Visualizing Coastal Erosion, Overwash and Coastal Flooding in New England

NASA Astrophysics Data System (ADS)

Young Morse, R.; Shyka, T.

2017-12-01

Powerful East Coast storms and their associated storm tides and large, battering waves can lead to severe coastal change through erosion and re-deposition of beach sediment. The United States Geological Survey (USGS) has modeled such potential for geological response using a storm-impact scale that compares predicted elevations of hurricane-induced water levels and associated wave action to known elevations of coastal topography. The resulting storm surge and wave run-up hindcasts calculate dynamic surf zone collisions with dune structures using discrete regime categories of; "collision" (dune erosion), "overwash" and "inundation". The National Weather Service (NWS) recently began prototyping this empirical technique under the auspices of the North Atlantic Regional Team (NART). Real-time erosion and inundation forecasts were expanded to include both tropical and extra-tropical cyclones along vulnerable beaches (hotspots) on the New England coast. Preliminary results showed successful predictions of impact during hurricane Sandy and several intense Nor'easters. The forecasts were verified using observational datasets, including "ground truth" reports from Emergency Managers and storm-based, dune profile measurements organized through a Maine Sea Grant partnership. In an effort to produce real-time visualizations of this forecast output, the Northeastern Regional Association of Coastal Ocean Observing Systems (NERACOOS) and the Gulf of Maine Research Institute (GMRI) partnered with NART to create graphical products of wave run-up levels for each New England "hotspot". The resulting prototype system updates the forecasts twice daily and allows users the ability to adjust atmospheric and sea state input into the calculations to account for model errors and forecast uncertainty. This talk will provide an overview of the empirical wave run-up calculations, the system used to produce forecast output and a demonstration of the new web based tool.

Two-Step Forecast of Geomagnetic Storm Using Coronal Mass Ejection and Solar Wind Condition

NASA Technical Reports Server (NTRS)

Kim, R.-S.; Moon, Y.-J.; Gopalswamy, N.; Park, Y.-D.; Kim, Y.-H.

2014-01-01

To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind criteria derived in this study (Bz = -5 nT or Ey = 3 mV/m for t = 2 h for moderate storms with minimum Dst less than -50 nT) (i.e. Magnetic Field Magnitude, B (sub z) less than or equal to -5 nanoTeslas or duskward Electrical Field, E (sub y) greater than or equal to 3 millivolts per meter for time greater than or equal to 2 hours for moderate storms with Minimum Disturbance Storm Time, Dst less than -50 nanoTeslas) and a Dst model developed by Temerin and Li (2002, 2006) (TL [i.e. Temerin Li] model). Using 55 CME-Dst pairs during 1997 to 2003, our solar wind criteria produce slightly better forecasts for 31 storm events (90 percent) than the forecasts based on the TL model (87 percent). However, the latter produces better forecasts for 24 nonstorm events (88 percent), while the former correctly forecasts only 71 percent of them. We then performed the two-step forecast. The results are as follows: (i) for 15 events that are incorrectly forecasted using CME parameters, 12 cases (80 percent) can be properly predicted based on solar wind conditions; (ii) if we forecast a storm when both CME and solar wind conditions are satisfied (n, i.e. cap operator - the intersection set that is comprised of all the elements that are common to both), the critical success index becomes higher than that from the forecast using CME parameters alone, however, only 25 storm events (81 percent) are correctly forecasted; and (iii) if we forecast a storm when either set of these conditions is satisfied (?, i.e. cup operator - the union set that is comprised of all the elements of either or both), all geomagnetic storms are correctly forecasted.

System designed for issuing landslide alerts in the San Francisco Bay area

USGS Publications Warehouse

Finley, D.

1987-01-01

A system for forecasting landslides during major storms has been developed for the San Francisco Bay area by the U.S Geological Survey and was successfully tested during heavy storms in the bay area during February 1986. Based on the forecasts provided by the USGS, the National Weather Service (NWS) included landslide warnings in its regular weather forecasts or in special weather statements transmitted to local radio and television stations and other news media. USGS scientists said the landslide forecasting and warning system for the San Francisco Bay area can be used as a prototype in developing similar systems for other parts of the Nation susceptible to landsliding. Studies show damage from landslides in the United States averages an estimated $1.5 billion per year. 

iFLOOD: A Real Time Flood Forecast System for Total Water Modeling in the National Capital Region

NASA Astrophysics Data System (ADS)

Sumi, S. J.; Ferreira, C.

2017-12-01

Extreme flood events are the costliest natural hazards impacting the US and frequently cause extensive damages to infrastructure, disruption to economy and loss of lives. In 2016, Hurricane Matthew brought severe damage to South Carolina and demonstrated the importance of accurate flood hazard predictions that requires the integration of riverine and coastal model forecasts for total water prediction in coastal and tidal areas. The National Weather Service (NWS) and the National Ocean Service (NOS) provide flood forecasts for almost the entire US, still there are service-gap areas in tidal regions where no official flood forecast is available. The National capital region is vulnerable to multi-flood hazards including high flows from annual inland precipitation events and surge driven coastal inundation along the tidal Potomac River. Predicting flood levels on such tidal areas in river-estuarine zone is extremely challenging. The main objective of this study is to develop the next generation of flood forecast systems capable of providing accurate and timely information to support emergency management and response in areas impacted by multi-flood hazards. This forecast system is capable of simulating flood levels in the Potomac and Anacostia River incorporating the effects of riverine flooding from the upstream basins, urban storm water and tidal oscillations from the Chesapeake Bay. Flood forecast models developed so far have been using riverine data to simulate water levels for Potomac River. Therefore, the idea is to use forecasted storm surge data from a coastal model as boundary condition of this system. Final output of this validated model will capture the water behavior in river-estuary transition zone far better than the one with riverine data only. The challenge for this iFLOOD forecast system is to understand the complex dynamics of multi-flood hazards caused by storm surges, riverine flow, tidal oscillation and urban storm water. Automated system simulations will help to develop a seamless integration with the boundary systems in the service-gap area with new insights into our scientific understanding of such complex systems. A visualization system is being developed to allow stake holders and the community to have access to the flood forecasting for their region with sufficient lead time.

Sources of Wind Variability at a Single Station in Complex Terrain During Tropical Cyclone Passage

DTIC Science & Technology

2013-12-01

Mesoscale Prediction System CPA Closest point of approach ET Extratropical transition FNMOC Fleet Numerical Meteorology and Oceanography Center...forecasts. However, 2 the TC forecast tracks and warnings they issue necessarily focus on the large-scale structure of the storm , and are not...winds at one station. Also, this technique is a storm - centered forecast and even if the grid spacing is on order of one kilometer, it is unlikely

Development of a severe local storm prediction system: A 60-day test of a mesoscale primitive equation model

NASA Technical Reports Server (NTRS)

Paine, D. A.; Zack, J. W.; Kaplan, M. L.

1979-01-01

The progress and problems associated with the dynamical forecast system which was developed to predict severe storms are examined. The meteorological problem of severe convective storm forecasting is reviewed. The cascade hypothesis which forms the theoretical core of the nested grid dynamical numerical modelling system is described. The dynamical and numerical structure of the model used during the 1978 test period is presented and a preliminary description of a proposed multigrid system for future experiments and tests is provided. Six cases from the spring of 1978 are discussed to illustrate the model's performance and its problems. Potential solutions to the problems are examined.

Ocean modelling and Early-Warning System for the Gulf of Thailand

NASA Astrophysics Data System (ADS)

de Lima Rego, Joao; Yan, Kun; Sisomphon, Piyamarn; Thanathanphon, Watin; Twigt, Daniel; Irazoqui Apecechea, Maialen

2017-04-01

Storm surges associated with severe tropical cyclones are among the most hazardous and damaging natural disasters to coastal areas. The Gulf of Thailand (GoT) has been periodically affected by typhoon induced storm surges in the past (e.g. storm Harriet in 1962, storm Gay in 1989 and storm Linda in 1997). Due to increased touristic / economic development and increased population density in the coastal zone, the combined effect and risk of high water level and increased rainfall / river discharge has dramatically increased and are expected to increase in future due to climate change effects. This presentation describes the development and implementation of the first real-time operational storm surge, wave and wave setup forecasting system in the GoT, a joint applied research initiative by Deltares in The Netherlands and the Hydro and Agro Informatics Institute (HAII) in Thailand. The modelling part includes a new hydrodynamic model to simulate tides and storm surges and two wave models (regional and local). The hydrodynamic model is based on Delft3D Flexible Mesh, capable of simulating water levels and detailed flows. The regional and the recently-developed local wave model are based on the SWAN model, a third-generation wave model. The operational platform is based on Delft-FEWS software, which coordinates all the data inputs, the modelling tasks and the automatic forecast exports including overland inundation in the upper Gulf of Thailand. The main objective of the Gulf of Thailand EWS is to provide daily accurate storm surge, wave and wave setup estimates automatically with various data exports possibilities to support this task. It adds a coastal component to HAII's existing practice of providing daily reports on fluvial flood forecasts, used for decision-support in issuing flood warnings for inland water systems in Thailand. Every day, three-day coastal forecasts are now produced based on the latest regional meteorological predictions. Examples are given to illustrate the system's development and main features, with a focus on decision-support products.

Improvement of forecast skill for severe weather by merging radar-based extrapolation and storm-scale NWP corrected forecast

NASA Astrophysics Data System (ADS)

Wang, Gaili; Wong, Wai-Kin; Hong, Yang; Liu, Liping; Dong, Jili; Xue, Ming

2015-03-01

The primary objective of this study is to improve the performance of deterministic high resolution rainfall forecasts caused by severe storms by merging an extrapolation radar-based scheme with a storm-scale Numerical Weather Prediction (NWP) model. Effectiveness of Multi-scale Tracking and Forecasting Radar Echoes (MTaRE) model was compared with that of a storm-scale NWP model named Advanced Regional Prediction System (ARPS) for forecasting a violent tornado event that developed over parts of western and much of central Oklahoma on May 24, 2011. Then the bias corrections were performed to improve the forecast accuracy of ARPS forecasts. Finally, the corrected ARPS forecast and radar-based extrapolation were optimally merged by using a hyperbolic tangent weight scheme. The comparison of forecast skill between MTaRE and ARPS in high spatial resolution of 0.01° × 0.01° and high temporal resolution of 5 min showed that MTaRE outperformed ARPS in terms of index of agreement and mean absolute error (MAE). MTaRE had a better Critical Success Index (CSI) for less than 20-min lead times and was comparable to ARPS for 20- to 50-min lead times, while ARPS had a better CSI for more than 50-min lead times. Bias correction significantly improved ARPS forecasts in terms of MAE and index of agreement, although the CSI of corrected ARPS forecasts was similar to that of the uncorrected ARPS forecasts. Moreover, optimally merging results using hyperbolic tangent weight scheme further improved the forecast accuracy and became more stable.

Toward an integrated storm surge application: ESA Storm Surge project

NASA Astrophysics Data System (ADS)

Lee, Boram; Donlon, Craig; Arino, Olivier

2010-05-01

Storm surges and their associated coastal inundation are major coastal marine hazards, both in tropical and extra-tropical areas. As sea level rises due to climate change, the impact of storm surges and associated extreme flooding may increase in low-lying countries and harbour cities. Of the 33 world cities predicted to have at least 8 million people by 2015, at least 21 of them are coastal including 8 of the 10 largest. They are highly vulnerable to coastal hazards including storm surges. Coastal inundation forecasting and warning systems depend on the crosscutting cooperation of different scientific disciplines and user communities. An integrated approach to storm surge, wave, sea-level and flood forecasting offers an optimal strategy for building improved operational forecasts and warnings capability for coastal inundation. The Earth Observation (EO) information from satellites has demonstrated high potential to enhanced coastal hazard monitoring, analysis, and forecasting; the GOCE geoid data can help calculating accurate positions of tide gauge stations within the GLOSS network. ASAR images has demonstrated usefulness in analysing hydrological situation in coastal zones with timely manner, when hazardous events occur. Wind speed and direction, which is the key parameters for storm surge forecasting and hindcasting, can be derived by using scatterometer data. The current issue is, although great deal of useful EO information and application tools exist, that sufficient user information on EO data availability is missing and that easy access supported by user applications and documentation is highly required. Clear documentation on the user requirements in support of improved storm surge forecasting and risk assessment is also needed at the present. The paper primarily addresses the requirements for data, models/technologies, and operational skills, based on the results from the recent Scientific and Technical Symposium on Storm Surges (www.surgesymposium.org, organized by the WMO-IOC Joint technical Commission for Oceanography and Marine Meteorology, JCOMM) and following activities, that have been supported by the Intergovernmental Oceanographic Commission (IOC) of UNESCO through JCOMM. The paper also reviews the capabilities of storm surge models, and current status in using Earth Observation (EO) information for advancing storm surge application tools, and further, for improving operational forecasts and warning capability for coastal inundation. In this context, the plans and expected results of the ESA Storm Surge Project (2010-2011) will be introduced.

Improvement of Storm Forecasts Using Gridded Bayesian Linear Regression for Northeast United States

NASA Astrophysics Data System (ADS)

Yang, J.; Astitha, M.; Schwartz, C. S.

2017-12-01

Bayesian linear regression (BLR) is a post-processing technique in which regression coefficients are derived and used to correct raw forecasts based on pairs of observation-model values. This study presents the development and application of a gridded Bayesian linear regression (GBLR) as a new post-processing technique to improve numerical weather prediction (NWP) of rain and wind storm forecasts over northeast United States. Ten controlled variables produced from ten ensemble members of the National Center for Atmospheric Research (NCAR) real-time prediction system are used for a GBLR model. In the GBLR framework, leave-one-storm-out cross-validation is utilized to study the performances of the post-processing technique in a database composed of 92 storms. To estimate the regression coefficients of the GBLR, optimization procedures that minimize the systematic and random error of predicted atmospheric variables (wind speed, precipitation, etc.) are implemented for the modeled-observed pairs of training storms. The regression coefficients calculated for meteorological stations of the National Weather Service are interpolated back to the model domain. An analysis of forecast improvements based on error reductions during the storms will demonstrate the value of GBLR approach. This presentation will also illustrate how the variances are optimized for the training partition in GBLR and discuss the verification strategy for grid points where no observations are available. The new post-processing technique is successful in improving wind speed and precipitation storm forecasts using past event-based data and has the potential to be implemented in real-time.

Hybrid vs Adaptive Ensemble Kalman Filtering for Storm Surge Forecasting

NASA Astrophysics Data System (ADS)

Altaf, M. U.; Raboudi, N.; Gharamti, M. E.; Dawson, C.; McCabe, M. F.; Hoteit, I.

2014-12-01

Recent storm surge events due to Hurricanes in the Gulf of Mexico have motivated the efforts to accurately forecast water levels. Toward this goal, a parallel architecture has been implemented based on a high resolution storm surge model, ADCIRC. However the accuracy of the model notably depends on the quality and the recentness of the input data (mainly winds and bathymetry), model parameters (e.g. wind and bottom drag coefficients), and the resolution of the model grid. Given all these uncertainties in the system, the challenge is to build an efficient prediction system capable of providing accurate forecasts enough ahead of time for the authorities to evacuate the areas at risk. We have developed an ensemble-based data assimilation system to frequently assimilate available data into the ADCIRC model in order to improve the accuracy of the model. In this contribution we study and analyze the performances of different ensemble Kalman filter methodologies for efficient short-range storm surge forecasting, the aim being to produce the most accurate forecasts at the lowest possible computing time. Using Hurricane Ike meteorological data to force the ADCIRC model over a domain including the Gulf of Mexico coastline, we implement and compare the forecasts of the standard EnKF, the hybrid EnKF and an adaptive EnKF. The last two schemes have been introduced as efficient tools for enhancing the behavior of the EnKF when implemented with small ensembles by exploiting information from a static background covariance matrix. Covariance inflation and localization are implemented in all these filters. Our results suggest that both the hybrid and the adaptive approach provide significantly better forecasts than those resulting from the standard EnKF, even when implemented with much smaller ensembles.

A quantitative comparison of precipitation forecasts between the storm-scale numerical weather prediction model and auto-nowcast system in Jiangsu, China

NASA Astrophysics Data System (ADS)

Wang, Gaili; Yang, Ji; Wang, Dan; Liu, Liping

2016-11-01

Extrapolation techniques and storm-scale Numerical Weather Prediction (NWP) models are two primary approaches for short-term precipitation forecasts. The primary objective of this study is to verify precipitation forecasts and compare the performances of two nowcasting schemes: a Beijing Auto-Nowcast system (BJ-ANC) based on extrapolation techniques and a storm-scale NWP model called the Advanced Regional Prediction System (ARPS). The verification and comparison takes into account six heavy precipitation events that occurred in the summer of 2014 and 2015 in Jiangsu, China. The forecast performances of the two schemes were evaluated for the next 6 h at 1-h intervals using gridpoint-based measures of critical success index, bias, index of agreement, root mean square error, and using an object-based verification method called Structure-Amplitude-Location (SAL) score. Regarding gridpoint-based measures, BJ-ANC outperforms ARPS at first, but then the forecast accuracy decreases rapidly with lead time and performs worse than ARPS after 4-5 h of the initial forecast. Regarding the object-based verification method, most forecasts produced by BJ-ANC focus on the center of the diagram at the 1-h lead time and indicate high-quality forecasts. As the lead time increases, BJ-ANC overestimates precipitation amount and produces widespread precipitation, especially at a 6-h lead time. The ARPS model overestimates precipitation at all lead times, particularly at first.

Design and skill assessment of an Operational Forecasting System for currents and sea level variability to the Santos Estuarine System - Brazil

NASA Astrophysics Data System (ADS)

Godoi Rezende Costa, C.; Castro, B. M.; Blumberg, A. F.; Leite, J. R. B., Sr.

2017-12-01

Santos City is subject to an average of 12 storm tide events per year. Such events bring coastal flooding able to threat human life and damage coastal infrastructure. Severe events have forced the interruption of ferry boat services and ship traffic through Santos Harbor, causing great impacts to Santos Port, the largest in South America, activities. Several studies have focused on the hydrodynamics of storm tide events but only a few of those studies have pursued an operational initiative to predict short term (< 3 days) sea level variability. The goals of this study are (i) to describe the design of an operational forecasting system built to predict sea surface elevation and currents in the Santos Estuarine System and (ii) to evaluate model performance in simulating observed sea surface elevation. The Santos Operational Forecasting System (SOFS) hydrodynamic module is based on the Stevens Institute Estuarine and Coastal Ocean Model (sECOM). The fully automated SOFS is designed to provide up to 71 h forecast of sea surface elevations and currents every day. The system automatically collects results from global models to run the SOFS nested into another sECOM based model for the South Brazil Bight (SBB). Global forecasting results used to force both models come from Mercator Ocean, released by Copernicus Marine Service, and from the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) stablished by the Center for Weather Forecasts and Climate Studies (with Portuguese acronym CPTEC). The complete routines task take about 8 hours of run time to finish. SOFS was able to hindcast a severe storm tide event that took place in Santos on August 21-22, 2016. Comparisons with observed sea level provided skills of 0.92 and maximum root mean square errors of 25 cm. The good agreement with observed data shows the potential of the designed system to predict storm tides and to support both human and assets protection.

Satellites see major winter storm marching toward the U.S. East Coast

NASA Image and Video Library

2017-12-08

NASA and NOAA satellites are providing various views of the major winter storm marching toward the U.S. East coast on March 13. The storm is forecast to merge with another system and is expected to bring large snowfall totals from the Mid-Atlantic to New England. NASA's Aqua satellite gathered infrared data from the storm system and the area ahead of the storm for cloud and ground temperatures. NOAA's GOES-East satellite provided visible and infrared imagery that showed the extent and the movement of the system. Forecasters at the National Weather Service's Weather Prediction Center (WPC) noted that the low pressure system crossing the Midwest states and Ohio Valley is expected to merge with another low off the southeast U.S. coast. WPC stated "This will allow for a strong nor'easter to develop near the coast and cause a late-season snowstorm from the central Appalachians to New England, including many of the big cities in the Northeast U.S." Credits: NASA/NOAA GOES Project

Synoptic analysis and hindcast of an intense bow echo in Western Europe: The 09 June 2014 storm

NASA Astrophysics Data System (ADS)

Mathias, Luca; Ermert, Volker; Kelemen, Fanni D.; Ludwig, Patrick; Pinto, Joaquim G.

2017-04-01

On Pentecost Monday of 09 June 2014, a severe mesoscale convective system (MCS) hit Belgium and Western Germany. This storm was one of the most severe thunderstorms in Germany for decades. The synoptic-scale and mesoscale characteristics of this storm are analyzed based on remote sensing data and in-situ measurements. Moreover, the forecast potential of the storm is evaluated using sensitivity experiments with a regional climate model. The key ingredients for the development of the Pentecost storm were the concurrent presence of low-level moisture, atmospheric conditional instability and wind shear. The synoptic and mesoscale analysis shows that the outflow of a decaying MCS above northern France triggered the storm, which exhibited the typical features of a bow echo like a mesovortex and rear inflow jet. This resulted in hurricane-force wind gusts (reaching 40 m/s) along a narrow swath in the Rhine-Ruhr region leading to substantial damage. Operational numerical weather predictions models mostly failed to forecast the storm, but high-resolution regional model hindcasts enable a realistic simulation of the storm. The model experiments reveal that the development of the bow echo is particularly sensitive to the initial wind field and the lower tropospheric moisture content. Correct initial and boundary conditions are therefore necessary for realistic numerical forecasts of such a bow echo event. We conclude that the Pentecost storm exhibited a comparable structure and a similar intensity to the observed bow echo systems in the United States.

Assessing the Predictability of Convection using Ensemble Data Assimilation of Simulated Radar Observations in an LETKF system

NASA Astrophysics Data System (ADS)

Lange, Heiner; Craig, George

2014-05-01

This study uses the Local Ensemble Transform Kalman Filter (LETKF) to perform storm-scale Data Assimilation of simulated Doppler radar observations into the non-hydrostatic, convection-permitting COSMO model. In perfect model experiments (OSSEs), it is investigated how the limited predictability of convective storms affects precipitation forecasts. The study compares a fine analysis scheme with small RMS errors to a coarse scheme that allows for errors in position, shape and occurrence of storms in the ensemble. The coarse scheme uses superobservations, a coarser grid for analysis weights, a larger localization radius and larger observation error that allow a broadening of the Gaussian error statistics. Three hour forecasts of convective systems (with typical lifetimes exceeding 6 hours) from the detailed analyses of the fine scheme are found to be advantageous to those of the coarse scheme during the first 1-2 hours, with respect to the predicted storm positions. After 3 hours in the convective regime used here, the forecast quality of the two schemes appears indiscernible, judging by RMSE and verification methods for rain-fields and objects. It is concluded that, for operational assimilation systems, the analysis scheme might not necessarily need to be detailed to the grid scale of the model. Depending on the forecast lead time, and on the presence of orographic or synoptic forcing that enhance the predictability of storm occurrences, analyses from a coarser scheme might suffice.

Chesapeake Inundation Prediction System (CIPS): A regional prototype for a national problem

USGS Publications Warehouse

Stamey, B.; Smith, W.; Carey, K.; Garbin, D.; Klein, F.; Wang, Hongfang; Shen, J.; Gong, W.; Cho, J.; Forrest, D.; Friedrichs, C.; Boicourt, W.; Li, M.; Koterba, M.; King, D.; Titlow, J.; Smith, E.; Siebers, A.; Billet, J.; Lee, J.; Manning, Douglas R.; Szatkowski, G.; Wilson, D.; Ahnert, P.; Ostrowski, J.

2007-01-01

Recent Hurricanes Katrina and Isabel, among others, not only demonstrated their immense destructive power, but also revealed the obvious, crucial need for improved storm surge forecasting and information delivery to save lives and property in future storms. Current operational methods and the storm surge and inundation products do not adequately meet requirements needed by Emergency Managers (EMs) at local, state, and federal levels to protect and inform our citizens. The Chesapeake Bay Inundation Prediction System (CIPS) is being developed to improve the accuracy, reliability, and capability of flooding forecasts for tropical cyclones and non-tropical wind systems such as nor'easters by modeling and visualizing expected on-land storm-surge inundation along the Chesapeake Bay and its tributaries. An initial prototype has been developed by a team of government, academic and industry partners through the Chesapeake Bay Observing System (CBOS) of the Mid-Atlantic Coastal Ocean Observing Regional Association (MACOORA) within the Integrated Ocean Observing System (IOOS). For demonstration purposes, this initial prototype was developed for the tidal Potomac River in the Washington, DC metropolitan area. The preliminary information from this prototype shows great potential as a mechanism by which NOAA National Weather Service (NWS) Forecast Offices (WFOs) can provide more specific and timely forecasts of likely inundation in individual localities from significant storm surge events. This prototype system has shown the potential to indicate flooding at the street level, at time intervals of an hour or less, and with vertical resolution of one foot or less. This information will significantly improve the ability of EMs and first responders to mitigate life and property loss and improve evacuation capabilities in individual communities. This paper provides an update and expansion of the initial prototype that was presented at the Oceans 2006 MTS/IEEE Conference in Boston, MA. ??2007 MTS.

Preliminary Study on Coupling Wave-Tide-Storm Surges Prediction System

NASA Astrophysics Data System (ADS)

You, S.; Park, S.; Seo, J.; Kim, K.

2008-12-01

The Korean Peninsula is surrounded by the Yellow Sea, East China Sea, and East Sea. This complex oceanographic system includes large tides in the Yellow Sea and seasonally varying monsoon and typhoon events. For Korea's coastal regions, floods caused by wave and storm surges are among the most serious threats. To predict more accurate wave and storm surge, the development of coupling wave-tide-storm surges prediction system is essential. For the time being, wave and storm surges predictions are still made separately in KMA (Korea Meteorological Administration) and most operational institute. However, many researchers have emphasized the effects of tides and storm surges on wind waves and recommended further investigations into the effects of wave-tide-storm surges interactions and coupling module on wave heights. However, tidal height and current give a great effect on the wave prediction in the Yellow sea where is very high tide and related research is not enough. At present, KMA has operated the wave (RWAM : Regional Wave Model) and storm surges/tide prediction system (RTSM : Regional Tide/Storm Surges Model) for ocean forecasting. The RWAM is WAVEWATCH III which is a third generation wave model developed by Tolman (1989). The RTSM is based on POM (Princeton Ocean Model, Blumberg and Mellor, 1987). The RWAM and RTSM cover the northwestern Pacific Ocean from 115°E to 150°E and from 20°N to 52°N. The horizontal grid intervals are 1/12° in both latitudinal and longitudinal directions. The development, testing and application of a coupling module in which wave-tide-storm surges are incorporated within the frame of KMA Ocean prediction system, has been considered as a step forward in respect of ocean forecasting. In addition, advanced wave prediction model will be applicable to the effect of ocean in the weather forecasting system. The main purpose of this study is to show how the coupling module developed and to report on a series of experiments dealing with the sensitivities and real case prediction of coupling wave-tide-storm surges prediction system.

Ionospheric storms—A challenge for empirical forecast of the total electron content

NASA Astrophysics Data System (ADS)

Borries, C.; Berdermann, J.; Jakowski, N.; Wilken, V.

2015-04-01

Since the last decades, the functioning of society depends more and more on well-functioning communication and navigation systems. As the availability and reliability of most of these satellite-based systems can be severely impacted by ionospheric storms, the accurate forecast of these events becomes a required task for mitigating social and economic risks. Here we aim to make initial steps toward an empirical model for ionospheric perturbations related to space weather events that are observable in the total electron content (TEC). The perturbation TEC forecast model will be a fast and robust approach, improving TEC forecasts based on climatological models during storm conditions. The derivation of such a model is a challenging task, because although a general dependence of the storm features (enhancement or depletion of electron density) on the storm onset time, local time, season and geomagnetic latitude is well known, there is a large deviation from the mean behavior. For a better understanding of storm conditions, this paper presents analyses of ionospheric storms observed in the TEC, broken down into diverse classes of storms. It provides a detailed characterization of the typical ionospheric storm behavior over Europe from high to midlatitudes, beyond case studies. Generally, the typical clear strong TEC enhancement starting in high latitudes and propagating equatorward is found to be strongest for storms starting in the morning hours independent of the season. In midlatitudes, it is strongest during noon. In addition, a clear difference between summer and winter storms is reported. While only winter storms develop high-latitude TEC enhancements, only summer storms typically exhibit TEC depletions during the storm recovery phase. During winter storms TEC enhancements can also occur the day following the storm onset, in contrast to summer storms. Strong correlation of TEC perturbation amplitudes to the Bz component of the interplanetary magnetic field and to a proxy of the polar cap potential are shown especially for summer midlatitude TEC enhancements during storms with and onset in the morning hours (6 to 12 UT over Europe) and for winter high-latitude TEC enhancements (around 60∘N). The results indicate the potential to derive improved predictions of maximum TEC deviations during space weather events, based on solar wind measurements.

Coastal and Riverine Flood Forecast Model powered by ADCIRC

NASA Astrophysics Data System (ADS)

Khalid, A.; Ferreira, C.

2017-12-01

Coastal flooding is becoming a major threat to increased population in the coastal areas. To protect coastal communities from tropical storms & hurricane damages, early warning systems are being developed. These systems have the capability of real time flood forecasting to identify hazardous coastal areas and aid coastal communities in rescue operations. State of the art hydrodynamic models forced by atmospheric forcing have given modelers the ability to forecast storm surge, water levels and currents. This helps to identify the areas threatened by intense storms. Study on Chesapeake Bay area has gained national importance because of its combined riverine and coastal phenomenon, which leads to greater uncertainty in flood predictions. This study presents an automated flood forecast system developed by following Advanced Circulation (ADCIRC) Surge Guidance System (ASGS) guidelines and tailored to take in riverine and coastal boundary forcing, thus includes all the hydrodynamic processes to forecast total water in the Potomac River. As studies on tidal and riverine flow interaction are very scarce in number, our forecast system would be a scientific tool to examine such area and fill the gaps with precise prediction for Potomac River. Real-time observations from National Oceanic and Atmospheric Administration (NOAA) and field measurements have been used as model boundary feeding. The model performance has been validated by using major historical riverine and coastal flooding events. Hydrodynamic model ADCIRC produced promising predictions for flood inundation areas. As better forecasts can be achieved by using coupled models, this system is developed to take boundary conditions from Global WaveWatchIII for the research purposes. Wave and swell propagation will be fed through Global WavewatchIII model to take into account the effects of swells and currents. This automated forecast system is currently undergoing rigorous testing to include any missing parameters which might provide better and more reliable forecast for the flood affected communities.

Severe storms forecast systems

NASA Technical Reports Server (NTRS)

Kaplan, M.; Zack, J.

1980-01-01

Two research tasks are described: (1) the improvement and enhancement of an existing mesoscale numerical simulation system, and (2) numerical diagnostic studies associated with an individual case of severe storm development (April 10, 1979 in the Red River Valley of Texas and Oklahoma).

Characterizing the Relationships Among Lightning and Storm Parameters: Lightning as a Proxy Variable

NASA Technical Reports Server (NTRS)

Goodman, S. J.; Raghavan, R.; William, E.; Weber, M.; Boldi, B.; Matlin, A.; Wolfson, M.; Hodanish, S.; Sharp. D.

1997-01-01

We have gained important insights from prior studies that have suggested relationships between lightning and storm growth, decay, convective rain flux, vertical distribution of storm mass and echo volume in the region, and storm energetics. A study was initiated in the Summer of 1996 to determine how total (in-cloud plus ground) lightning observations might provide added knowledge to the forecaster in the determination and identification of severe thunderstorms and weather hazards in real-time. The Melbourne Weather Office was selected as a primary site to conduct this study because Melbourne is the only site in the world with continuous and open access to total lightning (LDAR) data and a Doppler (WSR-88D) radar. A Lightning Imaging Sensor Data Applications Demonstration (LISDAD) system was integrated into the forecaster's workstation during the Summer 1996 to allow the forecaster to interact in real-time with the multi-sensor data being displayed. LISDAD currently ingests LDAR data, the cloud-to-ground National Lightning Detection Network (NLDN) data, and the Melbourne radar data in f real-time. The interactive features provide the duty forecaster the ability to perform quick diagnostics on storm cells of interest. Upon selection of a storm cell, a pop-up box appears displaying the time-history of various storm parameters (e.g., maximum radar reflectivity, height of maximum reflectivity, echo-top height, NLDN and LDAR lightning flash rates, storm-based vertically integrated liquid water content). This product is archived to aid on detailed post-analysis.

Ionospheric Data Assimilation and Targeted Observation Strategies: Proof of Concept Analysis in a Geomagnetic Storm Event

NASA Astrophysics Data System (ADS)

Kostelich, Eric; Durazo, Juan; Mahalov, Alex

2017-11-01

The dynamics of the ionosphere involve complex interactions between the atmosphere, solar wind, cosmic radiation, and Earth's magnetic field. Geomagnetic storms arising from solar activity can perturb these dynamics sufficiently to disrupt radio and satellite communications. Efforts to predict ``space weather,'' including ionospheric dynamics, require the development of a data assimilation system that combines observing systems with appropriate forecast models. This talk will outline a proof-of-concept targeted observation strategy, consisting of the Local Ensemble Transform Kalman Filter, coupled with the Thermosphere Ionosphere Electrodynamics Global Circulation Model, to select optimal locations where additional observations can be made to improve short-term ionospheric forecasts. Initial results using data and forecasts from the geomagnetic storm of 26-27 September 2011 will be described. Work supported by the Air Force Office of Scientific Research (Grant Number FA9550-15-1-0096) and by the National Science Foundation (Grant Number DMS-0940314).

Using Flow Charts to Visualize the Decision-Making Process in Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Aung, M. T. Y.; Myat, T.; Zheng, Y.; Mays, M. L.; Ngwira, C.; Damas, M. C.

2016-12-01

Our society today relies heavily on technological systems such as satellites, navigation systems, power grids and aviation. These systems are very sensitive to space weather disturbances. When Earth-directed space weather driven by the Sun arrives at the Earth, it causes changes to the Earth's radiation environment and the magnetosphere. Strong disturbances in the magnetosphere of the Earth are responsible for geomagnetic storms that can last from hours to days depending on strength of storms. Geomagnetic storms can severely impact critical infrastructure on Earth, such as the electric power grid, and Solar Energetic Particles that can endanger life in outer space. How can we lessen these adverse effects? They can be lessened through the early warning signals sent by space weather forecasters before CME or high-speed stream arrives. A space weather forecaster's duty is to send predicted notifications to high-tech industries and NASA missions so that they could take extra measures for protection. NASA space weather forecasters make prediction decisions by following certain steps and processes from the time an event occurs at the sun all the way to the impact locations. However, there has never been a tool that helps these forecasters visualize the decision process until now. A flow chart is created to help forecasters visualize the decision process. This flow chart provides basic knowledge of space weather and can be used to train future space weather forecasters. It also helps to cut down the training period and increase consistency in forecasting. The flow chart is also a great reference for people who are already familiar with space weather.

NOMADS-NOAA Operational Model Archive and Distribution System

Science.gov Websites

Forecast Maps Climate Climate Prediction Climate Archives Weather Safety Storm Ready NOAA Central Library (16km) 6 hours grib filter http OpenDAP-alt URMA hourly - http - Climate Models Climate Forecast System Flux Products 6 hours grib filter http - Climate Forecast System 3D Pressure Products 6 hours grib

A Numerical Simulation (Study) of a Strong West Coast December 2014 Winter Storm

NASA Astrophysics Data System (ADS)

Smelser, I.; Xu, L.; Amerault, C. M.; Baker, N. L.; Satterfield, E.; Chua, B.

2016-12-01

From December 10 through December 13, 2014, a powerful winter storm swept across the western US coastal states bringing widespread power outages, numerous downed trees and power lines, heavy rains, flooding and even a tornado in the Los Angeles basin. This windstorm was the strongest since October 2009, and was similar to classic wind storms such as the 1962 Columbus Day Storm (Read, 2015).The storm started developing over the Pacific Ocean north of Hawaii on Nov. 30, and formed an atmospheric river that eventually stretched from Hawaii to the west coast. The storm initially hit the Pacific Northwest on Dec. 9th and then split. The highest precipitation amounts started in British Colombia and moved south along the coast. By the Dec. 11th, the highest precipitation amounts were near San Francisco (CA). The peak wind gust (14.4 ms-1) for Monterey (CA) occurred at 1116Z on Dec. 11th while the heaviest 6-hr precipitation (42.9 mm) occurred between 18Z on Dec. 11th to 00Z on Dec. 12th. By Dec. 12th, the storm was centered over Southern California.This storm was poorly forecast by many operational NWP models even 2-3 days in advance (Mass, 2014). The NCEP Global Forecast System (GFS) showed considerably variability between successive model runs, and significant differences existed between Environment Canada, UK Met Office and ECMWF model forecasts. To study this extreme weather event, we used the Navy global (NAVGEM) and mesoscale (COAMPS®) NWP models, and compared the resulting forecasts to observations, satellite imagery and ECMWF (TIGGE) forecasts. NAVGEM, with Hybrid 4DVar, was run with a resolution of 31 km, and generated the boundary conditions for COAMPS® 4DVar and forecasts, that were run with triple-nested grids of 27, 9, and 3 km. The MesoWest data from the University of Utah were used for forecast verification, and to locate the times of highest precipitation and wind speed for different points along the coast. Both the online API and the python module were used to access and pull information from the data base. Overall, both NAVGEM and COAMPS® predicted the storm well. NAVGEM predicted the storm to be slower and more powerful than the analyses. The NAVGEM analysis and corresponding 5-day forecast accumulated 6-hr precipitation (Fig. 1) for Dec. 12th at 00Z agree well with the observed precipitation (4.29 cm) for Monterey (KMRY).

Forecasting Dust Storms Using the CARMA-Dust Model and MM5 Weather Data

NASA Astrophysics Data System (ADS)

Barnum, B. H.; Winstead, N. S.; Wesely, J.; Hakola, A.; Colarco, P.; Toon, O. B.; Ginoux, P.; Brooks, G.; Hasselbarth, L. M.; Toth, B.; Sterner, R.

2002-12-01

An operational model for the forecast of dust storms in Northern Africa, the Middle East and Southwest Asia has been developed for the United States Air Force Weather Agency (AFWA). The dust forecast model uses the 5th generation Penn State Mesoscale Meteorology Model (MM5), and a modified version of the Colorado Aerosol and Radiation Model for Atmospheres (CARMA). AFWA conducted a 60 day evaluation of the dust model to look at the model's ability to forecast dust storms for short, medium and long range (72 hour) forecast periods. The study used satellite and ground observations of dust storms to verify the model's effectiveness. Each of the main mesoscale forecast theaters was broken down into smaller sub-regions for detailed analysis. The study found the forecast model was able to forecast dust storms in Saharan Africa and the Sahel region with an average Probability of Detection (POD)exceeding 68%, with a 16% False Alarm Rate (FAR). The Southwest Asian theater had average POD's of 61% with FAR's averaging 10%.

Presenting Critical Space Weather Information to Customers and Stakeholders (Invited)

NASA Astrophysics Data System (ADS)

Viereck, R. A.; Singer, H. J.; Murtagh, W. J.; Rutledge, B.

2013-12-01

Space weather involves changes in the near-Earth space environment that impact technological systems such as electric power, radio communication, satellite navigation (GPS), and satellite opeartions. As with terrestrial weather, there are several different kinds of space weather and each presents unique challenges to the impacted technologies and industries. But unlike terrestrial weather, many customers are not fully aware of space weather or how it impacts their systems. This issue is further complicated by the fact that the largest space weather events occur very infrequently with years going by without severe storms. Recent reports have estimated very large potential costs to the economy and to society if a geomagnetic storm were to cause major damage to the electric power transmission system. This issue has come to the attention of emergency managers and federal agencies including the office of the president. However, when considering space weather impacts, it is essential to also consider uncertainties in the frequency of events and the predicted impacts. The unique nature of space weather storms, the specialized technologies that are impacted by them, and the disparate groups and agencies that respond to space weather forecasts and alerts create many challenges to the task of communicating space weather information to the public. Many customers that receive forecasts and alerts are highly technical and knowledgeable about the subtleties of the space environment. Others know very little and require ongoing education and explanation about how a space weather storm will affect their systems. In addition, the current knowledge and understanding of the space environment that goes into forecasting storms is quite immature. It has only been within the last five years that physics-based models of the space environment have played important roles in predictions. Thus, the uncertainties in the forecasts are quite large. There is much that we don't know about space weather and this influences our forecasts. In this presentation, I will discuss the unique challenges that space weather forecasters face when explaining what we know and what we don't know about space weather events to customers and policy makers.

Solar-Terrestrial Predictions: Proceedings of a workshop. Volume 2: Geomagnetic and space environment papers and ionosphere papers

NASA Astrophysics Data System (ADS)

Thompson, R. J.; Cole, D. G.; Wilkinson, P. J.; Shea, M. A.; Smart, D.

1990-11-01

The following subject areas were covered: a probability forecast for geomagnetic activity; cost recovery in solar-terrestrial predictions; magnetospheric specification and forecasting models; a geomagnetic forecast and monitoring system for power system operation; some aspects of predicting magnetospheric storms; some similarities in ionospheric disturbance characteristics in equatorial, mid-latitude, and sub-auroral regions; ionospheric support for low-VHF radio transmission; a new approach to prediction of ionospheric storms; a comparison of the total electron content of the ionosphere around L=4 at low sunspot numbers with the IRI model; the French ionospheric radio propagation predictions; behavior of the F2 layer at mid-latitudes; and the design of modern ionosondes.

Performance Comparison of the European Storm Surge Models and Chaotic Model in Forecasting Extreme Storm Surges

NASA Astrophysics Data System (ADS)

Siek, M. B.; Solomatine, D. P.

2009-04-01

Storm surge modeling has rapidly developed considerably over the past 30 years. A number of significant advances on operational storm surge models have been implemented and tested, consisting of: refining computational grids, calibrating the model, using a better numerical scheme (i.e. more realistic model physics for air-sea interaction), implementing data assimilation and ensemble model forecasts. This paper addresses the performance comparison between the existing European storm surge models and the recently developed methods of nonlinear dynamics and chaos theory in forecasting storm surge dynamics. The chaotic model is built using adaptive local models based on the dynamical neighbours in the reconstructed phase space of observed time series data. The comparison focused on the model accuracy in forecasting a recently extreme storm surge in the North Sea on November 9th, 2007 that hit the coastlines of several European countries. The combination of a high tide, north-westerly winds exceeding 50 mph and low pressure produced an exceptional storm tide. The tidal level was exceeded 3 meters above normal sea levels. Flood warnings were issued for the east coast of Britain and the entire Dutch coast. The Maeslant barrier's two arc-shaped steel doors in the Europe's biggest port of Rotterdam was closed for the first time since its construction in 1997 due to this storm surge. In comparison to the chaotic model performance, the forecast data from several European physically-based storm surge models were provided from: BSH Germany, DMI Denmark, DNMI Norway, KNMI Netherlands and MUMM Belgium. The performance comparison was made over testing datasets for two periods/conditions: non-stormy period (1-Sep-2007 till 14-Oct-2007) and stormy period (15-Oct-2007 till 20-Nov-2007). A scalar chaotic model with optimized parameters was developed by utilizing an hourly training dataset of observations (11-Sep-2005 till 31-Aug-2007). The comparison results indicated the chaotic model yields better forecasts than the existing European storm surge models. The best performance of European storm surge models for non-storm and storm conditions was achieved by KNMI (with Kalman filter data assimilation) and BSH with errors of 8.95cm and 10.92cm, respectively. Whereas the chaotic model can provide 6 and 48 hours forecasts with errors of 3.10cm and 8.55cm for non-storm condition and 5.04cm and 15.21cm for storm condition, respectively. The chaotic model can provide better forecasts primarily due to the fact that the chaotic model forecasting are estimated by local models which model and identify the similar development of storm surges in the past. In practice, the chaotic model can serve as a reliable and accurate model to support decision-makers in operational ship navigation and flood forecasting.

Geomagnetic storm forecasting service StormFocus: 5 years online

NASA Astrophysics Data System (ADS)

Podladchikova, Tatiana; Petrukovich, Anatoly; Yermolaev, Yuri

2018-04-01

Forecasting geomagnetic storms is highly important for many space weather applications. In this study, we review performance of the geomagnetic storm forecasting service StormFocus during 2011-2016. The service was implemented in 2011 at SpaceWeather.Ru and predicts the expected strength of geomagnetic storms as measured by Dst index several hours ahead. The forecast is based on L1 solar wind and IMF measurements and is updated every hour. The solar maximum of cycle 24 is weak, so most of the statistics are on rather moderate storms. We verify quality of selection criteria, as well as reliability of real-time input data in comparison with the final values, available in archives. In real-time operation 87% of storms were correctly predicted while the reanalysis running on final OMNI data predicts successfully 97% of storms. Thus the main reasons for prediction errors are discrepancies between real-time and final data (Dst, solar wind and IMF) due to processing errors, specifics of datasets.

Global scale predictability of floods

NASA Astrophysics Data System (ADS)

Weerts, Albrecht; Gijsbers, Peter; Sperna Weiland, Frederiek

2016-04-01

Flood (and storm surge) forecasting at the continental and global scale has only become possible in recent years (Emmerton et al., 2016; Verlaan et al., 2015) due to the availability of meteorological forecast, global scale precipitation products and global scale hydrologic and hydrodynamic models. Deltares has setup GLOFFIS a research-oriented multi model operational flood forecasting system based on Delft-FEWS in an open experimental ICT facility called Id-Lab. In GLOFFIS both the W3RA and PCRGLOB-WB model are run in ensemble mode using GEFS and ECMWF-EPS (latency 2 days). GLOFFIS will be used for experiments into predictability of floods (and droughts) and their dependency on initial state estimation, meteorological forcing and the hydrologic model used. Here we present initial results of verification of the ensemble flood forecasts derived with the GLOFFIS system. Emmerton, R., Stephens, L., Pappenberger, F., Pagano, T., Weerts, A., Wood, A. Salamon, P., Brown, J., Hjerdt, N., Donnelly, C., Cloke, H. Continental and Global Scale Flood Forecasting Systems, WIREs Water (accepted), 2016 Verlaan M, De Kleermaeker S, Buckman L. GLOSSIS: Global storm surge forecasting and information system 2015, Australasian Coasts & Ports Conference, 15-18 September 2015,Auckland, New Zealand.

Analyses and forecasts of a tornadic supercell outbreak using a 3DVAR system ensemble

NASA Astrophysics Data System (ADS)

Zhuang, Zhaorong; Yussouf, Nusrat; Gao, Jidong

2016-05-01

As part of NOAA's "Warn-On-Forecast" initiative, a convective-scale data assimilation and prediction system was developed using the WRF-ARW model and ARPS 3DVAR data assimilation technique. The system was then evaluated using retrospective short-range ensemble analyses and probabilistic forecasts of the tornadic supercell outbreak event that occurred on 24 May 2011 in Oklahoma, USA. A 36-member multi-physics ensemble system provided the initial and boundary conditions for a 3-km convective-scale ensemble system. Radial velocity and reflectivity observations from four WSR-88Ds were assimilated into the ensemble using the ARPS 3DVAR technique. Five data assimilation and forecast experiments were conducted to evaluate the sensitivity of the system to data assimilation frequencies, in-cloud temperature adjustment schemes, and fixed- and mixed-microphysics ensembles. The results indicated that the experiment with 5-min assimilation frequency quickly built up the storm and produced a more accurate analysis compared with the 10-min assimilation frequency experiment. The predicted vertical vorticity from the moist-adiabatic in-cloud temperature adjustment scheme was larger in magnitude than that from the latent heat scheme. Cycled data assimilation yielded good forecasts, where the ensemble probability of high vertical vorticity matched reasonably well with the observed tornado damage path. Overall, the results of the study suggest that the 3DVAR analysis and forecast system can provide reasonable forecasts of tornadic supercell storms.

Computer-Assisted Interactive Documentary and Performance Arts in Illimitable Space

NASA Astrophysics Data System (ADS)

Sheridan, William Michael

Winter can bring significant snow storm systems or nor'easters to New England. Understanding each factor which can affect nor'easters will allow forecasters to better predict the subsequent weather conditions. One important parameter is the sea surface temperature (SST) of the Atlantic Ocean, where many of these systems strengthen and gain much of their structure. The Weather Research and Forecasting (WRF) model was used to simulate four different nor'easters (Mar 2007, Dec 2007, Jan 2008, Dec 2010) using both observed and warmed SSTs. For the wanner SST simulations, the SSTs over the model domain were increased by 1°C. This change increased the total surface heat fluxes in all of the storms, and the resulting simulated storms were all more intense. The influence on the amount of snowfall over land was highly variable, depending on how close to the coastline the storms were and temperatures across the region.

Solar-Terrestrial Predictions

NASA Astrophysics Data System (ADS)

Thompson, R. J.; Cole, D. G.; Wilkinson, P. J.; Shea, M. A.; Smart, D.

1990-11-01

Volume 1: The following subject areas are covered: the magnetosphere environment; forecasting magnetically quiet periods; radiation hazards to human in deep space (a summary with special reference to large solar particle events); solar proton events (review and status); problems of the physics of solar-terrestrial interactions; prediction of solar proton fluxes from x-ray signatures; rhythms in solar activity and the prediction of episodes of large flares; the role of persistence in the 24-hour flare forecast; on the relationship between the observed sunspot number and the number of solar flares; the latitudinal distribution of coronal holes and geomagnetic storms due to coronal holes; and the signatures of flares in the interplanetary medium at 1 AU. Volume 2: The following subject areas were covered: a probability forecast for geomagnetic activity; cost recovery in solar-terrestrial predictions; magnetospheric specification and forecasting models; a geomagnetic forecast and monitoring system for power system operation; some aspects of predicting magnetospheric storms; some similarities in ionospheric disturbance characteristics in equatorial, mid-latitude, and sub-auroral regions; ionospheric support for low-VHF radio transmission; a new approach to prediction of ionospheric storms; a comparison of the total electron content of the ionosphere around L=4 at low sunspot numbers with the IRI model; the French ionospheric radio propagation predictions; behavior of the F2 layer at mid-latitudes; and the design of modern ionosondes.

Revisiting the latent heat nudging scheme for the rainfall assimilation of a simulated convective storm

NASA Astrophysics Data System (ADS)

Leuenberger, D.; Rossa, A.

2007-12-01

Next-generation, operational, high-resolution numerical weather prediction models require economical assimilation schemes for radar data. In the present study we evaluate and characterise the latent heat nudging (LHN) rainfall assimilation scheme within a meso-γ scale NWP model in the framework of identical twin simulations of an idealised supercell storm. Consideration is given to the model’s dynamical response to the forcing as well as to the sensitivity of the LHN scheme to uncertainty in the observations and the environment. The results indicate that the LHN scheme is well able to capture the dynamical structure and the right rainfall amount of the storm in a perfect environment. This holds true even in degraded environments but a number of important issues arise. In particular, changes in the low-level humidity field are found to affect mainly the precipitation amplitude during the assimilation with a fast adaptation of the storm to the system dynamics determined by the environment during the free forecast. A constant bias in the environmental wind field, on the other hand, has the potential to render a successful assimilation with the LHN scheme difficult, as the velocity of the forcing is not consistent with the system propagation speed determined by the wind. If the rainfall forcing moves too fast, the system propagation is supported and the assimilated storm and forecasts initialised therefrom develop properly. A too slow forcing, on the other hand, can decelerate the system and eventually disturb the system dynamics by decoupling the low-level moisture inflow from the main updrafts during the assimilation. This distortion is sustained in the free forecast. It has further been found that a sufficient temporal resolution of the rainfall input is crucial for the successful assimilation of a fast moving, coherent convective storm and that the LHN scheme, when applied to a convective storm, appears to necessitate a careful tuning.

NASA Launches NOAA Weather Satellite to Improve Forecasts

NASA Image and Video Library

2017-11-18

Early on the morning of Saturday, Nov. 18, NASA successfully launched for the National Oceanic and Atmospheric Administration (NOAA) the first in a series of four advanced polar-orbiting satellites, equipped with next-generation technology and designed to improve the accuracy of U.S. weather forecasts out to seven days. The Joint Polar Satellite System-1 (JPSS-1) lifted off on a United Launch Alliance Delta II rocket from Vandenberg Air Force Base on California’s central coast. JPSS-1 data will improve weather forecasting and help agencies involved with post-storm recovery by visualizing storm damage and the geographic extent of power outages.

Assimilation of ZDR Columns for Improving the Spin-Up and Forecasts of Convective Storms

NASA Astrophysics Data System (ADS)

Carlin, J.; Gao, J.; Snyder, J.; Ryzhkov, A.

2017-12-01

A primary motivation for assimilating radar reflectivity data is the reduction of spin-up time for modeled convection. To accomplish this, cloud analysis techniques seek to induce and sustain convective updrafts in storm-scale models by inserting temperature and moisture increments and hydrometeor mixing ratios into the model analysis from simple relations with reflectivity. Polarimetric radar data provide additional insight into the microphysical and dynamic structure of convection. In particular, the radar meteorology community has known for decades that convective updrafts cause, and are typically co-located with, differential reflectivity (ZDR) columns - vertical protrusions of enhanced ZDR above the environmental 0˚C level. Despite these benefits, limited work has been done thus far to assimilate dual-polarization radar data into numerical weather prediction models. In this study, we explore the utility of assimilating ZDR columns to improve storm-scale model analyses and forecasts of convection. We modify the existing Advanced Regional Prediction System's (ARPS) cloud analysis routine to adjust model temperature and moisture state variables using detected ZDR columns as proxies for convective updrafts, and compare the resultant cycled analyses and forecasts with those from the original reflectivity-based cloud analysis formulation. Results indicate qualitative and quantitative improvements from assimilating ZDR columns, including more coherent analyzed updrafts, forecast updraft helicity swaths that better match radar-derived rotation tracks, more realistic forecast reflectivity fields, and larger equitable threat scores. These findings support the use of dual-polarization radar signatures to improve storm-scale model analyses and forecasts.

Modeling North Atlantic Nor'easters With Modern Wave Forecast Models

NASA Astrophysics Data System (ADS)

Perrie, Will; Toulany, Bechara; Roland, Aron; Dutour-Sikiric, Mathieu; Chen, Changsheng; Beardsley, Robert C.; Qi, Jianhua; Hu, Yongcun; Casey, Michael P.; Shen, Hui

2018-01-01

Three state-of-the-art operational wave forecast model systems are implemented on fine-resolution grids for the Northwest Atlantic. These models are: (1) a composite model system consisting of SWAN implemented within WAVEWATCHIII® (the latter is hereafter, WW3) on a nested system of traditional structured grids, (2) an unstructured grid finite-volume wave model denoted "SWAVE," using SWAN physics, and (3) an unstructured grid finite element wind wave model denoted as "WWM" (for "wind wave model") which uses WW3 physics. Models are implemented on grid systems that include relatively large domains to capture the wave energy generated by the storms, as well as including fine-resolution nearshore regions of the southern Gulf of Maine with resolution on the scale of 25 m to simulate areas where inundation and coastal damage have occurred, due to the storms. Storm cases include three intense midlatitude cases: a spring Nor'easter storm in May 2005, the Patriot's Day storm in 2007, and the Boxing Day storm in 2010. Although these wave model systems have comparable overall properties in terms of their performance and skill, it is found that there are differences. Models that use more advanced physics, as presented in recent versions of WW3, tuned to regional characteristics, as in the Gulf of Maine and the Northwest Atlantic, can give enhanced results.

A Conceptual Model of the Severe-Storm Environment for Inclusion into Air Weather Service Severe-Storm Analysis and Forecast Procedures.

DTIC Science & Technology

1984-11-16

thunderstorm forecasting , Bull. Am. Meteorol. Soc. 34:250-252. 19. Galway , J.G. (1956) The lifted index as a prediction of latent instability, Bull...downwind, which are geographically related and can be traced through time by a forecaster . In fact, a typical Great Plains severe-storm situation has...weather station setting, only one sounding can be plotted and anal- yzed because of time constraints. Appendix C contains two single-station forecast

Evaluation of the NCEP CFSv2 45-day Forecasts for Predictability of Intraseasonal Tropical Storm Activities

NASA Astrophysics Data System (ADS)

Schemm, J. E.; Long, L.; Baxter, S.

2013-12-01

Evaluation of the NCEP CFSv2 45-day Forecasts for Predictability of Intraseasonal Tropical Storm Activities Jae-Kyung E. Schemm, Lindsey Long and Stephen Baxter Climate Prediction Center, NCEP/NWS/NOAA Predictability of intraseasonal tropical storm (TS) activities is assessed using the 1999-2010 CFSv2 hindcast suite. Weekly TS activities in the CFSv2 45-day forecasts were determined using the TS detection and tracking method devised by Carmago and Zebiak (2002). The forecast periods are divided into weekly intervals for Week 1 through Week 6, and also the 30-day mean. The TS activities in those intervals are compared to the observed activities based on the NHC HURDAT and JTWC Best Track datasets. The CFSv2 45-day hindcast suite is made of forecast runs initialized at 00, 06, 12 and 18Z every day during the 1999 - 2010 period. For predictability evaluation, forecast TS activities are analyzed based on 20-member ensemble forecasts comprised of 45-day runs made during the most recent 5 days prior to the verification period. The forecast TS activities are evaluated in terms of the number of storms, genesis locations and storm tracks during the weekly periods. The CFSv2 forecasts are shown to have a fair level of skill in predicting the number of storms over the Atlantic Basin with the temporal correlation scores ranging from 0.73 for Week 1 forecasts to 0.63 for Week 6, and the average RMS errors ranging from 0.86 to 1.07 during the 1999-2010 hurricane season. Also, the forecast track density distribution and false alarm statistics are compiled using the hindcast analyses. In real-time applications of the intraseasonal TS activity forecasts, the climatological TS forecast statistics will be used to make the model bias corrections in terms of the storm counts, track distribution and removal of false alarms. An operational implementation of the weekly TS activity prediction is planned for early 2014 to provide an objective input for the CPC's Global Tropical Hazards Outlooks.

Verification of Space Weather Forecasts using Terrestrial Weather Approaches

NASA Astrophysics Data System (ADS)

Henley, E.; Murray, S.; Pope, E.; Stephenson, D.; Sharpe, M.; Bingham, S.; Jackson, D.

2015-12-01

The Met Office Space Weather Operations Centre (MOSWOC) provides a range of 24/7 operational space weather forecasts, alerts, and warnings, which provide valuable information on space weather that can degrade electricity grids, radio communications, and satellite electronics. Forecasts issued include arrival times of coronal mass ejections (CMEs), and probabilistic forecasts for flares, geomagnetic storm indices, and energetic particle fluxes and fluences. These forecasts are produced twice daily using a combination of output from models such as Enlil, near-real-time observations, and forecaster experience. Verification of forecasts is crucial for users, researchers, and forecasters to understand the strengths and limitations of forecasters, and to assess forecaster added value. To this end, the Met Office (in collaboration with Exeter University) has been adapting verification techniques from terrestrial weather, and has been working closely with the International Space Environment Service (ISES) to standardise verification procedures. We will present the results of part of this work, analysing forecast and observed CME arrival times, assessing skill using 2x2 contingency tables. These MOSWOC forecasts can be objectively compared to those produced by the NASA Community Coordinated Modelling Center - a useful benchmark. This approach cannot be taken for the other forecasts, as they are probabilistic and categorical (e.g., geomagnetic storm forecasts give probabilities of exceeding levels from minor to extreme). We will present appropriate verification techniques being developed to address these forecasts, such as rank probability skill score, and comparing forecasts against climatology and persistence benchmarks. As part of this, we will outline the use of discrete time Markov chains to assess and improve the performance of our geomagnetic storm forecasts. We will also discuss work to adapt a terrestrial verification visualisation system to space weather, to help MOSWOC forecasters view verification results in near real-time; plans to objectively assess flare forecasts under the EU Horizon 2020 FLARECAST project; and summarise ISES efforts to achieve consensus on verification.

The probability forecast evaluation of hazard and storm wind over the territories of Russia and Europe

NASA Astrophysics Data System (ADS)

Perekhodtseva, E. V.

2012-04-01

The results of the probability forecast methods of summer storm and hazard wind over territories of Russia and Europe are submitted at this paper. These methods use the hydrodynamic-statistical model of these phenomena. The statistical model was developed for the recognition of the situation involving these phenomena. For this perhaps the samples of the values of atmospheric parameters (n=40) for the presence and for the absence of these phenomena of storm and hazard wind were accumulated. The compressing of the predictors space without the information losses was obtained by special algorithm (k=7<19m/s, the values of 65%24m/s, the values of 75%29m/s or the area of the tornado and strong squalls. The evaluation of this probability forecast was provided by criterion of Brayer. The estimation was successful and was equal for the European part of Russia B=0,37. The application of the probability forecast of storm and hazard winds allows to mitigate the economic losses when the errors of the first and second kinds of storm wind categorical forecast are not so small. A lot of examples of the storm wind probability forecast are submitted at this report.

Tropical-Cyclone Formation: Theory and Idealized Modelling

DTIC Science & Technology

2010-11-01

to saturation at the sea-surface temperature and the positive entropy flux from the ocean surface...and Atmospheric Administration; IFEX = Intensity Forecasting Experiment. 15GFS = NOAA Global Forecasting System ; NOGAPS = Navy Operational Global... Atmospheric Prediction System ; UKMET = United Kingdom Meteorological Office. 16 http://www.met.nps.edu/~mtmontgo/storms2010.html 18 overcomes

Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool

NASA Astrophysics Data System (ADS)

Wang, L.; Weiss, W. J.; Porter, J.; Schaake, J. C.; Day, G. N.; Sheer, D. P.

2013-12-01

Like most other water supply utilities, New York City's Department of Environmental Protection (DEP) has operational challenges associated with drought and wet weather events. During drought conditions, DEP must maintain water supply reliability to 9 million customers as well as meet environmental release requirements downstream of its reservoirs. During and after wet weather events, DEP must maintain turbidity compliance in its unfiltered Catskill and Delaware reservoir systems and minimize spills to mitigate downstream flooding. Proactive reservoir management - such as release restrictions to prepare for a drought or preventative drawdown in advance of a large storm - can alleviate negative impacts associated with extreme events. It is important for water managers to understand the risks associated with proactive operations so unintended consequences such as endangering water supply reliability with excessive drawdown prior to a storm event are minimized. Probabilistic hydrologic forecasts are a critical tool in quantifying these risks and allow water managers to make more informed operational decisions. DEP has recently completed development of an Operations Support Tool (OST) that integrates ensemble streamflow forecasts, real-time observations, and a reservoir system operations model into a user-friendly graphical interface that allows its water managers to take robust and defensible proactive measures in the face of challenging system conditions. Since initial development of OST was first presented at the 2011 AGU Fall Meeting, significant improvements have been made to the forecast system. First, the monthly AR1 forecasts ('Hirsch method') were upgraded with a generalized linear model (GLM) utilizing historical daily correlations ('Extended Hirsch method' or 'eHirsch'). The development of eHirsch forecasts improved predictive skill over the Hirsch method in the first week to a month from the forecast date and produced more realistic hydrographs on the tail end of high flow periods. These improvements allowed DEP to more effectively manage water quality control and spill mitigation operations immediately after storm events. Later on, post-processed hydrologic forecasts from the National Weather Service (NWS) including the Advanced Hydrologic Prediction Service (AHPS) and the Hydrologic Ensemble Forecast Service (HEFS) were implemented into OST. These forecasts further increased the predictive skill over the initial statistical models as current basin conditions (e.g. soil moisture, snowpack) and meteorological forecasts (with HEFS) are now explicitly represented. With the post-processed HEFS forecasts, DEP may now truly quantify impacts associated with wet weather events on the horizon, rather than relying on statistical representations of current hydrologic trends. This presentation will highlight the benefits of the improved forecasts using examples from actual system operations.

A Photo Storm Report Mobile Application, Processing/Distribution System, and AWIPS-II Display Concept

NASA Astrophysics Data System (ADS)

Longmore, S. P.; Bikos, D.; Szoke, E.; Miller, S. D.; Brummer, R.; Lindsey, D. T.; Hillger, D.

2014-12-01

The increasing use of mobile phones equipped with digital cameras and the ability to post images and information to the Internet in real-time has significantly improved the ability to report events almost instantaneously. In the context of severe weather reports, a representative digital image conveys significantly more information than a simple text or phone relayed report to a weather forecaster issuing severe weather warnings. It also allows the forecaster to reasonably discern the validity and quality of a storm report. Posting geo-located, time stamped storm report photographs utilizing a mobile phone application to NWS social media weather forecast office pages has generated recent positive feedback from forecasters. Building upon this feedback, this discussion advances the concept, development, and implementation of a formalized Photo Storm Report (PSR) mobile application, processing and distribution system and Advanced Weather Interactive Processing System II (AWIPS-II) plug-in display software.The PSR system would be composed of three core components: i) a mobile phone application, ii) a processing and distribution software and hardware system, and iii) AWIPS-II data, exchange and visualization plug-in software. i) The mobile phone application would allow web-registered users to send geo-location, view direction, and time stamped PSRs along with severe weather type and comments to the processing and distribution servers. ii) The servers would receive PSRs, convert images and information to NWS network bandwidth manageable sizes in an AWIPS-II data format, distribute them on the NWS data communications network, and archive the original PSRs for possible future research datasets. iii) The AWIPS-II data and exchange plug-ins would archive PSRs, and the visualization plug-in would display PSR locations, times and directions by hour, similar to surface observations. Hovering on individual PSRs would reveal photo thumbnails and clicking on them would display the full resolution photograph.Here, we present initial NWS forecaster feedback received from social media posted PSRs, motivating the possible advantages of PSRs within AWIPS-II, the details of developing and implementing a PSR system, and possible future applications beyond severe weather reports and AWIPS-II.

(abstract) Application of the GPS Worldwide Network in the Study of Global Ionospheric Storms

NASA Technical Reports Server (NTRS)

Ho, C. M.; Mannucci, A. J.; Lindqwister, U. J.; Pi, X.; Sparks, L. C.; Rao, A. M.; Wilsion, B. D.; Yuan, D. N.; Reyes, M.

1997-01-01

Ionospheric storm dynamics as a response to the geomagnetic storms is a very complicated global process involving many different mechanisms. Studying ionospheric storms will help us to understand the energy coupling process between the Sun and Earth and possibly also to effectively forecast space weather changes. Such a study requires a worldwide monitoring system. The worldwide GPS network, for the first time, makes near real-time global ionospheric TEC measurements a possibility.

Forecasts and Warnings of Extreme Solar Storms at the Sun

NASA Astrophysics Data System (ADS)

Lundstedt, H.

2015-12-01

The most pressing space weather forecasts and warnings are those of the most intense solar flares and coronal mass ejections. However, in trying to develop these forecasts and warnings, we are confronted to many fundamental questions. Some of those are: How to define an observable measure for an extreme solar storm? How extreme can a solar storm become and how long is the build up time? How to make forecasts and warnings? Many have contributed to clarifying these general questions. In his presentation we will describe our latest results on the topological complexity of magnetic fields and the use of SDO SHARP parameters. The complexity concept will then be used to discuss the second question. Finally we will describe probability estimates of extreme solar storms.

An early warning system for marine storm hazard mitigation

NASA Astrophysics Data System (ADS)

Vousdoukas, M. I.; Almeida, L. P.; Pacheco, A.; Ferreira, O.

2012-04-01

The present contribution presents efforts towards the development of an operational Early Warning System for storm hazard prediction and mitigation. The system consists of a calibrated nested-model train which consists of specially calibrated Wave Watch III, SWAN and XBeach models. The numerical simulations provide daily forecasts of the hydrodynamic conditions, morphological change and overtopping risk at the area of interest. The model predictions are processed by a 'translation' module which is based on site-specific Storm Impact Indicators (SIIs) (Ciavola et al., 2011, Storm impacts along European coastlines. Part 2: lessons learned from the MICORE project, Environmental Science & Policy, Vol 14), and warnings are issued when pre-defined threshold values are exceeded. For the present site the selected SIIs were (i) the maximum wave run-up height during the simulations; and (ii) the dune-foot horizontal retreat at the end of the simulations. Both SIIs and pre-defined thresholds were carefully selected on the grounds of existing experience and field data. Four risk levels were considered, each associated with an intervention approach, recommended to the responsible coastal protection authority. Regular updating of the topography/bathymetry is critical for the performance of the storm impact forecasting, especially when there are significant morphological changes. The system can be extended to other critical problems, like implications of global warming and adaptive management strategies, while the approach presently followed, from model calibration to the early warning system for storm hazard mitigation, can be applied to other sites worldwide, with minor adaptations.

Assimilation of Dual-Polarimetric Radar Observations with WRF GSI

NASA Technical Reports Server (NTRS)

Li, Xuanli; Mecikalski, John; Fehnel, Traci; Zavodsky, Bradley; Srikishen, Jayanthi

2014-01-01

Dual-polarimetric (dual-pol) radar typically transmits both horizontally and vertically polarized radio wave pulses. From the two different reflected power returns, more accurate estimate of liquid and solid cloud and precipitation can be provided. The upgrade of the traditional NWS WSR-88D radar to include dual-pol capabilities will soon be completed for the entire NEXRAD network. Therefore, the use of dual-pol radar network will have a broad impact in both research and operational communities. The assimilation of dual-pol radar data is especially challenging as few guidelines have been provided by previous research. It is our goal to examine how to best use dual-pol radar data to improve forecast of severe storm and forecast initialization. In recent years, the Development Testbed Center (DTC) has released the community Gridpoint Statistical Interpolation (GSI) DA system for the Weather Research and Forecasting (WRF) model. The community GSI system runs in independently environment, yet works functionally equivalent to operational centers. With collaboration with the NASA Short-term Prediction Research and Transition (SPoRT) Center, this study explores regional assimilation of the dual-pol radar variables from the WSR-88D radars for real case storms. Our presentation will highlight our recent effort on incorporating the horizontal reflectivity (ZH), differential reflectivity (ZDR), specific differential phase (KDP), and radial velocity (VR) data for initializing convective storms, with a significant focus being on an improved representation of hydrometeor fields. In addition, discussion will be provided on the development of enhanced assimilation procedures in the GSI system with respect to dual-pol variables. Beyond the dual-pol variable assimilation procedure developing within a GSI framework, highresolution (=1 km) WRF model simulations and storm scale data assimilation experiments will be examined, emphasizing both model initialization and short-term forecast of precipitation fields and processes. Further details of the methodology of data assimilation, the impact of different dual-pol variables, the influence on precipitation forecast will be presented at the conference.

Storming ahead

NASA Astrophysics Data System (ADS)

Showstack, Randy

Fourteen tropical storms, nine hurricanes, and four intense hurricanes with winds above 111 mph. That's the forecast for hurricane activity in the Atlantic Basin for the upcoming hurricane season which extends from June 1 through November 30, 1999, according to a Colorado State Hurricane Forecast team led by William Gray, professor of atmospheric science. The forecast supports an earlier report by the team.Hurricane activity, said Gray will be similar to 1998—which yielded 14 tropical storms, 10 hurricanes, and 3 intense storms. These numbers are significantly higher than the long-term statistical averages of 9.3, 5.8, and 2.2, annually.

Comparative analysis of GPS-derived TEC estimates and foF2 observations during storm conditions towards the expansion of ionospheric forecasting capabilities over Europe

NASA Astrophysics Data System (ADS)

Tsagouri, Ioanna; Belehaki, Anna; Elias, Panagiotis

2017-04-01

This paper builts the discussion on the comparative analysis of the variations in the peak electron density at F2 layer and the TEC parameter during a significant number of geomagnetic storm events that occurred in the present solar cycle 24. The ionospheric disturbances are determined through the comparison of actual observations of the foF2 critical frequency and GPS-TEC estimates obtained over European locations with the corresponding median estimates, and they are analysed in conjunction to the solar wind conditions at L1 point that are monitored by the ACE spacecraft. The quantification of the storm impact on the TEC parameter in terms of possible limitations introduced by different TEC derivation methods is carefully addressed.The results reveal similarities and differences in the response of the two parameters with respect to the solar wind drivers of the storms, as well as the local time and the latitude of the observation point. The aforementioned dependences drive the storm-time forecasts of the SWIF model (Solar Wind driven autorgressive model for Ionospheric short-term Forecast), which is operationally implemented in the DIAS system (http://dias.space.noa.gr) and extensively tested in performance at several occassions. In its present version, the model provides alerts and warnings for upcoming ionospheric disturbances, as well as single site and regional forecasts of the foF2 characteristic over Europe up to 24 hours ahead based on the assesment of the solar wind conditions at ACE location. In that respect, the results obtained above support the upgrade of the SWIF's modeling technique in forecasting the storm-time TEC variation within an operational environment several hours in advance. Preliminary results on the evaluation of the model's efficiency in TEC prediction are also discussed, giving special attention in the assesment of the capabilities through the TEC-derivation uncertanties for future discussions.

33 CFR 150.445 - When is oil in a single point mooring-oil transfer system (SPM-OTS) displaced with water?

Code of Federal Regulations, 2010 CFR

2010-07-01

... the pipeline end manifold must be closed whenever: (1) A storm warning forecasts weather conditions... vessel is about to depart the SPM because of storm conditions; or (3) The SPM is not scheduled for use in...

33 CFR 150.445 - When is oil in a single point mooring-oil transfer system (SPM-OTS) displaced with water?

Code of Federal Regulations, 2011 CFR

2011-07-01

... the pipeline end manifold must be closed whenever: (1) A storm warning forecasts weather conditions... vessel is about to depart the SPM because of storm conditions; or (3) The SPM is not scheduled for use in...

33 CFR 150.445 - When is oil in a single point mooring-oil transfer system (SPM-OTS) displaced with water?

Code of Federal Regulations, 2014 CFR

2014-07-01

... the pipeline end manifold must be closed whenever: (1) A storm warning forecasts weather conditions... vessel is about to depart the SPM because of storm conditions; or (3) The SPM is not scheduled for use in...

33 CFR 150.445 - When is oil in a single point mooring-oil transfer system (SPM-OTS) displaced with water?

Code of Federal Regulations, 2013 CFR

2013-07-01

... the pipeline end manifold must be closed whenever: (1) A storm warning forecasts weather conditions... vessel is about to depart the SPM because of storm conditions; or (3) The SPM is not scheduled for use in...

33 CFR 150.445 - When is oil in a single point mooring-oil transfer system (SPM-OTS) displaced with water?

Code of Federal Regulations, 2012 CFR

2012-07-01

... the pipeline end manifold must be closed whenever: (1) A storm warning forecasts weather conditions... vessel is about to depart the SPM because of storm conditions; or (3) The SPM is not scheduled for use in...

AI techniques in geomagnetic storm forecasting

NASA Astrophysics Data System (ADS)

Lundstedt, Henrik

This review deals with how geomagnetic storms can be predicted with the use of Artificial Intelligence (AI) techniques. Today many different Al techniques have been developed, such as symbolic systems (expert and fuzzy systems) and connectionism systems (neural networks). Even integrations of AI techniques exist, so called Intelligent Hybrid Systems (IHS). These systems are capable of learning the mathematical functions underlying the operation of non-linear dynamic systems and also to explain the knowledge they have learned. Very few such powerful systems exist at present. Two such examples are the Magnetospheric Specification Forecast Model of Rice University and the Lund Space Weather Model of Lund University. Various attempts to predict geomagnetic storms on long to short-term are reviewed in this article. Predictions of a month to days ahead most often use solar data as input. The first SOHO data are now available. Due to the high temporal and spatial resolution new solar physics have been revealed. These SOHO data might lead to a breakthrough in these predictions. Predictions hours ahead and shorter rely on real-time solar wind data. WIND gives us real-time data for only part of the day. However, with the launch of the ACE spacecraft in 1997, real-time data during 24 hours will be available. That might lead to the second breakthrough for predictions of geomagnetic storms.

Prediction of Winter Storm Tracks and Intensities Using the GFDL fvGFS Model

NASA Astrophysics Data System (ADS)

Rees, S.; Boaggio, K.; Marchok, T.; Morin, M.; Lin, S. J.

2017-12-01

The GFDL Finite-Volume Cubed-Sphere Dynamical core (FV3) is coupled to a modified version of the Global Forecast System (GFS) physics and initial conditions, to form the fvGFS model. This model is similar to the one being implemented as the next-generation operational weather model for the NWS, which is also FV3-powered. Much work has been done to verify fvGFS tropical cyclone prediction, but little has been done to verify winter storm prediction. These costly and dangerous storms impact parts of the U.S. every year. To verify winter storms we ran the NCEP operational cyclone tracker, developed at GFDL, on semi-real-time 13 km horizontal resolution fvGFS forecasts. We have found that fvGFS compares well to the operational GFS in storm track and intensity, though often predicts slightly higher intensities. This presentation will show the track and intensity verification from the past two winter seasons and explore possible reasons for bias.

Simplified methods for real-time prediction of storm surge uncertainty: The city of Venice case study

NASA Astrophysics Data System (ADS)

Mel, Riccardo; Viero, Daniele Pietro; Carniello, Luca; Defina, Andrea; D'Alpaos, Luigi

2014-09-01

Providing reliable and accurate storm surge forecasts is important for a wide range of problems related to coastal environments. In order to adequately support decision-making processes, it also become increasingly important to be able to estimate the uncertainty associated with the storm surge forecast. The procedure commonly adopted to do this uses the results of a hydrodynamic model forced by a set of different meteorological forecasts; however, this approach requires a considerable, if not prohibitive, computational cost for real-time application. In the present paper we present two simplified methods for estimating the uncertainty affecting storm surge prediction with moderate computational effort. In the first approach we use a computationally fast, statistical tidal model instead of a hydrodynamic numerical model to estimate storm surge uncertainty. The second approach is based on the observation that the uncertainty in the sea level forecast mainly stems from the uncertainty affecting the meteorological fields; this has led to the idea to estimate forecast uncertainty via a linear combination of suitable meteorological variances, directly extracted from the meteorological fields. The proposed methods were applied to estimate the uncertainty in the storm surge forecast in the Venice Lagoon. The results clearly show that the uncertainty estimated through a linear combination of suitable meteorological variances nicely matches the one obtained using the deterministic approach and overcomes some intrinsic limitations in the use of a statistical tidal model.

Development of the Centralized Storm Information System (CSIS) for use in severe weather prediction

NASA Technical Reports Server (NTRS)

Mosher, F. R.

1984-01-01

The centralized storm information system is now capable of ingesting and remapping radar scope presentations on a satellite projection. This can be color enhanced and superposed on other data types. Presentations from more than one radar can be composited on a single image. As with most other data sources, a simple macro establishes the loops and scheduling of the radar ingestions as well as the autodialing. There are approximately 60 NWS network 10 cm radars that can be interrogated. NSSFC forecasters have found this data source to be extremely helpful in severe weather situations. The capability to access lightning frequency data stored in a National Weather Service computer was added. Plans call for an interface with the National Meteorological Center to receive and display prognostic fields from operational computer forecast models. Programs are to be developed to plot and display locations of reported severe local storm events.

The Role of a Lid in the 31 May 1985 Tornado Outbreak

DTIC Science & Technology

1988-05-01

severe convection. Subjective analysis necessary to use this mode], however, is much too time consuming for operational forecasting . Therefore, a...analysis necessary to use this conceptual model, however, is much too time consuming for operational forecasting . Therefore, a computer application was...the forecasting of these systems continue to be desirable. Most severe convective storms in mid-latitudes are mesoscale phenomena. The term mesoscale

Long-Range Operational Military Forecasts for Afghanistan

DTIC Science & Technology

2007-03-01

the winter and early spring months with eastward–moving extratropical synoptic storms , such as the Cyprus and Genoa low pressure systems out of the...significant impact on the storm track, temperature, and precipitation across the Northern Atlantic and into Europe and the Mediterranean. The positive...advection of moisture out of the Arabian Sea or out of central Asia. The NAO impacts on 850hPa temperatures are associated with variations in storm

Storms in Space

NASA Astrophysics Data System (ADS)

Freeman, John W.

2012-11-01

Introduction; The cast of characters; Vignettes of the storm; 1. Two kinds of weather; 2. The saga of the storm; 3. Weather stations in space; 4. Lights in the night: the signature of the storm; 5. A walking tour of the magnetosphere; 6. The sun: where it all begins; 7. Nowcasting and forecasting storms in space; 8. Technology and the risks from storms in space; 9. A conversation with Joe Allen; 10. Manned exploration and space weather hazards; 11. The present and future of space weather forecasting; Mathematical appendix. A closer look; Glossary; Figure captions.

