Reference Gauge Research Articles

Evaluation of the measurement uncertainty during the calibration of metal reference gauges of the 2nd category

The paper considers problematic issues related to ensuring the uniformity of measurements in the field of legal metrology, namely, during the calibration of working measurement standards used for verification of legally regulated measuring instruments. One of the conditions for ensuring the uniformity of measurements is the compliance of any measuring instrument with the requirements that are prescribed in its technical specification, where standardized metrological characteristics are indicated, which allows us to conclude about the suitability of the instrument for measurements in a known range and with a known accuracy. The procedure for verification of legally regulated measuring instruments establishes a ratio between the expanded measurement uncertainty provided for by the measurement standard and the maximum permissible error of the measuring instruments of no more than one to three. Determining such a ratio is an example of indirect accounting for the measurement uncertainty. The reliability of the assessment of the compliance of a working measurement standard with metrological requirements, which are regulated by the technical specification, depends on the correctness of the procedures for evaluating the measurement uncertainty during calibrations. The paper indicates the problems of updating the existing regulatory framework for the calibration of measuring instruments using reference gauges as an example and ensuring metrological traceability of the results of the calibration of the liquid volume measuring equipment. Attention was drawn to the need to apply in Ukraine the international practice of the standardization of calibration techniques and methods of uncertainty evaluation to ensure the uniformity of measurements. A procedure for evaluating the measurement uncertainty during the calibration of the reference 2nd-grade gauge by the volumetric method, which is used as a working measurement standard when verifying legally regulated measuring instruments – fuel dispensers for refuelling cars – is proposed.

Calibration for endoscopic 3D shape measurement with cone beam projection

We demonstrate a calibration method for endoscopic three-dimensional shape measurement with cone beam projection. In this method, changes in the shape of the optical sectioning profiles are quantified and fitted while scanning a calibration board in the depth direction, using a cubic function. In accuracy tests using a flat plate and a ring reference gauge, the proposed method obtains an accuracy of 0.02 mm in the depth dimension and 0.09 mm in the radial dimension. These results represent 88% and 55% improvements compared to previous analysis. For medical applications, an ear examination simulator was employed, and our measurement results were compared to ground truth data obtained by microfocus X-ray computed tomography. The surface deviation of our method relative to the ground truth data was ±0.36mm during manual operation. A comparison of the measurement results before and after calibration revealed an improvement in the peak agreement with the ground truth data, with the deviation shifting from 0.2 mm to −0.05mm. Our strategy achieves a digital transformation of 3D endoscopy, which would benefit a number of medical fields.

Monitoring Braided River-Bed Dynamics at the Sub-Event Time Scale Using Time Series of Sentinel-1 SAR Imagery

Remote sensing plays a central role in the assessment of environmental phenomena and has increasingly become a powerful tool for monitoring shorelines, river morphology, flood-wave delineation and flood assessment. Optical-based monitoring and the characterization of river evolution at long time scales is a key tool in fluvial geomorphology. However, the evolution occurring during extreme events is crucial for the understanding of the river dynamics under severe flow conditions and requires the processing of data from active sensors to overcome cloud obstructions. This work proposes a cloud-based unsupervised algorithm for the intra-event monitoring of river dynamics during extreme flow conditions based on the time series of Sentinel-1 SAR data. The method allows the extraction of multi-temporal series of spatially explicit geometric parameters at high temporal and spatial resolutions, linking them to the hydrometric levels acquired by reference gauge stations. The intra-event reconstruction of inundation dynamics has led to (1) the estimation of the relationship between hydrometric level and wet area extension and (2) the assessment of bank erosion phenomena. In the first case, the behavior exhibits a change when the hydrometric level exceeds 1 m. In the second case, the erosion rate and cumulative lateral erosion were evaluated. The maximum erosion velocity was greater than 1 m/h, while the cumulative lateral erosion reached 130 m. Time series of SAR acquisitions, provided by Sentinel-1 satellites, were analyzed to quantify changes in the wet area of a reach of the Tagliamento river under different flow conditions. The algorithm, developed within the Python-API of GEE, can support many types of analyses of river dynamics, including morphological changes, floods monitoring, and bio-physical habitat dynamics. The results encourage future advancements and applications of the algorithm, specifically exploring SAR data from ICEYE and Capella Space constellations, which offer significantly higher spatial and temporal resolutions compared to Sentinel-1 data.

