In 2023, Mexico's minimum average temperature stood at 15.2 degrees Celsius, up from 14.5 degrees Celsius in the previous year. During the period in consideration, the minimum temperature in the Latin American country reached a record low in the year 2000, at some 12.9 degrees Celsius. Since then, temperatures have been slowly rising, recording some of Mexico's highest maximum temperatures on average in recent years.

The state of Tlaxcala recorded the coldest minimum average temperature across Mexico in 2023, at just 7.5 degrees Celsius. Meanwhile, Quintana Roo registered the highest minimum temperature that year – with values reaching 23 degrees Celsius – closely followed by the state of Tabasco. Accordingly, both states were amongst Mexico's warmest states on average in 2023.

In 2023, Mexico's maximum average temperature measured 30.2 degrees Celsius. This was an increase of 0.6 degrees Celsius from the previous year and the highest maximum temperature recorded in the Latin American country since at least the year 2000. Accordingly, 2023 was also Mexico's warmest year on average since the turn of the century.

This dataset contains yearly gridded information of precipitation, minimum, average and maximum precipitation for Mexico at a spatial resolution of 600 metres for the 1951-2020 period. This gridded dataset is georeferenced and provided in geographic coordinates (resolution 20 arc sec).Files:Yearly Precipitation: yearprecip_1951_2020.zip Yearly Maximum Temperature: year_tmax_1951_2020.zipYearly Minimum Temperature: year_tmin_1951_2020.zipYearly Average Temperature: year_tavg_1951_2020.zip

The month of June recorded Mexico's highest maximum average temperature in 2023, at some 35.3 degrees Celsius. This was followed by July and August, both with maximum temperatures of around 34 degrees Celsius. On the other hand – with an average maximum temperature of 24.2 degrees Celsius – December registered the lowest figure of 2023.

Monthly and yearly normals of Tmin, Tavg, Tmax and precipitation in Mexico for the 1951-1980 period. These normals were computed from the monthly values of the MexHiResClimDB which were in turn determined from the daily gridded values. Filesmonthlynorm5180precip.zip Precipitation monthly normals, 1951-1980 periodmonthlynorm5180avgtmin.zip Minimum temperature monthly normals, 1951-1980 periodmonthlynorm5180avgtmax.zip Maximum temperature monthly normals, 1951-1980 periodmonthlynorm5180avgtavg.zip Average temperature monthly normals, 1951-1980 periodyearnorm5180precip.zip Precipitation yearly normal 1951-1980 periodyearnorm5180avgtmin.zip Minimum temperature yearly normal 1951-1980 periodyearnorm5180avgtmax.zip Maximum temperature yearly normal 1951-1980 periodyearnorm5180avgtavg.zip Average temperature yearly normal 1951-1980 period

Climate Merida (Mexico)
This dataset falls under the category Environmental Data Environmental / Climate Assesments.
It contains the following data: Merida are in the middle and the summers are that easy to define. The best time to visit are January, February, March, October, November, December The month with the highest relative humidity is September (77.17 %). The month with the lowest relative humidity is April (54.53 %). The month with the highest number of rainy days is September (19.13 days). The month with the lowest number of rainy days is February (3.30 days).
This dataset was scouted on 2022-09-30 as part of a data sourcing project conducted by TUMI. License information might be outdated: Check original source for current licensing. The data can be accessed using the following URL / API Endpoint: https://en.climate-data.org/north-america/mexico/yucatan/merida-3374/See URL for data access and license information.

The state of Sinaloa recorded the highest maximum average temperature across Mexico in 2022, at some 33.2 degrees Celsius. Ranking second that year was the state of Campeche, with an annual maximum temperature of 33 degrees Celsius. By contrast – at only 23 degrees Celsius – State of Mexico registered the lowest maximum average temperature in 2022.

The core of this project focuses on monitoring the phenotypic and genotypic evolution of experimental and natural hybrid populations of swordtails for ten generations. To get a clear understanding of how evolution shapes genome wide ancestry and the distribution of species-specific alleles at functional loci during early generations of hybridization, it's important to monitor these populations using experimental crosses. Eight replicate 2000 L mesocosm stock tanks were built at high (1514 m), intermediate (980 m), and low (186 m) elevations near the CICHAZ field site were seeded with Xiphophorus birchmanni – X. malinche F1 hybrids. The F1s were generated by crossing X. malinche females with X. birchmanni malesin stock tanks at CICHAZ, a research station in Calnali, Mexico. Tanks at higher elevations experience cooler water temperatures. Our experimental design thereby allows us to characterize how ecological selection shapes genotypic and phenotypic differences in thermal tolerance across hybrid populations exposed to different temperature regimes. The data contained in these files include recorded water temperature (in Celsius), taken every six hours from three stock tanks at low (186 m: STL), medium (980 m: STM), and high (1514 m: STH) elevations, along with three natural river sites. File Natural.csv contains the natural sites and the file Stock Tanks.csv contains the corresponding natural sites. Acuapa (ACUA) is paired with STL, Aguazarca (AGZC) is paired with STM, and Tlatemaco (TLMC) is paired with STH.

