Preprocessing of hydrological models’ input in eWaterCycle with ESMValTool

Hydrological models exhibit great complexity and diversity in the exact methodologies applied, competing for hypotheses of hydrologic behaviour, technology stacks, and programming languages used in those models. The preprocessing of forcing (meteorological) data is often performed by various sets of scripts that may or may not be included with model source codes, making it hard to reproduce results. Moreover, forcing data can be retrieved from a wide variety of forcing products with discrepant variable names and frequencies, spatial and temporal resolutions, and spatial coverage. Even though there is an infinite amount of preprocessing scripts for different models, these preprocessing scripts use only a limited set of operations, mainly re-gridding, temporal and spatial manipulations, variable derivation, and unit conversion. Also, these exact same preprocessing functions are used in analysis and evaluation of output from Earth system models in climate science.Within the context of the eWaterCycle II project (https://www.ewatercycle.org/), a common preprocessing system has been created for hydrological modelling based on ESMValTool (Earth System Model Evaluation Tool). ESMValTool is a community-driven diagnostic and performance metrics tool that supports a broad range of preprocessing functions. Using a YAML script called a recipe, instructions are provided to ESMValTool: the datasets which need to be analyzed, the preprocessors that need to be applied, and the model-specific analysis (i.e. diagnostic script) which need to be run on data. ESMValTool is modular and flexible so all preprocessing functions can also be used directly in a Python script and additional analyses can easily be added.The current preprocessing pipeline of the eWaterCycle using ESMValTool consists of hydrological model-specific scripts and supports ERA5 and ERA-Interim data provided by the ECMWF (European Centre for Medium-Range Weather Forecasts), as well as CMIP5 and CMIP6 climate model data. The pipeline starts with the downloading and CMORization (Climate Model Output Rewriter) of input data. Then a recipe is prepared to find the data and run the preprocessors. When ESMValTool runs a recipe, it produces preprocessed data that can be passed as input to a hydrological model. It will also store provenance and citation information to ensure transparency and reproducibility. This leads to less time spent on building custom preprocessing, more reproducible and comparable hydrological science.In this presentation, we will give an overview of the current preprocessing pipeline of the eWaterCycle, outline ESMValTool preprocessing functions, and introduce available hydrological recipes and diagnostic scripts for the PCRGLOB, WFLOW, HYPE, MARRMOT and LISFLOOD models.

Download Full-text

ESMValTool pre-processing functions for eWaterCycle

10.5194/egusphere-egu2020-14745 ◽

2020 ◽

Author(s):

Fakhereh Alidoost ◽

Jerom Aerts ◽

Bouwe Andela ◽

Jaro Camphuijsen ◽

Nick van De Giesen ◽

...

Keyword(s):

