of 90 seconds to 12 minutes with 1" resolution, precise pointing, and unfettered by atmospheric seeing. The enormous data stream of 1.5 Terabytes per day from SAO will provide an unprecedented opportunity to understand the mysteries of solar eruptions. These ground-breaking observations will permit the application of a new technique, the differential affine velocity estimator for vector magnetograms (DAVE4VM), to measure photospheric plasma flows in active regions. These measurements will permit, for the first time, accurate assessments of the coronal free energy available for driving CMEs and flares. The details of photospheric plasma flows, particularly along magnetic neutral-lines, are critical to testing models for initiating coronal mass ejections (CMEs) and flares. Assimilating flows and fields into state-of-the art 3D MHD simulations that model the highly stratified solar atmosphere from the convection zone to the corona represents the next step towards achieving NASA's Living with a Star forecasting goals of predicting "when a solar eruption leading to a CME will occur." Our presentation will describe these major science and predictive advances that will be delivered by SDO/HMI.

Evaluation of the performance of a meso-scale NWP model to forecast solar irradiance on Reunion Island for photovoltaic power applications

NASA Astrophysics Data System (ADS)

Kalecinski, Natacha; Haeffelin, Martial; Badosa, Jordi; Periard, Christophe

2013-04-01

Solar photovoltaic power is a predominant source of electrical power on Reunion Island, regularly providing near 30% of electrical power demand for a few hours per day. However solar power on Reunion Island is strongly modulated by clouds in small temporal and spatial scales. Today regional regulations require that new solar photovoltaic plants be combined with storage systems to reduce electrical power fluctuations on the grid. Hence cloud and solar irradiance forecasting becomes an important tool to help optimize the operation of new solar photovoltaic plants on Reunion Island. Reunion Island, located in the South West of the Indian Ocean, is exposed to persistent trade winds, most of all in winter. In summer, the southward motion of the ITCZ brings atmospheric instabilities on the island and weakens trade winds. This context together with the complex topography of Reunion Island, which is about 60 km wide, with two high summits (3070 and 2512 m) connected by a 1500 m plateau, makes cloudiness very heterogeneous. High cloudiness variability is found between mountain and coastal areas and between the windward, leeward and lateral regions defined with respect to the synoptic wind direction. A detailed study of local dynamics variability is necessary to better understand cloud life cycles around the island. In the presented work, our approach to explore the short-term solar irradiance forecast at local scales is to use the deterministic output from a meso-scale numerical weather prediction (NWP) model, AROME, developed by Meteo France. To start we evaluate the performance of the deterministic forecast from AROME by using meteorological measurements from 21 meteorological ground stations widely spread around the island (and with altitudes from 8 to 2245 m). Ground measurements include solar irradiation, wind speed and direction, relative humidity, air temperature, precipitation and pressure. Secondly we study in the model the local dynamics and thermodynamics that control cloud development and solar irradiance in order to define new predictors to improve probabilistic forecast of solar irradiance.

Solar Effects of Low-Earth Orbit objects in ORDEM 3.0

NASA Technical Reports Server (NTRS)

Vavrin, A. B.; Anz-Meador, P.; Kelley, R. L.

2014-01-01

Variances in atmospheric density are directly related to the variances in solar flux intensity between 11- year solar cycles. The Orbital Debris Engineering Model (ORDEM 3.0) uses a solar flux table as input for calculating orbital lifetime of intact and debris objects in Low-Earth Orbit. Long term projections in solar flux activity developed by the NASA Orbital Debris Program Office (ODPO) extend the National Oceanic and Atmospheric Administration Space Environment Center (NOAA/SEC) daily historical flux values with a 5-year projection. For purposes of programmatic scheduling, the Q2 2009 solar flux table was chosen for ORDEM 3.0. Current solar flux activity shows that the current solar cycle has entered a period of lower solar flux intensity than previously forecasted in 2009. This results in a deviation of the true orbital debris environment propagation in ORDEM 3.0. In this paper, we present updated orbital debris populations in LEO using the latest solar flux values. We discuss the effects on recent breakup events such as the FY-1C anti-satellite test and the Iridium 33 / Cosmos 2251 accidental collision. Justifications for chosen solar flux tables are discussed.

Solar radio bursts as a tool for space weather forecasting

NASA Astrophysics Data System (ADS)

Klein, Karl-Ludwig; Matamoros, Carolina Salas; Zucca, Pietro

2018-01-01

The solar corona and its activity induce disturbances that may affect the space environment of the Earth. Noticeable disturbances come from coronal mass ejections (CMEs), which are large-scale ejections of plasma and magnetic fields from the solar corona, and solar energetic particles (SEPs). These particles are accelerated during the explosive variation of the coronal magnetic field or at the shock wave driven by a fast CME. In this contribution, it is illustrated how full Sun microwave observations can lead to (1) an estimate of CME speeds and of the arrival time of the CME at the Earth, (2) the prediction of SEP events attaining the Earth. xml:lang="fr"

Advanced solar irradiances applied to satellite and ionospheric operational systems

NASA Astrophysics Data System (ADS)

Tobiska, W. Kent; Schunk, Robert; Eccles, Vince; Bouwer, Dave

Satellite and ionospheric operational systems require solar irradiances in a variety of time scales and spectral formats. We describe the development of a system using operational grade solar irradiances that are applied to empirical thermospheric density models and physics-based ionospheric models used by operational systems that require a space weather characterization. The SOLAR2000 (S2K) and SOLARFLARE (SFLR) models developed by Space Environment Technologies (SET) provide solar irradiances from the soft X-rays (XUV) through the Far Ultraviolet (FUV) spectrum. The irradiances are provided as integrated indices for the JB2006 empirical atmosphere density models and as line/band spectral irradiances for the physics-based Ionosphere Forecast Model (IFM) developed by the Space Environment Corporation (SEC). We describe the integration of these irradiances in historical, current epoch, and forecast modes through the Communication Alert and Prediction System (CAPS). CAPS provides real-time and forecast HF radio availability for global and regional users and global total electron content (TEC) conditions.

The use of satellite data assimilation methods in regional NWP for solar irradiance forecasting

NASA Astrophysics Data System (ADS)

Kurzrock, Frederik; Cros, Sylvain; Chane-Ming, Fabrice; Potthast, Roland; Linguet, Laurent; Sébastien, Nicolas

2016-04-01

As an intermittent energy source, the injection of solar power into electricity grids requires irradiance forecasting in order to ensure grid stability. On time scales of more than six hours ahead, numerical weather prediction (NWP) is recognized as the most appropriate solution. However, the current representation of clouds in NWP models is not sufficiently precise for an accurate forecast of solar irradiance at ground level. Dynamical downscaling does not necessarily increase the quality of irradiance forecasts. Furthermore, incorrectly simulated cloud evolution is often the cause of inaccurate atmospheric analyses. In non-interconnected tropical areas, the large amplitudes of solar irradiance variability provide abundant solar yield but present significant problems for grid safety. Irradiance forecasting is particularly important for solar power stakeholders in these regions where PV electricity penetration is increasing. At the same time, NWP is markedly more challenging in tropic areas than in mid-latitudes due to the special characteristics of tropical homogeneous convective air masses. Numerous data assimilation methods and strategies have evolved and been applied to a large variety of global and regional NWP models in the recent decades. Assimilating data from geostationary meteorological satellites is an appropriate approach. Indeed, models converting radiances measured by satellites into cloud properties already exist. Moreover, data are available at high temporal frequencies, which enable a pertinent cloud cover evolution modelling for solar energy forecasts. In this work, we present a survey of different approaches which aim at improving cloud cover forecasts using the assimilation of geostationary meteorological satellite data into regional NWP models. Various approaches have been applied to a variety of models and satellites and in different regions of the world. Current methods focus on the assimilation of cloud-top information, derived from infrared channels. For example, those information have been directly assimilated by modifying the water vapour profile in the initial conditions of the WRF model in California using GOES satellite imagery. In Europe, the assimilation of cloud-top height and relative humidity has been performed in an indirect approach using an ensemble Kalman filter. In this case Meteosat SEVIRI cloud information has been assimilated in the COSMO model. Although such methods generally provide improved cloud cover forecasts in mid-latitudes, the major limitation is that only clear-sky or completely cloudy cases can be considered. Indeed, fractional clouds cause a measured signal mixing cold clouds and warmer Earth surface. If the model's initial state is directly forced by cloud properties observed by satellite, the changed model fields have to be smoothed in order to avoid numerical instability. Other crucial aspects which influence forecast quality in the case of satellite radiance assimilation are channel selection, bias and error treatment. The overall promising satellite data assimilation methods in regional NWP have not yet been explicitly applied and tested under tropical conditions. Therefore, a deeper understanding on the benefits of such methods is necessary to improve irradiance forecast schemes.

Using Science Data and Models for Space Weather Forecasting - Challenges and Opportunities

NASA Technical Reports Server (NTRS)

Hesse, Michael; Pulkkinen, Antti; Zheng, Yihua; Maddox, Marlo; Berrios, David; Taktakishvili, Sandro; Kuznetsova, Masha; Chulaki, Anna; Lee, Hyesook; Mullinix, Rick;

The solar magnetic activity band interaction and instabilities that shape quasi-periodic variability

PubMed Central

McIntosh, Scott W.; Leamon, Robert J.; Krista, Larisza D.; Title, Alan M.; Hudson, Hugh S.; Riley, Pete; Harder, Jerald W.; Kopp, Greg; Snow, Martin; Woods, Thomas N.; Kasper, Justin C.; Stevens, Michael L.; Ulrich, Roger K.

2015-01-01

Solar magnetism displays a host of variational timescales of which the enigmatic 11-year sunspot cycle is most prominent. Recent work has demonstrated that the sunspot cycle can be explained in terms of the intra- and extra-hemispheric interaction between the overlapping activity bands of the 22-year magnetic polarity cycle. Those activity bands appear to be driven by the rotation of the Sun's deep interior. Here we deduce that activity band interaction can qualitatively explain the ‘Gnevyshev Gap'—a well-established feature of flare and sunspot occurrence. Strong quasi-annual variability in the number of flares, coronal mass ejections, the radiative and particulate environment of the heliosphere is also observed. We infer that this secondary variability is driven by surges of magnetism from the activity bands. Understanding the formation, interaction and instability of these activity bands will considerably improve forecast capability in space weather and solar activity over a range of timescales. PMID:25849045

An early solar dynamo prediction: Cycle 23 is approximately cycle 22

NASA Technical Reports Server (NTRS)

Schatten, Kenneth H.; Pesnell, W. Dean

1993-01-01

In this paper, we briefly review the 'dynamo' and 'geomagnetic precursor' methods of long-term solar activity forecasting. These methods depend upon the most basic aspect of dynamo theory to predict future activity, future magnetic field arises directly from the magnification of pre-existing magnetic field. We then generalize the dynamo technique, allowing the method to be used at any phase of the solar cycle, through the development of the 'Solar Dynamo Amplitude' (SODA) index. This index is sensitive to the magnetic flux trapped within the Sun's convection zone but insensitive to the phase of the solar cycle. Since magnetic fields inside the Sun can become buoyant, one may think of the acronym SODA as describing the amount of buoyant flux. Using the present value of the SODA index, we estimate that the next cycle's smoothed peak activity will be about 210 +/- 30 solar flux units for the 10.7 cm radio flux and a sunspot number of 170 +/- 25. This suggests that solar cycle #23 will be large, comparable to cycle #22. The estimated peak is expected to occur near 1999.7 +/- 1 year. Since the current approach is novel (using data prior to solar minimum), these estimates may improve when the upcoming solar minimum is reached.

A unified high-resolution wind and solar dataset from a rapidly updating numerical weather prediction model

DOE PAGES

James, Eric P.; Benjamin, Stanley G.; Marquis, Melinda

2016-10-28

A new gridded dataset for wind and solar resource estimation over the contiguous United States has been derived from hourly updated 1-h forecasts from the National Oceanic and Atmospheric Administration High-Resolution Rapid Refresh (HRRR) 3-km model composited over a three-year period (approximately 22 000 forecast model runs). The unique dataset features hourly data assimilation, and provides physically consistent wind and solar estimates for the renewable energy industry. The wind resource dataset shows strong similarity to that previously provided by a Department of Energy-funded study, and it includes estimates in southern Canada and northern Mexico. The solar resource dataset represents anmore » initial step towards application-specific fields such as global horizontal and direct normal irradiance. This combined dataset will continue to be augmented with new forecast data from the advanced HRRR atmospheric/land-surface model.« less

New insights on short-term solar irradiance forecast for space weather applications

NASA Astrophysics Data System (ADS)

Vieira, L. A.; Dudok de Wit, T.; Balmaceda, L. A.; Dal Lago, A.; Da Silva, L. A.; Gonzalez, W. D.

2013-12-01

The conditions of the thermosphere, the ionosphere, the neutral atmosphere, and the oceans on time scales from days to millennia are highly dependent on the solar electromagnetic output, the solar irradiance. The development of physics-based solar irradiance models during the last decade improved significantly our understanding of the solar forcing on Earth's climate. These models are based on the assumption that most of the solar irradiance variability is related to the magnetic field structure of the Sun. Recently, these models were extended to allow short-term forecast (1 to 15 days) of the total and spectral solar irradiance. The extension of the irradiance models is based on solar surface magnetic flux models and/or artificial neural network models. Here, we discuss in details the irradiance forecast models based on observations of the solar surface magnetic field realized by the HMI instrument on board of SDO spacecraft. We constrained and validated the models by comparing the output of the models and observations of the solar irradiance made by instruments onboard The SORCE spacecraft. This study received funding from the European Community's Seventh Framework Programme (FP7/2007-2013, FP7-SPACE-2010-1) under the grant agreement nrs. 218816 (SOTERIA project, www.soteria-space.eu) and 261948 (ATMOP,www.atmop.eu), and by the CNPq/Brazil under the grant number 312488/2012-2. We also gratefully thank the instrument teams for making their data available.

Future mission studies: Forecasting solar flux directly from its chaotic time series

NASA Technical Reports Server (NTRS)

Ashrafi, S.

1991-01-01

The mathematical structure of the programs written to construct a nonlinear predictive model to forecast solar flux directly from its time series without reference to any underlying solar physics is presented. This method and the programs are written so that one could apply the same technique to forecast other chaotic time series, such as geomagnetic data, attitude and orbit data, and even financial indexes and stock market data. Perhaps the most important application of this technique to flight dynamics is to model Goddard Trajectory Determination System (GTDS) output of residues between observed position of spacecraft and calculated position with no drag (drag flag = off). This would result in a new model of drag working directly from observed data.

Forecasting space weather over short horizons: Revised and updated estimates

NASA Astrophysics Data System (ADS)

Reikard, Gordon

2018-07-01

Space weather reflects multiple causes. There is a clear influence for the sun on the near-earth environment. Solar activity shows evidence of chaotic properties, implying that prediction may be limited beyond short horizons. At the same time, geomagnetic activity also reflects the rotation of the earth's core, and local currents in the ionosphere. The combination of influences means that geomagnetic indexes behave like multifractals, exhibiting nonlinear variability, with intermittent outliers. This study tests a range of models: regressions, neural networks, and a frequency domain algorithm. Forecasting tests are run for sunspots and irradiance from 1820 onward, for the Aa geomagnetic index from 1868 onward, and the Am index from 1959 onward, over horizons of 1-7 days. For irradiance and sunspots, persistence actually does better over short horizons. None of the other models really dominate. For the geomagnetic indexes, the persistence method does badly, while the neural net also shows large errors. The remaining models all achieve about the same level of accuracy. The errors are in the range of 48% at 1 day, and 54% at all later horizons. Additional tests are run over horizons of 1-4 weeks. At 1 week, the best models reduce the error to about 35%. Over horizons of four weeks, the model errors increase. The findings are somewhat pessimistic. Over short horizons, geomagnetic activity exhibits so much random variation that the forecast errors are extremely high. Over slightly longer horizons, there is some improvement from estimating in the frequency domain, but not a great deal. Including solar activity in the models does not yield any improvement in accuracy.

Ionospheric ion temperature forecasting in multiples of 27 days

NASA Astrophysics Data System (ADS)

Sojka, Jan J.; Schunk, Robert W.; Nicolls, Michael J.

2014-03-01

The ionospheric variability found at auroral locations is usually assumed to be unpredictable. The magnetosphere, which drives this ionospheric variability via storms and substorms, is at best only qualitatively describable. In this study we demonstrate that over a 3 year period, ionospheric variability observed from Poker Flat, Alaska, has, in fact, a high degree of long-term predictability. The observations used in this study are (a) the solar wind high speed stream velocity measured by the NASA Advanced Composition Explorer satellite, used to define the corotating interaction region (CIR), and (b) the ion temperature at 300 km altitude measured by the National Science Foundation Poker Flat Incoherent Scatter Radar over Poker Flat, Alaska. After determining a seasonal and diurnal climatology for the ion temperature, we show that the residual ion temperature heating events occur synchronously with CIR-geospace interactions. Furthermore, we demonstrate examples of ion temperature forecasting at 27, 54, and 81 days. A rudimentary operational forecasting scenario is described for forecasting recurrence 27 days ahead for the CIR-generated geomagnetic storms. These forecasts apply specifically to satellite tracking operations (thermospheric drag) and emergency HF-radio communications (ionospheric modifications) in the polar regions. The forecast is based on present-day solar and solar wind observations that can be used to uniquely identify the coronal hole and its CIR. From this CIR epoch, a 27 day forecast is then made.

Optimization of Evaporative Demand Models for Seasonal Drought Forecasting

NASA Astrophysics Data System (ADS)

McEvoy, D.; Huntington, J. L.; Hobbins, M.

2015-12-01

Providing reliable seasonal drought forecasts continues to pose a major challenge for scientists, end-users, and the water resources and agricultural communities. Precipitation (Prcp) forecasts beyond weather time scales are largely unreliable, so exploring new avenues to improve seasonal drought prediction is necessary to move towards applications and decision-making based on seasonal forecasts. A recent study has shown that evaporative demand (E0) anomaly forecasts from the Climate Forecast System Version 2 (CFSv2) are consistently more skillful than Prcp anomaly forecasts during drought events over CONUS, and E0 drought forecasts may be particularly useful during the growing season in the farming belts of the central and Midwestern CONUS. For this recent study, we used CFSv2 reforecasts to assess the skill of E0 and of its individual drivers (temperature, humidity, wind speed, and solar radiation), using the American Society for Civil Engineers Standardized Reference Evapotranspiration (ET0) Equation. Moderate skill was found in ET0, temperature, and humidity, with lesser skill in solar radiation, and no skill in wind. Therefore, forecasts of E0 based on models with no wind or solar radiation inputs may prove to be more skillful than the ASCE ET0. For this presentation we evaluate CFSv2 E0 reforecasts (1982-2009) from three different E0 models: (1) ASCE ET0; (2) Hargreaves and Samani (ET-HS), which is estimated from maximum and minimum temperature alone; and (3) Valiantzas (ET-V), which is a modified version of the Penman method for use when wind speed data are not available (or of poor quality) and is driven only by temperature, humidity, and solar radiation. The University of Idaho's gridded meteorological data (METDATA) were used as observations to evaluate CFSv2 and also to determine if ET0, ET-HS, and ET-V identify similar historical drought periods. We focus specifically on CFSv2 lead times of one, two, and three months, and season one forecasts; which are time scales with moderate skill and are more likely to be used in hydro-climatic applications and decision-making.

Hindcast and forecast of grand solar minina and maxima using a three-frequency dynamo model based on Jupiter-Saturn tidal frequencies modulating the 11-year sunspot cycle

NASA Astrophysics Data System (ADS)

Scafetta, Nicola

2016-04-01

The Schwabe frequency band of the Zurich sunspot record since 1749 is found to be made of three major cycles with periods of about 9.98, 10.9 and 11.86 years. The two side frequencies appear to be closely related to the spring tidal period of Jupiter and Saturn (range between 9.5 and 10.5 years, and median 9.93 years) and to the tidal sidereal period of Jupiter (about 11.86 years). The central cycle can be associated to a quasi-11-year sunspot solar dynamo cycle that appears to be approximately synchronized to the average of the two planetary frequencies. A simplified harmonic constituent model based on the above two planetary tidal frequencies and on the exact dates of Jupiter and Saturn planetary tidal phases, plus a theoretically deduced 10.87-year central cycle reveals complex quasi-periodic interference/beat patterns. The major beat periods occur at about 115, 61 and 130 years, plus a quasi-millennial large beat cycle around 983 years. These frequencies and other oscillations appear once the model is non-linearly processed. We show that equivalent synchronized cycles are found in cosmogenic records used to reconstruct solar activity and in proxy climate records throughout the Holocene (last 12,000 years) up to now. The quasi-secular beat oscillations hindcast reasonably well the known prolonged periods of low solar activity during the last millennium such as the Oort, Wolf, Sporer, Maunder and Dalton minima, as well as the 17 115-year long oscillations found in a detailed temperature reconstruction of the Northern Hemisphere covering the last 2000 years. The millennial cycle hindcasts equivalent solar and climate cycles for 12,000 years. Finally, the harmonic model herein proposed reconstructs the prolonged solar minima that occurred during 1900- 1920 and 1960-1980 and the secular solar maxima around 1870-1890, 1940-1950 and 1995-2005 and a secular upward trending during the 20th century: this modulated trending agrees well with some solar proxy model, with the ACRIM TSI satellite composite and with the global surface temperature modulation since 1850. The model forecasts a new prolonged solar minimum during 2020-2045, which would be produced mostly by the minima of both the 61 and 115-year reconstructed cycles. Finally, the model predicts that during low solar activity periods, the solar cycle length tends to be longer, as some researchers have claimed. These results clearly indicate that both solar and climate oscillations are linked to planetary motion and, furthermore, their timing can be reasonably hindcast and forecast for decades, centuries and millennia. Scafetta, N.: Multi-scale harmonic model for solar and climate cyclical variation throughout the Holocene based on Jupiter-Saturn tidal frequencies plus the 11-year solar dynamo cycle. J. Atmos. Sol.- Terr. Phys. 80, 296-311 (2012). Scafetta, N.: Does the Sun work as a nuclear fusion amplifier of planetary tidal forcing? A proposal for a physical mechanism based on the mass-luminosity relation. J. Atmos. Sol.-Terr. Phys. 81-82, 27-40 (2012). Scafetta, N.: Discussion on the spectral coherence between planetary, solar and climate oscillations: a reply to some critiques. Astrophys. Space Sci. 354, 275-299 (2014).

Spring-fall asymmetry of substorm strength, geomagnetic activity and solar wind: Implications for semiannual variation and solar hemispheric asymmetry

USGS Publications Warehouse

Mursula, K.; Tanskanen, E.; Love, J.J.

2011-01-01

We study the seasonal variation of substorms, geomagnetic activity and their solar wind drivers in 1993-2008. The number of substorms and substorm mean duration depict an annual variation with maxima in Winter and Summer, respectively, reflecting the annual change of the local ionosphere. In contradiction, substorm mean amplitude, substorm total efficiency and global geomagnetic activity show a dominant annual variation, with equinoctial maxima alternating between Spring in solar cycle 22 and Fall in cycle 23. The largest annual variations were found in 1994 and 2003, in the declining phase of the two cycles when high-speed streams dominate the solar wind. A similar, large annual variation is found in the solar wind driver of substorms and geomagnetic activity, which implies that the annual variation of substorm strength, substorm efficiency and geomagnetic activity is not due to ionospheric conditions but to a hemispherically asymmetric distribution of solar wind which varies from one cycle to another. Our results imply that the overall semiannual variation in global geomagnetic activity has been seriously overestimated, and is largely an artifact of the dominant annual variation with maxima alternating between Spring and Fall. The results also suggest an intimate connection between the asymmetry of solar magnetic fields and some of the largest geomagnetic disturbances, offering interesting new pathways for forecasting disturbances with a longer lead time to the future. Copyright ?? 2011 by the American Geophysical Union.

Forecasting of Radiation Belts: Results From the PROGRESS Project.

NASA Astrophysics Data System (ADS)

Balikhin, M. A.; Arber, T. D.; Ganushkina, N. Y.; Walker, S. N.

2017-12-01

Forecasting of Radiation Belts: Results from the PROGRESS Project. The overall goal of the PROGRESS project, funded in frame of EU Horizon2020 programme, is to combine first principles based models with the systems science methodologies to achieve reliable forecasts of the geo-space particle radiation environment.The PROGRESS incorporates three themes : The propagation of the solar wind to L1, Forecast of geomagnetic indices, and forecast of fluxes of energetic electrons within the magnetosphere. One of the important aspects of the PROGRESS project is the development of statistical wave models for magnetospheric waves that affect the dynamics of energetic electrons such as lower band chorus, hiss and equatorial noise. The error reduction ratio (ERR) concept has been used to optimise the set of solar wind and geomagnetic parameters for organisation of statistical wave models for these emissions. The resulting sets of parameters and statistical wave models will be presented and discussed. However the ERR analysis also indicates that the combination of solar wind and geomagnetic parameters accounts for only part of the variance of the emissions under investigation (lower band chorus, hiss and equatorial noise). In addition, advances in the forecast of fluxes of energetic electrons, exploiting empirical models and the first principles IMPTAM model achieved by the PROGRESS project is presented.

Space Monitoring Data Center at Moscow State University

NASA Astrophysics Data System (ADS)

Kalegaev, Vladimir; Bobrovnikov, Sergey; Barinova, Vera; Myagkova, Irina; Shugay, Yulia; Barinov, Oleg; Dolenko, Sergey; Mukhametdinova, Ludmila; Shiroky, Vladimir

Space monitoring data center of Moscow State University provides operational information on radiation state of the near-Earth space. Internet portal http://swx.sinp.msu.ru/ gives access to the actual data characterizing the level of solar activity, geomagnetic and radiation conditions in the magnetosphere and heliosphere in the real time mode. Operational data coming from space missions (ACE, GOES, ELECTRO-L1, Meteor-M1) at L1, LEO and GEO and from the Earth’s surface are used to represent geomagnetic and radiation state of near-Earth environment. On-line database of measurements is also maintained to allow quick comparison between current conditions and conditions experienced in the past. The models of space environment working in autonomous mode are used to generalize the information obtained from observations on the whole magnetosphere. Interactive applications and operational forecasting services are created on the base of these models. They automatically generate alerts on particle fluxes enhancements above the threshold values, both for SEP and relativistic electrons using data from LEO orbits. Special forecasting services give short-term forecast of SEP penetration to the Earth magnetosphere at low altitudes, as well as relativistic electron fluxes at GEO. Velocities of recurrent high speed solar wind streams on the Earth orbit are predicted with advance time of 3-4 days on the basis of automatic estimation of the coronal hole areas detected on the images of the Sun received from the SDO satellite. By means of neural network approach, Dst and Kp indices online forecasting 0.5-1.5 hours ahead, depending on solar wind and the interplanetary magnetic field, measured by ACE satellite, is carried out. Visualization system allows representing experimental and modeling data in 2D and 3D.

Ensemble downscaling in coupled solar wind-magnetosphere modeling for space weather forecasting.

PubMed

Owens, M J; Horbury, T S; Wicks, R T; McGregor, S L; Savani, N P; Xiong, M

2014-06-01

Advanced forecasting of space weather requires simulation of the whole Sun-to-Earth system, which necessitates driving magnetospheric models with the outputs from solar wind models. This presents a fundamental difficulty, as the magnetosphere is sensitive to both large-scale solar wind structures, which can be captured by solar wind models, and small-scale solar wind "noise," which is far below typical solar wind model resolution and results primarily from stochastic processes. Following similar approaches in terrestrial climate modeling, we propose statistical "downscaling" of solar wind model results prior to their use as input to a magnetospheric model. As magnetospheric response can be highly nonlinear, this is preferable to downscaling the results of magnetospheric modeling. To demonstrate the benefit of this approach, we first approximate solar wind model output by smoothing solar wind observations with an 8 h filter, then add small-scale structure back in through the addition of random noise with the observed spectral characteristics. Here we use a very simple parameterization of noise based upon the observed probability distribution functions of solar wind parameters, but more sophisticated methods will be developed in the future. An ensemble of results from the simple downscaling scheme are tested using a model-independent method and shown to add value to the magnetospheric forecast, both improving the best estimate and quantifying the uncertainty. We suggest a number of features desirable in an operational solar wind downscaling scheme. Solar wind models must be downscaled in order to drive magnetospheric models Ensemble downscaling is more effective than deterministic downscaling The magnetosphere responds nonlinearly to small-scale solar wind fluctuations.

Turbulence-driven Coronal Heating and Improvements to Empirical Forecasting of the Solar Wind

NASA Astrophysics Data System (ADS)

Woolsey, Lauren N.; Cranmer, Steven R.

2014-06-01

Forecasting models of the solar wind often rely on simple parameterizations of the magnetic field that ignore the effects of the full magnetic field geometry. In this paper, we present the results of two solar wind prediction models that consider the full magnetic field profile and include the effects of Alfvén waves on coronal heating and wind acceleration. The one-dimensional magnetohydrodynamic code ZEPHYR self-consistently finds solar wind solutions without the need for empirical heating functions. Another one-dimensional code, introduced in this paper (The Efficient Modified-Parker-Equation-Solving Tool, TEMPEST), can act as a smaller, stand-alone code for use in forecasting pipelines. TEMPEST is written in Python and will become a publicly available library of functions that is easy to adapt and expand. We discuss important relations between the magnetic field profile and properties of the solar wind that can be used to independently validate prediction models. ZEPHYR provides the foundation and calibration for TEMPEST, and ultimately we will use these models to predict observations and explain space weather created by the bulk solar wind. We are able to reproduce with both models the general anticorrelation seen in comparisons of observed wind speed at 1 AU and the flux tube expansion factor. There is significantly less spread than comparing the results of the two models than between ZEPHYR and a traditional flux tube expansion relation. We suggest that the new code, TEMPEST, will become a valuable tool in the forecasting of space weather.

Life of the Earth in the solar atmosphere (multimedia manual)

NASA Astrophysics Data System (ADS)

Kononovich, E. V.; Smirnova, O. B.; Matveychuk, T. V.; Jakunina, G. V.; Krasotkin, S. A.

2006-08-01

The purpose of this manual is to illustrate the major physical processes occurring in the Sun - Earth system and ecology of the planet life. The material includes three individual parts: "The Earth", "The Sun" and "The solar-terrestrial connections". Sections do not require cross-references since each of them is self-complete. Inside the sections the material is located in sequences based on the principle: from simple to complex. The material is designed for students of the senior classes of high school and junior university level interested by the problem. The section "The Earth" is devoted to the description of the basic characteristics of the planet: internal structure, magnetic field, lithosphere and an atmosphere together with various occurring in them tectonic, hydro- and atmospheric processes. The top layers of an atmosphere, an ionosphere, a zone of polar lights, radiating belts, magnetosphere are also considered. The section "The Sun" includes the following subsections: the Sun as a star, internal structure of the Sun, Solar atmosphere, solar activity, cyclicity of the solar activity, helioseismology. In the section "The solar-terrestrial connections" the previous material is used to present the influence of the active solar processes on the most various aspects of a terrestrial life: ecological, biological, mental, social, economic and so forth. The problem of forecasting of the solar activity as the key parameter determining a condition of the so-called space weather is considered.

Geomagnetic storm forecasting service StormFocus: 5 years online

NASA Astrophysics Data System (ADS)

Podladchikova, Tatiana; Petrukovich, Anatoly; Yermolaev, Yuri

2018-04-01

Forecasting geomagnetic storms is highly important for many space weather applications. In this study, we review performance of the geomagnetic storm forecasting service StormFocus during 2011-2016. The service was implemented in 2011 at SpaceWeather.Ru and predicts the expected strength of geomagnetic storms as measured by Dst index several hours ahead. The forecast is based on L1 solar wind and IMF measurements and is updated every hour. The solar maximum of cycle 24 is weak, so most of the statistics are on rather moderate storms. We verify quality of selection criteria, as well as reliability of real-time input data in comparison with the final values, available in archives. In real-time operation 87% of storms were correctly predicted while the reanalysis running on final OMNI data predicts successfully 97% of storms. Thus the main reasons for prediction errors are discrepancies between real-time and final data (Dst, solar wind and IMF) due to processing errors, specifics of datasets.

Solar and Heliospheric Data Requirements: Going Further Than L1

NASA Technical Reports Server (NTRS)

Szabo, A.

2011-01-01

Current operational space weather forecasting relies on solar wind observations made by the ACE spacecraft located at the L1 point providing 30-40 minutes warning time. Some use is also made of SOHO and STEREO solar imaging that potentially can give multiple days of warning time. However, our understanding of the propagation and evolution of solar wind transients is still limited resulting in a typical timing uncertainty of approximately 10 hours. In order to improve this critical understanding, a number of NASA missions are being planned. Specifically the Solar Probe Plus and Solar Orbiter missions will investigate the inner Heliospheric evolution of coronal mass ejections and the acceleration and propagation of solar energetic particles. In addition, a number of multi-spacecraft concepts have been studied that have the potential to significantly improve the accuracy of long-term space weather forecasts.

42 years of continuous observations of the Solar 1 diameter from 1974 to 2015 - What do they forecast.

NASA Astrophysics Data System (ADS)

Humberto Andrei, Alexandre; Penna, Jucira; Boscardin, Sergio; Papa, Andres R. R.; Garcia, Marcos Antonio; Sigismondi, Costantino

2016-07-01

Several research groups in the world developed observational programs for the Sun in order to measure its apparent diameter over time with dedicated instruments, called solar astrolabes, since 1974. Their data have been gathered in several observing stations connected in the R2S3 (Réseau de Suivi au Sol du Rayon Solaire) network and through reciprocal visits and exchanges: Nice/Calern Observatoire/France, Rio de Janeiro Observatório Nacional/Brazil, Observatório de São Paulo IAGUSP/Brazil, Observatório Abrahão de Moraes IAGUSP/Brazil, Antalya Observatory/Turkey, San Fernando/Spain. Since all the optics and data treatment of the solar astrolabes was the same, from the oldest, with a single fixed objective prism, to the newest, with an angle variable objective prism and digital image acquisition, their results could be put together. Each instrument had its own density filter with a prismatic effect responsible for a particular shift. Thus, identical data gathering and just a different prismatic shift, enabled to reconcile all those series by using the common stretches and derive a single additive constant to place each one onto a common average. By doing so, although the value itself of the ground observed solar diameter is lost, its variations are determined over 35 years. On the combined series of the ground observed solar diameter a modulation with the 11 years main solar cycle is evident. However when such modulation is removed, both from the solar diameter compound series and from the solar activity series (as given by the sunspots count), a very strong anticorrelation is revealed. This suggested a larger diameter for the forthcoming cycles. This was very well verified for solar cycle 23, and correctly forecasted for cycle 24,in a behavior similar to that on the Minima of Dalton and Maunder. The ground monitoring keeps being routinely followed at Observatório Nacional in Rio de Janeiro, now using the Solar Heliometer, specially built to this end . The Heliometer has the same focal length and aperture of the earlier solar astrolabes, and the diameter determination uses the same physical and mathematical definition of the solar limb. Therefore the same robust, no-hypothesis, simple combination by an adding constant, can be used to include the Heliometer measurements along the previous long, continuous series. As a result the series of measurements of the variation of the solar diameter reaches 42 years, and covers also the solar cycle 24. In this paper we review all the individual series chief elements, as well as the calculation and values of the adding constants. We show the earlier comparison that lead to an anticorrelation at 0.867 to the solar activity record, when the 11 years modulation is expurgate, and exhibits an impressively accurate description of cycle 23. On the strength of such successful analysis we employ the new longer series to discuss the current solar cycle 24 and forecast for the following solar cycle 25. We thus advocate in favor of continued and continuous ground measurements of the solar diameter, on the usefulness of making these results available to the scientific community at large, and on the matter-of-fact, real variations of the solar diameter on long term time periods and/or local places on the Sun, in this case possibly associated to major magnetism driven solar transients.

An Automated Solar Synoptic Analysis Software System

NASA Astrophysics Data System (ADS)

Hong, S.; Lee, S.; Oh, S.; Kim, J.; Lee, J.; Kim, Y.; Lee, J.; Moon, Y.; Lee, D.

2012-12-01

We have developed an automated software system of identifying solar active regions, filament channels, and coronal holes, those are three major solar sources causing the space weather. Space weather forecasters of NOAA Space Weather Prediction Center produce the solar synoptic drawings as a daily basis to predict solar activities, i.e., solar flares, filament eruptions, high speed solar wind streams, and co-rotating interaction regions as well as their possible effects to the Earth. As an attempt to emulate this process with a fully automated and consistent way, we developed a software system named ASSA(Automated Solar Synoptic Analysis). When identifying solar active regions, ASSA uses high-resolution SDO HMI intensitygram and magnetogram as inputs and providing McIntosh classification and Mt. Wilson magnetic classification of each active region by applying appropriate image processing techniques such as thresholding, morphology extraction, and region growing. At the same time, it also extracts morphological and physical properties of active regions in a quantitative way for the short-term prediction of flares and CMEs. When identifying filament channels and coronal holes, images of global H-alpha network and SDO AIA 193 are used for morphological identification and also SDO HMI magnetograms for quantitative verification. The output results of ASSA are routinely checked and validated against NOAA's daily SRS(Solar Region Summary) and UCOHO(URSIgram code for coronal hole information). A couple of preliminary scientific results are to be presented using available output results. ASSA will be deployed at the Korean Space Weather Center and serve its customers in an operational status by the end of 2012.

Validation of the CME Geomagnetic forecast alerts under COMESEP alert system

NASA Astrophysics Data System (ADS)

Dumbovic, Mateja; Srivastava, Nandita; Khodia, Yamini; Vršnak, Bojan; Devos, Andy; Rodriguez, Luciano

2017-04-01

An automated space weather alert system has been developed under the EU FP7 project COMESEP (COronal Mass Ejections and Solar Energetic Particles: http://comesep.aeronomy.be) to forecast solar energetic particles (SEP) and coronal mass ejection (CME) risk levels at Earth. COMESEP alert system uses automated detection tool CACTus to detect potentially threatening CMEs, drag-based model (DBM) to predict their arrival and CME geo-effectiveness tool (CGFT) to predict their geomagnetic impact. Whenever CACTus detects a halo or partial halo CME and issues an alert, DBM calculates its arrival time at Earth and CGFT calculates its geomagnetic risk level. Geomagnetic risk level is calculated based on an estimation of the CME arrival probability and its likely geo-effectiveness, as well as an estimate of the geomagnetic-storm duration. We present the evaluation of the CME risk level forecast with COMESEP alert system based on a study of geo-effective CMEs observed during 2014. The validation of the forecast tool is done by comparing the forecasts with observations. In addition, we test the success rate of the automatic forecasts (without human intervention) against the forecasts with human intervention using advanced versions of DBM and CGFT (self standing tools available at Hvar Observatory website: http://oh.geof.unizg.hr). The results implicate that the success rate of the forecast is higher with human intervention and using more advanced tools. This work has received funding from the European Commission FP7 Project COMESEP (263252). We acknowledge the support of Croatian Science Foundation under the project 6212 „Solar and Stellar Variability".

Solar Atmosphere to Earth's Surface: Long Lead Time dB/dt Predictions with the Space Weather Modeling Framework

NASA Astrophysics Data System (ADS)

Welling, D. T.; Manchester, W.; Savani, N.; Sokolov, I.; van der Holst, B.; Jin, M.; Toth, G.; Liemohn, M. W.; Gombosi, T. I.

2017-12-01

The future of space weather prediction depends on the community's ability to predict L1 values from observations of the solar atmosphere, which can yield hours of lead time. While both empirical and physics-based L1 forecast methods exist, it is not yet known if this nascent capability can translate to skilled dB/dt forecasts at the Earth's surface. This paper shows results for the first forecast-quality, solar-atmosphere-to-Earth's-surface dB/dt predictions. Two methods are used to predict solar wind and IMF conditions at L1 for several real-world coronal mass ejection events. The first method is an empirical and observationally based system to estimate the plasma characteristics. The magnetic field predictions are based on the Bz4Cast system which assumes that the CME has a cylindrical flux rope geometry locally around Earth's trajectory. The remaining plasma parameters of density, temperature and velocity are estimated from white-light coronagraphs via a variety of triangulation methods and forward based modelling. The second is a first-principles-based approach that combines the Eruptive Event Generator using Gibson-Low configuration (EEGGL) model with the Alfven Wave Solar Model (AWSoM). EEGGL specifies parameters for the Gibson-Low flux rope such that it erupts, driving a CME in the coronal model that reproduces coronagraph observations and propagates to 1AU. The resulting solar wind predictions are used to drive the operational Space Weather Modeling Framework (SWMF) for geospace. Following the configuration used by NOAA's Space Weather Prediction Center, this setup couples the BATS-R-US global magnetohydromagnetic model to the Rice Convection Model (RCM) ring current model and a height-integrated ionosphere electrodynamics model. The long lead time predictions of dB/dt are compared to model results that are driven by L1 solar wind observations. Both are compared to real-world observations from surface magnetometers at a variety of geomagnetic latitudes. Metrics are calculated to examine how the simulated solar wind drivers impact forecast skill. These results illustrate the current state of long-lead-time forecasting and the promise of this technology for operational use.

A NOAA/SWPC Perspective on Space Weather Forecasts That Fail

NASA Astrophysics Data System (ADS)

Biesecker, D. A.

2014-12-01

The Space Weather Prediction Center (SWPC) at NOAA is the Official US source for space weather watches, warning and alerts. These alerts are provided to a breadth of customers covering a range of industries, including electric utilities, airlines, emergency managers, and users of precision GPS to name a few. This talk will review the current tools used by SWPC to forecast geomagnetic storms, solar flares, and solar energetic particle events and present the SWPC performance in each of these areas. We will include a discussion of the current limitations and examples of events that proved difficult to forecast.

A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network

PubMed Central

Tokumitsu, Masahiro; Ishida, Yoshiteru

2014-01-01

This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing. PMID:24803190

A space weather forecasting system with multiple satellites based on a self-recognizing network.

PubMed

Tokumitsu, Masahiro; Ishida, Yoshiteru

2014-05-05

This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

Quantized Advantages to a Proposed Satellite at L5 from Simulated Synoptic Magnetograms

NASA Astrophysics Data System (ADS)

Schwarz, A. M.; Petrie, G. J. D.

2017-12-01

The dependency the Earth and its inhabitants have on the Sun is delicate and complex and sometimes dangerous. At the NSO, we provide 24/7 coverage of the full-disk solar magnetic field used in solar forecasting, however this only includes data from the Sun's Earth facing side. Ideally we would like to have constant coverage of the entire solar surface, however we are limited in our solar viewing angle. Our project attempts to quantify the advantages of full-disk magnetograms from a proposed satellite at L5. With instrumentation at L5 we would have an additional 60 degrees of solar surface coverage not seen from Earth. These 60 degrees crucially contain the solar longitudes that are about to rotate towards Earth. Using a full-surface flux-transport model of the evolving solar photospheric field, I created a simulation of full-disk observations from Earth and L5. Using standard solar forecasting tools we quantify the relative accuracy of the Earth-Only and Earth plus L5 forecasts relative to the "ground truth" of the full surface field model, the ideal case. My results gauge exactly how much polar coverage is improved, contrast the spherical multipoles of each model, and use a Potential-Field Source-Surface (PFSS) magnetic field analysis model to find comparisons in the neutral lines and open field coverage.

PREDICTION OF SOLAR FLARES USING UNIQUE SIGNATURES OF MAGNETIC FIELD IMAGES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raboonik, Abbas; Safari, Hossein; Alipour, Nasibe

Prediction of solar flares is an important task in solar physics. The occurrence of solar flares is highly dependent on the structure and topology of solar magnetic fields. A new method for predicting large (M- and X-class) flares is presented, which uses machine learning methods applied to the Zernike moments (ZM) of magnetograms observed by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory for a period of six years from 2010 June 2 to 2016 August 1. Magnetic field images consisting of the radial component of the magnetic field are converted to finite sets of ZMs andmore » fed to the support vector machine classifier. ZMs have the capability to elicit unique features from any 2D image, which may allow more accurate classification. The results indicate whether an arbitrary active region has the potential to produce at least one large flare. We show that the majority of large flares can be predicted within 48 hr before their occurrence, with only 10 false negatives out of 385 flaring active region magnetograms and 21 false positives out of 179 non-flaring active region magnetograms. Our method may provide a useful tool for the prediction of solar flares, which can be employed alongside other forecasting methods.« less

Local TEC modelling and forecasting using neural networks

NASA Astrophysics Data System (ADS)

Tebabal, A.; Radicella, S. M.; Nigussie, M.; Damtie, B.; Nava, B.; Yizengaw, E.

2018-07-01

Modelling the Earth's ionospheric characteristics is the focal task for the ionospheric community to mitigate its effect on the radio communication, and satellite navigation. However, several aspects of modelling are still challenging, for example, the storm time characteristics. This paper presents modelling efforts of TEC taking into account solar and geomagnetic activity, time of the day and day of the year using neural networks (NNs) modelling technique. The NNs have been designed with GPS-TEC measured data from low and mid-latitude GPS stations. The training was conducted using the data obtained for the period from 2011 to 2014. The model prediction accuracy was evaluated using data of year 2015. The model results show that diurnal and seasonal trend of the GPS-TEC is well reproduced by the model for the two stations. The seasonal characteristics of GPS-TEC is compared with NN and NeQuick 2 models prediction when the latter one is driven by the monthly average value of solar flux. It is found that NN model performs better than the corresponding NeQuick 2 model for low latitude region. For the mid-latitude both NN and NeQuick 2 models reproduce the average characteristics of TEC variability quite successfully. An attempt of one day ahead forecast of TEC at the two locations has been made by introducing as drivers previous day solar flux and geomagnetic index values. The results show that a reasonable day ahead forecast of local TEC can be achieved.

Local TEC Modelling and Forecasting using Neural Networks

NASA Astrophysics Data System (ADS)

Tebabal, A.; Radicella, S. M.; Nigussie, M.; Damtie, B.; Nava, B.; Yizengaw, E.

2017-12-01

Abstract Modelling the Earth's ionospheric characteristics is the focal task for the ionospheric community to mitigate its effect on the radio communication, satellite navigation and technologies. However, several aspects of modelling are still challenging, for example, the storm time characteristics. This paper presents modelling efforts of TEC taking into account solar and geomagnetic activity, time of the day and day of the year using neural networks (NNs) modelling technique. The NNs have been designed with GPS-TEC measured data from low and mid-latitude GPS stations. The training was conducted using the data obtained for the period from 2011 to 2014. The model prediction accuracy was evaluated using data of year 2015. The model results show that diurnal and seasonal trend of the GPS-TEC is well reproduced by the model for the two stations. The seasonal characteristics of GPS-TEC is compared with NN and NeQuick 2 models prediction when the latter one is driven by the monthly average value of solar flux. It is found that NN model performs better than the corresponding NeQuick 2 model for low latitude region. For the mid-latitude both NN and NeQuick 2 models reproduce the average characteristics of TEC variability quite successfully. An attempt of one day ahead forecast of TEC at the two locations has been made by introducing as driver previous day solar flux and geomagnetic index values. The results show that a reasonable day ahead forecast of local TEC can be achieved.

A distributed big data storage and data mining framework for solar-generated electricity quantity forecasting

NASA Astrophysics Data System (ADS)

Wang, Jianzong; Chen, Yanjun; Hua, Rui; Wang, Peng; Fu, Jia

2012-02-01

Photovoltaic is a method of generating electrical power by converting solar radiation into direct current electricity using semiconductors that exhibit the photovoltaic effect. Photovoltaic power generation employs solar panels composed of a number of solar cells containing a photovoltaic material. Due to the growing demand for renewable energy sources, the manufacturing of solar cells and photovoltaic arrays has advanced considerably in recent years. Solar photovoltaics are growing rapidly, albeit from a small base, to a total global capacity of 40,000 MW at the end of 2010. More than 100 countries use solar photovoltaics. Driven by advances in technology and increases in manufacturing scale and sophistication, the cost of photovoltaic has declined steadily since the first solar cells were manufactured. Net metering and financial incentives, such as preferential feed-in tariffs for solar-generated electricity; have supported solar photovoltaics installations in many countries. However, the power that generated by solar photovoltaics is affected by the weather and other natural factors dramatically. To predict the photovoltaic energy accurately is of importance for the entire power intelligent dispatch in order to reduce the energy dissipation and maintain the security of power grid. In this paper, we have proposed a big data system--the Solar Photovoltaic Power Forecasting System, called SPPFS to calculate and predict the power according the real-time conditions. In this system, we utilized the distributed mixed database to speed up the rate of collecting, storing and analysis the meteorological data. In order to improve the accuracy of power prediction, the given neural network algorithm has been imported into SPPFS.By adopting abundant experiments, we shows that the framework can provide higher forecast accuracy-error rate less than 15% and obtain low latency of computing by deploying the mixed distributed database architecture for solar-generated electricity.

Ensemble downscaling in coupled solar wind-magnetosphere modeling for space weather forecasting

PubMed Central

Owens, M J; Horbury, T S; Wicks, R T; McGregor, S L; Savani, N P; Xiong, M

2014-01-01

Advanced forecasting of space weather requires simulation of the whole Sun-to-Earth system, which necessitates driving magnetospheric models with the outputs from solar wind models. This presents a fundamental difficulty, as the magnetosphere is sensitive to both large-scale solar wind structures, which can be captured by solar wind models, and small-scale solar wind “noise,” which is far below typical solar wind model resolution and results primarily from stochastic processes. Following similar approaches in terrestrial climate modeling, we propose statistical “downscaling” of solar wind model results prior to their use as input to a magnetospheric model. As magnetospheric response can be highly nonlinear, this is preferable to downscaling the results of magnetospheric modeling. To demonstrate the benefit of this approach, we first approximate solar wind model output by smoothing solar wind observations with an 8 h filter, then add small-scale structure back in through the addition of random noise with the observed spectral characteristics. Here we use a very simple parameterization of noise based upon the observed probability distribution functions of solar wind parameters, but more sophisticated methods will be developed in the future. An ensemble of results from the simple downscaling scheme are tested using a model-independent method and shown to add value to the magnetospheric forecast, both improving the best estimate and quantifying the uncertainty. We suggest a number of features desirable in an operational solar wind downscaling scheme. Key Points Solar wind models must be downscaled in order to drive magnetospheric models Ensemble downscaling is more effective than deterministic downscaling The magnetosphere responds nonlinearly to small-scale solar wind fluctuations PMID:26213518

Solar-terrestrial influences on weather and climate; Proceedings of the Symposium, Ohio State University, Columbus, Ohio, August 24-28, 1978

NASA Technical Reports Server (NTRS)

Mccormac, B. M. (Editor); Seliga, T. A.

1979-01-01

The book contains most of the invited papers and contributions presented at the symposium/workshop on solar-terrestrial influences on weather and climate. Four main issues dominate the activities of the symposium: whether solar variability relationships to weather and climate is a fundamental scientific question to which answers may have important implications for long-term weather and climate prediction; the sun-weather relationships; other potential solar influences on weather including the 11-year sunspot cycle, the 27-day solar rotation, and special solar events such as flares and coronal holes; and the development of practical use of solar variability as a tool for weather and climatic forecasting, other than through empirical approaches. Attention is given to correlation topics; solar influences on global circulation and climate models; lower and upper atmospheric coupling, including electricity; planetary motions and other indirect factors; experimental approaches to sun-weather relationships; and the role of minor atmospheric constituents.

Solar flares, proton showers, and the Space Shuttle

NASA Technical Reports Server (NTRS)

Rust, D. M.

1982-01-01

Attention is given the hazards posed to Space Shuttle crews by energetic proton radiation from inherently unpredictable solar flares, such as that of April 10-13, 1981, which was experienced by the Space Shuttle Columbia. The most energetic protons from this flare reached the earth's atmosphere an hour after flare onset, and would have posed a potentially lethal threat to astronauts engaged in extravehicular activity in a polar or geosynchronous orbit rather than the low-latitude, low-altitude orbit of this mission. It is shown that proton-producing flares are associated with energization in shocks, many of which are driven by coronal mass ejections. Insights gained from the Solar Maximum Year programs allow reconsideration of proton shower forecasting, which will be essential in the prediction of the weather that Space Shuttle astronauts will encounter during extravehicular activities.

Turbulence-driven coronal heating and improvements to empirical forecasting of the solar wind

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woolsey, Lauren N.; Cranmer, Steven R.

