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  • 1
    Online Resource
    Online Resource
    Cham :Springer International Publishing AG,
    Keywords: Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (396 pages)
    Edition: 1st ed.
    ISBN: 9783319772738
    Series Statement: Space Sciences Series of ISSI Series ; v.65
    Language: English
    Note: Intro -- Contents -- Preface to the Special Issue ''ISSI Workshop on Shallow Clouds and Water Vapor, Circulation and Climate Sensitivity'' -- 1 Convective Self-Aggregation in Numerical Simulations: A Review -- 1 Introduction -- 2 Characteristics of Self-Aggregation -- 2.1 General Evolution of Aggregation -- 2.2 Identifying Metrics -- 2.3 Time Scale -- 2.4 Length Scale -- 2.5 Impacts -- 3 Mechanisms of Self-Aggregation -- 3.1 Surface Fluxes -- 3.1.1 Sensitivity to SST -- 3.2 Longwave Radiation -- 3.2.1 Sensitivity to SST -- 3.3 Shortwave Radiation -- 3.3.1 Sensitivity to SST -- 3.4 Advective Processes -- 3.5 Moisture Feedbacks -- 3.6 Triggering Versus Maintenance -- 4 Importance of Self-Aggregation -- 5 Conclusions -- 5.1 What Aspects of Self-Aggregation do Modeling Studies Agree on? -- 5.2 What Remains Uncertain? -- 5.3 What Could be Explored More? -- 5.4 Synthesis -- References -- 2 Observing Convective Aggregation -- 1 Introduction -- 1.1 Importance of Aggregation -- 1.2 Literature Review: Observational Studies of Convective Organization -- 2 Observational Perspectives on Processes Important for Idealized Convective Aggregation -- 2.1 Metrics to Quantify Feedbacks -- 2.2 Initiation Processes -- 2.2.1 Longwave Radiation -- 2.2.2 Surface Fluxes -- 2.2.3 Shortwave Radiation -- 2.2.4 Moisture-Convection Feedbacks -- 2.3 Sensitivity to SST -- 2.4 Maintenance Processes -- 3 Comparing the Idealized World to the Natural World -- 3.1 Time Scales of Self-Aggregation -- 3.2 Mean Wind and Wind Shear -- 3.3 Humidity Profiles -- 3.4 Equatorial Wave Dynamics -- 3.5 Ocean Interaction and Feedback -- 4 Observational Perspectives on Aggregation in a Warming Climate -- 5 Future Observational Aspirations -- 5.1 Evolution of Convective Organization Using Satellite Data -- 5.2 Spaceborne Cloud Radar Approaches. , 5.3 Feasibility of a Ground-Based Observational Network -- 6 Conclusions -- References -- 3 An Observational View of Relationships Between Moisture Aggregation, Cloud, and Radiative Heating Profiles -- 1 Introduction -- 2 Characterizing Aggregation in Clouds and Their Environment -- 2.1 Observations from the A-Train -- 2.2 Characterizing Aggregation in the Water Vapor Field -- 3 Relationships Among Clouds, Humidity, and Aggregation -- 3.1 Cloudiness Depends on Sea Surface Temperature and Aggregation State -- 3.2 Cloudiness, Radiative Heating, and Convective Intensity -- 3.3 Does Vapor Aggregation Imply Convective Aggregation? -- 4 Summary and Discussion -- References -- 4 Correction to: An Observational View of Relationships Between Moisture Aggregation, Cloud, and Radiative Heating Profiles -- 5 Implications of Warm Rain in Shallow Cumulus and Congestus Clouds for Large-Scale Circulations -- 1 Introduction -- 2 Warm Rain in Large-Scale Circulations -- 2.1 A Two-Column RCE Model -- 2.2 Circulating Equilibria in the Two-Column System -- 2.3 Shallow Cumulus -- 2.4 Congestus -- 3 From a Conceptual Model to Nature -- 3.1 Large-Eddy Simulations -- 3.2 Observations -- 4 Concluding Thoughts -- References -- 6 A Survey of Precipitation-Induced Atmospheric Cold Pools over Oceans and Their Interactions with the Larger-Scale Environment -- 1 Introduction -- 2 Cold Pools from Boundary Layers not Exceeding 2 km Altitude -- 3 Cold Pools from Convection Reaching the Mid-Troposphere -- 4 Cold Pools from Deep Tropical Convection -- 5 Remaining Questions -- 5.1 The Relationship of Trade Wind Cold Pools to Cloud Cover -- 5.2 Thermodynamic Secondary Initiation