ALBERT

Description: The first flash produced by a storm usually does not strike ground, but little has been published concerning the time after the first flash before a cloud-to-ground flash occurs, particularly for a variety of climatological regions. To begin addressing this issue, this study analyzed data from very-high-frequency (VHF) lightning mapping systems, which detect flashes of all types, and from the U.S. National Lightning Detection Network (NLDN), which identifies flash type and detects roughly 90% of cloud-to-ground flashes overall. VHF mapping data were analyzed from three regions: north Texas, Oklahoma, and the high plains of Colorado, Kansas, and Nebraska. The percentage of storms in which a cloud-to-ground flash was detected in the first minute of lightning activity varied from 0% in the high plains to 10%–20% in Oklahoma and north Texas. The distribution of delays to the first cloud-to-ground flash varied similarly. In Oklahoma and north Texas, 50% of storms produced a cloud-to-ground flash within 5–10 min, and roughly 10% failed to produce a cloud-to-ground flash within 1 h. In the high plains, however, it required 30 min for 50% of storms to have produced a cloud-to-ground flash, and 20% produced no ground flash within 1 h. The authors suggest that the reason high plains storms take longer to produce cloud-to-ground lightning is because the formation of the lower charge needed to produce most cloud-to-ground flashes is inhibited either by delaying the formation of precipitation in the mid- and lower levels of storms or by many of the storms having an inverted-polarity electrical structure.

Description: Foehn wind blowing through the Kolkhida (Kolkheti) Lowland in the southwestern Caucasus (western Georgia) was observed on an Envisat synthetic aperture radar (SAR) image as it encountered an atmospheric cyclonic eddy over the Black Sea on 13 September 2010. This SAR image reveals unprecedented finescale features of the near-surface wind fields that cannot be resolved by other sensors. It shows, among others, the deflection of the foehn wind by the atmospheric eddy. Quantitative information on the near-surface wind field over the sea is extracted from the SAR image.

Description: Advanced Microwave Sounding Unit A (AMSU-A) observation-error covariances are objectively estimated by comparing satellite radiances with radiosonde data. Channels 6–8 are examined as being weakly dependent on the surface and on the stratosphere above the radiosonde top level. Significant horizontal, interchannel, temporal, and intersatellite correlations are found. Besides, cross correlations between satellite and forecast (background) errors (largely disregarded in practical data assimilation) proved to be far from zero. The directional isotropy hypothesis is found to be valid for satellite error correlations. Dependencies on the scan position, the season, and the satellite are also checked. Bootstrap simulations demonstrate that the estimated covariances are statistically significant. The estimated correlations are shown to be caused by the satellite errors in question and not by other (nonsatellite) factors.

Description: The response of sea surface temperature (SST) to tropical cyclones is studied using gridded SST data and global cyclone tracks from the period 1981–2008. A compositing approach is used whereby temperature time series before and after cyclone occurrence at individual cyclone track positions are averaged together. Results reveal a variability of several days in the time of maximum cooling with respect to cyclone passage, with the most common occurrence 1 day after cyclone passage. When compositing is carried out relative to the day of maximum cooling, the global average response to cyclone passage is a local minimum SST anomaly of −0.9°C. The recovery of the ocean to cyclone passage is generally quite rapid with 44% of the data points recovering to climatological SST within 5 days, and 88% of the data points recovering within 30 days. Although differences exist between the mean results from the separate tropical cyclone basins, they are in broad agreement with the global mean results. Storm intensity and translation speed affect both the size of the SST response and the recovery time. Cyclones occurring in the first half of the cyclone season disrupt the seasonal warming trend, which is not resumed until 20–30 days after cyclone passage. Conversely, cyclone occurrences in the later half of the season bring about a 0.5°C temperature drop from which the ocean does not recover due to the seasonal cooling cycle.

