Comprehensive database of first and last frost dates for US ZIP codes based on weather station data

Date of freeze for historical (1985-2005) and future (2071-2090, RCP 8.5) time periods, and absolute change between them, based on analysis of MACAv2METDATA.

This dataset includes frost tube data from 37 stations in the Upper Midwest (Minnesota, North Dakota, Wisconsin), USA. The responsible agency was the St. Paul District of the U.S. Army Corps of Engineers. These data were collected during 1971-1981 (no data for 1976/77) by cooperative observers who gathered the data for use in their spring run-off hydrologic predictions. The observers had frost tubes installed by District personnel in their back yards. The early penetration of frost at the beginning of the freezing season was not observed, but most observers picked up the record when 1 or 2' of frost had occurred. This data base, a preliminary version, was constructed by Richard K. Haugen and Glenn King from the manuscript records of the cooperative observers and is presented on the CAPS Version 1.0 CD-ROM, June 1998.

This dataset contains water balance data for each year when winter wheat was grown at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL). Winter wheat was grown on two large, precision weighing lysimeters, each in the center of a 4.44 ha square field in the 1989-1990, 1991-1992, and 1992-1993 seasons. Irrigation was by linear move sprinkler system. Full irrigations were managed to replenish soil water used by the crop on a weekly or more frequent basis as determined by soil profile water content readings made with a neutron probe to 2.4-m depth in the field. Deficit irrigations were less than full - see crop calendars and irrigation data in these files for details. The weighing lysimeters were used to measure relative soil water storage to 0.05 mm accuracy at 5-minute intervals, and the 5-minute change in soil water storage was used along with precipitation and irrigation amounts to calculate crop evapotranspiration (ET), which is reported at 15-minute intervals. Because the large (3 m by 3 m surface area) weighing lysimeters are better rain gages than are tipping bucket gages, the 15-minute precipitation data are derived for each lysimeter from changes in lysimeter mass. The land slope is <0.3% and flat. The water balance data consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost fall, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected. The ET data should be considered to be the best values offered in these datasets. Even though ET data are also presented in the "lysimeter" datasets, the values herein are the result of a more rigorous quality control process. Dew and frost accumulation varies from year to year and seasonally within a year, and it is affected by lysimeter surface condition [bare soil, tillage condition, residue amount and orientation (flat or standing), etc.]. Particularly during winter and depending on humidity and cloud cover, dew and frost accumulation sometimes accounts for an appreciable percentage of total daily ET. These datasets originate from research aimed at determining crop water use (ET), crop coefficients for use in ET-based irrigation scheduling based on a reference ET, crop growth, yield, harvest index, and crop water productivity as affected by irrigation method, timing, amount (full or some degree of deficit), agronomic practices, cultivar, and weather. Prior publications have focused on winter wheat ET, crop coefficients, and crop water productivity. Crop coefficients have been used by ET networks. The data have utility for testing simulation models of crop ET, growth, and yield. Resources in this dataset:Resource Title: 1989 Bushland, TX. West Winter Wheat Evapotranspiration, Irrigation, and Water Balance Data. File Name: 1989_W_Wheat_water_balance.xlsxResource Description: The data consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost accumulation, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to precipitation, irrigation, frost and dew accumulation, emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected.Resource Title: 1990 Bushland, TX. West Winter Wheat Evapotranspiration, Irrigation, and Water Balance Data. File Name: 1990_W_Wheat_water_balance.xlsxResource Description: The data consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost accumulation, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to precipitation, irrigation, frost and dew accumulation, emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected.Resource Title: 1991 Bushland, TX. East Winter Wheat Evapotranspiration, Irrigation, and Water Balance Data. File Name: 1991_E_Wheat_water_balance.xlsxResource Description: The data consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost accumulation, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to precipitation, irrigation, frost and dew accumulation, emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected.Resource Title: 1992 Bushland, TX. East Winter Wheat Evapotranspiration, Irrigation, and Water Balance Data. File Name: 1992_E_Wheat_water_balance.xlsxResource Description: The data consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost accumulation, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to precipitation, irrigation, frost and dew accumulation, emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected.Resource Title: 1992 Bushland, TX. West Winter Wheat Evapotranspiration, Irrigation, and Water Balance Data. File Name: 1992_W_Wheat_water_balance.xlsxResource Description: The data consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost accumulation, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to precipitation, irrigation, frost and dew accumulation, emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected.Resource Title: 1993 Bushland, TX. West Winter Wheat Evapotranspiration, Irrigation, and Water Balance Data. File Name: 1993_W_Wheat_water_balance.xlsxResource Description: The data consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost accumulation, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to precipitation, irrigation, frost and dew accumulation, emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected.

This dataset includes frost tube data from 37 stations in the Upper Midwest (Minnesota, North Dakota, Wisconsin), USA. The responsible agency was the St. Paul District of the U.S. Army Corps of Engineers. These data were collected during 1971-1981 (no data for 1976/77) by cooperative observers who gathered the data for use in their spring run-off hydrologic predictions. The observers had frost tubes installed by District personnel in their back yards. The early penetration of frost at the beginning of the freezing season was not observed, but most observers picked up the record when 1 or 2' of frost had occurred. This data base, a preliminary version, was constructed by Richard K. Haugen and Glenn King from the manuscript records of the cooperative observers and is presented on the CAPS Version 1.0 CD-ROM, June 1998.

