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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Applied Meteorology Unit (AMU) Quarterly Report - Fourth Quarter FY-10

Three AMU tasks were completed in this Quarter, each resulting in a forecast tool now being used in operations and a final report documenting how the work was done. AMU personnel completed the following tasks (1) Phase II of the Peak Wind Tool for General Forecasting task by delivering an improved wind forecasting tool to operations and providing training on its use; (2) a graphical user interface (GUI) she updated with new scripts to complete the ADAS Update and Maintainability task, and delivered the scripts to the Spaceflight Meteorology Group on Johnson Space Center, Texas and National Weather Service in Melbourne, Fla.; and (3) the Verify MesoNAM Performance task after we created and delivered a GUI that forecasters will use to determine the performance of the operational MesoNAM weather model forecast.

Bauman, William↗
NASA NTRS1992

Tropical intraseasonal oscillation and its prediction by the NMC operational model

Results are presented of an investigation of the tropical intraseasonal oscillation (ISO) and its impact on the extended-range forecast in the NMC operational model during Phase II (14 December 1986-31 March 1987) of the Dynamical Extended Range Forecast. Based on principal component analysis of the velocity potential and streamfunction, evidence was found of tropical-extratropical interaction associated with the ISO. The NMC model possess significant forecast skills for the principal streamfunction and velocity potential modes up to the first ten days. Results of the error growth analysis suggest that the principal modes of velocity potential have large errors comparable to the model random errors. By comparison, the initial errors in the streamfunction are much smaller. The error growth for both tropical and extratropical modes are found to be significantly suppressed during periods of strong ISO relative to periods of weak ISO. The increase in extratropical forecast skill is likely due to (1) the model's ability to better capture ISO signals in the tropics and (2) the increased coupling between the tropics and extratropics during periods of strong ISO.

Lau, K.-M.↗
NASA NTRS1991

Assessment and forecasting of lightning potential and its effect on launch operations at Cape Canaveral Air Force Station and John F. Kennedy Space Center

Lightning plays a pivotal role in the operation decision process for space and ballistic launches at Cape Canaveral Air Force Station and Kennedy Space Center. Lightning forecasts are the responsibility of Detachment 11, 4th Weather Wing's Cape Canaveral Forecast Facility. These forecasts are important to daily ground processing as well as launch countdown decisions. The methodology and equipment used to forecast lightning are discussed. Impact on a recent mission is summarized.

Weems, J.↗
NASA NTRS1983

Satellite freeze forecast system. Operating/troubleshooting manual

Examples of operational procedures are given to assist users of the satellites freeze forecasting system (SFFS) in logging in on to the computer, executing the programs in the menu, logging off the computer, and setting up the automatic system. Directions are also given for displaying, acquiring, and listing satellite maps; for communicating via terminal and monitor displays; and for what to do when the SFFS doesn't work. Administrative procedures are included.

Martsolf, J. D.↗
NASA NTRS2005

Forecasting Lightning at Kennedy Space Center/Cape Canaveral Air Force Station, Florida

