Evaluating the Practicability of the new Urban Climate Model PALM-4U using a Living-Lab Approach

Numerical urban climate models have the potential to be commonly used tools in urban development processes in practice. With integrated modules for building and envelope simulation these complex models allow the assessment of measures in the building sector on the urban climate, e.g. for mitigation of urban heat island effects or preparing for the effects of climate change. However, the currently existing models do not fulfil the requirements that arise in the field of urban planning, as they lack for example functionality, user-friendliness, are hard to integrate in the municipalities’ technical equipment or are not freely available. The German research and development project Urban Climate under Change (2016-2019) developed and validated a new innovative urban climate model called PALM-4U. Aim of the research was to create a model that meets the requirements of users in science as well as practitioners in engineering offices and urban administrations. Therefore, technical features and operational functionalities which the model has to meet to support users in their daily work have been assessed in a first project phase. In total more than 200 requirements were collected which are summed up in the so called “User and Requirements Catalogue”. They served as the basis for testing and evaluating the model’s real-world applicability. To ensure that these complex requirements are met, the whole project follows a transdisciplinary approach integrating science (model development and data assimilation) and practice (user requirements, testing and evaluation) applying a living lab approach: Stakeholders from participating cities and companies took part in on-site workshops, introducing the model with practical use-cases. Afterwards, participants were given tasks covering different features of the model’s applications, which they tested in personal use. The model fulfils the majority of the tested requirements and the users appreciated the model’s concept and functionality. But further development is necessary to provide the practitioners a tool that is applicable in their daily work: Preparation of input data, a user-friendly graphical user-interface, enhanced interfaces to other software and planning tools, use cases that were prepared from experts as well as guidelines and tools for result assessment and interpretation were main suggestions for improvement..

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A new ensemble-based statistical methodology to verify changes in weather and climate models

10.5194/egusphere-egu21-4255 ◽

2021 ◽

Author(s):

Christian Zeman ◽

Christoph Schär

Keyword(s):

Climate Models ◽

Climate Model ◽

Numerical Models ◽

Hypothesis Test ◽

Model Development ◽

Atmospheric Model ◽

Statistical Hypothesis ◽

Model Parameters ◽

Rounding Errors ◽

Weather And Climate

Since their first operational application in the 1950s, atmospheric numerical models have become essential tools in weather and climate prediction. As such, they are a constant subject to changes, thanks to advances in computer systems, numerical methods, and the ever increasing knowledge about the atmosphere of Earth. Many of the changes in today's models relate to seemingly unsuspicious modifications, associated with minor code rearrangements, changes in hardware infrastructure, or software upgrades. Such changes are meant to preserve the model formulation, yet the verification of such changes is challenged by the chaotic nature of our atmosphere - any small change, even rounding errors, can have a big impact on individual simulations. Overall this represents a serious challenge to a consistent model development and maintenance framework.Here we propose a new methodology for quantifying and verifying the impacts of minor atmospheric model changes, or its underlying hardware/software system, by using ensemble simulations in combination with a statistical hypothesis test. The methodology can assess effects of model changes on almost any output variable over time, and can also be used with different hypothesis tests.We present first applications of the methodology with the regional weather and climate model COSMO. The changes considered include a major system upgrade of the supercomputer used, the change from double to single precision floating-point representation, changes in the update frequency of the lateral boundary conditions, and tiny changes to selected model parameters. While providing very robust results, the methodology also shows a large sensitivity to more significant model changes, making it a good candidate for an automated tool to guarantee model consistency in the development cycle.

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How Well Can We Represent the Spectrum of Convective Clouds in a Climate Model? Comparisons between Internal Parameterization Variables and Radar Observations

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-17-0191.1 ◽

2018 ◽

Vol 75 (5) ◽

pp. 1509-1524 ◽

Cited By ~ 4

Author(s):

Laurent Labbouz ◽

Zak Kipling ◽

Philip Stier ◽

Alain Protat

Keyword(s):