High resolution climate projection of storm surge at the Venetian coast

NASA Astrophysics Data System (ADS)

Mel, R.; Sterl, A.; Lionello, P.

2013-04-01

Climate change impact on storm surge regime is of great importance for the safety and maintenance of Venice. In this study a future storm surge scenario is evaluated using new high resolution sea level pressure and wind data recently produced by EC-Earth, an Earth System Model based on the operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts (ECMWF). The study considers an ensemble of six 5 yr long simulations of the rcp45 scenario at 0.25° resolution and compares the 2094-2098 to the 2004-2008 period. EC-Earth sea level pressure and surface wind fields are used as input for a shallow water hydrodynamic model (HYPSE) which computes sea level and barotropic currents in the Adriatic Sea. Results show that a high resolution climate model is needed for producing realistic values of storm surge statistics and confirm previous studies in that they show little sensitivity of storm surge levels to climate change. However, some climate change signals are detected, such as increased persistence of high pressure conditions, an increased frequency of windless hour, and a decreased number of moderate windstorms.

Key forecasts shaping nursing's perfect storm.

PubMed

Yoder-Wise, Patricia S

2007-01-01

Perfect storms abound in nursing and healthcare. How we plan for them and how we forecast effectively which ones will have tremendous impact on how we lead the profession is a challenge to anyone who is or will be a leader. This article focuses on key forecasts that contribute to creating perfect storms of the future. The "perfect storm" is a term found in multiple disciplines. The phrase denotes the condition that exists when events occur simultaneously with the result that this confluence has a greater impact than what could have resulted from a chance combination. Although perfect storms are rare, they have enormous impact when they occur, and if an alteration in any of the events occurs, the overall impact is lessened.

Cyclone Xaver seen by SARAL/AltiKa

NASA Astrophysics Data System (ADS)

Scharroo, Remko; Fenoglio, Luciana; Annunziato, Alessandro

2014-05-01

During the first week of December 2013, Cyclone Xaver pounded the coasts and the North Sea. On 6 December, all along the Wadden Sea, the barrier islands along the north of the Netherlands and the northwest of Germany experienced record storm surges. We show a comparison of the storm surge measured by the radar altimeter AltiKa on-board the SARAL satellite and various types of in-situ data and models. Two tide gauges along the German North Sea coast, one in the southern harbour of the island of Helgoland and one on an offshore lighthouse Alte Weser, confirmed that the storm drove sea level to about three meters above the normal tide level. Loading effects during the storm are also detected by the GPS measurements at several tide gauge stations. The altimeter in the mean time shows that the storm surge was noticeable as far as 400 km from the coast. The altimeter measured wind speeds of 20 m/s nearly monotonically throughout the North Sea. An offshore anemometer near the island of Borkum corroborated this value. A buoy near the FINO1 offshore platform measured wave heights of 8 m, matching quite well the measurements from the altimeter, ranging from 6 m near the German coast to 12 m further out into the North Sea. Furthermore we compare the altimeter-derived and in-situ sea level, wave height and wind speed products with outputs from the Operation Circulation and Forecast model of the Bundesamt für Seeschifffahrt und Hydrographie (BSH) and with a global storm surge forecast and inundation model of the Joint Research Centre (JRC) of the European Commission. The Operational circulation model of BSH (BSHcmod) and its component, the surge model (BSHsmod), perform daily predictions for the next 72 hours based on the meteorological model of the Deutsche Wetterdienst (DWD). The JRC Storm Surge Calculation System is a new development that has been established at the JRC in the framework of the Global Disasters Alerts and Coordination System (GDACS). The system uses meteorological forecasts produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) to estimate (with a 2-day lead time) potential storm surges due to cyclone or general storm events. Departure between model and altimeter-derived values, in particularly wind, are investigated and discussed. The qualitative agreement is satisfactory; the maximum storm surge peak is correctly estimated by BSH but underestimated by JRC due to insufficient wind forcing. The wind speed of SARAL/AltiKa agrees well with the ECMWF model wind speed but is lower than the DWD model estimate. The authors acknowledge the kind support from the BSH, the Bundesumweltministerium (BMU), Projectträger Jülich (PTJ), and the Wasser- und Schifffahrtsverwaltung des Bundes (WSV).

Effect of pellet-cladding interaction (PCI) and degradation mechanisms on spent nuclear fuel rod mechanical performance during transportation

NASA Astrophysics Data System (ADS)

Peterson, Brittany Ann

Winter storms can affect millions of people, with impacts such as disruptions to transportation, hazards to human health, reduction in retail sales, and structural damage. Blizzard forecasts for Alberta Clippers can be a particular challenge in the Northern Plains, as these systems typically depart from the Canadian Rockies, intensify, and impact the Northern Plains all within 24 hours. The purpose of this study is to determine whether probabilistic forecasts derived from a local physics-based ensemble can improve specific aspects of winter storm forecasts for three Alberta Clipper cases. Verification is performed on the ensemble members and ensemble mean with a focus on quantifying uncertainty in the storm track, two-meter winds, and precipitation using the MERRA and NOHRSC SNODAS datasets. This study finds that addition improvements are needed to proceed with operational use of the ensemble blizzard products, but the use of a proxy for blizzard conditions yields promising results.

Improving global flood risk awareness through collaborative research: Id-Lab

NASA Astrophysics Data System (ADS)

Weerts, A.; Zijderveld, A.; Cumiskey, L.; Buckman, L.; Verlaan, M.; Baart, F.

2015-12-01

Scientific and end-user collaboration on operational flood risk modelling and forecasting requires an environment where scientists and end-users can physically work together and demonstrate, enhance and learn about new tools, methods and models for forecasting and warning purposes. Therefore, Deltares has built a real-time demonstration, training and research infrastructure ('operational' room and ICT backend). This research infrastructure supports various functions like (1) Real time response and disaster management, (2) Training, (3) Collaborative Research, (4) Demonstration. The research infrastructure will be used for a mixture of these functions on a regular basis by Deltares and a multitude of both scientists as well as end users such as universities, research institutes, consultants, governments and aid agencies. This infrastructure facilitates emergency advice and support during international and national disasters caused by rainfall, tropical cyclones or tsunamis. It hosts research flood and storm surge forecasting systems for global/continental/regional scale. It facilitates training for emergency & disaster management (along with hosting forecasting system user trainings in for instance the forecasting platform Delft-FEWS) both internally and externally. The facility is expected to inspire and initiate creative innovations by bringing together different experts from various organizations. The room hosts interactive modelling developments, participatory workshops and stakeholder meetings. State of the art tools, models and software, being applied across the globe are available and on display within the facility. We will present the Id-Lab in detail and we will put particular focus on the global operational forecasting systems GLOFFIS (Global Flood Forecasting Information System) and GLOSSIS (Global Storm Surge Information System).

Assessing the spatial variability of mountain precipitation in California's Sierra Nevada using the Airborne Snow Observatory

NASA Astrophysics Data System (ADS)

Brandt, T.; Deems, J. S.; Painter, T. H.; Dozier, J.

2016-12-01

In California's Sierra Nevada, 10 or fewer winter storms are responsible for most of the annual precipitation, which falls mostly as snow. Presently, surface stations are used to measure the dynamics of mountain precipitation. However, even in places like the Sierra Nevada—one of the most gauged regions in the world—the paucity of surface stations can lead to large errors in precipitation thereby biasing both total water year and short-term streamflow forecasts. Remotely sensed snow depth and water equivalent, at a time scale that resolves storms, might provide a novel solution to the problems of: (1) quantifying the spatial variability of mountain precipitation; and (2) assessing gridded precipitation products that are mostly based on surface station interpolation. NASA's Airborne Snow Observatory (ASO), an imaging spectrometer and LiDAR system, has measured snow in the Tuolumne River Basin in California's Sierra Nevada for the past four years, 2013-2016; and, measurements will continue. Principally, ASO monitors the progression of melt for water supply forecasting, nonetheless, a number of flights bracketed storms allowing for estimates of snow accumulation. In this study we examine a few of the ASO recorded storms to determine both the basin and subbasin orographic effect as well as the spatial patterns in total precipitation. We then compare these results to a number of gridded climate products and weather models including: Daymet, the Parameter-elevation Regressions on Independent Slopes Model (PRISM), the North American Land Data Assimilation System (NLDAS-2), and the Weather Research and Forecasting (WRF) model. Finally, to put each ASO recorded storm into context, we use a climatology produced from snow pillows and the North American Regional Reanalysis (NARR) for 2014-2016 to examine key accumulation events, and classify storms based on their integrated water vapor flux.

Operation of a real-time warning system for debris flows in the San Francisco bay area, California

USGS Publications Warehouse

Wilson, Raymond C.; Mark, Robert K.; Barbato, Gary; ,

1993-01-01

The United States Geological Survey (USGS) and the National Weather Service (NWS) have developed an operational warning system for debris flows during severe rainstorms in the San Francisco Bay region. The NWS makes quantitative forecasts of precipitation from storm systems approaching the Bay area and coordinates a regional network of radio-telemetered rain gages. The USGS has formulated thresholds for the intensity and duration of rainfall required to initiate debris flows. The first successful public warnings were issued during a severe storm sequence in February 1986. Continued operation of the warning system since 1986 has provided valuable working experience in rainfall forecasting and monitoring, refined rainfall thresholds, and streamlined procedures for issuing public warnings. Advisory statements issued since 1986 are summarized.

The Importance of Hurricane Research to Life, Property, the Economy, and National Security.

NASA Astrophysics Data System (ADS)

Busalacchi, A. J.

2017-12-01

The devastating 2017 Atlantic hurricane season has brought into stark relief how much hurricane forecasts have improved - and how important it is to make them even better. Whereas the error in 48-hour track forecasts has been reduced by more than half, according to the National Hurricane Center, intensity forecasts remain challenging, especially with storms such as Harvey that strengthened from a tropical depression to a Category 4 hurricane in less than three days. The unusually active season, with Hurricane Irma sustaining 185-mph winds for a record 36 hours and two Atlantic hurricanes reaching 150-mph winds simultaneously for the first time, also highlighted what we do, and do not, know about how tropical cyclones will change as the climate warms. The extraordinary toll of Hurricanes Harvey, Irma, and Maria - which may ultimately be responsible for hundreds of deaths and an estimated $200 billion or more in damages - underscores why investments into improved forecasting must be a national priority. At NCAR and UCAR, scientists are working with their colleagues at federal agencies, the private sector, and the university community to advance our understanding of these deadly storms. Among their many projects, NCAR researchers are making experimental tropical cyclone forecasts using an innovative Earth system model that allows for variable resolution. We are working with NOAA to issue flooding, inundation, and streamflow forecasts for areas hit by hurricanes, and we have used extremely high-resolution regional models to simulate successfully the rapid hurricane intensification that has proved so difficult to predict. We are assessing ways to better predict the damage potential of tropical cyclones by looking beyond wind speed to consider such important factors as the size and forward motion of the storm. On the important question of climate change, scientists have experimented with running coupled climate models at a high enough resolution to spin up a hurricane, and we have used a convection-permitting regional model to examine how named storms of the past might look if they were to formed in a warmer, wetter future. Finally, research is also being performed to better communicate forecasts to help residents make informed choices when a damaging storm approaches.

Predictability of tropical cyclone events on intraseasonal timescales with the ECMWF monthly forecast model

NASA Astrophysics Data System (ADS)

Elsberry, Russell L.; Jordan, Mary S.; Vitart, Frederic

2010-05-01

The objective of this study is to provide evidence of predictability on intraseasonal time scales (10-30 days) for western North Pacific tropical cyclone formation and subsequent tracks using the 51-member ECMWF 32-day forecasts made once a week from 5 June through 25 December 2008. Ensemble storms are defined by grouping ensemble member vortices whose positions are within a specified separation distance that is equal to 180 n mi at the initial forecast time t and increases linearly to 420 n mi at Day 14 and then is constant. The 12-h track segments are calculated with a Weighted-Mean Vector Motion technique in which the weighting factor is inversely proportional to the distance from the endpoint of the previous 12-h motion vector. Seventy-six percent of the ensemble storms had five or fewer member vortices. On average, the ensemble storms begin 2.5 days before the first entry of the Joint Typhoon Warning Center (JTWC) best-track file, tend to translate too slowly in the deep tropics, and persist for longer periods over land. A strict objective matching technique with the JTWC storms is combined with a second subjective procedure that is then applied to identify nearby ensemble storms that would indicate a greater likelihood of a tropical cyclone developing in that region with that track orientation. The ensemble storms identified in the ECMWF 32-day forecasts provided guidance on intraseasonal timescales of the formations and tracks of the three strongest typhoons and two other typhoons, but not for two early season typhoons and the late season Dolphin. Four strong tropical storms were predicted consistently over Week-1 through Week-4, as was one weak tropical storm. Two other weak tropical storms, three tropical cyclones that developed from precursor baroclinic systems, and three other tropical depressions were not predicted on intraseasonal timescales. At least for the strongest tropical cyclones during the peak season, the ECMWF 32-day ensemble provides guidance of formation and tracks on 10-30 day timescales.

Adapting NEMO for use as the UK operational storm surge forecasting model

NASA Astrophysics Data System (ADS)

Furner, Rachel; Williams, Jane; Horsburgh, Kevin; Saulter, Andrew

2016-04-01

The United Kingdom is an area vulnerable to damage due to storm surges, particularly the East Coast which suffered losses estimated at over £1 billion during the North Sea surge event of the 5th and 6th December 2013. Accurate forecasting of storm surge events for this region is crucial to enable government agencies to assess the risk of overtopping of coastal defences so they can respond appropriately, minimising risk to life and infrastructure. There has been an operational storm surge forecast service for this region since 1978, using a numerical model developed by the National Oceanography Centre (NOC) and run at the UK Met Office. This is also implemented as part of an ensemble prediction system, using perturbed atmospheric forcing to produce an ensemble surge forecast. In order to ensure efficient use of future supercomputer developments and to create synergy with existing operational coastal ocean models the Met Office and NOC have begun a joint project transitioning the storm surge forecast system from the current CS3X code base to a configuration based on the Nucleus for European Modelling of the Ocean (NEMO). This work involves both adapting NEMO to add functionality, such as allowing the drying out of ocean cells and changes allowing NEMO to run efficiently as a two-dimensional, barotropic model. As the ensemble surge forecast system is run with 12 members 4 times a day computational efficiency is of high importance. Upon completion this project will enable interesting scientific comparisons to be made between a NEMO based surge model and the full three-dimensional baroclinic NEMO based models currently run within the Met Office, facilitating assessment of the impact of baroclinic processes, and vertical resolution on sea surface height forecasts. Moving to a NEMO code base will also allow many future developments to be more easily used within the storm surge model due to the wide range of options which currently exist within NEMO or are planned for future NEMO releases, such as data assimilation, and surge-wave coupling. Assessment of tidal performance of the NEMO-surge configuration and comparison to the existing operational CS3X model has been carried out. Evaluation of the models focus on performance relative to the UK Class A tide gauge network, a dataset which was established following the devastating flood of 1953 and which is managed by the British Oceanographic Data Service (BODC) based at NOC. Trials of the NEMO model in tide-only mode have illustrated the importance of having a well specified bathymetry and, for the 7km scaled model, a secondary sensitivity to bed friction coefficient and the specification of the coastline. Preliminary results will also be presented from model runs with atmospheric (wind stress and pressure at mean sea-level) forcing.

a 24/7 High Resolution Storm Surge, Inundation and Circulation Forecasting System for Florida Coast

NASA Astrophysics Data System (ADS)

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

2012-12-01

A 24/7 forecasting system for Florida is needed because of the high risk of tropical storm surge-induced coastal inundation and damage, and the need to support operational management of water resources, utility infrastructures, and fishery resources. With the anticipated climate change impacts, including sea level rise, coastal areas are facing the challenges of increasing inundation risk and increasing population. Accurate 24/7 forecasting of water level, inundation, and circulation will significantly enhance the sustainability of coastal communities and environments. Supported by the Southeast Coastal Ocean Observing Regional Association (SECOORA) through NOAA IOOS, a 24/7 high-resolution forecasting system for storm surge, coastal inundation, and baroclinic circulation is being developed for Florida using CH3D Storm Surge Modeling System (CH3D-SSMS). CH3D-SSMS is based on the CH3D hydrodynamic model coupled to a coastal wave model SWAN and basin scale surge and wave models. CH3D-SSMS has been verified with surge, wave, and circulation data from several recent hurricanes in the U.S.: Isabel (2003); Charley, Dennis and Ivan (2004); Katrina and Wilma (2005); Ike and Fay (2008); and Irene (2011), as well as typhoons in the Pacific: Fanapi (2010) and Nanmadol (2011). The effects of tropical cyclones on flow and salinity distribution in estuarine and coastal waters has been simulated for Apalachicola Bay as well as Guana-Tolomato-Matanzas Estuary using CH3D-SSMS. The system successfully reproduced different physical phenomena including large waves during Ivan that damaged I-10 Bridges, a large alongshore wave and coastal flooding during Wilma, salinity drop during Fay, and flooding in Taiwan as a result of combined surge and rain effect during Fanapi. The system uses 4 domains that cover entire Florida coastline: West, which covers the Florida panhandle and Tampa Bay; Southwest spans from Florida Keys to Charlotte Harbor; Southeast, covering Biscayne Bay and Miami and East, which continues north to the Florida/Georgia border. The system has a data acquisition and processing module that is used to collect data for model runs (e.g. wind, river flow, precipitation). Depending on the domain, forecasts runs can take ~1-18 hours to complete on a single CPU (8-core) system (1-2 hrs for 2D setup and up to 18 hrs for a 3D setup) with 4 forecasts generated per day. All data is archived / catalogued and model forecast skill is continuously being evaluated. In addition to the baseline forecasts, additional forecasts are being perform using various options for wind forcing (GFS, GFDL, WRF, and parametric hurricane models), model configurations (2D/ 3D), and open boundary conditions by coupling with large scale models (ROMS, NCOM, HYCOM), as well as incorporating real-time and forecast river flow and precipitation data to better understand how to improve model skill. In addition, new forecast products (e.g. more informative inundation maps) are being developed to targeted stakeholders. To support modern data standards, CH3D-SSMS results are available online via a THREDDS server in CF-Compliant NetCDF format as well as other stakeholder-friendly (e.g. GIS) formats. The SECOORA website provides visualization of the model via GODIVA-THREDDS interface.

An Investigation of Interplanetary Structures for Solar Cycles 23 and 24 and their Space Weather Consequences.

NASA Astrophysics Data System (ADS)

Sultan, M. S.; Jules, A.; Marchese, P.; Damas, M. C.

2017-12-01

It is crucial to study space weather because severe interplanetary conditions can cause geomagnetic storms that may damage both space- and ground-based technological systems such as satellites, communication systems, and power grids. Interplanetary coronal mass ejections (ICMEs) and corotating interaction regions (CIRs) are the primary drivers of geomagnetic storms. As they travel through interplanetary space and reach geospace, their spatial structures change which can result in various geomagnetic effects. Therefore, studying these drivers and their structures is essential in order to better understand and mitigate their impact on technological systems, as well as to forecast geomagnetic storms. In this study, over 150 storms were cross-checked for both solar cycles (SC) 23 and 24. This data has revealed the most common interplanetary structures, i.e., sheath (Sh); magnetic cloud following a shock front (sMC); sheath region and magnetic cloud (Sh/MC); and corotating interaction regions (CIRs). Furthermore, plasma parameters as well as variation in the intensity and duration of storms resulting from different interplanetary structures are studied for their effect on geomagnetically induced currents (GICs), as well as for their effect on power grids. Although preliminary results for SC 23 indicate that storm intensity may play a dominant role for GICs, duration might also be a factor, albeit smaller. Results from both SC 23 and 24 are analyzed and compared, and should lead to an enhanced understanding of space weather consequences of interplanetary structures and their possible forecasting.

Testing a Mobile Version of a Cross-Chain Loran Atmospheric (M-CLASS) Sounding System.

NASA Astrophysics Data System (ADS)

Rust, W. David; Burgess, Donald W.; Maddox, Robert A.; Showell, Lester C.; Marshall, Thomas C.; Lauritsen, Dean K.

1990-02-01

We have Rested the NCAR Cross-Chain LORAN Atmospheric Sounding System (CLASS) in a fully mobile configuration, which we call M-CLASS. The sondes use LORAN-C navigation signals to allow calculation of balloon position and horizontal winds. In nonstormy environments, thermodynamics and wind data were almost always of high quality. Besides providing special soundings for operational forecasts and research programs, a major feature of mobile ballooning with M-CLASS is the ability to obtain additional data by flying other instruments on the balloons. We flew an electric field meter, along with a sonde, into storms on 8 of the initial 47 test flights in the spring of 1987. In storms, pressure, temperature, humidity, and wind data were of good quality about 80%, 75%, 60%, and 40% of the time, respectively. In a flight into a mesocyclone, we measured electric fields as high as 135 kV/m (at 10 km MSL) in a region of negative charge. The electric field data from several storms allow a quantitative assessment of conditions that accompany loss of LORAN data. LORAN tracking was lost at a median field of about 16 kV/m, and it returned at a median field of about 7 kV/m. Corona discharge from the LORAN antenna on the sonde was a cause of the loss of LORAN. We provided our early-afternoon M-CLASS test soundings to the National Weather Service Forecast Office in Norman, Oklahoma, in near real-time via amateur packet radio and also to the National Severe Storms Forecast Center. These soundings illustrate the potential for improving operational forecasts. Other test flights showed that M-CLASS data can provide high-resolution information on evolution of the Great Plains low-level jet stream. Our intercept of Hurricane Gilbert provided M-CLASS soundings in the right quadrant of the storm. We observed substantial wind shear in the lowest levels of the soundings around the time tornadoes were reported in south Texas. This intercept demonstrated the feasibility of taking M-CLASS data during the landfall phase of hurricanes and tropical storms.

Potential Seasonal Predictability for Winter Storms over Europe

NASA Astrophysics Data System (ADS)

Wild, Simon; Befort, Daniel J.; Leckebusch, Gregor C.

2017-04-01

Reliable seasonal forecasts of strong extra-tropical cyclones and windstorms would have great social and economical benefits, as these events are the most costly natural hazards over Europe. In a previous study we have shown good agreement of spatial climatological distributions of extra-tropical cyclones and wind storms in state-of-the-art multi-member seasonal prediction systems with reanalysis. We also found significant seasonal prediction skill of extra-tropical cyclones and windstorms affecting numerous European countries. We continue this research by investigating the mechanisms and precursor conditions (primarily over the North Atlantic) on a seasonal time scale leading to enhanced extra-tropical cyclone activity and winter storm frequency over Europe. Our results regarding mechanisms show that an increased surface temperature gradient at the western edge of the North Atlantic can be related to enhanced winter storm frequency further downstream causing for example a greater number of storms over the British Isles, as observed in winter 2013-14.The so-called "Horseshoe Index", a SST tripole anomaly pattern over the North Atlantic in the summer months can also cause a higher number of winter storms over Europe in the subsequent winter. We will show results of AMIP-type sensitivity experiments using an AGCM (ECHAM5), supporting this hypothesis. Finally we will analyse whether existing seasonal forecast systems are able to capture these identified mechanisms and precursor conditions affecting the models' seasonal prediction skill.

METEOR - an artificial intelligence system for convective storm forecasting

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

Elio, R.; De haan, J.; Strong, G.S.

1987-03-01

An AI system called METEOR, which uses the meteorologist's heuristics, strategies, and statistical tools to forecast severe hailstorms in Alberta, is described, emphasizing the information and knowledge that METEOR uses to mimic the forecasting procedure of an expert meteorologist. METEOR is then discussed as an AI system, emphasizing the ways in which it is qualitatively different from algorithmic or statistical approaches to prediction. Some features of METEOR's design and the AI techniques for representing meteorological knowledge and for reasoning and inference are presented. Finally, some observations on designing and implementing intelligent consultants for meteorological applications are made. 7 references.

The Use of Pre-Storm Boundary-Layer Baroclinicity in Determining and Operationally Implementing the Atlantic Surface Cyclone Intensification Index

NASA Astrophysics Data System (ADS)

Cione, Joseph; Pietrafes, Leonard J.

The lateral motion of the Gulf Stream off the eastern seaboard of the United States during the winter season can act to dramatically enhance the low-level baroclinicity within the coastal zone during periods of offshore cold advection. The ralative close proximity of the Gulf Stream current off the mid-Atlantic coast can result in the rapid and intense destabilization of the marine atmospheric boundary layer directly above and shoreward of the Gulf Stream within this region. This airmass modification period often precedes either wintertime coastal cyclogenesis or the cyclonic re-development of existing mid-latitude cyclones. A climatological study investigating the relationship between the severity of the pre-storm, cold advection period and subsequent cyclogenic intensification was undertaken by Cione et al. in 1993. Findings from this study illustrate that the thermal structure of the continental airmass as well as the position of the Gulf Stream front relative to land during the pre-storm period (i.e., 24-48 h prior to the initial cyclonic intensification) are linked to the observed rate of surface cyclonic deepening for storms that either advected into or initially developed within the Carolina-southeast Virginia offshore coastal zone. It is a major objective of this research to test the potential operational utility of this pre-storm low level baroclinic linkage to subsequent cyclogenesis in an actual National Weather Service (NWS) coastal winter storm forecast setting.The ability to produce coastal surface cyclone intensity forecasts recently became available to North Carolina State University researchers and NWS forecasters. This statistical forecast guidance utilizes regression relationships derived from a nine-season (January 1982-April 1990), 116-storm study conducted previously. During the period between February 1994 and February 1996, the Atlantic Surface Cyclone Intensification Index (ASCII) was successfully implemented in an operational setting by the NWS at the Raleigh-Durham (RAH) forecast office for 10 winter storms. Analysis of these ASCII forecasts will be presented.

Using Enabling Technologies to Facilitate the Comparison of Satellite Observations with the Model Forecasts for Hurricane Study

NASA Astrophysics Data System (ADS)

Li, P.; Knosp, B.; Hristova-Veleva, S. M.; Niamsuwan, N.; Johnson, M. P.; Shen, T. P. J.; Tanelli, S.; Turk, J.; Vu, Q. A.

2014-12-01

Due to their complexity and volume, the satellite data are underutilized in today's hurricane research and operations. To better utilize these data, we developed the JPL Tropical Cyclone Information System (TCIS) - an Interactive Data Portal providing fusion between Near-Real-Time satellite observations and model forecasts to facilitate model evaluation and improvement. We have collected satellite observations and model forecasts in the Atlantic Basin and the East Pacific for the hurricane seasons since 2010 and supported the NASA Airborne Campaigns for Hurricane Study such as the Genesis and Rapid Intensification Processes (GRIP) in 2010 and the Hurricane and Severe Storm Sentinel (HS3) from 2012 to 2014. To enable the direct inter-comparisons of the satellite observations and the model forecasts, the TCIS was integrated with the NASA Earth Observing System Simulator Suite (NEOS3) to produce synthetic observations (e.g. simulated passive microwave brightness temperatures) from a number of operational hurricane forecast models (HWRF and GFS). An automated process was developed to trigger NEOS3 simulations via web services given the location and time of satellite observations, monitor the progress of the NEOS3 simulations, display the synthetic observation and ingest them into the TCIS database when they are done. In addition, three analysis tools, the joint PDF analysis of the brightness temperatures, ARCHER for finding the storm-center and the storm organization and the Wave Number Analysis tool for storm asymmetry and morphology analysis were integrated into TCIS to provide statistical and structural analysis on both observed and synthetic data. Interactive tools were built in the TCIS visualization system to allow the spatial and temporal selections of the datasets, the invocation of the tools with user specified parameters, and the display and the delivery of the results. In this presentation, we will describe the key enabling technologies behind the design of the TCIS interactive data portal and analysis tools, including the spatial database technology for the representation and query of the level 2 satellite data, the automatic process flow using web services, the interactive user interface using the Google Earth API, and a common and expandable Python wrapper to invoke the analysis tools.

Weather assessment and forecasting

NASA Technical Reports Server (NTRS)

1977-01-01

Data management program activities centered around the analyses of selected far-term Office of Applications (OA) objectives, with the intent of determining if significant data-related problems would be encountered and if so what alternative solutions would be possible. Three far-term (1985 and beyond) OA objectives selected for analyses as having potential significant data problems were large-scale weather forecasting, local weather and severe storms forecasting, and global marine weather forecasting. An overview of general weather forecasting activities and their implications upon the ground based data system is provided. Selected topics were specifically oriented to the use of satellites.

Is It Going to Rain Today? Understanding the Weather Forecast.

ERIC Educational Resources Information Center

Allsopp, Jim; And Others

1996-01-01

Presents a resource for science teachers to develop a better understanding of weather forecasts, including outlooks, watches, warnings, advisories, severe local storms, winter storms, floods, hurricanes, nonprecipitation hazards, precipitation probabilities, sky condition, and UV index. (MKR)

Military Hydrology. Report 8. Feasibility of Utilizing Satellite and Radar Data in Hydrologic Forecasting.

DTIC Science & Technology

1985-09-01

Extratropical Storm ," Draft Report. Atlas, David. 1964. "Advances in Radar Meteorology," Advances in Geophysics, Vol 10, Academic Press, N.Y., pp 318-478. Barnes...forecasting purposes, data on storm morphology, direction of movement, and rate of movement are re- quired in addition to the data cited above. 7...or storm duration. He also showed that, for a given sampling error, the gage density needed for warm season storms was two to three times greater than

Adaptive use of research aircraft data sets for hurricane forecasts

NASA Astrophysics Data System (ADS)

Biswas, M. K.; Krishnamurti, T. N.

2008-02-01

This study uses an adaptive observational strategy for hurricane forecasting. It shows the impacts of Lidar Atmospheric Sensing Experiment (LASE) and dropsonde data sets from Convection and Moisture Experiment (CAMEX) field campaigns on hurricane track and intensity forecasts. The following cases are used in this study: Bonnie, Danielle and Georges of 1998 and Erin, Gabrielle and Humberto of 2001. A single model run for each storm is carried out using the Florida State University Global Spectral Model (FSUGSM) with the European Center for Medium Range Weather Forecasts (ECMWF) analysis as initial conditions, in addition to 50 other model runs where the analysis is randomly perturbed for each storm. The centers of maximum variance of the DLM heights are located from the forecast error variance fields at the 84-hr forecast. Back correlations are then performed using the centers of these maximum variances and the fields at the 36-hr forecast. The regions having the highest correlations in the vicinity of the hurricanes are indicative of regions from where the error growth emanates and suggests the need for additional observations. Data sets are next assimilated in those areas that contain high correlations. Forecasts are computed using the new initial conditions for the storm cases, and track and intensity skills are then examined with respect to the control forecast. The adaptive strategy is capable of identifying sensitive areas where additional observations can help in reducing the hurricane track forecast errors. A reduction of position error by approximately 52% for day 3 of forecast (averaged over 7 storm cases) over the control runs is observed. The intensity forecast shows only a slight positive impact due to the model’s coarse resolution.

Storm Surge Modeling of Typhoon Haiyan at the Naval Oceanographic Office Using Delft3D

NASA Astrophysics Data System (ADS)

Gilligan, M. J.; Lovering, J. L.

2016-02-01

The Naval Oceanographic Office provides estimates of the rise in sea level along the coast due to storm surge associated with tropical cyclones, typhoons, and hurricanes. Storm surge modeling and prediction helps the US Navy by providing a threat assessment tool to help protect Navy assets and provide support for humanitarian assistance/disaster relief efforts. Recent advancements in our modeling capabilities include the use of the Delft3D modeling suite as part of a Naval Research Laboratory (NRL) developed Coastal Surge Inundation Prediction System (CSIPS). Model simulations were performed on Typhoon Haiyan, which made landfall in the Philippines in November 2013. Comparisons of model simulations using forecast and hindcast track data highlight the importance of accurate storm track information for storm surge predictions. Model runs using the forecast track prediction and hindcast track information give maximum storm surge elevations of 4 meters and 6.1 meters, respectively. Model results for the hindcast simulation were compared with data published by the JSCE-PICE Joint survey for locations in San Pedro Bay (SPB) and on the Eastern Samar Peninsula (ESP). In SPB, where wind-induced set-up predominates, the model run using the forecast track predicted surge within 2 meters in 38% of survey locations and within 3 meters in 59% of the locations. When the hindcast track was used, the model predicted within 2 meters in 77% of the locations and within 3 meters in 95% of the locations. The model was unable to predict the high surge reported along the ESP produced by infragravity wave-induced set-up, which is not simulated in the model. Additional modeling capabilities incorporating infragravity waves are required to predict storm surge accurately along open coasts with steep bathymetric slopes, such as those seen in island arcs.

The North Alabama Severe Thunderstorm Observations, Research, and Monitoring Network (STORMnet)

NASA Technical Reports Server (NTRS)

Goodman, S. J.; Blakeslee, R.; Christian, H.; Boccippio, D.; Koshak, W.; Bailey, J.; Hall, J.; Bateman, M.; McCaul, E.; Buechler, D.;

Improvements of Storm Surge Modelling in the Gulf of Venice with Satellite Data: The ESA Due Esurge-Venice Project

NASA Astrophysics Data System (ADS)

De Biasio, F.; Bajo, M.; Vignudelli, S.; Papa, A.; della Valle, A.; Umgiesser, G.; Donlon, C.; Zecchetto, S.

2016-08-01

Among the most detrimental natural phenomena, storm surges heavily endanger the environment, the economy and the everyday life of sea-side countries and coastal zones. Considering that 120.000.000 people live in the Mediterranean area, with additional 200.000.000 presences in Summer for tourism purposes, the correct prediction of storm surges is crucial to avoid fatalities and economic losses. Earth Observation (EO) can play an important role in operational storm surge forecasting, yet it is not widely diffused in the storm surge community. In 2011 the European Space Agency (ESA), through its Data User Element (DUE) programme, financed two projects aimed at encouraging the uptake of EO data in this sector: eSurge and eSurge-Venice (eSV). The former was intended to address the issues of a wider users' community, while the latter was focused on a restricted geographical area: the northern Adriatic Sea and the Gulf of Venice. Among the objectives of the two projects there were a number of storm surge hindcast experiments using satellite data, to demonstrate the improvements on the surge forecast brought by EO. We report here the results of the hindcast experiments of the eSV project. They were aimed to test the sensitivity of a storm surge model to a forcing wind field modified with scatterometer data in order to reduce the bias between simulated and observed winds. Hindcast experiments were also performed to test the response of the storm surge model to the assimilation, with a dual 4D-Var system, of satellite altimetry observations as model errors of the initial state of the sea surface level. Remarkable improvements on the storm surge forecast have been obtained for what concerns the modified model wind forcing. Encouraging results have been obtained also in the assimilation experiments.

Development of Operational Wave-Tide-Storm surges Coupling Prediction System

NASA Astrophysics Data System (ADS)

You, S. H.; Park, S. W.; Kim, J. S.; Kim, K. L.

2009-04-01

The Korean Peninsula is surrounded by the Yellow Sea, East China Sea, and East Sea. This complex oceanographic system includes large tides in the Yellow Sea and seasonally varying monsoon and typhoon events. For Korea's coastal regions, floods caused by wave and storm surges are among the most serious threats. To predict more accurate wave and storm surges, the development of coupling wave-tide-storm surges prediction system is essential. For the time being, wave and storm surges predictions are still made separately in KMA (Korea Meteorological Administration) and most operational institute. However, many researchers have emphasized the effects of tides and storm surges on wind waves and recommended further investigations into the effects of wave-tide-storm surges interactions and coupling module. In Korea, especially, tidal height and current give a great effect on the wave prediction in the Yellow sea where is very high tide and related research is not enough. At present, KMA has operated the wave (RWAM : Regional Wave Model) and storm surges/tide prediction system (STORM : Storm Surges/Tide Operational Model) for ocean forecasting. The RWAM is WAVEWATCH III which is a third generation wave model developed by Tolman (1989). The STORM is based on POM (Princeton Ocean Model, Blumberg and Mellor, 1987). The RWAM and STORM cover the northwestern Pacific Ocean from 115°E to 150°E and from 20°N to 52°N. The horizontal grid intervals are 1/12° in both latitudinal and longitudinal directions. These two operational models are coupled to simulate wave heights for typhoon case. The sea level and current simulated by storm surge model are used for the input of wave model with 3 hour interval. The coupling simulation between wave and storm surge model carried out for Typhoon Nabi (0514), Shanshan(0613) and Nari (0711) which were effected on Korea directly. We simulated significant wave height simulated by wave model and coupling model and compared difference between uncoupling and coupling cases for each typhoon. When the typhoon Nabi hit at southern coast of Kyushu, predicted significant wave height reached over 10 m. The difference of significant wave height between wave and wave-tide-storm surges model represents large variation at the southwestern coast of Korea with about 0.5 m. Other typhoon cases also show similar results with typhoon Nabi case. For typhoon Shanshan case the difference of significant wave height reached up to 0.3 m. When the typhoon Nari was affected in the southern coast of Korea, predicted significant wave height was about 5m. The typhoon Nari case also shows the difference of significant wave height similar with other typhoon cases. Using the observation from ocean buoy operated by KMA, we compared wave information simulated by wave and wave-storm surges coupling model. The significant wave height simulated by wave-tide-storm surges model shows the tidal modulation features in the western and southern coast of Korea. And the difference of significant wave height between two models reached up to 0.5 m. The coupling effect also can be identified in the wave direction, wave period and wave length. In addition, wave spectrum is also changeable due to coupling effect of wave-tide-storm surges model. The development, testing and application of a coupling module in which wave-tide-storm surges are incorporated within the frame of KMA Ocean prediction system, has been considered as a step forward in respect of ocean forecasting. In addition, advanced wave prediction model will be applicable to the effect of ocean in the weather forecasting system. The main purpose of this study is to show how the coupling module developed and to report on a series of experiments dealing with the sensitivities and real case prediction of coupling wave-tide-storm surges prediction system.

The Potential Observation Network Design with Mesoscale Ensemble Sensitivities in Complex Terrain

DTIC Science & Technology

2012-03-01

in synoptic storms , extratropical transition and developing hurricanes. Because they rely on lagged covariances from a finite-sized ensemble, they...diagnose predictors of forecast error in synoptic storms , extratropical transition and developing hurricanes. Because they rely on lagged covariances...sensitivities can be used successfully to diagnose predictors of forecast error in synoptic storms (Torn and Hakim 2008), extratropical transition (Torn and

Comprehensive Flood Plain Studies Using Spatial Data Management Techniques.

DTIC Science & Technology

1978-06-01

Hydrologic Engineer- ing Center computer programs that forecast urban storm water quality and dynamic in- stream water quality response to waste...determination. Water Quality The water quality analysis planned for the pilot study includes urban storm water quality forecasting and in-streamn...analysis is performed under the direction of Tony Thomas. Chief, Research Branch, by Jess Abbott for storm water quality analysis, R. G. Willey for

Extreme Wind, Rain, Storm Surge, and Flooding: Why Hurricane Impacts are Difficult to Forecast?

NASA Astrophysics Data System (ADS)

Chen, S. S.

2017-12-01

The 2017 hurricane season is estimated as one of the costliest in the U.S. history. The damage and devastation caused by Hurricane Harvey in Houston, Irma in Florida, and Maria in Puerto Rico are distinctly different in nature. The complexity of hurricane impacts from extreme wind, rain, storm surge, and flooding presents a major challenge in hurricane forecasting. A detailed comparison of the storm impacts from Harvey, Irma, and Maria will be presented using observations and state-of-the-art new generation coupled atmosphere-wave-ocean hurricane forecast model. The author will also provide an overview on what we can expect in terms of advancement in science and technology that can help improve hurricane impact forecast in the near future.

Analysis and Forecast of Two Storms Characterized by Extreme Deepening Rates

NASA Technical Reports Server (NTRS)

Reale, Oreste; Riishojgaard, Lars Peter

2003-01-01

Between 25 and 27 December 1999 two very intense cyclones, named Lothar and Martin, swept across northern and western France causing substantial life and property loss. In this work, the finite volume general circulation model and data assimilation system (fvDAS) developed at the Data Assimilation Office of the NASA Goddard Space and Flight Center is being used to investigate these storms. In the first part of this article the dynamics of the storms is analyzed, and some important mechanisms are unveiled. The second part describes a set of eleven data assimilation experiments to study the impact of different data types on the automated analyses. Cloud-track winds provided by EUMETSAT and surface winds from QuikSCAT are being used. These data are assimilated with a range of different parameter settings of the forecast error covariance model. The results show that generally the additional wind data set have positive impacts on the analyses: particularly, the analysis of Lothar can be slightly improved by using the Eumetsat winds, and the analysis of Martin can be strongly improved by using the full-resolution QuikSCAT winds with a more localized influence. The third part of this article is focused on the forecast of Lothar which is very well predicted in the 1-5 day range by the fvDAS system.

Coastal emergency managers' preferences for storm surge forecast communication.

PubMed

Morrow, Betty Hearn; Lazo, Jeffrey K

2014-01-01

Storm surge, the most deadly hazard associated with tropical and extratropical cyclones, is the basis for most evacuation decisions by authorities. One factor believed to be associated with evacuation noncompliance is a lack of understanding of storm surge. To address this problem, federal agencies responsible for cyclone forecasts are seeking more effective ways of communicating storm surge threat. To inform this process, they are engaging various partners in the forecast and warning process.This project focuses on emergency managers. Fifty-three emergency managers (EMs) from the Gulf and lower Atlantic coasts were surveyed to elicit their experience with, sources of, and preferences for storm surge information. The emergency managers-who are well seasoned in hurricane response and generally rate the surge risk in their coastal areas above average or extremely high-listed storm surge as their major concern with respect to hurricanes. They reported a general lack of public awareness about surge. Overall they support new ways to convey the potential danger to the public, including the issuance of separate storm surge watches and warnings, and the expression of surge heights using feet above ground level. These EMs would like more maps, graphics, and visual materials for use in communicating with the public. An important concern is the timing of surge forecasts-whether they receive them early enough to be useful in their evacuation decisions.

Synoptic Scale North American Weather Tracks and the Formation of North Atlantic Windstorms

NASA Astrophysics Data System (ADS)

Baum, A. J.; Godek, M. L.

2014-12-01

Each winter, dozens of fatalities occur when intense North Atlantic windstorms impact Western Europe. Forecasting the tracks of these storms in the short term is often problematic, but long term forecasts provide an even greater challenge. Improved prediction necessitates the ability to identify these low pressure areas at formation and understand commonalities that distinguish these storms from other systems crossing the Atlantic, such as where they develop. There is some evidence that indicates the majority of intense windstorms that reach Europe have origins far west, as low pressure systems that develop over the North American continent. This project aims to identify the specific cyclogenesis regions in North America that produce a significantly greater number of dangerous storms. NOAA Ocean Prediction Center surface pressure reanalysis maps are used to examine the tracks of storms. Strong windstorms are characterized by those with a central pressure of less than 965 hPa at any point in their life cycle. Tracks are recorded using a coding system based on source region, storm track and dissipation region. The codes are analyzed to determine which region contains the most statistical significance with respect to strong Atlantic windstorm generation. The resultant set of codes also serves as a climatology of North Atlantic extratropical cyclones. Results indicate that a number of windstorms favor cyclogenesis regions off the east coast of the United States. A large number of strong storms that encounter east coast cyclogenesis zones originate in the central mountain region, around Colorado. These storms follow a path that exits North America around New England and subsequently travel along the Canadian coast. Some of these are then primed to become "bombs" over the open Atlantic Ocean.

Integrating Fluvial and Oceanic Drivers in Operational Flooding Forecasts for San Francisco Bay

NASA Astrophysics Data System (ADS)

Herdman, Liv; Erikson, Li; Barnard, Patrick; Kim, Jungho; Cifelli, Rob; Johnson, Lynn

2016-04-01

The nine counties that make up the San Francisco Bay area are home to 7.5 million people and these communties are susceptible to flooding along the bay shoreline and inland creeks that drain to the bay. A forecast model that integrates fluvial and oceanic drivers is necessary for predicting flooding in this complex urban environment. The U.S. Geological Survey ( USGS) and National Weather Service (NWS) are developing a state-of-the-art flooding forecast model for the San Francisco Bay area that will predict watershed and ocean-based flooding up to 72 hours in advance of an approaching storm. The model framework for flood forecasts is based on the USGS-developed Coastal Storm Modeling System (CoSMoS) that was applied to San Francisco Bay under the Our Coast Our Future project. For this application, we utilize Delft3D-FM, a hydrodynamic model based on a flexible mesh grid, to calculate water levels that account for tidal forcing, seasonal water level anomalies, surge and in-Bay generated wind waves from the wind and pressure fields of a NWS forecast model, and tributary discharges from the Research Distributed Hydrologic Model (RDHM), developed by the NWS Office of Hydrologic Development. The flooding extent is determined by overlaying the resulting water levels onto a recently completed 2-m digital elevation model of the study area which best resolves the extensive levee and tidal marsh systems in the region. Here we present initial pilot results of hindcast winter storms in January 2010 and December 2012, where the flooding is driven by oceanic and fluvial factors respectively. We also demonstrate the feasibility of predicting flooding on an operational time scale that incorporates both atmospheric and hydrologic forcings.

OSSE Assessment of Ocean Observing System Enhancements to Improve Coupled Tropical Cyclone Intensity Prediction

NASA Astrophysics Data System (ADS)

Halliwell, G. R., Jr.; Mehari, M. F.; Dong, J.; Kourafalou, V.; Atlas, R. M.; Kang, H.; Le Henaff, M.

2016-02-01

A new ocean OSSE system validated in the tropical/subtropical Atlantic Ocean is used to evaluate ocean observing strategies during the 2014 hurricane season with the goal of improving coupled tropical cyclone forecasts. Enhancements to the existing operational ocean observing system are evaluated prior to two storms, Edouard and Gonzalo, where ocean measurements were obtained during field experiments supported by the 2013 Disaster Relief Appropriation Act. For Gonzalo, a reference OSSE is performed to evaluate the impact of two ocean gliders deployed north and south of Puerto Rico and two Alamo profiling floats deployed in the same general region during most of the hurricane season. For Edouard, a reference OSSE is performed to evaluate impacts of the pre-storm ocean profile survey conducted by NOAA WP-3D aircraft. For both storms, additional OSSEs are then conducted to evaluate more extensive seasonal and pre-storm ocean observing strategies. These include (1) deploying a larger number of synthetic ocean gliders during the hurricane season, (2) deploying pre-storm synthetic thermistor chains or synthetic profiling floats along one or more "picket fence" lines that cross projected storm tracks, and (3) designing pre-storm airborne profiling surveys to have larger impacts than the actual pre-storm survey conducted for Edouard. Impacts are evaluated based on error reduction in ocean parameters important to SST cooling and hurricane intensity such as ocean heat content and the structure of the ocean eddy field. In all cases, ocean profiles that sample both temperature and salinity down to 1000m provide greater overall error reduction than shallower temperature profiles obtained from AXBTs and thermistor chains. Large spatial coverage with multiple instruments spanning a few degrees of longitude and latitude is necessary to sufficiently reduce ocean initialization errors over a region broad enough to significantly impact predicted surface enthalpy flux into the storm. Error reduction in hurricane intensity forecasts resulting from the additional ocean observations is then assessed by initializing the ocean component of the HYCOM-HWRF coupled prediction system with analyses produced by the OSSE system.

Real-time landslide warning during heavy rainfall

USGS Publications Warehouse

Keefer, D.K.; Wilson, R.C.; Mark, R.K.; Brabb, E.E.; Brown, W. M.; Ellen, S.D.; Harp, E.L.; Wieczorek, G.F.; Alger, C.S.; Zatkin, R.S.

1987-01-01

A real-time system for issuing warnings of landslides during major storms is being developed for the San Francisco Bay region, California. The system is based on empirical and theoretical relations between rainfall and landslide initiation, geologic determination of areas susceptible to landslides, real-time monitoring of a regional network of telemetering rain gages, and National Weather Service precipitation forecasts. This system was used to issue warnings during the storms of 12 to 21 February 1986, which produced 800 millimeters of rainfall in the region. Although analysis after the storms suggests that modifications and additional developments are needed, the system successfully predicted the times of major landslide events. It could be used as a prototype for systems in other landslide-prone regions.

Analog ensemble and Bayesian regression techniques to improve the wind speed prediction during extreme storms in the NE U.S.

NASA Astrophysics Data System (ADS)

Yang, J.; Astitha, M.; Delle Monache, L.; Alessandrini, S.

2016-12-01

Accuracy of weather forecasts in Northeast U.S. has become very important in recent years, given the serious and devastating effects of extreme weather events. Despite the use of evolved forecasting tools and techniques strengthened by increased super-computing resources, the weather forecasting systems still have their limitations in predicting extreme events. In this study, we examine the combination of analog ensemble and Bayesian regression techniques to improve the prediction of storms that have impacted NE U.S., mostly defined by the occurrence of high wind speeds (i.e. blizzards, winter storms, hurricanes and thunderstorms). The predicted wind speed, wind direction and temperature by two state-of-the-science atmospheric models (WRF and RAMS/ICLAMS) are combined using the mentioned techniques, exploring various ways that those variables influence the minimization of the prediction error (systematic and random). This study is focused on retrospective simulations of 146 storms that affected the NE U.S. in the period 2005-2016. In order to evaluate the techniques, leave-one-out cross validation procedure was implemented regarding 145 storms as the training dataset. The analog ensemble method selects a set of past observations that corresponded to the best analogs of the numerical weather prediction and provides a set of ensemble members of the selected observation dataset. The set of ensemble members can then be used in a deterministic or probabilistic way. In the Bayesian regression framework, optimal variances are estimated for the training partition by minimizing the root mean square error and are applied to the out-of-sample storm. The preliminary results indicate a significant improvement in the statistical metrics of 10-m wind speed for 146 storms using both techniques (20-30% bias and error reduction in all observation-model pairs). In this presentation, we discuss the various combinations of atmospheric predictors and techniques and illustrate how the long record of predicted storms is valuable in the improvement of wind speed prediction.

Aircraft measurements and analysis of severe storms: 1976 field experiment

NASA Technical Reports Server (NTRS)

Sinclair, P. C.

1982-01-01

Severe storm aircraft measurements are documented, as well as the instrumentation and operational features of aircraft mobility capabilities. The measurements and data analyses indicate that the concept of a highly mobile research aircraft capability for obtaining detailed measurements of wind, temperature, moisture, spherics, etc., near and within severe storm systems, forecast 48 hours in advance in a 1000 nm operating radius, is feasible, and was successfully demonstrated. The measurements and analyses reveal several severe storm features and insights with respect to storm air flow circulations and inflow-outflow orientation. Precipitation downdraft air is recirculated back into the updraft core below the scud cloud in both back and front feeder type storms. In a back feeder type storm, the downdraft outflow air ahead of the storm is also recirculated back into the updraft region near cloud base.

Hurricane feedback research may improve intensity forecasts

NASA Astrophysics Data System (ADS)

Schultz, Colin

2012-06-01

Forecasts of a hurricane's intensity are generally much less accurate than forecasts of its most likely path. Large-scale atmospheric patterns dictate where a hurricane will go and how quickly it will get there. The storm's intensity, however, depends on small-scale shifts in atmospheric stratification, upwelling rates, and other transient dynamics that are difficult to predict. Properly understanding the risk posed by an impending storm depends on having a firm grasp of all three properties: translational speed, intensity, and path. Drawing on 40 years of hurricane records representing 3090 different storms, Mei et al. propose that a hurricane's translational speed and intensity may be closely linked.

The Lake Victoria Intense Storm Early Warning System (VIEWS)

NASA Astrophysics Data System (ADS)

Thiery, Wim; Gudmundsson, Lukas; Bedka, Kristopher; Semazzi, Fredrick; Lhermitte, Stef; Willems, Patrick; van Lipzig, Nicole; Seneviratne, Sonia I.

2017-04-01

Weather extremes have harmful impacts on communities around Lake Victoria in East Africa. Every year, intense nighttime thunderstorms cause numerous boating accidents on the lake, resulting in thousands of deaths among fishermen. Operational storm warning systems are therefore crucial. Here we complement ongoing early warning efforts based on NWP, by presenting a new satellite data-driven storm prediction system, the prototype Lake Victoria Intense storm Early Warning System (VIEWS). VIEWS derives predictability from the correlation between afternoon land storm activity and nighttime storm intensity on Lake Victoria, and relies on logistic regression techniques to forecast extreme thunderstorms from satellite observations. Evaluation of the statistical model reveals that predictive power is high and independent of the input dataset. We then optimise the configuration and show that also false alarms contain valuable information. Our results suggest that regression-based models that are motivated through process understanding have the potential to reduce the vulnerability of local fishing communities around Lake Victoria. The experimental prediction system is publicly available under the MIT licence at http://github.com/wthiery/VIEWS.

Investigating NWP initialization sensitivities in heavy precipitation events

NASA Astrophysics Data System (ADS)

Frediani, M. E. B.; Anagnostou, E. N.; Papadopoulos, A.

2010-09-01

This study aims to investigate the effect of different types of model initialization applied to extreme storms simulations. Storms with extreme precipitation can usually produce flash floods that cause several damages to the society. Lives and property are destroyed from the landslides when they could be speared if forecasted a few hours in advance. The forecasts depend on several factors; among them the initialization fields play an important role. These fields are the starting point for the simulation and therefore it controls the quality of the forecast. This study evaluates the sensitivities of WRF to the initialization from two perspectives, (1) resolution and (2) initial atmospheric fields. Two storms that lead to flash flood are simulated. The first one happened in Northeast Italy in 04/09/2009 (NI), and the second in Germany, in 02/06/2008 (GE). These storms present contrasting characteristics, NI was a maritime originated storm enhanced by local orography while GE was a typical summer convection. Three different sources of atmospheric fields defining the initial conditions are applied: (a) ECMWF operational analysis at resolution of 0.25 deg, (b) GFS operational analysis at 0.5deg and (c) LAPS analysis at ~15km, produced operationally at HCMR. The rainfall forecasted is compared against in situ ground radar and surface rain gauges observations through a set of quantitative precipitation forecast scores.

Central Pacific Hurricane Center - Honolulu, Hawai`i

Science.gov Websites

distance between lat/lon points Saffir-Simpson Scale Tropical Storm - winds 39-73 mph (34-63 kt) Category 1 Research and Development NOAA Hurricane Research Division Joint Hurricane Testbed Hurricane Forecast WFO Honolulu Weather Prediction Center Storm Prediction Center Ocean Prediction Center Local Forecast

Three-dimensional variational assimilation of MODIS aerosol optical depth: Implementation and application to a dust storm over East Asia

NASA Astrophysics Data System (ADS)

Liu, Zhiquan; Liu, Quanhua; Lin, Hui-Chuan; Schwartz, Craig S.; Lee, Yen-Huei; Wang, Tijian

2011-12-01

Assimilation of the Moderate Resolution Imaging Spectroradiometer (MODIS) total aerosol optical depth (AOD) retrieval products (at 550 nm wavelength) from both Terra and Aqua satellites have been developed within the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) three-dimensional variational (3DVAR) data assimilation system. This newly developed algorithm allows, in a one-step procedure, the analysis of 3-D mass concentration of 14 aerosol variables from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) module. The Community Radiative Transfer Model (CRTM) was extended to calculate AOD using GOCART aerosol variables as input. Both the AOD forward model and corresponding Jacobian model were developed within the CRTM and used in the 3DVAR minimization algorithm to compute the AOD cost function and its gradient with respect to 3-D aerosol mass concentration. The impact of MODIS AOD data assimilation was demonstrated by application to a dust storm from 17 to 24 March 2010 over East Asia. The aerosol analyses initialized Weather Research and Forecasting/Chemistry (WRF/Chem) model forecasts. Results indicate that assimilating MODIS AOD substantially improves aerosol analyses and subsequent forecasts when compared to MODIS AOD, independent AOD observations from the Aerosol Robotic Network (AERONET) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, and surface PM10 (particulate matter with diameters less than 10 μm) observations. The newly developed AOD data assimilation system can serve as a tool to improve simulations of dust storms and general air quality analyses and forecasts.

Revisiting the synoptic-scale predictability of severe European winter storms using ECMWF ensemble reforecasts

NASA Astrophysics Data System (ADS)

Pantillon, Florian; Knippertz, Peter; Corsmeier, Ulrich

2017-10-01

New insights into the synoptic-scale predictability of 25 severe European winter storms of the 1995-2015 period are obtained using the homogeneous ensemble reforecast dataset from the European Centre for Medium-Range Weather Forecasts. The predictability of the storms is assessed with different metrics including (a) the track and intensity to investigate the storms' dynamics and (b) the Storm Severity Index to estimate the impact of the associated wind gusts. The storms are well predicted by the whole ensemble up to 2-4 days ahead. At longer lead times, the number of members predicting the observed storms decreases and the ensemble average is not clearly defined for the track and intensity. The Extreme Forecast Index and Shift of Tails are therefore computed from the deviation of the ensemble from the model climate. Based on these indices, the model has some skill in forecasting the area covered by extreme wind gusts up to 10 days, which indicates a clear potential for early warnings. However, large variability is found between the individual storms. The poor predictability of outliers appears related to their physical characteristics such as explosive intensification or small size. Longer datasets with more cases would be needed to further substantiate these points.

Variational Continuous Assimilation of TMI and SSM/I Rain Rates: Impact on GEOS-3 Hurricane Analyses and Forecasts

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; Reale, Oreste

2003-01-01

We describe a variational continuous assimilation (VCA) algorithm for assimilating tropical rainfall data using moisture and temperature tendency corrections as the control variable to offset model deficiencies. For rainfall assimilation, model errors are of special concern since model-predicted precipitation is based on parameterized moist physics, which can have substantial systematic errors. This study examines whether a VCA scheme using the forecast model as a weak constraint offers an effective pathway to precipitation assimilation. The particular scheme we exarnine employs a '1+1' dimension precipitation observation operator based on a 6-h integration of a column model of moist physics from the Goddard Earth Observing System (GEOS) global data assimilation system DAS). In earlier studies, we tested a simplified version of this scheme and obtained improved monthly-mean analyses and better short-range forecast skills. This paper describes the full implementation ofthe 1+1D VCA scheme using background and observation error statistics, and examines how it may improve GEOS analyses and forecasts of prominent tropical weather systems such as hurricanes. Parallel assimilation experiments with and without rainfall data for Hurricanes Bonnie and Floyd show that assimilating 6-h TMI and SSM/I surfice rain rates leads to more realistic storm features in the analysis, which, in turn, provide better initial conditions for 5-day storm track prediction and precipitation forecast. These results provide evidence that addressing model deficiencies in moisture tendency may be crucial to making effective use of precipitation information in data assimilation.

Near Real Time Data for Operational Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Berger, T. E.

2014-12-01

Space weather operations presents unique challenges for data systems and providers. Space weather events evolve more quickly than terrestrial weather events. While terrestrial weather occurs on timescales of minutes to hours, space weather storms evolve on timescales of seconds to minutes. For example, the degradation of the High Frequency Radio communications between the ground and commercial airlines is nearly instantaneous when a solar flare occurs. Thus the customer is observing impacts at the same time that the operational forecast center is seeing the event unfold. The diversity and spatial scale of the space weather system is such that no single observation can capture the salient features. The vast space that encompasses space weather and the scarcity of observations further exacerbates the situation and make each observation even more valuable. The physics of interplanetary space, through which many major storms propagate, is very different from the physics of the ionosphere where most of the impacts are felt. And while some observations can be made from ground-based observatories, many of the most critical data comes from satellites, often in unique orbits far from Earth. In this presentation, I will describe some of the more important sources and types of data that feed into the operational alerts, watches, and warnings of space weather storms. Included will be a discussion of some of the new space weather forecast models and the data challenges that they bring forward.

Relations Between Rainfall and Postfire Debris-Flow and Flood Magnitudes for Emergency-Response Planning, San Gabriel Mountains, Southern California

USGS Publications Warehouse

Cannon, Susan H.; Boldt, Eric M.; Kean, Jason W.; Laber, Jayme; Staley, Dennis M.

2010-01-01

Following wildfires, emergency-response and public-safety agencies are faced often with making evacuation decisions and deploying resources both well in advance of each coming winter storm and during storms themselves. Information critical to this process is provided for recently burned areas in the San Gabriel Mountains of southern California. The National Weather Service (NWS) issues Quantitative Precipitation Forecasts (QPFs) for the San Gabriel Mountains twice a day, at approximately 4 a.m. and 4 p.m., along with unscheduled updates when conditions change. QPFs provide estimates of rainfall totals in 3-hour increments for the first 12-hour period and in 6-hour increments for the second 12-hour period. Estimates of one-hour rainfall intensities can be provided in the forecast narrative, along with probable peak intensities and timing, although with less confidence than rainfall totals. A compilation of information on the hydrologic response to winter storms from recently burned areas in southern California steeplands was used to develop a system for classifying the magnitude of the postfire hydrologic response. The four-class system is based on a combination of the reported volume of individual debris flows, the consequences of these events in an urban setting, and the spatial extent of the response to the triggering storm. Threshold rainfall conditions associated with debris flow and floods of different magnitude classes are defined by integrating local rainfall data with debris-flow and flood magnitude information. The within-storm rainfall accumulations (A) and durations (D) above which magnitude I events are expected are defined by A=0.3D0.6. The function A=0.5D0.6 defines the within-storm rainfall accumulations and durations above which a magnitude III event will occur in response to a regional-scale storm, and a magnitude II event will occur if the storm affects only a few drainage basins. The function A=1.0D0.5defines the rainfall conditions above which magnitude III events can be expected. Rainfall trigger-magnitude relations are linked with potential emergency-response actions in the form of an emergency-response decision chart. The chart leads a user through steps to determine potential event magnitudes, and identify possible evacuation and resource-deployment levels as a function of either individual storm forecasts or measured precipitation during storms. The ability to use this information in the planning and response decision-making process may result in significant financial savings and increased safety for both the public and emergency responders.

Physical and Dynamical Linkages Between Lightning Jumps and Storm Conceptual Models

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Carey, Lawrence D.; Schultz, Elise V.; Blakeslee, Richard J.; Goodman, Steven J.

2014-01-01

The presence and rates of total lightning are both correlated to and physically dependent upon storm updraft strength, mixed phase precipitation volume and the size of the charging zone. The updraft modulates the ingredients necessary for electrification within a thunderstorm, while the updraft also plays a critical role in the development of severe and hazardous weather. Therefore utilizing this relationship, the monitoring of lightning rates and jumps provides an additional piece of information on the evolution of a thunderstorm, more often than not, at higher temporal resolution than current operational radar systems. This correlation is the basis for the total lightning jump algorithm that has been developed in recent years. Currently, the lightning jump algorithm is being tested in two separate but important efforts. Schultz et al. (2014; this conference) is exploring the transition of the algorithm from its research based formulation to a fully objective algorithm that includes storm tracking, Geostationary Lightning Mapper (GLM) Proxy data and the lightning jump algorithm. Chronis et al. (2014) provides context for the transition to current operational forecasting using lightning mapping array based products. However, what remains is an end-to-end physical and dynamical basis for coupling total lightning flash rates to severe storm manifestation, so the forecaster has a reason beyond simple correlation to utilize the lightning jump algorithm within their severe storm conceptual models. Therefore, the physical basis for the lightning jump algorithm in relation to severe storm dynamics and microphysics is a key component that must be further explored. Many radar studies have examined flash rates and their relationship to updraft strength, updraft volume, precipitation-sized ice mass, etc.; however, their relationship specifically to lightning jumps is fragmented within the literature. Thus the goal of this study is to use multiple Doppler and polarimetric radar techniques to resolve the physical and dynamical storm characteristics specifically around the time of the lightning jump. This information will help forecasters anticipate lightning jump occurrence, or even be of use to determine future characteristics of a given storm (e.g., development of a mesocyclone, downdraft, or hail signature on radar), providing additional lead time/confidence in the severe storm warning paradigm.

Physical and Dynamical Linkages between Lightning Jumps and Storm Conceptual Models

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Carey, Lawrence D.; Schultz, Elise V.; Blakeslee, Richard J.; Goodman, Steven J.

2014-01-01

The presence and rates of total lightning are both correlated to and physically dependent upon storm updraft strength, mixed phase precipitation volume and the size of the charging zone. The updraft modulates the ingredients necessary for electrification within a thunderstorm, while the updraft also plays a critical role in the development of severe and hazardous weather. Therefore utilizing this relationship, the monitoring of lightning rates and jumps provides an additional piece of information on the evolution of a thunderstorm, more often than not, at higher temporal resolution than current operational radar systems. This correlation is the basis for the total lightning jump algorithm that has been developed in recent years. Currently, the lightning jump algorithm is being tested in two separate but important efforts. Schultz et al. (2014; this conference) is exploring the transition of the algorithm from its research based formulation to a fully objective algorithm that includes storm tracking, Geostationary Lightning Mapper (GLM) Proxy data and the lightning jump algorithm. Chronis et al. (2014; this conference) provides context for the transition to current operational forecasting using lightning mapping array based products. However, what remains is an end-to-end physical and dynamical basis for coupling total lightning flash rates to severe storm manifestation, so the forecaster has a reason beyond simple correlation to utilize the lightning jump algorithm within their severe storm conceptual models. Therefore, the physical basis for the lightning jump algorithm in relation to severe storm dynamics and microphysics is a key component that must be further explored. Many radar studies have examined flash rates and their relationship to updraft strength, updraft volume, precipitation-sized ice mass, etc.; however, their relationship specifically to lightning jumps is fragmented within the literature. Thus the goal of this study is to use multiple Doppler and polarimetric radar techniques to resolve the physical and dynamical storm characteristics specifically around the time of the lightning jump. This information will help forecasters anticipate lightning jump occurrence, or even be of use to determine future characteristics of a given storm (e.g., development of a mesocyclone, downdraft, or hail signature on radar), providing additional lead time/confidence in the severe storm warning paradigm.

L-band microwave remote sensing and land data assimilation improve the representation of pre-storm soil moisture conditions for hydrologic forecasting

USDA-ARS?s Scientific Manuscript database

Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i...

Impact of CAMEX-4 Data Sets for Hurricane Forecasts using a Global Model

NASA Technical Reports Server (NTRS)

Kamineni, Rupa; Krishnamurti, T. N.; Pattnaik, S.; Browell, Edward V.; Ismail, Syed; Ferrare, Richard A.

2005-01-01

This study explores the impact on hurricane data assimilation and forecasts from the use of dropsondes and remote-sensed moisture profiles from the airborne Lidar Atmospheric Sensing Experiment (LASE) system. We show that the use of these additional data sets, above those from the conventional world weather watch, has a positive impact on hurricane predictions. The forecast tracks and intensity from the experiments show a marked improvement compared to the control experiment where such data sets were excluded. A study of the moisture budget in these hurricanes showed enhanced evaporation and precipitation over the storm area. This resulted in these data sets making a large impact on the estimate of mass convergence and moisture fluxes, which were much smaller in the control runs. Overall this study points to the importance of high vertical resolution humidity data sets for improved model results. We note that the forecast impact from the moisture profiling data sets for some of the storms is even larger than the impact from the use of dropwindsonde based winds.

Balancing Flood Risk and Water Supply in California: Policy Search Combining Short-Term Forecast Ensembles and Groundwater Recharge

NASA Astrophysics Data System (ADS)

Herman, J. D.; Steinschneider, S.; Nayak, M. A.

2017-12-01

Short-term weather forecasts are not codified into the operating policies of federal, multi-purpose reservoirs, despite their potential to improve service provision. This is particularly true for facilities that provide flood protection and water supply, since the potential flood damages are often too severe to accept the risk of inaccurate forecasts. Instead, operators must maintain empty storage capacity to mitigate flood risk, even if the system is currently in drought, as occurred in California from 2012-2016. This study investigates the potential for forecast-informed operating rules to improve water supply efficiency while maintaining flood protection, combining state-of-the-art weather hindcasts with a novel tree-based policy optimization framework. We hypothesize that forecasts need only accurately predict the occurrence of a storm, rather than its intensity, to be effective in regions like California where wintertime, synoptic-scale storms dominate the flood regime. We also investigate the potential for downstream groundwater injection to improve the utility of forecasts. These hypotheses are tested in a case study of Folsom Reservoir on the American River. Because available weather hindcasts are relatively short (10-20 years), we propose a new statistical framework to develop synthetic forecasts to assess the risk associated with inaccurate forecasts. The efficiency of operating policies is tested across a range of scenarios that include varying forecast skill and additional groundwater pumping capacity. Results suggest that the combined use of groundwater storage and short-term weather forecasts can substantially improve the tradeoff between water supply and flood control objectives in large, multi-purpose reservoirs in California.

Depth-area-duration characteristics of storm rainfall in Texas using Multi-Sensor Precipitation Estimates

NASA Astrophysics Data System (ADS)

McEnery, J. A.; Jitkajornwanich, K.

2012-12-01

This presentation will describe the methodology and overall system development by which a benchmark dataset of precipitation information has been used to characterize the depth-area-duration relations in heavy rain storms occurring over regions of Texas. Over the past two years project investigators along with the National Weather Service (NWS) West Gulf River Forecast Center (WGRFC) have developed and operated a gateway data system to ingest, store, and disseminate NWS multi-sensor precipitation estimates (MPE). As a pilot project of the Integrated Water Resources Science and Services (IWRSS) initiative, this testbed uses a Standard Query Language (SQL) server to maintain a full archive of current and historic MPE values within the WGRFC service area. These time series values are made available for public access as web services in the standard WaterML format. Having this volume of information maintained in a comprehensive database now allows the use of relational analysis capabilities within SQL to leverage these multi-sensor precipitation values and produce a valuable derivative product. The area of focus for this study is North Texas and will utilize values that originated from the West Gulf River Forecast Center (WGRFC); one of three River Forecast Centers currently represented in the holdings of this data system. Over the past two decades, NEXRAD radar has dramatically improved the ability to record rainfall. The resulting hourly MPE values, distributed over an approximate 4 km by 4 km grid, are considered by the NWS to be the "best estimate" of rainfall. The data server provides an accepted standard interface for internet access to the largest time-series dataset of NEXRAD based MPE values ever assembled. An automated script has been written to search and extract storms over the 18 year period of record from the contents of this massive historical precipitation database. Not only can it extract site-specific storms, but also duration-specific storms and storms separated by user defined inter-event periods. A separate storm database has been created to store the selected output. By storing output within tables in a separate database, we can make use of powerful SQL capabilities to perform flexible pattern analysis. Previous efforts have made use of historic data from limited clusters of irregularly spaced physical gauges. Spatial extent of the observational network has been a limiting factor. The relatively dense distribution of MPE provides a virtual mesh of observations stretched over the landscape. This work combines a unique hydrologic data resource with programming and database analysis to characterize storm depth-area-duration relationships.

Understanding Variability in Beach Slope to Improve Forecasts of Storm-induced Water Levels

NASA Astrophysics Data System (ADS)

Doran, K. S.; Stockdon, H. F.; Long, J.

2014-12-01

The National Assessment of Hurricane-Induced Coastal Erosion Hazards combines measurements of beach morphology with storm hydrodynamics to produce forecasts of coastal change during storms for the Gulf of Mexico and Atlantic coastlines of the United States. Wave-induced water levels are estimated using modeled offshore wave height and period and measured beach slope (from dune toe to shoreline) through the empirical parameterization of Stockdon et al. (2006). Spatial and temporal variability in beach slope leads to corresponding variability in predicted wave setup and swash. Seasonal and storm-induced changes in beach slope can lead to differences on the order of a meter in wave runup elevation, making accurate specification of this parameter essential to skillful forecasts of coastal change. Spatial variation in beach slope is accounted for through alongshore averaging, but temporal variability in beach slope is not included in the final computation of the likelihood of coastal change. Additionally, input morphology may be years old and potentially very different than the conditions present during forecast storm. In order to improve our forecasts of hurricane-induced coastal erosion hazards, the temporal variability of beach slope must be included in the final uncertainty of modeled wave-induced water levels. Frequently collected field measurements of lidar-based beach morphology are examined for study sites in Duck, North Carolina, Treasure Island, Florida, Assateague Island, Virginia, and Dauphin Island, Alabama, with some records extending over a period of 15 years. Understanding the variability of slopes at these sites will help provide estimates of associated water level uncertainty which can then be applied to other areas where lidar observations are infrequent, and improve the overall skill of future forecasts of storm-induced coastal change. Stockdon, H. F., Holman, R. A., Howd, P. A., and Sallenger Jr, A. H. (2006). Empirical parameterization of setup,swash, and runup. Coastal engineering, 53(7), 573-588.

Mid-latitude storm track variability and its influence on atmospheric composition

NASA Astrophysics Data System (ADS)

Knowland, K. E.; Doherty, R. M.; Hodges, K.

2013-12-01

Using the storm tracking algorithm, TRACK (Hodges, 1994, 1995, 1999), we have studied the behaviour of storm tracks in the North Atlantic basin, using 850-hPa relative vorticity from the ERA-Interim Re-analysis (Dee et al., 2011). We have correlated surface ozone measurements at rural coastal sites in Europe to the storm track data to explore the role mid-latitude cyclones and their transport of pollutants play in determining surface air quality in Western Europe. To further investigate this relationship, we have used the Monitoring Atmospheric Composition Climate (MACC) Re-analysis dataset (Inness et al., 2013) in TRACK. The MACC Re-analysis is a 10-year dataset which couples a chemistry transport model (Mozart-3; Stein 2009, 2012) to an extended version of the European Centre for Medium-Range Weather Forecasts' (ECMWF) Integrated Forecast System (IFS). Storm tracks in the MACC Re-analysis compare well to the storm tracks using the ERA-Interim Re-analysis for the same 10-year period, as both are based on ECMWF IFSs. We also compare surface ozone values from MACC to surface ozone measurements previously studied. Using TRACK, we follow ozone (O3) and carbon monoxide (CO) through the life cycle of storms from North America to Western Europe. Along the storm tracks, we examine the distribution of CO and O3 within 6 degrees of the center of each storm and vertically at different pressure levels in the troposphere. We hope to better understand the mechanisms with which pollution is vented from the boundary layer to the free troposphere, as well as transport of pollutants to rural areas. Our hope is to give policy makers more detailed information on how climate variability associated with storm tracks between 1979-2013 may affect air quality in Northeast USA and Western Europe.

Use of radar rainfall estimates and forecasts to prevent flash flood in real time by using a road inundation warning system

NASA Astrophysics Data System (ADS)

Versini, Pierre-Antoine

2012-01-01

SummaryImportant damages occur in small headwater catchments when they are hit by severe storms with complex spatio-temporal structure, sometimes resulting in flash floods. As these catchments are mostly not covered by sensor networks, it is difficult to forecast these floods. This is particularly true for road submersions, representing major concerns for flood event managers. The use of Quantitative Precipitation Estimates and Forecasts (QPE/QPF) especially based on radar measurements could particularly be adequate to evaluate rainfall-induced risks. Although their characteristic time and space scales would make them suitable for flash flood modelling, the impact of their uncertainties remain uncertain and have to be evaluated. The Gard region (France) has been chosen as case study. This area is frequently affected by severe flash floods, and an application devoted to the road network has also been recently developed for the North part of this region. This warning system combines distributed hydro-meteorological modelling and susceptibility analysis to provide warnings of road inundations. The warning system has been tested on the specific storm of the 29-30 September 2007. During this event, around 200 mm dropped on the South part of the Gard and many roads were submerged. Radar-based QPE and QPF have been used to forecast the exact location of road submersions and the results have been compared to the effective road submersions actually occurred during the event as listed by the emergency services. Used on an area it has not been calibrated, the results confirm that the road submersion warning system represents a promising tool for anticipating and quantifying the consequences of storm events at ground. It rates the submersion risk with an acceptable level of accuracy and demonstrates also the quality of high spatial and temporal resolution radar rainfall data in real time, and the possibility to use them despite their uncertainties. However because of the quality of rainfall forecasts falls drastically with time, it is not often sufficient to provide valuable information for lead times exceeding 1 h.

The Design and Evaluation of the Lighting Imaging Sensor Data Applications Display (LISDAD)

NASA Technical Reports Server (NTRS)

Boldi, B.; Hodanish, S.; Sharp, D.; Williams, E.; Goodman, Steven; Raghavan, R.; Matlin, A.; Weber, M.

1998-01-01

The design and evaluation of the Lightning Imaging Sensor Data Applications Display (LISDAD). The ultimate goal of the LISDAD system is to quantify the utility of total lightning information in short-term, severe-weather forecasting operations. To this end, scientists from NASA, NWS, and MIT organized an effort to study the relationship of lightning and severe-weather on a storm-by-storm, and even cell-by-cell basis for as many storms as possible near Melbourne, Florida. Melbourne was chosen as it offers a unique combination of high probability of severe weather and proximity to major relevant sensors - specifically: NASA's total lightning mapping system at Kennedy Space Center (the LDAR system at KSC); a NWS/NEXRAD radar (at Melbourne); and a prototype Integrated Terminal Weather System (ITWS, at Orlando), which obtains cloud-to-ground lightning Information from the National Lightning Detection Network (NLDN), and also uses NSSL's Severe Storm Algorithm (NSSL/SSAP) to obtain information about various storm-cell parameters. To assist in realizing this project's goal, an interactive, real-time data processing system (the LISDAD system) has been developed that supports both operational short-term weather forecasting and post facto severe-storm research. Suggestions have been drawn from the operational users (NWS/Melbourne) in the design of the data display and its salient behavior. The initial concept for the users Graphical Situation Display (GSD) was simply to overlay radar data with lightning data, but as the association between rapid upward trends in the total lightning rate and severe weather became evident, the display was significantly redesigned. The focus changed to support the display of time series of storm-parameter data and the automatic recognition of cells that display rapid changes in the total-lightning flash rate. The latter is calculated by grouping discrete LDAR radiation sources into lightning flashes using a time-space association algorithm. Specifically, the GSD presents the user with the Composite Maximum Reflectivity obtained from the NWS/NEXRAD. Superimposed upon this background image are placed small black circles indicating the locations of storm cells identified by the NSSL/SSA. The circles become cyan if lightning is detected within the storm-cell; if the cell has lightning rates indicative of a severe-storm, the circle turns red. This paper will: (1) review the design of LISDAD system; (2) present some examples of its data display; and shown results of the lightning based severe-weather prediction algorithm.

Climate and Weather Analysis of Afghanistan Thunderstorms

DTIC Science & Technology

2011-09-01

dry, continental polar (cP) air. The subtropical jet (STJ) and Extratropical storm track tend to lie south of Kabul. Mean high SFC temperatures...March-April-May (MAM). Note that AFG lies to the east of a broad trough centered over southern Europe and to the west of broad ridge centered over... Extratropical Cyclone FAR False Alarm Rate FOB Forward Operating Base FRN Forecaster Reference Notebook GFS Global Forecast System GoA

Numerical Study of the Port of Miami (Importance of Dodge Island) in Storm Surge and Flooding Forecasting in North Biscayne Bay

NASA Astrophysics Data System (ADS)

Liu, H.; Zhang, K.; Li, Y.

2011-12-01

The importance of Port of Miami (Dodge Island) in storm surge and flooding forecasting in North Biscayne Bay was investigated by using the numerical model Coastal and Estuarine Storm Tide (CEST). Firstly, CEST was applied to Hurricane Andrew of 1992 in the Biscayne Bay basin and validated by in situ measurements, which indicated the model results had good agreement with measured data. Secondly, two sets of experiments using Hurricane Miami of 1926 were conducted to study the role of Dodge Island in storm surge and flooding forecasting in North Biscayne Bay: one set of experiments were run in today's Biscayne Bay basin and another set of experiments were run in Biscayne Bay basin of 1926 in which Dodge Island was not created yet. Results indicated that storm surge and flooding areas were reduced a little bit in Miami River areas when Dodge Island was not there. Meanwhile, storm surge and flooding areas in North Miami and Miami Beach regions were largely increased. Results further indicated that as long as the hurricane made landfall in south of Dodge Island, it can provide a good protection for Miami Beach area to reduce storm surge and flooding impacts.