Processes -- References -- 7 Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review -- 1 Seeking Observational Constraints on Low-Cloud Feedbacks -- 2 Cloud-Controlling Factors -- 3 Low-Cloud Feedbacks. , 4 Implications for Climate Sensitivity -- 5 Sources of Uncertainty -- 5.1 Fundamental Issues -- 5.1.1 F1. Are Cloud Sensitivities Time-scale Invariant? -- 5.1.2 F2. Are Clouds Responding to the Controlling Factors? -- 5.1.3 F3. Uncertainty in the Climate Change Prediction of Cloud-Controlling -- Factors -- 5.1.4 F4. Time-Dependency of Cloud-Controlling Factors During a Climate Change -- 5.2 Implementation Issues -- 5.2.1 I1. Imperfect Observations of Clouds and Their Controlling Factors -- 5.2.2 I2. Limited Duration of the Observational Record -- 5.2.3 I3. Limited Spatial Sampling of the Observations -- 5.2.4 I4. Imprecise Statistical Modeling -- 5.2.5 I5. Incomplete Set of Cloud-Controlling Factors -- 6 Summary and Final Remarks -- References -- 8 Mechanisms and Model Diversity of Trade-Wind Shallow Cumulus Cloud Feedbacks: A Review -- 1 Introduction -- 2 Interpreting Model Differences in Trade-Wind Cloud Responses to Warming in General Circulation Models -- 2.1 Boundary-Layer Moisture Budget -- 2.2 The Role of Shallow Convective Mixing -- 3 A Mass Budget Perspective on Cloud-Base Cloud Fraction -- 4 High-Resolution Simulation of Shallow Cumulus Cloud Changes and Mechanisms -- 4.1 Trade-Wind Shallow Cumulus Cloud Response to Warming in LES -- 4.1.1 The Role of Precipitation -- 4.1.2 The Role of Organization -- 4.2 Robustness and Uncertainties of LES Studies -- 5 Connecting LES and GCM Interpretations of Shallow Cumulus Cloud Feedback Mechanisms -- 6 Observational Support for Trade-Wind Shallow Cumulus Cloud Feedbacks -- 7 Synthesis -- References -- 9 Importance Profiles for Water Vapor -- 1 Introduction -- 2 Simplest: The Profile of -- Mass Errors from Vapor Measurement Errors -- 3 Radiative Kernels: Sensitivity of OLR to Humidity -- 4 Importance of Vapor for Deep Convection -- 5 Importance Functions for Passive Remote Sensing. , 6 Summary and Conclusions -- References -- 10 Structure and Dynamical Influence of Water Vapor in the Lower Tropical Troposphere -- 1 Introduction -- 2 Data and Context -- 2.1 Airborne Measurements and the Barbados Cloud Observatory -- 2.1.1 Dropsonde Humidity Measurements During the NARVAL Campaigns -- 2.1.2 WALES -- 2.2 SAPHIR and Megha-Tropiques -- 2.3 Infrared Atmospheric Sounding Interferometer (IASI) -- 3 How Lower-Tropospheric Humidity Influences Clouds, Convection and Circulation -- 3.1 Humidity in the Planetary Boundary Layer -- 3.2 Column Water Vapor (Thermodynamic Effects) -- 3.3 Column Water Vapor (radiative effects) -- 3.4 Elevated Moist Layers -- 4 Remotely Sensed Humidity Variations During NARVAL-1 and NARVAL-2 -- 4.1 General Structure of Humidity Retrievals from SAPHIR -- 4.2 Evaluation of SAPHIR Retrievals by WALES -- 4.3 Comparison with IASI and the Added Value of Retrieving Isotopologues -- 5 A Hypothesis for the Preponderance of Melting Level Convection -- 6 Conclusions -- References -- 11 The Representation of Tropospheric Water Vapor Over Low-Latitude Oceans in (Re-)analysis: Errors, Impacts, and the Ability to Exploit Current and Prospective Observations -- 1 Tropospheric Water Vapor Over Low-Latitude Oceans -- 2 Integrating Observations in Space and Time: Data Assimilation and (Re-)analysis -- 2.1 Producing Meteorological (Re-)analyses -- 2.1.1 Global Forecast Models -- 2.1.2 Data Assimilation Systems -- 2.1.3 Challenges in Assimilating Moisture -- 2.2 Analysis and Reanalysis -- 3 What Measurements Inform Current Estimates? -- 3.1 Microwave and Infrared Sounding -- 3.1.1 Principles of Measurement -- 3.1.2 Why Both Microwave and Infrared Observations are Useful -- 3.1.3 Prospects -- 3.2 Estimates of Precipitable Water from