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Dataset

 

Microbiology-Ocean-Cloud Coupling in the High Arctic (MOCCHA): Met Office Unified Model data and associated Cloudnet outputs (UM_CASIM-100_Cloudnet)

Update Frequency: Not Planned
Latest Data Update: 2023-02-09
Status: Ongoing
Online Status: ONLINE
Publication State: Citable
Publication Date: 2023-03-07
DOI Publication Date: 2023-03-07
Download Stats: last 12 months
Dataset Size: 126 Files | 23MB

Abstract

Met Office Unified Model single-site (Oden) output during MOCCHA. These model and observation data are used in McCusker et al. : Evaluating Arctic clouds modelled with the Unified Model and Integrated Forecasting System, Atmospheric Chemistry and Physics, 2023.

Model data from the Met Office Unified Model are in directory 'um_model_data/'. Data are hourly data taken from grid box closest to ship location. Where the ship covers more than one grid box within an hour period, data are averaged from all grid boxes crossed. All data files are in a netCDF format, with one file per day. Rose suite ID: u-cc278. Model options include:
Unified Model version - 11.3,
CASIM microphysics + cloud scheme (i_cld_vn = 1).
Double-moment cloud microphysics - droplet activation = Abdul-Razzak and Ghan (2000); ice nucleation = Cooper (1986).
3 modes of soluble aerosol, no insoluble aerosol.
Accumulation mode soluble aerosol - num = 1.00e8 /m3, mass = 1.50e-9 kg/kg.
Aitken and coarse modes = 0.
No aerosol processing.
Updated RHcrit profile used in Unified Model vn11.4.
Uses sea ice options from the global model (alpham = 0.72, dtice = 2.0).
U and V wind components interpolated on to common vertical grid.

Model data from directory um_model_data/ are subsequently passed through the Cloudnet algorithm to produce calibrated model data that may be used for direct comparisons with observations. Cloudnet combines cloud radar, ceilometer, microwave radiometer, and radiosonde profiles averaged to a common grid at the cloud radar resolution to derive a set of retrieved cloud properties. The Cloudnet products are designed to be used for evaluation of weather forecast models as well as fundamental process studies of cloud. From a modelling perspective, Cloudnet converts liquid and ice mass mixing ratios to the respective cloud water contents for direct comparison with observations, as well as filtering ice water contents for values that would be unobservable by radar. Note that the latitude/longitude relevant for each date in question can be found in these Cloudnet files.

In directories:
iwc-Z-T-metum-grid/ - data include ice water content and total ice water path for observations and model.
lwc-scaled-metum-grid/ - data include cloud liquid water content and liquid water path for observations and model.
cloud-fraction-metum-grid/ - data include cloud fractions by volume for observations and model.

Citable as:  McCusker, G.; Vuellers, J. (2023): Microbiology-Ocean-Cloud Coupling in the High Arctic (MOCCHA): Met Office Unified Model data and associated Cloudnet outputs (UM_CASIM-100_Cloudnet). NERC EDS Centre for Environmental Data Analysis, 07 March 2023. doi:10.5285/ebc32b4b3e3d4e1788bbdd66b6abb5de. https://dx.doi.org/10.5285/ebc32b4b3e3d4e1788bbdd66b6abb5de
Abbreviation: Not defined
Keywords: MOCCHA, Met Office, Unified Model, Cloudnet, Oden, cloud microphysics, aerosol

Details

Previous Info:
No news update for this record
Previously used record identifiers:
No related previous identifiers.
Access rules:
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence(s):
https://artefacts.ceda.ac.uk/licences/missing_licence.pdf
When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

Model data were generated using the Met Office Unified Model (UM) at 1.5km horizontal resolution over a 500x500 domain centred on 86.625N, 30E. Data has been converted to netCDF by Gillian Young McCusker (G.Y.McCusker@leeds.ac.uk) using Python (Iris/netCDF4), then passed on to the CEDA for long-term archiving. Cloudnet data were generated by Jutta Vuellers (j.vuellers@leeds.ac.uk).

