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35 results for “ICAR”
Dataset - Assessing the Added Value of the Intermediate Complexity Atmospheric Research Model (ICAR) for Precipitation in Complex Topography
<p>Abstract. The coarse grid spacing of global circulation models necessitates the application of downscaling techniques to investigate the local impact of a changing global climate. Difficulties arise for data sparse regions in complex topography which are computationally demanding for dynamic downscaling and often not suitable for statistical downscaling due to the lack of high quality observational data. The Intermediate Complexity Atmospheric Research Model (ICAR) is a physics-based model that can be applied without relying on measurements for training and is computationally more efficient than dynamic downscaling models. This study presents the first in-depth evaluation of multi-year precipitation time series generated with ICAR on a 4 × 4 km<sup>2</sup> grid for the South Island of New Zealand for an eleven-year period, ranging from 2007 until 2017. It focuses on complex topography and evaluates ICAR at 16 weather stations, eleven of which are situated in the Southern Alps between 700 m MSL and 2150 m MSL. ICAR is assessed with standard skill scores and the effect of model top elevation, topography, season, atmospheric background state and synoptic weather patterns on these scores are investigated. The results show a strong dependence of ICAR skill on the choice of the model top elevation, with the highest scores obtained for 4 km above topography. Furthermore, ICAR is found to provide added value over its ERA-Interim reanalysis forcing data set for alpine weather stations, improving mean squared errors (MSE) by up to 53 % and 30 % on median. It performs similarly during all seasons with an MSE minimum during winter, while flow linearity and atmospheric stability were found to increase skill scores. ICAR scores are highest during weather patterns associated with flow perpendicular to the Southern Alps and lowest for flow parallel to the alpine range. While measured precipitation is underestimated by ICAR, these results show the skill of ICAR in a real-world application, and may be improved upon by further observational calibration or bias correction techniques.<br> Based on these findings ICAR shows the potential to generate downscaled fields for long term impact studies in data sparse regions with complex topography.</p>
Data set - Idealized ridge simulations with ICAR and WRF
<p>The verification of models in general is a non-trivial task and can, due to epistemological and practical reasons, never be considered as complete. As a consequence, a model may yield correct results for the wrong reasons, i.e. by a different chain of processes than found in observations. While in the atmospheric sciences guidelines and strategies exist to maximize the chances that models are correct for the right reasons, these are mostly applicable to full-physics models, such as numerical weather prediction models. The Intermediate Complexity Atmospheric Research (ICAR) model is an atmospheric model employing linear mountain wave theory to represent the wind field. In this wind field atmospheric quantities, such as temperature and moisture are advected and a microphysics scheme is applied to represent the formation of clouds and precipitation. This study conducts an in-depth process-based evaluation of ICAR, employing idealized simulations to increase the understanding of the model and develop recommendations to maximize the probability that its results are correct for the right reasons. To contrast the obtained results from the linear-theory-based ICAR model to a full-physics model, idealized simulations with the Weather Research and Forecasting (WRF) model are conducted. The impact of the developed recommendations is then demonstrated with a case study for the South Island of New Zealand. The results of this investigation suggest three modifications to improve different aspects of ICAR simulations. The representation of the wind field within the domain improves when the dry and the moist Brunt-Väisälä frequencies are calculated in accordance to linear mountain wave theory from the unperturbed base state rather than from the time-dependent perturbed atmosphere. Imposing boundary conditions at the upper boundary different to the standard zero gradient boundary condition is shown to reduce errors in the potential temperature and water vapor fields. Furthermore, the results show that there is a lowest possible model top elevation that should not be undercut to avoid influences of the model top on cloud and precipitation processes within the domain. The method to determine the lowest model top elevation is applied to both the idealized simulations as well as the real terrain case study. Notable differences between the ICAR and WRF simulations are observed across all investigated quantities such as the wind field, water vapor and hydrometeor distributions, and the distribution of precipitation. The case study indicates a large shift in the precipitation maximum for the ICAR simulation employing the developed recommendations in contrast to an unmodified version of ICAR. The cause for the shift is found in influences of the model top on cloud formation and precipitation processes in the ICAR simulations. Furthermore, the results show that when model skill is evaluated from statistical metrics based on comparisons to surface observations only, such analysis may not reflect the skill of the model in capturing atmospheric processes such as gravity waves and cloud formation.</p>
Impact of Reverse vs. Forward ICARE Training Interventions
ClinicalTrials.gov study NCT03480581. IPD Sharing: NO. Countries: 1. Publications: 7.
Endothelial Function in a Sample Group of Patients From the ICARE Study
ClinicalTrials.gov study NCT00314379. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Comparison of Different Portable Tonometers (Icare Pro, TONO-Pen AVIA, Perkins Tonometer, PASCAL Hand Held Dynamic Contour Tonometer)
ClinicalTrials.gov study NCT01325324. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Interest of CARE Rule to Exclude the Hypothesis of an Acute Coronary Syndrome Without Bioassay - ICARE
ClinicalTrials.gov study NCT02813499. IPD Sharing: Not stated. Countries: 2. Publications: 1.
Improving Renal Complications in Adolescents With Type 2 Diabetes Through REsearch Cohort Study (National iCARE Study)
ClinicalTrials.gov study NCT02818192. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Improving Cardiac Rehabilitation Outcomes Through Mobile Case Management (iCARE)
ClinicalTrials.gov study NCT04938661. IPD Sharing: NO. Countries: 1. Publications: 0.
iCare vs Tonopen vs Goldmann Applanation Post-vitrectomy Surgery
ClinicalTrials.gov study NCT01786954. IPD Sharing: Not stated. Countries: 1. Publications: 0.
iCare Stress Management e-Training for Dementia Family Caregivers
ClinicalTrials.gov study NCT01378195. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Infiltration in Rheumatology With 3D Virtual Reality Headset Pilot Study for the Evaluation of Satisfaction (ICARE)
ClinicalTrials.gov study NCT07103096. IPD Sharing: NO. Countries: 1. Publications: 0.
Monitoring of the IOP After SLT Using iCare Home
ClinicalTrials.gov study NCT03310788. IPD Sharing: NO. Countries: 1. Publications: 0.
iCARE 2.0: A Pilot Intervention of Dialectical Behavioural Therapy for Youth With Type 2 Diabetes.
ClinicalTrials.gov study NCT05107154. IPD Sharing: NO. Countries: 1. Publications: 0.
Quick Measure Study for iCare ST500 and iCare IC200
ClinicalTrials.gov study NCT07156630. IPD Sharing: NO. Countries: 1. Publications: 0.
Project ICARE: Intervening for Community Awareness, Respect, & Empowerment
ClinicalTrials.gov study NCT00712088. IPD Sharing: Not stated. Countries: 1. Publications: 0.
iCare HOME2 Clinical Trial
ClinicalTrials.gov study NCT05162989. IPD Sharing: NO. Countries: 1. Publications: 0.
Icare Tonometry Effects on Keratometry Readings, Topography Readings, and Corneal Staining
ClinicalTrials.gov study NCT03275142. IPD Sharing: NO. Countries: 1. Publications: 0.
iCare for Cancer Patients
ClinicalTrials.gov study NCT02435550. IPD Sharing: NO. Countries: 1. Publications: 0.
iCare 2: Personalized Genomic Mutation Informed Treatment of Patients With Myelodysplastic Syndromes
ClinicalTrials.gov study NCT03446638. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Horizontal vs. Vertical Positioning of the iCare Rebound Tonometer and Effects on Intraocular Pressure Readings
ClinicalTrials.gov study NCT02837536. IPD Sharing: NO. Countries: 1. Publications: 0.
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