Regional Earth System Model Research Articles

Demonstrating the asymmetry of the Indian Ocean Dipole response in regional earth system model of CORDEX-SA

An accurate representation of the Indian Ocean Dipole (IOD) is crucial for the reliable projection of Indian summer monsoon rainfall, making it necessary to improve the understanding of the response of the IOD in the warming climate. For the first time, a high-resolution regional earth system model (RESM) over the CORDEX-SA domain is used to investigate the IOD characteristics. The model performance is evaluated in simulating the IOD and associated mechanism. RESM shows a good resemblance in simulating IOD phases (positive and negative). However, the systematic discrepancy is observed in magnitude. Additionally, RESM well represented the positive IOD's inter-event variability. For example, the stronger event dominated by significant cold anomalies over Sumatra with enhanced westward-extended while a moderate event shows weak cooling confined to the region of Sumatra. Additionally, RESM shows potential to distinguish the ENSO and non-ENSO years with more remarkable skill in representing the spatial pattern of SST over IOD region during non-ESNO years than ENSO years. The RESM realistically simulated the IOD amplitude with greater skill than CMIP5/6 models reported in the earlier studies, indicating reliability towards the projection of the Indian summer monsoon. The weaker IOD-ENSO relationship is caused by producing the more significant number of IOD during non-ENSO years. Despite this reliable fidelity, IOD's slightly earlier peak is driven by the early establishment of low-level equatorial easterly wind. This study provided valuable insight into the IOD's different phases, responsible forcings, and limitations of the RESM in accounting for the role of internal climate variability that can be useful for further improvement in the model physics.

Impact of air–sea coupling on the simulation of Indian summer monsoon using a high-resolution Regional Earth System Model over CORDEX-SA

A new high-resolution Regional Earth System Model, namely ROM, has been implemented over CORDEX-SA towards examining the impact of air–sea coupling on the Indian summer monsoon characteristics. ROM's simulated mean ISM rainfall and associated dynamical and thermodynamical processes, including the representation of northward and eastward propagating convention bands, are closer to observation than its standalone atmospheric model component (REMO), highlighting the advantage of air–sea coupling. However, the value addition of air–sea coupling varies spatially with more significant improvements over regions with large biases. Bay of Bengal and the eastern equatorial Indian Ocean are the most prominent region where the highest added value is observed with a significant reduction up to 50–500% precipitation bias. Most of the changes in precipitation over the ocean are associated with convective precipitation (CP) due to the suppression of convective activity caused by the negative feedback due to the inclusion of air–sea coupling. However, CP and large-scale precipitation (LP) improvements show east–west asymmetry over the Indian land region. The substantial LP bias reduction is noticed over the wet bias region of western central India due to its suppression, while enhanced CP over eastern central India contributed to the reduction of dry bias. An insignificant change is noticed over Tibetan Plateau, northern India, and Indo Gangetic plains. The weakening of moisture-laden low-level Somalia Jets causes the diminishing of moisture supply from the Arabian Sea (AS) towards Indian land regions resulting in suppressed precipitation, reducing wet bias, especially over western central India. The anomalous high kinetic energy over AS, wind shear, and tropospheric temperature gradient in REMO compared to observation is substantially reduced in the ROM, facilitating the favourable condition for suppressing moisture feeding and hence the wet bias over west-central India in ROM. The warmer midlatitude in ROM than REMO over eastern central India strengthens the convection, enhancing precipitation results in reducing the dry bias. Despite substantially improved ROM’performance, it still exhibits some systematic biases (wet/dry) partially associated with the persistent warm/cold SST bias and land–atmosphere interaction.