Data Quality:
Data quality were checked by the MOCCHA project data authors before supplying to CEDA. Further information on quality may be available in related documentation. No quality control has been performed by the Centre for Environmental Data Analysis (CEDA)
File Format:
Data are netCDF formatted

Process overview

This dataset was generated by the computation detailed below.
Title

Met Office operational Unified Model (UM) deployed on the Monsoon2 system, a collaborative facility supplied under the Joint Weather and Climate Research Programme - a strategic partnership between the Met Office and the Natural Environment Research Council. This work also used JASMIN, the UK collaborative data analysis facility, to post-process model data.

Abstract

Input Description

None

Output Description

None

Software Reference

None

  • units: m2 s-1
  • var_id: BL_momentum_diffusion
  • long_name: BL_momentum_diffusion
  • units: m
  • var_id: height
  • long_name: Height above mean sea level
  • units: m
  • var_id: altitude
  • long_name: Height of lidar above mean sea level
  • units: degrees_north
  • var_id: latitude
  • long_name: Latitude of site
  • units: degrees_north
  • var_id: longitude
  • long_name: Longitude of site
  • units: 1
  • var_id: model_Cv
  • long_name: Model cloud fraction
  • units: 1
  • var_id: model_Cv_filtered_min
  • long_name: Model cloud fraction by volume with undetectable cirrus removed assuming radar 3 dB less sensitive than best guess
  • units: 1
  • var_id: model_Cv_filtered_max
  • long_name: Model cloud fraction by volume with undetectable cirrus removed assuming radar 3 dB more sensitive than best guess
  • units: 1
  • var_id: model_Cv_filtered
  • long_name: Model cloud fraction by volume with undetectable cirrus removed using best guess of radar sensitivity
  • units: kg m-3
  • var_id: model_iwc
  • long_name: Model ice water content
  • units: kg m-3
  • var_id: model_iwc_filtered_min
  • long_name: Model ice water content with undetectable cirrus removed assuming radar 3 dB less sensitive than best guess
  • units: kg m-3
  • var_id: model_iwc_filtered_max
  • long_name: Model ice water content with undetectable cirrus removed assuming radar 3 dB more sensitive than best guess
  • units: kg m-3
  • var_id: model_iwc_filtered
  • long_name: Model ice water content with undetectable cirrus removed using best guess of radar sensitivity
  • units: kg m-3
  • var_id: model_lwc
  • long_name: Model liquid water content
  • units: 1
  • var_id: n
  • long_name: Number of radar pixels, 1 hour sampling
  • units: 1
  • var_id: n_adv
  • long_name: Number of radar pixels, 1.5km sampling
  • units: 1
  • var_id: Ca
  • long_name: Observed cloud fraction by area, 1 hour sampling
  • units: 1
  • var_id: Ca_adv
  • long_name: Observed cloud fraction by area, 1.5km sampling
  • units: 1
  • var_id: Cv
  • long_name: Observed cloud fraction by volume, 1 hour sampling
  • units: 1
  • var_id: Cv_adv
  • long_name: Observed cloud fraction by volume, 1.5km sampling
  • units: kg m-3
  • var_id: iwc_inc_rain
  • long_name: Observed mean ice water content (including attenuated and raining profiles), 1 hour sampling
  • units: kg m-3
  • var_id: iwc_adv_inc_rain
  • long_name: Observed mean ice water content (including attenuated and raining profiles), 1.5 km.
  • units: kg m-3
  • var_id: iwc_inc_att
  • long_name: Observed mean ice water content (including attenuated profiles), 1 hour sampling
  • units: kg m-3
  • var_id: iwc_adv_inc_att
  • long_name: Observed mean ice water content (including attenuated profiles), 1.5 km.
  • units: kg m-3
  • var_id: iwc
  • long_name: Observed mean ice water content, 1 hour sampling
  • units: kg m-3
  • var_id: iwc_adv
  • long_name: Observed mean ice water content, 1.5 km.
