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At least 73 records · Page 4

Radiative Forcing by Well-Mixed Greenhouse Gases: Estimates from Climate Models in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4)

The radiative effects from increased concentrations of well-mixed greenhouse gases (WMGHGs) represent the most significant and best understood anthropogenic forcing of the climate system. The most comprehensive tools for simulating past and future climates influenced by WMGHGs are fully coupled atmosphere-ocean general circulation models (AOGCMs). Because of the importance of WMGHGs as forcing agents it is essential that AOGCMs compute the radiative forcing by these gases as accurately as possible. We present the results of a radiative transfer model intercomparison between the forcings computed by the radiative parameterizations of AOGCMs and by benchmark line-by-line (LBL) codes. The comparison is focused on forcing by CO2, CH4, N2O, CFC-11, CFC-12, and the increased H2O expected in warmer climates. The models included in the intercomparison include several LBL codes and most of the global models submitted to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). In general, the LBL models are in excellent agreement with each other. However, in many cases, there are substantial discrepancies among the AOGCMs and between the AOGCMs and LBL codes. In some cases this is because the AOGCMs neglect particular absorbers, in particular the near-infrared effects of CH4 and N2O, while in others it is due to the methods for modeling the radiative processes. The biases in the AOGCM forcings are generally largest at the surface level. We quantify these differences and discuss the implications for interpreting variations in forcing and response across the multimodel ensemble of AOGCM simulations assembled for the IPCC AR4.

Collins, W. D.↗

Constraining Arctic Climate Projections of Wintertime Warming With Surface Turbulent Flux Observations and Representation of Surface-Atmosphere Coupling

The drivers of rapid Arctic climate change—record sea ice loss, warming SSTs, and a lengthening of the sea ice melt season—compel us to understand how this complex system operates and use this knowledge to enhance Arctic predictability. Changing energy flows sparked by sea ice decline, spotlight atmosphere-surface coupling processes as central to Arctic system function and its climate change response. Despite this, the representation of surface turbulent flux parameterizations in models has not kept pace with our understanding. The large uncertainty in Arctic climate change projections, the central role of atmosphere-surface coupling, and the large discrepancy in model representation of surface turbulent fluxes indicates that these processes may serve as useful observational constraints on projected Arctic climate change. This possibility requires an evaluation of surface turbulent fluxes and their sensitivity to controlling factors (surface-air temperature and moisture differences, sea ice, and winds) within contemporary climate models (here Coupled Model Intercomparison Project 6). The influence of individual controlling factors and their interactions is diagnosed using a multi-linear regression approach. This evaluation is done for four sea ice loss regimes, determined from observational sea ice loss trends, to control for the confounding effects of natural variability between models and observations. The comparisons between satellite- and model-derived surface turbulent fluxes illustrate that while models capture the general sensitivity of surface turbulent fluxes to declining sea ice and to surface-air gradients of temperature and moisture, substantial mean state biases exist. Specifically, the central Arctic is too weak of a heat sink to the winter atmosphere compared to observations, with implications to the simulated atmospheric circulation variability and thermodynamic profiles. Models were found to be about 50% more efficient at turning an air-sea temperature gradient anomaly into a sensible heat flux anomaly relative to observations. Further, the influence of sea ice concentration on the sensible heat flux is underestimated in models compared to observations. The opposite is found for the latent heat flux variability in models; where the latent heat flux is too sensitive to a sea ice concentration anomaly. Lastly, the results suggest that present-day trends in sea ice retreat regions may serve as suitable observational constraints of projected Arctic warming.

turbulent fluxes↗

Integrating the Interconnections Between Groundwater and Land Surface Processes Through the Coupled NASA Land Information System and ParFlow Environment

Understanding the interactions between the atmosphere, the land, and the subsurface is fundamental to hydrology and is critical for a better assessment of the impacts of climate change and human management on hydrological systems. However, many land surface models simplify the subsurface hydrology and thereby these interactions. In this study, we couple the land surface model Noah-MP included in the NASA Land Information System (LIS) with the integrated hydrologic model ParFlow (ParFlow-LIS) using the Earth System Modeling Framework (ESMF) and the National United Operational Prediction Capability (NUOPC). This coupling improves the simulation of water and energy cycle processes by adding the three-dimensional variably saturated and heterogeneous flow in the subsurface using sophisticated and nonlinear physics-based equations as well as the advances in satellite remote sensing-based data assimilation of the land surface, thereby benefiting the integrated hydrologic modeling and data assimilation community. We use the High Plains aquifer, located in the central United States, as a testbed to evaluate the coupled ParFlow-LIS system. The new ParFlow-LIS system accounts for the effects of topographically driven flows on the land surface, producing more fine-scale patterns of land surface states and fluxes than standalone LIS. In addition, ParFlow-LIS enables the consideration of the effect of subsurface water storage on evapotranspiration. This is particularly important in areas and times with dry soils, such as during drought conditions or in the presence of a cone of depression due to pumping.