Input Data ◽

Hydrological Modeling ◽

Performance Metrics ◽

Climate Model ◽

Processing System ◽

Observation Data ◽

Hydrological Models ◽

Earth System ◽

Evaluation Tool ◽

The Impact

eWaterCycle is a framework in which hydrological modelers can work together in a collaborative environment. In this environment, they can, for example, compare and analyze the results of models that use different sources of (meteorological) forcing data. The final goal of eWaterCycle is to advance the state of FAIR (Findable, Accessible, Interoperable, and Reusable) and open science in hydrological modeling.Comparing hydrological models has always been a challenging task. Hydrological models exhibit great complexity and diversity in the exact methodologies applied, competing for hypotheses of hydrologic behavior, technology stacks, and programming languages used in those models. Pre-processing of forcing data is one of the roadblocks that was identified during the FAIR Hydrological Modelling workshop organized by the Lorentz Center in April 2019. Forcing data can be retrieved from a wide variety of sources with discrepant variable names and frequencies, and spatial and temporal resolutions. Moreover, some hydrological models make specific assumptions about the definition of the forcing variables. The pre-processing is often performed by various sets of scripts that may or may not be included with model source codes, making it hard to reproduce results. Generally, there are common steps in the data preparation among different models. Therefore, it would be a valuable asset to the hydrological community if the pre-processing of FAIR input data could also be done in a FAIR manner.Within the context of the eWaterCycle II project, a common pre-processing system has been created for hydrological modeling based on ESMValTool (Earth System Model Evaluation Tool). ESMValTool is a community diagnostic and performance metrics tool developed for the evaluation of Earth system models. The ESMValTool pre-processing functions cover a broad range of operations on data before diagnostics or metrics are applied; for example, vertical interpolation, land-sea masking, re-gridding, multi-model statistics, temporal and spatial manipulations, variable derivation and unit conversion. The pre-processor performs these operations in a centralized, documented and efficient way. The current pre-processing pipeline of the eWaterCycle using ESMValTool consists of hydrological model-specific recipes and supports ERA5 and ERA-Interim data provided by the ECMWF (European Centre for Medium-Range Weather Forecasts). The pipeline starts with the downloading and CMORization (Climate Model Output Rewriter) of input data. Then a recipe is prepared to find the data and run the preprocessors. When ESMValTool runs a recipe, it will also run the diagnostic script that contains model-specific analysis to derive required forcing variables, and it will store provenance information to ensure transparency and reproducibility. In the near future, the pipeline is extended to include Earth observation data, as these data are paramount to the data assimilation in eWaterCycle.In this presentation we will show how using the pre-processor from ESMValTool for Hydrological modeling leads to connecting Hydrology and Climate sciences, and increase the impact and sustainability of ESMValTool.

Download Full-text

Recent developments on the Earth System Model Evaluation Tool

10.5194/egusphere-egu21-3476 ◽

2021 ◽

Author(s):

Bouwe Andela ◽

Fakhereh Alidoost ◽

Lukas Brunner ◽

Jaro Camphuijsen ◽

Bas Crezee ◽

...

Keyword(s):

Model Evaluation ◽

Performance Metrics ◽

Climate Model ◽

Earth System Model ◽

System Model ◽

Earth System ◽

Evaluation Tool ◽

Scientific Review ◽

The Earth ◽

User Friendly

The Earth System Model Evaluation Tool (ESMValTool) is a free and open-source community diagnostic and performance metrics tool for the evaluation of Earth system models such as those participating in the Coupled Model Intercomparison Project (CMIP). Version 2 of the tool (Righi et al. 2020, www.esmvaltool.org) features a brand new design composed of a core that finds and processes data according to a &#8216;recipe&#8217; and an extensive collection of ready-to-use recipes and associated diagnostic codes for reproducing results from published papers. Development and discussion of the tool (mostly) takes place in public on https://github.com/esmvalgroup and anyone with an interest in climate model evaluation is welcome to join there.&#160;Since the initial release of version 2 in the summer of 2020, many improvements have been made to the tool. It is now more user friendly with extensive documentation available on docs.esmvaltool.org and a step by step online tutorial. Regular releases, currently planned three times a year, ensure that recent contributions become available quickly while still ensuring a high level of quality control. The tool can be installed from conda, but portable docker and singularity containers are also available.&#160;Recent new features include a more user-friendly command-line interface, citation information per figure including CMIP6 data citation using ES-DOC, more and faster preprocessor functions that require less memory, automatic corrections for a larger number of CMIP6 datasets, support for more observational and reanalysis datasets, and more recipes and diagnostics.&#160;The tool is now also more reliable, with improved automated testing through more unit tests for the core, as well as a recipe testing service running at DKRZ for testing the scientific recipes and diagnostics that are bundled into the tool. The community maintaining and developing the tool is growing, making the project less dependent on individual contributors. There are now technical and scientific review teams that review new contributions for technical quality and scientific correctness and relevance respectively, two new principal investigators for generating a larger support base in the community, and a newly created user engagement team that is taking care of improving the overall user experience.

