scholarly journals Model calibration using ESEm v1.1.0 – an open, scalable Earth system emulator

2021 ◽  
Vol 14 (12) ◽  
pp. 7659-7672
Author(s):  
Duncan Watson-Parris ◽  
Andrew Williams ◽  
Lucia Deaconu ◽  
Philip Stier
Keyword(s):  
Model Calibration ◽  
General Circulation ◽  
High Performance ◽  
Circulation Model ◽  
Parametric Uncertainty ◽  
Large Computer ◽  
The Earth ◽  
Large Ensembles ◽  
Cloud Resolving Model ◽  
Scenario Uncertainty

Abstract. Large computer models are ubiquitous in the Earth sciences. These models often have tens or hundreds of tuneable parameters and can take thousands of core hours to run to completion while generating terabytes of output. It is becoming common practice to develop emulators as fast approximations, or surrogates, of these models in order to explore the relationships between these inputs and outputs, understand uncertainties, and generate large ensembles datasets. While the purpose of these surrogates may differ, their development is often very similar. Here we introduce ESEm: an open-source tool providing a general workflow for emulating and validating a wide variety of models and outputs. It includes efficient routines for sampling these emulators for the purpose of uncertainty quantification and model calibration. It is built on well-established, high-performance libraries to ensure robustness, extensibility and scalability. We demonstrate the flexibility of ESEm through three case studies using ESEm to reduce parametric uncertainty in a general circulation model and explore precipitation sensitivity in a cloud-resolving model and scenario uncertainty in the CMIP6 multi-model ensemble.

scholarly journals Model calibration using ESEm v1.0.0 – an open, scalable Earth System Emulator

2021 ◽  
Author(s):  
Duncan Watson-Parris ◽  
Andrew Williams ◽  
Lucia Deaconu ◽  
Philip Stier
Keyword(s):  
Model Calibration ◽  
General Circulation ◽  
High Performance ◽  
Circulation Model ◽  
Parametric Uncertainty ◽  
Large Computer ◽  
The Earth ◽  
Large Ensembles ◽  
Cloud Resolving Model ◽  
Scenario Uncertainty

Abstract. Large computer models are ubiquitous in the earth sciences. These models often have tens or hundreds of tuneable parameters and can take thousands of core-hours to run to completion while generating terabytes of output. It is becoming common practice to develop emulators as fast approximations, or surrogates, of these models in order to explore the relationships between these inputs and outputs, understand uncertainties and generate large ensembles datasets. While the purpose of these surrogates may differ, their development is often very similar. Here we introduce ESEm: an open-source tool providing a general workflow for emulating and validating a wide variety of models and outputs. It includes efficient routines for sampling these emulators for the purpose of uncertainty quantification and model calibration. It is built on well-established, high-performance libraries to ensure robustness, extensibility and scalability. We demonstrate the flexibility of ESEm through three case-studies using ESEm to reduce parametric uncertainty in a general circulation model, explore precipitation sensitivity in a cloud resolving model and scenario uncertainty in the CMIP6 multi-model ensemble.

scholarly journals Theoretical aspects of the onset of Indian summer monsoon from perturbed orography simulations in a GCM

2006 ◽  
Vol 24 (8) ◽  
pp. 2075-2089 ◽  
Author(s):  
A. Chakraborty ◽  
R. S. Nanjundiah ◽  
J. Srinivasan
Keyword(s):  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
General Circulation ◽  
Large Scale ◽  
Vertical Motion ◽  
Circulation Model ◽  
Threshold Value ◽  
The Earth ◽  
Static Energy ◽  
The Impact

Abstract. A theory is proposed to determine the onset of the Indian Summer Monsoon (ISM) in an Atmospheric General Circulation Model (AGCM). The onset of ISM is delayed substantially in the absence of global orography. The impact of orography over different parts of the Earth on the onset of ISM has also been investigated using five additional perturbed simulations. The large difference in the date of onset of ISM in these simulations has been explained by a new theory based on the Surface Moist Static Energy (SMSE) and vertical velocity at the mid-troposphere. It is found that onset occurs only after SMSE crosses a threshold value and the large-scale vertical motion in the middle troposphere becomes upward. This study shows that both dynamics and thermodynamics play profound roles in the onset of the monsoon.

scholarly journals A description of the FAMOUS (version XDBUA) climate model and control run

