The Atmospheric General Circulation Model ECHAM6 Model Description

Total Page:16

File Type:pdf, Size:1020Kb

The Atmospheric General Circulation Model ECHAM6 Model Description The atmospheric general circulation model ECHAM6 Model description M.A. Giorgetta, E. Roeckner, T. Mauritsen, J. Bader, T. Crueger, M. Esch, S. Rast, L. Kornblueh, H. Schmidt, S. Kinne, C. Hohenegger, B. Möbis, T. Krismer, K.–H. Wieners, B. Stevens 135 Berichte zur Erdsystemforschung 2013 Reports on Earth System Science 135 Berichte zur Erdsystemforschung 2013 The atmospheric general circulation model ECHAM6 Model description M.A. Giorgetta, E. Roeckner, T. Mauritsen, J. Bader, T. Crueger, M. Esch, S. Rast, L. Kornblueh, H. Schmidt, S. Kinne, C. Hohenegger, B. Möbis, T. Krismer, K.–H. Wieners, B. Stevens 135 Reports on Earth System Science 2013 ISSN 1614-1199 M.A. Giorgetta, E. Roeckner, T. Mauritsen, J. Bader, T. Crueger, M. Esch, S. Rast1, L. Kornblueh, H. Schmidt, S. Kinne, C. Hohenegger, B. Möbis, T. Krismer, K.–H. Wieners, B. Stevens Max-Planck-Institut für Meteorologie Bundesstrasse 53 20146 Hamburg [email protected] ISSN 1614-1199 The atmospheric general circulation model ECHAM6 Model description M.A. Giorgetta, E. Roeckner, T. Mauritsen, J. Bader, T. Crueger, M. Esch, S. Rast, L. Kornblueh, H. Schmidt, S. Kinne, C. Hohenegger, B. Möbis, T. Krismer, K.–H. Wieners, B. Stevens Hamburg, June 21, 2013 Contents 1. Introduction 9 2. Atmosphere 11 2.1. Dynamical Core.................................... 12 2.1.1. The continuous equations.......................... 12 2.1.2. Horizontal discretization........................... 15 2.1.3. Vertical discretization............................ 20 2.1.4. Time integration scheme........................... 28 2.1.5. Nudging of dynamical variables....................... 33 2.2. Transport....................................... 36 2.3. Radiative Transfer.................................. 39 2.3.1. Correlated k method............................. 39 2.3.2. Shortwave................................... 41 2.3.3. Longwave radiation............................. 44 2.3.4. Radiative Properties............................. 45 2.3.5. Implementation and Numerical Aspects.................. 45 2.4. Turbulent transport and surface fluxes....................... 46 2.4.1. Conservative variables and definitions................... 46 2.4.2. TKE closure model.............................. 47 2.4.3. Interaction with the surface......................... 51 2.4.4. Numerical solution.............................. 53 2.4.5. Solving the TKE-equation.......................... 55 2.5. Cumulus convection................................. 57 2.5.1. Organized entrainment............................ 57 2.5.2. Organized detrainment............................ 58 2.5.3. Adjustment closure.............................. 59 2.5.4. Trigger of cumulus convection........................ 61 2.6. Large-scale cloud scheme............................... 62 2.6.1. Governing equations............................. 62 2.6.2. Cloud cover.................................. 63 2.6.3. Sedimentation and cloud microphysics................... 64 2.7. Parameterization of the momentum flux deposition due to a gravity wave spectrum 73 2.7.1. Hines Doppler spread theory........................ 73 2.7.2. The Hines Doppler Spread Parameterization (HDSP)........... 74 2.7.3. Summary................................... 79 2.7.4. Implementation Details........................... 80 2.8. Parameterized gravity wave drag from subgrid scale orography......... 82 2.8.1. Representation of the subgrid scale orography............... 82 2.8.2. Gravity wave drag from subgrid-scale orography............. 82 2.8.3. Gravity wave drag.............................. 84 2.9. Water Vapor in the Middle Atmosphere...................... 86 3 3. Land 87 4. Slab Ocean and Sea Ice 88 4.1. Slab ocean....................................... 89 4.2. Sea Ice......................................... 91 4.2.1. Calculation of sea ice melting separately for bare/snow covered ice and meltponds................................... 91 4.2.2. Snow on ice.................................. 93 4.2.3. New sea ice albedo scheme......................... 95 5. Atmosphere surface coupling 102 6. Model resolutions and resolution dependent parameters 103 6.1. Model resolutions and resolution-dependent parameters............. 104 6.1.1. Available model resolutions......................... 104 6.1.2. Resolution-dependent parameters...................... 104 6.1.3. Code implementation............................ 105 7. External data 106 7.1. Solar irradiation................................... 107 7.1.1. Historic.................................... 107 7.1.2. Scenarios................................... 108 7.1.3. Climatologies................................. 108 7.2. CO2, CH4, N2O, CFCs............................... 110 7.2.1. 