Harmonic Fitting Research Articles

Obtaining Continental‐Scale, High‐Resolution 2‐D Ionospheric Flows and Application to Meso‐Scale Flow Science

AbstractAn approach for creating continental‐scale, multi‐scale plasma convection maps in the nightside high‐latitude ionosphere using the spherical elementary current systems technique has been developed and evaluated. The capability to reconstruct meso‐scale flow channels improved dramatically, and the velocity errors were reduced by ∼30% compared to the spherical harmonic fitting method. Uncertainties of velocity vectors estimated by varying the model setup was also low. Convection maps for a substorm event revealed multiple flow channels in the polar cap, dominating the convection in the quiet time and early growth phase. The meso‐scale flows extended toward the nightside auroral oval and had continuous flow channels over >20° of latitude, and the flow channels dynamically merged and bifurcated. The substorm onset occurred along one of the flow channels, and the azimuthal extent of the enhanced flows coincided with the initial width of the auroral breakup. During the expansion phase, the meso‐scale flows repetitively crossed the oval poleward boundary, and some of them contributed to subauroral polarization streams enhancements. Increased flows extended duskward, along with the westward traveling surge. Then, flows near midnight weakened and evolved to the Harang flow shear. The meso‐scale flow channels had significant (∼10%–40% on average) contributions to the total plasma transport. The meso‐scale flows were highly variable on ∼10 min time scales and their individual maximum contributions reached upto 73%. These results demonstrate the capability of specifying realistic convection patterns, quantifying the contribution of meso‐scale transport, and evaluating the relationship between meso‐scale flows and localized auroral forms.

A New Rotating Axes Method for Processing High-Resolution Horizontal Velocity Measurements on EM-APEX floats

Abstract A new rotating axes method (RAM) is developed to improve the vertical resolution of the horizontal current velocity measurements u at EM-APEX floats. Unlike the traditional harmonic fitting method (HFM), which yields u averaged in 50-s intervals, RAM decodes and interprets 1-Hz measurements of horizontal seawater velocity , and averages in 12-s windows for removing wind waves with a typical peak frequency ∼ 0.12 Hz. Estimates of u from RAM agree with those from HFM but with a higher vertical resolution of ∼1.5 m, 4 times better than HFM. Note that extracting float signals due to seawater motion needs to assume slow-varying voltage offset ΔΦoffset. The typical variations of estimated ΔΦoffset do not affect the results of u significantly. Estimates of u are excluded when ΔΦoffset fluctuates strongly in time and scatter significantly. RAM is applied to float measurements taken near Mien-Hua Canyon, Taiwan. Composite vertical shear spectra Ψ computed using u from RAM exhibit a spectral slope of −1, as expected for the saturated internal waves in the vertical fine-scale range. The RAM provides EM-APEX float’s horizontal velocity measurements into fine vertical scales and will help improve our understanding of energy cascade from internal wave breaking and shear instability into turbulence mixing.

A Dual-Branch Speech Enhancement Model with Harmonic Repair

Recent speech enhancement studies have mostly focused on completely separating noise from human voices. Due to the lack of specific structures for harmonic fitting in previous studies and the limitations of the traditional convolutional receptive field, there is an inevitable decline in the auditory quality of the enhanced speech, leading to a decrease in the performance of subsequent tasks such as speech recognition and speaker identification. To address these problems, this paper proposes a Harmonic Repair Large Frame enhancement model, called HRLF-Net, that uses a harmonic repair network for denoising, followed by a real-imaginary dual branch structure for restoration. This approach fully utilizes the harmonic overtones to match the original harmonic distribution of speech. In the subsequent branch process, it restores the speech to specifically optimize its auditory quality to the human ear. Experiments show that under HRLF-Net, the intelligibility and quality of speech are significantly improved, and harmonic information is effectively restored.

High Variability Periods in the EEG Distinguish Cognitive Brain States.