Impact of Lidar Wind Sounding on Mesoscale Forecast

NASA Technical Reports Server (NTRS)

Miller, Timothy L.; Chou, Shih-Hung; Goodman, H. Michael (Technical Monitor)

2001-01-01

An Observing System Simulation Experiment (OSSE) was conducted to study the impact of airborne lidar wind sounding on mesoscale weather forecast. A wind retrieval scheme, which interpolates wind data from a grid data system, simulates the retrieval of wind profile from a satellite lidar system. A mesoscale forecast system based on the PSU/NCAR MM5 model is developed and incorporated the assimilation of the retrieved line-of-sight wind. To avoid the "identical twin" problem, the NCEP reanalysis data is used as our reference "nature" atmosphere. The simulated space-based lidar wind observations were retrieved by interpolating the NCEP values to the observation locations. A modified dataset obtained by smoothing the NCEP dataset was used as the initial state whose forecast was sought to be improved by assimilating the retrieved lidar observations. Forecasts using wind profiles with various lidar instrument parameters has been conducted. The results show that to significantly improve the mesoscale forecast the satellite should fly near the storm center with large scanning radius. Increasing lidar firing rate also improves the forecast. Cloud cover and lack of aerosol degrade the quality of the lidar wind data and, subsequently, the forecast.

Predicting global thunderstorm activity for sprite observations from the International Space Station

NASA Astrophysics Data System (ADS)

Yair, Y.; Mezuman, K.; Ziv, B.; Priente, M.; Glickman, M.; Takahashi, Y.; Inoue, T.

2012-04-01

The global rate of sprites occurring above thunderstorms, estimated from the ISUAL satellite data, is ~0.5 per minute (Chen et al., 2008). During the summer 2011, in the framework of the "Cosmic Shore" project, we conducted a concentrated attempt to image sprites from the ISS. The methodology for target selection was based on that developed for the space shuttle MEIDEX sprite campaign (Ziv et al., 2004). There are several types of convective systems generating thunderstorms which differ in their effectiveness for sprite production (Lyons et al., 2009), and so we had to evaluate the ability of the predicted storms to produce sprites. We used the Aviation Weather Center (http://aviationweather.gov) daily significant weather forecast maps (SIGWX) to select regions with high probability for convective storms and lightning such that they were within the camera filed-of-view as deduced from the ISS trajectory and distance to the limb. In order to enhance the chance for success, only storms with predicted "Frequent Cb" and cloud tops above 45 Kft (~14 km) were selected. Additionally, we targeted tropical storms and hurricanes over the oceans. The accuracy of the forecast method enabled obtaining the first-ever color images of sprites from space. We will report the observations showing various types of sprites in many different geographical locations, and correlated parent lightning properties derived from ELF and global and local lightning location networks. Chen, A. B., et al. (2008), Global distributions and occurrence rates of transient luminous events, J. Geophys. Res., 113,A08306, doi:10.1029/2008JA013101 Lyons, W. A., et al. (2009), The meteorological and electrical structure of TLE-producing convective storms. In: Betz et al. (eds.): Lighting: principles instruments and applications, Springer-Science + Business Media B.V.. Ziv, B., Y. Yair, K. Pressman and M. Fullekrug, (2004), Verification of the Aviation Center global forecasts of Mesoscale Convective Systems. Jour. App. Meteor., 43, 720-726.

Coupling Fluvial and Oceanic Drivers in Flooding Forecasts for San Francisco Bay

NASA Astrophysics Data System (ADS)

Herdman, L.; Kim, J.; Cifelli, R.; Barnard, P.; Erikson, L. H.; Johnson, L. E.; Chandrasekar, V.

2016-12-01

San Francisco Bay is a highly urbanized estuary and the surrounding communities are susceptible to flooding along the bay shoreline and inland rivers and creeks that drain to the Bay. A forecast model that integrates fluvial and oceanic drivers is necessary for predicting flooding in this complex urban environment. This study introduces the state-of-the-art coupling of the USGS Coastal Storm Modeling System (CoSMoS) with the NWS Research Distributed Hydrologic Model (RDHM) for San Francisco Bay. For this application, we utilize Delft3D-FM, a hydrodynamic model based on a flexible mesh grid, to calculate water levels that account for tidal forcing, seasonal water level anomalies, surge and in-Bay generated wind waves from the wind and pressure fields of a NWS forecast model. The tributary discharges from RDHM are dynamic, meteorologically driven allowing for operational use of CoSMoS which has previously relied on statistical estimates of river discharge. The flooding extent is determined by overlaying the resulting maximum water levels onto a recently updated 2-m digital elevation model of the study area which best resolves the extensive levee and tidal marsh systems in the region. The results we present here are focused on the interaction of the Bay and the Napa River watershed. This study demonstrates the interoperability of the CoSMoS and RDHM prediction models. We also use this pilot region to examine storm flooding impacts in a series of storm scenarios that simulate 5-100yr return period events in terms of either coastal or fluvial events. These scenarios demonstrate the wide range of possible flooding outcomes considering rainfall recurrence intervals, soil moisture conditions, storm surge, wind speed, and tides (spring and neap). With a simulated set of over 25 storm scenarios we show how the extent, level, and duration of flooding is dependent on these atmospheric and hydrologic parameters and we also determine a range of likely flood events.

European Wintertime Windstorms and its Links to Large-Scale Variability Modes

NASA Astrophysics Data System (ADS)

Befort, D. J.; Wild, S.; Walz, M. A.; Knight, J. R.; Lockwood, J. F.; Thornton, H. E.; Hermanson, L.; Bett, P.; Weisheimer, A.; Leckebusch, G. C.

2017-12-01

Winter storms associated with extreme wind speeds and heavy precipitation are the most costly natural hazard in several European countries. Improved understanding and seasonal forecast skill of winter storms will thus help society, policy-makers and (re-) insurance industry to be better prepared for such events. We firstly assess the ability to represent extra-tropical windstorms over the Northern Hemisphere of three seasonal forecast ensemble suites: ECMWF System3, ECMWF System4 and GloSea5. Our results show significant skill for inter-annual variability of windstorm frequency over parts of Europe in two of these forecast suites (ECMWF-S4 and GloSea5) indicating the potential use of current seasonal forecast systems. In a regression model we further derive windstorm variability using the forecasted NAO from the seasonal model suites thus estimating the suitability of the NAO as the only predictor. We find that the NAO as the main large-scale mode over Europe can explain some of the achieved skill and is therefore an important source of variability in the seasonal models. However, our results show that the regression model fails to reproduce the skill level of the directly forecast windstorm frequency over large areas of central Europe. This suggests that the seasonal models also capture other sources of variability/predictability of windstorms than the NAO. In order to investigate which other large-scale variability modes steer the interannual variability of windstorms we develop a statistical model using a Poisson GLM. We find that the Scandinavian Pattern (SCA) in fact explains a larger amount of variability for Central Europe during the 20th century than the NAO. This statistical model is able to skilfully reproduce the interannual variability of windstorm frequency especially for the British Isles and Central Europe with correlations up to 0.8.

L-band microwave remote sensing and land data assimilation improve the representation of pre-storm soil moisture conditions for hydrologic forecasting.

PubMed

Crow, W T; Chen, F; Reichle, R H; Liu, Q

2017-06-16

Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total stream flow divided by total rainfall accumulation in depth units) and pre-storm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L-band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting stream flow response to future rainfall events.

L-band microwave remote sensing and land data assimilation improve the representation of pre-storm soil moisture conditions for hydrologic forecasting

PubMed Central

Crow, W.T.; Chen, F.; Reichle, R.H.; Liu, Q.

2018-01-01

Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total stream flow divided by total rainfall accumulation in depth units) and pre-storm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L-band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting stream flow response to future rainfall events. PMID:29657342

On using scatterometer and altimeter data to improve storm surge forecasting in the Adriatic Sea

NASA Astrophysics Data System (ADS)

Bajo, Marco; Umgiesser, Georg; De Biasio, Francesco; Vignudelli, Stefano; Zecchetto, Stefano

2017-04-01

Satellite data are seldom used in storm surge forecasting. Among the most important issues related to the storm surge forecasting are the quality of the model wind forcing and the initial condition of the sea surface elevation. In this work, focused on storm surge forecasting in the Adriatic Sea, satellite scatterometer wind data are used to correct the wind speed and direction biases of the ECMWF global atmospheric model by tuning the spatial fields, as an alternative to data assimilation. The capability of such an unbiased wind is tested against that of a high resolution wind, produced by a regional non-hydrostatic model. On the other hand, altimeter Total Water Level Envelope (TWLE) data, which provide the sea level elevation, are used to improve the accuracy of the initial state of the model simulations. This is done by assimilating into a storm surge model the TWLE obtained by the altimeter observations along ground tracks, after subtraction of the tidal components. In order to test the methodology, eleven storm surge events recorded in Venice, from 2008 to 2012, have been simulated using different configurations of forcing wind and altimeter data assimilation. Results show that the relative error on the estimation of the maximum surge peak, averaged over the cases considered, decreases from 13% to 7% using both the unbiased wind and the altimeter data assimilation, while forcing the hydrodynamic model with the high resolution wind (no tuning), the altimeter data assimilation reduces the error from 9% to 6%.

Developing empirical lightning cessation forecast guidance for the Kennedy Space Center

NASA Astrophysics Data System (ADS)

Stano, Geoffrey T.

The Kennedy Space Center in east Central Florida is one of the few locations in the country that issues lightning advisories. These forecasts are vital to the daily operations of the Space Center and take on even greater significance during launch operations. The U.S. Air Force's 45th Weather Squadron (45WS), who provides forecasts for the Space Center, has a good record of forecasting the initiation of lightning near their locations of special concern. However, the remaining problem is knowing when to cancel a lightning advisory. Without specific scientific guidelines detailing cessation activity, the Weather Squadron must keep advisories in place longer than necessary to ensure the safety of personnel and equipment. This unnecessary advisory time costs the Space Center millions of dollars in lost manpower each year. This research presents storm and environmental characteristics associated with lightning cessation that then are utilized to create lightning cessation guidelines for isolated thunderstorms for use by the 45WS during the warm season months of May through September. The research uses data from the Lightning Detection and Ranging (LDAR) network at the Kennedy Space Center, which can observe intra-cloud and portions of cloud-to-ground lightning strikes. Supporting data from the Cloud-to-Ground Lightning Surveillance System (CGLSS), radar observations from the Melbourne WSR-88D, and Cape Canaveral morning radiosonde launches also are included. Characteristics of 116 thunderstorms comprising our dataset are presented. Most of these characteristics are based on LDAR-derived spark and flash data and have not been described previously. In particular, the first lightning activity is quantified as either cloud-to-ground (CG) or intra-cloud (IC). Only 10% of the storms in this research are found to initiate with a CG strike. Conversely, only 16% of the storms end with a CG strike. Another characteristic is the average horizontal extent of all the flashes comprising a storm. Our average is 12-14 km, while the greatest flash extends 26 km. Comparisons between the starting altitude of the median and last flashes of a storm are analyzed, with only 37% of the storms having a higher last flash initiating altitude. Additional observations are made of the total lightning flash rate, percentage of CG to IC lightning, trends of individual flash initiation altitudes versus the average initiation altitude, the average inter-flash time distribution, and time series of inter-flash times. Five schemes to forecast lightning cessation are developed and evaluated. 100 of the 116 storms were randomly selected as the dependent sample, while the remaining 16 storms were used for verification. The schemes included a correlation and regression tree analysis, multiple linear regression, trends of storm duration, trend of the altitude of the greatest reflectivity to the time of the final flash, and a percentile scheme. Surprisingly, the percentile method was found to be the most effective technique and the simplest. The inclusion of real time storm parameters is found to have little effect on the results, suggesting that different forecast predictors, such as microphysical data from polarimetric radar, will be necessary to produce improved skill. When the percentile method used a confidence level of 99.5%, it successfully maintained lightning advisories for all 16 independent storms on which the schemes were tested. Since the computed wait time was 25 min, compared to the 45WS' most conservative and accurate wait time of 30 min, the percentile method saves 5 min for each advisory. This 5 min of savings safely shortens the Weather Squadron's advisories and saves money. Additionally, these results are the first to evaluate the 30/30 rule that is used commonly. The success of the percentile method is surprising since it out performs more complex procedures involving correlation and regression tree analysis and regression schemes. These more sophisticated statistical analyses were expected to perform better since they include more predictors in the forecasts. However, with the predictors available to us, this was not the case. While not the expected result, the percentile method succeeds in creating a safe and expedited forecast.

Integration of the Total Lightning Jump Algorithm into Current Operational Warning Environment Conceptual Models

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Carey, Lawrence D.; Schultz, Elise V.; Stano, Geoffrey T.; Gatlin, Patrick N.

2013-01-01

The presence and rates of total lightning are both correlated to and physically dependent upon storm updraft strength, mixed phase precipitation volume and the size of the charging zone. The updraft modulates the ingredients necessary for electrification within a thunderstorm, while the updraft also plays a critical role in the development of severe and hazardous weather. Therefore utilizing this relationship, the monitoring of lightning rates and jumps provides an additional piece of information on the evolution of a thunderstorm, more often than not, at higher temporal resolution than current operational radar systems. This correlation is the basis for the total lightning jump algorithm that has been developed in recent years. In order to become a viable option for operational forecasters to incorporate into their severe storm monitoring process, the total lightning jump must be placed into the framework of several severe storm conceptual models (e.g., radar evolution, storm morphology) which forecasters have built through training and experience. Thus, one of the goals of this study is to examine and relate the lightning jump concept to often used radar parameters (e.g., dBZ vertical structure, VIL, MESH, MESO/shear) in the warning environment. Tying lightning trends and lightning jump occurrences to these radar based parameters will provide forecasters with an additional tool that they can use to build an accurate realtime depiction as to what is going on in a given environment. Furthermore, relating the lightning jump concept to these parameters could also increase confidence in a warning decision they have already made, help tip the scales on whether or not to warn on a given storm, or to draw the forecaster s attention to a particular storm that is rapidly developing. Furthermore the lightning information will add vital storm scale information in regions that are not well covered by radar, or when radar failures occur. The physical basis for the lightning jump algorithm in relation to severe storm dynamics and microphysics is a key component that must be further explored. Many radar studies have examined flash rates and their relation to updraft strength, updraft volume, precipitation -sized ice mass, etc.; however, very few have related the concept of the lightning jump and manifestation of severe weather to storm dynamics and microphysics using multi -Doppler and polarimetric radar techniques. Therefore, the second half of this study will combine the lightning jump algorithm and these radar techniques in order to place the lightning jump concept into a physical and dynamical framework. This analysis includes examining such parameters as mixed phase precipitation volume, charging zone, updraft strength and updraft volume. Such a study should provide increased understanding of and confidence in the strengths and limitations of the lightning jump algorithm in the storm warning process.

Data registration and integration requirements for severe storms research

NASA Technical Reports Server (NTRS)

Dalton, J. T.

1982-01-01

Severe storms research is characterized by temporal scales ranging from minutes (for thunderstorms and tornadoes) to hours (for hurricanes and extra-tropical cyclones). Spatial scales range from tens to hundreds of kilometers. Sources of observational data include a variety of ground based and satellite systems. Requirements for registration and intercomparison of data from these various sources are examined and the potential for operational forecasting application of techniques resulting from the research is discussed. The sensor characteristics and processing procedures relating to the overlay and integrated analysis of satellite and surface observations for severe storms research are reviewed.

The eSurge-Venice project: how satellite data can improve the storm surge forecasting in the northern Adriatic Sea

NASA Astrophysics Data System (ADS)

Zecchetto, Stefano; Vignudelli, Stefano; Donlon, Craig; De Biasio, Francesco; Della Valle, Antonio; Umgiesser, Georg; Bajo, Marco

The Data User Element (DUE) program of the European Space Agency (ESA) is funding two projects (eSurge and eSurge-Venice) aimed to demonstrate the improvement of the storm surge forecasting through the use of Earth Observation (EO) data. eSurge-Venice (http://www.esurge-venice.eu/), is specifically focused on the Gulf of Venice, northern Adriatic Sea. The project objectives are: a) Select a number of Storm Surge Events occurred in the Venice lagoon since 1999; b) Provide the available satellite EO data related to the Storm Surge Events, mainly satellite winds and altimeter data, as well as all the available in-situ data and model forecasts; c) Provide a demonstration Near Real Time service (eSurge-Venice live) of EO data products and services in support of operational and experimental forecasting and warning services; d) Run a number of re-analysis cases, both for historical and contemporary storm surge events, to demonstrate the usefulness of EO data. Present storm surge models use atmospheric model wind fields as forcing. These are know to underestimate the wind in small basins like the Adriatic Sea (~1000 km by 300 km), where the orography plays an important role in shaping the winds. Therefore there is the need to verify and tune the atmospheric model wind fields used in the storm surge modeling, an activity which can easily done using satellite scatterometer winds. The project is now in the middle of his life, and promising preliminary results have been achieved using satellite scatterometer wind data to forge the atmospheric model wind fields forcing the storm surge model. This contribution will present the methodology adopted to tune the model wind fields according to the bias with scatterometer winds and the improvements induced in the storm surge model hindcast.

Use of High-resolution WRF Simulations to Forecast Lightning Threat

NASA Technical Reports Server (NTRS)

McCaul, William E.; LaCasse, K.; Goodman, S. J.

2006-01-01

Recent observational studies have confirmed the existence of a robust statistical relationship between lightning flash rates and the amount of large precipitating ice hydrometeors in storms. This relationship is exploited, in conjunction with the capabilities of recent forecast models such as WRF, to forecast the threat of lightning from convective storms using the output fields from the model forecasts. The simulated vertical flux of graupel at -15C is used in this study as a proxy for charge separation processes and their associated lightning risk. Six-h simulations are conducted for a number of case studies for which three-dimensional lightning validation data from the North Alabama Lightning Mapping Array are available. Experiments indicate that initialization of the WRF model on a 2 km grid using Eta boundary conditions, Doppler radar radial velocity and reflectivity fields, and METAR and ACARS data yield the most realistic simulations. An array of subjective and objective statistical metrics are employed to document the utility of the WRF forecasts. The simulation results are also compared to other more traditional means of forecasting convective storms, such as those based on inspection of the convective available potential energy field.

High-Resolution WRF Forecasts of Lightning Threat

NASA Technical Reports Server (NTRS)

Goodman, S. J.; McCaul, E. W., Jr.; LaCasse, K.

2007-01-01

Tropical Rainfall Measuring Mission (TRMM)lightning and precipitation observations have confirmed the existence of a robust relationship between lightning flash rates and the amount of large precipitating ice hydrometeors in storms. This relationship is exploited, in conjunction with the capabilities of the Weather Research and Forecast (WRF) model, to forecast the threat of lightning from convective storms using the output fields from the model forecasts. The simulated vertical flux of graupel at -15C is used in this study as a proxy for charge separation processes and their associated lightning risk. Initial experiments using 6-h simulations are conducted for a number of case studies for which three-dimensional lightning validation data from the North Alabama Lightning Mapping Array are available. The WRF has been initialized on a 2 km grid using Eta boundary conditions, Doppler radar radial velocity and reflectivity fields, and METAR and ACARS data. An array of subjective and objective statistical metrics is employed to document the utility of the WRF forecasts. The simulation results are also compared to other more traditional means of forecasting convective storms, such as those based on inspection of the convective available potential energy field.

Ocean Model Impact Study for Coupled Hurricane Forecasting: An HFIP Initiative

NASA Astrophysics Data System (ADS)

Kim, H. S. S.; Halliwell, G. R., Jr.; Tallapragada, V.; Black, P. G.; Bond, N.; Chen, S.; Cione, J.; Cronin, M. F.; Ginis, I.; Liu, B.; Miller, L.; Jayne, S. R.; Sanabia, E.; Shay, L. K.; Uhlhorn, E.; Zhu, L.

2016-02-01

Established in 2009, the NOAA Hurricane Forecast Improvement Project (HFIP) is a ten-year project to promote accelerated improvements hurricane track and intensity forecasts (Gall et al. 2013). The Ocean Model Impact Tiger Team (OMITT) consisting of model developers and research scientists was formed as one of HFIP working groups in December 2014, to evaluate the impact of ocean coupling in tropical cyclone (TC) forecasts. The team investigated the ocean model impact in real cases for Category 3 Hurricane Edouard in 2014, using simulations and observations that were collected for different stages of the hurricane. Two Eastern North Pacific Hurricanes in 2015, Blanca and Dolores, are also of special interest. These two powerful Category 4 storms followed a similar track, however, they produced dramatically different ocean cooling, about 7.2oC for Hurricane Blanca but only about 2.7oC for Hurricane Dolores, and the corresponding intensity changes were negative 40 ms-1 and 20 ms-1, respectively. Two versions of operational HWRF and COAMPS-TC coupled prediction systems are employed in the study. These systems are configured to have 1D and 3D ocean dynamics coupled to the atmosphere. The ocean components are initialized separately with climatology, analysis and nowcast products to evaluate the impact of ocean initialization on hurricane forecasts. Real storm forecast experiments are being designed and performed with different levels of the ocean model complexity and various model configurations to study model sensitivity. In this talk, we report the OMITT activities conducted during the past year, present preliminary results of on-going investigation of air-sea interactions in the simulations, and discuss future plans toward improving coupled TC predictions. Gall, R., J. Franklin, F. Marks, E.N. Rappaport, and F. Toepfer, 2013: THE HURRICANE FORECAST IMPROVEMENT PROJECT. Bull. Amer. Meteor. Soc., 329-343.

Integration of the Total Lightning Jump Algorithm into Current Operational Warning Environment Conceptual Models

NASA Technical Reports Server (NTRS)

Shultz, Christopher J.; Carey, Lawrence D.; Schultz, Elise V.; Stano, Geoffrey T.; Blakeslee, Richard J.; Goodman, Steven J.

2014-01-01

The presence and rates of total lightning are both correlated to and physically dependent upon storm updraft strength, mixed phase precipitation volume and the size of the charging zone. The updraft modulates the ingredients necessary for electrification within a thunderstorm, while the updraft also plays a critical role in the development of severe and hazardous weather. Therefore utilizing this relationship, the monitoring of lightning rates and jumps provides an additional piece of information on the evolution of a thunderstorm, more often than not, at higher temporal resolution than current operational radar systems. This correlation is the basis for the total lightning jump algorithm that has been developed in recent years. Currently, the lightning jump algorithm is being tested in two separate but important efforts. Schultz et al. (2014; AMS 10th Satellite Symposium) is exploring the transition of the algorithm from its research based formulation to a fully objective algorithm that includes storm tracking, Geostationary Lightning Mapper (GLM) Proxy data and the lightning jump algorithm. Chronis et al. (2014; this conference) provides context for the transition to current operational forecasting using lightning mapping array based products. However, what remains is an end to end physical and dynamical basis for relating lightning rates to severe storm manifestation, so the forecaster has a reason beyond simple correlation to utilize the lightning jump algorithm within their severe storm conceptual models. Therefore, the physical basis for the lightning jump algorithm in relation to severe storm dynamics and microphysics is a key component that must be further explored. Many radar studies have examined flash rates and their relation to updraft strength, updraft volume, precipitation-sized ice mass, etc.; however, relation specifically to lightning jumps is fragmented within the literature. Thus the goal of this study is to use multiple Doppler techniques to resolve the physical and dynamical storm characteristics specifically around the time of the lightning jump. This information will help forecasters anticipate lightning jump occurrence, or even be of use to determine future characteristics of a given storm (e.g., development of a mesocyclone, downdraft, or hail signature on radar), providing additional lead time/confidence in the severe storm warning paradigm.

Early warnings of hazardous thunderstorms over Lake Victoria

NASA Astrophysics Data System (ADS)

Thiery, Wim; Gudmundsson, Lukas; Bedka, Kristopher; Semazzi, Fredrick H. M.; Lhermitte, Stef; Willems, Patrick; van Lipzig, Nicole P. M.; Seneviratne, Sonia I.

2017-07-01

Weather extremes have harmful impacts on communities around Lake Victoria in East Africa. Every year, intense nighttime thunderstorms cause numerous boating accidents on the lake, resulting in thousands of deaths among fishermen. Operational storm warning systems are therefore crucial. Here we complement ongoing early warning efforts based on numerical weather prediction, by presenting a new satellite data-driven storm prediction system, the prototype Lake Victoria Intense storm Early Warning System (VIEWS). VIEWS derives predictability from the correlation between afternoon land storm activity and nighttime storm intensity on Lake Victoria, and relies on logistic regression techniques to forecast extreme thunderstorms from satellite observations. Evaluation of the statistical model reveals that predictive power is high and independent of the type of input dataset. We then optimise the configuration and show that false alarms also contain valuable information. Our results suggest that regression-based models that are motivated through process understanding have the potential to reduce the vulnerability of local fishing communities around Lake Victoria. The experimental prediction system is publicly available under the MIT licence at http://github.com/wthiery/VIEWS.

An evaluation of the precipitation distribution associated with landfalling tropical systems

NASA Astrophysics Data System (ADS)

Atallah, Eyad H.

Several recent landfalling tropical cyclones (e.g. Dennis, Floyd, and Irene 1999) have highlighted a need for a refinement in the forecasting paradigms and techniques in the area of quantitative precipitation forecasting (QPF). Accordingly, several landfalling tropical storms were composited based on the precipitation distribution relative to the cyclone track (i.e. left of, right of, or along track), and cases from each composite were examined using a potential vorticity (PV) and quasi-geostrophic (QG) framework. Results indicate that a left of track precipitation distribution (e.g. Floyd 1999) is characteristic of tropical systems undergoing extratropical transition (ET). In these cases, a significant positively tilted mid-latitude trough approaches the cyclone from the northwest, shifting precipitation to the north-northwest of the cyclone. PV redistribution through diabatic heating then leads to enhanced ridging over and downstream of the tropical cyclone resulting in an increase in the cyclonic advection of vorticity by the thermal wind. Precipitation distribution is heaviest to the right of the track of the storm when downstream intensification of the ridge is important (e.g. David, 1979). Enhancement of the downstream ridge ahead of a weak mid-latitude trough accentuates the PV gradient between the tropical system and the downstream ridge. This, in combination with a slight acceleration in the movement of the tropical system, produces a region of enhanced positive PV advection (implied ascent) between the tropical system and the downstream ridge. Precipitation is heaviest along/very near the track of a storm when shear values are low and/or oriented along the track of the tropical cyclone (e.g. Fran 1996). Without large scale forcing for vertical motion associated with a midlatitude trough, most of the ascent remains concentrated near the storm core in the region of greatest diabatic heating and maximum wind speeds. In all cases, the diabatic enhancement of the downstream ridge is instrumental in the redistribution of precipitation about the tropical system. Unfortunately, this process is not well simulated in operational forecast models, leading to systematic errors in QPF.

Satellite altimetry and the intensification of Hurricane Katrina

NASA Astrophysics Data System (ADS)

Scharroo, Remko; Smith, Walter H. F.; Lillibridge, John L.

Remotely sensed infrared images of Hurricane Katrina taken on 26, 27, and 28 August 2005 (Figure 1, left panels) show the aerial extent of the cloud cover and the central “eye” increasing as the storm that swamped areas of the U.S. Gulf Coast intensified. Computer animations of such image sequences show forecasters the tracks of storms and are a familiar staple of weather news. Less well known is the role that satellite altimetry plays both in forecasting conditions that can intensify a tropical storm and in observing the storm conditions at the sea surface.Satellite altimeter data indicate that Katrina intensified over areas of anomalously high dynamic topography rather than areas of unusually warm surface waters. Altimeter data from Katrina also for the first time observed the building of a storm surge.

COMESEP: bridging the gap between the SEP, CME, and terrestrial effects scientific communities

NASA Astrophysics Data System (ADS)

Crosby, Norma; Veronig, Astrid; Rodriguez, Luciano; Vrsnak, Bojan; Vennerstrøm, Susanne; Malandraki, Olga; Dalla, Silvia; Srivastava, Nandita

2016-04-01

In the past there has been a tendency for the geomagnetic storm and solar energetic particle (SEP) communities to work in parallel rather than to apply a cross-disciplinary work approach specifically in regard to space weather forecasting. To provide more awareness on the existing links between these communities, as well as further bridge this gap, the three-year EU FP7 COMESEP (COronal Mass Ejections and Solar Energetic Particles: forecasting the space weather impact) project emphasized cross-collaboration between the SEP, coronal mass ejection, and terrestrial effects scientific communities. COMESEP went from basic solar-terrestrial physics research to space weather operations by developing, validating and implementing multi-purpose tools into an operational 24/7 alert service. Launched in November 2013, the COMESEP alert system provides space weather stakeholders geomagnetic storm alerts ("Event based" and "Next 24 hours") and SEP (proton) storm alerts (E > 10 MeV and E > 60 MeV) without human intervention based on the COMESEP definition of risk. COMESEP alerts and forecasts are freely available on the COMESEP alert website (http://www.comesep.eu/alert), as well as disseminated by e-mail to registered users. Acknowledgement: This work has received funding from the European Commission FP7 Project COMESEP (263252).

Storm Prediction Center Fire Weather Forecasts

Science.gov Websites

Archive NOAA Weather Radio Research Non-op. Products Forecast Tools Svr. Tstm. Events SPC Publications SPC Composite Maps Fire Weather Graphical Composite Maps Forecast and observational maps for various fire

A numerical investigation of the President's Day storm of February 18-19, 1979

NASA Technical Reports Server (NTRS)

Nappi, A. J.; Warner, T. T.

1983-01-01

The reported investigation is based on the use of a three-dimensional, primitive equation model. The President's Day storm, formed in the Gulf of Mexico as a massive anticyclone, affected the northern states with record-breaking cold temperatures. Attention is given to the physical processes relevant to storm formation, the forecast model, a description of experiments and model forecasts, and model results. An attempt is made to determine the important dynamic processes at work during the evolution of the storm. The jet streak interactions which occurred in the cyclogenetic environment, the effects of cold air damming, and the formation of a strong mesoscale coastal front are found to be of particular interest.

UAS Applications for Hurricane Science, Hurrican and Severe Storm Sentinel (HS3)

NASA Technical Reports Server (NTRS)

Braun, Scott

2014-01-01

Earth Science Industry Update: UAS Applications for Hurricane Science Unmanned systems can significantly transform hurricane observations and monitoring, improving our knowledge about and ability to forecast storm formation, track, and intensity change. NASA's use of the Global Hawk has demonstrated the scientific value of this platform and provided a proof-of-concept for operational applications. However, science flight operations face several challenges and constraints. In this session, learn about how NASA adapted the Global Hawk to do science; How NASA conducts its hurricane missions, and some of the challenges and constraints they face; Science results from NASA's recent hurricane field campaigns using the Global Hawk. How assimilation of dropsonde and radar data into weather prediction models may improve forecast accuracy; Other Earth science problems that could be addressed with Global Hawks.

GOES-S Mission Science Briefing

NASA Image and Video Library

2018-02-27

In the Kennedy Space Center's Press Site auditorium, Jim Roberts, a scientist with the Earth System Research Laboratory's Office of Atmospheric Research for NOAA, left, and Kristin Calhoun, a research scientist with NOAA's National Severe Storms Laboratory, speak to members of the media at a mission briefing on National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. The spacecraft is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

Analysis of Summer Thunderstorms in Central Alabama Using the NASA Land Information System

NASA Technical Reports Server (NTRS)

James, Robert; Case, Jonathan; Molthan, Andrew; Jedloved, Gary

2010-01-01

Forecasters have difficulty predicting "random" afternoon thunderstorms during the summer months. Differences in soil characteristics could be a contributing factor for storms. The NASA Land Information System (LIS) may assist forecasters in predicting summer convection by identifying boundaries in land characteristics. This project identified case dates during the summer of 2009 by analyzing synoptic weather maps, radar, and satellite data to look for weak atmospheric forcing and disorganized convective development. Boundaries in land characteristics that may have lead to convective initiation in central Alabama were then identified using LIS.

An Integrated 0-1 Hour First-Flash Lightning Nowcasting, Lightning Amount and Lightning Jump Warning Capability

NASA Technical Reports Server (NTRS)

Mecikalski, John; Jewett, Chris; Carey, Larry; Zavodsky, Brad; Stano, Geoffrey; Chronis, Themis

2015-01-01

Using satellite-based methods that provide accurate 0-1 hour convective initiation (CI) nowcasts, and rely on proven success coupling satellite and radar fields in the Corridor Integrated Weather System (CIWS; operated and developed at MIT-Lincoln Laboratory), to subsequently monitor for first-flash lightning initiation (LI) and later period lightning trends as storms evolve. Enhance IR-based methods within the GOES-R CI Algorithm (that must meet specific thresholds for a given cumulus cloud before the cloud is considered to have an increased likelihood of producing lightning next 90 min) that forecast LI. Integrate GOES-R CI and LI fields with radar thresholds (e.g., first greater than or equal to 40 dBZ echo at the -10 C altitude) and NWP model data within the WDSS-II system for LI-events from new convective storms. Track ongoing lightning using Lightning Mapping Array (LMA) and pseudo-Geostationary Lightning Mapper (GLM) data to assess per-storm lightning trends (e.g., as tied to lightning jumps) and outline threat regions. Evaluate the ability to produce LI nowcasts through a "lightning threat" product, and obtain feedback from National Weather Service forecasters on its value as a decision support tool.

The North Alabama Lightning Mapping Array: Recent Severe Storm Observations and Future Prospects

NASA Technical Reports Server (NTRS)

Goodman, S. J.; Blakeslee, R.; Christian, H.; Koshak, W.; Bailey, J.; Hall, J.; McCaul, E.; Buechler, D.; Darden, C.; Burks, J.

2004-01-01

The North Alabama Lightning Mapping Array became operational in November 2001 as a principal component of a severe weather test bed to infuse new science and technology into the short-term forecasting of severe and hazardous weather, principally within nearby National Weather Service forecast offices. Since the installation of the LMA, it has measured the total lightning activity of a large number of severe weather events, including three supercell tornado outbreaks, two supercell hailstorm events, and numerous microburst-producing storms and ordinary non-severe thunderstorms. The key components of evolving storm morphology examined are the time rate-of-change (temporal trending) of storm convective and precipitation characteristics that can be diagnosed in real-time using NEXRAD WSR-88D Doppler radar (echo growth and decay, precipitation structures and velocity features, outflow boundaries), LMA (total lightning flash rate and its trend) and National Lightning Detection Network (cloud-to- ground lightning, its polarity and trends). For example, in a transitional season supercell tornado outbreak, peak total flash rates for typical supercells in Tennessee reached 70-100/min, and increases in the total flash rate occurred during storm intensification as much as 20-25 min prior to at least some of the tornadoes. The most intense total flash rate measured during this outbreak (over 800 flashes/min) occurred in a storm in Alabama. In the case of a severe summertime pulse thunderstorm in North Alabama, the peak total flash rate reached 300/min, with a strong increase in total lightning evident some 9 min before damaging winds were observed at the surface. In this paper we provide a sampling of LMA observations and products during severe weather events to illustrate the capability of the system, and discuss the prospects for improving the short-term forecasting of convective weather using total lightning data.

Statistical uncertainty of extreme wind storms over Europe derived from a probabilistic clustering technique

NASA Astrophysics Data System (ADS)

Walz, Michael; Leckebusch, Gregor C.

2016-04-01

Extratropical wind storms pose one of the most dangerous and loss intensive natural hazards for Europe. However, due to only 50 years of high quality observational data, it is difficult to assess the statistical uncertainty of these sparse events just based on observations. Over the last decade seasonal ensemble forecasts have become indispensable in quantifying the uncertainty of weather prediction on seasonal timescales. In this study seasonal forecasts are used in a climatological context: By making use of the up to 51 ensemble members, a broad and physically consistent statistical base can be created. This base can then be used to assess the statistical uncertainty of extreme wind storm occurrence more accurately. In order to determine the statistical uncertainty of storms with different paths of progression, a probabilistic clustering approach using regression mixture models is used to objectively assign storm tracks (either based on core pressure or on extreme wind speeds) to different clusters. The advantage of this technique is that the entire lifetime of a storm is considered for the clustering algorithm. Quadratic curves are found to describe the storm tracks most accurately. Three main clusters (diagonal, horizontal or vertical progression of the storm track) can be identified, each of which have their own particulate features. Basic storm features like average velocity and duration are calculated and compared for each cluster. The main benefit of this clustering technique, however, is to evaluate if the clusters show different degrees of uncertainty, e.g. more (less) spread for tracks approaching Europe horizontally (diagonally). This statistical uncertainty is compared for different seasonal forecast products.

Extremes of Extra-tropical Storms and Drivers of Variability on Different Time Scales

NASA Astrophysics Data System (ADS)

Leckebusch, G. C.

2015-12-01

Extreme extra-tropical cyclones are highly complex dynamical systems with relevance not only for the meteorological and climatological conditions themselves, but also for impacts on different sectors of society and economy. In this presentation latest research results to severe cyclones and related wind fields from synoptic to multi-decadal and anthropogenic scales will be presented, including recent work to risk assessment of potential damages out of this natural hazard. Nevertheless, the focus is laid on the seasonal timescale and recent results to predictability and predictive skills out of different forecast suites will be discussed. In this context, three seasonal forecast suites, namely ECMWF System 3, ECMWF System 4 and Met Office HadGEM-GA3, are analysed regarding their ability to represent wintertime extra-tropical cyclone and wind storm events for the period 1992 until 2011. Two objective algorithms have been applied to 6 hourly MSLP data and 12 hourly wind speeds in 925hPa to detect cyclone and wind storm events, respectively. Results show that all model suites are able to simulate the climatological mean distribution of cyclones and wind storms. For wind storms, all model suites show positive skill in simulating the inter-annual variability over the sub-tropical Pacific. Results for the Atlantic region are more model dependent, with all models showing negative correlations over the western Atlantic. Over the eastern Atlantic/Western Europe only HadGEM-GA3 and ECMWF-S4 reveal significant positive correlations. However, it is found that results over this region are not robust in time for ECMWF-S4, as correlations drop if using 1982 until 2011 instead of 1992 until 2011. Factors of potential predictability will be discussed.

A short-term ionospheric forecasting empirical regional model (IFERM) to predict the critical frequency of the F2 layer during moderate, disturbed, and very disturbed geomagnetic conditions over the European area

NASA Astrophysics Data System (ADS)

Pietrella, M.

2012-02-01

A short-term ionospheric forecasting empirical regional model (IFERM) has been developed to predict the state of the critical frequency of the F2 layer (foF2) under different geomagnetic conditions. IFERM is based on 13 short term ionospheric forecasting empirical local models (IFELM) developed to predict foF2 at 13 ionospheric observatories scattered around the European area. The forecasting procedures were developed by taking into account, hourly measurements of foF2, hourly quiet-time reference values of foF2 (foF2QT), and the hourly time-weighted accumulation series derived from the geomagnetic planetary index ap, (ap(τ)), for each observatory. Under the assumption that the ionospheric disturbance index ln(foF2/foF2QT) is correlated to the integrated geomagnetic disturbance index ap(τ), a set of statistically significant regression coefficients were established for each observatory, over 12 months, over 24 h, and under 3 different ranges of geomagnetic activity. This data was then used as input to compute short-term ionospheric forecasting of foF2 at the 13 local stations under consideration. The empirical storm-time ionospheric correction model (STORM) was used to predict foF2 in two different ways: scaling both the hourly median prediction provided by IRI (STORM_foF2MED,IRI model), and the foF2QT values (STORM_foF2QT model) from each local station. The comparison between the performance of STORM_foF2MED,IRI, STORM_foF2QT, IFELM, and the foF2QT values, was made on the basis of root mean square deviation (r.m.s.) for a large number of periods characterized by moderate, disturbed, and very disturbed geomagnetic activity. The results showed that the 13 IFELM perform much better than STORM_foF2,sub>MED,IRI and STORM_foF2QT especially in the eastern part of the European area during the summer months (May, June, July, and August) and equinoctial months (March, April, September, and October) under disturbed and very disturbed geomagnetic conditions, respectively. The performance of IFELM is also very good in the western and central part of the Europe during the summer months under disturbed geomagnetic conditions. STORM_foF2MED,IRI performs particularly well in central Europe during the equinoctial months under moderate geomagnetic conditions and during the summer months under very disturbed geomagnetic conditions. The forecasting maps generated by IFERM on the basis of the results provided by the 13 IFELM, show very large areas located at middle-high and high latitudes where the foF2 predictions quite faithfully match the foF2 measurements, and consequently IFERM can be used for generating short-term forecasting maps of foF2 (up to 3 h ahead) over the European area.

Building regional early flood warning systems by AI techniques

NASA Astrophysics Data System (ADS)

Chang, F. J.; Chang, L. C.; Amin, M. Z. B. M.

2017-12-01

Building early flood warning system is essential for the protection of the residents against flood hazards and make actions to mitigate the losses. This study implements AI technology for forecasting multi-step-ahead regional flood inundation maps during storm events. The methodology includes three major schemes: (1) configuring the self-organizing map (SOM) to categorize a large number of regional inundation maps into a meaningful topology; (2) building dynamic neural networks to forecast multi-step-ahead average inundated depths (AID); and (3) adjusting the weights of the selected neuron in the constructed SOM based on the forecasted AID to obtain real-time regional inundation maps. The proposed models are trained, and tested based on a large number of inundation data sets collected in regions with the most frequent and serious flooding in the river basin. The results appear that the SOM topological relationships between individual neurons and their neighbouring neurons are visible and clearly distinguishable, and the hybrid model can continuously provide multistep-ahead visible regional inundation maps with high resolution during storm events, which have relatively small RMSE values and high R2 as compared with numerical simulation data sets. The computing time is only few seconds, and thereby leads to real-time regional flood inundation forecasting and make early flood inundation warning system. We demonstrate that the proposed hybrid ANN-based model has a robust and reliable predictive ability and can be used for early warning to mitigate flood disasters.

ALASKA MARINE VHF VOICE

Science.gov Websites

Tsunamis 406 EPIRB's National Weather Service Marine Forecasts ALASKA MARINE VHF VOICE Marine Forecast greater danger near shore or any shallow waters? NATIONAL WEATHER SERVICE PRODUCTS VIA ALASKA MARINE VHF VOICE NOAA broadcasts offshore forecasts, nearshore forecasts and storm warnings on marine VHF channels

Model Improvement by Assimilating Observations of Storm-Induced Coastal Change

NASA Astrophysics Data System (ADS)

Long, J. W.; Plant, N. G.; Sopkin, K.

2010-12-01

Discrete, large scale, meteorological events such as hurricanes can cause wide-spread destruction of coastal islands, habitats, and infrastructure. The effects can vary significantly along the coast depending on the configuration of the coastline, variable dune elevations, changes in geomorphology (sandy beach vs. marshland), and alongshore variations in storm hydrodynamic forcing. There are two primary methods of determining the changing state of a coastal system. Process-based numerical models provide highly resolved (in space and time) representations of the dominant dynamics in a physical system but must employ certain parameterizations due to computational limitations. The predictive capability may also suffer from the lack of reliable initial or boundary conditions. On the other hand, observations of coastal topography before and after the storm allow the direct quantification of cumulative storm impacts. Unfortunately these measurements suffer from instrument noise and a lack of necessary temporal resolution. This research focuses on the combination of these two pieces of information to make more reliable forecasts of storm-induced coastal change. Of primary importance is the development of a data assimilation strategy that is efficient, applicable for use with highly nonlinear models, and able to quantify the remaining forecast uncertainty based on the reliability of each individual piece of information used in the assimilation process. We concentrate on an event time-scale and estimate/update unobserved model information (boundary conditions, free parameters, etc.) by assimilating direct observations of coastal change with those simulated by the model. The data assimilation can help estimate spatially varying quantities (e.g. friction coefficients) that are often modeled as homogeneous and identify processes inadequately characterized in the model.

Predicting the next storm surge flood

USGS Publications Warehouse

Stamey, B.; Wang, Hongfang; Koterba, M.

2007-01-01

The Virginia Institute of Marine Science (VIMS), National Weather Services (NWS) Sterling and Wakefield, Weather Forecast Offices (WFO), and the Chesapeake Bay Observing System (CBOS) jointly developed a prototype system of a regional capability to address national problem. The system was developed to integrate high-resolution atmospheric and hydrodynamic and storm surge models, evaluate the ability of the prototype to predict land inundation in the Washington, D.C., and provide flooding results to Emergency Managers (EM) using portive. The system is a potential tool for NWS WFOs to provide support to the EMs, first in the Chesapeake Bay region and then in other coastal regions by applying similar approaches in other coastal and Great Lakes regions. The Chesapeake Inundation Prediction System (CIPS) also is building on the initial prototype to predict the combined effects of storm surge and tidal and river flow inundation in the Chesapeake Bay and its tributaries.

Designsafe-Ci a Cyberinfrastructure for Natural Hazard Simulation and Data

NASA Astrophysics Data System (ADS)

Dawson, C.; Rathje, E.; Stanzione, D.; Padgett, J.; Pinelli, J. P.

2017-12-01

DesignSafe is the web-based research platform of the Natural Hazards Engineering Research Infrastructure (NHERI) network that provides the computational tools needed to manage and analyze critical data for natural hazards research, with wind and storm surge related hazards being a primary focus. One of the simulation tools under DesignSafe is the Advanced Circulation (ADCIRC) model, a coastal ocean model used in storm surge analysis. ADCIRC is an unstructured, finite element model with high resolution capabilities for studying storm surge impacts, and has long been used in storm surge hind-casting and forecasting. In this talk, we will demonstrate the use of ADCIRC within the DesignSafe platform and its use for forecasting Hurricane Harvey. We will also demonstrate how to analyze, visualize and archive critical storm surge related data within DesignSafe.

An analysis of simulated and observed storm characteristics

NASA Astrophysics Data System (ADS)

Benestad, R. E.

2010-09-01

A calculus-based cyclone identification (CCI) method has been applied to the most recent re-analysis (ERAINT) from the European Centre for Medium-range Weather Forecasts and results from regional climate model (RCM) simulations. The storm frequency for events with central pressure below a threshold value of 960-990hPa were examined, and the gradient wind from the simulated storm systems were compared with corresponding estimates from the re-analysis. The analysis also yielded estimates for the spatial extent of the storm systems, which was also included in the regional climate model cyclone evaluation. A comparison is presented between a number of RCMs and the ERAINT re-analysis in terms of their description of the gradient winds, number of cyclones, and spatial extent. Furthermore, a comparison between geostrophic wind estimated though triangules of interpolated or station measurements of SLP is presented. Wind still represents one of the more challenging variables to model realistically.

Ionospheric research for space weather service support

NASA Astrophysics Data System (ADS)

Stanislawska, Iwona; Gulyaeva, Tamara; Dziak-Jankowska, Beata

2016-07-01

Knowledge of the behavior of the ionosphere is very important for space weather services. A wide variety of ground based and satellite existing and future systems (communications, radar, surveillance, intelligence gathering, satellite operation, etc) is affected by the ionosphere. There are the needs for reliable and efficient support for such systems against natural hazard and minimalization of the risk failure. The joint research Project on the 'Ionospheric Weather' of IZMIRAN and SRC PAS is aimed to provide on-line the ionospheric parameters characterizing the space weather in the ionosphere. It is devoted to science, techniques and to more application oriented areas of ionospheric investigation in order to support space weather services. The studies based on data mining philosophy increasing the knowledge of ionospheric physical properties, modelling capabilities and gain applications of various procedures in ionospheric monitoring and forecasting were concerned. In the framework of the joint Project the novel techniques for data analysis, the original system of the ionospheric disturbance indices and their implementation for the ionosphere and the ionospheric radio wave propagation are developed since 1997. Data of ionosonde measurements and results of their forecasting for the ionospheric observatories network, the regional maps and global ionospheric maps of total electron content from the navigational satellite system (GNSS) observations, the global maps of the F2 layer peak parameters (foF2, hmF2) and W-index of the ionospheric variability are provided at the web pages of SRC PAS and IZMIRAN. The data processing systems include analysis and forecast of geomagnetic indices ap and kp and new eta index applied for the ionosphere forecasting. For the first time in the world the new products of the W-index maps analysis are provided in Catalogues of the ionospheric storms and sub-storms and their association with the global geomagnetic Dst storms is investigated. The products of the Project web sites at http://www.cbk.waw.pl/rwc and http://www.izmiran.ru/services/iweather are widely used in scientific investigations and numerous applications by the telecommunication and navigation operators and users whose number at the web sites is growing substantially from month to month.

3 CFR 8523 - Proclamation 8523 of May 20, 2010. National Hurricane Preparedness Week, 2010

Code of Federal Regulations, 2011 CFR

2011-01-01

... coastal and inland communities face the danger of these powerful storms. From high winds and storm surges... Preparedness Week, I urge individuals, families, communities, and businesses to take time to plan for the storm season before it begins. While hurricane forecasting has improved, storms may still develop with little...

Incorporating the Wind Erosion Prediction System (WEPS) Into a Regional Air Quality Modeling System for the Pacific Northwest

USDA-ARS?s Scientific Manuscript database

In the Pacific Northwest, wind storms intermittently cause massive dust events that reduce visibility along roadways and jeopardize health as a result of extremely high concentrations of PM10 (particulate matter less than or equal to 10µm in diameter). An early warning dust forecast system is needed...

National Severe Storms Forecast Center

NASA Technical Reports Server (NTRS)

1977-01-01

The principal mission of the National Severe Storms Forecast Center (NSSFC) is to maintain a continuous watch of weather developments that are capable of producing severe local storms, including tornadoes, and to prepare and issue messages designated as either Weather Outlooks or Tornado or Severe Thunderstorm Watches for dissemination to the public and aviation services. In addition to its assigned responsibility at the national level, the NSSFC is involved in a number of programs at the regional and local levels. Subsequent subsections and paragraphs describe the NSSFC, its users, inputs, outputs, interfaces, capabilities, workload, problem areas, and future plans in more detail.

Forecasting in an integrated surface water-ground water system: The Big Cypress Basin, South Florida

NASA Astrophysics Data System (ADS)

Butts, M. B.; Feng, K.; Klinting, A.; Stewart, K.; Nath, A.; Manning, P.; Hazlett, T.; Jacobsen, T.

2009-04-01

The South Florida Water Management District (SFWMD) manages and protects the state's water resources on behalf of 7.5 million South Floridians and is the lead agency in restoring America's Everglades - the largest environmental restoration project in US history. Many of the projects to restore and protect the Everglades ecosystem are part of the Comprehensive Everglades Restoration Plan (CERP). The region has a unique hydrological regime, with close connection between surface water and groundwater, and a complex managed drainage network with many structures. Added to the physical complexity are the conflicting needs of the ecosystem for protection and restoration, versus the substantial urban development with the accompanying water supply, water quality and flood control issues. In this paper a novel forecasting and real-time modelling system is presented for the Big Cypress Basin. The Big Cypress Basin includes 272 km of primary canals and 46 water control structures throughout the area that provide limited levels of flood protection, as well as water supply and environmental quality management. This system is linked to the South Florida Water Management District's extensive real-time (SCADA) data monitoring and collection system. Novel aspects of this system include the use of a fully distributed and integrated modeling approach and a new filter-based updating approach for accurately forecasting river levels. Because of the interaction between surface- and groundwater a fully integrated forecast modeling approach is required. Indeed, results for the Tropical Storm Fay in 2008, the groundwater levels show an extremely rapid response to heavy rainfall. Analysis of this storm also shows that updating levels in the river system can have a direct impact on groundwater levels.

Use of High-Resolution WRF Simulations to Forecast Lightning Threat

NASA Technical Reports Server (NTRS)

McCaul, E. W., Jr.; LaCasse, K.; Goodman, S. J.; Cecil, D. J.

2008-01-01

Recent observational studies have confirmed the existence of a robust statistical relationship between lightning flash rates and the amount of large precipitating ice hydrometeors aloft in storms. This relationship is exploited, in conjunction with the capabilities of cloud-resolving forecast models such as WRF, to forecast explicitly the threat of lightning from convective storms using selected output fields from the model forecasts. The simulated vertical flux of graupel at -15C and the shape of the simulated reflectivity profile are tested in this study as proxies for charge separation processes and their associated lightning risk. Our lightning forecast method differs from others in that it is entirely based on high-resolution simulation output, without reliance on any climatological data. short [6-8 h) simulations are conducted for a number of case studies for which three-dmmensional lightning validation data from the North Alabama Lightning Mapping Array are available. Experiments indicate that initialization of the WRF model on a 2 km grid using Eta boundary conditions, Doppler radar radial velocity fields, and METAR and ACARS data y&eld satisfactory simulations. __nalyses of the lightning threat fields suggests that both the graupel flux and reflectivity profile approaches, when properly calibrated, can yield reasonable lightning threat forecasts, although an ensemble approach is probably desirable in order to reduce the tendency for misplacement of modeled storms to hurt the accuracy of the forecasts. Our lightning threat forecasts are also compared to other more traditional means of forecasting thunderstorms, such as those based on inspection of the convective available potential energy field.

Automated Statistical Forecast Method to 36-48H ahead of Storm Wind and Dangerous Precipitation at the Mediterranean Region

NASA Astrophysics Data System (ADS)

Perekhodtseva, E. V.

2009-09-01

Development of successful method of forecast of storm winds, including squalls and tornadoes and heavy rainfalls, that often result in human and material losses, could allow one to take proper measures against destruction of buildings and to protect people. Well-in-advance successful forecast (from 12 hours to 48 hour) makes possible to reduce the losses. Prediction of the phenomena involved is a very difficult problem for synoptic till recently. The existing graphic and calculation methods still depend on subjective decision of an operator. Nowadays in Russia there is no hydrodynamic model for forecast of the maximal precipitation and wind velocity V> 25m/c, hence the main tools of objective forecast are statistical methods using the dependence of the phenomena involved on a number of atmospheric parameters (predictors). Statistical decisive rule of the alternative and probability forecast of these events was obtained in accordance with the concept of "perfect prognosis" using the data of objective analysis. For this purpose the different teaching samples of present and absent of this storm wind and rainfalls were automatically arranged that include the values of forty physically substantiated potential predictors. Then the empirical statistical method was used that involved diagonalization of the mean correlation matrix R of the predictors and extraction of diagonal blocks of strongly correlated predictors. Thus for these phenomena the most informative predictors were selected without loosing information. The statistical decisive rules for diagnosis and prognosis of the phenomena involved U(X) were calculated for choosing informative vector-predictor. We used the criterion of distance of Mahalanobis and criterion of minimum of entropy by Vapnik-Chervonenkis for the selection predictors. Successful development of hydrodynamic models for short-term forecast and improvement of 36-48h forecasts of pressure, temperature and others parameters allowed us to use the prognostic fields of those models for calculations of the discriminant functions in the nodes of the grid 150x150km and the values of probabilities P of dangerous wind and thus to get fully automated forecasts. In order to change to the alternative forecast the author proposes the empirical threshold values specified for this phenomenon and advance period 36 hours. In the accordance to the Pirsey-Obukhov criterion (T), the success of these automated statistical methods of forecast of squalls and tornadoes to 36 -48 hours ahead and heavy rainfalls in the warm season for the territory of Italy, Spain and Balkan countries is T = 1-a-b=0,54: 0,78 after author experiments. A lot of examples of very successful forecasts of summer storm wind and heavy rainfalls over the Italy and Spain territory are submitted at this report. The same decisive rules were applied to the forecast of these phenomena during cold period in this year too. This winter heavy snowfalls in Spain and in Italy and storm wind at this territory were observed very often. And our forecasts are successful.

Regional early flood warning system: design and implementation

NASA Astrophysics Data System (ADS)

Chang, L. C.; Yang, S. N.; Kuo, C. L.; Wang, Y. F.

2017-12-01

This study proposes a prototype of the regional early flood inundation warning system in Tainan City, Taiwan. The AI technology is used to forecast multi-step-ahead regional flood inundation maps during storm events. The computing time is only few seconds that leads to real-time regional flood inundation forecasting. A database is built to organize data and information for building real-time forecasting models, maintaining the relations of forecasted points, and displaying forecasted results, while real-time data acquisition is another key task where the model requires immediately accessing rain gauge information to provide forecast services. All programs related database are constructed in Microsoft SQL Server by using Visual C# to extracting real-time hydrological data, managing data, storing the forecasted data and providing the information to the visual map-based display. The regional early flood inundation warning system use the up-to-date Web technologies driven by the database and real-time data acquisition to display the on-line forecasting flood inundation depths in the study area. The friendly interface includes on-line sequentially showing inundation area by Google Map, maximum inundation depth and its location, and providing KMZ file download of the results which can be watched on Google Earth. The developed system can provide all the relevant information and on-line forecast results that helps city authorities to make decisions during typhoon events and make actions to mitigate the losses.

Forecasting of Storm Surge Floods Using ADCIRC and Optimized DEMs

NASA Technical Reports Server (NTRS)

Valenti, Elizabeth; Fitzpatrick, Patrick

2005-01-01

Increasing the accuracy of storm surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite element based codes. It affords a capability for simulating tidal circulation and storm surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate.

Use of Remote Sensing Data to Enhance NWS Storm Damage Toolkit

NASA Technical Reports Server (NTRS)

Jedlove, Gary J.; Molthan, Andrew L.; White, Kris; Burks, Jason; Stellman, Keith; Smith, Mathew

2012-01-01

In the wake of a natural disaster such as a tornado, the National Weather Service (NWS) is required to provide a very detailed and timely storm damage assessment to local, state and federal homeland security officials. The Post ]Storm Data Acquisition (PSDA) procedure involves the acquisition and assembly of highly perishable data necessary for accurate post ]event analysis and potential integration into a geographic information system (GIS) available to its end users and associated decision makers. Information gained from the process also enables the NWS to increase its knowledge of extreme events, learn how to better use existing equipment, improve NWS warning programs, and provide accurate storm intensity and damage information to the news media and academia. To help collect and manage all of this information, forecasters in NWS Southern Region are currently developing a Storm Damage Assessment Toolkit (SDAT), which incorporates GIS ]capable phones and laptops into the PSDA process by tagging damage photography, location, and storm damage details with GPS coordinates for aggregation within the GIS database. However, this tool alone does not fully integrate radar and ground based storm damage reports nor does it help to identify undetected storm damage regions. In many cases, information on storm damage location (beginning and ending points, swath width, etc.) from ground surveys is incomplete or difficult to obtain. Geographic factors (terrain and limited roads in rural areas), manpower limitations, and other logistical constraints often prevent the gathering of a comprehensive picture of tornado or hail damage, and may allow damage regions to go undetected. Molthan et al. (2011) have shown that high resolution satellite data can provide additional valuable information on storm damage tracks to augment this database. This paper presents initial development to integrate satellitederived damage track information into the SDAT for near real ]time use by forecasters and decision makers.

Use of Remote Sensing Data to Enhance NWS Storm Damage Toolkit

NASA Astrophysics Data System (ADS)

Jedlovec, G.; Molthan, A.; White, K.; Burks, J.; Stellman, K.; Smith, M. R.

2012-12-01

In the wake of a natural disaster such as a tornado, the National Weather Service (NWS) is required to provide a very detailed and timely storm damage assessment to local, state and federal homeland security officials. The Post-Storm Data Acquisition (PSDA) procedure involves the acquisition and assembly of highly perishable data necessary for accurate post-event analysis and potential integration into a geographic information system (GIS) available to its end users and associated decision makers. Information gained from the process also enables the NWS to increase its knowledge of extreme events, learn how to better use existing equipment, improve NWS warning programs, and provide accurate storm intensity and damage information to the news media and academia. To help collect and manage all of this information, forecasters in NWS Southern Region are currently developing a Storm Damage Assessment Toolkit (SDAT), which incorporates GIS-capable phones and laptops into the PSDA process by tagging damage photography, location, and storm damage details with GPS coordinates for aggregation within the GIS database. However, this tool alone does not fully integrate radar and ground based storm damage reports nor does it help to identify undetected storm damage regions. In many cases, information on storm damage location (beginning and ending points, swath width, etc.) from ground surveys is incomplete or difficult to obtain. Geographic factors (terrain and limited roads in rural areas), manpower limitations, and other logistical constraints often prevent the gathering of a comprehensive picture of tornado or hail damage, and may allow damage regions to go undetected. Molthan et al. (2011) have shown that high resolution satellite data can provide additional valuable information on storm damage tracks to augment this database. This paper presents initial development to integrate satellite-derived damage track information into the SDAT for near real-time use by forecasters and decision makers.

An operational integrated short-term warning solution for solar radiation storms: introducing the Forecasting Solar Particle Events and Flares (FORSPEF) system

NASA Astrophysics Data System (ADS)

Anastasiadis, Anastasios; Sandberg, Ingmar; Papaioannou, Athanasios; Georgoulis, Manolis; Tziotziou, Kostas; Jiggens, Piers; Hilgers, Alain

2015-04-01

We present a novel integrated prediction system, of both solar flares and solar energetic particle (SEP) events, which is in place to provide short-term warnings for hazardous solar radiation storms. FORSPEF system provides forecasting of solar eruptive events, such as solar flares with a projection to coronal mass ejections (CMEs) (occurrence and velocity) and the likelihood of occurrence of a SEP event. It also provides nowcasting of SEP events based on actual solar flare and CME near real-time alerts, as well as SEP characteristics (peak flux, fluence, rise time, duration) per parent solar event. The prediction of solar flares relies on a morphological method which is based on the sophisticated derivation of the effective connected magnetic field strength (Beff) of potentially flaring active-region (AR) magnetic configurations and it utilizes analysis of a large number of AR magnetograms. For the prediction of SEP events a new reductive statistical method has been implemented based on a newly constructed database of solar flares, CMEs and SEP events that covers a large time span from 1984-2013. The method is based on flare location (longitude), flare size (maximum soft X-ray intensity), and the occurrence (or not) of a CME. Warnings are issued for all > C1.0 soft X-ray flares. The warning time in the forecasting scheme extends to 24 hours with a refresh rate of 3 hours while the respective warning time for the nowcasting scheme depends on the availability of the near real-time data and falls between 15-20 minutes. We discuss the modules of the FORSPEF system, their interconnection and the operational set up. The dual approach in the development of FORPSEF (i.e. forecasting and nowcasting scheme) permits the refinement of predictions upon the availability of new data that characterize changes on the Sun and the interplanetary space, while the combined usage of solar flare and SEP forecasting methods upgrades FORSPEF to an integrated forecasting solution. This work has been funded through the "FORSPEF: FORecasting Solar Particle Events and Flares", ESA Contract No. 4000109641/13/NL/AK

Valley Fever: Earth Observations for Risk Reduction

NASA Astrophysics Data System (ADS)

Sprigg, W. A.

2012-12-01

Advances in satellite Earth observation systems, numerical weather prediction, and dust storm modeling yield new tools for public health warnings, advisories and epidemiology of illnesses associated with airborne desert dust. Valley Fever, endemic from California through the US/Mexico border region into Central and South America, is triggered by inhalation of soil-dwelling fungal spores. The path from fungal growth to airborne threat depends on environmental conditions observable from satellite. And space-based sensors provide initial conditions for dust storm forecasts and baselines for the epidemiology of Valley Fever and other dust-borne aggravation of respiratory and cardiovascular disease. A new Pan-American Center for the World Meteorological Organization Sand and Dust Storm Warning Advisory and Assessment System creates an opportunity to advance Earth science applications in public health.

Enhanced outage prediction modeling for strong extratropical storms and hurricanes in the Northeastern United States

NASA Astrophysics Data System (ADS)

Cerrai, D.; Anagnostou, E. N.; Wanik, D. W.; Bhuiyan, M. A. E.; Zhang, X.; Yang, J.; Astitha, M.; Frediani, M. E.; Schwartz, C. S.; Pardakhti, M.

2016-12-01

The overwhelming majority of human activities need reliable electric power. Severe weather events can cause power outages, resulting in substantial economic losses and a temporary worsening of living conditions. Accurate prediction of these events and the communication of forecasted impacts to the affected utilities is necessary for efficient emergency preparedness and mitigation. The University of Connecticut Outage Prediction Model (OPM) uses regression tree models, high-resolution weather reanalysis and real-time weather forecasts (WRF and NCAR ensemble), airport station data, vegetation and electric grid characteristics and historical outage data to forecast the number and spatial distribution of outages in the power distribution grid located within dense vegetation. Recent OPM improvements consist of improved storm classification and addition of new predictive weather-related variables and are demonstrated using a leave-one-storm-out cross-validation based on 130 severe extratropical storms and two hurricanes (Sandy and Irene) in the Northeast US. We show that it is possible to predict the number of trouble spots causing outages in the electric grid with a median absolute percentage error as low as 27% for some storm types, and at most around 40%, in a scale that varies between four orders of magnitude, from few outages to tens of thousands. This outage information can be communicated to the electric utility to manage allocation of crews and equipment and minimize the recovery time for an upcoming storm hazard.

Functional and performance requirements of the next NOAA-Kasas City computer system

NASA Technical Reports Server (NTRS)

Mosher, F. R.

1985-01-01

The development of the Advanced Weather Interactive Processing System for the 1990's (AWIPS-90) will result in more timely and accurate forecasts with improved cost effectiveness. As part of the AWIPS-90 initiative, the National Meteorological Center (NMC), the National Severe Storms Forecast Center (NSSFC), and the National Hurricane Center (NHC) are to receive upgrades of interactive processing systems. This National Center Upgrade program will support the specialized inter-center communications, data acquisition, and processing needs of these centers. The missions, current capabilities and general functional requirements for the upgrade to the NSSFC are addressed. System capabilities are discussed along with the requirements for the upgraded system.

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.

THE PERFECT STORM

Science.gov Websites

Office Marine, Tropical, and Tsunami Services Branch Items of Interest Marine Forecasts Text, Graphic , Tropical, and Tsunami Services Branch, Items of Interest, Forecasts, Observations, Portals, Dissemination

Transforming community access to space science models

NASA Astrophysics Data System (ADS)

MacNeice, Peter; Hesse, Michael; Kuznetsova, Maria; Maddox, Marlo; Rastaetter, Lutz; Berrios, David; Pulkkinen, Antti

2012-04-01

Researching and forecasting the ever changing space environment (often referred to as space weather) and its influence on humans and their activities are model-intensive disciplines. This is true because the physical processes involved are complex, but, in contrast to terrestrial weather, the supporting observations are typically sparse. Models play a vital role in establishing a physically meaningful context for interpreting limited observations, testing theory, and producing both nowcasts and forecasts. For example, with accurate forecasting of hazardous space weather conditions, spacecraft operators can place sensitive systems in safe modes, and power utilities can protect critical network components from damage caused by large currents induced in transmission lines by geomagnetic storms.

Transforming Community Access to Space Science Models

NASA Technical Reports Server (NTRS)

MacNeice, Peter; Heese, Michael; Kunetsova, Maria; Maddox, Marlo; Rastaetter, Lutz; Berrios, David; Pulkkinen, Antti

2012-01-01

Researching and forecasting the ever changing space environment (often referred to as space weather) and its influence on humans and their activities are model-intensive disciplines. This is true because the physical processes involved are complex, but, in contrast to terrestrial weather, the supporting observations are typically sparse. Models play a vital role in establishing a physically meaningful context for interpreting limited observations, testing theory, and producing both nowcasts and forecasts. For example, with accurate forecasting of hazardous space weather conditions, spacecraft operators can place sensitive systems in safe modes, and power utilities can protect critical network components from damage caused by large currents induced in transmission lines by geomagnetic storms.

Evaluation of precipitation nowcasting techniques for the Alpine region

NASA Astrophysics Data System (ADS)

Panziera, L.; Mandapaka, P.; Atencia, A.; Hering, A.; Germann, U.; Gabella, M.; Buzzi, M.

2010-09-01

This study presents a large sample evaluation of different nowcasting systems over the Southern Swiss Alps. Radar observations are taken as a reference against which to assess the performance of the following short-term quantitative precipitation forecasting methods: -Eulerian persistence: the current radar image is taken as forecast. -Lagrangian persistence: precipitation patterns are advected following the field of storm motion (the MAPLE algorithm is used). -NORA: novel nowcasting system which exploits the presence of the orographic forcing; by comparing meteorological predictors estimated in real-time with those from the large historical data set, the events with the highest resemblance are picked to produce the forecast. -COSMO2, the limited area numerical model operationally used at MeteoSwiss -Blending of the aforementioned nowcasting tools precipitation forecasts. The investigation is aimed to set up a probabilistic radar rainfall runoff model experiment for steep Alpine catchments as part of the European research project IMPRINTS.

3 CFR 8830 - Proclamation 8830 of May 25, 2012. National Hurricane Preparedness Week, 2012

Code of Federal Regulations, 2013 CFR

2013-01-01

... damage from storm surges, flooding, high winds, and tornadoes. During National Hurricane Preparedness... prepare before storms strike. With the National Oceanic and Atmospheric Administration’s National Hurricane Center, we continue to advance accurate tropical storm forecasting that gives individuals more...

Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs

NASA Technical Reports Server (NTRS)

Valenti, Elizabeth; Fitzpatrick, Patrick

2006-01-01

Increasing the accuracy of storm-surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm-surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm-surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and, most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite-element-based codes. It affords a capability for simulating tidal circulation and storm-surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm-surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate. To keep the computational load manageable, this work was conducted using only the wind stress, calculated by using historical data from Hurricane Camille, as the input condition for the model. Hurricane storm-surge simulations were performed on an eight-node Linux computer cluster. Each node contained dual 2-GHz processors, 2GB of memory, and a 40GB hard drive. The digital elevation model (DEM) for this region was specified using a combination of Navy data (over water), NOAA data (for the coastline), and optimized Interferometric Synthetic Aperture Radar data (over land). This high-resolution topographical data of the Mississippi coastal region provided the ADCIRC model with improved input with which to calculate improved storm-surge forecasts.

Forecast cooling of the Atlantic subpolar gyre and associated impacts.

PubMed

Hermanson, Leon; Eade, Rosie; Robinson, Niall H; Dunstone, Nick J; Andrews, Martin B; Knight, Jeff R; Scaife, Adam A; Smith, Doug M

2014-07-28

Decadal variability in the North Atlantic and its subpolar gyre (SPG) has been shown to be predictable in climate models initialized with the concurrent ocean state. Numerous impacts over ocean and land have also been identified. Here we use three versions of the Met Office Decadal Prediction System to provide a multimodel ensemble forecast of the SPG and related impacts. The recent cooling trend in the SPG is predicted to continue in the next 5 years due to a decrease in the SPG heat convergence related to a slowdown of the Atlantic Meridional Overturning Circulation. We present evidence that the ensemble forecast is able to skilfully predict these quantities over recent decades. We also investigate the ability of the forecast to predict impacts on surface temperature, pressure, precipitation, and Atlantic tropical storms and compare the forecast to recent boreal summer climate.

Exploring Dust Impacts on Tropical Systems from the NASA HS-3 Field Campaign

NASA Technical Reports Server (NTRS)

Nowottnick, Ed; Colarco, Pete; da Silva, Arlindo; Barahona, Donifan; Hlavka, Dennis

2015-01-01

One of the overall scientific goals of the NASA Hurricane and Severe Storm Sentinel (HS-3) field campaign is to better understand the role of the Saharan Air Layer (SAL) in tropical storm development. During the 2012 HS-3 deployment, the Cloud Physics Lidar (CPL) observed dust within SAL air in close proximity to a developing Nadine (September 11, 2012). Throughout the mission, the NASA GEOS-5 modeling system supported HS-3 by providing 0.25 degrees resolution 5-day global forecasts of aerosols, which were used to support mission planning. The aerosol module was radiatively interactive within the GEOS-5 model, but aerosols were not directly coupled to cloud and precipitation processes. In this study we revisit the aerosol forecasts with an updated version of the GEOS-5 model. For the duration of Hurricane Nadine, we run multiday climate simulations leading up to each respective Global Hawk flight with and without aerosol direct interaction. For each set of simulations, we compare simulated dust mass fluxes to identify differences in SAL entrainment related to the interaction between dust aerosols and the atmosphere. We find that the direct effects of dust induce a low level anticyclonic circulation that temporarily shields Nadine from the intrusion of dry air, leading to a more intense storm.

NASA Sees Storms Affecting the Western U.S.

NASA Image and Video Library

2017-12-08

Extreme rain events have been affecting California and snow has blanketed the Pacific Northwest. This visible image from NASA's Aqua satellite on Jan. 6, 2017, at 3:35 p.m. EST (20:35 UTC) shows snow cover in the U.S. Pacific Northwest in Washington, Idaho, Oregon, northern California and Nevada. On Jan. 9, another area of low pressure moved over Oregon, where the National Weather Service is forecasting heavy snows. It was the same week last year that the West Coast endured a similar bout of very wet weather. Heavy rain affected the Pacific coast in 2016 during the same week from Jan. 5 through Jan. 7, as a progression of storm systems in the Eastern Pacific Ocean hit southern California and generated flooding and mudslides. For updated forecasts, visit the National Weather Service website at: www.weather.gov Learn more about NASA's view of the storm: go.nasa.gov/2j0xpvW Credits: NASA Goddard MODIS Rapid Response NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

The Representation of Extra-tropical Cyclones in Recent Re-Analyses: ERA-Interim, NASA-MERRA, NCEP-CFS and JRA25

NASA Astrophysics Data System (ADS)

Hodges, K.

2010-12-01

Re-analyses are produced using a forecast model, data assimilation system and historical observations. Whilst the observations are common between the re-analyses the way they are assimilated and the forecast model used are often different between the re-analyses which can introduce uncertainty in the representation of particular phenomena between the re-analyses, for example the distribution and properties of weather systems. It is important to inter-compare re-analyses to determine the uncertainty in their representation of the atmosphere, its circulation and weather systems in order to have confidence in their use for studies of the atmosphere and validating climate models. The four recent re-analyses, ERA-Interim, NASA-MERRA, NCEP-CFS and JRA25 are explored and compared for the representation of synoptic scale extra-tropical cyclones. Previous studies of the older re-analyses. ERA40, NCEP-NCAR and DOE has shown that whilst in the NH there was relatively good agreement between the re-analyses in terms of the distribution and properties of extra-tropical cyclones, in the SH there was much larger uncertainty. The newest re-analyses are produced at much higher resolutions than previous re-analyses, in addition more modern data assimilation systems and forecast models have been used. Hence, it would be hoped that the representation of cyclones will be improved to the same extent as that seen in modern NWP systems. This study contrasts extra-tropical cyclones, their distribution and properties, between these new re-analyses and compares them with cyclones in the slightly older though lower resolution JRA25 re-analysis. Results will show that in general in the higher resolution re-analysis more cyclones are identified than in JRA25. In the NH the distribution of storms agrees as well if not better than was the case for the older re-analyses. However, it is in the SH that the largest improvement in agreement is seen for the distribution of storms. For ERA-Interim, NASA-MERRA and NCEP-CFS the agreement in the SH is almost as good as in the NH with the best agreement occurring between ERA-Interim and NCEP-CFS. However, the comparison with JRA25 shows the same level of uncertainty as seen with the older re-analyses. Determining the separation distances of storms using storm matching confirm these results. The biggest differences between the re-analyses occurs for the intensity of storms with the NASA-MERRA having consistently the strongest extreme storms in terms of pressure and winds and JRA25 the weakest, ERA-Interim and NCEP-CFS are very similar in this respect. Using vorticity as an intensity measure shows the greatest sensitivity and goes with resolution. If time permits a comparison of the structure of the storms will also be presented. The approach used only highlights the uncertainty between the re-analyses it does not say which one is right. To try to address this some early results of comparing the re-analyses directly with observations of low level winds from scatterometers in the vicinity of storms will be presented if time permits.

Forecast model applications of retrieved three dimensional liquid water fields

NASA Technical Reports Server (NTRS)

Raymond, William H.; Olson, William S.

1990-01-01

Forecasts are made for tropical storm Emily using heating rates derived from the SSM/I physical retrievals described in chapters 2 and 3. Average values of the latent heating rates from the convective and stratiform cloud simulations, used in the physical retrieval, are obtained for individual 1.1 km thick vertical layers. Then, the layer-mean latent heating rates are regressed against the slant path-integrated liquid and ice precipitation water contents to determine the best fit two parameter regression coefficients for each layer. The regression formulae and retrieved precipitation water contents are utilized to infer the vertical distribution of heating rates for forecast model applications. In the forecast model, diabatic temperature contributions are calculated and used in a diabatic initialization, or in a diabatic initialization combined with a diabatic forcing procedure. Our forecasts show that the time needed to spin-up precipitation processes in tropical storm Emily is greatly accelerated through the application of the data.

NASA Sees Tropical Storm Bill Making Landfall in Texas

NASA Image and Video Library

2015-06-16

On June 15 at 19:15 UTC (3:15 p.m. EDT) the MODIS instrument aboard NASA's Aqua satellite captured a visible image of Tropical Storm Bill approaching Texas and Louisiana. Powerful thunderstorms circled the center in fragmented bands. At 11 a.m. CDT on June 16, a Tropical Storm Warning was in effect from Baffin Bay to High Island Texas as Bill was making landfall. The National Hurricane Center noted that Bill is expected to produce total rain accumulations of 4 to 8 inches over eastern Texas and eastern Oklahoma and 2 to 4 inches over western Arkansas and southern Missouri, with possible isolated maximum amounts of 12 inches in eastern Texas. In eastern Texas and far western Louisiana today and tonight, isolated tornadoes are also possible, as with any landfalling tropical storm. Tropical storm conditions are expected to continue into the evening in the warning area. Along the coasts, the combination of a storm surge and the tide will cause normally dry areas near the coast to be flooded by rising waters. The water could reach the following heights above ground if the peak surge occurs at the time of high tide. The NHC noted that the Upper Texas coast could experience 2 to 4 feet, and the western Louisiana coast between 1 to 2 feet. At 10 a.m. CDT (1500 UTC), the center of Tropical Storm Bill was located near latitude 28.2 North, longitude 96.4 West. Bill was moving toward the northwest near 10 mph (17 kph) and that general motion is expected to continue today. The latest minimum central pressure reported by an Air Force Reserve Hurricane Hunter aircraft was 997 millibars. Reports from an Air Force Reserve reconnaissance aircraft indicate that maximum sustained winds remain near 60 mph (95 kph) with higher gusts. Unlike Carlos, Bill is not a compact storm. Tropical-storm-force winds extend outward up to 150 miles (240 km) from the center. Between 9 and 10 a.m. CDT, an automated observing station at Port O'Connor also reported a sustained wind of 44 mph (70 kph) and a gust to 53 mph (85 kph). For updated forecasts, watches and warnings, visit the National Hurricane Center webpage at www.nhc.noaa.gov. For local forecasts and advisories, visit: www.weather.gov. Bill is forecast to continue moving inland and is expected to be a tropical depression by Wednesday, June 17, west of Dallas. The remnants of Bill are forecast to move into the Midwest later in the week. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Predicting Airspace Capacity Impacts Using the Consolidated Storm Prediction for Aviation

NASA Technical Reports Server (NTRS)

Russell, Carl

2010-01-01

Convective weather is currently the largest contributor to air traffic delays in the United States. In order to make effective traffic flow management decisions to mitigate these delays, weather forecasts must be made as early and as accurately as possible. A forecast product that could be used to mitigate convective weather impacts is the Consolidated Storm Prediction for Aviation. This product provides forecasts of cloud water content and convective top heights at 0- to 8-hour look-ahead times. The objective of this study was to examine a method of predicting the impact of convective weather on air traffic sector capacities using these forecasts. Polygons representing forecast convective weather were overlaid at multiple flight levels on a sector map to calculate the fraction of each sector covered by weather. The fractional volume coverage was used as the primary metric to determine convection s impact on sectors. Results reveal that the forecasts can be used to predict the probability and magnitude of weather impacts on sector capacity up to eight hours in advance.

Contrasting environments associated with storm prediction center tornado outbreak forecasts using synoptic-scale composite analysis

NASA Astrophysics Data System (ADS)

Bates, Alyssa Victoria

Tornado outbreaks have significant human impact, so it is imperative forecasts of these phenomena are accurate. As a synoptic setup lays the foundation for a forecast, synoptic-scale aspects of Storm Prediction Center (SPC) outbreak forecasts of varying accuracy were assessed. The percentages of the number of tornado outbreaks within SPC 10% tornado probability polygons were calculated. False alarm events were separately considered. The outbreaks were separated into quartiles using a point-in-polygon algorithm. Statistical composite fields were created to represent the synoptic conditions of these groups and facilitate comparison. Overall, temperature advection had the greatest differences between the groups. Additionally, there were significant differences in the jet streak strengths and amounts of vertical wind shear. The events forecasted with low accuracy consisted of the weakest synoptic-scale setups. These results suggest it is possible that events with weak synoptic setups should be regarded as areas of concern by tornado outbreak forecasters.

Storm Surge and Tide Interaction: A Complete Paradigm

NASA Astrophysics Data System (ADS)

Horsburgh, K.