land surface modeling↗

Mesoscale Convective Systems in SCSMEX: Simulated by a Regional Climate Model and a Cloud Resolving Model

A Regional Land-Atmosphere Climate Simulation (RELACS) System is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes, in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water and energy cycles in Indo-China/South China Sea (SCS)/China, North America and South America. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Goddard Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model, PLACE allows for the effect A vegetation, and thus important physical processes such as evapotranspiration and interception are included. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate the atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. RELACS has been used to simulate the onset of the South China Sea Monsoon in 1986, 1991 and 1998. Sensitivity tests on various land surface models, cumulus parameterization schemes (CPSs), sea surface temperature (SST) variations and midlatitude influences have been performed. These tests have indicated that the land surface model has a major impact on the circulation over the South China Sea. CPSs can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. RELACS has also been used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during 1998. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. Also, the Goddard Cumulus Ensemble (GCE) model which allows for realistic moist processes as well as explicit interactions between cloud and radiation, and cloud and surface processes will be used to simulate convective systems associated with the onset of the South China Sea Monsoon in 1998. The GCE model also includes the same PLACE and radiation scheme used in the RELACS. A detailed comparison between the results from the GCE model and RELACS will be performed.

Tao, W.-K.↗

Mesoscale Convective Systems in SCSMEX: Simulated by a Regional Climate Model and a Cloud Resolving Model

A Regional Land-Atmosphere Climate Simulation (RELACS) System is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes, in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water and energy cycles in Indo-China/ South China Sea (SCS)/China, N. America and S. America. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Goddard Parameterization for Land-Atmosphere-C loud Exchange (PLACE) land surface model. PLACE allows for the effects of vegetation, and thus important physical processes such as evapotranspiration and interception are included. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate the atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. RELACS has been used to simulate the onset of the South China Sea Monsoon in 1986, 1997 and 1998. Sensitivity tests on various land surface models, cumulus parameterization schemes (CPSs), sea surface temperature (SST) variations and midlatitude influences have been performed. These tests have indicated that the land surface model has a major impact on the circulation over the S. China Sea. CPSs can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. RELACS has also been used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during 1998. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. Also, the Goddard Cumulus Ensemble (GCE) model which allows for realistic moist processes as well as explicit interactions between cloud and radiation, and cloud and surface processes will be used to simulate convective systems associated with the onset of the South China Sea Monsoon in 1998. The GCE model also includes the same PLACE and radiation scheme used in the RELACS. A detailed comparison between the results from the GCE model and RELACS will be performed.

Tao, W.-K.↗

Containerized GEOS: Toward a Portable Climate Model

The NASA Goddard Earth Observing System (GEOS) is an Earth system model used for weather, climate, and other scientific applications. GEOS consists of linked components that can run in various configurations such as atmosphere-only and coupled atmosphere-ocean. Running this model on any new supercomputing system depends on operating systems, compilers, MPI stacks, and libraries being present and correctly configured. To remove that burden from users, our project explores building and running GEOS using Singularity containers – files containing all the needed software dependencies – on both NASA high-end computing systems and commercial cloud computing environments. Ultimately, the goal is for containerized GEOS to make it easier for users outside of NASA to deploy and run the model on any machine.

