Generation Of Global Climate Models Research Articles

Asymmetric Sea Surface Salinity Response to Global Warming: “Fresh Gets Fresher but Salty Hesitates”

AbstractEfforts to detect long‐term changes in global mean evaporation minus precipitation over the ocean remain ambiguous. Here we define an ad hoc sea surface salinity index to assess the observed and simulated intensification of the freshwater flux pattern over the global ocean and, thus, of the overall water cycle. A recent salinity reconstruction shows a long‐term amplification of the climatological patterns, thereby supporting the popular “fresh gets fresher, salty gets saltier” paradigm. Unlike in a previous study, no systematic underestimation of this amplification is found in the latest generation of global climate models. Yet, the “fresh gets fresher” paradigm is much more robust than its “salty gets saltier” counterpart and the proposed salinity index does not yet provide a strong constraint on the model‐dependent projected intensification of the global water cycle intensification along the 21st century.

Indian Agriculture Under Climate Change: The Competing Effect of Temperature and Rainfall Anomalies

AbstractThe latest generation of global climate models robustly projects that monsoon rainfall anomalies in India will significantly increase in the 21st century due to global warming. This raises the question of the impact of these changes on the agricultural yield. Based on annual district data for the years 1966-2014, we estimate the relationship between weather indices (amount of seasonal rainfall, number of wet days, average temperature) and the most widely grown kharif crops, including rice, in a flexible non-parametric way. We use the empirical relationship in order to predict district-specific crop yield based on the climate projections of eight evaluated state-of-the-art climate models under two global warming scenarios for the years 2021-2100. We find that the loss in rice yield by the end of the 21st century lies on average between 3 - 22% depending on the underlying emission scenario. For the sustainable scenario impacts range from an increase of 3.2% to a decrease of 12.1% for individual districts. In the worst-case scenario, all districts are negatively affected, with a predicted decrease in rice yield ranging from 34% to a decrease of 11.5% in the long run. Potential gains due to increasing rainfall are more than offset by the negative impacts of increasing temperature. Adaptation efforts in the worst-case global warming scenario would need to cut the negative impacts of temperature by 50% in order to reach the outcome of the sustainable scenario.

The dynamics of evolutionary branching in an ecological model

Eco-evolutionary modelling involves the coupling of ecological equations to evolutionary ones. The interaction between ecological dynamics and evolutionary processes is essential to simulating evolutionary branching, a precursor to speciation. The creation and maintenance of biodiversity in models depends upon their ability to capture the dynamics of evolutionary branching. Understanding these systems requires low-dimension models that are amenable to analysis. The rapid reproduction rates of marine plankton ecosystems and their importance in determining the fluxes of climatically important gases between the ocean and atmosphere suggest that the next generation of global climate models needs to incorporate eco-evolutionary models in the ocean. This requires simple population-level models, that can represent such eco-evolutionary processes with orders of magnitude fewer equations than models that follow the dynamics of individual phenotypes. We present a general framework for developing eco-evolutionary models and consider its general properties. This framework defines a fitness function and assumes a beta distribution of phenotype abundances within each population. It simulates the change in total population size, the mean trait value, and the trait differentiation, from which the variance of trait values in the population may be calculated. We test the efficacy of the eco-evolutionary modelling framework by comparing the dynamics of evolutionary branching in a six-equation eco-evolutionary model that has evolutionary branching, with that of an equivalent one-hundred equation model that simulates the dynamics of every phenotype in the population. The latter model does not involve a population fitness function, nor does it assume a distribution of phenotype abundance across trait values. The eco-evolutionary population model and the phenotype model produce similar evolutionary branching, both qualitatively and quantitatively, in both symmetric and asymmetric fitness landscapes. In order to better understand the six-equation model, we develop a heuristic three-equation eco-evolutionary model. We use the density-independent mortality parameter as a convenient bifurcation parameter, so that differences in evolutionary branching dynamics in symmetric and asymmetric fitness landscapes may be investigated. This model shows that evolutionary branching of a stable population is flagged by a zero in the local trait curvature; the trait curvature then changes sign from negative to positive and back to negative, along the solution. It suggests that evolutionary branching points may be generated differently, with different dynamical properties, depending upon, in this case, the symmetry of the system. It also suggests that a changing environment, that may change attributes such as mortality, could have profound effects on an ecosystem’s ability to adapt. Our results suggest that the properties of the three-dimensional model can provide useful insights into the properties of the higher-dimension models. In particular, the bifurcation properties of the simple model predict the processes by which the more complicated models produce evolutionary branching points. The corresponding bifurcation properties of the phenotype and population models, evident in the dynamics of the phenotype distributions they predict, suggest that our eco-evolutionary modelling framework captures the essential properties that underlie the evolution of phenotypes in populations.

