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110 results for “solar radiation”
Solar radiation data from benchmark stations at the HJ Andrews Experimental Forest, 1973 to present
A three-level hydro-climatological network for data monitoring was established in 1994. The networks at each level are nested to form a coordinated program of data acquisition and measurement. A future vision of linking the benchmark meteorological stations with regional weather stations to expand the future scope of studies was also considered in designing this network. The first-level in this top-down approach consists of Benchmark Meteorological Stations (BMS) and Benchmark Stream Stations. The BMS are designed to represent the environment across the Andrews. These stations are intended to provide complete, long-term, high temporal resolution, meso-scale hydroclimatological data. The location of the BMS network is based on factors such as elevation, aspect, vegetation gradients, and accessibility. Collected meteorological parameters are generally standardized across the BMS as well as methods and instrumentation. Secondary Meteorological Stations also follow standardized methods and serve similar purposes but are somewhat limited in meteorological parameters collected. The Primary Meteorological Station (PRIMET), Central Meteorological Station (CENMET), Upper Lookout Meteorological Station (UPLMET), and Vanilla Leaf Meteorological Station (VANMET) are the four Benchmark Stations, Climatic Station at Watershed 2 (CS2MET), and the Hi-15 Meteorological Station (H15MET) are Secondary Stations. In 2006, an additional Secondary Station was added at Watershed 7 (WS7MET) These solar radiation parameters were previously part of database code MS001, but were separated out into their own database in 2024 and the entities and attributes were reorganized in 2025 into shortwave, longwave, net radiation and PAR. The shortwave and longwave entities include both incoming and outgoing radiation where measured (see probe_code and method_code).
Hubbard Brook Experimental Forest: Daily Solar Radiation Measurements, 1959 - present
Daily solar radiation has been measured at Hubbard Brook Experimental Forest Headquarters since 1959, using several different sensors. Radiation was recorded continuously first by a Belfort pyranograph and later by a Weather Measure pyranograph. The pyranograph has been at its current Headquarter location since 1960 and before that at weather station 1, near weir 1. With the installation of the automatic weather station in 1981, a LiCor pyranometer was collocated with the pyranograph and used as the primary radiation sensor. In April, 2018 the LiCor sensor was exchanged for an Apogee SP230 light sensor. Data checking was done on the entire record and values flagged when changes were made to previously posted, erroneous or missing data. These data are gathered at the Hubbard Brook Experimental Forest in Woodstock, NH, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Discrete water temperature, flow, solar radiation, chlorophyll-a and inundation, Sacramento-San Joaquin Delta, CA, 1999-2019
The objective of our study is to better understand the factors affecting chlorophyll-a production within a floodplain and its transport downstream to determine how lateral connectivity influences longitudinal connectivity. The Yolo Bypass is an engineered floodplain of the Sacramento River that inundates during periods of high outflow via overtopping weirs. Water traveling through the Yolo Bypass flows parallel to the Sacramento River and re-connects to the mainstem at the southern extent of the floodplain. Several monitoring programs in the Sacramento San-Joaquin Delta and Yolo Bypass collect discrete and continuous water quality data, including chlorophyll measurements. For this study, we synthesized available flow, water temperature, chlorophyll and inundation data between March 1999 to December 2019 and modeled the effects of environmental variables and inundation on chlorophyll-a production in the floodplain, the mainstem, and downstream of the floodplain/mainstem.
