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The Sun's outer atmosphere, or corona, is heated to millions of degrees, considerably hotter than its surface or photosphere. Explanations for this enigma typically invoke the deposition in the corona of nonthermal energy generated by magnetoconvection. However, the coronal heating mechanism remains unknown. We used observations from the Solar Dynamics Observatory and the Hinode solar physics mission to reveal a ubiquitous coronal mass supply in which chromospheric plasma in fountainlike jets or spicules is accelerated upward into the corona, with much of the plasma heated to temperatures between approximately 0.02 and 0.1 million kelvin (MK) and a small but sufficient fraction to temperatures above 1 MK. These observations provide constraints on the coronal heating mechanism(s) and highlight the importance of the interface region between photosphere and corona.

Using temperature data measured by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument from February 2002 to March 2020, the temperature linear trend and temperature responses to the solar cycle (SC), quasi-biennial oscillation (QBO), and El Niño–Southern Oscillation (ENSO) were investigated from 20 to 110 km for the latitude range of 50°S–50°N. A four-component harmonic fit was used to remove the seasonal variation from the observed monthly temperature series. Multiple linear regression (MLR) was applied to analyze the linear trend, SC, QBO, and ENSO terms. In this study, the near-global mean temperature shows consistent cooling trends throughout the entire middle atmosphere, ranging from −0.28 to −0.97 K decade−1. Additionally, it shows positive responses to the solar cycle, varying from −0.05 to 4.53 K per 100 solar flux units. A solar temperature response boundary between 50°S and 50°N is given, above which the atmospheric temperature is strongly affected by solar activity. The boundary penetrates deep below the stratopause to ∼42 km over the tropical region and rises to higher altitudes with latitude. Temperature responses to the QBO and ENSO can be observed up to the uppermesosphere and lower thermosphere. In the equatorial region, 40%–70%of the total variance is explained by QBO signals in the stratosphere and 30%–50% is explained by the solar signal in the uppermiddle atmosphere. Our results, obtained from 18-yr SABER observations, are expected to be an updated reliable estimation of the middle atmosphere temperature variability for the stratospheric ozone recovery period.

The lack of readily available sterilization processes for medicine and dentistry practices in the developing world is a major risk factor for the propagation of disease. Modern medical facilities in the developed world often use autoclave systems to sterilize medical instruments and equipment and process waste that could contain harmful contagions. Here, we show the use of broadband light-absorbing nanoparticles as solar photothermal heaters, which generate high-temperature steam for a standalone, efficient solar autoclave useful for sanitation of instruments or materials in resource-limited, remote locations. Sterilization was verified using a standard Geobacillus stearothermophilus-based biological indicator.

Observed changes in climate of the U.S. Pacific Northwest since the early twentieth century were examined using four different datasets. Annual mean temperature increased by approximately 0.6°–0.8°C from 1901 to 2012, with corroborating indicators including a lengthened freeze-free season, increased temperature of the coldest night of the year, and increased growing-season potential evapotranspiration. Seasonal temperature trends over shorter time scales (<50 yr) were variable. Despite increased warming rates in most seasons over the last half century, nonsignificant cooling was observed during spring from 1980 to 2012. Observations show a long-term increase in spring precipitation; however, decreased summer and autumn precipitation and increased potential evapotranspiration have resulted in larger climatic water deficits over the past four decades. A bootstrapped multiple linear regression model was used to better resolve the temporal heterogeneity of seasonal temperature and precipitation trends and to apportion trends to internal climate variability, solar variability, volcanic aerosols, and anthropogenic forcing. The El Niño–Southern Oscillation and the Pacific–North American pattern were the primary modulators of seasonal temperature trends on multidecadal time scales: solar and volcanic forcing were nonsignificant predictors and contributed weakly to observed trends. Anthropogenic forcing was a significant predictor of, and the leading contributor to, long-term warming; natural factors alone fail to explain the observed warming. Conversely, poor model skill for seasonal precipitation suggests that other factors need to be considered to understand the sources of seasonal precipitation trends.

NASA’s Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) instrument produced about 17 years of daily average Spectral Solar Irradiance (SSI) data for wavelengths 240 nm – 2416 nm. We choose a day of minimal solar activity, 2008-08-24, during the 2008 − 2009 minimum between cycles 23 and 24, and compute the brightness temperature (𝑇o) from that day’s solar spectral irradiance (𝑆𝑆𝐼o). We consider small variations of T and SSI about these reference values, and derive linear and quadratic analytic approximations by Taylor expansion about the reference day values. To determine approximation accuracy, we compare to exact brightness temperatures T computed from the Planck spectrum, by solving analytically for T, or equivalent root-finding in Wolfram Mathematica. We find that the linear analytic approximation overestimates, while the quadratic underestimates the exact result. This motivates search for statistical “fit” models “in between” the two analytic models, with minimum root-mean-square-error RMSE. We make this search using open-source statistical R software, determine coefficients for linear and quadratic fit models, and compare statistical with analytic RMSE’s. When only linear analytic and fit models are compared, the fit model is superior at ultraviolet, visible, and near infrared wavelengths. This again holds true when comparing only quadratic models. Quadratic is superior to linear for both analytic and statistical models, and statistical fits give smallest RMSE’s. Lastly, we use linear analytic and fit models to find an interpolating function in wavelength, useful in case the SIM results need adjustment to another choices of wavelengths, to compare or extend to any other instrument.