  • var_id: rain_rate_threshold
  • long_name: Rain rate threshold
  • units: mm hr-1
  • units: K
  • long_name: Temperature
  • var_id: model_temperature
  • var_id: time
  • units: hours
  • long_name: Time UTC
  • units: hours
  • var_id: forecast_time
  • long_name: Time since initialization of forecast
  • units: 1
  • var_id: column_Ca
  • long_name: Total column cloud cover, 1 hour sampling
  • units: 1
  • var_id: column_Ca_adv
  • long_name: Total column cloud cover, 1.5km sampling
  • units: Pa s-1
  • standard_name: omega
  • var_id: omega_500mb
  • long_name: Vertical wind in pressure coordinates
  • units: K
  • standard_name: air_potential_temperature
  • var_id: theta
  • units: Pa
  • standard_name: air_pressure
  • var_id: pressure
  • units: Pa
  • standard_name: air_pressure_at_sea_level
  • var_id: air_pressure_at_sea_level
  • units: K
  • standard_name: air_temperature
  • var_id: temperature
  • units: K
  • var_id: air_temperature_at_1.5m
  • long_name: air_temperature_at_1.5m
  • units: m
  • standard_name: atmosphere_boundary_layer_thickness
  • var_id: bl_depth
  • units: Pa
  • var_id: atmosphere_downward_eastward_stress
  • long_name: atmosphere_downward_eastward_stress
  • units: Pa
  • var_id: atmosphere_downward_northward_stress
  • long_name: atmosphere_downward_northward_stress
  • units: unknown
  • var_id: bulk_richardson_number
  • long_name: bulk_richardson_number
  • units: 1
  • var_id: cloud_area_fraction_assuming_maximum_random_overlap
  • long_name: cloud_area_fraction_assuming_maximum_random_overlap
  • units: 1
  • var_id: cloud_area_fraction_assuming_random_overlap
  • long_name: cloud_area_fraction_assuming_random_overlap
  • units: 1
  • var_id: cloud_fraction
  • long_name: cloud_volume_fraction_in_atmosphere_layer
  • units: unknown
  • var_id: bl_type
  • long_name: combined_boundary_layer_type
  • units: K
  • var_id: dew_point_temperature_at_1.5m
  • long_name: dew_point_temperature_at_1.5m
  • units: m s-1
  • standard_name: eastward_wind
  • var_id: uwind
  • units: m s-1
  • var_id: u_10m
  • long_name: eastward_wind_at_10m
  • units: unknown
  • var_id: entrainment_rate_BL
  • long_name: entrainment_rate_for_boundary_layer
  • units: unknown
  • var_id: entrainment_rate_SML
  • long_name: entrainment_rate_for_surface_mixed_layer
  • units: unknown
  • var_id: explicit_friction_velocity
  • long_name: explicit_friction_velocity
  • units: 1
  • var_id: fog_fraction
  • long_name: fog_area_fraction_at_1.5m
  • units: hours
  • var_id: forecast_time
  • long_name: forecast_time
  • units: m
  • var_id: height
  • long_name: height
  • units: m
  • var_id: height2
  • long_name: height2
  • units: unknown
  • var_id: h_decoupled_layer_base
  • long_name: height_of_decoupled_layer_base
  • units: unknown
  • var_id: h_sc_cloud_base
  • long_name: height_of_stratocumulus_cloud_base
  • units: 1
  • standard_name: high_type_cloud_area_fraction
  • var_id: high_cloud
  • units: km
  • var_id: horizontal_resolution
  • long_name: horizontal model resolution
  • units: km
  • var_id: horizontal_resolution
  • units: 1
  • var_id: ice_cloud_fraction
  • long_name: ice_cloud_volume_fraction_in_atmosphere_layer
  • units: unknown
  • var_id: IWP
  • long_name: large_scale_ice_water_path
  • units: unknown
  • var_id: LWP
  • long_name: large_scale_liquid_water_path
  • units: 1
  • var_id: liquid_cloud_fraction
  • long_name: liquid_cloud_volume_fraction_in_atmosphere_layer
  • units: 1
  • standard_name: low_type_cloud_area_fraction
  • var_id: low_cloud
  • units: kg kg-1
  • var_id: qsnow
  • standard_name: mass_fraction_of_cloud_ice_aggregates_in_air
  • units: unknown
  • var_id: qicecrystals
  • long_name: mass_fraction_of_cloud_ice_crystals_in_air
  • units: kg kg-1
