Changes
On May 11, 2023 at 5:18:08 PM UTC, patdavid:
-
Updated description of Downscaled and bias corrected dataset for multiple GCMs and variables from
### Abstract Understanding the impact of climate variability and change is of great importance for developing adaptation and mitigation strategies. Coarse resolution data sets such as simulations of general circulation models (GCMs) are important for reconstructing historical climate and predicting the future. However, scale discrepancy and biases limit the coarse resolution data sets from being directly used for impact assessments and decision making. One solution for bridging this gap is to downscale and bias correct coarse resolution data to the local scale. ### Purpose We bias corrected and downscaled 9 climate variables for 5 popular GCMs from the latest CMIP6 with a widly used method, namely quantile delta mapping (QDM). The dataset has spatial resolution of 0.25 degree and daily temporal scale. For each GCM, two emission levels are included(ssp126 as low emission level and ssp585 as high emission level). The names of the 5 GCMs are EC-Earth3, MPI-ESM1-2-HR, MRI-ESM2-0, IPSL-CM6A-LR,and GFDL-ESM4. The 9 variables include daily total precipitation (pr), daily maximum near-surface air temperature(tasmax), daily minimum near-surface air temperature (tasmin),eastward near-surface wind (uas),northward near-surface wind (vas),near-surface relative humidity (hurs), surface downwelling shortwave radiation (rsds), surface downwelling longwave radiation (rlds) and sea level pressure (psl). The dataset will be used as forcings for the watershed modeling and physical/biogeochemical modeling around the bay area to explore adaptation and mitigation strategies. **DOI: [10.57778/wqdc-q670](https://doi.org/10.57778/wqdc-q670)** ### Suggested Citation ### Related Publication Citation
to### Abstract Understanding the impact of climate variability and change is of great importance for developing adaptation and mitigation strategies. Coarse resolution data sets such as simulations of general circulation models (GCMs) are important for reconstructing historical climate and predicting the future. However, scale discrepancy and biases limit the coarse resolution data sets from being directly used for impact assessments and decision making. One solution for bridging this gap is to downscale and bias correct coarse resolution data to the local scale. ### Purpose We bias corrected and downscaled 9 climate variables for 5 popular GCMs from the latest CMIP6 with a widly used method, namely quantile delta mapping (QDM). The dataset has spatial resolution of 0.25 degree and daily temporal scale. For each GCM, two emission levels are included(ssp126 as low emission level and ssp585 as high emission level). The names of the 5 GCMs are EC-Earth3, MPI-ESM1-2-HR, MRI-ESM2-0, IPSL-CM6A-LR,and GFDL-ESM4. The 9 variables include daily total precipitation (pr), daily maximum near-surface air temperature(tasmax), daily minimum near-surface air temperature (tasmin),eastward near-surface wind (uas),northward near-surface wind (vas),near-surface relative humidity (hurs), surface downwelling shortwave radiation (rsds), surface downwelling longwave radiation (rlds) and sea level pressure (psl). The dataset will be used as forcings for the watershed modeling and physical/biogeochemical modeling around the bay area to explore adaptation and mitigation strategies. **DOI: [10.57778/wqdc-q670](https://doi.org/10.57778/wqdc-q670)** ### Suggested Citation Wang, F., & Tian, D. (2023). Downscaled and bias corrected dataset for multiple GCMs and variables (Version 1.0) [Data set]. Dauphin Island Sea Lab. https://doi.org/10.57778/WQDC-Q670 ### Related Publication Citation
f | 1 | { | f | 1 | { |
2 | "author": "Fang Wang", | 2 | "author": "Fang Wang", | ||
3 | "author_email": "fzw0024@auburn.edu", | 3 | "author_email": "fzw0024@auburn.edu", | ||
4 | "creator_user_id": "383a0dce-09ad-42af-8eb5-02327d57d2a3", | 4 | "creator_user_id": "383a0dce-09ad-42af-8eb5-02327d57d2a3", | ||
5 | "extras": [ | 5 | "extras": [ | ||
6 | { | 6 | { | ||
