scholarly journals Near-Real-Time Surface-Based CAPE from Merged Hyperspectral IR Satellite Sounder and Surface Meteorological Station Data

2019 ◽  
Vol 58 (8) ◽  
pp. 1613-1632 ◽  
Author(s):  
Callyn Bloch ◽  
Robert O. Knuteson ◽  
Antonia Gambacorta ◽  
Nicholas R. Nalli ◽  
Jessica Gartzke ◽  
...  
Keyword(s):  
Real Time ◽  
Convective Available Potential Energy ◽  
Processing System ◽  
Naval Research ◽  
Observation Data ◽  
Profile Data ◽  
Surface Observation ◽  
Polar Orbiting Satellite ◽  
The Impact ◽  
Surface Observations

AbstractNear-real-time satellite-derived temperature and moisture soundings provide information about the changing atmospheric vertical thermodynamic structure occurring between successive routine National Weather Service (NWS) radiosonde launches. In particular, polar-orbiting satellite soundings become critical to the computation of stability indices over the central United States in the midafternoon, when there are no operational NWS radiosonde launches. Accurate measurements of surface temperature and dewpoint temperature are key in the calculation of severe weather indices, including surface-based convective available potential energy (SBCAPE). This paper addresses a shortcoming of current operational infrared-based satellite soundings, which underestimate the surface parcel temperature and dewpoint when CAPE is nonzero. This leads to a systematic underestimate of SBCAPE. This paper demonstrates a merging of satellite-derived vertical profiles with surface observations to address this deficiency for near-real-time applications. The National Oceanic and Atmospheric Administration (NOAA) Center for Environmental Prediction (NCEP) Meteorological Assimilation Data Ingest System (MADIS) hourly surface observation data are blended with satellite soundings derived using the NOAA Unique Combined Atmospheric Processing System (NUCAPS) to create a greatly improved SBCAPE calculation. This study is not intended to validate NUCAPS or the combined NUCAPS + MADIS product, but to demonstrate the benefits of combining observational weather satellite profile data and surface observations. Two case studies, 18 June 2017 and 3 July 2017, are used in this study to illustrate the success of the combined NUCAPS + MADIS SBCAPE compared to the NUCAPS-only SBCAPE estimate. In addition, a 6-month period, April–September 2018, was analyzed to provide a comprehensive analysis of the impact of using surface observations in satellite SBCAPE calculations. To address the need for reduced data latency, a near-real-time merged satellite and surface observation product is demonstrated using NUCAPS products from the Community Satellite Processing Package (CSPP) applied to direct broadcast data received at the University of Wisconsin–Madison, Hampton University in Virginia, and the Naval Research Laboratory in Monterey, California. Through this study, it is found that the combination of the MADIS surface observation data and the NUCAPS satellite profile data improves the SBCAPE estimate relative to comparisons with the Storm Prediction Center (SPC) mesoscale analysis and the NAM analysis compared to the NUCAPS-only SBCAPE estimate. An assessment of the 6-month period between April and September 2018 determined the dry bias in NUCAPS at the surface is the primary cause of the underestimation of the NUCAPS-only SBCAPE estimate.

scholarly journals The Impact of Computers on the Test Cell of Tomorrow

1983 ◽  
Author(s):  
Clifford F. Ash
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Test Procedure ◽  
Processing System ◽  
Open Loop ◽  
Engine Operation ◽  
Computer Data ◽  
Automatic Data ◽  
Data Acquisition And Processing ◽  
The Impact

Rapidly increasing fuel costs, the increasing complexity of the new engines now available, along with the inaccuracies, inefficiencies and long test cycles inherent in manual testing push the cost of engine testing to unnecessary levels. One promising avenue of relief is the automation of gas turbine testing through the use of real-time computer data acquisition and processing systems. Remarkable progress has been made in the area of closed-loop or fully automatic operation of the test process from start-up using various programmable steps, recording results as dictated by the test procedure, controlling operation and a safe engine shut down. This paper discusses the successful application of a real-time computer system with both closed and open-loop capabilities. This particular system called “ADAPS™” (Automatic Data Acquisition and Processing System) handled its first 3,000 hours of engine operation without a single hardware or software interruption. Savings in manpower alone in that period was nearly 18,000 man-hours.

scholarly journals Evaluation of RapidScat Ocean Vector Winds for Data Assimilation and Reanalysis

