diff --git a/nwm_transform_nc/create_timeseries.py b/nwm_transform_nc/create_timeseries.py
new file mode 100644
index 0000000..007a26d
--- /dev/null
+++ b/nwm_transform_nc/create_timeseries.py
@@ -0,0 +1,1024 @@
+#!/bin/python
+##############################################################################
+#
+#  Originally developed at the
+#  United States Department of Commerce
+#  NOAA (National Oceanic and Atmospheric Administration)
+#  National Weather Service
+#  Office of Water Prediction
+#
+#  Author:
+#      Anders Nilsson, UCAR (created)
+#
+#
+#  Further development by scientists at CIROH,
+#  The Cooperative Institute for Research to Operations in Hydrology
+#
+##############################################################################
+
+"""
+This function generates a single timeseries from a list of files. The
+variable associated with time is an additional argument
+"""
+
+# Global system imports
+from argparse import ArgumentParser
+import logging
+import math
+import os
+from os.path import basename
+import re
+import socket
+import sys
+import time
+import traceback
+
+# Third-party imports
+import numpy
+from netCDF4 import Dataset, num2date, date2num
+
+# Global default constants
+
+__version__ = "1.0"
+
+# Format for logged messages
+DEFAULT_LOG_FORMAT = (
+    "%(asctime)s "
+    + socket.gethostname()
+    + " %(filename)s[%(process)d]: %(levelname)s: %(message)s"
+)
+
+# Format for the dates used in logged messages
+DEFAULT_DATE_FORMAT = "%Y-%m-%d %H:%M:%S %Z"
+
+#  Level of messages that are written to the log
+DEFAULT_LEVEL = logging.INFO
+
+# Global logger instance
+logger = logging.getLogger()
+
+#######################################################################
+#
+#  format_current_exception
+#
+#######################################################################
+
+
+def format_current_exception():
+    """Reformat the current exception into a suitable log message
+
+    This method reformats the current exception message including the
+    stack trace into a one-line message suitable for log files.
+
+    Args:
+        None
+
+    Exceptions:
+        None
+    """
+    # Get current exception information
+    (exception_type, exception_value, exception_traceback) = sys.exc_info()
+
+    # Get traceback entries
+    traceback_entries = traceback.extract_tb(exception_traceback)
+
+    # Construct one-line message
+    message = ""
+    for entry in traceback_entries:
+        message += "%s[%s[line %ld]]: " % (basename(entry[0]), entry[2], entry[1])
+
+    # Replace any newlines in the exception text
+    single_line = re.sub(" *\r?\n *", " : ", str(exception_value))
+
+    # Return created message
+    return message + single_line
+
+
+############################################################################
+#
+#  setup_arguments
+#
+############################################################################
+def setup_arguments():
+    """Configure command line parser
+
+    This method configures the command line argument parser and help message.
+
+    Args:
+        None
+
+    Returns:
+        A namespace containing all set configuration options
+
+    Exceptions:
+        None
+    """
+
+    # Initialize constants
+    program_description = ""
+    epilogue = ""
+
+    # Get command line arguments
+    parser = ArgumentParser(description=program_description, epilog=epilogue)
+
+    # Output file
+    parser.add_argument(
+        "output_file",
+        action="store",
+        type=str,
+        help="Output file that contains the time series",
+    )
+
+    # Input files
+    parser.add_argument(
+        "input_files",
+        metavar="INPUT",
+        type=str,
+        nargs="+",
+        help="Input files, with the first entry used as a " "template",
+    )
+
+    # Data variable(s)
+    parser.add_argument(
+        "-d",
+        "--data_variable",
+        dest="data_variables",
+        action="append",
+        type=str,
+        help="Specify a variable to concatenate by time. "
+        "May be specified more than once.",
+        metavar="VARIABLE",
+    )
+
+    # Time variable option
+    parser.add_argument(
+        "-t",
+        "--time_variable",
+        dest="time_variable",
+        action="store",
+        type=str,
+        default="time",
+        help="Specify the name of the time " 'variable, otherwise defaults to "time"',
+        metavar="VARIABLE",
+    )
+
+    # Reference time variable
+    parser.add_argument(
+        "-r",
+        "--reference_time_variable",
+        dest="reference_time_variable",
+        action="store",
+        type=str,
+        default="reference_time",
+        help="Specify the name of the reference time variable,"
+        ' otherwise defaults to "reference_time"',