7 | "key": "ISO.author.1", | 7 | "key": "ISO.author.1", | ||
8 | "value": "Di Tian <tiandi@auburn.edu>" | 8 | "value": "Di Tian <tiandi@auburn.edu>" | ||
9 | }, | 9 | }, | ||
10 | { | 10 | { | ||
11 | "key": "spatial", | 11 | "key": "spatial", | ||
12 | "value": "{\"type\": \"Polygon\", | 12 | "value": "{\"type\": \"Polygon\", | ||
13 | ":[[[-94.5,26],[-94.5,35.25],[-84.25,35.25],[-84.25,26],[-94.5,26]]]}" | 13 | ":[[[-94.5,26],[-94.5,35.25],[-84.25,35.25],[-84.25,26],[-94.5,26]]]}" | ||
14 | } | 14 | } | ||
15 | ], | 15 | ], | ||
16 | "groups": [], | 16 | "groups": [], | ||
17 | "id": "4070e122-eda3-4dfd-968c-72fa6046e7a8", | 17 | "id": "4070e122-eda3-4dfd-968c-72fa6046e7a8", | ||
18 | "isopen": true, | 18 | "isopen": true, | ||
19 | "license_id": "other-open", | 19 | "license_id": "other-open", | ||
20 | "license_title": "Other (Open)", | 20 | "license_title": "Other (Open)", | ||
21 | "maintainer": "data@disl.edu", | 21 | "maintainer": "data@disl.edu", | ||
22 | "maintainer_email": "data@disl.edu", | 22 | "maintainer_email": "data@disl.edu", | ||
23 | "metadata_created": "2023-05-10T19:59:57.832797", | 23 | "metadata_created": "2023-05-10T19:59:57.832797", | ||
n | 24 | "metadata_modified": "2023-05-11T17:15:24.500851", | n | 24 | "metadata_modified": "2023-05-11T17:18:08.111141", |
25 | "name": | 25 | "name": | ||
26 | ownscaled-and-bias-corrected-dataset-for-multiple-gcms-and-variables", | 26 | ownscaled-and-bias-corrected-dataset-for-multiple-gcms-and-variables", | ||
27 | "notes": "### Abstract\r\nUnderstanding the impact of climate | 27 | "notes": "### Abstract\r\nUnderstanding the impact of climate | ||
28 | variability and change is of great importance for developing | 28 | variability and change is of great importance for developing | ||
29 | adaptation \r\nand mitigation strategies. Coarse resolution data sets | 29 | adaptation \r\nand mitigation strategies. Coarse resolution data sets | ||
30 | such as simulations of general circulation models (GCMs) \r\nare | 30 | such as simulations of general circulation models (GCMs) \r\nare | ||
31 | important for reconstructing historical climate and predicting the | 31 | important for reconstructing historical climate and predicting the | ||
32 | future. However, scale discrepancy and \r\nbiases limit the coarse | 32 | future. However, scale discrepancy and \r\nbiases limit the coarse | ||
33 | resolution data sets from being directly used for impact assessments | 33 | resolution data sets from being directly used for impact assessments | ||
34 | and decision making. \r\nOne solution for bridging this gap is to | 34 | and decision making. \r\nOne solution for bridging this gap is to | ||
35 | downscale and bias correct coarse resolution data to the local | 35 | downscale and bias correct coarse resolution data to the local | ||
36 | scale.\r\n\r\n### Purpose\r\nWe bias corrected and downscaled 9 | 36 | scale.\r\n\r\n### Purpose\r\nWe bias corrected and downscaled 9 | ||
37 | climate variables for 5 popular GCMs from the latest CMIP6 \r\nwith a | 37 | climate variables for 5 popular GCMs from the latest CMIP6 \r\nwith a | ||
38 | widly used method, namely quantile delta mapping (QDM). \r\nThe | 38 | widly used method, namely quantile delta mapping (QDM). \r\nThe | ||
39 | dataset has spatial resolution of 0.25 degree and daily temporal | 39 | dataset has spatial resolution of 0.25 degree and daily temporal | ||
40 | scale. For each GCM, \r\ntwo emission levels are included(ssp126 as | 40 | scale. For each GCM, \r\ntwo emission levels are included(ssp126 as | ||
41 | low emission level and ssp585 as high emission level). \r\nThe names | 41 | low emission level and ssp585 as high emission level). \r\nThe names | ||
42 | of the 5 GCMs are EC-Earth3, MPI-ESM1-2-HR, MRI-ESM2-0, | 42 | of the 5 GCMs are EC-Earth3, MPI-ESM1-2-HR, MRI-ESM2-0, | ||
43 | IPSL-CM6A-LR,and GFDL-ESM4. \r\nThe 9 variables include daily total | 43 | IPSL-CM6A-LR,and GFDL-ESM4. \r\nThe 9 variables include daily total | ||
44 | precipitation (pr), daily maximum near-surface air | 44 | precipitation (pr), daily maximum near-surface air | ||
