Management and display of four-dimensional environmental data sets using McIDAS

Over the past four years, great strides have been made in the areas of data management and display of 4-D meteorological data sets. A survey was conducted of available and planned 4-D meteorological data sources. The data types were evaluated for their impact on the data management and display system. The requirements were analyzed for data base management generated by the 4-D data display system. The suitability of the existing data base management procedures and file structure were evaluated in light of the new requirements. Where needed, new data base management tools and file procedures were designed and implemented. The quality of the basic 4-D data sets was assured. The interpolation and extrapolation techniques of the 4-D data were investigated. The 4-D data from various sources were combined to make a uniform and consistent data set for display purposes. Data display software was designed to create abstract line graphic 3-D displays. Realistic shaded 3-D displays were created. Animation routines for these displays were developed in order to produce a dynamic 4-D presentation. A prototype dynamic color stereo workstation was implemented. A computer functional design specification was produced based on interactive studies and user feedback

Ordinary kriging for on-demand average wind interpolation of in-situ wind sensor data

We have developed a domain agnostic ordinary kriging algorithm accessible via a standards-based service-oriented architecture for sensor networks. We exploit the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) standards. We need on-demand interpolation maps so runtime performance is a major priority.Our sensor data comes from wind in-situ observation stations in an area approximately 200km by 125km. We provide on-demand average wind interpolation maps. These spatial estimates can then be compared with the results of other estimation models in order to identify spurious results that sometimes occur in wind estimation.Our processing is based on ordinary kriging with automated variogram model selection (AVMS). This procedure can smooth time point wind measurements to obtain average wind by using a variogram model that reflects the wind phenomenon characteristics. Kriging is enabled for wind direction estimation by a simple but effective solution to the problem of estimating periodic variables, based on vector rotation and stochastic simulation.In cases where for the region of interest all wind directions span 180 degrees, we rotate them so they lie between 90 and 270 degrees and apply ordinary kriging with AVMS directly to the meteorological angle. Else, we transform the meteorological angle to Cartesian space, apply ordinary kriging with AVMS and use simulation to transform the kriging estimates back to meteorological angle.Tests run on a 50 by 50 grid using standard hardware takes about 5 minutes to execute backward transformation with a sample size of 100,000. This is acceptable for our on-demand processing service requirements

Parallel processing and non-uniform grids in global air quality modeling

A large-scale global air quality model, running efficiently on a single vector processor, is enhanced to make more realistic and more long-term simulations feasible. Two strategies are combined: non-uniform grids and parallel processing. The communication through the hierarchy of non-uniform grids interferes with the inter-processor communication. We discuss load balance in the decomposition of the domain, I/O, and inter-processor communication. A model shows that the communication overhead for both techniques is very low, whence non-uniform grids allow for large speed-ups and high speed-up can be expected from parallelization. The implementation is in progress, and results of experiments will be reported elsewhere

Valuing information from mesoscale forecasts

The development of meso-gamma scale numerical weather prediction (NWP) models requires a substantial investment in research, development and computational resources. Traditional objective verification of deterministic model output fails to demonstrate the added value of high-resolution forecasts made by such models. It is generally accepted from subjective verification that these models nevertheless have a predictive potential for small-scale weather phenomena and extreme weather events. This has prompted an extensive body of research into new verification techniques and scores aimed at developing mesoscale performance measures that objectively demonstrate the return on investment in meso-gamma NWP. In this article it is argued that the evaluation of the information in mesoscale forecasts should be essentially connected to the method that is used to extract this information from the direct model output (DMO). This could be an evaluation by a forecaster, but, given the probabilistic nature of small-scale weather, is more likely a form of statistical post-processing. Using model output statistics (MOS) and traditional verification scores, the potential of this approach is demonstrated both on an educational abstraction and a real world example. The MOS approach for this article incorporates concepts from fuzzy verification. This MOS approach objectively weighs different forecast quality measures and as such it is an essential extension of fuzzy methods

Data catalog series for space science and applications flight missions. Volume 4B: Descriptions of data sets from meteorological and terrestrial applications spacecraft and investigations

The main purpose of the data catalog series is to provide descriptive references to data generated by space science flight missions. The data sets described include all of the actual holdings of the Space Science Data Center (NSSDC), all data sets for which direct contact information is available, and some data collections held and serviced by foreign investigators, NASA and other U.S. government agencies. This volume contains narrative descriptions of data sets from meteorological and terrestrial applications spacecraft and investigations. The following spacecraft series are included: Mariner, Pioneer, Pioneer Venus, Venera, Viking, Voyager, and Helios. Separate indexes to the planetary and interplanetary missions are also provided

BOMEX bulletin, no. 7

Abstracts of BOMEX related conference papers, sample products from BOMEX cloud photography and radar surveillance, and status summaries of BOMEX data processing and reductio

Development of Distributed Research Center for analysis of regional climatic and environmental changes

We present an approach and first results of a collaborative project being carried out by a joint team of researchers from the Institute of Monitoring of Climatic and Ecological Systems, Russia and Earth Systems Research Center UNH, USA. Its main objective is development of a hardware and software platform prototype of a Distributed Research Center (DRC) for monitoring and projecting of regional climatic and environmental changes in the Northern extratropical areas. The DRC should provide the specialists working in climate related sciences and decision-makers with accurate and detailed climatic characteristics for the selected area and reliable and affordable tools for their in-depth statistical analysis and studies of the effects of climate change. Within the framework of the project, new approaches to cloud processing and analysis of large geospatial datasets (big geospatial data) inherent to climate change studies are developed and deployed on technical platforms of both institutions. We discuss here the state of the art in this domain, describe web based information-computational systems developed by the partners, justify the methods chosen to reach the project goal, and briefly list the results obtained so far