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27 results for “meteorological parameters”
CO2 NEE and ER + air and soil meteorological and climate parameters in Alpine grasslands, Gran Paradiso National Park, 2017-2019
<p>The dataset “fluxes_meteoclimate_nivolet_V0” is a .csv file reporting CO<sub>2</sub> Net Ecosystem Exchange (NEE) and Ecosystem Respiration (ER) measured at Nivolet Plain, Gran Paradiso National Park, Italy, in a high-altitude Alpine grassland environment (about 2700 m.a.s.l.) using the flux chamber method, during the 2017, 2018 and 2019 vegetative seasons (July-September), approximately twice a month. NEE is measured with a transparent flux chamber, while ER with a shaded chamber. Data represent the average values and the corresponding standard deviations obtained from four sites at different altitudes and geological substrate of the soil. Each average value is obtained as a mean over a set of more than 20 point-measures for each site and each sampling date. Flux data are complemented by measurements of soil temperature and volumetric water content, air temperature and moisture, and solar radiance. The four sites are characterized by soils developed over carbonates (carb) (45.500212N-7.152213E), glacial deposits (glac) (45.490167N-7.139916E), gneiss rocks (gnei) (45.490256N-7.149253E) and alluvial deposits (allu) (45.492656 N-7.146092 E).</p> <p>Other relevant shortcuts used in the .csv table: Std = Standard deviation; VWC% = Volumetric Water Content %. Meteorological and climate variables recorded during the measurement of NEE and during the measurement of ER bring the suffix NEE and ER respectively (es. Pressure_NEE (hPa) = atmospheric pressure recorded during the measurement of Net Ecosystem Exchange).</p>
Observed and WRF-simulated near-surface meteorological parameters on selected James Ross Island glaciers during heatwaves in summer 2022/23
<p>The files contain time series of near-surface meteorological conditions observed on Triangular Glacier and Davies Dome on James Ross Island, Antarctica and simulated time series for these glaciers based on the Weather Research and Forecasting (WRF) model output. Observations of 2-m air temperature, 2-m wind speed, net radiation and glacier surface height are available from 01 November 2022 to 16 January 2023 (net radiation is available only on Triangular Glacier). Simulated values of 2-m air temperature, 2-m wind speed, net radiation, sensible and latent heat fluxes are available from 08 November 2022 to 16 January 2023.</p>
CO2 Net Ecosystem Exchange (NEE) and Ecosystem Respiration (ER) + meteorological parameters in alpine grasslands at Nivolet Plain, Gran Paradiso National Park, 2020 (IGG-CNR-CZO@NIVOLET)
<p>CO2 Net Ecosystem Exchange (NEE) and Ecosystem Respiration (ER) measured at Nivolet Plain, Gran Paradiso National Park, Italy, in a high-altitude Alpine grassland environment (about 2500-2700 m.a.s.l.) using the closed portable flux chamber method during the 2020 vegetative season (July-October), approximately twice a month. NEE is measured with a transparent chamber, while ER with a dark chamber (transparent chamber shaded with a cloth). Data represent the average values and the corresponding standard deviations obtained from five sites at different altitudes and soil substrates. Each average value is obtained as a mean over a set of 20 point-measurements for each site and each sampling date. Flux data are complemented by measurements of soil temperature and soil volumetric water content, air temperature, air RH, and solar radiance.</p> <p>During the measurement, air is pumped from the chamber to an IR gas analyzer (IRGA) and then injected again in the chamber. The CO2 concentration inside the chamber is measured for about 90 seconds and then the rate of concentration change is linearly interpolated (over 60s) to obtain the flux measurements. A detailed description of the sampling method can be found in Magnani et al. (2020).</p> <p>Instrumentation used: accumulation chambers (height: 31.5 cm; area of the base: 363 cm2), LI-COR LI-840 & LI-850 IR spectrophotometers, stainless-steel collars (inserted into the soil to a depth of about 1 cm), portable meteorological stations (pyranometer LSI Lastem DPA053, thermohygrometer LSI Lastem DMA672.1), pt100 soil temperature sensors, SM150T soil moisture sensor.</p>
CO2 Net Ecosystem Exchange (NEE) and Ecosystem Respiration (ER) + meteorological parameters in alpine grasslands at Nivolet Plain, Gran Paradiso National Park, 2021 (IGG-CNR-CZO@NIVOLET)
