scholarly journals A Novel Set of Geometric Verification Test Fields with Application to Distance Measures

2020 ◽  
Vol 148 (4) ◽  
pp. 1653-1673 ◽  
Author(s):  
Eric Gilleland ◽  
Gregor Skok ◽  
Barbara G. Brown ◽  
Barbara Casati ◽  
Manfred Dorninger ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Distance Measures ◽  
Small Scale ◽  
Second Phase ◽  
Clear Sky ◽  
A Value ◽  
Verification Methods ◽  
Intercomparison Project ◽  
Grid Points ◽  
Domain Iii

Abstract As part of the second phase of the spatial forecast verification intercomparison project (ICP), dubbed the Mesoscale Verification Intercomparison in Complex Terrain (MesoVICT) project, a new set of idealized test fields is prepared. This paper describes these new fields and their rationale and uses them to analyze a number of summary measures associated with distance and geometric-based approaches. The results provide guidance about how they inform about performance under various scenarios. The new case comparisons are grouped into four categories: (i) pathological situations such as when a variable is zero valued at all grid points; (ii) circular events aimed at evaluating how different methods handle contrived situations, such as equal but opposite translations, the presence of multiple events of same/different size, boundary effects, and the influence of the positioning of events in the domain; (iii) elliptical events representing simplified scenarios that mimic commonly encountered weather phenomena in complex terrain; and (iv) cases aimed at analyzing how the verification methods handle small-scale scattered events, very large events with holes (e.g., a small portion of clear sky on a cloudy overcast day), and the presence of noise in one or both fields. Results show that all analyzed measures perform poorly in the pathological setting. They are either not able to provide a result at all or they instigate a special rule to prescribe a value resulting in erratic results. The analysis also showed that methods provide similar information in many situations, but that each has its positive properties along with certain unique limitations.

The Setup of the MesoVICT Project

2018 ◽  
Vol 99 (9) ◽  
pp. 1887-1906 ◽  
Author(s):  
Manfred Dorninger ◽  
Eric Gilleland ◽  
Barbara Casati ◽  
Marion P. Mittermaier ◽  
Elizabeth E. Ebert ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Weather Prediction ◽  
Second Phase ◽  
Forecast Errors ◽  
Ensemble Forecasts ◽  
Verification Method ◽  
Verification Methods ◽  
Central United States ◽  
Diagnostic Capabilities ◽  
Spatial Verification

AbstractRecent advancements in numerical weather prediction (NWP) and the enhancement of model resolution have created the need for more robust and informative verification methods. In response to these needs, a plethora of spatial verification approaches have been developed in the past two decades. A spatial verification method intercomparison was established in 2007 with the aim of gaining a better understanding of the abilities of the new spatial verification methods to diagnose different types of forecast errors. The project focused on prescribed errors for quantitative precipitation forecasts over the central United States. The intercomparison led to a classification of spatial verification methods and a cataloging of their diagnostic capabilities, providing useful guidance to end users, model developers, and verification scientists. A decade later, NWP systems have continued to increase in resolution, including advances in high-resolution ensembles. This article describes the setup of a second phase of the verification intercomparison, called the Mesoscale Verification Intercomparison over Complex Terrain (MesoVICT). MesoVICT focuses on the application, capability, and enhancement of spatial verification methods to deterministic and ensemble forecasts of precipitation, wind, and temperature over complex terrain. Importantly, this phase also explores the issue of analysis uncertainty through the use of an ensemble of meteorological analyses.

scholarly journals Intercomparison of Spatial Forecast Verification Methods

2009 ◽  
Vol 24 (5) ◽  
pp. 1416-1430 ◽  
Author(s):  
Eric Gilleland ◽  
David Ahijevych ◽  
Barbara G. Brown ◽  
Barbara Casati ◽  
Elizabeth E. Ebert
Keyword(s):  
Poor Performance ◽  
Weather Forecast ◽  
Small Scale ◽  
False Alarms ◽  
New Methods ◽  
Enhanced Resolution ◽  
Verification Methods ◽  
Forecast Models ◽  
Intercomparison Project ◽  
Basic Characteristics