2008 ◽  
Vol 1 (1) ◽  
pp. 53-68 ◽  
Author(s):  
R. S. Smith ◽  
J. M. Gregory ◽  
A. Osprey
Keyword(s):  
General Circulation ◽  
High Performance ◽  
Climate Model ◽  
Computational Cost ◽  
Circulation Model ◽  
Cold Bias ◽  
Northern Latitudes ◽  
Climate Simulations ◽  
Atmosphere General Circulation Model ◽  
And Control

Abstract. FAMOUS is an ocean-atmosphere general circulation model of low resolution, capable of simulating approximately 120 years of model climate per wallclock day using current high performance computing facilities. It uses most of the same code as HadCM3, a widely used climate model of higher resolution and computational cost, and has been tuned to reproduce the same climate reasonably well. FAMOUS is useful for climate simulations where the computational cost makes the application of HadCM3 unfeasible, either because of the length of simulation or the size of the ensemble desired. We document a number of scientific and technical improvements to the original version of FAMOUS. These improvements include changes to the parameterisations of ozone and sea-ice which alleviate a significant cold bias from high northern latitudes and the upper troposphere, and the elimination of volume-averaged drifts in ocean tracers. A simple model of the marine carbon cycle has also been included. A particular goal of FAMOUS is to conduct millennial-scale paleoclimate simulations of Quaternary ice ages; to this end, a number of useful changes to the model infrastructure have been made.

scholarly journals An efficient method to generate a perturbed parameter ensemble of a fully coupled AOGCM without flux-adjustment

2013 ◽  
Vol 6 (5) ◽  
pp. 1447-1462 ◽  
Author(s):  
P. J. Irvine ◽  
L. J. Gregoire ◽  
D. J. Lunt ◽  
P. J. Valdes
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Parametric Uncertainty ◽  
Ocean General Circulation Model ◽  
Reanalysis Data ◽  
Entrainment Rate ◽  
Industrial Control ◽  
Simple Method ◽  
Fully Coupled ◽  
Flux Adjustment

Abstract. We present a simple method to generate a perturbed parameter ensemble (PPE) of a fully-coupled atmosphere-ocean general circulation model (AOGCM), HadCM3, without requiring flux-adjustment. The aim was to produce an ensemble that samples parametric uncertainty in some key variables and gives a plausible representation of the climate. Six atmospheric parameters, a sea-ice parameter and an ocean parameter were jointly perturbed within a reasonable range to generate an initial group of 200 members. To screen out implausible ensemble members, 20 yr pre-industrial control simulations were run and members whose temperature responses to the parameter perturbations were projected to be outside the range of 13.6 ± 2 °C, i.e. near to the observed pre-industrial global mean, were discarded. Twenty-one members, including the standard unperturbed model, were accepted, covering almost the entire span of the eight parameters, challenging the argument that without flux-adjustment parameter ranges would be unduly restricted. This ensemble was used in 2 experiments; an 800 yr pre-industrial and a 150 yr quadrupled CO2 simulation. The behaviour of the PPE for the pre-industrial control compared well to ERA-40 reanalysis data and the CMIP3 ensemble for a number of surface and atmospheric column variables with the exception of a few members in the Tropics. However, we find that members of the PPE with low values of the entrainment rate coefficient show very large increases in upper tropospheric and stratospheric water vapour concentrations in response to elevated CO2 and one member showed an implausible nonlinear climate response, and as such will be excluded from future experiments with this ensemble. The outcome of this study is a PPE of a fully-coupled AOGCM which samples parametric uncertainty and a simple methodology which would be applicable to other GCMs.

Statistical downscaling of general circulation model outputs to catchment scale hydroclimatic variables: issues, challenges and possible solutions

2014 ◽  
Vol 5 (4) ◽  
pp. 496-525 ◽  
Author(s):  
D. A. Sachindra ◽  
F. Huang ◽  
A. Barton ◽  
B. J. C. Perera
Keyword(s):  
General Circulation Model ◽  
Statistical Downscaling ◽  
General Circulation ◽  
Circulation Model ◽  
Potential Method ◽  
Mathematical Representation ◽  
Physical Processes ◽  
Catchment Scale ◽  
Scenario Uncertainty ◽  
Hydroclimatic Variables