To describe a novel measure of EEG signal variability that distinguishes cognitive brain states. We describe a novel characterization of amplitude variability in the EEG signal termed "High Variability Periods" or "HVPs", defined as segments when the standard deviation of a moving window is continuously higher than the quartile cutoff. We characterize the parameter space of the metric in terms of window size, overlap, and threshold to suggest ideal parameter choice and compare its performance as a discriminator of brain state to alternate single channel measures of variability such as entropy, complexity, harmonic regression fit, and spectral measures. We show that the average HVP duration provides a substantially distinct view of the signal relative to alternate metrics of variability and, when used in combination with these metrics, significantly enhances the ability to predict whether an individual has their eyes open or closed and is performing a working memory and Raven's pattern completion task. In addition, HVPs disappear under anesthesia and do not reappear in early periods of recovery. HVP metrics enhance the discrimination of various brain states and are fast to estimate. HVP metrics can provide an additional view of signal variability that has potential clinical application in the rapid discrimination of brain states.

Atmospheric Tides at Low Latitudes in the Martian Upper Atmosphere Observed by MAVEN IUVS

AbstractThe present work studies the variation of the wave 3 structure in the Martian upper atmosphere at low latitudes. CO2 densities produced by the Imaging Ultraviolet Spectrograph (IUVS) onboard the Mars Atmosphere and Volatile EvolutioN spacecraft from October 2014 to September 2021 are utilized to study the variation of the wave 3 structure under different seasons. By normalizing the densities to a fixed Extreme Ultraviolet level and applying harmonic fitting techniques, the wave 3 structures are derived from the IUVS observations. We find that the wave 3 structure tends to propagate eastward with increasing local time and altitude at low latitudes, which is consistent with the variability of the wave 3 structure at high latitudes. The altitudinal variation of the wave 3 structure also indicates that the dissipation effects become essential in the Martian upper atmosphere. By comparing the shifting speed of the wave structure with the phase speed of prominent tides in different seasons, we find that DE2 and SE1 jointly generate the wave 3 structure at low latitudes. This is confirmed by the seasonal variations of DE2 and SE1 proposed by Mars Climate Database (MCD) latitude‐Ls predictions. Comparisons of the MCD predictions with the height‐latitude amplitude distributions of the wave 3 structure reveal the existence of both DE2 and SE1 tides. By decomposing the wave 3 structure into latitudinal symmetric and antisymmetric components and comparing it with the first few Hough modes of DE2 and SE1, we confirm that DE2 and SE1 are the possible candidates that generate the wave 3 structure.

Effects of different seasonal fitting methods on the spatial distribution characteristics of common mode errors

This study investigated the effects of various seasonal fitting techniques on the spatial distribution of the common mode errors taking the coordinate time series of the continuous GPS reference stations of the Crustal Movement Observation Network of China (CMONOC) as an example. First, the seasonal term of coordinate time series was calculated using constant amplitude harmonic fitting (CAF), continuous wavelet transform (CWT), and smoothing spline fitting (SPF). The seasonal term and linear trend were then removed to obtain the residual time series. Finally, to determine the common mode errors of residual time series, principal component analysis (PCA) was applied. The results indicate that 1) smoothing spline fitting is superior to constant amplitude harmonic fitting and continuous wavelet transform in its ability to fit short-term irregular seasonal signals. In comparison to constant amplitude harmonic fitting, N/E/U has root mean square error (RMSE) values of smoothing spline fitting that are lower by 25%, 20%, and 14.4%, respectively. Smoothing spline fitting also has a higher coefficient of determination than continuous wavelet transform and constant amplitude harmonic fitting. The coefficient of determination in the U direction is larger than that in the N and E directions. 2) Each order PC of the residual series fitted by smoothing spline fitting exhibits apparent spatial aggregation characteristics, with PC1 having a uniform spatial distribution and presenting a largely positive response. Nevertheless, the residual series obtained by constant amplitude harmonic fitting and continuous wavelet transform exhibits scattered spatial response distribution features in each order PC. Compared to N and E, U’s spatial response distribution is distinct. From north to south, the spatial response of PC1 in the U direction progressively diminishes. In addition to being much lower than that in other locations, the Sichuan–Yunnan region’s spatial response value of PC1 and PC3 also exhibits a clear negative reaction. The root mean square error value of the residual series after smoothing spline fitting is the least, and the filtering effect is the best when comparing the spatial filtering effect based on the three fitting methods. We also compared the root mean square error reduction ratio before and after spatial filtering, and the results showed that the root mean square error reduction ratio before and after the residual series obtained by smoothing spline fitting is slightly larger than that obtained by other methods.

