Recent Upgrades to NASA SPoRT Initialization Datasets for the Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its NOAA/National Weather Service (NWS) partners that can initialize specific fields for local model runs within the NOAA/NWS Science and Training Resource Center Environmental Modeling System (EMS). The suite of SPoRT products for use in the EMS consists of a Sea Surface Temperature (SST) composite that includes a Lake Surface Temperature (LST) analysis over the Great Lakes, a Great Lakes sea-ice extent within the SST composite, a real-time Green Vegetation Fraction (GVF) composite, and NASA Land Information System (LIS) gridded output. This paper and companion poster describe each dataset and provide recent upgrades made to the SST, Great Lakes LST, GVF composites, and the real-time LIS runs

NASA SPoRT Initialization Datasets for Local Model Runs in the Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its National Weather Service (NWS) partners that can be used to initialize local model runs within the Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). These real-time datasets consist of surface-based information updated at least once per day, and produced in a composite or gridded product that is easily incorporated into the WRF EMS. The primary goal for making these NASA datasets available to the WRF EMS community is to provide timely and high-quality information at a spatial resolution comparable to that used in the local model configurations (i.e., convection-allowing scales). The current suite of SPoRT products supported in the WRF EMS include a Sea Surface Temperature (SST) composite, a Great Lakes sea-ice extent, a Greenness Vegetation Fraction (GVF) composite, and Land Information System (LIS) gridded output. The SPoRT SST composite is a blend of primarily the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared and Advanced Microwave Scanning Radiometer for Earth Observing System data for non-precipitation coverage over the oceans at 2-km resolution. The composite includes a special lake surface temperature analysis over the Great Lakes using contributions from the Remote Sensing Systems temperature data. The Great Lakes Environmental Research Laboratory Ice Percentage product is used to create a sea-ice mask in the SPoRT SST composite. The sea-ice mask is produced daily (in-season) at 1.8-km resolution and identifies ice percentage from 0 100% in 10% increments, with values above 90% flagged as ice

The Transition of High-Resolution NASA MODIS Sea Surface Temperatures into the WRF Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composite at 2-km resolution that has been implemented in version 3 of the National Weather Service (NWS) Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). The WRF EMS is a complete, full physics numerical weather prediction package that incorporates dynamical cores from both the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). The installation, configuration, and execution of either the ARW or NMM models is greatly simplified by the WRF EMS to encourage its use by NWS Weather Forecast Offices (WFOs) and the university community. The WRF EMS is easy to run on most Linux workstations and clusters without the need for compilers. Version 3 of the WRF EMS contains the most recent public release of the WRF-NMM and ARW modeling system (version 3 of the ARW is described in Skamarock et al. 2008), the WRF Pre-processing System (WPS) utilities, and the WRF Post-Processing program. The system is developed and maintained by the NWS National Science Operations Officer Science and Training Resource Coordinator. To initialize the WRF EMS with high-resolution MODIS SSTs, SPoRT developed the composite product consisting of MODIS SSTs over oceans and large lakes with the NCEP Real-Time Global (RTG) filling data over land points. Filling the land points is required due to minor inconsistencies between the WRF land-sea mask and that used to generate the MODIS SST composites. This methodology ensures a continuous field that adequately initializes all appropriate arrays in WRF. MODIS composites covering the Gulf of Mexico, western Atlantic Ocean and the Caribbean are generated daily at 0400, 0700, 1600, and 1900 UTC corresponding to overpass times of the NASA Aqua and Terra polar orbiting satellites. The MODIS SST product is output in gridded binary-1 (GRIB-1) data format for a seamless incorporation into WRF via the WPS utilities. The full-resolution, 1-km MODIS product is sub-sampled to 2-km grid spacing due to limitations in handling very large dimensions in the GRIB-1 data format. The GRIB-1 files are posted online at ftp://ftp.nsstc.org/sstcomp/WRF/, which is directly accessed by the WRF EMS scripts. The MODIS SST composites are also downloaded to the EMS data server, which is accessible by the WRF EMS users and NWS WFOs. The SPoRT MODIS SST composite provides the model with superior detail of the ocean gradients around Florida and surrounding waters, whereas the operational RTG SST typically depicts a relatively smooth field and is not able to capture sharp horizontal gradients in SST. Differences of 2-3 C are common over small horizontal distances, leading to enhanced SST gradients on either side of the Gulf Stream and along the edges of the cooler shelf waters. These sharper gradients can in turn produce atmospheric responses in simulated temperature and wind fields as depicted in LaCasse et al. Differences in atmospheric verification statistics over a several month study were generally small in the vicinity of south Florida; however, the validation of SSTs at specific buoy locations revealed important improvements in the biases and RMS errors, especially in the vicinity of the cooler shelf waters off the east-central Florida coast. A current weakness in the MODIS SST product is the occurrence of occasional discontinuities caused by high latency in SST coverage due to persistent cloud cover. An enhanced method developed by Jedlovec et al. (2009, GHRSST User Symposium) reduces the occurrence of these problems by adding Advanced Microwave Scanning Radiometer -- EOS (AMSR-E) SST data to the compositing process. Enhanced SST composites are produced over the ocean regions surrounding the Continental U.S. at four times each day corresponding to Terra and Aqua equator crossing times. For a given day and overpass time, both MODInd AMSR-E data from the previous seven days form a collection used in the compositing. At each MODIS pixel, cloud-free SST values from the collection are used to form a weighted average based on their latency (number of days from the current day). In this way, recent SST data are given more weight than older data. One of the primary issues involved in incorporating the AMSR-E microwave data in the composites is the tradeoff between the decreased spatial resolution of the AMSR-E data (25 km) and the increased coverage due to its near all-weather capability. Currently, the AMSR-E is given a weight of 20% compared to MODIS data, thereby preserving the spatial structure observed in the MODIS data. Day-time (night-time) AMSR-E SST data from Aqua are used with both Terra and Aqua MODIS day-time (night-time) SST data sets

