High Resolution Model Intercomparison Project Research Articles

River flow in the near future: a global perspective in the context of a high-emission climate change scenario

Abstract. There is high confidence that global warming intensifies all components of the global water cycle. This work investigates the possible effects of global warming on river flows worldwide in the coming decades. We conducted 18 global hydrological simulations to assess how river flows are projected to change in the near future (2015–2050) compared to the recent past (1950–2014). The simulations are forced by runoff from the High Resolution Model Intercomparison Project (HighResMIP) CMIP6 global climate models (GCMs), which assume a high-emission scenario for the projections. The assessment includes estimating the signal-to-noise (S/N) ratio and the time of emergence (ToE) of all the rivers in the world. Consistently with the water cycle intensification, the hydrological simulations project a clear positive global river discharge trend from ∼2000 that emerges beyond the levels of natural variability and becomes “unfamiliar” by 2017 and “unusual” by 2033. Simulations agree that the climate change signal is dominated by strong increases in the flows of rivers originating in central Africa and South Asia and those discharging into the Arctic Ocean, partially compensated for by the reduced flow projected for Patagonian rivers. The potential implications of such changes may include more frequent floods in central African and South Asian rivers, driven by the projected magnification of the annual cycles with unprecedented peaks, a freshening of the Arctic Ocean from extra freshwater release, and limited water availability in Patagonia given the projected drier conditions of its rivers. This underscores the critical need for a paradigm shift in prioritizing water-related concerns amidst the challenges of global warming.

A high-resolution perspective of extreme rainfall and river flow under extreme climate change in Southeast Asia

Abstract. This article provides high-resolution information on the projected changes in annual extreme rainfall and high- and low-streamflow events over Southeast Asia under extreme climate change. The analysis was performed using the bias-corrected result of the High-Resolution Model Intercomparison Project (HighResMIP) multi-model experiment for the period 1971–2050. Eleven rainfall indices were calculated, along with streamflow simulation using the PCR-GLOBWB hydrological model. The historical period 1981–2010 and the near-future period 2021–2050 were considered for this analysis. Results indicate that, over former mainland Southeast Asia, Myanmar will face more challenges in the near future. The east coast of Myanmar will experience more extreme high-rainfall conditions, while northern Myanmar will have longer dry spells. Over the Indonesian maritime continent, Sumatra and Java will suffer from an increase in dry-spell length of up to 40 %, while the increase in extreme high rainfall will occur over Borneo and mountainous areas in Papua. Based on the streamflow analysis, the impact of climate change is more prominent in a low-flow event than in a high-flow event. The majority of rivers in the central Mekong catchment, Sumatra, Peninsular Malaysia, Borneo, and Java will experience more extreme low-flow events. More extreme dry conditions in the near future are also seen from the increasing probability of future low-flow occurrences, which reaches 101 % and 90 %, on average, over Sumatra and Java, respectively. In addition, based on our results over Java and Sumatra, we found that the changes in extreme high- and low-streamflow events are more pronounced in rivers with steep hydrographs (rivers where flash floods are easily triggered), while rivers with flat hydrographs have a higher risk in terms of the probability of low-flow change.

Impacts of improved horizontal resolutions in the simulations of mean and extreme precipitation using CMIP6 HighResMIP models over West Africa.

We conducted an analysis of 16 historical simulations from the High-Resolution Model Intercomparison Project (HighResMIP) as part of the Coupled Model Intercomparison Project (CMIP) phase 6 (CMIP6). These simulations encompass both high- and low-resolution models and aim to investigate the impact of improved horizontal resolution on mean and extreme precipitation in West Africa between 1985 and 2014. Six Expert Team on Climate Change Detection and Indices (ETCCDI) were used to charactererize extreme indices. Bias adjustment was used to detect and adjust the biases in the models. Our observations indicate that the southeastern and southwestern regions of West Africa experience the most significant precipitation, which aligns with the simulations from HighResMIP. The enhanced horizontal resolution notably influences the simulation of orographically induced rainfall in elevated areas and intensifies precipitation in various aspects. When examining the highest 1-day precipitation, our observations reveal that most of the Guinea Coast region had 1-day rainfall exceeding 100mm. However, this was overestimated and in some simulations underestimated by HighResMIP simulations. Furthermore, an increase in horizontal resolution appears to enhance the ability of high-resolution models to replicate the observed patterns of heavy precipitation (R10mm) and very heavy rainfall (R20mm) days. Spatial and temporal analysis suggests that uncertainty exists in the simulation of extreme precipitation in both high- and low-resolution simulations over West Africa. Also, bias adjustment shows a significant bias in the simulations. To address this issue, we employed a bias adjustment approach.