Assessment of remotely sensed precipitation products for climatic and hydrological studies in arid to semi-arid data-scarce region, central-western Morocco

The lack of ground-based data remains the main challenge for hydrologists working in semi-arid to arid regions. In this context, remotely sensed precipitation products (SPPs) are crucial for widespread hydrological and climatic applications. The core benefit of SPPs is their high spatial-temporal resolution with evenly distributed precipitation estimates. However, their accuracy can vary considerably with climatic conditions and location and should be concisely evaluated beforehand. Therefore, this study is a first attempt to exhaustively compares and evaluates the performance of three widely used SPPs (CHIRPS, TRMM and PERSIANN) against ground-based observations at daily scale over the Souss data-sparse region (Central-western Morocco). Our proposed approach consisted of three main steps. The reference gauge method was adopted to evaluate daily precipitation data. Next, the hydrological simulation method was used to assess the performance of SPPs in simulating the observed streamflow in four locations of the SRB using multiple models. The non-parametric methods were applied to assess the capacity of SPPs in capturing precipitation extremes and characterizing the hydrological signature of SRB based on streamflow extreme detection. Our findings indicated that the three SPPs were not able to well reproduce the total amount of daily ground-based observations over the Souss region (CCmedian < 0.51; PBIAS > ±35%). The HEC-HMS model coupled with the TRMM product is the most appropriate combination for daily river flow restitution and for hydrologic signatures detection in SRB. For extreme precipitation events, CHIRPS showed satisfactory performance in capturing nearly all extreme events indices while PERSIANN and TRMM demonstrated reasonable ability to capture the wet extreme events. Therefore, it is still rather difficult to replace completely the ground-based data. Consequently, we recommend to further improve the satellite-based algorithms to adapt to the complex topography and special characteristics of semi-arid data-scarce regions.

Two-point diameter calibration of a sphere using a micro-coordinate measuring machine at NMIJ

The National Metrology Institute of Japan (NMIJ) has developed a highly accurate two-point diameter measurement method of a sphere using a micro-coordinate measuring machine (µ-CMM) with a low-force two-dimensional touch probe. The measured sphere is used as a reference to calibrate the probe of other µ-CMM in industry. Our strategy for measuring sphere’s diameter is that the probe radius of NMIJ’s µ-CMM is calibrated using a reference gauge block, and the NMIJ’s µ-CMM using the calibrated probe measures the mean two-point diameter of a sphere. To achieve the highly accurate calibration of the reference gauge block, we have adopted a double-sided interferometer (DSI) and an atomic force microscopy (AFM). The DSI measures the length of gauge block without wringing. The phase correction value of the gauge block is evaluated by measuring the surface roughness using the AFM. Using the DSI and AFM, the mechanical length of reference gauge block was obtained with the expanded uncertainty of 13 nm (k = 2). Then, the probe radius of NMIJ’s µ-CMM was also calibrated using the reference gauge block calibrated by the DSI and the AFM. The µ-CMM’s probe radius was obtained with the expanded uncertainty of 10 nm (k = 2). Finally, the µ-CMM measured the mean two-point diameter of a sphere with the expanded uncertainty 21 nm (k = 2) was demonstrated.

Development of a novel gauge filled with resin for X-ray CT

X-ray computed tomography (CT) systems have been widely used for three-dimensional (3D) measurements in the engineering field. Therefore, verifying X-ray CT systems with full traceability is necessary to ensure accurate measurements. Measurement errors of X-ray CT systems are evaluated using a reference gauge whose geometry is calibrated using 3D measuring systems with higher accuracy. Thus, this study developed and characterized a novel reference gauge for X-ray CT systems, comprising spheres embedded in a cylindrical resin.