+        metavar="VARIABLE",
+    )
+
+    # Skip files with missing variables option
+    parser.add_argument(
+        "-sm",
+        "--skip_missing",
+        dest="skip_missing",
+        action="store_true",
+        default=False,
+        help="Skip input files that are missing required "
+        "variables. Default is to error and stop if "
+        "one is missing.",
+    )
+
+    # Global attributes to delete
+    parser.add_argument(
+        "-g",
+        "--global_delete",
+        dest="removed_global_attributes",
+        action="append",
+        type=str,
+        help="Specify a global attribute that will not be "
+        "copied to the output file. May be specified "
+        "more than once.",
+        metavar="ATTRIBUTE",
+    )
+
+    # Chunk size
+    parser.add_argument(
+        "-c",
+        "--chunk_size",
+        dest="chunk_size",
+        action="store",
+        type=int,
+        default=5120,
+        help="Specify the number of rows within a chunk" ". Defaults to 5120.",
+        metavar="ROWS",
+    )
+    # Max memory in bytes
+    parser.add_argument(
+        "-m",
+        "--max_memory",
+        dest="max_memory",
+        action="store",
+        type=int,
+        default=1e9,
+        help="Specify the approximate maximum memory used "
+        "(in bytes). Defaults to 1GB (1e9)",
+        metavar="BYTES",
+    )
+
+    # Get version information
+    parser.add_argument(
+        "--version",
+        action="version",
+        version="%(prog)s " + str(__version__),
+        help="Display version number",
+    )
+
+    # Log message filtering by level
+    parser.add_argument(
+        "-v",
+        "--verbose",
+        action="store_true",
+        dest="verbose",
+        help="Display all info messages",
+    )
+
+    parser.add_argument(
+        "-q",
+        "--quiet",
+        action="store_true",
+        dest="quiet",
+        help="Display only error messages",
+    )
+
+    # Additional logging options
+    parser.add_argument(
+        "-s",
+        "--syslog",
+        dest="log_facility",
+        action="store",
+        type=str,
+        help="Route logging messages to syslog facility " "FACILITY",
+        metavar="FACILITY",
+    )
+    parser.add_argument(
+        "-l",
+        "--log",
+        dest="log_file",
+        action="store",
+        type=str,
+        help="Route logging messages to log file LOGFILE",
+        metavar="LOGFILE",
+    )
+
+    # This can exit if the help option is requested
+    return parser.parse_args()
+
+
+############################################################################
+#
+#  init_logging
+#
+############################################################################
+def init_logging():
+    """Initialize logging setup
+
+    This method intializes logging for the program.
+
+    Args:
+        None
+
+    Returns:
+        None
+
+    Exceptions:
+        None
+    """
+    # Set up logging
+    logging.basicConfig(format=DEFAULT_LOG_FORMAT, datefmt=DEFAULT_DATE_FORMAT)
+
+
+############################################################################
+#
+#  set_logging_options
+#
+############################################################################
+def set_logging_options(options):
+    """Set logging options
+
+    This method toggles any logging options set from the command line.
+
+    Args:
+        options (namespace argparse return) A namespace containing set
+            variables from the command line. This is returned from the
+            parse_args() method.
+
+    Returns:
+        None
+
+    Exceptions:
+        None
+    """
+
+    # Verbose logging?
+    if options.verbose:
+        log_level = logging.DEBUG
+    elif options.quiet:
+        log_level = logging.WARNING
+    else:
+        log_level = DEFAULT_LEVEL
+
+    logger.setLevel(log_level)
+
+    # Set up other logging destinations
+    formatter = logging.Formatter(DEFAULT_LOG_FORMAT, datefmt=DEFAULT_DATE_FORMAT)
+
+    if options.log_facility:
+        syshandler = logging.handlers.SysLogHandler(facility=options.log_facility)
+        syshandler.setFormatter(formatter)
+        logger.addHandler(syshandler)
+    if options.log_file:
+        filehandler = logging.FileHandler(options.log_file)
+        filehandler.setFormatter(formatter)
+        logger.addHandler(filehandler)
+
+
+############################################################################
+#
+#  Validate common dimensions
+#
+############################################################################
+def validate_common_dimensions(input_files, skip_missing):
+    """Ensure common dimensions among input files.
+
+    This routine ensures that within the given list of input files, the
+    dimensions match.