Large Scale ◽

Climate Models ◽

Climate Model ◽

Aerodynamic Drag ◽

Model Development ◽

Convective Cloud ◽

Height Distribution ◽

Radar Observations ◽

Convective Parameterization ◽

Convective Clouds

Current climate models cannot resolve individual convective clouds, and hence parameterizations are needed. The primary goal of convective parameterization is to represent the bulk impact of convection on the gridbox-scale variables. Spectral convective parameterizations also aim to represent the key features of the subgrid-scale convective cloud field such as cloud-top-height distribution and in-cloud vertical velocities in addition to precipitation rates. Ground-based radar retrievals of these quantities have been made available at Darwin, Australia, permitting direct comparisons of internal parameterization variables and providing new observational references for further model development. A spectral convective parameterization [the convective cloud field model (CCFM)] is discussed, and its internal equation of motion is improved. Results from the ECHAM–HAM model in single-column mode using the CCFM and the bulk mass flux Tiedtke–Nordeng scheme are compared with the radar retrievals at Darwin. The CCFM is found to outperform the Tiedtke–Nordeng scheme for cloud-top-height and precipitation-rate distributions. Radar observations are further used to propose a modified CCFM configuration with an aerodynamic drag and reduced entrainment parameter, further improving both the convective cloud-top-height distribution (important for large-scale impact of convection) and the in-cloud vertical velocities (important for aerosol activation). This study provides a new development in the CCFM, improving the representation of convective cloud spectrum characteristics observed in Darwin. This is a step toward an improved representation of convection and ultimately of aerosol effects on convection. It also shows how long-term radar observations of convective cloud properties can help constrain parameters of convective parameterization schemes.

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Systematic Climate Model Rainfall Biases over Southern Africa: Links to Moisture Circulation and Topography

Journal of Climate ◽

10.1175/jcli-d-18-0008.1 ◽

2018 ◽

Vol 31 (18) ◽

pp. 7533-7548 ◽

Cited By ~ 15

Author(s):

C. Munday ◽

R. Washington

Keyword(s):

Southern Africa ◽

Climate Models ◽

Climate Model ◽

Regional Scale ◽

Model Development ◽

Coupled Model ◽

Climate Science ◽

Summer Rainfall ◽

Southwest Indian Ocean ◽

Low Level

An important challenge for climate science is to understand the regional circulation and rainfall response to global warming. Unfortunately, the climate models used to project future changes struggle to represent present-day rainfall and circulation, especially at a regional scale. This is the case in southern Africa, where models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) overestimate summer rainfall by as much as 300% compared to observations and tend to underestimate rainfall in Madagascar and the southwest Indian Ocean. In this paper, we explore the climate processes associated with the rainfall bias, with the aim of assessing the reliability of the CMIP5 ensemble and highlighting important areas for model development. We find that the high precipitation rates in models that are wet over southern Africa are associated with an anomalous northeasterly moisture transport (~10–30 g kg−1 s−1) that penetrates across the high topography of Tanzania and Malawi and into subtropical southern Africa. This transport occurs in preference to a southeasterly recurvature toward Madagascar that is seen in drier models and reanalysis data. We demonstrate that topographically related model biases in low-level flow are important for explaining the intermodel spread in rainfall; wetter models have a reduced tendency to block the oncoming northeasterly flow compared to dry models. The differences in low-level flow among models are related to upstream wind speed and model representation of topography, both of which should be foci for model development.

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A community diagnostic tool for Chemistry Climate Model Validation

Geoscientific Model Development Discussions ◽

10.5194/gmdd-5-1229-2012 ◽

2012 ◽

Vol 5 (2) ◽

pp. 1229-1261

Author(s):

A. Gettelman ◽

V. Eyring ◽

C. Fischer ◽

H. Shiona ◽

I. Cionni ◽

...

Keyword(s):

Model Validation ◽

Climate Models ◽

Performance Metrics ◽

Climate Model ◽

Model Development ◽

Coupled Model ◽

Technical Note ◽

Complex Evaluation ◽

System User ◽

Intercomparison Project

Abstract. This technical note presents an overview of the Chemistry-Climate Model Validation Diagnostic (CCMVal-Diag) tool for model evaluation. The CCMVal-Diag tool is a flexible and extensible open source package that facilitates the complex evaluation of global models. Models can be compared to other models, ensemble members (simulations with the same model), and/or many types of observations. The tool can also compute quantitative performance metrics. The initial construction and application is to coupled Chemistry-Climate Models (CCMs) participating in CCMVal, but the evaluation of climate models that submitted output to the Coupled Model Intercomparison Project (CMIP) is also possible. The package has been used to assist with analysis of simulations for the 2010 WMO/UNEP Scientific Ozone Assessment and the SPARC Report on the Evaluation of CCMs. The CCMVal-Diag tool is described and examples of how it functions are presented, along with links to detailed descriptions, instructions and source code. The CCMVal-Diag tool is supporting model development as well as quantifying model improvements, both for different versions of individual models and for different generations of community-wide collections of models used in international assessments. The code allows further extensions by different users for different applications and types, e.g. to other components of the Earth System. User modifications are encouraged and easy to perform with a minimum of coding.