Regional earth system modelling framework for CORDEX-SA: an integrated model assessment for Indian summer monsoon rainfall

An effort is made to implement a regional earth system model (RESM); ROM, over CORDEX-South Asia (SA). The added value of RESM is assessed for mean precipitation, its variability (intraseasonal to interannual), extremes, and associated processes. In this regard, ROM’s fields are compared with the respective fields of its standalone version (REMO), the models belonging coupled model intercomparison project (CMIP5 and CMIP6), and regional climate models of CORDEX-CORE simulations. RESM shows substantial improvement for most of the Indian monsoon’s aspects; however, the magnitude of the value addition varies spatiotemporally and also with different aspects.. The improved representation of intraseasonal variability (active-break spell’s duration and intensity) and Interannual variability attributed to improved mean seasonal precipitation. Additionally, correct representation of sea surface temperature, Indian Ocean Dipole, and its underlying dynamics also contribute to improving the mean precipitation. The notable improvement is seen especially over the south-eastern regions of the Bay of Bengal (BoB) and South-Central India, where increasing (decreasing) low-pressure systems over Central India (BoB) are noticed as a consequence of air-sea coupling, leading to enhanced (reduced) precipitation over Central India (BoB), reducing dry (wet) bias found in REMO and the other models. Despite substantial improvements, RESM has a systematic wet bias in the mean precipitation associated with a warm bias over the western coast of the Arabian Sea. An overestimation of very high extreme precipitation due to the enhanced contribution of low-pressure systems indicates the model’s limitations, suggesting the need for further tuning of the RESM.

Assessment of the spatio-temporal variability of the added value on precipitation of convection-permitting simulation over the Iberian Peninsula using the RegIPSL regional earth system model

In this study, we have assessed the added value on the spatio-temporal distribution of the precipitation of convection-permitting simulation (3 km) compared to the parent coarse-scale parameterized convection simulation (20 km) with the high-resolution observational datasets i.e., SPREAD (5 km) and IBERIA01 (10 km) over the Iberian Peninsula (IP) in all four seasons during 2000–2009. Both simulations are evaluation runs based on ERA-Interim reanalysis and performed with the RegIPSL regional earth system model in the frame of the European Climate Prediction system (EUCP) H2020 project and COordinated Regional climate Downscaling Experiment (CORDEX). We have not found significant improvement in the convection-permitting simulation compared to the parent coarse-scale simulation for the seasonal mean precipitation of the IP except the spatial variation over mountainous peaks. The kilometer-scale simulation significantly underestimates the observed seasonal mean precipitation over the western parts of the IP compared to the coarse-scale simulation, which may be attributed to a change of local dynamics in the kilometer-scale simulation with a weakening and southward shift of the moisture-laden westerly winds approaching from the Atlantic Ocean over the IP (i.e., a decline in atmospheric moisture transport from the Atlantic Ocean towards the IP). However, the added value of kilometer-scale simulation over the driving coarse-scale simulation is obtained for various indices; in the representation of the spatio-temporal distribution of the wet-day precipitation frequency and intensity, and the extreme/heavy precipitation events for each season at both resolutions i.e., downscaled and upscaled. It has also been noted that the spatio-temporal distribution of precipitation for all metrics used varies between the two observational datasets for all seasons.

Diurnal cycle of surface energy fluxes in high mountain terrain: High‐resolution fully coupled atmosphere‐hydrology modelling and impact of lateral flow

AbstractWater and energy fluxes are inextricably interlinked within the interface of the land surface and the atmosphere. In the regional earth system models, the lower boundary parameterization of land surface neglects lateral hydrological processes, which may inadequately depict the surface water and energy fluxes variations, thus affecting the simulated atmospheric system through land‐atmosphere feedbacks. Therefore, the main objective of this study is to evaluate the hydrologically enhanced regional climate modelling in order to represent the diurnal cycle of surface energy fluxes in high spatial and temporal resolution. In this study, the Weather Research and Forecasting model (WRF) and coupled WRF Hydrological modelling system (WRF‐Hydro) are applied in a high alpine catchment in Northeastern Tibetan Plateau, the headwater area of the Heihe River. By evaluating and intercomparing model results by both models, the role of lateral flow processes on the surface energy fluxes dynamics is investigated. The model evaluations suggest that both WRF and coupled WRF‐Hydro reasonably represent the diurnal variations of the near‐surface meteorological fields, surface energy fluxes and hourly partitioning of available energy. By incorporating additional lateral flow processes, the coupled WRF‐Hydro simulates higher surface soil moisture over the mountainous area, resulting in increased latent heat flux and decreased sensible heat flux of around 20–50 W/m2 in their diurnal peak values during summertime, although the net radiation and ground heat fluxes remain almost unchanged. The simulation results show that the diurnal cycle of surface energy fluxes follows the local terrain and vegetation features. This highlights the importance of consideration of lateral flow processes over areas with heterogeneous terrain and land surfaces.