+
+    Args:
+        input_files (list of strings): A list of input NetCDF files
+        skip_missing (Boolean): Whether or not to skip files that
+            have the wrong dimensions, or just error
+
+    Returns:
+        A list of validated input NetCDF file paths
+
+    Exceptions:
+        ValueError if any of the dimensions do not match
+    """
+
+    logger.info("Validating common dimensions")
+    new_input_files = []
+
+    # Adding file test for clearer error messages
+    if not os.path.isfile(input_files[0]):
+        raise ValueError("Input file %s does not exist" % input_files[0])
+
+    with Dataset(input_files[0], "r") as archetype:
+        archetype_list = archetype.dimensions
+
+        for filename in input_files:
+
+            try:
+                # Adding file test for clearer error messages
+                if not os.path.isfile(filename):
+                    raise ValueError("Input file %s does not exist" % filename)
+
+                with Dataset(filename, "r") as input_file:
+                    other_dimensions = input_file.dimensions
+
+                    # Compare dimensions between the two files
+                    for dimension_name in archetype_list.keys():
+
+                        if (dimension_name not in other_dimensions) or (
+                            len(archetype_list[dimension_name])
+                            != len(other_dimensions[dimension_name])
+                        ):
+                            raise ValueError(
+                                "The NetCDF file {0} does not "
+                                "have the same dimensions as {1} "
+                                "({2}).".format(
+                                    filename, input_files[0], dimension_name
+                                )
+                            )
+                        # Otherwise, dimension present and matches
+
+                # Input file is good
+                new_input_files.append(filename)
+
+            except BaseException:
+                if skip_missing:
+                    # Display error and continue
+                    logger.error(format_current_exception())
+                else:
+                    # Error
+                    raise
+
+    # Update input list if necessary
+    if len(input_files) != len(new_input_files):
+        logger.info(
+            "Updating input file list with %d subtraction(s)",
+            len(input_files) - len(new_input_files),
+        )
+        input_files = new_input_files
+
+    logger.info("Done validating common dimensions")
+    return input_files
+
+
+############################################################################
+#
+#  Validate variables
+#
+############################################################################
+def validate_variables(input_files, variable_names, skip_missing):
+    """Ensure specified variables present among input files.
+
+    This routine ensures that the input files have all specified variables
+    present.
+
+    Args:
+        input_files (list of strings): A list of input NetCDF files
+        variable_names (list of strings): A list of variable names
+        skip_missing (Boolean): Whether or not to skip files that are
+            missing a variable. When this is True, a file that is missing
+            the specified variable(s) will be removed from the input file
+            list.
+
+    Returns:
+        A list of validated input NetCDF file paths
+
+    Exceptions:
+        ValueError if skip_missing is False and a file is missing a
+            specified variable
+    """
+
+    # Initialize
+    logger.info("Validating variable presence")
+    new_input_files = []
+
+    for filename in input_files:
+
+        try:
+            # Adding file test for clearer error messages
+            if not os.path.isfile(filename):
+                raise ValueError("Input file %s does not exist" % filename)
+
+            with Dataset(filename, "r") as input_file:
+
+                for variable_name in variable_names:
+                    if variable_name not in input_file.variables:
+                        raise ValueError(
+                            "Variable {0} not present in "
+                            "{1}".format(variable_name, filename)
+                        )
+
+            # Input file is good
+            new_input_files.append(filename)
+
+        except BaseException:
+            if skip_missing:
+                # Display error and continue
+                logger.error(format_current_exception())
+            else:
+                # Error
+                raise
+
+    # Update input list if necessary
+    if len(input_files) != len(new_input_files):
+        logger.info(
+            "Updating input file list with %d subtraction(s)",
+            len(input_files) - len(new_input_files),
+        )
+        input_files = new_input_files
+
+    logger.info("Done validating variable presence")
+    return input_files
+
+
+############################################################################
+#
+#  Copy dimensions
+#
+###########################################################################
+def copy_dimensions(input_file, output_file, dimension_names, new_size):
+    """Copy dimensions from one NetCDF file to another
+
+    This routine copies dimensions from one NetCDF file to another, with
+    the exception that any time dimensions are set to a specified number.
+
+    Args:
+        input_file (netCDF namespace Dataset): NetCDF file opened for reading
+        output_file (netCDF namespace Dataset): NetCDF file opened for writing
+        dimension_names (list of strings): A list of dimensions whose lengths
+            will be set to a new size instead of copying the original value.
+        new_size (integer): The new length of the specified dimensions
+
+    Returns:
+        None
+
+    Exceptions:
+        None
+    """
+
+    for (dimension_name, dimension) in input_file.dimensions.items():
+        if dimension_name in dimension_names:
+            dimension_length = new_size
+        elif dimension.isunlimited():
+            dimension_length = None
+        else:
+            dimension_length = len(dimension)
+
+        output_file.createDimension(dimension_name, dimension_length)
+
+
+###########################################################################
+#
+#  Copy variable attributes
+#
+##########################################################################
+def copy_attributes(input_variable, output_variable, removed_attributes=None):
+    """Copy attributes from one variable to another
+
+    This method creates a dictionary of attributes for greater python
+    version compatibility. This can also work on root Datasets, copying the
+    global attributes.