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Global exposure to flooding from the new CMIP6 climate model projections

Scientific Reports ◽

10.1038/s41598-021-83279-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yukiko Hirabayashi ◽

Masahiro Tanoue ◽

Orie Sasaki ◽

Xudong Zhou ◽

Dai Yamazaki

Keyword(s):

Spatial Patterns ◽

Flood Risk ◽

Climate Models ◽

Climate Model ◽

Model Development ◽

Coupled Model ◽

Model Intercomparison ◽

Internal Climate Variability ◽

Intercomparison Project ◽

New Generation

AbstractEstimates of future flood risk rely on projections from climate models. The relatively few climate models used to analyze future flood risk cannot easily quantify of their associated uncertainties. In this study, we demonstrated that the projected fluvial flood changes estimated by a new generation of climate models, the collectively known as Coupled Model Intercomparison Project Phase 6 (CMIP6), are similar to those estimated by CMIP5. The spatial patterns of the multi-model median signs of change (+ or −) were also very consistent, implying greater confidence in the projections. The model spread changed little over the course of model development, suggesting irreducibility of the model spread due to internal climate variability, and the consistent projections of models from the same institute suggest the potential to reduce uncertainties caused by model differences. Potential global exposure to flooding is projected to be proportional to the degree of warming, and a greater threat is anticipated as populations increase, demonstrating the need for immediate decisions.

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The representation of Northern Hemisphere blocking in current global climate models

10.5194/wcd-2019-19 ◽

2020 ◽

Cited By ~ 2

Author(s):

Reinhard Schiemann ◽

Panos Athanasiadis ◽

David Barriopedro ◽

Francisco Doblas-Reyes ◽

Katja Lohmann ◽

...

Keyword(s):

Climate Models ◽

Climate Model ◽

Global Climate ◽

Model Development ◽

Reanalysis Data ◽

Global Climate Models ◽

Cmip5 Models ◽

The Pacific ◽

Intercomparison Project ◽

Blocking Index

Abstract. Global Climate Models (GCMs) are known to suffer from biases in the simulation of atmospheric blocking, and this study provides an assessment of how blocking is represented by the latest generation of GCMs. It is evaluated (i) how historical CMIP6 (Climate Model Intercomparison Project Phase 6) simulations perform compared to CMIP5 simulations, and (ii) how horizontal model resolution affects the simulation of blocking in the CMIP6-HighResMIP (PRIMAVERA) model ensemble, which is designed to address this type of question. Two blocking indices are used to evaluate the simulated mean blocking frequency and blocking persistence for the Euro-Atlantic and Pacific regions in winter and summer against the corresponding estimates from atmospheric reanalysis data. There is robust evidence that CMIP6 models simulate blocking frequency and persistence better than CMIP5 models in the Atlantic and Pacific and in winter and summer. This improvement is sizeable so that, for example, winter blocking frequency in the median CMIP5 model in a large Euro-Atlantic domain is underestimated by 32 % using the absolute geopotential height (AGP) blocking index, whereas the same number is 19 % for the median CMIP6 model. As for the sensitivity of simulated blocking to resolution, it is found that the resolution increase, from typically 100 km to 20 km grid spacing, in the PRIMAVERA models, which are not re-tuned at the higher resolutions, benefits the mean blocking frequency in the Atlantic in winter and summer, and in the Pacific in summer. Simulated blocking persistence, however, is not seen to improve with resolution. Our results are consistent with previous studies suggesting that resolution is one of a number of interacting factors necessary for an adequate simulation of blocking in GCMs. The improvements reported in this study hold promise for further reductions in blocking biases as model development continues.

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Northern Hemisphere blocking simulation in current climate models: evaluating progress from the Climate Model Intercomparison Project Phase 5 to 6 and sensitivity to resolution

Weather and Climate Dynamics ◽

10.5194/wcd-1-277-2020 ◽

2020 ◽

Vol 1 (1) ◽

pp. 277-292 ◽

Cited By ~ 1

Author(s):

Reinhard Schiemann ◽

Panos Athanasiadis ◽

David Barriopedro ◽

Francisco Doblas-Reyes ◽

Katja Lohmann ◽

...

Keyword(s):

