An official website of the United States government
Meteorological measurements are being gathered at a site at the Minocqua Dam for these purposes: 1) to supplement the data from the raft on Sparkling Lake and 2) to provide standard meteorological measurements for the North Temperate Lakes site. The following parameters are measured and stored as daily values: 1) maximum air temperature, 2) minimum air temperature, 3) precipitation, 4) snowfall, and 5) snowdepth. Snowdepth data begin in 1996. Precipitation data are summed for 5- minute intervals during periods of detectable precipitation. Data are reported at 7am each day for the previous 24 hours. E.g, data for June 5 are for period 7am June 4 to 7am June 5. Sampling Frequency: data averaged to daily values Number of sites: 1
more »
« less
Minocqua Dam Monthly Meteorological Data at North Temperate Lakes LTER 1905 - current
Minoqua Dam, Wisconsin. Meteorological measurements are being gathered at a site at the Minocqua Dam for these purposes: 1) to supplement the data from the raft on Sparkling Lake and 2) to provide standard meteorological measurements for the North Temperate Lakes site. The following parameters are measured and stored as monthly values: 1) mean daily air temperature, 2) mean maximum air temperature, 3) mean minimum air temperature, 4) total precipitation, and 5) total snowfall. Sampling Frequency: data averaged to monthly values Number of sites: 1
more »
« less
- Award ID(s):
- 2025982
- PAR ID:
- 10493200
- Publisher / Repository:
- Environmental Data Initiative
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Meteorological measurements are being gathered at a site at the Noble F. Lee municipal airport located at Woodruff, WI for three purposes: 1) to supplement the data from the raft on Sparkling and Trout Lakes used for evaporation calculations, and 2) to provide standard meteorological measurements for the North Temperate Lakes site, and 3) to measure radiation for primary production studies in the study lakes at the site. The following parameters are measured at 1-minute intervals: 1) air temperature at 1.5 m above ground, 2) relative humidity at 1.5 m above ground, 3) wind speed and direction and peak wind speed at 3 m above ground, 4) total long-wave radiation, 5) total short-wave radiation, 6) photosynthetically active radiation (PAR), 7) total solar radiation, and 8) total precipitation. High resolution data is taken typically at 1 minute intervals as well as 1-hour and 24-hour averages. Half-hourly averages of PAR and shortwave radiation are also stored. Precipitation data are summed for 5-minute intervals during periods of detectable precipitation. Derived data included in this data set include dew point temperature as well as daily minimum and maximum values for some parameters. Number of sites: 1. Date/time is Central Standard Time (GMT - 06:00) throughout the year.more » « less
-
Downscaling coarse global and regional climate models allows researchers to access weather and climate data at finer temporal and spatial resolution, but there remains a need to compare these models with empirical data sources to assess model accuracy. Here, we validate a widely used software for generating North American downscaled climate data, ClimateNA, with a novel empirical data source, 20th century weather journals kept by Admiralty Island, Alaska homesteader, Allen Hasselborg. Using Hasselborg’s journals, we calculated monthly precipitation and monthly mean of the maximum daily air temperature across the years 1926 to 1954 and compared these to ClimateNA data generated from the Hasselborg homestead location and adjacent areas. To demonstrate the utility and potential implications of this validation for other disciplines such as hydrology, we used an established regression equation to generate time series of 95% low duration flow estimates for the month of August using mean annual precipitation from ClimateNA predictions and Hasselborg data. Across 279 months, we found strong correlation between modeled and observed measurements of monthly precipitation ( ρ = 0.74) and monthly mean of the maximum daily air temperature ( ρ = 0.98). Monthly precipitation residuals (calculated as ClimateNA data - Hasselborg data) generally demonstrated heteroscedasticity around zero, but a negative trend in residual values starting during the last decade of observations may have been due to a shift to the cold-phase Pacific Decadal Oscillation. Air temperature residuals demonstrated a consistent but small positive bias, with ClimateNA tending to overestimate air temperature relative to Hasselborg’s journals. The degree of correlation between weather patterns observed at the Hasselborg homestead site and ClimateNA data extracted from spatial grid cells across the region varied by wet and dry climate years. Monthly precipitation from both data sources tended to be more similar across a larger area during wet years (mean ρ across grid cells = 0.73) compared to dry years (mean ρ across grid cells = 0.65). The time series of annual 95% low duration flow estimates for the month of August generated using ClimateNA and Hasselborg data were moderately correlated ( ρ = 0.55). Our analysis supports previous research in other regions which also found ClimateNA to be a robust source for past climate data estimates.more » « less
-
Abstract There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate dataset for the preindustrial period so far.more » « less
-
null (Ed.)A constrained stochastic weather generator (CSWG) for producing daily mean air temperature and precipitation based on annual mean air temperature and precipitation from tree-ring records is developed and tested in this paper. The principle for stochastically generating daily mean air temperature assumes that temperatures in any year can be approximated by a sinusoidal wave function plus a perturbation from the baseline. The CSWG for stochastically producing daily precipitation is based on three additional assumptions: (1) In each month, the total precipitation can be estimated from annual precipitation if there exists a relationship between the annual and monthly precipitations. If that relationship exists, then (2) for each month, the number of dry days and the maximum daily precipitation can be estimated from the total precipitation in that month. Finally, (3) in each month, there exists a probability distribution of daily precipitation amount for each wet day. These assumptions allow the development of a weather generator that constrains statistically relevant daily temperature and precipitation predictions based on a specified annual value, and thus this study presents a unique method that can be used to explore historic (e.g., archeological questions) or future (e.g., climate change) daily weather conditions based upon specified annual values.more » « less
