Changes In Total Irradiance Research Articles

Solar Transposition Modeling via Deep Neural Networks With Sky Images

This article presents a notable advance toward the development of a new method of increasing the single-axis tracking photovoltaic (PV) system power output by improving the determination and near-term prediction of the optimum module tilt angle. The tilt angle of the plane receiving the greatest total irradiance changes with Sun position and atmospheric conditions including cloud formation and movement, aerosols, and particulate loading, as well as varying albedo within a module's field of view. In this article, we present a multi-input convolutional neural network that can create a profile of plane-of-array irradiance versus surface tilt angle over a full 180 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula> arc from horizon to horizon. As input, the neural network uses the calculated solar position and clear-sky irradiance values, along with sky images. The target irradiance values are provided by the multiplanar irradiance sensor (MPIS). In order to account for varying irradiance conditions, the MPIS signal is normalized by the theoretical clear-sky global horizontal irradiance. Using this information, the neural network outputs an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> -dimensional vector, where <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> is the number of points to approximate the MPIS curve via Fourier resampling. The output vector of the model is smoothed with a Gaussian kernel to account for error in the downsamping and subsequent upsampling steps, as well as to smooth the unconstrained output of the model. These profiles may be used to perform near-term prediction of angular irradiance, which can then inform the movement of a PV tracker.

Active region properties and irradiance variations

Total Solar Irradiance (TSI) has been measured for more than three decades. These observations demonstrate that total irradiance changes on time scales ranging from minutes to years and decades. Considerable efforts have been made to understand the physical origin of irradiance variations and to model the observed changes using measures of sunspots and faculae. In this paper, we study the short-term variations in TSI during the declining portion and minimum of solar cycle 22 and the rising portion of cycle 23 (1993–1998). This time interval of low solar activity allows us to study the effect of individual sunspot groups on TSI in detail. In this paper, we indicate that the effect of sunspot groups on total irradiance may depend on their type in the Zürich classification system and/or their evolution, and on their magnetic configuration. Some uncertainties in the data and other effects are also discussed.

Reconstruction of solar irradiance variations in cycle 23: Is solar surface magnetism the cause?

A model of solar irradiance variations is presented which is based on the assumption that solar surface magnetism is responsible for all total irradiance changes on time scales of days to years. A time series of daily magnetograms and empirical models of the thermal structure of magnetic features (sunspots, faculae) are combined to reconstruct total (and spectral) irra- diance from 1996 to 2002. Comparisons with observational data reveal an excellent correspondence, although the model only contains a single free parameter. This provides strong support for the hypothesis that solar irradiance variations are caused by changes in the amount and distribution of magnetic flux at the solar surface.

Stellar Irradiance Variations

The variability of several dozen stars similar to the Sun in mass, age, and average activity has been monitored regularly in chromospheric Ca II HK emission for over three decades, and photometrically for over fifteen years. Larger samples have been observed less comprehensively. Analogous solar time series exist. A comparison of solar variability with its stellar analogs indicates that the Sun's current behavior is not unusual among sunlike stars. Both solar models and stellar measurements suggest that a true luminosity variation underlies the cyclic total irradiance changes observed on the Sun.

Inference of Solar Irradiance Variability from Terrestrial Temperature Changes, 1880–1993: An Astrophysical Application of the Sun‐Climate Connection

