Weather forecasting generates significant societal benefits, which can be increased by improving accuracy and lead-time through better meteorological monitoring, modeling and computing. Forecasting relies on numerical weather prediction (NWP), which is significantly impacted by the availability of meteorological observations, with spacebased observations being the most important. Surface-based observations also contribute substantially to NWP performance, but current availability in Antarctica, Africa, South America, the Pacific and parts of Asia is insufficient. More observations from these regions would improve global NWP and forecasting quality, particularly in the datasparse regions themselves, but also over the rest of the globe. It is estimated that improvements in the coverage and exchange of surface-based observations to meet the World Meteorological Organization’s Global Basic Observing Network (GBON) specification can deliver additional global socioeconomic benefits of over $5 billion annually. This is a conservative estimate omitting non-financial benefits such as potential lives saved and improvements to well-being, so underestimates the full benefits, particularly for developing countries. Investing in improving surface-based observations in data sparse regions is also highly economically efficient, yielding a global benefit to cost ratio of over twenty-five. Assuming sufficient observational coverage, international data exchange is a very efficient multiplier of the value of observations. However, exchange is currently insufficient across all regions. In view of the growing climateand weatherrelated challenges facing humanity and recognizing that climate services similarly rely on meteorological monitoring, surface-based observations should be treated as a critical public good, with public oversight and open exchange within the meteorological and climatological communities.

The Aeolus mission objectives are to improve numerical weather prediction (NWP) and enhance the understanding and modeling of atmospheric dynamics on global and regional scale. Given the first successes of Aeolus in NWP, it is time to look forward to future vertical wind profiling capability to fulfill the rolling requirements in operational meteorology. Requirements for wind profiles and information on vertical wind shear are constantly evolving. The need for high-quality wind and profile information to capture and initialize small-amplitude, fast-evolving, and mesoscale dynamical structures increases, as the resolution of global NWP improved well into the 3D turbulence regime on horizontal scales smaller than 500 km. In addition, advanced requirements to describe the transport and dispersion of atmospheric constituents and better depict the circulation on climate scales are well recognized. Direct wind profile observations over the oceans, tropics, and Southern Hemisphere are not provided by the current global observing system. Looking to the future, most other wind observation techniques rely on cloud or regions of water vapor and are necessarily restricted in coverage. Therefore, after its full demonstration, an operational Aeolus -like follow-on mission obtaining globally distributed wind profiles in clear air by exploiting molecular scattering remains unique.

An attempt is made here to evaluate the skill of forecast during boreal summer monsoon regime over the Indian region using the Observation Simulation System Experiment (OSSE) with Doppler Wind LIDAR (DWL) onboard International Space Station (ISS), assimilated in the initial condition. Through various techniques such as pattern correlation, root mean square error etc, we found that there is some positive impact of assimilating the DWL data on the forecast particularly at the lower tropospheric level. Impact on lowering the RMSE is seen for wind fields in the 850 and 500 hPa over Indian domain but not much impact is seen over larger domain. The moisture field and cloud also show marginal impact due to assimilation of DWL. This indicates that possibly due to lower spatial resolution of DWL data and more data gap over Indian and surrounding oceanic region, the impact on forecast is less. However, it shows the promise that monsoon being a convectively coupled system; increase in spatial data by DWL may better resolve the low level wind and subsequently the low level shear which is important for convection trigger in boundary layer.

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 (Riishojgaard 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.