2014-12-01

Estimates show that in 2005, in the largest 136 coastal cities, there were 40 million people and 3,000 billion of assets exposed to 1 in 100 year coastal flood events. Mean sea level rise will increase this exposure to 150 million people and 35,000 billion of assets by 2070. Any further change in the statistics of flood frequency or severity would impact severely on economic and social systems. It is therefore crucial to understand the physical drivers of extreme storm surges, and to have confidence in datasets used for extreme sea level statistics. Much previous research has focussed on the process of tide-surge interaction, and it is now widely accepted that the physical basis of tide-surge interaction is that a phase shift of the tidal signal represents the effect of the surge on the tide. The second aspect of interaction is that shallow water momentum considerations imply that differing tidal states should modulate surge generation: wind stress should have greater surge-generating potential on lower tides. We present results from a storm surge model of the European shelf that demonstrate that tidal range does have an effect on the surges generated. The cycle-integrated effects of wind stress (i.e. the skew surge) are greater when tidal range is low. Our results contradict the absence of any such correlation in tide gauge records. This suggests that whilst the modulating effect of the tide on the skew surge (the time-independent difference between peak prediction and observations) is significant, the difference between individual storms is dominant. This implies that forecasting systems must predict salient detail of the most intense storms. A further implication is that flood forecasting models need to simulate tides with acceptable accuracy at all coastal locations. We extend our model analysis to show that the same modulation of storm surges (by tidal conditions) applies to tropical cyclones. We conduct simulations using a mature operational storm surge model in the Bay of Bengal with tropical cyclones from the IBTrACs database; we demonstrate that - just as with the extra-tropical case - higher storm surges on the Bangladesh coastline are generated during smaller tides.

Hydrodaynamic - Statistical Forecast Method To 36-48h Ahead Of Storm Wind And Tornadoes Over The Territory Of Europe And Siberia

NASA Astrophysics Data System (ADS)

Perekhodtseva, Elvira V.

2010-05-01

Development of successful method of forecast of storm winds, including squalls and tornadoes, that often result in human and material losses, could allow one to take proper measures against destruction of buildings and to protect people. Well-in-advance successful forecast (from 12 hours to 48 hour) makes possible to reduce the losses. Prediction of the phenomena involved is a very difficult problem for synoptic till recently. The existing graphic and calculation methods still depend on subjective decision of an operator. Nowadays in Russia there is no hydrodynamic model for forecast of the maximal wind velocity V> 25m/c, hence the main tools of objective forecast are statistical methods using the dependence of the phenomena involved on a number of atmospheric parameters (predictors). . Statistical decisive rule of the alternative and probability forecast of these events was obtained in accordance with the concept of "perfect prognosis" using the data of objective analysis. For this purpose the different teaching samples of present and absent of this storm wind and rainfalls were automatically arranged that include the values of forty physically substantiated potential predictors. Then the empirical statistical method was used that involved diagonalization of the mean correlation matrix R of the predictors and extraction of diagonal blocks of strongly correlated predictors. Thus for these phenomena the most informative predictors were selected without loosing information. The statistical decisive rules for diagnosis and prognosis of the phenomena involved U(X) were calculated for choosing informative vector-predictor. We used the criterion of distance of Mahalanobis and criterion of minimum of entropy by Vapnik-Chervonenkis for the selection predictors. Successful development of hydrodynamic models for short-term forecast and improvement of 36-48h forecasts of pressure, temperature and others parameters allowed us to use the prognostic fields of those models for calculations of the discriminant functions in the nodes of the grid 75x75km and the values of probabilities P of dangerous wind and thus to get fully automated forecasts. . In order to apply the alternative forecast to European part of Russia and Europe the author proposes the empirical threshold values specified for this phenomenon and advance period 36 hours. According to the Pirsey-Obukhov criterion (T), the success of this hydrometeorological-statistical method of forecast of storm wind and tornadoes to 36 -48 hours ahead in the warm season for the territory of Europe part of Russia and Siberia is T = 1-a-b=0,54-0,78 after independent and author experiments during the period 2004-2009 years. A lot of examples of very successful forecasts are submitted at this report for the territory of Europe and Russia. The same decisive rules were applied to the forecast of these phenomena during cold period in 2009-2010 years too. On the first month of 2010 a lot of cases of storm wind with heavy snowfall were observed and were forecasting over the territory of France, Italy and Germany.

Unique Datasets Collected by NOAA Hurricane Hunter Aircraft during the 2017 Atlantic Hurricane Season

NASA Astrophysics Data System (ADS)

Zawislak, J.; Reasor, P.

2017-12-01

Each year, NOAA's Atlantic Oceanographic & Meteorological Laboratory (AOML) Hurricane Research Division (HRD), in partnership with the National Hurricane Center (NHC) and NOAA's Environmental Modeling Center (EMC), operates a hurricane field program, the Intensity Forecast Experiment (IFEX). The experiment leverages the NOAA P-3 and G-IV hurricane hunter aircraft, based at NOAA's Office of Marine and Aviation Operations (OMAO) Aircraft Operations Center (AOC). The goals of IFEX are to improve understanding of physical processes in tropical cyclones (TCs), improve operational forecasts of TC intensity, structure, and rainfall by providing data into operational numerical modeling systems, and to develop and refine measurement technologies. This season the IFEX program, leveraging mainly operationally tasked EMC and NHC missions, sampled extensively Hurricanes Harvey, Irma, Jose, Maria, and Nate, as well as Tropical Storm Franklin. We will contribute to this important session by providing an overview of aircraft missions into these storms, guidance on the datasets made available from instruments onboard the P-3 and G-IV, and will offer some perspective on the science that can be addressed with these unique datasets, such as the value of those datasets towards model forecast improvement. NOAA aircraft sampled these storms during critical periods of intensification, and for Hurricanes Harvey and Irma, just prior to the devastating landfalls in the Caribbean and United States. The unique instrument suite on the P-3 offers inner core observations of the three-dimensional precipitation and vortex structure, lower troposphere (boundary layer) thermodynamic properties, and surface wind speed. In contrast, the G-IV flies at higher altitudes, sampling the environment surrounding the storms, and provides deep-tropospheric soundings from dropsondes.

An Approach to Remove the Systematic Bias from the Storm Surge forecasts in the Venice Lagoon

NASA Astrophysics Data System (ADS)

Canestrelli, A.

2017-12-01

In this work a novel approach is proposed for removing the systematic bias from the storm surge forecast computed by a two-dimensional shallow-water model. The model covers both the Adriatic and Mediterranean seas and provides the forecast at the entrance of the Venice Lagoon. The wind drag coefficient at the water-air interface is treated as a calibration parameter, with a different value for each range of wind velocities and wind directions. This sums up to a total of 16-64 parameters to be calibrated, depending on the chosen resolution. The best set of parameters is determined by means of an optimization procedure, which minimizes the RMS error between measured and modeled water level in Venice for the period 2011-2015. It is shown that a bias is present, for which the peaks of wind velocities provided by the weather forecast are largely underestimated, and that the calibration procedure removes this bias. When the calibrated model is used to reproduce events not included in the calibration dataset, the forecast error is strongly reduced, thus confirming the quality of our procedure. The proposed approach it is not site-specific and could be applied to different situations, such as storm surges caused by intense hurricanes.

Assessment of Modeling Capability for Reproducing Storm Impacts on TEC

NASA Astrophysics Data System (ADS)

Shim, J. S.; Kuznetsova, M. M.; Rastaetter, L.; Bilitza, D.; Codrescu, M.; Coster, A. J.; Emery, B. A.; Foerster, M.; Foster, B.; Fuller-Rowell, T. J.; Huba, J. D.; Goncharenko, L. P.; Mannucci, A. J.; Namgaladze, A. A.; Pi, X.; Prokhorov, B. E.; Ridley, A. J.; Scherliess, L.; Schunk, R. W.; Sojka, J. J.; Zhu, L.

2014-12-01

During geomagnetic storm, the energy transfer from solar wind to magnetosphere-ionosphere system adversely affects the communication and navigation systems. Quantifying storm impacts on TEC (Total Electron Content) and assessment of modeling capability of reproducing storm impacts on TEC are of importance to specifying and forecasting space weather. In order to quantify storm impacts on TEC, we considered several parameters: TEC changes compared to quiet time (the day before storm), TEC difference between 24-hour intervals, and maximum increase/decrease during the storm. We investigated the spatial and temporal variations of the parameters during the 2006 AGU storm event (14-15 Dec. 2006) using ground-based GPS TEC measurements in the selected 5 degree eight longitude sectors. The latitudinal variations were also studied in two longitude sectors among the eight sectors where data coverage is relatively better. We obtained modeled TEC from various ionosphere/thermosphere (IT) models. The parameters from the models were compared with each other and with the observed values. We quantified performance of the models in reproducing the TEC variations during the storm using skill scores. This study has been supported by the Community Coordinated Modeling Center (CCMC) at the Goddard Space Flight Center. Model outputs and observational data used for the study will be permanently posted at the CCMC website (http://ccmc.gsfc.nasa.gov) for the space science communities to use.

Exploring Options for an Integrated Water Level Observation Network in Alaska

NASA Astrophysics Data System (ADS)

McCammon, M.

2016-02-01

Portions' of Alaska's remote coastlines are among the Nation's most vulnerable to geohazards such as tsunami, extra-tropical storm surge, and erosion; and the availability of observations of water levels, ocean waves, and river discharge are severely lacking to support water level warnings and forecasts. Alaska is experiencing dramatic reductions in sea ice cover, changes in extra-tropical storm surge patterns, and thawing permafrost. These conditions are endangering coastal populations throughout the State. Gaps in the ocean observing system limit our State's ability to provide useful marine and sea ice forecasts, especially in the Arctic. A spectrum of observation platforms may provide an optimal solution for filling the most critical gaps in these coastal and ocean areas. The collaborations described in this talk and better leveraging of resources and capabilities across federal, state, and academic partners will provide the best opportunity for advancing our science capacity and capabilities in this remote region.

Evaluation of radar and automatic weather station data assimilation for a heavy rainfall event in southern China

NASA Astrophysics Data System (ADS)

Hou, Tuanjie; Kong, Fanyou; Chen, Xunlai; Lei, Hengchi; Hu, Zhaoxia

2015-07-01

To improve the accuracy of short-term (0-12 h) forecasts of severe weather in southern China, a real-time storm-scale forecasting system, the Hourly Assimilation and Prediction System (HAPS), has been implemented in Shenzhen, China. The forecasting system is characterized by combining the Advanced Research Weather Research and Forecasting (WRF-ARW) model and the Advanced Regional Prediction System (ARPS) three-dimensional variational data assimilation (3DVAR) package. It is capable of assimilating radar reflectivity and radial velocity data from multiple Doppler radars as well as surface automatic weather station (AWS) data. Experiments are designed to evaluate the impacts of data assimilation on quantitative precipitation forecasting (QPF) by studying a heavy rainfall event in southern China. The forecasts from these experiments are verified against radar, surface, and precipitation observations. Comparison of echo structure and accumulated precipitation suggests that radar data assimilation is useful in improving the short-term forecast by capturing the location and orientation of the band of accumulated rainfall. The assimilation of radar data improves the short-term precipitation forecast skill by up to 9 hours by producing more convection. The slight but generally positive impact that surface AWS data has on the forecast of near-surface variables can last up to 6-9 hours. The assimilation of AWS observations alone has some benefit for improving the Fractions Skill Score (FSS) and bias scores; when radar data are assimilated, the additional AWS data may increase the degree of rainfall overprediction.

A survey of major east coast snowstorms, 1960-1983. Part 2: Case studies of eighteen storms

NASA Technical Reports Server (NTRS)

Kocin, P. J.; Uccellini, L. W.

1985-01-01

Snowfall, surface and upper air charts, and available satellite images are presented for eighteen major East Coast snowstorms that occurred between 1960 and 1983. The charts and descriptions of key fields are provided so that students, weather forecasters, and researchers alike can visualize how a large sample of major winter cyclones form and intensify. Although there are noted similarities in certain aspects of the surface and upper tropospheric development of the storms, significant case-to-case variability precludes the ability to effectively composite these weather systems.

Reliability of windstorm predictions in the ECMWF ensemble prediction system

NASA Astrophysics Data System (ADS)

Becker, Nico; Ulbrich, Uwe

2016-04-01

Windstorms caused by extratropical cyclones are one of the most dangerous natural hazards in the European region. Therefore, reliable predictions of such storm events are needed. Case studies have shown that ensemble prediction systems (EPS) are able to provide useful information about windstorms between two and five days prior to the event. In this work, ensemble predictions with the European Centre for Medium-Range Weather Forecasts (ECMWF) EPS are evaluated in a four year period. Within the 50 ensemble members, which are initialized every 12 hours and are run for 10 days, windstorms are identified and tracked in time and space. By using a clustering approach, different predictions of the same storm are identified in the different ensemble members and compared to reanalysis data. The occurrence probability of the predicted storms is estimated by fitting a bivariate normal distribution to the storm track positions. Our results show, for example, that predicted storm clusters with occurrence probabilities of more than 50% have a matching observed storm in 80% of all cases at a lead time of two days. The predicted occurrence probabilities are reliable up to 3 days lead time. At longer lead times the occurrence probabilities are overestimated by the EPS.

Third National Aeronautics and Space Administration Weather and climate program science review

NASA Technical Reports Server (NTRS)

Kreins, E. R. (Editor)

1977-01-01

Research results of developing experimental and prototype operational systems, sensors, and space facilities for monitoring, and understanding the atmosphere are reported. Major aspects include: (1) detection, monitoring, and prediction of severe storms; (2) improvement of global forecasting; and (3) monitoring and prediction of climate change.

Addressing Common Cloud-Radiation Errors from 4-hour to 4-week Model Prediction

NASA Astrophysics Data System (ADS)

Benjamin, S.; Sun, S.; Grell, G. A.; Green, B.; Olson, J.; Kenyon, J.; James, E.; Smirnova, T. G.; Brown, J. M.

2017-12-01

Cloud-radiation representation in models for subgrid-scale clouds is a known gap from subseasonal-to-seasonal models down to storm-scale models applied for forecast duration of only a few hours. NOAA/ESRL has been applying common physical parameterizations for scale-aware deep/shallow convection and boundary-layer mixing over this wide range of time and spatial scales, with some progress to be reported in this presentation. The Grell-Freitas scheme (2014, Atmos. Chem. Phys.) and MYNN boundary-layer EDMF scheme (Olson / Benjamin et al. 2016 Mon. Wea. Rev.) have been applied and tested extensively for the NOAA hourly updated 3-km High-Resolution Rapid Refresh (HRRR) and 13-km Rapid Refresh (RAP) model/assimilation systems over the United States and North America, with targeting toward improvement to boundary-layer evolution and cloud-radiation representation in all seasons. This representation is critical for both warm-season severe convective storm forecasting and for winter-storm prediction of snow and mixed precipitation. At the same time the Grell-Freitas scheme has been applied also as an option for subseasonal forecasting toward improved US week 3-4 prediction with the FIM-HYCOM coupled model (Green et al 2017, MWR). Cloud/radiation evaluation using CERES satellite-based estimates have been applied to both 12-h RAP (13km) and also during Weeks 1-4 from 32-day FIM-HYCOM (60km) forecasts. Initial results reveal that improved cloud representation is needed for both resolutions and now is guiding further refinement for cloud representation including with the Grell-Freitas scheme and with the updated MYNN-EDMF scheme (both now also in global testing as well as with the 3km HRRR and 13km RAP models).

A multi-scale ensemble-based framework for forecasting compound coastal-riverine flooding: The Hackensack-Passaic watershed and Newark Bay

NASA Astrophysics Data System (ADS)

Saleh, F.; Ramaswamy, V.; Wang, Y.; Georgas, N.; Blumberg, A.; Pullen, J.

2017-12-01

Estuarine regions can experience compound impacts from coastal storm surge and riverine flooding. The challenges in forecasting flooding in such areas are multi-faceted due to uncertainties associated with meteorological drivers and interactions between hydrological and coastal processes. The objective of this work is to evaluate how uncertainties from meteorological predictions propagate through an ensemble-based flood prediction framework and translate into uncertainties in simulated inundation extents. A multi-scale framework, consisting of hydrologic, coastal and hydrodynamic models, was used to simulate two extreme flood events at the confluence of the Passaic and Hackensack rivers and Newark Bay. The events were Hurricane Irene (2011), a combination of inland flooding and coastal storm surge, and Hurricane Sandy (2012) where coastal storm surge was the dominant component. The hydrodynamic component of the framework was first forced with measured streamflow and ocean water level data to establish baseline inundation extents with the best available forcing data. The coastal and hydrologic models were then forced with meteorological predictions from 21 ensemble members of the Global Ensemble Forecast System (GEFS) to retrospectively represent potential future conditions up to 96 hours prior to the events. Inundation extents produced by the hydrodynamic model, forced with the 95th percentile of the ensemble-based coastal and hydrologic boundary conditions, were in good agreement with baseline conditions for both events. The USGS reanalysis of Hurricane Sandy inundation extents was encapsulated between the 50th and 95th percentile of the forecasted inundation extents, and that of Hurricane Irene was similar but with caveats associated with data availability and reliability. This work highlights the importance of accounting for meteorological uncertainty to represent a range of possible future inundation extents at high resolution (∼m).

Deflected Propagation of Coronal Mass Ejections: One of the Key Issues in Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Wang, Y.; Shen, C.; Zhuang, B.; Pan, Z.

2016-12-01

As the most important driver of severe space weather, coronal mass ejections (CMEs) and their geoeffectiveness have been studied intensively. Previous statistical studies have shown that not all the front-side halo CMEs are geoeffective, and not all non-recurrent geomagnetic storms can be tracked back to a CME. These phenomena may cause some failed predictions of the geoeffectiveness of CMEs. The recent notable event exhibiting such a failure was on 2015 March 15 when a fast CME originated from the west hemisphere. Space Weather Prediction Center (SWPC) of NOAA initially forecasted that the CME would at most cause a very minor geomagnetic disturbance labeled as G1. However, the CME produced the largest geomagnetic storm so far, at G4 level with the provisional Dst value of -223 nT, in the current solar cycle 24 [e.g., Kataoka et al., 2015; Wang et al., 2016]. Such an unexpected phenomenon naturally raises the first question for the forecasting of the geoeffectiveness of a CME, i.e., whether or not a CME will hit the Earth even though we know the source location and initial kinematic properties of the CME. A full understanding of the propagation trajectory, e.g., the deflected propagation, of a CME from the Sun to 1 AU is the key. With a few cases, we show the importance of the deflection effect in the space weather forecasting. An automated CME arrival forecasting system containing a deflected propagation model is presented. References:[1] Kataoka, R., D. Shiota, E. Kilpua, and K. Keika, Pileup accident hypothesis of magnetic storm on 17 March 2015, Geophys. Res. Lett., 42, 5155-5161, 2015.[2] Wang, Yuming, Quanhao Zhang, Jiajia Liu, Chenglong Shen, Fang Shen, Zicai Yang, T. Zic, B. Vrsnak, D. F. Webb, Rui Liu, S. Wang, Jie Zhang, Q. Hu, and B. Zhuang, On the Propagation of a Geoeffective Coronal Mass Ejection during March 15 - 17, 2015, J. Geophys. Res., accepted, doi:10.1002/2016JA022924, 2016.

Operational Forecasting and Warning systems for Coastal hazards in Korea

NASA Astrophysics Data System (ADS)

Park, Kwang-Soon; Kwon, Jae-Il; Kim, Jin-Ah; Heo, Ki-Young; Jun, Kicheon

2017-04-01

Coastal hazards caused by both Mother Nature and humans cost tremendous social, economic and environmental damages. To mitigate these damages many countries have been running the operational forecasting or warning systems. Since 2009 Korea Operational Oceanographic System (KOOS) has been developed by the leading of Korea Institute of Ocean Science and Technology (KIOST) in Korea and KOOS has been operated in 2012. KOOS is consists of several operational modules of numerical models and real-time observations and produces the basic forecasting variables such as winds, tides, waves, currents, temperature and salinity and so on. In practical application systems include storm surges, oil spills, and search and rescue prediction models. In particular, abnormal high waves (swell-like high-height waves) have occurred in the East coast of Korea peninsula during winter season owing to the local meteorological condition over the East Sea, causing property damages and the loss of human lives. In order to improve wave forecast accuracy even very local wave characteristics, numerical wave modeling system using SWAN is established with data assimilation module using 4D-EnKF and sensitivity test has been conducted. During the typhoon period for the prediction of sever waves and the decision making support system for evacuation of the ships, a high-resolution wave forecasting system has been established and calibrated.

Assimilation of GPM GMI Rainfall Product with WRF GSI

NASA Technical Reports Server (NTRS)

Li, Xuanli; Mecikalski, John; Zavodsky, Bradley

2015-01-01

The Global Precipitation Measurement (GPM) is an international mission to provide next-generation observations of rain and snow worldwide. The GPM built on Tropical Rainfall Measuring Mission (TRMM) legacy, while the core observatory will extend the observations to higher latitudes. The GPM observations can help advance our understanding of precipitation microphysics and storm structures. Launched on February 27th, 2014, the GPM core observatory is carrying advanced instruments that can be used to quantify when, where, and how much it rains or snows around the world. Therefore, the use of GPM data in numerical modeling work is a new area and will have a broad impact in both research and operational communities. The goal of this research is to examine the methodology of assimilation of the GPM retrieved products. The data assimilation system used in this study is the community Gridpoint Statistical Interpolation (GSI) system for the Weather Research and Forecasting (WRF) model developed by the Development Testbed Center (DTC). The community GSI system runs in independently environment, yet works functionally equivalent to operational centers. With collaboration with the NASA Short-term Prediction Research and Transition (SPoRT) Center, this research explores regional assimilation of the GPM products with case studies. Our presentation will highlight our recent effort on the assimilation of the GPM product 2AGPROFGMI, the retrieved Microwave Imager (GMI) rainfall rate data for initializing a real convective storm. WRF model simulations and storm scale data assimilation experiments will be examined, emphasizing both model initialization and short-term forecast of precipitation fields and processes. In addition, discussion will be provided on the development of enhanced assimilation procedures in the GSI system with respect to other GPM products. Further details of the methodology of data assimilation, preliminary result and test on the impact of GPM data and the influence on precipitation forecast will be presented at the conference.

Dust Storm Feature Identification and Tracking from 4D Simulation Data

NASA Astrophysics Data System (ADS)

Yu, M.; Yang, C. P.

2016-12-01

Dust storms cause significant damage to health, property and the environment worldwide every year. To help mitigate the damage, dust forecasting models simulate and predict upcoming dust events, providing valuable information to scientists, decision makers, and the public. Normally, the model simulations are conducted in four-dimensions (i.e., latitude, longitude, elevation and time) and represent three-dimensional (3D), spatial heterogeneous features of the storm and its evolution over space and time. This research investigates and proposes an automatic multi-threshold, region-growing based identification algorithm to identify critical dust storm features, and track the evolution process of dust storm events through space and time. In addition, a spatiotemporal data model is proposed, which can support the characterization and representation of dust storm events and their dynamic patterns. Quantitative and qualitative evaluations for the algorithm are conducted to test the sensitivity, and capability of identify and track dust storm events. This study has the potential to assist a better early warning system for decision-makers and the public, thus making hazard mitigation plans more effective.

Continuous Estimates of Precipitable Water Vapor Within and Around Hurricane Systems

NASA Astrophysics Data System (ADS)

Braun, J. J.; Iwabuchi, T.; van Hove, T.

2008-12-01

This study investigates how estimates of precipitable water vapor (PW) from Global Positioning System (GPS) stations can be used to quantify how atmospheric moisture influences the intensity of tropical storms and hurricanes. The motivation for this study is based on the fact that hurricanes derive their strength through water vapor that is both evaporated from warm ocean surfaces and the existing moisture in the surrounding atmospheric environment. Observationally, there are relatively few instruments that can accurately measure water vapor in the presence of clouds and rain. Retrievals of PW using GPS stations may be the most reliable way to continuously monitor column integrated water vapor. Using storm information from the National Hurricane Center (www.nhc.noaa.gov), we have compared storm intensity to PW estimates for all tropical storms and hurricanes making landfall within 100-km of a GPS station between 2003 and 2008. We find that PW is inversely correlated (r**2 < -0.7) to the drop in surface pressure observed at that station. We have also begun to relate atmospheric PW at a station to the local sea surface temperature (SST). This comparison can be used to measure how strongly atmospheric water vapor and SST are coupled. It can also be used to measure how quickly the atmosphere responds to changes in SST. Finally we have compared the estimated PW to the Global Forecast System (GFS) analysis fields that are used to initialize numerical weather prediction models. This comparison indicates that the GFS analysis fields have significantly larger errors in atmospheric moisture in the Caribbean and Gulf of Mexico when compared to differences over the continental United States. These results illustrate that estimates of PW are an important data set for atmospheric scientists and forecasters attempting to improve the prediction of hurricane intensity.

The Role of the AMOC in Forecast Cooling of the Atlantic Subpolar Gyre and Its Associated Impacts

NASA Astrophysics Data System (ADS)

Eade, R.; Hermanson, L.; Robinson, N.; Dunstone, N.; Andrews, M.; Knight, J.; Scaife, A. A.; Smith, D.

2014-12-01

Decadal variability in the North Atlantic and its subpolar gyre (SPG) has been shown to be predictable in climate models initialized with the concurrent ocean state. Numerous impacts over ocean and land have also been identified. Here we use three versions of the Met Office Decadal Prediction System to provide a multimodel ensemble forecast of the SPG and related impacts. The recent cooling trend in the SPG is predicted to continue in the next 5 years due to a decrease in the SPG heat convergence related to a slowdown of the Atlantic Meridional Overturning Circulation. We present evidence that the ensemble forecast is able to skilfully predict these quantities over recent decades. We also investigate the ability of the forecast to predict impacts on surface temperature, pressure, precipitation, and Atlantic tropical storms and compare the forecast to recent boreal summer climate.

Forecast cooling of the Atlantic subpolar gyre and associated impacts

PubMed Central

Hermanson, Leon; Eade, Rosie; Robinson, Niall H; Dunstone, Nick J; Andrews, Martin B; Knight, Jeff R; Scaife, Adam A; Smith, Doug M

2014-01-01

Decadal variability in the North Atlantic and its subpolar gyre (SPG) has been shown to be predictable in climate models initialized with the concurrent ocean state. Numerous impacts over ocean and land have also been identified. Here we use three versions of the Met Office Decadal Prediction System to provide a multimodel ensemble forecast of the SPG and related impacts. The recent cooling trend in the SPG is predicted to continue in the next 5 years due to a decrease in the SPG heat convergence related to a slowdown of the Atlantic Meridional Overturning Circulation. We present evidence that the ensemble forecast is able to skilfully predict these quantities over recent decades. We also investigate the ability of the forecast to predict impacts on surface temperature, pressure, precipitation, and Atlantic tropical storms and compare the forecast to recent boreal summer climate. PMID:25821269

Development of a Probabilistic Decision-Support Model to Forecast Coastal Resilience

NASA Astrophysics Data System (ADS)

Wilson, K.; Safak, I.; Brenner, O.; Lentz, E. E.; Hapke, C. J.

2016-02-01

Site-specific forecasts of coastal change are a valuable management tool in preparing for and assessing storm-driven impacts in coastal areas. More specifically, understanding the likelihood of storm impacts, recovery following events, and the alongshore variability of both is central in evaluating vulnerability and resiliency of barrier islands. We introduce a probabilistic modeling framework that integrates hydrodynamic, anthropogenic, and morphologic components of the barrier system to evaluate coastal change at Fire Island, New York. The model is structured on a Bayesian network (BN), which utilizes observations to learn statistical relationships between system variables. In addition to predictive ability, probabilistic models convey the level of confidence associated with a prediction, an important consideration for coastal managers. Our model predicts the likelihood of morphologic change on the upper beach based on several decades of beach monitoring data. A coupled hydrodynamic BN combines probabilistic and deterministic modeling approaches; by querying nearly two decades of nested-grid wave simulations that account for both distant swells and local seas, we produce scenarios of event and seasonal wave climates. The wave scenarios of total water level - a sum of run up, surge and tide - and anthropogenic modification are the primary drivers of morphologic change in our model structure. Preliminary results show the hydrodynamic BN is able to reproduce time series of total water levels, a critical validation process before generating scenarios, and forecasts of geomorphic change over three month intervals are up to 70% accurate. Predictions of storm-induced change and recovery are linked to evaluate zones of persistent vulnerability or resilience and will help managers target restoration efforts, identify areas most vulnerable to habitat degradation, and highlight resilient zones that may best support relocation of critical infrastructure.

Progress and Challenges in Short to Medium Range Coupled Prediction

NASA Technical Reports Server (NTRS)

Brassington, G. B.; Martin, M. J.; Tolman, H. L.; Akella, Santha; Balmeseda, M.; Chambers, C. R. S.; Cummings, J. A.; Drillet, Y.; Jansen, P. A. E. M.; Laloyaux, P.;

Integrating Windblown Dust Forecasts with Public Safety and Health Systems

NASA Astrophysics Data System (ADS)

Sprigg, W. A.

2014-12-01

Experiments in real-time prediction of desert dust emissions and downstream plume concentrations (~ 3.5 km near-surface spatial resolution) succeed to the point of challenging public safety and public health services to beta test a dust storm warning and advisory system in lowering risks of highway and airline accidents and illnesses such as asthma and valley fever. Key beta test components are: high-resolution models of dust emission, entrainment and diffusion, integrated with synoptic weather observations and forecasts; satellite-based detection and monitoring of soil properties on the ground and elevated above; high space and time resolution for health surveillance and transportation advisories.

Artificial Neural Network forecasting of storm surge water levels at major estuarine ports to supplement national tide-surge models and improve port resilience planning

NASA Astrophysics Data System (ADS)

French, Jon; Mawdsley, Robert; Fujiyama, Taku; Achuthan, Kamal

2017-04-01

Effective prediction of tidal storm surge is of considerable importance for operators of major ports, since much of their infrastructure is necessarily located close to sea level. Storm surge inundation can damage critical elements of this infrastructure and significantly disrupt port operations and downstream supply chains. The risk of surge inundation is typically approached using extreme value analysis, while short-term forecasting generally relies on coastal shelf-scale tide and surge models. However, extreme value analysis does not provide information on the duration of a surge event and can be sensitive to the assumptions made and the historic data available. Also, whilst regional tide and surge models perform well along open coasts, their fairly coarse spatial resolution means that they do not always provide accurate predictions for estuarine ports. As part of a NERC Environmental Risks to Infrastructure Innovation Programme project, we have developed a tool that is specifically designed to forecast the North Sea storm surges on major ports along the east coast of the UK. Of particular interest is the Port of Immingham, Humber estuary, which handles the largest volume of bulk cargo in the UK including major flows of coal and biomass for power generation. A tidal surge in December 2013, with an estimated return period of 760 years, partly flooded the port, damaged infrastructure and disrupted operations for several weeks. This and other recent surge events highlight the need for additional tools to supplement the national UK Storm Tide Warning Service. Port operators are also keen to have access to less computationally expensive forecasting tools for scenario planning and to improve their resilience to actual events. In this paper, we demonstrate the potential of machine learning methods based on Artificial Neural Networks (ANNs) to generate accurate short-term forecasts of extreme water levels at estuarine North Sea ports such as Immingham. An ANN is configured to take advantage of far-field information on developing tidal surges provided by tide gauges in NW Scotland (the 'external surge'), supported by observations of wind and atmospheric pressure and the predicted astronomical tide at Immingham. Missing data can cause problems with ANN models and a novel aspect of our implementation is the use of multiple redundant inputs (nearby tide gauges that experience a high degree of surge coherence) to synthesise a single external surge input. A similar approach is taken with meteorological forcings, creating an ANN that is resilient against data drop-outs within its input vector. The ANN generates 6 to 24 hour surge forecasts at Immingham with accuracy better than the present UK Storm Tide Warning Service. These can be used to cross-check national forecasts, generate more accurate estimates of likely flood depths, timings and durations and trigger planned responses to severe forecasts. Crucially, this capability can be 'owned' by the port operator, which encourages the development of a shared understanding of storm surge hazards and the challenges of port resilience planning between scientist and stakeholder.

Deflected Propagation of CMEs and Its Importance on the CME Arrival Forecasting

NASA Astrophysics Data System (ADS)

Wang, Yuming; Zhuang, Bin; Shen, Chenglong

2017-04-01

As the most important driver of severe space weather, coronal mass ejections (CMEs) and their geoeffectiveness have been studied intensively. Previous statistical studies have shown that not all the front-side halo CMEs are geoeffective, and not all non-recurrent geomagnetic storms can be tracked back to a CME. These phenomena may cause some failed predictions of the geoeffectiveness of CMEs. The recent notable event exhibiting such a failure was on 2015 March 15 when a fast CME originated from the west hemisphere. Space Weather Prediction Center (SWPC) of NOAA initially forecasted that the CME would at most cause a very minor geomagnetic disturbance labeled as G1. However, the CME produced the largest geomagnetic storm so far, at G4 level with the provisional Dst value of -223 nT, in the current solar cycle 24 [e.g., Kataoka et al., 2015; Wang et al., 2016]. Such an unexpected phenomenon naturally raises the first question for the forecasting of the geoeffectiveness of a CME, i.e., whether or not a CME will hit the Earth even though we know the source location and initial kinematic properties of the CME. A full understanding of the propagation trajectory, e.g., the deflected propagation, of a CME from the Sun to 1 AU is the key. With a few cases, we show the importance of the deflection effect in the space weather forecasting. An automated CME arrival forecasting system containing a deflected propagation model is presented.

Set-up and validation of a Delft-FEWS based coastal hazard forecasting system

NASA Astrophysics Data System (ADS)

Valchev, Nikolay; Eftimova, Petya; Andreeva, Nataliya

2017-04-01

European coasts are increasingly threatened by hazards related to low-probability and high-impact hydro-meteorological events. Uncertainties in hazard prediction and capabilities to cope with their impact lie in both future storm pattern and increasing coastal development. Therefore, adaptation to future conditions requires a re-evaluation of coastal disaster risk reduction (DRR) strategies and introduction of a more efficient mix of prevention, mitigation and preparedness measures. The latter presumes that development of tools, which can manage the complex process of merging data and models and generate products on the current and expected hydro-and morpho-dynamic states of the coasts, such as forecasting system of flooding and erosion hazards at vulnerable coastal locations (hotspots), is of vital importance. Output of such system can be of an utmost value for coastal stakeholders and the entire coastal community. In response to these challenges, Delft-FEWS provides a state-of-the-art framework for implementation of such system with vast capabilities to trigger the early warning process. In addition, this framework is highly customizable to the specific requirements of any individual coastal hotspot. Since its release many Delft-FEWS based forecasting system related to inland flooding have been developed. However, limited number of coastal applications was implemented. In this paper, a set-up of Delft-FEWS based forecasting system for Varna Bay (Bulgaria) and a coastal hotspot, which includes a sandy beach and port infrastructure, is presented. It is implemented in the frame of RISC-KIT project (Resilience-Increasing Strategies for Coasts - toolKIT). The system output generated in hindcast mode is validated with available observations of surge levels, wave and morphodynamic parameters for a sequence of three short-duration and relatively weak storm events occurred during February 4-12, 2015. Generally, the models' performance is considered as very good and results obtained - quite promising for reliable prediction of both boundary conditions and coastal hazard and gives a good basis for estimation of onshore impact.

Evaluation of radar rainfall estimates and nowcasts to prevent flash flood in real time by using a road submersion warning tool

NASA Astrophysics Data System (ADS)

Versini, Pierre-Antoine; Sempere-Torres, Daniel

2010-05-01

Important damages occur in small headwater catchments when they are hit by severe storms with complex spatio-temporal structure, sometimes resulting in flash floods. As these catchments are mostly not covered by sensor networks, it is difficult to forecast these floods. This is particularly true for road submersions. These are major concerns for flood event managers. The use of Quantitative Precipitation Estimates and Forecasts (QPE/QPF) especially based on radar measurements could particularly be adequate to evaluate rainfall-induced risks. Although their characteristic time and space scales would make them suitable for flash flood modelling, the impact of their uncertainties remain uncertain and have to be evaluated. The Gard region (France) has been chosen as case study. This area is frequently affected by severe flash floods and different kinds of rainfall observations are available in real time: radar rainfall estimates and nowcasts from METEO FRANCE and the CALAMAR system from SPC (state authority in charge of flood forecasting). An application devoted to the road network, has also been recently developed for this region. It combines distributed hydro-meteorological very short range forecasts and vulnerability analysis to provide warnings of road submersions. The first results demonstrate that it is technically possible to provide distributed short-term forecasts for a large number of sites. The study also demonstrates that a reliable estimation of the spatial distribution of rainfall is essential. For this reason, the road submersion warning system can be used to evaluate the quality of rainfall estimates and nowcasts. The warning system has been tested on the specific storm of the 29-30 September 2007. During this event, more than 300mm dropped on the South part of the Gard and many roads were submerged. Each of the mentioned rainfall datasets (i.e. estimates and nowcasts) was available in real time. They have been used to forecast the exact location of road submersions and the results have been compared to the effective road submersions actually occurred during the event as listed by the emergency services. The results confirm that the road submersion warning system represents a promising tool for anticipating and quantifying the consequences of storm events at ground. It rates the submersion risk with an acceptable level of accuracy and a reasonable false alarm ratio. It demonstrates also the quality of high spatial and temporal resolution radar rainfall data in real time, and the possibility to use them despite their uncertainties. However because of the quality of rainfall nowcasts falls drastically with time, it is not often sufficient to provide valuable information for lead times exceeding one hour.

WMO Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS): Research Implementation Status

NASA Astrophysics Data System (ADS)

Nickovic, Slobodan; Barrie, Leonard

2010-05-01

Strong winds cause lifting of large amounts of sand and dust from bare, dry soils into the atmosphere. For countries in and downwind of arid regions, airborne sand and dust presents serious risks to the environment, property and human health. Impacts on health include respiratory and cardio-vascular problems, eye infections and in some regions, diseases such as meningitis and valley fever. Dust can efficiently carry irritating spores, bacteria, viruses and persistent organic pollutants. It can also efficiently transport nutrients to parts of the world oceans and affect marine biomass production. Other impacts include negative effects on the ground transport, aviation, agriculture and visibility. The Inter-governmental Panel on Climate Change (IPCC) recognizes dust as a major component of the atmospheric aerosol that is an essential climate variable. Dust aerosol has important effects on weather through feedback on atmospheric dynamics, clouds and precipitation formation. Approximately 15 centres around the world provide sand and dust research operational forecasts. Many are operated by national meteorological services of the World Meteorological Organization (WMO). Sand and dust storm models can substantially reduce risk by providing dust concentration predictions for several days in advance. Numerical weather prediction systems that drive these models use complex parameterizations and assimilation of satellite, and surface-based observations to predict winds, clouds, precipitation and dust mobilization, transport, and removal from the atmosphere. Sand and dust forecast products contribute to the mitigation and reduction of risk through research based advances in understanding and forecasting products. Observations of sand and dust are made by many agencies and some of them are being coordinated globally through the WMO Global Atmosphere Watch (GAW) programme. In 2006, WMO and partners initiated the implementation of the Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) in order to improve the capabilities of countries affected by dust to reduce risks associated with airborne sand and dust. This project is in response to the desire of more than 40 WMO member countries to improve capabilities for more reliable sand and dust storm forecasts. The project has strong crosscutting features: it relies on real-time delivery of products; it integrates research communities (modelling, observation groups, and effects) and communities of practice (e.g. medical, aeronautical, agricultural users). There are two already established SDS-WAS nodes (Asian and North-Africa-Europe-Middle East) that coordinate implementation of the project objectives at regional levels. This presentation will review current status and future steps in the project implementation.

Adjoint Sensitivity Analyses Of Sand And Dust Storms In East Asia

NASA Astrophysics Data System (ADS)

Kay, J.; Kim, H.

2008-12-01

Sand and Dust Storm (SDS) in East Asia, so called Asian dust, is a seasonal meteorological phenomenon. Mostly in spring, dust particles blown into atmosphere in the arid area over northern China desert and Manchuria are transported to East Asia by prevailing flows. Three SDS events in East Asia from 2005 to 2008 are chosen to investigate how sensitive the SDS forecasts to the initial condition uncertainties and thence to suggest the sensitive regions for adaptive observations of the SDS events. Adaptive observations are additional observations in sensitive regions where the observations may have the most impact on the forecast by decreasing the forecast error. Three SDS events are chosen to represent different transport passes from the dust source regions to the Korean peninsula. To investigate the sensitivities to the initial condition, adjoint sensitivities that calculate gradient of the forecast aspect (i.e., response function) with respect to the initial condition are used. The forecast aspects relevant to the SDS transport are forecast error of the surface pressure, surface pressure perturbation, and steering vector of winds in the lower troposphere. Because the surface low pressure system usually plays an important role for SDS transport, the forecast error of the surface pressure and the surface pressure perturbation are chosen as the response function of the adjoint calculation. Another response function relevant to SDS transport is the steering flow over the downstream region (i.e., Korean peninsula) because direction and intensity of the prevailing winds usually determine the intensity and occurrence of the SDS events at the destination. The results show that the sensitive regions for the forecast error of the surface pressure and surface pressure perturbation are initially located in the vicinity of the trough and then propagate eastward as the low system moves eastward. The vertical structures of the adjoint sensitivities are upshear tilted structures, which are typical structures of extratropical cyclones. The adjoint sensitivities for lower tropospheric steering flow are also located near the trough, which confirms that the accurate forecast on the location and movement of the trough is essential to have better forecasts of Asian dust events. More comprehensive results and discussions of the adjoint sensitivity analyses for Asian dust events will be presented in the meeting.

Cyclic growth and dissolution of camphor crystals in quinary, ternary, and binary solutions: A study on crystal behavior in storm glass

NASA Astrophysics Data System (ADS)

Mitsuya, Takuro; Takahashi, Kyohei; Nagashima, Kazushige

2014-09-01

"Storm glass" is a hermetically sealed glass tube containing a solution of camphor. In 19th-century England, the pattern and quantity of the crystals were observed and interpreted as a weather forecasting tool. In the present study, the appearance of camphor crystals under cyclic temperature change was studied in three sample solutions, the storm glass solution (quinary system), camphor-ethanol-water (ternary system), and camphor-ethanol (binary system), to elucidate the effect of components in the storm glass on the appearance of camphor crystals. Equilibrium temperatures of camphor crystals as a function of the camphor concentration were also obtained to estimate the quantity of camphor crystals precipitated in the solutions. During the temperature cycles, the crystal height increased and decreased. The ranges (local maxima and minima) of crystal heights gradually decreased to approximately a constant range. Not only the crystal height but also the amplitude of the height variation in the quinary and ternary systems were much larger than those in the binary system, although the estimated weights of crystals precipitated in the quinary and ternary systems were smaller than that in the binary system. This fact resulted from the formation of dendrites in the quinary and ternary systems, which caused high porosity of sedimented crystals.

Validation of the CME Geomagnetic Forecast Alerts Under the COMESEP Alert System

NASA Astrophysics Data System (ADS)

Dumbović, Mateja; Srivastava, Nandita; Rao, Yamini K.; Vršnak, Bojan; Devos, Andy; Rodriguez, Luciano

2017-08-01

Under the European Union 7th Framework Programme (EU FP7) project Coronal Mass Ejections and Solar Energetic Particles (COMESEP, http://comesep.aeronomy.be), an automated space weather alert system has been developed to forecast solar energetic particles (SEP) and coronal mass ejection (CME) risk levels at Earth. The COMESEP alert system uses the automated detection tool called Computer Aided CME Tracking (CACTus) to detect potentially threatening CMEs, a drag-based model (DBM) to predict their arrival, and a CME geoeffectiveness tool (CGFT) to predict their geomagnetic impact. Whenever CACTus detects a halo or partial halo CME and issues an alert, the DBM calculates its arrival time at Earth and the CGFT calculates its geomagnetic risk level. The geomagnetic risk level is calculated based on an estimation of the CME arrival probability and its likely geoeffectiveness, as well as an estimate of the geomagnetic storm duration. We present the evaluation of the CME risk level forecast with the COMESEP alert system based on a study of geoeffective CMEs observed during 2014. The validation of the forecast tool is made by comparing the forecasts with observations. In addition, we test the success rate of the automatic forecasts (without human intervention) against the forecasts with human intervention using advanced versions of the DBM and CGFT (independent tools available at the Hvar Observatory website, http://oh.geof.unizg.hr). The results indicate that the success rate of the forecast in its current form is unacceptably low for a realistic operation system. Human intervention improves the forecast, but the false-alarm rate remains unacceptably high. We discuss these results and their implications for possible improvement of the COMESEP alert system.

Developing an early warning system for storm surge inundation in the Philippines

NASA Astrophysics Data System (ADS)

Tablazon, Judd; Mahar Francisco Lagmay, Alfredo; Francia Mungcal, Ma. Theresa; Gonzalo, Lia Anne; Dasallas, Lea; Briones, Jo Brianne Louise; Santiago, Joy; Suarez, John Kenneth; Lapidez, John Phillip; Caro, Carl Vincent; Ladiero, Christine; Malano, Vicente

2014-05-01

A storm surge is the sudden rise of sea water generated by an approaching storm, over and above the astronomical tides. This event imposes a major threat in the Philippine coastal areas, as manifested by Typhoon Haiyan on 08 November 2013 where more than 6,000 people lost their lives. It has become evident that the need to develop an early warning system for storm surges is of utmost importance. To provide forecasts of the possible storm surge heights of an approaching typhoon, the Nationwide Operational Assessment of Hazards under the Department of Science and Technology (DOST-Project NOAH) simulated historical tropical cyclones that entered the Philippine Area of Responsibility. Bathymetric data, storm track, central atmospheric pressure, and maximum wind speed were used as parameters for the Japan Meteorological Agency (JMA) Storm Surge Model. The researchers calculated the frequency distribution of maximum storm surge heights of all typhoons under a specific Public Storm Warning Signal (PSWS) that passed through a particular coastal area. This determines the storm surge height corresponding to a given probability of occurrence. The storm surge heights from the model were added to the maximum astronomical tide data from WXTide software. The team then created maps of probable area inundation and flood levels of storm surges along coastal areas for a specific PSWS using the results of the frequency distribution. These maps were developed from the time series data of the storm tide at 10-minute intervals of all observation points in the Philippines. This information will be beneficial in developing early warnings systems, static maps, disaster mitigation and preparedness plans, vulnerability assessments, risk-sensitive land use plans, shoreline defense efforts, and coastal protection measures. Moreover, these will support the local government units' mandate to raise public awareness, disseminate information about storm surge hazards, and implement appropriate counter-measures for a given PSWS.

Developing an early warning system for storm surge inundation in the Philippines

NASA Astrophysics Data System (ADS)

Tablazon, J.; Caro, C. V.; Lagmay, A. M. F.; Briones, J. B. L.; Dasallas, L.; Lapidez, J. P.; Santiago, J.; Suarez, J. K.; Ladiero, C.; Gonzalo, L. A.; Mungcal, M. T. F.; Malano, V.

2014-10-01

A storm surge is the sudden rise of sea water generated by an approaching storm, over and above the astronomical tides. This event imposes a major threat in the Philippine coastal areas, as manifested by Typhoon Haiyan on 8 November 2013 where more than 6000 people lost their lives. It has become evident that the need to develop an early warning system for storm surges is of utmost importance. To provide forecasts of the possible storm surge heights of an approaching typhoon, the Nationwide Operational Assessment of Hazards under the Department of Science and Technology (DOST-Project NOAH) simulated historical tropical cyclones that entered the Philippine Area of Responsibility. Bathymetric data, storm track, central atmospheric pressure, and maximum wind speed were used as parameters for the Japan Meteorological Agency Storm Surge Model. The researchers calculated the frequency distribution of maximum storm surge heights of all typhoons under a specific Public Storm Warning Signal (PSWS) that passed through a particular coastal area. This determines the storm surge height corresponding to a given probability of occurrence. The storm surge heights from the model were added to the maximum astronomical tide data from WXTide software. The team then created maps of probable area inundation and flood levels of storm surges along coastal areas for a specific PSWS using the results of the frequency distribution. These maps were developed from the time series data of the storm tide at 10 min intervals of all observation points in the Philippines. This information will be beneficial in developing early warnings systems, static maps, disaster mitigation and preparedness plans, vulnerability assessments, risk-sensitive land use plans, shoreline defense efforts, and coastal protection measures. Moreover, these will support the local government units' mandate to raise public awareness, disseminate information about storm surge hazards, and implement appropriate counter-measures for a given PSWS.

Sensitivity of sea-level forecasting to the horizontal resolution and sea surface forcing for different configurations of an oceanographic model of the Adriatic Sea

NASA Astrophysics Data System (ADS)

Bressan, Lidia; Valentini, Andrea; Paccagnella, Tiziana; Montani, Andrea; Marsigli, Chiara; Stefania Tesini, Maria

2017-04-01

At the Hydro-meteo-climate service of the Regional environmental agency of Emilia-Romagna, Italy (Arpae-SIMC), the oceanographic numerical model AdriaROMS is used in the operational forecasting suite to compute sea level, temperature, salinity and 3-D current fields of the Adriatic Sea (northern Mediterranean Sea). In order to evaluate the performance of the sea-level forecast and to study different configurations of the ROMS model, two marine storms occurred on the Emilia Romagna coast during the winter 2015-2016 are investigated. The main focus of this study is to analyse the sensitivity of the model to the horizontal resolution and to the meteorological forcing. To this end, the model is run with two different configurations and with two horizontal grids at 1 and 2 km resolution. To study the influence of the meteorological forcing, the two storms have been reproduced by running ROMS in ensemble mode, forced by the 16-members of the meteorological ensemble COSMO-LEPS system. Possible optimizations of the model set-up are deduced by the comparison of the different run outputs.

Evaluation of Probable Maximum Precipitation and Flood under Climate Change in the 21st Century

NASA Astrophysics Data System (ADS)

Gangrade, S.; Kao, S. C.; Rastogi, D.; Ashfaq, M.; Naz, B. S.; Kabela, E.; Anantharaj, V. G.; Singh, N.; Preston, B. L.; Mei, R.

2016-12-01

Critical infrastructures are potentially vulnerable to extreme hydro-climatic events. Under a warming environment, the magnitude and frequency of extreme precipitation and flood are likely to increase enhancing the needs to more accurately quantify the risks due to climate change. In this study, we utilized an integrated modeling framework that includes the Weather Research Forecasting (WRF) model and a high resolution distributed hydrology soil vegetation model (DHSVM) to simulate probable maximum precipitation (PMP) and flood (PMF) events over Alabama-Coosa-Tallapoosa River Basin. A total of 120 storms were selected to simulate moisture maximized PMP under different meteorological forcings, including historical storms driven by Climate Forecast System Reanalysis (CFSR) and baseline (1981-2010), near term future (2021-2050) and long term future (2071-2100) storms driven by Community Climate System Model version 4 (CCSM4) under Representative Concentrations Pathway 8.5 emission scenario. We also analyzed the sensitivity of PMF to various antecedent hydrologic conditions such as initial soil moisture conditions and tested different compulsive approaches. Overall, a statistical significant increase is projected for future PMP and PMF, mainly attributed to the increase of background air temperature. The ensemble of simulated PMP and PMF along with their sensitivity allows us to better quantify the potential risks associated with hydro-climatic extreme events on critical energy-water infrastructures such as major hydropower dams and nuclear power plants.

Real-time new satellite product demonstration from microwave sensors and GOES-16 at NRL TC web

NASA Astrophysics Data System (ADS)

Cossuth, J.; Richardson, K.; Surratt, M. L.; Bankert, R.

2017-12-01

The Naval Research Laboratory (NRL) Tropical Cyclone (TC) satellite webpage (https://www.nrlmry.navy.mil/TC.html) provides demonstration analyses of storm imagery to benefit operational TC forecast centers around the world. With the availability of new spectral information provided by GOES-16 satellite data and recent research into improved visualization methods of microwave data, experimental imagery was operationally tested to visualize the structural changes of TCs during the 2017 hurricane season. This presentation provides an introduction into these innovative satellite analysis methods, NRL's next generation satellite analysis system (the Geolocated Information Processing System, GeoIPSTM), and demonstration the added value of additional spectral frequencies when monitoring storms in near-realtime.

Airborne Dust Models in Valley Fever Research

NASA Astrophysics Data System (ADS)

Sprigg, W. A.; Galgiani, J. N.; Vujadinovic, M.; Pejanovic, G.; Vukovic, A. J.; Prasad, A. K.; Djurdjevic, V.; Nickovic, S.

2011-12-01

Dust storms (haboobs) struck Phoenix, Arizona, in 2011 on July 5th and again on July 18th. One potential consequence: an estimated 3,600 new cases of Valley Fever in Maricopa County from the first storm alone. The fungi, Coccidioides immitis, the cause of the respiratory infection, Valley Fever, lives in the dry desert soils of the American southwest and southward through Mexico, Central America and South America. The fungi become part of the dust storm and, a few weeks after inhalation, symptoms of Valley Fever may appear, including pneumonia-like illness, rashes, and severe fatigue. Some fatalities occur. Our airborne dust forecast system predicted the timing and extent of the storm, as it has done with other, often different, dust events. Atmosphere/land surface models can be part of public health services to reduce risk of Valley Fever and exacerbation of other respiratory and cardiovascular illness.

Structure of the Highly Sheared Tropical Storm Chantal During CAMEX -4

NASA Technical Reports Server (NTRS)

Heymsfield, Gerald M.; Halverson, J.; Black, M.; Marks, F.; Zipser, E.; Tian, L.; Belcher, L.; Bui, P.; Im, E.; Starr, David OC. (Technical Monitor)

2002-01-01

On 20 August 2001 during the Convection and Moisture Experiment 4 (CAMEX-4) and NOAA Hurricane Field Program (HFP2001), the NASA high-altitude ER-2 and medium-altitude DC-8, and lower-altitude NOAA P3 aircraft conducted a coordinated Quantitative Precipitation Estimation (QPE) mission focused on convection in Tropical Storm Chantal. This storm first became a depression on 14 August, a tropical storm on 17 August, and it maintained maximum winds of about 65-70 mph during 19-20 August with minimum pressures ranging from 1008 mb on 19 August to 1001 mb late on 20 August. The storm was westward moving and was forecasted to intensify and landfall near the Yucatan-Belize border late on 20 August. Chanter failed to intensify and instead exhibited a highly sheared structure with an open low-level circulation and intense convection well to the northeast of this circulation center. The NASA ER-2 and DC-8 aircraft were closely coordinated with the NOAA P3 (NOAA-42). The NASA aircraft collected remote sensing and in situ data sets, while the P3 collected lower level in situ and radar data; both the DC-8 and P3 released 7 and 24 dropsondes, respectively. These aircraft measurements provided a unique opportunity to examine the structure of a sheared system and why it did not develop as forecasted a few days earlier. This paper will describe a preliminary study of the precipitation and wind structure provided by the NASA aircraft within the context of the NOAA P3 measurements.

Communicating Uncertainties in Weather and Climate Information: Results of a National Academies Workshop

NASA Astrophysics Data System (ADS)

Friday, E.; Barron, E. J.; Elfring, C.; Geller, L.

2002-12-01

When a major East Coast snowstorm was forecast during the winter of 2001, people began preparing - both the public and the decision-makers responsible for public services. There was an air of urgency, heightened because just the previous year the region had been hit hard by a storm of unpredicted strength. But this time, the storm never materialized and people were left wondering what went "wrong" with the forecast. Did something go wrong or did forecasters just fail to communicate their information in an effective way? Did they convey a sense of the likelihood of the event and keep people up to date as information changed? In the summer of 2001, the National Academies' Board on Atmospheric Sciences and Climate hosted a workshop designed to explore the communication of uncertainty in weather and climate information. Workshop participants examined five case studies that were chosen to illustrate a range of forecast timescales and certainty levels. The cases were: Red River Flood, Grand Forks, April 1997; East Coast Winter Storm, March 2001; Oklahoma-Kansas Tornado Outbreak, May 3, 1999; El Nino 1997-1998, and Climate Change Science, a report issued in 2001. In each of these cases, participants examined who said what, when, to whom, how, and with what effect. The last two cases specifically address climate-related topics. This paper summarizes the final workshop report (Communicating Uncertainties in Weather and Climate Information: Summary of a Workshop, NRC 2002), including an overview of the five cases and lessons learned about communicating uncertainties in weather and climate forecasts. Among other findings, the report stresses that communication and appropriate dissemination of information, including information about uncertainty in the forecasts and the forecaster's confidence in the product, should be an integral, ongoing part of the forecasting process, not an afterthought. Explaining uncertainty should be an integral part of what weather and climate forecasters do and is essential to delivering accurate and useful information.

ENSO-based probabilistic forecasts of March-May U.S. tornado and hail activity

NASA Astrophysics Data System (ADS)

Lepore, Chiara; Tippett, Michael K.; Allen, John T.

2017-09-01

Extended logistic regression is used to predict March-May severe convective storm (SCS) activity based on the preceding December-February (DJF) El Niño-Southern Oscillation (ENSO) state. The spatially resolved probabilistic forecasts are verified against U.S. tornado counts, hail events, and two environmental indices for severe convection. The cross-validated skill is positive for roughly a quarter of the U.S. Overall, indices are predicted with more skill than are storm reports, and hail events are predicted with more skill than tornado counts. Skill is higher in the cool phase of ENSO (La Niña like) when overall SCS activity is higher. SCS forecasts based on the predicted DJF ENSO state from coupled dynamical models initialized in October of the previous year extend the lead time with only a modest reduction in skill compared to forecasts based on the observed DJF ENSO state.

STEREO as a "Planetary Hazards" Mission

NASA Technical Reports Server (NTRS)

Guhathakurta, M.; Thompson, B. J.

2014-01-01

NASA's twin STEREO probes, launched in 2006, have advanced the art and science of space weather forecasting more than any other spacecraft or solar observatory. By surrounding the Sun, they provide previously-impossible early warnings of threats approaching Earth as they develop on the solar far side. They have also revealed the 3D shape and inner structure of CMEs-massive solar storms that can trigger geomagnetic storms when they collide with Earth. This improves the ability of forecasters to anticipate the timing and severity of such events. Moreover, the unique capability of STEREO to track CMEs in three dimensions allows forecasters to make predictions for other planets, giving rise to the possibility of interplanetary space weather forecasting too. STEREO is one of those rare missions for which "planetary hazards" refers to more than one world. The STEREO probes also hold promise for the study of comets and potentially hazardous asteroids.

The North Alabama Lightning Mapping Array: Recent Results and Future Prospects

NASA Technical Reports Server (NTRS)

Goodman, S. J.; Blakeslee, R.; Christian, H.; Boccippio, D.; Koshak, W.; Bailey, J.; Hall, J.; Bateman, M.; McCaul, E.; Buechler, D.

2002-01-01

The North Alabama Lightning Mapping Array became operational in November 2001 as a principal component of a severe weather test bed to infuse new science and technologies into the short-term forecasting of severe and hazardous weather and the warning decision-making process. The LMA project is a collaboration among NASA scientists, National Weather Service (NWS) weather forecast offices (WFOs), emergency managers, and other partners. The time rate-of-change of storm characteristics and life-cycle trending are accomplished in real-time through the second generation Lightning Imaging Sensor Data Applications Display (LISDAD II) system, initially developed in T997 through a collaboration among NASA/MSFC, MIT/Lincoln Lab and the Melbourne, FL WFO. LISDAD II is now a distributed decision support system with a JAVA-based display application that allows anyone, anywhere to track individual storm histories within the Tennessee Valley region of the southeastern U.S. Since the inauguration of the LMA there has been an abundance of severe weather. During 23-24 November 2001, a major tornado outbreak was monitored by LMA in its first data acquisition effort (36 tornadoes in Alabama). Since that time the LMA has collected a vast amount of data on hailstorms and damaging wind events, non-tornadic supercells, and ordinary non-severe thunderstorms. In this paper we provide an overview of LMA observations and discuss future prospects for improving the short-term forecasting of convective weather.

L-band Microwave Remote Sensing and Land Data Assimilation Improve the Representation of Prestorm Soil Moisture Conditions for Hydrologic Forecasting

NASA Technical Reports Server (NTRS)

Crow, W. T.; Chen, F.; Reichle, R. H.; Liu, Q.

2017-01-01

Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total stream flow divided by total rainfall accumulation in depth units) and pre-storm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L-band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting stream flow response to future rainfall events.

Improved Satellite Techniques for Monitoring and Forecasting the Transition of Hurricanes to Extratropical Storms

NASA Technical Reports Server (NTRS)

Folmer, Michael; Halverson, Jeffrey; Berndt, Emily; Dunion, Jason; Goodman, Steve; Goldberg, Mitch

2014-01-01

The Geostationary Operational Environmental Satellites R-Series (GOES-R) and Joint Polar Satellite System (JPSS) Satellite Proving Grounds have introduced multiple proxy and operational products into operations over the last few years. Some of these products have proven to be useful in current operations at various National Weather Service (NWS) offices and national centers as a first look at future satellite capabilities. Forecasters at the National Hurricane Center (NHC), Ocean Prediction Center (OPC), NESDIS Satellite Analysis Branch (SAB) and the NASA Hurricane and Severe Storms Sentinel (HS3) field campaign have had access to a few of these products to assist in monitoring extratropical transitions of hurricanes. The red, green, blue (RGB) Air Mass product provides forecasters with an enhanced view of various air masses in one complete image to help differentiate between possible stratospheric/tropospheric interactions, moist tropical air masses, and cool, continental/maritime air masses. As a compliment to this product, a new Atmospheric Infrared Sounder (AIRS) and Cross-track Infrared Sounder (CrIS) Ozone product was introduced in the past year to assist in diagnosing the dry air intrusions seen in the RGB Air Mass product. Finally, a lightning density product was introduced to forecasters as a precursor to the new Geostationary Lightning Mapper (GLM) that will be housed on GOES-R, to monitor the most active regions of convection, which might indicate a disruption in the tropical environment and even signal the onset of extratropical transition. This presentation will focus on a few case studies that exhibit extratropical transition and point out the usefulness of these new satellite techniques in aiding forecasters forecast these challenging events.

Physics-based Space Weather Forecasting in the Project for Solar-Terrestrial Environment Prediction (PSTEP) in Japan

NASA Astrophysics Data System (ADS)

Kusano, K.

2016-12-01

Project for Solar-Terrestrial Environment Prediction (PSTEP) is a Japanese nation-wide research collaboration, which was recently launched. PSTEP aims to develop a synergistic interaction between predictive and scientific studies of the solar-terrestrial environment and to establish the basis for next-generation space weather forecasting using the state-of-the-art observation systems and the physics-based models. For this project, we coordinate the four research groups, which develop (1) the integration of space weather forecast system, (2) the physics-based solar storm prediction, (3) the predictive models of magnetosphere and ionosphere dynamics, and (4) the model of solar cycle activity and its impact on climate, respectively. In this project, we will build the coordinated physics-based model to answer the fundamental questions concerning the onset of solar eruptions and the mechanism for radiation belt dynamics in the Earth's magnetosphere. In this paper, we will show the strategy of PSTEP, and discuss about the role and prospect of the physics-based space weather forecasting system being developed by PSTEP.

Lognormal Assimilation of Water Vapor in a WRF-GSI Cycled System

NASA Astrophysics Data System (ADS)

Fletcher, S. J.; Kliewer, A.; Jones, A. S.; Forsythe, J. M.

2015-12-01

Recent publications have shown the viability of both detecting a lognormally-distributed signal for water vapor mixing ratio and the improved quality of satellite retrievals in a 1DVAR mixed lognormal-Gaussian assimilation scheme over a Gaussian-only system. This mixed scheme is incorporated into the Gridpoint Statistical Interpolation (GSI) assimilation scheme with the goal of improving forecasts from the Weather Research and Forecasting (WRF) Model in a cycled system. Results are presented of the impact of treating water vapor as a lognormal random variable. Included in the analysis are: 1) the evolution of Tropical Storm Chris from 2006, and 2) an analysis of a "Pineapple Express" water vapor event from 2005 where a lognormal signal has been previously detected.

Forecasts of geomagnetic activities and HF radio propagation conditions made at Hiraiso/Japan

NASA Technical Reports Server (NTRS)

Marubashi, K.; Miyamoto, Y.; Kidokoro, T.; Ishii, T.

1979-01-01

The Hiraiso Branch of RRL prediction techniques are summarized separately for the 27 day recurrent storm and the flare-associated storm. The storm predictions are compared with the actual geomagnetic activities in two ways. The first one is the comparison on a day to day basis. In the second comparison, the accuracy of the storm predictions during 1965-1976 are evaluated. In addition to the storm prediction, short-term predictions of HF radio propagation conditions are conducted at Hiraiso. The HF propagation predictions are briefly described as an example of the applications of the magnetic storm prediction.

AFFECTS - Advanced Forecast For Ensuring Communications Through Space

NASA Astrophysics Data System (ADS)

Bothmer, Volker

2013-04-01

Through the AFFECTS project funded by the European Union's 7th Framework Programme, European and US scientists develop an advanced proto-type space weather warning system to safeguard the operation of telecommunication and navigation systems on Earth to the threat of solar storms. The project is led by the University of Göttingen's Institute for Astrophysics and comprises worldwide leading research and academic institutions and industrial enterprises from Germany, Belgium, Ukraine, Norway and the United States. The key objectives of the AFFECTS project are: State-of-the-art analysis and modelling of the Sun-Earth chain of effects on the Earth's ionosphere and their subsequent impacts on communication systems based on multipoint space observations and complementary ground-based data. Development of a prototype space weather early warning system and reliable space weather forecasts, with specific emphasis on ionospheric applications. Dissemination of new space weather products and services to end users, the scientific community and general public. The presentation summarizes the project highlights, with special emphasis on the developed space weather forecast tools.

NOAA's weather forecasts go hyper-local with next-generation weather

Science.gov Websites

model NOAA HOME WEATHER OCEANS FISHERIES CHARTING SATELLITES CLIMATE RESEARCH COASTS CAREERS with next-generation weather model New model will help forecasters predict a storm's path, timing and intensity better than ever September 30, 2014 This is a comparison of two weather forecast models looking

On the log-normality of historical magnetic-storm intensity statistics: implications for extreme-event probabilities

USGS Publications Warehouse

Love, Jeffrey J.; Rigler, E. Joshua; Pulkkinen, Antti; Riley, Pete

2015-01-01

An examination is made of the hypothesis that the statistics of magnetic-storm-maximum intensities are the realization of a log-normal stochastic process. Weighted least-squares and maximum-likelihood methods are used to fit log-normal functions to −Dst storm-time maxima for years 1957-2012; bootstrap analysis is used to established confidence limits on forecasts. Both methods provide fits that are reasonably consistent with the data; both methods also provide fits that are superior to those that can be made with a power-law function. In general, the maximum-likelihood method provides forecasts having tighter confidence intervals than those provided by weighted least-squares. From extrapolation of maximum-likelihood fits: a magnetic storm with intensity exceeding that of the 1859 Carrington event, −Dst≥850 nT, occurs about 1.13 times per century and a wide 95% confidence interval of [0.42,2.41] times per century; a 100-yr magnetic storm is identified as having a −Dst≥880 nT (greater than Carrington) but a wide 95% confidence interval of [490,1187] nT.

Impact of using scatterometer and altimeter data on storm surge forecasting

NASA Astrophysics Data System (ADS)

Bajo, Marco; De Biasio, Francesco; Umgiesser, Georg; Vignudelli, Stefano; Zecchetto, Stefano

2017-05-01

Satellite data are rarely used in storm surge models because of the lack of established methodologies. Nevertheless, they can provide useful information on surface wind and sea level, which can potentially improve the forecast. In this paper satellite wind data are used to correct the bias of wind originating from a global atmospheric model, while satellite sea level data are used to improve the initial conditions of the model simulations. In a first step, the capability of global winds (biased and unbiased) to adequately force a storm surge model are assessed against that of a high resolution local wind. Then, the added value of direct assimilation of satellite altimeter data in the storm surge model is tested. Eleven storm surge events, recorded in Venice from 2008 to 2012, are simulated using different configurations of wind forcing and altimeter data assimilation. Focusing on the maximum surge peak, results show that the relative error, averaged over the eleven cases considered, decreases from 13% to 7%, using both the unbiased wind and assimilating the altimeter data, while, if the high resolution local wind is used to force the hydrodynamic model, the altimeter data assimilation reduces the error from 9% to 6%. Yet, the overall capabilities in reproducing the surge in the first day of forecast, measured by the correlation and by the rms error, improve only with the use of the unbiased global wind and not with the use of high resolution local wind and altimeter data assimilation.

Validation of the CME Geomagnetic forecast alerts under COMESEP alert system

NASA Astrophysics Data System (ADS)

Dumbovic, Mateja; Srivastava, Nandita; Khodia, Yamini; Vršnak, Bojan; Devos, Andy; Rodriguez, Luciano

2017-04-01

An automated space weather alert system has been developed under the EU FP7 project COMESEP (COronal Mass Ejections and Solar Energetic Particles: http://comesep.aeronomy.be) to forecast solar energetic particles (SEP) and coronal mass ejection (CME) risk levels at Earth. COMESEP alert system uses automated detection tool CACTus to detect potentially threatening CMEs, drag-based model (DBM) to predict their arrival and CME geo-effectiveness tool (CGFT) to predict their geomagnetic impact. Whenever CACTus detects a halo or partial halo CME and issues an alert, DBM calculates its arrival time at Earth and CGFT calculates its geomagnetic risk level. Geomagnetic risk level is calculated based on an estimation of the CME arrival probability and its likely geo-effectiveness, as well as an estimate of the geomagnetic-storm duration. We present the evaluation of the CME risk level forecast with COMESEP alert system based on a study of geo-effective CMEs observed during 2014. The validation of the forecast tool is done by comparing the forecasts with observations. In addition, we test the success rate of the automatic forecasts (without human intervention) against the forecasts with human intervention using advanced versions of DBM and CGFT (self standing tools available at Hvar Observatory website: http://oh.geof.unizg.hr). The results implicate that the success rate of the forecast is higher with human intervention and using more advanced tools. This work has received funding from the European Commission FP7 Project COMESEP (263252). We acknowledge the support of Croatian Science Foundation under the project 6212 „Solar and Stellar Variability".

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 COMESEP Alert System

NASA Astrophysics Data System (ADS)

Crosby, Norma; Veronig, Astrid; Rodriguez, Luciano; Vrsnak, Bojan; Vennerstrom, Susanne; Malandraki, Olga; Dalla, Silvia; Srivastava, Nandita; Hesse, Michael; Odstrcil, Dusan; Robbrecht, Eva

2014-05-01

Tools for forecasting geomagnetic storms and solar energetic particle (SEP) radiation storms have been developed under the three-year EU FP7 COMESEP (COronal Mass Ejections and Solar Energetic Particles) collaborative project. To enhance our understanding of the 3D kinematics and interplanetary propagation of coronal mass ejections (CMEs), the structure, propagation and evolution of CMEs have been investigated. In parallel, the sources and propagation of SEPs have been examined and modeled. During the third year of the COMESEP project the produced tools have been validated and implemented into an operational space weather alert system. The COMESEP Alert System provides notifications for the space weather community. To achieve this the system relies on both models and data, the latter including near real-time data as well as historical data. Geomagnetic and SEP radiation storm alerts are based on the COMESEP definition of risk. The COMESEP Alert System has recently been launched. Receiving COMESEP alerts are free of charge, but registration is required. For more information see the project website (http://www.comesep.eu/). This work has received funding from the European Commission FP7 Project COMESEP (263252).

GOES-S Mission Science Briefing

NASA Image and Video Library

2018-02-27

In the Kennedy Space Center's Press Site auditorium, members of the media participate in a mission briefing on National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. Briefing participants from left are: Steve Cole of NASA Communications; Dan Lindsey, GOES-R senior scientific advisor for NOAA; Louis Uccellini, director of the National Weather Service for NOAA; Jim Roberts, a scientist with the Earth System Research Laboratory's Office of Atmospheric Research for NOAA; Kristin Calhoun, a research scientist with NOAA's National Severe Storms Laboratory, and George Morrow, deputy director of NASA's Goddard Space Flight Center in Greenbelt, Maryland. GOES-S is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

UK Environmental Prediction - integration and evaluation at the convective scale

NASA Astrophysics Data System (ADS)

Lewis, Huw; Brunet, Gilbert; Harris, Chris; Best, Martin; Saulter, Andrew; Holt, Jason; Bricheno, Lucy; Brerton, Ashley; Reynard, Nick; Blyth, Eleanor; Martinez de la Torre, Alberto

2015-04-01

It has long been understood that accurate prediction and warning of the impacts of severe weather requires an integrated approach to forecasting. This was well demonstrated in the UK throughout winter 2013/14 when an exceptional run of severe winter storms, often with damaging high winds and intense rainfall led to significant damage from the large waves and storm surge along coastlines, and from saturated soils, high river flows and significant flooding inland. The substantial impacts on individuals, businesses and infrastructure indicate a pressing need to understand better the value that might be delivered through more integrated environmental prediction. To address this need, the Met Office, Centre for Ecology & Hydrology and National Oceanography Centre have begun to develop the foundations of a coupled high resolution probabilistic forecast system for the UK at km-scale. This links together existing model components of the atmosphere, coastal ocean, land surface and hydrology. Our initial focus on a 2-year Prototype project will demonstrate the UK coupled prediction concept in research mode, including an analysis of the winter 2013/14 storms and its impacts. By linking science development to operational collaborations such as the UK Natural Hazards Partnership, we can ensure that science priorities are rooted in user requirements. This presentation will provide an overview of UK environmental prediction activities and an update on progress during the first year of the Prototype project. We will present initial results from the coupled model development and discuss the challenges to realise the potential of integrated regional coupled forecasting for improving predictions and applications.

Flash floods in June and July 2009 in the Czech Republic

NASA Astrophysics Data System (ADS)

Sercl, Petr; Danhelka, Jan; Tyl, Radovan

2010-05-01

Several flash floods occurred in the territory of the Czech Republic during the last decade of June and beginning of July 2009. These events caused vast economic damage and unfortunately there were also 15 fatalities. The complete evaluation of flash floods from the point of view of its meteorological cause, hydrological development and impacts was done under the responsibility of Ministry of Environment of the Czech Republic. Czech Hydrometeorological Institute (CHMI) coordinated this project. The results of the project contain several concrete proposals to reduce the threat of flash floods in the Czech Republic. The proposals were focused on possible future improvements of CHMI forecasting service activities including all other parts of Flood prevention and protection system in the Czech Republic. The synoptic cause of floods was the extraordinary long (12 days is longest in more than 60 years history) presence of eastern cyclonic situation over the Central Europe bringing warm, moist and unstable air masses from Mediterranean and Black Sea area. Very intensive thunderstorms accompanied by torrential rain occurred almost daily. Storm cells were organized in train effect and crossed repeatedly the same places within several hours. The extremity of the flood events was also influenced by soil saturation due to daily occurrence of rainstorms. The peak flows exceeded significantly 100-year of recurrence time in many sites. The observed and mainly unobserved catchments were affected. The detailed fields of rainfall amounts were gained from the adjusted meteorological radar observation. All of the available rainfall measurements at the climatological and rain gage stations were used for the adjustment. Hydraulic and rainfall-runoff models were used to evaluate the hydrological response. It was proved again, that the outputs from currently used meteorological forecasting models are not sufficient for a reliable local forecast of the strong convective storms and their possible consequences - flash floods. Within the frame of the research project SP/1c4/16/07 "Implementation of new techniques for stream flow forecasting tools" (project period 2007-2011, funded by Ministry of Environment) a forecasting system for the estimation of runoff response to torrential rainfall has been developed. CN value automatic update based on antecedent precipitation is used to estimate possible runoff from storm. Ten minutes radar rainfall estimates and COTREC based nowcasting serve as meteorological input. Results of 2009 events hindcast are presented. It proved the underestimation of rainfall by raw radar data and thus the need for real time adjustment of radar estimates based on rain gauge data. The main output from presented forecasting system is an estimation of flash flood risk. Risk estimation is based on exceeding 3 defined thresholds defined as ratios between the estimated peak flow and theoretical 100-year flood on particular basin. The procedures mentioned above were being developed during the period 2008-2009. Intensive testing is expected by CHMI forecasting offices during 2010-2011.

The joint return period analysis of natural disasters based on monitoring and statistical modeling of multidimensional hazard factors.

PubMed

Liu, Xueqin; Li, Ning; Yuan, Shuai; Xu, Ning; Shi, Wenqin; Chen, Weibin

2015-12-15

As a random event, a natural disaster has the complex occurrence mechanism. The comprehensive analysis of multiple hazard factors is important in disaster risk assessment. In order to improve the accuracy of risk analysis and forecasting, the formation mechanism of a disaster should be considered in the analysis and calculation of multi-factors. Based on the consideration of the importance and deficiencies of multivariate analysis of dust storm disasters, 91 severe dust storm disasters in Inner Mongolia from 1990 to 2013 were selected as study cases in the paper. Main hazard factors from 500-hPa atmospheric circulation system, near-surface meteorological system, and underlying surface conditions were selected to simulate and calculate the multidimensional joint return periods. After comparing the simulation results with actual dust storm events in 54years, we found that the two-dimensional Frank Copula function showed the better fitting results at the lower tail of hazard factors and that three-dimensional Frank Copula function displayed the better fitting results at the middle and upper tails of hazard factors. However, for dust storm disasters with the short return period, three-dimensional joint return period simulation shows no obvious advantage. If the return period is longer than 10years, it shows significant advantages in extreme value fitting. Therefore, we suggest the multivariate analysis method may be adopted in forecasting and risk analysis of serious disasters with the longer return period, such as earthquake and tsunami. Furthermore, the exploration of this method laid the foundation for the prediction and warning of other nature disasters. Copyright © 2015 Elsevier B.V. All rights reserved.

The NASA CYGNSS Satellite Constellation for Tropical Cyclone Observations

NASA Astrophysics Data System (ADS)

Ruf, C. S.; Provost, D.; Rose, R.; Scherrer, J.; Atlas, R. M.; Chang, P.; Clarizia, M. P.; Garrison, J. L.; Gleason, S.; Katzberg, S. J.; Jelenak, Z.; Johnson, J. T.; Majumdar, S.; O'Brien, A.; Posselt, D. J.; Ridley, A. J.; Said, F.; Soisuvarn, S.; Zavorotny, V. U.

2016-12-01

The NASA Cyclone Global Navigation Satellite System (CYGNSS) is scheduled for launch in November 2016 to study the surface wind structure in and near the inner core of tropical cyclones. CYGNSS consists of a constellation of eight observatories carried into orbit on a single launch vehicle. Each observatory carries a 4-channel bistatic radar receiver tuned to receive GPS navigation signals scattered from the ocean surface. The eight satellites are spaced approximately twelve minutes apart in a common circular, low inclination orbit plane to provide frequent temporal sampling in the tropics. The 35deg orbit inclination results in coverage of the full globe between 38deg N and 38deg S latitude with a median(mean) revisit time of 3(7) hours The 32 CYGNSS radars operate in L-Band at a wavelength of 19 cm. This allows for adequate penetration to enable surface wind observations under all levels of precipitation, including those encountered in the inner core and eyewall of tropical cyclones. The combination of operation unaffected by heavy precipitation together with high temporal resolution throughout the life cycle of storms is expected to support significant improvements in the forecast skill of storm track and intensity, as well as better situational awareness of the extent and structure of storms in near real time. A summary of the properties of the CYGNSS science data products will be presented, together with an update on the results of ongoing Observation System Simulation Experiments performed by members of the CYGNSS science team over the past four years, in particular addressing the expected impact on storm track and intensity forecast skill. With launch scheduled for the month prior to AGU, the on orbit status of the constellation will also be presented.

Benefits of an Advanced Quantitative Precipitation Information System - San Francisco Bay Area Case Study

NASA Astrophysics Data System (ADS)

Cifelli, R.; Johnson, L. E.; White, A. B.

2014-12-01

Advancements in monitoring and prediction of precipitation and severe storms can provide significant benefits for water resource managers, allowing them to mitigate flood damage risks, capture additional water supplies and offset drought impacts, and enhance ecosystem services. A case study for the San Francisco Bay area provides the context for quantification of the benefits of an Advanced Quantitative Precipitation Information (AQPI) system. The AQPI builds off more than a decade of NOAA research and applications of advanced precipitation sensors, data assimilation, numerical models of storms and storm runoff, and systems integration for real-time operations. An AQPI would dovetail with the current National Weather Service forecast operations to provide higher resolution monitoring of rainfall events and longer lead time forecasts. A regional resource accounting approach has been developed to quantify the incremental benefits assignable to the AQPI system; these benefits total to $35 M/yr in the 9 county Bay region. Depending on the jurisdiction large benefits for flood damage avoidance may accrue for locations having dense development in flood plains. In other locations forecst=based reservoir operations can increase reservoir storage for water supplies. Ecosystem services benefits for fisheries may be obtained from increased reservoir storage and downstream releases. Benefits in the transporation sectors are associated with increased safety and avoided delays. Compared to AQPI system implementation and O&M costs over a 10 year operations period, a benefit - cost (B/C) ratio is computed which ranges between 2.8 to 4. It is important to acknowledge that many of the benefits are dependent on appropriate and adequate response by the hazards and water resources management agencies and citizens.