Matthew Thompson↗

Implications of Projected Climate Change for Groundwater Recharge in the Western United States

Existing studies on the impacts of climate change on groundwater recharge are either global or basin/ location-specific. The global studies lack the specificity to inform decision making, while the local studies do little to clarify potential changes over large regions (major river basins, states, or groups of states), a scale often important in the development of water policy. An analysis of the potential impact of climate change on groundwater recharge across the western United States (west of 100 degrees longitude) is presented synthesizing existing studies and applying current knowledge of recharge processes and amounts. Eight representative aquifers located across the region were evaluated. For each aquifer published recharge budget components were converted into four standard recharge mechanisms: diffuse, focused, irrigation, and mountain-systems recharge. Future changes in individual recharge mechanisms and total recharge were then estimated for each aquifer. Model-based studies of projected climate-change effects on recharge were available and utilized for half of the aquifers. For the remainder, forecasted changes in temperature and precipitation were logically propagated through each recharge mechanism producing qualitative estimates of direction of changes in recharge only (not magnitude). Several key patterns emerge from the analysis. First, the available estimates indicate average declines of 10-20% in total recharge across the southern aquifers, but with a wide range of uncertainty that includes no change. Second, the northern set of aquifers will likely incur little change to slight increases in total recharge. Third, mountain system recharge is expected to decline across much of the region due to decreased snowpack, with that impact lessening with higher elevation and latitude. Factors contributing the greatest uncertainty in the estimates include: (1) limited studies quantitatively coupling climate projections to recharge estimation methods using detailed, process-based numerical models; (2) a generally poor understanding of hydrologic flowpaths and processes in mountain systems; (3) difficulty predicting the response of focused recharge to potential changes in the frequency and intensity of extreme precipitation events; and (4) unconstrained feedbacks between climate, irrigation practices, and recharge in highly developed aquifer systems.

longitude↗

Non-Monotonic Response of the Climate System to Abrupt CO2 Forcing

We explore the climate system response to abrupt CO2 forcing, spanning the range 1 × to 8×CO2, with two state-of-the-art coupled atmosphere-ocean-sea-ice-land models: the NASA Goddard Institute for Space Studies Model E2.1-G (GISS-E2.1-G) and the Community Earth System Model (CESM-LE). We find that the effective climate sensitivity is a non-monotonic function of CO2 in both models, reaching a minimum at 3×CO2 for GISS-E2.1-G, and 4×CO2 for CESM-LE. A similar non-monotonic response is found in Northern Hemisphere surface temperature, sea-ice, precipitation, the latitude of zero precipitation minus-evaporation, and the strength of the Hadley cell. Interestingly, the Atlantic meridional overturning circulation collapses when non-monotonicity appears and does not recover for larger CO2 forcings. Analyzing the climate response over the same CO2 range with slab ocean versions of the same models, we demonstrate that the climate system's non-monotonic response is linked to ocean dynamics.

Non-monotonic response↗

NASA's Earth Observing System: The Transition from Climate Monitoring to Climate Change Prediction

Earth's 4.5 billion year history is a study in change. Natural geological forces have been rearranging the surface features and climatic conditions of our planet since its beginning. There is scientific evidence that some of these natural changes have not only led to mass extinctions of species (e.g., dinosaurs), but have also severely impacted human civilizations. For instance, there is evidence that a relatively sudden climate change caused a 300-year drought that contributed to the downfall of Akkadia, one of the most powerful empires in the Middle-East region around 2200 BC. More recently, the "little ice age" from 1200-1400 AD forced the Vikings to abandon Greenland when temperatures there dropped by about 1.5 C, rendering it too difficult to grow enough crops to sustain the population. Today, there is compelling scientific evidence that human activities have attained the magnitude of a geological force and are speeding up the rate of global change. For example, carbon dioxide levels have risen 30 percent since the industrial revolution and about 40 percent of the world's land surface has been transformed by humans. We don't understand the cause-and-effect relationships among Earth's land, ocean, and atmosphere well enough to predict what, if any, impacts these rapid changes will have on future climate conditions. We need to make many measurements all over the world, over a long period of time, in order to assemble the information needed to construct accurate computer models that will enable us to forecast climate change. In 1988, the Earth System Sciences Committee, sponsored by NASA, issued a report calling for an integrated, long-term strategy for measuring the vital signs of Earth's climate system. The report urged that the measurements must all be intimately coupled with focused process studies, they must facilitate development of Earth system models, and they must be stored in an information system that ensures open access to consistent, long-term data. This committee emphasized that the only feasible way to collect these consistent, long-term data is through the use of space-based Earth "remote sensors" (instruments that can measure from a distance things like temperature).

