Search NASA⌕ Search

SEARCH · Search NASA

Results for “Climate feedbacks”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Radiative and Physiological Effects of Increased CO2: How Does This Interaction Affect Climate?

Several climate models indicate that in a 2xCO2 environment, temperature and precipitation would increase and runoff would increase faster than precipitation. These models, however, did not allow the vegetation to increase its leaf density as a response to the physiological effects of increased CO2 and consequent changes in climate. Other assessments included these interactions but did not account for the vegetation downregulation to reduce plant's photosynthetic activity and as such resulted in a weak vegetation negative response. When we combine these interactions in climate simulations with 2xCO2, the associated increase in precipitation contributes primarily to increase evapotranspiration rather than surface runoff, consistent with observations, and results in an additional cooling effect not fully accounted for in previous 2xCO2 simulations. By accelerating the water cycle, this feedback slows but does not alleviate the projected warming, reducing the land surface warming by 0.6 C. Compared to previous studies, these results imply that long term negative feedback from CO2-induced increases in vegetation density could reduce temperature following a stabilization of CO2 concentration.

Bounoua, Lahouari↗
NASA NTRS2017

Global Precipitation Products at NASA GES DISC for Supporting Agriculture Research and Applications

This presentation describes precipitation products available at the NASA GES DISC that support agricultural research. XXXX Key environmental variables for agriculture: precipitation, temperature, water (soil moisture), solar radiation, NDVI, etc. Rainfed agriculture - major farming practices that rely on rainfall for water. Rainfed agriculture: >95% of farmed land (sub- Saharan Africa); 90% (Latin America); 75% (Near East and North Africa); 65% (East Asia); 60% (South Asia). Precipitation is very important for rainfed agriculture. Droughts can cause severe damage. Precipitation information can be used to monitor the growing season. The Goddard Earth Sciences (GES) Data and Information Services Center (DISC), one of 12 NASA data centers, located in Greenbelt, Maryland, USA. The GES DISC is a major data archive center for global precipitation, water & energy cycles, atmospheric composition, and climate variability Global and regional precipitation datasets (satellite-based and data assimilation Data services (subsetting, format conversion, online visualization, etc.) User services are available FAQs, How to (recipes), Glossary, etc. Social media (Twitter, YouTube, User forum) Help desk (phone, email, online feedback) Training materials (ARSET => Applied Remote Sensing Training) Liu,

precipitation↗
NASA NTRS2017

A 4 U Laser Heterodyne Radiometer for Methane (CH4) and Carbon Dioxide (CO2) Measurements from an Occultation-Viewing CubeSat

We present a design for a 4 U (20 cm 20 cm 10 cm) occultation-viewing laser heterodyne radiometer (LHR) that measures methane (CH4), carbon dioxide (CO2) and water vapor(H2O) in the limb that is designed for deployment on a 6 U CubeSat. The LHR design collects sunlight that has undergone absorption by the trace gas and mixes it with a distributive feedback (DFB) laser centered at 1640 nm that scans across CO2, CH4, and H2O absorption features. Upper troposphere lower stratosphere measurements of these gases provide key inputs to stratospheric circulation models: measuring stratospheric circulation and its variability is essential for projecting how climate change will affect stratospheric ozone.

occultation↗
NASA NTRSDate not supplied

Composition and Climate Impacts of Increasing Launches to Low Earth Orbit

We present simulations of an Earth system model in which launch vehicles inject gaseous and particulate combustion products into the stratosphere. We considered two plausible scenarios representative for the year 2050, one with 1000 launches per year and another with 10 times more, all of which assuming heavy lift (80 tons to low Earth orbit; LEO) launches using methane as a proxy for liquefied natural gas (LNG) fuel. An industry-standard plume flowfield model was used to predict emission of gaseous species including carbon monoxide, nitrogen oxides, and water vapor. Black carbon was introduced assuming vacuum emission equal 25% of equivalent kerosene engine. The gas emissions showed marginal or insignificant changes in atmospheric composition, while the black carbon emission was found to be the most influential component. Feedbacks involve tropopause and stratospheric warming, followed by a moistening of the stratosphere via tropospheric water vapor intrusions, together with a reduction in global albedo. The fact that LNG-fueled rockets could be a concern from aerosol emissions in our simulations, despite burning more efficiently than conventional fuels, underscores the need to better understand actual black carbon emissions from rocket engines in order to accurately predict the global impacts of launch vehicles on future climate.

