This dataset was scraped from the World Bank Climate Knowledge https://climateknowledgeportal.worldbank.org/ for all available countries from 1901 to 2022. Dataset also includes 5 year smooth temperature values.

This dataset provides values for TEMPERATURE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset provides values for TEMPERATURE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The table Global Temperatures by Country is part of the dataset Climate Change: Earth Surface Temperature Data, available at https://columbia.redivis.com/datasets/1e0a-f4931vvyg. It contains 577462 rows across 4 variables.

Abstract

Compilation of Earth Surface temperatures historical. Source: https://www.kaggle.com/berkeleyearth/climate-change-earth-surface-temperature-data

Documentation

Data compiled by the Berkeley Earth project, which is affiliated with Lawrence Berkeley National Laboratory. The Berkeley Earth Surface Temperature Study combines 1.6 billion temperature reports from 16 pre-existing archives. It is nicely packaged and allows for slicing into interesting subsets (for example by country). They publish the source data and the code for the transformations they applied. They also use methods that allow weather observations from shorter time series to be included, meaning fewer observations need to be thrown away.

In this dataset, we have include several files:

Global Land and Ocean-and-Land Temperatures (GlobalTemperatures.csv):

• Date: starts in 1750 for average land temperature and 1850 for max and min land temperatures and global ocean and land temperatures

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• LandAverageTemperature: global average land temperature in celsius

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• LandAverageTemperatureUncertainty: the 95% confidence interval around the average

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• LandMaxTemperature: global average maximum land temperature in celsius

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• LandMaxTemperatureUncertainty: the 95% confidence interval around the maximum land temperature

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• LandMinTemperature: global average minimum land temperature in celsius

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• LandMinTemperatureUncertainty: the 95% confidence interval around the minimum land temperature

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• LandAndOceanAverageTemperature: global average land and ocean temperature in celsius

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• LandAndOceanAverageTemperatureUncertainty: the 95% confidence interval around the global average land and ocean temperature

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**Other files include: **

• Global Average Land Temperature by Country (GlobalLandTemperaturesByCountry.csv)

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• Global Average Land Temperature by State (GlobalLandTemperaturesByState.csv)

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• Global Land Temperatures By Major City (GlobalLandTemperaturesByMajorCity.csv)

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• Global Land Temperatures By City (GlobalLandTemperaturesByCity.csv)

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The raw data comes from the Berkeley Earth data page.

The mean annual temperature in North America stood at -4.5 degrees Celsius in 1995. It is expected that, 30 years later in 2025, the average temperature will increase by 1.6 degrees Celsius due to the effects of global warming, under a scenario where global temperatures increase by 1.5 degree Celsius.

The average temperature in December 2024 was 38.25 degrees Fahrenheit in the United States, the fourth-largest country in the world. The country has extremely diverse climates across its expansive landmass. Temperatures in the United States On the continental U.S., the southern regions face warm to extremely hot temperatures all year round, the Pacific Northwest tends to deal with rainy weather, the Mid-Atlantic sees all four seasons, and New England experiences the coldest winters in the country. The North American country has experienced an increase in the daily minimum temperatures since 1970. Consequently, the average annual temperature in the United States has seen a spike in recent years. Climate Change The entire world has seen changes in its average temperature as a result of climate change. Climate change occurs due to increased levels of greenhouse gases which act to trap heat in the atmosphere, preventing it from leaving the Earth. Greenhouse gases are emitted from various sectors but most prominently from burning fossil fuels. Climate change has significantly affected the average temperature across countries worldwide. In the United States, an increasing number of people have stated that they have personally experienced the effects of climate change. Not only are there environmental consequences due to climate change, but also economic ones. In 2022, for instance, extreme temperatures in the United States caused over 5.5 million U.S. dollars in economic damage. These economic ramifications occur for several reasons, which include higher temperatures, changes in regional precipitation, and rising sea levels.

