The Quarterly Journal of the Royal Meteorological Society

Suomi, Irene; Gryning, Sven‐Erik; O'Connor, Ewan J.; Vihma, Timo

doi: 10.1002/qj.3059pmid: N/A

A new methodology is proposed for scaling Doppler lidar observations of wind gusts to make them comparable with those observed at a meteorological mast. Doppler lidars can then be used to measure wind gusts in regions and heights where traditional meteorological mast measurements are not available. This novel method also provides estimates for wind gusts at arbitrary gust durations, including those shorter than the temporal resolution of the Doppler lidar measurements. The input parameters for the scaling method are the measured wind‐gust speed as well as the mean and standard deviation of the horizontal wind speed. The method was tested using WindCube V2 Doppler lidar measurements taken next to a 100 m high meteorological mast. It is shown that the method can provide realistic Doppler lidar estimates of the gust factor, i.e. the ratio of the wind‐gust speed to the mean wind speed. The method reduced the bias in the Doppler lidar gust factors from 0.07 to 0.03 and can be improved further to reduce the bias by using a realistic estimate of turbulence. Wind gust measurements are often prone to outliers in the time series, because they represent the maximum of a (moving‐averaged) horizontal wind speed. To assure the data quality in this study, we applied a filtering technique based on spike detection to remove possible outliers in the Doppler lidar data. We found that the spike detection‐removal method clearly improved the wind‐gust measurements, both with and without the scaling method. Spike detection also outperformed the traditional Doppler lidar quality assurance method based on carrier‐to‐noise ratio, by removing additional unrealistic outliers present in the time series.

Arbogast, Étienne; Desroziers, Gérald; Berre, Loïk

doi: 10.1002/qj.3061pmid: N/A

The four‐dimensional ensemble variational (4DEnVar) formulation has received considerable attention during recent years, especially at numerical weather prediction centres that are (or were) relying on a 3D/4D‐Var formalism for their data assimilation systems. Since 4DEnVar background‐error covariances are, by construction, given by an ensemble of 4D nonlinear trajectories, an important issue is the way in which to build this ensemble. The use of an ensemble of perturbed 4DEnVar to generate the ensemble is a natural approach, but raises difficulties for the input and storage of 4D trajectories. A parallel implementation of such a 4DEnVar ensemble (En‐4DEnVar) approach is proposed, with distributed input and storage of ensemble perturbations. It has the benefit of an object‐oriented implementation of 4DEnVar, which has recently been developed at Météo‐France. First results obtained with the French global model Action de Recherche Petite Echelle Grande Echelle (ARPEGE) show that such an approach is efficient and suggest that En‐4DEnVar implementations are tractable.

Kolstad, E. W.

doi: 10.1002/qj.3068pmid: N/A

Marine cold air outbreaks (MCAOs) are large‐scale events in which cold air masses are advected over open ocean. It is well‐known that these events are linked to the formation of polar lows and other mesoscale phenomena associated with high wind speeds, and that they therefore in some cases represent a hazard to maritime activities. However, it is still unknown whether MCAOs are generally conducive to higher wind speeds than normal. Here this is investigated by comparing ocean near‐surface wind speeds during MCAOs in atmospheric reanalysis products with different horizontal grid spacings, along with two case‐studies using a convection‐permitting numerical weather prediction model. The study regions are the Labrador Sea and the Greenland–Iceland–Norwegian (GIN) Seas, where MCAOs have been shown to be important for air–sea interaction and deep water formation. One of the main findings is that wind speeds during the strongest MCAO events are higher than normal and higher than wind speeds during less severe events. Limited evidence from the case‐studies suggests that reanalyses with grid spacings of more than 50 km underestimate winds driven by the large ocean–atmosphere energy fluxes during MCAOs. The peak times of MCAOs usually occur when baroclinic waves pass over the regions. Therefore, the strong wind episodes during MCAOs generally last for just a few days. However, MCAOs as defined here can persist for 50 days or more.