The Applied Meteorology Unit (AMU) developed a set of statistical forecast equations that provide a probability of lightning occurrence on Kennedy Space Center (KSC) I Cape Canaveral Air Force Station (CCAFS) for the day during the warm season (May September). The 45th Weather Squadron (45 WS) forecasters at CCAFS in Florida include a probability of lightning occurrence in their daily 24-hour and weekly planning forecasts, which are briefed at 1100 UTC (0700 EDT). This information is used for general scheduling of operations at CCAFS and KSC. Forecasters at the Spaceflight Meteorology Group also make thunderstorm forecasts for the KSC/CCAFS area during Shuttle flight operations. Much of the current lightning probability forecast at both groups is based on a subjective analysis of model and observational data. The objective tool currently available is the Neumann-Pfeffer Thunderstorm Index (NPTI, Neumann 1971), developed specifically for the KSCICCAFS area over 30 years ago. However, recent studies have shown that 1-day persistence provides a better forecast than the NPTI, indicating that the NPTI needed to be upgraded or replaced. Because they require a tool that provides a reliable estimate of the daily thunderstorm probability forecast, the 45 WS forecasters requested that the AMU develop a new lightning probability forecast tool using recent data and more sophisticated techniques now possible through more computing power than that available over 30 years ago. The equation development incorporated results from two research projects that investigated causes of lightning occurrence near KSCICCAFS and over the Florida peninsula. One proved that logistic regression outperformed the linear regression method used in NPTI, even when the same predictors were used. The other study found relationships between large scale flow regimes and spatial lightning distributions over Florida. Lightning, probabilities based on these flow regimes were used as candidate predictors in the equation development. Fifteen years (1 989-2003) of warm season data were used to develop the forecast equations. The data sources included a local network of cloud-to-ground lightning sensors called the Cloud-to-Ground Lightning Surveillance System (CGLSS), 1200 UTC Florida synoptic soundings, and the 1000 UTC CCAFS sounding. Data from CGLSS were used to determine lightning occurrence for each day. The 1200 UTC soundings were used to calculate the synoptic-scale flow regimes and the 1000 UTC soundings were used to calculate local stability parameters, which were used as candidate predictors of lightning occurrence. Five logistic regression forecast equations were created through careful selection and elimination of the candidate predictors. The resulting equations contain five to six predictors each. Results from four performance tests indicated that the equations showed an increase in skill over several standard forecasting methods, good reliability, an ability to distinguish between non-lightning and lightning days, and good accuracy measures and skill scores. Given the overall good performance the 45 WS requested that the equations be transitioned to operations and added to the current set of tools used to determine the daily lightning probability of occurrence.

Lambert, Winfred↗
NASA NTRS1981

A numerical evaluation of TIROS-N and NOAA-6 analyses in a high resolution limited area model

Vertical temperature profiles derived from TIROS-N and NOAA-6 radiance measurements were used to create separate analyses for the period 0000 GMT 6 January to 0000 GMT 7 January 1980. The 0000 GMT 6 January satellite analyses and a conventional analysis were used to initialize and run the University of Wisconsin's version of the Australian Region Primitive Equations model. Forecasts based on conventional analyses were used to evaluate the forecasts based only on satellite upper air data. The forecasts based only on TIROS-N or NOAA-6 data did reasonably well in locating the main trough and ridge positions. The satellite initial analyses and forecasts revealed errors correlated to the synoptic situation. The trough in both TIROS-N and NOAA-6 forecasts which was initially too warm remained too warm as it propagated eastward during the forecast period. Thus, it is unlikely that the operational satellite data will improve forecasts in a data dense region. However, in regions of poor data coverage, the satellite data should have a beneficial effect on numerical forecasts.

Derber, J. C.↗
NASA NTRS2018

Using Machine-Learning Methods and Expert Prediction Probabilities to Forecast Solar Flares

It has long been known that studying connection between solar flares and properties of magnetic field in active regions is very important for understanding the flare physics and developing space weather forecasts. The Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) obtains tremendous amounts of magnetic field data products. However the operational NOAA Space Weather Prediction Center (SWPC) forecasts of solar flares still represent prediction probabilities issued by the experts. In this research we investigate the possibilities to enhance the daily operational flare forecasts performed at the SWPC by developing a synergy of the expert predictions and physics-based criteria, and by employing machine-learning methods. Among the physics-based criteria we consider the descriptors of the Polarity Inversion Line (PIL) and Space weather HMI Active Region Patches (SHARP), and derive from them daily characteristics of the entire Sun. We also consider the daily descriptors of the GOES Soft X-Ray (SXR) 1-8 Angstroms flux such as the flare history of the previous days and averaged X-Ray flux. We estimate the effectiveness in separation of flaring and non-flaring cases for each characteristic, as well as for the expert prediction probabilities, and find that some PIL, SHARP and SXR descriptors are as effective as the expert prediction probabilities and should be considered to issue the flare forecast. Finally, we train and test several Machine-Learning classification algorithms (Support Vector Classifiers with various kernel functions, k-Nearest Neighbor Classifier, Random Forest Classifier, and Neural Networks) using the most effective descriptors and expert prediction probabilities, and compare the obtained predictions with the current SWPC forecasts.