Coupled regional Earth system modeling in the Baltic Sea region

Abstract. Nonlinear responses to externally forced climate change are known to dampen or amplify the local climate impact due to complex cross-compartmental feedback loops in the Earth system. These feedbacks are less well represented in the traditional stand-alone atmosphere and ocean models on which many of today's regional climate assessments rely (e.g., EURO-CORDEX, NOSCCA and BACC II). This has promoted the development of regional climate models for the Baltic Sea region by coupling different compartments of the Earth system into more comprehensive models. Coupled models more realistically represent feedback loops than the information imposed on the region by prescribed boundary conditions and, thus, permit more degrees of freedom. In the past, several coupled model systems have been developed for Europe and the Baltic Sea region. This article reviews recent progress on model systems that allow two-way communication between atmosphere and ocean models; models for the land surface, including the terrestrial biosphere; and wave models at the air–sea interface and hydrology models for water cycle closure. However, several processes that have mostly been realized by one-way coupling to date, such as marine biogeochemistry, nutrient cycling and atmospheric chemistry (e.g., aerosols), are not considered here. In contrast to uncoupled stand-alone models, coupled Earth system models can modify mean near-surface air temperatures locally by up to several degrees compared with their stand-alone atmospheric counterparts using prescribed surface boundary conditions. The representation of small-scale oceanic processes, such as vertical mixing and sea-ice dynamics, appears essential to accurately resolve the air–sea heat exchange over the Baltic Sea, and these parameters can only be provided by online coupled high-resolution ocean models. In addition, the coupling of wave models at the ocean–atmosphere interface allows for a more explicit formulation of small-scale to microphysical processes with local feedbacks to water temperature and large-scale processes such as oceanic upwelling. Over land, important climate feedbacks arise from dynamical terrestrial vegetation changes as well as the implementation of land-use scenarios and afforestation/deforestation that further alter surface albedo, roughness length and evapotranspiration. Furthermore, a good representation of surface temperatures and roughness length over open sea and land areas is critical for the representation of climatic extremes such as heavy precipitation, storms, or tropical nights (defined as nights where the daily minimum temperature does not fall below 20 ∘C), and these parameters appear to be sensitive to coupling. For the present-day climate, many coupled atmosphere–ocean and atmosphere–land surface models have demonstrated the added value of single climate variables, in particular when low-quality boundary data were used in the respective stand-alone model. This makes coupled models a prospective tool for downscaling climate change scenarios from global climate models because these models often have large biases on the regional scale. However, the coupling of hydrology models to close the water cycle remains problematic, as the accuracy of precipitation provided by atmosphere models is, in most cases, insufficient to realistically simulate the runoff to the Baltic Sea without bias adjustments. Many regional stand-alone ocean and atmosphere models are tuned to suitably represent present-day climatologies rather than to accurately simulate climate change. Therefore, more research is required into how the regional climate sensitivity (e.g., the models' response to a given change in global mean temperature) is affected by coupling and how the spread is altered in multi-model and multi-scenario ensembles of coupled models compared with uncoupled ones.

