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G. K. Mather, M. J. Dixon, and J. M. de Jager

Abstract

The experimental design, analyses, and results of the first Nelspruit randomized cloud seeding experiment are described. The experiment ran for three years, commencing in October 1984, and involved the on-top seeding of new cloud turrets growing on the flanks of isolated multicellular storms using dry ice delivered from a Learjet at around the height of the −10°C isotherm. All storms were tracked by a radar operating in computer-controlled volume scan mode. A total of 169 storms were examined, of which 94 passed the selection criteria. The most important criterion was based upon a microphysical classification scheme obtained from measurements made by the instrumented Learjet. This scheme, based upon a ratio of cloud-base temperature to potential buoyancy at 500 mb, rejected those storms in which the production of precipitation via coalescence was unlikely.

A key element of the experiment was the ability to objectively track the storms using an automatic storm tracking algorithm. Storms were analyzed in terms of their track properties, some of the more important of which were storm volume, area, and rain flux. Analyses of these track properties in 10-min time intervals either side of decision time (the time the seed/no-seed decision was made) proved to be the most revealing in terms of observed changes and rates of changes in convective cloud processes. This analysis showed an almost fourfold percentage increase in radar-measured rain flux and storm area when the seeded and control storms were compared.

A confirmatory experiment was conducted in the third season. Storm track properties that showed an apparent response to seeding in each of the first two seasons were selected prior the commencement of the third season. All but one of these track properties either stayed the same or showed increases in the third season, confirming the hypothesis that there were radar-detected differences between the seeded and control storms.

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James W. Wilson, N. Andrew Crook, Cynthia K. Mueller, Juanzhen Sun, and Michael Dixon

This paper reviews the status of forecasting convective precipitation for time periods less than a few hours (nowcasting). Techniques for nowcasting thunderstorm location were developed in the 1960s and 1970s by extrapolating radar echoes. The accuracy of these forecasts generally decreases very rapidly during the first 30 min because of the very short lifetime of individual convective cells. Fortunately more organized features like squall lines and supercells can be successfully extrapolated for longer time periods. Physical processes that dictate the initiation and dissipation of convective storms are not necessarily observable in the past history of a particular echo development; rather, they are often controlled by boundary layer convergence features, environmental vertical wind shear, and buoyancy. Thus, successful forecasts of storm initiation depend on accurate specification of the initial thermodynamic and kinematic fields with particular attention to convergence lines. For these reasons the ability to improve on simple extrapolation techniques had stagnated until the present national observational network modernization program. The ability to observe small-scale boundary layer convergence lines is now possible with operational Doppler radars and satellite imagery. In addition, it has been demonstrated that high-resolution wind retrievals can be obtained from single Doppler radar. Two methods are presently under development for using these modern datasets to forecast thunderstorm evolution: knowledge-based expert systems and numerical forecasting models that are initialized with radar data. Both these methods are very promising and progressing rapidly. Operational tests of expert systems are presently taking place in the United Kingdom and in the United States.

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T. R. Knutson, T. L. Delworth, K. W. Dixon, I. M. Held, J. Lu, V. Ramaswamy, M. D. Schwarzkopf, G. Stenchikov, and R. J. Stouffer

Abstract

Historical climate simulations of the period 1861–2000 using two new Geophysical Fluid Dynamics Laboratory (GFDL) global climate models (CM2.0 and CM2.1) are compared with observed surface temperatures. All-forcing runs include the effects of changes in well-mixed greenhouse gases, ozone, sulfates, black and organic carbon, volcanic aerosols, solar flux, and land cover. Indirect effects of tropospheric aerosols on clouds and precipitation processes are not included. Ensembles of size 3 (CM2.0) and 5 (CM2.1) with all forcings are analyzed, along with smaller ensembles of natural-only and anthropogenic-only forcing, and multicentury control runs with no external forcing.

Observed warming trends on the global scale and in many regions are simulated more realistically in the all-forcing and anthropogenic-only forcing runs than in experiments using natural-only forcing or no external forcing. In the all-forcing and anthropogenic-only forcing runs, the model shows some tendency for too much twentieth-century warming in lower latitudes and too little warming in higher latitudes. Differences in Arctic Oscillation behavior between models and observations contribute substantially to an underprediction of the observed warming over northern Asia. In the all-forcing and natural-only forcing runs, a temporary global cooling in the models during the 1880s not evident in the observed temperature records is volcanically forced. El Niño interactions complicate comparisons of observed and simulated temperature records for the El Chichón and Mt. Pinatubo eruptions during the early 1980s and early 1990s.