Machine-Learning↗
NASA NTRS2016

Development, Application, and Transition of Aerosol and Trace Gas Products Derived from Next-Generation Satellite Observations to Operations

NASA Short-term Prediction Research and Transition (SPoRT) Center has a history of successfully transitioning unique observations and research capabilities to the operational weather community to improve short-term forecasts. SPoRTstrives to bridge the gap between research and operations by maintaining interactive partnerships with end users to develop products that match specific forecast challenges, provide training, and assess the products in the operational environment. This presentation focuses on recent product development, application, and transition of aerosol and trace gas products to operations for specific forecasting applications. Recent activities relating to the SPoRT ozone products, aerosol optical depth composite product, sulfur dioxide, and aerosol index products are discussed.

remote sensing↗
NASA NTRS1974

Short-range forecasts with the GISS model of the global atmosphere

A nine-layer, primitive equation (PE) model of the global atmosphere developed at the Goddard Institute for Space Studies (GISS) has been used to generate six 48-hr forecasts during December 1972 and January 1973. Operational analyses north of 18 N and experimental global analyses made available by the National Meteorological Center (NMC), NOAA, were used as the initial conditions; the operational analyses were used to verify the forecasts at 12-hr intervals over the Northern Hemisphere north of 22 N. The combined analyses were used to verify the forecasts in the global domain. RMS errors of the sea-level pressure, 1000-mb heights, and vector geostrophic winds, and 500-mb heights and vector geostrophic winds indicate that the GISS forecasts have skill comparable to those made by operational PE models.

Druyan, L. M.↗
NASA NTRS1967

Forecasting the Economic Impact of Future Space Station Operations

Recent manned and unmanned Earth-orbital operations have suggested great promise of improved knowledge and of substantial economic and associated benefits to be derived from services offered by a space station. Proposed application areas include agriculture, forestry, hydrology, public health, oceanography, natural disaster warning, and search/rescue operations. The need for reliable estimates of economic and related Earth-oriented benefits to be realized from Earth-orbital operations is discussed and recent work in this area is reviewed. Emphasis is given to those services based on remote sensing. Requirements for a uniform, comprehensive and flexible methodology are discussed. A brief review of the suggested methodology is presented. This methodology will be exercised through five case studies which were chosen from a gross inventory of almost 400 user candidates. The relationship of case study results to benefits in broader application areas is discussed, Some management implications of possible future program implementation are included.

Summer, R. A.↗
NASA NTRS2006

The Art and Science of Long-Range Space Weather Forecasting

Long-range space weather forecasts are akin to seasonal forecasts of terrestrial weather. We don t expect to forecast individual events but we do hope to forecast the underlying level of activity important for satellite operations and mission pl&g. Forecasting space weather conditions years or decades into the future has traditionally been based on empirical models of the solar cycle. Models for the shape of the cycle as a function of its amplitude become reliable once the amplitude is well determined - usually two to three years after minimum. Forecasting the amplitude of a cycle well before that time has been more of an art than a science - usually based on cycle statistics and trends. Recent developments in dynamo theory -the theory explaining the generation of the Sun s magnetic field and the solar activity cycle - have now produced models with predictive capabilities. Testing these models with historical sunspot cycle data indicates that these predictions may be highly reliable one, or even two, cycles into the future.

Hathaway, David H.↗
NASA NTRS2016

Comparative Analysis of NOAA REFM and SNB3GEO Tools for the Forecast of the Fluxes of High-Energy Electrons at GEO

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB3GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB3GEO forecasts use solar wind density and interplanetary magnetic field B(sub z) observations at L1. The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB3GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB3GEO forecast.