45 | temperature(tasmax), \r\ndaily minimum near-surface air temperature | 45 | temperature(tasmax), \r\ndaily minimum near-surface air temperature | ||
46 | (tasmin),eastward near-surface wind (uas),northward \r\nnear-surface | 46 | (tasmin),eastward near-surface wind (uas),northward \r\nnear-surface | ||
47 | wind (vas),near-surface relative humidity (hurs), surface downwelling | 47 | wind (vas),near-surface relative humidity (hurs), surface downwelling | ||
48 | shortwave radiation (rsds), \r\nsurface downwelling longwave radiation | 48 | shortwave radiation (rsds), \r\nsurface downwelling longwave radiation | ||
49 | (rlds) and sea level pressure (psl). The dataset will be used as | 49 | (rlds) and sea level pressure (psl). The dataset will be used as | ||
50 | forcings \r\nfor the watershed modeling and physical/biogeochemical | 50 | forcings \r\nfor the watershed modeling and physical/biogeochemical | ||
51 | modeling around the bay area to explore adaptation and \r\nmitigation | 51 | modeling around the bay area to explore adaptation and \r\nmitigation | ||
52 | strategies.\r\n\r\n**DOI: | 52 | strategies.\r\n\r\n**DOI: | ||
53 | [10.57778/wqdc-q670](https://doi.org/10.57778/wqdc-q670)**\r\n\r\n### | 53 | [10.57778/wqdc-q670](https://doi.org/10.57778/wqdc-q670)**\r\n\r\n### | ||
t | 54 | Suggested Citation\r\n\r\n### Related Publication Citation", | t | 54 | Suggested Citation\r\nWang, F., & Tian, D. (2023). Downscaled and bias |
55 | corrected dataset for multiple GCMs and variables (Version 1.0) [Data | ||||
56 | set]. Dauphin Island Sea Lab. | ||||
57 | https://doi.org/10.57778/WQDC-Q670\r\n\r\n### Related Publication | ||||
58 | Citation", | ||||
55 | "num_resources": 5, | 59 | "num_resources": 5, | ||
56 | "num_tags": 9, | 60 | "num_tags": 9, | ||
57 | "organization": { | 61 | "organization": { | ||
58 | "approval_status": "approved", | 62 | "approval_status": "approved", | ||
59 | "created": "2022-07-22T03:25:13.329710", | 63 | "created": "2022-07-22T03:25:13.329710", | ||
60 | "description": "The Dauphin Island Sea Lab's (DISL) mission is to | 64 | "description": "The Dauphin Island Sea Lab's (DISL) mission is to | ||
61 | become a center for transformative U.S. oceanic and coastal research | 65 | become a center for transformative U.S. oceanic and coastal research | ||
62 | and education.. Founded in 1971 by the State of Alabama Legislature to | 66 | and education.. Founded in 1971 by the State of Alabama Legislature to | ||
63 | maximize the marine sciences capabilities of several Alabama | 67 | maximize the marine sciences capabilities of several Alabama | ||
64 | institutions and minimize duplication. \r\n\r\nLocated on the eastern | 68 | institutions and minimize duplication. \r\n\r\nLocated on the eastern | ||
65 | tip of Dauphin Island, a barrier island in the northern Gulf of | 69 | tip of Dauphin Island, a barrier island in the northern Gulf of | ||
66 | Mexico, DISL is surrounded by Mobile Bay, the Mississippi Sound, and | 70 | Mexico, DISL is surrounded by Mobile Bay, the Mississippi Sound, and | ||
67 | the waters of the Gulf, making it a perfect location to conduct a wide | 71 | the waters of the Gulf, making it a perfect location to conduct a wide | ||
68 | range of marine science activity. \r\n\r\n[The University Programs | 72 | range of marine science activity. \r\n\r\n[The University Programs | ||
69 | (UP)](https://www.disl.edu/univ-prog/) serves the students of the | 73 | (UP)](https://www.disl.edu/univ-prog/) serves the students of the | ||
70 | Marine Environmental Sciences Consortium\u2019s (MESC) 22 public and | 74 | Marine Environmental Sciences Consortium\u2019s (MESC) 22 public and | ||
71 | private four-year colleges and universities through graduate and | 75 | private four-year colleges and universities through graduate and | ||
72 | undergraduate programs. Throughout the year, graduate students conduct | 76 | undergraduate programs. Throughout the year, graduate students conduct | ||