The three-dimensional global wind field is the most important remaining measurement needed to accurately assess the dynamics of the atmosphere. Wind information in the tropics, high latitudes, and stratosphere is particularly deficient. Furthermore, only a small fraction of the atmosphere is sampled in terms of wind profiles. This limits our ability to optimally specify initial conditions for numerical weather prediction (NWP) models and our understanding of several key climate change issues. Because of its extensive wind measurement heritage (since 1968) and especially the rapid recent technology advances, Doppler lidar has reached a level of maturity required for a space-based mission. The European Space Agency (ESA)'s Atmospheric Dynamics Mission Aeolus (ADM-Aeolus) Doppler wind lidar (DWL), now scheduled for launch in 2015, will be a major milestone. This paper reviews the expected impact of DWL measurements on NWP and climate research, measurement concepts, and the recent advances in technology that will set the stage for space-based deployment. Forecast impact experiments with actual airborne DWL measurements collected over the North Atlantic in 2003 and assimilated into the European Centre for Medium-Range Weather Forecasts (ECMWF) operational model are a clear indication of the value of lidar-measured wind profiles. Airborne DWL measurements collected over the western Pacific in 2008 and assimilated into both the ECMWF and U.S. Navy operational models support the earlier findings. These forecast impact experiments confirm observing system simulation experiments (OSSEs) conducted over the past 25–30 years. The addition of simulated DWL wind observations in recent OSSEs performed at the Joint Center for Satellite Data Assimilation (JCSDA) leads to a statistically significant increase in forecast skill.

[1] NOAA/NWS/NCEP/EMC, College Park, Maryland, USA, Michiko.Masutani@noaa.gov [2] Environment of Canada, Dorval, Qc, Canada, Louis.Garand@ec.gc.ca [3] NILU, Norwegian Institute for Air Research, Norway, William.A.Lahoz@nilu.no [4] European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK, erik.andersson@ecmwf.int [5] Environment of Canada, Toronto, On, Canada, Yves.Rochon@ec.gc.ca [6] Joint Center for Satellite Data Assimilation, College Park, MD, USA, Lars.P.Riishojgaard@nasa.gov [7] Hydro Meteorological Centre of Russia, Moscow, Russia, tsyrulnikov@mecom.ru [8] Department of Earth and Space Science and Engineering, York University, Canada, jcmcc@yorku.ca [9] NOAA/NWS/NCEP/EMC, Boulder, CO, USA, lidia.cucurull@noaa.gov [10] NOAA/Earth System Research Laboratory, Boulder, CO, USA, Yuanfu.Xie@noaa.gov [11] National Institute of Information and Communications Technology (NICT) Tokyo, Japan, sishii@nict.go.jp [12] NOAA/NWS/NCEP/EMC, College Park, MD, USA, Robert.Grumbine@noaa.gov [13] Met Office, Exeter, UK, gilbert.brunet@metoffice.gov.uk [14] NOAA/NWS/NCEP/EMC, College Park, MD, USA, Jack.Woollen@noaa.gov [15] Japan Meteorological Agency, Tokyo, Japan, y-sato@met.kishou.go.jp

Test beds have emerged as a critical mechanism linking weather research with forecasting operations. The U.S. Weather Research Program (USWRP) was formed in the 1990s to help identify key gaps in research related to major weather prediction problems and the role of observations and numerical models. This planning effort ultimately revealed the need for greater capacity and new approaches to improve the connectivity between the research and forecasting enterprise. Out of this developed the seeds for what is now termed test beds. While many individual projects, and even more broadly the NOAA/National Weather Service (NWS) Modernization, were successful in advancing weather prediction services, it was recognized that specific forecast problems warranted a more focused and elevated level of effort. The USWRP helped develop these concepts with science teams and provided seed funding for several of the test beds described. Based on the varying NOAA mission requirements for forecasting, differences in the organizational structure and methods used to provide those services, and differences in the state of the science related to those forecast challenges, test beds have taken on differing characteristics, strategies, and priorities. Current test bed efforts described have all emerged between 2000 and 2011 and focus on hurricanes (Joint Hurricane Testbed), precipitation (Hydrometeorology Testbed), satellite data assimilation (Joint Center for Satellite Data Assimilation), severe weather (Hazardous Weather Testbed), satellite data support for severe weather prediction (Short-Term Prediction Research and Transition Center), mesoscale modeling (Developmental Testbed Center), climate forecast products (Climate Testbed), testing and evaluation of satellite capabilities [Geostationary Operational Environmental Satellite-R Series (GOES-R) Proving Ground], aviation applications (Aviation Weather Testbed), and observing system experiments (OSSE Testbed).

