RCEMIP-II Experimental Design

RCEMIP-II consists of "mock-Walker" experiments that are identical to the RCEMIP-I RCE_large simulations except for a prescribed SST pattern. For more details, see the protocol paper, published at GMD: Wing, A.A., L.G. Silvers, and K.A. Reed (2024): RCEMIP-II: Mock-Walker Simulations as Phase II of the Radiative-Convective Equilibrium Model Intercomparison Project, Geosci. Model Dev., 17, 6195–6225, doi:10.5194/gmd-17-6195-2024

For CRMs on a cartesian rectangular domain of approximately 6000 km x 400 km,
$SST(x) = \langle SST\rangle - \frac{\Delta SST}{2}cos\left(\frac{2\pi x}{L_x}\right),$
where $\langle SST\rangle$ is the mean $SST$, $\Delta SST$ is the difference between the maximum $SST$ and the minimum $SST$, $x$ is the horizontal position along the long axis, and $L_x$ is the domain length. This sets the wavelength of the SST pattern equal to $L_x$ and places the maximum $SST$ at $L_x/2$. Simulations should be run for 200 days.

For GCMs on a sphere with real Earth radius,
$SST(\phi) = \langle SST\rangle + \frac{\Delta SST}{2}cos\left(\frac{360^\circ \phi}{\lambda}\right),$
where $\langle SST\rangle$ is the mean $SST$, $\Delta SST$ is the difference between the maximum $SST$ and the minimum $SST$, $\phi$ is latitude in degrees, and $\lambda = 54^\circ$ yields a wavelength of 6004.53 km (for the wavelength centered on the equator), to approximately match the CRM configuration. Simulations should be run for 3 years.

For GCRMs on a sphere with reduced Earth radius of $R_E/n$, where $R_E$ is the real Earth radius,
$SST(\phi) = \langle SST\rangle + \frac{\Delta SST}{2}cos\left(\frac{360^\circ \phi}{\lambda}\right),$
where $\langle SST\rangle$ is the mean $SST$, $\Delta SST$ is the difference between the maximum $SST$ and the minimum $SST$, $\phi$ is latitude in degrees. For $n = \pi R_e/6000 km$, which yields a radius of $R_E/n \approx R_E/3.336$, $\lambda = 180^{\circ}$ corresponds to distance of 6000 km, to match the CRM configuration. If a smaller Earth radius of $R_E/4$ is used, as was used by some GCRMs in Phase 1, $\lambda = 180^{\circ}$ corresponds to a distance of approximately 5000 km. Smaller Earth radii than this are not recommended. Simulations should be run for 200 days.

Five experiments are to be performed with different values of $\langle SST\rangle$ and $\Delta SST$:

  1. $\langle SST\rangle = 295 K$, $\Delta SST = 1.25 K$
  2. $\langle SST\rangle = 300 K$, $\Delta SST = 0.625 K$
  3. $\langle SST\rangle = 300 K$, $\Delta SST = 1.25 K$
  4. $\langle SST\rangle = 300 K$, $\Delta SST = 2.5 K$
  5. $\langle SST\rangle = 305 K$, $\Delta SST = 1.25 K$
Participants may choose to perform simulations with additional values of $\langle SST\rangle$ and $\Delta SST$ if desired.

RCEMIP-II Output

For model contributors, instructions for uploading your data to the DKRZ swiftbrowser can be found here. 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.

RCEMIP-II Contributing Models

"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.

Model Name/Version Model Abbreviation Contributed by
Das Atmosphaerische Modell (DAM) DAM David Romps (UC Berkeley/LBNL)
E3SM version 2 E3SM Walter Hannah (LLNL)
E3SM-MMF version 2 E3SM-MMF Walter Hannah (LLNL)
Meso-NH 5.6.2 MESONH Jean-Pierre Chaboureau (LAERO, Univ. Toulouse, CNRS)
Model for Interdisciplinary Research on Climate ver. 6 MIROC6 Keiichi Hashimoto (Univ. Tokyo)
Simple Convection Resolving E3SM Atmosphere Model (SCREAM) ver. 0 SCREAMv0 Peter Bogenschutz (LLNL)
System for Atmospheric Modeling (SAM v6.11.2) SAM_CRM Allison Wing (FSU), Graham O'Donnell (FSU)
Met Office Unified Model GA7.1 UKMO-GA7.1 Lorenzo Tomassini (UK Met Office)
UKMO Idealized Model Version 11.1 UKMOi-vn11.1-RA1-T Peter Hill (Univ. of Reading/ECWMF)
Vector Vorticity Equation Cloud-Resolving Model VVM Chien-Ming Wu (National Taiwan Univ.)


RCEMIP-I Experimental Design

RCEMIP-I 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.

Code

  1. Create analytic sounding used to initialize RCE_small: create_snd_analytic.m
  2. Compute diagnostics as in Wing et al. 2018; Wing et al. 2020:
  3. RCEMIP colors, as in Wing et al. (2020)

RCEMIP-I Output

Some clarification on the RCEMIP-I 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.

RCEMIP-I 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.

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)