Hubbard Brook Experimental Forest: 15 Minute Solar Radiation Measurements, 2014 - present
Beginning in 2014, solar radiation sensors were implemented at the Hubbard Brook Experimental Forest to measure solar radiation at 15-minute intervals. Two collocated LiCor sensors were installed at Station 1 in July 2014. The 15-minute record for Headquarters begins in 2018 with a single sensor. These data were gathered at the Hubbard Brook Experimental Forest in Woodstock, NH, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Spectral transmittance of solar radiation by screens and nets used in horticulture and agriculture
<p>We present a dataset of measurement of the spectral transmittance of 197 horticultural nets and screens from five companies. These materials span a range of uses from shading and reducing the heat load on plants to blocking pests such as birds and insects. Routinely, these materials are used in greenhouses and polytunnels to reduce the sunlight received by plants, however their spectral transmittance is not routinely measured. The spectral irradiance that plants receive can affect plant growth and photomorphogenesis, hence this information is of value when selecting the most appropriate material for a given purpose. The spectral transmittance of the materials was measured outdoors close to solar noon using an array spectrometer calibrated for the range 290-900 nm and compared directly with the ambient solar spectral irradiance. The measured spectrum encompasses those regions perceived by plants through known photoreceptors and used by plants in photosynthesis: ultraviolet (UV); photosynthetically active radiation (PAR), and near infra red (far red – FR).</p> <p>The solar spectral photon irradiance (μmol m<sup>-2</sup> s<sup>-1</sup>) transmitted by screens and nets from several manufacturers was measured with an array spectroradiometer. Our measurements and analyses are focused on the differences in spectral irradiance, created when employing these screens and nets, in order to address the lack of detailed studies of these light environments, rather than the physiochemical properties of materials or their cost-effectiveness. The measurements of spectral irradiance under climate screens, and shade and insect nets, were made on clear days in sunny conditions close to solar noon (between 10 a.m. to 2 p.m local time) at NC State University campus (35.78°N, -78.67°W) in late July and early August 2017, and in Viikki Field Plots at the University of Helsinki (60.22°N, 25.01°E, 55 m asl) in July and August 2018. The methods for measurements at North Carolina State University follow the protocol described below and published in <a href="https://doi.org/10.1371/journal.pone.0199628">Kotilainen et al., (2018)</a>, where a comprehensive assessment of the results of this subset of screens/nets and their meaning is also given.</p> <p>The measurements were performed in an open field with no surrounding structures or buildings within 20 m. Repeated measurements of each different sample were made in a randomised order, thus ensuring comparability among measurements. Measurements were made on a tripod 0.7 m above the ground and the sample was secured to a wooden plate 3 cm above the diffusor. A test, comparing four larger (1 x 1 m) samples against those of the standard dimensions that we used, found that the area of screen/net measured did not affect the results at this distance between the screen/net and diffusor. Thus, there was no evidence that unfiltered diffuse or scattered radiation interfered with measurements despite the relatively small dimensions of the sample.</p> <p>Measurements under each screen/net sample in 2017 (Svensson 13 x 19 cm, Mallas Textiles 8 x 10 cm) were made twice to account for any possible effect of sample placement over the cosine diffuser and change in the sun angle during a set of measurements. Given that no significant differences were evidence, the 2018 screen/net samples (Criado y Lopez 8 x 12 cm, Howitec 15 x 25 cm, Huachang yarns 25 x 30 cm, and Jiangsu Huachang Yarns and Fabrics 8 x 12 cm) were only measurement once. A recording of spectral irradiance without the screen/net of filtered sunlight was made directly before and after each filter measurement (called “Open”).