2018 ◽  
Vol 146 (1) ◽  
pp. 199-211 ◽  
Author(s):  
Will McCarty ◽  
Mohar Chattopadhyay ◽  
Austin Conaty
Keyword(s):  
Real Time ◽  
Forecast Error ◽  
Low Cost ◽  
Surface Wind ◽  
Space Station ◽  
Processing System ◽  
Error Reduction ◽  
Time Data ◽  
Full Data ◽  
The Impact

Abstract The Rapid Scatterometer (RapidScat) was built as a low-cost follow-on to the QuikSCAT mission. It flew on the International Space Station (ISS) and provided data from 3 October 2014 to 20 August 2016. These data allowed for the retrieval of surface wind vectors derived from surface roughness estimates measured from multiple coincident azimuth angles. These measurements were unique to the historical scatterometer record in that the ISS flies in a low inclination, non-sun-synchronous orbit. Scatterometry-derived wind vectors have been routinely assimilated in both forward processing and reanalysis systems run at the Global Modeling and Assimilation Office (GMAO). As the RapidScat retrievals were made available in near–real time, they were assimilated in the forward processing system, and the methods to assimilate and evaluate these retrievals are described. Time series of data statistics are presented first for the near-real-time data assimilated in GMAO forward processing. Second, the full data products provided by the RapidScat team are compared passively to the MERRA-2 reanalysis. Both sets of results show that the root-mean-square (RMS) difference of the observations and the GMAO model background fields increased over the course of the data record. Furthermore, the observations and the backgrounds are shown to be biased for both the zonal and meridional wind components. The retrievals are shown to have had a net forecast error reduction via the forecast sensitivity observation impact (FSOI) metric, which is a quantification of 24-h forecast error reduction, though the impact became neutral as the signal-to-noise ratio of the instrument decreased over its lifespan.

scholarly journals Short-Range Forecast Impact from Assimilation of GPS-IPW Observations into the Rapid Update Cycle

2007 ◽  
Vol 135 (8) ◽  
pp. 2914-2930 ◽  
Author(s):  
Tracy Lorraine Smith ◽  
Stanley G. Benjamin ◽  
Seth I. Gutman ◽  
Susan Sahm
Keyword(s):  
Relative Humidity ◽  
Real Time ◽  
Short Range ◽  
Mesoscale Model ◽  
Positive Impact ◽  
Convective Available Potential Energy ◽  
The United States ◽  
Time Of Day ◽  
Steady Increase ◽  
The Impact

Abstract Integrated precipitable water (IPW) estimates derived from time delays in the arrival of global positioning system (GPS) satellite signals are a relatively recent, high-frequency source of atmospheric moisture information available for real-time data assimilation. Different experimental versions of the Rapid Update Cycle (RUC) have assimilated these observations to assess GPS-IPW impact on moisture forecasts. In these tests, GPS-IPW data have proven to be a useful real-time source of moisture information, leading to more accurate short-range moisture forecasts when added to other observations. A multiyear experiment with parallel (one with GPS-IPW processed 24 h after the fact, one without) 3-h cycles using the original 60-km RUC was run from 1999 to 2004 with verification of each cycle against rawinsonde observations. This experiment showed a steady increase in the positive impact in short-range relative humidity (RH) forecasts due to the GPS-IPW data as the number of observing sites increased from 18 to almost 300 (as of 2004) across the United States and Canada. Positive impact from GPS-IPW on 850–700-hPa RH forecasts was also evident in 6- and 12-h forecasts. The impact of GPS-IPW data was also examined on forecasts from the more recent 20-km RUC, including a 1-h assimilation cycle and improved assimilation and physical parameterizations, now using real-time GPS-IPW retrievals available 30 min after valid time. In a 3-month comparison during the March–May 2004 period, 20-km RUC cycles with and without assimilation of GPS-IPW were compared with IPW for 3-, 6-, 9-, and 12-h forecasts. Using this measure, assimilation of GPS-IPW data led to the strongest improvements in the 3- and 6-h forecasts and smaller but still evident improvements in 9- and 12-h forecasts. In a severe convective weather case, inclusion of GPS-IPW data improved forecasts of convective available potential energy, an important predictor of severe storm potential, and relative humidity. Positive impact from GPS-IPW assimilation was found to vary over season, geographical location, and time of day, apparently related to variations in vertical mixing. For example, GPS-IPW has a stronger effect on improving RH forecasts at 850 hPa at nighttime (than daytime) and in cooler seasons (than warmer seasons) when surface moisture observations are less representative of conditions aloft. As a result of these studies, assimilation of GPS-IPW was added to the operational RUC run at NOAA/NCEP in June 2005 and to the operational North American Mesoscale model (also at NCEP) in June 2006 to improve their accuracy for short-range moisture forecasts.