King, Michael D.↗

Simulation of 1986 South China Sea Monsoon with a Regional Climate Model

A Regional Land-Atmosphere Climate Simulation System (RELACS) project is being developed at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes and in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water/energy cycles in the IndoChina/South China Sea (SCS) region. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. The original MM5 model (without PLACE) includes the option for either a simple slab soil model or a five-layer soil model (MRF) in which the soil moisture availability evolves over time. However, the MM5 soil models do not include the effects of vegetation, and thus important physical processes such as evapotranspiration and interception are precluded. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. In addition, the Penn State/NCAR MM5 atmospheric modeling system has been: (1) coupled to the Goddard Ice Microphysical scheme; (2) coupled to a turbulent kinetic energy (TKE) scheme; (3) modified to ensure cloud budget balance; and (4) incorporated initialization with the Goddard EOS data sets at NASA/Goddard Laboratory for Atmospheres. The improved MM5 with two nested domains (60 and 20 km horizontal resolution) was used to simulate convective activity over IndoChina and the South China Sea, during the monsoon season, from May 6 to May 20, 1986. The model results captured several dominant observed features, such as twin cyclones, a depression system over the Bay of Bengal, strong south-westerly winds over IndoChina before and during the on-set of convection over the SCS, and a vortex over the SCS. Two additional MM5 runs with different land process models, Blackadar and MRF, were performed, and their results are compared to the run with PLACE. The preliminary results indicate that the MM5 results using PLACE and Blackadar are in very good agreement, but the results using MRF do not contain the south-westerly wind over IndoChina prior to the on-set of convection over the SCS.

Tao, W. -K.↗

Linkages between terrestrial ecosystems and the atmosphere

The primary research issue in understanding the role of terrestrial ecosystems in global change is analyzing the coupling between processes with vastly differing rates of change, from photosynthesis to community change. Representing this coupling in models is the central challenge to modeling the terrestrial biosphere as part of the earth system. Terrestrial ecosystems participate in climate and in the biogeochemical cycles on several temporal scales. Some of the carbon fixed by photosynthesis is incorporated into plant tissue and is delayed from returning to the atmosphere until it is oxidized by decomposition or fire. This slower (i.e., days to months) carbon loop through the terrestrial component of the carbon cycle, which is matched by cycles of nutrients required by plants and decomposers, affects the increasing trend in atmospheric CO2 concentration and imposes a seasonal cycle on that trend. Moreover, this cycle includes key controls over biogenic trace gas production. The structure of terrestrial ecosystems, which responds on even longer time scales (annual to century), is the integrated response to the biogeochemical and environmental constraints that develop over the intermediate time scale. The loop is closed back to the climate system since it is the structure of ecosystems, including species composition, that sets the terrestrial boundary condition in the climate system through modification of surface roughness, albedo, and, to a great extent, latent heat exchange. These separate temporal scales contain explicit feedback loops which may modify ecosystem dynamics and linkages between ecosystems and the atmosphere. The long-term change in climate, resulting from increased atmospheric concentrations of greenhouse gases (e.g., CO2, CH4, and nitrous oxide (N2O)) will further modify the global environment and potentially induce further ecosystem change. Modeling these interactions requires coupling successional models to biogeochemical models to physiological models that describe the exchange of water, energy, and biogenic trace gases between the vegetation and the atmosphere at fine time scales. There does not appear to be any obvious way to allow direct reciprocal coupling of atmospheric general circulation models (GCM's), which inherently run with fine time steps, to ecosystem or successional models, which have coarse temporal resolution, without the interposition of physiological canopy models. This is equally true for biogeochemical models of the exchange of carbon dioxide and trace gases. This coupling across time scales is nontrivial and sets the focus for the modeling strategy.

Bretherton, Francis↗

The NASA Seasonal-to-Interannual Prediction Project (NSIPP)

The goal of the project is to develop an assimilation and forecast system based on a coupled atmosphere-ocean-land-surface-sea-ice model capable of using a combination of satellite and in situ data sources to improve the prediction of ENSO and other major S-I signals and their global teleconnections. The objectives of this annual report are to: (1) demonstrate the utility of satellite data, especially surface height surface winds, air-sea fluxes and soil moisture, in a coupled model prediction system; and (2) aid in the design of the observing system for short-term climate prediction by conducting OSSE's and predictability studies.

Rienecker, Michele↗

Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections

Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modelling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850-1900, using an observationally-based historical warming estimate of 0.8°C between 1850-1900 and 1995-2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above pre-industrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.

