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opencc-by-4.0May 2020View details →

PEATCLSM(Tb): A land surface data assimilation product for peatlands using PEATCLSM and brightness temperature (Tb) satellite observations (Northern Hemisphere output)

The datasets archived here include simulation results shown in the paper, “Improved Groundwater Table and L-band Brightness Temperature Estimates for Northern Hemisphere Peatlands Using New Model Physics and SMOS Observations in a Global Data Assimilation Framework”, published in Remote Sensing of Environment Journal (Bechtold et al., 2020). The output was produced by combining peatland-specific land surface modeling (Bechtold et al., 2019b) embedded in the NASA Catchment Land Surface Model (CLSM) with L-band brightness temperature (Tb) observations (SMOS), applying the data assimilation framework of the SMAP Level‐4 Soil Moisture product (Reichle et al., 2019). We provide netcdf files (9-km resolution EASEv2 grid, period Jan 2010 – Nov 2019, and between 45°N and 70°N, NE Asia excluded) of the four experiments of the manuscript: model-only (open-loop, OL) and data assimilation (DA) for each land model version, that is CLSM without and with the use of the PEATCLSM modules. The highest accuracy is provided by the DA product using PEATCLSM and Tb observations. When referring to the latter product use the name ‘PEATCLSM(Tb)’. We provide three types of netcdf files: •    daily_images_*.nc: Daily land states and fluxes (Table 1), provided as netCDF image-chunked image stack •    ObsFcstAna_images_*.nc: Brightness temperature observations, forecasts and analysis (Table 2), provided as netCDF image-chunked image stack •    incr_timeseries_*.nc: Data assimilation increments (Table 3), provided as netCDF timeseries-chunked image stack The file content is described in the file PEATCLSM_Tb_Documentation_20200505.pdf Please contact Michel Bechtold (michel.bechtold@kuleuven.be) for any questions. Data usage statement: This work is licensed under a Creative Commons Attribution 4.0 International License: https://creativecommons.org/licenses/by/4.0/ If you decide to work with this data, we kindly ask to be informed at the outset of the nature of this work. If the data are essential to the work, or if an important result or conclusion depends on the PEATCLSM(Tb) data product, we would appreciate that you discuss these findings with us to ensure correct use and interpretation of the PEATCLSM(Tb) product. Furthermore, we are continuously improving the data assimilation product, a discussion of your work at an early stage may (i) help us to improve our product, and (ii) allow us to provide you with a newer version. Thanks! References: Bechtold, M., De Lannoy, G. J. M., Reichle, R. H., & Koster, R. D. (2019a). PEAT-CLSM simulation output (Northern Peatlands) version 1. https://doi.org/10.17605/OSF.IO/E58YM Bechtold, M. et al. (2019b). PEAT‐CLSM: A Specific Treatment of Peatland Hydrology in the NASA Catchment Land Surface Model. Journal of Advances in Modeling Earth Systems, 11(7), 2130–2162. https://doi.org/10.1029/2018MS001574 Bechtold, M., De Lannoy, G. J. M., Reichle, R. H., Roose, D., Balliston, N., Burdun, I., Devito, K., Kurbatova, J., Strack, M., & Zarov, E. A. (2020). Improved Groundwater Table and L-band Brightness Temperature Estimates for Northern Hemisphere Peatlands Using New Model Physics and SMOS Observations in a Global Data Assimilation Framework. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2020.111805 Reichle, R. H., Liu, Q., Koster, R. D., Crow, W. T., De Lannoy, G. J. M., Kimball, J. S., Ardizzone, J. V., Bosch, D., Colliander, A., Cosh, M., Kolassa, J., Mahanama, S. P., Prueger, J., Starks, P., & Walker, J. P. (2019). Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product. Journal of Advances in Modeling Earth Systems, 11(10), 3106–3130. https://doi.org/10.1029/2019MS001729

opencc-by-4.0Apr 2024View details →

Crocus-ERA-Interim daily snow product over the Northern Hemisphere at 0.5° resolution

