Showing papers in "Quarterly Journal of the Royal Meteorological Society in 2014"

Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends

Abstract: Incomplete global coverage is a potential source of bias in global temperature reconstructions if the unsampled regions are not uniformly distributed over the planet's surface. The widely used Hadley Centre–Climatic Reseach Unit Version 4 (HadCRUT4) dataset covers on average about 84% of the globe over recent decades, with the unsampled regions being concentrated at the poles and over Africa. Three existing reconstructions with near-global coverage are examined, each suggesting that HadCRUT4 is subject to bias due to its treatment of unobserved regions. Two alternative approaches for reconstructing global temperatures are explored, one based on an optimal interpolation algorithm and the other a hybrid method incorporating additional information from the satellite temperature record. The methods are validated on the basis of their skill at reconstructing omitted sets of observations. Both methods provide results superior to excluding the unsampled regions, with the hybrid method showing particular skill around the regions where no observations are available. Temperature trends are compared for the hybrid global temperature reconstruction and the raw HadCRUT4 data. The widely quoted trend since 1997 in the hybrid global reconstruction is two and a half times greater than the corresponding trend in the coverage-biased HadCRUT4 data. Coverage bias causes a cool bias in recent temperatures relative to the late 1990s, which increases from around 1998 to the present. Trends starting in 1997 or 1998 are particularly biased with respect to the global trend. The issue is exacerbated by the strong El Nino event of 1997–1998, which also tends to suppress trends starting during those years.

An inherently mass‐conserving semi‐implicit semi‐Lagrangian discretization of the deep‐atmosphere global non‐hydrostatic equations

Abstract: Following previous work on an inherently mass-conserving semi-implicit (SI) semi-Lagrangian (SL) discretization of the two-dimensional (2D) shallow-water equations and 2D vertical slice equations, that approach is here extended to the 3D deep-atmosphere, non-hydrostatic global equations. As with the reduced-dimension versions of this model, an advantage of the approach is that it preserves the same basic structure as a standard, non-mass-conserving, SISL version of the model. Additionally, the model is simply switchable to hydrostatic and/or shallow-atmosphere forms. It is also designed to allow simple switching between various geometries (Cartesian, spherical, spheroidal). The resulting mass-conserving model is applied to a standard set of test problems for such models in spherical geometry and compared with results from the standard SISL version of the model.

Evolution of ECMWF sub‐seasonal forecast skill scores

Abstract: Sub-seasonal forecasts have been routinely produced at ECMWF since 2002 with reforecasts produced ‘on the fly’ to calibrate the real-time sub-seasonal forecasts. In this study, the skill of the reforecasts from April 2002 to March 2012 and covering a common set of years (1995 to 2001) has been evaluated. Results indicate that the skill of the ECMWF reforecasts to predict the Madden–Julian Oscillation (MJO) has improved significantly since 2002, with an average gain of about 1 day of prediction skill per year. The amplitude of the MJO has also become more realistic, although the model still tends to produce MJOs which are weaker than in the ECMWF re-analysis. As a consequence, the ability of the ECMWF model to simulate realistic MJO teleconnections over the Northern and Southern Extratropics has improved dramatically over the 10-year period. Forecast skill scores have also improved in the Extratropics. For instance, weekly mean forecasts of the North Atlantic Oscillation Index are more skilful in recent years than 10 years ago. A large part of this improvement seems to be linked to the improvements in the representation of the MJO. Skill to predict 2 m temperature anomalies over the Northern Extratropics has also improved almost continuously since 2002. Changes in the horizontal and vertical resolutions of the atmospheric model had only a small impact on the skill scores, suggesting that most of the improvements in the ECMWF sub-seasonal forecasts were due to changes in model physics which were primarily designed to improve the model climate and medium-range forecasts. The impact of changes in the data assimilation system and in the observing data has not been considered in this study, since all the reforecasts used for this study were initialized from the same re-analysis over a common set of years.