ESMValTool pre-processing functions for eWaterCycle

2020 ◽  
Author(s):  
Fakhereh Alidoost ◽  
Jerom Aerts ◽  
Bouwe Andela ◽  
Jaro Camphuijsen ◽  
Nick van De Giesen ◽  
...  
Keyword(s):  
Input Data ◽  
Hydrological Modeling ◽  
Performance Metrics ◽  
Climate Model ◽  
Processing System ◽  
Observation Data ◽  
Hydrological Models ◽  
Earth System ◽  
Evaluation Tool ◽  
The Impact

<p>eWaterCycle is a framework in which hydrological modelers can work together in a collaborative environment. In this environment, they can, for example, compare and analyze the results of models that use different sources of (meteorological) forcing data. The final goal of eWaterCycle is to advance the state of FAIR (Findable, Accessible, Interoperable, and Reusable) and open science in hydrological modeling.</p><p>Comparing hydrological models has always been a challenging task. Hydrological models exhibit great complexity and diversity in the exact methodologies applied, competing for hypotheses of hydrologic behavior, technology stacks, and programming languages used in those models. Pre-processing of forcing data is one of the roadblocks that was identified during the FAIR Hydrological Modelling workshop organized by the Lorentz Center in April 2019. Forcing data can be retrieved from a wide variety of sources with discrepant variable names and frequencies, and spatial and temporal resolutions. Moreover, some hydrological models make specific assumptions about the definition of the forcing variables. The pre-processing is often performed by various sets of scripts that may or may not be included with model source codes, making it hard to reproduce results. Generally, there are common steps in the data preparation among different models. Therefore, it would be a valuable asset to the hydrological community if the pre-processing of FAIR input data could also be done in a FAIR manner.</p><p>Within the context of the eWaterCycle II project, a common pre-processing system has been created for hydrological modeling based on ESMValTool (Earth System Model Evaluation Tool). ESMValTool is a community diagnostic and performance metrics tool developed for the evaluation of Earth system models. The ESMValTool pre-processing functions cover a broad range of operations on data before diagnostics or metrics are applied; for example, vertical interpolation, land-sea masking, re-gridding, multi-model statistics, temporal and spatial manipulations, variable derivation and unit conversion. The pre-processor performs these operations in a centralized, documented and efficient way. The current pre-processing pipeline of the eWaterCycle using ESMValTool consists of hydrological model-specific recipes and supports ERA5 and ERA-Interim data provided by the ECMWF (European Centre for Medium-Range Weather Forecasts). The pipeline starts with the downloading and CMORization (Climate Model Output Rewriter) of input data. Then a recipe is prepared to find the data and run the preprocessors. When ESMValTool runs a recipe, it will also run the diagnostic script that contains model-specific analysis to derive required forcing variables, and it will store provenance information to ensure transparency and reproducibility. In the near future, the pipeline is extended to include Earth observation data, as these data are paramount to the data assimilation in eWaterCycle.</p><p>In this presentation we will show how using the pre-processor from ESMValTool for Hydrological modeling leads to connecting Hydrology and Climate sciences, and increase the impact and sustainability of ESMValTool.</p>

scholarly journals Observation Impact during the North Atlantic TReC—2003

2005 ◽  
Vol 133 (8) ◽  
pp. 2297-2309 ◽  
Author(s):  
Rolf H. Langland
Keyword(s):  
North Atlantic ◽  
Land Surface ◽  
Forecast Error ◽  
Naval Research ◽  
Observation Data ◽  
In Situ Data ◽  
The North ◽  
Surface Data ◽  
The North Atlantic ◽  
The Impact

Abstract An adjoint-based method is used to calculate the impact of observation data on a measure of short-range forecast error in the Navy Operational Global Atmospheric Prediction System (NOGAPS) during November and December 2003. The evaluated observations include all regular satellite and in situ data assimilated in the Naval Research Laboratory (NRL) Atmospheric Variational Data Assimilation System (NAVDAS) at 1800 UTC, and also targeted dropsonde profiles provided by the North Atlantic Observing-System Research and Predictability Experiment (THORPEX) Regional Campaign (NA-TReC) field program. Commerical aircraft observations account for 46% of the total forecast error reduction by observations in the NA-TReC domain, which includes the North Atlantic and adjacent regions of North America and Europe. Targeted dropsonde data have high impact per observation, but the impact of all dropsonde data is less than 2% of the total during the 2-month study period. Eight of 12 targeted dropsonde cases reduce forecast error. The percent of total impact for other observations assimilated at 1800 UTC in the NA-TReC domain is as follows: Advanced Microwave Sounding Unit-A (AMSU-A) radiances (16%), satellite winds (14%), land surface data (9%), radiosondes (8%), and ship-surface data (5%). If observations over the entire global domain are evaluated, the largest impact of data provided at 1800 UTC during November and December 2003 is provided by AMSU-A radiance data (48% of total).

