Airline flight planning - The weather connection

NASA Technical Reports Server (NTRS)

Steinberg, R.

1981-01-01

The history of airline flight planning is briefly reviewed. Over half a century ago, when scheduled airline services began, weather data were almost nonexistent. By the early 1950's a reliable synoptic network provided upper air reports. The next 15 years saw a rapid growth in commercial aviation, and airlines introduced computer techniques to flight planning. The 1970's saw the development of weather satellites. The current state of flight planning activities is analyzed. It is found that accurate flight planning will require meteorological information on a finer scale than can be provided by a synoptic forecast. Opportunities for a new approach are examined, giving attention to the available options, a mesoscale numerical weather prediction model, limited area fine mesh models, man-computer interactive display systems, the use of interactive techniques with the present upper air data base, and the implementation of interactive techniques.

Weather Forecasting From Woolly Art to Solid Science

NASA Astrophysics Data System (ADS)

Lynch, P.

THE PREHISTORY OF SCIENTIFIC FORECASTING Vilhelm Bjerknes Lewis Fry Richardson Richardson's Forecast THE BEGINNING OF MODERN NUMERICAL WEATHER PREDICTION John von Neumann and the Meteorology Project The ENIAC Integrations The Barotropic Model Primitive Equation Models NUMERICAL WEATHER PREDICTION TODAY ECMWF HIRLAM CONCLUSIONS REFERENCES

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-10-20

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

An Overview of Numerical Weather Prediction on Various Scales

NASA Astrophysics Data System (ADS)

Bao, J.-W.

2009-04-01

The increasing public need for detailed weather forecasts, along with the advances in computer technology, has motivated many research institutes and national weather forecasting centers to develop and run global as well as regional numerical weather prediction (NWP) models at high resolutions (i.e., with horizontal resolutions of ~10 km or higher for global models and 1 km or higher for regional models, and with ~60 vertical levels or higher). The need for running NWP models at high horizontal and vertical resolutions requires the implementation of non-hydrostatic dynamic core with a choice of horizontal grid configurations and vertical coordinates that are appropriate for high resolutions. Development of advanced numerics will also be needed for high resolution global and regional models, in particular, when the models are applied to transport problems and air quality applications. In addition to the challenges in numerics, the NWP community is also facing the challenges of developing physics parameterizations that are well suited for high-resolution NWP models. For example, when NWP models are run at resolutions of ~5 km or higher, the use of much more detailed microphysics parameterizations than those currently used in NWP model will become important. Another example is that regional NWP models at ~1 km or higher only partially resolve convective energy containing eddies in the lower troposphere. Parameterizations to account for the subgrid diffusion associated with unresolved turbulence still need to be developed. Further, physically sound parameterizations for air-sea interaction will be a critical component for tropical NWP models, particularly for hurricane predictions models. In this review presentation, the above issues will be elaborated on and the approaches to address them will be discussed.

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vs in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Impact of the 4 April 2014 Saharan dust outbreak on the photovoltaic power generation in Germany

NASA Astrophysics Data System (ADS)

Rieger, Daniel; Steiner, Andrea; Bachmann, Vanessa; Gasch, Philipp; Förstner, Jochen; Deetz, Konrad; Vogel, Bernhard; Vogel, Heike

2017-11-01

The importance for reliable forecasts of incoming solar radiation is growing rapidly, especially for those countries with an increasing share in photovoltaic (PV) power production. The reliability of solar radiation forecasts depends mainly on the representation of clouds and aerosol particles absorbing and scattering radiation. Especially under extreme aerosol conditions, numerical weather prediction has a systematic bias in the solar radiation forecast. This is caused by the design of numerical weather prediction models, which typically account for the direct impact of aerosol particles on radiation using climatological mean values and the impact on cloud formation assuming spatially and temporally homogeneous aerosol concentrations. These model deficiencies in turn can lead to significant economic losses under extreme aerosol conditions. For Germany, Saharan dust outbreaks occurring 5 to 15 times per year for several days each are prominent examples for conditions, under which numerical weather prediction struggles to forecast solar radiation adequately. We investigate the impact of mineral dust on the PV-power generation during a Saharan dust outbreak over Germany on 4 April 2014 using ICON-ART, which is the current German numerical weather prediction model extended by modules accounting for trace substances and related feedback processes. We find an overall improvement of the PV-power forecast for 65 % of the pyranometer stations in Germany. Of the nine stations with very high differences between forecast and measurement, eight stations show an improvement. Furthermore, we quantify the direct radiative effects and indirect radiative effects of mineral dust. For our study, direct effects account for 64 %, indirect effects for 20 % and synergistic interaction effects for 16 % of the differences between the forecast including mineral dust radiative effects and the forecast neglecting mineral dust.

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

NASA Technical Reports Server (NTRS)

Chronis, Themis; Case, Jonathan L.; Papadopoulos, Anastasios; Anagnostou, Emmanouil N.; Mecikalski, John R.; Haines, Stephanie L.

2008-01-01

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.

Operational Dust Prediction

NASA Technical Reports Server (NTRS)

Benedetti, Angela; Baldasano, Jose M.; Basart, Sara; Benincasa, Francesco; Boucher, Olivier; Brooks, Malcolm E.; Chen, Jen-Ping; Colarco, Peter R.; Gong, Sunlin; Huneeus, Nicolas;

77 FR 69436 - JPSS Polar Satellite-Gap Mitigation-Request for Public Comment

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-19

... positive steps to mitigate the negative impacts to NOAA's numerical weather forecasts that could be...-satellite data, weather modeling, and data assimilation improvements. NOAA is convening teams of internal... of NOAA's numerical weather forecasts should we experience a loss of polar satellite environmental...

The quiet revolution of numerical weather prediction.

PubMed

Bauer, Peter; Thorpe, Alan; Brunet, Gilbert

2015-09-03

Advances in numerical weather prediction represent a quiet revolution because they have resulted from a steady accumulation of scientific knowledge and technological advances over many years that, with only a few exceptions, have not been associated with the aura of fundamental physics breakthroughs. Nonetheless, the impact of numerical weather prediction is among the greatest of any area of physical science. As a computational problem, global weather prediction is comparable to the simulation of the human brain and of the evolution of the early Universe, and it is performed every day at major operational centres across the world.

Studies regarding the quality of numerical weather forecasts of the WRF model integrated at high-resolutions for the Romanian territory

DOE PAGES

Iriza, Amalia; Dumitrache, Rodica C.; Lupascu, Aurelia; ...

2016-01-01

Our paper aims to evaluate the quality of high-resolution weather forecasts from the Weather Research and Forecasting (WRF) numerical weather prediction model. The lateral and boundary conditions were obtained from the numerical output of the Consortium for Small-scale Modeling (COSMO) model at 7 km horizontal resolution. Furthermore, the WRF model was run for January and July 2013 at two horizontal resolutions (3 and 1 km). The numerical forecasts of the WRF model were evaluated using different statistical scores for 2 m temperature and 10 m wind speed. Our results showed a tendency of the WRF model to overestimate the valuesmore » of the analyzed parameters in comparison to observations.« less

Studies regarding the quality of numerical weather forecasts of the WRF model integrated at high-resolutions for the Romanian territory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iriza, Amalia; Dumitrache, Rodica C.; Lupascu, Aurelia

Our paper aims to evaluate the quality of high-resolution weather forecasts from the Weather Research and Forecasting (WRF) numerical weather prediction model. The lateral and boundary conditions were obtained from the numerical output of the Consortium for Small-scale Modeling (COSMO) model at 7 km horizontal resolution. Furthermore, the WRF model was run for January and July 2013 at two horizontal resolutions (3 and 1 km). The numerical forecasts of the WRF model were evaluated using different statistical scores for 2 m temperature and 10 m wind speed. Our results showed a tendency of the WRF model to overestimate the valuesmore » of the analyzed parameters in comparison to observations.« less

Extreme weather caused by concurrent cyclone, front and thunderstorm occurrences

PubMed Central

Dowdy, Andrew J.; Catto, Jennifer L.

2017-01-01

Phenomena such as cyclones, fronts and thunderstorms can cause extreme weather in various regions throughout the world. Although these phenomena have been examined in numerous studies, they have not all been systematically examined in combination with each other, including in relation to extreme precipitation and extreme winds throughout the world. Consequently, the combined influence of these phenomena represents a substantial gap in the current understanding of the causes of extreme weather events. Here we present a systematic analysis of cyclones, fronts and thunderstorms in combination with each other, as represented by seven different types of storm combinations. Our results highlight the storm combinations that most frequently cause extreme weather in various regions of the world. The highest risk of extreme precipitation and extreme wind speeds is found to be associated with a triple storm type characterized by concurrent cyclone, front and thunderstorm occurrences. Our findings reveal new insight on the relationships between cyclones, fronts and thunderstorms and clearly demonstrate the importance of concurrent phenomena in causing extreme weather. PMID:28074909

Space Weather Storm Responses at Mars: Lessons from A Weakly Magnetized Terrestrial Planet

NASA Astrophysics Data System (ADS)

Luhmann, J. G.; Dong, C. F.; Ma, Y. J.; Curry, S. M.; Li, Yan; Lee, C. O.; Hara, T.; Lillis, R.; Halekas, J.; Connerney, J. E.; Espley, J.; Brain, D. A.; Dong, Y.; Jakosky, B. M.; Thiemann, E.; Eparvier, F.; Leblanc, F.; Withers, P.; Russell, C. T.

2017-10-01

Much can be learned from terrestrial planets that appear to have had the potential to be habitable, but failed to realize that potential. Mars shows evidence of a once hospitable surface environment. The reasons for its current state, and in particular its thin atmosphere and dry surface, are of great interest for what they can tell us about habitable zone planet outcomes. A main goal of the MAVEN mission is to observe Mars' atmosphere responses to solar and space weather influences, and in particular atmosphere escape related to space weather `storms' caused by interplanetary coronal mass ejections (ICMEs). Numerical experiments with a data-validated MHD model suggest how the effects of an observed moderately strong ICME compare to what happens during a more extreme event. The results suggest the kinds of solar and space weather conditions that can have evolutionary importance at a planet like Mars.

Atlas : A library for numerical weather prediction and climate modelling

NASA Astrophysics Data System (ADS)

Deconinck, Willem; Bauer, Peter; Diamantakis, Michail; Hamrud, Mats; Kühnlein, Christian; Maciel, Pedro; Mengaldo, Gianmarco; Quintino, Tiago; Raoult, Baudouin; Smolarkiewicz, Piotr K.; Wedi, Nils P.

2017-11-01

The algorithms underlying numerical weather prediction (NWP) and climate models that have been developed in the past few decades face an increasing challenge caused by the paradigm shift imposed by hardware vendors towards more energy-efficient devices. In order to provide a sustainable path to exascale High Performance Computing (HPC), applications become increasingly restricted by energy consumption. As a result, the emerging diverse and complex hardware solutions have a large impact on the programming models traditionally used in NWP software, triggering a rethink of design choices for future massively parallel software frameworks. In this paper, we present Atlas, a new software library that is currently being developed at the European Centre for Medium-Range Weather Forecasts (ECMWF), with the scope of handling data structures required for NWP applications in a flexible and massively parallel way. Atlas provides a versatile framework for the future development of efficient NWP and climate applications on emerging HPC architectures. The applications range from full Earth system models, to specific tools required for post-processing weather forecast products. The Atlas library thus constitutes a step towards affordable exascale high-performance simulations by providing the necessary abstractions that facilitate the application in heterogeneous HPC environments by promoting the co-design of NWP algorithms with the underlying hardware.

Reflections on the Conception, Birth, and Childhood of Numerical Weather Prediction

NASA Astrophysics Data System (ADS)

Lorenz, Edward N.

2006-05-01

In recognition of the contributions of Norman Phillips and Joseph Smagorinsky to the field of numerical weather prediction (NWP), a symposium was held in 2003; this account is an amplification of a talk presented there. Ideas anticipating the advent of NWP, the first technically successful numerical weather forcast, and the subsequent progression of NWP to a mature discipline are described, with special emphasis on the work of Phillips and Smagorinsky and their mentor Jule Charney.

Increasing Range and Lethality of Extended-Range Munitions (ERMS) using Numerical Weather Prediction (NWP) and the AUV Workbench to Compute a Ballistic Correction (BALCOR)

DTIC Science & Technology

2006-12-01

2 D . APPROACH TAKEN......................................................................................3 E...7 d . FORCEnet.................................................................................8 D . HISTORY OF LONG-RANGE PROJECTILES (LRPS...46 D . NUMERICAL WEATHER MODELING CENTERS...............................47 1. Fleet Numerical Meteorological

A Data Assimilation System For Operational Weather Forecast In Galicia Region (nw Spain)

NASA Astrophysics Data System (ADS)

Balseiro, C. F.; Souto, M. J.; Pérez-Muñuzuri, V.; Brewster, K.; Xue, M.

Regional weather forecast models, such as the Advanced Regional Prediction System (ARPS), over complex environments with varying local influences require an accurate meteorological analysis that should include all local meteorological measurements available. In this work, the ARPS Data Analysis System (ADAS) (Xue et al. 2001) is applied as a three-dimensional weather analysis tool to include surface station and rawinsonde data with the NCEP AVN forecasts as the analysis background. Currently in ADAS, a set of five meteorological variables are considered during the analysis: horizontal grid-relative wind components, pressure, potential temperature and spe- cific humidity. The analysis is used for high resolution numerical weather prediction for the Galicia region. The analysis method used in ADAS is based on the successive corrective scheme of Bratseth (1986), which asymptotically approaches the result of a statistical (optimal) interpolation, but at lower computational cost. As in the optimal interpolation scheme, the Bratseth interpolation method can take into account the rel- ative error between background and observational data, therefore they are relatively insensitive to large variations in data density and can integrate data of mixed accuracy. This method can be applied economically in an operational setting, providing signifi- cant improvement over the background model forecast as well as any analysis without high-resolution local observations. A one-way nesting is applied for weather forecast in Galicia region, and the use of this assimilation system in both domains shows better results not only in initial conditions but also in all forecast periods. Bratseth, A.M. (1986): "Statistical interpolation by means of successive corrections." Tellus, 38A, 439-447. Souto, M. J., Balseiro, C. F., Pérez-Muñuzuri, V., Xue, M. Brewster, K., (2001): "Im- pact of cloud analysis on numerical weather prediction in the galician region of Spain". Submitted to Journal of Applied Meteorology. Xue, M., Wang. D., Gao, J., Brewster, K, Droegemeier, K. K., (2001): "The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilation". Meteor. Atmos Physics. Accepted

Assessing the Role of Seafloor Weathering in Global Geochemical Cycling

NASA Astrophysics Data System (ADS)

Farahat, N. X.; Abbot, D. S.; Archer, D. E.

2015-12-01

Low-temperature alteration of the basaltic upper oceanic crust, known as seafloor weathering, has been proposed as a mechanism for long-term climate regulation similar to the continental climate-weathering negative feedback. Despite this potentially far-reaching impact of seafloor weathering on habitable planet evolution, existing modeling frameworks do not include the full scope of alteration reactions or recent findings of convective flow dynamics. We present a coupled fluid dynamic and geochemical numerical model of low-temperature, off-axis hydrothermal activity. This model is designed to explore the the seafloor weathering flux of carbon to the oceanic crust and its responsiveness to climate fluctuations. The model's ability to reproduce the seafloor weathering environment is evaluated by constructing numerical simulations for comparison with two low-temperature hydrothermal systems: A transect east of the Juan de Fuca Ridge and the southern Costa Rica Rift flank. We explore the sensitivity of carbon uptake by seafloor weathering on climate and geology by varying deep ocean temperature, seawater dissolved inorganic carbon, continental weathering inputs, and basaltic host rock in a suite of numerical experiments.

Simulation of the Impact of New Aircraft-and Satellite-based Ocean Surface Wind Measurements on Wind Analyses and Numerical Forecasts

NASA Technical Reports Server (NTRS)

Miller, TImothy; Atlas, Robert; Black, Peter; Chen, Shuyi; Jones, Linwood; Ruf, Chris; Uhlhorn, Eric; Gamache, John; Amarin, Ruba; El-Nimri, Salem;

Estimating 1 min rain rate distributions from numerical weather prediction

NASA Astrophysics Data System (ADS)

Paulson, Kevin S.

2017-01-01

Internationally recognized prognostic models of rain fade on terrestrial and Earth-space EHF links rely fundamentally on distributions of 1 min rain rates. Currently, in Rec. ITU-R P.837-6, these distributions are generated using the Salonen-Poiares Baptista method where 1 min rain rate distributions are estimated from long-term average annual accumulations provided by numerical weather prediction (NWP). This paper investigates an alternative to this method based on the distribution of 6 h accumulations available from the same NWPs. Rain rate fields covering the UK, produced by the Nimrod network of radars, are integrated to estimate the accumulations provided by NWP, and these are linked to distributions of fine-scale rain rates. The proposed method makes better use of the available data. It is verified on 15 NWP regions spanning the UK, and the extension to other regions is discussed.

Demonstrating the Alaska Ocean Observing System in Prince William Sound

NASA Astrophysics Data System (ADS)

Schoch, G. Carl; McCammon, Molly

2013-07-01

The Alaska Ocean Observing System and the Oil Spill Recovery Institute developed a demonstration project over a 5 year period in Prince William Sound. The primary goal was to develop a quasi-operational system that delivers weather and ocean information in near real time to diverse user communities. This observing system now consists of atmospheric and oceanic sensors, and a new generation of computer models to numerically simulate and forecast weather, waves, and ocean circulation. A state of the art data management system provides access to these products from one internet portal at http://www.aoos.org. The project culminated in a 2009 field experiment that evaluated the observing system and performance of the model forecasts. Observations from terrestrial weather stations and weather buoys validated atmospheric circulation forecasts. Observations from wave gages on weather buoys validated forecasts of significant wave heights and periods. There was an emphasis on validation of surface currents forecasted by the ocean circulation model for oil spill response and search and rescue applications. During the 18 day field experiment a radar array mapped surface currents and drifting buoys were deployed. Hydrographic profiles at fixed stations, and by autonomous vehicles along transects, were made to acquire measurements through the water column. Terrestrial weather stations were the most reliable and least costly to operate, and in situ ocean sensors were more costly and considerably less reliable. The radar surface current mappers were the least reliable and most costly but provided the assimilation and validation data that most improved ocean circulation forecasts. We describe the setting of Prince William Sound and the various observational platforms and forecast models of the observing system, and discuss recommendations for future development.

Generic magnetohydrodynamic model at the Community Coordinated Modeling Center

NASA Astrophysics Data System (ADS)

Honkonen, I. J.; Rastaetter, L.; Glocer, A.

2016-12-01

The Community Coordinated Modeling Center (CCMC) at NASA Goddard Space Flight Center is a multi-agency partnership to enable, support and perform research and development for next-generation space science and space weather models. CCMC currently hosts nearly 100 numerical models and a cornerstone of this activity is the Runs on Request (RoR) system which allows anyone to request a model run and analyse/visualize the results via a web browser. CCMC is also active in the education community by organizing student research contests, heliophysics summer schools, and space weather forecaster training for students, government and industry representatives. Recently a generic magnetohydrodynamic (MHD) model was added to the CCMC RoR system which allows the study of a variety of fluid and plasma phenomena in one, two and three dimensions using a dynamic point-and-click web interface. For example students can experiment with the physics of fundamental wave modes of hydrodynamic and MHD theory, behavior of discontinuities and shocks as well as instabilities such as Kelvin-Helmholtz.Students can also use the model to experiments with numerical effects of models, i.e. how the process of discretizing a system of equations and solving them on a computer changes the solution. This can provide valuable background understanding e.g. for space weather forecasters on the effects of model resolution, numerical resistivity, etc. on the prediction.

Strategies for Near Real Time Estimates of Precipitable Water Vapor from GPS Ground Receivers

NASA Technical Reports Server (NTRS)

Y., Bar-Sever; Runge, T.; Kroger, P.

1995-01-01

GPS-based estimates of precipitable water vapor (PWV) may be useful in numerical weather models to improve short-term weather predictions. To be effective in numerical weather prediction models, GPS PWV estimates must be produced with sufficient accuracy in near real time. Several estimation strategies for the near real time processing of GPS data are investigated.

Use of MODIS Cloud Top Pressure to Improve Assimilation Yields of AIRS Radiances in GSI

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi

2014-01-01

Improvements to global and regional numerical weather prediction have been demonstrated through assimilation of data from NASA's Atmospheric Infrared Sounder (AIRS). Current operational data assimilation systems use AIRS radiances, but impact on regional forecasts has been much smaller than for global forecasts. Previously, it has been shown that cloud top designation associated with quality control procedures within the Gridpoint Statistical Interpolation (GSI) system used operationally by a number of Joint Center for Satellite Data Assimilation (JCSDA) partners may not provide the best representation of cloud top pressure (CTP). Because this designated CTP determines which channels are cloud-free and, thus, available for assimilation, ensuring the most accurate representation of this value is imperative to obtaining the greatest impact from satellite radiances. This paper examines the assimilation of hyperspectral sounder data used in operational numerical weather prediction by comparing analysis increments and numerical forecasts generated using operational techniques with a research technique that swaps CTP from the Moderate-resolution Imaging Spectroradiometer (MODIS) for the value of CTP calculated from the radiances within GSI.

Using 3-D Numerical Weather Data in Piloted Simulations

NASA Technical Reports Server (NTRS)

Daniels, Taumi S.

2016-01-01

This report describes the process of acquiring and using 3-D numerical model weather data sets in NASA Langley's Research Flight Deck (RFD). A set of software tools implement the process and can be used for other purposes as well. Given time and location information of a weather phenomenon of interest, the user can download associated numerical weather model data. These data are created by the National Oceanic and Atmospheric Administration (NOAA) High Resolution Rapid Refresh (HRRR) model, and are then processed using a set of Mathworks' Matlab(TradeMark) scripts to create the usable 3-D weather data sets. Each data set includes radar re ectivity, water vapor, component winds, temperature, supercooled liquid water, turbulence, pressure, altitude, land elevation, relative humidity, and water phases. An open-source data processing program, wgrib2, is available from NOAA online, and is used along with Matlab scripts. These scripts are described with sucient detail to make future modi cations. These software tools have been used to generate 3-D weather data for various RFD experiments.

Simulating carbon capture by enhanced weathering with croplands: an overview of key processes highlighting areas of future model development

PubMed Central

Quegan, Shaun; Banwart, Steven A.

2017-01-01

Enhanced weathering (EW) aims to amplify a natural sink for CO2 by incorporating powdered silicate rock with high reactive surface area into agricultural soils. The goal is to achieve rapid dissolution of minerals and release of alkalinity with accompanying dissolution of CO2 into soils and drainage waters. EW could counteract phosphorus limitation and greenhouse gas (GHG) emissions in tropical soils, and soil acidification, a common agricultural problem studied with numerical process models over several decades. Here, we review the processes leading to soil acidification in croplands and how the soil weathering CO2 sink is represented in models. Mathematical models capturing the dominant processes and human interventions governing cropland soil chemistry and GHG emissions neglect weathering, while most weathering models neglect agricultural processes. We discuss current approaches to modelling EW and highlight several classes of model having the potential to simulate EW in croplands. Finally, we argue for further integration of process knowledge in mathematical models to capture feedbacks affecting both longer-term CO2 consumption and crop growth and yields. PMID:28381633

Sub-kilometer Numerical Weather Prediction in complex urban areas

NASA Astrophysics Data System (ADS)

Leroyer, S.; Bélair, S.; Husain, S.; Vionnet, V.

2013-12-01

A Sub-kilometer atmospheric modeling system with grid-spacings of 2.5 km, 1 km and 250 m and including urban processes is currently being developed at the Meteorological Service of Canada (MSC) in order to provide more accurate weather forecasts at the city scale. Atmospheric lateral boundary conditions are provided with the 15-km Canadian Regional Deterministic Prediction System (RDPS). Surface physical processes are represented with the Town Energy Balance (TEB) model for the built-up covers and with the Interactions between the Surface, Biosphere, and Atmosphere (ISBA) land surface model for the natural covers. In this study, several research experiments over large metropolitan areas and using observational networks at the urban scale are presented, with a special emphasis on the representation of local atmospheric circulations and their impact on extreme weather forecasting. First, numerical simulations are performed over the Vancouver metropolitan area during a summertime Intense Observing Period (IOP of 14-15 August 2008) of the Environmental Prediction in Canadian Cities (EPiCC) observational network. The influence of the horizontal resolution on the fine-scale representation of the sea-breeze development over the city is highlighted (Leroyer et al., 2013). Then severe storms cases occurring in summertime within the Greater Toronto Area (GTA) are simulated. In view of supporting the 2015 PanAmerican and Para-Pan games to be hold in GTA, a dense observational network has been recently deployed over this region to support model evaluations at the urban and meso scales. In particular, simulations are conducted for the case of 8 July 2013 when exceptional rainfalls were recorded. Leroyer, S., S. Bélair, J. Mailhot, S.Z. Husain, 2013: Sub-kilometer Numerical Weather Prediction in an Urban Coastal Area: A case study over the Vancouver Metropolitan Area, submitted to Journal of Applied Meteorology and Climatology.

Improved Impact of Atmospheric Infrared Sounder (AIRS) Radiance Assimilation in Numerical Weather Prediction

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Chou, Shih-Hung; Jedlovec, Gary

2012-01-01

Improvements to global and regional numerical weather prediction (NWP) have been demonstrated through assimilation of data from NASA s Atmospheric Infrared Sounder (AIRS). Current operational data assimilation systems use AIRS radiances, but impact on regional forecasts has been much smaller than for global forecasts. Retrieved profiles from AIRS contain much of the information that is contained in the radiances and may be able to reveal reasons for this reduced impact. Assimilating AIRS retrieved profiles in an identical analysis configuration to the radiances, tracking the quantity and quality of the assimilated data in each technique, and examining analysis increments and forecast impact from each data type can yield clues as to the reasons for the reduced impact. By doing this with regional scale models individual synoptic features (and the impact of AIRS on these features) can be more easily tracked. This project examines the assimilation of hyperspectral sounder data used in operational numerical weather prediction by comparing operational techniques used for AIRS radiances and research techniques used for AIRS retrieved profiles. Parallel versions of a configuration of the Weather Research and Forecasting (WRF) model with Gridpoint Statistical Interpolation (GSI) that mimics the analysis methodology, domain, and observational datasets for the regional North American Mesoscale (NAM) model run at the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) are run to examine the impact of each type of AIRS data set. The first configuration will assimilate the AIRS radiance data along with other conventional and satellite data using techniques implemented within the operational system; the second configuration will assimilate AIRS retrieved profiles instead of AIRS radiances in the same manner. Preliminary results of this study will be presented and focus on the analysis impact of the radiances and profiles for selected cases.

Mining key elements for severe convection prediction based on CNN

NASA Astrophysics Data System (ADS)

Liu, Ming; Pan, Ning; Zhang, Changan; Sha, Hongzhou; Zhang, Bolei; Liu, Liang; Zhang, Meng

2017-04-01

Severe convective weather is a kind of weather disasters accompanied by heavy rainfall, gust wind, hail, etc. Along with recent developments on remote sensing and numerical modeling, there are high-volume and long-term observational and modeling data accumulated to capture massive severe convective events over particular areas and time periods. With those high-volume and high-variety weather data, most of the existing studies and methods carry out the dynamical laws, cause analysis, potential rule study, and prediction enhancement by utilizing the governing equations from fluid dynamics and thermodynamics. In this study, a key-element mining method is proposed for severe convection prediction based on convolution neural network (CNN). It aims to identify the key areas and key elements from huge amounts of historical weather data including conventional measurements, weather radar, satellite, so as numerical modeling and/or reanalysis data. Under this manner, the machine-learning based method could help the human forecasters on their decision-making on operational weather forecasts on severe convective weathers by extracting key information from the real-time and historical weather big data. In this paper, it first utilizes computer vision technology to complete the data preprocessing work of the meteorological variables. Then, it utilizes the information such as radar map and expert knowledge to annotate all images automatically. And finally, by using CNN model, it cloud analyze and evaluate each weather elements (e.g., particular variables, patterns, features, etc.), and identify key areas of those critical weather elements, then help forecasters quickly screen out the key elements from huge amounts of observation data by current weather conditions. Based on the rich weather measurement and model data (up to 10 years) over Fujian province in China, where the severe convective weathers are very active during the summer months, experimental tests are conducted with the new machine-learning method via CNN models. Based on the analysis of those experimental results and case studies, the proposed new method have below benefits for the severe convection prediction: (1) helping forecasters to narrow down the scope of analysis and saves lead-time for those high-impact severe convection; (2) performing huge amount of weather big data by machine learning methods rather relying on traditional theory and knowledge, which provide new method to explore and quantify the severe convective weathers; (3) providing machine learning based end-to-end analysis and processing ability with considerable scalability on data volumes, and accomplishing the analysis work without human intervention.

The Impact of Different Complexity on Numerical Weather Predictions within the Coupled Global Online Modeling System

NASA Astrophysics Data System (ADS)

Zhang, L.; Grell, G. A.; McKeen, S. A.; Ahmadov, R.

2017-12-01

The global Flow-following finite-volume Icosahedra Model (FIM), which was developed in the Global Systems Division of NOAA/ESRL and the Finite-volume cubed-sphere dynamical core (FV3) developed by GFDL, have been coupled online with aerosol and gas-phase chemistry schemes (FIM-Chem and FV3-Chem). Within the aerosol and chemistry modules, the models handle wet and dry deposition, chemical reactions, aerosol direct and semi-direct effect, anthropogenic emissions, biogenic emissions, biomass burning, dust and sea-salt emissions. They are able to provide chemical weather predictions at various spatial resolutions and with different levels of complexity. FIM-Chem is also able to quantify the impact of aerosol on numerical weather predictions (NWP). Currently, three different chemical schemes have been coupled with the FIM model. The simplest aerosol modules are from the GOCART model with its simplified parameterization of sulfur/sulfate chemistry. The photochemical gas-phase mechanism RACM was included to determine the impact of additional complexity on the aerosol and gas simulations. We have also implemented a more sophisticated aerosol scheme that includes secondary organic aerosols (SOA) based on the VBS approach. The model performance has been evaluated by comparing with the ATom-1 observations. FIM-Chem is able to reproduce many observed aerosol and gas features very well. A five-day NWP on 120 km horizontal resolution using FIM-Chem has been done for the end of July, 2016 to quantify the impact of the three different chemical schemes on weather forecasts. Compared to a meteorological run that excludes the model chemical schemes, and is driven only by background AODs from the GFS model, the 5-day forecast results shows significant impact on weather predictions when including the prognostic aerosol schemes. This includes convective precipitation, surface temperature, and 700 hPa air temperature. We also use FIM-Chem to investigate the 2012 South American Biomass Burning Analysis (SAMBBA) campaign period to determine whether more complex chemistry provides benefits for global numerical weather prediction.

Graphical tools for TV weather presentation

NASA Astrophysics Data System (ADS)

Najman, M.

2010-09-01

Contemporary meteorology and its media presentation faces in my opinion following key tasks: - Delivering the meteorological information to the end user/spectator in understandable and modern fashion, which follows industry standard of video output (HD, 16:9) - Besides weather icons show also the outputs of numerical weather prediction models, climatological data, satellite and radar images, observed weather as actual as possible. - Does not compromise the accuracy of presented data. - Ability to prepare and adjust the weather show according to actual synoptic situtation. - Ability to refocus and completely adjust the weather show to actual extreme weather events. - Ground map resolution weather data presentation need to be at least 20 m/pixel to be able to follow the numerical weather prediction model resolution. - Ability to switch between different numerical weather prediction models each day, each show or even in the middle of one weather show. - The graphical weather software need to be flexible and fast. The graphical changes nee to be implementable and airable within minutes before the show or even live. These tasks are so demanding and the usual original approach of custom graphics could not deal with it. It was not able to change the show every day, the shows were static and identical day after day. To change the content of the weather show daily was costly and most of the time impossible with the usual approach. The development in this area is fast though and there are several different options for weather predicting organisations such as national meteorological offices and private meteorological companies to solve this problem. What are the ways to solve it? What are the limitations and advantages of contemporary graphical tools for meteorologists? All these questions will be answered.

P161 Improved Impact of Atmospheric Infrared Sounder (AIRS) Radiance Assimilation in Numerical Weather Prediction

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley T.; Chou, Shih-Hung; Jedlovec, Gary J.

2012-01-01

For over 6 years, AIRS radiances have been assimilated operationally into National (e.g. Environmental Modeling Center (EMC)) and International (e.g. European Centre for Medium-Range Weather Forecasts (ECMWF)), operational centers; assimilated in the North American Mesoscale (NAM) since 2008. Due partly to data latency and operational constraints, hyperspectral radiance assimilation has had less impact on the Gridpoint Statistical Interpolation (GSI) system used in the NAM and GFS. Objective of this project is to use AIRS retrieved profiles as a proxy for the AIRS radiances in situations where AIRS radiances are unable to be assimilated in the current operational system by evaluating location and magnitude of analysis increments.

Operational atmospheric modeling system CARIS for effective emergency response associated with hazardous chemical releases in Korea.

PubMed

Kim, Cheol-Hee; Park, Jin-Ho; Park, Cheol-Jin; Na, Jin-Gyun

2004-03-01

The Chemical Accidents Response Information System (CARIS) was developed at the Center for Chemical Safety Management in South Korea in order to track and predict the dispersion of hazardous chemicals in the case of an accident or terrorist attack involving chemical companies. The main objective of CARIS is to facilitate an efficient emergency response to hazardous chemical accidents by rapidly providing key information in the decision-making process. In particular, the atmospheric modeling system implemented in CARIS, which is composed of a real-time numerical weather forecasting model and an air pollution dispersion model, can be used as a tool to forecast concentrations and to provide a wide range of assessments associated with various hazardous chemicals in real time. This article introduces the components of CARIS and describes its operational modeling system. Some examples of the operational modeling system and its use for emergency preparedness are presented and discussed. Finally, this article evaluates the current numerical weather prediction model for Korea.

On the sensitivity of numerical weather prediction to remotely sensed marine surface wind data - A simulation study

NASA Technical Reports Server (NTRS)

Cane, M. A.; Cardone, V. J.; Halem, M.; Halberstam, I.

1981-01-01

The reported investigation has the objective to assess the potential impact on numerical weather prediction (NWP) of remotely sensed surface wind data. Other investigations conducted with similar objectives have not been satisfactory in connection with a use of procedures providing an unrealistic distribution of initial errors. In the current study, care has been taken to duplicate the actual distribution of information in the conventional observing system, thus shifting the emphasis from accuracy of the data to the data coverage. It is pointed out that this is an important consideration in assessing satellite observing systems since experience with sounder data has shown that improvements in forecasts due to satellite-derived information is due less to a general error reduction than to the ability to fill data-sparse regions. The reported study concentrates on the evaluation of the observing system simulation experimental design and on the assessment of the potential of remotely sensed marine surface wind data.

Utilization of satellite data and regional scale numerical models in short range weather forecasting

NASA Technical Reports Server (NTRS)

Kreitzberg, C. W.

1985-01-01

Overwhelming evidence was developed in a number of studies of satellite data impact on numerical weather prediction that it is unrealistic to expect satellite temperature soundings to improve detailed regional numerical weather prediction. It is likely that satellite data over the United States would substantially impact mesoscale dynamical predictions if the effort were made to develop a composite moisture analysis system. The horizontal variability of moisture, most clearly depicited in images from satellite water vapor channels, would not be determined from conventional rawinsondes even if that network were increased by a doubling of both the number of sites and the time frequency.

Regional 3-D Modeling of Ground Geoelectric Field for the Northeast United States due to Realistic Geomagnetic Disturbances

NASA Astrophysics Data System (ADS)

Ivannikova, E.; Kruglyakov, M.; Kuvshinov, A. V.; Rastaetter, L.; Pulkkinen, A. A.; Ngwira, C. M.

2017-12-01

During extreme space weather events electric currents in the Earth's magnetosphere and ionosphere experience large variations, which leads to dramatic intensification of the fluctuating magnetic field at the surface of the Earth. According to Faraday's law of induction, the fluctuating geomagnetic field in turn induces electric field that generates harmful currents (so-called "geomagnetically induced currents"; GICs) in grounded technological systems. Understanding (via modeling) of the spatio-temporal evolution of the geoelectric field during enhanced geomagnetic activity is a key consideration in estimating the hazard to technological systems from space weather. We present the results of ground geoelectric field modeling for the Northeast United States, which is performed with the use of our novel numerical tool based on integral equation approach. The tool exploits realistic regional three-dimensional (3-D) models of the Earth's electrical conductivity and realistic global models of the spatio-temporal evolution of the magnetospheric and ionospheric current systems responsible for geomagnetic disturbances. We also explore in detail the manifestation of the coastal effect (anomalous intensification of the geoelectric field near the coasts) in this region.

UMTS Network Stations

NASA Astrophysics Data System (ADS)

Hernandez, C.

2010-09-01

The weakness of small island electrical grids implies a handicap for the electrical generation with renewable energy sources. With the intention of maximizing the installation of photovoltaic generators in the Canary Islands, arises the need to develop a solar forecasting system that allows knowing in advance the amount of PV generated electricity that will be going into the grid, from the installed PV power plants installed in the island. The forecasting tools need to get feedback from real weather data in "real time" from remote weather stations. Nevertheless, the transference of this data to the calculation computer servers is very complicated with the old point to point telecommunication systems that, neither allow the transfer of data from several remote weather stations simultaneously nor high frequency of sampling of weather parameters due to slowness of the connection. This one project has developed a telecommunications infrastructure that allows sensorizadas remote stations, to send data of its sensors, once every minute and simultaneously, to the calculation server running the solar forecasting numerical models. For it, the Canary Islands Institute of Technology has added a sophisticated communications network to its 30 weather stations measuring irradiation at strategic sites, areas with high penetration of photovoltaic generation or that have potential to host in the future photovoltaic power plants connected to the grid. In each one of the stations, irradiance and temperature measurement instruments have been installed, over inclined silicon cell, global radiation on horizontal surface and room temperature. Mobile telephone devices have been installed and programmed in each one of the weather stations, which allow the transfer of their data taking advantage of the UMTS service offered by the local telephone operator. Every minute the computer server running the numerical weather forecasting models receives data inputs from 120 instruments distributed over the 30 radiometric stations. As a the result, currently it exist a stable, flexible, safe and economic infrastructure of radiometric stations and telecommunications that allows, on the one hand, to have data in real time from all 30 remote weather stations, and on the other hand allows to communicate with them in order to reprogram them and to carry out maintenance works.

Metal stable isotopes in weathering and hydrology: Chapter 10

USGS Publications Warehouse

Bullen, Thomas D.; Holland, Heinrich; Turekian, K.

2014-01-01

This chapter highlights some of the major developments in the understanding of the causes of metal stable isotope compositional variability in and isotope fractionation between natural materials and provides numerous examples of how that understanding is providing new insights into weathering and hydrology. At this stage, our knowledge of causes of stable isotope compositional variability among natural materials is greatest for the metals lithium, magnesium, calcium, and iron, the isotopes of which have already provided important information on weathering and hydrological processes. Stable isotope compositional variability for other metals such as strontium, copper, zinc, chromium, barium, molybdenum, mercury, cadmium, and nickel has been demonstrated but is only beginning to be applied to questions related to weathering and hydrology, and several research groups are currently exploring the potential. And then there are other metals such as titanium, vanadium, rhenium, and tungsten that have yet to be explored for variability of stable isotope composition in natural materials, but which may hold untold surprises in their utility. This impressive list of metals having either demonstrated or potential stable isotope signals that could be used to address important unsolved questions related to weathering and hydrology, constitutes a powerful toolbox that will be increasingly utilized in the coming decades.

Changing Weather Extremes Call for Early Warning of Potential for Catastrophic Fire

NASA Astrophysics Data System (ADS)

Boer, Matthias M.; Nolan, Rachael H.; Resco De Dios, Víctor; Clarke, Hamish; Price, Owen F.; Bradstock, Ross A.

2017-12-01

Changing frequencies of extreme weather events and shifting fire seasons call for enhanced capability to forecast where and when forested landscapes switch from a nonflammable (i.e., wet fuel) state to the highly flammable (i.e., dry fuel) state required for catastrophic forest fires. Current forest fire danger indices used in Europe, North America, and Australia rate potential fire behavior by combining numerical indices of fuel moisture content, potential rate of fire spread, and fire intensity. These numerical rating systems lack the physical basis required to reliably quantify forest flammability outside the environments of their development or under novel climate conditions. Here, we argue that exceedance of critical forest flammability thresholds is a prerequisite for major forest fires and therefore early warning systems should be based on a reliable prediction of fuel moisture content plus a regionally calibrated model of how forest fire activity responds to variation in fuel moisture content. We demonstrate the potential of this approach through a case study in Portugal. We use a physically based fuel moisture model with historical weather and fire records to identify critical fuel moisture thresholds for forest fire activity and then show that the catastrophic June 2017 forest fires in central Portugal erupted shortly after fuels in the region dried out to historically unprecedented levels.

Evaluating the Impact of Atmospheric Infrared Sounder (AIRS) Data On Convective Forecasts

NASA Technical Reports Server (NTRS)

Kozlowski, Danielle; Zavodsky, Bradley

2011-01-01

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service (NWS) offices. SPoRT provides real-time NASA products and capabilities to its partners to address specific operational forecast challenges. The mission of SPoRT is to transition observations and research capabilities into operations to help improve short-term weather forecasts on a regional scale. Two areas of focus are data assimilation and modeling, which can to help accomplish SPoRT's programmatic goals of transitioning NASA data to operational users. Forecasting convective weather is one challenge that faces operational forecasters. Current numerical weather prediction (NWP) models that operational forecasters use struggle to properly forecast location, timing, intensity and/or mode of convection. Given the proper atmospheric conditions, convection can lead to severe weather. SPoRT's partners in the National Oceanic and Atmospheric Administration (NOAA) have a mission to protect the life and property of American citizens. This mission has been tested as recently as this 2011 severe weather season, which has seen more than 300 fatalities and injuries and total damages exceeding $10 billion. In fact, during the three day period from 25-27 April, 1,265 storms reports (362 tornado reports) were collected making this three day period one of most active in American history. To address the forecast challenge of convective weather, SPoRT produces a real-time NWP model called the SPoRT Weather Research and Forecasting (SPoRT-WRF), which incorporates unique NASA data sets. One of the NASA assets used in this unique model configuration is retrieved profiles from the Atmospheric Infrared Sounder (AIRS).The goal of this project is to determine the impact that these AIRS profiles have on the SPoRT-WRF forecasts by comparing to a current operational model and a control SPoRT-WRF model that does not contain AIRS profiles.

Creating a Realistic Weather Environment for Motion-Based Piloted Flight Simulation

NASA Technical Reports Server (NTRS)

Daniels, Taumi S.; Schaffner, Philip R.; Evans, Emory T.; Neece, Robert T.; Young, Steve D.

2012-01-01

A flight simulation environment is being enhanced to facilitate experiments that evaluate research prototypes of advanced onboard weather radar, hazard/integrity monitoring (HIM), and integrated alerting and notification (IAN) concepts in adverse weather conditions. The simulation environment uses weather data based on real weather events to support operational scenarios in a terminal area. A simulated atmospheric environment was realized by using numerical weather data sets. These were produced from the High-Resolution Rapid Refresh (HRRR) model hosted and run by the National Oceanic and Atmospheric Administration (NOAA). To align with the planned flight simulation experiment requirements, several HRRR data sets were acquired courtesy of NOAA. These data sets coincided with severe weather events at the Memphis International Airport (MEM) in Memphis, TN. In addition, representative flight tracks for approaches and departures at MEM were generated and used to develop and test simulations of (1) what onboard sensors such as the weather radar would observe; (2) what datalinks of weather information would provide; and (3) what atmospheric conditions the aircraft would experience (e.g. turbulence, winds, and icing). The simulation includes a weather radar display that provides weather and turbulence modes, derived from the modeled weather along the flight track. The radar capabilities and the pilots controls simulate current-generation commercial weather radar systems. Appropriate data-linked weather advisories (e.g., SIGMET) were derived from the HRRR weather models and provided to the pilot consistent with NextGen concepts of use for Aeronautical Information Service (AIS) and Meteorological (MET) data link products. The net result of this simulation development was the creation of an environment that supports investigations of new flight deck information systems, methods for incorporation of better weather information, and pilot interface and operational improvements for better aviation safety. This research is part of a larger effort at NASA to study the impact of the growing complexity of operations, information, and systems on crew decision-making and response effectiveness; and then to recommend methods for improving future designs.

Retrospective Analog Year Analyses Using NASA Satellite Data to Improve USDA's World Agricultural Supply and Demand Estimates

NASA Technical Reports Server (NTRS)

Teng, William; Shannon, Harlan

2011-01-01

The USDA World Agricultural Outlook Board (WAOB) is responsible for monitoring weather and climate impacts on domestic and foreign crop development. One of WAOB's primary goals is to determine the net cumulative effect of weather and climate anomalies on final crop yields. To this end, a broad array of information is consulted, including maps, charts, and time series of recent weather, climate, and crop observations; numerical output from weather and crop models; and reports from the press, USDA attach s, and foreign governments. The resulting agricultural weather assessments are published in the Weekly Weather and Crop Bulletin, to keep farmers, policy makers, and commercial agricultural interests informed of weather and climate impacts on agriculture. Because both the amount and timing of precipitation significantly affect crop yields, WAOB often uses precipitation time series to identify growing seasons with similar weather patterns and help estimate crop yields for the current growing season, based on observed yields in analog years. Historically, these analog years are visually identified; however, the qualitative nature of this method sometimes precludes the definitive identification of the best analog year. Thus, one goal of this study is to derive a more rigorous, statistical approach for identifying analog years, based on a modified coefficient of determination, termed the analog index (AI). A second goal is to compare the performance of AI for time series derived from surface-based observations vs. satellite-based measurements (NASA TRMM and other data).

On the potential use of radar-derived information in operational numerical weather prediction

NASA Technical Reports Server (NTRS)

Mcpherson, R. D.

1986-01-01

Estimates of requirements likely to be levied on a new observing system for mesoscale meteonology are given. Potential observing systems for mesoscale numerical weather prediction are discussed. Thermodynamic profiler radiometers, infrared radiometer atmospheric sounders, Doppler radar wind profilers and surveillance radar, and moisture profilers are among the instruments described.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Proposed Use of the NASA Ames Nebula Cloud Computing Platform for Numerical Weather Prediction and the Distribution of High Resolution Satellite Imagery

NASA Technical Reports Server (NTRS)

Limaye, Ashutosh S.; Molthan, Andrew L.; Srikishen, Jayanthi

2010-01-01

The development of the Nebula Cloud Computing Platform at NASA Ames Research Center provides an open-source solution for the deployment of scalable computing and storage capabilities relevant to the execution of real-time weather forecasts and the distribution of high resolution satellite data to the operational weather community. Two projects at Marshall Space Flight Center may benefit from use of the Nebula system. The NASA Short-term Prediction Research and Transition (SPoRT) Center facilitates the use of unique NASA satellite data and research capabilities in the operational weather community by providing datasets relevant to numerical weather prediction, and satellite data sets useful in weather analysis. SERVIR provides satellite data products for decision support, emphasizing environmental threats such as wildfires, floods, landslides, and other hazards, with interests in numerical weather prediction in support of disaster response. The Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS) has been configured for Nebula cloud computing use via the creation of a disk image and deployment of repeated instances. Given the available infrastructure within Nebula and the "infrastructure as a service" concept, the system appears well-suited for the rapid deployment of additional forecast models over different domains, in response to real-time research applications or disaster response. Future investigations into Nebula capabilities will focus on the development of a web mapping server and load balancing configuration to support the distribution of high resolution satellite data sets to users within the National Weather Service and international partners of SERVIR.

An evaluation of the impact of biomass burning smoke aerosol particles on near surface temperature forecasts

NASA Astrophysics Data System (ADS)

Zhang, J.; Reid, J. S.; Benedetti, A.; Christensen, M.; Marquis, J. W.

2016-12-01

Currently, with the improvements in aerosol forecast accuracies through aerosol data assimilation, the community is unavoidably facing a scientific question: is it worth the computational time to insert real-time aerosol analyses into numerical models for weather forecasts? In this study, by analyzing a significant biomass burning aerosol event that occurred in 2015 over the Northern part of the Central US, the impact of aerosol particles on near-surface temperature forecasts is evaluated. The aerosol direct surface cooling efficiency, which links surface temperature changes to aerosol loading, is derived from observational-based data for the first time. The potential of including real-time aerosol analyses into weather forecasting models for near surface temperature forecasts is also investigated.

Using GPS RO L1 data for calibration of the atmospheric path delay model for data reduction of the satellite altimetery observations.

NASA Astrophysics Data System (ADS)

Petrov, L.

2017-12-01

Processing satellite altimetry data requires the computation of path delayin the neutral atmosphere that is used for correcting ranges. The path delayis computed using numerical weather models and the accuracy of its computationdepends on the accuracy of numerical weather models. Accuracy of numerical modelsof numerical weather models over Antarctica and Greenland where there is a very sparse network of ground stations, is not well known. I used the dataset of GPS RO L1 data, computed predicted path delay for ROobservations using the numerical whether model GEOS-FPIT, formed the differences with observed path delay and used these differences for computationof the corrections to the a priori refractivity profile. These profiles wereused for computing corrections to the a priori zenith path delay. The systematic patter of these corrections are used for de-biasing of the the satellite altimetry results and for characterization of the systematic errorscaused by mismodeling atmosphere.

Coupling a Mesoscale Numerical Weather Prediction Model with Large-Eddy Simulation for Realistic Wind Plant Aerodynamics Simulations (Poster)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Draxl, C.; Churchfield, M.; Mirocha, J.

Wind plant aerodynamics are influenced by a combination of microscale and mesoscale phenomena. Incorporating mesoscale atmospheric forcing (e.g., diurnal cycles and frontal passages) into wind plant simulations can lead to a more accurate representation of microscale flows, aerodynamics, and wind turbine/plant performance. Our goal is to couple a numerical weather prediction model that can represent mesoscale flow [specifically the Weather Research and Forecasting model] with a microscale LES model (OpenFOAM) that can predict microscale turbulence and wake losses.

Chemical models for martian weathering profiles: Insights into formation of layered phyllosilicate and sulfate deposits

NASA Astrophysics Data System (ADS)

Zolotov, Mikhail Yu.; Mironenko, Mikhail V.

2016-09-01

Numerical chemical models for water-basalt interaction have been used to constrain the formation of stratified mineralogical sequences of Noachian clay-bearing rocks exposed in the Mawrth Vallis region and in other places on cratered martian highlands. The numerical approaches are based on calculations of water-rock type chemical equilibria and models which include rates of mineral dissolution. Results show that the observed clay-bearing sequences could have formed through downward percolation and neutralization of acidic H2SO4-HCl solutions. A formation of weathering profiles by slightly acidic fluids equilibrated with current atmospheric CO2 requires large volumes of water and is inconsistent with observations. Weathering by solutions equilibrated with putative dense CO2 atmospheres leads to consumption of CO2 to abundant carbonates which are not observed in clay stratigraphies. Weathering by H2SO4-HCl solutions leads to formation of amorphous silica, Al-rich clays, ferric oxides/oxyhydroxides, and minor titanium oxide and alunite at the top of weathering profiles. Mg-Fe phyllosilicates, Ca sulfates, zeolites, and minor carbonates precipitate from neutral and alkaline solutions at depth. Acidic weathering causes leaching of Na, Mg, and Ca from upper layers and accumulation of Mg-Na-Ca sulfate-chloride solutions at depth. Neutral MgSO4 type solutions dominate in middle parts of weathering profiles and could occur in deeper layers owing to incomplete alteration of Ca minerals and a limited trapping of Ca to sulfates. Although salts are not abundant in the Noachian geological formations, the results suggest the formation of Noachian salty solutions and their accumulation at depth. A partial freezing and migration of alteration solutions could have separated sulfate-rich compositions from low-temperature chloride brines and contributed to the observed diversity of salt deposits. A Hesperian remobilization and release of subsurface MgSO4 type solutions into newly-formed depressions could account for formation of some massive layered sulfate deposits through freezing or evaporation. This scenario explains the observed deficiency of salts in Noachian formations, a paucity of Hesperian phyllosilicates, and the occurrence of sulfate deposits in Valles Marineris troughs, chaotic terrains, and some craters of the Hesperian age.

Application of Raytracing Through the High Resolution Numerical Weather Model HIRLAM for the Analysis of European VLBI

NASA Technical Reports Server (NTRS)

Garcia-Espada, Susana; Haas, Rudiger; Colomer, Francisco

2010-01-01

An important limitation for the precision in the results obtained by space geodetic techniques like VLBI and GPS are tropospheric delays caused by the neutral atmosphere, see e.g. [1]. In recent years numerical weather models (NWM) have been applied to improve mapping functions which are used for tropospheric delay modeling in VLBI and GPS data analyses. In this manuscript we use raytracing to calculate slant delays and apply these to the analysis of Europe VLBI data. The raytracing is performed through the limited area numerical weather prediction (NWP) model HIRLAM. The advantages of this model are high spatial (0.2 deg. x 0.2 deg.) and high temporal resolution (in prediction mode three hours).

Why 1D electrical resistivity techniques can result in inaccurate siting of boreholes in hard rock aquifers and why electrical resistivity tomography must be preferred: the example of Benin, West Africa

NASA Astrophysics Data System (ADS)

Alle, Iboukoun Christian; Descloitres, Marc; Vouillamoz, Jean-Michel; Yalo, Nicaise; Lawson, Fabrice Messan Amen; Adihou, Akonfa Consolas

2018-03-01

Hard rock aquifers are of particular importance for supplying people with drinking water in Africa and in the world. Although the common use of one-dimensional (1D) electrical resistivity techniques to locate drilling site, the failure rate of boreholes is usually high. For instance, about 40% of boreholes drilled in hard rock aquifers in Benin are unsuccessful. This study investigates why the current use of 1D techniques (e.g. electrical profiling and electrical sounding) can result in inaccurate siting of boreholes, and checks the interest and the limitations of the use of two-dimensional (2D) Electrical Resistivity Tomography (ERT). Geophysical numerical modeling and comprehensive 1D and 2D resistivity surveys were carried out in hard rock aquifers in Benin. The experiments carried out at 7 sites located in different hard rock groups confirmed the results of the numerical modeling: the current use of 1D techniques can frequently leads to inaccurate siting, and ERT better reveals hydrogeological targets such as thick weathered zone (e.g. stratiform fractured layer and preferential weathering associated with subvertical fractured zone). Moreover, a cost analysis demonstrates that the use of ERT can save money at the scale of a drilling programme if ERT improves the success rate by only 5% as compared to the success rate obtained with 1D techniques. Finally, this study demonstrates, using the example of Benin, that the use of electrical resistivity profiling and sounding for siting boreholes in weathered hard rocks of western Africa should be discarded and replaced by the use of ERT technique, more efficient.

Numerical tools to predict the environmental loads for offshore structures under extreme weather conditions

NASA Astrophysics Data System (ADS)

Wu, Yanling

2018-05-01

In this paper, the extreme waves were generated using the open source computational fluid dynamic (CFD) tools — OpenFOAM and Waves2FOAM — using linear and nonlinear NewWave input. They were used to conduct the numerical simulation of the wave impact process. Numerical tools based on first-order (with and without stretching) and second-order NewWave are investigated. The simulation to predict force loading for the offshore platform under the extreme weather condition is implemented and compared.

The Impact of Current and Future Polar Orbiting Satellite Data on Numerical Weather Prediction at NASA/GSFC

NASA Technical Reports Server (NTRS)

Atlas, Robert

2004-01-01

The lack of adequate observational data continues to be recognized as a major factor limiting both atmospheric research and numerical prediction on a variety of temporal and spatial scales. Since the advent of meteorological satellites in the 1960's, a considerable research effort has been directed toward the design of space-borne meteorological sensors, the development of optimal methods for the utilization of these data, (and an assessment of the influence of existing satellite data and the potential influence of future satellite observations on numerical weather prediction. This has included both Observing System Experiments (OSEs) and Observing System Simulation Experiments (OSSEs). OSEs are conducted to evaluate the impact of specific observations or classes of observations on analyses and forecasts. While OSEs are performed with existing data, OSSEs are conducted to evaluate the potential for future observing systems to improve-NWP, as well as to evaluate trade-offs in observing system design, and to develop and test improved methods for data assimilation. At the conference, results from OSEs to evaluate satellite data sets that have recently become available to the global observing system, such as AIRS and Seawinds, and results from OSSEs to determine the potential impact of space-based lidar winds will be presented.

Development and Implementation of Dynamic Scripts to Execute Cycled GSI/WRF Forecasts

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi; Berndt, Emily; Li, Xuanli; Watson, Leela

2014-01-01

The Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model and Gridpoint Statistical Interpolation (GSI) data assimilation (DA) are the operational systems that make up the North American Mesoscale (NAM) model and the NAM Data Assimilation System (NDAS) analysis used by National Weather Service forecasters. The Developmental Testbed Center (DTC) manages and distributes the code for the WRF and GSI, but it is up to individual researchers to link the systems together and write scripts to run the systems, which can take considerable time for those not familiar with the code. The objective of this project is to develop and disseminate a set of dynamic scripts that mimic the unique cycling configuration of the operational NAM to enable researchers to develop new modeling and data assimilation techniques that can be easily transferred to operations. The current version of the SPoRT GSI/WRF Scripts (v3.0.1) is compatible with WRF v3.3 and GSI v3.0.

Impact of Cloud Analysis on Numerical Weather Prediction in the Galician Region of Spain.

NASA Astrophysics Data System (ADS)

Souto, M. J.; Balseiro, C. F.; Pérez-Muñuzuri, V.; Xue, M.; Brewster, K.

2003-01-01

The Advanced Regional Prediction System (ARPS) is applied to operational numerical weather prediction in Galicia, northwest Spain. The model is run daily for 72-h forecasts at a 10-km horizontal spacing. Located on the northwest coast of Spain and influenced by the Atlantic weather systems, Galicia has a high percentage (nearly 50%) of rainy days per year. For these reasons, the precipitation processes and the initialization of moisture and cloud fields are very important. Even though the ARPS model has a sophisticated data analysis system (`ADAS') that includes a 3D cloud analysis package, because of operational constraints, the current forecast starts from the 12-h forecast of the National Centers for Environmental Prediction Aviation Model (AVN). Still, procedures from the ADAS cloud analysis are being used to construct the cloud fields based on AVN data and then are applied to initialize the microphysical variables in ARPS. Comparisons of the ARPS predictions with local observations show that ARPS can predict very well both the daily total precipitation and its spatial distribution. ARPS also shows skill in predicting heavy rains and high winds, as observed during November 2000, and especially in the prediction of the 5 November 2000 storm that caused widespread wind and rain damage in Galicia. It is demonstrated that the cloud analysis contributes to the success of the precipitation forecasts.

Real-time Retrieving Atmospheric Parameters from Multi-GNSS Constellations

NASA Astrophysics Data System (ADS)

Li, X.; Zus, F.; Lu, C.; Dick, G.; Ge, M.; Wickert, J.; Schuh, H.

2016-12-01

The multi-constellation GNSS (e.g. GPS, GLONASS, Galileo, and BeiDou) bring great opportunities and challenges for real-time retrieval of atmospheric parameters for supporting numerical weather prediction (NWP) nowcasting or severe weather event monitoring. In this study, the observations from different GNSS are combined together for atmospheric parameter retrieving based on the real-time precise point positioning technique. The atmospheric parameters retrieved from multi-GNSS observations, including zenith total delay (ZTD), integrated water vapor (IWV), horizontal gradient (especially high-resolution gradient estimates) and slant total delay (STD), are carefully analyzed and evaluated by using the VLBI, radiosonde, water vapor radiometer and numerical weather model to independently validate the performance of individual GNSS and also demonstrate the benefits of multi-constellation GNSS for real-time atmospheric monitoring. Numerous results show that the multi-GNSS processing can provide real-time atmospheric products with higher accuracy, stronger reliability and better distribution, which would be beneficial for atmospheric sounding systems, especially for nowcasting of extreme weather.

Investigating Anomalies in the Output Generated by the Weather Research and Forecasting (WRF) Model

NASA Astrophysics Data System (ADS)

Decicco, Nicholas; Trout, Joseph; Manson, J. Russell; Rios, Manny; King, David

2015-04-01

The Weather Research and Forecasting (WRF) model is an advanced mesoscale numerical weather prediction (NWP) model comprised of two numerical cores, the Numerical Mesoscale Modeling (NMM) core, and the Advanced Research WRF (ARW) core. An investigation was done to determine the source of erroneous output generated by the NMM core. In particular were the appearance of zero values at regularly spaced grid cells in output fields and the NMM core's evident (mis)use of static geographic information at a resolution lower than the nesting level for which the core is performing computation. A brief discussion of the high-level modular architecture of the model is presented as well as methods utilized to identify the cause of these problems. Presented here are the initial results from a research grant, ``A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Richard Stockton College of NJ and the FAA''.

Historical winter weather assessment for snow fence design using a numerical weather model.

DOT National Transportation Integrated Search

2017-03-30

Noriaki Ohara, Ph.D., Assistant Professor (0000-0002-7829-0779) : Snow fence is an effective hazard mitigation measure for the low visibility and low friction of the road surface under : winter weather condition. Prevailing wind directions and snow p...

A Comparison of Wind Speed Data from Mechanical and Ultrasonic Anemometers

NASA Technical Reports Server (NTRS)

Short, D.; Wells, L.; Merceret, F.; Roeder, W. P.

2006-01-01

This study compared the performance of mechanical and ultrasonic anemometers at the Eastern Range (ER; Kennedy Space Center and Cape Canaveral Air Force Station on Florida's Atlantic coast) and the Western Range (WR; Vandenberg Air Force Base on California's Pacific coast). Launch Weather Officers, forecasters, and Range Safety analysts need to understand the performance of wind sensors at the ER and WR for weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The current ER and WR weather tower wind instruments are being changed from the current propeller-and-vane (ER) and cup-and-vane (WR) sensors to ultrasonic sensors through the Range Standardization and Automation (RSA) program. The differences between mechanical and ultrasonic techniques have been found to cause differences in the statistics of peak wind speed in previous studies. The 45th Weather Squadron (45 WS) and the 30th Weather Squadron (30 WS) requested the Applied Meteorology Unit (AMU) to compare data between RSA and current sensors to determine if there are significant differences. Approximately 3 weeks of Legacy and RSA wind data from each range were used in the study, archived during May and June 2005. The ER data spanned the full diurnal cycle, while the WR data was confined to 1000-1600 local time. The sample of 1-minute data from numerous levels on 5 different towers on each range totaled more than 500,000 minutes of data (482,979 minutes of data after quality control). The 10 towers were instrumented at several levels, ranging from 12 ft to 492 ft above ground level. The RSA sensors were collocated at the same vertical levels as the present sensors and typically within 15 ft horizontally of each another. Data from a total of 53 RSA ultrasonic sensors, collocated with present sensors were compared. The 1-minute average wind speed/direction and the 1-second peak wind speed/direction were compared.

Orogen and long-term carbon cycle, what numerical modelling can tell us about their interactions.

NASA Astrophysics Data System (ADS)

Maffre, P.; Godderis, Y.; Carretier, S.; Ladant, J. B.; Moquet, J. S.; Donnadieu, Y.

2017-12-01

If the uplift of current mountain ranges is often cited as a possible cause for Cenozoic cooling and the onset of the quaternary glaciation, this hypothesis is highly discussed. The main reason is that mountain uplift has a wide range of consequences, turning on or of sources or sinks of CO2. Most of these CO2 fluxes are still poorly constrained. Indeed, high erosion rates of mountain ranges increase silicate weathering by increasing fresh material supply (Goddéris et al. 2017) and enhance organic matter burial throughout intense sediment discharge by rivers (Galy et al. 2007). Yet, the effect of fresh matter supply by erosion is different if it happens on a weathering-limited or a supply-limited place (West 2012), and as eroded clasts are often weathered in pediments or floodplains (Moquet et al 2011, Lupker et al. 2012), it makes the issue more complex. Moreover, mountain ranges dramatically alter local and global climatic pattern by affecting atmospheric and oceanic circulation (Maffre et al. 2017), which must have consequences on weathering efficiency. Finally, it has been shown that the CO2 source due to sulphur oxidation can locally exceed the CO2 sink associated to silicate weathering (Torres et al. 2016) and may be relevant at geological timescale (Torres et al. 2014). Our aim here is to investigate theses processes in a global model in order to quantify their relative importance. We used the spatially resolved numerical model GEOCLIM (geoclimmodel.worpress.com) to test the effect of orography on CO2 fluxes with present-day continent configuration. We designed for that purpose two experiments, with and without orography, everything else kept as present-day state. Preliminary results show antagonist effects of mountain ranges. While erosion acts to enhance weathering efficiency when mountains are built, dryer and cooler conditions triggered by reorganization of ocean-atmosphere circulation act to reduce it. A first quantification using weathering data to constraint the model gives a probable range of 30% less to 100% more weathering with mountains (at constant CO2), depending on the sensitivity to the model to climate pattern or erosion. The uncertainty is primarily due to the lack of data.

The GOES-R Geostationary Lightning Mapper (GLM) and the Global Observing System for Total Lightning

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, R. J.; Koshak, W.; Buechler, D.; Carey, L.; Chronis, T.; Mach, D.; Bateman, M.; Peterson, H.; McCaul, E. W., Jr.;

Comparison of Weather Shows in Eastern Europe

NASA Astrophysics Data System (ADS)

Najman, M.

2009-09-01

Comparison of Weather Shows in Eastern Europe Television weather shows in Eastern Europe have in most cases in the high graphical standard. There is though a wast difference in duration and information content in the weather shows. There are few signs and regularities by which we can see the character of the weather show. The main differences are mainly caused by the income structure of the TV station. Either it is a fully privately funded TV relying on the TV commercials income. Or it is a public service TV station funded mainly by the national budget or fixed fee structure/tax. There are wast differences in duration and even a graphical presentation of the weather. Next important aspect is a supplier of the weather information and /or the processor. Shortly we can say, that when the TV show is produced by the national met office, the TV show consists of more scientific terms, synoptic maps, satellite imagery, etc. If the supplier is the private meteorological company, the weather show is more user-friendly, laical with less scientific terms. We are experiencing a massive shift in public weather knowledge and demand for information. In the past, weather shows consisted only of maps with weather icons. In todaýs world, even the laic weather shows consist partly of numerical weather model outputs - they are of course designed to be understandable and graphically attractive. Outputs of the numerical weather models used to be only a part of daily life of a professional meteorologist, today they are common part of life of regular people. Video samples are a part of this presentation.

On the analytic and numeric optimisation of airplane trajectories under real atmospheric conditions

NASA Astrophysics Data System (ADS)

Gonzalo, J.; Domínguez, D.; López, D.

2014-12-01

From the beginning of aviation era, economic constraints have forced operators to continuously improve the planning of the flights. The revenue is proportional to the cost per flight and the airspace occupancy. Many methods, the first started in the middle of last century, have explore analytical, numerical and artificial intelligence resources to reach the optimal flight planning. In parallel, advances in meteorology and communications allow an almost real-time knowledge of the atmospheric conditions and a reliable, error-bounded forecast for the near future. Thus, apart from weather risks to be avoided, airplanes can dynamically adapt their trajectories to minimise their costs. International regulators are aware about these capabilities, so it is reasonable to envisage some changes to allow this dynamic planning negotiation to soon become operational. Moreover, current unmanned airplanes, very popular and often small, suffer the impact of winds and other weather conditions in form of dramatic changes in their performance. The present paper reviews analytic and numeric solutions for typical trajectory planning problems. Analytic methods are those trying to solve the problem using the Pontryagin principle, where influence parameters are added to state variables to form a split condition differential equation problem. The system can be solved numerically -indirect optimisation- or using parameterised functions -direct optimisation-. On the other hand, numerical methods are based on Bellman's dynamic programming (or Dijkstra algorithms), where the fact that two optimal trajectories can be concatenated to form a new optimal one if the joint point is demonstrated to belong to the final optimal solution. There is no a-priori conditions for the best method. Traditionally, analytic has been more employed for continuous problems whereas numeric for discrete ones. In the current problem, airplane behaviour is defined by continuous equations, while wind fields are given in a discrete grid at certain time intervals. The research demonstrates advantages and disadvantages of each method as well as performance figures of the solutions found for typical flight conditions under static and dynamic atmospheres. This provides significant parameters to be used in the selection of solvers for optimal trajectories.

Investigation of the Mid-Atlantic coast sudden cold water

NASA Astrophysics Data System (ADS)

Sun, D.; Kafatos, M.; Liu, Z.; Chiu, L.

2003-12-01

In the midsummer of this year, it was reported that there was a tremendous change in ocean temperature along the Mid-Atlantic coast, dropping as much as 10 degrees overnight. This sudden sea surface temperature drop affected local tourism and fishing, keep the tourists out of water at this vacation time, caused local tuna fishing hasn't been as good this year, but the cold water lured chill-loving striped bass close to shore, and has two to three weeks of great rockfish, which fishermen could normally get till fall. This article investigates this event by using satellite observations, numerical model outputs, and surface weather analysis. It is found that the North Atlantic cold current, combined with the coastal upwelling driven by the weather influence might cause this sudden cold SST event.

