The first multimodel study to estimate the predictability of a boreal sudden stratospheric warming (SSW) is performed using five NWP systems. During the 2012/13 boreal winter, anomalous upward propagating planetary wave activity was observed toward the end of December, which was followed by a rapid deceleration of the westerly circulation around 2 January 2013, and on 7 January 2013 the zonal-mean zonal wind at 608N and 10 hPa reversed to easterly. This stratospheric dynamical activity was followed by an equatorward shift of the tropospheric jet stream and by a high pressure anomaly over the North Atlantic, which resulted in severe cold conditions in the United Kingdom and northern Europe. In most of the five models, the SSW event was predicted 10 days in advance. However, only some ensemble members in most of the models predicted weakening of westerly wind when the models were initialized 15 days in advance of the SSW. Further dynamical analysis of the SSW shows that this event was characterized by the anomalous planetary wavenumber-1 amplification followed by the anomalous wavenumber-2 amplification in the stratosphere, which resulted in a split vortex occurring between 6 and 8 January 2013. The models have some success in reproducing wavenumber-1 activity when initialized 15 days in advance, but they generally failed to produce the wavenumber-2 activity during the final days of the event. Detailed analysis shows that models have reasonably good skill in forecasting tropospheric blocking features that stimulate wavenumber-2 amplification in the troposphere, but they have limited skill in reproducing wavenumber-2 amplification in the stratosphere.

For the next generation of the World Area Forecast System (WAFS), the global Graphical Turbulence Guidance (G-GTG) has been developed using global numerical weather prediction (NWP) model outputs as an input to compute a set of turbulence diagnostics, identifying strong spatial gradients of meteorological variables associated with clear-air turbulence (CAT) and mountain-wave turbulence (MWT). The G-GTG provides an atmospheric turbulence intensity metric of energy dissipation rate (EDR) to the 1/3 power (m2/3 s–1), which is the International Civil Aviation Organization (ICAO) standard for aircraft reporting. Deterministic CAT and MWT EDR forecasts are derived from ensembles of calibrated multiple CAT and MWT diagnostics, respectively, with the final forecast provided by the gridpoint-by-gridpoint maximum of the CAT and MWT ensemble means. In addition, a probabilistic EDR forecast is produced by the percentage agreement of the individual CAT and MWT diagnostics that exceed a certain EDR threshold for turbulence (i.e., multidiagnostic ensemble). Objective evaluations of the G-GTG against global in situ EDR measurement data show that both deterministic and probabilistic G-GTG significantly improve the current WAFS CAT product, mainly because the G-GTG takes into account turbulence from various sources related to CAT and MWT. The probabilistic G-GTG forecast is more reliable at predicting light-or-greater (EDR > 0.15)- than moderate-or-greater (EDR > 0.22)-level turbulence, although it suffers from overforecasting. This will be improved in the future when we use this methodology with NWP ensembles and more observation data will be available for calibration. We expect that the new G-GTG forecasts will be beneficial to aviation users globally.

Carbonates record information regarding the timing, nature and conditions of the fluids circulating through asteroid parent bodies during aqueous alteration events. Determining carbonate abundances and their relationships with organic matter improves our understanding of the genesis of major carbonaceous components in chondritic materials. In this study, five CM2 carbonaceous chondrites (CM2.2 Nogoya, CM2.3 Jbilet Winselwan, CM2.5 Murchison, CM2 Santa Cruz, and CM2TII Wisconsin Range 91600) were studied with Raman spectroscopy. Carbonates were identified in these meteorite samples by the distinctive Raman band in the ~1100 cm-1 region, representing the symmetric stretching vibration mode (v 1) of the (CO 3) 2anion. Carbonates identified in the meteorite samples are all calcite, with the exception of a single dolomite grain in Nogoya. The v 1 positions of the CM calcites are 2−3 cm-1 higher than in pure calcite, which suggests that they contain significant impurity cations. Typical graphitic first-order D and G bands were identified in the meteorite matrix as well as in ~25% of the analyzed carbonate grains. From the Raman results, we postulate that the carbonates might not have formed under equilibrium conditions from a single fluid. The first

As the stratosphere is largely characterized by its ozone abundance, the quality of the ozone field is important for a realistic representation of the stratosphere in weather and climate models. While the stratosphere is directly affected by radiative heating from ozone photodissociation, ozone abundance might also impact the representation of the troposphere since the stratosphere and troposphere are dynamically linked. In this paper, we examine the potential benefits of using ozone data from the Earth Observing System (EOS) Microwave Limb Sounder (MLS) for medium‐extended range tropospheric forecasts in a current numerical weather prediction system. The global component of the Met Office Global and Regional Ensemble Prediction System is used, which is run at a resolution of N216 L85 with 24 ensemble members. We compare two scenarios of 31 day forecasts covering the same period, one with the current operational ozone climatology and the other with a monthly mean zonally averaged ozone field computed from the MLS data set. In the extreme case of the Arctic “ozone hole” of March 2011, our results show a general reduction in stratospheric forecast errors in the tropics and Southern Hemisphere as a result of the improved representation of ozone. However, even in such a scenario, where the MLS ozone field is much superior to that of the control, we find that tropospheric forecast errors in the medium‐extended range are dominated by the spread of ensemble members and no significant reduction in the root‐mean‐square forecast errors.