73 | research, and attend classes while completing their degree under the | 77 | research, and attend classes while completing their degree under the | ||
74 | mentorship of faculty and staff at the Dauphin Island Sea Lab. | 78 | mentorship of faculty and staff at the Dauphin Island Sea Lab. | ||
75 | \r\n\r\n[The Discovery Hall Programs (DHP)](https://www.disl.edu/dhp/) | 79 | \r\n\r\n[The Discovery Hall Programs (DHP)](https://www.disl.edu/dhp/) | ||
76 | oversees educational programs for K-12 field programs, | 80 | oversees educational programs for K-12 field programs, | ||
77 | teacher-training, and community outreach opportunities. \r\n[The | 81 | teacher-training, and community outreach opportunities. \r\n[The | ||
78 | Estuarium](https://www.disl.edu/aquarium/), our public aquarium | 82 | Estuarium](https://www.disl.edu/aquarium/), our public aquarium | ||
79 | located on the Dauphin Island Sea Lab campus, is a part of DHP's | 83 | located on the Dauphin Island Sea Lab campus, is a part of DHP's | ||
80 | educational outreach mission. The Estuarium focuses solely on the | 84 | educational outreach mission. The Estuarium focuses solely on the | ||
81 | Mobile-Tensaw Estuary System. The BayMobile allows DHP educators to | 85 | Mobile-Tensaw Estuary System. The BayMobile allows DHP educators to | ||
82 | bring marine science to students across Alabama in the classroom and | 86 | bring marine science to students across Alabama in the classroom and | ||
83 | at community events. \r\n\r\nResearch programs at the Dauphin Island | 87 | at community events. \r\n\r\nResearch programs at the Dauphin Island | ||
84 | Sea Lab range from biogeochemistry and oceanography to ecosystem | 88 | Sea Lab range from biogeochemistry and oceanography to ecosystem | ||
85 | ecology. While much of our research focuses on the near-shore and | 89 | ecology. While much of our research focuses on the near-shore and | ||
86 | estuarine processes of the northern Gulf of Mexico, field sites of our | 90 | estuarine processes of the northern Gulf of Mexico, field sites of our | ||
87 | internationally-renowned faculty also include the Arctic, Mexico, | 91 | internationally-renowned faculty also include the Arctic, Mexico, | ||
88 | Australia, and other countries.\r\n\r\nThe Dauphin Island Sea Lab also | 92 | Australia, and other countries.\r\n\r\nThe Dauphin Island Sea Lab also | ||
89 | offers state and local government, industry, and agency | 93 | offers state and local government, industry, and agency | ||
90 | decision-makers a range of coastal zone management services, including | 94 | decision-makers a range of coastal zone management services, including | ||
91 | access to the nationally acclaimed data management center. Armed with | 95 | access to the nationally acclaimed data management center. Armed with | ||
92 | data through the DISL data management center, entities can make | 96 | data through the DISL data management center, entities can make | ||
93 | well-informed decisions and sound policies while considering | 97 | well-informed decisions and sound policies while considering | ||
94 | environmental impact. Another key contributor to successful coastal | 98 | environmental impact. Another key contributor to successful coastal | ||
95 | zone management is the Mobile Bay National Estuary Program, which | 99 | zone management is the Mobile Bay National Estuary Program, which | ||
96 | falls within the services of DISL.\r\n\r\n", | 100 | falls within the services of DISL.\r\n\r\n", | ||
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102 | "state": "active", | 106 | "state": "active", | ||
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116 | "datastore_contains_all_records_of_source_file": false, | 120 | "datastore_contains_all_records_of_source_file": false, | ||
117 | "description": "All the original GCM data without BC and | 121 | "description": "All the original GCM data without BC and | ||
118 | downscaling\r\n\r\n - CMIP6_GCMs/MPI-ESM1-2-HR # | 122 | downscaling\r\n\r\n - CMIP6_GCMs/MPI-ESM1-2-HR # | ||
119 | GCM MPI-ESM1-2-HR \r\n - CMIP6_GCMs/MPI-ESM1-2-HR/ssp126 # | 123 | GCM MPI-ESM1-2-HR \r\n - CMIP6_GCMs/MPI-ESM1-2-HR/ssp126 # | ||