Effect of increased ocean resolution on model errors in El Niño–Southern Oscillation and its teleconnections

AbstractDespite the complexity of the underlying processes, coupled climate models simulate fairly realistic El Niño–Southern Oscillation dynamics and teleconnections. However, there are many long‐standing errors that remain. We use the High Resolution Model Intercomparison Project suite of models to assess how El Niño–Southern Oscillation and its late‐winter teleconnection to the North Pacific changes when ocean resolution is quadrupled from 1° to 0.25°. We find that increased resolution eliminates large errors in the western extent of El Niño and La Niña sea‐surface temperature anomalies, and that there is some improvement in the asymmetry between El Niño and La Niña. In low‐resolution models, the teleconnections from El Niño and La Niña to the North Pacific are both underestimated and are centred too far west. With increased resolution, the position of the teleconnection is highly accurate during El Niño, but there is less improvement during La Niña. We find no significant improvements in teleconnection strength for either phase. Tropical mean‐state sea‐surface temperatures are found to be too cold by around 1°C throughout the central/eastern Pacific in low‐resolution models, but this bias is not present in high‐resolution models. Despite this, a large discrepancy between observed and modelled mean‐state tropical rainfall persists in high‐resolution models, which may limit improvements in the simulation of the La Niña teleconnection.

Evaluating the Water Cycle Over CONUS at the Watershed Scale for the Energy Exascale Earth System Model Version 1 (E3SMv1) Across Resolutions

AbstractThe water cycle is an important component of the earth system and it plays a key role in many facets of society, including energy production, agriculture, and human health and safety. In this study, the Energy Exascale Earth System Model version 1 (E3SMv1) is run with low‐resolution (roughly 110 km) and high‐resolution (roughly 25 km) configurations—as established by the High Resolution Model Intercomparison Project protocol—to evaluate the atmospheric and terrestrial water budgets over the conterminous United States (CONUS) at the large watershed scale. The warm season water cycle slows down in the HR experiment relative to the LR, with decreasing fluxes of precipitation, evapotranspiration, atmospheric moisture convergence, and runoff. The reductions in these terms exacerbate biases for some watersheds, while reducing them in others. For example, precipitation biases are exacerbated at HR over the Eastern and Central CONUS watersheds, while precipitation biases are reduced at HR over the Western CONUS watersheds. The most pronounced changes with resolution to the water cycle come from reductions in precipitation and evapotranspiration. The reduction in evapotranspiration reduces the biases across nearly all of the CONUS. Additional exploratory metrics show improvements to water cycle extremes (both in precipitation and streamflow), fractional contributions of different storm types to total precipitation, and mountain snowpack.

Assessing the future influence of the North Pacific trade wind precursors on ENSO in the CMIP6 HighResMIP multimodel ensemble

The El Niño Southern Oscillation (ENSO), as one of the largest coupled climate modes, influences the livelihoods of millions of people and ecosystems survival. Thus, how ENSO is expected to behave under the influence of anthropogenic climate change is a substantial question to investigate. In this paper, we analyze future predictions of specific traits of ENSO, in combination with a subset of well-established precursors—the Trade Wind Charging and North Pacific Meridional Mode (TWC/NPMM). We study it across three sets of experiments from a protocol-driven ensemble from CMIP6—the High Resolution Model Intercomparison Project (HighResMIP). Namely, (1) experiments at constant 1950’s radiative forcings, and (2) experiments of present (1950–2014) and (3) future (2015–2050) climate with prescribed increasing radiative forcings. We first investigate the current and predicted spatial characteristics of ENSO events, by calculating area, amplitude and longitude of the Center of Heat Index (CHI). We see that TWC/NPMM-charged events are consistently stronger, in both the presence and absence of external forcings; however, as anthropogenic forcings increase, the area of all ENSO events increases. Since the TWC/NPMM-ENSO relationship has been shown to affect the oscillatory behavior of ENSO, we analyze ENSO frequency by calculating CHI-analogous indicators on the Continuous Wavelet Transform (CWT) of its signal. With this new methodology, we show that across the ensemble, ENSO oscillates at different frequencies, and its oscillatory behavior shows different degrees of stochasticity, over time and across models. However, we see no consistent indication of future trends in the oscillatory behavior of ENSO and the TWC/NPMM-ENSO relationship.