Forecasting models of the solar wind often rely on simple parameterizations of the magnetic field that ignore the effects of the full magnetic field geometry. In this paper, we present the results of two solar wind prediction models that consider the full magnetic field profile and include the effects of Alfvén waves on coronal heating and wind acceleration. The one-dimensional magnetohydrodynamic code ZEPHYR self-consistently finds solar wind solutions without the need for empirical heating functions. Another one-dimensional code, introduced in this paper (The Efficient Modified-Parker-Equation-Solving Tool, TEMPEST), can act as a smaller, stand-alone code for use in forecasting pipelines. TEMPESTmore » is written in Python and will become a publicly available library of functions that is easy to adapt and expand. We discuss important relations between the magnetic field profile and properties of the solar wind that can be used to independently validate prediction models. ZEPHYR provides the foundation and calibration for TEMPEST, and ultimately we will use these models to predict observations and explain space weather created by the bulk solar wind. We are able to reproduce with both models the general anticorrelation seen in comparisons of observed wind speed at 1 AU and the flux tube expansion factor. There is significantly less spread than comparing the results of the two models than between ZEPHYR and a traditional flux tube expansion relation. We suggest that the new code, TEMPEST, will become a valuable tool in the forecasting of space weather.« less

Modeling and Analysis of Geoelectric Fields: Extended Solar Shield

NASA Astrophysics Data System (ADS)

Ngwira, C. M.; Pulkkinen, A. A.

2016-12-01

In the NASA Applied Sciences Program Solar Shield project, an unprecedented first-principles-based system to forecast geomagnetically induced current (GIC) in high-voltage power transmission systems was developed. Rapid progress in the field of numerical physics-based space environment modeling has led to major developments over the past few years. In this study modeling and analysis of induced geoelectric fields is discussed. Specifically, we focus on the successful incorporation of 3-D EM transfer functions in the modeling of E-fields, and on the analysis of near real-time simulation outputs used in the Solar Shield forecast system. The extended Solar Shield is a collaborative project between DHS, NASA, NOAA, CUA and EPRI.

Towards the intrahour forecasting of direct normal irradiance using sky-imaging data.

PubMed

Nou, Julien; Chauvin, Rémi; Eynard, Julien; Thil, Stéphane; Grieu, Stéphane

2018-04-01

Increasing power plant efficiency through improved operation is key in the development of Concentrating Solar Power (CSP) technologies. To this end, one of the most challenging topics remains accurately forecasting the solar resource at a short-term horizon. Indeed, in CSP plants, production is directly impacted by both the availability and variability of the solar resource and, more specifically, by Direct Normal Irradiance (DNI). The present paper deals with a new approach to the intrahour forecasting (the forecast horizon [Formula: see text] is up to [Formula: see text] ahead) of DNI, taking advantage of the fact that this quantity can be split into two terms, i.e. clear-sky DNI and the clear sky index. Clear-sky DNI is forecasted from DNI measurements, using an empirical model (Ineichen and Perez, 2002) combined with a persistence of atmospheric turbidity. Moreover, in the framework of the CSPIMP (Concentrating Solar Power plant efficiency IMProvement) research project, PROMES-CNRS has developed a sky imager able to provide High Dynamic Range (HDR) images. So, regarding the clear-sky index, it is forecasted from sky-imaging data, using an Adaptive Network-based Fuzzy Inference System (ANFIS). A hybrid algorithm that takes inspiration from the classification algorithm proposed by Ghonima et al. (2012) when clear-sky anisotropy is known and from the hybrid thresholding algorithm proposed by Li et al. (2011) in the opposite case has been developed to the detection of clouds. Performance is evaluated via a comparative study in which persistence models - either a persistence of DNI or a persistence of the clear-sky index - are included. Preliminary results highlight that the proposed approach has the potential to outperform these models (both persistence models achieve similar performance) in terms of forecasting accuracy: over the test data used, RMSE (the Root Mean Square Error) is reduced of about [Formula: see text], with [Formula: see text], and [Formula: see text], with [Formula: see text].

Implications of solar irradiance variability upon long-term changes in the Earth's atmospheric temperatures

NASA Technical Reports Server (NTRS)

Lee, Robert B., III

1992-01-01

From 1979 through 1987, it is believed that variability in the incoming solar energy played a significant role in changing the Earth's climate. Using high-precision spacecraft radiometric measurements, the incoming total solar irradiance (total amount of solar power per unit area) and the Earth's mean, global atmospheric temperatures were found to vary in phase with each other. The observed irradiance and temperature changes appeared to be correlated with the 11-year cycle of solar magnetic activity. During the period from 1979 through 1985, both the irradiance and temperature decreased. From 1985 to 1987, they increased. The irradiance changed approximately 0.1 percent, while the temperature varied as much as 0.6 C. During the 1979-1987 period, the temperatures were forecasted to rise linearly because of the anthropogenic build-up of carbon dioxide and the hypothesized 'global warming', 'greenhouse effect', scenarios. Contrary to these scenarios, the temperatures were found to vary in a periodic manner in phase with the solar irradiance changes. The observed correlations between irradiance and temperature variabilily suggest that the mean, global temperature of the Earth may decline between 1990 and 1997 as solar magnetic activity decreases.

The Effect of a Potentially Low Solar Cycle #24 on Orbital Lifetimes of Fengyun 1-C Debris

NASA Technical Reports Server (NTRS)

Whitlock, David; Johnson, Nicholas; Matney, Mark; Krisko, Paula

2008-01-01

The magnitude of Solar Cycle #24 will have a non-trivial impact on the lifetimes of debris pieces that resulted from the intentional hypervelocity impact of the Fengyun 1-C satellite in January 2007. Recent solar flux measurements indicate Solar Cycle #24 has begun in the last few months, and will continue until approximately 2019. While there have been differing opinions on whether the intensity of this solar cycle will be higher or lower than usual, the Space Weather Prediction Center within the National Oceanic Atmospheric Administration (NOAA/SWPC) has recently forecast unusually low solar activity, which would result in longer orbital lifetimes. Using models for both the breakup of Fengyun 1-C and the propagation of the resultant debris cloud, the Orbital Debris Program Office at NASA Johnson Space Center conducted a study to better understand the impact of the solar cycle on lifetimes for pieces as small as 1 mm. Using a modified collision breakup model and PROP3D propagation software, the orbits of nearly 2 million objects 1 mm and larger were propagated for up to 200 years. By comparing a normal solar cycle with that of the NOAA/SWPC forecast low cycle, the effect of the solar flux on the lifetimes of the debris pieces is evaluated. The modeling of the low solar cycle shows an additional debris count of 12% for pieces larger than 10 cm by 2019 when compared to the resultant debris count using a normal cycle. The difference becomes more exaggerated (over 15%) for debris count in the smaller size regimes. However, in 50 years, the models predict the differences in debris count from differing models of Solar Cycle #24 to be less than 10% for all size regimes, with less variance in the smaller sizes. Understanding the longevity of the debris cloud will affect collision probabilities for both operational spacecraft and large derelict objects over the next century and beyond.

Geomagnetic activity during 10 - 11 solar cycles that has been observed by old Russian observatories.

NASA Astrophysics Data System (ADS)

Seredyn, Tomasz; Wysokinski, Arkadiusz; Kobylinski, Zbigniew; Bialy, Jerzy

2016-07-01

A good knowledge of solar-terrestrial relations during past solar activity cycles could give the appropriate tools for a correct space weather forecast. The paper focuses on the analysis of the historical collections of the ground based magnetic observations and their operational indices from the period of two sunspot solar cycles 10 - 11, period 1856 - 1878 (Bartels rotations 324 - 635). We use hourly observations of H and D geomagnetic field components registered at Russian stations: St. Petersburg - Pavlovsk, Barnaul, Ekaterinburg, Nertshinsk, Sitka, and compare them to the data obtained from the Helsinki observatory. We compare directly these records and also calculated from the data of the every above mentioned station IHV indices introduced by Svalgaard (2003), which have been used for further comparisons in epochs of assumed different polarity of the heliospheric magnetic field. We used also local index C9 derived by Zosimovich (1981) from St. Petersburg - Pavlovsk data. Solar activity is represented by sunspot numbers. The correlative and continuous wavelet analyses are applied for estimation of the correctness of records from different magnetic stations. We have specially regard to magnetic storms in the investigated period and the special Carrington event of 1-2 Sep 1859. Generally studied magnetic time series correctly show variability of the geomagnetic activity. Geomagnetic activity presents some delay in relation to solar one as it is seen especially during descending and minimum phase of the even 11-year cycle. This pattern looks similarly in the case of 16 - 17 solar cycles.

A new short-term forecasting model for the total electron content storm time disturbances

NASA Astrophysics Data System (ADS)

Tsagouri, Ioanna; Koutroumbas, Konstantinos; Elias, Panagiotis

2018-06-01

This paper aims to introduce a new model for the short-term forecast of the vertical Total Electron Content (vTEC). The basic idea of the proposed model lies on the concept of the Solar Wind driven autoregressive model for Ionospheric short-term Forecast (SWIF). In its original version, the model is operationally implemented in the DIAS system (http://dias.space.noa.gr) and provides alerts and warnings for upcoming ionospheric disturbances, as well as single site and regional forecasts of the foF2 critical frequency over Europe up to 24 h in advance. The forecasts are driven by the real time assessment of the solar wind conditions at ACE location. The comparative analysis of the variations in foF2 and vTEC during eleven geomagnetic storm events that occurred in the present solar cycle 24 reveals similarities but also differences in the storm-time response of the two characteristics with respect to the local time and the latitude of the observation point. Since the aforementioned dependences drive the storm-time forecasts of the SWIF model, the results obtained here support the upgrade of the SWIF's modeling technique in forecasting the storm-time vTEC variation from its onset to full development and recovery. According to the proposed approach, the vTEC storm-time response can be forecasted from 1 to 12-13 h before its onset, depending on the local time of the observation point at storm onset at L1. Preliminary results on the assessment of the performance of the proposed model and further considerations on its potential implementation in operational mode are also discussed.

Geoeffectiveness (D (sub st) and K (sub p)) of Interplanetary Coronal Mass Ejections During 1995-2009 and Implications for Storm Forecasting

NASA Technical Reports Server (NTRS)

Richardson, I. G.; Cane, H. V.

2011-01-01

We summarize the geoeffectiveness (based on the Dst and Kp indices) of the more than 300 interplanetary coronal mass ejections (ICMEs) that passed the Earth during 1996-2009, encompassing solar cycle 23. We subsequently estimate the probability that an ICME will generate geomagnetic activity that exceeds certain thresholds of Dst or Kp, including the NOAA "G" storm scale, based on maximum values of the southward magnetic field component (Bs), the solar wind speed (V), and the y component (Ey) of the solar wind convective electric field E = -V x B, in the ICME or sheath ahead of the ICME. Consistent with previous studies, the geoeffectiveness of an ICME is correlated with Bs or Ey approx.= VBs in the ICME or sheath, indicating that observations from a solar wind monitor upstream of the Earth are likely to provide the most reliable forecasts of the activity associated with an approaching ICME. There is also a general increase in geoeffectiveness with ICME speed, though the overall event-to-event correlation is weaker than for Bs and Ey. Nevertheless, using these results, we suggest that the speed of an ICME approaching the Earth inferred, for example, from routine remote sensing by coronagraphs on spacecraft well separated from the Earth or by all-sky imagers, could be used to estimate the likely geoeffectiveness of the ICME (our "comprehensive" ICME database provides a proxy for ICMEs identified in this way) with a longer lead time than may be possible using an upstream monitor

An application of a multi model approach for solar energy prediction in Southern Italy

NASA Astrophysics Data System (ADS)

Avolio, Elenio; Lo Feudo, Teresa; Calidonna, Claudia Roberta; Contini, Daniele; Torcasio, Rosa Claudia; Tiriolo, Luca; Montesanti, Stefania; Transerici, Claudio; Federico, Stefano

2015-04-01

The accuracy of the short and medium range forecast of solar irradiance is very important for solar energy integration into the grid. This issue is particularly important for Southern Italy where a significant availability of solar energy is associated with a poor development of the grid. In this work we analyse the performance of two deterministic models for the prediction of surface temperature and short-wavelength radiance for two sites in southern Italy. Both parameters are needed to forecast the power production from solar power plants, so the performance of the forecast for these meteorological parameters is of paramount importance. The models considered in this work are the RAMS (Regional Atmospheric Modeling System) and the WRF (Weather Research and Forecasting Model) and they were run for the summer 2013 at 4 km horizontal resolution over Italy. The forecast lasts three days. Initial and dynamic boundary conditions are given by the 12 UTC deterministic forecast of the ECMWF-IFS (European Centre for Medium Weather Range Forecast - Integrated Forecasting System) model, and were available every 6 hours. Verification is given against two surface stations located in Southern Italy, Lamezia Terme and Lecce, and are based on hourly output of models forecast. Results for the whole period for temperature show a positive bias for the RAMS model and a negative bias for the WRF model. RMSE is between 1 and 2 °C for both models. Results for the whole period for the short-wavelength radiance show a positive bias for both models (about 30 W/m2 for both models) and a RMSE of 100 W/m2. To reduce the model errors, a statistical post-processing technique, i.e the multi-model, is adopted. In this approach the two model's outputs are weighted with an adequate set of weights computed for a training period. In general, the performance is improved by the application of the technique, and the RMSE is reduced by a sizeable fraction (i.e. larger than 10% of the initial RMSE) depending on the forecasting time and parameter. The performance of the multi model is discussed as a function of the length of the training period and is compared with the performance of the MOS (Model Output Statistics) approach. ACKNOWLEDGMENTS This work is partially supported by projects PON04a2E Sinergreen-ResNovae - "Smart Energy Master for the energetic government of the territory" and PONa3_00363 "High Technology Infrastructure for Climate and Environment Monitoring" (I-AMICA) founded by Italian Ministry of University and Research (MIUR) PON 2007-2013. The ECMWF and CNMCA (Centro Nazionale di Meteorologia e Climatologia Aeronautica) are acknowledged for the use of the MARS (Meteorological Archive and Retrieval System).

Towards a More Accurate Solar Power Forecast By Improving NWP Model Physics

NASA Astrophysics Data System (ADS)

Köhler, C.; Lee, D.; Steiner, A.; Ritter, B.

2014-12-01

The growing importance and successive expansion of renewable energies raise new challenges for decision makers, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the uncertainties associated with the large share of weather-dependent power sources. Precise power forecast, well-timed energy trading on the stock market, and electrical grid stability can be maintained. The research project EWeLiNE is a collaboration of the German Weather Service (DWD), the Fraunhofer Institute (IWES) and three German transmission system operators (TSOs). Together, wind and photovoltaic (PV) power forecasts shall be improved by combining optimized NWP and enhanced power forecast models. The conducted work focuses on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. Not only the representation of the model cloud characteristics, but also special events like Sahara dust over Germany and the solar eclipse in 2015 are treated and their effect on solar power accounted for. An overview of the EWeLiNE project and results of the ongoing research will be presented.

Case Studies of Forecasting Ionospheric Total Electron Content

NASA Astrophysics Data System (ADS)

Mannucci, A. J.; Meng, X.; Verkhoglyadova, O. P.; Tsurutani, B.; McGranaghan, R. M.

2017-12-01

We report on medium-range forecast-mode runs of ionosphere-thermosphere coupled models that calculate ionospheric total electron content (TEC), focusing on low-latitude daytime conditions. A medium-range forecast-mode run refers to simulations that are driven by inputs that can be predicted 2-3 days in advance, for example based on simulations of the solar wind. We will present results from a weak geomagnetic storm caused by a high-speed solar wind stream on June 29, 2012. Simulations based on the Global Ionosphere Thermosphere Model (GITM) and the Thermosphere Ionosphere Electrodynamic General Circulation Model (TIEGCM) significantly over-estimate TEC in certain low latitude daytime regions, compared to TEC maps based on observations. We will present the results from a more intense coronal mass ejection (CME) driven storm where the simulations are closer to observations. We compare high latitude data sets to model inputs, such as auroral boundary and convection patterns, to assess the degree to which poorly estimated high latitude drivers may be the largest cause of discrepancy between simulations and observations. Our results reveal many factors that can affect the accuracy of forecasts, including the fidelity of empirical models used to estimate high latitude precipitation patterns, or observation proxies for solar EUV spectra, such as the F10.7 index. Implications for forecasts with few-day lead times are discussed

Validation of Model Forecasts of the Ambient Solar Wind

NASA Technical Reports Server (NTRS)

Macneice, P. J.; Hesse, M.; Kuznetsova, M. M.; Rastaetter, L.; Taktakishvili, A.

2009-01-01

Independent and automated validation is a vital step in the progression of models from the research community into operational forecasting use. In this paper we describe a program in development at the CCMC to provide just such a comprehensive validation for models of the ambient solar wind in the inner heliosphere. We have built upon previous efforts published in the community, sharpened their definitions, and completed a baseline study. We also provide first results from this program of the comparative performance of the MHD models available at the CCMC against that of the Wang-Sheeley-Arge (WSA) model. An important goal of this effort is to provide a consistent validation to all available models. Clearly exposing the relative strengths and weaknesses of the different models will enable forecasters to craft more reliable ensemble forecasting strategies. Models of the ambient solar wind are developing rapidly as a result of improvements in data supply, numerical techniques, and computing resources. It is anticipated that in the next five to ten years, the MHD based models will supplant semi-empirical potential based models such as the WSA model, as the best available forecast models. We anticipate that this validation effort will track this evolution and so assist policy makers in gauging the value of past and future investment in modeling support.

Active Longitude and Solar Flare Occurrences

NASA Astrophysics Data System (ADS)

Gyenge, N.; Ludmány, A.; Baranyi, T.

2016-02-01

The aim of the present work is to specify the spatio-temporal characteristics of flare activity observed by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) and the Geostationary Operational Environmental Satellite (GOES) in connection with the behavior of the longitudinal domain of enhanced sunspot activity known as active longitude (AL). By using our method developed for this purpose, we identified the AL in every Carrington Rotation provided by the Debrecen Photoheliographic Data. The spatial probability of flare occurrence has been estimated depending on the longitudinal distance from AL in the northern and southern hemispheres separately. We have found that more than 60% of the RHESSI and GOES flares is located within +/- 36^\\circ from the AL. Hence, the most flare-productive active regions tend to be located in or close to the active longitudinal belt. This observed feature may allow for the prediction of the geo-effective position of the domain of enhanced flaring probability. Furthermore, we studied the temporal properties of flare occurrence near the AL and several significant fluctuations were found. More precisely, the results of the method are the following fluctuations: 0.8, 1.3, and 1.8 years. These temporal and spatial properties of the solar flare occurrence within the active longitudinal belts could provide us with an enhanced solar flare forecasting opportunity.

Forecasting F10.7 with Solar Magnetic Flux Transport Modeling (Postprint)

DTIC Science & Technology

2012-04-03

Charles N. Arge Joel B. Mozer Project Manager, RVBXS Chief, RVB This report is published in the interest of...within 6 hours of the F10.7 measurements during the years 1993 through 2010, the Spearman correlation coefficient, rs, for an empirical model of...estimation of the Earth-side solar magnetic field distribution used to forecast F10.7. Spearman correlation values of approximately 0.97, 0.95, and 0.93 are

NREL: Renewable Resource Data Center - Solar Resource Publications

Science.gov Websites

Publications The following links provide useful information about solar resource tools and data resources, solar data, or solar technology". Resource Assessment and Forecasting Group Publications By | 1985 | 1984 | 1983 | 1982 | 1981 | 1980 Miscellaneous Printable Version RReDC Home Biomass Resource

A Two Dimensional Prediction of Solar Cycle 25

NASA Astrophysics Data System (ADS)

Munoz-Jaramillo, A.; Martens, P. C.

2017-12-01

To this date solar cycle most cycle predictions have focused on the forecast of solar cycle amplitude and cycle bell-curve shape. However, recent intriguing observational results suggest that all solar cycles follow the same longitudinal path regardless of their amplitude, and have a very similar decay once they reach a sufficient level of maturity. Cast in the light of our current understanding, these results suggest that the toroidal fields inside the Sun are subject to a very high turbulent diffusivity (of the order of magnitude of mixing-length estimates), and their equatorward propagation is driven by a steady meridional flow. Assuming this is the case, we will revisit the relationship between the polar fields at minimum and the amplitude of the next cycle and deliver a new generation of polar-field based predictions that include the depth of the minimum, as well as the latitude and time of the first active regions of solar cycle 25.

Investigation of the Effects of Solar and Geomagnetic Changes on the Total Electron Content: Mid-Latitude Region

NASA Astrophysics Data System (ADS)

Ulukavak, Mustafa; Yalcinkaya, Mualla

2016-04-01

The Global Positioning System (GPS) is used as an important tool for ionosphere monitoring and obtaining the Total Electron Content (TEC). GPS satellites, positioned in the Earth's orbit, are used as sensors to investigate the space weather conditions. In this study, solar and geomagnetic activity variations were investigated between the dates 1 March-30 June 2015 for the mid-latitude region. GPS-TEC variations were calculated for each selected International GNSS Service (IGS) station in Europe. GNSS data was obtained from Crustal Dynamics Data and Information System (CDDIS) archive. Solar and geomagnetic activity indices (Kp, F10.7 ve Dst) were obtained from the Oceanic and Atmospheric Administration (NOAA), the Canadian Space Weather Forecast Centre (CSWFC) and Data Analysis Center for geomagnetism and Space Magnetism Graduate School of Science, Kyoto University (WDC) archives. GPS-TEC variations were determined for the quiet periods of the solar and geomagnetic activities. GPS-TEC changes were then compared with respect to the quiet periods of the solar and geomagnetic activities. Global Ionosphere Maps (GIM) IONEX files, obtained from the IGS analysis center, was used to check the robustness of the GPS-TEC variations. The investigations revealed that it is possible to use the GPS-TEC data for monitoring the ionospheric disturbances.

Strong coronal channelling and interplanetary evolution of a solar storm up to Earth and Mars

PubMed Central

Möstl, Christian; Rollett, Tanja; Frahm, Rudy A.; Liu, Ying D.; Long, David M.; Colaninno, Robin C.; Reiss, Martin A.; Temmer, Manuela; Farrugia, Charles J.; Posner, Arik; Dumbović, Mateja; Janvier, Miho; Démoulin, Pascal; Boakes, Peter; Devos, Andy; Kraaikamp, Emil; Mays, Mona L.; Vršnak, Bojan

2015-01-01

The severe geomagnetic effects of solar storms or coronal mass ejections (CMEs) are to a large degree determined by their propagation direction with respect to Earth. There is a lack of understanding of the processes that determine their non-radial propagation. Here we present a synthesis of data from seven different space missions of a fast CME, which originated in an active region near the disk centre and, hence, a significant geomagnetic impact was forecasted. However, the CME is demonstrated to be channelled during eruption into a direction +37±10° (longitude) away from its source region, leading only to minimal geomagnetic effects. In situ observations near Earth and Mars confirm the channelled CME motion, and are consistent with an ellipse shape of the CME-driven shock provided by the new Ellipse Evolution model, presented here. The results enhance our understanding of CME propagation and shape, which can help to improve space weather forecasts. PMID:26011032

Prediction Model for Relativistic Electrons at Geostationary Orbit

NASA Technical Reports Server (NTRS)

Khazanov, George V.; Lyatsky, Wladislaw

2008-01-01

We developed a new prediction model for forecasting relativistic (greater than 2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/interplanetary magnetic field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is stable and incredibly high (about 0.9). The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible.

Relativistic Electrons at Geostationary Orbit: Modeling Results

NASA Technical Reports Server (NTRS)

Khazanov, George V.; Lyatsky, Wladislaw

2008-01-01

We developed a new prediction model for forecasting relativistic (greater than 2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/interplanetary magnetic field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is stable and incredibly high (about 0.9). The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible.

Solar Energetic Particles Events and Human Exploration: Measurements in a Space Habitat

NASA Astrophysics Data System (ADS)

Narici, L.; Berrilli, F.; Casolino, M.; Del Moro, D.; Forte, R.; Giovannelli, L.; Martucci, M.; Mergè, M.; Picozza, P.; Rizzo, A.; Scardigli, S.; Sparvoli, R.; Zeitlin, C.

2016-12-01

Solar activity is the source of Space Weather disturbances. Flares, CME and coronal holes modulate physical conditions of circumterrestrial and interplanetary space and ultimately the fluxes of high-energy ionized particles, i.e., solar energetic particle (SEP) and galactic cosmic ray (GCR) background. This ionizing radiation affects spacecrafts and biological systems, therefore it is an important issue for human exploration of space. During a deep space travel (for example the trip to Mars) radiation risk thresholds may well be exceeded by the crew, so mitigation countermeasures must be employed. Solar particle events (SPE) constitute high risks due to their impulsive high rate dose. Forecasting SPE appears to be needed and also specifically tailored to the human exploration needs. Understanding the parameters of the SPE that produce events leading to higher health risks for the astronauts in deep space is therefore a first priority issue. Measurements of SPE effects with active devices in LEO inside the ISS can produce important information for the specific SEP measured, relative to the specific detector location in the ISS (in a human habitat with a shield typical of manned space-crafts). Active detectors can select data from specific geo-magnetic regions along the orbits, allowing geo-magnetic selections that best mimic deep space radiation. We present results from data acquired in 2010 - 2012 by the detector system ALTEA inside the ISS (18 SPEs detected). We compare this data with data from the detector Pamela on a LEO satellite, with the RAD data during the Curiosity Journey to Mars, with GOES data and with several Solar physical parameters. While several features of the radiation modulation are easily understood by the effect of the geomagnetic field, as an example we report a proportionality of the flux in the ISS with the energetic proton flux measured by GOES, some features appear more difficult to interpret. The final goal of this work is to find the characteristics of solar events leading to highest radiation risks in a human habitat during deep space exploration to best focus the needed forecasting.

Application of data assimilation to solar wind forecasting models

NASA Astrophysics Data System (ADS)

Innocenti, M.; Lapenta, G.; Vrsnak, B.; Temmer, M.; Veronig, A.; Bettarini, L.; Lee, E.; Markidis, S.; Skender, M.; Crespon, F.; Skandrani, C.; Soteria Space-Weather Forecast; Data Assimilation Team

2010-12-01

Data Assimilation through Kalman filtering [1,2] is a powerful statistical tool which allows to combine modeling and observations to increase the degree of knowledge of a given system. We apply this technique to the forecast of solar wind parameters (proton speed, proton temperature, absolute value of the magnetic field and proton density) at 1 AU, using the model described in [3] and ACE data as observations. The model, which relies on GOES 12 observations of the percentage of the meridional slice of the sun covered by coronal holes, grants 1-day and 6-hours in advance forecasts of the aforementioned quantities in quiet times (CMEs are not taken into account) during the declining phase of the solar cycle and is tailored for specific time intervals. We show that the application of data assimilation generally improves the quality of the forecasts during quiet times and, more notably, extends the periods of applicability of the model, which can now provide reliable forecasts also in presence of CMEs and for periods other than the ones it was designed for. Acknowledgement: The research leading to these results has received funding from the European Commission’s Seventh Framework Programme (FP7/2007-2013) under the grant agreement N. 218816 (SOTERIA project: http://www.soteria-space.eu). References: [1] R. Kalman, J. Basic Eng. 82, 35 (1960); [2] G. Welch and G. Bishop, Technical Report TR 95-041, University of North Carolina, Department of Computer Science (2001); [3] B. Vrsnak, M. Temmer, and A. Veronig, Solar Phys. 240, 315 (2007).

Forecasting Optimal Solar Energy Supply in Jiangsu Province (China): A Systematic Approach Using Hybrid of Weather and Energy Forecast Models

PubMed Central

Zhao, Xiuli; Yiranbon, Ethel

2014-01-01

The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, “least-cost,” and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor. PMID:24511292

Forecasting optimal solar energy supply in Jiangsu Province (China): a systematic approach using hybrid of weather and energy forecast models.

PubMed

Zhao, Xiuli; Asante Antwi, Henry; Yiranbon, Ethel

2014-01-01

The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, "least-cost," and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.

Apparent Relations Between Solar Activity and Solar Tides Caused by the Planets

NASA Technical Reports Server (NTRS)

Hung, Ching-Cheh

2007-01-01

A solar storm is a storm of ions and electrons from the Sun. Large solar storms are usually preceded by solar flares, phenomena that can be characterized quantitatively from Earth. Twenty-five of the thirty-eight largest known solar flares were observed to start when one or more tide-producing planets (Mercury, Venus, Earth, and Jupiter) were either nearly above the event positions (less than 10 deg. longitude) or at the opposing side of the Sun. The probability for this to happen at random is 0.039 percent. This supports the hypothesis that the force or momentum balance (between the solar atmospheric pressure, the gravity field, and magnetic field) on plasma in the looping magnetic field lines in solar corona could be disturbed by tides, resulting in magnetic field reconnection, solar flares, and solar storms. Separately, from the daily position data of Venus, Earth, and Jupiter, an 11-year planet alignment cycle is observed to approximately match the sunspot cycle. This observation supports the hypothesis that the resonance and beat between the solar tide cycle and nontidal solar activity cycle influences the sunspot cycle and its varying magnitudes. The above relations between the unpredictable solar flares and the predictable solar tidal effects could be used and further developed to forecast the dangerous space weather and therefore reduce its destructive power against the humans in space and satellites controlling mobile phones and global positioning satellite (GPS) systems.

Application of a deep-learning method to the forecast of daily solar flare occurrence using Convolution Neural Network

NASA Astrophysics Data System (ADS)

Shin, Seulki; Moon, Yong-Jae; Chu, Hyoungseok

2017-08-01

As the application of deep-learning methods has been succeeded in various fields, they have a high potential to be applied to space weather forecasting. Convolutional neural network, one of deep learning methods, is specialized in image recognition. In this study, we apply the AlexNet architecture, which is a winner of Imagenet Large Scale Virtual Recognition Challenge (ILSVRC) 2012, to the forecast of daily solar flare occurrence using the MatConvNet software of MATLAB. Our input images are SOHO/MDI, EIT 195Å, and 304Å from January 1996 to December 2010, and output ones are yes or no of flare occurrence. We select training dataset from Jan 1996 to Dec 2000 and from Jan 2003 to Dec 2008. Testing dataset is chosen from Jan 2001 to Dec 2002 and from Jan 2009 to Dec 2010 in order to consider the solar cycle effect. In training dataset, we randomly select one fifth of training data for validation dataset to avoid the overfitting problem. Our model successfully forecasts the flare occurrence with about 0.90 probability of detection (POD) for common flares (C-, M-, and X-class). While POD of major flares (M- and X-class) forecasting is 0.96, false alarm rate (FAR) also scores relatively high(0.60). We also present several statistical parameters such as critical success index (CSI) and true skill statistics (TSS). Our model can immediately be applied to automatic forecasting service when image data are available.

An early prediction of 25th solar cycle using Hurst exponent

NASA Astrophysics Data System (ADS)

Singh, A. K.; Bhargawa, Asheesh

2017-11-01

The analysis of long memory processes in solar activity, space weather and other geophysical phenomena has been a major issue even after the availability of enough data. We have examined the data of various solar parameters like sunspot numbers, 10.7 cm radio flux, solar magnetic field, proton flux and Alfven Mach number observed for the year 1976-2016. We have done the statistical test for persistence of solar activity based on the value of Hurst exponent (H) which is one of the most classical applied methods known as rescaled range analysis. We have discussed the efficiency of this methodology as well as prediction content for next solar cycle based on long term memory. In the present study, Hurst exponent analysis has been used to investigate the persistence of above mentioned (five) solar activity parameters and a simplex projection analysis has been used to predict the ascension time and the maximum number of counts for 25th solar cycle. For available dataset of the year 1976-2016, we have calculated H = 0.86 and 0.82 for sunspot number and 10.7 cm radio flux respectively. Further we have calculated maximum number of counts for sunspot numbers and F10.7 cm index as 102.8± 24.6 and 137.25± 8.9 respectively. Using the simplex projection analysis, we have forecasted that the solar cycle 25th would start in the year 2021 (January) and would last up to the year 2031 (September) with its maxima in June 2024.

The Scientific Foundations of Forecasting Magnetospheric Space Weather

NASA Astrophysics Data System (ADS)

Eastwood, J. P.; Nakamura, R.; Turc, L.; Mejnertsen, L.; Hesse, M.

2017-11-01

The magnetosphere is the lens through which solar space weather phenomena are focused and directed towards the Earth. In particular, the non-linear interaction of the solar wind with the Earth's magnetic field leads to the formation of highly inhomogenous electrical currents in the ionosphere which can ultimately result in damage to and problems with the operation of power distribution networks. Since electric power is the fundamental cornerstone of modern life, the interruption of power is the primary pathway by which space weather has impact on human activity and technology. Consequently, in the context of space weather, it is the ability to predict geomagnetic activity that is of key importance. This is usually stated in terms of geomagnetic storms, but we argue that in fact it is the substorm phenomenon which contains the crucial physics, and therefore prediction of substorm occurrence, severity and duration, either within the context of a longer-lasting geomagnetic storm, but potentially also as an isolated event, is of critical importance. Here we review the physics of the magnetosphere in the frame of space weather forecasting, focusing on recent results, current understanding, and an assessment of probable future developments.

Exploiting the Magnetic Origin of Solar Activity in Forecasting Thermospheric Density Variations

DTIC Science & Technology

2014-09-01

computed daily sums of Φr integrated over the disk using synoptic maps from both MDI and the Helioseismic and Magnetic Imager ( HMI ) on the Solar Dynamics...generally well understood, making a proxy derived from measured magnetic fields potentially much easier 2010 2011 2012 2013 2014 0 1 2 3 HMI /SDO Φ r (1...200 250 300 F10.7 0 1 2 3 Φ r (1 02 3 M X ) r = 0.90 Figure 5: The same as Fig. 4, but for Φr derived from HMI observations of the magnetic field

A new data assimilation engine for physics-based thermospheric density models

NASA Astrophysics Data System (ADS)

Sutton, E. K.; Henney, C. J.; Hock-Mysliwiec, R.

2017-12-01

The successful assimilation of data into physics-based coupled Ionosphere-Thermosphere models requires rethinking the filtering techniques currently employed in fields such as tropospheric weather modeling. In the realm of Ionospheric-Thermospheric modeling, the estimation of system drivers is a critical component of any reliable data assimilation technique. How to best estimate and apply these drivers, however, remains an open question and active area of research. The recently developed method of Iterative Re-Initialization, Driver Estimation and Assimilation (IRIDEA) accounts for the driver/response time-delay characteristics of the Ionosphere-Thermosphere system relative to satellite accelerometer observations. Results from two near year-long simulations are shown: (1) from a period of elevated solar and geomagnetic activity during 2003, and (2) from a solar minimum period during 2007. This talk will highlight the challenges and successes of implementing a technique suited for both solar min and max, as well as expectations for improving neutral density forecasts.

Variability of foF2 in the African equatorial ionosphere

NASA Astrophysics Data System (ADS)

Akala, A. O.; Oyeyemi, E. O.; Somoye, E. O.; Adeloye, A. B.; Adewale, A. O.

2010-06-01

This paper presents the impact of diurnal, seasonal and solar activity effects on the variability of ionospheric foF2 in the African equatorial latitude. Three African ionospheric stations; Dakar (14.8°N, 17.4°W, dip: 11.4°N), Ouagadougou (12.4°N, 1.5°W, dip: 2.8°N) and Djibouti (11.5°N, 42.8°E, dip: 7.2°N) were considered for the investigation. The overall aim is to provide African inputs that will be of assistance at improving existing forecasting models. The diurnal analysis revealed that the ionospheric critical frequency (foF2) is more susceptible to variability during the night-time than the day-time, with two peaks in the range; 18-38% during post-sunset hours and 35-55% during post-midnight hours. The seasonal and solar activity analyses showed a post-sunset September Equinox maximum and June Solstice maximum of foF2 variability in all the stations for all seasons. At all the stations, foF2 variability was high for low solar activity year. Overall, we concluded that equatorial foF2 variability increases with decreasing solar activity during night-time.

The scientific challenges to forecasting and nowcasting the magnetospheric response to space weather (Invited)

NASA Astrophysics Data System (ADS)

Hesse, M.; Kuznetsova, M. M.; Birn, J.; Pulkkinen, A. A.

2013-12-01

Space weather is different from terrestrial weather in an essential way. Terrestrial weather has benefitted from a long history of research, which has led to a deep and detailed level of understanding. In comparison, space weather is scientifically in its infancy. Many key processes in the causal chains from processes on the Sun to space weather effects in various locations in the heliosphere remain either poorly understood or not understood at all. Space weather is therefore, and will remain in the foreseeable future, primarily a research field. Extensive further research efforts are needed before we can reasonably expect the precision and fidelity of weather forecasts. For space weather within the Earth's magnetosphere, the coupling between solar wind and magnetosphere is of crucial importance. While past research has provided answers, often on qualitative levels, to some of the most fundamental questions, answers to some of the latter and the ability to predict quantitatively remain elusive. This presentation will provide an overview of pertinent aspects of solar wind-magnetospheric coupling, its importance for space weather near the Earth, and it will analyze the state of our ability to describe and predict its efficiency. It will conclude with a discussion of research activities, which are aimed at improving our ability to quantitatively forecast coupling processes.

A New Polar Magnetic Index of Geomagnetic Activity and its Application to Monitoring Ionospheric Parameters

NASA Technical Reports Server (NTRS)

Lyatsky, Wladislaw; Khazanov, George V.

2008-01-01

For improving the reliability of Space Weather prediction, we developed a new, Polar Magnetic (PM) index of geomagnetic activity, which shows high correlation with both upstream solar wind data and related events in the magnetosphere and ionosphere. Similarly to the existing polar cap PC index, the new, PM index was computed from data from two near-pole geomagnetic observatories; however, the method for computing the PM index is different. The high correlation of the PM index with both solar wind data and events in Geospace environment makes possible to improve significantly forecasting geomagnetic disturbances and such important parameters as the cross-polar-cap voltage and global Joule heating in high latitude ionosphere, which play an important role in the development of geomagnetic, ionospheric and thermospheric disturbances. We tested the PM index for 10-year period (1995-2004). The correlation between PM index and upstream solar wind data for these years is very high (the average correlation coefficient R approximately equal to 0.86). The PM index also shows the high correlation with the cross-polar-cap voltage and hemispheric Joule heating (the correlation coefficient between the actual and predicted values of these parameters is approximately 0.9), which results in significant increasing the prediction reliability of these parameters. Using the PM index of geomagnetic activity provides a significant increase in the forecasting reliability of geomagnetic disturbances and related events in Geospace environment. The PM index may be also used as an important input parameter in modeling ionospheric, magnetospheric, and thermospheric processes.

A Public-Private-Acadmic Partnership to Advance Solar Power Forecasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haupt, Sue Ellen

The National Center for Atmospheric Research (NCAR) is pleased to have led a partnership to advance the state-of-the-science of solar power forecasting by designing, developing, building, deploying, testing, and assessing the SunCast™ Solar Power Forecasting System. The project has included cutting edge research, testing in several geographically- and climatologically-diverse high penetration solar utilities and Independent System Operators (ISOs), and wide dissemination of the research results to raise the bar on solar power forecasting technology. The partners include three other national laboratories, six universities, and industry partners. This public-private-academic team has worked in concert to perform use-inspired research to advance solarmore » power forecasting through cutting-edge research to advance both the necessary forecasting technologies and the metrics for evaluating them. The project has culminated in a year-long, full-scale demonstration of provide irradiance and power forecasts to utilities and ISOs to use in their operations. The project focused on providing elements of a value chain, beginning with the weather that causes a deviation from clear sky irradiance and progresses through monitoring and observations, modeling, forecasting, dissemination and communication of the forecasts, interpretation of the forecast, and through decision-making, which produces outcomes that have an economic value. The system has been evaluated using metrics developed specifically for this project, which has provided rich information on model and system performance. Research was accomplished on the very short range (0-6 hours) Nowcasting system as well as on the longer term (6-72 hour) forecasting system. The shortest range forecasts are based on observations in the field. The shortest range system, built by Brookhaven National Laboratory (BNL) and based on Total Sky Imagers (TSIs) is TSICast, which operates on the shortest time scale with a latency of only a few minutes and forecasts that currently go out to about 15 min. This project has facilitated research in improving the hardware and software so that the new high definition cameras deployed at multiple nearby locations allow discernment of the clouds at varying levels and advection according to the winds observed at those levels. Improvements over “smart persistence” are about 29% for even these very short forecasts. StatCast is based on pyranometer data measured at the site as well as concurrent meteorological observations and forecasts. StatCast is based on regime-dependent artificial intelligence forecasting techniques and has been shown to improve on “smart persistence” forecasts by 15-50%. A second category of short-range forecasting systems employ satellite imagery and use that information to discern clouds and their motion, allowing them to project the clouds, and the resulting blockage of irradiance, in time. CIRACast (the system produced by the Cooperative Institute for Atmospheric Research [CIRA] at Colorado State University) was already one of the more advanced cloud motion systems, which is the reason that team was brought to this project. During the project timeframe, the CIRA team was able to advance cloud shadowing, parallax removal, and implementation of better advecting winds at different altitudes. CIRACast shows generally a 25-40% improvement over Smart Persistence between sunrise and approximately 1600 UTC (Coordinated Universal Time) . A second satellite-based system, MADCast (Multi-sensor Advective Diffusive foreCast system), assimilates data from multiple satellite imagers and profilers to assimilate a fully three-dimensional picture of the cloud into the dynamic core of WRF. During 2015, MADCast (provided at least 70% improvement over Smart Persistence, with most of that skill being derived during partly cloudy conditions. That allows advection of the clouds via the Weather Research and Forecasting (WRF) model dynamics directly. After WRF-Solar™ showed initial success, it was also deployed in nowcasting mode with coarser runs out to 6 hours made hourly. It provided improvements on the order of 50-60% over Smart Persistence for forecasts up to 1600 UTC. The advantages of WRF-Solar-Nowcasting and MADCast were then blended to develop the new MAD-WRF model that incorporates the most important features of each of those models, both assimilating satellite cloud fields and using WRF-So far physics to develop and dissipate clouds. MAE improvements for MAD-WRF for forecasts from 3-6 hours are improved over WRF-Solar-Now by 20%. While all the Nowcasting system components by themselves provide improvement over Smart Persistence, the largest benefit is derived when they are smartly blended together by the Nowcasting Integrator to produce an integrated forecast. The development of WRF-Solar™ under this project has provided the first numerical weather prediction (NWP) model specifically designed to meet the needs of irradiance forecasting. The first augmentation improved the solar tracking algorithm to account for deviations associated with the eccentricity of the Earth’s orbit and the obliquity of the Earth. Second, WRF-Solar™ added the direct normal irradiance (DNI) and diffuse (DIF) components from the radiation parameterization to the model output. Third, efficient parameterizations were implemented to either interpolate the irradiance in between calls to the expensive radiative transfer parameterization, or to use a fast radiative transfer code that avoids computing three-dimensional heating rates but provides the surface irradiance. Fourth, a new parameterization was developed to improve the representation of absorption and scattering of radiation by aerosols (aerosol direct effect). A fifth advance is that the aerosols now interact with the cloud microphysics, altering the cloud evolution and radiative properties, an effect that has been traditionally only implemented in atmospheric computationally costly chemistry models. A sixth development accounts for the feedbacks that sub-grid scale clouds produce in shortwave irradiance as implemented in a shallow cumulus parameterization Finally, WRF-Solar™ also allows assimilation of infrared irradiances from satellites to determine the three dimensional cloud field, allowing for an improved initialization of the cloud field that increases the performance of short-range forecasts. We find that WRF-Solar™ can improve clear sky irradiance prediction by 15-80% over a standard version of WRF, depending on location and cloud conditions. In a formal comparison to the NAM baseline, WRF-Solar™ showed improvements in the Day-Ahead forecast of 22-42%. The SunCast™ system requires substantial software engineering to blend all of the new model components as well as existing publically available NWP model runs. To do this we use an expert system for the Nowcasting blender and the Dynamic Integrated foreCast (DICast®) system for the NWP models. These two systems are then blended, we use an empirical power conversion method to convert the irradiance predictions to power, then apply an analog ensemble (AnEn) approach to further tune the forecast as well as to estimate its uncertainty. The AnEn module decreased RMSE (root mean squared error) by 17% over the blended SunCast™ power forecasts and provided skill in the probabilistic forecast with a Brier Skill Score of 0.55. In addition, we have also developed a Gridded Atmospheric Forecast System (GRAFS) in parallel, leveraging cost share funds. An economic evaluation based on Production Cost Modeling in the Public Service Company of Colorado showed that the observed 50% improvement in forecast accuracy will save their customers $819,200 with the projected MW deployment for 2024. Using econometrics, NCAR has scaled this savings to a national level and shown that an annual expected savings for this 50% forecast error reduction ranges from $11M in 2015 to $43M expected in 2040 with increased solar deployment. This amounts to a $455M discounted savings over the 26 year period of analysis.« less

WIRE: Weather Intelligence for Renewable Energies

NASA Astrophysics Data System (ADS)

Heimo, A.; Cattin, R.; Calpini, B.

2010-09-01

Renewable energies such as wind and solar energy will play an important, even decisive role in order to mitigate and adapt to the projected dramatic consequences to our society and environment due to climate change. Due to shrinking fossil resources, the transition to more and more renewable energy shares is unavoidable. But, as wind and solar energy are strongly dependent on highly variable weather processes, increased penetration rates will also lead to strong fluctuations in the electricity grid which need to be balanced. Proper and specific forecasting of ‘energy weather' is a key component for this. Therefore, it is today appropriate to scientifically address the requirements to provide the best possible specific weather information for forecasting the energy production of wind and solar power plants within the next minutes up to several days. Towards such aims, Weather Intelligence will first include developing dedicated post-processing algorithms coupled with weather prediction models and with past and/or online measurement data especially remote sensing observations. Second, it will contribute to investigate the difficult relationship between the highly intermittent weather dependent power production and concurrent capacities such as transport and distribution of this energy to the end users. Selecting, resp. developing surface-based and satellite remote sensing techniques well adapted to supply relevant information to the specific post-processing algorithms for solar and wind energy production short-term forecasts is a major task with big potential. It will lead to improved energy forecasts and help to increase the efficiency of the renewable energy productions while contributing to improve the management and presumably the design of the energy grids. The second goal will raise new challenges as this will require first from the energy producers and distributors definitions of the requested input data and new technologies dedicated to the management of power plants and electricity grids and second from the meteorological measurement community to deliver suitable, short term high quality forecasts to fulfill these requests with emphasis on highly variable weather conditions and spatially distributed energy productions often located in complex terrain. This topic has been submitted for a new COST Action under the title "Short-Term High Resolution Wind and Solar Energy Production Forecasts".

Addressing forecast uncertainty impact on CSP annual performance

NASA Astrophysics Data System (ADS)

Ferretti, Fabio; Hogendijk, Christopher; Aga, Vipluv; Ehrsam, Andreas

2017-06-01

This work analyzes the impact of weather forecast uncertainty on the annual performance of a Concentrated Solar Power (CSP) plant. Forecast time series has been produced by a commercial forecast provider using the technique of hindcasting for the full year 2011 in hourly resolution for Ouarzazate, Morocco. Impact of forecast uncertainty has been measured on three case studies, representing typical tariff schemes observed in recent CSP projects plus a spot market price scenario. The analysis has been carried out using an annual performance model and a standard dispatch optimization algorithm based on dynamic programming. The dispatch optimizer has been demonstrated to be a key requisite to maximize the annual revenues depending on the price scenario, harvesting the maximum potential out of the CSP plant. Forecasting uncertainty affects the revenue enhancement outcome of a dispatch optimizer depending on the error level and the price function. Results show that forecasting accuracy of direct solar irradiance (DNI) is important to make best use of an optimized dispatch but also that a higher number of calculation updates can partially compensate this uncertainty. Improvement in revenues can be significant depending on the price profile and the optimal operation strategy. Pathways to achieve better performance are presented by having more updates both by repeatedly generating new optimized trajectories but also more often updating weather forecasts. This study shows the importance of working on DNI weather forecasting for revenue enhancement as well as selecting weather services that can provide multiple updates a day and probabilistic forecast information.

Solar Cycle 24 and the Solar Dynamo

NASA Technical Reports Server (NTRS)

Pesnell, W. D.; Schatten, K.

2007-01-01

We will discuss the polar field precursor method for solar activity prediction, which predicts cycle 24 will be significantly lower than recent activity cycles, and some new ideas rejuvenating Babcock's shallow surface dynamo. The polar field precursor method is based on Babcock and Leighton's dynamo models wherein the polar field at solar minimum plays a major role in generating the next cycle's toroidal field and sunspots. Thus, by examining the polar fields of the Sun near solar minimum, a forecast for the next cycle's activity is obtained. With the current low value for the Sun's polar fields, this method predicts solar cycle 24 will be one of the lowest in recent times, with smoothed F10.7 radio flux values peaking near 135 plus or minus 35 (2 sigma), in the 2012-2013 timeframe (equivalent to smoothed Rz near 80 plus or minus 35 [2 sigma]). One may have to consider solar activity as far back as the early 20th century to find a cycle of comparable magnitude. We discuss unusual behavior in the Sun's polar fields that support this prediction. Normally, the solar precursor method is consistent with the geomagnetic precursor method, wherein geomagnetic variations are thought to be a good measure of the Sun's polar field strength. Because of the unusual polar field, the Earth does not appear to be currently bathed in the Sun's extended polar field (the interplanetary field), hence negating the primal cause behind the geomagnetic precursor technique. We also discuss how percolation may support Babcock's original shallow solar dynamo. In this process ephemeral regions from the solar magnetic carpet, guided by shallow surface fields, may collect to form pores and sunspots.

Comparing Temporally-Separated Solar Wind Structures at 1 AU (STEREO A and OMNI)

NASA Astrophysics Data System (ADS)

Galvin, A. B.; Farrugia, C. J.; Jian, L. K.

2017-12-01

One may use the longitudinal coverage of different spacecraft assets, or the same asset over sequential Carrington Rotations, to study the solar wind behavior from long-lived structures (coronal holes, active regions), or occasionally observe the extent of transient structures (Farrugia et al., 2011). This is of interest as the evolution of the extent and persistence of interplanetary coronal mass ejections (ICMEs) and of stream interaction regions (SIRs) have implications for space weather forecasting. One challenge is that one must be aware of the temporal evolution of the structure on the Sun and the affect of `sampling' different solar sources due to different solar latitudes of the in-situ spacecraft observations. Here we look at case studies of recent event time intervals during 2015-2017 where solar wind emanating from long-lived coronal-hole structures are observed both at STEREO A and at near-Earth assets (OMNI2). The observations are taken at similar solar latitudes and longitudes but temporally separated by several days or weeks.

Comparative analysis of GPS-derived TEC estimates and foF2 observations during storm conditions towards the expansion of ionospheric forecasting capabilities over Europe

NASA Astrophysics Data System (ADS)

Tsagouri, Ioanna; Belehaki, Anna; Elias, Panagiotis

2017-04-01

This paper builts the discussion on the comparative analysis of the variations in the peak electron density at F2 layer and the TEC parameter during a significant number of geomagnetic storm events that occurred in the present solar cycle 24. The ionospheric disturbances are determined through the comparison of actual observations of the foF2 critical frequency and GPS-TEC estimates obtained over European locations with the corresponding median estimates, and they are analysed in conjunction to the solar wind conditions at L1 point that are monitored by the ACE spacecraft. The quantification of the storm impact on the TEC parameter in terms of possible limitations introduced by different TEC derivation methods is carefully addressed.The results reveal similarities and differences in the response of the two parameters with respect to the solar wind drivers of the storms, as well as the local time and the latitude of the observation point. The aforementioned dependences drive the storm-time forecasts of the SWIF model (Solar Wind driven autorgressive model for Ionospheric short-term Forecast), which is operationally implemented in the DIAS system (http://dias.space.noa.gr) and extensively tested in performance at several occassions. In its present version, the model provides alerts and warnings for upcoming ionospheric disturbances, as well as single site and regional forecasts of the foF2 characteristic over Europe up to 24 hours ahead based on the assesment of the solar wind conditions at ACE location. In that respect, the results obtained above support the upgrade of the SWIF's modeling technique in forecasting the storm-time TEC variation within an operational environment several hours in advance. Preliminary results on the evaluation of the model's efficiency in TEC prediction are also discussed, giving special attention in the assesment of the capabilities through the TEC-derivation uncertanties for future discussions.

Cloud Forecasting and 3-D Radiative Transfer Model Validation using Citizen-Sourced Imagery

NASA Astrophysics Data System (ADS)

Gasiewski, A. J.; Heymsfield, A.; Newman Frey, K.; Davis, R.; Rapp, J.; Bansemer, A.; Coon, T.; Folsom, R.; Pfeufer, N.; Kalloor, J.