120 | GCM MPI-ESM1-2-HR for the low emssion level ssp126(2015 to 2100)\r\n - | 124 | GCM MPI-ESM1-2-HR for the low emssion level ssp126(2015 to 2100)\r\n - | ||
121 | CMIP6_GCMs/MPI-ESM1-2-HR/ssp585 # GCM MPI-ESM1-2-HR for the | 125 | CMIP6_GCMs/MPI-ESM1-2-HR/ssp585 # GCM MPI-ESM1-2-HR for the | ||
122 | high emssion level ssp585(2015 to 2100)\r\n - | 126 | high emssion level ssp585(2015 to 2100)\r\n - | ||
123 | CMIP6_GCMs/MPI-ESM1-2-HR/historical # GCM MPI-ESM1-2-HR in the | 127 | CMIP6_GCMs/MPI-ESM1-2-HR/historical # GCM MPI-ESM1-2-HR in the | ||
124 | historical period (1979 to 2014)\r\n - CMIP6_GCMs/EC-Earth3 | 128 | historical period (1979 to 2014)\r\n - CMIP6_GCMs/EC-Earth3 | ||
125 | # GCM EC-Earth3 \r\n - CMIP6_GCMs/EC-Earth3/ssp126 # GCM | 129 | # GCM EC-Earth3 \r\n - CMIP6_GCMs/EC-Earth3/ssp126 # GCM | ||
126 | EC-Earth3 for the low emssion level ssp126(2015 to 2100)\r\n - | 130 | EC-Earth3 for the low emssion level ssp126(2015 to 2100)\r\n - | ||
127 | CMIP6_GCMs/EC-Earth3/ssp585 # GCM EC-Earth3 for the high | 131 | CMIP6_GCMs/EC-Earth3/ssp585 # GCM EC-Earth3 for the high | ||
128 | emssion level ssp585(2015 to 2100)\r\n - | 132 | emssion level ssp585(2015 to 2100)\r\n - | ||
129 | CMIP6_GCMs/EC-Earth3/historical # GCM EC-Earth3 in the | 133 | CMIP6_GCMs/EC-Earth3/historical # GCM EC-Earth3 in the | ||
130 | historical period (1979 to 2014)\r\n - CMIP6_GCMs/MRI-ESM2-0 | 134 | historical period (1979 to 2014)\r\n - CMIP6_GCMs/MRI-ESM2-0 | ||
131 | # GCM MRI-ESM2-0\r\n - CMIP6_GCMs/MRI-ESM2-0/ssp126 # GCM | 135 | # GCM MRI-ESM2-0\r\n - CMIP6_GCMs/MRI-ESM2-0/ssp126 # GCM | ||
132 | MRI-ESM2-0 for the low emssion level ssp126(2015 to 2100)\r\n - | 136 | MRI-ESM2-0 for the low emssion level ssp126(2015 to 2100)\r\n - | ||
133 | CMIP6_GCMs/MRI-ESM2-0/ssp585 # GCM MRI-ESM2-0 for the | 137 | CMIP6_GCMs/MRI-ESM2-0/ssp585 # GCM MRI-ESM2-0 for the | ||
134 | high emssion level ssp585(2015 to 2100)\r\n - | 138 | high emssion level ssp585(2015 to 2100)\r\n - | ||
135 | CMIP6_GCMs/MRI-ESM2-0/historical # GCM MRI-ESM2-0 in the | 139 | CMIP6_GCMs/MRI-ESM2-0/historical # GCM MRI-ESM2-0 in the | ||
136 | historical period (1979 to 2014)\r\n - CMIP6_GCMs/IPSL-CM6A-LR | 140 | historical period (1979 to 2014)\r\n - CMIP6_GCMs/IPSL-CM6A-LR | ||
137 | # GCM IPSL-CM6A-LR \r\n - | 141 | # GCM IPSL-CM6A-LR \r\n - | ||
138 | CMIP6_GCMs/IPSL-CM6A-LR/ssp126 # GCM IPSL-CM6A-LR for the | 142 | CMIP6_GCMs/IPSL-CM6A-LR/ssp126 # GCM IPSL-CM6A-LR for the | ||
139 | low emssion level ssp126(2015 to 2100)\r\n - | 143 | low emssion level ssp126(2015 to 2100)\r\n - | ||
140 | CMIP6_GCMs/IPSL-CM6A-LR/ssp585 # GCM IPSL-CM6A-LR for the | 144 | CMIP6_GCMs/IPSL-CM6A-LR/ssp585 # GCM IPSL-CM6A-LR for the | ||
141 | high emssion level ssp585(2015 to 2100)\r\n - | 145 | high emssion level ssp585(2015 to 2100)\r\n - | ||
142 | CMIP6_GCMs/IPSL-CM6A-LR/historical # GCM IPSL-CM6A-LR in the | 146 | CMIP6_GCMs/IPSL-CM6A-LR/historical # GCM IPSL-CM6A-LR in the | ||
143 | historical period (1979 to 2014)\r\n - CMIP6_GCMs/GFDL-ESM4 | 147 | historical period (1979 to 2014)\r\n - CMIP6_GCMs/GFDL-ESM4 | ||
144 | # GCM GFDL-ESM4 \r\n - CMIP6_GCMs/GFDL-ESM4/ssp126 | 148 | # GCM GFDL-ESM4 \r\n - CMIP6_GCMs/GFDL-ESM4/ssp126 | ||
145 | # GCM GFDL-ESM4 for the low emssion level ssp126(2015 to 2100) | 149 | # GCM GFDL-ESM4 for the low emssion level ssp126(2015 to 2100) | ||
146 | \r\n - CMIP6_GCMs/GFDL-ESM4/ssp585 # GCM GFDL-ESM4 for | 150 | \r\n - CMIP6_GCMs/GFDL-ESM4/ssp585 # GCM GFDL-ESM4 for | ||
147 | the high emssion level ssp126(2015 to 2100)\r\n - | 151 | the high emssion level ssp126(2015 to 2100)\r\n - | ||
148 | CMIP6_GCMs/GFDL-ESM4/historical # GCM GFDL-ESM4 in the | 152 | CMIP6_GCMs/GFDL-ESM4/historical # GCM GFDL-ESM4 in the | ||
149 | historical period (1979 to 2014)\r\n", | 153 | historical period (1979 to 2014)\r\n", | ||
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188 | ted-dataset-for-multiple-gcms-and-variables/ERA5-single-daily.tar.gz", | 192 | ted-dataset-for-multiple-gcms-and-variables/ERA5-single-daily.tar.gz", | ||
