COSMO-CLM regional climate simulations in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework: a review

In the last decade, the Climate Limited-area Modeling Community (CLM-Community) has contributed to the Coordinated Regional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM-Community model, ERA-Interim reanalysis and eight global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44∘ (∼ 50 km), 0.22∘ (∼ 25 km), and 0.11∘ (∼ 12 km) over the CORDEX domains Europe, South Asia, East Asia, Australasia, and Africa. This major effort resulted in 80 regional climate simulations publicly available through the Earth System Grid Federation (ESGF) web portals for use in impact studies and climate scenario assessments. Here we review the production of these simulations and assess their results in terms of mean near-surface temperature and precipitation to aid the future design of the COSMO-CLM model simulations. It is found that a domain-specific parameter tuning is beneficial, while increasing horizontal model resolution (from 50 to 25 or 12 km grid spacing) alone does not always improve the performance of the simulation. Moreover, the COSMO-CLM performance depends on the driving data. This is generally more important than the dependence on horizontal resolution, model version, and configuration. Our results emphasize the importance of performing regional climate projections in a coordinated way, where guidance from both the global (GCM) and regional (RCM) climate modeling communities is needed to increase the reliability of the GCM–RCM modeling chain

Exploring information exchange in climate system and climate models

The climate system is one of the classical examples of a complex dynamical system consisting of interacting sub-systems through mass, momentum, and energy exchange across various spatial and temporal scales. This thesis aims to detect and quantify sub-component interactions from an information exchange (IE) perspective. For this purpose, IE estimators derived from information theory are explored and applied to the available climate data obtained from observations, reanalysis, global and regional climate models. Specifically, this thesis investigates the usefulness of information theory methods for process-oriented climate model evaluation. Firstly, methods derived from the concepts of information theory such as transfer entropy and information flow along with their linear and non-linear estimation techniques are initially tested and applied to idealized two-dimensional dynamical systems. The results revealed an expected direction and magnitude of IE providing insights into underlying dynamics. However, as expected the linear estimators are robust for linear systems but fail for non-linear systems. Though the non-linear estimators (kernel and kraskov) showed expected results for all the idealized systems, their free tuning parameters are to be tested for consistent results. Moreover, these methods are sensitive to the available time series length. A real world example case study involving the dynamics between the Indian and Pacific oceans revealed a physically consistent bi-directional IE. However, unexpected IE was detected in the example of North Atlantic and European air temperatures indicating hidden drivers. Though IE provides insights into system dynamics, the availability of time series length and the system at hand must be carefully taken into account before inferring any possible interpretations of the results. Quantifying the IE from El-Ni\~{n}o southern oscillation (ENSO) and Indian Ocean Dipole (IOD) to the Indian Summer Monsoon Rainfall (ISMR) with the observational and reanalysis data sets revealed that both ENSO and IOD are synergistic predictors for the inter-annual variability of the ISMR over central India i.e., the monsoon core region. Though the investigated three Global Climate Models (GCM) could not reveal the underlying IE dynamics of ENSO, IOD, and ISMR, a Regional Climate Model (RCM) simulation downscaling one of the GCMs with realistic large scale signals across the lateral boundaries showed good agreement with the observations. Evaluating a coupled regional climate modeling system driven by two different global data sets with IE estimators revealed significant differences between the process chains linking the north-west Mediterranean sea surface temperatures, evaporation, wind speed, and the Vb-cyclone induced precipitation over Danube, Odra, and Elbe catchments in the historical period (1951-2005). Detailed investigation revealed that the north-west Mediterranean Sea in the coupled regional simulation driven by ERA-20C reanalysis corresponded to the Vb-cyclone precipitation over the three catchments while no such correspondence is noted in the EC-EARTH driven simulation. This discrepancy is attributed to the