</p> <p>The spectrometer used had been calibrated for measurements of UV and visible solar radiation (Maya2000 Pro Ocean Optics, Dunedin, FL, USA; D7-H-SMA cosine diffuser, Bentham Instruments Ltd, Reading, UK - see <a href="https://doi.org/10.1002/ece3.4496">Hartikainen et al., 2018</a> for details of the measurement protocol). Briefly, each measurement of irradiance transmitted beneath a screen or net was followed by sequence of measurements in the dark and with a polycarbonate filter attenuating all UV radiation. These controls accounted for the dark noise and stray light in the UV waveband. Both a correction for the shape of the slit function and for stray light were included in the post-processing of the spectra (<a href="http://uv4plants.org/methods/how-to-check-an-array-spectrometer/">Aphalo et al., 2016</a>). Bracketing was performed by taking a measurement of the UV region and splicing this together this the entire spectrum. All measurements were processed using the Photobiology packages in R.</p> <p>Measurements of solar spectral irradiance in the wavelength range from 290 nm to 900 nm were processed in R, using the <em>photobiology</em> packages developed for spectral analysis (<a href="https://doi.org/10.19232/uv4pb.2015.1.14">Aphalo, 2015</a>). We present spectral photon irradiance (μmol m<sup>-2</sup> s<sup>-1</sup>) and spectral energy irradiance (W m<sup>-2</sup>). Plants absorbs photons producing a chemical change (Grotthus Law) thus photon irradiance is more easily applicable understanding to biological processes in plants. The spectral transmittance of the screens/nets are the most useful data presented. Essentially the patterns of spectral attenuation will be consistent, irrespective of whether spectra are expressed as photon or energy irradiance.</p> <p>Utilizing predefined functions available in the <em>photobiology</em> packages, we calculated the integrals and photon ratios of these integrals as follows: UVB:PAR 280–315 nm/400-700 nm, UVA:PAR 315–400 nm/400-700 nm, blue:green (B:G) 420–490 nm/500-570 nm, blue:red (B:R) 420–490 nm/620-680 nm. Red and far-red for the calculation of R:FR ratio are 655–665 nm and 725–735 nm, respectively. UVB radiation and UVA radiation are defined according to ISO, blue, green and red according to <a href="https://doi.org/10.1104/pp.110.160820">Sellaro et al. (2010)</a>, and R:FR according to <a href="https://doi.org/10.1146/annurev.pp.33.060182.002405">Smith(1982)</a>.</p> <p>The same definitions of the UV-waveband are maintained for both spectral integrals and their ratios throughout, i.e. according to ISO, (<a href="http://doi:%2010.21273/HORTTECH03648-16">Both et al., 2017</a>). This is because the UVB and UVA wavebands of solar radiation follow distinct daily patterns of variation; UVB irradiance is highest during the four hours around solar noon, whereas the UVA region of solar radiation remains a similar proportion of total irradiance throughout the day. These differences also imply that UVA and UVB radiation follow different diurnal and seasonal patterns of variation (<a href="https://doi.org/10.1111/j.1751-1097.2007.00216.x">Seckmeyer et al., 2007</a>).</p> <p><strong>Data Files Available</strong></p> <p><strong>DataBaseScreensNets.zip</strong></p> <p>Graphs (.jpg files) of actual measured (1) spectral energy irradiance, (2) spectral photon irradiance, and (3) proportion transmittance of solar radiation, for each screen and net. (1) Energy Irradiance figures (suffix _EI.) and (2) Photon Irradiance figures (suffix _PI.) are plot of the measured values of irradiance under the filter (screen/net) and corresponding measurements without the screen or net (“open” measurement) for comparison (290-898 nm wavelength range). The proportion transmittance under each screen or net is calculated from comparison of the open and measured spectrum (suffix _Trans). The low-wavelength tail end of the spectrum is trimmed (<310 nm) in each plots since % transmittance are inflated by low signal to noise ratio in the UV-B region where irradiance values are very low.