Variability and Changes in Temperature, Precipitation and Snow in the Desaguadero-Salado-Chadileuvú-Curacó Basin, Argentina

We analyze the variability and changes in mean temperature, annual precipitation, and snow water equivalent (SWE) in the Desaguadero-Salado-Chadileuvú-Curacó (DSCC) basin, observed in a recent period, and their projected future values. The current climate and observed changes are studied based on the scarce observation records available in the region. Simulations from the High-Resolution Model Intercomparison Project (HighResMIP v1.0) are used for the analysis of future climate projections. The mean annual temperature presents a major rise between 1 and 2 °C throughout the region in the 1961–2020 period. The annual precipitation has nonlinear positive trends of varied importance. The SWE has decreased noticeably since 2010. Interannual variability also plays a key role, with dominant cycles between 2.8 and 4 years and between 7.5 and 10 years. The projected changes, computed as the difference between the 1985–2014 and 2021–2050 averages, reveal a rise in mean annual temperature in the entire basin, with an eastward magnitude increase from 1 to more than 2 °C. The annual precipitation is projected to increase up to 10% over most of the basin, except in the Andes, where it will decrease. The maximum annual SWE will also continue to decrease, in agreement with the trend observed in recent years.

Evaluation of CMIP6 HighResMIP Models and ERA5 Reanalysis in Simulating Summer Precipitation over the Tibetan Plateau

The High Resolution Model Intercomparison Project (HighResMIP) experiment within the Coupled Model Intercomparison Project Phase 6 (CMIP6) has enabled the evaluation of the performance of climate models over complex terrain for the first time. The study aims to evaluate summer (June to August) precipitation characteristics over the Tibetan Plateau (TP). Precipitation derived from HighResMIP models and ERA5 are compared against the China Merged Precipitation Analysis (CMPA). The nineteen models that participated in HighResMIP are classified into three categories based on their horizontal resolution: high resolution (HR), middle resolution (MR), and low resolution (LR). The multimodel ensemble means (MMEs) of the three categories of models are evaluated. The spatial distribution and elevation dependency of the hourly precipitation characteristics, which include the diurnal peak hour, diurnal variation amplitude, and frequency–intensity structure, are our main focus. The MME-HR and ERA5 both show comparable ability in simulating precipitation in the TP. The MME-HR has a smaller deviation in the precipitation amount and diurnal variation at various altitudes. The ERA5 can better simulate the elevation dependence of the frequency–intensity structure, but its elevation dependence of diurnal variation shows a trend opposite to the observations. Although the MME-HR produces the best simulation results among the three MMEs, the simulation effects of HighResMIP’s precipitation in the TP do not necessarily improve with increasing the horizontal resolution from LR to MR. The finer model resolution has a small impact on the simulation effect of precipitation intensity, but the coarser model resolution will limit the generation of heavy precipitation. These findings give intensive measures for evaluating precipitation in complex terrain and can help us in comprehending rainfall biases in global climate model simulation.

To what extent horizontal resolution improves the simulation of precipitation in CMIP6 HighResMIP models over Southwest China?