Download Full-text

Earth System Model Evaluation Tool (ESMValTool) v2.0 – an extended set of large-scale diagnostics for quasi-operational and comprehensive evaluation of Earth system models in CMIP

Geoscientific Model Development ◽

10.5194/gmd-13-3383-2020 ◽

2020 ◽

Vol 13 (7) ◽

pp. 3383-3438 ◽

Cited By ~ 10

Author(s):

Veronika Eyring ◽

Lisa Bock ◽

Axel Lauer ◽

Mattia Righi ◽

Manuel Schlund ◽

...

Keyword(s):

Model Evaluation ◽

Large Scale ◽

Performance Metrics ◽

Earth System Model ◽

System Model ◽

Earth System ◽

Evaluation Tool ◽

The Earth ◽

And Performance ◽

Earth System Models

Abstract. The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of Earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility. It consists of (1) an easy-to-install, well-documented Python package providing the core functionalities (ESMValCore) that performs common preprocessing operations and (2) a diagnostic part that includes tailored diagnostics and performance metrics for specific scientific applications. Here we describe large-scale diagnostics of the second major release of the tool that supports the evaluation of ESMs participating in CMIP Phase 6 (CMIP6). ESMValTool v2.0 includes a large collection of diagnostics and performance metrics for atmospheric, oceanic, and terrestrial variables for the mean state, trends, and variability. ESMValTool v2.0 also successfully reproduces figures from the evaluation and projections chapters of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and incorporates updates from targeted analysis packages, such as the NCAR Climate Variability Diagnostics Package for the evaluation of modes of variability, the Thermodynamic Diagnostic Tool (TheDiaTo) to evaluate the energetics of the climate system, as well as parts of AutoAssess that contains a mix of top–down performance metrics. The tool has been fully integrated into the Earth System Grid Federation (ESGF) infrastructure at the Deutsches Klimarechenzentrum (DKRZ) to provide evaluation results from CMIP6 model simulations shortly after the output is published to the CMIP archive. A result browser has been implemented that enables advanced monitoring of the evaluation results by a broad user community at much faster timescales than what was possible in CMIP5.

Download Full-text

The EC-Earth3 Earth System Model for the Climate Model Intercomparison Project 6

10.5194/gmd-2020-446 ◽

2021 ◽

Cited By ~ 3

Author(s):

Ralf Döscher ◽

Mario Acosta ◽

Andrea Alessandri ◽

Peter Anthoni ◽

Almut Arneth ◽

...

Keyword(s):

Physical Performance ◽

Performance Metrics ◽

Climate Model ◽

Earth System Model ◽

System Model ◽

Historical Period ◽

Earth System ◽

Dynamic Features ◽

The Earth ◽

Intercomparison Project

Abstract. The Earth System Model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different HPC systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behaviour and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.

Download Full-text

Effects of climate model radiation, humidity and wind estimates on hydrological simulations

Hydrology and Earth System Sciences ◽

10.5194/hess-16-305-2012 ◽

2012 ◽

Vol 16 (2) ◽

pp. 305-318 ◽

Cited By ~ 62

Author(s):

I. Haddeland ◽

J. Heinke ◽

F. Voß ◽

S. Eisner ◽

C. Chen ◽

...

Keyword(s):