Abstract Advancements in weather forecast models and their enhanced resolution have led to substantially improved and more realistic-appearing forecasts for some variables. However, traditional verification scores often indicate poor performance because of the increased small-scale variability so that the true quality of the forecasts is not always characterized well. As a result, numerous new methods for verifying these forecasts have been proposed. These new methods can mostly be classified into two overall categories: filtering methods and displacement methods. The filtering methods can be further delineated into neighborhood and scale separation, and the displacement methods can be divided into features based and field deformation. Each method gives considerably more information than the traditional scores, but it is not clear which method(s) should be used for which purpose. A verification methods intercomparison project has been established in order to glean a better understanding of the proposed methods in terms of their various characteristics and to determine what verification questions each method addresses. The study is ongoing, and preliminary qualitative results for the different approaches applied to different situations are described here. In particular, the various methods and their basic characteristics, similarities, and differences are described. In addition, several questions are addressed regarding the application of the methods and the information that they provide. These questions include (i) how the method(s) inform performance at different scales; (ii) how the methods provide information on location errors; (iii) whether the methods provide information on intensity errors and distributions; (iv) whether the methods provide information on structure errors; (v) whether the approaches have the ability to provide information about hits, misses, and false alarms; (vi) whether the methods do anything that is counterintuitive; (vii) whether the methods have selectable parameters and how sensitive the results are to parameter selection; (viii) whether the results can be easily aggregated across multiple cases; (ix) whether the methods can identify timing errors; and (x) whether confidence intervals and hypothesis tests can be readily computed.

scholarly journals Novel measures for summarizing high-resolution forecast performance

2021 ◽  
Vol 7 (1) ◽  
pp. 13-34
Author(s):  
Eric Gilleland
Keyword(s):  
High Resolution ◽  
Perfect Match ◽  
Small Scale ◽  
Worst Case ◽  
Forecast Performance ◽  
New Methods ◽  
A Value ◽  
Spatial Alignment ◽  
Single User ◽  
Grid Points

Abstract. In ascertaining the performance of a high-resolution gridded forecast against an analysis, called the verification set, on the same grid, care must be taken to account for the over-accumulation of small-scale errors and double penalties. It is also useful to consider both location errors and intensity errors. In the last 2 decades, many new methods have been proposed for analyzing these kinds of verification sets. Many of these new methods involve fairly complicated strategies that do not naturally summarize forecast performance succinctly. This paper presents two new spatial-alignment performance measures, G and Gβ. The former is applied without any requirement for user decisions, while the latter has a single user-chosen parameter, β, that takes on a value from zero to one, where one corresponds to a perfect match and zero corresponds to the user's notion of a worst case. Unlike any previously proposed distance-based measure, both handle the often-encountered case in which all values in one or both of the verification set are zero. Moreover, its value is consistent if only a few grid points are nonzero.

Values Underlying Preferences for Adaptive Governance in a Chilean Small-Scale Fishing Community

2020 ◽  
Author(s):  
Sarah A. Ebel ◽  
Christine M. Beitl ◽  
Michael P. Torre
Keyword(s):  
Environmental Change ◽  
Environmental Governance ◽  
Small Scale ◽  
Adaptive Governance ◽  
Fishing Community ◽  
A Value ◽  
Ways Of Life ◽  
Value Frames

Environmental change requires individuals and institutions to facilitate adaptive governance. However, facilitating adaptive governance may be difficult because resource users’ perceptions of desirable ways of life vary. These perceptions influence preferences related to environmental governance and may stem from the ways individuals subjectively value their work and their connections to their environment. This paper uses a value-based approach to examine individual and institutional preferences for adaptive governance in Carelmapu, Chile. We show that two groups had different value frames rooted in divergent ontologies which influenced their actions related to adaptive governance, creating conflict.

