ALBERT

Beschreibung: An approach to make use of Atmospheric Infrared Sounder (AIRS) cloud-affected infrared radiances has been developed at Météo-France in the context of the global numerical weather prediction model. The method is based on (i) the detection and the characterization of clouds by the CO2-slicing algorithm and (ii) the identification of clear–cloudy channels using the ECMWF cloud-detection scheme. Once a hypothetical cloud-affected pixel is detected by the CO2-slicing scheme, the cloud-top pressure and the effective cloud fraction are provided to the radiative transfer model simultaneously with other atmospheric variables to simulate cloud-affected radiances. Furthermore, the ECMWF scheme flags each channel of the pixel as clear or cloudy. In the current configuration of the assimilation scheme, channels affected by clouds whose cloud-top pressure ranges between 600 and 950 hPa are assimilated over sea in addition to clear channels. Results of assimilation experiments are presented. On average, 3.5% of additional pixels are assimilated over the globe but additional assimilated channels are much more numerous for mid- to high latitudes (10% of additional assimilated channels on average). Encouraging results are found in the quality of the analyses: background departures of AIRS observations are reduced, especially for surface channels, which are globally 4 times smaller, and the analysis better fits some conventional and satellite data. Global forecasts are slightly improved for the geopotential field. These improvements are significant up to the 72-h forecast range. Predictability improvements have been obtained for a case study: a low pressure system that affected the southeastern part of Italy in September 2006. The trajectory, intensity, and the whole development of the cyclogenesis are better predicted, whatever the forecast range, for this case study.

Beschreibung: The Indian mesosphere–stratosphere–troposphere (MST) radar observations during the passage of 37 convective systems are utilized to investigate the characteristics of vertical air velocity w in different convection categories (shallow, deep, and decaying) and also the differences in draft core statistics from the wet to dry spell. The radar and optical rain gauge measurements show pronounced differences in core statistics (in terms of their vertical structure, draft strength, size, number, and the elevation angle) and surface rainfall characteristics from the dry to wet spell. The shallow convective cores are preponderant in the dry spell. Composite w profiles, retrieved from all deep cases and also from individual convection cases, depict an upper-tropospheric peak in the wet spell and a bimodal distribution (peaks at 5 and 11–13 km) in the dry spell, illustrating that they are characteristic features of wet and dry spells. The average vertical extents of the cores are nearly equal (about 8 km) in both spells of the monsoon; however, the core-base (and top) altitudes are different. In both wet and dry spells, the composite w profile for all cores show similar vertical variation to that of for updraft cores, while the composite w for downdraft cores do not show much variation with altitude, indicating that the updraft cores dictate the vertical structure of composite w. The core size varies considerably (a factor of 2) with altitude in both spells of the monsoon. Although nearly equal in the lower troposphere in both phases of the monsoon, the core size is larger by 1–2 km in the dry spell in the middle and upper troposphere. Consistent with the longer lifetime (bigger core size) of cores in the dry spell, the cores are more inclined (with a mean elevation angle of 30°) in the dry spell. The surface rainfall distribution is wider and has large number of intense rainfall rates in the wet spell. The mean rainfall rate for the wet spell is also larger by a factor of 2, consistent with earlier studies.

Beschreibung: The diffusion kernel filter is a sequential particle-method approach to data assimilation of time series data and evolutionary models. The method is applicable to nonlinear/non-Gaussian problems. Within branches of prediction it parameterizes small fluctuations of Brownian-driven paths about deterministic paths. Its implementation is relatively straightforward, provided a tangent linear model is available. A by-product of the parameterization is a bound on the infinity norm of the covariance matrix of such fluctuations (divided by the grid model dimension). As such it can be used to define a notion of “prediction” itself. It can also be used to assess the short time sensitivity of the deterministic history to Brownian noise or Gaussian initial perturbations. In pure oceanic Lagrangian data assimilation, the dynamics and the statistics are nonlinear and non-Gaussian, respectively. Both of these characteristics challenge conventional methods, such as the extended Kalman filter and the popular ensemble Kalman filter. The diffusion kernel filter is proposed as an alternative and is evaluated here on a problem that is often used as a test bed for Lagrangian data assimilation: it consists of tracking point vortices and passive drifters, using a dynamical model and data, both of which have known error statistics. It is found that the diffusion kernel filter captures the first few moments of the random dynamics, with a computational cost that is competitive with a particle filter estimation strategy. The authors also introduce a clustered version of the diffusion kernel filter (cDKF), which is shown to be significantly more efficient with regard to computational cost, at the expense of a slight degradation in the description of the statistics of the dynamical history. Upon parallelizing branches of prediction, cDKF can be computationally competitive with EKF.