Are Atmospheric Updrafts a Key to Unlocking Climate Forcing and Sensitivity?

DOE PAGES

Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel; ...

2016-06-08

Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less

Self-Organizing Maps-based ocean currents forecasting system.

PubMed

Vilibić, Ivica; Šepić, Jadranka; Mihanović, Hrvoje; Kalinić, Hrvoje; Cosoli, Simone; Janeković, Ivica; Žagar, Nedjeljka; Jesenko, Blaž; Tudor, Martina; Dadić, Vlado; Ivanković, Damir

2016-03-16

An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training.

Self-Organizing Maps-based ocean currents forecasting system

PubMed Central

Vilibić, Ivica; Šepić, Jadranka; Mihanović, Hrvoje; Kalinić, Hrvoje; Cosoli, Simone; Janeković, Ivica; Žagar, Nedjeljka; Jesenko, Blaž; Tudor, Martina; Dadić, Vlado; Ivanković, Damir

2016-01-01

An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training. PMID:26979129

Precipitation Estimates for Hydroelectricity

NASA Technical Reports Server (NTRS)

Tapiador, Francisco J.; Hou, Arthur Y.; de Castro, Manuel; Checa, Ramiro; Cuartero, Fernando; Barros, Ana P.

2011-01-01

Hydroelectric plants require precise and timely estimates of rain, snow and other hydrometeors for operations. However, it is far from being a trivial task to measure and predict precipitation. This paper presents the linkages between precipitation science and hydroelectricity, and in doing so it provides insight into current research directions that are relevant for this renewable energy. Methods described include radars, disdrometers, satellites and numerical models. Two recent advances that have the potential of being highly beneficial for hydropower operations are featured: the Global Precipitation Measuring (GPM) mission, which represents an important leap forward in precipitation observations from space, and high performance computing (HPC) and grid technology, that allows building ensembles of numerical weather and climate models.

WRF-Fire: coupled weather-wildland fire modeling with the weather research and forecasting model

Treesearch

Janice L. Coen; Marques Cameron; John Michalakes; Edward G. Patton; Philip J. Riggan; Kara M. Yedinak

2012-01-01

A wildland fire behavior module (WRF-Fire) was integrated into the Weather Research and Forecasting (WRF) public domain numerical weather prediction model. The fire module is a surface fire behavior model that is two-way coupled with the atmospheric model. Near-surface winds from the atmospheric model are interpolated to a finer fire grid and used, with fuel properties...

Weather models as virtual sensors to data-driven rainfall predictions in urban watersheds

NASA Astrophysics Data System (ADS)

Cozzi, Lorenzo; Galelli, Stefano; Pascal, Samuel Jolivet De Marc; Castelletti, Andrea

2013-04-01

Weather and climate predictions are a key element of urban hydrology where they are used to inform water management and assist in flood warning delivering. Indeed, the modelling of the very fast dynamics of urbanized catchments can be substantially improved by the use of weather/rainfall predictions. For example, in Singapore Marina Reservoir catchment runoff processes have a very short time of concentration (roughly one hour) and observational data are thus nearly useless for runoff predictions and weather prediction are required. Unfortunately, radar nowcasting methods do not allow to carrying out long - term weather predictions, whereas numerical models are limited by their coarse spatial scale. Moreover, numerical models are usually poorly reliable because of the fast motion and limited spatial extension of rainfall events. In this study we investigate the combined use of data-driven modelling techniques and weather variables observed/simulated with a numerical model as a way to improve rainfall prediction accuracy and lead time in the Singapore metropolitan area. To explore the feasibility of the approach, we use a Weather Research and Forecast (WRF) model as a virtual sensor network for the input variables (the states of the WRF model) to a machine learning rainfall prediction model. More precisely, we combine an input variable selection method and a non-parametric tree-based model to characterize the empirical relation between the rainfall measured at the catchment level and all possible weather input variables provided by WRF model. We explore different lead time to evaluate the model reliability for different long - term predictions, as well as different time lags to see how past information could improve results. Results show that the proposed approach allow a significant improvement of the prediction accuracy of the WRF model on the Singapore urban area.

Development and validation of a weather-based warning system to advise fungicide applications to control dollar spot on turfgrass.

PubMed

Smith, D L; Kerns, J P; Walker, N R; Payne, A F; Horvath, B; Inguagiato, J C; Kaminski, J E; Tomaso-Peterson, M; Koch, P L

2018-01-01

Dollar spot is one of the most common diseases of golf course turfgrass and numerous fungicide applications are often required to provide adequate control. Weather-based disease warning systems have been developed to more accurately time fungicide applications; however, they tend to be ineffective and are not currently in widespread use. The primary objective of this research was to develop a new weather-based disease warning system to more accurately advise fungicide applications to control dollar spot activity across a broad geographic and climactic range. The new dollar spot warning system was developed from data collected at field sites in Madison, WI and Stillwater, OK in 2008 and warning system validation sites were established in Madison, WI, Stillwater, OK, Knoxville, TN, State College, PA, Starkville, MS, and Storrs, CT between 2011 and 2016. A meta-analysis of all site-years was conducted and the most effective warning system for dollar spot development consisted of a five-day moving average of relative humidity and average daily temperature. Using this model the highest effective probability that provided dollar spot control similar to that of a calendar-based program across the numerous sites and years was 20%. Additional analysis found that the 20% spray threshold provided comparable control to the calendar-based program while reducing fungicide usage by up to 30%, though further refinement may be needed as practitioners implement this warning system in a range of environments not tested here. The weather-based dollar spot warning system presented here will likely become an important tool for implementing precision disease management strategies for future turfgrass managers, especially as financial and regulatory pressures increase the need to reduce pesticide usage on golf course turfgrass.

Development and validation of a weather-based warning system to advise fungicide applications to control dollar spot on turfgrass

PubMed Central

Smith, D. L.; Kerns, J. P.; Walker, N. R.; Payne, A. F.; Horvath, B.; Inguagiato, J. C.; Kaminski, J. E.; Tomaso-Peterson, M.

2018-01-01

Dollar spot is one of the most common diseases of golf course turfgrass and numerous fungicide applications are often required to provide adequate control. Weather-based disease warning systems have been developed to more accurately time fungicide applications; however, they tend to be ineffective and are not currently in widespread use. The primary objective of this research was to develop a new weather-based disease warning system to more accurately advise fungicide applications to control dollar spot activity across a broad geographic and climactic range. The new dollar spot warning system was developed from data collected at field sites in Madison, WI and Stillwater, OK in 2008 and warning system validation sites were established in Madison, WI, Stillwater, OK, Knoxville, TN, State College, PA, Starkville, MS, and Storrs, CT between 2011 and 2016. A meta-analysis of all site-years was conducted and the most effective warning system for dollar spot development consisted of a five-day moving average of relative humidity and average daily temperature. Using this model the highest effective probability that provided dollar spot control similar to that of a calendar-based program across the numerous sites and years was 20%. Additional analysis found that the 20% spray threshold provided comparable control to the calendar-based program while reducing fungicide usage by up to 30%, though further refinement may be needed as practitioners implement this warning system in a range of environments not tested here. The weather-based dollar spot warning system presented here will likely become an important tool for implementing precision disease management strategies for future turfgrass managers, especially as financial and regulatory pressures increase the need to reduce pesticide usage on golf course turfgrass. PMID:29522560

Assessing Climate Change Impacts for Military Installations in the Southwest United States During the Warm Season

NASA Astrophysics Data System (ADS)

Castro, C.

2013-05-01

Arid and semi-arid regions are experiencing some of the most adverse impacts of climate change with increased heat waves, droughts, and extreme weather. These events will likely exacerbate socioeconomic and political instabilities in regions where the United States has vital strategic interests and ongoing military operations. The Southwest U.S. is strategically important in that it houses some of the most spatially expansive and important military installations in the country. The majority of severe weather events in the Southwest occur in association with the North American monsoon system (NAMS), and current observational record has shown a 'wet gets wetter and dry gets drier' global monsoon precipitation trend. We seek to evaluate the warm season extreme weather projection in the Southwest U.S., and how the extremes can affect Department of Defense (DoD) military facilities in that region. A baseline methodology is being developed to select extreme warm season weather events based on historical sounding data and moisture surge observations from Gulf of California. Numerical Weather Prediction (NWP)-type high resolution simulations will be performed for the extreme events identified from Weather Research and Forecast (WRF) model simulations initiated from IPCC GCM and NCAR Reanalysis data in both climate control and climate change periods. The magnitude in extreme event changes will be analyzed, and the synoptic forcing patterns of the future severe thunderstorms will provide a guide line to assess if the military installations in the Southwest will become more or less susceptible to severe weather in the future.

Development, Implementation, and Skill Assessment of the NOAA/NOS Great Lakes Operational Forecast System

DTIC Science & Technology

2011-01-01

USA) 2011 Abstract The NOAA Great Lakes Operational Forecast System ( GLOFS ) uses near-real-time atmospheric observa- tions and numerical weather...Operational Oceanographic Products and Services (CO-OPS) in Silver Spring, MD. GLOFS has been making operational nowcasts and forecasts at CO-OPS... GLOFS ) uses near-real-time atmospheric observations and numerical weather prediction forecast guidance to produce three-dimensional forecasts of water

Medium-range fire weather forecasts

Treesearch

J.O. Roads; K. Ueyoshi; S.C. Chen; J. Alpert; F. Fujioka

1991-01-01

The forecast skill of theNational Meteorological Center's medium range forecast (MRF) numerical forecasts of fire weather variables is assessed for the period June 1,1988 to May 31,1990. Near-surface virtual temperature, relative humidity, wind speed and a derived fire weather index (FWI) are forecast well by the MRF model. However, forecast relative humidity has...

Waterspout Forecasting Method Over the Eastern Adriatic Using a High-Resolution Numerical Weather Model

NASA Astrophysics Data System (ADS)

Renko, Tanja; Ivušić, Sarah; Telišman Prtenjak, Maja; Šoljan, Vinko; Horvat, Igor

2018-03-01

In this study, a synoptic and mesoscale analysis was performed and Szilagyi's waterspout forecasting method was tested on ten waterspout events in the period of 2013-2016. Data regarding waterspout occurrences were collected from weather stations, an online survey at the official website of the National Meteorological and Hydrological Service of Croatia and eyewitness reports from newspapers and the internet. Synoptic weather conditions were analyzed using surface pressure fields, 500 hPa level synoptic charts, SYNOP reports and atmospheric soundings. For all observed waterspout events, a synoptic type was determined using the 500 hPa geopotential height chart. The occurrence of lightning activity was determined from the LINET lightning database, and waterspouts were divided into thunderstorm-related and "fair weather" ones. Mesoscale characteristics (with a focus on thermodynamic instability indices) were determined using the high-resolution (500 m grid length) mesoscale numerical weather model and model results were compared with the available observations. Because thermodynamic instability indices are usually insufficient for forecasting waterspout activity, the performance of the Szilagyi Waterspout Index (SWI) was tested using vertical atmospheric profiles provided by the mesoscale numerical model. The SWI successfully forecasted all waterspout events, even the winter events. This indicates that the Szilagyi's waterspout prognostic method could be used as a valid prognostic tool for the eastern Adriatic.

Outlook for Improved Numerical Weather Prediction Using Satellite Data with a Special Emphasis on the Hydrological Variables,

DTIC Science & Technology

1983-11-18

Prediction, June 6-9, 1983, Omaha, Nebr., AMS, pp. 269-274. (5) Bellon, A., S. Lovejoy , and G. L. Austin, 1980: Combining satellite and radar data...1979: Global sea-ice limits. In Inventory of Snow Cover and Sea Ice Data. Rep. GD-7, Institute of Arctic and Alpine Research, edited by R. G. Crane... parent organization in parentheses and location or current name in square brackets follow the acronym definition. AFCRL Air Force Cambridge Research

Applications for Near-Real Time Satellite Cloud and Radiation Products

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Palikonda, Rabindra; Chee, Thad L.; Bedka, Kristopher M.; Smith, W.; Ayers, Jeffrey K.; Benjamin, Stanley; Chang, F.-L.; Nguyen, Louis; Norris, Peter;

Flight Deck Weather Avoidance Decision Support: Implementation and Evaluation

NASA Technical Reports Server (NTRS)

Wu, Shu-Chieh; Luna, Rocio; Johnson, Walter W.

2013-01-01

Weather related disruptions account for seventy percent of the delays in the National Airspace System (NAS). A key component in the weather plan of the Next Generation of Air Transportation System (NextGen) is to assimilate observed weather information and probabilistic forecasts into the decision process of flight crews and air traffic controllers. In this research we explore supporting flight crew weather decision making through the development of a flight deck predicted weather display system that utilizes weather predictions generated by ground-based radar. This system integrates and presents this weather information, together with in-flight trajectory modification tools, within a cockpit display of traffic information (CDTI) prototype. that the CDTI features 2D and perspective 3D visualization models of weather. The weather forecast products that we implemented were the Corridor Integrated Weather System (CIWS) and the Convective Weather Avoidance Model (CWAM), both developed by MIT Lincoln Lab. We evaluated the use of CIWS and CWAM for flight deck weather avoidance in two part-task experiments. Experiment 1 compared pilots' en route weather avoidance performance in four weather information conditions that differed in the type and amount of predicted forecast (CIWS current weather only, CIWS current and historical weather, CIWS current and forecast weather, CIWS current and forecast weather and CWAM predictions). Experiment 2 compared the use of perspective 3D and 21/2D presentations of weather for flight deck weather avoidance. Results showed that pilots could take advantage of longer range predicted weather forecasts in performing en route weather avoidance but more research will be needed to determine what combinations of information are optimal and how best to present them.

Evaluation of the Impact of AIRS Radiance and Profile Data Assimilation in Partly Cloudy Regions

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi; Jedlovec, Gary

2013-01-01

Improvements to global and regional numerical weather prediction have been demonstrated through assimilation of data from NASA s Atmospheric Infrared Sounder (AIRS). Current operational data assimilation systems use AIRS radiances, but impact on regional forecasts has been much smaller than for global forecasts. Retrieved profiles from AIRS contain much of the information that is contained in the radiances and may be able to reveal reasons for this reduced impact. Assimilating AIRS retrieved profiles in an identical analysis configuration to the radiances, tracking the quantity and quality of the assimilated data in each technique, and examining analysis increments and forecast impact from each data type can yield clues as to the reasons for the reduced impact. By doing this with regional scale models individual synoptic features (and the impact of AIRS on these features) can be more easily tracked. This project examines the assimilation of hyperspectral sounder data used in operational numerical weather prediction by comparing operational techniques used for AIRS radiances and research techniques used for AIRS retrieved profiles. Parallel versions of a configuration of the Weather Research and Forecasting (WRF) model with Gridpoint Statistical Interpolation (GSI) are run to examine the impact AIRS radiances and retrieved profiles. Statistical evaluation of a long-term series of forecast runs will be compared along with preliminary results of in-depth investigations for select case comparing the analysis increments in partly cloudy regions and short-term forecast impacts.

Evaluation of the Impact of Atmospheric Infrared Sounder (AIRS) Radiance and Profile Data Assimilation in Partly Cloudy Regions

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi; Jedlovec, Gary

2013-01-01

Improvements to global and regional numerical weather prediction have been demonstrated through assimilation of data from NASA s Atmospheric Infrared Sounder (AIRS). Current operational data assimilation systems use AIRS radiances, but impact on regional forecasts has been much smaller than for global forecasts. Retrieved profiles from AIRS contain much of the information that is contained in the radiances and may be able to reveal reasons for this reduced impact. Assimilating AIRS retrieved profiles in an identical analysis configuration to the radiances, tracking the quantity and quality of the assimilated data in each technique, and examining analysis increments and forecast impact from each data type can yield clues as to the reasons for the reduced impact. By doing this with regional scale models individual synoptic features (and the impact of AIRS on these features) can be more easily tracked. This project examines the assimilation of hyperspectral sounder data used in operational numerical weather prediction by comparing operational techniques used for AIRS radiances and research techniques used for AIRS retrieved profiles. Parallel versions of a configuration of the Weather Research and Forecasting (WRF) model with Gridpoint Statistical Interpolation (GSI) are run to examine the impact AIRS radiances and retrieved profiles. Statistical evaluation of 6 weeks of forecast runs will be compared along with preliminary results of in-depth investigations for select case comparing the analysis increments in partly cloudy regions and short-term forecast impacts.

Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

NASA Technical Reports Server (NTRS)

Zhu, Jiang; Stevens, E.; Zavodsky, B. T.; Zhang, X.; Heinrichs, T.; Broderson, D.

2014-01-01

Data assimilation has been demonstrated very useful in improving both global and regional numerical weather prediction. Alaska has very coarser surface observation sites. On the other hand, it gets much more satellite overpass than lower 48 states. How to utilize satellite data to improve numerical prediction is one of hot topics among weather forecast community in Alaska. The Geographic Information Network of Alaska (GINA) at University of Alaska is conducting study on satellite data assimilation for WRF model. AIRS/CRIS sounder profile data are used to assimilate the initial condition for the customized regional WRF model (GINA-WRF model). Normalized standard deviation, RMSE, and correlation statistic analysis methods are applied to analyze one case of 48 hours forecasts and one month of 24-hour forecasts in order to evaluate the improvement of regional numerical model from Data assimilation. The final goal of the research is to provide improved real-time short-time forecast for Alaska regions.

Local Infrasound Variability Related to In Situ Atmospheric Observation

NASA Astrophysics Data System (ADS)

Kim, Keehoon; Rodgers, Arthur; Seastrand, Douglas

2018-04-01

Local infrasound is widely used to constrain source parameters of near-surface events (e.g., chemical explosions and volcanic eruptions). While atmospheric conditions are critical to infrasound propagation and source parameter inversion, local atmospheric variability is often ignored by assuming homogeneous atmospheres, and their impact on the source inversion uncertainty has never been accounted for due to the lack of quantitative understanding of infrasound variability. We investigate atmospheric impacts on local infrasound propagation by repeated explosion experiments with a dense acoustic network and in situ atmospheric measurement. We perform full 3-D waveform simulations with local atmospheric data and numerical weather forecast model to quantify atmosphere-dependent infrasound variability and address the advantage and restriction of local weather data/numerical weather model for sound propagation simulation. Numerical simulations with stochastic atmosphere models also showed nonnegligible influence of atmospheric heterogeneity on infrasound amplitude, suggesting an important role of local turbulence.

Effects of sounding temperature assimilation on weather forecasting - Model dependence studies

NASA Technical Reports Server (NTRS)

Ghil, M.; Halem, M.; Atlas, R.

1979-01-01

In comparing various methods for the assimilation of remote sounding information into numerical weather prediction (NWP) models, the problem of model dependence for the different results obtained becomes important. The paper investigates two aspects of the model dependence question: (1) the effect of increasing horizontal resolution within a given model on the assimilation of sounding data, and (2) the effect of using two entirely different models with the same assimilation method and sounding data. Tentative conclusions reached are: first, that model improvement as exemplified by increased resolution, can act in the same direction as judicious 4-D assimilation of remote sounding information, to improve 2-3 day numerical weather forecasts. Second, that the time continuous 4-D methods developed at GLAS have similar beneficial effects when used in the assimilation of remote sounding information into NWP models with very different numerical and physical characteristics.

The Value of Information and Geospatial Technologies for the analysis of tidal current patterns in the Guanabara Bay (Rio de Janeiro)

NASA Astrophysics Data System (ADS)

Isotta Cristofori, Elena; Demarchi, Alessandro; Facello, Anna; Cámaro, Walther; Hermosilla, Fernando; López, Jaime

2016-04-01

The study and validation of tidal current patterns relies on the combination of several data sources such as numerical weather prediction models, hydrodynamic models, weather stations, current drifters and remote sensing observations. The assessment of the accuracy and the reliability of produced patterns and the communication of results, including an easy to understand visualization of data, is crucial for a variety of stakeholders including decision-makers. The large diffusion of geospatial equipment such as GPS, current drifters, aerial photogrammetry, allows to collect data in the field using mobile and portable devices with a relative limited effort in terms of time and economic resources. Theses real-time measurements are essential in order to validate the models and specifically to assess the skill of the model during critical environmental conditions. Moreover, the considerable development in remote sensing technologies, cartographic services and GPS applications have enabled the creation of Geographic Information Systems (GIS) capable to store, analyze, manage and integrate spatial or geographical information with hydro-meteorological data. This valuable contribution of Information and geospatial technologies can benefit manifold decision-makers including high level sport athletes. While the numerical approach, commonly used to validate models with in-situ data, is more familiar for scientific users, high level sport users are not familiar with a numerical representations of data. Therefore the integration of data collected in the field into a GIS allows an immediate visualization of performed analysis into geographic maps. This visualization represents a particularly effective way to communicate current patterns assessment results and uncertainty in information, leading to an increase of confidence level about the forecast. The aim of this paper is to present the methodology set-up in collaboration with the Austrian Sailing Federation, for the study of tidal current patterns of the Guanabara Bay, venue for the sailing competitions of Rio 2016 Olympic Games. The methodology relies on the integration of a consistent amount of data collected in the field, hydrodynamic model output, cartography and "key-signs" visible on the water into a GIS, proving to be particularly useful to simplify the final information, to help the learning process and to improve the decision making.

Numerical Weather Prediction Models on Linux Boxes as tools in meteorological education in Hungary

NASA Astrophysics Data System (ADS)

Gyongyosi, A. Z.; Andre, K.; Salavec, P.; Horanyi, A.; Szepszo, G.; Mille, M.; Tasnadi, P.; Weidiger, T.

2012-04-01

Education of Meteorologist in Hungary - according to the Bologna Process - has three stages: BSc, MSc and PhD, and students graduating at each stage get the respective degree (BSc, MSc and PhD). The three year long base BSc course in Meteorology can be chosen by undergraduate students in the fields of Geosciences, Environmental Sciences and Physics. BasicsFundamentals in Mathematics (Calculus), Physics (General and Theoretical) Physics and Informatics are emphasized during their elementary education. The two year long MSc course - in which about 15 to 25 students are admitted each year - can be studied only at our the Eötvös Loránd uUniversity in the our country. Our aim is to give a basic education in all fields of Meteorology. Main topics are: Climatology, Atmospheric Physics, Atmospheric Chemistry, Dynamic and Synoptic Meteorology, Numerical Weather Prediction, modeling Modeling of surfaceSurface-atmosphere Iinteractions and Cclimate change. Education is performed in two branches: Climate Researcher and Forecaster. Education of Meteorologist in Hungary - according to the Bologna Process - has three stages: BSc, MSc and PhD, and students graduating at each stage get the respective degree. The three year long BSc course in Meteorology can be chosen by undergraduate students in the fields of Geosciences, Environmental Sciences and Physics. Fundamentals in Mathematics (Calculus), (General and Theoretical) Physics and Informatics are emphasized during their elementary education. The two year long MSc course - in which about 15 to 25 students are admitted each year - can be studied only at the Eötvös Loránd University in our country. Our aim is to give a basic education in all fields of Meteorology: Climatology, Atmospheric Physics, Atmospheric Chemistry, Dynamic and Synoptic Meteorology, Numerical Weather Prediction, Modeling of Surface-atmosphere Interactions and Climate change. Education is performed in two branches: Climate Researcher and Forecaster. Numerical modeling became a common tool in the daily practice of weather experts forecasters due to the i) increasing user demands for weather data by the costumers, ii) the growth in computer resources, iii) numerical weather prediction systems available for integration on affordable, off the shelf computers and iv) available input data (from ECMWF or NCEP) for model integrations. Beside learning the theoretical basis, since the last year. Students in their MSc or BSc Thesis Research or in Student's Research ProjectsStudent's Research Projects h have the opportunity to run numerical models and to analyze the outputs for different purposes including wind energy estimation, simulation of the dynamics of a polar low, and subtropical cyclones, analysis of the isentropic potential vorticity field, examination of coupled atmospheric dispersion models, etc. A special course in the application of numerical modeling has been held (is being announced for the upcoming semester) (is being announced for the upcoming semester) for our students in order to improve their skills on this field. Several numerical model (NRIPR ETA and WRF) systems have been adapted in the University and integrated WRF have been tested and used for the geographical region of the Carpathian Basin (NRIPR, ETA and WRF). Recently ALADIN/CHAPEAU the academic version of the ARPEGE ALADIN cy33t1 meso-scale numerical weather prediction model system (which is the operational forecasting tool of our National Weather Service) has been installed at our Institute. ALADIN is the operational forecasting model of the Hungarian Meteorological Service and developed in the framework of the international ALADIN co-operation. Our main objectives are i) the analysis of different typical weather situations, ii) fine tuning of parameterization schemes and the iii) comparison of the ALADIN/CHAPEAU and WRF model outputs based on case studies. The necessary hardware and software innovations has have been done. In the presentation the computer resources needed for the integration of both WRF and ALADIN/CHAPEAU models will be briefly described. The software developments performed for the evaluation and comparison of the different modeling systems will be demonstrated. The main objectives of the education program on the practical numerical weather modeling will be introduced, as well as its detailed thematics and the structure of the labs.

Application of Observing System Simulation Experiments (OSSEs) to determining science and user requirements for space-based missions

NASA Astrophysics Data System (ADS)

Atlas, R. M.

2016-12-01

Observing System Simulation Experiments (OSSEs) provide an effective method for evaluating the potential impact of proposed new observing systems, as well as for evaluating trade-offs in observing system design, and in developing and assessing improved methodology for assimilating new observations. As such, OSSEs can be an important tool for determining science and user requirements, and for incorporating these requirements into the planning for future missions. Detailed OSSEs have been conducted at NASA/ GSFC and NOAA/AOML in collaboration with Simpson Weather Associates and operational data assimilation centers over the last three decades. These OSSEs determined correctly the quantitative potential for several proposed satellite observing systems to improve weather analysis and prediction prior to their launch, evaluated trade-offs in orbits, coverage and accuracy for space-based wind lidars, and were used in the development of the methodology that led to the first beneficial impacts of satellite surface winds on numerical weather prediction. In this talk, the speaker will summarize the development of OSSE methodology, early and current applications of OSSEs and how OSSEs will evolve in order to enhance mission planning.

Comment on “Rain dance”

NASA Astrophysics Data System (ADS)

Orville, Harold D.

A recent news brief about cloud seeding work being conducted in Cohuila, Mexico, (“Rain Dance,” Eos, July 23, 1996) contained unfounded, off-hand remarks that are a disservice to many scientists and professionals in the cloud physics and weather modification community. The news brief stated that “most previous attempts to catalyze rainfall by cloud seeding have produced inconclusive results, and almost none of the experiments have had a sound scientific basis.” The inconclusive results are primarily statistical; many outstanding scientific results have developed from the 50-year history of research into weather modification.Also, most of the work that I know about has proceeded on the scientific basis that was developed over the years by the scientific and operational communities, and it is improving with time. It is grossly inaccurate to say that almost none of the experiments have had a sound scientific basis. Improvements in technology are strengthening that scientific basis, and current physical and numerical studies being conducted in many places are improving understanding. (See reviews of the status of weather modification from the American Meteorological Society [1992] and the World Meteorological Organization [1992].)

Quasi-most unstable modes: a window to 'À la carte' ensemble diversity?

NASA Astrophysics Data System (ADS)

Homar Santaner, Victor; Stensrud, David J.

2010-05-01

The atmospheric scientific community is nowadays facing the ambitious challenge of providing useful forecasts of atmospheric events that produce high societal impact. The low level of social resilience to false alarms creates tremendous pressure on forecasting offices to issue accurate, timely and reliable warnings.Currently, no operational numerical forecasting system is able to respond to the societal demand for high-resolution (in time and space) predictions in the 12-72h time span. The main reasons for such deficiencies are the lack of adequate observations and the high non-linearity of the numerical models that are currently used. The whole weather forecasting problem is intrinsically probabilistic and current methods aim at coping with the various sources of uncertainties and the error propagation throughout the forecasting system. This probabilistic perspective is often created by generating ensembles of deterministic predictions that are aimed at sampling the most important sources of uncertainty in the forecasting system. The ensemble generation/sampling strategy is a crucial aspect of their performance and various methods have been proposed. Although global forecasting offices have been using ensembles of perturbed initial conditions for medium-range operational forecasts since 1994, no consensus exists regarding the optimum sampling strategy for high resolution short-range ensemble forecasts. Bred vectors, however, have been hypothesized to better capture the growing modes in the highly nonlinear mesoscale dynamics of severe episodes than singular vectors or observation perturbations. Yet even this technique is not able to produce enough diversity in the ensembles to accurately and routinely predict extreme phenomena such as severe weather. Thus, we propose a new method to generate ensembles of initial conditions perturbations that is based on the breeding technique. Given a standard bred mode, a set of customized perturbations is derived with specified amplitudes and horizontal scales. This allows the ensemble to excite growing modes across a wider range of scales. Results show that this approach produces significantly more spread in the ensemble prediction than standard bred modes alone. Several examples that illustrate the benefits from this approach for severe weather forecasts will be provided.

Development of the Semi-implicit Time Integration in KIM-SH

NASA Astrophysics Data System (ADS)

NAM, H.

2015-12-01

The Korea Institute of Atmospheric Prediction Systems (KIAPS) was founded in 2011 by the Korea Meteorological Administration (KMA) to develop Korea's own global Numerical Weather Prediction (NWP) system as nine year (2011-2019) project. The KIM-SH is a KIAPS integrated model-spectral element based in the HOMME. In KIM-SH, the explicit schemes are employed. We introduce the three- and two-time-level semi-implicit scheme in KIM-SH as the time integration. Explicit schemes however have a tendancy to be unstable and require very small timesteps while semi-implicit schemes are very stable and can have much larger timesteps.We define the linear and reference values, then by definition of semi-implicit scheme, we apply the linear solver as GMRES. The numerical results from experiments will be introduced with the current development status of the time integration in KIM-SH. Several numerical examples are shown to confirm the efficiency and reliability of the proposed schemes.

Numerical weather prediction model tuning via ensemble prediction system

NASA Astrophysics Data System (ADS)

Jarvinen, H.; Laine, M.; Ollinaho, P.; Solonen, A.; Haario, H.

2011-12-01

This paper discusses a novel approach to tune predictive skill of numerical weather prediction (NWP) models. NWP models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. Currently, numerical values of these parameters are specified manually. In a recent dual manuscript (QJRMS, revised) we developed a new concept and method for on-line estimation of the NWP model parameters. The EPPES ("Ensemble prediction and parameter estimation system") method requires only minimal changes to the existing operational ensemble prediction infra-structure and it seems very cost-effective because practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating each member of the ensemble of predictions using different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In the presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an atmospheric general circulation model based ensemble prediction system show that the NWP model tuning capacity of EPPES scales up to realistic models and ensemble prediction systems. Finally, a global top-end NWP model tuning exercise with preliminary results is published.

78 FR 51267 - Hours of Service of Drivers: National Ready Mixed Concrete Association; Application for Exemption

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-20

... rule is extremely difficult due to the numerous variables associated with delivery (e.g., weather... 2 hours resulting from weather or unforeseen construction delays. NRMCA claims that these frequent...

Appropriate Simulants are a Requirement for Mars Surface Systems Technology Development

NASA Technical Reports Server (NTRS)

Edmunson, Jennifer E.; McLemore, Carole A.; Rickman, Douglas L.

2012-01-01

To date, there are two simulants for martian regolith: JSC Mars-1A, produced from palagonitic (weathered) basaltic tephra mined from the Pu'u Nene cinder cone in Hawaii [1] by commercial company Orbitec, and Mojave Mars Simulant (MMS), produced from Saddleback Basalt in the western Mojave desert by the Jet Propulsion Laboratory [2]. Until numerous recent orbiters, rovers, and landers were sent to Mars, weathered basalt was surmised to cover every inch of the martian landscape. All missions since Viking have disproven that the entire martian surface is weathered basalt. In fact, the outcrops, features, and surfaces that are significantly different from weathered basalt are too numerous to realistically count. There are gullies, evaporites, sand dunes, lake deposits, hydrothermal deposits, alluvium, etc. that indicate sedimentary and chemical processes. There is no one size fits all simulant. Each unique area requires its own simulant in order to test technologies and hardware, thereby reducing risk.

Adding Weather to Wargames

DTIC Science & Technology

2007-01-01

Aid (IWEDA) we developed techniques that allowed significant improvement in weather effects and impacts for wargames. TAWS was run for numerous and...found that the wargame realism was increased without impacting the run time. While these techniques are applicable to wargames in general, we tested...them by incorporation into the Advanced Warfighting Simulation (AWARS) model. AWARS was modified to incorporate weather impacts upon sensor

SAR observation and numerical modeling of tidal current wakes at the East China Sea offshore wind farm

NASA Astrophysics Data System (ADS)

Li, XiaoMing; Chi, Lequan; Chen, Xueen; Ren, YongZheng; Lehner, Susanne

2014-08-01

A TerraSAR-X (TS-X) Synthetic Aperture Radar (SAR) image acquired at the East China Sea offshore wind farm presents distinct wakes at a kilometer scale on the lee of the wind turbines. The presumption was that these wakes were caused by wind movement around turbine blades. However, wind analysis using spaceborne radiometer data, numerical weather prediction, and in situ measurements suggest that the prevailing wind direction did not align with the wakes. By analyzing measurement at the tidal gauge station and modeling of the tidal current field, these trailing wakes are interpreted to have formed when a strong tidal current impinged on the cylindrical monopiles of the wind turbines. A numerical simulation was further conducted to reproduce the tidal current wake under such conditions. Comparison of the simulated surface velocity in the wake region with the TS-X sea surface backscatter intensity shows a similar trend. Consequently, turbulence intensity (T.I.) of the tidal current wakes over multiple piles is studied using the TS-X observation. It is found that the T.I. has a logarithmic relation with distance. Furthermore, another case study showing wakes due to wind movement around turbine blades is presented to discuss the differences in the tidal current wakes and wind turbine wakes. The conclusion is drawn that small-scale wakes formed by interaction of the tidal current and the turbine piles could be also imaged by SAR when certain conditions are satisfied. The study is anticipated to draw more attentions to the impacts of offshore wind foundations on local hydrodynamic field.

Predictability of extreme weather events for NE U.S.: improvement of the numerical prediction using a Bayesian regression approach

NASA Astrophysics Data System (ADS)

Yang, J.; Astitha, M.; Anagnostou, E. N.; Hartman, B.; Kallos, G. B.

2015-12-01

Weather prediction accuracy has become very important for the Northeast U.S. given the devastating effects of extreme weather events in the recent years. Weather forecasting systems are used towards building strategies to prevent catastrophic losses for human lives and the environment. Concurrently, weather forecast tools and techniques have evolved with improved forecast skill as numerical prediction techniques are strengthened by increased super-computing resources. In this study, we examine the combination of two state-of-the-science atmospheric models (WRF and RAMS/ICLAMS) by utilizing a Bayesian regression approach to improve the prediction of extreme weather events for NE U.S. The basic concept behind the Bayesian regression approach is to take advantage of the strengths of two atmospheric modeling systems and, similar to the multi-model ensemble approach, limit their weaknesses which are related to systematic and random errors in the numerical prediction of physical processes. The first part of this study is focused on retrospective simulations of seventeen storms that affected the region in the period 2004-2013. Optimal variances are estimated by minimizing the root mean square error and are applied to out-of-sample weather events. The applicability and usefulness of this approach are demonstrated by conducting an error analysis based on in-situ observations from meteorological stations of the National Weather Service (NWS) for wind speed and wind direction, and NCEP Stage IV radar data, mosaicked from the regional multi-sensor for precipitation. The preliminary results indicate a significant improvement in the statistical metrics of the modeled-observed pairs for meteorological variables using various combinations of the sixteen events as predictors of the seventeenth. This presentation will illustrate the implemented methodology and the obtained results for wind speed, wind direction and precipitation, as well as set the research steps that will be followed in the future.

Creating Weather System Ensembles Through Synergistic Process Modeling and Machine Learning

NASA Astrophysics Data System (ADS)

Chen, B.; Posselt, D. J.; Nguyen, H.; Wu, L.; Su, H.; Braverman, A. J.

2017-12-01

Earth's weather and climate are sensitive to a variety of control factors (e.g., initial state, forcing functions, etc). Characterizing the response of the atmosphere to a change in initial conditions or model forcing is critical for weather forecasting (ensemble prediction) and climate change assessment. Input - response relationships can be quantified by generating an ensemble of multiple (100s to 1000s) realistic realizations of weather and climate states. Atmospheric numerical models generate simulated data through discretized numerical approximation of the partial differential equations (PDEs) governing the underlying physics. However, the computational expense of running high resolution atmospheric state models makes generation of more than a few simulations infeasible. Here, we discuss an experiment wherein we approximate the numerical PDE solver within the Weather Research and Forecasting (WRF) Model using neural networks trained on a subset of model run outputs. Once trained, these neural nets can produce large number of realization of weather states from a small number of deterministic simulations with speeds that are orders of magnitude faster than the underlying PDE solver. Our neural network architecture is inspired by the governing partial differential equations. These equations are location-invariant, and consist of first and second derivations. As such, we use a 3x3 lon-lat grid of atmospheric profiles as the predictor in the neural net to provide the network the information necessary to compute the first and second moments. Results indicate that the neural network algorithm can approximate the PDE outputs with high degree of accuracy (less than 1% error), and that this error increases as a function of the prediction time lag.

Ensemble Models

EPA Science Inventory

Ensemble forecasting has been used for operational numerical weather prediction in the United States and Europe since the early 1990s. An ensemble of weather or climate forecasts is used to characterize the two main sources of uncertainty in computer models of physical systems: ...

Error discrimination of an operational hydrological forecasting system at a national scale

NASA Astrophysics Data System (ADS)

Jordan, F.; Brauchli, T.

2010-09-01

The use of operational hydrological forecasting systems is recommended for hydropower production as well as flood management. However, the forecast uncertainties can be important and lead to bad decisions such as false alarms and inappropriate reservoir management of hydropower plants. In order to improve the forecasting systems, it is important to discriminate the different sources of uncertainties. To achieve this task, reanalysis of past predictions can be realized and provide information about the structure of the global uncertainty. In order to discriminate between uncertainty due to the weather numerical model and uncertainty due to the rainfall-runoff model, simulations assuming perfect weather forecast must be realized. This contribution presents the spatial analysis of the weather uncertainties and their influence on the river discharge prediction of a few different river basins where an operational forecasting system exists. The forecast is based on the RS 3.0 system [1], [2], which is also running the open Internet platform www.swissrivers.ch [3]. The uncertainty related to the hydrological model is compared to the uncertainty related to the weather prediction. A comparison between numerous weather prediction models [4] at different lead times is also presented. The results highlight an important improving potential of both forecasting components: the hydrological rainfall-runoff model and the numerical weather prediction models. The hydrological processes must be accurately represented during the model calibration procedure, while weather prediction models suffer from a systematic spatial bias. REFERENCES [1] Garcia, J., Jordan, F., Dubois, J. & Boillat, J.-L. 2007. "Routing System II, Modélisation d'écoulements dans des systèmes hydrauliques", Communication LCH n° 32, Ed. Prof. A. Schleiss, Lausanne [2] Jordan, F. 2007. Modèle de prévision et de gestion des crues - optimisation des opérations des aménagements hydroélectriques à accumulation pour la réduction des débits de crue, thèse de doctorat n° 3711, Ecole Polytechnique Fédérale, Lausanne [3] Keller, R. 2009. "Le débit des rivières au peigne fin", Revue Technique Suisse, N°7/8 2009, Swiss engineering RTS, UTS SA, Lausanne, p. 11 [4] Kaufmann, P., Schubiger, F. & Binder, P. 2003. Precipitation forecasting by a mesoscale numerical weather prediction (NWP) model : eight years of experience, Hydrology and Earth System

Coordination, Data Management and Enhancement of the International Arctic Buoy Programme (IABP) a US Interagency Arctic Buoy Programme \\201USIABP\\202 contribution to the IABP

DTIC Science & Technology

2013-09-30

data from the IABP ); 2.) Forecasting weather and sea ice conditions; 3.) Forcing, assimilation and validation of global weather and climate models ...International Arctic Buoy Programme ( IABP ) A US Interagency Arctic Buoy Programme (USIABP) contribution to the IABP Dr. Ignatius G. Rigor Polar...ice motion. These observations are assimilated into Numerical Weather Prediction (NWP) models that are used to forecast weather on synoptic time

Decay of sandstone monuments in Petra (Jordan): Gravity-induced stress as a stabilizing factor

NASA Astrophysics Data System (ADS)

Řihošek, Jaroslav; Bruthans, Jiří; Mašín, David; Filippi, Michal; Schweigstillova, Jana

2016-04-01

As demonstrated by physical experiments and numerical modeling the gravity-induced stress (stress in further text) in sandstone massive reduces weathering and erosion rate (Bruthans et al. 2014). This finding is in contrast to common view that stress threatens stability of man-made monuments carved to sandstone. Certain low- levels of gravity-induced stress can in fact stabilize and protect these forms against weathering and disintegration. The purpose of this investigation is to evaluate the effect of the stress on weathering of sandstone monuments at the Petra World Heritage Site in Jordan via field observations, salt weathering experiments, and physical and numerical modeling. Previous studies on weathering of Petra monuments have neglected the impact of stress, but the ubiquitous presence of stress-controlled landforms in Petra suggests that it has a substantial effect on weathering and erosion processes on man-made monuments and natural surfaces. Laboratory salt weathering experiments with cubes of Umm Ishrin sandstone from Petra demonstrated the inverse relationship between stress magnitude and decay rate. Physical modeling with Strelec locked sand from the Czech Republic was used to simulate weathering and decay of Petra monuments. Sharp forms subjected to water erosion decayed to rounded shapes strikingly similar to tombs in Petra subjected to more than 2000 years of weathering and erosion. The physical modeling results enabled visualization of the recession of monument surfaces in high spatial and temporal resolution and indicate that the recession rate of Petra monuments is far from constant both in space and time. Numerical modeling of stress fields confirms the physical modeling results. This novel approach to investigate weathering clearly demonstrates that increased stress decreases the decay rate of Petra monuments. To properly delineate the endangered zones of monuments, the potential damage caused by weathering agents should be combined with stress modeling and verified by documentation of real damage. This research was funded by Grant Agency of Charles University (no. 386815) Bruthans J., Soukup J., Vaculíková J., Filippi M., Schweigstillova J., Mayo A.L., Mašín D., Kletetschka G.,Řihošek J. (2014): Sandstone landforms shaped by negative feedback between stress and erosion. Nature Geoscience 7(8): 597-601.

Monitoring Intense Thunderstorms in the Hindu-Kush Himalayan Region

NASA Technical Reports Server (NTRS)

Gatlin, Patrick; Cecil, Daniel; Case, Jonathan; Bell, Jordan; Petersen, Walter; Adhikary, Bhupesh

2016-01-01

Some of the most intense thunderstorms on the planet routinely occur in the Hindu-Kush Himalaya region(HKH) region where many government organizations lack the capacity needed to predict, observe and effectively respond to the threats and hazards associated with high impact convective weather. This project combines innovative numerical weather prediction, satellite-based precipitation and land imagery techniques into a high impact weather assessment toolkit (HIWAT) that will build the capabilities of national meteorological departments and other weather sensitive agencies in the HKH region to assess the potential threats and impacts of high impact convective weather.

Wake Response to an Ocean-Feedback Mechanism: Madeira Island Case Study

NASA Astrophysics Data System (ADS)

Caldeira, Rui M. A.; Tomé, Ricardo

2013-08-01

We focus on an island wake episode that occurred in the Madeira Archipelago region of the north-east Atlantic at 32.5° N, 17° W. The Weather Research and Forecasting numerical model was used in a (one-way) downscaling mode, considering initial and boundary conditions from the European Centre for Medium-range Weather Forecasts system. The current literature emphasizes adiabatic effects on the dynamical aspects of atmospheric wakes. Changes in mountain height and consequently its relation to the atmospheric inversion layer should explain the shift in wake regimes, from a `strong-wake' to `weak-wake' scenario. Nevertheless, changes in sea-surface temperature variability in the lee of an island can induce similar regime shifts because of exposure to stronger solar radiation. Increase in evaporation contributes to the enhancement of convection and thus to the uplift of the stratified atmospheric layer above the critical height, with subsequent internal gravity wave activity.

Monitoring Marine Weather Systems Using Quikscat and TRMM Data

NASA Technical Reports Server (NTRS)

Liu, W.; Tang, W.; Datta, A.; Hsu, C.

1999-01-01

We do not understand nor are able to predict marine storms, particularly tropical cyclones, sufficiently well because ground-based measurements are sparse and operational numerical weather prediction models do not have sufficient spatial resolution nor accurate parameterization of the physics.

The solar atmosphere and the structure of active regions. [aircraft accidents, weather

NASA Technical Reports Server (NTRS)

Sturrock, P. A.

1975-01-01

Numerical analyses of solar activities are presented. The effect of these activities on aircraft and weather conditions was studied. Topics considered are: (1) solar flares; (2) solar X-rays; and (3) solar magnetic fields (charts are shown).

A Goddard Multi-Scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.;

A short-term ensemble wind speed forecasting system for wind power applications

NASA Astrophysics Data System (ADS)

Baidya Roy, S.; Traiteur, J. J.; Callicutt, D.; Smith, M.

2011-12-01

This study develops an adaptive, blended forecasting system to provide accurate wind speed forecasts 1 hour ahead of time for wind power applications. The system consists of an ensemble of 21 forecasts with different configurations of the Weather Research and Forecasting Single Column Model (WRFSCM) and a persistence model. The ensemble is calibrated against observations for a 2 month period (June-July, 2008) at a potential wind farm site in Illinois using the Bayesian Model Averaging (BMA) technique. The forecasting system is evaluated against observations for August 2008 at the same site. The calibrated ensemble forecasts significantly outperform the forecasts from the uncalibrated ensemble while significantly reducing forecast uncertainty under all environmental stability conditions. The system also generates significantly better forecasts than persistence, autoregressive (AR) and autoregressive moving average (ARMA) models during the morning transition and the diurnal convective regimes. This forecasting system is computationally more efficient than traditional numerical weather prediction models and can generate a calibrated forecast, including model runs and calibration, in approximately 1 minute. Currently, hour-ahead wind speed forecasts are almost exclusively produced using statistical models. However, numerical models have several distinct advantages over statistical models including the potential to provide turbulence forecasts. Hence, there is an urgent need to explore the role of numerical models in short-term wind speed forecasting. This work is a step in that direction and is likely to trigger a debate within the wind speed forecasting community.

Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

NASA Technical Reports Server (NTRS)

Bell, Jordan R.; Case, Jonathan L.; Molthan, Andrew L.

2011-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center develops new products and techniques that can be used in operational meteorology. The majority of these products are derived from NASA polar-orbiting satellite imagery from the Earth Observing System (EOS) platforms. One such product is a Greenness Vegetation Fraction (GVF) dataset, which is produced from Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the new SPoRT-MODIS GVF dataset on land surface models apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. The second phase of the project is to examine the impacts of the SPoRT GVF dataset on NWP using the Weather Research and Forecasting (WRF) model. Two separate WRF model simulations were made for individual severe weather case days using the NCEP GVF (control) and SPoRT GVF (experimental), with all other model parameters remaining the same. Based on the sensitivity results in these case studies, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and lower direct surface heating, which typically resulted in lower (higher) predicted 2-m temperatures (2-m dewpoint temperatures). The opposite was true for areas with lower GVF in the SPoRT model runs. These differences in the heating and evaporation rates produced subtle yet quantifiable differences in the simulated convective precipitation systems for the selected severe weather case examined.

The GOES-R/JPSS Approach for Identifying Hazardous Low Clouds: Overview and Operational Impacts

NASA Astrophysics Data System (ADS)

Calvert, Corey; Pavolonis, Michael; Lindstrom, Scott; Gravelle, Chad; Terborg, Amanda

2017-04-01

Low ceiling and visibility is a weather hazard that nearly every forecaster, in nearly every National Weather Service (NWS) Weather Forecast Office (WFO), must regularly address. In addition, national forecast centers such as the Aviation Weather Center (AWC), Alaska Aviation Weather Unit (AAWU) and the Ocean Prediction Center (OPC) are responsible for issuing low ceiling and visibility related products. As such, reliable methods for detecting and characterizing hazardous low clouds are needed. Traditionally, hazardous areas of Fog/Low Stratus (FLS) are identified using a simple stand-alone satellite product that is constructed by subtracting the 3.9 and 11 μm brightness temperatures. However, the 3.9-11 μm brightness temperature difference (BTD) has several major limitations. In an effort to address the limitations of the BTD product, the GOES-R Algorithm Working Group (AWG) developed an approach that fuses satellite, Numerical Weather Prediction (NWP) model, Sea Surface Temperature (SST) analyses, and other data sets (e.g. digital surface elevation maps, surface emissivity maps, and surface type maps) to determine the probability that hazardous low clouds are present using a naïve Bayesian classifier. In addition, recent research has focused on blending geostationary (e.g. GOES-R) and low earth orbit (e.g. JPSS) satellite data to further improve the products. The FLS algorithm has adopted an enterprise approach in that it can utilize satellite data from a variety of current and future operational sensors and NWP data from a variety of models. The FLS products are available in AWIPS/N-AWIPS/AWIPS-II and have been evaluated within NWS operations over the last four years as part of the Satellite Proving Ground. Forecaster feedback has been predominantly positive and references to these products within Area Forecast Discussions (AFD's) indicate that the products are influencing operational forecasts. At the request of the NWS, the FLS products are currently being transitioned to NOAA/NESDIS operations, which will ensure that users have long-term access to these products. This paper will provide an overview of the FLS products and illustrate how they are being used to improve transportation safety and efficiency.

The Global Drifter Program Currents, Sea Surface Temperature, Atmospheric Pressure and Waves in the World's OceanThe Global Drifter Program Currents, Sea Surface Temperature, Atmospheric Pressure and Waves in the World's Ocean

NASA Astrophysics Data System (ADS)

Centurioni, Luca

2017-04-01

The Global Drifter Program is the principal component of the Global Surface Drifting Buoy Array, a branch of NOAA's Global Ocean Observing System and a scientific project of the Data Buoy Cooperation Panel (DBCP). The DBCP is an international program coordinating the use of autonomous data buoys to observe atmospheric and oceanographic conditions over ocean areas where few other measurements are taken. The Global Drifter Program maintains an array of over 1,250 Lagrangian drifters, reporting in near real-time and designed measure 15 m depth Lagrangian currents, sea surface temperature (SST) and sea level atmospheric pressure (SLP), among others, to fulfill the needs to observe the air-sea interface at temporal and spatial scales adequate to support short to medium-range weather forecasting, ocean state estimates and climate science. This overview talk will discuss the main achievements of the program, the main impacts for satellite SST calibration and validation, for numerical weather prediction, and it will review the main scientific findings based on the use of Lagrangian currents. Finally, we will present new developments in Lagrangian drifter technology, which include special drifters designed to measure sea surface salinity, wind and directional wave spectra. New opportunities for expanding the scope of the Global Drifter Program will be discussed.

Numerical Methods in Atmospheric and Oceanic Modelling: The Andre J. Robert Memorial Volume

NASA Astrophysics Data System (ADS)

Rosmond, Tom

Most people, even including some in the scientific community, do not realize how much the weather forecasts they use to guide the activities of their daily lives depend on very complex mathematics and numerical methods that are the basis of modern numerical weather prediction (NWP). André Robert (1929-1993), to whom Numerical Methods in Atmospheric and Oceanic Modelling is dedicated, had a career that contributed greatly to the growth of NWP and the role that the atmospheric computer models of NWP play in our society. There are probably no NWP models running anywhere in the world today that do not use numerical methods introduced by Robert, and those of us who work with and use these models everyday are indebted to him.The first two chapters of the volume are chronicles of Robert's life and career. The first is a 1987 interview by Harold Ritchie, one of Robert's many proteges and colleagues at the Canadian Atmospheric Environment Service. The interview traces Robert's life from his birth in New York to French Canadian parents, to his emigration to Quebec at an early age, his education and early employment, and his rise in stature as one of the preeminent research meteorologists of our time. An amusing anecdote he relates is his impression of weather forecasts while he was considering his first job as a meteorologist in the early 1950s. A newspaper of the time placed the weather forecast and daily horoscope side by side, and Robert regarded each to have a similar scientific basis. Thankfully he soon realized there was a difference between the two, and his subsequent career certainly confirmed the distinction.

Turbulence sources in mountain terrain: results from MATERHORN program

NASA Astrophysics Data System (ADS)

Di Sabatino, Silvana; Leo, Laura S.; Fernando, Harindra J. S.; Pardyjak, Eric R.; Hocut, Chris M.

2016-04-01

Improving high-resolution numerical weather prediction in complex terrain is essential for the many applications involving mountain weather. It is commonly recognized that high intensity weather phenomena near mountains are a safety hazard to aircrafts and unmanned aerial vehicles, but the prediction of highly variable weather is often unsatisfactory due to inadequacy of resolution or lack of the correct dynamics in the model. Improving mountain weather forecasts has been the goal of the interdisciplinary Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) program (2011-2016). In this paper, we will report some of the findings focusing on several mechanisms of generating turbulence in near surface flows in the vicinity of an isolated mountain. Specifically, we will discuss nocturnal flows under low synoptic forcing. It has been demonstrated that such calm conditions are hard to predict in typical weather predictions models where forcing is dominated by local features that are poorly included in numerical models. It is found that downslope flows in calm and clear nights develop rapidly after sunset and usually persists for few hours. Owing to multiscale flow interactions, slope flows appear to be intermittent and disturbed, with a tendency to decay through the night yet periodically and unexpectedly generated. One of the interesting feature herein is the presence of oscillations that can be associated to different types of waves (e.g. internal and trapping waves) which may break to produce extra mixing. Pulsations of katabatic flow at critical internal-wave frequency, flow intrusions arriving from different topographies and shear layers of flow fanning out from the gaps all contribute to the weakly or intermittently turbulent state. Understanding of low frequency contributions to the total kinetic energy represent a step forward into modelling sub-grid effects in numerical models used for aviation applications.

A weather-driven model of malaria transmission.

PubMed

Hoshen, Moshe B; Morse, Andrew P

2004-09-06

Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission. This paper describes a mathematical-biological model of the parasite dynamics, comprising both the weather-dependent within-vector stages and the weather-independent within-host stages. Numerical evaluations of the model in both time and space show that it qualitatively reconstructs the prevalence of infection. A process-based modelling structure has been developed that may be suitable for the simulation of malaria forecasts based on seasonal weather forecasts.

Using random forests to diagnose aviation turbulence.

PubMed

Williams, John K

Atmospheric turbulence poses a significant hazard to aviation, with severe encounters costing airlines millions of dollars per year in compensation, aircraft damage, and delays due to required post-event inspections and repairs. Moreover, attempts to avoid turbulent airspace cause flight delays and en route deviations that increase air traffic controller workload, disrupt schedules of air crews and passengers and use extra fuel. For these reasons, the Federal Aviation Administration and the National Aeronautics and Space Administration have funded the development of automated turbulence detection, diagnosis and forecasting products. This paper describes a methodology for fusing data from diverse sources and producing a real-time diagnosis of turbulence associated with thunderstorms, a significant cause of weather delays and turbulence encounters that is not well-addressed by current turbulence forecasts. The data fusion algorithm is trained using a retrospective dataset that includes objective turbulence reports from commercial aircraft and collocated predictor data. It is evaluated on an independent test set using several performance metrics including receiver operating characteristic curves, which are used for FAA turbulence product evaluations prior to their deployment. A prototype implementation fuses data from Doppler radar, geostationary satellites, a lightning detection network and a numerical weather prediction model to produce deterministic and probabilistic turbulence assessments suitable for use by air traffic managers, dispatchers and pilots. The algorithm is scheduled to be operationally implemented at the National Weather Service's Aviation Weather Center in 2014.

Hurricane Forecasting with the High-resolution NASA Finite-volume General Circulation Model

NASA Technical Reports Server (NTRS)

Atlas, R.; Reale, O.; Shen, B.-W.; Lin, S.-J.; Chern, J.-D.; Putman, W.; Lee, T.; Yeh, K.-S.; Bosilovich, M.; Radakovich, J.

2004-01-01

A high-resolution finite-volume General Circulation Model (fvGCM), resulting from a development effort of more than ten years, is now being run operationally at the NASA Goddard Space Flight Center and Ames Research Center. The model is based on a finite-volume dynamical core with terrain-following Lagrangian control-volume discretization and performs efficiently on massive parallel architectures. The computational efficiency allows simulations at a resolution of a quarter of a degree, which is double the resolution currently adopted by most global models in operational weather centers. Such fine global resolution brings us closer to overcoming a fundamental barrier in global atmospheric modeling for both weather and climate, because tropical cyclones and even tropical convective clusters can be more realistically represented. In this work, preliminary results of the fvGCM are shown. Fifteen simulations of four Atlantic tropical cyclones in 2002 and 2004 are chosen because of strong and varied difficulties presented to numerical weather forecasting. It is shown that the fvGCM, run at the resolution of a quarter of a degree, can produce very good forecasts of these tropical systems, adequately resolving problems like erratic track, abrupt recurvature, intense extratropical transition, multiple landfall and reintensification, and interaction among vortices.

The Atmospheric Infrared Sounder- An Overview

NASA Technical Reports Server (NTRS)

Larnbrigtsen, Bjorn; Fetzer, Eric; Lee, Sung-Yung; Irion, Fredrick; Hearty, Thomas; Gaiser, Steve; Pagano, Thomas; Aumann, Hartmut; Chahine, Moustafa

2004-01-01

The Atmospheric Infrared Sounder (AIRS) was launched in May 2002. Along with two companion microwave sensors, it forms the AIRS Sounding Suite. This system is the most advanced atmospheric sounding system to date, with measurement accuracies far surpassing those available on current weather satellites. The data products are calibrated radiances from all three sensors and a number of derived geophysical parameters, including vertical temperature and humidity profiles, surface temperature, cloud fraction, cIoud top pressure, and profiles of ozone. These products are generated under cloudy as well as clear conditions. An ongoing calibration validation effort has confirmed that the system is very accurate and stable, and many of the geophysical parameters have been validated. AIRS is in some cases more accurate than any other source and can therefore be difficult to validate, but this offers interesting new research opportunities. The applications for the AIRS products range from numerical weather prediction to atmospheric research - where the AIRS water vapor products near the surface and in the mid to upper troposphere will make it possible to characterize and model phenomena that are key for short-term atmospheric processes, such as weather patterns, to long-term processes, such as interannual cycles (e.g., El Nino) and climate change.

Simulation of the Impact of New Aircraft- and Satellite-Based Ocean Surface Wind Measurements on H*Wind Analyses and Numerical Forecasts

NASA Technical Reports Server (NTRS)

Miller, Timothy; Atlas, Robert; Black, Peter; Chen, Shuyi; Hood, Robbie; Johnson, James; Jones, Linwood; Ruf, Chris; Uhlhorn, Eric; Krishnamurti, T. N.;

Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10): a World Weather Research Programme Project

NASA Astrophysics Data System (ADS)

Isaac, G. A.; Joe, P. I.; Mailhot, J.; Bailey, M.; Bélair, S.; Boudala, F. S.; Brugman, M.; Campos, E.; Carpenter, R. L.; Crawford, R. W.; Cober, S. G.; Denis, B.; Doyle, C.; Reeves, H. D.; Gultepe, I.; Haiden, T.; Heckman, I.; Huang, L. X.; Milbrandt, J. A.; Mo, R.; Rasmussen, R. M.; Smith, T.; Stewart, R. E.; Wang, D.; Wilson, L. J.

2014-01-01

A World Weather Research Programme (WWRP) project entitled the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) was developed to be associated with the Vancouver 2010 Olympic and Paralympic Winter Games conducted between 12 February and 21 March 2010. The SNOW-V10 international team augmented the instrumentation associated with the Winter Games and several new numerical weather forecasting and nowcasting models were added. Both the additional observational and model data were available to the forecasters in real time. This was an excellent opportunity to demonstrate existing capability in nowcasting and to develop better techniques for short term (0-6 h) nowcasts of winter weather in complex terrain. Better techniques to forecast visibility, low cloud, wind gusts, precipitation rate and type were evaluated. The weather during the games was exceptionally variable with many periods of low visibility, low ceilings and precipitation in the form of both snow and rain. The data collected should improve our understanding of many physical phenomena such as the diabatic effects due to melting snow, wind flow around and over terrain, diurnal flow reversal in valleys associated with daytime heating, and precipitation reductions and increases due to local terrain. Many studies related to these phenomena are described in the Special Issue on SNOW-V10 for which this paper was written. Numerical weather prediction and nowcast models have been evaluated against the unique observational data set now available. It is anticipated that the data set and the knowledge learned as a result of SNOW-V10 will become a resource for other World Meteorological Organization member states who are interested in improving forecasts of winter weather.

Seafloor weathering buffering climate: numerical experiments

NASA Astrophysics Data System (ADS)

Farahat, N. X.; Archer, D. E.; Abbot, D. S.

2013-12-01

Continental silicate weathering is widely held to consume atmospheric CO2 at a rate controlled in part by temperature, resulting in a climate-weathering feedback [Walker et al., 1981]. It has been suggested that weathering of oceanic crust of warm mid-ocean ridge flanks also has a CO2 uptake rate that is controlled by climate [Sleep and Zahnle, 2001; Brady and Gislason, 1997]. Although this effect might not be significant on present-day Earth [Caldeira, 1995], seafloor weathering may be more pronounced during snowball states [Le Hir et al., 2008], during the Archean when seafloor spreading rates were faster [Sleep and Zahnle, 2001], and on waterworld planets [Abbot et al., 2012]. Previous studies of seafloor weathering have made significant contributions using qualitative, generally one-box, models, and the logical next step is to extend this work using a spatially resolved model. For example, experiments demonstrate that seafloor weathering reactions are temperature dependent, but it is not clear whether the deep ocean temperature affects the temperature at which the reactions occur, or if instead this temperature is set only by geothermal processes. Our goal is to develop a 2-D numerical model that can simulate hydrothermal circulation and resulting alteration of oceanic basalts, and can therefore address such questions. A model of diffusive and convective heat transfer in fluid-saturated porous media simulates hydrothermal circulation through porous oceanic basalt. Unsteady natural convection is solved for using a Darcy model of porous media flow that has been extensively benchmarked. Background hydrothermal circulation is coupled to mineral reaction kinetics of basaltic alteration and hydrothermal mineral precipitation. In order to quantify seafloor weathering as a climate-weathering feedback process, this model focuses on hydrothermal reactions that influence carbon uptake as well as ocean alkalinity: silicate rock dissolution, calcium and magnesium leaching reactions, carbonate precipitation, and clay formation.

Simulation of the Impact of New Aircraft- and Satellite-Based Ocean Surface Wind Measurements on H*Wind Analyses and Numerical Forecasts

NASA Technical Reports Server (NTRS)

Miller, Timothy; Atlas, Robert; Black, Peter; Buckley, Courtney; Chen, Shuyi; Hood, robbie; Johnson, James; Jones, Linwood; Ruf, Chris; Uhlhorn, Eric;

Aviation Weather Information Requirements Study

NASA Technical Reports Server (NTRS)

Keel, Byron M.; Stancil, Charles E.; Eckert, Clifford A.; Brown, Susan M.; Gimmestad, Gary G.; Richards, Mark A.; Schaffner, Philip R. (Technical Monitor)

2000-01-01

The Aviation Safety Program (AvSP) has as its goal an improvement in aviation safety by a factor of 5 over the next 10 years and a factor of 10 over the next 20 years. Since weather has a big impact on aviation safety and is associated with 30% of all aviation accidents, Weather Accident Prevention (WxAP) is a major element under this program. The Aviation Weather Information (AWIN) Distribution and Presentation project is one of three projects under this element. This report contains the findings of a study conducted by the Georgia Tech Research Institute (GTRI) under the Enhanced Weather Products effort, which is a task under AWIN. The study examines current aviation weather products and there application. The study goes on to identify deficiencies in the current system and to define requirements for aviation weather products that would lead to an increase in safety. The study also provides an overview the current set of sensors applied to the collection of aviation weather information. New, modified, or fused sensor systems are identified which could be applied in improving the current set of weather products and in addressing the deficiencies defined in the report. In addition, the study addresses and recommends possible sensors for inclusion in an electronic pilot reporting (EPIREP) system.

Benefits of Sharing Information from Commercial Airborne Forward-Looking Sensors in the Next Generation Air Transportation System

NASA Technical Reports Server (NTRS)

Schaffner, Philip R.; Harrah, Steven; Neece, Robert T.

2012-01-01

The air transportation system of the future will need to support much greater traffic densities than are currently possible, while preserving or improving upon current levels of safety. Concepts are under development to support a Next Generation Air Transportation System (NextGen) that by some estimates will need to support up to three times current capacity by the year 2025. Weather and other atmospheric phenomena, such as wake vortices and volcanic ash, constitute major constraints on airspace system capacity and can present hazards to aircraft if encountered. To support safe operations in the NextGen environment advanced systems for collection and dissemination of aviation weather and environmental information will be required. The envisioned NextGen Network Enabled Weather (NNEW) infrastructure will be a critical component of the aviation weather support services, providing access to a common weather picture for all system users. By taking advantage of Network Enabled Operations (NEO) capabilities, a virtual 4-D Weather Data Cube with aviation weather information from many sources will be developed. One new source of weather observations may be airborne forward-looking sensors, such as the X-band weather radar. Future sensor systems that are the subject of current research include advanced multi-frequency and polarimetric radar, a variety of Lidar technologies, and infrared imaging spectrometers.

Evolution of porosity and diffusivity associated with chemical weathering of a basalt clast

DOE Office of Scientific and Technical Information (OSTI.GOV)

Navarre-Sitchler, A.; Steefel, C.I.; Yang, L.

Weathering of rocks as a result of exposure to water and the atmosphere can cause significant changes in their chemistry and porosity. In low-porosity rocks, such as basalts, changes in porosity, resulting from chemical weathering, are likely to modify the rock's effective diffusivity and permeability, affecting the rate of solute transport and thus potentially the rate of overall weathering to the extent that transport is the rate limiting step. Changes in total porosity as a result of mineral dissolution and precipitation have typically been used to calculate effective diffusion coefficients through Archie's law for reactive transport simulations of chemical weathering,more » but this approach fails to account for unconnected porosity that does not contribute to transport. In this study, we combine synchrotron X-ray microcomputed tomography ({mu}CT) and laboratory and numerical diffusion experiments to examine changes in both total and effective porosity and effective diffusion coefficients across a weathering interface in a weathered basalt clast from Costa Rica. The {mu}CT data indicate that below a critical value of {approx}9%, the porosity is largely unconnected in the basalt clast. The {mu}CT data were further used to construct a numerical pore network model to determine upscaled, effective diffusivities as a function of total porosity (ranging from 3 to 30%) for comparison with diffusivities determined in laboratory tracer experiments. By using effective porosity as the scaling parameter and accounting for critical porosity, a model is developed that accurately predicts continuum-scale effective diffusivities across the weathering interface of the basalt clast.« less

ARM - Midlatitude Continental Convective Clouds

DOE Data Explorer

Jensen, Mike; Bartholomew, Mary Jane; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-19

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

ARM - Midlatitude Continental Convective Clouds (comstock-hvps)

DOE Data Explorer

Jensen, Mike; Comstock, Jennifer; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

2012-01-06

Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

E-GVAP, the EIG EUMETNET GNSS Water Vapour Programme

NASA Astrophysics Data System (ADS)

Jones, J.; de Haan, S.; Vedel, H.

2011-12-01

The main purpose of E-GVAP is to deliver near real-time (NRT) ground based GNSS delay data for usage in operational meteorology. This involves the collection and processing of raw GNSS data to estimate zenith total delay (ZTD) and subsequent collection and distribution of ZTD data to European national meteorological services. Validation and quality control, production of 2D animated water vapour maps, development of best practices for GNSS data processing and data usage in Numerical Weather Prediction (NWP) models, are other important aspects. Furthermore there is a current push for more real-time observations which would have positive impacts in high both resolution NWP and for nowcasting applications. We present an overview of the current status of E-GVAP.

Tailored high-resolution numerical weather forecasts for energy efficient predictive building control

NASA Astrophysics Data System (ADS)

Stauch, V. J.; Gwerder, M.; Gyalistras, D.; Oldewurtel, F.; Schubiger, F.; Steiner, P.