The Crocus-ERA-Interim daily snow product is derived from the complex snow scheme Crocus coupled to the ISBA (Interactions between Soil–Biosphere–Atmosphere) land surface model (<a href="http://dx.doi.org/10.1175/JHM-D-12-012.1">Brun et al., 2013</a>) and embedded into the SURFEX numerical platform (<a href="https://www.umr-cnrm.fr/surfex/">https://www.umr-cnrm.fr/surfex/</a>). The model is driven by a meteorological forcing (temperature, precipitation, humidity, winds, etc) derived from the ERA-Interim global atmospheric reanalysis (<a href="https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-interim">https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-interim</a>). This product only concerns open field snowpack, i.e. only low vegetation is modeled (no forest). It covers the entire Northern Hemisphere at 0.5° resolution over the 1979-07-01 to 2019-06-30 period. Snow depth and snow water equivalent (i.e. the snow mass) are available at a dailly frequency. The simulated snow depth, snow water equivalent, and density over open fields were validated against local observations from over 1000 monitoring sites in Northern Eurasian, available either once a day or three times per month (<a href="http://dx.doi.org/10.1175/JHM-D-12-012.1">Brun et al., 2013</a>). This product was used by the NOAA <a href="https://arctic.noaa.gov/report-card/">Artic Report Card</a> from 2017 to 2020 for the annual survey of the Terrestrial Snow Cover anomalies over the Northern Hemisphere. This product was also used in several research studies (e.g. <a href="https://doi.org/10.1175/JCLI-D-15-0229.1">Mudryk et al., 2015</a>; <a href="https://doi.org/10.5194/tc-14-1579-2020">Mortimer et al., 2020</a>; <a href="https://doi.org/10.5194/tc-17-5007-2023">Kouki et al., 2023</a>). The successor of this product based on ERA5 at 0.25° resolution over 1950 to 2023 can be found in <a href="https://doi.org/10.5281/zenodo.10943718">Decharme (2024b)</a>.

opencc-by-4.0Apr 2024View details →

Crocus-ERA5 daily snow product over the Northern Hemisphere at 0.25° resolution

The Crocus-ERA5 daily snow product is derived from the complex snow scheme Crocus coupled to the ISBA (Interactions between Soil–Biosphere–Atmosphere) land surface model (<a href="http://dx.doi.org/10.1175/JHM-D-12-012.1">Brun et al., 2013</a>) and embedded into the SURFEX numerical platform (<a href="https://www.umr-cnrm.fr/surfex/">https://www.umr-cnrm.fr/surfex/</a>). The model is driven by a meteorological forcing (temperature, precipitation, humidity, winds, etc) derived from the ERA5 global atmospheric reanalysis (<a href="https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5">https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5</a>). This product only concerns open field snowpack, i.e. only low vegetation is modeled (no forest). It covers the entire Northern Hemisphere at 0.25° resolution over the 1950-07-01 to 2023-06-30 period. All snow characteristics (see later) are available at a dailly frequency. This product is the successor of the Crocus-ERA-Interim daily snow product (<a href="../records/10911538">Decharme, 2024</a>). It is used by the NOAA <a href="https://arctic.noaa.gov/report-card/">Artic Report Card</a> from 2021 to present for the annual survey of the Terrestrial Snow Cover anomalies over the Northern Hemisphere. An evaluation of the snow water equivalent product can be found in <a href="https://egusphere.copernicus.org/preprints/2024/egusphere-2023-3014/">Mudryk et al. (2024)</a> where it is compared to observations and to about twenty alternative datasets.

opencc-by-4.0Jun 2022View details →

Supporting Data for: McKenna et al. (2018), Arctic sea-ice loss in different regions leads to contrasting Northern Hemisphere impacts

