Description: Potential vorticity (PV) cutoffs are stratospheric air masses separated from the circumpolar stratospheric reservoir on an isentropic surface. They typically form via Rossby wave breaking and can strongly influence midlatitude weather; however, the processes governing their evolution are not fully understood. A detailed analysis of two exceptionally long-lived PV cutoffs over Europe is presented to identify the main dynamical and physical processes during their life-cycle. To this end, operational analyses from the European Centre for Medium Range Weather Forecasts (ECMWF) are used together with the cloud top height product from EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). A combination of Eulerian and Lagrangian diagnostics reveals a complex temporal evolution of the intensity and vertical structure of the two PV cutoffs. They diabatically decay or reappear on lower isentropes and, at the same time, intensify or become reabsorbed by the stratospheric reservoir on higher isentropes. This complex three-dimensional evolution is influenced by a combination of direct and indirect diabatic effects. Convective latent heating, long-wave radiative cooling, and turbulent entrainment of overshooting clouds can all directly modify PV of the cutoff air parcels (direct diabatic effects). In addition, if the cutoff is located in a region with sufficient baroclinicity and low-level moisture, it can contribute to large-scale diabatic ascent, similar to warm conveyor belts in classical extratropical cyclones. The divergent wind and the anticyclonic circulation associated with the low-PV outflow in the upper troposphere can lead to deformation and filamentation of the PV cutoff (indirect diabatic effects). This study extends our understanding of PV cutoffs by (i) emphasising their intricate vertical structure and temporal evolution, (ii) revealing the complex interplay of diabatic processes and how they contribute to the decay and intensification of cutoffs, and (iii) indicating the challenge in correctly forecasting these dynamically important flow features.

Description: Sea surface temperatures form a vital part of global mean surface temperature records. Historical observation methods have changed substantially over time from buckets to engine room intake sensors, hull sensors and drifting buoys, rendering their use for climatological studies problematic. There are substantial uncertainties in the relative biases of different observations which may impact the global temperature record. Island and coastal weather stations can be compared to coastal sea surface temperature observations to obtain an assessment of changes in bias over time. The process is made more challenging by differences in the rate of warming between air temperatures and sea surface temperatures, and differences across coastal boundaries. A preliminary sea surface temperature reconstruction homogenized using coastal weather station data suggests significant changes to the sea surface temperature record, although there are substantial uncertainties of which only some can be quantified. A large warm excursion in versions 4 and 5 of the NOAA Extended Reconstructed Sea Surface Temperature during World War 2 is rejected, as is a cool excursion around 1910 present in all existing records. The mid-century plateau is cooler than in existing reconstructions.

Description: State-of-the-art climate models rely on bulk formulae arising from the Monin-Obukhov semi-empirical theory to estimate turbulent air-sea fluxes. The mathematical structure of those formulae implies several difficulties when trying to study the numerical properties of coupling algorithms used for practical applications. This paper introduces a methodology for building physically realistic approximations of existing bulk formulae that would also satisfy suitable mathematical properties (explicit character, regularity, differentiability). This is achieved by applying the Sobol’ method to compute sensitivity indices in order to reduce the number of inputs and derive a simple metamodel for the parameterization of turbulent air-sea fluxes. Numerical results show excellent agreement between our approximations and the standard bulk formulae. In particular, single column simulations using the TOGA-Coare experiment within the LMDZ atmospheric model show negligible changes in numerical results.

Description: Observations from aircraft are an important element of the global observing network. A promising new observation source, deriving wind and temperature measurements from air traffic management data, has previously been reported on by a small number of groups. This paper further investigates the error characteristics by comparing a year's worth of in situ observed winds and temperatures from a commercial British Airways Boeing 747 (B747) with the derived Mode-Selective (Mode-S) Enhanced Surveillance (EHS) observations from the Met Office network of Mode-S receivers. It is shown that whilst the winds and high altitude temperatures are of good quality they show error profiles with altitude that are different for ascent and descent. The data shows that the situation of the aircraft is critical to understand the biases; this is dependent on the aircraft, operator and airport, making corrections infeasible. Further understanding is gained by an intercomparison flight with the UK Facility for Airborne Atmospheric Measurement (FAAM) BAe 146 aircraft. This showed a good comparison with Mode-S EHS winds, with a RMS difference between the FAAM data and B747 Mode-S EHS data of 1.5 ms −1 and 0.9 ms −1 for the u and v components respectively; Comparing the FAAM data and B747 flight data recorder (FDR) provided RMS differences of 0.6 ms −1 and 1.4 ms −1 respectively. This suggests that the data quality from Mode-S EHS is similar to that which can be achieved from a commercial aircraft. The temperature RMS differences were found to be 1.6 K and 0.5 K when the FAAM data is compared to the Mode-S EHS data and FDR data from the B747 respectively, suggesting that the temperature Mode-S EHS data are of an inferior quality.