Kärcher, B.

doi: 10.1002/qj.3069pmid: N/A

Homogeneous droplet freezing in the warm cirrus regime (230–240 K) is investigated along idealized convective cloud trajectories using a spectral parcel model developed to track droplet freezing events accurately. The novel model is described and used to study ice formation from rapidly ascending (vertical velocity 0.6–6 m s−1) air parcels containing cloud condensation nuclei (CCN) and liquid water droplets. Homogeneous freezing events in warm cirrus are affected by latent heat exchange and produce a mode of small ice crystals with maximum dimensions 10–100 μm after initial supersaturation quenching. During the formation stage, ice‐crystal number concentrations formed homogeneously in convective cloud outflow are hardly affected by ice‐crystal settling and depend sensitively on vertical velocity. In the case of CCN activation into cloud water droplets prior to or along with freezing, relative humidity variations also result in widely varying ice numbers that are insensitive to CCN solubility. These results offer pointers on how further progress can be achieved in simulating and better understanding the formation of upper tropospheric ice clouds originating from convective detrainment zones.

Duruisseau, Fabrice; Chambon, Philippe; Guedj, Stéphanie; Guidard, Vincent; Fourrié, Nadia; Taillefer, Françoise; Brousseau, Pierre; Mahfouf, Jean‐François; Roca, Rémy

doi: 10.1002/qj.3070pmid: N/A

Observing the Earth with a microwave radiometer on board a geostationary satellite has generated interest for several decades. Such a mission would add a high observation rate in the microwave spectrum, offered by a geostationary orbit, to the sounding capabilities of the current observing system. The instrumental concept under study considers a microwave radiometer with six channels with different observation errors within the 183.31 GHz water vapour absorption band.

Gautam, Alok S.; Siingh, Devendraa; Kamra, A. K.

doi: 10.1002/qj.3071pmid: N/A

Measurements of ion mobility spectra in the range of 0.00133–3.16 cm2 s−1 volt−1 were made at a tropical station, Pune, India from March 2010 to December 2012. A total of 12 004 hourly averaged ion mobility spectra were obtained over the entire period. The average mobility spectrum shows three distinct peaks for the traditional categories of small, intermediate and large ions. However, to understand the seasonal variability and statistical characteristics of ions that justify their further division into five different categories, we have divided our data into five mobility ranges of small cluster, big cluster, intermediate, light large and heavy large ions. Our results show that small ions in atmospheric conditions at Pune can be further divided into two classes with the boundary at a mobility of 1.78 cm2 s−1 volt−1 (diameter 0.66 nm) where relative standard deviation of ion concentrations starts increasing instead of decreasing with mobility. Some but not all small cluster ions of negative polarity are likely to grow to the intermediate ion size. Further, the growth from small to big cluster ions is faster for negative than positive ions. In contrast to the observations of higher mean values of ion concentration in warm season than in winter at a midlatitude station, our observations show higher mean values of ion concentration in winter than in the warm season at this tropical station. This contrast in observations at the two sites is explained by trapping of radioactive emanations by snow at the ground during winter at the midlatitude site.

Magnusson, L.

doi: 10.1002/qj.3072pmid: N/A

Although the quality of medium‐range forecasts has increased considerably over the decades since the start of operational forecasts at the European Centre for Medium‐Range Weather Forecasts (ECMWF), individual forecasts still occasionally experience very large errors. Often the phrasing ‘drop‐outs’ or ‘forecast busts’ is used for such episodes. The aim of this report is to use a combination of methods to track errors in three cases of extreme forecast errors between 2014 and 2016, to understand the error sources better. Manual error tracking and ensemble sensitivity are used to give a first guess for the source region and relaxation experiments are used to confirm the result. In the three cases investigated, the errors originated from the tropical eastern Pacific, western/central Canada and western Atlantic, respectively. The mechanisms behind the errors are discussed in the report. The results from this study can form a basis for further investigations of these cases and the methodology explained can be applied to understand future bust cases, to increase our knowledge of the origin and propagation of forecast errors.