2010-09-01

The high proportion of the total primary energy consumption by buildings has increased the public interest in the optimisation of buildings' operation and is also driving the development of novel control approaches for the indoor climate. In this context, the use of weather forecasts presents an interesting and - thanks to advances in information and predictive control technologies and the continuous improvement of numerical weather prediction (NWP) models - an increasingly attractive option for improved building control. Within the research project OptiControl (www.opticontrol.ethz.ch) predictive control strategies for a wide range of buildings, heating, ventilation and air conditioning (HVAC) systems, and representative locations in Europe are being investigated with the aid of newly developed modelling and simulation tools. Grid point predictions for radiation, temperature and humidity of the high-resolution limited area NWP model COSMO-7 (see www.cosmo-model.org) and local measurements are used as disturbances and inputs into the building system. The control task considered consists in minimizing energy consumption whilst maintaining occupant comfort. In this presentation, we use the simulation-based OptiControl methodology to investigate the impact of COSMO-7 forecasts on the performance of predictive building control and the resulting energy savings. For this, we have selected building cases that were shown to benefit from a prediction horizon of up to 3 days and therefore, are particularly suitable for the use of numerical weather forecasts. We show that the controller performance is sensitive to the quality of the weather predictions, most importantly of the incident radiation on differently oriented façades. However, radiation is characterised by a high temporal and spatial variability in part caused by small scale and fast changing cloud formation and dissolution processes being only partially represented in the COSMO-7 grid point predictions. On the other hand, buildings are affected by particularly local weather conditions at the building site. To overcome this discrepancy, we make use of local measurements to statistically adapt the COSMO-7 model output to the meteorological conditions at the building. For this, we have developed a general correction algorithm that exploits systematic properties of the COSMO-7 prediction error and explicitly estimates the degree of temporal autocorrelation using online recursive estimation. The resulting corrected predictions are improved especially for the first few hours being the most crucial for the predictive controller and, ultimately for the reduction of primary energy consumption using predictive control. The use of numerical weather forecasts in predictive building automation is one example in a wide field of weather dependent advanced energy saving technologies. Our work particularly highlights the need for the development of specifically tailored weather forecast products by (statistical) postprocessing in order to meet the requirements of specific applications.

Weather forecasting expert system study

NASA Technical Reports Server (NTRS)

1985-01-01

Weather forecasting is critical to both the Space Transportation System (STS) ground operations and the launch/landing activities at NASA Kennedy Space Center (KSC). The current launch frequency places significant demands on the USAF weather forecasters at the Cape Canaveral Forecasting Facility (CCFF), who currently provide the weather forecasting for all STS operations. As launch frequency increases, KSC's weather forecasting problems will be great magnified. The single most important problem is the shortage of highly skilled forecasting personnel. The development of forecasting expertise is difficult and requires several years of experience. Frequent personnel changes within the forecasting staff jeopardize the accumulation and retention of experience-based weather forecasting expertise. The primary purpose of this project was to assess the feasibility of using Artificial Intelligence (AI) techniques to ameliorate this shortage of experts by capturing aria incorporating the forecasting knowledge of current expert forecasters into a Weather Forecasting Expert System (WFES) which would then be made available to less experienced duty forecasters.

Mechanical weathering and rock erosion by climate-dependent subcritical cracking

NASA Astrophysics Data System (ADS)

Eppes, Martha-Cary; Keanini, Russell

2017-06-01

This work constructs a fracture mechanics framework for conceptualizing mechanical rock breakdown and consequent regolith production and erosion on the surface of Earth and other terrestrial bodies. Here our analysis of fracture mechanics literature explicitly establishes for the first time that all mechanical weathering in most rock types likely progresses by climate-dependent subcritical cracking under virtually all Earth surface and near-surface environmental conditions. We substantiate and quantify this finding through development of physically based subcritical cracking and rock erosion models founded in well-vetted fracture mechanics and mechanical weathering, theory, and observation. The models show that subcritical cracking can culminate in significant rock fracture and erosion under commonly experienced environmental stress magnitudes that are significantly lower than rock critical strength. Our calculations also indicate that climate strongly influences subcritical cracking—and thus rock weathering rates—irrespective of the source of the stress (e.g., freezing, thermal cycling, and unloading). The climate dependence of subcritical cracking rates is due to the chemophysical processes acting to break bonds at crack tips experiencing these low stresses. We find that for any stress or combination of stresses lower than a rock's critical strength, linear increases in humidity lead to exponential acceleration of subcritical cracking and associated rock erosion. Our modeling also shows that these rates are sensitive to numerous other environment, rock, and mineral properties that are currently not well characterized. We propose that confining pressure from overlying soil or rock may serve to suppress subcritical cracking in near-surface environments. These results are applicable to all weathering processes.

Use of simulated satellite radiances from a mesoscale numerical model to understand kinematic and dynamic processes

NASA Technical Reports Server (NTRS)

Kalb, Michael; Robertson, Franklin; Jedlovec, Gary; Perkey, Donald

1987-01-01

Techniques by which mesoscale numerical weather prediction model output and radiative transfer codes are combined to simulate the radiance fields that a given passive temperature/moisture satellite sensor would see if viewing the evolving model atmosphere are introduced. The goals are to diagnose the dynamical atmospheric processes responsible for recurring patterns in observed satellite radiance fields, and to develop techniques to anticipate the ability of satellite sensor systems to depict atmospheric structures and provide information useful for numerical weather prediction (NWP). The concept of linking radiative transfer and dynamical NWP codes is demonstrated with time sequences of simulated radiance imagery in the 24 TIROS vertical sounder channels derived from model integrations for March 6, 1982.

Atmospheric Diabatic Heating in Different Weather States and the General Circulation

NASA Technical Reports Server (NTRS)

Rossow, William B.; Zhang, Yuanchong; Tselioudis, George

2016-01-01

Analysis of multiple global satellite products identifies distinctive weather states of the atmosphere from the mesoscale pattern of cloud properties and quantifies the associated diabatic heating/cooling by radiative flux divergence, precipitation, and surface sensible heat flux. The results show that the forcing for the atmospheric general circulation is a very dynamic process, varying strongly at weather space-time scales, comprising relatively infrequent, strong heating events by ''stormy'' weather and more nearly continuous, weak cooling by ''fair'' weather. Such behavior undercuts the value of analyses of time-averaged energy exchanges in observations or numerical models. It is proposed that an analysis of the joint time-related variations of the global weather states and the general circulation on weather space-time scales might be used to establish useful ''feedback like'' relationships between cloud processes and the large-scale circulation.

Walker Branch Throughfall Displacement Experiment Data Report: Site Characterization, System Performance, Weather, Species Composition, and Growth (NDP-078 and 078A)

DOE Data Explorer

Cushman, Robert M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States), Carbon Dioxide Information Analysis Center, Environmental Sciences Division; Hanson, Paul J. [Oak Ridge National Laboratory, Oak Ridge, TN (USA), Environmental Sciences Division; Todd, Donald E. [Oak Ridge National Laboratory, Oak Ridge, TN (USA), Environmental Sciences Division; Riggs, Jeffery S. [Oak Ridge National Laboratory, Oak Ridge, TN (USA), Instrumentation and Controls Division; Wolfe, Mark E. [Tennessee Valley Authority, Norris, TN (USA); O'Neill, Elizabeth G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States), Environmental Sciences Division

2001-07-01

This numeric data package provides data sets, and accompanying documentation, on site characterization, system performance, weather, species composition, and growth for the Throughfall Displacement Experiment, which was established in the Walker Branch Watershed of East Tennessee to provide data on the responses of forests to altered precipitation regimes. The specific data sets include soil water content and potential, coarse fraction of the soil profile, litter layer temperature, soil temperature, monthly weather, daily weather, hourly weather, species composition of trees and saplings, mature tree and sapling annual growth, and relative leaf area index. Fortran and SAS(TM) access codes are provided to read the ASCII data files.

UTM Weather Presentation

NASA Technical Reports Server (NTRS)

Chan, William N.; Kopardekar, Parimal H.; Carmichael, Bruce; Cornman, Larry

2017-01-01

Presentation highlighting how weather affected UAS operations during the UTM field tests. Research to develop UAS weather translation models with a description of current and future work for UTM weather.

Observing System Forecast Experiments at the DAO

NASA Technical Reports Server (NTRS)

Atlas, Robert

2001-01-01

Since the advent of meteorological satellites in the 1960's, numerous experiments have been conducted in order to evaluate the impact of these and other data on atmospheric analysis and prediction. Such studies have included both OSE'S and OSSE's. The OSE's were conducted to evaluate the impact of specific observations or classes of observations on analyses and forecasts. Such experiments have been performed for selected types of conventional data and for various satellite data sets as they became available. (See for example the 1989 ECMWF/EUMETSAT workshop proceedings on "The use of satellite data in operational numerical weather prediction" and the references contained therein.) The ODYSSEY were conducted to evaluate the potential for future observing systems to improve Numerical Weather Prediction NWP and to plan for the Global Weather Experiment and more recently for EVANS (Atlas et al., 1985a; Arnold and Day, 1986; Hoffman et al., 1990). In addition, OSSE's have been run to evaluate trade-offs in the design of observing systems and observing networks (Atlas and Emmitt, 1991; Rohaly and Krishnamurti, 1993), and to test new methodology for data assimilation (Atlas and Bloom, 1989).

The measurement of winds over the ocean from Skylab with application to measuring and forecasting typhoons and hurricanes

NASA Technical Reports Server (NTRS)

Cardone, V. J.; Pierson, W. J.

1975-01-01

On Skylab, a combination microwave radar-radiometer (S193) made measurements in a tropical hurricane (AVA), a tropical storm, and various extratropical wind systems. The winds at each cell scanned by the instrument were determined by objective numerical analysis techniques. The measured radar backscatter is compared to the analyzed winds and shown to provide an accurate method for measuring winds from space. An operational version of the instrument on an orbiting satellite will be able to provide the kind of measurements in tropical cyclones available today only by expensive and dangerous aircraft reconnaissance. Additionally, the specifications of the wind field in the tropical boundary layer should contribute to improved accuracy of tropical cyclone forecasts made with numerical weather predictions models currently being applied to the tropical atmosphere.

Towards assimilation of InSAR data in operational weather models

NASA Astrophysics Data System (ADS)

Mulder, Gert; van Leijen, Freek; Barkmeijer, Jan; de Haan, Siebren; Hanssen, Ramon

2017-04-01

InSAR signal delays due to the varying atmospheric refractivity are a potential data source to improve weather models [1]. Especially with the launch of the new Sentinel-1 satellites, which increases data coverage, latency and accessibility, it may become possible to operationalize the assimilation of differential integrated refractivity (DIR) values in numerical weather models. Although studies exist on comparison between InSAR data and weather models [2], the impact of assimilation of DIR values in an operational weather model has never been assessed. In this study we present different ways to assimilate DIR values in an operational weather model and show the first forecast results. There are different possibilities to assimilate InSAR-data in a weather model. For example, (i) absolute DIR values can be derived using additional GNSS zenith or slant delay values, (ii) DIR values can be converted to water vapor pressures, or (iii) water vapor pressures can be derived for different heights by combining GNSS and InSAR data. However, an increasing number of assumptions in these processing steps will increase the uncertainty in the final results. Therefore, we chose to insert the InSAR derived DIR values after minimal additional processing. In this study we use the HARMONIE model [3], which is a spectral, non-hydrostatic model with a resolution of about 2.5 km. Currently, this is the operational model in 11 European countries and based on the AROME model [4]. To assimilate the DIR values in the weather model we use a simple adjustment of the weather parameters over the full slant column to match the DIR values. This is a first step towards a more sophisticated approach based on the 3D-VAR or 4D-VAR schemes [5]. Where both assimilation schemes can correct for different weather parameters simultaneously, and 4D-VAR allow us to assimilate DIR values at the exact moment of satellite overpass instead of the start of the forecast window. The approach will be demonstrated based on several case studies. This research can be seen as a first step towards the operational use of InSAR data in state-of-the-art weather models and can be a driver for the design and development for new SAR missions, such as NISAR. References: [1] Hanssen, R. F., Weckwerth, T. M., Zebker, H. A., & Klees, R. (1999). High-resolution water vapor mapping from interferometric radar measurements.Science, 283(5406), 1297-1299. [2] P. Mateus, R. Tomé, G. Nico and J. Catalão, "Three-Dimensional Variational Assimilation of InSAR PWV Using the WRFDA Model," in IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 12, pp. 7323-7330, Dec. 2016. [3] Navascués, B., Calvo, J., Morales, G., Santos, C., Callado, A., Cansado, A., ... & García-Colombo, O. (2013). Long-term verification of HIRLAM and ECMWF forecasts over southern europe: History and perspectives of numerical weather prediction at AEMET. Atmospheric Research, 125, 20-33. [4] Seity, Y., P. Brousseau, S. Malardel, G. Hello, P. Bénard, F. Bouttier, C. Lac, and V. Masson, 2011: The AROME-France Convective-Scale Operational Model. Mon. Wea. Rev., 139, 976-991. [5] Lorenc, A. C. and Rawlins, F. (2005), Why does 4D-Var beat 3D-Var?. Q.J.R. Meteorol. Soc., 131: 3247-3257.

Atmospheric Electrical Activity and the Prospects for Improving Short-Term, Weather Forcasting

NASA Technical Reports Server (NTRS)

Goodman, Steven J.

2003-01-01

How might lightning measurements be used to improve short-term (0-24 hr) weather forecasting? We examine this question under two different prediction strategies. These include integration of lightning data into short-term forecasts (nowcasts) of convective (including severe) weather hazards and the assimilation of lightning data into cloud-resolving numerical weather prediction models. In each strategy we define specific metrics of forecast improvement and a progress assessment. We also address the conventional observing system deficiencies and potential gap-filling information that can be addressed through the use of the lightning measurement.

A weather-driven model of malaria transmission

PubMed Central

Hoshen, Moshe B; Morse, Andrew P

2004-01-01

Background Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission. Methods This paper describes a mathematical-biological model of the parasite dynamics, comprising both the weather-dependent within-vector stages and the weather-independent within-host stages. Results Numerical evaluations of the model in both time and space show that it qualitatively reconstructs the prevalence of infection. Conclusion A process-based modelling structure has been developed that may be suitable for the simulation of malaria forecasts based on seasonal weather forecasts. PMID:15350206

Atmospheric Test Models and Numerical Experiments for the Simulation of the Global Distributions of Weather Data Transponders III. Horizontal Distributions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Molenkamp, C.R.; Grossman, A.

1999-12-20

A network of small balloon-borne transponders which gather very high resolution wind and temperature data for use by modern numerical weather predication models has been proposed to improve the reliability of long-range weather forecasts. The global distribution of an array of such transponders is simulated using LLNL's atmospheric parcel transport model (GRANTOUR) with winds supplied by two different general circulation models. An initial study used winds from CCM3 with a horizontal resolution of about 3 degrees in latitude and longitude, and a second study used winds from NOGAPS with a 0.75 degree horizontal resolution. Results from both simulations show thatmore » reasonable global coverage can be attained by releasing balloons from an appropriate set of launch sites.« less

International Cooperative for Aerosol Prediction Workshop on Aerosol Forecast Verification

NASA Technical Reports Server (NTRS)

Benedetti, Angela; Reid, Jeffrey S.; Colarco, Peter R.

2011-01-01

The purpose of this workshop was to reinforce the working partnership between centers who are actively involved in global aerosol forecasting, and to discuss issues related to forecast verification. Participants included representatives from operational centers with global aerosol forecasting requirements, a panel of experts on Numerical Weather Prediction and Air Quality forecast verification, data providers, and several observers from the research community. The presentations centered on a review of current NWP and AQ practices with subsequent discussion focused on the challenges in defining appropriate verification measures for the next generation of aerosol forecast systems.

Workshop Summary: International Cooperative for Aerosol Prediction Workshop On Aerosol Forecast Verification

NASA Technical Reports Server (NTRS)

Benedetti, Angela; Reid, Jeffrey S.; Colarco, Peter R.

2011-01-01

The purpose of this workshop was to reinforce the working partnership between centers who are actively involved in global aerosol forecasting, and to discuss issues related to forecast verification. Participants included representatives from operational centers with global aerosol forecasting requirements, a panel of experts on Numerical Weather Prediction and Air Quality forecast verification, data providers, and several observers from the research community. The presentations centered on a review of current NWP and AQ practices with subsequent discussion focused on the challenges in defining appropriate verification measures for the next generation of aerosol forecast systems.

Investigation of Convective Initiation Along a Dryline Using Observations and Numerical Weather Prediction Model

NASA Astrophysics Data System (ADS)

Weldegaber, M. H.; Demoz, B. B.; Sparling, L.; Hoff, R. M.; Chiao, S.

2007-12-01

A narrow zone of strong horizontal moisture gradient, known as a dryline, is frequently observed over portions of the Southern Great Plains of the United States. The dryline is a boundary separating warm, moist maritime air from the Gulf of Mexico and hot, dry continental air from southwest U.S. and northern Mexico. The dryline acts as a focus for severe convective storms, and often leads to flooding and tornadoes. Although most storms initiate at or near the dryline, the exact processes by which convection is triggered and the preferred location for convection along the dryline are not well understood. Because the underlying processes are highly nonlinear, current numerical weather prediction (NWP) models show poor skill in their ability to accurately forecast these events. In this research a non-convective dryline case over Oklahoma and Texas panhandle on 22 May 2002 was considered. Using extensive high spatial and temporal resolution observational data from the International H2O Project, a field campaign in 2002 (IHOP_2002), and the National Center for Atmospheric Research (NCAR) Weather Forecasting and Research (WRF) model moisture evolution and variability in the boundary layer is thoroughly analyzed and investigated. Performance of the model and the possible reason why the anticipated dryline on 22 May 2002 did not trigger convective storm over Homestead - OK area are discussed. Results of the observational analysis indicate that abundant moisture did not sustain over Homestead - OK area during 22 May 2002. Moreover, vertical structure of water vapor mixing ratio indicate that moisture was not deep enough for vertically moving air parcels due to the dryline convergence provide the necessary destabilization effect to support deep convection initiation during this period.

Sensitivity analysis of numerical weather prediction radiative schemes to forecast direct solar radiation over Australia

NASA Astrophysics Data System (ADS)

Mukkavilli, S. K.; Kay, M. J.; Taylor, R.; Prasad, A. A.; Troccoli, A.

2014-12-01

The Australian Solar Energy Forecasting System (ASEFS) project requires forecasting timeframes which range from nowcasting to long-term forecasts (minutes to two years). As concentrating solar power (CSP) plant operators are one of the key stakeholders in the national energy market, research and development enhancements for direct normal irradiance (DNI) forecasts is a major subtask. This project involves comparing different radiative scheme codes to improve day ahead DNI forecasts on the national supercomputing infrastructure running mesoscale simulations on NOAA's Weather Research & Forecast (WRF) model. ASEFS also requires aerosol data fusion for improving accurate representation of spatio-temporally variable atmospheric aerosols to reduce DNI bias error in clear sky conditions over southern Queensland & New South Wales where solar power is vulnerable to uncertainities from frequent aerosol radiative events such as bush fires and desert dust. Initial results from thirteen years of Bureau of Meteorology's (BOM) deseasonalised DNI and MODIS NASA-Terra aerosol optical depth (AOD) anomalies demonstrated strong negative correlations in north and southeast Australia along with strong variability in AOD (~0.03-0.05). Radiative transfer schemes, DNI and AOD anomaly correlations will be discussed for the population and transmission grid centric regions where current and planned CSP plants dispatch electricity to capture peak prices in the market. Aerosol and solar irradiance datasets include satellite and ground based assimilations from the national BOM, regional aerosol researchers and agencies. The presentation will provide an overview of this ASEFS project task on WRF and results to date. The overall goal of this ASEFS subtask is to develop a hybrid numerical weather prediction (NWP) and statistical/machine learning multi-model ensemble strategy that meets future operational requirements of CSP plant operators.

Enviro-HIRLAM online integrated meteorology-chemistry modelling system: strategy, methodology, developments and applications (v7.2)

NASA Astrophysics Data System (ADS)

Baklanov, Alexander; Smith Korsholm, Ulrik; Nuterman, Roman; Mahura, Alexander; Pagh Nielsen, Kristian; Hansen Sass, Bent; Rasmussen, Alix; Zakey, Ashraf; Kaas, Eigil; Kurganskiy, Alexander; Sørensen, Brian; González-Aparicio, Iratxe

2017-08-01

The Environment - High Resolution Limited Area Model (Enviro-HIRLAM) is developed as a fully online integrated numerical weather prediction (NWP) and atmospheric chemical transport (ACT) model for research and forecasting of joint meteorological, chemical and biological weather. The integrated modelling system is developed by the Danish Meteorological Institute (DMI) in collaboration with several European universities. It is the baseline system in the HIRLAM Chemical Branch and used in several countries and different applications. The development was initiated at DMI more than 15 years ago. The model is based on the HIRLAM NWP model with online integrated pollutant transport and dispersion, chemistry, aerosol dynamics, deposition and atmospheric composition feedbacks. To make the model suitable for chemical weather forecasting in urban areas, the meteorological part was improved by implementation of urban parameterisations. The dynamical core was improved by implementing a locally mass-conserving semi-Lagrangian numerical advection scheme, which improves forecast accuracy and model performance. The current version (7.2), in comparison with previous versions, has a more advanced and cost-efficient chemistry, aerosol multi-compound approach, aerosol feedbacks (direct and semi-direct) on radiation and (first and second indirect effects) on cloud microphysics. Since 2004, the Enviro-HIRLAM has been used for different studies, including operational pollen forecasting for Denmark since 2009 and operational forecasting atmospheric composition with downscaling for China since 2017. Following the main research and development strategy, further model developments will be extended towards the new NWP platform - HARMONIE. Different aspects of online coupling methodology, research strategy and possible applications of the modelling system, and fit-for-purpose model configurations for the meteorological and air quality communities are discussed.

ON THE IMPACT OF SUPER RESOLUTION WSR-88D DOPPLER RADAR DATA ASSIMILATION ON HIGH RESOLUTION NUMERICAL MODEL FORECASTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiswell, S

2009-01-11

Assimilation of radar velocity and precipitation fields into high-resolution model simulations can improve precipitation forecasts with decreased 'spin-up' time and improve short-term simulation of boundary layer winds (Benjamin, 2004 & 2007; Xiao, 2008) which is critical to improving plume transport forecasts. Accurate description of wind and turbulence fields is essential to useful atmospheric transport and dispersion results, and any improvement in the accuracy of these fields will make consequence assessment more valuable during both routine operation as well as potential emergency situations. During 2008, the United States National Weather Service (NWS) radars implemented a significant upgrade which increased the real-timemore » level II data resolution to 8 times their previous 'legacy' resolution, from 1 km range gate and 1.0 degree azimuthal resolution to 'super resolution' 250 m range gate and 0.5 degree azimuthal resolution (Fig 1). These radar observations provide reflectivity, velocity and returned power spectra measurements at a range of up to 300 km (460 km for reflectivity) at a frequency of 4-5 minutes and yield up to 13.5 million point observations per level in super-resolution mode. The migration of National Weather Service (NWS) WSR-88D radars to super resolution is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current operational mesoscale model domains utilize grid spacing several times larger than the legacy data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of super resolution reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution is investigated here to determine the impact of the improved data resolution on model predictions.« less

The issues of current rainfall estimation techniques in mountain natural multi-hazard investigation

NASA Astrophysics Data System (ADS)

Zhuo, Lu; Han, Dawei; Chen, Ningsheng; Wang, Tao

2017-04-01

Mountain hazards (e.g., landslides, debris flows, and floods) induced by rainfall are complex phenomena that require good knowledge of rainfall representation at different spatiotemporal scales. This study reveals rainfall estimation from gauges is rather unrepresentative over a large spatial area in mountain regions. As a result, the conventional practice of adopting the triggering threshold for hazard early warning purposes is insufficient. The main reason is because of the huge orographic influence on rainfall distribution. Modern rainfall estimation methods such as numerical weather prediction modelling and remote sensing utilising radar from the space or on land are able to provide spatially more representative rainfall information in mountain areas. But unlike rain gauges, they only indirectly provide rainfall measurements. Remote sensing suffers from many sources of errors such as weather conditions, attenuation and sampling methods, while numerical weather prediction models suffer from spatiotemporal and amplitude errors depending on the model physics, dynamics, and model configuration. A case study based on Sichuan, China is used to illustrate the significant difference among the three aforementioned rainfall estimation methods. We argue none of those methods can be relied on individually, and the challenge is on how to make the full utilisation of the three methods conjunctively because each of them only provides partial information. We propose that a data fusion approach should be adopted based on the Bayesian inference method. However such an approach requires the uncertainty information from all those estimation techniques which still need extensive research. We hope this study will raise the awareness of this important issue and highlight the knowledge gap that should be filled in so that such a challenging problem could be tackled collectively by the community.

Recent examples of mesoscale numerical forecasts of severe weather events along the east coast

NASA Technical Reports Server (NTRS)

Kocin, P. J.; Uccellini, L. W.; Zack, J. W.; Kaplan, M. L.

1984-01-01

Mesoscale numerical forecasts utilizing the Mesoscale Atmospheric Simulation System (MASS) are documented for two East Coast severe weather events. The two events are the thunderstorm and heavy snow bursts in the Washington, D.C. - Baltimore, MD region on 8 March 1984 and the devastating tornado outbreak across North and South Carolina on 28 March 1984. The forecasts are presented to demonstrate the ability of the model to simulate dynamical interactions and diabatic processes and to note some of the problems encountered when using mesoscale models for day-to-day forecasting.

How accurate are the weather forecasts for Bierun (southern Poland)?

NASA Astrophysics Data System (ADS)

Gawor, J.

2012-04-01

Weather forecast accuracy has increased in recent times mainly thanks to significant development of numerical weather prediction models. Despite the improvements, the forecasts should be verified to control their quality. The evaluation of forecast accuracy can also be an interesting learning activity for students. It joins natural curiosity about everyday weather and scientific process skills: problem solving, database technologies, graph construction and graphical analysis. The examination of the weather forecasts has been taken by a group of 14-year-old students from Bierun (southern Poland). They participate in the GLOBE program to develop inquiry-based investigations of the local environment. For the atmospheric research the automatic weather station is used. The observed data were compared with corresponding forecasts produced by two numerical weather prediction models, i.e. COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) developed by Naval Research Laboratory Monterey, USA; it runs operationally at the Interdisciplinary Centre for Mathematical and Computational Modelling in Warsaw, Poland and COSMO (The Consortium for Small-scale Modelling) used by the Polish Institute of Meteorology and Water Management. The analysed data included air temperature, precipitation, wind speed, wind chill and sea level pressure. The prediction periods from 0 to 24 hours (Day 1) and from 24 to 48 hours (Day 2) were considered. The verification statistics that are commonly used in meteorology have been applied: mean error, also known as bias, for continuous data and a 2x2 contingency table to get the hit rate and false alarm ratio for a few precipitation thresholds. The results of the aforementioned activity became an interesting basis for discussion. The most important topics are: 1) to what extent can we rely on the weather forecasts? 2) How accurate are the forecasts for two considered time ranges? 3) Which precipitation threshold is the most predictable? 4) Why are some weather elements easier to verify than others? 5) What factors may contribute to the quality of the weather forecast?

A high-fidelity weather time series generator using the Markov Chain process on a piecewise level

NASA Astrophysics Data System (ADS)

Hersvik, K.; Endrerud, O.-E. V.

2017-12-01

A method is developed for generating a set of unique weather time-series based on an existing weather series. The method allows statistically valid weather variations to take place within repeated simulations of offshore operations. The numerous generated time series need to share the same statistical qualities as the original time series. Statistical qualities here refer mainly to the distribution of weather windows available for work, including durations and frequencies of such weather windows, and seasonal characteristics. The method is based on the Markov chain process. The core new development lies in how the Markov Process is used, specifically by joining small pieces of random length time series together rather than joining individual weather states, each from a single time step, which is a common solution found in the literature. This new Markov model shows favorable characteristics with respect to the requirements set forth and all aspects of the validation performed.

Uncertainty Forecasts Improve Weather-Related Decisions and Attenuate the Effects of Forecast Error

ERIC Educational Resources Information Center

Joslyn, Susan L.; LeClerc, Jared E.

2012-01-01

Although uncertainty is inherent in weather forecasts, explicit numeric uncertainty estimates are rarely included in public forecasts for fear that they will be misunderstood. Of particular concern are situations in which precautionary action is required at low probabilities, often the case with severe events. At present, a categorical weather…

More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?

PubMed Central

Palmer, T. N.

2014-01-01

This paper sets out a new methodological approach to solving the equations for simulating and predicting weather and climate. In this approach, the conventionally hard boundary between the dynamical core and the sub-grid parametrizations is blurred. This approach is motivated by the relatively shallow power-law spectrum for atmospheric energy on scales of hundreds of kilometres and less. It is first argued that, because of this, the closure schemes for weather and climate simulators should be based on stochastic–dynamic systems rather than deterministic formulae. Second, as high-wavenumber elements of the dynamical core will necessarily inherit this stochasticity during time integration, it is argued that the dynamical core will be significantly over-engineered if all computations, regardless of scale, are performed completely deterministically and if all variables are represented with maximum numerical precision (in practice using double-precision floating-point numbers). As the era of exascale computing is approached, an energy- and computationally efficient approach to cloud-resolved weather and climate simulation is described where determinism and numerical precision are focused on the largest scales only. PMID:24842038

More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?

PubMed

Palmer, T N

2014-06-28

This paper sets out a new methodological approach to solving the equations for simulating and predicting weather and climate. In this approach, the conventionally hard boundary between the dynamical core and the sub-grid parametrizations is blurred. This approach is motivated by the relatively shallow power-law spectrum for atmospheric energy on scales of hundreds of kilometres and less. It is first argued that, because of this, the closure schemes for weather and climate simulators should be based on stochastic-dynamic systems rather than deterministic formulae. Second, as high-wavenumber elements of the dynamical core will necessarily inherit this stochasticity during time integration, it is argued that the dynamical core will be significantly over-engineered if all computations, regardless of scale, are performed completely deterministically and if all variables are represented with maximum numerical precision (in practice using double-precision floating-point numbers). As the era of exascale computing is approached, an energy- and computationally efficient approach to cloud-resolved weather and climate simulation is described where determinism and numerical precision are focused on the largest scales only.

Near-real-time Estimation and Forecast of Total Precipitable Water in Europe

NASA Astrophysics Data System (ADS)

Bartholy, J.; Kern, A.; Barcza, Z.; Pongracz, R.; Ihasz, I.; Kovacs, R.; Ferencz, C.

2013-12-01

Information about the amount and spatial distribution of atmospheric water vapor (or total precipitable water) is essential for understanding weather and the environment including the greenhouse effect, the climate system with its feedbacks and the hydrological cycle. Numerical weather prediction (NWP) models need accurate estimations of water vapor content to provide realistic forecasts including representation of clouds and precipitation. In the present study we introduce our research activity for the estimation and forecast of atmospheric water vapor in Central Europe using both observations and models. The Eötvös Loránd University (Hungary) operates a polar orbiting satellite receiving station in Budapest since 2002. This station receives Earth observation data from polar orbiting satellites including MODerate resolution Imaging Spectroradiometer (MODIS) Direct Broadcast (DB) data stream from satellites Terra and Aqua. The received DB MODIS data are automatically processed using freely distributed software packages. Using the IMAPP Level2 software total precipitable water is calculated operationally using two different methods. Quality of the TPW estimations is a crucial question for further application of the results, thus validation of the remotely sensed total precipitable water fields is presented using radiosonde data. In a current research project in Hungary we aim to compare different estimations of atmospheric water vapor content. Within the frame of the project we use a NWP model (DBCRAS; Direct Broadcast CIMSS Regional Assimilation System numerical weather prediction software developed by the University of Wisconsin, Madison) to forecast TPW. DBCRAS uses near real time Level2 products from the MODIS data processing chain. From the wide range of the derived Level2 products the MODIS TPW parameter found within the so-called mod07 results (Atmospheric Profiles Product) and the cloud top pressure and cloud effective emissivity parameters from the so-called mod06 results (Cloud Product) are assimilated twice a day (at 00 and 12 UTC) by DBCRAS. DBCRAS creates 72 hours long weather forecasts with 48 km horizontal resolution. DBCRAS is operational at the University since 2009 which means that by now sufficient data is available for the verification of the model. In the present study verification results for the DBCRAS total precipitable water forecasts are presented based on analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Numerical indices are calculated to quantify the performance of DBCRAS. During a limited time period DBCRAS was also ran without assimilating MODIS products which means that there is possibility to quantify the effect of assimilating MODIS physical products on the quality of the forecasts. For this limited time period verification indices are compared to decide whether MODIS data improves forecast quality or not.

Emulation for probabilistic weather forecasting

NASA Astrophysics Data System (ADS)

Cornford, Dan; Barillec, Remi

2010-05-01

Numerical weather prediction models are typically very expensive to run due to their complexity and resolution. Characterising the sensitivity of the model to its initial condition and/or to its parameters requires numerous runs of the model, which is impractical for all but the simplest models. To produce probabilistic forecasts requires knowledge of the distribution of the model outputs, given the distribution over the inputs, where the inputs include the initial conditions, boundary conditions and model parameters. Such uncertainty analysis for complex weather prediction models seems a long way off, given current computing power, with ensembles providing only a partial answer. One possible way forward that we develop in this work is the use of statistical emulators. Emulators provide an efficient statistical approximation to the model (or simulator) while quantifying the uncertainty introduced. In the emulator framework, a Gaussian process is fitted to the simulator response as a function of the simulator inputs using some training data. The emulator is essentially an interpolator of the simulator output and the response in unobserved areas is dictated by the choice of covariance structure and parameters in the Gaussian process. Suitable parameters are inferred from the data in a maximum likelihood, or Bayesian framework. Once trained, the emulator allows operations such as sensitivity analysis or uncertainty analysis to be performed at a much lower computational cost. The efficiency of emulators can be further improved by exploiting the redundancy in the simulator output through appropriate dimension reduction techniques. We demonstrate this using both Principal Component Analysis on the model output and a new reduced-rank emulator in which an optimal linear projection operator is estimated jointly with other parameters, in the context of simple low order models, such as the Lorenz 40D system. We present the application of emulators to probabilistic weather forecasting, where the construction of the emulator training set replaces the traditional ensemble model runs. Thus the actual forecast distributions are computed using the emulator conditioned on the ‘ensemble runs' which are chosen to explore the plausible input space using relatively crude experimental design methods. One benefit here is that the ensemble does not need to be a sample from the true distribution of the input space, rather it should cover that input space in some sense. The probabilistic forecasts are computed using Monte Carlo methods sampling from the input distribution and using the emulator to produce the output distribution. Finally we discuss the limitations of this approach and briefly mention how we might use similar methods to learn the model error within a framework that incorporates a data assimilation like aspect, using emulators and learning complex model error representations. We suggest future directions for research in the area that will be necessary to apply the method to more realistic numerical weather prediction models.

Space Weather Effects Produced by the Ring Current Particles

NASA Astrophysics Data System (ADS)

Ganushkina, Natalia; Jaynes, Allison; Liemohn, Michael

2017-11-01

One of the definitions of space weather describes it as the time-varying space environment that may be hazardous to technological systems in space and/or on the ground and/or endanger human health or life. The ring current has its contributions to space weather effects, both in terms of particles, ions and electrons, which constitute it, and magnetic and electric fields produced and modified by it at the ground and in space. We address the main aspects of the space weather effects from the ring current starting with brief review of ring current discovery and physical processes and the Dst-index and predictions of the ring current and storm occurrence based on it. Special attention is paid to the effects on satellites produced by the ring current electrons. The ring current is responsible for several processes in the other inner magnetosphere populations, such as the plasmasphere and radiation belts which is also described. Finally, we discuss the ring current influence on the ionosphere and the generation of geomagnetically induced currents (GIC).

A Weather Radar Simulator for the Evaluation of Polarimetric Phased Array Performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Byrd, Andrew D.; Ivic, Igor R.; Palmer, Robert D.

A radar simulator capable of generating time series data for a polarimetric phased array weather radar has been designed and implemented. The received signals are composed from a high-resolution numerical prediction weather model. Thousands of scattering centers, each with an independent randomly generated Doppler spectrum, populate the field of view of the radar. The moments of the scattering center spectra are derived from the numerical weather model, and the scattering center positions are updated based on the three-dimensional wind field. In order to accurately emulate the effects of the system-induced cross-polar contamination, the array is modeled using a complete setmore » of dual-polarization radiation patterns. The simulator offers reconfigurable element patterns and positions as well as access to independent time series data for each element, resulting in easy implementation of any beamforming method. It also allows for arbitrary waveform designs and is able to model the effects of quantization on waveform performance. Simultaneous, alternating, quasi-simultaneous, and pulse-to-pulse phase coded modes of polarimetric signal transmission have been implemented. This framework allows for realistic emulation of the effects of cross-polar fields on weather observations, as well as the evaluation of possible techniques for the mitigation of those effects.« less

Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

NASA Technical Reports Server (NTRS)

Bell, Jordan R.; Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.

2012-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the SPoRT-MODIS GVF dataset on a land surface model (LSM) apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. In the West, higher latent heat fluxes prevailed, which enhanced the rates of evapotranspiration and soil moisture depletion in the LSM. By late Summer and Autumn, both the average sensible and latent heat fluxes increased in the West as a result of the more rapid soil drying and higher coverage of GVF. The impacts of the SPoRT GVF dataset on NWP was also examined for a single severe weather case study using the Weather Research and Forecasting (WRF) model. Two separate coupled LIS/WRF model simulations were made for the 17 July 2010 severe weather event in the Upper Midwest using the NCEP and SPoRT GVFs, with all other model parameters remaining the same. Based on the sensitivity results, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and lower direct surface heating, which typically resulted in lower (higher) predicted 2-m temperatures (2-m dewpoint temperatures). Portions of the Northern Plains states experienced substantial increases in convective available potential energy as a result of the higher SPoRT/MODIS GVFs. These differences produced subtle yet quantifiable differences in the simulated convective precipitation systems for this event.

Towards more accurate wind and solar power prediction by improving NWP model physics

NASA Astrophysics Data System (ADS)

Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo

2014-05-01

The growing importance and successive expansion of renewable energies raise new challenges for decision makers, economists, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the errors and provide an a priori estimate of remaining uncertainties associated with the large share of weather-dependent power sources. For this purpose it is essential to optimize NWP model forecasts with respect to those prognostic variables which are relevant for wind and solar power plants. An improved weather forecast serves as the basis for a sophisticated power forecasts. Consequently, a well-timed energy trading on the stock market, and electrical grid stability can be maintained. The German Weather Service (DWD) currently is involved with two projects concerning research in the field of renewable energy, namely ORKA*) and EWeLiNE**). Whereas the latter is in collaboration with the Fraunhofer Institute (IWES), the project ORKA is led by energy & meteo systems (emsys). Both cooperate with German transmission system operators. The goal of the projects is to improve wind and photovoltaic (PV) power forecasts by combining optimized NWP and enhanced power forecast models. In this context, the German Weather Service aims to improve its model system, including the ensemble forecasting system, by working on data assimilation, model physics and statistical post processing. This presentation is focused on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. First steps leading to improved physical parameterization schemes within the NWP-model are presented. Wind mast measurements reaching up to 200 m height above ground are used for the estimation of the (NWP) wind forecast error at heights relevant for wind energy plants. One particular problem is the daily cycle in wind speed. The transition from stable stratification during nighttime to well mixed conditions during the day presents a big challenge to NWP models. Fast decrease and successive increase in hub-height wind speed after sunrise, and the formation of nocturnal low level jets will be discussed. For PV, the life cycle of low stratus clouds and fog is crucial. Capturing these processes correctly depends on the accurate simulation of diffusion or vertical momentum transport and the interaction with other atmospheric and soil processes within the numerical weather model. Results from Single Column Model simulations and 3d case studies will be presented. Emphasis is placed on wind forecasts; however, some references to highlights concerning the PV-developments will also be given. *) ORKA: Optimierung von Ensembleprognosen regenerativer Einspeisung für den Kürzestfristbereich am Anwendungsbeispiel der Netzsicherheitsrechnungen **) EWeLiNE: Erstellung innovativer Wetter- und Leistungsprognosemodelle für die Netzintegration wetterabhängiger Energieträger, www.projekt-eweline.de

New, Improved Bulk-microphysical Schemes for Studying Precipitation Processes in WRF. Part 1; Comparisons with Other Schemes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Shi, J.; Chen, S. S> ; Lang, S.; Hong, S.-Y.; Thompson, G.; Peters-Lidard, C.; Hou, A.; Braun, S.;

Wintertime component of the THORPEX Pacific-Asian Regional Campaign (T-PARC)

NASA Astrophysics Data System (ADS)

Song, Y.; Toth, Z.; Asuma, Y.; Reynolds, C.; Lngland, R.; Szunyogh, I.; Colle, B.; Chang, E.; Doyle, C.; Kats, A.

2009-04-01

The winter component of the T-PARC is an international field project that aims at improving high impact weather event forecasts for North America. The main objective is to understand how perturbations from the tropics, Eurasia and polar fronts travel through waveguide and turn into high impact weather events. Through adaptive observations by using manned aircrafts (NOAA G-IV and US Air force C-130s) and Russian rawinsonde network over data sparse regions, it is expected that accurate initial conditions will improve the numerical weather forecasts. Non-adaptive aircraft measurements over the Pacific Rim and part of India are also deployed through E-AMDAR program, which is expected to improve the background field over Asia where perturbations are initiated. The campaign is led by NOAA and joined by agencies and universities from US, Canada, Mexico, Japan, ECWMF, and Russia. While most observational data will be assimilated by operational centers to improve real time numerical weather predictions, post field studies will focus on aspects such as: data impact on forecast and analysis, dry and moist processes that affect the formation and propagation of perturbations, meso-scale storm structure, error growth, forecast "busts" under certain atmospheric regimes, and socio-economic applications such as costs and benefits of improved forecasts and their use by the public for high impact weather events. In particular, a Winter Olympics demonstration project (February 12 - February 28) is expected to be a test bed during winter T-PARC for real user outreach and application purposes. Effectiveness of existing targeting methods as well as new targeting methods in the 3-5 day lead time range will be pursued and other aspects related to data assimilation and numerical forecasts (both deterministic and ensemble forecasts) will be investigated within this project as well.

Retrospective Analog Year Analyses Using NASA Satellite Data to Improve USDA's World Agricultural Supply and Demand Estimates

NASA Astrophysics Data System (ADS)

Teng, W. L.; Shannon, H. D.

2011-12-01

The USDA World Agricultural Outlook Board (WAOB) is responsible for monitoring weather and climate impacts on domestic and foreign crop development. One of WAOB's primary goals is to determine the net cumulative effect of weather and climate anomalies on final crop yields. To this end, a broad array of information is consulted, including maps, charts, and time series of recent weather, climate, and crop observations; numerical output from weather and crop models; and reports from the press, USDA attachés, and foreign governments. The resulting agricultural weather assessments are published in the Weekly Weather and Crop Bulletin, to keep farmers, policy makers, and commercial agricultural interests informed of weather and climate impacts on agriculture. Because both the amount and timing of precipitation significantly impact crop yields, WAOB often uses precipitation time series to identify growing seasons with similar weather patterns and help estimate crop yields for the current growing season, based on observed yields in analog years. Although, historically, these analog years are identified through visual inspection, the qualitative nature of this methodology sometimes precludes the definitive identification of the best analog year. One goal of this study is to introduce a more rigorous, statistical approach for identifying analog years. This approach is based on a modified coefficient of determination, termed the analog index (AI). The derivation of AI will be described. Another goal of this study is to compare the performance of AI for time series derived from surface-based observations vs. satellite-based measurements (NASA TRMM and other data). Five study areas and six growing seasons of data were analyzed (2003-2007 as potential analog years and 2008 as the target year). Results thus far show that, for all five areas, crop yield estimates derived from satellite-based precipitation data are closer to measured yields than are estimates derived from surface-based precipitation measurements. Work is continuing to include satellite-based surface soil moisture data and model-assimilated root zone soil moisture. This study is part of a larger effort to improve WAOB estimates by integrating NASA remote sensing observations and research results into WAOB's decision-making environment.

Enhancing USDA's Retrospective Analog Year Analyses Using NASA Satellite Precipitation and Soil Moisture Data

NASA Astrophysics Data System (ADS)

Teng, W. L.; Shannon, H. D.

2013-12-01

The USDA World Agricultural Outlook Board (WAOB) is responsible for monitoring weather and climate impacts on domestic and foreign crop development. One of WAOB's primary goals is to determine the net cumulative effect of weather and climate anomalies on final crop yields. To this end, a broad array of information is consulted, including maps, charts, and time series of recent weather, climate, and crop observations; numerical output from weather and crop models; and reports from the press, USDA attachés, and foreign governments. The resulting agricultural weather assessments are published in the Weekly Weather and Crop Bulletin, to keep farmers, policy makers, and commercial agricultural interests informed of weather and climate impacts on agriculture. Because both the amount and timing of precipitation significantly affect crop yields, WAOB has often, as part of its operational process, used historical time series of surface-based precipitation observations to visually identify growing seasons with similar (analog) weather patterns as, and help estimate crop yields for, the current growing season. As part of a larger effort to improve WAOB estimates by integrating NASA remote sensing observations and research results into WAOB's decision-making environment, a more rigorous, statistical method for identifying analog years was developed. This method, termed the analog index (AI), is based on the Nash-Sutcliffe model efficiency coefficient. The AI was computed for five study areas and six growing seasons of data analyzed (2003-2007 as potential analog years and 2008 as the target year). Previously reported results compared the performance of AI for time series derived from surface-based observations vs. satellite-retrieved precipitation data. Those results showed that, for all five areas, crop yield estimates derived from satellite-retrieved precipitation data are closer to measured yields than are estimates derived from surface-based precipitation observations. Subsequent work has compared the relative performance of AI for time series derived from satellite-retrieved surface soil moisture data and from root zone soil moisture derived from the assimilation of surface soil moisture data into a land surface model. These results, which also showed the potential benefits of satellite data for analog year analyses, will be presented.

Protection of passive radio frequencies used for earth exploration by satellite

NASA Astrophysics Data System (ADS)

Rochard, Guy

2004-10-01

Space-borne passive sensing of the Earth"s surface and atmosphere has an essential and increasing importance in Earth Observation. The impressive progress recently made or shortly expected in weather analysis, warning and forecasts (in particular for dangerous weather phenomena as rain and floods, storms, cyclones, droughts) as well as in the study and prediction of climate change, is mainly attributable to the spaceborne observations. On this basis, economic studies show that meteorological services have a high positive impact on a wide range of economic activities, notwithstanding safety of life and property aspects. Space-borne passive sensing feeds crucial observational data to numerical weather predction models run on the most advanced super-computers that are operated by a few global forecasting centers. All meteorological and environmental satellite organizations operate these crucial remote-sensing missions as part of the GOS of the World Weather Watch and others... Spaceborne passive sensing for meterological applications is performed in frequency bands allocated to the Earth Exploration-Satellite Service. This is named "EESS passive" in the ITU-R Radio Regulations. The appropriate bands are uniquely determined by the physical properties (e.g. molecular resonance) of constituents of the atmosphere, and are therefore one of the unique natural resources (similarly to Radio Astronomy bands). Passive measurements at several frequencies in the microwave spectrum must be made simultaneously in order to extract the individual contribution of the geophysical parameter of interest. Bands below 100 GHz are of particular importance to provide an "all-weather" capability since many clouds are almost transparent at these frequencies. Along this line, the two first figures below about zenithal opacity describes respectively the atmosphere optical thickness due to water vapor and dry components in the frequency range 1 to 275 GHz and 275 GHz to 1000 GHz on which have been based the definition of most of the current allocations to EESS (passive) that are listed, as currently specified in ITU-R Rec. SA.515-3 summarized below. Interference criteria and performance criteria of passive sensors are indicated in ITU-R Rec(s) SA.1028-2 and 1029-2, respectively. A common summary of these two Rec(s) is also available below.

High-quality weather data for grid integration studies

NASA Astrophysics Data System (ADS)

Draxl, C.

2016-12-01

As variable renewable power penetration levels increase in power systems worldwide, renewable integration studies are crucial to ensure continued economic and reliable operation of the power grid. In this talk we will shed light on requirements for grid integration studies as far as wind and solar energy are concerned. Because wind and solar plants are strongly impacted by weather, high-resolution and high-quality weather data are required to drive power system simulations. Future data sets will have to push limits of numerical weather prediction to yield these high-resolution data sets, and wind data will have to be time-synchronized with solar data. Current wind and solar integration data sets will be presented. The Wind Integration National Dataset (WIND) Toolkit is the largest and most complete grid integration data set publicly available to date. A meteorological data set, wind power production time series, and simulated forecasts created using the Weather Research and Forecasting Model run on a 2-km grid over the continental United States at a 5-min resolution is now publicly available for more than 126,000 land-based and offshore wind power production sites. The Solar Integration National Dataset (SIND) is available as time synchronized with the WIND Toolkit, and will allow for combined wind-solar grid integration studies. The National Solar Radiation Database (NSRDB) is a similar high temporal- and spatial resolution database of 18 years of solar resource data for North America and India. Grid integration studies are also carried out in various countries, which aim at increasing their wind and solar penetration through combined wind and solar integration data sets. We will present a multi-year effort to directly support India's 24x7 energy access goal through a suite of activities aimed at enabling large-scale deployment of clean energy and energy efficiency. Another current effort is the North-American-Renewable-Integration-Study, with the aim of providing a seamless data set across borders for a whole continent, to simulate and analyze the impacts of potential future large wind and solar power penetrations on bulk power system operations.

The Initiation of Solar Eruptions by Flux Emergence

NASA Astrophysics Data System (ADS)

Leake, J. E.; Linton, M.; Antiochos, S. K.

2013-12-01

Understanding the mechanism for the initiation of solar eruptions, or coronal mass ejections (CMEs), is a vital step in the prediction of space weather. There are a number of different theoretical and numerical magnetic models for the initiation of CMEs, and to some extent they all rely on idealized initial conditions or boundary conditions. These idealizations typically involve the presence of pre-formed sheared magnetic fields in the corona, which contain enough free energy to drive an eruption, or the generation of sheared magnetic fields by velocity/electric field boundary flows. The roots of coronal magnetic fields lie in the convection zone, and to understand the CME initiation mechanism, we must understand how these convection zone fields emerge from the high beta convection zone into the low beta corona. Using visco-resistive MHD numerical simulations, we show how simple convection zone magnetic fields that are consistent with our understanding of the solar dynamo can dynamically emerge through the photosphere/chromosphere and into the corona and form sheared magnetic structures which are capable of erupting and creating CMEs. These results extend current CME models by introducing increased realism and removing the idealized initial coronal field conditions and kinematic boundary conditions, which is an important step in relating space weather and the Sun's dynamo generation of magnetic field. This work was funded by NASA's 'Living With a Star' program.

The Impact of Microphysics on Intensity and Structure of Hurricanes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Shi, Jainn; Lang, Steve; Peters-Lidard, Christa

2006-01-01

During the past decade, both research and operational numerical weather prediction models, e.g. Weather Research and Forecast (WRF) model, have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with a 1-2 km or less horizontal resolutions. WFW is a next-generation mesoscale forecast model and assimilation system that has incorporated modern software framework, advanced dynamics, numeric and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WFW model can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options such as Lin et al. (1983), WSM 6-class and Thompson microphysics schemes. We have recently implemented three sophisticated cloud microphysics schemes into WRF. The cloud microphysics schemes have been extensively tested and applied for different mesoscale systems in different geographical locations. The performances of these schemes have been compared to those from other WRF microphysics options. We are performing sensitivity tests in using WW to examine the impact of six different cloud microphysical schemes on hurricane track, intensity and rainfall forecast. We are also performing the inline tracer calculation to comprehend the physical processes @e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes.

Meteodrones - Meteorological Planetary Boundary Layer Measurements by Vertical Drone Soundings

NASA Astrophysics Data System (ADS)

Lauer, Jonas; Fengler, Martin

2017-04-01

As of today, there is a gap in the operational data collection of meteorological observations in the Planetary Boundary Layer (PBL). This lack of spatially and temporally reliable knowledge of PBL conditions and energy fluxes with the surface causes shortcomings in the prediction of micro- and mesoscale phenomena such as convection, temperature inversions, local wind systems or fog. The currently used remote sensing instruments share the drawback of only partially covering necessary variables. To fill this data gap, since 2012, Meteomatics has been developing a drone measurement system, the Meteodrone, to measure the parameters wind speed, wind direction, dewpoint, temperature and air pressure of the PBL up to 1.5 km above ground. Both the data quality and the assimilation into a regional numerical weather model could be determined in several pilot studies. Besides, a project in cooperation with the NSSL (National Severe Storms Laboratory) was launched in October 2016 with the goal of capturing pre-convective conditions for improved severe storm forecasts in Oklahoma. Also, related measurements, such as air pollution measurements in the Misox valley to determine LDSP values, were successfully conducted. The main goal of the project is the operational data collection of PBL measurements and the assimilation of this data into regional numerical weather forecast models. Considering the high data quality indicated in all conducted studies as well as the trouble-free execution, this goal is both worthwhile and realistic.

Retrieval and Validation of Zenith and Slant Path Delays From the Irish GPS Network

NASA Astrophysics Data System (ADS)

Hanafin, Jennifer; Jennings, S. Gerard; O'Dowd, Colin; McGrath, Ray; Whelan, Eoin

2010-05-01

Retrieval of atmospheric integrated water vapour (IWV) from ground-based GPS receivers and provision of this data product for meteorological applications has been the focus of a number of Europe-wide networks and projects, most recently the EUMETNET GPS water vapour programme. The results presented here are from a project to provide such information about the state of the atmosphere around Ireland for climate monitoring and improved numerical weather prediction. Two geodetic reference GPS receivers have been deployed at Valentia Observatory in Co. Kerry and Mace Head Atmospheric Research Station in Co. Galway, Ireland. These two receivers supplement the existing Ordnance Survey Ireland active network of 17 permanent ground-based receivers. A system to retrieve column-integrated atmospheric water vapour from the data provided by this network has been developed, based on the GPS Analysis at MIT (GAMIT) software package. The data quality of the zenith retrievals has been assessed using co-located radiosondes at the Valentia site and observations from a microwave profiling radiometer at the Mace Head site. Validation of the slant path retrievals requires a numerical weather prediction model and HIRLAM (High-Resolution Limited Area Model) version 7.2, the current operational forecast model in use at Met Éireann for the region, has been used for this validation work. Results from the data processing and comparisons with the independent observations and model will be presented.

ESiWACE: A Center of Excellence for HPC applications to support cloud resolving earth system modelling

NASA Astrophysics Data System (ADS)

Biercamp, Joachim; Adamidis, Panagiotis; Neumann, Philipp

2017-04-01

With the exa-scale era approaching, length and time scales used for climate research on one hand and numerical weather prediction on the other hand blend into each other. The Centre of Excellence in Simulation of Weather and Climate in Europe (ESiWACE) represents a European consortium comprising partners from climate, weather and HPC in their effort to address key scientific challenges that both communities have in common. A particular challenge is to reach global models with spatial resolutions that allow simulating convective clouds and small-scale ocean eddies. These simulations would produce better predictions of trends and provide much more fidelity in the representation of high-impact regional events. However, running such models in operational mode, i.e with sufficient throughput in ensemble mode clearly will require exa-scale computing and data handling capability. We will discuss the ESiWACE initiative and relate it to work-in-progress on high-resolution simulations in Europe. We present recent strong scalability measurements from ESiWACE to demonstrate current computability in weather and climate simulation. A special focus in this particular talk is on the Icosahedal Nonhydrostatic (ICON) model used for a comparison of high resolution regional and global simulations with high quality observation data. We demonstrate that close-to-optimal parallel efficiency can be achieved in strong scaling global resolution experiments on Mistral/DKRZ, e.g. 94% for 5km resolution simulations using 36k cores on Mistral/DKRZ. Based on our scalability and high-resolution experiments, we deduce and extrapolate future capabilities for ICON that are expected for weather and climate research at exascale.

High Quality Data for Grid Integration Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clifton, Andrew; Draxl, Caroline; Sengupta, Manajit

As variable renewable power penetration levels increase in power systems worldwide, renewable integration studies are crucial to ensure continued economic and reliable operation of the power grid. The existing electric grid infrastructure in the US in particular poses significant limitations on wind power expansion. In this presentation we will shed light on requirements for grid integration studies as far as wind and solar energy are concerned. Because wind and solar plants are strongly impacted by weather, high-resolution and high-quality weather data are required to drive power system simulations. Future data sets will have to push limits of numerical weather predictionmore » to yield these high-resolution data sets, and wind data will have to be time-synchronized with solar data. Current wind and solar integration data sets are presented. The Wind Integration National Dataset (WIND) Toolkit is the largest and most complete grid integration data set publicly available to date. A meteorological data set, wind power production time series, and simulated forecasts created using the Weather Research and Forecasting Model run on a 2-km grid over the continental United States at a 5-min resolution is now publicly available for more than 126,000 land-based and offshore wind power production sites. The National Solar Radiation Database (NSRDB) is a similar high temporal- and spatial resolution database of 18 years of solar resource data for North America and India. The need for high-resolution weather data pushes modeling towards finer scales and closer synchronization. We also present how we anticipate such datasets developing in the future, their benefits, and the challenges with using and disseminating such large amounts of data.« less

Probabilistic Weather Information Tailored to the Needs of Transmission System Operators

NASA Astrophysics Data System (ADS)

Alberts, I.; Stauch, V.; Lee, D.; Hagedorn, R.

2014-12-01

Reliable and accurate forecasts for wind and photovoltaic (PV) power production are essential for stable transmission systems. A high potential for improving the wind and PV power forecasts lies in optimizing the weather forecasts, since these energy sources are highly weather dependent. For this reason the main objective of the German research project EWeLiNE is to improve the quality the underlying numerical weather predictions towards energy operations. In this project, the German Meteorological Service (DWD), the Fraunhofer Institute for Wind Energy and Energy System Technology, and three of the German transmission system operators (TSOs) are working together to improve the weather and power forecasts. Probabilistic predictions are of particular interest, as the quantification of uncertainties provides an important tool for risk management. Theoretical considerations suggest that it can be advantageous to use probabilistic information to represent and respond to the remaining uncertainties in the forecasts. However, it remains a challenge to integrate this information into the decision making processes related to market participation and power systems operations. The project is planned and carried out in close cooperation with the involved TSOs in order to ensure the usability of the products developed. It will conclude with a demonstration phase, in which the improved models and newly developed products are combined into a process chain and used to provide information to TSOs in a real-time decision support tool. The use of a web-based development platform enables short development cycles and agile adaptation to evolving user needs. This contribution will present the EWeLiNE project and discuss ideas on how to incorporate probabilistic information into the users' current decision making processes.

Gravity Wave Detection through All-sky Imaging of Airglow

NASA Astrophysics Data System (ADS)

Nguyen, T. V.; Martinez, A.; Porat, I.; Hampton, D. L.; Bering, E., III; Wood, L.

2017-12-01

Airglow, the faint glow of the atmosphere, is caused by the interaction of air molecules with radiation from the sun. Similarly, the aurora is created by interactions of air molecules with the solar wind. It has been shown that airglow emissions are altered by gravity waves passing through airglow source region (100-110km), making it possible to study gravity waves and their sources through airglow imaging. University of Houston's USIP - Airglow team designed a compact, inexpensive all-sky imager capable of detecting airglow and auroral emissions using a fisheye lens, a simple optical train, a filter wheel with 4 specific filters, and a CMOS camera. This instrument has been used in USIP's scientific campaign in Alaska throughout March 2017. During this period, the imager captured auroral activity in the Fairbanks region. Due to lunar conditions and auroral activity images from the campaign did not yield visible signs of airglow. Currently, the team is trying to detect gravity wave patterns present in the images through numerical analysis. Detected gravity wave patterns will be compared to local weather data, and may be used to make correlations between gravity waves and weather events. Such correlations could provide more data on the relationship between the mesosphere and lower layers of the atmosphere. Practical applications of this research include weather prediction and detection of air turbulence.

Ensemble forecasting of short-term system scale irrigation demands using real-time flow data and numerical weather predictions

NASA Astrophysics Data System (ADS)

Perera, Kushan C.; Western, Andrew W.; Robertson, David E.; George, Biju; Nawarathna, Bandara

2016-06-01

Irrigation demands fluctuate in response to weather variations and a range of irrigation management decisions, which creates challenges for water supply system operators. This paper develops a method for real-time ensemble forecasting of irrigation demand and applies it to irrigation command areas of various sizes for lead times of 1 to 5 days. The ensemble forecasts are based on a deterministic time series model coupled with ensemble representations of the various inputs to that model. Forecast inputs include past flow, precipitation, and potential evapotranspiration. These inputs are variously derived from flow observations from a modernized irrigation delivery system; short-term weather forecasts derived from numerical weather prediction models and observed weather data available from automatic weather stations. The predictive performance for the ensemble spread of irrigation demand was quantified using rank histograms, the mean continuous rank probability score (CRPS), the mean CRPS reliability and the temporal mean of the ensemble root mean squared error (MRMSE). The mean forecast was evaluated using root mean squared error (RMSE), Nash-Sutcliffe model efficiency (NSE) and bias. The NSE values for evaluation periods ranged between 0.96 (1 day lead time, whole study area) and 0.42 (5 days lead time, smallest command area). Rank histograms and comparison of MRMSE, mean CRPS, mean CRPS reliability and RMSE indicated that the ensemble spread is generally a reliable representation of the forecast uncertainty for short lead times but underestimates the uncertainty for long lead times.

Comparison of Selected Weather Translation Products

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak

2017-01-01

Weather is a primary contributor to the air traffic delays within the National Airspace System (NAS). At present, it is the individual decision makers who use weather information and assess its operational impact in creating effective air traffic management solutions. As a result, the estimation of the impact of forecast weather and the quality of ATM response relies on the skill and experience level of the decision maker. FAA Weather-ATM working groups have developed a Weather-ATM integration framework that consists of weather collection, weather translation, ATM impact conversion and ATM decision support. Some weather translation measures have been developed for hypothetical operations such as decentralized free flight, whereas others are meant to be relevant in current operations. This paper does comparative study of two different weather translation products relevant in current operations and finds that these products have strong correlation with each other. Given inaccuracies in prediction of weather, these differences would not be expected to be of significance in statistical study of a large number of decisions made with a look-ahead time of two hours or more.

Current gaps in understanding and predicting space weather: An operations perspective

NASA Astrophysics Data System (ADS)

Murtagh, W. J.

2016-12-01

The NOAA Space Weather Prediction Center (SWPC), one of the nine National Weather Service (NWS) National Centers for Environmental Prediction, is the Nation's official source for space weather alerts and warnings. Space weather effects the technology that forms the backbone of global economic vitality and national security, including satellite and airline operations, communications networks, and the electric power grid. Many of SWPC's over 48,000 subscribers rely on space weather forecasts for critical decision making. But extraordinary gaps still exist in our ability to meet customer needs for accurate and timely space weather forecasts and warnings. The 2015 National Space Weather Strategy recognizes that it is imperative that we improve the fundamental understanding of space weather and increase the accuracy, reliability, and timeliness of space-weather observations and forecasts in support of the growing demands. In this talk we provide a broad perspective of the key challenges that currently limit the forecaster's ability to better understand and predict space weather. We also examine the impact of these limitations on the end-user community.

Studying the Processes Contributed to the Hairpin Turn of Hurricane Joaquin with WRF numerical simulations and TCI-2015 observations

NASA Astrophysics Data System (ADS)

Pu, Z.; Yu, Y.

2016-12-01

The prediction of Hurricane Joaquin's hairpin clockwise during 1 and 2 October 2015 presents a forecasting challenge during real-time numerical weather prediction, as tracks of several major numerical weather prediction models differ from each other. To investigate the large-scale environment and hurricane inner-core structures related to the hairpin turn of Joaquin, a series of high-resolution mesoscale numerical simulations of Hurricane Joaquin had been performed with an advanced research version of the Weather Research and Forecasting (WRF) model. The outcomes were compared with the observations obtained from the US Office of Naval Research's Tropical Cyclone Intensity (TCI) Experiment during 2015 hurricane season. Specifically, five groups of sensitivity experiments with different cumulus, boundary layer, and microphysical schemes as well as different initial and boundary conditions and initial times in WRF simulations had been performed. It is found that the choice of the cumulus parameterization scheme plays a significant role in reproducing reasonable track forecast during Joaquin's hairpin turn. The mid-level environmental steering flows can be the reason that leads to different tracks in the simulations with different cumulus schemes. In addition, differences in the distribution and amounts of the latent heating over the inner-core region are associated with discrepancies in the simulated intensity among different experiments. Detailed simulation results, comparison with TCI-2015 observations, and comprehensive diagnoses will be presented.

Memory efficient solution of the primitive equations for numerical weather prediction on the CYBER 205

NASA Technical Reports Server (NTRS)

Tuccillo, J. J.

1984-01-01

Numerical Weather Prediction (NWP), for both operational and research purposes, requires only fast computational speed but also large memory. A technique for solving the Primitive Equations for atmospheric motion on the CYBER 205, as implemented in the Mesoscale Atmospheric Simulation System, which is fully vectorized and requires substantially less memory than other techniques such as the Leapfrog or Adams-Bashforth Schemes is discussed. The technique presented uses the Euler-Backard time marching scheme. Also discussed are several techniques for reducing computational time of the model by replacing slow intrinsic routines by faster algorithms which use only hardware vector instructions.

Premature Extinction of the Weather Observer: How Much Risk is the Air Force Assuming

DTIC Science & Technology

2015-12-01

is impacted in some way by the weather and the forecast. DOD assets are exposed to haz- ardous weather conditions each year, the effects of which...discussion of ASOS accuracy follows and is accompanied by an assessment of sur- face weather observations’ impacts to operations as a function of time as well...from some back-up techniques. This section details current knowledge of AMOS and cor- responding impacts of AMOS employment. Current Fielded Systems

Ship Shoal as a prospective borrow site for barrier island restoration, coastal south-central Louisiana, Usa: Numerical wave modeling and field measurements of hydrodynamics and sediment transport

USGS Publications Warehouse

Stone, G.W.; Pepper, D.A.; Xu, Jie; Zhang, X.

2004-01-01

Ship Shoal, a transgressive sand body located at the 10 m isobath off south-central Louisiana, is deemed a potential sand source for restoration along the rapidly eroding Isles Dernieres barrier chain and possibly other sites in Louisiana. Through numerical wave modeling we evaluate the potential response of mining Ship Shoal on the wave field. During severe and strong storms, waves break seaward of the western flank of Ship Shoal. Therefore, removal of Ship Shoal (approximately 1.1 billion m3) causes a maximum increase of the significant wave height by 90%-100% and 40%-50% over the shoal and directly adjacent to the lee of the complex for two strong storm scenarios. During weak storms and fair weather conditions, waves do not break over Ship Shoal. The degree of increase in significant wave height due to shoal removal is considerably smaller, only 10%-20% on the west part of the shoal. Within the context of increasing nearshore wave energy levels, removal of the shoal is not significant enough to cause increased erosion along the Isles Dernieres. Wave approach direction exerts significant control on the wave climate leeward of Ship Shoal for stronger storms, but not weak storms or fairweather. Instrumentation deployed at the shoal allowed comparison of measured wave heights with numerically derived wave heights using STWAVE. Correlation coefficients are high in virtually all comparisons indicating the capability of the model to simulate wave behavior satisfactorily at the shoal. Directional waves, currents and sediment transport were measured during winter storms associated with frontal passages using three bottom-mounted arrays deployed on the seaward and landward sides of Ship Shoal (November, 1998-January, 1999). Episodic increases in wave height, mean and oscillatory current speed, shear velocity, and sediment transport rates, associated with recurrent cold front passages, were measured. Dissipation mechanisms included both breaking and bottom friction due to variable depths across the shoal crest and variable wave amplitudes during storms and fair-weather. Arctic surge fronts were associated with southerly storm waves, and southwesterly to westerly currents and sediment transport. Migrating cyclonic fronts generated northerly swell that transformed into southerly sea, and currents and sediment transport that were southeasterly overall. Waves were 36% higher and 9% longer on the seaward side of the shoal, whereas mean currents were 10% stronger landward, where they were directed onshore, in contrast to the offshore site, where seaward currents predominated. Sediment transport initiated by cold fronts was generally directed southeasterly to southwesterly at the offshore site, and southerly to westerly at the nearshore site. The data suggest that both cold fronts and the shoal, exert significant influences on regional hydrodynamics and sediment transport.

Space Weather: What is it, and Why Should a Meteorologist Care?

NASA Technical Reports Server (NTRS)

SaintCyr, Chris; Murtagh, Bill

2008-01-01

"Space weather" is a term coined almost 15 years ago to describe environmental conditions ABOVE Earth's atmosphere that affect satellites and astronauts. As society has become more dependent on technology, we nave found that space weather conditions increasingly affect numerous commercial and infrastructure sectors: airline operations, the precision positioning industry, and the electric power grid, to name a few. Similar to meteorology where "weather" often refers to severe conditions, "space weather" includes geomagnetic storms, radiation storms, and radio blackouts. But almost all space weather conditions begin at the Sun--our middle-age, magnetically-variable star. At NASA, the science behind space weather takes place in the Heliophysics Division. The Space Weather Prediction Center in Boulder, Colorado, is manned jointly by NCAA and US Air Force personnel, and it provides space weather alerts and warnings for disturbances that can affect people and equipment working in space and on Earth. Organizationally, it resides in NOAA's National Weather Service as one of the National Centers for Environmental Prediction. In this seminar we hope to give the audience a brief introduction to the causes of space weather, discuss some of the effects, and describe the state of the art in forecasting. Our goal is to highlight that meteorologists are increasingly becoming the "first responders" to questions about space weather causes and effects.