NASA Goddard Space Flight Center's Software Systems Support Office (SSSO) is participating in a multi-agency study of the impact of assimilating Doppler wind lidar observations on numerical weather prediction. Funded by NASA's Earth Science Technology Office, SSSO has worked with Simpson Weather Associates to produce time series of synthetic lidar observations mimicking the OAWL and WISSCR lidar instruments deployed on the International Space Station. In addition, SSSO has worked to assimilate a portion of these observations those drawn from the NASA fvGCM Nature Run into the NASA GEOS-DAS global weather prediction system in a series of Observing System Simulation Experiments (OSSEs). These OSSEs will complement parallel OSSEs prepared by the Joint Center for Satellite Data Assimilation and by NOAA's Atlantic Oceanographic and Meteorological Laboratory. In this talk, we will describe our procedure and provide available OSSE results.

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.

The absence of vertically resolved wind observations over large portions of the globe is a welldocumented shortcoming of the Global Observing System. While AMVs provide very good horizontal coverage of single-level wind observations over most of the globe, one of the most promising paths toward obtaining vertically resolved wind information is a space-based Doppler Wind Lidar. The European Space Agency will launch its ADM/Aeolus DWL technology demonstration mission in 2014, and the US is planning to deploy its first DWL system as one of NASA’s Decadal Survey missions sometime after 2020. The NASA-NOAA Joint Observing System Simulation Experiment (OSSE) system has been used to assess the expected impact on numerical weather prediction skill of various possible configurations of this mission. We report on a series of experiment undertaken with this system in the expected impact on NCEP forecast skill of a hypothetical DWL system was simulated. The experiments show the respective impacts of measuring one or two wind components as well as the impact of increasing the horizontal data coverage.

Observing System Simulation Experiments (OSSEs) are a powerful tool used to assess the potential impact on numerical weather prediction skill from planned or hypothetical future observing systems. Over the last 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. OSSEs were conducted at Joint Center for Satellite Data Assimilation (JCSDA) and positive impacts from GWOS on medium range weather forecast were demonstrated.For OSSEs, all major observations used for the data assimilation have to be simulated as a control observation in addition to the observations being tested by an OSSE. Simulation of control observations and OSSE calibration are the most significant initial investments for an OSSE before it can be used to evaluate the data impact of future instruments. The Nature Run data and control observation that were simulated at NOAA from the Nature Run are made available from a NASA portal and NCAR for international collaborative Joint OSSEs.Recent developments and plans for a JCSDA OSSE based on a 2012 observation system will be also described.

The status of current efforts to assimilate cloud‐ and precipitation‐affected satellite data is summarised with special focus on infrared and microwave radiance data obtained from operational Earth observation satellites. All global centres pursue efforts to enhance infrared radiance data usage due to the limited availability of temperature observations in cloudy regions where forecast skill is estimated to strongly depend on the initial conditions. Most systems focus on the sharpening of weighting functions at cloud top providing high vertical resolution temperature increments to the analysis, mainly in areas of persistent high and low cloud cover. Microwave radiance assimilation produces impact on the deeper atmospheric moisture structures as well as cloud microphysics and, through control variable and background‐error formulation, also on temperature but to lesser extent than infrared data. Examples of how the impacts of these two observation types are combined are shown for subtropical low‐level cloud regimes. The overall impact of assimilating such data on forecast skill is measurably positive despite the fact that the employed assimilation systems have been constructed and optimized for clear‐sky data. This leads to the conclusion that a better understanding and modelling of model processes in cloud‐affected areas and data assimilation system enhancements through inclusion of moist processes and their error characterization will contribute substantially to future forecast improvement. Copyright © 2011 Royal Meteorological Society, Crown in the right of Canada, and British Crown copyright, the Met Office

The absence of vertically resolved wind observations over large portions of the globe is a wellrecognized gap in the Global Observing System. One of the most promising paths toward closing this gap is to deploy one or more space-based Doppler Wind Lidars. The European Space Agency is planning to launch its ADM/Aeolus technology demonstration mission in 2013, and the US is planning to deploy its first DWL as one of NASA’s Decadal Survey missions sometime after 2020. In support of the US mission definition effort, a testcbed has been established under the NASA-NOAA Joint OSSE collaboration to assess the NWP impact of various possible configurations of such a mission. Based on a comprehensive series of OSSEs we show the expected impact on NCEP forecast skill of simulated observations from various configurations of a space-borne hybrid (coherent and direct detections) lidar system. The experiments demonstrate the impacts of measuring one or two wind components, respectively as well as the impact of doubling the amount of data available.