Heat-flow experiments in liquid 4He with a variable cylindrical geometry

1987 ◽  
Vol 174 ◽  
pp. 209-231 ◽  
Author(s):  
H. Gao ◽  
G. Metcalfe ◽  
T. Jung ◽  
R. P. Behringer
Keyword(s):  
Cylindrical Geometry ◽  
Small Scale ◽  
Onset Of Convection ◽  
Aspect Ratios ◽  
A Value ◽  
Prandtl Numbers ◽  
Convection Rolls ◽  
Flow Experiments ◽  
Increasing Function ◽  
Good Agreement

This paper first describes an apparatus for measuring the Nusselt number N versus the Rayleigh number R of convecting normal liquid 4He layers. The most important feature of the apparatus is its ability to provide layers of different heights d, and hence different aspect ratios [Gcy ]. The horizontal cross-section of each layer is circular, and [Gcy ] is defined by [Gcy ] = D/2d where D is the diameter of the layer. We report results for 2.4 [les ] [Gcy ] [les ] 16 and for Prandtl numbers Pr spanning 0.5 [lsim ] Pr [lsim ] 0.9 These results are presented in terms of the slope N1 = RcdN/dR evaluated just above the onset of convection at Rc. We find that N1 is only a slowly increasing function of [Gcy ] in the range 6 [lsim ] [Gcy ] [lsim ] 16, and that it has a value there which is quite close to 0.72. This value of N1 is in good agreement with variational calcuations by Ahlers et al. (1981) pertinent to parallel convection rolls in cylindrical geometry. Particularly for [Gcy ] [lsim ] 6, we find additional small-scale structure in N1 associated with changes in the number of convection rolls with changing [Gcy ]. An additional test of the linearzied hydrodynamics is given by measurements of Rc. We find good agreement between theory and our data for Rc.

scholarly journals Multiscale Mountain Waves Influencing a Major Orographic Precipitation Event

2007 ◽  
Vol 64 (3) ◽  
pp. 711-737 ◽  
Author(s):  
Matthew F. Garvert ◽  
Bradley Smull ◽  
Cliff Mass
Keyword(s):  
Mesoscale Model ◽  
Precipitation Forecast ◽  
Precipitation Event ◽  
Small Scale ◽  
Second Phase ◽  
Mountain Waves ◽  
Low Level ◽  
Orographic Rainfall ◽  
Vertically Propagating ◽  
Horizontal Wavelength

Abstract This study combines high-resolution mesoscale model simulations and comprehensive airborne Doppler radar observations to identify kinematic structures influencing the production and mesoscale distribution of precipitation and microphysical processes during a period of heavy prefrontal orographic rainfall over the Cascade Mountains of Oregon on 13–14 December 2001 during the second phase of the Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE-2) field program. Airborne-based radar detection of precipitation from well upstream of the Cascades to the lee allows a depiction of terrain-induced wave motions in unprecedented detail. Two distinct scales of mesoscale wave–like air motions are identified: 1) a vertically propagating mountain wave anchored to the Cascade crest associated with strong midlevel zonal (i.e., cross barrier) flow, and 2) smaller-scale (<20-km horizontal wavelength) undulations over the windward foothills triggered by interaction of the low-level along-barrier flow with multiple ridge–valley corrugations oriented perpendicular to the Cascade crest. These undulations modulate cloud liquid water (CLW) and snow mixing ratios in the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5), with modeled structures comparing favorably to radar-documented zones of enhanced reflectivity and CLW measured by the NOAA P3 aircraft. Errors in the model representation of a low-level shear layer and the vertically propagating mountain waves are analyzed through a variety of sensitivity tests, which indicated that the mountain wave’s amplitude and placement are extremely sensitive to the planetary boundary layer (PBL) parameterization being employed. The effects of 1) using unsmoothed versus smoothed terrain and 2) the removal of upstream coastal terrain on the flow and precipitation over the Cascades are evaluated through a series of sensitivity experiments. Inclusion of unsmoothed terrain resulted in net surface precipitation increases of ∼4%–14% over the windward slopes relative to the smoothed-terrain simulation. Small-scale waves (<20-km horizontal wavelength) over the windward slopes significantly impact the horizontal pattern of precipitation and hence quantitative precipitation forecast (QPF) accuracy.

