diff --git a/datasets/cmip6-tasmax-monthly-annual-max.data.mdx b/datasets/cmip6-tasmax-monthly-annual-max.data.mdx index 06b9cd744..ef577b77e 100644 --- a/datasets/cmip6-tasmax-monthly-annual-max.data.mdx +++ b/datasets/cmip6-tasmax-monthly-annual-max.data.mdx @@ -25,7 +25,7 @@ infoDescription: | - **Temporal Resolution:** Annual - **Spatial Extent:** Global - **Spatial Resolution:** 0.25 degrees x 0.25 degrees - - **Data Units:** F + - **Data Units:** °F - **Data Type:** Research disableExplore: true layers: @@ -71,7 +71,7 @@ layers: source: NASA spatialExtent: Global temporalResolution: Annual - unit: Days + unit: °F --- @@ -83,10 +83,10 @@ layers: * **Temporal Resolution:** Annual * **Spatial Extent:** Global * **Spatial Resolution:** 0.25 degrees x 0.25 degrees - * **Data Units:** Degrees Farenheit + * **Data Units:** Degrees Fahrenheit * **Data Type:** Research - This dataset provides the Annual Maximum Near-Surface Air Temperature from 1950 - 2100. The projections are provided for the four different SSP standard scenarios ([SSP126, SSP245, SSP370, SSP585](https://www.dkrz.de/en/communication/climate-simulations/cmip6-en/the-ssp-scenarios)). The Annual Maximum Near-Surface Air Temperature serves as an essential metric for assessing and understanding future climate for the different emissions scenario, and is a valuable tool for climate scientists, researchers, and policymakers. Monitoring and projecting near surface air temperature over time allows for the identification of trends and variations in temperature extremes, which is crucial for understanding the impact of climate change on local and global climates. + This dataset provides the Annual Maximum Near-Surface Air Temperature from 1950 - 2100. The projections are provided for the four different SSP standard scenarios ([SSP126, SSP245, SSP370, SSP585](https://www.dkrz.de/en/communication/climate-simulations/cmip6-en/the-ssp-scenarios)). The Annual Maximum Near-Surface Air Temperature serves as an essential metric for assessing and understanding future climate for the different emissions scenarios, and is a valuable tool for climate scientists, researchers, and policymakers. Monitoring and projecting near surface air temperature over time allows for the identification of trends and variations in temperature extremes, which is crucial for understanding the impact of climate change on local and global climates.