Temperature data classified as maximum, mean, and minimum temperature and relative humidity measures from the meteorological station located at the regional airport in Bogota and Buenos Aries, called the National Service of Hydrology and Meteorology. Mexico data was collected from the National Polytechnic Institute of Mexico and National Meteorological System. In Santiago, Chile weather data was provided by the air pollution monitoring network with stations across the city, the REDCAM2 (Red de Monitoreo Automatica de la Calidad del Aire Metropolitana) Automatic Monitoring Network of Metropolitan Air Quality. The data from these stations were averaged to obtain temperature values for the Gran Santiago region. Daily temperature and relative humidity readings were made by automatic-recording instruments.

With an average temperature of some 28.3 degrees Celsius, the southern state of Campeche was Mexico's warmest state in 2023. This was closely followed by Tabasco and Yucatán, with average temperatures reaching 28.1 and 27.9 degrees Celsius, respectively. On the other side of the spectrum, State of Mexico recorded the lowest mean temperature across the Latin American country, at just 15.5 degrees Celsius.

These rasters provide the local mean annual extreme low temperature from 1991 to 2020 in an 800m x 800m grid covering the USA (including Puerto Rico) based on interpolation of data from more than a thousand weather stations. Each location's Plant Hardiness Zone is calculated based on classifying that temperature into 5 degree bands.The classified rasters are then used to create print and interactive maps.Temperature station data for the 2023 edition of the USDA Plant Hardiness Zone Map (PHZM) came from many different sources. In the eastern and central United States, Puerto Rico, and Hawaii, data came primarily from weather stations of the National Weather Service and several state networks. In the western United States and Alaska, data from stations maintained by USDA Natural Resources Conservation Service, USDA Forest Service, U.S. Department of the Interior (DOI) Bureau of Reclamation, and DOI Bureau of Land Management also helped to better define hardiness zones in mountainous areas. Environment Canada provided data from Canadian stations, and data from Mexican stations came from the Mexico National Weather Service and the Global Historical Climate Network. The USDA PHZM was produced with PRISM, a highly sophisticated climate mapping technology developed at Oregon State University. The map was produced from a digital computer grid, with each cell measuring about a half mile on a side. PRISM estimated the mean annual extreme minimum temperature for each grid cell (or pixel on the map) by examining data from nearby stations; determining how the temperature changed with elevation; and accounting for possible coastal effects, temperature inversions, and the type of topography (ridge top, hill slope, or valley bottom). Information on PRISM can be obtained from the PRISM Climate Group website https://prism.oregonstate.edu. Once a draft of the map was completed, it was reviewed by a team of climatologists, agricultural meteorologists, and horticultural experts. If the zone for an area appeared anomalous to these expert reviewers, experts doublechecked the draft maps for errors or biases. A detailed explanation of the mapmaking process and a discussion of the horticultural applications of the 2012 PHZM (similar to 2023) are available from the articles listed below. Daly, C., M.P. Widrlechner, M.D. Halbleib, J.I. Smith, and W.P. Gibson. 2012. Development of a new USDA Plant Hardiness Zone Map for the United States. Journal of Applied Meteorology and Climatology, 51: 242-264.Widrlechner, M.P., C. Daly, M. Keller, and K. Kaplan. 2012. Horticultural Applications of a Newly Revised USDA Plant Hardiness Zone Map. HortTechnology, 22: 6-19.

If freezing limits establishment of warm desert shrubs at high latitudes, shrubland distributions may be altered as a result of rising global temperatures. However, variation in plant physiology and morphology can be observed across climate gradients and may be acted on by selection to produce adaptation to local climate conditions, thereby ameliorating low temperature stress. Freezing damage in evergreens is closely linked to vessel size distribution because larger xylem conduits are more likely to become air-filled during freezing. In addition, plastic variation, rather than genetic, may be responsible for differences in freezing tolerance among populations. In order to determine if local adaptation to freezing is present in two species of the genus Larrea, L. tridentata and L. divaricata, we investigated xylem vessel size distributions in field grown L. tridentata adults and saplings grown in a common garden from high latitude (Sevilleta National Wildlife Refuge) and low latitude (Higuerillas, Mexico) sites in the Chihuahuan Desert in North America. High latitude (Bajada del Diablo, Argentina) and low latitude (Chamical, Argentina) populations of Larrea divaricata were selected for investigation from the Monte Desert in South America.

