Recherche

Zenodo Translation missing: fr.blacklight.search.logo
Regional model (ACM) output used to investigate the uncertainty in regional future projections of the northwest North Atlantic (Rutherford et al., 2024; BG)
Zenodo
Rutherford, Krysten; Fennel, Katja; Garcia Suarez, Lina; John, Jasmin G. — 2024-01-14 Key variables from the regional Atlantic Canada model (ACM) used to investigate the uncertainty in projections of the northwest North Atlantic. The dataset includes all model variables required to reproduce the key results in Rutherford et al. (2024, BG). See Rutherford_etal_BG_ACM_data_README.txt for more details. https://creativecommons.org/licenses/by/4.0/legalcode
Zenodo Translation missing: fr.blacklight.search.logo
DALROMS-NWA12 v1.0, a coupled circulation-sea ice-biogeochemistry model for the northwest North Atlantic: output files (2 of 2)
Zenodo
Ohashi, Kyoko; Laurent, Arnaud; Renkl, Christoph; Sheng, Jinyu; Fennel, Katja; Oliver, Eric — 2024-07-16 DALROMS-NWA12 v1.0 is a coupled circulation-sea ice-biogeochemistry modelling system based on ROMS, CICE, and MCT. The model domain covers the North Atlantic Ocean from ~81 deg W to ~39 deg W and ~33.5 deg N to 76 deg N. This record includes daily-mean output of all (ocean circulation, sea ice, and biogeochemistry) modules for September 2015. Similar files for September 2013 are available at https://doi.org/10.5281/zenodo.12744506. Model codes, scripts for compiling the model, and sample CPP header files and runtime parameter files (namelists) for physics-only simulations are available at https://doi.org/10.5281/zenodo.12752091. CPP header and runtime parameter files for the biogeochemistry module are available upon request. Sample input files for physics-only simulations are available at https://doi.org/10.5281/zenodo.12752190, https://doi.org/10.5281/zenodo.12734049, and https://doi.org/10.5281/zenodo.12735153. Input files for the biogeochemistry module are available upon request. https://creativecommons.org/licenses/by/4.0/legalcode
Zenodo Translation missing: fr.blacklight.search.logo
Climate model (CM2.6) and regional model (ACM) outputs used to investigate the physical drivers and biogeochemical effects of the weakening of the northwest North Atlantic Shelfbreak Jet (Garcia-Suarez & Fennel., 2024; JAMES)
Zenodo
Garcia-Suarez, Lina; Fennel, Katja — 2024-07-31 Key variables from the climate model GFDL CM2.6 and the regional Atlantic Canada model (ACM) used to investigate the physical drivers and the biogeochemical effects of the weakening of the shelfbreak jet in the northwest North Atlantic Ocean. The dataset includes all model variables required to reproduce the key results in Garcia-Suarez & Fennel (2024, JAMES). See GarciaSuarezandFennel_JAMES_CM26_ACM_data_README.txt for more details. https://creativecommons.org/licenses/by/4.0/legalcode
Zenodo Translation missing: fr.blacklight.search.logo
Data and Processing from "Carbon-centric dynamics of Earth's marine phytoplankton"
Zenodo
Stoer, Adam; Fennel, Katja — 2024-10-01 Brief Summary: This documentation is for associated data and code for:  A. Stoer, K. Fennel, Carbon-centric dynamics of Earth's marine phytoplankton. Proceedings of the National Academy of Sciences (2024).   To cite this software and data, please use: A. Stoer, K. Fennel, Data and processing from "Carbon-centric dynamics of Earth's marine phytoplankton". Zenodo. https://doi.org/10.5281/zenodo.10949682. Deposited 1 October 2024.   