Neetu, S.; Lengaigne, M.; Menon, H. B.; Vialard, J.; Mangeas, M.; Menkes, C. E.; Ali, M. M.; Suresh, I.; Knaff, J. A.

doi: 10.1002/qj.3073pmid: N/A

This paper assesses the characteristics of linear statistical models developed for tropical cyclone (TC) intensity prediction at global scale. To that end, multilinear regression models are developed separately for each TC‐prone basin to estimate the intensification of a TC given its initial characteristics and environmental parameters along its track. We use identical large‐scale environmental parameters in all basins, derived from a 1979–2012 reanalysis product. The resulting models display comparable skill to previously described similar hindcast schemes. Although the resulting mean absolute errors are rather similar in all basins, the models beat persistence by 20–40% in most basins, except in the North Atlantic and northern Indian Ocean, where the skill gain is weaker (10–25%). A large fraction (60–80%) of the skill gain arises from the TC characteristics (intensity and its rate of change) at the beginning of the forecast. Vertical shear followed by the maximum potential intensity are the environmental parameters that yield most skill globally, but with individual contributions that strongly depend on the basin. Hindcast models built from environmental predictors calculated from their seasonal climatology perform almost as well as using real‐time values. This has the potential to considerably simplify the implementation of operational forecasts in such models. Finally, these models perform poorly to predict intensity changes for Category 2 and weaker TCs, while they are 2–4 times more skilful for the strongest TCs (Category 3 and above). This suggests that these linear models do not properly capture the processes controlling the early stages of TC intensification.

Scheffler, Guillermo; Pulido, Manuel

doi: 10.1002/qj.3074pmid: N/A

The impact of optimal parameters in a non‐orographic gravity‐wave drag parametrization on the middle atmosphere circulation of the Southern Hemisphere is examined. Optimal parameters are estimated using a data assimilation technique. The proposed technique aims to reduce the delay in the winter vortex breakdown of the Southern Hemisphere found in general circulation models, which may be associated with a poor representation of gravity‐wave activity. We introduce two different implementations of the parameter estimation method: an offline estimation method and a sequential estimation method. The delay in the zonal‐mean zonal‐wind transition is largely alleviated by the optimal gravity‐wave parameters. The sequential method diminishes the model biases during winter vortex evolution, through gravity‐wave drag alone. On the other hand, the offline method accounts better for unresolved–resolved wave interactions and the zonal‐wind transition. We show that the final warmings in the lower mesosphere are driven mainly by planetary‐wave breaking. These are affected by changes in the gravity‐wave drag that are responsible for stratospheric preconditioning. Parameter estimation during the vortex breakdown is a challenging task that requires the use of sophisticated estimation techniques, because there are strong interactions between unresolved gravity‐wave drag and planetary waves.

Christensen, H. M.; Lock, S.‐J.; Moroz, I. M.; Palmer, T. N.

doi: 10.1002/qj.3075pmid: N/A

The Stochastically Perturbed Parametrization Tendencies (SPPT) scheme is used at weather and climate forecasting centres worldwide to represent model uncertainty that arises from simplifications involved in the parametrization process. It uses spatio‐temporally correlated multiplicative noise to perturb the sum of the parametrized tendencies. However, SPPT does not distinguish between different parametrization schemes, which do not necessarily have the same error characteristics. A generalization to SPPT is proposed, whereby the tendency from each parametrization scheme can be perturbed using an independent stochastic pattern. This acknowledges that the forecast errors arising from different parametrizations are not perfectly correlated. Two variations of this ‘independent SPPT’ (iSPPT) approach are tested in the Integrated Forecasting System (IFS). The first perturbs all parametrized tendencies independently, while the second groups tendencies before perturbation. The iSPPT schemes lead to statistically significant improvements in forecast reliability in the Tropics in medium‐range weather forecasts. This improvement can be attributed to a large, beneficial increase in ensemble spread in regions with significant convective activity. The iSPPT schemes also lead to improved forecast skill in the extratropics for a set of cases in which the synoptic initial conditions were more likely to result in European ‘forecast busts’. Longer 13 month simulations are also considered to indicate the effect of iSPPT on the mean climate of the IFS.