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V. Ramaswamy, W. Collins, J. Haywood, J. Lean, N. Mahowald, G. Myhre, V. Naik, K. P. Shine, B. Soden, G. Stenchikov, and T. Storelvmo

RF (e.g., Tarasick et al. 2019 ; Carslaw et al. 2017 ). Besides atmospheric constituents, other radiative influences also began to be quantified under the broad concept of “radiative forcing.” These included land-use and land-cover changes due to vegetation changes, primarily in the Northern Hemisphere. The initial considerations were for the changes induced in the albedo of the surfaces due to human activity ( Sagan et al. 1979 ). Later, other physical factors in the context of forced changes

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Robert F. Adler, Christian Kummerow, David Bolvin, Scott Curtis, and Chris Kidd

Abstract

Three years of Tropical Rainfall Measuring Mission (TRMM) monthly estimates of tropical surface rainfall are analyzed to document and understand the differences among the TRMM-based estimates and how these differences relate to the pre-TRMM estimates and current operational analyses. Variation among the TRMM estimates is shown to be considerably smaller than among a pre-TRMM collection of passive microwave-based products. Use of both passive and active microwave techniques in TRMM should lead to increased confidence in converged estimates.

Current TRMM estimates are shown to have a range of about 20% for the tropical ocean as a whole, with variations in heavily raining ocean areas of the Intertropical Convergence Zone (ITCZ) and South Pacific Convergence Zone (SPCZ) having differences over 30%. In midlatitude ocean areas the differences are smaller. Over land there is a distinct difference between the Tropics and midlatitude with a reversal between some of the products as to which tends to be relatively high or low. Comparisons of TRMM estimates with ocean atoll and land rain gauge information point to products that might have significant regional biases. The bias of the radar-based product is significantly low compared with atoll rain gauge data, while the passive microwave product is significantly high compared to rain gauge data in the deep Tropics.

The evolution of rainfall patterns during the recent change from intense El Niño to a long period of La Niña and then a gradual return to near neutral conditions is described using TRMM. The time history of integrated rainfall over the tropical oceans (and land) during this period differs among the passive and active microwave TRMM estimates.

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Edward J. Zipser

Abstract

The “hot tower” hypothesis requires the existence of deep cumulonimbus clouds in the deep Tropics as essential agents, which accomplish the mass and energy transport essential for the maintenance of the general circulation. As the role of the deep convective clouds has been generally accepted, the popularity of referring to these deep “hot” towers as undilute towers also has gained acceptance. This paper examines the consequences of assuming that the deep convective clouds over tropical oceans consist of undilute ascent from the subcloud layer.

Using simple applications of parcel theory, it is concluded that observed properties of typical cumulonimbus updrafts in low- to midtroposphere over tropical oceans are inconsistent with the presence of undilute updrafts. Such undilute updrafts are far more consistent with observations in severe storms of midlatitudes. The observations over tropical oceans can be hypothetically explained by assuming large dilution of updrafts by entrainment below about 500 hPa, followed by freezing of condensate. This freezing and subsequent ascent along an ice adiabat reinvigorates the updrafts and permits them to reach the tropical tropopause with the necessary high values of moist static energy, as the hot tower hypothesis requires. The large difference observed between ocean and land clouds can be explained by assuming slightly smaller entrainment rates for clouds over land. These small entrainment differences have a very large effect on updrafts in the middle and upper troposphere and can presumably account for the large differences in convective vigor, ice scattering, and lightning flash rates that are observed. It follows that convective available potential energy (CAPE) is not a particularly good predictor of the behavior of deep convection.

Using the Tropical Rainfall Measuring Mission (TRMM) to map a proxy for the most intense storms on earth between 36°S and 36°N, they are found mostly outside the deep Tropics, with the notable exception of tropical Africa.

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Larry K. Berg and Peter J. Lamb

lead author of this chapter was a member). The ARM Program’s research efforts have since grown from these original projects to include diverse teams of scientists working at National Laboratories, academia, and private industry. Most of this chapter will focus on two research areas in which the ARM Program has made significant progress: Understanding the impact of small-scale variations in the surface fluxes, how these variations should be represented in large-scale atmospheric models, and land-use

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Frank D. Marks Jr.

Abstract

Radar played an important role in studies of tropical cyclones since it was developed in the 1940s. In the last 15 years, technological improvements such as the U.S. National Oceanic and Atmospheric Administration (NOAA) WP-3D tail airborne Doppler radar, the operational Weather Service Radar 1988-Doppler (WSR-88D) radar network, portable Doppler radars, and the first spaceborne radar system on the National Aeronautics and Space Administration Tropical Rainfall Measuring Mission (NASA TRMM) satellite have produced a new generation of tropical cyclone data whose analysis has given scientists an unprecedented opportunity to document the dynamics and rainfall of tropical cyclones, and has led to improved understanding of these devastating storms.