1850-present, present to 2100 and beyond................. 110 7.3. Ozone......................................... 111 7.3.1. Historic.................................... 111 7.3.2. Scenarios................................... 112 7.3.3. Climatologies................................. 113 7.4. Aerosols........................................ 114 7.4.1. Tropospheric aerosols............................ 114 7.4.2. Stratospheric aerosols............................ 122 7.5. Sea surface temperature and ice cover....................... 127 7.5.1. Historic.................................... 127 7.5.2. Climatologies................................. 127 7.5.3. Aqua planet.................................. 127 7.6. Land data....................................... 128 7.6.1. Land sea maps................................ 128 7.6.2. Orography.................................. 128 7.6.3. Vegetation maps............................... 128 8. Errata 129 8.1. Albedo of melt–ponds................................ 130 8.2. Bug in anthropogenic aerosol data set....................... 130 8.3. Energy conservation violation............................ 130 8.4. Bug in gravity wave drag parameterization – Asymmetry............ 131 8.5. Horizontal diffusion in MR resolution........................ 131 A. The unparameterized equations 132 A.1. Introduction...................................... 133 4 A.2. The advective form of the unparameterized equations.............. 134 A.2.1. The material derivative........................... 134 A.2.2. The equation of state............................ 134 A.2.3. Mass conservation.............................. 135 A.2.4. The velocity equation............................ 135 A.2.5. The thermodynamic equation........................ 135 A.3. The flux forms of the equations........................... 136 A.4. The introduction of diffusive fluxes......................... 137 A.5. Approximations and definitions........................... 139 A.6. Return to the advective form............................ 139 A.7. The model equations................................. 140 B. Orbital Variations 142 B.1. Introduction...................................... 142 B.1.1. Obliquity................................... 142 B.1.2. Eccentricity.................................. 143 B.1.3. Precession................................... 144 B.2. Precise orbit determination based on VSOP87................... 144 B.2.1. VSOP — Variations Séculaires des Orbites Planétaires.......... 144 B.2.2. Nutation................................... 147 B.3. Kepler based orbit for paleoclimate applications.................. 148 B.4. Differences in the daily insolation due to the two given orbits.......... 149 B.5. Orbit tables...................................... 152 References 164 5 List of Tables 2.1. Truncation and associated number of Gaussian latitudes............. 20 2.2. Vertical-coordinate parameters........................... 24 2.3. Band structure for longwave radiative transfer................... 40 2.4. Band structure for shortwave radiative transfer.................. 41 2.5. Parameters, symbols and control parameters of namelist GWSCTL....... 81 4.1. Sea ice albedo parameterization scheme...................... 96 4.2. Constants for bare sea ice albedo.......................... 97 4.3. Constants for melt pond fraction as a function of melt pond depth for multiyear ice........................................... 99 4.4. Constants for melt pond albedo........................... 101 7.1. Solar irradiation as defined for the original SRTM radiation scheme....... 109 7.2. Pressure levels in Pa of ozone climatology..................... 111 7.3. Refractive indices of sulfate, dust, and sea salt.................. 116 7.4. File names of files containing tropospheric aerosol optical properties...... 122 7.5. Pressure coordinate for optical properties of aerosols............... 123 7.6. Wavelength bands for optical properties of volcanic aerosols........... 124 7.7. Available land sea masks dependent on ECHAM6 and MPI-OM resolution... 128 B.1. First summand of heliocentric latitude (VSOP87D)................ 153 B.2. Second summand of heliocentric latitude (VSOP87D).............. 154 B.3. Third summand of heliocentric latitude (VSOP87D)............... 155 B.4. Fourth summand of heliocentric latitude (VSOP87D)............... 155 B.5. Fifth summand of heliocentric latitude (VSOP87D)................ 156 B.6. Sixth summand of heliocentric latitude (VSOP87D)............... 156 B.7. First summand of heliocentric longitude (VSOP87D)............... 156 B.8. Second summand of heliocentric longitude (VSOP87D).............. 156 B.9. First summand of distance (VSOP87D)...................... 158 B.10.Second summand of distance (VSOP87D)..................... 158 B.11.Third summand of distance (VSOP87D).....................