This is a dataset of output from version 4 of the Reading Intermediate Global Circulation Model (IGCM4) that was used in the article:  McKenna, C. M., Bracegirdle, T. J., Shuckburgh, E. F., Haynes, P. H., & Joshi, M. M. (2018). Arctic sea ice loss in different regions leads to contrasting Northern Hemisphere impacts. Geophysical Research Letters, 45, 945-954. <a href="https://doi.org/10.1002/2017GL076433">https://doi.org/10.1002/2017GL076433</a>   Files required to setup the IGCM4 simulations are given in the directory 'IGCM4_setup'. All other directories contain netcdf files of timeseries of various monthly mean fields for each IGCM4 simulation (see paper for details on these simulations). The available variables are: <ul> <li>ua:   zonal winds</li> <li>zg:   geopotential height</li> <li>ts:   surface temperature</li> <li>hfls, hfss, rlds, rlus:   surface heatfluxes</li> <li>Flat, Fz, divF:   Eliassen-Palm flux vectors and their divergence (only for months November-February)</li> </ul> The ua and zg variables are given for different pressure levels indicated in the filenames (e.g., ua500 is ua at 500 hPa). ua is additionally given in terms of the zonal mean with latitude and pressure. zg is additionally given in terms of longitude and pressure, averaged over latitudes between 60N-80N. All files follow CF conventions in terms of metadata, variable names, etc.  Note that the CTL, ATL, PAC, and ATLandPAC simulations were all run continuously in time (i.e., every year starts from the end of the previous year). The 0.5ATL and 0.5PAC simulations, however, were run for 300 years in three separate 100-year chunks (i.e., the initial conditions used to start each 100-year chunk were different). The three 100-year chunks have been appended together in the netcdf files.

opencc-by-4.0Aug 2022View details →

Ground ice content predictions for the Northern Hemisphere permafrost region at 1-km resolution, version 1.1

Ground ice content is one of the least known characteristics of the permafrost-affected soils in the Northern Hemisphere. At the same time, ground ice content exerts a crucial effect on the thermal response of permafrost to changing climate and environmental conditions, and dictates the permafrost degradation-related geomorphic, hydrologic, and ecological processes, including thermokarst. This dataset presents numerical estimates of volumetric ice content over the permafrost region at a 1-km spatial resolution. The predictions are representative of pore and segregated ice contents in the topmost five meters of permafrost. We use compilations of field measurements of ground ice contents from across the permafrost region to train statistical models and to predict volumetric ice content with the aid of high-resolution geospatial data on climatic, soil and topography conditions. The dataset facilitates assessments of conditions of changing permafrost landscapes at an improved spatial and thematic resolution.

opencc-by-4.0Jun 2024View details →

ESA Cryo-TEMPO - Northern hemisphere land/ocean flag and distance to coast at resolution of 250 m.

Land/Ocean flag nd distance to coast at high spatial resolution (250m) in the northern hemisphere. The land/ocean flag is computed from merged Open Street Map and Natural Earth land polygons. The shapefiles were rasterized and reprojected to northern hemisphere using gdal. All land mass with the exception of Greenland are based on Open Street Map. Distance to coast was computed with gdal (gdal_proximity.py).  The file format is netCDF-4 and the datafile contains two variables (land_ocean_flag & distance_to_coast). The coordinate reference system of the variables is defined by EPSG:6931 (WGS 84 / NSIDC EASE-Grid 2.0 North) and the bounds of the data set are supplied as xc and yc variables in the data file.  The file is used in the ESA CryoSat-2 Thematic Products (Cryo-TEMPO) Polar Ocean and Sea Ice products in the northern hemisphere.

opencc-by-4.0Mar 2024View details →

Models and Datasets for "Extracting Paleoweather from Paleoclimate: A Deep Learning Reconstruction of Northern Hemisphere Summertime Atmospheric Blocking over the Last Millennium"

