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NASA NTRS2004

Research Infusion Collaboration: Finding Defect Patterns in Reused Code

The 'Finding Defect Patterns in Reused Code' Research Infusion Collaboration was performed by Jet Propulsion Laboratory/Caltech under Contract 104-07-02.679 102 197 08.14.4. This final report describes the collaboration and documents the findings, including lessons learned.The research infusion collaboration characterized, using Orthogonal Defect Classification, defect reports for code that will be reused in mission-critical software on Deep Space Network Antenna controllers. Code reuse is estimated to be 90%, so it is important to identify systemic defects, or patterns, prior to reuse of this code. The work also identified ways to avoid certain types of defects and to test more efficiently.The primary objectives of the project were:to analyze defect patterns of the code to be reused based on the defects'Orthogonal Defect Classification (ODC)and to achieve a successful infusion of ODC to a project.

orthogonal defect classification (ODC)↗

NASA NTRS2008

Spiking Neurons for Analysis of Patterns

Artificial neural networks comprising spiking neurons of a novel type have been conceived as improved pattern-analysis and pattern-recognition computational systems. These neurons are represented by a mathematical model denoted the state-variable model (SVM), which among other things, exploits a computational parallelism inherent in spiking-neuron geometry. Networks of SVM neurons offer advantages of speed and computational efficiency, relative to traditional artificial neural networks. The SVM also overcomes some of the limitations of prior spiking-neuron models. There are numerous potential pattern-recognition, tracking, and data-reduction (data preprocessing) applications for these SVM neural networks on Earth and in exploration of remote planets. Spiking neurons imitate biological neurons more closely than do the neurons of traditional artificial neural networks. A spiking neuron includes a central cell body (soma) surrounded by a tree-like interconnection network (dendrites). Spiking neurons are so named because they generate trains of output pulses (spikes) in response to inputs received from sensors or from other neurons. They gain their speed advantage over traditional neural networks by using the timing of individual spikes for computation, whereas traditional artificial neurons use averages of activity levels over time. Moreover, spiking neurons use the delays inherent in dendritic processing in order to efficiently encode the information content of incoming signals. Because traditional artificial neurons fail to capture this encoding, they have less processing capability, and so it is necessary to use more gates when implementing traditional artificial neurons in electronic circuitry. Such higher-order functions as dynamic tasking are effected by use of pools (collections) of spiking neurons interconnected by spike-transmitting fibers. The SVM includes adaptive thresholds and submodels of transport of ions (in imitation of such transport in biological neurons). These features enable the neurons to adapt their responses to high-rate inputs from sensors, and to adapt their firing thresholds to mitigate noise or effects of potential sensor failure. The mathematical derivation of the SVM starts from a prior model, known in the art as the point soma model, which captures all of the salient properties of neuronal response while keeping the computational cost low. The point-soma latency time is modified to be an exponentially decaying function of the strength of the applied potential. Choosing computational efficiency over biological fidelity, the dendrites surrounding a neuron are represented by simplified compartmental submodels and there are no dendritic spines. Updates to the dendritic potential, calcium-ion concentrations and conductances, and potassium-ion conductances are done by use of equations similar to those of the point soma. Diffusion processes in dendrites are modeled by averaging among nearest-neighbor compartments. Inputs to each of the dendritic compartments come from sensors. Alternatively or in addition, when an affected neuron is part of a pool, inputs can come from other spiking neurons. At present, SVM neural networks are implemented by computational simulation, using algorithms that encode the SVM and its submodels. However, it should be possible to implement these neural networks in hardware: The differential equations for the dendritic and cellular processes in the SVM model of spiking neurons map to equivalent circuits that can be implemented directly in analog very-large-scale integrated (VLSI) circuits.

