Vision for Producing Fresh Water Using Space Power

An escalating climate crisis is stressing the Earth\u27s environment. One significantly affected area is the global water infrastructure that includes hydropower, flood defense, drainage, and irrigation systems. The effect of adverse climate change on freshwater systems aggravates population growth and weakens economic conditions. In the western U.S., for example, reduced water supplies plus increased demand are likely to provoke more interstate and urban-rural competition for over-allocated water resources. Seawater desalination has existed for decades as a proven technology for supplying water in coastal areas; however, desalination processes are energy intensive and this has reduced their widespread use. It is noted that California offshore oil and gas platforms already use seawater desalination to produce fresh water for platform personnel and equipment. It is proposed that as California coastal oil and gas platforms come to the end of their productive lives, they be re-commissioned for use as large-scale fresh water production facilities. Solar arrays, mounted on the platforms, are able to provide some of the power needed for seawater desalination during the daytime. However, for efficient fresh water production, a facility must be operated 24 hours a day. The use of solar power transmitted from orbiting satellites (Solar Power Satellites - SPS) to substantially augment the solar array power generated from natural sunlight is a feasible concept. We discuss the architecture of using a SPS in geosynchronous orbit (GEO) to enable 24 hours a day operations for fresh water production through seawater desalination. Production of industrial quantities of fresh water on re-commissioned oil and gas platforms, using energy transmitted from solar power satellites, is a breakthrough concept for addressing the pressing climate, water, and economic issues of the 21st Century using space assets

A strategic architecture for growing a space economy utilizing foundational space weather

We face unprecedented resource stresses in the 21st Century such as global climate disruptions, freshwater scarcity, expanding energy demands, and the threat of global pandemics. Historically, societies have relieved resource stress by increasing trade, innovating technologically, expanding territorially, regulating, redistributing, making alliances, creating new economic models, training new skills, as well as conducting war. Do we continue depleting our already strained resources leading to more regulation, redistribution, alliances, new economics, and war or do we grow our resources using innovation, expansion, new economics, and new skills? We present the argument for evolving space development using asteroid mining as the primary activity for frontier expansion aided by Low Earth Orbit (LEO), Moon, and Mars waystations. Forecast space weather is a necessary technology baseline for developing this pathway. All activity off Earth will require a fundamental knowledge of how the energetics of space will affect technological progress. We discuss the critical elements this space economy expansion, including technical feasibility and infrastructure development, economic and geopolitical viability complete with the US National Space Weather Program dialogue, ethical and legal considerations, and risk management. This discussion helps us understand how a space economy is feasible with the aggregation of many existing and new technologies into more advanced systems engineering projects.Comment: The Anemomilos Plan is the short titl

Progress Towards Real-Time Radiation Measurements on Aircraft

The Space Weather Center (SWC) at Utah State University has created a team to deploy and obtain radiation effective dose rate data from dosimeters flown on commercial aircraft. The objective is to improve the accuracy of radiation dose and dose rate estimates for commercial aviation flight crews. There are two general sources of radiation exposure for flight crews: (1) the ever-present, background galactic cosmic rays (GCR), which originate outside the solar system, and (2) the solar energetic particle (SEP) events (or solar cosmic rays), which are associated with solar flares and coronal mass ejections lasting for several hours to days with widely varying intensity. The Automated Radiation Measurements for Aviation Safety (ARMAS) project is making substantial progress, currently implementing dosimeters flown in commercial aircraft to provide and improve sample data collected for the Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) estimates. We report on the results of our flights and the calibration of the dosimeters

Benchmarking Forecasting Models for Space Weather Drivers

Space weather indices are commonly used to drive operational forecasts of various geospace systems, including the thermosphere for mass density and satellite drag. The drivers serve as proxies for various processes that cause energy flow and deposition in the geospace system. Forecasts of neutral mass density is a major uncertainty in operational orbit prediction and collision avoidance for objects in low earth orbit (LEO). For the strongly driven system, accuracy of space weather driver forecasts is crucial for operations. The High Accuracy Satellite Drag Model (HASDM) currently employed by the United States Air Force in an operational environment is driven by four (4) solar and two (2) geomagnetic proxies. Space Environment Technologies (SET) is contracted by the space command to provide forecasts for the drivers. This work performs a comprehensive assessment for the performance of the driver forecast models. The goal is to provide a benchmark for future improvements of the forecast models. Using an archived data set spanning six (6) years and 15,000 forecasts across solar cycle 24, we quantify the temporal statistics of the model performance