Advanced instruments of current and planned satellite missions will increasingly provide large volumes of data related to the atmospheric, oceanic, and land surface state. Here are described recent advances in satellite data assimilation which will help ensure that full benefit is derived from the considerable investment in these space-based missions. A series of Observing System Experiments (OSEs) which indicate the utility of current data types is summarised. A key part of the preparation for advanced instruments such as those to be flown on NPOESS, NPP and GOES-R is the assimilation of data from heritage instruments. Here, the assimilation of data from some heritage instruments is described. The instruments include the Atmospheric Infrared Sounder (AIRS), the High-Resolution InfraRed Sounder (HIRS), the Special Sensor Microwave Imager Sounder (SSM/IS), the Advanced Microwave Sounding Unit (AMSU), COSMIC, WindSat and the Moderate Resolution Imaging Spectroradiometer (MODIS). Data from these instruments have been assimilated as part of preparation for advanced instruments such as the Cross-track Infrared Sounder (CrIS), the Visible/Infrared Imager and Radiometer Suite (VIIRS), the Advanced Baseline Imager (ABI) and the Advanced Technology Microwave Sounder (ATMS). In addition, Observing System Simulation Experiments (OSSEs) for new missions such as the ADM Aeolus have also been completed. This activity is noted here and will allow the NWP community to make early use of the data from new instruments soon after they are launched. INTRODUCTION - THE CHALLENGE

The United States is merging its two polar-orbiting operational environmental satellite programs operated by the Department of Commerce and the Department of Defense into a single system, which is called the National Polar-orbiting Operational Environmental Satellite System (NPOESS). During the next decade, NPOESS will provide global operational data to meet many of the needs of weather forecasters, climate researchers, and global decision makers for remotely sensed Earth science data and global environmental monitoring. The NPOESS Preparatory Project (NPP) will be launched in 2011 as a precursor to NPOESS to reduce final development risks for NPOESS and to provide continuity of global imaging and atmospheric sounding data from the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) missions. Beginning in 2014, NPOESS spacecraft will be launched into an afternoon orbit and in 2016 into an early-morning orbit to provide significantly improved operational capabilities and benefits to satisfy critical civil and national security requirements for space-based, remotely sensed environmental data. The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Meteorological Operation (MetOp) spacecraft will complement NPOESS in a midmorning orbit. The joint constellation will provide global coverage with a data refresh rate of approximately four hours. NPOESS will observe more phenomena simultaneously from space and deliver a data volume significantly greater than its operational predecessors with substantially improved data delivery to users. Higher-resolution (spatial and spectral) and more accurate imaging and atmospheric sounding data will enable improvements in short-to medium-range weather forecasts. Multispectral and hyperspectral instruments on NPOESS will provide global imagery and sounding products useful to the forecaster that are complementary to those available from geostationary satellites. NPOESS will support the operational needs of meteorological, oceanographic, environmental, climatic, and space environmental remote sensing programs and provide continuity of data for climate researchers. This article that describes NPOESS was completed and accepted for publication prior to the White House decision in February 2010 ordering a major restructuring of the NPOESS program. The Department of Commerce will now assume primary responsibility for the afternoon polar-orbiting operational environmental satellite orbit and the Department of Defense will take primary responsibility for the early morning orbit. However, NPP, as described in this article, is still scheduled to be launched in 2011. Several of the instruments and program elements described in this article are also likely to be carried forward into future U. S. polar-orbiting operational environmental satellite missions.