2017-12-01

Cloud radiative feedback mechanisms are one of the largest sources of uncertainty in global climate models. Variations in local 3D cloud structure impact the interpretation of NASA CERES and MODIS data for top-of-atmosphere radiation studies over clouds. Much of this uncertainty results from lack of knowledge of cloud vertical and horizontal structure. Surface-based data on 3-D cloud structure from a multi-sensor array of low-latency ground-based cameras can be used to intercompare radiative transfer models based on MODIS and other satellite data with CERES data to improve the 3-D cloud parameterizations. Closely related, forecasting of solar insolation and associated cloud cover on time scales out to 1 hour and with spatial resolution of 100 meters is valuable for stabilizing power grids with high solar photovoltaic penetrations. Data for cloud-advection based solar insolation forecasting with requisite spatial resolution and latency needed to predict high ramp rate events obtained from a bottom-up perspective is strongly correlated with cloud-induced fluctuations. The development of grid management practices for improved integration of renewable solar energy thus also benefits from a multi-sensor camera array. The data needs for both 3D cloud radiation modelling and solar forecasting are being addressed using a network of low-cost upward-looking visible light CCD sky cameras positioned at 2 km spacing over an area of 30-60 km in size acquiring imagery on 30 second intervals. Such cameras can be manufactured in quantity and deployed by citizen volunteers at a marginal cost of 200-400 and operated unattended using existing communications infrastructure. A trial phase to understand the potential utility of up-looking multi-sensor visible imagery is underway within this NASA Citizen Science project. To develop the initial data sets necessary to optimally design a multi-sensor cloud camera array a team of 100 citizen scientists using self-owned PDA cameras is being organized to collect distributed cloud data sets suitable for MODIS-CERES cloud radiation science and solar forecasting algorithm development. A low-cost and robust sensor design suitable for large scale fabrication and long term deployment has been developed during the project prototyping phase.

The National Solar Radiation Database (NSRDB)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sengupta, Manajit; Habte, Aron; Lopez, Anthony

This presentation provides a high-level overview of the National Solar Radiation Database (NSRDB), including sensing, measurement and forecasting, and discusses observations that are needed for research and product development.

On an improvement of UV index forecast: UV index diagnosis and forecast for Belsk, Poland, in Spring/Summer 1999

NASA Astrophysics Data System (ADS)

Krzyścin, J. W.; Jaroslawski, J.; Sobolewski, P.

2001-10-01

A forecast of the UV index for the following day is presented. The standard approach to the UV index modelling is applied, i.e., the clear-sky UV index is multiplied by the UV cloud transmission factor. The input to the clear-sky model (tropospheric ultraviolet and visible-TUV model, Madronich, in: M. Tevini (Ed.), Environmental Effects of Ultraviolet Radiation, Lewis Publisher, Boca Raton, /1993, p. 17) consists of the total ozone forecast (by a regression model using the observed and forecasted meteorological variables taken as the initial values of aviation (AVN) global model and their 24-hour forecasts, respectively) and aerosols optical depth (AOD) forecast (assumed persistence). The cloud transmission factor forecast is inferred from the 24-h AVN model run for the total (Sun/+sky) solar irradiance at noon. The model is validated comparing the UV index forecasts with the observed values, which are derived from the daily pattern of the UV erythemal irradiance taken at Belsk (52°N,21°E), Poland, by means of the UV Biometer Solar model 501A for the period May-September 1999. Eighty-one percent and 92% of all forecasts fall into /+/-1 and /+/-2 index unit range, respectively. Underestimation of UV index occurs only in 15%. Thus, the model gives a high security in Sun protection for the public. It is found that in /~35% of all cases a more accurate forecast of AOD is needed to estimate the daily maximum of clear-sky irradiance with the error not exceeding 5%. The assumption of the persistence of the cloud characteristics appears as an alternative to the 24-h forecast of the cloud transmission factor in the case when the AVN prognoses are not available.

Updates on CCMC Activities and GSFC Space Weather Services

NASA Technical Reports Server (NTRS)

Zhengm Y.; Hesse, M.; Kuznetsova, M.; Pulkkinen, A.; Rastaetter, L.; Maddox, M.; Taktakishvili, A.; Berrios, D.; Chulaki, A.; Lee, H.;

Acceleration, Transport, Forecasting and Impact of solar energetic particles in the framework of the 'HESPERIA' HORIZON 2020 project

NASA Astrophysics Data System (ADS)

Malandraki, Olga; Klein, Karl-Ludwig; Vainio, Rami; Agueda, Neus; Nunez, Marlon; Heber, Bernd; Buetikofer, Rolf; Sarlanis, Christos; Crosby, Norma

2017-04-01

High-energy solar energetic particles (SEPs) emitted from the Sun are a major space weather hazard motivating the development of predictive capabilities. In this work, the current state of knowledge on the origin and forecasting of SEP events will be reviewed. Subsequently, we will present the EU HORIZON2020 HESPERIA (High Energy Solar Particle Events foRecastIng and Analysis) project, its structure, its main scientific objectives and forecasting operational tools, as well as the added value to SEP research both from the observational as well as the SEP modelling perspective. The project addresses through multi-frequency observations and simulations the chain of processes from particle acceleration in the corona, particle transport in the magnetically complex corona and interplanetary space to the detection near 1 AU. Furthermore, publicly available software to invert neutron monitor observations of relativistic SEPs to physical parameters that can be compared with space-borne measurements at lower energies is provided for the first time by HESPERIA. In order to achieve these goals, HESPERIA is exploiting already available large datasets stored in databases such as the neutron monitor database (NMDB) and SEPServer that were developed under EU FP7 projects from 2008 to 2013. Forecasting results of the two novel SEP operational forecasting tools published via the consortium server of 'HESPERIA' will be presented, as well as some scientific key results on the acceleration, transport and impact on Earth of high-energy particles. Acknowledgement: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 637324.

Fine Forecasts: Encouraging the Media to Include Ultraviolet Radiation Information in Summertime Weather Forecasts

ERIC Educational Resources Information Center

Richards, R.; Reeder, A. I.; Bulliard, J.-L.

2004-01-01

Melanoma and skin cancer are largely attributable to over-exposure to solar ultraviolet radiation (UVR). Reports of UVR levels within media weather forecasts appear to be well received by the public and have good potential to communicate the need for appropriate sun protection to a broad audience. This study describes provision of UVR messages by…

An Analysis of Unseasonal Equatorial Plasma Bubbles in July 2014

NASA Astrophysics Data System (ADS)

Carter, B. A.; Currie, J. L.; Pradipta, R.; Groves, K. M.; Caton, R. G.; Yokoyama, T.

2017-12-01

In the equatorial ionosphere, the Raleigh-Taylor (RT) plasma instability in the post sunset region is known to cause plasma depletions, known as equatorial plasma bubbles (EPBs). These EPBs can have adverse effects on satellite-reliant technologies by causing scintillations in the phase and amplitude of Global Navigation Satellite System (GNSS) signals. The effect of EPBs on satellite-reliant technologies highlights a need for reliable forecasting of EPBs in the low-latitude regions, which requires a solid understanding of their climatology and daily variability. The climatology of EPB occurrence is known to correlate with the angle between the magnetic field and solar terminator. This angle controls the longitudinal E-region conductivity gradient across the day-night terminator, which influences the strength of the pre-reversal enhancement in the upward plasma drift, a dominant term in the linear RT growth rate. This relationship is well established from ground-based GNSS and satellite-based studies. However, reliable forecasts have not been developed by space weather forecasting agencies due to the lack of understanding of EPB daily variability. During July, EPB occurrence is small in the South-East Asia longitude sector due to the relatively large angle between the magnetic field and solar terminator. As a result, the pre-reversal enhancement in the upward plasma drift is typically low during this period, creating less favourable conditions for EPB growth. However, despite the typically low pre-reversal enhancement strength, this analysis reveals that July 2014 is not devoid of EPB events above South-East Asia. These unseasonal EPB events during July 2014 are studied in the context of the prevalently low solar and geomagnetic activity conditions. Given the lack of solar and geomagnetic control, the influence of the lower atmosphere on EPB generation (e.g., via atmospheric gravity wave seeding) is explored. These events provide a unique opportunity to investigate the factors that affect the daily variability of EPBs, which will contribute towards the development of EPB prediction capabilities.

NREL Projects Awarded More Than $3 Million to Advance Novel Solar

Science.gov Websites

in Grid Operations," evaluating a research solution to better integrate solar power generation funding program, which advances state-of-the-art techniques for predicting solar power generation to Office to advance predictive modeling of solar power as part of its Solar Forecasting 2 funding program

High-quality weather data for grid integration studies

NASA Astrophysics Data System (ADS)

Draxl, C.

2016-12-01

As variable renewable power penetration levels increase in power systems worldwide, renewable integration studies are crucial to ensure continued economic and reliable operation of the power grid. In this talk we will shed light on requirements for grid integration studies as far as wind and solar energy are concerned. Because wind and solar plants are strongly impacted by weather, high-resolution and high-quality weather data are required to drive power system simulations. Future data sets will have to push limits of numerical weather prediction to yield these high-resolution data sets, and wind data will have to be time-synchronized with solar data. Current wind and solar integration data sets will be presented. The Wind Integration National Dataset (WIND) Toolkit is the largest and most complete grid integration data set publicly available to date. A meteorological data set, wind power production time series, and simulated forecasts created using the Weather Research and Forecasting Model run on a 2-km grid over the continental United States at a 5-min resolution is now publicly available for more than 126,000 land-based and offshore wind power production sites. The Solar Integration National Dataset (SIND) is available as time synchronized with the WIND Toolkit, and will allow for combined wind-solar grid integration studies. The National Solar Radiation Database (NSRDB) is a similar high temporal- and spatial resolution database of 18 years of solar resource data for North America and India. Grid integration studies are also carried out in various countries, which aim at increasing their wind and solar penetration through combined wind and solar integration data sets. We will present a multi-year effort to directly support India's 24x7 energy access goal through a suite of activities aimed at enabling large-scale deployment of clean energy and energy efficiency. Another current effort is the North-American-Renewable-Integration-Study, with the aim of providing a seamless data set across borders for a whole continent, to simulate and analyze the impacts of potential future large wind and solar power penetrations on bulk power system operations.

Solar thematic maps for space weather operations

USGS Publications Warehouse

Rigler, E. Joshua; Hill, Steven M.; Reinard, Alysha A.; Steenburgh, Robert A.

2012-01-01

Thematic maps are arrays of labels, or "themes", associated with discrete locations in space and time. Borrowing heavily from the terrestrial remote sensing discipline, a numerical technique based on Bayes' theorem captures operational expertise in the form of trained theme statistics, then uses this to automatically assign labels to solar image pixels. Ultimately, regular thematic maps of the solar corona will be generated from high-cadence, high-resolution SUVI images, the solar ultraviolet imager slated to fly on NOAA's next-generation GOES-R series of satellites starting ~2016. These thematic maps will not only provide quicker, more consistent synoptic views of the sun for space weather forecasters, but digital thematic pixel masks (e.g., coronal hole, active region, flare, etc.), necessary for a new generation of operational solar data products, will be generated. This paper presents the mathematical underpinnings of our thematic mapper, as well as some practical algorithmic considerations. Then, using images from the Solar Dynamics Observatory (SDO) Advanced Imaging Array (AIA) as test data, it presents results from validation experiments designed to ascertain the robustness of the technique with respect to differing expert opinions and changing solar conditions.

South Pole of the Sun, March 20, 2007

NASA Image and Video Library

2007-04-27

NASA Solar TErrestrial RElations Observatory satellites have provided the first 3-dimensional images of the Sun. This view will aid scientists ability to understand solar physics to improve space weather forecasting. .

North Pole of the Sun, March 20, 2007

NASA Image and Video Library

2007-04-27

NASA Solar TErrestrial RElations Observatory satellites have provided the first 3-dimensional images of the Sun. This view will aid scientists ability to understand solar physics to improve space weather forecasting.

Forecasting E > 50-MeV proton events with the proton prediction system (PPS)

NASA Astrophysics Data System (ADS)

Kahler, Stephen W.; White, Stephen M.; Ling, Alan G.

2017-11-01

Forecasting solar energetic (E > 10-MeV) particle (SEP) events is an important element of space weather. While several models have been developed for use in forecasting such events, satellite operations are particularly vulnerable to higher-energy (≥50-MeV) SEP events. Here we validate one model, the proton prediction system (PPS), which extends to that energy range. We first develop a data base of E ≥ 50-MeV proton events >1.0 proton flux units (pfu) events observed on the GOES satellite over the period 1986-2016. We modify the PPS to forecast proton events at the reduced level of 1 pfu and run PPS for four different solar input parameters: (1) all ≥M5 solar X-ray flares; (2) all ≥200 sfu 8800-MHz bursts with associated ≥M5 flares; (3) all ≥500 sfu 8800-MHz bursts; and (4) all ≥5000 sfu 8800-MHz bursts. The validation contingency tables and skill scores are calculated for all groups and used as a guide to use of the PPS. We plot the false alarms and missed events as functions of solar source longitude, and argue that the longitude-dependence employed by PPS does not match modern observations. Use of the radio fluxes as the PPS driver tends to result in too many false alarms at the 500 sfu threshold, and misses more events than the soft X-ray predictor at the 5000 sfu threshold.

NREL and IBM Improve Solar Forecasting with Big Data | Energy Systems

Science.gov Websites

forecasting model using deep-machine-learning technology. The multi-scale, multi-model tool, named Watt-sun the first standard suite of metrics for this purpose. Validating Watt-sun at multiple sites across the

Analysis and verification of a prediction model of solar energetic proton events

NASA Astrophysics Data System (ADS)

Wang, J.; Zhong, Q.

2017-12-01

The solar energetic particle event can cause severe radiation damages near Earth. The alerts and summary products of the solar energetic proton events were provided by the Space Environment Prediction Center (SEPC) according to the flux of the greater than 10 MeV protons taken by GOES satellite in geosynchronous orbit. The start of a solar energetic proton event is defined as the time when the flux of the greater than 10 MeV protons equals or exceeds 10 proton flux units (pfu). In this study, a model was developed to predict the solar energetic proton events, provide the warning for the solar energetic proton events at least minutes in advance, based on both the soft X-ray flux and integral proton flux taken by GOES. The quality of the forecast model was measured against verifications of accuracy, reliability, discrimination capability, and forecast skills. The peak flux and rise time of the solar energetic proton events in the six channels, >1MeV, >5 MeV, >10 MeV, >30 MeV, >50 MeV, >100 MeV, were also simulated and analyzed.

An empirical model to forecast solar wind velocity through statistical modeling

NASA Astrophysics Data System (ADS)

Gao, Y.; Ridley, A. J.

2013-12-01

The accurate prediction of the solar wind velocity has been a major challenge in the space weather community. Previous studies proposed many empirical and semi-empirical models to forecast the solar wind velocity based on either the historical observations, e.g. the persistence model, or the instantaneous observations of the sun, e.g. the Wang-Sheeley-Arge model. In this study, we use the one-minute WIND data from January 1995 to August 2012 to investigate and compare the performances of 4 models often used in literature, here referred to as the null model, the persistence model, the one-solar-rotation-ago model, and the Wang-Sheeley-Arge model. It is found that, measured by root mean square error, the persistence model gives the most accurate predictions within two days. Beyond two days, the Wang-Sheeley-Arge model serves as the best model, though it only slightly outperforms the null model and the one-solar-rotation-ago model. Finally, we apply the least-square regression to linearly combine the null model, the persistence model, and the one-solar-rotation-ago model to propose a 'general persistence model'. By comparing its performance against the 4 aforementioned models, it is found that the accuracy of the general persistence model outperforms the other 4 models within five days. Due to its great simplicity and superb performance, we believe that the general persistence model can serve as a benchmark in the forecast of solar wind velocity and has the potential to be modified to arrive at better models.

915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jensen, M.; Bartholomew, M. J.; Giangrande, S.

When considering the amount of shortwave radiation incident on a photovoltaic solar array and, therefore, the amount and stability of the energy output from the system, clouds represent the greatest source of short-term (i.e., scale of minutes to hours) variability through scattering and reflection of incoming solar radiation. Providing estimates of this short-term variability is important for determining and regulating the output from large solar arrays as they connect with the larger power infrastructure. In support of the installation of a 37-MW solar array on the grounds of Brookhaven National Laboratory (BNL), a study of the impacts of clouds onmore » the output of the solar array has been undertaken. The study emphasis is on predicting the change in surface solar radiation resulting from the observed/forecast cloud field on a 5-minute time scale. At these time scales, advection of cloud elements over the solar array is of particular importance. As part of the BNL Aerosol Life Cycle Intensive Operational Period (IOP), a 915-MHz Radar Wind Profiler (RWP) was deployed to determine the profile of low-level horizontal winds and the depth of the planetary boundary layer. The initial deployment mission of the 915-MHz RWP for cloud forecasting has been expanded the deployment to provide horizontal wind measurements for estimating and constraining cloud advection speeds. A secondary focus is on the observation of dynamics and microphysics of precipitation during cold season/winter storms on Long Island. In total, the profiler was deployed at BNL for 1 year from May 2011 through May 2012.« less

915-Mhz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jensen, M.; Bartholomew, M. J.; Giangrande, S.

When considering the amount of shortwave radiation incident on a photovoltaic solar array and, therefore, the amount and stability of the energy output from the system, clouds represent the greatest source of short-term (i.e., scale of minutes to hours) variability through scattering and reflection of incoming solar radiation. Providing estimates of this short-term variability is important for determining and regulating the output from large solar arrays as they connect with the larger power infrastructure. In support of the installation of a 37-MW solar array on the grounds of Brookhaven National Laboratory (BNL), a study of the impacts of clouds onmore » the output of the solar array has been undertaken. The study emphasis is on predicting the change in surface solar radiation resulting from the observed/forecast cloud field on a 5-minute time scale. At these time scales, advection of cloud elements over the solar array is of particular importance. As part of the BNL Aerosol Life Cycle Intensive Operational Period (IOP), a 915-MHz Radar Wind Profiler (RWP) was deployed to determine the profile of low-level horizontal winds and the depth of the planetary boundary layer. The initial deployment mission of the 915-MHz RWP for cloud forecasting has been expanded the deployment to provide horizontal wind measurements for estimating and constraining cloud advection speeds. A secondary focus is on the observation of dynamics and microphysics of precipitation during cold season/winter storms on Long Island. In total, the profiler was deployed at BNL for 1 year from May 2011 through May 2012.« less

Effects of Solar UV Radiation and Climate Change on Biogeochemical Cycling: Interactions and Feedbacks

EPA Science Inventory

Solar UV radiation, climate and other drivers of global change are undergoing significant changes and models forecast that these changes will continue for the remainder of this century. Here we assess the effects of solar UV radiation on biogeochemical cycles and the interactions...

Space weather activities in Australia

NASA Astrophysics Data System (ADS)

Cole, D.

Space Weather Plan Australia has a draft space weather plan to drive and focus appropriate research into services that meet future industry and social needs. The Plan has three main platforms, space weather monitoring and service delivery, support for priority research, and outreach to the community. The details of monitoring, service, research and outreach activities are summarised. A ground-based network of 14 monitoring stations from Antarctica to Papua New Guinea is operated by IPS, a government agency. These sites monitor ionospheric and geomagnetic characteristics, while two of them also monitor the sun at radio and optical wavelengths. Services provided through the Australian Space Forecast Centre (ASFC) include real-time information on the solar, space, ionospheric and geomagnetic environments. Data are gathered automatically from monitoring sites and integrated with data exchanged internationally to create snapshots of current space weather conditions and forecasts of conditions up to several days ahead. IPS also hosts the WDC for Solar-Terrestrial Science and specialises in ground-based solar, ionospheric, and geomagnetic data sets, although recent in-situ magnetospheric measurements are also included. Space weather activities A research consortium operates the Tasman International Geospace Environment Radar (TIGER), an HF southward pointing auroral radar operating from Hobart (Tasmania). A second cooperative radar (Unwin radar) is being constructed in the South Island of New Zealand. This will intersect with TIGER over the auroral zone and enhance the ability of the radar to image the surge of currents that herald space environment changes entering the Polar Regions. Launched in November 2002, the micro satellite FEDSAT, operated by the Cooperative Research Centre for Satellite Systems, has led to successful space science programs and data streams. FEDSAT is making measurements of the magnetic field over Australia and higher latitudes. It also carries a GPS receiver measuring total electron content data for magnetospheric and ionospheric studies. Understanding cosmic ray phenomena requires observations from a range of locations. The Mawson observatory, comprising low and high energy surface and high energy underground instruments, is the largest and most sophisticated observatory of its type in the Southern Hemisphere, and the only one at polar latitudes. The Australian Antarctic Division operates similar detectors at other sites. Australia has proved to be a successful site for ground-based studies and satellite downlink facilities for international collaborative projects, such as ILWS, which are monitoring Sun-Earth activity and exploring techniques for space weather forecasting.

Short-range solar radiation forecasts over Sweden

NASA Astrophysics Data System (ADS)

Landelius, Tomas; Lindskog, Magnus; Körnich, Heiner; Andersson, Sandra

2018-04-01

In this article the performance for short-range solar radiation forecasts by the global deterministic and ensemble models from the European Centre for Medium-Range Weather Forecasts (ECMWF) is compared with an ensemble of the regional mesoscale model HARMONIE-AROME used by the national meteorological services in Sweden, Norway and Finland. Note however that only the control members and the ensemble means are included in the comparison. The models resolution differs considerably with 18 km for the ECMWF ensemble, 9 km for the ECMWF deterministic model, and 2.5 km for the HARMONIE-AROME ensemble. The models share the same radiation code. It turns out that they all underestimate systematically the Direct Normal Irradiance (DNI) for clear-sky conditions. Except for this shortcoming, the HARMONIE-AROME ensemble model shows the best agreement with the distribution of observed Global Horizontal Irradiance (GHI) and DNI values. During mid-day the HARMONIE-AROME ensemble mean performs best. The control member of the HARMONIE-AROME ensemble also scores better than the global deterministic ECMWF model. This is an interesting result since mesoscale models have so far not shown good results when compared to the ECMWF models. Three days with clear, mixed and cloudy skies are used to illustrate the possible added value of a probabilistic forecast. It is shown that in these cases the mesoscale ensemble could provide decision support to a grid operator in terms of forecasts of both the amount of solar power and its probabilities.

Final Technical Report for Contract No. DE-EE0006332, "Integrated Simulation Development and Decision Support Tool-Set for Utility Market and Distributed Solar Power Generation"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cormier, Dallas; Edra, Sherwin; Espinoza, Michael

This project will enable utilities to develop long-term strategic plans that integrate high levels of renewable energy generation, and to better plan power system operations under high renewable penetration. The program developed forecast data streams for decision support and effective integration of centralized and distributed solar power generation in utility operations. This toolset focused on real time simulation of distributed power generation within utility grids with the emphasis on potential applications in day ahead (market) and real time (reliability) utility operations. The project team developed and demonstrated methodologies for quantifying the impact of distributed solar generation on core utility operations,more » identified protocols for internal data communication requirements, and worked with utility personnel to adapt the new distributed generation (DG) forecasts seamlessly within existing Load and Generation procedures through a sophisticated DMS. This project supported the objectives of the SunShot Initiative and SUNRISE by enabling core utility operations to enhance their simulation capability to analyze and prepare for the impacts of high penetrations of solar on the power grid. The impact of high penetration solar PV on utility operations is not only limited to control centers, but across many core operations. Benefits of an enhanced DMS using state-of-the-art solar forecast data were demonstrated within this project and have had an immediate direct operational cost savings for Energy Marketing for Day Ahead generation commitments, Real Time Operations, Load Forecasting (at an aggregate system level for Day Ahead), Demand Response, Long term Planning (asset management), Distribution Operations, and core ancillary services as required for balancing and reliability. This provided power system operators with the necessary tools and processes to operate the grid in a reliable manner under high renewable penetration.« less

Solar Particle Radiation Storms Forecasting and Analysis within the Framework of the `HESPERIA' HORIZON 2020 Project

NASA Astrophysics Data System (ADS)

Posner, A.; Malandraki, O.; Nunez, M.; Heber, B.; Labrenz, J.; Kühl, P.; Milas, N.; Tsiropoula, G.; Pavlos, E.

2017-12-01

Two prediction tools that have been developed in the framework of HESPERIA based upon the proven concepts UMASEP and REleASE. Near-relativistic (NR) electrons traveling faster than ions (30 MeV protons have 0.25c) are used to forecast the arrival of protons of Solar Energetic Particle (SEP) events with real-time measurements of NR electrons. The faster electrons arrive at L1 30 to 90 minutes before the slower protons. REleASE (Relativistic Electron Alert System for Exploration, Posner, 2007) uses this effect to predict the proton flux by utilizing actual electron fluxes and their most recent increases. Through HESPERIA, a clone of REleASE was built in open source programming language. The same forecasting principle was adapted to real-time data from ACE/EPAM. It is shown that HESPERIA REleASE forecasting works with any NR electron flux measurements. >500 MeV solar protons are so energetic that they usually have effects on the ground, producing Ground Level Enhancement (GLE) events. Within HESPERIA, a predictor of >500 SEP proton events near earth (geostationary orbit) has been developed. In order to predict these events, UMASEP (Núñez, 2011, 2015) has been used. UMASEP makes a lag-correlation of solar electromagnetic (EM) flux with the particle flux near earth. If the correlation is high, the model infers that there is a magnetic connection through which particles are arriving. If, additionally, the intensity of the flux of the associated solar event is also high, then UMASEP issues a SEP prediction. In the case of the prediction of >500 MeV SEP events, the implemented system, called HESPERIA UMASEP-500, correlates X-ray flux with differential proton fluxes by GOES, and with fluxes collected by neutron monitor stations around the world. When the correlation estimation and flare surpasses thresholds, a >500 MeV SEP forecast is issued. These findings suggest that a synthesis of the various approaches may improve over the status quo. Both forecasting tools are operational on the HESPERIA server maintained at the National Observatory of Athens (https://www.hesperia.astro.noa.gr/). This project received funding from the EU's Horizon 2020 research and innovation programme under grant No 637324.

Forecasting solar proton event with artificial neural network

NASA Astrophysics Data System (ADS)

Gong, J.; Wang, J.; Xue, B.; Liu, S.; Zou, Z.

Solar proton event (SPE), relatively rare but popular in solar maximum, can bring hazard situation to spacecraft. As a special event, SPE always accompanies flare, which is also called proton flare. To produce such an eruptive event, large amount energy must be accumulated within the active region. So we can investigate the character of the active region and its evolving trend, together with other such as cm radio emission and soft X-ray background to evaluate the potential of SEP in chosen area. In order to summarize the omen of SPEs in the active regions behind the observed parameters, we employed AI technology. Full connecting neural network was chosen to fulfil this job. After constructing the network, we train it with 13 parameters that was able to exhibit the character of active regions and their evolution trend. More than 80 sets of event parameter were defined to teach the neural network to identify whether an active region was potential of SPE. Then we test this model with a data base consisting SPE and non-SPE cases that was not used to train the neural network. The result showed that 75% of the choice by the model was right.

Forecasting residential solar photovoltaic deployment in California

DOE PAGES

Dong, Changgui; Sigrin, Benjamin; Brinkman, Gregory

2016-12-06

Residential distributed photovoltaic (PV) deployment in the United States has experienced robust growth, and policy changes impacting the value of solar are likely to occur at the federal and state levels. To establish a credible baseline and evaluate impacts of potential new policies, this analysis employs multiple methods to forecast residential PV deployment in California, including a time-series forecasting model, a threshold heterogeneity diffusion model, a Bass diffusion model, and National Renewable Energy Laboratory's dSolar model. As a baseline, the residential PV market in California is modeled to peak in the early 2020s, with a peak annual installation of 1.5-2more » GW across models. We then use the baseline results from the dSolar model and the threshold model to gauge the impact of the recent federal investment tax credit (ITC) extension, the newly approved California net energy metering (NEM) policy, and a hypothetical value-of-solar (VOS) compensation scheme. We find that the recent ITC extension may increase annual PV installations by 12%-18% (roughly 500 MW, MW) for the California residential sector in 2019-2020. The new NEM policy only has a negligible effect in California due to the relatively small new charges (< 100 MW in 2019-2020). Moreover, impacts of the VOS compensation scheme (0.12 cents per kilowatt-hour) are larger, reducing annual PV adoption by 32% (or 900-1300 MW) in 2019-2020.« less

Forecasting residential solar photovoltaic deployment in California

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, Changgui; Sigrin, Benjamin; Brinkman, Gregory

Residential distributed photovoltaic (PV) deployment in the United States has experienced robust growth, and policy changes impacting the value of solar are likely to occur at the federal and state levels. To establish a credible baseline and evaluate impacts of potential new policies, this analysis employs multiple methods to forecast residential PV deployment in California, including a time-series forecasting model, a threshold heterogeneity diffusion model, a Bass diffusion model, and National Renewable Energy Laboratory's dSolar model. As a baseline, the residential PV market in California is modeled to peak in the early 2020s, with a peak annual installation of 1.5-2more » GW across models. We then use the baseline results from the dSolar model and the threshold model to gauge the impact of the recent federal investment tax credit (ITC) extension, the newly approved California net energy metering (NEM) policy, and a hypothetical value-of-solar (VOS) compensation scheme. We find that the recent ITC extension may increase annual PV installations by 12%-18% (roughly 500 MW, MW) for the California residential sector in 2019-2020. The new NEM policy only has a negligible effect in California due to the relatively small new charges (< 100 MW in 2019-2020). Moreover, impacts of the VOS compensation scheme (0.12 cents per kilowatt-hour) are larger, reducing annual PV adoption by 32% (or 900-1300 MW) in 2019-2020.« less

Left Limb of North Pole of the Sun, March 20, 2007

NASA Image and Video Library

2007-04-27

NASA Solar TErrestrial RElations Observatory satellites have provided the first 3-dimensional images of the Sun. This view will aid scientists ability to understand solar physics to improve space weather forecasting.

Right Limb of the South Pole of the Sun, March 18, 2007

NASA Image and Video Library

2007-04-27

NASA Solar TErrestrial RElations Observatory satellites have provided the first 3-dimensional images of the Sun. This view will aid scientists ability to understand solar physics to improve space weather forecasting.

Closer View of the Equatorial Region of the Sun, March 24, 2007

NASA Image and Video Library

2007-04-27

NASA Solar TErrestrial RElations Observatory satellites have provided the first 3-dimensional images of the Sun. This view will aid scientists ability to understand solar physics to improve space weather forecasting.

Forecasting space weather: Can new econometric methods improve accuracy?

NASA Astrophysics Data System (ADS)

Reikard, Gordon

2011-06-01

Space weather forecasts are currently used in areas ranging from navigation and communication to electric power system operations. The relevant forecast horizons can range from as little as 24 h to several days. This paper analyzes the predictability of two major space weather measures using new time series methods, many of them derived from econometrics. The data sets are the A p geomagnetic index and the solar radio flux at 10.7 cm. The methods tested include nonlinear regressions, neural networks, frequency domain algorithms, GARCH models (which utilize the residual variance), state transition models, and models that combine elements of several techniques. While combined models are complex, they can be programmed using modern statistical software. The data frequency is daily, and forecasting experiments are run over horizons ranging from 1 to 7 days. Two major conclusions stand out. First, the frequency domain method forecasts the A p index more accurately than any time domain model, including both regressions and neural networks. This finding is very robust, and holds for all forecast horizons. Combining the frequency domain method with other techniques yields a further small improvement in accuracy. Second, the neural network forecasts the solar flux more accurately than any other method, although at short horizons (2 days or less) the regression and net yield similar results. The neural net does best when it includes measures of the long-term component in the data.

What If We Had A Magnetograph at Lagrangian L5?

NASA Technical Reports Server (NTRS)

Pevtsov, Alexei A.; Bertello, Luca; MacNeice, Peter; Petrie, Gordon

2016-01-01

Synoptic Carrington charts of magnetic field are routinely used as an input for modelings of solar wind and other aspects of space weather forecast. However, these maps are constructed using only the observations from the solar hemisphere facing Earth. The evolution of magnetic flux on the "farside" of the Sun, which may affect the topology of coronal field in the "nearside," is largely ignored. It is commonly accepted that placing a magnetograph in Lagrangian L5 point would improve the space weather forecast. However, the quantitative estimates of anticipated improvements have been lacking. We use longitudinal magnetograms from the Synoptic Optical Long-term Investigations of the Sun (SOLIS) to investigate how adding data from L5 point would affect the outcome of two major models used in space weather forecast.

Searching for Missing Pieces for Solar Flare Forecasting

NASA Astrophysics Data System (ADS)

Leka, K. D.

2015-12-01

Knowledge of the state of the solar photospheric magnetic field at a single instant in time does not appear sufficient to uniquely predict the size and timing of impending solar flares. Such knowledge may provide necessary conditions, such as estimates of the magnetic energy needed for a flare to occur. Given the necessary conditions, it is often assumed that the evolution of the field, possibly by only a small amount, may trigger the onset of a flare. We present the results of a study using time series of photospheric vector field data from the Helioseismic and Magnetic Imager (HMI) on NASA's Solar Dynamics Observatory (SDO) to quantitatively parameterize both the state and evolution of solar active regions - their complexity, magnetic topology and energy - as related to solar flare events. We examine both extensive and intensive parameters and their short-term temporal behavior, in the context of predicting flares at various thresholds. Statistical tests based on nonparametric Discriminant Analysis are used to compare pre-flare epochs to a control group of flare-quiet epochs and active regions. Results regarding the type of photospheric signature examined and the efficacy of using the present state vs. temporal evolution to predict solar flares is quantified by standard skill scores. This work is made possible by contracts NASA NNH12CG10C and NOAA/SBIR WC-133R-13-CN-0079.

Magnetohydrodynamic modelling of solar disturbances in the interplanetary medium

NASA Astrophysics Data System (ADS)

Dryer, M.

1985-12-01

A scientifically constructed series of interplanetary magnetohydrodynamic models is made that comprise the foundations for a composite solar terrestrial environment model. These models, unique in the field of solar wind physics, include both 2-1/2D as well as 3D time dependent codes that will lead to future operational status. We have also developed a geomagnetic storm forecasting strategy, referred to as the Solar Terrestrial Environment Model (STEM/2000), whereby these models would be appended in modular fashion to solar, magnetosphere, ionosphere, thermosphere, and neutral atmosphere models. We stress that these models, while still not appropriate at this date for operational use, outline a strategy or blueprint for the future. This strategy, if implemented in its essential features, offers a high probability for technology transfer from theory to operational testing within, approximately, a decade. It would ensure that real time observations would be used to drive physically based models that outputs of which would be used by space environment forecasters.

Predictions of Sunspot Cycle 24: A Comparison with Observations

NASA Astrophysics Data System (ADS)

Bhatt, N. J.; Jain, R.

2017-12-01

The space weather is largely affected due to explosions on the Sun viz. solar flares and CMEs, which, however, in turn depend upon the magnitude of the solar activity i e. number of sunspots and their magnetic configuration. Owing to these space weather effects, predictions of sunspot cycle are important. Precursor techniques, particularly employing geomagnetic indices, are often used in the prediction of the maximum amplitude of a sunspot cycle. Based on the average geomagnetic activity index aa (since 1868 onwards) for the year of the sunspot minimum and the preceding four years, Bhatt et al. (2009) made two predictions for sunspot cycle 24 considering 2008 as the year of sunspot minimum: (i) The annual maximum amplitude would be 92.8±19.6 (1-sigma accuracy) indicating a somewhat weaker cycle 24 as compared to cycles 21-23, and (ii) smoothed monthly mean sunspot number maximum would be in October 2012±4 months (1-sigma accuracy). However, observations reveal that the sunspot minima extended up to 2009, and the maximum amplitude attained is 79, with a monthly mean sunspot number maximum of 102.3 in February 2014. In view of the observations and particularly owing to the extended solar minimum in 2009, we re-examined our prediction model and revised the prediction results. We find that (i) The annual maximum amplitude of cycle 24 = 71.2 ± 19.6 and (ii) A smoothed monthly mean sunspot number maximum in January 2014±4 months. We discuss our failure and success aspects and present improved predictions for the maximum amplitude as well as for the timing, which are now in good agreement with the observations. Also, we present the limitations of our forecasting in the view of long term predictions. We show if year of sunspot minimum activity and magnitude of geomagnetic activity during sunspot minimum are taken correctly then our prediction method appears to be a reliable indicator to forecast the sunspot amplitude of the following solar cycle. References:Bhatt, N.J., Jain, R. & Aggarwal, M.: 2009, Sol. Phys. 260, 225

PREDICTING CORONAL MASS EJECTIONS USING MACHINE LEARNING METHODS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bobra, M. G.; Ilonidis, S.

Of all the activity observed on the Sun, two of the most energetic events are flares and coronal mass ejections (CMEs). Usually, solar active regions that produce large flares will also produce a CME, but this is not always true. Despite advances in numerical modeling, it is still unclear which circumstances will produce a CME. Therefore, it is worthwhile to empirically determine which features distinguish flares associated with CMEs from flares that are not. At this time, no extensive study has used physically meaningful features of active regions to distinguish between these two populations. As such, we attempt to domore » so by using features derived from (1) photospheric vector magnetic field data taken by the Solar Dynamics Observatory ’s Helioseismic and Magnetic Imager instrument and (2) X-ray flux data from the Geostationary Operational Environmental Satellite’s X-ray Flux instrument. We build a catalog of active regions that either produced both a flare and a CME (the positive class) or simply a flare (the negative class). We then use machine-learning algorithms to (1) determine which features distinguish these two populations, and (2) forecast whether an active region that produces an M- or X-class flare will also produce a CME. We compute the True Skill Statistic, a forecast verification metric, and find that it is a relatively high value of ∼0.8 ± 0.2. We conclude that a combination of six parameters, which are all intensive in nature, will capture most of the relevant information contained in the photospheric magnetic field.« less

South Pole of the Sun, March 20, 2007 Anaglyph

NASA Image and Video Library

2007-04-27

NASA Solar TErrestrial RElations Observatory satellites have provided the first 3-dimensional images of the Sun. This view will aid scientists ability to understand solar physics to improve space weather forecasting. 3D glasses are necessary.

North Pole of the Sun, March 20, 2007 Anaglyph

NASA Image and Video Library

2007-04-27

NASA Solar TErrestrial RElations Observatory satellites have provided the first 3-dimensional images of the Sun. This view will aid scientists ability to understand solar physics to improve space weather forecasting. 3D glasses are necessary.

Application and verification of the NMMB/BSC-CTM forecast for solar energy

NASA Astrophysics Data System (ADS)

Soret, Albert; Serradell, Kim; Piot, Matthias; Ortega, Daniel; Obiso, Vincenzo; Jorba, Oriol

2016-04-01

In the beginning of April 2014, northern Europe was affected by a mineral dust intrusion. On 4 April 2014, the power prediction for German solar installations was estimated as 21 GW, whereas the measured power production merely reached 11 GW. This strong overestimation significantly affected the hourly price in the wholesale electricity market: prices were firstly assessed at around 27 € /MWh but rapidly reached a level close to 150 € /MWh after recognizing the lack of solar output. It has been found that a large proportion of the uncertainty of existing NWP models can be attributed to the lack of accurate aerosol data used in order to model solar radiation. Despite the advancements in the modelling of aerosol-cloud interactions, current meteorological models use parameterizations made mostly for climate considerations (generally monthly-based). In this contribution, we analyse model results of the direct radiative effect of mineral dust over Germany at the beginning of April 2014. For that, the NMMB/BSC Chemical Transport Model (NMMB/BSC-CTM) is applied on a regional domain at 0.1° horizontal resolution. The NMMB/BSC-CTM is a new on-line chemical weather prediction system coupling atmospheric and chemistry processes. In the radiation module of the model, mineral dust is treated as a radiatively active substance interacting both short and longwave radiation. The impact of the mineral dust outbreaks on meteorology is discussed by comparing model forecasts meteorological observations. The analysis focuses on the performance of the NMMB/BSC-CTM to simulate the radiative effects of a mineral dust intrusion far from source regions. Model results would help to illustrate the added value of on-line models for long term analysis of solar resource. On-going developments: integration of anthropogenic sources and implementation of indirect radiative effects will be also presented.

The climate of the Taimyr Peninsula in the Holocene and a Forecast of Climatic Changes in the Arctic

NASA Astrophysics Data System (ADS)

Ukraintseva, V.

2009-04-01

Based on the data of the spore-pollen and radiocarbon methods during our research of a peat bog in the south-eastern part of the Taimyr Peninsula we discovered for the first time the natural dynamics of the climate for this region during the period of the last 10 500 years [2, 3] and made a long-term forecast of climatic changes both for the Taimyr Peninsula and for other Arctic regions. By the quantitative characteristics of the climate and their dynamics in time, reconstructed for the basin of the Fomich River (71 ° 42 ' North, 108 ° 03 ' East) and for the Taimyr Peninsula on the whole, we have established two climatic types: tundra (10500 ±140 years BP- 7040 ± 60 years BP) and forest (5720± 60 years BP - 500 ± 60 years BP to the present time). In the first half of the Holocene the climate there was rather stable; only 7530 years ago a sharp cooling took place; the second half of the Holocene, beginning with 5720 years ago, is characterized by alternating fluctuations in the climate [3]. Taking only the palaeoclimatic reconstructions as a basis, we can talk about a trend of climatic changes in the future. However comparing the Sun activity` forecast, expressed in Wolf units (Max W), made by V.N. Kupetsky [1], with the climatic characteristics, which we have reconstructed, we could then make a more precise forecast of climatic changes for the Taimyr Peninsula and the Russian part of the Arctic (Table). The above forecast lets us make the following basically important conclusions: (1) the climate`s warming, which is currently being observed on the Earth (the 23rd cycle of the Sun`s activity) will last till 2011; (2) during the following two cycles (24th and 25th) the Sun`s activity will decrease to 100-110 Wolf units, which will cause a cooling of the climate on the Earth; (3) in the following, the 26th cycle, the Sun`s activity will increase up to 130 Wolf units, which will cause a warming of the climate; (4) in the 27th cycle (2037-2048) the Sun`s activity will decrease to 100 Wolf units, causing a cooling on the Earth again. Thus, the forecast of climatic changes in the Arctic, which we have worked up and based on the Sun-Earth connections, is an objective natural reality. The climate fluctuations in the Arctic, which we have identified for the last 12-10 thousand years, will continue in the forthcoming 50-100 years. Consequently, only the synthesis of solar-telescopic, palaeoclimatic and modern meteorological data allows making a valid long-term global forecast of climatic changes and of the Earth`s landscape in the future. Regional and local forecasts developed on the basis of a global forecast will be then of the primary value. Since the solar-telescopic data are alpha and omega for forecast constructions, their publication in the open press is an absolute necessity. This would enable scientists to make realistic forecasts of climatic changes for specific districts and regions of the Earth in the future. The contemporary scientific knowledge level does not show us any other way yet. Bibliography: 1. Kupetsky, V.N. Landscapes of freezing seas. Dissertation for the Degree of Doctor of Geographical Science. Saint-Petersburg State University, 1998 ( Russian). 2. Ukraintseva, V.V. Use of the index of similarity for the assessment of fossil spore-pollen spectra // Modern Problems of Paleofloristics, Paleophytogeography and Phytostratigraphy. Transaction of the International Paleobotanical Conference. Moscow, May 17-18, 2005. Vol.1. - Moscow: GEOS, 2005. P. 314 - 318. 3. Ukraintseva, V.V. On the new method of reconstruction of climates of the past on the basis of the spore-pollen analysis method data// SOCIETY. ENVIRONMENT. DEVELOPMENT. 2008. No.3. P.142-154 (Russian). 4. Ukraintseva V.V., Pospelov I.N. Reconstruction of Climates of the Past and a Forecast: a New Method in Principal// The Holocene, 2008 (in press).

Detection of emerging sunspot regions in the solar interior.

PubMed

Ilonidis, Stathis; Zhao, Junwei; Kosovichev, Alexander

2011-08-19

Sunspots are regions where strong magnetic fields emerge from the solar interior and where major eruptive events occur. These energetic events can cause power outages, interrupt telecommunication and navigation services, and pose hazards to astronauts. We detected subsurface signatures of emerging sunspot regions before they appeared on the solar disc. Strong acoustic travel-time anomalies of an order of 12 to 16 seconds were detected as deep as 65,000 kilometers. These anomalies were associated with magnetic structures that emerged with an average speed of 0.3 to 0.6 kilometer per second and caused high peaks in the photospheric magnetic flux rate 1 to 2 days after the detection of the anomalies. Thus, synoptic imaging of subsurface magnetic activity may allow anticipation of large sunspot regions before they become visible, improving space weather forecast.

Assessing Space Weather Applications and Understanding: IMF Bz at L1

NASA Astrophysics Data System (ADS)

Riley, P.; Savani, N.; Mays, M. L.; Austin, H. J.

2017-12-01

The CCMC - International (CCMC-I) is designed as a self-organizing informal forum for facilitating novel global initiatives on space weather research, development, forecasting and education. Here we capitalize on CCMC'AGUs experience in providing highly utilized web-based services, leadership and trusted relationships with space weather model developers. One of the CCMC-I initiatives is the International Forum for Space Weather Capabilities Assessment. As part of this initiative, within the solar and heliosphere domain, we focus our community discussion on forecasting the magnetic structure of interplanetary CMEs and the ambient solar wind. During the International CCMC-LWS Working Meeting in April 2017 the group instigated open communication to agree upon a standardized process by which all current and future models can be compared under an unbiased test. In this poster, we present our initial findings how we expect different models will move forward with validating and forecasting the magnetic vectors of the solar wind at L1. We also present a new IMF Bz Score-board which will be used to assist in the transitioning of research models into more operational settings.

Data Assimilation in the Solar Wind: Challenges and First Results.

PubMed

Lang, Matthew; Browne, Philip; van Leeuwen, Peter Jan; Owens, Mathew

2017-11-01

Data assimilation (DA) is used extensively in numerical weather prediction (NWP) to improve forecast skill. Indeed, improvements in forecast skill in NWP models over the past 30 years have directly coincided with improvements in DA schemes. At present, due to data availability and technical challenges, DA is underused in space weather applications, particularly for solar wind prediction. This paper investigates the potential of advanced DA methods currently used in operational NWP centers to improve solar wind prediction. To develop the technical capability, as well as quantify the potential benefit, twin experiments are conducted to assess the performance of the Local Ensemble Transform Kalman Filter (LETKF) in the solar wind model ENLIL. Boundary conditions are provided by the Wang-Sheeley-Arge coronal model and synthetic observations of density, temperature, and momentum generated every 4.5 h at 0.6 AU. While in situ spacecraft observations are unlikely to be routinely available at 0.6 AU, these techniques can be applied to remote sensing of the solar wind, such as with Heliospheric Imagers or interplanetary scintillation. The LETKF can be seen to improve the state at the observation location and advect that improvement toward the Earth, leading to an improvement in forecast skill in near-Earth space for both the observed and unobserved variables. However, sharp gradients caused by the analysis of a single observation in space resulted in artificial wavelike structures being advected toward Earth. This paper is the first attempt to apply DA to solar wind prediction and provides the first in-depth analysis of the challenges and potential solutions.

Data Assimilation in the Solar Wind: Challenges and First Results

NASA Astrophysics Data System (ADS)

Lang, Matthew; Browne, Philip; van Leeuwen, Peter Jan; Owens, Mathew

2017-11-01

Data assimilation (DA) is used extensively in numerical weather prediction (NWP) to improve forecast skill. Indeed, improvements in forecast skill in NWP models over the past 30 years have directly coincided with improvements in DA schemes. At present, due to data availability and technical challenges, DA is underused in space weather applications, particularly for solar wind prediction. This paper investigates the potential of advanced DA methods currently used in operational NWP centers to improve solar wind prediction. To develop the technical capability, as well as quantify the potential benefit, twin experiments are conducted to assess the performance of the Local Ensemble Transform Kalman Filter (LETKF) in the solar wind model ENLIL. Boundary conditions are provided by the Wang-Sheeley-Arge coronal model and synthetic observations of density, temperature, and momentum generated every 4.5 h at 0.6 AU. While in situ spacecraft observations are unlikely to be routinely available at 0.6 AU, these techniques can be applied to remote sensing of the solar wind, such as with Heliospheric Imagers or interplanetary scintillation. The LETKF can be seen to improve the state at the observation location and advect that improvement toward the Earth, leading to an improvement in forecast skill in near-Earth space for both the observed and unobserved variables. However, sharp gradients caused by the analysis of a single observation in space resulted in artificial wavelike structures being advected toward Earth. This paper is the first attempt to apply DA to solar wind prediction and provides the first in-depth analysis of the challenges and potential solutions.

Evaluation of a Revised Interplanetary Shock Prediction Model: 1D CESE-HD-2 Solar-Wind Model

NASA Astrophysics Data System (ADS)

Zhang, Y.; Du, A. M.; Du, D.; Sun, W.

2014-08-01

We modified the one-dimensional conservation element and solution element (CESE) hydrodynamic (HD) model into a new version [ 1D CESE-HD-2], by considering the direction of the shock propagation. The real-time performance of the 1D CESE-HD-2 model during Solar Cycle 23 (February 1997 - December 2006) is investigated and compared with those of the Shock Time of Arrival Model ( STOA), the Interplanetary-Shock-Propagation Model ( ISPM), and the Hakamada-Akasofu-Fry version 2 ( HAFv.2). Of the total of 584 flare events, 173 occurred during the rising phase, 166 events during the maximum phase, and 245 events during the declining phase. The statistical results show that the success rates of the predictions by the 1D CESE-HD-2 model for the rising, maximum, declining, and composite periods are 64 %, 62 %, 57 %, and 61 %, respectively, with a hit window of ± 24 hours. The results demonstrate that the 1D CESE-HD-2 model shows the highest success rates when the background solar-wind speed is relatively fast. Thus, when the background solar-wind speed at the time of shock initiation is enhanced, the forecasts will provide potential values to the customers. A high value (27.08) of χ 2 and low p-value (< 0.0001) for the 1D CESE-HD-2 model give considerable confidence for real-time forecasts by using this new model. Furthermore, the effects of various shock characteristics (initial speed, shock duration, background solar wind, longitude, etc.) and background solar wind on the forecast are also investigated statistically.

Radiation protection for manned space activities

NASA Technical Reports Server (NTRS)

Jordan, T. M.

1983-01-01

The Earth's natural radiation environment poses a hazard to manned space activities directly through biological effects and indirectly through effects on materials and electronics. The following standard practices are indicated that address: (1) environment models for all radiation species including uncertainties and temporal variations; (2) upper bound and nominal quality factors for biological radiation effects that include dose, dose rate, critical organ, and linear energy transfer variations; (3) particle transport and shielding methodology including system and man modeling and uncertainty analysis; (4) mission planning that includes active dosimetry, minimizes exposure during extravehicular activities, subjects every mission to a radiation review, and specifies operational procedures for forecasting, recognizing, and dealing with large solar flaes.

Proceedings of the Flat-Plate Solar Array Project Workshop on Low-Cost Polysilicon for Terrestrial Photovoltaic Solar-Cell Applications

NASA Technical Reports Server (NTRS)

1986-01-01

Sessions conducted included: polysilicon material requirements; economics; process development in the U.S.; international process development; and polysilicon market and forecasts. Twenty-one papers were presented and discussed.

Comparison between three algorithms for Dst predictions over the 2003 2005 period

NASA Astrophysics Data System (ADS)

Amata, E.; Pallocchia, G.; Consolini, G.; Marcucci, M. F.; Bertello, I.

2008-02-01

We compare, over a two and half years period, the performance of a recent artificial neural network (ANN) algorithm for the Dst prediction called EDDA [Pallocchia, G., Amata, E., Consolini, G., Marcucci, M.F., Bertello, I., 2006. Geomagnetic Dst index forecast based on IMF data only. Annales Geophysicae 24, 989-999], based on IMF inputs only, with the performance of the ANN Lundstedt et al. [2002. Operational forecasts of the geomagnetic Dst index. Geophysical Research Letters 29, 341] algorithm and the Wang et al. [2003. Influence of the solar wind dynamic pressure on the decay and injection of the ring current. Journal of Geophysical Research 108, 51] algorithm based on differential equations, which both make use of both IMF and plasma inputs. We show that: (1) all three algorithms perform similarly for "small" and "moderate" storms; (2) the EDDA and Wang algorithms perform similarly and considerably better than the Lundstedt et al. [2002. Operational forecasts of the geomagnetic Dst index. Geophysical Research Letters 29, 341] algorithm for "intense" and for "severe" storms; (3) the EDDA algorithm has the clear advantage, for space weather operational applications, that it makes use of IMF inputs only. The advantage lies in the fact that plasma data are at times less reliable and display data gaps more often than IMF measurements, especially during large solar disturbances, i.e. during periods when space weather forecast are most important. Some considerations are developed on the reasons why EDDA may forecast the Dst index without making use of solar wind density and velocity data.