The simulations support previous findings that twentieth-century global warming has resulted from a combination of natural and anthropogenic forcing, with anthropogenic forcing being the dominant cause of the pronounced late-twentieth-century warming. The regional results provide evidence for an emergent anthropogenic warming signal over many, if not most, regions of the globe. The warming signal has emerged rather monotonically in the Indian Ocean/western Pacific warm pool during the past half-century. The tropical and subtropical North Atlantic and the tropical eastern Pacific are examples of regions where the anthropogenic warming signal now appears to be emerging from a background of more substantial multidecadal variability.

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R. J. Stouffer, A. J. Broccoli, T. L. Delworth, K. W. Dixon, R. Gudgel, I. Held, R. Hemler, T. Knutson, Hyun-Chul Lee, M. D. Schwarzkopf, B. Soden, M. J. Spelman, M. Winton, and Fanrong Zeng

Abstract

The climate response to idealized changes in the atmospheric CO2 concentration by the new GFDL climate model (CM2) is documented. This new model is very different from earlier GFDL models in its parameterizations of subgrid-scale physical processes, numerical algorithms, and resolution. The model was constructed to be useful for both seasonal-to-interannual predictions and climate change research. Unlike previous versions of the global coupled GFDL climate models, CM2 does not use flux adjustments to maintain a stable control climate. Results from two model versions, Climate Model versions 2.0 (CM2.0) and 2.1 (CM2.1), are presented.

Two atmosphere–mixed layer ocean or slab models, Slab Model versions 2.0 (SM2.0) and 2.1 (SM2.1), are constructed corresponding to CM2.0 and CM2.1. Using the SM2 models to estimate the climate sensitivity, it is found that the equilibrium globally averaged surface air temperature increases 2.9 (SM2.0) and 3.4 K (SM2.1) for a doubling of the atmospheric CO2 concentration. When forced by a 1% per year CO2 increase, the surface air temperature difference around the time of CO2 doubling [transient climate response (TCR)] is about 1.6 K for both coupled model versions (CM2.0 and CM2.1). The simulated warming is near the median of the responses documented for the climate models used in the 2001 Intergovernmental Panel on Climate Change (IPCC) Working Group I Third Assessment Report (TAR).

The thermohaline circulation (THC) weakened in response to increasing atmospheric CO2. By the time of CO2 doubling, the weakening in CM2.1 is larger than that found in CM2.0: 7 and 4 Sv (1 Sv ≡ 106 m3 s−1), respectively. However, the THC in the control integration of CM2.1 is stronger than in CM2.0, so that the percentage change in the THC between the two versions is more similar. The average THC change for the models presented in the TAR is about 3 or 4 Sv; however, the range across the model results is very large, varying from a slight increase (+2 Sv) to a large decrease (−10 Sv).

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Rym Msadek, T. L. Delworth, A. Rosati, W. Anderson, G. Vecchi, Y.-S. Chang, K. Dixon, R. G. Gudgel, W. Stern, A. Wittenberg, X. Yang, F. Zeng, R. Zhang, and S. Zhang

Abstract

Decadal prediction experiments were conducted as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5) using the GFDL Climate Model, version 2.1 (CM2.1) forecast system. The abrupt warming of the North Atlantic Subpolar Gyre (SPG) that was observed in the mid-1990s is considered as a case study to evaluate forecast capabilities and better understand the reasons for the observed changes. Initializing the CM2.1 coupled system produces high skill in retrospectively predicting the mid-1990s shift, which is not captured by the uninitialized forecasts. All the hindcasts initialized in the early 1990s show a warming of the SPG; however, only the ensemble-mean hindcasts initialized in 1995 and 1996 are able to reproduce the observed abrupt warming and the associated decrease and contraction of the SPG. Examination of the physical mechanisms responsible for the successful retrospective predictions indicates that initializing the ocean is key to predicting the mid-1990s warming. The successful initialized forecasts show an increased Atlantic meridional overturning circulation and North Atlantic Current transport, which drive an increased advection of warm saline subtropical waters northward, leading to a westward shift of the subpolar front and, subsequently, a warming and spindown of the SPG. Significant seasonal climate impacts are predicted as the SPG warms, including a reduced sea ice concentration over the Arctic, an enhanced warming over the central United States during summer and fall, and a northward shift of the mean ITCZ. These climate anomalies are similar to those observed during a warm phase of the Atlantic multidecadal oscillation, which is encouraging for future predictions of North Atlantic climate.