Predicting the Impacts of Climate Change on Central American Agriculture

NASA Astrophysics Data System (ADS)

Winter, J. M.; Ruane, A. C.; Rosenzweig, C.

2011-12-01

Agriculture is a vital component of Central America's economy. Poor crop yields and harvest reliability can produce food insecurity, malnutrition, and conflict. Regional climate models (RCMs) and agricultural models have the potential to greatly enhance the efficiency of Central American agriculture and water resources management under both current and future climates. A series of numerical experiments was conducted using Regional Climate Model Version 3 (RegCM3) and the Weather Research and Forecasting Model (WRF) to evaluate the ability of RCMs to reproduce the current climate of Central America and assess changes in temperature and precipitation under multiple future climate scenarios. Control simulations were thoroughly compared to a variety of observational datasets, including local weather station data, gridded meteorological data, and high-resolution satellite-based precipitation products. Future climate simulations were analyzed for both mean shifts in climate and changes in climate variability, including extreme events (droughts, heat waves, floods). To explore the impacts of changing climate on maize, bean, and rice yields in Central America, RCM output was used to force the Decision Support System for Agrotechnology Transfer Model (DSSAT). These results were synthesized to create climate change impacts predictions for Central American agriculture that explicitly account for evolving distributions of precipitation and temperature extremes.

Ionospheric Sounding Opportunities Using Signal Data From Preexisting Amateur Radio And Other Networks

NASA Astrophysics Data System (ADS)

Cushley, A. C.; Noel, J. M. A.

2015-12-01

Amateur radio and other transmissions used for dedicated purposes, such as the Automatic Packet Reporting System (APRS) and Automatic Dependent Surveillance Broadcast (ADS-B), are signals that exist for another reason, but can be used for ionospheric sounding. Whether mandated and government funded or voluntarily constructed and operated, these networks provide data that can be used for scientific and operational purposes which rely on space weather data. Given the current state of the global economic environment and fiscal consequences to scientific research funding in Canada, these types of networks offer an innovative solution with preexisting hardware for more real-time and archival space-weather data to supplement current methods, particularly for data assimilation, modelling and forecasting. Furthermore, mobile ground-based transmitters offer more flexibility for deployment than stationary receivers. Numerical modelling has demonstrated that APRS and ADS-B signals are subject to Faraday rotation (FR) as they pass through the ionosphere. Ray tracingtechniques were used to determine the characteristics of individual waves, including the wave path and the state of polarization. The modelled FR was computed and converted to total electron content (TEC) along the raypaths. TEC data can be used as input for computerized ionospheric tomography (CIT) in order to reconstruct electron density maps of the ionosphere.

Overview of Hydrometeorologic Forecasting Procedures at BC Hydro

NASA Astrophysics Data System (ADS)

McCollor, D.

2004-12-01

Energy utility companies must balance production from limited sources with increasing demand from industrial, business, and residential consumers. The utility planning process requires a balanced, efficient, and effective distribution of energy from source to consumer. Therefore utility planners must consider the impact of weather on energy production and consumption. Hydro-electric companies should be particularly tuned to weather because their source of energy is water, and water supply depends on precipitation. BC Hydro operates as the largest hydro-electric company in western Canada, managing over 30 reservoirs within the province of British Columbia, and generating electricity for 1.6 million people. BC Hydro relies on weather forecasts of watershed precipitation and temperature to drive hydrologic reservoir inflow models and of urban temperatures to meet energy demand requirements. Operations and planning specialists in the company rely on current, value-added weather forecasts for extreme high-inflow events, daily reservoir operations planning, and long-term water resource management. Weather plays a dominant role for BC Hydro financial planners in terms of sensitive economic responses. For example, a two percent change in hydropower generation, due in large part to annual precipitation patterns, results in an annual net change of \\50 million in earnings. A five percent change in temperature produces a \\5 million change in yearly earnings. On a daily basis, significant precipitation events or temperature extremes involve potential profit/loss decisions in the tens of thousands of dollars worth of power generation. These factors are in addition to environmental and societal costs that must be considered equally as part of a triple bottom line reporting structure. BC Hydro water resource managers require improved meteorological information from recent advancements in numerical weather prediction. At BC Hydro, methods of providing meteorological forecast data are changing as new downscaling and ensemble techniques evolve to improve environmental information supplied to water managers.

Weather Forecaster Understanding of Climate Models

NASA Astrophysics Data System (ADS)

Bol, A.; Kiehl, J. T.; Abshire, W. E.

2013-12-01

Weather forecasters, particularly those in broadcasting, are the primary conduit to the public for information on climate and climate change. However, many weather forecasters remain skeptical of model-based climate projections. To address this issue, The COMET Program developed an hour-long online lesson of how climate models work, targeting an audience of weather forecasters. The module draws on forecasters' pre-existing knowledge of weather, climate, and numerical weather prediction (NWP) models. In order to measure learning outcomes, quizzes were given before and after the lesson. Preliminary results show large learning gains. For all people that took both pre and post-tests (n=238), scores improved from 48% to 80%. Similar pre/post improvement occurred for National Weather Service employees (51% to 87%, n=22 ) and college faculty (50% to 90%, n=7). We believe these results indicate a fundamental misunderstanding among many weather forecasters of (1) the difference between weather and climate models, (2) how researchers use climate models, and (3) how they interpret model results. The quiz results indicate that efforts to educate the public about climate change need to include weather forecasters, a vital link between the research community and the general public.

Training the next generation of scientists in Weather Forecasting: new approaches with real models

NASA Astrophysics Data System (ADS)

Carver, Glenn; Váňa, Filip; Siemen, Stephan; Kertesz, Sandor; Keeley, Sarah

2014-05-01

The European Centre for Medium Range Weather Forecasts operationally produce medium range forecasts using what is internationally acknowledged as the world leading global weather forecast model. Future development of this scientifically advanced model relies on a continued availability of experts in the field of meteorological science and with high-level software skills. ECMWF therefore has a vested interest in young scientists and University graduates developing the necessary skills in numerical weather prediction including both scientific and technical aspects. The OpenIFS project at ECMWF maintains a portable version of the ECMWF forecast model (known as IFS) for use in education and research at Universities, National Meteorological Services and other research and education organisations. OpenIFS models can be run on desktop or high performance computers to produce weather forecasts in a similar way to the operational forecasts at ECMWF. ECMWF also provide the Metview desktop application, a modern, graphical, and easy to use tool for analysing and visualising forecasts that is routinely used by scientists and forecasters at ECMWF and other institutions. The combination of Metview with the OpenIFS models has the potential to deliver classroom-friendly tools allowing students to apply their theoretical knowledge to real-world examples using a world-leading weather forecasting model. In this paper we will describe how the OpenIFS model has been used for teaching. We describe the use of Linux based 'virtual machines' pre-packaged on USB sticks that support a technically easy and safe way of providing 'classroom-on-a-stick' learning environments for advanced training in numerical weather prediction. We welcome discussions with interested parties.

Diagnosis of an intense atmospheric river impacting the pacific northwest: Storm summary and offshore vertical structure observed with COSMIC satellite retrievals

USGS Publications Warehouse

Neiman, P.J.; Ralph, F.M.; Wick, G.A.; Kuo, Y.-H.; Wee, T.-K.; Ma, Z.; Taylor, G.H.; Dettinger, M.D.

2008-01-01

This study uses the new satellite-based Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission to retrieve tropospheric profiles of temperature and moisture over the data-sparse eastern Pacific Ocean. The COSMIC retrievals, which employ a global positioning system radio occultation technique combined with "first-guess" information from numerical weather prediction model analyses, are evaluated through the diagnosis of an intense atmospheric river (AR; i.e., a narrow plume of strong water vapor flux) that devastated the Pacific Northwest with flooding rains in early November 2006. A detailed analysis of this AR is presented first using conventional datasets and highlights the fact that ARs are critical contributors to West Coast extreme precipitation and flooding events. Then, the COSMIC evaluation is provided. Offshore composite COSMIC soundings north of, within, and south of this AR exhibited vertical structures that are meteorologically consistent with satellite imagery and global reanalysis fields of this case and with earlier composite dropsonde results from other landfalling ARs. Also, a curtain of 12 offshore COSMIC soundings through the AR yielded cross-sectional thermodynamic and moisture structures that were similarly consistent, including details comparable to earlier aircraft-based dropsonde analyses. The results show that the new COSMIC retrievals, which are global (currently yielding ???2000 soundings per day), provide high-resolution vertical-profile information beyond that found in the numerical model first-guess fields and can help monitor key lower-tropospheric mesoscale phenomena in data-sparse regions. Hence, COSMIC will likely support a wide array of applications, from physical process studies to data assimilation, numerical weather prediction, and climate research. ?? 2008 American Meteorological Society.

Space-weather assets developed by the French space-physics community

NASA Astrophysics Data System (ADS)

Rouillard, A. P.; Pinto, R. F.; Brun, A. S.; Briand, C.; Bourdarie, S.; Dudok De Wit, T.; Amari, T.; Blelly, P.-L.; Buchlin, E.; Chambodut, A.; Claret, A.; Corbard, T.; Génot, V.; Guennou, C.; Klein, K. L.; Koechlin, L.; Lavarra, M.; Lavraud, B.; Leblanc, F.; Lemorton, J.; Lilensten, J.; Lopez-Ariste, A.; Marchaudon, A.; Masson, S.; Pariat, E.; Reville, V.; Turc, L.; Vilmer, N.; Zucarello, F. P.

2016-12-01

We present a short review of space-weather tools and services developed and maintained by the French space-physics community. They include unique data from ground-based observatories, advanced numerical models, automated identification and tracking tools, a range of space instrumentation and interconnected virtual observatories. The aim of the article is to highlight some advances achieved in this field of research at the national level over the last decade and how certain assets could be combined to produce better space-weather tools exploitable by space-weather centres and customers worldwide. This review illustrates the wide range of expertise developed nationally but is not a systematic review of all assets developed in France.

Climatic variability of a fire-weather index based on turbulent kinetic energy and the Haines Index

Treesearch

Warren E. Heilman; Xindi Bian

2010-01-01

Combining the Haines Index (HI) with near-surface turbulent kinetic energy (TKEs) through a product of the two values (HITKEs) has shown promise as an indicator of the atmospheric potential for extreme and erratic fire behavior in the U.S. Numerical simulations of fire-weather evolution during past wildland fire episodes in...

Severe storms and local weather research

NASA Technical Reports Server (NTRS)

1981-01-01

Developments in the use of space related techniques to understand storms and local weather are summarized. The observation of lightning, storm development, cloud development, mesoscale phenomena, and ageostrophic circulation are discussed. Data acquisition, analysis, and the development of improved sensor and computer systems capability are described. Signal processing and analysis and application of Doppler lidar data are discussed. Progress in numerous experiments is summarized.

Middle Atmosphere Program. Handbook for MAP, volume 20

NASA Technical Reports Server (NTRS)

Bowhill, S. A. (Editor); Edwards, B. (Editor)

1986-01-01

Various topics related to investigations of the middle atmosphere are discussed. Numerical weather prediction, performance characteristics of weather profiling radars, determination of gravity wave and turbulence parameters, case studies of gravity-wave propagation, turbulence and diffusion due to gravity waves, the climatology of gravity waves, mesosphere-stratosphere-troposphere radar, antenna arrays, and data management techniques are among the topics discussed.

Large-Scale Aerosol Modeling and Analysis

DTIC Science & Technology

2008-09-30

novel method of simultaneous real- time measurements of ice-nucleating particle concentrations and size- resolved chemical composition of individual...is to develop a practical predictive capability for visibility and weather effects of aerosol particles for the entire globe for timely use in...prediction follows that used in numerical weather prediction, namely real- time assessment for initialization of first-principles models. The Naval

Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Case, Jonathan; Venners, Jason; Schroeder, Richard; Checchi, Milton; Zavodsky, Bradley; Limaye, Ashutosh; O'Brien, Raymond

2015-01-01

The use of cloud computing resources continues to grow within the public and private sector components of the weather enterprise as users become more familiar with cloud-computing concepts, and competition among service providers continues to reduce costs and other barriers to entry. Cloud resources can also provide capabilities similar to high-performance computing environments, supporting multi-node systems required for near real-time, regional weather predictions. Referred to as "Infrastructure as a Service", or IaaS, the use of cloud-based computing hardware in an on-demand payment system allows for rapid deployment of a modeling system in environments lacking access to a large, supercomputing infrastructure. Use of IaaS capabilities to support regional weather prediction may be of particular interest to developing countries that have not yet established large supercomputing resources, but would otherwise benefit from a regional weather forecasting capability. Recently, collaborators from NASA Marshall Space Flight Center and Ames Research Center have developed a scripted, on-demand capability for launching the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS), which includes pre-compiled binaries of the latest version of the Weather Research and Forecasting (WRF) model. The WRF-EMS provides scripting for downloading appropriate initial and boundary conditions from global models, along with higher-resolution vegetation, land surface, and sea surface temperature data sets provided by the NASA Short-term Prediction Research and Transition (SPoRT) Center. This presentation will provide an overview of the modeling system capabilities and benchmarks performed on the Amazon Elastic Compute Cloud (EC2) environment. In addition, the presentation will discuss future opportunities to deploy the system in support of weather prediction in developing countries supported by NASA's SERVIR Project, which provides capacity building activities in environmental monitoring and prediction across a growing number of regional hubs throughout the world. Capacity-building applications that extend numerical weather prediction to developing countries are intended to provide near real-time applications to benefit public health, safety, and economic interests, but may have a greater impact during disaster events by providing a source for local predictions of weather-related hazards, or impacts that local weather events may have during the recovery phase.

78 FR 35571 - Fisheries of the Caribbean, Gulf of Mexico, and South Atlantic; Shrimp Fishery Off the Southern...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-13

...) when state waters close as a result of severe winter weather. Amendment 9 also revises the overfished... Atlantic shrimp cold weather closure.'' This is because the current regulations refer to the FMP for the... weather and a closure of state waters. Currently, a state must demonstrate at least an 80-percent...

Road Weather and Connected Vehicles

NASA Astrophysics Data System (ADS)

Pisano, P.; Boyce, B. C.

2015-12-01

On average, there are over 5.8 M vehicle crashes each year of which 23% are weather-related. Weather-related crashes are defined as those crashes that occur in adverse weather or on slick pavement. The vast majority of weather-related crashes happen on wet pavement (74%) and during rainfall (46%). Connected vehicle technologies hold the promise to transform road-weather management by providing improved road weather data in real time with greater temporal and geographic accuracy. This will dramatically expand the amount of data that can be used to assess, forecast, and address the impacts that weather has on roads, vehicles, and travelers. The use of vehicle-based measurements of the road and surrounding atmosphere with other, more traditional weather data sources, and create road and atmospheric hazard products for a variety of users. The broad availability of road weather data from mobile sources will vastly improve the ability to detect and forecast weather and road conditions, and will provide the capability to manage road-weather response on specific roadway links. The RWMP is currently demonstrating how weather, road conditions, and related vehicle data can be used for decision making through an innovative Integrated Mobile Observations project. FHWA is partnering with 3 DOTs (MN, MI, & NV) to pilot these applications. One is a mobile alerts application called the Motorists Advisories and Warnings (MAW) and a maintenance decision support application. These applications blend traditional weather information (e.g., radar, surface stations) with mobile vehicle data (e.g., temperature, brake status, wiper status) to determine current weather conditions. These weather conditions, and other road-travel-relevant information, are provided to users via web and phone applications. The MAW provides nowcasts and short-term forecasts out to 24 hours while the EMDSS application can provide forecasts up to 72 hours in advance. The three DOTs have placed readers and external road weather sensors on their maintenance fleet vehicles to collect vehicular and meteorological data. Data from all three states is sent to a processing system called the Pikalert® Vehicle Data Translator (VDT) that quality checks and uses the data to infer current and forecasted weather conditions.

Pikalert(R) System Vehicle Data Translator (VDT) Utilizing Integrated Mobile Observations Pikalert VDT Enhancements, Operations, & Maintenance

DOT National Transportation Integrated Search

2017-03-24

The Pikalert System provides high precision road weather guidance. It assesses current weather and road conditions based on observations from connected vehicles, road weather information stations, radar, and weather model analysis fields. It also for...

46 CFR 44.01-13 - Heavy weather plan.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 2 2014-10-01 2014-10-01 false Heavy weather plan. 44.01-13 Section 44.01-13 Shipping... VOYAGES Administration § 44.01-13 Heavy weather plan. (a) Each heavy weather plan under § 44.01-12(b) must... Inspection. Approval of a heavy weather plan is limited to the current hurricane season. (b) The cognizant...

46 CFR 44.01-13 - Heavy weather plan.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 2 2010-10-01 2010-10-01 false Heavy weather plan. 44.01-13 Section 44.01-13 Shipping... VOYAGES Administration § 44.01-13 Heavy weather plan. (a) Each heavy weather plan under § 44.01-12(b) must... Inspection. Approval of a heavy weather plan is limited to the current hurricane season. (b) The cognizant...

46 CFR 44.01-13 - Heavy weather plan.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 2 2013-10-01 2013-10-01 false Heavy weather plan. 44.01-13 Section 44.01-13 Shipping... VOYAGES Administration § 44.01-13 Heavy weather plan. (a) Each heavy weather plan under § 44.01-12(b) must... Inspection. Approval of a heavy weather plan is limited to the current hurricane season. (b) The cognizant...

46 CFR 44.01-13 - Heavy weather plan.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 2 2012-10-01 2012-10-01 false Heavy weather plan. 44.01-13 Section 44.01-13 Shipping... VOYAGES Administration § 44.01-13 Heavy weather plan. (a) Each heavy weather plan under § 44.01-12(b) must... Inspection. Approval of a heavy weather plan is limited to the current hurricane season. (b) The cognizant...

46 CFR 44.01-13 - Heavy weather plan.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 2 2011-10-01 2011-10-01 false Heavy weather plan. 44.01-13 Section 44.01-13 Shipping... VOYAGES Administration § 44.01-13 Heavy weather plan. (a) Each heavy weather plan under § 44.01-12(b) must... Inspection. Approval of a heavy weather plan is limited to the current hurricane season. (b) The cognizant...

Numerical methods for comparing fresh and weathered oils by their FTIR spectra.

PubMed

Li, Jianfeng; Hibbert, D Brynn; Fuller, Stephen

2007-08-01

Four comparison statistics ('similarity indices') for the identification of the source of a petroleum oil spill based on the ASTM standard test method D3414 were investigated. Namely, (1) first difference correlation coefficient squared and (2) correlation coefficient squared, (3) first difference Euclidean cosine squared and (4) Euclidean cosine squared. For numerical comparison, an FTIR spectrum is divided into three regions, described as: fingerprint (900-700 cm(-1)), generic (1350-900 cm(-1)) and supplementary (1770-1685 cm(-1)), which are the same as the three major regions recommended by the ASTM standard. For fresh oil samples, each similarity index was able to distinguish between replicate independent spectra of the same sample and between different samples. In general, the two first difference-based indices worked better than their parent indices. To provide samples to reveal relationships between weathered and fresh oils, a simple artificial weathering procedure was carried out. Euclidean cosine and correlation coefficients both worked well to maintain identification of a match in the fingerprint region and the two first difference indices were better in the generic region. Receiver operating characteristic curves (true positive rate versus false positive rate) for decisions on matching using the fingerprint region showed two samples could be matched when the difference in weathering time was up to 7 days. Beyond this time the true positive rate falls and samples cannot be reliably matched. However, artificial weathering of a fresh source sample can aid the matching of a weathered sample to its real source from a pool of very similar candidates.

Browsing Space Weather Data and Models with the Integrated Space Weather Analysis (iSWA) System

NASA Technical Reports Server (NTRS)

Maddox, Marlo M.; Mullinix, Richard E.; Berrios, David H.; Hesse, Michael; Rastaetter, Lutz; Pulkkinen, Antti; Hourcle, Joseph A.; Thompson, Barbara J.

2011-01-01

The Integrated Space Weather Analysis (iSWA) System is a comprehensive web-based platform for space weather information that combines data from solar, heliospheric and geospace observatories with forecasts based on the most advanced space weather models. The iSWA system collects, generates, and presents a wide array of space weather resources in an intuitive, user-configurable, and adaptable format - thus enabling users to respond to current and future space weather impacts as well as enabling post-impact analysis. iSWA currently provides over 200 data and modeling products, and features a variety of tools that allow the user to browse, combine, and examine data and models from various sources. This presentation will consist of a summary of the iSWA products and an overview of the customizable user interfaces, and will feature several tutorial demonstrations highlighting the interactive tools and advanced capabilities.

Genetically optimizing weather predictions

NASA Astrophysics Data System (ADS)

Potter, S. B.; Staats, Kai; Romero-Colmenero, Encarni

2016-07-01

humidity, air pressure, wind speed and wind direction) into a database. Built upon this database, we have developed a remarkably simple approach to derive a functional weather predictor. The aim is provide up to the minute local weather predictions in order to e.g. prepare dome environment conditions ready for night time operations or plan, prioritize and update weather dependent observing queues. In order to predict the weather for the next 24 hours, we take the current live weather readings and search the entire archive for similar conditions. Predictions are made against an averaged, subsequent 24 hours of the closest matches for the current readings. We use an Evolutionary Algorithm to optimize our formula through weighted parameters. The accuracy of the predictor is routinely tested and tuned against the full, updated archive to account for seasonal trends and total, climate shifts. The live (updated every 5 minutes) SALT weather predictor can be viewed here: http://www.saao.ac.za/ sbp/suthweather_predict.html

Benchmarking on Tsunami Currents with ComMIT

NASA Astrophysics Data System (ADS)

Sharghi vand, N.; Kanoglu, U.

2015-12-01

There were no standards for the validation and verification of tsunami numerical models before 2004 Indian Ocean tsunami. Even, number of numerical models has been used for inundation mapping effort, evaluation of critical structures, etc. without validation and verification. After 2004, NOAA Center for Tsunami Research (NCTR) established standards for the validation and verification of tsunami numerical models (Synolakis et al. 2008 Pure Appl. Geophys. 165, 2197-2228), which will be used evaluation of critical structures such as nuclear power plants against tsunami attack. NCTR presented analytical, experimental and field benchmark problems aimed to estimate maximum runup and accepted widely by the community. Recently, benchmark problems were suggested by the US National Tsunami Hazard Mitigation Program Mapping & Modeling Benchmarking Workshop: Tsunami Currents on February 9-10, 2015 at Portland, Oregon, USA (http://nws.weather.gov/nthmp/index.html). These benchmark problems concentrated toward validation and verification of tsunami numerical models on tsunami currents. Three of the benchmark problems were: current measurement of the Japan 2011 tsunami in Hilo Harbor, Hawaii, USA and in Tauranga Harbor, New Zealand, and single long-period wave propagating onto a small-scale experimental model of the town of Seaside, Oregon, USA. These benchmark problems were implemented in the Community Modeling Interface for Tsunamis (ComMIT) (Titov et al. 2011 Pure Appl. Geophys. 168, 2121-2131), which is a user-friendly interface to the validated and verified Method of Splitting Tsunami (MOST) (Titov and Synolakis 1995 J. Waterw. Port Coastal Ocean Eng. 121, 308-316) model and is developed by NCTR. The modeling results are compared with the required benchmark data, providing good agreements and results are discussed. Acknowledgment: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no 603839 (Project ASTARTE - Assessment, Strategy and Risk Reduction for Tsunamis in Europe)

Status of NASA Satellite, Field Observations, and Numerical Modeling Addressing the Impact of Urbanization on Short and Long Term Precipitation Variability

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Manyin, Michael; Burian, Steve; Garza, Carlos

2004-01-01

Howard (1833a) made the first documented observation of a temperature difference between an urban area and its rural environment. Manley (1958) termed this contrast the "urban heat island (UHI)". The UHI has now become a widely acknowledged, observed, and researched phenomenon because of its broad implications. It is estimated that by the year 2025, 60% of the world's population will live in cities (UNFP, 1999). In the United States, the current urban growth rate is approximately 12.5%, with 80% currently living in urban areas. As cities continue to grow, urban sprawl creates unique problems related to land use, transportation, agriculture, housing, pollution, and development for policymakers. Urban expansion and its associated urban heat islands also have measurable impacts on weather and climate processes.

New efficient optimizing techniques for Kalman filters and numerical weather prediction models

NASA Astrophysics Data System (ADS)

Famelis, Ioannis; Galanis, George; Liakatas, Aristotelis

2016-06-01

The need for accurate local environmental predictions and simulations beyond the classical meteorological forecasts are increasing the last years due to the great number of applications that are directly or not affected: renewable energy resource assessment, natural hazards early warning systems, global warming and questions on the climate change can be listed among them. Within this framework the utilization of numerical weather and wave prediction systems in conjunction with advanced statistical techniques that support the elimination of the model bias and the reduction of the error variability may successfully address the above issues. In the present work, new optimization methods are studied and tested in selected areas of Greece where the use of renewable energy sources is of critical. The added value of the proposed work is due to the solid mathematical background adopted making use of Information Geometry and Statistical techniques, new versions of Kalman filters and state of the art numerical analysis tools.

Investigation and Modeling of Cranberry Weather Stress.

NASA Astrophysics Data System (ADS)

Croft, Paul Joseph

Cranberry bog weather conditions and weather-related stress were investigated for development of crop yield prediction models and models to predict daily weather conditions in the bog. Field investigations and data gathering were completed at the Rutgers University Blueberry/Cranberry Research Center experimental bogs in Chatsworth, New Jersey. Study indicated that although cranberries generally exhibit little or no stomatal response to changing atmospheric conditions, the evaluation of weather-related stress could be accomplished via use of micrometeorological data. Definition of weather -related stress was made by establishing critical thresholds of the frequencies of occurrence, and magnitudes of, temperature and precipitation in the bog based on values determined by a review of the literature and a grower questionnaire. Stress frequencies were correlated with cranberry yield to develop predictive models based on the previous season's yield, prior season data, prior and current season data, current season data; and prior and current season data through July 31 of the current season. The predictive ability of the prior season models was best and could be used in crop planning and production. Further examination of bog micrometeorological data permitted the isolation of those weather conditions conducive to cranberry scald and allowed for the institution of a pilot scald advisory program during the 1991 season. The micrometeorological data from the bog was also used to develop models to predict daily canopy temperature and precipitation, based on upper air data, for grower use. Models were developed for each month for maximum and minimum temperatures and for precipitation and generally performed well. The modeling of bog weather conditions is an important first step toward daily prediction of cranberry weather-related stress.

The potential impact of scatterometry on oceanography - A wave forecasting case

NASA Technical Reports Server (NTRS)

Cane, M. A.; Cardone, V. J.

1981-01-01

A series of observing system simulation experiments have been performed in order to assess the potential impact of marine surface wind data on numerical weather prediction. In addition to conventional data, the experiments simulated the time-continuous assimilation of remotely sensed marine surface wind or temperature sounding data. The wind data were fabricated directly for model grid points intercepted by a Seasat-1 scatterometer swath and were assimilated into the lowest active level (945 mb) of the model using a localized successive correction method. It is shown that Seasat wind data can greatly improve numerical weather forecasts due to better definition of specific features. The case of the QE II storm is examined.

Contrail Tracking and ARM Data Product Development

NASA Technical Reports Server (NTRS)

Duda, David P.; Russell, James, III

2005-01-01

A contrail tracking system was developed to help in the assessment of the effect of commercial jet contrails on the Earth's radiative budget. The tracking system was built by combining meteorological data from the Rapid Update Cycle (RUC) numerical weather prediction model with commercial air traffic flight track data and satellite imagery. A statistical contrail-forecasting model was created a combination of surface-based contrail observations and numerical weather analyses and forecasts. This model allows predictions of widespread contrail occurrences for contrail research on either a real-time basis or for long-term time scales. Satellite-derived cirrus cloud properties in polluted and unpolluted regions were compared to determine the impact of air traffic on cirrus.

Innovative Near Real-Time Data Dissemination Tools Developed by the Space Weather Research Center

NASA Astrophysics Data System (ADS)

Maddox, Marlo M.; Mullinix, Richard; Mays, M. Leila; Kuznetsova, Maria; Zheng, Yihua; Pulkkinen, Antti; Rastaetter, Lutz

2013-03-01

Access to near real-time and real-time space weather data is essential to accurately specifying and forecasting the space environment. The Space Weather Research Center at NASA Goddard Space Flight Center's Space Weather Laboratory provides vital space weather forecasting services primarily to NASA robotic mission operators, as well as external space weather stakeholders including the Air Force Weather Agency. A key component in this activity is the iNtegrated Space Weather Analysis System which is a joint development project at NASA GSFC between the Space Weather Laboratory, Community Coordinated Modeling Center, Applied Engineering & Technology Directorate, and NASA HQ Office Of Chief Engineer. The iSWA system was developed to address technical challenges in acquiring and disseminating space weather environment information. A key design driver for the iSWA system was to generate and present vast amounts of space weather resources in an intuitive, user-configurable, and adaptable format - thus enabling users to respond to current and future space weather impacts as well as enabling post-impact analysis. Having access to near real-time and real-time data is essential to not only ensuring that relevant observational data is available for analysis - but also in ensuring that models can be driven with the requisite input parameters at proper and efficient temporal and spacial resolutions. The iSWA system currently manages over 300 unique near-real and real-time data feeds from various sources consisting of both observational and simulation data. A comprehensive suite of actionable space weather analysis tools and products are generated and provided utilizing a mixture of the ingested data - enabling new capabilities in quickly assessing past, present, and expected space weather effects. This paper will highlight current and future iSWA system capabilities including the utilization of data from the Solar Dynamics Observatory mission. http://iswa.gsfc.nasa.gov/

Space Weather Forecasting Operational Needs: A view from NOAA/SWPC

NASA Astrophysics Data System (ADS)

Biesecker, D. A.; Onsager, T. G.; Rutledge, R.

2017-12-01

The gaps in space weather forecasting are many. From long lead time forecasts, to accurate warnings with lead time to take action, there is plenty of room for improvement. Significant numbers of new observations would improve this picture, but it's also important to recognize the value of numerical modeling. The obvious interplanetary mission concepts that would be ideal would be 1) to measure the in-situ solar wind along the entire Sun-Earth line from as near to the Sun as possible all the way to Earth 2) a string of spacecraft in 1 AU heliocentric orbits making in-situ measurements as well as remote-sensing observations of the Sun, corona, and heliosphere. Even partially achieving these ideals would benefit space weather services, improving lead time and providing greater accuracy further into the future. The observations alone would improve forecasting. However, integrating these data into numerical models, as boundary conditions or via data assimilation, would provide the greatest improvements.

Visualizing Uncertainty for Probabilistic Weather Forecasting based on Reforecast Analogs

NASA Astrophysics Data System (ADS)

Pelorosso, Leandro; Diehl, Alexandra; Matković, Krešimir; Delrieux, Claudio; Ruiz, Juan; Gröeller, M. Eduard; Bruckner, Stefan

2016-04-01

Numerical weather forecasts are prone to uncertainty coming from inaccuracies in the initial and boundary conditions and lack of precision in numerical models. Ensemble of forecasts partially addresses these problems by considering several runs of the numerical model. Each forecast is generated with different initial and boundary conditions and different model configurations [GR05]. The ensembles can be expressed as probabilistic forecasts, which have proven to be very effective in the decision-making processes [DE06]. The ensemble of forecasts represents only some of the possible future atmospheric states, usually underestimating the degree of uncertainty in the predictions [KAL03, PH06]. Hamill and Whitaker [HW06] introduced the "Reforecast Analog Regression" (RAR) technique to overcome the limitations of ensemble forecasting. This technique produces probabilistic predictions based on the analysis of historical forecasts and observations. Visual analytics provides tools for processing, visualizing, and exploring data to get new insights and discover hidden information patterns in an interactive exchange between the user and the application [KMS08]. In this work, we introduce Albero, a visual analytics solution for probabilistic weather forecasting based on the RAR technique. Albero targets at least two different type of users: "forecasters", who are meteorologists working in operational weather forecasting and "researchers", who work in the construction of numerical prediction models. Albero is an efficient tool for analyzing precipitation forecasts, allowing forecasters to make and communicate quick decisions. Our solution facilitates the analysis of a set of probabilistic forecasts, associated statistical data, observations and uncertainty. A dashboard with small-multiples of probabilistic forecasts allows the forecasters to analyze at a glance the distribution of probabilities as a function of time, space, and magnitude. It provides the user with a more accurate measure of forecast uncertainty that could result in better decision-making. It offers different level of abstractions to help with the recalibration of the RAR method. It also has an inspection tool that displays the selected analogs, their observations and statistical data. It gives the users access to inner parts of the method, unveiling hidden information. References [GR05] GNEITING T., RAFTERY A. E.: Weather forecasting with ensemble methods. Science 310, 5746, 248-249, 2005. [KAL03] KALNAY E.: Atmospheric modeling, data assimilation and predictability. Cambridge University Press, 2003. [PH06] PALMER T., HAGEDORN R.: Predictability of weather and climate. Cambridge University Press, 2006. [HW06] HAMILL T. M., WHITAKER J. S.: Probabilistic quantitative precipitation forecasts based on reforecast analogs: Theory and application. Monthly Weather Review 134, 11, 3209-3229, 2006. [DE06] DEITRICK S., EDSALL R.: The influence of uncertainty visualization on decision making: An empirical evaluation. Springer, 2006. [KMS08] KEIM D. A., MANSMANN F., SCHNEIDEWIND J., THOMAS J., ZIEGLER H.: Visual analytics: Scope and challenges. Springer, 2008.

Weather Driven Renewable Energy Analysis, Modeling New Technologies

NASA Astrophysics Data System (ADS)

Paine, J.; Clack, C.; Picciano, P.; Terry, L.

2015-12-01

Carbon emission reduction is essential to hampering anthropogenic climate change. While there are several methods to broach carbon reductions, the National Energy with Weather System (NEWS) model focuses on limiting electrical generation emissions by way of a national high-voltage direct-current transmission that takes advantage of the strengths of different regions in terms of variable sources of energy. Specifically, we focus upon modeling concentrating solar power (CSP) as another source to contribute to the electric grid. Power tower solar fields are optimized taking into account high spatial and temporal resolution, 13km and hourly, numerical weather prediction model data gathered by NOAA from the years of 2006-2008. Importantly, the optimization of these CSP power plants takes into consideration factors that decrease the optical efficiency of the heliostats reflecting solar irradiance. For example, cosine efficiency, atmospheric attenuation, and shadowing are shown here; however, it should be noted that they are not the only limiting factors. While solar photovoltaic plants can be combined for similar efficiency to the power tower and currently at a lower cost, they do not have a cost-effective capability to provide electricity when there are interruptions in solar irradiance. Power towers rely on a heat transfer fluid, which can be used for thermal storage changing the cost efficiency of this energy source. Thermal storage increases the electric stability that many other renewable energy sources lack, and thus, the ability to choose between direct electric conversion and thermal storage is discussed. The figure shown is a test model of a CSP plant made up of heliostats. The colors show the optical efficiency of each heliostat at a single time of the day.

Improving Weather Forecasts Through Reduced Precision Data Assimilation

NASA Astrophysics Data System (ADS)

Hatfield, Samuel; Düben, Peter; Palmer, Tim

2017-04-01

We present a new approach for improving the efficiency of data assimilation, by trading numerical precision for computational speed. Future supercomputers will allow a greater choice of precision, so that models can use a level of precision that is commensurate with the model uncertainty. Previous studies have already indicated that the quality of climate and weather forecasts is not significantly degraded when using a precision less than double precision [1,2], but so far these studies have not considered data assimilation. Data assimilation is inherently uncertain due to the use of relatively long assimilation windows, noisy observations and imperfect models. Thus, the larger rounding errors incurred from reducing precision may be within the tolerance of the system. Lower precision arithmetic is cheaper, and so by reducing precision in ensemble data assimilation, we can redistribute computational resources towards, for example, a larger ensemble size. Because larger ensembles provide a better estimate of the underlying distribution and are less reliant on covariance inflation and localisation, lowering precision could actually allow us to improve the accuracy of weather forecasts. We will present results on how lowering numerical precision affects the performance of an ensemble data assimilation system, consisting of the Lorenz '96 toy atmospheric model and the ensemble square root filter. We run the system at half precision (using an emulation tool), and compare the results with simulations at single and double precision. We estimate that half precision assimilation with a larger ensemble can reduce assimilation error by 30%, with respect to double precision assimilation with a smaller ensemble, for no extra computational cost. This results in around half a day extra of skillful weather forecasts, if the error-doubling characteristics of the Lorenz '96 model are mapped to those of the real atmosphere. Additionally, we investigate the sensitivity of these results to observational error and assimilation window length. Half precision hardware will become available very shortly, with the introduction of Nvidia's Pascal GPU architecture and the Intel Knights Mill coprocessor. We hope that the results presented here will encourage the uptake of this hardware. References [1] Peter D. Düben and T. N. Palmer, 2014: Benchmark Tests for Numerical Weather Forecasts on Inexact Hardware, Mon. Weather Rev., 142, 3809-3829 [2] Peter D. Düben, Hugh McNamara and T. N. Palmer, 2014: The use of imprecise processing to improve accuracy in weather & climate prediction, J. Comput. Phys., 271, 2-18

Increasing horizontal resolution in numerical weather prediction and climate simulations: illusion or panacea?

PubMed

Wedi, Nils P

2014-06-28

The steady path of doubling the global horizontal resolution approximately every 8 years in numerical weather prediction (NWP) at the European Centre for Medium Range Weather Forecasts may be substantially altered with emerging novel computing architectures. It coincides with the need to appropriately address and determine forecast uncertainty with increasing resolution, in particular, when convective-scale motions start to be resolved. Blunt increases in the model resolution will quickly become unaffordable and may not lead to improved NWP forecasts. Consequently, there is a need to accordingly adjust proven numerical techniques. An informed decision on the modelling strategy for harnessing exascale, massively parallel computing power thus also requires a deeper understanding of the sensitivity to uncertainty--for each part of the model--and ultimately a deeper understanding of multi-scale interactions in the atmosphere and their numerical realization in ultra-high-resolution NWP and climate simulations. This paper explores opportunities for substantial increases in the forecast efficiency by judicious adjustment of the formal accuracy or relative resolution in the spectral and physical space. One path is to reduce the formal accuracy by which the spectral transforms are computed. The other pathway explores the importance of the ratio used for the horizontal resolution in gridpoint space versus wavenumbers in spectral space. This is relevant for both high-resolution simulations as well as ensemble-based uncertainty estimation. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Efficient Ways to Learn Weather Radar Polarimetry

ERIC Educational Resources Information Center

Cao, Qing; Yeary, M. B.; Zhang, Guifu

2012-01-01

The U.S. weather radar network is currently being upgraded with dual-polarization capability. Weather radar polarimetry is an interdisciplinary area of engineering and meteorology. This paper presents efficient ways to learn weather radar polarimetry through several basic and practical topics. These topics include: 1) hydrometeor scattering model…

Weather Fundamentals: Meteorology. [Videotape].

ERIC Educational Resources Information Center

1998

The videos in this educational series, for grades 4-7, help students understand the science behind weather phenomena through dramatic live-action footage, vivid animated graphics, detailed weather maps, and hands-on experiments. This episode (23 minutes) looks at how meteorologists gather and interpret current weather data collected from sources…

Adaptive Numerical Algorithms in Space Weather Modeling

NASA Technical Reports Server (NTRS)

Toth, Gabor; vanderHolst, Bart; Sokolov, Igor V.; DeZeeuw, Darren; Gombosi, Tamas I.; Fang, Fang; Manchester, Ward B.; Meng, Xing; Nakib, Dalal; Powell, Kenneth G.;

Chart links solar, geophysical events with impacts on space technologies

NASA Astrophysics Data System (ADS)

Davenport, George R.

While developing a Space Weather Training Program for Air Force Space Command and the 50th Weather Squadron, both based in Colorado, ARINC Incorporated produced a flowchart that correlates solar and geophysical events with their impacts on Air Force systems.Personnel from both organizations collaborated in the development of the flowchart and provided many comments and suggestions. The model became the centerpiece of the Space Environment Impacts Reference Pamphlet, as well as the formal Space Weather Training Program. Although it is not a numerical or computer model, the flowchart became known as the “Space Environmental Impacts Model.”

Meteorological and Environmental Inputs to Aviation Systems

NASA Technical Reports Server (NTRS)

Camp, Dennis W. (Editor); Frost, Walter (Editor)

1988-01-01

Reports on aviation meteorology, most of them informal, are presented by representatives of the National Weather Service, the Bracknell (England) Meteorological Office, the NOAA Wave Propagation Lab., the Fleet Numerical Oceanography Center, and the Aircraft Owners and Pilots Association. Additional presentations are included on aircraft/lidar turbulence comparison, lightning detection and locating systems, objective detection and forecasting of clear air turbulence, comparative verification between the Generalized Exponential Markov (GEM) Model and official aviation terminal forecasts, the evaluation of the Prototype Regional Observation and Forecast System (PROFS) mesoscale weather products, and the FAA/MIT Lincoln Lab. Doppler Weather Radar Program.

Fuzzy logic-based analogue forecasting and hybrid modelling of horizontal visibility

NASA Astrophysics Data System (ADS)

Tuba, Zoltán; Bottyán, Zsolt

2018-04-01

Forecasting visibility is one of the greatest challenges in aviation meteorology. At the same time, high accuracy visibility forecasts can significantly reduce or make avoidable weather-related risk in aviation as well. To improve forecasting visibility, this research links fuzzy logic-based analogue forecasting and post-processed numerical weather prediction model outputs in hybrid forecast. Performance of analogue forecasting model was improved by the application of Analytic Hierarchy Process. Then, linear combination of the mentioned outputs was applied to create ultra-short term hybrid visibility prediction which gradually shifts the focus from statistical to numerical products taking their advantages during the forecast period. It gives the opportunity to bring closer the numerical visibility forecast to the observations even it is wrong initially. Complete verification of categorical forecasts was carried out; results are available for persistence and terminal aerodrome forecasts (TAF) as well in order to compare. The average value of Heidke Skill Score (HSS) of examined airports of analogue and hybrid forecasts shows very similar results even at the end of forecast period where the rate of analogue prediction in the final hybrid output is 0.1-0.2 only. However, in case of poor visibility (1000-2500 m), hybrid (0.65) and analogue forecasts (0.64) have similar average of HSS in the first 6 h of forecast period, and have better performance than persistence (0.60) or TAF (0.56). Important achievement that hybrid model takes into consideration physics and dynamics of the atmosphere due to the increasing part of the numerical weather prediction. In spite of this, its performance is similar to the most effective visibility forecasting methods and does not follow the poor verification results of clearly numerical outputs.

Modelling economic losses of historic and present-day high-impact winter storms in Switzerland

NASA Astrophysics Data System (ADS)

Welker, Christoph; Martius, Olivia; Stucki, Peter; Bresch, David; Dierer, Silke; Brönnimann, Stefan

2015-04-01

Windstorms can cause significant financial damage and they rank among the most hazardous meteorological hazards in Switzerland. Risk associated with windstorms involves the combination of hazardous weather conditions, such as high wind gust speeds, and socio-economic factors, such as the distribution of assets as well as their susceptibilities to damage. A sophisticated risk assessment is important in a wide range of areas and has benefits for e.g. the insurance industry. However, a sophisticated risk assessment needs a large sample of storm events for which high-resolution, quantitative meteorological and/or loss data are available. Latter is typically an aggravating factor. For present-day windstorms in Switzerland, the data basis is generally sufficient to describe the meteorological development and wind forces as well as the associated impacts. In contrast, historic windstorms are usually described by graphical depictions of the event and/or by weather and loss reports. The information on historic weather events is overall sparse and the available historic weather and loss reports mostly do not provide quantitative information. It has primarily been the field of activity of environmental historians to study historic weather extremes and their impacts. Furthermore, the scarce availability of atmospheric datasets reaching back sufficiently in time has so far limited the analysis of historic weather events. The Twentieth Century Reanalysis (20CR) ensemble dataset, a global atmospheric reanalysis currently spanning 1871 to 2012, offers potentially a very valuable resource for the analysis of historic weather events. However, the 2°×2° latitude-longitude grid of the 20CR is too coarse to realistically represent the complex orography of Switzerland, which has considerable ramifications for the representation of smaller-scale features of the surface wind field influenced by the local orography. Using the 20CR as a starting point, this study illustrates a method to simulate the wind field and related economic impact of both historic and present-day high-impact winter storms in Switzerland since end of the 19th century. Our technique involves the dynamical downscaling of the 20CR to 3 km horizontal resolution using the numerical Weather Research and Forecasting model and the subsequent loss simulation using an open-source impact model. This impact model estimates, for modern economic and social conditions, storm-related economic losses at municipality level, and thus allows a numerical simulation of the impact from both historic and present-day severe winter storms in Switzerland on a relatively fine spatial scale. In this study, we apply the modelling chain to a storm sample of almost 90 high-impact winter storms in Switzerland since 1871, and we are thus able to make a statement of the typical wind and loss patterns of hazardous windstorms in Switzerland. To evaluate our modelling chain, we compare simulated storm losses with insurance loss data for the present-day windstorms "Lothar" and "Joachim" in December 1999 and December 2011, respectively. Our study further includes a range of sensitivity experiments and a discussion of the main sources of uncertainty.

Enviro-HIRLAM/ HARMONIE Studies in ECMWF HPC EnviroAerosols Project

NASA Astrophysics Data System (ADS)

Hansen Sass, Bent; Mahura, Alexander; Nuterman, Roman; Baklanov, Alexander; Palamarchuk, Julia; Ivanov, Serguei; Pagh Nielsen, Kristian; Penenko, Alexey; Edvardsson, Nellie; Stysiak, Aleksander Andrzej; Bostanbekov, Kairat; Amstrup, Bjarne; Yang, Xiaohua; Ruban, Igor; Bergen Jensen, Marina; Penenko, Vladimir; Nurseitov, Daniyar; Zakarin, Edige

2017-04-01

The EnviroAerosols on ECMWF HPC project (2015-2017) "Enviro-HIRLAM/ HARMONIE model research and development for online integrated meteorology-chemistry-aerosols feedbacks and interactions in weather and atmospheric composition forecasting" is aimed at analysis of importance of the meteorology-chemistry/aerosols interactions and to provide a way for development of efficient techniques for on-line coupling of numerical weather prediction and atmospheric chemical transport via process-oriented parameterizations and feedback algorithms, which will improve both the numerical weather prediction and atmospheric composition forecasts. Two main application areas of the on-line integrated modelling are considered: (i) improved numerical weather prediction with short-term feedbacks of aerosols and chemistry on formation and development of meteorological variables, and (ii) improved atmospheric composition forecasting with on-line integrated meteorological forecast and two-way feedbacks between aerosols/chemistry and meteorology. During 2015-2016 several research projects were realized. At first, the study on "On-line Meteorology-Chemistry/Aerosols Modelling and Integration for Risk Assessment: Case Studies" focused on assessment of scenarios with accidental and continuous emissions of sulphur dioxide for case studies for Atyrau (Kazakhstan) near the northern part of the Caspian Sea and metallurgical enterprises on the Kola Peninsula (Russia), with GIS integration of modelling results into the RANDOM (Risk Assessment of Nature Detriment due to Oil spill Migration) system. At second, the studies on "The sensitivity of precipitation simulations to the soot aerosol presence" & "The precipitation forecast sensitivity to data assimilation on a very high resolution domain" focused on sensitivity and changes in precipitation life-cycle under black carbon polluted conditions over Scandinavia. At third, studies on "Aerosol effects over China investigated with a high resolution convection permitting weather model" & "Meteorological and chemical urban scale modelling for Shanghai metropolitan area" with focus on aerosol effects and influence of urban areas in China at regional-subregional-urban scales. At fourth, study on "Direct variational data assimilation algorithm for atmospheric chemistry data with transport and transformation model" with focus on testing chemical data assimilation algorithm of in situ concentration measurements on real data scenario. At firth, study on "Aerosol influence on High Resolution NWP HARMONIE Operational Forecasts" with focus on impact of sea salt aerosols on numerical weather prediction during low precipitation events. And finally, study on "Impact of regional afforestation on climatic conditions in metropolitan areas: case study of Copenhagen" with focus on impact of forest and land-cover change on formation and development of temperature regimes in the Copenhagen metropolitan area of Denmark. Selected results and findings will be presented and discussed.

rpe v5: an emulator for reduced floating-point precision in large numerical simulations

NASA Astrophysics Data System (ADS)

Dawson, Andrew; Düben, Peter D.

2017-06-01

This paper describes the rpe (reduced-precision emulator) library which has the capability to emulate the use of arbitrary reduced floating-point precision within large numerical models written in Fortran. The rpe software allows model developers to test how reduced floating-point precision affects the result of their simulations without having to make extensive code changes or port the model onto specialized hardware. The software can be used to identify parts of a program that are problematic for numerical precision and to guide changes to the program to allow a stronger reduction in precision.The development of rpe was motivated by the strong demand for more computing power. If numerical precision can be reduced for an application under consideration while still achieving results of acceptable quality, computational cost can be reduced, since a reduction in numerical precision may allow an increase in performance or a reduction in power consumption. For simulations with weather and climate models, savings due to a reduction in precision could be reinvested to allow model simulations at higher spatial resolution or complexity, or to increase the number of ensemble members to improve predictions. rpe was developed with a particular focus on the community of weather and climate modelling, but the software could be used with numerical simulations from other domains.

A stochastic ensemble-based model to predict crop water requirements from numerical weather forecasts and VIS-NIR high resolution satellite images in Southern Italy

NASA Astrophysics Data System (ADS)

Pelosi, Anna; Falanga Bolognesi, Salvatore; De Michele, Carlo; Medina Gonzalez, Hanoi; Villani, Paolo; D'Urso, Guido; Battista Chirico, Giovanni

2015-04-01

Irrigation agriculture is one the biggest consumer of water in Europe, especially in southern regions, where it accounts for up to 70% of the total water consumption. The EU Common Agricultural Policy, combined with the Water Framework Directive, imposes to farmers and irrigation managers a substantial increase of the efficiency in the use of water in agriculture for the next decade. Ensemble numerical weather predictions can be valuable data for developing operational advisory irrigation services. We propose a stochastic ensemble-based model providing spatial and temporal estimates of crop water requirements, implemented within an advisory service offering detailed maps of irrigation water requirements and crop water consumption estimates, to be used by water irrigation managers and farmers. The stochastic model combines estimates of crop potential evapotranspiration retrieved from ensemble numerical weather forecasts (COSMO-LEPS, 16 members, 7 km resolution) and canopy parameters (LAI, albedo, fractional vegetation cover) derived from high resolution satellite images in the visible and near infrared wavelengths. The service provides users with daily estimates of crop water requirements for lead times up to five days. The temporal evolution of the crop potential evapotranspiration is simulated with autoregressive models. An ensemble Kalman filter is employed for updating model states by assimilating both ground based meteorological variables (where available) and numerical weather forecasts. The model has been applied in Campania region (Southern Italy), where a satellite assisted irrigation advisory service has been operating since 2006. This work presents the results of the system performance for one year of experimental service. The results suggest that the proposed model can be an effective support for a sustainable use and management of irrigation water, under conditions of water scarcity and drought. Since the evapotranspiration term represents a staple component in the water balance of a catchment, as outstanding future development, the model could also offer an advanced support for water resources management decisions at catchment scale.

Assessing the Impact of Observations on Numerical Weather Forecasts Using the Adjoint Method

NASA Technical Reports Server (NTRS)

Gelaro, Ronald

2012-01-01

The adjoint of a data assimilation system provides a flexible and efficient tool for estimating observation impacts on short-range weather forecasts. The impacts of any or all observations can be estimated simultaneously based on a single execution of the adjoint system. The results can be easily aggregated according to data type, location, channel, etc., making this technique especially attractive for examining the impacts of new hyper-spectral satellite instruments and for conducting regular, even near-real time, monitoring of the entire observing system. This talk provides a general overview of the adjoint method, including the theoretical basis and practical implementation of the technique. Results are presented from the adjoint-based observation impact monitoring tool in NASA's GEOS-5 global atmospheric data assimilation and forecast system. When performed in conjunction with standard observing system experiments (OSEs), the adjoint results reveal both redundancies and dependencies between observing system impacts as observations are added or removed from the assimilation system. Understanding these dependencies may be important for optimizing the use of the current observational network and defining requirements for future observing systems

On The Development of One-way Nesting of Air-pollution Model Smog Into Numerical Weather Prediction Model Eta

NASA Astrophysics Data System (ADS)

Halenka, T.; Bednar, J.; Brechler, J.

The spatial distribution of air pollution on the regional scale (Bohemian region) is simulated by means of Charles University puff model SMOG. The results are used for the assessment of the concentration fields of ozone, nitrogen oxides and other ozone precursors. Current improved version of the model covers up to 16 groups of basic compounds and it is based on trajectory computation and puff interaction both by means of Gaussian diffusion mixing and chemical reactions of basic species. Gener- ally, the method used for trajectory computation is valuable mainly for episodes sim- ulation, nevertheless, climatological study can be solved as well by means of average wind rose. For the study being presented huge database of real emission sources was incorporated with all kind of sources included. Some problem with the background values of concentrations was removed. The model SMOG has been nested into the forecast model ETA to obtain appropriate meteorological data input. We can estimate air pollution characteristics both for episodes analysis and the prediction of future air quality conditions. Necessary prognostic variables from the numerical weather pre- diction model are taken for the region of the central Bohemia, where the original puff model was tested. We used mainly 850 hPa wind field for computation of prognos- tic trajectories, the influence of surface temperature as a parameter of photochemistry reactions as well as the effect of cloudness has been tested.

Numerical Hindcast Experiments for Study Tropical Convections and MJO Events during Year of Tropical Convection

NASA Astrophysics Data System (ADS)

Chern, J.; Tao, W.; Shen, B.

2011-12-01

The Madden-Julian oscillation (MJO) is the dominant component of intraseasonal variability in the tropic. It interacts and influences a wide range of weather and climate phenomena across different temporal and spatial scales. Despite the important role the MJO plays in the weather and climate system, past multi-model MJO intercomparison studies have shown that current global general circulation models (GCMs) still have considerable shortcomings in representing and forecasting this phenomenon. To improve representation of MJO and tropical convective cloud systems in global model, an Multiscale Modeling Framework (MMF) in which a cloud-resolving model takes the place of the sing-column cumulus parameterization used in convectional GCMs has been successfully developed at NAAS Goddard (Tao et al. 2009). To evaluate and improve the ability of this modeling system in representation and prediction of the MJO, several numerical hindcast experiments of a few selected MJO events during YOTC have been carried out. The ability of the model to simulate the MJO events is examined using diagnostic and skill metrics developed by the CLIVAR MJO Working Group Project as well as comparisons with a high-resolution global mesoscale model simulations, satellite observations, and analysis dataset. Several key variables associated with the MJO are investigated, including precipitation, outgoing longwave radiation, large-scale circulation, surface latent heat flux, low-level moisture convergence, vertical structure of moisture and hydrometers, and vertical diabatic heating profiles to gain insight of cloud processes associated with the MJO events.

Short Term Exogenic Climate Change Forcing

NASA Astrophysics Data System (ADS)

Krahenbuhl, Daniel

Several short term exogenic forcings affecting Earth's climate are but recently identified. Lunar nutation periodicity has implications for numerical meteorological prediction. Abrupt shifts in solar wind bulk velocity, particle density, and polarity exhibit correlation with terrestrial hemispheric vorticity changes, cyclonic strengthening and the intensification of baroclinic disturbances. Galactic Cosmic ray induced tropospheric ionization modifies cloud microphysics, and modulates the global electric circuit. This dissertation is constructed around three research questions: (1): What are the biweekly declination effects of lunar gravitation upon the troposphere? (2): How do United States severe weather reports correlate with heliospheric current sheet crossings? and (3): How does cloud cover spatially and temporally vary with galactic cosmic rays? Study 1 findings show spatial consistency concerning lunar declination extremes upon Rossby longwaves. Due to the influence of Rossby longwaves on synoptic scale circulation, our results could theoretically extend numerical meteorological forecasting. Study 2 results indicate a preference for violent tornadoes to occur prior to a HCS crossing. Violent tornadoes (EF3+) are 10% more probable to occur near, and 4% less probable immediately after a HCS crossing. The distribution of hail and damaging wind reports do not mirror this pattern. Polarity is critical for the effect. Study 3 results confirm anticorrelation between solar flux and low-level marine-layer cloud cover, but indicate substantial regional variability between cloud cover altitude and GCRs. Ultimately, this dissertation serves to extend short term meteorological forecasting, enhance climatological modeling and through analysis of severe violent weather and heliospheric events, protect property and save lives.

The development of a flash flood severity index

NASA Astrophysics Data System (ADS)

Schroeder, Amanda J.; Gourley, Jonathan J.; Hardy, Jill; Henderson, Jen J.; Parhi, Pradipta; Rahmani, Vahid; Reed, Kimberly A.; Schumacher, Russ S.; Smith, Brianne K.; Taraldsen, Matthew J.

2016-10-01

Flash flooding is a high impact weather event that requires clear communication regarding severity and potential hazards among forecasters, researchers, emergency managers, and the general public. Current standards used to communicate these characteristics include return periods and the United States (U.S.) National Weather Service (NWS) 4-tiered river flooding severity scale. Return periods are largely misunderstood, and the NWS scale is limited to flooding on gauged streams and rivers, often leaving out heavily populated urban corridors. To address these shortcomings, a student-led group of interdisciplinary researchers came together in a collaborative effort to develop an impact-based Flash Flood Severity Index (FFSI). The index was proposed as a damage-based, post-event assessment tool, and preliminary work toward the creation of this index has been completed and presented here. Numerous case studies were analyzed to develop the preliminary outline for the FFSI, and three examples of such cases are included in this paper. The scale includes five impact-based categories ranging from Category 1 very minor flooding to Category 5 catastrophic flooding. Along with the numerous case studies used to develop the initial outline of the scale, empirical data in the form of semi-structured interviews were conducted with multiple NWS forecasters across the country and their responses were analyzed to gain more perspective on the complicated nature of flash flood definitions and which tools were found to be most useful. The feedback from these interviews suggests the potential for acceptance of such an index if it can account for specific challenges.

Light scattering and absorption by space weathered planetary bodies: Novel numerical solution

NASA Astrophysics Data System (ADS)

Markkanen, Johannes; Väisänen, Timo; Penttilä, Antti; Muinonen, Karri

2017-10-01

Airless planetary bodies are exposed to space weathering, i.e., energetic electromagnetic and particle radiation, implantation and sputtering from solar wind particles, and micrometeorite bombardment.Space weathering is known to alter the physical and chemical composition of the surface of an airless body (C. Pieters et al., J. Geophys. Res. Planets, 121, 2016). From the light scattering perspective, one of the key effects is the production of nanophase iron (npFe0) near the exposed surfaces (B. Hapke, J. Geophys. Res., 106, E5, 2001). At visible and ultraviolet wavelengths these particles have a strong electromagnetic response which has a major impact on scattering and absorption features. Thus, to interpret the spectroscopic observations of space-weathered asteroids, the model should treat the contributions of the npFe0 particles rigorously.Our numerical approach is based on the hierarchical geometric optics (GO) and radiative transfer (RT). The modelled asteroid is assumed to consist of densely packed silicate grains with npFe0 inclusions. We employ our recently developed RT method for dense random media (K. Muinonen, et al., Radio Science, submitted, 2017) to compute the contributions of the npFe0 particles embedded in silicate grains. The dense media RT method requires computing interactions of the npFe0 particles in the volume element for which we use the exact fast superposition T-matrix method (J. Markkanen, and A.J. Yuffa, JQSRT 189, 2017). Reflections and refractions on the grain surface and propagation in the grain are addressed by the GO. Finally, the standard RT is applied to compute scattering by the entire asteroid.Our numerical method allows for a quantitative interpretation of the spectroscopic observations of space-weathered asteroids. In addition, it may be an important step towards more rigorous a thermophysical model of asteroids when coupled with the radiative and conductive heat transfer techniques.Acknowledgments. Research supported by European Research Council with Advanced Grant No. 320773 SAEMPL. Computational resources provided by CSC- IT Centre for Science Ltd, Finland.

A survey of customers of space weather information

NASA Astrophysics Data System (ADS)

Schrijver, C. J.; Rabanal, J. P.

2013-09-01

We present an analysis of the users of space weather information based on 2783 responses to an online survey among subscribers of NOAA's Space Weather Prediction Center e-mail services. The survey requested information focused on the three NOAA space weather scales: geomagnetic storms, solar radiation storms, and radio blackouts. Space weather information is most commonly obtained for reasons of human safety and continuity or reliability of operations. The information is primarily used for situational awareness, as aid to understand anomalies, to avoid impacts on current and near-future operations by implementing mitigating strategies, and to prepare for potential near-future impacts that might occur in conjunction with contingencies that include electric power outages or GPS perturbations. Interest in, anticipated impacts from, and responses to the three main categories of space weather are quite uniform across societal sectors. Approximately 40% of the respondents expect serious to very serious impacts from space weather events if no action were taken to mitigate or in the absence of adequate space weather information. The impacts of space weather are deemed to be substantially reduced because of the availability of, and their response to, space weather forecasts and alerts. Current and near-future space weather conditions are generally highly valued, considered useful, and generally, though not fully, adequate to avoid or mitigate societal impacts. We conclude that even among those receiving space weather information, there is considerable uncertainty about the possible impacts of space weather and thus about how to act on the space weather information that is provided.

The ALADIN System and its canonical model configurations AROME CY41T1 and ALARO CY40T1

NASA Astrophysics Data System (ADS)

Termonia, Piet; Fischer, Claude; Bazile, Eric; Bouyssel, François; Brožková, Radmila; Bénard, Pierre; Bochenek, Bogdan; Degrauwe, Daan; Derková, Mariá; El Khatib, Ryad; Hamdi, Rafiq; Mašek, Ján; Pottier, Patricia; Pristov, Neva; Seity, Yann; Smolíková, Petra; Španiel, Oldřich; Tudor, Martina; Wang, Yong; Wittmann, Christoph; Joly, Alain

2018-01-01

The ALADIN System is a numerical weather prediction (NWP) system developed by the international ALADIN consortium for operational weather forecasting and research purposes. It is based on a code that is shared with the global model IFS of the ECMWF and the ARPEGE model of Météo-France. Today, this system can be used to provide a multitude of high-resolution limited-area model (LAM) configurations. A few configurations are thoroughly validated and prepared to be used for the operational weather forecasting in the 16 partner institutes of this consortium. These configurations are called the ALADIN canonical model configurations (CMCs). There are currently three CMCs: the ALADIN baseline CMC, the AROME CMC and the ALARO CMC. Other configurations are possible for research, such as process studies and climate simulations. The purpose of this paper is (i) to define the ALADIN System in relation to the global counterparts IFS and ARPEGE, (ii) to explain the notion of the CMCs, (iii) to document their most recent versions, and (iv) to illustrate the process of the validation and the porting of these configurations to the operational forecast suites of the partner institutes of the ALADIN consortium. This paper is restricted to the forecast model only; data assimilation techniques and postprocessing techniques are part of the ALADIN System but they are not discussed here.

Data Assimilation in the Solar Wind: Challenges and First Results

NASA Astrophysics Data System (ADS)

Lang, Matthew; Browne, Phil; van Leeuwen, Peter Jan; Owens, Matt

2017-04-01

Data assimilation (DA) is currently underused in the solar wind field to improve the modelled variables using observations. Data assimilation has been used in Numerical Weather Prediction (NWP) models with great success, and it can be seen that the improvement of DA methods in NWP modelling has led to improvements in forecasting skill over the past 20-30 years. The state of the art DA methods developed for NWP modelling have never been applied to space weather models, hence it is important to implement the improvements that can be gained from these methods to improve our understanding of the solar wind and how to model it. The ENLIL solar wind model has been coupled to the EMPIRE data assimilation library in order to apply these advanced data assimilation methods to a space weather model. This coupling allows multiple data assimilation methods to be applied to ENLIL with relative ease. I shall discuss twin experiments that have been undertaken, applying the LETKF to the ENLIL model when a CME occurs in the observation and when it does not. These experiments show that there is potential in the application of advanced data assimilation methods to the solar wind field, however, there is still a long way to go until it can be applied effectively. I shall discuss these issues and suggest potential avenues for future research in this area.

Assessing Upper-Level Winds on Day-of-Launch

NASA Technical Reports Server (NTRS)

Bauman, William H., III; Wheeler, Mark M.

2012-01-01

On the day-or-launch. the 45th Weather Squadron Launch Weather Officers (LWOS) monitor the upper-level winds for their launch customers to include NASA's Launch Services Program (LSP). During launch operations, the payload launch team sometimes asks the LWO if they expect the upper level winds to change during the countdown but the LWOs did not have the capability to quickly retrieve or display the upper-level observations and compare them to the numerical weather prediction model point forecasts. The LWOs requested the Applied Meteorology Unit (AMU) develop a capability in the form of a graphical user interface (GUI) that would allow them to plot upper-level wind speed and direction observations from the Kennedy Space Center Doppler Radar Wind Profilers and Cape Canaveral Air Force Station rawinsondes and then overlay model point forecast profiles on the observation profiles to assess the performance of these models and graphically display them to the launch team. The AMU developed an Excel-based capability for the LWOs to assess the model forecast upper-level winds and compare them to observations. They did so by creating a GUI in Excel that allows the LWOs to first initialize the models by comparing the O-hour model forecasts to the observations and then to display model forecasts in 3-hour intervals from the current time through 12 hours.

Dynamic Routing of Aircraft in the Presence of Adverse Weather Using a POMDP Framework

NASA Technical Reports Server (NTRS)

Balaban, Edward; Roychoudhury, Indranil; Spirkovska, Lilly; Sankararaman, Shankar; Kulkarni, Chetan; Arnon, Tomer

2017-01-01

Each year weather-related airline delays result in hundreds of millions of dollars in additional fuel burn, maintenance, and lost revenue, not to mention passenger inconvenience. The current approaches for aircraft route planning in the presence of adverse weather still mainly rely on deterministic methods. In contrast, this work aims to deal with the problem using a Partially Observable Markov Decision Processes (POMDPs) framework, which allows for reasoning over uncertainty (including uncertainty in weather evolution over time) and results in solutions that are more robust to disruptions. The POMDP-based decision support system is demonstrated on several scenarios involving convective weather cells and is benchmarked against a deterministic planning system with functionality similar to those currently in use or under development.

A Wind Forecasting System for Energy Application

NASA Astrophysics Data System (ADS)

Courtney, Jennifer; Lynch, Peter; Sweeney, Conor

2010-05-01

Accurate forecasting of available energy is crucial for the efficient management and use of wind power in the national power grid. With energy output critically dependent upon wind strength there is a need to reduce the errors associated wind forecasting. The objective of this research is to get the best possible wind forecasts for the wind energy industry. To achieve this goal, three methods are being applied. First, a mesoscale numerical weather prediction (NWP) model called WRF (Weather Research and Forecasting) is being used to predict wind values over Ireland. Currently, a gird resolution of 10km is used and higher model resolutions are being evaluated to establish whether they are economically viable given the forecast skill improvement they produce. Second, the WRF model is being used in conjunction with ECMWF (European Centre for Medium-Range Weather Forecasts) ensemble forecasts to produce a probabilistic weather forecasting product. Due to the chaotic nature of the atmosphere, a single, deterministic weather forecast can only have limited skill. The ECMWF ensemble methods produce an ensemble of 51 global forecasts, twice a day, by perturbing initial conditions of a 'control' forecast which is the best estimate of the initial state of the atmosphere. This method provides an indication of the reliability of the forecast and a quantitative basis for probabilistic forecasting. The limitation of ensemble forecasting lies in the fact that the perturbed model runs behave differently under different weather patterns and each model run is equally likely to be closest to the observed weather situation. Models have biases, and involve assumptions about physical processes and forcing factors such as underlying topography. Third, Bayesian Model Averaging (BMA) is being applied to the output from the ensemble forecasts in order to statistically post-process the results and achieve a better wind forecasting system. BMA is a promising technique that will offer calibrated probabilistic wind forecasts which will be invaluable in wind energy management. In brief, this method turns the ensemble forecasts into a calibrated predictive probability distribution. Each ensemble member is provided with a 'weight' determined by its relative predictive skill over a training period of around 30 days. Verification of data is carried out using observed wind data from operational wind farms. These are then compared to existing forecasts produced by ECMWF and Met Eireann in relation to skill scores. We are developing decision-making models to show the benefits achieved using the data produced by our wind energy forecasting system. An energy trading model will be developed, based on the rules currently used by the Single Electricity Market Operator for energy trading in Ireland. This trading model will illustrate the potential for financial savings by using the forecast data generated by this research.

