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At least 343 records · Page 19

Observed effects of landscape variability on convective clouds

A case is presented in which clouds are observed to form first over a mesoscale-size area (100 x 300 km) of harvested wheat in Oklahoma, where the ground temperature is warmer than adjoining areas dominated by growing vegetation. In addition, clouds are suppressed over relatively long bands downwind of small man-made lakes and areas characterized by heavy tree cover. The observed variability of cloud relative to landscape type is compared with that simulated with a one-dimensional boundary-layer model. Clouds form earliest over regions characterized by high, sensible heat flux, and are suppressed over regions characterized by high, latent heat flux during relatively dry atmospheric conditions. This observation has significance in gaining understanding of the feedback mechanisms of land modification on climate, as well as understanding relatively short-range weather forecasting.

Rabin, Robert M.↗

Newly found evidence of Sun-climate relationships

Solar radiation cycles drive climatic changes intercyclically. These interdecadal changes were detected as variations in solar total irradiances over the time period of recorded global surface-air-temperature (SAT) and have been restored utilizing Earth Radiation Budget Channel 10C measurements (1978-1990), Greenwich Observatory faculae data (1874-1975), and Taipei Observatory Active Region data (1964-1991). Analysis of the two separate events was carried out by treating each as a discrete time series determined by the length of each solar cycle. The results show that the global SAT responded closely to the input of solar cyclical activities, S, with a quantitative relation of T = 1.62 * S with a correlation coefficient of 0.61. This correlation peaks at 0.71 with a built-in time lag of 32 months in temperature response. Solar forcing in interannual time scale was also detected and the derived relationship of T = 0.17 * S with a correlation coefficient of 0.66 was observed. Our analysis shows derived climate sensitivities approximately fit the theoretical feedback slope, 4T(sup 3).

Kim, Hongsuk H.↗

A Review of Global Satellite-Derived Snow Products

Snow cover over the Northern Hemisphere plays a crucial role in the Earth's hydrology and surface energy balance, and modulates feedbacks that control variations of global climate. While many of these variations are associated with exchanges of energy and mass between the land surface and the atmosphere, other expected changes are likely to propagate downstream and affect oceanic processes in coastal zones. For example, a large component of the freshwater flux into the Arctic Ocean comes from snow melt. The timing and magnitude of this flux affects biological and thermodynamic processes in the Arctic Ocean, and potentially across the globe through their impact on North Atlantic Deep Water formation. Several recent global remotely sensed products provide information at unprecedented temporal, spatial, and spectral resolutions. In this article we review the theoretical underpinnings and characteristics of three key products. We also demonstrate the seasonal and spatial patterns of agreement and disagreement amongst them, and discuss current and future directions in their application and development. Though there is general agreement amongst these products, there can be disagreement over certain geographic regions and under conditions of ephemeral, patchy and melting snow.

Frei, Allan↗

A Review of Global Satellite-Derived Snow Products

Snow cover over the Northern Hemisphere plays a crucial role in the Earth s hydrology and surface energy balance, and modulates feedbacks that control variations of global climate. While many of these variations are associated with exchanges of energy and mass between the land surface and the atmosphere, other expected changes are likely to propagate downstream and affect oceanic processes in coastal zones. For example, a large component of the freshwater flux into the Arctic Ocean comes from snow melt. The timing and magnitude of this flux affects biological and thermodynamic processes in the Arctic Ocean, and potentially across the globe through their impact on North Atlantic Deep Water formation. Several recent global remotely sensed products provide information at unprecedented temporal, spatial, and spectral resolutions. In this article we review the theoretical underpinnings and characteristics of three key products. We also demonstrate the seasonal and spatial patterns of agreement and disagreement amongst them, and discuss current and future directions in their application and development. Though there is general agreement amongst these products, there can be disagreement over certain geographic regions and under conditions of ephemeral, patchy and melting snow