Huntsberger, Terrance↗

NASA NTRS2008

Pattern-Recognition System for Approaching a Known Target

A closed-loop pattern-recognition system is designed to provide guidance for maneuvering a small exploratory robotic vehicle (rover) on Mars to return to a landed spacecraft to deliver soil and rock samples that the spacecraft would subsequently bring back to Earth. The system could be adapted to terrestrial use in guiding mobile robots to approach known structures that humans could not approach safely, for such purposes as reconnaissance in military or law-enforcement applications, terrestrial scientific exploration, and removal of explosive or other hazardous items. The system has been demonstrated in experiments in which the Field Integrated Design and Operations (FIDO) rover (a prototype Mars rover equipped with a video camera for guidance) is made to return to a mockup of Mars-lander spacecraft. The FIDO rover camera autonomously acquires an image of the lander from a distance of 125 m in an outdoor environment. Then under guidance by an algorithm that performs fusion of multiple line and texture features in digitized images acquired by the camera, the rover traverses the intervening terrain, using features derived from images of the lander truss structure. Then by use of precise pattern matching for determining the position and orientation of the rover relative to the lander, the rover aligns itself with the bottom of ramps extending from the lander, in preparation for climbing the ramps to deliver samples to the lander. The most innovative aspect of the system is a set of pattern-recognition algorithms that govern a three-phase visual-guidance sequence for approaching the lander. During the first phase, a multifeature fusion algorithm integrates the outputs of a horizontal-line-detection algorithm and a wavelet-transform-based visual-area-of-interest algorithm for detecting the lander from a significant distance. The horizontal-line-detection algorithm is used to determine candidate lander locations based on detection of a horizontal deck that is part of the lander.

Huntsberger, Terrance↗

NASA NTRS2008

Patterned Ferroelectric Films for Tunable Microwave Devices

Tunable microwave devices based on metal terminals connected by thin ferroelectric films can be made to perform better by patterning the films to include suitably dimensioned, positioned, and oriented constrictions. The patterns can be formed during fabrication by means of selective etching processes. If the width of the ferroelectric film in such a device is reduced at one or more locations, then both the microwave field and any applied DC bias (tuning) electric field become concentrated at those locations. The magnitudes of both the permittivity and the dielectric loss of a ferroelectric material are reduced by application of a DC field. Because the concentration of the DC field in the constriction(s) magnifies the permittivity- and loss-reducing effects of the applied DC voltage, the permittivity and dielectric loss in the constriction(s) are smaller in the constriction(s) than they are in the wider parts of the ferroelectric film. Furthermore, inasmuch as displacement current must flow through either the constriction(s) or the low-loss dielectric substrate, the net effect of the constriction(s) is equivalent to that of incorporating one or more low-loss, low-permittivity region(s) in series with the high-loss, high-permittivity regions. In a series circuit, the properties of the low-capacitance series element (in this case, the constriction) dominate the overall performance. Concomitantly, the capacitance between the metal terminals is reduced. By making the capacitance between the metal terminals small but tunable, a constriction increases the upper limit of the frequency range amenable to ferroelectric tuning. The present patterning concept is expected to be most advantageous for devices and circuits that must operate at frequencies from about 4 to about 60 GHz. A constriction can be designed such that the magnitude of the microwave electric field and the effective width of the region occupied by the microwave electric field become functions of the applied DC electric field, so that tunability is enhanced. It should even be possible to design the constriction to obtain a specific tuning-versus-voltage profile.

Miranda, Felix A.↗

NASA NTRS2007

Pattern Matcher for Trees Constructed from Lists

A software library has been developed that takes a high-level description of a pattern to be satisfied and applies it to a target. If the two match, it returns success; otherwise, it indicates a failure. The target is semantically a tree that is constructed from elements of terminal and non-terminal nodes represented through lists and symbols. Additionally, functionality is provided for finding the element in a set that satisfies a given pattern and doing a tree search, finding all occurrences of leaf nodes that match a given pattern. This process is valuable because it is a new algorithmic approach that significantly improves the productivity of the programmers and has the potential of making their resulting code more efficient by the introduction of a novel semantic representation language. This software has been used in many applications delivered to NASA and private industry, and the cost savings that have resulted from it are significant.

James, Mark↗

NASA NTRS2007

Fabrication of Buried Nanochannels From Nanowire Patterns

A method of fabricating channels having widths of tens of nanometers in silicon substrates and burying the channels under overlying layers of dielectric materials has been demonstrated. With further refinement, the method might be useful for fabricating nanochannels for manipulation and analysis of large biomolecules at single-molecule resolution. Unlike in prior methods, burying the channels does not involve bonding of flat wafers to the silicon substrates to cover exposed channels in the substrates. Instead, the formation and burying of the channels are accomplished in a more sophisticated process that is less vulnerable to defects in the substrates and less likely to result in clogging of, or leakage from, the channels. In this method, the first step is to establish the channel pattern by forming an array of sacrificial metal nanowires on an SiO2-on-Si substrate. In particular, the wire pattern is made by use of focused-ion-beam (FIB) lithography and a subsequent metallization/lift-off process. The pattern of metal nanowires is then transferred onto the SiO2 layer by reactive-ion etching, which yields sacrificial SiO2 nanowires covered by metal. After removal of the metal covering the SiO2 nanowires, what remains are SiO2 nanowires on an Si substrate. Plasma-enhanced chemical vapor deposition (PECVD) is used to form a layer of a dielectric material over the Si substrate and over the SiO2 wires on the surface of the substrate. FIB milling is then performed to form trenches at both ends of each SiO2 wire. The trenches serve as openings for the entry of chemicals that etch SiO2 much faster than they etch Si. Provided that the nanowires are not so long that the diffusion of the etching chemicals is blocked, the sacrificial SiO2 nanowires become etched out from between the dielectric material and the Si substrate, leaving buried channels. At the time of reporting the information for this article, channels 3 m long, 20 nm deep, and 80 nm wide (see figure) had been fabricated by this method.

