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The Global Wind Observing Sounder (GWOS) concept, which has been developed as a hypothetical space-based hybrid wind lidar system by NASA in response to the 2007 National Research Council (NRC) decadal survey, is expected to provide global wind profile observations with high vertical resolution, precision, and accuracy when realized. The assimilation of Doppler wind lidar (DWL) observations anticipated from the GWOS is being conducted as a series of observing system simulation experiments (OSSEs) at the Joint Center for Satellite Data Assimilation (JCSDA). A companion paper (Riishøjgaard et al.) describes the simulation of this lidar wind data and evaluates the impact on global numerical weather prediction (NWP) of the baseline GWOS using a four-telescope configuration to provide independent line-of-sight wind speeds, while this paper sets out to assess the NWP impact of GWOS equipped with alternative paired configurations of telescopes. The National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) analysis system and the Global Forecast System (GFS) were used, at a resolution of T382 with 64 layers, as the assimilation system and the forecast model, respectively, in these lidar OSSEs. A set of 45-day assimilation and forecast experiments from 2 July to 15 August 2005 was set up and executed. In this OSSE study, a control simulation utilizing all of the data types assimilated in the operational GSI/GFS system was compared to three OSSE simulations that added lidar wind data from the different configurations of telescopes (one-, two-, and four-look configurations). First, the root-mean-square error (RMSE) of wind analysis is compared against the nature run. A significant reduction of the stratospheric RMSE of wind analyses is found for all latitudes when lidar wind profiles are used in the assimilation system. The forecast impacts of lidar data on the wind and mass forecasts are also presented. In addition, the anomaly correlations (AC) of geopotential height forecasts at 500 hPa were evaluated to compare the control and different GWOS telescope configuration experiments. The results show that the assimilation of lidar data from the GWOS (one, two, or four looks) can improve the NCEP GFS wind and mass field forecasts. The addition of the simulated lidar wind observations leads to a statistically significant increase in AC scores.

Observing system impact assessments using atmospheric simulation experiments are conducted to provide an objective quantitative evaluation of future observing systems and instruments. Such simulation experiments using a proxy true atmosphere, Nature Run, are known as observing system simulation experiments (OSSEs). Through OSSEs, future observing systems that effectively use data assimilation systems in order to improve weather forecasts can be designed. Various types of simulation experiments have been performed in the past by many scientists, but the OSSE at the National Centers for Environmental Prediction (NCEP) presented in this paper is the most extensive and complete OSSE. The agreement between data impacts from simulated data and the corresponding real data is satisfactory. The NCEP OSSE is also the first OSSE where radiance data from satellites were simulated and assimilated. Since a Doppler wind lidar (DWL) is a very costly instrument, various simulation experiments have been funded and performed. OSSEs that evaluate the data impact of DWL are demonstrated. The results show a potentially powerful impact from DWL. In spite of the many controversies regarding simulation experiments, this paper demonstrates that carefully constructed OSSEs are able to provide useful information that influences the design of future observing systems. Various factors that affect the assessment of the impact are discussed.

Observing System Simulation Experiments (OSSEs) are a powerful tool used to assess the potential impact on numerical weather prediction skill of planned or hypothetical future observing systems. Over the past several years an international Joint OSSE collaboration has emerged centered on the use of NASA's and NOAA's data assimilation systems. A Nature Run provided by the European Centre for Medium Range Weather Forecasts (ECMWF) has undergone extensive validation, and a set of simulated reference observations have been subjected to a set of calibration experiments. One of the first candidate observing systems assessed by this system is a wind lidar based on the Global Wind Observing Sounder (GWOS) concept developed by NASA in response to the National Research Council (NRC) Decadal Survey. A set of 45‐day assimilation and forecast experiments has been set up and executed. The experiments were done using the NCEP operational forecast system, and the results show that wind lidar observations are likely to provide a significant increase in forecast skill even when used in a modern, radiance‐based assimilation system. Key Points This OSSEs support the idea that wind observations are important for NWP skill Hypothetical wind lidar provides a important contribution to NCEP forecast skill Impact on skill is largest in tropics but is sustained longer in extratropics

An Observing System Simulation Experiment (OSSE) system has been implemented at the National Oceanographic and Atmospheric Administration Earth Systems Research Laboratory in the US as part of an international Joint OSSE effort. The setup of the OSSE consists of a Nature Run from a 13-month free run of the European Center for Medium-Range Weather Forecasts operational model, synthetic observations developed at the National Centers for Environmental Prediction (NCEP) and the National Aeronautics and Space Administration Global Modelling and Assimilation Office, and an operational version of the NCEP Gridpoint Statistical Interpolation data assimilation and Global Forecast System numerical weather prediction model. Synthetic observations included both conventional observations and the following radiance observations: AIRS, AMSU-A, AMSU-B, HIRS2, HIRS3, MSU, GOES radiance and OSBUV. Calibration was performed by modifying the error added to the conventional synthetic observations to achieve a match between data denial impacts on the analysis state in the OSSE system and in the real data system. Following calibration, the performance of the OSSE system was evaluated in terms of forecast skill scores and impact of observations on forecast fields.

