############################################################################################################# # In this directory you will find model outputs from the Regional Climate Model HIRHAM5 for Greenland # # The model is run at the Danish Meteorological Institute by Ruth Mottram, Fredrik Boberg and Peter Langen # # This file contains some metadata and terms of use relating to HIRHAM5 # # # # Date last updated 28/04/2016 # Date last updated 03/09/2018 # ############################################################################################################# This readme file relates to files shared here: http://prudence.dmi.dk/data/temp/RUM/HIRHAM/GREENLAND/ERAI Simulation information ---------------------- GR6x2 is the latest simulation using HIRHAM5. The set-up is published in Langen et al., 2015, Rae et al (2012) and Lucas-Picher et al., 2012, but with a significantly improved surface scheme as given in Langen et al., 2017 and Mottram et al., 2017 The model is run at a horizontal resolution of 0.05 degrees (~5km), forced on the boundaries by the EC-Earth global climate model as run at DMI. The model is forced every six hours with the global model, and has an internal time step of 90 seconds. There are 31 vertical levels in the atmosphere. We here present two timeslice simulations of 20 years driven by the RCP4.5 emissions scenario for the mid and end of the 21st century. HIRHAM5 uses the topography of Bamber et al. (2001) and a recently updated high resolution ice mask produced by the PROMICE group at GEUS (contact mcit@geus.dk for more information), both are interpolated to the model resolution. Surface Mass Balance is only calculated explicitly at glacier points (where the ice fraction is more than half the grid cell). For simplicity, we have put up only daily values here. Sub-daily data is available for certain model fields, please contact us if you need this, it may require some extra processing. HIRHAM5 outputs dozens of variables and only a small selection is placed here, contact us if something you require is missing. Variable names are based on standard GRIB vars: Surface albedo of glacier points albedom Temperature (2m air) - TAS Temp (surface/skin) - TSURF LW net - TRADS SW net - SRADS SWin - DSWRAD LW in - DLWRAD Precip - PR (usually kg m^2 or mm per day) Snowfall - SNFALL Snow and glacier melt on glacier points – snmel Runoff (from land points) - MRROS Runoff from glacier points - rogl Latent heat flux - AHFL Sensible heat flux - AHFS Snowdepth on land - SNW Snowdepth on glacier points - sn Superimposed ice on glacies - supimp Surface mass balance (on glaciers) – gld Column refreezing (in snowpack on glaciers) – rfrz Subsurface temperature in five soil layers - TSL 1-5 Cloud cover - CLCOV Mean sea lvel pressure - PSL Rainfall - RAIN Relative humidity - RELHUM 850 hPa temperature - TA850 U component wind velocity - UAS V copmponent wind velocity - VAS maximum wind speed - WIMAX, SFCWINDMAX Evaporation and sublimation (glacier points) - evspsbl Evaporation and sublimation (whole domain) - EVSPSBL Surface pressure - PS glacier mask - glmask topography - topo_geog References: Langen, P. L., Mottram, R. H., Christensen, J. H., Boberg, F., Rodehacke, C. B., Stendel, M., van As, D., Ahlstrøm, A. P., Mortensen, J., Rysgaard, S., Petersen, D., Svendsen, K. H., Aðalgeirsdóttir, G., Cappelen, J., Quantifying energy and mass fluxes controlling Godthåbsfjord freshwater input in a 5 km simulation (1991-2012), Journal of Climate (2015) P Lucas-Picher, M Wulff-Nielsen, JH Christensen Guðfinna Aðalgeirsdóttir, Ruth Mottram, Sebastian B Simonsen Very high resolution regional climate model simulations over Greenland: Identifying added value Journal of Geophysical Research: Atmospheres, 2012 Rae, J. G. L., Aðalgeirsdóttir, G., Edwards, T. L., Fettweis, X., Gregory, J. M., Hewitt, H. T., Lowe, J. A., Lucas-Picher, P., Mottram, R. H., Payne, A. J., Ridley, J. K., Shannon, S. R., van de Berg, W. J., van de Wal, R. S. W., van den Broeke, M. R., Greenland ice sheet surface mass balance: evaluating simulations and making projections with regional climate models, The Cryosphere, 6 (2012) ##################################################################################################################################### # TERMS OF USE: # # These simulations are freely available to the scientific community to use for research purposes, but they take a great deal of # # time, effort and money to produce. We therefore request to be co-author(s) on any papers produced using these data, in particular,# # if daily outputs are used or if we need to do extra data manipulations on your behalf. # # Please contact us if you need more assistance with data interpretation or a particular sub-set of the data. # # It is often faster and simpler # # for other scientists to ask us to select particular regions/data types or to interpret results, however bear in mind we’re a small# # group working on a lot of different projects! # # # # By downloading and using this data you agree to the following terms and conditions: # # # # a) I agree to restrict my use of regional climate model output for non-commercial research and # # educational purposes only. # # Results from non-commercial research are expected to be made generally available through open # # publication and must not be considered proprietary. Materials prepared for educational purposes # # cannot be sold. These restrictions may only be relaxed by permission of DMI. # # # # b)I will hold no individual, organisation or group responsible for any errors in the models or in their output data. # # # # c) In publications that rely on the model output, I will appropriately credit the data # # providers by an acknowledgement similar to the following: # # # # “We acknowledge the Arctic and Climate Research section at the Danish Meteorological Institute for producing and making available# # their HIRHAM5 model output" # # # # d) I acknowledge the potential limitations of the data obtained from this archive. These may include # # (but are not necessarily limited to) errors in the models, shortcomings in the experiment designs, the # # conjectural quality of the forcing scenarios used to drive the models, and statistical uncertainty of # # model results. # # # # e) I understand that although the model output has been subjected to a quality control procedure, # # unrecognized errors almost certainly remain. # # # ##################################################################################################################################### Contact: Ruth Mottram: rum@dmi.dk Peter Langen: pla@dmi.dk Fredrik Boberg: fbo@dmi.dk