Microwave Observations -- 3.3 GNSS Radio Occultation: A Global Refractometer. , 3.3.1 Principles of Measurement -- 3.3.2 Vertical Resolution, Accuracy, and Limitations -- 3.3.3 Prospects -- 4 Errors in Water Vapor Distributions and the Resulting Impacts -- 4.1 Assessing Errors in the Analyzed Distribution of Water Vapor -- 4.1.1 Assessment in Subsiding Regions -- 4.1.2 Assessment in Convecting Regions -- 4.2 Assessing Impacts -- 5 Characterizing Water Vapor in a More Richly Observed World -- 5.1 Limited Observations and Model Error -- 5.2 Exploiting Richer Observations -- References -- 12 Airborne Lidar Observations of Water Vapor Variability in Tropical Shallow Convective Environment -- 1 Introduction -- 2 The DLR Airborne Water Vapor Lidar -- 3 The Meteosat Images -- 4 Results -- 4.1 Overview -- 4.2 Strong Heterogeneity in the Cloud Layer -- 4.3 Dry Regions in Both Cloud and Sub-cloud Layers -- 4.4 Transport of Moisture Through the Cloud Layer by Shallow Convection -- 4.5 Mean, Variance and Skewness Profiles of Water Vapor -- 5 Conclusions and Outlook -- References -- 13 Emerging Technologies and Synergies for Airborne and Space-Based Measurements of Water Vapor Profiles -- 1 Introduction -- 2 Differential Absorption Lidar -- 2.1 Measurement Capabilities -- 2.2 Technology Readiness -- 3 Differential Absorption Radar -- 3.1 Measurement Capabilities -- 3.2 Technology Readiness -- 4 Microwave Occultation -- 4.1 Measurement Approach -- 4.2 Measurement Capabilities -- 4.3 Technology Readiness -- 5 Hyperspectral Microwave -- 5.1 Measurement Capabilities -- 5.2 Technology Readiness -- 6 Synergies of Observing Systems -- 6.1 Value of Ground-Based Profiling -- 6.2 Examples of Synergetic Applications -- 6.2.1 Combining Lidar and Microwave Radiometer -- 6.2.2 Combining Satellite and Ground-Based Observations -- 6.3 Future Perspectives -- 7 Summary and Conclusions -- References. , 14 Observational Constraints on Cloud Feedbacks: The Role of Active Satellite Sensors.
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  • 2
    ISSN: 1432-0894
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract This study presents a comparison of the water vapor and clear-sky greenhouse effect dependence on sea surface temperature for climate variations of different types. Firstly, coincident satellite observations and meteorological analyses are used to examine seasonal and interannual variations and to evaluate the performance of a general circulation model. Then, this model is used to compare the results inferred from the analysis of observed climate variability with those derived from global climate warming experiments. One part of the coupling between the surface temperature, the water vapor and the clear-sky greenhouse effect is explained by the dependence of the saturation water vapor pressure on the atmospheric temperature. However, the analysis of observed and simulated fields shows that the coupling is very different according to the type of region under consideration and the type of climate forcing that is applied to the Earth-atmosphere system. This difference, due to the variability of the vertical structure of the atmosphere, is analyzed in detail by considering the temperature lapse rate and the vertical profile of relative humidity. Our results suggest that extrapolating the feedbacks inferred from seasonal and short-term interannual climate variability to longer-term climate changes requires great caution. It is argued that our confidence in climate models' predictions would be increased significantly if the basic physical processes that govern the variability of the vertical structure of the atmosphere, and its relation to the large-scale circulation, were better understood and simulated. For this purpose, combined observational and numerical studies focusing on physical processes are needed.