On the Importance of the Flare's Late Phase for the Solar Extreme Ultraviolet Irradiance

The new solar extreme ultraviolet (EUV) irradiance observations from NASA Solar Dynamics Observatory (SDO) have revealed a new class of solar flares that are referred to as late phase flares. These flares are characterized by the hot 2-5 MK coronal emissions (e.g., Fe XVI 33.5 nm) showing large secondary peaks that appear many minutes to hours after an eruptive flare event. In contrast, the cool 0.7-1.5 MK coronal emissions (e.g., Fe IX 17.1 nm) usually dim immediately after the flare onset and do not recover until after the delayed second peak of the hot coronal emissions. We refer to this period of 1-5 hours after the fl amrea sin phase as the late phase, and this late phase is uniquely different than long duration flares associated with 2-ribbon flares or large filament eruptions. Our analysis of the late phase flare events indicates that the late phase involves hot coronal loops near the flaring region, not directly related to the original flaring loop system but rather with the higher post-eruption fields. Another finding is that space weather applications concerning Earth s ionosphere and thermosphere need to consider these late phase flares because they can enhance the total EUV irradiance flare variation by a factor of 2 when the late phase contribution is included

Science through Machine Learning: Quantification of Poststorm Thermospheric Cooling

Machine learning (ML) is often viewed as a black-box regression technique that is unable to provide considerable scientific insight. ML models are universal function approximators and - if used correctly - can provide scientific information related to the ground-truth dataset used for fitting. A benefit to ML over parametric models is that there are no predefined basis functions limiting the phenomena that can be modeled. In this work, we develop ML models on three datasets: the Space Environment Technologies (SET) High Accuracy Satellite Drag Model (HASDM) density database, a spatiotemporally matched dataset of outputs from the Jacchia-Bowman 2008 Empirical Thermospheric Density Model (JB2008), and an accelerometer-derived density dataset from CHAllenging Minisatellite Payload (CHAMP). These ML models are compared to the Naval Research Laboratory Mass Spectrometer and Incoherent Scatter radar (NRLMSIS 2.0) model to study the presence of post-storm cooling in the middle-thermosphere. We find that both NRLMSIS 2.0 and JB2008-ML do not account for post-storm cooling and consequently perform poorly in periods following strong geomagnetic storms (e.g. the 2003 Halloween storms). Conversely, HASDM-ML and CHAMP-ML do show evidence of post-storm cooling indicating that this phenomenon is present in the original datasets. Results show that density reductions up to 40% can occur 1--3 days post-storm depending on location and the strength of the storm

Resolving Ionospheric E-region Modeling Challenges: The Solar Photon Flux Dependence

The EVE instrument of the NASA Solar Dynamics Observatory (SDO) provides for the first time EUV and XUV measurements of the solar irradiance that adequately define the major source of ionization of the atmosphere. In our study we modeled the E-region of the ionosphere and analyzed how it is affected by the solar irradiance data obtained by EVE and contrast this with the S2000 Solar Irradiance model, used previously. The ionosphere has two major layers, the E-layer at 100 km, and the F-layer at 300 km. The difference in solar irradiances are small except at some wavelength bands, it is these differences that lead to a better understanding of the physical/chemical processes of the E-region. Observations of the ionospheric layers is best achieved using incoherent scatter radars (ISR). We have compared our model with ISR data available from Arecibo Puerto Rico in an effort to understand how specific solar irradiance wavelength bands affect the E-region. This study focuses on two specific wavelength bands 0.1-15 nm and 91-103 nm. Both are responsible for E-region production, but in quite different manners