Search Results

You are looking at 1 - 3 of 3 items for

  • Author or Editor: G. F. Cunningham x
  • All content x
Clear All Modify Search
Carol S. Hsu, Morton G. Wurtele, Glenn F. Cunningham, and Peter M. Woiceshyn

Abstract

A series of 6-h, synoptic, gridded, global surface wind fields with a resolution of 100 km was generated using the dataset of dealiased Seasat satellite scatterometer (SASS) winds produced as described by Peteherych et al. This paper is an account of the construction of surface pressure fields from these SASS synoptic wind fields only, as carried out by different methods, and the comparison of these pressure fields with National Centers for Environmental Prediction (NCEP) analyses, with the pressure fields of the European Centre for Medium-Range Weather Forecasts (ECMWF), and with the special analyses of the Gulf of Alaska Experiment.

One of the methods we use to derive the pressure fields utilizes a two-layer planetary boundary layer (PBL) model iterative scheme that relates the geostrophic wind vector to the surface wind vector, surface roughness, humidity, diabatic and baroclinic effects, and secondary flow. A second method involves the assumption of zero two-dimensional divergence, leading to a Poisson equation (the “balance equation”) in pressure, with the wind field serving as a forcing function.

The pressure fields computed from the SASS winds using a two-layer PBL model closely approximate the NCEP and ECMWF fields. In some cases, the PBL-model-derived pressure fields can detect mesoscale features not resolved in either the NCEP or ECMWF analyses. Balanced pressure fields are much smoother and less well resolved than the PBL-model-derived or NCEP fields. Systematic differences between balanced pressure fields and the PBL-model-derived fields are attributed to the neglect of horizontal divergence in the balance equation. The effect of stratification is found to produce a larger impact than secondary flow or thermal wind effects on the derived pressure fields. Inclusion of secondary flow tends to weaken both low and high pressure centers, whereas inclusion of stratification intensifies low centers and weakens high centers.

Full access
R. Kwok, T. Markus, J. Morison, S. P. Palm, T. A. Neumann, K. M. Brunt, W. B. Cook, D. W. Hancock, and G. F. Cunningham

Abstract

The sole instrument on the upcoming Ice, Cloud, and Land Elevation Satellite (ICESat-2) altimetry mission is a micropulse lidar that measures the time of flight of individual photons from laser pulses transmitted at 532 nm. Prior to launch, the Multiple Altimeter Beam Experimental Lidar (MABEL) serves as an airborne implementation for testing and development. This paper provides a first examination of MABEL data acquired on two flights over sea ice in April 2012: one north of the Arctic coast of Greenland and the other in the east Greenland Sea. The phenomenology of photon distributions in the sea ice returns is investigated. An approach to locate the surface and estimate its elevation in the distributions is described, and its achievable precision is assessed. Retrieved surface elevations over relatively flat leads in the ice cover suggest that precisions of several centimeters are attainable. Restricting the width of the elevation window used in the surface analysis can mitigate potential biases in the elevation estimates due to subsurface returns at 532 nm. Comparisons of nearly coincident elevation profiles from MABEL with those acquired by an analog lidar show good agreement. Discrimination of ice and open water, a crucial step in the determination of sea ice freeboard and the estimation of ice thickness, is facilitated by contrasts in the observed signal–background photon statistics. Future flight paths will sample a broader range of seasonal ice conditions for further evaluation of the year-round profiling capabilities and limitations of the MABEL instrument.

Full access
M. Susan Lozier, Sheldon Bacon, Amy S. Bower, Stuart A. Cunningham, M. Femke de Jong, Laura de Steur, Brad deYoung, Jürgen Fischer, Stefan F. Gary, Blair J. W. Greenan, Patrick Heimbach, Naomi P. Holliday, Loïc Houpert, Mark E. Inall, William E. Johns, Helen L. Johnson, Johannes Karstensen, Feili Li, Xiaopei Lin, Neill Mackay, David P. Marshall, Herlé Mercier, Paul G. Myers, Robert S. Pickart, Helen R. Pillar, Fiammetta Straneo, Virginie Thierry, Robert A. Weller, Richard G. Williams, Chris Wilson, Jiayan Yang, Jian Zhao, and Jan D. Zika

Abstract

For decades oceanographers have understood the Atlantic meridional overturning circulation (AMOC) to be primarily driven by changes in the production of deep-water formation in the subpolar and subarctic North Atlantic. Indeed, current Intergovernmental Panel on Climate Change (IPCC) projections of an AMOC slowdown in the twenty-first century based on climate models are attributed to the inhibition of deep convection in the North Atlantic. However, observational evidence for this linkage has been elusive: there has been no clear demonstration of AMOC variability in response to changes in deep-water formation. The motivation for understanding this linkage is compelling, since the overturning circulation has been shown to sequester heat and anthropogenic carbon in the deep ocean. Furthermore, AMOC variability is expected to impact this sequestration as well as have consequences for regional and global climates through its effect on the poleward transport of warm water. Motivated by the need for a mechanistic understanding of the AMOC, an international community has assembled an observing system, Overturning in the Subpolar North Atlantic Program (OSNAP), to provide a continuous record of the transbasin fluxes of heat, mass, and freshwater, and to link that record to convective activity and water mass transformation at high latitudes. OSNAP, in conjunction with the Rapid Climate Change–Meridional Overturning Circulation and Heatflux Array (RAPID–MOCHA) at 26°N and other observational elements, will provide a comprehensive measure of the three-dimensional AMOC and an understanding of what drives its variability. The OSNAP observing system was fully deployed in the summer of 2014, and the first OSNAP data products are expected in the fall of 2017.

Full access