Dataset
Microbiology-Ocean-Cloud Coupling in the High Arctic (MOCCHA): Met Office Unified Model data and associated Cloudnet outputs (UM_RA2T_Cloudnet)
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-cc568. Model options include:
Cloud microphysics: Both the global model and LAM use the PC2 (Wilson et al., 2008) cloud scheme (i_cld_vn = 2); specifically, the LAM uses the RA2T_CON configuration.
Also set l_subgrid_qcl_mp to .true. to allow for turbulent production of mixed-phase cloud.
Extended boundary layer diagnostic list.
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.
Details
| Previous Info: |
No news update for this record
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| Previously used record identifiers: |
No related previous identifiers.
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| Access rules: |
Access to these data is available to any registered CEDA user. Please Login or Register for an account to gain access.
Use of these data is covered by the following licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. 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)
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| File Format: |
Data are netCDF formatted
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Related Documents
Process overview
| 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: 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: 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: 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.
- 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: Pa s-1
- standard_name: omega
- var_id: omega_500mb
- long_name: Vertical wind in pressure coordinates
- units: km
- var_id: horizontal_resolution
- long_name: horizontal model resolution
Co-ordinate Variables
Temporal Range
2018-08-14T00:00:00
2018-09-14T00:00:00
Geographic Extent
89.9000° |
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3.9800° |
73.7600° |
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56.0100° |