Choi, Daniel↗

NASA NTRS2006

Pattern-Recognition Algorithm for Locking Laser Frequency

A computer program serves as part of a feedback control system that locks the frequency of a laser to one of the spectral peaks of cesium atoms in an optical absorption cell. The system analyzes a saturation absorption spectrum to find a target peak and commands a laser-frequency-control circuit to minimize an error signal representing the difference between the laser frequency and the target peak. The program implements an algorithm consisting of the following steps: Acquire a saturation absorption signal while scanning the laser through the frequency range of interest. Condition the signal by use of convolution filtering. Detect peaks. Match the peaks in the signal to a pattern of known spectral peaks by use of a pattern-recognition algorithm. Add missing peaks. Tune the laser to the desired peak and thereafter lock onto this peak. Finding and locking onto the desired peak is a challenging problem, given that the saturation absorption signal includes noise and other spurious signal components; the problem is further complicated by nonlinearity and shifting of the voltage-to-frequency correspondence. The pattern-recognition algorithm, which is based on Hausdorff distance, is what enables the program to meet these challenges.

Karayan, Vahag↗

NASA NTRS2010

Flagging and Correction of Pattern Noise in the Kepler Focal Plane Array

In order for Kepler to achieve its required less than 20 PPM photometric precision for magnitude 12 and brighter stars, instrument-induced variations in the CCD readout bias pattern (our "2D black image"), which are either fixed or slowly varying in time, must be identified and the corresponding pixels either corrected or removed from further data processing. The two principle sources of these readout bias variations are crosstalk between the 84 science CCDs and the 4 fine guidance sensor (FGS) CCDs and a high frequency amplifier oscillation on less than 40% of the CCD readout channels. The crosstalk produces a synchronous pattern in the 2D black image with time-variation observed in less than 10% of individual pixel bias histories. We will describe a method of removing the crosstalk signal using continuously-collected data from masked and over-clocked image regions (our "collateral data"), and occasionally-collected full-frame images and reverse-clocked readout signals. We use this same set to detect regions affected by the oscillating amplifiers. The oscillations manifest as time-varying moir pattern and rolling bands in the affected channels. Because this effect reduces the performance in only a small fraction of the array at any given time, we have developed an approach for flagging suspect data. The flags will provide the necessary means to resolve any potential ambiguity between instrument-induced variations and real photometric variations in a target time series. We will also evaluate the effectiveness of these techniques using flight data from background and selected target pixels.

Kolodziejczak, Jeffery J.↗

NASA NTRS2011

The Analysis of the Patterns of Radiation-Induced DNA Damage Foci by a Stochastic Monte Carlo Model of DNA Double Strand Breaks Induction by Heavy Ions and Image Segmentation Software

To create a generalized mechanistic model of DNA damage in human cells that will generate analytical and image data corresponding to experimentally observed DNA damage foci and will help to improve the experimental foci yields by simulating spatial foci patterns and resolving problems with quantitative image analysis. Material and Methods: The analysis of patterns of RIFs (radiation-induced foci) produced by low- and high-LET (linear energy transfer) radiation was conducted by using a Monte Carlo model that combines the heavy ion track structure with characteristics of the human genome on the level of chromosomes. The foci patterns were also simulated in the maximum projection plane for flat nuclei. Some data analysis was done with the help of image segmentation software that identifies individual classes of RIFs and colocolized RIFs, which is of importance to some experimental assays that assign DNA damage a dual phosphorescent signal. Results: The model predicts the spatial and genomic distributions of DNA DSBs (double strand breaks) and associated RIFs in a human cell nucleus for a particular dose of either low- or high-LET radiation. We used the model to do analyses for different irradiation scenarios. In the beam-parallel-to-the-disk-of-a-flattened-nucleus scenario we found that the foci appeared to be merged due to their high density, while, in the perpendicular-beam scenario, the foci appeared as one bright spot per hit. The statistics and spatial distribution of regions of densely arranged foci, termed DNA foci chains, were predicted numerically using this model. Another analysis was done to evaluate the number of ion hits per nucleus, which were visible from streaks of closely located foci. In another analysis, our image segmentaiton software determined foci yields directly from images with single-class or colocolized foci. Conclusions: We showed that DSB clustering needs to be taken into account to determine the true DNA damage foci yield, which helps to determine the DSB yield. Using the model analysis, a researcher can refine the DSB yield per nucleus per particle. We showed that purely geometric artifacts, present in the experimental images, can be analytically resolved with the model, and that the quantization of track hits and DSB yields can be provided to the experimentalists who use enumeration of radiation-induced foci in immunofluorescence experiments using proteins that detect DNA damage. An automated image segmentaiton software can prove useful in a faster and more precise object counting for colocolized foci images.

