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This chpater reviews the use of spatial-temporal models in identifying potential risks of plague outbreaks into the human population. Using earth observations by satellites remote sensing there has been a systematic analysis and mapping of the close coupling between the vectors of the disease and climate variability. The overall result is that incidence of plague is correlated to positive El Nino/Southem Oscillation (ENSO).
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We have been developing a simplified spatial-temporal discrimination model similar to our simplified spatial model in that masking is assumed to be a function of the local visible contrast energy. The overall spatial-temporal sensitivity of the model is calibrated to predict the detectability of targets on a uniform background. To calibrate the spatial-temporal integration functions that define local visible contrast energy, spatial-temporal masking data are required. Observer thresholds were measured (2IFC) for the detection of a 12 msec target stimulus in the presence of a 700 msec mask. Targets were 1, 3 or 9 c/deg sine wave gratings. Masks were either one of these gratings or two of them combined. The target was presented in 17 temporal positions with respect to the mask, including positions before, during and after the mask. Peak masking was found near mask onset and offset for 1 and 3 c/deg targets, while masking effects were more nearly uniform during the mask for the 9 c/deg target. As in the purely spatial case, the simplified model can not predict all the details of masking as a function of masking component spatial frequencies, but overall the prediction errors are small.
Abstract Objective The study was designed to assess long-term variability in the distribution of juvenile Pacific salmon Oncorhynchus spp. and Sablefish Anoplopoma fimbria. The study also evaluated whether Sablefish and Pacific salmon shared food resources and looked to characterize Sablefish during an understudied period of their life cycle. Methods To meet the objectives, the study used data from 26 years of surface trawls conducted in Oregon and Washington coastal waters (1998–2023). Spatial–temporal models were used to measure changes in abundance and distribution of Pacific salmon and Sablefish along with covariates of ocean temperature. The study evaluated trophic characteristics of Pacific salmon and Sablefish from 2020 for differences. The temporal variation in size and diets of Sablefish were also analyzed, along with energy density of fish caught in 2020. Result The spatial–temporal model demonstrated that there has been a nearshore expansion of juvenile Sablefish over the past 26 years that was correlated with increased ocean temperature. The nearshore expansion of Sablefish resulted in increased spatial and trophic overlap with juvenile Pacific salmon. While feeding in nearshore waters, juvenile Sablefish demonstrated competitive feeding advantages over juvenile Pacific salmon during a critical phase of salmonid early marine life history. Juvenile Sablefish exhibited significant ontogenetic diet and energetic shifts, and even the smallest (68–80 mm fork length) were piscivorous. Conclusions If juvenile Sablefish numbers continue to increase relative to Pacific salmon, they could exert more competitive pressure, especially if food resources become limited. Pacific salmon may experience adverse effects from competition, regardless of whether or not juvenile Sablefish, which have recently expanded into nearshore waters, successfully recruit to the adult population.
Complete retention lagoons with wastewater reuse for agricultural purposes may offer sustainability advantages over alternative systems for small communities in semiarid regions. This study quantifies the environmental life cycle impact of adopting agriculture water reuse systems using case study data to estimate operating and building infrastructure impacts and spatial–temporal modeling to quantify resource trade-offs. Water reuse system benefits are highly dependent on supply–storage–demand dynamics. The relative size of irrigated agricultural land to the lagoon size was the most significant factor influencing site water application rates. The benefits are sensitive to changes in air emissions occurring from the agricultural land and further emphasize the importance of proper fertilizer management when adopting water reuse systems. Wastewater reuse from complete retention lagoons reduce life cycle GHG emissions, primarily through excavation reductions, offset fertilizer use, and especially from increased crop yields from wastewater reuse at previously rainfed sites.
As we transition towards a decarbonized economy, the integration of variable renewable energy resources and new demands (e.g., electric vehicles, heat pumps) into the electricity grid places unprecedented pressure on grid operators to effectively anticipate and manage peak load. In this context, machine learning algorithms are proving to be indispensable for accurate short-term load forecasting, a crucial task to address these challenges. This study benchmarks 6 machine learning algorithms, including three neural networks and three tree-based algorithms, across various levels of spatial aggregation and time horizons (1, 4, 8, 24, and 48 h). The central contribution of this work is the comparison and analysis of load forecasting models not only based on statistical metrics, but also based on a novel error metric, which evaluates the cost implications of forecast errors for power system stakeholders. Results show that tree-based models outperform neural networks, based on statistical metrics, and yield less skewed error distributions for most spatial scales. However, through the lens of the novel error metric, neural networks are the more competitive choice, especially for forecast horizons that exceed 8 h. The study concludes with actionable recommendations to grid operators and highlights the need for the development of error metrics that link forecasting accuracy to operational costs. To promote transparency and open science, the datasets and Python code are open-sourced via a supplementary repository.
An observational program was established in 1983 to monitor the spatial and temporal variations in the Jovian atmosphere over short and long time scales. The program involves tracking several different longitudes as they rotate around the planet from one limb to another. This tracking experiment was done at many different wavelengths including the 3-0 S(1) and S(0) hydrogen quadrupole lines as well as several broad band methane absorptions. The June 1983 hydrogen quadrupole data was reduced and equivalent widths were measured for approximately 25 east-west positions across the planet at 7 different latitudes for both wavelengths. The data for the South Tropical Zone (20 deg. S) was modeled extensively and the effects of the various model parameters on the value of the calculated equivalent widths of both lines was measured as a longitude rotated from the east (or morning) limb to the west (or evening) limb. The value of the equivalent width is also quite sensitive to the height of the NH3 cloud top and to the value used for the single scattering albedo. A combination of these parameters changing on a diurnal time scale could also explain these observations. This gradual increase from one limb to the other appears in the data for both the North and South Equatorial Belts as well as the equatorial region and the North Tropical Zone. Models that used only normal hydrogen and models that used only equilibrium hydrogen were studied.