Bias Correction ◽

Large Scale ◽

Climate Models ◽

Climate Model ◽

Meteorological Data ◽

Correction Method ◽

Hydrological Models ◽

Temperature And Precipitation ◽

Effects Of Radiation ◽

Precipitation And Temperature

Abstract. Due to biases in the output of climate models, a bias correction is often needed to make the output suitable for use in hydrological simulations. In most cases only the temperature and precipitation values are bias corrected. However, often there are also biases in other variables such as radiation, humidity and wind speed. In this study we tested to what extent it is also needed to bias correct these variables. Responses to radiation, humidity and wind estimates from two climate models for four large-scale hydrological models are analysed. For the period 1971–2000 these hydrological simulations are compared to simulations using meteorological data based on observations and reanalysis; i.e. the baseline simulation. In both forcing datasets originating from climate models precipitation and temperature are bias corrected to the baseline forcing dataset. Hence, it is only effects of radiation, humidity and wind estimates that are tested here. The direct use of climate model outputs result in substantial different evapotranspiration and runoff estimates, when compared to the baseline simulations. A simple bias correction method is implemented and tested by rerunning the hydrological models using bias corrected radiation, humidity and wind values. The results indicate that bias correction can successfully be used to match the baseline simulations. Finally, historical (1971–2000) and future (2071–2100) model simulations resulting from using bias corrected forcings are compared to the results using non-bias corrected forcings. The relative changes in simulated evapotranspiration and runoff are relatively similar for the bias corrected and non bias corrected hydrological projections, although the absolute evapotranspiration and runoff numbers are often very different. The simulated relative and absolute differences when using bias corrected and non bias corrected climate model radiation, humidity and wind values are, however, smaller than literature reported differences resulting from using bias corrected and non bias corrected climate model precipitation and temperature values.

Download Full-text

A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-7-7191-2010 ◽

2010 ◽

Vol 7 (5) ◽

pp. 7191-7229 ◽

Cited By ~ 3

Author(s):

S. N. Gosling ◽

R. G. Taylor ◽

N. W. Arnell ◽

M. C. Todd

Keyword(s):

Climate Change ◽

Hydrological Model ◽

Climate Model ◽

Annual Runoff ◽

Structural Uncertainty ◽

Hydrological Models ◽

Catchment Scale ◽

Monthly Runoff ◽

Global Mean ◽

Impacts Of Climate Change

Abstract. We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and developmental conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangxi (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs include SLURP v. 12.2 (Liard), SLURP v. 12.7 (Mekong), Pitman (Okavango), MGB-IPH (Rio Grande), AV-SWAT-X 2005 (Xiangxi) and Cat-PDM (Harper's Brook). Simulations of mean annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961–1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global-mean air temperature of 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 °C relative to baseline from the UKMO HadCM3 Global Climate Model (GCM) to explore response to different amounts of climate forcing, and (2) a prescribed increase in global-mean air temperature of 2.0 °C relative to baseline for seven GCMs to explore response to climate model structural uncertainty. We find that the differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM, and they are generally larger for indicators of high and low monthly runoff. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are represented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs. This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evapotranspiration estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme (Q5, Q95) monthly runoff, all of which have implications for future water management issues.

Download Full-text

Model evaluation expectations of European ESM communities: results from a survey

10.5194/egusphere-egu21-15681 ◽

2021 ◽

Author(s):

Jerome Servonnat ◽

Eric Guilyardi ◽

Zofia Stott ◽

Kim Serradell ◽

Axel Lauer ◽

...

Keyword(s):

Model Evaluation ◽

Common Ground ◽

Performance Metrics ◽

Coupled Model ◽

System Modelling ◽

Earth System ◽

Evaluation Tool ◽

Technical Standards ◽

Community Effort ◽

And Performance

Developing an Earth system model evaluation tool for a broad user community is a real challenge, as the potential users do not necessarily have the same needs or expectations. While many evaluation tasks across user communities include common steps, significant differences are also apparent, not least the investment by institutions and individuals in bespoke tools. A key question is whether there is sufficient common ground to pursue a community tool with broad appeal and application.We present the main results of a survey carried out by Assimila for the H2020 IS-ENES3 project to review the model evaluation needs of European Earth System Modelling communities. Interviewing approximately 30 participants among several European institutions, the survey targeted a broad range of users, including model developers, model users, evaluation data providers, and infrastructure providers. The output of the study provides an analysis of&#160; requirements focusing on key technical, standards, and governance aspects.The study used ESMValTool as a&#160; current benchmark in terms of European evaluation tools. It is a community diagnostics and performance metrics tool for the evaluation of Earth System Models that allows for comparison of single or multiple models, either against predecessor versions or against observations. The tool is being developed in such a way that additional analyses can be added. As a community effort open to both users and developers, it encourages open exchange of diagnostic source code and evaluation results. It is currently used in Coupled Model Intercomparison Projects as well as for the development and testing of &#8220;new&#8221; models.A key result of the survey is the widespread support for ESMValTool amongst users, developers, and even those who have taken or promote other approaches. The results of the survey identify priorities and opportunities in the further development of the ESMValTool to ensure long-term adoption of the tool by a broad community.