Climate Models ◽

Climate Model ◽

Global Climate ◽

Model Development ◽

Global Climate Models ◽

Assessment Model ◽

Climate Simulation ◽

Cmip5 Models ◽

Model Intercomparison ◽

Intercomparison Project

Abstract. Global climate models (GCMs) are known to suffer from biases in the simulation of atmospheric blocking, and this study provides an assessment of how blocking is represented by the latest generation of GCMs. It is evaluated (i) how historical CMIP6 (Climate Model Intercomparison Project Phase 6) simulations perform compared to CMIP5 simulations and (ii) how horizontal model resolution affects the simulation of blocking in the CMIP6-HighResMIP (PRIMAVERA – PRocess-based climate sIMulation: AdVances in high-resolution modelling and European climate Risk Assessment) model ensemble, which is designed to address this type of question. Two blocking indices are used to evaluate the simulated mean blocking frequency and blocking persistence for the Euro-Atlantic and Pacific regions in winter and summer against the corresponding estimates from atmospheric reanalysis data. There is robust evidence that CMIP6 models simulate blocking frequency and persistence better than CMIP5 models in the Atlantic and Pacific and during winter and summer. This improvement is sizeable so that, for example, winter blocking frequency in the median CMIP5 model in a large Euro-Atlantic domain is underestimated by 33 % using the absolute geopotential height (AGP) blocking index, whereas the same number is 18 % for the median CMIP6 model. As for the sensitivity of simulated blocking to resolution, it is found that the resolution increase, from typically 100 to 20 km grid spacing, in most of the PRIMAVERA models, which are not re-tuned at the higher resolutions, benefits the mean blocking frequency in the Atlantic in winter and summer and in the Pacific in summer. Simulated blocking persistence, however, is not seen to improve with resolution. Our results are consistent with previous studies suggesting that resolution is one of a number of interacting factors necessary for an adequate simulation of blocking in GCMs. The improvements reported in this study hold promise for further reductions in blocking biases as model development continues.

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Evaluation of frontal precipitation in CMIP6 models

10.5194/egusphere-egu2020-9371 ◽

2020 ◽

Author(s):

Jennifer Catto ◽

Matthew Priestley

Keyword(s):

Extreme Precipitation ◽

Climate Models ◽

Climate Model ◽

Model Development ◽

Model Performance ◽

Weather System ◽

Hourly Precipitation ◽

Model Biases ◽

Atmospheric Fronts ◽

Precipitation Estimates

Process-based evaluation of precipitation is key to understanding climate model biases. It is vital to ensure that precipitation is produced in the model due to the correct mechanisms (or weather system). Atmospheric fronts have been shown to be responsible for a large proportion of total and extreme precipitation in the mid-latitudes. Therefore, representation of precipitation associated with fronts in climate models needs to be tested.We applied objective front identification to the historical simulations from the CMIP6 archive and linked them with their 6-hourly precipitation accumulations. We compared the model outputs to the results from observationally constrained datasets. The fronts were identified from ERA5 and linked to precipitation estimates from sources including ERA5, and satellite products. This allows the precipitation errors to be decomposed into components associated with the frequency and intensity of frontal and non-frontal precipitation.The diagnostics from the analysis have been made into metrics which could be used to evaluate model performance and aid in focussing future model development.

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A community diagnostic tool for chemistry climate model validation

Geoscientific Model Development ◽

10.5194/gmd-5-1061-2012 ◽

2012 ◽

Vol 5 (5) ◽

pp. 1061-1073 ◽

Cited By ~ 9

Author(s):

A. Gettelman ◽

V. Eyring ◽

C. Fischer ◽

H. Shiona ◽

I. Cionni ◽

...

Keyword(s):

Model Validation ◽

Climate Models ◽

Climate Model ◽

Model Development ◽

Coupled Model ◽

Technical Note ◽

The Earth ◽

Complex Evaluation ◽

System User ◽

Intercomparison Project

Abstract. This technical note presents an overview of the Chemistry-Climate Model Validation Diagnostic (CCMVal-Diag) tool for model evaluation. The CCMVal-Diag tool is a flexible and extensible open source package that facilitates the complex evaluation of global models. Models can be compared to other models, ensemble members (simulations with the same model), and/or many types of observations. The initial construction and application is to coupled chemistry-climate models (CCMs) participating in CCMVal, but the evaluation of climate models that submitted output to the Coupled Model Intercomparison Project (CMIP) is also possible. The package has been used to assist with analysis of simulations for the 2010 WMO/UNEP Scientific Ozone Assessment and the SPARC Report on the Evaluation of CCMs. The CCMVal-Diag tool is described and examples of how it functions are presented, along with links to detailed descriptions, instructions and source code. The CCMVal-Diag tool supports model development as well as quantifies model changes, both for different versions of individual models and for different generations of community-wide collections of models used in international assessments. The code allows further extensions by different users for different applications and types, e.g. to other components of the Earth system. User modifications are encouraged and easy to perform with minimum coding.

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A More Powerful Reality Test for Climate Models

Eos ◽

10.1029/2016eo051663 ◽

2016 ◽

Vol 97 ◽

Cited By ~ 32

Author(s):

Peter Gleckler ◽

Charles Doutriaux ◽

Paul Durack ◽

Karl Taylor ◽

Yuying Zhang ◽

...

Keyword(s):

Community Engagement ◽

Model Evaluation ◽

Climate Models ◽

Climate Model ◽

Model Development ◽

Climate Model Evaluation

A new climate model evaluation package will deliver objective comparisons between models and observations for research and model development and provide a framework for community engagement.

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