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Zhichang Guo, Paul A. Dirmeyer, Randal D. Koster, Y. C. Sud, Gordon Bonan, Keith W. Oleson, Edmond Chan, Diana Verseghy, Peter Cox, C. T. Gordon, J. L. McGregor, Shinjiro Kanae, Eva Kowalczyk, David Lawrence, Ping Liu, David Mocko, Cheng-Hsuan Lu, Ken Mitchell, Sergey Malyshev, Bryant McAvaney, Taikan Oki, Tomohito Yamada, Andrew Pitman, Christopher M. Taylor, Ratko Vasic, and Yongkang Xue

Abstract

The 12 weather and climate models participating in the Global Land–Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land–atmosphere coupling and some intriguing commonalities. In this paper, the causes of variations in coupling strength—both the geographic variations within a given model and the model-to-model differences—are addressed. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage—an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first-stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation–precipitation connection, however, also play a key role.

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Randal D. Koster, Y. C. Sud, Zhichang Guo, Paul A. Dirmeyer, Gordon Bonan, Keith W. Oleson, Edmond Chan, Diana Verseghy, Peter Cox, Harvey Davies, Eva Kowalczyk, C. T. Gordon, Shinjiro Kanae, David Lawrence, Ping Liu, David Mocko, Cheng-Hsuan Lu, Ken Mitchell, Sergey Malyshev, Bryant McAvaney, Taikan Oki, Tomohito Yamada, Andrew Pitman, Christopher M. Taylor, Ratko Vasic, and Yongkang Xue

Abstract

The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detail so that any interested modeling group can repeat them easily and thereby place their model’s coupling strength within the broad range of those documented here.

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Catherine A. Senior, John H. Marsham, Ségolène Berthou, Laura E. Burgin, Sonja S. Folwell, Elizabeth J. Kendon, Cornelia M. Klein, Richard G. Jones, Neha Mittal, David P. Rowell, Lorenzo Tomassini, Théo Vischel, Bernd Becker, Cathryn E. Birch, Julia Crook, Andrew J. Dougill, Declan L. Finney, Richard J. Graham, Neil C. G. Hart, Christopher D. Jack, Lawrence S. Jackson, Rachel James, Bettina Koelle, Herbert Misiani, Brenda Mwalukanga, Douglas J. Parker, Rachel A. Stratton, Christopher M. Taylor, Simon O. Tucker, Caroline M. Wainwright, Richard Washington, and Martin R. Willet

Abstract

Pan-Africa convection-permitting regional climate model simulations have been performed to study the impact of high resolution and the explicit representation of atmospheric moist convection on the present and future climate of Africa. These unique simulations have allowed European and African climate scientists to understand the critical role that the representation of convection plays in the ability of a contemporary climate model to capture climate and climate change, including many impact-relevant aspects such as rainfall variability and extremes. There are significant improvements in not only the small-scale characteristics of rainfall such as its intensity and diurnal cycle, but also in the large-scale circulation. Similarly, effects of explicit convection affect not only projected changes in rainfall extremes, dry spells, and high winds, but also continental-scale circulation and regional rainfall accumulations. The physics underlying such differences are in many cases expected to be relevant to all models that use parameterized convection. In some cases physical understanding of small-scale change means that we can provide regional decision-makers with new scales of information across a range of sectors. We demonstrate the potential value of these simulations both as scientific tools to increase climate process understanding and, when used with other models, for direct user applications. We describe how these ground-breaking simulations have been achieved under the U.K. Government’s Future Climate for Africa Programme. We anticipate a growing number of such simulations, which we advocate should become a routine component of climate projection, and encourage international coordination of such computationally and human-resource expensive simulations as effectively as possible.

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Christopher J. Anderson, Raymond W. Arritt, Zaitao Pan, Eugene S. Takle, William J. Gutowski Jr., Francis O. Otieno, Renato da Silva, Daniel Caya, Jens H. Christensen, Daniel Lüthi, Miguel A. Gaertner, Clemente Gallardo, Filippo Giorgi, René Laprise, Song-You Hong, Colin Jones, H-M. H. Juang, J. J. Katzfey, John L. McGregor, William M. Lapenta, Jay W. Larson, John A. Taylor, Glen E. Liston, Roger A. Pielke Sr., and John O. Roads

Abstract

Thirteen regional climate model (RCM) simulations of June–July 1993 were compared with each other and observations. Water vapor conservation and precipitation characteristics in each RCM were examined for a 10° × 10° subregion of the upper Mississippi River basin, containing the region of maximum 60-day accumulated precipitation in all RCMs and station reports.

All RCMs produced positive precipitation minus evapotranspiration (PE > 0), though most RCMs produced PE below the observed range. RCM recycling ratios were within the range estimated from observations. No evidence of common errors of E was found. In contrast, common dry bias of P was found in the simulations.

Daily cycles of terms in the water vapor conservation equation were qualitatively similar in most RCMs. Nocturnal maximums of P and C (convergence) occurred in 9 of 13 RCMs, consistent with observations. Three of the four driest simulations failed to couple P and C overnight, producing afternoon maximum P. Further, dry simulations tended to produce a larger fraction of their 60-day accumulated precipitation from low 3-h totals.

