The sensitivity of forecasts to observations is evaluated using an ensemble approach with data drawn from a pseudo-operational ensemble Kalman filter. For Gaussian statistics and a forecast metric defined as a scalar function of the forecast variables, the effect of observations on the forecast metric is quantified by changes in the metric mean and variance. For a single observation, expressions for these changes involve a product of scalar quantities, which can be rapidly evaluated for large numbers of observations. This tech-nique is applied to determining climatological forecast sensitivity and predicting the impact of observations on sea level pressure and precipitation forecast metrics. The climatological 24-h forecast sensitivity of the average pressure over western Washington State shows a region of maximum sensitivity to the west of the region, which tilts gently westward with height. The accuracy of ensemble sensitivity predictions is tested by withholding a single buoy pressure observation from this region and comparing this perturbed forecast with the control case where the buoy is assimilated. For 30 cases, there is excellent agreement between these forecast differences and the ensemble predictions, as measured by the forecast metric. This agreement decreases for increasing numbers of observations. Nevertheless, by using statistical confidence tests to address sampling error, the impact of thousands of observations on forecast-metric variance is shown to be well estimated by a subset of the O(100) most significant observations.

Ensemble Kalman filter (EnKF) data assimilation experiments are conducted on a limited-area domain over the Pacific Northwest region of the United States, using the Weather Research and Forecasting model. Idealized surface pressure, radiosoundings, and aircraft observations are assimilated every 6 h for a 7-day period in January 2004. The objectives here are to study the performance of the filter in constraining analysis errors with a relatively inhomogeneous, sparse-observation network and to explore the potential for such a network to serve as the basis for a real-time EnKF system dedicated to the Pacific Northwest region of the United States. When only a single observation type is assimilated, results show that the ensemble-mean analysis error and ensemble spread (standard deviation) are significantly reduced com-pared to a control ensemble without assimilation for both observed and unobserved variables. Analysis errors are smaller than background errors over nearly the entire domain when averaged over the 7-day period. Moreover, comparisons of background errors and observation increments at each assimilation step suggest that the flow-dependent filter corrections are accurate in both scale and amplitude. An illustrative example concerns a misspecified mesoscale 500-hPa short-wave trough moving along the British Columbia coast, which is corrected by surface pressure observations alone. The relative impact of each observation type upon different variables and vertical levels is also discussed. 1.

Abstract not found

A foehn wind is a warm, dry, downslope wind resulting from synoptic-scale, cross-barrier flow over a mountain range. Foehn winds are a climatological

According to observations of hurricanes located relatively close to the land, intense and persistent lightning takes place within a 250–300-km radius ring around the hurricane center, whereas the lightning activity in the eyewall takes place only during comparatively short periods usually attributed to eyewall replacement. The mechanism responsible for the formation of the maximum flash density at the tropical cyclone (TC) periphery is not well understood as yet. In this study it is hypothesized that lightning at the TC periphery arises under the influence of small continental aerosol particles (APs), which affect the microphysics and the dynamics of clouds at the TC periphery. To show that aerosols change the cloud microstructure and the dynamics to foster lightning formation, the authors use a 2D mixed-phase cloud model with spectral microphysics. It is shown that aerosols that penetrate the cloud base of maritime clouds dramatically increase the amount of supercooled water, as well as the ice contents and vertical velocities. As a result, in clouds developing in the air with high AP concentration, ice crystals, graupel, frozen drops and/or hail, and supercooled water can coexist within a single cloud zone, which allows collisions and charge separation. The simulation of possible aerosol effects on the landfalling tropical cyclone has been carried out using a 3-km-resolution Weather Research and Forecast (WRF) mesoscale model. It is shown that aerosols change the cloud microstructure in a way that permits the attribution of the observed lightning structure to the effects of continental aerosols. It is also shown that aerosols, which invigorate clouds at 250–300 km from the TC center, decrease the convection intensity in the TC center, leading to some TC weakening. The results suggest that aerosols change the intensity and the spatial distribution of precipitation in landfalling TCs and can possibly contribute to the weekly cycle of the intensity and precipitation of landfalling TCs. More detailed investigations of the TC–aerosol interaction are required. 1.

