ለውጦች

              
    

          
          
        
        

            
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  "author": "Dr. Geeta Persad, Dr. Ifeanyichukwu Nduka",
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  "author": "Dr. Geeta Persad, Dr. Ifeanyichukwu Nduka",
            
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  "author_email": "geeta.persad@jsg.utexas.edu, 
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  "author_email": "geeta.persad@jsg.utexas.edu, 
            
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icnduka@jsg.utexas.edu",
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icnduka@jsg.utexas.edu",
            
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  "creator_user_id": "1ff32a65-f81d-475a-a8d3-9ddb81ec4550",
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  "groups": [],
            
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  "license_id": "notspecified",
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  "license_id": "notspecified",
            
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  "license_title": "License not specified",
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  "license_title": "License not specified",
            
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  "maintainer": "Dr. Ifeanyichukwu Nduka, Cameron Cummins",
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  "maintainer": "Dr. Ifeanyichukwu Nduka, Cameron Cummins",
            
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  "maintainer_email": "icnduka@jsg.utexas.edu, 
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  "maintainer_email": "icnduka@jsg.utexas.edu, 
            
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cameron.cummins@utexas.edu",
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cameron.cummins@utexas.edu",
            
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  "metadata_created": "2025-09-24T21:32:41.087476",
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  "metadata_created": "2025-09-24T21:32:41.087476",
            
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  "metadata_modified": "2025-10-08T16:25:16.732048",
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  "metadata_modified": "2025-10-08T16:25:25.392431",
            
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  "name": "setx_climate_data",
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  "name": "setx_climate_data",
            
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  "notes": "For the SETx-UIFL, the daily NASA Earth Exchange Global 
17
  "notes": "For the SETx-UIFL, the daily NASA Earth Exchange Global 
            
18
Daily Downscaled Projections (NEX-GDDP-CMIP6) dataset climate 
18
Daily Downscaled Projections (NEX-GDDP-CMIP6) dataset climate 
            
19
projections were downscaled from ~27km to 1km. The SETx dataset 
19
projections were downscaled from ~27km to 1km. The SETx dataset 
            
20
provides very high-resolution climate data for the historical 
20
provides very high-resolution climate data for the historical 
            
21
(1950-2014) and future scenarios derived from CMIP6 global models 
21
(1950-2014) and future scenarios derived from CMIP6 global models 
            
22
under the four Tier 1 Shared Socioeconomic Pathways (SSPs 1.26, 2.45, 
22
under the four Tier 1 Shared Socioeconomic Pathways (SSPs 1.26, 2.45, 
            
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3.70 & 5.85), developed for the IPCC Sixth Assessment Report.\r\n\r\nA 
23
3.70 & 5.85), developed for the IPCC Sixth Assessment Report.\r\n\r\nA 
            
24
subset of ten NEX-GDDP-CMIP6 models was selected for SETx-UIFL to 
24
subset of ten NEX-GDDP-CMIP6 models was selected for SETx-UIFL to 
            
25
provide robust daily historical and future climate conditions in 
25
provide robust daily historical and future climate conditions in 
            
26
Southeast Texas. These models were chosen to represent a balance of 
26
Southeast Texas. These models were chosen to represent a balance of 
            
27
model families, climate sensitivities, and availability across 
27
model families, climate sensitivities, and availability across 
            
28
scenarios, ensuring a diverse and reliable ensemble for regional 
28
scenarios, ensuring a diverse and reliable ensemble for regional 
            
29
analysis. The selected models are:\r\n\r\n - BCC-CSM2-MR\r\n - 
29
analysis. The selected models are:\r\n\r\n - BCC-CSM2-MR\r\n - 
            
30
CESM2\r\n - CMCC-ESM2\r\n - CNRM-ESM2-1\r\n - EC-Earth3\r\n - 
30
CESM2\r\n - CMCC-ESM2\r\n - CNRM-ESM2-1\r\n - EC-Earth3\r\n - 
            
31
FGOALS-g3\r\n - GFDL-CM4\r\n - MPI-ESM1-2-HR\r\n - MRI-ESM2-0\r\n - 
31
FGOALS-g3\r\n - GFDL-CM4\r\n - MPI-ESM1-2-HR\r\n - MRI-ESM2-0\r\n - 
            
32
NorESM2-MM\r\n\r\nThe following daily variables were downscaled for 
32
NorESM2-MM\r\n\r\nThe following daily variables were downscaled for 
            
33
SETx-UIFL:\r\n\r\n - `tasmax` \u2013 Near-surface maximum air 
33
SETx-UIFL:\r\n\r\n - `tasmax` \u2013 Near-surface maximum air 
            
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temperature\r\n - `tasmin` \u2013 Near-surface minimum air 
34
temperature\r\n - `tasmin` \u2013 Near-surface minimum air 
            
35
temperature\r\n - `tas` \u2013 Near-surface mean air temperature\r\n - 
35
temperature\r\n - `tas` \u2013 Near-surface mean air temperature\r\n - 
            
36
`pr` \u2013 Daily precipitation total\r\n - `hurs` \u2013 Near-surface 
36
`pr` \u2013 Daily precipitation total\r\n - `hurs` \u2013 Near-surface 
            
37
relative humidity\r\n - `huss` \u2013 Near-surface specific 
37
relative humidity\r\n - `huss` \u2013 Near-surface specific 
            
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humidity\r\n - `rsds` \u2013 Surface downwelling shortwave 
38
humidity\r\n - `rsds` \u2013 Surface downwelling shortwave 
            
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radiation\r\n - `rlds` \u2013 Surface downwelling longwave 
39
radiation\r\n - `rlds` \u2013 Surface downwelling longwave 
            
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radiation\r\n - `sfcWind` \u2013 Near-surface wind speed\r\n\r\nThese 
40
radiation\r\n - `sfcWind` \u2013 Near-surface wind speed\r\n\r\nThese 
            
41
downscaled data support regional impact analysis and can also be 
41
downscaled data support regional impact analysis and can also be 
            
42
applied in other scientific studies requiring localized climate 
42
applied in other scientific studies requiring localized climate 
            
43
projections. The original dataset is publicly available at: 
43
projections. The original dataset is publicly available at: 
            
44
https://doi.org/10.7917/OFSG3345](https://doi.org/10.7917/OFSG3345).",
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https://doi.org/10.7917/OFSG3345](https://doi.org/10.7917/OFSG3345).",
            
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    "approval_status": "approved",
            
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    "created": "2024-12-13T20:42:01.291625",
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    "created": "2024-12-13T20:42:01.291625",
            
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    "description": "Southeast Texas Urban Integrated Field Lab 
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    "description": "Southeast Texas Urban Integrated Field Lab 
            
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(SETx-UIFL) is a DOE-funded Urban Integrated Field Laboratory studying 
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(SETx-UIFL) is a DOE-funded Urban Integrated Field Laboratory studying 
            
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the Beaumont-Port Arthur area. The project focuses on Gulf Coast 
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the Beaumont-Port Arthur area. The project focuses on Gulf Coast 
            
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communities with industrial facilities and population change 
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communities with industrial facilities and population change 
            
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challenges.",
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