Earth system model↗
NASA NTRS2020

Toward More Realistic Simulation and Prediction of Dust Storms on Mars

Major (regional and global)dust storms dominate weather and climate variability on present-day Mars. Absorption and scattering of visible and IR radiation by dust strongly affect the thermal state of the thin Mars atmosphere, while dust provides condensation nuclei for water and CO2 cloud particles, which also affect radiative fluxes. Global dust storms (GDS) occur ~three times per Mars decade and to date have been observed in only northern fall and winter,when the global circulation is strongest. Tenfold increases in column dust opacity are typical during GDS, with intense vertical motions transporting dust to far higher altitudes than usual. The key processes and feedbacks that produce GDS remain poorly understood, hence current atmospheric models fail to self-consistently simulate observed dust storm activity. This means we have no predictive capability for when GDS may occur, either now or in Mars’s past. And crucially, due to the huge impact of GDS on the atmosphere and surface, our lack of ability to simulate realistic dust storms has major implications for Mars science and exploration: from understanding the present climate (§2.1),to modeling past climates and water cycles (§2.2), to exploring how wind, water, and dust cycles varied over time to interpret geology and assess potential habitability(§2.3), to quantifying and mitigating risks posed to Mars missions (§2.4)

Claire E Newman↗
NASA NTRS2002

The Sun's Impact on Climate

We provide an overview of the impact of the Sun on the Earth atmosphere and climate system, focused on heating of Earth's atmosphere and oceans. We emphasize the importance of the spectral measurements of SIM and SOLSTICE- that we must know how solar variations are distributed over ultraviolet, visible, and infrared wavelengths, since these have separate characteristic influences on Earth's ozone layer, clouds, and upper layers of the oceans. Emphasis is also given to understanding both direct and indirect influences of the Sun on the Earth, which involve feedbacks between Earth's stratosphere, troposphere, and oceans, each with unique time scales, dynamics, chemistry, and biology, interacting non-linearly. Especially crucial is the role of all three phases of water on Earth, water vapor being the primary greenhouse gas in the atmosphere, the importance of trace gases such as CO2 arising from their absorption in the "water vapor window" at 800 - 1250/cm (12.5 to 8 microns). Melting of polar ice is one major response to the post-industrial global warming, enhanced due to "ice-albedo" feedback. Finally, water in liquid form has a major influence due to cloud albedo feedback, and also due to the oceans' absorption of solar radiation, particularly at visible wavelengths, through the visible "liquid water window" that allows penetration of visible light deep into the mixed layer, while nearby ultraviolet and infrared wavelengths do not penetrate past the upper centimeter ocean surface skin layer. A large fraction of solar energy absorbed by the oceans goes into the latent heat of evaporation. Thus the solar heating of the atmosphere-ocean system is strongly coupled through the water cycle of evaporation, cloud formation, precipitation, surface runoff and ice formation, to Earth's energy budget and climate, each different climate component responding to variations in different solar spectral bands, at ultraviolet, visible and infrared wavelengths.

Cahalan, Robert↗
NASA NTRS2004

Seasonal-to-Interannual Variability and Land Surface Processes

Atmospheric chaos severely limits the predictability of precipitation on subseasonal to interannual timescales. Hope for accurate long-term precipitation forecasts lies with simulating atmospheric response to components of the Earth system, such as the ocean, that can be predicted beyond a couple of weeks. Indeed, seasonal forecasts centers now rely heavily on forecasts of ocean circulation. Soil moisture, another slow component of the Earth system, is relatively ignored by the operational seasonal forecasting community. It is starting, however, to garner more attention. Soil moisture anomalies can persist for months. Because these anomalies can have a strong impact on evaporation and other surface energy fluxes, and because the atmosphere may respond consistently to anomalies in the surface fluxes, an accurate soil moisture initialization in a forecast system has the potential to provide additional forecast skill. This potential has motivated a number of atmospheric general circulation model (AGCM) studies of soil moisture and its contribution to variability in the climate system. Some of these studies even suggest that in continental midlatitudes during summer, oceanic impacts on precipitation are quite small relative to soil moisture impacts. The model results, though, are strongly model-dependent, with some models showing large impacts and others showing almost none at all. A validation of the model results with observations thus naturally suggests itself, but this is exceedingly difficult. The necessary contemporaneous soil moisture, evaporation, and precipitation measurements at the large scale are virtually non-existent, and even if they did exist, showing statistically that soil moisture affects rainfall would be difficult because the other direction of causality - wherein rainfall affects soil moisture - is unquestionably active and is almost certainly dominant. Nevertheless, joint analyses of observations and AGCM results do reveal some suggestions of land-atmosphere feedback in the observational record, suggestions that soil moisture can affect precipitation over seasonal timescales and across certain large continental areas. The strength of this observed feedback in nature is not large but is still significant enough to be potentially useful, e.g., for forecasts. This talk will address all of these issues. It will begin with a brief overview of land surface modeling in atmospheric models but will then focus on recent research - using both observations and models - into the impact of land surface processes on variability in the climate system.

