Radiance Preprocessing for Assimilation in the Hourly Updating Rapid Refresh Mesoscale Model: A Study Using AIRS Data

2017 ◽  
Vol 32 (5) ◽  
pp. 1781-1800 ◽  
Author(s):  
Haidao Lin ◽  
Stephen S. Weygandt ◽  
Agnes H. N. Lim ◽  
Ming Hu ◽  
John M. Brown ◽  
...  
Keyword(s):  
Bias Correction ◽  
Short Range ◽  
Mesoscale Model ◽  
Channel Selection ◽  
Atmospheric Temperature ◽  
Study Data ◽  
Satellite Systems ◽  
Initial Application ◽  
Radiance Data ◽  
The Impact

Abstract This study describes the initial application of radiance bias correction and channel selection in the hourly updated Rapid Refresh model. For this initial application, data from the Atmospheric Infrared Sounder (AIRS) are used; this dataset gives atmospheric temperature and water vapor information at higher vertical resolution and accuracy than previously launched low-spectral resolution satellite systems. In this preliminary study, data from AIRS are shown to add skill to short-range weather forecasts over a relatively data-rich area. Two 1-month retrospective runs were conducted to evaluate the impact of assimilating clear-sky AIRS radiance data on 1–12-h forecasts using a research version of the National Oceanic and Atmospheric Administration (NOAA) Rapid Refresh (RAP) regional mesoscale model already assimilating conventional and other radiance [AMSU-A, Microwave Humidity Sounder (MHS), HIRS-4] data. Prior to performing the assimilation, a channel selection and bias-correction spinup procedure was conducted that was appropriate for the RAP configuration. RAP forecasts initialized from analyses with and without AIRS data were verified against radiosonde, surface atmosphere, precipitation, and satellite radiance observations. Results show that the impact from AIRS radiance data on short-range forecast skill in the RAP system is small but positive and statistically significant at the 95% confidence level. The RAP-specific channel selection and bias correction procedures described in this study were the basis for similar applications to other radiance datasets now assimilated in version 3 of RAP implemented at NOAA’s National Centers for Environmental Prediction (NCEP) in August 2016.

scholarly journals An Alternative Bias Correction Scheme for CrIS Data Assimilation in a Regional Model

2019 ◽  
Vol 147 (3) ◽  
pp. 809-839 ◽  
Author(s):  
Xin Li ◽  
Xiaolei Zou ◽  
Mingjian Zeng
Keyword(s):  
Data Assimilation ◽  
Bias Correction ◽  
Moving Average ◽  
Atmospheric Temperature ◽  
Lapse Rate ◽  
Specific Humidity ◽  
Convective Precipitation ◽  
Temperature Structure ◽  
The Impact ◽  
Mean Square Errors

Bias correction (BC) is a crucial step for satellite radiance data assimilation (DA). In this study, the traditional airmass BC scheme in the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) is investigated for Cross-track Infrared Sounder (CrIS) DA. The ability of the airmass predictors to model CrIS biases is diagnosed. Correlations between CrIS observation-minus-background ( O − B) samples and the two lapse rate–related airmass predictors employed by GSI are found to be very weak, indicating that the bias correction contributed by the airmass BC scheme is small. A modified BC scheme, which directly calculates the moving average of O − B departures from data of the previous 2 weeks with respect to scan position and latitudinal band, is proposed and tested. The impact of the modified BC scheme on CrIS radiance DA is compared with the variational airmass BC scheme. Results from 1-month analysis/forecast experiments show that the modified BC scheme removes nearly all scan-dependent and latitude-dependent biases, while residual biases are still found in some channels when the airmass BC scheme is applied. Smaller predicted root-mean-square errors of temperature and specific humidity and higher equivalent threat scores are obtained by the DA experiment using the modified BC scheme. If O − B samples are replaced by observation-minus-analysis ( O − A) samples for bias estimates in the modified BC scheme, the forecast impacts are reduced but remain positive. A convective precipitation case that occurred on 21 August 2016 is investigated. Using the modified BC scheme, the atmospheric temperature structure and the geopotential height structures near trough/ridge areas are better resolved, resulting in better precipitation forecasts.