Recommended publications
  • Climate Models and Their Evaluation
    8 Climate Models and Their Evaluation Coordinating Lead Authors: David A. Randall (USA), Richard A. Wood (UK) Lead Authors: Sandrine Bony (France), Robert Colman (Australia), Thierry Fichefet (Belgium), John Fyfe (Canada), Vladimir Kattsov (Russian Federation), Andrew Pitman (Australia), Jagadish Shukla (USA), Jayaraman Srinivasan (India), Ronald J. Stouffer (USA), Akimasa Sumi (Japan), Karl E. Taylor (USA) Contributing Authors: K. AchutaRao (USA), R. Allan (UK), A. Berger (Belgium), H. Blatter (Switzerland), C. Bonfi ls (USA, France), A. Boone (France, USA), C. Bretherton (USA), A. Broccoli (USA), V. Brovkin (Germany, Russian Federation), W. Cai (Australia), M. Claussen (Germany), P. Dirmeyer (USA), C. Doutriaux (USA, France), H. Drange (Norway), J.-L. Dufresne (France), S. Emori (Japan), P. Forster (UK), A. Frei (USA), A. Ganopolski (Germany), P. Gent (USA), P. Gleckler (USA), H. Goosse (Belgium), R. Graham (UK), J.M. Gregory (UK), R. Gudgel (USA), A. Hall (USA), S. Hallegatte (USA, France), H. Hasumi (Japan), A. Henderson-Sellers (Switzerland), H. Hendon (Australia), K. Hodges (UK), M. Holland (USA), A.A.M. Holtslag (Netherlands), E. Hunke (USA), P. Huybrechts (Belgium), W. Ingram (UK), F. Joos (Switzerland), B. Kirtman (USA), S. Klein (USA), R. Koster (USA), P. Kushner (Canada), J. Lanzante (USA), M. Latif (Germany), N.-C. Lau (USA), M. Meinshausen (Germany), A. Monahan (Canada), J.M. Murphy (UK), T. Osborn (UK), T. Pavlova (Russian Federationi), V. Petoukhov (Germany), T. Phillips (USA), S. Power (Australia), S. Rahmstorf (Germany), S.C.B. Raper (UK), H. Renssen (Netherlands), D. Rind (USA), M. Roberts (UK), A. Rosati (USA), C. Schär (Switzerland), A. Schmittner (USA, Germany), J. Scinocca (Canada), D. Seidov (USA), A.G.
    [Show full text]
  • The Lagrangian Chemistry and Transport Model ATLAS: Validation of Advective Transport and Mixing
    Geosci. Model Dev., 2, 153–173, 2009 www.geosci-model-dev.net/2/153/2009/ Geoscientific © Author(s) 2009. This work is distributed under Model Development the Creative Commons Attribution 3.0 License. The Lagrangian chemistry and transport model ATLAS: validation of advective transport and mixing I. Wohltmann and M. Rex Alfred Wegener Institute for Polar and Marine Research, Potsdam, Germany Received: 25 June 2009 – Published in Geosci. Model Dev. Discuss.: 3 July 2009 Revised: 15 September 2009 – Accepted: 2 October 2009 – Published: 2 November 2009 Abstract. We present a new global Chemical Transport In the context of this paper, numerical diffusion is defined Model (CTM) with full stratospheric chemistry and La- as any process that is triggered by the model calculations grangian transport and mixing called ATLAS (Alfred We- and behaves like a diffusive process acting on the chemical gener InsTitute LAgrangian Chemistry/Transport System). species in the model. Typically, numerical diffusion will be Lagrangian (trajectory-based) models have several important spurious and unrealistic, e.g. present in every grid cell with advantages over conventional Eulerian (grid-based) models, the same magnitude. We do not consider processes as nu- including the absence of spurious numerical diffusion, ef- merical diffusion here which are deliberately introduced into ficient code parallelization and no limitation of the largest the model, e.g. to mimic the observed diffusion. Eulerian ap- time step by the Courant-Friedrichs-Lewy criterion. The ba- proaches suffer from numerical diffusion because they con- sic concept of transport and mixing is similar to the approach tain an advection step that transfers information between dif- in the commonly used CLaMS model.