The International Surface Pressure Databank (ISPD) is the world's largest collection of global surface and sea‐level pressure observations. It was developed by extracting observations from established international archives, through international cooperation with data recovery facilitated by the Atmospheric Circulation Reconstructions over the Earth (ACRE) initiative, and directly by contributing universities, organizations, and countries. The dataset period is currently 1768–2012 and consists of three data components: observations from land stations, marine observing systems, and tropical cyclone best track pressure reports. Version 2 of the ISPD (ISPDv2) was created to be observational input for the Twentieth Century Reanalysis Project (20CR) and contains the quality control and assimilation feedback metadata from the 20CR. Since then, it has been used for various general climate and weather studies, and an updated version 3 (ISPDv3) has been used in the ERA‐20C reanalysis in connection with the European Reanalysis of Global Climate Observations project (ERA‐CLIM). The focus of this paper is on the ISPDv2 and the inclusion of the 20CR feedback metadata. The Research Data Archive at the National Center for Atmospheric Research provides data collection and access for the ISPDv2, and will provide access to future versions.

Tree phenology mediates land–atmosphere mass and energy exchange and is a determinant of ecosystem structure and function. In the dry tropics, including African savannas, many trees grow new leaves during the dry season – weeks or months before the rains typically start. This syndrome of pre-rain green-up has long been recognized at small scales, but the high spatial and interspecific variability in leaf phenology has precluded regional generalizations. We used remote sensing data to show that this precocious phenology is ubiquitous across the woodlands and savannas of southern tropical Africa. In 70% of the study area, green-up preceded rain onset by > 20 d (42% > 40 d). All the main vegetation formations exhibited pre-rain green-up, by as much as 53 ± 18 d (in the wet miombo). Green-up showed low interannual variability (SD between years = 11 d), and high spatial variability (> 100 d). These results are consistent with a high degree of local phenological adaptation, and an insolation trigger of green-up. Tree–tree competition and niche separation may explain the ubiquity of this precocious phenology. The ubiquity of pre-rain green-up described here challenges existing model representations and suggests resistance (but not necessarily resilience) to the delay in rain onset predicted under climate change.

The National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR) have cooperated in a project (denoted reanalysis) to produce a retroactive record of more than 50 years of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involved the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data.

The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high-resolution coupled atmosphere–ocean–land surface–sea ice system to provide the best estimate of the state of these coupled domains over this period. The current CFSR will be extended as an operational, real-time product into the future. New features of the CFSR include 1) coupling of the atmosphere and ocean during the generation of the 6-h guess field, 2) an interactive sea ice model, and 3) assimilation of satellite radiances by the Gridpoint Statistical Interpolation (GSI) scheme over the entire period. The CFSR global atmosphere resolution is ~38 km (T382) with 64 levels extending from the surface to 0.26 hPa. The global ocean's latitudinal spacing is 0.25° at the equator, extending to a global 0.5° beyond the tropics, with 40 levels to a depth of 4737 m. The global land surface model has four soil levels and the global sea ice model has three layers. The CFSR atmospheric model has observed variations in carbon dioxide (CO₂) over the 1979–2009 period, together with changes in aerosols and other trace gases and solar variations. Most available in situ and satellite observations were included in the CFSR. Satellite observations were used in radiance form, rather than retrieved values, and were bias corrected with “spin up” runs at full resolution, taking into account variable CO₂ concentrations. This procedure enabled the smooth transitions of the climate record resulting from evolutionary changes in the satellite observing system. CFSR atmospheric, oceanic, and land surface output products are available at an hourly time resolution and a horizontal resolution of 0.5° latitude × 0.5° longitude. The CFSR data will be distributed by the National Climatic Data Center (NCDC) and NCAR. This reanalysis will serve many purposes, including providing the basis for most of the NCEP Climate Prediction Center's operational climate products by defining the mean states of the atmosphere, ocean, land surface, and sea ice over the next 30-yr climate normal (1981–2010); providing initial conditions for historical forecasts that are required to calibrate operational NCEP climate forecasts (from week 2 to 9 months); and providing estimates and diagnoses of the Earth's climate state over the satellite data period for community climate research. Preliminary analysis of the CFSR output indicates a product that is far superior in most respects to the reanalysis of the mid-1990s. The previous NCEP–NCAR reanalyses have been among the most used NCEP products in history; there is every reason to believe the CFSR will supersede these older products both in scope and quality, because it is higher in time and space resolution, covers the atmosphere, ocean, sea ice, and land, and was executed in a coupled mode with a more modern data assimilation system and forecast model.

The NASA Atmospheric InfraRed Sounder (AIRS), the first of the new generation of meteorological advanced sounders for operational and research use, is part of a large international investment to upgrade the operational meteorological satellite systems.

A 3-month ecologic investigation was done to identify the reservoir of Ebola virus following the 1995 outbreak in Kikwit, Democratic Republic of the Congo. Efforts focused on the fields where the putative primary case had worked but included other habitats near Kikwit. Samples were collected from 3066 vertebrates and tested for the presence of antibodies to Ebola (subtype Zaire) virus: All tests were negative, and attempts to isolate Ebola virus were unsuccessful. The investigation was hampered by a lack of information beyond the daily activities of the primary case, a lack of information on Ebola virus ecology, which precluded the detailed study of select groups of animals, and sample-size limitations for rare species. The epidemiology of Ebola hemorrhagic fever suggests that humans have only intermittent contact with the virus, which complicates selection of target species. Further study of the epidemiology of human outbreaks to further define the environmental contact of primary cases would be of great value.