Monthly mean climatic data for Antarctic automatic weather stations

1993 ◽  
pp. 1-21 ◽  
Author(s):  
Charles R. Stearns ◽  
Linda M. Keller ◽  
George A. Weidner ◽  
Manuela Sievers
Keyword(s):  
Climatic Data ◽  
Weather Stations

TROPICAL CYCLONE WINDS AT LANDFALL: The ASOS–C-MAN Wind Exposure Documentation Project

2004 ◽  
Vol 85 (6) ◽  
pp. 845-852 ◽  
Author(s):  
Mark Powell ◽  
David Bowman ◽  
David Gilhousen ◽  
Shirley Murillo ◽  
Nick Carrasco ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Building Design ◽  
Web Pages ◽  
Climatic Data ◽  
National Climatic Data Center ◽  
Wind Exposure ◽  
Wind Measurements ◽  
Weather Stations ◽  
Aerodynamic Roughness ◽  
American Society

Photographs describing the wind exposure at automatic weather stations susceptible to tropical cyclones are now available on Web pages at the National Climatic Data Center and the National Data Buoy Center. Given the exposure for one of eight wind direction sectors, a user may estimate the aerodynamic roughness and correct mean wind measurements to an open-terrain exposure. The open-terrain exposure is consistent with the tropical cyclone advisories and forecasts issued by the National Weather Service, as well as building design wind load standards published by the American Society of Civil Engineers.

scholarly journals Low-Cost Automatic Weather Stations in the Internet of Things

Information ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 146
Author(s):  
Konstantinos Ioannou ◽  
Dimitris Karampatzakis ◽  
Petros Amanatidis ◽  
Vasileios Aggelopoulos ◽  
Ilias Karmiris
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Low Cost ◽  
The Internet ◽  
Climatic Data ◽  
Time Data ◽  
New Era ◽  
Observation Systems ◽  
Weather Stations ◽  
The Internet Of Things

Automatic Weather Stations (AWS) are extensively used for gathering meteorological and climatic data. The World Meteorological Organization (WMO) provides publications with guidelines for the implementation, installation, and usages of these stations. Nowadays, in the new era of the Internet of Things, there is an ever-increasing necessity for the implementation of automatic observing systems that will provide scientists with the real-time data needed to design and apply proper environmental policy. In this paper, an extended review is performed regarding the technologies currently used for the implementation of Automatic Weather Stations. Furthermore, we also present the usage of new emerging technologies such as the Internet of Things, Edge Computing, Deep Learning, LPWAN, etc. in the implementation of future AWS-based observation systems. Finally, we present a case study and results from a testbed AWS (project AgroComp) developed by our research team. The results include test measurements from low-cost sensors installed on the unit and predictions provided by Deep Learning algorithms running locally.

Accuracy of Weather Data in Long-Term Pavement Performance Program Database

2000 ◽  
Vol 1699 (1) ◽  
pp. 151-159 ◽  
Author(s):  
Chung-Lung Wu ◽  
Gonzalo R. Rada ◽  
Aramis Lopez ◽  
Yingwu Fang
Keyword(s):  
Weather Conditions ◽  
Test Site ◽  
Climatic Conditions ◽  
Weighting Scheme ◽  
Pavement Performance ◽  
Weather Data ◽  
Climatic Data ◽  
National Climatic Data Center ◽  
Weather Stations

To provide accurate climatic data for pavements under the Long-Term Pavement Performance (LTPP) Program, a climatic database was developed in 1992 and subsequently revised and expanded in 1998. In the development of this database, up to five nearby weather stations were selected for each test site. Pertinent weather data for the selected weather stations were obtained from the U.S. National Climatic Data Center and the Canadian Climatic Center. With a 1/ R2 weighting scheme, site-specific climatic data were derived from the nearby weather station data. The derived data were referred to as “virtual”weather data. To evaluate the effect of environmental factors on pavement performance and design, automated weather stations (AWS) were installed at LTPP Specific Pavement Study Projects 1, 2, and 8 to collect on-site weather data. Since the virtual weather data were developed for all LTPP test sites and will be used for future pavement performance studies, it is essential that the derived virtual data be accurate and representative of the actual onsite climatic conditions. The availability of the AWS weather data has provided an opportunity to evaluate whether virtual weather data can be used to represent on-site weather conditions. Daily temperature data and monthly temperature and precipitation data were used in this experiment. On the basis of the comparisons made between the virtual and onsite measured (AWS) data, it appears that climatic data derived from nearby weather stations using the 1/R2 weighting scheme estimate the actual weather data reasonably well and thus can be used to represent on-site weather conditions in pavement research and design.