Propagation of the Madden-Julian Oscillation through the Maritime Continent and scale interaction with the diurnal cycle of precipitation

Abstract: The convectively active part of the Madden-Julian Oscillation (MJO) propagates eastward through the warm pool, from the Indian Ocean through the Maritime Continent (the Indonesian archipelago) to the western Pacific. The Maritime Continent's complex topography means the exact nature of the MJO propagation through this region is unclear. Model simulations of the MJO are often poor over the region, leading to local errors in latent heat release and global errors in medium-range weather prediction and climate simulation. Using 14 northern winters of TRMM satellite data it is shown that, where the mean diurnal cycle of precipitation is strong, 80% of the MJO precipitation signal in the Maritime Continent is accounted for by changes in the amplitude of the diurnal cycle. Additionally, the relationship between outgoing long-wave radiation (OLR) and precipitation is weakened here, such that OLR is no longer a reliable proxy for precipitation. The canonical view of the MJO as the smooth eastward propagation of a large-scale precipitation envelope also breaks down over the islands of the Maritime Continent. Instead, a vanguard of precipitation (anomalies of 2.5 mm day^-1 over 10^6 km^2) jumps ahead of the main body by approximately 6 days or 2000 km. Hence, there can be enhanced precipitation over Sumatra, Borneo or New Guinea when the large-scale MJO envelope over the surrounding ocean is one of suppressed precipitation. This behaviour can be accommodated into existing MJO theories. Frictional and topographic moisture convergence and relatively clear skies ahead of the main convective envelope combine with the low thermal inertia of the islands, to allow a rapid response in the diurnal cycle which rectifies onto the lower-frequency MJO. Hence, accurate representations of the diurnal cycle and its scale interaction appear to be necessary for models to simulate the MJO successfully.

High-latitude influence of the quasi-biennial oscillation

Abstract: The interannual variability of the stratospheric winter polar vortex is correlated with the phase of the quasi-biennial oscillation (QBO) of tropical stratospheric winds. This dynamical coupling between high and low latitudes, often referred to as the Holton–Tan effect, has been the subject of numerous observational and modelling studies, yet important questions regarding its mechanism remain unanswered. In particular it remains unclear which vertical levels of the QBO exert the strongest influence on the winter polar vortex, and how QBO–vortex coupling interacts with the effects of other sources of atmospheric interannual variability such as the 11-year solar cycle or the El Nino Southern Oscillation. As stratosphere-resolving general circulation models begin to resolve the QBO and represent its teleconnections with other parts of the climate system, it seems timely to summarize what is currently known about the QBO’s high-latitude influence. In this review article, we offer a synthesis of the modelling and observational analyses of QBO–vortex coupling that have appeared in the literature, and update the observational record.

Estimating low‐frequency variability and trends in atmospheric temperature using ERA‐Interim

Abstract: Low-frequency variability and trends in temperature from 1979 to 2012 are examined. Observational improvements are noted and near-surface behaviour of the ECMWF ERA-Interim reanalysis is reviewed. Attention is then focussed on how closely ERA-Interim fits the upper-air data it assimilates, the bias adjustments it infers for satellite data, and its agreement with the ERA-40, MERRA and JRA-55 reanalyses and with model simulations. Global-mean fits to independently homogenised radiosonde temperatures and variationally adjusted satellite brightness temperatures are mainly within 0.1 K in the troposphere, with some degradation over time from assimilating varying amounts of aircraft and rain-affected microwave-radiance data, and from a change in source of sea-surface-temperature analysis. Lower-tropospheric warming appears to be somewhat underestimated. Temperature variations in the tropical upper troposphere correlate well with those at the surface, but amplitude is more than doubled, in agreement with modelling. Specific humidity varies in concert; relative humidity is largely uniform, but dips during El Nino events. Agreement with the other reanalyses is particularly close in the lower stratosphere, where radiance data and the background model constrain cooling to be slightly slower than in the homogenised radiosonde data. Perturbations to global-mean temperatures from underestimating warming following the El Chichon and Pinatubo volcanic eruptions and from assimilating recent GPSRO data are at most 0.2 K, less than 20% of the net change since 1979 at 50 hPa. Middle-stratospheric variations are more uncertain. Recent cooling appears to be underestimated by assimilating increasing amounts of unadjusted radiosonde data, but results do not support a recent reprocessing of earlier sounding data that suggests stronger middle-stratospheric cooling than previously indicated. Strong analysed upper-stratospheric cooling agrees quite well with model simulations if occasional jumps due to unadjusted bias changes in high-sounding satellite data are discounted. Producing ERA-Interim in two separate streams caused only minor discontinuities where streams join at the start of 1989.