+
+    Args:
+        input_variable (netCDF namespace variable): variable to copy from
+        output_variable (netCDF namespace variable): variable to copy to
+        removed_attributes (list of strings): A list of attribute names to
+            not copy to the new variable.
+    Returns:
+        None
+
+    Exceptions:
+        None
+    """
+
+    new_attributes = {}
+
+    for key in input_variable.ncattrs():
+        # Filter out unwanted attributes
+        if not removed_attributes or key not in removed_attributes:
+            new_attributes[key] = input_variable.getncattr(key)
+
+    output_variable.setncatts(new_attributes)
+
+
+############################################################################
+#
+#  Copy coordinate variables
+#
+############################################################################
+def copy_coordinate_variables(input_file, output_file, excluded_variables):
+    """Copy coordinate variables from one NetCDF file to another
+
+    This routine copies coordinate variables from one NetCDF file to another,
+    excluding any on a specified list.
+
+    Args:
+        input_file (netCDF namespace Dataset): NetCDF file opened for reading
+        output_file (netCDF namespace Dataset): NetCDF file opened for writing
+        excluded_variables (list of strings): A list of coordinate variable
+            names that will not be copied over to the new NetCDF file.
+
+    Returns:
+        None
+
+    Exceptions:
+        None
+    """
+
+    all_variables = set(input_file.variables)
+    all_dimensions = set(input_file.dimensions)
+    # Coordinate variables are variables that have dimensions with the same
+    # name
+    coordinate_variables = all_variables & all_dimensions
+
+    # Skip specified variables
+    for excluded_variable in excluded_variables:
+        if excluded_variable in coordinate_variables:
+            coordinate_variables.remove(excluded_variable)
+
+    for variable_name in coordinate_variables:
+        logger.info("Creating coordinate variable %s", variable_name)
+        coordinate = input_file.variables[variable_name]
+
+        # Create the new variable. Enabling compression with default chunk size
+        output_coordinate = output_file.createVariable(
+            variable_name,
+            coordinate.dtype,
+            (variable_name,),
+            zlib=True,
+            complevel=4,
+            shuffle=True,
+        )
+
+        # Copy any attributes
+        copy_attributes(coordinate, output_coordinate)
+
+        # Copy any values
+        output_coordinate[:] = coordinate[:]
+
+
+########################################################################
+#
+#  create processing chunk ranges
+#
+#######################################################################
+def create_processing_chunks(number_files, number_rows, chunk_rows, max_memory):
+    """Create a list of processing ranges
+
+    This divides up the primary dimension into processing ranges in
+    order to conserve memory, where each range is either a multiple of the
+    output chunk size, or the entire file.
+
+    Args:
+        number_files (integer): The number of files that are being used,
+        number_rows (integer): The size of the input primary data dimension
+        chunk_rows (integer): The number of rows in each netCDF file chunk
+        max_memory (integer): The approximage maximum number of bytes of
+            memory that the function should use.
+
+    Returns:
+        A list of ranges that span the specified number of rows
+
+    Exceptions:
+        None
+    """
+
+    # Initialize
+    processing_chunks = []
+    previous_row = 0
+
+    # This is a best guess on function internals after folowing function
+    # behavior with "top".
+    bytes_per_value = 8 * 5
+
+    # Want processing chunk rows to be multiples of file storage chunk rows,
+    # if possible.
+    batch_rows = min(
+        int(
+            math.ceil(
+                min(max_memory, float(number_rows) * number_files * bytes_per_value)
+                / (bytes_per_value * number_files)
+                / chunk_rows
+            )
+        )
+        * chunk_rows,
+        number_rows,
+    )
+
+    # Have to make sure is not one single row (range does not like step 0)
+    if batch_rows != 0:
+        for row in range(batch_rows, number_rows - 1, batch_rows):
+            processing_chunks.append([previous_row, previous_row + batch_rows])
+            previous_row = row
+
+    processing_chunks.append([previous_row, number_rows])
+
+    return processing_chunks
+
+
+############################################################################
+#
+#  create time series variable
+#
+############################################################################
+def create_time_series_variable(
+    input_file,
+    output_file,
+    variable_name,
+    time_variable,
+    reference_time_variable,
+    input_filepaths,
+    chunk_rows,
+    max_memory,
+):
+    """Initialize the output time series variable
+
+    This routine initializes the output time series variable with attributes,
+    dimensions, and chunking information copied from the input file.