Frei, Allan↗

Impact of Aerosols on Convective Clouds and Precipitation

Aerosols are a critical.factor in the atmospheric hydrological cycle and radiation budget. As a major agent for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosols have a major impact on the dynamics, microphysics, and electrification properties of continental mixed-phase convective clouds. In addition, high aerosol concentrations in urban environments could affect precipitation variability by providing a significant source of cloud condensation nuclei (CCN). Such pollution . effects on precipitation potentially have enormous climatic consequences both in terms of feedbacks involving the land surface via rainfall as well as the surface energy budget and changes in latent heat input to the atmosphere. Basically, aerosol concentrations can influence cloud droplet size distributions, the warm-rain process, the cold-rain process, cloud-top heights, the depth of the mixed-phase region, and the occurrence of lightning. Recently, many cloud resolution models (CRMs) have been used to examine the role of aerosols on mixed-phase convective clouds. These modeling studies have many differences in terms of model configuration (two- or three-dimensional), domain size, grid spacing (150-3000 m), microphysics (two-moment bulk, simple or sophisticated spectral-bin), turbulence (1st or 1.5 order turbulent kinetic energy (TKE)), radiation, lateral boundary conditions (i.e., closed, radiative open or cyclic), cases (isolated convection, tropical or midlatitude squall lines) and model integration time (e.g., 2.5 to 48 hours). Among these modeling studies, the most striking difference is that cumulative precipitation can either increase or decrease in response to higher concentrations of CCN. In this presentation, we review past efforts and summarize our current understanding of the effect of aerosols on convective precipitation processes. Specifically, this paper addresses the following topics: observational evidence of the effect of aerosols on precipitation processes, and results from (CRM) simulations. Note that this presentation is mainly based on a recent paper published in Geophy. Rev. (Tao et al. 2012).

Tao, Wei-Kuo↗

A Review of Global Satellite-derived Snow Products

Snow cover over the Northern Hemisphere plays a crucial role in the Earth's hydrology and surface energy balance, and modulates feedbacks that control variations of global climate. While many of these variations are associated with exchanges of energy and mass between the land surface and the atmosphere, other expected changes are likely to propagate downstream and affect oceanic processes in coastal zones. For example, a large component of the freshwater flux into the Arctic Ocean comes from snow melt. The timing and magnitude of this flux affects biological and thermodynamic processes in the Arctic Ocean, and potentially across the globe through their impact on North Atlantic Deep Water formation. Several recent global remotely sensed products provide information at unprecedented temporal, spatial, and spectral resolutions. In this article we review the theoretical underpinnings and characteristics of three key products. We also demonstrate the seasonal and spatial patterns of agreement and disagreement amongst them, and discuss current and future directions in their application and development. Though there is general agreement amongst these products, there can be disagreement over certain geographic regions and under conditions of ephemeral, patchy and melting snow.

