RCEMIP Experimental Design

RCEMIP includes the following two sets of experiments designed to address the three scientific objectives:

  1. RCE_small: RCE simulation on a small square domain (for CRMs) or single column (for GCMs)
    • RCE_small295: uniform, fixed sea surface temperature (SST) of 295 K.
    • RCE_small300: uniform, fixed SST of 300 K.
    • RCE_small305: uniform, fixed SST of 305 K.
  2. RCE_large: RCE simulation on a large, rectangular domain (for CRMs) or global (for GCMs)
    • RCE_large295: uniform, fixed sea surface temperature (SST) of 295 K.
    • RCE_large300: uniform, fixed SST of 300 K.
    • RCE_large305: uniform, fixed SST of 305 K.

The detailed parameter settings and output specifications can be found in the RCEMIP protocol paper.

Analytic Sounding

The following code may be used to generate the analytic sounding used to initialize RCE_small:

  1. Create analytic sounding: create_snd_analytic.m

Diagnostic Code

Code to compute the diagnostics described in the RCEMIP protocol paper can be found below:

  1. Organization index: IORG.py
  2. Subsidence fraction: calc_sf.m, uses binavg.m

Output

Some clarification on the output specification can be found here (updated October 2, 2018).

A list of known bugs and inconsistencies with the RCEMIP protocol can be found here.

The standardized RCEMIP output is hosted by the German Climate Computing Center (DKRZ) and is publicly available at http://hdl.handle.net/21.14101/d4beee8e-6996-453e-bbd1-ff53b6874c0e. In addition to the raw data, several post-processed domain- and time-average statistics are available in the A-Statistics folder as .csv files. Please let us know that you are using the RCEMIP data by filling out this form. If you use RCEMIP data in a publication, we ask that you cite the RCEMIP protocol paper (Wing et al. 2018), the RCEMIP overview paper (Wing et al. 2020), and including the following acknowledgement statement:

We thank the German Climate Computing Center (DKRZ) for hosting the standardized RCEMIP data, which is publicly available at http://hdl.handle.net/21.14101/d4beee8e-6996-453e-bbd1-ff53b6874c0e.

For model contributors, instructions for uploading your data to the DKRZ swiftbrowser can be found here (updated October 2, 2018). For technical questions about uploading or downloading data to/from the DKRZ cloud, contact Karsten Peters (peters at dkrz.de). Along with your model data, please fill out and upload this model documentation form.

Contributing Models

RCEMIP includes cloud-resolving models (CRMs), global cloud-resolving models (GCRMs), large eddy simulations (LES), general circulation models (GCMs), and single-column models (SCMs). "Model Name/Version" links to the citation for the model, "Model Abbreviation" is the abbreviation used in the DKRZ Swift Cloud and links to the RCEMIP model documentation form for the model.

Simulations uploaded to DKRZ Swift Cloud

Model Name/Version Model Abbreviation Contributed by
Community Atmosphere Model version 5 CAM5_GCM Kevin Reed (Stony Brook Univ.), I-Kuan Hu (Univ. of Miami)
Community Atmosphere Model version 6 CAM6_GCM Kevin Reed (Stony Brook Univ.), I-Kuan Hu (Univ. of Miami)
CM1 (cm1r19.6) CM1 George Bryan (NCAR)
CNRM-CM6-1 CNRM-CM6-1 Romain Roehrig (Meteo-France/CNRM)
DALES DALES Stephan de Roode (TU Delft), Fredrik Jansson (TU Delft, Centrum Wiskunde & Informatica)
Das Atmosphaerische Modell (DAM) dam David Romps (UC Berkeley/LBNL)
echam-6.3.04p1 ECHAM6_GCM Tobias Becker (MPI-M)
GEOS 5.21 GEOS_GCM Nathan Arnold (NASA GMAO)
GFDL-FV3-CRM FV3 Ming Zhao (NOAA GFDL)
icon-2.3.00 ICON_LEM_CRM Tobias Becker (MPI-M)
icon-2.3.00 ICON_NWP_CRM Tobias Becker (MPI-M)
ICON-A ICON_GCM Sebastian Mueller (MPI-M)
IPSL-CM5A-LR IPSL-CM6 Max Popp, Sandrine Bony (LMD)
Meso-NH 5.4.1 MESONH Jean-Pierre Chaboureau (CNRS/Univ. Toulouse)
MicroHH version 2.0 MicroHH Chiel van Heerwaarden (Wageningen Univ.)
Model for Prediction Across Scales (MPAS), v. 5.2 MPAS Rosimar Rios-Berrios (NCAR)
NICAM.16.3 NICAM Tomoki Ohno (JAMSTEC)
System for Atmospheric Modeling - CRM (SAM v6.11.2) SAM_CRM Allison Wing (FSU)
System for Atmospheric Modeling - LES (SAM v6.11.2) SAM_CRM Martin Singh (Monash Univ.)
System for Atmospheric Modeling - GCRM (SAM v7.3) SAM_GCRM Marat Khairoutdinov (Stony Brook Univ.)
Seoul National University Atmosphere Model Version 0 SAM0-UNICON Min-Seop Ahn, Daehyun Kim (Univ. of Washington)
SCALE/5.2.5 SCALE Shuhei Matsugishi, Hiroaki Miura (Univ. of Tokyo)
Super-parameterized Community Atmosphere Model SP-CAM Mark Branson, David Randall (Colorado State Univ.)
Multi-instance Super-parameterized Community Atmosphere Model SPX-CAM Mark Branson, David Randall (Colorado State Univ.)
UCLA-LES UCLA_CRM Cathy Hohenegger (MPI-M)
Met Office Unified Model Global Atmosphere GA7.1 UKMO-GA7.1 Lorenzo Tomassini (UK Met Office)
UKMO Idealized Model Version 11.0 - CASIM UKMOi-vn11.1-CASIM Todd Jones (Univ. of Reading)
UKMO Idealized Model Version 11.0 - RA1-T UKMOi-vn11.1-RA1-T Todd Jones (Univ. of Reading)
UKMO Idealized Model Version 11.0 - RA1-T - Homog. Rad. UKMOi-vn11.1-RA1-T-hrad Todd Jones (Univ. of Reading)
UKMO Idealized Model Version 11.0 - RA1-T - No Cloud Scheme UKMOi-vn11.1-RA1-T-nocloud Todd Jones (Univ. of Reading)
WRF v3.9.1 WRF-CRM Kulkarni Gayatri, Thara Prabhakaran (IITM)
WRF v3.5.1 - Explicit Convection WRF_COL_CRM Zane Martin, Shuguang Wang (Columbia Univ.)
WRF v3.5.1 - Parameterized Convection WRF_GCM Yumin Moon, Daehyun Kim (Univ. of Washington)