PREFACE: WMO/GEO Expert Meeting On An International Sand And Dust Storm Warning System

NASA Astrophysics Data System (ADS)

Pérez, C.; Baldasano, J. M.

2009-03-01

This volume of IOP Conference Series: Earth and Environmental Science presents a selection of papers that were given at the WMO/GEO Expert Meeting on an International Sand and Dust Storm Warning System hosted by the Barcelona Supercomputing Center - Centro Nacional de Supercomputación in Barcelona (Spain) on 7-9 November 2007 (http://www.bsc.es/wmo). A sand and dust storm (SDS) is a meteorological phenomenon common in arid and semi-arid regions and arises when a gust front passes or when the wind force exceeds the threshold value where loose sand and dust are removed from the dry surface. After aeolian uptake, SDS reduce visibility to a few meters in and near source regions, and dust plumes are transported over distances as long as thousands of kilometres. Aeolian dust is unique among aerosol phenomena: (1) with the possible exception of sea-salt aerosol, it is globally the most abundant of all aerosol species, (2) it appears as the dominating component of atmospheric aerosol over large areas of the Earth, (3) it represents a serious hazard for life, health, property, environment and economy (occasionally reaching the grade of disaster or catastrophic event) and (4) its influence, impacts, complex interactions and feedbacks within the Earth System span a wide range of spatial and temporal scales. From a political and societal point of view, the concern for SDS and the need for international cooperation were reflected after a survey conducted in 2005 by the World Meteorological Organization (WMO) in which more than forty WMO Member countries expressed their interest for creating or improving capacities for SDS warning advisory and assessment. In this context, recent major advances in research - including, for example, the development and implementation of advanced observing systems, the theoretical understanding of the mechanisms responsible for sand and dust storm generation and the development of global and regional dust models - represent the basis for developing applications focusing on societal benefit and risk reduction. However, at present there are interdisciplinary research challenges to overwhelm current uncertainties in order to reach full potential. Furthermore, the community of practice for SDS observations, forecasts and analyses is mainly scientifically based and rather disconnected from potential users. This requires the development of interfaces with operational communities at international and national levels, strongly focusing on the needs of people and factors at risk. The WMO has taken the lead with international partners to develop and implement a Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS). The history of the WMO SDS-WAS development is as follows. On 12-14 September 2004, an International Symposium on Sand and Dust Storms was held in Beijing at the China Meteorological Agency followed by a WMO Experts Workshop on Sand and Dust Storms. The recommendations of that workshop led to a proposal to create a WMO Sand and Dust Storm Project coordinated jointly with the Global Atmosphere Watch (GAW). This was approved by the steering body of the World Weather Research Programme (WWRP) in 2005. Responding to a WMO survey conducted in 2005, more than forty WMO Member countries expressed interest in participating in activities to improve capacities for more reliable sand and dust storm monitoring, forecasting and assessment. On 31 October to 1 November 2006 in Shanghai, the steering committee of the Sand and Dust Storm Project proposed the development and implementation of a Sand and Dust Storm Warning, Advisory and Assessment System (SDS-WAS). The WMO Secretariat in Geneva formed an ad-hoc Internal Group on SDS-WAS consisting of scientific officers representing WMO research, observations, operational prediction, service delivery and applications programmes such as aviation and agriculture. In May 2007, the 14th WMO Congress endorsed the launching of the SDS-WAS. It also welcomed the strong support of Spain to host a regional centre for the European/African/Middle East node of SDS-WAS and to play a lead role in implementation. In August 2007, the Korean Meteorological Administration hosted the 2nd International Workshop on Sand and Dust Storms highlighting Korean SDS-WAS activities as well as those of Asian regional partners. From 7-9 November 2007, Spain hosted the WMO/GEO Expert Meeting on SDS-WAS at the Barcelona Supercomputing Center. This consultation meeting brought 100 international experts together from research, observation, forecasting and user countries especially in Africa and the Middle East to discuss the way forward in SDS-WAS implementation. The general objective of the WMO/GEO Expert Meeting on an International Sand and Dust Storm Warning System was to discuss and recommend actions needed to develop a global routine SDS-WAS based on integrating numerical SDS prediction and observing systems, and on establishing effective cooperation between data producers and user communities in order to provide SDS-WAS products capable of contributing to the reduction of risks from SDS. The specific objectives were: to identify, present and suggest future real-time observations for forecast verification and dust surveillance: satellite, ground-based remote sensing (passive and active) and in-situ monitoring to present ongoing forecasting activities to discuss and identify user needs: health, air quality, air transport operations, ocean, and others to identify and discuss dust research issues relevant for operational forecast applications to present the concept of SDS-WAS and Regional Centers The meeting was organised around invited presentations and discussions on observations, modelling and users of the SDS-WAS. C Pérez and J M Baldasano Editors INTERNATIONAL STEERING COMMITTEE José María Baldasano (Chairman) - Barcelona Supercomputing Center, Spain Emilio Cuevas - Instituto Nacional de Meteorología, Spain Leonard A Barrie - World Meteorological Organisation, Switzerland Young J Kim - Gwangju Institute of Science and Technology, Korea Menas Kafatos - George Mason University, USA Xiaoye Zhang - Chinese Meteorology Administration, China Slobodan Nickovic - World Meteorological Organisation, Switzerland Carlos Pérez - Barcelona Supercomputing Center, Spain William A Sprigg - University of Arizona, USA Stéphane Alfaro - Université de Paris Val de Marne, France Ina Tegen - Leibniz Institute for Tropospheric Research, Germany Mohamed Mahmoud Eissa - Under-secretary of State for Researches, Egypt Sunling Gong - Environment Canada, Canada Emily Firth - GEO Secretariat, Switzerland LOCAL ORGANISING COMMITTEE José María Baldasano - Barcelona Supercomputing Center, Spain Carlos Pérez - Barcelona Supercomputing Center, Spain Renata Giménez - Barcelona Supercomputing Center, Spain Emilio Cuevas - Instituto Nacional de Meteorología, Spain Slobodan Nickovic - World Meteorological Organisation, Switzerland J M Marcos - Instituto Nacional de Meteorología, Spain Manuel Palomares - Instituto Nacional de Meteorología, Spain Xavier Querol - Consejo Superior de Investigaciones Científicas, Spain Conference photograph

Storm Prediction Center Day 3-8 Fire Weather Forecast Issued on May 27,

Science.gov Websites

National RADAR Product Archive NOAA Weather Radio Research Non-op. Products Forecast Tools Svr. Tstm information in MS-Word or PDF. Note: Through September 29, 2015 the SPC will issue Experimental Probabilistic

Space Weather, Geomagnetic Disturbances and Impact on the High-Voltage Transmission Systems

NASA Technical Reports Server (NTRS)

Pullkkinen, A.

2011-01-01

Geomagnetically induced currents (GIC) affecting the performance of high-voltage power transmission systems are one of the most significant hazards space weather poses on the operability of critical US infrastructure. The severity of the threat was emphasized, for example, in two recent reports: the National Research Council (NRC) report "Severe Space Weather Events--Understanding Societal and Economic Impacts: A Workshop Report" and the North American Electric Reliability Corporation (NERC) report "HighImpact, Low-Frequency Event Risk to the North American Bulk Power System." The NRC and NERC reports demonstrated the important national security dimension of space weather and GIC and called for comprehensive actions to forecast and mitigate the hazard. In this paper we will give a brief overview of space weather storms and accompanying geomagnetic storm events that lead to GIC. We will also review the fundamental principles of how GIC can impact the power transmission systems. Space weather has been a subject of great scientific advances that have changed the wonder of the past to a quantitative field of physics with true predictive power of today. NASA's Solar Shield system aimed at forecasting of GIC in the North American high-voltage power transmission system can be considered as one of the ultimate fruits of those advances. We will review the fundamental principles of the Solar Shield system and provide our view of the way forward in the science of GIC.

Growth of Errors and Uncertainties in Medium Range Ensemble Forecasts of U.S. East Coast Cool Season Extratropical Cyclones

NASA Astrophysics Data System (ADS)

Zheng, Minghua

Cool-season extratropical cyclones near the U.S. East Coast often have significant impacts on the safety, health, environment and economy of this most densely populated region. Hence it is of vital importance to forecast these high-impact winter storm events as accurately as possible by numerical weather prediction (NWP), including in the medium-range. Ensemble forecasts are appealing to operational forecasters when forecasting such events because they can provide an envelope of likely solutions to serve user communities. However, it is generally accepted that ensemble outputs are not used efficiently in NWS operations mainly due to the lack of simple and quantitative tools to communicate forecast uncertainties and ensemble verification to assess model errors and biases. Ensemble sensitivity analysis (ESA), which employs a linear correlation and regression between a chosen forecast metric and the forecast state vector, can be used to analyze the forecast uncertainty development for both short- and medium-range forecasts. The application of ESA to a high-impact winter storm in December 2010 demonstrated that the sensitivity signals based on different forecast metrics are robust. In particular, the ESA based on the leading two EOF PCs can separate sensitive regions associated with cyclone amplitude and intensity uncertainties, respectively. The sensitivity signals were verified using the leave-one-out cross validation (LOOCV) method based on a multi-model ensemble from CMC, ECMWF, and NCEP. The climatology of ensemble sensitivities for the leading two EOF PCs based on 3-day and 6-day forecasts of historical cyclone cases was presented. It was found that the EOF1 pattern often represents the intensity variations while the EOF2 pattern represents the track variations along west-southwest and east-northeast direction. For PC1, the upper-level trough associated with the East Coast cyclone and its downstream ridge are important to the forecast uncertainty in cyclone strength. The initial differences in forecasting the ridge along the west coast of North America impact the EOF1 pattern most. For PC2, it was shown that the shift of the tri-polar structure is most significantly related to the cyclone track forecasts. The EOF/fuzzy clustering tool was applied to diagnose the scenarios in operational ensemble forecast of East Coast winter storms. It was shown that the clustering method could efficiently separate the forecast scenarios associated with East Coast storms based on the 90-member multi-model ensemble. A scenario-based ensemble verification method has been proposed and applied it to examine the capability of different EPSs in capturing the analysis scenarios for historical East Coast cyclone cases at lead times of 1-9 days. The results suggest that the NCEP model performs better in short-range forecasts in capturing the analysis scenario although it is under-dispersed. The ECMWF ensemble shows the best performance in the medium range. The CMC model is found to show the smallest percentage of members in the analysis group and a relatively high missing rate, suggesting that it is less reliable regarding capturing the analysis scenario when compared with the other two EPSs. A combination of NCEP and CMC models has been found to reduce the missing rate and improve the error-spread skill in medium- to extended-range forecasts. Based on the orthogonal features of the EOF patterns, the model errors for 1-6-day forecasts have been decomposed for the leading two EOF patterns. The results for error decomposition show that the NCEP model tends to better represent both EOF1 and EOF2 patterns by showing less intensity and displacement errors during 1-3 days. The ECMWF model is found to have the smallest errors in both EOF1 and EOF2 patterns during 4-6 days. We have also found that East Coast cyclones in the ECMWF forecast tend to be towards the southwest of the other two models in representing the EOF2 pattern, which is associated with the southwest-northeast shifting of the cyclone. This result suggests that ECMWF model may have a tendency to show a closer-to-shore solution in forecasting East Coast winter storms. The downstream impacts of Rossby wave packets (RWPs) on the predictability of winter storms are investigated to explore the source of ensemble uncertainties. The composited RWPA anomalies show that there are enhanced RWPs propagating across the Pacific in both large-error and large-spread cases over the verification regions. There are also indications that the errors might propagate with a speed comparable with the group velocity of RWPs. Based on the composite results as well as our observations of the operation daily RWPA, a conceptual model of errors/uncertainty development associated with RWPs has been proposed to serve as a practical tool to understand the evolution of forecast errors and uncertainties associated with the coherent RWPs originating from upstream as far as western Pacific. (Abstract shortened by ProQuest.).

Development of a System to Generate Near Real Time Tropospheric Delay and Precipitable Water Vapor in situ at Geodetic GPS Stations, to Improve Forecasting of Severe Weather Events

NASA Astrophysics Data System (ADS)

Moore, A. W.; Bock, Y.; Geng, J.; Gutman, S. I.; Laber, J. L.; Morris, T.; Offield, D. G.; Small, I.; Squibb, M. B.

2012-12-01

We describe a system under development for generating ultra-low latency tropospheric delay and precipitable water vapor (PWV) estimates in situ at a prototype network of geodetic GPS sites in southern California, and demonstrating their utility in forecasting severe storms commonly associated with flooding and debris flow events along the west coast of North America through infusion of this meteorological data at NOAA National Weather Service (NWS) Forecast Offices and the NOAA Earth System Research Laboratory (ESRL). The first continuous geodetic GPS network was established in southern California in the early 1990s and much of it was converted to real-time (latency <1s) high-rate (1Hz) mode over the following decades. GPS stations are multi-purpose and can also provide estimates of tropospheric zenith delays, which can be converted into mm-accuracy PWV using collocated pressure and temperature measurements, the basis for GPS meteorology (Bevis et al. 1992, 1994; Duan et al. 1996) as implemented by NOAA with a nationwide distribution of about 300 GPS-Met stations providing PW estimates at subhourly resolution currently used in operational weather forecasting in the U.S. We improve upon the current paradigm of transmitting large quantities of raw data back to a central facility for processing into higher-order products. By operating semi-autonomously, each station will provide low-latency, high-fidelity and compact data products within the constraints of the narrow communications bandwidth that often occurs in the aftermath of natural disasters. The onsite ambiguity-resolved precise point positioning solutions are enabled by a power-efficient, low-cost, plug-in Geodetic Module for fusion of data from in situ sensors including GPS and a low-cost MEMS meteorological sensor package. The decreased latency (~5 minutes) PW estimates will provide the detailed knowledge of the distribution and magnitude of PW that NWS forecasters require to monitor and predict severe winter storms, landfalling atmospheric rivers, and summer thunderstorms associated with the North American monsoon. On the national level, the ESRL will evaluate the utility of ultra-low resolution GNSS observations to improve NOAA's warning and forecast capabilities. The overall objective is to better forecast, assess, and mitigate natural hazards through the flow of information from multiple geodetic stations to scientists, mission planners, decision makers, and first responders.

Storm Surge Simulation and Ensemble Forecast for Hurricane Irene (2011)

NASA Astrophysics Data System (ADS)

Lin, N.; Emanuel, K.

2012-12-01

Hurricane Irene, raking the U.S. East Coast during the period of 26-30 August 2011, caused widespread damage estimated at $15.8 billion and was responsible for 49 direct deaths (Avila and Cangialosi, 2011). Although the most severe impact in the northeastern U.S. was catastrophic inland flooding, with its unusually large size, Irene also generated high waves and storm surges and caused moderate to major coastal flooding. The most severe surge damage occurred between Oregon Inlet and Cape Hatteras in North Carolina (NC). Significant storm surge damage also occurred along southern Chesapeake Bay, and moderate and high surges were observed along the coast from New Jersey (NJ) northward. A storm surge of 0.9-1.8 m caused hundreds of millions of dollars in property damage in New York City (NYC) and Long Island, despite the fact that the storm made landfall to the west of NYC with peak winds of no more than tropical storm strength. Making three U.S. landfalls (in NC, NJ, and NY), Hurricane Irene provides a unique case for studying storm surge along the eastern U.S. coastline. We apply the hydrodynamic model ADCIRC (Luettich et al. 1992) to conduct surge simulations for Pamlico Sound, Chesapeake Bay, and NYC, using best track data and parametric wind and pressure models. The results agree well with tidal-gauge observations. Then we explore a new methodology for storm surge ensemble forecasting and apply it to Irene. This method applies a statistical/deterministic hurricane model (Emanuel et al. 2006) to generate large numbers of storm ensembles under the storm environment described by the 51 ECMWF ensemble members. The associated surge ensembles are then generated with the ADCIRC model. The numerical simulation is computationally efficient, making the method applicable to real-time storm surge ensemble forecasting. We report the results for NYC in this presentation. The ADCIRC simulation using the best track data generates a storm surge of 1.3 m and a storm tide of 2.1 m at the Battery, NYC, which agree well with the observed storm surge of 1.33 m and storm tide of 2.12 m, although the simulated surge arrives about 2 hours earlier than the observed. Based on the surge climatology estimated by Lin et al. (2012), Hurricane Irene's storm surge is approximately a 60-year event for NYC, but its storm tide, with the surge happening right at the high astronomical tide, is a 100-year event. Lin et al. (2012) also projected that such 100-year storm tide events might occur on average every 3-20 years by the end of the century, under the IPCC A1B emission scenario and a 1-m sea level rise. The ensemble forecasting, starting from two and one days (each with 1000 ensembles) before Irene's first landfall in NC, shows that Irene's actual storm surge at the Battery had a chance of about 9% and 10% to be exceeded, respectively. The largest surges among the two ensemble sets are 2.28 m and 2.05 m, respectively. If happening at the high tide, as with Hurricane Irene, the worst-case storm tides would be about 3-3.2 m, similar to the highest historical water level at the Battery due to a hurricane in 1821. Lin et al. (2012) estimated that such a storm tide of about 3.1 m had a return period of about 500 years under current climate conditions, but the return period might become 25-240 years by the end of the century, under the IPCC A1B emission scenario and a 1-m sea level rise.

National Weather Service Warning Performance Based on the WSR-88D.

NASA Astrophysics Data System (ADS)

Polger, Paul D.; Goldsmith, Barry S.; Przywarty, Richard C.; Bocchieri, Joseph R.

1994-02-01

The National Weather Service (NWS) began operational use of the Weather Surveillance Radar-1988 Doppler (WSR-88D) system in March 1991 at Norman, Oklahoma. WSR-88D data have been available to forecasters at five additional offices: Melbourne, Florida, and sterling, Virginia (since January 1992); St. Louis, Missouri, and Dodge City, Kansas (since March 1992); and Houston, Texas (since April 1992). The performance of the severe local storm and flash flood warning programs at the six offices before and after the availability of the WSR-88D was measured quantitatively. The verification procedures and statistical measures used in the quantitative evaluation were those used operationally by the NWS.The statistics show that the warnings improved dramatically when the WSR-88D was in operation. Specifically, the probability of detection of severe weather events increased and the number of false alarms decreased. There was also a marked improvement in the lead time for all severe local storm and flash flood events. These improvements were evident throughout the effective range of the radar. Stratification of severe local storm data by severe thunderstorms versus tornadoes revealed an improvement in the NWS's ability to differentiate between tornadic and nontornadic storms when the WSR-88D was in operation. Four individual cases are examined to illustrate how forecasters used the WSR-88D to achieve the improved results. These cases focus on the unique features of the WSR-88D that provide an advantage over conventional NWS radars.

Solar Storm GIC Forecasting: Solar Shield Extension Development of the End-User Forecasting System Requirements

NASA Technical Reports Server (NTRS)

Pulkkinen, A.; Mahmood, S.; Ngwira, C.; Balch, C.; Lordan, R.; Fugate, D.; Jacobs, W.; Honkonen, I.

2015-01-01

A NASA Goddard Space Flight Center Heliophysics Science Division-led team that includes NOAA Space Weather Prediction Center, the Catholic University of America, Electric Power Research Institute (EPRI), and Electric Research and Management, Inc., recently partnered with the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) to better understand the impact of Geomagnetically Induced Currents (GIC) on the electric power industry. This effort builds on a previous NASA-sponsored Applied Sciences Program for predicting GIC, known as Solar Shield. The focus of the new DHS S&T funded effort is to revise and extend the existing Solar Shield system to enhance its forecasting capability and provide tailored, timely, actionable information for electric utility decision makers. To enhance the forecasting capabilities of the new Solar Shield, a key undertaking is to extend the prediction system coverage across Contiguous United States (CONUS), as the previous version was only applicable to high latitudes. The team also leverages the latest enhancements in space weather modeling capacity residing at Community Coordinated Modeling Center to increase the Technological Readiness Level, or Applications Readiness Level of the system http://www.nasa.gov/sites/default/files/files/ExpandedARLDefinitions4813.pdf.

Potential impact of remote sensing data on sea-state analysis and prediction

NASA Technical Reports Server (NTRS)

Cardone, V. J.

1983-01-01

The severe North Atlantic storm which damaged the ocean liner Queen Elizabeth 2 (QE2) was studied to assess the impact of remotely sensed marine surface wind data obtained by SEASAT-A, on sea state specifications and forecasts. Alternate representations of the surface wind field in the QE2 storm were produced from the SEASAT enhanced data base, and from operational analyses based upon conventional data. The wind fields were used to drive a high resolution spectral ocean surface wave prediction model. Results show that sea state analyses would have been vastly improved during the period of storm formation and explosive development had remote sensing wind data been available in real time. A modest improvement in operational 12 to 24 hour wave forecasts would have followed automatically from the improved initial state specification made possible by the remote sensing data in both numerical and sea state prediction models. Significantly improved 24 to 48 hour wave forecasts require in addition to remote sensing data, refinement in the numerical and physical aspects of weather prediction models.

Compilation of Abstracts of Theses Submitted by Candidates for Degrees, 1 October 1981 - 30 September 1982.

DTIC Science & Technology

1983-05-01

the European Center for Medium Range Weather Forecasts is used to define the storm and to calculate the budgets. Important differences are found...geopotential field at 850, 700 and 500mb on a 120 point grid with 5 degree latitude and longitude spacing that is centered on the storm . The 120 EOF... storm movement and intensity during the past 36 hours. The EOF-based regression equations are verified over an independent sample of 50 storms , and

New technology and tool prepared for communication against storm surges.

NASA Astrophysics Data System (ADS)

Letkiewicz, Beata

2010-05-01

The aim of the presentation is description of the new technology and tool prepared for communication, information and issue of warnings against storm surges. The Maritime Branch of the Institute of Meteorology and Water Management is responsible for preparing the forecast as warning, where the end users are Government Officials and Public. The Maritime Branch carry out the project "Strengthening the administrative capacity in order to improve the management of Polish coastal zone environment" (supported by a grant from Norway through the Norwegian Financial Mechanism). The expected final result of the project is web site www.baltyk.pogodynka.pl. One of the activities of the project is - set up of information website www.baltyk.pogodynka.pl, giving public access to the complied data. Information on web site: - meta data - marine data (on-line measurement: sea level, water temperature, salinity, oxygen concentration); - data bases of mathematical model outputs - forecast data (sea level, currents); - ice conditions of the Baltic Sea, - instructions, information materials with information of polish coastal zone. The aim of set up of the portal is development of communication between users of the system, exchange of the knowledge of marine environment and natural hazards such as storm surges, improving the ability of the region in the scope of the data management about the sea environment and the coastal zone.

A Total Lightning Perspective of the 20 May 2013 Moore, Oklahoma Supercell

NASA Technical Reports Server (NTRS)

Stano, Geoffrey T.; Schultz, Christopher J.; Carey, Lawrence D.; MacGorman, Don R.; Calhoun, Kristin M.

2014-01-01

In the early afternoon of 20 May 2013, a storm initiated to the west-southwest of Newcastle, Oklahoma. This storm would rapidly intensify into the parent supercell of the tornado that struck the city of Moore, Oklahoma. This article describes what contributions total lightning observations from the Oklahoma Lightning Mapping Array could provide to operational forecasters had these observations been available in real-time. This effort includes a focus on the GOES-R pseudo-geostationary lightning mapper demonstration product as well as the NASA SPoRT / Meteorological Development Laboratory's total lightning tracking tool. These observations and tools identified several contributions. Two distinct lightning jumps at 1908 and 1928 UTC provided a lead time of 19 minutes ahead of severe hail and 26 minutes ahead of the Moore, Oklahoma tornado's touchdown. These observations provide strong situational awareness to forecasters, as the lightning jumps are related to the rapid strengthening of the storm's updraft and mesocyclone and serve as a precursor to the stretching of the storm vortex ahead severe weather.

An overview of 2016 WISE Urban Summer Observation Campaign (WUSOC 2016) in the Seoul metropolitan area of South Korea

NASA Astrophysics Data System (ADS)

Jung, Jae-Won; Kim, Sang-Woo; Shim, Jae-Kwan; Kwak, Kyung-Hwan

2017-04-01

The Weather Information Service Engine (WISE), launched project of the Korea Meteorological Administration (KMA), aims to operate the urban meteorological observation network from 2012 to 2019 and to test and operate the application weather service (e.g., flash flood, road weather, city ecology, city microclimate, dispersion of hazardous substance etc.) in 2019 through the development of Advanced Storm-scale Analysis Prediction System(ASAPS) for the production of storm-scale hazard weather monitoring and prediction system. The WISE institute has completed construction of 31 urban meteorological observation cities in Seoul metropolitan area and has built a real-time test operation and verification system by improving the ASAPS that produces 1 km and 6 hour forecast information based on the 5 km forecast information of KMA. Field measurements of 2016 WISE Urban Summer Observation Campaign (WUSOC 2016) was conducted in the Seoul metropolitan area of South Korea from August 22 to October 14, 2016. Involving over 70 researchers from more than 12 environmental and atmospheric science research groups in South Korea, WUSOC2016 focused on special observations, severe rain storm observations using mobile observation car and radiosonde, wind profile observations using Wind Doppler Lidar and radiosonde, etc., around the Seoul metropolitan area. WUSOC2016 purpose at data quality control, accuracy verification, usability check, and quality improvement of ASAPS at observation stations constructed in WISE. In addition, we intend to contribute to the activation of urban fusion weather research and risk weather research through joint observation and data sharing.

Microwave Imager Measures Sea Surface Temperature Through Clouds

NASA Technical Reports Server (NTRS)

2002-01-01

This image was acquired over Tropical Atlantic and U.S. East Coast regions on Aug. 22 - Sept. 23, 1998. Cloud data were collected by the Geostationary Operational Environmental Satellite (GOES). Sea Surface Temperature (SST) data were collected aboard the NASA/NASDA Tropical Rainfall Measuring Mission (TRMM) satellite by The TRMM Microwave Imager (TMI). TMI is the first satellite microwave sensor capable of accurately measuring sea surface temperature through clouds, as shown in this scene. For years scientists have known there is a strong correlation between sea surface temperature and the intensity of hurricanes. But one of the major stumbling blocks for forecasters has been the precise measurement of those temperatures when a storm begins to form. In this scene, clouds have been made translucent to allow an unobstructed view of the surface. Notice Hurricane Bonnie approaching the Carolina Coast (upper left) and Hurricane Danielle following roughly in its path (lower right). The ocean surface has been falsely colored to show a map of water temperature--dark blues are around 75oF, light blues are about 80oF, greens are about 85oF, and yellows are roughly 90oF. A hurricane gathers energy from warm waters found at tropical latitudes. In this image we see Hurricane Bonnie cross the Atlantic, leaving a cooler trail of water in its wake. As Hurricane Danielle followed in Bonnie's path, the wind speed of the second storm dropped markedly, as available energy to fuel the storm dropped off. But when Danielle left Bonnie's wake, wind speeds increased due to temperature increases in surface water around the storm. As a hurricane churns up the ocean, it's central vortex draws surface heat and water into the storm. That suction at the surface causes an upwelling of deep water. At depth, tropical ocean waters are significantly colder than water found near the surface. As they're pulled up to meet the storm, those colder waters essentially leave a footprint in the storm's wake which might last as long as two weeks. Forecasters can quantify the difference in surface temperatures between this footprint and the surrounding temperatures and use that information to better predict storm intensity. If another storm intersects with this cold water trail, it is likely to lose significant strength due to the fact that the colder water does not contain as much potential energy as warm water. TRMM Fact Sheet Predicting Hurricane Intensity Far from Land Remote Sensing Systems Image courtesy TRMM Project, Remote Sensing Systems, and Scientific Visualization Studio, NASA Goddard Space Flight Center

Advances in using satellite altimetry to observe storm surge

NASA Astrophysics Data System (ADS)

Han, Guoqi

2017-04-01

Storm surges are the major cause for coastal flooding, resulting in catastrophic damage to properties and loss of life in coastal communities. Thus it is important to utilize new technology to enhance our capabilities of observing storm surges and ultimately to improve our capacity for forecasting storm surges and mitigating damage and loss. In this talk we first review traditional methods of monitoring storm surges. We then provide examples of storm surges observed by nadir satellite altimetry, during Hurricane Sandy and Igor, as well as typhoon and cyclone events. We further evaluate satellite results against tide-gauge data and explain storm surge features. Finally, we discuss the potential of a wide-swath altimetry mission, the Surface Water and Ocean Topography (SWOT), for observing storm surges.

Future Weather Forecasting in the Year 2020-Investing in Technology Today: Improving Weather and Environmental Predictions

NASA Technical Reports Server (NTRS)

Anthes, Richard; Schoeberl, Mark

2000-01-01

Fast-forward twenty years to the nightly simultaneous TV/webcast. Accurate 8-14 day regional forecasts will be available as will be a whole host of linked products including economic impact, travel, energy usage, etc. On-demand, personalized street-level forecasts will be downloaded into your PDA. Your home system will automatically update the products of interest to you (e.g. severe storm forecasts, hurricane predictions, etc). Short and long range climate forecasts will be used by your "Quicken 2020" to make suggest changes in your "futures" investment portfolio. Through a lively and informative multi-media presentation, leading Space-Earth Science Researchers and Technologists will share their vision for the year 2020, offering a possible futuristic forecast enabled through the application of new technologies under development today. Copies of the 'broadcast' will be available on Beta Tape for your own future use. If sufficient interest exists, the program may also be made available for broadcasters wishing to do stand-ups with roll-ins from the San Francisco meeting for their viewers back home.

Landfalling Tropical Cyclones: Forecast Problems and Associated Research Opportunities

USGS Publications Warehouse

Marks, F.D.; Shay, L.K.; Barnes, G.; Black, P.; Demaria, M.; McCaul, B.; Mounari, J.; Montgomery, M.; Powell, M.; Smith, J.D.; Tuleya, B.; Tripoli, G.; Xie, Lingtian; Zehr, R.

1998-01-01

The Fifth Prospectus Development Team of the U.S. Weather Research Program was charged to identify and delineate emerging research opportunities relevant to the prediction of local weather, flooding, and coastal ocean currents associated with landfalling U.S. hurricanes specifically, and tropical cyclones in general. Central to this theme are basic and applied research topics, including rapid intensity change, initialization of and parameterization in dynamical models, coupling of atmospheric and oceanic models, quantitative use of satellite information, and mobile observing strategies to acquire observations to evaluate and validate predictive models. To improve the necessary understanding of physical processes and provide the initial conditions for realistic predictions, a focused, comprehensive mobile observing system in a translating storm-coordinate system is required. Given the development of proven instrumentation and improvement of existing systems, three-dimensional atmospheric and oceanic datasets need to be acquired whenever major hurricanes threaten the United States. The spatial context of these focused three-dimensional datasets over the storm scales is provided by satellites, aircraft, expendable probes released from aircraft, and coastal (both fixed and mobile), moored, and drifting surface platforms. To take full advantage of these new observations, techniques need to be developed to objectively analyze these observations, and initialize models aimed at improving prediction of hurricane track and intensity from global-scale to mesoscale dynamical models. Multinested models allow prediction of all scales from the global, which determine long- term hurricane motion to the convective scale, which affect intensity. Development of an integrated analysis and model forecast system optimizing the use of three-dimensional observations and providing the necessary forecast skill on all relevant spatial scales is required. Detailed diagnostic analyses of these datasets will lead to improved understanding of the physical processes of hurricane motion, intensity change, the atmospheric and oceanic boundary layers, and the air- sea coupling mechanisms. The ultimate aim of this effort is the construction of real-time analyses of storm surge, winds, and rain, prior to and during landfall, to improve warnings and provide local officials with the comprehensive information required for recovery efforts in the hardest hit areas as quickly as possible.

Simulation and analysis of synoptic scale dust storms over the Arabian Peninsula

NASA Astrophysics Data System (ADS)

Beegum, S. Naseema; Gherboudj, Imen; Chaouch, Naira; Temimi, Marouane; Ghedira, Hosni

2018-01-01

Dust storms are among the most severe environmental problems in arid and semi-arid regions of the world. The predictability of seven dust events, viz. D1: April 2-4, 2014; D2: February 23-24, 2015; D3: April 1-3, 2015; D4: March 26-28, 2016; D5: August 3-5, 2016; D6: March 13-14, 2017 and D7:March 19-21, 2017, are investigated over the Arabian Peninsula using a regionally adapted chemistry transport model CHIMERE coupled with the Weather Research and Forecast (WRF) model. The hourly forecast products of particulate matter concentrations (PM10) and aerosol optical depths (AOD) are compared against both satellite-based (MSG/SEVRI RGB dust, MODIS Deep Blue Aerosol Optical Depth: DB-AOD, Ozone Monitoring Instrument observed UV Aerosol Absorption Index: OMI-AI) and ground-based (AERONET AOD) remote sensing products. The spatial pattern and the time series of the simulations show good agreement with the observations in terms of the dust intensity as well as the spatiotemporal distribution. The causative mechanisms of these dust events are identified by the concurrent analyses of the meteorological data. From these seven storms, five are associated with synoptic scale meteorological processes, such as prefrontal storms (D1 and D7), postfrontal storms of short (D2), and long (D3) duration types, and a summer shamal storm (D6). However, the storms D4 and D6 are partly associated with mesoscale convective type dust episodes known as haboobs. The socio-economic impacts of the dust events have been assessed by estimating the horizontal visibility, air quality index (AQI), and the dust deposition flux (DDF) from the forecasted dust concentrations. During the extreme dust events, the horizontal visibility drops to near-zero values co-occurred withhazardous levels of AQI and extremely high dust deposition flux (250 μg cm- 2 day- 1).

Evidence for Gravity Wave Seeding of Convective Ionospheric Storms Possibly Initiated by Thunderstorms

NASA Astrophysics Data System (ADS)

Kelley, M. C.; Dao, E. V.

2018-05-01

With the increase in solar activity, the Communication/Outage Forecast System satellite decayed on orbit to below the F peak. As such, we can study the development of convective ionospheric storms and, most importantly, study large-scale seeding of the responsible instability. For decades, gravity has been suggested as being responsible for the long wavelengths in the range of 200 to 1,000 km, as are commonly observed using airglow and satellite data. Here we suggest that convective thunderstorms are a likely source of gravity waves and point out that recent theoretical analysis has shown this connection to be quite possible.

A High Resolution Tropical Cyclone Power Outage Forecasting Model for the Continental United States

NASA Astrophysics Data System (ADS)

Pino, J. V.; Quiring, S. M.; Guikema, S.; Shashaani, S.; Linger, S.; Backhaus, S.

2017-12-01

Tropical cyclones cause extensive damage to the power infrastructure system throughout the United States. This damage can leave millions without power for extended periods of time, as most recently seen with Hurricane Matthew (2016). Accurate and timely prediction of power outages are essential for utility companies, emergency management agencies, and governmental organizations. Here we present a high-resolution (250 m x 250 m) hurricane power outage model for the United States. The model uses only publicly-available data to make predictions. It uses forecasts of storm variables such as maximum 3-second wind gust, duration of strong winds > 20 m s-2, soil moisture, and precipitation. It also incorporates static environmental variables such as elevation characteristics, land cover type, population density, tree species data, and root zone depth. A web tool was established for use by the Department of Energy (DOE) so that the model can be used for real-time outage forecasting or for synthetic tropical cyclones as an exercise in emergency management. This web tool provides DOE decision-makers with high impact analytic results and products that can be disseminated to federal, local, and state agencies. The results then aid utility companies in their pre- and post-storm activities, thus decreasing restoration times and lowering costs.

Observing storm surges from satellite altimetry

NASA Astrophysics Data System (ADS)

Han, Guoqi

2016-07-01

Storm surges can cause catastrophic damage to properties and loss of life in coastal communities. Thus it is important to enhance our capabilities of observing and forecasting storm surges for mitigating damage and loss. In this presentation we show examples of observing storm surges around the world using nadir satellite altimetry, during Hurricane Sandy, Igor, and Isaac, as well as other cyclone events. The satellite observations are evaluated against tide-gauge observations and discussed for dynamic mechanisms. We also show the potential of a new wide-swath altimetry mission, the Surface Water and Ocean Topography (SWOT), for observing storm surges.

Short-term Forecasting Tools for Agricultural Nutrient Management.

PubMed

Easton, Zachary M; Kleinman, Peter J A; Buda, Anthony R; Goering, Dustin; Emberston, Nichole; Reed, Seann; Drohan, Patrick J; Walter, M Todd; Guinan, Pat; Lory, John A; Sommerlot, Andrew R; Sharpley, Andrew

2017-11-01

The advent of real-time, short-term farm management tools is motivated by the need to protect water quality above and beyond the general guidance offered by existing nutrient management plans. Advances in high-performance computing and hydrologic or climate modeling have enabled rapid dissemination of real-time information that can assist landowners and conservation personnel with short-term management planning. This paper reviews short-term decision support tools for agriculture that are under various stages of development and implementation in the United States: (i) Wisconsin's Runoff Risk Advisory Forecast (RRAF) System, (ii) New York's Hydrologically Sensitive Area Prediction Tool, (iii) Virginia's Saturated Area Forecast Model, (iv) Pennsylvania's Fertilizer Forecaster, (v) Washington's Application Risk Management (ARM) System, and (vi) Missouri's Design Storm Notification System. Although these decision support tools differ in their underlying model structure, the resolution at which they are applied, and the hydroclimates to which they are relevant, all provide forecasts (range 24-120 h) of runoff risk or soil moisture saturation derived from National Weather Service Forecast models. Although this review highlights the need for further development of robust and well-supported short-term nutrient management tools, their potential for adoption and ultimate utility requires an understanding of the appropriate context of application, the strategic and operational needs of managers, access to weather forecasts, scales of application (e.g., regional vs. field level), data requirements, and outreach communication structure. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

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.;

Assessing the Impact of Pre-gpm Microwave Precipitation Observations in the Goddard WRF Ensemble Data Assimilation System

NASA Technical Reports Server (NTRS)

Chambon, Philippe; Zhang, Sara Q.; Hou, Arthur Y.; Zupanski, Milija; Cheung, Samson

2013-01-01

The forthcoming Global Precipitation Measurement (GPM) Mission will provide next generation precipitation observations from a constellation of satellites. Since precipitation by nature has large variability and low predictability at cloud-resolving scales, the impact of precipitation data on the skills of mesoscale numerical weather prediction (NWP) is largely affected by the characterization of background and observation errors and the representation of nonlinear cloud/precipitation physics in an NWP data assimilation system. We present a data impact study on the assimilation of precipitation-affected microwave (MW) radiances from a pre-GPM satellite constellation using the Goddard WRF Ensemble Data Assimilation System (Goddard WRF-EDAS). A series of assimilation experiments are carried out in a Weather Research Forecast (WRF) model domain of 9 km resolution in western Europe. Sensitivities to observation error specifications, background error covariance estimated from ensemble forecasts with different ensemble sizes, and MW channel selections are examined through single-observation assimilation experiments. An empirical bias correction for precipitation-affected MW radiances is developed based on the statistics of radiance innovations in rainy areas. The data impact is assessed by full data assimilation cycling experiments for a storm event that occurred in France in September 2010. Results show that the assimilation of MW precipitation observations from a satellite constellation mimicking GPM has a positive impact on the accumulated rain forecasts verified with surface radar rain estimates. The case-study on a convective storm also reveals that the accuracy of ensemble-based background error covariance is limited by sampling errors and model errors such as precipitation displacement and unresolved convective scale instability.

The eSurge-Venice project: altimeter and scatterometer satellite data to improve the storm surge forecasting in the city of Venice

NASA Astrophysics Data System (ADS)

Zecchetto, Stefano; De Biasio, Francesco; Umgiesser, Georg; Bajo, Marco; Vignudelli, Stefano; Papa, Alvise; Donlon, Craig; Bellafiore, Debora

2013-04-01

On the framework of the Data User Element (DUE) program, the European Space Agency is funding a project to use altimeter Total Water Level Envelope (TWLE) and scatterometer wind data to improve the storm surge forecasting in the Adriatic Sea and in the city of Venice. The project will: a) Select a number of Storm Surge Events occurred in the Venice lagoon in the period 1999-present day b) Provide the available satellite Earth Observation (EO) data related to the Storm Surge Events, mainly satellite winds and altimeter data, as well as all the available in-situ data and model forecasts c) Provide a demonstration Near Real Time service of EO data products and services in support of operational and experimental forecasting and warning services d) Run a number of re-analysis cases, both for historical and contemporary storm surge events, to demonstrate the usefulness of EO data The re-analysis experiments, based on hindcasts performed by the finite element 2-D oceanographic model SHYFEM (https://sites.google.com/site/shyfem/), will 1. use different forcing wind fields (calibrated and not calibrated with satellite wind data) 2. use Storm Surge Model initial conditions determined from altimeter TWLE data. The experience gained working with scatterometer and Numerical Weather Prediction (NWP) winds in the Adriatic Sea tells us that the bias NWP-Scatt wind is negative and spatially and temporally not uniform. In particular, a well established point is that the bias is higher close to coasts then offshore. Therefore, NWP wind speed calibration will be carried out on each single grid point in the Adriatic Sea domain over the period of a Storm Surge Event, taking into account of existing published methods. Point #2 considers two different methodologies to be used in re-analysis tests. One is based on the use of the TWLE values from altimeter data in the Storm Surge Model (SSM), applying data assimilation methodologies and trying to optimize the initial conditions of the simulation.The second possibility is an indirect exploitation of the TWLE data from altimeter in an ensemble-like framework, obtained by slight variations of the external forcing. In this case the wind data from NWP models will be weakly altered (shifted in phase), the drag coefficient will be modified, and the initial condition of the model slightly shifted in time to account for the uncertainty of these factors. This contribution will illustrate the geophysical context of work and outline the results.

Long Range Forecast Possibilities for X-Band Radar Construction on Shemya

DTIC Science & Technology

2002-05-24

strong winds, since the Aleutian Low and expanding polar vortex affect the region in the winter, as do tropical storms and frontal passages in the...summer. This, combined with Shemya being located near the exit region of the climatological storm track off the East Asian continent, makes the island...12-13 5. Path of tropical storms in the North Pacific, for the entire 160-year period

Detection and Prediction of Hail Storms in Satellite Imagery using Deep Learning

NASA Astrophysics Data System (ADS)

Pullman, M.; Gurung, I.; Ramachandran, R.; Maskey, M.

2017-12-01

Natural hazards, such as damaging hail storms, dramatically disrupt both industry and agriculture, having significant socio-economic impacts in the United States. In 2016, hail was responsible for 3.5 billion and 23 million dollars in damage to property and crops, respectively, making it the second costliest 2016 weather phenomenon in the United States. The destructive nature and high cost of hail storms has driven research into the development of more accurate hail-prediction algorithms in an effort to mitigate societal impacts. Recently, weather forecasting efforts have turned to deep learning neural networks because neural networks can more effectively model complex, nonlinear, dynamical phenomenon that exist in large datasets through multiple stages of transformation and representation. In an effort to improve hail-prediction techniques, we propose a deep learning technique that leverages satellite imagery to detect and predict the occurrence of hail storms. The technique is applied to satellite imagery from 2006 to 2016 for the contiguous United States and incorporates hail reports obtained from the National Center for Environmental Information Storm Events Database for training and validation purposes. In this presentation, we describe a novel approach to predicting hail via a neural network model that creates a large labeled dataset of hail storms, the accuracy and results of the model, and its applications for improving hail forecasting.

Impact of TRMM and SSM/I Rainfall Assimilation on Global Analysis and QPF

NASA Technical Reports Server (NTRS)

Hou, Arthur; Zhang, Sara; Reale, Oreste

2002-01-01

Evaluation of QPF skills requires quantitatively accurate precipitation analyses. We show that assimilation of surface rain rates derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and Special Sensor Microwave/Imager (SSM/I) improves quantitative precipitation estimates (QPE) and many aspects of global analyses. Short-range forecasts initialized with analyses with satellite rainfall data generally yield significantly higher QPF threat scores and better storm track predictions. These results were obtained using a variational procedure that minimizes the difference between the observed and model rain rates by correcting the moist physics tendency of the forecast model over a 6h assimilation window. In two case studies of Hurricanes Bonnie and Floyd, synoptic analysis shows that this procedure produces initial conditions with better-defined tropical storm features and stronger precipitation intensity associated with the storm.

Validation of Satellite-based Rainfall Estimates for Severe Storms (Hurricanes & Tornados)

NASA Astrophysics Data System (ADS)

Nourozi, N.; Mahani, S.; Khanbilvardi, R.

2005-12-01

Severe storms such as hurricanes and tornadoes cause devastating damages, almost every year, over a large section of the United States. More accurate forecasting intensity and track of a heavy storm can help to reduce if not to prevent its damages to lives, infrastructure, and economy. Estimating accurate high resolution quantitative precipitation (QPE) from a hurricane, required to improve the forecasting and warning capabilities, is still a challenging problem because of physical characteristics of the hurricane even when it is still over the ocean. Satellite imagery seems to be a valuable source of information for estimating and forecasting heavy precipitation and also flash floods, particularly for over the oceans where the traditional ground-based gauge and radar sources cannot provide any information. To improve the capability of a rainfall retrieval algorithm for estimating QPE of severe storms, its product is evaluated in this study. High (hourly 4km x 4km) resolutions satellite infrared-based rainfall products, from the NESDIS Hydro-Estimator (HE) and also PERSIANN (Precipitation Estimation from Remotely Sensed Information using an Artificial Neural Networks) algorithms, have been tested against NEXRAD stage-IV and rain gauge observations in this project. Three strong hurricanes: Charley (category 4), Jeanne (category 3), and Ivan (category 3) that caused devastating damages over Florida in the summer 2004, have been considered to be investigated. Preliminary results demonstrate that HE tends to underestimate rain rates when NEXRAD shows heavy storm (rain rates greater than 25 mm/hr) and to overestimate when NEXRAD gives low rainfall amounts, but PERSIANN tends to underestimate rain rates, in general.

Local ensemble transform Kalman filter for ionospheric data assimilation: Observation influence analysis during a geomagnetic storm event

NASA Astrophysics Data System (ADS)

Durazo, Juan A.; Kostelich, Eric J.; Mahalov, Alex

2017-09-01

We propose a targeted observation strategy, based on the influence matrix diagnostic, that optimally selects where additional observations may be placed to improve ionospheric forecasts. This strategy is applied in data assimilation observing system experiments, where synthetic electron density vertical profiles, which represent those of Constellation Observing System for Meteorology, Ionosphere, and Climate/Formosa satellite 3, are assimilated into the Thermosphere-Ionosphere-Electrodynamics General Circulation Model using the local ensemble transform Kalman filter during the 26 September 2011 geomagnetic storm. During each analysis step, the observation vector is augmented with five synthetic vertical profiles optimally placed to target electron density errors, using our targeted observation strategy. Forecast improvement due to assimilation of augmented vertical profiles is measured with the root-mean-square error (RMSE) of analyzed electron density, averaged over 600 km regions centered around the augmented vertical profile locations. Assimilating vertical profiles with targeted locations yields about 60%-80% reduction in electron density RMSE, compared to a 15% average reduction when assimilating randomly placed vertical profiles. Assimilating vertical profiles whose locations target the zonal component of neutral winds (Un) yields on average a 25% RMSE reduction in Un estimates, compared to a 2% average improvement obtained with randomly placed vertical profiles. These results demonstrate that our targeted strategy can improve data assimilation efforts during extreme events by detecting regions where additional observations would provide the largest benefit to the forecast.

The Mauna Kea Weather Center: Custom Atmospheric Forecasting Support for Mauna Kea

NASA Astrophysics Data System (ADS)

Businger, Steven

2011-03-01

The success of operations at Mauna Kea Observatories is strongly influenced by weather conditions. The Mauna Kea Weather Center, an interdisciplinary research program, was established in 1999 to develop and provide custom weather support for Mauna Kea Observatories. The operational forecasting goals of the program are to facilitate the best possible use of favorable atmospheric conditions for scientific benefit and to ensure operational safety. During persistent clear periods, astronomical observing quality varies substantially due to changes in the vertical profiles of temperature, wind, moisture, and turbulence. Cloud and storm systems occasionally cause adverse or even hazardous conditions. A dedicated, daily, real-time mesoscale numerical modeling effort provides crucial forecast guidance in both cases. Several key atmospheric variables are forecast with sufficient skill to be of operational and scientific benefit to the telescopes on Mauna Kea. Summit temperature forecasts allow mirrors to be set to the ambient temperature to reduce image distortion. Precipitable water forecasts allow infrared observations to be prioritized according to atmospheric opacity. Forecasts of adverse and hazardous conditions protect the safety of personnel and allow for scheduling of maintenance when observing is impaired by cloud. The research component of the project continues to improve the accuracy and content of the forecasts. In particular, case studies have resulted in operational forecasts of astronomical observing quality, or seeing.

Tropical Storm Hagupit Weakening as it Nears Manila

NASA Image and Video Library

2017-12-08

Tropical Storm Hagupit's low level circulation center is being obscured by its deep central convection and intensities are hard to pinpoint as the storm interacts with land. Once clear over the waters of the South China Sea Hagupit is forecast to continue weakening as it approaches the southern coast of Vietnam. This image was taken by the Suomi NPP satellite's VIIRS instrument around 0510Z on December 8, 2014. NASA/NOAA/NPP Credit: NASA/NOAA via NOAA Environmental Visualization Laboratory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Real-time Interplanetary Shock Prediciton System

NASA Astrophysics Data System (ADS)

Vandegriff, J.; Ho, G.; Plauger, J.

A system is being developed to predict the arrival times and maximum intensities of energetic storm particle (ESP) events at the earth. Measurements of particle flux values at L1 being made by the Electron, Proton, and Alpha Monitor (EPAM) instrument aboard NASA's ACE spacecraft are made available in real-time by the NOAA Space Environment Center as 5 minute averages of several proton and electron energy channels. Past EPAM flux measurements can be used to train forecasting algorithms which then run on the real-time data. Up to 3 days before the arrival of the interplanetary shock associated with an ESP event, characteristic changes in the particle intensities (such as decreased spectral slope and increased overall flux level) are easily discernable. Once the onset of an event is detected, a neural net is used to forecast the arrival time and flux level for the event. We present results obtained with this technique for forecasting the largest of the ESP events detected by EPAM. Forecasting information will be made publicly available through http://sd-www.jhuapl.edu/ACE/EPAM/, the Johns Hopkins University Applied Physics Lab web site for the ACE/EPAM instrument.

Short-range quantitative precipitation forecasting using Deep Learning approaches

NASA Astrophysics Data System (ADS)

Akbari Asanjan, A.; Yang, T.; Gao, X.; Hsu, K. L.; Sorooshian, S.

2017-12-01

Predicting short-range quantitative precipitation is very important for flood forecasting, early flood warning and other hydrometeorological purposes. This study aims to improve the precipitation forecasting skills using a recently developed and advanced machine learning technique named Long Short-Term Memory (LSTM). The proposed LSTM learns the changing patterns of clouds from Cloud-Top Brightness Temperature (CTBT) images, retrieved from the infrared channel of Geostationary Operational Environmental Satellite (GOES), using a sophisticated and effective learning method. After learning the dynamics of clouds, the LSTM model predicts the upcoming rainy CTBT events. The proposed model is then merged with a precipitation estimation algorithm termed Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) to provide precipitation forecasts. The results of merged LSTM with PERSIANN are compared to the results of an Elman-type Recurrent Neural Network (RNN) merged with PERSIANN and Final Analysis of Global Forecast System model over the states of Oklahoma, Florida and Oregon. The performance of each model is investigated during 3 storm events each located over one of the study regions. The results indicate the outperformance of merged LSTM forecasts comparing to the numerical and statistical baselines in terms of Probability of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), RMSE and correlation coefficient especially in convective systems. The proposed method shows superior capabilities in short-term forecasting over compared methods.

An extreme dust storm over the Arabian Peninsula in Spring 2015: the role of convective mixing and vortex stretching

NASA Astrophysics Data System (ADS)

Hauser, Seraphine; Pante, Gregor; Pantillon, Florian; Knippertz, Peter

2017-04-01

The Arabian Peninsula is one of the World's largest dust sources. Severe dust storms occur throughout the year dominated by synoptic-scale driven frontal systems in winter and spring and convective systems during summer and autumn. Dust storm frequency peaks in spring, when extra-tropical upper-level troughs associated with near-surface cold fronts regularly penetrate into the peninsula. In this study we investigate the dynamics of an extreme springtime dust event, which covered the entire Arabian Peninsula and the adjacent Indian Ocean in early April 2015. In addition to the more common trough/frontal characteristics, EUMETSAT's false-colour dust product shows a striking vortex-like structure during the initial state of the storm. Several SYNOP stations on the Arabian Peninsula report severe dust storms, rapid temperature drop, strong increase in wind speed up to 40 kn and zero visibility for several hours on 01 and 02 April. Remarkably also, 61 mm of rainfall are observed on 01 April at the station Arar in northern Saudi Arabia (annual average 52 mm), clearly indicating a convective contribution to this event. Some evidence for significant precipitation is also found in satellite products. Operational analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF) show a distinct short-wave upper-level trough swiftly propagating across the region during this period, accompanied by high relative vorticity values of up to 10 times the planetary vorticity. This vorticity is associated with the trough's curvature, but also with the large cyclonic shear at the northern side of the subtropical jet. The passage of the upper-level disturbance is well timed to overpass the region of the Arabian Peninsula heat low around midday, where vorticity is thermally generated. Most likely the deep boundary layer facilitated the triggering of convection by the upper-level forcing. Ultimately, downward mixing of the high vorticity by convection plus vortex stretching cause exceptionally high vorticity near the surface, which initiated this extreme and unusual dust storm. Short-range ECMWF forecasts produce precipitation but not as extreme as measured at Arar. The model also generates strong near-surface winds, which are generally in good agreement with the SYNOP observations. Interestingly, however, the 10 m wind direction falls short to reflect the extreme cyclonic curvature evident in station observations, pointing to an underestimation of the vortex in the model. We hypothesise that the ECMWF model with its parameterised convection is unable to realistically represent the vertical mixing and vortex stretching. Numerical simulations on the convection permitting scale might improve forecasts of such events, but this is yet to be tested.

Directional Analysis of the Storm Surge from Hurricane Sandy 2012, with Applications to Charleston, New Orleans, and the Philippines

PubMed Central

Drews, Carl; Galarneau, Thomas J.

2015-01-01

Hurricane Sandy in late October 2012 drove before it a storm surge that rose to 4.28 meters above mean lower low water at The Battery in lower Manhattan, and flooded the Hugh L. Carey automobile tunnel between Brooklyn and The Battery. This study examines the surge event in New York Harbor using the Weather Research and Forecasting (WRF) atmospheric model and the Coupled-Ocean-Atmosphere-Wave- Sediment Transport / Regional Ocean Modeling System (COAWST/ROMS). We present a new technique using directional analysis to calculate and display maps of a coastline's potential for storm surge; these maps are constructed from wind fields blowing from eight fixed compass directions. This analysis approximates the surge observed during Hurricane Sandy. The directional analysis is then applied to surge events at Charleston, South Carolina, New Orleans, Louisiana, and Tacloban City, the Philippines. Emergency managers could use these directional maps to prepare their cities for an approaching storm, on planning horizons from days to years. PMID:25822480

Directional analysis of the storm surge from Hurricane Sandy 2012, with applications to Charleston, New Orleans, and the Philippines.

PubMed

Drews, Carl; Galarneau, Thomas J

2015-01-01

Hurricane Sandy in late October 2012 drove before it a storm surge that rose to 4.28 meters above mean lower low water at The Battery in lower Manhattan, and flooded the Hugh L. Carey automobile tunnel between Brooklyn and The Battery. This study examines the surge event in New York Harbor using the Weather Research and Forecasting (WRF) atmospheric model and the Coupled-Ocean-Atmosphere-Wave- Sediment Transport/Regional Ocean Modeling System (COAWST/ROMS). We present a new technique using directional analysis to calculate and display maps of a coastline's potential for storm surge; these maps are constructed from wind fields blowing from eight fixed compass directions. This analysis approximates the surge observed during Hurricane Sandy. The directional analysis is then applied to surge events at Charleston, South Carolina, New Orleans, Louisiana, and Tacloban City, the Philippines. Emergency managers could use these directional maps to prepare their cities for an approaching storm, on planning horizons from days to years.

A numerical study on hurricane-induced storm surge and inundation in Charleston Harbor, South Carolina

NASA Astrophysics Data System (ADS)

Peng, Machuan; Xie, Lian; Pietrafesa, Leonard J.

2006-08-01

A storm surge and inundation model is configured in Charleston Harbor and its adjacent coastal region to study the harbor's response to hurricanes. The hydrodynamic component of the modeling system is based on the Princeton Ocean Model, and a scheme with multiple inundation speed options is imbedded in the model for the inundation calculation. Historic observations (Hurricane Hugo and its related storm surge and inundation) in the Charleston Harbor region indicate that among three possible inundation speeds in the model, taking Ct (gd)1/2 (Ct is a terrain-related parameter) as the inundation speed is the best choice. Choosing a different inundation speed in the model has effects not only on inundation area but also on storm surge height. A nesting technique is necessary for the model system to capture the mesoscale feature of a hurricane and meanwhile to maintain a higher horizontal resolution in the harbor region, where details of the storm surge and inundation are required. Hurricane-induced storm surge and inundation are very sensitive to storm tracks. Twelve hurricanes with different tracks are simulated to investigate how Charleston Harbor might respond to tracks that are parallel or perpendicular to the coastline or landfall at Charleston at different angles. Experiments show that large differences of storm surge and inundation may have occurred if Hurricane Hugo had approached Charleston Harbor with a slightly different angle. A hurricane's central pressure, radius of maximum wind, and translation speed have their own complicated effects on surge and inundation when the hurricane approaches the coast on different tracks. Systematic experiments are performed in order to illustrate how each of such factors, or a combination of them, may affect the storm surge height and inundation area in the Charleston Harbor region. Finally, suggestions are given on how this numerical model system may be used for hurricane-induced storm surge and inundation forecasting.

High resolution modelling of wind fields for optimization of empirical storm flood predictions

NASA Astrophysics Data System (ADS)

Brecht, B.; Frank, H.

2014-05-01

High resolution wind fields are necessary to predict the occurrence of storm flood events and their magnitude. Deutscher Wetterdienst (DWD) created a catalogue of detailed wind fields of 39 historical storms at the German North Sea coast from the years 1962 to 2011. The catalogue is used by the Niedersächsisches Landesamt für Wasser-, Küsten- und Naturschutz (NLWKN) coastal research center to improve their flood alert service. The computation of wind fields and other meteorological parameters is based on the model chain of the DWD going from the global model GME via the limited-area model COSMO with 7 km mesh size down to a COSMO model with 2.2 km. To obtain an improved analysis COSMO runs are nudged against observations for the historical storms. The global model GME is initialised from the ERA reanalysis data of the European Centre for Medium-Range Weather Forecasts (ECMWF). As expected, we got better congruency with observations of the model for the nudging runs than the normal forecast runs for most storms. We also found during the verification process that different land use data sets could influence the results considerably.

Can High-resolution WRF Simulations Be Used for Short-term Forecasting of Lightning?

NASA Technical Reports Server (NTRS)

Goodman, S. J.; Lapenta, W.; McCaul, E. W., Jr.; LaCasse, K.; Petersen, W.

2006-01-01

A number of research teams have begun to make quasi-operational forecast simulations at high resolution with models such as the Weather Research and Forecast (WRF) model. These model runs have used horizontal meshes of 2-4 km grid spacing, and thus resolved convective storms explicitly. In the light of recent global satellite-based observational studies that reveal robust relationships between total lightning flash rates and integrated amounts of precipitation-size ice hydrometeors in storms, it is natural to inquire about the capabilities of these convection-resolving models in representing the ice hydrometeor fields faithfully. If they do, this might make operational short-term forecasts of lightning activity feasible. We examine high-resolution WRF simulations from several Southeastern cases for which either NLDN or LMA lightning data were available. All the WRF runs use a standard microphysics package that depicts only three ice species, cloud ice, snow and graupel. The realism of the WRF simulations is examined by comparisons with both lightning and radar observations and with additional even higher-resolution cloud-resolving model runs. Preliminary findings are encouraging in that they suggest that WRF often makes convective storms of the proper size in approximately the right location, but they also indicate that higher resolution and better hydrometeor microphysics would be helpful in improving the realism of the updraft strengths, reflectivity and ice hydrometeor fields.

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.

The Early-Warning System for incoming storm surge and tide in the Republic of Mauritius

NASA Astrophysics Data System (ADS)

Bogaard, Tom; de Lima Rego, Joao; Vatvani, Deepak; Virasami, Renganaden; Verlaan, Martin

2016-04-01

The Republic of Mauritius (ROM) is a group of islands in the South West of the Indian Ocean, consisting of the main islands of Mauritius, Rodrigues and Agalega and the archipelago of Saint Brandon. The ROM is particularly vulnerable to the adverse effects of climate change, especially in the coastal zone, where a convergence of accelerating sea level rise and increasing intensity of tropical cyclones is expected to result in considerable economic loss, humanitarian stresses, and environmental degradation. Storm surges and swell waves are expected to be aggravated through sea level rise and climate change effects on weather patterns. Adaptation to increased vulnerability requires a re-evaluation of existing preparedness measures. The focus of this project is on more effective preparedness and issuing of alerts developing a fully-automated Early-Warning System for incoming storm surge and tide, together with the Mauritius Meteorological Services and the National Disaster Risk Reduction and Management Centre (NDRRMC), such that coastal communities in Mauritius, Rodrigues and Agalega Islands are able to evacuate timely and safely in case of predicted extreme water levels. The Mauritius Early-Warning System for storm surge and tide was implemented using software from Deltares' Open-Source and free software Community. A set of five depth-averaged Delft3D-FLOW hydrodynamic models are run every six-hours with a forecast horizon of three days, simulating water levels along the coast of the three main islands. Two regional models of horizontal resolution 5km force the three detailed models of 500m resolution; all models are forced at the surface by the 0.25° NOAA/GFS meteorological forecasts. In addition, our Wind-Enhancement Scheme is used to blend detailed cyclone track bulletin's info with the larger-scale Numerical Weather Predictions. Measured data is retrieved near real-time from available Automatic Weather Stations. All these workflows are managed by the operational platform software, Delft-FEWS. The presently operational Mauritius Early-Warning System produces a set of intuitive tables for each island, containing time- and space-varying information on threshold crossings by predicted water levels. At multiple locations for each island of the ROM, the operator is informed in one glance about the recommended preparedness level, from "Safe" to "Watch", "Alert" or "Warning" based on water level forecasts. The HTML page was designed together with the MMS and the NDRRMC, in order to be easy to interpret and disseminate by local authorities.

GOES-S NASA Social

NASA Image and Video Library

2018-02-28

Tim Walsh, GOES-R System Program director for the National Oceanic and Atmospheric Administration, or NOAA, speaks to members of social media in the Kennedy Space Center’s Press Site auditorium. The briefing focused on the Geostationary Operational Environmental Satellite, or GOES-S, the second spacecraft in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U.S. Deep South Summer Convection

NASA Technical Reports Server (NTRS)

McCaul, Eugene W., Jr.; Case, Jonathan L.; Zavodsky, Bradley; Srikishen, Jayanthi; Medlin, Jeffrey; Wood, Lance

2014-01-01

Convection-allowing numerical weather simula- tions have often been shown to produce convective storms that have significant sensitivity to choices of model physical parameterizations. Among the most important of these sensitivities are those related to cloud microphysics, but planetary boundary layer parameterizations also have a significant impact on the evolution of the convection. Aspects of the simulated convection that display sensitivity to these physics schemes include updraft size and intensity, simulated radar reflectivity, timing and placement of storm initi- ation and decay, total storm rainfall, and other storm features derived from storm structure and hydrometeor fields, such as predicted lightning flash rates. In addition to the basic parameters listed above, the simulated storms may also exhibit sensitivity to im- posed initial conditions, such as the fields of soil temper- ature and moisture, vegetation cover and health, and sea and lake water surface temperatures. Some of these sensitivities may rival those of the basic physics sensi- tivities mentioned earlier. These sensitivities have the potential to disrupt the accuracy of short-term forecast simulations of convective storms, and thereby pose sig- nificant difficulties for weather forecasters. To make a systematic study of the quantitative impacts of each of these sensitivities, a matrix of simulations has been performed using all combinations of eight separate microphysics schemes, three boundary layer schemes, and two sets of initial conditions. The first version of initial conditions consists of the default data from large-scale operational model fields, while the second features specialized higher- resolution soil conditions, vegetation conditions and water surface temperatures derived from datasets created at NASA's Short-term Prediction and Operational Research Tran- sition (SPoRT) Center at the National Space Science and Technology Center (NSSTC) in Huntsville, AL. Simulations as outlined above, each 48 in number, were conducted for five midsummer weakly sheared coastal convective events each at two sites, Mobile, AL (MOB) and Houston, TX (HGX). Of special interest to operational forecasters at MOB and HGX were accuracy of timing and placement of convective storm initiation, reflectivity magnitudes and coverage, rainfall and inferred lightning threat.

An Assessment of the Subseasonal Predictability of Severe Thunderstorm Environments and Activity using the Climate Forecast System Version 2

NASA Astrophysics Data System (ADS)

Stepanek, Adam J.

The prospect for skillful long-term predictions of atmospheric conditions known to directly contribute to the onset and maintenance of severe convective storms remains unclear. A thorough assessment of the capability for a global climate model such as the Climate Forecast System Version 2 (CFSv2) to skillfully represent parameters related to severe weather has the potential to significantly improve medium- to long-range outlooks vital to risk managers. Environmental convective available potential energy (CAPE) and deep-layer vertical wind shear (DLS) can be used to distinguish an atmosphere conducive to severe storms from one supportive of primarily non-severe 'ordinary' convection. As such, this research concentrates on the predictability of CAPE, DLS, and a product of the two parameters (CAPEDLS) by the CFSv2 with a specific focus on the subseasonal timescale. Individual month-long verification periods from the Climate Forecast System reanalysis (CFSR) dataset are measured against a climatological standard using cumulative distribution function (CDF) and area-under-the-CDF (AUCDF) techniques designed mitigate inherent model biases while concurrently assessing the entire distribution of a given parameter in lieu of a threshold-based approach. Similar methods imposed upon the CFS reforecast (CFSRef) and operational CFSv2 allow for comparisons elucidating both spatial and temporal trends in skill using correlation coefficients, proportion correct metrics, Heidke skill score (HSS), and root-mean-square-error (RMSE) statistics. Key results show the CFSv2-based output often demonstrates skill beyond a climatologically-based threshold when the forecast is notably anomalous from the 29-year (1982-2010) mean CFSRef prediction (exceeding one standard deviation at grid point level). CFSRef analysis indicates enhanced skill during the months of April and June (relative to May) and for predictions of DLS. Furthermore, years exhibiting skill in terms of RMSE are shown to possess certain correlations with El Nino-Southern Oscillation conditions from the preceding winter and concurrent Madden Julian Oscillation activity. Applying results gleaned from the CFSRef analysis to the operational CFSv2 (2011-16) indicates predictive skill can be increased by isolating forecasts meeting multiple parameter-based relationships.

Ensemble Sensitivity Analysis of a Severe Downslope Windstorm in Complex Terrain: Implications for Forecast Predictability Scales and Targeted Observing Networks

DTIC Science & Technology

2013-09-01

wave breaking (NWB) and eight wave breaking (WB) storms are shown...studies, and it follows that the wind storm characteristics are likely more three dimensional as well. For the purposes of this study, a severe DSWS is...regularly using the HWAS network at USAFA since its installation in 2004. A careful examination of these events reveals downslope storms that are

Statistical Analysis of Ensemble Forecasts of Tropical Cyclone Tracks over the North Atlantic

DTIC Science & Technology

2012-06-01

Figure 6. Official tracks of the 2008 Atlantic hurricane season. Storms are listed in the top-right box with the symbols and track color explained in...Atlantic hurricane season. Storms are listed in the top-right box with the symbols and track color explained in the legend in the bottom-right box (From...NHC 2012l). ...................................................13 Figure 8. Official tracks of the 2010 Atlantic hurricane season. Storms are listed

Development of extended WRF variational data assimilation system (WRFDA) for WRF non-hydrostatic mesoscale model

NASA Astrophysics Data System (ADS)

Pattanayak, Sujata; Mohanty, U. C.

2018-06-01

The paper intends to present the development of the extended weather research forecasting data assimilation (WRFDA) system in the framework of the non-hydrostatic mesoscale model core of weather research forecasting system (WRF-NMM), as an imperative aspect of numerical modeling studies. Though originally the WRFDA provides improved initial conditions for advanced research WRF, we have successfully developed a unified WRFDA utility that can be used by the WRF-NMM core, as well. After critical evaluation, it has been strategized to develop a code to merge WRFDA framework and WRF-NMM output. In this paper, we have provided a few selected implementations and initial results through single observation test, and background error statistics like eigenvalues, eigenvector and length scale among others, which showcase the successful development of extended WRFDA code for WRF-NMM model. Furthermore, the extended WRFDA system is applied for the forecast of three severe cyclonic storms: Nargis (27 April-3 May 2008), Aila (23-26 May 2009) and Jal (4-8 November 2010) formed over the Bay of Bengal. Model results are compared and contrasted within the analysis fields and later on with high-resolution model forecasts. The mean initial position error is reduced by 33% with WRFDA as compared to GFS analysis. The vector displacement errors in track forecast are reduced by 33, 31, 30 and 20% to 24, 48, 72 and 96 hr forecasts respectively, in data assimilation experiments as compared to control run. The model diagnostics indicates successful implementation of WRFDA within the WRF-NMM system.

Risk Analysis and Forecast Service for Geomagnetically Induced Currents in Europe

NASA Astrophysics Data System (ADS)

Wik, Magnus; Pirjola, Risto; Viljanen, Ari; Lundstedt, Henrik

Geomagnetically induced currents (GIC), occurring during magnetic storms, pose a widespread natural disaster risk to the reliable operation of electric power transmission grids, oil and gas pipelines, telecommunication cables and railway systems. The solar magnetic activity is the cause of GIC. Solar coronal holes can cause recurrent inter-vals of raised geomagnetic activity, and coronal mass ejections (CME) at the Sun, sometimes producing very high speed plasma clouds with enhanced magnetic fields and particle densities, can cause the strongest geomagnetic storms. When the solar wind interacts with the geomag-netic field, energy is transferred to the magnetosphere, driving strong currents in the ionosphere. When these currents change in time a geoelectric field is induced at the surface of the Earth and in the ground. Finally, this field drives GIC in the ground and in any technological conductor systems. The worst consequence of a severe magnetic storm within a power grid is a complete blackout, as happened in the province of Québec, Canada, in March 1989, and in the city of Malmü, Sweden, in October 2003. Gas and oil pipelines are not regarded as vulnerable to the immediate impact of GIC, but the corrosion rate of buried steel pipes can increase due to GIC, which may thus shorten the lifetime of a pipe. European Risk from Geomagnetically Induced Currents (EURISGIC) is an EU project, that, if approved, will produce the first European-wide real-time prototype forecast service of GIC in power systems, based on in-situ solar wind observations and comprehensive simulations of the Earth's magnetosphere. This project focuses on high-voltage power transmission networks, which are probably currently the most susceptible to GIC effects. Geomagnetic storms cover large geographical regions, at times the whole globe. Consequently, power networks are rightly described as being European critical infrastructures whose disruption or destruction could have a significant impact. The project includes six research institutes and one SME, within Europe and US. The Federal Emergency Management Agency (FEMA), the Swedish civil contingencies agency (MSB), and representatives from the European Commission are collaborating with the NOAA National Weather Service and other research institutes on various space weather scenarios -geomagnetic storms with widespread blackouts and disruptions in communications. The aim of this new project is to conduct a risk analysis from GIC on critical infrastructure. Large amounts of natural gas are transported from Russia to Central Europe. Those long pipelines are prone to GIC impacts, which should also be evaluated quantitatively. We will use the EURISGIC project to inform the pipeline community of present European capability in GIC modelling, forecasting and in developing mitigation measures.

Ionospheric ion temperature forecasting in multiples of 27 days

NASA Astrophysics Data System (ADS)

Sojka, Jan J.; Schunk, Robert W.; Nicolls, Michael J.

2014-03-01

The ionospheric variability found at auroral locations is usually assumed to be unpredictable. The magnetosphere, which drives this ionospheric variability via storms and substorms, is at best only qualitatively describable. In this study we demonstrate that over a 3 year period, ionospheric variability observed from Poker Flat, Alaska, has, in fact, a high degree of long-term predictability. The observations used in this study are (a) the solar wind high speed stream velocity measured by the NASA Advanced Composition Explorer satellite, used to define the corotating interaction region (CIR), and (b) the ion temperature at 300 km altitude measured by the National Science Foundation Poker Flat Incoherent Scatter Radar over Poker Flat, Alaska. After determining a seasonal and diurnal climatology for the ion temperature, we show that the residual ion temperature heating events occur synchronously with CIR-geospace interactions. Furthermore, we demonstrate examples of ion temperature forecasting at 27, 54, and 81 days. A rudimentary operational forecasting scenario is described for forecasting recurrence 27 days ahead for the CIR-generated geomagnetic storms. These forecasts apply specifically to satellite tracking operations (thermospheric drag) and emergency HF-radio communications (ionospheric modifications) in the polar regions. The forecast is based on present-day solar and solar wind observations that can be used to uniquely identify the coronal hole and its CIR. From this CIR epoch, a 27 day forecast is then made.

Explicit prediction of hail using multimoment microphysics schemes for a hailstorm of 19 March 2014 in eastern China

NASA Astrophysics Data System (ADS)

Luo, Liping; Xue, Ming; Zhu, Kefeng; Zhou, Bowen

2017-07-01

In the late afternoon of 19 March 2014, a severe hailstorm swept through eastern central Zhejiang province, China. The storm produced golf ball-sized hail, strong winds, and lighting, lasting approximately 1 h over the coastal city of Taizhou. The Advanced Regional Prediction System is used to simulate the hailstorm using different configurations of the Milbrandt-Yau microphysics scheme that predict one, two, or three moments of the hydrometeor particle size distribution. Simulated fields, including accumulated precipitation and maximum estimated hail size (MESH), are verified against rain gauge observations and radar-derived MESH, respectively. For the case of the 19 March 2014 storms, the general evolution is better predicted with multimoment microphysics schemes than with the one-moment scheme; the three-moment scheme produces the best forecast. Predictions from the three-moment scheme qualitatively agree with observations in terms of size and amount of hail reaching the surface. The life cycle of the hailstorm is analyzed, using the most skillful, three-moment forecast. Based upon the tendency of surface hail mass flux, the hailstorm life cycle can be divided into three stages: developing, mature, and dissipating. Microphysical budget analyses are used to examine microphysical processes and characteristics during these three stages. The vertical structures within the storm and their link to environmental shear conditions are discussed; together with the rapid fall of hailstones, these structures and conditions appear to dictate this pulse storm's short life span. Finally, a conceptual model for the life cycle of pulse hailstorms is proposed.

Corps Water Management System (CWMS) Decision Support Modeling and Integration Use in the June 2007 Texas Floods

NASA Astrophysics Data System (ADS)

Charley, W. J.; Luna, M.

2007-12-01

The U.S. Army Corps of Engineers Corps Water Management System (CWMS) is a comprehensive data acquisition and hydrologic modeling system for short-term decision support of water control operations in real time. It encompasses data collection, validation and transformation, data storage, visualization, real time model simulation for decision-making support, and data dissemination. CWMS uses an Oracle database and Sun Solaris workstations for data processes, storage and the execution of models, with a client application (the Control and Visualization Interface, or CAVI) that can run on a Windows PC. CWMS was used by the Lower Colorado River Authority (LCRA) to make hydrologic forecasts of flows on the Lower Colorado River and operate reservoirs during the June 2007 event in Texas. The LCRA receives real-time observed gridded spatial rainfall data from OneRain, Inc. that which is a result of adjusting NexRad rainfall data with precipitation gages. This data is used, along with future precipitation estimates, for hydrologic forecasting by the rainfall-runoff modeling program HEC-HMS. Forecasted flows from HEC-HMS and combined with observed flows and reservoir information to simulate LCRA's reservoir operations and help engineers make release decisions based on the results. The river hydraulics program, HEC-RAS, computes river stages and water surface profiles for the computed flow. An inundation boundary and depth map of water in the flood plain can be calculated from the HEC-RAS results using ArcInfo. By varying future precipitation and releases, engineers can evaluate different "What if?" scenarios. What was described as an "extraordinary cluster of thunderstorms" that stalled over Burnet and Llano counties in Texas on June 27, 2007, dropped 17 to 19 inches of rainfall over a 6-hour period. The storm was classified over a 500-year event and the resulting flow over some of the smaller tributaries as a 100-year or better. CWMS was used by LCRA for flood forecasting and reservoir operations. The models accurately forecasting the flows and allowed engineers to determine that only four floodgates needed to be opened for Mansfield dam, in the Chain of Highland lakes. CWMS also forecasted the peak of the flood well before it happened. Smaller rain storms continued for a period of weeks and CWMS was used throughout the event calculating lake levels, closing of gates along with a hydro-generation schedule.

Application of satellite-based rainfall and medium range meteorological forecast in real-time flood forecasting in the Mahanadi River basin

NASA Astrophysics Data System (ADS)

Nanda, Trushnamayee; Beria, Harsh; Sahoo, Bhabagrahi; Chatterjee, Chandranath

2016-04-01

Increasing frequency of hydrologic extremes in a warming climate call for the development of reliable flood forecasting systems. The unavailability of meteorological parameters in real-time, especially in the developing parts of the world, makes it a challenging task to accurately predict flood, even at short lead times. The satellite-based Tropical Rainfall Measuring Mission (TRMM) provides an alternative to the real-time precipitation data scarcity. Moreover, rainfall forecasts by the numerical weather prediction models such as the medium term forecasts issued by the European Center for Medium range Weather Forecasts (ECMWF) are promising for multistep-ahead flow forecasts. We systematically evaluate these rainfall products over a large catchment in Eastern India (Mahanadi River basin). We found spatially coherent trends, with both the real-time TRMM rainfall and ECMWF rainfall forecast products overestimating low rainfall events and underestimating high rainfall events. However, no significant bias was found for the medium rainfall events. Another key finding was that these rainfall products captured the phase of the storms pretty well, but suffered from consistent under-prediction. The utility of the real-time TRMM and ECMWF forecast products are evaluated by rainfall-runoff modeling using different artificial neural network (ANN)-based models up to 3-days ahead. Keywords: TRMM; ECMWF; forecast; ANN; rainfall-runoff modeling

Forecasting near-surface weather conditions and precipitation in Alaska's Prince William Sound with the PWS-WRF modeling system

NASA Astrophysics Data System (ADS)

Olsson, Peter Q.; Volz, Karl P.; Liu, Haibo

2013-07-01

In the summer of 2009, several scientific teams engaged in a field program in Prince William Sound (PWS), Alaska to test an end-to-end atmosphere/ocean prediction system specially designed for this region. The "Sound Predictions Field Experiment" (FE) was a test of the PWS-Observing System (PWS-OS) and the culmination of a five-year program to develop an observational and prediction system for the Sound. This manuscript reports on results of an 18-day high-resolution atmospheric forecasting field project using the Weather Research and Forecasting (WRF) model.Special attention was paid to surface meteorological properties and precipitation. Upon reviewing the results of the real-time forecasts, modifications were incorporated in the PWS-WRF modeling system in an effort to improve objective forecast skill. Changes were both geometric (model grid structure) and physical (different physics parameterizations).The weather during the summer-time FE was typical of the PWS in that it was characterized by a number of minor disturbances rotating around an anchored low, but with no major storms in the Gulf of Alaska. The basic PWS-WRF modeling system as implemented operationally for the FE performed well, especially considering the extremely complex terrain comprising the greater PWS region.Modifications to the initial PWS-WRF modeling system showed improvement in predicting surface variables, especially where the ambient flow interacted strongly with the terrain. Prediction of precipitation on an accumulated basis was more accurate than prediction on a day-to-day basis. The 18-day period was too short to provide reliable assessment and intercomparison of the quantitative precipitation forecasting (QPF) skill of the PWS-WRF model variants.