Koster, Randal↗
NASA NTRS2019

The Global Fire Atlas of Individual Fire Size, Duration, Speed and Direction

Natural and human-ignited fires affect all major biomes, altering ecosystem structure, biogeochemical cycles and atmospheric composition. Satellite observations provide global data on spatiotemporal patterns of biomass burning and evidence for the rapid changes in global fire activity in response to land management and climate. Satellite imagery also provides detailed information on the daily or sub-daily position of fires that can be used to understand the dynamics of individual fires. The Global Fire Atlas is a new global dataset that tracks the dynamics of individual fires to determine the timing and location of ignitions, fire size and duration, and daily expansion, fire line length, speed, and direction of spread. Here, we present the underlying methodology and Global Fire Atlas results for 2003–2016 derived from daily moderate-resolution (500 m) Collection 6 MCD64A1 burned-area data. The algorithm identified 13.3 million individual fires over the study period, and estimated fire perimeters were in good agreement with independent data for the continental United States. A small number of large fires dominated sparsely populated arid and boreal ecosystems, while burned area in agricultural and other human-dominated landscapes was driven by high ignition densities that resulted in numerous smaller fires. Long-duration fires in boreal regions and natural landscapes in the humid tropics suggest that fire season length exerts a strong control on fire size and total burned area in these areas. In arid ecosystems with low fuel densities, high fire spread rates resulted in large, short-duration fires that quickly consumed available fuels. Importantly, multiday fires contributed the majority of burned area in all biomass burning regions. A first analysis of the largest, longest and fastest fires that occurred around the world revealed coherent regional patterns of extreme fires driven by large-scale climate forcing. Global Fire Atlas data are publicly available through http://www.globalfiredata.org (last access: 9 August 2018) and https://doi.org/10.3334/ORNLDAAC/1642, and individual fire information and summary data products provide new information for benchmarking fire models within ecosystem and Earth system models, understanding vegetation–fire feedbacks, improving global emissions estimates, and characterizing the changing role of fire in the Earth system.

global fire atlas↗
NASA NTRSDate not supplied

Supporting Arctic Research, Engagement, and Policy With GMAO’s Next Generation Reanalysis & Prediction Systems

Modeling efforts at NASA aim to advance scientific understanding of the Earth system and its response to natural and human-induced changes and to improve our ability to predict climate, weather, and natural hazards. These efforts are particularly relevant for communities, scientists and stakeholders working and living in the Arctic. Here, we highlight current and planned Earth system prediction and data assimilation products from the Global Modeling and Assimilation Office (GMAO). We invite feedback and discussion on GMAO’s model and reanalysis development in support of Arctic research, engagement, and policy.

