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Surface warming is projected to increase global mean rainfall primarily by increasing the radiative cooling of the atmosphere. However, the radiative mechanisms which cause cooling to increase are not well understood. Here, we show that changes in cooling are driven primarily by changes in atmospheric opacity, particularly within the water vapor window. This suggests that changes in mean rainfall are primarily controlled by the thermodynamic and spectroscopic properties of Earth’s main greenhouse gases: water vapor and carbon dioxide. Consistent with comprehensive general circulation models, our results explain why mean rainfall increases with surface warming at about 2% per kelvin, why this rate is largely unchanged over numerous doublings of atmospheric carbon dioxide, and why mean rainfall decreases in hothouse climates. 

Radiative forcing by carbon dioxide depends on the difference between surface and stratospheric temperature scaled by the logarithm of its concentration (Wilson and Gea-Banacloche 2012; Jeevanjee et al. 2021). This relationship arises due to the cooling-to-space theory or theτ= 1 law, where all emission of infrared radiation originates from the atmospheric pressure level where the gas reaches sufficient optical thickness (in the case of CO₂, in the stratosphere). Here we develop theoretical understanding of forcing by other well-mixed greenhouse gases including methane (CH₄), nitrous oxide (N₂O), and chlorofluorocarbons (CFCs). Radiative forcing by an optically thin absorber (e.g., CFC-12) is governed by emission throughout the troposphere and scaled by the total change in gas concentration, such that a linear increase in gas abundance yields a linear increase in forcing. We examine the factors that control the magnitude of radiative forcing, demonstrating analytically that CFC-12 is a stronger per-molecule absorber than CO₂due to its larger average cross-section, rather than its band width or spectral position. Application in idealized atmospheres with simplified lapse rates illustrates how radiative forcing by optically thin gases depends almost linearly on lapse rate. Finally, gases that are both optically thin and optically thick across their absorption spectrum, such as N₂O and CH₄, can be understood as a combination of the two regimes, yielding a super-logarithmic relationship to concentration. Our theory is in excellent agreement with full-physics line-by-line calculations in atmospheres with and without spectral overlap by water vapor 

Abstract The infrared window region (780–1,250 cm⁻¹, 12.8 to 8.0 μm) is of great importance to Earth's climate due to its high transparency and thermal energy. We present here a new investigation of the transparency of this spectral region based on observations by interferometers of downwelling surface radiance at two DOE Atmospheric Radiation Measurement program sites. We focus on the dominant source of absorption in this region, the water vapor continuum, and derive updated values of spectral absorption coefficients for both the self and foreign continua. Our results show that the self continuum is too strong in the previous version of Mlawer‐Tobin_Clough‐Kneizys‐Davies (MT_CKD) water vapor continuum model, a result that is consistent with other recent analyses, while the foreign continuum is too weak in MT_CKD. In general, the weaker self continuum derived in this study results in an overall increase in atmospheric transparency in the window, although in atmospheres with low amounts of water vapor the transparency may slightly decrease due to the increase in foreign continuum absorption. These continuum changes lead to a significant decrease in downwelling longwave flux at the surface for moist atmospheres and a modest increase in outgoing longwave radiation. The increased fraction of surface‐leaving radiation that escapes to space leads to a notable increase (∼5–10%) in climate feedback, implying that climate simulations that use the new infrared window continuum will show somewhat less warming than before. This study also points out the possibly important role that aerosol absorption may play in the longwave radiative budget. 

Abstract We investigate the effect of uncertainty in water vapor continuum absorption at terrestrial wavenumbers on CO₂forcing , longwave feedbackλ, and climate sensitivity at surface temperaturesT_sbetween 270 and 330 K. We calculate this uncertainty using a line‐by‐line radiative‐transfer model and a single‐column atmospheric model, assuming a moist‐adiabatic temperature lapse‐rate and 80% relative humidity in the troposphere, an isothermal stratosphere, and clear skies. Due to the lack of a comprehensive model of continuum uncertainty, we represent continuum uncertainty in two different idealized approaches: In the first, we assume that the total continuum absorption is constrained at reference conditions; in the second, we assume that the total continuum absorption is constrained for all atmospheres in our model. In both approaches, we decrease the self continuum by 10% and adjust the foreign continuum accordingly. We find that continuum uncertainty mainly affects through its effect onλ. In the first approach, continuum uncertainty mainly affectsλthrough a decrease in the total continuum absorption withT_s; in the second approach, continuum uncertainty affectsλthrough a vertical redistribution of continuum absorption. In both experiments, the effect of continuum uncertainty on is modest atT_s = 288 K (≈0.02 K) but substantial atT_s ≥ 300 K (up to 0.2 K), because at highT_s, the effects of decreasing the self continuum and increasing the foreign continuum have the same sign. These results highlight the importance of a correct partitioning between self and foreign continuum to accurately determine the temperature dependence of Earth's climate sensitivity. 

