This PDF file contains the front matter associated with SPIE Proceedings Volume 6685, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

We introduce a formalism for computing the Cramer-Rao lower bound (CRLB) for a general dynamical system, develop an approach to bounding the process noise for a general dynamical system, and discuss the application of this formalism in the context of a prototypical forecasting model. This model consists of a simple transport diffusion process with assimilation updates based on point source measurements. We investigate the use of Krylov subspace techniques for efficient computation of two point correlation functions, and the use of this technique in generating a coarse-grained state covariance.

The preliminary steps of assimilating AIRS radiance data into a mesoscale model are presented. First, a stand-alone 1D-Var driver is developed in order to retrieve temperature and specific humidity profiles from AIRS data using background profiles obtained from a mesoscale model. Vertical background error covariance matrices are calculated for both temperature and specific humidity. The inverses of the background error covariance matrices are estimated using a singular value decomposition procedure, in which the small singular values and associated small-scale structures in the background error covariances are removed. By comparing with two available collocated radiosonde data, it is then shown that AIRS radiance-derived vertical profiles of temperature and specific humidity are more consistent to radiosonde observations than the background profiles. Finally, a multi-profile retrieval is performed which produced largest analysis increments of temperature and moisture in the region of a mid- and upper-level moisture gradient associated with a cold front.

By tracking a GPS satellite with an antenna of receivers, it is possible to estimate the difference between the satellite elevation angle and the actual arrival angle of the transmitted signal in the line of sight of the antenna. Those measurements are assimilated through the use of a fast ray-tracing observation operator and its adjoint into a high resolution version of the Weather Research and Forecast model. Such assimilation has the potential to improve the description and prediction of the local refractivity field, through improved pressure, temperature and humidity, around the antenna.

A three-dimensional variational data assimilation (3DVAR) system (ROMS3DAR) has been developed in the framework of the Regional Ocean Modeling System (ROMS). This system enables the capability of predicting meso- to small-scale variations with temporal scales from hours to days in the coastal oceans. To cope with the particular difficulties that result from complex coastlines and bottom topography, unbalanced flows and sparse observations, ROMS3DVAR utilizes several novel strategies. These strategies include the implementation of three-dimensional anisotropic and inhomogeneous error correlations, application of particular weak dynamic contraints, and implementation of efficient and reliable algorithms for minimizing the cost function. ROMS3DVAR has been implemented in a quasi-real-time fashion in support of both the Southern and Central California Coastal Ocean Observing System (SCCOOS and CenCOOS). ROMS3DVAR assimilates a variety of observations, including satellite sea surface temperatures and sea surface heights, High Frequency (HF) radar velocities, ship reports and other available temperature and salinity profiles. The evaluation showed useful forecast skills.

Surface current observations made by high-frequency radar in the Monterey Bay region during August 2003 are assimilated using a three-dimensional variational data assimilation scheme developed for the Regional Ocean Modeling System (ROMS-DAS). The observed upwelling and relaxation surface currents in Monterey Bay are well recovered in the analysis. A new mapping method based on ROMS-DAS is also proposed. This method is based on a variational algorithm for the calculation of stream function and velocity potential from given velocity fields, and has the ability to interpolate vectors over any irregular domain.

We present the first results of the assimilation of ocean colour datasets into coastal ocean biogeochemical models for the tropical Fitzroy Estuary and Keppel Bay system (FEKB) contingent to the Great Barrier Reef lagoon. As part of the Great Barrier Reef Monitoring Program, a regional algorithm for operational delivery of valid coastal ocean colour products was recently developed for FEKB. A new generation of regional specific algorithm for the FEKB system had to be developed for large satellite datasets of the MODIS sensors as the global algorithms failed. Concurrently, a biogeochemical model was developed for the system, built upon a three-dimensional hydrodynamic and sediment dynamic model, and simulating nitrogen and phosphorus dynamics including the dynamics of dissolved organic material as well as pelagic and benthic primary production. One of the aims was to provide estimates of material fluxes from Keppel Bay to the Great Barrier Reef Lagoon. The biogeochemical model was run first with fixed boundary conditions based on the limited in situ measurements, then with boundary conditions derived from satellite datasets using the region-specific algorithm. Several methodologies for linking of remote sensing observations to model variables were evaluated over a period of one year (2004). When remote sensing information was used to inform the boundaries, estimates of material fluxes in the model changed substantially in magnitude and direction.

The Pacific Ocean deep sea height data around latitude 20 N from Jason-1 satellite was analyzed in terms of standard deviation (std) and fractal dimension during a 90-day period that included the coronal mass ejection event of 2003 Oct 29 where a peak solar energetic particles of about 30,000 pfu was measured. The surface height standard deviation series was observed to have two peaks that corresponded to two typhoon events of Oct 25 and Nov 26, 2003. The cross correlation of the height-std series and average-height series showed a positive correlation with time delay. The fractal dimension of the height series peaked on Nov 1 (fractal dimension ~1.96 with a background 90-day average of ~ 1.81) and no corresponding peak was observed in the other time series data. Computer simulation of the fractal dimension of a finite random series suggested a standard deviation of about 0.071. Annual and long-term trends of the fractal dimensions were also found and investigated. The possible contribution of coronal mass ejection to the surface height series fractal dimension and the height correlation to chlorophyll were discussed.