Lauren C Andrews↗
NASA NTRS2017

Selection of a Representative Subset of Global Climate Models that Captures the Profile of Regional Changes for Integrated Climate Impacts Assessment

We present the Representative Temperature and Precipitation (T&P) GCM Subsetting Approach developed within the Agricultural Model Intercomparison and Improvement Project (AgMIP) to select a practical subset of global climate models (GCMs) for regional integrated assessment of climate impacts when resource limitations do not permit the full ensemble of GCMs to be evaluated given the need to also focus on impacts sector and economics models. Subsetting inherently leads to a loss of information but can free up resources to explore important uncertainties in the integrated assessment that would otherwise be prohibitive. The Representative T&P GCM Subsetting Approach identifies five individual GCMs that capture a profile of the full ensemble of temperature and precipitation change within the growing season while maintaining information about the probability that basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry) are projected in the full GCM ensemble. We demonstrate the selection methodology for maize impacts in Ames, Iowa, and discuss limitations and situations when additional information may be required to select representative GCMs. We then classify 29 GCMs over all land areas to identify regions and seasons with characteristic diagonal skewness related to surface moisture as well as extreme skewness connected to snow-albedo feedbacks and GCM uncertainty. Finally, we employ this basic approach to recognize that GCM projections demonstrate coherence across space, time, and greenhouse gas concentration pathway. The Representative T&P GCM Subsetting Approach provides a quantitative basis for the determination of useful GCM subsets, provides a practical and coherent approach where previous assessments selected solely on availability of scenarios, and may be extended for application to a range of scales and sectoral impacts.

Climate Change; GCMs; Climate Model Subset; Repres↗
NASA NTRS2012

Changes in the Intensity and Frequency of Atmospheric Blocking and Associated Heat Waves During Northern Summer Over Eurasia in the CMIP5 Model Simulations

The Russia heat wave and wild fires of the summer of 2010 was the most extreme weather event in the history of the country. Studies show that the root cause of the 2010 Russia heat wave/wild fires was an atmospheric blocking event which started to develop at the end of June and peaked around late July and early August. Atmospheric blocking in the summer of 2010 was anomalous in terms of the size, duration, and the location, which shifted to the east from the normal location. This and other similar continental scale severe summertime heat waves and blocking events in recent years have raised the question of whether such events are occurring more frequently and with higher intensity in a warmer climate induced by greenhouse gases. We studied the spatial and temporal distributions of the occurrence and intensity of atmospheric blocking and associated heat waves for northern summer over Eurasia based on CMIPS model simulations. To examine the global warming induced change of atmospheric blocking and heat waves, experiments for a high emissions scenario (RCP8.S) and a medium mitigation scenario (RCP4.S) are compared to the 20th century simulations (historical). Most models simulate the mean distributions of blockings reasonably well, including major blocking centers over Eurasia, northern Pacific, and northern Atlantic. However, the models tend to underestimate the number of blockings compared to MERRA and NCEPIDOE reanalysis, especially in western Siberia. Models also reproduced associated heat waves in terms of the shifting in the probability distribution function of near surface temperature. Seven out of eight models used in this study show that the frequency of atmospheric blocking over the Europe will likely decrease in a warmer climate, but slightly increase over the western Siberia. This spatial pattern resembles the blocking in the summer of 2010, indicating the possibility of more frequent occurrences of heat waves in western Siberia. In this talk, we will also discuss the potential effect of atmosphere-land feedback, particularly how the wetter spring affects the frequency and intensity of atmospheric blocking and heat wave during summer.

Kim, Kyu-Myong↗
NASA NTRS2019

A Crop Yield Change Emulator for Use in GCAM and Similar Models: Persephone v1.0

Future changes in Earth system state will impact agricultural yields and, through these changed yields, can have profound impacts on the global economy. Global gridded crop models estimate the influence of these Earth system changes on future crop yields but are often too computationally intensive to dynamically couple into global multisector economic models, such as the Global Change Assessment Model (GCAM) and other similar-in-scale models. Yet, generalizing a faster site-specific crop model’s results to be used globally will introduce inaccuracies, and the question of which model to use is unclear given the wide variation in yield response across crop models. To examine the feedback loop among socioeconomics, Earth system changes, and crop yield changes, rapidly generated yield responses with some quantification of crop response uncertainty are desirable. The Persephone v1.0 response functions presented in this work are based on the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Climate-Crop Modeling Project (C3MP) sensitivity test data set and are focused on providing GCAM and similar models with a tractable number of rapid to evaluate dynamic yield response functions corresponding to a range of the yield response sensitivities seen in the C3MP data set. With the Persephone response functions, a new variety of agricultural impact experiments will be open to GCAM and other economic models: for example, examining the economic impacts of a multi-year drought in a key agricultural region and how economic changes in response to the drought can, in turn, impact the drought.

