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NASA NTRS2019

The Connected Isotopic Water Cycle in the Community Earth System Model Version 1

Because of the pervasive role of water in the Earth system, the relative abundances of stable isotopologues of water are valuable for understanding atmospheric, oceanic, and biospheric processes, and for interpreting paleoclimate proxy reconstructions. Isotopologues are transported by both largescale and turbulent flows, and the ratio of heavy to light isotopologues changes due to fractionation that can accompany condensation and evaporation processes. Correctly predicting the isotopic distributions requires resolving the relationships between largescale ocean and atmospheric circulation and smallerscale hydrological processes, which can be accomplished within a coupled climate modeling framework. Here we present the water isotopeenabled version of the Community Earth System Model version 1 (iCESM1), which simulates global variations in water isotopic ratios in the atmosphere, land, ocean, and sea ice. In a transient Last Millennium simulation covering the 850-2005 period, iCESM1 correctly captures the latetwentiethcentury structure of δ(exp 18)O and δD over the global oceans, with more limited accuracy over land. The relationship between salinity and seawater δ(exp 18)O is also well represented over the observational period, including interbasin variations. We illustrate the utility of coupled, isotopeenabled simulations using both Last Millennium simulations and freshwater hosing experiments with iCESM1. Closing the isotopic mass balance between all components of the coupled model provides new confidence in the underlying depiction of the water cycle in CESM, while also highlighting areas where the underlying hydrologic balance can be improved. The iCESM1 is poised to be a vital community resource for ongoing model development with both modern and paleoclimate applications.

Brady, E.↗
NASA NTRS2016

The Model Intercomparison Project on the Climatic Response to Volcanic Forcing (VolMIP): Experimental Design and Forcing Input Data for CMIP6

The enhancement of the stratospheric aerosol layer by volcanic eruptions induces a complex set of responses causing global and regional climate effects on a broad range of timescales. Uncertainties exist regarding the climatic response to strong volcanic forcing identified in coupled climate simulations that contributed to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). In order to better understand the sources of these model diversities, the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) has defined a coordinated set of idealized volcanic perturbation experiments to be carried out in alignment with the CMIP6 protocol. VolMIP provides a common stratospheric aerosol data set for each experiment to minimize differences in the applied volcanic forcing. It defines a set of initial conditions to assess how internal climate variability contributes to determining the response. VolMIP will assess to what extent volcanically forced responses of the coupled ocean-atmosphere system are robustly simulated by state-of-the-art coupled climate models and identify the causes that limit robust simulated behavior, especially differences in the treatment of physical processes. This paper illustrates the design of the idealized volcanic perturbation experiments in the VolMIP protocol and describes the common aerosol forcing input data sets to be used.

Volcanoes↗
NASA NTRS2015

Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections

The representative concentration pathway (RCP) simulations included in phase 5 of the Coupled Model Intercomparison Project (CMIP5) quantify the response of the climate system to different natural and anthropogenic forcing scenarios. These simulations differ because of 1) forcing, 2) the representation of the climate system in atmosphere-ocean general circulation models (AOGCMs), and 3) the presence of unforced (internal) variability. Global and local sea level rise projections derived from these simulations, and the emergence of distinct responses to the four RCPs depend on the relative magnitude of these sources of uncertainty at different lead times. Here, the uncertainty in CMIP5 projections of sea level is partitioned at global and local scales, using a 164-member ensemble of twenty-first-century simulations. Local projections at New York City (NYSL) are highlighted. The partition between model uncertainty, scenario uncertainty, and internal variability in global mean sea level (GMSL) is qualitatively consistent with that of surface air temperature, with model uncertainty dominant for most of the twenty-first century. Locally, model uncertainty is dominant through 2100, with maxima in the North Atlantic and the Arctic Ocean. The model spread is driven largely by 4 of the 16 AOGCMs in the ensemble; these models exhibit outlying behavior in all RCPs and in both GMSL and NYSL. The magnitude of internal variability varies widely by location and across models, leading to differences of several decades in the local emergence of RCPs. The AOGCM spread, and its sensitivity to model exclusion and/or weighting, has important implications for sea level assessments, especially if a local risk management approach is utilized.