The impact of real-time continuous glucose monitoring on metabolic control in children with type 1 diabetes

2020 ◽  
Author(s):  
Ruxandra Calapod Ioana ◽  
Irina Bojoga ◽  
Duta Simona Gabriela ◽  
Ana-Maria Stancu ◽  
Amalia Arhire ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Real Time ◽  
Metabolic Control ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
The Impact

THE IMPACT OF TV ADVERTISING ON VIRAL: ANALYSIS USING REAL-TIME AD RATINGS

2019 ◽  
Vol 2019 ◽  
pp. 790-791
Author(s):  
Cunhyeong Ci ◽  
◽  
Hyo-Gyoo Kim ◽  
Seungbae Park ◽  
Heebok Lee
Keyword(s):  
Real Time ◽  
Tv Advertising ◽  
The Impact

778-P: The Impact of Self-Management Blood Glucose (SMBG) Real-Time Decision Support on Glycemic Control in Adult with T1D in China

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 778-P
Author(s):  
ZIYU LIU ◽  
CHAOFAN WANG ◽  
XUEYING ZHENG ◽  
SIHUI LUO ◽  
DAIZHI YANG ◽  
...  
Keyword(s):  
Decision Support ◽  
Blood Glucose ◽  
Glycemic Control ◽  
Real Time ◽  
Self Management ◽  
The Impact

45. Education at distance: Broadcasting ECG rounds to Southeastern Ontario (BESO Project). An innovative approach for teaching electrocardiography

2007 ◽  
Vol 30 (4) ◽  
pp. 51 ◽  
Author(s):  
A. Baranchuk ◽  
G. Dagnone ◽  
P. Fowler ◽  
M. N. Harrison ◽  
L. Lisnevskaia ◽  
...  
Keyword(s):  
Health Care ◽  
Real Time ◽  
Digital Signal ◽  
Teaching Methodology ◽  
Care Providers ◽  
Long Distance ◽  
Medicine Clerkship ◽  
Time Problem ◽  
The Impact ◽  
Ecg Interpretation

Electrocardiography (ECG) interpretation is an essential skill for physicians as well as for many other health care professionals. Continuing education is necessary to maintain these skills. The process of teaching and learning ECG interpretation is complex and involves both deductive mechanisms and recognition of patterns for different clinical situations (“pattern recognition”). The successful methodologies of interactive sessions and real time problem based learning have never been evaluated with a long distance education model. To evaluate the efficacy of broadcasting ECG rounds to different hospitals in the Southeastern Ontario region; to perform qualitative research to determine the impact of this methodology in developing and maintaining skills in ECG interpretation. ECG rounds are held weekly at Kingston General Hospital and will be transmitted live to Napanee, Belleville, Oshawa, Peterborough and Brockville. The teaching methodology is based on real ECG cases. The audience is invited to analyze the ECG case and the coordinator will introduce comments to guide the case through the proper algorithm. Final interpretation will be achieved emphasizing the deductive process and the relevance of each case. An evaluation will be filled out by each participant at the end of each session. Videoconferencing works through a vast array of internet LANs, WANs, ISDN phone lines, routers, switches, firewalls and Codecs (Coder/Decoder) and bridges. A videoconference Codec takes the analog audio and video signal codes and compresses it into a digital signal and transmits that digital signal to another Codec where the signal is decompressed and retranslated back into analog video and audio. This compression and decompression allows large amounts of data to be transferred across a network at close to real time (384 kbps with 30 frames of video per second). Videoconferencing communication works on voice activation so whichever site is speaking has the floor and is seen by all the participating sites. A continuous presence mode allows each site to have the same visual and audio involvement as the host site. A bridged multipoint can connect between 8 and 12 sites simultaneously. This innovative methodology for teaching ECG will facilitate access to developing and maintaining skills in ECG interpretation for a large number of health care providers. Bertsch TF, Callas PW, Rubin A. Effectiveness of lectures attended via interactive video conferencing versus in-person in preparing third-year internal medicine clerkship students for clinical practice examinations. Teach Learn Med 2007; 19(1):4-8. Yellowlees PM, Hogarth M, Hilty DM. The importance of distributed broadband networks to academic biomedical research and education programs. Acad Psychaitry 2006;30:451-455

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