Introducing the New Regional Community Earth System Model, R-CESM

AbstractThe development of high-resolution, fully coupled, regional Earth system model systems is important for improving our understanding of climate variability, future projections, and extreme events at regional scales. Here we introduce and present an overview of the newly developed Regional Community Earth System Model (R-CESM). Different from other existing regional climate models, R-CESM is based on the Community Earth System Model version 2 (CESM2) framework. We have incorporated the Weather Research and Forecasting (WRF) Model and Regional Ocean Modeling System (ROMS) into CESM2 as additional components. As such, R-CESM can be conveniently used as a regional dynamical downscaling tool for the global CESM solutions or/and as a standalone high-resolution regional coupled model. The user interface of R-CESM follows that of CESM, making it readily accessible to the broader community. Among countless potential applications of R-CESM, we showcase here a few preliminary studies that illustrate its novel aspects and value. These include 1) assessing the skill of R-CESM in a multiyear, high-resolution, regional coupled simulation of the Gulf of Mexico; 2) examining the impact of WRF and CESM ocean–atmosphere coupling physics on tropical cyclone simulations; and 3) a convection-permitting simulation of submesoscale ocean–atmosphere interactions. We also discuss capabilities under development such as (i) regional refinement using a high-resolution ROMS nested within global CESM and (ii) “online” coupled data assimilation. Our open-source framework (publicly available at https://github.com/ihesp/rcesm1) can be easily adapted to a broad range of applications that are of interest to the users of CESM, WRF, and ROMS.

Role of reservoir regulation and groundwater feedback in a simulated ground‐soil‐vegetation continuum: A long‐term regional scale analysis

AbstractThe regional terrestrial water cycle is strongly altered by human activities. Among them, reservoir regulation is a way to spatially and temporally allocate water resources in a basin for multi‐purposes. However, it is still not sufficiently understood how reservoir regulation modifies the regional terrestrial‐ and subsequently, the atmospheric water cycle. To address this question, the representation of reservoir regulation into the terrestrial component of fully coupled regional Earth system models is required. In this study, an existing process‐based reservoir network module is implemented into NOAH‐HMS, that is, the terrestrial component of an atmospheric–hydrologic modelling system, namely, the WRF‐HMS. It allows to quantitatively differentiate role of reservoir regulation and of groundwater feedback in a simulated ground‐soil‐vegetation continuum. Our study focuses on the Poyang Lake basin, where the largest freshwater lake of China and reservoirs of different sizes are located. As compared to streamflow observations, the newly extended NOAH‐HMS slightly improves the streamflow and streamflow duration curves simulation for the Poyang Lake basin for the period 1979–1986. The inclusion of reservoir regulation leads to major changes in the simulated groundwater recharges and evaporation from reservoirs at local scale, but has minor effects on the simulated soil moisture and surface runoff at basin scale. The performed groundwater feedback sensitivity analysis shows that the strength of the groundwater feedback is not altered by the consideration of reservoir regulation. Furthermore, both reservoir regulation and groundwater feedback modify the partitioning of the simulated evapotranspiration, thus affecting the atmospheric water cycle in the Poyang Lake region. This finding motivates future research with our extended fully coupled atmospheric–hydrologic modelling system by the community.

The ENEA-REG system (v1.0), a multi-component regional Earth system model: sensitivity to different atmospheric components over the Med-CORDEX (Coordinated Regional Climate Downscaling Experiment) region

Abstract. In this study, a new regional Earth system model is developed and applied to the Med-CORDEX (Coordinated Regional Climate Downscaling Experiment) region. The ENEA-REG system is made up of two interchangeable regional climate models as atmospheric components (RegCM, REGional Climate Model, and WRF, Weather Research and Forecasting), a river model (Hydrological Discharge, HD), and an ocean model (Massachusetts Institute of Technology General Circulation Model, MITgcm); processes taking place at the land surface are represented within the atmospheric models with the possibility to use several land surface schemes of different complexity. The coupling between these components is performed through the RegESM driver. Here, we present and describe our regional Earth system model and evaluate its components using a multidecadal hindcast simulation over the period 1980–2013 driven by ERA-Interim reanalysis. We show that the atmospheric components correctly reproduce both large-scale and local features of the Euro-Mediterranean climate, although we found some remarkable biases: in particular, WRF has a significant cold bias during winter over the northeastern bound of the domain and a warm bias in the whole continental Europe during summer, while RegCM overestimates the wind speed over the Mediterranean Sea. Similarly, the ocean component correctly reproduces the analyzed ocean properties with performances comparable to the state-of-art coupled regional models contributing to the Med-CORDEX initiative. Our regional Earth system model allows studying the Euro-Mediterranean climate system and can be applied to both hindcast and scenario simulations.