THE USE OF FLUID-FILLED CATHETERS AS REFERENCE BLOOD PRESSURE MONITORS

The standard ISO 81060–2:2018 allows the use of invasive blood pressure monitoring systems as reference gauges in clinical trials of automated non-invasive automated sphygmomanometers. The reference measuring system is subject to requirements for a maximum permissible error of ±2 mmHg, and the resonant frequency and damping coefficient must also be characterized. The 'catheter-sensor' system used in clinical practice only has defined parameters required by the standard for the chamber with the pressure sensor. The characteristic parameters of the whole measuring system cannot be defined even when the type of catheter used is known, because after every irrigation the system changes the values of its natural frequency (fn) and damping ratio (ζ). These parameters directly define the frequency response of the system, its resonant frequency and the damping coefficient. The characteristic parameters of the 'catheter-sensor' system were defined on the basis of an analysis of a second-order linear model and the measurement of the step response of the real system. Measurements have shown that repeated irrigation of the same 'catheter-sensor' system can change the value of the system’s natural frequency by tens of Hz. In well-irrigated systems, the accuracy required by the standard was met. The following values were determined for this system: fn = 38.8 Hz and ζ = 0.130. In the second case, when the system was probably affected by air bubble compliancy, the measurement accuracy was much lower. The discovered deviation was tens of mmHg. This system had fn = 6.5 Hz a ζ = 0.281.

Snowfall Model Validation Using Surface Observations and an Optimal Estimation Snowfall Retrieval

AbstractIn the winter, orographic precipitation falls as snow in the mid- to high latitudes where it causes avalanches, affects local infrastructure, or leads to flooding during the spring thaw. We present a technique to validate operational numerical weather prediction model simulations in complex terrain. The presented verification technique uses a combined retrieval approach to obtain surface snowfall accumulation and vertical profiles of snow water at the Haukeliseter test site, Norway. Both surface observations and vertical profiles of snow are used to validate model simulations from the Norwegian Meteorological Institute’s operational forecast system and two simulations with adjusted cloud microphysics. Retrieved surface snowfall is validated against measurements conducted with a double-fence automated reference gauge (DFAR). In comparison, the optimal estimation snowfall retrieval produces +10.9% more surface snowfall than the DFAR. The predicted surface snowfall from the operational forecast model and two additional simulations with microphysical adjustments (CTRL and ICE-T) are overestimated at the surface with +41.0%, +43.8%, and +59.2%, respectively. Simultaneously, the CTRL and ICE-T simulations underestimate the mean snow water path by −1071.4% and −523.7%, respectively. The study shows that we would reach false conclusions only using surface accumulation or vertical snow water content profiles. These results highlight the need to combine ground-based in situ and vertically profiling remote sensing instruments to identify biases in numerical weather prediction.

Rainfall estimates from opportunistic sensors in Germany across spatio-temporal scales

Study region: The study region is Germany and two sub-regions in Germany, i.e. the state of Rhineland-Palatinate and the city of Reutlingen.Study focus: Opportunistic rainfall sensors, namely personal weather stations and commercial microwave links, together with rain gauge data from the German Weather Service, were used in different combinations to derive rainfall maps with a geostatistical interpolation framework for Germany. This kriging type framework considered the uncertainty of opportunistic sensors and the line structure of commercial microwave links. The resulting rainfall maps were compared to two gauge-adjusted radar products and evaluated to three reference gauge datasets in the respective study regions on both daily and hourly basis.New Hydrological Insights for the Region: The interpolated rainfall products from opportunistic sensors provided good agreement to the reference rain gauges. The dataset combinations including information from the opportunistic sensors performed best. The addition of rain gauges from the German Weather Service did not consistently lead to an improvement of the interpolated rainfall maps. On the country-wide, daily scale the interpolated rainfall maps performed well, but the gauge-adjusted radar products were closer to the reference. For the regional and local scale in Rhineland-Palatinate and Reutlingen with an hourly resolution, the interpolated rainfall maps outperformed the interpolated product from DWD rain gauges and showed a similar agreement to the reference as the radar products.