Snyder, Abigail↗
NASA NTRS2020

GISS Model E2.2: A Climate Model Optimized for the Middle Atmosphere. Part 2: Validation of Large-Scale Transport and Evaluation of Climate Response

Here we examine the large‐scale transport characteristics of the new ``Middle Atmosphere" NASA Goddard Institute for Space Studies climate model (E2.2). First we evaluate the stratospheric transport circulation in historical atmosphere‐only simulations integrated with interactive trace gas and aerosol chemistry. Compared to lower vertical resolution model versions, E2.2 exhibits improved tropical ascent and older stratospheric mean ages that are more consistent with observed values. In the troposphere, poleward transport to the Arctic and interhemispheric mean ages in E2.2 are comparable to models participating in the Chemistry Climate Modeling Initiative. In addition to validating E2.2 we also assess its ``transport sensitivity" using the coupled atmosphere‐ocean abrupt 4xCO2 and transient 1%CO2 simulations submitted to the Coupled Model Intercomparison Project, Phase 6, along with a 2xCO2 simulation used to evaluate the linearity of the transport circulation's response to increased CO2. We show that decreases (increases) in a stratospheric mean age (idealized surface loss) tracer scale linearly with increased lower stratospheric upwelling, which also increases linearly with warming tropical sea surface temperatures (SSTs). Abrupt 2xCO2 and 4xCO2 experiments constrained with (fixed) pre‐industrial SSTs are also used to quantify the relative importance of rapid adjustments versus SST feedbacks to the transport circulation responses in the model. Finally, sensitivity experiments are presented to illustrate the impact of changes in the convective parameterization on stratospheric transport.

GISS Model E2.2↗
NASA NTRSDate not supplied

Role of Arctic Low Clouds in the Arctic Climate System: Isolating the Surface Type Influence on Arctic Low-Clouds

Interactions between sea ice and clouds represent a mechanism through which sea ice influences climate. Understanding the cloud response to the rapidly changing Arctic surface properties is necessary for improving climate simulations and projection of future change inside and outside the Arctic. Towards the goal of understanding the cloud response to sea ice, we composite cloud properties for ice-free, marginal ice zone (MIZ), and ice-covered surfaces during MIZ crossing events to analyze the cloud property differences between surface types. Restricting the analysis to MIZ crossing events enables the isolation of the sea ice effect on clouds from meteorological factors. We find larger cloud fraction and total water concentration below ~1.5 km over ice-free relative to ice-covered surfaces during non-summer months. During summer, the results suggest larger cloud fraction and total water concentration over ice-free surfaces, however differences do not exceed observational uncertainty. Cloud property differences are linked to atmospheric thermodynamic profile differences, namely ice-free surfaces are warmer, moister, less stable, and have more positive surface turbulent fluxes than ice-covered surfaces. Ice-free minus ice-covered cloud property differences scale with surface temperature differences and are only found in the presence of a surface temperature difference. Our results suggest a 0.02 cloud fraction and 0.005 g m 3 total water concentration increase (~5%) at the level of maximum cloud fraction between 2000-2021 due to the observed Arctic sea ice decline in fall, corresponding to ~2 Wm 2 increase in the net surface radiative flux supporting a positive sea ice-cloud radiative feedback in fall and winter and a negative sea ice-cloud radiative feedback in spring. We propose an updated conceptual model where the average surface type influence on cloud properties is mediated by surface temperature differences between ice-free and ice-covered surfaces.

Arctic climate↗
NASA NTRS1999

Response to CO2 Transient Increase in the GISS Coupled Model: Regional Coolings in a Warming Climate