Download Full-text

Towards Open and FAIR Hydrological Modelling with eWaterCycle

10.5194/egusphere-egu21-7797 ◽

2021 ◽

Author(s):

Niels Drost ◽

Jerom P.M. Aerts ◽

Fakhereh Alidoost ◽

Bouwe Andela ◽

Jaro Camphuijsen ◽

...

Keyword(s):

Ad Hoc ◽

Hydrological Model ◽

Climate Model ◽

Hydrological Modelling ◽

Analysis Tool ◽

Hydrological Models ◽

Software Environment ◽

Processing Pipeline ◽

Basic Model ◽

Input Processing

The eWaterCycle platform (https://www.ewatercycle.org/) is a fully Open Source system designed explicitly to advance the state of Open and FAIR Hydrological modelling. While working with Hydrologists to create a fully Open and FAIR comparison study, we noticed that many ad-hoc tools and scripts are used to create input (forcing, parameters) for a hydrological model from the source datasets such as climate reanalysis and land-use data. To make this part of the modelling process better reproducible and more transparent we have created a common forcing input processing pipeline based on an existing climate model analysis tool: ESMValTool (https://www.esmvaltool.org/).&#160;Using ESMValTool, the eWaterCycle platform can perform commonly required preprocessing steps such as cropping, re-gridding, and variable derivation in a standardized manner. If needed, it also allows for custom steps for a hydrological model. Our pre-processing pipeline directly supports commonly used datasets such as ERA-5, ERA-Interim, and CMIP climate model data, and creates ready-to-run forcing data for a number of Hydrological models.Besides creating forcing data, the eWaterCycle platform allows scientists to run Hydrological models in a standardized way using Jupyter notebooks, wrapping the models inside a container environment, and interfacing to these using BMI, the Basic Model Interface (https://bmi.readthedocs.io/). The container environment (based on Docker) stores the entire software stack, including the operating system and libraries, in such a way that a model run can be reproduced using an identical software environment on any other computer.The reproducible processing of forcing and a reproducible software environment are important steps towards our goal of fully reproducible, Open, and FAIR Hydrological modelling. Ultimately, we hope to make it possible to fully reproduce a hydrological model experiment from data pre-processing to analysis, using only a few clicks.

Download Full-text

ESMValCore: analyzing CMIP data made easy

10.5194/egusphere-egu2020-17472 ◽

2020 ◽

Author(s):

Bouwe Andela ◽

Lisa Bock ◽

Björn Brötz ◽

Faruk Diblen ◽

Laura Dreyer ◽

...

Keyword(s):