Selection of Multiple Donor Gauges via Graphical Lasso for Estimation of Daily Streamflow Time Series

AbstractA fundamental challenge in estimations of daily streamflow time series at sites with incomplete records is how to effectively and efficiently select reference/donor gauges from an existing gauge network to infer the missing data. While research on estimating missing streamflow time series is not new, the existing approaches either use a single reference streamflow gauge or employ a set of “ad hoc” reference gauges, leaving a systematic selection of reference gauges as a long‐standing open question. In this work, a novel method is introduced that facilitates a systematic selection of multiple reference gauges from any given streamflow network. The idea is to mathematically characterize the network‐wise correlation structure of a streamflow network via graphical Markov modeling and to further transform a dense network into a sparsely connected one. The resulted underlying sparse graph from the graphical model encodes conditional independence conditions among all reference gauges from the streamflow network, allowing determination of an optimum subset of the donor gauges. The sparsity is discovered by using the Graphical Lasso algorithm with an L1 norm regularization parameter and a thresholding parameter. These two parameters are determined by a multi‐objective optimization process. Furthermore, the graphical modeling approach is employed to solve another open problem in gauge removal planning decision (e.g., due to operation budget constraints): which gauges to remove would statistically guarantee the least loss of information by estimations from the remaining gauges? Our graphical model‐based method is demonstrated with daily streamflow data from a network of 34 gauges over the Ohio River basin region.

Using Deep Learning for Automatic Water Stage Measurements

AbstractImage‐based gauging stations can allow for significant densification of monitoring networks of river water stages. However, thus far, most camera gauges do not provide the robustness of accurate measurements due to the varying appearance of water in the stream throughout the year. We introduce an approach that allows for automatic and reliable water stage measurement combining deep learning and photogrammetric techniques. First, a convolutional neural network (CNN), a class of deep learning, is applied to the segmentation (i.e., pixel classification) of water in images. The CNNs SegNet and fully convolutional network (FCN) are associated with a transfer learning strategy to segment water on images acquired by a Raspberry Pi camera. Errors of water segmentation with the two CNNs are lower than 3%. Second, the image information is transformed into metric water stage values by intersecting the extracted water contour, generated using the segmentation results, with a 3D model reconstructed with structure‐from‐motion (SfM) photogrammetry. The highest correlations between a reference gauge and the image‐based approaches reached 0.93, and average deviations were lower than 4 cm. Our approach allows for the densification of river monitoring networks based on camera gauges, providing accurate water stage measurements.

Evaluation of six precipitation products in the Mekong River Basin

Continuous and reliable precipitation records are essential for hydrological and meteorological studies. In the Mekong River Basin (MRB), there are many satellite-based and gauge-based precipitation products. It is necessary to evaluate the reliabilities of these precipitation products. In this study, we evaluated six widely used precipitation products in the MRB on a monthly scale, namely Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of water resources v1101 (APHRODITE), Global Precipitation Climatology Center v2018 (GPCC), Climatic Research Unit Time-Series v4.03 (CRU), Climate Hazards group InfraRed Precipitation with Stations v2.0 (CHIRPS), Multi-Source Weighted-Ensemble Precipitation v1.0 (MSWEP), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR). Two evaluation methods, namely the reference gauge method and the hydrological simulation method, were used. For the reference gauge method, APHRODITE had the best consistency with precipitation observations at 25 reference gauges among the six precipitation products. For the hydrological simulation method, hydrological model using APHRODITE as the input obtained the most accurate runoff simulations among the six precipitation products. Thus, APHRODITE could be a reliable precipitation product in the MRB. The evaluation results provide a useful reference for the hydrological and meteorological study in the MRB.

Performance of the ATMOS41 All-in-One Weather Station for Weather Monitoring.