    [Show full text]
  • ESM-Tools Version 4.0: a Modular Infrastructure for Stand-Alone
    ESM-Tools Version 4.0: A modular infrastructure for stand-alone and coupled Earth System Modelling (ESM) Dirk Barbi1, Nadine Wieters1, Paul Gierz1, Fatemeh Chegini1, 3, Sara Khosravi2, and Luisa Cristini1 1Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany 2Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Potsdam, Germany 3Max Planck Institute for Meteorology, Hamburg, Germany Correspondence: Luisa Cristini ([email protected]) Abstract. Earth system and climate modelling involves the simulation of processes on a wide range of scales and within and across various compartments of the Earth system. In practice, component models are often developed independently by different research groups, adapted by others to their special interests, and then combined using a dedicated coupling software. This 5 procedure not only leads to a strongly growing number of available versions of model components and coupled setups, but also to model- and HPC-system dependent ways of obtaining, configuring, building, and operating them. Therefore, implementing these Earth System Models (ESMs) can be challenging and extremely time consuming, especially for less experienced mod- ellers, or scientists aiming to use different ESMs as in the case of inter-comparison projects. To assist researchers and modellers by reducing avoidable complexity, we developed the ESM-Tools software, which provides 10 a standard way for downloading, configuring, compiling, running and monitoring different models on a variety of High Perfor- mance Computing (HPC) systems. It should be noted that the ESM-Tools are equally applicable and helpful for stand-alone as for coupled models. In fact, the ESM-Tools are used as standard compile and runtime infrastructure for FESOM2, and currently also applied for ECHAM and ICON standalone simulations.
    [Show full text]
  • Documentation and Software User’S Manual, Version 4.1
    The Canadian Seasonal to Interannual Prediction System version 2 (CanSIPSv2) Canadian Meteorological Centre Technical Note H. Lin1, W. J. Merryfield2, R. Muncaster1, G. Smith1, M. Markovic3, A. Erfani3, S. Kharin2, W.-S. Lee2, M. Charron1 1-Meteorological Research Division 2-Canadian Centre for Climate Modelling and Analysis (CCCma) 3-Canadian Meteorological Centre (CMC) 7 May 2019 i Revisions Version Date Authors Remarks 1.0 2019/04/22 Hai Lin First draft 1.1 2019/04/26 Hai Lin Corrected the bias figures. Comments from Ryan Muncaster, Bill Merryfield 1.2 2019/05/01 Hai Lin Figures of CanSIPSv2 uses CanCM4i plus GEM-NEMO 1.3 2019/05/03 Bill Merrifield Added CanCM4i information, sea ice Hai Lin verification, 6.6 and 9 1.4 2019/05/06 Hai Lin All figures of CanSIPSv2 with CanCM4i and GEM-NEMO, made available by Slava Kharin ii © Environment and Climate Change Canada, 2019 Table of Contents 1 Introduction ............................................................................................................................. 4 2 Modifications to models .......................................................................................................... 6 2.1 CanCM4i .......................................................................................................................... 6 2.2 GEM-NEMO .................................................................................................................... 6 3 Forecast initialization .............................................................................................................
