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Publication Year: 2022

121 to 130 of 727 Results

2_Asia_Oceania_Data_Import_Peat.ipynb Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis Jupyter Notebook - 12.6 KB - MD5: 45dd12aa67af30d36636be39e3436737 Code This notebook will download and process (reproject, union Southeast Asia and Oceania, rasterize, synchronize in HR or LR and encoding) Asia and Oceania peat shapefiles
2_Asia_Oceania_Data_Import_Peat.py Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis Python Source Code - 7.3 KB - MD5: 7aadf793ebc05409196952a7e7477680 Code This code will download and process (reproject, union Southeast Asia and Oceania, rasterize, synchronize in HR or LR and encoding) Asia and Oceania peat shapefiles
2_Data_Import_Peat.ipynb Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis Jupyter Notebook - 204.2 KB - MD5: 49714f9c6d1bba4ef193a86103fd83c4 Code This notebook will download and process (reproject, union) peat shapefiles
2_Data_Import_Peat.py Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis Python Source Code - 6.5 KB - MD5: 3b50a90ec99dc1f651bfabd5ce1faecc Code This code will download and process (reproject, union) peat shapefiles
3_Seasonality_Index.ipynb Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis Jupyter Notebook - 331.4 KB - MD5: de477606342adce6dd7fecc70d03da0b Code This notebook will calculate the following variables: precipitation amount (yearly) and seasonality index (dimensionless) and the coefficient of variation of precipitation (CV)
3_Seasonality_Index.py Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis Python Source Code - 9.2 KB - MD5: 9122c11174bdf1944f009d4fa8b4c973 Code This code will calculate the following variables: precipitation amount (yearly) and seasonality index (dimensionless) and the coefficient of variation of precipitation (CV)
4_Tropical_Peats.ipynb Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis Jupyter Notebook - 215.2 KB - MD5: aea19aa99261170a0c1ab8a775eb5622 Code This notebook will process and plot the climate space (precipitation amount, seasonality index or precipitation CV) of tropical peatland areas in HR or LR
4_Tropical_Peats.py Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis Python Source Code - 19.4 KB - MD5: 6761d5c0833253811a79547ff622a3ee Code This code will process and plot the climate space (precipitation amount, seasonality index or precipitation CV) of tropical peatland areas in HR or LR
5_Precip_Reconstruction.ipynb Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis Jupyter Notebook - 557.1 KB - MD5: 8324b04aef79baaa64e5c07ecc02fc6a Code This notebook will allow estimating past changes in precipitation amount and/or seasonality using peat δDn-C29 values compared with a wide range of δDprecip values at the CEN-17.4 site computed using an empirical approach based on modern climate data
5_Precip_Reconstruction.py Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis Python Source Code - 21.7 KB - MD5: 51f4f64aba511a2b0c61bcf4e4a34c5a Code This code will allow estimating past changes in precipitation amount and/or seasonality using peat δDn-C29 values compared with a wide range of δDprecip values at the CEN-17.4 site computed using an empirical approach based on modern climate data

2_Asia_Oceania_Data_Import_Peat.ipynb

Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis

Jupyter Notebook - 12.6 KB -

Code

This notebook will download and process (reproject, union Southeast Asia and Oceania, rasterize, synchronize in HR or LR and encoding) Asia and Oceania peat shapefiles

2_Asia_Oceania_Data_Import_Peat.py

Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis

Python Source Code - 7.3 KB -

Code

This code will download and process (reproject, union Southeast Asia and Oceania, rasterize, synchronize in HR or LR and encoding) Asia and Oceania peat shapefiles

2_Data_Import_Peat.ipynb

Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis

Jupyter Notebook - 204.2 KB -

Code

This notebook will download and process (reproject, union) peat shapefiles

2_Data_Import_Peat.py

Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis

Python Source Code - 6.5 KB -

Code

This code will download and process (reproject, union) peat shapefiles

3_Seasonality_Index.ipynb

Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis

Jupyter Notebook - 331.4 KB -

Code

This notebook will calculate the following variables: precipitation amount (yearly) and seasonality index (dimensionless) and the coefficient of variation of precipitation (CV)

3_Seasonality_Index.py

Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis

Python Source Code - 9.2 KB -

Code

This code will calculate the following variables: precipitation amount (yearly) and seasonality index (dimensionless) and the coefficient of variation of precipitation (CV)

4_Tropical_Peats.ipynb

Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis

Jupyter Notebook - 215.2 KB -

Code

This notebook will process and plot the climate space (precipitation amount, seasonality index or precipitation CV) of tropical peatland areas in HR or LR

4_Tropical_Peats.py

Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis

Python Source Code - 19.4 KB -

Code

This code will process and plot the climate space (precipitation amount, seasonality index or precipitation CV) of tropical peatland areas in HR or LR

5_Precip_Reconstruction.ipynb

Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis

Jupyter Notebook - 557.1 KB -

Code

This notebook will allow estimating past changes in precipitation amount and/or seasonality using peat δDn-C29 values compared with a wide range of δDprecip values at the CEN-17.4 site computed using an empirical approach based on modern climate data

5_Precip_Reconstruction.py

Oct 21, 2022 - Hydroclimatic vulnerability of peat carbon in the central Congo Basin: codes for age-depth models, geospatial data processing and analysis

Python Source Code - 21.7 KB -

Code

This code will allow estimating past changes in precipitation amount and/or seasonality using peat δDn-C29 values compared with a wide range of δDprecip values at the CEN-17.4 site computed using an empirical approach based on modern climate data

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