Validation of the CME Geomagnetic Forecast Alerts Under the COMESEP Alert System

NASA Astrophysics Data System (ADS)

Dumbović, Mateja; Srivastava, Nandita; Rao, Yamini K.; Vršnak, Bojan; Devos, Andy; Rodriguez, Luciano

2017-08-01

Under the European Union 7th Framework Programme (EU FP7) project Coronal Mass Ejections and Solar Energetic Particles (COMESEP, http://comesep.aeronomy.be), an automated space weather alert system has been developed to forecast solar energetic particles (SEP) and coronal mass ejection (CME) risk levels at Earth. The COMESEP alert system uses the automated detection tool called Computer Aided CME Tracking (CACTus) to detect potentially threatening CMEs, a drag-based model (DBM) to predict their arrival, and a CME geoeffectiveness tool (CGFT) to predict their geomagnetic impact. Whenever CACTus detects a halo or partial halo CME and issues an alert, the DBM calculates its arrival time at Earth and the CGFT calculates its geomagnetic risk level. The geomagnetic risk level is calculated based on an estimation of the CME arrival probability and its likely geoeffectiveness, as well as an estimate of the geomagnetic storm duration. We present the evaluation of the CME risk level forecast with the COMESEP alert system based on a study of geoeffective CMEs observed during 2014. The validation of the forecast tool is made by comparing the forecasts with observations. In addition, we test the success rate of the automatic forecasts (without human intervention) against the forecasts with human intervention using advanced versions of the DBM and CGFT (independent tools available at the Hvar Observatory website, http://oh.geof.unizg.hr). The results indicate that the success rate of the forecast in its current form is unacceptably low for a realistic operation system. Human intervention improves the forecast, but the false-alarm rate remains unacceptably high. We discuss these results and their implications for possible improvement of the COMESEP alert system.

The Solar Wind and Geomagnetic Activity as a Function of Time Relative to Corotating Interaction Regions

NASA Technical Reports Server (NTRS)

McPherron, Robert L.; Weygand, James

2006-01-01

Corotating interaction regions during the declining phase of the solar cycle are the cause of recurrent geomagnetic storms and are responsible for the generation of high fluxes of relativistic electrons. These regions are produced by the collision of a high-speed stream of solar wind with a slow-speed stream. The interface between the two streams is easily identified with plasma and field data from a solar wind monitor upstream of the Earth. The properties of the solar wind and interplanetary magnetic field are systematic functions of time relative to the stream interface. Consequently the coupling of the solar wind to the Earth's magnetosphere produces a predictable sequence of events. Because the streams persist for many solar rotations it should be possible to use terrestrial observations of past magnetic activity to predict future activity. Also the high-speed streams are produced by large unipolar magnetic regions on the Sun so that empirical models can be used to predict the velocity profile of a stream expected at the Earth. In either case knowledge of the statistical properties of the solar wind and geomagnetic activity as a function of time relative to a stream interface provides the basis for medium term forecasting of geomagnetic activity. In this report we use lists of stream interfaces identified in solar wind data during the years 1995 and 2004 to develop probability distribution functions for a variety of different variables as a function of time relative to the interface. The results are presented as temporal profiles of the quartiles of the cumulative probability distributions of these variables. We demonstrate that the storms produced by these interaction regions are generally very weak. Despite this the fluxes of relativistic electrons produced during those storms are the highest seen in the solar cycle. We attribute this to the specific sequence of events produced by the organization of the solar wind relative to the stream interfaces. We also show that there are large quantitative differences in various parameters between the two cycles.

Theoretical Technology Research for ISTP/SOLARMAX

NASA Technical Reports Server (NTRS)

Ashour-Abdalla, Maha; Acuna, Mario (Technical Monitor)

2000-01-01

During the last decade, we have been developing theoretical tools to support the scientific objectives of the International Solar Terrestrial Physics (ISTP) program. Results from our mission-oriented theory program have contributed significantly to the development of predictive capabilities by using real upstream solar wind conditions as input to our models and forecasting events observed downstream near Earth. We also developed the capability to unravel the complex information contained in ion velocity distribution functions measured near the Earth to determine their origin and energization process. During solar maximum, solar flares and coronal mass ejections (CMEs) dominate the sun's activity. It is now widely accepted that the impact of CMEs (or magnetic clouds) with the Earth's magnetosphere is the cause of most magnetic storms during solar maximum. One important aspect of a CME is the occurrence of solar energetic particle (SEP) events. During these events, protons, electrons, and heavy ions of solar origin are accelerated to very high energies by shock waves driven out from the sun. We carried out a series of large-scale kinetic (LSK) simulations to model the effect of SEPs on the near-Earth environment and the accessibility of these high-energy particles to the inner magnetosphere. We present the results of these studies.

Flares, Fears, and Forecasts: Public Misconceptions About the Sunspot Cycle

NASA Astrophysics Data System (ADS)

Larsen, K.

2012-06-01

Among the disaster scenarios perpetrated by 2012 apocalypse aficionados is the destruction of humankind due to solar flares and coronal mass ejections (CMEs). These scenarios reflect common misconceptions regarding the solar cycle. This paper (based on an annual meeting poster) sheds light on those misconceptions and how the AAVSO Solar Section can address them.

Automatic recognition of coronal type II radio bursts: The ARBIS 2 method and first observations

NASA Astrophysics Data System (ADS)

Lobzin, Vasili; Cairns, Iver; Robinson, Peter; Steward, Graham; Patterson, Garth

Major space weather events such as solar flares and coronal mass ejections are usually accompa-nied by solar radio bursts, which can potentially be used for real-time space weather forecasts. Type II radio bursts are produced near the local plasma frequency and its harmonic by fast electrons accelerated by a shock wave moving through the corona and solar wind with a typi-cal speed of 1000 km s-1 . The coronal bursts have dynamic spectra with frequency gradually falling with time and durations of several minutes. We present a new method developed to de-tect type II coronal radio bursts automatically and describe its implementation in an extended Automated Radio Burst Identification System (ARBIS 2). Preliminary tests of the method with spectra obtained in 2002 show that the performance of the current implementation is quite high, ˜ 80%, while the probability of false positives is reasonably low, with one false positive per 100-200 hr for high solar activity and less than one false event per 10000 hr for low solar activity periods. The first automatically detected coronal type II radio bursts are also presented. ARBIS 2 is now operational with IPS Radio and Space Services, providing email alerts and event lists internationally.

Right Limb of the South Pole of the Sun, March 18, 2007 Anaglyph

NASA Image and Video Library

2007-04-27

NASA Solar TErrestrial RElations Observatory satellites have provided the first 3-dimensional images of the Sun. This view will aid scientists ability to understand solar physics to improve space weather forecasting. 3D glasses are necessary.

Left Limb of North Pole of the Sun, March 20, 2007 Anaglyph

NASA Image and Video Library

2007-04-27

NASA Solar TErrestrial RElations Observatory satellites have provided the first 3-dimensional images of the Sun. This view will aid scientists ability to understand solar physics to improve space weather forecasting. 3D glasses are necessary.

Closer View of the Equatorial Region of the Sun, March 24, 2007 Anaglyph

NASA Image and Video Library

2007-04-27

NASA Solar TErrestrial RElations Observatory satellites have provided the first 3-dimensional images of the Sun. This view will aid scientists ability to understand solar physics to improve space weather forecasting. 3D glasses are necessary.

DATA ASSIMILATION APPROACH FOR FORECAST OF SOLAR ACTIVITY CYCLES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kitiashvili, Irina N., E-mail: irina.n.kitiashvili@nasa.gov

Numerous attempts to predict future solar cycles are mostly based on empirical relations derived from observations of previous cycles, and they yield a wide range of predicted strengths and durations of the cycles. Results obtained with current dynamo models also deviate strongly from each other, thus raising questions about criteria to quantify the reliability of such predictions. The primary difficulties in modeling future solar activity are shortcomings of both the dynamo models and observations that do not allow us to determine the current and past states of the global solar magnetic structure and its dynamics. Data assimilation is a relativelymore » new approach to develop physics-based predictions and estimate their uncertainties in situations where the physical properties of a system are not well-known. This paper presents an application of the ensemble Kalman filter method for modeling and prediction of solar cycles through use of a low-order nonlinear dynamo model that includes the essential physics and can describe general properties of the sunspot cycles. Despite the simplicity of this model, the data assimilation approach provides reasonable estimates for the strengths of future solar cycles. In particular, the prediction of Cycle 24 calculated and published in 2008 is so far holding up quite well. In this paper, I will present my first attempt to predict Cycle 25 using the data assimilation approach, and discuss the uncertainties of that prediction.« less

MiniCOR: A miniature coronagraph for an interplanetary CUBESAT

NASA Astrophysics Data System (ADS)

Vourlidas, A.; Korendyke, C.; Liewer, P. C.; Cutler, J.; Howard, R.; Plunkett, S. P.; Thernisien, A. F.

2015-12-01

Coronagraphs occupy a unique place in Heliophysics, critical to both NAA and NOAA programs. They are the primary means for the study of the extended solar coorna and its short/long term activity. In addition coronagraphs are the only instrument that can image coronal mass ejections (CMEs) leaving the Sun and provide ciritical information for space weather forecasting. We descirbe a low cost miniaturzied CubeSat coronagraph, MiniCOR, designed to operate in deep space which will returndata with higher cadence and sensitivity than that from the SOHO/LASCO coronagraphs. MiniCOR is a six unit (6U) science craft with a tightly integrated, single instrument interplanetary flight system optiized for science. MiniCOR fully exploits recent technology advance in CubeSat technology and active pixel sensors. With a factor of 2.9 improvement in light gathering power over SOHO and quasi-continuous data collection, MiniCOR can observe the slow solar wind, CMEs and shocks with sufficient signal-to-noise ratio (SNR) to open new windows on our understanding of the inner Heliosphere. An operating Minic'OR would prvide coornagraphic observations in support of the upcoming Solar Probe Plus (SPP) and Solar Orbiter (SO) missions.

Towards a Solid Foundation of Using Remotely Sensed Solar-Induced Chlorophyll Fluorescence for Crop Monitoring and Yield Forecast

NASA Astrophysics Data System (ADS)

Chen, Y.; Sun, Y.; You, L.; Liu, Y.

2017-12-01

The growing demand for food production due to population increase coupled with high vulnerability to volatile environmental changes poses a paramount challenge for mankind in the coming century. Real-time crop monitoring and yield forecasting must be a key part of any solution to this challenge as these activities provide vital information needed for effective and efficient crop management and for decision making. However, traditional methods of crop growth monitoring (e.g., remotely sensed vegetation indices) do not directly relate to the most important function of plants - photosynthesis and therefore crop yield. The recent advance in the satellite remote sensing of Solar-Induced chlorophyll Fluorescence (SIF), an integrative photosynthetic signal from molecular origin and a direct measure of plant functions holds great promise for real-time monitoring of crop growth conditions and forecasting yields. In this study, we use satellite measurements of SIF from both the Global Ozone Monitoring Experiment-2 (GOME-2) onboard MetOp-A and the Orbiting Carbon Observatory-2 (OCO-2) satellites to estimate crop yield using both process-based and statistical models. We find that SIF-based crop yield well correlates with the global yield product Spatial Production Allocation Model (SPAM) derived from ground surveys for all major crops including maize, soybean, wheat, sorghum, and rice. The potential and challenges of using upcoming SIF satellite missions for crop monitoring and prediction will also be discussed.

A brief history of Regional Warning Center China (RWC-China)

NASA Astrophysics Data System (ADS)

He, Han; Wang, Huaning; Du, Zhanle; Huang, Xin; Yan, Yan; Dai, Xinghua; Guo, Juan; Wang, Jialong

2018-03-01

Solar-terrestrial prediction services in China began in 1969 at the Beijing Astronomical Observatory (BAO), Chinese Academy of Sciences (CAS). In 1990, BAO joined the International URSIgram and World Days Service (IUWDS) and started solar-terrestrial data and prediction interchanges with other members of IUWDS. The short-term solar activity prediction service with standard URSIgram codes began in January 1991 at BAO, and forecasts have been issued routinely every weekday from then on. The Regional Warning Center Beijing (RWC-Beijing) of IUWDS was officially approved in China in 1991 and was formally established in February 1992. In 1996, the IUWDS was changed to the current name, the International Space Environment Service (ISES). In 2000, the RWC-Beijing was renamed RWC-China according to ISES requirements. In 2001, the National Astronomical Observatories, CAS (NAOC) was established. All the solar-terrestrial data and prediction services of BAO were taken up by NAOC. The headquarters of RWC-China is located on the campus of NAOC.

Virtual solar field - An opportunity to optimize transient processes in line-focus CSP power plants

NASA Astrophysics Data System (ADS)

Noureldin, Kareem; Hirsch, Tobias; Pitz-Paal, Robert

2017-06-01

Optimizing solar field operation and control is a key factor to improve the competitiveness of line-focus solar thermal power plants. However, the risks of assessing new and innovative control strategies on operational power plants hinder such optimizations and result in applying more conservative control schemes. In this paper, we describe some applications for a whole solar field transient in-house simulation tool developed at the German Aerospace Centre (DLR), the Virtual Solar Field (VSF). The tool offers a virtual platform to simulate real solar fields while coupling the thermal and hydraulic conditions of the field with high computational efficiency. Using the tool, developers and operator can probe their control strategies and assess the potential benefits while avoiding the high risks and costs. In this paper, we study the benefits gained from controlling the loop valves and of using direct normal irradiance maps and forecasts for the field control. Loop valve control is interesting for many solar field operators since it provides a high degree of flexibility to the control of the solar field through regulating the flow rate in each loop. This improves the reaction to transient condition, such as passing clouds and field start-up in the morning. Nevertheless, due to the large number of loops and the sensitivity of the field control to the valve settings, this process needs to be automated and the effect of changing the setting of each valve on the whole field control needs to be taken into account. We used VSF to implement simple control algorithms to control the loop valves and to study the benefits that could be gained from using active loop valve control during transient conditions. Secondly, we study how using short-term highly spatially-resolved DNI forecasts provided by cloud cameras could improve the plant energy yield. Both cases show an improvement in the plant efficiency and outlet temperature stability. This paves the road for further investigations of new control strategies or for optimizations of the currently implemented ones.

Innovative second-generation wavelets construction with recurrent neural networks for solar radiation forecasting.

PubMed

Capizzi, Giacomo; Napoli, Christian; Bonanno, Francesco

2012-11-01

Solar radiation prediction is an important challenge for the electrical engineer because it is used to estimate the power developed by commercial photovoltaic modules. This paper deals with the problem of solar radiation prediction based on observed meteorological data. A 2-day forecast is obtained by using novel wavelet recurrent neural networks (WRNNs). In fact, these WRNNS are used to exploit the correlation between solar radiation and timescale-related variations of wind speed, humidity, and temperature. The input to the selected WRNN is provided by timescale-related bands of wavelet coefficients obtained from meteorological time series. The experimental setup available at the University of Catania, Italy, provided this information. The novelty of this approach is that the proposed WRNN performs the prediction in the wavelet domain and, in addition, also performs the inverse wavelet transform, giving the predicted signal as output. The obtained simulation results show a very low root-mean-square error compared to the results of the solar radiation prediction approaches obtained by hybrid neural networks reported in the recent literature.

Potential Improvements in Space Weather Forecasting using New Products Developed for the Upcoming DSCOVR Solar Wind Mission

NASA Astrophysics Data System (ADS)

Cash, M. D.; Biesecker, D. A.; Reinard, A. A.

2013-05-01

The Deep Space Climate Observatory (DSCOVR) mission, which is scheduled for launch in late 2014, will provide real-time solar wind thermal plasma and magnetic measurements to ensure continuous monitoring for space weather forecasting. DSCOVR will be located at the L1 Lagrangian point and will include a Faraday cup to measure the proton and alpha components of the solar wind and a triaxial fluxgate magnetometer to measure the magnetic field in three dimensions. The real-time data provided by DSCOVR will be used to generate space weather applications and products that have been demonstrated to be highly accurate and provide actionable information for customers. We present several future space weather products currently under evaluation for development. New potential space weather products for use with DSCOVR real-time data include: automated shock detection, more accurate L1 to Earth delay time, automatic solar wind regime identification, and prediction of rotations in solar wind Bz within magnetic clouds. Additional ideas from the community on future space weather products are encouraged.

The National Solar Observatory Digital Library - a resource for space weather studies

NASA Astrophysics Data System (ADS)

Hill, F.; Erdwurm, W.; Branston, D.; McGraw, R.

2000-09-01

We describe the National Solar Observatory Digital Library (NSODL), consisting of 200GB of on-line archived solar data, a RDBMS search engine, and an Internet HTML-form user interface. The NSODL is open to all users and provides simple access to solar physics data of basic importance for space weather research and forecasting, heliospheric research, and education. The NSODL can be accessed at the URL www.nso.noao.edu/diglib.

Forecasting Space Weather Events for a Neighboring World

NASA Technical Reports Server (NTRS)

Zheng, Yihua; Mason, Tom; Wood, Erin L.

2015-01-01

Shortly after NASA's Mars Atmosphere and Volatile EvolutioN mission (MAVEN) spacecraft entered Mars' orbit on 21 September 2014, scientists glimpsed the Martian atmosphere's response to a front of solar energetic particles (SEPs) and an associated coronal mass ejection (CME). In response to some solar flares and CMEs, streams of SEPs burst from the solar atmosphere and are further accelerated in the interplanetary medium between the Sun and the planets. These particles deposit their energy and momentum into anything in their path, including the Martian atmosphere and MAVEN particle detectors. MAVEN scientists had been alerted to the likely CME-Mars encounter by a space weather prediction system that had its origins in space weather forecasting for Earth but now forecasts space weather for Earth's neighboring planets. The two Solar Terrestrial Relations Observatory spacecraft and Solar Heliospheric Observatory observed a CME on 26 September, with a trajectory that suggested a Mars intercept. A computer model developed for solar wind prediction, the Wang-Sheeley-Arge-Enlil cone model [e.g., Zheng et al., 2013; Parsons et al., 2011], running in real time at the Community Coordinated Modeling Center (CCMC) located at NASA Goddard since 2006, showed the CME propagating in the direction of Mars (Figure 1). According to MAVEN particle detectors, the disturbance and accompanying SEP enhancement at the leading edge of the CME reached Mars at approximately 17 hours Universal Time on 29 September 2014. Such SEPs may have a profound effect on atmospheric escape - they are believed to be a possible means for driving atmospheric loss. SEPs can cause loss of Mars' upper atmosphere through several loss mechanisms including sputtering of the atmosphere. Sputtering occurs when atoms are ejected from the atmosphere due to impacts with energetic particles.

Solar Activity from 2006 to 2014 and Short-term Forecasts of Solar Proton Events Using the ESPERTA Model

NASA Astrophysics Data System (ADS)

Alberti, T.; Laurenza, M.; Cliver, E. W.; Storini, M.; Consolini, G.; Lepreti, F.

2017-03-01

To evaluate the solar energetic proton (SEP) forecast model of Laurenza et al., here termed ESPERTA, we computed the input parameters (soft X-ray (SXR) fluence and ˜1 MHz radio fluence) for all ≥M2 SXR flares from 2006 to 2014. This database is outside the 1995-2005 interval on which ESPERTA was developed. To assess the difference in the general level of activity between these two intervals, we compared the occurrence frequencies of SXR flares and SEP events for the first six years of cycles 23 (1996 September-2002 September) and 24 (2008 December-2014 December). We found a reduction of SXR flares and SEP events of 40% and 46%, respectively, in the latter period. Moreover, the numbers of ≥M2 flares with high values of SXR and ˜1 MHz fluences (>0.1 J m-2 and >6 × 105 sfu × minute, respectively) are both reduced by ˜30%. A somewhat larger percentage decrease of these two parameters (˜40% versus ˜30%) is obtained for the 2006-2014 interval in comparison with 1995-2005. Despite these differences, ESPERTA performance was comparable for the two intervals. For the 2006-2014 interval, ESPERTA had a probability of detection (POD) of 59% (19/32) and a false alarm rate (FAR) of 30% (8/27), versus a POD = 63% (47/75) and an FAR = 42% (34/81) for the original 1995-2005 data set. In addition, for the 2006-2014 interval the median (average) warning time was estimated to be ˜2 hr (˜7 hr), versus ˜6 hr (˜9 hr), for the 1995-2005 data set.

Solar Activity from 2006 to 2014 and Short-term Forecasts of Solar Proton Events Using the ESPERTA Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alberti, T.; Lepreti, F.; Laurenza, M.

2017-03-20

To evaluate the solar energetic proton (SEP) forecast model of Laurenza et al., here termed ESPERTA, we computed the input parameters (soft X-ray (SXR) fluence and ∼1 MHz radio fluence) for all ≥M2 SXR flares from 2006 to 2014. This database is outside the 1995–2005 interval on which ESPERTA was developed. To assess the difference in the general level of activity between these two intervals, we compared the occurrence frequencies of SXR flares and SEP events for the first six years of cycles 23 (1996 September–2002 September) and 24 (2008 December–2014 December). We found a reduction of SXR flares andmore » SEP events of 40% and 46%, respectively, in the latter period. Moreover, the numbers of ≥M2 flares with high values of SXR and ∼1 MHz fluences (>0.1 J m{sup −2} and >6 × 10{sup 5} sfu × minute, respectively) are both reduced by ∼30%. A somewhat larger percentage decrease of these two parameters (∼40% versus ∼30%) is obtained for the 2006–2014 interval in comparison with 1995–2005. Despite these differences, ESPERTA performance was comparable for the two intervals. For the 2006–2014 interval, ESPERTA had a probability of detection (POD) of 59% (19/32) and a false alarm rate (FAR) of 30% (8/27), versus a POD = 63% (47/75) and an FAR = 42% (34/81) for the original 1995–2005 data set. In addition, for the 2006–2014 interval the median (average) warning time was estimated to be ∼2 hr (∼7 hr), versus ∼6 hr (∼9 hr), for the 1995–2005 data set.« less

Non-neutralized Electric Currents in Solar Active Regions and Flare Productivity

NASA Astrophysics Data System (ADS)

Kontogiannis, Ioannis; Georgoulis, Manolis K.; Park, Sung-Hong; Guerra, Jordan A.

2017-11-01

We explore the association of non-neutralized currents with solar flare occurrence in a sizable sample of observations, aiming to show the potential of such currents in solar flare prediction. We used the high-quality vector magnetograms that are regularly produced by the Helioseismic Magnetic Imager, and more specifically, the Space weather HMI Active Region Patches (SHARP). Through a newly established method that incorporates detailed error analysis, we calculated the non-neutralized currents contained in active regions (AR). Two predictors were produced, namely the total and the maximum unsigned non-neutralized current. Both were tested in AR time-series and a representative sample of point-in-time observations during the interval 2012 - 2016. The average values of non-neutralized currents in flaring active regions are higher by more than an order of magnitude than in non-flaring regions and correlate very well with the corresponding flare index. The temporal evolution of these parameters appears to be connected to physical processes, such as flux emergence and/or magnetic polarity inversion line formation, that are associated with increased solar flare activity. Using Bayesian inference of flaring probabilities, we show that the total unsigned non-neutralized current significantly outperforms the total unsigned magnetic flux and other well-established current-related predictors. It therefore shows good prospects for inclusion in an operational flare-forecasting service. We plan to use the new predictor in the framework of the FLARECAST project along with other highly performing predictors.

Patrol of the short wavelength activity and flares of Sun as star

NASA Astrophysics Data System (ADS)

Afanasiev, I.; Avakyan, S.; Leonov, N.; Serova, A.; Voronin, N.

Monitoring of the spectral range which most affects solar-terrestrial relationship - soft X-ray and extreme UV-radiations allows to solve ? problem of solar activity influence on all aspects of the Sun - Earth ties and to select the most important precursors of solar flares and the solar events related with a flare (such as proton events, high-velocity plasma streams in the solar wind, shock waves, coronal mass ejection and, the most important, the beginning of principal magnetic storms). Solar activity is constantly monitored at present (in the USA) only in two sections of the spectrum of ionizing radiation: <0.8 nm and >115 (119) nm. However, so far there has been no monitoring of the flux in the most geoeffective region of the spectrum (0.8-115 nm) from the entire disk of the sun; this region completely monitors the main part of the ionosphere of the earth and the ionosphere of the other planets of the solar system, including the formation and status of the main ionospheric maxima. This occurs solely because of technical and methodological difficulties in performing the measurements and calibration in this spectral range on spacecraft, because it is necessity to use only windowless optics. At the present the solar the optical - electronic equipment (OEE) is testing and there are plans to launch OEE of Space Solar Patrol (SSP) consisting of solar radiometers and spectrometers at the Russian Module of the International Space Station. So the solving the problem of the permanent monitoring-patrol of ionizing radiation from the full disk of the Sun appears in the main tasks of fundamental scientific studies in space. The results of this monitoring can be contribution in development of simultaneous studies in several sciences, such as: - solar astrophysics (state of all solar atmospheric regions), - meteorology, physics of atmosphere (the influence of solar activity on global changes, climate and weather including the effects of atmo s pheric electricity), - aeronomy, astronautics (the influence of solar activity on density of upper atmo s phere and space craft slowing clown by it and characteristics of spacecraft outer atmo s phere), - radiophysics (determination and forecast ionospheric state of planets and radiowave transfer conditions), - heliobiology (the role of solar activity in biology and medical events), - seismology, possible sociology. There are the Resolutions with support of SSP Mission of the importance of this project from Commissions C, D and E of COSPAR, 1996, Commission G of URSI, 1996 and General Assembly of IAGA, 1999.

Some Advances in Downscaling Probabilistic Climate Forecasts for Agricultural Decision Support

NASA Astrophysics Data System (ADS)

Han, E.; Ines, A.

2015-12-01

Seasonal climate forecasts, commonly provided in tercile-probabilities format (below-, near- and above-normal), need to be translated into more meaningful information for decision support of practitioners in agriculture. In this paper, we will present two new novel approaches to temporally downscale probabilistic seasonal climate forecasts: one non-parametric and another parametric method. First, the non-parametric downscaling approach called FResampler1 uses the concept of 'conditional block sampling' of weather data to create daily weather realizations of a tercile-based seasonal climate forecasts. FResampler1 randomly draws time series of daily weather parameters (e.g., rainfall, maximum and minimum temperature and solar radiation) from historical records, for the season of interest from years that belong to a certain rainfall tercile category (e.g., being below-, near- and above-normal). In this way, FResampler1 preserves the covariance between rainfall and other weather parameters as if conditionally sampling maximum and minimum temperature and solar radiation if that day is wet or dry. The second approach called predictWTD is a parametric method based on a conditional stochastic weather generator. The tercile-based seasonal climate forecast is converted into a theoretical forecast cumulative probability curve. Then the deviates for each percentile is converted into rainfall amount or frequency or intensity to downscale the 'full' distribution of probabilistic seasonal climate forecasts. Those seasonal deviates are then disaggregated on a monthly basis and used to constrain the downscaling of forecast realizations at different percentile values of the theoretical forecast curve. As well as the theoretical basis of the approaches we will discuss sensitivity analysis (length of data and size of samples) of them. In addition their potential applications for managing climate-related risks in agriculture will be shown through a couple of case studies based on actual seasonal climate forecasts for: rice cropping in the Philippines and maize cropping in India and Kenya.

Advanced Cloud Forecasting for Solar Energy’s Impact on Grid Modernization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Werth, D.; Nichols, R.

Solar energy production is subject to variability in the solar resource – clouds and aerosols will reduce the available solar irradiance and inhibit power production. The fact that solar irradiance can vary by large amounts at small timescales and in an unpredictable way means that power utilities are reluctant to assign to their solar plants a large portion of future energy demand – the needed power might be unavailable, forcing the utility to make costly adjustments to its daily portfolio. The availability and predictability of solar radiation therefore represent important research topics for increasing the power produced by renewable sources.

Correlation between solar flare productivity and photospheric vector magnetic fields

NASA Astrophysics Data System (ADS)

Cui, Yanmei; Wang, Huaning

2008-11-01

Studying the statistical correlation between the solar flare productivity and photospheric magnetic fields is very important and necessary. It is helpful to set up a practical flare forecast model based on magnetic properties and improve the physical understanding of solar flare eruptions. In the previous study ([Cui, Y.M., Li, R., Zhang, L.Y., He, Y.L., Wang, H.N. Correlation between solar flare productivity and photospheric magnetic field properties 1. Maximum horizontal gradient, length of neutral line, number of singular points. Sol. Phys. 237, 45 59, 2006]; from now on we refer to this paper as ‘Paper I’), three measures of the maximum horizontal gradient, the length of the neutral line, and the number of singular points are computed from 23990 SOHO/MDI longitudinal magnetograms. The statistical relationship between the solar flare productivity and these three measures is well fitted with sigmoid functions. In the current work, the three measures of the length of strong-shear neutral line, total unsigned current, and total unsigned current helicity are computed from 1353 vector magnetograms observed at Huairou Solar Observing Station. The relationship between the solar flare productivity and the current three measures can also be well fitted with sigmoid functions. These results are expected to be beneficial to future operational flare forecasting models.

The Impact of Discontinuity Front Orientation on the Accuracy of L1 Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Szabo, A.

2013-12-01

Current space weather forecasting from the Sun-Earth first Lagrange (L1) point assumes that all observed solar wind discontinuity fronts (interplanetary shocks, ICME boundaries) are perpendicular to the Sun-Earth line and are propagating radially out from eh Sun. In reality, these weather fronts can have significantly tilted orientation. Combined ACE, Wind and Soho observations allow the quantification of this effect. With the launch of the DSCOVR spacecraft in early 2015, dual real-time solar wind measurements will become available (at least at some time). Algorithms and their impact exploiting this unique scenario will be discussed.

Big Data Analytics for Modelling and Forecasting of Geomagnetic Field Indices

NASA Astrophysics Data System (ADS)

Wei, H. L.

2016-12-01

A massive amount of data are produced and stored in research areas of space weather and space climate. However, the value of a vast majority of the data acquired every day may not be effectively or efficiently exploited in our daily practice when we try to forecast solar wind parameters and geomagnetic field indices using these recorded measurements or digital signals, probably due to the challenges stemming from the dealing with big data which are characterized by the 4V futures: volume (a massively large amount of data), variety (a great number of different types of data), velocity (a requirement of quick processing of the data), and veracity (the trustworthiness and usability of the data). In order to obtain more reliable and accurate predictive models for geomagnetic field indices, it requires that models should be developed from the big data analytics perspective (or it at least benefits from such a perspective). This study proposes a few data-based modelling frameworks which aim to produce more efficient predictive models for space weather parameters forecasting by means of system identification and big data analytics. More specifically, it aims to build more reliable mathematical models that characterise the relationship between solar wind parameters and geomagnetic filed indices, for example the dependent relationship of Dst and Kp indices on a few solar wind parameters and magnetic field indices, namely, solar wind velocity (V), southward interplanetary magnetic field (Bs), solar wind rectified electric field (VBs), and dynamic flow pressure (P). Examples are provided to illustrate how the proposed modelling approaches are applied to Dst and Kp index prediction.

Space Weather Products and Tools Used in Auroral Monitoring and Forecasting at CCMC/SWRC

NASA Technical Reports Server (NTRS)

Zheng, Yihua; Rastaetter, Lutz

2015-01-01

Key points discussed in this chapter are (1) the importance of aurora research to scientific advances and space weather applications, (2) space weather products at CCMC that are relevant to aurora monitoring and forecasting, and (3) the need for more effort from the whole community to achieve a better and long-lead-time forecast of auroral activity. Aurora, as manifestations of solar wind-magnetosphere-ionosphere coupling that occurs in a region of space that is relatively easy to access for sounding rockets, satellites, and other types of observational platforms, serves as a natural laboratory for studying the underlying physics of the complex system. From a space weather application perspective, auroras can cause surface charging of technological assets passing through the region, result in scintillation effects affecting communication and navigation, and cause radar cluttering that hinders military and civilian applications. Indirectly, an aurora and its currents can induce geomagnetically induced currents (GIC) on the ground, which poses major concerns for the wellbeing and operation of power grids, particularly during periods of intense geomagnetic activity. In addition, accurate auroral forecasting is desired for auroral tourism. In this chapter, we first review some of the existing auroral models and discuss past validation efforts. Such efforts are crucial in transitioning a model(s) from research to operations and for further model improvement and development that also benefits scientific endeavors. Then we will focus on products and tools that are used for auroral monitoring and forecasting at the Space Weather Research Center (SWRC). As part of the CCMC (Community Coordinated Modeling Center), SWRC has been providing space weather services since 2010.

Verification of short lead time forecast models: applied to Kp and Dst forecasting

NASA Astrophysics Data System (ADS)

Wintoft, Peter; Wik, Magnus

2016-04-01

In the ongoing EU/H2020 project PROGRESS models that predicts Kp, Dst, and AE from L1 solar wind data will be used as inputs to radiation belt models. The possible lead times from L1 measurements are shorter (10s of minutes to hours) than the typical duration of the physical phenomena that should be forecast. Under these circumstances several metrics fail to single out trivial cases, such as persistence. In this work we explore metrics and approaches for short lead time forecasts. We apply these to current Kp and Dst forecast models. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 637302.

Sensing, Measurement, and Forecasting | Grid Modernization | NREL

Science.gov Websites

into operational intelligence to support grid operations and planning. Photo of solar resource monitoring equipment Grid operations involve assessing the grid's health in real time, predicting its to hours and days-to support advances in power system operations and planning. Capabilities Solar

Short-term solar irradiance forecasting via satellite/model coupling

DOE PAGES

Miller, Steven D.; Rogers, Matthew A.; Haynes, John M.; ...

2017-12-01

The short-term (0-3 h) prediction of solar insolation for renewable energy production is a problem well-suited to satellite-based techniques. The spatial, spectral, temporal and radiometric resolution of instrumentation hosted on the geostationary platform allows these satellites to describe the current cloud spatial distribution and optical properties. These properties relate directly to the transient properties of the downwelling solar irradiance at the surface, which come in the form of 'ramps' that pose a central challenge to energy load balancing in a spatially distributed network of solar farms. The short-term evolution of the cloud field may be approximated to first order simplymore » as translational, but care must be taken in how the advection is handled and where the impacts are assigned. In this research, we describe how geostationary satellite observations are used with operational cloud masking and retrieval algorithms, wind field data from Numerical Weather Prediction (NWP), and radiative transfer calculations to produce short-term forecasts of solar insolation for applications in solar power generation. The scheme utilizes retrieved cloud properties to group pixels into contiguous cloud objects whose future positions are predicted using four-dimensional (space + time) model wind fields, selecting steering levels corresponding to the cloud height properties of each cloud group. The shadows associated with these clouds are adjusted for sensor viewing parallax displacement and combined with solar geometry and terrain height to determine the actual location of cloud shadows. For mid/high-level clouds at mid-latitudes and high solar zenith angles, the combined displacements from these geometric considerations are non-negligible. The cloud information is used to initialize a radiative transfer model that computes the direct and diffuse-sky solar insolation at both shadow locations and intervening clear-sky regions. Here, we describe the formulation of the algorithm and validate its performance against Surface Radiation (SURFRAD; Augustine et al., 2000, 2005) network observations. Typical errors range from 8.5% to 17.2% depending on the complexity of cloud regimes, and an operational demonstration outperformed persistence-based forecasting of Global Horizontal Irradiance (GHI) under all conditions by ~10 W/m2.« less

Short-term solar irradiance forecasting via satellite/model coupling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, Steven D.; Rogers, Matthew A.; Haynes, John M.

The short-term (0-3 h) prediction of solar insolation for renewable energy production is a problem well-suited to satellite-based techniques. The spatial, spectral, temporal and radiometric resolution of instrumentation hosted on the geostationary platform allows these satellites to describe the current cloud spatial distribution and optical properties. These properties relate directly to the transient properties of the downwelling solar irradiance at the surface, which come in the form of 'ramps' that pose a central challenge to energy load balancing in a spatially distributed network of solar farms. The short-term evolution of the cloud field may be approximated to first order simplymore » as translational, but care must be taken in how the advection is handled and where the impacts are assigned. In this research, we describe how geostationary satellite observations are used with operational cloud masking and retrieval algorithms, wind field data from Numerical Weather Prediction (NWP), and radiative transfer calculations to produce short-term forecasts of solar insolation for applications in solar power generation. The scheme utilizes retrieved cloud properties to group pixels into contiguous cloud objects whose future positions are predicted using four-dimensional (space + time) model wind fields, selecting steering levels corresponding to the cloud height properties of each cloud group. The shadows associated with these clouds are adjusted for sensor viewing parallax displacement and combined with solar geometry and terrain height to determine the actual location of cloud shadows. For mid/high-level clouds at mid-latitudes and high solar zenith angles, the combined displacements from these geometric considerations are non-negligible. The cloud information is used to initialize a radiative transfer model that computes the direct and diffuse-sky solar insolation at both shadow locations and intervening clear-sky regions. Here, we describe the formulation of the algorithm and validate its performance against Surface Radiation (SURFRAD; Augustine et al., 2000, 2005) network observations. Typical errors range from 8.5% to 17.2% depending on the complexity of cloud regimes, and an operational demonstration outperformed persistence-based forecasting of Global Horizontal Irradiance (GHI) under all conditions by ~10 W/m2.« less

A Tool for Empirical Forecasting of Major Flares, Coronal Mass Ejections, and Solar Particle Events from a Proxy of Active-Region Free Magnetic Energy

DTIC Science & Technology

2011-04-07

Center, Huntsville, Alabama , USA. 2Physics Department, University of Alabama in Huntsville, Huntsville, Alabama , USA. 3Center for Space Plasma and...Aeronomic Research, University of Alabama in Huntsville, Huntsville, Alabama , USA. SPACE WEATHER, VOL. 9, S04003, doi:10.1029/2009SW000537, 2011...PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) University of of Alabama in Huntsville,Center for Space Plasma and Aeronomic Research,Huntsville,AL,35899

Wind speed time series reconstruction using a hybrid neural genetic approach

NASA Astrophysics Data System (ADS)

Rodriguez, H.; Flores, J. J.; Puig, V.; Morales, L.; Guerra, A.; Calderon, F.

2017-11-01

Currently, electric energy is used in practically all modern human activities. Most of the energy produced came from fossil fuels, making irreversible damage to the environment. Lately, there has been an effort by nations to produce energy using clean methods, such as solar and wind energy, among others. Wind energy is one of the cleanest alternatives. However, the wind speed is not constant, making the planning and operation at electric power systems a difficult activity. Knowing in advance the amount of raw material (wind speed) used for energy production allows us to estimate the energy to be generated by the power plant, helping the maintenance planning, the operational management, optimal operational cost. For these reasons, the forecast of wind speed becomes a necessary task. The forecast process involves the use of past observations from the variable to forecast (wind speed). To measure wind speed, weather stations use devices called anemometers, but due to poor maintenance, connection error, or natural wear, they may present false or missing data. In this work, a hybrid methodology is proposed, and it uses a compact genetic algorithm with an artificial neural network to reconstruct wind speed time series. The proposed methodology reconstructs the time series using a ANN defined by a Compact Genetic Algorithm.

Cloud Impacts on Pavement Temperature in Energy Balance Models

NASA Astrophysics Data System (ADS)

Walker, C. L.

2013-12-01

Forecast systems provide decision support for end-users ranging from the solar energy industry to municipalities concerned with road safety. Pavement temperature is an important variable when considering vehicle response to various weather conditions. A complex, yet direct relationship exists between tire and pavement temperatures. Literature has shown that as tire temperature increases, friction decreases which affects vehicle performance. Many forecast systems suffer from inaccurate radiation forecasts resulting in part from the inability to model different types of clouds and their influence on radiation. This research focused on forecast improvement by determining how cloud type impacts the amount of shortwave radiation reaching the surface and subsequent pavement temperatures. The study region was the Great Plains where surface solar radiation data were obtained from the High Plains Regional Climate Center's Automated Weather Data Network stations. Road pavement temperature data were obtained from the Meteorological Assimilation Data Ingest System. Cloud properties and radiative transfer quantities were obtained from the Clouds and Earth's Radiant Energy System mission via Aqua and Terra Moderate Resolution Imaging Spectroradiometer satellite products. An additional cloud data set was incorporated from the Naval Research Laboratory Cloud Classification algorithm. Statistical analyses using a modified nearest neighbor approach were first performed relating shortwave radiation variability with road pavement temperature fluctuations. Then statistical associations were determined between the shortwave radiation and cloud property data sets. Preliminary results suggest that substantial pavement forecasting improvement is possible with the inclusion of cloud-specific information. Future model sensitivity testing seeks to quantify the magnitude of forecast improvement.

Operational Real-time Forecast of MeV Electrons at Geosynchronous Orbit Based on ACE and GOES-10 Measurements

NASA Astrophysics Data System (ADS)

Li, X.; Temerin, M. A.; Monk, S.; Baker, D. N.; Reeves, G. D.

2002-05-01

The MeV electrons, also known as `killer electrons', have a deleterious impact on satellites through deep dielectric charging and the bodies of astronauts through radiation damage during extravehicular activity. Using a recently developed model based on the standard radial diffusion equation [Li et al., 2001], we show that the intensity of these MeV electrons at geosynchronous orbit can be quantitatively predicted 1-2 days in advance given knowledge of the solar wind. Our current model is operating in real-time, using real-time data from ACE and GOES-10, to make forecast of >2 MeV eletrons at geosynchronous orbit up to 48 hours in advance, the results are available on the web, currently updated every two hours (http://lasp.colorado.edu/~monk/xlf2.html).

The Radiation, Interplanetary Shocks, and Coronal Sources (RISCS) Toolset

NASA Technical Reports Server (NTRS)

Zank, G. P.; Spann, J.

2014-01-01

We outline a plan to develop a physics based predictive toolset RISCS to describe the interplanetary energetic particle and radiation environment throughout the inner heliosphere, including at the Earth. To forecast and "nowcast" the radiation environment requires the fusing of three components: 1) the ability to provide probabilities for incipient solar activity; 2) the use of these probabilities and daily coronal and solar wind observations to model the 3D spatial and temporal heliosphere, including magnetic field structure and transients, within 10 AU; and 3) the ability to model the acceleration and transport of energetic particles based on current and anticipated coronal and heliospheric conditions. We describe how to address 1) - 3) based on our existing, well developed, and validated codes and models. The goal of RISCS toolset is to provide an operational forecast and "nowcast" capability that will a) predict solar energetic particle (SEP) intensities; b) spectra for protons and heavy ions; c) predict maximum energies and their duration; d) SEP composition; e) cosmic ray intensities, and f) plasma parameters, including shock arrival times, strength and obliquity at any given heliospheric location and time. The toolset would have a 72 hour predicative capability, with associated probabilistic bounds, that would be updated hourly thereafter to improve the predicted event(s) and reduce the associated probability bounds. The RISCS toolset would be highly adaptable and portable, capable of running on a variety of platforms to accommodate various operational needs and requirements.

Short-Term Global Horizontal Irradiance Forecasting Based on Sky Imaging and Pattern Recognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, Brian S; Feng, Cong; Cui, Mingjian

Accurate short-term forecasting is crucial for solar integration in the power grid. In this paper, a classification forecasting framework based on pattern recognition is developed for 1-hour-ahead global horizontal irradiance (GHI) forecasting. Three sets of models in the forecasting framework are trained by the data partitioned from the preprocessing analysis. The first two sets of models forecast GHI for the first four daylight hours of each day. Then the GHI values in the remaining hours are forecasted by an optimal machine learning model determined based on a weather pattern classification model in the third model set. The weather pattern ismore » determined by a support vector machine (SVM) classifier. The developed framework is validated by the GHI and sky imaging data from the National Renewable Energy Laboratory (NREL). Results show that the developed short-term forecasting framework outperforms the persistence benchmark by 16% in terms of the normalized mean absolute error and 25% in terms of the normalized root mean square error.« less

Origin and Ion Charge State Evolution of Solar Wind Transients 4 - 7 August 2011

NASA Astrophysics Data System (ADS)

Rodkin, Denis; Goryaev, Farid; Pagano, Paolo; Gibb, Gordon; Slemzin, Vladimir; Shugay, Yulia; Veselovsky, Igor; Mackay, Duncan

2017-04-01

Identification of transients and their origins on the Sun is one of the most important problems of the space weather forecasting. In our work, we present a case study of the complex event consisting of several solar wind transients detected by ACE on 4 - 7 August 2011, that caused a geomagnetic storm with Dst= - 110 nT. The supposed coronal sources - three flares and coronal mass ejections (CMEs) occurred on 2 - 4 August 2011 in the active region AR 11261. To investigate the solar origins and formation of these transients, we studied kinematic and thermodynamic properties of expanding coronal structures using the SDO/AIA EUV images and the differential emission measure (DEM) diagnostics. The Helioseismic and Magnetic Imager (HMI) magnetic field maps were used as the input data for the 3D numerical model to describe the flux rope ejection. We characterize the early phase of the flux rope ejection in the corona, where the usual three-component CME structure formed. The flux rope ejected with the speed about 200 km/s to the height of 0.25 Rsun. The kinematics of the modeled CME front well agrees with the STEREO EUV measurements. Using the results of the plasma diagnostics and MHD modeling, we calculated the ion charge ratios of carbon and oxygen as well as the mean charge state of iron ions of the 2 August 2011 CME taking into account the processes of heating, cooling, expansion, ionization and recombination of the moving plasma in the corona up to the freeze-in region. We estimated a probable heating rate of the CME plasma in the low corona by matching the calculated ion composition parameters of the CME with that measured in-situ parameters of the solar wind transients. We also consider the similarities and discrepancies between the results of the MHD simulation and the observation of the event. Our results show that analysis of the ion composition of CMEs enables to disclose a relationship between parameters of the solar wind transients and properties of their solar origins, which opens new possibilities to validate and improve the solar wind forecasting models.

New Space Weather Forecasting at NOAA with Michigan's Geospace Model

NASA Astrophysics Data System (ADS)

Singer, H. J.; Millward, G. H.; Balch, C. C.; Cash, M. D.; Onsager, T. G.; Toth, G.; Welling, D. T.; Gombosi, T. I.

2016-12-01

We will present first results from the University of Michigan's Geospace model that is transitioning, during 2016, from a research capability into operations at the NOAA Space Weather Prediction Center. The first generation of space weather products from this model will be described. These initial products will support power grid operators, as well as other users, with both global and regional, short-term predictions of geomagnetic activity. The Geospace model is a coupled system including three components: the BATS-R-US magnetohydrodynamic (MHD) model of the magnetosphere; the Ridley ionosphere electrodynamics model (RIM); and the Rice Convection Model (RCM), an inner magnetosphere ring-current model developed at Rice University. The model is driven by solar wind data from a satellite at L1 (now NOAA's DSCOVR satellite) and F10.7, a proxy for solar extreme ultra-violet radiation. The Geospace model runs continuously, driven by the 1-minute cadence real-time L1 data that is propagated to the inflow boundary of the MHD code. The model steps back to an earlier time and then continues forward if high-speed solar wind overtakes slower solar wind. This mode of operation is unique among the models at NOAA's National Center for Environment Prediction's Central Operations (NCO), and it is also different from the typical scientific simulation mode. All of this work has involved 3D graphical model displays and validation tools that are being developed to support forecasters and web-based external users. Lessons learned during the transition process will be described, as well as the iterative process that occurs between Research and Operations and the scientific challenges for future model and product improvements.

Solar wind modulation of UK lightning

NASA Astrophysics Data System (ADS)

Davis, Chris; Harrison, Giles; Lockwood, Mike; Owens, Mathew; Barnard, Luke

2013-04-01

The response of lightning rates in the UK to arrival of high speed solar wind streams at Earth is investigated using a superposed epoch analysis. The fast solar wind streams' arrivals are determined from modulation of the solar wind Vy component, measured by the Advanced Composition Explorer (ACE) spacecraft. Lightning rate changes around these event times are then determined from the very low frequency Arrival Time Difference (ATD) system of the UK Met Office. Arrival of high speed streams at Earth is found to be preceded by a decrease in total solar irradiance and an increase in sunspot number and Mg II emissions. These are consistent with the high speed stream's source being co-located with an active region appearing on the Eastern solar limb and rotating at the 27 day rate of the Sun. Arrival of the high speed stream at Earth also coincides with a rapid decrease in cosmic ray flux and an increase in lightning rates over the UK, persisting for around 40 days. The lightning rate increase is corroborated by an increase in the total number of thunder days observed by UK Met stations, again for around 40 days after the arrival of a high speed solar wind stream. This increase in lightning may be beneficial to medium range forecasting of hazardous weather.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nakafuji, Dora; Gouveia, Lauren

This project supports development of the next generation, integrated energy management infrastructure (EMS) able to incorporate advance visualization of behind-the-meter distributed resource information and probabilistic renewable energy generation forecasts to inform real-time operational decisions. The project involves end-users and active feedback from an Utility Advisory Team (UAT) to help inform how information can be used to enhance operational functions (e.g. unit commitment, load forecasting, Automatic Generation Control (AGC) reserve monitoring, ramp alerts) within two major EMS platforms. Objectives include: Engaging utility operations personnel to develop user input on displays, set expectations, test and review; Developing ease of use and timelinessmore » metrics for measuring enhancements; Developing prototype integrated capabilities within two operational EMS environments; Demonstrating an integrated decision analysis platform with real-time wind and solar forecasting information and timely distributed resource information; Seamlessly integrating new 4-dimensional information into operations without increasing workload and complexities; Developing sufficient analytics to inform and confidently transform and adopt new operating practices and procedures; Disseminating project lessons learned through industry sponsored workshops and conferences;Building on collaborative utility-vendor partnership and industry capabilities« less

A Comparative Verification of Forecasts from Two Operational Solar Wind Models (Postprint)

DTIC Science & Technology

2012-02-08

much confidence to place on predicted parameters. Cost /benefit information is provided to administrators who decide to sustain or replace existing...magnetic field magnitude and three components of the magnetic field vector in the geocentric solar magnetospheric (GSM) coordinate system at each hour of

Active Longitude and Coronal Mass Ejection Occurrences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gyenge, N.; Kiss, T. S.; Erdélyi, R.

The spatial inhomogeneity of the distribution of coronal mass ejection (CME) occurrences in the solar atmosphere could provide a tool to estimate the longitudinal position of the most probable CME-capable active regions in the Sun. The anomaly in the longitudinal distribution of active regions themselves is often referred to as active longitude (AL). In order to reveal the connection between the AL and CME spatial occurrences, here we investigate the morphological properties of active regions. The first morphological property studied is the separateness parameter, which is able to characterize the probability of the occurrence of an energetic event, such asmore » a solar flare or CME. The second morphological property is the sunspot tilt angle. The tilt angle of sunspot groups allows us to estimate the helicity of active regions. The increased helicity leads to a more complex buildup of the magnetic structure and also can cause CME eruption. We found that the most complex active regions appear near the AL and that the AL itself is associated with the most tilted active regions. Therefore, the number of CME occurrences is higher within the AL. The origin of the fast CMEs is also found to be associated with this region. We concluded that the source of the most probably CME-capable active regions is at the AL. By applying this method, we can potentially forecast a flare and/or CME source several Carrington rotations in advance. This finding also provides new information for solar dynamo modeling.« less

Active Longitude and Coronal Mass Ejection Occurrences

NASA Astrophysics Data System (ADS)

Gyenge, N.; Singh, T.; Kiss, T. S.; Srivastava, A. K.; Erdélyi, R.

2017-03-01

The spatial inhomogeneity of the distribution of coronal mass ejection (CME) occurrences in the solar atmosphere could provide a tool to estimate the longitudinal position of the most probable CME-capable active regions in the Sun. The anomaly in the longitudinal distribution of active regions themselves is often referred to as active longitude (AL). In order to reveal the connection between the AL and CME spatial occurrences, here we investigate the morphological properties of active regions. The first morphological property studied is the separateness parameter, which is able to characterize the probability of the occurrence of an energetic event, such as a solar flare or CME. The second morphological property is the sunspot tilt angle. The tilt angle of sunspot groups allows us to estimate the helicity of active regions. The increased helicity leads to a more complex buildup of the magnetic structure and also can cause CME eruption. We found that the most complex active regions appear near the AL and that the AL itself is associated with the most tilted active regions. Therefore, the number of CME occurrences is higher within the AL. The origin of the fast CMEs is also found to be associated with this region. We concluded that the source of the most probably CME-capable active regions is at the AL. By applying this method, we can potentially forecast a flare and/or CME source several Carrington rotations in advance. This finding also provides new information for solar dynamo modeling.

The Plasma Environment Associated With Equatorial Ionospheric Irregularities

NASA Astrophysics Data System (ADS)

Smith, Jonathon M.; Heelis, R. A.

2018-02-01

We examine the density structure of equatorial depletions referred to here as equatorial plasma bubbles (EPBs). Data recorded by the Ion Velocity Meter as part of the Coupled Ion Neutral Dynamics Investigation (CINDI) aboard the Communication/Navigation Outage Forecasting System (C/NOFS) satellite are used to study EPBs from 1600 to 0600 h local time at altitudes from 350 to 850 km. The data are taken during the 7 years from 2008 to 2014, more than one half of a magnetic solar cycle, that include solar minimum and a moderate solar maximum. Using a rolling ball algorithm, EPBs are identified by profiles in the plasma density, each having a depth measured as the percent change between the background and minimum density (ΔN/N). During solar moderate activity bubbles observed in the topside postsunset sector are more likely to have large depths compared to those observed in the topside postmidnight sector. Large bubble depths can be observed near 350 km in the bottomside F region in the postsunset period. Conversely at solar minimum the distribution of depths is similar in the postsunset and postmidnight sectors in all longitude sectors. Deep bubbles are rarely observed in the topside postsunset sector and never in the bottomside above 400 km in altitude. We suggest that these features result from the vertical drift of the plasma for these two solar activity levels. These drift conditions affect both the background density in which bubbles are embedded and the growth rate of perturbations in the bottomside where bubbles originate.