scholarly journals Short-Range Precipitation Forecasts from Time-Lagged Multimodel Ensembles during the HMT-West-2006 Campaign

2008 ◽  
Vol 9 (3) ◽  
pp. 477-491 ◽  
Author(s):  
Huiling Yuan ◽  
John A. McGinley ◽  
Paul J. Schultz ◽  
Christopher J. Anderson ◽  
Chungu Lu
Keyword(s):  
High Resolution ◽  
Bias Correction ◽  
Short Range ◽  
Mesoscale Model ◽  
Atmospheric Modeling ◽  
Training Data ◽  
Local Analysis ◽  
Calibration Methods ◽  
Time Lagged ◽  
Multimodel Ensembles

Abstract High-resolution (3 km) time-lagged (initialized every 3 h) multimodel ensembles were produced in support of the Hydrometeorological Testbed (HMT)-West-2006 campaign in northern California, covering the American River basin (ARB). Multiple mesoscale models were used, including the Weather Research and Forecasting (WRF) model, Regional Atmospheric Modeling System (RAMS), and fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). Short-range (6 h) quantitative precipitation forecasts (QPFs) and probabilistic QPFs (PQPFs) were compared to the 4-km NCEP stage IV precipitation analyses for archived intensive operation periods (IOPs). The two sets of ensemble runs (operational and rerun forecasts) were examined to evaluate the quality of high-resolution QPFs produced by time-lagged multimodel ensembles and to investigate the impacts of ensemble configurations on forecast skill. Uncertainties in precipitation forecasts were associated with different models, model physics, and initial and boundary conditions. The diabatic initialization by the Local Analysis and Prediction System (LAPS) helped precipitation forecasts, while the selection of microphysics was critical in ensemble design. Probability biases in the ensemble products were addressed by calibrating PQPFs. Using artificial neural network (ANN) and linear regression (LR) methods, the bias correction of PQPFs and a cross-validation procedure were applied to three operational IOPs and four rerun IOPs. Both the ANN and LR methods effectively improved PQPFs, especially for lower thresholds. The LR method outperformed the ANN method in bias correction, in particular for a smaller training data size. More training data (e.g., one-season forecasts) are desirable to test the robustness of both calibration methods.

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.

Coexistent Osteoarthritis and Parkinson’s Disease: Data from the Parkinson’s Foundation Outcomes Project

2020 ◽  
Vol 10 (4) ◽  
pp. 1601-1610
Author(s):  
Jaimie A. Roper ◽  
Abigail C. Schmitt ◽  
Hanzhi Gao ◽  
Ying He ◽  
Samuel Wu ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Study Data ◽  
Functional Mobility ◽  
Quality Improvement Initiative ◽  
Timed Up And Go ◽  
Mobility Performance ◽  
Risk Of Mortality ◽  
The Impact

Background: The impact of concurrent osteoarthritis on mobility and mortality in individuals with Parkinson’s disease is unknown. Objective: We sought to understand to what extent osteoarthritis severity influenced mobility across time and how osteoarthritis severity could affect mortality in individuals with Parkinson’s disease. Methods: In a retrospective observational longitudinal study, data from the Parkinson’s Foundation Quality Improvement Initiative was analyzed. We included 2,274 persons with Parkinson’s disease. The main outcomes were the effects of osteoarthritis severity on functional mobility and mortality. The Timed Up and Go test measured functional mobility performance. Mortality was measured as the osteoarthritis group effect on survival time in years. Results: More individuals with symptomatic osteoarthritis reported at least monthly falls compared to the other groups (14.5% vs. 7.2% without reported osteoarthritis and 8.4% asymptomatic/minimal osteoarthritis, p = 0.0004). The symptomatic group contained significantly more individuals with low functional mobility (TUG≥12 seconds) at baseline (51.5% vs. 29.0% and 36.1%, p < 0.0001). The odds of having low functional mobility for individuals with symptomatic osteoarthritis was 1.63 times compared to those without reported osteoarthritis (p < 0.0004); and was 1.57 times compared to those with asymptomatic/minimal osteoarthritis (p = 0.0026) after controlling pre-specified covariates. Similar results hold at the time of follow-up while changes in functional mobility were not significant across groups, suggesting that osteoarthritis likely does not accelerate the changes in functional mobility across time. Coexisting symptomatic osteoarthritis and Parkinson’s disease seem to additively increase the risk of mortality (p = 0.007). Conclusion: Our results highlight the impact and potential additive effects of symptomatic osteoarthritis in persons with Parkinson’s disease.