The aim of this paper is to discuss the issues and challenges associated with statistical downscaling of general circulation model (GCM) outputs to hydroclimatic variables at catchment scale and also to discuss potential solutions to address these issues and challenges. Outputs of GCMs (predictors of statistical downscaling models) suffer a considerable degree of uncertainty, mainly due to the lack of theoretical robustness caused by the limited understanding of various physical processes of the atmosphere and the incomplete mathematical representation of those processes in GCMs. The presence of several future GHG emission scenarios with equal likelihood of occurrence leads to scenario uncertainty. Outputs of a downscaling study are dependent on the quality and the length of the record of field observations, as statistical downscaling models are calibrated and validated against these observations of the hydroclimatic variables (predictands of statistical downscaling models). The downscaled results vary from one statistical downscaling technique to another due to different representations of the predictor–predictand relationships. Also different techniques used in selecting the predictors for statistical downscaling models influence the model outputs. Although statistical downscaling faces these issues, it is still considered as a potential method of predicting the catchment scale hydroclimatology from GCM outputs.

scholarly journals Design and Performance Analysis of a Massively Parallel Atmospheric General Circulation Model

2000 ◽  
Vol 8 (1) ◽  
pp. 49-57 ◽  
Author(s):  
Daniel S. Schaffer ◽  
Max J. Suárez
Keyword(s):  
General Circulation Model ◽  
General Circulation ◽  
High Performance ◽  
Degrees Of Freedom ◽  
Parallel Machines ◽  
Atmospheric General Circulation Model ◽  
Circulation Model ◽  
Massively Parallel ◽  
Atmospheric General Circulation ◽  
And Performance

In the 1990's, computer manufacturers are increasingly turning to the development of parallel processor machines to meet the high performance needs of their customers. Simultaneously, atmospheric scientists studying weather and climate phenomena ranging from hurricanes to El Niño to global warming require increasingly fine resolution models. Here, implementation of a parallel atmospheric general circulation model (GCM) which exploits the power of massively parallel machines is described. Using the horizontal data domain decomposition methodology, this FORTRAN 90 model is able to integrate a 0.6° longitude by 0.5° latitude problem at a rate of 19 Gigaflops on 512 processors of a Cray T3E 600; corresponding to 280 seconds of wall-clock time per simulated model day. At this resolution, the model has 64 times as many degrees of freedom and performs 400 times as many floating point operations per simulated day as the model it replaces.

Anthropogenic Aerosols Dominate Forced Multidecadal Sahel Precipitation Change through Distinct Atmospheric and Oceanic Drivers

2020 ◽  
Vol 33 (23) ◽  
pp. 10187-10204
Author(s):  
Haruki Hirasawa ◽  
Paul J. Kushner ◽  
Michael Sigmond ◽  
John Fyfe ◽  
Clara Deser
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Forced Response ◽  
Sea Surface ◽  
Atmospheric Response ◽  
Anthropogenic Aerosols ◽  
Coupled General Circulation Model ◽  
Large Ensembles ◽  
Primary Driver ◽  
Sahel Precipitation

AbstractSahel precipitation has undergone substantial multidecadal time scale changes during the twentieth century that have had severe impacts on the region’s population. Using initial-condition large ensembles (LE) of coupled general circulation model (GCM) simulations from two institutions, forced multidecadal variability is found in which Sahel precipitation declines from the 1950s to 1970s and then recovers from the 1970s to 2000s. This forced variability has similar timing to, but considerably smaller magnitude than, observed Sahel precipitation variability. Isolating the response using single forcing simulations within the LEs reveals that anthropogenic aerosols (AA) are the primary driver of this forced variability. The roles of the direct-atmospheric and the ocean-mediated atmospheric responses to AA forcing are determined with the atmosphere–land GCM (AGCM) components of the LE coupled GCMs. The direct-atmospheric response arises from changes to aerosol and precursor emissions with unchanged oceanic boundary conditions while the ocean-mediated response arises from changes to AA-forced sea surface temperatures and sea ice concentrations diagnosed from the AA-forced LE. In the AGCMs studied here, the direct-atmospheric response dominates the AA-forced 1970s − 1950s Sahel drying. On the other hand, the 2000s − 1970s wetting is mainly driven by the ocean-mediated effect, with some direct atmospheric contribution. Although the responses show differences, there is qualitative agreement between the AGCMs regarding the roles of the direct-atmospheric and ocean-mediated responses. Since these effects often compete and show nonlinearity, the model dependence of these effects and their role in the net aerosol-forced response of Sahel precipitation need to be carefully accounted for in future model analysis.

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