Statistical Analysis of Atmospheric Forecast Model Accuracy - A Focus on Multiple Atmospheric Variables and Location-Based Analysis

DTIC Science & Technology

2014-04-01

WRF ) model is a numerical weather prediction system designed for operational forecasting and atmospheric research. This report examined WRF model... WRF , weather research and forecasting, atmospheric effects 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18. NUMBER OF...and Forecasting ( WRF ) model. The authors would also like to thank Ms. Sherry Larson, STS Systems Integration, LLC, ARL Technical Publishing Branch

Forecasting Winter Storms in the Sierra: A Social Science Perspective in Keeping the Public Safe without Negatively Impacting the Local Tourism Industry

NASA Astrophysics Data System (ADS)

Milne, R.; Wallmann, J.; Myrick, D. T.

2010-12-01

The National Weather Service Office in Reno is responsible for issuing Blizzard Warnings, Winter Storm Warnings, and Winter Weather Advisories for the Sierra, including the Lake Tahoe Basin and heavily traveled routes such as Interstate 80, Highway 395 and Highway 50. These forecast products prepare motorists for harsh travel conditions as well as those venturing into the backcountry, which are essential to the NWS mission of saving lives and property. During the winter season, millions of people from around the world visit the numerous world class ski resorts in the Sierra and the Lake Tahoe Basin, which is vital to the local economy. This situation creates a challenging decision for the forecasters to provide appropriate wording in winter statements to keep the public safe, without significantly impacting the local tourism-based economy. Numerous text and graphical products, including online weather briefings, are utilized by NWS Reno to highlight hazards in ensuring the public, businesses, and other government agencies are prepared for winter storms and take appropriate safety measures. The effectiveness of these product types will be explored, with past snowstorms used as examples to show how forecasters determine which type of text or graphical product is most appropriate to convey the hazardous weather threats.

The Weathering of Antarctic Meteorites: Climatic Controls on Weathering Rates and Implications for Meteorite Accumulation

NASA Technical Reports Server (NTRS)

Benoit, P. H.; Akridge, J. M. C.; Sears, D. W. G.; Bland, P. A.

1995-01-01

Weathering of meteorites includes a variety of chemical and mineralogical changes, including conversion of metal to iron oxides, or rust. Other changes include the devitrification of glass, especially in fusion crust. On a longer time scale, major minerals such as olivine, pyroxene, and feldspar are partially or wholly converted to various phyllosilicates. The degree of weathering of meteorite finds is often noted using a qualitative system based on visual inspection of hand specimens. Several quantitative weathering classification systems have been proposed or are currently under development. Wlotzka has proposed a classification system based on mineralogical changes observed in polished sections and Mossbauer properties of meteorite powders have also been used. In the current paper, we discuss induced thermoluminescence (TL) as an indicator of degree of weathering of individual meteorites. The quantitative measures of weathering, including induced TL, suffer from one major flaw, namely that their results only apply to small portions of the meteorite.

Characterizing severe weather potential in synoptically weakly forced thunderstorm environments

NASA Astrophysics Data System (ADS)

Miller, Paul W.; Mote, Thomas L.

2018-04-01

Weakly forced thunderstorms (WFTs), short-lived convection forming in synoptically quiescent regimes, are a contemporary forecasting challenge. The convective environments that support severe WFTs are often similar to those that yield only non-severe WFTs and, additionally, only a small proportion of individual WFTs will ultimately produce severe weather. The purpose of this study is to better characterize the relative severe weather potential in these settings as a function of the convective environment. Thirty-one near-storm convective parameters for > 200 000 WFTs in the Southeastern United States are calculated from a high-resolution numerical forecasting model, the Rapid Refresh (RAP). For each parameter, the relative odds of WFT days with at least one severe weather event is assessed along a moving threshold. Parameters (and the values of them) that reliably separate severe-weather-supporting from non-severe WFT days are highlighted.Only two convective parameters, vertical totals (VTs) and total totals (TTs), appreciably differentiate severe-wind-supporting and severe-hail-supporting days from non-severe WFT days. When VTs exceeded values between 24.6 and 25.1 °C or TTs between 46.5 and 47.3 °C, odds of severe-wind days were roughly 5 × greater. Meanwhile, odds of severe-hail days became roughly 10 × greater when VTs exceeded 24.4-26.0 °C or TTs exceeded 46.3-49.2 °C. The stronger performance of VT and TT is partly attributed to the more accurate representation of these parameters in the numerical model. Under-reporting of severe weather and model error are posited to exacerbate the forecasting challenge by obscuring the subtle convective environmental differences enhancing storm severity.

Online coupled regional meteorology-chemistry models in Europe: current status and prospects

NASA Astrophysics Data System (ADS)

Baklanov, A.; Schluenzen, K. H.; Suppan, P.; Baldasano, J.; Brunner, D.; Aksoyoglu, S.; Carmichael, G.; Douros, J.; Flemming, J.; Forkel, R.; Galmarini, S.; Gauss, M.; Grell, G.; Hirtl, M.; Joffre, S.; Jorba, O.; Kaas, E.; Kaasik, M.; Kallos, G.; Kong, X.; Korsholm, U.; Kurganskiy, A.; Kushta, J.; Lohmann, U.; Mahura, A.; Manders-Groot, A.; Maurizi, A.; Moussiopoulos, N.; Rao, S. T.; Savage, N.; Seigneur, C.; Sokhi, R.; Solazzo, E.; Solomos, S.; Sørensen, B.; Tsegas, G.; Vignati, E.; Vogel, B.; Zhang, Y.

2013-05-01

The simulation of the coupled evolution of atmospheric dynamics, pollutant transport, chemical reactions and atmospheric composition is one of the most challenging tasks in environmental modelling, climate change studies, and weather forecasting for the next decades as they all involve strongly integrated processes. Weather strongly influences air quality (AQ) and atmospheric transport of hazardous materials, while atmospheric composition can influence both weather and climate by directly modifying the atmospheric radiation budget or indirectly affecting cloud formation. Until recently, however, due to the scientific complexities and lack of computational power, atmospheric chemistry and weather forecasting have developed as separate disciplines, leading to the development of separate modelling systems that are only loosely coupled. The continuous increase in computer power has now reached a stage that enables us to perform online coupling of regional meteorological models with atmospheric chemical transport models. The focus on integrated systems is timely, since recent research has shown that meteorology and chemistry feedbacks are important in the context of many research areas and applications, including numerical weather prediction (NWP), AQ forecasting as well as climate and Earth system modelling. However, the relative importance of online integration and its priorities, requirements and levels of detail necessary for representing different processes and feedbacks can greatly vary for these related communities: (i) NWP, (ii) AQ forecasting and assessments, (iii) climate and earth system modelling. Additional applications are likely to benefit from online modelling, e.g.: simulation of volcanic ash or forest fire plumes, pollen warnings, dust storms, oil/gas fires, geo-engineering tests involving changes in the radiation balance. The COST Action ES1004 - European framework for online integrated air quality and meteorology modelling (EuMetChem) - aims at paving the way towards a new generation of online integrated atmospheric chemical transport and meteorology modelling with two-way interactions between different atmospheric processes including dynamics, chemistry, clouds, radiation, boundary layer and emissions. As its first task, we summarise the current status of European modelling practices and experience with online coupled modelling of meteorology with atmospheric chemistry including feedback mechanisms and attempt reviewing the various issues connected to the different modules of such online coupled models but also providing recommendations for coping with them for the benefit of the modelling community at large.

Wind energy resource modelling in Portugal and its future large-scale alteration due to anthropogenic induced climate changes =

NASA Astrophysics Data System (ADS)

Carvalho, David Joao da Silva

The high dependence of Portugal from foreign energy sources (mainly fossil fuels), together with the international commitments assumed by Portugal and the national strategy in terms of energy policy, as well as resources sustainability and climate change issues, inevitably force Portugal to invest in its energetic self-sufficiency. The 20/20/20 Strategy defined by the European Union defines that in 2020 60% of the total electricity consumption must come from renewable energy sources. Wind energy is currently a major source of electricity generation in Portugal, producing about 23% of the national total electricity consumption in 2013. The National Energy Strategy 2020 (ENE2020), which aims to ensure the national compliance of the European Strategy 20/20/20, states that about half of this 60% target will be provided by wind energy. This work aims to implement and optimise a numerical weather prediction model in the simulation and modelling of the wind energy resource in Portugal, both in offshore and onshore areas. The numerical model optimisation consisted in the determination of which initial and boundary conditions and planetary boundary layer physical parameterizations options provide wind power flux (or energy density), wind speed and direction simulations closest to in situ measured wind data. Specifically for offshore areas, it is also intended to evaluate if the numerical model, once optimised, is able to produce power flux, wind speed and direction simulations more consistent with in situ measured data than wind measurements collected by satellites. This work also aims to study and analyse possible impacts that anthropogenic climate changes may have on the future wind energetic resource in Europe. The results show that the ECMWF reanalysis ERA-Interim are those that, among all the forcing databases currently available to drive numerical weather prediction models, allow wind power flux, wind speed and direction simulations more consistent with in situ wind measurements. It was also found that the Pleim-Xiu and ACM2 planetary boundary layer parameterizations are the ones that showed the best performance in terms of wind power flux, wind speed and direction simulations. This model optimisation allowed a significant reduction of the wind power flux, wind speed and direction simulations errors and, specifically for offshore areas, wind power flux, wind speed and direction simulations more consistent with in situ wind measurements than data obtained from satellites, which is a very valuable and interesting achievement. This work also revealed that future anthropogenic climate changes can negatively impact future European wind energy resource, due to tendencies towards a reduction in future wind speeds especially by the end of the current century and under stronger radiative forcing conditions.

Multispacecraft Observations and Modeling of the 22/23 June 2015 Geomagnetic Storm

NASA Technical Reports Server (NTRS)

Reiff, P. H.; Daou, A. G.; Sazykin, S. Y.; Nakamura, R.; Hairston, M. R.; Coffey, V.; Chandler, M. O.; Anderson, B. J.; Russell, C. T.; Welling, D.;

The Status of the NASA MEaSUREs Combined ASTER and MODIS Emissivity Over Land (CAMEL) Products

NASA Astrophysics Data System (ADS)

Borbas, E. E.; Feltz, M.; Hulley, G. C.; Knuteson, R. O.; Hook, S. J.

2017-12-01

As part of a NASA MEaSUREs Land Surface Temperature and Emissivity project, the University of Wisconsin, Space Science and Engineering Center and the NASA's Jet Propulsion Laboratory have developed a global monthly mean emissivity Earth System Data Record (ESDR). The CAMEL ESDR was produced by merging two current state-of-the-art emissivity datasets: the UW-Madison MODIS Infrared emissivity dataset (UWIREMIS), and the JPL ASTER Global Emissivity Dataset v4 (GEDv4). The dataset includes monthly global data records of emissivity, uncertainty at 13 hinge points between 3.6-14.3 µm, and Principal Components Analysis (PCA) coefficients at 5 kilometer resolution for years 2003 to 2015. A high spectral resolution algorithm is also provided for HSR applications. The dataset is currently being tested in sounder retrieval algorithm (e.g. CrIS, IASI) and has already been implemented in RTTOV-12 for immediate use in numerical weather modeling and data assimilation. This poster will present the current status of the dataset.

Rock-weathering rates as functions of time

USGS Publications Warehouse

Colman, Steven M.

1981-01-01

The scarcity of documented numerical relations between rock weathering and time has led to a common assumption that rates of weathering are linear. This assumption has been strengthened by studies that have calculated long-term average rates. However, little theoretical or empirical evidence exists to support linear rates for most chemical-weathering processes, with the exception of congruent dissolution processes. The few previous studies of rock-weathering rates that contain quantitative documentation of the relation between chemical weathering and time suggest that the rates of most weathering processes decrease with time. Recent studies of weathering rinds on basaltic and andesitic stones in glacial deposits in the western United States also clearly demonstrate that rock-weathering processes slow with time. Some weathering processes appear to conform to exponential functions of time, such as the square-root time function for hydration of volcanic glass, which conforms to the theoretical predictions of diffusion kinetics. However, weathering of mineralogically heterogeneous rocks involves complex physical and chemical processes that generally can be expressed only empirically, commonly by way of logarithmic time functions. Incongruent dissolution and other weathering processes produce residues, which are commonly used as measures of weathering. These residues appear to slow movement of water to unaltered material and impede chemical transport away from it. If weathering residues impede weathering processes then rates of weathering and rates of residue production are inversely proportional to some function of the residue thickness. This results in simple mathematical analogs for weathering that imply nonlinear time functions. The rate of weathering becomes constant only when an equilibrium thickness of the residue is reached. Because weathering residues are relatively stable chemically, and because physical removal of residues below the ground surface is slight, many weathering features require considerable time to reach constant rates of change. For weathering rinds on volcanic stones in the western United States, this time is at least 0.5 my. ?? 1981.

Pilot's Automated Weather Support System (PAWSS) concepts demonstration project. Phase 1: Pilot's weather information requirements and implications for weather data systems design

NASA Technical Reports Server (NTRS)

Crabill, Norman L.; Dash, Ernie R.

1991-01-01

The weather information requirements for pilots and the deficiencies of the current aviation weather support system in meeting these requirements are defined. As the amount of data available to pilots increases significantly in the near future, expert system technology will be needed to assist pilots in assimilating that information. Some other desirable characteristics of an automation-assisted system for weather data acquisition, dissemination, and assimilation are also described.

High Impact Weather Forecasts and Warnings with the GOES-R Geostationary Lightning Mapper (GLM)

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, Richard J.; Koshak, William; Mach, Douglas M.

2011-01-01

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. A major advancement over the current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM). The GLM will operate continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, a GOES-R Risk Reduction Science Team and Algorithm Working Group Lightning Applications Team have begun to develop cal/val performance monitoring tools and new applications using the GLM alone, in conjunction with other instruments, and merged or blended integrated observing system products combining satellite, radar, in-situ and numerical models. Proxy total lightning data from the NASA Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional ground-based lightning networks are being used to develop the pre-launch algorithms, test data sets, and applications, as well as improve our knowledge of thunderstorm initiation and evolution. In this presentation we review the planned implementation of the instrument and suite of operational algorithms.

Are weather models better than gridded observations for precipitation in the mountains? (Invited)

NASA Astrophysics Data System (ADS)

Gutmann, E. D.; Rasmussen, R.; Liu, C.; Ikeda, K.; Clark, M. P.; Brekke, L. D.; Arnold, J.; Raff, D. A.

2013-12-01

Mountain snowpack is a critical storage component in the water cycle, and it provides drinking water for tens of millions of people in the Western US alone. This water store is susceptible to climate change both because warming temperatures are likely to lead to earlier melt and a temporal shift of the hydrograph, and because changing atmospheric conditions are likely to change the precipitation patterns that produce the snowpack. Current measurements of snowfall in complex terrain are limited in number due in part to the logistics of installing equipment in complex terrain. We show that this limitation leads to statistical artifacts in gridded observations of current climate including errors in precipitation season totals of a factor of two or more, increases in wet day fraction, and decreases in storm intensity. In contrast, a high-resolution numerical weather model (WRF) is able to reproduce observed precipitation patterns, leading to confidence in its predictions for areas without measurements and new observations support this. Running WRF for a future climate scenario shows substantial changes in the spatial patterns of precipitation in the mountains related to the physics of hydrometeor production and detrainment that are not captured by statistical downscaling products. The stationarity in statistical downscaling products is likely to lead to important errors in our estimation of future precipitation in complex terrain.

Developments in the Gung Ho dynamical core

NASA Astrophysics Data System (ADS)

Melvin, Thomas

2017-04-01

Gung Ho is the new dynamical core being developed for the next generation Met Office weather and climate model, suitable for meeting the exascale challenge on emerging computer architectures. It builds upon the earlier collaborative project between the Met Office, NERC and STFC Daresbury of the same name to investigate suitable numerical methods for dynamical cores. A mixed-finite element approach is used, where different finite element spaces are used to represent various fields. This method provides a number of beneficial improvements over the current model, such a compatibility and inherent conservation on quasi-uniform unstructured meshes, whilst maintaining the accuracy and good dispersion properties of the staggered grid currently used. Furthermore, the mixed finite element approach allows a large degree of flexibility in the type of mesh, order of approximation and discretisation, providing a simple way to test alternative options to obtain the best model possible.

A Comparison of the Forecast Skills among Three Numerical Models

NASA Astrophysics Data System (ADS)

Lu, D.; Reddy, S. R.; White, L. J.

2003-12-01

Three numerical weather forecast models, MM5, COAMPS and WRF, operating with a joint effort of NOAA HU-NCAS and Jackson State University (JSU) during summer 2003 have been chosen to study their forecast skills against observations. The models forecast over the same region with the same initialization, boundary condition, forecast length and spatial resolution. AVN global dataset have been ingested as initial conditions. Grib resolution of 27 km is chosen to represent the current mesoscale model. The forecasts with the length of 36h are performed to output the result with 12h interval. The key parameters used to evaluate the forecast skill include 12h accumulated precipitation, sea level pressure, wind, surface temperature and dew point. Precipitation is evaluated statistically using conventional skill scores, Threat Score (TS) and Bias Score (BS), for different threshold values based on 12h rainfall observations whereas other statistical methods such as Mean Error (ME), Mean Absolute Error(MAE) and Root Mean Square Error (RMSE) are applied to other forecast parameters.

Simulation of a severe convective storm using a numerical model with explicitly incorporated aerosols

NASA Astrophysics Data System (ADS)

Lompar, Miloš; Ćurić, Mladjen; Romanic, Djordje

2017-09-01

Despite an important role the aerosols play in all stages of cloud lifecycle, their representation in numerical weather prediction models is often rather crude. This paper investigates the effects the explicit versus implicit inclusion of aerosols in a microphysics parameterization scheme in Weather Research and Forecasting (WRF) - Advanced Research WRF (WRF-ARW) model has on cloud dynamics and microphysics. The testbed selected for this study is a severe mesoscale convective system with supercells that struck west and central parts of Serbia in the afternoon of July 21, 2014. Numerical products of two model runs, i.e. one with aerosols explicitly (WRF-AE) included and another with aerosols implicitly (WRF-AI) assumed, are compared against precipitation measurements from surface network of rain gauges, as well as against radar and satellite observations. The WRF-AE model accurately captured the transportation of dust from the north Africa over the Mediterranean and to the Balkan region. On smaller scales, both models displaced the locations of clouds situated above west and central Serbia towards southeast and under-predicted the maximum values of composite radar reflectivity. Similar to satellite images, WRF-AE shows the mesoscale convective system as a merged cluster of cumulonimbus clouds. Both models over-predicted the precipitation amounts; WRF-AE over-predictions are particularly pronounced in the zones of light rain, while WRF-AI gave larger outliers. Unlike WRF-AI, the WRF-AE approach enables the modelling of time evolution and influx of aerosols into the cloud which could be of practical importance in weather forecasting and weather modification. Several likely causes for discrepancies between models and observations are discussed and prospects for further research in this field are outlined.

Numerical modeling analysis of the mesoscale environment conducive to two tornado events using the COSMO.Gr model over Greece

NASA Astrophysics Data System (ADS)

Avgoustoglou, E.; Matsangouras, I. T.; Pytharoulis, I.; Kamperakis, N.; Mylonas, M.; Nastos, P. T.; Bluestein, H. W.

2018-08-01

The COnsortium for Small-scale MOdeling (COSMO) was formed in October 1998, and its general goal is to develop, improve and maintain a non-hydrostatic limited-area atmospheric model. The COSMO model has been designed both for operational numerical weather prediction (NWP) as well as various scientific applications on the meso-β and meso-γ scale. Two tornado case studies were selected to investigate the ability of COSMO model to depict the characteristics of severe convective weather, which favoured the development of the associated storms. The first tornado (TR01) occurred, close to Ag. Ilias village, 8 Km north-western of Aitoliko city over western Greece on February 7, 2013, while the second tornado (TR02) was developed close to Palio Katramio village, 8 Km southern from Xanthi city over northern Greece on November 25, 2015. Although both tornadoes had a short lifetime, they caused significant damages. The COSMO.GR atmospheric model was initialized with analysis from the European Centre for Medium-Range Weather Forecasts (ECMWF). The resulting numerical products with spatial resolution of 0.02° (∼ 2 km) over the geographical domain of Greece depicted very well the severe convective conditions close to tornadoes formation. The Energy Helicity Index (EHI) diagnostic variable in both numerical simulations showed a gradual increase of values closing to the location and time of the tornadogenesis. Similar to EHI, the storm relative helicity (SRH) spatio-temporal analysis followed a gradual increase prior to the tornadogenesis events and was reduced after them.

Evaluation of an operational water cycle prediction system for the Laurentian Great Lakes and St. Lawrence River

NASA Astrophysics Data System (ADS)

Fortin, Vincent; Durnford, Dorothy; Smith, Gregory; Dyck, Sarah; Martinez, Yosvany; Mackay, Murray; Winter, Barbara

2017-04-01

Environment and Climate Change Canada (ECCC) is implementing new numerical guidance products based on fully coupled numerical models to better inform the public as well as specialized users on the current and future state of various components of the water cycle, including stream flow and water levels. Outputs from this new system, named the Water Cycle Prediction System (WCPS), have been available for the Great Lakes and St. Lawrence River watershed since June 2016. WCPS links together ECCC's weather forecasting model, GEM, the 2-D ice model C-ICE, the 3-D lake and ocean model NEMO, and a 2-D hydrological model, WATROUTE. Information concerning the water cycle is passed between the models at intervals varying from a few minutes to one hour. It currently produces two forecasts per day for the next three days of the complete water cycle in the Great Lakes region, the largest freshwater lake system in the world. Products include spatially-varying precipitation, evaporation, river discharge, water level anomalies, surface water temperatures, ice coverage, and surface currents. These new products are of interest to water resources and management authority, flood forecasters, hydroelectricity producers, navigation, environmental disaster managers, search and rescue teams, agriculture, and the general public. This presentation focuses on the evaluation of various elements forecasted by the system, and weighs the advantages and disadvantages of running the system fully coupled.

Fabrication and researching of weathering resistant double cladding power delivery fiber

NASA Astrophysics Data System (ADS)

Rong, Liang; Ren, Junjiang; Li, Rundong; Wang, Lianping; Zou, Huan

2016-01-01

A novel well weathering resistant power delivery fiber which is of double cladding and high optical energy transmitting ability is developed via fluoroplastic out sheath extruding process. The fiber has been comprehensively evaluated including optical performance, mechanical performance, environmental suitability and laser transmitting property. It is shown that the fiber has not only low attenuation, high numerical aperture and better mechanical bending performance, but also outstanding weathering resistance and high power laser transmitting performance, which implies the qualification of the fiber for various kinds of applying situations, such as laser ignition, laser induced expanding sound underwater, ship-based and airborne laser weapon.

For how long can we predict the weather? - Insights into atmospheric predictability from global convection-allowing simulations

NASA Astrophysics Data System (ADS)

Judt, Falko

2017-04-01

A tremendous increase in computing power has facilitated the advent of global convection-resolving numerical weather prediction (NWP) models. Although this technological breakthrough allows for the seamless prediction of weather from local to global scales, the predictability of multiscale weather phenomena in these models is not very well known. To address this issue, we conducted a global high-resolution (4-km) predictability experiment using the Model for Prediction Across Scales (MPAS), a state-of-the-art global NWP model developed at the National Center for Atmospheric Research. The goals of this experiment are to investigate error growth from convective to planetary scales and to quantify the intrinsic, scale-dependent predictability limits of atmospheric motions. The globally uniform resolution of 4 km allows for the explicit treatment of organized deep moist convection, alleviating grave limitations of previous predictability studies that either used high-resolution limited-area models or global simulations with coarser grids and cumulus parameterization. Error growth is analyzed within the context of an "identical twin" experiment setup: the error is defined as the difference between a 20-day long "nature run" and a simulation that was perturbed with small-amplitude noise, but is otherwise identical. It is found that in convectively active regions, errors grow by several orders of magnitude within the first 24 h ("super-exponential growth"). The errors then spread to larger scales and begin a phase of exponential growth after 2-3 days when contaminating the baroclinic zones. After 16 days, the globally averaged error saturates—suggesting that the intrinsic limit of atmospheric predictability (in a general sense) is about two weeks, which is in line with earlier estimates. However, error growth rates differ between the tropics and mid-latitudes as well as between the troposphere and stratosphere, highlighting that atmospheric predictability is a complex problem. The comparatively slower error growth in the tropics and in the stratosphere indicates that certain weather phenomena could potentially have longer predictability than currently thought.

The representation of low-level clouds during the West African monsoon in weather and climate models

NASA Astrophysics Data System (ADS)

Kniffka, Anke; Hannak, Lisa; Knippertz, Peter; Fink, Andreas

2016-04-01

The West African monsoon is one of the most important large-scale circulation features in the tropics and the associated seasonal rainfalls are crucial to rain-fed agriculture and water resources for hundreds of millions of people. However, numerical weather and climate models still struggle to realistically represent salient features of the monsoon across a wide range of scales. Recently it has been shown that substantial errors in radiation and clouds exist in the southern parts of West Africa (8°W-8°E, 5-10°N) during summer. This area is characterised by strong low-level jets associated with the formation of extensive ultra-low stratus clouds. Often persisting long after sunrise, these clouds have a substantial impact on the radiation budget at the surface and thus the diurnal evolution of the planetary boundary layer (PBL). Here we present some first results from a detailed analysis of the representation of these clouds and the associated PBL features across a range of weather and climate models. Recent climate model simulations for the period 1991-2010 run in the framework of the Year of Tropical Convection (YOTC) offer a great opportunity for this analysis. The models are those used for the latest Assessment Report of the Intergovernmental Panel on Climate Change, but for YOTC the model output has a much better temporal resolution, allowing to resolve the diurnal cycle, and includes diabatic terms, allowing to much better assess physical reasons for errors in low-level temperature, moisture and thus cloudiness. These more statistical climate model analyses are complemented by experiments using ICON (Icosahedral non-hydrostatic general circulation model), the new numerical weather prediction model of the German Weather Service and the Max Planck Institute for Meteorology. ICON allows testing sensitivities to model resolution and numerical schemes. These model simulations are validated against (re-)analysis data, satellite observations (e.g. CM SAF cloud and radiation data) and ground-based eye observations of clouds and radiation measurements from weather stations. Our results show that many of the climate models have great difficulties representing the diurnal cycle of winds and clouds, leading to associated errors in radiation. Typical errors include a substantial underestimation of the lowest clouds accompanied by an overestimation of clouds at the top of the monsoon layer, indicating systematic problems in vertical exchange processes, which are also reflected in large errors in jet speed. Consequently, many models show a too flat diurnal cycle in cloudiness. This contribution is part of the EU-funded DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) project that aims to investigate the impact of the drastic increase in anthropogenic emissions in West Africa on the local weather and climate, for example through cloud-aerosol interactions. The analysis of the capability of state-of-the-art numerical models to represent low-level cloudiness presented here is an important requisite for the planned assessments of the influence of anthropogenic aerosol.

Numerical simulations of island effects on airflow and weather during the summer over the island of Oahu

Treesearch

Hiep Van Nguyen; Yie-Leng Chen; Francis Fujioka

2010-01-01

The high-resolution (1.5 km) nonhydrostatic fifth-generation Pennsylvania StateUniversity–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) and an advanced land surface model (LSM) are used to study the island-induced airflow and weather for the island of Oahu, Hawaii, under summer trade wind conditions. Despite Oahu’s relatively small...

Anomalous Lightning Behavior During the 26-27 August 2007 Northern Great Plains Severe Weather Event

NASA Astrophysics Data System (ADS)

Logan, Timothy

2018-02-01

Positive polarity lightning strokes can be useful indicators of thunderstorm behavior. A combination of National Lightning Detection Network and Next Generation Radar retrievals is used to analyze the anomalous positive cloud-to-ground (CG) lightning behavior of a rare, late summer severe weather event that occurred on 26-27 August 2007 in the Northern Great Plains region of the United States and southern Canada. Seven discrete supercells (SC1-SC7) exhibiting frequent and intense lightning were responsible for numerous reports of severe weather (e.g., severe hail and 16 tornadoes) including catastrophic damage to the town of Northwood, North Dakota, caused by SC2. Biomass burning smoke from wildfires in Idaho and Montana was present prior to convective initiation. A positive CG lightning stroke rate of nearly 30 strokes per minute was observed 10 min before the EF4 tornado struck Northwood. SC2 was also responsible for all the reports of tornadoes exceeding an EF2 rating. The strongest peak currents (>200 kA) were observed in SC1-SC4 with SC2 having a maximum value of 280 kA. SC2 dominated the statistics of the line of supercells accounting for 27% of all CG lightning strokes. Positive CG lightning accounted for over 40% of all CG lightning strokes in SC4-SC7 on average, and the maximum exceeded 90% in SC6 and SC7. Increasing positive CG lightning dominance was correlated with an increasing northward gradient of smoke aerosol loading in addition to severe weather being reported before the maximum in positive CG lighting stroke rate (SC5 and SC6). This suggests that a complex combination of synoptic forcing and aerosol perturbation likely led to the observed anomalous positive CG lightning behavior in the supercells.

ASI/CGS products and services in support of GNSS-meteorology

NASA Astrophysics Data System (ADS)

Pacione, Rosa; Pace, Brigida; Bianco, Giuseppe

2013-04-01

For more than a decade, ASI/CGS has supported ground-based GNSS meteorology in Europe participating in various projects such as MAGIC, COST-716, TOUGH, E-GVAP (phase I and II) and providing Zenith Tropospheric path Delays (ZTD) derived from a European network of GNSS stations covering mainly the central Mediterranean area. Working in close cooperation with the meteorological community, GNSS data are analyzed in order to provide ZTD with different latencies ranging from post-processing, useful for climate studies, to near-real time, for hourly assimilation into Numerical Weather Prediction (NWP) model. However advancements in NWP models (such as the Met Office UKV 1.5km model) with rapid update cycles require observations with improved timeliness and with greater spatial and temporal resolution than is currently available. To fulfil this requirement a sub-hourly PPP processing has been set-up, and is under evaluation, thanks to the availability of the IGS RT orbit and clock corrections. Moreover ZTD estimates are the input data for developing new and enhanced products: ZTD residuals fields and Integrated Water Vapour (IWV) maps. The former will be helpful in augmenting empirical tropospheric models for positioning applications. The latter are useful for nowcasting and severe weather monitoring since they let to follow IWV time evolution. We present an overview of the developed products and services; the new directions in support of NWP applications and the nowcasting and forecasting of severe weather events that emerge within E-GVAP phase III and the EU COST Action "Advanced Global Navigation Satellite Systems tropospheric products for monitoring Severe Weather Events and Climate" (GNSS4SWEC). Acknowledgements. This work has been carried out under ASI contract I-014-10-0.

Impact of Probabilistic Weather on Flight Routing Decisions

NASA Technical Reports Server (NTRS)

Sheth, Kapil; Sridhar, Banavar; Mulfinger, Daniel

2006-01-01

Flight delays in the United States have been found to increase year after year, along with the increase in air traffic. During the four-month period from May through August of 2005, weather related delays accounted for roughly 70% of all reported delays, The current weather prediction in tactical (within 2 hours) timeframe is at manageable levels, however, the state of forecasting weather for strategic (2-6 hours) timeframe is still not dependable for long-term planning. In the absence of reliable severe weather forecasts, the decision-making for flights longer than two hours is challenging. This paper deals with an approach of using probabilistic weather prediction for Traffic Flow Management use, and a general method using this prediction for estimating expected values of flight length and delays in the National Airspace System (NAS). The current state-of-the-art convective weather forecasting is employed to aid the decision makers in arriving at decisions for traffic flow and flight planing. The six-agency effort working on the Next Generation Air Transportation System (NGATS) have considered weather-assimilated decision-making as one of the principal foci out of a list of eight. The weather Integrated Product Team has considered integrated weather information and improved aviation weather forecasts as two of the main efforts (Ref. 1, 2). Recently, research has focused on the concept of operations for strategic traffic flow management (Ref. 3) and how weather data can be integrated for improved decision-making for efficient traffic management initiatives (Ref. 4, 5). An overview of the weather data needs and benefits of various participants in the air traffic system along with available products can be found in Ref. 6. Previous work related to use of weather data in identifying and categorizing pilot intrusions into severe weather regions (Ref. 7, 8) has demonstrated a need for better forecasting in the strategic planning timeframes and moving towards a probabilistic description of weather (Ref. 9). This paper focuses on. specified probability in a local region for flight intrusion/deviation decision-making. The process uses a probabilistic weather description, implements that in a air traffic assessment system to study trajectories of aircraft crossing a cut-off probability contour. This value would be useful for meteorologists in creating optimum distribution profiles for severe weather, Once available, the expected values of flight path and aggregate delays are calculated for efficient operations. The current research, however, does not deal with the issue of multiple cell encounters, as well as echo tops, and will be a topic of future work.

Global Environmental Micro Sensors Test Operations in the Natural Environment

NASA Technical Reports Server (NTRS)

Adams, Mark L.; Buza, Matthew; Manobianco, John; Merceret, Francis J.

2007-01-01

ENSCO, Inc. is developing an innovative atmospheric observing system known as Global Environmental Micro Sensors (GEMS). The GEMS concept features an integrated system of miniaturized in situ, airborne probes measuring temperature, relative humidity, pressure, and vector wind velocity. In order for the probes to remain airborne for long periods of time, their design is based on a helium-filled super-pressure balloon. The GEMS probes are neutrally buoyant and carried passively by the wind at predetermined levels. Each probe contains onboard satellite communication, power generation, processing, and geolocation capabilities. ENSCO has partnered with the National Aeronautics and Space Administration's Kennedy Space Center (KSC) for a project called GEMS Test Operations in the Natural Environment (GEMSTONE) that will culminate with limited prototype flights of the system in spring 2007. By leveraging current advances in micro and nanotechnology, the probe mass, size, cost, and complexity can be reduced substantially so that large numbers of probes could be deployed routinely to support ground, launch, and landing operations at KSC and other locations. A full-scale system will improve the data density for the local initialization of high-resolution numerical weather prediction systems by at least an order of magnitude and provide a significantly expanded in situ data base to evaluate launch commit criteria and flight rules. When applied to launch or landing sites, this capability will reduce both weather hazards and weather-related scrubs, thus enhancing both safety and cost-avoidance for vehicles processed by the Shuttle, Launch Services Program, and Constellation Directorates. The GEMSTONE project will conclude with a field experiment in which 10 to 15 probes are released over KSC in east central Florida. The probes will be neutrally buoyant at different altitudes from 500 to 3000 meters and will report their position, speed, heading, temperature, humidity, and pressure via satellite. The GEMS data will be validated against reference observations provided by current weather instrumentation located at KSC. This paper will report on the results of the GEMSTONE project and discuss the challenges encountered in developing an airborne sensor system.

Thermocline Storage Filled with Structured Ceramics. Numerical Consistency of the Developed Numerical Model and First Observations

NASA Astrophysics Data System (ADS)

Motte, Fabrice; Bugler-Lamb, Samuel L.; Falcoz, Quentin

2015-07-01

The attraction of solar energy is greatly enhanced by the possibility of it being used during times of reduced or non-existent solar flux, such as weather induced intermittences or the darkness of the night. Therefore optimizing thermal storage for use in solar energy plants is crucial for the success of this sustainable energy source. Here we present a study of a structured bed filler dedicated to Thermocline type thermal storage, believed to outweigh the financial and thermal benefits of other systems currently in use such as packed bed Thermocline tanks. Several criterions such as Thermocline thickness and Thermocline centering are defined with the purpose of facilitating the assessment of the efficiency of the tank to complement the standard concepts of power output. A numerical model is developed that reduces to two dimensions the modeling of such a tank. The structure within the tank is designed to be built using simple bricks harboring rectangular channels through which the solar heat transfer and storage fluid will flow. The model is scrutinized and tested for physical robustness, and the results are presented in this paper. The consistency of the model is achieved within particular ranges for each physical variable.

The Impact of Microphysical Schemes on Hurricane Intensity and Track

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Shi, Jainn Jong; Chen, Shuyi S.; Lang, Stephen; Lin, Pay-Liam; Hong, Song-You; Peters-Lidard, Christa; Hou, Arthur

2011-01-01

During the past decade, both research and operational numerical weather prediction models [e.g. the Weather Research and Forecasting Model (WRF)] have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with 1-2 km or less horizontal resolutions. WRF is a next-generation meso-scale forecast model and assimilation system. It incorporates a modern software framework, advanced dynamics, numerics and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WRF can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options. At NASA Goddard, four different cloud microphysics options have been implemented into WRF. The performance of these schemes is compared to those of the other microphysics schemes available in WRF for an Atlantic hurricane case (Katrina). In addition, a brief review of previous modeling studies on the impact of microphysics schemes and processes on the intensity and track of hurricanes is presented and compared against the current Katrina study. In general, all of the studies show that microphysics schemes do not have a major impact on track forecasts but do have more of an effect on the simulated intensity. Also, nearly all of the previous studies found that simulated hurricanes had the strongest deepening or intensification when using only warm rain physics. This is because all of the simulated precipitating hydrometeors are large raindrops that quickly fall out near the eye-wall region, which would hydrostatically produce the lowest pressure. In addition, these studies suggested that intensities become unrealistically strong when evaporative cooling from cloud droplets and melting from ice particles are removed as this results in much weaker downdrafts in the simulated storms. However, there are many differences between the different modeling studies, which are identified and discussed.

The origins of computer weather prediction and climate modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lynch, Peter

2008-03-20

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. Amore » fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.« less

The origins of computer weather prediction and climate modeling

NASA Astrophysics Data System (ADS)

Lynch, Peter

2008-03-01

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.

Using Virtualization to Integrate Weather, Climate, and Coastal Science Education

NASA Astrophysics Data System (ADS)

Davis, J. R.; Paramygin, V. A.; Figueiredo, R.; Sheng, Y.

2012-12-01

To better understand and communicate the important roles of weather and climate on the coastal environment, a unique publically available tool is being developed to support research, education, and outreach activities. This tool uses virtualization technologies to facilitate an interactive, hands-on environment in which students, researchers, and general public can perform their own numerical modeling experiments. While prior efforts have focused solely on the study of the coastal and estuary environments, this effort incorporates the community supported weather and climate model (WRF-ARW) into the Coastal Science Educational Virtual Appliance (CSEVA), an education tool used to assist in the learning of coastal transport processes; storm surge and inundation; and evacuation modeling. The Weather Research and Forecasting (WRF) Model is a next-generation, community developed and supported, mesoscale numerical weather prediction system designed to be used internationally for research, operations, and teaching. It includes two dynamical solvers (ARW - Advanced Research WRF and NMM - Nonhydrostatic Mesoscale Model) as well as a data assimilation system. WRF-ARW is the ARW dynamics solver combined with other components of the WRF system which was developed primarily at NCAR, community support provided by the Mesoscale and Microscale Meteorology (MMM) division of National Center for Atmospheric Research (NCAR). Included with WRF is the WRF Pre-processing System (WPS) which is a set of programs to prepare input for real-data simulations. The CSEVA is based on the Grid Appliance (GA) framework and is built using virtual machine (VM) and virtual networking technologies. Virtualization supports integration of an operating system, libraries (e.g. Fortran, C, Perl, NetCDF, etc. necessary to build WRF), web server, numerical models/grids/inputs, pre-/post-processing tools (e.g. WPS / RIP4 or UPS), graphical user interfaces, "Cloud"-computing infrastructure and other tools into a single ready-to-use package. Thus, the previous ornery task of setting up and compiling these tools becomes obsolete and the research, educator or student can focus on using the tools to study the interactions between weather, climate and the coastal environment. The incorporation of WRF into the CSEVA has been designed to be synergistic with the extensive online tutorials and biannual tutorials hosted by NCAR. Included are working examples of the idealized test simulations provided with WRF (2D sea breeze and squalls, a large eddy simulation, a Held and Suarez simulation, etc.) To demonstrate the integration of weather, coastal and coastal science education, example applications are being developed to demonstrate how the system can be used to couple a coastal and estuarine circulation, transport and storm surge model with downscale reanalysis weather and future climate predictions. Documentation, tutorials and the enhanced CSEVA itself will be found on the web at: http://cseva.coastal.ufl.edu.

Method and System for Dynamic Automated Corrections to Weather Avoidance Routes for Aircraft in En Route Airspace

NASA Technical Reports Server (NTRS)

McNally, B. David (Inventor); Erzberger, Heinz (Inventor); Sheth, Kapil (Inventor)

2015-01-01

A dynamic weather route system automatically analyzes routes for in-flight aircraft flying in convective weather regions and attempts to find more time and fuel efficient reroutes around current and predicted weather cells. The dynamic weather route system continuously analyzes all flights and provides reroute advisories that are dynamically updated in real time while the aircraft are in flight. The dynamic weather route system includes a graphical user interface that allows users to visualize, evaluate, modify if necessary, and implement proposed reroutes.

Graphical Weather Information System Evaluation: Usability, Perceived Utility, and Preferences from General Aviation Pilots

NASA Technical Reports Server (NTRS)

Latorella, Kara A.; Chamberlain, James P.

2002-01-01

Weather is a significant factor in General Aviation (GA) accidents and fatality rates. Graphical Weather Information Systems (GWISs) for the flight deck are appropriate technologies for mitigating the difficulties GA pilots have with current aviation weather information sources. This paper describes usability evaluations of a prototype GWIS by 12 GA pilots after using the system in flights towards convective weather. We provide design guidance for GWISs and discuss further research required to support weather situation awareness and in-flight decision making for GA pilots.

Evaluation and economic value of winter weather forecasts

NASA Astrophysics Data System (ADS)

Snyder, Derrick W.

State and local highway agencies spend millions of dollars each year to deploy winter operation teams to plow snow and de-ice roadways. Accurate and timely weather forecast information is critical for effective decision making. Students from Purdue University partnered with the Indiana Department of Transportation to create an experimental winter weather forecast service for the 2012-2013 winter season in Indiana to assist in achieving these goals. One forecast product, an hourly timeline of winter weather hazards produced daily, was evaluated for quality and economic value. Verification of the forecasts was performed with data from the Rapid Refresh numerical weather model. Two objective verification criteria were developed to evaluate the performance of the timeline forecasts. Using both criteria, the timeline forecasts had issues with reliability and discrimination, systematically over-forecasting the amount of winter weather that was observed while also missing significant winter weather events. Despite these quality issues, the forecasts still showed significant, but varied, economic value compared to climatology. Economic value of the forecasts was estimated to be 29.5 million or 4.1 million, depending on the verification criteria used. Limitations of this valuation system are discussed and a framework is developed for more thorough studies in the future.

Weathering Patterns of Forensic Biomarker Compounds and PAHs in Coastal Marsh Sediment Samples since the 2010 Deepwater Horizon Oil Spill

NASA Astrophysics Data System (ADS)

Overton, E. B.; Meyer, B.; Miles, S.; Olson, G.; Adhikari, P. L.

2016-02-01

It has been well established that the composition of oil, when spilled into the marine environment, undergoes substantial changes caused by weathering. The general sequence of this compositional change begins with straight chain alkanes (the fastest to degrade), followed by low molecular weight branched and cyclic alkanes and, finally the aromatics. Most resistant to weathering are the higher molecular weight cyclic and branched alkanes (i.e., the "forensic biomarker compounds" such as the hopanes and steranes) and tri-aromatic ringed steroids. The composition of these biomarker compounds is particularly resistant to change because they are not affected by evaporative weathering, are not water soluble, and are not readily degraded by microbial and/or photo-oxidation. However, after extensive time in the environment, being subjected to numerous weathering factors, biomarker compositional patterns are beginning to exhibit significant changes. This presentation will describe the general weathering patterns of petroleum residues in sediment samples collected from marsh areas of coastal Louisiana over a five year period. Particular attention will focus on compositional changes that have been observed in the steranes and diasteranes compounds that traditionally have been considered the most resistant to compositional changes due to weathering.

Mexican Space Weather Service (SCiESMEX)

NASA Astrophysics Data System (ADS)

Gonzalez-Esparza, J. A.; De la Luz, V.; Corona-Romero, P.; Mejia-Ambriz, J. C.; Gonzalez, L. X.; Sergeeva, M. A.; Romero-Hernandez, E.; Aguilar-Rodriguez, E.

2017-01-01

Legislative modifications of the General Civil Protection Law in Mexico in 2014 included specific references to space hazards and space weather phenomena. The legislation is consistent with United Nations promotion of international engagement and cooperation on space weather awareness, studies, and monitoring. These internal and external conditions motivated the creation of a space weather service in Mexico. The Mexican Space Weather Service (SCiESMEX in Spanish) (www.sciesmex.unam.mx) was initiated in October 2014 and is operated by the Institute of Geophysics at the Universidad Nacional Autonoma de Mexico (UNAM). SCiESMEX became a Regional Warning Center of the International Space Environment Services (ISES) in June 2015. We present the characteristics of the service, some products, and the initial actions for developing a space weather strategy in Mexico. The service operates a computing infrastructure including a web application, data repository, and a high-performance computing server to run numerical models. SCiESMEX uses data of the ground-based instrumental network of the National Space Weather Laboratory (LANCE), covering solar radio burst emissions, solar wind and interplanetary disturbances (by interplanetary scintillation observations), geomagnetic measurements, and analysis of the total electron content (TEC) of the ionosphere (by employing data from local networks of GPS receiver stations).

Realistic natural atmospheric phenomena and weather effects for interactive virtual environments

NASA Astrophysics Data System (ADS)

McLoughlin, Leigh

Clouds and the weather are important aspects of any natural outdoor scene, but existing dynamic techniques within computer graphics only offer the simplest of cloud representations. The problem that this work looks to address is how to provide a means of simulating clouds and weather features such as precipitation, that are suitable for virtual environments. Techniques for cloud simulation are available within the area of meteorology, but numerical weather prediction systems are computationally expensive, give more numerical accuracy than we require for graphics and are restricted to the laws of physics. Within computer graphics, we often need to direct and adjust physical features or to bend reality to meet artistic goals, which is a key difference between the subjects of computer graphics and physical science. Pure physically-based simulations, however, evolve their solutions according to pre-set rules and are notoriously difficult to control. The challenge then is for the solution to be computationally lightweight and able to be directed in some measure while at the same time producing believable results. This work presents a lightweight physically-based cloud simulation scheme that simulates the dynamic properties of cloud formation and weather effects. The system simulates water vapour, cloud water, cloud ice, rain, snow and hail. The water model incorporates control parameters and the cloud model uses an arbitrary vertical temperature profile, with a tool described to allow the user to define this. The result of this work is that clouds can now be simulated in near real-time complete with precipitation. The temperature profile and tool then provide a means of directing the resulting formation..

National Weather Service Forecast Office Guam Home

Science.gov Websites

National Alerts Text Current Conditions Observations Satellite Hydrology River & Lake AHPS Radar Imagery AAFB (Guam) AAFB (Guam) Dial up CONUS Radar Forecasts Activity Planner Guam Public Marine Aviation ; Weather Topics: Local Alerts, Current Conditions, Radar, Satellite, Climate, W-GUM.Webmaster@noaa.gov

A study of comprehension and use of weather information by various agricultural groups in Wisconsin

NASA Technical Reports Server (NTRS)

Smith, J. L.

1972-01-01

An attempt was made to determine whether current techniques are adequate for communicating improved weather forecasts to users. Primary concern was for agricultural users. Efforts were made to learn the preferred source of weather forecasts and the frequency of use. Attempts were also made to measure knowledge of specific terms having to do with weather and comprehension of terms less often used but critical to varying intensities of weather.

Introduction of the Mobile Platform for the Meteorological Observations in Seoul Metropolitan City of Korea

NASA Astrophysics Data System (ADS)

Baek, K. T.; Lee, S.; Kang, M.; Lee, G.

2016-12-01

Traffic accidents due to adverse weather such as fog, heavy rainfall, flooding and road surface freezing have been increasing in Korea. To reduce damages caused by the severe weather on the road, a forecast service of combined real-time road-wise weather and the traffic situation is required. Conventional stationary meteorological observations in sparse location system are limited to observe the detailed road environment. For this reason, a mobile meteorological observation platform has been coupled in Weather Information Service Engine (WISE) which is the prototype of urban-scale high resolution weather prediction system in Seoul metropolitan area of Korea in early August 2016. The instruments onboard are designed to measure 15 meteorological parameters; pressure, temperature, relative humidity, precipitation, up/down net radiation, up/down longwave radiation, up/down shortwave radiation, road surface condition, friction coefficient, water depth, wind direction and speed. The observations from mobile platform show a distinctive advantage of data collection in need for road conditions and inputs for the numerical forecast model. In this study, we introduce and examine the feasibility of mobile observations in urban weather prediction and applications.

Monitoring a local extreme weather event with the scope of hyperspectral sounding

NASA Astrophysics Data System (ADS)

Satapathy, Jyotirmayee; Jangid, Buddhi Prakash

2018-06-01

Operational space-based hyperspectral Infrared sounders retrieve atmospheric temperature and humidity profiles from the measured radiances. These sounders like Atmospheric InfraRed Sounder, Infrared Atmospheric Sounding Interferometer as well as INSAT-3D sounders on geostationary orbit have proved to be very successful in providing these retrievals on global and regional scales, respectively, with good enough spatio-temporal resolutions and are well competent with that of traditional profiles from radiosondes and models fields. The aim of this work is to show how these new generation hyperspectral Infrared sounders can benefit in real-time weather monitoring. We have considered a regional extreme weather event to demonstrate how the profiles retrieved from these operational sounders are consistent with the environmental conditions which have led to this severe weather event. This work has also made use of data products of Moderate Resolution Imaging Spectroradiometer as well as by radiative transfer simulation of clear and cloudy atmospheric conditions using Numerical Weather Prediction profiles in conjunction with INSAT-3D sounder. Our results indicate the potential use of high-quality hyperspectral atmospheric profiles to aid in delineation of real-time weather prediction.

The effort to increase the space weather forecasting accuracy in KSWC

NASA Astrophysics Data System (ADS)

Choi, J. S.

2017-12-01

The Korean Space Weather Center (KSWC) of the National Radio Research Agency (RRA) is a government agency which is the official source of space weather information for Korean Government and the primary action agency of emergency measure to severe space weather condition as the Regional Warning Center of the International Space Environment Service (ISES). KSWC's main role is providing alerts, watches, and forecasts in order to minimize the space weather impacts on both of public and commercial sectors of satellites, aviation, communications, navigations, power grids, and etc. KSWC is also in charge of monitoring the space weather condition and conducting research and development for its main role of space weather operation in Korea. Recently, KSWC are focusing on increasing the accuracy of space weather forecasting results and verifying the model generated results. The forecasting accuracy will be calculated based on the probability statistical estimation so that the results can be compared numerically. Regarding the cosmic radiation does, we are gathering the actual measured data of radiation does using the instrument by cooperation with the domestic airlines. Based on the measurement, we are going to verify the reliability of SAFE system which was developed by KSWC to provide the cosmic radiation does information with the airplane cabin crew and public users.

A numerical circulation model with topography for the Martian Southern Hemisphere

NASA Technical Reports Server (NTRS)

Mass, C.; Sagan, C.

1975-01-01

A quasi-geostrophic numerical model, including friction, radiation, and the observed planetary topography, is applied to the general circulation of the Martian atmosphere in the Southern Hemisphere at latitudes south of about 35 deg. Near equilibrium weather systems developed after about 5 model days. To avoid violating the quasi-geostrophic approximation, only 0.8 of the already smoothed relief was employed. Weather systems and velocity fields are strikingly tied to topography. A 2mb middle latitude jet stream is found of remarkably terrestrial aspect. Highest surface velocities, both horizontal and vertical, are predicted in western Hellas Planitia and eastern Argyre Planitia, which are observed to be preferred sites of origin of major Martian dust storms. Mean horizontal velocities and vertical velocities are found just above the surface velocity boundary layer.

Study of the tornado event in Greece on March 25, 2009: Synoptic analysis and numerical modeling using modified topography

NASA Astrophysics Data System (ADS)

Matsangouras, I. T.; Nastos, P. T.; Pytharoulis, I.

2016-03-01

Recent research revealed that western Greece and NW Peloponnese are regions that favor prefrontal tornadic incidence. On March 25, 2009 a tornado developed approximately at 10:30 UTC near Varda village (NW Peloponnese). Tornado intensity was T4-T5 (TORRO scale) and consequently caused an economic impact of 350,000 € over the local society. The goals of this study are: (i) to analyze synoptic and remote sensing features regarding the tornado event over NW Peloponnese and (ii) to investigate the role of topography in tornadogenesis triggered under strong synoptic scale forcing over that area. Synoptic analysis was based on the European Centre for Medium-Range Weather Forecasts (ECMWF) data sets. The analysis of daily anomaly of synoptic conditions with respect to 30 years' climatology (1981-2010), was based on the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis data sets. In addition, numerous remote sensing data sets were derived by the Hellenic National Meteorological Service (HNMS) weather station network in order to better interpret the examined tornado event. Finally, numerical modeling was performed using the non-hydrostatic Weather Research and Forecasting model (WRF), initialized by ECMWF gridded analyses, with telescoping nested grids that allow the representation of atmospheric circulations ranging from the synoptic scale down to the meso-scale. The two numerical experiments were performed on the basis of: (a) the presence and (b) the absence of topography (landscape), so as to determine whether the occurrence of a tornado - identified by diagnostic instability indices - could be indicated by modifying topography. The energy helicity index (EHI), the bulk Richardson number (BRN) shear, the storm-relative environmental helicity (SRH), and the maximum convective available potential energy (MCAPE, for parcels with maximum θe) were considered as principal diagnostic instability variables and employed in both numerical experiments. Furthermore, model verification was conducted, accompanied by analysis of the absolute vorticity budget. Synoptic analysis revealed that the synoptic weather conditions on March 25, 2009 are in agreement with the composite synoptic climatology for tornado days over western Greece. In addition, maximum daily anomalies at the barometric levels of 500, 700, 850 and 925 hPa were found, compared to the climatology of composite mean anomalies for tornado days over western Greece. Numerical simulations revealed that the topography of NW Peloponnese did not constitute an important factor during the tornado event on March 25, 2009, based on EHI, SRH, BRN, and MCAPE analyses.

The NASA Severe Thunderstorm Observations and Regional Modeling (NASA STORM) Project

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Gatlin, Patrick N.; Lang, Timothy J.; Srikishen, Jayanthi; Case, Jonathan L.; Molthan, Andrew L.; Zavodsky, Bradley T.; Bailey, Jeffrey; Blakeslee, Richard J.; Jedlovec, Gary J.

2016-01-01

The NASA Severe Storm Thunderstorm Observations and Regional Modeling(NASA STORM) project enhanced NASA’s severe weather research capabilities, building upon existing Earth Science expertise at NASA Marshall Space Flight Center (MSFC). During this project, MSFC extended NASA’s ground-based lightning detection capacity to include a readily deployable lightning mapping array (LMA). NASA STORM also enabled NASA’s Short-term Prediction and Research Transition (SPoRT) to add convection allowing ensemble modeling to its portfolio of regional numerical weather prediction (NWP) capabilities. As a part of NASA STORM, MSFC developed new open-source capabilities for analyzing and displaying weather radar observations integrated from both research and operational networks. These accomplishments enabled by NASA STORM are a step towards enhancing NASA’s capabilities for studying severe weather and positions them for any future NASA related severe storm field campaigns.

National Weather Service Forecast Office - Honolulu, Hawai`i

Science.gov Websites

Locations - Coastal Forecast Kauai Northwest Waters Kauai Windward Waters Kauai Leeward Waters Kauai Channel Coastal Wind Observations Buoy Reports, and current weather conditions for selected locations tides , sunrise and sunset information Coastal Waters Forecast general weather overview Tropical information

KSC Weather and Research

NASA Technical Reports Server (NTRS)

Maier, Launa; Huddleston, Lisa; Smith, Kristin

2016-01-01

This briefing outlines the history of Kennedy Space Center (KSC) Weather organization, past research sponsored or performed, current organization, responsibilities, and activities, the evolution of weather support, future technologies, and an update on the status of the buoys located offshore of Cape Canaveral Air Force Station and KSC.

The Czech Hydrometeorological Institute's severe storm nowcasting system

NASA Astrophysics Data System (ADS)

Novak, Petr

2007-02-01

To satisfy requirements for operational severe weather monitoring and prediction, the Czech Hydrometeorological Institute (CHMI) has developed a severe storm nowcasting system which uses weather radar data as its primary data source. Previous CHMI studies identified two methods of radar echo prediction, which were then implemented during 2003 into the Czech weather radar network operational weather processor. The applications put into operations were the Continuity Tracking Radar Echoes by Correlation (COTREC) algorithm, and an application that predicts future radar fields using the wind field derived from the geopotential at 700 hPa calculated from a local numerical weather prediction model (ALADIN). To ensure timely delivery of the prediction products to the users, the forecasts are implemented into a web-based viewer (JSMeteoView) that has been developed by the CHMI Radar Department. At present, this viewer is used by all CHMI forecast offices for versatile visualization of radar and other meteorological data (Meteosat, lightning detection, NWP LAM output, SYNOP data) in the Internet/Intranet environment, and the viewer has detailed geographical navigation capabilities.

Optimal interpolation analysis of leaf area index using MODIS data

USGS Publications Warehouse

Gu, Yingxin; Belair, Stephane; Mahfouf, Jean-Francois; Deblonde, Godelieve

2006-01-01

A simple data analysis technique for vegetation leaf area index (LAI) using Moderate Resolution Imaging Spectroradiometer (MODIS) data is presented. The objective is to generate LAI data that is appropriate for numerical weather prediction. A series of techniques and procedures which includes data quality control, time-series data smoothing, and simple data analysis is applied. The LAI analysis is an optimal combination of the MODIS observations and derived climatology, depending on their associated errors σo and σc. The “best estimate” LAI is derived from a simple three-point smoothing technique combined with a selection of maximum LAI (after data quality control) values to ensure a higher quality. The LAI climatology is a time smoothed mean value of the “best estimate” LAI during the years of 2002–2004. The observation error is obtained by comparing the MODIS observed LAI with the “best estimate” of the LAI, and the climatological error is obtained by comparing the “best estimate” of LAI with the climatological LAI value. The LAI analysis is the result of a weighting between these two errors. Demonstration of the method described in this paper is presented for the 15-km grid of Meteorological Service of Canada (MSC)'s regional version of the numerical weather prediction model. The final LAI analyses have a relatively smooth temporal evolution, which makes them more appropriate for environmental prediction than the original MODIS LAI observation data. They are also more realistic than the LAI data currently used operationally at the MSC which is based on land-cover databases.

Space Weather Modeling Services at the Community Coordinated Modeling Center

NASA Technical Reports Server (NTRS)

Hesse, Michael

2006-01-01

The Community Coordinated Modeling Center (CCMC) is a multi-agency partnership, which aims at the creation of next generation space weather models. The goal of the CCMC is to support the research and developmental work necessary to substantially increase the present-day modeling capability for space weather purposes, and to provide models for transition to the Rapid Prototyping Centers at the space weather forecast centers. This goal requires close collaborations with and substantial involvement of the research community. The physical regions to be addressed by CCMC-related activities range from the solar atmosphere to the Earth's upper atmosphere. The CCMC is an integral part of the National Space Weather Program Implementation Plan, of NASA's Living With a Star (LWS) initiative, and of the Department of Defense Space Weather Transition Plan. CCMC includes a facility at NASA Goddard Space Flight Center. CCMC also provides, to the research community, access to state-of-the-art space research models. In this paper we will provide a description of the current CCMC status, discuss current plans, research and development accomplishments and goals, and describe the model testing and validation process undertaken as part of the CCMC mandate. Special emphasis will be on solar and heliospheric models currently residing at CCMC, and on plans for validation and verification.

Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

NASA Astrophysics Data System (ADS)

DY, C. Y.; Fung, J. C. H.

2016-08-01

A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.

A Multi-Season Study of the Effects of MODIS Sea-Surface Temperatures on Operational WRF Forecasts at NWS Miami, FL

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Santos, Pablo; Lazarus, Steven M.; Splitt, Michael E.; Haines, Stephanie L.; Dembek, Scott R.; Lapenta, William M.

2008-01-01

Studies at the Short-term Prediction Research and Transition (SPORT) Center have suggested that the use of Moderate Resolution Imaging Spectroradiometer (MODIS) sea-surface temperature (SST) composites in regional weather forecast models can have a significant positive impact on short-term numerical weather prediction in coastal regions. Recent work by LaCasse et al (2007, Monthly Weather Review) highlights lower atmospheric differences in regional numerical simulations over the Florida offshore waters using 2-km SST composites derived from the MODIS instrument aboard the polar-orbiting Aqua and Terra Earth Observing System satellites. To help quantify the value of this impact on NWS Weather Forecast Offices (WFOs), the SPORT Center and the NWS WFO at Miami, FL (MIA) are collaborating on a project to investigate the impact of using the high-resolution MODIS SST fields within the Weather Research and Forecasting (WRF) prediction system. The project's goal is to determine whether more accurate specification of the lower-boundary forcing within WRF will result in improved land/sea fluxes and hence, more accurate evolution of coastal mesoscale circulations and the associated sensible weather elements. The NWS MIA is currently running WRF in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software. Twenty-seven hour forecasts are run dally initialized at 0300, 0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and adjacent waters of the Gulf of Mexico and Atlantic Ocean. Each model run is initialized using the Local Analysis and Prediction System (LAPS) analyses available in AWIPS. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at 1/12deg resolution (approx.9 km); however, the RTG product does not exhibit fine-scale details consistent with its grid resolution. SPORT is conducting parallel WRF EMS runs identical to the operational runs at NWS MIA except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water, The MODIS SST composites for initializing the SPORT WRF runs are generated on a 2-km grid four times daily at 0400, 0700, 1600, and 1900 UTC, based on the times of the overhead passes of the Aqua and Terra satellites. The incorporation of the MODIS SST data into the SPORT WRF runs is staggered such that SSTs are updated with a new composite every six hours in each of the WRF runs. From mid-February to July 2007, over 500 parallel WRF simulations have been collected for analysis and verification. This paper will present verification results comparing the NWS MIA operational WRF runs to the SPORT experimental runs, and highlight any substantial differences noted in the predicted mesoscale phenomena for specific cases.

Microplastics in the environment: Challenges in analytical chemistry - A review.

PubMed

Silva, Ana B; Bastos, Ana S; Justino, Celine I L; da Costa, João P; Duarte, Armando C; Rocha-Santos, Teresa A P

2018-08-09

Microplastics can be present in the environment as manufactured microplastics (known as primary microplastics) or resulting from the continuous weathering of plastic litter, which yields progressively smaller plastic fragments (known as secondary microplastics). Herein, we discuss the numerous issues associated with the analysis of microplastics, and to a less extent of nanoplastics, in environmental samples (water, sediments, and biological tissues), from their sampling and sample handling to their identification and quantification. The analytical quality control and quality assurance associated with the validation of analytical methods and use of reference materials for the quantification of microplastics are also discussed, as well as the current challenges within this field of research and possible routes to overcome such limitations. Copyright © 2018 Elsevier B.V. All rights reserved.

Preliminary analysis of pilot ratings of 'part line' information importance

NASA Technical Reports Server (NTRS)

Pritchett, Amy; Hansman, R. John

1993-01-01

With the introduction of digital datalink communications into the Air Traffic Control (ATC) system, there is concern over the potential loss of situational awareness by flight crews due to the reduction in the 'Party Line Information' (PLI). This information is available to the pilot by overhearing communications between ATC and other aircraft. A survey was distributed to determine current PLI use by several pilot operational groups, experience levels and geographic regions. The survey identified numerous important elements. PLI was rated the highest for operations near or on approach to the airport. Several significant variations were found between pilots from different operational groups and experience levels. Traffic and weather information were the most frequently cited as information required to obtain global situation awareness.

Preliminary Analysis of Pilot Ratings of "Party Line" Information Importance

NASA Technical Reports Server (NTRS)

Pritchett, Amy; Hansman, R. John

1993-01-01

With the introduction of digital data link communications into the ATC system, there is concern over the potential loss of situational awareness by flight crews due to the reduction in the 'Party Line' Information (PLI). This information is available to the pilot by overhearing communications between ATC and other aircraft. A survey was distributed to determine current PLI use by several pilot operational groups, experience levels and geographic regions. The survey identified numerous important elements. PLI was rated the highest for operations near or on approach to the airport. Several significant variations were found between pilots from different operational groups and experience levels. Traffic and weather information were the most frequently cited as information required to obtain global situation awareness.

Space weather. Ionospheric control of magnetotail reconnection.

PubMed

Lotko, William; Smith, Ryan H; Zhang, Binzheng; Ouellette, Jeremy E; Brambles, Oliver J; Lyon, John G

2014-07-11

Observed distributions of high-speed plasma flows at distances of 10 to 30 Earth radii (R(E)) in Earth's magnetotail neutral sheet are highly skewed toward the premidnight sector. The flows are a product of the magnetic reconnection process that converts magnetic energy stored in the magnetotail into plasma kinetic and thermal energy. We show, using global numerical simulations, that the electrodynamic interaction between Earth's magnetosphere and ionosphere produces an asymmetry consistent with observed distributions in nightside reconnection and plasmasheet flows and in accompanying ionospheric convection. The primary causal agent is the meridional gradient in the ionospheric Hall conductance which, through the Cowling effect, regulates the distribution of electrical currents flowing within and between the ionosphere and magnetotail. Copyright © 2014, American Association for the Advancement of Science.

National Weather Service Forecast Office - Honolulu, Hawai`i

Science.gov Websites

Locations - Coastal Forecast Kauai Northwest Waters Kauai Windward Waters Kauai Leeward Waters Kauai Channel Oahu Forecast Oahu Surf Forecast Coastal Wind Observations Buoy Reports, and current weather conditions for selected locations tides, sunrise and sunset information Coastal Waters Forecast general weather

DEGRADATION AND TOXIC ASSESSMENT OF WEATHERED TOXAPHENE IN SOILS

EPA Science Inventory

The risk assessment of weathered toxaphene is currently being investigated by NCEA-Cin in an effort to evaluate the potential health risks from exposure to complex mixture of weathered chemicals under both anaerobic and aerobic conditions. The goal of this effort is to develop me...

Calling computers names in Swedish

DOE PAGES

Carlsson, Johan

2017-11-01

I very much enjoyed reading Jim Fleming’s article on Carl-Gustaf Rossby and the seminal contributions Rossby made to meteorology. Furthermore, the otherwise excellent article has two errors. Something must have gotten lost in translation to cause Fleming to claim that “Rossby pursued numerical weather prediction in Sweden in an era in which there was no Swedish word for digital computer.” With applied mathematician Germund Dahlquist, Rossby developed a weather model for the Binär Elektronisk Sekvens Kalkylator (BESK; Binary Electronic Sequence Calculator). Designed and built in Sweden, BESK was the world’s fastest computer when it became operational in 1953. From Septembermore » 1954, BESK weather simulations enabled routine 24-hour national forecasts.« less

Quantitative impact of aerosols on numerical weather prediction. Part II: Impacts to IR radiance assimilation

NASA Astrophysics Data System (ADS)

Marquis, J. W.; Campbell, J. R.; Oyola, M. I.; Ruston, B. C.; Zhang, J.

2017-12-01

This is part II of a two-part series examining the impacts of aerosol particles on weather forecasts. In this study, the aerosol indirect effects on weather forecasts are explored by examining the temperature and moisture analysis associated with assimilating dust contaminated hyperspectral infrared radiances. The dust induced temperature and moisture biases are quantified for different aerosol vertical distribution and loading scenarios. The overall impacts of dust contamination on temperature and moisture forecasts are quantified over the west coast of Africa, with the assistance of aerosol retrievals from AERONET, MPL, and CALIOP. At last, methods for improving hyperspectral infrared data assimilation in dust contaminated regions are proposed.

Calling computers names in Swedish

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlsson, Johan

I very much enjoyed reading Jim Fleming’s article on Carl-Gustaf Rossby and the seminal contributions Rossby made to meteorology. Furthermore, the otherwise excellent article has two errors. Something must have gotten lost in translation to cause Fleming to claim that “Rossby pursued numerical weather prediction in Sweden in an era in which there was no Swedish word for digital computer.” With applied mathematician Germund Dahlquist, Rossby developed a weather model for the Binär Elektronisk Sekvens Kalkylator (BESK; Binary Electronic Sequence Calculator). Designed and built in Sweden, BESK was the world’s fastest computer when it became operational in 1953. From Septembermore » 1954, BESK weather simulations enabled routine 24-hour national forecasts.« less

Modeling the Zeeman effect in high altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

NASA Astrophysics Data System (ADS)

Larsson, R.; Milz, M.; Rayer, P.; Saunders, R.; Bell, W.; Booton, A.; Buehler, S. A.; Eriksson, P.; John, V.

2015-10-01

We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high altitude Special Sensor Microwave Imager/Sounder channels 19-22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively) and the expected profile errors at the affected altitudes (estimated to be around 5 K). For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Same channel, there is 1.2 K in average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Same channel, there is 1.3 K in average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K) and smaller standard deviations (at below 0.4 K) when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies causing up to ± 7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to better constrain the upper atmospheric temperatures.

Modeling the Zeeman effect in high-altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

NASA Astrophysics Data System (ADS)

Larsson, Richard; Milz, Mathias; Rayer, Peter; Saunders, Roger; Bell, William; Booton, Anna; Buehler, Stefan A.; Eriksson, Patrick; John, Viju O.