The climate is changing—that is now indisputable. There is a scientific consensus that the world is becoming a warmer place principally attributable to human activities. In the words of the Intergovernmental Panel on Climate Change (IPCC) in its fourth assessment report: “Warming of the climate system is unequivocal. ” 1 For nearly 1 million years before the Industrial Revolution, the carbon dioxide (CO 2) concentration in the atmosphere ranged between 170 and 280 parts per million (ppm). Levels are now far above that range—387 ppm—higher than the highest point in at least the past 800,000 years, and the rate of increase may be accelerating. 2 Under high-emissions scenarios, concentrations by the end of the 21st century could exceed those experienced on the planet for tens of millions of years. Article 2 of the United Nations Framework Convention on Climate Change sets the objective of achieving a “stabilization of greenhouse gas emissions at a level that would prevent dangerous anthropogenic interference with the climate system. ” 3 To the extent that avoiding “dangerous ” interference

Commission Contract No. 500-02-004 Commission Work Authorization No: MR-036

9 The performance of five boundary layer parameterizations in the Weather Research and Forecasting model is examined for marine boundary layer cloud regions using a single column model version of the WRF model. Most parameterizations show a poor agreement of the vertical boundary layer structure when compared with Large-Eddy Simulation models. These comparisons against Large-Eddy Simulation show that a parameterization based on the Eddy-Diffusivity/Mass-Flux approach provides a better performance. The results also illustrate the key role of boundary layer parameterizations in model performance.

a tsunami struck the southern coast of Java, Indonesia, causing over 730 casualties. The triggering earthquake located 225 km off the coast of Pan-gandaran (9.222 ◦ S, 107.320 ◦ E), occurred at 15:19 LT (UTC +7) with a 7.7 magnitude on the Richter scale (Harward Cen-ter and CEA/DAM). In order to calibrate numerical models and understand the phenomenon, we conducted a 6-weeks field survey in July and August 2006 from Cimerak district in West Java to Gunung Kidul district in Central Java. Data collection involved measurements of wave height before its breaking, flow depth, run-up height, inundation depth, flow directions and a detailed chronology of the tsunami. Eyewitnesses accounted for three main waves. The max-imum height of the second wave ranged from 4.2 to 8.6 m before its breaking. Maximum flow depth after the wave’s breaking reached 5 m, and maximum runup heights reached 15.7 m. Our run-up values are about 1.5 higher than those obtained by the other field surveys carried out until present. They are also higher than the values computed through pre-liminary models. The 17 July 2006 tsunami has been generated by a “tsunami earthquake”, i.e. an earthquake of low or medium scale that triggers a tsunami of high magnitude. The run-up heights progressively decreased eastwards, which is consis-tent with a tsunami triggered by fault dislocation, as the one that hit the Nicaragua’s coast with similar run-up heights on the 2 September 1992. An earthquake with associated land-slides could also have generated the 17 July 2006 tsunami, as ever observed in Papua-New-Guinea in 1998.

The impacts of assimilating radar data and other mesoscale observations in real-time, convection-allowing model forecasts were evaluated during the spring seasons of 2008 and 2009 as part of the HazardousWeather Test Bed Spring Experiment activities. In tests of a prototype continental U.S.-scale forecast system, focusing primarily on regions with active deep convection at the initial time, assimilation of these observations had a positive impact. Daily interrogation of output by teams of modelers, forecasters, and verification experts provided additional insights into the value-added characteristics of the unique assimilation forecasts. This evaluation revealed that the positive effects of the assimilation were greatest during the first 3–6 h of each forecast, appeared to be most pronounced with larger convective systems, and may have been related to a phase lag that sometimes developed when the convective-scale information was not assimilated. These preliminary results are currently being evaluated further using advanced objective verification techniques. 1.