Affordable and accurate weather monitoring systems are essential in low-income and developing countries and, more recently, are needed in small-scale research such as precision agriculture and urban climate studies. A variety of low-cost solutions are available on the market, but the use of non-standard technologies raises concerns for data quality. Research-grade all-in-one weather stations could present a reliable, cost effective solution while being robust and easy to use. This study evaluates the performance of the commercially available ATMOS41 all-in-one weather station. Three stations were deployed next to a high-performance reference station over a three-month period. The ATMOS41 stations showed good performance compared to the reference, and close agreement among the three stations for most standard weather variables. However, measured atmospheric pressure showed uncertainties >0.6 hPa and solar radiation was underestimated by 3%, which could be corrected with a locally obtained linear regression function. Furthermore, precipitation measurements showed considerable variability, with observed differences of ±7.5% compared to the reference gauge, which suggests relatively high susceptibility to wind-induced errors. Overall, the station is well suited for private user applications such as farming, while the use in research should consider the limitations of the station, especially regarding precise precipitation measurements.

Uncertainty evaluation of the static expansion system and its long-term stability at NMIJ

A pressure standard based on the static expansion of gases has been made available at the National Metrology Institute of Japan (NMIJ) for gauge calibrations in the range of 0.1 mPa–2 kPa over the past 30 years. The static expansion system (SES) generates calibration pressures by multiple-step gas expansions using two expansion ratios (R900≃907.3 and R50≃53.4). These expansion ratios were determined using the two reference gauges method instead of the one reference gauge method, which has been in use thus far. Relative uncertainties of 0.073% (k = 1) for R900 and 0.036% (k = 1) for R50 were obtained, and the calibration uncertainties were slightly improved compared to the current calibration and measurement capability (CMC) of the SES at NMIJ as follows:U = 0.28% (k = 2) (1 mPa–10 Pa) for spinning rotor gauges (SRGs).U = 0.23% (k = 2) (0.2 Pa–10 Pa) for capacitance diaphragm gauges (CDGs).U = 0.17% (k = 2) (10 Pa–110 Pa) for CDGs.In addition, the calibration results of the check standards of the past 12 years are reported. The data suggest that the SES was stable compared to the calibration uncertainty over the years.

Evaluation of Three-Hourly TMPA Rainfall Products Using Telemetric Rain Gauge Observations at Lai Nullah Basin in Islamabad, Pakistan

Flash floods which occur due to heavy rainfall in hilly and semi-hilly areas may prove deleterious when they hit urban centers. The prediction of such localized and heterogeneous phenomena is a challenge due to a scarcity of in-situ rainfall. A possible solution is the utilization of satellite-based precipitation products. The current study evaluates the efficacy of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) three-hourly products, i.e., 3B42 near-real-time (3B42RT) and 3B42 research version (3B42V7) at a sub-daily time scale. Various categorical indices have been used to assess the capability of products in the detection of rain/no-rain. Hourly rain rates are assessed by employing the most commonly used statistical measures, such as correlation coefficients (CC), mean bias error (MBE), mean absolute error (MAE), and root-mean-square error (RMSE). Further, a diurnal analysis is performed to authenticate TMPA’s performance in specific hours of the day. In general, the results show the good capability of both TMPA products in the detection of rain/no-rain events in all seasons except winter. Specifically, 3B42V7 performed better than 3B42RT. Moreover, both products detect a high number of rainy days falsely in light rain ranges. Regarding rainfall measurements, TMPA products exhibit an overall underestimation. Seasonally, 3B42V7 underestimates rainfall in monsoon and post-monsoon, and overestimates in winter and pre-monsoon. 3B42RT, on the other hand, underestimates rainfall in all seasons. A greater MBE and RMSE are found with both TMPA rain measurements in monsoon and post-monsoon seasons. Overall, a weak correlation and high MBE between the TMPA (3B42RT, 3B42V7) and reference gauge hourly rain rates are found at a three-hourly time scale (CC = 0.41, 0.38, MBE = −0.92, −0.70). The correlation is significant at decadal (CC = 0.79, 0.77) and monthly (CC = 0.91, 0,90) timescales. Furthermore, diurnal rainfall analysis indicates low credibility of 3B42RT to detect flash flooding. Within the parameters of this study, we conclude that the TMPA products are not the best choice at a three-hourly time scale in hilly/semi-hilly areas of Pakistan. However, both products can be used at daily, yet more reliably above daily, time scales, with 3B42V7 preferable due to its consistency.