Beschreibung: Superparameterization (SP) is a large-scale modeling system with explicit representation of small-scale and mesoscale processes provided by a cloud-resolving model (CRM) embedded in each column of a large-scale model. New efficient sparse space–time algorithms based on the original idea of SP are presented. The large-scale dynamics are unchanged, but the small-scale model is solved in a reduced spatially periodic domain to save the computation cost following a similar idea applied by one of the authors for aquaplanet simulations. In addition, the time interval of integration of the small-scale model is reduced systematically for the same purpose, which results in a different coupling mechanism between the small- and large-scale models. The new algorithms have been applied to a stringent two-dimensional test suite involving moist convection interacting with shear with regimes ranging from strong free and forced squall lines to dying scattered convection as the shear strength varies. The numerical results are compared with the CRM and original SP. It is shown here that for all of the regimes of propagation and dying scattered convection, the large-scale variables such as horizontal velocity and specific humidity are captured in a statistically accurate way (pattern correlations above 0.75) based on space–time reduction of the small-scale models by a factor of ⅓; thus, the new efficient algorithms for SP result in a gain of roughly a factor of 10 in efficiency while retaining a statistical accuracy on the large-scale variables. Even the models with ⅙ reduction in space–time with a gain of 36 in efficiency are able to distinguish between propagating squall lines and dying scattered convection with a pattern correlation above 0.6 for horizontal velocity and specific humidity. These encouraging results suggest the possibility of using these efficient new algorithms for limited-area mesoscale ensemble forecasting.

Beschreibung: On 24 November 2005, 11 lattice steel towers of a high-voltage electrical transmission line running along the edge of an escarpment were damaged by an accumulation of rime on overhead ground wires. Cold air pooling in the Columbia basin of eastern Washington several days before the failure led to the formation of low-level fog and low clouds with temperatures below freezing at the elevation of the transmission line. The liquid water content profile of the cloud formed by air rising over Badger Mountain north of Wenatchee, Washington, is estimated using the air temperature, dewpoint temperature, and air pressure as measured at Wenatchee in the Columbia River valley below the line. Cloud median volume droplet diameters are estimated using typical droplet concentrations. The validity of the computed liquid water content is determined by comparing the measured cloud-base heights at Wenatchee with the calculated cloud-base heights. The mass and density of ice accreted on the ground wires and conductors of the transmission line are modeled using assumed wind speeds at the top of the escarpment with the estimated cloud properties. Results are compared with the density and mass of an ice sample retrieved from the field. This event is compared with other modeled in-cloud icing events from 1973 to 2007 using the period of record of Wenatchee weather data. This paper illustrates an approach for estimating the severity of in-cloud icing on the wires of transmission lines subject to cloud liquid water contents that have been enhanced by the local terrain.

Beschreibung: This paper examines ensemble Kalman filter (EnKF) performance for a number of different EnKF configurations. The study is performed in a perfect-model context using the logistic map as forecast model. The focus is on EnKF performance when the ensemble is small. In accordance with theory, it is found that those configurations that maintain an appropriate ensemble spread are indeed those with the smallest ensemble mean error in a data assimilation cycle. Thus, the deficient ensemble spread produced by the single-ensemble EnKF results in increased ensemble mean error for this configuration. This problem with the conceptually simplest EnKF motivates an examination of a variety of other configurations. These include the configuration with a pair of ensembles and several configurations with overlapping ensembles, such as the four-subensemble configuration (used operationally at the Canadian Meteorological Centre) and the configuration in which observations are assimilated into each member using a gain computed from all of the other members. Also examined is a configuration that uses the jackknife estimator to obtain an estimate of the gain and an estimate of its uncertainty. Using these estimates, a different perturbed gain is then produced for each ensemble member. In general, it is found that these latter configurations outperform both the single-ensemble EnKF and the configuration with a pair of ensembles. In addition to these “stochastic” filters, the performance of a “deterministic” filter (which does not use perturbed observations) is also examined.