Ponomarev, Artem↗

NASA NTRS2011

Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.

Restrepo, Carolina↗

NASA NTRS2005

Artificial Immune System for Recognizing Patterns

A method of recognizing or classifying patterns is based on an artificial immune system (AIS), which includes an algorithm and a computational model of nonlinear dynamics inspired by the behavior of a biological immune system. The method has been proposed as the theoretical basis of the computational portion of a star-tracking system aboard a spacecraft. In that system, a newly acquired star image would be treated as an antigen that would be matched by an appropriate antibody (an entry in a star catalog). The method would enable rapid convergence, would afford robustness in the face of noise in the star sensors, would enable recognition of star images acquired in any sensor or spacecraft orientation, and would not make an excessive demand on the computational resources of a typical spacecraft. Going beyond the star-tracking application, the AIS-based pattern-recognition method is potentially applicable to pattern- recognition and -classification processes for diverse purposes -- for example, reconnaissance, detecting intruders, and mining data.

Huntsberger, Terrance↗

NASA NTRS2011

Control of Stationary Cross-Flow Modes in a Mach 3.5 Boundary Layer Using Patterned Passive and Active Roughness

Spanwise-periodic roughness designed to excite selected wavelengths of stationary cross- ow modes was investigated in a 3-D boundary layer at Mach 3.5. The test model was a sharp-tipped 14deg right-circular cone. The model and integrated sensor traversing system were placed in the Mach 3.5 Supersonic Low Disturbance Tunnel (SLDT) equipped with a "quiet design" nozzle at the NASA Langley Research Center. The model was oriented at a 4:2deg angle of attack to produce a mean cross-fl ow velocity component in the boundary layer over the cone. Five removable cone tips have been investigated. One has a smooth surface that is used to document the baseline ("natural") conditions. Two had minute (20 - 40 micron) "dimples" that are equally spaced around the circumference, at a streamwise location that is just upstream of the linear stability neutral growth branch for cross- ow modes. The azimuthal mode numbers of the dimpled tips were selected to either enhance the most amplified wave numbers, or to suppress the growth of the most amplified wave numbers. Two of the cone tips had an array of plasma streamwise vortex generators that were designed to simulate the disturbances produced by the passive patterned roughness. The results indicate that the stationary cross-fl ow modes were highly receptive to the patterned roughness of both passive and active types. The patterned passive roughness that was designed to suppress the growth of the most amplified modes had an azimuthal wavelength that was 66% smaller that that of the most amplified stationary cross- ow mode. This had the effect to increase the transition Reynolds number from 25% to 50% depending on the measurement technique. The application of the research is on turbulent transition control on swept wings of supersonic aircraft. The plasma-based roughness has the advantage over the passive roughness of being able to be adaptable to different conditions that would occur during a flight mission.

Schuele, Chan Yong↗

NASA NTRS2012

Conditions for Symmetries in the Buckle Patterns of Laminated-Composite Plates

Conditions for the existence of certain symmetries to exist in the buckle patterns of symmetrically laminated composite plates are presented. The plates considered have a general planform with cutouts, variable thickness and stiffnesses, and general support and loading conditions. The symmetry analysis is based on enforcing invariance of the corresponding eigenvalue problem for a group of coordinate transformations associated with buckle patterns commonly exhibited by symmetrically laminated plates. The buckle-pattern symmetries examined include a central point of inversion symmetry, one plane of reflective symmetry, and two planes of reflective symmetry.

