Program For Climate Model Diagnosis And Intercomparison Research Articles

Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3

Abstract. Systematic, routine, and comprehensive evaluation of Earth system models (ESMs) facilitates benchmarking improvement across model generations and identifying the strengths and weaknesses of different model configurations. By gauging the consistency between models and observations, this endeavor is becoming increasingly necessary to objectively synthesize the thousands of simulations contributed to the Coupled Model Intercomparison Project (CMIP) to date. The Program for Climate Model Diagnosis and Intercomparison (PCMDI) Metrics Package (PMP) is an open-source Python software package that provides quick-look objective comparisons of ESMs with one another and with observations. The comparisons include metrics of large- to global-scale climatologies, tropical inter-annual and intra-seasonal variability modes such as the El Niño–Southern Oscillation (ENSO) and Madden–Julian Oscillation (MJO), extratropical modes of variability, regional monsoons, cloud radiative feedbacks, and high-frequency characteristics of simulated precipitation, including its extremes. The PMP comparison results are produced using all model simulations contributed to CMIP6 and earlier CMIP phases. An important objective of the PMP is to document the performance of ESMs participating in the recent phases of CMIP, together with providing version-controlled information for all datasets, software packages, and analysis codes being used in the evaluation process. Among other purposes, this also enables modeling groups to assess performance changes during the ESM development cycle in the context of the error distribution of the multi-model ensemble. Quantitative model evaluation provided by the PMP can assist modelers in their development priorities. In this paper, we provide an overview of the PMP, including its latest capabilities, and discuss its future direction.

Erratum to: Spatial variations of sea-level rise and impacts: An application of DIVA

Acknowledgments Brown and Nicholls were supported by the UK Natural Environment Research Council(NERC), under the QUEST programme (grant number NE/E001882/1). Lowe was supported by the AVOIDprogramme (DECC and Defra) under contract GA0215.For the sea-level rise patterns we acknowledge the international modelling groups for providing their datafor analysis, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) for collecting andarchiving the model data, the JSC/CLIVAR Working Group on Coupled Modelling (WGCM) and theirCoupled Model Intercomparison Project (CMIP) and Climate Simulation Panel for organising the model dataanalysis activity, and the IPCC WG1 TSU for technical support. The IPCC Data Archive at LawrenceLivermore National Laboratory is supported by the Office of Science, US Department of Energy.We thank Anne Pardaens and Ivan Haigh for comments and assistance in constructing the sea-level risescenarios.Climatic ChangeDOI 10.1007/s10584-013-0991-1The online version of the original article can be found at http://dx.doi.org/10.1007/s10584-013-0925-y.S. Brown (*)

STATISTICAL SURROGATE MODELS FOR PREDICTION OF HIGH-CONSEQUENCE CLIMATE CHANGE

In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the lowprobability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest. An SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the program for climate model diagnosis and intercomparison (PCMDI), or to a collection of outputs from a general circulation model (GCM), e.g., the community Earth system model (CESM) and its predecessors. Because of its reduced size and complexity, the realization of a large number of independent model outputs from an SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.

Quality assessment concept of the World Data Center for Climate and its application to CMIP5 data

Abstract. The preservation of data in a high state of quality which is suitable for interdisciplinary use is one of the most pressing and challenging current issues in long-term archiving. For high volume data such as climate model data, the data and data replica are no longer stored centrally but distributed over several local data repositories, e.g. the data of the Climate Model Intercomparison Project Phase 5 (CMIP5). The most important part of the data is to be archived, assigned a DOI, and published according to the World Data Center for Climate's (WDCC) application of the DataCite regulations. The integrated part of WDCC's data publication process, the data quality assessment, was adapted to the requirements of a federated data infrastructure. A concept of a distributed and federated quality assessment procedure was developed, in which the workload and responsibility for quality control is shared between the three primary CMIP5 data centers: Program for Climate Model Diagnosis and Intercomparison (PCMDI), British Atmospheric Data Centre (BADC), and WDCC. This distributed quality control concept, its pilot implementation for CMIP5, and first experiences are presented. The distributed quality control approach is capable of identifying data inconsistencies and to make quality results immediately available for data creators, data users and data infrastructure managers. Continuous publication of new data versions and slow data replication prevents the quality control from check completion. This together with ongoing developments of the data and metadata infrastructure requires adaptations in code and concept of the distributed quality control approach.