2016-03-01

We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high-altitude Special Sensor Microwave Imager/Sounder channels 19-22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively) and the expected profile errors at the affected altitudes (estimated to be around 5 K). For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Concerning the same channel, there is 1.2 K on average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Regarding the same channel, there is 1.3 K on average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K) and smaller standard deviations (at below 0.4 K) when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies, causing up to ±7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to better constrain the upper atmospheric temperatures.

Space Weather - Current Capabilities, Future Requirements, and the Path to Improved Forecasting

NASA Astrophysics Data System (ADS)

Mann, Ian

2016-07-01

We present an overview of Space Weather activities and future opportunities including assessments of current status and capabilities, knowledge gaps, and future directions in relation to both observations and modeling. The review includes input from the scientific community including from SCOSTEP scientific discipline representatives (SDRs), COSPAR Main Scientific Organizers (MSOs), and SCOSTEP/VarSITI leaders. The presentation also draws on results from the recent activities related to the production of the COSPAR-ILWS Space Weather Roadmap "Understanding Space Weather to Shield Society" [Schrijver et al., Advances in Space Research 55, 2745 (2015) http://dx.doi.org/10.1016/j.asr.2015.03.023], from the activities related to the United Nations (UN) Committee on the Peaceful Uses of Outer Space (COPUOS) actions in relation to the Long-term Sustainability of Outer Space (LTS), and most recently from the newly formed and ongoing efforts of the UN COPUOS Expert Group on Space Weather.

NATIONAL WEATHER SERVICE MARINE PRODUCTS VIA NOAA WEATHER RADIO

Science.gov Websites

! Boating Safety Beach Hazards Rip Currents Hypothermia Hurricanes Thunderstorms Lightning Coastal Flooding Radio network provides voice broadcasts of local and coastal marine forecasts on a continuous cycle. The forecasts are produced by local National Weather Service Forecast Offices. Coastal stations also broadcast

Teaching Heliophysics Science to Undergraduates in an Engineering Context

NASA Astrophysics Data System (ADS)

Baker, J. B.; Sweeney, D. G.; Ruohoniemi, J.

2013-12-01

In recent years, space research at Virginia Tech has experienced rapid growth since the initiation of the Center for Space Science and Engineering Research (Space@VT) during the summer of 2007. The Space@VT center resides in the College of Engineering and currently comprises approximately 30-40 faculty and students. Space@VT research encompasses a wide spectrum of science and engineering activities including: magnetosphere-ionosphere data analysis; ground- and space-based instrument development; spacecraft design and environmental interactions; and numerical space plasma simulations. In this presentation, we describe how Space@VT research is being integrated into the Virginia Tech undergraduate engineering curriculum via classroom instruction and hands-on group project work. In particular, we describe our experiences teaching a new sophomore course titled 'Exploration of the Space Environment' which covers a broad range of scientific, engineering, and societal aspects associated with the exploration and technological exploitation of space. Topics covered include: science of the space environment; space weather hazards and societal impacts; elementary orbital mechanics and rocket propulsion; spacecraft engineering subsystems; and applications of space-based technologies. We also describe a high-altitude weather balloon project which has been offered as a 'hands-on' option for fulfilling the course project requirements of the course.

Role of Laboratory Plasma Experiments in exploring the Physics of Solar Eruptions

NASA Astrophysics Data System (ADS)

Tripathi, S.

2017-12-01

Solar eruptive events are triggered over a broad range of spatio-temporal scales by a variety of fundamental processes (e.g., force-imbalance, magnetic-reconnection, electrical-current driven instabilities) associated with arched magnetoplasma structures in the solar atmosphere. Contemporary research on solar eruptive events is at the forefront of solar and heliospheric physics due to its relevance to space weather. Details on the formation of magnetized plasma structures on the Sun, storage of magnetic energy in such structures over a long period (several Alfven transit times), and their impulsive eruptions have been recorded in numerous observations and simulated in computer models. Inherent limitations of space observations and uncontrolled nature of solar eruptions pose significant challenges in testing theoretical models and developing the predictive capability for space-weather. The pace of scientific progress in this area can be significantly boosted by tapping the potential of appropriately scaled laboratory plasma experiments to compliment solar observations, theoretical models, and computer simulations. To give an example, recent results from a laboratory plasma experiment on arched magnetic flux ropes will be presented and future challenges will be discussed. (Work supported by National Science Foundation, USA under award number 1619551)

ERS-1 scatterometer calibration and validation activities at ECMWF. B: From radar backscatter characteristics to wind vector solutions

NASA Technical Reports Server (NTRS)

Stoffelen, AD; Anderson, David L. T.; Woiceshyn, Peter M.

1992-01-01

Calibration and validation activities for the ERS-1 scatterometer were carried out at ECMWF (European Center for Medium range Weather Forecast) complementary to the 'Haltenbanken' field campaign off the coast of Norway. At a Numerical Weather Prediction (NWP) center a wealth of verifying data is available both in time and space. This data is used to redefine the wind retrieval procedure given the instrumental characteristics. It was found that a maximum likelihood estimation procedure to obtain the coefficients of a reformulated sigma deg to wind relationship should use radar measurements in logarithmic rather than physical space, and use winds as the wind components rather than wind speed and direction. Doing this, a much more accurate transfer function than the one currently operated by ESA was derived. Sigma deg measurement space shows no signature of a separation in an upwind solution cone and a downwind solution cone. As such signature was anticipated in ESA's wind direction ambiguity removal algorithm, reconsideration of the procedure is necessary. Despite the fact that revisions have to be made in the process of wind retrieval; a grid potential is shown for scatterometry in meteorology and climatology.

Integrated Wind Power Planning Tool

NASA Astrophysics Data System (ADS)

Rosgaard, M. H.; Giebel, G.; Nielsen, T. S.; Hahmann, A.; Sørensen, P.; Madsen, H.

2012-04-01

This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the working title "Integrated Wind Power Planning Tool". The project commenced October 1, 2011, and the goal is to integrate a numerical weather prediction (NWP) model with purely statistical tools in order to assess wind power fluctuations, with focus on long term power system planning for future wind farms as well as short term forecasting for existing wind farms. Currently, wind power fluctuation models are either purely statistical or integrated with NWP models of limited resolution. With regard to the latter, one such simulation tool has been developed at the Wind Energy Division, Risø DTU, intended for long term power system planning. As part of the PSO project the inferior NWP model used at present will be replaced by the state-of-the-art Weather Research & Forecasting (WRF) model. Furthermore, the integrated simulation tool will be improved so it can handle simultaneously 10-50 times more turbines than the present ~ 300, as well as additional atmospheric parameters will be included in the model. The WRF data will also be input for a statistical short term prediction model to be developed in collaboration with ENFOR A/S; a danish company that specialises in forecasting and optimisation for the energy sector. This integrated prediction model will allow for the description of the expected variability in wind power production in the coming hours to days, accounting for its spatio-temporal dependencies, and depending on the prevailing weather conditions defined by the WRF output. The output from the integrated prediction tool constitute scenario forecasts for the coming period, which can then be fed into any type of system model or decision making problem to be solved. The high resolution of the WRF results loaded into the integrated prediction model will ensure a high accuracy data basis is available for use in the decision making process of the Danish transmission system operator, and the need for high accuracy predictions will only increase over the next decade as Denmark approaches the goal of 50% wind power based electricity in 2020, from the current 20%.

Integrated Wind Power Planning Tool

NASA Astrophysics Data System (ADS)

Rosgaard, Martin; Giebel, Gregor; Skov Nielsen, Torben; Hahmann, Andrea; Sørensen, Poul; Madsen, Henrik

2013-04-01

This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the title "Integrated Wind Power Planning Tool". The goal is to integrate a mesoscale numerical weather prediction (NWP) model with purely statistical tools in order to assess wind power fluctuations, with focus on long term power system planning for future wind farms as well as short term forecasting for existing wind farms. Currently, wind power fluctuation models are either purely statistical or integrated with NWP models of limited resolution. Using the state-of-the-art mesoscale NWP model Weather Research & Forecasting model (WRF) the forecast error is sought quantified in dependence of the time scale involved. This task constitutes a preparative study for later implementation of features accounting for NWP forecast errors in the DTU Wind Energy maintained Corwind code - a long term wind power planning tool. Within the framework of PSO 10464 research related to operational short term wind power prediction will be carried out, including a comparison of forecast quality at different mesoscale NWP model resolutions and development of a statistical wind power prediction tool taking input from WRF. The short term prediction part of the project is carried out in collaboration with ENFOR A/S; a Danish company that specialises in forecasting and optimisation for the energy sector. The integrated prediction model will allow for the description of the expected variability in wind power production in the coming hours to days, accounting for its spatio-temporal dependencies, and depending on the prevailing weather conditions defined by the WRF output. The output from the integrated short term prediction tool constitutes scenario forecasts for the coming period, which can then be fed into any type of system model or decision making problem to be solved. The high resolution of the WRF results loaded into the integrated prediction model will ensure a high accuracy data basis is available for use in the decision making process of the Danish transmission system operator. The need for high accuracy predictions will only increase over the next decade as Denmark approaches the goal of 50% wind power based electricity in 2025 from the current 20%.

High Resolution Modeling in Mountainous Terrain for Water Resource Management: AN Extreme Precipitation Event Case Study

NASA Astrophysics Data System (ADS)

Masarik, M. T.; Watson, K. A.; Flores, A. N.; Anderson, K.; Tangen, S.

2016-12-01

The water resources infrastructure of the Western US is designed to deliver reliable water supply to users and provide recreational opportunities for the public, as well as afford flood control for communities by buffering variability in precipitation and snow storage. Thus water resource management is a balancing act of meeting multiple objectives while trying to anticipate and mitigate natural variability of water supply. Currently, the forecast guidance available to personnel managing resources in mountainous terrain is lacking in two ways: the spatial resolution is too coarse, and there is a gap in the intermediate time range (10-30 days). To address this need we examine the effectiveness of using the Weather Research and Forecasting (WRF) model, a state of the art, regional, numerical weather prediction model, as a means to generate high-resolution weather guidance in the intermediate time range. This presentation will focus on a reanalysis and hindcasting case study of the extreme precipitation and flooding event in the Payette River Basin of Idaho during the period of June 2nd-4th, 2010. For the reanalysis exercise we use NCEP's Climate Forecast System Reanalysis (CFSR) and the North American Regional Reanalysis (NARR) data sets as input boundary conditions to WRF. The model configuration includes a horizontal spatial resolution of 3km in the outer nest, and 1 km in the inner nest, with output temporal resolution of 3 hrs and 1 hr, respectively. The hindcast simulations, which are currently underway, will make use of the NCEP Climate Forecast System Reforecast (CFSRR) data. The current state of these runs will be discussed. Preparations for the second of two components in this project, weekly WRF forecasts during the intense portion of the water year, will be briefly described. These forecasts will use the NCEP Climate Forecast System version 2 (CFSv2) operational forecast data as boundary conditions to provide forecast guidance geared towards water resource managers out to a lead time of 30 days. We are particularly interested in the degree to which there is forecast skill in basinwide precipitation occurrence, departure from climatology, timing, and amount in the intermediate time range.

The use of weather surveillance radar and high-resolution three dimensional weather data to monitor a spruce budworm mass exodus flight

Treesearch

Yan Boulanger; Frédéric Fabry; Alamelu Kilambi; Deepa S. Pureswaran; Brian R. Sturtevant; Rémi Saint-Amant

2017-01-01

The likely spread of the current spruce budworm (SBW; Choristoneura fumiferana [Clem.]) outbreak fromhigh to low density areas brings to the forefront a pressing need to understand its dispersal dynamics and to document mass exodus flights in relation to weather patterns. In this study, we used the weather surveillance radar of Val d'Irène in...

Measurements of Ionospheric Density, Temperature, and Spacecraft Charging in a Space Weather Constellation

NASA Astrophysics Data System (ADS)

Balthazor, R. L.; McHarg, M. G.; Wilson, G.

2016-12-01

The Integrated Miniaturized Electrostatic Analyzer (IMESA) is a space weather sensor developed by the United States Air Force Academy and integrated and flown by the DoD's Space Test Program. IMESA records plasma spectrograms from which can be derived plasma density, temperature, and spacecraft frame charging. Results from IMESA currently orbiting on STPSat-3 are presented, showing frame charging effects dependent on a complex function of the number of solar panel cell strings switched in, solar panel current, and plasma density. IMESA will fly on four more satellites launching in the next two calendar years, enabling an undergraduate DoD space weather constellation in Low Earth Orbit that has the ability to significantly improve space weather forecasting capabilities using assimilative forecast models.

Simulated building energy demand biases resulting from the use of representative weather stations

DOE PAGES

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd; ...

2017-11-06

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. Here, we quantify the potential reduction in temperature and load biases from using an increasing number of weather stations over the western U.S. Our novel approach is based on deriving temperature and load time series using incrementally more weather stations, ranging frommore » 8 to roughly 150, to evaluate the ability to capture weather patterns across different seasons. Using 8 stations across the western U.S., one from each IECC climate zone, results in an average absolute summertime temperature bias of ~4.0 °C with respect to a high-resolution gridded dataset. The mean absolute bias drops to ~1.5 °C using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.5%. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20–40% bias of peak building loads during both summer and winter, a significant error for capacity expansion planners who may use these types of simulations. Using weather stations close to population centers reduces both mean and peak load biases. Our approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

Simulated building energy demand biases resulting from the use of representative weather stations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. Here, we quantify the potential reduction in temperature and load biases from using an increasing number of weather stations over the western U.S. Our novel approach is based on deriving temperature and load time series using incrementally more weather stations, ranging frommore » 8 to roughly 150, to evaluate the ability to capture weather patterns across different seasons. Using 8 stations across the western U.S., one from each IECC climate zone, results in an average absolute summertime temperature bias of ~4.0 °C with respect to a high-resolution gridded dataset. The mean absolute bias drops to ~1.5 °C using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.5%. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20–40% bias of peak building loads during both summer and winter, a significant error for capacity expansion planners who may use these types of simulations. Using weather stations close to population centers reduces both mean and peak load biases. Our approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

Simulated building energy demand biases resulting from the use of representative weather stations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burleyson, Casey D.; Voisin, Nathalie; Taylor, Z. Todd

Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in weather that may be important for simulations aimed at understanding how building stocks respond to a changing climate. We quantify the potential reduction in bias from using an increasing number of weather stations over the western U.S. The approach is based on deriving temperature and load time series using incrementally more weather stations, ranging from 8 to roughly 150, tomore » capture weather across different seasons. Using 8 stations, one from each climate zone, across the western U.S. results in an average absolute summertime temperature bias of 7.2°F with respect to a spatially-resolved gridded dataset. The mean absolute bias drops to 2.8°F using all available weather stations. Temperature biases of this magnitude could translate to absolute summertime mean simulated load biases as high as 13.8%, a significant error for capacity expansion planners who may use these types of simulations. Increasing the size of the domain over which biases are calculated reduces their magnitude as positive and negative biases may cancel out. Using 8 representative weather stations can lead to a 20-40% overestimation of peak building loads during both summer and winter. Using weather stations close to population centers reduces both mean and peak load biases. This approach could be used by others designing aggregate building simulations to understand the sensitivity to their choice of weather stations used to drive the models.« less

Prevalence of asthma symptoms in schoolchildren, and climate in west European countries: an ecologic study.

PubMed

Arnedo-Pena, Alberto; García-Marcos, Luis; Bercedo-Sanz, Alberto; Aguinaga-Ontoso, Inés; González-Díaz, Carlos; García-Merino, Agueda; Busquets-Monge, Rosa; Suárez-Varela, Maria Morales; Batlles-Garrido, Juan; Blanco-Quirós, Alfredo A; López-Silvarrey, Angel; García-Hernández, Gloria; Fuertes, Jorge

2013-09-01

The aim of the present study was to estimate the associations between the prevalence of asthma symptoms in schoolchildren and meteorological variables in west European countries that participated in the International Study of Asthma and Allergies in Children (ISAAC), Phase III 1997-2003. An ecologic study was carried out. The prevalence of asthma was obtained from this study from 48 centers in 14 countries, and meteorological variables from those stations closest to ISAAC centers, together with other socioeconomic and health care variables. Multilevel mixed-effects linear regression models were used. For schoolchildren aged 6-7 years, the prevalence rate of asthma decreased with an increase in mean annual sunshine hours, showed a positive association with rainy weather, and warm temperature, and a negative one with relative humidity and physician density (PD). Current wheeze prevalence was stronger in autumn/winter seasons and decreased with increasing PD. Severe current wheeze decreased with PD. For schoolchildren aged 13-14 years, the prevalence rates of asthma and current wheeze increased with rainy weather, and these rates decreased with increased PD. Current wheeze, as measured by a video questionnaire, was inversely associated with sunny weather, and nurse density. Severe current wheeze prevalence was stronger during autumn/winter seasons, decreased with PD, and indoor chlorinated public swimming pool density, and increased with rainy weather. Meteorological factors, including sunny and rainy weather, and PD may have some effect on the prevalence rates of asthma symptoms in children from west European countries.

Prevalence of asthma symptoms in schoolchildren, and climate in west European countries: an ecologic study

NASA Astrophysics Data System (ADS)

Arnedo-Pena, Alberto; García-Marcos, Luis; Bercedo-Sanz, Alberto; Aguinaga-Ontoso, Inés; González-Díaz, Carlos; García-Merino, Águeda; Busquets-Monge, Rosa; Suárez-Varela, Maria Morales; Batlles-Garrido, Juan; Blanco-Quirós, Alfredo A.; López-Silvarrey, Angel; García-Hernández, Gloria; Fuertes, Jorge

2013-09-01

The aim of the present study was to estimate the associations between the prevalence of asthma symptoms in schoolchildren and meteorological variables in west European countries that participated in the International Study of Asthma and Allergies in Children (ISAAC), Phase III 1997-2003. An ecologic study was carried out. The prevalence of asthma was obtained from this study from 48 centers in 14 countries, and meteorological variables from those stations closest to ISAAC centers, together with other socioeconomic and health care variables. Multilevel mixed-effects linear regression models were used. For schoolchildren aged 6-7 years, the prevalence rate of asthma decreased with an increase in mean annual sunshine hours, showed a positive association with rainy weather, and warm temperature, and a negative one with relative humidity and physician density (PD). Current wheeze prevalence was stronger in autumn/winter seasons and decreased with increasing PD. Severe current wheeze decreased with PD. For schoolchildren aged 13-14 years, the prevalence rates of asthma and current wheeze increased with rainy weather, and these rates decreased with increased PD. Current wheeze, as measured by a video questionnaire, was inversely associated with sunny weather, and nurse density. Severe current wheeze prevalence was stronger during autumn/winter seasons, decreased with PD, and indoor chlorinated public swimming pool density, and increased with rainy weather. Meteorological factors, including sunny and rainy weather, and PD may have some effect on the prevalence rates of asthma symptoms in children from west European countries.

Risk-Hedged Approach for Re-Routing Air Traffic Under Weather Uncertainty

NASA Technical Reports Server (NTRS)

Sadovsky, Alexander V.; Bilimoria, Karl D.

2016-01-01

This presentation corresponds to: our paper explores a new risk-hedged approach for re-routing air traffic around forecast convective weather. In this work, flying through a more likely weather instantiation is considered to pose a higher level of risk. Current operational practice strategically plans re-routes to avoid only the most likely (highest risk) weather instantiation, and then tactically makes any necessary adjustments as the weather evolves. The risk-hedged approach strategically plans re-routes by minimizing the risk-adjusted path length, incorporating multiple possible weather instantiations with associated likelihoods (risks). The resulting model is transparent and is readily analyzed for realism and treated with well-understood shortest-path algorithms. Risk-hedged re-routes are computed for some example weather instantiations. The main result is that in some scenarios, relative to an operational-practice proxy solution, the risk-hedged solution provides the benefits of lower risk as well as shorter path length. In other scenarios, the benefits of the risk-hedged solution are ambiguous, because the solution is characterized by a tradeoff between risk and path length. The risk-hedged solution can be executed in those scenarios where it provides a clear benefit over current operational practice.

Quantitative impact of aerosols on numerical weather prediction. Part I: Direct radiative forcing

NASA Astrophysics Data System (ADS)

Marquis, J. W.; Zhang, J.; Reid, J. S.; Benedetti, A.; Christensen, M.

2017-12-01

While the effects of aerosols on climate have been extensively studied over the past two decades, the impacts of aerosols on operational weather forecasts have not been carefully quantified. Despite this lack of quantification, aerosol plumes can impact weather forecasts directly by reducing surface reaching solar radiation and indirectly through affecting remotely sensed data that are used for weather forecasts. In part I of this study, the direct impact of smoke aerosol plumes on surface temperature forecasts are quantified using a smoke aerosol event affecting the United States Upper-Midwest in 2015. NCEP, ECMWF and UKMO model forecast surface temperature uncertainties are studied with respect to aerosol loading. Smoke aerosol direct cooling efficiencies are derived and the potential of including aerosol particles in operational forecasts is discussed, with the consideration of aerosol trends, especially over regions with heavy aerosol loading.

Weighting Statistical Inputs for Data Used to Support Effective Decision Making During Severe Emergency Weather and Environmental Events

NASA Technical Reports Server (NTRS)

Gardner, Adrian

2010-01-01

National Aeronautical and Space Administration (NASA) weather and atmospheric environmental organizations are insatiable consumers of geophysical, hydrometeorological and solar weather statistics. The expanding array of internet-worked sensors producing targeted physical measurements has generated an almost factorial explosion of near real-time inputs to topical statistical datasets. Normalizing and value-based parsing of such statistical datasets in support of time-constrained weather and environmental alerts and warnings is essential, even with dedicated high-performance computational capabilities. What are the optimal indicators for advanced decision making? How do we recognize the line between sufficient statistical sampling and excessive, mission destructive sampling ? How do we assure that the normalization and parsing process, when interpolated through numerical models, yields accurate and actionable alerts and warnings? This presentation will address the integrated means and methods to achieve desired outputs for NASA and consumers of its data.

Severe weather investigation using GNSS signals - a new dimension of GNSS meteorology

NASA Astrophysics Data System (ADS)

Rohm, W.; Zhang, K.; Choy, S.; Kuleshov, Y.; Bosy, J.; Kroszczyński, K.

2012-04-01

The Global Navigation Satellite Systems (GNSS) signals transmitted from satellites are subjected to atmospheric delays since the signals have to propagate through different layers of the atmosphere before GNSS receiver receives them. Two major distinctive effects according to the nature of the impact on the signal propagation are the ionosphere which is a dispersive media and the troposphere which is a non-dispersive layer. In this study, our focus of research is concentrated on the troposphere and the severe weather phenomena caused by midlatitude cyclonic storms. GNSS tomography technique is used to investigate both the spatial and temporal structures of a cyclonic storm. New algorithms will be developed based on optimal integrations of various observation techniques, such as ground-based meteorological measurements, radiosonde data, numerical weather prediction (NWP) models, GNSS radio occultation (RO) profiles. Our initial results suggest that the ground-based GNSS CORS stations will play a major role in the integration process. The structure and distribution of the GNSS CORS network and satellite constellations in context of size and resolution of tomography model are investigated along with the a priori information required, observation and estimation time interval and precision and accuracy needs. A number of numerical analyses are carried out using actual measurements in different parts of the world to evaluate the new algorithms developed through international collaboration. It is expected that GNSS tomography with a number of integrated measurements will provide an important insight into the vertical as well as the horizontal structure of different kinds of severe weather phenomena. It is also expected that GNSS tomography will become an important tool for the study of the severe weather processes, such as the development, maturation, and dissipation stages, which is complementary to other meteorological techniques such as weather radars and microwave radiometers. Potential usages of the new technique in real and/or near-real time would provide an exciting opportunity to launch monitoring and warning services that are able to offer vital information for community and decision makers.

A GEOCLIM simulation of climatic and biogeochemical consequences of Pangea breakup

NASA Astrophysics Data System (ADS)

Donnadieu, Y.; GoddéRis, Y.; Pierrehumbert, R.; Dromart, G.; Fluteau, F.; Jacob, R.

2006-11-01

Large fluctuations in continental configuration occur throughout the Mesozoic. While it has long been recognized that paleogeography may potentially influence atmospheric CO2 via the continental silicate weathering feedback, no numerical simulations have been done, because of the lack of a spatially resolved climate-carbon model. GEOCLIM, a coupled numerical model of the climate and global biogeochemical cycles, is used to investigate the consequences of the Pangea breakup. The climate module of the GEOCLIM model is the FOAM atmospheric general circulation model, allowing the calculation of the consumption of atmospheric CO2 through continental silicate weathering with a spatial resolution of 7.5°long × 4.5°lat. Seven time slices have been simulated. We show that the breakup of the Pangea supercontinent triggers an increase in continental runoff, resulting in enhanced atmospheric CO2 consumption through silicate weathering. As a result, atmospheric CO2 falls from values above 3000 ppmv during the Triassic down to rather low levels during the Cretaceous (around 400 ppmv), resulting in a decrease in global mean annual continental temperatures from about 20°C to 10°C. Silicate weathering feedback and paleogeography both act to force the Earth system toward a dry and hot world reaching its optimum over the last 260 Myr during the Middle-Late Triassic. In the super continent case, given the persistent aridity, the model generates high CO2 values to produce very warm continental temperatures. Conversely, in the fragmented case, the runoff becomes the most important contributor to the silicate weathering rate, hence producing a CO2 drawdown and a fall in continental temperatures. Finally, another unexpected outcome is the pronounced fluctuation in carbonate accumulation simulated by the model in response to the Pangea breakup. These fluctuations are driven by changes in continental carbonate weathering flux. Accounting for the fluctuations in area available for carbonate platforms, the simulated ratio of carbonate deposition between neritic and deep sea environments is in better agreement with available data.

Benefits Analysis of Multi-Center Dynamic Weather Routes

NASA Technical Reports Server (NTRS)

Sheth, Kapil; McNally, David; Morando, Alexander; Clymer, Alexis; Lock, Jennifer; Petersen, Julien

2014-01-01

Dynamic weather routes are flight plan corrections that can provide airborne flights more than user-specified minutes of flying-time savings, compared to their current flight plan. These routes are computed from the aircraft's current location to a flight plan fix downstream (within a predefined limit region), while avoiding forecasted convective weather regions. The Dynamic Weather Routes automation has been continuously running with live air traffic data for a field evaluation at the American Airlines Integrated Operations Center in Fort Worth, TX since July 31, 2012, where flights within the Fort Worth Air Route Traffic Control Center are evaluated for time savings. This paper extends the methodology to all Centers in United States and presents benefits analysis of Dynamic Weather Routes automation, if it was implemented in multiple airspace Centers individually and concurrently. The current computation of dynamic weather routes requires a limit rectangle so that a downstream capture fix can be selected, preventing very large route changes spanning several Centers. In this paper, first, a method of computing a limit polygon (as opposed to a rectangle used for Fort Worth Center) is described for each of the 20 Centers in the National Airspace System. The Future ATM Concepts Evaluation Tool, a nationwide simulation and analysis tool, is used for this purpose. After a comparison of results with the Center-based Dynamic Weather Routes automation in Fort Worth Center, results are presented for 11 Centers in the contiguous United States. These Centers are generally most impacted by convective weather. A breakdown of individual Center and airline savings is presented and the results indicate an overall average savings of about 10 minutes of flying time are obtained per flight.

ECOLES: a Citizen Observers network engaging communities to map climate change at the local level

NASA Astrophysics Data System (ADS)

Thejll, Peter; Walker, Nicholas; Sandholt, Inge; Brown, Ian; Solberg, Rune; Suwala, Jason; Kelly, Richard; Tangen, Helge; Berglund, Robin; Dean, Andy; Engset, Rune; Siewertsen, Bjarne

2016-04-01

Engaging people in environmental studies is an important way to bring across awareness of expected future climate changes, and also a way to measure environmental change in ways that are better or complementary to remote sensing methods. With a hands-on approach, people are more likely to embrace the idea that climate change is occurring, and with modern technologies it is possible to collect quite stunning amounts of relevant data. We suggest several national activities tailored to conditions in each of the participating countries and also to existing national CO-projects. The project focuses on gathering data on biological changes, on weather, and on snow-pack information in Nordic countries as well as Greenland and Canada. Data will be gathered with existing equipment (mobile phones and internet-connected weather stations) and the project provides the means for collation of data into a database for dissemination and quality control. Numerical data collected by small non-professional weather stations or mobile phones with sensors are not directly useful quantitatively for e.g. numerical weather prediction without validation of data quality, but with validation there is a huge untapped potential due to the number of observers. Students are a central part of the project, which also seeks to engage people out and about in nature, and people with their own weather stations or other environmental data-collection activities, as well as passive data collection from mobile phone data sensors in people's bags and pockets. Appropriate software, educational and training materials will be designed with end-users in mind; school-age materials will be produced in the appropriate languages (e.g. Kalaallisut for COs of school age in Greenland).

Evaluation of numerical weather predictions performed in the context of the project DAPHNE

NASA Astrophysics Data System (ADS)

Tegoulias, Ioannis; Pytharoulis, Ioannis; Bampzelis, Dimitris; Karacostas, Theodore

2014-05-01

The region of Thessaly in central Greece is one of the main areas of agricultural production in Greece. Severe weather phenomena affect the agricultural production in this region with adverse effects for farmers and the national economy. For this reason the project DAPHNE aims at tackling the problem of drought by means of weather modification through the development of the necessary tools to support the application of a rainfall enhancement program. In the present study the numerical weather prediction system WRF-ARW is used, in order to assess its ability to represent extreme weather phenomena in the region of Thessaly. WRF is integrated in three domains covering Europe, Eastern Mediterranean and Central-Northern Greece (Thessaly and a large part of Macedonia) using telescoping nesting with grid spacing of 15km, 5km and 1.667km, respectively. The cases examined span throughout the transitional and warm period (April to September) of the years 2008 to 2013, including days with thunderstorm activity. Model results are evaluated against all available surface observations and radar products, taking into account the spatial characteristics and intensity of the storms. Preliminary results indicate a good level of agreement between the simulated and observed fields as far as the standard parameters (such as temperature, humidity and precipitation) are concerned. Moreover, the model generally exhibits a potential to represent the occurrence of the convective activity, but not its exact spatiotemporal characteristics. Acknowledgements This research work has been co-financed by the European Union (European Regional Development Fund) and Greek national funds, through the action "COOPERATION 2011: Partnerships of Production and Research Institutions in Focused Research and Technology Sectors" (contract number 11SYN_8_1088 - DAPHNE) in the framework of the operational programme "Competitiveness and Entrepreneurship" and Regions in Transition (OPC II, NSRF 2007-2013)

Impact of bacterial ice nucleating particles on weather predicted by a numerical weather prediction model

NASA Astrophysics Data System (ADS)

Sahyoun, Maher; Korsholm, Ulrik S.; Sørensen, Jens H.; Šantl-Temkiv, Tina; Finster, Kai; Gosewinkel, Ulrich; Nielsen, Niels W.

2017-12-01

Bacterial ice-nucleating particles (INP) have the ability to facilitate ice nucleation from super-cooled cloud droplets at temperatures just below the melting point. Bacterial INP have been detected in cloud water, precipitation, and dry air, hence they may have an impact on weather and climate. In modeling studies, the potential impact of bacteria on ice nucleation and precipitation formation on global scale is still uncertain due to their small concentration compared to other types of INP, i.e. dust. Those earlier studies did not account for the yet undetected high concentration of nanoscale fragments of bacterial INP, which may be found free or attached to soil dust in the atmosphere. In this study, we investigate the sensitivity of modeled cloud ice, precipitation and global solar radiation in different weather scenarios to changes in the fraction of cloud droplets containing bacterial INP, regardless of their size. For this purpose, a module that calculates the probability of ice nucleation as a function of ice nucleation rate and bacterial INP fraction was developed and implemented in a numerical weather prediction model. The threshold value for the fraction of cloud droplets containing bacterial INP needed to produce a 1% increase in cloud ice was determined at 10-5 to 10-4. We also found that increasing this fraction causes a perturbation in the forecast, leading to significant differences in cloud ice and smaller differences in convective and total precipitation and in net solar radiation reaching the surface. These effects were most pronounced in local convective events. Our results show that bacterial INP can be considered as a trigger factor for precipitation, but not an enhancement factor.

Impact of grain size and rock composition on simulated rock weathering

NASA Astrophysics Data System (ADS)

Israeli, Yoni; Emmanuel, Simon

2018-05-01

Both chemical and mechanical processes act together to control the weathering rate of rocks. In rocks with micrometer size grains, enhanced dissolution at grain boundaries has been observed to cause the mechanical detachment of particles. However, it remains unclear how important this effect is in rocks with larger grains, and how the overall weathering rate is influenced by the proportion of high- and low-reactivity mineral phases. Here, we use a numerical model to assess the effect of grain size on chemical weathering and chemo-mechanical grain detachment. Our model shows that as grain size increases, the weathering rate initially decreases; however, beyond a critical size no significant decrease in the rate is observed. This transition occurs when the density of reactive boundaries is less than ˜ 20 % of the entire domain. In addition, we examined the weathering rates of rocks containing different proportions of high- and low-reactivity minerals. We found that as the proportion of low-reactivity minerals increases, the weathering rate decreases nonlinearly. These simulations indicate that for all compositions, grain detachment contributes more than 36 % to the overall weathering rate, with a maximum of ˜ 50 % when high- and low-reactivity minerals are equally abundant in the rock. This occurs because selective dissolution of the high-reactivity minerals creates large clusters of low-reactivity minerals, which then become detached. Our results demonstrate that the balance between chemical and mechanical processes can create complex and nonlinear relationships between the weathering rate and lithology.

The Geostationary Lightning Mapper (GLM) for the GOES-R Series Next Generation Operational Environmental Satellite Constellation

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, Richard; Koshak, William; Petersen, Walter; Carey, Larry; Mach, Douglas; Buechler, Dennis; Bateman, Monte; McCaul, Eugene; Bruning, Eric;

Near Real Time MISR Wind Observations for Numerical Weather Prediction

NASA Astrophysics Data System (ADS)

Mueller, K. J.; Protack, S.; Rheingans, B. E.; Hansen, E. G.; Jovanovic, V. M.; Baker, N.; Liu, J.; Val, S.

2014-12-01

The Multi-angle Imaging SpectroRadiometer (MISR) project, in association with the NASA Langley Atmospheric Science Data Center (ASDC), has this year adapted its original production software to generate near-real time (NRT) cloud-motion winds as well as radiance imagery from all nine MISR cameras. These products are made publicly available at the ASDC with a latency of less than 3 hours. Launched aboard the sun-synchronous Terra platform in 1999, the MISR instrument continues to acquire near-global, 275 m resolution, multi-angle imagery. During a single 7 minute overpass of any given area, MISR retrieves the stereoscopic height and horizontal motion of clouds from the multi-angle data, yielding meso-scale near-instantaneous wind vectors. The ongoing 15-year record of MISR height-resolved winds at 17.6 km resolution has been validated against independent data sources. Low-level winds dominate the sampling, and agree to within ±3 ms-1 of collocated GOES and other observations. Low-level wind observations are of particular interest to weather forecasting, where there is a dearth of observations suitable for assimilation, in part due to reliability concerns associated with winds whose heights are assigned by the infrared brightness temperature technique. MISR cloud heights, on the other hand, are generated from stereophotogrammetric pattern matching of visible radiances. MISR winds also address data gaps in the latitude bands between geostationary satellite coverage and polar orbiting instruments that obtain winds from multiple overpasses (e.g. MODIS). Observational impact studies conducted by the Naval Research Laboratory (NRL) and by the German Weather Service (Deutscher Wetterdienst) have both demonstrated forecast improvements when assimilating MISR winds. An impact assessment using the GEOS-5 system is currently in progress. To benefit air quality forecasts, the MISR project is currently investigating the feasibility of generating near-real time aerosol products.

Development of an Objective High Spatial Resolution Soil Moisture Index

NASA Astrophysics Data System (ADS)

Zavodsky, B.; Case, J.; White, K.; Bell, J. R.

2015-12-01

Drought detection, analysis, and mitigation has become a key challenge for a diverse set of decision makers, including but not limited to operational weather forecasters, climatologists, agricultural interests, and water resource management. One tool that is heavily used is the United States Drought Monitor (USDM), which is derived from a complex blend of objective data and subjective analysis on a state-by-state basis using a variety of modeled and observed precipitation, soil moisture, hydrologic, and vegetation and crop health data. The NASA Short-term Prediction Research and Transition (SPoRT) Center currently runs a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework. The LIS-Noah is run at 3-km resolution for local numerical weather prediction (NWP) and situational awareness applications at select NOAA/National Weather Service (NWS) forecast offices over the Continental U.S. (CONUS). To enhance the practicality of the LIS-Noah output for drought monitoring and assessing flood potential, a 30+-year soil moisture climatology has been developed in an attempt to place near real-time soil moisture values in historical context at county- and/or watershed-scale resolutions. This LIS-Noah soil moisture climatology and accompanying anomalies is intended to complement the current suite of operational products, such as the North American Land Data Assimilation System phase 2 (NLDAS-2), which are generated on a coarser-resolution grid that may not capture localized, yet important soil moisture features. Daily soil moisture histograms are used to identify the real-time soil moisture percentiles at each grid point according to the county or watershed in which the grid point resides. Spatial plots are then produced that map the percentiles as proxies to the different USDM categories. This presentation will highlight recent developments of this gridded, objective soil moisture index, comparison to subjective analyses, and application examples.

Communicating weather forecast uncertainty: Do individual differences matter?

PubMed

Grounds, Margaret A; Joslyn, Susan L

2018-03-01

Research suggests that people make better weather-related decisions when they are given numeric probabilities for critical outcomes (Joslyn & Leclerc, 2012, 2013). However, it is unclear whether all users can take advantage of probabilistic forecasts to the same extent. The research reported here assessed key cognitive and demographic factors to determine their relationship to the use of probabilistic forecasts to improve decision quality. In two studies, participants decided between spending resources to prevent icy conditions on roadways or risk a larger penalty when freezing temperatures occurred. Several forecast formats were tested, including a control condition with the night-time low temperature alone and experimental conditions that also included the probability of freezing and advice based on expected value. All but those with extremely low numeracy scores made better decisions with probabilistic forecasts. Importantly, no groups made worse decisions when probabilities were included. Moreover, numeracy was the best predictor of decision quality, regardless of forecast format, suggesting that the advantage may extend beyond understanding the forecast to general decision strategy issues. This research adds to a growing body of evidence that numerical uncertainty estimates may be an effective way to communicate weather danger to general public end users. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

4-D Cloud Water Content Fields Derived from Operational Satellite Data

NASA Technical Reports Server (NTRS)

Smith, William L., Jr.; Minnis, Patrick

2010-01-01

In order to improve operational safety and efficiency, the transportation industry, including aviation, has an urgent need for accurate diagnoses and predictions of clouds and associated weather conditions. Adverse weather accounts for 70% of all air traffic delays within the U.S. National Airspace System. The Federal Aviation Administration has determined that as much as two thirds of weather-related delays are potentially avoidable with better weather information and roughly 20% of all aviation accidents are weather related. Thus, it is recognized that an important factor in meeting the goals of the Next Generation Transportation System (NexGen) vision is the improved integration of weather information. The concept of a 4-D weather cube is being developed to address that need by integrating observed and forecasted weather information into a shared 4-D database, providing an integrated and nationally consistent weather picture for a variety of users and to support operational decision support systems. Weather analyses and forecasts derived using Numerical Weather Prediction (NWP) models are a critical tool that forecasters rely on for guidance and also an important element in current and future decision support systems. For example, the Rapid Update Cycle (RUC) and the recently implemented Rapid Refresh (RR) Weather Research and Forecast (WRF) models provide high frequency forecasts and are key elements of the FAA Aviation Weather Research Program. Because clouds play a crucial role in the dynamics and thermodynamics of the atmosphere, they must be adequately accounted for in NWP models. The RUC, for example, cycles at full resolution five cloud microphysical species (cloud water, cloud ice, rain, snow, and graupel) and has the capability of updating these fields from observations. In order to improve the models initial state and subsequent forecasts, cloud top altitude (or temperature, T(sub c)) derived from operational satellite data, surface observations of cloud base altitude, radar reflectivity, and lightning data are used to help build and remove clouds in the models assimilation system. Despite this advance and the many recent advances made in our understanding of cloud physical processes and radiative effects, many problems remain in adequately representing clouds in models. While the assimilation of cloud top information derived from operational satellite data has merit, other information is available that has not yet been exploited. For example, the vertically integrated cloud water content (CWC) or cloud water path (CWP) and cloud geometric thickness (delta Z) are standard products being derived routinely from operational satellite data. These and other cloud products have been validated under a variety of conditions. Since the uncertainties have generally been found to be less than those found in model analyses and forecasts, the satellite products should be suitable for data assimilation, provided an appropriate strategy can be developed that links the satellite-derived cloud parameters with cloud parameters specified in the model. In this paper, we briefly outline such a strategy and describe a methodology to retrieve cloud water content profiles from operational satellite data. Initial results and future plans are presented. It is expected that the direct assimilation of this new product will provide the most accurate depiction of the vertical distribution of cloud water ever produced at the high spatial and temporal resolution needed for short term weather analyses and forecasts.

Parler de la pluie et du beau temps en classe de langue (Talking About Rain and Good Weather in Language Class).

ERIC Educational Resources Information Center

Viallon, Virginie; Jamet, Claude

1996-01-01

Use of television weather broadcasts is recommended for instruction in both French language and culture. Class activities can focus on geography, comprehension of meteorological terminology, or predicting the weather in different areas based on current charts. Some exercises are suggested. (MSE)

Constructing Data Albums for Significant Severe Weather Events

NASA Technical Reports Server (NTRS)

Greene, Ethan; Zavodsky, Bradley; Ramachandran, Rahul; Kulkarni, Ajinkya; Li, Xiang; Bakare, Rohan; Basyal, Sabin; Conover, Helen

2014-01-01

Data Albums provide a one-stop-shop combining datasets from NASA, NWS, online new sources, and social media. Data Albums will help meteorologists better understand severe weather events to improve predictive models. Developed a new ontology for severe weather based off current hurricane Data Album and selected relevant NASA datasets for inclusion.

A Framework to Understand Extreme Space Weather Event Probability.

PubMed

Jonas, Seth; Fronczyk, Kassandra; Pratt, Lucas M

2018-03-12

An extreme space weather event has the potential to disrupt or damage infrastructure systems and technologies that many societies rely on for economic and social well-being. Space weather events occur regularly, but extreme events are less frequent, with a small number of historical examples over the last 160 years. During the past decade, published works have (1) examined the physical characteristics of the extreme historical events and (2) discussed the probability or return rate of select extreme geomagnetic disturbances, including the 1859 Carrington event. Here we present initial findings on a unified framework approach to visualize space weather event probability, using a Bayesian model average, in the context of historical extreme events. We present disturbance storm time (Dst) probability (a proxy for geomagnetic disturbance intensity) across multiple return periods and discuss parameters of interest to policymakers and planners in the context of past extreme space weather events. We discuss the current state of these analyses, their utility to policymakers and planners, the current limitations when compared to other hazards, and several gaps that need to be filled to enhance space weather risk assessments. © 2018 Society for Risk Analysis.

Stochastic Parameterization: Toward a New View of Weather and Climate Models

DOE PAGES

Berner, Judith; Achatz, Ulrich; Batté, Lauriane; ...

2017-03-31

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less

Aerosols and their Impact on Radiation, Clouds, Precipitation & Severe Weather Events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Zhanqing; Rosenfeld, Daniel; Fan, Jiwen

Aerosols, the tiny particles suspended in the atmosphere, have been in the forefront of environmental and climate change sciences as the primary atmospheric pollutant and external force affecting Earth’s weather and climate. There are two dominant mechanisms by which aerosols affect weather and climate: aerosol-radiation interactions (ARI) and aerosol-cloud interactions (ACI). ARI arises from aerosol scattering and absorption, which alters the radiation budgets of the atmosphere and surface, while ACI is rooted to the fact that aerosols serve as cloud condensation nuclei and ice nuclei. Both ARI and ACI are coupled with atmospheric dynamics to produce a chain of complexmore » interactions with a large range of meteorological variables that influence both weather and climate. Elaborated here are the impacts of aerosols on the radiation budget, clouds (microphysics, structure, and lifetime), precipitation, and severe weather events (lightning, thunderstorms, hail, and tornados). Depending on environmental variables and aerosol properties, the effects can be both positive and negative, posing the largest uncertainties in the external forcing of the climate system. This has considerably hindered our ability in projecting future climate changes and in doing accurate numerical weather predictions.« less

Stochastic Parameterization: Toward a New View of Weather and Climate Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berner, Judith; Achatz, Ulrich; Batté, Lauriane

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less

Evaluation of downscaled, gridded climate data for the conterminous United States

USGS Publications Warehouse

Robert J. Behnke,; Stephen J. Vavrus,; Andrew Allstadt,; Thomas P. Albright,; Thogmartin, Wayne E.; Volker C. Radeloff,

2016-01-01

Weather and climate affect many ecological processes, making spatially continuous yet fine-resolution weather data desirable for ecological research and predictions. Numerous downscaled weather data sets exist, but little attempt has been made to evaluate them systematically. Here we address this shortcoming by focusing on four major questions: (1) How accurate are downscaled, gridded climate data sets in terms of temperature and precipitation estimates?, (2) Are there significant regional differences in accuracy among data sets?, (3) How accurate are their mean values compared with extremes?, and (4) Does their accuracy depend on spatial resolution? We compared eight widely used downscaled data sets that provide gridded daily weather data for recent decades across the United States. We found considerable differences among data sets and between downscaled and weather station data. Temperature is represented more accurately than precipitation, and climate averages are more accurate than weather extremes. The data set exhibiting the best agreement with station data varies among ecoregions. Surprisingly, the accuracy of the data sets does not depend on spatial resolution. Although some inherent differences among data sets and weather station data are to be expected, our findings highlight how much different interpolation methods affect downscaled weather data, even for local comparisons with nearby weather stations located inside a grid cell. More broadly, our results highlight the need for careful consideration among different available data sets in terms of which variables they describe best, where they perform best, and their resolution, when selecting a downscaled weather data set for a given ecological application.

Evaluating aerosol impacts on Numerical Weather Prediction in two extreme dust and biomass-burning events

NASA Astrophysics Data System (ADS)

Remy, Samuel; Benedetti, Angela; Jones, Luke; Razinger, Miha; Haiden, Thomas

2014-05-01

The WMO-sponsored Working Group on Numerical Experimentation (WGNE) set up a project aimed at understanding the importance of aerosols for numerical weather prediction (NWP). Three cases are being investigated by several NWP centres with aerosol capabilities: a severe dust case that affected Southern Europe in April 2012, a biomass burning case in South America in September 2012, and an extreme pollution event in Beijing (China) which took place in January 2013. At ECMWF these cases are being studied using the MACC-II system with radiatively interactive aerosols. Some preliminary results related to the dust and the fire event will be presented here. A preliminary verification of the impact of the aerosol-radiation direct interaction on surface meteorological parameters such as 2m Temperature and surface winds over the region of interest will be presented. Aerosol optical depth (AOD) verification using AERONET data will also be discussed. For the biomass burning case, the impact of using injection heights estimated by a Plume Rise Model (PRM) for the biomass burning emissions will be presented.

Urban pluvial flood prediction: a case study evaluating radar rainfall nowcasts and numerical weather prediction models as model inputs.

PubMed

Thorndahl, Søren; Nielsen, Jesper Ellerbæk; Jensen, David Getreuer

2016-12-01

Flooding produced by high-intensive local rainfall and drainage system capacity exceedance can have severe impacts in cities. In order to prepare cities for these types of flood events - especially in the future climate - it is valuable to be able to simulate these events numerically, both historically and in real-time. There is a rather untested potential in real-time prediction of urban floods. In this paper, radar data observations with different spatial and temporal resolution, radar nowcasts of 0-2 h leadtime, and numerical weather models with leadtimes up to 24 h are used as inputs to an integrated flood and drainage systems model in order to investigate the relative difference between different inputs in predicting future floods. The system is tested on the small town of Lystrup in Denmark, which was flooded in 2012 and 2014. Results show it is possible to generate detailed flood maps in real-time with high resolution radar rainfall data, but rather limited forecast performance in predicting floods with leadtimes more than half an hour.

National Weather Service

Science.gov Websites

Forecast and Warning Services of the National Weather Service Introduction Quantitative precipitation future which is an active area of research currently. 2) Evaluate HPN performance for forecast periods

Spacebuoy: A University Nanosat Space Weather Mission (III)

DTIC Science & Technology

2013-10-11

ionospheric forecasting models; specifically the operational Global Assimilation of Ionospheric Measurements (GAIM) model currently used by the Air Force... ionospheric forecasting models; specifically the operational Global Assimilation of Ionospheric Measurements (GAIM) model currently used by the Air...Mission Objectives • Provide critical space weather data for use in ionospheric forecasting efforts, particularly assimilated data used in the GAIM

MetEd Learning Resources from COMET: Assisting With User Readiness for the JPSS Era

NASA Astrophysics Data System (ADS)

Bol, A.; Page, E. M.; Dills, P. N.; Lee, T.; Weingroff, M.; Stevermer, A.

2017-12-01

The COMET® Program (www.comet.ucar.edu) is funded by NOAA NESDIS as well as EUMETSAT and the Meteorological Service of Canada to develop and deliver education and training in satellite meteorology. COMET's self-paced online training resources are freely available 24/7/365 via the MetEd Website (meted.ucar.edu) to help learners stay current regarding new instruments, capabilities, products and applications. Experts from NOAA-NESDIS and its Cooperative Institutes, the Meteorological Service of Canada, EUMETSAT, the Naval Research Laboratory and others, work with COMET staff to create lessons that encourage greater use of current and future satellite observations and products. As of fall 2017, over 90 satellite-focused, interactive lessons are available in English via the MetEd Web site at http://meted.ucar.edu/topics/satellite. Many of these lessons are also available in Spanish and French, with some Portuguese offerings also available, making learning resources more accessible to a larger international audience. This presentation will focus on COMET's satellite training offerings that are directly applicable to helping users learn more about the capabilities of the S-NPP and JPSS satellite series just in time for JPSS-1 becoming operational. MetEd's educational offerings include lessons on the VIIRS imager and its applications, and a recently updated lesson on nighttime visible observation using the VIIRS Day-Night Band. We'll show how the lessons introduce users to the advances these systems bring to forecasting, numerical weather prediction, and environmental monitoring. We'll also highlight newly developed lessons covering various aspects of JPSS for National Weather Service forecasters, and discuss current and future work.

The Ensemble Space Weather Modeling System (eSWMS): Status, Capabilities and Challenges

NASA Astrophysics Data System (ADS)

Fry, C. D.; Eccles, J. V.; Reich, J. P.

2010-12-01

Marking a milestone in space weather forecasting, the Space Weather Modeling System (SWMS) successfully completed validation testing in advance of operational testing at Air Force Weather Agency’s primary space weather production center. This is the first coupling of stand-alone, physics-based space weather models that are currently in operations at AFWA supporting the warfighter. Significant development effort went into ensuring the component models were portable and scalable while maintaining consistent results across diverse high performance computing platforms. Coupling was accomplished under the Earth System Modeling Framework (ESMF). The coupled space weather models are the Hakamada-Akasofu-Fry version 2 (HAFv2) solar wind model and GAIM1, the ionospheric forecast component of the Global Assimilation of Ionospheric Measurements (GAIM) model. The SWMS was developed by team members from AFWA, Explorations Physics International, Inc. (EXPI) and Space Environment Corporation (SEC). The successful development of the SWMS provides new capabilities beyond enabling extended lead-time, data-driven ionospheric forecasts. These include ingesting diverse data sets at higher resolution, incorporating denser computational grids at finer time steps, and performing probability-based ensemble forecasts. Work of the SWMS development team now focuses on implementing the ensemble-based probability forecast capability by feeding multiple scenarios of 5 days of solar wind forecasts to the GAIM1 model based on the variation of the input fields to the HAFv2 model. The ensemble SWMS (eSWMS) will provide the most-likely space weather scenario with uncertainty estimates for important forecast fields. The eSWMS will allow DoD mission planners to consider the effects of space weather on their systems with more advance warning than is currently possible. The payoff is enhanced, tailored support to the warfighter with improved capabilities, such as point-to-point HF propagation forecasts, single-frequency GPS error corrections, and high cadence, high-resolution Space Situational Awareness (SSA) products. We present the current status of eSWMS, its capabilities, limitations and path of transition to operational use.

Meteorological tools in support to the railway security system on the Calabria region

NASA Astrophysics Data System (ADS)

Laviola, Sante; Gabriele, Salvatore; Iovine, Giulio; Baldini, Luca; Chiravalloti, Francesco; Federico, Stefano; Miglietta, Marcello Mario; Milani, Lisa; Procopio, Antonio; Roberto, Nicoletta; Tiesi, Alessandro; Agostino, Mario; Niccoli, Raffaele; Stassi, Sergio; Rago, Valeria

2017-04-01

RAMSES (RAilway Meteorological SEcurity System) is a pilot project co-funded by the Italian Railway Company - RFI S.p.A. and conceived for the mitigation of the hydrological risk along the Calabria railways. RAMSES aims at improving the forecast of very short life-cycle convection systems, responsible of intense and localized rainfalls affecting small catchment areas, which are often underestimated by the numerical weather models and even non-adequately detected by the network of sparse raingauges. The RAMSES operational design is based on a synergistic and integrated architecture, providing a series of information able to identify the most active convective cells and monitoring their evolution in terms of vertical structure, rain intensity and geo-hydrological effects at ground (debris flow, landslides, collapses of bridges, erosion of the ballast). The RAMSES meteorological component is designed to identify and track the short-term evolution (15-60 min) of convective cells, by means of imaging techniques based on dual-polarization weather radar and Meteosat data. In support of this quasi-real time analysis, the numerical model WRF provides the weather forecast at 3-6 hours range by ingesting, through the assimilation system LAPS, the observational data (rain gauges, ground weather stations, radar, satellites) in order to improve the initial condition. Finally, the hydraulic flow modeling is used to assess the ground effects in terms of landslide susceptibility, rainfall-runoff intensity, debris impact on the drainage network and evaluate of risk along the railway track.

A NOAA/SWPC Perspective on Space Weather Forecasts That Fail

NASA Astrophysics Data System (ADS)

Biesecker, D. A.

2014-12-01

The Space Weather Prediction Center (SWPC) at NOAA is the Official US source for space weather watches, warning and alerts. These alerts are provided to a breadth of customers covering a range of industries, including electric utilities, airlines, emergency managers, and users of precision GPS to name a few. This talk will review the current tools used by SWPC to forecast geomagnetic storms, solar flares, and solar energetic particle events and present the SWPC performance in each of these areas. We will include a discussion of the current limitations and examples of events that proved difficult to forecast.

Employing Tropospheric Numerical Weather Prediction Model for High-Precision GNSS Positioning

NASA Astrophysics Data System (ADS)

Alves, Daniele; Gouveia, Tayna; Abreu, Pedro; Magário, Jackes

2014-05-01

In the past few years is increasing the necessity of realizing high accuracy positioning. In this sense, the spatial technologies have being widely used. The GNSS (Global Navigation Satellite System) has revolutionized the geodetic positioning activities. Among the existent methods one can emphasize the Precise Point Positioning (PPP) and network-based positioning. But, to get high accuracy employing these methods, mainly in real time, is indispensable to realize the atmospheric modeling (ionosphere and troposphere) accordingly. Related to troposphere, there are the empirical models (for example Saastamoinen and Hopfield). But when highly accuracy results (error of few centimeters) are desired, maybe these models are not appropriated to the Brazilian reality. In order to minimize this limitation arises the NWP (Numerical Weather Prediction) models. In Brazil the CPTEC/INPE (Center for Weather Prediction and Climate Studies / Brazilian Institute for Spatial Researches) provides a regional NWP model, currently used to produce Zenithal Tropospheric Delay (ZTD) predictions (http://satelite.cptec.inpe.br/zenital/). The actual version, called eta15km model, has a spatial resolution of 15 km and temporal resolution of 3 hours. In this paper the main goal is to accomplish experiments and analysis concerning the use of troposphere NWP model (eta15km model) in PPP and network-based positioning. Concerning PPP it was used data from dozens of stations over the Brazilian territory, including Amazon forest. The results obtained with NWP model were compared with Hopfield one. NWP model presented the best results in all experiments. Related to network-based positioning it was used data from GNSS/SP Network in São Paulo State, Brazil. This network presents the best configuration in the country to realize this kind of positioning. Actually the network is composed by twenty stations (http://www.fct.unesp.br/#!/pesquisa/grupos-de-estudo-e-pesquisa/gege//gnss-sp-network2789/). The results obtained employing NWP model also were compared to Hopfield one, and the results were very interesting. The theoretical concepts, experiments, results and analysis will be presented in this paper.

Acceptance criteria for urban dispersion model evaluation

NASA Astrophysics Data System (ADS)

Hanna, Steven; Chang, Joseph

2012-05-01

The authors suggested acceptance criteria for rural dispersion models' performance measures in this journal in 2004. The current paper suggests modified values of acceptance criteria for urban applications and tests them with tracer data from four urban field experiments. For the arc-maximum concentrations, the fractional bias should have a magnitude <0.67 (i.e., the relative mean bias is less than a factor of 2); the normalized mean-square error should be <6 (i.e., the random scatter is less than about 2.4 times the mean); and the fraction of predictions that are within a factor of two of the observations (FAC2) should be >0.3. For all data paired in space, for which a threshold concentration must always be defined, the normalized absolute difference should be <0.50, when the threshold is three times the instrument's limit of quantification (LOQ). An overall criterion is then applied that the total set of acceptance criteria should be satisfied in at least half of the field experiments. These acceptance criteria are applied to evaluations of the US Department of Defense's Joint Effects Model (JEM) with tracer data from US urban field experiments in Salt Lake City (U2000), Oklahoma City (JU2003), and Manhattan (MSG05 and MID05). JEM includes the SCIPUFF dispersion model with the urban canopy option and the urban dispersion model (UDM) option. In each set of evaluations, three or four likely options are tested for meteorological inputs (e.g., a local building top wind speed, the closest National Weather Service airport observations, or outputs from numerical weather prediction models). It is found that, due to large natural variability in the urban data, there is not a large difference between the performance measures for the two model options and the three or four meteorological input options. The more detailed UDM and the state-of-the-art numerical weather models do provide a slight improvement over the other options. The proposed urban dispersion model acceptance criteria are satisfied at over half of the field experiments.

A Milestone in Commercial Space Weather: USTAR Center for Space Weather

NASA Astrophysics Data System (ADS)

Tobiska, W.; Schunk, R. W.; Sojka, J. J.; Thompson, D. C.; Scherliess, L.; Zhu, L.; Gardner, L. C.

2009-12-01

As of 2009, Utah State University (USU) hosts a new organization to develop commercial space weather applications using funding that has been provided by the State of Utah’s Utah Science Technology and Research (USTAR) initiative. The USTAR Center for Space Weather (UCSW) is located on the USU campus in Logan, Utah and is developing innovative applications for mitigating adverse space weather effects in technological systems. Space weather’s effects upon the near-Earth environment are due to dynamic changes in the Sun’s photons, particles, and fields. Of the space environment domains that are affected by space weather, the ionosphere is the key region that affects communication and navigation systems. The UCSW has developed products for users of systems that are affected by space weather-driven ionospheric changes. For example, on September 1, 2009 USCW released, in conjunction with Space Environment Technologies, the world’s first real-time space weather via an iPhone app. Space WX displays the real-time, current global ionosphere total electron content along with its space weather drivers; it is available through the Apple iTunes store and is used around the planet. The Global Assimilation of Ionospheric Measurements (GAIM) system is now being run operationally in real-time at UCSW with the continuous ingestion of hundreds of global data streams to dramatically improve the ionosphere’s characterization. We discuss not only funding and technical advances that have led to current products but also describe the direction for UCSW that includes partnering opportunities for moving commercial space weather into fully automated specification and forecasting over the next half decade.

A Case Study of the Impact of AIRS Temperature Retrievals on Numerical Weather Prediction

NASA Technical Reports Server (NTRS)

Reale, O.; Atlas, R.; Jusem, J. C.

2004-01-01

Large errors in numerical weather prediction are often associated with explosive cyclogenesis. Most studes focus on the under-forecasting error, i.e. cases of rapidly developing cyclones which are poorly predicted in numerical models. However, the over-forecasting error (i.e., to predict an explosively developing cyclone which does not occur in reality) is a very common error that severely impacts the forecasting skill of all models and may also present economic costs if associated with operational forecasting. Unnecessary precautions taken by marine activities can result in severe economic loss. Moreover, frequent occurrence of over-forecasting can undermine the reliance on operational weather forecasting. Therefore, it is important to understand and reduce the prdctions of extreme weather associated with explosive cyclones which do not actually develop. In this study we choose a very prominent case of over-forecasting error in the northwestern Pacific. A 960 hPa cyclone develops in less than 24 hour in the 5-day forecast, with a deepening rate of about 30 hPa in one day. The cyclone is not versed in the analyses and is thus a case of severe over-forecasting. By assimilating AIRS data, the error is largely eliminated. By following the propagation of the anomaly that generates the spurious cyclone, it is found that a small mid-tropospheric geopotential height negative anomaly over the northern part of the Indian subcontinent in the initial conditions, propagates westward, is amplified by orography, and generates a very intense jet streak in the subtropical jet stream, with consequent explosive cyclogenesis over the Pacific. The AIRS assimilation eliminates this anomaly that may have been caused by erroneous upper-air data, and represents the jet stream more correctly. The energy associated with the jet is distributed over a much broader area and as a consequence a multiple, but much more moderate cyclogenesis is observed.

Applied environmental fluid mechanics: what's the weather in your backyard?

NASA Astrophysics Data System (ADS)

Chow, F. K.

2011-12-01

The microclimates of the San Francisco Bay Area can lead to 30-40F differences in temperature from the coast to just 30 miles inland. The reasons for this include local topography which affects development of the atmospheric boundary layer. A Bay Area resident's experience of fog, air pollution, and weather events therefore differs greatly depending on exactly where they live. Such local weather phenomena provide a natural topic for introduction to boundary layer processes and are the basis of a new course developed at the University of California, Berkeley. This course complements the PI's research focus on numerical methods applied to atmospheric boundary layer flow over complex terrain. This new outreach and research-based course was created to teach students about the boundary layer and teach them how to use a community weather prediction model, WRF, to simulate conditions in the local area, while at the same time being actively involved in public outreach. The course was offered in the Civil and Environmental Engineering department with the collaboration and support of the Lawrence Hall of Science, Berkeley's public science museum. The students chose topics such as air quality, wind energy, climate change, and plume dispersion, all applied to the local San Francisco Bay Area. The students conducted independent research on their team projects, involving literature reviews, numerical model setup, and analysis of model results through comparison with field observations. The outreach component of the course included website design and culminated in demonstrations at the Lawrence Hall of Science. The seven student teams presented hands-on demos to 300-400 visitors, mostly kids 4-9 years old and their parents. Involving students directly in outreach efforts is hoped to encourage continued integration of research and education in their own careers. Early exposure to numerical modeling also improves student technical skills for future career experiences . Given positive feedback from students, the course will now be offered regularly as a senior design class which will also fulfill engineering graduation requirements.

Toward a Concept of Operations for Aviation Weather Information Implementation in the Evolving National Airspace System

NASA Technical Reports Server (NTRS)

McAdaragh, Raymon M.

2002-01-01

The capacity of the National Airspace System is being stressed due to the limits of current technologies. Because of this, the FAA and NASA are working to develop new technologies to increase the system's capacity which enhancing safety. Adverse weather has been determined to be a major factor in aircraft accidents and fatalities and the FAA and NASA have developed programs to improve aviation weather information technologies and communications for system users The Aviation Weather Information Element of the Weather Accident Prevention Project of NASA's Aviation Safety Program is currently working to develop these technologies in coordination with the FAA and industry. This paper sets forth a theoretical approach to implement these new technologies while addressing the National Airspace System (NAS) as an evolving system with Weather Information as one of its subSystems. With this approach in place, system users will be able to acquire the type of weather information that is needed based upon the type of decision-making situation and condition that is encountered. The theoretical approach addressed in this paper takes the form of a model for weather information implementation. This model addresses the use of weather information in three decision-making situations, based upon the system user's operational perspective. The model also addresses two decision-making conditions, which are based upon the need for collaboration due to the level of support offered by the weather information provided by each new product or technology. The model is proposed for use in weather information implementation in order to provide a systems approach to the NAS. Enhancements to the NAS collaborative decision-making capabilities are also suggested.

Weather and seasonal climate prediction for South America using a multi-model superensemble

NASA Astrophysics Data System (ADS)

Chaves, Rosane R.; Ross, Robert S.; Krishnamurti, T. N.

2005-11-01

This work examines the feasibility of weather and seasonal climate predictions for South America using the multi-model synthetic superensemble approach for climate, and the multi-model conventional superensemble approach for numerical weather prediction, both developed at Florida State University (FSU). The effect on seasonal climate forecasts of the number of models used in the synthetic superensemble is investigated. It is shown that the synthetic superensemble approach for climate and the conventional superensemble approach for numerical weather prediction can reduce the errors over South America in seasonal climate prediction and numerical weather prediction.For climate prediction, a suite of 13 models is used. The forecast lead-time is 1 month for the climate forecasts, which consist of precipitation and surface temperature forecasts. The multi-model ensemble is comprised of four versions of the FSU-Coupled Ocean-Atmosphere Model, seven models from the Development of a European Multi-model Ensemble System for Seasonal to Interannual Prediction (DEMETER), a version of the Community Climate Model (CCM3), and a version of the predictive Ocean Atmosphere Model for Australia (POAMA). The results show that conditions over South America are appropriately simulated by the Florida State University Synthetic Superensemble (FSUSSE) in comparison to observations and that the skill of this approach increases with the use of additional models in the ensemble. When compared to observations, the forecasts are generally better than those from both a single climate model and the multi-model ensemble mean, for the variables tested in this study.For numerical weather prediction, the conventional Florida State University Superensemble (FSUSE) is used to predict the mass and motion fields over South America. Predictions of mean sea level pressure, 500 hPa geopotential height, and 850 hPa wind are made with a multi-model superensemble comprised of six global models for the period January, February, and December of 2000. The six global models are from the following forecast centers: FSU, Bureau of Meteorology Research Center (BMRC), Japan Meteorological Agency (JMA), National Centers for Environmental Prediction (NCEP), Naval Research Laboratory (NRL), and Recherche en Prevision Numerique (RPN). Predictions of precipitation are made for the period January, February, and December of 2001 with a multi-analysis-multi-model superensemble where, in addition to the six forecast models just mentioned, five additional versions of the FSU model are used in the ensemble, each with a different initialization (analysis) based on different physical initialization procedures. On the basis of observations, the results show that the FSUSE provides the best forecasts of the mass and motion field variables to forecast day 5, when compared to both the models comprising the ensemble and the multi-model ensemble mean during the wet season of December-February over South America. Individual case studies show that the FSUSE provides excellent predictions of rainfall for particular synoptic events to forecast day 3. Copyright

Numerical simulations of an advection fog event over Shanghai Pudong International Airport with the WRF model

NASA Astrophysics Data System (ADS)

Lin, Caiyan; Zhang, Zhongfeng; Pu, Zhaoxia; Wang, Fengyun

2017-10-01

A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advection fog event over Shanghai Pudong International Airport (ZSPD) with the Weather Research and Forecasting (WRF) model. Using the current operational settings at the Meteorological Center of East China Air Traffic Management Bureau, the WRF model successfully predicts the fog event at ZSPD. Additional numerical experiments are performed to examine the physical processes associated with the fog event. The results indicate that prediction of this particular fog event is sensitive to microphysical schemes for the time of fog dissipation but not for the time of fog onset. The simulated timing of the arrival and dissipation of the fog, as well as the cloud distribution, is substantially sensitive to the planetary boundary layer and radiation (both longwave and shortwave) processes. Moreover, varying forecast lead times also produces different simulation results for the fog event regarding its onset and duration, suggesting a trade-off between more accurate initial conditions and a proper forecast lead time that allows model physical processes to spin up adequately during the fog simulation. The overall outcomes from this study imply that the complexity of physical processes and their interactions within the WRF model during fog evolution and dissipation is a key area of future research.

A numerical model for the whole Wadden Sea: results on the hydrodynamics

NASA Astrophysics Data System (ADS)

Gräwe, Ulf; Duran-Matute, Matias; Gerkema, Theo; Flöser, Götz; Burchard, Hans

2015-04-01

A high-resolution baroclinic three-dimensional numerical model for the entire Wadden Sea of the German Bight in the southern North Sea is first validated against field data for surface elevation, current velocity, temperature and salinity at selected stations and then used to calculate fluxes of volume, heat and salt inside the Wadden Sea and the exchange between the Wadden Sea and the adjacent North Sea through the major tidal inlets. The General Estuarine Transport Model (GETM) is simulating the reference years 2009-2011. The numerical grid has a resolution of 200x200m and 30 adaptive vertical layers. It is the final stage of a multi-nested setup, starting from the North Atlantic. The atmospheric forcing is taken from the operational forecast of the German Weather Service. Additionally, the freshwater discharge of 23 local rivers and creeks are included. For validation, we use observations from a ship of opportunity measuring sea surface properties, tidal gauge stations, high frequency of salinity and volume transport estimates for the Mardiep and Spiekeroog inlet. Finally, the estuarine overturning circulation in three tidal gulleys is quantified. Regional differences between the gullies are assessed and drivers of the estuarine circulation are identified. Moreover, we will give a consistent estimate of the tidal prisms for all tidal inlets in the entire Wadden Sea.