Online tomography algorithm based on laser absorption spectroscopy

Conventional calibration-free wavelength modulation spectroscopy generally requires complex absorption spectrum simulations in combination with spectral databases and laser modulation parameters, placing high demands on the accuracy of a priori spectral parameters and hardware parameters. Meanwhile, inappropriate initial values can increase the computation time and even lead to local optimal solutions. In order to improve the computational efficiency, a rapid calibration-free wavelength modulation spectroscopy to obtain the integrated absorbance is presented in this work. First, this method is computationally efficient, requiring only algebraic calculations by using the 2nd, 4th, and 6th harmonic center peak height parameters to obtain the integrated absorbance, eliminating the need for computationally intensive harmonic fitting calculations. Secondly, this method has low dependence on the spectral database, requiring only line intensity and low-state energy level spectral parameters. Finally, this method is highly adaptable and does not require scanning the complete absorption spectral line shape, which solves the problem of incomplete harmonic signals caused by the conventional method at high temperature and high pressure due to the broadening of the absorption spectral line. This method has previously been used only for line-of-sight measurements at low-frequency experimental signals in stable environments, and for calculating the integrated absorbance at average temperature, concentration and pressure states. In this work, the method is applied to non-uniform complex combustion field tomography and combined with the proposed tomographic system to achieve online reconstructing temperature and concentration distributions. The accuracy and computational efficiency of the method in obtaining the integrated absorbance are verified by numerical simulations and experiments on the butane burner flame. The results show that the presented method is consistent with the reconstructed distribution compared with the conventional wavelength modulation method, with a maximum relative deviation of only 0.94% from the measurement and 3.5% from the thermocouple measurement, verifying the accuracy of the method. The computational efficiencies of the two methods for obtaining the integrated absorbance are analyzed. The average calculation time per path is 0.15 s for the present method and 21.10 s for the conventional method. The calculation efficiency of the present method is at least two orders of magnitude higher than that of the conventional method, which provides a fast and reliable research method and technical means to realize the industrial-grade online reconstruction of temperature and concentration distribution of combustion fields.

On extraction of twist-two Compton form factors from DVCS observables through harmonic analysis

We investigate the exercise of locally extracting the real and imaginary parts of the four twist-2 Compton form factors (CFFs) left{mathcal{H},mathcal{E},overset{sim }{mathcal{H}},overset{sim }{mathcal{E}}right} which arise in the deeply virtual Compton scattering (DVCS) process e + p → e + p + γ. Neglecting dynamical higher-twist contributions, we find that there are a sufficient number of DVCS observables and degrees of freedom to extract all 8 leading quantities model-independently, exploiting the azimuthal dependence of the absolute cross sections across all possible beam and target polarizations at a common kinematical point in {Q, t, xB, y}. As an example, for typical JLab lab-frame kinematics, we simplify the reduced DVCS observables to their dominant terms, providing a sufficient number of equations for local determination of the twist-2 CFFs. We demonstrate the feasibility using harmonic fitting to both cross sections and beam spin asymmetries with both real and pseudo-data.

The impact of head-related impulse response delay treatment strategy on psychoacoustic cue reconstruction errors from virtual loudspeaker arrays.