Open Source ◽

Performance Metrics ◽

Modular Design ◽

Coupled Model ◽

Application Programming Interface ◽

Earth System ◽

Evaluation Tool ◽

System Models ◽

Scientific Analysis ◽

Earth System Models

The Earth System Model Evaluation Tool (ESMValTool) is a free and open-source community diagnostic and performance metrics tool for the evaluation of Earth system models participating in the Coupled Model Intercomparison Project (CMIP). Version 2 of the tool (Righi et al. 2019, www.esmvaltool.org) features a brand new design, consisting of ESMValCore (https://github.com/esmvalgroup/esmvalcore), a package for working with CMIP data and ESMValTool (https://github.com/esmvalgroup/esmvaltool), a package containing the scientific analysis scripts. This new version has been specifically developed to handle the increased data volume of CMIP Phase 6 (CMIP6) and the related challenges posed by the analysis and the evaluation of output from multiple high-resolution or complex Earth system models. The tool also supports CMIP5 and CMIP3 datasets, as well as a large number of re-analysis and observational datasets that can be formatted according to the same standards (CMOR) on-the-fly or through scripts currently included in the ESMValTool package.At the heart of this new version is the ESMValCore software package, which provides a configurable framework for finding CMIP files using a &#8220;data reference syntax&#8221;, applying commonly used pre-processing functions to them, running analysis scripts, and recording provenance. Numerous pre-processing functions, e.g. for data selection, regridding, and statistics are readily available and the modular design makes it easy to add more. The ESMValCore package is easy to install with relatively few dependencies, written in Python 3, based on state-of-the-art open-source libraries such as Iris and Dask, and widely used standards such as YAML, NetCDF, CF-Conventions, and W3C PROV. An extensive set of automated tests and code quality checks ensure the reliability of the package. Documentation is available at https://esmvaltool.readthedocs.io.The ESMValCore package uses human-readable recipes to define which variables and datasets to use, how to pre-process that data, and what scientific analysis scripts to run. The package provides convenient interfaces, based on the YAML and NetCDF/CF-convention file formats, for running diagnostic scripts written in any programming language. Because the ESMValCore framework takes care of running the workflow defined in the recipe in parallel, most analyses run much faster, with no additional programming effort required from the authors of the analysis scripts. For example, benchmarks show a factor of 30 speedup with respect to version 1 of the tool for a representative recipe on a 24 core machine. A large collection of standard recipes and associated analysis scripts is available in the ESMValTool package for reproducing selected peer-reviewed analyses. The ESMValCore package can also be used with any other script that implements it&#8217;s easy to use interface. All pre-processing functions of the ESMValCore can also be used directly from any Python program. These features allow for use by a wide community of scientific users and developers with different levels of programming skills and experience.Future plans involve extending the public Python API (application programming interface) from just preprocessor functions to include all functionality, including finding the data and running diagnostic scripts. This would make ESMValCore suitable for interactive data exploration from a Jupyter Notebook.

Download Full-text

ESMValTool - introducing a powerful model evaluation tool

10.5194/egusphere-egu2020-19181 ◽

2020 ◽

Author(s):

Valeriu Predoi ◽

Bouwe Andela ◽

Lee De Mora ◽

Axel Lauer

Keyword(s):

Model Evaluation ◽

Performance Metrics ◽

Stratospheric Ozone ◽

Scientific Development ◽

Multiple Model ◽

Earth System ◽

Evaluation Tool ◽

Climate Interactions ◽

Systematic Biases ◽

And Performance

The Earth System Model eValuation Tool (ESMValTool) is a powerful community-driven diagnostics and performance metrics tool. It is used for the evaluation of Earth System Models (ESMs) and allows for routine comparisons of either multiple model versions or observational datasets. ESMValTool's design is highly modular and flexible so that additional analyses can easily be added; in fact, this is essential to encourage the community-based approach to its scientific development. A set of standardized recipes for each scientific topic reproduces specific diagnostics or performance metrics that have demonstrated their importance in ESM evaluation in the peer-reviewed literature. Scientific themes include selected Essential Climate Variables, a range of known systematic biases common to ESMs such as coupled tropical climate variability, monsoons, Southern Ocean processes, continental dry biases and soil hydrology-climate interactions, as well as atmospheric CO3 budgets, tropospheric and stratospheric ozone, and tropospheric aerosols. We will outline the main functional characteristics of ESMValTool Version 2; we will also introduce the reader to the current set of diagnostics and the methods they can use to contribute to its development.

Download Full-text