Southwest China (SWC) is located in the eastern part of Tibetan Plateau (TP) with large elevation differences and complex topography, which has always been a challenge to the simulation of precipitation in climate modeling community. In this study, the differences in the simulation of precipitation over the SWC are evaluated using the lower and higher resolution models (LR and HR) from the High–Resolution Model Intercomparison Project (HighResMIP) protocol in Coupled Model Intercomparison Project Phase 6 (CMIP6). Our results indicate that the spatial patterns of annual precipitation over the SWC for the period 1985–2014 are well reproduced in most of the HR and LR models, with an increasing tendency from the northwest to southeast. Compared with LR models, the wet biases over the eastern TP and the dry biases over the Sichuan Basin are significantly reduced in HR models. The bias for annual precipitation of the multi–model ensemble mean (MME) has been reduced from 0.97 mm/day (LR) to 0.72 mm/day (HR). In addition, the simulation of extreme precipitation is significantly improved in the finer horizontal resolution models, showing effectively reduced simulation biases in the Sichuan Basin compared with the LR models. The frequency and intensity of extremes are represented by heavy precipitation days (R10 mm) and maximum consecutive 5 days precipitation (Rx5day), which the relative changes have been decreased from 66% (LR) to 47% (HR) in R10 mm and decreased from 23% (LR) to 19% (HR) in Rx5day. We further examine the possible reasons for the difference between LR and HR models in precipitation simulation, showing that the HR models could generate “additional” cyclonic circulation and promote more upward motion with the water vapor convergence, thus correcting the dry biases of precipitation simulation over the Sichuan Basin. This indicates that atmospheric circulation and moisture conditions could be simulated more realistically in climate model with a finer resolution, further improving precipitation simulation performance.

The double‐ITCZ problem in CMIP6 and the influences of deep convection and model resolution

AbstractThe double Intertropical Convergence Zone (ITCZ) bias is an outstanding bias in many climate models. This work assesses the annual‐mean double‐ITCZ problem in the models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) based on several quantitative indices. Within the 46 CMIP6 models, 9 models from mainland China are evaluated as a group to verify the effort of model development from one perspective. The double‐ITCZ bias and its large intermodel spread still exist in CMIP6 models. The overall performance of the models from Chinese mainland is similar with all CMIP6 models. It is found that the top‐five models with relatively low double‐ITCZ biases can effectively restrain the frequency of deep convection and related sea surface temperature (SST) bias in the southeastern Pacific dry subsidence region, which highlights the necessity of improving convective physics in climate models. Impacts of model resolution on the double‐ITCZ problem are examined by comparing the high‐ and low‐resolution groups in CMIP6 and High Resolution Model Intercomparison Project (HighResMIP) historical experiments, respectively. Increased resolution in atmospheric models is found to be able to reduce the positive precipitation bias over the tropical southern Atlantic and improve the simulation of deep convection frequency and convective precipitation ratio there. However, the double‐ITCZ bias over the Pacific is not improved significantly by increased resolution.

Current and Future Climate Extremes Over Latin America and Caribbean: Assessing Earth System Models from High Resolution Model Intercomparison Project (HighResMIP)

Extreme temperature and precipitation events are the primary triggers of hazards, such as heat waves, droughts, floods, and landslides, with localized impacts. In this sense, the finer grids of Earth System models (ESMs) could play an essential role in better estimating extreme climate events. The performance of High Resolution Model Intercomparison Project (HighResMIP) models is evaluated using the Expert Team on Climate Change Detection and Indices (ETCCDI) over the 1981–2014 period and future changes (2021–2050) under Shared Socioeconomic Pathway SSP5–8.5, over ten regions in Latin America and the Caribbean. The impact of increasing the horizontal resolution in estimating extreme climate variability on a regional scale is first compared against reference gridded datasets, including reanalysis, satellite, and merging products. We used three different groups based on the resolution of the model’s grid (sg): (i) low (0.8° ≤ sg ≤ 1.87°), (ii) intermediate (0.5° ≤ sg ≤ 0.7°), and (iii) high (0.23° ≥ sg ≤ 0.35°). Our analysis indicates that there was no clear evidence to support the posit that increasing horizontal resolution improves model performance. The ECMWF-IFS family of models appears to be a plausible choice to represent climate extremes, followed by the ensemble mean of HighResMIP in their intermediate resolution. For future climate, the projections indicate a consensus of temperature and precipitation climate extremes increase across most of the ten regions. Despite the uncertainties presented in this study, climate models have been and will continue to be an important tool for assessing risk in the face of extreme events.