Impacts of the EA and SCA patterns on the European twentieth century NAO–winter climate relationship

Abstract: Much of the twentieth century multidecadal variability in the relationship between North Atlantic Oscillation (NAO) and winter climate over the North Atlantic–European sector can be linked to the combined effects of the NAO and either the East Atlantic pattern (EA) or the Scandinavian pattern (SCA). Our study documents how different NAO–EA and NAO–SCA combinations influence winter climatic conditions (temperature and precipitation) as a consequence of NAO dipole migrations. Using teleconnectivity maps, we find that the zero-correlated line of the NAO–winter-climate relationship migrates southwards when the EA is in the opposite phase to the NAO, related to a southwestwards migration of the NAO dipole under these conditions. Similarly, a clockwise movement of the NAO–winter-climate correlated areas occurs when the phase of the SCA is opposite to that of the NAO, reflecting a clockwise movement of the NAO dipole under these conditions. Our study provides new insights into the causes of spatial and temporal nonstationarity in the climate–NAO relationships, particularly with respect to winter precipitation. Furthermore, interannual variability in the north–south winter precipitation gradient in the UK appears to reflect the migration of the NAO dipole linked to linear combinations of the NAO and the EA. The study also has important implications for studies of the role of the NAO in modulating the wind energy resource of the UK and Ireland, as well as for the selection of locations for terrestrial proxy archive reconstruction of past states of the NAO.

An iterative ensemble Kalman smoother

Abstract: The iterative ensemble Kalman filter (IEnKF) was recently proposed in order to improve the performance of ensemble Kalman filtering with strongly nonlinear geophysical models. The IEnKF can be used as a lag-one smoother and extended to a fixed-lag smoother: the iterative ensemble Kalman smoother (IEnKS). The IEnKS is an ensemble variational method. It does not require the use of the tangent linear of the evolution and observation models, nor the adjoint of these models: the required sensitivities (gradient and Hessian) are obtained from the ensemble. Looking for optimal performance, out of the many possible extensions we consider a quasi-static algorithm. The IEnKS is explored for the Lorenz '95 model and for a two-dimensional turbulence model. As the logical extension of the IEnKF, the IEnKS significantly outperforms standard Kalman filters and smoothers in strongly nonlinear regimes. In mildly nonlinear regimes (typically synoptic-scale meteorology), its filtering performance is marginally but clearly better than the standard ensemble Kalman filter and it keeps improving as the length of the temporal data assimilation window is increased. For long windows, its smoothing performance outranks the standard smoothers very significantly, a result that is believed to stem from the variational but flow-dependent nature of the algorithm. For very long windows, the use of a multiple data assimilation variant of the scheme, where observations are assimilated several times, is advocated. This paves the way for finer reanalysis, freed from the static prior assumption of 4D-Var but also partially freed from the Gaussian assumptions that usually impede standard ensemble Kalman filtering and smoothing.

Probabilistic quantitative precipitation forecasting using Ensemble Model Output Statistics

Abstract: Statistical post-processing of dynamical forecast ensembles is an essential component of weather forecasting. In this article, we present a post-processing method which generates full predictive probability distributions for precipitation accumulations based on ensemble model output statistics (EMOS). We model precipitation amounts by a generalized extreme value distribution which is left-censored at zero. This distribution permits modelling precipitation on the original scale without prior transformation of the data. A closed form expression for its continuous ranked probability score can be derived and permits computationally efficient model fitting. We discuss an extension of our approach which incorporates further statistics characterizing the spatial variability of precipitation amounts in the vicinity of the location of interest. The proposed EMOS method is applied to daily 18 h forecasts of 6 h accumulated precipitation over Germany in 2011 using the COSMO-DE ensemble prediction system operated by the German Meteorological Service. It yields calibrated and sharp predictive distributions and compares favourably with extended logistic regression and Bayesian model averaging which are state-of-the-art approaches for precipitation post-processing. The incorporation of neighbourhood information further improves predictive performance and turns out to be a useful strategy to account for displacement errors of the dynamical forecasts in a probabilistic forecasting framework.

Climate system response to stratospheric ozone depletion and recovery

Abstract: We review what is presently known about the climate system response to stratospheric ozone depletion and its projected recovery, focusing on the responses of the atmosphere, ocean and cryosphere. Compared with well-mixed greenhouse gases (GHGs), the radiative forcing of climate due to observed stratospheric ozone loss is very small: in spite of this, recent trends in stratospheric ozone have caused profound changes in the Southern Hemisphere (SH) climate system, primarily by altering the tropospheric midlatitude jet, which is commonly described as a change in the Southern Annular Mode. Ozone depletion in the late twentieth century was the primary driver of the observed poleward shift of the jet during summer, which has been linked to changes in tropospheric and surface temperatures, clouds and cloud radiative effects, and precipitation at both middle and low latitudes. It is emphasized, however, that not all aspects of the SH climate response to stratospheric ozone forcing can be understood in terms of changes in the midlatitude jet. The response of the Southern Ocean and sea ice to ozone depletion is currently a matter of debate. For the former, the debate is centred on the role of ocean eddies in possibly opposing wind-driven changes in the mean circulation. For the latter, the issue is reconciling the observed expansion of Antarctic sea-ice extent during the satellite era with robust modelling evidence that the ice should melt as a result of stratospheric ozone depletion (and increases in GHGs). Despite lingering uncertainties, it has become clear that ozone depletion has been instrumental in driving SH climate change in recent decades. Similarly, ozone recovery will figure prominently in future climate change, with its impacts expected to largely cancel the impacts of increasing GHGs during the next half-century.

