The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open source terms or to credentialed users. The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the U.S. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multi-agency development of coupled modeling systems, controlled experimentation and testing, and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NavGEM), HYbrid Coordinate Ocean Model (HYCOM), and Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS®); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and GEOS-5 atmospheric general circulation model.

Here we present the first steps in developing a global multi-model aerosol forecasting ensemble intended for eventual operational and basic research use. Drawing from members of the International Cooperative for Aerosol Prediction (ICAP) latest generation of quasi-operational aerosol models, 5-day aerosol optical thickness (AOT) forecasts are analyzed for December 2011 through November 2012 from four institutions: European Centre for Medium-Range Weather Forecasts (ECMWF), Japan Meteorological Agency (JMA), NASA Goddard Space Flight Center (GSFC), and Naval Research Lab/Fleet Numerical Meteorology and Oceanography Center (NRL/FNMOC). For dust, we also include the National Oceanic and Atmospheric Administration-National Geospatial Advisory Committee (NOAA NGAC) product in our analysis. The Barcelona Supercomputing Centre and UK Met Office dust products have also recently become members of ICAP, but have insufficient data to be included in this analysis period. A simple consensus ensemble of member and mean AOT fields for modal species (e.g., fine and coarse mode, and a separate dust ensemble) is used to create the ICAP Multi-Model Ensemble (ICAP-MME). The ICAP-MME is run daily at 00:00 UTC for 6-hourly forecasts out to 120 h. Basing metrics on comparisons to 21 regionally representative Aerosol Robotic Network (AERONET) sites, all models generally captured the basic aerosol features of the globe. However, there is an overall AOT low bias among models, particularly for high AOT events. Biomass burning regions have the most diversity in seasonal average AOT. The Southern Ocean, though low in AOT, nevertheless also has high diversity. With regard to root mean square error (RMSE), as expected the ICAP-MME placed first over all models worldwide, and was typically first or second in ranking against all models at individual sites. These results are encouraging; furthermore, as more global operational aerosol models come online, we expect their inclusion in a robust operational multi-model ensemble will provide valuable aerosol forecasting guidance.

The National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) is initialized four times per day (0000, 0600, 1200, and 1800 UTC). NCEP upgraded their operational CFS to version 2 on March 30, 2011. This is the same model that was used to create the NCEP Climate Forecast System Reanalysis (CFSR). CFSv2 monthly atmospheric, oceanic and land surface output products are available at 0.3, 0.5, 1.0, 1.9, and 2.5 degree horizontal resolutions as 6-hourly diurnal monthly means (0000, 0600, 1200, and 1800 UTC) and regular full monthly means. For more information about CFS, please see http://cfs.ncep.noaa.gov/ [http://cfs.ncep.noaa.gov/].

A whole atmosphere model has been developed to demonstrate the impact of terrestrial weather on the upper atmosphere. The dynamical core is based on the NWS Global Forecast System model, which has been extended to cover altitudes from the ground to 600 km. The model includes the physical processes responsible for the stochastic nature of the lower atmosphere, which is a source of variability for the upper atmosphere. The upper levels include diffusive separation, wind induced transport of major species, and uses specific enthalpy as the dependent variable, to accommodate composition dependent gas constants and specific heats. A one‐year model simulation reveals planetary waves explicitly up to 100 km altitude. At higher altitude, multi‐day periodicities in the dynamics appear as a modulation of tidal amplitudes, particularly the migrating semi‐diurnal tide in the lower thermosphere dynamo region. The penetration of planetary wave periodicities from tropospheric weather into the upper atmosphere can explain terrestrial weather sources of variability in the thermospheric and ionospheric.

The goal of the Southeast Bering Sea Carrying Capacity (SEBSCC) program is to document the role of juvenile pollock in the eastern Bering Sea ecosystem. This includes examination of factors that affect their survival and development and testing of annual indices of pre-recruit (age-1) abundance (from the SEBSCC Concept Paper, July 1995). Within this framework, the purpose of the Indices Working Group (IWG, which was developed at the SEBSCC Principal Investigators meeting held in January 2001) is as follows. Based on the best understanding of ecosystem dynamics, identify potential single-or multi-parameter constructs or indices (e.g., wind mixing, time of spring bloom, etc.) that lead to development of survival indices for pollock in the egg, larval and young of the year life history stages. This information will provide input to the National Marine Fisheries Service (NMFS) stock assessment model and/or models of juvenile pollock for use by fisheries scientists at the Alaska Fisheries Science Center (AFSC)/NMFS. As noted by Napp et al (2000) pollock is the most abundant species harvested in the Bering Sea, accounting for > 65% of the total groundfish biomass and during the 1980s when their total biomass exceeded 20 million tones. The biomass trends of three major trophic guilds in the eastern Bering Sea (1979 to 1998: Schumacher et al., in press) show that while the total biomass of pollock in the 1990s is less than in the 1980s, they still dominate biomass in any of the guilds which include marine birds, mammals, other fishes and crabs. Walleye pollock is a nodal species in the food web (NRC Report, 1996) with juveniles being the It is natural that that pollock have been the focus of the Coastal Ocean Program's SEBSECC. The choice of developing a survival index for the early life history stages (eggs through young of the year) allows an early forecast of potential recruitment to the fishery and a metric that can be compared to existing time series of age-1 abundance (Figure 1). A switch model was developed for the eastern Bering Sea (Megrey et al., 1996), which identifies candidates for causing mortality by life history stage and the mortality variability of each stage indicating the stage contributing the most variability in recruitment to the fishery is set (Figure 2). In this model, transport and turbulence have their greatest impact on mortality of yoke-sack through feeding larval stages. It is the vertical structure of temperature, …

