Surface-enhanced Raman scattering (SERS) is a powerful spectroscopy technique that can provide non-destructive and ultra-sensitive characterization down to single molecular level, comparable to single-molecule fluorescence spectroscopy. However, generally substrates based on metals such as Ag, Au and Cu, either with roughened surfaces or in the form of nanoparticles, are required to realise a substantial SERS effect, and this has severely limited the breadth of practical applications of SERS. A number of approaches have extended the technique to non-traditional substrates, most notably tip-enhanced Raman spectroscopy (TERS) where the probed substance (molecule or material surface) can be on a generic substrate and where a nanoscale gold tip above the substrate acts as the Raman signal amplifier. The drawback is that the total Raman scattering signal from the tip area is rather weak, thus limiting TERS studies to molecules with large Raman cross-sections. Here, we report an approach, which we name shell-isolated nanoparticle-enhanced Raman spectroscopy, in which the Raman signal amplification is provided by gold nanoparticles with an ultrathin silica or alumina shell. A monolayer of such nanoparticles is spread as 'smart dust' over the surface that is to be probed. The ultrathin coating keeps the nanoparticles from agglomerating, separates them from direct contact with the probed material and allows the nanoparticles to conform to different contours of substrates. High-quality Raman spectra were obtained on various molecules adsorbed at Pt and Au single-crystal surfaces and from Si surfaces with hydrogen monolayers. These measurements and our studies on yeast cells and citrus fruits with pesticide residues illustrate that our method significantly expands the flexibility of SERS for useful applications in the materials and life sciences, as well as for the inspection of food safety, drugs, explosives and environment pollutants.

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A new version of the Global Ensemble Forecast System (GEFS, v11) is tested and compared with the operational version (v10) in a 2-yr parallel run. The breeding-based scheme with ensemble transformation and rescaling (ETR) used in the operational GEFS is replaced by the ensemble Kalman filter (EnKF) to generate initial ensemble perturbations. The global medium-range forecast model and the Global Forecast System (GFS) analysis used as the initial conditions are upgraded to the GFS 2015 implementation version. The horizontal resolution of GEFS increases from Eulerian T254 (~52 km) for the first 8 days of the forecast and T190 (~70 km) for the second 8 days to semi-Lagrangian T574 (~34 km) and T382 (~52 km), respectively. The sigma pressure hybrid vertical layers increase from 42 to 64 levels. The verification of geopotential height, temperature, and wind fields at selected levels shows that the new GEFS significantly outperforms the operational GEFS up to days 8–10 except for an increased warm bias over land in the extratropics. It is also found that the parallel system has better reliability in the short-range probability forecasts of precipitation during warm seasons, but no clear improvement in cold seasons. There is a significant degradation of TC track forecasts at days 6–7 during the 2012–14 TC seasons over the Atlantic and eastern Pacific. This degradation is most likely a sampling issue from a low number of TCs during these three TC seasons. The results for an extended verification period (2011–14) and the recent two hurricane seasons (2015 and 2016) are generally positive. The new GEFS became operational at NCEP on 2 December 2015.

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To understand the mechanisms responsible for the secondary eyewall replacement cycles and associated intensity changes in intense tropical cyclones (TCs), two numerical experiments are conducted in this study with the Weather Research and Forecasting (WRF) model. In the experiments, identical initial conditions and model parameters are utilized except that the concentration of ice particles is enhanced in the sensitivity run. With enhanced ice concentrations, it is found that the secondary eyewall forms at an increased radius, the time required for eyewall replacement is extended, and the intensity fluctuation is relatively large. The enhanced concentrations of ice particles at the upper tropospheric outflow layer produces a noticeable subsidence region (moat) surrounding the primary eyewall. The presence of the moat forces the secondary eyewall to form at a relatively large radius. The axisymmetric equivalent potential temperature budget analysis reveals that the demise of the inner eyewall is primarily due to the interception of the boundary layer inflow supply of entropy by the outer convective ring, whereas the advection of low entropy air from the middle levels to the boundary inflow layers in the moat is not essential. The interception process becomes inefficient when the secondary eyewall is at a large radius; hence, the corresponding eyewall replacement is slow. After the demise of the inner eyewall, the outer eyewall has to maintain a warm core not only in the previous eye, but also in the moat. The presence of low equivalent potential temperature air in the moat results in the significant weakening of storm intensity. The results found here suggest that monitoring the features of the moat and the outer eyewall region can provide a clue for the prediction of TC intensity change associated with eyewall replacement.