List of folders and subfolders and what they contain: raw data: Contains raw data used in the analysis. This folder does not contain the satellite imagery, which will need to be downloaded from the NASA Ocean Color website (https://oceancolor.gsfc.nasa.gov/). bgc-argo float data (subfolder): Includes Argo data from its original source or put into a similar Argo format global region data (subfolder): Includes data used to subset the Argo profiles into each 10deg lat region and basin. graff et al 2015 data (subfolder): Include the data digitized from Graff et al.'s Fig. 2. processed data: data processing by this study (Stoer and Fennel, 2024) processed bgc-argo data (subfolder): A binned processed file is present for each Argo float used in the analysis. Note these files include those describe in Table S1 (these are later processed in "3_stock_bloom_calc.py") processed satellite data (subfolder): includes a 10-deg latitude averaged for each satellite image processed (called "chl_sat_df_merged.csv"). This is later used to calculate a satellite chlorophyll-a climatology in "3_stock_bloom_calc.py". processed chla-irrad data (subfolder): includes the quality-controlled light diffuse attenuation data coupled with the chlorophyll-a fluorescence data to calculate slope factor corrections (the file is called "processed chla-irrad data.csv"). processed topography data (subfolder): includes smoothed topography data (file named "ETOPO_2022_v1_60s_N90W180_surface_mod.tiff"). software: 0_ftp_argo_data_download.py: This program downloads the Argo data from the Global Data Assembly Center's FTP. Running this program will provide new Argo float profiles. However, there will be new floats and profiles present if downloaded. This will not match the historical record of Argo floats used in this analysis but could be useful for replicating this analysis when more data becomes available. The historical record of BGC-Argo floats are present in "/raw data/bgc-argo float data/" path. If you wish to downloaded other float data, see Gordon et al. (2020), Hamilton and Leidos (2017) and the data from the misclab website (https://misclab.umeoce.maine.edu/floats/). 1_argo_data_processing.py: This program quality-controls and bins the biogeochemical data into a consistent format. This includes corrections and checks, like the spike/noise test or the non-photochemical quenching correction. 2_sat_data_processing.py: this program processes the satellite data downloaded from the NASA Ocean Color website. 3_stock_bloom_calc.py: this is the main program used to described the results of the study. The program takes the processed Argo data and groups it into regions and calculates slope factors, phytoplankton carbon & chlorophyll-a, global stocks, and bloom metrics. 4_stock_calc_longhurst_province.py: This program repeats the global stocks calculations performed in "3_stock_bloom_calc.py" but bases the grouping on Longhurst Biogeochemical Provinces. How to Replicate this Analysis: Each program should be run in the order listed above. Path names where the data files have been downloaded will need to be updated in the code.   To use the exact same Sprof files as used in the paper, skip running "0_ftp_argo_data_download.py" and start with "1_argo_data_processing.py" instead. Use the float data from the folder "bgc-argo float data". The program "0_ftp_argo_data_download.py" downloads the latest data from Argo database, so it is useful for updating the analysis. The program "1_argo_data_processing.py" may also be skipped to save time and the processed BGC-Argo float data may be used instead (see folder named "processed bgc-argo data").    Similarly, the program "2_sat_data_processing.py" may also be skipped, which otherwise can take multiple hours to process. The raw data is available from the NASA Ocean Color website (https://oceancolor.gsfc.nasa.gov/). The processed data from "2_sat_data_processing.py" is available so this step may be skipped to save time as well.   The program "3_stock_bloom_calc.py" will require running "ocean_toolbox.py" (see below) in another tab. The portion of the program that involves QC for the irradiance profiles has been commented out to save processing time, and the pre-processed data used in the study has been linked instead (see folder "processed light data"). Similarly, pre-processed topography data is present in this repository. The original Earth Topography data can be accessed at https://www.ncei.noaa.gov/products/etopo-global-relief-model.   