Frei, Allan↗

Landsat at 45: How it Changed the Way We See the Earth

On October 24, 1946, more than 10 years before the launch of the first artificial satellite Sputnik, scientists at the White Sands Missile Range in New Mexico placed a camera on top of a captured German V-2 ballistic missile. As the rocket flew to an altitude of about 65 miles - just above the generally recognized border of outer space - the 35-millimeter motion picture camera snapped a frame every one and a half seconds. Minutes later, the missile came crashing back down and slammed into the ground at more than 340 mph, but the film survived and gave us our first glimpse of Earth from space. Earth Resources Technology Satellite aka Landsat It was images like those first grainy black and white pictures and later those taken by America's first astronauts in the 1960's that inspired the development of the Earth Resources Technology Satellite (ERTS). From the unique vantage point of space, we could now observe Earth using a variety of different instruments to monitor changes over time. The ERTS-1 satellite, wisely renamed Landsat-1, was launched aboard a Delta rocket on July 23, 1972, into a Sun-synchronous polar orbit at an altitude of about 560 miles. In this unique orbit, Landsat could observe the same point on the Earth every 18 days, always with the same solar illumination, allowing for precise monitoring of changes on the ground over time. Landsat-1, derived from the highly successful Nimbus weather satellites, carried two instruments that allowed it to take images not only in visible light but also in infrared, well-suited to track changes in vegetation over time. Designed to last only one year, Landsat-1 actually operated for nearly three years, by which time it had been joined in space by Landsat-2, a near identical copy of the original. Since then, ever more sophisticated instruments were flown aboard Landsat-3 through -8, with Landsat-9 planned for launch in 2020, acquiring millions of images of Earth over more than four decades. At first, images from Landsat were processed by NASA and hardcopies sold to users for a fee, a somewhat tedious process. Since 2008, images have been made available to all interested users by the US Geological Survey (USGS) at no cost via the Internet in near real time. So, how can Landsat help? In short, Landsat looks. And looks. And proves Yogi right. Space-based images from Landsat and other similar satellites offer a unique and critical capability to observe land use over time by providing repetitive observations of the Earth otherwise unavailable. The data provided by the images can be used by scientists and politicians to inform wise decisions in areas such as agriculture, climate, ecosystems and biodiversity, energy, forest management, human health, fire, natural disasters, urban growth and water management. This overview article doesn't allow for examples from each of these disciplines, but details can be found at the following website: https://landsat.gsfc.nasa.gov/how_landsat_helps/. One third of the US economy is influenced by climate, weather and natural hazards, providing strong economic incentives to sustain a healthy space-based Earth observation program. One example, however, may be illustrative of how Landsat and other space-based observations can be helpful in monitoring and documenting some effects of global climate change. It had been noted since the 1970's that permafrost in subarctic areas like Siberia was melting at an accelerating rate. It also became apparent that this led to the formation of hundreds of melt lakes and the liberation of large quantities of methane, a gas that in the short-term has more potent greenhouse effects than carbon dioxide. The methane turned the water in these lakes blue, making them easy to track over time by satellite. Additionally, the newly released methane has been carbon dated to tens of thousands of years ago, meaning that it had remained frozen since the last Ice Age and therefore hadn't been accounted for in models of the Earth's overall carbon balance. Release of sufficient methane by an increasingly warming climate could actually cause a positive feedback loop in global warming, melting more permafrost and releasing yet more methane. Further monitoring by Landsat and other platforms will reveal whether this process is reversible or whether we've passed the tipping point. In addition to the highly successful Landsat series of satellites, NASA and other agencies such as the National Oceanic and Atmospheric Administration (NOAA) operate a fleet of other Earth observing platforms, many with more specific research goals such as monitoring sea ice levels or atmospheric carbon content. Several instruments aboard the International Space Station also contribute to this overall effort to better understand short- and long-term changes to the Earth. Many of these missions are guided by the 2009 Decadal Survey published by the National Research Council of the National Academy of Sciences. Europe, Russia and China all see the value of space-based Earth observation by deploying their own fleet of satellites.

Uri, John↗

Coordinating AgMIP Data and Models Across Global and Regional Scales for 1.5°C and 2.0°C Assessments

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some bread basket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate. This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels’.

interdisciplinary↗

Cities Exacerbate Climate Warming

Urbanization is a complex land transformation, not explicitly resolved within large-scale climate models. Long-term timeseries of high-resolution satellite data are essential to characterize it within land surface models and assess its contribution to surface temperature changes. The potential for additional surface warming from urbanization-induced land use change is investigated and de-coupled from that due to change in climate over the continental US using a decadal timescale. We show that, aggregated over the US, the summer mean urban-induced surface temperature increased by 0.15°C, with a warming of 0.24°C in cities built in vegetated areas and a cooling of 0.25°C in cities built in non-vegetated arid areas. This temperature change is comparable in magnitude to the 0.13°C/decade global warming trend observed over the last 50 years caused by increased CO2. We also show that the effect of urban-induced change on surface temperature is felt above and beyond that of the CO2 effect. Our results suggest that climate mitigation policies must consider urbanization feedback to put a limit on the worldwide mean temperature increase.

Lahouari Bounoua↗

Quantifying the Negative Feedback of Vegetation to Greenhouse Warming: A Modeling Approach

Several climate models indicate that in a 2 x CO2 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 down-regulation 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 2 x CO2, 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 simulations with elevated CO2. 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.