Known errors exist in loudspeaker array processing techniques, often degrading source localization and timbre. The goal of the present study was to use virtual loudspeaker arrays to investigate how treatment of the interaural time delay (ITD) cue from each loudspeaker impacts these errors. Virtual loudspeaker arrays rendered over headphones using head-related impulse responses (HRIRs) allow flexible control of array size. Here, three HRIR delay treatment strategies were evaluated using minimum-phase loudspeaker HRIRs: reapplying the original HRIR delays, applying the relative ITD to the contralateral ear, or separately applying the HRIR delays prior to virtual array processing. Seven array sizes were simulated, and panning techniques were used to estimate HRIRs from 3000 directions using higher-order Ambisonics, vector-base amplitude panning, and the closest loudspeaker technique. Compared to a traditional, physical array, the prior HRIR delay treatment strategy produced similar errors with a 95% reduction in the required array size. When compared to direct spherical harmonic (SH) fitting of head-related transfer functions (HRTFs), the prior delays strategy reduced errors in reconstruction accuracy of timbral and directional psychoacoustic cues. This result suggests that delay optimization can greatly reduce the number of virtual loudspeakers required for accurate rendering of acoustic scenes without SH-based HRTF representation.

Improving neural network classification of indigenous forest in New Zealand with phenological features

Accurate and up-to-date land cover maps inform and support effective management and policy decisions. Describing phenological changes in spectral response using time-series data may help to distinguish vegetation types, thereby allowing for more specificity within vegetation classification. In this research, we test this by classifying indigenous forest vegetation in New Zealand, using PlanetScope (PS) and Sentinel-2 (S-2) satellite time-series data.The study was undertaken in a podocarp forest in New Zealand's central north island, which was classified into nine land cover classes. Phenological features, based on S-2 imagery, were extracted, including the enhanced vegetation index (EVI), enhanced vegetation index 2 (EVI2) and normalised difference vegetation index (NDVI). Google Earth Engine (GEE) harmonic analysis and TIMESAT double logistic fitting function were used to extract phenological features. Pixel-based classifications were performed using a Neural Network on six different scenarios. The accuracy of the classification scenarios was determined and the importance score for each feature was evaluated.Using only the fused PS and S-2 bands, the land cover in the study area was classified with 90.1% accuracy. Adding phenological features increased the classification accuracy to 93.1%. When combined with VIs, texture features, and a digital terrain model, the addition of phenological features increased the classification accuracy to 96.6%. Including GEE-generated phenological features resulted in better classification accuracies than TIMESAT features. In terms of feature importance evaluation, EVI2- and NDVI-generated phenological features all had high scores; the effectiveness of EVI features could potentially have been limited by the quality of the blue band. The results demonstrate that it is possible to produce a more accurate classification of New Zealand's native vegetation by using phenological features. This method offers important cost-savings as the platforms for phenological analysis are free to use.

Data Assimilation of High‐Latitude Electric Fields: Extension of a Multi‐Resolution Gaussian Process Model (Lattice Kriging) to Vector Fields

AbstractWe develop a new methodology for the multi‐resolution assimilation of electric fields by extending a Gaussian process model (Lattice Kriging) used for scalar field originally to vector field. This method takes the background empirical model as “a priori” knowledge and fuses real observations under the Gaussian process framework. The comparison of assimilated results under two different background models and three different resolutions suggests that (a) the new method significantly reduces fitting errors compared with the global spherical harmonic fitting (SHF) because it uses range‐limited basis functions ideal for the local fitting and (b) the fitting resolution, determined by the number of basis functions, is adjustable and higher resolution leads to smaller errors, indicating that more structures in the data are captured. We also test the sensitivity of the fitting results to the total amount of input data: (a) as the data amount increases, the fitting results deviate from the background model and become more determined by data and (b) the impacts of data can reach remote regions with no data available. The assimilation also better captures short‐period variations in local PFISR measurements than the SHF and maintains a coherent pattern with the surrounding. The multi‐resolution Lattice Kriging is examined via attributing basis functions into multiple levels with different resolutions (fine level is located in the region with observations). Such multi‐resolution fitting has the smallest error and shortest computation time, making the regional high‐resolution modeling efficient. Our method can be modified to achieve the multi‐resolution assimilation for other vector fields from unevenly distributed observations.

Strategy to Decrease the Angle Measurement Error Introduced by the Use of Circular Grating in Dynamic Torque Calibration.