Variability↗
NASA NTRSDate not supplied

Investigating seasonal ENSO forecast amplitude calibration for GEOS-S2S-2

The GEOS-S2S-2 is a global coupled model and assimilation system, encompassing many aspects of the Earth climate system. This project looked at seasonal (nine-month) ensemble forecasts, over the period from 1982 through the present. We explored and validated a forecast amplitude correction technique used by the North American Multi-Model Ensemble (NMME), of which GEOS is a member, for Niño3.4 sea-surface temperature (SST) anomaly predictions. The method relies on deriving a set of correction factors based on the standard deviations of hindcast and observed SST anomalies. This algorithm was implemented at the Global Modeling and Assimilation Office (GMAO) and applied to the GEOS-S2S-2 Niño 3.4 hindcasts. In general, the correction reduced the forecast amplitude. This improved the quality of the forecasts when measured by the root mean square error (RMSE) of the ensemble mean forecast. RMSE decreased for most initialization months and forecast leads. The correction had a larger impact on seasons with strong El Niño-Southern Oscillation (ENSO) events than neutral seasons. The effects of the correction on the ensemble characteristics were also examined, and a variation of the algorithm was proposed that preserves the ensemble spread. The outcome of this project is a tool that can be used to calibrate GEOS-S2S-2 ENSO forecasts and potentially improve the precision of multi-model El Niño outlooks.

ENSO↗
NASA NTRS2018

Consequences of Different Air-Sea Feedbacks on Ocean Using MITgcm and MERRA-2 Forcing: Implications for Coupled Data Assimilation Systems

Ocean surface flux estimates from atmospheric and oceanic reanalyses contain errors that compensate for inaccuracies in the respective atmosphere and ocean models used to generate these reanalyses. A conundrum for climate studies is the discrepancy between surface fluxes that minimize model-data differences for an atmosphere-only model vs surface fluxes that minimize model-data differences for an ocean model. As a first step towards a consistent coupled ocean-atmosphere data-assimilation (DA) system, we compare surface net heat flux from a state-of-the-art atmospheric reanalysis, the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), to net heat flux from a state-of-the-art ocean state estimate, the Estimating the Circulation and Climate of the Ocean Version 4 (ECCO-v4). The possible impacts of the MERRA-2 and ECCO-v4 air-sea net heat flux difference in a coupled DA system were assessed using a set of experiments designed to imitate different “flavors” of a coupled DA system in an ocean-only setup. This was done by forcing the ECCO-v4 underlying ocean model - the Massachusetts Institute of Technology general circulation model (MITgcm) - with different sets of MERRA-2 fields and utilizing different forcing methods. By doing so we were able to turn off different air-sea feedbacks which, in a coupled DA setup, are partially muted by the constraining observations. The set of experiments, therefore, represents a range of active feedbacks in different “flavors” of coupled data-assimilation systems. For the period 1992–2011, MERRA-2 net heat flux has a global mean difference of -4.9 Wm(exp -2) relative to ECCO-v4. When MERRA-2 surface fields are used to force MITgcm, imbalances in the energy and the hydrological cycles of MERRA-2, which are directly related to the fact that MERRA-2 was created without an interactive ocean, propagate to the ocean. The experiment in which MITgcm is forced with MERRA-2 fluxes (MERRA-2-flux experiment) results in a 2.5°C global mean Sea Surface Temperature (SST) cooling, a 1m reduction in global mean sea level, and other drastic changes in the large scale ocean circulation relative to those resulting when the MITgcm is forced with the optimized ECCO-v4 net heat flux (the ECCO-v4 experiment itself). When MITgcm is forced with MERRA-2 state variables (MERRA-2-state experiment), the SST is somewhat restored to the observed SST, but the errors are shifted to the water cycle, resulting in a global mean sea level increase of 2.7 m. To further explore the pros and cons of these two approaches, we introduce a new intermediate forcing method in which the ocean is forced with turbulent fluxes but has a long wave feedback. This method, unlike MERRA-2 state, preserves the MERRA-2 water and salinity cycles, and it reduces the SST error compared to the MERRA-2-flux experiment, but the SST is not as good as that in the MERRA-2-state experiment. Our results have implications for ocean-model forcing recipes and clearly reveal the undesirable consequences of limiting the feedbacks in either these types of experiments or in coupled DA.