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A document discusses work that obtains a low-dimensional model that captures both temporal and spatial flow by constructing spatial and temporal four-mode models for two classic flow problems. The models are based on the proper orthogonal decomposition at two reference Reynolds numbers. Model predictions are made at an intermediate Reynolds number and compared with direct numerical simulation results at the new Reynolds number.
Seasonal variability of the temperature structure of Uranus is modeled for all latitudes in the .0004 to 2 bar pressure range in anticipation of the Voyager encounter in January 1986. Atmospheric heating in the model results on the one hand from an internal heat source and, on the other hand, from absorption of solar energy by methane and by non-conservative aerosols located between the 0.5 and 2 bar levels. Various cases for the behavior of the internal heat flux are investigated, such as constant with latitude or constrained to yield a time-averaged thermal emission independent of latitude. Meridional transport of heat in the stably stratified atmosphere is not taken into account. The results indicate that the Voyager encounter time, very small north-south temperature asymmetry should be expected. Moreover, the northern hemisphere, although not illuminated, should emit as much energy (within one percent) as the southern hemisphere at this date. At a given latitude, extreme temperatures are reached at the equinoxes. At the poles, seasonal amplitudes of about 10 K in the upper stratosphere and 6 K at the 0.6 bar level are predicted, and the variation with time of the emission to space is found to be at most 20 percent. The atmosphere of Uranus appears to be characterized by very long radiative response times (mainly due to its cold temperature) which inhibit the large seasonal variations that one could otherwise expect in view of the high obliquity of the planet and its long orbital period.
Different implications of employment of the temporal or spatial model in direct numerical simulations of transition based on the complete Navier-Stokes equations are outlined, and it is noted that in situations where approximations are not justified, the temporal model cannot be employed. The discussion is then concentrated on developing numerical methods for solving the Navier-Stokes equations based on the spatial model that are applicable for realistic situations for which the temporal model would not be valid. It is concluded that in the future numerical simulations based on the spatial approach will replace, to a large extent, the temporal simulations.
The application of neural network models to scientific machine learning tasks has proliferated in recent years. In particular, neural networks have proved to be adept at modeling processes with spatial–temporal complexity. Nevertheless, these highly parameterized models have garnered skepticism in their ability to produce outputs with quantified error bounds over the regimes of interest. Hence there is a need to find uncertainty quantification methods that are suitable for neural networks. In this work we present comparisons of the parametric uncertainty quantification of neural networks modeling complex spatial–temporal processes with Hamiltonian Monte Carlo and Stein variational gradient descent and its projected variant. Specifically we apply these methods to graph convolutional neural network models of evolving systems modeled with recurrent neural network and neural ordinary differential equations architectures. We show that Stein variational inference is a viable alternative to Monte Carlo methods with some clear advantages for complex neural network models. For our exemplars, Stein variational interference gave similar pushed forward uncertainty profiles through time compared to Hamiltonian Monte Carlo, albeit with generally more generous variance. As a result, projected Stein variational gradient descent also produced similar uncertainty profiles to the non-projected counterpart, but large reductions in the active weight space were confounded by the stability of the neural network predictions and the convoluted likelihood landscape.
Temporal and spatial fetures of central equatorial Pacific Ocean sea-level variation appear similar, in measurements from two very different systems (one in the ocean and one carried on a satellite), and in results from a numerical model of the region. In particular, there is an interannual cycle: during El Nino, Kelvin waves appear at the equator, and the sea-surface ridge associated with the equatorial current system shifts southward; in non-El Nino years, instability waves appear at 6 deg N (strongest around the end of each calendar year), and the ridge shifts to the north. This three-way comparison gives support to both measurement systems and to the numerical model.
Spatial and temporal variations of surface radiative temperatures of the burned and unburned areas of the Konza tallgrass prairie were studied. The role of management practices, topographic conditions and the uncertainties associated with in situ or airborne surface temperature measurements were assessed. Evaluation of diurnal and seasonal spectral characteristics of the burned and unburned areas of the prairie was also made. This was accomplished based on the analysis of measured spectral reflectance of the grass canopies under field conditions, and modelling their spectral behavior using a one dimensional radiative transfer model.
The paper examines the time-dependent models of the aurora which show that various ionospheric parameters respond to the onset of auroral ionization with different time histories. A pass of the Atmosphere Explorer C satellite over Poker Flat, Alaska, and ground based photometric and photographic observations have been used to resolve the time-space ambiguity of a specific auroral event. The density of the O(+), NO(+), O2(+), and N2(+) ions, the electron density, and the electron temperature observed at 280 km altitude in a 50 km wide segment of an auroral arc are predicted by the model if particle precipitation into the region commenced about 11 min prior to the overpass.
The external (surface incident) charged particle radiation, predicted for the ST satellite at the three different mission altitudes, was determined in two ways: (1) by orbital flux-integration and (2) by geographical instantaneous flux-mapping. The latest standard models of the environment were used in this effort. Magnetic field definitions for three nominal circular trajectories and for the geographic mapping positions were obtained from a current field model. Spatial and temporal variations or conditions affecting the static environment models were considered and accounted for, wherever possible. Limited shielding and dose evaluations were performed for a simple geometry. Results, given in tabular and graphical form, are analyzed, explained, and discussed. Conclusions are included.