Micro-climatic monitoring of air and ground was started in 1990 to evaluate climatic controls on the present-day diurnal soil frost environment in the Western Cape mountains of South Africa. To this effect two data logger stations were established in the summit region of the Waaihoek mountains. Two sites were established at Waaihoek Peak and Mount Superior, respectively.Waaihoek Peak - The Waaihoek Peak monitoring site is positioned on the southeast extension of a small summit plateau at 1900m elevation where it changes into a southeast trending ridge flanked by two small valleys. The station stands on a 4 to 5 degree slope with an aspect of 140 degrees and is underlain by steeply dipping quartzitic sandstone of the Peninsula Formation. A shallow sandy soil here reaches a thickness of 0.35m and supports a sparse vegetation cover of Restio (Cape reeds) species up to 0.2m high with a total cover of around 30%. Initially both daily and hourly records were kept which necessitated frequent visits to replace the data storage tapes. As from 29-11-1992 only daily records were kept, including maximum and minimum temperature and 24 hour precipitation totals. Average daily soil moisture levels were recorded only as the range between daily maximum and minium values proved to be minimal.Mount Superior - Field observations established the presence of active soil frost features near Mount Superior during December 1991. A second data logger site was consequently established by 1-5-1993 to provide microclimatic data from a site with a different substrate and currently active soil-frost processes. The Mount Superior station is positioned 5km SSE of the Waaihoek Peak site on a flat summit plateau of Cedarberg shale at 1860m elevation. The surface cover is comprised of fractured bedrock and bare shallow soil with tussocks of Restio spp. up to 0.5m high. Daily maximum and minimum temperature were recorded for each sensor as well as daily average relative soil moisture levels and daily precipitation totals.These data are presented on the CAPS Version 1.0 CD-ROM, June 1998.

This indicator report trends in the number of frost days for 30 sites across Aotearoa New Zealand from 1972 to 2022. The number of frost days changes from year to year in response to variable weather patterns, and their occurrence is also influenced by climate change. Climate models project we may experience fewer cold and more warm extremes in the future. Changes in the number and timing of frost days can affect agriculture, horticulture, and viticulture, for example, by damaging and destroying crops at sensitive growth stages.

Variables: site: site the NIWA climate stations represent. period_start, period end: the period the trend represents. p_value: probability of obtaining test results at least as extreme as the result actually observed. slope: Sen slope statistic to describe rate of change. conf Low, conf Highl: 90% confidence intervals of the slope statistic (low and high). conf_level: specified confidence level of the estimate. z: Z score. trend_method: Statistical method. n: number of data points included in trend calculation. note: note s, var_s, tau: Mann-Kendall test statistics. alternative: the alternative hypothesis used for the Mann-Kendall test trend likelihood: likelihood of trend direction adapted from IPCC criteria. lat: approx. lattitude location of NIWA climate stations to represent a site. lon: approx. longitude location of NIWA climate stations to represent a site. region: region of the site the NIWA climate stations represent. pretty_site_name: site the NIWA climate stations represent. region_simple: region of the site the NIWA climate stations represent. site_simple: site the NIWA climate stations represent.

References: Hutchinson, G. K., Richards, K., & Risk, W. H. (2000). Aspects of accumulated heat patterns (growing-degree days) and pasture growth in Southland. Proceedings of the New Zealand Grassland Association, 62, 81–85. https://doi.org/10.33584/jnzg.2000.62.2396

Macara, G., Nichol, D., Liley, B., & Noll, B. (2023). Ministry for the Environment Atmosphere and Climate Report 2023: Updated Datasets supplied by NIWA (NIWA Client Report No. 2023072WN). https://environment.govt.nz/publications/atmosphere-and-climate-indicators-2023-updated-datasets

Macara, G., & Tait, A. (2015). Infilling of missing climate data: temperature, rainfall and wind (NIWA Client Report No. WLG2015-33). https://data.mfe.govt.nz/document/21253-macara-g-tait-a-2015-infilling-of-missing-climate-data-for-the-2015-environmental-synthesis-report-temperature-rainfall-and-wind/

Mastrandrea, M. D., Field, C. B., Stocker, T. F., Edenhofer, O., Ebi, K. L., Frame, D. J., Held, H., Kriegler, E., Mach, K. J., Matschoss, P. R., Plattner, G.-K., Yohe, G. W., & Zwiers, F. W. (2010). Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties. Intergovernmental Panel on Climate Change (IPCC). https://www.ipcc.ch/site/assets/uploads/2018/05/uncertainty-guidance-note.pdf

Seismic mseed files in SDS format containing geophone records from temporary mini-array deployments in Hornsund, Svalbard recorded within an SIOS-funded FROST project. The dataset comprises the following data: 24x3C + 20x1C in August 2023 (on-ice and tundra) and 20x1C in May and August 2024 (tundra).