Associated publication: Karamperidou, C., Extracting Paleoweather from Paleoclimate: A Deep Learning Reconstruction of Northern Hemisphere Summertime Atmospheric Blocking over the Last Millennium, Nature Communications Earth & Environment, (2024)   This repository contains: <ul> <li>the architecture and weights of PaleoBlockNet v1.0</li> <li>the following ensemble DL reconstructions of JJA frequency of blocked days inferred by PaleoBlockNet: <ol> <li>the 10-member NTREND-based DL reconstruction; uses as input the NTREND DA N.Hemisphere MJJA surface temperature anomaly by King et al. (2021)</li> <li>the 100-member PHYDA-based DL reconstruction; uses as input the PHYDA JJA surface temperature anomaly by Steiger et al. (2018)</li> <li>the 12-member LME-based DL reconstruction; uses as input the CESM-LME surface temperature anomaly; this is a sensitivity experiment (see publication for details).</li> </ol> </li> <li>Integrated Gradients that assign importance to the input features for PaleoblockNet's blocking inferences </li> <li>train-validate-test samples to use with sample scripts from the Gituhub repo github/ckaramp-research/paleoblocknet</li> </ul>   If you use this dataset, please cite the associated publication and the present repository. To interactively explore the datasets, a web interface has been developed and can be accessed at <a href="https://www2.hawaii.edu/~ckaramp/paleoblocknet">https://www2.hawaii.edu/~ckaramp/paleoblocknet</a> Contact the author Christina Karamperidou (<a title="Karamperidou Research Group" href="https://www2.hawaii.edu/~ckaramp" target="_blank" rel="noopener">https://www2.hawaii.edu/~ckaramp</a>) for more information about the details of these datasets.

opencc-by-4.0Jul 2024View details →

Comprehensive Mini-Database of the Northern Hemisphere's Winter Sky: 100 Raw Images from Ensenada, Mexico

We carried out several test sessions for data collection to adjust the settings of our optical system. From October 2022 to June 2023, we executed numerous sessions to assemble our primary catalog, capturing an extensive array of sky views. A total of 100 sky observations were recorded from various directions without restrictions. These sessions were held at the peak of a hill where CICESE, our research institute, is situated at coordinates 31°52′21.5′′ N 116°40′11.8′′ W in Ensenada, Baja California, Mexico. This location was chosen because it is relatively free from urban light pollution and noise, despite its proximity to the city outskirts. This position minimizes city light interference on one side, slightly reducing light pollution, although image quality was occasionally compromised by the light pollution and facility lighting. Using the ASI Studio software, we captured high-resolution images of 5496 × 3672 pixels without employing pixel binning to achieve the highest possible resolution. The camera's settings were adjusted to an exposure time of 0.5 seconds and standard gain, with the lens focused at infinity and an aperture set at f/4. This setup enabled us to detect significant background noise and numerous areas that could potentially contain stars. More information about the article is in the: <a href="https://doi.org/10.3390/aerospace10090748">https://doi.org/10.3390/aerospace10090748</a>

opencc-by-4.0Dec 2022View details →

NH-SWE: Northern Hemisphere Snow Water Equivalent dataset based on in-situ snow depth time series and the regionalisation of the ΔSNOW model