Accounting for correlated error in the assimilation of high‐resolution sounder data

Abstract: Until January 2013, data from the high-resolution sounder IASI were assimilated with a diagonal observation-error covariance matrix within the Met Office 4D-Var assimilation scheme, assuming no correlation between channels. The errors were inflated to account indirectly for known inter-channel error correlations. This is sub-optimal as it artificially down-weights observations from these instruments. The true nature of these correlations for IASI are estimated here using data from the Met Office 4D-Var assimilation scheme and a posteriori diagnostics based on analysis and background departures. The diagnosed matrices are symmetrised and reconditioned, to make them suitable for use in the operational assimilation scheme. These matrices have been tested in full assimilation experiments. The results of these experiments show that using the new matrices improves forecast accuracy due to more weight in the assimilation being given to the IASI observations, particularly those from water-vapour-sensitive channels.

Modelling the diurnal cycle of tropical convection across the ‘grey zone’

Abstract: We present the results of simulations carried out with the Met Office Unified Model at 12, 4 and 1.5 km resolution for a large region centred on West Africa using several different representations of the convection processes. These span a range of resolutions from much coarser than the size of the convection processes to cloud-system-resolving and thus encompass the intermediate ‘grey zone’. The diurnal cycle in the extent of convective regions in the models is tested against observations from the Geostationary Earth Radiation Budget instrument on Meteosat-8. By this measure, the two best-performing simulations are a 12 km model without convective parametrization, using Smagorinsky-style subgrid-scale mixing in all three dimensions, and a 1.5 km simulation with two-dimensional Smagorinsky mixing. Of these, the 12 km model produces a better match to the magnitude of the total cloud fraction but the 1.5 km one results in better timing for its peak value. The results suggest that the previously reported improvement in the representation of the diurnal cycle of convective organization in the 4 km model compared with the standard 12 km configuration is principally a result of the convection scheme employed rather than the improved resolution per se. The details of this result and implications for high-resolution model simulations are discussed.

The impact of the AMO on the West African monsoon annual cycle

Abstract: A combination of observations and re-analysis was used to investigate the mechanisms of the connection between the Atlantic Multidecadal Oscillation (AMO) and Sahel rainfall. A composite technique based on the AMO index was used to identify differences between warm and cold phases of the AMO. A significant summer rainfall increase over the Sahel during warm phases of the AMO was observed, with large increases during the typical monsoon onset period in June. In spring of warm phases of the AMO prior to monsoon onset, strengthening of the Saharan heat-low and its associated shallow meridional overturning circulation is observed. The intensified shallow meridional overturning circulation increases moisture flux into the Sahel from the south during spring while increased westerly winds from the Atlantic increase westerly moisture flux into the Sahel during spring and summer. The strengthening of the heat-low is accompanied by increases in Mediterranean sea-surface temperatures during warm phases of the AMO that lead to increases in moisture flux convergence in the northeast Sahel. During warm phases of the AMO the African easterly jet is farther north than in cold phases, and increased African easterly wave (AEW) activity across West Africa and into the Atlantic is observed. This increased AEW activity particularly in the early hurricane season, as measured by eddy kinetic energy, may be contributing to the increased number of Atlantic tropical storms during warm phases of the AMO.

Spatial variability of liquid cloud and rain: observations and microphysical effects

Abstract: Spatial variability of liquid cloud water content and rainwater content is analysed from three different observational platforms: in situ measurements from research aircraft, land-based remote sensing techniques using radar and lidar, and spaceborne remote sensing from CloudSat. The variance is found to increase with spatial scale, but also depends strongly on the cloud or rain fraction regime, with overcast regions containing less variability than broken cloud fields. This variability is shown to lead to large biases, up to a factor of 4, in both the autoconversion and accretion rates estimated at a model grid scale of ≈40 km by a typical microphysical parametrization using in-cloud mean values. A parametrization for the subgrid variability of liquid cloud and rainwater content is developed, based on the observations, which varies with both the grid scale and cloud or rain fraction, and is applicable for all model grid scales. It is then shown that if this parametrization of the variability is analytically incorporated into the autoconversion and accretion rate calculations, the bias is significantly reduced.

