Quantifying Cloud-Fog-Induced Reductions in Near-Surface Solar Radiation Using the Reduction Ratio Method
Authors/Creators
- 1. Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan
- 2. Department of Earth and Environmental Engineering, Columbia University, New York, USA
- 3. Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, Australia
- 4. National Science and Technology Center for Disaster Reduction, New Taipei City, Taiwan
- 5. Department of Geography, National Taiwan University, Taipei, Taiwan
Description
Version history
Version 2:
This version updates Figure1.py and MainFigure.ipynb to match the revised manuscript submitted to Geophysical Research Letters. Specifically, a scale bar was added to Figure 1. No changes were made to the input datasets, analysis workflow, or scientific results.
Code
All results were analyzed and visualized by Python version 3.9.18.
| Filename | Description |
| MainFigures.ipynb | Jupyter Notebook for reproduce all figures in the article. |
| Figure*.py | Python file for reproduce each figure in the article. |
Data
Ground Station Observation
| Filename | Description |
| 467530_hr_19800101_20230101.csv | Alishan station data managed by Central Weather Administration (CWA) of Taiwan, which is generated from Atmospheric Science Research and Application Databank. |
Solar Radiation Reduction Ratio (RRSR) Results
| Filename | Description |
|
ReductionRatio_20151001_20220930_31_daily.nc |
RRSR of Taiwan (119.9°E–122.1°E, 21.8°N–25.4°N, 0.01° x 0.01°) from 2015-10-01 to 2022-09-30, which is generated from TCCIP Grid-point Surface Insolation Derived from Geostationary Satellite Dataset. |
|
*_hr_20151001_20220930_seasonal.csv |
Seasonal mean RRSR for 6 CWA stations (Alishan, Anbu, Yushan, Sun Moon Lake, Chiayi, and Keelung). |
|
*_hr_20151001_20220930_DJF_NE_means.csv |
Winter (December–February) event-mean RRSR for 6 CWA stations (Alishan, Anbu, Yushan, Sun Moon Lake, Chiayi, and Keelung). |
Land and Non-rainy Mask
| Filename | Description |
|
LandNonRainyMask_2015_2022.nc |
Mask for land area and non-rainy data, which is generated from TCCIP Gridded Historical Daily Dataset for Taiwan. |
Land-type Classification
Generated from Schulz et al. (2017).
| Filename | Description |
| MCF2017.zip | Shapefile of montane cloud forests (MCFs) region in Taiwan. |
| nonMCF2017.zip | Shapefile of forest region other than montane cloud forest in Taiwan. |
| MCFfraction_TCCIP.npy | Forest classification in Taiwan regrid to TCCIP dataset. |
North-easterlies events classification
Adopted from Taiwan Atmospheric Event Database.
| Filename | Description |
| TAD_NE.csv |
North-easterlies events classification based on the criteria of Taiwan Atmospheric Event Database (TAD). |
Others
Generated from Open Data in Taiwan.
| Filename | Description |
| Taiwan_WGS84.zip | Shapefile of coastlines of Taiwan. |
| dem20_TCCIPInsolation.nc | Digital Elevation Model of Taiwan regrid to TCCIP dataset. |
Note
- Please unzip .zip first to get shapfile before reproduce the figures in the article.
Files
MainFigures.ipynb
Files
(2.4 GB)
| Name | Size | |
|---|---|---|
|
md5:2a43d5391172936a0cdbcf60032d9bcc
|
99 Bytes | Preview Download |
|
md5:1b58b6fc861e86526b68bfa29e983c36
|
119 Bytes | Preview Download |
|
md5:05d83d10a41c83dd906454ff0eaac5a4
|
98 Bytes | Preview Download |
|
md5:00a7cb240bb18315a2bc34f7e8d59a6f
|
117 Bytes | Preview Download |
|
md5:c4fbc5c5f99611d02bc9740617f0d09a
|
100 Bytes | Preview Download |
|
md5:edc755ec48e404184c2d391ddf4d8918
|
118 Bytes | Preview Download |
|
md5:51fcb47d844f06556fea0638399528de
|
117.3 MB | Preview Download |
|
md5:0fc2cab1ca301009a11826124f46c37e
|
100 Bytes | Preview Download |
|
md5:7e5f7312fe4730e30056e2926d0f36b4
|
119 Bytes | Preview Download |
|
md5:d79ce0f0e64480e96aeb773768a62cbe
|
101 Bytes | Preview Download |
|
md5:9a6ebe5e7ac00351e9e0cf62656ba3e9
|
120 Bytes | Preview Download |
|
md5:fff81a29e7cfb53498de80dc3ac1a9dd
|
98 Bytes | Preview Download |
|
md5:ab8d9df8e1e4a19e85041d5b40761878
|
122 Bytes | Preview Download |
|
md5:ce57238536789fdaec1960a9f5405c33
|
1.2 MB | Download |
|
md5:940a0d6ee97147b75f1442cff5f72f7a
|
20.9 kB | Download |
|
md5:552d0798100a3e244cdcdba33f0d0725
|
4.2 kB | Download |
|
md5:a65efb0756d3efe8985bbda450cb8ea7
|
33.1 kB | Download |
|
md5:7e9d769602a99d33320e4fecb0b2cd4b
|
25.2 kB | Download |
|
md5:6d5aa40a9b6c1829662046613505d8db
|
17.9 MB | Download |
|
md5:7fd9fb71a4e8d396949434ecb2525360
|
12.6 MB | Preview Download |
|
md5:53417e15a0f0ff7663d6a989fe39b96f
|
3.2 MB | Preview Download |
|
md5:dc7fc581a2da72366e07ee1b59c767d0
|
9.7 MB | Download |
|
md5:1858f5a328d202329fb668c0401d7f5b
|
9.0 MB | Preview Download |
|
md5:0b17314ef7f410812a38f91b80ff6ee1
|
2.2 GB | Download |
|
md5:0be958d3dec06e13bf89e8e43c511d36
|
46.6 kB | Preview Download |
|
md5:c622c956df479b8c33443803b84469b4
|
1.5 MB | Preview Download |
Additional details
Software
- Programming language
- Python