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R. J. Stouffer, J. Yin, J. M. Gregory, K. W. Dixon, M. J. Spelman, W. Hurlin, A. J. Weaver, M. Eby, G. M. Flato, H. Hasumi, A. Hu, J. H. Jungclaus, I. V. Kamenkovich, A. Levermann, M. Montoya, S. Murakami, S. Nawrath, A. Oka, W. R. Peltier, D. Y. Robitaille, A. Sokolov, G. Vettoretti, and S. L. Weber

Abstract

The Atlantic thermohaline circulation (THC) is an important part of the earth's climate system. Previous research has shown large uncertainties in simulating future changes in this critical system. The simulated THC response to idealized freshwater perturbations and the associated climate changes have been intercompared as an activity of World Climate Research Program (WCRP) Coupled Model Intercomparison Project/Paleo-Modeling Intercomparison Project (CMIP/PMIP) committees. This intercomparison among models ranging from the earth system models of intermediate complexity (EMICs) to the fully coupled atmosphere–ocean general circulation models (AOGCMs) seeks to document and improve understanding of the causes of the wide variations in the modeled THC response. The robustness of particular simulation features has been evaluated across the model results. In response to 0.1-Sv (1 Sv ≡ 106 m3 s−1) freshwater input in the northern North Atlantic, the multimodel ensemble mean THC weakens by 30% after 100 yr. All models simulate some weakening of the THC, but no model simulates a complete shutdown of the THC. The multimodel ensemble indicates that the surface air temperature could present a complex anomaly pattern with cooling south of Greenland and warming over the Barents and Nordic Seas. The Atlantic ITCZ tends to shift southward. In response to 1.0-Sv freshwater input, the THC switches off rapidly in all model simulations. A large cooling occurs over the North Atlantic. The annual mean Atlantic ITCZ moves into the Southern Hemisphere. Models disagree in terms of the reversibility of the THC after its shutdown. In general, the EMICs and AOGCMs obtain similar THC responses and climate changes with more pronounced and sharper patterns in the AOGCMs.

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G. A. Vecchi, T. Delworth, R. Gudgel, S. Kapnick, A. Rosati, A. T. Wittenberg, F. Zeng, W. Anderson, V. Balaji, K. Dixon, L. Jia, H.-S. Kim, L. Krishnamurthy, R. Msadek, W. F. Stern, S. D. Underwood, G. Villarini, X. Yang, and S. Zhang

Abstract

Tropical cyclones (TCs) are a hazard to life and property and a prominent element of the global climate system; therefore, understanding and predicting TC location, intensity, and frequency is of both societal and scientific significance. Methodologies exist to predict basinwide, seasonally aggregated TC activity months, seasons, and even years in advance. It is shown that a newly developed high-resolution global climate model can produce skillful forecasts of seasonal TC activity on spatial scales finer than basinwide, from months and seasons in advance of the TC season. The climate model used here is targeted at predicting regional climate and the statistics of weather extremes on seasonal to decadal time scales, and comprises high-resolution (50 km × 50 km) atmosphere and land components as well as more moderate-resolution (~100 km) sea ice and ocean components. The simulation of TC climatology and interannual variations in this climate model is substantially improved by correcting systematic ocean biases through “flux adjustment.” A suite of 12-month duration retrospective forecasts is performed over the 1981–2012 period, after initializing the climate model to observationally constrained conditions at the start of each forecast period, using both the standard and flux-adjusted versions of the model. The standard and flux-adjusted forecasts exhibit equivalent skill at predicting Northern Hemisphere TC season sea surface temperature, but the flux-adjusted model exhibits substantially improved basinwide and regional TC activity forecasts, highlighting the role of systematic biases in limiting the quality of TC forecasts. These results suggest that dynamical forecasts of seasonally aggregated regional TC activity months in advance are feasible.