The role of MEXART in the National Space Weather Laboratory of Mexico: Detection of solar wind, CMEs, ionosphere, active regions and flares.

NASA Astrophysics Data System (ADS)

Mejia-Ambriz, J.; Gonzalez-Esparza, A.; De la Luz, V.; Villanueva-Hernandez, P.; Andrade, E.; Aguilar-Rodriguez, E.; Chang, O.; Romero Hernandez, E.; Sergeeva, M. A.; Perez Alanis, C. A.; Reyes-Marin, P. A.

2017-12-01

The National Space Weather Laboratory - Laboratorio Nacional de Clima Espacial (LANCE) - of Mexico has different ground based instruments to study and monitor the space weather. One of these instruments is the Mexican Array Radio Telescope (MEXART) which is principally dedicated to remote sensing the solar wind and coronal mass ejections (CMEs) at 140 MHz, the instrument can detect solar wind densities and speeds from about 0.4 to 1 AU by modeling observations of interplanetary scintillation (IPS). MEXART is also able to detect ionospheric disturbances associated with transient space weather events by the analysis of ionospheric scintillation (IONS) . Additionally, MEXART has followed the Sun since the beginning of the current Solar Cycle 24 with records of 8 minutes per day, and occasionally, has partially detected the process of strong solar flares. Here we show the contributions of MEXART to the LANCE by reporting recent detections of CMEs by IPS, the arrive of transient events at Earth by IONS, the influence of active regions in the flux of the Sun at 140 MHz and the detection of a M6.5 class flare. Furthermore we report the status of a near real time analysis of IPS data for forecast purposes and the potential contribution to the Worldwide IPS Stations network (WIPSS), which is an effort to achieve a better coverage of the solar wind observations in the inner heliosphere.

On the forecasting the unfavorable periods in the technosphere by the space weather factors

NASA Astrophysics Data System (ADS)

Lyakhov, N. N.

2002-12-01

There is the considerable progress in development of geomagnetic disturbances forecast technique, in the necessary time, by solar activity phenomena last years. The possible relationship between violations of the traffic safety terms (VTS) in East Siberian Railway during 1986-1999 and the space weather factors was investigated. The overall number of cases under consideration is equal to 11575. By methods of correlation and spectral analysis it was shown, that statistics of VTS has not a random and it's character is probably caused by space weather factors. The principal difference between rhythmic of VTS by purely technical reasons (MECH) (failures in mechanical systems) and, that of VTS caused by wrong operations of a personnel (MAN), is noted. Increase of sudden storm commencements number results in increase of probability of mistakable actions of an operator. Probability of violations in mechanical systems increases with increase of number of quiet geomagnetic conditions. This, in its turn, dictate different approach to the ordered rows of MECH and MAN data when forecasting the unfavourable periods as the priods of increased risk in working out a wrong decision by technological process participants. The advances in forecasting of geomagnetic environment technique made possible to start construction of systems of the operative informing about unfavourable factors of space weather for the interested organizations.

The scientific challenges to forecasting the propagation of space weather through the heliosphere (Invited)

NASA Astrophysics Data System (ADS)

van der Holst, B.; Manchester, W.; Sokolov, I.; Toth, G.; Gombosi, T. I.

2013-12-01

Coronal mass ejections (CMEs) are a major source of potentially destructive space weather conditions. Understanding and forecasting these events are of utmost importance. In this presentation we discuss the progress towards a physics-based predictive capability within the Space Weather Modeling Framework (SWMF). We demonstrate our latest development in the AWSoM (Alfven Wave Solar Model) global model of the solar corona and inner heliosphere. This model accounts for the coupled thermodynamics of the electrons and protons via single fluid magnetohydrodynamics. The coronal heating and solar wind acceleration are addressed with Alfvén wave turbulence. The realistic 3D magnetic field is simulated using data from the photospheric magnetic field measurements. The AWSoM model serves as a workhorse for modeling CMEs from initial eruption to prediction at 1AU. With selected events we will demonstrate the complexity and challenges associated with CME propagation.

A neural network controller for hydronic heating systems of solar buildings.

PubMed

Argiriou, Athanassios A; Bellas-Velidis, Ioannis; Kummert, Michaël; André, Philippe

2004-04-01

An artificial neural network (ANN)-based controller for hydronic heating plants of buildings is presented. The controller has forecasting capabilities: it includes a meteorological module, forecasting the ambient temperature and solar irradiance, an indoor temperature predictor module, a supply temperature predictor module and an optimizing module for the water supply temperature. All ANN modules are based on the Feed Forward Back Propagation (FFBP) model. The operation of the controller has been tested experimentally, on a real-scale office building during real operating conditions. The operation results were compared to those of a conventional controller. The performance was also assessed via numerical simulation. The detailed thermal simulation tool for solar systems and buildings TRNSYS was used. Both experimental and numerical results showed that the expected percentage of energy savings with respect to a conventional controller is of about 15% under North European weather conditions.

Validation of community models: 3. Tracing field lines in heliospheric models

NASA Astrophysics Data System (ADS)

MacNeice, Peter; Elliott, Brian; Acebal, Ariel

2011-10-01

Forecasting hazardous gradual solar energetic particle (SEP) bursts at Earth requires accurately modeling field line connections between Earth and the locations of coronal or interplanetary shocks that accelerate the particles. We test the accuracy of field lines reconstructed using four different models of the ambient coronal and inner heliospheric magnetic field, through which these shocks must propagate, including the coupled Wang-Sheeley-Arge (WSA)/ENLIL model. Evaluating the WSA/ENLIL model performance is important since it is the most sophisticated model currently available to space weather forecasters which can model interplanetary coronal mass ejections and, when coupled with particle acceleration and transport models, will provide a complete model for gradual SEP bursts. Previous studies using a simpler Archimedean spiral approach above 2.5 solar radii have reported poor performance. We test the accuracy of the model field lines connecting Earth to the Sun at the onset times of 15 impulsive SEP bursts, comparing the foot points of these field lines with the locations of surface events believed to be responsible for the SEP bursts. We find the WSA/ENLIL model performance is no better than the simplest spiral model, and the principal source of error is the model's inability to reproduce sufficient low-latitude open flux. This may be due to the model's use of static synoptic magnetograms, which fail to account for transient activity in the low corona, during which reconnection events believed to initiate the SEP acceleration may contribute short-lived open flux at low latitudes. Time-dependent coronal models incorporating these transient events may be needed to significantly improve Earth/Sun field line forecasting.

Prior Flaring as a Complement to Free Magnetic Energy for Forecasting Solar Eruptions

NASA Technical Reports Server (NTRS)

Falconer, David A.; Moore, Ronald L.; Barghouty, Abdulnasser F.; Khazanov, Igor

2012-01-01

From a large database of (1) 40,000 SOHO/MDI line-of-sight magnetograms covering the passage of 1,300 sunspot active regions across the 30 deg radius central disk of the Sun, (2) a proxy of each active region's free magnetic energy measured from each of the active region's central-disk-passage magnetograms, and (3) each active region's full-disk-passage history of production of major flares and fast coronal mass ejections (CMEs), we find new statistical evidence that (1) there are aspects of an active region's magnetic field other than the free energy that are strong determinants of the active region's productivity of major flares and fast CMEs in the coming few days, (2) an active region's recent productivity of major flares, in addition to reflecting the amount of free energy in the active region, also reflects these other determinants of coming productivity of major eruptions, and (3) consequently, the knowledge of whether an active region has recently had a major flare, used in combination with the active region's free-energy proxy measured from a magnetogram, can greatly alter the forecast chance that the active region will have a major eruption in the next few days after the time of the magnetogram. The active-region magnetic conditions that, in addition to the free energy, are reflected by recent major flaring are presumably the complexity and evolution of the field.

Applications of a shadow camera system for energy meteorology

NASA Astrophysics Data System (ADS)

Kuhn, Pascal; Wilbert, Stefan; Prahl, Christoph; Garsche, Dominik; Schüler, David; Haase, Thomas; Ramirez, Lourdes; Zarzalejo, Luis; Meyer, Angela; Blanc, Philippe; Pitz-Paal, Robert

2018-02-01

Downward-facing shadow cameras might play a major role in future energy meteorology. Shadow cameras directly image shadows on the ground from an elevated position. They are used to validate other systems (e.g. all-sky imager based nowcasting systems, cloud speed sensors or satellite forecasts) and can potentially provide short term forecasts for solar power plants. Such forecasts are needed for electricity grids with high penetrations of renewable energy and can help to optimize plant operations. In this publication, two key applications of shadow cameras are briefly presented.

Data-driven agent-based modeling, with application to rooftop solar adoption

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Haifeng; Vorobeychik, Yevgeniy; Letchford, Joshua

Agent-based modeling is commonly used for studying complex system properties emergent from interactions among many agents. We present a novel data-driven agent-based modeling framework applied to forecasting individual and aggregate residential rooftop solar adoption in San Diego county. Our first step is to learn a model of individual agent behavior from combined data of individual adoption characteristics and property assessment. We then construct an agent-based simulation with the learned model embedded in artificial agents, and proceed to validate it using a holdout sequence of collective adoption decisions. We demonstrate that the resulting agent-based model successfully forecasts solar adoption trends andmore » provides a meaningful quantification of uncertainty about its predictions. We utilize our model to optimize two classes of policies aimed at spurring solar adoption: one that subsidizes the cost of adoption, and another that gives away free systems to low-income house- holds. We find that the optimal policies derived for the latter class are significantly more efficacious, whereas the policies similar to the current California Solar Initiative incentive scheme appear to have a limited impact on overall adoption trends.« less

Data-driven agent-based modeling, with application to rooftop solar adoption

DOE PAGES

Zhang, Haifeng; Vorobeychik, Yevgeniy; Letchford, Joshua; ...

2016-01-25

Agent-based modeling is commonly used for studying complex system properties emergent from interactions among many agents. We present a novel data-driven agent-based modeling framework applied to forecasting individual and aggregate residential rooftop solar adoption in San Diego county. Our first step is to learn a model of individual agent behavior from combined data of individual adoption characteristics and property assessment. We then construct an agent-based simulation with the learned model embedded in artificial agents, and proceed to validate it using a holdout sequence of collective adoption decisions. We demonstrate that the resulting agent-based model successfully forecasts solar adoption trends andmore » provides a meaningful quantification of uncertainty about its predictions. We utilize our model to optimize two classes of policies aimed at spurring solar adoption: one that subsidizes the cost of adoption, and another that gives away free systems to low-income house- holds. We find that the optimal policies derived for the latter class are significantly more efficacious, whereas the policies similar to the current California Solar Initiative incentive scheme appear to have a limited impact on overall adoption trends.« less

Forecast of geomagnetic storms using CME parameters and the WSA-ENLIL model

NASA Astrophysics Data System (ADS)

Moon, Y.; Lee, J.; Jang, S.; Na, H.; Lee, J.

2013-12-01

Intense geomagnetic storms are caused by coronal mass ejections (CMEs) from the Sun and their forecast is quite important in protecting space- and ground-based technological systems. The onset and strength of geomagnetic storms depend on the kinematic and magnetic properties of CMEs. Current forecast techniques mostly use solar wind in-situ measurements that provide only a short lead time. On the other hand, techniques using CME observations near the Sun have the potential to provide 1-3 days of lead time before the storm occurs. Therefore, one of the challenging issues is to forecast interplanetary magnetic field (IMF) southward components and hence geomagnetic storm strength with a lead-time on the order of 1-3 days. We are going to answer the following three questions: (1) when does a CME arrive at the Earth? (2) what is the probability that a CME can induce a geomagnetic storm? and (3) how strong is the storm? To address the first question, we forecast the arrival time and other physical parameters of CMEs at the Earth using the WSA-ENLIL model with three CME cone types. The second question is answered by examining the geoeffective and non-geoeffective CMEs depending on CME observations (speed, source location, earthward direction, magnetic field orientation, and cone-model output). The third question is addressed by examining the relationship between CME parameters and geomagnetic indices (or IMF southward component). The forecast method will be developed with a three-stage approach, which will make a prediction within four hours after the solar coronagraph data become available. We expect that this study will enable us to forecast the onset and strength of a geomagnetic storm a few days in advance using only CME parameters and the physics-based models.

On dependence of seismic activity on 11 year variations in solar activity and/or cosmic rays

NASA Astrophysics Data System (ADS)

Zhantayev, Zhumabek; Khachikyan, Galina; Breusov, Nikolay

2014-05-01

It is found in the last decades that seismic activity of the Earth has a tendency to increase with decreasing solar activity (increasing cosmic rays). A good example of this effect may be the growing number of catastrophic earthquakes in the recent rather long solar minimum. Such results support idea on existence a solar-lithosphere relationship which, no doubts, is a part of total pattern of solar-terrestrial relationships. The physical mechanism of solar-terrestrial relationships is not developed yet. It is believed at present that one of the main contenders for such mechanism may be the global electric circuit (GEC) - vertical current loops, piercing and electrodynamically coupling all geospheres. It is also believed, that the upper boundary of the GEC is located at the magnetopause, where magnetic field of the solar wind reconnects with the geomagnetic field, that results in penetrating solar wind energy into the earth's environment. The effectiveness of the GEC operation depends on intensity of cosmic rays (CR), which ionize the air in the middle atmosphere and provide its conductivity. In connection with the foregoing, it can be expected: i) quantitatively, an increasing seismic activity from solar maximum to solar minimum may be in the same range as increasing CR flux; and ii) in those regions of the globe, where the crust is shipped by the magnetic field lines with number L= ~ 2.0, which are populated by anomalous cosmic rays (ACR), the relationship of seismic activity with variations in solar activity will be manifested most clearly, since there is a pronounced dependence of ACR on solar activity variations. Checking an assumption (i) with data of the global seismological catalog of the NEIC, USGS for 1973-2010, it was found that yearly number of earthquake with magnitude M≥4.5 varies into the 11 year solar cycle in a quantitative range of about 7-8% increasing to solar minimum, that qualitatively and quantitatively as well is in agreement with the variations of CR in the 11 year solar cycle. Checking an assumptions (ii), it is found that during the period from 1973 to 2010, the twenty earthquakes with magnitude M≥7.0 occurred in the seismic areas, where geomagnetic force lines L=2.0 -2.2 are loaned into the earth's crust. Surprisingly, all of these strong earthquakes occurred only at declining phase of the 11 year solar cycle, while were absent at ascending phase. This result proves an expectation (ii) and can be taken into account for forecasting strong earthquake occurrence in the seismic areas where the crust is riddled with geomagnetic field lines L= ~ 2.0. In conclusion: the results support a modern idea that earthquake occurrence is related to operation of global electric circuit, but more research are required to study this problem in more details.

Quantitative impact of aerosols on numerical weather prediction. Part I: Direct radiative forcing

NASA Astrophysics Data System (ADS)

Marquis, J. W.; Zhang, J.; Reid, J. S.; Benedetti, A.; Christensen, M.

2017-12-01

While the effects of aerosols on climate have been extensively studied over the past two decades, the impacts of aerosols on operational weather forecasts have not been carefully quantified. Despite this lack of quantification, aerosol plumes can impact weather forecasts directly by reducing surface reaching solar radiation and indirectly through affecting remotely sensed data that are used for weather forecasts. In part I of this study, the direct impact of smoke aerosol plumes on surface temperature forecasts are quantified using a smoke aerosol event affecting the United States Upper-Midwest in 2015. NCEP, ECMWF and UKMO model forecast surface temperature uncertainties are studied with respect to aerosol loading. Smoke aerosol direct cooling efficiencies are derived and the potential of including aerosol particles in operational forecasts is discussed, with the consideration of aerosol trends, especially over regions with heavy aerosol loading.

Coronal hole evolution from multi-viewpoint data as input for a STEREO solar wind speed persistence model

NASA Astrophysics Data System (ADS)

Temmer, Manuela; Hinterreiter, Jürgen; Reiss, Martin A.

2018-03-01

We present a concept study of a solar wind forecasting method for Earth, based on persistence modeling from STEREO in situ measurements combined with multi-viewpoint EUV observational data. By comparing the fractional areas of coronal holes (CHs) extracted from EUV data of STEREO and SoHO/SDO, we perform an uncertainty assessment derived from changes in the CHs and apply those changes to the predicted solar wind speed profile at 1 AU. We evaluate the method for the time period 2008-2012, and compare the results to a persistence model based on ACE in situ measurements and to the STEREO persistence model without implementing the information on CH evolution. Compared to an ACE based persistence model, the performance of the STEREO persistence model which takes into account the evolution of CHs, is able to increase the number of correctly predicted high-speed streams by about 12%, and to decrease the number of missed streams by about 23%, and the number of false alarms by about 19%. However, the added information on CH evolution is not able to deliver more accurate speed values for the forecast than using the STEREO persistence model without CH information which performs better than an ACE based persistence model. Investigating the CH evolution between STEREO and Earth view for varying separation angles over ˜25-140° East of Earth, we derive some relation between expanding CHs and increasing solar wind speed, but a less clear relation for decaying CHs and decreasing solar wind speed. This fact most likely prevents the method from making more precise forecasts. The obtained results support a future L5 mission and show the importance and valuable contribution using multi-viewpoint data.

Molecular Oxygen in the Thermosphere: Issues and Measurement Strategies

NASA Astrophysics Data System (ADS)

Picone, J. M.; Hedin, A. E.; Drob, D. P.; Meier, R. R.; Bishop, J.; Budzien, S. A.

2002-05-01

We review the state of empirical knowledge regarding the distribution of molecular oxygen in the lower thermosphere (100-200 km), as embodied by the new NRLMSISE-00 empirical atmospheric model, its predecessors, and the underlying databases. For altitudes above 120 km, the two major classes of data (mass spectrometer and solar ultraviolet [UV] absorption) disagree significantly regarding the magnitude of the O2 density and the dependence on solar activity. As a result, the addition of the Solar Maximum Mission (SMM) data set (based on solar UV absorption) to the NRLMSIS database has directly impacted the new model, increasing the complexity of the model's formulation and generally reducing the thermospheric O2 density relative to MSISE-90. Beyond interest in the thermosphere itself, this issue materially affects detailed models of ionospheric chemistry and dynamics as well as modeling of the upper atmospheric airglow. Because these are key elements of both experimental and operational systems which measure and forecast the near-Earth space environment, we present strategies for augmenting the database through analysis of existing data and through future measurements in order to resolve this issue.

On the change in the spectral composition of solar ultraviolet emission preceding proton flares, and its connection with the preflare fluctuations in the horizontal component of the geomagnetic field

NASA Astrophysics Data System (ADS)

Sheiner, Olga; Snegirev, Sergei; Smirnova, Anna

The importance problem of Solar-terrestrial physics is regular forecasting of solar activity phenomena, which negatively influence the human’s health, operating safety, communication, radar sets and others. We previously reported the existence of long-period pulsations of H component of the geomagnetic field recorded at stations tested 2-3 days before the proton solar flares. There are the increasing of pulsation amplitude of the horizontal component of the magnetic field with periods of 30-60 minutes. The spectrum of the flux of ultraviolet solar radiation on the eve of proton flares was conducted to determine the presence of oscillations - precursors of flares, as one of the possible agents causing amplification of large periods pulsations of H component of the geomagnetic field. Used data on ultraviolet radiation of the sun with a wavelength of 115-127 nm are obtained from a geostationary satellite GOES 15, the method of wavelet analysis is used. It is found the congruence in the behavior of spectral components with periods of 30-60 minutes in the ground-based measurements and in UV emission for 3-1 days before the proton flare.

Response of the dynamic and thermodynamic structure of the stratosphere to the solar cycle in the boreal winter

NASA Astrophysics Data System (ADS)

Shi, Chunhua; Gao, Yannan; Cai, Juan; Guo, Dong; Lu, Yan

2018-04-01

The response of the dynamic and thermodynamic structure of the stratosphere to the solar cycle in the boreal winter is investigated based on measurements of the solar cycle by the Spectral Irradiance Monitor onboard the SORCE satellite, monthly ERA-Interim Reanalysis data from the European Center for Medium-Range Weather Forecasts, the radiative transfer scheme of the Beijing Climate Center (BCC-RAD) and a multiple linear regression model. The results show that during periods of strong solar activity, the solar shortwave heating anomaly from the climatology in the tropical upper stratosphere triggers a local warm anomaly and strong westerly winds in mid-latitudes, which strengthens the upward propagation of planetary wave 1 but prevents that of wave 2. The enhanced westerly jet makes a slight adjustment to the propagation path of wave 1, but prevents wave 2 from propagating upward, decreases the dissipation of wave 2 in the extratropical upper stratosphere and hence weakens the Brewer-Dobson circulation. The adiabatic heating term in relation to the Brewer-Dobson circulation shows anomalous warming in the tropical lower stratosphere and anomalous cooling in the mid-latitude upper stratosphere.

Electron Flux Models for Different Energies at Geostationary Orbit

NASA Technical Reports Server (NTRS)

Boynton, R. J.; Balikhin, M. A.; Sibeck, D. G.; Walker, S. N.; Billings, S. A.; Ganushkina, N.

2016-01-01

Forecast models were derived for energetic electrons at all energy ranges sampled by the third-generation Geostationary Operational Environmental Satellites (GOES). These models were based on Multi-Input Single-Output Nonlinear Autoregressive Moving Average with Exogenous inputs methodologies. The model inputs include the solar wind velocity, density and pressure, the fraction of time that the interplanetary magnetic field (IMF) was southward, the IMF contribution of a solar wind-magnetosphere coupling function proposed by Boynton et al. (2011b), and the Dst index. As such, this study has deduced five new 1 h resolution models for the low-energy electrons measured by GOES (30-50 keV, 50-100 keV, 100-200 keV, 200-350 keV, and 350-600 keV) and extended the existing >800 keV and >2 MeV Geostationary Earth Orbit electron fluxes models to forecast at a 1 h resolution. All of these models were shown to provide accurate forecasts, with prediction efficiencies ranging between 66.9% and 82.3%.

Solar wind driven empirical forecast models of the time derivative of the ground magnetic field

NASA Astrophysics Data System (ADS)

Wintoft, Peter; Wik, Magnus; Viljanen, Ari

2015-03-01

Empirical models are developed to provide 10-30-min forecasts of the magnitude of the time derivative of local horizontal ground geomagnetic field (|dBh/dt|) over Europe. The models are driven by ACE solar wind data. A major part of the work has been devoted to the search and selection of datasets to support the model development. To simplify the problem, but at the same time capture sudden changes, 30-min maximum values of |dBh/dt| are forecast with a cadence of 1 min. Models are tested both with and without the use of ACE SWEPAM plasma data. It is shown that the models generally capture sudden increases in |dBh/dt| that are associated with sudden impulses (SI). The SI is the dominant disturbance source for geomagnetic latitudes below 50° N and with minor contribution from substorms. However, at occasions, large disturbances can be seen associated with geomagnetic pulsations. For higher latitudes longer lasting disturbances, associated with substorms, are generally also captured. It is also shown that the models using only solar wind magnetic field as input perform in most cases equally well as models with plasma data. The models have been verified using different approaches including the extremal dependence index which is suitable for rare events.

COMESEP: bridging the gap between the SEP, CME, and terrestrial effects scientific communities

NASA Astrophysics Data System (ADS)

Crosby, Norma; Veronig, Astrid; Rodriguez, Luciano; Vrsnak, Bojan; Vennerstrøm, Susanne; Malandraki, Olga; Dalla, Silvia; Srivastava, Nandita

2016-04-01

In the past there has been a tendency for the geomagnetic storm and solar energetic particle (SEP) communities to work in parallel rather than to apply a cross-disciplinary work approach specifically in regard to space weather forecasting. To provide more awareness on the existing links between these communities, as well as further bridge this gap, the three-year EU FP7 COMESEP (COronal Mass Ejections and Solar Energetic Particles: forecasting the space weather impact) project emphasized cross-collaboration between the SEP, coronal mass ejection, and terrestrial effects scientific communities. COMESEP went from basic solar-terrestrial physics research to space weather operations by developing, validating and implementing multi-purpose tools into an operational 24/7 alert service. Launched in November 2013, the COMESEP alert system provides space weather stakeholders geomagnetic storm alerts ("Event based" and "Next 24 hours") and SEP (proton) storm alerts (E > 10 MeV and E > 60 MeV) without human intervention based on the COMESEP definition of risk. COMESEP alerts and forecasts are freely available on the COMESEP alert website (http://www.comesep.eu/alert), as well as disseminated by e-mail to registered users. Acknowledgement: This work has received funding from the European Commission FP7 Project COMESEP (263252).

Post Alpbach-summerschool project: CARRINGTON MISSION FOR CME DETECTION TO IMPROVE SPACE WEATHER FORECAST

NASA Astrophysics Data System (ADS)

Scheucher, Markus; Urbar, Jaroslav; Musset, Sophie; Andersson, Viktor; Gini, Francesco; Gorski, Jedrzej; Jüstel, Peter; Kiefer, René; Lee, Arrow; Meskers, Arjan; Miles, Oscar; Perakis, Nikolas; Rußwurm, Michael; Scully, Stephen; Seifert, Bernhard; Sorba, Arianna

2014-05-01

The effects of solar activity, especially Coronal Mass Ejections (CMEs), on Earth- and satellite-based systems are well-known and can cause major damage to space-dependent infrastructure. The main problem in current space weather forecasting is the inability to determine necessary forecast parameters of CMEs and Corotating Interaction Regions (CIRs) early enough to react. We present the design for a novel space mission consisting of two spacecraft that is aimed to perform stereoscopic measurements on Earth-directed CMEs and in-situ measurements of CIRs. The magnetic field orientation and structure of CMEs will be measured close to the Sun, using spectro-polarimetry. Geoeffectiveness will be derived by remote sensing the CMEs magnetic field at 0.64AU from the Sun, determining the full magnetic field vector of a CME. This will be achieved by the novel concept of measuring its polarising effects on spacecraft to spacecraft laser beams based upon heterodyne interferometry. Overall structure and trajectory of CMEs will also be monitored by heliospheric imagers and in-situ plasma instruments. To achieve the mission objectives, the orbit is heliocentric at 1AU with a separation angle from the Earth of ±50°. The operational mission lifetime is 6 years with a proposed 6 year extension. If implemented, Carrington will serve as a forecast system which will significantly improve the minimum forecast time for the fastest CMEs with 2000 km/s, from 13 minutes based on current L1 satellites, to around 3 hours.

Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.

2010-01-01

The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the loadmore » and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. Currently, uncertainties associated with wind and load forecasts, as well as uncertainties associated with random generator outages and unexpected disconnection of supply lines, are not taken into account in power grid operation. Thus, operators have little means to weigh the likelihood and magnitude of upcoming events of power imbalance. In this project, funded by the U.S. Department of Energy (DOE), a framework has been developed for incorporating uncertainties associated with wind and load forecast errors, unpredicted ramps, and forced generation disconnections into the energy management system (EMS) as well as generation dispatch and commitment applications. A new approach to evaluate the uncertainty ranges for the required generation performance envelope including balancing capacity, ramping capability, and ramp duration has been proposed. The approach includes three stages: forecast and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence levels. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis, incorporating all sources of uncertainties of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the “flying brick” technique has been developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation algorithm has been developed to validate the accuracy of the confidence intervals.« less

A Robust Design Approach to Cost Estimation: Solar Energy for Marine Corps Expeditionary Operations

DTIC Science & Technology

2014-04-30

areas as photovoltaic arrays for power harvesting, light emitting diodes (LED) for decreased energy consumption, and improved battery and smart power ...conversion system that allows Marines to power systems with solar energy. Each GREENS is comprised of eight photovoltaic array panels, four high-energy...Brandon Newell conducted an experiment where he assessed the capabilities of the HOMER model in forecasting the power output of a solar panel at the

Operational specification and forecasting advances for Dst, LEO thermospheric densities, and aviation radiation dose and dose rate

NASA Astrophysics Data System (ADS)

Tobiska, W.; Knipp, D. J.; Burke, W. J.; Bouwer, D.; Bailey, J. J.; Hagan, M. P.; Didkovsky, L. V.; Garrett, H. B.; Bowman, B. R.; Gannon, J. L.; Atwell, W.; Blake, J. B.; Crain, W.; Rice, D.; Schunk, R. W.; Fulgham, J.; Bell, D.; Gersey, B.; Wilkins, R.; Fuschino, R.; Flynn, C.; Cecil, K.; Mertens, C. J.; Xu, X.; Crowley, G.; Reynolds, A.; Azeem, S. I.; Wiley, S.; Holland, M.; Malone, K.

2013-12-01

Space weather's effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun's photons, particles, and fields. Of the space environment domains that are affected by space weather, the magnetosphere, thermosphere, and even troposphere are key regions that are affected. Space Environment Technologies (SET) has developed and is producing innovative space weather applications. Key operational systems for providing timely information about the effects of space weather on these domains are SET's Magnetosphere Alert and Prediction System (MAPS), LEO Alert and Prediction System (LAPS), and Automated Radiation Measurements for Aviation Safety (ARMAS) system. MAPS provides a forecast Dst index out to 6 days through the data-driven, redundant data stream Anemomilos algorithm. Anemomilos uses observational proxies for the magnitude, location, and velocity of solar ejecta events. This forecast index is used by satellite operations to characterize upcoming geomagnetic storms, for example. LAPS is the SET fully redundant operational system providing recent history, current epoch, and forecast solar and geomagnetic indices for use in operational versions of the JB2008 thermospheric density model. The thermospheric densities produced by that system, driven by the LAPS data, are forecast to 72-hours to provide the global mass densities for satellite operators. ARMAS is a project that has successfully demonstrated the operation of a micro dosimeter on aircraft to capture the real-time radiation environment due to Galactic Cosmic Rays and Solar Energetic Particles. The dose and dose-rates are captured on aircraft, downlinked in real-time via the Iridium satellites, processed on the ground, incorporated into the most recent NAIRAS global radiation climatology data runs, and made available to end users via the web and smart phone apps. ARMAS provides the 'weather' of the radiation environment to improve air-crew and passenger safety. Many of the data products from MAPS, LAPS, and ARMAS are available on the SpaceWx smartphone app for iPhone, iPad, iPod, and Android professional users and public space weather education. We describe recent forecasting advances for moving the space weather information from these automated systems into operational, derivative products for communications, aviation, and satellite operations uses.

Development of a satellite-based nowcasting system for surface solar radiation

NASA Astrophysics Data System (ADS)

Limbach, Sebastian; Hungershoefer, Katja; Müller, Richard; Trentmann, Jörg; Asmus, Jörg; Schömer, Elmar; Groß, André

2014-05-01

The goal of the RadNowCast project was the development of a tool-chain for a satellite-based nowcasting of the all sky global and direct surface solar radiation. One important application of such short-term forecasts is the computation of the expected energy yield of photovoltaic systems. This information is of great importance for an efficient balancing of power generation and consumption in large, decentralized power grids. Our nowcasting approach is based on an optical-flow analysis of a series of Meteosat SEVIRI satellite images. For this, we extended and combined several existing software tools and set up a series of benchmarks for determining the optimal forecasting parameters. The first step in our processing-chain is the determination of the cloud albedo from the HRV (High Resolution Visible)-satellite images using a Heliosat-type method. The actual nowcasting is then performed by a commercial software system in two steps: First, vector fields characterizing the movement of the clouds are derived from the cloud albedo data from the previous 15 min to 2 hours. Next, these vector fields are combined with the most recent cloud albedo data in order to extrapolate the cloud albedo in the near future. In the last step of the processing, the Gnu-Magic software is used to calculate the global and direct solar radiation based on the forecasted cloud albedo data. For an evaluation of the strengths and weaknesses of our nowcastig system, we analyzed four different benchmarks, each of which covered different weather conditions. We compared the forecasted data with radiation data derived from the real satellite images of the corresponding time steps. The impact of different parameters on the cloud albedo nowcasting and the surface radiation computation has been analysed. Additionally, we could show that our cloud-albedo-based forecasts outperform forecasts based on the original HRV images. Possible future extension are the incorporation of additional data sources, for example NWC-SAF high resolution wind fields, in order to improve the quality of the atmospheric motion fields, and experiments with custom, optimized software components for the optical-flow estimation and the nowcasting.

Wake Response to an Ocean-Feedback Mechanism: Madeira Island Case Study

NASA Astrophysics Data System (ADS)

Caldeira, Rui M. A.; Tomé, Ricardo

2013-08-01

We focus on an island wake episode that occurred in the Madeira Archipelago region of the north-east Atlantic at 32.5° N, 17° W. The Weather Research and Forecasting numerical model was used in a (one-way) downscaling mode, considering initial and boundary conditions from the European Centre for Medium-range Weather Forecasts system. The current literature emphasizes adiabatic effects on the dynamical aspects of atmospheric wakes. Changes in mountain height and consequently its relation to the atmospheric inversion layer should explain the shift in wake regimes, from a `strong-wake' to `weak-wake' scenario. Nevertheless, changes in sea-surface temperature variability in the lee of an island can induce similar regime shifts because of exposure to stronger solar radiation. Increase in evaporation contributes to the enhancement of convection and thus to the uplift of the stratified atmospheric layer above the critical height, with subsequent internal gravity wave activity.

Analysis of extreme summers and prior late winter/spring conditions in central Europe

NASA Astrophysics Data System (ADS)

Träger-Chatterjee, C.; Müller, R. W.; Bendix, J.

2013-05-01

Drought and heat waves during summer in mid-latitudes are a serious threat to human health and agriculture and have negative impacts on the infrastructure, such as problems in energy supply. The appearance of such extreme events is expected to increase with the progress of global warming. A better understanding of the development of extremely hot and dry summers and the identification of possible precursors could help improve existing seasonal forecasts in this regard, and could possibly lead to the development of early warning methods. The development of extremely hot and dry summer seasons in central Europe is attributed to a combined effect of the dominance of anticyclonic weather regimes and soil moisture-atmosphere interactions. The atmospheric circulation largely determines the amount of solar irradiation and the amount of precipitation in an area. These two variables are themselves major factors controlling the soil moisture. Thus, solar irradiation and precipitation are used as proxies to analyse extreme sunny and dry late winter/spring and summer seasons for the period 1958-2011 in Germany and adjacent areas. For this purpose, solar irradiation data from the European Center for Medium Range Weather Forecast 40-yr and interim re-analysis dataset, as well as remote sensing data are used. Precipitation data are taken from the Global Precipitation Climatology Project. To analyse the atmospheric circulation geopotential data at 850 hPa are also taken from the European Center for Medium Range Weather Forecast 40-yr and interim re-analysis datasets. For the years in which extreme summers in terms of high solar irradiation and low precipitation are identified, the previous late winter/spring conditions of solar irradiation and precipitation in Germany and adjacent areas are analysed. Results show that if the El Niño-Southern Oscillation (ENSO) is not very intensely developed, extremely high solar irradiation amounts, together with extremely low precipitation amounts during late winter/spring, might serve as precursor of extremely sunny and dry summer months to be expected.

A computer vision approach for solar radiation nowcasting using MSG images

NASA Astrophysics Data System (ADS)

Álvarez, L.; Castaño Moraga, C. A.; Martín, J.

2010-09-01

Cloud structures and haze are the two main atmospheric phenomena that reduce the performance of solar power plants, since they absorb solar energy reaching terrestrial surface. Thus, accurate forecasting of solar radiation is a challenging research area that involves both a precise localization of cloud structures and haze, as well as the attenuation introduced by these artifacts. Our work presents a novel approach for nowcasting services based on image processing techniques applied to MSG satellite images provided by the EUMETSAT Rapid Scan Service (RSS) service. These data are an interesting source of information for our purposes since every 5 minutes we obtain actual information of the atmospheric state in nearly real time. However, a workaround must be given in order to forecast solar radiation. To that end, we synthetically forecast MSG images forecasts from past images applying computer vision techniques adapted to fluid flows in order to evolve atmospheric state. First, we classify cloud structures on two different layers, corresponding to top and bottom clouds, which includes haze. This two-level classification responds to the dominant climate conditions found in our region of interest, the Canary Islands archipelago, regulated by the Gulf Stream and Trade Winds. Vertical structure of Trade Winds consists of two layers, the bottom one, which is fresh and humid, and the top one, which is warm and dry. Between these two layers a thermal inversion appears that does not allow bottom clouds to go up and naturally divides clouds in these two layers. Top clouds can be directly obtained from satellite images by means of a segmentation algorithm on histogram heights. However, bottom clouds are usually overlapped by the former, so an inpainting algorithm is used to recover overlapped areas of bottom clouds. For each layer, cloud motion is estimated through a correlation based optic flow algorithm that provides a vector field that describes the displacement field in each layer between two consecutive images in a sequence. Since RSS service from EUMETSAT provides images every 5 minutes (Δt), the cloud motion vector field between images at time t0 and (t0 - Δt) is quite similar to that between (t0 - Δt) and (t0 - 2Δt). Under this assumption, we infer the motion vector field for the next image in order to build a synthetic version of the image at time (t0 + Δt). The computation of this future motion vector field takes into account terrain orography in order to produce more realistic forecasts. In this sense, we are currently working on the integration of information from NWP outputs in order to introduce other atmospheric phenomena. Applying this algorithm several times we are able to produce short-term forecasts up to 6 hours with encouraging performance. To validate our results, we use both, comparison of synthetically generated images with the corresponding images at a given time, and direct solar radiation measurement with the set of meteorological stations located at several points of the canarian archipelago.

The Ensemble Space Weather Modeling System (eSWMS): Status, Capabilities and Challenges

NASA Astrophysics Data System (ADS)

Fry, C. D.; Eccles, J. V.; Reich, J. P.

2010-12-01

Marking a milestone in space weather forecasting, the Space Weather Modeling System (SWMS) successfully completed validation testing in advance of operational testing at Air Force Weather Agency’s primary space weather production center. This is the first coupling of stand-alone, physics-based space weather models that are currently in operations at AFWA supporting the warfighter. Significant development effort went into ensuring the component models were portable and scalable while maintaining consistent results across diverse high performance computing platforms. Coupling was accomplished under the Earth System Modeling Framework (ESMF). The coupled space weather models are the Hakamada-Akasofu-Fry version 2 (HAFv2) solar wind model and GAIM1, the ionospheric forecast component of the Global Assimilation of Ionospheric Measurements (GAIM) model. The SWMS was developed by team members from AFWA, Explorations Physics International, Inc. (EXPI) and Space Environment Corporation (SEC). The successful development of the SWMS provides new capabilities beyond enabling extended lead-time, data-driven ionospheric forecasts. These include ingesting diverse data sets at higher resolution, incorporating denser computational grids at finer time steps, and performing probability-based ensemble forecasts. Work of the SWMS development team now focuses on implementing the ensemble-based probability forecast capability by feeding multiple scenarios of 5 days of solar wind forecasts to the GAIM1 model based on the variation of the input fields to the HAFv2 model. The ensemble SWMS (eSWMS) will provide the most-likely space weather scenario with uncertainty estimates for important forecast fields. The eSWMS will allow DoD mission planners to consider the effects of space weather on their systems with more advance warning than is currently possible. The payoff is enhanced, tailored support to the warfighter with improved capabilities, such as point-to-point HF propagation forecasts, single-frequency GPS error corrections, and high cadence, high-resolution Space Situational Awareness (SSA) products. We present the current status of eSWMS, its capabilities, limitations and path of transition to operational use.

Ionosphere monitoring and forecast activities within the IAG working group "Ionosphere Prediction"

NASA Astrophysics Data System (ADS)

Hoque, Mainul; Garcia-Rigo, Alberto; Erdogan, Eren; Cueto Santamaría, Marta; Jakowski, Norbert; Berdermann, Jens; Hernandez-Pajares, Manuel; Schmidt, Michael; Wilken, Volker

2017-04-01

Ionospheric disturbances can affect technologies in space and on Earth disrupting satellite and airline operations, communications networks, navigation systems. As the world becomes ever more dependent on these technologies, ionospheric disturbances as part of space weather pose an increasing risk to the economic vitality and national security. Therefore, having the knowledge of ionospheric state in advance during space weather events is becoming more and more important. To promote scientific cooperation we recently formed a Working Group (WG) called "Ionosphere Predictions" within the International Association of Geodesy (IAG) under Sub-Commission 4.3 "Atmosphere Remote Sensing" of the Commission 4 "Positioning and Applications". The general objective of the WG is to promote the development of ionosphere prediction algorithm/models based on the dependence of ionospheric characteristics on solar and magnetic conditions combining data from different sensors to improve the spatial and temporal resolution and sensitivity taking advantage of different sounding geometries and latency. Our presented work enables the possibility to compare total electron content (TEC) prediction approaches/results from different centers contributing to this WG such as German Aerospace Center (DLR), Universitat Politècnica de Catalunya (UPC), Technische Universität München (TUM) and GMV. DLR developed a model-assisted TEC forecast algorithm taking benefit from actual trends of the TEC behavior at each grid point. Since during perturbations, characterized by large TEC fluctuations or ionization fronts, this approach may fail, the trend information is merged with the current background model which provides a stable climatological TEC behavior. The presented solution is a first step to regularly provide forecasted TEC services via SWACI/IMPC by DLR. UPC forecast model is based on applying linear regression to a temporal window of TEC maps in the Discrete Cosine Transform (DCT) domain. Performance tests are being conducted at the moment in order to improve UPC predicted products for 1-, 2-days ahead. In addition, UPC is working to enable short-term predictions based on UPC real-time GIMs (labelled URTG) and implementing an improved prediction approach. TUM developed a forecast method based on a time series analysis of TEC products which are either B-spline coefficients estimated by a Kalman filter or TEC grid maps derived from the B-spline coefficients. The forecast method uses a Fourier series expansion to extract the trend functions from the estimated TEC product. Then the trend functions are carried out to provide predicted TEC products. The forecast algorithm developed by GMV is based on the ionospheric delay estimation from previous epochs using GNSS data and the main dependence of ionospheric delays on solar and magnetic conditions. Since the ionospheric behavior is highly dependent on the region of the Earth, different region-based algorithmic modifications have been implemented in GMV's magicSBAS ionospheric algorithms to be able to estimate and forecast ionospheric delays worldwide. Different TEC prediction approaches outlined here will certainly help to learn about forecasting ionospheric ionization.

Challenges in Heliophysics and Space Weather: What Instrumentation for the Future?

NASA Astrophysics Data System (ADS)

Guhathakurta, Madhulika

A hundred years ago, the sun-Earth connection (the field of heliophysics research and space weather impacts) was of interest to only a small number of scientists. Solar activity had little effect on daily life. Today, a single strong solar flare could bring civilization to its knees. Modern society has come to depend on technologies sensitive to solar radiation and geomagnetic storms. Particularly vulnerable are intercontinental power grids, interplanetary robotic and human exploration, satellite operations and communications, and GPS navigation. These technologies are woven into the fabric of daily life, from health care and finance to basic utilities. Both short- and long-term forecasting models are urgently needed to mitigate the effects of solar storms and to anticipate their collective impact on aviation, astronaut safety, terrestrial climate and others. Even during a relatively weak solar maximum, the potential consequences that such events can have on society are too important to ignore. The challenges associated with space weather affect all developed and developing countries. Work on space weather specification, modeling, and forecasting has great societal benefit: It is basic research with a high public purpose. At present, we have a fleet “Heliophysics System Observatory” of dedicated spacecraft titled (e.g. SOHO, STEREO, SDO, ACE), and serendipitous resources contributing data for space weather modeling from both remote observations of the sun and in-situ measurements to provide sparse space weather situational awareness which were mostly built for a 2-3 year lifetime and are wearing out and won’t be around for very long. Missions currently in formulation will significantly enhance the capability of physics-based models that are used to understand and predict the impact of the variable sun. To enhance current models, and make them effective in predicting space weather throughout the solar system, we need a distributed network of spacecraft collecting relevant data that can be assimilated into models. In this talk I will discuss several additional approaches that could be used for the necessary augmentation of the existing HSO capabilities and replacement of aging HSO instruments, enabling interplanetary space weather and climate predictions.

Improving Forecasts of Cumulus: An Intersection of the Renewable Energy and Climate Science Communities

NASA Astrophysics Data System (ADS)

Berg, L. K.; Gustafson, W. I., Jr.; Kassianov, E.; Long, C. N.

2015-12-01

Accurate forecasts of broken cloud fields and their associated impact on the downwelling solar irradiance has remained a challenge to the renewable energy industry. Likewise, shallow cumulus play an important role in the Earth's radiation budget and hydrologic cycle and are of interest to the weather forecasting and climate science communities. The main challenge associated with predicting these clouds are their relatively small size (on the order of a kilometer or less) relative to the model grid spacing. Recently, however, there have been significant efforts put into improving forecasts of shallow clouds and the associated temporal and spatial variability of the solar irradiance that they induce. As an example of these efforts, we will describe recent modifications to the standard Kain-Fritsch parameterization as applied within the Weather Research and Forecasting (WRF) model that are designed to improve predictions of the macroscale and microscale structure of shallow cumulus. These modifications are shown to lead to a realistic increase in the simulated cloud fraction and associated decrease in the solar irradiance. We will evaluate our results using data collected at the Department of Energy's Atmospheric Radiation Measurement (ARM) Southern Great Plains site, which is located in north-central Oklahoma. Our team has analyzed over 5 years of data collected at this site to document the macroscale structure of the clouds (including cloud fraction, cloud-base and cloud-top height) as well as their impact on the downwelling shortwave and longwave irradiance. One particularly interesting impact of shallow cumuli is the enhancement of the diffuse radiation, such that during periods in which the sun is not blocked, the observed irradiance can be significantly larger than the corresponding clear sky case. To date, this feature is not accurately represented by models that apply the plane-parallel assumption applied in the standard radiation parameterizations.

Solar Drivers for Space Weather Operations (Invited)

NASA Astrophysics Data System (ADS)

White, S. M.

2013-12-01

Most space weather effects can be tied back to the Sun, and major research efforts are devoted to understanding the physics of the relevant phenomena with a long-term view of predicting their occurrence. This talk will focus on the current state of knowledge regarding the solar drivers of space weather, and in particular the connection between the science and operational needs. Topics covered will include the effects of solar ionizing flux on communications and navigation, radio interference, flare forecasting, the solar wind and the arrival of coronal mass ejections at Earth.

Forecasting the impact of an 1859-caliber superstorm on geosynchronous Earth-orbiting satellites: Transponder resources

NASA Astrophysics Data System (ADS)

Odenwald, Sten F.; Green, James L.

2007-06-01

We calculate the economic impact on the existing geosynchronous Earth-orbiting satellite population of an 1859-caliber superstorm event were it to occur between 2008 and 2018 during the next solar activity cycle. From a detailed model for transponder capacity and leasing, we have investigated the total revenue loss over the entire solar cycle, as a function of superstorm onset year and intensity. Our Monte Carlo simulations of 1000 possible superstorms, of varying intensity and onset year, suggest that the minimum revenue loss could be of the order of 30 billion. The losses would be larger than this if more that 20 satellites are disabled, if future launch rates do not keep up with the expected rate of retirements, or if the number of spare transponders falls below ˜30%. Consequently, revenue losses can be significantly reduced below 30 billion if the current satellite population undergoes net growth beyond 300 units during Solar Cycle 24 and a larger margin of unused transponders is maintained.

Space Science

NASA Image and Video Library

2002-02-01

This photograph depicts the Solar X-Ray Imager (SXI) being installed in the X-Ray Calibration Facility (XRCF) vacuum chamber for testing at the Marshall Space Flight Center (MSFC). The XRCF vacuum chamber simulates a space environment with low temperature and pressure. The x-ray images from SXI on the Geostationary Operational Environmental Satellite-12 (GOES-12) will be used by the National Oceanic and Atmospheric Administration (NOAA) and U.S. Air Force to forecast the intensity and speed of solar disturbances that could destroy satellite electronics or disrupt long-distance radio communications. The SXI will observe solar flares, coronal mass ejections, coronal holes, and active regions in the x-ray region of the electromagnetic spectrum. These features are the dominant sources of disturbances in space weather. The imager instrument consists of a telescope assembly with a 6.3-inch (16-centimeter) diameter grazing incidence mirror and a detector system. The imager was developed, tested, and calibrated by MSFC, in conjunction with the NASA Goddard Space Flight Center and U.S. Air Force.

An Observationally Constrained Model of a Flux Rope that Formed in the Solar Corona

NASA Astrophysics Data System (ADS)

James, Alexander W.; Valori, Gherardo; Green, Lucie M.; Liu, Yang; Cheung, Mark C. M.; Guo, Yang; van Driel-Gesztelyi, Lidia

2018-03-01

Coronal mass ejections (CMEs) are large-scale eruptions of plasma from the coronae of stars. Understanding the plasma processes involved in CME initiation has applications for space weather forecasting and laboratory plasma experiments. James et al. used extreme-ultraviolet (EUV) observations to conclude that a magnetic flux rope formed in the solar corona above NOAA Active Region 11504 before it erupted on 2012 June 14 (SOL2012-06-14). In this work, we use data from the Solar Dynamics Observatory (SDO) to model the coronal magnetic field of the active region one hour prior to eruption using a nonlinear force-free field extrapolation, and find a flux rope reaching a maximum height of 150 Mm above the photosphere. Estimations of the average twist of the strongly asymmetric extrapolated flux rope are between 1.35 and 1.88 turns, depending on the choice of axis, although the erupting structure was not observed to kink. The decay index near the apex of the axis of the extrapolated flux rope is comparable to typical critical values required for the onset of the torus instability, so we suggest that the torus instability drove the eruption.

Detection of Ionospheric Alfven Resonator Signatures in the Equatorial Ionosphere

NASA Technical Reports Server (NTRS)

Simoes, Fernando; Klenzing, Jeffrey; Ivanov, Stoyan; Pfaff, Robert; Freudenreich, Henry; Bilitza, Dieter; Rowland, Douglas; Bromund, Kenneth; Liebrecht, Maria Carmen; Martin, Steven;

Measurements of Ionospheric Density, Temperature, and Spacecraft Charging in a Space Weather Constellation

NASA Astrophysics Data System (ADS)

Balthazor, R. L.; McHarg, M. G.; Wilson, G.

2016-12-01

The Integrated Miniaturized Electrostatic Analyzer (IMESA) is a space weather sensor developed by the United States Air Force Academy and integrated and flown by the DoD's Space Test Program. IMESA records plasma spectrograms from which can be derived plasma density, temperature, and spacecraft frame charging. Results from IMESA currently orbiting on STPSat-3 are presented, showing frame charging effects dependent on a complex function of the number of solar panel cell strings switched in, solar panel current, and plasma density. IMESA will fly on four more satellites launching in the next two calendar years, enabling an undergraduate DoD space weather constellation in Low Earth Orbit that has the ability to significantly improve space weather forecasting capabilities using assimilative forecast models.

Forward Modeling of Coronal Mass Ejection Flux Ropes in the Inner Heliosphere with 3DCORE.

PubMed

Möstl, C; Amerstorfer, T; Palmerio, E; Isavnin, A; Farrugia, C J; Lowder, C; Winslow, R M; Donnerer, J M; Kilpua, E K J; Boakes, P D

2018-03-01

Forecasting the geomagnetic effects of solar storms, known as coronal mass ejections (CMEs), is currently severely limited by our inability to predict the magnetic field configuration in the CME magnetic core and by observational effects of a single spacecraft trajectory through its 3-D structure. CME magnetic flux ropes can lead to continuous forcing of the energy input to the Earth's magnetosphere by strong and steady southward-pointing magnetic fields. Here we demonstrate in a proof-of-concept way a new approach to predict the southward field B z in a CME flux rope. It combines a novel semiempirical model of CME flux rope magnetic fields (Three-Dimensional Coronal ROpe Ejection) with solar observations and in situ magnetic field data from along the Sun-Earth line. These are provided here by the MESSENGER spacecraft for a CME event on 9-13 July 2013. Three-Dimensional Coronal ROpe Ejection is the first such model that contains the interplanetary propagation and evolution of a 3-D flux rope magnetic field, the observation by a synthetic spacecraft, and the prediction of an index of geomagnetic activity. A counterclockwise rotation of the left-handed erupting CME flux rope in the corona of 30° and a deflection angle of 20° is evident from comparison of solar and coronal observations. The calculated Dst matches reasonably the observed Dst minimum and its time evolution, but the results are highly sensitive to the CME axis orientation. We discuss assumptions and limitations of the method prototype and its potential for real time space weather forecasting and heliospheric data interpretation.