Observational Constraints on Basin‐Scale Runoff: A Request for Both Improved ESMs and Streamflow Reconstructions

AbstractEfforts to predict long‐term changes in continental runoff at both global and basin scales generally remain ambiguous. Here we use a global runoff reconstruction and a Bayesian statistical method to narrow uncertainties in runoff projections from the latest generation of global climate models. Three representative tropical river basins are used to illustrate the application and showcase the potential for substantial reduction in modeling uncertainty. Yet, results are fairly sensitive to the selected reconstruction thus highlighting the need for reliable and homogeneized gridded runoff data sets or river discharge measurements. Moreover, climate models do not account for water withdrawals, whose effect on observed runoff should also be removed in order to detect and attribute the hydrological effect of climate change. Finally, and more importantly, most models fail at capturing the observed recent decrease in runoff ratio, which may highlight either model deficiencies or increasing water derivation over the selected river basins.

Future climate projection across Tanzania under CMIP6 with high-resolution regional climate model

Climate change is one of the most pressing challenges faced by developing countries due to their lower adaptive capacity, with far-reaching impacts on agriculture. The mid-century period is widely regarded as a critical moment, during which adaptation is deemed essential to mitigating the associated impacts. This study presents future climate projections across Tanzania using the latest generation of global climate models (CMIP6) combined with a high-resolution regional climate model. The findings indicate that, the trends in temperature and precipitation in Tanzania from 1991 to 2020, minimum temperatures showed the highest variability with a trend of 0.3 °C, indicating significant fluctuations in minimum temperature over the decades. Maximum temperatures also showed high variability with a trend of 0.4 °C. There is a range of variability in precipitation per decade for different regions in Tanzania, with some regions experiencing significant decreases in precipitation of up to − 90.3 mm and − 127.6 mm. However, there were also regions that experienced increases in precipitation, although these increases were generally less than 4.8 mm over the decades. The projections of minimum and maximum temperatures from 2040 to 2071 under the Shared Socioeconomic Pathways (SSP) 2–4.5 and SSP 5–8.5 are projected to increase by 0.14 °C to 0.21 °C per decade, across different regions. The average projected precipitation changes per decade vary across regions. Some regions are projected to experience increases in precipitation. Other regions are projected to show decreases in precipitation within the range of − 0.6 mm to 15.5 mm and − 1.5 mm to 47.4 mm under SSP2–4.5 and SSP5–8.5 respectively. Overall, both scenarios show an increase in projected temperatures and precipitation for most regions in Tanzania, with some areas experiencing more significant increases compared to others. The changes in temperatures and precipitation are expected to have significant impacts on agriculture and water resources in Tanzania.

NPCC4: New York City climate risk information 2022-observations and projections.

New York City (NYC) faces many challenges in the coming decades due to climate change and its interactions with social vulnerabilities and uneven urban development patterns and processes. This New York City Panel on Climate Change (NPCC) report contributes to the Panel's mandate to advise the city on climate change and provide timely climate risk information that can inform flexible and equitable adaptation pathways that enhance resilience to climate change. This report presents up-to-date scientific information as well as updated sea level rise projections of record. We also present a new methodology related to climate extremes and describe new methods for developing the next generation of climate projections for the New York metropolitan region. Future work by the Panel should compare the temperature and precipitation projections presented in this report with a subset of models to determine the potential impact and relevance of the "hot model" problem. NPCC4 expects to establish new projections-of-record for precipitation and temperature in 2024 based on this comparison and additional analysis. Nevertheless, the temperature and precipitation projections presented in this report may be useful for NYC stakeholders in the interim as they rely on the newest generation of global climate models.