    Type of Medium: Electronic Resource
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  • 3
    ISSN: 1432-0894
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract. This study presents a comparison of the water vapor and clear-sky greenhouse effect dependence on sea surface temperature for climate variations of different types. Firstly, coincident satellite observations and meteorological analyses are used to examine seasonal and interannual variations and to evaluate the performance of a general circulation model. Then, this model is used to compare the results inferred from the analysis of observed climate variability with those derived from global climate warming experiments. One part of the coupling between the surface temperature, the water vapor and the clear-sky greenhouse effect is explained by the dependence of the saturation water vapor pressure on the atmospheric temperature. However, the analysis of observed and simulated fields shows that the coupling is very different according to the type of region under consideration and the type of climate forcing that is applied to the Earth-atmosphere system. This difference, due to the variability of the vertical structure of the atmosphere, is analyzed in detail by considering the temperature lapse rate and the vertical profile of relative humidity. Our results suggest that extrapolating the feedbacks inferred from seasonal and short-term interannual climate variability to longer-term climate changes requires great caution. It is argued that our confidence in climate models' predictions would be increased significantly if the basic physical processes that govern the variability of the vertical structure of the atmosphere, and its relation to the large-scale circulation, were better understood and simulated. For this purpose, combined observational and numerical studies focusing on physical processes are needed.
    Type of Medium: Electronic Resource
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  • 4
    Publication Date: 2022-05-27
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Stevens, B., Bony, S., Farrell, D., Ament, F., Blyth, A., Fairall, C., Karstensen, J., Quinn, P. K., Speich, S., Acquistapace, C., Aemisegger, F., Albright, A. L., Bellenger, H., Bodenschatz, E., Caesar, K.-A., Chewitt-Lucas, R., de Boer, G., Delanoë, J., Denby, L., Ewald, F., Fildier, B., Forde, M., George, G., Gross, S., Hagen, M., Hausold, A., Heywood, K. J., Hirsch, L., Jacob, M., Jansen, F., Kinne, S., Klocke, D., Kölling, T., Konow, H., Lothon, M., Mohr, W., Naumann, A. K., Nuijens, L., Olivier, L., Pincus, R., Pöhlker, M., Reverdin, G., Roberts, G., Schnitt, S., Schulz, H., Siebesma, A. P., Stephan, C. C., Sullivan, P., Touzé-Peiffer, L., Vial, J., Vogel, R., Zuidema, P., Alexander, N., Alves, L., Arixi, S., Asmath, H., Bagheri, G., Baier, K., Bailey, A., Baranowski, D., Baron, A., Barrau, S., Barrett, P. A., Batier, F., Behrendt, A., Bendinger, A., Beucher, F., Bigorre, S., Blades, E., Blossey, P., Bock, O., Böing, S., Bosser, P., Bourras, D., Bouruet-Aubertot, P., Bower, K., Branellec, P., Branger, H., Brennek, M., Brewer, A., Brilouet , P.