Inner Magnetosphere Modeling at the CCMC: Ring Current, Radiation Belt and Magnetic Field Mapping

NASA Astrophysics Data System (ADS)

Rastaetter, L.; Mendoza, A. M.; Chulaki, A.; Kuznetsova, M. M.; Zheng, Y.

2013-12-01

Modeling of the inner magnetosphere has entered center stage with the launch of the Van Allen Probes (RBSP) in 2012. The Community Coordinated Modeling Center (CCMC) has drastically improved its offerings of inner magnetosphere models that cover energetic particles in the Earth's ring current and radiation belts. Models added to the CCMC include the stand-alone Comprehensive Inner Magnetosphere-Ionosphere (CIMI) model by M.C. Fok, the Rice Convection Model (RCM) by R. Wolf and S. Sazykin and numerous versions of the Tsyganenko magnetic field model (T89, T96, T01quiet, TS05). These models join the LANL* model by Y. Yu hat was offered for instant run earlier in the year. In addition to these stand-alone models, the Comprehensive Ring Current Model (CRCM) by M.C. Fok and N. Buzulukova joined as a component of the Space Weather Modeling Framework (SWMF) in the magnetosphere model run-on-request category. We present modeling results of the ring current and radiation belt models and demonstrate tracking of satellites such as RBSP. Calculations using the magnetic field models include mappings to the magnetic equator or to minimum-B positions and the determination of foot points in the ionosphere.

Working Group 1 "Advanced GNSS Processing Techniques" of the COST Action GNSS4SWEC: Overview of main achievements

NASA Astrophysics Data System (ADS)

Douša, Jan; Dick, Galina; Kačmařík, Michal; Václavovic, Pavel; Pottiaux, Eric; Zus, Florian; Brenot, Hugues; Moeller, Gregor; Hinterberger, Fabian; Pacione, Rosa; Stuerze, Andrea; Eben, Kryštof; Teferle, Norman; Ding, Wenwu; Morel, Laurent; Kaplon, Jan; Hordyniec, Pavel; Rohm, Witold

2017-04-01

The COST Action ES1206 GNSS4SWEC addresses new exploitations of the synergy between developments in GNSS and meteorological communities. The Working Group 1 (Advanced GNSS processing techniques) deals with implementing and assessing new methods for GNSS tropospheric monitoring and precise positioning exploiting all modern GNSS constellations, signals, products etc. Besides other goals, WG1 coordinates development of advanced tropospheric products in support of weather numerical and non-numerical nowcasting. These are ultra-fast and high-resolution tropospheric products available in real time or in a sub-hourly fashion and parameters in support of monitoring an anisotropy of the troposphere, e.g. horizontal gradients and tropospheric slant path delays. This talk gives an overview of WG1 activities and, particularly, achievements in two activities, Benchmark and Real-time demonstration campaigns. For the Benchmark campaign a complex data set of GNSS observations and various meteorological data were collected for a two-month period in 2013 (May-June) which included severe weather events in central Europe. An initial processing of data sets from GNSS and numerical weather models (NWM) provided independently estimated reference parameters - ZTDs and tropospheric horizontal gradients. The comparison of horizontal tropospheric gradients from GNSS and NWM data demonstrated a very good agreement among independent solutions with negligible biases and an accuracy of about 0.5 mm. Visual comparisons of maps of zenith wet delays and tropospheric horizontal gradients showed very promising results for future exploitations of advanced GNSS tropospheric products in meteorological applications such as severe weather event monitoring and weather nowcasting. The Benchmark data set is also used for an extensive validation of line-of-sight tropospheric Slant Total Delays (STD) from GNSS, NWM-raytracing and Water Vapour Radiometer (WVR) solutions. Seven institutions delivered their STDs estimated based on GNSS observations processed using different software and strategies. STDs from NWM ray-tracing came from three institutions using four different NWM models. Results show generally a very good mutual agreement among all solutions from all techniques. The influence of adding not cleaned GNSS post-fit residuals, i.e. residuals that still contains non-tropospheric systematic effects such as multipath, to estimated STDs will be presented. The Real-time demonstration campaign aims at enhancing and assessing ultra-fast GNSS tropospheric products for severe weather and NWM nowcasting. Results are showed from real-time demonstrations as well as offline production simulating real-time using Benchmark campaign.

Chemical studies of H chondrites. II - Weathering effects in the Victoria Land, Antarctic population and comparison of two Antarctic populations with non-Antarctic falls

NASA Astrophysics Data System (ADS)

Dennison, J. E.; Lipschutz, M. E.

1987-03-01

The authors report RNAA data for 14 siderophile, lithophile and chalcophile volatile/mobile trace elements in interior portions of 45 different H4-6 chondrites (49 samples) from Victoria Land, Antarctica and 5 H5 chondrites from the Yamato Mts., Antarctica. Relative to H5 chondrites of weathering types A and B, all elements are depleted (10 at statistically significant levels) in extensively weathered (types B/C and C) samples. Chondrites of weathering types A and B seem compositionally uncompromised and as useful as contemporary falls for trace-element studies. When data distributions for these 14 trace elements in non-Antarctic H chondrite falls and unpaired samples from Victoria Land and from the Yamato Mts. (Queen Maud Land) are compared statistically, numerous significant differences are apparent. These and other differences give ample cause to doubt that the various sample populations derive from the same parent population. The observed differences do no reflect weathering, chance or other trivial causes: a preterrestrial source must be responsible.

Mexican Space Weather Service (SCIESMEX)

NASA Astrophysics Data System (ADS)

Gonzalez-Esparza, A.; De la Luz, V.; Mejia-Ambriz, J. C.; Aguilar-Rodriguez, E.; Corona-Romero, P.; Gonzalez, L. X.

2015-12-01

Recent modifications of the Civil Protection Law in Mexico include now specific mentions to space hazards and space weather phenomena. During the last few years, the UN has promoted international cooperation on Space Weather awareness, studies and monitoring. Internal and external conditions motivated the creation of a Space Weather Service in Mexico (SCIESMEX). The SCIESMEX (www.sciesmex.unam.mx) is operated by the Geophysics Institute at the National Autonomous University of Mexico (UNAM). The UNAM has the experience of operating several critical national services, including the National Seismological Service (SSN); besides that has a well established scientific group with expertise in space physics and solar- terrestrial phenomena. The SCIESMEX is also related with the recent creation of the Mexican Space Agency (AEM). The project combines a network of different ground instruments covering solar, interplanetary, geomagnetic, and ionospheric observations. The SCIESMEX has already in operation computing infrastructure running the web application, a virtual observatory and a high performance computing server to run numerical models. SCIESMEX participates in the International Space Environment Services (ISES) and in the Inter-progamme Coordination Team on Space Weather (ICTSW) of the Word Meteorological Organization (WMO).

78 FR 17178 - Fisheries of the Caribbean, Gulf of Mexico, and South Atlantic; Shrimp Fishery Off the Southern...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-20

... waters close as a result of severe winter weather. Amendment 9 would also revise the overfished and... has been severely depleted by cold weather. Based on information from standardized assessments, if a... changes to the current regulatory text within Sec. 622.35(d), ``South Atlantic shrimp cold weather closure...

LAWS (Laser Atmospheric Wind Sounder) earth observing system

NASA Technical Reports Server (NTRS)

1988-01-01

Wind profiles can be measured from space using current technology. These wind profiles are essential for answering many of the interdisciplinary scientific questions to be addressed by EOS, the Earth Observing System. This report provides guidance for the development of a spaceborne wind sounder, the Laser Atmospheric Wind Sounder (LAWS), discussing the current state of the technology and reviewing the scientific rationale for the instrument. Whether obtained globally from the EOS polar platform or in the tropics and subtropics from the Space Station, wind profiles from space will provide essential information for advancing the skill of numerical weather prediction, furthering knowledge of large-scale atmospheric circulation and climate dynamics, and improving understanding of the global biogeochemical and hydrologic cycles. The LAWS Instrument Panel recommends that it be given high priority for new instrument development because of the pressing scientific need and the availability of the necessary technology. LAWS is to measure wind profiles with an accuracy of a few meters per second and to sample at intervals of 100 km horizontally for layers km thick.

Development of the Joint NASA/NCAR General Circulation Model

NASA Technical Reports Server (NTRS)

Lin, S.-J.; Rood, R. B.

1999-01-01

The Data Assimilation Office at NASA/Goddard Space Flight Center is collaborating with NCAR/CGD in an ambitious proposal for the development of a unified climate, numerical weather prediction, and chemistry transport model which is suitable for global data assimilation of the physical and chemical state of the Earth's atmosphere. A prototype model based on the NCAR CCM3 physics and the NASA finite-volume dynamical core has been built. A unique feature of the NASA finite-volume dynamical core is its advanced tracer transport algorithm on the floating Lagrangian control-volume coordinate. The model currently has a highly idealized ozone production/loss chemistry derived from the observed 2D (latitude-height) climatology of the recent decades. Nevertheless, the simulated horizontal wave structure of the total ozone is in good qualitative agreement with the observed (TOMS). Long term climate simulations and NWP experiments have been carried out. Current up to date status and futur! e plan will be discussed in the conference.

Storm Prediction Center Convective Outlooks

Science.gov Websites

Current Watches Meso. Discussions Conv. Outlooks Tstm. Outlooks Fire Wx Outlooks XML logo RSS Feeds E-Mail : Retrieve Outlooks Weather Topics: Watches, Mesoscale Discussions, Outlooks, Fire Weather, All Products

WPC Winter Weather Forecasts

Science.gov Websites

Summaries Heat Index Tropical Products Daily Weather Map GIS Products Current Watches/ Warnings Satellite and Radar Imagery GOES-East Satellite GOES-West Satellite National Radar Product Archive WPC

Single-Column Modeling, GCM Parameterizations and Atmospheric Radiation Measurement Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Somerville, R.C.J.; Iacobellis, S.F.

2005-03-18

Our overall goal is identical to that of the Atmospheric Radiation Measurement (ARM) Program: the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data at all three ARM sites, and the implementation and testing of these parameterizations in global and regional models. To test recently developed prognostic parameterizations based on detailed cloud microphysics, we have first compared single-column model (SCM) output with ARM observations at the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Topical Western Pacific (TWP) sites. We focus on the predicted cloud amounts and on a suite of radiativemore » quantities strongly dependent on clouds, such as downwelling surface shortwave radiation. Our results demonstrate the superiority of parameterizations based on comprehensive treatments of cloud microphysics and cloud-radiative interactions. At the SGP and NSA sites, the SCM results simulate the ARM measurements well and are demonstrably more realistic than typical parameterizations found in conventional operational forecasting models. At the TWP site, the model performance depends strongly on details of the scheme, and the results of our diagnostic tests suggest ways to develop improved parameterizations better suited to simulating cloud-radiation interactions in the tropics generally. These advances have made it possible to take the next step and build on this progress, by incorporating our parameterization schemes in state-of-the-art 3D atmospheric models, and diagnosing and evaluating the results using independent data. Because the improved cloud-radiation results have been obtained largely via implementing detailed and physically comprehensive cloud microphysics, we anticipate that improved predictions of hydrologic cycle components, and hence of precipitation, may also be achievable. We are currently testing the performance of our ARM-based parameterizations in state-of-the--art global and regional models. One fruitful strategy for evaluating advances in parameterizations has turned out to be using short-range numerical weather prediction as a test-bed within which to implement and improve parameterizations for modeling and predicting climate variability. The global models we have used to date are the CAM atmospheric component of the National Center for Atmospheric Research (NCAR) CCSM climate model as well as the National Centers for Environmental Prediction (NCEP) numerical weather prediction model, thus allowing testing in both climate simulation and numerical weather prediction modes. We present detailed results of these tests, demonstrating the sensitivity of model performance to changes in parameterizations.« less

Interactions between tectonics, silicate weathering, and climate explored with carbon cycle modeling

NASA Astrophysics Data System (ADS)

Penman, D. E.; Caves Rugenstein, J. K.; Ibarra, D. E.; Winnick, M.

2017-12-01

Earth's long-term carbon cycle is thought to benefit from a stabilizing negative feedback in the form of CO2 consumption by the chemical weathering of silicate minerals: during periods of elevated atmospheric pCO2, chemical weathering rates increase, thus consuming more atmospheric CO2 and cooling global climate, whereas during periods of low pCO2, weathering rates decrease, allowing buildup of CO2 in the atmosphere and warming. At equilibrium, CO2 consumption by silicate weathering balances volcanic CO2 degassing at a specific atmospheric pCO2 dictated by the relationship between total silicate weathering rate and pCO2: Earth's "weathering curve." We use numerical carbon cycle modeling to demonstrate that the shape and slope of the weathering curve is crucial to understanding proposed tectonic controls on pCO2 and climate. First, the shape of the weathering curve dictates the equilibrium response of the carbon cycle to changes in the rate of background volcanic/solid Earth CO2 degassing, which has been suggested to vary significantly with plate tectonic reorganizations over geologic timescales. Second, we demonstrate that if tectonic events can significantly change the weathering curve, this can act as an effective driver of pCO2 and climate on tectonic timescales by changing the atmospheric pCO2 at which silicate weathering balances a constant volcanic/solid Earth degassing rate. Finally, we review the complex interplay of environmental factors that affect modern weathering rates in the field and highlight how the resulting uncertainty surrounding the shape of Earth's weathering curve significantly hampers our ability to quantitatively predict the response of pCO2 and climate to tectonic forcing, and thus represents a substantial knowledge gap in Earth science. We conclude with strategies for closing this knowledge gap by using precise paleoclimatic reconstructions of intervals with known tectonic forcings.

Historical Time Series of Extreme Convective Weather in Finland

NASA Astrophysics Data System (ADS)

Laurila, T. K.; Mäkelä, A.; Rauhala, J.; Olsson, T.; Jylhä, K.

2016-12-01

Thunderstorms, lightning, tornadoes, downbursts, large hail and heavy precipitation are well-known for their impacts to human life. In the high latitudes as in Finland, these hazardous warm season convective weather events are focused in the summer season, roughly from May to September with peak in the midsummer. The position of Finland between the maritime Atlantic and the continental Asian climate zones makes possible large variability in weather in general which reflects also to the occurrence of severe weather; the hot, moist and extremely unstable air masses sometimes reach Finland and makes possible for the occurrence of extreme and devastating weather events. Compared to lower latitudes, the Finnish climate of severe convection is "moderate" and contains a large year-to-year variation; however, behind the modest annual average is hidden the climate of severe weather events that practically every year cause large economical losses and sometimes even losses of life. Because of the increased vulnerability of our modern society, these episodes have gained recently plenty of interest. During the decades, the Finnish Meteorological Institute (FMI) has collected observations and damage descriptions of severe weather episodes in Finland; thunderstorm days (1887-present), annual number of lightning flashes (1960-present), tornados (1796-present), large hail (1930-present), heavy rainfall (1922-present). The research findings show e.g. that a severe weather event may occur practically anywhere in the country, although in general the probability of occurrence is smaller in the Northern Finland. This study, funded by the Finnish Research Programme on Nuclear Power Plant Safety (SAFIR), combines the individual Finnish severe weather time series' and examines their trends, cross-correlation and correlations with other atmospheric parameters. Furthermore, a numerical weather model (HARMONIE) simulation is performed for a historical severe weather case for analyzing how well the present state-of-the-art models grasp these small-scale weather phenomena. Our results give important background for estimating the Finnish severe weather climate in the future.

Successfully Transitioning Science Research to Space Weather Applications

NASA Technical Reports Server (NTRS)

Spann, James

2012-01-01

The awareness of potentially significant impacts of space weather on spaceand ground ]based technological systems has generated a strong desire in many sectors of government and industry to effectively transform knowledge and understanding of the variable space environment into useful tools and applications for use by those entities responsible for systems that may be vulnerable to space weather impacts. Essentially, effectively transitioning science knowledge to useful applications relevant to space weather has become important. This talk will present proven methodologies that have been demonstrated to be effective, and how in the current environment those can be applied to space weather transition efforts.

Weather data dissemination to aircraft

NASA Technical Reports Server (NTRS)

Mcfarland, Richard H.; Parker, Craig B.

1990-01-01

Documentation exists that shows weather to be responsible for approximately 40 percent of all general aviation accidents with fatalities. Weather data products available on the ground are becoming more sophisticated and greater in number. Although many of these data are critical to aircraft safety, they currently must be transmitted verbally to the aircraft. This process is labor intensive and provides a low rate of information transfer. Consequently, the pilot is often forced to make life-critical decisions based on incomplete and outdated information. Automated transmission of weather data from the ground to the aircraft can provide the aircrew with accurate data in near-real time. The current National Airspace System Plan calls for such an uplink capability to be provided by the Mode S Beacon System data link. Although this system has a very advanced data link capability, it will not be capable of providing adequate weather data to all airspace users in its planned configuration. This paper delineates some of the important weather data uplink system requirements, and describes a system which is capable of meeting these requirements. The proposed system utilizes a run-length coding technique for image data compression and a hybrid phase and amplitude modulation technique for the transmission of both voice and weather data on existing aeronautical Very High Frequency (VHF) voice communication channels.

An Analysis of Numerical Weather Prediction of the Diabatic Rossby Vortex

DTIC Science & Technology

2014-06-01

Forecast SLP Mean and Spread ...............................................................................................148   2.   DRV02 72 Hour...ECMWF Ensemble Forecast SLP Mean and Spread ...............................................................................................149   3...DRV03 72 Hour ECMWF Ensemble Forecast SLP Mean and Spread

Glossary - NOAA's National Weather Service

Science.gov Websites

Organization Search NWS All NOAA Go Local forecast by "City, St" Search by city. Press enter or Text Bulletins By State By Message Type National Forecast Models Numerical Models Statistical Models

ENVIRONMENTAL TECHNOLOGY VERIFICATION (ETV) PROGRAM: WET-WEATHER FLOW/SOURCE WATER PROTECTION

EPA Science Inventory

This paper presents an overview of the Environmental Protection Agency's (EPA) Environmental Technology Verification (ETV) program which was established to overcome the numerous impediments to commercialization experienced by developers of innovative environmental technologies. ...

Impact of a variational objective analysis scheme on a regional area numerical model: The Italian Air Force Weather Service experience

NASA Astrophysics Data System (ADS)

Bonavita, M.; Torrisi, L.

2005-03-01

A new data assimilation system has been designed and implemented at the National Center for Aeronautic Meteorology and Climatology of the Italian Air Force (CNMCA) in order to improve its operational numerical weather prediction capabilities and provide more accurate guidance to operational forecasters. The system, which is undergoing testing before operational use, is based on an “observation space” version of the 3D-VAR method for the objective analysis component, and on the High Resolution Regional Model (HRM) of the Deutscher Wetterdienst (DWD) for the prognostic component. Notable features of the system include a completely parallel (MPI+OMP) implementation of the solution of analysis equations by a preconditioned conjugate gradient descent method; correlation functions in spherical geometry with thermal wind constraint between mass and wind field; derivation of the objective analysis parameters from a statistical analysis of the innovation increments.

Research on regional numerical weather prediction

NASA Technical Reports Server (NTRS)

Kreitzberg, C. W.

1976-01-01

Extension of the predictive power of dynamic weather forecasting to scales below the conventional synoptic or cyclonic scales in the near future is assessed. Lower costs per computation, more powerful computers, and a 100 km mesh over the North American area (with coarser mesh extending beyond it) are noted at present. Doubling the resolution even locally (to 50 km mesh) would entail a 16-fold increase in costs (including vertical resolution and halving the time interval), and constraints on domain size and length of forecast. Boundary conditions would be provided by the surrounding 100 km mesh, and time-varying lateral boundary conditions can be considered to handle moving phenomena. More physical processes to treat, more efficient numerical techniques, and faster computers (improved software and hardware) backing up satellite and radar data could produce further improvements in forecasting in the 1980s. Boundary layer modeling, initialization techniques, and quantitative precipitation forecasting are singled out among key tasks.

Large-eddy simulations of a Salt Lake Valley cold-air pool

NASA Astrophysics Data System (ADS)

Crosman, Erik T.; Horel, John D.

2017-09-01

Persistent cold-air pools are often poorly forecast by mesoscale numerical weather prediction models, in part due to inadequate parameterization of planetary boundary-layer physics in stable atmospheric conditions, and also because of errors in the initialization and treatment of the model surface state. In this study, an improved numerical simulation of the 27-30 January 2011 cold-air pool in Utah's Great Salt Lake Basin is obtained using a large-eddy simulation with more realistic surface state characterization. Compared to a Weather Research and Forecasting model configuration run as a mesoscale model with a planetary boundary-layer scheme where turbulence is highly parameterized, the large-eddy simulation more accurately captured turbulent interactions between the stable boundary-layer and flow aloft. The simulations were also found to be sensitive to variations in the Great Salt Lake temperature and Salt Lake Valley snow cover, illustrating the importance of land surface state in modelling cold-air pools.

The role of sediments stored in valleys in modulating the Quaternary weathering flux variations

NASA Astrophysics Data System (ADS)

Carretier, Sebastien; Goddéris, Yves; Vigier, Nathalie; Maffre, Pierre

2017-04-01

Silicate weathering is known to be central to the regulation of atmospheric CO2. Yet it is unclear how weathering responds to climatic variations. Data sets based on different proxies in sediment cores suggest either negligible Quaternary silicate weathering variations, or more weathering during wet and hot periods, or even the reverse. For example, a recent study based on d7Li in clay of Himalayan river terraces suggests, counter-intuitively, a less intense weathering during hot and wet periods compared to dry periods for the last 40 ka, with no clear physical explanation. We analyse catchment scale weathering signals using the numerical model Cidre, coupling landscape evolution with chemical weathering. Chemical weathering occurs within a regolith, either produced in situ at a rate depending on regolith thickness, temperature and precipitation, or corresponding to a deposit. The chemical flux is calculated from the dissolution of granitoid clasts, first exhumed on the hillslopes and then transported and potentially stocked in the valleys. This approach accounts for part of the stochastic nature of grain weathering within a catchment. We prescribe an uplift to an initial horizontal surface to reach a dynamic equilibrium under a constant climate. Then, we vary the precipitation rate and the temperature, alternating cold and dry periods with hot and wet periods (10 to 400 ka tested). When these variations are applied to an equilibrium mountain covered by a regolith ("transport-limited"), the weathering outlfux and the erosion flux are larger during wet and hot periods. On the contrary, for less weatherable conditions such that the mountain is not covered by regolith ("kinetically-limited"), the weathering is the highest at the beginning of the dry, cold and low erosive periods. This apparent paradox is explained by the temporary accumulation of sediment in the valleys in response to the drought. The hillslopes being striped, these valley deposits constitute the only weathering reservoir, whose large volume compensates for the unfavourable climatic conditions. Such a behaviour explains out-of-phase weathering signals, and suggests that the dominant weathering reservoir goes back and forth between the hillslopes and the valleys during climatic oscillations.

The Impact of Microphysics on Intensity and Structure of Hurricanes and Mesoscale Convective Systems

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Shi, Jainn J.; Jou, Ben Jong-Dao; Lee, Wen-Chau; Lin, Pay-Liam; Chang, Mei-Yu

2007-01-01

During the past decade, both research and operational numerical weather prediction models, e.g. Weather Research and Forecast (WRF) model, have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with a 1-2 km or less horizontal resolutions. WRF is a next-generation mesoscale forecast model and assimilation system that has incorporated modern software framework, advanced dynamics, numeric and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WRF model can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options such as Purdue Lin et al. (1983), WSM 6-class and Thompson microphysics schemes. We have recently implemented three sophisticated cloud microphysics schemes into WRF. The cloud microphysics schemes have been extensively tested and applied for different mesoscale systems in different geographical locations. The performances of these schemes have been compared to those from other WRF microphysics options. We are performing sensitivity tests in using WRF to examine the impact of six different cloud microphysical schemes on precipitation processes associated hurricanes and mesoscale convective systems developed at different geographic locations [Oklahoma (IHOP), Louisiana (Hurricane Katrina), Canada (C3VP - snow events), Washington (fire storm), India (Monsoon), Taiwan (TiMREX - terrain)]. We will determine the microphysical schemes for good simulated convective systems in these geographic locations. We are also performing the inline tracer calculation to comprehend the physical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems.

Atmospheric oscillations comparison on long term tropospheric delay time series derived from ray-tracing and GPS

NASA Astrophysics Data System (ADS)

Nikolaidou, Thalia; Santos, Marcelo

2017-04-01

The caused time delay induced by the atmosphere on the GNSS signals (NAD), depends primarily on the amount of atmosphere the signal traverses till it reaches to the Earth's surface and can exceed t 20 m for low elevation angles (around 3 degrees). For a particular ray i.e. satellite/quasar-antenna link, the delay depends on the atmospheric parameters of total pressure, temperature, and the partial pressure of water vapor. Because of that, numerical weather models (NWM) have already proven beneficial for atmospheric modelling and geodesy. By direct raytracing, inside NWM, the VMF1 and the University of New Brunswick VMF1 (UNB-VMF1) (Urquhart et al. 2011), access the 3D variation of the meteorological parameters that determine the delay thus being the state-the-art mapping functions used today. The raytracing procedure is capable of providing NADs delays for any point on the Earth's surface. In this study we study the impact of regional numerical weather models, with high spatial and temporal resolution, namely 25km and 6h. These models outweigh the currently used NWM by having about 2.6 times better spatial resolution. Raytracing through such NWM, using the independent raytracing algorithm develop at UNB (Nievinski, 2009), we acquire superior quality NADs with regional application. We ray-trace for the International GNSS service (IGS) network stations for a time span of 11 years. Benchmarking against the IGS troposphere product is performed to access the accuracy of our results. A periodicity analysis is conducted to examine the signature of atmospheric oscillations on the NAD time series. In order to recognize the NAD periodicities, we compared our product against the GPS-derived IGS troposphere product. Systematic effects within each single technique are identified and long-term NAD stability is accessed.

Remote Sensing of Supercooled Cloud Layers in Cold Climate Using Ground Based Integrated Sensors System and Comparison with Pilot Reports and model forecasts

NASA Astrophysics Data System (ADS)

Boudala, Faisal; Wu, Di; Gultepe, Ismail; Anderson, Martha; turcotte, marie-france

2017-04-01

In-flight aircraft icing is one of the major weather hazards to aviation . It occurs when an aircraft passes through a cloud layer containing supercooled drops (SD). The SD in contact with the airframe freezes on the surface which degrades the performance of the aircraft.. Prediction of in-flight icing requires accurate prediction of SD sizes, liquid water content (LWC), and temperature. The current numerical weather predicting (NWP) models are not capable of making accurate prediction of SD sizes and associated LWC. Aircraft icing environment is normally studied by flying research aircraft, which is quite expensive. Thus, developing a ground based remote sensing system for detection of supercooled liquid clouds and characterization of their impact on severity of aircraft icing one of the important tasks for improving the NWPs based predictions and validations. In this respect, Environment and Climate Change Canada (ECCC) in cooperation with the Department of National Defense (DND) installed a number of specialized ground based remote sensing platforms and present weather sensors at Cold Lake, Alberta that includes a multi-channel microwave radiometer (MWR), K-band Micro Rain radar (MRR), Ceilometer, Parsivel distrometer and Vaisala PWD22 present weather sensor. In this study, a number of pilot reports confirming icing events and freezing precipitation that occurred at Cold Lake during the 2014-2016 winter periods and associated observation data for the same period are examined. The icing events are also examined using aircraft icing intensity estimated using ice accumulation model which is based on a cylindrical shape approximation of airfoil and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model predicted LWC, median volume diameter and temperature. The results related to vertical atmospheric profiling conditions, surface observations, and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model predictions are given. Preliminary results suggest that remote sensing and present weather sensors based observations of cloud SD regions can be used to describe micro and macro physical characteristics of the icing conditions. The model based icing intensity prediction reasonably agreed with the PIREPs and MWR observations.

Results from Evaluations of Gridded CrIS/ATMS Visualization for Operational Forecasting

NASA Astrophysics Data System (ADS)

Stevens, E.; Zavodsky, B.; Dostalek, J.; Berndt, E.; Hoese, D.; White, K.; Bowlan, M.; Gambacorta, A.; Wheeler, A.; Haisley, C.; Smith, N.

2017-12-01

For forecast challenges which require diagnosis of the three-dimensional atmosphere, current observations, such as radiosondes, may not offer enough information. Satellite data can help fill the spatial and temporal gaps between soundings. In particular, temperature and moisture retrievals from the NOAA-Unique Combined Atmospheric Processing System (NUCAPS), which combines infrared soundings from the Cross-track Infrared Sounder (CrIS) with the Advanced Technology Microwave Sounder (ATMS) to retrieve profiles of temperature and moisture. NUCAPS retrievals are available in a wide swath with approximately 45-km spatial resolution at nadir and a local Equator crossing time of 1:30 A.M./P.M. enabling three-dimensional observations at asynoptic times. This abstract focuses on evaluation of a new visualization for NUCAPS within the operational National Weather Service Advanced Weather Interactive Processing System (AWIPS) decision support system that allows these data to be viewed in gridded horizontal maps or vertical cross sections. Two testbed evaluations have occurred in 2017: a Cold Air Aloft (CAA) evaluation at the Alaska Center Weather Service Unit and a Convective Potential evaluation at the NOAA Hazardous Weather Testbed. For CAA, at high latitudes during the winter months, the air at altitudes used by passenger and cargo aircraft can reach temperatures cold enough (-65°C) to begin to freeze jet fuel, and Gridded NUCAPS visualization was shown to help fill in the spatial and temporal gaps in data-sparse areas across the Alaskan airspace by identifying the 3D spatial extent of cold air features. For convective potential, understanding the vertical distribution of temperature and moisture is also very important for forecasting the potential for convection related to severe weather such as lightning, large hail, and tornadoes. The Gridded NUCAPS visualization was shown to aid forecasters in understanding temperature and moisture characteristics at critical levels for determining cap strength and instability. In both cases, when the products are used in conjunction with numerical output to reinforce confidence in model products or provide an alternative observation if forecasters are not sure the model is properly representing the atmosphere.

WRF Simulation over the Eastern Africa by use of Land Surface Initialization

NASA Astrophysics Data System (ADS)

Sakwa, V. N.; Case, J.; Limaye, A. S.; Zavodsky, B.; Kabuchanga, E. S.; Mungai, J.

2014-12-01

The East Africa region experiences severe weather events associated with hazards of varying magnitude. It receives heavy precipitation which leads to wide spread flooding and lack of sufficient rainfall in some parts results into drought. Cases of flooding and drought are two key forecasting challenges for the Kenya Meteorological Service (KMS). The source of heat and moisture depends on the state of the land surface which interacts with the boundary layer of the atmosphere to produce excessive precipitation or lack of it that leads to severe drought. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface within weakly-sheared environments, such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in numerical weather prediction models. Improved modeling capabilities within the region have the potential to enhance forecast guidance in support of daily operations and high-impact weather over East Africa. KMS currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Non-hydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over Eastern Africa.SPoRT and SERVIR provide land surface initialization datasets and model verification tool. The NASA Land Information System (LIS) provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Model verification is done using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. These MET tools enable KMS to monitor model forecast accuracy in near real time. This study highlights verification results of WRF runs over East Africa using the LIS land surface initialization.

Storm Prediction Center Storm Reports

Science.gov Websites

Current Watches Meso. Discussions Conv. Outlooks Tstm. Outlooks Fire Wx Outlooks XML logo RSS Feeds E-Mail , Mesoscale Discussions, Outlooks, Fire Weather, All Products, Contact Us NOAA / National Weather Service

Snowfall Rate Retrieval Using Passive Microwave Measurements and Its Applications in Weather Forecast and Hydrology

NASA Technical Reports Server (NTRS)

Meng, Huan; Ferraro, Ralph; Kongoli, Cezar; Yan, Banghua; Zavodsky, Bradley; Zhao, Limin; Dong, Jun; Wang, Nai-Yu

2015-01-01

(AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow-on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has also been developed. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. It employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derives the probability of snowfall. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two-stream radiative transfer model. A method adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. The SFR products are being used mainly in two communities: hydrology and weather forecast. Global blended precipitation products traditionally do not include snowfall derived from satellites because such products were not available operationally in the past. The ATMS and AMSU/MHS SFR now provide the winter precipitation information for these blended precipitation products. Weather forecasters mainly rely on radar and station observations for snowfall forecast. The SFR products can fill in gaps where no conventional snowfall data are available to forecasters. The products can also be used to confirm radar and gauge snowfall data and increase forecasters' confidence in their prediction.

Preparing the remote sensing community toward the NPP/NPOESS era

NASA Astrophysics Data System (ADS)

Kuciauskas, A. P.; Lee, T. F.; Turk, F. J.; Richardson, K. A.; Hawkins, J. D.; Kent, J. E.; Miller, S. D.; McWilliams, G.

2008-12-01

Under the auspices of the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Integrated Program Office (IPO), the Naval Research Laboratory in Monterey (NRLMRY) was tasked to develop NexSat, a weather satellite web-based resource, to illustrate future sensing capabilities within the Visible/Infrared Imager Radiometer Suite (VIIRS) sensor onboard the NPOESS Preparatory Project (NPP) and NPOESS era. NexSat acquires and processes data from polar orbiters (AVHRR, MODIS, SeaWiFS, DMSP, and TRMM) that serve as heritage instruments to the VIIRS. Geostationary sensors and numerical weather prediction (NWP) overlays supplement the image products suite, making NexSat a one-stop shop for current and future environmental monitoring. NRLMRY collaborates with the Cooperative Institute for Research in the Atmosphere (CIRA) and the Cooperative Institute for Meteorological Satellite Studies (CIMSS) for product development. Together with the Cooperative Program for Operational Meteorology, Education and Training (COMET®), NRLMRY provides educational outreach to research and development communities as well as to the general public. This paper intends to describe the products within the NexSat webpage and its training resources. The product suite consists of generic and state of the art images. Along with the standard visible, IR, and water vapor products, NexSat also includes dust enhancement, cloud properties, cloud profiling, snow cloud discrimination, volcanic ash plumes, hot spots, aerosol content over land and water. NexSat training resources will be described, including on-line product tutorials, a course module, as well as outreach efforts to the National Weather Service, government agencies, academic institutions, and international organizations.

Hurricane and Monsoon Tracking with Driftsondes

NASA Astrophysics Data System (ADS)

Drobinski, Philippe; Cocquerez, Philippe; Doerenbecher, A.; Hock, Terrence; Lavaysse, C.; Parsons, D.; Redelsperger, J. L.

Tropical cyclones (TCs) are a typical weather threat. The threat can apply to humans, their properties, and activities. Their prediction, particularly their trajectory and intensity, remains difficult. In addition, TCs develop above the tropical oceans where the coverage by in situ observations is poor and within cloud clusters (mesoscale convective systems MCS) that limit the ability of numerical weather prediction (NWP) models to assimilate satellite data [18]. Improved forecast of TCs trajectories is a huge benefit in terms of material costs of evacuations and damage, not being able to quantify saved life.

New Technologies for Weather Accident Prevention

NASA Technical Reports Server (NTRS)

Stough, H. Paul, III; Watson, James F., Jr.; Daniels, Taumi S.; Martzaklis, Konstantinos S.; Jarrell, Michael A.; Bogue, Rodney K.

2005-01-01

Weather is a causal factor in thirty percent of all aviation accidents. Many of these accidents are due to a lack of weather situation awareness by pilots in flight. Improving the strategic and tactical weather information available and its presentation to pilots in flight can enhance weather situation awareness and enable avoidance of adverse conditions. This paper presents technologies for airborne detection, dissemination and display of weather information developed by the National Aeronautics and Space Administration (NASA) in partnership with the Federal Aviation Administration (FAA), National Oceanic and Atmospheric Administration (NOAA), industry and the research community. These technologies, currently in the initial stages of implementation by industry, will provide more precise and timely knowledge of the weather and enable pilots in flight to make decisions that result in safer and more efficient operations.

Utilization of Live Localized Weather Information for Sustainable Agriculture

NASA Astrophysics Data System (ADS)

Anderson, J.; Usher, J.

2010-09-01

Authors: Jim Anderson VP, Global Network and Business Development WeatherBug® Professional Jeremy Usher Managing Director, Europe WeatherBug® Professional Localized, real-time weather information is vital for day-to-day agronomic management of all crops. The challenge for agriculture is twofold in that local and timely weather data is not often available for producers and farmers, and it is not integrated into decision-support tools they require. Many of the traditional sources of weather information are not sufficient for agricultural applications because of the long distances between weather stations, meaning the data is not always applicable for on-farm decision making processes. The second constraint with traditional weather information is the timeliness of the data. Most delivery systems are designed on a one-hour time step, whereas many decisions in agriculture are based on minute-by-minute weather conditions. This is especially true for decisions surrounding chemical and fertilizer application and frost events. This presentation will outline how the creation of an agricultural mesonet (weather network) can enable producers and farmers with live, local weather information from weather stations installed in farm/field locations. The live weather information collected from each weather station is integrated into a web-enabled decision support tool, supporting numerous on-farm agronomic activities such as pest management, or dealing with heavy rainfall and frost events. Agronomic models can be used to assess the potential of disease pressure, enhance the farmer's abilities to time pesticide applications, or assess conditions contributing to yield and quality fluctuations. Farmers and industry stakeholders may also view quality-assured historical weather variables at any location. This serves as a record-management tool for viewing previously uncharted agronomic weather events in graph or table form. This set of weather tools is unique and provides a significant enhancement to the agronomic decision-support process. Direct benefits to growers can take the form of increased yield and grade potential, as well as savings in money and time. Pest management strategies become more efficient due to timely and localized disease and pest modelling, and increased efficacy of pest and weed control. Examples from the Canadian Wheat Board (CWB) WeatherFarm weather network will be utilized to illustrate the processes, decision tools and benefits to producers and farmers.

WPC 48-Hour Surface Weather Forecast

Science.gov Websites

Summaries Heat Index Tropical Products Daily Weather Map GIS Products Current Watches/ Warnings Satellite and Radar Imagery GOES-East Satellite GOES-West Satellite National Radar Product Archive WPC

WPC 12-Hour Surface Weather Forecast

Science.gov Websites

Summaries Heat Index Tropical Products Daily Weather Map GIS Products Current Watches/ Warnings Satellite and Radar Imagery GOES-East Satellite GOES-West Satellite National Radar Product Archive WPC

WPC 36-Hour Surface Weather Forecast

Science.gov Websites

Summaries Heat Index Tropical Products Daily Weather Map GIS Products Current Watches/ Warnings Satellite and Radar Imagery GOES-East Satellite GOES-West Satellite National Radar Product Archive WPC

WPC Excessive Rainfall and Winter Weather Forecasts

Science.gov Websites

Summaries Heat Index Tropical Products Daily Weather Map GIS Products Current Watches/ Warnings Satellite and Radar Imagery GOES-East Satellite GOES-West Satellite National Radar Product Archive WPC

WPC 24-Hour Surface Weather Forecast

Science.gov Websites

Summaries Heat Index Tropical Products Daily Weather Map GIS Products Current Watches/ Warnings Satellite and Radar Imagery GOES-East Satellite GOES-West Satellite National Radar Product Archive WPC

76 FR 409 - Philadelphia International Airport, Capacity Enhancement Program, Environmental Impact Statement...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-04

... in the Philadelphia Metropolitan Area during all weather conditions. This ROD sets forth FAA's final... current and future aviation demand in the Philadelphia Metropolitan Area during all weather conditions...

NOAA MF/HF VOICE - 4125 kHz

Science.gov Websites

current weather conditions in their operating area. All NWS marine forecasts rely heavily on the Voluntary weather conditions in their operating area. Home, Parent Office, Marine, Tropical, and Tsunami Services

Multiple Weather Factors Affect Apparent Survival of European Passerine Birds

PubMed Central

Salewski, Volker; Hochachka, Wesley M.; Fiedler, Wolfgang

2013-01-01

Weather affects the demography of animals and thus climate change will cause local changes in demographic rates. In birds numerous studies have correlated demographic factors with weather but few of those examined variation in the impacts of weather in different seasons and, in the case of migrants, in different regions. Using capture-recapture models we correlated weather with apparent survival of seven passerine bird species with different migration strategies to assess the importance of selected facets of weather throughout the year on apparent survival. Contrary to our expectations weather experienced during the breeding season did not affect apparent survival of the target species. However, measures for winter severity were associated with apparent survival of a resident species, two short-distance/partial migrants and a long-distance migrant. Apparent survival of two short distance migrants as well as two long-distance migrants was further correlated with conditions experienced during the non-breeding season in Spain. Conditions in Africa had statistically significant but relatively minor effects on the apparent survival of the two long-distance migrants but also of a presumably short-distance migrant and a short-distance/partial migrant. In general several weather effects independently explained similar amounts of variation in apparent survival for the majority of species and single factors explained only relatively low amounts of temporal variation of apparent survival. Although the directions of the effects on apparent survival mostly met our expectations and there are clear predictions for effects of future climate we caution against simple extrapolations of present conditions to predict future population dynamics. Not only did weather explains limited amounts of variation in apparent survival, but future demographics will likely be affected by changing interspecific interactions, opposing effects of weather in different seasons, and the potential for phenotypic and microevolutionary adaptations. PMID:23593131

An Overview of Science Challenges Pertaining to our Understanding of Extreme Geomagnetically Induced Currents. Chapter 8

NASA Technical Reports Server (NTRS)

Ngwira, Chigomezyo M.; Pulkkinen, Antti A.

2018-01-01

Vulnerability of man-made infrastructure to Earth-directed space weather events is a serious concern for today's technology-dependent society. Space weather-driven geomagnetically induced currents (GICs) can disrupt operation of extended electrically conducting technological systems. The threat of adverse impacts on critical technological infrastructure, like power grids, oil and gas pipelines, and communication networks, has sparked renewed interest in extreme space weather. Because extreme space weather events have low occurrence rate but potentially high impact, this presents a major challenge for our understanding of extreme GIC activity. In this chapter, we discuss some of the key science challenges pertaining to our understanding of extreme events. In addition, we present an overview of GICs including highlights of severe impacts over the last 80 years and recent U.S. Federal actions relevant to this community.

Strategies and Innovative Approaches for the Future of Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Hoeksema, J. T.

2012-12-01

The real and potential impacts of space weather have been well documented, yet neither the required research and operations programs, nor the data, modeling and analysis infrastructure necessary to develop and sustain a reliable space weather forecasting capability for a society are in place. The recently published decadal survey "Solar and Space Physics: A Science for a Technological Society" presents a vision for the coming decade and calls for a renewed national commitment to a comprehensive program in space weather and climatology. New resources are imperative. Particularly in the current fiscal environment, implementing a responsible strategy to address these needs will require broad participation across agencies and innovative approaches to make the most of existing resources, capitalize on current knowledge, span gaps in capabilities and observations, and focus resources on overcoming immediate roadblocks.

Space Weather Influence on Relative Motion Control using the Touchless Electrostatic Tractor

NASA Astrophysics Data System (ADS)

Hogan, Erik A.; Schaub, Hanspeter

2016-09-01

With recent interest in the use of electrostatic forces for contactless tugging and attitude control of noncooperative objects for orbital servicing and active debris mitigation, the need for a method of remote charge control arises. In this paper, the use of a directed electron beam for remote charge control is considered in conjunction with the relative motion control. A tug vehicle emits an electron beam onto a deputy object, charging it negatively. At the same time, the tug is charged positively due to beam emission, resulting in an attractive electrostatic force. The relative position feedback control between the tug and the passive debris object is studied subject to the charging being created through an electron beam. Employing the nominal variations of the GEO space weather conditions across longitude slots, two electrostatic tugging strategies are considered. First, the electron beam current is adjusted throughout the orbit in order to maximize this resulting electrostatic force. This open-loop control strategy compensates for changes in the nominally expected local space weather environment in the GEO region to adjust for fluctuations in the local plasma return currents. Second, the performance impact of using a fixed electron beam current on the electrostatic tractor is studied if the same natural space weather variations are assumed. The fixed electron beam current shows a minor performance penalty (<5 %) while providing a much simpler implementation that does not require any knowledge of local space weather conditions.

The main pillar: Assessment of space weather observational asset performance supporting nowcasting, forecasting, and research to operations.

PubMed

Posner, A; Hesse, M; St Cyr, O C

2014-04-01

Space weather forecasting critically depends upon availability of timely and reliable observational data. It is therefore particularly important to understand how existing and newly planned observational assets perform during periods of severe space weather. Extreme space weather creates challenging conditions under which instrumentation and spacecraft may be impeded or in which parameters reach values that are outside the nominal observational range. This paper analyzes existing and upcoming observational capabilities for forecasting, and discusses how the findings may impact space weather research and its transition to operations. A single limitation to the assessment is lack of information provided to us on radiation monitor performance, which caused us not to fully assess (i.e., not assess short term) radiation storm forecasting. The assessment finds that at least two widely spaced coronagraphs including L4 would provide reliability for Earth-bound CMEs. Furthermore, all magnetic field measurements assessed fully meet requirements. However, with current or even with near term new assets in place, in the worst-case scenario there could be a near-complete lack of key near-real-time solar wind plasma data of severe disturbances heading toward and impacting Earth's magnetosphere. Models that attempt to simulate the effects of these disturbances in near real time or with archival data require solar wind plasma observations as input. Moreover, the study finds that near-future observational assets will be less capable of advancing the understanding of extreme geomagnetic disturbances at Earth, which might make the resulting space weather models unsuitable for transition to operations. Manuscript assesses current and near-future space weather assetsCurrent assets unreliable for forecasting of severe geomagnetic stormsNear-future assets will not improve the situation.

The main pillar: Assessment of space weather observational asset performance supporting nowcasting, forecasting, and research to operations

PubMed Central

Posner, A; Hesse, M; St Cyr, O C

2014-01-01

Space weather forecasting critically depends upon availability of timely and reliable observational data. It is therefore particularly important to understand how existing and newly planned observational assets perform during periods of severe space weather. Extreme space weather creates challenging conditions under which instrumentation and spacecraft may be impeded or in which parameters reach values that are outside the nominal observational range. This paper analyzes existing and upcoming observational capabilities for forecasting, and discusses how the findings may impact space weather research and its transition to operations. A single limitation to the assessment is lack of information provided to us on radiation monitor performance, which caused us not to fully assess (i.e., not assess short term) radiation storm forecasting. The assessment finds that at least two widely spaced coronagraphs including L4 would provide reliability for Earth-bound CMEs. Furthermore, all magnetic field measurements assessed fully meet requirements. However, with current or even with near term new assets in place, in the worst-case scenario there could be a near-complete lack of key near-real-time solar wind plasma data of severe disturbances heading toward and impacting Earth's magnetosphere. Models that attempt to simulate the effects of these disturbances in near real time or with archival data require solar wind plasma observations as input. Moreover, the study finds that near-future observational assets will be less capable of advancing the understanding of extreme geomagnetic disturbances at Earth, which might make the resulting space weather models unsuitable for transition to operations. Key Points Manuscript assesses current and near-future space weather assets Current assets unreliable for forecasting of severe geomagnetic storms Near-future assets will not improve the situation PMID:26213516

Weather dissemination and public usage

NASA Technical Reports Server (NTRS)

Stacey, M. S.

1973-01-01

The existing public usage of weather information was examined. A survey was conducted to substantiate the general public's needs for dissemination of current (0-12 hours) weather information, needs which, in a previous study, were found to be extensive and urgent. The goal of the study was to discover how the general public obtains weather information, what information they seek and why they seek it, to what use this information is put, and to further ascertain the public's attitudes and beliefs regarding weather reporting and the diffusion of weather information. Major findings from the study include: 1. The public has a real need for weather information in the 0-6 hour bracket. 2. The visual medium is preferred but due to the lack of frequent (0-6 hours) forecasts, the audio media only, i.e., telephone recordings and radio weathercasts, were more frequently used. 3. Weather information usage is sporadic.

Sea breeze: Induced mesoscale systems and severe weather

NASA Technical Reports Server (NTRS)

Nicholls, M. E.; Pielke, R. A.; Cotton, W. R.

1990-01-01

Sea-breeze-deep convective interactions over the Florida peninsula were investigated using a cloud/mesoscale numerical model. The objective was to gain a better understanding of sea-breeze and deep convective interactions over the Florida peninsula using a high resolution convectively explicit model and to use these results to evaluate convective parameterization schemes. A 3-D numerical investigation of Florida convection was completed. The Kuo and Fritsch-Chappell parameterization schemes are summarized and evaluated.

Key Issues for Seamless Integrated Chemistry–Meteorology Modeling

EPA Science Inventory

Online coupled meteorology–atmospheric chemistry models have greatly evolved in recent years. Although mainly developed by the air quality modeling community, these integrated models are also of interest for numerical weather prediction and climate modeling, as they can con...

NASA/MSFC FY90 Global Scale Atmospheric Processes Research Program Review

NASA Technical Reports Server (NTRS)

Leslie, Fred W. (Editor)

1990-01-01

Research supported by the Global Atmospheric Research Program at the Marshall Space Flight Center on atmospheric remote sensing, meteorology, numerical weather forecasting, satellite data analysis, cloud precipitation, atmospheric circulation, atmospheric models and related topics is discussed.

AWE: Aviation Weather Data Visualization Environment

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Lodha, Suresh K.

2000-01-01

The two official sources for aviation weather reports both provide weather information to a pilot in a textual format. A number of systems have recently become available to help pilots with the visualization task by providing much of the data graphically. However, two types of aviation weather data are still not being presented graphically. These are airport-specific current weather reports (known as meteorological observations, or METARs) and forecast weather reports (known as terminal area forecasts, or TAFs). Our system, Aviation Weather Environment (AWE), presents intuitive graphical displays for both METARs and TAFs, as well as winds aloft forecasts. We start with a computer-generated textual aviation weather briefing. We map this briefing onto a cartographic grid specific to the pilot's area of interest. The pilot is able to obtain aviation-specific weather for the entire area or for his specific route. The route, altitude, true airspeed, and proposed departure time can each be modified in AWE. Integral visual display of these three elements of weather reports makes AWE a useful planning tool, as well as a weather briefing tool.

Application of a COSMO Mesoscale Model to Assess the Influence of Forest Cover Changes on Regional Weather Conditions

NASA Astrophysics Data System (ADS)

Olchev, A.; Rozinkina, I.; Kuzmina, E.; Nikitin, M.; Rivin, G. S.

2017-12-01

Modern changes in land use and forest cover have a significant influence on local, regional, and global weather and climate conditions. In this study, the mesoscale model COSMO is used to estimate the possible influence of forest cover change in the central part of the East European Plain on regional weather conditions. The "model region" of the study is surrounded by geographical coordinates 55° and 59°N and 28° and 37°E and situated in the central part of a large modeling domain (50° - 70° N and 15° 55° E), covering almost the entire East European Plain in Northern Eurasia. The forests cover about 50% of the area of the "model region". The modeling study includes 3 main numerical experiments. The first assumes total deforestation of the "model region" and replacement of forests by grasslands. The second is represented by afforestation of the "model region." In the third, weather conditions are simulated with present land use and vegetation structures of the "model region." Output of numerical experiments is at 13.2 km grid resolution, and the ERA-Interim global atmospheric reanalysis (with 6-h resolution in time and 0.75°×0.75° in space) is used to quantify initial and boundary conditions. Numerical experiments for the warm period of 2010 taken as an example show that deforestation and afforestation processes in the selected region can lead to significant changes in weather conditions. Deforestation processes in summer conditions can result in increased air temperature and wind speed, reduction of precipitation, lower clouds, and relative humidity. The afforestation process can result in opposite effects (decreased air temperature, increased precipitation, higher air humidity and fog frequency, and strengthened storm winds). Maximum meteorological changes under forest cover changes are projected for the summer months (July and August). It was also shown that changes of some meteorological characteristics (e.g., air temperature) is observed in the "model region" only, and changes in precipitation amount are seen in the entire territory of the East European Plain, even in areas which are a great distance from the boundaries of the "model region." The study was supported by a grant from the Russian Science Foundation (14-14-00956).

The Advanced Technology Microwave Sounder (ATMS): A New Operational Sensor Series

NASA Technical Reports Server (NTRS)

Kim, Edward; Lyu, Cheng-H Joseph; Leslie, R. Vince; Baker, Neal; Mo, Tsan; Sun, Ninghai; Bi, Li; Anderson, Mike; Landrum, Mike; DeAmici, Giovanni;

Active Sensing Air Pressure Using Differential Absorption Barometric Radar

NASA Astrophysics Data System (ADS)

Lin, B.

2016-12-01

Tropical storms and other severe weathers cause huge life losses and property damages and have major impacts on public safety and national security. Their observations and predictions need to be significantly improved. This effort tries to develop a feasible active microwave approach that measures surface air pressure, especially over open seas, from space using a Differential-absorption BArometric Radar (DiBAR) operating at 50-55 GHz O2 absorption band in order to constrain assimilated dynamic fields of numerical weather Prediction (NWP) models close to actual conditions. Air pressure is the most important variable that drives atmospheric dynamics, and currently can only be measured by limited in-situ observations over oceans. Even over land there is no uniform coverage of surface air pressure measurements. Analyses show that with the proposed space radar the errors in instantaneous (averaged) pressure estimates can be as low as 4mb ( 1mb) under all weather conditions. NASA Langley research team has made substantial progresses in advancing the DiBAR concept. The feasibility assessment clearly shows the potential of surface barometry using existing radar technologies. The team has also developed a DiBAR system design, fabricated a Prototype-DiBAR (P-DiBAR) for proof-of-concept, conducted laboratory, ground and airborne P-DiBAR tests. The flight test results are consistent with the instrumentation goals. The precision and accuracy of radar surface pressure measurements are within the range of the theoretical analysis of the DiBAR concept. Observational system simulation experiments for space DiBAR performance based on the existing DiBAR technology and capability show substantial improvements in tropical storm predictions, not only for the hurricane track and position but also for the hurricane intensity. DiBAR measurements will provide us an unprecedented level of the prediction and knowledge on global extreme weather and climate conditions.

The Advanced Technology Microwave Sounder (ATMS): First Year On-Orbit

NASA Technical Reports Server (NTRS)

Kim, Edward J.

2012-01-01

The Advanced Technology Microwave Sounder (ATMS) is a new satellite microwave sounding sensor designed to provide operational weather agencies with atmospheric temperature and moisture profile information for global weather forecasting and climate applications. A TMS will continue the microwave sounding capabilities first provided by its predecessors, the Microwave Sounding Unit (MSU) and Advanced Microwave Sounding Unit (AMSU). The first flight unit was launched a year ago in October, 2011 aboard the Suomi-National Polar-Orbiting Partnership (S-NPP) satellite, part of the new Joint Polar-Orbiting Satellite System (JPSS). Microwave soundings by themselves are the highest-impact input data used by Numerical Weather Prediction models; and A TMS, when combined with the Cross-track Infrared Sounder (CrIS), forms the Cross-track Infrared and Microwave Sounding Suite (CrIMSS). The microwave soundings help meet sounding requirements under cloudy sky conditions and provide key profile information near the surface. ATMS was designed & built by Aerojet Corporation in Azusa, California, (now Northrop Grumman Electronic Systems). It has 22 channels spanning 23-183 GHz, closely following the channel set of the MSU, AMSU-AI/2, AMSU-B, Microwave Humidity Sounder (MHS), and Humidity Sounder for Brazil (HSB). It continues their cross-track scanning geometry, but for the first time, provides Nyquist sample spacing. All this is accomplished with approximately V. the volume, Y, the mass, and Y, the power of the three AMSUs. A description will be given of its performance from its first year of operation as determined by post-launch calibration activities. These activities include radiometric calibration using the on-board warm targets and cold space views, and geolocation determination. Example imagery and zooms of specific weather events will be shown. The second ATMS flight model is currently under construction and planned for launch on the "Jl" satellite of the JPSS program in approximately 2016. Additional units are expected on the J2 and 13 satellites, as well as potentially on future European METOP satellites.

Integration of Weather Avoidance and Traffic Separation

NASA Technical Reports Server (NTRS)

Consiglio, Maria C.; Chamberlain, James P.; Wilson, Sara R.

2011-01-01

This paper describes a dynamic convective weather avoidance concept that compensates for weather motion uncertainties; the integration of this weather avoidance concept into a prototype 4-D trajectory-based Airborne Separation Assurance System (ASAS) application; and test results from a batch (non-piloted) simulation of the integrated application with high traffic densities and a dynamic convective weather model. The weather model can simulate a number of pseudo-random hazardous weather patterns, such as slow- or fast-moving cells and opening or closing weather gaps, and also allows for modeling of onboard weather radar limitations in range and azimuth. The weather avoidance concept employs nested "core" and "avoid" polygons around convective weather cells, and the simulations assess the effectiveness of various avoid polygon sizes in the presence of different weather patterns, using traffic scenarios representing approximately two times the current traffic density in en-route airspace. Results from the simulation experiment show that the weather avoidance concept is effective over a wide range of weather patterns and cell speeds. Avoid polygons that are only 2-3 miles larger than their core polygons are sufficient to account for weather uncertainties in almost all cases, and traffic separation performance does not appear to degrade with the addition of weather polygon avoidance. Additional "lessons learned" from the batch simulation study are discussed in the paper, along with insights for improving the weather avoidance concept. Introduction

Increasing Cold Weather Masonry Construction Productivity

DOT National Transportation Integrated Search

1997-08-01

The thermal protection requirements for cold weather masonry, as established in current industry specifications, were evaluated. Experiments were conducted to define the most relevant factors in the process of freezing of newly placed mortar. The eff...

Analysis of Spatial Autocorrelation for Optimal Observation Network in Korea

NASA Astrophysics Data System (ADS)

Park, S.; Lee, S.; Lee, E.; Park, S. K.

2016-12-01

Many studies for improving prediction of high-impact weather have been implemented, such as THORPEX (The Observing System Research and Predictability Experiment), FASTEX (Fronts and Atlantic Storm-Track Experiment), NORPEX (North Pacific Experiment), WSR/NOAA (Winter Storm Reconnaissance), and DOTSTAR (Dropwindsonde Observations for Typhoon Surveillance near the TAiwan Region). One of most important objectives in these studies is to find effects of observation on forecast, and to establish optimal observation network. However, there are lack of such studies on Korea, although Korean peninsula exhibits a highly complex terrain so it is difficult to predict its weather phenomena. Through building the future optimal observation network, it is necessary to increase utilization of numerical weather prediction and improve monitoring·tracking·prediction skills of high-impact weather in Korea. Therefore, we will perform preliminary study to understand the spatial scale for an expansion of observation system through Spatial Autocorrelation (SAC) analysis. In additions, we will develop a testbed system to design an optimal observation network. Analysis is conducted with Automatic Weather System (AWS) rainfall data, global upper air grid observation (i.e., temperature, pressure, humidity), Himawari satellite data (i.e., water vapor) during 2013-2015 of Korea. This study will provide a guideline to construct observation network for not only improving weather prediction skill but also cost-effectiveness.

The influence of weather on Golden Eagle migration in northwestern Montana

USGS Publications Warehouse

Yates, R.E.; McClelland, B.R.; Mcclelland, P.T.; Key, C.H.; Bennetts, R.E.

2001-01-01

We analyzed the influence of 17 weather factors on migrating Golden Eagles (Aquila chrysaetos) near the Continental Divide in Glacier National Park, Montana, U.S.A. Local weather measurements were recorded at automated stations on the flanks of two peaks within the migration path. During a total of 506 hr of observation, the yearly number of Golden Eagles in autumn counts (1994-96) averaged 1973; spring counts (1995 and 1996) averaged 605 eagles. Mean passage rates (eagles/hr) were 16.5 in autumn and 8.2 in spring. Maximum rates were 137 in autumn and 67 in spring. Using generalized linear modeling, we tested for the effects of weather factors on the number of eagles counted. In the autumn model, the number of eagles increased with increasing air temperature, rising barometric pressure, decreasing relative humidity, and interactions among those factors. In the spring model, the number of eagles increased with increasing wind speed, barometric pressure, and the interaction between these factors. Our data suggest that a complex interaction among weather factors influenced the number of eagles passing on a given day. We hypothesize that in complex landscapes with high topographic relief, such as Glacier National Park, numerous weather factors produce different daily combinations to which migrating eagles respond opportunistically. ?? 2001 The Raptor Research Foundation, Inc.

Future Missions for Space Weather Specifications and Forecasts

NASA Astrophysics Data System (ADS)

Onsager, T. G.; Biesecker, D. A.; Anthes, R. A.; Maier, M. W.; Gallagher, F. W., III; St Germain, K.

2017-12-01

The progress of technology and the global integration of our economic and security infrastructures have introduced vulnerabilities to space weather that demand a more comprehensive ability to specify and to predict the dynamics of the space environment. This requires a comprehensive network of real-time space-based and ground-based observations with long-term continuity. In order to determine the most cost effective space architectures for NOAA's weather, space weather, and environmental missions, NOAA conducted the NOAA Satellite Observing System Architecture (NSOSA) study. This presentation will summarize the process used to document the future needs and the relative priorities for NOAA's operational space-based observations. This involves specifying the most important observations, defining the performance attributes at different levels of capability, and assigning priorities for achieving the higher capability levels. The highest priority observations recommended by the Space Platform Requirements Working Group (SPRWG) for improvement above a minimal capability level will be described. Finally, numerous possible satellite architectures have been explored to assess the costs and benefits of various architecture configurations.

Benefits of Sharing Information: Supermodel Ensemble and Applications in South America

NASA Astrophysics Data System (ADS)

Dias, P. L.

2006-05-01

A model intercomparison program involving a large number of academic and operational institutions has been implemented in South America since 2003, motivated by the SALLJEX Intercomparison Program in 2003 (a research program focused on the identification of the role of the Andes low level jet moisture transport from the Amazon to the Plata basin) and the WMO/THORPEX (www.wmo.int/thorpex) goals to improve predictability through the proper combination of numerical weather forecasts. This program also explores the potential predictability associated with the combination of a large number of possible scenarios in the time scale of a few days to up to 15 days. Five academic institutions and five operational forecasting centers in several countries in South America, 1 academic institution in the USA, and the main global forecasting centers (NCEP, UKMO, ECMWF) agreed to provide numerical products based on operational and experimental models. The metric for model validation is concentrated on the fit of the forecast to surface observations. Meteorological data from airports, synoptic stations operated by national weather services, automatic data platforms maintained by different institutions, the PIRATA buoys etc are all collected through LDM/NCAR or direct transmission. Approximately 40 models outputs are available on a daily basis, twice a day. A simple procedure based on data assimilation principles was quite successful in combining the available forecasts in order to produce temperature, dew point, wind, pressure and precipitation forecasts at station points in S. America. The procedure is based on removing each model bias at the observational point and a weighted average based on the mean square error of the forecasts. The base period for estimating the bias and mean square error is of the order of 15 to 30 days. Products of the intercomparison model program and the optimal statistical combination of the available forecasts are public and available in real time (www.master.iag.usp.br/). Monitoring of the use of the products reveal a growing trend in the last year (reaching about 10.000 accesses per day in recent months). The intercomparison program provides a rich data set for educational products (real time use in Synoptic Meteorology and Numerical Weather Forecasting lectures), operational weather forecasts in national or regional weather centers and for research purposes. During the first phase of the program it was difficult to convince potential participants to share the information in the public homepage. However, as the system evolved, more and more institutions became associated with the program. The general opinion of the participants is that the system provides an unified metric for evaluation, a forum for discussion of the physical origin of the model forecast differences and therefore improvement of the quality of the numerical guidance.

FlooDSuM - a decision support methodology for assisting local authorities in flood situations

NASA Astrophysics Data System (ADS)

Schwanbeck, Jan; Weingartner, Rolf

2014-05-01

Decision making in flood situations is a difficult task, especially in small to medium-sized mountain catchments (30 - 500 km2) which are usually characterized by complex topography, high drainage density and quick runoff response to rainfall events. Operating hydrological models driven by numerical weather prediction systems, which have a lead-time of several hours up to few even days, would be beneficial in this case as time for prevention could be gained. However, the spatial and quantitative accuracy of such meteorological forecasts usually decrease with increasing lead-time. In addition, the sensitivity of rainfall-runoff models to inaccuracies in estimations of areal rainfall increases with decreasing catchment size. Accordingly, decisions on flood alerts should ideally be based on areal rainfall from high resolution and short-term numerical weather prediction, nowcasts or even real-time measurements, which is transformed into runoff by a hydrological model. In order to benefit from the best possible rainfall data while retaining enough time for alerting and for prevention, the hydrological model should be fast and easily applicable by decision makers within local authorities themselves. The proposed decision support methodology FlooDSuM (Flood Decision Support Methodology) aims to meet those requirements. Applying FlooDSuM, a few successive binary decisions of increasing complexity have to be processed following a flow-chart-like structure. Prepared data and straightforwardly applicable tools are provided for each of these decisions. Maps showing the current flood disposition are used for the first step. While danger of flooding cannot be excluded more and more complex and time consuming methods will be applied. For the final decision, a set of scatter-plots relating areal precipitation to peak flow is provided. These plots take also further decisive parameters into account such as storm duration, distribution of rainfall intensity in time as well as the catchment's antecedent moisture conditions. The proposed approach is currently tested in two catchments in the Swiss Pre-Alps and Alps. We will show the general setup and selected results. The findings of those case studies will lead to further improvements of the proposed approach.

Space Weather Monitoring for ISS Space Environments Engineering and Crew Auroral Observations

NASA Technical Reports Server (NTRS)

Minow, Joseph I.; Pettit, Donald R.; Hartman, William A.

2012-01-01

The awareness of potentially significant impacts of space weather on spaceand ground ]based technological systems has generated a strong desire in many sectors of government and industry to effectively transform knowledge and understanding of the variable space environment into useful tools and applications for use by those entities responsible for systems that may be vulnerable to space weather impacts. Essentially, effectively transitioning science knowledge to useful applications relevant to space weather has become important. This talk will present proven methodologies that have been demonstrated to be effective, and how in the current environment those can be applied to space weather transition efforts.

Dynamic Weather Routes: A Weather Avoidance Concept for Trajectory-Based Operations

NASA Technical Reports Server (NTRS)

McNally, B. David; Love, John

2011-01-01

The integration of convective weather modeling with trajectory automation for conflict detection, trial planning, direct routing, and auto resolution has uncovered a concept that could help controllers, dispatchers, and pilots identify improved weather routes that result in significant savings in flying time and fuel burn. Trajectory automation continuously and automatically monitors aircraft in flight to find those that could potentially benefit from improved weather reroutes. Controllers, dispatchers, and pilots then evaluate reroute options to assess their suitability given current weather and traffic. In today's operations aircraft fly convective weather avoidance routes that were implemented often hours before aircraft approach the weather and automation does not exist to automatically monitor traffic to find improved weather routes that open up due to changing weather conditions. The automation concept runs in real-time and employs two keysteps. First, a direct routing algorithm automatically identifies flights with large dog legs in their routes and therefore potentially large savings in flying time. These are common - and usually necessary - during convective weather operations and analysis of Fort Worth Center traffic shows many aircraft with short cuts that indicate savings on the order of 10 flying minutes. The second and most critical step is to apply trajectory automation with weather modeling to determine what savings could be achieved by modifying the direct route such that it avoids weather and traffic and is acceptable to controllers and flight crews. Initial analysis of Fort Worth Center traffic suggests a savings of roughly 50% of the direct route savings could be achievable.The core concept is to apply trajectory automation with convective weather modeling in real time to identify a reroute that is free of weather and traffic conflicts and indicates enough time and fuel savings to be considered. The concept is interoperable with today's integrated FMS/datalink. Auxiliary(lat/long) waypoints define a minimum delay reroute between current position and a downstream capture fix beyond the weather. These auxiliary waypoints can be uplinked to equipped aircraft and auto-loaded into the FMS. Alternatively, for unequipped aircraft, auxiliary waypoints can be replaced by nearby named fixes, but this could reduce potential savings. The presentation includes an overview of the automation approach and focuses on several cases in terms of potential savings, reroute complexity, best auxiliary waypoint solution vs. named fix solution, and other metrics.