</p> <p>The database screens and net are identified by the name of the company “_” name of the screen/net for all 197 materials.</p> <p>These figures can be reproduced from the file “ScreensNets_irrad_trans.txt” using the R code “Plotting_DataBaseScreensNets.r”</p> <p><strong>ImagesScreensNets.zip</strong></p> <p>Image files (.jpg files) from photos and scans of each of the measured screens and nets. One image from each of the 197 filter materials (screens/nets) measured is stored in folders arranged according to the company for each filter type. The companies are: Criado y Lopez; HowiTech; Huanchang yarns; Jiangsu Huachang Yarns & Fabrics; Mallas_Textiles and Svensson.</p> <p><strong>ScreensNets_irrad_trans.txt</strong></p> <p>This is the main database file containing the measurements of spectral irradiance beneath each filter material (screen/net) from 290 nm – 898 nm and corresponding open reading, and calculated spectral transmittance.</p> <p>Data are in columns as follows: (A) Company – the Company name; (B) FilterName – the filter name as given by the company; (C) Serial - a serial number, effectively equivalent to the order in which the materials were measured; (D) wavelength – at intervals recorded by the array spectrometer running for each spectrum from 290.02 nm to 897.73 nm; (D) FilterEI - energy irradiance of transmitted solar radiation measured 3 cm beneath the filter material (screen/net) at each wavelength of the spectrum; (E) FilterPI – photon irradiance equivalent to the energy irradiance; (F) OpenEI – energy irradiance of solar radiation at the same location without the filter material (screen/net) (G) OpenPI – photon irradiance equivalent to the energy irradiance; (H) FilterFactor – the proportion of radiation transmitted by the filter material (screen/net) at each wavelength measured, a value between 0.0 and 1.0 (values out of range at low wavelengths in the UV-B region are replaced with 0.0 or 0.1).</p> <p>Processed spectra are given: processing of raw spectra was done with <em>Photobiology</em> packages in R. Full spectra were recorded with an integration time set manually to give maximum counts of just less than 60 000 at the wavelength corresponding to peak spectral irradiance. Bracketing was performed by recording a second spectrum (long spectrum) with ten-times longer integration time than this, to achieve greater accuracy of measurement in the UV region (< 400 nm). These two spectra were spliced together. Each filter measurement was accompanied by a dark measurement (to estimate dark noise) and a measurement under a polycarbonate filter (PC) to correct for stray light. In 2018, these two readings were performed immediately after the filter material (screen/net) was measured; both within 10 s total of the filter material measurement for both the full spectrum, and long spectrum.</p> <p><strong>ScreensNets_irrad_trans.xlsx</strong></p> <p>This Excel file contains the same information in columns as the file ScreensNets_irrad_trans.txt but with a second worksheet showing the trimming calculations for out-of-range readings at low UV-B wavelength and with an addition final column, the irradiance spectrum open29_irrad (described below).</p> <p><strong>Open29_irrad.txt</strong></p> <p>In order to obtain standardised BSWF files to comparison with each other, the calculated proportion spectral transmittance results for each filter material (screen/net) were applied to a “standard” solar-noon open-spectrum from Helsinki recorded on a date close to midsummer (Open29_irrad.txt). This spectrum was measured as described above.</p> <p>This spectrum was measured at Viikki Fields, Helsinki on Wed June 27<sup>th</sup> 2018 at 13:15:33 EEST (Integration Time, 110000 μsec; bracketting x10) in a completely open area.