189 | "url_type": null | 193 | "url_type": null | ||
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191 | { | 195 | { | ||
192 | "cache_last_updated": null, | 196 | "cache_last_updated": null, | ||
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196 | "datastore_contains_all_records_of_source_file": false, | 200 | "datastore_contains_all_records_of_source_file": false, | ||
197 | "description": " - ERA5-single-hourly # Hourly ERA5 data | 201 | "description": " - ERA5-single-hourly # Hourly ERA5 data | ||
198 | directly downloaded from ECMWF website\r\n - ERA5-single-hourly/hurs # | 202 | directly downloaded from ECMWF website\r\n - ERA5-single-hourly/hurs # | ||
199 | Hourly ERA5 data for near-surface relative humidity (hurs)\r\n - | 203 | Hourly ERA5 data for near-surface relative humidity (hurs)\r\n - | ||
200 | ERA5-single-hourly/psl # Hourly ERA5 data for sea level pressure | 204 | ERA5-single-hourly/psl # Hourly ERA5 data for sea level pressure | ||
201 | (psl)\r\n - ERA5-single-hourly/rlds # Hourly ERA5 data for surface | 205 | (psl)\r\n - ERA5-single-hourly/rlds # Hourly ERA5 data for surface | ||
202 | downwelling longwave radiation (rlds)\r\n - ERA5-single-hourly/rsds # | 206 | downwelling longwave radiation (rlds)\r\n - ERA5-single-hourly/rsds # | ||
203 | Hourly ERA5 data for surface downwelling shortwave radiation | 207 | Hourly ERA5 data for surface downwelling shortwave radiation | ||
204 | (rsds)\r\n - ERA5-single-hourly/uas # Hourly ERA5 data for eastward | 208 | (rsds)\r\n - ERA5-single-hourly/uas # Hourly ERA5 data for eastward | ||
205 | near-surface wind (uas)\r\n - ERA5-single-hourly/vas # Hourly ERA5 | 209 | near-surface wind (uas)\r\n - ERA5-single-hourly/vas # Hourly ERA5 | ||
206 | data for northward near-surface wind (vas)\r\n - | 210 | data for northward near-surface wind (vas)\r\n - | ||
207 | ERA5-single-hourly/d2m # Hourly ERA5 data for 2m dew temperature\r\n | 211 | ERA5-single-hourly/d2m # Hourly ERA5 data for 2m dew temperature\r\n | ||
208 | - ERA5-single-hourly/pr # Hourly ERA5 data for total | 212 | - ERA5-single-hourly/pr # Hourly ERA5 data for total | ||
209 | precipitation\r\n - ERA5-single-hourly/t2m # Hourly ERA5 data for 2m | 213 | precipitation\r\n - ERA5-single-hourly/t2m # Hourly ERA5 data for 2m | ||
210 | temperature\r\n", | 214 | temperature\r\n", | ||
211 | "format": "TAR", | 215 | "format": "TAR", | ||
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226 | "url_type": null | 230 | "url_type": null | ||
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228 | { | 232 | { | ||
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233 | "datastore_contains_all_records_of_source_file": false, | 237 | "datastore_contains_all_records_of_source_file": false, | ||
234 | "description": "All the BC/downscaled results through | 238 | "description": "All the BC/downscaled results through | ||
235 | QDM\r\n\r\n - QDM/IPSL-CM6A-LR # | 239 | QDM\r\n\r\n - QDM/IPSL-CM6A-LR # | ||
236 | BC/downscaled results for GCM IPSL-CM6A-LR | 240 | BC/downscaled results for GCM IPSL-CM6A-LR | ||
237 | \r\n - QDM/IPSL-CM6A-LR/ssp126 # BC/downscaled | 241 | \r\n - QDM/IPSL-CM6A-LR/ssp126 # BC/downscaled | ||
238 | results for GCM IPSL-CM6A-LR of ssp126(2015 to 2100) \r\n - | 242 | results for GCM IPSL-CM6A-LR of ssp126(2015 to 2100) \r\n - | ||
239 | QDM/IPSL-CM6A-LR/ssp585 # BC/downscaled results for | 243 | QDM/IPSL-CM6A-LR/ssp585 # BC/downscaled results for | ||
240 | GCM IPSL-CM6A-LR of ssp585(2015 to 2100)\r\n - QDM/EC-Earth3 | 244 | GCM IPSL-CM6A-LR of ssp585(2015 to 2100)\r\n - QDM/EC-Earth3 | ||
241 | # BC/downscaled results for GCM EC-Earth3 \r\n - QDM/EC-Earth3/ssp126 | 245 | # BC/downscaled results for GCM EC-Earth3 \r\n - QDM/EC-Earth3/ssp126 | ||
242 | # BC/downscaled results for GCM EC-Earth3 of ssp126(2015 to 2100) | 246 | # BC/downscaled results for GCM EC-Earth3 of ssp126(2015 to 2100) | ||
243 | \r\n - QDM/EC-Earth3/ssp585 # BC/downscaled | 247 | \r\n - QDM/EC-Earth3/ssp585 # BC/downscaled | ||
244 | results for GCM EC-Earth3 of ssp585(2015 to 2100) \r\n - | 248 | results for GCM EC-Earth3 of ssp585(2015 to 2100) \r\n - | ||