Bounous, L.↗

Impact of Dust Radiative Forcing upon Climate

Dust aerosols perturb the atmospheric radiative flux at both solar and thermal wavelengths, altering the energy and water cycles. The climate adjusts by redistributing energy and moisture, so that local temperature perturbations, for example, depend upon the forcing over the entire extent of the perturbed circulation. Within regions frequently mixed by deep convection, including the deep tropics, dust particles perturb the surface air temperature primarily through radiative forcing at the top of the atmosphere (TOA). Many models predict that dust reduces global precipitation. This reduction is typically attributed to the decrease of surface evaporation in response to dimming of the surface. A counterexample is presented, where greater shortwave absorption by dust increases evaporation and precipitation despite greater dimming of the surface. This is attributed to the dependence of surface evaporation upon TOA forcing through its influence upon surface temperature and humidity. Perturbations by dust to the surface wind speed and vegetation (through precipitation anomalies) feed back upon the dust aerosol concentration. The current uncertainty of radiative forcing attributed to dust and the resulting range of climate perturbations calculated by models remain a useful test of our understanding of the mechanisms relating dust radiative forcing to the climate response.

Feedback upon dust mobilization↗

Role of Snowfall Versus Air Temperatures for Greenland Ice Sheet Melt-Albedo Feedbacks

The Greenland Ice Sheet is a leading contributor to global sea-level rise because climate warming has enhanced surface meltwater runoff. Melt rates are particularly sensitive to air temperatures due to feedbacks with albedo. The primary melt-albedo feedback, fluctuation of seasonal snowlines, however, is determined not only by melt but also by antecedent snowfall which could delay the onset of dark glacier ice exposure. Here we investigate the role of snowfall versus air temperatures on ice sheet melt-albedo feedbacks using satellite remote sensing and atmospheric reanalysis data. We find several lines of evidence that snowline fluctuations are driven primarily by air temperatures and that snowfall is a secondary control. First, standardized linear regressions indicate that the timing of glacier ice exposure is nearly twice as sensitive to air temperatures than antecedent snowfall. Second, in 74% of the ablation zone by area, winter snowfall rates are not significantly correlated with winter air temperatures. This relationship implies that ice sheet melt due to climate warming is unlikely to be compensated by higher snowfall rates in the ablation zone. Third, we find no significant change in snowfall rates in the ablation zone during our 1981–2021 study period. Our findings demonstrate that snowfall is unlikely to reduce future ice sheet melt and that ice sheet meltwater runoff should be accurately predicted by air temperatures. Although given the importance of melt-albedo feedbacks, ice sheet models that parameterize albedo or are coupled with regional climate models are likely to provide the most accurate projections of mass loss.

J. C. Ryan↗

Four-planet meteorology

All planets with atmospheres have common characteristics which are helpful in understanding weather and climate on earth. Of the terrestrial planets, Mars displays the most earth-like characteristics. The feedback mechanism of the Martian Great Dust Storms may control climate on a global scale and shows some parallels to the water cycle on the earth. Venus, on the other hand, has atmosphere motions and characteristics far different from those of earth but appears to be valuable for comparative meteorology and it seems to be a simple weather machine due to absence of axial tilt. A completely gaseous Jupiter also can help because its atmosphere, driven by internal heat, flows round-and-round, showing the same general patterns for years at a time. Results of studying extraterrestrial atmospheres are most important for understanding earth's multi-year weather cycles such as the droughts in the American West every 22 years or effects of the Little Ice Age (1450-1915) on agriculture in the North Hemisphere.