Storylines for Future Projections of Precipitation Over New Zealand in CMIP6 Models

AbstractLarge uncertainty exists in the sign of long‐term changes in regional scale mean precipitation across the current generation of global climate models. To explore the physical drivers of this uncertainty for New Zealand, here we adopt a storyline approach applying cluster analysis to spatial patterns of future projected seasonal mean precipitation change across CMIP6 models (n = 43). For the winter precipitation change signal, the models split roughly into two main groups: both groups have a very robust wet signal across the west coast of the South Island but differ notably in terms of the sign of precipitation change across the north of the North Island. These far north winter precipitation differences appear related to how far the Hadley cell edge and regional eddy‐driven jet shift across the models relative to their historical positions. In contrast, for summer, most models have a markedly weaker and spatially non‐uniform response, where internal variability often plays a large role. However, a small group of models predict a robust wet signal across most of the country in summer. This “wet model” group is characterized by a regional La Niña‐like increase in high pressure shifted further to the south‐east of New Zealand, associated with more frequent north‐easterly flow over the country and accompanied by significant warming of local sea surface temperatures. This regional circulation response appears related to changes in stationary Rossby wave paths as opposed to changes in La Niña occurrence frequency itself.

Strong aerosol cooling alone does not explain cold-biased mid-century temperatures in CMIP6 models

Abstract. The current generation of global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) exhibits a surprisingly cold-biased ensemble-mean mid-20th century global-mean surface temperature anomaly, compared to the previous generation Phase 5 (CMIP5) and to the observed mid-century (1940–1970) temperature anomaly. Most CMIP6 models, 31 of 36 models in contrast to 17 of 27 CMIP5 models, are colder than the uncertainty range of the observed anomaly, indicating that the CMIP6 suppressed warming is not caused by a few cold models. However, no clear cause that sufficiently explains the tendency towards suppressed mid-20th century warming emerges. Whereas models that best match observations exclusively exhibit weaker aerosol forcing than that exhibited by colder models, there is not a clear relationship between mid-century temperatures and aerosol forcing. Likewise, no systematic differences emerge among other model aerosol representations, such as inclusion of aerosol–cloud interactions for ice clouds in the model or the type of aerosol model input data set used, nor variations in greenhouse gas forcing or climate sensitivity, that could explain the suppressed warming. This indicates the presence of another cause, or more likely a set of causes, of the suppressed warming in many CMIP6 models. Thus, the prospect of a strong constraint on present-day aerosol forcing based on the mid-century warming is weakened, even if it is encouraging that those models that do match the observed warming best all have relatively weak aerosol forcing.

Aridification of Colorado River Basin's Snowpack Regions Has Driven Water Losses Despite Ameliorating Effects of Vegetation

AbstractThe Colorado River Basin is an important natural resource for the semi‐arid southwestern United States (US), where it provides water to more than 40 million people. While nearly 1.5°C of anthropogenic warming has occurred across this region from the 1880s to 2021, climate models show little agreement in the precipitation change during the same historical period, with no trend in the mean of the latest (sixth) generation of Global Climate Models. As such, here we focus on how the CO2 increase and associated anthropogenic warming over the historical period has impacted runoff across the Colorado Basin. We find that the Colorado Basin's runoff over the historical period has decreased by 8.1% per degree Celsius of warming (°C−1). However, the magnitude of this sensitivity is reduced to 6.8% °C−1 when considering vegetation response to historical CO2. For present‐day conditions, this translates to runoff reductions of 10.3% due to anthropogenic increases in both temperature and CO2 since 1880. We demonstrate that Colorado Basin's natural flow has been decreased by roughly the storage of Lake Mead during the 2000–2021 megadrought due to this long term anthropogenic influence, suggesting the basin's first shortage in 2021 would likely not have occurred without anthropogenic warming. We further show warming has led to disproportionate aridification in snowpack regions, causing runoff to decline at double the rate relative to non‐snowpack regions. Thus, despite only making up ∼30% of the basin's drainage area, 86% of runoff decreases in the Colorado Basin is driven by water loss in snowpack regions.

CMIP6 Earth System Models Project Greater Acceleration of Climate Zone Change Due To Stronger Warming Rates

AbstractWarming climate and precipitation changes induce notable shifts in climate zones. In this study, the latest generation of global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the previous generation CMIP5 under high‐emission scenarios are used together with observations and applied to the Köppen‐Geiger climate classification. The aim is to shed light on how projected warming and changes in precipitation will influence future climate zones and their associated ecosystems while revealing differences between the two model generations. Compared to CMIP5 models, CMIP6 models exhibit slightly improved performance in replicating the observed Köppen‐Geiger map for the historical (1976–2005) period and similar inter‐model agreement for the future. The models show major changes in climate zones with a range of projections depending on which ensemble subset is used: 37.9%–48.1% of the global land area is projected to change climate zone by the end of the century, with the most pronounced changes expected over Europe (71.4%–88.6%) and North America (51.2%–65.8%). CMIP6 models project a higher rate of areal climate zone change (km2/year) throughout the 21st century, which is mainly driven by their greater global land warming rates. Using a likely equilibrium climate sensitivity subset of CMIP6 models that is consistent with the latest evidence constrains the climate zone shifts, and their projections better match the results of CMIP5 simulations. Although the high warming rates of some CMIP6 models are less credible, the risks associated with them are greater, and they heighten the need for urgent action to preserve terrestrial ecosystems.