Description: The mechanism for the upscale growth of small errors through the atmospheric mesoscales has not been conclusively identified, but geostrophic adjustment in response to diabatically generated motions such as cumulus convection is a plausible candidate. In a companion paper, an analytic solution of the linearised, hydrostatic Boussinesq equations to an impulsive, localised heat source that mimics the effect of latent heating within a convective cloud on an unperturbed, rotating environment is found. Three characteristics of the solution are shown to be potentially useful for identifying the geostrophic adjustment process in numerical simulations. The predictions relate to the horizontal gravity wave speed, the Rossby number and the quantitative relationship between a precipitation anomaly and the balanced flow response (i.e. large-scale vorticity). Here these predictions are tested in the framework of error growth experiments in idealised numerical simulations of a convective cloud field. Three different rotation rates are employed in order to identify the geostrophic adjustment mechanism and allow a quantitative comparison with the predictions of the analytic model. The gravity wave speed estimated from the simulations resembles the theoretical value and is independent of the Coriolis parameter, as predicted. The Rossby number resulting from the proposed scaling of temporal and spatial coordinates features a unique shape and the vorticity diagnostic agrees quantitatively with the analytical predictions. Based on these findings it is put forward that upscale error growth through the atmospheric mesoscales is governed by the geostrophic adjustment process.

Description: A new generation of L-band sensors, such as ESA's Soil Moisture Ocean Salinity (SMOS) mission, have the capability to provide information on the ocean-surface wind speed under high wind and rain conditions. In this study we evaluate the use of SMOS wind speeds within Met Office numerical weather prediction (NWP). Observation minus model background (O-B) departure statistics are used to investigate SMOS error characteristics, quality flags, and develop a quality control method. Observation errors and spatial correlation distances are estimated using a statistical method. Observing system experiments are performed to diagnose the impact of SMOS on NWP forecasts and analyses, including tropical cyclone (TC) predictions. The quality of SMOS retrievals appears reduced in the presence of sea ice, strong river plumes, and radio-frequency interference (RFI) contamination. SMOS wind retrievals have reduced sensitivity at low-moderate winds speeds. Above 15 ms -1 , SMOS winds tend to be faster than the model and have higher O-B variance compared to scatterometer winds from ASCAT. Above 30 m/s RMS errors from SMOS are smaller than ASCAT. The impact of SMOS on TC predictions is sensitive to the use of the Met Office TC Central Pressure Initialisation Scheme (TCCPIS) which is confirmed to have a large, beneficial impact on intensity predictions. The assimilation of SMOS results in a small increase in TC intensity leading to a reduction in pressure/wind errors in the analysis and short-range forecasts, but cannot replicate the impact from the TCCPIS. The spatial resolution of SMOS is a clear limitation for analysing TC structure. In the case of Hurricane Kilo, the analysed and short-range forecast central pressures are closer to best-track when the storm radius is large and the eye is resolved. The challenge is to extract the useful information on intensity whilst preserving storm structure.

