Earth’s albedo and its symmetry

Abstract The properties of Earth's albedo and its symmetries are analyzed using twenty years of space-based Energy Balanced And Filled product of Clouds and the Earth's Radiant Energy System measurements. Despite surface asymmetries, top of the atmosphere temporally & hemispherically averaged reflected solar irradiance R appears symmetric over Northern/Southern hemispheres. This is confirmed with the use of surrogate time-series, which provides margins of 0.1±0.28Wm?2 for possible hemispheric differences supported by Clouds and Earth's Radiant System data. R time-series are further analyzed by decomposition into a seasonal (yearly and half yearly) cycle and residuals. Variability in the reflected solar irradiance is almost entirely (99%) due to the seasonal variations, mostly due to seasonal variations in insolation. The residuals of hemispherically averaged R are not only small, but also indistinguishable from noise, and thus not correlated across hemispheres. This makes yearly and sub-yearly timescales unlikely as the basis for a symmetry-establishing mechanism. The residuals however contain a global trend that is large, as compared to expected albedo feedbacks. It is also hemispherically symmetric, and thus indicates the possibility of a symmetry enforcing mechanism at longer timescales. To pinpoint precisely which parts of the Earth system establish the hemispheric symmetry, we create an energetically consistent cloud-albedo field from the data. We show that the surface albedo asymmetry is compensated by asymmetries between clouds over extra-tropical oceans, with southern hemispheric storm-tracks being 11% cloudier than their northern hemisphere counterparts. This again indicates that, assuming the albedo symmetry is not a result of chance, its mechanism likely operates on large temporal and spatial scales

Earth Radiation Budget Science, 1978

An earth radiation budget satellite system planned in order to understand climate on various temporal and spatial scales is considered. Topics discussed include: climate modeling, climate diagnostics, radiation modeling, radiation variability and correlation studies, cloudiness and the radiation budget, and radiation budget and related measurements in 1985 and beyond

Minimal recipes for global cloudiness

Clouds are primary modulators of Earth’s energy balance. It is thus important to understand the links connecting variabilities in cloudiness to variabilities in other state variables of the climate system, and also describe how these links would change in a changing climate. A conceptual model of global cloudiness can help elucidate these points. In this work we derive simple representations of cloudiness, that can be useful in creating a theory of global cloudiness. These representations illustrate how both spatial and temporal variability of cloudiness can be expressed in terms of basic state variables. Specifically, cloud albedo is captured by a nonlinear combination of pressure velocity and a measure of the low-level stability, and cloud longwave effect is captured by surface temperature, pressure velocity, and standard deviation of pressure velocity. We conclude with a short discussion on the usefulness of this work in the context of global warming response studies

Plain Facts About Anthropogenic Global Climate Change and Warming: A Review

Anthropogenic global climate change (AGC) is proceeding rapidly. The proximate cause is the greenhouse effect of carbon dioxide, methane and other greenhouse gases (GHG), which have rapidly accumulated in the atmosphere from burning fossil fuels and other human activities. Measurements of incoming and outgoing radiation have verified the warming imbalance. Effects manifest themselves in accelerating sea level rise and diminishment of the cryosphere. This has already created climatic refugees and water stress, and will destroy coastal infrastructure. It also impacts ecosystems and biodiversity in many ways. To avoid catastrophic effects, fossil fuel use must cease and carbon sinks must be protected and expanded. While voluminous scientific evidence supports the need for action, the U.S.A. has not acted. A survey of manifestos of geographically diverse conservative national parties in nine industrialized democracies (US, Canada, UK, Spain, Norway, Sweden, Germany, Australia, New Zealand; Båstrand 2015) shows that eight see this as an urgent problem to be solved; the exception being the U.S. Republican Party. I explore reasons for this anomaly

Discovering the Importance of Mesoscale Cloud Organization Through Unsupervised Classification

The representation of shallow trade wind convective clouds in climate models dominates the uncertainty in climate sensitivity estimates. In particular the radiative impact of cloud spatial organization is poorly understood. This work presents the first unsupervised neural network model which autonomously discovers cloud organization regimes in satellite images. Trained on 10,000 GOES‐16 satellite images (tropical Atlantic and boreal winter) the regimes found are shown to exist in a hierarchy of organizational scales, with sub‐clusters having distinct radiative properties. The model requires no time‐consuming and subjective hand‐labeled data based on predefined structures allowing for objective study of very large data sets. The model enables the study of environmental conditions in different organizational regimes and in transitions between regimes and objective comparisons of model behavior with observations through cloud structures emerging in both. These abilities enable the discovery of previously unknown physical relationships in cloud processes, enabling better representation of clouds in weather and climate simulations