scholarly journals Measuring frailty in younger populations: a rapid review of evidence

BMJ Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. e047051
Author(s):  
Gemma F Spiers ◽  
Tafadzwa Patience Kunonga ◽  
Alex Hall ◽  
Fiona Beyer ◽  
Elisabeth Boulton ◽  
...  
Keyword(s):  
Patient Outcomes ◽  
Predictive Validity ◽  
Data Extraction ◽  
Grey Literature ◽  
Frailty Index ◽  
Study Data ◽  
Rapid Review ◽  
Eligibility Criteria ◽  
Adult Age ◽  
The Impact

ObjectivesFrailty is typically assessed in older populations. Identifying frailty in adults aged under 60 years may also have value, if it supports the delivery of timely care. We sought to identify how frailty is measured in younger populations, including evidence of the impact on patient outcomes and care.DesignA rapid review of primary studies was conducted.Data sourcesFour databases, three sources of grey literature and reference lists of systematic reviews were searched in March 2020.Eligibility criteriaEligible studies measured frailty in populations aged under 60 years using experimental or observational designs, published after 2000 in English.Data extraction and synthesisRecords were screened against review criteria. Study data were extracted with 20% of records checked for accuracy by a second researcher. Data were synthesised using a narrative approach.ResultsWe identified 268 studies that measured frailty in samples that included people aged under 60 years. Of these, 85 studies reported evidence about measure validity. No measures were identified that were designed and validated to identify frailty exclusively in younger groups. However, in populations that included people aged over and under 60 years, cumulative deficit frailty indices, phenotype measures, the FRAIL Scale, the Liver Frailty Index and the Short Physical Performance Battery all demonstrated predictive validity for mortality and/or hospital admission. Evidence of criterion validity was rare. The extent to which measures possess validity across the younger adult age (18–59 years) spectrum was unclear. There was no evidence about the impact of measuring frailty in younger populations on patient outcomes and care.ConclusionsLimited evidence suggests that frailty measures have predictive validity in younger populations. Further research is needed to clarify the validity of measures across the adult age spectrum, and explore the utility of measuring frailty in younger groups.

scholarly journals Risk of Nursing Home Use Among Older Americans: The Impact of Psychiatric History and Trajectories of Cognitive Function

2021 ◽  
Author(s):  
Maria T Brown ◽  
Miriam Mutambudzi
Keyword(s):  
Nursing Home ◽  
Cognitive Function ◽  
Latent Class ◽  
Study Data ◽  
Psychiatric Training ◽  
Psychiatric History ◽  
Term Care ◽  
Increased Risk ◽  
Course Variables ◽  
The Impact

Abstract Objectives Mental illness and cognitive functioning may be independently associated with nursing home use. We investigated the strength of the association between baseline (1998) psychiatric history, 8-year cognitive function trajectories, and prospective incidence of nursing home use over a 10-year period while accounting for relevant covariates in U.S. adults aged 65 and older. We hypothesized that self-reported baseline history of psychiatric, emotional, or nervous problems would be associated with a greater risk of nursing home use and that cognition trajectories with the greatest decline would be associated with a subsequent higher risk of nursing home use. Methods We used 8 waves (1998–2016) of Health and Retirement Study data for adults aged 65 years and older. Latent class mixture modeling identified 4 distinct cognitive function trajectory classes (1998–2006): low-declining, medium-declining, medium-stable, and high-declining. Participants from the 1998 wave (N = 5,628) were classified into these 4 classes. Competing risks regression analysis modeled the subhazard ratio of nursing home use between 2006 and 2016 as a function of baseline psychiatric history and cognitive function trajectories. Results Psychiatric history was independently associated with greater risk of nursing home use (subhazard ratio [SHR] 1.26, 95% confidence interval [CI] 1.06–1.51, p &lt; .01), net the effects of life course variables. Furthermore, “low-declining” (SHR 2.255, 95% CI 1.70–2.99, p &lt; .001) and “medium-declining” (2.103, 95% CI 1.69–2.61, p &lt; .001) trajectories predicted increased risk of nursing home use. Discussion Evidence of these associations can be used to educate policymakers and providers about the need for appropriate psychiatric training for staff in community-based and residential long-term care programs.