Description: This study investigates the impact of abnormally moist soil conditions across the southern Great Plains upon the overland reintensification of North Atlantic Tropical Cyclone Erin (2007). This is tested by analyzing the contributions of three soil moisture–related signals—a seasonal signal, an along-track rainfall signal, and an early postlandfall rainfall signal—to the intensity of the vortex. In so doing, a suite of nine convection-permitting numerical simulations using the Advanced Research Weather Research and Forecasting model (WRF-ARW) is used. Of the signals tested, soil moisture contributions from the anomalously wet months preceding Erin are found to have the greatest positive impact upon the intensity of the vortex, though this impact is on the order of that from climatological soil moisture conditions. The greatest impact of the early rainfall signal contributions is found when it is added to the seasonal signal. Along-track rainfall during the simulation period has a minimal impact. Variations in soil moisture content result in impacts upon the boundary layer thermodynamic environment via boundary layer mixing. Greater soil moisture content results in weaker mixing, a shallower boundary layer, and greater moisture and instability. Differences in the intensity of convection that develops and its accompanying latent heat release aloft result in greater warm-core development and surface vortex intensification within the simulations featuring greater soil moisture content. Implications of these findings to the tropical cyclone development process are discussed. Given that the reintensification is shown to occur in, apart from land, an otherwise favorable environment for tropical cyclone development and results in a vortex with a structure similar to developing tropical cyclones, these findings provide new insight into the conditions under which tropical cyclones develop.

Description: Twenty-member real-time convection-allowing storm-scale ensemble forecasts with perturbations to model physics, dynamics, initial conditions (IC), and lateral boundary conditions (LBC) during the NOAA Hazardous Weather Testbed Spring Experiment provide a unique opportunity to study the relative impact of different sources of perturbation on convection-allowing ensemble diversity. In Part II of this two-part study, systematic similarity/dissimilarity of hourly precipitation forecasts among ensemble members from the spring season of 2009 are identified using hierarchical cluster analysis (HCA) with a fuzzy object-based threat score (OTS), developed in Part I. In addition to precipitation, HCA is also performed on ensemble forecasts using the traditional Euclidean distance for wind speed at 10 m and 850 hPa, and temperature at 500 hPa. At early lead times (3 h, valid at 0300 UTC) precipitation forecasts cluster primarily by data assimilation and model dynamic core, indicating a dominating impact of models, with secondary clustering by microphysics. There is an increasing impact of the planetary boundary layer (PBL) scheme on clustering relative to the microphysics scheme at later lead times. Forecasts of 10-m wind speed cluster primarily by the PBL scheme at early lead times, with an increasing impact of LBC at later lead times. Forecasts of midtropospheric variables cluster primarily by IC at early lead times and LBC at later lead times. The radar and Mesonet data assimilation (DA) show its impact, with members without DA in a distinct cluster, through the 12-h lead time (valid at 1200 UTC) for both precipitation and nonprecipitation variables. The implication for optimal ensemble design for storm-scale forecasts is also discussed.

Description: Convection-allowing ensemble forecasts with perturbations to model physics, dynamics, and initial (IC) and lateral boundary conditions (LBC) generated by the Center for the Analysis and Prediction of Storms for the NOAA Hazardous Weather Testbed (HWT) Spring Experiments provide a unique opportunity to understand the relative impact of different sources of perturbation on convection-allowing ensemble diversity. Such impacts are explored in this two-part study through an object-oriented hierarchical cluster analysis (HCA) technique. In this paper, an object-oriented HCA algorithm, where the dissimilarity of precipitation forecasts is quantified with a nontraditional object-based threat score (OTS), is developed. The advantages of OTS-based HCA relative to HCA using traditional Euclidean distance and neighborhood probability-based Euclidean distance (NED) as dissimilarity measures are illustrated by hourly accumulated precipitation ensemble forecasts during a representative severe weather event. Clusters based on OTS and NED are more consistent with subjective evaluation than clusters based on traditional Euclidean distance because of the sensitivity of Euclidean distance to small spatial displacements. OTS improves the clustering further compared to NED. Only OTS accounts for important features of precipitation areas, such as shape, size, and orientation, and OTS is less sensitive than NED to precise spatial location and precipitation amount. OTS is further improved by using a fuzzy matching method. Application of OTS-based HCA for regional subdomains is also introduced. Part II uses the HCA method developed in this paper to explore systematic clustering of the convection-allowing ensemble during the full 2009 HWT Spring Experiment period.