scholarly journals Statistical analysis in support of maintaining a healthy traditional Siamese cat population

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Arthur M. A. Pistorius ◽  
Ineke Blokker
Keyword(s):  
Genetic Diversity ◽  
Cluster Analysis ◽  
Companion Animals ◽  
Hereditary Diseases ◽  
Small Scale ◽  
Genetic Traits ◽  
Inbreeding Coefficients ◽  
A Value ◽  
Siamese Cat ◽  
Line Breeding

Abstract Background For many years, breeders of companion animals have applied inbreeding or line breeding to transfer desirable genetic traits from parents to their offspring. Simultaneously, this resulted in a considerable spread of hereditary diseases and phenomena associated with inbreeding depression. Results Our cluster analysis of kinship and inbreeding coefficients suggests that the Thai or traditional Siamese cat could be considered as a subpopulation of the Siamese cat, which shares common ancestors, although they are considered as separate breeds. In addition, model-based cluster analysis could detect regional differences between Thai subpopulations. We show that by applying optimal contribution selection and simultaneously limiting the contributions by other breeds, the genetic diversity within subpopulations can be improved. Conclusion In principle, the European mainland Thai cat population can achieve a genetic diversity of about 26 founder genome equivalents, a value that could potentially sustain a genetically diverse population. However, reaching such a target will be difficult in the absence of a supervised breeding program. Suboptimal solutions can be obtained by minimisation of kinships within regional subpopulations. Exchanging animals between different regions on a small scale might be already quite useful to reduce the kinship, by achieving a potential diversity of 23 founder genome equivalents. However, contributions by other breeds should be minimised to preserve the original Siamese gene pool.

Evaluation of Surface Analyses and Forecasts with a Multiscale Ensemble Kalman Filter in Regions of Complex Terrain

2011 ◽  
Vol 139 (6) ◽  
pp. 2008-2024 ◽  
Author(s):  
Brian C. Ancell ◽  
Clifford F. Mass ◽  
Gregory J. Hakim
Keyword(s):  
Kalman Filter ◽  
High Resolution ◽  
Data Assimilation ◽  
Ensemble Kalman Filter ◽  
Complex Terrain ◽  
Error Variance ◽  
Small Scale ◽  
Observation Error ◽  
Grid Spacing ◽  
Background Error

Abstract Previous research suggests that an ensemble Kalman filter (EnKF) data assimilation and modeling system can produce accurate atmospheric analyses and forecasts at 30–50-km grid spacing. This study examines the ability of a mesoscale EnKF system using multiscale (36/12 km) Weather Research and Forecasting (WRF) model simulations to produce high-resolution, accurate, regional surface analyses, and 6-h forecasts. This study takes place over the complex terrain of the Pacific Northwest, where the small-scale features of the near-surface flow field make the region particularly attractive for testing an EnKF and its flow-dependent background error covariances. A variety of EnKF experiments are performed over a 5-week period to test the impact of decreasing the grid spacing from 36 to 12 km and to evaluate new approaches for dealing with representativeness error, lack of surface background variance, and low-level bias. All verification in this study is performed with independent, unassimilated observations. Significant surface analysis and 6-h forecast improvements are found when EnKF grid spacing is reduced from 36 to 12 km. Forecast improvements appear to be a consequence of increased resolution during model integration, whereas analysis improvements also benefit from high-resolution ensemble covariances during data assimilation. On the 12-km domain, additional analysis improvements are found by reducing observation error variance in order to address representativeness error. Removing model surface biases prior to assimilation significantly enhances the analysis. Inflating surface wind and temperature background error variance has large impacts on analyses, but only produces small improvements in analysis RMS errors. Both surface and upper-air 6-h forecasts are nearly unchanged in the 12-km experiments. Last, 12-km WRF EnKF surface analyses and 6-h forecasts are shown to generally outperform those of the Global Forecast System (GFS), North American Model (NAM), and the Rapid Update Cycle (RUC) by about 10%–30%, although these improvements do not extend above the surface. Based on these results, future improvements in multiscale EnKF are suggested.