This data set consists of ground frost observations made by gravediggers in Illinois. Frost depth and snow depth were determined visually at fresh excavations. In addition, subjective information was collected on surface conditions.

11709 Global import shipment records of Frost free with prices, volume & current Buyer’s suppliers relationships based on actual Global import trade database.

14 Global export shipment records of Frost,free with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

What does the data show?

This data shows the annual number of frost days (days where the minimum temperature is below 0°C) averaged over the 1991-2020 period. The data is from the HadUK-Grid v.1.1.0.0 dataset and is provided on the 2km British National Grid (BNG).

What are the naming conventions and how do I explore the data?

This data contains a field for the average over the period, named ‘Airfrost Days’.

To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578

Data source

HadUK-Grid v1.1.0.0 (downloaded 11/03/2022)

Useful links

Further information on HadUK-Grid Further information on understanding climate data within the Met Office Climate Data Portal

This dataset contains water balance data for each growing season (year) when maize (Zea mays, L., also known as corn in the United States) was grown for grain at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL). Maize was grown for grain on two large, precision weighing lysimeters, each in the center of a 4.44 ha square field. Irrigation was by linear move sprinkler system in 1989, 1990, and 1994. In 2013, 2016, and 2018, maize was grown on four lysimeters; two lysimeters and their respective fields were irrigated using subsurface drip irrigation (SDI), and two lysimeters and their respective fields were irrigated by a linear move sprinkler system. Irrigations were managed to replenish soil water used by the crop on a weekly or more frequent basis as determined by soil profile water content readings made with a neutron probe to 2.4-m depth in the field. The weighing lysimeters were used to measure relative soil water storage to 0.05 mm accuracy at 5-minute intervals, and the 5-minute change in soil water storage was used along with precipitation and irrigation amounts to calculate crop evapotranspiration (ET), which is reported at 15-minute intervals. Because the large (3 m by 3 m surface area) weighing lysimeters are better rain gages than are tipping bucket gages, the 15-minute precipitation data are derived for each lysimeter from changes in lysimeter mass. The land slope is

The FROST provides chemical analysis of four time-resolved sorbent samples on a LECO GCxGC Bench Time of Flight Mass Spectrometer, using a Gerstel MPS Thermal Desorption System. Samples collected via FROST can be analyzed on one of two Sandia National Laboratories' instruments. One instrument will provide ultra-high mass spectrometer resolution (up to four decimal points or m/z data) and can be used for identification of true unknowns. Data can include suspected formulas of species not included in any current mass spectra database. This instrument also has a low limit of detection of known species (tens of femtogram range). The second instrument can provide an order of magnitude lower limits of detection (into the single-digit femtogram range) for known species currently in mass spectra databases. This system is also more resilient to environmental samples that contain higher levels of moisture.

This data report is a summary of snow-survey information collected during a trip to the Arctic Slope April 12-15, 2004. The data were all collected as part of the Biocomplexity of Frost-Boil Ecosystems study (Walker et al. 2004). Snow is an important factor affecting soil-surface temperatures during the winter. These data will be used to help model the influence of snow on frost heave. The data collected included

Snow depth and soil temperature information from 97 of the 117 permanent plots (releves) that are part of a vegetation classification study.

Snow density and snow-water-equivalent (SWE) measurements from the midpoints of the four sides of each of ten 10x10-m grids at Happy Valley, Sagwon, Franklin Bluffs, and Deadhorse. We were not able to access the grids on B.P.-leased lands atWest Dock, and Howe Island, because we did not have B.P.'s "authorization to proceed".

Snow depths at every meter within each of the ten grids.

Snow profile descriptions from each of the ten grids.

Heave measurements from iron re-bar at releve sites and V. Romanovsky heave meters.

Snow depth measurements every 100 m within 1 x 1 km plot and at 45 permanent plots at Happy Valley.

About this dataset

Context

The dataset tabulates the Frost population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Frost. The dataset can be utilized to understand the population distribution of Frost by age. For example, using this dataset, we can identify the largest age group in Frost.

Key observations

The largest age group in Frost, TX was for the group of age 45-49 years with a population of 109 (11.91%), according to the 2021 American Community Survey. At the same time, the smallest age group in Frost, TX was the 85+ years with a population of 7 (0.77%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Frost is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Frost total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Frost Population by Age. You can refer the same here

This dataset provides information about the number of properties, residents, and average property values for 50th Street cross streets in Frost, MN.

Frost depth data shown in this map is queried from the North Central River Forecast Center (NCRFC) database late morning each day. Frost depth reports here are commonly from frost tube instruments, visual reports from construction or cemetery sites, or other types of electronic probes. Frost conditions are an important factor for hydrologic forecasting as frozen soil limits infiltration of water thereby generating more runoff from rain and snowmelt than soil that is not frozen. Knowing soil frost condition is also important for many activities including agriculture, horticulture, transportation, construction, and even grave digging.

This dataset provides information about the number of properties, residents, and average property values for Fm 667 cross streets in Frost, TX.

This dataset contains the predicted prices of the asset Frost over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.