A version of "3_stock_bloom_calc.py" using Longhurst provinces is available for exploring alternative groupings and their effects on stock calculations. See the program named "4_stock_calc_longhurst_province.py". You will need to download the Longhurst biogeochemical provinces from https://www.marineregions.org/. To explore the effects of different slope factors, averaging methods, bbp spectral slopes, etc, the user will likely want to make changes to "3_stock_bloom_calc.py". Please do not hesitate to contact the correponding author (Adam Stoer) for guidance or questions. ocean_toolbox.py: import statsmodels.formula.api as smfimport osimport matplotlib.pyplot as pltimport numpy as npfrom uncertainties import unumpy as unpfrom scipy import stats def file_grab(root,find,start): #grabs files by file extensions and location    filelst = []    for subdir, dirs, files in os.walk(root):        for file in files:            filepath = subdir + os.sep + file            if filepath.endswith(find):                if filepath.startswith(start):                    filelst.append(filepath)    return filelst def sep_bbp(data, name_z, name_chla, name_bbp):        '''    data: Pandas Dataframe containing the profile data    name_z: name of the depth variable in data    name_chla: name of the chlorophyll-a variable in data    name_bbp: name of the particle backscattering variable in data            returns: the data variable with particle backscattering partitioned into     phytoplankton (bbpphy) and non-algal particle components (bbpnap).    '''    #name_chla = 'chla'    #name_z = 'depth'    #name_bbp = 'bbp470'    dcm = data[data.loc[:,name_chla]==data.loc[:,name_chla].max()][name_z].values[0] # Find depth of deep chla maximum    part_prof = data[(data.loc[:,name_bbp]<np.median(data.loc[:,name_bbp]))] # find median bbp of profile            mod = smf.quantreg('bbp470 ~ ' + str(name_z),                        part_prof).fit(q=0.01) # Find model to 1 percentile    y_pred = mod.predict(part_prof.loc[:,name_z]) # Create predicted bbp_nap        part_prof.loc[:,'bbp_back'] = y_pred.values # Predicted bbp NAP from linear trend    z_lim = part_prof.loc[(part_prof.loc[:,'bbp_back'].div(part_prof.loc[:,name_bbp])>=1), name_z].min()                                                 # Find depth where bbp NAP and bbp intersect    data.loc[data[name_z]>=z_lim, 'bbp_back'] = data.loc[data[name_z]>=z_lim, name_bbp].tolist()    data.loc[data[name_z]<z_lim,'bbp_back'] = data.loc[data[name_z]==z_lim, name_bbp].values[0] #data.loc[data[name_z]<z_lim, name_z].mul(lr.slope).add(lr.intercept)            data.loc[:,'bbpphy'] = data.loc[:, name_bbp].sub(data.loc[:,'bbp_back']) # Subtract bbp NAP from bbp for bbp from phytoplankton    data.loc[(data['bbpphy']<0)|(data['depth']>z_lim),'bbpphy'] = 0 # Subtract bbp NAP from bbp for bbp from phytoplankton     return data['bbpphy'], z_lim def bbp_to_cphy(bbp_data, sf):        '''    data: Pandas Dataframe containing the profile data    name_bbp: name of the particulate backscattering variable in data    name_bbp_err: name of particulate backscattering error variable in data        returns: the data variable with particle backscattering [/m] converted into    phytoplankton carbon [mg/m^3].    '''        cphy_data = bbp_data.mul(sf)         return cphy_data https://creativecommons.org/licenses/by/4.0/legalcode
Zenodo Translation missing: fr.blacklight.search.logo
DALROMS-NWA12 v1.0, a coupled circulation-sea ice-biogeochemistry model for the northwest North Atlantic: input files (1 of 3)
Zenodo
