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Albert Simon
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Simon Albert, Kirsten Abernethy, Badin Gibbes, Alistair Grinham, Nixon Tooler, and Shankar Aswani
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Simon Albert, Kirsten Abernethy, Badin Gibbes, Alistair Grinham, Nixon Tooler, and Shankar Aswani

Abstract

For millions of people living along the coastal fringe, sea level rise is perhaps the greatest threat to livelihoods over the coming century. With the refinement and downscaling of global climate models and increasing availability of airborne-lidar-based inundation models, it is possible to predict and quantify these threats with reasonable accuracy where such information is available. For less developed countries, especially small island states, access to high-resolution digital elevation models (DEMs) derived from lidar is limited. The only freely available DEMs that could be used for inundation modeling by these nations are those based on data from the Shuttle Radar Topography Mission (SRTM). These data, with a horizontal resolution of ≈90 m and a vertical accuracy of ±5–10 m, are generally unsuitable for local-scale planning and adaption projects. To address this disparity, low-cost ground-based techniques were tested and applied to accurately determine coastal topography in the Solomon Islands. This method had a significantly improved vertical accuracy (±2 cm) and was readily learned by local community members, who were able to independently map and determine the vulnerability of their costal community to inundation from sea level rise. For areas where lidar is not economically viable, this method is intended to provide an important balance of cost, simplicity, accuracy, and local participation that can assist remote coastal communities with coastal planning decisions. The method can enhance local capacity and arguably promotes more meaningful local engagement in sea level rise planning and adaptation activities.

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Bert G. Heusinkveld, Simon M. Berkowicz, Adrie F. G. Jacobs, Albert A. M. Holtslag, and Willy C. A. M. Hillen

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The development of a simple and low-cost portable weighing microlysimeter that makes use of a load cell for automated recording and for studying daily dew formation, rate of accumulation, and subsequent evaporation in arid or semiarid regions during rainless seasons is presented. The sampling cup is 3.5 cm deep, with the load cell itself situated at 20-cm depth to minimize temperature effects. The device was tested in a sand dune experimental station situated near Nizzana, northwest Negev Desert, Israel, during which extensive micrometeorological measurements were collected. One microlysimeter was placed in a playa and a second was installed on the stabilized midslope of an adjacent linear sand dune. To assess the performance of the load cell microlysimeters (LCM), one pair of manual microlysimeters was installed next to each LCM. A third pair was installed at a point between the LCMs and a fourth pair above the midslope LCM. Sixteen overnight measurements were carried out within a 6-week period. The LCM could measure dew with an error of ±0.02 mm. The daily dew variation in the samples during the 16 overnight measurements ranged up to 0.2 mm on stable dune slopes but up to 0.4 mm on the playa. This difference is attributed to the playa’s high silt and clay content and salinity. Dew formation and accumulation were found to occur long before the soil-surface temperature reached the dewpoint temperature of the air. The cost of building this microlysimeter, excluding labor, is about $175 (U.S.).

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Peter W. Thorne, Kate M. Willett, Rob J. Allan, Stephan Bojinski, John R. Christy, Nigel Fox, Simon Gilbert, Ian Jolliffe, John J. Kennedy, Elizabeth Kent, Albert Klein Tank, Jay Lawrimore, David E. Parker, Nick Rayner, Adrian Simmons, Lianchun Song, Peter A. Stott, and Blair Trewin

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William J. Merryfield, Johanna Baehr, Lauriane Batté, Emily J. Becker, Amy H. Butler, Caio A. S. Coelho, Gokhan Danabasoglu, Paul A. Dirmeyer, Francisco J. Doblas-Reyes, Daniela I. V. Domeisen, Laura Ferranti, Tatiana Ilynia, Arun Kumar, Wolfgang A. Müller, Michel Rixen, Andrew W. Robertson, Doug M. Smith, Yuhei Takaya, Matthias Tuma, Frederic Vitart, Christopher J. White, Mariano S. Alvarez, Constantin Ardilouze, Hannah Attard, Cory Baggett, Magdalena A. Balmaseda, Asmerom F. Beraki, Partha S. Bhattacharjee, Roberto Bilbao, Felipe M. de Andrade, Michael J. DeFlorio, Leandro B. Díaz, Muhammad Azhar Ehsan, Georgios Fragkoulidis, Sam Grainger, Benjamin W. Green, Momme C. Hell, Johnna M. Infanti, Katharina Isensee, Takahito Kataoka, Ben P. Kirtman, Nicholas P. Klingaman, June-Yi Lee, Kirsten Mayer, Roseanna McKay, Jennifer V. Mecking, Douglas E. Miller, Nele Neddermann, Ching Ho Justin Ng, Albert Ossó, Klaus Pankatz, Simon Peatman, Kathy Pegion, Judith Perlwitz, G. Cristina Recalde-Coronel, Annika Reintges, Christoph Renkl, Balakrishnan Solaraju-Murali, Aaron Spring, Cristiana Stan, Y. Qiang Sun, Carly R. Tozer, Nicolas Vigaud, Steven Woolnough, and Stephen Yeager
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William J. Merryfield, Johanna Baehr, Lauriane Batté, Emily J. Becker, Amy H. Butler, Caio A. S. Coelho, Gokhan Danabasoglu, Paul A. Dirmeyer, Francisco J. Doblas-Reyes, Daniela I. V. Domeisen, Laura Ferranti, Tatiana Ilynia, Arun Kumar, Wolfgang A. Müller, Michel Rixen, Andrew W. Robertson, Doug M. Smith, Yuhei Takaya, Matthias Tuma, Frederic Vitart, Christopher J. White, Mariano S. Alvarez, Constantin Ardilouze, Hannah Attard, Cory Baggett, Magdalena A. Balmaseda, Asmerom F. Beraki, Partha S. Bhattacharjee, Roberto Bilbao, Felipe M. de Andrade, Michael J. DeFlorio, Leandro B. Díaz, Muhammad Azhar Ehsan, Georgios Fragkoulidis, Sam Grainger, Benjamin W. Green, Momme C. Hell, Johnna M. Infanti, Katharina Isensee, Takahito Kataoka, Ben P. Kirtman, Nicholas P. Klingaman, June-Yi Lee, Kirsten Mayer, Roseanna McKay, Jennifer V. Mecking, Douglas E. Miller, Nele Neddermann, Ching Ho Justin Ng, Albert Ossó, Klaus Pankatz, Simon Peatman, Kathy Pegion, Judith Perlwitz, G. Cristina Recalde-Coronel, Annika Reintges, Christoph Renkl, Balakrishnan Solaraju-Murali, Aaron Spring, Cristiana Stan, Y. Qiang Sun, Carly R. Tozer, Nicolas Vigaud, Steven Woolnough, and Stephen Yeager

Abstract

Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.

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