A circular grating angle encoder is a key component in the dynamic torque calibration system. To improve the accuracy of an angle measurement, in this paper, the source of the angle measurement error of the circular grating is analyzed; an eccentricity error model and an inclination error model are proposed, respectively; further, these two models are combined to establish a total error model. Through the simulation study with the models, the conditions, in which the eccentricity error or inclination error can be ignored, are discussed. The calibration and compensation methods of the angle measurement error are given, and a progressive error compensation function which integrates the first harmonic fitting and the second harmonic fitting is obtained. An experiment is performed to verify the proposed calibration and compensation methods. The peak-to-peak value of the compensated angle measurement error of the single reading head can be reduced by about 93.76%, which approximates to the error of the mean value of the double reading heads. The experimental results show that the error calibration and compensation method based on the proposed error model can effectively compensate the angle measurement error of the circular grating with a single reading head, and obtain a high-precision measurement angle.

Research on a method of eliminating the line broadening caused by the wavelength shift based on the first harmonic.

Using laser spectroscopy for gas detection, short-term rapid changes in ambient temperature, system noise, and circuit aging are likely to cause line broadening, which affects the accuracy of gas concentration measurement. Firstly, the correction method of the impact on line broadening is analyzed theoretically. A method is proposed to eliminate the line broadening caused by the wavelength shift based on the first harmonic detection. After removing the background noise and filtering, the standard harmonic fitting and broadening elimination are carried out. Meanwhile, a methane gas detection system is established and experiments are conducted. The experimental results show that after the standard harmonic fitting, the maximum value of the baseline is reduced from 2 to 0.078, and the maximum absolute value of the baseline in the absorption-free region is reduced from 2.07 to 0.072. The standard deviation after the broadening correction is 0.047, and the standard deviation without considering the effect of broadening is 0.203, which proves that the accuracy of trace gas detection is improved and has good engineering practical value.

Receiver phase alignment using fitted SVD derived sensitivities from routine prescans

Magnetic resonance imaging radio frequency arrays are composed of multiple receive coils that have their signals combined to form an image. Combination requires an estimate of the radio frequency coil sensitivities to align signal phases and prevent destructive interference. At lower fields this can be accomplished using a uniform physical reference coil. However, at higher fields, uniform volume coils are lacking and, when available, suffer from regions of low receive sensitivity that result in poor sensitivity estimation and combination. Several approaches exist that do not require a physical reference coil but require manual intervention, specific prescans, or must be completed post-acquisition. This makes these methods impractical for large multi-volume datasets such as those collected for novel types of functional MRI or quantitative susceptibility mapping, where magnitude and phase are important. This pilot study proposes a fitted SVD method which utilizes existing combination methods to create a phase sensitive combination method targeted at large multi-volume datasets. This method uses any multi-image prescan to calculate the relative receive sensitivities using voxel-wise singular value decomposition. These relative sensitivities are fitted to the solid harmonics using an iterative least squares fitting algorithm. Fits of the relative sensitivities are used to align the phases of the receive coils and improve combination in subsequent acquisitions during the imaging session. This method is compared against existing approaches in the human brain at 7 Tesla by examining the combined data for the presence of singularities and changes in phase signal-to-noise ratio. Two additional applications of the method are also explored, using the fitted SVD method in an asymmetrical coil and in a case with subject motion. The fitted SVD method produces singularity-free images and recovers between 95–100% of the phase signal-to-noise ratio depending on the prescan data resolution. Using solid harmonic fitting to interpolate singular value decomposition derived receive sensitivities from existing prescans allows the fitted SVD method to be used on all acquisitions within a session without increasing exam duration. Our fitted SVD method is able to combine imaging datasets accurately without supervision during online reconstruction.