Impact of anthropogenic heat emissions on London's temperatures

Abstract: We investigate the role of the anthropogenic heat flux on the urban heat island of London. To do this, the time-varying anthropogenic heat flux is added to an urban surface-energy balance parametrization, the Met Office–Reading Urban Surface Exchange Scheme (MORUSES), implemented in a 1 km resolution version of the UK Met Office Unified Model. The anthropogenic heat flux is derived from energy-demand data for London and is specified on the model's 1 km grid; it includes variations on diurnal and seasonal time-scales. We contrast a spring case with a winter case, to illustrate the effects of the larger anthropogenic heat flux in winter and the different roles played by thermodynamics in the different seasons. The surface-energy balance channels the anthropogenic heat into heating the urban surface, which warms slowly because of the large heat capacity of the urban surface. About one third of this additional warming goes into increasing the outgoing long-wave radiation and only about two thirds goes into increasing the sensible heat flux that warms the atmosphere. The anthropogenic heat flux has a larger effect on screen-level temperatures in the winter case, partly because the anthropogenic flux is larger then and partly because the boundary layer is shallower in winter. For the specific winter case studied here, the anthropogenic heat flux maintains a well-mixed boundary layer through the whole night over London, whereas the surrounding rural boundary layer becomes strongly stably stratified. This finding is likely to have important implications for air quality in winter. On the whole, inclusion of the anthropogenic heat flux improves the comparison between model simulations and measurements of screen-level temperature slightly and indicates that the anthropogenic heat flux is beginning to be an important factor in the London urban heat island.

Enhanced radiance bias correction in the National Centers for Environmental Prediction's Gridpoint Statistical Interpolation data assimilation system

Abstract: Radiance bias correction is an important and necessary step in the proper use of satellite observations in a data assimilation system. The original radiance bias-correction scheme used in the Gridpoint Statistical Interpolation (GSI) data assimilation system consists of two components: a variational air-mass dependent component and a scan-angle component. The air-mass component is updated within the GSI, while the scan-angle component is updated outside the GSI. This study examines and enhances several aspects of the radiance bias-correction problem. First, a modified pre-conditioning is applied to the bias-correction coefficients and the analysis variables to speed up convergence of the minimization process. A new procedure for applying the modified pre-conditioning in the GSI is utilized. Second, capabilities for detecting any new/missing/recovering radiance data and initializing the bias correction for new radiance data are implemented. A new scheme is proposed and employed to adjust the background-error variances for the bias-correction coefficients automatically, using an approximation of the analysis-error variances from the previous cycle, and to remove the pre-specified predictor scaling parameters. Finally, the capability to perform bias correction for passive channels within the GSI is developed with a new approach. The two-step bias-correction procedure originally used is replaced with a one-step variational bias-correction scheme within the GSI. Experiment results with the GSI-based hybrid ensemble-variational system show that using the modified pre-conditioning leads to a better convergence rate. Moreover, with the one-step scheme, the anomaly correlation of geopotential height at 500 mb is neutral in the Northern Hemisphere but improved in the Southern Hemisphere. The root-mean-square (RMS) error of wind is comparable to that of the two-step scheme and the biases of the global temperature 24 h and 48 h forecasts fitted to the rawinsonde are reduced.

The impact of downscaled initial condition perturbations on convective-scale ensemble forecasts of precipitation

Abstract: A major issue in convective-scale ensemble prediction systems (EPSs) is the specification of effective initial condition perturbations (ICPs). The present work considers the suitability of downscaled ICPs from a multi-model global EPS for short-range regional ensemble forecasts of convective precipitation at convection-permitting resolution. Previous studies indicated the importance of convective-scale initial condition uncertainties, with the most pronounced impact in weather conditions characterised by weak versus strong synoptic-scale forcing of convection. However, the downscaled ICPs do not explicitly represent small-scale uncertainty, which questions their effectiveness in convective-scale EPSs. To investigate the issue, the high-resolution ensemble system of the Deutscher Wetterdienst, COSMO-DE-EPS, which includes physics perturbations and lateral boundary condition perturbations in addition to ICPs, is employed. Forecasts are compared with a second EPS, identical but without ICPs, for a period of 3.5 months in the central European warm season. Weakly forced conditions are considered separately from strongly forced conditions, using an objective classification based on the area-averaged convective adjustment time-scale. Generally for all EPSs, forecast quality measures show a distinct behaviour in strong versus weak forcing conditions. However, the impact of the ICPs is found to be similar in the two regimes. The impact of the ICPs is clearly largest and positive (consistently in terms of ensemble variance and probabilistic forecast quality, but negative for the equitable threat score) in the first six forecast hours when the ICPs dominate the physics perturbations and lateral boundary condition perturbations. The ICPs then decay relatively quickly with lead time as the physics perturbations and lateral boundary condition perturbations start to become important and later dominant. Probabilistic precipitation forecasts by the EPSs outperform the deterministic COSMO-DE at the same convection-permitting resolution, and this more strongly in the first nine forecast hours with the EPS applying the ICPs.