The Earth System Grid Federation: Delivering globally accessible petascale data for CMIP5

The fifth Coupled Model Intercomparison Project (CMIP5) will involve the global production and analysis of petabytes of data. The Program for Climate Model Diagnosis and Intercomparison (PCMDI), with responsibility for archival for CMIP5, has established the global “Earth System Grid Federation” (ESGF) of data producers and data archives to support CMIP5. ESGF will provide a set of globally synchronised views of globally distributed data – including some large cache replicants which will be persisted for (at least) decades. Here we describe the archive requirements and key aspects of the resulting architecture. ESGF will stress international networks, as well as the data archives themselves – but significantly less than would have been the case of a centralised archive. Developing and deploying the ESGF has exploited good will and best efforts, but future developments are likely to require more formalised architecture and management.

New Results on the Thermodynamic Properties of the Climate System

Abstract In this paper the authors exploit two equivalent formulations of the average rate of material entropy production in the climate system to propose an approximate splitting between contributions due to vertical and eminently horizontal processes. This approach is based only on 2D radiative fields at the surface and at the top of atmosphere. Using 2D fields at the top of atmosphere alone, lower bounds to the rate of material entropy production and to the intensity of the Lorenz energy cycle are derived. By introducing a measure of the efficiency of the planetary system with respect to horizontal thermodynamic processes, it is possible to gain insight into a previous intuition on the possibility of defining a baroclinic heat engine extracting work from the meridional heat flux. The approximate formula of the material entropy production is verified and used for studying the global thermodynamic properties of climate models (CMs) included in the Program for Climate Model Diagnosis and Intercomparison (PCMDI)/phase 3 of the Coupled Model Intercomparison Project (CMIP3) dataset in preindustrial climate conditions. It is found that about 90% of the material entropy production is due to vertical processes such as convection, whereas the large-scale meridional heat transport contributes to only about 10% of the total. This suggests that the traditional two-box models used for providing a minimal representation of entropy production in planetary systems are not appropriate, whereas a basic—but conceptually correct—description can be framed in terms of a four-box model. The total material entropy production is typically 55 mW m−2 K−1, with discrepancies on the order of 5%, and CMs’ baroclinic efficiencies are clustered around 0.055. The lower bounds on the intensity of the Lorenz energy cycle featured by CMs are found to be around 1.0–1.5 W m−2, which implies that the derived inequality is rather stringent. When looking at the variability and covariability of the considered thermodynamic quantities, the agreement among CMs is worse, suggesting that the description of feedbacks is more uncertain. The contributions to material entropy production from vertical and horizontal processes are positively correlated, so that no compensation mechanism seems in place. Quite consistently among CMs, the variability of the efficiency of the system is a better proxy for variability of the entropy production due to horizontal processes than that of the large-scale heat flux. The possibility of providing constraints on the 3D dynamics of the fluid envelope based only on 2D observations of radiative fluxes seems promising for the observational study of planets and for testing numerical models.

Improving use of satellite data in evaluating climate models

U.S. Department of Energy—NASA Workshop; Livermore, California, 12–13 October 2010; Observations are essential for the development and evaluation of climate models, and satellite measurements provide uniquely comprehensive data for both purposes. The objective of a recent U.S. Department of Energy—NASA workshop was to better enable a diverse research community to exploit the wealth of NASA products that are relevant for climate model evaluation. The meeting brought together data experts from 20 NASA instrument and data teams with the staff of Lawrence Livermore National Laboratory's Program for Climate Model Diagnosis and Intercomparison (PCMDI).

Celebrating Two Decades of the Program for Climate Model Diagnosis and Intercomparison

No Abstract available.

Antarctic precipitation and climate-change predictions: horizontal resolution and margin vs plateau issues

AbstractAll climate models participating in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, as made available by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) as the Coupled Model Intercomparison Project 3 (CMIP3) archive, predict a significant surface warming of Antarctica by the end of the 21st century under a moderate (SRESA1B) greenhouse-gas scenario. All models but one predict a concurrent precipitation increase but with a large scatter of results. The models with finer horizontal resolution tend to predict a larger precipitation increase. Because modeled Antarctic surface mass balance is known to be sensitive to horizontal resolution, extrapolating predictions from the different models with respect to model resolution may provide simple yet better multi-model estimates of Antarctic precipitation change than mere averaging or even more complex approaches. Using such extrapolation, a conservative estimate of the predicted precipitation increase at the end of the 21st century is +30 kg m–2 a–1 on the grounded ice sheet, corresponding to a >1m ma–1 sea-level rise. About three-quarters of this rise originates from the marginal regions of the Antarctic ice sheet with surface elevation below 2250 m. This is where field programs are most urgently needed to better understand and monitor accumulation at the surface of Antarctica, and to improve and verify prediction models.