Middle Atmosphere Temperature Changes Derived from SABER Observations during 2002-2020

AbstractUsing temperature data measured by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument from February 2002 to March 2020, the temperature linear trend and temperature responses to the solar cycle (SC), Quasi-Biennial Oscillation (QBO), and El Niño-Southern Oscillation (ENSO) were investigated from 20 km to 110 km for the latitude range of 50°S-50°N. A four-component harmonic fit was used to remove the seasonal variation from the observed monthly temperature series. Multiple linear regression (MLR) was applied to analyze the linear trend, SC, QBO, and ENSO terms. In this study, the near-global mean temperature shows consistent cooling trends throughout the entire middle atmosphere, ranging from -0.28 to -0.97 K/decade. Additionally, it shows positive responses to the solar cycle, varying from -0.05 to 4.53 K/100sfu. A solar temperature response boundary between 50°S and 50°N is given, above which the atmospheric temperature is strongly affected by solar activity. The boundary penetrates deep below the stratopause to ~ 42 km over the tropical region and rises to higher altitudes with latitude. Temperature responses to the QBO and ENSO can be observed up to the upper mesosphere and lower thermosphere. In the equatorial region, 40%-70% of the total variance is explained by QBO signals in the stratosphere and 30%-50% is explained by the solar signal in the upper middle atmosphere. Our results, obtained from 18-year SABER observations, are expected to be an updated reliable estimation of the middle atmosphere temperature variability for the stratospheric ozone recovery period.

Sensitivity of Spectral Indices on Burned Area Detection using Landsat Time Series in Savannas of Southern Burkina Faso

Accurate and efficient burned area mapping and monitoring are fundamental for environmental applications. Studies using Landsat time series for burned area mapping are increasing and popular. However, the performance of burned area mapping with different spectral indices and Landsat time series has not been evaluated and compared. This study compares eleven spectral indices for burned area detection in the savanna area of southern Burkina Faso using Landsat data ranging from October 2000 to April 2016. The same reference data are adopted to assess the performance of different spectral indices. The results indicate that Burned Area Index (BAI) is the most accurate index in burned area detection using our method based on harmonic model fitting and breakpoint identification. Among those tested, fire-related indices are more accurate than vegetation indices, and Char Soil Index (CSI) performed worst. Furthermore, we evaluate whether combining several different spectral indices can improve the accuracy of burned area detection. According to the results, only minor improvements in accuracy can be attained in the studied environment, and the performance depended on the number of selected spectral indices.

The use of signage as a tool for social integration in tourist cities: examples of relevant cases in Catalonia

Purpose This paper aims to expose the evolution in the use of the so-called reception tools and tourist information that are present at the time of consumption of a trip towards an interest in and a willingness to link local residents and tourists in a friendly, inclusive and conciliatory way. This is the case of territorial signage designed for pedestrians, a growing protagonist of the urban landscape of many cities, which has found in its formulation the appropriate response to unify the messages and criteria that are addressed to all audiences and people with all types of sensitivities. Design/methodology/approach Based on an extensive fieldwork study conducted in 2013 and 2017 in the 62 most populated cities of Catalonia, different variables related to the shape of the signage and the content presented in them were analysed. To this end, a specific pattern of ad-hoc observation and structured interviews were applied to determine the social transition of the content and approaches used in the signage. Findings While signage is initially considered to be a basic solution with purely informative content, poor in qualitative aspects and often neglected by those responsible for its management, over time it has emerged as a tool that serves to unify the interests of the citizens who share the same space for mutual interaction. It is characterised by providing open and transversal information for all citizens without focussing on or thematising tourism in an exclusive and segregated way, separating it from the rest of the aspects that make up the nature of the urban landscape. Originality/value This paper confirms that these tangible instruments of support for tourists, beyond seeking a harmonic fit in the urban planning of today's cities, are also complicit in seeking social cohesion in the present-day paradigm of the conflicts created by urban tourism.

Selecting nonlinear piezoelectricity for fully autonomous self-sensing synchronized switch damping on inductor technique

Recently, the importance of nonlinear piezoelectricity in smart piezoelectric devices has been receiving attention. Considering two sophisticated models of nonlinear piezoelectricity, we proposed a systematic methodology to select a model that is suitable for a piezoelectric smart attenuation device employing a fully autonomous self-sensing synchronized switch damping on inductor (SSDI) circuit. We derived the electromechanical equation based on the two models by considering a practical structure where the piezoelectric materials are attached using an adhesive and cover the structure partially. Then, the nonlinear parameters were determined using harmonic balance method (HBM) and nonlinear data fitting. We selected a suitable model by comparing the numerical analysis and experimental results of three datasets for the open, short, and SSDI circuits. It is difficult to distinguish the two models clearly from the frequency response peak values of the displacement or piezoelectric voltage. However, the difference between the two models was observed in the backbone curve properties of the peak frequency and the shape of frequency response curves, particularly for the short circuit. The methodology established in this work allows us to systematically select a suitable model of nonlinear piezoelectricity for a smart attenuation device.