  • standard_name: mass_fraction_of_cloud_liquid_water_in_air
  • var_id: qliq
  • units: kg kg-1
  • var_id: qice
  • standard_name: mass_fraction_of_total_cloud_ice_in_air
  • units: 1
  • standard_name: medium_type_cloud_area_fraction
  • var_id: medium_cloud
  • units: unknown
  • var_id: mixing_length_for_momentum
  • long_name: mixing_length_for_momentum
  • units: m s-1
  • standard_name: northward_wind
  • var_id: vwind
  • units: m s-1
  • var_id: v_10m
  • long_name: northward_wind_at_10m
  • units: unknown
  • var_id: qnliq
  • long_name: number_concentration_of_cloud_droplets_in_air
  • units: unknown
  • standard_name: number_concentration_of_ice_crystals_in_air
  • var_id: qnice
  • units: unknown
  • var_id: obukhov_length
  • long_name: obukhov_length
  • units: %
  • var_id: rh_1.5m
  • long_name: relative_humidity_at_1.5m
  • units: 1
  • standard_name: sea_ice_area_fraction
  • var_id: sea_ice_fraction
  • units: kg kg-1
  • var_id: q
  • standard_name: specific_humidity
  • units: 1
  • var_id: q_1.5m
  • long_name: specific_humidity_at_1.5m
  • units: kg m-2 s-1
  • standard_name: stratiform_rainfall_flux
  • var_id: rainfall_flux
  • units: kg m-2 s-1
  • standard_name: stratiform_snowfall_flux
  • var_id: snowfall_flux
  • units: Pa
  • standard_name: surface_air_pressure
  • var_id: sfc_pressure
  • units: Pa
  • standard_name: surface_downward_eastward_stress
  • var_id: surface_downward_eastward_stress
  • units: Pa
  • standard_name: surface_downward_northward_stress
  • var_id: surface_downward_northward_stress
  • units: W m-2
  • var_id: surface_downwelling_LW_radiation
  • long_name: surface_downwelling_LW_radiation
  • units: W m-2
  • var_id: surface_downwelling_SW_radiation
  • long_name: surface_downwelling_SW_radiation
  • units: W m-2
  • var_id: surface_net_LW_radiation
  • long_name: surface_net_LW_radiation
  • units: W m-2
  • var_id: surface_net_SW_radiation
  • long_name: surface_net_SW_radiation
  • units: m
  • standard_name: surface_roughness_length
  • var_id: surface_roughness_length
  • units: K
  • standard_name: surface_temperature
  • var_id: sfc_temperature
  • units: W m-2
  • standard_name: surface_upward_latent_heat_flux
  • var_id: latent_heat_flux
  • units: W m-2
  • standard_name: surface_upward_sensible_heat_flux
  • var_id: sensible_heat_flux
  • units: kg m-2 s-1
  • standard_name: surface_upward_water_flux
  • var_id: surface_upward_water_flux
  • units: W m-2
  • standard_name: toa_incoming_shortwave_flux
  • var_id: toa_incoming_shortwave_flux
  • units: W m-2
  • standard_name: toa_outgoing_longwave_flux
  • var_id: toa_outgoing_longwave_flux
  • units: W m-2
  • standard_name: toa_outgoing_shortwave_flux
  • var_id: toa_outgoing_shortwave_flux
  • units: unknown
  • var_id: total_column_q
  • long_name: total_column_q
  • var_id: radr_refl
  • long_name: total_radar_reflectivity
  • units: unknown
  • var_id: tke
  • long_name: turbulent_kinetic_energy
  • units: m
  • var_id: turbulent_mixing_height_after_bl
  • long_name: turbulent_mixing_height_after_boundary_layer
  • units: m s-1
  • standard_name: upward_air_velocity
  • var_id: wwind
  • units: unknown
  • var_id: vertical_buoyancy_gradient
  • long_name: vertical_buoyancy_gradient
  • units: m
  • var_id: visibility
  • long_name: visibility_in_air_at_1.5m
  • units: unknown
  • var_id: water_evaporation_amount
  • standard_name: water_evaporation_amount
  • units: unknown
  • var_id: seaice_albedo_agg
  • long_name: weighted_sea_ice_albedo_aggregated
  • units: m
  • var_id: wet_bulb_freezing_level_altitude
  • long_name: wet_bulb_freezing_level_altitude

Co-ordinate Variables

Coverage
Temporal Range
Start time:
2018-08-14T00:00:00
End time:
2018-09-14T00:00:00
Geographic Extent

 
89.9000°
 
3.9800°
 
73.7600°
 
56.0100°