Description: The ensemble Kalman filter is now an important component of ensemble forecasting. While using the linear relationship between the observation and state variables makes it applicable for large systems, relying on linearity introduces nonnegligible bias since the true distribution will never be Gaussian. This paper analyzes the bias of the ensemble Kalman filter from a statistical perspective and proposes a debiasing method called the nonlinear ensemble adjustment filter. This new filter transforms the forecast ensemble in a statistically principled manner so that the updated ensemble has the desired mean and variance. It is also easily localizable and, hence, potentially useful for large systems. Its performance is demonstrated and compared with other Kalman filter and particle filter variants through various experiments on the Lorenz-63 and Lorenz-96 systems. The results show that the new filter is stable and accurate for challenging situations such as nonlinear, high-dimensional systems with sparse observations.

Description: A flight-level aircraft dataset consisting of 79 Atlantic basin hurricanes from 1977 to 2007 was used to develop an unprecedented climatology of inner-core intensity and structure changes associated with eyewall replacement cycles (ERCs). During an ERC, the inner-core structure was found to undergo dramatic changes that result in an intensity oscillation and rapid broadening of the wind field. Concentrated temporal sampling by reconnaissance aircraft in 14 of the 79 hurricanes captured virtually the entire evolution of 24 ERC events. The analysis of this large dataset extends the phenomenological paradigm of ERCs described in previous observational case studies by identifying and exploring three distinct phases of ERCs: intensification, weakening, and reintensification. In general, hurricanes intensify, sometimes rapidly, when outer wind maxima are first encountered by aircraft. The mean locations of the inner and outer wind maximum at the start of an ERC are 35 and 106 km from storm center, respectively. The intensification rate of the inner wind maximum begins to slow and the storm ultimately weakens as the inner-core structure begins to organize into concentric rings. On average, the inner wind maximum weakens 10 m s−1 before the outer wind maximum surpasses the inner wind maximum as it continues to intensify. This reintensification can be quite dramatic and often brings the storm to its maximum lifetime intensity. The entire ERC lasts 36 h on average. Comparison of flight-level data and microwave imagery reveals that the first appearance of an outer wind maximum, often associated with a spiral rainband, typically precedes the weakening of the storm by roughly 9 h, but the weakening is already well under way by the time a secondary convective ring with a well-defined moat appears in microwave imagery. The data also show that winds beyond the outer wind maximum remain elevated even after the outer wind maximum contracts inward. Additionally, the contraction of the outer wind maximum usually ceases at a radius larger than the location of the inner wind maximum at the start of the ERC. The combination of a larger primary eyewall and expanded outer wind field increase the integrated kinetic energy by an average of 28% over the course of a complete ERC despite little change in the maximum intensity between the times of onset and completion of the event.

Description: Since April 2007, the numerical weather prediction model, COSMO (Consortium for Small Scale Modelling), has been used operationally in a convection-permitting configuration, named COSMO-DE, at the Deutscher Wetterdienst (DWD; German weather service). Here the authors discuss the model changes that were necessary for the convective scale, and report on the experience from the first years of operational application of the model. For COSMO-DE the ability of the numerical solver to treat small-scale structures has been improved by using a Runge–Kutta method, which allows for the use of higher-order upwind advection schemes. The one-moment cloud microphysics parameterization has been extended by a graupel class, and adaptations for describing evaporation of rain and stratiform precipitation processes were made. Comparisons with a much more sophisticated two-moment scheme showed only minor differences in most cases with the exception of strong squall-line situations. Whereas the deep convection parameterization was switched off completely, small-scale shallow convection was still parameterized by the appropriate part of the Tiedtke scheme. During the first year of operational use, convective events in synoptically driven situations were satisfactorily simulated. Also the daily cycles of summertime 10-m wind and 1-h precipitation sums were well captured. However, it became evident that the boundary layer description had to be adapted to enhance convection initiation in airmass convection situations. Here the asymptotic Blackadar length scale l∞ had proven to be a sensitive parameter.