The NOAA WP-3D airborne Doppler datasets led to improved understanding of the symmetric vortex and the major asymmetries. The addition of a second airborne Doppler radar on the other WP-3D enabled true dual-Doppler analyses and the ability to study the temporal evolution of the Kinematic structure over 3–6 h. The advent of the WSR-88D Doppler radar network, and the construction of portable Doppler radars that can be moved to a location near tropical cyclone landfall, has also generated new and unique datasets enabling improved understanding of 1) severe weather events associated with landfalling tropical cyclones, 2) boundary layer wind structure as the storm moves from over the sea to over land, and 3) spatial and temporal changes in the storm rain distribution. The WP-3D airborne Doppler and WSR-88D data have also been instrumental in developing a suite of operational single Doppler radar algorithms to objectively analyze a tropical cyclone's wind field by determining the storm location and defining the primary, secondary, and major asymmetric circulations. These algorithms are used operationally on the WP-3D aircraft and on the ground at NOAA's Tropical Prediction Center/National Hurricane Center.

The WSR-88D rainfall data, together with new satellite microwave passive and active sensors on the NASA TRMM satellite, are proving useful in studies of the temporal and spatial variability of rain in tropical cyclones. The instantaneous satellite snapshots provide rain estimates to improve our understanding of tropical cyclone rain distributions globally, providing estimates from one instrument and common algorithms in each basin, while the WSR-88D provides high-temporal-resolution rain estimates (1 h), to improve our understanding of the temporal variability of the rain as the storm makes landfall.

While these new datasets have led to improved understanding, they have also led to a number of new challenges that the radar meteorology community must face by transferring the understanding gained into new applications and improved numerical weather prediction. These challenges will drive our science well into the next century.

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Christa D. Peters-Lidard, Faisal Hossain, L. Ruby Leung, Nate McDowell, Matthew Rodell, Francisco J. Tapiador, F. Joe Turk, and Andrew Wood

estimating actual ET fall into three categories: energy balance (e.g., Su et al. 2005 ; Anderson et al. 1997 , 2011 ), combination [e.g., Penman–Monteith or Shuttleworth–Wallace ( Shuttleworth and Wallace 1985 )] and complementary approaches (e.g., Bouchet 1963 ), or combinations thereof (e.g., Mallick et al. 2013 ), and the choice and performance depends primarily on the availability of required data ( Mueller et al. 2013 ). Most modern land surface models used in climate models (as will be

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David A. Randall, Cecilia M. Bitz, Gokhan Danabasoglu, A. Scott Denning, Peter R. Gent, Andrew Gettelman, Stephen M. Griffies, Peter Lynch, Hugh Morrison, Robert Pincus, and John Thuburn

1950. Then, starting with the 1950s, the sections are organized by decade, but with some exceptions to maintain narrative continuity. We tell the story of each decade using several subsections, some of which are focused on particular ESM components. We have attempted to interweave our accounts of the developments of numerical methods, radiative transfer, turbulence and cloud parameterizations, ocean and sea ice modeling, and land surface modeling, because of course that is the way it really

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Minghua Zhang, Richard C. J. Somerville, and Shaocheng Xie

( Wang and Zhang 2014 ), among others. The third is to use SCMs with ARM forcing data to improve understanding of processes, including growth of ice particles ( Comstock et al. 2008 ), cloud feedbacks ( Del Genio et al. 2005 ), the interaction of deep and shallow convections ( Wang and Zhang 2013 ), and land–atmosphere interactions ( Sud et al. 2001 ). It should be noted that model development and improvement using SCMs is often done in conjunction with CRM or LES simulations under the same large

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observations will be used to initialize and validate cloud-resolving models, and as a basis for comparing parameterizations. These improved parameterizations will be incorporated into a regional climate model of the Arctic and global climate models. Collaboration with other programs, such as the Surface Heat Budget of the Arctic Ocean (SHEBA), the First ISCCP (International Satellite Cloud Climatology Experiment) Regional Experiment (FIRE), and Land-Atmosphere-Ice-Interactions (LAII) allows ARM to address

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Sue Ellen Haupt, Branko Kosović, Scott W. McIntosh, Fei Chen, Kathleen Miller, Marshall Shepherd, Marcus Williams, and Sheldon Drobot

the world’s population. In turn, as humans change land use for agriculture, the environment is impacted, and we must understand these changes to avoid unintended consequences. This section also continues the theme of Part II of this series ( Haupt et al. 2019b ), which dealt with topics related to growing populations. Section 2 culminates with a discussion of the food–energy–water nexus and its susceptibility to a changing climate. Section 3 discusses our current understanding (and limits to

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