Description: Eurasia is one of the most sensitive areas to climate change in the world. Its western and eastern coasts are very likely to exhibit different temperature and precipitation variations in response to the global climate change. By using precipitation (PRCP), maximum temperature ( T max ), minimum temperature ( T min ), and daily temperature range (DTR) data from 333 meteorological stations in Western (WE) and Eastern Eurasia (EE), we quantitatively compared spatial-temporal changes on both the seasonal and annual scales from 1961 to 2012. Results showed that PRCP mainly exhibited increasing trends in northern WE and decreasing trends in southern WE, whereas PRCP in EE recorded an increase-decrease-increase trend from high to low latitudes. The increase of annual PRCP in WE was higher than that in EE. On the seasonal scale, the PRCP in WE recorded an opposite trend from EE. T max and T min significantly increased for almost all stations on the annual and seasonal scales, especially during the winter. Nevertheless, the increase of T min was higher than that of T max in EE, resulting in a decreased DTR on both the seasonal and annual scales. An adverse trend of DTR was detected in WE. Our results concluded that AO was the major large-scale atmospheric circulation affecting the trends of PRCP (negative correlation) and temperature (positive correlation) over WE and EE, and it might play an important role in future climate change.

Description: In this study, high-resolution projections of temperature and precipitation changes over Canada were developed through the PRECIS model under Representative Concentration Pathways (RCPs). In detail, the PRECIS model was employed to conduct simulations for the historical period over the entirety of Canada, driven by the boundary conditions from both ERA-Interim (1979 -2011) and HadGEM2-ES (1959 - 2005). The performance of PRECIS simulations in reproducing historical climatology of Canada was then validated through comparison with observed temperature and precipitation over the baseline period (1986 - 2005). The boundary conditions from HadGEM2-ES under RCP4.5 and RCP8.5 will be used to drive PRECIS for simulating climatic variables over Canada for the period of 2005 - 2099. Future climate projections of temperature and precipitation as well as their extreme indices over two time slices (i.e., 2046 - 2065 and 2076 - 2095) were extracted and analyzed. The results could help investigate how the regional climate over Canada will respond to global warming as well as the spatiotemporal characteristics of plausible climate changes in the Canadian context. The validation results demonstrate that the PRECIS model is effective in reproducing the historical climatological patterns of annual mean temperature and total precipitation across Canada. Projections of temperature and precipitation for the two future periods indicate that there will be an apparent increasing pattern over Canada. The projected changes derived in this study can provide decision-makers with valuable information to evaluate possible impacts on economic, social, and environmental sectors at regional and local scales.

Description: Atmospheric natural hazards pose a risk to people, aircraft and infrastructure. Automated algorithms can detect these hazards from satellite imagery so that the relevant advice can be issued. The transparency and adaptability of these automated algorithms is important to cater to the needs of the end user, who should be able to readily interpret the hazard warning. This means avoiding heuristic techniques. Decision theory is a statistical tool that transparently considers the risk of false positives and negatives when detecting the hazard. By assigning losses to incorrect actions, ownership of the hazard warning is shared between the scientists and risk managers. These losses are readily adaptable depending on the perceived threat of the hazard. This study demonstrates how decision theory can be applied to the detection of atmospheric natural hazards using the example of volcanic ash during an ongoing eruption. The only observations are the difference in brightness temperature between two channels on the SEVIRI sensor. We apply the method to two volcanic eruptions: the 2010 eruption of Eyjafjallajökull, Iceland, and the 2011 eruption of Puyehue-Cordón Caulle, Chile. The simple probabilistic method appears to work well and is able to distinguish volcanic ash from desert dust, which is a common false positive for volcanic ash. As is made clear, decision theory is a tool for decision support, providing transparency and adaptability, but it still requires careful input from scientists and risk managers. Effectively it provides a space where these groups of experts can meet and convert their shared understanding of a hazard into a choice of action.

Description: Ray tracing techniques have been used to investigate numerical effects on the propagation of acoustic and gravity waves in a non-hydrostatic dynamical core discretised using an Arakawa C-grid horizontal staggering of variables and a Charney-Phillips vertical staggering of variables with a semi-implicit timestepping scheme. The space discretisation places limits on resolvable wavenumbers, and redirects the group velocity and the propagation of wave energy towards the vertical. The time discretisation slows the wave propagation while maintaining the group velocity direction. Wave amplitudes grow exponentially with height due to the decrease in the background density, which can cause instabilities in whole-atmosphere models. Although molecular viscosity effectively damps the exponential growth of waves above about 150 km, additional numerical damping might be needed to prevent instabilities in the lowermost thermosphere. These results are relevant to the Met Office Unified Model, and provide insight into how the stability of the model may be improved as the model's upper boundary is raised into the thermosphere.