Ehud Strobach↗
NASA NTRS2020

Fast Responses on Pre-Industrial Climate from Present-Day Aerosols in A CMIP6 Multi-Model Study

In this work, we use Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations from 10 Earth system models (ESMs) and general circulation models (GCMs) to study the fast climate responses on pre-industrial climate, due to present-day aerosols. All models carried out two sets of simulations: a control experiment with all forcings set to the year 1850 and a perturbation experiment with all forcings identical to the control, except for aerosols with precursor emissions set to the year 2014. In response to the pattern of all aerosols effective radiative forcing (ERF), the fast temperature responses are characterized by cooling over the continental areas, especially in the Northern Hemisphere, with the largest cooling over East Asia and India, sulfate being the dominant aerosol surface temperature driver for present-day emissions. In the Arctic there is a warming signal for winter in the ensemble mean of fast temperature responses, but the model-to-model variability is large, and it is presumably linked to aerosol-induced circulation changes. The largest fast precipitation responses are seen in the tropical belt regions, generally characterized by a reduction over continental regions and presumably a southward shift of the tropical rain belt. This is a characteristic and robust feature among most models in this study, associated with weakening of the monsoon systems around the globe (Asia, Africa and America) in response to hemispherically asymmetric cooling from a Northern Hemisphere aerosol perturbation, forcing possibly the Intertropical Convergence Zone (ITCZ) and tropical precipitation to shift away from the cooled hemisphere despite that aerosols' effects on temperature and precipitation are only partly realized in these simulations as the sea surface temperatures are kept fixed. An interesting feature in aerosol-induced circulation changes is a characteristic dipole pattern with intensification of the Icelandic Low and an anticyclonic anomaly over southeastern Europe, inducing warm air advection towards the northern polar latitudes in winter.

Pre-industrial climate↗
NASA NTRS2000

Participation in the GISS EOS Proposal

To model the mass balance of the Greenland and Antarctic ice-sheets, Research Assistant Veronique Bugnion developed a snowpack model which embodies a physically based approach to modeling the temperature and density distribution of a snow, firn, and ice mixture. The snowpack model performed satisfactorily in capturing the surface energy balance and melt amounts measured at stations in Greenland and Antarctica. Also a comparison between the predicted extent of the wet snow zone obtained with the model and the same quantity derived from satellite microwave measurements showed excellent agreement. In addition the model's simulated total runoff was close to the best estimates from observations for the Greenland and Antarctic ice caps. Ms. Bugnion and research scientist Andrei Sokolov coupled the snowpack model to the climate submodel of MIT's Integrated Global System Model (IGSM) and integrated forward over the 21st century for a range of climate change scenarios, using forcings from simulations with the IGSM. The changes in mass balance of the ice caps were then translated into changes in sea level. For the scenarios with small to moderate warming, the runoff from Greenland and Antarctica is minimal. For the scenarios with a larger warming, there is a net increase in sea-level of 2-3 cm from Greenland, and a decrease of between 2 and 5 cm from Antarctica. These results show that the net change in sea level which can be expected to follow climatic changes in the Arctic and Antarctic regions, a decrease of 2 to 4 cm or less by the end of the 21st century, is smaller than most previously published estimates.

Stone, Peter H.↗
NASA NTRS2003

The Earth System Model

The Earth System Model is the natural evolution of current climate models and will be the ultimate embodiment of our geophysical understanding of the planet. These models are constructed from components - atmosphere, ocean, ice, land, chemistry, solid earth, etc. models and merged together through a coupling program which is responsible for the exchange of data from the components. Climate models and future earth system models will have standardized modules, and these standards are now being developed by the ESMF project funded by NASA. The Earth System Model will have a variety of uses beyond climate prediction. The model can be used to build climate data records making it the core of an assimilation system, and it can be used in OSSE experiments to evaluate. The computing and storage requirements for the ESM appear to be daunting. However, the Japanese ES theoretical computing capability is already within 20% of the minimum requirements needed for some 2010 climate model applications. Thus it seems very possible that a focused effort to build an Earth System Model will achieve succcss.