Explicit simulation of ice particle habits in a Numerical Weather Prediction Model

NASA Astrophysics Data System (ADS)

Hashino, Tempei

2007-05-01

This study developed a scheme for explicit simulation of ice particle habits in Numerical Weather Prediction (NWP) Models. The scheme is called Spectral Ice Habit Prediction System (SHIPS), and the goal is to retain growth history of ice particles in the Eulerian dynamics framework. It diagnoses characteristics of ice particles based on a series of particle property variables (PPVs) that reflect history of microphysieal processes and the transport between mass bins and air parcels in space. Therefore, categorization of ice particles typically used in bulk microphysical parameterization and traditional bin models is not necessary, so that errors that stem from the categorization can be avoided. SHIPS predicts polycrystals as well as hexagonal monocrystals based on empirically derived habit frequency and growth rate, and simulates the habit-dependent aggregation and riming processes by use of the stochastic collection equation with predicted PPVs. Idealized two dimensional simulations were performed with SHIPS in a NWP model. The predicted spatial distribution of ice particle habits and types, and evolution of particle size distributions showed good quantitative agreement with observation This comprehensive model of ice particle properties, distributions, and evolution in clouds can be used to better understand problems facing wide range of research disciplines, including microphysics processes, radiative transfer in a cloudy atmosphere, data assimilation, and weather modification.

The contributions of Lewis Fry Richardson to drainage theory, soil physics, and the soil-plant-atmosphere continuum

NASA Astrophysics Data System (ADS)

Knight, John; Raats, Peter

2016-04-01

The EGU Division on Nonlinear Processes in Geophysics awards the Lewis Fry Richardson Medal. Richardson's significance is highlighted in http://www.egu.eu/awards-medals/portrait-lewis-fry-richardson/, but his contributions to soil physics and to numerical solutions of heat and diffusion equations are not mentioned. We would like to draw attention to those little known contributions. Lewis Fry Richardson (1881-1953) made important contributions to many fields including numerical weather prediction, finite difference solutions of partial differential equations, turbulent flow and diffusion, fractals, quantitative psychology and studies of conflict. He invented numerical weather prediction during World War I, although his methods were not successfully applied until 1950, after the invention of fast digital computers. In 1922 he published the book `Numerical weather prediction', of which few copies were sold and even fewer were read until the 1950s. To model heat and mass transfer in the atmosphere, he did much original work on turbulent flow and defined what is now known as the Richardson number. His technique for improving the convergence of a finite difference calculation is known as Richardson extrapolation, and was used by John Philip in his 1957 semi-analytical solution of the Richards equation for water movement in unsaturated soil. Richardson's first papers in 1908 concerned the numerical solution of the free surface problem of unconfined flow of water in saturated soil, arising in the design of drain spacing in peat. Later, for the lower boundary of his atmospheric model he needed to understand the movement of heat, liquid water and water vapor in what is now called the vadose zone and the soil plant atmosphere system, and to model coupled transfer of heat and flow of water in unsaturated soil. Finding little previous work, he formulated partial differential equations for transient, vertical flow of liquid water and for transfer of heat and water vapor. He paid considerable attention to the balances of water and energy at the soil-atmosphere and plant-atmosphere interfaces, making use of the concept of transfer resistance introduced by Brown and Escombe (1900) for leaf-atmosphere interfaces. He incorporated finite difference versions of all equations into his numerical weather forecasting model. From 1916, Richardson drove an ambulance in France in World War I, did weather computations in his spare time, and wrote a draft of his book. Later researchers such as L.A. Richards, D.A. de Vries and J.R. Philip from the 1930s to the 1950s were unaware that Richardson had anticipated many of their ideas on soil liquid water, heat, water vapor, and the soil-plant-atmosphere system. The Richards (1931) equation could rightly be called the Richardson (1922) equation! Richardson (1910) developed what we now call the Crank Nicolson implicit method for the heat or diffusion equation. To save effort, he used an explicit three level method after the first time step. Crank and Nicolson (1947) pointed out the instability in the explicit method, and used his implicit method for all time steps. Hanks and Bowers (1962) adapted the Crank Nicolson method to solve the Richards equation. So we could say that Hanks and Bowers used the Richardson finite difference method to solve the Richardson equation for soil water flow!

Improving the Long-Term Stability of Atmospheric Surface Deformation Predictions by Mitigating the Effects of Orography Updates in Operational Weather Forecast Models

NASA Astrophysics Data System (ADS)

Dill, Robert; Bergmann-Wolf, Inga; Thomas, Maik; Dobslaw, Henryk

2016-04-01

The global numerical weather prediction model routinely operated at the European Centre for Medium-Range Weather Forecasts (ECMWF) is typically updated about two times a year to incorporate the most recent improvements in the numerical scheme, the physical model or the data assimilation procedures into the system for steadily improving daily weather forecasting quality. Even though such changes frequently affect the long-term stability of meteorological quantities, data from the ECMWF deterministic model is often preferred over alternatively available atmospheric re-analyses due to both the availability of the data in near real-time and the substantially higher spatial resolution. However, global surface pressure time-series, which are crucial for the interpretation of geodetic observables, such as Earth rotation, surface deformation, and the Earth's gravity field, are in particular affected by changes in the surface orography of the model associated with every major change in horizontal resolution happened, e.g., in February 2006, January 2010, and May 2015 in case of the ECMWF operational model. In this contribution, we present an algorithm to harmonize surface pressure time-series from the operational ECMWF model by projecting them onto a time-invariant reference topography under consideration of the time-variable atmospheric density structure. The effectiveness of the method will be assessed globally in terms of pressure anomalies. In addition, we will discuss the impact of the method on predictions of crustal deformations based on ECMWF input, which have been recently made available by GFZ Potsdam.

Application of Numerical Weather Models to Mitigating Atmospheric Artifacts in InSAR

NASA Astrophysics Data System (ADS)

Foster, J. H.; Kealy, J.; Businger, S.; Cherubini, T.; Brooks, B. A.; Albers, S. C.; Lu, Z.; Poland, M. P.; Chen, S.; Mass, C.

2011-12-01

A high-resolution weather "hindcasting" system to model the atmosphere at the time of SAR scene acquisitions has been established to investigate and mitigate the impact of atmospheric water vapor on InSAR deformation maps. Variations in the distributions of water vapor in the atmosphere between SAR acquisitions lead to artifacts in interferograms that can mask real ground motion signals. A database of regional numerical weather prediction model outputs generated by the University of Washington and U.C. Davis for times matching SAR acquisitions was used as "background" for higher resolution analyses of the atmosphere for Mount St Helens volcano in Washington, and Los Angeles in southern California. Using this background, we use LAPS to incrementally incorporate all other available meteorological data sets, including GPS, to explore the impact of additional observations on model accuracy. Our results suggest that, even with significant quantities of contemporaneously measured data, high-resolution atmospheric analyses are unable to model the timing and location of water vapor perturbations accurately enough to produce robust and reliable phase screens that can be directly subtracted from interferograms. Despite this, the analyses are able to reproduce the statistical character of the atmosphere with some confidence, suggesting that, in the absence of unusually dense in-situ measurements (such as is the case with GPS data for Los Angeles), weather analysis can play a valuable role in constraining the power-spectrum expected in an interferogram due to the troposphere. This could be used to provide objective weights to scenes during traditional stacking or to tune the filter parameters in time-series analyses.

Municipalities' Preparedness for Weather Hazards and Response to Weather Warnings

PubMed Central

Mehiriz, Kaddour; Gosselin, Pierre

2016-01-01

The study of the management of weather-related disaster risks by municipalities has attracted little attention even though these organizations play a key role in protecting the population from extreme meteorological conditions. This article contributes to filling this gap with new evidence on the level and determinants of Quebec municipalities’ preparedness for weather hazards and response to related weather warnings. Using survey data from municipal emergency management coordinators and secondary data on the financial and demographic characteristics of municipalities, the study shows that most Quebec municipalities are sufficiently prepared for weather hazards and undertake measures to protect the population when informed of imminent extreme weather events. Significant differences between municipalities were noted though. Specifically, the level of preparedness was positively correlated with the municipalities’ capacity and population support for weather-related disaster management policies. In addition, the risk of weather-related disasters increases the preparedness level through its effect on population support. We also found that the response to weather warnings depended on the risk of weather-related disasters, the preparedness level and the quality of weather warnings. These results highlight areas for improvement in the context of increasing frequency and/or severity of such events with current climate change. PMID:27649547

Municipalities' Preparedness for Weather Hazards and Response to Weather Warnings.

PubMed

Mehiriz, Kaddour; Gosselin, Pierre

2016-01-01

The study of the management of weather-related disaster risks by municipalities has attracted little attention even though these organizations play a key role in protecting the population from extreme meteorological conditions. This article contributes to filling this gap with new evidence on the level and determinants of Quebec municipalities' preparedness for weather hazards and response to related weather warnings. Using survey data from municipal emergency management coordinators and secondary data on the financial and demographic characteristics of municipalities, the study shows that most Quebec municipalities are sufficiently prepared for weather hazards and undertake measures to protect the population when informed of imminent extreme weather events. Significant differences between municipalities were noted though. Specifically, the level of preparedness was positively correlated with the municipalities' capacity and population support for weather-related disaster management policies. In addition, the risk of weather-related disasters increases the preparedness level through its effect on population support. We also found that the response to weather warnings depended on the risk of weather-related disasters, the preparedness level and the quality of weather warnings. These results highlight areas for improvement in the context of increasing frequency and/or severity of such events with current climate change.

Long range forecasts of the Northern Hemisphere anomalies with antecedent sea surface temperature patterns

NASA Technical Reports Server (NTRS)

Kung, Ernest C.

1994-01-01

The contract research has been conducted in the following three major areas: analysis of numerical simulations and parallel observations of atmospheric blocking, diagnosis of the lower boundary heating and the response of the atmospheric circulation, and comprehensive assessment of long-range forecasting with numerical and regression methods. The essential scientific and developmental purpose of this contract research is to extend our capability of numerical weather forecasting by the comprehensive general circulation model. The systematic work as listed above is thus geared to developing a technological basis for future NASA long-range forecasting.

Wind power forecasting: IEA Wind Task 36 & future research issues

NASA Astrophysics Data System (ADS)

Giebel, G.; Cline, J.; Frank, H.; Shaw, W.; Pinson, P.; Hodge, B.-M.; Kariniotakis, G.; Madsen, J.; Möhrlen, C.

2016-09-01

This paper presents the new International Energy Agency Wind Task 36 on Forecasting, and invites to collaborate within the group. Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind Energy tries to organise international collaboration, among national meteorological centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, MetOffice, met.no, DMI,...), operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions. As first results, an overview of current issues for research in short-term forecasting of wind power is presented.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giebel, G.; Cline, J.; Frank, H.

Here, this paper presents the new International Energy Agency Wind Task 36 on Forecasting, and invites to collaborate within the group. Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind Energy tries to organise international collaboration, among national meteorological centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, MetOffice, met.no, DMI,...), operational forecaster and forecast users. The Taskmore » is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions. As first results, an overview of current issues for research in short-term forecasting of wind power is presented.« less

Biological and geophysical feedbacks with fire in the Earth system

NASA Astrophysics Data System (ADS)

Archibald, S.; Lehmann, C. E. R.; Belcher, C. M.; Bond, W. J.; Bradstock, R. A.; Daniau, A.-L.; Dexter, K. G.; Forrestel, E. J.; Greve, M.; He, T.; Higgins, S. I.; Hoffmann, W. A.; Lamont, B. B.; McGlinn, D. J.; Moncrieff, G. R.; Osborne, C. P.; Pausas, J. G.; Price, O.; Ripley, B. S.; Rogers, B. M.; Schwilk, D. W.; Simon, M. F.; Turetsky, M. R.; Van der Werf, G. R.; Zanne, A. E.

2018-03-01

Roughly 3% of the Earth’s land surface burns annually, representing a critical exchange of energy and matter between the land and atmosphere via combustion. Fires range from slow smouldering peat fires, to low-intensity surface fires, to intense crown fires, depending on vegetation structure, fuel moisture, prevailing climate, and weather conditions. While the links between biogeochemistry, climate and fire are widely studied within Earth system science, these relationships are also mediated by fuels—namely plants and their litter—that are the product of evolutionary and ecological processes. Fire is a powerful selective force and, over their evolutionary history, plants have evolved traits that both tolerate and promote fire numerous times and across diverse clades. Here we outline a conceptual framework of how plant traits determine the flammability of ecosystems and interact with climate and weather to influence fire regimes. We explore how these evolutionary and ecological processes scale to impact biogeochemical and Earth system processes. Finally, we outline several research challenges that, when resolved, will improve our understanding of the role of plant evolution in mediating the fire feedbacks driving Earth system processes. Understanding current patterns of fire and vegetation, as well as patterns of fire over geological time, requires research that incorporates evolutionary biology, ecology, biogeography, and the biogeosciences.

LOSCAR: Long-term Ocean-atmosphere-Sediment CArbon cycle Reservoir Model

NASA Astrophysics Data System (ADS)

Zeebe, R. E.

2011-06-01

The LOSCAR model is designed to efficiently compute the partitioning of carbon between ocean, atmosphere, and sediments on time scales ranging from centuries to millions of years. While a variety of computationally inexpensive carbon cycle models are already available, many are missing a critical sediment component, which is indispensable for long-term integrations. One of LOSCAR's strengths is the coupling of ocean-atmosphere routines to a computationally efficient sediment module. This allows, for instance, adequate computation of CaCO3 dissolution, calcite compensation, and long-term carbon cycle fluxes, including weathering of carbonate and silicate rocks. The ocean component includes various biogeochemical tracers such as total carbon, alkalinity, phosphate, oxygen, and stable carbon isotopes. We have previously published applications of the model tackling future projections of ocean chemistry and weathering, pCO2 sensitivity to carbon cycle perturbations throughout the Cenozoic, and carbon/calcium cycling during the Paleocene-Eocene Thermal Maximum. The focus of the present contribution is the detailed description of the model including numerical architecture, processes and parameterizations, tuning, and examples of input and output. Typical CPU integration times of LOSCAR are of order seconds for several thousand model years on current standard desktop machines. The LOSCAR source code in C can be obtained from the author by sending a request to loscar.model@gmail.com.

Florida's propagation report

NASA Technical Reports Server (NTRS)

Helmken, Henry; Henning, Rudolf

1994-01-01

One of the key goals of the Florida Center is to obtain a maximum of useful information on propagation behavior unique to its subtropical weather and subtropical climate. Such weather data is of particular interest when it is (or has the potential to become) useful for developing and implementing techniques to compensate for adverse weather effects. Also discussed are data observations, current challenges, CDF's, sun movement, and diversity experiments.

Development of Rail Temperature Prediction Model : Research Results

DOT National Transportation Integrated Search

2008-06-01

Preventing track buckling is important to the railroad industry's goal of operational safety. It is a common practice for railroads to impose slow orders during hot weather when the risk of track buckling is high. Numerous factors affect track buckli...

Road weather connected vehicle applications : benefit-cost analysis interim report.

DOT National Transportation Integrated Search

2013-01-01

RWMP is currently engaged in a project to evaluate the potential benefits of road weather connected vehicle applications. Of particular interest are the potential improvements in safety, reductions in travel time, improved travel reliability, reducti...

Baselining current road weather information : final report

DOT National Transportation Integrated Search

2009-06-10

This final report contains research findings on the characterization of the quality and value of road weather information resources used by members of the surface transportation community in their decision-making process. The objectives of the projec...

Highway traffic noise in the United States : problem and response

DOT National Transportation Integrated Search

2013-09-01

Over the past decade, the Federal Highway Administrations (FHWA) Road Weather Management Program (RWMP) has championed the cause of improving traffic operations and safety during weather events. The programs current emphasis is to encourage age...

Amazonian chemical weathering rate derived from stony meteorite finds at Meridiani Planum on Mars

NASA Astrophysics Data System (ADS)

Schröder, Christian; Bland, Phil A.; Golombek, Matthew P.; Ashley, James W.; Warner, Nicholas H.; Grant, John A.

2016-11-01

Spacecraft exploring Mars such as the Mars Exploration Rovers Spirit and Opportunity, as well as the Mars Science Laboratory or Curiosity rover, have accumulated evidence for wet and habitable conditions on early Mars more than 3 billion years ago. Current conditions, by contrast, are cold, extremely arid and seemingly inhospitable. To evaluate exactly how dry today's environment is, it is important to understand the ongoing current weathering processes. Here we present chemical weathering rates determined for Mars. We use the oxidation of iron in stony meteorites investigated by the Mars Exploration Rover Opportunity at Meridiani Planum. Their maximum exposure age is constrained by the formation of Victoria crater and their minimum age by erosion of the meteorites. The chemical weathering rates thus derived are ~1 to 4 orders of magnitude slower than that of similar meteorites found in Antarctica where the slowest rates are observed on Earth.

Amazonian chemical weathering rate derived from stony meteorite finds at Meridiani Planum on Mars.

PubMed

Schröder, Christian; Bland, Phil A; Golombek, Matthew P; Ashley, James W; Warner, Nicholas H; Grant, John A

2016-11-11

Spacecraft exploring Mars such as the Mars Exploration Rovers Spirit and Opportunity, as well as the Mars Science Laboratory or Curiosity rover, have accumulated evidence for wet and habitable conditions on early Mars more than 3 billion years ago. Current conditions, by contrast, are cold, extremely arid and seemingly inhospitable. To evaluate exactly how dry today's environment is, it is important to understand the ongoing current weathering processes. Here we present chemical weathering rates determined for Mars. We use the oxidation of iron in stony meteorites investigated by the Mars Exploration Rover Opportunity at Meridiani Planum. Their maximum exposure age is constrained by the formation of Victoria crater and their minimum age by erosion of the meteorites. The chemical weathering rates thus derived are ∼1 to 4 orders of magnitude slower than that of similar meteorites found in Antarctica where the slowest rates are observed on Earth.

Amazonian chemical weathering rate derived from stony meteorite finds at Meridiani Planum on Mars

PubMed Central

Schröder, Christian; Bland, Phil A.; Golombek, Matthew P.; Ashley, James W.; Warner, Nicholas H.; Grant, John A.

2016-01-01

Spacecraft exploring Mars such as the Mars Exploration Rovers Spirit and Opportunity, as well as the Mars Science Laboratory or Curiosity rover, have accumulated evidence for wet and habitable conditions on early Mars more than 3 billion years ago. Current conditions, by contrast, are cold, extremely arid and seemingly inhospitable. To evaluate exactly how dry today's environment is, it is important to understand the ongoing current weathering processes. Here we present chemical weathering rates determined for Mars. We use the oxidation of iron in stony meteorites investigated by the Mars Exploration Rover Opportunity at Meridiani Planum. Their maximum exposure age is constrained by the formation of Victoria crater and their minimum age by erosion of the meteorites. The chemical weathering rates thus derived are ∼1 to 4 orders of magnitude slower than that of similar meteorites found in Antarctica where the slowest rates are observed on Earth. PMID:27834377

Numerical simulation of the rapid intensification of Hurricane Katrina (2005): Sensitivity to boundary layer parameterization schemes

NASA Astrophysics Data System (ADS)

Liu, Jianjun; Zhang, Feimin; Pu, Zhaoxia

2017-04-01

Accurate forecasting of the intensity changes of hurricanes is an important yet challenging problem in numerical weather prediction. The rapid intensification of Hurricane Katrina (2005) before its landfall in the southern US is studied with the Advanced Research version of the WRF (Weather Research and Forecasting) model. The sensitivity of numerical simulations to two popular planetary boundary layer (PBL) schemes, the Mellor-Yamada-Janjic (MYJ) and the Yonsei University (YSU) schemes, is investigated. It is found that, compared with the YSU simulation, the simulation with the MYJ scheme produces better track and intensity evolution, better vortex structure, and more accurate landfall time and location. Large discrepancies (e.g., over 10 hPa in simulated minimum sea level pressure) are found between the two simulations during the rapid intensification period. Further diagnosis indicates that stronger surface fluxes and vertical mixing in the PBL from the simulation with the MYJ scheme lead to enhanced air-sea interaction, which helps generate more realistic simulations of the rapid intensification process. Overall, the results from this study suggest that improved representation of surface fluxes and vertical mixing in the PBL is essential for accurate prediction of hurricane intensity changes.

The sensitivity of precipitation simulations to the soot aerosol presence

NASA Astrophysics Data System (ADS)

Palamarchuk, Iuliia; Ivanov, Sergiy; Mahura, Alexander; Ruban, Igor

2016-04-01

The role of aerosols in nonlinear feedbacks on atmospheric processes is in a focus of many researches. Particularly, the importance of black carbon particles for evolution of physical weather including precipitation formation and release is investigated by numerical modelling as well as observation networks. However, certain discrepancies between results obtained by different methods are remained. The increasing of complexity in numerical weather modelling systems leads to enlarging a volume of output data and promises to reveal new aspects in complexity of interactions and feedbacks. The Harmonie-38h1.2 model with the AROME physical package is used to study changes in precipitation life-cycle under black carbon polluted conditions. A model configuration includes a radar data assimilation procedure on a high resolution domain covering the Scandinavia region. Model results show that precipitation rate and distribution as well as other variables of atmospheric dynamics and physics over the domain are sensitive to aerosol concentrations. The attention should also be paid to numerical aspects, such as a list of observation types involved in assimilation. The use of high resolution radar information allows to include mesoscale features in initial conditions and to decrease the growth rate of a model error with the lead time.

A GEOCLIM Simulation Of Climatic And Biogeochemical Consequences Of Pangea Break Up

NASA Astrophysics Data System (ADS)

Donnadieu, Y.; Godderis, Y.; Pierrehumbert, R.; Dromart, G.; Jacob, R.

2006-12-01

Large fluctuations in continental configuration occur all along the Mesozoic times. While it has long been recognized that paleogeography may potentially influence atmospheric CO2 via the continental silicate weathering feedback, no numerical simulation have been done given the lack of a spatially resolved climate- carbon model. GEOCLIM, a coupled numerical model of the climate and global biogeochemical cycles, is used to investigate the consequences of the Pangea break up. The climate module of the GEOCLIM model is the FOAM atmospheric general circulation model, allowing the calculation of the consumption of atmospheric CO2 through continental silicate weathering with a spatial resolution of 7.5°long 4.5°lat. Seven time slices have been simulated. We show that the break up of the Pangea supercontinent triggers an increase in continental runoff, resulting in enhanced atmospheric CO2 consumption through silicate weathering. As a result, atmospheric CO2 falls from values above 3000 ppmv during the Triassic, down to rather low levels during the Cretaceous (around 400 ppmv), resulting in a decrease in continental temperatures from about 20°C to 10°C. Silicate weathering feedback and paleogeography both act to force the Earth system toward a dry and hot world reaching its optimum over the last 260 Ma during the Middle-Late Triassic. In the super continent case, given the relative aridity that cannot be climatically overwhelmed, the model generates high CO2 values to produce very warm continental temperatures compensating for the lack of continental humidity. Conversely, in the fragmented case, the runoff becomes the most important contributor to the silicate weathering rate, hence, producing a CO2 drawdown and a fall in continental temperatures. Finally, an other unexpected outcome is the pronounced fluctuations in carbonate accumulation simulated by the model in response to the Pangea break up. These fluctuations are driven by changes in continental carbonate weathering flux. Accounting for the fluctuations in area available for carbonate platforms, the simulated ratio of carbonate deposition between neritic and deep sea environments is in better agreement with available data.

Mission Driven Scene Understanding: Dynamic Environments

DTIC Science & Technology

2016-06-01

the Army mission. Then, for example, helpful image cues that relate to mission activities may include time of day, current and future weather...mission.10 In other words, visual saliency also can be used to highlight key image cues that relate to Army mission activities.10 For example, an...to the Army mission. Then, for example, helpful image cues that relate to mission activities may include time of day, current and future weather

A survey of of uses and value of space weather information

NASA Astrophysics Data System (ADS)

Schrijver, C. J.; Rabanal, J.

2013-12-01

We analyze some 2,800 responses to a survey among subscribers of NOAA's Space Weather Prediction Center email services. Interest in, anticipated impacts from, and responses to solar flares, energetic particle events, and geomagnetic storms are quite uniform across societal sectors. Approximately 40% of the respondents expect serious to very serious impacts from space weather events if no action were taken to mitigate or in the absence of adequate space weather information. The impacts of space weather are deemed to be substantially reduced because of the availability of, and the response to, space-weather forecasts and alerts. Space weather information is primarily used as aid to understand anomalies, to implement mitigating strategies designed to avoid impacts on operations, and to prepare for potential contingencies related directly or indirectly to space weather. Current and near-future space-weather conditions are generally highly valued, considered useful, and generally, though not fully, adequate to avoid or mitigate societal impacts (related most frequently to human safety and reliability of operations). We conclude that even among those receiving space weather information, there is considerable uncertainty about how to act on the information provided.

High potential for weathering and climate effects of non-vascular vegetation in the Late Ordovician

NASA Astrophysics Data System (ADS)

Porada, Philipp; Lenton, Tim; Pohl, Alexandre; Weber, Bettina; Mander, Luke; Donnadieu, Yannick; Beer, Christian; Pöschl, Ulrich; Kleidon, Axel

2017-04-01

Early non-vascular vegetation in the Late Ordovician may have strongly increased chemical weathering rates of surface rocks at the global scale. This could have led to a drawdown of atmospheric CO2 and, consequently, a decrease in global temperature and an interval of glaciations. Under current climatic conditions, usually field or laboratory experiments are used to quantify enhancement of chemical weathering rates by non-vascular vegetation. However, these experiments are constrained to a small spatial scale and a limited number of species. This complicates the extrapolation to the global scale, even more so for the geological past, where physiological properties of non-vascular vegetation may have differed from current species. Here we present a spatially explicit modelling approach to simulate large-scale chemical weathering by non-vascular vegetation in the Late Ordovician. For this purpose, we use a process-based model of lichens and bryophytes, since these organisms are probably the closest living analogue to Late Ordovician vegetation. The model explicitly represents multiple physiological strategies, which enables the simulated vegetation to adapt to Ordovician climatic conditions. We estimate productivity of Ordovician vegetation with the model, and relate it to chemical weathering by assuming that the organisms dissolve rocks to extract phosphorus for the production of new biomass. Thereby we account for limits on weathering due to reduced supply of unweathered rock material in shallow regions, as well as decreased transport capacity of runoff for dissolved weathered material in dry areas. We simulate a potential global weathering flux of 2.8 km3 (rock) per year, which we define as volume of primary minerals affected by chemical transformation. Our estimate is around 3 times larger than today's global chemical weathering flux. Furthermore, chemical weathering rates simulated by our model are highly sensitive to atmospheric CO2 concentration, which implies a strong negative feedback between weathering by non-vascular vegetation and Ordovician climate.

Plants and microorganisms as drivers of mineral weathering

NASA Astrophysics Data System (ADS)

Dontsova, K.; Chorover, J.; Maier, R.; Hunt, E.; Zaharescu, D. G.

2011-12-01

Plants and microorganisms play important role in mineral weathering and soil formation modifying their environment to make it more hospitable for life. This presentation summarizes several collaborative studies that focused on understanding how interactions between plants and microorganisms, where plants provide the energy through photosynthesis, drive mineral weathering and result in soil formation. Plants influence weathering through multiple mechanisms that have been previously established, such as increase in CO2 concentration in the soil through root respiration and degradation of plant residues and exudates by heterotrophic microorganisms, release of organic acids that promote mineral dissolution, removal of weathering products from soil solution through uptake, and water redistribution. Weathering processes result in nutrient release that satisfies immediate needs of the plants and microorganisms, as well as precipitation of secondary phases, that provide surfaces for retention of nutrients and organic carbon accumulation. What makes understanding contribution of plants and microorganisms, such as bacteria and fungi, to mineral weathering challenging is the fact that they closely interact, enhancing and amplifying each other's contribution. In order to address multiple processes that contribute to and result from biological weathering a combination of chemical, biological, mineralogical, and computational techniques and methodologies is needed. This complex array of methodologies includes bulk techniques, such as determination of total dissolved organic and inorganic carbon and nitrogen, ion chromatography and high performance liquid chromatography to characterize amount and composition of exuded organic acids, inductively coupled plasma mass spectrometry to determine concentrations of lithogenic elements in solution, X-ray diffraction to characterize changes in mineral composition of the material, DNA extraction to characterize community structure, as well as microscopic techniques. These techniques in combination with numerical geochemical modeling are being employed to improve our understanding of biological weathering.

Numerical simulation of tornadoes' meteorological conditions over Greece: A case study of tornadic activity over NW Peloponnese on March 25, 2009

NASA Astrophysics Data System (ADS)

Matsangouras, Ioannis T.; Nastos, Panagiotis T.; Pytharoulis, Ioannis

2014-05-01

Recent research revealed that NW Peloponnese, Greece is an area that favours pre-frontal tornadic incidence. This study presents the results of the synoptic analysis of the meteorological conditions during a tornado event over NW Peloponnese on March 25, 2009. Further, the role of topography in tornado genesis is examined. The tornado was formed approximately at 10:30 UTC, south-west of Vardas village, crossed the Nea Manolada and faded away at Lappas village, causing several damage. The length of its track was approximately 9-10 km and this tornado was characterized as F2 (Fujita scale) or T4-T5 in TORRO intensity scale. Synoptic analysis was based on ECMWF datasets, as well as on daily composite mean and anomaly of the geopotential heights at the middle and lower troposphere from NCEP/NCAR reanalysis. In addition, numerous datasets derived from weather observations and remote sensing were used in order to interpret better the examined extreme event. Finally, a numerical simulation was performed using the non-hydrostatic Weather Research and Forecasting model (WRF), initialized with ECMWF gridded analyses, with telescoping nested grids that allow the representation of atmospheric circulations ranging from the synoptic scale down to the meso-scale. In the numerical simulations the topography of the inner grid was modified by: a) 0% (actual topography) and b) -100% (without topography).

Robust Engineering Designs for Infrastructure Adaptation to a Changing Climate

NASA Astrophysics Data System (ADS)

Samaras, C.; Cook, L.

2015-12-01

Infrastructure systems are expected to be functional, durable and safe over long service lives - 50 to over 100 years. Observations and models of climate science show that greenhouse gas emissions resulting from human activities have changed climate, weather and extreme events. Projections of future changes (albeit with uncertainties caused by inadequacies of current climate/weather models) can be made based on scenarios for future emissions, but actual future emissions are themselves uncertain. Most current engineering standards and practices for infrastructure assume that the probabilities of future extreme climate and weather events will match those of the past. Climate science shows that this assumption is invalid, but is unable, at present, to define these probabilities over the service lives of existing and new infrastructure systems. Engineering designs, plans, and institutions and regulations will need to be adaptable for a range of future conditions (conditions of climate, weather and extreme events, as well as changing societal demands for infrastructure services). For their current and future projects, engineers should: Involve all stakeholders (owners, financers, insurance, regulators, affected public, climate/weather scientists, etc.) in key decisions; Use low regret, adaptive strategies, such as robust decision making and the observational method, comply with relevant standards and regulations, and exceed their requirements where appropriate; Publish design studies and performance/failure investigations to extend the body of knowledge for advancement of practice. The engineering community should conduct observational and modeling research with climate/weather/social scientists and the concerned communities and account rationally for climate change in revised engineering standards and codes. This presentation presents initial research on decisionmaking under uncertainty for climate resilient infrastructure design.

Modeling AWSoM CMEs with EEGGL: A New Approach for Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Jin, M.; Manchester, W.; van der Holst, B.; Sokolov, I.; Toth, G.; Vourlidas, A.; de Koning, C. A.; Gombosi, T. I.

2015-12-01

The major source of destructive space weather is coronal mass ejections (CMEs). However, our understanding of CMEs and their propagation in the heliosphere is limited by the insufficient observations. Therefore, the development of first-principals numerical models plays a vital role in both theoretical investigation and providing space weather forecasts. Here, we present results of the simulation of CME propagation from the Sun to 1AU by combining the analytical Gibson & Low (GL) flux rope model with the state-of-art solar wind model AWSoM. We also provide an approach for transferring this research model to a space weather forecasting tool by demonstrating how the free parameters of the GL flux rope can be prescribed based on remote observations via the new Eruptive Event Generator by Gibson-Low (EEGGL) toolkit. This capability allows us to predict the long-term evolution of the CME in interplanetary space. We perform proof-of-concept case studies to show the capability of the model to capture physical processes that determine CME evolution while also reproducing many observed features both in the corona and at 1 AU. We discuss the potential and limitations of this model as a future space weather forecasting tool.

Activity of Science and Operational Research of NICT Space Weather

NASA Astrophysics Data System (ADS)

Ishii, Mamoru; Nagatsuma, Tsutomu; Watari, Shinichi; Shinagawa, Hiroyuki; Tsugawa, Takuya; Kubo, Yuki

Operational space weather forecast is for contribution to social infrastructure than for academic interests. These user need will determine the target of research, e.g., the precision level, spatial and temporal resolution and/or required lead time. We, NICT, aim two target in the present mid-term strategic plan, which are (1) forecast of ionospheric disturbance influencing to satellite positioning, and (2) forecast of disturbance in radiation belt influencing to satellite operation. We have our own observation network and develop empirical and numerical models for achieving each target. However in actual situation, it is much difficult to know the user needs quantitatively. Most of space weather phenomena makes the performance of social infrastructure poor, for example disconnect of HF communication, increase of GNSS error. Most of organizations related to these operation are negative to open these information. We have personal interviews to solve this issue. In this interview, we try to collect incident information related to space weather in each field, and to retrieve which space weather information is necessary for users. In this presentation we will introduce our research and corresponding new service, in addition to our recent scientific results.

Weather Effects on Crop Diseases in Eastern Germany

NASA Astrophysics Data System (ADS)

Conradt, Tobias

2017-04-01

Since the 1970s there are several long-term monitoring programmes for plant diseases and pests in Germany. Within the framework of a national research project, some otherwise confidential databases comprising 77 111 samples from numerous sites accross Eastern Germany could be accessed and analysed. The pest data covered leaf rust (Puccinia triticina) and powdery mildew (Blumeria graminis) in winter wheat, aphids (Aphididae, four genera) on wheat and other cereal crops, late blight (Phytophthora infestans) in potatoes, and pollen beetles (Brassicogethes aeneus) on rape. These data were complemented by daily weather observations from the German Weather Service (DWD). In a first step, Pearson correlations between weather variables and pest frequencies were calculated for seasonal time periods of different start months and durations and ordered into so-called correlograms. This revealed principal weather effects on disease spread - e. g. that wind is favourable for mildew throughout the year or that rape pollen beetles like it warm, but not during wintertime. Secondly, the pest frequency samples were found to resemble gamma distributions, and a generalised linear model was fitted to describe their parameter shift depending on end-of-winter temperatures for aphids on cereals. The method clearly shows potential for systematic pest risk assessments regarding climate change.

Automated shock detection and analysis algorithm for space weather application

NASA Astrophysics Data System (ADS)

Vorotnikov, Vasiliy S.; Smith, Charles W.; Hu, Qiang; Szabo, Adam; Skoug, Ruth M.; Cohen, Christina M. S.

2008-03-01

Space weather applications have grown steadily as real-time data have become increasingly available. Numerous industrial applications have arisen with safeguarding of the power distribution grids being a particular interest. NASA uses short-term and long-term space weather predictions in its launch facilities. Researchers studying ionospheric, auroral, and magnetospheric disturbances use real-time space weather services to determine launch times. Commercial airlines, communication companies, and the military use space weather measurements to manage their resources and activities. As the effects of solar transients upon the Earth's environment and society grow with the increasing complexity of technology, better tools are needed to monitor and evaluate the characteristics of the incoming disturbances. A need is for automated shock detection and analysis methods that are applicable to in situ measurements upstream of the Earth. Such tools can provide advance warning of approaching disturbances that have significant space weather impacts. Knowledge of the shock strength and speed can also provide insight into the nature of the approaching solar transient prior to arrival at the magnetopause. We report on efforts to develop a tool that can find and analyze shocks in interplanetary plasma data without operator intervention. This method will run with sufficient speed to be a practical space weather tool providing useful shock information within 1 min of having the necessary data to ground. The ability to run without human intervention frees space weather operators to perform other vital services. We describe ways of handling upstream data that minimize the frequency of false positive alerts while providing the most complete description of approaching disturbances that is reasonably possible.

Impact of atmospheric CO2 levels on continental silicate weathering

NASA Astrophysics Data System (ADS)

Beaulieu, E.; GoddéRis, Y.; Labat, D.; Roelandt, C.; Oliva, P.; Guerrero, B.

2010-07-01

Anthropogenic sources are widely accepted as the dominant cause for the increase in atmospheric CO2 concentrations since the beginning of the industrial revolution. Here we use the B-WITCH model to quantify the impact of increased CO2 concentrations on CO2 consumption by weathering of continental surfaces. B-WITCH couples a dynamic biogeochemistry model (LPJ) and a process-based numerical model of continental weathering (WITCH). It allows simultaneous calculations of the different components of continental weathering fluxes, terrestrial vegetation dynamics, and carbon and water fluxes. The CO2 consumption rates are estimated at four different atmospheric CO2 concentrations, from 280 up to 1120 ppmv, for 22 sites characterized by silicate lithologies (basalt, granite, or sandstones). The sensitivity to atmospheric CO2 variations is explored, while temperature and rainfall are held constant. First, we show that under 355 ppmv of atmospheric CO2, B-WITCH is able to reproduce the global pattern of weathering rates as a function of annual runoff, mean annual temperature, or latitude for silicate lithologies. When atmospheric CO2 increases, evapotranspiration generally decreases due to progressive stomatal closure, and the soil CO2 pressure increases due to enhanced biospheric productivity. As a result, vertical drainage and soil acidity increase, promoting CO2 consumption by mineral weathering. We calculate an increase of about 3% of the CO2 consumption through silicate weathering (mol ha-1 yr-1) for 100 ppmv rise in CO2. Importantly, the sensitivity of the weathering system to the CO2 rise is not uniform and heavily depends on the climatic, lithologic, pedologic, and biospheric settings.

Estimating the effects of extreme weather on transportation infrastructure.

DOT National Transportation Integrated Search

2016-12-01

Climate change, already taking place, is expected to become more pronounced in the future. Current damage assessment models for extreme weather events, such as FEMAs Hazus, do not take the full impact to transportation systems into consideration. ...

Improving the health forecasting alert system for cold weather and heat-waves in England: a case-study approach using temperature-mortality relationships

NASA Astrophysics Data System (ADS)

Masato, Giacomo; Cavany, Sean; Charlton-Perez, Andrew; Dacre, Helen; Bone, Angie; Carmicheal, Katie; Murray, Virginia; Danker, Rutger; Neal, Rob; Sarran, Christophe

2015-04-01

The health forecasting alert system for cold weather and heatwaves currently in use in the Cold Weather and Heatwave plans for England is based on 5 alert levels, with levels 2 and 3 dependent on a forecast or actual single temperature action trigger. Epidemiological evidence indicates that for both heat and cold, the impact on human health is gradual, with worsening impact for more extreme temperatures. The 60% risk of heat and cold forecasts used by the alerts is a rather crude probabilistic measure, which could be substantially improved thanks to the state-of-the-art forecast techniques. In this study a prototype of a new health forecasting alert system is developed, which is aligned to the approach used in the Met Office's (MO) National Severe Weather Warning Service (NSWWS). This is in order to improve information available to responders in the health and social care system by linking temperatures more directly to risks of mortality, and developing a system more coherent with other weather alerts. The prototype is compared to the current system in the Cold Weather and Heatwave plans via a case-study approach to verify its potential advantages and shortcomings. The prototype health forecasting alert system introduces an "impact vs likelihood matrix" for the health impacts of hot and cold temperatures which is similar to those used operationally for other weather hazards as part of the NSWWS. The impact axis of this matrix is based on existing epidemiological evidence, which shows an increasing relative risk of death at extremes of outdoor temperature beyond a threshold which can be identified epidemiologically. The likelihood axis is based on a probability measure associated with the temperature forecast. The new method is tested for two case studies (one during summer 2013, one during winter 2013), and compared to the performance of the current alert system. The prototype shows some clear improvements over the current alert system. It allows for a much greater degree of flexibility, provides more detailed regional information about the health risks associated with periods of extreme temperatures, and is more coherent with other weather alerts which may make it easier for front line responders to use. It will require validation and engagement with stakeholders before it can be considered for use.

RAMSES: a nowcasting system for mitigating geo-hydrological risk along the railway

NASA Astrophysics Data System (ADS)

Gabriele, Salvatore; Terranova, Oreste G.; Pascale, Stefania; Rago, Valeria; Chiaravalloti, Francesco; Sabatino, Pietro; Brocca, Luca; Laviola, Sante; Baldini, Luca; Federico, Stefano; Miglietta, Mario M.; Marra, Gian Paolo; Niccoli, Raffaele; Arcuri, Salvatore; Catalano, Filippo; Stassi, Sergio; Baccillieri, Maurizio; Agostino, Mario; Iovine, Giulio G. R.

2016-04-01

In recent years, a number of exceptional rainfall events of short / very short duration (from 15 minutes to about 2 hours) caused incidents and service interruptions due to landslides, collapses of bridges, and erosion of the ballast, along the Calabrian railway. RAMSES (RAilway Meteorological SEcurity System) is a pilot CNR project, recently co-funded by RFI S.p.A. and aimed at mitigating the risk along the railway. Forecasting of weather events responsible of heavy convective rainfall, even when provided with some advance, is not generally performed with reliable localization. In fact, objective limits of the numerical weather prediction derive from grid resolution, often exceeding the size of convective cells. These phenomena, whose recurrence periods seem to show a reduction due to climate changes, affect limited areas and are characterized by a very short life cycle. As a consequence, failures of hydraulic crossings are increasingly being recorded together with landslide-related debris invasion along the drainage network and slopes. RAMSES aims at improving short term (3-6 hours) weather forecasts and ground effects at local scale. The employed approach is base on synergistic and integrated operational tools to provide weather information on small-size basins. The system will also allow to promptly identify and track the short-term evolution (15-60 min) of convective cells, by means of imaging techniques based on quasi-real time radar and Meteosat data. The extension of the temporal horizon of the forecast up to three hours will be performed by using the Local Analysis and Prediction System (LAPS) model. This latter employs, as a "first guess", the output of the WRF numerical model: such analyses are updated and improved by means of observational data from different instruments (e.g. on land weather stations, radar, satellites, etc.). Finally, the assessment of ground effects will be accomplished for selected study areas, by means of landslide susceptibility mapping combined with hydrological, rainfall-runoff and hydraulic flow modeling.

Preparing for Operational Use of High Priority Products from the Joint Polar Satellite System (JPSS) in Numerical Weather Prediction

NASA Astrophysics Data System (ADS)

Nandi, S.; Layns, A. L.; Goldberg, M.; Gambacorta, A.; Ling, Y.; Collard, A.; Grumbine, R. W.; Sapper, J.; Ignatov, A.; Yoe, J. G.

2017-12-01

This work describes end to end operational implementation of high priority products from National Oceanic and Atmospheric Administration's (NOAA) operational polar-orbiting satellite constellation, to include Suomi National Polar-orbiting Partnership (S-NPP) and the Joint Polar Satellite System series initial satellite (JPSS-1), into numerical weather prediction and earth systems models. Development and evaluation needed for the initial implementations of VIIRS Environmental Data Records (EDR) for Sea Surface Temperature ingestion in the Real-Time Global Sea Surface Temperature Analysis (RTG) and Polar Winds assimilated in the National Weather Service (NWS) Global Forecast System (GFS) is presented. These implementations ensure continuity of data in these models in the event of loss of legacy sensor data. Also discussed is accelerated operational implementation of Advanced Technology Microwave Sounder (ATMS) Temperature Data Records (TDR) and Cross-track Infrared Sounder (CrIS) Sensor Data Records, identified as Key Performance Parameters by the National Weather Service. Operational use of SNPP after 28 October, 2011 launch took more than one year due to the learning curve and development needed for full exploitation of new remote sensing capabilities. Today, ATMS and CrIS data positively impact weather forecast accuracy. For NOAA's JPSS initial satellite (JPSS-1), scheduled for launch in late 2017, we identify scope and timelines for pre-launch and post-launch activities needed to efficiently transition these capabilities into operations. As part of these alignment efforts, operational readiness for KPPs will be possible as soon as 90 days after launch. The schedule acceleration is possible because of the experience with S-NPP. NOAA operational polar-orbiting satellite constellation provides continuity and enhancement of earth systems observations out to 2036. Program best practices and lessons learned will inform future implementation for follow-on JPSS-3 and -4 missions ensuring benefits and enhancements during the system's design life.

Space Weather Models at the CCMC And Their Capabilities

NASA Technical Reports Server (NTRS)

Hesse, Michael; Rastatter, Lutz; MacNeice, Peter; Kuznetsova, Masha

2007-01-01

The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second focus of CCMC activities is on validation and verification of space weather models, and on the transition of appropriate models to space weather forecast centers. As part of the latter activity, the CCMC develops real-time simulation systems that stress models through routine execution. A by-product of these real-time calculations is the ability to derive model products, which may be useful for space weather operators. In this presentation, we will provide an overview of the community-provided, space weather-relevant, model suite, which resides at CCMC. We will discuss current capabilities, and analyze expected future developments of space weather related modeling.

Quantitative Precipitation Nowcasting: A Lagrangian Pixel-Based Approach

DTIC Science & Technology

2012-01-01

Sorooshian, T. Bellerby, and G. Huffman, 2010: REFAME: Rain Estimation Using Forward-Adjusted Advection of Microwave Estimates. J. of Hydromet ., 11...precipitation forecasting using information from radar and Numerical Weather Prediction models. J. of Hydromet ., 4(6):1168-1180. Germann, U., and I

Meteorological Processes Affecting Air Quality – Research and Model Development Needs

EPA Science Inventory

Meteorology modeling is an important component of air quality modeling systems that defines the physical and dynamical environment for atmospheric chemistry. The meteorology models used for air quality applications are based on numerical weather prediction models that were devel...

Spatio-temporal modelling for assessing air pollution in Santiago de Chile

NASA Astrophysics Data System (ADS)

Nicolis, Orietta; Camaño, Christian; Mařın, Julio C.; Sahu, Sujit K.

2017-01-01

In this work, we propose a space-time approach for studying the PM2.5 concentration in the city of Santiago de Chile. In particular, we apply the autoregressive hierarchical model proposed by [1] using the PM2.5 observations collected by a monitoring network as a response variable and numerical weather forecasts from the Weather Research and Forecasting (WRF) model as covariate together with spatial and temporal (periodic) components. The approach is able to provide short-term spatio-temporal predictions of PM2.5 concentrations on a fine spatial grid (at 1km × 1km horizontal resolution.)

Strategies for Near Real Time Estimation of Precipitable Water Vapor

NASA Technical Reports Server (NTRS)

Bar-Sever, Yoaz E.

1996-01-01

Traditionally used for high precision geodesy, the GPS system has recently emerged as an equally powerful tool in atmospheric studies, in particular, climatology and meteorology. There are several products of GPS-based systems that are of interest to climatologists and meteorologists. One of the most useful is the GPS-based estimate of the amount of Precipitable Water Vapor (PWV) in the troposphere. Water vapor is an important variable in the study of climate changes and atmospheric convection (Yuan et al., 1993), and is of crucial importance for severe weather forecasting and operational numerical weather prediction (Kuo et al., 1993).

Overview of NASA MSFC and UAH Space Weather Modeling and Data Efforts

NASA Technical Reports Server (NTRS)

Parker, Linda Neergaard

2016-01-01

Marshall Space Flight Center, along with its industry and academia neighbors, has a long history of space environment model development and testing. Space weather efforts include research, testing, model development, environment definition, anomaly investigation, and operational support. This presentation will highlight a few of the current space weather activities being performed at Marshall and through collaborative efforts with University of Alabama in Huntsville scientists.

Issues Involved in the Development of an Open Standard for Data Link of Aviation Weather Information

NASA Technical Reports Server (NTRS)

Grappel, R. D.

2000-01-01

This paper describes how an effective and efficient data link system for the dissemination of aviation weather information could be constructed. The system is built upon existing 'open standard' foundations drawn from current aviation and computer technologies. Issues of communications protocols and application data formats are discussed. The proposed aviation weather data link system is dependent of the actual link mechanism selected.

Recent Progress of Solar Weather Forecasting at Naoc

NASA Astrophysics Data System (ADS)

He, Han; Wang, Huaning; Du, Zhanle; Zhang, Liyun; Huang, Xin; Yan, Yan; Fan, Yuliang; Zhu, Xiaoshuai; Guo, Xiaobo; Dai, Xinghua

The history of solar weather forecasting services at National Astronomical Observatories, Chinese Academy of Sciences (NAOC) can be traced back to 1960s. Nowadays, NAOC is the headquarters of the Regional Warning Center of China (RWC-China), which is one of the members of the International Space Environment Service (ISES). NAOC is responsible for exchanging data, information and space weather forecasts of RWC-China with other RWCs. The solar weather forecasting services at NAOC cover short-term prediction (within two or three days), medium-term prediction (within several weeks), and long-term prediction (in time scale of solar cycle) of solar activities. Most efforts of the short-term prediction research are concentrated on the solar eruptive phenomena, such as flares, coronal mass ejections (CMEs) and solar proton events, which are the key driving sources of strong space weather disturbances. Based on the high quality observation data of the latest space-based and ground-based solar telescopes and with the help of artificial intelligence techniques, new numerical models with quantitative analyses and physical consideration are being developed for the predictions of solar eruptive events. The 3-D computer simulation technology is being introduced for the operational solar weather service platform to visualize the monitoring of solar activities, the running of the prediction models, as well as the presenting of the forecasting results. A new generation operational solar weather monitoring and forecasting system is expected to be constructed in the near future at NAOC.

Sources and Uses of Weather Information for Agricultural Decision Makers.

NASA Astrophysics Data System (ADS)

McNew, Kevin P.; Mapp, Harry P.; Duchon, Claude E.; Merritt, Earl S.

1991-04-01

Numerous studies have examined the importance of weather information to farmers and ranchers across the U.S. This study is focused on the kinds of weather information received by farmers and ranchers, the sources of that information, and its use in production and marketing decisions. Our results are based on a survey of 292 producers from the principal agricultural areas of Oklahoma. Producers were classified into five categories related to their source of income from crop and livestock sales.Among temperature, precipitation, relative humility, and wind speed, temperature information was most widely received. Forecast lengths of highest interest were 24-h and 5-day forecasts. Precipitation information was used by many respondents for planting and harvesting decisions. Weather data and forecasts seem to be of greater value to diversified crop and livestock operators than specialized crop and livestock, perhaps due to more frequent timing decisions. Relative humility and wind information appear to be important especially during specific times of the growing season, for example, at harvest time and time of pesticide application. Television is the primary source of weather information for more than 60% of the producers.It appears that there may be a role for both public and private entities in transforming weather data and forecasts into recommendations to crop and livestock producers. Further research is needed to determine the potential value of weather information for alternative production, marketing and livestock decisions, different categories of producers, and different geographic regions.

Space Weather Studies at Istanbul Technical University

NASA Astrophysics Data System (ADS)

Kaymaz, Zerefsan

2016-07-01

This presentation will introduce the Upper Atmosphere and Space Weather Laboratory of Istanbul Technical University (ITU). It has been established to support the educational needs of the Faculty of Aeronautics and Astronautics in 2011 to conduct scientific research in Space Weather, Space Environment, Space Environment-Spacecraft Interactions, Space instrumentation and Upper Atmospheric studies. Currently the laboratory has some essential infrastructure and the most instrumentation for ionospheric observations and ground induced currents from the magnetosphere. The laboratory has two subunits: SWIFT dealing with Space Weather Instrumentation and Forecasting unit and SWDPA dealing with Space Weather Data Processing and Analysis. The research area covers wide range of upper atmospheric and space science studies from ionosphere, ionosphere-magnetosphere coupling, magnetic storms and magnetospheric substorms, distant magnetotail, magnetopause and bow shock studies, as well as solar and solar wind disturbances and their interaction with the Earth's space environment. We also study the spacecraft environment interaction and novel plasma instrument design. Several scientific projects have been carried out in the laboratory. Operational objectives of our laboratory will be carried out with the collaboration of NASA's Space Weather Laboratory and the facilities are in the process of integration to their prediction services. Educational and research objectives, as well as the examples from the research carried out in our laboratory will be demonstrated in this presentation.

Space Weather Modeling at the Community Coordinated Modeling Center

NASA Technical Reports Server (NTRS)

Hesse M.

2005-01-01

The Community Coordinated Modeling Center (CCMC) is a multi-agency partnership, which aims at the creation of next generation space weather models. The goal of the CCMC is to support the research and developmental work necessary to substantially increase the present-day modeling capability for space weather purposes, and to provide models for transition to the rapid prototyping centers at the space weather forecast centers. This goal requires dose collaborations with and substantial involvement of the research community. The physical regions to be addressed by CCMC-related activities range from the solar atmosphere to the Earth's upper atmosphere. The CCMC is an integral part of the National Space Weather Program Implementation Plan, of NASA's Living With a Star (LWS) initiative, and of the Department of Defense Space Weather Transition Plan. CCMC includes a facility at NASA Goddard Space Flight Center, as well as distributed computing facilities provided by the US Air Force. CCMC also provides, to the research community, access to state-of-the-art space research models. In this paper we will provide updates on CCMC status, on current plans, research and development accomplishments and goals, and on the model testing and validation process undertaken as part of the CCMC mandate. Special emphasis will be on solar and heliospheric models currently residing at CCMC, and on plans for validation and verification.

Improved Use of Satellite Imagery to Forecast Hurricanes

NASA Technical Reports Server (NTRS)

Louis, Jean-Francois

2001-01-01

This project tested a novel method that uses satellite imagery to correct phase errors in the initial state for numerical weather prediction, applied to hurricane forecasts. The system was tested on hurricanes Guillermo (1997), Felicia (1997) and Iniki (1992). We compared the performance of the system with and without phase correction to a procedure that uses bogus data in the initial state, similar to current operational procedures. The phase correction keeps the hurricane on track in the analysis and is far superior to a system without phase correction. Compared to operational procedure, phase correction generates somewhat worse 3-day forecast of the hurricane track, but better forecast of intensity. It is believed that the phase correction module would work best in the context of 4-dimensional variational data assimilation. Very little modification to 4DVar would be required.

A Geosynchronous Lidar System for Atmospheric Winds and Moisture Measurements

NASA Technical Reports Server (NTRS)

Emmitt, G. D.

2001-01-01

An observing system comprised of two lidars in geosychronous orbit would enable the synoptic and meso-scale measurement of atmospheric winds and moisture both of which are key first-order variables of the Earth's weather equation. Simultaneous measurement of these parameters at fast revisit rates promises large advancements in our weather prediction skills. Such capabilities would be unprecedented and a) yield greatly improved and finer resolution initial conditions for models, b) make existing costly and cumbersome measurement approaches obsolete, and c) obviate the use of numerical techniques needed to correct data obtained using present observing systems. Additionally, simultaneous synoptic wind and moisture observations would lead to improvements in model parameterizations, and in our knowledge of small-scale weather processes. Technology and science data product assessments are ongoing. Results will be presented during the conference.

Innovative Near Real-Time Data Dissemination Tools Developed by the Space Weather Research Center

NASA Astrophysics Data System (ADS)

Mullinix, R.; Maddox, M. M.; Berrios, D.; Kuznetsova, M.; Pulkkinen, A.; Rastaetter, L.; Zheng, Y.

2012-12-01

Space weather affects virtually all of NASA's endeavors, from robotic missions to human exploration. Knowledge and prediction of space weather conditions are therefore essential to NASA operations. The diverse nature of currently available space environment measurements and modeling products compels the need for a single access point to such information. The Integrated Space Weather Analysis (iSWA) System provides this single point access along with the capability to collect and catalog a vast range of sources including both observational and model data. NASA Goddard Space Weather Research Center heavily utilizes the iSWA System daily for research, space weather model validation, and forecasting for NASA missions. iSWA provides the capabilities to view and analyze near real-time space weather data from any where in the world. This presentation will describe the technology behind the iSWA system and describe how to use the system for space weather research, forecasting, training, education, and sharing.

Implications of Automotive and Trucking On-Board Information Systems for General Aviation Cockpit Weather Systems

NASA Technical Reports Server (NTRS)

Sireli, Yesim; Kauffmann, Paul; Gupta, Surabhi; Kachroo, Pushkin

2002-01-01

In this study, current characteristics and future developments of Intelligent Transportation Systems (ITS) in the automobile and trucking industry are investigated to identify the possible implications of such systems for General Aviation (GA) cockpit weather systems. First, ITS are explained based on tracing their historical development in various countries. Then, current systems and the enabling communication technologies are discussed. Finally, a market analysis for GA is included.

Verification of the skill of numerical weather prediction models in forecasting rainfall from U.S. landfalling tropical cyclones

NASA Astrophysics Data System (ADS)

Luitel, Beda; Villarini, Gabriele; Vecchi, Gabriel A.

2018-01-01

The goal of this study is the evaluation of the skill of five state-of-the-art numerical weather prediction (NWP) systems [European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC)] in forecasting rainfall from North Atlantic tropical cyclones (TCs). Analyses focus on 15 North Atlantic TCs that made landfall along the U.S. coast over the 2007-2012 period. As reference data we use gridded rainfall provided by the Climate Prediction Center (CPC). We consider forecast lead-times up to five days. To benchmark the skill of these models, we consider rainfall estimates from one radar-based (Stage IV) and four satellite-based [Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA, both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); the CPC MORPHing Technique (CMORPH)] rainfall products. Daily and storm total rainfall fields from each of these remote sensing products are compared to the reference data to obtain information about the range of errors we can expect from "observational data." The skill of the NWP models is quantified: (1) by visual examination of the distribution of the errors in storm total rainfall for the different lead-times, and numerical examination of the first three moments of the error distribution; (2) relative to climatology at the daily scale. Considering these skill metrics, we conclude that the NWP models can provide skillful forecasts of TC rainfall with lead-times up to 48 h, without a consistently best or worst NWP model.

Numerical simulation of raindrop scattering for C-band dual-polarization Doppler weather radar parameters

NASA Astrophysics Data System (ADS)

Teng, Shiwen; Hu, Hanfeng; Liu, Chao; Hu, Fangchao; Wang, Zhenhui; Yin, Yan

2018-07-01

The dual-polarization Doppler weather radar plays an important role in precipitation estimation and weather monitoring. For radar applications, the retrieval of precipitation microphysical characteristics is of great importance, and requires assumed scattering properties of raindrops. This study numerically investigates the scattering properties of raindrops and considers the capability of numerical models for raindrop scattering simulations. Besides the widely used spherical and oblate spheroid models, a non-spheroidal model based on realistic raindrop geometries with a flattened base and a smoothly rounded top is also considered. To study the effects of scattering simulations on radar applications, the polarization radar parameters are modeled based on the scattering properties calculated by different scattering models (i.e. the extended boundary condition T-matrix (EBCM) method and discretize dipole approximation (DDA)) and given size distributions, and compared with observations of a C-band dual-polarization radar. Note that, when the spatial resolution of the DDA simulation is large enough, the DDA results can be very close to those of the EBCM. Most simulated radar variables, except copolar correlation coefficient, match closely with radar observations, and the results based on different non-spheroidal models considered in this study show little differences. The comparison indicates that, even for the C-band radar, the effects of raindrop shape and canting angle on scattering properties are relatively minor due to relatively small size parameters. However, although more realistic particle geometry model may provide better representation on raindrop shape, considering the relatively time-consuming and complex scattering simulations for those particles, the oblate spheroid model with appropriate axis ratio variation is suggested for polarization radar applications.

A Review and Reflections on the Sun-Climate Connection

NASA Technical Reports Server (NTRS)

Goldberg, Richard A.

1990-01-01

The field of sun-climate is beset with an extraordinary number of numerical correlations attempting to relate various periodicities of solar activity with changes in the Earth's weather and climate. Signatures representing climatological variability have been sought for cycles as short as the solar 28-day rotational period up to Milankovich periods of thousands of years, although a majority of correlations have concentrated on the 11-year sunspot and 22-year Hale double sunspot cycles. For the shorter term, parameters including temperature, pressure, winds storm tracks, rainfall, and water levels in rivers and lakes, etc. have been correlated with solar variability. For longer periods, it has been necessary to seek more indirect evidence in ice cores, tree rings, and geologic deep sea cores. Other atmospheric parameters relating to atmospheric electricity and the global electric circuit have also been correlated in similar fashion. Unfortunately, few, if any, of this wide spectrum of numerical correlations have been associated with any viable physical explanation, making most studies in the field an exercise in numerical statistics. More recently, a few suggestions for plausible coupling processes have begun to appear. These, coupled with new and stronger correlations involving selective binning of climatological data sets have injected new life and hope to this field. An overview is given of the historical past and current perspectives, to evaluate possible avenues for defining physical linking processes in the future.

An outline of the review on space weather in Latin America: space science, research networks and space weather center

NASA Astrophysics Data System (ADS)

De Nardin, C. M.; Dasso, S.; Gonzalez-Esparza, A.

2016-12-01

The present work is an outline of a three-part review on space weather in Latin America. The first paper (part 1) comprises the evolution of several Latin American institutions investing in space science since the 1960's, focusing on the solar-terrestrial interactions, which today is commonly called space weather. Despite recognizing advances in space research in all of Latin America, this part 1 is restricted to the development observed in three countries in particular (Argentina, Brazil and Mexico), due to the fact that these countries have recently developed operational centers for monitoring space weather. The review starts with a brief summary of the first groups to start working with space science in Latin America. This first part of the review closes with the current status and the research interests of these groups, which are described in relation to the most significant works and challenges of the next decade in order to aid in the solving of space weather open issues. The second paper (part 2) comprises a summary of scientific challenges in space weather research that are considered to be open scientific questions and how they are being addressed in terms of instrumentation by the international community, including the Latin American groups. We also provide an inventory of the networks and collaborations being constructed in Latin America, including details on the data processing, capabilities and a basic description of the resulting variables. These instrumental networks currently used for space science research are gradually being incorporated into the space weather monitoring data pipelines as their data provides key variables for monitoring and forecasting space weather, which allow these centers to monitor space weather and issue warnings and alerts. The third paper (part 3) presents the decision process for the spinning off of space weather prediction centers from space science groups with our interpretation of the reason/opportunities that leads to this. Lastly, the constraints for the progress in space weather monitoring, research, and forecast are listed with recommendations to overcome them, which we believe will lead to the access of key variables for the monitoring and forecasting space weather, which will allow these centers to better monitor space weather and issue warnings and alerts.

Synopsis of the Review on Space Weather in Latin America: Space Science, Research Networks and Space Weather Center

NASA Astrophysics Data System (ADS)

Denardini, Clezio Marcos; Dasso, Sergio; Gonzalez-Esparza, Americo

2016-07-01

The present work is a synopsis of a three-part review on space weather in Latin America. The first paper (part 1) comprises the evolution of several Latin American institutions investing in space science since the 1960's, focusing on the solar-terrestrial interactions, which today is commonly called space weather. Despite recognizing advances in space research in all of Latin America, this part 1 is restricted to the development observed in three countries in particular (Argentina, Brazil and Mexico), due to the fact that these countries have recently developed operational centers for monitoring space weather. The review starts with a brief summary of the first groups to start working with space science in Latin America. This first part of the review closes with the current status and the research interests of these groups, which are described in relation to the most significant works and challenges of the next decade in order to aid in the solving of space weather open issues. The second paper (part 2) comprises a summary of scientific challenges in space weather research that are considered to be open scientific questions and how they are being addressed in terms of instrumentation by the international community, including the Latin American groups. We also provide an inventory of the networks and collaborations being constructed in Latin America, including details on the data processing, capabilities and a basic description of the resulting variables. These instrumental networks currently used for space science research are gradually being incorporated into the space weather monitoring data pipelines as their data provides key variables for monitoring and forecasting space weather, which allow these centers to monitor space weather and issue warnings and alerts. The third paper (part 3) presents the decision process for the spinning off of space weather prediction centers from space science groups with our interpretation of the reason/opportunities that leads to this. Lastly, the constraints for the progress in space weather monitoring, research, and forecast are listed with recommendations to overcome them, which we believe will lead to the access of key variables for the monitoring and forecasting space weather, which will allow these centers to better monitor space weather and issue warnings and alerts.

A Real-time 3D Visualization of Global MHD Simulation for Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Murata, K.; Matsuoka, D.; Kubo, T.; Shimazu, H.; Tanaka, T.; Fujita, S.; Watari, S.; Miyachi, H.; Yamamoto, K.; Kimura, E.; Ishikura, S.

2006-12-01

Recently, many satellites for communication networks and scientific observation are launched in the vicinity of the Earth (geo-space). The electromagnetic (EM) environments around the spacecraft are always influenced by the solar wind blowing from the Sun and induced electromagnetic fields. They occasionally cause various troubles or damages, such as electrification and interference, to the spacecraft. It is important to forecast the geo-space EM environment as well as the ground weather forecasting. Owing to the recent remarkable progresses of super-computer technologies, numerical simulations have become powerful research methods in the solar-terrestrial physics. For the necessity of space weather forecasting, NICT (National Institute of Information and Communications Technology) has developed a real-time global MHD simulation system of solar wind-magnetosphere-ionosphere couplings, which has been performed on a super-computer SX-6. The real-time solar wind parameters from the ACE spacecraft at every one minute are adopted as boundary conditions for the simulation. Simulation results (2-D plots) are updated every 1 minute on a NICT website. However, 3D visualization of simulation results is indispensable to forecast space weather more accurately. In the present study, we develop a real-time 3D webcite for the global MHD simulations. The 3-D visualization results of simulation results are updated every 20 minutes in the following three formats: (1)Streamlines of magnetic field lines, (2)Isosurface of temperature in the magnetosphere and (3)Isoline of conductivity and orthogonal plane of potential in the ionosphere. For the present study, we developed a 3-D viewer application working on Internet Explorer browser (ActiveX) is implemented, which was developed on the AVS/Express. Numerical data are saved in the HDF5 format data files every 1 minute. Users can easily search, retrieve and plot past simulation results (3D visualization data and numerical data) by using the STARS (Solar-terrestrial data Analysis and Reference System). The STARS is a data analysis system for satellite and ground-based observation data for solar-terrestrial physics.

MISTiC Winds, a Micro-Satellite Constellation Approach to High Resolution Observations of the Atmosphere Using Infrared Sounding and 3D Winds Measurements

NASA Technical Reports Server (NTRS)

Maschhoff, K. R.; Polizotti, J. J.; Aumann, H. H.; Susskind, J.

2016-01-01

MISTiC(TM) Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiCs extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sunsynchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's AIRS that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenasat much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key remaining technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is statistical forecasting futile?

NASA Astrophysics Data System (ADS)

Singh, Jitendra; Sekharan, Sheeba; Karmakar, Subhankar; Ghosh, Subimal; Zope, P. E.; Eldho, T. I.

2017-04-01

Mumbai, the commercial and financial capital of India, experiences incessant annual rain episodes, mainly attributable to erratic rainfall pattern during monsoons and urban heat-island effect due to escalating urbanization, leading to increasing vulnerability to frequent flooding. After the infamous episode of 2005 Mumbai torrential rains when only two rain gauging stations existed, the governing civic body, the Municipal Corporation of Greater Mumbai (MCGM) came forward with an initiative to install 26 automatic weather stations (AWS) in June 2006 (MCGM 2007), which later increased to 60 AWS. A comprehensive statistical analysis to understand the spatio-temporal pattern of rainfall over Mumbai or any other coastal city in India has never been attempted earlier. In the current study, a thorough analysis of available rainfall data for 2006-2014 from these stations was performed; the 2013-2014 sub-hourly data from 26 AWS was found useful for further analyses due to their consistency and continuity. Correlogram cloud indicated no pattern of significant correlation when we considered the closest to the farthest gauging station from the base station; this impression was also supported by the semivariogram plots. Gini index values, a statistical measure of temporal non-uniformity, were found above 0.8 in visible majority showing an increasing trend in most gauging stations; this sufficiently led us to conclude that inconsistency in daily rainfall was gradually increasing with progress in monsoon. Interestingly, night rainfall was lesser compared to daytime rainfall. The pattern-less high spatio-temporal variation observed in Mumbai rainfall data signifies the futility of independently applying advanced statistical techniques, and thus calls for simultaneous inclusion of physics-centred models such as different meso-scale numerical weather prediction systems, particularly the Weather Research and Forecasting (WRF) model.

MISTiC Winds, a Micro-Satellite Constellation Approach to High Resolution Observations of the Atmosphere using Infrared Sounding and 3D Winds Measurements

NASA Astrophysics Data System (ADS)

Maschhoff, K. R.; Polizotti, J. J.; Susskind, J.; Aumann, H. H.

2015-12-01

MISTiCTM Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiC's extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sun-synchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's Atmospheric Infrared Sounder that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenas-at much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

MISTiC Winds: A micro-satellite constellation approach to high resolution observations of the atmosphere using infrared sounding and 3D winds measurements

NASA Astrophysics Data System (ADS)

Maschhoff, K. R.; Polizotti, J. J.; Aumann, H. H.; Susskind, J.

2016-09-01

MISTiCTM Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiC's extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sunsynchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's AIRS that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenas-at much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key remaining technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

Mistic winds, a microsatellite constellation approach to high-resolution observations of the atmosphere using infrared sounding and 3d winds measurements

NASA Astrophysics Data System (ADS)

Maschhoff, K. R.; Polizotti, J. J.; Aumann, H. H.; Susskind, J.

2016-10-01

MISTiC Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiC's extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sunsynchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's AIRS that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenas-at much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key remaining technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.