Simulation and Projection of Tropical Cyclone Activities over the Western North Pacific by CMIP6 HighResMIP

Abstract This study assesses the relative impacts of model resolutions, tropical cyclone (TC) trackers, and ocean coupling on simulating TC climatology over the western North Pacific (WNP) based on six Coupled Model Intercomparison Project phase 6 (CMIP6) High-Resolution Model Intercomparison Project (HighResMIP) models from 1979 to 2014. The HighResMIP multimodel ensemble (MME) analysis shows that the high resolution has a higher Taylor skill score II (S2) in both temporal and spatial patterns of TC genesis frequency and accumulated cyclone energy (ACE) than the low resolution. In contrast, the TempestExtremes tracker (coupled run) results in a higher S2 in temporal patterns but a lower S2 in spatial patterns than the TRACK tracker (uncoupled run). Among the three factors, increased resolution leads to the greatest improvement in S2 in both temporal and spatial patterns. Furthermore, this study investigates the projections of future TC activity over the WNP by HighResMIP under the SSP5–8.5 scenario. Overall, HighResMIP MMEs project a decrease in the genesis frequency, track density, and ACE of all TCs, with the high-resolution, TRACK tracker, and uncoupled run showing greater magnitude. The high-resolution MMEs, using both trackers, project an increase in the genesis frequency and ACE of intense TCs in the coupled run. Moreover, TC track density and ACE show a larger poleward migration in the coupled run than in the uncoupled run, consistent with the significant surface warming in the northern WNP.

Impact of increased resolution on the representation of the Canary upwelling system in climate models

Abstract. We investigate the representation of the Canary upwelling system (CUS) in six global coupled climate models operated at high and standard resolution as part of the High Resolution Model Intercomparison Project (HighResMIP). The models' performance in reproducing the observed CUS is assessed in terms of various upwelling indices based on sea surface temperature (SST), wind stress, and sea surface height, focusing on the effect of increasing model spatial resolution. Our analysis shows that possible improvement in upwelling representation due to the increased spatial resolution depends on the subdomain of the CUS considered. Strikingly, along the Iberian Peninsula region, which is the northernmost part of the CUS, the models show lower skill at higher resolution compared to their corresponding lower-resolution version in both components for all the indices analyzed in this study. In contrast, over the southernmost part of the CUS, from the north of Morocco to the Senegalese coast, the high-ocean- and high-atmosphere-resolution models simulate a more realistic upwelling than the standard-resolution models, which largely differ from the range of observational estimates. These results suggest that increasing resolution is not a sufficient condition to obtain a systematic improvement in the simulation of the upwelling phenomena as represented by the indices considered here, and other model improvements notably in terms of the physical parameterizations may also play a role.

Application-specific optimal model weighting of global climate models: A red tide example

Global climate models (GCMs) and Earth system models (ESMs) provide many climate services with environmental relevance. The High Resolution Model Intercomparison Project (HighResMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) provides model runs of GCMs and ESMs to address regional phenomena. Developing a parsimonious ensemble of CMIP6 requires multiple ensemble methods such as independent-model subset selection, prescreening-based subset selection, and model weighting. The work presented here focuses on application-specific optimal model weighting, with prescreening-based subset selection. As such, independent ensemble members are categorized, selected, and weighted based on their ability to reproduce physically-interpretable features of interest that are problem-specific. We discuss the strengths and caveats of optimal model weighting using a case study of red tide prediction in the Gulf of Mexico along the West Florida Shelf. Red tide is a common name of specific harmful algal blooms that occur worldwide, causing adverse socioeconomic and environmental impacts. Our results indicate the importance of prescreening-based subset selection as optimal model weighting can underplay robust ensemble members by optimizing error cancellation. Prescreening-based subset selection also provides insights about the validity of the model weights. By illustrating the caveats of using non-representative models when optimal model weighting is used, the findings and discussion of this study are pertinent to many other climate services.

Impact of climate change on site characteristics of eight major astronomical observatories using high-resolution global climate projections until 2050