Balikhin, M. A.↗
NASA NTRS2010

An Objective Verification of the North American Mesoscale Model for Kennedy Space Center and Cape Canaveral Air Force Station

The 45th Weather Squadron (45 WS) Launch Weather Officers use the 12-km resolution North American Mesoscale (NAM) model (MesoNAM) text and graphical product forecasts extensively to support launch weather operations. However, the actual performance of the model at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) has not been measured objectively. In order to have tangible evidence of model performance, the 45 WS tasked the Applied Meteorology Unit to conduct a detailed statistical analysis of model output compared to observed values. The model products are provided to the 45 WS by ACTA, Inc. and include hourly forecasts from 0 to 84 hours based on model initialization times of 00, 06, 12 and 18 UTC. The objective analysis compared the MesoNAM forecast winds, temperature and dew point, as well as the changes in these parameters over time, to the observed values from the sensors in the KSC/CCAFS wind tower network. Objective statistics will give the forecasters knowledge of the model's strength and weaknesses, which will result in improved forecasts for operations.

Bauman, William H., III↗
NASA NTRS2010

An Objective Verification of the North American Mesoscale Model for Kennedy Space Center and Cape Canaveral Air Force Station

The 45th Weather Squadron (45 WS) Launch Weather Officers (LWO's) use the 12-km resolution North American Mesoscale (NAM) model (MesoNAM) text and graphical product forecasts extensively to support launch weather operations. However, the actual performance of the model at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) has not been measured objectively. In order to have tangible evidence of model performance, the 45 WS tasked the Applied Meteorology Unit (AMU; Bauman et ai, 2004) to conduct a detailed statistical analysis of model output compared to observed values. The model products are provided to the 45 WS by ACTA, Inc. and include hourly forecasts from 0 to 84 hours based on model initialization times of 00, 06, 12 and 18 UTC. The objective analysis compared the MesoNAM forecast winds, temperature (T) and dew pOint (T d), as well as the changes in these parameters over time, to the observed values from the sensors in the KSC/CCAFS wind tower network shown in Table 1. These objective statistics give the forecasters knowledge of the model's strengths and weaknesses, which will result in improved forecasts for operations.

Bauman, William H., III↗
NASA NTRS2018

Improving NASA GEOS Atmospheric CO2 Simulations by Calibrating CASA Surface Fluxes with an Empirical Sink

With the adoption of the Paris climate accord, efforts to monitor and understand both anthropogenic and natural carbon sources and sinks are increasing across the world. Given their low latency and global coverage, satellite observations of atmospheric carbon dioxide (CO2) are poised to make important contributions to this field. The combination of satellite data and high resolution global models can be used to monitor changes in carbon fluxes and to evaluate the consistency of nationally reported emissions estimates in support of multiple stakeholder communities. However, a consistent challenge to such work has been the high latency of surface carbon flux estimates, which are often not available for a year or more. This presentation describes the construction of surface carbon flux estimates meant to improve the near real time simulation of atmospheric CO2 with NASA's Goddard Earth Observing System (GEOS) general circulation model. The surface flux estimates begin with a collection of bottom-up fluxes which incorporate satellite measurements in their construction, e.g. vegetation indices in the Carnegie-Ames-Stanford Approach (CASA) and nighttime lights in the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). From there, we take the additional step of using an empirical sink to calibrate terrestrial net biospheric exchange (NBE) to estimated values from atmospheric inversion systems. This approach removes a known, systematic bias in predicted atmospheric mixing ratios. Using these fluxes in a free running simulation, the model is able to reproduce in situ measurements with the same skill as when it uses gridded fluxes from a flux inversion system. Using these fluxes as a prior in an assimilation system, e.g. one incorporating retrievals of column CO2 from the Orbiting Carbon Observatory 2 (OCO-2), allows the analysis to capture variability in CO2 on scales that would be missed otherwise. This approach supports NASA's capability to forecast atmospheric CO2 up to two weeks in advance by leveraging a GEOS system used to produce quasi-operational weather analyses and forecasts, providing a valuable new tool to the carbon monitoring research and applications communities.