Potential heat-risk avoidance from nationally determined emission reductions targets in the future

The increasing heat stress from the combined effect of changes such as temperature and humidity in the context of global change receives growing concerns. However, there is limited information for future changes in heat stress, as well as its potential socioeconomic impact, under the intended nationally determined mitigation scenarios. This study established an efficient evaluation method to quantify the benefits from the potential heat stress reduction from a continued intended nationally determined contributions (INDC) mitigation effort. The future heat stress over global land, quantified by the wet bulb globe temperature, was investigated based on the temperature sensitivity approach and multi-model simulations from the latest generation global climate models. The INDC continuous-effort scenario and the delayed-effort scenario, as well as the target-control scenarios of 2 °C warming, were compared. We found that with the delayed mitigation efforts, the increase in frequency, duration, and cumulative intensity of extreme heat stress relative to the INDC continuous-effort scenario in the late 21st century could reach to 113%, 193%, and 212%, respectively. If more ambitious efforts above current INDC pledges were implemented to achieve the 2 °C global temperature goal, the corresponding avoided impact of heat stress frequency, duration, and cumulative intensity in the late 21st century was estimated to be 32%, 37%, and 40%, respectively. Future changes in heat stress in low latitudes, where most developing countries are located, are most sensitive to emission reduction. Our results highlighted the potential avoided heat stress-related impact of global warming from efforts towards climate change mitigation.

Exposure of mammal genetic diversity to mid‐21st century global change

Accelerating climate and land‐use change are rapidly transforming Earth's biodiversity. While there is substantial evidence on the exposure and vulnerability of biodiversity to global change at the species level, the global exposure of intraspecific genetic diversity (GD) is still unknown. Here, we assess the exposure of mitochondrial GD to mid‐21st century climate and land‐use change in terrestrial mammal assemblages at grid‐cell and bioclimatic region scales under alternative narratives of future societal development. We used global predictions of mammal GD distribution based on thousands of georeferenced mitochondrial genes for hundreds of mammal species, the latest generation of global climate models from the ongoing sixth phase of the Coupled Model Intercomparison Project (CMIP6), and global future projections of land‐use prepared for CMIP6. We found that more than 50% of the genetically poorest geographic areas (grid‐cells), primarily distributed in tundra, boreal forests/taiga and temperate bioclimatic regions, will be exposed to mean annual temperature rise that exceeds 2°C compared to the baseline period under all considered future scenarios. We also show that at least 30% of the most genetically rich areas in tropical, subtropical and montane regions will be exposed to an increase of mean annual temperature > 2°C under less optimal scenarios. Genetic diversity in these rich regions is also predicted to be exposed to severe reductions of primary vegetation area and increasing human activities (an average loss of 5–10% of their total area under the less sustainable land‐use scenarios). Our findings reveal a substantial exposure of mammal GD to the combined effects of global climate and land‐use change. Meanwhile the post‐2020 conservation goals are overlooking genetic diversity, our study identifies both genetically poor and highly diverse areas severely exposed to global change, paving the road to better estimate the geography of biodiversity vulnerability to global change.

Implications of CMIP6 Projected Drying Trends for 21st Century Amazonian Drought Risk

AbstractRecent exceptionally hot droughts in Amazonia have highlighted the potential role of global warming in driving changes in rainfall and temperatures in the region. The previous generation of global climate models projected that eastern Amazonia would receive less future precipitation while western Amazonia would receive more precipitation, but many of these models disagreed on future precipitation trends in the region. Here Coupled Modeling Intercomparison Project, Phase 6 (CMIP6) models are used to examine the shifting risk of eastern Amazonian droughts under high and low future greenhouse gas emissions scenarios. This new generation of models shows better agreement that most of the Amazonian basin will receive less future rainfall, with particularly strong agreement that eastern and southern Amazonia will dry in the 21st century. These models suggest that global warming may be increasing the likelihood of exceptionally hot drought in the region. With unabated global warming, recent particularly warm and severe droughts will become more common by midcentury, but reducing the rate of greenhouse gas emissions can make extremely hot and dry years less common in the future. Simulated future rainfall changes in Amazonia under high greenhouse gas emissions are associated with changes in the tropical Pacific, but many climate models struggle to reproduce observed trends in the tropical Pacific. These shortcomings highlight the need to improve confidence in global climate models' ability to simulate observed trends in the tropics, even if more CMIP6 models agree on the sign of future rainfall trends.

