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Ehard, Benedikt; Malardel, Sylvie; Dörnbrack, Andreas; Kaifler, Bernd; Kaifler, Natalie; Wedi, Nils
doi: 10.1002/qj.3206pmid: N/A
Middle atmospheric lidar temperature observations conducted above Sodankylä, Finland (67.4°N, 26.6°E), during December 2015 are compared with two estimates of the atmospheric state computed by the integrated forecast system (IFS) of the European Centre for Medium‐Range Weather Forecasts (ECMWF). The first set corresponds to an hourly sampling of the middle atmosphere by high‐resolution analyses and very short‐range forecasts produced by the operational IFS cycle 41r1 at a horizontal resolution of 16 km. The second set is retrieved from the upgraded IFS cycle 41r2 (horizontal resolution 9 km), which was running in parallel with cycle 41r1 during the validation before it became operational. A remarkable agreement between both IFS datasets and the lidar temperature observations above Sodankylä is found below 45 km altitude. Above 45 km altitude, within the sponge layer of the IFS, both IFS datasets depict lower temperatures than the observations, with the 9 km runs showing the coldest temperatures. Various sensitivity experiments conducted with the IFS are analyzed and compared with the lidar observations to investigate the impact of the different changes implemented in IFS cycle 41r2. It is found that both the scientific changes and the horizontal resolution upgrade contribute to the colder mesosphere above Sodankylä. The data assimilation seems to amplify this effect even further.
doi: 10.1002/qj.3224pmid: 31031421
Turbulence data from the CASES‐99 field experiment, over comparatively horizontally homogeneous and flat terrain, are separated based on the anisotropy of the Reynolds stress tensor (into isotropic, two‐component axisymmetric and one‐component turbulence) and flux‐variance similarity scaling relations are tested. Results illustrate that different states of anisotropy correspond to different similarity relations, especially under unstable stratification. Experimental data with close to isotropic turbulence match similarity relationships well. On the other hand, very anisotropic turbulence deviates significantly from the traditional scaling relations. We examine in detail the characteristics of these states of anisotropy, identify conditions in which they occur and connect them with different governing parameters. The governing parameters of turbulence anisotropy are shown to be different for stable and unstable stratification, but are able to delineate clearly the conditions in which each of the anisotropy states occurs.
Pelletier, C.; Lemarié, F.; Blayo, E.
doi: 10.1002/qj.3233pmid: N/A
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 article introduces a methodology for building physically realistic approximations of existing bulk formulae which 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 parametrization 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.
Cowtan, Kevin; Rohde, Robert; Hausfather, Zeke
doi: 10.1002/qj.3235pmid: N/A
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.
doi: 10.1002/qj.3238pmid: N/A
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 article 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 show 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 and 0.9 m/s for the u and v components respectively. Comparing the FAAM data and B747 flight data recorder (FDR) provided RMS differences of 0.6 and 1.4 m/s 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 and 0.5 K when the FAAM data were 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.
Portmann, R.; Crezee, B.; Quinting, J.; Wernli, H.
doi: 10.1002/qj.3239pmid: N/A
Potential vorticity (PV) cut‐offs 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 cut‐offs 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 cut‐offs. 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 cut‐off air parcels (direct diabatic effects). In addition, if the cut‐off 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 cut‐off (indirect diabatic effects). This study extends our understanding of PV cut‐offs by (a) emphasizing their intricate vertical structure and temporal evolution, (b) revealing the complex interplay of diabatic processes and how they contribute to the decay and intensification of cut‐offs, and (c) indicating the challenge in correctly forecasting these dynamically important flow features.
