This dataset provides early instrumental data recovered in Latin-America and the Caribbean. Data have been retrieved from 20 countries (Argentina, Bahamas, Belize, Brazil, British Guiana, Chile, Colombia, Costa Rica, Cuba, Ecuador, France (Martinique and Guadalupe), Guatemala, Jamaica, Mexico, Nicaragua, Panama, Peru, Puerto Rico, El Salvador and Suriname) and they cover the 18th and 19th centuries. The main meteorological variables retrieved are air temperature, atmospheric pressure and precipitation but other variables, such as humidity, wind direction, or state of the sky have been retrieved when possible. In total, more than 300.000 early instrumental observations have been rescued. Each archive shows a headline with the following information: ID: 6 letters, the first three make reference to the country and the last three letters to the city/location of the observations. Country: Current name of the country where the observation were recorded. City: Current name of the city or location where the observation were recorded. Period: Time period covered by the series at monthly scale when possible. Resolution: Time resolution of the series. Observers: Name of the people that recorded the measurements. Location Observatory: Latitude and longitude of the observatory in WGS84, altitude when available. The name of the observatory or the street where it was is provided, when the location is exactly known. When the precise location is unknown a probable latitude and longitude is provided. Meteorological variables: Describe all the meteorological variables recorded, its units and the corresponding columns in the file. Data source: The complete reference of the documentary source in which the meteorological record was provided. Descriptive Name: A name of the archive that makes reference to the location and the period covered by the series. Other comments: All the metadata rescued about the observations or the observer. Also provides extreme or rare events recorded by the observer and any other information that could be useful to interpret the series. After the headline, the first columns give the temporal information of the record (year, season, month, day and hour) and the following columns show the measurements of each meteorological variable. Every column has a short descriptive title.

This layer shows Population and Poverty Status. This is shown by state and county boundaries. This service contains the 2018-2022 release of data from the American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of people whose income in the past 12 months is below poverty level. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right.Current Vintage: 2018-2022ACS Table(s): B17017, C17002, DP02, DP03Data downloaded from: Census Bureau's API for American Community Survey Date of API call: January 18, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.