Schoeberl, Mark↗
NASA NTRS2018

Pliocene and Eocene Provide Best Analogs for Near-Future Climates

As the world warms due to rising greenhouse gas concentrations, the Earth system moves toward climate states without societal precedent, challenging adaptation. Past Earth system states offer possible model systems for the warming world of the coming decades. These include the climate states of the Early Eocene (ca. 50 Ma), the Mid-Pliocene (3.3–3.0 Ma), the Last Interglacial (129–116 ka), the Mid-Holocene (6 ka), preindustrial (ca. 1850 CE), and the 20th century. Here, we quantitatively assess the similarity of future projected climate states to these six geohistorical benchmarks using simulations from the Hadley Centre Coupled Model Version 3 (HadCM3), the Goddard Institute for Space Studies Model E2-R (GISS), and the Community Climate System Model, Versions 3 and 4 (CCSM) Earth system models. Under the Representative Concentration Pathway 8.5 (RCP8.5) emission scenario, by 2030 CE, future climates most closely resemble Mid-Pliocene climates, and by 2150 CE, they most closely resemble Eocene climates. Under RCP4.5, climate stabilizes at Pliocene-like conditions by 2040 CE. Pliocene-like and Eocene-like climates emerge first in continental interiors and then expand outward. Geologically novel climates are uncommon in RCP4.5 (<1%) but reach 8.7% of the globe under RCP8.5, characterized by high temperatures and precipitation. Hence, RCP4.5 is roughly equivalent to stabilizing at Pliocene-like climates, while unmitigated emission trajectories, such as RCP8.5, are similar to reversing millions of years of long-term cooling on the scale of a few human generations. Both the emergence of geologically novel climates and the rapid reversion to Eocene-like climates may be outside the range of evolutionary adaptive capacity.

climate change↗
NASA NTRS2020

Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6

Human land use activities have resulted in large changes to the biogeochemical and biophysical properties of the Earth's surface, with consequences for climate and other ecosystem services. In the future, land use activities are likely to expand and/or intensify further to meet growing demands for food, fiber, and energy. As part of the World Climate Research Program Coupled Model Intercomparison Project (CMIP6), the international community has developed the next generation of advanced Earth system models (ESMs) to estimate the combined effects of human activities (e.g., land use and fossil fuel emissions) on the carbon–climate system. A new set of historical data based on the History of the Global Environment database (HYDE), and multiple alternative scenarios of the future (2015–2100) from Integrated Assessment Model (IAM) teams, is required as input for these models. With most ESM simulations for CMIP6 now completed, it is important to document the land use patterns used by those simulations. Here we present results from the Land-Use Harmonization 2 (LUH2) project, which smoothly connects updated historical reconstructions of land use with eight new future projections in the format required for ESMs. The harmonization strategy estimates the fractional land use patterns, underlying land use transitions, key agricultural management information, and resulting secondary lands annually, while minimizing the differences between the end of the historical reconstruction and IAM initial conditions and preserving changes depicted by the IAMs in the future. The new approach builds on a similar effort from CMIP5 and is now provided at higher resolution (0.25°×0.25°) over a longer time domain (850–2100, with extensions to 2300) with more detail (including multiple crop and pasture types and associated management practices) using more input datasets (including Landsat remote sensing data) and updated algorithms (wood harvest and shifting cultivation); it is assessed via a new diagnostic package. The new LUH2 products contain > 50 times the information content of the datasets used in CMIP5 and are designed to enable new and improved estimates of the combined effects of land use on the global carbon–climate system.

land use land cover change↗
NASA NTRS2012

Assessment of the APCC Coupled MME Suite in Predicting the Distinctive Climate Impacts of Two Flavors of ENSO during Boreal Winter

Forecast skill of the APEC Climate Center (APCC) Multi-Model Ensemble (MME) seasonal forecast system in predicting two main types of El Nino-Southern Oscillation (ENSO), namely canonical (or cold tongue) and Modoki ENSO, and their regional climate impacts is assessed for boreal winter. The APCC MME is constructed by simple composite of ensemble forecasts from five independent coupled ocean-atmosphere climate models. Based on a hindcast set targeting boreal winter prediction for the period 19822004, we show that the MME can predict and discern the important differences in the patterns of tropical Pacific sea surface temperature anomaly between the canonical and Modoki ENSO one and four month ahead. Importantly, the four month lead MME beats the persistent forecast. The MME reasonably predicts the distinct impacts of the canonical ENSO, including the strong winter monsoon rainfall over East Asia, the below normal rainfall and above normal temperature over Australia, the anomalously wet conditions across the south and cold conditions over the whole area of USA, and the anomalously dry conditions over South America. However, there are some limitations in capturing its regional impacts, especially, over Australasia and tropical South America at a lead time of one and four months. Nonetheless, forecast skills for rainfall and temperature over East Asia and North America during ENSO Modoki are comparable to or slightly higher than those during canonical ENSO events.