Time series of daily Snow Water Equivalent (SWE) and Snow Density over the Northern Hemisphere, based on in-situ station observations of snow depth converted to SWE using the ΔSNOW model (Winkler et al., 2021) and regionalised parameters.  An extensive description of the dataset and the method to generate it can be found in the data descriptor manuscript published in the journal Earth System Science Data: <a href="https://essd.copernicus.org/preprints/essd-2023-31/">https://essd.copernicus.org/articles/15/2577/2023/essd-15-2577-2023</a>  Dataset: A total of 11,0071 time series of modelled SWE and estimated snow density at the point scale, spanning 1950-2022, at daily resolution. "NH-SWE_dataset_MAP.png" shows a Northern Hemisphere map with the location of all stations in the NH-SWE dataset and their elevation in meters.  Files: The dataset is provided in two different formats: <ol> <li>Individual .csv files for each station in the NH-SWE dataset at "NH_SWE_dataset_vector_files.zip"</li> <li>Full-dataset .csv matrices with dates as rows and NH-SWE stations as columns at "NH_SWE_dataset_matrix_files.zip"</li> </ol> Metadata: "NH_SWE_METADATA.csv" Includes information on NH-SWE stations location (ID, country, station name, coordinates, elevation), data source, length of time series, model parameters and the climate variables used to estimate them, and average snow climatology such as average maximum snow depth, average peak SWE and average maximum snow cover duration. More details and units in the "README_fileformats.txt" file.  ΔSNOW model parameter regionalisation: The code to obtain the ΔSNOW model parameters based on climate variables for all the stations in the NH-SWE dataset is shared in "DeltaSNOW_parameter_regionalisation.zip". The method is extensively described in the data descriptor manuscript by Fontrodona-Bach et al., (2023) submitted to Earth System Science Data. More details in the "README_regionalisation.txt" file.  Data use: Free, provided adequate citation of both the data descriptor manuscript and the zenodo record. See "README_datausage.txt" Version history: v1: Initial upload. The ΔSNOW model regionalisation was missing. v2: Manuscript submission version. Updated dataset and includes the ΔSNOW model regionalisation code. Reported errors: The dataset accidentally contains one station from the Southern Hemisphere (NH-SWE ID 500001), located in Antarctica (Country code AY).  The longitude of a few stations exceeds +180 decimal degrees. To obtain the correct value within the [-180,180] decimal degree longitude bounds, the value exceeding +180 needs to be added to -180 degrees (e.g. +181.0 degrees is actually -179.0 degrees). Swedish stations have two different country codes, SE for the ECA&D stations, and SW for the GHCNd stations.  Japan country code is "JA" in the metadata, although the official country code should be JP.

opencc-by-4.0Mar 2023View details →

Spatial predictions of suitable environments for palsas and peat plateaus in the Northern Hemisphere for recent and future periods

Here we provide raster files of suitable environments for palsas and peat plateaus in the Northern Hemisphere. These files are results of a scientific study by Könönen et al. (2022, preprint). Files are provided in TIFF-format, and they describe the occurrence probability of the suitable environments for palsas and peat plateaus.   Könönen, O. H., Karjalainen, O., Aalto, J., Luoto, M., and Hjort, J.: Environmental spaces for palsas and peat plateaus are disappearing at a circumpolar scale, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2022-135, in review, 2022.

opencc-by-4.0Mar 2023View details →

Northern Hemisphere Lamb Weather Types from historical GCM experiments and various reanalyses