Revised forecast: Another stormy summer ahead

NASA Astrophysics Data System (ADS)

Carlowicz, Michael

After predicting in November 1995 that the 1996 hurricane season would be less active than the typical year (Eos, December 12, 1995), William Gray and his colleagues from Colorado State University have revised their forecast. Plugging updated atmospheric data into their statistical model, the researchers are now predicting seven hurricanes—two of them intense (category 3, 4, or 5)—and 11 named storms for the summer and fall of 1996. Net tropical cyclone activity for the hurricane season, which lasts from June 1 to December 1, should be 105% of the 25-year average, according to Gray.In November, Gray and Chris Landsea of NOAA's Hurricane Research Division predicted eight tropical storms and five hurricanes (two intense), less than the historical averages of 9.3 named storms and 5.7 hurricanes per season. The change in expectations is the result of new accounting for trends in temperature and barometric pressure in Africa and around the Atlantic Basin.

The NASA Thunderstorm Observations and Research (ThOR) Mission: Lightning Mapping from Space to Improve the Short-term Forecasting of Severe Storms

NASA Technical Reports Server (NTRS)

Goodman, S. J.; Christian, H. J.; Boccippio, D. J.; Koshak, W. J.; Cecil, D. J.; Arnold, James E. (Technical Monitor)

2002-01-01

The ThOR mission uses a lightning mapping sensor in geostationary Earth orbit to provide continuous observations of thunderstorm activity over the Americas and nearby oceans. The link between lightning activity and cloud updrafts is the basis for total lightning observations indicating the evolving convective intensification and decay of storms. ThOR offers a national operational demonstration of the utility of real-time total lightning mapping for earlier and more reliable identification of potentially severe and hazardous storms. Regional pilot projects have already demonstrated that the dominance in-cloud lightning and increasing in-cloud lash rates are known to precede severe weather at the surface by tens of minutes. ThOR is currently planned for launch in 2005 on a commercial or research satellite. Real-time data will be provided to selected NWS Weather Forecast Offices and National Centers (EMC/AWC/SPC) for evaluation.

Storm-based Cloud-to-Ground Lightning Probabilities and Warnings

NASA Astrophysics Data System (ADS)

Calhoun, K. M.; Meyer, T.; Kingfield, D.

2017-12-01

A new cloud-to-ground (CG) lightning probability algorithm has been developed using machine-learning methods. With storm-based inputs of Earth Networks' in-cloud lightning, Vaisala's CG lightning, multi-radar/multi-sensor (MRMS) radar derived products including the Maximum Expected Size of Hail (MESH) and Vertically Integrated Liquid (VIL), and near storm environmental data including lapse rate and CAPE, a random forest algorithm was trained to produce probabilities of CG lightning up to one-hour in advance. As part of the Prototype Probabilistic Hazard Information experiment in the Hazardous Weather Testbed in 2016 and 2017, National Weather Service forecasters were asked to use this CG lightning probability guidance to create rapidly updating probability grids and warnings for the threat of CG lightning for 0-60 minutes. The output from forecasters was shared with end-users, including emergency managers and broadcast meteorologists, as part of an integrated warning team.

Developing Empirical Lightning Cessation Forecast Guidance for the Cape Canaveral Air Force Station and Kennedy Space Center

NASA Technical Reports Server (NTRS)

Stano, Geoffrey T.; Fuelberg, Henry E.; Roeder, William P.

2010-01-01

This research addresses the 45th Weather Squadron's (45WS) need for improved guidance regarding lightning cessation at Cape Canaveral Air Force Station and Kennedy Space Center (KSC). KSC's Lightning Detection and Ranging (LDAR) network was the primary observational tool to investigate both cloud-to-ground and intracloud lightning. Five statistical and empirical schemes were created from LDAR, sounding, and radar parameters derived from 116 storms. Four of the five schemes were unsuitable for operational use since lightning advisories would be canceled prematurely, leading to safety risks to personnel. These include a correlation and regression tree analysis, three variants of multiple linear regression, event time trending, and the time delay between the greatest height of the maximum dBZ value to the last flash. These schemes failed to adequately forecast the maximum interval, the greatest time between any two flashes in the storm. The majority of storms had a maximum interval less than 10 min, which biased the schemes toward small values. Success was achieved with the percentile method (PM) by separating the maximum interval into percentiles for the 100 dependent storms.

Synoptic Factors Affecting Structure Predictability of Hurricane Alex (2016)

NASA Astrophysics Data System (ADS)

Gonzalez-Aleman, J. J.; Evans, J. L.; Kowaleski, A. M.

2016-12-01

On January 7, 2016, a disturbance formed over the western North Atlantic basin. After undergoing tropical transition, the system became the first hurricane of 2016 - and the first North Atlantic hurricane to form in January since 1938. Already an extremely rare hurricane event, Alex then underwent extratropical transition [ET] just north of the Azores Islands. We examine the factors affecting Alex's structural evolution through a new technique called path-clustering. In this way, 51 ensembles from the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System (ECMWF-EPS) are grouped based on similarities in the storm's path through the Cyclone Phase Space (CPS). The differing clusters group various possible scenarios of structural development represented in the ensemble forecasts. As a result, it is possible to shed light on the role of the synoptic scale in changing the structure of this hurricane in the midlatitudes through intercomparison of the most "realistic" forecast of the evolution of Alex and the other physically plausible modes of its development.

A twenty-first century California observing network for monitoring extreme weather events

USGS Publications Warehouse

White, A.B.; Anderson, M.L.; Dettinger, M.D.; Ralph, F.M.; Hinojosa, A.; Cayan, D.R.; Hartman, R.K.; Reynolds, D.W.; Johnson, L.E.; Schneider, T.L.; Cifelli, R.; Toth, Z.; Gutman, S.I.; King, C.W.; Gehrke, F.; Johnston, P.E.; Walls, C.; Mann, Dorte; Gottas, D.J.; Coleman, T.

2013-01-01

During Northern Hemisphere winters, the West Coast of North America is battered by extratropical storms. The impact of these storms is of paramount concern to California, where aging water supply and flood protection infrastructures are challenged by increased standards for urban flood protection, an unusually variable weather regime, and projections of climate change. Additionally, there are inherent conflicts between releasing water to provide flood protection and storing water to meet requirements for water supply, water quality, hydropower generation, water temperature and flow for at-risk species, and recreation. In order to improve reservoir management and meet the increasing demands on water, improved forecasts of precipitation, especially during extreme events, is required. Here we describe how California is addressing their most important and costliest environmental issue – water management – in part, by installing a state-of-the-art observing system to better track the area’s most severe wintertime storms.

U.S. preparedness for severe storms questioned

NASA Astrophysics Data System (ADS)

Showstack, Randy

Doug Hill, chief meteorologist for WJLA-TV in Washington, D.C., recalled the broadcast news coverage of two supercell thunderstorms that swept through the region on September 24, producing three tornadoes and causing two fatalities. Hill said that only one local radio station which airs his forecasts activated the federal emergency alert system to immediately notify the public about the tornadoes, and added that there should be some changes in requirements. “Somehow, broadcast stations have to get the idea that these warnings and requests to activate [the alerts] are not done [just] for fun,” he said.Hill was among several experts appearing at an October 11 congressional hearing, “Weatherproofing the U.S.: Are We Prepared for Severe Storms?” The hearing, which was held by the U.S. House of Representatives' Science Committee, included testimony about the nation's emergency preparedness in dealing with several types of severe weather: tornadoes, hurricanes, and wind storms.

Wave ensemble forecast in the Western Mediterranean Sea, application to an early warning system.

NASA Astrophysics Data System (ADS)

Pallares, Elena; Hernandez, Hector; Moré, Jordi; Espino, Manuel; Sairouni, Abdel

2015-04-01

The Western Mediterranean Sea is a highly heterogeneous and variable area, as is reflected on the wind field, the current field, and the waves, mainly in the first kilometers offshore. As a result of this variability, the wave forecast in these regions is quite complicated to perform, usually with some accuracy problems during energetic storm events. Moreover, is in these areas where most of the economic activities take part, including fisheries, sailing, tourism, coastal management and offshore renewal energy platforms. In order to introduce an indicator of the probability of occurrence of the different sea states and give more detailed information of the forecast to the end users, an ensemble wave forecast system is considered. The ensemble prediction systems have already been used in the last decades for the meteorological forecast; to deal with the uncertainties of the initial conditions and the different parametrizations used in the models, which may introduce some errors in the forecast, a bunch of different perturbed meteorological simulations are considered as possible future scenarios and compared with the deterministic forecast. In the present work, the SWAN wave model (v41.01) has been implemented for the Western Mediterranean sea, forced with wind fields produced by the deterministic Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS). The wind fields includes a deterministic forecast (also named control), between 11 and 21 ensemble members, and some intelligent member obtained from the ensemble, as the mean of all the members. Four buoys located in the study area, moored in coastal waters, have been used to validate the results. The outputs include all the time series, with a forecast horizon of 8 days and represented in spaghetti diagrams, the spread of the system and the probability at different thresholds. The main goal of this exercise is to be able to determine the degree of the uncertainty of the wave forecast, meaningful between the 5th and the 8th day of the prediction. The information obtained is then included in an early warning system, designed in the framework of the European project iCoast (ECHO/SUB/2013/661009) with the aim of set alarms in coastal areas depending on the wave conditions, the sea level, the flooding and the run up in the coast.

Coupled atmosphere-ocean-wave simulations of a storm event over the Gulf of Lion and Balearic Sea

USGS Publications Warehouse

Renault, Lionel; Chiggiato, Jacopo; Warner, John C.; Gomez, Marta; Vizoso, Guillermo; Tintore, Joaquin

2012-01-01

The coastal areas of the North-Western Mediterranean Sea are one of the most challenging places for ocean forecasting. This region is exposed to severe storms events that are of short duration. During these events, significant air-sea interactions, strong winds and large sea-state can have catastrophic consequences in the coastal areas. To investigate these air-sea interactions and the oceanic response to such events, we implemented the Coupled Ocean-Atmosphere-Wave-Sediment Transport Modeling System simulating a severe storm in the Mediterranean Sea that occurred in May 2010. During this event, wind speed reached up to 25 m.s-1 inducing significant sea surface cooling (up to 2°C) over the Gulf of Lion (GoL) and along the storm track, and generating surface waves with a significant height of 6 m. It is shown that the event, associated with a cyclogenesis between the Balearic Islands and the GoL, is relatively well reproduced by the coupled system. A surface heat budget analysis showed that ocean vertical mixing was a major contributor to the cooling tendency along the storm track and in the GoL where turbulent heat fluxes also played an important role. Sensitivity experiments on the ocean-atmosphere coupling suggested that the coupled system is sensitive to the momentum flux parameterization as well as air-sea and air-wave coupling. Comparisons with available atmospheric and oceanic observations showed that the use of the fully coupled system provides the most skillful simulation, illustrating the benefit of using a fully coupled ocean-atmosphere-wave model for the assessment of these storm events.

UV Remote Sensing Data Products - Turning Data Into Knowledge

NASA Astrophysics Data System (ADS)

Weiss, M.; Paxton, L.; Schaefer, R. K.; Comberiate, J.; Hsieh, S. W.; Romeo, G.; Wolven, B. C.; Zhang, Y.

2013-12-01

The DMSP/SSUSI instruments have been taking UV images of the upper atmosphere for more than a decade. Each of the SSUSI instruments takes complete global UV images on a daily basis. Although this scientific data is very valuable, it is not actionable information. Perhaps the simplest use of SSUSI data is the assimilation of radiances into the GAIM ionospheric forecast model; even then, the data must be massaged to get it into a GAIM-ingestable form. We describe a development effort funded by the DMSP program and the Air Force Weather Agency to turn the raw data into actionable information in the form of SSUSI environmental data parameters and other derived information. We will describe current nowcasts, forecasts, and other related actionable information (e.g. auroral oval forecasts) that is currently generated by the SSUSI ground processing system for AFWA, and also concepts we have for future tools (e.g., geomagnetic storm alerts, scintillation forecasts, HF radio propagation information, auroral radar clutter) to turn more of the SSUSI dataset into actionable knowledge.

Matching current windstorms to historical analogues

NASA Astrophysics Data System (ADS)

Becker, Bernd; Maisey, Paul; Scannell, Claire; Vanvyve, Emilie; Mitchell, Lorna; Steptoe, Hamish

2015-04-01

European windstorms are capable of producing devastating socioeconomic impacts. They are capable of causing power outages to millions of people, closing transport networks, uprooting trees, causing walls, buildings and other structures to collapse, which in the worst cases has resulted in dozens of fatalities. In Europe windstorms present the greatest natural hazard risk for primary insurers and result in the greatest aggregate loss due to the high volume of claims. In the winter of 2013/2014 alone storms Christian, Xaver, Dirk and Tini cost the insurance industry an estimated EUR 2.5 bn. Here we make use of a high resolution (4 km) historical storm footprint catalogue which contains over 6000 storms. This catalogue was created using the 35 year ERA-Interim model reanalysis dataset, downscaled to 12 km and then to 4.4 km. This approach was taken in order to provide a long term, high resolution data set, consistent with Met Office high resolution deterministic forecast capability for Europe. The footprints are defined as the maximum 3 second gust at each model grid point over a 72 hour period during each storm. Matches between current/forecast storm footprints and footprints from the historical catalogue are found using fingerprint identification techniques, by way of calculating image texture derived from the gray-level-co-occurrence matrix (Haralick, 1973). The best match is found by firstly adding the current or forecast footprints to the stack of the historical storm catalogue. An "identical twin" or "best match" of this footprint is then sought from within this stack. This search is repeated for a set of measures (15 in total) including position of the strongest gusts, storm damage potential and 13 Haralick measures. Each time a candidate is found, the nearest neighbours are noted and a rank proximity measure is calculated. Finally, the Frobenius norm (distance between the two fields at each grid-point averaged) is calculated. This provides an independent assessment of the goodness of fit made by the rank proximity measure. Using this technique a series of potential historical footprints matching the current footprint is found. Each potential match is indexed according to its closeness to the current footprint where an index rating of 0 is a perfect match or "identical twin". Such pattern matching of current and forecast windstorms against an historical archive can enable insurers estimate a rapid prediction of likely loss and aid the timely deployment of staff and funds at the right level.

On the use of wave parameterizations and a storm impact scaling model in National Weather Service Coastal Flood and decision support operations

USGS Publications Warehouse

Mignone, Anthony; Stockdon, H.; Willis, M.; Cannon, J.W.; Thompson, R.

2012-01-01

National Weather Service (NWS) Weather Forecast Offices (WFO) are responsible for issuing coastal flood watches, warnings, advisories, and local statements to alert decision makers and the general public when rising water levels may lead to coastal impacts such as inundation, erosion, and wave battery. Both extratropical and tropical cyclones can generate the prerequisite rise in water level to set the stage for a coastal impact event. Forecasters use a variety of tools including computer model guidance and local studies to help predict the potential severity of coastal flooding. However, a key missing component has been the incorporation of the effects of waves in the prediction of total water level and the associated coastal impacts. Several recent studies have demonstrated the importance of incorporating wave action into the NWS coastal flood program. To follow up on these studies, this paper looks at the potential of applying recently developed empirical parameterizations of wave setup, swash, and runup to the NWS forecast process. Additionally, the wave parameterizations are incorporated into a storm impact scaling model that compares extreme water levels to beach elevation data to determine the mode of coastal change at predetermined “hotspots” of interest. Specifically, the storm impact model compares the approximate storm-induced still water level, which includes contributions from tides, storm surge, and wave setup, to dune crest elevation to determine inundation potential. The model also compares the combined effects of tides, storm surge, and the 2 % exceedance level for vertical wave runup (including both wave setup and swash) to dune toe and crest elevations to determine if erosion and/or ocean overwash may occur. The wave parameterizations and storm impact model are applied to two cases in 2009 that led to significant coastal impacts and unique forecast challenges in North Carolina: the extratropical “Nor'Ida” event during 11-14 November and the large swell event from distant Hurricane Bill on 22 August. The coastal impacts associated with Nor'Ida were due to the combined effects of surge, tide, and wave processes and led to an estimated 5.8 million dollars in damage. While the impacts from Hurricane Bill were not as severe as Nor'Ida, they were mainly associated with wave processes. Thus, this event exemplifies the importance of incorporating waves into the total water level and coastal impact prediction process. These examples set the stage for potential future applications including adaption to the more complex topography along the New England coast.

GOES-S NASA Social

NASA Image and Video Library

2018-02-28

Mic Woltman, chief of the Fleet Systems Integration Branch of NASA's Launch Services Program, left, and Gabriel Rodriguez-Mena, a United Launch Alliance systems test engineer, speak to members of social media in the Kennedy Space Center’s Press Site auditorium. The briefing focused on the National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. The spacecraft is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

Monitoring inland storm tide and flooding from Hurricane Irene along the Atlantic Coast of the United States, August 2011

USGS Publications Warehouse

McCallum, Brian E.; Painter, Jaime A.; Frantz, Eric R.

2012-01-01

The U.S. Geological Survey (USGS) deployed a temporary monitoring network of water-level sensors at 212 locations along the Atlantic coast from South Carolina to Maine during August 2011 to record the timing, areal extent, and magnitude of inland hurricane storm tide and coastal flooding generated by Hurricane Irene. Water-level sensor locations were selected to augment existing tide-gage networks to ensure adequate monitoring in areas forecasted to have substantial storm tide. As defined by the National Oceanic and Atmospheric Administration (NOAA; 2011a,b), storm tide is the water-level rise generated by a coastal storm as a result of the combination of storm surge and astronomical tide.

JPSS Data Product Applications for Monitoring Severe Weather and Environmental Hazards

NASA Astrophysics Data System (ADS)

Liu, X.; Zhou, L.; Divakarla, M. G.; Atkins, T.

2016-12-01

The Joint Polar Satellite System (JPSS) is the National Oceanic and Atmospheric Administration's (NOAA's) next-generation polar-orbiting operational environmental satellite system. The Suomi National Polar-orbiting Partnership (S-NPP) is the first satellite in the JPSS series. One of the JPSS supported key mission areas is to reduce the loss of life from high-impact weather events while improving efficient economies through environmental information. Combining with the sensors on other polar and geostationary satellite platforms, JPSS observations provided much enhanced capabilities for the Nation's essential products and services, including forecasting severe weather like hurricanes, potential tornadic outbreaks, and blizzards days in advance, and assessing environmental hazards such as droughts, floods, forest fires, poor air quality and harmful coastal waters. Sensor and Environmental Data Records (SDRs/EDRs) derived from S-NPP and follow-on JPSS satellites provide critical data for environmental assessments, forecasts and warnings. This paper demonstrates the use of S-NPP science data products towards analysis events of severe weather and environmental hazards, such as Paraguay Flooding, Hurricane Iselle, the record-breaking winter storm system that impacted the US East Coast area early this year, and Fort McMurray wildfire. A brief description of these examples and a detailed discussion of the winter storm event are presented in this paper. VIIRS (Visible Infrared Imaging Radiometer Suite) and ATMS (Advanced Technology Microwave Sounder) SDR/EDR products collected from multiple days of S-NPP observations are analyzed to study the progression of the winter storm and illustrate how JPSS products captured the storm system. The products used for this study included VIIRS day/night band (DNB) and true color images, ocean turbidity images, snow cover fraction, and the multi-sensor snowfall rates. Quantitative evaluation of the ATMS derived snowfall rates with the radar estimates revealed good agreement. Use of STAR JPSS product monitoring and visualization tools to evaluate these events, and applications of these tools for anomaly detection, mitigation, and science maintenance of the long-term stability of the data products is also presented in this paper.

ENSURF: multi-model sea level forecast - implementation and validation results for the IBIROOS and Western Mediterranean regions

NASA Astrophysics Data System (ADS)

Pérez, B.; Brouwer, R.; Beckers, J.; Paradis, D.; Balseiro, C.; Lyons, K.; Cure, M.; Sotillo, M. G.; Hackett, B.; Verlaan, M.; Fanjul, E. A.

2012-03-01

ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast that makes use of several storm surge or circulation models and near-real time tide gauge data in the region, with the following main goals: 1. providing easy access to existing forecasts, as well as to its performance and model validation, by means of an adequate visualization tool; 2. generation of better forecasts of sea level, including confidence intervals, by means of the Bayesian Model Average technique (BMA). The Bayesian Model Average technique generates an overall forecast probability density function (PDF) by making a weighted average of the individual forecasts PDF's; the weights represent the Bayesian likelihood that a model will give the correct forecast and are continuously updated based on the performance of the models during a recent training period. This implies the technique needs the availability of sea level data from tide gauges in near-real time. The system was implemented for the European Atlantic facade (IBIROOS region) and Western Mediterranean coast based on the MATROOS visualization tool developed by Deltares. Results of validation of the different models and BMA implementation for the main harbours are presented for these regions where this kind of activity is performed for the first time. The system is currently operational at Puertos del Estado and has proved to be useful in the detection of calibration problems in some of the circulation models, in the identification of the systematic differences between baroclinic and barotropic models for sea level forecasts and to demonstrate the feasibility of providing an overall probabilistic forecast, based on the BMA method.

Estimating Reservoir Inflow Using RADAR Forecasted Precipitation and Adaptive Neuro Fuzzy Inference System

NASA Astrophysics Data System (ADS)

Yi, J.; Choi, C.

2014-12-01

Rainfall observation and forecasting using remote sensing such as RADAR(Radio Detection and Ranging) and satellite images are widely used to delineate the increased damage by rapid weather changeslike regional storm and flash flood. The flood runoff was calculated by using adaptive neuro-fuzzy inference system, the data driven models and MAPLE(McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as the input variables.The result of flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated by comparing it with the actual data.The Adaptive Neuro Fuzzy method was applied to the Chungju Reservoir basin in Korea. The six rainfall events during the flood seasons in 2010 and 2011 were used for the input data.The reservoir inflow estimation results were comparedaccording to the rainfall data used for training, checking and testing data in the model setup process. The results of the 15 models with the combination of the input variables were compared and analyzed. Using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation in this study.The model using the MAPLE forecasted precipitation data showed better result for inflow estimation in the Chungju Reservoir.

A Unified Data Assimilation Strategy for Regional Coupled Atmosphere-Ocean Prediction Systems

NASA Astrophysics Data System (ADS)

Xie, Lian; Liu, Bin; Zhang, Fuqing; Weng, Yonghui

2014-05-01

Improving tropical cyclone (TC) forecasts is a top priority in weather forecasting. Assimilating various observational data to produce better initial conditions for numerical models using advanced data assimilation techniques has been shown to benefit TC intensity forecasts, whereas assimilating large-scale environmental circulation into regional models by spectral nudging or Scale-Selective Data Assimilation (SSDA) has been demonstrated to improve TC track forecasts. Meanwhile, taking into account various air-sea interaction processes by high-resolution coupled air-sea modelling systems has also been shown to improve TC intensity forecasts. Despite the advances in data assimilation and air-sea coupled models, large errors in TC intensity and track forecasting remain. For example, Hurricane Nate (2011) has brought considerable challenge for the TC operational forecasting community, with very large intensity forecast errors (27, 25, and 40 kts for 48, 72, and 96 h, respectively) for the official forecasts. Considering the slow-moving nature of Hurricane Nate, it is reasonable to hypothesize that air-sea interaction processes played a critical role in the intensity change of the storm, and accurate representation of the upper ocean dynamics and thermodynamics is necessary to quantitatively describe the air-sea interaction processes. Currently, data assimilation techniques are generally only applied to hurricane forecasting in stand-alone atmospheric or oceanic model. In fact, most of the regional hurricane forecasting models only included data assimilation techniques for improving the initial condition of the atmospheric model. In such a situation, the benefit of adjustments in one model (atmospheric or oceanic) by assimilating observational data can be compromised by errors from the other model. Thus, unified data assimilation techniques for coupled air-sea modelling systems, which not only simultaneously assimilate atmospheric and oceanic observations into the coupled air-sea modelling system, but also nudging the large-scale environmental flow in the regional model towards global model forecasts are of increasing necessity. In this presentation, we will outline a strategy for an integrated approach in air-sea coupled data assimilation and discuss its benefits and feasibility from incremental results for select historical hurricane cases.

Water Management Applications of Advanced Precipitation Products

NASA Astrophysics Data System (ADS)

Johnson, L. E.; Braswell, G.; Delaney, C.

2012-12-01

Advanced precipitation sensors and numerical models track storms as they occur and forecast the likelihood of heavy rain for time frames ranging from 1 to 8 hours, 1 day, and extended outlooks out to 3 to 7 days. Forecast skill decreases at the extended time frames but the outlooks have been shown to provide "situational awareness" which aids in preparation for flood mitigation and water supply operations. In California the California-Nevada River Forecast Centers and local Weather Forecast Offices provide precipitation products that are widely used to support water management and flood response activities of various kinds. The Hydrometeorology Testbed (HMT) program is being conducted to help advance the science of precipitation tracking and forecasting in support of the NWS. HMT high-resolution products have found applications for other non-federal water management activities as well. This presentation will describe water management applications of HMT advanced precipitation products, and characterization of benefits expected to accrue. Two case examples will be highlighted, 1) reservoir operations for flood control and water supply, and 2) urban stormwater management. Application of advanced precipitation products in support of reservoir operations is a focus of the Sonoma County Water Agency. Examples include: a) interfacing the high-resolution QPE products with a distributed hydrologic model for the Russian-Napa watersheds, b) providing early warning of in-coming storms for flood preparedness and water supply storage operations. For the stormwater case, San Francisco wastewater engineers are developing a plan to deploy high resolution gap-filling radars looking off shore to obtain longer lead times on approaching storms. A 4 to 8 hour lead time would provide opportunity to optimize stormwater capture and treatment operations, and minimize combined sewer overflows into the Bay.ussian River distributed hydrologic model.

Investigating Lateral Boundary Forcing of Weather Research and Forecasting (WRF) Model Forecasts for Artillery Mission Support

DTIC Science & Technology

2013-01-01

the internal variability, such as the storm track or rainfall pattern (8). Arguments have emerged for the use of small domains in certain cases as...Sensitivity experiments were performed with the WRF-ARW over Meiningen, Germany for two strong wintertime extratropical cyclones. These cases were chosen

Flood forecasting within urban drainage systems using NARX neural network.

PubMed

Abou Rjeily, Yves; Abbas, Oras; Sadek, Marwan; Shahrour, Isam; Hage Chehade, Fadi

2017-11-01

Urbanization activity and climate change increase the runoff volumes, and consequently the surcharge of the urban drainage systems (UDS). In addition, age and structural failures of these utilities limit their capacities, and thus generate hydraulic operation shortages, leading to flooding events. The large increase in floods within urban areas requires rapid actions from the UDS operators. The proactivity in taking the appropriate actions is a key element in applying efficient management and flood mitigation. Therefore, this work focuses on developing a flooding forecast system (FFS), able to alert in advance the UDS managers for possible flooding. For a forecasted storm event, a quick estimation of the water depth variation within critical manholes allows a reliable evaluation of the flood risk. The Nonlinear Auto Regressive with eXogenous inputs (NARX) neural network was chosen to develop the FFS as due to its calculation nature it is capable of relating water depth variation in manholes to rainfall intensities. The campus of the University of Lille is used as an experimental site to test and evaluate the FFS proposed in this paper.

Observations of the structure and evolution of surface and flight-level wind asymmetries in Hurricane Rita (2005)

NASA Astrophysics Data System (ADS)

Rogers, Robert; Uhlhorn, Eric

2008-11-01

Knowledge of the magnitude and distribution of surface winds, including the structure of azimuthal asymmetries in the wind field, are important factors for tropical cyclone forecasting. With its ability to remotely measure surface wind speeds, the stepped frequency microwave radiometer (SFMR) has assumed a prominent role for the operational tropical cyclone forecasting community. An example of this instrument's utility is presented here, where concurrent measurements of aircraft flight-level and SFMR surface winds are used to document the wind field evolution over three days in Hurricane Rita (2005). The amplitude and azimuthal location (phase) of the wavenumber-1 asymmetry in the storm-relative winds varied at both levels over time. The peak was found to the right of storm track at both levels on the first day. By the third day, the peak in flight-level storm-relative winds remained to the right of storm track, but it shifted to left of storm track at the surface, resulting in a 60-degree shift between the surface and flight-level and azimuthal variations in the ratio of surface to flight-level winds. The asymmetric differences between the surface and flight-level maximum wind radii also varied, indicating a vortex whose tilt was increasing.

On the Log-Normality of Historical Magnetic-Storm Intensity Statistics: Implications for Extreme-Event Probabilities

NASA Astrophysics Data System (ADS)

Love, J. J.; Rigler, E. J.; Pulkkinen, A. A.; Riley, P.

2015-12-01

An examination is made of the hypothesis that the statistics of magnetic-storm-maximum intensities are the realization of a log-normal stochastic process. Weighted least-squares and maximum-likelihood methods are used to fit log-normal functions to -Dst storm-time maxima for years 1957-2012; bootstrap analysis is used to established confidence limits on forecasts. Both methods provide fits that are reasonably consistent with the data; both methods also provide fits that are superior to those that can be made with a power-law function. In general, the maximum-likelihood method provides forecasts having tighter confidence intervals than those provided by weighted least-squares. From extrapolation of maximum-likelihood fits: a magnetic storm with intensity exceeding that of the 1859 Carrington event, -Dst > 850 nT, occurs about 1.13 times per century and a wide 95% confidence interval of [0.42, 2.41] times per century; a 100-yr magnetic storm is identified as having a -Dst > 880 nT (greater than Carrington) but a wide 95% confidence interval of [490, 1187] nT. This work is partially motivated by United States National Science and Technology Council and Committee on Space Research and International Living with a Star priorities and strategic plans for the assessment and mitigation of space-weather hazards.

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.

GOES-S Mission Science Briefing

NASA Image and Video Library

2018-02-27

In the Kennedy Space Center's Press Site auditorium, Jim Roberts, a scientist with the Earth System Research Laboratory's Office of Atmospheric Research for NOAA, speaks to members of the media at a mission briefing on National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. The spacecraft is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

GOES-S NASA Social

NASA Image and Video Library

2018-02-28

Gabriel Rodriguez-Mena, a United Launch Alliance systems test engineer, speaks to members of social media in the Kennedy Space Center’s Press Site auditorium. The briefing focused on the National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. The spacecraft is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

A look into hurricane Maria rapid intensification using Meteo-France's Arome-Antilles model.

NASA Astrophysics Data System (ADS)

Pilon, R.; Faure, G.; Dupont, T.; Chauvin, F.

2017-12-01

Category 5 Hurricane Maria created a string of humanitarian crises. It caused billions of dollars of damage over the Caribbean but is also one of the worst natural disaster in Dominica.The hurricane took approximately 29 hours to strengthen from a tropical storm to a major category 5 hurricane. Here we present real-time forecasts of high resolution (2.5 km) Arome-Antilles regional model forced by real-time ECMWF's Integrated Forecasting System. The model was able to relatively represent well the rapid intensification of the hurricane whether it was in timing or in location of the eye and strength of its eye wall.We will present an outline of results.

Features Based Assessments of Warm Season Convective Precipitation Forecasts From the High Resolution Rapid Refresh Model

NASA Astrophysics Data System (ADS)

Bytheway, Janice L.

Forecast models have seen vast improvements in recent years, via increased spatial and temporal resolution, rapid updating, assimilation of more observational data, and continued development and improvement of the representation of the atmosphere. One such model is the High Resolution Rapid Refresh (HRRR) model, a 3 km, hourly-updated, convection-allowing model that has been in development since 2010 and running operationally over the contiguous US since 2014. In 2013, the HRRR became the only US model to assimilate radar reflectivity via diabatic assimilation, a process in which the observed reflectivity is used to induce a latent heating perturbation in the model initial state in order to produce precipitation in those areas where it is indicated by the radar. In order to support the continued development and improvement of the HRRR model with regard to forecasts of convective precipitation, the concept of an assessment is introduced. The assessment process aims to connect model output with observations by first validating model performance then attempting to connect that performance to model assumptions, parameterizations and processes to identify areas for improvement. Observations from remote sensing platforms such as radar and satellite can provide valuable information about three-dimensional storm structure and microphysical properties for use in the assessment, including estimates of surface rainfall, hydrometeor types and size distributions, and column moisture content. A features-based methodology is used to identify warm season convective precipitating objects in the 2013, 2014, and 2015 versions of HRRR precipitation forecasts, Stage IV multisensor precipitation products, and Global Precipitation Measurement (GPM) core satellite observations. Quantitative precipitation forecasts (QPFs) are evaluated for biases in hourly rainfall intensity, total rainfall, and areal coverage in both the US Central Plains (29-49N, 85-105W) and US Mountain West (29-49N, 105-125W). Features identified in the model and Stage IV were tracked through time in order to evaluate forecasts through several hours of the forecast period. The 2013 version of the model was found to produce significantly stronger convective storms than observed, with a slight southerly displacement from the observed storms during the peak hours of convective activity (17-00 UTC). This version of the model also displayed a strong relationship between atmospheric water vapor content and cloud thickness over the central plains. In the 2014 and 2015 versions of the model, storms in the western US were found to be smaller and weaker than the observed, and satellite products (brightness temperatures and reflectivities) simulated using model output indicated that many of the forecast storms contained too much ice above the freezing level. Model upgrades intended to decrease the biases seen in early versions include changes to the reflectivity assimilation, the addition of sub-grid scale cloud parameterizations, changes to the representation of surface processes and the addition of aerosol processes to the microphysics. The effects of these changes are evident in each successive version of the model, with reduced biases in intensity, elimination of the southerly bias, and improved representation of the onset of convection.

Augmentation of Early Intensity Forecasting in Tropical Cyclones

DTIC Science & Technology

2011-09-30

modeled storms to the measured signatures. APPROACH The deviation-angle variance technique was introduced in Pineros et al. (2008) as a procedure to...the algorithm developed in the first year of the project. The new method used best-track storm fixes as the points to compute the DAV signal. We...In the North Atlantic basin, RMSE for tropical storm category is 11 kt, hurricane categories 1-3 is 12.5 kt, category 4 is 18 kt and category 5 is

Forecasters Handbook for the Middle East/Arabian Sea.

DTIC Science & Technology

1983-06-01

much of the Northeast Monsoon. j. Dust storms are infrequent during the NE Monsoon season except in the northern Red Sea where vigorous extratropical ... storm 3-30 affecting the Gulf of Aden and the southern Red Sea on June 26, 1979. 3-12 Isopleths of mean pressure differences (mb) between 3-38 strong...areas but increases the wind stress effect known as "water pileup" (analogous to " storm surge" along open coasts). 2.4 Monsoon Regimes A set of criteria

Forecasters Handbook for Japan and Adjacent Sea Areas

DTIC Science & Technology

1988-06-01

a strengthening Siberian high pressure cell. 4.5.1.1 Synoptic Patterns Summer is a season of reduced extratropical storm activity over the East China...the waters adjacent to eastern Asia, summer is a period of reduced extratropical storm activity over the Yellow Sea. Figure 2-6 (page 2-23) depicts...since the southeastern part of the sea is 6-15 closer to the extratropical storm tracks discussed in section 6.3.1.1 above. 6.3.1.3 Upper Level Winds

Geodetic Space Weather Monitoring by means of Ionosphere Modelling

NASA Astrophysics Data System (ADS)

Schmidt, Michael

2017-04-01

The term space weather indicates physical processes and phenomena in space caused by radiation of energy mainly from the Sun. Manifestations of space weather are (1) variations of the Earth's magnetic field, (2) the polar lights in the northern and southern hemisphere, (3) variations within the ionosphere as part of the upper atmosphere characterized by the existence of free electrons and ions, (4) the solar wind, i.e. the permanent emission of electrons and photons, (5) the interplanetary magnetic field, and (6) electric currents, e.g. the van Allen radiation belt. It can be stated that ionosphere disturbances are often caused by so-called solar storms. A solar storm comprises solar events such as solar flares and coronal mass ejections (CMEs) which have different effects on the Earth. Solar flares may cause disturbances in positioning, navigation and communication. CMEs can effect severe disturbances and in extreme cases damages or even destructions of modern infrastructure. Examples are interruptions to satellite services including the global navigation satellite systems (GNSS), communication systems, Earth observation and imaging systems or a potential failure of power networks. Currently the measurements of solar satellite missions such as STEREO and SOHO are used to forecast solar events. Besides these measurements the Earth's ionosphere plays another key role in monitoring the space weather, because it responses to solar storms with an increase of the electron density. Space-geodetic observation techniques, such as terrestrial GNSS, satellite altimetry, space-borne GPS (radio occultation), DORIS and VLBI provide valuable global information about the state of the ionosphere. Additionally geodesy has a long history and large experience in developing and using sophisticated analysis and combination techniques as well as empirical and physical modelling approaches. Consequently, geodesy is predestinated for strongly supporting space weather monitoring via modelling the ionosphere and detecting and forecasting its disturbances. At present a couple of nations, such as the US, UK, Japan, Canada and China, are taken the threats from extreme space weather events seriously and support the development of observing strategies and fundamental research. However, (extreme) space weather events are in all their consequences on the modern highly technologized society, causative global problems which have to be treated globally and not regionally or even nationally. Consequently, space weather monitoring must include (1) all space-geodetic observation techniques and (2) geodetic evaluation methods such as data combination, real-time modelling and forecast. In other words, geodetic space weather monitoring comprises the basic ideas of GGOS and will provide products such as forecasts of severe solar events in order to initiate necessary activities to protect the infrastructure of modern society.

GOES-S Mission Science Briefing

NASA Image and Video Library

2018-02-27

In the Kennedy Space Center's Press Site auditorium, Kristin Calhoun, a research scientist with NOAA's National Severe Storms Laboratory, speaks to members of the media at a mission briefing on National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. The spacecraft is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

An ensemble forecast of the South China Sea monsoon

NASA Astrophysics Data System (ADS)

Krishnamurti, T. N.; Tewari, Mukul; Bensman, Ed; Han, Wei; Zhang, Zhan; Lau, William K. M.

1999-05-01

This paper presents a generalized ensemble forecast procedure for the tropical latitudes. Here we propose an empirical orthogonal function-based procedure for the definition of a seven-member ensemble. The wind and the temperature fields are perturbed over the global tropics. Although the forecasts are made over the global belt with a high-resolution model, the emphasis of this study is on a South China Sea monsoon. Over this domain of the South China Sea includes the passage of a Tropical Storm, Gary, that moved eastwards north of the Philippines. The ensemble forecast handled the precipitation of this storm reasonably well. A global model at the resolution Triangular Truncation 126 waves is used to carry out these seven forecasts. The evaluation of the ensemble of forecasts is carried out via standard root mean square errors of the precipitation and the wind fields. The ensemble average is shown to have a higher skill compared to a control experiment, which was a first analysis based on operational data sets over both the global tropical and South China Sea domain. All of these experiments were subjected to physical initialization which provides a spin-up of the model rain close to that obtained from satellite and gauge-based estimates. The results furthermore show that inherently much higher skill resides in the forecast precipitation fields if they are averaged over area elements of the order of 4° latitude by 4° longitude squares.

Residual delay maps unveil global patterns of atmospheric nonlinearity and produce improved local forecasts

PubMed Central

Sugihara, George; Casdagli, Martin; Habjan, Edward; Hess, Dale; Dixon, Paul; Holland, Greg

1999-01-01

We use residual-delay maps of observational field data for barometric pressure to demonstrate the structure of latitudinal gradients in nonlinearity in the atmosphere. Nonlinearity is weak and largely lacking in tropical and subtropical sites and increases rapidly into the temperate regions where the time series also appear to be much noisier. The degree of nonlinearity closely follows the meridional variation of midlatitude storm track frequency. We extract the specific functional form of this nonlinearity, a V shape in the lagged residuals that appears to be a basic feature of midlatitude synoptic weather systems associated with frontal passages. We present evidence that this form arises from the relative time scales of high-pressure versus low-pressure events. Finally, we show that this nonlinear feature is weaker in a well regarded numerical forecast model (European Centre for Medium-Range Forecasts) because small-scale temporal and spatial variation is smoothed out in the grided inputs. This is significant, in that it allows us to demonstrate how application of statistical corrections based on the residual-delay map may provide marked increases in local forecast accuracy, especially for severe weather systems. PMID:10588685

Impact of CYGNSS Data on Tropical Cyclone Analyses and Forecasts in a Regional OSSE Framework

NASA Astrophysics Data System (ADS)

Annane, B.; McNoldy, B. D.; Leidner, S. M.; Atlas, R. M.; Hoffman, R.; Majumdar, S.

2016-12-01

The Cyclone Global Navigation Satellite System, or CYGNSS, is a planned constellation of micro-satellites that will utilize reflected Global Positioning System (GPS) satellite signals to retrieve ocean surface wind speed along the satellites' ground tracks. The orbits are designed so that there is excellent coverage of the tropics and subtropics, resulting in more thorough spatial sampling and improved sampling intervals over tropical cyclones than is possible with current spaceborne scatterometer and passive microwave sensor platforms. Furthermore, CYGNSS will be able to retrieve winds under all precipitating conditions, and over a large range of wind speeds.A regional Observing System Simulation Experiment (OSSE) framework was developed at NOAA/AOML and University of Miami that features a high-resolution regional nature run (27-km regional domain with 9/3/1 km storm-following nests; Nolan et al., 2013) embedded within a lower-resolution global nature run . Simulated observations are generated by sampling from the nature run and are provided to a data assimilation scheme, which produces analyses for a high-resolution regional forecast model, the 2014 operational Hurricane-WRF model. For data assimilation, NOAA's GSI and EnKF systems are used. Analyses are performed on the parent domain at 9-km resolution. The forecast model uses a single storm-following 3-km resolution nest. Synthetic CYGNSS wind speed data have also been created, and the impacts of the assimilation of these data on the forecasts of tropical cyclone track and intensity will be discussed.In addition to the choice of assimilation scheme, we have also examined a number of other factors/parameters that effect the impact of simulated CYGNSS observations, including frequency of data assimilation cycling (e.g., hourly, 3-hourly and 6-hourly) and the assimilation of scalar versus vector synthetic CYGNSS winds.We have found sensitivity to all of the factors tested and will summarize the methods used for testing as well as results. Generally, we have found that more frequent cycling is better than less; and flow-dependent background error covariances (e.g., EnKF) are better than static or climatological assumptions about the background error covariance.

On the forecasting the unfavorable periods in the technosphere by the space weather factors

NASA Astrophysics Data System (ADS)

Lyakhov, N. N.

2002-12-01

There is the considerable progress in development of geomagnetic disturbances forecast technique, in the necessary time, by solar activity phenomena last years. The possible relationship between violations of the traffic safety terms (VTS) in East Siberian Railway during 1986-1999 and the space weather factors was investigated. The overall number of cases under consideration is equal to 11575. By methods of correlation and spectral analysis it was shown, that statistics of VTS has not a random and it's character is probably caused by space weather factors. The principal difference between rhythmic of VTS by purely technical reasons (MECH) (failures in mechanical systems) and, that of VTS caused by wrong operations of a personnel (MAN), is noted. Increase of sudden storm commencements number results in increase of probability of mistakable actions of an operator. Probability of violations in mechanical systems increases with increase of number of quiet geomagnetic conditions. This, in its turn, dictate different approach to the ordered rows of MECH and MAN data when forecasting the unfavourable periods as the priods of increased risk in working out a wrong decision by technological process participants. The advances in forecasting of geomagnetic environment technique made possible to start construction of systems of the operative informing about unfavourable factors of space weather for the interested organizations.

Long-Range Lightning Products for Short Term Forecasting of Tropical Cyclogenesis

NASA Astrophysics Data System (ADS)

Businger, S.; Pessi, A.; Robinson, T.; Stolz, D.

2010-12-01

This paper will describe innovative graphical products derived in real time from long-range lightning data. The products have been designed to aid in short-term forecasting of tropical cyclone development for the Tropical Cyclone Structure Experiment 2010 (TCS10) held over the western Pacific Ocean from 17 August to 17 October 2010 and are available online at http://www.soest.hawaii.edu/cgi-bin/pacnet/tcs10.pl. The long-range lightning data are from Vaisala’s Global Lightning Data 360 (GLD360) network and include time, location, current strength, polarity, and data quality indication. The products currently provided in real time include i. Infrared satellite imagery overlaid with lighting flash locations, with color indication of current strength and polarity (shades of blue for negative to ground and red for positive to ground). ii. A 15x15 degree storm-centered tile of IR imagery overlaid with lightning data as in i). iii. A pseudo reflectivity product showing estimates of radar reflectivity based on lightning rate - rain rate conversion derived from TRMM and PacNet data. iv. A lightning history product that plots each hour of lightning flash locations in a different color for a 12-hour period. v. Graphs of lightning counts within 50 or 300 km radius, respectively, of the storm center vs storm central sea-level pressure. vi. A 2-D graphic showing storm core lightning density along the storm track. The first three products above can be looped to gain a better understanding of the evolution of the lightning and storm structure. Examples of the graphics and their utility will be demonstrated and discussed. Histogram of lightning counts within 50 km of the storm center and graph of storm central pressure as a function of time.

Total Lightning and Radar Storm Characteristics Associated with Severe Storms in Central Florida

NASA Technical Reports Server (NTRS)

Goodman, Steven J; Raghavan, R.; Buechler, Dennis; Hodanish, S.; Sharp, D.; Williams, E.; Boldi, B.; Matlin, A.; Weber, M.

1998-01-01

This paper examines the three dimensional characteristics of lightning flashes and severe storms observed in Central Florida during 1997-1998. The lightning time history of severe and tornadic storms were captured during the on-going ground validation campaign supporting the Lightning Imaging Sensor (LIS) experiment on the Tropical Rainfall Measuring Mission (TRMM). The ground validation campaign is a collaborative experiment that began in 1997 and involves scientists at the Global Hydrology and Climate Center, MIT/Lincoln Laboratories, and the NWS Forecast Office at Melbourne, FL. Lightning signatures that may provide potential early warning of severe storms are being evaluated by the forecasters at the NWS/MLB office. Severe storms with extreme flash rates sometimes exceeding 300 per minute and accompanying rapid increases in flash rate prior to the onset of the severe weather (hall, damaging winds, tornadoes) have been reported by Hodanish et al. and Williams et al. (1998-this conference). We examine the co-evolving changes in storm structure (mass, echo top, shear, latent heat release) and kinematics associated with these extreme and rapid flash rate changes over time. The flash frequency and density are compared with the three dimensional radar reflectivity structure of the storm to help interpret the possible mechanisms producing the extreme and rapidly increasing flash rates. For two tornadic storms examined thus far, we find the burst of lightning is associated with the development of upper level rotation in the storm. In one case, the lightning burst follows the formation of a bounded weak echo region (BWER). The flash rates diminish with time as the rotation develops to the ground in conjunction with the decent of the reflectivity core. Our initial findings suggest the dramatic increase of flash rates is associated with a sudden and dramatic increase in storm updraft intensity which we hypothesize is stretching vertical vorticity as well as enhancing the development of the mixed phase region of the storm. We discuss the importance of these factors in producing both the observed extreme flash rates and the severe weather that follows in these storms and others to be presented.

The May 1967 great storm and radio disruption event: Extreme space weather and extraordinary responses

NASA Astrophysics Data System (ADS)

Knipp, D. J.; Ramsay, A. C.; Beard, E. D.; Boright, A. L.; Cade, W. B.; Hewins, I. M.; McFadden, R. H.; Denig, W. F.; Kilcommons, L. M.; Shea, M. A.; Smart, D. F.

2016-09-01

Although listed as one of the most significant events of the last 80 years, the space weather storm of late May 1967 has been of mostly fading academic interest. The storm made its initial mark with a colossal solar radio burst causing radio interference at frequencies between 0.01 and 9.0 GHz and near-simultaneous disruptions of dayside radio communication by intense fluxes of ionizing solar X-rays. Aspects of military control and communication were immediately challenged. Within hours a solar energetic particle event disrupted high-frequency communication in the polar cap. Subsequently, record-setting geomagnetic and ionospheric storms compounded the disruptions. We explain how the May 1967 storm was nearly one with ultimate societal impact, were it not for the nascent efforts of the United States Air Force in expanding its terrestrial weather monitoring-analysis-warning-prediction efforts into the realm of space weather forecasting. An important and long-lasting outcome of this storm was more formal Department of Defense-support for current-day space weather forecasting. This story develops during the rapid rise of solar cycle 20 and the intense Cold War in the latter half of the twentieth century. We detail the events of late May 1967 in the intersecting categories of solar-terrestrial interactions and the political-military backdrop of the Cold War. This was one of the "Great Storms" of the twentieth century, despite the apparent lack of large geomagnetically induced currents. Radio disruptions like those discussed here warrant the attention of today's radio-reliant, cellular-phone and satellite-navigation enabled world.

ENSURF: multi-model sea level forecast - implementation and validation results for the IBIROOS and Western Mediterranean regions

NASA Astrophysics Data System (ADS)

Pérez, B.; Brower, R.; Beckers, J.; Paradis, D.; Balseiro, C.; Lyons, K.; Cure, M.; Sotillo, M. G.; Hacket, B.; Verlaan, M.; Alvarez Fanjul, E.

2011-04-01

ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast that makes use of existing storm surge or circulation models today operational in Europe, as well as near-real time tide gauge data in the region, with the following main goals: - providing an easy access to existing forecasts, as well as to its performance and model validation, by means of an adequate visualization tool - generation of better forecasts of sea level, including confidence intervals, by means of the Bayesian Model Average Technique (BMA) The system was developed and implemented within ECOOP (C.No. 036355) European Project for the NOOS and the IBIROOS regions, based on MATROOS visualization tool developed by Deltares. Both systems are today operational at Deltares and Puertos del Estado respectively. The Bayesian Modelling Average technique generates an overall forecast probability density function (PDF) by making a weighted average of the individual forecasts PDF's; the weights represent the probability that a model will give the correct forecast PDF and are determined and updated operationally based on the performance of the models during a recent training period. This implies the technique needs the availability of sea level data from tide gauges in near-real time. Results of validation of the different models and BMA implementation for the main harbours will be presented for the IBIROOS and Western Mediterranean regions, where this kind of activity is performed for the first time. The work has proved to be useful to detect problems in some of the circulation models not previously well calibrated with sea level data, to identify the differences on baroclinic and barotropic models for sea level applications and to confirm the general improvement of the BMA forecasts.

Case Studies of Forecasting Ionospheric Total Electron Content

NASA Astrophysics Data System (ADS)

Mannucci, A. J.; Meng, X.; Verkhoglyadova, O. P.; Tsurutani, B.; McGranaghan, R. M.

2017-12-01

We report on medium-range forecast-mode runs of ionosphere-thermosphere coupled models that calculate ionospheric total electron content (TEC), focusing on low-latitude daytime conditions. A medium-range forecast-mode run refers to simulations that are driven by inputs that can be predicted 2-3 days in advance, for example based on simulations of the solar wind. We will present results from a weak geomagnetic storm caused by a high-speed solar wind stream on June 29, 2012. Simulations based on the Global Ionosphere Thermosphere Model (GITM) and the Thermosphere Ionosphere Electrodynamic General Circulation Model (TIEGCM) significantly over-estimate TEC in certain low latitude daytime regions, compared to TEC maps based on observations. We will present the results from a more intense coronal mass ejection (CME) driven storm where the simulations are closer to observations. We compare high latitude data sets to model inputs, such as auroral boundary and convection patterns, to assess the degree to which poorly estimated high latitude drivers may be the largest cause of discrepancy between simulations and observations. Our results reveal many factors that can affect the accuracy of forecasts, including the fidelity of empirical models used to estimate high latitude precipitation patterns, or observation proxies for solar EUV spectra, such as the F10.7 index. Implications for forecasts with few-day lead times are discussed

Diabatic forcing and intialization with assimilation of cloud water and rainwater in a forecast model

NASA Technical Reports Server (NTRS)

Raymond, William H.; Olson, William S.; Callan, Geary

1995-01-01

In this study, diabatic forcing, and liquid water assimilation techniques are tested in a semi-implicit hydrostatic regional forecast model containing explicit representations of grid-scale cloud water and rainwater. Diabatic forcing, in conjunction with diabatic contributions in the initialization, is found to help the forecast retain the diabatic signal found in the liquid water or heating rate data, consequently reducing the spinup time associated with grid-scale precipitation processes. Both observational Special Sensor Microwave/Imager (SSM/I) and model-generated data are used. A physical retrieval method incorporating SSM/I radiance data is utilized to estimate the 3D distribution of precipitating storms. In the retrieval method the relationship between precipitation distributions and upwelling microwave radiances is parameterized, based upon cloud ensemble-radiative model simulations. Regression formulae relating vertically integrated liquid and ice-phase precipitation amounts to latent heating rates are also derived from the cloud ensemble simulations. Thus, retrieved SSM/I precipitation structures can be used in conjunction with the regression-formulas to infer the 3D distribution of latent heating rates. These heating rates are used directly in the forecast model to help initiate Tropical Storm Emily (21 September 1987). The 14-h forecast of Emily's development yields atmospheric precipitation water contents that compare favorably with coincident SSM/I estimates.

Development of the Coastal Storm Modeling System (CoSMoS) for predicting the impact of storms on high-energy, active-margin coasts

USGS Publications Warehouse

Barnard, Patrick; Maarten van Ormondt,; Erikson, Li H.; Jodi Eshleman,; Hapke, Cheryl J.; Peter Ruggiero,; Peter Adams,; Foxgrover, Amy C.

2014-01-01

The Coastal Storm Modeling System (CoSMoS) applies a predominantly deterministic framework to make detailed predictions (meter scale) of storm-induced coastal flooding, erosion, and cliff failures over large geographic scales (100s of kilometers). CoSMoS was developed for hindcast studies, operational applications (i.e., nowcasts and multiday forecasts), and future climate scenarios (i.e., sea-level rise + storms) to provide emergency responders and coastal planners with critical storm hazards information that may be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. The prototype system, developed for the California coast, uses the global WAVEWATCH III wave model, the TOPEX/Poseidon satellite altimetry-based global tide model, and atmospheric-forcing data from either the US National Weather Service (operational mode) or Global Climate Models (future climate mode), to determine regional wave and water-level boundary conditions. These physical processes are dynamically downscaled using a series of nested Delft3D-WAVE (SWAN) and Delft3D-FLOW (FLOW) models and linked at the coast to tightly spaced XBeach (eXtreme Beach) cross-shore profile models and a Bayesian probabilistic cliff failure model. Hindcast testing demonstrates that, despite uncertainties in preexisting beach morphology over the ~500 km alongshore extent of the pilot study area, CoSMoS effectively identifies discrete sections of the coast (100s of meters) that are vulnerable to coastal hazards under a range of current and future oceanographic forcing conditions, and is therefore an effective tool for operational and future climate scenario planning.

Using Heliospheric Imaging for Storm Forecasting - SMEI CME Observations as a Tool for Operational Forecasting at AFWA

NASA Astrophysics Data System (ADS)

Webb, D. F.; Johnston, J. C.; Fry, C. D.; Kuchar, T. A.

2008-12-01

Observations of coronal mass ejections (CMEs) from heliospheric imagers such as the Solar Mass Ejection Imager (SMEI) can lead to significant improvements in operational space weather forecasting. We are working with the Air Force Weather Agency (AFWA) to ingest SMEI all-sky imagery with appropriate tools to help forecasters improve their operational space weather forecasts. We describe two approaches: 1) Near- real time analysis of propagating CMEs from SMEI images alone combined with near-Sun observations of CME onsets and, 2) Using these calculations of speed as a mid-course correction to the HAFv2 solar wind model forecasts. HAFv2 became operational at AFWA in late 2006. The objective is to determine a set of practical procedures that the duty forecaster can use to update or correct a solar wind forecast using heliospheric imager data. SMEI observations can be used inclusively to make storm forecasts, as recently discussed in Webb et al. (Space Weather, in press, 2008). We have developed a point-and-click analysis tool for use with SMEI images and are working with AFWA to ensure that timely SMEI images are available for analyses. When a frontside solar eruption occurs, especially if within about 45 deg. of Sun center, a forecaster checks for an associated CME observed by a coronagraph within an appropriate time window. If found, especially if the CME is a halo type, the forecaster checks SMEI observations about a day later, depending on the apparent initial CME speed, for possibly associated CMEs. If one is found, then the leading edge is measured over several successive frames and an elongation-time plot constructed. A minimum of three data points, i.e., over 3-4 orbits or about 6 hours, are necessary for such a plot. Using the solar source location and onset time of the CME from, e.g., SOHO observations, and assuming radial propagation, a distance-time relation is calculated and extrapolated to the 1 AU distance. As shown by Webb et al., the storm onset time is then expected to be about 3 hours after this 1 AU arrival time (AT). The prediction program is updated as more SMEI data become available. Currently when an appropriate solar event occurs, AFWA routinely runs the HAFv2 model to make a forecast of the shock and ejecta arrival times at Earth. SMEI data can be used to improve this prediction. The HAFv2 model can produce synthetic sky maps of predicted CME brightness for comparison with SMEI images. The forecaster uses SMEI imagery to observe and track the CME. The forecaster then measures the CME location and speed using the SMEI imagery and the HAFv2 synthetic sky maps. After comparing the SMEI and HAFv2 results, the forecaster can adjust a key input to HAFv2, such as the initial speed of the disturbance at the Sun or the mid-course speed. The forecaster then iteratively runs HAFv2 until the observed and forecast sky maps match. The final HAFv2 solution becomes the new forecast. When the CME/shock arrives at (or does not reach) Earth, the forecaster verifies the forecast and updates the forecast skill statistics. Eventually, we plan to develop a more automated version of this procedure.

Detection and Modeling of a Meteotsunami in Lake Erie During a High Wind Event on May 27, 2012

NASA Astrophysics Data System (ADS)

Anderson, E. J.; Schwab, D. J.; Lombardy, K. A.; LaPlante, R. E.

2012-12-01

On May 27, 2012, a mesoscale convective system moved southeast across the central basin of Lake Erie (the shallowest of the Great Lakes) causing an increase in surface wind speed from 3 to 15 m/s over a few minutes. Although no significant pressure change was observed during this period (+1 mbar), the storm resulted in 3 reported edge waves on the southern shore (5 minutes apart), with wave heights up to 7 feet (2.13 m). Witnesses along the coast reported that the water receded before the waves hit, the only warning of the impending danger. After impact on the southern shore, several individuals were stranded in the water near Cleveland, Ohio. Fortunately, there were no fatalities or serious injury as a result of the edge waves. The storm event yielded two separate but similar squall line events that impacted the southern shore of Lake Erie several hours apart. The first event had little impact on nearshore conditions, however, the second event (moving south-eastward at 21.1 m/s or 41 knots), resulted in 7 ft waves near Cleveland as reported above. The thunderstorms generated three closely packed outflow boundaries that intersected the southern shore of Lake Erie between 1700 and 1730 UTC. The outflow boundaries were followed by a stronger outflow at 1800 UTC. Radial velocities on the WSR-88D in Cleveland, Ohio indicated the winds were stronger in the second outflow boundary. The radar indicated winds between 20.6 and 24.7 m/s (40 and 48 knots) within 240 meters (800 feet) above ground level. In order to better understand the storm event and the cause of the waves that impacted the southern shore, a three-dimensional hydrodynamic model of Lake Erie has been developed using the Finite Volume Coastal Ocean Model (FVCOM). The model is being developed as part of the Great Lakes Coastal Forecasting (GLCFS), a set of experimental real-time pre-operational hydrodynamic models run at the NOAA Great Lakes Research Laboratory that forecast currents, waves, temperature, and water levels for the Great Lakes and connecting channels. The model is simulated for the storm period on May 27, 2012 to reproduce both the benign and the wave-inducing events using interpolated 6-minute meteorology (wind, pressure, air temperature) from shoreline observations recorded by the National Weather Service. Additional scenarios are carried out to understand the influence of storm speed and direction, wind speed, and pressure change on edge wave production near the southern shore of Lake Erie. Through this study, we hope to fully elucidate the early summer meteotsunami event and build an understanding that will enable the development of a meteotsunami forecasting system for the Great Lakes.

Effects of Geomagnetic Storms on the Postsunset Vertical Plasma Drift in the Equatorial Ionosphere

NASA Astrophysics Data System (ADS)

Huang, Chao-Song

2018-05-01

It has been observed that geomagnetic storms cause suppression of the occurrence of equatorial spread F or plasma bubbles in the evening sector. In this study, we use ion drift data measured by the Communication/Navigation Outage Forecasting System satellite over 6 years (2008-2014) to derive the dependence of the vertical ion drift at the prereversal enhancement peak on the strength of magnetic storms (the Dst index). It is found that the average vertical ion drift does not change much for Dst in the range between 0 and -60 nT but decreases approximately linearly with the increasing magnitude of Dst for Dst < -60 nT. The net decrease in the average vertical ion drift is 30 m/s when Dst changes from -60 to -90 nT. This result is derived when the ion drift data during the storm main phase are excluded, so the decrease of the vertical ion drift is caused by storm time disturbance dynamo. A possible interpretation of this phenomenon is that geomagnetic activity must be strong enough (e.g., Dst < -60 nT) so disturbance winds can reach the equatorial region and change plasma drifts there. The storm time disturbance dynamo becomes dominant in the equatorial ionospheric dynamics near the end of the storm main phase, 4.7 hr after the storm onset. The postsunset vertical ion drift is significantly decreased during the early stage of the storm recovery phase but becomes almost fully recovered when Dst increases close to -60 nT.

Tropical cyclone induced asymmetry of sea level surge and fall and its presentation in a storm surge model with parametric wind fields

NASA Astrophysics Data System (ADS)

Peng, Machuan; Xie, Lian; Pietrafesa, Leonard J.

The asymmetry of tropical cyclone induced maximum coastal sea level rise (positive surge) and fall (negative surge) is studied using a three-dimensional storm surge model. It is found that the negative surge induced by offshore winds is more sensitive to wind speed and direction changes than the positive surge by onshore winds. As a result, negative surge is inherently more difficult to forecast than positive surge since there is uncertainty in tropical storm wind forecasts. The asymmetry of negative and positive surge under parametric wind forcing is more apparent in shallow water regions. For tropical cyclones with fixed central pressure, the surge asymmetry increases with decreasing storm translation speed. For those with the same translation speed, a weaker tropical cyclone is expected to gain a higher AI (asymmetry index) value though its induced maximum surge and fall are smaller. With fixed RMW (radius of maximum wind), the relationship between central pressure and AI is heterogeneous and depends on the value of RMW. Tropical cyclone's wind inflow angle can also affect surge asymmetry. A set of idealized cases as well as two historic tropical cyclones are used to illustrate the surge asymmetry.

ECMWF Extreme Forecast Index for water vapor transport: A forecast tool for atmospheric rivers and extreme precipitation

NASA Astrophysics Data System (ADS)

Lavers, David A.; Pappenberger, Florian; Richardson, David S.; Zsoter, Ervin

2016-11-01

In winter, heavy precipitation and floods along the west coasts of midlatitude continents are largely caused by intense water vapor transport (integrated vapor transport (IVT)) within the atmospheric river of extratropical cyclones. This study builds on previous findings that showed that forecasts of IVT have higher predictability than precipitation, by applying and evaluating the European Centre for Medium-Range Weather Forecasts Extreme Forecast Index (EFI) for IVT in ensemble forecasts during three winters across Europe. We show that the IVT EFI is more able (than the precipitation EFI) to capture extreme precipitation in forecast week 2 during forecasts initialized in a positive North Atlantic Oscillation (NAO) phase; conversely, the precipitation EFI is better during the negative NAO phase and at shorter leads. An IVT EFI example for storm Desmond in December 2015 highlights its potential to identify upcoming hydrometeorological extremes, which may prove useful to the user and forecasting communities.

Extra-tropical Cyclones and Windstorms in Seasonal Forecasts

NASA Astrophysics Data System (ADS)

Leckebusch, Gregor C.; Befort, Daniel J.; Weisheimer, Antje; Knight, Jeff; Thornton, Hazel; Roberts, Julia; Hermanson, Leon

2015-04-01

Severe damages and large insured losses over Europe related to natural phenomena are mostly caused by extra-tropical cyclones and their related windstorm fields. Thus, an adequate representation of these events in seasonal prediction systems and reliable forecasts up to a season in advance would be of high value for society and economy. In this study, state-of-the-art seasonal forecast prediction systems are analysed (ECMWF, UK Met Office) regarding the general climatological representation and the seasonal prediction of extra-tropical cyclones and windstorms during the core winter season (DJF) with a lead time of up to four months. Two different algorithms are used to identify cyclones and windstorm events in these datasets. Firstly, we apply a cyclone identification and tracking algorithm based on the Laplacian of MSLP and secondly, we use an objective wind field tracking algorithm to identify and track continuous areas of extreme high wind speeds (cf. Leckebusch et al., 2008), which can be related to extra-tropical winter cyclones. Thus, for the first time, we can analyse the forecast of severe wind events near to the surface caused by extra-tropical cyclones. First results suggest a successful validation of the spatial climatological distributions of wind storm and cyclone occurrence in the seasonal forecast systems in comparison with reanalysis data (ECMWF-ERA40 & ERAInterim) in general. However, large biases are found for some areas. The skill of the seasonal forecast systems in simulating the year-to-year variability of the frequency of severe windstorm events and cyclones is investigated using the ranked probability skill score. Positive skill is found over large parts of the Northern Hemisphere as well as for the most intense extra-tropical cyclones and its related wind fields.

Influence of warning information changes on emergency response

NASA Astrophysics Data System (ADS)

Heisterkamp, Tobias; Ulbrich, Uwe; Glade, Thomas; Tetzlaff, Gerd

2014-05-01

Mitigation and risk reduction of natural hazards is significantly related to the possibility of predicting the actual event. Some hazards can already be forecasted several days in advance. For these hazards, early warning systems have been developed, installed and improved over the years. The formation of winter storms for example can be recognized up to one week before they pass through Central Europe. This relative long early warning time has the advantage that forecasters can concretise the warnings over time. Therefore, warnings can even be adapted to alternating conditions within the process, the observation or changes in its modelling. Emergency managers are one group of warning recipients in the civil protection sector. They have to prepare or initiate prevention or response measures at a specific point of time, depending on the required lead time of the referring actions. At this point of time already, the forecast and its equivalent warning, has to be assumed as a stage of reality, hence the decision-makers have to come to a conclusion. These decisions are based on spatial and temporal knowledge of the forecasted event and the consequential situation of risk. With incoming warning updates, the detailed status of information is permanently being alternated. Consequently, decisions can be influenced by the development of the warning situation and the inherent tendency before a certain point of time. They can also be adapted to updates later on, according to the changing 'decision reality'. The influence of these dynamic hazard situations on operational planning and response by emergency managers is investigated in case studies on winter storms for Berlin, Germany. Therefore, the issued warnings by the weather service and data of operation of Berlin Fire Brigades are analysed and compared. This presentation shows and discusses first results.

NASA-NOAA's Suomi NPP Satellite Gets Colorful Look at Hurricane Blanca

NASA Image and Video Library

2015-06-05

NASA-NOAA's Suomi NPP satellite flew over Hurricane Blanca in the Eastern Pacific Ocean and gathered infrared data on the storm that was false-colored to show locations of the strongest thunderstorms within the storm. The Visible Infrared Imaging Radiometer Suite or VIIRS instrument aboard the satellite gathered infrared data of the storm that was made into an image at the University of Wisconsin-Madison. The image was false-colored to show temperature. Coldest cloud top temperatures indicate higher, stronger, thunderstorms within a tropical cyclone. Those are typically the strongest storms with potential for heavy rainfall. VIIRS is a scanning radiometer that collects visible and infrared imagery and "radiometric" measurements. Basically it means that VIIRS data is used to measure cloud and aerosol properties, ocean color, sea and land surface temperature, ice motion and temperature, fires, and Earth's albedo (reflected light). The VIIRS image from June 5 at 8:11 UTC (4:11 a.m. EDT) showed two areas of coldest cloud top temperatures and strongest storms were west-southwest and east-northeast of the center of Blanca's circulation center. On June 5 at 5 a.m. EDT (0900 UTC) Blanca's maximum sustained winds were near 105 mph (165 kph) with higher gusts. The National Hurricane Center (NHC) forecast expects some strengthening during the next day or so. Weakening is forecast to begin by late Saturday. At that time, NHC placed the center of Hurricane Blanca near latitude 14.3 North, longitude 106.2 West. That puts the center about 350 miles (560 km) south-southwest of Manzanillo, Mexico and about 640 miles (1,030 km) south-southeast of Cabo San Lucas, Mexico. The estimated minimum central pressure is 968 millibars (28.59 inches). Blanca is moving toward the northwest near 10 mph (17 kph). A northwestward to north-northwestward motion at a similar forward speed is expected to continue through Saturday night. Blanca has been stirring up surf along the coast of southwestern Mexico and will reach the Pacific coast of the Baja California peninsula and the southern Gulf of California later today, June 5. These swells are likely to cause life-threatening surf and rip current conditions. On the forecast track, the center of Blanca will approach the southern Baja California peninsula on Sunday. NHC cautions that "Interests in the southern Baja California peninsula should monitor the progress of Blanca. A tropical storm or hurricane watch will likely be required for a portion of Baja California Sur later today." The NHC forecast track shows Blanca making landfall in the southeastern tip of Baja California on Sunday, June 7 and tracking north-northeast along the Baja California peninsula, for several days following. Image credit: Credits: NASA/NOAA/UW-CIMSS NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Forecasting challenges during the severe weather outbreak in Central Europe on 25 June 2008

NASA Astrophysics Data System (ADS)

Púčik, Tomáš; Francová, Martina; Rýva, David; Kolář, Miroslav; Ronge, Lukáš

2011-06-01

On 25 June 2008, severe thunderstorms caused widespread damage and two fatalities in the Czech Republic. Significant features of the storms included numerous downbursts on a squall line that exhibited a bow echo reflectivity pattern, with sustained wind gusts over 32 m/s at several reporting stations. Moreover, a tornado and several downbursts of F2 intensity occurred within the convective system, collocated with the development of mesovortices within the larger scale bow echo. The extent of the event was sufficient to call it a derecho, as the windstorm had affected Eastern Germany, Southern Poland, Slovakia, Austria and Northern Hungary as well. Ahead of the squall line, several well-organized isolated cells occurred, exhibiting supercellular characteristics, both from a radar and visual perspective. These storms produced large hail and also isolated severe wind gusts. This paper deals mostly with the forecasting challenges that were experienced by the meteorologist on duty during the evolution of this convective scenario. The main challenge of the day was to identify the region that would be most affected by severe convection, especially as the numerical weather prediction failed to anticipate the extent and the progress of the derecho-producing mesoscale convective systems (MCSs). Convective storms developed in an environment conducive to severe thunderstorms, with strong wind shear confined mostly to the lower half of the troposphere. These developments also were strongly influenced by mesoscale factors, especially a mesolow centered over Austria and its trough stretching to Eastern Bohemia. The paper demonstrates how careful mesoscale analysis could prove useful in dealing with such convective situations. Remote-sensing methods are also shown to be useful in such situations, especially when they can offer sufficient lead time to issue a warning, which is not always the case.

The Impact of Atmospheric InfraRed Sounder (AIRS) Profiles on Short-term Weather Forecasts

NASA Technical Reports Server (NTRS)

Chou, Shih-Hung; Zavodsky, Brad; Jedlovec, Gary J.; Lapenta, William

2007-01-01

The Atmospheric Infrared Sounder (AIRS), together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced spacebased atmospheric sounding systems. The combined AlRS/AMSU system provides radiance measurements used to retrieve temperature profiles with an accuracy of 1 K over 1 km layers under both clear and partly cloudy conditions, while the accuracy of the derived humidity profiles is 15% in 2 km layers. Critical to the successful use of AIRS profiles for weather and climate studies is the use of profile quality indicators and error estimates provided with each profile Aside form monitoring changes in Earth's climate, one of the objectives of AIRS is to provide sounding information of sufficient accuracy such that the assimilation of the new observations, especially in data sparse region, will lead to an improvement in weather forecasts. The purpose of this paper is to describe a procedure to optimally assimilate highresolution AIRS profile data in a regional analysis/forecast model. The paper will focus on the impact of AIRS profiles on a rapidly developing east coast storm and will also discuss preliminary results for a 30-day forecast period, simulating a quasi-operation environment. Temperature and moisture profiles were obtained from the prototype version 5.0 EOS science team retrieval algorithm which includes explicit error information for each profile. The error profile information was used to select the highest quality temperature and moisture data for every profile location and pressure level for assimilation into the ARPS Data Analysis System (ADAS). The AIRS-enhanced analyses were used as initial fields for the Weather Research and Forecast (WRF) system used by the SPORT project for regional weather forecast studies. The ADASWRF system will be run on CONUS domain with an emphasis on the east coast. The preliminary assessment of the impact of the AIRS profiles will focus on quality control issues associated with AIRS, intelligent use of the quality indicators, and forecast verification.

Development of an Impact-Oriented Quantitative Coastal Inundation forecasting and early warning system with social and economic assessment

NASA Astrophysics Data System (ADS)

Fakhruddin, S. H. M.; Babel, Mukand S.; Kawasaki, Akiyuki

2014-05-01

Coastal inundations are an increasing threat to the lives and livelihoods of people living in low-lying, highly-populated coastal areas. According to a World Bank Report in 2005, at least 2.6 million people may have drowned due to coastal inundation, particularly caused by storm surges, over the last 200 years. Forecasting and prediction of natural events, such as tropical and extra-tropical cyclones, inland flooding, and severe winter weather, provide critical guidance to emergency managers and decision-makers from the local to the national level, with the goal of minimizing both human and economic losses. This guidance is used to facilitate evacuation route planning, post-disaster response and resource deployment, and critical infrastructure protection and securing, and it must be available within a time window in which decision makers can take appropriate action. Recognizing this extreme vulnerability of coastal areas to inundation/flooding, and with a view to improve safety-related services for the community, research should strongly enhance today's forecasting, prediction and early warning capabilities in order to improve the assessment of coastal vulnerability and risks and develop adequate prevention, mitigation and preparedness measures. This paper tries to develop an impact-oriented quantitative coastal inundation forecasting and early warning system with social and economic assessment to address the challenges faced by coastal communities to enhance their safety and to support sustainable development, through the improvement of coastal inundation forecasting and warning systems.

The Goes-R Geostationary Lightning Mapper (GLM)

NASA Technical Reports Server (NTRS)

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

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. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved storm diagnostic capability with the Advanced Baseline Imager. The GLM will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) 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 Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. In this paper we will report on new Nowcasting and storm warning applications being developed and evaluated at various NOAA Testbeds.

Comparison of Dst Forecast Models for Intense Geomagnetic Storms

NASA Technical Reports Server (NTRS)

Ji, Eun-Young; Moon, Y.-J.; Gopalswamy, N.; Lee, D.-H.

2012-01-01

We have compared six disturbance storm time (Dst) forecast models using 63 intense geomagnetic storms (Dst <=100 nT) that occurred from 1998 to 2006. For comparison, we estimated linear correlation coefficients and RMS errors between the observed Dst data and the predicted Dst during the geomagnetic storm period as well as the difference of the value of minimum Dst (Delta Dst(sub min)) and the difference in the absolute value of Dst minimum time (Delta t(sub Dst)) between the observed and the predicted. As a result, we found that the model by Temerin and Li gives the best prediction for all parameters when all 63 events are considered. The model gives the average values: the linear correlation coefficient of 0.94, the RMS error of 14.8 nT, the Delta Dst(sub min) of 7.7 nT, and the absolute value of Delta t(sub Dst) of 1.5 hour. For further comparison, we classified the storm events into two groups according to the magnitude of Dst. We found that the model of Temerin and Lee is better than the other models for the events having 100 <= Dst < 200 nT, and three recent models (the model of Wang et al., the model of Temerin and Li, and the model of Boynton et al.) are better than the other three models for the events having Dst <= 200 nT.

Establishing a Numerical Modeling Framework for Hydrologic Engineering Analyses of Extreme Storm Events

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

Chen, Xiaodong; Hossain, Faisal; Leung, L. Ruby

In this study a numerical modeling framework for simulating extreme storm events was established using the Weather Research and Forecasting (WRF) model. Such a framework is necessary for the derivation of engineering parameters such as probable maximum precipitation that are the cornerstone of large water management infrastructure design. Here this framework was built based on a heavy storm that occurred in Nashville (USA) in 2010, and verified using two other extreme storms. To achieve the optimal setup, several combinations of model resolutions, initial/boundary conditions (IC/BC), cloud microphysics and cumulus parameterization schemes were evaluated using multiple metrics of precipitation characteristics. Themore » evaluation suggests that WRF is most sensitive to IC/BC option. Simulation generally benefits from finer resolutions up to 5 km. At the 15km level, NCEP2 IC/BC produces better results, while NAM IC/BC performs best at the 5km level. Recommended model configuration from this study is: NAM or NCEP2 IC/BC (depending on data availability), 15km or 15km-5km nested grids, Morrison microphysics and Kain-Fritsch cumulus schemes. Validation of the optimal framework suggests that these options are good starting choices for modeling extreme events similar to the test cases. This optimal framework is proposed in response to emerging engineering demands of extreme storm events forecasting and analyses for design, operations and risk assessment of large water infrastructures.« less

Forecast for the Remainder of the Leonid Storm Season

NASA Technical Reports Server (NTRS)

Jenniskens, Peter; DeVincenzi, Donald L. (Technical Monitor)

2001-01-01

The dust trails of comet 55P/Tempel-Tuttle lead to Leonid storms on Earth, threatening satellites in orbit. We present a new model that accounts in detail for the observed properties of dust tails evolved by the comet at previous oppositions. The prediction model shows the 1767-dust trail closer to Earth's orbit in 2001 than originally thought; increasing expected peak rates for North America observers. Predictions for the 2002 storms are less affected. We demonstrate that the observed shower profiles can be understood as a projection of the comet lightcurve.

Long-Range Operational Military Forecasts for Iraq

DTIC Science & Technology

2007-03-01

http://www.afccc.af.mil 5 March 2007] .................................................. 4 Figure 3. Primary storm tracks for: (a) June, July, August...Laboratory ETC extratropical cyclone FA forecast accuracy FAR false alarm rate HSS Heidke skill score IO Indian Ocean IOZM Indian Ocean Zonal...precipitation is associated with transient extratropical cyclones (ETCs). Most of Iraq’s terrain is relatively flat with little change in elevation

The GOES-R Proving Ground: 2012 Update

NASA Astrophysics Data System (ADS)

Gurka, J.; Goodman, S. J.; Schmit, T.; Demaria, M.; Mostek, A.; Siewert, C.; Reed, B.

2011-12-01

The Geostationary Operational Environmental Satellite (GOES)-R will provide a great leap forward in observing capabilities, but will also offer a significant challenge to ensure that users are ready to exploit the vast improvements in spatial, spectral, and temporal resolutions. To ensure user readiness, forecasters and other users must have access to prototype advanced products well before launch, and have the opportunity to provide feedback to product developers and computing and communications managers. The operational assessment is critical to ensure that the end products and NOAA's computing and communications systems truly meet their needs in a rapidly evolving environment. The GOES-R Proving Ground (PG) engages the National Weather Service (NWS) forecast, watch and warning community and other agency users in pre-operational demonstrations of select products with GOES-R attributes (enhanced spectral, spatial, and temporal resolution). In the PG, developers and forecasters test and apply algorithms for new GOES-R satellite data and products using proxy and simulated data sets, including observations from current and future satellite instruments (MODIS, AIRS, IASI, SEVIRI, NAST-I, NPP/VIIRS/CrIS, LIS), lightning networks, and computer simulated products. The complete list of products to be evaluated in 2012 will be determined after evaluating results from experiments in 2011 at the NWS' Storm Prediction Center, National Hurricane Center, Aviation Weather Center, Ocean Prediction Center, Hydrometeorological Prediction Center, and from the six NWS regions. In 2012 and beyond, the PG will test and validate data processing and distribution systems and the applications of these products in operational settings. Additionally developers and forecasters will test and apply display techniques and decision aid tools in operational environments. The PG is both a recipient and a source of training. Training materials are developed using various distance training tools in close collaboration with NWS Training Division and its partners at COMET, CIMSS, CIRA and other offices. The training is used to prepare the participants of PG activities, such as the Hazardous Weather Testbed's Spring Experiment and other locations listed above. A key component of the proving ground is two-way interaction, where researchers introduce new products and techniques to forecasters and other scientists. The forecasters and other users then provide feedback and ideas for improved or new products and how to best incorporate these into NOAA's integrated observing and analysis operations. This presentation will provide examples of GOES-R proxy products and forecaster evaluations from experiments at the Storm Prediction Center (SPC), the National Hurricane Center (NHC), the Aviation Weather Center (AWC), and the Alaska Region.

