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In 2011, the National Oceanic and Atmospheric Administration (NOAA) began a cooperative initiative with the academic community to help address a vexing issue that has long been known as a disconnection between the operational and research realms for weather forecasting and data assimilation. The issue is the gap, more exotically referred to as the “valley of death,” between efforts within the broader research community and NOAA’s activities, which are heavily driven by operational constraints. With the stated goals of leveraging research community efforts to benefit NOAA’s mission and offering a path to operations for the latest research activities that support the NOAA mission, satellite data assimilation in particular, this initiative aims to enhance the linkage between NOAA’s operational systems and the research efforts. A critical component is the establishment of an efficient operations-to-research (O2R) environment on the Supercomputer for Satellite Simulations and Data Assimilation Studies (S4). This O2R environment is critical for successful research-to-operations (R2O) transitions because it allows rigorous tracking, implementation, and merging of any changes necessary (to operational software codes, scripts, libraries, etc.) to achieve the scientific enhancement. So far, the S4 O2R environment, with close to 4,700 computing cores (60 TFLOPs) and 1,700-TB disk storage capacity, has been a great success and consequently was recently expanded to significantly increase its computing capacity. The objective of this article is to highlight some of the major achievements and benefits of this O2R approach and some lessons learned, with the ultimate goal of inspiring other O2R/R2O initiatives in other areas and for other applications.

The objective of this study is to investigate the quality of clouds simulated by the National Centers for Environmental Prediction global forecast system (GFS) model and to examine the causes for some systematic errors seen in the simulations through use of satellite and ground-based measurements. In general, clouds simulated by the GFS model had similar spatial patterns and seasonal trends as those retrieved from passive and active satellite sensors, but large systematic biases exist for certain cloud regimes especially underestimation of low-level marine stratocumulus clouds in the eastern Pacific and Atlantic oceans. This led to the overestimation (underestimation) of outgoing longwave (shortwave) fluxes at the top-of-atmosphere. While temperature profiles from the GFS model were comparable to those obtained from different observational sources, the GFS model overestimated the relative humidity field in the upper and lower troposphere. The cloud condensed water mixing ratio, which is a key input variable in the current GFS cloud scheme, was largely underestimated due presumably to excessive removal of cloud condensate water through strong turbulent diffusion and/or an improper boundary layer scheme. To circumvent the problem associated with modeled cloud mixing ratios, we tested an alternative cloud parameterization scheme that requires inputs of atmospheric dynamic and thermodynamic variables. Much closer agreements were reached in cloud amounts, especially for marine stratocumulus clouds. We also evaluate the impact of cloud overlap on cloud fraction by applying a linear combination of maximum and random overlap assumptions with a de-correlation length determined from satellite products. Significantly better improvements were found for high-level clouds than for low-level clouds, due to differences in the dominant cloud geometry between these two distinct cloud types.

Experimental weather forecasts at the Joint Center for Satellite Data Assimilation (JCSDA) using Atmospheric Infrared Sounder (AIRS) radiance observations indicate significant improvements in global forecast skill compared with the operational system without AIRS data. The improvement in forecast skill at six days is equivalent to gaining an extension of forecast capability of several hours. This magnitude of improvement is quite significant when compared with the rate of general forecast improvement over the last decade. A several hour increase in forecast range at five or six days normally takes several years to achieve at operational weather centers.

BCTMP has emerged as a significant market pulp in the last 10 years. From it's introduction in the late 1970's as a supplement to integrated mechanical pulps for use in newsprint, it has established a significant position in the furnish of a number of paper products around the world.The introduction of any new product in any industry is always accompanied by a resistance to change by users, rapid technological developments in both the production process and in the application and lingering hangovers from early failures. This has certainly characterised the history of market BCTMP.The success of BCTMP in the last 10 years in overcoming these obstacles has been due to a number of factors including : -Development of a number of new grades specifically designed for particular end uses-The use of species new to BCTMP-Focus on the functional advantages that BCTMP can bring to paper that other fibres can not match-Improvements in consistency of quality-Improvements in the BCTMP process which have lead to a greater members of products and lower production costs-Lowering or removal of North American barriers in paper specifications and standards-Continuing growth of user awareness resulting from BCTMP producers marketing effortsBCTMP is now well positioned for the future as a dynamic, low cost fibre, capable of meeting the rapidly changing demands of the worlds paper industry.