Jeong, Hye-In↗
NASA NTRS2014

Use of Machine Learning Techniques for Iidentification of Robust Teleconnections to East African Rainfall Variability in Observations and Models

Providing advance warning of East African rainfall variations is a particular focus of several groups including those participating in the Famine Early Warming Systems Network. Both seasonal and long-term model projections of climate variability are being used to examine the societal impacts of hydrometeorological variability on seasonal to interannual and longer time scales. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of both seasonal and climate model projections to develop downscaled scenarios for using in impact modeling. The utility of these projections is reliant on the ability of current models to capture the embedded relationships between East African rainfall and evolving forcing within the coupled ocean-atmosphere-land climate system. Previous studies have posited relationships between variations in El Niño, the Walker circulation, Pacific decadal variability (PDV), and anthropogenic forcing. This study applies machine learning methods (e.g. clustering, probabilistic graphical model, nonlinear PCA) to observational datasets in an attempt to expose the importance of local and remote forcing mechanisms of East African rainfall variability. The ability of the NASA Goddard Earth Observing System (GEOS5) coupled model to capture the associated relationships will be evaluated using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations.

Roberts, J. Brent↗
NASA NTRS2010

Decadal Prediction Efforts in GMAO (Global Modeling and Assimilation Office)

The Global Modeling and Assimilation Office (GMAO) plans to use our GEOS-5 atmosphere-ocean general circulation model (AOGCM) to explore issues associated with predictability on decadal time scales and to contribute to the decadal prediction project that is part ofCMIP5. The GEOS-5 AOGCM is comprised of the GEOS-5 AGCM with the Catchment Land Surface Model, coupled to GFDL's MOM, version 4. We have assimilation systems for both the atmosphere and ocean. For our climate prediction efforts, the atmosphere will be initialized from the GEOS-5 Modem Era Retrospective-analysis for Research and Applications (MERRA), available from 1979 to present at 112 resolution, and from 1948 to present at 2 resolution. The ocean assimilation is conducted within the coupled model framework, using the MERRA as a constraint for both the atmosphere and the ocean. The decadal prediction experiments will be conducted with a 1 atmosphere and a 112 ocean. Some initial results will be presented, focusing on initialization aspects of the GEOS-5 system.

Rienecker, Michele M.↗
NASA NTRS2008

NASA's Modern Era Retrospective-Analysis for Research and Applications (MERRA): Early Results and Future Directions

This talk will review the status and progress of the NASA/Global Modeling and Assimilation Office (GMAO) atmospheric global reanalysis project called the Modern Era Retrospective-Analysis for Research and Applications (MERRA). An overview of NASA's emerging capabilities for assimilating a variety of other Earth Science observations of the land, ocean, and atmospheric constituents will also be presented. MERRA supports NASA Earth science by synthesizing the current suite of research satellite observations in a climate data context (covering the period 1979-present), and by providing the science and applications communities with of a broad range of weather and climate data with an emphasis on improved estimates of the hydrological cycle. MERRA is based on a major new version of the Goddard Earth Observing System Data Assimilation System (GEOS-5), that includes the Earth System Modeling Framework (ESMF)-based GEOS-5 atmospheric general circulation model and the new NOAA National Centers for Environmental Prediction (NCEP) unified grid-point statistical interpolation (GST) analysis scheme developed as a collaborative effort between NCEP and the GMAO. In addition to MERRA, the GMAO is developing new capabilities in aerosol and constituent assimilation, ocean, ocean biology, and land surface assimilation. This includes the development of an assimilation capability for tropospheric air quality monitoring and prediction, the development of a carbon-cycle modeling and assimilation system, and an ocean data assimilation system for use in coupled short-term climate forecasting.

Schubert, Siegfried↗
NASA NTRS2014

Impacts of Irrigation on Daily Extremes in the Coupled Climate System

Widespread irrigation alters regional climate through changes to the energy and water budgets of the land surface. Within general circulation models, simulation studies have revealed significant changes in temperature, precipitation, and other climate variables. Here we investigate the feedbacks of irrigation with a focus on daily extremes at the global scale. We simulate global climate for the year 2000 with and without irrigation to understand irrigation-induced changes. Our simulations reveal shifts in key climate-extreme metrics. These findings indicate that land cover and land use change may be an important contributor to climate extremes both locally and in remote regions including the low-latitudes.