This dataset contains 6-hourly instantaneous discrete Lamb circulation type time series (Lamb 1972) on a 2.5 degrees longitude-latitude grid covering the northern hemisphere extratropics between 30ºN and 70ºN for the period 1979-2005 or longer. These "Lamb catalogues" were calculated upon SLP data from the historical experiments run with 61 distinct GCMs participating in the Coupled Model Intercomparison Project phases 5 and 6, and also from three distinct reanalyses (ERA5 extended to 2020 from version 5 onwards, ERA-Interim and JRA-55). For 13 out of the aforementioned 61 GCMs, 72 additional runs are provided to explore the role of internal model variability. For more information, please refer to the following article: Brands, S.: A circulation-based performance atlas of the CMIP5 and 6 models for regional climate studies in the Northern Hemisphere mid-to-high latitudes, Geosci. Model Dev., 15, 1375–1411, https://doi.org/10.5194/gmd-15-1375-2022, 2022. or contact: brandssf@ifca.unican.es Reference: Lamb, H.: British Isles Weather types and a register of daily sequence of circulation patterns, 1861-1971, Geophysical Memoir, 116, 85pp., HMSO, 1972. CAUTION: When unpacked, this dataset occupies 110 GB of your local disk space. Update information: Version 2 of this archive includes the model_source_attributes.txt file containing the "source" attributes stored in the netCDF files obtained from ESGF. This attribute provides details about the individual component models within the coupled model configurations used in CMIP5 and 6. Version 3 of this archive includes 10 new GCMs, two additional runs for CNRM-CM6-1 and an updated version of model_source_attributes.txt Version 3.1 includes README.txt, which explains the content of the files located in the tar.gz file. Version 4 further includes Lamb Weather Type catalogues for the ERA5 reanalysis and 4 additional GCMs. All files have been compressed individually.  The <model_source_attributes.txt> file is depreciated and no longer updated. It is replaced by the Python function <get_historical_metadata.py> available from https://doi.org/10.5281/zenodo.4555367. This function contains an exhaustive metadata archive of the 60 GCMs considered here. Version 4.1 The LWT catalogue for CMCC-CM2-HR4 is included for consistency with the respective Southern Hemisphere dataset published at https://doi.org/10.5281/zenodo.7612987 Version 5 is a major dataset update featuring the following improvements: 1. The attributes from the netCDF source files "psl...nc" obtained from ESGF were copied into the files available here. These attributes are indicated with the prefix "udata...." (for "underlying data"). 2. All non-standard calenders from the underlying netCDF files from ESGF were converted into standard using the "xarray.Dataset.convert_calendar" function. The original calendar information was stored as additional netCDF attribute. 3. The "patch" method from Python's xesmf module was used to regrid the original psl data from the native GCM grid available from ESGF to the regular lat-lon 2.5° grid common to all applied GCMs and reanalyses. contact: Swen Brands, brandssf@ifca.unican.es   Principal Research Articles, Software and Complementary Datasets Associated with this Dataset Brands, S. (2022). A circulation-based performance atlas of the CMIP5 and 6 models for regional climate studies in the Northern Hemisphere mid-to- high latitudes. Geoscientific Model Development, 15 (4), 1375–1411. doi: https://doi.org/10.5194/gmd-15-1375-2022 Brands, S. (2022). A circulation-based performance atlas of the CMIP5 and 6 mod- els for regional climate studies in the northern hemisphere [data set]. Zenodo. doi: https://doi.org/10.5281/zenodo.4452080 Brands, S. (2022). Common error patterns in the regional atmospheric circulation simulated by the CMIP multi-model ensemble. Geophysical Research Letters, 49 (23), e2022GL101446. doi: https://doi.org/10.1029/2022GL101446 Brands, Swen, Tatebe, Hiroaki, Danek, Christopher, Fernández, Jesús, Swart, Neil C., Volodin, Evgeny, Kim, YoungHo, Collier, Mark, Bi, Dave, & Tongwen, Wu. (2022). Python code to calculate Lamb circulation types derived from historical CMIP simulations and reanalysis data. In Geoscientific Model Development: Vols. gmd-2020-418 (Version 4). Zenodo. https://doi.org/10.5281/zenodo.6390256 Brands, S., Fernández-Granja, J. A., Bedia, J., Casanueva, A., & Fernández, J. (2023). Auxiliary online material to Brands et al. (2023): A global climate model performance atlas for the