Weir, B.↗
NASA NTRS2002

Global Precipitation Measurement Program and the Development of Dual-Frequency Precipitation Radar

The Global Precipitation Measurement (GPM) program is a mission to measure precipitation from space, and is a similar but much expanded mission of the Tropical Rainfall Measuring Mission. Its scope is not limited to scientific research, but includes practical and operational applications such as weather forecasting and water resource management. To meet the requirements of operational use, the GPM uses multiple low-orbiting satellites to increase the sampling frequency and to create three-hourly global rain maps that will be delivered to the world in quasi-real time. A dual-frequency radar (DPR) will be installed on the primary satellite that plays an important role in the whole mission. The DPR will realize measurement of precipitation with high sensitivity, high precision and high resolutions. This paper describes an outline of the GPM program, its issues and the roles and development of the DPR.

Iguchi, Toshio↗
NASA NTRS2001

Weather Prediction Improvement Using Advanced Satellite Technology

We discuss in this paper some of the problems that exist today in the fall utilization of satellite data to improve weather forecasts and we propose specific recommendations to solve them. This discussion can be viewed as an aspect of the general debate on how best to organize the transition from research to operational satellites and how to evaluate the impact of a research instrument on numerical weather predictions. A method for providing this transition is offered by the National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP). This mission will bridge the time between the present NOAA and Department of Defense (DOD) polar orbiting missions and the initiation of the converged NPOESS series and will evaluate some of the Earth Observing System (EOS) instruments as appropriate for operational missions. Thus, this mission can be viewed as an effort to meet the operational requirements of NOAA and DOD and the research requirements of NASA. More generally, however, it can be said that the process of going from the conception of new, more advanced instruments to their operational implementation and full utilization by the weather forecast communities is not optimal. Instruments developed for research purposes may have insufficient funding to explore their potential operational capabilities. Furthermore, instrument development programs designed for operational satellites typically have insufficient funding for assimilation algorithms needed to transform the satellite observations into data that can be used by sophisticated global weather forecast models. As a result, years often go by before satellite data are efficiently used for operational forecasts. NASA and NOAA each have unique expertise in the design of satellite instruments, their use for basic and applied research and their utilization in weather and climate research. At a time of limited resources, the two agencies must combine their efforts to work toward common goals of full utilization of satellite data. This is a challenge that requires the assimilation of myriad new data into increasingly sophisticated numerical forecast models that run on increasingly sophisticated computer systems. In section II, we briefly outline the impact of satellite data on the quality of the National Centers for Environmental Prediction (NCEP) forecasts. In section III, we describe the present status of the utilization of satellite data in NCEP models and the challenges that lie ahead. In section IV, we propose solutions whose goals are summarized in section V.

Einaudi, Franco↗
NASA NTRS2008

Towards Improved Forecasts of Atmospheric and Oceanic Circulations over the Complex Terrain of the Eastern Mediterranean

Forecasting atmospheric and oceanic circulations accurately over the Eastern Mediterranean has proved to be an exceptional challenge. The existence of fine-scale topographic variability (land/sea coverage) and seasonal dynamics variations can create strong spatial gradients in temperature, wind and other state variables, which numerical models may have difficulty capturing. The Hellenic Center for Marine Research (HCMR) is one of the main operational centers for wave forecasting in the eastern Mediterranean. Currently, HCMR's operational numerical weather/ocean prediction model is based on the coupled Eta/Princeton Ocean Model (POM). Since 1999, HCMR has also operated the POSEIDON floating buoys as a means of state-of-the-art, real-time observations of several oceanic and surface atmospheric variables. This study attempts a first assessment at improving both atmospheric and oceanic prediction by initializing a regional Numerical Weather Prediction (NWP) model with high-resolution sea surface temperatures (SST) from remotely sensed platforms in order to capture the small-scale characteristics.

Chronis, Themis↗