This statistic shows a ranking of the estimated worldwide average temperature in 2020, differentiated by country. The figure refers to the projected annual average temperature for the period 2020-2039 as modelled by the GISS-E2-R model in the RCP 4.5 scenario (Medium-low emission).The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

The table Global Temperatures by City is part of the dataset Climate Change: Earth Surface Temperature Data, available at https://columbia.redivis.com/datasets/1e0a-f4931vvyg. It contains 8599212 rows across 7 variables.

This dataset provides values for TEMPERATURE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The mean annual temperature in the United Kingdom was **** degrees Celsius in 2023, an increase of **** degrees Celsius compared to the the mean temperature from 1991 to 2020. In the same year, England had the highest annual mean temperature in the UK, at almost ** degrees Celsius.

This dataset provides values for TEMPERATURE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset provides high-resolution gridded temperature and precipitation observations from a selection of sources. Additionally the dataset contains daily global average near-surface temperature anomalies. All fields are defined on either daily or monthly frequency. The datasets are regularly updated to incorporate recent observations. The included data sources are commonly known as GISTEMP, Berkeley Earth, CPC and CPC-CONUS, CHIRPS, IMERG, CMORPH, GPCC and CRU, where the abbreviations are explained below. These data have been constructed from high-quality analyses of meteorological station series and rain gauges around the world, and as such provide a reliable source for the analysis of weather extremes and climate trends. The regular update cycle makes these data suitable for a rapid study of recently occurred phenomena or events. The NASA Goddard Institute for Space Studies temperature analysis dataset (GISTEMP-v4) combines station data of the Global Historical Climatology Network (GHCN) with the Extended Reconstructed Sea Surface Temperature (ERSST) to construct a global temperature change estimate. The Berkeley Earth Foundation dataset (BERKEARTH) merges temperature records from 16 archives into a single coherent dataset. The NOAA Climate Prediction Center datasets (CPC and CPC-CONUS) define a suite of unified precipitation products with consistent quantity and improved quality by combining all information sources available at CPC and by taking advantage of the optimal interpolation (OI) objective analysis technique. The Climate Hazards Group InfraRed Precipitation with Station dataset (CHIRPS-v2) incorporates 0.05° resolution satellite imagery and in-situ station data to create gridded rainfall time series over the African continent, suitable for trend analysis and seasonal drought monitoring. The Integrated Multi-satellitE Retrievals dataset (IMERG) by NASA uses an algorithm to intercalibrate, merge, and interpolate “all'' satellite microwave precipitation estimates, together with microwave-calibrated infrared (IR) satellite estimates, precipitation gauge analyses, and potentially other precipitation estimators over the entire globe at fine time and space scales for the Tropical Rainfall Measuring Mission (TRMM) and its successor, Global Precipitation Measurement (GPM) satellite-based precipitation products. The Climate Prediction Center morphing technique dataset (CMORPH) by NOAA has been created using precipitation estimates that have been derived from low orbiter satellite microwave observations exclusively. Then, geostationary IR data are used as a means to transport the microwave-derived precipitation features during periods when microwave data are not available at a location. The Global Precipitation Climatology Centre dataset (GPCC) is a centennial product of monthly global land-surface precipitation based on the ~80,000 stations world-wide that feature record durations of 10 years or longer. The data coverage per month varies from ~6,000 (before 1900) to more than 50,000 stations. The Climatic Research Unit dataset (CRU v4) features an improved interpolation process, which delivers full traceability back to station measurements. The station measurements of temperature and precipitation are public, as well as the gridded dataset and national averages for each country. Cross-validation was performed at a station level, and the results have been published as a guide to the accuracy of the interpolation. This catalogue entry complements the E-OBS record in many aspects, as it intends to provide high-resolution gridded meteorological observations at a global rather than continental scale. These data may be suitable as a baseline for model comparisons or extreme event analysis in the CMIP5 and CMIP6 dataset.

Temperatures have risen in the last 100 years around the world. In the 1910s, global average temperatures were some 0.38 degrees Celsius lower than the average temperatures between 1910 and 2000. In the most recent decade, the world experienced temperatures that were 1.21 degrees Celsius over the average.