Anchorage Receives Record Snowfall

NASA Technical Reports Server (NTRS)

2002-01-01

The forecast called for flurries, but the snow accumulated on the ground in Anchorage, Alaska, at the rate of 2 inches per hour (5 cm per hour) for much of Saturday, March 16, 2002. By the time the winter storm passed on Sunday afternoon, Anchorage had received 28.6 inches (72.6 cm) of snow, surpassing by far the previous record of 15.6 inches (39.6 cm) set on December 29, 1955. Flights were canceled and schools were closed as a result of the storm. This true-color image of Alaska was acquired by the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), flying aboard the OrbView-2 satellite, on March 18. It appears another large, low-pressure system is heading toward the Anchorage region, which could bring substantially more snowfall. The low-pressure system can be identified by the characteristic spiral pattern of clouds located off Alaska's southwestern coast in this scene.

Cloudsat tropical cyclone database

NASA Astrophysics Data System (ADS)

Tourville, Natalie D.

CloudSat (CS), the first 94 GHz spaceborne cloud profiling radar (CPR), launched in 2006 to study the vertical distribution of clouds. Not only are CS observations revealing inner vertical cloud details of water and ice globally but CS overpasses of tropical cyclones (TC's) are providing a new and exciting opportunity to study the vertical structure of these storm systems. CS TC observations are providing first time vertical views of TC's and demonstrate a unique way to observe TC structure remotely from space. Since December 2009, CS has intersected every globally named TC (within 1000 km of storm center) for a total of 5,278 unique overpasses of tropical systems (disturbance, tropical depression, tropical storm and hurricane/typhoon/cyclone (HTC)). In conjunction with the Naval Research Laboratory (NRL), each CS TC overpass is processed into a data file containing observational data from the afternoon constellation of satellites (A-TRAIN), Navy's Operational Global Atmospheric Prediction System Model (NOGAPS), European Center for Medium range Weather Forecasting (ECMWF) model and best track storm data. This study will describe the components and statistics of the CS TC database, present case studies of CS TC overpasses with complementary A-TRAIN observations and compare average reflectivity stratifications of TC's across different atmospheric regimes (wind shear, SST, latitude, maximum wind speed and basin). Average reflectivity stratifications reveal that characteristics in each basin vary from year to year and are dependent upon eye overpasses of HTC strength storms and ENSO phase. West Pacific (WPAC) basin storms are generally larger in size (horizontally and vertically) and have greater values of reflectivity at a predefined height than all other basins. Storm structure at higher latitudes expands horizontally. Higher vertical wind shear (≥ 9.5 m/s) reduces cloud top height (CTH) and the intensity of precipitation cores, especially in HTC strength storms. Average zero and ten dBZ height thresholds confirm WPAC storms loft precipitation sized particles higher into the atmosphere than in other basins. Two CS eye overpasses (32 hours apart) of a weakening Typhoon Nida in 2009 reveal the collapse of precipitation cores, warm core anomaly and upper tropospheric ice water content (IWC) under steady moderate shear conditions.

Climatology and Predictability of Cool-Season High Wind Events in the New York City Metropolitan and Surrounding Area

NASA Astrophysics Data System (ADS)

Layer, Michael

Damaging wind events not associated with severe convective storms or tropical cyclones can occur over the Northeast U.S. during the cool season and can cause significant problems with transportation, infrastructure, and public safety. These non-convective wind events (NCWEs) events are difficult for operational forecasters to predict in the NYC region as revealed by relatively poor verification statistics in recent years. This study investigates the climatology of NCWEs occurring between 15 September and 15 May over 13 seasons from 2000-2001 through 2012-2013. The events are broken down into three distinct types commonly observed in the region: pre-cold frontal (PRF), post-cold frontal (POF), and nor'easter/coastal storm (NEC) cases. Relationships between observed winds and some atmospheric parameters such as 900 hPa height gradient, 3-hour MSLP tendency, low-level wind profile, and stability are also studied. Overall, PRF and NEC events exhibit stronger height gradients, stronger low-level winds, and stronger low-level stability than POF events. Model verification is also conducted over the 2009-2014 time period using the Short Range Ensemble Forecast system (SREF) from the National Centers for Environmental Prediction (NCEP). Both deterministic and probabilistic verification metrics are used to evaluate the performance of the ensemble during NCWEs. Although the SREF has better forecast skill than most of the deterministic SREF control members, it is rather poorly calibrated, and exhibits a significant overforecasting, or positive wind speed bias in the lower atmosphere.

Dynamics and Predictability of Tropical Cyclone Genesis, Structure and Intensity Change

DTIC Science & Technology

2012-09-30

analyses and forecasts of tropical cyclones, including genesis, intensity change, and extratropical transition. A secondary objective is to understand... storm -centered assimilation algorithm. Basic research in Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the...COMPLETED For the four storms consider (Nuri, Jangmi, Sinlaku, and Hagupit), an 80-member EnKF has been cycled on observations (surface, rawinsondes, GPS

Coastal Storm Model.

DTIC Science & Technology

1976-04-30

hindcasting, whereas a con- stant azimuth and storm velocity are used in forecasting. Tte results of hindcast analysis at several sites are included in... undersea breeze conditions and wave- current interactions in the surf zone; Tech. Report TC-149-4, ONR Contract N00014-69-C-0107, Tetra Tech, Inc., Pasadena...MARYLAND 21043 DEPARTMENT UF GEOSCIENrES PURI)IUL UNIVERSITY -DR. RURERT L. MILLER ___ LAFAYE- TTE , INDIANA 47901 DEPARTMENT OF GEOPHYSICAL SCIENCES

Regional Assessment of Storm-triggered Shall Landslide Risks using the SLIDE (SLope-Infiltration-Distributed Equilibrium) Model

NASA Astrophysics Data System (ADS)

Hong, Y.; Kirschbaum, D. B.; Fukuoka, H.

2011-12-01

The key to advancing the predictability of rainfall-triggered landslides is to use physically based slope-stability models that simulate the dynamical response of the subsurface moisture to spatiotemporal variability of rainfall in complex terrains. An early warning system applying such physical models has been developed to predict rainfall-induced shallow landslides over Java Island in Indonesia and Honduras. The prototyped early warning system integrates three major components: (1) a susceptibility mapping or hotspot identification component based on a land surface geospatial database (topographical information, maps of soil properties, and local landslide inventory etc.); (2) a satellite-based precipitation monitoring system (http://trmm.gsfc.nasa.gov) and a precipitation forecasting model (i.e. Weather Research Forecast); and (3) a physically-based, rainfall-induced landslide prediction model SLIDE (SLope-Infiltration-Distributed Equilibrium). The system utilizes the modified physical model to calculate a Factor of Safety (FS) that accounts for the contribution of rainfall infiltration and partial saturation to the shear strength of the soil in topographically complex terrains. The system's prediction performance has been evaluated using a local landslide inventory. In Java Island, Indonesia, evaluation of SLIDE modeling results by local news reports shows that the system successfully predicted landslides in correspondence to the time of occurrence of the real landslide events. Further study of SLIDE is implemented in Honduras where Hurricane Mitch triggered widespread landslides in 1998. Results shows within the approximately 1,200 square kilometers study areas, the values of hit rates reached as high as 78% and 75%, while the error indices were 35% and 49%. Despite positive model performance, the SLIDE model is limited in the early warning system by several assumptions including, using general parameter calibration rather than in situ tests and neglecting geologic information. Advantages and limitations of this model will be discussed with respect to future applications of landslide assessment and prediction over large scales. In conclusion, integration of spatially distributed remote sensing precipitation products and in-situ datasets and physical models in this prototype system enable us to further develop a regional early warning tool in the future for forecasting storm-induced landslides.

Applying AI tools to operational space environmental analysis

NASA Technical Reports Server (NTRS)

Krajnak, Mike; Jesse, Lisa; Mucks, John

1995-01-01

The U.S. Air Force and National Oceanic Atmospheric Agency (NOAA) space environmental operations centers are facing increasingly complex challenges meeting the needs of their growing user community. These centers provide current space environmental information and short term forecasts of geomagnetic activity. Recent advances in modeling and data access have provided sophisticated tools for making accurate and timely forecasts, but have introduced new problems associated with handling and analyzing large quantities of complex data. AI (Artificial Intelligence) techniques have been considered as potential solutions to some of these problems. Fielding AI systems has proven more difficult than expected, in part because of operational constraints. Using systems which have been demonstrated successfully in the operational environment will provide a basis for a useful data fusion and analysis capability. Our approach uses a general purpose AI system already in operational use within the military intelligence community, called the Temporal Analysis System (TAS). TAS is an operational suite of tools supporting data processing, data visualization, historical analysis, situation assessment and predictive analysis. TAS includes expert system tools to analyze incoming events for indications of particular situations and predicts future activity. The expert system operates on a knowledge base of temporal patterns encoded using a knowledge representation called Temporal Transition Models (TTM's) and an event database maintained by the other TAS tools. The system also includes a robust knowledge acquisition and maintenance tool for creating TTM's using a graphical specification language. The ability to manipulate TTM's in a graphical format gives non-computer specialists an intuitive way of accessing and editing the knowledge base. To support space environmental analyses, we used TAS's ability to define domain specific event analysis abstractions. The prototype system defines events covering reports of natural phenomena such as solar flares, bursts, geomagnetic storms, and five others pertinent to space environmental analysis. With our preliminary event definitions we experimented with TAS's support for temporal pattern analysis using X-ray flare and geomagnetic storm forecasts as case studies. We are currently working on a framework for integrating advanced graphics and space environmental models into this analytical environment.

Increasing Storm Water Capture for Water Supply using Forecast Informed Reservoir Operations (FIRO) in Orange County, California

NASA Astrophysics Data System (ADS)

Hutchinson, A.; Woodside, G.; Ralph, F. M.

2017-12-01

Stormwater represents a significant source of water used by the Orange County Water District (OCWD) to recharge the Orange County groundwater basin. Over the last 20 years, OCWD has captured and recharged an average of 50,000 acre-feet per year (afy) of stormwater. Much of this recharge is made possible by the capture of stormwater in the Prado Dam Conservation Pool. OCWD has and continues to work closely with the US Army Corps of Engineers (USACE) to manage the conservation pool and to increase the amount of water that can be temporarily impounded in the conservation pool. Currently, the Conservation Pool is allowed to rise to elevation 498 ft msl (approx. 10,000 af of storage) during the storm season and to 505 ft msl (approx. 20,000 af of storage) during the non-storm season. OCWD has been working with the USACE on a Feasibility Study to permanently allow for storage of stormwater up to elevation 505 msl year-round. Even though increasing the Conservation Pool will increase the amount of stormwater captured, the weather forecasting used to manage the conservation pool can be improved in order to minimize lost opportunities to capture water or unnecessary releases of water to the ocean. To increase the efficiency of stormwater capture, OCWD is partnering with the Center for Western Weather and Water Extremes (http://cw3e.ucsd.edu/) to study the viability of using Forecast-Informed Reservoir Operations (FIRO) at Prado Dam. FIRO represents the next generation of operating water reservoirs using the best available technology. Moreover, given the importance of atmospheric river (AR) storms on water supplies in California, FIRO represents a methodology to take advantage of our increasing understanding of AR storms which are infrequent but provide a large percentage of total precipitation.

The Hurricane-flood-landslide continuum-forecasting Hurricane effects at landfall

USGS Publications Warehouse

Negri, A.J.; Golden, J.H.; Updike, R.G.

2004-01-01

The integration of remote-sensing and in-situ observations, and assimilation of these observations into high-resolution mesoscale models was described. It was observed that the greatest loss of life and property is the direct result of the storm because of the high winds and heavy rain. The research were conducted to develop a warning system that included satellite observations to track dangerous level of precipitation and hurricane. The focus of the continuum project was to improve the ability to predict the evolution of the Earth system.

Chantal Loses Closed Circulation, Still Poses Threats to Hispaniola

NASA Image and Video Library

2017-12-08

Chantal's satellite presentation has deteriorated markedly this morning and is barely classifiable by the Dvorak Technique. Forecasted strong westerly shear and interactions with land over the next couple of days should cause further weakening of the storm as it transitions back into a tropical wave. Tropical Storm Warnings remain in effect for the entire coast of the Dominican Republic, the entire coast of Haiti, Turks and Caicos and the southeastern Bahamas. This image was taken by GOES West at 1200Z on July 10, 2013. Copy credit: NOAA Photo credit: Credit: NOAA/NASA GOES Project More info about the storm: 1.usa.gov/12mvQcC NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Lightning Sensors for Observing, Tracking and Nowcasting Severe Weather

PubMed Central

Price, Colin

2008-01-01

Severe and extreme weather is a major natural hazard all over the world, often resulting in major natural disasters such as hail storms, tornados, wind storms, flash floods, forest fires and lightning damages. While precipitation, wind, hail, tornados, turbulence, etc. can only be observed at close distances, lightning activity in these damaging storms can be monitored at all spatial scales, from local (using very high frequency [VHF] sensors), to regional (using very low frequency [VLF] sensors), and even global scales (using extremely low frequency [ELF] sensors). Using sensors that detect the radio waves emitted by each lightning discharge, it is now possible to observe and track continuously distant thunderstorms using ground networks of sensors. In addition to the number of lightning discharges, these sensors can also provide information on lightning characteristics such as the ratio between intra-cloud and cloud-to-ground lightning, the polarity of the lightning discharge, peak currents, charge removal, etc. It has been shown that changes in some of these lightning characteristics during thunderstorms are often related to changes in the severity of the storms. In this paper different lightning observing systems are described, and a few examples are provided showing how lightning may be used to monitor storm hazards around the globe, while also providing the possibility of supplying short term forecasts, called nowcasting. PMID:27879700

Development of the physics driver in NOAA Environmental Modeling System (NEMS)

NASA Astrophysics Data System (ADS)

Lei, H.; Iredell, M.; Tripp, P.

2016-12-01

As a key component of the Next Generation Global Prediction System (NGGPS), a physics driver is developed in the NOAA Environmental Modeling System (NEMS) in order to facilitate the research, development, and transition to operations of innovations in atmospheric physical parameterizations. The physics driver connects the atmospheric dynamic core, the Common Community Physics Package and the other NEMS-based forecast components (land, ocean, sea ice, wave, and space weather). In current global forecasting system, the physics driver has incorporated major existing physics packages including radiation, surface physics, cloud and microphysics, ozone, and stochastic physics. The physics driver is also applicable to external physics packages. The structure adjustment in NEMS by separating the PHYS trunk is to create an open physics package pool. This open platform is beneficial to the enhancement of U.S. weather forecast ability. In addition, with the universal physics driver, the NEMS can also be used for specific functions by connecting external target physics packages through physics driver. The test of its function is to connect a physics dust-radiation model in the system. Then the modified system can be used for dust storm prediction and forecast. The physics driver is also developed into a standalone form. This is to facilitate the development works on physics packages. The developers can save instant fields of meteorology data and snapshots from the running system , and then used them as offline driving data fields to test the new individual physics modules or small modifications to current modules. This prevents the run of whole system for every test.

The GOES-R Geostationary Lightning Mapper (GLM)

NASA Astrophysics Data System (ADS)

Goodman, Steven J.; Blakeslee, Richard J.; Koshak, William J.; Mach, Douglas; Bailey, Jeffrey; Buechler, Dennis; Carey, Larry; Schultz, Chris; Bateman, Monte; McCaul, Eugene; Stano, Geoffrey

2013-05-01

The Geostationary Operational Environmental Satellite R-series (GOES-R) is the next block of four satellites to follow the existing GOES constellation currently operating over the Western Hemisphere. Advanced spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved cloud and moisture imagery with the 16-channel Advanced Baseline Imager (ABI). The GLM will map total lightning activity continuously day and night with near-uniform storm-scale spatial resolution of 8 km with a product refresh rate of less than 20 s over the Americas and adjacent oceanic regions in the western hemisphere. 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, an Algorithm Working Group (AWG) Lightning Detection Science and Applications Team developed the Level 2 (stroke and flash) algorithms from the Level 1 lightning event (pixel level) data. Proxy data sets used to develop the GLM operational algorithms as well as cal/val performance monitoring tools were derived from the NASA Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) instruments in low Earth orbit, and from ground-based lightning networks and intensive prelaunch field campaigns. The GLM will produce the same or similar lightning flash attributes provided by the LIS and OTD, and thus extend their combined climatology over the western hemisphere into the coming decades. Science and application development along with preoperational product demonstrations and evaluations at NWS forecast offices and NOAA testbeds will prepare the forecasters to use GLM as soon as possible after the planned launch and checkout of GOES-R in late 2015. New applications will use GLM alone, in combination with the ABI, or integrated (fused) with other available tools (weather radar and ground strike networks, nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing more timely and accurate forecasts and warnings.

Short-Term fo F2 Forecast: Present Day State of Art

NASA Astrophysics Data System (ADS)

Mikhailov, A. V.; Depuev, V. H.; Depueva, A. H.

An analysis of the F2-layer short-term forecast problem has been done. Both objective and methodological problems prevent us from a deliberate F2-layer forecast issuing at present. An empirical approach based on statistical methods may be recommended for practical use. A forecast method based on a new aeronomic index (a proxy) AI has been proposed and tested over selected 64 severe storm events. The method provides an acceptable prediction accuracy both for strongly disturbed and quiet conditions. The problems with the prediction of the F2-layer quiet-time disturbances as well as some other unsolved problems are discussed

Mesoscale aspects of jet streak coupling and implications for the short term forecasting of severe convective storms. [severe environmental storms and mesoscale experiment (SESAME)

NASA Technical Reports Server (NTRS)

Uccellini, L. W.; Kocin, P. J.

1981-01-01

An analysis of a tornado outbreak in Wichita Falls, Texas was analyzed. The coupling of upper and lower tropospheric jet streaks, leading to severe storm outbreaks is illustrated. The high resolution SESAME data sets indicate that mass and momentum adjustments which couple upper and lower tropospheric jets occur within a 3 to 6 hr time frame over a 100 to 500 km domain, and establish the role of isallobaric forcing in the storm development. It is suggested that the output rate of data from the existing 12 hr network be increased to provide better temporal resolution of wind, mass and moisture data.

Latest View of Hurricane Joaquin

NASA Image and Video Library

2017-12-08

Hurricane Joaquin continued to intensify in the Bahamas on October 1 and NASA and NOAA satellites have been providing valuable data on the storm. NASA's GPM and Terra satellites and NOAA's GOES-East satellite provided rainfall, cloud extent, cloud height and other data to forecasters. Joaquin became a major hurricane today, October 1, reaching Category 3 status on the Saffir-Simpson Wind Scale. On October 1 at 1330 UTC (9:30 a.m. EDT) NOAA's GOES-East satellite captured this visible image of Hurricane Joaquin covering the southern Bahamas and extending over southeastern Cuba, and the island of Hispaniola (which includes Haiti and the Dominican Republic). Joaquin's eye had become completely visible now that the storm had reached Category 3 status. On October 1, a Hurricane Warning was in effect for the Central Bahamas, Northwestern Bahamas including the Abacos, Berry Islands, Eleuthera, Grand Bahama Island, and New Providence, The Acklins, Crooked Island, and Mayaguana in the southeastern Bahamas. A Hurricane Watch was in effect for Bimini and Andros Island, and a Tropical Storm Warning was in effect for the remainder of the southeastern Bahamas excluding the Turks and Caicos Islands and Andros Island. According to NHC, at 8 a.m. EDT (1200 UTC), the center of Hurricane Joaquin was located near latitude 23.2 North, longitude 73.7 West. That's just 10 miles (15 km) north of Samana Cays, Bahamas and about 75 miles (120 km) southeast of San Salvador, Bahamas. Joaquin was moving toward the west-southwest near 5 mph (7 kph), and this motion is expected to continue today. NHC noted that a turn toward the west- northwest is forecast tonight (Oct. 1), followed by a turn toward the north and an increase in forward speed on Friday, Oct. 2. On the forecast track, the center of Joaquin will move near or over portions of the central Bahamas today and tonight and pass near or over portions of the northwestern Bahamas on Friday. Maximum sustained winds are near 120 mph (195 km/h) with higher gusts. Joaquin is a category 3 hurricane on the Saffir-Simpson Hurricane Wind Scale. Some strengthening is forecast in the next day or so, with some fluctuations in intensity possible on Friday. Hurricane force winds extend outward up to 35 miles (55 km) from the center and tropical storm force winds extend outward up to 140 miles (220 km). The minimum central pressure just extrapolated by an Air Force Reserve Hurricane Hunter aircraft is 942 millibars. For updated forecasts, watches and warnings visit the National Hurricane Center (NHC) website: www.nhc.noaa.gov. Credit: NASA/NOAA GOES Project NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

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.

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.

JPSS application in a near real time regional numerical forecast system at CIMSS

NASA Astrophysics Data System (ADS)

Li, J.; Wang, P.; Han, H.; Zhu, F.; Schmit, T. J.; Goldberg, M.

2015-12-01

Observations from next generation of environmental sensors onboard the Suomi National Polar-Orbiting Parnership (S-NPP) and its successor, the Joint Polar Satellite System (JPSS), provide us the critical information for numerical weather forecast (NWP). How to better represent these satellite observations and how to get value added information into NWP system still need more studies. Recently scientists from Cooperative Institute of Meteorological Satellite Studies (CIMSS) at University of Wisconsin-Madison have developed a near realtime regional Satellite Data Assimilation system for Tropical storm forecasts (SDAT) (http://cimss.ssec.wisc.edu/sdat). The system is built with the community Gridpoint Statistical Interpolation (GSI) assimilation and advanced Weather Research Forecast (WRF) model. With GSI, SDAT can assimilate all operational available satellite data including GOES, AMSUA/AMSUB, HIRS, MHS, ATMS, AIRS and IASI radiances and some satellite derived products. In addition, some research products, such as hyperspectral IR retrieved temperature and moisture profiles, GOES imager atmospheric motion vector (AMV) and GOES sounder layer precipitable water (LPW), are also added into the system. Using SDAT as a research testbed, studies have been conducted to show how to improve high impact weather forecast by better handling cloud information in satellite data. Previously by collocating high spatial resolution MODIS data with hyperspectral resolution AIRS data, precise clear pixels of AIRS can be identified and some partially or thin cloud contamination from pixels can be removed by taking advantage of high spatial resolution and high accurate MODIS cloud information. The results have demonstrated that both of these strategies have greatly improved the hurricane track and intensity forecast. We recently have extended these methodologies into processing CrIS/VIIRS data. We also tested similar ideas in microwave sounders by the collocation of AMSU/MODIS and ATMS/VIIRS data. The experiments along with other SDAT progresses will be presented in the meeting.

Prediflood: A French research project aiming at developing a road submersion warning system for flash flood prone areas

NASA Astrophysics Data System (ADS)

Naulin, J. P.; Payrastre, O.; Gaume, E.; Delrieu, G.; Arnaud, P.; Lutoff, C.; Vincendon, B.

2010-09-01

Accurate flood forecasts are crucial for an efficient flood event management. Until now, hydro-meteorological forecasts have been mainly used for early-warnings in France (Meteorological and flood vigilance maps) or over the world (Flash-flood guidances). Forecasts are also often limited to the main streams or to specific watersheds with particular assets like hydropower dams, leaving aside large parts of the territory. Distributed hydro-meteorological forecasting models, able to take advantage of the now available high spatial and temporal resolution rainfall measurements, are promising tools for anticipating and quantifying the short term consequences of storm events all over a region. They would be very useful, especially in regions frequently affected by severe storms with complex spatio-temporal patterns. They would provide the necessary information for flood event management services to identify the areas at risk and to take the appropriate safety and rescue measures: prepositioning of rescue means, stopping of the traffic on exposed roads, determination of safe accesses or evacuation routes. Some preliminary tests conducted by the LCPC within the European project FLOODsite have shown encouraging results of a distributed hydro-meteorological forecasting model. It seems possible, despite the limits of the available rainfall measurements and the shortcomings of the rainfall-runoff models, to deliver distributed forecasts of possible local flood consequences - road submersion risk rating at about 5000 different locations over the Gard department in the tested case - with an acceptable level of accuracy. The PreDiFlood project (http://heberge.lcpc.fr/prediflood/) aims at consolidating and extending these first results with the objective to conduct pre-operational tests with possible end-users at the end of the project. Such a tool will not replace, but complement existing flood forecasting approaches in time and space domains that have not been covered until now (short term forecasting at a regional scale). It will produce a completely new type of forecasts and the usefulness of such data for the emergency services for their real-time decision making will be assessed within the project. Beyond the direct operational objectives, this project aims at demonstrating, on a specific application (the now-casting of road submersions), the possibilities and also the limits and hence the needed improvements of tools that are still underused: radar quantitative precipitation estimates but also precipitation now-castings, distributed rainfall-runoff models, and the recent knowledge acquired on flash-floods consequence evaluation as well as event management.

Development of a Seasonal Extratropical Cyclone Activity Outlook for the North Pacific, Bering Sea, and Alaskan Regions

NASA Astrophysics Data System (ADS)

Shippee, N. J.; Atkinson, D. E.; Walsh, J. E.; Partain, J.; Gottschalck, J.; Marra, J. J.

2013-12-01

Storm activity (i.e. 'storminess') and associated forecasting skill in the North Pacific, Bering Sea, and Alaska is relatively well understood on a daily to weekly scale, however, two important elements are missing from current capacity. First, there is no way to predict storm activity at the monthly to seasonal time frame. Second, storm activity is characterized in terms that best serve weather specialists, and which are often not very informative for different sectors of the public. Increasing the utility of forecasts for end users requires consultation with these groups, and can include expressing storm activity in terms of, for example, strong-wind return intervals or ship hull strength. These types of forecasts can provide valuable information for use in community planning, resource allocation, or potential risk assessment. A preliminary study of seasonal storminess predictability in the North Pacific and Alaska regions has shown that a key factor related to the annual variation of seasonal storminess is the strength of the Aleutian Low as measured using indices such as the North Pacific Index (NPI) or Aleutian Low Pressure Index (ALPI). Use of Empirical Orthogonal Function (EOF) analysis to identify patterns in storminess variability indicates that the primary mode of annual variation is found to be best explained by the variation in the strength of the Aleutian Low. NPI and the first component of storm activity for the entire region are found to be are highly correlated (R = 0.83). This result is supported by the works of others such as Rodionov et al. (2007), who note the impact of the strength of the Aleutian Low on storm track and speed. Additionally, the phase of the Pacific Decadal Oscillation (PDO), along with NPI, have been shown to be highly correlated with annual variance in the seasonal storminess for the North Pacific and Alaska. Additional skill has been identified when the phase of the Pacific Decadal Oscillation (PDO) is explicitly considered along with that of the NPI. For example, where the December through March NPI anomaly is negative, indicating a strong Aleutian Low, and PDO anomaly is positive, storminess is increased in the Aleutians and the Bering Sea and storms more rapidly exit the Gulf of Alaska. In similar fashion, when the phases of the NPI and PDO anomaly are switched, the storminess increases into the Gulf of Alaska with slower moving storms and longer residence time in the Gulf of Alaska. Methods used to develop the seasonal outlooks and the overall results of the will be overviewed in this presentation.

The Impact of Microphysics and Planetary Boundary Layer Physics on Model Simulation of U.S. Deep South Summer Convection

NASA Technical Reports Server (NTRS)

McCaul, Eugene W., Jr.; Case, Jonathan L.; Zavodsky, Bradley T.; Srikishen, Jayanthi; Medlin, Jeffrey M.; Wood, Lance

2014-01-01

Inspection of output from various configurations of high-resolution, explicit convection forecast models such as the Weather Research and Forecasting (WRF) model indicates significant sensitivity to the choices of model physics pararneterizations employed. Some of the largest apparent sensitivities are related to the specifications of the cloud microphysics and planetary boundary layer physics packages. In addition, these sensitivities appear to be especially pronounced for the weakly-sheared, multicell modes of deep convection characteristic of the Deep South of the United States during the boreal summer. Possible ocean-land sensitivities also argue for further examination of the impacts of using unique ocean-land surface initialization datasets provided by the NASA Short-term Prediction Research and Transition (SPoRn Center to select NOAAlNWS weather forecast offices. To obtain better quantitative understanding of these sensitivities and also to determine the utility of the ocean-land initialization data, we have executed matrices of regional WRF forecasts for selected convective events near Mobile, AL (MOB), and Houston, TX (HGX). The matrices consist of identically initialized WRF 24-h forecasts using any of eight microphysics choices and any of three planetary boWldary layer choices. The resulting 24 simulations performed for each event within either the MOB or HGX regions are then compared to identify the sensitivities of various convective storm metrics to the physics choices. Particular emphasis is placed on sensitivities of precipitation timing, intensity, and coverage, as well as amount and coverage oflightuing activity diagnosed from storm kinematics and graupel in the mixed phase layer. The results confirm impressions gleaned from study of the behavior of variously configured WRF runs contained in the ensembles produced each spring at the Center for the Analysis and Prediction of Storms, but with the benefit of more straightforward control of the physics package choices. The design of the experiments thus allows for more direct interpretation of the sensitivities to each possible physics combination. The results should assist forecasters in their efforts to anticipate and correct for possible biases in simulated WRF convection patterns, and help the modeling community refine their model parameterizations.

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U. S. Deep South Summer Convection

NASA Technical Reports Server (NTRS)

McCaul, E. W., Jr.; Case, J. L.; Zavodsky, B. T.; Srikishen, J.; Medlin, J. M.; Wood, L.

2014-01-01

Inspection of output from various configurations of high-resolution, explicit convection forecast models such as the Weather Research and Forecasting (WRF) model indicates significant sensitivity to the choices of model physics parameterizations employed. Some of the largest apparent sensitivities are related to the specifications of the cloud microphysics and planetary boundary layer physics packages. In addition, these sensitivities appear to be especially pronounced for the weakly-sheared, multicell modes of deep convection characteristic of the Deep South of the United States during the boreal summer. Possible ocean-land sensitivities also argue for further examination of the impacts of using unique ocean-land surface initialization datasets provided by the NASA Short-term Prediction Research and Transition (SPoRT Center to select NOAA/NWS weather forecast offices. To obtain better quantitative understanding of these sensitivities and also to determine the utility of the ocean-land initialization data, we have executed matrices of regional WRF forecasts for selected convective events near Mobile, AL (MOB), and Houston, TX (HGX). The matrices consist of identically initialized WRF 24-h forecasts using any of eight microphysics choices and any of three planetary boundary layer choices. The resulting 24 simulations performed for each event within either the MOB or HGX regions are then compared to identify the sensitivities of various convective storm metrics to the physics choices. Particular emphasis is placed on sensitivities of precipitation timing, intensity, and coverage, as well as amount and coverage of lightning activity diagnosed from storm kinematics and graupel in the mixed phase layer. The results confirm impressions gleaned from study of the behavior of variously configured WRF runs contained in the ensembles produced each spring at the Center for the Analysis and Prediction of Storms, but with the benefit of more straightforward control of the physics package choices. The design of the experiments thus allows for more direct interpretation of the sensitivities to each possible physics combination. The results should assist forecasters in their efforts to anticipate and correct for possible biases in simulated WRF convection patterns, and help the modeling community refine their model parameterizations.

A 3-month long operational implementation of an ensemble prediction system of storm surge for the city of Venice

NASA Astrophysics Data System (ADS)

Mel, Riccardo; Lionello, Piero

2014-05-01

Advantages of an ensemble prediction forecast (EPF) technique that has been used for sea level (SL) prediction at the Northern Adriatic coast are investigated. The aims is to explore whether EPF is more precise than the traditional Deterministic Forecast (DF) and the value of the added information, mainly on forecast uncertainty. Improving the SL forecast for the city of Venice is of paramount importance for the management and maintenance of this historical city and for operating the movable barriers that are presently being built for its protection. The operational practice is simulated for three months from 1st October to 31st December 2010. The EPF is based on the HYPSE model, which is a standard single-layer nonlinear shallow water model, whose equations are derived from the depth averaged momentum equations and predicts the SL. A description of the model is available in the scientific literature. Forcing of HYPSE are provided by three different sets of 3-hourly ECMWF 10m-wind and MSLP fields: the high resolution meteorological forecast (which is used for the deterministic SL forecast, DF), the control run forecast (CRF, that differs from the DF forecast only for it lower meteorological fields resolution) and the 50 ensemble members of the ECMWF EPS (which are used for the SL-EPS. The resolution of DF fields is T1279 and resolution of both CRF and ECMWF EPS fields is T639 resolution. The 10m wind and MSLP fields have been downloaded at 0.125degs (DF) and 0.25degs(CRF and EPS) and linearly interpolated to the HYPSE grid (which is the same for all simulations). The version of HYPSE used in the SR EPS uses a rectangular mesh grid of variable size, which has the minimum grid step (0.03 degrees) in the northern part of the Adriatic Sea, from where grid step increases with a 1.01 factor in both latitude and longitude (In practice, resolution varies in the range from 3.3 to 7km). Results are analyzed considering the EPS spread, the rms of the simulations, the Brier Skill Score and are compared to observations at tide gauges distributed along the Croatian and Italian coast of the Adriatic Sea. It is shown that the ensemble spread is indeed a reliable indicator of the uncertainty of the storm surge prediction. Further, results show how uncertainty depends on the predicted value of sea level and how it increases with the forecast time range. The accuracy of the ensemble mean forecast is actually larger than that of the deterministic forecast, though the latter is produced by meteorological forcings at higher resolution

Comparison of Ionospheric Parameters during Similar Geomagnetic Storms

NASA Astrophysics Data System (ADS)

Blagoveshchensky, D. V.

2018-03-01

The degree of closeness of ionospheric parameters during one magnetic storm and of the same parameters during another, similar, storm is estimated. Overall, four storms—two pairs of storms close in structure and appearance according to recording of the magnetic field X-component—were analyzed. The examination was based on data from Sodankyla observatory (Finland). The f-graphs of the ionospheric vertical sounding, magnetometer data, and riometer data on absorption were used. The main results are as follows. The values of the critical frequencies foF2, foF1, and foE for different but similar magnetic storms differ insignificantly. In the daytime, the difference is on average 6% (from 0 to 11.1%) for all ionospheric layers. In the nighttime conditions, the difference for foF2 is 4%. The nighttime values of foEs differ on average by 20%. These estimates potentially make it possible to forecast ionospheric parameters for a particular storm.

Local amplification of storm surge by Super Typhoon Haiyan in Leyte Gulf.

PubMed

Mori, Nobuhito; Kato, Masaya; Kim, Sooyoul; Mase, Hajime; Shibutani, Yoko; Takemi, Tetsuya; Tsuboki, Kazuhisa; Yasuda, Tomohiro

2014-07-28

Typhoon Haiyan, which struck the Philippines in November 2013, was an extremely intense tropical cyclone that had a catastrophic impact. The minimum central pressure of Typhoon Haiyan was 895 hPa, making it the strongest typhoon to make landfall on a major island in the western North Pacific Ocean. The characteristics of Typhoon Haiyan and its related storm surge are estimated by numerical experiments using numerical weather prediction models and a storm surge model. Based on the analysis of best hindcast results, the storm surge level was 5-6 m and local amplification of water surface elevation due to seiche was found to be significant inside Leyte Gulf. The numerical experiments show the coherent structure of the storm surge profile due to the specific bathymetry of Leyte Gulf and the Philippines Trench as a major contributor to the disaster in Tacloban. The numerical results also indicated the sensitivity of storm surge forecast.

Tropical cyclone intensities from satellite microwave data

NASA Technical Reports Server (NTRS)

Vonderhaar, T. H.; Kidder, S. Q.

1980-01-01

Radial profiles of mean 1000 mb to 250 mb temperature from the Nimbus 6 scanning microwave spectrometer (SCAMS) were constructed around eight intensifying tropical storms in the western Pacific. Seven storms showed distinct inward temperature gradients required for intensification; the eighth displayed no inward gradient and was decaying 24 hours later. The possibility that satellite data might be used to forecast tropical cyclone turning motion was investigated using estimates obtained from Nimbus 6 SCAMS data tapes of the mean 1000 mb to 250 mb temperature field around eleven tropical storms in 1975. Analysis of these data show that for turning storms, in all but one case, the turn was signaled 24 hours in advance by a significant temperature gradient perpendicular to the storm's path, at a distance of 9 deg to 13 deg in front of the storm. A thresholding technique was applied to the North Central U.S. during the summer to estimate precipitation frequency. except

Severe rainfall prediction systems for civil protection purposes

NASA Astrophysics Data System (ADS)

Comellas, A.; Llasat, M. C.; Molini, L.; Parodi, A.; Siccardi, F.

2010-09-01

One of the most common natural hazards impending on Mediterranean regions is the occurrence of severe weather structures able to produce heavy rainfall. Floods have killed about 1000 people across all Europe in last 10 years. With the aim of mitigating this kind of risk, quantitative precipitation forecasts (QPF) and rain probability forecasts are two tools nowadays available for national meteorological services and institutions responsible for weather forecasting in order to and predict rainfall, by using either the deterministic or the probabilistic approach. This study provides an insight of the different approaches used by Italian (DPC) and Catalonian (SMC) Civil Protection and the results they achieved with their peculiar issuing-system for early warnings. For the former, the analysis considers the period between 2006-2009 in which the predictive ability of the forecasting system, based on the numerical weather prediction model COSMO-I7, has been put into comparison with ground based observations (composed by more than 2000 raingauge stations, Molini et al., 2009). Italian system is mainly focused on regional-scale warnings providing forecasts for periods never shorter than 18 hours and very often have a 36-hour maximum duration . The information contained in severe weather bulletins is not quantitative and usually is referred to a specific meteorological phenomena (thunderstorms, wind gales et c.). Updates and refining have a usual refresh time of 24 hours. SMC operates within the Catalonian boundaries and uses a warning system that mixes both quantitative and probabilistic information. For each administrative region ("comarca") Catalonia is divided into, forecasters give an approximate value of the average predicted rainfall and the probability of overcoming that threshold. Usually warnings are re-issued every 6 hours and their duration depends on the predicted time extent of the storm. In order to provide a comprehensive QPF verification, the rainfall predicted by Mesoscale Model 5 (MM5), the SMC forecast operational model, is compared with the local rain gauge network for year 2008 (Comellas et al., 2010). This study presents benefits and drawbacks of both Italian and Catalonian systems. Moreover, a particular attention is paid on the link between system's predictive ability and the predicted severe weather type as a function of its space-time development.

The Framework of a Coastal Hazards Model - A Tool for Predicting the Impact of Severe Storms

USGS Publications Warehouse

Barnard, Patrick L.; O'Reilly, Bill; van Ormondt, Maarten; Elias, Edwin; Ruggiero, Peter; Erikson, Li H.; Hapke, Cheryl; Collins, Brian D.; Guza, Robert T.; Adams, Peter N.; Thomas, Julie

2009-01-01

The U.S. Geological Survey (USGS) Multi-Hazards Demonstration Project in Southern California (Jones and others, 2007) is a five-year project (FY2007-FY2011) integrating multiple USGS research activities with the needs of external partners, such as emergency managers and land-use planners, to produce products and information that can be used to create more disaster-resilient communities. The hazards being evaluated include earthquakes, landslides, floods, tsunamis, wildfires, and coastal hazards. For the Coastal Hazards Task of the Multi-Hazards Demonstration Project in Southern California, the USGS is leading the development of a modeling system for forecasting the impact of winter storms threatening the entire Southern California shoreline from Pt. Conception to the Mexican border. The modeling system, run in real-time or with prescribed scenarios, will incorporate atmospheric information (that is, wind and pressure fields) with a suite of state-of-the-art physical process models (that is, tide, surge, and wave) to enable detailed prediction of currents, wave height, wave runup, and total water levels. Additional research-grade predictions of coastal flooding, inundation, erosion, and cliff failure will also be performed. Initial model testing, performance evaluation, and product development will be focused on a severe winter-storm scenario developed in collaboration with the Winter Storm Working Group of the USGS Multi-Hazards Demonstration Project in Southern California. Additional offline model runs and products will include coastal-hazard hindcasts of selected historical winter storms, as well as additional severe winter-storm simulations based on statistical analyses of historical wave and water-level data. The coastal-hazards model design will also be appropriate for simulating the impact of storms under various sea level rise and climate-change scenarios. The operational capabilities of this modeling system are designed to provide emergency planners with the critical information they need to respond quickly and efficiently and to increase public safety and mitigate damage associated with powerful coastal storms. For instance, high resolution local models will predict detailed wave heights, breaking patterns, and current strengths for use in warning systems for harbor-mouth navigation and densely populated coastal regions where beach safety is threatened. The offline applications are intended to equip coastal managers with the information needed to manage and allocate their resources effectively to protect sections of coast that may be most vulnerable to future severe storms.

Multi-spacecraft testing of time-dependent interplanetary MHD models for operational forecasting of geomagnetic storms

NASA Technical Reports Server (NTRS)

Dryer, M.; Smith, Z. K.

1989-01-01

An MHD 2-1/2D, time-dependent model is used, together with observations of six solar flares during February 3-7, 1986, to demonstrate global, large-scale, compound disturbances in the solar wind over a wide range of heliolongitudes. This scenario is one that is likely to occur many times during the cruise, possibly even encounter, phases of the Multi-Comet Mission. It is suggested that a model such as this one should be tested with multi-spacecraft data (such as the MCM and earth-based probes) with several goals in view: (1) utility of the model for operational real-time forecasting of geomagnetic storms, and (2) scientific interpretation of certain forms of cometary activities and their possible association with solar-generated activity.

The coming megafloods

USGS Publications Warehouse

Dettinger, Michael D.; Ingram, B. Lynn

2013-01-01

Scientists who created a simulated megastorm, called ARkStorm, that was patterned after the 1861 flood but was less severe, found that such a torrent could force more than a million people to evacuate and cause $400 billion in losses if it happened in California today. Forecasters are getting better at predicting the arrival of atmospheric rivers, which will improve warnings about flooding from the common storms and about the potential for catastrophe from a megastorm.

Storm Prediction Center May 27, 2018 1730 UTC Day 2 Convective Outlook

Science.gov Websites

services. < Day 1 Outlook Day 3 Outlook > May 27, 2018 1730 UTC Day 2 Convective Outlook Updated: Sun May 27 17:24:17 UTC 2018 (Print Version | 20180527 1730Z Day 2 shapefile | 20180527 1730Z Day JavaScript/Active Scripting. Forecast Discussion SPC AC 271724 Day 2 Convective Outlook NWS Storm Prediction

Storm Prediction Center May 28, 2018 0100 UTC Day 1 Convective Outlook

Science.gov Websites

services. Day 2 Outlook > May 28, 2018 0100 UTC Day 1 Convective Outlook Updated: Mon May 28 01:01:01 UTC 2018 (Print Version | 20180528 0100Z Day 1 shapefile | 20180528 0100Z Day 1 KML ) Probabilistic to . Forecast Discussion SPC AC 280101 Day 1 Convective Outlook NWS Storm Prediction Center Norman OK 0801 PM

PAI-OFF: A new proposal for online flood forecasting in flash flood prone catchments

NASA Astrophysics Data System (ADS)

Schmitz, G. H.; Cullmann, J.

2008-10-01

SummaryThe Process Modelling and Artificial Intelligence for Online Flood Forecasting (PAI-OFF) methodology combines the reliability of physically based, hydrologic/hydraulic modelling with the operational advantages of artificial intelligence. These operational advantages are extremely low computation times and straightforward operation. The basic principle of the methodology is to portray process models by means of ANN. We propose to train ANN flood forecasting models with synthetic data that reflects the possible range of storm events. To this end, establishing PAI-OFF requires first setting up a physically based hydrologic model of the considered catchment and - optionally, if backwater effects have a significant impact on the flow regime - a hydrodynamic flood routing model of the river reach in question. Both models are subsequently used for simulating all meaningful and flood relevant storm scenarios which are obtained from a catchment specific meteorological data analysis. This provides a database of corresponding input/output vectors which is then completed by generally available hydrological and meteorological data for characterizing the catchment state prior to each storm event. This database subsequently serves for training both a polynomial neural network (PoNN) - portraying the rainfall-runoff process - and a multilayer neural network (MLFN), which mirrors the hydrodynamic flood wave propagation in the river. These two ANN models replace the hydrological and hydrodynamic model in the operational mode. After presenting the theory, we apply PAI-OFF - essentially consisting of the coupled "hydrologic" PoNN and "hydrodynamic" MLFN - to the Freiberger Mulde catchment in the Erzgebirge (Ore-mountains) in East Germany (3000 km 2). Both the demonstrated computational efficiency and the prediction reliability underline the potential of the new PAI-OFF methodology for online flood forecasting.

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

Jordanova, Vania K

Understanding the response at Earth of the Sun's varying energy output and forecasting geomagnetic activity is of central interest to space science, since intense geomagnetic storms may cause severe damages on technological systems and affect communications. Episodes of southward (Bz

Real-time validation of the Dst Predictor model

USGS Publications Warehouse

McCollough, James P.; Young, Shawn L.; Rigler, E. Joshua; Simpson, Hal A.

2015-01-01

The Dst Predictor model, which has been running real-time in the Space Weather Analysis and Forecast System (SWAFS), provides 1-hour and 4-hour forecasts of the Dst index. This is useful for awareness of impending geomagnetic activity, as well as driving other real-time models that use Dst as an input. In this report, we examine the performance of this forecast model in detail. When validating indices it should be noted that performance is only with respect to a reference index as they are derived quantities assumed to reflect a state of the magnetosphere that cannot be directly measured. In this case U.S. Geological Survey (USGS) Definitive Dst is the reference index (Section 3). Whether or not the model better reflects the actual activity level is nearly impossible to discern and is outside the scope of this report. We evaluate the performance of the model by computing continuous predictant skill scores against USGS Definitive Dst values as “observations” (Section 4.2). The two sets of data are not well-correlated for both 1-hour and 4-hour forecasts. The Dst Predictor Prediction Efficiency for both the 1- and 4-hour forecasts suggests poor performance versus the climatological mean. However, the skill score against a nowcast persistence model is positive, suggesting value added by the Dst Predictor model. We further examine statistics for storm times (Section 4.3) with similar results: nowcast persistence performs worse than Dst Predictor.  Dst Predictor is superior to the nowcast persistence model for the metric used in this study. We recommend continued use of the DstPredictor model for 1-and4-hour Dst predictions along with active study of other Dst forecast models that do not rely on nowcast inputs (Section 6). The lack of certified requirements makes further recommendations difficult. A study of how the error in Dst translates to error in models and a better understanding of operational needs for magnetic storm warning are needed to determine such requirements. Nowcast persistence is often hard to beat for short term forecasts and specification and Dst Predictor clearly performs well against that standard (with 1-hour and 4-hour skill-scores of 0.233 and 0.485 respectively), although poor in absolute terms (with1-hourand4-hour prediction efficiencies of-64.6and-43.1, respectively).

Utility of CrIS/ATMS profiles to diagnose extratropical transition

NASA Astrophysics Data System (ADS)

Berndt, Emily; Folmer, Michael

2018-03-01

Anticipating changes in hurricane intensity can be challenging in data sparse regions of the North Atlantic Ocean. Hyperspectral infrared retrieved profiles have the potential to provide a wealth of information about the vertical structure of thermodynamic characteristics of the atmosphere such as temperature and moisture which can impact hurricane intensity. Increased forecaster situational awareness and identification of moist or dry layers in the near-storm environment can indicate impending changes in storm intensity. This investigation demonstrates the utility and value of hyperspectral infrared retrieved profiles to diagnose thermodynamic characteristics of the near-storm environment to anticipate changes in hurricane intensity.

Space weather forecasting with a Multimodel Ensemble Prediction System (MEPS)

NASA Astrophysics Data System (ADS)

Schunk, R. W.; Scherliess, L.; Eccles, V.; Gardner, L. C.; Sojka, J. J.; Zhu, L.; Pi, X.; Mannucci, A. J.; Butala, M.; Wilson, B. D.; Komjathy, A.; Wang, C.; Rosen, G.

2016-07-01

The goal of the Multimodel Ensemble Prediction System (MEPS) program is to improve space weather specification and forecasting with ensemble modeling. Space weather can have detrimental effects on a variety of civilian and military systems and operations, and many of the applications pertain to the ionosphere and upper atmosphere. Space weather can affect over-the-horizon radars, HF communications, surveying and navigation systems, surveillance, spacecraft charging, power grids, pipelines, and the Federal Aviation Administration (FAA's) Wide Area Augmentation System (WAAS). Because of its importance, numerous space weather forecasting approaches are being pursued, including those involving empirical, physics-based, and data assimilation models. Clearly, if there are sufficient data, the data assimilation modeling approach is expected to be the most reliable, but different data assimilation models can produce different results. Therefore, like the meteorology community, we created a Multimodel Ensemble Prediction System (MEPS) for the Ionosphere-Thermosphere-Electrodynamics (ITE) system that is based on different data assimilation models. The MEPS ensemble is composed of seven physics-based data assimilation models for the ionosphere, ionosphere-plasmasphere, thermosphere, high-latitude ionosphere-electrodynamics, and middle to low latitude ionosphere-electrodynamics. Hence, multiple data assimilation models can be used to describe each region. A selected storm event that was reconstructed with four different data assimilation models covering the middle and low latitude ionosphere is presented and discussed. In addition, the effect of different data types on the reconstructions is shown.

The Impact of Cross-track Infrared Sounder (CrIS) Cloud-Cleared Radiances on Hurricane Joaquin (2015) and Matthew (2016) Forecasts

NASA Astrophysics Data System (ADS)

Wang, Pei; Li, Jun; Li, Zhenglong; Lim, Agnes H. N.; Li, Jinlong; Schmit, Timothy J.; Goldberg, Mitchell D.

2017-12-01

Hyperspectral infrared (IR) sounders provide high vertical resolution atmospheric sounding information that can improve the forecast skill in numerical weather prediction. Commonly, only clear radiances are assimilated, because IR sounder observations are highly affected by clouds. A cloud-clearing (CC) technique, which removes the cloud effects from an IR cloudy field of view (FOV) and derives the cloud-cleared radiances (CCRs) or clear-sky equivalent radiances, can be an alternative yet effective way to take advantage of the thermodynamic information from cloudy skies in data assimilation. This study develops a Visible Infrared Imaging Radiometer Suite (VIIRS)-based CC method for deriving Cross-track Infrared Sounder (CrIS) CCRs under partially cloudy conditions. Due to the lack of absorption bands on VIIRS, two important quality control steps are implemented in the CC process. Validation using VIIRS clear radiances indicates that the CC method can effectively obtain the CrIS CCRs for FOVs with partial cloud cover. To compare the impacts from assimilation of CrIS original radiances and CCRs, three experiments are carried out on two storm cases, Hurricane Joaquin (2015) and Hurricane Matthew (2016), using Gridpoint Statistical Interpolation assimilation system and Weather Research and Forecasting-Advanced Research Version models. At the analysis time, more CrIS observations are assimilated when using CrIS CCRs than with CrIS original radiances. Comparing temperature, specific humidity, and U/V winds with radiosondes indicates that the data impacts are growing larger with longer time forecasts (beyond 72 h forecast). Hurricane track forecasts also show improvements from the assimilation of CrIS CCRs due to better weather system forecasts. The impacts of CCRs on intensity are basically neutral with mixed positive and negative results.

Rainfall and Extratropical Transition of Tropical Cyclones: Simulation, Prediction, and Projection

NASA Astrophysics Data System (ADS)

Liu, Maofeng

Rainfall and associated flood hazards are one of the major threats of tropical cyclones (TCs) to coastal and inland regions. The interaction of TCs with extratropical systems can lead to enhanced precipitation over enlarged areas through extratropical transition (ET). To achieve a comprehensive understanding of rainfall and ET associated with TCs, this thesis conducts weather-scale analyses by focusing on individual storms and climate-scale analyses by focusing on seasonal predictability and changing properties of climatology under global warming. The temporal and spatial rainfall evolution of individual storms, including Hurricane Irene (2011), Hurricane Hanna (2008), and Hurricane Sandy (2012), is explored using the Weather Research and Forecast (WRF) model and a variety of hydrometeorological datasets. ET and Orographic mechanism are two key players in the rainfall distribution of Irene over regions experiencing most severe flooding. The change of TC rainfall under global warming is explored with the Forecast-oriented Low Ocean Resolution (FLOR) climate model under representative concentration pathway (RCP) 4.5 scenario. Despite decreased TC frequency, FLOR projects increased landfalling TC rainfall over most regions of eastern United States, highlighting the risk of increased flood hazards. Increased storm rain rate is an important player of increased landfalling TC rainfall. A higher atmospheric resolution version of FLOR (HiFLOR) model projects increased TC rainfall at global scales. The increase of TC intensity and environmental water vapor content scaled by the Clausius-Clapeyron relation are two key factors that explain the projected increase of TC rainfall. Analyses on the simulation, prediction, and projection of the ET activity with FLOR are conducted in the North Atlantic. FLOR model exhibits good skills in simulating many aspects of present-day ET climatology. The 21st-century-projection under RCP4.5 scenario demonstrates the dominant role of ET events on the projected increase of TC frequency in the eastern North Atlantic, highlighting increased exposure of the northeastern United States and Western Europe to storm hazards. Retrospective seasonal forecast experiments demonstrate the skill of HiFLOR in predicting basinwide and regional ET frequency. This skill, however, is not seen in the seasonal prediction of ET rate. More work on the property of signal-to-noise ratio of ET rate is needed.

Assimilating InSAR Maps of Water Vapor to Improve Heavy Rainfall Forecasts: A Case Study With Two Successive Storms

NASA Astrophysics Data System (ADS)

Mateus, Pedro; Miranda, Pedro M. A.; Nico, Giovanni; Catalão, João.; Pinto, Paulo; Tomé, Ricardo

2018-04-01

Very high resolution precipitable water vapor maps obtained by the Sentinel-1 A synthetic aperture radar (SAR), using the SAR interferometry (InSAR) technique, are here shown to have a positive impact on the performance of severe weather forecasts. A case study of deep convection which affected the city of Adra, Spain, on 6-7 September 2015, is successfully forecasted by the Weather Research and Forecasting model initialized with InSAR data assimilated by the three-dimensional variational technique, with improved space and time distributions of precipitation, as observed by the local weather radar and rain gauge. This case study is exceptional because it consisted of two severe events 12 hr apart, with a timing that allows for the assimilation of both the ascending and descending satellite images, each for the initialization of each event. The same methodology applied to the network of Global Navigation Satellite System observations in Iberia, at the same times, failed to reproduce observed precipitation, although it also improved, in a more modest way, the forecast skill. The impact of precipitable water vapor data is shown to result from a direct increment of convective available potential energy, associated with important adjustments in the low-level wind field, favoring its release in deep convection. It is suggested that InSAR images, complemented by dense Global Navigation Satellite System data, may provide a new source of water vapor data for weather forecasting, since their sampling frequency could reach the subdaily scale by merging different SAR platforms, or when future geosynchronous radar missions become operational.

Using HPC within an operational forecasting configuration

NASA Astrophysics Data System (ADS)

Jagers, H. R. A.; Genseberger, M.; van den Broek, M. A. F. H.

2012-04-01

Various natural disasters are caused by high-intensity events, for example: extreme rainfall can in a short time cause major damage in river catchments, storms can cause havoc in coastal areas. To assist emergency response teams in operational decisions, it's important to have reliable information and predictions as soon as possible. This starts before the event by providing early warnings about imminent risks and estimated probabilities of possible scenarios. In the context of various applications worldwide, Deltares has developed an open and highly configurable forecasting and early warning system: Delft-FEWS. Finding the right balance between simulation time (and hence prediction lead time) and simulation accuracy and detail is challenging. Model resolution may be crucial to capture certain critical physical processes. Uncertainty in forcing conditions may require running large ensembles of models; data assimilation techniques may require additional ensembles and repeated simulations. The computational demand is steadily increasing and data streams become bigger. Using HPC resources is a logical step; in different settings Delft-FEWS has been configured to take advantage of distributed computational resources available to improve and accelerate the forecasting process (e.g. Montanari et al, 2006). We will illustrate the system by means of a couple of practical applications including the real-time dynamic forecasting of wind driven waves, flow of water, and wave overtopping at dikes of Lake IJssel and neighboring lakes in the center of The Netherlands. Montanari et al., 2006. Development of an ensemble flood forecasting system for the Po river basin, First MAP D-PHASE Scientific Meeting, 6-8 November 2006, Vienna, Austria.

Comparison of the Effects of RAS vs. Kain-Fritsch Convective Schemes on Katrina Forecasts with GEOS-5

NASA Technical Reports Server (NTRS)

Miller, Timothy L.; Cohen, Charles; Paxton, Jessica; Robertson, F. R. (Pete)

2009-01-01

Global forecasts were made with the 0.25-degree latitude version of GEOS-5, with the RAS scheme and with the Kain-Fritsch scheme. Examination was made of the Katrina (2005) hurricane simulation. Replacement of the RAS convective scheme with the K-F scheme results in a much more vigorous Katrina, closer to reality. Still, the result is not as vigorous as reality. In terms of wind maximum, the gap was closed by 50%. The result seems to be due to the RAS scheme drying out the boundary layer, thus hampering the grid-scale secondary circulation and attending cyclone development. The RAS case never developed a full warm core, whereas the K-F case did. Not shown here: The K-F scheme also resulted in a more vigorous storm than when GEOS-5 is run with no convective parameterization. Also not shown: An experiment in which the RAS firing level was moved up by 3 model levels resulted in a stronger, warm-core storm, though not as strong as the K-F case. Effects on storm track were noticed, but not studied.

The forecast of coastal recession in the eastern gulf of Finland for the twenty-first century

NASA Astrophysics Data System (ADS)

Leont'yev, I. O.; Ryabchuk, D. V.; Sergeev, A. Yu.; Kovaleva, O. A.

2015-05-01

The evolution of a significant part of the coast in the study area is determined by extreme storm surges eroding the upper part of dunes and inducing coastal recession. In order to forecast the recession a special method using numerical modelling of storm-induced changes in the coastal profiles based on the CROSS-P model is used. The response of the shoreline profile to sea-level rise is estimated using the Bruun rule. Three types of future coastal evolution are distinguished depending on slope of an active part of the profile. It is shown that if the most probable patterns of storm activity and sea level rise occur then the relatively steep coasts in an area from Komarovo to Solnechnoe will retreat by 302-40 meters. Recession of less steep coasts (Ushkovo, south Kotlin, and Petrodvorets) is expected to be 10-20 meters, whereas the extremely gently dipping coasts (in the vicinity of Sestroretsk and near the northern end of the St. Petersburg Flood Protection Complex (FPC)) will retreat by 50-100 m.

A method for determining average beach slope and beach slope variability for U.S. sandy coastlines

USGS Publications Warehouse

Doran, Kara S.; Long, Joseph W.; Overbeck, Jacquelyn R.

2015-01-01

The U.S. Geological Survey (USGS) National Assessment of Hurricane-Induced Coastal Erosion Hazards compares measurements of beach morphology with storm-induced total water levels to produce forecasts of coastal change for storms impacting the Gulf of Mexico and Atlantic coastlines of the United States. The wave-induced water level component (wave setup and swash) is estimated by using modeled offshore wave height and period and measured beach slope (from dune toe to shoreline) through the empirical parameterization of Stockdon and others (2006). Spatial and temporal variability in beach slope leads to corresponding variability in predicted wave setup and swash. For instance, seasonal and storm-induced changes in beach slope can lead to differences on the order of 1 meter (m) in wave-induced water level elevation, making accurate specification of this parameter and its associated uncertainty essential to skillful forecasts of coastal change. A method for calculating spatially and temporally averaged beach slopes is presented here along with a method for determining total uncertainty for each 200-m alongshore section of coastline.

Analysis of ionosphere variability over low-latitude GNSS stations during 24th solar maximum period

NASA Astrophysics Data System (ADS)

Venkata Ratnam, D.; Sivavaraprasad, G.; Latha Devi, N. S. M. P.

2017-07-01

Global Positioning System (GPS) is a remote sensing tool of space weather and ionospheric variations. However, the interplanetary space-dependent drifts in the ionospheric irregularities cause predominant ranging errors in the GPS signals. The dynamic variability of the low-latitude ionosphere is an imperative threat to the satellite-based radio communication and navigation ranging systems. The study of temporal and spatial variations in the ionosphere has triggered new investigations in modelling, nowcasting and forecasting the ionospheric variations. Hence, in this paper, the dynamism in the day-to-day, month-to-month and seasonal variability of the ionospheric Total Electron Content (TEC) has been explored during the solar maximum period, January-December 2013, of the 24th solar cycle. The spatial and temporal variations of the ionosphere are analysed using the TEC values derived from three Indian low-latitude GPS stations, namely, Bengaluru, Guntur and Hyderabad, separated by 13-18° in latitude and 77-81° in longitude. The observed regional GPS-TEC variations are compared with the predicted TEC values of the International Reference Ionosphere (IRI-2012 and 2007) models. Ionospheric parameters such as Vertical TEC (VTEC), relative TEC deviation index and monthly variations in the grand-mean of ionosphere TEC and TEC intensity, along with the upper and lower quartiles, are adopted to investigate the ionosphere TEC variability during quiet and disturbed days. The maximum ionospheric TEC variability is found during March and September equinoxes, followed by December solstice while the minimum variability is observed during June solstice. IRI models are in reasonable agreement with GPS TEC but are overestimating during dawn hours (01:00-06:00 LT) as compared to the dusk hours. Higher percentage deviations are observed during equinoctial months than summer over EIA stations, Guntur and Hyderabad. GPS TEC variations are overestimated during dawn hours for all the seasons over Bengaluru. It has also been observed that positive storm effect (enhancement of TEC) is observed during the main phase of the March storm, 2013 (March 16-18, 2013) while both positive and negative storm effects (depletion of TEC) are registered during the main phase of the June storm, 2013 (June 28-30, 2013) at Bengaluru and Guntur, respectively. IRI-2012 model has slightly large discrepancies with the GPS-VTEC compared with the IRI-2007 model during the June storm, 2013 over Guntur station. This analysis highlights the importance of upgrading the IRI models due to their discrepancies during quiet and disturbed states of the ionosphere and developing an early warning forecast system to alert about ionosphere variability.

GOES-S NASA Social

NASA Image and Video Library

2018-02-28

A.J. Sandora, Lockheed Martin's GOES-R Series Mechanical Operations Assembly, Test and Launch Operations (ATLO) manager, speaks to members of social media in the Kennedy Space Center’s Press Site auditorium. The briefing focused on the National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. Built by Lockheed Martin Space Systems of Littleton, Colorado, the spacecraft is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

Using Model Helicopters for Meteorological Observations in Support of Tornado Forecasting

NASA Astrophysics Data System (ADS)

Harrison, William; Roscoe, Bryan; Schafer, David; Bluestein, Howard; Lary, David

2012-10-01

In order to gain a better understanding of the physical factors involved in tornadogenesis, a complete 3-D profile of winds, temperature, and humidity in the forward-flank and rear-flank gust front regions in supercells is required. Conventional methods of making comparative measurements in and around storms are very limited. Measurements that comprehensively profile the boundary layer winds and thermodynamics are valuable but rare. A better understanding of the physical properties in these boundary layers will improve forecasts and increase warning times in affected areas. Remote-controlled model helicopters are a uniquely qualified platform for this application, allowing us to fully profile these boundary layers. Our system will consist of a swarm of autonomous acrobatic helicopters, each outfitted with temperature, pressure, humidity, and wind speed sensors.

Tropical cyclones in the North American Regional Reanalysis: The impact of satellite-derived precipitation over ocean

NASA Astrophysics Data System (ADS)

Zick, Stephanie E.; Matyas, Corene J.

2015-09-01

Continued advancement in the realm of tropical cyclone (TC) forecasting requires a more accurate depiction of these storms at model initialization. This study examines the impact of precipitation assimilation on the representation of TCs in the North American Regional Reanalysis before and after the 2004 introduction of precipitation assimilation over ocean in the vicinity of TCs. The probability distribution function of rainfall rates indicates that light (heavy) precipitation was overforecast (underforecast) in the early time period. Since the precipitation assimilation is applied through an adjustment to the latent heating distribution, the data assimilation system in the later time period initializes a low-level moisture and heating profile that is more conducive to the initiation of deep convection and the generation of precipitation. Consequently, the deep convection and enhanced latent heat release lead to a more robust warm-core temperature perturbation and a better developed secondary circulation, which supplies the TC with larger quantities of moisture from the large-scale environment. Furthermore, the evolution of TC size, which was objectively estimated though the radius of outermost closed isobar, is significantly more skillful (p < 0.05) in post-2003 storms. Based on this study, precipitation assimilation leads to a better analysis of temperature, winds, and moisture in the vicinity of TCs, resulting in improved representations of the water budget and storm life cycle. Therefore, we conclude that efforts toward the development of precipitation assimilation techniques from radar and satellite data sets will be valuable toward the construction of improved TC forecasting tools with more authentic TC representation.

The use of coastal altimetry to support storm surge studies in project eSurge

NASA Astrophysics Data System (ADS)

Cipollini, P.; Harwood, P.; Snaith, H.; Vignudelli, S.; West, L.; Zecchetto, S.; Donlon, C.

2012-04-01

One of the most promising applications of the new field of coastal altimetry, i.e. the discipline aiming to recover meaningful estimates of geophysical parameters (sea level, significant wave height and wind speed) from satellite altimeter data in the coastal zone, is the study of storm surges. The understanding and realistic modelling of surges supports both preparation and mitigation activities and should eventually bring enormous societal benefits, especially to some of the world's poorest countries (like Bangladesh). Earth Observation data have an important role to play in storm surge monitoring and forecasting, but the full uptake of these data by users (such as environmental agencies and tidal prediction centres) must first be encouraged by showcasing their usefulness, and then supported by providing easy access. Having recognized the above needs, The European Space Agency has recently launched a Data User Element (DUE) project called eSurge. The main purposes of eSurge are a) to contribute to an integrated approach to storm surge, wave, sea-level and flood forecasting through Earth Observation, as part of a wider optimal strategy for building an improved forecast and early warning capability for coastal inundation; and b) to increase the use of the advanced capabilities of ESA and other satellite data for storm surge applications. The project is led by Logica UK, with NOC (UK), DMI (Denmark), CMRC (Ireland) and KNMI (Netherlands) as scientific partners. A very important component of eSurge is the development, validation and provision of dedicated coastal altimetry products, which is the focus of the present contribution. Coastal altimetry has a prominent role to play as it measures the total water level envelope directly, and this is one of the key quantities required by storm surge applications and services. But it can also provide important information on the wave field in the coastal strip, which helps the development of more realistic wave models that in turn can be used to improve the forecast of wave setup and overtopping processes. We will present examples of how altimetry has captured a few significant surge events in European Seas, and we will describe how a multi-mission coastal altimetry processor is going to be integrated in the eSurge system. The delayed-time reprocessed coastal altimetry data will be blended with tide gauge data to extract the main modes of variability in the coastal regions. Then data from the tide gauges can be used to estimate water level in real time, based on the modes of variability found. In a later phase of the project, the eSurge coastal altimetry processor will be extended to be able to ingest Near-Real-time (NRT) raw altimetric waveforms and generate the relevant NRT products, a definite first for coastal altimetry. The pilot regions for this application will be the European Seas (where an area of specific interest is the Northern Adriatic, which is being investigated within a related initiative called eSurge-Venice) and the North Indian Ocean. In summary, we expect eSurge to be one of the first pre-operational applications of coastal altimetry and a proof of the benefits to society that can be brought by this relatively new branch of marine remote sensing.

Ionospheric behaviour during storm recovery phase

NASA Astrophysics Data System (ADS)

Buresova, D.; Lastovicka, J.; Boska, J.; Sindelarova, T.; Chum, J.

2012-04-01

Intensive ionospheric research, numerous multi-instrumental observations and large-scale numerical simulations of ionospheric F region response to magnetic storm-induced disturbances during the last several decades were primarily focused on the storm main phase, in most cases covering only a few hours of the recovery phase following after storm culmination. Ionospheric behaviour during entire recovery phase still belongs to not sufficiently explored and hardly predictable features. In general, the recovery phase is characterized by an abatement of perturbations and a gradual return to the "ground state" of ionosphere. However, observations of stormy ionosphere show significant departures from the climatology also within this phase. This paper deals with the quantitative and qualitative analysis of the ionospheric behaviour during the entire recovery phase of strong-to-severe magnetic storms at middle latitudes for nowadays and future modelling and forecasting purposes.

Tropical-Like Cyclones in the Mediterranean: The case of Medicane "Qendresa" in 2014

NASA Astrophysics Data System (ADS)

Patlakas, P.; Nenes, A.; Nikolopoulos, E. I.; Kallos, G. B.

2016-12-01

Intense storm characteristics and structure that resemble hurricanes can periodically form over the Mediterranean Sea. These so-called Medicanes form in a similar fashion to tropical cyclones, despite the different climatic characteristics between the Mediterranean Sea and the tropical oceans. Unlike their tropical counterparts, Medicanes are poorly understood and studied. The recurrence interval of such extreme conditions is lower than tropical cyclones, but they can cause significant damages to property and pose threat to human lives. The frequency and intensity of Medicanes, in response to climate change, is also completely unknown. One recent event is the case of Medicane "Qendresa" that took place during 7-8 November 2014. It was generated in the maritime area between Italy and Tunisia and dissipated within about 48 hours. Winds and wind gusts reached 111 km/h and 154 km/h respectively, while the lowest recorded pressure reached the value of 978.6 hPa. At the same time, a 24h accumulated precipitation of more than 100 mm was recorded in the SE part of Sicily during the second day of the event. The contact of the system with Sicily and the exhibited stationarity caused the large amounts of precipitating water over the island. The quick dissipation can be attributed to the relatively quick landfall that severely reduced latent heat supply from the warm sea surface. The formation of a cyclone was forecasted by the most of operational models but its characteristics deviated significantly. In this study we utilize a state-of-the-art atmospheric model, the RAMS-ICLAMS Modeling System, to simulate the full lifecycle of the storm and study in detail the underlying mechanisms associated with the initiation, intensification and dissipation of the system. A series of sensitivity simulations define the key drivers behind the formation and development of Medicanes. The simulations revealed the high sensitivity of these systems to different dynamical and microphysical characteristics. Nevertheless, the simulations system employed here displayed a remarkable level of agreement in terms of structure and storm characteristics when compared to available in-situ measurements and satellite data. We conclude with important conclusions on the main factors that contribute to model fidelity and potential future forecasts.

Development of a multi-sensor based urban discharge forecasting system using remotely sensed data: A case study of extreme rainfall in South Korea

NASA Astrophysics Data System (ADS)

Yoon, Sunkwon; Jang, Sangmin; Park, Kyungwon

2017-04-01

Extreme weather due to changing climate is a main source of water-related disasters such as flooding and inundation and its damage will be accelerated somewhere in world wide. To prevent the water-related disasters and mitigate their damage in urban areas in future, we developed a multi-sensor based real-time discharge forecasting system using remotely sensed data such as radar and satellite. We used Communication, Ocean and Meteorological Satellite (COMS) and Korea Meteorological Agency (KMA) weather radar for quantitative precipitation estimation. The Automatic Weather System (AWS) and McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) were used for verification of rainfall accuracy. The optimal Z-R relation was applied the Tropical Z-R relationship (Z=32R1.65), it has been confirmed that the accuracy is improved in the extreme rainfall events. In addition, the performance of blended multi-sensor combining rainfall was improved in 60mm/h rainfall and more strong heavy rainfall events. Moreover, we adjusted to forecast the urban discharge using Storm Water Management Model (SWMM). Several statistical methods have been used for assessment of model simulation between observed and simulated discharge. In terms of the correlation coefficient and r-squared discharge between observed and forecasted were highly correlated. Based on this study, we captured a possibility of real-time urban discharge forecasting system using remotely sensed data and its utilization for real-time flood warning. Acknowledgement This research was supported by a grant (13AWMP-B066744-01) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korean government.

An experiment in hurricane track prediction using parallel computing methods

NASA Technical Reports Server (NTRS)

Song, Chang G.; Jwo, Jung-Sing; Lakshmivarahan, S.; Dhall, S. K.; Lewis, John M.; Velden, Christopher S.

1994-01-01

The barotropic model is used to explore the advantages of parallel processing in deterministic forecasting. We apply this model to the track forecasting of hurricane Elena (1985). In this particular application, solutions to systems of elliptic equations are the essence of the computational mechanics. One set of equations is associated with the decomposition of the wind into irrotational and nondivergent components - this determines the initial nondivergent state. Another set is associated with recovery of the streamfunction from the forecasted vorticity. We demonstrate that direct parallel methods based on accelerated block cyclic reduction (BCR) significantly reduce the computational time required to solve the elliptic equations germane to this decomposition and forecast problem. A 72-h track prediction was made using incremental time steps of 16 min on a network of 3000 grid points nominally separated by 100 km. The prediction took 30 sec on the 8-processor Alliant FX/8 computer. This was a speed-up of 3.7 when compared to the one-processor version. The 72-h prediction of Elena's track was made as the storm moved toward Florida's west coast. Approximately 200 km west of Tampa Bay, Elena executed a dramatic recurvature that ultimately changed its course toward the northwest. Although the barotropic track forecast was unable to capture the hurricane's tight cycloidal looping maneuver, the subsequent northwesterly movement was accurately forecasted as was the location and timing of landfall near Mobile Bay.

Establishment of turbidity forecasting model and early-warning system for source water turbidity management using back-propagation artificial neural network algorithm and probability analysis.

PubMed

Yang, Tsung-Ming; Fan, Shu-Kai; Fan, Chihhao; Hsu, Nien-Sheng

2014-08-01

The purpose of this study is to establish a turbidity forecasting model as well as an early-warning system for turbidity management using rainfall records as the input variables. The Taipei Water Source Domain was employed as the study area, and ANOVA analysis showed that the accumulative rainfall records of 1-day Ping-lin, 2-day Ping-lin, 2-day Fei-tsui, 2-day Shi-san-gu, 2-day Tai-pin and 2-day Tong-hou were the six most significant parameters for downstream turbidity development. The artificial neural network model was developed and proven capable of predicting the turbidity concentration in the investigated catchment downstream area. The observed and model-calculated turbidity data were applied to developing the turbidity early-warning system. Using a previously determined turbidity as the threshold, the rainfall criterion, above which the downstream turbidity would possibly exceed this respective threshold turbidity, for the investigated rain gauge stations was determined. An exemplary illustration demonstrated the effectiveness of the proposed turbidity early-warning system as a precautionary alarm of possible significant increase of downstream turbidity. This study is the first report of the establishment of the turbidity early-warning system. Hopefully, this system can be applied to source water turbidity forecasting during storm events and provide a useful reference for subsequent adjustment of drinking water treatment operation.

Storm Surge Measurement with an Airborne Scanning Radar Altimeter

NASA Technical Reports Server (NTRS)

Wright, C. W.; Walsh, E. J.; Krabill, W. B.; Shaffer, W. A.; Baig, S. R.; Peng, M.; Pietrafesa, L. J.; Garcia, A. W.; Marks, F. D., Jr.; Black, P. G.;

On the Evolution of Precipitation Associated with a Wintertime East Coast Cyclone: A GALE Preliminary Study.

DTIC Science & Technology

1985-01-01

CYCLES (CYCLone Extratropical Storms project), a more elaborate study of precipitation structure, has been carried out by Hobbs and his collaborators...toward the heavily populated northeast portion of the country. The disruption of human activity caused by these often poorly forecast storms is...daily synoptic maps over a century ago permitted analysis of the structure and behavior of extratropical cyclones. Since then considerable literature

Current research on aviation weather (bibliography), 1979

NASA Technical Reports Server (NTRS)

Turkel, B. S.; Frost, W.

1980-01-01

The titles, managers, supporting organizations, performing organizations, investigators and objectives of 127 current research projects in advanced meteorological instruments, forecasting, icing, lightning, visibility, low level wind shear, storm hazards/severe storms, and turbulence are tabulated and cross-referenced. A list of pertinent reference material produced through the above tabulated research activities is given. The acquired information is assembled in bibliography form to provide a readily available source of information in the area of aviation meteorology.

Added Value of Assimilating Himawari-8 AHI Water Vapor Radiances on Analyses and Forecasts for "7.19" Severe Storm Over North China

NASA Astrophysics Data System (ADS)

Wang, Yuanbing; Liu, Zhiquan; Yang, Sen; Min, Jinzhong; Chen, Liqiang; Chen, Yaodeng; Zhang, Tao

2018-04-01

Himawari-8 is the first launched and operational new-generation geostationary meteorological satellite. The Advanced Himawari Imager (AHI) on board Himawari-8 provides continuous high-resolution observations of severe weather phenomena in space and time. In this study, the capability to assimilate AHI radiances has been developed within the Weather Research and Forecasting (WRF) model's data assimilation system. As the first attempt to assimilate AHI using WRF data assimilation at convective scales, the added value of hourly AHI clear-sky radiances from three water vapor channels on convection-permitting (3 km) analyses and forecasts of the "7.19" severe rainstorm that occurred over north China during 18-21 July 2016 was investigated. Analyses were produced hourly, and 24 h forecasts were produced every 6 h. The results showed that improved wind and humidity fields were obtained in analyses and forecasts verified against conventional observations after assimilating AHI water vapor radiances when compared to the control experiment which assimilated only conventional observations. It was also found that the assimilation of AHI water vapor radiances had a clearly positive impact on the rainfall forecast for the first 6 h lead time, especially for heavy rainfall exceeding 100 mm when verified against the observed rainfall. Furthermore, the horizontal and vertical distribution of features in the moisture fields were improved after assimilating AHI water vapor radiances, eventually contributing to a better forecast of the severe rainstorm.

A near real time regional JPSS and GOES-R data assimilation system for high impact weather research and applications

NASA Astrophysics Data System (ADS)

Li, J.; Wang, P.; Han, H.; Schmit, T. J.

2014-12-01

JPSS and GOES-R observations play important role in numerical weather prediction (NWP). However, how to best represent the information from satellite observations and how to get value added information from these satellite data into regional NWP models, including both radiance and derived products, still need investigations. In order to enhance the applications of JPSS and GOES-R data in regional NWP for high impact weather forecasts, scientists from Cooperative Institute of Meteorological Satellite Studies (CIMSS) at University of Wisconsin-Madison have recently developed a near realtime regional Satellite Data Assimilation system for Tropical storm forecasts (SDAT) (http://cimss.ssec.wisc.edu/sdat). The system consists of the community Gridpoint Statistical Interpolation (GSI) assimilation system and the advanced Weather Research Forecast (WRF) model. In addition to assimilate GOES, AMSUA/AMSUB, HIRS, MHS, ATMS (Suomi-NPP), AIRS and IASI radiances, the SDAT is also able to assimilate satellite-derived products such as hyperspectral IR retrieved temperature and moisture profiles, total precipitable water (TPW), GOES Sounder (and future GOES-R) layer precipitable water (LPW) and GOES Imager atmospheric motion vector (AMV) products into the system. Real time forecasted GOES infrared (IR) images simulated from SDAT output have also been part of the SDAT system for applications and forecast evaluations. To set up the system parameters, a series of experiments have been carried out to test the impacts of different initialization schemes, including different background error matrix, different NCEP global model date sets, and different WRF model horizontal resolutions. Using SDAT as a research testbed, researches have been conducted for different satellite data impacts study, as well as different techniques for handling clouds in radiance assimilation. Since the fall of 2013, the SDAT system has been running in near real time. The results from historical cases and 2014 hurricane season cases will be compared with the operational GFS and HWRF, and presented at the meeting.

Proximity sounding analysis for derechos and supercells: an assessment of similarities and differences

NASA Astrophysics Data System (ADS)

Doswell, Charles A.; Evans, Jeffry S.