An argument is made for greater emphasis on shared infrastructure and commonality in codes and data.

A neural network algorithm used in this study to derive Special Sensor Microwave/Imager (SSM/I) wind speeds from the Defense Meteorological Satellite Program satellite-observed brightness temperatures is briefly reviewed. The SSM/I winds derived from the neural network algorithm are not only of better quality, but also cover a larger area when compared to those generated from the currently operational Goodberlet algorithm. The areas of increased coverage occur mainly over the regions of active weather developments where the operational Goodberlet algorithm fails to produce good quality wind data due to high moisture contents of the atmosphere. These two main characteristics associated with the SSM/I winds derived from the neural network algorithm are discussed.SSM/I wind speed data derived from both the neural network algorithm and the operational Goodberlet algorithm are tested in parallel global data assimilation and forecast experiments for a period of about three weeks. The results show that the use of neural-network-derived SSM/I wind speed data leads to a greater improvement in the first-guess wind fields than use of wind data generated by the operational algorithm. Similarly, comparison of the forecast results shows that use of the neural-network-derived SSM/I wind speed data in the data assimilation and forecast experiment gives better forecasts when compared to those from the operational run that uses the SSM/I winds from the Goodberlet algorithm. These results of comparison between the two parallel analyses and forecasts from the global data assimilation experiments are discussed.

The NCEP and NCAR are cooperating in a project (denoted ''reanalysis'') to produce a 40-year record of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involves the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data; quality controlling and assimilating these data with a data assimilation system that is kept unchanged over the reanalysis period 1957-96. This eliminates perceived climate jumps associated with changes in the data assimilation system.The NCEP/NCAR 40-yr reanalysis uses a frozen state-of-the-art global data assimilation system and a database as complete as possible. The data assimilation and the model used are identical to the global system implemented operationally at the NCEP on 11 January 1995, except that the horizontal resolution is T62 (about 210 km). The database has been enhanced with many sources of observations not available in real time for operations, provided by different countries and organizations. The system has been designed with advanced quality control and monitoring components, and can produce 1 mon of reanalysis per day on a Gray YMP/8 supercomputer. Different types of output archives are being created to satisfy different user needs, including a ''quick look'' CD-ROM (one per year) with six tropospheric and stratospheric fields available twice daily, as well as surface, top-of-the atmosphere, and isentropic fields. Reanalysis information and selected output is also available on-line via the Internet (http//:nic.fb4.noaa.gov:8000). A special CDROM, containing 13 years of selected observed, daily, monthly, and climatological data from the NCEP/NCAR Reanalysis, is included with this issue. Output variables are classified into four classes, depending on the degree to which they are influenced by the observations and/or the model. For example, ''C'' variables (such as precipitation and surface fluxes) are completely determined by the model during the data assimilation and should be used with caution. Nevertheless, a comparison of these variables with observations and with several climatologies shows that they generally contain considerable useful information. Eight-day forecasts, produced every 5 days, should be useful for predictability studies and for monitoring the quality of the observing systems.The 40 years of reanalysis (1957-96) should be completed in early 1997. A continuation into the future through an identical Climate Data Assimilation System will allow researchers to reliably compare recent anomalies with those in earlier decades. Since changes in the observing systems will inevitably produce perceived changes in the climate, parallel reanalyses (at least 1 year long) will be generated for the periods immediately after the introduction of new observing systems, such as new types of satellite data.NCEP plans currently call for an updated reanalysis using a state-of-the-art system every five years or so. The successive reanalyses will be greatly facilitated by the generation of the comprehensive database in the present reanalysis.

A number of improvements were implemented on 6 March 1991 into the National Meteorological Center's global model, which is used in the global data assimilation system (GDAS), the aviation (AVN) forecast, and the medium-range forecast (MRF): The horizontal resolution of the forecast model was increased from triangular truncation T80 to T126, which corresponds to an equivalent increase in grid resolution from 160 km to 105 km.The use of enhanced orography has been discontinued and replaced by mean orography.A new marine-stratus parameterization was introduced.A new mass-conservation constraint was implemented.The horizontal diffusion in the medium scales was reduced by adopting the Leith formulation.A new, more accurate sea-surface temperature analysis is now used.In this note, we discuss each of the changes and briefly review the new model performance.