245 | QDM/MPI-ESM1-2-HR # BC/downscaled results for | 249 | QDM/MPI-ESM1-2-HR # BC/downscaled results for | ||
246 | GCM MPI-ESM1-2-HR \r\n - QDM/MPI-ESM1-2-HR/ssp126 # | 250 | GCM MPI-ESM1-2-HR \r\n - QDM/MPI-ESM1-2-HR/ssp126 # | ||
247 | BC/downscaled results for GCM MPI-ESM1-2-HR of ssp126(2015 to | 251 | BC/downscaled results for GCM MPI-ESM1-2-HR of ssp126(2015 to | ||
248 | 2100)\r\n - QDM/MPI-ESM1-2-HR/ssp585 # BC/downscaled | 252 | 2100)\r\n - QDM/MPI-ESM1-2-HR/ssp585 # BC/downscaled | ||
249 | results for GCM MPI-ESM1-2-HR of ssp585(2015 to 2100)\r\n - | 253 | results for GCM MPI-ESM1-2-HR of ssp585(2015 to 2100)\r\n - | ||
250 | QDM/MRI-ESM2-0 # BC/downscaled results for | 254 | QDM/MRI-ESM2-0 # BC/downscaled results for | ||
251 | GCM MRI-ESM2-0 \r\n - QDM/MRI-ESM2-0/ssp126 # | 255 | GCM MRI-ESM2-0 \r\n - QDM/MRI-ESM2-0/ssp126 # | ||
252 | BC/downscaled results for GCM MRI-ESM2-0 of ssp126(2015 to 2100)\r\n - | 256 | BC/downscaled results for GCM MRI-ESM2-0 of ssp126(2015 to 2100)\r\n - | ||
253 | QDM/MRI-ESM2-0/ssp585 # BC/downscaled results for | 257 | QDM/MRI-ESM2-0/ssp585 # BC/downscaled results for | ||
254 | GCM MRI-ESM2-0 of ssp585(2015 to 2100)\r\n - QDM/GFDL-ESM4 | 258 | GCM MRI-ESM2-0 of ssp585(2015 to 2100)\r\n - QDM/GFDL-ESM4 | ||
255 | # BC/downscaled results for GCM GFDL-ESM4 \r\n - QDM/GFDL-ESM4/ssp126 | 259 | # BC/downscaled results for GCM GFDL-ESM4 \r\n - QDM/GFDL-ESM4/ssp126 | ||
256 | # BC/downscaled results for GCM GFDL-ESM4 of ssp126(2015 to 2100)\r\n | 260 | # BC/downscaled results for GCM GFDL-ESM4 of ssp126(2015 to 2100)\r\n | ||
257 | - QDM/GFDL-ESM4/ssp585. # BC/downscaled results | 261 | - QDM/GFDL-ESM4/ssp585. # BC/downscaled results | ||
258 | for GCM GFDL-ESM4 of ssp585(2015 to 2100)\r\n", | 262 | for GCM GFDL-ESM4 of ssp585(2015 to 2100)\r\n", | ||
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273 | nd-bias-corrected-dataset-for-multiple-gcms-and-variables/QDM.tar.gz", | 277 | nd-bias-corrected-dataset-for-multiple-gcms-and-variables/QDM.tar.gz", | ||
274 | "url_type": null | 278 | "url_type": null | ||
275 | }, | 279 | }, | ||
276 | { | 280 | { | ||
277 | "cache_last_updated": null, | 281 | "cache_last_updated": null, | ||
278 | "cache_url": null, | 282 | "cache_url": null, | ||
279 | "created": "2023-05-10T21:00:12.447018", | 283 | "created": "2023-05-10T21:00:12.447018", | ||
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282 | "description": "Jupyter notebook with extra information on the | 286 | "description": "Jupyter notebook with extra information on the | ||
283 | dataset.\r\nRetrieved from: | 287 | dataset.\r\nRetrieved from: | ||
284 | https://github.com/OyBcSt/Climate_data/blob/main/index.ipynb", | 288 | https://github.com/OyBcSt/Climate_data/blob/main/index.ipynb", | ||
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299 | d-bias-corrected-dataset-for-multiple-gcms-and-variables/index.ipynb", | 303 | d-bias-corrected-dataset-for-multiple-gcms-and-variables/index.ipynb", | ||
300 | "url_type": "" | 304 | "url_type": "" | ||
301 | } | 305 | } | ||
302 | ], | 306 | ], | ||
303 | "state": "active", | 307 | "state": "active", | ||
304 | "tags": [ | 308 | "tags": [ | ||
305 | { | 309 | { | ||
306 | "display_name": "daily maximum near-surface air temperature", | 310 | "display_name": "daily maximum near-surface air temperature", | ||
307 | "id": "4e20a5f5-3150-40ac-91b2-f2db16af98fe", | 311 | "id": "4e20a5f5-3150-40ac-91b2-f2db16af98fe", | ||
308 | "name": "daily maximum near-surface air temperature", | 312 | "name": "daily maximum near-surface air temperature", | ||
309 | "state": "active", | 313 | "state": "active", | ||
310 | "vocabulary_id": null | 314 | "vocabulary_id": null | ||
311 | }, | 315 | }, | ||
312 | { | 316 | { | ||
313 | "display_name": "daily minimum near-surface air temperature", | 317 | "display_name": "daily minimum near-surface air temperature", | ||
314 | "id": "c868053d-8971-4a12-a91e-6d9705f48297", | 318 | "id": "c868053d-8971-4a12-a91e-6d9705f48297", | ||