Improving the Southern Ocean cloud albedo biases in a general circulation model

Abstract. The present generation of global climate models is characterised by insufficient reflection of short-wave radiation over the Southern Ocean due to a misrepresentation of clouds. This is a significant concern as it leads to excessive heating of the ocean surface, sea surface temperature biases and subsequent problems with atmospheric dynamics. In this study, we modify cloud microphysics in a recent version of the Met Office's Unified Model and show that choosing a more realistic value for the shape parameter of atmospheric ice crystals, in better agreement with theory and observations, benefits the simulation of short-wave radiation. In the model, for calculating the growth rate of ice crystals through deposition, the default assumption is that all ice particles are spherical in shape. We modify this assumption to effectively allow for oblique shapes or aggregates of ice crystals. Along with modified ice nucleation temperatures, we achieve a reduction in the annual-mean short-wave cloud radiative effect over the Southern Ocean by up to ∼4 W m−2 and seasonally much larger reductions compared to the control model. By slowing the growth of the ice phase, the model simulates substantially more supercooled liquid cloud.

Drivers of the enhanced decline of land near-surface relative humidity to abrupt 4xCO2 in CNRM-CM6-1

Projected changes in near-surface relative humidity (RH) remain highly model-dependent over land and may have been underestimated by the former generation global climate models. Here the focus in on the recent CNRM-CM6-1 model, which shows an enhanced land surface drying in response to quadrupled atmospheric CO2 compared to its CNRM-CM5 predecessor. Atmosphere-only experiments with prescribed sea surface temperature (SST) are used to decompose the simulated RH changes into separate responses to uniform SST warming, pattern of SST anomalies, changes in sea-ice concentration, as well as direct radiative and physiological CO2 effects. Results show that the strong drying simulated by CNRM-CM6-1 is due to both fast CO2 effects and a SST-mediated response. The enhanced drying compared to CNRM-CM5 is partly due to the introduction of the physiological CO2 effect that was not accounted for in CNRM-CM5. The global ocean warming also contributes to the RH decline over land, in reasonable agreement with the moisture advection mechanism proposed by earlier studies which however does not fully capture the contrasted RH response between the two CNRM models. The SST anomaly pattern is a significant driver of changes in RH humidity at the regional scale, which are partly explained by changes in atmospheric circulation. The improved land surface model may also contribute to a stronger soil moisture feedback in CNRM-CM6-1, which can amplify the surface aridity induced by global warming and, thereby, lead to a non-linear response of RH.

Effective resolution in high resolution global atmospheric models for climate studies

AbstractWe estimate the extent of spatial scales that atmospheric models in a new generation of global climate models, used in the Coupled Model Intercomparison Project 6, are able to resolve on the basis of kinetic energy spectra, commonly referred to as the effective resolution. We examine the spectra derived from the rotational and divergent parts of the wind for six state‐of‐the‐art global climate models that have been run with at least two horizontal resolutions. For each of the high resolution configurations, the effective resolution enhancement is less than proportional to the increase of the nominal resolution. The highest effective resolution obtained by the models in this study is roughly 200 km. This shows that the newest generation of high resolution climate models starts to resolve synoptic scales relevant for the dynamics of weather events.

Skill of CMIP5 climate models to reproduce the stability indices in identifying thunderstorms over the Gangetic West Bengal

The skills of present generation Global Climate Models (GCMs) have been evaluated in reproducing the climatology of stability indices for the identification of thunderstorm over the Gangetic West Bengal (GWB) region. Three different stability Indices viz., K-Index (KI), Boyden Index (BI), and Total Totals Index (TT) have been used in this study. Estimated values of TT and BI from reanalysis data have shown significant (at 10%) declining trends in pre-monsoon season however, they have a similar month-to-month variation of trends as simulated by the GCMs. Similar declining trends as reanalysis data were also noticed in March. On the other hand, most GCMs were able to reproduce the mean climatology of BI and TT but failed to show better skill for KI. The values of correlation between GCMs simulated TT and KI have shown decreasing trends from March to May months which was almost similar to the reanalysis data. In general, the frequency of occurrence of different types of thunderstorms was more in May and less in March as per the analysis of KI and TT indices from the reanalysis data. It was found that few GCMs were able to discriminate the occurrences of thunderstorm/non-thunderstorm like the reanalysis data. Over the study region, either of KI or TT or a combination of both may be used to study the occurrence of thunderstorm/non-thunderstorms. However, based on the analysis of climatological mean, trend, and threshold values, TT has shown better performance than KI. It is concluded that the present generation of GCMs has shown a mixed response in simulating the stability indices to identify thunderstorm/non-thunderstorms over the GWB.