Recent changes in the glaciers of Heard Island

Polar Record ◽  
1986 ◽  
Vol 23 (144) ◽  
pp. 255-272 ◽  
Author(s):  
Ian F. Allison ◽  
Peter L. Keage
Keyword(s):  
Sea Level ◽  
Climatic Data ◽  
Volcanic Island ◽  
Pressure System ◽  
Tidewater Glaciers ◽  
Ice Caps ◽  
Heard Island ◽  
Maximum Elevation ◽  
Low Pressure System ◽  
Weather Stations

ABSTRACTHeard Island, a heavily glacierized volcanic island in the Southern Ocean, is 80% ice-covered, with glaciers descending from 2,400 m to sea level: major glaciers are up to 7 km long with areas exceeding 10 km. Much of the island was photographed from the air in 1947 and again in early 1980. Photographs and limited ground surveys record changes (mostly retreats) in glacier fronts. Retreat is most marked on the eastern flanks where former tidewater glaciers are now grounded inland. Glaciers on northern and windward western flanks still end in ice cliffs but have narrowed; glaciers and ice caps on Laurens Peninsula (maximum elevation 710 m) are up to 65% smaller. Nearby lies Kerguelen and other southern islands with long climatic records have warrned significantly since the early 1960s. Surface and upper-air climatic data from Heard Island 1947–54 and records from automatic weather stations 1980–82 suggest that Heard too has warmed slightly, concurrently with a possible northward shift of low-pressure system tracks in this region. Temperatures have remained above average through the early 1980s and glacier retreat is expected to continue.

scholarly journals Adjustments to the indicators of the heating and cooling degree-days for regions of the Republic of Uzbekistan

2021 ◽  
Vol 939 (1) ◽  
pp. 012017
Author(s):  
N R Avezova ◽  
E Yu Rakhimov ◽  
N N Dalmuradova ◽  
M B Shermatova
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Scientific Data ◽  
Climatic Data ◽  
Degree Days ◽  
Heating And Cooling ◽  
Cooling Degree Days ◽  
Weather Stations ◽  
The Republic ◽  
Supply Systems

Abstract This paper identifies the indicators of the calculated heating and cooling degree-days for the territory of Uzbekistan. The revealed values of the maximum and average daily outside air temperature were taken into account based on the collection, processing and analysis of the latest archives of climatic data. These data was obtained from open sources of weather stations, suitable for servicing scientific data, in order to enter adjustments to forecasts in the design of heat and cold supply systems in buildings and structures, which, in turn, mitigate the effects of climate change.

scholarly journals Assessment of Irrigation Water Requirement for Major Vegetable Crops Using Penman-Monteith and Alternative Models in Northern Togo

2020 ◽  
Vol 3 (3) ◽  
Keyword(s):  
Irrigation Water ◽  
Water Resource Management ◽  
Irrigation Scheduling ◽  
Water Requirement ◽  
Climatic Data ◽  
Vegetable Crops ◽  
Irrigation Water Requirement ◽  
Increasing Trend ◽  
Weather Stations ◽  
Semi Arid

Climate change has seriously impacted water availability and agriculture production in arid and semi-arid climates. Estimation of actual crop evapotranspiration (ETa) is critical for agricultural water resource management and proper irrigation scheduling. This study aimed to (1) estimate the reference evapotranspiration (ETo) and four vegetables actual ETa during crop off season using Penman–Monteith method and alternative climatic data models and, (2) to determine the irrigation water requirement for these main vegetable crops in northern Togo. Four (4) ground based weather stations were considered across the northern region of Togo for 1987 - 2016 period. Non parametric Mann-Kendall test was used for the significance of the trend analysis of off season reference and actual evapotranspiration. The results showed a decreasing trend in off season ETo at Dapaong, Mango and Kara weather stations while Niamtougou showed an increasing trend in the long term ETo. From all stations, only Niamtougou had a significant increasing trend in ETa for all vegetable crops under this study. Among the study locations, Mango had the highest irrigation water requirement for all four vegetable crops, followed by Kara. The lowest irrigation requirement was obtained at Dapaong. These results will help in irrigation planning for tomato, cabbage, carrot and onion in the semi-arid climate of Togo and similar environment.

Stochastic simulation of the spatio-temporal field of the average daily heat index in Southern Russia

2020 ◽  
Vol 82 ◽  
pp. 149-160
Author(s):  
N Kargapolova
Keyword(s):  
Heat Waves ◽  
Numerical Models ◽  
Heat Index ◽  
Real Field ◽  
Gaussian Field ◽  
The Real ◽  
Southern Russia ◽  
Weather Stations ◽  
Spatio Temporal ◽  
Temporal Field

Numerical models of the heat index time series and spatio-temporal fields can be used for a variety of purposes, from the study of the dynamics of heat waves to projections of the influence of future climate on humans. To conduct these studies one must have efficient numerical models that successfully reproduce key features of the real weather processes. In this study, 2 numerical stochastic models of the spatio-temporal non-Gaussian field of the average daily heat index (ADHI) are considered. The field is simulated on an irregular grid determined by the location of weather stations. The first model is based on the method of the inverse distribution function. The second model is constructed using the normalization method. Real data collected at weather stations located in southern Russia are used to both determine the input parameters and to verify the proposed models. It is shown that the first model reproduces the properties of the real field of the ADHI more precisely compared to the second one, but the numerical implementation of the first model is significantly more time consuming. In the future, it is intended to transform the models presented to a numerical model of the conditional spatio-temporal field of the ADHI defined on a dense spatio-temporal grid and to use the model constructed for the stochastic forecasting of the heat index.

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