ALBERT

Beschreibung: When cumulonimbus clouds aggregate, developing into a single entity with precipitation covering a horizontal scale of hundreds of kilometers, they are called mesoscale convective systems (MCSs). They account for much of Earth’s precipitation, generate severe weather events and flooding, produce prodigious cirriform anvil clouds, and affect the evolution of the larger-scale circulation. Understanding the inner workings of MCSs has resulted from developments in observational technology and modeling. Time–space conversion of ordinary surface and upper-air observations provided early insight into MCSs, but deeper understanding has followed field campaigns using increasingly sophisticated radars, better aircraft instrumentation, and an ever-widening range of satellite instruments, especially satellite-borne radars. High-resolution modeling and theoretical insights have shown that aggregated cumulonimbus clouds induce a mesoscale circulation consisting of air overturning on a scale larger than the scale of individual convective up- and downdrafts. These layers can be kilometers deep and decoupled from the boundary layer in elevated MCSs. Cooling in the lower troposphere and heating aloft characterize the stratiform regions of MCSs. As a result, long-lived MCSs with large stratiform regions have a top-heavy heating profile that generates potential vorticity in midlevels, thus influencing the larger-scale circulation within which the MCSs occur. Global satellite data show MCSs varying in structure, depending on the prevailing large-scale circulation and topography. These patterns are likely to change with global warming. In addition, environmental pollution affects MCS structure and dynamics subtly. Feedbacks of MCSs therefore need to be included or parameterized in climate models.

Beschreibung: We describe the historical evolution of the conceptualization, formulation, quantification, application, and utilization of “radiative forcing” (RF) of Earth’s climate. Basic theories of shortwave and longwave radiation were developed through the nineteenth and twentieth centuries and established the analytical framework for defining and quantifying the perturbations to Earth’s radiative energy balance by natural and anthropogenic influences. The insight that Earth’s climate could be radiatively forced by changes in carbon dioxide, first introduced in the nineteenth century, gained empirical support with sustained observations of the atmospheric concentrations of the gas beginning in 1957. Advances in laboratory and field measurements, theory, instrumentation, computational technology, data, and analysis of well-mixed greenhouse gases and the global climate system through the twentieth century enabled the development and formalism of RF; this allowed RF to be related to changes in global-mean surface temperature with the aid of increasingly sophisticated models. This in turn led to RF becoming firmly established as a principal concept in climate science by 1990. The linkage with surface temperature has proven to be the most important application of the RF concept, enabling a simple metric to evaluate the relative climate impacts of different agents. The late 1970s and 1980s saw accelerated developments in quantification, including the first assessment of the effect of the forcing due to the doubling of carbon dioxide on climate (the “Charney” report). The concept was subsequently extended to a wide variety of agents beyond well-mixed greenhouse gases (WMGHGs; carbon dioxide, methane, nitrous oxide, and halocarbons) to short-lived species such as ozone. The WMO and IPCC international assessments began the important sequence of periodic evaluations and quantifications of the forcings by natural (solar irradiance changes and stratospheric aerosols resulting from volcanic eruptions) and a growing set of anthropogenic agents (WMGHGs, ozone, aerosols, land surface changes, contrails). From the 1990s to the present, knowledge and scientific confidence in the radiative agents acting on the climate system have proliferated. The conceptual basis of RF has also evolved as both our understanding of the way radiative forcing drives climate change and the diversity of the forcing mechanisms have grown. This has led to the current situation where “effective radiative forcing” (ERF) is regarded as the preferred practical definition of radiative forcing in order to better capture the link between forcing and global-mean surface temperature change. The use of ERF, however, comes with its own attendant issues, including challenges in its diagnosis from climate models, its applications to small forcings, and blurring of the distinction between rapid climate adjustments (fast responses) and climate feedbacks; this will necessitate further elaboration of its utility in the future. Global climate model simulations of radiative perturbations by various agents have established how the forcings affect other climate variables besides temperature (e.g., precipitation). The forcing–response linkage as simulated by models, including the diversity in the spatial distribution of forcings by the different agents, has provided a practical demonstration of the effectiveness of agents in perturbing the radiative energy balance and causing climate changes. The significant advances over the past half century have established, with very high confidence, that the global-mean ERF due to human activity since preindustrial times is positive (the 2013 IPCC assessment gives a best estimate of 2.3 W m−2, with a range from 1.1 to 3.3 W m−2; 90% confidence interval). Further, except in the immediate aftermath of climatically significant volcanic eruptions, the net anthropogenic forcing dominates over natural radiative forcing mechanisms. Nevertheless, the substantial remaining uncertainty in the net anthropogenic ERF leads to large uncertainties in estimates of climate sensitivity from observations and in predicting future climate impacts. The uncertainty in the ERF arises principally from the incorporation of the rapid climate adjustments in the formulation, the well-recognized difficulties in characterizing the preindustrial state of the atmosphere, and the incomplete knowledge of the interactions of aerosols with clouds. This uncertainty impairs the quantitative evaluation of climate adaptation and mitigation pathways in the future. A grand challenge in Earth system science lies in continuing to sustain the relatively simple essence of the radiative forcing concept in a form similar to that originally devised, and at the same time improving the quantification of the forcing. This, in turn, demands an accurate, yet increasingly complex and comprehensive, accounting of the relevant processes in the climate system.