The impact of climate model sea surface temperature biases on tropical cyclone simulations

Sea surface temperature (SST) patterns both local to and remote from tropical cyclone (TC) development regions are important drivers of the variability of TC activity. Therefore, reliable simulations and predictions of TC activity depend on a realistic representation of tropical SST. Nevertheless, severe SST biases are common to the current generation of global climate models, especially in the tropical Pacific and Atlantic. These biases are strongly positive in the southeastern tropical basins, and negative, but weaker, in the northwestern tropical basins. To investigate the impact of the tropical SST biases on simulated TC activity, an atmospheric-only tropical channel model was used to conduct several sets of ensemble simulations. The simulations suggest an underrepresentation in Atlantic TC activity caused by the Atlantic cold bias alone, and an overrepresentation in Eastern North Pacific (ENP) TC activity due to the Atlantic cold bias and Pacific warm bias jointly. While the local impact of SST biases on TC activity is generally induced by the local anomalous SST and the associated changes in atmospheric conditions, the remote impact of the Atlantic bias on the ENP TCs is strongly driven by the change in topographically forced regional circulation. Moreover, an eastward shift in Western North Pacific TCs was generated by the Pacific SST biases, even though basin-wide TC activity indicators change insignificantly. The results indicate the importance of considering SST bias effects on simulated TC activity in climate model studies and highlight key regions where reducing SST biases could potentially improve TC representation in climate models.

Dynamical and Thermodynamic Elements of Modeled Climate Change at the East African Margin of Convection

AbstractWe propose a dynamical interpretation of model projections for an end‐of‐century wetting in equatorial East Africa. In the current generation of global climate models, increased atmospheric moisture content associated with warming is not the dominant process explaining the increase in rainfall, as the regional circulation is only weakly convergent even during the rainy seasons. Instead, projected wetter future conditions are generally consistent with the El Niño‐like trend in tropical Pacific sea surface temperatures in climate models. In addition, a weakening in moisture convergence over the adjacent Congo Basin and Maritime Continent cores of convection results in the weakening of near‐surface winds, which increases moisture advection from the Congo Basin core toward the East African margin. Overall confidence in the projections is limited by the significant biases in simulation of the regional climatology and disagreement between observed and modeled tropical Pacific sea surface temperature trends to date.

Simulation, Modeling, and Dynamically Based Parameterization of Organized Tropical Convection for Global Climate Models

Abstract A new approach for treating organized convection in global climate models (GCMs) referred to as multiscale coherent structure parameterization (MCSP) introduces physical and dynamical effects of organized convection that are missing from contemporary parameterizations. The effects of vertical shear are approximated by a nonlinear slantwise overturning model based on Lagrangian conservation principles. Simulation of the April 2009 Madden–Julian oscillation event during the Year of Tropical Convection (YOTC) over the Indian Ocean using the Weather Research and Forecasting (WRF) Model at 1.3-km grid spacing identifies self-similar properties for squall lines, MCSs, and superclusters embedded in equatorial waves. The slantwise overturning model approximates this observed self-similarity. The large-scale effects of MCSP are examined in two categories of GCM. First, large-scale convective systems simulated in an aquaplanet model are approximated by slantwise overturning with attention to convective momentum transport. Second, MCSP is utilized in the Community Atmosphere Model, version 5.5 (CAM5.5), as tendency equations for second-baroclinic heating and convective momentum transport. The difference between MCSP and CAM5.5 is a direct measure of the global effects of organized convection. Consistent with TRMM measurements, the MCSP generates large-scale precipitation patterns in the tropical warm pool and the adjoining locale; improves precipitation in the intertropical convergence zone (ITCZ), South Pacific convergence zone (SPCZ), and Maritime Continent regions; and affects tropical wave modes. In conclusion, the treatment of organized convection by MCSP is salient for the next generation of GCMs.