High-Resolution Climate Change Impact Analysis on Expected Future Water Availability in the Upper Jordan Catchment and the Middle East

2014 ◽  
Vol 15 (4) ◽  
pp. 1517-1531 ◽  
Author(s):  
Gerhard Smiatek ◽  
Harald Kunstmann ◽  
Andreas Heckl
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Water Availability ◽  
Impact Analysis ◽  
River Flow ◽  
Climate Model ◽  
Mesoscale Model ◽  
Global Climate Model ◽  
Full Range ◽  
The Impact

Abstract The impact of climate change on the future water availability of the upper Jordan River (UJR) and its tributaries Dan, Snir, and Hermon located in the eastern Mediterranean is evaluated by a highly resolved distributed approach with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) run at 18.6- and 6.2-km resolution offline coupled with the Water Flow and Balance Simulation Model (WaSiM). The MM5 was driven with NCEP reanalysis for 1971–2000 and with Hadley Centre Coupled Model, version 3 (HadCM3), GCM forcings for 1971–2099. Because only one regional–global climate model combination was applied, the results may not give the full range of possible future projections. To describe the Dan spring behavior, the hydrological model was extended by a bypass approach to allow the fast discharge components of the Snir to enter the Dan catchment. Simulation results for the period 1976–2000 reveal that the coupled system was able to reproduce the observed discharge rates in the partially karstic complex terrain to a reasonable extent with the high-resolution 6.2-km meteorological input only. The performed future climate simulations show steadily rising temperatures with 2.2 K above the 1976–2000 mean for the period 2031–60 and 3.5 K for the period 2070–99. Precipitation trends are insignificant until the middle of the century, although a decrease of approximately 12% is simulated. For the end of the century, a reduction in rainfall ranging between 10% and 35% can be expected. Discharge in the UJR is simulated to decrease by 12% until 2060 and by 26% until 2099, both related to the 1976–2000 mean. The discharge decrease is associated with a lower number of high river flow years.

scholarly journals A Study on Ownership Structure and Financial Performance of Listed Beverage Food and Tobacco Companies in Sri Lanka

2017 ◽  
Vol 7 (2) ◽  
pp. 36
Author(s):  
Saseela Balagobei ◽  
Thirunavukkarasu Velnampy
Keyword(s):  
Sri Lanka ◽  
Financial Performance ◽  
Ownership Structure ◽  
Relevant Literature ◽  
Foreign Ownership ◽  
Study Data ◽  
Secondary Sources ◽  
Correlation And Regression Analysis ◽  
Corporate Governance Mechanisms ◽  
The Impact

The relevant literature suggests that ownership structure is one of the main corporate governance mechanisms influencing the scope of financial performance. The aim of this study is to investigate the relationship between ownership structure and financial performance of listed beverage food and tobacco companies for the period of 2010-2015. This study also examines the impact of ownership structure on financial performance. The sample consists of 10 listed beverage food and tobacco companies in Sri Lanka. In this study, data was collected from secondary sources and hypotheses are examined by using Pearson’s correlation and regression analysis. The results reveal that ownership concentration and foreign ownership structure are positively correlated with financial performance of listed beverage food and tobacco companies while institutional ownership structure isn’t significantly correlated with financial performance. It is also found that there is a significant impact of foreign ownership structure on financial performance. Higher the foreign ownership structure in listed beverage food and tobacco companies, the higher the financial performance which is preferable for the shareholders and it improves the wealth of companies.

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