Abstract Broadband (spectrally‐integrated) radiation calculations are dominated by the expense of spectral integration, and many applications require fast parameterizations for computing radiative flux. Here we describe a novel approach using a linear weighted sum of monochromatic calculations at a small set of optimally‐chosen frequencies. The empirically‐optimized quadrature method is used to compute atmospheric boundary fluxes, net flux profiles throughout the atmosphere, heating rate profiles, and top‐of‐the‐atmosphere forcing by CO₂, in the longwave for clear skies. We evaluate the method against two modern correlatedk‐distribution models and find that we can achieve comparable errors with 32 spectral points. We also examine the effect of minimizing different cost functions, and find that in order to accurately represent heating rates and CO₂forcing, these quantities must be included in the cost function. 

Abstract Weather forecasts made with imperfect models contain state‐dependent errors. Data assimilation (DA) partially corrects these errors with new information from observations. As such, the corrections, or “analysis increments,” produced by the DA process embed information about model errors. An attempt is made here to extract that information to improve numerical weather prediction. Neural networks (NNs) are trained to predict corrections to the systematic error in the National Oceanic and Atmospheric Administration's FV3‐GFS model based on a large set of analysis increments. A simple NN focusing on an atmospheric column significantly improves the estimated model error correction relative to a linear baseline. Leveraging large‐scale horizontal flow conditions using a convolutional NN, when compared to the simple column‐oriented NN, does not improve skill in correcting model error. The sensitivity of model error correction to forecast inputs is highly localized by vertical level and by meteorological variable, and the error characteristics vary across vertical levels. Once trained, the NNs are used to apply an online correction to the forecast during model integration. Improvements are evaluated both within a cycled DA system and across a collection of 10‐day forecasts. It is found that applying state‐dependent NN‐predicted corrections to the model forecast improves the overall quality of DA and improves the 10‐day forecast skill at all lead times. 

The Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) took place from 7 January to 11 July 2020 in the tropical North Atlantic between the eastern edge of Barbados and 51∘ W, the longitude of the Northwest Tropical Atlantic Station (NTAS) mooring. Measurements were made to gather information on shallow atmospheric convection, the effects of aerosols and clouds on the ocean surface energy budget, and mesoscale oceanic processes. Multiple platforms were deployed during ATOMIC including the NOAA RV Ronald H. Brown (RHB) (7 January to 13 February) and WP-3D Orion (P-3) aircraft (17 January to 10 February), the University of Colorado's Robust Autonomous Aerial Vehicle-Endurant Nimble (RAAVEN) uncrewed aerial system (UAS) (24 January to 15 February), NOAA- and NASA-sponsored Saildrones (12 January to 11 July), and Surface Velocity Program Salinity (SVPS) surface ocean drifters (23 January to 29 April). The RV Ronald H. Brown conducted in situ and remote sensing measurements of oceanic and atmospheric properties with an emphasis on mesoscale oceanic–atmospheric coupling and aerosol–cloud interactions. In addition, the ship served as a launching pad for Wave Gliders, Surface Wave Instrument Floats with Tracking (SWIFTs), and radiosondes. Details of measurements made from the RV Ronald H. Brown, ship-deployed assets, and other platforms closely coordinated with the ship during ATOMIC are provided here. These platforms include Saildrone 1064 and the RAAVEN UAS as well as the Barbados Cloud Observatory (BCO) and Barbados Atmospheric Chemistry Observatory (BACO). Inter-platform comparisons are presented to assess consistency in the data sets. Data sets from the RV Ronald H. Brown and deployed assets have been quality controlled and are publicly available at NOAA's National Centers for Environmental Information (NCEI) data archive (https://www.ncei.noaa.gov/archive/accession/ATOMIC-2020, last access: 2 April 2021). Point-of-contact information and links to individual data sets with digital object identifiers (DOIs) are provided herein. 

Abstract 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. 

Abstract. The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or the life cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso- (200 km) and larger (500 km) scales, roughly 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air–sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that EUREC4A explored – from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation – are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at https://doi.org/10.25326/165 (Stevens, 2021), and a film documenting the campaign is provided as a video supplement.