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The hemispheric symmetry of albedo and its contributing factors in satellite observations and global climate models is evaluated. The analysis is performed on the annual mean time scale, on which a bimodality in the joint distribution of albedo and cloud fraction is evident, resulting from tropical and subtropical clouds and midlatitude clouds, respectively. Hemispheric albedo symmetry is not found in individual ocean-only latitude bands; comparing the Northern and Southern Hemisphere (NH and SH), regional mean albedo is higher in the NH tropics and lower in the NH subtropics and midlatitudes than in the SH counterparts. This follows the hemispheric asymmetry of cloud fraction. In midlatitudes and tropics the hemispheric asymmetry in cloud albedo also contributes to the asymmetry in total albedo, whereas in the subtropics the cloud albedo is more hemispherically symmetric. According to the observations, cloud contributions to compensation for higher clear-sky albedo in the NH come primarily from cloud albedo in midlatitudes and cloud amount in the subtropics. Current-generation climate models diverge in their representation of these relationships, but common features of the model-data comparison include weaker-than-observed asymmetry in cloud fraction and cloud albedo in the tropics, weaker or reversed cloud fraction asymmetry in the subtropics, and agreement with observed cloud albedo asymmetry in the midlatitudes. Models on average reproduce the NH-SH asymmetry in total albedo over the 60 degrees S-60 degrees N ocean but show higher occurrence of brighter clouds in the SH compared to observations. The albedo bias in both hemispheres is reinforced by overestimated clear-sky albedo in the models.

Earth's albedo is the primary determinant of the amount of energy absorbed by the Earth-atmosphere system. It is a function of the fractional cloud cover and the cloudy-and clear-sky albedos, and thereby of the aerosol loading of the atmosphere. Here, we introduce a method by which we can examine the spatial distribution of the albedo variability that is independent of variations in the two dominant factors of albedo: cloud fraction and liquid water path (LWP). The analysis is based on data simultaneously retrieved from the CERES and MODIS instruments carried on board the Aqua satellite. We analysed the daily overpass data between July 2002 and June 2014 and showed that perturbations in albedo, accounting for variations induced by cloud fraction and LWP, display a coherent geographical pattern. Positive deviations occur in proximity to known anthropogenic aerosol sources, and negative deviations coincide with areas of intense precipitation, acting as aerosol sinks. A simple multiplication of the observed positive perturbations in albedo with the solar flux of 340Wm(-2) yields a magnitude of that effect of several watts per square meter locally. While the location and scale of the geographical pattern might suggest an anthropogenic contribution to the positive albedo perturbations, it is imperative to first carefully examine all other possible causal factors behind the perturbations. Finally, although we have not attempted a full calculation of detection limits, the analysis is capable of sensing very small changes in average albedo of the order of 0.003 out of a total albedo of the order of 0.3. Hence, the applied method might find utilisation in a variety of situations where there is a need to quantify small perturbations of a dependent variable in noisy global data sets., AuthorCount:4

Earth's equilibrium climate sensitivity (ECS) and forcing of Earth's climate system over the industrial era have been re-examined in two new assessments: the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and a study by Otto et al. (2013). The ranges of these quantities given in these assessments and also in the Fourth (2007) IPCC Assessment are analyzed here within the framework of a planetary energy balance model, taking into account the observed increase in global mean surface temperature over the instrumental record together with best estimates of the rate of increase of planetary heat content. This analysis shows systematic differences among the several assessments and apparent inconsistencies within individual assessments. Importantly, the likely range of ECS to doubled CO2 given in AR5, 1.5-4.5 K/(3.7 W m(-2)) exceeds the range inferred from the assessed likely range of forcing, 1.2-2.9 K/(3.7 W m(-2)), where 3.7 W m(-2) denotes the forcing for doubled CO2. Such differences underscore the need to identify their causes and reduce the underlying uncertainties. Explanations might involve underestimated negative aerosol forcing, overestimated total forcing, overestimated climate sensitivity, poorly constrained ocean heating, limitations of the energy balance model, or a combination of effects.

Planetary albedo the reflectivity for solar radiation is of singular importance in determining the amount of solar energy taken in by the Earth-atmosphere system. Modeling albedo, and specifically cloud albedo, correctly is crucial for realistic climate simulations. A method is presented herein by which regional cloud albedo can be quantified from the relation between total albedo and cloud fraction, which in observations is found to be approximately linear on a monthly mean scale. This analysis is based primarily on the combination of cloud fraction data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and albedo data from the Clouds and the Earth's Radiant Energy System (CERES), but the results presented are also supported by the combination of cloud fraction and proxy albedo data from satelliteborne lidar [Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CA LIPSO)]. These data are measured and derived completely independently from the CERES-MODIS data. Applied to low-level marine stratiform clouds in three regions (off the coasts of South America, Africa, and North America), the analysis reveals regionally uniform monthly mean cloud albedos, indicating that the variation in cloud shortwave radiative properties is small on this scale. A coherent picture of low effective cloud albedo emerges, in the range from 0.35 to 0.42, on the basis of data from CERES and MODIS. In its simplicity, the method presented appears to be useful as a diagnostic tool and as a constraint on climate models. To demonstrate this, the same method is applied to cloud fraction and albedo output from several current-generation climate models [from the Coupled Model Intercomparison Project, phase 3 (CMIP3), archive]. Although the multimodel mean cloud albedo estimates agree to within 20% with the satellite-based estimates for the three focus regions, model-based estimates of cloud albedo are found to display much larger variability than do the observations, with, 4