Present and future projections of heatwave hazard-risk over India: A regional earth system model assessment

The heatwave is a disastrous hazard having significant impacts on health and society. This study analyses the heatwave hazards and risk for India's current and future scenarios using socioeconomic vulnerability and temperature datasets during the summer (April–June) season. The Census of India (CoI) 2011 datasets were considered to assess current vulnerability and projected from the SocioEconomic Data And Application Center (SEDAC) population at Shared Socioeconomic Pathway (SSP) 4 for future vulnerability. Whereas IMD temperature data used for hazard assessment for the present scenario (1958–2005) while projected temperature data from regional earth system model REMO-OASIS-MPIOM (ROM) were used for the future (2006–2099) scenario. The study exhibited the most hazardous, vulnerable, and risk-prone regions identified as the south-eastern coast and Indo-Gangetic plains and some populous districts with metropolitan regions (Mumbai, Delhi, and Kolkata) under the current scenario. The coupled model ROM has efficiently captured the critical districts with higher and lower risk, showing its future projection capability. The study highlighted that the heatwave hazard-risk would significantly worsen in future scenarios in all districts under enhanced global warming and largely affecting the districts in the eastern and middle Indo-Gangetic plains and Malabar region. The present study will provide sufficient insights into designing mitigation strategies and future adaptive planning for the heatwave risk, which is one of the targets under Sustainable Development Goal 13 (Goal 13: Climate Action).

Responses of Arctic cyclones to biogeophysical feedbacks under future warming scenarios in a regional Earth system model

Arctic cyclones, as a prevalent feature in the coupled dynamics of the Arctic climate system, have large impacts on the atmospheric transport of heat and moisture and deformation and drifting of sea ice. Previous studies based on historical and future simulations with climate models suggest that Arctic cyclogenesis is affected by the Arctic amplification of global warming, for instance, a growing land-sea thermal contrast. We thus hypothesize that biogeophysical feedbacks (BF) over the land, here mainly referring to the albedo-induced warming in spring and evaporative cooling in summer, may have the potential to significantly change cyclone activity in the Arctic. Based on a regional Earth system model (RCA-GUESS) which couples a dynamic vegetation model and a regional atmospheric model and an algorithm of cyclone detection and tracking, this study assesses for the first time the impacts of BF on the characteristics of Arctic cyclones under three IPCC Representative Concentration Pathways scenarios (i.e. RCP2.6, RCP4.5 and RCP8.5). Our analysis focuses on the spring- and summer time periods, since previous studies showed BF are the most pronounced in these seasons. We find that BF induced by changes in surface heat fluxes lead to changes in land-sea thermal contrast and atmospheric stability. This, in turn, noticeably changes the atmospheric baroclinicity and, thus, leads to a change of cyclone activity in the Arctic, in particular to the increase of cyclone frequency over the Arctic Ocean in spring. This study highlights the importance of accounting for BF in the prediction of Arctic cyclones and the role of circulation in the Arctic regional Earth system.

