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Basic surface meteorology data including wind, temperature, precipitation, other variables. Data is from the Antarctic division (AAD) of the Australian Bureau of Meteorology (BOM).
Proving basic surface meteorology, soil hydrology and temperature, and fluxes of energy (radiation and turbulent fluxes) and water (precipitation, evaporation, and soil moisture).
The Saskatchewan Research Council (SRC) collected surface meteorological and radiation data from December 1993 until December 1996. The data set comprises Suite A (meteorological and energy balance measurements) and Suite B (diffuse solar and longwave measurements) components. Suite A measurements were taken at each of ten sites, and Suite B measurements were made at five of the Suite A sites. The data cover an approximate area of 500 km (North-South) by 1000 km (East-West) (a large portion of northern Manitoba and northern Saskatchewan). The measurement network was designed to provide researchers with a sufficient record of near-surface meteorological and radiation measurements. The data are provided in tabular ASCII files, and were collected by Aircraft Flux and Meteorology (AFM)-7. The surface meteorological and radiation data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).
Blowing snow is a common weather phenomenon in Antarctica and plays an important role in the water vapor cycle and ice sheet mass balance. Although it has a significant impact on the climate of Antarctica, people do not know much about this process. Fog events are difficult to distinguish from blowing snow events using existing detection algorithms by a ceilometer. In this study, based on ceilometer, the meteorological parameters observed by surface meteorology systems are further combined to detect blowing snow and fog using the AdaBoost algorithm. The weather phenomena recorded by human observers are ‘true’. The dataset is collected from 1 January 2016 to 31 December 2016 at the AWARE site. Among them, three-quarters of the data are used as the training set and the rest of the data as the testing set. The classification accuracy of the proposed algorithm for the testing set is about 94%. Compared with the Loeb method, the proposed algorithm can detect 89.12% of blowing snow events and 76.10% of fog events, while the Loeb method can only identify 64.29% of blowing snow events and 31.87% of fog events.
The Canadian Atmospheric Environment Service (AES) provided BOREAS with hourly and daily surface meteorological data from 23 of the AES meteorological stations located across Canada and upper air data from 1 station at The Pas, Manitoba. Due to copyright restrictions on the full resolution surface meteorological data, this data set contains 5-day average values for the surface parameters. The upper air data are provided in their full resolution form. The 5-day averaging was performed in order to create a data set that could be publicly distributed at no cost. Temporally, the surface meteorological data cover the period of January 1975 to December 1996 and the upper air data cover the period of January 1961 to November 1996. The data are provided in tabular ASCII files, and are classified as AFM-staff data. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
The Saskatchewan Forest Fire Control Centre (SFFCC) provided surface meteorological data to BOREAS from its archive. This data set contains hourly surface meteorological data from 18 of the Meteorological stations located across Saskatchewan. Included in these data are parameters of date, time, temperature, relative humidity, wind direction, wind speed, and precipitation. Temporally, the data cover the period of May through September of 1994 and 1995. The data are provided in comma-delimited ASCII files, and are classified as AFM-Staff data. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
The Surface Meteorological System (MET) consist mainly of conventional in situ sensors that obtain a defined “core” set of measurements. The core set of measurements is: Barometric Pressure (kPa), Temperature (°C), Relative Humidity (%), Arithmetic-Averaged Wind Speed (m/s), Vector-Averaged Wind Speed (m/s), and Vector-Averaged Wind Direction (deg). The sensors that collect the core variables are mounted at the standard heights defined for each variable: • Winds: 10 meters • Temperature and Relative Humidity: 2 meters • Barometric Pressure: 1 meter. Depending upon the geographical location, different models and types of sensors may be used to measure the core variables due to the conditions experienced at those locations. Most sites have additional sensors that measure other variables that are unique to that site or are well suited for the climate of the location but not at others.