In 2023, Mexico's warmest months were registered during the summer, with July recording the highest average temperature that year, at some 27.6 degrees Celsius. On the other hand – with an average temperature of 17 degrees Celsius – December was the coolest month in 2023. That same year, Campeche was Mexico's warmest state on average.

The Advanced Weather Interactive Processing System (AWIPS) uses shapefiles for base maps in the system. These shapefiles contain boundaries of areas used by NWS for forecasts and warnings as well as map backgrounds.NWS BordersThe County Warning Area boundaries are the counties/zones for which each Weather Forecast Office (WFO) is responsible for issuing forecasts and warnings. The shapefile was created by aggregating public zones with the same CWA designation into a single polygon and manually adjusting the boundaries of the exceptions to the rule.The NWS county and state borders are background map used internally in NWS.Coastal Marine Zone ForecastThis map layer contains links to NWS marine weather forecasts for coastal or nearshore waters within 20nm of shore out to Day 5. It includes predictions on the likelihood of precipitation and/or reduced visibility, surface wind direction and speed, seas or combined seas, and icing. Air temperature forecasts are optional. The forecasts will also include any marine weather advisories, watches, and/or warnings. The purpose of the forecasts is to support and promote safe transportation across the coastal waters. The forecasts are issued twice per day with updates as necessary by NWS Weather Forecast Offices (WFOs) along the coast and Great Lakes.Offshore Zone ForecastsThis map layer contains links to NWS marine weather forecasts for offshore waters beyond 20 or 30nm of shore out to Day 5. The forecast provides information to mariners who travel on the oceanic waters adjacent to the U.S., its territorial coastal waters and the Caribbean Sea. The forecasts include predictions on the likelihood of precipitation and/or reduced visibility, surface wind direction and speed, seas and likelihood of icing out to Day 5 along with information about any warnings. The offshore forecasts for the Western North Atlantic and Eastern North Pacific Oceans are produced by NWS/NCEP's Ocean Prediction Center. The offshore forecasts for the Gulf of Mexico and Caribbean Sea are issued by the NWS/NCEP National Hurricane Center's Tropical Analysis and Forecast Branch (TAFB). OPC and NHC/TAFB issues the forecasts four times daily at regular intervals, with updates when necessary. The offshore forecast for the waters around Hawaii are issued by the NWS Weather Forecast Office in Honolulu, HI four times daily at regular intervals, with updates when necessary. The offshore forecasts for Alaska waters in the Bering Sea and Gulf of Alaska are issued by NWS Weather Forecast Offices in Alaska at least twice a day with updates as necessary. The WFOs in Alaska include WFO Anchorage, WFO Fairbanks, and WFO Juneau.Public Weather Zone ForecastsThis layer includes links to NWS web pages posting the latest NWS surface weather forecasts, a zone-type forecast providing the average forecast conditions across the zone, usually at the county-scale or sub-county scale. These text forecasts include predictions of weather, sky cover, maximum and minimum surface air temperatures, surface wind direction and speed, and probability of precipitation out to 7 days into the future. In addition, the forecast highlights at the top include any active weather advisories, watches, and/or warnings. These zone predictions are derived from gridded forecasts created by NWS Weather Forecast Offices throughout the U.S. The text weather forecasts are usually issued in the early morning (e.g. 4AM LT) and early evening (4PM LT). They are updated during late mornings and late night and during fast changing weather conditions.Fire Weather Zone ForecastsThis layer includes links to NWS web pages posting the latest NWS Fire Weather Planning Forecasts, a zone-type forecast providing the average fire weather conditions across the zone. According to the NWS, the forecast is "used by land management personnel primarily for input in decision-making related to pre-suppression and other planning." The forecast is valid from the time of issuance through day five and sometimes through day seven and usually has a minimum of three 12-hour time periods. The forecast will have included a discussion of weather patterns affecting the forecast zone or area, identification of any active fire weather watches/warnings and a table of predicted fire weather variables for the next two days: 1) sky/weather conditions, 2) max/min air temperatures, 3) max/min relative humidity, 4) 0-minute average wind direction/speed at 20 feet and sometimes at another height (e.g. 10,000, 15,000 ft), 5) precipitation amount, duration, and timing, 6) mixing height, 7) transport winds, 8) vent category, and 9) several fire weather indices such as Haines Index, Lightning Activity (LAL), Chance of Wetting Rainfall (CWR), Dispersion Index, Low Visibility Occurrence Risk Index (LVORI), and Max LVORI. In addition, it will usually have a forecast in plain text for days 3 to 7. Sometimes an optional outlook of expected conditions for day 6 or possibly for day 6 and 7 is expected. The forecasts are issued by NWS WFOs at least once daily during the local fire season.Metadata:CWA: https://www.weather.gov/gis/CWAmetadataCoastal Marine: https://www.weather.gov/gis/CoastalMarineMetadataOffshore: https://www.weather.gov/gis/OffshoreZoneMetadataPublic Zones: https://www.weather.gov/gis/PublicZoneMetadataFire Zones: https://www.weather.gov/gis/FireZoneMetadataCounties: https://www.weather.gov/gis/CountyMetadataStates: https://www.weather.gov/gis/StateMetadataLink to data download: https://www.weather.gov/gis/AWIPSShapefilesQuestions/Concerns about the service, please contact the DISS GIS teamTime Information:This service is not time enabled