315 | "name": "daily minimum near-surface air temperature", | 319 | "name": "daily minimum near-surface air temperature", | ||
316 | "state": "active", | 320 | "state": "active", | ||
317 | "vocabulary_id": null | 321 | "vocabulary_id": null | ||
318 | }, | 322 | }, | ||
319 | { | 323 | { | ||
320 | "display_name": "daily total precipitation", | 324 | "display_name": "daily total precipitation", | ||
321 | "id": "4bbcd693-85e1-4434-9322-969dab47085a", | 325 | "id": "4bbcd693-85e1-4434-9322-969dab47085a", | ||
322 | "name": "daily total precipitation", | 326 | "name": "daily total precipitation", | ||
323 | "state": "active", | 327 | "state": "active", | ||
324 | "vocabulary_id": null | 328 | "vocabulary_id": null | ||
325 | }, | 329 | }, | ||
326 | { | 330 | { | ||
327 | "display_name": "eastward near-surface wind", | 331 | "display_name": "eastward near-surface wind", | ||
328 | "id": "12a798a4-0f36-474d-94e6-16a9c03fc906", | 332 | "id": "12a798a4-0f36-474d-94e6-16a9c03fc906", | ||
329 | "name": "eastward near-surface wind", | 333 | "name": "eastward near-surface wind", | ||
330 | "state": "active", | 334 | "state": "active", | ||
331 | "vocabulary_id": null | 335 | "vocabulary_id": null | ||
332 | }, | 336 | }, | ||
333 | { | 337 | { | ||
334 | "display_name": "near-surface relative humidity", | 338 | "display_name": "near-surface relative humidity", | ||
335 | "id": "52c808b1-40aa-4cdf-8fb1-375051eb0b9e", | 339 | "id": "52c808b1-40aa-4cdf-8fb1-375051eb0b9e", | ||
336 | "name": "near-surface relative humidity", | 340 | "name": "near-surface relative humidity", | ||
337 | "state": "active", | 341 | "state": "active", | ||
338 | "vocabulary_id": null | 342 | "vocabulary_id": null | ||
339 | }, | 343 | }, | ||
340 | { | 344 | { | ||
341 | "display_name": "northward near-surface wind", | 345 | "display_name": "northward near-surface wind", | ||
342 | "id": "2cc3dd62-31fb-4353-815a-d7e0c994a0e7", | 346 | "id": "2cc3dd62-31fb-4353-815a-d7e0c994a0e7", | ||
343 | "name": "northward near-surface wind", | 347 | "name": "northward near-surface wind", | ||
344 | "state": "active", | 348 | "state": "active", | ||
345 | "vocabulary_id": null | 349 | "vocabulary_id": null | ||
346 | }, | 350 | }, | ||
347 | { | 351 | { | ||
348 | "display_name": "sea level pressure", | 352 | "display_name": "sea level pressure", | ||
349 | "id": "94ce9862-eac9-4d3e-839a-e90134c3fbf4", | 353 | "id": "94ce9862-eac9-4d3e-839a-e90134c3fbf4", | ||
350 | "name": "sea level pressure", | 354 | "name": "sea level pressure", | ||
351 | "state": "active", | 355 | "state": "active", | ||
352 | "vocabulary_id": null | 356 | "vocabulary_id": null | ||
353 | }, | 357 | }, | ||
354 | { | 358 | { | ||
355 | "display_name": "surface downwelling longwave radiation", | 359 | "display_name": "surface downwelling longwave radiation", | ||
356 | "id": "22bbd1c2-ef28-49b3-b445-1c384be06550", | 360 | "id": "22bbd1c2-ef28-49b3-b445-1c384be06550", | ||
357 | "name": "surface downwelling longwave radiation", | 361 | "name": "surface downwelling longwave radiation", | ||
358 | "state": "active", | 362 | "state": "active", | ||
359 | "vocabulary_id": null | 363 | "vocabulary_id": null | ||
360 | }, | 364 | }, | ||
361 | { | 365 | { | ||
362 | "display_name": "surface downwelling shortwave radiation", | 366 | "display_name": "surface downwelling shortwave radiation", | ||
363 | "id": "54129a45-0d9d-4b61-b88f-2debe2ca9377", | 367 | "id": "54129a45-0d9d-4b61-b88f-2debe2ca9377", | ||
364 | "name": "surface downwelling shortwave radiation", | 368 | "name": "surface downwelling shortwave radiation", | ||
365 | "state": "active", | 369 | "state": "active", | ||
366 | "vocabulary_id": null | 370 | "vocabulary_id": null | ||
367 | } | 371 | } | ||
368 | ], | 372 | ], | ||
369 | "title": "Downscaled and bias corrected dataset for multiple GCMs | 373 | "title": "Downscaled and bias corrected dataset for multiple GCMs | ||
370 | and variables", | 374 | and variables", | ||
371 | "type": "dataset", | 375 | "type": "dataset", | ||
372 | "url": "", | 376 | "url": "", | ||
373 | "version": "" | 377 | "version": "" | ||
374 | } | 378 | } |