Source record↗

Historical and Future Changes in Air Pollutants from CMIP6 Models

Poor air quality is currently responsible for large impacts on human health across the world. In addition, the air pollutants ozone (O3) and particulate matter less than 2.5 µm in diameter (PM2.5) are also radiatively active in the atmosphere and can influence Earth's climate. It is important to understand the effect of air quality and climate mitigation measures over the historical period and in different future scenarios to ascertain any impacts from air pollutants on both climate and human health. The Coupled Model Intercomparison Project Phase 6 (CMIP6) presents an opportunity to analyse the change in air pollutants simulated by the current generation of climate and Earth system models that include a representation of chemistry and aerosols (particulate matter). The shared socio-economic pathways (SSPs) used within CMIP6 encompass a wide range of trajectories in precursor emissions and climate change, allowing for an improved analysis of future changes to air pollutants. Firstly, we conduct an evaluation of the available CMIP6 models against surface observations of O3 and PM2.5. CMIP6 models consistently overestimate observed surface O3 concentrations across most regions and in most seasons by up to 16 ppb, with a large diversity in simulated values over Northern Hemisphere continental regions. Conversely, observed surface PM2.5 concentrations are consistently underestimated in CMIP6 models by up to 10 µg m−3, particularly for the Northern Hemisphere winter months, with the largest model diversity near natural emission source regions. The biases in CMIP6 models when compared to observations of O3 and PM2.5 are similar to those found in previous studies. Over the historical period (1850–2014) large increases in both surface O3 and PM2.5 are simulated by the CMIP6 models across all regions, particularly over the mid to late 20th century, when anthropogenic emissions increase markedly. Large regional historical changes are simulated for both pollutants across East and South Asia with an annual mean increase of up to 40 ppb for O3 and 12 µg m−3 for PM2.5. In future scenarios containing strong air quality and climate mitigation measures (ssp126), annual mean concentrations of air pollutants are substantially reduced across all regions by up to 15 ppb for O3 and 12 µg m−3 for PM2.5. However, for scenarios that encompass weak action on mitigating climate and reducing air pollutant emissions (ssp370), annual mean increases in both surface O3 (up 10 ppb) and PM2.5 (up to 8 µg m−3) are simulated across most regions, although, for regions like North America and Europe small reductions in PM2.5 are simulated due to the regional reduction in precursor emissions in this scenario. A comparison of simulated regional changes in both surface O3 and PM2.5 from individual CMIP6 models highlights important regional differences due to the simulated interaction of aerosols, chemistry, climate and natural emission sources within models. The projection of regional air pollutant concentrations from the latest climate and Earth system models used within CMIP6 shows that the particular future trajectory of climate and air quality mitigation measures could have important consequences for regional air quality, human health and near-term climate. Differences between individual models emphasise the importance of understanding how future Earth system feedbacks influence natural emission sources, e.g. response of biogenic emissions under climate change.

Air pollutants↗

Intraseasonal Variations in Tropical Energy Balance: Relevance to Climate Sensitivity?

Intraseasonal variability of deep convection represents a fundamental mode of organization for tropical convection. While most studies of intraseasonal oscillations (ISOs) have focused on the spatial propagation and dynamics of convectively coupled circulations, here we examine the projection of ISOs on the tropically-averaged heat and moisture budget. One unresolved question concerns the degree to which observable variations in the "fast" processes (e.g. convection, radiative / turbulent fluxes) can inform our understanding of feedback mechanisms operable in the context of climate change. Our analysis use daily data from satellite observations, the Modern Era analysis for Research and Applications (MERRA), and other model integrations to address these questions: (i) How are tropospheric temperature variations related to that tropical deep convection and the associated ice cloud fractional amount (ICF), ice water path (IWP), and properties of warmer liquid clouds? (ii) What role does moisture transport play vis-a-vis ocean latent heat flux in enabling the evolution of deep convection to mediate PBL - free atmospheric temperature equilibration? (iii) What affect do convectively generated upper-tropospheric clouds have on the TOA radiation budget? Our methodology is similar to that of Spencer et al., (2007 GRL ) whereby a composite time series of various quantities over 60+ ISO events is built using tropical mean tropospheric temperature signal as a reference to which the variables are related at various lag times (from -30 to +30 days). The area of interest encompasses the global oceans between 20oN/S. The increase of convective precipitation cannot be sustained by evaporation within the domain, implying strong moisture transports into the tropical ocean area. The decrease in net TOA radiation that develops after the peak in deep convective rainfall, is part of the response that constitutes a "discharge" / "recharge" mechanism that facilitates tropical heat balance maintenance on these time scales. However, water vapor and hydrologic scaling relationships for this mode of variability cast doubt on the utility of ISO variations as proxies for climate sensitivity response to external radiatively forced (e.g. greenhouse gas-induced) climate change.