    [Show full text]
  • Validation of Climate Models
    Validation of Climate Models Simon Tett 19/6/06 with thanks to: Keith Williams, Mark Webb, Mark Rodwell, Roy Kershaw, Sean Milton, Gill Martin, Tim Johns, Jonathan Gregory, Peter Thorne, Philip Brohan & © Crown copyright John Caesar Page 1 Approaches Parameterisation & Forecast error Climatology's Climate Variability Climate Change. © Crown copyright Page 2 Methodology for improving parametrizations CRMs Observations Forcing Evaluation Evaluation g Fo Analysis Development in rc rc on in Fo ati g alu Ev NWP Forecast SCMs Development Forcing Evaluation (consistent errors?) © Crown copyright Page 3 Tropical Systematic Biases in NWP Moisture balance from Thermodynamic (RH) Profile Errors Idealised Aquaplanet – suggest Vs ARM Manus Sondes JAS 2003– convection largest contributor to Errors in convection? humidity biases Convection too shallow? 20 hPa Unrealistic 77 Moistening and drying 192 in forecasts 367 576 777 Moister at cloud base & Freezing level 922 © Crown copyright Page 4 S.Milton & M.Willett NWP Tropical T, RH, and Wind Errors vs Sondes Summer 2005 – Impact of new Physics A package of physics improvements introduced in March 2006 Improved Thermodynamic Profiles • Adaptive detrainment (conv) –> improve detrainment of moisture. • Changes to marine BL –> reduce LH fluxes Old • Non-gradient momentum stress. -> Improve low level winds Model New Physics ΔRH Day 5 Circulation Errors In Equatorial Winds Reduced ΔT Day 5 S. Derbyshire, A. Maidens, A. Brown, J.Edwards, M.Willett & S.Milton © Crown copyright Page 5 Spinup Tendencies Used to assess the contribution of individual physical parametrisations and dynamics to systematic errors. Run a ~60-member ensemble of 1 to 5 day integrations started from operational NWP analyses scattered evenly over a period e.g.
    [Show full text]
  • Atmospheric Dispersion of Radioactive Material in Radiological Risk Assessment and Emergency Response
    Progress in NUCLEAR SCIENCE and TECHNOLOGY, Vol. 1, p.7-13 (2011) REVIEW Atmospheric Dispersion of Radioactive Material in Radiological Risk Assessment and Emergency Response YAO Rentai * China Institute for Radiation Protection, P.O.Box 120, Taiyuan, Shanxi 030006, China The purpose of a consequence assessment system is to assess the consequences of specific hazards on people and the environment. In this paper, the studies on technique and method of atmospheric dispersion modeling of radioactive material in radiological risk assessment and emergency response are reviewed in brief. Some current statuses of nuclear accident consequences assessment in China were introduced. In the future, extending the dispersion modeling scales such as urban building scale, establishing high quality experiment dataset and method of model evaluation, improved methods of real-time modeling using limited inputs, and so on, should be promoted with high priority of doing much more work. KEY WORDS: atmospheric model, risk assessment, emergency response, nuclear accident 11) I. Introduction from U.S. NOAA, and SPEEDI/WSPEEDI from The studies and developments of techniques and methods Japan/JAERI. However, the needs of emergency of atmospheric dispersion modeling of radioactive material management may not be well satisfied by existing models in radiological risk assessment and emergency response which are not well designed and confronted with difficulty have evolved over the past 50-60 years. The three marked in detailed constructions of local wind and turbulence
    [Show full text]
  • Lecture 29. Introduction to Atmospheric Chemical Transport Models
    Lecture 29. Introduction to atmospheric chemical transport models. Part 1. Objectives: 1. Model types. 2. Box models. 3. One-dimensional models. 4. Two-dimensional models. 5. Three-dimensional models. Readings: Graedel T. and P.Crutzen. “Atmospheric change: an earth system perspective”. Chapter 15.”Bulding environmental chemical models”, 1992. 1. Model types. Mathematical models provide the necessary framework for integration of our understanding of individual atmospheric processes and study of their interactions. Note, that atmosphere is a complex reactive system in which numerous physical and chemical processes occur simultaneously. • Atmospheric chemical transport models are defined according to their spatial scale: Model Typical domain scale Typical resolution Microscale 200x200x100 m 5 m Mesoscale(urban) 100x100x5 km 2 km Regional 1000x1000x10 km 20 km Synoptic(continental) 3000x3000x20 km 80 km Global 65000x65000x20km 50x50 1 Figure 29.1 Components of a chemical transport model (Seinfeld and Pandis, 1998). 2 • Domain of the atmospheric model is the area that is simulated. The computation domain consists of an array of computational cells, each having uniform chemical composition. The size of cells determines the spatial resolution of the model. • Atmospheric chemical transport models are also characterized by their dimensionality: zero-dimensional (box) model; one-dimensional (column) model; two-dimensional model; and three-dimensional model. • Model time scale depends on a specific application varying from hours (e.g., air quality model) to hundreds of years (e.g., climate models) 3 Two principal approaches to simulate changes in the chemical composition of a given air parcel: 1) Lagrangian approach: air parcel moves with the local wind so that there is no mass exchange that is allowed to enter the air parcel and its surroundings (except of species emissions).