Information can be inferred on the timing and amplitude of solar total irradiance changes over 1880- 1993 by simulating the global terrestrial surface temperature changes produced by these irradiance changes and comparing them with observed temperatures. The profiles of solar irradiance variations used in the climate simulations are adopted from several different proxies: (1) the length of the sunspot cycle, (2) the mean sunspot number, and (3) a composite proxy that includes the two previous indicators plus the equatorial solar rotation rate, the fraction of penumbral spot coverage, and the rate of decay of the sunspot cycle. We use a seasonal energy-conservation climate/upwelling-diffusion ocean model, forced by the assumed profiles of solar total irradiance variations, combined with variations in anthropogenic greenhouse gases. Optimized cases imply total irradiance changes during 1880-1993 in the range 0.18%-0.77%.If the solar irradiance profiles found from the climate simulations are required to be consistent with recent satellite observations, then the composite solar profile reconstructed by Hoyt & Schatten, combined with the anthropogenic greenhouse forcing, explains the highest fraction of the variance of observed global mean temperatures. In this case, the solar and greenhouse combination accounts for 92% of the observed long-term temperature variance during 1880-1993. The simulation implies that the solar part of the forcing alone would account for 71% of the global mean temperature variance, compared to 51% for the greenhouse gases' part alone. It also suggests a solar total irradiance variation of 0.5% during the interval 1880-1993. Such an amplitude of solar total irradiance change is consistent with astrophysical limits of brightness changes on timescales of decades to centuries independently derived from observations of solar-type stars (including the Sun).

Modelling the climatic response to solar variability

The Sun, the primary energy source driving the climate system, is known to vary in time both in total irradiance and in spectral composition in the ultraviolet. According to solar interior evolution models, the solar luminosity has increased steadily by 25-30% over the past 4 x 109years. Periodic variations are also suspected with characteristic timescales of 11 or 22 years, 80-90 years and possibly longer periods. The ultraviolet radiation below 300 nm also exhibits significant changes over the 27-day solar rotation period as well as the 11-year solar cycle. Variations in the solar constant are expected to produce both direct and indirect (feedback) perturbations in the global surface temperature. A hierarchy of zero- to three-dimensional models have been used to study the complex couplings involved by such effects. The response of a zonally averaged model to possible total irradiance changes associated with the Gleissberg cycle is investigated and compared with measurements of the sea-surface temperature made since 1860. Changes in the solar ultraviolet irradiance modulate the amount and distribution of atmospheric ozone, which is predicted to change by several percent in the stratosphere. These perturbations directly affect the middle atmospheric thermal structure, but may also generate indirect effects that could possibly account for some short-term geophysical signatures of solar activity. The cycle-modulated energetic particle interaction with the middle atmosphere is also a possible source of global climatic perturbations.

Light Responses of a Submersed Macrophyte: Implications For Survival in Turbid Tidal Waters

Responses and acclimation of the submersed vascular plant Potamogeton perfoliatus L. to changes in total irradiance were investigated by growing replicate plant populations under neutral density screens to create three treatment levels (11, 32, and 100% of ambient). Changes in the relationship between photosynthesis and irradiance (P—I) were monitored during a 17—d treatment period and to 16—d "recovery" period, as were concentrations of photosynthetic pigments and several morphological features. Both initial slope of P—I relations and leaf chl a content increased significantly within 3 d after the beginning of shade treatment. These responses, which represent mechanisms of increasing photosynthetic efficiency at low irradiance, were also reversed within 3 d after treatment removal. Significant morphological responses to the recovery from shade were evident within 10 d, including: elongation of stems, thinning of lower leaves, and canopy formation at the water surface. Preliminary calculations indicate that both photosynthetic and morphological acclimations to shade conferred substantial improvements in P. perfoliatus production at experimentally reduced irradiance compared to pretreatment conditions. Significant decreases in plant stem density, biomass, and reproduction, as well as increases in mortality, were observed for plants at low (but not medium) growth irradiance. The inability of populations treated at low irradiance to exhibit any recovery (i.e., posttreatment increases) in these variables after 16 d of full ambient light suggests that 11% of ambient irradiance was below the minimum level needed for survival of this plant. Time scales for significant shade acclimation responses were comparable to the temporal scales of changes in light climate for aquatic ecosystems such as Chesapeake Bay. It is argued that, although stem elongation is a beneficial response to shade for P. perfoliatus in turbid lakes, it may be nonadaptive in turbulent tidal waters because of increased susceptibility to fragmentation.