inheritance of the simulation biases from GCM into the RCM. In the future period (1965-2099), no significant changes in the processes are noted from the simulation. Overall, this thesis used IE estimators in investigating the underlying dynamics of climate system and climate models. The estimators proved useful in providing insights into climate system dynamics assisting in a process based climate model evaluation.Das Klimasystem ist ein typisches Beispiel für ein komplexes dynamisches System, das aus verschiedenen Subsystemen besteht, die durch Massen-, Impuls- und Energieaustausch auf verschiedenen räumlichen und zeitlichen Skalen miteinander interagieren. Ziel dieser Arbeit ist es, die Wechselwirkungen zwischen den Subsystemen aus der Perspektive des Informationsaustauschs (engl. Information Exchange, IE) zu erkennen und zu quantifizieren. Zu diesem Zweck werden aus der Informationstheorie abgeleitete Maße für den Informationsfluß untersucht und auf die verfügbaren Klimadaten bestehend aus Beobachtungen, Reanalysen, globalen Klimamodellen und regionalen Klimamodellen angewendet. Insbesondere zeigt die vorgelegte Arbeit die Nützlichkeit informationstheoretischer Methoden für die prozessorientierte Klimamodellbewertung. Aus den Konzepten der Informationstheorie abgeleitete Methoden wie die Transferentropie, der sogenannte Informationsfluss, sowie deren lineare und nichtlineare Schätzverfahren werden zunächst getestet und auf idealisierte zweidimensionale Systeme angewendet. Die Ergebnisse liefern eine Abschätzung für die Richtung und Größe des Informationsflusses, was Einblicke in die zugrundeliegende Dynamik bietet. Wie erwartet sind die linearen Schätzer zwar robust für lineare Systeme, versagen aber bei nichtlinearen Systemen. Obwohl die nichtlinearen Schätzer (Kernel und Kraskov) robuste Ergebnisse für alle idealisierten Systeme zeigen, müssen ihre freien Tuning-parameter auf konsistente Ergebnisse getestet werden. Außerdem sind diese Methoden empfindlich gegenüber den Eigenschaften der verwendeten Zeitreihen (z.B. der Zeitreihenlänge). Die nichtlinearen Schätzer ergaben einen physikalisch konsistenten bidirektionalen Informationsaustausch zwischen dem Indischen und dem Pazifischen Ozean. Am Beispiel der Lufttemperaturen im Nordatlantik und in Europa wurde jedoch ein unerwarteter Informationsaustausch zwischen beiden Regionen festgestellt, der auf versteckte Einflussfaktoren hinweist. Obwohl die Informationstheorie wichtige Einblicke in die Systemdynamik gewährt, müssen die Länge der verfügbaren Zeitreihen und das jeweilige System sorgfältig berücksichtigt werden, bevor mögliche Interpretationen der Ergebnisse abgeleitet werden können. Die Quantifizierung des Informationsaustauschs von El-Niño und der Southern Oscillation (kurz ENSO) und dem Dipol des Indischen Ozeans (IOD) auf den Indischen Sommermonsunregen (IMSR) mithilfe von Beobachtungsund Reanalysedaten ergab, dass sowohl ENSO als auch IOD synergetische Prädiktoren für die inter-annuelle Variabilität des ISMR über Zentralindien, d.h. der Monsunkernregion, sind. Obwohl die drei untersuchten globalen Klimamodelle (GCM) die zugrundeliegende Dynamik von ENSO, IOD und ISMR nicht aufzeigen konnten, zeigte eine einzelne regionale Klimamodell-Simulation (RCM), bei der eines der GCMs mit realistischen großräumigen Signalen entlang der lateralen Grenzen regionalisiert wurde, eine gute Übereinstimmung mit den Beobachtungen. Dieses Ergebnis unterstreicht die Nützlichkeit der informationstheoretischen Schätzer für die prozessorientierte Evaluierung von Klimamodellen. Die Bewertung gekoppelter regionaler Klimamodellsysteme mit informationstheoretischen Maßen ergab signifikante Unterschiede zwischen den Prozessketten, die die Meeresoberflächentemperaturen des nordwestlichen Mittelmeers, die Verdunstung, die Windgeschwindigkeit und den von Vb-Zyklonen verursachten Niederschlag über den Einzugsgebieten von Donau, Oder und Elbe im historischen Zeitraum (1951-2005) verbinden. Detaillierte Untersuchungen ergaben, dass das nordwestliche Mittelmeer in der gekoppelten regionalen Klimasimulation auf der Grundlage der ERA-20C-Reanalyse den Vb-Zyklonenniederschlag über den drei Einzugsgebieten beeinflusst, während in der EC-EARTH-Simulation keine derartigen Zusammenhänge festgestellt wurden. Diese Diskrepanz wird auf die Vererbung der Fehlern in der Klimasimulation vom GCM auf das RCM zurückgeführt. In der zukünftigen Periode (1965-2099) werden keine signifikanten Änderungen der Prozesse in der Simulation festgestellt. Insgesamt hat diese Arbeit gezeigt, dass die Schätzer für den Informationsaustausch zusätzliche Einblicke in die zugrundeliegende Systemdynamik liefern und damit eine prozessbasierte Klimamodellbewertung unterstützen

Quantification of information exchange in idealized and climate system applications