Southern Hemisphere extratrop- ics based on regional atmospheric circulation patterns. figshare. doi: https://doi.org/10.6084/m9.figshare.22193443.v1 Brands, S., Fernández-Granja, J. A., Bedia, J., Casanueva, A., & Fernández, J. (2023b). Southern Hemisphere Lamb Weather Types from historical GCM experiments and various reanalyses (1.0) [data set]. Zenodo. doi: https://doi.org/10.5281/zenodo.7612988 Brands, S., Tatebe, H., Danek, C., Fernández, J., Swart, N., Volodin, E., . . . Tong- wen, W. (2023). GCM metadata archive get historical metadata.py (v1.1). Zenodo. doi: https://doi.org/10.5281/zenodo.7715383 Fernández-Granja, J. A., Brands, S., Bedia, J., Casanueva, A., & Fernández, J. (2023). Exploring the limits of the Jenkinson–Collison weather types clas- sification scheme: a global assessment based on various reanalyses. Climate Dynamics. doi: 10.1007/s00382-022-06658-7   References of the source GCMs and Early References of the Lamb Weather Typing Method Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., . . . Kristjánsson, J. E. (2013). The Norwegian Earth System Model, NorESM1-M – part 1: Description and basic evaluation of the physical climate. Geoscientific Model Development, 6 (3), 687–720. doi: 10.5194/gmd-6-687-2013 Bi, D., Dix, M., Marsland, S., O’Farrell, S., Sullivan, A., Bodman, R., . . . Heerde- gen, A. (2020). Configuration and spin-up of ACCESS-CM2, the new gener- ation Australian Community Climate and Earth System Simulator Coupled Model. Journal of Southern Hemisphere Earth Systems Science, 70 (1), 225- 251. doi: doi:10.1071/ES19040 Bi, D., Dix, M., Marsland, S. J., O’Farrell, S., Rashid, H., Uotila, P., . . . Puri, K. (2013). The ACCESS coupled model: description, control climate and evaluation. Australian Meteorological and Oceanographic Journal , 63 , 41-64. doi: 0.22499/2.6301.004 Boucher, O., Servonnat, J., Albright, A. L., Aumont, O., Balkanski, Y., Bastrikov, V., . . . Vuichard, N. (2020). Presentation and evaluation of the IPSL-CM6A- LR climate model. Journal of Advances in Modeling Earth Systems, 12 (7), e2019MS002010. doi: 10.1029/2019MS002010 Cao, J., Wang, B., Yang, Y.-M., Ma, L., Li, J., Sun, B., . . . Wu, L. (2018). The NUIST Earth System Model (NESM) version 3: description and prelimi- nary evaluation. Geoscientific Model Development, 11 (7), 2975–2993. doi: 10.5194/gmd-11-2975-2018 Cherchi, A., Fogli, P. G., Lovato, T., Peano, D., Iovino, D., Gualdi, S., . . . Navarra, A. (2019). Global mean climate and main patterns of variability in the CMCC- CM2 coupled model. Journal of Advances in Modeling Earth Systems, 11 (1), 185-209. doi: 10.1029/2018MS001369 Chylek, P., Li, J., Dubey, M. K., Wang, M., & Lesins, G. (2011). Observed and model simulated 20th century arctic temperature variability: Canadian Earth System Model CanESM2. Atmospheric Chemistry and Physics Discussions, 11 , 22893–22907. doi: 10.5194/acpd-11-22893-2011 Collins, W. J., Bellouin, N., Doutriaux-Boucher, M., Gedney, N., Halloran, P., Hinton, T., . . . Woodward, S. (2011). Development and evaluation of an Earth-System model – HadGEM2. Geoscientific Model Development, 4 (4),1051–1075.doi: 10.5194/gmd-4-1051-2011 Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., . . . Vitart, F. (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc., 137 (656, Part a), 553-597. doi: 10.1002/qj.828 Döscher, R., Acosta, M., Alessandri, A., Anthoni, P., Arneth, A., Arsouze, T., . . . Zhang, Q. (2021). The EC-Earth3 Earth System Model for the Coupled Model Intercomparison Project 6. Geoscientific Model Development Discussions, 2021 , 1–90. doi: 10.5194/gmd-2020-446 Dufresne, J.-L., Foujols, M.-A., Denvil, S., Caubel, A., Marti, O., Aumont, O., . . . Vuichard, N. (2013). Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5. Clim. Dyn., 40 (9-10), 2123-2165. doi: 10.1007/s00382-012-1636-1 Dunne, J. P., Horowitz, L. W., Adcroft, A. J., Ginoux, P., Held, I. M., John, J. G., . . . Zhao, M. (2020). The GFDL Earth System Model version 4.1 (GFDL- ESM 4.1): Overall coupled model description and simulation characteristics. Journal of Advances in Modeling Earth Systems, 12 (11), e2019MS002015. doi: https://doi.org/10.1029/2019MS002015 Dunne, J. P., John, J. G., Adcroft, A. J., Griffies, S. M., Hallberg, R. W., Shevli- akova, E., . . . Zadeh, N. (2012). GFDL’s ESM2 Global Coupled Climate- Carbon Earth System Models. 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Half-hourly gap-filled Northern Hemisphere lake and reservoir carbon flux and micrometeorology, 2006 - 2015