    [Show full text]
  • A Brief Summary of Plans for the GMAO Core Priorities and Initiatives for the Next 5 Years
    A Brief Summary of Plans for the GMAO Core Priorities and Initiatives for the Next 5 years Provided as information for ROSES 2012 A.13 – MAP Developments in the GMAO are focused on the next generation systems, GEOS-6, and an Integrated Earth System Analysis and the associated modeling system that supports that analysis. GEOS-6 and IESA (1) The GEOS-6 system will be built around the next generation, non-hydrostatic atmospheric model with aerosol-cloud microphysics (advances upon the Morrison-Gettelman cloud microphysics and the Modal Aerosol Model (MAM) aerosol microphysics module for the inclusion of aerosol indirect effects) and an accompanying hybrid (ensemble-variational) 4DVar atmospheric assimilation system. (2) IESA capabilities for other parts of the earth system, including atmospheric chemical constituents and aerosols, ocean circulation, land hydrology, and carbon budget will be built upon our existing separate assimilation capabilities. The GEOS Model Our modeling strategy is driven by the need to have a comprehensive global model valid for both weather and climate and for use in both simulation and assimilation. Our main task in atmospheric modeling during the next five years will be to make the transition to GEOS-6. This direction is driven by (i) the need to improve the representation of clouds and precipitation to enable use of cloud- and precipitation-contaminated satellite radiance observations in NWP, and (ii) the research goal of understanding and predicting weather- climate connections. Development will focus on 1km to 10km resolutions that will be needed for the data assimilation system (DAS). Climate resolutions (10-100km) will not be ignored, but developments for resolutions coarser than 50 km will have lower priority.
    [Show full text]
  • Assimila Blank
    NERC NERC Strategy for Earth System Modelling: Technical Support Audit Report Version 1.1 December 2009 Contact Details Dr Zofia Stott Assimila Ltd 1 Earley Gate The University of Reading Reading, RG6 6AT Tel: +44 (0)118 966 0554 Mobile: +44 (0)7932 565822 email: [email protected] NERC STRATEGY FOR ESM – AUDIT REPORT VERSION1.1, DECEMBER 2009 Contents 1. BACKGROUND ....................................................................................................................... 4 1.1 Introduction .............................................................................................................. 4 1.2 Context .................................................................................................................... 4 1.3 Scope of the ESM audit ............................................................................................ 4 1.4 Methodology ............................................................................................................ 5 2. Scene setting ........................................................................................................................... 7 2.1 NERC Strategy......................................................................................................... 7 2.2 Definition of Earth system modelling ........................................................................ 8 2.3 Broad categories of activities supported by NERC ................................................. 10 2.4 Structure of the report ...........................................................................................