Seasonal dependence of the urban heat island on the street canyon aspect ratio

Abstract: In this article we study the relation between the urban heat island (UHI) in the urban canyon and street geometry, in particular the aspect ratio. Model results and observations show that two counteracting processes govern the relation between the nocturnal UHI and the building aspect ratio: i.e. trapping of long-wave radiation and shadowing effects. In general, trapping of long-wave radiation supports the UHI, whereas shadowing effects reduce the UHI. The net effect depends on the UHI definition and the amount of available short-wave radiation penetrating the canyon. In summer, autumn and spring the shadowing effects can already reduce the UHI starting at an aspect ratio between 0.5 and 1. The analysis is carried out using several methods. Firstly, the single-column model version of the Weather Research and Forecasting (WRF) model is used extensively. Two separate runs, one rural and one urban, are used to estimate the UHI. Secondly, the urban canyon temperature at the 2 m level is introduced, which allows for direct comparison between modelled and observed air temperatures within the urban canyon. Finally, the model is evaluated for all four seasons. The results of this research provide important insights for urban planning on how to use the aspect ratio to mitigate the UHI in the urban canyon.

Observations of the chemical composition of stratospheric aerosol particles

Abstract: Recent instrumentation can distinguish various types of aerosol particles in the stratosphere and determine their relative abundance. In the background lower stratosphere between major volcanic eruptions, most particles are either relatively pure sulphuric acid, sulphuric acid with material from ablated meteoroids or mixed organic-sulphate particles that originated in the troposphere. The meteoritic iron and magnesium appear to be dissolved whereas the aluminum and silicon appear to be inclusions. Most stratospheric aerosol mass is liquid sulphuric acid and associated water, but a large fraction of particles contain either inclusions of meteoritic elements such as silicon or organic material that is probably effloresced or glassy. These solid phases could have large but unknown implications for the ability of particles to act as freezing nuclei for polar stratospheric clouds. Internally mixed black carbon is a measurable but very small component of the stratospheric aerosol by mass. Despite their importance for heterogeneous chemistry, there are few quantitative measurements of halogens in stratospheric particles.

An Analysis of the Observed Low-level Structure of Rapidly Intensifying and Mature Hurricane Earl (2010)

Abstract: : We examine dynamic and thermodynamic aspects of Atlantic hurricane Earl (2010) during its intensification and mature phases over four days of intensive measurements. During this period, Earl underwent an episode of rapid intensification, maturity, secondary eyewall replacement, re-intensification and the early part of its decline. The observations are used to appraise elements of a new model for tropical-cyclone intensification. The results affirm the conventional (vortex interior) and boundary-layer spin-up mechanisms that form dynamical elements of the azimuthally averaged view of the new intensification model. The average maximum tangential winds beneath the eyewall are found to exceed the gradient wind by between 20 and 60%. The results suggest also that the gradient wind balance approximation in the low-level vortex interior above the strong inflow layer may not be as accurate in the inner-core region of a tropical cyclone during its intensification as has been widely held. An analysis of the low-level thermodynamic structure affirms the radial increase of moist equivalent potential temperature, e ,with decreasing radius during the intensification process,a necessary ingredient of the new model for maintaining convective instability in the presence of a warming upper troposphere. An unanticipated finding is the discovery of an unmixed boundary layer in terms of e within several hundred kilometres of the vortex centre. In the inner-core region, this finding is not consistent with the axisymmetric eruption of the boundary layer into the eyewall unless there are non-conservative (eddy) processes acting to modify the entropy of ascending air.