+
+    Args:
+        input_file (netCDF namespace Dataset): NetCDF file opened for reading
+        output_file (netCDF namespace Dataset): NetCDF file opened for writing
+        variable_name (string): The name of the time series data variable
+        time_variable (string): The name of the time variable
+        reference_time_variable (string): The name of the reference time
+            variable
+        input_file_paths (list of strings): A list of input NetCDF files
+        chunk_rows (integer): The number of rows that span a chunk
+        max_memory (integer): The approximate maximum number of bytes of
+            memory that the function should use.
+
+    Returns:
+        None
+
+    Exceptions:
+        ValueError if the variable does not exist in the input file
+    """
+
+    logger.info("Creating variable %s", variable_name)
+
+    # Copy variable metadata
+    variable = input_file.variables[variable_name]
+
+    if variable_name in [time_variable, reference_time_variable]:
+        # Time variables
+        new_variable_dimensions = variable.dimensions
+    else:
+        new_variable_dimensions = variable.dimensions + (time_variable,)
+
+    # Set chunking information
+    chunk_size = [chunk_rows] * (len(new_variable_dimensions) - 1)
+    chunk_size.append(len(input_filepaths))
+
+    output_variable = output_file.createVariable(
+        variable_name,
+        variable.dtype,
+        new_variable_dimensions,
+        chunksizes=chunk_size,
+        zlib=True,
+        complevel=4,
+        shuffle=True,
+    )
+
+    # Copy variable attributes
+    copy_attributes(variable, output_variable)
+
+    # Load variable arrays
+    variable_arrays = []
+
+    # Calculate processing chunk list
+    processing_chunks = create_processing_chunks(
+        len(input_filepaths),
+        len(input_file.dimensions[variable.dimensions[0]]),
+        chunk_rows,
+        max_memory,
+    )
+
+    # Time data may have to be adjusted as the reference date and
+    # units might not match the primary input file (archetype).
+    # Fortunately, the date2num and num2date functions take care
+    # of this.
+    if variable_name in [time_variable, reference_time_variable]:
+
+        for input_data_file in input_filepaths:
+            with Dataset(input_data_file, "r") as data_frame:
+
+                # Note that date2num outputs double types, so there may be
+                # rounding issues
+                variable_arrays.append(
+                    date2num(
+                        num2date(
+                            data_frame.variables[variable_name][:],
+                            data_frame.variables[variable_name].units,
+                        ),
+                        input_file.variables[variable_name].units,
+                    )
+                )
+
+        logger.info("Restacking variable %s", variable_name)
+
+        if str(output_variable.dtype).startswith("int"):
+            # Have to make sure any double type date output is correctly
+            # rounded to any integer type. The default behavior is to truncate
+            # any precision.
+            output_variable[:] = numpy.rint(numpy.column_stack(variable_arrays))
+        else:
+            output_variable[:] = numpy.column_stack(variable_arrays)
+
+        # Flush contents
+        output_file.sync()
+
+    else:
+
+        # Loop through chunks in order to minimize memory footprints
+        logger.info(
+            "Restacking %s using %d processing chunks",
+            variable_name,
+            len(processing_chunks),
+        )
+
+        for chunk_range in processing_chunks:
+
+            variable_arrays = []
+
+            for input_data_file in input_filepaths:
+                # This repeated reopening/reclosing of the files is not
+                # optimal, performance-wise. Could be threaded?
+                with Dataset(input_data_file, "r") as data_frame:
+
+                    # Double check variable existence
+                    if variable_name not in data_frame.variables:
+                        raise ValueError(
+                            "Variable {0} not present in "
+                            "{1}".format(variable_name, input_data_file)
+                        )
+
+                    # Regular variable, no conversion needed
+                    # At the moment, input variable is assumed to be one dimensional
+                    variable_arrays.append(
+                        data_frame.variables[variable_name][
+                            chunk_range[0] : chunk_range[1]
+                        ]
+                    )
+
+            output_variable[chunk_range[0] : chunk_range[1], :] = numpy.column_stack(
+                variable_arrays
+            )
+
+            # Flush contents
+            output_file.sync()
+
+    logger.info("Done restacking variable %s", variable_name)
+
+
+############################################################################
+#
+#  Create time series
+#
+############################################################################
+def create_time_series(
+    input_filepaths,
+    output_filepath,
+    data_variables,
+    time_variable,
+    reference_time_variable,
+    chunk_length,
+    max_memory,
+    removed_global_attributes,
+    skip_missing,
+):
+    """Create a time series out of NetCDF files
+
+    This concatenates a list of NetCDF files into one time series.