Climate↗

Scientific Data From Precipitation Driver Response Model Intercomparison Project

This data descriptor reports the main scientific values from General Circulation Models (GCMs) in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). The purpose of the GCM simulations has been to enhance the scientific understanding of how changes in greenhouse gases, aerosols, and incoming solar radiation perturb the Earth’s radiation balance and its climate response in terms of changes in temperature and precipitation. Here we provide global and annual mean results for a large set of coupled atmospheric-ocean GCM simulations and a description of how to easily extract files from the dataset. The simulations consist of single idealized perturbations to the climate system and have been shown to achieve important insight in complex climate simulations. We therefore expect this data set to be valuable and highly used to understand simulations from complex GCMs and Earth System Models for various phases of the Coupled Model Intercomparison Project

Precipitation Driver Response Model Intercompariso↗

GEOS-5 System Developments for Decadal Climate Prediction at NASA/GMAO

The GEOS-5 AOGCM is being used to conduct the CMIP5 decadal prediction suite. The model is comprised of the GEOS-5 AGCM coupled to MOM4 and CICE, with aerosol distributions from GOCART. The decadal predictions are initialized from the GEOS Ocean-Ice reanalysis that is coupled to MERRA, GMAO's atmospheric reanalysis. Perturbations are generated using a bred vector approach. The integrations are still underway. The system and preliminary results will be presented.

Rienecker, Michele↗

Oceanic Observations

For many years, merchant ships and the naval fleets of various countries have been the major source of data over and in the open ocean. Oceanographic research experiments and process studies in the field have also contributed to the climatological data bases for the global ocean, but, for the most part, these have been limited in duration and extent. However, over the last 10 years under the auspices of the World Climate Research Program and the International Geosphere Biosphere Program the role of the oceans in global and climate change has taken on increased significance. This has created a need for a considerably improved understanding of the seasonal, interannual, decadal and longer time-scale variability of the physical and biogeochemical attributes of the global ocean. As a result, over the past 10 years several major international field programs have been implemented and have had a tremendous impact on the number of in situ observations obtained for the global ocean. The Tropical Ocean Global Atmosphere (TOGA) program, the World Ocean Circulation Experiment (WOCE), and the Joint Global Ocean Flux Study (JGOFS) were designed with observational, modelling, and process study components aimed at analyzing different aspects of the ocean's role in the coupled climate system. In parallel with the field programs, continuous space-based observations of sea surface temperature, sea surface topography, and sea surface winds spanning nearly a decade or longer have become a reality. During this same time period, numerical ocean models and computational power have advanced to the point where the oceanographic observations, both in situ and remotely sensed, can be assimilated into numerical ocean models in order to provide a four-dimensional (x-y-z-t) depiction of the evolving state of the global ocean.

Busalacchi, Antonio J.↗

The effects of cloud radiative forcing on an ocean-covered planet

Cumulus anvil clouds, whose importance has been emphasized by observationalists in recent years, exert a very powerful influence on deep tropical convection by tending to radiatively destabilize the troposphere. In addition, they radiatively warm the column in which they reside. Their strong influence on the simulated climate argues for a much more refined parameterization in the General Circulation Model (GCM). For Seaworld, the atmospheric cloud radiative forcing (ACRF) has a powerful influence on such basic climate parameters as the strength of the Hadley circulation, the existence of a single narrow InterTropical Convergence Zone (ITCZ), and the precipitable water content of the atmosphere. It seems likely, however, that in the real world the surface CRF feeds back negatively to suppress moist convection and the associated cloudiness, and so tends to counteract the effects of the ACRF. Many current climate models have fixed sea surface temperatures but variable land-surface temperatures. The tropical circulations of such models may experience a position feedback due to ACRF over the oceans, and a negative or weak feedback due to surface CRF over the land. The overall effects of the CRF on the climate system can only be firmly established through much further analysis, which can benefit greatly from the use of a coupled ocean-atmospheric model.

Randall, David A.↗

Overview of Aerosol Distribution

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 clouds and precipitation is still lacking despite decades of research. 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 years ago that the global CO2 levels are rising, posing threat of global warming, we need an array of satellites and field measurements coupled with chemical transport models to understand the global aerosol system. This complexity of the aerosol problem results from their short lifetime (1 week) and variable chemical composition. A new generation of satellites provides exciting opportunities to measure the global distribution of aerosols, distinguishing natural from anthropogenic aerosol and measuring their interaction with clouds and climate. I shall discuss these topics and application of the data to air quality monitoring.

Kaufman, Yoram↗