Nemeth, Michael P.↗

NASA NTRS2012

An In-Depth Study of the Abundance Pattern in the Hot Interstellar Medium in NGC 4649

We present our X-ray imaging spectroscopic analysis of data from deep Suzuku and XMM-Newton Observatory exposures of the Virgo Cluster elliptical galaxy NGC 4649 (M60), focusing on the abundance pattern in the hot interstellar medium (ISM). All measured elements show a radial decline in abundance, with the possible exception of O. We construct steady state solutions to the chemical evolution equations that include infall in addition to stellar mass return and SNIa enrichment, and consider recently published SNIa yields. By adjusting a single model parameter to obtain a match to the global abundance pattern in NGC 4649 we infer that accretion of subsolar metallicity external gas has reduced the overall ISM metallicity and diluted the effectiveness of SNIa to skew the pattern towards low alpha/Fe ratios, and estimate the combination of SNIa rate and level of dilution. Evidently, newly-introduced gas is heated as it is integrated into. and interacts with, the hot gas that is already present. These results indicate a complex flow and enrichment history for NGC 4649, reflecting the continual evolution of elliptical galaxies beyond the formation epoch. The heating and circulation of accreted gas may help reconcile this dynamic history with the mostly passive evolution of elliptical stellar populations. In an appendix we examine the effects of the recent updated atomic database AtomDB in spectral fitting of thermal plasmas with hot ISM temperatures in the elliptical galaxy range.

Lowenstein, Michael↗

NASA NTRS2012

Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap formation at these sites illustrate potential issues for separating logging damages from natural forest disturbances over longer time scales. Multi-temporal airborne LiDAR data and coincident field measurements provide complementary perspectives on disturbance and recovery processes in intact and degraded Amazon forests. Compared to forest inventory plots, the large size of each individual site permitted analyses of landscape-scale processes that would require extremely high investments to study using traditional forest inventory methods.

Morton, D. C.↗

NASA NTRS2012

Patterns In Debris Disks: No Planets Required?

Debris disks like those around Fomalhaut and Beta Pictoris show striking dust patterns often attributed to hidden exoplanets. These patterns have been crucial for constraining the masses and orbits of these planets. But adding a bit of gas to our models of debris disks--too little gas to detect--seems to alter this interpretation. Small amounts of gas lead to new dynamical instabilities that may mimic the narrow eccentric rings and other structures planets would create in a gas-free disk. Can we still use dust patterns to find hidden exoplanets?

Kuchner, Marc↗

NASA NTRS2012

An In-Depth Study of the Abundance Pattern in the Hot Interstellar Medium in NGC 4649

We present our X-ray imaging spectroscopic analysis of data from deep Suzaku and XMM-Newton Observatory exposures of the Virgo Cluster elliptical galaxy NGC 4649 (M60), focusing on the abundance pattern in the hot interstellar medium (ISM). All measured elements show a radial decline in abundance, with the possible exception of Oxygen. We construct steady state solutions to the chemical evolution equations that include infall in addition to stellar mass return and Type Ia supernovae (SNIa) enrichment, and consider recently published SNIa yields. By adjusting a single model parameter to obtain a match to the global abundance pattern in NGC 4649 we infer that introduction of subsolar metallicity external gas has reduced the overall ISM metallicity and diluted the effectiveness of SNIa to skew the pattern towards low alpha/Fe ratios, and estimate the combination of SNIa rate and level of dilution. Evidently, newly-introduced gas is heated as it is integrated into, and interacts with, the hot gas that is already present. These results indicate a complex flow and enrichment history for NGC 4649, reflecting the continual evolution of elliptical galaxies beyond the formation epoch. The heating and circulation of accreted gas may help reconcile this dynamic history with the mostly passive evolution of elliptical stellar populations. In an appendix we examine the effects of the recent updated atomic database AtomDB in spectral fitting of thermal plasmas with hot ISM temperatures in the elliptical galaxy range.

Loewenstein, Michael↗

NASA NTRS2013

Probability of US Heat Waves Affected by a Subseasonal Planetary Wave Pattern

Heat waves are thought to result from subseasonal atmospheric variability. Atmospheric phenomena driven by tropical convection, such as the Asian monsoon, have been considered potential sources of predictability on subseasonal timescales. Mid-latitude atmospheric dynamics have been considered too chaotic to allow significant prediction skill of lead times beyond the typical 10-day range of weather forecasts. Here we use a 12,000-year integration of an atmospheric general circulation model to identify a pattern of subseasonal atmospheric variability that can help improve forecast skill for heat waves in the United States. We find that heat waves tend to be preceded by 15-20 days by a pattern of anomalous atmospheric planetary waves with a wavenumber of 5. This circulation pattern can arise as a result of internal atmospheric dynamics and is not necessarily linked to tropical heating.We conclude that some mid-latitude circulation anomalies that increase the probability of heat waves are predictable beyond the typical weather forecast range.

Mid-Latitude Circulation↗