Impact of horizontal resolution on monsoon precipitation for CORDEX-South Asia: A regional earth system model assessment

For the first time for CORDEX-South Asia, a high-resolution regional earth system model (ROM) is adopted to assess the impact of horizontal resolution (0.22° and 0.11°) in simulating the Indian summer monsoon rainfall (ISMR) and the underlying spatiotemporal variability. ROM at both resolutions bears a close resemblance to observations in simulating the mean precipitation climatology compared to other regional climate models (RCMs) participated in CORDEX- South Asia. ROM shows substantial improvement relative to the ensemble mean of the RCMs included in CORDEX-South Asia. While comparing both simulations with observations, some systematic wet and dry bias over Central India (CI) and Northern Western Ghats is noticed. In general, the wet/dry bias over India is mainly associated with the overestimation/underestimation of the large-scale/convective component. Increasing horizontal resolution from 0.22° to 0.11° significantly adds value in simulating the JJAS mean precipitation by reducing the wet bias over western central India (WCI) and southern peninsular India and dry bias over eastern CI. The reduction in wet/dry bias is mainly associated with suppression/enhancement of the large scale/convective precipitation. This improvement in mean precipitation is partially due to the improved representation of the propagation of mesoscale systems such as boreal summer intraseasonal oscillation (eastward and northward). Despite the above improvements, the wet precipitation bias, particularly over WCI, persists. The weaker Findlater Jet associated with weaker land-ocean thermal contrast caused by the warm sea surface temperature (SST) bias over the western Arabian Sea (AS) suggests that AS moisture transport does not contribute to the wet bias over India. The wet bias is possibly associated with favourable atmospheric conditions (atmospheric instability).

Vegetation‐Climate Feedbacks Enhance Spatial Heterogeneity of Pan‐Amazonian Ecosystem States Under Climate Change

AbstractAmazonian ecosystems range from rainforest to open dryland vegetation, with a following decrease in biomass along the moisture gradient. Biomass can vary greatly at the ecological transition zone between grass dominated savannahs and the forest. It is not well understood if the transition zone could expand under climate change, and thereby reduce ecosystem stability and carbon storage in biomass. Here, we quantify such changes by using a high‐resolution regional Earth system model under RCP 8.5 climate scenario. We disentangle the effects of climate, CO2, and land use by considering vegetation‐climate feedbacks. Our results suggest that future climate change combined with elevated atmospheric CO2 concentration tends to induce a larger spatial gradient of ecosystem states, increasing the transition area by ∼110% at the end of the century. Vegetation feedbacks generally amplify the climate effect by intensifying the climate‐induced warming and drought, further enhancing spatial heterogeneity.

Less Nutrients but More Phytoplankton: Long-Term Ecosystem Dynamics of the Southern North Sea

We here assess long-term trends in marine primary producers in the southern North Sea (SNS) with respect to ongoing regional Earth system changes. We applied a coupled high-resolution (1.5–4.5 km) 3d-physical-biogeochemical regional Earth System model that includes an advanced phytoplankton growth model and benthic biogeochemistry to hindcast ecosystem dynamics in the period 1961–2012. We analyzed the simulation together with in situ observations. Coinciding with the decreasing nutrient level at the beginning of the 1990s, we find a surprising increase in phytoplankton in the German Bight, but not in the more offshore parts of the SNS. We explain these complex patterns by a series of factors which are lacking in many state-of-the-art coupled ecosystem models such as changed light availability and physiological acclimation in phytoplankton. We also show that many coastal time-series stations in the SNS are located in small patches where our model predicts an opposite trend than found for the surrounding waters. Together, these findings call for a reconsideration of current modeling and monitoring schemes.