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Anders A. Jensen, James O. Pinto, Sean C. C. Bailey, Ryan A. Sobash, Gijs de Boer, Adam L. Houston, Phillip B. Chilson, Tyler Bell, Glen Romine, Suzanne W. Smith, Dale A. Lawrence, Cory Dixon, Julie K. Lundquist, Jamey D. Jacob, Jack Elston, Sean Waugh, and Matthias Steiner

Abstract

Uncrewed aircraft system (UAS) observations collected during the 2018 LAPSE-RATE field campaign were assimilated into a high-resolution configuration of the Weather Research and Forecasting model using an ensemble Kalman filter. The benefit of UAS observations was assessed for a terrain-driven (drainage and upvalley) flow event that occurred within Colorado’s San Luis Valley (SLV) using independent observations. The analysis and prediction of the strength, depth and horizontal extent of drainage flow from the Saguache Canyon and the subsequent transition to upvalley and up-canyon flow was improved compared to that obtained both without DA (benchmark) and when only surface observations were assimilated. Assimilation of UAS observations greatly improved the analyses of vertical variations in temperature, relative humidity, and winds at multiple locations in the northern portion of the SLV with reductions in both bias and the root mean square error of roughly 40% for each variable compared to the benchmark run. Despite these noted improvements, some biases remain that were tied to measurement error and/or the impact of the boundary layer parameterization on vertically spreading the observations, both of which require further exploration. The results presented here highlight how observations obtained with a fleet of profiling UAS improve limited-area, high-resolution analyses and short-term forecasts in complex terrain.

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Gijs de Boer, Constantin Diehl, Jamey Jacob, Adam Houston, Suzanne W. Smith, Phillip Chilson, David G. Schmale III, Janet Intrieri, James Pinto, Jack Elston, David Brus, Osku Kemppinen, Alex Clark, Dale Lawrence, Sean C. C. Bailey, Michael P. Sama, Amy Frazier, Christopher Crick, Victoria Natalie, Elizabeth Pillar-Little, Petra Klein, Sean Waugh, Julie K. Lundquist, Lindsay Barbieri, Stephan T. Kral, Anders A. Jensen, Cory Dixon, Steven Borenstein, Daniel Hesselius, Kathleen Human, Philip Hall, Brian Argrow, Troy Thornberry, Randy Wright, and Jason T. Kelly

ABSTRACT

Because unmanned aircraft systems (UAS) offer new perspectives on the atmosphere, their use in atmospheric science is expanding rapidly. In support of this growth, the International Society for Atmospheric Research Using Remotely-Piloted Aircraft (ISARRA) has been developed and has convened annual meetings and “flight weeks.” The 2018 flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation–A Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE), involved a 1-week deployment to Colorado’s San Luis Valley. Between 14 and 20 July 2018 over 100 students, scientists, engineers, pilots, and outreach coordinators conducted an intensive field operation using unmanned aircraft and ground-based assets to develop datasets, community, and capabilities. In addition to a coordinated “Community Day” which offered a chance for groups to share their aircraft and science with the San Luis Valley community, LAPSE-RATE participants conducted nearly 1,300 research flights totaling over 250 flight hours. The measurements collected have been used to advance capabilities (instrumentation, platforms, sampling techniques, and modeling tools), conduct a detailed system intercomparison study, develop new collaborations, and foster community support for the use of UAS in atmospheric science.

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Ian M. Brooks, Margaret J. Yelland, Robert C. Upstill-Goddard, Philip D. Nightingale, Steve Archer, Eric d'Asaro, Rachael Beale, Cory Beatty, Byron Blomquist, A. Anthony Bloom, Barbara J. Brooks, John Cluderay, David Coles, John Dacey, Michael Degrandpre, Jo Dixon, William M. Drennan, Joseph Gabriele, Laura Goldson, Nick Hardman-Mountford, Martin K. Hill, Matt Horn, Ping-Chang Hsueh, Barry Huebert, Gerrit De Leeuw, Timothy G. Leighton, Malcolm Liddicoat, Justin J. N. Lingard, Craig Mcneil, James B. Mcquaid, Ben I. Moat, Gerald Moore, Craig Neill, Sarah J. Norris, Simon O'Doherty, Robin W. Pascal, John Prytherch, Mike Rebozo, Erik Sahlee, Matt Salter, Ute Schuster, Ingunn Skjelvan, Hans Slagter, Michael H. Smith, Paul D. Smith, Meric Srokosz, John A. Stephens, Peter K. Taylor, Maciej Telszewski, Roisin Walsh, Brian Ward, David K. Woolf, Dickon Young, and Henk Zemmelink

Abstract

No Abstract available.

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