The distribution and variability of low-level cloud in the North-Atlantic trades

Abstract: In the North Atlantic trades, variations in the distribution of low-level cloud are rich. Using two years of observations from a remote-sensing site located on the east coast of Barbados, the vertical distribution of cloud and its contribution to low-level cloud amount are explored. The vertical distribution of first-detected cloud-base heights is marked by a strong peak near the lifting condensation level (LCL) from passive optically thin shallow cumuli. Cloud with a base near this level dominates the total cloud cover with a contribution of about two-thirds. The other one-third comes from cloud with its cloud base further aloft at heights > 1 km, such as cumulus edges or stratiform cloud below the trade inversion. Cloud found aloft, regardless of where its base is located, contains more variance, in particular near the inversion and on time-scales longer than a day. In turn, cloud near the LCL is surprisingly invariant on longer time-scales, although consistent with existing theories. Because this component does not systematically vary, changes in cloud cover in response to changes in meteorology or climate may be limited to changes in its contribution from cloud aloft.

Forecast sensitivity to observations in the Met Office Global numerical weather prediction system

Abstract: An adjoint-based method for calculating the impacts of observations in the Met Office's global four-dimensional variational assimilation (4D-Var) system is documented. Our approach is novel, as we seek from the outset a linearized approximation to partition the finite impact from a batch of observations, but our method and results are very similar to those of other systems. The large beneficial impacts measured for satellite radiances and radiosonde soundings in our system are interesting results. We also identify areas for potential improvement, such as the assimilation of Northern Hemisphere stratospheric satellite radio occultation (GPSRO) observations, polar atmospheric motion vectors and tropical cyclone (TC) bogus observations synthesized automatically from tropical cyclone warning centre advisory messages. We use a toy model to explain why only just over 50% of observations improve the forecast. Growing modes, observational errors and errors in the verifying forecast contribute approximately equally and we suggest that our necessarily imperfect knowledge of background-error statistics also contributes.

The convective adjustment time-scale as indicator of predictability of convective precipitation

Abstract: Predictability of convective precipitation depends on the interaction between synoptic forcing and local-scale flow characteristics. In order to assess different predictability levels it is desirable to objectively determine the dominant process in a given meteorological situation. Such a measure is given by the convective adjustment time-scale τ, a physically based quantity that distinguishes between strong and weak synoptically forced precipitation regimes. By employing the convective adjustment time-scale diagnostic, forecasts of the convection-permitting COSMO-DE ensemble prediction system available for a total of 88 days in summer 2009 are examined. Based on the normalized ensemble spread of hourly precipitation rates, it is shown that the practical predictability of total precipitation is higher during strong large-scale forcing than during weak forcing. Likewise, the forecast skill, determined using two deterministic scores, is higher during strong than during weak forcing conditions. Different predictability levels of convective precipitation can be revealed by examining distinct sub-ensembles depending on their source of uncertainty. The impact of variations in the boundary conditions of the driving global models used in the ensemble system is quite insensitive to the prevailing flow regime, while the impact of physics perturbations representing the model error is clearly weather regime dependent, exhibiting a strong contribution only during weakly forced conditions. Then convective precipitation turns out to be especially sensitive to variations in the physics parametrization even at forecast lead times of 12 to 18 hours during the main convective period in the afternoon. Two case-studies exemplifying the strong and weak forcing regimes are shown, to illustrate how forecast skill varies and the different ensemble members cluster as the precipitation event evolves.

A nonlinear multiscale interaction model for atmospheric blocking: The eddy‐blocking matching mechanism

Abstract: In this article, a nonlinear multiscale interaction (NMI) model is used to propose an eddy-blocking matching (EBM) mechanism to account for how synoptic eddies reinforce or suppress a blocking flow. It is shown that the spatial structure of the eddy vorticity forcing (EVF) arising from upstream synoptic eddies determines whether an incipient block can grow into a meandering blocking flow through its interaction with the transient synoptic eddies from the west. Under certain conditions, the EVF exhibits a low-frequency oscillation on time-scales of 2–3 weeks. During the EVF phase with a negative-over- positive dipole structure, a blocking event can be resonantly excited through the transport of eddy energy into the incipient block by the EVF. As the EVF changes into an opposite phase, the blocking decays. The NMI model produces life cycles of blocking events that resemble observations. Moreover, it is shown that the eddy north–south straining is a response of the eddies to a dipole- or Ω-type block. In our model, as in observations, two synoptic anticyclones (cyclones) can attract and merge with one another as the blocking intensifies, but only when the feedback of the blocking on the eddies is included. Thus, we attribute the eddy straining and associated vortex interaction to the feedback of the intensified blocking on synoptic eddies. The results illustrate the concomitant nature of the eddy deformation, the role of which, as a potential vorticity source for the blocking flow, becomes important only during the mature stage of a block. Our EBM mechanism suggests that an incipient block flow is amplified (or suppressed) under certain conditions by the EVF coming from the upstream of the blocking region. This also suggests that weather and climate models need to be run with a grid size below 100 km in order to simulate the matching EVF and thus atmospheric blocking.