Introduction to the Regional Coupled Model WRF4-LICOM: Performance and Model Intercomparison over the Western North Pacific

Regional coupled modeling is one of the frontiers of regional climate modeling, but intercomparison has not been well coordinated. In this study, a community regional climate model, WRF4, with a resolution of 15 km, was coupled with a high-resolution (0.1°) North Pacific Ocean model (LICOM_np). The performance of the regional coupled model, WRF4_LICOM, was compared to that of another regional coupled model, RegCM4_LICOM, which was a coupling of version 4 of the Regional Climate Model (RegCM4) with LICOM_np. The analysis focused on the 2005 western North Pacific summer monsoon rainfall. The results showed that the regional coupled models with either RegCM4 or WRF4 as their atmospheric model component simulated the broad features over the WNP reasonably well. Quantitative intercomparison of the regional coupled simulations exhibited different biases for different climate variables. RegCM4_LICOM exhibited smaller biases in its simulation of the averaged June–July–August SST and rainfall, while WRF4_LICOM better captured the tropical cyclone (TC) intensity, the percentage contributions of rainfall induced by TCs to the total rainfall, and the diurnal cycle of rainfall and stratiform percentages, especially over land areas. The different behaviors in rainfall simulated by the two models were partly ascribed to the behaviors in the simulated western North Pacific subtropical high (WNPSH). The stronger (weaker) WNPSH in WRF4_LICOM (RegCM4_LICOM) was driven by overestimated (underestimated) diabatic heating, which peaked at approximately 450 hPa over the region around the Philippines in association with different condensation-radiation processes. Coupling of WRF4 with LIOCM is a crucial step towards the development of the next generation of regional earth system models at the Chinese Academy of Sciences.

The Interplay of Recent Vegetation and Sea Ice Dynamics—Results From a Regional Earth System Model Over the Arctic

AbstractRecent accelerated warming over the Arctic coincides with sea ice reduction and shifting patterns of land cover. We use a state‐of‐the‐art regional Earth system model, RCAO‐GUESS, which comprises a dynamic vegetation model (LPJ‐GUESS), a regional atmosphere model (RCA), and an ocean sea ice model (RCO), to explore the dynamic coupling between vegetation and sea ice during 1989–2011. Our results show that RCAO‐GUESS captures recent trends in observed sea ice concentration and extent, with the inclusion of vegetation dynamics resulting in larger, more realistic variations in summer and autumn than the model that does not account for vegetation dynamics. Vegetation feedbacks induce concomitant changes in downwelling longwave radiation, near‐surface temperature, mean sea level pressure, and sea ice reductions, suggesting a feedback chain linking vegetation change to sea ice dynamics. This study highlights the importance of including interactive vegetation dynamics in modeling the Arctic climate system, particularly when predicting sea ice dynamics.

Thirty Years of Regional Climate Modeling: Where Are We and Where Are We Going next?

AbstractThe year 2019 marks the thirtieth anniversary of the development of the first regional climate model (RCM), and here an overview is provided of the progress in regional modeling research and of the main challenges lying ahead. RCMs were primarily developed to provide fine‐scale climate information for impact studies, but they have evolved into general and multipurpose modeling tools. Among the main achievements in RCM research the focus is on: the development of community RCMs applicable to a wide variety of studies and regional contexts; the increase of model simulation length up to centennial scales and spatial resolutions up to convection‐permitting scales (few kilometers), leading to a better understanding of regional to local climate change signals; the development of fully coupled Regional Earth System Models; the inception of intercomparison projects culminating in the international Coordinated Regional Climate Downscaling Experiment; the extensive use of RCM simulations for impact assessments; and the involvement of the scientific community from developing countries in climate modeling research. Among the outstanding issues in need of more attention are the Added Value of using this downscaling technique; various technical aspects concerning RCM simulations; and uncertainties in RCM‐based climate projections. Future directions in RCM research are discussed, with highlight on: transition to convection‐permitting modeling systems; further development of Regional Earth System Models including the human component; next phase of the Coordinated Regional Climate Downscaling Experiment project; and use of RCMs in the distillation of actionable information for contribution to climate service activities. A brief historical overview of regional climate modeling is also presented.