Based on transient temperature field theory of heat conduction, the solar temperature field calculation model of U-shape sectioned high-speed railway cable-stayed bridge under actions of concrete beams and ballast was established. Using parametric programming language, finite element calculation modules considering climate conditions, bridge site, structure dimension and material thermophysical properties were compiled. Six standard day cycles with the strongest yearly radiation among the bridge sites were selected for sectional solar temperature field calculation and temperature distributions under different temperature-sensitive parameters were compared. The results show that under the influence of sunshine, U-shape section of the beam shows obvious nonlinear distribution characteristics and the maximum cross-section temperature difference is more than 21 °C; the ballast significantly reduces sunshine temperature difference of the beam and temperature peak of the bottom margin lags with the increase of ballast thickness; the maximum cross-section vertical temperature gradient appears in summer while large transverse temperature difference appears in winter.

The potential role of solar variations in modulating recent climate has been debated for many decades and recent papers suggest that solar forcing may be less than previously believed. Because solar variability before the satellite period must be scaled from proxy data, large uncertainty exists about phase and magnitude of the forcing. We used a coupled climate system model to determine whether proxy-based irradiance series are capable of inducing climatic variations that resemble variations found in climate reconstructions, and if part of the previously estimated large range of past solar irradiance changes could be excluded. Transient simulations, covering the published range of solar irradiance estimates, were integrated from 850 AD to the present. Solar forcing as well as volcanic and anthropogenic forcing are detectable in the model results despite internal variability. The resulting climates are generally consistent with temperature reconstructions. Smaller, rather than larger, long-term trends in solar irradiance appear more plausible and produced modeled climates in better agreement with the range of Northern Hemisphere temperature proxy records both with respect to phase and magnitude. Despite the direct response of the model to solar forcing, even large solar irradiance change combined with realistic volcanic forcing over past centuries could not explain the late 20th century warming without inclusion of greenhouse gas forcing. Although solar and volcanic effects appear to dominate most of the slow climate variations within the past thousand years, the impacts of greenhouse gases have dominated since the second half of the last century.

A record from Wanxiang Cave, China, characterizes Asian Monsoon (AM) history over the past 1810 years. The summer monsoon correlates with solar variability, Northern Hemisphere and Chinese temperature, Alpine glacial retreat, and Chinese cultural changes. It was generally strong during Europe's Medieval Warm Period and weak during Europe's Little Ice Age, as well as during the final decades of the Tang, Yuan, and Ming Dynasties, all times that were characterized by popular unrest. It was strong during the first several decades of the Northern Song Dynasty, a period of increased rice cultivation and dramatic population increase. The sign of the correlation between the AM and temperature switches around 1960, suggesting that anthropogenic forcing superseded natural forcing as the major driver of AM changes in the late 20th century.

The paper presents the Simulator for Investigation of Solar Temperature Error of Radiosondes (SISTER), a setup that was developed to quantify the solar heating of the temperature sensor of radiosondes under laboratory conditions by recreating as closely as possible the atmospheric and illumination conditions that are encountered during a daytime radiosounding ascent. SISTER controls the pressure (3 to 1020 hPa) and ventilation speed of the air inside the wind-tunnel-like setup to simulate the conditions between the surface and 35 km altitude, to determine the dependence of the radiation temperature error on the irradiance and the convective cooling. The radiosonde is mounted inside a quartz tube, while the complete sensor boom is illuminated by an external light source to include the conductive heat transfer between sensor and boom. A special feature of SISTER is that the radiosonde is rotated around its axis to imitate the spinning of the radiosonde in flight. The characterisation of the radiation temperature error is performed for various pressures, ventilation speeds, and illumination angles, yielding a 2D parameterisation of the radiation error for each illumination angle, with an uncertainty smaller than 0.2 K (k=2) for typical ascend speeds. This parameterisation is applied in the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) processing for radiosonde data, which relies on the extensive characterisation of the sensor properties to produce a traceable reference data product which is free of manufacturer-dependent effects. The GRUAN radiation correction model combines the laboratory characterisation with model calculations of the actual radiation field during the sounding to estimate the correction profile. In the second part of this paper it is described how this procedure was applied in the development of the GRUAN data product for the Vaisala RS41 radiosonde (version 1, RS41-GDP.1). The magnitude of the averaged correction profile increases gradually from 0.1 K at the surface to approximately 0.8 K at 35 km altitude. Comparisons between sounding data (N=154) that were GRUAN-processed and Vaisala-processed reveal that the daytime differences (GRUAN−Vaisala) are smaller than +0.1 K in the troposphere and increase above the tropopause steadily with altitude to +0.35 K at 35 km. These differences are just within the limits of the combined uncertainties (with coverage factor k=2) of both data products, meaning that the GRUAN processing and the Vaisala processing are in agreement.

The Sun's outer coronal layer exists at a temperature of millions of kelvins, much hotter than the solar surface we observe. How this high temperature is maintained and what energy sources are involved continue to puzzle and fascinate solar researchers. Recently, the Hinode spacecraft was launched to observeand measure the plasma properties of the Sun's outer layers. The data collected by Hinode reveal much about the role of magnetic field interactions and how plasma waves might transport energy to the corona. These results open a new era in high-resolution observation of the Sun.