Surface meteorological data (3m wind speed, wind direction, 2m air temperature, relative humidity, pressure, downwelling irradiance, total rainfall) gathered on the Sequim-PNNL campus ('upstairs'). Equipment is manufactured and calibrated by Campbell Scientific. Placement and height of sensors follows recommended guidelines of the NWS.
The Release 5.1 Surface meteorology and Solar Energy (SSE) data contains parameters formulated for assessing and designing renewable energy systems. Parameters fall under 11 categories including: Solar cooking, solar thermal applications, solar geometry, tilted solar panels, energy storage systems, surplus product storage systems, cloud information, temperature, wind, other meteorological factors, and supporting information. This latest release contains new parameters based on recommendations by the renewable energy industry and it is more accurate than previous releases. On-line plotting capabilities allow quick evaluation of potential renewable energy projects for any region of the world. The SSE data set is formulated from NASA satellite- and reanalysis-derived insolation and meteorological data for the 10-year period July 1983 through June 1993. Results are provided for 1 degree latitude by 1 degree longitude grid cells over the globe. Average daily and monthly measurements for 1195 World Radiation Data Centre ground sites are also available. [Mission Objectives] The SSE project contains insolation and meteorology data intended to aid in the development of renewable energy systems. Collaboration between SSE and technology industries such as the Hybrid Optimization Model for Electric Renewables ( HOMER ) may aid in designing electric power systems that employ some combination of wind turbines, photovoltaic panels, or diesel generators to produce electricity. [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1993-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].
The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-6 team from the National Oceanic and Atmospheric Adminsitration/Environment Technology Laboratory (NOAA/ETL) collected surface meteorological data from 21 May to 20 Sep 1994 near the Southern Study Area-Old Jack Pine (SSA-OJP) tower site. The data are in tabular ASCII files. The surface meteorological data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).
This study examines the link between upper-tropospheric planetary-scale Rossby waves and surface meteorological parameters based on the observations made in association with the Ganges Valley Aerosol Experiment (GVAX) campaign at an extratropical site at Aryabhatta Research Institute of Observational Sciences, Nainital (29.45° N, 79.5° E) during November–December 2011. The spectral analysis of the tropospheric wind field from radiosonde measurements indicates a predominance power of around 8 days in the upper troposphere during the observational period. An analysis of the 200 hPa meridional wind (v200 hPa) anomalies from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis shows distinct Rossby-wave-like structures over a high-altitude site in the central Himalayan region. Furthermore, the spectral analysis of global v200 hPa anomalies indicates the Rossby waves are characterized by zonal wave number 6. The amplification of the Rossby wave packets over the site leads to persistent subtropical jet stream (STJ) patterns, which further affects the surface weather conditions. The propagating Rossby waves in the upper troposphere along with the undulations in the STJ create convergence and divergence regions in the mid-troposphere. Therefore, the surface meteorological parameters such as the relative humidity, wind speeds, and temperature are synchronized with the phase of the propagating Rossby waves. Moreover, the present study finds important implications for medium-range forecasting through the upper-level Rossby waves over the study region.
The Surface meteorology and Solar Energy (SSE) data set contains over 200 parameters formulated for assessing and designing renewable energy systems.The SSE data set is formulated from NASA satellite- and reanalysis-derived insolation and meteorological data for the 10-year period July 1983 through June 1993. Results are provided for 1 degree latitude by 1 degree longitude grid cells over the globe. Average daily and monthly measurements for 1195 World Radiation Data Centre ground sites are also available. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1993-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree].