Automatic Image‐Based Water Stage Measurement for Long‐Term Observations in Ungauged Catchments

AbstractSmall‐scale and headwater catchments are mostly ungauged, even though their observation could help to improve the understanding of hydrological processes. However, it is expensive to build and maintain conventional measurement networks. Thus, the heterogeneous characteristics and behavior of catchments are currently not fully observed. This study introduces a method to capture water stage with a flexible low‐cost camera setup. By considering the temporal signature of the water surface, water lines are automatically retrieved via image processing. The image coordinates are projected into object space to estimate the actual water stage. This requires high‐resolution 3D models of the river bed and bank area, which are calculated in a local coordinate system with structure from motion, employing terrestrial as well as unmanned aerial vehicle imagery. A medium‐ and a small‐scale catchment are investigated to assess the accuracy and reliability of the introduced method. Results reveal that the average deviation between the water stages measured with the camera gauge and a reference gauge are below 6 mm in the medium‐scale catchment. Trends of water stage changes are captured reliably in both catchments. The developed approach uses a low‐cost camera design in combination with image‐based water level measurements and high‐resolution topography from structure from motion. In future, adding tracking algorithms can help to densify existing gauging networks.

A novel method of diameter measurement of pistons used in pressure standards using scanning principle and fusion technique

The requirement of improved certainties in the measurement of the diameter and the form of cylindrical artifacts is increasing day-by-day. Such requirements become indispensable in typical applications, like the inspection of the fuel injection systems and calibration of pressure balances. A new experiment is set to measure the diameter of a cylindrical artifact, particularly the piston of a pressure-measuring device. Three displacement sensors are used to scan the cross-section of a cylinder and a reference gauge block. At the same time, the scanning process is simulated for ideal conditions. The coordinate data thus obtained in the scanning is fused on to a circle. The misalignments in the experimental setup are refined by iterative scanning the artifacts under test until the experimentally obtained surface profiles match with the simulated ones. Then, the fused circle represents the diameter of the cylindrical object. According to substitution technique, the deviation of the diameter of the artifact under test is determined from the size of the gauge block. Finally, the expanded measurement uncertainty is estimated.

Valuing scarce observation of rainfall variability with flexible semi-distributed hydrological modelling – Mountainous Mediterranean context

To represent spatial and temporal variability in rainfall adequately, rainfall-runoff models must compromise among modelling objectives, data availability, conceptualization options, and the actual variability in rainfall. This is of utmost importance for challenges of integrated water management in the rapidly changing Mediterranean context. We evaluated the sensitivity of the SWAT model to combinations of spatial rainfall variability and catchment subdivision in a data-scarce mesoscale mountainous Mediterranean context. The case study focused on the Joumine catchment, in northern Tunisia, which is emblematic of agro-hydro-chemical changes and challenges. The double-mass curve method was used to verify the consistency of rainfall time series from 1991 to 2003, indicating proportionality between annual rainfall at the reference gauge and that of the nearest gauge. The rainfall lapse rate at the Joumine catchment was 69.9 mm per 100 m of altitude. Seven sets of rain gauges and five subdivision configurations of the catchment were simulated. Differences between measured and predicted streamflow at the outlet were assessed using three indices of model fit. Predicted streamflow was extremely sensitive to spatial rainfall variability but relatively insensitive to catchment subdivision. Daily predictions were most accurate for the wettest year (2002−2003) and least accurate for the driest year (1993–1994).