Climate change scenarios at hourly time‐step over Switzerland from an enhanced temporal downscaling approach

AbstractMany physically‐based models for climate change impact studies require sub‐daily temporal resolution of the forcing data to provide meaningful predictions. However, climate scenarios are typically available at daily time step, severely limiting the application of such physically‐based models. In this study, we propose an enhanced delta‐change method for downscaling climate change scenarios from daily to hourly resolution. The approach presented provides objective criteria for assessing the quality of the determined delta and downscaled time series, while also fixing issues of common quantile mapping methods used for spatial downscaling related to the decrease of correlation between different variables. However, this new approach has limitations in correctly representing statistically extreme events and changes in the frequency of discontinuous events such as precipitation. Smoothing of historical and future data is required prior to applying the delta‐change method, and the related parameters are found to have a subtle impact on the correctness of the representation of the seasonal means as well as the resulting (artificial) variability in the scenario data product. This new method is universal and can be applied with smoothing approaches apart from the harmonic fitting used in this work and in the past. In this study, the assessment suggested the use of seven harmonics for the smoothing of the input data as a best choice of this parameter for the data used. The method is applied to a Swiss climate change scenario data set, CH2018, and to a complement of this set to a Swiss alpine measurement network obtained by spatial transfer of CH2018, resulting in a set of 68 climate change scenarios at hourly resolution for 188 stations over Switzerland significantly expanding upon the spatial and temporal resolution of the CH2018 data set. All source code to perform such an analysis and the complete data product are provided open access.

Reconstructing daily 30 m NDVI over complex agricultural landscapes using a crop reference curve approach

Multi-sensor remote sensing data fusion technologies have been developed and widely applied in recent years, providing a feasible and economical solution to increase the availability of high spatial and temporal resolution data. These methods, however, have been challenging to apply in highly heterogeneous areas, especially in complex agricultural landscapes where there are rapid changes at small scales, while features at larger scales change more slowly. In this study, we developed a novel method to reconstruct daily 30 m Normalized Difference Vegetation Index (NDVI) using imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat and Landsat-like platforms, and the Cropland Data Layer (CDL). This method utilizes a crop reference curve (CRC) approach, in which a set of NDVI time series are extracted from pure MODIS pixels (250 m resolution) identified using the CDL, and then used to fit Landsat-like observations (30 m). The CRC based method was applied over a complex agricultural landscape in the Choptank River watershed on the Eastern Shore of Maryland. Landsat data from 2013 and 2014 and Harmonized Landsat and Sentinel-2 (HLS) data from 2018 were used to reconstruct 30 m daily NDVI maps for major crop types. Results show that the relative error (RE) in reconstructed NDVI is around 6–8% during periods of rapid crop growth, and 3–5% during peak periods when growth is slow. The accuracy of the CRC method outperforms a standard image pair-based data fusion algorithm (Spatial and Temporal Adaptive Reflectance Fusion Model; STARFM), which yields RE of 4–9% in slow-growth periods and 10–16% in fast-growth periods when clear Landsat images are scarce. The CRC method was also compared with time-series data fusion methods, including a harmonic fitting model and the SaTellite dAta IntegRation (STAIR) model. The results show that CRC gives similar results when the Landsat-like image availability is high (around 27 images per year), but outperforms other methods when availability is limited (less than 15 images per year). The reconstructed NDVI time series for corn, soybean, winter wheat/soybean and forest at 30-m resolution show clear phenological patterns at the sub-field scale. The resulting 30-m NDVI timeseries data provide useful information for mapping crop phenology and monitoring crop condition in complex agricultural landscapes, especially for complex double-cropping areas. However, the input requirement of an accurate 30-m crop classification map constrains its application to areas and periods where classifications are available.