-E., Brügmann, B., Buehler, S. A., Burke, E., Burton, R., Calmer, R., Canonici, J.-C., Carton, X., Cato Jr., G., Charles, J. A., Chazette, P., Chen, Y., Chilinski, M. T., Choularton, T., Chuang, P., Clarke, S., Coe, H., Cornet, C., Coutris, P., Couvreux, F., Crewell, S., Cronin, T., Cui, Z., Cuypers, Y., Daley, A., Damerell, G. M., Dauhut, T., Deneke, H., Desbios, J.-P., Dörner, S., Donner, S., Douet, V., Drushka, K., Dütsch, M., Ehrlich, A., Emanuel, K., Emmanouilidis, A., Etienne, J.-C., Etienne-Leblanc, S., Faure, G., Feingold, G., Ferrero, L., Fix, A., Flamant, C., Flatau, P. J., Foltz, G. R., Forster, L., Furtuna, I., Gadian, A., Galewsky, J., Gallagher, M., Gallimore, P., Gaston, C., Gentemann, C., Geyskens, N., Giez, A., Gollop, J., Gouirand, I., Gourbeyre, C., de Graaf, D., de Groot, G. E., Grosz, R., Güttler, J., Gutleben, M., Hall, K., Harris, G., Helfer, K. C., Henze, D., Herbert, C., Holanda, B., Ibanez-Landeta, A., Intrieri, J., Iyer, S., Julien, F., Kalesse, H., Kazil, J., Kellman, A., Kidane, A. T., Kirchner, U., Klingebiel, M., Körner, M., Kremper, L. A., Kretzschmar, J., Krüger, O., Kumala, W., Kurz, A., L'Hégaret, P., Labaste, M., Lachlan-Cope, T., Laing, A., Landschützer, P., Lang, T., Lange, D., Lange, I., Laplace, C., Lavik, G., Laxenaire, R., Le Bihan, C., Leandro, M., Lefevre, N., Lena, M., Lenschow, D., Li, Q., Lloyd, G., Los, S., Losi, N., Lovell, O., Luneau, C., Makuch, P., Malinowski, S., Manta, G., Marinou, E., Marsden, N., Masson, S., Maury, N., Mayer, B., Mayers-Als, M., Mazel, C., McGeary, W., McWilliams, J. C., Mech, M., Mehlmann, M., Meroni, A. N., Mieslinger, T., Minikin, A., Minnett, P., Möller, G., Morfa Avalos, Y., Muller, C., Musat, I., Napoli, A., Neuberger, A., Noisel, C., Noone, D., Nordsiek, F., Nowak, J. L., Oswald, L., Parker, D. J., Peck, C., Person, R., Philippi, M., Plueddemann, A., Pöhlker, C., Pörtge, V., Pöschl, U., Pologne, L., Posyniak, M., Prange, M., Quiñones Meléndez, E., Radtke, J., Ramage, K., Reimann, J., Renault, L., Reus, K., Reyes, A., Ribbe, J., Ringel, M., Ritschel, M., Rocha, C. B., Rochetin, N., Röttenbacher, J., Rollo, C., Royer, H., Sadoulet, P., Saffin, L., Sandiford, S., Sandu, I., Schäfer, M., Schemann, V., Schirmacher, I., Schlenczek, O., Schmidt, J., Schröder, M., Schwarzenboeck, A., Sealy, A., Senff, C. J., Serikov, I., Shohan, S., Siddle, E., Smirnov, A., Späth, F., Spooner, B., Stolla, M. K., Szkółka, W., de Szoeke, S. P., Tarot, S., Tetoni, E., Thompson, E., Thomson, J., Tomassini, L., Totems, J., Ubele, A. A., Villiger, L., von Arx, J., Wagner, T., Walther, A., Webber, B., Wendisch, M., Whitehall, S., Wiltshire, A., Wing, A. A., Wirth, M., Wiskandt, J., Wolf, K., Worbes, L., Wright, E., Wulfmeyer, V., Young, S., Zhang, C., Zhang, D., Ziemen, F., Zinner, T., and Zöger, M.: EUREC4A. Earth System Science Data, 13(8), (2021): 4067–4119, https://doi.org/10.5194/essd-13-4067-2021.
    Description: 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.