Ohashi, Kyoko; Laurent, Arnaud; Renkl, Christoph; Sheng, Jinyu; Fennel, Katja; Oliver, Eric — 2024-07-16 DALROMS-NWA12 v1.0 is a coupled circulation-sea ice-biogeochemistry modelling system based on ROMS, CICE, and MCT. The model domain covers the North Atlantic Ocean from ~81 deg W to ~39 deg W and ~33.5 deg N to 76 deg N. This record includes most of the input files necessary for a physics-only simulation from 1 September to 31 December 2013. The remaining input files for this period, which should be placed in the directory sponge/ within the directory tree contained in this record, are available at https://doi.org/10.5281/zenodo.12734049 and https://doi.org/10.5281/zenodo.12735153. Input files for the biogeochemistry module are available upon request. Model codes, scripts for compiling the model, and sample CPP header files and runtime parameter files (namelists) for physics-only simulations are available at https://doi.org/10.5281/zenodo.12752091. CPP header and runtime parameter files for the biogeochemistry module are available upon request. Sample output files (from the physics and biogeochemistry modules) are available at https://doi.org/10.5281/zenodo.12744506 and https://doi.org/10.5281/zenodo.12746262. https://creativecommons.org/licenses/by/4.0/legalcode
Zenodo Translation missing: fr.blacklight.search.logo
DALROMS-NWA12 v1.0, a coupled circulation-sea ice-biogeochemistry model for the northwest North Atlantic: output files (1 of 2)
Zenodo
Ohashi, Kyoko; Laurent, Arnaud; Renkl, Christoph; Sheng, Jinyu; Fennel, Katja; Oliver, Eric — 2024-07-16 DALROMS-NWA12 v1.0 is a coupled circulation-sea ice-biogeochemistry modelling system based on ROMS, CICE, and MCT. The model domain covers the North Atlantic Ocean from ~81 deg W to ~39 deg W and ~33.5 deg N to 76 deg N. This record includes daily-mean output of all (ocean circulation, sea ice, and biogeochemistry) modules for September 2013, when the simulation was initialized. Similar files for January 2015 are available at https://doi.org/10.5281/zenodo.12746262. Model codes, scripts for compiling the model, and sample CPP header files and runtime parameter files (namelists) for physics-only simulations are available at https://doi.org/10.5281/zenodo.12752091. CPP header and runtime parameter files for the biogeochemistry module are available upon request. Sample input files for physics-only simulations are available at https://doi.org/10.5281/zenodo.12752190, https://doi.org/10.5281/zenodo.12734049, and https://doi.org/10.5281/zenodo.12735153. Input files for the biogeochemistry module are available upon request. https://creativecommons.org/licenses/by/4.0/legalcode
Zenodo Translation missing: fr.blacklight.search.logo
Climate model (CM2.6) and regional model (ACM) processed output used to investigate the physical drivers and biogeochemical effects of the weakening of the northwest North Atlantic Shelfbreak Jet (Garcia-Suarez & Fennel., 2024; JAMES)
Zenodo
Garcia-Suarez, Lina; Fennel, Katja — 2024-11-28 Key processed output from the climate model GFDL CM2.6 and the regional Atlantic Canada model (ACM) used to investigate the physical drivers and the biogeochemical effects of the weakening of the shelfbreak jet in the northwest North Atlantic Ocean. The dataset includes all model variables required to reproduce the key results in Garcia-Suarez & Fennel (2024, JAMES). See GarciaSuarezandFennel_JAMES_CM26_ACM_data_README_v2.txt for more details. https://creativecommons.org/licenses/by-sa/4.0/legalcode
Zenodo Translation missing: fr.blacklight.search.logo
DALROMS-NWA12 v1.0, a coupled circulation-sea ice-biogeochemistry model for the northwest North Atlantic: input files (2 of 3)
Zenodo