<p>CO2 Net Ecosystem Exchange (NEE) and Ecosystem Respiration (ER) measured at Nivolet Plain, Gran Paradiso National Park, Italy, in a high-altitude Alpine grassland environment (about 2500-2700 m.a.s.l.) using the closed portable flux chamber method during the 2021 vegetative season (July-October), approximately twice a month. NEE is measured with a transparent chamber, while ER with a dark chamber (transparent chamber shaded with a cloth). Data represent the average values and the corresponding standard deviations obtained from five sites at different altitudes and soil substrates. Each average value is obtained as a mean over a set of 20 point-measurements for each site and each sampling date. Flux data are complemented by measurements of soil temperature and soil volumetric water content, air temperature, air RH, and solar radiance.</p> <p>During the measurement, air is pumped from the chamber to an IR gas analyzer (IRGA) and then injected again in the chamber. The CO2 concentration inside the chamber is measured for about 90 seconds and then the rate of concentration change is linearly interpolated (over 60s) to obtain the flux measurements. A detailed description of the sampling method can be found in Magnani et al. (2020).</p> <p>Instrumentation used: accumulation chambers (height: 31.5 cm; area of the base: 363 cm2), LI-COR LI-840 & LI-850 IR spectrophotometers, stainless-steel collars (inserted into the soil to a depth of about 1 cm), portable meteorological stations (pyranometer LSI Lastem DPA053, thermohygrometer LSI Lastem DMA672.1), pt100 soil temperature sensors, SM150T soil moisture sensor.</p>
Dataset from "Constraining Martian regolith and vortex parameters from combined seismic and meteorological measurements"
<p>The table provided below (in CSV format) includes derived data obtained from the raw data of the InSight SEIS and APSS experiments. For the raw data, we acknowledge:</p> <p>InSight Mars SEIS Data Service. (2019). SEIS raw data, Insight Mission. IPGP, JPL, CNES, ETHZ, ICL, MPS, ISAE-Supaero, LPG, MFSC. https://doi.org/10.18715/SEIS.INSIGHT.XB_2016</p> <p>The dataset in this table was used to produce Figures 6, 7, 11 and 12 of the following paper:</p> <p>N. Murdoch, A. Spiga, R. Lorenz, R.F. Garcia, C. Perrin, R. Widmer-Schnidrig, S. Rodriguez, N. Compaire, N. H. Warner, D. Mimoun, D. Banfield, P. Lognonné and W.B. Banerdt. Constraining Martian regolith and vortex parameters from combined seismic and meteorological measurements. Journal of Geophysical Research: Planets.</p> <p>The table provides derived vortex parameters of all vortices studied in this paper. The columns of the table contain the following properties of every vortex event: Sol, UTC date and time, Local Mean Solar Time (LMST), Observed pressure deficit <span class="math-tex">\(\Delta P_{obs}\)</span> (determined from the fit to the Ellehoj et al. (2010) model after filtering in the 0.02 - 0.3 Hz frequency band), Observed pressure drop encounter duration <span class="math-tex">\(\tau\)</span> (FWHM determined from the fit to the Ellehoj et al. (2010) model after filtering in the 0.02 - 0.3 Hz frequency band), the Ellehoj et al. (2010) model goodness of fit to the vortex pressure data (after filtering in the 0.02 - 0.3 Hz frequency band), Mean background wind speed <span class="math-tex">\(v\)</span>, Standard deviation of background wind speed <span class="math-tex">\(\sigma_v\)</span>, Maximum radial tilt <span class="math-tex">\(\theta_{obs}\)</span>, Azimuth at maximum radial tilt (i.e. at closest approach) <span class="math-tex">\(\alpha_{obs}\)</span>, Mean miss distance <span class="math-tex">\(x\)</span> (i.e. when <span class="math-tex">\(S = v\)</span>), <span class="math-tex">\(\eta \)</span> (defined as <span class="math-tex">\(E/(1-\nu^2) \)</span>), Mean <span class="math-tex">\(\zeta\)</span> (i.e. when <span class="math-tex">\(S = v\)</span>). For further details about these parameters please see the paper cited above.</p>
Measurements of diurnal variations of meteorological parameters and subsurface water temperature in Lake Kinneret, Israel, during the period (Sept. 6 – 20, 2015)