Beschreibung: Wind stress imposed on the upper ocean by a hurricane can limit the hurricane’s intensity primarily through shear-induced mixing of the upper ocean and subsequent cooling of the sea surface. Since shear-induced mixing is a one-dimensional process, some recent studies suggest that coupling a one-dimensional ocean model to a hurricane model may be sufficient for capturing the storm-induced sea surface temperature cooling in the region providing heat energy to the hurricane. Using both a one-dimensional and a three-dimensional version of the same ocean model, it is shown here that the neglect of upwelling, which can only be captured by a three-dimensional ocean model, underestimates the storm-core sea surface cooling for hurricanes translating at

Beschreibung: Tornadoes often strike as isolated events, but many occur as part of a major outbreak of tornadoes. Nontornadic outbreaks of severe convective storms are more common across the United States but pose different threats than do those associated with a tornado outbreak. The main goal of this work is to distinguish between significant instances of these outbreak types objectively by using statistical modeling techniques on numerical weather prediction output initialized with synoptic-scale data. The synoptic-scale structure contains information that can be utilized to discriminate between the two types of severe weather outbreaks through statistical methods. The Weather Research and Forecast model (WRF) is initialized with synoptic-scale input data (the NCEP–NCAR reanalysis dataset) on a set of 50 significant tornado outbreaks and 50 nontornadic severe weather outbreaks. Output from the WRF at 18-km grid spacing is used in the objective classification. Individual severe weather parameters forecast by the model near the time of the outbreak are analyzed from simulations initialized at 24, 48, and 72 h prior to the outbreak. An initial candidate set of 15 variables expected to be related to severe storms is reduced to a set of 6 or 7, depending on lead time, that possess the greatest classification capability through permutation testing. These variables serve as inputs into two statistical methods, support vector machines and logistic regression, to classify outbreak type. Each technique is assessed based on bootstrap confidence limits of contingency statistics. An additional backward selection of the reduced variable set is conducted to determine which variable combination provides the optimal contingency statistics. Results for the contingency statistics regarding the verification of discrimination capability are best at 24 h; at 48 h, modest degradation is present. By 72 h, the contingency statistics decline by up to 15%. Overall, results are encouraging, with probability of detection values often exceeding 0.8 and Heidke skill scores in excess of 0.7 at 24-h lead time.

Beschreibung: Rainfall characteristics and mesoscale properties of precipitation systems in mei-yu seasons over South China, Taiwan, and the South China Sea (SCS) during 1998–2007 are investigated in this study. Mei-yu rainbands are defined using the Tropical Rainfall Measuring Mission 3B42 rainfall product and then applied to divide the mei-yu season into the mei-yu and break periods. In the 10-yr “climatology,” on average, the mei-yu rainbands have a lifetime of 4–5 days and most frequently occur near the South China coast. During the mei-yu periods, rainfall maxima are found over the Pearl River Delta, the foothills of the Yun-Gui Plateau, and Wuyi Mountain, with the first two maxima corresponding to especially heavy rainfall. Intraseasonal variations on the convective structures, especially over land, are distinct among the mei-yu, break, pre-mei-yu, and post-mei-yu, based on analysis of convection intensity proxies and vertical radar reflectivity profiles of precipitation features. Lightning flash rates are consistent with the convective structure. The most frequent lightning over South China and Taiwan is in the pre-mei-yu and the least is during the mei-yu, which suggests different microphysical structures. Therefore, the discrimination of intraseasonal transitions on convective vertical structures may have important implications to the problems of cumulus parameterization, model validation, rainfall estimation, and latent heat retrievals. Intraseasonal variations of convective structures over the SCS are less evident than those over land. Storms over the SCS during the mei-yu are slightly convectively stronger than those in the break. Oceanic features with strong ice scattering have much lower lightning flash rates than their counterparts over land.