Context. Sites for next-generation telescopes are chosen decades before the first light of a telescope. Site selection is usually based on recent measurements over a period that is too short to account for long-term changes in observing conditions such as those arising from anthropogenic climate change. For astronomical facilities with a typical lifetime of 30 yr, it is therefore essential to be aware of climate evolution to optimise observing time. Aims. In this study, we analyse trends in astronomical observing conditions for eight sites. Most sites either already host telescopes that provide in situ measurements of weather parameters or are candidates for hosting next-generation telescopes. For a fine representation of orography, we use the highest resolution global climate model (GCM) ensemble available provided by the high-resolution model intercomparison project and developed as part of the European Union Horizon 2020 PRIMAVERA project. Methods. We evaluate atmosphere-only and coupled PRIMAVERA GCM historical simulations against in situ measurements and the fifth generation atmospheric reanalysis (ERA5) of the European centre for medium-range weather forecasts for the period 1979–2014. The projections of changes in current site conditions are then analysed for the period 2015–2050 using PRIMAVERA future climate simulations. Results. Over most sites, we find that PRIMAVERA GCMs show a good agreement in temperature, specific humidity, and precipitable water vapour compared to in situ observations and ERA5. The ability of PRIMAVERA to simulate those variables increases confidence in their projections. For those variables, the model ensemble projects an increasing trend for all sites, which will result in progressively poorer astronomical observing conditions compared to current conditions. On the other hand, no significant trends are projected for relative humidity, cloud cover, or astronomical seeing and PRIMAVERA does not simulate these variables well compared to observations and reanalyses. Therefore, there is little confidence in these projections. Conclusions. Our results show that climate change will negatively impact the quality of astronomical observations and is likely to increase time lost due to bad site conditions. We stress that it is essential for astronomers to include long-term climate projections in their process for site selection and monitoring. We show that high-resolution GCMs can be used to analyse the effect of climate change on site characteristics of next-generation telescopes.

How well do the CMIP6 HighResMIP models simulate precipitation over the Tibetan Plateau?

The simulation of precipitation over the Tibetan Plateau (TP) is still a challenge in climate modeling community, although there have been a number of improvements in recent global climate models. In this study, we evaluate the differences in the simulation of precipitation over the TP using multi–resolution outputs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) High Resolution Model Intercomparison Project (HighResMIP). Our results show that both the high resolution (HR) and low resolution (LR) models could generally simulate the annual precipitation well over the TP during the period of 1998–2014. With their finer resolution, the HR models, give some improvements in the simulation of annual precipitation, showing a significantly reduced “wet bias” over the TP compared with the LR models. In addition, the increased resolution performs a better simulation of the precipitation extremes, especially over the southern and southeastern TP, revealing the added value of HR models. We further investigate the differences in the simulation of precipitation between the LR and HR models using a linearized moisture budget equation, which suggests that the underlying differences can be largely explained by the contribution of the dynamic effect (δDY). This effect, dominated by the differences in the simulation of the atmospheric circulation, could induce local moisture convergence, generating excessive precipitation in the LR models compared with the HR models. This implies that the large–scale circulation and moisture conditions can be resolved more realistically in HR models, which is an important factor in determining the simulation of precipitation over the TP.

CAS FGOALS-f3-H Dataset for the High-Resolution Model Intercomparison Project (HighResMIP) Tier 2

Following the High-Resolution Model Intercomparison Project (HighResMIP) Tier 2 protocol under the Coupled Model Intercomparison Project Phase 6 (CMIP6), three numerical experiments are conducted with the Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System Model, version f3-H (CAS FGOALS-f3-H), and a 101-year (1950–2050) global high-resolution simulation dataset is presented in this study. The basic configuration of the FGOALS-f3-H model and numerical experiments design are briefly described, and then the historical simulation is validated. Forced by observed radiative agents from 1950 to 2014, the coupled model essentially reproduces the observed long-term trends of temperature, precipitation, and sea ice extent, as well as the large-scale pattern of temperature and precipitation. With an approximate 0.25° horizontal resolution in the atmosphere and 0.1° in the ocean, the coupled models also simulate energetic western boundary currents and the Antarctic Circulation Current (ACC), reasonable characteristics of extreme precipitation, and realistic frontal scale air-sea interaction. The dataset and supporting detailed information have been published in the Earth System Grid Federation (ESGF, https://esgf-node.llnl.gov/projects/cmip6/).