<p>The datasets include in-situ 10-minute measurements of subsurface water temperature taken at a depth of 20 cm, at a site A (32.82 <sup>o</sup>N; 35.60 <sup>o</sup>E) located near the center of Lake Kinneret, during the period (Sept. 6 – 20, 2015). Lake Kinneret is located in Israel. The Campbell 107-L temperature probe was used (specifications are available online at <a href="https://www.campbellsci.asia/107-l">https://www.campbellsci.asia/107-l</a> ). The datasets also include meteorological measurements taken at the same site, such as air temperature, relative humidity, wind speed, upwelling and downwelling longwave (4.5 - 42 µm) radiation. The above meteorological measurements were taken at a height of 2 - 3 m above the lake surface. Measurements at the site A are associated with the Kinneret Limnological Laboratory, Israel Oceanographic and Limnological Research (<a href="https://www.ocean.org.il/kinneret-limnological-laboratory-center/">https://www.ocean.org.il/kinneret-limnological-laboratory-center/</a> ).</p> <p><em>Data format: xlsx file. The file includes water temperature (WT, <sup>o</sup>C), wind speed (WS, m/s), air temperature (Tair, <sup>o</sup>C), relative humidity (RH, %), upwelling longwave radiation (Upwelling LW, W/m<sup>2</sup>) and downwelling longwave radiation (Downwelling LW, W/m<sup>2</sup>).</em></p> <p>Files (140.40 KB)</p>
Basic Meteorological Parameters measured by surface observation
<p>This dataset is an example of various weather stations in europe which collect meteorological data from the earths surface. <br>The selected station is located in Thessaloniki city centre. The dataset is a json of different parameters measured with temporal resolution of 10min. The json includes a 24h time interval.<br>Measured parameters are: <br>2m Air Temperature, Dewpoint, Windspeed, Wind direction, Wind gust, Relative Humidity, Mean Sealevel Pressure, Pressure, Global Radiation</p> <p>The data is availlable via API at Meteologix.com .</p> <p>(curl --request GET --url '<a href="https://api.kachelmannwetter.com/v02/stations/BK0078/observations?endTime=2024-10-21&startTime=2024-10-20" target="_blank" rel="noopener noreferrer">https://api.kachelmannwetter.com/v02/stations/BK0078/observations?endTime=2024-10-21&startTime=2024-10-20</a>' <span>--header </span><span>'Accept: application/json' </span><span> --header </span><span>'Authorization: Basic undefined')</span></p>
CO2 NEE and ER + air and soil meteorological and climate parameters in Arctic tundra, Ny Ålesund (Svalbard, NO) - summer 2019
<p>The dataset “fluxes_meteoclimate_NyAlesund” is a .csv file reporting CO2 fluxes and basic meteoclimatic variables measured in the Bayelva Basin near Ny Ålesund, in the Brøgger peninsula, Spitsbergen, Norway (78°55’24’’ N, 11°55’15’’E) during the 2019 growing season peak (July-August). Average coordinates of the measuring site are: 78°55’25.7” N,11°53’29.4” E. Fluxes were measured using the flux chamber method: the Net Ecosystem Exchange (NEE) was measured with a transparent flux chamber, while the Ecosystem Respiration (ER) with a shaded chamber. Three types of sampling were performed: at a fixed point during 24h ('point' in column sampling); in points randomly distributed over a site ('site' in column sampling); and in points covered with specific species ('species' in column sampling). Flux data are complemented by measurements of soil temperature (Ts, in Celsius degrees), soil volumetric water content (VWC, in %), atmospheric pressure (Pr, in hPa), air temperature (Ta, in Celsius degrees), air moisture (RH, in %), and solar radiance (rs , in W/m2). The Green Fractional Cover (GFC, between 0 and 1) of the vegetation inscribed within the sampling surface was estimated from digital RGB pictures taken at nadir. Measurements were divided into 4 classes, depending on the prevailing cover type: bare soil (BS), vascular vegetation (V), non-vascular vegetation (NV, including lichens, mosses and bacterial soil crust) and mix of vascular and non-vascular vegetation (MIX). Class V was further split into 5 subclasses: Carex spp. (CX), Dryas octopetala (DR), Salix Polaris (SL), Saxifraga oppostifolia (SX) and Silene acaulis (SI). </p>
Fig. 2 in The impact of meteorological parameters on the biological productivity of mycorrhizal mushrooms in Eastern Siberia
Fig. 2. The variation of total amount of month precipitations *** in August and biological productivity**** of mushrooms in different years. *** variation of total amount of month precipitations, **** biological productivity
Fig. 1 in The impact of meteorological parameters on the biological productivity of mycorrhizal mushrooms in Eastern Siberia
Fig. 1. The variation of average month temperature * of soil at a depth of 40 cm below the natural cover in August and biological productivity** of mushrooms in different years. * variation of average month temperature, ** biological productivity, *** 1 centner = 100 kilograms (a centner is a metric unit of mass equal to one hundred kilograms).