Ohashi, Kyoko; Laurent, Arnaud; Renkl, Christoph; Sheng, Jinyu; Fennel, Katja; Oliver, Eric — 2024-07-16 DALROMS-NWA12 v1.0 is a coupled circulation-sea ice-biogeochemistry modelling system based on ROMS, CICE, and MCT. The model domain covers the North Atlantic Ocean from ~81 deg W to ~39 deg W and ~33.5 deg N to 76 deg N. This record includes the files necessary for nudging the simulated temperature and salinity towards Copernicus GLORYS12V1 reanalysis values in a simulation from 1 September to 31 December 2013. The remaining input files for this period are available at https://doi.org/10.5281/zenodo.12752190 and https://doi.org/10.5281/zenodo.12735153. Model codes, scripts for compiling the model, and sample CPP header files and runtime parameter files (namelists) for phyiscs-only simulations are available at https://doi.org/10.5281/zenodo.12752091. CPP header and runtime parameter files for the biogeochemistry module are available upon request. Sample output files (from the physics and biogeochemistry modules) are available at https://doi.org/10.5281/zenodo.12744506 and https://doi.org/10.5281/zenodo.12746262. https://creativecommons.org/licenses/by/4.0/legalcode
Zenodo Translation missing: fr.blacklight.search.logo
Model output (ROMS_HH3) of simulating OAE in Halifax Harbour
Zenodo
Wang, Bin; Fennel, Katja — 2025-01-10 This repository provides model output (HRM3) for analysis in the following article: Wang B., Laurent A., Pei Q., Sheng J., Atamanchuk D., Fennel K. Maximizing the detectability of Ocean Alkalinity Enhancement (OAE) while minimizing its exposure risks: Insights from a numerical study. preprint https://creativecommons.org/licenses/by/4.0/legalcode
Zenodo Translation missing: fr.blacklight.search.logo
DALROMS-NWA12 v1.0, a coupled circulation-sea ice-biogeochemistry model for the northwest North Atlantic: input files (3 of 3)
Zenodo
Ohashi, Kyoko; Laurent, Arnaud; Renkl, Christoph; Sheng, Jinyu; Fennel, Katja; Oliver, Eric — 2024-07-16 DALROMS-NWA12 v1.0 is a coupled circulation-sea ice-biogeochemistry modelling system based on ROMS, CICE, and MCT. The model domain covers the North Atlantic Ocean from ~81 deg W to ~39 deg W and ~33.5 deg N to 76 deg N. This record includes the files necessary for nudging the currents towards Copernicus GLORYS12V1 reanalysis values in a simulation from 1 September to 31 December 2013. The remaining input files for this period are available at https://doi.org/10.5281/zenodo.12752190 and https://doi.org/10.5281/zenodo.12734049. Model codes, scripts for compiling the model, and sample CPP header files and runtime parameter files (namelists) for physics-only simulations are available at https://doi.org/10.5281/zenodo.12752091. CPP header and runtime parameter files for the biogeochemistry module are available upon request. Sample output files (from the physics and biogeochemistry modules) are available at https://doi.org/10.5281/zenodo.12744506 and https://doi.org/10.5281/zenodo.12746262. https://creativecommons.org/licenses/by/4.0/legalcode
Zenodo Translation missing: fr.blacklight.search.logo
Model output (ROMS_HH2) of simulating OAE in Halifax Harbour
Zenodo
Wang, Bin; Fennel, Katja — 2025-01-10 This repository provides model output (HRM2) for analysis in the following article: Wang B., Laurent A., Pei Q., Sheng J., Atamanchuk D., Fennel K. Maximizing the detectability of Ocean Alkalinity Enhancement (OAE) while minimizing its exposure risks: Insights from a numerical study. preprint https://creativecommons.org/licenses/by/4.0/legalcode

Instructions pour la recherche cartographique

1.Activez le filtre cartographique en cliquant sur le bouton « Limiter à la zone sur la carte ».
2.Déplacez la carte pour afficher la zone qui vous intéresse. Maintenez la touche Maj enfoncée et cliquez pour encadrer une zone spécifique à agrandir sur la carte. Les résultats de la recherche changeront à mesure que vous déplacerez la carte.
3.Pour voir les détails d’un emplacement, vous pouvez cliquer soit sur un élément dans les résultats de recherche, soit sur l’épingle d’un emplacement sur la carte et sur le lien associé au titre.
Remarque : Les groupes servent à donner un aperçu visuel de l’emplacement des données. Puisqu’un maximum de 50 emplacements peut s’afficher sur la carte, il est possible que vous n’obteniez pas un portrait exact du nombre total de résultats de recherche.

(source : Zenodo) AND (auteur : Fennel, Katja)

Limiter par :

Effacer tout

au