+
+    Args:
+        input_filepaths (list of strings): A list of input file paths to
+             concatenates. The first file will be used a as a template to
+             create the output file.
+        output_filepath (string): The filepath of the output file that will
+             be created.
+        data_variables (list of strings): A list containing the variable(s)
+             to concatenate into a time series.
+        time_variable (string): The name of the time variable to use
+        reference_time_variables (string): The name of the reference time
+             variable to use.
+        chunk_length (integer): The number of rows that a chunk will span
+        max_memory (integer): The approximate maximum number of bytes of
+            memory that the function should use.
+        removed_global_attributes (list of strings): A list of global
+            attribute names that will not be copied to the output file
+        skip_missing (Boolean): Whether or not to skip input files that
+            are missing variables
+
+    Returns:
+        None
+
+    Exceptions:
+        None
+    """
+    all_variables = []
+    [all_variables.append(v) for v in data_variables]
+
+    # Also add time and reference time variables, if specified
+    if time_variable:
+        all_variables.append(time_variable)
+    if reference_time_variable:
+        all_variables.append(reference_time_variable)
+
+    # Cleanup flags
+    remove_output = False
+
+    try:
+        # Validate input files
+        input_filepaths = validate_variables(
+            input_filepaths,
+            all_variables,
+            skip_missing,
+        )
+        input_filepaths = validate_common_dimensions(input_filepaths, skip_missing)
+
+        # Open output file
+        with Dataset(
+            output_filepath, "w", clobber=True, format="NETCDF4"
+        ) as output_file:
+            remove_output = True
+            logger.info("Creating %s", output_filepath)
+
+            # Copy base information from the first entry (archetype)
+            with Dataset(input_filepaths[0], "r") as archetype:
+
+                # Copy dimensions from the archetype
+                copy_dimensions(
+                    archetype,
+                    output_file,
+                    [time_variable, reference_time_variable],
+                    len(input_filepaths),
+                )
+
+                # Copy coordinate variables from the archetype
+                # (excluding time-related ones)
+                copy_coordinate_variables(
+                    archetype, output_file, [time_variable, reference_time_variable]
+                )
+
+                # Copy global attributes from the archetype
+                copy_attributes(archetype, output_file, removed_global_attributes)
+
+                # Loop through specified variables
+                for variable in all_variables:
+
+                    # Create and fill variable
+                    create_time_series_variable(
+                        archetype,
+                        output_file,
+                        variable,
+                        time_variable,
+                        reference_time_variable,
+                        input_filepaths,
+                        chunk_length,
+                        max_memory,
+                    )
+
+        # Success
+        remove_output = False
+
+    except BaseException:
+
+        # Cleanup
+        if remove_output:
+            os.remove(output_filepath)
+
+        raise
+
+
+############################################################################
+#
+#  "Main"
+#
+############################################################################
+def main():
+    """Main
+
+    This program attempts to concatenate several NetCDF files containing one
+    dimensional variables for a given time into file containing a two
+    dimensional time series.
+
+    Args:
+        None (see setup_arguments for command line arguments)
+
+    Returns:
+        None
+
+    Exceptions:
+        None
+    """
+
+    try:
+        # Set up logging
+        init_logging()
+
+        # Get command line arguments
+        # This can raise SystemExit if the help option is requested
+        options = setup_arguments()
+
+        # Further configure logging
+        set_logging_options(options)
+
+        # Do work
+        create_time_series(
+            options.input_files,
+            options.output_file,
+            options.data_variables,
+            options.time_variable,
+            options.reference_time_variable,
+            options.chunk_size,
+            options.max_memory,
+            options.removed_global_attributes,
+            options.skip_missing,
+        )
+
+        # Terminate logging interface. This might be automatic
+        logging.shutdown()
+
+        # Success
+        return
+
+    except SystemExit:
+        return
+    except BaseException:
+
+        # Log any exception message
+        logger.error(format_current_exception())
+
+        # Terminate logging interface. This might be automatic
+        logging.shutdown()
+
+        # Failure
+        sys.exit(1)
+
+
+# Is this main?