</p> <p>To apply the transmittance data to their own locations, database users should substitute the spectrum from their own location for Open29_irrad.txt to obtain spectral irradiance data for the effects of the filter materials (screens/net) at their site using the R code Calculating_Spectral_Integrals.r</p> <p><strong>ScreensNets_spectral_integrals.txt</strong></p> <p>The file gives a matrix of spectral integrals and ratios calculated with the <em>Photobiology</em> packages in R for each of the spectra presented in ScreensNets_irrad_trans.txt. Column headings are the filter material ID, made up from the “Company name” “_” “filter name”. The first column contains row names identifying spectral integrals and ratios calculated – first as energy irradiance then as photon irradiance and finally as photon ratios. Calculations are made using the BSWF (<strong>Spectral_Integrals_Function.r</strong>) as follows: PAR_e; UVB_e; UVA_e; UVb350_e; UVa350_e; Blue_e; Green_e; Red_e; Far_red_e; GEN_G_e; GEN_T_e; PG_e; DNA_N_e; CIE_e; FLAV_e; Infra_red_e; PAR_q; UVB_q; UVA_q; UVb350_q; UVa350_q; Blue_q; Green_q; Red_q; Far_red_q; GEN_G_q; GEN_T_q; PG_q; DNA_N_q; CIE_q; FLAV_q; Infra_red_q; UVB_UVA; UVB_PAR; UVA_PAR; R_FR_Sellaro; R_FR_Smith10; R_FR_Smith20; B_G; B_R; PhyEqi.</p> <p><strong>ScreensNets_spectral_integrals.xlsx</strong></p> <p>This files contains the same data as ScreensNets_spectral_integrals.txt and shows on individual worksheets, processing of original, smoothed (in Photobiology package to improve the signal to noise in the UV-B tail of the spectr), and corrected (with values of transmittance greater than 1.0 or less than 0.0 replaced in the UV-B tail) data; and comparisons of the Original vs. Corrected, and Original vs. Smoothed data. The same BSWF calculations for the example open spectrum open29_irrad (used for standardisation) are given on their own worksheet, as is the corresponding “FilterFactor” (proportion spectral transmittance) for each spectral integral and spectral photon ratio. The final worksheet “Type” lists the filters and their expected function (i.e. shade, pest net, hale net, ground cover etc.).</p> <p>This “FilterFactor” information could be of practical use in situations where the spectral irradiance is unavailable for a given location, and comparisons among filters need to be made from only partial data (e.g. PAR PPDF). These FilterFactors can be applied to the PAR PPDF for instance to calculate the daily light integral through the day for horticultural proposes. Please note that differences in the shape of the solar spectrum at different locations will cause (small) deviations in the transmitted PAR PPFD calculated from the spectral integral compared with the more precise calculation from the spectral irradiance. Although for the purposes of comparison between filters these are likely to be of minor importance. </p> <p><strong>Plotting_DataBaseScreensNets.r</strong></p> <p>This file gives the R code for plotting the graphs in DataBaseScreensNets.zip from the source file ScreensNets_irrad_trans.txt. Make sure that the required packages are loaded. The code was run in R version 3.4.3.</p> <p><strong>Calculating_Spectral_Integrals.r</strong></p> <p>The file gives the R code to calculate spectral integrals and to include an open measurement for standardisation (Open29_irrad) from the source file ScreensNets_irrad_trans.txt (as described above). The spectra in ScreensNets_irrad_trans.txt are converted to source.spct for use in the Photobiology packages.</p> <p><strong>Spectral_Integrals_Function.r</strong></p> <p>The file is a function requiring the Photobiology packages in R to run. It is needed to calculate the spectral integrals described above and can be amended to obtain whichever spectral integrals and photon ratios from the Photobiology packages are desired.</p>
Quality controlled observations of hourly incoming shortwave radiation data at the surface for solar resource mapping in Norway (2016-2020).