The (GISS) Goddard Institute for Space Studies coupled atmosphere-ocean model is used to investigate the effect of increased atmospheric CO2 by comparing a compounded 1 percent CO2 increase experiment with a control simulation. After 70 years of integration, the global surface air temperature in the 1 percent CO2 experiment is 1.43 C warmer. In spite of this global warming, there are two distinct regions, the northern Atlantic Ocean and the southern Pacific Ocean, where the surface air temperature is up to 4 C cooler. This situation is maintained by two positive feedbacks: a local effect on convection in the South Pacific and a non-local impact on the meridional circulation in the North Atlantic. The poleward transport of latent energy and dry static energy by the atmosphere is greater in the 1 percent CO2 experiment, caused by warming and therefore increased water vapor and greater greenhouse capacity at lower latitudes. The larger atmospheric transports tend to reduce upward vertical fluxes of heat and moisture from the ocean surface at high latitudes, which has the effect of stabilizing the ocean, reducing both convection and the thermohaline circulation. With less convection, less warm water is brought up from below, and with a reduced North Atlantic thermohaline circulation (by 30 percent at time of CO2 doubling), the poleward energy transport by the oceans decreases. The colder water then leads to further reductions in evaporation, decreases of salinity at high latitudes, continued stabilization of the ocean, and maintenance of reduced convection and meridional overturning. Although sea ice decreases globally, it increases in the cooling regions which reduces the overall climate sensitivity; its effect is most pronounced in the Southern Hemisphere. Tropical warming has been observed over the past several decades; if modeling studies such as this and others which have produced similar effects are valid, these processes may already be beginning.

Russell, Gary L.↗
NASA NTRS2019

How Do Climate Change Experiments Alter Plot-Scale Climate?

To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation. Climate manipulations can manifest in complex ways, however, challenging interpretations of biological responses. We reviewed publications to compile a database of daily plot-scale climate data from 15 active-warming experiments. We find that the common practices of analysing treatments as mean or categorical changes (e.g. warmed vs.unwarmed) masks important variation in treatment effects over space and time. Our synthesis showed that measured mean warming, in plots with the same target warming within a study, differed by up to 1.6° Celsius degrees (63% of target), on average, across six studies with blocked designs. Variation was high across sites and designs: for example, plots differed by 1.1°Celsius degrees (47% of target) on average, for infrared studies with feedback control (n = 3) vs. by 2.2° Celsius degrees (80% of target) on average for infrared with constant wattage designs (n = 2). Warming treatments produce non-temperature effects as well, such as soil drying. The combination of these direct and indirect effects is complex and can have important biological consequences. With a case study of plant phenology across five experiments in our database, we show how accounting for drier soils with warming tripled the estimated sensitivity of budburst to temperature. We provide recommendations for future analyses, experimental design,and data sharing to improve our mechanistic understanding from climate change experiments, and thus their utility to accurately forecast species' responses.

warming experiment↗
NASA NTRS1983

Simple energy balance model resolving the seasons and the continents - Application to the astronomical theory of the ice ages

An analysis is undertaken of the properties of a one-level seasonal energy balance climate model having explicit, two-dimensional land-sea geography, where land and sea surfaces are strictly distinguished by the local thermal inertia employed and transport is governed by a smooth, latitude-dependent diffusion mechanism. Solutions of the seasonal cycle for the cases of both ice feedback exclusion and inclusion yield good agreements with real data, using minimal turning of the adjustable parameters. Discontinuous icecap growth is noted for both a solar constant that is lower by a few percent and a change of orbital elements to favor cool Northern Hemisphere summers. This discontinuous sensitivity is discussed in the context of the Milankovitch theory of the ice ages, and the associated branch structure is shown to be analogous to the 'small ice cap' instability of simpler models.

North, G. R.↗
NASA NTRS2022

Mid-Pliocene El Niño/Southern Oscillation Suppressed By Pacific Intertropical Convergence Zone Shift

The El Niño/Southern Oscillation (ENSO), the dominant driver of year-to-year climate variability in the equatorial Pacific Ocean, impacts climate pattern across the globe. However, the response of the ENSO system to past and potential future temperature increases is not fully understood. Here we investigate ENSO variability in the warmer climate of the mid-Pliocene (~3.0–3.3 Ma), when surface temperatures were ~2–3 °C above modern values, in a large ensemble of climate models—the Pliocene Model Intercomparison Project. We show that the ensemble consistently suggests a weakening of ENSO variability, with a mean reduction of 25% (±16%). We further show that shifts in the equatorial Pacific mean state cannot fully explain these changes. Instead, ENSO was suppressed by a series of off-equatorial processes triggered by a northward displacement of the Pacific intertropical convergence zone: weakened convective feedback and intensified Southern Hemisphere circulation, which inhibit various processes that initiate ENSO. The connection between the climatological intertropical convergence zone position and ENSO we find in the past is expected to operate in our warming world with important ramifications for ENSO variability.

Atmospheric dynamics↗