Solar and Space Physics: A Science for a Technological Society

NASA Technical Reports Server (NTRS)

2013-01-01

From the interior of the Sun, to the upper atmosphere and near-space environment of Earth, and outward to a region far beyond Pluto where the Sun's influence wanes, advances during the past decade in space physics and solar physics the disciplines NASA refers to as heliophysics have yielded spectacular insights into the phenomena that affect our home in space. This report, from the National Research Council's (NRC's) Committee for a Decadal Strategy in Solar and Space Physics, is the second NRC decadal survey in heliophysics. Building on the research accomplishments realized over the past decade, the report presents a program of basic and applied research for the period 2013-2022 that will improve scientific understanding of the mechanisms that drive the Sun's activity and the fundamental physical processes underlying near-Earth plasma dynamics, determine the physical interactions of Earth's atmospheric layers in the context of the connected Sun-Earth system, and enhance greatly the capability to provide realistic and specific forecasts of Earth's space environment that will better serve the needs of society. Although the recommended program is directed primarily to NASA (Science Mission Directorate -- Heliophysics Division) and the National Science Foundation (NSF) (Directorate for Geosciences -- Atmospheric and Geospace Sciences) for action, the report also recommends actions by other federal agencies, especially the National Oceanic and Atmospheric Administration (NOAA) those parts of NOAA charged with the day-to-day (operational) forecast of space weather. In addition to the recommendations included in this summary, related recommendations are presented in the main text of the report.

Forward Modeling of Coronal Mass Ejection Flux Ropes in the Inner Heliosphere with 3DCORE

NASA Astrophysics Data System (ADS)

Möstl, C.; Amerstorfer, T.; Palmerio, E.; Isavnin, A.; Farrugia, C. J.; Lowder, C.; Winslow, R. M.; Donnerer, J. M.; Kilpua, E. K. J.; Boakes, P. D.

2018-03-01

Forecasting the geomagnetic effects of solar storms, known as coronal mass ejections (CMEs), is currently severely limited by our inability to predict the magnetic field configuration in the CME magnetic core and by observational effects of a single spacecraft trajectory through its 3-D structure. CME magnetic flux ropes can lead to continuous forcing of the energy input to the Earth's magnetosphere by strong and steady southward-pointing magnetic fields. Here we demonstrate in a proof-of-concept way a new approach to predict the southward field Bz in a CME flux rope. It combines a novel semiempirical model of CME flux rope magnetic fields (Three-Dimensional Coronal ROpe Ejection) with solar observations and in situ magnetic field data from along the Sun-Earth line. These are provided here by the MESSENGER spacecraft for a CME event on 9-13 July 2013. Three-Dimensional Coronal ROpe Ejection is the first such model that contains the interplanetary propagation and evolution of a 3-D flux rope magnetic field, the observation by a synthetic spacecraft, and the prediction of an index of geomagnetic activity. A counterclockwise rotation of the left-handed erupting CME flux rope in the corona of 30° and a deflection angle of 20° is evident from comparison of solar and coronal observations. The calculated Dst matches reasonably the observed Dst minimum and its time evolution, but the results are highly sensitive to the CME axis orientation. We discuss assumptions and limitations of the method prototype and its potential for real time space weather forecasting and heliospheric data interpretation.

Solar Cycle #24 and the Solar Dynamo

NASA Technical Reports Server (NTRS)

Schatten, Kenneth; Pesnell, W. Dean

2007-01-01

We focus on two solar aspects related to flight dynamics. These are the solar dynamo and long-term solar activity predictions. The nature of the solar dynamo is central to solar activity predictions, and these predictions are important for orbital planning of satellites in low earth orbit (LEO). The reason is that the solar ultraviolet (UV) and extreme ultraviolet (EUV) spectral irradiances inflate the upper atmospheric layers of the Earth, forming the thermosphere and exosphere through which these satellites orbit. Concerning the dynamo, we discuss some recent novel approaches towards its understanding. For solar predictions we concentrate on a solar precursor method, in which the Sun's polar field plays a major role in forecasting the next cycle s activity based upon the Babcock-Leighton dynamo. With a current low value for the Sun s polar field, this method predicts that solar cycle #24 will be one of the lowest in recent times, with smoothed F10.7 radio flux values peaking near 130 plus or minus 30 (2 sigma), in the 2013 timeframe. One may have to consider solar activity as far back as the early 20th century to find a cycle of comparable magnitude. Concomitant effects of low solar activity upon satellites in LEO will need to be considered, such as enhancements in orbital debris. Support for our prediction of a low solar cycle #24 is borne out by the lack of new cycle sunspots at least through the first half of 2007. Usually at the present epoch in the solar cycle (approx. 7+ years after the last solar maximum), for a normal size following cycle, new cycle sunspots would be seen. The lack of their appearance at this time is only consistent with a low cycle #24. Polar field observations of a weak magnitude are consistent with unusual structures seen in the Sun s corona. Polar coronal holes are the hallmarks of the Sun's open field structures. At present, it appears that the polar coronal holes are relatively weak, and there have been many equatorial coronal holes. This appears consistent with a weakening polar field, but coronal hole data must be scrutinized carefully as observing techniques have changed. We also discuss new solar dynamo ideas, and the SODA (SOlar Dynamo Amplitude) index, which provides the user with the ability to track the Sun's hidden, dynamo magnetic fields throughout the various stages of the Sun's cycle. Our solar dynamo ideas are a modernization and rejuvenation of the Babcock-Leighton original idea of a shallow solar dynamo, using modern observations that appear to support their shallow dynamo viewpoint. We are in awe of being able to see an object the size of the Sun undergoing as dramatic a change as our model provides in a few short years. The Sun, however, has undergone changes as rapid as this before! The weather on the Sun is at least as fickle as the weather on the Earth.

Solar Cycle #24 and the Solar Dynamo

NASA Technical Reports Server (NTRS)

Pesnell, W. Dean; Schatten, Kenneth

2007-01-01

We focus on two solar aspects related to flight dynamics. These are the solar dynamo and long-term solar activity predictions. The nature of the solar dynamo is central to solar activity predictions, and these predictions are important for orbital planning of satellites in low earth orbit (LEO). The reason is that the solar ultraviolet (UV) and extreme ultraviolet (EUV) spectral irradiances inflate the upper atmospheric layers of the Earth, forming the thermosphere and exosphere through which these satellites orbit. Concerning the dynamo, we discuss some recent novel approaches towards its understanding. For solar predictions we concentrate on a solar precursor method, in which the Sun s polar field plays a major role in forecasting the next cycle s activity based upon the Babcock- Leighton dynamo. With a current low value for the Sun s polar field, this method predicts that solar cycle #24 will be one of the lowest in recent times, with smoothed F10.7 radio flux values peaking near 130+ 30 (2 4, in the 2013 timeframe. One may have to consider solar activity as far back as the early 20th century to find a cycle of comparable magnitude. Concomitant effects of low solar activity upon satellites in LEO will need to be considered, such as enhancements in orbital debris. Support for our prediction of a low solar cycle #24 is borne out by the lack of new cycle sunspots at least through the first half of 2007. Usually at the present epoch in the solar cycle (-7+ years after the last solar maximum), for a normal size following cycle, new cycle sunspots would be seen. The lack of their appearance at this time is only consistent with a low cycle #24. Polar field observations of a weak magnitude are consistent with unusual structures seen in the Sun s corona. Polar coronal holes are the hallmarks of the Sun s open field structures. At present, it appears that the polar coronal holes are relatively weak, and there have been many equatorial coronal holes. This appears consistent with a weakening polar field, but coronal hole data must be scrutinized carefully as observing techniques have changed. We also discuss new solar dynamo ideas, and the SODA (Solar Dynamo Amplitude) index, which provides the user with the ability to track the Sun s hidden, dynamo magnetic fields throughout the various stages of the Sun s cycle. Our solar dynamo ideas are a modernization and rejuvenation of the Babcock-Leighton original idea of a shallow solar dynamo, using modem observations that appear to support their shallow dynamo viewpoint. We are in awe of being able to see an object the size of the Sun undergoing as dramatic a change as our model provides in a few short years. The Sun, however, has undergone changes as rapid as this before! The weather on the Sun is at least as fickle as the weather on the Earth.

JPRS Report, Science & Technology. Japan: Economic Planning Agency Technology Forecast to the Year 2010.

DTIC Science & Technology

1991-11-17

are several concrete examples of how these affect application. (1) For the development and spread of solar photoelectric power generation, under the...technician in charge of each generator. In order to promote the installation of solar cells at various households and businesses, the relevant laws must be...products from microorganisms ’ Solar photoelectric power Communications satellites Skyscrapers Alone in 1st Tied for 1st 10 Years Ago Present !i

Constructing probabilistic scenarios for wide-area solar power generation

DOE PAGES

Woodruff, David L.; Deride, Julio; Staid, Andrea; ...

2017-12-22

Optimizing thermal generation commitments and dispatch in the presence of high penetrations of renewable resources such as solar energy requires a characterization of their stochastic properties. In this study, we describe novel methods designed to create day-ahead, wide-area probabilistic solar power scenarios based only on historical forecasts and associated observations of solar power production. Each scenario represents a possible trajectory for solar power in next-day operations with an associated probability computed by algorithms that use historical forecast errors. Scenarios are created by segmentation of historic data, fitting non-parametric error distributions using epi-splines, and then computing specific quantiles from these distributions.more » Additionally, we address the challenge of establishing an upper bound on solar power output. Our specific application driver is for use in stochastic variants of core power systems operations optimization problems, e.g., unit commitment and economic dispatch. These problems require as input a range of possible future realizations of renewables production. However, the utility of such probabilistic scenarios extends to other contexts, e.g., operator and trader situational awareness. Finally, we compare the performance of our approach to a recently proposed method based on quantile regression, and demonstrate that our method performs comparably to this approach in terms of two widely used methods for assessing the quality of probabilistic scenarios: the Energy score and the Variogram score.« less

Constructing probabilistic scenarios for wide-area solar power generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woodruff, David L.; Deride, Julio; Staid, Andrea

Optimizing thermal generation commitments and dispatch in the presence of high penetrations of renewable resources such as solar energy requires a characterization of their stochastic properties. In this study, we describe novel methods designed to create day-ahead, wide-area probabilistic solar power scenarios based only on historical forecasts and associated observations of solar power production. Each scenario represents a possible trajectory for solar power in next-day operations with an associated probability computed by algorithms that use historical forecast errors. Scenarios are created by segmentation of historic data, fitting non-parametric error distributions using epi-splines, and then computing specific quantiles from these distributions.more » Additionally, we address the challenge of establishing an upper bound on solar power output. Our specific application driver is for use in stochastic variants of core power systems operations optimization problems, e.g., unit commitment and economic dispatch. These problems require as input a range of possible future realizations of renewables production. However, the utility of such probabilistic scenarios extends to other contexts, e.g., operator and trader situational awareness. Finally, we compare the performance of our approach to a recently proposed method based on quantile regression, and demonstrate that our method performs comparably to this approach in terms of two widely used methods for assessing the quality of probabilistic scenarios: the Energy score and the Variogram score.« less

Exploring predictive performance: A reanalysis of the geospace model transition challenge

NASA Astrophysics Data System (ADS)

Welling, D. T.; Anderson, B. J.; Crowley, G.; Pulkkinen, A. A.; Rastätter, L.

2017-01-01

The Pulkkinen et al. (2013) study evaluated the ability of five different geospace models to predict surface dB/dt as a function of upstream solar drivers. This was an important step in the assessment of research models for predicting and ultimately preventing the damaging effects of geomagnetically induced currents. Many questions remain concerning the capabilities of these models. This study presents a reanalysis of the Pulkkinen et al. (2013) results in an attempt to better understand the models' performance. The range of validity of the models is determined by examining the conditions corresponding to the empirical input data. It is found that the empirical conductance models on which global magnetohydrodynamic models rely are frequently used outside the limits of their input data. The prediction error for the models is sorted as a function of solar driving and geomagnetic activity. It is found that all models show a bias toward underprediction, especially during active times. These results have implications for future research aimed at improving operational forecast models.

Quantifying variability in fast and slow solar wind: From turbulence to extremes

NASA Astrophysics Data System (ADS)

Tindale, E.; Chapman, S. C.; Moloney, N.; Watkins, N. W.

2017-12-01

Fast and slow solar wind exhibit variability across a wide range of spatiotemporal scales, with evolving turbulence producing fluctuations on sub-hour timescales and the irregular solar cycle modulating the system over many years. Here, we apply the data quantile-quantile (DQQ) method [Tindale and Chapman 2016, 2017] to over 20 years of Wind data, to study the time evolution of the statistical distribution of plasma parameters in fast and slow solar wind. This model-independent method allows us to simultaneously explore the evolution of fluctuations across all scales. We find a two-part functional form for the statistical distributions of the interplanetary magnetic field (IMF) magnitude and its components, with each region of the distribution evolving separately over the solar cycle. Up to a value of 8nT, turbulent fluctuations dominate the distribution of the IMF, generating the approximately lognormal shape found by Burlaga [2001]. The mean of this core-turbulence region tracks solar cycle activity, while its variance remains constant, independent of the fast or slow state of the solar wind. However, when we test the lognormality of this core-turbulence component over time, we find the model provides a poor description of the data at solar maximum, where sharp peaks in the distribution dominate over the lognormal shape. At IMF values higher than 8nT, we find a separate, extremal distribution component, whose moments are sensitive to solar cycle phase, the peak activity of the cycle and the solar wind state. We further investigate these `extremal' values using burst analysis, where a burst is defined as a continuous period of exceedance over a predefined threshold. This form of extreme value statistics allows us to study the stochastic process underlying the time series, potentially supporting a probabilistic forecast of high-energy events. Tindale, E., and S.C. Chapman (2016), Geophys. Res. Lett., 43(11) Tindale, E., and S.C. Chapman (2017), submitted Burlaga, L.F. (2001), J. Geophys. Res., 106(A8)

PROBABILITY OF CME IMPACT ON EXOPLANETS ORBITING M DWARFS AND SOLAR-LIKE STARS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kay, C.; Opher, M.; Kornbleuth, M., E-mail: ckay@bu.edu

2016-08-01

Solar coronal mass ejections (CMEs) produce adverse space weather effects at Earth. Planets in the close habitable zone of magnetically active M dwarfs may experience more extreme space weather than at Earth, including frequent CME impacts leading to atmospheric erosion and leaving the surface exposed to extreme flare activity. Similar erosion may occur for hot Jupiters with close orbits around solar-like stars. We have developed a model, Forecasting a CME's Altered Trajectory (ForeCAT), which predicts a CME's deflection. We adapt ForeCAT to simulate CME deflections for the mid-type M dwarf V374 Peg and hot Jupiters with solar-type hosts. V374 Peg'smore » strong magnetic fields can trap CMEs at the M dwarfs's Astrospheric Current Sheet, that is, the location of the minimum in the background magnetic field. Solar-type CMEs behave similarly, but have much smaller deflections and do not become trapped at the Astrospheric Current Sheet. The probability of planetary impact decreases with increasing inclination of the planetary orbit with respect to the Astrospheric Current Sheet: 0.5–5 CME impacts per day for M dwarf exoplanets, 0.05–0.5 CME impacts per day for solar-type hot Jupiters. We determine the minimum planetary magnetic field necessary to shield a planet's atmosphere from CME impacts. M dwarf exoplanets require values between tens and hundreds of Gauss. Hot Jupiters around a solar-type star, however, require a more reasonable <30 G. These values exceed the magnitude required to shield a planet from the stellar wind, suggesting that CMEs may be the key driver of atmospheric losses.« less

Space Radiation Monitoring Center at SINP MSU

NASA Astrophysics Data System (ADS)

Kalegaev, Vladimir; Barinova, Wera; Barinov, Oleg; Bobrovnikov, Sergey; Dolenko, Sergey; Mukhametdinova, Ludmila; Myagkova, Irina; Nguen, Minh; Panasyuk, Mikhail; Shiroky, Vladimir; Shugay, Julia

2015-04-01

Data on energetic particle fluxes from Russian satellites have been collected in Space monitoring data center at Moscow State University in the near real-time mode. Web-portal http://smdc.sinp.msu.ru/ provides operational information on radiation state of the near-Earth space. Operational data are coming from space missions ELECTRO-L1, Meteor-M2. High-resolution data on energetic electron fluxes from MSU's satellite VERNOV with RELEC instrumentation on board are also available. Specific tools allow the visual representation of the satellite orbit in 3D space simultaneously with particle fluxes variations. Concurrent operational data coming from other spacecraft (ACE, GOES, SDO) and from the Earth's surface (geomagnetic indices) are used to represent geomagnetic and radiation state of near-Earth environment. Internet portal http://swx.sinp.msu.ru provides access to the actual data characterizing the level of solar activity, geomagnetic and radiation conditions in heliosphere and the Earth's magnetosphere in the real-time mode. Operational forecasting services automatically generate alerts on particle fluxes enhancements above the threshold values, both for SEP and relativistic electrons, using data from LEO and GEO orbits. The models of space environment working in autonomous mode are used to generalize the information obtained from different missions for the whole magnetosphere. On-line applications created on the base of these models provide short-term forecasting for SEP particles and relativistic electron fluxes at GEO and LEO, Dst and Kp indices online forecasting up to 1.5 hours ahead. Velocities of high-speed streams in solar wind on the Earth orbit are estimated with advance time of 3-4 days. Visualization system provides representation of experimental and modeling data in 2D and 3D.

Perturbed-input-data ensemble modeling of magnetospheric dynamics

NASA Astrophysics Data System (ADS)

Morley, S.; Steinberg, J. T.; Haiducek, J. D.; Welling, D. T.; Hassan, E.; Weaver, B. P.

2017-12-01

Many models of Earth's magnetospheric dynamics - including global magnetohydrodynamic models, reduced complexity models of substorms and empirical models - are driven by solar wind parameters. To provide consistent coverage of the upstream solar wind these measurements are generally taken near the first Lagrangian point (L1) and algorithmically propagated to the nose of Earth's bow shock. However, the plasma and magnetic field measured near L1 is a point measurement of an inhomogeneous medium, so the individual measurement may not be sufficiently representative of the broader region near L1. The measured plasma may not actually interact with the Earth, and the solar wind structure may evolve between L1 and the bow shock. To quantify uncertainties in simulations, as well as to provide probabilistic forecasts, it is desirable to use perturbed input ensembles of magnetospheric and space weather forecasting models. By using concurrent measurements of the solar wind near L1 and near the Earth, we construct a statistical model of the distributions of solar wind parameters conditioned on their upstream value. So that we can draw random variates from our model we specify the conditional probability distributions using Kernel Density Estimation. We demonstrate the utility of this approach using ensemble runs of selected models that can be used for space weather prediction.

Integrating Solar PV in Utility System Operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mills, A.; Botterud, A.; Wu, J.

2013-10-31

This study develops a systematic framework for estimating the increase in operating costs due to uncertainty and variability in renewable resources, uses the framework to quantify the integration costs associated with sub-hourly solar power variability and uncertainty, and shows how changes in system operations may affect these costs. Toward this end, we present a statistical method for estimating the required balancing reserves to maintain system reliability along with a model for commitment and dispatch of the portfolio of thermal and renewable resources at different stages of system operations. We estimate the costs of sub-hourly solar variability, short-term forecast errors, andmore » day-ahead (DA) forecast errors as the difference in production costs between a case with “realistic” PV (i.e., subhourly solar variability and uncertainty are fully included in the modeling) and a case with “well behaved” PV (i.e., PV is assumed to have no sub-hourly variability and can be perfectly forecasted). In addition, we highlight current practices that allow utilities to compensate for the issues encountered at the sub-hourly time frame with increased levels of PV penetration. In this analysis we use the analytical framework to simulate utility operations with increasing deployment of PV in a case study of Arizona Public Service Company (APS), a utility in the southwestern United States. In our analysis, we focus on three processes that are important in understanding the management of PV variability and uncertainty in power system operations. First, we represent the decisions made the day before the operating day through a DA commitment model that relies on imperfect DA forecasts of load and wind as well as PV generation. Second, we represent the decisions made by schedulers in the operating day through hour-ahead (HA) scheduling. Peaking units can be committed or decommitted in the HA schedules and online units can be redispatched using forecasts that are improved relative to DA forecasts, but still imperfect. Finally, we represent decisions within the operating hour by schedulers and transmission system operators as real-time (RT) balancing. We simulate the DA and HA scheduling processes with a detailed unit-commitment (UC) and economic dispatch (ED) optimization model. This model creates a least-cost dispatch and commitment plan for the conventional generating units using forecasts and reserve requirements as inputs. We consider only the generation units and load of the utility in this analysis; we do not consider opportunities to trade power with neighboring utilities. We also do not consider provision of reserves from renewables or from demand-side options. We estimate dynamic reserve requirements in order to meet reliability requirements in the RT operations, considering the uncertainty and variability in load, solar PV, and wind resources. Balancing reserve requirements are based on the 2.5th and 97.5th percentile of 1-min deviations from the HA schedule in a previous year. We then simulate RT deployment of balancing reserves using a separate minute-by-minute simulation of deviations from the HA schedules in the operating year. In the simulations we assume that balancing reserves can be fully deployed in 10 min. The minute-by-minute deviations account for HA forecasting errors and the actual variability of the load, wind, and solar generation. Using these minute-by-minute deviations and deployment of balancing reserves, we evaluate the impact of PV on system reliability through the calculation of the standard reliability metric called Control Performance Standard 2 (CPS2). Broadly speaking, the CPS2 score measures the percentage of 10-min periods in which a balancing area is able to balance supply and demand within a specific threshold. Compliance with the North American Electric Reliability Corporation (NERC) reliability standards requires that the CPS2 score must exceed 90% (i.e., the balancing area must maintain adequate balance for 90% of the 10-min periods). The combination of representing DA forecast errors in the DA commitments, using 1-min PV data to simulate RT balancing, and estimates of reliability performance through the CPS2 metric, all factors that are important to operating systems with increasing amounts of PV, makes this study unique in its scope.« less

Evaluation and prediction of solar radiation for energy management based on neural networks

NASA Astrophysics Data System (ADS)

Aldoshina, O. V.; Van Tai, Dinh

2017-08-01

Currently, there is a high rate of distribution of renewable energy sources and distributed power generation based on intelligent networks; therefore, meteorological forecasts are particularly useful for planning and managing the energy system in order to increase its overall efficiency and productivity. The application of artificial neural networks (ANN) in the field of photovoltaic energy is presented in this article. Implemented in this study, two periodically repeating dynamic ANS, that are the concentration of the time delay of a neural network (CTDNN) and the non-linear autoregression of a network with exogenous inputs of the NAEI, are used in the development of a model for estimating and daily forecasting of solar radiation. ANN show good productivity, as reliable and accurate models of daily solar radiation are obtained. This allows to successfully predict the photovoltaic output power for this installation. The potential of the proposed method for controlling the energy of the electrical network is shown using the example of the application of the NAEI network for predicting the electric load.

Geospace monitoring for space weather research and operation

NASA Astrophysics Data System (ADS)

Nagatsuma, Tsutomu

2017-10-01

Geospace, a space surrounding the Earth, is one of the key area for space weather. Because geospace environment dynamically varies depending on the solar wind conditions. Many kinds of space assets are operating in geospace for practical purposes. Anomalies of space assets are sometimes happened because of space weather disturbances in geospace. Therefore, monitoring and forecasting of geospace environment is very important tasks for NICT's space weather research and development. To monitor and to improve forecasting model, fluxgate magnetometers and HF radars are operated by our laboratory, and its data are used for our research work, too. We also operate real-time data acquisition system for satellite data, such as DSCOVR, STEREO, and routinely received high energy particle data from Himawari-8. Based on these data, we are monitoring current condition of geomagnetic disturbances, and that of radiation belt. Using these data, we have developed empirical models for relativistic electron flux at GEO and inner magnetosphere. To provide userfriendly information , we are trying to develop individual spacecraft anomaly risk estimation tool based on combining models of space weather and those of spacecraft charging, Current status of geospace monitoring, forecasting, and research activities are introduced.

Solar irradiance assessment in insular areas using Himawari-8 satellite images

NASA Astrophysics Data System (ADS)

Liandrat, O.; Cros, S.; Turpin, M.; Pineau, J. F.

2016-12-01

The high amount of surface solar irradiance (SSI) in the tropics is an advantage for a profitable PV production. It will allow many tropical islands to pursue their economic growth with a clean, affordable and locally produced energy. However, the local meteorological conditions induce a very high variability which is problematic for a safe and gainful injection into the power grid. This issue is even more critical in non-interconnected territories where network stability is an absolute necessity. Therefore, the injection of PV power is legally limited in some European oversea territories. In this context, intraday irradiance forecasting (several hours ahead) is particularly useful to mitigate the production variability by reducing the cost of power storage management. At this time scale, cloud cover evolves with a stochastic behaviour not properly represented in numerical weather prediction (NWP) models. Analysing cloud motion using images from geostationary meteorological satellites is a well-known alternative to forecasting SSI up to 6 hours ahead with a better accuracy than NWP models. In this study, we present and apply our satellite-based solar irradiance forecasting methods over two measurement sites located in the field of view of the satellite Himawari-8: Cocos (Keeling) Islands (Australia) and New Caledonia (France). In particular, we converted 4 months of images from Himawari-8 visible channel into cloud index maps. Then, we applied an algorithm computing a cloud motion vector field from a short sequence of consecutive images. Comparisons between forecasted SSI at 1 hour of time horizon and collocated pyranometric measurements show a relative RMSE between 20 and 27%. Error sources related to the tropic insular context (coastal area heterogeneity, sub-pixel scale orographic cloud appearance, convective situation…) are discussed at every implementation step for the different methods.

Risk Analysis and Forecast Service for Geomagnetically Induced Currents in Europe

NASA Astrophysics Data System (ADS)

Wik, Magnus; Pirjola, Risto; Viljanen, Ari; Lundstedt, Henrik

Geomagnetically induced currents (GIC), occurring during magnetic storms, pose a widespread natural disaster risk to the reliable operation of electric power transmission grids, oil and gas pipelines, telecommunication cables and railway systems. The solar magnetic activity is the cause of GIC. Solar coronal holes can cause recurrent inter-vals of raised geomagnetic activity, and coronal mass ejections (CME) at the Sun, sometimes producing very high speed plasma clouds with enhanced magnetic fields and particle densities, can cause the strongest geomagnetic storms. When the solar wind interacts with the geomag-netic field, energy is transferred to the magnetosphere, driving strong currents in the ionosphere. When these currents change in time a geoelectric field is induced at the surface of the Earth and in the ground. Finally, this field drives GIC in the ground and in any technological conductor systems. The worst consequence of a severe magnetic storm within a power grid is a complete blackout, as happened in the province of Québec, Canada, in March 1989, and in the city of Malmü, Sweden, in October 2003. Gas and oil pipelines are not regarded as vulnerable to the immediate impact of GIC, but the corrosion rate of buried steel pipes can increase due to GIC, which may thus shorten the lifetime of a pipe. European Risk from Geomagnetically Induced Currents (EURISGIC) is an EU project, that, if approved, will produce the first European-wide real-time prototype forecast service of GIC in power systems, based on in-situ solar wind observations and comprehensive simulations of the Earth's magnetosphere. This project focuses on high-voltage power transmission networks, which are probably currently the most susceptible to GIC effects. Geomagnetic storms cover large geographical regions, at times the whole globe. Consequently, power networks are rightly described as being European critical infrastructures whose disruption or destruction could have a significant impact. The project includes six research institutes and one SME, within Europe and US. The Federal Emergency Management Agency (FEMA), the Swedish civil contingencies agency (MSB), and representatives from the European Commission are collaborating with the NOAA National Weather Service and other research institutes on various space weather scenarios -geomagnetic storms with widespread blackouts and disruptions in communications. The aim of this new project is to conduct a risk analysis from GIC on critical infrastructure. Large amounts of natural gas are transported from Russia to Central Europe. Those long pipelines are prone to GIC impacts, which should also be evaluated quantitatively. We will use the EURISGIC project to inform the pipeline community of present European capability in GIC modelling, forecasting and in developing mitigation measures.

New Radiosonde Temperature Bias Adjustments for Potential NWP Applications Based on GPS RO Data

NASA Astrophysics Data System (ADS)

Sun, B.; Reale, A.; Ballish, B.; Seidel, D. J.

2014-12-01

Conventional radiosonde observations (RAOBs), along with satellite and other in situ data, are assimilated in numerical weather prediction (NWP) models to generate a forecast. Radiosonde temperature observations, however, have solar and thermal radiation induced biases (typically a warm daytime bias from sunlight heating the sensor and a cold bias at night as the sensor emits longwave radiation). Radiation corrections made at stations based on algorithms provided by radiosonde manufacturers or national meteorological agencies may not be adequate, so biases remain. To adjust these biases, NWP centers may make additional adjustments to radiosonde data. However, the radiation correction (RADCOR) schemes used in the NOAA NCEP data assimilation and forecasting system is outdated and does not cover several widely-used contemporary radiosonde types. This study focuses on work whose objective is to improve these corrections and test their impacts on the NWP forecasting and analysis. GPS Radio Occultation (RO) dry temperature (Tdry) is considered to be highly accurate in the upper troposphere and low stratosphere where atmospheric water vapor is negligible. This study uses GPS RO Tdry from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) as the reference to quantify the radiation induced RAOB temperature errors by analyzing ~ 3-yr collocated RAOB and COSMIC GPS RO data compile by the NOAA Products Validation System (NPROVS). The new radiation adjustments are developed for different solar angle categories and for all common sonde types flown in the WMO global operational upper air network. Results for global and several commonly used sondes are presented in the context of NCEP Global Forecast System observation-minus-background analysis, indicating projected impacts in reducing forecast error. Dedicated NWP impact studies to quantify the impact of the new RADCOR schemes on the NCEP analyses and forecast are under consideration.

Solar-wind predictions for the Parker Solar Probe orbit. Near-Sun extrapolations derived from an empirical solar-wind model based on Helios and OMNI observations

NASA Astrophysics Data System (ADS)

Venzmer, M. S.; Bothmer, V.

2018-03-01

Context. The Parker Solar Probe (PSP; formerly Solar Probe Plus) mission will be humanitys first in situ exploration of the solar corona with closest perihelia at 9.86 solar radii (R⊙) distance to the Sun. It will help answer hitherto unresolved questions on the heating of the solar corona and the source and acceleration of the solar wind and solar energetic particles. The scope of this study is to model the solar-wind environment for PSPs unprecedented distances in its prime mission phase during the years 2018 to 2025. The study is performed within the Coronagraphic German And US SolarProbePlus Survey (CGAUSS) which is the German contribution to the PSP mission as part of the Wide-field Imager for Solar PRobe. Aim. We present an empirical solar-wind model for the inner heliosphere which is derived from OMNI and Helios data. The German-US space probes Helios 1 and Helios 2 flew in the 1970s and observed solar wind in the ecliptic within heliocentric distances of 0.29 au to 0.98 au. The OMNI database consists of multi-spacecraft intercalibrated in situ data obtained near 1 au over more than five solar cycles. The international sunspot number (SSN) and its predictions are used to derive dependencies of the major solar-wind parameters on solar activity and to forecast their properties for the PSP mission. Methods: The frequency distributions for the solar-wind key parameters, magnetic field strength, proton velocity, density, and temperature, are represented by lognormal functions. In addition, we consider the velocity distributions bi-componental shape, consisting of a slower and a faster part. Functional relations to solar activity are compiled with use of the OMNI data by correlating and fitting the frequency distributions with the SSN. Further, based on the combined data set from both Helios probes, the parameters frequency distributions are fitted with respect to solar distance to obtain power law dependencies. Thus an empirical solar-wind model for the inner heliosphere confined to the ecliptic region is derived, accounting for solar activity and for solar distance through adequate shifts of the lognormal distributions. Finally, the inclusion of SSN predictions and the extrapolation down to PSPs perihelion region enables us to estimate the solar-wind environment for PSPs planned trajectory during its mission duration. Results: The CGAUSS empirical solar-wind model for PSP yields dependencies on solar activity and solar distance for the solar-wind parameters' frequency distributions. The estimated solar-wind median values for PSPs first perihelion in 2018 at a solar distance of 0.16 au are 87 nT, 340 km s-1, 214 cm-3, and 503 000 K. The estimates for PSPs first closest perihelion, occurring in 2024 at 0.046 au (9.86 R⊙), are 943 nT, 290 km s-1, 2951 cm-3, and 1 930 000 K. Since the modeled velocity and temperature values below approximately 20 R⊙appear overestimated in comparison with existing observations, this suggests that PSP will directly measure solar-wind acceleration and heating processes below 20 R⊙ as planned.

Department of Defense Space Science and Technology Strategy 2015

DTIC Science & Technology

2015-01-01

solar cells at 34% efficiency enabling higher power spacecraft capability. These solar cells developed by the Air Force Research Laboratory (AFRL...Reduce size, weight, power , cost, and improve thermal management for SATCOM terminals  Support intelligence surveillance and reconnaissance (ISR...Improve understanding and awareness of the Earth-to-Sun environment  Improve space environment forecast capabilities and tools to predict operational

The effects of regional insolation differences upon advanced solar thermal electric power plant performance and energy costs

NASA Technical Reports Server (NTRS)

Latta, A. F.; Bowyer, J. M.; Fujita, T.; Richter, P. H.

1979-01-01

The performance and cost of the 10 MWe advanced solar thermal electric power plants sited in various regions of the continental United States were determined. The regional insolation data base is discussed. A range for the forecast cost of conventional electricity by region and nationally over the next several cades are presented.

First Use of Synoptic Vector Magnetograms for Global Nonlinear, Force-Free Coronal Magnetic Field Models

NASA Technical Reports Server (NTRS)

Tadesse, T.; Wiegelmann, T.; Gosain, S.; MacNeice, P.; Pevtsov, A. A.

2014-01-01

Context. The magnetic field permeating the solar atmosphere is generally thought to provide the energy for much of the activity seen in the solar corona, such as flares, coronal mass ejections (CMEs), etc. To overcome the unavailability of coronal magnetic field measurements, photospheric magnetic field vector data can be used to reconstruct the coronal field. Currently, there are several modelling techniques being used to calculate three-dimensional field lines into the solar atmosphere. Aims. For the first time, synoptic maps of a photospheric-vector magnetic field synthesized from the vector spectromagnetograph (VSM) on Synoptic Optical Long-term Investigations of the Sun (SOLIS) are used to model the coronal magnetic field and estimate free magnetic energy in the global scale. The free energy (i.e., the energy in excess of the potential field energy) is one of the main indicators used in space weather forecasts to predict the eruptivity of active regions. Methods. We solve the nonlinear force-free field equations using an optimization principle in spherical geometry. The resulting threedimensional magnetic fields are used to estimate the magnetic free energy content E(sub free) = E(sub nlfff) - E(sub pot), which is the difference of the magnetic energies between the nonpotential field and the potential field in the global solar corona. For comparison, we overlay the extrapolated magnetic field lines with the extreme ultraviolet (EUV) observations by the atmospheric imaging assembly (AIA) on board the Solar Dynamics Observatory (SDO). Results. For a single Carrington rotation 2121, we find that the global nonlinear force-free field (NLFFF) magnetic energy density is 10.3% higher than the potential one. Most of this free energy is located in active regions.

Relationship between coronal holes and high speed streams at L1: arrival times, durations, and intensities

NASA Astrophysics Data System (ADS)

Luo, B.; Bu, X.; Liu, S.; Gong, J.

2017-12-01

Coronal holes are sources of high-speed steams (HSS) of solar wind. When coronal holes appear at mid/low latitudes on the Sun, consequential HSSs may impact Earth and cause recurrent geospace environment disturbances, such as geomagnetic storms, relativistic electron enhancements at the geosynchronous orbit, and thermosphere density enhancements. Thus, it is of interests for space weather forecasters to predict when (arrival times), how long (time durations), and how severe (intensities) HSSs may impact Earth when they notice coronal holes on the sun and are anticipating their geoeffectiveness. In this study, relationship between coronal holes and high speed streams will be statistically investigated. Several coronal hole parameters, including passage times of solar central meridian, coronal hole longitudinal widths, intensities reflected by mean brightness, are derived using Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA) images for years 2011 to 2016. These parameters will be correlated with in-situ solar wind measurements measured at the L1 point by the ACE spacecraft, which can give some results that are useful for space weather forecaster in predicting the arrival times, durations, and intensities of coronal hole high-speed streams in about 3 days advance.

An improved empirical model of electron and ion fluxes at geosynchronous orbit based on upstream solar wind conditions

DOE PAGES

Denton, M. H.; Henderson, M. G.; Jordanova, V. K.; ...

2016-07-01

In this study, a new empirical model of the electron fluxes and ion fluxes at geosynchronous orbit (GEO) is introduced, based on observations by Los Alamos National Laboratory (LANL) satellites. The model provides flux predictions in the energy range ~1 eV to ~40 keV, as a function of local time, energy, and the strength of the solar wind electric field (the negative product of the solar wind speed and the z component of the magnetic field). Given appropriate upstream solar wind measurements, the model provides a forecast of the fluxes at GEO with a ~1 h lead time. Model predictionsmore » are tested against in-sample observations from LANL satellites and also against out-of-sample observations from the Compact Environmental Anomaly Sensor II detector on the AMC-12 satellite. The model does not reproduce all structure seen in the observations. However, for the intervals studied here (quiet and storm times) the normalized root-mean-square deviation < ~0.3. It is intended that the model will improve forecasting of the spacecraft environment at GEO and also provide improved boundary/input conditions for physical models of the magnetosphere.« less

Integrating Solar PV in Utility System Operations: Analytical Framework and Arizona Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Jing; Botterud, Audun; Mills, Andrew

2015-06-01

A systematic framework is proposed to estimate the impact on operating costs due to uncertainty and variability in renewable resources. The framework quantifies the integration costs associated with subhourly variability and uncertainty as well as day-ahead forecasting errors in solar PV (photovoltaics) power. A case study illustrates how changes in system operations may affect these costs for a utility in the southwestern United States (Arizona Public Service Company). We conduct an extensive sensitivity analysis under different assumptions about balancing reserves, system flexibility, fuel prices, and forecasting errors. We find that high solar PV penetrations may lead to operational challenges, particularlymore » during low-load and high solar periods. Increased system flexibility is essential for minimizing integration costs and maintaining reliability. In a set of sensitivity cases where such flexibility is provided, in part, by flexible operations of nuclear power plants, the estimated integration costs vary between $1.0 and $4.4/MWh-PV for a PV penetration level of 17%. The integration costs are primarily due to higher needs for hour-ahead balancing reserves to address the increased sub-hourly variability and uncertainty in the PV resource. (C) 2015 Elsevier Ltd. All rights reserved.« less

The DSCOVR Solar Wind Mission and Future Space Weather Products

NASA Astrophysics Data System (ADS)

Cash, M. D.; Biesecker, D. A.; Reinard, A. A.

2012-12-01

The Deep Space Climate Observatory (DSCOVR) mission, scheduled for launch in mid-2014, will provide real-time solar wind thermal plasma and magnetic measurements to ensure continuous monitoring for space weather forecasting. DSCOVR will orbit L1 and will serve as a follow-on mission to NASA's Advanced Composition Explorer (ACE), which was launched in 1997. DSCOVR will have a total of six instruments, two of which will provide real-time data necessary for space weather forecasting: a Faraday cup to measure the proton and alpha components of the solar wind, and a triaxial fluxgate magnetometer to measure the magnetic field in three dimensions. Real-time data provided by DSCOVR will include Vx, Vy, Vz, n, T, Bx, By, and Bz. Such real-time L1 data is used in generating space weather applications and products that have been demonstrated to be highly accurate and provide actionable information for customers. We evaluate current space weather products driven by ACE and discuss future products under development for DSCOVR. New space weather products under consideration include: automated shock detection, more accurate L1 to Earth delay time, and prediction of rotations in solar wind Bz within magnetic clouds. Suggestions from the community on product ideas are welcome.

Time Variations in Forecasts and Occurrences of Large Solar Energetic Particle Events

NASA Astrophysics Data System (ADS)

Kahler, S. W.

2015-12-01

The onsets and development of large solar energetic (E > 10 MeV) particle (SEP) events have been characterized in many studies. The statistics of SEP event onset delay times from associated solar flares and coronal mass ejections (CMEs), which depend on solar source longitudes, can be used to provide better predictions of whether a SEP event will occur following a large flare or fast CME. In addition, size distributions of peak SEP event intensities provide a means for a probabilistic forecast of peak intensities attained in observed SEP increases. SEP event peak intensities have been compared with their rise and decay times for insight into the acceleration and transport processes. These two time scales are generally treated as independent parameters describing the development of a SEP event, but we can invoke an alternative two-parameter description based on the assumption that decay times exceed rise times for all events. These two parameters, from the well known Weibull distribution, provide an event description in terms of its basic shape and duration. We apply this distribution to several large SEP events and ask what the characteristic parameters and their dependence on source longitudes can tell us about the origins of these important events.

A new framework to increase the efficiency of large-scale solar power plants.

NASA Astrophysics Data System (ADS)

Alimohammadi, Shahrouz; Kleissl, Jan P.

2015-11-01

A new framework to estimate the spatio-temporal behavior of solar power is introduced, which predicts the statistical behavior of power output at utility scale Photo-Voltaic (PV) power plants. The framework is based on spatio-temporal Gaussian Processes Regression (Kriging) models, which incorporates satellite data with the UCSD version of the Weather and Research Forecasting model. This framework is designed to improve the efficiency of the large-scale solar power plants. The results are also validated from measurements of the local pyranometer sensors, and some improvements in different scenarios are observed. Solar energy.

ROSA deploy

NASA Image and Video Library

2017-06-18

iss052e002857 (6/18/2017) --- The Roll-Out Solar Array (ROSA) is a new type of solar panel that rolls open in space like a party favor and is more compact than current rigid panel designs. The ROSA investigation tests deployment and retraction, shape changes when the Earth blocks the sun, and other physical challenges to determine the array’s strength and durability. ROSA has the potential to replace solar arrays on future satellites, making them more compact and lighter weight. Satellite radio and television, weather forecasting, GPS and other services used on Earth would all benefit from high-performance solar arrays.

ROSA deploy

NASA Image and Video Library

2017-06-18

iss052e004379 (6/18/2017) --- The Roll-Out Solar Array (ROSA) is a new type of solar panel that rolls open in space like a party favor and is more compact than current rigid panel designs. The ROSA investigation tests deployment and retraction, shape changes when the Earth blocks the sun, and other physical challenges to determine the array’s strength and durability. ROSA has the potential to replace solar arrays on future satellites, making them more compact and lighter weight. Satellite radio and television, weather forecasting, GPS and other services used on Earth would all benefit from high-performance solar arrays.

ROSA deploy

NASA Image and Video Library

2017-06-18

iss052e002871 (6/18/2017) --- The Roll-Out Solar Array (ROSA) is a new type of solar panel that rolls open in space like a party favor and is more compact than current rigid panel designs. The ROSA investigation tests deployment and retraction, shape changes when the Earth blocks the sun, and other physical challenges to determine the array’s strength and durability. ROSA has the potential to replace solar arrays on future satellites, making them more compact and lighter weight. Satellite radio and television, weather forecasting, GPS and other services used on Earth would all benefit from high-performance solar arrays.

Origin of the Wang-Sheeley-Arge solar wind model

NASA Astrophysics Data System (ADS)

Sheeley, Neil R., Jr.

2017-03-01

A correlation between solar wind speed at Earth and the amount of magnetic field line expansion in the corona was verified in 1989 using 22 years of solar and interplanetary observations. We trace the evolution of this relationship from its birth 15 years earlier in the Skylab era to its current use as a space weather forecasting technique. This paper is the transcript of an invited talk at the joint session of the Historical Astronomy Division and the Solar Physics Division of the American Astronomical Society during its 224th meeting in Boston, MA, on 3 June 2014.

Identifying open magnetic field regions of the Sun and their heliospheric counterparts

NASA Astrophysics Data System (ADS)

Krista, L. D.; Reinard, A.

2017-12-01

Open magnetic regions on the Sun are either long-lived (coronal holes) or transient (dimmings) in nature. Both phenomena are fundamental to our understanding of the solar behavior as a whole. Coronal holes are the sources of high-speed solar wind streams that cause recurrent geomagnetic storms. Furthermore, the variation of coronal hole properties (area, location, magnetic field strength) over the solar activity cycle is an important marker of the global evolution of the solar magnetic field. Dimming regions, on the other hand, are short-lived coronal holes that often emerge in the wake of solar eruptions. By analyzing their physical properties and their temporal evolution, we aim to understand their connection with their eruptive counterparts (flares and coronal mass ejections) and predict the possibility of a geomagnetic storm. The author developed the Coronal Hole Automated Recognition and Monitoring (CHARM) and the Coronal Dimming Tracker (CoDiT) algorithms. These tools not only identify but track the evolution of open magnetic field regions. CHARM also provides daily coronal hole maps, that are used for forecasts at the NOAA Space Weather Prediction Center. Our goal is to better understand the processes that give rise to eruptive and non-eruptive open field regions and investigate how these regions evolve over time and influence space weather.

Solar Flare Prediction Science-to-Operations: the ESA/SSA SWE A-EFFort Service

NASA Astrophysics Data System (ADS)

Georgoulis, Manolis K.; Tziotziou, Konstantinos; Themelis, Konstantinos; Magiati, Margarita; Angelopoulou, Georgia

2016-07-01

We attempt a synoptical overview of the scientific origins of the Athens Effective Solar Flare Forecasting (A-EFFort) utility and the actions taken toward transitioning it into a pre-operational service of ESA's Space Situational Awareness (SSA) Programme. The preferred method for solar flare prediction, as well as key efforts to make it function in a fully automated environment by coupling calculations with near-realtime data-downloading protocols (from the Solar Dynamics Observatory [SDO] mission), pattern recognition (solar active-region identification) and optimization (magnetic connectivity by simulated annealing) will be highlighted. In addition, the entire validation process of the service will be described, with its results presented. We will conclude by stressing the need for across-the-board efforts and synergistic work in order to bring science of potentially limited/restricted interest into realizing a much broader impact and serving the best public interests. The above presentation was partially supported by the ESA/SSA SWE A-EFFort project, ESA Contract No. 4000111994/14/D/MRP. Special thanks go to the ESA Project Officers R. Keil, A. Glover, and J.-P. Luntama (ESOC), M. Bobra and C. Balmer of the SDO/HMI team at Stanford University, and M. Zoulias at the RCAAM of the Academy of Athens for valuable technical help.

The RMI Space Weather and Navigation Systems (SWANS) Project

NASA Astrophysics Data System (ADS)

Warnant, Rene; Lejeune, Sandrine; Wautelet, Gilles; Spits, Justine; Stegen, Koen; Stankov, Stan

The SWANS (Space Weather and Navigation Systems) research and development project (http://swans.meteo.be) is an initiative of the Royal Meteorological Institute (RMI) under the auspices of the Belgian Solar-Terrestrial Centre of Excellence (STCE). The RMI SWANS objectives are: research on space weather and its effects on GNSS applications; permanent mon-itoring of the local/regional geomagnetic and ionospheric activity; and development/operation of relevant nowcast, forecast, and alert services to help professional GNSS/GALILEO users in mitigating space weather effects. Several SWANS developments have already been implemented and available for use. The K-LOGIC (Local Operational Geomagnetic Index K Calculation) system is a nowcast system based on a fully automated computer procedure for real-time digital magnetogram data acquisition, data screening, and calculating the local geomagnetic K index. Simultaneously, the planetary Kp index is estimated from solar wind measurements, thus adding to the service reliability and providing forecast capabilities as well. A novel hybrid empirical model, based on these ground-and space-based observations, has been implemented for nowcasting and forecasting the geomagnetic index, issuing also alerts whenever storm-level activity is indicated. A very important feature of the nowcast/forecast system is the strict control on the data input and processing, allowing for an immediate assessment of the output quality. The purpose of the LIEDR (Local Ionospheric Electron Density Reconstruction) system is to acquire and process data from simultaneous ground-based GNSS TEC and digital ionosonde measurements, and subsequently to deduce the vertical electron density distribution. A key module is the real-time estimation of the ionospheric slab thickness, offering additional infor-mation on the local ionospheric dynamics. The RTK (Real Time Kinematic) status mapping provides a quick look at the small-scale ionospheric effects on the RTK precision for several GPS stations in Belgium. The service assesses the effect of small-scale ionospheric irregularities by monitoring the high-frequency TEC rate of change at any given station. This assessment results in a (colour) code assigned to each station, code ranging from "quiet" (green) to "extreme" (red) and referring to the local ionospheric conditions. Alerts via e-mail are sent to subscribed users when disturbed conditions are observed. SoDIPE (Software for Determining the Ionospheric Positioning Error) estimates the position-ing error due to the ionospheric conditions only (called "ionospheric error") in high-precision positioning applications (RTK in particular). For each of the Belgian Active Geodetic Network (AGN) baselines, SoDIPE computes the ionospheric error and its median value (every 15 min-utes). Again, a (colour) code is assigned to each baseline, ranging from "nominal" (green) to "extreme" (red) error level. Finally, all available baselines (drawn in colour corresponding to error level) are displayed on a map of Belgium. The future SWANS work will focus on regional ionospheric monitoring and developing various other nowcast and forecast services.

Automatic prediction of solar flares and super geomagnetic storms

NASA Astrophysics Data System (ADS)

Song, Hui

Space weather is the response of our space environment to the constantly changing Sun. As the new technology advances, mankind has become more and more dependent on space system, satellite-based services. A geomagnetic storm, a disturbance in Earth's magnetosphere, may produce many harmful effects on Earth. Solar flares and Coronal Mass Ejections (CMEs) are believed to be the major causes of geomagnetic storms. Thus, establishing a real time forecasting method for them is very important in space weather study. The topics covered in this dissertation are: the relationship between magnetic gradient and magnetic shear of solar active regions; the relationship between solar flare index and magnetic features of solar active regions; based on these relationships a statistical ordinal logistic regression model is developed to predict the probability of solar flare occurrences in the next 24 hours; and finally the relationship between magnetic structures of CME source regions and geomagnetic storms, in particular, the super storms when the D st index decreases below -200 nT is studied and proved to be able to predict those super storms. The results are briefly summarized as follows: (1) There is a significant correlation between magnetic gradient and magnetic shear of active region. Furthermore, compared with magnetic shear, magnetic gradient might be a better proxy to locate where a large flare occurs. It appears to be more accurate in identification of sources of X-class flares than M-class flares; (2) Flare index, defined by weighting the SXR flares, is proved to have positive correlation with three magnetic features of active region; (3) A statistical ordinal logistic regression model is proposed for solar flare prediction. The results are much better than those data published in the NASA/SDAC service, and comparable to the data provided by the NOAA/SEC complicated expert system. To our knowledge, this is the first time that logistic regression model has been applied in solar physics to predict flare occurrences; (4) The magnetic orientation angle [straight theta], determined from a potential field model, is proved to be able to predict the probability of super geomagnetic storms (D= st <=-200nT). The results show that those active regions associated with | [straight theta]| < 90° are more likely to cause a super geomagnetic storm.

NREL Integrate: RCS-4-42326

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hudgins, Andrew P.; Waight, Jim; Grover, Shailendra

OMNETRIC Corp., Duke Energy, CPS Energy, and the University of Texas at San Antonio (UTSA) created a project team to execute the project 'OpenFMB Reference Architecture Demonstration.' The project included development and demonstration of concepts that will enable the electric utility grid to host larger penetrations of renewable resources. The project concept calls for the aggregation of renewable resources and loads into microgrids and the control of these microgrids with an implementation of the OpenFMB Reference Architecture. The production of power from the renewable resources that are appearing on the grid today is very closely linked to the weather. Themore » difficulty of forecasting the weather, which is well understood, leads to difficulty in forecasting the production of renewable resources. The current state of the art in forecasting the power production from renewables (solar PV and wind) are accuracies in the range of 12-25 percent NMAE. In contrast the demand for electricity aggregated to the system level, is easier to predict. The state of the art of demand forecasting done, 24 hours ahead, is about 2-3% MAPE. Forecasting the load to be supplied from conventional resources (demand minus generation from renewable resources) is thus very hard to forecast. This means that even a few hours before the time of consumption, there can be considerable uncertainty over what must be done to balance supply and demand. Adding to the problem of difficulty of forecasting, is the reality of the variability of the actual production of power from renewables. Due to the variability of wind speeds and solar insolation, the actual output of power from renewable resources can vary significantly over a short period of time. Gusts of winds result is variation of power output of wind turbines. The shadows of clouds moving over solar PV arrays result in the variation of power production of the array. This compounds the problem of balancing supply and demand in real time. Establishing a control system that can manage distribution systems with large penetrations of renewable resources is difficult due to two major issues: (1) the lack of standardization and interoperability between the vast array of equipment in operation and on the market, most of which use different and proprietary means of communication and (2) the magnitude of the network and the information it generates and consumes. The objective of this project is to provide the industry with a design concept and tools that will enable the electric power grid to overcome these barriers and support a larger penetration of clean energy from renewable resources.« less

SUVI Thematic Maps: A new tool for space weather forecasting

NASA Astrophysics Data System (ADS)

Hughes, J. M.; Seaton, D. B.; Darnel, J.