Mesh Climate Change Data of Japan Ver.2 for Climate Change Impact Assessments Under IPCC SRES A1B and A2

The Intergovernmental Panel on Climate Change (IPCC) published the Fourth Assessment Report (AR4) in 2007 and stated that recent climate change and variation are induced by increases in the atmospheric greenhouse gases (GHG) concentration due to anthropogenic activities. The report includes the results of impact assessments on a wide range of sectors. These assessments have been conducted based on future climate projections, which refer to aspects of the future climate evaluated by Atmosphere-Ocean Coupled General Circulation Models (CGCMs). The projection data used in the AR4 are archived under the Program for Climate Model Diagnosis and Intercomparison (PCMDI) promoted by the U.S. Department of Energy. We interpolated the projection data around Japan and constructed a dataset entitled the “Mesh climate change data of Japan Ver. 2” for the climate change impact study. Nine projections performed by seven models under the A1B and A2 of the Special Report on Emissions Scenarios (SRES) were implemented for the dataset. They consist of mesh data with a size of 7.5′ in longitude and 5.0′ in latitude, i.e. approximately 10×10 km (45″ in longitude and 30″ in latitude, approximately 1×1 km, for one high-resolution model). The dataset includes five climatic elements, i.e. the daily mean, maximum, and minimum surface air temperatures, daily total precipitation, and daily accumulated shortwave radiation for three periods, 1981-2000, 2046-2065, and 2081-2100. This article describes the details concerning the construction and characteristics of the data.

Results from the carbon-land model intercomparison project (C-LAMP) and availability of the data on the earth system grid (ESG)

This paper describes the Carbon-Land Model Intercomparison Project (C-LAMP) being carried out through a collaboration between the Community Climate System Model (CCSM) Biogeochemistry Working Group, a DOE SciDAC-2 project, and the DOE Program for Climate Model Diagnosis and Intercomparison (PCMDI). The goal of the project is to intercompare terrestrial biogeochemistry models running within the CCSM framework to determine the best set of processes to include in future versions of CCSM. As a part of the project, observational datasets are being collected and used to score the scientific performance of these models following a well-defined set of metrics. In addition, metadata standards for terrestrial biosphere models are being developed to support archival and distribution of the C-LAMP model output via the Earth System Grid (ESG). Progress toward completion of this project and preliminary results from the first set of experiments are reported.

Coupled Climate Model appraisal: A benchmark for future studies

Studies of future climate scenarios, such as those conducted in support of the Intergovernmental Panel on Climate Change (IPCC, http://www.ipcc.ch/), rely heavily on numerical experiments performed with coupled ocean‐atmosphere general circulation models (OAGCMs). In order to assess the results of such climate change experiments, a benchmark for evaluating model performance is required.To provide this benchmark, Lawrence Livermore National Laboratory's Program for Climate Model Diagnosis and Intercomparison (PCMDI) conducted an extensive appraisal of multidecadal climate simulations by 11 coupled OAGCMs that were developed during the period of 1995–2002 [Bader etal., 2004].While diverse representations of atmosphere, ocean, sea ice, land, and of their respective couplings were employed (see Table 1), all of these climate models were run with current values of solar and greenhouse gas radiative forcings. Thus, by comparing details of the OAGCM simulations with analogous facets of climate observations, the needed model‐performance benchmark can be obtained. If, for instance, a model simulation closely replicates the salient features of the present climate, a necessary (though not sufficient) condition is met for placing some confidence in the model's projections of the climate of the next several decades.

The New GFDL Global Atmosphere and Land Model AM2–LM2: Evaluation with Prescribed SST Simulations

Abstract The configuration and performance of a new global atmosphere and land model for climate research developed at the Geophysical Fluid Dynamics Laboratory (GFDL) are presented. The atmosphere model, known as AM2, includes a new gridpoint dynamical core, a prognostic cloud scheme, and a multispecies aerosol climatology, as well as components from previous models used at GFDL. The land model, known as LM2, includes soil sensible and latent heat storage, groundwater storage, and stomatal resistance. The performance of the coupled model AM2–LM2 is evaluated with a series of prescribed sea surface temperature (SST) simulations. Particular focus is given to the model's climatology and the characteristics of interannual variability related to E1 Niño– Southern Oscillation (ENSO). One AM2–LM2 integration was performed according to the prescriptions of the second Atmospheric Model Intercomparison Project (AMIP II) and data were submitted to the Program for Climate Model Diagnosis and Intercomparison (PCMDI). Particular strengths of AM2–LM2, as judged by comparison to other models participating in AMIP II, include its circulation and distributions of precipitation. Prominent problems of AM2– LM2 include a cold bias to surface and tropospheric temperatures, weak tropical cyclone activity, and weak tropical intraseasonal activity associated with the Madden–Julian oscillation. An ensemble of 10 AM2–LM2 integrations with observed SSTs for the second half of the twentieth century permits a statistically reliable assessment of the model's response to ENSO. In general, AM2–LM2 produces a realistic simulation of the anomalies in tropical precipitation and extratropical circulation that are associated with ENSO.