Climate↗
NASA NTRS2024

Accurate Assessment of Land-Atmosphere Coupling in Climate Models Requires High Frequency Data Output

Land-atmosphere (L-A) interactions are important for understanding convective processes, climate feedbacks, the development and perpetuation of droughts, heatwaves, pluvials, and other land-centred climate anomalies. Local L-A coupling (LoCo) metrics capture relevant L-A processes, highlighting the impact of soil and vegetation states on surface flux partitioning, and the impact of surface fluxes on boundary layer (BL) growth, development, and entrainment of air above the BL. A primary goal of the Climate Process Team on Coupling Land and Atmospheric Subgrid Parameterizations (CLASP) is parameterizing and characterizing the impact of subgrid heterogeneity in global and regional earth system models (ESMs) to improve the connection between land and atmospheric states and processes. A critical step in achieving that aim is the incorporation of L-A metrics, especially LoCo metrics, into climate model diagnostic process streams. However, because land-atmosphere interactions span time scales of minutes (e.g., turbulent fluxes), hours (e.g., BL growth and decay), days (e.g., soil moisture memory), and seasons (e.g., variability of behavioural regimes between soil moisture and latent heat flux), with multiple processes of interest happening in different geographic regions at different times of year, there is not a single metric that captures all the modes, means, and methods of interaction between the land and the atmosphere. And while monthly means of most of the LoCo-relevant variables are routinely saved from ESM simulations, data storage constraints typically preclude routine archival of the hourly data that would enable the calculation of all LoCo metrics. Here we outline a reasonable data request that would allow for adequate characterization of sub-daily coupling processes between the land and the atmosphere, preserving enough sub-daily output to describe, analyse, and better understand L-A coupling in modern climate models. A secondary request involves embedding calculations within the models to determine mean properties in and above the BL to further improve characterization of model behaviour. Higher-frequency model output will (i) allow for more direct comparison with observational field campaigns on process-relevant time scales, (ii) enable demonstration of inter-model spread in L-A coupling processes, and (iii) aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.

Kirsten L. Findell↗
NASA NTRS2018

Connecting Regional Aerosol Emissions Reductions to Local and Remote Precipitation Responses

The unintended climatic implications of aerosol and precursor emission reductions implemented to protect public health are poorly understood. We investigate the precipitation response to regional changes in aerosol emissions using three coupled chemistry-climate models: NOAA Geophysical Fluid Dynamics Laboratory Coupled Model 3 (GFDL-CM3), NCAR Community Earth System Model (CESM1), and NASA Goddard Institute for Space Studies ModelE2 (GISS-E2). Our approach contrasts a long present-day control simulation from each model (up to 400 years with perpetual year 2000 or 2005 emissions) with 14 individual aerosol emissions perturbation simulations (160-240 years each). We perturb emissions of sulfur dioxide and/or carbonaceous aerosol within six world regions and assess the significance of precipitation responses relative to internal variability determined by the control simulation and across the models. Global and regional precipitation mostly increases when we reduce regional aerosol emissions in the models, with the strongest responses occurring for sulfur dioxide emissions reductions from Europe and the United States. Precipitation responses to aerosol emissions reductions are largest in the tropics and project onto the El Nino Southern Oscillation (ENSO). Regressing precipitation onto an Indo-Pacific zonal sea level pressure gradient index (a proxy for ENSO) indicates that the ENSO component of the precipitation response to regional aerosol removal can be as large as 20% of the total simulated response. Precipitation increases in the Sahel in response to aerosol reductions in remote regions because an anomalous interhemispheric temperature gradient alters the position of the Intertropical Convergence Zone (ITCZ). This mechanism holds across multiple aerosol reduction simulations and models.

Westervelt, Daniel M.↗
NASA NTRS2005

It's a Sooty Problem: Black Carbon and Aerosols from Space

Our knowledge of atmospheric aerosols (smoke, pollution, dust or sea salt particles, small enough to be suspended in the air), their evolution, composition, variability in space and time and interaction with solar radiation, clouds and precipitation is lacking despite decades of research. Just recently we recognized that understanding the global aerosol system is fundamental for progress in climate change and hydrological cycle research. While a single instrument was used to demonstrate 50 yrs ago that the global CO2 levels are rising, posing thread to our climate, we need an may of satellites, surface networks of radiometers, elaborated laboratory and field experiments coupled with chemical transport models to understand the global aerosol system. This complexity of the aerosol problem results from their short lifetime (1 week), variability of the chemical composition and complex chemical and physical processes in the atmosphere. The result is a heterogeneous distribution of aerosol and their properties. The new generation of satellites and surface networks of radiometers provides exciting opportunities to measure the aerosol properties and their interaction with clouds and climate. However farther development in the satellite capability, aerosol chemical models and climate models is needed to fully decipher the aerosol secrets with accuracy required to predict future climates.

Kaufman, Yoram J.↗