2017-12-01

The new Solar Ultraviolet Imager (SUVI) instruments aboard NOAA's GOES-R series satellites collect continuous, high-quality imagery of the Sun in six wavelengths. SUVI imagers produce at least one image every 10 seconds, or 8,640 images per day, considerably more data than observers can digest in real time. Over the projected 20-year lifetime of the four GOES-R series spacecraft, SUVI will provide critical imagery for space weather forecasters and produce an extensive but unwieldy archive. In order to condense the database into a dynamic and searchable form we have developed solar thematic maps, maps of the Sun with key features, such as coronal holes, flares, bright regions, quiet corona, and filaments, identified. Thematic maps will be used in NOAA's Space Weather Prediction Center to improve forecaster response time to solar events and generate several derivative products. Likewise, scientists use thematic maps to find observations of interest more easily. Using an expert-trained, naive Bayesian classifier to label each pixel, we create thematic maps in real-time. We created software to collect expert classifications of solar features based on SUVI images. Using this software, we compiled a database of expert classifications, from which we could characterize the distribution of pixels associated with each theme. Given new images, the classifier assigns each pixel the most appropriate label according to the trained distribution. Here we describe the software to collect expert training and the successes and limitations of the classifier. The algorithm excellently identifies coronal holes but fails to consistently detect filaments and prominences. We compare the Bayesian classifier to an artificial neural network, one of our attempts to overcome the aforementioned limitations. These results are very promising and encourage future research into an ensemble classification approach.

Operational specification and forecasting advances for Dst, LEO thermospheric densities, and aviation radiation dose and dose rate

NASA Astrophysics Data System (ADS)

Tobiska, W. Kent

Space weather’s effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun’s photons, particles, and fields. Of the space environment domains that are affected by space weather, the magnetosphere, thermosphere, and even troposphere are key regions that are affected. Space Environment Technologies (SET) has developed and is producing innovative space weather applications. Key operational systems for providing timely information about the effects of space weather on these domains are SET’s Magnetosphere Alert and Prediction System (MAPS), LEO Alert and Prediction System (LAPS), and Automated Radiation Measurements for Aviation Safety (ARMAS) system. MAPS provides a forecast Dst index out to 6 days through the data-driven, redundant data stream Anemomilos algorithm. Anemomilos uses observational proxies for the magnitude, location, and velocity of solar ejecta events. This forecast index is used by satellite operations to characterize upcoming geomagnetic storms, for example. In addition, an ENLIL/Rice Dst prediction out to several days has also been developed and will be described. LAPS is the SET fully redundant operational system providing recent history, current epoch, and forecast solar and geomagnetic indices for use in operational versions of the JB2008 thermospheric density model. The thermospheric densities produced by that system, driven by the LAPS data, are forecast to 72-hours to provide the global mass densities for satellite operators. ARMAS is a project that has successfully demonstrated the operation of a micro dosimeter on aircraft to capture the real-time radiation environment due to Galactic Cosmic Rays and Solar Energetic Particles. The dose and dose-rates are captured on aircraft, downlinked in real-time via the Iridium satellites, processed on the ground, incorporated into the most recent NAIRAS global radiation climatology data runs, and made available to end users via the web and smart phone apps. ARMAS provides the “weather” of the radiation environment to improve air-crew and passenger safety. Many of the data products from MAPS, LAPS, and ARMAS are available on the SpaceWx smartphone app for iPhone, iPad, iPod, and Android professional users and public space weather education. We describe recent forecasting advances for moving the space weather information from these automated systems into operational, derivative products for communications, aviation, and satellite operations uses.

Forecast the energetic electron flux on geosynchronous orbit with interplanetary parameters

NASA Astrophysics Data System (ADS)

Xue, B.; Ye, Z.

The high flux of energetic electron on geo-synchronous orbit can cause many kinds of malfunction of the satellite there, within which the bulk charging is the most significant that several broadcast satellite failures were confirmed to be due to this effect. The electron flux on geo-synchronous orbit varies in a large range even up to three orders accompanied the passage of interplanetary magnetic cloud and the following geomagnetic disturbances. Upon investigating electron flux, interplanetary solar wind data, and geomagnetic data as well, we found that: (1) The enhancement of energetic flux on the geo-synchronous orbit exhibits periodic recurrence of 27days. (2)Significant increase of electron flux relates to interplanetary index and characters of their distribution. (3)The electron flux also has relation to solar activity index. In our research work, artificial neural network was employed and constructed according to the job. The neural network, we call it full connecting network, was proved to be a sufficient tool to analyze the character of the evolving parameters, remember the omen of "electron storm", and establish the relationship between interplanetary parameters etc., and the fluence of high energetic electrons. The neural network was carefully constructed and trained to do the job mentioned above. Preliminary result showed that the accuracy forecast of electron flux 1 day ahead can reach 80%, and 70% for 2 days ahead.

Solar wind structure out of the ecliptic plane over solar cycles

NASA Astrophysics Data System (ADS)

Sokol, J. M.; Bzowski, M.; Tokumaru, M.

2017-12-01

Sun constantly emits a stream of plasma known as solar wind. Ground-based observations of the solar wind speed through the interplanetary scintillations (IPS) of radio flux from distant point sources and in-situ measurements by Ulysses mission revealed that the solar wind flow has different characteristics depending on the latitude. This latitudinal structure evolves with the cycle of solar activity. The knowledge on the evolution of solar wind structure is important for understanding the interaction between the interstellar medium surrounding the Sun and the solar wind, which is responsible for creation of the heliosphere. The solar wind structure must be taken into account in interpretation of most of the observations of heliospheric energetic neutral atoms, interstellar neutral atoms, pickup ions, and heliospheric backscatter glow. The information on the solar wind structure is not any longer available from direct measurements after the termination of Ulysses mission and the only source of the solar wind out of the ecliptic plane is the IPS observations. However, the solar wind structure obtained from this method contains inevitable gaps in the time- and heliolatitude coverage. Sokół et al 2015 used the solar wind speed data out of the ecliptic plane retrieved from the IPS observations performed by Institute for Space-Earth Environmental Research (Nagoya University, Japan) and developed a methodology to construct a model of evolution of solar wind speed and density from 1985 to 2013 that fills the data gaps. In this paper we will present a refined model of the solar wind speed and density structure as a function of heliographic latitude updated by the most recent data from IPS observations. And we will discuss methods of extrapolation of the solar wind structure out of the ecliptic plane for the past solar cycles, when the data were not available, as well as forecasting for few years upward.

Forecasting Propagation and Evolution of CMEs in an Operational Setting: What Has Been Learned

NASA Technical Reports Server (NTRS)

Zheng, Yihua; Macneice, Peter; Odstrcil, Dusan; Mays, M. L.; Rastaetter, Lutz; Pulkkinen, Antti; Taktakishvili, Aleksandre; Hesse, Michael; Kuznetsova, M. Masha; Lee, Hyesook;

Forecasting propagation and evolution of CMEs in an operational setting: What has been learned

NASA Astrophysics Data System (ADS)

Zheng, Yihua; Macneice, Peter; Odstrcil, Dusan; Mays, M. L.; Rastaetter, Lutz; Pulkkinen, Antti; Taktakishvili, Aleksandre; Hesse, Michael; Masha Kuznetsova, M.; Lee, Hyesook; Chulaki, Anna

2013-10-01

of the major types of solar eruption, coronal mass ejections (CMEs) not only impact space weather, but also can have significant societal consequences. CMEs cause intense geomagnetic storms and drive fast mode shocks that accelerate charged particles, potentially resulting in enhanced radiation levels both in ions and electrons. Human and technological assets in space can be endangered as a result. CMEs are also the major contributor to generating large amplitude Geomagnetically Induced Currents (GICs), which are a source of concern for power grid safety. Due to their space weather significance, forecasting the evolution and impacts of CMEs has become a much desired capability for space weather operations worldwide. Based on our operational experience at Space Weather Research Center at NASA Goddard Space Flight Center (http://swrc.gsfc.nasa.gov), we present here some of the insights gained about accurately predicting CME impacts, particularly in relation to space weather operations. These include: 1. The need to maximize information to get an accurate handle of three-dimensional (3-D) CME kinetic parameters and therefore improve CME forecast; 2. The potential use of CME simulation results for qualitative prediction of regions of space where solar energetic particles (SEPs) may be found; 3. The need to include all CMEs occurring within a 24 h period for a better representation of the CME interactions; 4. Various other important parameters in forecasting CME evolution in interplanetary space, with special emphasis on the CME propagation direction. It is noted that a future direction for our CME forecasting is to employ the ensemble modeling approach.

SHOCK CONNECTIVITY IN THE 2010 AUGUST AND 2012 JULY SOLAR ENERGETIC PARTICLE EVENTS INFERRED FROM OBSERVATIONS AND ENLIL MODELING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bain, H. M.; Luhmann, J. G.; Li, Y.

During periods of increased solar activity, coronal mass ejections (CMEs) can occur in close succession and proximity to one another. This can lead to the interaction and merger of CME ejecta as they propagate in the heliosphere. The particles accelerated in these shocks can result in complex solar energetic particle (SEP) events, as observing spacecraft form both remote and local shock connections. It can be challenging to understand these complex SEP events from in situ profiles alone. Multipoint observations of CMEs in the near-Sun environment, from the Solar Terrestrial Relations Observatory –Sun Earth Connection Coronal and Heliospheric Investigation and themore » Solar and Heliospheric Observatory Large Angle and Spectrometric Coronagraph, greatly improve our chances of identifying the origin of these accelerated particles. However, contextual information on conditions in the heliosphere, including the background solar wind conditions and shock structures, is essential for understanding SEP properties well enough to forecast their characteristics. Wang–Sheeley–Arge WSA-ENLIL + Cone modeling provides a tool to interpret major SEP event periods in the context of a realistic heliospheric model and to determine how much of what is observed in large SEP events depends on nonlocal magnetic connections to shock sources. We discuss observations of the SEP-rich periods of 2010 August and 2012 July in conjunction with ENLIL modeling. We find that much SEP activity can only be understood in the light of such models, and in particular from knowing about both remote and local shock source connections. These results must be folded into the investigations of the physics underlying the longitudinal extent of SEP events, and the source connection versus diffusion pictures of interpretations of SEP events.« less

Can We Predict CME Deflections Based on Solar Magnetic Field Configuration Alone?

NASA Astrophysics Data System (ADS)

Kay, C.; Opher, M.; Evans, R. M.

2013-12-01

Accurate space weather forecasting requires knowledge of the trajectory of coronal mass ejections (CMEs), including predicting CME deflections close to the Sun and through interplanetary space. Deflections of CMEs occur due to variations in the background magnetic field or solar wind speed, magnetic reconnection, and interactions with other CMEs. Using our newly developed model of CME deflections due to gradients in the background solar magnetic field, ForeCAT (Kay et al. 2013), we explore the questions: (a) do all simulated CMEs ultimately deflect to the minimum in the background solar magnetic field? (b) does the majority of the deflection occur in the lower corona below 4 Rs? ForeCAT does not include temporal variations in the magnetic field of active regions (ARs), spatial variations in the background solar wind speed, magnetic reconnection, or interactions with other CMEs. Therefore we focus on the effects of the steady state solar magnetic field. We explore two different Carrington Rotations (CRs): CR 2029 (April-May 2005) and CR 2077 (November-December 2008). Little is known about how the density and magnetic field fall with distance in the lower corona. We consider four density models derived from observations (Chen 1996, Mann et al. 2003, Guhathakurta et al. 2006, Leblanc et al. 1996) and two magnetic field models (PFSS and a scaled model). ForeCAT includes drag resulting from both CME propagation and deflection through the background solar wind. We vary the drag coefficient to explore the effect of drag on the deflection at 1 AU.

Integrated Modeling of the Battlespace Environment

DTIC Science & Technology

2010-10-01

Office of Counsel.Code 1008.3 ADOR/Director NCST E. R. Franchi , 7000 Public Affairs (Unclassified/ Unlimited Only). Code 7030 4 Division, Code...ESMF: the Hakamada- Akasofu-Fry version 2 (HAFv2) solar wind model and the global assimilation of ionospheric mea- surements (GAIM1) forecast...ground-truth measurements for comparison with the solar wind predictions. Global Assimilation of Ionospheric Measurements The GAIMv2.3 effort

Development and Transition of the Radiation, Interplanetary Shocks, and Coronal Sources (RISCS) Toolset

NASA Technical Reports Server (NTRS)

Spann, James F.; Zank, G.

2014-01-01

We outline a plan to develop and transition a physics based predictive toolset called The Radiation, Interplanetary Shocks, and Coronal Sources (RISCS) to describe the interplanetary energetic particle and radiation environment throughout the inner heliosphere, including at the Earth. To forecast and "nowcast" the radiation environment requires the fusing of three components: 1) the ability to provide probabilities for incipient solar activity; 2) the use of these probabilities and daily coronal and solar wind observations to model the 3D spatial and temporal heliosphere, including magnetic field structure and transients, within 10 Astronomical Units; and 3) the ability to model the acceleration and transport of energetic particles based on current and anticipated coronal and heliospheric conditions. We describe how to address 1) - 3) based on our existing, well developed, and validated codes and models. The goal of RISCS toolset is to provide an operational forecast and "nowcast" capability that will a) predict solar energetic particle (SEP) intensities; b) spectra for protons and heavy ions; c) predict maximum energies and their duration; d) SEP composition; e) cosmic ray intensities, and f) plasma parameters, including shock arrival times, strength and obliquity at any given heliospheric location and time. The toolset would have a 72 hour predicative capability, with associated probabilistic bounds, that would be updated hourly thereafter to improve the predicted event(s) and reduce the associated probability bounds. The RISCS toolset would be highly adaptable and portable, capable of running on a variety of platforms to accommodate various operational needs and requirements. The described transition plan is based on a well established approach developed in the Earth Science discipline that ensures that the customer has a tool that meets their needs

Forward Modeling of Coronal Mass Ejection Flux Ropes in the Inner Heliosphere with 3DCORE

PubMed Central

Amerstorfer, T.; Palmerio, E.; Isavnin, A.; Farrugia, C. J.; Lowder, C.; Winslow, R. M.; Donnerer, J. M.; Kilpua, E. K. J.; Boakes, P. D.

2018-01-01

Abstract Forecasting the geomagnetic effects of solar storms, known as coronal mass ejections (CMEs), is currently severely limited by our inability to predict the magnetic field configuration in the CME magnetic core and by observational effects of a single spacecraft trajectory through its 3‐D structure. CME magnetic flux ropes can lead to continuous forcing of the energy input to the Earth's magnetosphere by strong and steady southward‐pointing magnetic fields. Here we demonstrate in a proof‐of‐concept way a new approach to predict the southward field B z in a CME flux rope. It combines a novel semiempirical model of CME flux rope magnetic fields (Three‐Dimensional Coronal ROpe Ejection) with solar observations and in situ magnetic field data from along the Sun‐Earth line. These are provided here by the MESSENGER spacecraft for a CME event on 9–13 July 2013. Three‐Dimensional Coronal ROpe Ejection is the first such model that contains the interplanetary propagation and evolution of a 3‐D flux rope magnetic field, the observation by a synthetic spacecraft, and the prediction of an index of geomagnetic activity. A counterclockwise rotation of the left‐handed erupting CME flux rope in the corona of 30° and a deflection angle of 20° is evident from comparison of solar and coronal observations. The calculated Dst matches reasonably the observed Dst minimum and its time evolution, but the results are highly sensitive to the CME axis orientation. We discuss assumptions and limitations of the method prototype and its potential for real time space weather forecasting and heliospheric data interpretation. PMID:29780287

GOLD Mission Launches to Study Near-Space Environment

NASA Image and Video Library

2018-01-25

On Jan. 25, NASA’s Global-scale Observations of the Limb and Disk, or GOLD mission, launched from French Guiana. GOLD is an instrument launching on a commercial satellite to inspect, from geostationary orbit, the dynamic intermingling of space and Earth’s uppermost atmosphere. GOLD will seek to understand what drives change in this region where terrestrial weather in the lower atmosphere interacts with the tumult of solar activity from above and Earth’s magnetic field. Resulting data will improve forecasting models of space weather events that can impact life on Earth, as well as satellites and astronauts in space.

Quasi-static time-series simulation using OpenDSS in IEEE distribution feeder model with high PV penetration and its impact on solar forecasting

NASA Astrophysics Data System (ADS)

Mohammed, Touseef Ahmed Faisal

Since 2000, renewable electricity installations in the United States (excluding hydropower) have more than tripled. Renewable electricity has grown at a compounded annual average of nearly 14% per year from 2000-2010. Wind, Concentrated Solar Power (CSP) and solar Photo Voltaic (PV) are the fastest growing renewable energy sectors. In 2010 in the U.S., solar PV grew over 71% and CSP grew by 18% from the previous year. Globally renewable electricity installations have more than quadrupled from 2000-2010. Solar PV generation grew by a factor of more than 28 between 2000 and 2010. The amount of CSP and solar PV installations are increasing on the distribution grid. These PV installations transmit electrical current from the load centers to the generating stations. But the transmission and distribution grid have been designed for uni-directional flow of electrical energy from generating stations to load centers. This causes imbalances in voltage and switchgear of the electrical circuitry. With the continuous rise in PV installations, analysis of voltage profile and penetration levels remain an active area of research. Standard distributed photovoltaic (PV) generators represented in simulation studies do not reflect the exact location and variability properties such as distance between interconnection points to substations, voltage regulators, solar irradiance and other environmental factors. Quasi-Static simulations assist in peak load planning hour and day ahead as it gives a time sequence analysis to help in generation allocation. Simulation models can be daily, hourly or yearly depending on duty cycle and dynamics of the system. High penetration of PV into the power grid changes the voltage profile and power flow dynamically in the distribution circuits due to the inherent variability of PV. There are a number of modeling and simulations tools available for the study of such high penetration PV scenarios. This thesis will specifically utilize OpenDSS, a open source Distribution System Simulator developed by Electric Power Research Institute, to simulate grid voltage profile with a large scale PV system under quasi-static time series considering variations of PV output in seconds, minutes, and the average daily load variations. A 13 bus IEEE distribution feeder model is utilized with distributed residential and commercial scale PV at different buses for simulation studies. Time series simulations are discussed for various modes of operation considering dynamic PV penetration at different time periods in a day. In addition, this thesis demonstrates simulations taking into account the presence of moving cloud for solar forecasting studies.

Building a new space weather facility at the National Observatory of Athens

NASA Astrophysics Data System (ADS)

Kontogiannis, Ioannis; Belehaki, Anna; Tsiropoula, Georgia; Tsagouri, Ioanna; Anastasiadis, Anastasios; Papaioannou, Athanasios

2016-01-01

The PROTEAS project has been initiated at the Institute of Astronomy, Astrophysics, Space Applications and Remote Sensing (IAASARS) of the National Observatory of Athens (NOA). One of its main objectives is to provide observations, processed data and space weather nowcasting and forecasting products, designed to support the space weather research community and operators of commercial and industrial systems. The space weather products to be released by this facility, will be the result of the exploitation of ground-based, as well as space-borne observations and of model results and tools already available or under development by IAASARS researchers. The objective will be achieved through: (a) the operation of a small full-disk solar telescope to conduct regular observations of the Sun in the H-alpha line; (b) the construction of a database with near real-time solar observations which will be available to the community through a web-based facility (HELIOSERVER); (c) the development of a tool for forecasting Solar Energetic Particle (SEP) events in relation to observed solar eruptive events; (d) the upgrade of the Athens Digisonde with digital transceivers and the capability of operating in bi-static link mode and (e) the sustainable operation of the European Digital Upper Atmosphere Server (DIAS) upgraded with additional data sets integrated in an interface with the HELIOSERVER and with improved models for the real-time quantification of the effects of solar eruptive events in the ionosphere.

The GONG Farside Project

NASA Astrophysics Data System (ADS)

Leibacher, J. W.; Braun, D.; González Hernández, I.; Goodrich, J.; Kholikov, S.; Lindsey, C.; Malanushenko, A.; Scherrer, P.

2005-05-01

The GONG program is currently providing near-real-time helioseismic images of the farside of the Sun. The continuous stream of low resolution images, obtained from the 6 earth based GONG stations, are merged into a single data series that are the input to the farside pipeline. In order to validate the farside images, it is crucial to compare the results obtained from different instruments. We show comparisons between the farside images provided by the MDI instrument and the GONG ones. New aditions to the pipeline will allow us to create full-hemisphere farside images, examples of the latest are shown in this poster. Our efforts are now concentrated in calibrating the farside signal so it became a reliable solar activity forecasting tool. We are also testing single-skip acoustic power holography at 5-7 mHz as a prospective means of reinforcing the signatures of active regions crossing the the east and west limb and monitoring acoustic emission in the neighborhoods of Sun's the poles. This work utilizes data obtained by the Global Oscillation Network Group (GONG) Program, managed by the National Solar Observatory, which is operated by AURA, Inc. under a cooperative agreement with the National Science Foundation. The data were acquired by instruments operated by the Big Bear Solar Observatory, High Altitude Observatory, Learmonth Solar Observatory, Udaipur Solar Observatory, Instituto de Astrofisico de Canarias, and Cerro Tololo Interamerican Observatory, as well as the Michaelson Doppler Imager on SoHO, a mission of international cooperation between ESA and NASA. This work has been supported by the NASA Living with a Star - Targeted Research and Technology program.

7 CFR 612.2 - Snow survey and water supply forecast activities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 6 2010-01-01 2010-01-01 false Snow survey and water supply forecast activities. 612... SUPPLY FORECASTS § 612.2 Snow survey and water supply forecast activities. To carry out the cooperative snow survey and water supply forecast program, NRCS: (a) Establishes, maintains, and operates manual...

7 CFR 612.2 - Snow survey and water supply forecast activities.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 6 2014-01-01 2014-01-01 false Snow survey and water supply forecast activities. 612... SUPPLY FORECASTS § 612.2 Snow survey and water supply forecast activities. To carry out the cooperative snow survey and water supply forecast program, NRCS: (a) Establishes, maintains, and operates manual...

7 CFR 612.2 - Snow survey and water supply forecast activities.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 6 2013-01-01 2013-01-01 false Snow survey and water supply forecast activities. 612... SUPPLY FORECASTS § 612.2 Snow survey and water supply forecast activities. To carry out the cooperative snow survey and water supply forecast program, NRCS: (a) Establishes, maintains, and operates manual...

7 CFR 612.2 - Snow survey and water supply forecast activities.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 6 2011-01-01 2011-01-01 false Snow survey and water supply forecast activities. 612... SUPPLY FORECASTS § 612.2 Snow survey and water supply forecast activities. To carry out the cooperative snow survey and water supply forecast program, NRCS: (a) Establishes, maintains, and operates manual...

7 CFR 612.2 - Snow survey and water supply forecast activities.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 6 2012-01-01 2012-01-01 false Snow survey and water supply forecast activities. 612... SUPPLY FORECASTS § 612.2 Snow survey and water supply forecast activities. To carry out the cooperative snow survey and water supply forecast program, NRCS: (a) Establishes, maintains, and operates manual...

Multi-wavelength and High-resolution Observations of Solar Eruptive Activities

NASA Astrophysics Data System (ADS)

Shen, Y. D.

2014-09-01

In recent years, various solar eruptive activities have been observed in the solar atmosphere, such as solar flares, filament eruptions, jets, coronal mass ejections (CMEs), and magnetohydrodynamics (MHD) waves. Previous observations have indicated that solar magnetic field plays a dominant role in the processes of all kinds of solar activities. Since many large-scale solar eruptive activities can cause significant effects on the space environment of the Earth as well as the human life, studying and forecasting the solar activities are urgent tasks for us. In addition, the Sun is the nearest star to the Earth, so that people can directly observe and study it in detail. Hence, studying the Sun can also provide a reference to study other stars in the universe. This thesis focuses on the multi-wavelength and high-resolution observations of three types of solar eruptive activities: filament eruptions, coronal jets, and coronal MHD waves. By analyzing various observations taken by ground-based and space-borne instruments, we try to understand the inherent physical mechanisms, and construct models to interpret different kinds of solar eruptive activities. The triggering mechanism and the cause of a failed filament eruption are studied in Chapter 3, which indicates that the energy released in the flare is a key factor to the fate of the filament. Two successive filament eruptions are studied in Chapter 4, which indicates that the magnetic implosion could be the physical linkage between them, and the structures of coronal magnetic fields are important for producing sympathetic eruptions. A magnetic unwinding jet and a blowout jet are studied in Chapters 5 and 6, respectively. The former exhibits obvious radial expansion, which undergoes three distinct phases: the slow expansion phase, the fast expansion phase, and the steady phase. In addition, calculation indicates that the non-potential magnetic field in the jet can supply sufficient energy for producing the unwinding jet. The latter is associated with a simultaneous bubble-like and a jet-like CME. It is found that the jet-like CME is driven by the reconnection between the closed field and the ambient open field, while the bubble-like CME is associated with the mini-filament confined by the closed field. In Chapter 7, a quasi-periodic fast propagating (QFP) magnetosonic wave and the associated flare are studied. It is found that the wave and the flare have the same periods, suggesting their common origin. In addition, the leakage of photospheric p-mode oscillation to the corona is also an important source of QFP waves. Large-scale coronal waves are studied in Chapters 8 and 9. It is found that coronal waves can be observed in the low solar atmosphere like the top of the photosphere. Based on the analysis, we propose that large-scale coronal waves are fast magnetosonic or shock waves, which are driven by the expanding flanks of the associated CMEs. A short summary and unsolved problems are given in Chapter 10. Along with the fast development of many new solar telescopes, high quality observations will certainly help us to reveal the true physics behind various solar eruptive activities.

A Study of the Solar Wind-Magnetosphere Coupling Using Neural Networks

NASA Astrophysics Data System (ADS)

Wu, Jian-Guo; Lundstedt, Henrik

1996-12-01

The interaction between solar wind plasma and interplanetary magnetic field (IMF) and Earth's magnetosphere induces geomagnetic activity. Geomagnetic storms can cause many adverse effects on technical systems in space and on the Earth. It is therefore of great significance to accurately predict geomagnetic activity so as to minimize the amount of disruption to these operational systems and to allow them to work as efficiently as possible. Dynamic neural networks are powerful in modeling the dynamics encoded in time series of data. In this study, we use partially recurrent neural networks to study the solar wind-magnetosphere coupling by predicting geomagnetic storms (as measured by the Dstindex) from solar wind measurements. The solar wind, the IMF and the geomagnetic index Dst data are hourly averaged and read from the National Space Science Data Center's OMNI database. We selected these data from the period 1963 to 1992, which cover 10552h and contain storm time periods 9552h and quiet time periods 1000h. The data are then categorized into three data sets: a training set (6634h), across-validation set (1962h), and a test set (1956h). The validation set is used to determine where the training should be stopped whereas the test set is used for neural networks to get the generalization capability (the out-of-sample performance). Based on the correlation analysis between the Dst index and various solar wind parameters (including various combinations of solar wind parameters), the best coupling functions can be found from the out-of-sample performance of trained neural networks. The coupling functions found are then used to forecast geomagnetic storms one to several hours in advance. The comparisons are made on iterating the single-step prediction several times and on making a non iterated, direct prediction. Thus, we will present the best solar wind-magnetosphere coupling functions and the corresponding prediction results. Interesting Links: Lund Space Weather and AI Center

Space Environment Modelling with the Use of Artificial Intelligence Methods

NASA Astrophysics Data System (ADS)

Lundstedt, H.; Wintoft, P.; Wu, J.-G.; Gleisner, H.; Dovheden, V.

1996-12-01

Space based technological systems are affected by the space weather in many ways. Several severe failures of satellites have been reported at times of space storms. Our society also increasingly depends on satellites for communication, navigation, exploration, and research. Predictions of the conditions in the satellite environment have therefore become very important. We will here present predictions made with the use of artificial intelligence (AI) techniques, such as artificial neural networks (ANN) and hybrids of AT methods. We are developing a space weather model based on intelligence hybrid systems (IHS). The model consists of different forecast modules, each module predicts the space weather on a specific time-scale. The time-scales range from minutes to months with the fundamental time-scale of 1-5 minutes, 1-3 hours, 1-3 days, and 27 days. Solar and solar wind data are used as input data. From solar magnetic field measurements, either made on the ground at Wilcox Solar Observatory (WSO) at Stanford, or made from space by the satellite SOHO, solar wind parameters can be predicted and modelled with ANN and MHD models. Magnetograms from WSO are available on a daily basis. However, from SOHO magnetograms will be available every 90 minutes. SOHO magnetograms as input to ANNs will therefore make it possible to even predict solar transient events. Geomagnetic storm activity can today be predicted with very high accuracy by means of ANN methods using solar wind input data. However, at present real-time solar wind data are only available during part of the day from the satellite WIND. With the launch of ACE in 1997, solar wind data will on the other hand be available during 24 hours per day. The conditions of the satellite environment are not only disturbed at times of geomagnetic storms but also at times of intense solar radiation and highly energetic particles. These events are associated with increased solar activity. Predictions of these events are therefore also handled with the modules in the Lund Space Weather Model. Interesting Links: Lund Space Weather and AI Center

Chaos in the sunspot cycle - Analysis and prediction

NASA Technical Reports Server (NTRS)

Mundt, Michael D.; Maguire, W. Bruce, II; Chase, Robert R. P.

1991-01-01

The variability of solar activity over long time scales, given semiquantitatively by measurements of sunspot numbers, is examined as a nonlinear dynamical system. First, a discussion of the data set used and the techniques utilized to reduce the noise and capture the long-term dynamics inherent in the data is presented. Subsequently, an attractor is reconstructed from the data set using the method of time delays. The reconstructed attractor is then used to determine both the dimension of the underlying system and also the largest Lyapunov exponent, which together indicate that the sunspot cycle is indeed chaotic and also low dimensional. In addition, recent techniques of exploiting chaotic dynamics to provide accurate, short-term predictions are utilized in order to improve upon current forecasting methods and also to place theoretical limits on predictability extent. The results are compared to chaotic solar-dynamo models as a possible physically motivated source of this chaotic behavior.

3D electron density distributions in the solar corona during solar minima: assessment for more realistic solar wind modeling

NASA Astrophysics Data System (ADS)

de Patoul, J.; Foullon, C.; Riley, P.

2015-12-01

Knowledge of the electron density distribution in the solar corona put constraints on the magnetic field configurations for coronal modeling, and on initial conditions for solar wind modeling. We work with polarized SOHO/LASCO-C2 images from the last two recent minima of solar activity (1996-1997 and 2008-2010), devoid of coronal mass ejections. We derive the 4D electron density distributions in the corona by applying a newly developed time-dependent tomographic reconstruction method. First we compare the density distributions obtained from tomography with magnetohydrodynamic (MHD) solutions. The tomography provides more accurate distributions of electron densities in the polar regions, and we find that the observed density varies with the solar cycle in both polar and equatorial regions. Second, we find that the highest-density structures do not always correspond to the predicted large-scale heliospheric current sheet or its helmet streamer but can follow the locations of pseudo-streamers. We conclude that tomography offers reliable density distribution in the corona, reproducing the slow time evolution of coronal structures, without prior knowledge of the coronal magnetic field over a full rotation. Finally, we suggest that the highest-density structures show a differential rotation well above the surface depending on how it is magnetically connected to the surface. Such valuable information on the rotation of large-scale structures could help to connect the sources of the solar wind to their in-situ counterparts in future missions such as Solar Orbiter and Solar Probe Plus. This research combined with the MHD coronal modeling efforts has the potential to increase the reliability for future space weather forecasting.

Operational Dust Prediction

NASA Technical Reports Server (NTRS)

Benedetti, Angela; Baldasano, Jose M.; Basart, Sara; Benincasa, Francesco; Boucher, Olivier; Brooks, Malcolm E.; Chen, Jen-Ping; Colarco, Peter R.; Gong, Sunlin; Huneeus, Nicolas;

Predicting the magnetic vectors within coronal mass ejections arriving at Earth: 1. Initial architecture

NASA Astrophysics Data System (ADS)

Savani, N. P.; Vourlidas, A.; Szabo, A.; Mays, M. L.; Richardson, I. G.; Thompson, B. J.; Pulkkinen, A.; Evans, R.; Nieves-Chinchilla, T.

2015-06-01

The process by which the Sun affects the terrestrial environment on short timescales is predominately driven by the amount of magnetic reconnection between the solar wind and Earth's magnetosphere. Reconnection occurs most efficiently when the solar wind magnetic field has a southward component. The most severe impacts are during the arrival of a coronal mass ejection (CME) when the magnetosphere is both compressed and magnetically connected to the heliospheric environment. Unfortunately, forecasting magnetic vectors within coronal mass ejections remain elusive. Here we report how, by combining a statistically robust helicity rule for a CME's solar origin with a simplified flux rope topology, the magnetic vectors within the Earth-directed segment of a CME can be predicted. In order to test the validity of this proof-of-concept architecture for estimating the magnetic vectors within CMEs, a total of eight CME events (between 2010 and 2014) have been investigated. With a focus on the large false alarm of January 2014, this work highlights the importance of including the early evolutionary effects of a CME for forecasting purposes. The angular rotation in the predicted magnetic field closely follows the broad rotational structure seen within the in situ data. This time-varying field estimate is implemented into a process to quantitatively predict a time-varying Kp index that is described in detail in paper II. Future statistical work, quantifying the uncertainties in this process, may improve the more heuristic approach used by early forecasting systems.

Operational, Real-Time, Sun-to-Earth Interplanetary Shock Predictions During Solar Cycle 23

NASA Astrophysics Data System (ADS)

Fry, C. D.; Dryer, M.; Sun, W.; Deehr, C. S.; Smith, Z.; Akasofu, S.

2002-05-01

We report on our progress in predicting interplanetary shock arrival time (SAT) in real-time, using three forecast models: the Hakamada-Akasofu-Fry (HAF) modified kinematic model, the Interplanetary Shock Propagation Model (ISPM) and the Shock Time of Arrival (STOA) model. These models are run concurrently to provide real-time predictions of the arrival time at Earth of interplanetary shocks caused by solar events. These "fearless forecasts" are the first, and presently only, publicly distributed predictions of SAT and are undergoing quantitative evaluation for operational utility and scientific benchmarking. All three models predict SAT, but the HAF model also provides a global view of the propagation of interplanetary shocks through the pre-existing, non-uniform heliospheric structure. This allows the forecaster to track the propagation of the shock and to differentiate between shocks caused by solar events and those associated with co-rotating interaction regions (CIRs). This study includes 173 events during the period February, 1997 to October, 2000. Shock predictions were compared with spacecraft observations at the L1 location to determine how well the models perform. Sixty-eight shocks were observed at L1 within 120 hours of an event. We concluded that 6 of these observed shocks were caused by CIRs, and the remainder were caused by solar events. The forecast skill of the models are presented in terms of RMS errors, contingency tables and skill scores commonly used by the weather forecasting community. The false alarm rate for HAF was higher than for ISPM or STOA but much lower than for predictions based upon empirical studies or climatology. Of the parameters used to characterize a shock source at the Sun, the initial speed of the coronal shock, as represented by the observed metric type II speed, has the largest influence on the predicted SAT. We also found that HAF model predictions based upon type II speed are generally better for shocks originating from sites near central meridian, and worse for limb events. This tendency suggests that the observed type II speed is more representative of the interplanetary shock speed for events occurring near central meridian. In particular, the type II speed appears to underestimate the actual Earth-directed IP shock speed when the source of the event is near the limb. Several of the most interesting events (Bastille Day epoch (2000), April Fools Day epoch (2001))will be discussed in more detail with the use of real-time animations.

Short-Term Load Forecasting Error Distributions and Implications for Renewable Integration Studies: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, B. M.; Lew, D.; Milligan, M.

2013-01-01

Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves necessary to compensate errors. In this work, we performed a statistical analysis of themore » day-ahead (and two-day-ahead) load forecasting errors observed in two independent system operators for a one-year period. Comparisons were made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identified time periods when the load is more likely to be under- or overforecast.« less

Nowcast and Short-Term Forecast of Solar Radiation for Photovoltaic power and Solar thermal using 3rd generation geostationary satellite.

NASA Astrophysics Data System (ADS)

Takenaka, H.; Teruyuki, N.; Nakajima, T. Y.; Higurashi, A.; Hashimoto, M.; Suzuki, K.; Uchida, J.; Nagao, T. M.; Shi, C.; Inoue, T.

2017-12-01

It is important to estimate the earth's radiation budget accurately for understanding of climate. Clouds can cool the Earth by reflecting solar radiation but also maintain warmth by absorbing and emitting terrestrial radiation. similarly aerosols also have an effect on radiation budget by absorption and scattering of Solar radiation. In this study, we developed the high speed and accurate algorithm for shortwave (SW) radiation budget and it's applied to geostationary satellite for rapid analysis. It enabled highly accurate monitoring of solar radiation and photo voltaic (PV) power generation. Next step, we try to update the algorithm for retrieval of Aerosols and Clouds. It indicates the accurate atmospheric parameters for estimation of solar radiation. (This research was supported in part by CREST/EMS).

Cloud and DNI nowcasting with MSG/SEVIRI for the optimized operation of concentrating solar power plants

NASA Astrophysics Data System (ADS)

Sirch, Tobias; Bugliaro, Luca; Zinner, Tobias; Möhrlein, Matthias; Vazquez-Navarro, Margarita

2017-02-01

A novel approach for the nowcasting of clouds and direct normal irradiance (DNI) based on the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG) satellite is presented for a forecast horizon up to 120 min. The basis of the algorithm is an optical flow method to derive cloud motion vectors for all cloudy pixels. To facilitate forecasts over a relevant time period, a classification of clouds into objects and a weighted triangular interpolation of clear-sky regions are used. Low and high level clouds are forecasted separately because they show different velocities and motion directions. Additionally a distinction in advective and convective clouds together with an intensity correction for quickly thinning convective clouds is integrated. The DNI is calculated from the forecasted optical thickness of the low and high level clouds. In order to quantitatively assess the performance of the algorithm, a forecast validation against MSG/SEVIRI observations is performed for a period of 2 months. Error rates and Hanssen-Kuiper skill scores are derived for forecasted cloud masks. For a forecast of 5 min for most cloud situations more than 95 % of all pixels are predicted correctly cloudy or clear. This number decreases to 80-95 % for a forecast of 2 h depending on cloud type and vertical cloud level. Hanssen-Kuiper skill scores for cloud mask go down to 0.6-0.7 for a 2 h forecast. Compared to persistence an improvement of forecast horizon by a factor of 2 is reached for all forecasts up to 2 h. A comparison of forecasted optical thickness distributions and DNI against observations yields correlation coefficients larger than 0.9 for 15 min forecasts and around 0.65 for 2 h forecasts.

Impacts of Severe Weather, Climate Zone, and Energy Factors on Base Realignment and Closure (BRAC)

DTIC Science & Technology

2015-03-26

hydroelectric, solar photovoltaic , and wind power . Aside from locations and facilities that use electricity to heat, natural gas is the only...have large photovoltaic solar arrays with unique buy-back contracts or power -purchase agreements. These renewable energy projects benefit primarily...these costs, a Monte Carlo simulation is used to forecast annual costs and account for uncertainty with tornado and hurricane risks, along with

Probabilistic Assessment of Cancer Risk for Astronauts on Lunar Missions

NASA Technical Reports Server (NTRS)

Kim, Myung-Hee Y.; Cucinotta, Francis A.

2009-01-01

During future lunar missions, exposure to solar particle events (SPEs) is a major safety concern for crew members during extra-vehicular activities (EVAs) on the lunar surface or Earth-to-moon transit. NASA s new lunar program anticipates that up to 15% of crew time may be on EVA, with minimal radiation shielding. For the operational challenge to respond to events of unknown size and duration, a probabilistic risk assessment approach is essential for mission planning and design. Using the historical database of proton measurements during the past 5 solar cycles, a typical hazard function for SPE occurrence was defined using a non-homogeneous Poisson model as a function of time within a non-specific future solar cycle of 4000 days duration. Distributions ranging from the 5th to 95th percentile of particle fluences for a specified mission period were simulated. Organ doses corresponding to particle fluences at the median and at the 95th percentile for a specified mission period were assessed using NASA s baryon transport model, BRYNTRN. The cancer fatality risk for astronauts as functions of age, gender, and solar cycle activity were then analyzed. The probability of exceeding the NASA 30- day limit of blood forming organ (BFO) dose inside a typical spacecraft was calculated. Future work will involve using this probabilistic risk assessment approach to SPE forecasting, combined with a probabilistic approach to the radiobiological factors that contribute to the uncertainties in projecting cancer risks.

The statistical analysis of energy release in small-scale coronal structures

NASA Astrophysics Data System (ADS)

Ulyanov, Artyom; Kuzin, Sergey; Bogachev, Sergey

We present the results of statistical analysis of impulsive flare-like brightenings, which numerously occur in the quiet regions of solar corona. For our study, we utilized high-cadence observations performed with two EUV-telescopes - TESIS/Coronas-Photon and AIA/SDO. In total, we processed 6 sequences of images, registered throughout the period between 2009 and 2013, covering the rising phase of the 24th solar cycle. Based on high-speed DEM estimation method, we developed a new technique to evaluate the main parameters of detected events (geometrical sizes, duration, temperature and thermal energy). We then obtained the statistical distributions of these parameters and examined their variations depending on the level of solar activity. The results imply that near the minimum of the solar cycle the energy release in quiet corona is mainly provided by small-scale events (nanoflares), whereas larger events (microflares) prevail on the peak of activity. Furthermore, we investigated the coronal conditions that had specified the formation and triggering of registered flares. By means of photospheric magnetograms obtained with MDI/SoHO and HMI/SDO instruments, we examined the topology of local magnetic fields at different stages: the pre-flare phase, the peak of intensity and the ending phase. To do so, we introduced a number of topological parameters including the total magnetic flux, the distance between magnetic sources and their mutual arrangement. The found correlation between the change of these parameters and the formation of flares may offer an important tool for application of flare forecasting.

A Restrospective and Prospective Examination of NOAA Solar Imaging

NASA Astrophysics Data System (ADS)

Hill, S. M.

2015-12-01

NOAA has provided soft X-ray imaging of the lower corona since the early 2000's. It is currently building the spacecraft and instrumentation to observe the sun in the extreme ultraviolet (EUV) through 2036. After more than 6 million calibrated images, it is appropriate to examine NOAA data as providing retrospective context for scientific missions. In particular, this presentation examines the record of GOES Solar X-ray Imager (SXI) observations, including continuity, photometric stability and comparison to other contemporary x-ray imagers. The first GOES Solar X-ray Imager was launched in 2001 and entered operations in 2003. The current SXIs will remain in operations until approximately 2020, when a new series of Solar (extreme-)Ultraviolet Imagers (SUVIs) will replace them as the current satellites reach their end of life. In the sense that the SXIs are similar to Yokoh's SXT and Hinode's XRT, the SUVI instruments will be similar to SOHO's EIT and SDO's AIA. The move to narrowband EUV imagers will better support eventual operational estimation of plasma conditions. In particular, plans are to leverage advances in automated image processing and segmentation to assist forecasters. While NOAA's principal use of these observations is real-time space weather forecasting, they will continue to provide a consistent context measurement for researchers for decades to come.

Prediction of the solar modulation of galactic cosmic rays and radiation dose of aircrews up to the solar cycle 26

NASA Astrophysics Data System (ADS)

Miyake, S.; Kataoka, R.; Sato, T.

2016-12-01

The solar modulation of galactic cosmic rays (GCRs), which is the variation of the terrestrial GCR flux caused by the heliospheric environmental change, is basically anti-correlated with the solar activity with so-called 11-year periodicity. In the current weak solar cycle 24, we expect that the flux of GCRs is getting higher than that in the previous solar cycles, leading to the increase in the radiation exposure in the space and atmosphere. In order to quantitatively evaluate the possible solar modulation of GCRs and resultant radiation exposure at flight altitude during the solar cycles 24, 25, and 26, we have developed the time-dependent and three-dimensional model of the solar modulation of GCRs. Our model can give the flux of GCRs anywhere in the heliosphere by assuming the variation of the solar wind velocity, the strength of the interplanetary magnetic field, and its tilt angle. We solve the curvature and gradient drift motion of GCRs in the heliospheric magnetic field, and therefore reproduce the 22-year variation of the solar modulation of GCRs. It is quantitatively confirmed that our model reproduces the energy spectra observed by BESS and PAMELA. We then calculate the variation of the GCR energy spectra during the solar cycles 24, 25, and 26, by extrapolating the solar wind parameters and tilt angle. We also calculate the neutron monitor counting rate and the radiation dose of aircrews at flight altitude, by the air-shower simulation performed by PHITS (Particle and Heavy Ion Transport code System). In this presentation, we report the quantitative forecast values of the solar modulation of GCRs, neutron monitor counting rate, and the radiation dose at flight altitude up to the cycle 26, including the discussion of the charge sign dependence on those results.

ICARUS Mission, Next Step of Coronal Exploration after Solar Orbiter and Solar Probe Plus

NASA Astrophysics Data System (ADS)

Krasnoselskikh, V.; Tsurutani, B.; Velli, M.; Maksimovic, M.; Balikhin, M. A.; Dudok de Wit, T.; Kretzschmar, M.

2017-12-01

The primary scientific goal of ICARUS, a mother-daughter satellite mission, will be to determine how the magnetic field and plasma dynamics in the outer solar atmosphere give rise to the corona, the solar wind and the heliosphere. Reaching this goal will be a Rosetta-stone step, with results broadly applicable in the fields of space plasma and astrophysics. Within ESA's Cosmic Vision roadmap, these goals address Theme 2: How does the solar system work ?" Investigating basic processes occurring from the Sun to the edge of the Solar System". ICARUS will not only advance our understanding of the plasma environment around the Sun, but also of the numerous magnetically active stars with hot plasma coronae. ICARUS I will perform the firstever direct in situ measurements of electromagnetic fields, particle acceleration, wave activity, energy distribution and flows directly in the regions where the solar wind emerges from the coronal plasma. ICARUS I will have a perihelion at 1 Solar radius from its surface, it will cross the region where the major energy deposition occurs. The polar orbit of ICARUS I will enable crossing the regions where both the fast and slow wind are generated. It will probe local characteristics of the plasma and provide unique information about the processes involved in the creation of the solar wind. ICARUS II will observe this region using remote-sensing instruments, providing simultaneous information about regions crossed by ICARUS I and the solar atmosphere below as observed by solar telescopes. It will provide bridges for understanding the magnetic links between heliosphere and solar atmosphere. Such information is crucial to understanding of the physics and electrodynamics of the solar atmosphere. ICARUS II will also play an important relay role, enabling the radio-link with ICARUS I. It will receive, collect and store information transmitted from ICARUS I during its closest approach to the Sun. It will perform preliminary data processing and transmit it to the Earth. Performing such unique in situ measurements in the region where deadly solar energetic particles are energized, ICARUS will make fundamental contributions to our ability to monitor and forecast the space radiation environment. Such knowledge is extremely important for space explorations, especially for long-term manned space missions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woodroffe, Jesse; Jordanova, Vania; Toth, Gabor

Extreme weather happens worldwide and it takes place in the magnetosphere. The magnetosphere is the place where the majority of earth’s satellites reside. These satellites provide weather forecasting and serve as national defense. When solar storms take place, they can damage satellites.

Progress in preliminary studies at Ottana Solar Facility

NASA Astrophysics Data System (ADS)

Demontis, V.; Camerada, M.; Cau, G.; Cocco, D.; Damiano, A.; Melis, T.; Musio, M.

2016-05-01

The fast increasing share of distributed generation from non-programmable renewable energy sources, such as the strong penetration of photovoltaic technology in the distribution networks, has generated several problems for the management and security of the whole power grid. In order to meet the challenge of a significant share of solar energy in the electricity mix, several actions aimed at increasing the grid flexibility and its hosting capacity, as well as at improving the generation programmability, need to be investigated. This paper focuses on the ongoing preliminary studies at the Ottana Solar Facility, a new experimental power plant located in Sardinia (Italy) currently under construction, which will offer the possibility to progress in the study of solar plants integration in the power grid. The facility integrates a concentrating solar power (CSP) plant, including a thermal energy storage system and an organic Rankine cycle (ORC) unit, with a concentrating photovoltaic (CPV) plant and an electrical energy storage system. The facility has the main goal to assess in real operating conditions the small scale concentrating solar power technology and to study the integration of the two technologies and the storage systems to produce programmable and controllable power profiles. A model for the CSP plant yield was developed to assess different operational strategies that significantly influence the plant yearly yield and its global economic effectiveness. In particular, precise assumptions for the ORC module start-up operation behavior, based on discussions with the manufacturers and technical datasheets, will be described. Finally, the results of the analysis of the: "solar driven", "weather forecasts" and "combined storage state of charge (SOC)/ weather forecasts" operational strategies will be presented.

Statistical modeling of Earth's plasmasphere

NASA Astrophysics Data System (ADS)

Veibell, Victoir

The behavior of plasma near Earth's geosynchronous orbit is of vital importance to both satellite operators and magnetosphere modelers because it also has a significant influence on energy transport, ion composition, and induced currents. The system is highly complex in both time and space, making the forecasting of extreme space weather events difficult. This dissertation examines the behavior and statistical properties of plasma mass density near geosynchronous orbit by using both linear and nonlinear models, as well as epoch analyses, in an attempt to better understand the physical processes that precipitates and drives its variations. It is shown that while equatorial mass density does vary significantly on an hourly timescale when a drop in the disturbance time scale index ( Dst) was observed, it does not vary significantly between the day of a Dst event onset and the day immediately following. It is also shown that increases in equatorial mass density were not, on average, preceded or followed by any significant change in the examined solar wind or geomagnetic variables, including Dst, despite prior results that considered a few selected events and found a notable influence. It is verified that equatorial mass density and and solar activity via the F10.7 index have a strong correlation, which is stronger over longer timescales such as 27 days than it is over an hourly timescale. It is then shown that this connection seems to affect the behavior of equatorial mass density most during periods of strong solar activity leading to large mass density reactions to Dst drops for high values of F10.7. It is also shown that equatorial mass density behaves differently before and after events based on the value of F10.7 at the onset of an equatorial mass density event or a Dst event, and that a southward interplanetary magnetic field at onset leads to slowed mass density growth after event onset. These behavioral differences provide insight into how solar and geomagnetic conditions impact mass density at geosynchronous orbit, enabling operators to better anticipate the response to space weather events and magnetosphere models to include mass density effects in magnetosphere simulations. It is shown that it is possible to classify an equatorial mass density event onset as being distinct from the three hours preceding it, indicating that there are distinguishing characteristics of solar wind and geomagnetic conditions surrounding an event. It is also been shown that given four days of solar and geomagnetic conditions, an event can be forecasted a day in advance with reasonable accuracy, but also with a number of false positives. These false positives have similarly distributed values as the true positives, though, indicating more data are needed to distinguish impending events.

Do Solar Coronal Holes Affect the Properties of Solar Energetic Particle Events?

NASA Technical Reports Server (NTRS)

Kahler, S. W.; Arge, C. N.; Akiyama, S.; Gopalswamy, N.

2013-01-01

The intensities and timescales of gradual solar energetic particle (SEP) events at 1 AU may depend not only on the characteristics of shocks driven by coronal mass ejections (CMEs), but also on large-scale coronal and interplanetary structures. It has long been suspected that the presence of coronal holes (CHs) near the CMEs or near the 1-AU magnetic footpoints may be an important factor in SEP events. We used a group of 41 E (is) approx. 20 MeV SEP events with origins near the solar central meridian to search for such effects. First we investigated whether the presence of a CH directly between the sources of the CME and of the magnetic connection at 1 AU is an important factor. Then we searched for variations of the SEP events among different solar wind (SW) stream types: slow, fast, and transient. Finally, we considered the separations between CME sources and CH footpoint connections from 1 AU determined from four-day forecast maps based on Mount Wilson Observatory and the National Solar Observatory synoptic magnetic-field maps and the Wang-Sheeley-Arge model of SW propagation. The observed in-situ magnetic-field polarities and SW speeds at SEP event onsets tested the forecast accuracies employed to select the best SEP/CH connection events for that analysis. Within our limited sample and the three analytical treatments, we found no statistical evidence for an effect of CHs on SEP event peak intensities, onset times, or rise times. The only exception is a possible enhancement of SEP peak intensities in magnetic clouds.

Predicting the magnetic vectors within coronal mass ejections arriving at Earth: 2. Geomagnetic response

NASA Astrophysics Data System (ADS)

Savani, N. P.; Vourlidas, A.; Richardson, I. G.; Szabo, A.; Thompson, B. J.; Pulkkinen, A.; Mays, M. L.; Nieves-Chinchilla, T.; Bothmer, V.