Li, Jiangnan; Barker, Howard W.
doi: 10.1002/qj.3241pmid: N/A
A method for calculating domain‐average radiative flux profiles, called Gaussian Quadrature Independent Column Approximation (GQ‐ICA), is introduced and assessed using cloud properties retrieved from A‐Train satellite data. This method could be suitable for use in large‐scale atmospheric models. Like the Monte Carlo ICA (McICA), GQ‐ICA uses N stochastically generated subgrid‐scale cloudy columns. The independent variable is the sorted, from smallest to largest, sequence of N sub‐column values of liquid and ice cloud water paths. The integrand is essentially the radiative transfer equation. Accurate GQ integration requires integrands to be relatively smooth functions. Unlike McICA, GQ‐ICA performs full solar and infrared spectral integrations on nG < < N sub‐columns which are identified by rules governing nG‐node GQ. The nG flux profiles are appropriately weighted and summed to give domain averages. Several sorting procedures were considered, and all results are based on the CCCma radiation algorithm. For solar radiation, 1‐node GQ‐ICA can produce significant bias errors, but its random errors are generally less than McICA's. These biases, however, are almost eliminated by 2‐node GQ‐ICA. For GQ‐ICA to better McICA's random errors for infrared fluxes, at least the 2‐node version is needed. Ultimately, 2‐node GQ‐ICA random errors for net fluxes at surface and top‐of‐atmosphere are typically 30–50% of McICA's. This is partly because solar and infrared solvers operate on the same sub‐columns. GQ‐ICA random errors for atmospheric heating rates are comparable to McICA's even for 3‐node GQ‐ICA. Computational times required for the 2‐ and 3‐node GQ‐ICA are, respectively, ∼180 and ∼230% of McICA's.
doi: 10.1002/qj.3242pmid: N/A
We introduce a verification score for probabilistic forecasts of contours – the Spatial Probability Score (SPS). Defined as the spatial integral of local (Half) Brier Scores, the SPS can be considered the spatial analogue of the Continuous Ranked Probability Score (CRPS). Applying the SPS to idealized ensemble forecasts of the Arctic sea‐ice edge in a global coupled climate model, we demonstrate that the metric responds in a meaningful way to ensemble size, spread, and bias. When applied to individual forecasts or ensemble means (or quantiles), the SPS is reduced to the ‘volume’ of mismatch, which in the case of the ice edge corresponds to the Integrated Ice Edge Error (IIEE). By comparing initialized forecasts with climatological and persistence forecasts, we confirm earlier findings on the potential predictability of the Arctic sea‐ice edge from a probabilistic viewpoint. We conclude that the SPS is a promising probabilistic verification metric, for contour forecasts in general and for ice‐edge forecasts in particular.
Klasa, Christina; Arpagaus, Marco; Walser, André; Wernli, Heini
doi: 10.1002/qj.3245pmid: N/A
Specific aspects of the performance of COSMO‐E, a newly operational convection‐permitting ensemble prediction system run by the Swiss national weather service, are evaluated for three contrasting precipitation events and compared with its driving model, the ECMWF ensemble (EC ENS). The events include locally triggered air‐mass convection on four consecutive days (CONV), a complex flood‐producing rainfall episode (LSF1), and a summertime cold‐frontal precipitation event (LSF2). Investigating the precipitation forecasts reveals that COSMO‐E outperforms EC ENS in all cases in terms of precipitation pattern, whereas both ensembles fail in predicting the correct domain‐averaged precipitation for LSF1 and struggle with the correct timing of the daily precipitation onset for CONV. For LSF2, EC ENS produces an almost perfect time series of domain‐averaged precipitation, but this seemingly excellent forecast fails in predicting the spatial distribution. Spread–error relationships also yield a rather complex picture. The higher resolution of COSMO‐E leads to increased spread and reduced underdispersion for near‐surface variables. However, in the free troposphere the two ensembles perform similarly, and the agreement of spread and error varies between cases, variables and levels. For both events with large‐scale advection, underdispersion occurs for mid‐tropospheric relative humidity near fronts, whose propagation is overconfident in EC ENS, while for the convective event COSMO‐E clearly shows larger spread than EC ENS. Because frontal propagation is largely determined by lateral boundary conditions, this underdispersion also occurs for COSMO‐E. In summary, this study confirms the benefit of a convection‐permitting model for many aspects of ensemble forecasting, and illustrates the challenge of robustly assessing the quality of an ensemble forecast for hydrometeorologically relevant events.
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