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A four-dimensional (4D) ensemble-variational data assimilation (DA) system (4DEnsVar) was developed, building upon the infrastructure of the gridpoint statistical interpolation (GSI)-based hybrid DA system. 4DEnsVar used ensemble perturbations valid at multiple time periods throughout the DA window to estimate 4D error covariances during the variational minimization, avoiding the tangent linear and adjoint of the forecast model. The formulation of its implementation in GSI was described. The performance of the system was investigated by evaluating the global forecasts and hurricane track forecasts produced by the NCEP Global Forecast System (GFS) during the 5-week summer period assimilating operational conventional and satellite data. The newly developed system was used to address a few questions regarding 4DEnsVar. 4DEnsVar in general improved upon its 3D counterpart, 3DEnsVar. At short lead times, the improvement over the Northern Hemisphere extratropics was similar to that over the Southern Hemisphere extratropics. At longer lead times, 4DEnsVar showed more improvement in the Southern Hemisphere than in the Northern Hemisphere. The 4DEnsVar showed less impact over the tropics. The track forecasts of 16 tropical cyclones initialized by 4DEnsVar were more accurate than 3DEnsVar after 1-day forecast lead times. The analysis generated by 4DEnsVar was more balanced than 3DEnsVar. Case studies showed that increments from 4DEnsVar using more frequent ensemble perturbations approximated the increments from direct, nonlinear model propagation better than using less frequent ensemble perturbations. Consistently, the performance of 4DEnsVar including both the forecast accuracy and the balances of analyses was in general degraded when less frequent ensemble perturbations were used. The tangent linear normal mode constraint had positive impact for global forecast but negative impact for TC track forecasts.

“Accessibility,” defined as the ease (or difficulty) with which opportunities for activity can be reached from a given location, can be measured with the cumulative amount of opportunities from an origin within a given amount of travel time. These indicators can be used in regional planning and modeling efforts to integrate land use and travel demand, and an attempt should be made to calculate these indicators for the smallest geographic area. The primary objective of this paper is to illustrate the creation of realistic space-sensitive and time-sensitive block-level accessibility indicators to track the availability of opportunities. These indicators support the development of an activity-based travel demand model by Southern California Association of Governments to provide second-by-second and parcel-by-parcel modeling and simulation. The indicators also provided the base information for mapping opportunities of access to 15 types of industries at different times during a day. The indicators and their maps were defined for the entire region of Southern California through largely available data that included the Census Transportation Planning Package, Dun & Brad-street postprocessed data, detailed highway networks and travel times from the four-step regional models, and arrival and departure times of workers by industry.

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