2017-02-01

This is a companion to Savani et al. (2015) that discussed how a first-order prediction of the internal magnetic field of a coronal mass ejection (CME) may be made from observations of its initial state at the Sun for space weather forecasting purposes (Bothmer-Schwenn scheme (BSS) model). For eight CME events, we investigate how uncertainties in their predicted magnetic structure influence predictions of the geomagnetic activity. We use an empirical relationship between the solar wind plasma drivers and Kp index together with the inferred magnetic vectors, to make a prediction of the time variation of Kp (Kp(BSS)). We find a 2σ uncertainty range on the magnetic field magnitude (|B|) provides a practical and convenient solution for predicting the uncertainty in geomagnetic storm strength. We also find the estimated CME velocity is a major source of error in the predicted maximum Kp. The time variation of Kp(BSS) is important for predicting periods of enhanced and maximum geomagnetic activity, driven by southerly directed magnetic fields, and periods of lower activity driven by northerly directed magnetic field. We compare the skill score of our model to a number of other forecasting models, including the NOAA/Space Weather Prediction Center (SWPC) and Community Coordinated Modeling Center (CCMC)/SWRC estimates. The BSS model was the most unbiased prediction model, while the other models predominately tended to significantly overforecast. The True skill score of the BSS prediction model (TSS = 0.43 ± 0.06) exceeds the results of two baseline models and the NOAA/SWPC forecast. The BSS model prediction performed equally with CCMC/SWRC predictions while demonstrating a lower uncertainty.

The main pillar: Assessment of space weather observational asset performance supporting nowcasting, forecasting, and research to operations.

PubMed

Posner, A; Hesse, M; St Cyr, O C

2014-04-01

Space weather forecasting critically depends upon availability of timely and reliable observational data. It is therefore particularly important to understand how existing and newly planned observational assets perform during periods of severe space weather. Extreme space weather creates challenging conditions under which instrumentation and spacecraft may be impeded or in which parameters reach values that are outside the nominal observational range. This paper analyzes existing and upcoming observational capabilities for forecasting, and discusses how the findings may impact space weather research and its transition to operations. A single limitation to the assessment is lack of information provided to us on radiation monitor performance, which caused us not to fully assess (i.e., not assess short term) radiation storm forecasting. The assessment finds that at least two widely spaced coronagraphs including L4 would provide reliability for Earth-bound CMEs. Furthermore, all magnetic field measurements assessed fully meet requirements. However, with current or even with near term new assets in place, in the worst-case scenario there could be a near-complete lack of key near-real-time solar wind plasma data of severe disturbances heading toward and impacting Earth's magnetosphere. Models that attempt to simulate the effects of these disturbances in near real time or with archival data require solar wind plasma observations as input. Moreover, the study finds that near-future observational assets will be less capable of advancing the understanding of extreme geomagnetic disturbances at Earth, which might make the resulting space weather models unsuitable for transition to operations. Manuscript assesses current and near-future space weather assetsCurrent assets unreliable for forecasting of severe geomagnetic stormsNear-future assets will not improve the situation.

The main pillar: Assessment of space weather observational asset performance supporting nowcasting, forecasting, and research to operations

PubMed Central

Posner, A; Hesse, M; St Cyr, O C

2014-01-01

Space weather forecasting critically depends upon availability of timely and reliable observational data. It is therefore particularly important to understand how existing and newly planned observational assets perform during periods of severe space weather. Extreme space weather creates challenging conditions under which instrumentation and spacecraft may be impeded or in which parameters reach values that are outside the nominal observational range. This paper analyzes existing and upcoming observational capabilities for forecasting, and discusses how the findings may impact space weather research and its transition to operations. A single limitation to the assessment is lack of information provided to us on radiation monitor performance, which caused us not to fully assess (i.e., not assess short term) radiation storm forecasting. The assessment finds that at least two widely spaced coronagraphs including L4 would provide reliability for Earth-bound CMEs. Furthermore, all magnetic field measurements assessed fully meet requirements. However, with current or even with near term new assets in place, in the worst-case scenario there could be a near-complete lack of key near-real-time solar wind plasma data of severe disturbances heading toward and impacting Earth's magnetosphere. Models that attempt to simulate the effects of these disturbances in near real time or with archival data require solar wind plasma observations as input. Moreover, the study finds that near-future observational assets will be less capable of advancing the understanding of extreme geomagnetic disturbances at Earth, which might make the resulting space weather models unsuitable for transition to operations. Key Points Manuscript assesses current and near-future space weather assets Current assets unreliable for forecasting of severe geomagnetic storms Near-future assets will not improve the situation PMID:26213516

Payette River Basin Project: Improving Operational Forecasting in Complex Terrain through Chemistry

NASA Astrophysics Data System (ADS)

Blestrud, D.; Kunkel, M. L.; Parkinson, S.; Holbrook, V. P.; Benner, S. G.; Fisher, J.

2015-12-01

Idaho Power Company (IPC) is an investor owned hydroelectric based utility, serving customers throughout southern Idaho and eastern Oregon. The University of Arizona (UA) runs an operational 1.8-km resolution Weather and Research Forecast (WRF) model for IPC, which is incorporated into IPC near and real-time forecasts for hydro, solar and wind generation, load servicing and a large-scale wintertime cloud seeding operation to increase winter snowpack. Winter snowpack is critical to IPC, as hydropower provides ~50% of the company's generation needs. In efforts to improve IPC's near-term forecasts and operational guidance to its cloud seeding program, IPC is working extensively with UA and the National Center for Atmospheric Research (NCAR) to improve WRF performance in the complex terrain of central Idaho. As part of this project, NCAR has developed a WRF based cloud seeding module (WRF CS) to deliver high-resolution, tailored forecasts to provide accurate guidance for IPC's operations. Working with Boise State University (BSU), IPC is conducting a multiyear campaign to validate the WRF CS's ability to account for and disperse the cloud seeding agent (AgI) within the boundary layer. This improved understanding of how WRF handles the AgI dispersion and fate will improve the understanding and ultimately the performance of WRF to forecast other parameters. As part of this campaign, IPC has developed an extensive ground based monitoring network including a Remote Area Snow Sampling Device (RASSD) that provides spatially and temporally discrete snow samples during active cloud seeding periods. To quantify AgI dispersion in the complex terrain, BSU conducts trace element analysis using LA-ICP-MS on the RASSD sampled snow to provide measurements (at the 10-12 level) of incorporated AgI, measurements are compare directly with WRF CS's estimates of distributed AgI. Modeling and analysis results from previous year's research and plans for coming seasons will be presented.

Obituary: Jeannette Virginia Lincoln, 1915-2003

NASA Astrophysics Data System (ADS)

Coffey, Helen E.

2004-12-01

J. (Jeannette) Virginia Lincoln died on 1 August 2003 of natural causes at age 87. She was a pioneer in space weather forecasting and was instrumental in establishing the World Data Center-A for Solar-Terrestrial Physics (WDC-A for STP) at the National Oceanic and Atmospheric Administration's (NOAA) National Geophysical Data Center (NGDC). Lincoln received a U.S. Department of Commerce Gold Medal for Distinguished Service in 1973 for outstanding accomplishments and leadership. She was elected a Fellow of the American Geophysical Union, a Fellow of the American Association for the Advancement of Science, and a Fellow of the Society of Women Engineers. A physicist, she served as Division Chief of the Solar-Terrestrial Physics Division (STPD) and Director of WDC-A for STP from 1966 until her retirement in 1980. Virginia was born on Labor Day, 7 September 1915, in Ames, Iowa, to Rush B. Lincoln and Jeannette Bartholomew Lincoln. Her father, Rush B. Lincoln (b. 1881, d. 1977 at age 95), served as a Major General in the U.S. Air Force. He was a direct descendant of the brother of President Abraham Lincoln. Her mother Jeannette Bartholomew Lincoln (d. 1986 at age 104) taught Chemistry at Iowa State University. Her brother, Rush B. Lincoln, Jr. (d. 2002), was five years older. Her grandfather Lincoln fought in the Civil War as a Confederate Captain. Virginia was immersed in military life and continued many contacts and visited military installations throughout her life. Her parents lived with her until their deaths. She enjoyed the perks of being a General's daughter, actively participating in her parent's lives, and served as caregiver in their declining years. Influenced by her Army background, she developed a strong assertive personality and good problem-solving capabilities. She received a bachelor's degree in physics from Wellesley College in 1936 and a master's degree from Iowa State University in 1938. She was an instructor in household equipment at Iowa State from 1936 to 1942. Electric appliances were new-fangled devices and people had to be educated in their use. In 1942, Virginia joined the U.S. National Bureau of Standards in Washington, DC, as a physicist in the Interservice Radio Propagation Laboratory (IRPL), working in ionospheric research. In 1946 the Central Radio Propagation Laboratory (CRPL) was formed to centralize research and provide predictions in the field of radio propagation, including investigating solar and geophysical effects and ionospheric data. In 1954 CRPL moved to Boulder, Colorado. Her first job was preparing monthly ionospheric prediction contour maps as a radio weather forecaster. The predictions were used in selecting frequencies for long distance communications. Alan H. Shapley, Department of Terrestrial Magnetism, had contracts with solar observatories to obtain their data, and worked with Lincoln on forecasts. In 1949, Virginia helped create a statistical method for predicting sunspot activity that is still used today in forecasting solar storms that can disrupt radio communication on Earth. Taking on administrative responsibilities, Virginia was appointed Chief of Radio Warning Services in 1959, the first woman to head a section in the federal bureau. Also in 1959, Lincoln was the only woman in the official U.S. delegation of over 50 scientists to attend a meeting of the International Geophysical Year (IGY) in the former Soviet Union. Using her Russian slides, Virginia gave many talks about the IGY to groups including the Chemical Society banquet, educational associations and women's service clubs. She was part of weekly meetings with Walt Roberts and the High Altitude Observatory (HAO) staff, discussing solar-terrestrial relationships. They developed auroral and cosmic ray indices for the Calendar Records (graphical display of indices and outstanding solar-terrestrial events each day) of the IGY. In 1966 she gave up forecasting work to devote time to data center work, serving as Director of the WDC-A for STP and the STP Division Chief for NOAA NGDC. She was passionate about the World Data Center system and maintaining data archives for future generations. She would introduce herself as "I am the World Data Center for Solar-Terrestrial Physics." Attending many foreign and U.S. meetings, she constantly searched for new data sets to add to the STP collection. She retired in 1980 after 38 years of federal service. When she was inducted into the Colorado Women's Hall of Fame in March 2000, she said: "My work with the World Data Centers introduced me to colleagues worldwide that became a source of much enjoyment, seeing them periodically at the international scientific meetings in Europe, Asia, and Australia." She was a past chair of the Denver Section of the Society of Women Engineers and very active in encouraging girls to study math and science. A member of the Association of Federal Professional and Administrative Women (AFPAW) and the Federally Employed Women (FEW), she supported improving the status of women. Virginia categorized herself as a joiner. She was active in many organizations, achieving life membership in the American Association of University Women (AAUW) and the Young Women's Christian Association (YWCA). In her younger days she was a figure skater and she enjoyed square dancing, playing golf, and traveling. She also enjoyed the arts and held season tickets to the University of Colorado Artist Series, the Denver Center for the Performing Arts, the opera, and the Colorado Music Festival. She was preceded in death by her parents and her brother Rush. Survivors include a nephew, Rush B. Lincoln III, a niece Deborah Lincoln Niekras, four great nieces and a great nephew. Her memoirs, "My Busy Life: How I Never Stopped Enjoying It" by Jeanette Virginia Lincoln, are available at the Carnegie Library in Boulder, Colorado. Also available are her history of her father "Rush Blodget Lincoln, My Father - the General" and a history of her mother's family. Lincoln's legacy in the World Data Center system continues to this day.

Detailed analysis of dynamic evolution of three Active Regions at the photospheric level before flare and CME occurrence

NASA Astrophysics Data System (ADS)

Ye, Yudong; Korsós, M. B.; Erdélyi, R.

2018-01-01

We present a combined analysis of the applications of the weighted horizontal magnetic gradient (denoted as WGM in Korsós et al. (2015)) method and the magnetic helicity tool (Berger and Field, 1984) employed for three active regions (ARs), namely NOAA AR 11261, AR 11283 and AR 11429. We analysed the time series of photospheric data from the Solar Dynamics Observatory taken between August 2011 and March 2012. During this period the three ARs produced a series of flares (eight M- and six X-class) and coronal mass ejections (CMEs). AR 11261 had four M-class flares and one of them was accompanied by a fast CME. AR 11283 had similar activities with two M- and two X-class flares, but only with a slow CME. Finally, AR 11429 was the most powerful of the three ARs as it hosted five compact and large solar flare and CME eruptions. For applying the WGM method we employed the Debrecen sunspot data catalogue, and, for estimating the magnetic helicity at photospheric level we used the Space-weather HMI Active Region Patches (SHARP's) vector magnetograms from SDO/HMI (Solar Dynamics Observatory/Helioseismic and Magnetic Imager). We followed the evolution of the components of the WGM and the magnetic helicity before the flare and CME occurrences. We found a unique and mutually shared behaviour, called the U-shaped pattern, of the weighted distance component of WGM and of the shearing component of the helicity flux before the flare and CME eruptions. This common pattern is associated with the decreasing-receding phases yet reported only known to be a necessary feature prior to solar flare eruption(s) but found now at the same time in the evolution of the shearing helicity flux. This result leads to the conclusions that (i) the shearing motion of photospheric magnetic field may be a key driver for solar eruption in addition to the flux emerging process, and that (ii) the found decreasing-approaching pattern in the evolution of shearing helicity flux may be another precursor indicator for improving the forecasting of solar eruptions.

The solar eclipse: a natural meteorological experiment

PubMed Central

2016-01-01

A solar eclipse provides a well-characterized reduction in solar radiation, of calculable amount and duration. This captivating natural astronomical phenomenon is ideally suited to science outreach activities, but the predictability of the change in solar radiation also provides unusual conditions for assessing the atmospheric response to a known stimulus. Modern automatic observing networks used for weather forecasting and atmospheric research have dense spatial coverage, so the quantitative meteorological responses to an eclipse can now be evaluated with excellent space and time resolution. Numerical models representing the atmosphere at high spatial resolution can also be used to predict eclipse-related changes and interpret the observations. Combining the models with measurements yields the elements of a controlled atmospheric experiment on a regional scale (10–1000 km), which is almost impossible to achieve by other means. This modern approach to ‘eclipse meteorology’ as identified here can ultimately improve weather prediction models and be used to plan for transient reductions in renewable electricity generation. During the 20 March 2015 eclipse, UK electrical energy demand increased by about 3 GWh (11 TJ) or about 4%, alongside reductions in the wind and photovoltaic electrical energy generation of 1.5 GWh (5.5 TJ). This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’. PMID:27550768

A global SOLIS vector spectromagnetograph (VSM) network

NASA Astrophysics Data System (ADS)

Streander, K. V.; Giampapa, M. S.; Harvey, J. W.; Henney, C. J.; Norton, A. A.

2008-07-01

Understanding the Sun's magnetic field related activity is far from complete as reflected in the limited ability to make accurate predictions of solar variability. To advance our understanding of solar magnetism, the National Solar Observatory (NSO) constructed the Synoptic Optical Long-term Investigations of the Sun (SOLIS) suite of instruments to conduct high precision optical measurements of processes on the Sun whose study requires sustained observations over long time periods. The Vector Spectromagnetograph (VSM), the principal SOLIS instrument, has been in operation since 2003 and obtains photospheric vector data, as well as photospheric and chromospheric longitudinal magnetic field measurements. Instrument performance is being enhanced by employing new, high-speed cameras that virtually freeze seeing, thus improving sensitivity to measure the solar magnetic field configuration. A major operational goal is to provide real-time and near-real-time data for forecasting space weather and increase scientific yield from shorter duration solar space missions and ground-based research projects. The National Solar Observatory proposes to build two near-duplicates of the VSM instrument and place them at international sites to form a three-site global VSM network. Current electronic industry practice of short lifetime cycles leads to improved performance and reduced acquisition costs but also to redesign costs and engineering impacts that must be minimized. The current VSM instrument status and experience gained from working on the original instrument is presented herein and used to demonstrate that one can dramatically reduce the estimated cost and fabrication time required to duplicate and commission two additional instruments.

Wind Energy Management System Integration Project Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.

2010-09-01

The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and windmore » forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. In this report, a new methodology to predict the uncertainty ranges for the required balancing capacity, ramping capability and ramp duration is presented. Uncertainties created by system load forecast errors, wind and solar forecast errors, generation forced outages are taken into account. The uncertainty ranges are evaluated for different confidence levels of having the actual generation requirements within the corresponding limits. The methodology helps to identify system balancing reserve requirement based on a desired system performance levels, identify system “breaking points”, where the generation system becomes unable to follow the generation requirement curve with the user-specified probability level, and determine the time remaining to these potential events. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (California ISO) real life data have shown the effectiveness of the proposed approach. A tool developed based on the new methodology described in this report will be integrated with the California ISO systems. Contractual work is currently in place to integrate the tool with the AREVA EMS system.« less

Space Solar Patrol data and changes in weather and climate, including global warming

NASA Astrophysics Data System (ADS)

Avakyan, S. V.; Baranova, L. A.; Leonov, N. B.; Savinov, E. P.; Voronin, N. A.

2010-08-01

In this paper, the results obtained during the execution of several ISTC projects are presented. The general aim of these projects has been the study of global changes in the environment, connected with solar activity. A brief description of the optical apparatus of the Space Solar Patrol (SSP) developed and built in the framework of the ISTC projects 385, 385.2, 1523 and 2500 is given. The SSP is intended for permanent monitoring of spectra and absolute fluxes of soft x-ray and extreme ultraviolet (x-ray/EUV) radiation from the full disk of the Sun which ionizes the upper atmosphere of the Earth. Permanent solar monitoring in the main part of the ionizing radiation spectra 0.8-115 (119) nm does not exist. The apparatus of the SSP was developed in the years 1996-2005 with multiyear experience of developing such apparatus in S I Vavilov State Optical Institute. The basis of this apparatus is the use of unique detectors of ionizing radiation—open secondary electron multipliers, which are 'solar blind' to near UV, visible and IR radiation from the Sun, and new methodology of these solar spectroradiometric absolute measurements. The prospects are discussed of using the SSP data for the investigation and forecast of the influence of solar variability on the weather and climate including global warming and also on the biosphere including human beings (proposal 3878). This article was originally submitted for inclusion with the papers from the 9th International Symposium on Measurement Science and Intelligent Instruments (ISMTII-2009), published in the May 2010 issue.

Clear-Sky Probability for the August 21, 2017, Total Solar Eclipse Using the NREL National Solar Radiation Database

DOE Office of Scientific and Technical Information (OSTI.GOV)

Habte, Aron M; Roberts, Billy J; Kutchenreiter, Mark C

The National Renewable Energy Laboratory (NREL) and collaborators have created a clear-sky probability analysis to help guide viewers of the August 21, 2017, total solar eclipse, the first continent-spanning eclipse in nearly 100 years in the United States. Using cloud and solar data from NREL's National Solar Radiation Database (NSRDB), the analysis provides cloudless sky probabilities specific to the date and time of the eclipse. Although this paper is not intended to be an eclipse weather forecast, the detailed maps can help guide eclipse enthusiasts to likely optimal viewing locations. Additionally, high-resolution data are presented for the centerline of themore » path of totality, representing the likelihood for cloudless skies and atmospheric clarity. The NSRDB provides industry, academia, and other stakeholders with high-resolution solar irradiance data to support feasibility analyses for photovoltaic and concentrating solar power generation projects.« less

Solar Probe Plus: Report of the Science and Technology Definition Team

NASA Technical Reports Server (NTRS)

2008-01-01

Solar Probe+ will be an extraordinary and historic mission, exploring what is arguably the last region of the solar system to be visited by a spacecraft, the Sun s outer atmosphere or corona as it extends out into space. Approaching as close as 9.5 RS* (8.5 RS above the Sun s surface), Solar Probe+ will repeatedly sample the near-Sun environment, revolutionizing our knowledge and understanding of coronal heating and of the origin and evolution of the solar wind and answering critical questions in heliophysics that have been ranked as top priorities for decades. Moreover, by making direct, in-situ measurements of the region where some of the most hazardous solar energetic particles are energized, Solar Probe+ will make a fundamental contribution to our ability to characterize and forecast the radiation environment in which future space explorers will work and live.

Development of a short-term irradiance prediction system using post-processing tools on WRF-ARW meteorological forecasts in Spain

NASA Astrophysics Data System (ADS)

Rincón, A.; Jorba, O.; Baldasano, J. M.

2010-09-01

The increased contribution of solar energy in power generation sources requires an accurate estimation of surface solar irradiance conditioned by geographical, temporal and meteorological conditions. The knowledge of the variability of these factors is essential to estimate the expected energy production and therefore help stabilizing the electricity grid and increase the reliability of available solar energy. The use of numerical meteorological models in combination with statistical post-processing tools may have the potential to satisfy the requirements for short-term forecasting of solar irradiance for up to several days ahead and its application in solar devices. In this contribution, we present an assessment of a short-term irradiance prediction system based on the WRF-ARW mesoscale meteorological model (Skamarock et al., 2005) and several post-processing tools in order to improve the overall skills of the system in an annual simulation of the year 2004 in Spain. The WRF-ARW model is applied with 4 km x 4 km horizontal resolution and 38 vertical layers over the Iberian Peninsula. The hourly model irradiance is evaluated against more than 90 surface stations. The stations are used to assess the temporal and spatial fluctuations and trends of the system evaluating three different post-processes: Model Output Statistics technique (MOS; Glahn and Lowry, 1972), Recursive statistical method (REC; Boi, 2004) and Kalman Filter Predictor (KFP, Bozic, 1994; Roeger et al., 2003). A first evaluation of the system without post-processing tools shows an overestimation of the surface irradiance, due to the lack of atmospheric absorbers attenuation different than clouds not included in the meteorological model. This produces an annual BIAS of 16 W m-2 h-1, annual RMSE of 106 W m-2 h-1 and annual NMAE of 42%. The largest errors are observed in spring and summer, reaching RMSE of 350 W m-2 h-1. Results using Kalman Filter Predictor show a reduction of 8% of RMSE, 83% of BIAS, and NMAE decreases down to 32%. The REC method shows a reduction of 6% of RMSE, 79% of BIAS, and NMAE decreases down to 28%. When comparing stations at different altitudes, the overestimation is enhanced at coastal stations (less than 200m) up to 900 W m-2 h-1. The results allow us to analyze strengths and drawbacks of the irradiance prediction system and its application in the estimation of energy production from photovoltaic system cells. References Boi, P.: A statistical method for forecasting extreme daily temperatures using ECMWF 2-m temperatures and ground station measurements, Meteorol. Appl., 11, 245-251, 2004. Bozic, S.: Digital and Kalman filtering, John Wiley, Hoboken, New Jersey, 2nd edn., 1994. Glahn, H. and Lowry, D.: The use of Model Output Statistics (MOS) in Objective Weather Forecasting, Applied Meteorology, 11, 1203-1211, 1972. Roeger, C., Stull, R., McClung, D., Hacker, J., Deng, X., and Modzelewski, H.: Verification of Mesoscale Numerical Weather Forecasts in Mountainous Terrain for Application to Avalanche Prediction, Weather and forecasting, 18, 1140-1160, 2003. Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, D. M., Wang, W., and Powers, J. G.: A Description of the Advanced Research WRF Version 2, Tech. Rep. NCAR/TN-468+STR, NCAR Technical note, 2005.

Evidence for Gravity Wave Seeding of Convective Ionospheric Storms Possibly Initiated by Thunderstorms

NASA Astrophysics Data System (ADS)

Kelley, M. C.; Dao, E. V.

2018-05-01

With the increase in solar activity, the Communication/Outage Forecast System satellite decayed on orbit to below the F peak. As such, we can study the development of convective ionospheric storms and, most importantly, study large-scale seeding of the responsible instability. For decades, gravity has been suggested as being responsible for the long wavelengths in the range of 200 to 1,000 km, as are commonly observed using airglow and satellite data. Here we suggest that convective thunderstorms are a likely source of gravity waves and point out that recent theoretical analysis has shown this connection to be quite possible.

Wind Power Forecasting Error Frequency Analyses for Operational Power System Studies: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Florita, A.; Hodge, B. M.; Milligan, M.

2012-08-01

The examination of wind power forecasting errors is crucial for optimal unit commitment and economic dispatch of power systems with significant wind power penetrations. This scheduling process includes both renewable and nonrenewable generators, and the incorporation of wind power forecasts will become increasingly important as wind fleets constitute a larger portion of generation portfolios. This research considers the Western Wind and Solar Integration Study database of wind power forecasts and numerical actualizations. This database comprises more than 30,000 locations spread over the western United States, with a total wind power capacity of 960 GW. Error analyses for individual sites andmore » for specific balancing areas are performed using the database, quantifying the fit to theoretical distributions through goodness-of-fit metrics. Insights into wind-power forecasting error distributions are established for various levels of temporal and spatial resolution, contrasts made among the frequency distribution alternatives, and recommendations put forth for harnessing the results. Empirical data are used to produce more realistic site-level forecasts than previously employed, such that higher resolution operational studies are possible. This research feeds into a larger work of renewable integration through the links wind power forecasting has with various operational issues, such as stochastic unit commitment and flexible reserve level determination.« less

Evaluation of the NCEP CFSv2 45-day Forecasts for Predictability of Intraseasonal Tropical Storm Activities

NASA Astrophysics Data System (ADS)

Schemm, J. E.; Long, L.; Baxter, S.

2013-12-01

Evaluation of the NCEP CFSv2 45-day Forecasts for Predictability of Intraseasonal Tropical Storm Activities Jae-Kyung E. Schemm, Lindsey Long and Stephen Baxter Climate Prediction Center, NCEP/NWS/NOAA Predictability of intraseasonal tropical storm (TS) activities is assessed using the 1999-2010 CFSv2 hindcast suite. Weekly TS activities in the CFSv2 45-day forecasts were determined using the TS detection and tracking method devised by Carmago and Zebiak (2002). The forecast periods are divided into weekly intervals for Week 1 through Week 6, and also the 30-day mean. The TS activities in those intervals are compared to the observed activities based on the NHC HURDAT and JTWC Best Track datasets. The CFSv2 45-day hindcast suite is made of forecast runs initialized at 00, 06, 12 and 18Z every day during the 1999 - 2010 period. For predictability evaluation, forecast TS activities are analyzed based on 20-member ensemble forecasts comprised of 45-day runs made during the most recent 5 days prior to the verification period. The forecast TS activities are evaluated in terms of the number of storms, genesis locations and storm tracks during the weekly periods. The CFSv2 forecasts are shown to have a fair level of skill in predicting the number of storms over the Atlantic Basin with the temporal correlation scores ranging from 0.73 for Week 1 forecasts to 0.63 for Week 6, and the average RMS errors ranging from 0.86 to 1.07 during the 1999-2010 hurricane season. Also, the forecast track density distribution and false alarm statistics are compiled using the hindcast analyses. In real-time applications of the intraseasonal TS activity forecasts, the climatological TS forecast statistics will be used to make the model bias corrections in terms of the storm counts, track distribution and removal of false alarms. An operational implementation of the weekly TS activity prediction is planned for early 2014 to provide an objective input for the CPC's Global Tropical Hazards Outlooks.

Community Coordinated Modeling Center (CCMC): Using innovative tools and services to support worldwide space weather scientific communities and networks

NASA Astrophysics Data System (ADS)

Mendoza, A. M.; Bakshi, S.; Berrios, D.; Chulaki, A.; Evans, R. M.; Kuznetsova, M. M.; Lee, H.; MacNeice, P. J.; Maddox, M. M.; Mays, M. L.; Mullinix, R. E.; Ngwira, C. M.; Patel, K.; Pulkkinen, A.; Rastaetter, L.; Shim, J.; Taktakishvili, A.; Zheng, Y.

2012-12-01

Community Coordinated Modeling Center (CCMC) was established to enhance basic solar terrestrial research and to aid in the development of models for specifying and forecasting conditions in the space environment. In achieving this goal, CCMC has developed and provides a set of innovative tools varying from: Integrated Space Weather Analysis (iSWA) web -based dissemination system for space weather information, Runs-On-Request System providing access to unique collection of state-of-the-art solar and space physics models (unmatched anywhere in the world), Advanced Online Visualization and Analysis tools for more accurate interpretation of model results, Standard Data formats for Simulation Data downloads, and recently Mobile apps (iPhone/Android) to view space weather data anywhere to the scientific community. The number of runs requested and the number of resulting scientific publications and presentations from the research community has not only been an indication of the broad scientific usage of the CCMC and effective participation by space scientists and researchers, but also guarantees active collaboration and coordination amongst the space weather research community. Arising from the course of CCMC activities, CCMC also supports community-wide model validation challenges and research focus group projects for a broad range of programs such as the multi-agency National Space Weather Program, NSF's CEDAR (Coupling, Energetics and Dynamics of Atmospheric Regions), GEM (Geospace Environment Modeling) and Shine (Solar Heliospheric and INterplanetary Environment) programs. In addition to performing research and model development, CCMC also supports space science education by hosting summer students through local universities; through the provision of simulations in support of classroom programs such as Heliophysics Summer School (with student research contest) and CCMC Workshops; training next generation of junior scientists in space weather forecasting; and educating the general public about the importance and impacts of space weather effects. Although CCMC is organizationally comprised of United States federal agencies, CCMC services are open to members of the international science community and encourages interagency and international collaboration. In this poster, we provide an overview of using Community Coordinated Modeling Center (CCMC) tools and services to support worldwide space weather scientific communities and networks.;

Space weather forecasting: Past, Present, Future

NASA Astrophysics Data System (ADS)

Lanzerotti, L. J.

2012-12-01

There have been revolutionary advances in electrical technologies over the last 160 years. The historical record demonstrates that space weather processes have often provided surprises in the implementation and operation of many of these technologies. The historical record also demonstrates that as the complexity of systems increase, including their interconnectedness and interoperability, they can become more susceptible to space weather effects. An engineering goal, beginning during the decades following the 1859 Carrington event, has been to attempt to forecast solar-produced disturbances that could affect technical systems, be they long grounded conductor-based or radio-based or required for exploration, or the increasingly complex systems immersed in the space environment itself. Forecasting of space weather events involves both frontier measurements and models to address engineering requirements, and industrial and governmental policies that encourage and permit creativity and entrepreneurship. While analogies of space weather forecasting to terrestrial weather forecasting are frequently made, and while many of the analogies are valid, there are also important differences. This presentation will provide some historical perspectives on the forecast problem, a personal assessment of current status of several areas including important policy issues, and a look into the not-too-distant future.

Modulation of galactic cosmic rays in solar cycles 22-24: Analysis and physical interpretation

NASA Astrophysics Data System (ADS)

Kalinin, M. S.; Bazilevskaya, G. A.; Krainev, M. B.; Svirzhevskaya, A. K.; Svirzhevsky, N. S.; Starodubtsev, S. A.

2017-09-01

This work represents a physical interpretation of cosmic ray modulation in the 22nd-24th solar cycles, including an interpretation of an unusual behavior of their intensity in the last minimum of the solar activity (2008-2010). In terms of the Parker modulation model, which deals with regularly measured heliospheric characteristics, it is shown that the determining factor of the increased intensity of the galactic cosmic rays in the minimum of the 24th solar cycle is an anomalous reduction of the heliospheric magnetic field strength during this time interval under the additional influence of the solar wind velocity and the tilt angle of the heliospheric current sheet. We have used in the calculations the dependence of the diffusion tensor on the rigidity in the form K ij ∝ R 2-μ with μ = 1.2 in the sector zones of the heliospheric magnetic field and with μ = 0.8 outside the sector zones, which leads to an additional amplification of the diffusion mechanism of cosmic ray modulation. The proposed approach allows us to describe quite satisfactorily the integral intensity of protons with an energy above 0.1 GeV and the energy spectra in the minima of the 22nd-24th solar cycles at the same value of the free parameter. The determining factor of the anomalously high level of the galactic cosmic ray intensity in the minimum of the 24th solar cycle is the significant reduction of the heliospheric magnetic field strength during this time interval. The forecast of the intensity level in the minimum of the 25th solar cycle is provided.

Preconditioning of Interplanetary Space Due to Transient CME Disturbances

DOE Office of Scientific and Technical Information (OSTI.GOV)

Temmer, M.; Reiss, M. A.; Hofmeister, S. J.

Interplanetary space is characteristically structured mainly by high-speed solar wind streams emanating from coronal holes and transient disturbances such as coronal mass ejections (CMEs). While high-speed solar wind streams pose a continuous outflow, CMEs abruptly disrupt the rather steady structure, causing large deviations from the quiet solar wind conditions. For the first time, we give a quantification of the duration of disturbed conditions (preconditioning) for interplanetary space caused by CMEs. To this aim, we investigate the plasma speed component of the solar wind and the impact of in situ detected interplanetary CMEs (ICMEs), compared to different background solar wind modelsmore » (ESWF, WSA, persistence model) for the time range 2011–2015. We quantify in terms of standard error measures the deviations between modeled background solar wind speed and observed solar wind speed. Using the mean absolute error, we obtain an average deviation for quiet solar activity within a range of 75.1–83.1 km s{sup −1}. Compared to this baseline level, periods within the ICME interval showed an increase of 18%–32% above the expected background, and the period of two days after the ICME displayed an increase of 9%–24%. We obtain a total duration of enhanced deviations over about three and up to six days after the ICME start, which is much longer than the average duration of an ICME disturbance itself (∼1.3 days), concluding that interplanetary space needs ∼2–5 days to recover from the impact of ICMEs. The obtained results have strong implications for studying CME propagation behavior and also for space weather forecasting.« less

Forecasting Occurrences of Activities.

PubMed

Minor, Bryan; Cook, Diane J

2017-07-01

While activity recognition has been shown to be valuable for pervasive computing applications, less work has focused on techniques for forecasting the future occurrence of activities. We present an activity forecasting method to predict the time that will elapse until a target activity occurs. This method generates an activity forecast using a regression tree classifier and offers an advantage over sequence prediction methods in that it can predict expected time until an activity occurs. We evaluate this algorithm on real-world smart home datasets and provide evidence that our proposed approach is most effective at predicting activity timings.

EEC focuses new energy budget on solar and conservation R and D

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1979-12-17

Solar energy, followed by conservation and geothermal energy, will have top priority for the European Economic Community's (ECC) $142 million energy research budget through 1983. Proposals for the cost-shared projects, of which EEC will pay half, are being accepted by eligible companies and research organizations. Committees for each technology advise the European Commission on which proposals to accept and suggest an appropriate funding level. The EEC also funds demonstrations of promising research to determine economic feasibility. Major emphasis will be placed during the present four-year budget for solar research on photovoltaics. Other projects include a European solar-insolation atlas and solar-heatingmore » manual, advanced batteries, and energy storage systems. Geothermal projects will focus on resource mapping, exploratory drilling, hydrogen production, and energy forecasting. (DCK)« less

The new Met Office strategy for seasonal forecasts

NASA Astrophysics Data System (ADS)

Hewson, T. D.

2012-04-01

In October 2011 the Met Office began issuing a new-format UK seasonal forecast, called "The 3-month Outlook". Government interest in a UK-relevant product had been heightened by infrastructure issues arising during the severe cold of previous winters. At the same time there was evidence that the Met Office's "GLOSEA4" long range forecasting system exhibited some hindcast skill for the UK, that was comparable to its hindcast skill for the larger (and therefore less useful) 'northern Europe' region. Also, the NAO- and AO- signals prevailing in the previous two winters had been highlighted by the GLOSEA4 model well in advance. This presentation will initially give a brief overview of GLOSEA4, describing key features such as evolving sea-ice, a well-resolved stratosphere, and the perturbation strategy. Skill measures will be shown, along with forecasts for the last 3 winters. The new structure 3-month outlook will then be described and presented. Previously, our seasonal forecasts had been based on a tercile approach. The new format outlook aims to substantially improve upon this by illustrating graphically, and with text, the full range of possible outcomes, and by placing those outcomes in the context of climatology. In one key component the forecast pdfs (probability density functions) are displayed alongside climatological pdfs. To generate the forecast pdf we take the bias-corrected GLOSEA4 output (42 members), and then incorporate, via expert team, all other relevant information. Firstly model forecasts from other centres are examined. Then external 'forcing factors', such as solar, and the state of the land-ocean-ice system, are referenced, assessing how well the models represent their influence, and bringing in statistical relationships where appropriate. The expert team thereby decides upon any changes to the GLOSEA4 data, employing an interactive tool to shift, expand or contract the forecast pdfs accordingly. The full modification process will be illustrated during the presentation. Another key component of the 3-month outlook is the focus it places on potential hazards and impacts. To date specific references have been made to snow and ice disruption, to replenishment expectation for regions suffering water supply shortages, and to windstorm frequency. This aspect will be discussed, showing also some subjective verification. In future we hope to extend the 3-month outlook framework to other parts of the world, notably Africa, a region where the Met Office, with DfID support, is working collaboratively to improve real-time long range forecasts. Brief reference will also be made to such activities.

Validation of Community Models: 2. Development of a Baseline, Using the Wang-Sheeley-Arge Model

NASA Technical Reports Server (NTRS)

MacNeice, Peter

2009-01-01

This paper is the second in a series providing independent validation of community models of the outer corona and inner heliosphere. Here I present a comprehensive validation of the Wang-Sheeley-Arge (WSA) model. These results will serve as a baseline against which to compare the next generation of comparable forecasting models. The WSA model is used by a number of agencies to predict Solar wind conditions at Earth up to 4 days into the future. Given its importance to both the research and forecasting communities, it is essential that its performance be measured systematically and independently. I offer just such an independent and systematic validation. I report skill scores for the model's predictions of wind speed and interplanetary magnetic field (IMF) polarity for a large set of Carrington rotations. The model was run in all its routinely used configurations. It ingests synoptic line of sight magnetograms. For this study I generated model results for monthly magnetograms from multiple observatories, spanning the Carrington rotation range from 1650 to 2074. I compare the influence of the different magnetogram sources and performance at quiet and active times. I also consider the ability of the WSA model to forecast both sharp transitions in wind speed from slow to fast wind and reversals in the polarity of the radial component of the IMF. These results will serve as a baseline against which to compare future versions of the model as well as the current and future generation of magnetohydrodynamic models under development for forecasting use.

Louisiana Airport System Plan aviation activity forecasts 1990-2010.

DOT National Transportation Integrated Search

1991-07-01

This report documents the methodology used to develop the aviation activity forecasts prepared as a part of the update to the Louisiana Airport System Plan and provides Louisiana aviation forecasts for the years 1990 to 2010. In general, the forecast...

A space weather information service based upon remote and in-situ measurements of coronal mass ejections heading for Earth

NASA Astrophysics Data System (ADS)

Hartkorn, O. A.; Ritter, B.; Meskers, A. J. H.; Miles, O.; Russwurm, M.; Scully, S.; Roldan, A.; Juestel, P.; Reville, V.; Lupu, S.; Ruffenach, A.

2014-12-01

The Earth's magnetosphere is formed as a consequence of the interaction between the planet's magnetic field and the solar wind, a continuous plasma stream from the Sun. A number of different solar wind phenomena have been studied over the past forty years with the intention of understandingand forcasting solar behavior and space weather. In particular, Earth-bound interplanetary coronal mass ejections (CMEs) can significantly disturb the Earth's magnetosphere for a short time and cause geomagnetic storms. We present a mission concept consisting of six spacecraft that are equally spaced in a heliocentric orbit at 0.72 AU. These spacecraft will monitor the plasma properties, the magnetic field's orientation and magnitude, and the 3D-propagation trajectory of CMEs heading for Earth. The primary objective of this mission is to increase space weather forecasting time by means of a near real-time information service, that is based upon in-situ and remote measurements of the CME properties. The mission secondary objective is the improvement of scientific space weather models. In-situ measurements are performed using a Solar Wind Analyzer instrumentation package and flux gate magnetometers. For remote measurements, coronagraphs are employed. The proposed instruments originate from other space missions with the intention to reduce mission costs and to streamline the mission design process. Communication with the six identical spacecraft is realized via a deep space network consisting of six ground stations. This network provides an information service that is in uninterrupted contact with the spacecraft, allowing for continuos space weather monitoring. A dedicated data processing center will handle all the data, and forward the processed data to the SSA Space Weather Coordination Center. This organization will inform the general public through a space weather forecast. The data processing center will additionally archive the data for the scientific community. This concept mission allows for major advances in space weather forecasting and the scientific modeling of space weather.

Empirical forecast of the quiet time Ionosphere over Europe: a comparative model investigation

NASA Astrophysics Data System (ADS)

Badeke, R.; Borries, C.; Hoque, M. M.; Minkwitz, D.

2016-12-01

The purpose of this work is to find the best empirical model for a reliable 24 hour forecast of the ionospheric Total Electron Content (TEC) over Europe under geomagnetically quiet conditions. It will be used as an improved reference for the description of storm-induced perturbations in the ionosphere. The observational TEC-data were obtained from the International GNSS Service (IGS). Four different forecast model approaches were validated with observational IGS TEC-data: a 27 day median model (27d), a Fourier Analysis (FA) approach, the Neustrelitz TEC global model (NTCM-GL) and NeQuick 2. Two years were investigated depending on the solar activity: 2015 (high activity) and 2008 (low avtivity) The time periods of magnetic storms, which were identified with the Dst index, were excluded from the validation. For both years the two models 27d and FA show better results than NTCM-GL and NeQuick 2. For example for the year 2015 and 15° E / 50° N the difference between the IGS data and the predicted 27d model shows a mean value of 0.413 TEC units (TECU), a standard deviation of 3.307 TECU and a correlation coefficient of 0.921, while NTCM-GL and NeQuick 2 have mean differences of around 2-3 TECU, standard deviations of 4.5-5 TECU and correlation coefficients below 0.85. Since 27d and FA predictions strongly depend on observational data, the results confirm that data driven forecasts perform better than the climatological models NTCM-GL and NeQuick 2. However, the benefits of NTCM-GL and NeQuick 2 are actually the lower data dependency, i.e. they do not lack on precision when observational IGS TEC data are unavailable. Hence a combination of the different models is recommended reacting accordingly to the different data availabilities.

Implementation and Verification of the Chen Prediction Technique for Forecasting Large Nonrecurrent Storms*

NASA Astrophysics Data System (ADS)

Arge, C. N.; Chen, J.; Slinker, S.; Pizzo, V. J.

2000-05-01

The method of Chen et al. [1997, JGR, 101, 27499] is designed to accurately identify and predict the occurrence, duration, and strength of largegeomagnetic storms using real-time solar wind data. The method estimates the IMF and the geoeffectiveness of the solar wind upstream of a monitor and can provide warning times that range from a few hours to more than 10 hours. The model uses physical features of solar wind structures that cause large storms: long durations of southward interplanetary magnetic field. It is currently undergoing testing, improvement, and validation at NOAA/SEC in effort to transition it into a real-time space weather forecasting tool. The original version of the model has modified so that it now makes hourly (as opposed to daily) predictions and has been improved in effort to enhance both its predictive capability and reliability. In this paper, we report on the results of a 2-year historical verification study of the model using ACE real-time data. The prediction performances of the original and improved versions of the model are then compared. A real-time prediction web page has been developed and is on line at NOAA/SEC. *Work supported by ONR.

Stochastic modelling of temperatures affecting the in situ performance of a solar-assisted heat pump: The univariate approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loveday, D.L.; Craggs, C.

Univariate stochastic modeling, using Box-Jenkins methods, is carried out for three air temperatures which can influence the performance of a solar-assisted heat pump system. In this system, external ambient air (the low grade source) is pre-heated by the conventional tiled roof of an occupied domestic residence. The air then crosses the evaporator of an electrically driven split heat pump which is situated in the roof space. Autocorrelation coefficients are presented for time series of the following dry-bulb temperatures: the external air, the residence internal (lounge) air, and the air in the roofspace after pre-heating but prior to crossing the heatmore » pump evaporator. Hourly data relating to a two-week period in the heating season was utilized, providing a 336-h dataset. Univariate models fitted to the first 300 observations were validated by forecasting ahead for the remaining 36 h in steps of 1 h. Comparison of forecasted and measured values showed good agreement, except for a 4-h period in which the intensity of solar radiation exceeded that which prevailed during the modeled period. It is concluded that the Box-Jenkins approach can be used to develop univariate mathematical models which adequately describe building and climate thermal behavior, and that the importance of solar radiation in this respect should not be overlooked.« less

High Quality Data for Grid Integration Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clifton, Andrew; Draxl, Caroline; Sengupta, Manajit

As variable renewable power penetration levels increase in power systems worldwide, renewable integration studies are crucial to ensure continued economic and reliable operation of the power grid. The existing electric grid infrastructure in the US in particular poses significant limitations on wind power expansion. In this presentation we will shed light on requirements for grid integration studies as far as wind and solar energy are concerned. Because wind and solar plants are strongly impacted by weather, high-resolution and high-quality weather data are required to drive power system simulations. Future data sets will have to push limits of numerical weather predictionmore » to yield these high-resolution data sets, and wind data will have to be time-synchronized with solar data. Current wind and solar integration data sets are presented. The Wind Integration National Dataset (WIND) Toolkit is the largest and most complete grid integration data set publicly available to date. A meteorological data set, wind power production time series, and simulated forecasts created using the Weather Research and Forecasting Model run on a 2-km grid over the continental United States at a 5-min resolution is now publicly available for more than 126,000 land-based and offshore wind power production sites. The National Solar Radiation Database (NSRDB) is a similar high temporal- and spatial resolution database of 18 years of solar resource data for North America and India. The need for high-resolution weather data pushes modeling towards finer scales and closer synchronization. We also present how we anticipate such datasets developing in the future, their benefits, and the challenges with using and disseminating such large amounts of data.« less

Real-time Ensemble Forecasting of Coronal Mass Ejections using the WSA-ENLIL+Cone Model

NASA Astrophysics Data System (ADS)

Mays, M. L.; Taktakishvili, A.; Pulkkinen, A. A.; MacNeice, P. J.; Rastaetter, L.; Kuznetsova, M. M.; Odstrcil, D.

2013-12-01

Ensemble forecasting of coronal mass ejections (CMEs) provides significant information in that it provides an estimation of the spread or uncertainty in CME arrival time predictions due to uncertainties in determining CME input parameters. Ensemble modeling of CME propagation in the heliosphere is performed by forecasters at the Space Weather Research Center (SWRC) using the WSA-ENLIL cone model available at the Community Coordinated Modeling Center (CCMC). SWRC is an in-house research-based operations team at the CCMC which provides interplanetary space weather forecasting for NASA's robotic missions and performs real-time model validation. A distribution of n (routinely n=48) CME input parameters are generated using the CCMC Stereo CME Analysis Tool (StereoCAT) which employs geometrical triangulation techniques. These input parameters are used to perform n different simulations yielding an ensemble of solar wind parameters at various locations of interest (satellites or planets), including a probability distribution of CME shock arrival times (for hits), and geomagnetic storm strength (for Earth-directed hits). Ensemble simulations have been performed experimentally in real-time at the CCMC since January 2013. We present the results of ensemble simulations for a total of 15 CME events, 10 of which were performed in real-time. The observed CME arrival was within the range of ensemble arrival time predictions for 5 out of the 12 ensemble runs containing hits. The average arrival time prediction was computed for each of the twelve ensembles predicting hits and using the actual arrival time an average absolute error of 8.20 hours was found for all twelve ensembles, which is comparable to current forecasting errors. Some considerations for the accuracy of ensemble CME arrival time predictions include the importance of the initial distribution of CME input parameters, particularly the mean and spread. When the observed arrivals are not within the predicted range, this still allows the ruling out of prediction errors caused by tested CME input parameters. Prediction errors can also arise from ambient model parameters such as the accuracy of the solar wind background, and other limitations. Additionally the ensemble modeling setup was used to complete a parametric event case study of the sensitivity of the CME arrival time prediction to free parameters for ambient solar wind model and CME.

2008 Solar Technologies Market Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Price, S.; Margolis, R.; Barbose, G.

2010-01-01

The focus of this report is the U.S. solar electricity market, including photovoltaic (PV) and concentrating solar power (CSP) technologies. The report is organized into five chapters. Chapter 1 provides an overview of global and U.S. installation trends. Chapter 2 presents production and shipment data, material and supply chain issues, and solar industry employment trends. Chapter 3 presents cost, price, and performance trends. Chapter 4 discusses policy and market drivers such as recently passed federal legislation, state and local policies, and developments in project financing. Chapter 5 provides data on private investment trends and near-term market forecasts. Highlights of thismore » report include: (1) The global PV industry has seen impressive growth rates in cell/module production during the past decade, with a 10-year compound annual growth rate (CAGR) of 46% and a 5-year CAGR of 56% through 2008. (2) Thin-film PV technologies have grown faster than crystalline silicon over the past 5 years, with a 10-year CAGR of 47% and a 5-year CAGR of 87% for thin-film shipments through 2008. (3) Global installed PV capacity increased by 6.0 GW in 2008, a 152% increase over 2.4 GW installed in 2007. (4) The United States installed 0.34 GW of PV capacity in 2008, a 63% increase over 0.21 GW in 2007. (5) Global average PV module prices dropped 23% from $4.75/W in 1998 to $3.65/W in 2008. (6) Federal legislation, including the Emergency Economic Stabilization Act of 2008 (EESA, October 2008) and the American Recovery and Reinvestment Act (ARRA, February 2009), is providing unprecedented levels of support for the U.S. solar industry. (7) In 2008, global private-sector investment in solar energy technology topped $16 billion, including almost $4 billion invested in the United States. (8) Solar PV market forecasts made in early 2009 anticipate global PV production and demand to increase fourfold between 2008 and 2012, reaching roughly 20 GW of production and demand by 2012. (9) Globally, about 13 GW of CSP was announced or proposed through 2015, based on forecasts made in mid-2009. Regional market shares for the 13 GW are about 51% in the United States, 33% in Spain, 8% in the Middle East and North Africa, and 8% in Australasia, Europe, and South Africa. Of the 6.5-GW project pipeline in the United States, 4.3 GW have power purchase agreements (PPAs). The PPAs comprise 41% parabolic trough, 40% power tower, and 19% dish-engine systems.« less

A long-duration active region: Evolution and quadrature observations of ejective events

NASA Astrophysics Data System (ADS)

Cremades, H.; Mandrini, C. H.; Fuentes, M. C. López; Merenda, L.; Cabello, I.; López, F. M.; Poisson, M.

2017-10-01

Unknown aspects of the initiation, evolution, and associated phenomena of coronal mass ejections (CMEs), together with their capability of perturbing the fragile technological equilibrium on which nowadays society depends, turn them a compelling subject of study. While space weather forecasts are thus far not able to predict when and where in the Sun will the next CME take place, various CME triggering mechanisms have been proposed, without reaching consensus on which is the predominant one. To improve our knowledge in these respects, we investigate a long-duration active region throughout its life, from birth until decay along five solar rotations, in connection with its production of ejective events. We benefit from the wealth of solar remote-sensing data with improved temporal, spatial, and spectral resolution provided by the ground-breaking space missions STEREO, SDO, and SOHO. During the investigated time interval, which covers the months July - November 2010, the STEREO spacecraft were nearly 180 degrees apart, allowing for the uninterrupted tracking of the active region and its ensuing CMEs. The ejective aspect is examined from multi-viewpoint coronagraphic images, while the dynamics of the active region photospheric magnetic field are inspected by means of SDO/HMI data for specific subintervals of interest. The ultimate goal of this work in progress is to identify common patterns in the ejective aspect that can be connected with the active region characteristics.

Electricity forecasting on the individual household level enhanced based on activity patterns

PubMed Central

Gajowniczek, Krzysztof; Ząbkowski, Tomasz

2017-01-01

Leveraging smart metering solutions to support energy efficiency on the individual household level poses novel research challenges in monitoring usage and providing accurate load forecasting. Forecasting electricity usage is an especially important component that can provide intelligence to smart meters. In this paper, we propose an enhanced approach for load forecasting at the household level. The impacts of residents’ daily activities and appliance usages on the power consumption of the entire household are incorporated to improve the accuracy of the forecasting model. The contributions of this paper are threefold: (1) we addressed short-term electricity load forecasting for 24 hours ahead, not on the aggregate but on the individual household level, which fits into the Residential Power Load Forecasting (RPLF) methods; (2) for the forecasting, we utilized a household specific dataset of behaviors that influence power consumption, which was derived using segmentation and sequence mining algorithms; and (3) an extensive load forecasting study using different forecasting algorithms enhanced by the household activity patterns was undertaken. PMID:28423039

Electricity forecasting on the individual household level enhanced based on activity patterns.

PubMed

Gajowniczek, Krzysztof; Ząbkowski, Tomasz

2017-01-01

Leveraging smart metering solutions to support energy efficiency on the individual household level poses novel research challenges in monitoring usage and providing accurate load forecasting. Forecasting electricity usage is an especially important component that can provide intelligence to smart meters. In this paper, we propose an enhanced approach for load forecasting at the household level. The impacts of residents' daily activities and appliance usages on the power consumption of the entire household are incorporated to improve the accuracy of the forecasting model. The contributions of this paper are threefold: (1) we addressed short-term electricity load forecasting for 24 hours ahead, not on the aggregate but on the individual household level, which fits into the Residential Power Load Forecasting (RPLF) methods; (2) for the forecasting, we utilized a household specific dataset of behaviors that influence power consumption, which was derived using segmentation and sequence mining algorithms; and (3) an extensive load forecasting study using different forecasting algorithms enhanced by the household activity patterns was undertaken.