Performance of CMIP6 HighResMIP on the Representation of Onset and Cessation of Seasonal Rainfall in Southern West Africa

Changes in rainfall onset and cessation dates are critical for improving decision making and adaptation strategies in numerous socio-economic sectors. An objective method of determining onset and cessation date is employed over Southern West Africa (SWA) in this study. The method is applied over 34 years of the quasi-global rainfall dataset from the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) and five High Resolution Model Intercomparison Project (HighResMIP) model datasets under the Coupled Model Intercomparison Project Phase 6 (CMIP6) experiment. Generally, a strong agreement exists between CHIRPS and the HighResMIP models in capturing the behaviour of seasonal rainfall over SWA, with models able to capture the bimodal rainfall season. The ability of models in capturing onset and cessation dates as observed in CHIRPS shows the strength of these models in representing the short break between the two wet seasons that is otherwise known as the ‘Little Dry Season’. Patterns observed in the onset and cessation dates over the SWA region are consistent with the northward and southward displacement of the Intertropical Convergence Zone (ITCZ). The seasonal timing of the models shows good agreement with observations such that most mean onset/cessation dates agree within 26 days. While IPSL-CM6A-ATM-HR, a model among the five HighResMIPs used in the study, best agrees with CHIRPS in representing onset and cessation dates during the unimodal rainfall season, no one model best agrees with CHIRPS during the bimodal season, with models outperforming each other in representing onset/cessation dates with little variation.

Representation of Lake–Atmosphere Interactions and Lake-Effect Snowfall in the Laurentian Great Lakes Basin among HighResMIP Global Climate Models

Abstract Credible modeling, tools, and guidance, regarding the changing Laurentian Great Lakes and the climatic impacts, are needed by local decision-makers to inform their management and planning. The present study addresses this need through a model evaluation study of the representation of lake–atmosphere interactions and resulting lake-effect snowfall in the Great Lakes region. Analysis focuses on an extensive ensemble of 74 historical simulations generated by 23 high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP). The model assessment addresses the modeling treatment of the Great Lakes, the spatial distribution and seasonality of climatological snowfall, the seasonal cycle of lake-surface temperatures and overlake turbulent fluxes, and the lake-effect ratio between upwind and downwind precipitation. A deeper understanding of model performance and biases is achieved by partitioning results between HighResMIP GCMs that are 1) coupled to 1D lake models versus GCMs that exclude lake models, 2) between prescribed-ocean model configurations versus fully coupled configurations, and 3) between deep Lake Superior versus relatively shallow Lake Erie. While the HighResMIP GCMs represent the Great Lakes by a spectrum of approaches that include land grid cells, ocean grid cells (with lake surface temperature and ice cover boundary conditions provided by the Met Office Hadley Center Sea Ice and Sea Surface Temperature Dataset), and 1D lake models, the current investigation demonstrates that none of these rudimentary approaches adequately represent the complex nature of seasonal lake temperature and ice cover evolution and its impact on lake–atmosphere interactions and lake-effect precipitation in the Great Lakes region. Significance Statement The purpose of this study is to evaluate the capability of high-resolution global climate models to simulate lake–atmosphere interactions and lake-effect snowfall in the Great Lakes region, given the critical influence of the lakes on regional climate and vast societal and environmental impacts of lake-effect snowfall. It is determined that the models inadequately represent lake temperatures and ice cover, often leading to insufficient annual snowfall in the lake-effect zones. More advanced, three-dimensional lake models need to be coupled to climate models to support greater credibility in regional lake and climate simulations and future climate projections.

Earth system models for regional environmental management of red tide: Prospects and limitations of current generation models and next generation development.

Earth system models (ESMs) serve as a unique research infrastructure for quality climate services, yet their application for environmental management at regional scale has not yet been fully explored. The unprecedented resolution and model fidelity of the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations, especially of the High-Resolution Model Intercomparison Project (HighResMIP) focusing on regional phenomena, offer opportunities for such applications. This article presents the first venture into using the HighResMIP simulations to tackle a regional environmental issue, the Florida Red Tide. This is a harmful algae bloom caused by the dinoflagellate Karenia brevis, a toxic single-celled microscopic protist. We use CMIP6 historical simulations to establish a causal agreement between the position of Loop Current, a warm ocean current that moves into the Gulf of Mexico, and the occurrence of K. brevis blooms on the Western Florida shelf. Results show that the high-resolution ESMs are capable of simulating the phenomena of interest (i.e., Loop Current) at the regional spatial scale with generally adequate data-model agreement in the context of the relation between Loop Current and red tide. We use this case study to elaborate on the prospects and limitations of using publicly available CMIP data for regional environmental management. We highlight the current gaps and the developmental needs for the next generation ESMs, and discuss the role of stakeholder participation in future ESMs development to facilitate the translation of scientific understanding to better inform decision-making of regional environmental management.