Important issues involving the assimilation of rain-affected observations using an adjoint mesoscale modeling system are addressed in this study. The adjoint model of the explicit moist physics parameterization is included in the modeling system, which allows for the calculation of gradients with respect to the initial hydrometeor concentrations (cloud water/ice, rain, snow, and graupel). Cloud-scale idealized four dimensional variational data assimilation experiments demonstrate the benefit of assimilating precipitation information and the ability of the adjoint model to produce useful gradients with respect to the hydrometeor fields. The agreement between model fields and observations is greater (especially for the early forecast hydrometeor fields) when rainy observations are incorporated into the assimilation process versus only assimilating conventional model data (windspeeds, temperature, pressure). Additional data assimilation experiments are conducted with microwave radiances. These data improve the initial precipitation structure of a tropical cyclone. These experiments are promising steps for the incorporation of rain-affected observations in operational data assimilation systems.

New satellite observations reveal several distinct features of the South China Sea (SCS) summer climate: an intense low-level southwesterly wind jet off the coast of south Vietnam, a precipitation band on the western flank of the north-south running Annam mountain range, and a rainfall shadow to the east in the western SCS off the east coast of Vietnam. A high-resolution full-physics regional atmospheric model is used to investigate the mechanism for the formation of SCS summer climate. A comparison of the control model simulation with a sensitivity experiment with the mountain range artificially removed demonstrates that the aforementioned features form due to orographic effects of the Annam mountains. Under the prevailing southwesterly monsoon, the mountain range forces the ascending motion on the windward and subsidence on the lee side, giving rise to bands of active and suppressed convection, respectively. On the south edge of the mountain range, the southwesterlies are accelerated to form an offshore low-level wind jet. The mid-summer cooling in the SCS induced by this wind jet further helps reduce precipitation over the central SCS. A reduced-gravity ocean model is used to investigate the ocean response to the orographically induced wind forcing, which is found to be important for the formation of the double-gyre circulation observed in the summer in SCS, in particular for the northern cyclonic circulation. Thus, orography is a key to shaping the SCS summer climate both in the atmosphere and in the ocean.

Correlation analysis and accumulated anomaly as statistical approaches are employed to investigate the relationship between the western Pacific subtropical high (sub-high for short) and May-June precipitation (MJP) in Fujian and, moreover, NCEP/NCAR reanalysis-calculated vertical integration of transported vapor are used to make a comparative study on differences in circulation and element fields between dry and wet years for May-June in the project province. Results show that 1) the situation of the sub-high weaker than mean and southward of normal favors excessive MJP in Fujian. In dry years the western Pacific positive SSTA area that intensifies the sub-high is to the south of Japan, leading to the sub-high stronger in comparison to normal and northward of mean while in wet years the sub-high takes a more southern position due to the western Pacific 10-25°N SST higher with respect to normal; 2) in dry (wet) years SW warm, moist air is considerably weakened (reinforced) for South China including Fujian. However, the upper-level strengthened SW air-transported vapor arrives at Fujian predominantly via the turning of easterly flows from the south side of the sub-high, a new discovery worthy of further research for understanding the role of warm, wet air originating from the Bay of Bengal in MJP forecasts over the study region.

GRAPES (Global and Regional Assimilation Prediction System) is the Chinese new generation numerical weather prediction (NWP) system which has been operational run in the national operational NWP centers. However, sparseness of conventional data is the biggest challenge in upgrading NWP in China. Application of satellite observations is the most effective way to solve the problem of data sparseness, therefore the assimilation of satellite data into GRAPES analysis system is the first priority in the development of GRAPES model. In this paper we show the effects of assimilating satellite remote sensing data into GRAPES-3DVar (three-dimensional variational assimilation system) for a landing typhoon precipitation process in the east of China in 2006. The typhoon case is named Bilis, which landed in Fujian province on July 14 2006 and caused a prolonged and intense precipitation. Typhoon Bilis affected China for 120 hours since it landed, which is unusual in the history of China. In the end, the simulation of precipitation process associated with typhoon Bilis using GRAPES-Meso is also showed, and the performance of GRAPES is evaluated.

A GPS retrieval algorithm is developed for obtaining in-cloud vertical profiles of the atmospheric state from Global Positioning System (GPS) radio occultation (RO) data, using MODIS (Moderate Resolution Imaging Spectroradiometer) cloud-top pressure and cloud-top temperature as auxiliary information. The cloud-base height is estimated based on the vertical distributions of density scale height, temperature lapse rate and relative humidity using GPS wet retrievals. The proposed algorithm is tested upon 31 cloudy GPS RO profiles from Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC). It is found that the retrieval temperature is warmer than NCEP-reanalysis in the upper levels of the cloud and colder near and below the cloud base. Dropsonde observations for Hurricane Rita confirm this characteristic feature of the NCEP temperature analysis within clouds. The cloud thickness and cloud-base height that are determined by the proposed criteria are validated qualitatively with IR and VIS satellite images. Sensitivity of the GPS in-cloud profile retrieval to the MODIS cloud top pressure is also shown.