    Description: This research has been supported by the people and government of Barbados; the Max Planck Society and its supporting members; the German Research Foundation (DFG) and the German Federal Ministry of Education and Research (grant nos. GPF18-1_69 and GPF18-2_50); the European Research Council (ERC) advanced grant EUREC4A (grant agreement no. 694768) under the European Union’s Horizon 2020 research and innovation program (H2020), with additional support from CNES (the French National Centre for Space Studies) through the EECLAT proposal, Météo-France, the CONSTRAIN H2020 project (grant agreement no. 820829), and the French AERIS Research Infrastructure; the Natural Environment Research Council (NE/S015868/1, NE/S015752/1, and NE/S015779/1); ERC under the European Union’s H2020 program (COMPASS, advanced grant agreement no. 74110); the French national program LEFE INSU, by IFREMER, the French research fleet, CNES, the French research infrastructures AERIS and ODATIS, IPSL, the Chaire Chanel program of the Geosciences Department at ENS, and the European Union's Horizon 2020 research and innovation program under grant agreement no. 817578 TRIATLAS; NOAA’s Climate Variability and Prediction Program within the Climate Program Office (grant nos. GC19-305 and GC19-301); NOAA cooperative agreement NA15OAR4320063; NOAA's Climate Program Office and base funds to NOAA/AOML's Physical Oceanography Division; Swiss National Science Foundation grant no. 188731; the UAS Program Office, Climate Program Office, and Physical Sciences Laboratory and by the US National Science Foundation (NSF) through grant AGS-1938108; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC 2037 “CLICCS – Climate, Climatic Change, and Society” – project no. 390683824; and Poland’s National Science Centre grant no. UMO-2018/30/M/ST10/00674 and Foundation for Polish Science grant no. POIR.04.04.00-00-3FD6/17-02.
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 5
    Publication Date: 2022-05-26
    Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Surveys in Geophysics 38 (2017): 1529–1568, doi:10.1007/s10712-017-9428-0.
    Description: Trade-wind cumuli constitute the cloud type with the highest frequency of occurrence on Earth, and it has been shown that their sensitivity to changing environmental conditions will critically influence the magnitude and pace of future global warming. Research over the last decade has pointed out the importance of the interplay between clouds, convection and circulation in controling this sensitivity. Numerical models represent this interplay in diverse ways, which translates into different responses of trade-cumuli to climate perturbations. Climate models predict that the area covered by shallow cumuli at cloud base is very sensitive to changes in environmental conditions, while process models suggest the opposite. To understand and resolve this contradiction, we propose to organize a field campaign aimed at quantifying the physical properties of trade-cumuli (e.g., cloud fraction and water content) as a function of the large-scale environment. Beyond a better understanding of clouds-circulation coupling processes, the campaign will provide a reference data set that may be used as a benchmark for advancing the modelling and the satellite remote sensing of clouds and circulation. It will also be an opportunity for complementary investigations such as evaluating model convective parameterizations or studying the role of ocean mesoscale eddies in air–sea interactions and convective organization.
    Description: The EUREC4A project is supported by the European Research Council (ERC), under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 694768), by the Max Planck Society and by DFG (Deutsche Forschungsgemeinschaft, German Research Foundation) Priority Program SPP 1294.
    Keywords: Trade-wind cumulus ; Shallow convection ; Cloud feedback ; Atmospheric circulation ; Field campaign
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 6
    Publication Date: 2020-02-06
    Description: Trade-wind cumuli constitute the cloud type with the highest frequency of occurrence on Earth, and it has been shown that their sensitivity to changing environmental conditions will critically influence the magnitude and pace of future global warming. Research over the last decade has pointed out the importance of the interplay between clouds, convection and circulation in controling this sensitivity. Numerical models represent this interplay in diverse ways, which translates into different responses of trade-cumuli to climate perturbations. Climate models predict that the area covered by shallow cumuli at cloud base is very sensitive to changes in environmental conditions, while process models suggest the opposite. To understand and resolve this contradiction, we propose to organize a field campaign aimed at quantifying the physical properties of trade-cumuli (e.g., cloud fraction and water content) as a function of the large-scale environment. Beyond a better understanding of clouds-circulation coupling processes, the campaign will provide a reference data set that may be used as a benchmark for advancing the modelling and the satellite remote sensing of clouds and circulation. It will also be an opportunity for complementary investigations such as evaluating model convective parameterizations or studying the role of ocean mesoscale eddies in air–sea interactions and convective organization
    Type: Article , PeerReviewed
    Format: text
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  • 7
    Publication Date: 2024-02-07
    Description: 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.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Format: video
    Format: video
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