GSM is a series of standards defining various aspects of mobile voice and data communications. These standards provide a framework that looks set to underlie modern mobile business communications well into the 21st century.

International audience; This paper describes the Heterodyne Instrument for the Far-Infrared (HIFI), to be launched onboard of ESA's Herschel Space Observatory, by 2008. It includes the first results from the instrument level tests. The instrument is designed to be electronically tuneable over a wide and continuous frequency range in the Far Infrared, with velocity resolutions better than 0.1 km/s with a high sensitivity. This will enable detailed investigations of a wide variety of astronomical sources, ranging from solar system objects, star formation regions to nuclei of galaxies. The instrument comprises 5 frequency bands covering 480-1150 GHz with SIS mixers and a sixth dual frequency band, for the 1410-1910 GHz range, with Hot Electron Bolometer Mixers (HEB). The Local Oscillator (LO) subsystem consists of a dedicated Ka-band synthesizer followed by 7 times 2 chains of frequency multipliers, 2 chains for each frequency band. A pair of Auto-Correlators and a pair of Acousto-Optic spectrometers process the two IF signals from the dual-polarization front-ends to provide instantaneous frequency coverage of 4 GHz, with a set of resolutions (140 kHz to 1 MHz), better than < 0.1 km/s. After a successful qualification program, the flight instrument was delivered and entered the testing phase at satellite level. We will also report on the pre-flight test and calibration results together with the expected in-flight performance.

The National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Administration (NOAA), and Department of Defense (D oD), Joint Center for Satellite Data Assimilation (JCSDA) was established in 2000/2001. The goal of the JCSDA is to accelerate the use of observations from earth-orbiting satellites into operational numerical environmental analysis and prediction systems for the purpose of improving weather and oceanic forecasts, seasonal climate forecasts and the accuracy of climate data sets. As a result, a series of data assimilation experiments were undertaken at the JCSDA as part of the preparations for the operational assimilation of AIRS data by its partner organizations 1,2 . Here, for the first time full spatial reso lution radiance data, availab le in real-time from th e AIRS instrument, were used at the JCSDA in data assimilation studies over the globe utilizing the operational NCEP Global Forecast System (GFS). The radiance data from each channel of the instrument were carefully screened for cloud effects and those radiances which were deemed to be clear of cloud effects were used by the GFS forecast system. The result of these assimilation trials has been a first demonstration of significant improvements in forecast skill over both the Northern and Southern Hemisphere compared to the operational system without AIRS data. The experi mental system was designed in a way that rendered it feasible for operational app lication, and that constraint involved us ing the subset of AIRS channels chosen for operational distribution and an analysis methodology close to the current analysis practice, with particular consideration given to time limitations. As a result, operational application of these AIRS data was enabled by the recent NCEP operational upgrade. In addition, because of the improved impact resulting from use of this enhanced d ata set compared to that used operati onally to date, provision of a real-time “warmest field” of view data set has been est ablished for use by international NWP Centers. Keywords: AIRS, data assimilation, satellite meteorology

Full spatial resolution AIRS hyperspectral data have been used in a data assimilation study over the globe utilizing the operational NCEP Global Forecast System (GFS). The result of this assimilation trial has been significant improvements in forecast skill over the Southern Hemisphere and improvement over the Northern Hemisphere.

One of the inherent difficulties in writing a book about work with children with complex emotional and behavioural difficulties is choosing what to say and what to leave out, short of writing a boo...

AMERICAN METEOROLOGICAL SOCIETY | 891 AFFILIATIONS : LE MARSHALL, JUNG, DERBER, TREADON, LORD, GOLDBERG, WOLF, LIU, JOINER, WOOLLEN, TODLING, VAN DELST, AND TAHARA—NASA, NOAA, and U.S. Department of Defense Joint Center for Satellite Data Assimilation, Camp Springs, Maryland; CHAHINE—NASA Jet Propulsion Laboratory, Pasadena, California CORRESPONDING AUTHOR: John Le Marshall, Joint Center for Satellite Data Assimilation, NOAA Science Center, 5200 Auth Road, Camp Springs, MD 20746 E-mail: John.Lemarshall@noaa.gov