This archive accompanies the manuscript New insights into diel to interannual variation in carbon emissions from lakes and reservoirs We synthesize 171 site-months (and 3,832 site-hours) of high-frequency flux measurements to quantify the magnitudes and temporal variability of direct CO2 fluxes from 13 lakes and reservoirs in the Northern Hemisphere (NH). Constraining short- and long-term variability is necessary to improve detection of temporal changes of CO2 fluxes in response to natural and anthropogenic drivers. These data were collected based on a workshop and open call for eddy covariance observations over lakes organized by Ankur Desai (UW-Madison), Timo Vesala (U Helsinki), and Malgorzata Golub (DKIT).

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opencc-zeroSep 2019View details →

FIG. 11. — A in The modern ontological natures of the Cairina moschata (Linnaeus, 1758) duck. Cases from Perú, the northern hemisphere, and digital communities

FIG. 11. — A, logo of D'Artagnan Foods Inc. Image via Wikimedia Commons; B, poster of campaign to stop the expansion of foie gras industry in China (https:// safarus.wordpress.com/2012/03/24/chinese-activists-call-for-boycott-of-the-largest-foie-gras-farm, last consultation: 06/09/2019).

opencc-by-4.0Oct 2024View details →

LegacyVegetation: Northern Hemisphere reconstruction of past plant cover and total tree cover from pollen archives of the last 14 ka

Open the record for dataset details and reuse information.

Fig. 5 in Revised Diagnosis and First Northern Hemisphere Records of the Rare Clingfish Lepadichthys akiko (Gobiesocidae: Diademichthyinae)

Fig. 5. Distributional records of Lepadichthys akiko. Stars and circle indicate records based on collected specimens and underwater photographs, respectively. Closed and open symbols indicate type locality and newly recorded localities, respectively.

Fig. 6 in Revised Diagnosis and First Northern Hemisphere Records of the Rare Clingfish Lepadichthys akiko (Gobiesocidae: Diademichthyinae)

Fig. 6. Preserved specimen of Lepadichthys bolini from Palau (BPBM 9219, 28.1 mm SL). A, lateral view; B, dorsal view; C, ventral view.

Fig. 4 in Revised Diagnosis and First Northern Hemisphere Records of the Rare Clingfish Lepadichthys akiko (Gobiesocidae: Diademichthyinae)

Fig. 4. Underwater photographs of Lepadichthys akiko from Okinawa Island, Japan (A, KPM-NR 73666; B, KPM-NR 176523). Specimens not collected. Photos by Y. Terada.

Fig. 1 in Revised Diagnosis and First Northern Hemisphere Records of the Rare Clingfish Lepadichthys akiko (Gobiesocidae: Diademichthyinae)

Fig. 1. Preserved specimens of Lepadichthys akiko from Palau (A, BPBM 37705, 12.3 mm SL; B–D, BPBM, 37695, 14.0 mm SL). A, B, lateral view; C, dorsal view; D, ventral view.

Fig. 3 in Revised Diagnosis and First Northern Hemisphere Records of the Rare Clingfish Lepadichthys akiko (Gobiesocidae: Diademichthyinae)

Fig. 3. Head sensory canal pores of Lepadichthys akiko, BPBM 37695, 14.0 mm SL. Bar indicates 1.0 mm.