<p>Observed hourly incoming shortwave radiation data at the surface of Norway for the years 2016-2020 along with quality control flags, visualization plots and a descriptive report. The data has been collected, visually inspected and quality controlled within the SunPoint project (SUn in Norway - POtential and INTegration of the solar energy resource, Norwegian Research Council project 320750). The main data source is frost.met.no but some gaps were filled with data directly obtained by the station holders.</p> <p>There are three NetDCF files for 47 stations selected after quality control:</p> <ul> <li>rsds_1hr_selection_v5_2016-2020.nc: Raw data</li> <li>rsds_flagged_1hr_selection_v5_2016-2020.nc: Raw data with flags</li> <li>rsds_cleaned_1hr_selection_v5_2016-2020.nc: Filtered data (i.e. all flagged data has been removed)</li> </ul> <p>and one NetCDF file for all available stations (106 stations)</p> <ul> <li>rsds_1hr_frost_and_more_2016-2020.nc</li> </ul> <p>Version 3.5 of the McClear clear-sky model is used for flagging which reduces the bias to ground measurements compared to earlier versions. </p> <p>The visualization and automated quality control routines are available in the Scripts.zip file (python).</p>
A dataset of global variations in directional solar radiation exposure for ocular research using the libRadtran radiative transfer model
<p>Directional solar photon flux density has particular relevance to eye disease research (keratitis, cataract formation, macula degeneration) because ocular components (cornea, lens, retina) experience different exposures dependent on global location, structural geometry of the eye and human behaviour (Sliney, 1997). The human macula has a field of view of ~17<strong>°</strong>, or 0.06901537 sr (Strasburger, Rentschler & Jüttner, 2011) and its cone of exposure can be modelled at a range of global locations using a radiation transfer model to estimate different directions of irradiation. This dataset provides examples of spectral radiance within the macula field of vision, calculated with the radiative transfer model libRadtran v2.0.3 (Mayer & Kylling, 2005). Three data sets are provided at different latitudes without correction for spectral ocular transmission. Unless otherwise specified, all simulations were parametrized according to local meteorological condition (altitude, pressure, temperature) and atmospheric conditions on the simulated day (aerosol optical density, water column, O<sub>3</sub> and NO<sub>2</sub> concentrations). The model was parametrized for a subject looking northward toward the ground (-15<strong>°</strong> from horizon), at a height of 170 cm above the ground.</p> <p>For each simulation, a separate file is available for each condition (latitude, time, date, see below) that includes radiance at each wavelength. Radiance values are in mW m<sup>-2</sup> nm<sup>-1</sup> sr<sup>-1</sup>.</p> <p>The technique provides future opportunity to model global exposures of different ocular components to spectral solar irradiance using information on ocular transmission, local terrain, albedo and human behaviour in order to explore their relevance in epidemiological studies of age-related eye disease.</p> <p>For each simulation, a separate file is available for each condition (latitude, time, date, see below) that includes radiance at each wavelength. Radiance values are in mW m<sup>-2</sup> nm<sup>-1</sup> sr<sup>-1</sup>.</p> <p>The technique provides future opportunity to model global exposures of different ocular components to spectral solar irradiance using information on ocular transmission, local terrain, albedo and human behaviour in order to explore their relevance in epidemiological studies of age-related eye disease.</p> <p><em>Simulation 1: </em>This data set reports the spectral radiance from 250 - 500 nm at:</p> <ul> <li>3 latitudes (61.0: Southern Finland, 50.1 Northern France, 38.0: Central Spain).</li> <li>4 dates (April 17<sup>th</sup>, July 1<sup>st</sup>, September 1<sup>st</sup>, November 6<sup>th</sup> 2019).</li> <li>24 hours.</li> <li>8 cardinal directions (every 45<strong>° </strong>from North).</li> <li>2 aerosol optical densities (0.1 and 2.5).</li> </ul> <p><em>Simulation 2: </em>This data set reports the spectral radiance from 250 - 2,500 nm at:</p> <ul> <li>3 latitudes (61.0: Southern Finland, 50.1 Northern France, 38.0: Central Spain).</li> <li>4 dates (April 17<sup>th</sup>, July 1<sup>st</sup>, September 1<sup>st</sup>, November 6<sup>th</sup> 2019).</li> <li>24 hours.</li> <li>1 cardinal direction (North).</li> <li>2 aerosol optical densities (0.1 and 2.5).</li> </ul> <p><em>Simulation 3: </em>This data set reports the spectral radiance from 250 - 500 nm at:</p> <ul> <li>1 latitude (61.0: Southern Finland).</li> <li>4 dates (April 17<sup>th</sup>, July 1<sup>st</sup>, September 1<sup>st</sup>, November 6<sup>th</sup> 2019).</li> <li>24 hours.</li> <li>9 cardinal directions (every 40<strong>° </strong>from North).</li> <li>3 bidirectional reflectance distribution functions for the ground (forest, urban, snow).</li> <li>2 tilt angles for the eye direction (0<strong>° </strong> from horizon or -15<strong>°</strong> from horizon, toward the ground).</li> </ul> <p> </p>
Seasonality of in-lake and meteorological data from seven lakes, including daily measurements of water temperature, chlorophyll-a, dissolved oxygen, ice cover, air temperature, and solar radiation
This data product supports the manuscript "Seasons and seasonality in lakes: a synthesis amid global change" (Lewis et al. 2026; in review). Data were analyzed to understand how seasonality varies among diverse lakes and variables. Specifically, this data publication includes daily mean water temperature, chlorophyll-a, and dissolved oxygen at multiple depths, ice cover (binary), air temperature and solar radiation. Data availability and collection methods differ among lakes, as described in the Methods.