Indian Summer Monsoon as simulated by the regional earth system model RegCM-ES: the role of local air–sea interaction

In this study the regional earth system model RegCM-ES is applied over the South Asia CORDEX domain to improve the simulation of the variability of the Indian Summer Monsoon. RegCM-ES has been integrated for 30 years, from 1979 to 2008, with a spatial resolution of 50 km in the atmospheric component, 18 km in the ocean and 50 or 12 km in the two hydrological models used for this study. A new hydrological component, the Cetemps Hydrological Model (CHyM), is included in the coupled system composed by the regional climate model RegCM4 and the ocean model MITgcm. In our analysis we show how the two way air–sea feedback simulated by the coupled system largely improves the representation of intraseasonal (ISV) and interannual (IAV) modes of variability of the Indian Summer Monsoon Rainfall (ISMR). The comparison with the Hydrological Discharge (HD) model shows large improvements in simulating the correct amount of freshwater river discharge over the Bay of Bengal (BoB), one of the fundamental factor responsible for the formation of the shallow barrier layer (BL) over the BoB. However, the improvements in river discharge do not have a clear effect on the BL due to excessive mixing in the ocean model. The improvements in the simulation of IAV are primarily due to the ability of RegCM-ES to reproduce the Intraseasonal Oscillation modes and to the complex mechanism related to the delayed response of the ISMR to the ENSO forcing. Our results highlight the very important role of fine scale air–sea feedbacks in modulating the ISMR and the internal dynamics of this phenomenon.

Toward modular in situ visualization in Earth system models: the regional modeling system RegESM 1.1

Abstract. The data volume produced by regional and global multicomponent Earth system models is rapidly increasing because of the improved spatial and temporal resolution of the model components and the sophistication of the numerical models regarding represented physical processes and their complex non-linear interactions. In particular, very small time steps need to be defined in non-hydrostatic high-resolution modeling applications to represent the evolution of the fast-moving processes such as turbulence, extratropical cyclones, convective lines, jet streams, internal waves, vertical turbulent mixing and surface gravity waves. Consequently, the employed small time steps cause extra computation and disk input–output overhead in the modeling system even if today's most powerful high-performance computing and data storage systems are considered. Analysis of the high volume of data from multiple Earth system model components at different temporal and spatial resolutions also poses a challenging problem to efficiently perform integrated data analysis of the massive amounts of data when relying on the traditional postprocessing methods today. This study mainly aims to explore the feasibility and added value of integrating existing in situ visualization and data analysis methods within the model coupling framework. The objective is to increase interoperability between Earth system multicomponent code and data-processing systems by providing an easy-to-use, efficient, generic and standardized modeling environment. The new data analysis approach enables simultaneous analysis of the vast amount of data produced by multicomponent regional Earth system models during the runtime. The presented methodology also aims to create an integrated modeling environment for analyzing fast-moving processes and their evolution both in time and space to support a better understanding of the underplaying physical mechanisms. The state-of-the-art approach can also be employed to solve common problems in the model development cycle, e.g., designing a new subgrid-scale parameterization that requires inspecting the integrated model behavior at a higher temporal and spatial scale simultaneously and supporting visual debugging of the multicomponent modeling systems, which usually are not facilitated by existing model coupling libraries and modeling systems.

Self‐Amplifying Feedbacks Accelerate Greening and Warming of the Arctic

AbstractIncreased greening, higher vegetation productivity, and shrubification have been observed in Arctic tundra in response to recent warming. Such changes have affected the near‐surface climate through opposing biogeophysical feedbacks (BF) associated with changes to albedo and evapotranspiration. However, the likely spatiotemporal variations of BF to future climate change and the consequences for Arctic vegetation and ecology have not been robustly quantified. We apply a regional Earth system model (RCA‐GUESS) interactively coupling atmospheric dynamics to land vegetation response in three potential 21st‐century radiative forcing simulations for the Arctic. We find that BF, dominated by albedo‐mediated warming in early spring and evapotranspiration‐mediated cooling in summer, have the potential to amplify or modulate local warming and enhance summer precipitation over land. The magnitude of these effects depends on radiative forcing and subsequent ecosystem responses. Thus, it is important to account for BF when assessing future Arctic climate change and its ecosystem impacts.