The second Wind Forecast Improvement Project (WFIP2) is an 18-month field campaign in the Pacific Northwest U.S.A., whose goal is to improve the accuracy of numerical-weather-prediction forecasts in complex terrain. The WFIP2 campaign involved the deployment of a large suite of in situ and remote sensing instrumentation, including eight 915-MHz wind-profiling radars, and surface meteorological stations. The evolution and annual variability of the daytime convective planetary-boundary-layer (PBL) height is investigated using the wind-profiling radars. Three models with different horizontal grid spacing are evaluated: the Rapid Refresh, the High-Resolution Rapid Refresh, and its nested version. The results are used to assess errors in the prediction of PBL height within the experimental and control versions of the models, with the experimental versions including changes and additions to the model parametrizations developed during the field campaign, and the control version using the parametrizations present in the National Oceanic and Atmospheric Administration/National Centers for Environmental Prediction operational version of the models at the start of the project. Results show that the high-resolution models outperform the low-resolution versions, the experimental versions perform better compared with the control versions, model PBL height estimations are more accurate on cloud-free days, and model estimates of the PBL height growth rate are more accurate than model estimates of the rate of decay. Finally, using surface sensors, we assess surface meteorological variables, finding improved surface irradiance and, to a lesser extent, improved 2-m temperature in the experimental version of the model.
The aerosol observing system (AOS) surface meteorology instrument is an ancillary sensor that provides temperature, relative humidity, pressure, wind speed and direction, and precipitation data relevant to the AOS. It consists of a Vaisala weather transmitter (WXT520 or WXT530) mounted on top of the AOS aerosol inlet, at a height of approximately 10 meters.
In 1995, the BOREAS science teams identified the need for a continuous surface meteorological and radiation data set to support flux and surface process modeling efforts. This data set contains actual, substituted, and interpolated 15-minute meteorological and radiation data compiled from several surface measurements sites over the BOREAS SSA and NSA. Temporally, the data cover 01-Jan-1994 to 31-Dec-1996. The data are stored in tabular ASCII files, and are classified as AFM-Staff data.
As a component of the National Aeronautics and Space Administration (NASA) Weather Focus Area and Global Precipitation Measurement (GPM) Ground Validation participation in the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018) field research and forecast demonstration programs, hourly ocean surface meteorology properties were retrieved from the GPM microwave observations for January – March 2018. In this study, the retrieved ocean surface meteorological products – 2-m temperature, 2-m specific humidity, and 10-m wind speed were assimilated into a regional numerical weather prediction (NWP) framework to explore the application of these observations for two heavy snowfall events during the ICE-POP 2018: 27-28 February, and 7-8 March 2018. The Weather Research and Forecasting (WRF) model and the community Gridpoint Statistical Interpolation (GSI) were used to conduct high resolution simulations and data assimilation experiments. The results indicate that the data assimilation has a large influence on surface thermodynamic and wind fields in the model initial condition for both events. With cycled data assimilation, significantly positive influence of the retrieved surface observation was found for the March case with improved quantitative precipitation forecast and reduced error in temperature forecast. A slightly smaller yet positive impact was also found in the forecast of the February case.
The Saildrone Baja field campaign was an international effort to collect measurements across the air-sea interface for a 62-day period between April 11-June 11, 2018. The field campaign was executed using a saildrone, an unmanned surface vehicle (USV) carrying a comprehensive suite of instruments to measure meteorological, ocean surface, and subsurface data. We use these data to validate near-surface meteorology and ocean surface temperature fields in theGlobal Earth Observing System (GEOS). This is the first study using Saildrone data to validate GEOS products. As these USV platforms become more prevalent, they could be used to improve model representation of the air-sea interface variables.
The Purdue Regional Objective Analysis of the Mesoscale (PROAM) is a Barness-type scheme for the analysis of surface meteorological data. Modifications are introduced to the original version in order to increase its flexibility and to permit greater ease of usage. The code was rewritten for an interactive computer environment. Furthermore, a multiple iteration technique suggested by Barnes was implemented for greater accuracy. PROAM was subjected to a series of experiments in order to evaluate its performance under a variety of analysis conditions. The tests include use of a known analytic temperature distribution in order to quantify error bounds for the scheme. Similar experiments were conducted using actual atmospheric data. Results indicate that the multiple iteration technique increases the accuracy of the analysis. Furthermore, the tests verify appropriate values for the analysis parameters in resolving meso-beta scale phenomena.