Often in climate system studies, linear and symmetric statistical measures are applied to quantify interactions among subsystems or variables. However, they do not allow identification of the driving and responding subsystems. Therefore, in this study, we aimed to apply asymmetric measures from information theory: the axiomatically proposed transfer entropy and the first principle-based information flow to detect and quantify climate interactions. As their estimations are challenging, we initially tested nonparametric estimators like transfer entropy (TE)-binning, TE-kernel, and TE k-nearest neighbor and parametric estimators like TE-linear and information flow (IF)-linear with idealized two-dimensional test cases along with their sensitivity on sample size. Thereafter, we experimentally applied these methods to the Lorenz-96 model and to two real climate phenomena, i.e., (1) the Indo-Pacific Ocean coupling and (2) North Atlantic Oscillation (NAO)–European air temperature coupling. As expected, the linear estimators work for linear systems but fail for strongly nonlinear systems. The TE-kernel and TE k-nearest neighbor estimators are reliable for linear and nonlinear systems. Nevertheless, the nonparametric methods are sensitive to parameter selection and sample size. Thus, this work proposes a composite use of the TE-kernel and TE k-nearest neighbor estimators along with parameter testing for consistent results. The revealed information exchange in Lorenz-96 is dominated by the slow subsystem component. For real climate phenomena, expected bidirectional information exchange between the Indian and Pacific SSTs was detected. Furthermore, expected information exchange from NAO to European air temperature was detected, but also unexpected reversal information exchange. The latter might hint to a hidden process driving both the NAO and European temperatures. Hence, the limitations, availability of time series length and the system at hand must be taken into account before drawing any conclusions from TE and IF-linear estimations

The synergistic impact of ENSO and IOD on Indian summer monsoon rainfall in observations and climate simulations – an information theory perspective

The El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) are two well-known temporal oscillations in sea surface temperature (SST), which are both thought to influence the interannual variability of Indian summer monsoon rainfall (ISMR). Until now, there has been no measure to assess the simultaneous information exchange (IE) from both ENSO and IOD to ISMR. This study explores the information exchange from two source variables (ENSO and IOD) to one target (ISMR). First, in order to illustrate the concepts and quantification of two-source IE to a target, we use idealized test cases consisting of linear and nonlinear dynamical systems. Our results show that these systems exhibit net synergy (i.e., the combined influence of two sources on a target is greater than the sum of their individual contributions), even with uncorrelated sources in both the linear and nonlinear systems. We test IE quantification with various estimators (linear, kernel, and Kraskov estimators) for robustness. Next, the two-source IE from ENSO and IOD to ISMR is investigated in observations, reanalysis, three global climate model (GCM) simulations, and three nested higher-resolution simulations using a regional climate model (RCM). This (1) quantifies IE from ENSO and IOD to ISMR in the natural system and (2) applies IE in the evaluation of the GCM and RCM simulations. The results show that both ENSO and IOD contribute to ISMR interannual variability. Interestingly, significant net synergy is noted in the central parts of the Indian subcontinent, which is India's monsoon core region. This indicates that both ENSO and IOD are synergistic predictors in the monsoon core region. But, they share significant net redundant information in the southern part of the Indian subcontinent. The IE patterns in the GCM simulations differ substantially from the patterns derived from observations and reanalyses. Only one nested RCM simulation IE pattern adds value to the corresponding GCM simulation pattern. Only in this case does the GCM simulation show realistic SST patterns and moisture transport during the various ENSO and IOD phases. This confirms, once again, the importance of the choice of GCM in driving a higher-resolution RCM. This study shows that two-source IE is a useful metric that helps in better understanding the climate system and in process-oriented climate model evaluation.ISSN:2190-4987ISSN:2190-497

Heavy Vb‑cyclone precipitation: a transfer entropy application showcase

Several past summer floods in Central Europe were associated with so-called Vb‑cyclones propagating from the Mediterranean Sea north-eastward to Central Europe. This study illustrates the usefulness of the parametric transfer entropy measure TE‑linear in investigating heavy Vb‑cyclone precipitation events in the Odra catchment (Poland). With the application of the TE‑linear approach, we confirm the impact of the Mediterranean Sea on precipitation intensification. Moreover, we also detect significant information exchange to Vb‑cyclone precipitation from evaporation over the European continent along the typical Vb‑cyclone pathway. Thus, the Mediterranean Sea could enhance the Vb‑cyclone precipitation by pre-moistening continental moisture source regions that contribute to precipitation downstream in the investigated catchments. Overall, the transfer entropy approach with the measure TE‑linear proved to be computationally effective and complementary to traditional methods such as Lagrangian and Eulerian diagnostics

The first ensemble of kilometer-scale simulations of a hydrological year over the third pole