Robertson, Franklin R.↗

Modeling Climate Responses to Spectral Solar Forcing on Centennial and Decadal Time Scales

We report a series of experiments to explore clima~ responses to two types of solar spectral forcing on decadal and centennial time scales - one based on prior reconstructions, and another implied by recent observations from the SORCE (Solar Radiation and Climate Experiment) SIM (Spectral 1rradiance Monitor). We apply these forcings to the Goddard Institute for Space Studies (GISS) Global/Middle Atmosphere Model (GCMAM). that couples atmosphere with ocean, and has a model top near the mesopause, allowing us to examine the full response to the two solar forcing scenarios. We show different climate responses to the two solar forCing scenarios on decadal time scales and also trends on centennial time scales. Differences between solar maximum and solar minimum conditions are highlighted, including impacts of the time lagged reSponse of the lower atmosphere and ocean. This contrasts with studies that assume separate equilibrium conditions at solar maximum and minimum. We discuss model feedback mechanisms involved in the solar forced climate variations.

Wen, G.↗

Earth System Modeling and Field Experiments in the Arctic-Boreal Zone - Report from a NASA Workshop

Early climate modeling studies predicted that the Arctic Ocean and surrounding circumpolar land masses would heat up earlier and faster than other parts of the planet as a result of greenhouse gas-induced climate change, augmented by the sea-ice albedo feedback effect. These predictions have been largely borne out by observations over the last thirty years. However, despite constant improvement, global climate models have greater difficulty in reproducing the current climate in the Arctic than elsewhere and the scatter between projections from different climate models is much larger in the Arctic than for other regions. Biogeochemical cycle (BGC) models indicate that the warming in the Arctic-Boreal Zone (ABZ) could lead to widespread thawing of the permafrost, along with massive releases of CO2 and CH4, and large-scale changes in the vegetation cover in the ABZ. However, the uncertainties associated with these BGC model predictions are even larger than those associated with the physical climate system models used to describe climate change. These deficiencies in climate and BGC models reflect, at least in part, an incomplete understanding of the Arctic climate system and can be related to inadequate observational data or analyses of existing data. A workshop was held at NASA/GSFC, May 22-24 2012, to assess the predictive capability of the models, prioritize the critical science questions; and make recommendations regarding new field experiments needed to improve model subcomponents. This presentation will summarize the findings and recommendations of the workshop, including the need for aircraft and flux tower measurements and extension of existing in-situ measurements to improve process modeling of both the physical climate and biogeochemical cycle systems. Studies should be directly linked to remote sensing investigations with a view to scaling up the improved process models to the Earth System Model scale. Data assimilation and observing system simulation studies should be used to guide the deployment pattern and schedule for inversion studies as well. Synthesis and integration of previously funded Arctic-Boreal projects (e.g., ABLE, BOREAS, ICESCAPE, ICEBRIDGE, ARCTAS) should also be undertaken. Such an effort would include the integration of multiple remotely sensed products from the EOS satellites and other resources.

Sellers, Piers↗

Clouds and Convective Self-Aggregation in a Multi-Model Ensemble of Radiative-Convective Equilibrium Simulations

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective56equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climatecsensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique amongst intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than un-aggregated simulations. Plain Language Summary This study investigates tropical clouds and climate using results from more than 30 different numerical models set up in a simplified framework. The dataset of model simulations is unique in that it includes a wide range of model types configured in a consistent manner. We address some of the biggest open questions in climate science, including how cloud properties change with warming and the role that the tendency of clouds to form clusters plays in determining the average climate and how climate changes. While there are large differences in how the different models simulate average temperature, humidity, and cloudiness, in a majority of models, the amount of high clouds decreases as climate warms. Nearly all models simulate a tendency for clouds to cluster together. There is agreement that when the clouds are clustered, the atmosphere is drier with fewer clouds overall. We don’t find a conclusive result for how cloud clustering changes as the climate warms.

Allison A. Wing↗