Summary

Annual estimates of mean surface temperature change measured with respect to a baseline climatology, corresponding to the period 1951-1980.

Estimates of changes in the mean surface temperature are presented, in Degree Celsius, for the years 1961-2021 by country and for World.

Acknowledgement

Thanks to IMF for providing the data

Foto von Li-An Lim auf Unsplash

Global Temperature: Daily Average: United States: Sheppard Afb data was reported at 27.500 Degrees Celsius in 01 Oct 2024. This records a decrease from the previous number of 30.000 Degrees Celsius for 24 Sep 2024. Global Temperature: Daily Average: United States: Sheppard Afb data is updated daily, averaging 30.000 Degrees Celsius from Sep 2024 (Median) to 01 Oct 2024, with 5 observations. The data reached an all-time high of 35.500 Degrees Celsius in 19 Sep 2024 and a record low of 25.000 Degrees Celsius in 23 Sep 2024. Global Temperature: Daily Average: United States: Sheppard Afb data remains active status in CEIC and is reported by Climate Prediction Center. The data is categorized under Global Database’s United States – Table US.CPC.GT: Environmental: Global Temperature: Daily Average.

Temperatures have risen in the last 100 years around the world. In the 1910s, North America had an average temperature some **** degrees Celsius lower than average temperatures between 1910 and 2000. In the most recent decade, this region experienced temperatures **** degrees Celsius over the average. All global regions (excluding Oceania) experienced an increased temperature over one degree Celsius in the 2010s, compared to the average between 1910 and 2000.

Dataset del covid-19 obtenido mediante técnicas de web Scrapping

ABSTRACT Background: Following two years of the Covid-19 pandemic, thousands of deaths were registered around the world, however, death tolls differed from a country to another. A question on whether climate parameters in each country could or not affects coronavirus incidence and Covid-19 death toll is under debate. Objective: In the present work, it is aimed to check the numbers of deaths caused by Covid-19 in 39 countries of four continents (America, Europe, Africa and Asia), and to analyse their possible correlation with climate parameters in a given country, such as the mean of annual temperature, the annual average sunshine hours and the annual average UV index in each country. Methods: We have sought the deaths number caused by Covid-19 in 39 countries and have analysed its correlation degree with the mean annual temperature, the average annual sunshine hours and the average annual UV index. Correlation and determination factors were obtained by Microsoft Exell software (2016). Results: In the present study, higher numbers of deaths related to Covid-19 were registered in many countries of Europe and America compared to other countries in Africa and Asia. On the other hand, after both the first year and the second year of the pandemic, the death numbers registered in the 39 countries of our study were very negatively correlated with the three climate factors of our study, namely, annual average temperature, sunshine hours and UV index. Conclusion:The results of the present study prove that the above climate parameters may have some kind of influence on the coronavirus incidence through a yet unknown mechanism. Our data support the hypothesis that countries which have elevated annual temperatures and elevated sunshine hours may be less vulnerable to the coronavirus SARS-CoV-2 and to its associated Covid-19 disease. Countries with the above characteristics have also elevated levels of average annual UV rays that might play a key role against the spread of the coronavirus.Thus, geographical latitude and longitude of a given country could have been the key points for the outcome of virus incidence and Covid-19 spread around the globe during the past two years. The results prove that elevated levels of temperature, sunshine hours and UV index could play a protective effect against the coronavirus, although their mechanisms of action are still unknown.

The FAOSTAT Temperature change on land domain disseminates statistics of mean surface temperature change by country, with annual updates. The current dissemination covers the period 1961–2024. Statistics are available for monthly, seasonal and annual mean temperature anomalies, i.e., temperature change with respect to a baseline climatology, corresponding to the period 1951–1980. The standard deviation of the temperature change of the baseline methodology is also available. Data are based on the publicly available GISTEMP data, the Global Surface Temperature Change data distributed by the National Aeronautics and Space Administration Goddard Institute for Space Studies (NASA-GISS).