description: This data set provides Daymet Version 3 model output data as gridded estimates of daily weather parameters for North America and Hawaii: including Canada, Mexico, the United States of America, Puerto Rico, and Bermuda. The island areas of Hawaii and Puerto Rico are available as files separate from the continental land mass. Daymet output variables include the following parameters: minimum temperature, maximum temperature, precipitation, shortwave radiation, vapor pressure, snow water equivalent, and day length. The data set covers the period from January 1, 1980 to December 31 of the most recent full calendar year. Each subsequent year is processed individually at the close of a calendar year. Daymet variables are continuous surfaces provided as individual files, by variable and year, at a 1-km x 1-km spatial resolution and a daily temporal resolution. Data are in a Lambert Conformal Conic projection for North America and are distributed in a netCDF file (version 1.6) format compliant to Climate and Forecast (CF) metadata conventions. https://daymet.ornl.gov/overview.html Reference: Thornton, P.E., M.M. Thornton, B.W. Mayer, Y. Wei, R. Devarakonda, R.S. Vose, and R.B. Cook. 2016. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 3. ORNL DAAC, Oak Ridge, Tennessee, USA. http://dx.doi.org/10.3334/ORNLDAAC/1328; abstract: This data set provides Daymet Version 3 model output data as gridded estimates of daily weather parameters for North America and Hawaii: including Canada, Mexico, the United States of America, Puerto Rico, and Bermuda. The island areas of Hawaii and Puerto Rico are available as files separate from the continental land mass. Daymet output variables include the following parameters: minimum temperature, maximum temperature, precipitation, shortwave radiation, vapor pressure, snow water equivalent, and day length. The data set covers the period from January 1, 1980 to December 31 of the most recent full calendar year. Each subsequent year is processed individually at the close of a calendar year. Daymet variables are continuous surfaces provided as individual files, by variable and year, at a 1-km x 1-km spatial resolution and a daily temporal resolution. Data are in a Lambert Conformal Conic projection for North America and are distributed in a netCDF file (version 1.6) format compliant to Climate and Forecast (CF) metadata conventions. https://daymet.ornl.gov/overview.html Reference: Thornton, P.E., M.M. Thornton, B.W. Mayer, Y. Wei, R. Devarakonda, R.S. Vose, and R.B. Cook. 2016. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 3. ORNL DAAC, Oak Ridge, Tennessee, USA. http://dx.doi.org/10.3334/ORNLDAAC/1328

This accession contains the Global Ocean Surface Underway Data (GOSUD) v3.0 thermosalinographs data from 1992-01-01 to 1992-12-31 as submitted to NOAA/NCEI. The data includes information about sea surface temperature and salinity, in netCDF formatted files, obtained with the use of thermosalinographs (TSG) installed in a variety of ships. The datasets provided by the various contributors are collected and assembled by GOSUD, an initiative of the International Oceanographic Data and Information Exchange (IODE) of the Intergovernmental Oceanographic Commission (IOC) programme. All data are quality controlled and flagged by GOSUD following the GOSUD procedures and criteria. The measured variables or parameters include conductivity, sea surface salinity, sea surface water temperature (using internal sensor), water temperature (using external sensor, when available), latitude, longitude and time. The originator's data have different temporal resolutions ranging from three minute median filtered values to one hour point values. The spatial coverage of the dataset is global.

description: LOCA is a statistical downscaling technique that uses past history to add improved fine-scale detail to global climate models. We have used LOCA to downscale 32 global climate models from the CMIP5 archive at a 1/16th degree spatial resolution, covering North America from central Mexico through Southern Canada. The historical period is 1950-2005, and there are two future scenarios available: RCP 4.5 and RCP 8.5 over the period 2006-2100 (although some models stop in 2099). The variables currently available are daily minimum and maximum temperature, and daily precipitation. For more information visit: http://loca.ucsd.edu/; abstract: LOCA is a statistical downscaling technique that uses past history to add improved fine-scale detail to global climate models. We have used LOCA to downscale 32 global climate models from the CMIP5 archive at a 1/16th degree spatial resolution, covering North America from central Mexico through Southern Canada. The historical period is 1950-2005, and there are two future scenarios available: RCP 4.5 and RCP 8.5 over the period 2006-2100 (although some models stop in 2099). The variables currently available are daily minimum and maximum temperature, and daily precipitation. For more information visit: http://loca.ucsd.edu/