Performance evaluation of latest integrated multi-satellite retrievals for Global Precipitation Measurement (IMERG) over the northern highlands of Pakistan

Recently, the Global Precipitation Measurement (GPM) mission has released the Integrated Multi-satellite Retrievals for GPM (IMERG) at a fine spatial (0.1° × 0.1°) and temporal (half hourly) resolutions. A comprehensive evaluation of this newly launched precipitation product is very important for satellite-based precipitation data users as well as for algorithm developers. The objective of this study was to provide a preliminary and timely performance evaluation of the IMERG product over the northern high lands of Pakistan. For comparison reference, the real-time and post real-time Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products were also evaluated parallel to the IMERG. All of the selected precipitation products were evaluated at annual, monthly, seasonal and daily time scales using reference gauges data from April 2014 to December 2016. The results showed that: (1) the precipitation estimates from IMERG, 3B42V7 and 3B42RT products correlated well with the reference gauges observations at monthly time scale (CC = 0.93, 0.91, 0.88, respectively), whereas moderately at the daily time scale (CC = 0.67, 0.61, and 0.58, respectively); (2) Compared to the 3B42V7 and 3B42RT, the precipitation estimates from IMERG were more reliable in all seasons particularly in the winter season with lowest relative bias (2.61%) and highest CC (0.87); (3) IMERG showed a clear superiority over 3B42V7 and 3B42RT products in order to capture spatial distribution of precipitation over the northern Pakistan; (4) Relative to the 3B42V7 and 3B42RT, daily precipitation estimates from IMEREG showed lowest relative bias (9.20% vs. 21.40% and 26.10%, respectively) and RMSE (2.05 mm/day vs. 2.49 mm/day and 2.88 mm/day, respectively); and (5) Light precipitation events (0–1 mm/day) were usually overestimated by all said satellite-based precipitation products. In contrast moderate (1–20 mm/day) to heavy (>20 mm/day) precipitation events were underestimated by both TMPA products while IMERG was found capable to detect moderate to heavy precipitation events more precisely. Overall, the performance of IMERG was better than that of TMPA products. This preliminary evaluation of new generation of satellite-based precipitation estimates might be a useful feedback for sensor and algorithm developers as well as data users.

Characteristics of Linear Variable Differential Transformer(LVDT) Probe for Gauge Blocks Calibration

The LVDT probe is a very important component used in gauge blocks calibration via a mechanical comparative method. The probe is used to determine the central length difference between a reference gauge block and gauge block under-tested (UTC). Typically, an UTC and a reference gauge block have the same nominal length. However, some gauge blocks UTC are specially made for specific purpose where the reference gauge blocks with the same nominal length are not commercially available. Various reference gauge blocks are wrung in order to provide nominal length the same as that of the UTC. Wringing process is the troublesome step and causes larger measurement uncertainty. The lower accuracy is higher number of gauge block used to create reference gauge block, in order to improve accuracy of measurement, the LVDT probe was used at the longer range where the reference gauge block and the UTC don’t need to be the same nominal length. In this paper, characteristics of LVDT probe was investigated as it is related to the accuracy of the measurement result. Errors of LVDT probe came from non-linearity, calibration factor, retrace error, repeatability and maximum difference in length. A pair of gauge block, calculated by the Twyman-Green interferometer, length different range 5 μm to 230 μm was used in the study. Non-linearity of LVDT is evaluated by a simple linear regression model. The non-linearity of LVDT probe, calibration factor, retrace error, repeatability and maximum difference in length are 25 nm, 1.0003, 3 nm, 6 nm and 80 nm, respectively. Therefore, by using this technique, central length difference between the 2 gauge blocks up to 80 nm can be calibrated with the uncertainty due to non-linearity of 15 nm The experiment shows the large error of retrace closes to 0.02 μm at 0.09 μm. This can be determined the maximum difference in length to calibrate gauge blocks at difference nominal lengths. The measurement uncertainty of non-linearity is evaluated and it is close to 15 nm.