In station reports, accumulation from high (low) 3-h totals had a nocturnal (early morning) maximum. This time lag occurred, in part, because many mesoscale convective systems had reached peak intensity overnight and had declined in intensity by early morning. None of the RCMs contained such a time lag. It is recommended that short-period experiments be performed to examine the ability of RCMs to simulate mesoscale convective systems prior to generating long-period simulations for hydroclimatology.

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Douglas J Parker, Alan M Blyth, Steven J. Woolnough, Andrew J. Dougill, Caroline L. Bain, Estelle de Coning, Mariane Diop-Kane, Andre Kamga Foamouhoue, Benjamin Lamptey, Ousmane Ndiaye, Paolo Ruti, Elijah A. Adefisan, Leonard K Amekudzi, Philip Antwi-Agyei, Cathryn E. Birch, Carlo Cafaro, Hamish Carr, Benard Chanzu, Samantha J. Clarke, Helen Coskeran, Sylvester K. Danuor, Felipe M. de Andrade, Kone Diakaria, Cheikh Dione, Cheikh Abdoulahat Diop, Jennifer K. Fletcher, Amadou T Gaye, James L. Groves, Masilin Gudoshava, Andrew J. Hartley, Linda C. Hirons, Ishiyaku Ibrahim, Tamora D. James, Kamoru A. Lawal, John H Marsham, J N Mutemi, Emmanuel Chilekwu Okogbue, Eniola Olaniyan, J. B. Omotosho, Joseph Portuphy, Alexander J. Roberts, Juliane Schwendike, Zewdu T. Segele, Thorwald H.M. Stein, Andrea L Taylor, Christopher M Taylor, Tanya A. Warnaars, Stuart Webster, Beth J. Woodhams, and Lorraine Youds

Abstract

Africa is poised for a revolution in the quality and relevance of weather predictions, with potential for great benefits in terms of human and economic security. This revolution will be driven by recent international progress in nowcasting, numerical weather prediction, theoretical tropical dynamics and forecast communication, but will depend on suitable scientific investment being made. The commercial sector has recognized this opportunity and new forecast products are being made available to African stakeholders. At this time, it is vital that robust scientific methods are used to develop and evaluate the new generation of forecasts. The GCRF African SWIFT project represents an international effort to advance scientific solutions across the fields of nowcasting, synoptic and short-range severe weather prediction, subseasonal-to-seasonal (S2S) prediction, user engagement and forecast evaluation. This paper describes the opportunities facing African meteorology and the ways in which SWIFT is meeting those opportunities and identifying priority next steps.

Delivery and maintenance of weather forecasting systems exploiting these new solutions requires a trained body of scientists with skills in research and training; modelling and operational prediction; communications and leadership. By supporting partnerships between academia and operational agencies in four African partner countries, the SWIFT project is helping to build capacity and capability in African forecasting science. A highlight of SWIFT is the coordination of three weather-forecasting “Testbeds” – the first of their kind in Africa – which have been used to bring new evaluation tools, research insights, user perspectives and communications pathways into a semi-operational forecasting environment.

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David C. Fritts, Ronald B. Smith, Michael J. Taylor, James D. Doyle, Stephen D. Eckermann, Andreas Dörnbrack, Markus Rapp, Bifford P. Williams, P.-Dominique Pautet, Katrina Bossert, Neal R. Criddle, Carolyn A. Reynolds, P. Alex Reinecke, Michael Uddstrom, Michael J. Revell, Richard Turner, Bernd Kaifler, Johannes S. Wagner, Tyler Mixa, Christopher G. Kruse, Alison D. Nugent, Campbell D. Watson, Sonja Gisinger, Steven M. Smith, Ruth S. Lieberman, Brian Laughman, James J. Moore, William O. Brown, Julie A. Haggerty, Alison Rockwell, Gregory J. Stossmeister, Steven F. Williams, Gonzalo Hernandez, Damian J. Murphy, Andrew R. Klekociuk, Iain M. Reid, and Jun Ma

Abstract

The Deep Propagating Gravity Wave Experiment (DEEPWAVE) was designed to quantify gravity wave (GW) dynamics and effects from orographic and other sources to regions of dissipation at high altitudes. The core DEEPWAVE field phase took place from May through July 2014 using a comprehensive suite of airborne and ground-based instruments providing measurements from Earth’s surface to ∼100 km. Austral winter was chosen to observe deep GW propagation to high altitudes. DEEPWAVE was based on South Island, New Zealand, to provide access to the New Zealand and Tasmanian “hotspots” of GW activity and additional GW sources over the Southern Ocean and Tasman Sea. To observe GWs up to ∼100 km, DEEPWAVE utilized three new instruments built specifically for the National Science Foundation (NSF)/National Center for Atmospheric Research (NCAR) Gulfstream V (GV): a Rayleigh lidar, a sodium resonance lidar, and an advanced mesosphere temperature mapper. These measurements were supplemented by in situ probes, dropsondes, and a microwave temperature profiler on the GV and by in situ probes and a Doppler lidar aboard the German DLR Falcon. Extensive ground-based instrumentation and radiosondes were deployed on South Island, Tasmania, and Southern Ocean islands. Deep orographic GWs were a primary target but multiple flights also observed deep GWs arising from deep convection, jet streams, and frontal systems. Highlights include the following: 1) strong orographic GW forcing accompanying strong cross-mountain flows, 2) strong high-altitude responses even when orographic forcing was weak, 3) large-scale GWs at high altitudes arising from jet stream sources, and 4) significant flight-level energy fluxes and often very large momentum fluxes at high altitudes.

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