The observed increase in global mean surface temperature (GMST) over the industrial era is less than 40% of that expected from observed increases in long-lived greenhouse gases together with the best-estimate equilibrium climate sensitivity given by the 2007 Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Possible reasons for this warming discrepancy are systematically examined here. The warming discrepancy is found to be due mainly to some combination of two factors: the IPCC best estimate of climate sensitivity being too high and/or the greenhouse gas forcing being partially offset by forcing by increased concentrations of atmospheric aerosols; the increase in global heat content due to thermal disequilibrium accounts for less than 25% of the discrepancy, and cooling by natural temperature variation can account for only about 15%. Current uncertainty in climate sensitivity is shown to preclude determining the amount of future fossil fuel CO2 emissions that would be compatible with any chosen maximum allowable increase in GMST; even the sign of such allowable future emissions is unconstrained. Resolving this situation, by empirical determination of the earth's climate sensitivity from the historical record over the industrial period or through use of climate models whose accuracy is evaluated by their performance over this period, is shown to require substantial reduction in the uncertainty of aerosol forcing over this period., authorCount :5

Experts consider the many roles that clouds play in the changing climate—one of the least understood and most puzzling aspects of atmospheric science.

Experts consider the many roles that clouds play in the changing climate—one of the least understood and most puzzling aspects of atmospheric science.

Experts consider the many roles that clouds play in the changing climate—one of the least understood and most puzzling aspects of atmospheric science.

We briefly but systematically review major sources of aerosol data, emphasizing suites of measurements that seem most likely to contribute to assessments of global aerosol climate forcing. The strengths and limitations of existing satellite, surface, and aircraft remote sensing systems are described, along with those of direct sampling networks and ship-based stations. It is evident that an enormous number of aerosol-related observations have been made, on a wide range of spatial and temporal sampling scales, and that many of the key gaps in this collection of data could be filled by technologies that either exist or are expected to be available in the near future. Emphasis must be given to combining remote sensing and in situ active and passive observations and integrating them with aerosol chemical transport models, in order to create a more complete environmental picture, having sufficient detail to address current climate forcing questions. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) initiative would provide an organizational framework to meet this goal.

Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the long-term benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, inter-agency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; mu

Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the long-term benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, inter-agency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; mu

We briefly but systematically review major sources of aerosol data, emphasizing suites of measurements that seem most likely to contribute to assessments of global aerosol climate forcing. The strengths and limitations of existing satellite, surface, and aircraft remote sensing systems are described, along with those of direct sampling networks and ship-based stations. It is evident that an enormous number of aerosol-related observations have been made, on a wide range of spatial and temporal sampling scales, and that many of the key gaps in this collection of data could be filled by technologies that either exist or are expected to be available in the near future. Emphasis must be given to combining remote sensing and in situ active and passive observations and integrating them with aerosol chemical transport models, in order to create a more complete environmental picture, having sufficient detail to address current climate forcing questions. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) initiative would provide an organizational framework to meet this goal.

A new method of analysis for S(IV) is described incorporating a counter-flow virtual impactor for collection and evaporation of cloud droplets with an SO2 analyzer. This technique allows analysis of aqueous S(IV) concentration in real-time and overcomes some sampling or analysis problems of conventional sampling with bulk cloud water collectors and wet chemical analysis methods. The technique is demonstrated by the correlated responses of the S(IV) instrument and instruments measuring physical properties of clouds while passing in and out of clouds. Measured aqueous S(IV) concentrations ranged from the detection limit (0.1 nmol per m3 of air) to 1.8 nmol m-3 in clouds in Ohio. S(IV) molar concentrations (moles/l of cloud water) were not calculable from these measurements, but can be calculated when a measurement of the liquid water content of the collected cloud water is made simultaneously.

A new method of analysis for S(IV) is described incorporating a counter-flow virtual impactor for collection and evaporation of cloud droplets with an SO2 analyzer. This technique allows analysis of aqueous S(IV) concentration in real-time and overcomes some sampling or analysis problems of conventional sampling with bulk cloud water collectors and wet chemical analysis methods. The technique is demonstrated by the correlated responses of the S(IV) instrument and instruments measuring physical properties of clouds while passing in and out of clouds. Measured aqueous S(IV) concentrations ranged from the detection limit (0.1 nmol per m3 of air) to 1.8 nmol m-3 in clouds in Ohio. S(IV) molar concentrations (moles/l of cloud water) were not calculable from these measurements, but can be calculated when a measurement of the liquid water content of the collected cloud water is made simultaneously.

Monthly mean maximum and minimum temperatures for over 50% (10%) of the Northern (Southern) Hemisphere landmass, accounting for 37% of the global landmass, indicate that the rise of the minimum temperature has occurred at a rate three times that of the maximum temperature during the period 1951-90 (0.84°C versus 0.28°C). The decrease of the diumal temperature range is approximately equal to the increase of mean temperature. The asymmetry is detectable in all seasons and in most of the regions studied.

Two approaches to the problem of measuring humidity at high altitudes are described. The first consists of the adaptation of the principle of gas chromatography to the separation of minute amounts of water from air. The laboratory experiments and apparatus are described. A possible design for an automatic chromatographic hygrometer is presented. The second approach consists of the use of the chromatographic packing as the dielectric of a small capacitor. The results of experiments with this new technique are presented. This device is unique inasmuch as its response can be described by an acceptable theory. The results of a literature survey are summarized.