Air temperature, ET, and solar radiation data for A1 data logger (DP219), 1987 - 2006.
Climatological data were collected from a ridgetop climate station east of Niwot Ridge (A1 at 2195 m) throughout the year using an Omnidata DP219 datapod. This instrument has a sample interval of 10 minutes and maximum and minimum values are instantaneously recorded. Averages are means of 144 values and totals are totals of 144 values. Parameters measured were evapotranspiration, solar radiation, maximum temperature, minimum temperature, and average temperature.
Air temperature and solar radiation data for Arikaree Glacier data logger (DP211), 1986 - 2006.
Climatological data were collected from an upper Green Lakes Valley climate station (Arikaree Glacier) throughout the year using an Omnidata DP211 datapod. This instrument has a sample interval of 5 minutes and records averages of those 5-minute readings every 2 hours. Thus, daily totals represent totals of 288 values. Parameters measured were air temperature (averages) and solar radiation (totals).
Air temperature, ET, and solar radiation data for B1 data logger (DP219), 1987 - 2006.
Climatological data were collected from a ridgetop climate station east of Niwot Ridge (B1 at 2591 m) throughout the year using an Omnidata DP219 datapod. This instrument has a sample interval of 10 minutes and maximum and minimum values are instantaneously recorded. Averages are means of 144 values and totals are totals of 144 values. Parameters measured were evapotranspiration, solar radiation, maximum temperature, minimum temperature, and average temperature.
Air temperature and solar radiation data for C1 data logger (DP211), 1993 - 2006.
Climatological data were collected from a Niwot Ridge climate station (C1) throughout the year using an Omnidata DP211 datapod. This instrument has a sample interval of 5 minutes and records averages of those 5-minute readings every 2 hours. Thus, daily totals represent totals of 288 values. Parameters measured were temperature (averages) and solar radiation (totals).
Air temperature and solar radiation data for D1 data logger (DP211), 1990 - 2006.
Climatological data were collected from an upper Niwot Ridge climate station (D1) throughout the year using an Omnidata DP211 datapod. This instrument has a sample interval of 5 minutes and records averages of those 5-minute readings every 2 hours. Thus, daily totals represent totals of 288 values. Parameters measured were temperature (averages) and solar radiation (totals).