HIDDEN MARKOV MODELS IN TEXT RECOGNITION

1995 ◽  
Vol 09 (06) ◽  
pp. 925-958 ◽  
Author(s):  
J.C. ANIGBOGU ◽  
A. BELAÏD
Keyword(s):  
Hidden Markov Models ◽  
Character Recognition ◽  
Markov Models ◽  
Hidden Markov ◽  
Majority Vote ◽  
The Other ◽  
Distance Measures ◽  
Original Form ◽  
Verification Methods ◽  
Font Identification

A multi-level multifont character recognition is presented. The system proceeds by first delimiting the context of the characters. As a way of enhancing system performance, typographical information is extracted and used for font identification before actual character recognition is performed. This has the advantage of sure character identification as well as text reproduction in its original form. The font identification is based on decision trees where the characters are automatically arranged differently in confusion classes according to the physical characteristics of fonts. The character recognizers are built around the first and second order hidden Markov models (HMM) as well as Euclidean distance measures. The HMMs use the Viterbi and the Extended Viterbi algorithms to which enhancements were made. Also present is a majority-vote system that polls the other systems for “advice” before deciding on the identity of a character. Among other things, this last system is shown to give better results than each of the other systems applied individually. The system finally uses combinations of stochastic and dictionary verification methods for word recognition and error-correction.

scholarly journals Estimation of the terms acting on local surface one-hour temperature variations in Paris region: the specific contribution of clouds

2021 ◽  
Author(s):  
Oscar Rojas ◽  
Marjolaine Chiriaco ◽  
Sophie Bastin ◽  
Justine Ringard
Keyword(s):  
Heat Exchange ◽  
Radiative Forcing ◽  
Sensible Heat Flux ◽  
Surface Energy Budget ◽  
Small Scale ◽  
Radiative Effect ◽  
Temperature Variations ◽  
Annual Cycles ◽  
Clear Sky ◽  
Hourly Temperature

Abstract. Local temperature variations at the surface are mainly dominated by small-scale processes coupled through the surface energy budget terms, which depend mostly on radiation availability and thus cloud processes. A method to determine each of these terms based almost exclusively on observations is presented in this paper, with the main objective to estimate their importance in hourly surface temperature variations at the SIRTA observatory, near Paris. Almost all terms are estimated from the multi-year dataset SIRTA-ReOBS, following a few parametrizations. The four main terms acting on temperature variations are radiative forcing (separated into clear-sky and cloud radiation), atmospheric heat exchange, ground heat exchange, and advection. Compared to direct measurements of hourly temperature variations, it is shown that the sum of the four terms gives a good estimate of the hourly temperature variations, allowing a better assessment of the contribution of each term to the variation, with an accurate diurnal and annual cycles representation, especially for the radiative terms. A random forest analysis shows that whatever the season, clouds are the main modulator of the clear sky radiation for 1-hour temperature variations during the day, and mainly drive these 1-hour temperature variations during the night. Then, the specific role of clouds is analyzed exclusively in cloudy conditions considering the behavior of some classical meteorological variables along with lidar profiles. Cloud radiative effect in shortwave and longwave and lidar profiles show a consistent seasonality during the daytime, with a dominance of mid- and high-level clouds detected at the SIRTA observatory, which also affects surface temperatures and upward sensible heat flux. During the nighttime, despite cloudy conditions and having a strong cloud longwave radiative effect, temperatures are the lowest and are therefore mostly controlled by larger-scale processes at this time.

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