+if __name__ == "__main__":
+    main()
diff --git a/nwm_transform_nc/gettest.wgetlist.sh b/nwm_transform_nc/gettest.wgetlist.sh
new file mode 100644
index 0000000..d5ec864
--- /dev/null
+++ b/nwm_transform_nc/gettest.wgetlist.sh
@@ -0,0 +1,5 @@
+# tip from here: https://askubuntu.com/questions/214018/how-to-make-wget-faster-or-multithreading
+# https://stackoverflow.com/questions/7577615/parallel-wget-in-bash
+# and here: https://github.com/axel-download-accelerator/axel/issues/168
+cat gettest.wgetlist.txt | xargs -n 1 -P 8 wget -P data -c
+cat gettest.wgetlist_medium.txt | xargs -n 1 -P 8 wget -P data -c
diff --git a/nwm_transform_nc/gettest.wgetlist.txt b/nwm_transform_nc/gettest.wgetlist.txt
new file mode 100644
index 0000000..c2b81c2
--- /dev/null
+++ b/nwm_transform_nc/gettest.wgetlist.txt
@@ -0,0 +1,54 @@
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f001.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f002.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f003.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f004.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f005.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f006.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f007.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f008.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f009.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f010.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f011.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f012.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f013.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f014.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f015.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f016.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f017.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220823/short_range/nwm.t12z.short_range.channel_rt.f018.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f001.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f002.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f003.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f004.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f005.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f006.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f007.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f008.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f009.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f010.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f011.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f012.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f013.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f014.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f015.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f016.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f017.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t00z.short_range.channel_rt.f018.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f001.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f002.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f003.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f004.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f005.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f006.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f007.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f008.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f009.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f010.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f011.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f012.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f013.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f014.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f015.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f016.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f017.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/short_range/nwm.t12z.short_range.channel_rt.f018.conus.nc
diff --git a/nwm_transform_nc/gettest.wgetlist_medium.txt b/nwm_transform_nc/gettest.wgetlist_medium.txt
new file mode 100644
index 0000000..f6a4be7
--- /dev/null
+++ b/nwm_transform_nc/gettest.wgetlist_medium.txt
@@ -0,0 +1,240 @@
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f001.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f002.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f003.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f004.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f005.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f006.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f007.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f008.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f009.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f010.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f011.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f012.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f013.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f014.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f015.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f016.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f017.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f018.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f019.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f020.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f021.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f022.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f023.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f024.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f025.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f026.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f027.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f028.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f029.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f030.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f031.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f032.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f033.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f034.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f035.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f036.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f037.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f038.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f039.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f040.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f041.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f042.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f043.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f044.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f045.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f046.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f047.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f048.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f049.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f050.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f051.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f052.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f053.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f054.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f055.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f056.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f057.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f058.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f059.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f060.conus.nc
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+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f207.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f208.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f209.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f210.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f211.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f212.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f213.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f214.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f215.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f216.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f217.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f218.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f219.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f220.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f221.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f222.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f223.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f224.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f225.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f226.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f227.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f228.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f229.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f230.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f231.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f232.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f233.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f234.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f235.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f236.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f237.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f238.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f239.conus.nc
+https://storage.googleapis.com/national-water-model/nwm.20220824/medium_range_mem1/nwm.t12z.medium_range.channel_rt_1.f240.conus.nc
diff --git a/nwm_transform_nc/test_create_timeseries.py b/nwm_transform_nc/test_create_timeseries.py
new file mode 100644
index 0000000..f5ab5d1
--- /dev/null
+++ b/nwm_transform_nc/test_create_timeseries.py
@@ -0,0 +1,322 @@
+from create_timeseries import create_time_series
+import time
+
+logfile = "log_short_range_test.txt"
+output_file = "nwm.t12z.short_range.channel_rt.conus.nc"
+data_variables = ["streamflow"]
+chunk_size = 5120
+max_memory = 1e9
+time_variable = "time"
+reference_time_variable = "reference_time"
+removed_global_attributes = ""
+skip_missing = False
+
+start_time = time.time()
+print("running short_range files")
+input_files_short_range = [
+    "data/nwm.t12z.short_range.channel_rt.f001.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f002.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f003.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f004.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f005.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f006.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f007.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f008.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f009.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f010.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f011.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f012.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f013.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f014.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f015.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f016.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f017.conus.nc",
+    "data/nwm.t12z.short_range.channel_rt.f018.conus.nc",
+]
+
+output = create_time_series(
+    input_files_short_range,
+    output_file,
+    data_variables,
+    time_variable,
+    reference_time_variable,
+    chunk_size,
+    max_memory,
+    removed_global_attributes,
+    skip_missing,
+)
+print(time.time() - start_time)
+
+"""
+The same behavior can be obtained with this commandline call:
+python create_timeseries.py -l log.txt nwm.t12z.short_range.channel_rt.conus.nc data/nwm.t12z.short_range.channel_rt.f001.conus.nc data/nwm.t12z.short_range.channel_rt.f002.conus.nc data/nwm.t12z.short_range.channel_rt.f003.conus.nc data/nwm.t12z.short_range.channel_rt.f004.conus.nc data/nwm.t12z.short_range.channel_rt.f005.conus.nc data/nwm.t12z.short_range.channel_rt.f006.conus.nc data/nwm.t12z.short_range.channel_rt.f007.conus.nc data/nwm.t12z.short_range.channel_rt.f008.conus.nc data/nwm.t12z.short_range.channel_rt.f009.conus.nc data/nwm.t12z.short_range.channel_rt.f010.conus.nc data/nwm.t12z.short_range.channel_rt.f011.conus.nc data/nwm.t12z.short_range.channel_rt.f012.conus.nc data/nwm.t12z.short_range.channel_rt.f013.conus.nc data/nwm.t12z.short_range.channel_rt.f014.conus.nc data/nwm.t12z.short_range.channel_rt.f015.conus.nc data/nwm.t12z.short_range.channel_rt.f016.conus.nc data/nwm.t12z.short_range.channel_rt.f017.conus.nc data/nwm.t12z.short_range.channel_rt.f018.conus.nc
+"""
+
+
+start_time = time.time()
+print("running medium_range files")
+logfile = "log_medium_range_test.txt"
+output_file = "nwm.t12z.medium_range.channel_rt.conus.nc"
+data_variables = ["streamflow"]
+chunk_size = 72000
+max_memory = 1e10
+time_variable = "time"
+reference_time_variable = "reference_time"
+removed_global_attributes = ""
+skip_missing = False
+
+input_files_medium_range = [