New Mechanics of Spinal Injury

The prediction and prevention of spinal injury is an important aspect of preventive health science. The spine, or vertebral column, represents a chain of 26 movable vertebral bodies, joint together by transversal viscoelastic intervertebral discs and longitudinal elastic tendons. This paper proposes a new locally-coupled loading-rate hypothesis}, which states that the main cause of both soft- and hard-tissue spinal injury is a localized Euclidean jolt, or SE(3)-jolt, an impulsive loading that strikes a localized spine in several coupled degrees-of-freedom simultaneously. To show this, based on the previously defined covariant force law, we formulate the coupled Newton-Euler dynamics of the local spinal motions and derive from it the corresponding coupled SE(3)-jolt dynamics. The SE(3)-jolt is the main cause of two basic forms of spinal injury: (i) hard-tissue injury of local translational dislocations; and (ii) soft-tissue injury of local rotational disclinations. Both the spinal dislocations and disclinations, as caused by the SE(3)-jolt, are described using the Cosserat multipolar viscoelastic continuum model. Keywords: localized spinal injury, coupled loading-rate hypothesis, coupled Newton-Euler dynamics, Euclidean jolt dynamics, spinal dislocations and disclinationsComment: 14 pages, 1 figure, Late

The Gait Profile Score and Movement Analysis Profile

The Gait Deviation Index (GDI) has been proposed as an index of overall gait pathology. This study proposesan interpretation of the difference measure upon which the GDI is based, which naturally leads to thedefinition of a similar index, the Gait Profile Score (GPS). The GPS can be calculated independently of thefeature analysis upon which the GDI is based. Understanding what the underlying difference measurerepresents also suggests that reporting a raw score, as the GPS does, may have advantages over thelogarithmic transformation and z-scaling incorporated in the GDI. It also leads to the concept of aMovement Analysis Profile(MAP) to summarisemuch of the information contained within kinematic data.A validation study on all children attending a paediatric gait analysis service over 3 years (407children) provides evidence to support the use of the GPS through analysis of its frequency distributionacross different Gross Motor Function Classification System(GMFCS) and Gillette Functional AssessmentQuestionnaire (FAQ) categories, investigation of intra-session variability, and correlation with the squareroot of GGI. Correlation with GDI confirms the strong relationship between the two measures.The study concludes that GDI and GPS are alternative and closely related measures. The GDI has priorart and is particularly useful in applications arising out of feature analysis such as cluster analysis orsubject matching. The GPS will be easier to calculate for new models where a large reference dataset isnot available and in association with applications using the MAP

A new method for evaluating ankle foot orthosis characteristics: BRUCE

The mechanical characteristics of ankle foot orthoses (AFOs), such as the stiffness and neutral angle around the ankle and metatarsal-phalangeal (MTP) joints, are rarely quantified. Paradoxically, it is expected that these characteristics determine the function of the AFO in pathological gait. Therefore a device to determine these AFO characteristics named BRUCE was designed based on multidisciplinary consensus. The design is based on a replicated human leg that is manually driven and continuously registers joint configuration and force exerted by the AFO onto the device. From this information, neutral angles and stiffnesses around the ankle and MTP joints are determined using a linear fit. The reliability of the stiffnesses and neutral angles was studied by repeatedly measuring the mechanical characteristics of four different AFOs, and evaluating the inter-session, intra-session, and inter-observer errors. The reliability study revealed that ankle and MTP stiffness could be measured with very high reliability (ICC = 0.98-1.00). Ankle and MTP neutral angles showed reasonable reliability (ICC = 0.79-0.92). Measurement error in the neutral angles could mainly be attributed to the difference in testers. With a fixed tester excellent reliability was obtained (ICC = 0.99-0.99). The results derived using BRUCE can help to gain insight into the role of the mechanical characteristics of AFOs in correcting pathological gait. Objective information of AFO characteristics is expected to lead to a better founded prescription of AFOs, resulting in optimal functional benefit for the patient. © 2009 Elsevier B.V