    [Show full text]
  • DJ Karoly Et
    Supporting Online Material “Detection of a human influence on North American climate”, D. J. Karoly et al. (2003) Materials and Methods Description of the climate models GFDL R30 is a spectral atmospheric model with rhomboidal truncation at wavenumber 30 equivalent to 3.75° longitude × 2.2° latitude (96 × 80) with 14 levels in the vertical. The atmospheric model is coupled to an 18 level gridpoint (192 × 80) ocean model where two ocean grid boxes underlie each atmospheric grid box exactly. Both models are described by Delworth et al. (S1) and Dixon et al. (S2). HadCM2 and HadCM3 use the same atmospheric horizontal resolution, 3.75°× 2.5° (96 × 72) finite difference model (T42/R30 equivalent) with 19 levels in the atmosphere and 20 levels in the ocean (S3, S4). For HadCM2, the ocean horizontal grid lies exactly under that of the atmospheric model. The ocean component of HadCM3 uses much higher resolution (1.25° × 1.25°) with six ocean grid boxes for every atmospheric grid box. In the context of results shown here, the main difference between the two models is that HadCM3 includes improved representations of physical processes in the atmosphere and the ocean (S5). For example, HadCM3 employs a radiation scheme that explicitly represents the radiative effects of minor greenhouse gases as well as CO2, water vapor and ozone (S6), as well as a simple parametrization of background aerosol (S7). ECHAM4/OPYC3 is an atmospheric T42 spectral model equivalent to 2.8° longitude × 2.8° latitude (128 × 64) with 19 vertical layers. The ocean model OPYC3 uses isopycnals as the vertical coordinate system.
    [Show full text]
  • Climate Reanalysis
    from Newsletter Number 139 – Spring 2014 METEOROLOGY Climate reanalysis doi:10.21957/qnreh9t5 Dick Dee interviewed by Bob Riddaway Climate reanalysis This article appeared in the Meteorology section of ECMWF Newsletter No. 139 – Spring 2014, pp. 15–21. Climate reanalysis Dick Dee interviewed by Bob Riddaway Dick Dee is the Head of the Reanalysis Section at ECMWF. He is responsible for leading a group of scientists producing state-of-the art global climate datasets. This has involved coordinating two international research projects: ERA-CLIM and ERA-CLIM2. The ERA-CLIM2 project has recently started – what is its purpose? This exciting new project extends and expands the work begun in the ERA-CLIM project that ended in December 2013. The aim is to produce physically consistent reanalyses of the global atmosphere, ocean, land-surface, cryosphere and the carbon cycle – see Box A for more information about what is involved in reanalysis. The project is at the heart of a concerted effort in Europe to build the information infrastructure needed to support climate monitoring, climate research and climate services, based on the best available science and observations. The ERA-CLIM2 project will rely on ECMWF’s expertise in modelling and data assimilation to develop a first th coupled ocean-atmosphere reanalysis spanning the 20 century. It includes activities aimed at improving the available observational record (e.g. through data rescue and reprocessing), the assimilating model (primarily by coupling the atmosphere with the ocean) and the data assimilation techniques (e.g. related to data assimilation in coupled models). The project will also develop improved data services in order to prepare for the need to support new classes of users, including providers of climate services and European policy makers.
    [Show full text]
  • ESM-Tools Version 4.0: a Modular Infrastructure for Stand-Alone and Coupled Earth System Modelling
    https://doi.org/10.5194/gmd-2020-100 Preprint. Discussion started: 11 August 2020 c Author(s) 2020. CC BY 4.0 License. ESM-Tools Version 4.0: A modular infrastructure for stand-alone and coupled Earth System Modelling (ESM) Dirk Barbi1, Nadine Wieters1, Paul Gierz1, Fatemeh Chegini1, 3, Sara Khosravi2, and Luisa Cristini1 1Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany 2Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Potsdam, Germany 3Max Planck Institute for Meteorology, Hamburg, Germany Correspondence: Luisa Cristini ([email protected]) Abstract. Earth system and climate modelling involves the simulation of processes on a wide range of scales and within and across var- ious components of the Earth system. In practice, component models are often developed independently by different research groups and then combined using a dedicated coupling software. This procedure not only leads to a strongly growing number of 5 available versions of model components and coupled setups, but also to model- and system-dependent ways of obtaining and operating them. Therefore, implementing these Earth System Models (ESMs) can be challenging and extremely time consum- ing, especially for less experienced modellers, or scientists aiming to use different ESMs as in the case of inter-comparison projects. To assist researchers and modellers by reducing avoidable complexity, we developed the ESM-Tools software, which pro- 10 vides a standard way for downloading, configuring, compiling, running and monitoring different models - coupled ESMs and stand-alone models alike - on a variety of High Performance Computing (HPC) systems.1 With the ESM-Tools, the user is only required to provide a short script consisting of only the experiment specific definitions, while the software executes all the phases of a simulation in the correct order.
    [Show full text]