Dataset on sub-daily vertical profiles of physicochemical parameters and chlorophyll concentration in El Val reservoir, together with its daily meteorological data, storage state and downstream flow (2018-2022).
This dataset contains the physicochemical parameters and chlorophyll concentration of El Val reservoir (province of Zaragoza, Spain), together with its meteorological conditions, the water level, the stored volume and the flow rate of the effluent, the Queiles River, a few meters downstream of the dam. These data are useful to feed deterministic, data driven or hybrid hydrological models with different purposes, like the identification of the impact of meteorological conditions on the physicochemical properties of the reservoir, like the thermal stratification, as well as the assessment of different management strategies in the reservoir. The original data were collected by the Confederación Hidrográfica del Ebro (CHE) and were published in real time through the web page of the Ebro Automatic Water Quality Information System (SAICA Ebro by its initials in Spanish) and the Ebro Automatic Hydrographic Information System (SAIH Ebro by its initials in Spanish). Then, the CHE curated the data that are finally available to the citizens under request by variable and date. In order to facilitate their availability and reuse, these data have been gathered, pre-processed and packaged in the form of datasets. Specifically, they are structured in four data tables: vertical profiles of physicochemical data in the reservoir, meteorological data in the same basin, water level and stored water volume in the reservoir and water flow rate of the Queiles River downstream of the reservoir.
Measurements of meteorological parameters and subsurface water temperature in the hypersaline Dead Sea in September 2015
Open the record for dataset details and reuse information.
Meteorological parameters and climate zones
<p>Reader needs author approval</p>
Atmospheric aerosol, gases and meteorological parameters measured during the LAPSE-RATE campaign - Kansas State University data sets
<p>This publication summarizes the measurements and data sets generated by Kansas State University (KSU) during the LAPSE-RATE that took place in the San Luis Valley of Colorado during the summer of 2018. These data sets offer observations of atmospheric aerosols at the surface and in vertical column acquired by KSU rotary-wing Unmanned Aerial System. </p>
Atmospheric aerosol, gases and meteorological parameters measured during the LAPSE-RATE campaign - Finnish Meteorological Institute data sets
<p>This publication summarizes the measurements and data sets generated by Finnish Meteorological Institute (FMI) during the LAPSE-RATE that took place in the San Luis Valley of Colorado during the summer of 2018. These data sets offer observations of atmospheric aerosols and gases at the surface and in vertical column acquired by FMI rotary-wing Unmanned Aerial System and FMI ground module. </p>
OCO-3 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V11r (OCO3_L2_Met) at GES DISC
Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations.The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.
OCO-3 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V10r (OCO3_L2_Met) at GES DISC
Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations.The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.
OCO-2 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V11r (OCO2_L2_Met) at GES DISC
Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass meteorological parameters interpolated from global assimilation model for each sounding.
ISLSCP II ECMWF Near-Surface Meteorology Parameters
This data set for the ISLSCP Initiative II data collection provides meteorology data with fixed, monthly, monthly-6-hourly, 6-hourly, and 3-hourly temporal resolutions. The data were derived from the European Centre for Medium-range Weather Forecasts (ECMWF) near-surface meteorology data set, 40-year re-analysis, or ERA-40 (Simmons and Gibson, 2000), which covers the years 1957 to 2001. The data were processed onto the ISLSCP II Earth grid with a spatial resolution of 1-degree in both latitude and longitude, and span the common ISLSCP II period from 1986 to 1995.The ECMWF forecast system is called the Integrated Forecasting System (IFS) and was developed in co-operation with Meteo-France. For ERA40 it is used with 60 levels from the top of the model at 10 Pa to the lowest level at about 10 m above the surface. There are 46 compressed (.tar.gz) data files with this data set. Each uncompressed file contains space-delimited text (.asc) data files.
OCO-2 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V10r (OCO2_L2_Met) at GES DISC
Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.In early 2021, the OCO Team identified an issue with OCO-2 level 2 products processed since January 28, 2020. The Ancillary Geometric Product (AGAP) file, a static file used in OCO-2 Geolocation processing, was inadvertently replaced with an obsolete version. This AGAP file included a ~300 m pointing error. As a result, all OCO-2 Level 2, version 10r, data files for the period January 28 - December 31, 2020, were corrected and replaced. The replacement process was completed by the end of June, 2021. The significance of this error has been described in Kiel et al. (2019; doi:10.5194/amt-12-2241-2019).The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass meteorological parameters interpolated from global assimilation model for each sounding.
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