Proximity soundings (within 2 h and 167 km) of derechos (long-lived, widespread damaging convective windstorms) and supercells have been obtained. More than 65 derechos, accompanied by 115 proximity soundings, are identified during the years 1983 to 1993. The derechos have been divided into categories according to the synoptic situation: strong forcing (SF), weak forcing (WF), and "hybrid" cases (which are neither weakly nor strongly forced). Nearly 100 supercell proximity soundings have been found for the period 1998 to 2001, subdivided into nontornadic and tornadic supercells; tornadic supercells were further subdivided into those producing significant (>F1 rating) tornadoes and weak tornadoes (F0-F1 rating). WF derecho situations typically are characterized by warm, moist soundings with large convective available potential instability (CAPE) and relatively weak vertical wind shear. SF derechos usually have stronger wind shears, and cooler and less moist soundings with lower CAPE than the weakly forced cases. Most derechos exhibit strong storm-relative inflow at low levels. In WF derechos, this is usually the result of rapid convective system movement, whereas in SF derechos, storm-relative inflow at low levels is heavily influenced by relatively strong low-level windspeeds. "Hybrid" cases collectively are similar to an average of the SF and WF cases. Supercells occur in environments that are not all that dissimilar from those that produce SF derechos. It appears that some parameter combining instability and deep layer shear, such as the Energy-Helicity Index (EHI), can help discriminate between tornadic and nontornadic supercell situations. Soundings with significant tornadoes (F2 and greater) typically show high 0-1 km relative humidities, and strong 0-1 km shear. Results suggest it may not be easy to forecast the mode of severe thunderstorm activity (i.e., derecho versus supercell) on any particular day, given conditions that favor severe thunderstorm activity in general. It is possible that the convective initiation mechanism is an important factor, with linear initiation favoring derechos, whereas nonlinear forcing might favor supercells. Upper-level storm-relative flow in supercells tends to be rear-to-front, whereas for derechos, storm-relative flow tends to be front-to-rear through a deep surface-based layer. However, knowing the storm-relative hodograph requires knowledge of storm motion, which can be a challenge to predict. These results generally imply that probabilistic forecasts of convective mode could be a successful strategy.

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.

Tropical Storm Lowell Becomes 7th Eastern Pacific Hurricane

NASA Image and Video Library

2014-08-21

NOAA's GOES-West satellite watched as Tropical Storm Lowell strengthened into a large hurricane during the morning of August 21 and opened its eye. Hurricane force winds extend outward up to 60 miles (95 km) from the center, while tropical storm force winds extend outward up to 185 miles (295 km). The storm stretches over a greater distance. Lowell became the seventh hurricane of the Eastern Pacific Ocean season today, August 21 at 11 a.m. EDT (1500 UTC). Maximum sustained winds had increased to 75 mph (120 kph) making Lowell a Category One hurricane on the Saffir-Simpson Wind Scale. Little change in intensity is forecast by the National Hurricane Center (NHC) today, and NHC forecasters expect a slow weakening trend later today through August 22. It was centered near latitude 20.0 north and longitude 122.1 west, about 810 miles (1,300 km) west-southwest of the southern tip of Baja California, Mexico. It is moving to the northwest near 3 mph (4 kph) and is expected to move faster in that direction over the next two days. The NHC said that Lowell should begin to slowly weaken by August 22 as it moves over progressively cooler waters and into a drier and more stable air mass. Since Lowell is such a large cyclone, it will likely take longer than average to spin down. The GOES-West image of Lowell was created at the NASA/NOAA GOES Project, located at NASA's Goddard Space Flight Center in Greenbelt, Maryland. Rob Gutro NASA's Goddard Space Flight Center Credit: NOAA/NASA GOES Project NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Using radar-derived parameters to forecast lightning cessation for nonisolated storms

NASA Astrophysics Data System (ADS)

Davey, Matthew J.; Fuelberg, Henry E.

2017-03-01

Lightning impacts operations at the Kennedy Space Center (KSC) and other outdoor venues leading to injuries, inconvenience, and detrimental economic impacts. This research focuses on cases of "nonisolated" lightning which we define as one cell whose flashes have ceased although it is still embedded in weak composite reflectivity (Z ≥ 15 dBZ) with another cell that is still producing flashes. The objective is to determine if any radar-derived parameters provide useful information about the occurrence of lightning cessation in remnant storms. The data set consists of 50 warm season (May-September) nonisolated storms near KSC during 2013. The research utilizes the National Lightning Detection Network, the second generation Lightning Detection and Ranging network, and polarized radar data. These data are merged and analyzed using the Warning Decision Support System-Integrated Information at 1 min intervals. Our approach only considers 62 parameters, most of which are related to the noninductive charging mechanism. They included the presence of graupel at various thermal altitudes, maximum reflectivity of the decaying storm at thermal altitudes, maximum connecting composite reflectivity between the decaying cell and active cell, minutes since the previous flash, and several others. Results showed that none of the parameters reliably indicated lightning cessation for even our restrictive definition of nonisolated storms. Additional research is needed before cessation can be determined operationally with the high degree of accuracy required for safety.

Synoptic Regulation of The 3 May 1999 Oklahoma Tornado Outbreak

NASA Astrophysics Data System (ADS)

Schultz, D. M.; Roebber, P. J.; Romero, R.

Despite the relatively successful long-lead-time forecasts of the storms during the 3 May 1999 tornadic outbreak in Oklahoma and Kansas, forecasters were unable to predict with confidence details concerning convective initiation and convective mode. The forecasters identified three synoptic processes they were monitoring for clues as to how the event would unfold. These elements were (a) the absence of strong surface convergence along a dryline in western Oklahoma and the Texas panhandle, (b) the presence of a cirrus shield that was hypothesized to limit surface heating, and (c) the arrival into Oklahoma of an upper-level wind-speed maximum (associated with the so- called southern PV anomaly) that was responsible for favorable synoptic-scale ascent and the cirrus shield. The Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model Version 5 (MM5) is used in forecast mode (using the operational AVN run data to provide initial and lateral boundary conditions) to explore the sen- sitivity of the outbreak to these features using simulations down to 2-km horizontal grid spacing. A 30-h control simulation is compared to the available observations and captures important qualitative characteristics of the event, including convective initi- ation east of the dryline and organization of mesoscale convective systems into long lived, long-track supercells. Additional simulations in which the initial strength of the southern PV anomaly is altered suggest that synoptic regulation of the 3 May 1999 event was imposed by the effects of the southern PV anomaly. The model results in- dicate that: (1) convective initiation in the weakly forced environment was achieved through modification of the existing cap through both surface heating and synoptic- scale ascent associated with the southern PV anomaly; (2) supercellular organization was supported regardless of the strength of the southern PV anomaly, although weak- to-moderate forcing from this feature was most conducive to the production of long lived supercells and strong forcing resulted in a trend toward linear mesoscale convec- tive systems; (3) the cirrus shield was important in limiting development of convection and reducing competition between storms.

Impact of parameterization of physical processes on simulation of track and intensity of tropical cyclone Nargis (2008) with WRF-NMM model.

PubMed

Pattanayak, Sujata; Mohanty, U C; Osuri, Krishna K

2012-01-01

The present study is carried out to investigate the performance of different cumulus convection, planetary boundary layer, land surface processes, and microphysics parameterization schemes in the simulation of a very severe cyclonic storm (VSCS) Nargis (2008), developed in the central Bay of Bengal on 27 April 2008. For this purpose, the nonhydrostatic mesoscale model (NMM) dynamic core of weather research and forecasting (WRF) system is used. Model-simulated track positions and intensity in terms of minimum central mean sea level pressure (MSLP), maximum surface wind (10 m), and precipitation are verified with observations as provided by the India Meteorological Department (IMD) and Tropical Rainfall Measurement Mission (TRMM). The estimated optimum combination is reinvestigated with six different initial conditions of the same case to have better conclusion on the performance of WRF-NMM. A few more diagnostic fields like vertical velocity, vorticity, and heat fluxes are also evaluated. The results indicate that cumulus convection play an important role in the movement of the cyclone, and PBL has a crucial role in the intensification of the storm. The combination of Simplified Arakawa Schubert (SAS) convection, Yonsei University (YSU) PBL, NMM land surface, and Ferrier microphysics parameterization schemes in WRF-NMM give better track and intensity forecast with minimum vector displacement error.

Variational optimization analysis of temperature and moisture advection in a severe storm environment

NASA Technical Reports Server (NTRS)

Mcfarland, M. J.

1975-01-01

Horizontal wind components, potential temperature, and mixing ratio fields associated with a severe storm environment in the south central U.S. were analyzed from synoptic upper air observations with a nonhomogeneous, anisotropic weighting function. Each data field was filtered with variational optimization analysis techniques. Variational optimization analysis was also performed on the vertical motion field and was used to produce advective forecasts of the potential temperature and mixing ratio fields. Results show that the dry intrusion is characterized by warm air, the advection of which produces a well-defined upward motion pattern. A corresponding downward motion pattern comprising a deep vertical circulation in the warm air sector of the low pressure system was detected. The axes alignment of maximum dry and warm advection with the axis of the tornado-producing squall line also resulted.

Hydrometeorological Hazards: Monitoring, Forecasting, Risk Assessment, and Socioeconomic Responses

NASA Technical Reports Server (NTRS)

Wu, Huan; Huang, Maoyi; Tang, Qiuhong; Kirschbaum, Dalia B.; Ward, Philip

2017-01-01

Hydrometeorological hazards are caused by extreme meteorological and climate events, such as floods, droughts, hurricanes,tornadoes, or landslides. They account for a dominant fraction of natural hazards and occur in all regions of the world, although the frequency and intensity of certain hazards and societies vulnerability to them differ between regions. Severe storms, strong winds, floods, and droughts develop at different spatial and temporal scales, but all can become disasters that cause significant infrastructure damage and claim hundreds of thousands of lives annually worldwide. Oftentimes, multiple hazards can occur simultaneously or trigger cascading impacts from one extreme weather event. For example, in addition to causing injuries, deaths, and material damage, a tropical storm can also result in flooding and mudslides, which can disrupt water purification and sewage disposal systems, cause overflow of toxic wastes, andincrease propagation of mosquito-borne diseases.

Convective Mode and Mesoscale Heavy Rainfall Forecast Challenges during a High-Impact Weather Period along the Gulf Coast and Florida from 17-20 May 2016

NASA Astrophysics Data System (ADS)

Bosart, L. F.; Wallace, B. C.

2017-12-01

Two high-impact convective storm forecast challenges occurred between 17-20 May 2016 during NOAA's Hazardous Weather Testbed Spring Forecast Experiment (SFE) at the Storm Prediction Center. The first forecast challenge was 286 mm of unexpected record-breaking rain that fell on Vero Beach (VRB), Florida, between 1500 UTC 17 May and 0600 UTC 18 May, more than doubling the previous May daily rainfall record. The record rains in VRB occurred subsequent to the formation of a massive MCS over the central Gulf of Mexico between 0900-1000 UTC 17 May. This MCS, linked to the earlier convection associated with an anomalously strong subtropical jet (STJ) over the Gulf of Mexico, moved east-northeastward toward Florida. The second forecast challenge was a large MCS that formed over the Mexican mountains near the Texas-Mexican border, moved eastward and grew upscale prior to 1200 UTC 19 May. This MCS further strengthened offshore after 1800 UTC 19 May beneath the STJ. SPC SFE participants expected this MCS to move east-northeastward and bring heavy rain due to training echoes along the Gulf coast as far eastward as the Florida panhandle. Instead, this MCS transitioned into a bowing MCS that resembled a low-end derecho and produced a 4-6 hPa cold pool with widespread surface wind gusts between 35-50 kt. Both MCS events occurred in a large-scale baroclinic environment along the northern Gulf coast. Both MCS events responded to antecedent convection within this favorable large-scale environment. Rainfall amounts with the first heavy rain-producing MCS were severely underestimated by models and forecasters alike. The second MCS produced the greatest forecaster angst because rainfall totals were forecast too high (MCS propagated too fast) and severe wind reports were much more widespread than anticipated (because of cold pool formation). This presentation will attempt to untangle what happened and why it happened.

The FASTER Approach: A New Tool for Calculating Real-Time Tsunami Flood Hazards

NASA Astrophysics Data System (ADS)

Wilson, R. I.; Cross, A.; Johnson, L.; Miller, K.; Nicolini, T.; Whitmore, P.

2014-12-01

In the aftermath of the 2010 Chile and 2011 Japan tsunamis that struck the California coastline, emergency managers requested that the state tsunami program provide more detailed information about the flood potential of distant-source tsunamis well ahead of their arrival time. The main issue is that existing tsunami evacuation plans call for evacuation of the predetermined "worst-case" tsunami evacuation zone (typically at a 30- to 50-foot elevation) during any "Warning" level event; the alternative is to not call an evacuation at all. A solution to provide more detailed information for secondary evacuation zones has been the development of tsunami evacuation "playbooks" to plan for tsunami scenarios of various sizes and source locations. To determine a recommended level of evacuation during a distant-source tsunami, an analytical tool has been developed called the "FASTER" approach, an acronym for factors that influence the tsunami flood hazard for a community: Forecast Amplitude, Storm, Tides, Error in forecast, and the Run-up potential. Within the first couple hours after a tsunami is generated, the National Tsunami Warning Center provides tsunami forecast amplitudes and arrival times for approximately 60 coastal locations in California. At the same time, the regional NOAA Weather Forecast Offices in the state calculate the forecasted coastal storm and tidal conditions that will influence tsunami flooding. Providing added conservatism in calculating tsunami flood potential, we include an error factor of 30% for the forecast amplitude, which is based on observed forecast errors during recent events, and a site specific run-up factor which is calculated from the existing state tsunami modeling database. The factors are added together into a cumulative FASTER flood potential value for the first five hours of tsunami activity and used to select the appropriate tsunami phase evacuation "playbook" which is provided to each coastal community shortly after the forecast is provided.

Testing a Coupled Global-limited-area Data Assimilation System using Observations from the 2004 Pacific Typhoon Season

NASA Astrophysics Data System (ADS)

Holt, C. R.; Szunyogh, I.; Gyarmati, G.; Hoffman, R. N.; Leidner, M.

2011-12-01

Tropical cyclone (TC) track and intensity forecasts have improved in recent years due to increased model resolution, improved data assimilation, and the rapid increase in the number of routinely assimilated observations over oceans. The data assimilation approach that has received the most attention in recent years is Ensemble Kalman Filtering (EnKF). The most attractive feature of the EnKF is that it uses a fully flow-dependent estimate of the error statistics, which can have important benefits for the analysis of rapidly developing TCs. We implement the Local Ensemble Transform Kalman Filter algorithm, a vari- ation of the EnKF, on a reduced-resolution version of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model and the NCEP Regional Spectral Model (RSM) to build a coupled global-limited area anal- ysis/forecast system. This is the first time, to our knowledge, that such a system is used for the analysis and forecast of tropical cyclones. We use data from summer 2004 to study eight tropical cyclones in the Northwest Pacific. The benchmark data sets that we use to assess the performance of our system are the NCEP Reanalysis and the NCEP Operational GFS analyses from 2004. These benchmark analyses were both obtained by the Statistical Spectral Interpolation, which was the operational data assimilation system of NCEP in 2004. The GFS Operational analysis assimilated a large number of satellite radiance observations in addition to the observations assimilated in our system. All analyses are verified against the Joint Typhoon Warning Center Best Track data set. The errors are calculated for the position and intensity of the TCs. The global component of the ensemble-based system shows improvement in po- sition analysis over the NCEP Reanalysis, but shows no significant difference from the NCEP operational analysis for most of the storm tracks. The regional com- ponent of our system improves position analysis over all the global analyses. The intensity analyses, measured by the minimum sea level pressure, are of similar quality in all of the analyses. Regional deterministic forecasts started from our analyses are generally not significantly different from those started from the GFS operational analysis. On average, the regional experiments performed better for longer than 48 h sea level pressure forecasts, while the global forecast performed better in predicting the position for longer than 48 h.

Forecasting of monsoon heavy rains: challenges in NWP

NASA Astrophysics Data System (ADS)

Sharma, Kuldeep; Ashrit, Raghavendra; Iyengar, Gopal; Bhatla, R.; Rajagopal, E. N.

2016-05-01

Last decade has seen a tremendous improvement in the forecasting skill of numerical weather prediction (NWP) models. This is attributed to increased sophistication in NWP models, which resolve complex physical processes, advanced data assimilation, increased grid resolution and satellite observations. However, prediction of heavy rains is still a challenge since the models exhibit large error in amounts as well as spatial and temporal distribution. Two state-of-art NWP models have been investigated over the Indian monsoon region to assess their ability in predicting the heavy rainfall events. The unified model operational at National Center for Medium Range Weather Forecasting (NCUM) and the unified model operational at the Australian Bureau of Meteorology (Australian Community Climate and Earth-System Simulator -- Global (ACCESS-G)) are used in this study. The recent (JJAS 2015) Indian monsoon season witnessed 6 depressions and 2 cyclonic storms which resulted in heavy rains and flooding. The CRA method of verification allows the decomposition of forecast errors in terms of error in the rainfall volume, pattern and location. The case by case study using CRA technique shows that contribution to the rainfall errors come from pattern and displacement is large while contribution due to error in predicted rainfall volume is least.

Numerical study of Asian dust transport during the springtime of 2001 simulated with the Chemical Weather Forecasting System (CFORS) model

NASA Astrophysics Data System (ADS)

Uno, Itsushi; Satake, Shinsuke; Carmichael, Gregory R.; Tang, Youhua; Wang, Zifa; Takemura, Toshihiko; Sugimoto, Nobuo; Shimizu, Atsushi; Murayama, Toshiyuki; Cahill, Thomas A.; Cliff, Steven; Uematsu, Mitsuo; Ohta, Sachio; Quinn, Patricia K.; Bates, Timothy S.

2004-10-01

The regional-scale aerosol transport model Chemical Weather Forecasting System (CFORS) is used for analysis of large-scale dust phenomena during the Asian Pacific Regional Characterization Experiment (ACE-Asia) intensive observation. Dust modeling results are examined with the surface weather reports, satellite-derived dust index (Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI)), Mie-scattering lidar observation, and surface aerosol observations. The CFORS dust results are shown to accurately reproduce many of the important observed features. Model analysis shows that the simulated dust vertical loading correlates well with TOMS AI and that the dust loading is transported with the meandering of the synoptic-scale temperature field at the 500-hPa level. Quantitative examination of aerosol optical depth shows that model predictions are within 20% difference of the lidar observations for the major dust episodes. The structure of the ACE-Asia Perfect Dust Storm, which occurred in early April, is clarified with the help of the CFORS model analysis. This storm consisted of two boundary layer components and one elevated dust (>6-km height) feature (resulting from the movement of two large low-pressure systems). Time variation of the CFORS dust fields shows the correct onset timing of the elevated dust for each observation site, but the model results tend to overpredict dust concentrations at lower latitude sites. The horizontal transport flux at 130°E longitude is examined, and the overall dust transport flux at 130°E during March-April is evaluated to be 55 Tg.

Can Regional Climate Modeling Capture the Observed Changes in Spatial Organization of Extreme Storms at Higher Temperatures?

NASA Astrophysics Data System (ADS)

Li, J.; Wasko, C.; Johnson, F.; Evans, J. P.; Sharma, A.

2018-05-01

The spatial extent and organization of extreme storm events has important practical implications for flood forecasting. Recently, conflicting evidence has been found on the observed changes of storm spatial extent with increasing temperatures. To further investigate this question, a regional climate model assessment is presented for the Greater Sydney region, in Australia. Two regional climate models were considered: the first a convection-resolving simulation at 2-km resolution, the second a resolution of 10 km with three different convection parameterizations. Both the 2- and the 10-km resolutions that used the Betts-Miller-Janjic convective scheme simulate decreasing storm spatial extent with increasing temperatures for 1-hr duration precipitation events, consistent with the observation-based study in Australia. However, other observed relationships of extreme rainfall with increasing temperature were not well represented by the models. Improved methods for considering storm organization are required to better understand potential future changes.

New Hurricane Exhibit

NASA Image and Video Library

2007-08-29

A new exhibit in StenniSphere depicting NASA's role in hurricane prediction and research and SSC's role in helping the region recover from Hurricane Katrina. The cyclone-shaped exhibit focuses on the effects of the Aug. 29, 2005 storm and outlines how NASA is working to improve weather forecasting. Through photos, 3-D models and digital animations, the exhibit tells the story of what happened inside the storm and how NASA's scientific research can increase the accuracy of hurricane tracking and modeling.

New Hurricane Exhibit

NASA Technical Reports Server (NTRS)

2007-01-01

A new exhibit in StenniSphere depicting NASA's role in hurricane prediction and research and SSC's role in helping the region recover from Hurricane Katrina. The cyclone-shaped exhibit focuses on the effects of the Aug. 29, 2005 storm and outlines how NASA is working to improve weather forecasting. Through photos, 3-D models and digital animations, the exhibit tells the story of what happened inside the storm and how NASA's scientific research can increase the accuracy of hurricane tracking and modeling.

Simulating and Forecasting Flooding Events in the City of Jeddah, Saudi Arabia

NASA Astrophysics Data System (ADS)

Ghostine, Rabih; Viswanadhapalli, Yesubabu; Hoteit, Ibrahim

2014-05-01

Metropolitan cities in the Kingdom of Saudi Arabia, as Jeddah and Riyadh, are more frequently experiencing flooding events caused by strong convective storms that produce intense precipitation over a short span of time. The flooding in the city of Jeddah in November 2009 was described by civil defense officials as the worst in 27 years. As of January 2010, 150 people were reported killed and more than 350 were missing. Another flooding event, less damaging but comparably spectacular, occurred one year later (Jan 2011) in Jeddah. Anticipating floods before they occur could minimize human and economic losses through the implementation of appropriate protection, provision and rescue plans. We have developed a coupled hydro-meteorological model for simulating and predicting flooding events in the city of Jeddah. We use the Weather Research Forecasting (WRF) model assimilating all available data in the Jeddah region for simulating the storm events in Jeddah. The resulting rain is then used on 10 minutes intervals to feed up an advanced numerical shallow water model that has been discretized on an unstructured grid using different numerical schemes based on the finite elements or finite volume techniques. The model was integrated on a high-resolution grid size varying between 0.5m within the streets of Jeddah and 500m outside the city. This contribution will present the flooding simulation system and the simulation results, focusing on the comparison of the different numerical schemes on the system performances in terms of accuracy and computational efficiency.

Operational specification and forecasting advances for Dst, LEO thermospheric densities, and aviation radiation dose and dose rate

NASA Astrophysics Data System (ADS)

Tobiska, W.; Knipp, D. J.; Burke, W. J.; Bouwer, D.; Bailey, J. J.; Hagan, M. P.; Didkovsky, L. V.; Garrett, H. B.; Bowman, B. R.; Gannon, J. L.; Atwell, W.; Blake, J. B.; Crain, W.; Rice, D.; Schunk, R. W.; Fulgham, J.; Bell, D.; Gersey, B.; Wilkins, R.; Fuschino, R.; Flynn, C.; Cecil, K.; Mertens, C. J.; Xu, X.; Crowley, G.; Reynolds, A.; Azeem, S. I.; Wiley, S.; Holland, M.; Malone, K.

2013-12-01

Space weather's effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun's photons, particles, and fields. Of the space environment domains that are affected by space weather, the magnetosphere, thermosphere, and even troposphere are key regions that are affected. Space Environment Technologies (SET) has developed and is producing innovative space weather applications. Key operational systems for providing timely information about the effects of space weather on these domains are SET's Magnetosphere Alert and Prediction System (MAPS), LEO Alert and Prediction System (LAPS), and Automated Radiation Measurements for Aviation Safety (ARMAS) system. MAPS provides a forecast Dst index out to 6 days through the data-driven, redundant data stream Anemomilos algorithm. Anemomilos uses observational proxies for the magnitude, location, and velocity of solar ejecta events. This forecast index is used by satellite operations to characterize upcoming geomagnetic storms, for example. LAPS is the SET fully redundant operational system providing recent history, current epoch, and forecast solar and geomagnetic indices for use in operational versions of the JB2008 thermospheric density model. The thermospheric densities produced by that system, driven by the LAPS data, are forecast to 72-hours to provide the global mass densities for satellite operators. ARMAS is a project that has successfully demonstrated the operation of a micro dosimeter on aircraft to capture the real-time radiation environment due to Galactic Cosmic Rays and Solar Energetic Particles. The dose and dose-rates are captured on aircraft, downlinked in real-time via the Iridium satellites, processed on the ground, incorporated into the most recent NAIRAS global radiation climatology data runs, and made available to end users via the web and smart phone apps. ARMAS provides the 'weather' of the radiation environment to improve air-crew and passenger safety. Many of the data products from MAPS, LAPS, and ARMAS are available on the SpaceWx smartphone app for iPhone, iPad, iPod, and Android professional users and public space weather education. We describe recent forecasting advances for moving the space weather information from these automated systems into operational, derivative products for communications, aviation, and satellite operations uses.

Local amplification of storm surge by Super Typhoon Haiyan in Leyte Gulf

PubMed Central

Mori, Nobuhito; Kato, Masaya; Kim, Sooyoul; Mase, Hajime; Shibutani, Yoko; Takemi, Tetsuya; Tsuboki, Kazuhisa; Yasuda, Tomohiro

2014-01-01

Typhoon Haiyan, which struck the Philippines in November 2013, was an extremely intense tropical cyclone that had a catastrophic impact. The minimum central pressure of Typhoon Haiyan was 895 hPa, making it the strongest typhoon to make landfall on a major island in the western North Pacific Ocean. The characteristics of Typhoon Haiyan and its related storm surge are estimated by numerical experiments using numerical weather prediction models and a storm surge model. Based on the analysis of best hindcast results, the storm surge level was 5–6 m and local amplification of water surface elevation due to seiche was found to be significant inside Leyte Gulf. The numerical experiments show the coherent structure of the storm surge profile due to the specific bathymetry of Leyte Gulf and the Philippines Trench as a major contributor to the disaster in Tacloban. The numerical results also indicated the sensitivity of storm surge forecast. PMID:25821268

A Bayesian Approach Based Outage Prediction in Electric Utility Systems Using Radar Measurement Data

DOE PAGES

Yue, Meng; Toto, Tami; Jensen, Michael P.; ...

2017-05-18

Severe weather events such as strong thunderstorms are some of the most significant and frequent threats to the electrical grid infrastructure. Outages resulting from storms can be very costly. While some tools are available to utilities to predict storm occurrences and damage, they are typically very crude and provide little means of facilitating restoration efforts. This study developed a methodology to use historical high-resolution (both temporal and spatial) radar observations of storm characteristics and outage information to develop weather condition dependent failure rate models (FRMs) for different grid components. Such models can provide an estimation or prediction of the outagemore » numbers in small areas of a utility’s service territory once the real-time measurement or forecasted data of weather conditions become available as the input to the models. Considering the potential value provided by real-time outages reported, a Bayesian outage prediction (BOP) algorithm is proposed to account for both strength and uncertainties of the reported outages and failure rate models. The potential benefit of this outage prediction scheme is illustrated in this study.« less

A Bayesian Approach Based Outage Prediction in Electric Utility Systems Using Radar Measurement Data

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

Yue, Meng; Toto, Tami; Jensen, Michael P.

Severe weather events such as strong thunderstorms are some of the most significant and frequent threats to the electrical grid infrastructure. Outages resulting from storms can be very costly. While some tools are available to utilities to predict storm occurrences and damage, they are typically very crude and provide little means of facilitating restoration efforts. This study developed a methodology to use historical high-resolution (both temporal and spatial) radar observations of storm characteristics and outage information to develop weather condition dependent failure rate models (FRMs) for different grid components. Such models can provide an estimation or prediction of the outagemore » numbers in small areas of a utility’s service territory once the real-time measurement or forecasted data of weather conditions become available as the input to the models. Considering the potential value provided by real-time outages reported, a Bayesian outage prediction (BOP) algorithm is proposed to account for both strength and uncertainties of the reported outages and failure rate models. The potential benefit of this outage prediction scheme is illustrated in this study.« less

Hindcast of extreme sea states in North Atlantic extratropical storms

NASA Astrophysics Data System (ADS)

Ponce de León, Sonia; Guedes Soares, Carlos

2015-02-01

This study examines the variability of freak wave parameters around the eye of northern hemisphere extratropical cyclones. The data was obtained from a hindcast performed with the WAve Model (WAM) model forced by the wind fields of the Climate Forecast System Reanalysis (CFSR). The hindcast results were validated against the wave buoys and satellite altimetry data showing a good correlation. The variability of different wave parameters was assessed by applying the empirical orthogonal functions (EOF) technique on the hindcast data. From the EOF analysis, it can be concluded that the first empirical orthogonal function (V1) accounts for greater share of variability of significant wave height (Hs), peak period (Tp), directional spreading (SPR) and Benjamin-Feir index (BFI). The share of variance in V1 varies for cyclone and variable: for the 2nd storm and Hs V1 contains 96 % of variance while for the 3rd storm and BFI V1 accounts only for 26 % of variance. The spatial patterns of V1 show that the variables are distributed around the cyclones centres mainly in a lobular fashion.

Storm Prediction Center Forecast Products

Science.gov Websites

thunderstorm and tornado watches which are in effect over the contiguous United States. Please read about the Discussions This is the current graphic showing any mesoscale discussions (MD's) which are in effect over the

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

Woodroffe, Jesse; Jordanova, Vania; Toth, Gabor

Extreme weather happens worldwide and it takes place in the magnetosphere. The magnetosphere is the place where the majority of earth’s satellites reside. These satellites provide weather forecasting and serve as national defense. When solar storms take place, they can damage satellites.

Flood forecasting using non-stationarity in a river with tidal influence - a feasibility study

NASA Astrophysics Data System (ADS)

Killick, Rebecca; Kretzschmar, Ann; Ilic, Suzi; Tych, Wlodek

2017-04-01

Flooding is the most common natural hazard causing damage, disruption and loss of life worldwide. Despite improvements in modelling and forecasting of water levels and flood inundation (Kretzschmar et al., 2014; Hoitink and Jay, 2016), there are still large discrepancies between predictions and observations particularly during storm events when accurate predictions are most important. Many models exist for forecasting river levels (Smith et al., 2013; Leedal et al., 2013) however they commonly assume that the errors in the data are independent, stationary and normally distributed. This is generally not the case especially during storm events suggesting that existing models are not describing the drivers of river level in an appropriate fashion. Further challenges exist in the lower sections of a river influenced by both river and tidal flows and their interaction and there is scope for improvement in prediction. This paper investigates the use of a powerful statistical technique to adaptively forecast river levels by modelling the process as locally stationary. The proposed methodology takes information on both upstream and downstream river levels and incorporates meteorological information (rainfall forecasts) and tidal levels when required to forecast river levels at a specified location. Using this approach, a single model will be capable of predicting water levels in both tidal and non-tidal river reaches. In this pilot project, the methodology of Smith et al. (2013) using harmonic tidal analysis and data based mechanistic modelling is compared with the methodology developed by Killick et al. (2016) utilising data-driven wavelet decomposition to account for the information contained in the upstream and downstream river data to forecast a non-stationary time-series. Preliminary modelling has been carried out using the tidal stretch of the River Lune in North-west England and initial results are presented here. Future work includes expanding the methodology to forecast river levels at a network of locations simultaneously. References Hoitink, A. J. F., and D. A. Jay (2016), Tidal river dynamics: Implications for deltas, Rev. Geophys., 54, 240-272 Killick, R., Knight, M., Nason, G.P., Eckley, I.A. (2016) The Local Partial Autocorrelation Function and its Application to the Forecasting of Locally Stationary Time Series. Submitted Kretzschmar, Ann and Tych, Wlodek and Chappell, Nick A (2014) Reversing hydrology: estimation of sub-hourly rainfall time-series from streamflow. Env. Modell Softw., 60. pp. 290-301 D. Leedal, A. H. Weerts, P. J. Smith, & K. J. Beven. (2013). Application of data-based mechanistic modelling for flood forecasting at multiple locations in the Eden catchment in the National Flood Forecasting System (England and Wales). HESS, 17(1), 177-185. Smith, P., Beven, K., Horsburgh, K., Hardaker, P., & Collier, C. (2013). Data-based mechanistic modelling of tidally affected river reaches for flood warning purposes: An example on the River Dee, UK. , Q.J.R. Meteorol. Soc. 139(671), 340-349.

The role of microphysics in the development of mesoscale areas of high winds around occluded cyclones

NASA Astrophysics Data System (ADS)

Baker, T. P.; Knippertz, P.; Blyth, A.

2012-04-01

Extratropical cyclones are an integral part of the weather in north-western Europe and can be associated with heavy precipitation and strong winds. While synoptic-scale aspects of these storms are often satisfactorily forecast several days in advance, mesoscale features within these systems such as bands of heavy rain or localized wind maxima, which are often the cause of the most damaging effects, are significantly less well understood and predicted by operational forecasts. Accurate predictions of the location, timing and intensity of these features are, however, highly important for the mitigation of the adverse effects that they bring. This is one of the motivations for the UK consortium DIAMET (DIAbatic influences on Mesoscale structures in ExtraTropical storms) that is focused on improving the understanding and predictability of these potentially damaging mesoscale features embedded within larger synoptic-scale extratropical storms. The project is based around a number of field campaigns using the Facility for Airborne Atmospheric Measurements (FAAM) BAe146 research aircraft along with other remote and in-situ measurements. An overview of the project will be presented by Geraint Vaughan in this session. This study analyses the effects of microphysics on the mesoscale dynamics within extratropical storms, in particular the high wind areas around occluded fronts wrapped around the core of a matured cyclonic storm. It has been hypothesized that evaporation and melting of hydrometeors in this region can lead to downward momentum transport and thereby increase near-surface winds (sometimes referred to as sting jets). The main tool for this study is the Weather Research and Forecasting (WRF) model. High-resolution simulations are run for several cases from the DIAMET field campaigns to examine how the development of strong winds around occluded fronts is affected by the microphysics. The model results using different microphysics schemes are compared with the observational data from the BAe146 aircraft and other sources such as wind profilers and radiosondes. In initial model simulations of a secondary frontal wave observed during the 2009 T-NAWDEX pilot flights, the microphysics in the parameterization scheme used has a large impact on the winds observed around the hook of the occlusion. The advanced double-moment Morrison and Thompson schemes show 12-hour mean 10m winds about 50% higher than the simpler WSM3 (WRF single moment) scheme in this area. These results suggest that ice processes could play an important role in the downward transport of momentum in this part of the cyclone. Further results from this and other cases from the field campaigns will be presented at the conference.

Comprehensive glossary of weather terms for storm spotters. Technical memo

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

Branick, M.L.

1993-01-01

The glossary contains weather-related terms that may be either heard or used by severe local storm spotters or spotter groups. Its purposes are (1) to achieve some level of standardization in the definitions of the terms that are used, and (2) provide a reference from which the meanings of any terms, especially the lesser-used ones, can be found. The idea is to allow smooth and effective communication between storm spotters and forecasters, and vice versa. A complete list of terms probably is impossible to arrive at, but this list is as comprehensive as possible. The definitions are written in whatmore » hopefully passes as layman's terms. They are written to be easily understood by the storm spotter, regardless of his or her meteorological background.« less

The October 25th 2015 super-cell storm over central Israel: numerical simulations with the WRF model

NASA Astrophysics Data System (ADS)

Lynn, Barry; Yair, Yoav

2017-04-01

We present high-resolution WRF simulations with lightning assimilation (Fierro et al., 2012; Lynn et al., 2015) coupled with the Dynamic Lightning Scheme (Lynn et al., 2012) of the October 25th 2015 super-cell event in the eastern Mediterranean. That storm developed within the northern tip of a Red-Sea trough off the Egyptian coastline near Alexandria, with deep convective cells rapidly growing over the sea, exhibiting cloud top temperatures colder than -70°C ( 18 km) and radar reflectivity cores > 65 dBz at 10 km. As the cells crossed the Israeli coast-line north of Tel-Aviv, they exhibited intensive lightning activity, severe hail, downbursts, and intense rain. The lightning detection system of the Israeli Electrical Corporation registered a total of over 17,000 CGs, and for 20 minutes at the peak of the event recorded CG flash-rates greater than 430 strokes per minute (if including IC strokes, it was likely higher). The results of the simulations properly reconstruct the rapid growth of vertically extensive high-reflectivity cores, with significant amounts of graupel, ice and supercooled water within the charging zone below -20C. This guaranteed the effectiveness of non-inductive charge separation processes leading to the exceptional flash rates that were observed. Fierro, A. O, E. R. Mansell, C. L. Ziegler, and D. R. MacGorman, 2012: Application of a Lightning Data Assimilation Technique in the WRF-ARW Model at Cloud-Resolving Scales for the Tornado Outbreak of 24 May 2011. Mon. Wea. Rev., 140, 2609-2627. Lynn, B. H., G. Kelman, and G. Ellrod, 2015: An Evaluation of the Efficacy of Using Observed Lightning to Improve Convective Lightning Forecasts. Wea. Forecasting, 30, 405-423. Lynn, B. H., Y. Yair, C. Price, G. Kelman, and A. J. Clark, 2012: Predicting cloud-to-ground and intracloud lightning in weather forecast models.Wea. Forecasting, 27, 1470-1488, doi:10.1175/WAF-D-11-00144.1.

The Geostationary Lighting Mapper (GLM) for GOES-R: A New Operational Capability to Improve Storm Forecasts and Warnings

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, R.; Koshak, William J.; Petersen, W. A.; Carey, L.; Mah, D.

2010-01-01

The next generation Geostationary Operational Environmental Satellite (GOES-R) series is a follow on to the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved spectral (3x), spatial (4x), and temporal (5x) resolution for the Advanced Baseline Imager (ABI). The GLM, an optical transient detector and imager operating in the near-IR at 777.4 nm will map all (in-cloud and cloud-to-ground) lighting flashes 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, from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fully operational. 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 prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time lightning mapping data are being provided in an experimental mode to selected National Weather Service (NWS) national centers and forecast offices via the GOES-R Proving Ground to help improve our understanding of the application of these data in operational settings and facilitate Day-1 user readiness for this new capability.

Simulating the meteorology and PM10 concentrations in Arizona dust storms using the Weather Research and Forecasting model with Chemistry (Wrf-Chem).

PubMed

Hyde, Peter; Mahalov, Alex; Li, Jialun

2018-03-01

Nine dust storms in south-central Arizona were simulated with the Weather Research and Forecasting with Chemistry model (WRF-Chem) at 2 km resolution. The windblown dust emission algorithm was the Air Force Weather Agency model. In comparison with ground-based PM 10 observations, the model unevenly reproduces the dust-storm events. The model adequately estimates the location and timing of the events, but it is unable to precisely replicate the magnitude and timing of the elevated hourly concentrations of particles 10 µm and smaller ([PM 10 ]).Furthermore, the model underestimated [PM 10 ] in highly agricultural Pinal County because it underestimated surface wind speeds and because the model's erodible fractions of the land surface data were too coarse to effectively resolve the active and abandoned agricultural lands. In contrast, the model overestimated [PM 10 ] in western Arizona along the Colorado River because it generated daytime sea breezes (from the nearby Gulf of California) for which the surface-layer speeds were too strong. In Phoenix, AZ, the model's performance depended on the event, with both under- and overestimations partly due to incorrect representation of urban features. Sensitivity tests indicate that [PM 10 ] highly relies on meteorological forcing. Increasing the fraction of erodible surfaces in the Pinal County agricultural areas improved the simulation of [PM 10 ] in that region. Both 24-hr and 1-hr measured [PM 10 ] were, for the most part, and especially in Pinal County, extremely elevated, with the former exceeding the health standard by as much as 10-fold and the latter exceeding health-based guidelines by as much as 70-fold. Monsoonal thunderstorms not only produce elevated [PM 10 ], but also cause urban flash floods and disrupt water resource deliveries. Given the severity and frequency of these dust storms, and conceding that the modeling system applied in this work did not produce the desired agreement between simulations and observations, additional research in both the windblown dust emissions model and the weather research/physicochemical model is called for. While many dust storms can be considered to be natural, in semi-arid climates such storms often have an anthropogenic component in their sources of dust. Applying the natural, exceptional events policy to these storms with strong signatures of anthropogenic sources would appear not only to be misguided but also to stifle genuine regulatory efforts at remediation. Those dust storms that have resulted, in part, from passage over abandoned farm land should no longer be considered "natural"; policymakers and lawmakers need to compel the owners of such land to reduce its potential for windblown dust.

Coastal Marsh Monitoring for Persistent Saltwater Intrusion

NASA Technical Reports Server (NTRS)

Hall, Callie M.

2008-01-01

This viewgraph presentation reviews NASA's work on the project that supports the Gulf of Mexico Alliance (GOMA) Governors Action Plan to monitor the coastal wetlands for saltwater intrusion. The action items that relate to the task are: (1) Obtain information on projected relative sea level rise, subsidence, and storm vulnerability to help prioritize conservation projects, including restoration, enhancement, and acquisition, and (2) Develop and apply ecosystem models to forecast the habitat structure and succession following hurricane disturbance and changes in ecological functions and services that impact vital socio-economic aspects of coastal systems. The objectives of the program are to provide resource managers with remote sensing products that support ecosystem forecasting models requiring salinity and inundation data. Specifically, the proposed work supports the habitat-switching modules in the Coastal Louisiana Ecosystem Assessment and Restoration (CLEAR) model, which provides scientific evaluation for restoration management.

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.

The Cooperative VAS Program with the Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

Diak, George R.; Menzel, W. Paul

1988-01-01

Work was divided between the analysis/forecast model development and evaluation of the impact of satellite data in mesoscale numerical weather prediction (NWP), development of the Multispectral Atmospheric Mapping Sensor (MAMS), and other related research. The Cooperative Institute for Meteorological Satellite Studies (CIMSS) Synoptic Scale Model (SSM) has progressed from a relatively basic analysis/forecast system to a package which includes such features as nonlinear vertical mode initialization, comprehensive Planetary Boundary Layer (PBL) physics, and the core of a fully four-dimensional data assimilation package. The MAMS effort has produced a calibrated visible and infrared sensor that produces imager at high spatial resolution. The MAMS was developed in order to study small scale atmospheric moisture variability, to monitor and classify clouds, and to investigate the role of surface characteristics in the production of clouds, precipitation, and severe storms.

Subtropical Dust Storms and Downslope Wind Events

NASA Astrophysics Data System (ADS)

Pokharel, Ashok Kumar; Kaplan, Michael L.; Fiedler, Stephanie

2017-10-01

We performed detailed mesoscale observational analyses and Weather Research and Forecasting (WRF) model simulations to study the terrain-induced downslope winds that generated dust-emitting winds at the beginning of three strong subtropical dust storms in three distinctly different regions of North Africa and the Arabian Peninsula. We revisit the Harmattan dust storm of 2 March 2004, the Saudi dust storm of 9 March 2009, and the Bodélé Depression dust storm of 8 December 2011 and use high-resolution WRF modeling to assess the dynamical processes during the onset of the storms in more depth. Our results highlight the generation of terrain-induced downslope winds in response to the transition of the atmospheric flow from a subcritical to supercritical state in all three cases. These events precede the unbalanced adjustment processes in the lee of the mountain ranges that produced larger-scale dust aerosol mobilization and transport. We see that only the higher-resolution data sets can resolve the mesoscale processes, which are mainly responsible for creating strong low-level terrain-induced downslope winds leading to the initial dust storms.

Tropical Cyclones, Hurricanes, and Climate: NASA's Global Cloud-Scale Simulations and New Observations that Characterize the Lifecycle of Hurricanes

NASA Technical Reports Server (NTRS)

Putman, William M.

2010-01-01

One of the primary interests of Global Change research is the impact of climate changes and climate variability on extreme weather events, such as intense tropical storms and hurricanes. Atmospheric climate models run at resolutions of global weather models have been used to study the impact of climate variability, as seen in sea surface temperatures, on the frequency and intensity of tropical cyclones. NASA's Goddard Earth Observing System Model, version 5 (GEOS-5) in ensembles run at 50 km resolution has been able to reproduce the interannual variations of tropical cyclone frequency seen in nature. This, and other global models, have found it much more difficult to reproduce the interannual changes in intensity, a result that reflects the inability of the models to simulate the intensities of the most extreme storms. Better representation of the structures of cyclones requires much higher resolution models. Such improved representation is also fundamental to making best use of satellite observations. In collaboration with NOAA's Geophysical Fluid Dynamics Laboratory, GEOS-5 now has the capability of running at much higher resolution to better represent cloud-scale resolutions. Global simulations at cloud-permitting resolutions (10- to 3.5-km) allows for the development of realistic tropical cyclones from tropical storm 119 km/hr winds) to category 5 (>249km1hr winds) intensities. GEOS-5 has produced realistic rain-band and eye-wall structures in tropical cyclones that can be directly analyzed against satellite observations. For the first time a global climate model is capable of representing realistic intensity and track variability on a seasonal scale across basins. GEOS-5 is also used in assimilation mode to test the impact of NASA's observations on tropical cyclone forecasts. One such test, for tropical cyclone Nargis in the Indian Ocean in May 2008, showed that observations from Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU-A) on Aqua substantially reduced forecast track errors. Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. SA is also bringing several state of the art instruments in recent field campaigns to peer under the clouds and study the inner workings of the tropical storms. With the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth science field experiment in 2010 that includes the Global Hawk Unmanned Airborne System (UAS) configured with a suite of in situ and remote sensing instruments that are observing and characterizing the lifecycle of hurricanes, we expect significant improvement in our understanding of the track and intensification processes with the assimilation of the satellite and field campaign observations of meteorological parameters in the numerical prediction models.

North Atlantic Ocean OSSE system development: Nature Run evaluation and application to hurricane interaction with the Gulf Stream

NASA Astrophysics Data System (ADS)

Kourafalou, Vassiliki H.; Androulidakis, Yannis S.; Halliwell, George R.; Kang, HeeSook; Mehari, Michael M.; Le Hénaff, Matthieu; Atlas, Robert; Lumpkin, Rick

2016-11-01

A high resolution, free-running model has been developed for the hurricane region of the North Atlantic Ocean. The model is evaluated with a variety of observations to ensure that it adequately represents both the ocean climatology and variability over this region, with a focus on processes relevant to hurricane-ocean interactions. As such, it can be used as the "Nature Run" (NR) model within the framework of Observing System Simulation Experiments (OSSEs), designed specifically to improve the ocean component of coupled ocean-atmosphere hurricane forecast models. The OSSE methodology provides quantitative assessment of the impact of specific observations on the skill of forecast models and enables the comprehensive design of future observational platforms and the optimization of existing ones. Ocean OSSEs require a state-of-the-art, high-resolution free-running model simulation that represents the true ocean (the NR). This study concentrates on the development and data based evaluation of the NR model component, which leads to a reliable model simulation that has a dual purpose: (a) to provide the basis for future hurricane related OSSEs; (b) to explore process oriented studies of hurricane-ocean interactions. A specific example is presented, where the impact of Hurricane Bill (2009) on the eastward extension and transport of the Gulf Stream is analyzed. The hurricane induced cold wake is shown in both NR simulation and observations. Interaction of storm-forced currents with the Gulf Stream produced a temporary large reduction in eastward transport downstream from Cape Hatteras and had a marked influence on frontal displacement in the upper ocean. The kinetic energy due to ageostrophic currents showed a significant increase as the storm passed, and then decreased to pre-storm levels within 8 days after the hurricane advanced further north. This is a unique result of direct hurricane impact on a western boundary current, with possible implications on the ocean feedback on hurricane evolution.

The North Alabama Lightning Mapping Array (LMA): A Network Overview

NASA Technical Reports Server (NTRS)

Blakeslee, R. J.; Bailey, J.; Buechler, D.; Goodman, S. J.; McCaul, E. W., Jr.; Hall, J.

2005-01-01

The North Alabama Lightning Mapping Array (LMA) is s a 3-D VHF regional lightning detection system that provides on-orbit algorithm validation and instrument performance assessments for the NASA Lightning Imaging Sensor, as well as information on storm kinematics and updraft evolution that offers the potential to improve severe storm warning lead time by up t o 50% and decrease te false alarm r a t e ( for non-tornado producing storms). In support of this latter function, the LMA serves as a principal component of a severe weather test bed to infuse new science and technology into the short-term forecasting of severe and hazardous weather, principally within nearby National Weather Service forecast offices. The LMA, which became operational i n November 2001, consists of VHF receivers deployed across northern Alabama and a base station located at the National Space Science and Technology Center (NSSTC), which is on t h e campus of the University of Alabama in Huntsville. The LMA system locates the sources of impulsive VHF radio signals s from lightning by accurately measuring the time that the signals aririve at the different receiving stations. Each station's records the magnitude and time of the peak lightning radiation signal in successive 80 ms intervals within a local unused television channel (channel 5, 76-82 MHz in our case ) . Typically hundreds of sources per flash can be reconstructed, which i n t u r n produces accurate 3-dimensional lightning image maps (nominally <50 m error within 150 la. range). The data are transmitted back t o a base station using 2.4 GHz wireless Ethernet data links and directional parabolic grid antennas. There are four repeaters in the network topology and the links have an effective data throughput rate ranging from 600 kbits s -1 t o 1.5 %its s -1. This presentation provides an overview of t h e North Alabama network, the data processing (both real-time and post processing) and network statistics.

NASA Studies Lightning Storms Using High-Flying, Uninhabited Vehicle

NASA Technical Reports Server (NTRS)

2001-01-01

A NASA team studying the causes of electrical storms and their effects on our home planet achieved a milestone on August 21, 2002, completing the study's longest-duration research flight and monitoring four thunderstorms in succession. Radio news media can talk with Dr. Richard Blakeslee, the project's principal investigator, and Tony Kim, project manager at the Marshall Space Flight Center (MSFC), about their results and how their work will help improve future weather forecasting ability. Based at the Naval Air Station Key West, Florida, researchers with the Altus Cumulus Electrification Study (ACES) used the Altus II remotely- piloted aircraft to study a thunderstorm in the Atlantic Ocean off Key West, two storms at the western edge of the Everglades, and a large storm over the northwestern corner of the Everglades. This photograph shows Tony Kim And Dr. Richard Blakeslee of MSFC testing aircraft sensors that would be used to measure the electric fields produced by thunderstorm as part of NASA's ACES. With dual goals of gathering weather data safely and testing the adaptability of the uninhabited aircraft, the ACES study is a collaboration among the MSFC, the University of Alabama in Huntsville, NASA's Goddard Space Flight Center in Greenbelt, Maryland, Pernsylvania State University in University Park, and General Atomics Aeronautical Systems, Inc.

Tropical Cyclone Paul

NASA Image and Video Library

2010-03-30

NASA image March 29, 2010 Tropical Cyclone Paul spanned the ocean waters between Australia and New Guinea on March 29, 2010. The MODIS on NASA’s Terra satellite captured this natural-color image the same day. The center of the cyclone is along the coast of Northern Territory’s Arnhem Land. Clouds run counter-clockwise across the Gulf of Carpentaria and Cape York Peninsula, over New Guinea’s Pulau Dolok, and over the Arafura Sea. On March 29, 2010, the U.S. Navy’s Joint Typhoon Warning Center (JTWC) reported that Tropical Cyclone Paul storm had maximum sustained winds of 60 knots (110 kilometers per hour) and gusts up to 75 knots (140 kilometers per hour). The storm was located roughly 315 nautical miles (585 kilometers) east of Darwin. The storm had moved slowly toward the southwest over the previous several hours. The JTWC forecast that the storm would likely maintain its current intensity for several more hours before slowly dissipating over land. Credit: NASA/GSFC/Jeff Schmaltz/MODIS To learn more about this image go to: modis.gsfc.nasa.gov/gallery/individual.php?db_date=2010-0... NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe.

Regional dust storm modeling for health services: The case of valley fever

NASA Astrophysics Data System (ADS)

Sprigg, William A.; Nickovic, Slobodan; Galgiani, John N.; Pejanovic, Goran; Petkovic, Slavko; Vujadinovic, Mirjam; Vukovic, Ana; Dacic, Milan; DiBiase, Scott; Prasad, Anup; El-Askary, Hesham

2014-09-01

On 5 July 2011, a massive dust storm struck Phoenix, Arizona (USA), raising concerns for increased cases of valley fever (coccidioidomycosis, or, cocci). A quasi-operational experimental airborne dust forecast system predicted the event and provides model output for continuing analysis in collaboration with public health and air quality communities. An objective of this collaboration was to see if a signal in cases of valley fever in the region could be detected and traced to the storm - an American haboob. To better understand the atmospheric life cycle of cocci spores, the DREAM dust model (also herein, NMME-DREAM) was modified to simulate spore emission, transport and deposition. Inexact knowledge of where cocci-causing fungus grows, the low resolution of cocci surveillance and an overall active period for significant dust events complicate analysis of the effect of the 5 July 2011 storm. In the larger context of monthly to annual disease surveillance, valley fever statistics, when compared against PM10 observation networks and modeled airborne dust concentrations, may reveal a likely cause and effect. Details provided by models and satellites fill time and space voids in conventional approaches to air quality and disease surveillance, leading to land-atmosphere modeling and remote sensing that clearly mark a path to advance valley fever epidemiology, surveillance and risk avoidance.

Some Aspects of Forecasting Severe Thunderstorms during Cool-Season Return-Flow Episodes.

NASA Astrophysics Data System (ADS)

Weiss, Steven J.

1992-08-01

Historically, the Gulf of Mexico has been considered a primary source of water vapor that influences the weather for much of the United States east of the Rocky Mountains. Although severe thunderstorms and tornadoes occur most frequently during the spring and summer months, the periodic transport of Gulf moisture inland ahead of traveling baroclinic waves can result in significant severe-weather episodes during the cool season.To gain insight into the short-range skill in forecasting surface synoptic patterns associated with moisture return from the Gulf, operational numerical weather prediction models from the National Meteorological Center were examined. Sea level pressure fields from the Limited-Area Fine-Mesh Model (LFM), Nested Grid Model (NGM), and the aviation (AVN) run of the Global Spectral Model, valid 48 h after initial data time, were evaluated for three cool-season cases that preceded severe local storm outbreaks. The NGM and AVN provided useful guidance in forecasting the onset of return flow along the Gulf coast. There was a slight tendency for these models to be slightly slow in the development of return flow. In contrast the LFM typically overforecasts the occurrence of return flow and tends to `open the Gulf' from west to east too quickly.Although the low-level synoptic pattern may be forecast correctly, the overall prediction process is hampered by a data void over the Gulf. It is hypothesized that when the return-flow moisture is located over the Gulf, model forecasts of stability and the resultant operational severe local storm forecasts are less skillful compared to situations when the moisture has spread inland already. This hypothesis is tested by examining the performance of the initial second-day (day 2) severe thunderstorm outlook issued by the National Severe Storms Forecast Center during the Gulf of Mexico Experiment (GUFMEX) in early 1988.It has been found that characteristically different air masses were present along the Gulf coast prior to the issuance of outlooks that accurately predicted the occurrence of severe thunderstorms versus outlooks that did not verify well. Unstable air masses with ample low-level moisture were in place along the coast prior to the issuance of the `good' day 2 outlooks, whereas relatively dry, stable air masses were present before the issuance of `false-alarm' outlooks. In the latter cases, large errors in the NGM 48-h lifted-index predictions were located north of the Gulf coast.

Forecasting Lightning Threat using Cloud-resolving Model Simulations

NASA Technical Reports Server (NTRS)

McCaul, E. W., Jr.; Goodman, S. J.; LaCasse, K. M.; Cecil, D. J.

2009-01-01

As numerical forecasts capable of resolving individual convective clouds become more common, it is of interest to see if quantitative forecasts of lightning flash rate density are possible, based on fields computed by the numerical model. Previous observational research has shown robust relationships between observed lightning flash rates and inferred updraft and large precipitation ice fields in the mixed phase regions of storms, and that these relationships might allow simulated fields to serve as proxies for lightning flash rate density. It is shown in this paper that two simple proxy fields do indeed provide reasonable and cost-effective bases for creating time-evolving maps of predicted lightning flash rate density, judging from a series of diverse simulation case study events in North Alabama for which Lightning Mapping Array data provide ground truth. One method is based on the product of upward velocity and the mixing ratio of precipitating ice hydrometeors, modeled as graupel only, in the mixed phase region of storms at the -15\\dgc\\ level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domainwide statistics of the peak values of simulated flash rate proxy fields against domainwide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. A blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Weather Research and Forecast Model simulations of selected North Alabama cases show that this model can distinguish the general character and intensity of most convective events, and that the proposed methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because models tend to have more difficulty in correctly predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models, the techniques proposed herein should continue to be applicable as newer and more accurate physically-based model versions, physical parameterizations, initialization techniques and ensembles of cloud-allowing forecasts become available.

Test operation of a real-time tsunami inundation forecast system using actual data observed by S-net

NASA Astrophysics Data System (ADS)

Suzuki, W.; Yamamoto, N.; Miyoshi, T.; Aoi, S.

2017-12-01

If the tsunami inundation information can be rapidly and stably forecast before the large tsunami attacks, the information would have effectively people realize the impeding danger and necessity of evacuation. Toward that goal, we have developed a prototype system to perform the real-time tsunami inundation forecast for Chiba prefecture, eastern Japan, using off-shore ocean bottom pressure data observed by the seafloor observation network for earthquakes and tsunamis along the Japan Trench (S-net) (Aoi et al., 2015, AGU). Because tsunami inundation simulation requires a large computation cost, we employ a database approach searching the pre-calculated tsunami scenarios that reasonably explain the observed S-net pressure data based on the multi-index method (Yamamoto et al., 2016, EPS). The scenario search is regularly repeated, not triggered by the occurrence of the tsunami event, and the forecast information is generated from the selected scenarios that meet the criterion. Test operation of the prototype system using the actual observation data started in April, 2017 and the performance and behavior of the system during non-tsunami event periods have been examined. It is found that the treatment of the noises affecting the observed data is the main issue to be solved toward the improvement of the system. Even if the observed pressure data are filtered to extract the tsunami signals, the noises in ordinary times or unusually large noises like high ocean waves due to storm affect the comparison between the observed and scenario data. Due to the noises, the tsunami scenarios are selected and the tsunami is forecast although any tsunami event does not actually occur. In most cases, the selected scenarios due to the noises have the fault models in the region along the Kurile or Izu-Bonin Trenches, far from the S-net region, or the fault models below the land. Based on the parallel operation of the forecast system with a different scenario search condition and examination of the fault models, we improve the stability and performance of the forecast system.This work was supported by Council for Science, Technology and Innovation(CSTI), Cross-ministerial Strategic Innovation Promotion Program (SIP), "Enhancement of societal resiliency against natural disasters"(Funding agency: JST).

GOES-S Liftoff

NASA Image and Video Library

2018-03-01

A United Launch Alliance Atlas V rocket lifts off from Space Launch Complex 41 at Cape Canaveral Air Force Station carrying the NOAA Geostationary Operational Environmental Satellite, or GOES-S. Liftoff was at 5:02 p.m. EST. GOES-S is the second satellite in a series of next-generation weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting.

Implementation and Verification of the Chen Prediction Technique for Forecasting Large Nonrecurrent Storms*

NASA Astrophysics Data System (ADS)

Arge, C. N.; Chen, J.; Slinker, S.; Pizzo, V. J.

2000-05-01

The method of Chen et al. [1997, JGR, 101, 27499] is designed to accurately identify and predict the occurrence, duration, and strength of largegeomagnetic storms using real-time solar wind data. The method estimates the IMF and the geoeffectiveness of the solar wind upstream of a monitor and can provide warning times that range from a few hours to more than 10 hours. The model uses physical features of solar wind structures that cause large storms: long durations of southward interplanetary magnetic field. It is currently undergoing testing, improvement, and validation at NOAA/SEC in effort to transition it into a real-time space weather forecasting tool. The original version of the model has modified so that it now makes hourly (as opposed to daily) predictions and has been improved in effort to enhance both its predictive capability and reliability. In this paper, we report on the results of a 2-year historical verification study of the model using ACE real-time data. The prediction performances of the original and improved versions of the model are then compared. A real-time prediction web page has been developed and is on line at NOAA/SEC. *Work supported by ONR.

Storm Prediction Center - Mesoscale Analysis Pages

Science.gov Websites

Archive NOAA Weather Radio Research Non-op. Products Forecast Tools Svr. Tstm. Events SPC Publications SPC experimental ESRL RAPv2-based Mesoanalysis fields is no longer available. Summary of changes in March 2012: The

The development of a probabilistic approach to forecast coastal change

USGS Publications Warehouse

Lentz, Erika E.; Hapke, Cheryl J.; Rosati, Julie D.; Wang, Ping; Roberts, Tiffany M.

2011-01-01

This study demonstrates the applicability of a Bayesian probabilistic model as an effective tool in predicting post-storm beach changes along sandy coastlines. Volume change and net shoreline movement are modeled for two study sites at Fire Island, New York in response to two extratropical storms in 2007 and 2009. Both study areas include modified areas adjacent to unmodified areas in morphologically different segments of coast. Predicted outcomes are evaluated against observed changes to test model accuracy and uncertainty along 163 cross-shore transects. Results show strong agreement in the cross validation of predictions vs. observations, with 70-82% accuracies reported. Although no consistent spatial pattern in inaccurate predictions could be determined, the highest prediction uncertainties appeared in locations that had been recently replenished. Further testing and model refinement are needed; however, these initial results show that Bayesian networks have the potential to serve as important decision-support tools in forecasting coastal change.

Intercomparison of vertical structure of storms revealed by ground-based (NMQ) and spaceborne radars (CloudSat-CPR and TRMM-PR).

PubMed

Fall, Veronica M; Cao, Qing; Hong, Yang

2013-01-01

Spaceborne radars provide great opportunities to investigate the vertical structure of clouds and precipitation. Two typical spaceborne radars for such a study are the W-band Cloud Profiling Radar (CPR) and Ku-band Precipitation Radar (PR), which are onboard NASA's CloudSat and TRMM satellites, respectively. Compared to S-band ground-based radars, they have distinct scattering characteristics for different hydrometeors in clouds and precipitation. The combination of spaceborne and ground-based radar observations can help in the identification of hydrometeors and improve the radar-based quantitative precipitation estimation (QPE). This study analyzes the vertical structure of the 18 January, 2009 storm using data from the CloudSat CPR, TRMM PR, and a NEXRAD-based National Mosaic and Multisensor QPE (NMQ) system. Microphysics above, within, and below the melting layer are studied through an intercomparison of multifrequency measurements. Hydrometeors' type and their radar scattering characteristics are analyzed. Additionally, the study of the vertical profile of reflectivity (VPR) reveals the brightband properties in the cold-season precipitation and its effect on the radar-based QPE. In all, the joint analysis of spaceborne and ground-based radar data increases the understanding of the vertical structure of storm systems and provides a good insight into the microphysical modeling for weather forecasts.

Tropical Storm Kyle (2002) and cold-air damming: their interactions and impacts on heavy rainfall in the Carolinas

NASA Astrophysics Data System (ADS)

Garcia-Rivera, Jose M.; Lin, Yuh-Lang; Rastigejev, Yevgenii

2016-06-01

The interactions between an Appalachian cold-air damming event and the near passage of Tropical Storm Kyle (2002) along the coastal Carolinas are assessed by using a numerical weather prediction model. As the storm moved along the coastline, it began extra-tropical transition, bringing heavy rains to both the coastal region and inland towards the Piedmont of North Carolina. Our goal is to quantify the effects of both interacting weather systems on heavy precipitation to improve the dynamical understanding of such effects, as well as precipitation forecasts in the study region. A series of sensitivity tests were performed to isolate and quantify the effects of both systems on the total accumulated precipitation. It was found that (a) for this type of along-coast track, the pre-existing cold-air damming played only a minor role on the total accumulated precipitation, (b) the outer circulation of Kyle weakened the cold-air damming due to a redirection of the mean flow away from the east side of the Appalachian Mountains, and (c) the combination of Kyle with a shortwave mid- to upper-level trough and a surface coastal front were responsible for the heavy precipitation experienced in the study area through the advection of moisture, vorticity, and the forcing of upward motion.

Intercomparison of Vertical Structure of Storms Revealed by Ground-Based (NMQ) and Spaceborne Radars (CloudSat-CPR and TRMM-PR)

PubMed Central

Fall, Veronica M.; Hong, Yang

2013-01-01

Spaceborne radars provide great opportunities to investigate the vertical structure of clouds and precipitation. Two typical spaceborne radars for such a study are the W-band Cloud Profiling Radar (CPR) and Ku-band Precipitation Radar (PR), which are onboard NASA's CloudSat and TRMM satellites, respectively. Compared to S-band ground-based radars, they have distinct scattering characteristics for different hydrometeors in clouds and precipitation. The combination of spaceborne and ground-based radar observations can help in the identification of hydrometeors and improve the radar-based quantitative precipitation estimation (QPE). This study analyzes the vertical structure of the 18 January, 2009 storm using data from the CloudSat CPR, TRMM PR, and a NEXRAD-based National Mosaic and Multisensor QPE (NMQ) system. Microphysics above, within, and below the melting layer are studied through an intercomparison of multifrequency measurements. Hydrometeors' type and their radar scattering characteristics are analyzed. Additionally, the study of the vertical profile of reflectivity (VPR) reveals the brightband properties in the cold-season precipitation and its effect on the radar-based QPE. In all, the joint analysis of spaceborne and ground-based radar data increases the understanding of the vertical structure of storm systems and provides a good insight into the microphysical modeling for weather forecasts. PMID:24459424

Mid-latitude Plasma Irregularities During Sub-Auroral Polarization Streams

NASA Astrophysics Data System (ADS)

Smith, N.; Loper, R. D.

2017-12-01

Geomagnetic storming impacts the ionosphere in different ways at different latitudes. In the mid latitudes, Sub-Auroral Polarization Streams (SAPS) may trigger a redistribution of plasma leading to the creation of ionospheric troughs, storm enhanced density plumes, and acceleration of sub-auroral ion drifts. Solar cycle data, real time space weather satellite data, and radar data will be analyzed to study mid-latitude plasma densities and characterize the plasma anomalies SAPS create in order to increase short-term mid-latitude space weather forecasting.

The Fronts and Atlantic Storm-Track Experiment (FASTEX): Scientific Objectives and Experimental Design.

NASA Astrophysics Data System (ADS)

Joly, Alain; Jorgensen, Dave; Shapiro, Melvyn A.; Thorpe, Alan; Bessemoulin, Pierre; Browning, Keith A.; Cammas, Jean-Pierre; Chalon, Jean-Pierre; Clough, Sidney A.; Emanuel, Kerry A.; Eymard, Laurence; Gall, Robert; Hildebrand, Peter H.; Langland, Rolf H.; Lemaître, Yvon; Lynch, Peter; Moore, James A.; Persson, P. Ola G.; Snyder, Chris; Wakimoto, Roger M.

1997-09-01

The Fronts and Atlantic Storm-Track Experiment (FASTEX) will address the life cycle of cyclones evolving over the North Atlantic Ocean in January and February 1997. The objectives of FASTEX are to improve the forecasts of end-of-storm-track cyclogenesis (primarily in the eastern Atlantic but with applicability to the Pacific) in the range 24 to 72 h, to enable the testing of theoretical ideas on cyclone formation and development, and to document the vertical and the mesoscale structure of cloud systems in mature cyclones and their relation to the dynamics. The observing system includes ships that will remain in the vicinity of the main baroclinic zone in the central Atlantic Ocean, jet aircraft that will fly and drop sondes off the east coast of North America or over the central Atlantic Ocean, turboprop aircraft that will survey mature cyclones off Ireland with dropsondes, and airborne Doppler radars, including ASTRAIA/ELDORA. Radiosounding frequency around the North Atlantic basin will be increased, as well as the number of drifting buoys. These facilities will be activated during multiple-day intensive observing periods in order to observe the same meteorological systems at several stages of their life cycle. A central archive will be developed in quasi-real time in Toulouse, France, thus allowing data to be made widely available to the scientific community.

An entropy decision approach in flash flood warning: rainfall thresholds definition

NASA Astrophysics Data System (ADS)

Montesarchio, V.; Napolitano, F.; Ridolfi, E.

2009-09-01

Flash floods events are floods characterised by very rapid response of the basins to the storms, and often they involve loss of life and damage to common and private properties. Due to the specific space-time scale of this kind of flood, generally only a short lead time is available for triggering civil protection measures. Thresholds values specify the precipitation amount for a given duration that generates a critical discharge in a given cross section. The overcoming of these values could produce a critical situation in river sites exposed to alluvial risk, so it is possible to compare directly the observed or forecasted precipitation with critical reference values, without running on line real time forecasting systems. This study is focused on the Mignone River basin, located in Central Italy. The critical rainfall threshold values are evaluated minimising an utility function based on the informative entropy concept. The study concludes with a system performance analysis, in terms of correctly issued warning, false alarms and missed alarms.

Operational wave now- and forecast in the German Bight as a basis for the assessment of wave-induced hydrodynamic loads on coastal dikes

NASA Astrophysics Data System (ADS)

Dreier, Norman; Fröhle, Peter

2017-12-01

The knowledge of the wave-induced hydrodynamic loads on coastal dikes including their temporal and spatial resolution on the dike in combination with actual water levels is of crucial importance of any risk-based early warning system. As a basis for the assessment of the wave-induced hydrodynamic loads, an operational wave now- and forecast system is set up that consists of i) available field measurements from the federal and local authorities and ii) data from numerical simulation of waves in the German Bight using the SWAN wave model. In this study, results of the hindcast of deep water wave conditions during the winter storm on 5-6 December, 2013 (German name `Xaver') are shown and compared with available measurements. Moreover field measurements of wave run-up from the local authorities at a sea dike on the German North Sea Island of Pellworm are presented and compared against calculated wave run-up using the EurOtop (2016) approach.

An Extensive Study on Dynamical aspects of Dust Storm over the United Arab Emirates during 18-20 March 2012

NASA Astrophysics Data System (ADS)

Basha, Ghouse; Phanikumar, Devulapalli V.; Ouarda, Taha B. M. J.

2015-04-01

On 18 March 2012, a super dust storm event occurred over Middle East (ME) and lasted for several hours. Following to this, another dust storm occurred on early morning of 20 March 2012 with almost higher intensity. Both these storms reduced the horizontal visibility to few hundreds of meters and represented as one of the most intense and long duration dust storms over United Arab Emirates (UAE) in recent times. These storms also reduced the air quality in most parts of the ME implying the shutdown of Airports, schools and hundreds of people were hospitalized with respirational problems. In the context of the above, we have made a detailed study on the dynamical processes leading to triggering of dust storm over UAE and neighboring regions. We have also analyzed its impact on surface, and vertical profiles of background parameters and aerosols during the dust storm period by using ground-based, space borne, dust forecasting model, and reanalysis data sets. The synoptic and dynamic conditions responsible for the occurrence of the dust storm are discussed extensively by using European Centre for Medium-Range Weather Forecasts (ECMWF) ERA interim reanalysis data sets. The Impact of dust storm on surface and upper air radiosonde measurements and aerosol optical properties are also investigated before, during and after the dust storm event. During the dust storm, surface temperature decreased by 15oC when compared to before and after the event. PM10 values significantly increased maximum of about 1600µg/m3. Spatial variation of Aerosol Optical Depth (AOD) from Moderate-resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI) aerosol index (AI) exhibited very high values during the event and source region can be identified of dust transport to our region with this figure. The total attenuated backscatter at 550nm from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite shows the vertical extent of dust up to 8km. The dynamics of this event is related to coupling of subtropical jet and polar jet over the Saudi Arabia region, which leads to massive dust storm generation and dust transport through Rub-Al-Khali, and Persian Gulf over the UAE region. AOD from ground based measurements showed fourfold increase from 0.2 to 1.8 during the event implying an atmospheric forcing of ~ 150 Wm-2. In addition, vertical profile of heating rate showed heating of ~1.5 K/day at 3-4 km during the event. In the view of the above, the present event is discussed in the light of current understanding of dust storm aerosol optical and physical processes and associated dynamics over UAE region.

Operational Use of the AIRS Total Column Ozone Retrievals Along with the RGB Air Mass Product as Part of the GOES-R Proving Ground

NASA Technical Reports Server (NTRS)

Folmer, Michael; Zavodsky, Bradley; Molthan, Andrew

2012-01-01

The National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Hydrometeorological Prediction Center (HPC) and Ocean Prediction Center (OPC) provide short-term and medium-range forecast guidance of heavy precipitation, strong winds, and other features often associated with mid-latitude cyclones over both land and ocean. As a result, detection of factors that lead to rapid cyclogenesis and high wind events is key to improving forecast skill. One phenomenon that has been identified with these events is the stratospheric intrusion that occurs near tropopause folds. This allows for deep mixing near the top of the atmosphere where dry air high in ozone concentrations and potential vorticity descends (sometimes rapidly) deep into the mid-troposphere. Observations from satellites can aid in detection of these stratospheric air intrusions (SAI) regions. Specifically, multispectral composite imagery assign a variety of satellite spectral bands to the red, green, and blue (RGB) color components of imagery pixels and result in color combinations that can assist in the detection of dry stratospheric air associated with PV advection, which in turn may alert forecasters to the possibility of a rapidly strengthening storm system. Single channel or RGB satellite imagery lacks quantitative information about atmospheric moisture unless the sampled brightness temperatures or other data are converted to estimates of moisture via a retrieval process. Thus, complementary satellite observations are needed to capture a complete picture of a developing storm system. Here, total column ozone retrievals derived from a hyperspectral sounder are used to confirm the extent and magnitude of SAIs. Total ozone is a good proxy for defining locations and intensity of SAIs and has been used in studies evaluating that phenomenon (e.g. Tian et al. 2007, Knox and Schmidt 2005). Steep gradients in values of total ozone seen by satellites have been linked to stratosphere-troposphere exchange (WMO, 1985).

The FIRO-2017 Field Campaign: Findings from a Unique Observing Period in the Russian River Watershed in Northern California during Jan - Mar 2017

NASA Astrophysics Data System (ADS)

Wilson, A. M.; Ralph, M.; Demirdjian, R.; Kawzenuk, B.; Cannon, F.; Cordeira, J. M.

2017-12-01

Forecast Informed Reservoir Operations (FIRO) is a proposed water management strategy that aims to improve water supply, maintain reduction in flood risk, and achieve ecosystem sustainability using data from state of the art watershed monitoring and weather and water forecasting. The first testbed for this strategy is Lake Mendocino, in the Russian River Watershed in northern California. In order to accomplish these goals, it is necessary to understand and better predict Atmospheric Rivers (ARs), which provide 50% of the annual precipitation, and cause most of the heavy rain and flood events in this watershed. To support this effort, a field campaign was held during January-March 2017 in the Russian River Watershed with the science objectives of understanding AR evolution as the AR makes landfall and interacts with terrain, assess reasons for additional variance in the relationship between storm total precipitation and bulk water vapor flux, and to form a unique database for model verification. Coastal and inland field sites equipped with multiple ground-based sensors as well as Vaisala radiosonde systems were deployed to support these objectives. The 2017 water year was among the wettest recorded in California. During the January-March 2017 period, the coastal/inland pair of radiosonde systems captured 13 storms with maximum integrated vapor transport (IVT) values nearing 1200 kg/m/s. This presentation will provide an overview of the water year and the field campaign observations. Results indicate that bulk upslope water vapor flux measured by the ARO, which is the measurement regularly available to forecasters and researchers, correlates extremely well with integrated vapor transport (IVT). The profiles of water vapor flux observed by the coastal and inland sites are very different both in maximum flux magnitude and height of the maximum flux.

The Great "Non-Event" of 7 January 2014: Challenges in CME Arrival Time and Geomagnetic Storm Strength Prediction

NASA Astrophysics Data System (ADS)

Mays, M. L.; Thompson, B. J.; Jian, L.; Evans, R. M.; Savani, N.; Odstrcil, D.; Nieves-Chinchilla, T.; Richardson, I. G.

2014-12-01

We present a case study of the 7 January 2014 event in order to highlight current challenges in space weather forecasting of CME arrival time and geomagnetic storm strength. On 7 January 2014 an X1.2 flare and CME with a radial speed ~2400 km/s was observed from active region 11943. The flaring region was only ten degrees southwest of disk center with extensive dimming south of the active region and preliminary analysis indicated a fairly rapid arrival at Earth (~36 hours). Of the eleven forecasting groups world-wide who participated in CCMC's Space Weather Scoreboard (http://kauai.ccmc.gsfc.nasa.gov/SWScoreBoard), nine predicted early arrivals and six predicted dramatic geomagnetic storm impacts (Kp predictions ranged from 6 to 9). However, the CME only had a glancing blow arrival at Earth - Kp did not rise above 3 and there was no geomagnetic storm. What happened? One idea is that the large coronal hole to the northeast of the active region could have deflected the CME. This coronal hole produced a high speed stream near Earth reaching an uncommon speed of 900 km/s four days after the observed CME arrival. However, no clear CME deflection was observed in the outer coronagraph fields of view (~5-20Rs) where CME measurements are derived to initiate models, therefore deflection seems unlikely. Another idea is the effect of the CME flux rope orientation with respect to Earth orbit. We show that using elliptical major and minor axis widths obtained by GCS fitting for the initial CME parameters in ENLIL would have improved the forecast to better reflect the observed glancing blow in-situ signature. We also explore the WSA-ENLIL+Cone simulations, the background solar wind solution, and compare with the observed CME arrival at Venus (from Venus Express) and Earth.

Comparison between three algorithms for Dst predictions over the 2003 2005 period

NASA Astrophysics Data System (ADS)

Amata, E.; Pallocchia, G.; Consolini, G.; Marcucci, M. F.; Bertello, I.

2008-02-01

We compare, over a two and half years period, the performance of a recent artificial neural network (ANN) algorithm for the Dst prediction called EDDA [Pallocchia, G., Amata, E., Consolini, G., Marcucci, M.F., Bertello, I., 2006. Geomagnetic Dst index forecast based on IMF data only. Annales Geophysicae 24, 989-999], based on IMF inputs only, with the performance of the ANN Lundstedt et al. [2002. Operational forecasts of the geomagnetic Dst index. Geophysical Research Letters 29, 341] algorithm and the Wang et al. [2003. Influence of the solar wind dynamic pressure on the decay and injection of the ring current. Journal of Geophysical Research 108, 51] algorithm based on differential equations, which both make use of both IMF and plasma inputs. We show that: (1) all three algorithms perform similarly for "small" and "moderate" storms; (2) the EDDA and Wang algorithms perform similarly and considerably better than the Lundstedt et al. [2002. Operational forecasts of the geomagnetic Dst index. Geophysical Research Letters 29, 341] algorithm for "intense" and for "severe" storms; (3) the EDDA algorithm has the clear advantage, for space weather operational applications, that it makes use of IMF inputs only. The advantage lies in the fact that plasma data are at times less reliable and display data gaps more often than IMF measurements, especially during large solar disturbances, i.e. during periods when space weather forecast are most important. Some considerations are developed on the reasons why EDDA may forecast the Dst index without making use of solar wind density and velocity data.

Constraining storm-scale forecasts of deep convective initiation with surface weather observations

NASA Astrophysics Data System (ADS)

Madaus, Luke

Successfully forecasting when and where individual convective storms will form remains an elusive goal for short-term numerical weather prediction. In this dissertation, the convective initiation (CI) challenge is considered as a problem of insufficiently resolved initial conditions and dense surface weather observations are explored as a possible solution. To better quantify convective-scale surface variability in numerical simulations of discrete convective initiation, idealized ensemble simulations of a variety of environments where CI occurs in response to boundary-layer processes are examined. Coherent features 1-2 hours prior to CI are found in all surface fields examined. While some features were broadly expected, such as positive temperature anomalies and convergent winds, negative temperature anomalies due to cloud shadowing are the largest surface anomaly seen prior to CI. Based on these simulations, several hypotheses about the required characteristics of a surface observing network to constrain CI forecasts are developed. Principally, these suggest that observation spacings of less than 4---5 km would be required, based on correlation length scales. Furthermore, it is anticipated that 2-m temperature and 10-m wind observations would likely be more relevant for effectively constraining variability than surface pressure or 2-m moisture observations based on the magnitudes of observed anomalies relative to observation error. These hypotheses are tested with a series of observing system simulation experiments (OSSEs) using a single CI-capable environment. The OSSE results largely confirm the hypotheses, and with 4-km and particularly 1-km surface observation spacing, skillful forecasts of CI are possible, but only within two hours of CI time. Several facets of convective-scale assimilation, including the need for properly-calibrated localization and problems from non-Gaussian ensemble estimates of the cloud field are discussed. Finally, the characteristics of one candidate dense surface observing network are examined: smartphone pressure observations. Available smartphone pressure observations (and 1-hr pressure tendency observations) are tested by assimilating them into convective-allowing ensemble forecasts for a three-day active convective period in the eastern United States. Although smartphone observations contain noise and internal disagreement, they are effective at reducing short-term forecast errors in surface pressure, wind and precipitation. The results suggest that smartphone pressure observations could become a viable mesoscale observation platform, but more work is needed to enhance their density and reduce error. This work concludes by reviewing and suggesting other novel candidate observation platforms with a potential to improve convective-scale forecasts of CI.