Combining satellite observations and reanalysis energy transports to estimate global net surface energy fluxes 1985-2012

Two methods are developed to estimate net surface energy fluxes based upon satellite-based reconstructions of radiative fluxes at the top of atmosphere and the atmospheric energy tendencies and transports from the ERA-Interim reanalysis. Method 1 applies the mass adjusted energy divergence from ERA-Interim while method 2 estimates energy divergence based upon the net energy difference at the top of atmosphere and the surface from ERA-Interim. To optimise the surface flux and its variability over ocean, the divergences over land are constrained to match the monthly area mean surface net energy flux variability derived from a simple relationship between the surface net energy flux and the surface temperature change. The energy divergences over the oceans are then adjusted to remove an unphysical residual global mean atmospheric energy divergence. The estimated net surface energy fluxes are compared with other data sets from reanalysis and atmospheric model simulations. The spatial correlation coefficients of multi-annual means between the estimations made here and other data sets are all around 0.9. There are good agreements in area mean anomaly variability over the global ocean, but discrepancies in the trend over the eastern Pacific are apparent

Global Warming

This book is intended to introduce the reader to examples of the range of practical problems posed by "Global Warming". It includes 11 chapters split into 5 sections. Section 1 outlines the recent changes in the Indian Monsoon, the importance of greenhouse gases to life, and the relative importance of changes in solar radiation in causing the changes. Section 2 discusses the changes to natural hazards such as floods, retreating glaciers and potential sea level changes. Section 3 examines planning cities and transportation systems in the light of the changes, while section 4 looks at alternative energy sources. Section 5 estimates the changes to the carbon pool in the alpine meadows of the Qinghai-Tibet Plateau. The 11 authors come from 9 different countries, so the examples are taken from a truly international set of problems

Trends in cyclones in the high-latitude North Atlantic during 1979-2016

We report an increase in winter (DJF) cyclone densities in the areas around Svalbard and in northwestern Barents Sea and a decrease in cyclone densities in southeastern Barents Sea during 1979-2016. Despite high interannual variability, the trends are significant at the 90% confidence level. The changes appear as a result of a shift into a more meridional winter storm track in the high-latitude North Atlantic, associated with a positive trend in the Scandinavian Pattern. A significant decrease in the Brunt-Vaisala frequency east of Svalbard and a significant increase in the Eady Growth Rate north of Svalbard indicate increased baroclinicity, favouring enhanced cyclone activity in these regions. For the first time, we apply composite analysis to explicitly address regional consequences of these wintertime changes in the high-latitude North Atlantic. We find a tendency toward a warmer and more moist atmospheric state in the Barents Sea and over Svalbard with increased cyclone activity around Svalbard.Peer reviewe

Tracing The Origins And Propagation Of African Easterly Waves And Mesoscale Convective Systems Using Pattern Recognition And Data Fusion

This thesis is focus on developing pattern recognition techniques to trace the origins and propagation of the Pre-Tropical Storm Debby (2006) African easterly waves (AEWs) and mesoscale convective systems (MCSs) using satellite imagery. The results are used to verify a numerical weather prediction (NWP) model. The pre-Debby MCSs’ movement and formation needs to be precisely and objectively tracked. These MCSs could be generated over mountains in North Africa, such as Ethiopian Highlands (EH), Darfur Mountains (DF), and Asir Mountains (AS), going through complicated splitting and merging processes. Thus, an objectively analyzed MCS movement is essential not only to help provide data to verify numerical modeling results, but also to help understand the formation and propagation of the African easterly waves and MCSs. The technique used could be applied to other AEWs and MCSs leading to tropical cyclogenesis. This, in turn, will improve the NWP over the data sparse areas, such as over eastern and central North Africa. The accuracy of numerical simulations of pre-tropical cyclone (TC) AEWs and MCSs is improved by fusing data with different data fusion techniques. In order to provide enhanced information to help predict the weather, this thesis investigates various techniques of data fusion. In many cases, fusing data provides more accurate and complete initial data for the NWP models which will then reduce the errors in weather prediction