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<Prose>
The NASA Earth Exchange (NEX) Global Daily Downscaled Projections (GDDP) dataset, or NEX-GDDP-CMIP6, was created to assist the science community in conducting studies of climate change impacts at local to regional scales and to enhance public understanding of possible future climate patterns at the spatial scale of individual towns, cities, and watersheds. The archive contains downscaled historical (1950 - 2015) and future (2015 - 2100) projections of [climate variables](https://www.nature.com/articles/s41597-022-01393-4/tables/2) such as humidity, precipitation, and near-surface air temperature, based on output from [Phase 6 of the Climate Model Intercomparison Project (CMIP6)](https://www.wcrp-climate.org/wgcm-cmip/cmip-video). The downscaled products are provided at 0.25 degree horizontal resolution. The data are also available for four different future climate scenarios modeled as part of CMIP6. These scenarios take into account future radiative forcing levels (from low to high) as well as “Shared Socioeconomic Pathways” (SSPs) which are a collection of narratives that describe potential paths society will take in order to combat climate change. The SSPs range from a highly sustainable approach (SSP1) to a narrative where society continues to rely heavily on fossil fuel resources (SSP5). The four resulting combined scenarios are SSP126, SSP245, SSP370 and SSP585. Learn more about the scenarios here: [https://www.dkrz.de/en/communication/climate-simulations/cmip6-en/the-ssp-scenarios](https://www.dkrz.de/en/communication/climate-simulations/cmip6-en/the-ssp-scenarios)
<Prose>
The NASA Earth Exchange (NEX) Global Daily Downscaled Projections (GDDP) dataset, or NEX-GDDP-CMIP6, was created to assist the science community in conducting studies of climate change impacts at local to regional scales and to enhance public understanding of possible future climate patterns at the spatial scale of individual towns, cities, and watersheds. The archive contains downscaled historical (1950 - 2015) and future (2015 - 2100) projections of [climate variables](https://www.nature.com/articles/s41597-022-01393-4/tables/2) such as humidity, precipitation, and near-surface air temperature, based on output from [Phase 6 of the Climate Model Intercomparison Project (CMIP6)](https://www.wcrp-climate.org/wgcm-cmip/cmip-video). The downscaled products are provided at 0.25 degree horizontal resolution. The data are also available for four different future climate scenarios modeled as part of CMIP6. These scenarios take into account future radiative forcing levels (from low to high) as well as “Shared Socioeconomic Pathways” (SSPs) which are a collection of narratives that describe potential paths society will take in order to combat climate change. The SSPs range from a highly sustainable approach (SSP1) to a narrative where society continues to rely heavily on fossil fuel resources (SSP5). The four resulting combined scenarios are SSP126, SSP245, SSP370 and SSP585. Learn more about the scenarios here: [https://www.dkrz.de/en/communication/climate-simulations/cmip6-en/the-ssp-scenarios](https://www.dkrz.de/en/communication/climate-simulations/cmip6-en/the-ssp-scenarios)

This dataset provides the number of days per year from 2015 - 2100 that the maximum temperature is projected to exceed a threshold of 90 degrees fahrenheit (°F) and 110°F. 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)). This type of maximum temperature threshold index serves as an essential metric for assessing and understanding the patterns and extremes in temperature regimes, and is a valuable tool for climate scientists, researchers, and policymakers. Each threshold holds distinct climatological significance. Lower thresholds, such as 90°F, are often associated with typical warm conditions, while higher thresholds, like 110°F, indicate extreme heat events. Monitoring these thresholds 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.
## Data Summary
* **Temporal Extent:** 2015 - 2100
* **Temporal Resolution:** Annual
* **Spatial Extent:** Global
* **Spatial Resolution:** 0.25 degrees x 0.25 degrees
* **Data Units:** Days (Days per year above 90°F or 110°F)
* **Data Type:** Research

## Data Summary
* **Temporal Extent:** 2015 - 2100
* **Temporal Resolution:** Annual
* **Spatial Extent:** Global
* **Spatial Resolution:** 0.25 degrees x 0.25 degrees
* **Data Units:** Days (Days per year above 90°F or 110°F)
* **Data Type:** Research

</Prose>
This dataset provides the number of days per year from 2015 - 2100 that the maximum temperature is projected to exceed a threshold of 90 degrees fahrenheit (°F) and 110°F. 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)). This type of maximum temperature threshold index serves as an essential metric for assessing and understanding the patterns and extremes in temperature regimes, and is a valuable tool for climate scientists, researchers, and policymakers. Each threshold holds distinct climatological significance. Lower thresholds, such as 90°F, are often associated with typical warm conditions, while higher thresholds, like 110°F, indicate extreme heat events. Monitoring these thresholds 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.
</Prose>
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<Prose>
## Source Data Access
The Projected Annual Days Above 90°F and 110°F threshold index were created using the following dataset as an input:

NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) [https://doi.org/10.7917/OFSG3345](https://doi.org/10.7917/OFSG3345)

## Acknowledgment
This climate index, Days per Year Projected to Exceed 90°F and 110°F, was calculated using the NEX-GDDP-CMIP6 downscaled climate projections by the NASA Earth eXchange (NEX) at NASA Ames Research Center. NEX-GDDP-CMIP6 was created by NEX and is distributed by the NASA Center for Climate Simulation.
<Prose>
## Source Data Access
The Projected Annual Days Above 90°F and 110°F threshold index were created using the following dataset as an input:

## Dataset Preparation & Disclaimer
This dataset was derived using the Daily Maximum Near-Surface Temperature data variable (tasmax) from the NEX-GDDP-CMIP6 ACCESS-CM2 model as an input. From this input, the number of days per year that the Daily Maximum Near-Surface Temperature exceeded each threshold were calculated. Only the ACCESS-CM2 model from CMIP6 was used in deriving this product. A full list of CMIP6 models available for the NEX-GDDP-CMIP6 product can be [found here](https://www.nature.com/articles/s41597-022-01393-4/tables/3). Learn more about the ACCESS-CM2 model here: [https://research.csiro.au/access/about](https://research.csiro.au/access/about/).
NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) [https://doi.org/10.7917/OFSG3345](https://doi.org/10.7917/OFSG3345)

## Acknowledgment
This climate index, Days per Year Projected to Exceed 90°F and 110°F, was calculated using the NEX-GDDP-CMIP6 downscaled climate projections by the NASA Earth eXchange (NEX) at NASA Ames Research Center. NEX-GDDP-CMIP6 was created by NEX and is distributed by the NASA Center for Climate Simulation.

The downscaled product (NEX-GDDP-CMIP6) used as an input to this dataset were produced using a daily variant of the monthly bias Bias-Correction Spatial Disaggregation (BCSD) method and are at 0.25 degree horizontal resolution. The demand for downscaling of Global Climate Model (GCM) outputs arises since most GCMs are run using relatively coarse resolution grids (e.g., a few degrees), which limit their ability to capture the spatial details in climate patterns that are often required or desired in regional or local analyses. Even the most advanced GCMs may produce projections that are globally accurate but locally biased in their statistical characteristics (i.e., mean, variance, etc.) when compared with observations. The BCSD approach used in generating the input downscaled dataset inherently assumes that the relative spatial patterns observed from 1960 through 2014 will remain constant under future climate change. Other than the higher spatial resolution and bias correction, the input dataset does not add information beyond what is contained in the original CMIP6 scenarios, and preserves the frequency of periods of anomalously high and low values (i.e., extreme events) within each individual scenario. Due to the lack of validation of the GMFD over oceans, GDDP values over smaller island areas might not be realistic.
## Dataset Preparation & Disclaimer
This dataset was derived using the Daily Maximum Near-Surface Temperature data variable (tasmax) from the NEX-GDDP-CMIP6 ACCESS-CM2 model as an input. From this input, the number of days per year that the Daily Maximum Near-Surface Temperature exceeded each threshold were calculated. Only the ACCESS-CM2 model from CMIP6 was used in deriving this product. A full list of CMIP6 models available for the NEX-GDDP-CMIP6 product can be [found here](https://www.nature.com/articles/s41597-022-01393-4/tables/3). Learn more about the ACCESS-CM2 model here: [https://research.csiro.au/access/about](https://research.csiro.au/access/about/).

Learn more about CMIP6 at the following publication:
Thrasher, B., Wang, W., Michaelis, A. et al. NASA Global Daily Downscaled Projections, CMIP6. Sci Data 9, 262 (2022). [https://doi.org/10.1038/s41597-022-01393-4](https://doi.org/10.1038/s41597-022-01393-4)
The downscaled product (NEX-GDDP-CMIP6) used as an input to this dataset were produced using a daily variant of the monthly bias Bias-Correction Spatial Disaggregation (BCSD) method and are at 0.25 degree horizontal resolution. The demand for downscaling of Global Climate Model (GCM) outputs arises since most GCMs are run using relatively coarse resolution grids (e.g., a few degrees), which limit their ability to capture the spatial details in climate patterns that are often required or desired in regional or local analyses. Even the most advanced GCMs may produce projections that are globally accurate but locally biased in their statistical characteristics (i.e., mean, variance, etc.) when compared with observations. The BCSD approach used in generating the input downscaled dataset inherently assumes that the relative spatial patterns observed from 1960 through 2014 will remain constant under future climate change. Other than the higher spatial resolution and bias correction, the input dataset does not add information beyond what is contained in the original CMIP6 scenarios, and preserves the frequency of periods of anomalously high and low values (i.e., extreme events) within each individual scenario. Due to the lack of validation of the GMFD over oceans, GDDP values over smaller island areas might not be realistic.

Learn more about CMIP6 at the following publication:
Thrasher, B., Wang, W., Michaelis, A. et al. NASA Global Daily Downscaled Projections, CMIP6. Sci Data 9, 262 (2022). [https://doi.org/10.1038/s41597-022-01393-4](https://doi.org/10.1038/s41597-022-01393-4)

All data displayed in Earth.gov has been transformed from the original format (NetCDF) into Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) and quality checked to ensure the data transformation has been performed correctly.
All data displayed in Earth.gov has been transformed from the original format (NetCDF) into Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)) and quality checked to ensure the data transformation has been performed correctly.

This dataset is intended for use in scientific research only, and use of this dataset for other purposes, such as commercial applications, and engineering or design studies is not recommended without consultation with a qualified expert.
</Prose>
This dataset is intended for use in scientific research only, and use of this dataset for other purposes, such as commercial applications, and engineering or design studies is not recommended without consultation with a qualified expert.
</Prose>
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