Datasets related to the study "Spatial variability and future evolution of surface solar radiation over Northern France and Benelux: a regional climate model approach"
<p>This dataset contains the data of the manuscript "Spatial variability and future evolution of surface solar radiation over Northern France and Benelux: a regional climate model approach" under publication in Atmospheric Chemistry and Physics. <br>It includes CNRM-ALADIN64 simulations of surface solar radiation, cloud fraction, aerosol optical depth and water vapor content. <br>A directory is dedicated to HINDCAST simulations. It includes all datasets involved in the evaluation of CNRM-ALADIN64 simulations, as well as all datasets used for the analysis of the spatial variability of surface solar irradiance over the recent past. <br>Another directory is dedicated to future climate simulations. In this case, several sub directories can be found, representing either the simulations over the historical period (2005-2014, i.e. HIST directory), or simulations at mid (2045-2054, "mid" suffix) and long term (2091-2100, "end" suffix) horizons for SSP1-1.9 and SSP3-7.0. Each set of climate simulations is composed of three members (r1f, r2f, r3f), which were used collectively to increase the statistical significance of our analysis. </p>
Data supporting "Solar radiation drives methane emissions from the shoots of Scots pine"
<p>Data supporting our New Phytologist publication "Solar radiation drives methane emissions from the shoots of Scots pine". </p>
In-stream solar radiation measurements in Miramichi River basin (Canada)
<p>This dataset and associated analysis describe the spatial (catchment and reach scale) and temporal (seasonal, daily and hourly scales) variability in the transmission coefficient, that is the ratio of in-stream solar radiation to above-canopy solar radiation which represents the proportion of incoming solar radiation reaching streams. Data were collected in the Miramichi River basin (Canada). In-stream solar radiation measurements were taken in a small headwater stream (Trib), a medium-sized stream (CatBk) and a wide river (LSWM).</p> <p> </p> <p> </p> <p> </p>
Direct solar Radiation (DNI) data in Aglantzia Cyprus July 2016- December 2020
<p>DNI data registrered on the roof of the Novel Technologies Laboratory Building of the Cyprus Institute (coordinates <a href="https://maps.app.goo.gl/HBZAVfvxJCv61dFn7">35.141446, 33.380970</a>), from the 1st of July 2016 until the 31st of December 2020. The time step is 1 s.</p> <p>The instrument is LP Pyhre 16 AC with EKO STR 21G tracker. </p> <p> </p>
Understory and canopy phenology, I/Io, solar radiation, and temperature related to Trelease Woods, Urbana, IL, USA from 1995–2022
<p>This study used phenological field observations made year-round for 15 dominant canopy tree species (1995-2022), understory saplings of three species (1995-2022), and 33 herb species (1995-2017) in Trelease Woods, a mature old-growth deciduous forest remnant near Urbana, Illinois, USA. The phenological data sets are paired with basal-area data, mid-day light transmission data from 21 days in 2002, daily solar radiation data from a NOAA (SURFRAD) site at Bondville, Illinois, and daily temperature data from a nearby weather station in Champaign, Illinois. These datasets were used to parameterize models of canopy light transmittance and understory plant light interception.</p> <p>These data sets were used to test the mismatch hypothesis, viz, whether canopy trees or understory plants are more sensitive to climate change, thus changing through time the relative amount of transmitted light understory species intercept. We estimated how four factors (understory phenology, cold temperatures, canopy phenology, and sunlight) individually limit the potential light interception of each understory species.</p>
Simulated top-of-atmosphere (120 km) downward and upward solar and thermal-infrared irradiances and ice cloud optical thickness; calculated solar, TIR and net cloud radiative effect. Simulated with ice crystal properties for aggregates, droxtals, and plates based on Yang (2013).
<p>This dataset consists of three .nc files for ice crystal shapes of aggregates, plates, and droxtals. The files include ice cloud optical thickness <span class="math-tex">\(\tau\)</span> (550nm), the simulated upward and downward irradiances <span class="math-tex">\(F\)</span> at the top-of-atmosphere (with and without the presence of the ice cloud), and the calculated ice cloud radiative effect <span class="math-tex">\(\Delta F\)</span> (solar [0.3-3.5 <span class="math-tex">\(\mu\)</span>m], thermal-infrared [3.5-75 <span class="math-tex">\(\mu\)</span>m], and net). The data set allows the user to extract <span class="math-tex">\(\Delta F\)</span> values for their parameter combinations. The available cloudy and cloud-free irradiances further allow to calculate the cirrus radiative effect (RE) by scaling the 'cloudy' RE with the required cloud cover. This serves as a first-approximation because, as 3D effects are neglected.</p>
Data from: No support for solar radiation as a major evolutionary driver of malar stripes in falcons
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