A new atmospheric dataset for forcing ice–ocean models: Evaluation of reforecasts using the Canadian global deterministic prediction system

Abstract: Despite the availability of several atmospheric reanalyses (e.g. ERA-Interim) there exists both considerable uncertainty in surface forcing fields for ice/ocean modelling and sensitivity to the choice of product used. Here we introduce a relatively high-resolution alternative forcing dataset for ice–ocean models derived from the Canadian Meteorological Centre's (CMC) global deterministic prediction system (GDPS). A set of daily 30 h reforecasts is produced using the GDPS 33 km resolution model providing hourly atmospheric forcing fields for the period 2002–2011. The CMC GDPS reforecasts (CGRF) are compared with ERA-Interim and several observational datasets to evaluate their suitability for forcing ocean models. In particular, the surface temperature, humidity and winds of the CGRF show equivalent biases to those found in ERA-interim. Moreover, the higher resolution of the CGRF permit a more detailed representation of atmospheric structures and topographic steering, resulting in finer-scale coastal features and wind-stress curl. Although the CGRF dataset is not a reanalysis and thus is expected to be less well constrained by available observations, its higher resolution and small bias make it an attractive alternative for forcing ice-ocean models.

Twentieth century North Atlantic jet variability

Abstract: Long records of the latitude and speed of the North Atlantic eddy-driven jet stream since 1871 are presented from the newly available Twentieth Century Reanalysis. These jet variations underlie the variability associated with patterns such as the North Atlantic Oscillation (NAO) and have considerable societal impact through variations in the prevailing westerly winds. While the NAO combines variations in the latitude and speed of the jet, these two characteristics are shown to have quite different seasonal cycles and interannual variability, suggesting that they may have different dynamical influences. In general, the features exhibited in shorter records are shown to be robust, for example the strong skewness of the NAO distribution. Related to this is a clear multimodality of the jet latitude distribution, which suggests the existence of preferred positions of the jet. Decadal variations in jet latitude are shown to correspond to changes in the occurrence of these preferred positions. However, it is the speed rather than the latitude of the jet that exhibits the strongest decadal variability, and in most seasons this is clearly distinct from a white-noise representation of the seasonal means. When viewed in this longer term context, the variations of recent decades do not appear unusual and recent values of jet latitude and speed are not unprecedented in the historical record.

Decomposition and graphical portrayal of the quantile score

Abstract: This study expands the pool of verification methods for probabilistic weather and climate predictions by a decomposition of the quantile score (QS). The QS is a proper score function and evaluates predictive quantiles on a set of forecast–observation pairs. We introduce a decomposition of the QS in reliability, resolution and uncertainty and discuss the biases of the decomposition. Further, a reliability diagram for quantile forecasts is presented. Verification with the QS and its decomposition is illustrated on precipitation forecasts derived from the mesoscale weather prediction ensemble COSMO-DE-EPS of the German Meteorological Service. We argue that the QS is ready to become as popular as the Brier score in forecast verification.

A comparison of 4DVar with ensemble data assimilation methods

Abstract: © 2013 Royal Meteorological Society and Crown Copyright, the Met Office.Three data assimilation methods are compared for their ability to produce the best analysis: (i) 4DVar, four-dimensional variational data assimilation using linear and adjoint models with either a (perfect) 3D climatological background-error covariance or a 3D ensemble background-error covariance; (ii) EDA, an ensemble of 4DEnVars, which is a variational method using a 4D ensemble covariance; and (iii) the deterministic ensemble Kalman filter (DEnKF, also using a 4D ensemble covariance). The accuracy of the deterministic analysis from each method was measured for both perfect and imperfect toy model experiments. With a perfect model, 4DVar with the climatological covariance is easily beaten by the ensemble methods, due to the importance of flow-dependent background-error covariances. When model error is present, 4DVar is more competitive and its relative performance is improved by increasing the observation density. This is related to the model error representation in the background-error covariance. The dynamical time-consistency of the 4D ensemble background-error covariance is degraded by the localization, since the localization function and the nonlinear model do not commute. As a result, 4DVar with the ensemble covariance performs significantly better than the other ensemble methods when severe localization is required, i.e. for a small ensemble.