An accurate understanding of the current and future water cycle over the Third Pole is of great societal importance, given the role this region plays as a water tower for densely populated areas downstream. An emerging and promising approach for skillful climate assessments over regions of complex terrain is kilometer-scale climate modeling. As a foundational step towards such simulations over the Third Pole, we present a multi-model and multi-physics ensemble of kilometer-scale regional simulations for the hydrological year of October 2019 to September 2020. The ensemble consists of 13 simulations performed by an international consortium of 10 research groups, configured with a horizontal grid spacing ranging from 2.2 to 4 km covering all of the Third Pole region. These simulations are driven by ERA5 and are part of a Coordinated Regional Climate Downscaling EXperiment Flagship Pilot Study on Convection-Permitting Third Pole. The simulations are compared against available gridded and in-situ observations and remote-sensing data, to assess the performance and spread of the model ensemble compared to the driving reanalysis during the cold and warm seasons. Although ensemble evaluation is hindered by large differences between the gridded precipitation datasets used as a reference over this region, we show that the ensemble improves on many warm-season precipitation metrics compared with ERA5, including most wet-day and hour statistics, and also adds value in the representation of wet spells in both seasons. As such, the ensemble will provide an invaluable resource for future improvements in the process understanding of the hydroclimate of this remote but important region.ISSN:0930-7575ISSN:1432-089

Simulating Aquaplanet Using ICON with a GT4Py DSL Dynamical Core

We present the results of our efforts porting the dynamical core of the ICON climate and numerical weather prediction (NWP) model to GT4Py. GT4Py is a Domain Specific Language (DSL) designed for weather and climate applications, which allows domain scientists to write performance portable climate and weather code within a high level Python-based frontend. Porting code to GT4Py greatly improves readability as compared to equivalent GPU-accelerated codes written in Fortran + OpenACC. Additionally the DSL allows for a separation of concerns between the domain scientists, software engineers and optimization experts. The fine grained and automatic integration of the DSL generated code back into the Fortran ICON code enables us to compare the original Fortran code to the DSL generated code by running both versions. We call this the verification mode of the integration. On the other hand, in the substitution mode, only the DSL generated version of the code is executed. After a thorough verification process of the model porting, we present results from the Aquaplanet idealized experiment on a global icosahedral grid of resolution ~80km. We also compare the performance of ICON with GT4Py dycore with the standard ICON-NWP model running on GPUs

Towards Ensemble-Based Kilometer-Scale Climate Simulations over the Third Pole Region

International audienc

COSMO-CLM regional climate simulations in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework: a review

In the last decade, the Climate Limited-area Modeling Community (CLM-Community) has contributed to the Coordinated Regional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM-Community model, ERA-Interim reanalysis and eight global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44 degrees (similar to 50 km), 0.22 degrees (similar to 25 km), and 0.11 degrees (similar to 12 km) over the CORDEX domains Europe, South Asia, East Asia, Australasia, and Africa. This major effort resulted in 80 regional climate simulations publicly available through the Earth System Grid Federation (ESGF) web portals for use in impact studies and climate scenario assessments. Here we review the production of these simulations and assess their results in terms of mean near-surface temperature and precipitation to aid the future design of the COSMO-CLM model simulations. It is found that a domain-specific parameter tuning is beneficial, while increasing horizontal model resolution (from 50 to 25 or 12 km grid spacing) alone does not always improve the performance of the simulation. Moreover, the COSMO-CLM performance depends on the driving data. This is generally more important than the dependence on horizontal resolution, model version, and configuration. Our results emphasize the importance of performing regional climate projections in a coordinated way, where guidance from both the global (GCM) and regional (RCM) climate modeling communities is needed to increase the reliability of the GCM-RCM modeling chain.11Ysciescopu

COSMO-CLM regional climate simulations in the CORDEX framework: a review

In the last decade, the Climate Limited-area Modeling (CLM) Community has contributed to the Coordinated Regional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM community model, ERA-Interim reanalysis and eight Global Climate Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44◦(∼50 km), 0.22◦ (∼25 km) and 0.11◦ (∼12 km) over the CORDEX domains Europe, South Asia, East Asia, Australasia and Africa. This major effort resulted in 80 regional climate simulations publicly available through the Earth System Grid Federation (ESGF) web portals for use in impact studies and climate scenario assessments. Here we review the production of these simulations and assess their results in terms of mean near-surface temperature and precipitation to aid the future design of the COSMO-CLM model simulations. It is found that a domain-specific parameter tuning is beneficial, while increasing horizontal model resolution (from 50 to 25 or 12 km grid spacing) alone does not always improve the performance of the simulation. Moreover, the COSMO-CLM performance depends on the driving data. This is generally more important than the dependence on horizontal resolution, model version and configuration. Our results emphasize the importance of performing regional climate projections in a coordinated way, where guidance from both the global (GCM) and regional (RCM) climate modelling communities is needed to increase the reliability of the GCM-RCM modelling chain