+    "data/nwm.t12z.medium_range.channel_rt_1.f001.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f002.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f003.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f004.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f005.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f006.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f007.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f008.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f009.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f010.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f011.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f012.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f013.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f014.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f015.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f016.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f017.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f018.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f019.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f020.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f021.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f022.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f023.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f024.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f025.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f026.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f027.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f028.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f029.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f030.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f031.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f032.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f033.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f034.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f035.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f036.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f037.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f038.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f039.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f040.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f041.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f042.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f043.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f044.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f045.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f046.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f047.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f048.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f049.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f050.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f051.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f052.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f053.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f054.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f055.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f056.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f057.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f058.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f059.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f060.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f061.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f062.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f063.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f064.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f065.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f066.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f067.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f068.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f069.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f070.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f071.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f072.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f073.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f074.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f075.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f076.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f077.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f078.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f079.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f080.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f081.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f082.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f083.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f084.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f085.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f086.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f087.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f088.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f089.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f090.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f091.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f092.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f093.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f094.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f095.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f096.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f097.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f098.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f099.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f100.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f101.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f102.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f103.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f104.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f105.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f106.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f107.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f108.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f109.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f110.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f111.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f112.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f113.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f114.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f115.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f116.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f117.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f118.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f119.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f120.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f121.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f122.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f123.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f124.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f125.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f126.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f127.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f128.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f129.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f130.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f131.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f132.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f133.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f134.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f135.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f136.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f137.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f138.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f139.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f140.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f141.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f142.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f143.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f144.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f145.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f146.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f147.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f148.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f149.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f150.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f151.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f152.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f153.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f154.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f155.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f156.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f157.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f158.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f159.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f160.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f161.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f162.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f163.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f164.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f165.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f166.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f167.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f168.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f169.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f170.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f171.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f172.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f173.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f174.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f175.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f176.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f177.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f178.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f179.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f180.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f181.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f182.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f183.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f184.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f185.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f186.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f187.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f188.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f189.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f190.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f191.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f192.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f193.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f194.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f195.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f196.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f197.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f198.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f199.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f200.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f201.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f202.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f203.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f204.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f205.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f206.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f207.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f208.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f209.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f210.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f211.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f212.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f213.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f214.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f215.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f216.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f217.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f218.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f219.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f220.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f221.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f222.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f223.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f224.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f225.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f226.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f227.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f228.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f229.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f230.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f231.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f232.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f233.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f234.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f235.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f236.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f237.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f238.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f239.conus.nc",
+    "data/nwm.t12z.medium_range.channel_rt_1.f240.conus.nc",
+]
+
+output = create_time_series(
+    input_files_medium_range,
+    output_file,
+    data_variables,
+    time_variable,
+    reference_time_variable,
+    chunk_size,
+    max_memory,
+    removed_global_attributes,
+    skip_missing,
+)
+print(time.time() - start_time)