Beschreibung: The microphysical processes inside convective clouds play an important role in climate. They directly control the amount of detrainment of cloud hydrometeor and water vapor from updrafts. The detrained water substance in turn affects the anvil cloud formation, upper-tropospheric water vapor distribution, and thus the atmospheric radiation budget. In global climate models, convective parameterization schemes have not explicitly represented microphysics processes in updrafts until recently. In this paper, the authors provide a review of existing schemes for convective microphysics parameterization. These schemes are broadly divided into three groups: tuning-parameter-based schemes (simplest), single-moment schemes, and two-moment schemes (most comprehensive). Common weaknesses of the tuning-parameter-based and single-moment schemes are outlined. Examples are presented from one of the two-moment schemes to demonstrate the performance of the scheme in simulating the hydrometeor distribution in convection and its representation of the effect of aerosols on convection.

Beschreibung: No Abstract available.

Beschreibung: Today’s global Earth system models began as simple regional models of tropospheric weather systems. Over the past century, the physical realism of the models has steadily increased, while the scope of the models has broadened to include the global troposphere and stratosphere, the ocean, the vegetated land surface, and terrestrial ice sheets. This chapter gives an approximately chronological account of the many and profound conceptual and technological advances that made today’s models possible. For brevity, we omit any discussion of the roles of chemistry and biogeochemistry, and terrestrial ice sheets.

Beschreibung: In situ observations of cloud properties made by airborne probes play a critical role in ice cloud research through their role in process studies, parameterization development, and evaluation of simulations and remote sensing retrievals. To determine how cloud properties vary with environmental conditions, in situ data collected during different field projects processed by different groups must be used. However, because of the diverse algorithms and codes that are used to process measurements, it can be challenging to compare the results. Therefore it is vital to understand both the limitations of specific probes and uncertainties introduced by processing algorithms. Since there is currently no universally accepted framework regarding how in situ measurements should be processed, there is a need for a general reference that describes the most commonly applied algorithms along with their strengths and weaknesses. Methods used to process data from bulk water probes, single-particle light-scattering spectrometers and cloud-imaging probes are reviewed herein, with emphasis on measurements of the ice phase. Particular attention is paid to how uncertainties, caveats, and assumptions in processing algorithms affect derived products since there is currently no consensus on the optimal way of analyzing data. Recommendations for improving the analysis and interpretation of in situ data include the following: establishment of a common reference library of individual processing algorithms, better documentation of assumptions used in these algorithms, development and maintenance of sustainable community software for processing in situ observations, and more studies that compare different algorithms with the same benchmark datasets.