Trust me, my neighbors say it's raining outside

Chen, Alexander B.; Behl, Madhur; Goodall, Jonathan L.

doi:10.1145/3276774.3276792

Cited by 9 publications

(5 citation statements)

References 7 publications

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“…There are already several approaches to using the precipitation data from PWSs (e.g. Chen et al, 2018;Cifelli et al, 2005), but they are generally based on daily data and simple QC approaches. Studies using more sophisticated QC workflows for hourly or sub-hourly precipitation data from PWSs are still limited.…”

Section: Discussionmentioning

confidence: 99%

The use of personal weather station observations to improve precipitation estimation and interpolation

Bàrdossy

Seidel

Hachem

2021

Hydrol. Earth Syst. Sci.

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Abstract. The number of personal weather stations (PWSs) with data available through the internet is increasing gradually in many parts of the world. The purpose of this study is to investigate the applicability of these data for the spatial interpolation of precipitation using a novel approach based on indicator correlations and rank statistics. Due to unknown errors and biases of the observations, rainfall amounts from the PWS network are not considered directly. Instead, it is assumed that the temporal order of the ranking of these data is correct. The crucial step is to find the stations which fulfil this condition. This is done in two steps – first, by selecting the locations using the time series of indicators of high precipitation amounts. Then, the remaining stations are then checked for whether they fit into the spatial pattern of the other stations. Thus, it is assumed that the quantiles of the empirical distribution functions are accurate. These quantiles are then transformed to precipitation amounts by a quantile mapping using the distribution functions which were interpolated from the information from the German National Weather Service (Deutscher Wetterdienst – DWD) data only. The suggested procedure was tested for the state of Baden-Württemberg in Germany. A detailed cross validation of the interpolation was carried out for aggregated precipitation amount of 1, 3, 6, 12 and 24 h. For each of these temporal aggregations, nearly 200 intense events were evaluated, and the improvement of the interpolation was quantified. The results show that the filtering of observations from PWSs is necessary as the interpolation error after the filtering and data transformation decreases significantly. The biggest improvement is achieved for the shortest temporal aggregations.

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Section: Discussionmentioning

confidence: 99%

The use of personal weather station observations to improve precipitation estimation and interpolation

Bàrdossy

Seidel

Hachem

2021

Hydrol. Earth Syst. Sci.

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“…Rainfall measurements from PWS have also become a challenge for NMHS. Therefore, in the last decade, the research concerned all parameters measured by PWS [1][2][3], a single parameter to be used in the analysis of urban climate and urban heat island [4][5][6][7][8], and precipitation [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Selected Amateur Rain Gauges with Hellmann Rain Gauge Measurements

Droździoł

Absalon

2023

Climate

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The paper compares precipitation measurements from the Stratus manual rain gauge from the CoCoRaHS network and two Davis Vantage Vue and Davis Vantage Pro 2A rain gauges with the Hellmann rain gauge. Comparative measurements were made on a specially prepared experimental plot. The statistical calculations took into account 15 full months in the period from 1 October 2019, to 31 December 2020. In order to estimate the differences in measurements between amateur rain gauges and the Hellmann rain gauge, two statistics were calculated: the mean square error (MSE) and the mean absolute error (MAE). In order to present formal and more detailed differences in measurements between amateur rain gauges and the Hellmann rain gauge, analyses were performed using a linear regression model. The general form of the tested models was presented. The procedure for estimating the parameters of the models and the method of comparing the fit of the models to the data were described, and the rain gauge whose measurements were most closely related to the measurements of the Hellmann rain gauge was indicated. The study showed that the higher price of amateur rain gauges does not mean higher quality. The study showed that the Stratus rain gauge was the best at recording daily precipitation totals. The Davis Vantage Pro 2A rain gauge recorded daily precipitation sums with less accuracy. The Davis Vantage Vue rain gauge, despite being located on the roof, recorded similar rainfall totals as the Hellmann rain gauge. It was found that, despite the different construction and measurement methods, the precipitation measurement data from the Stratus rain gauge and the Davis Vantage Vue rain gauge are suitable both for climate monitoring and for use, after applying quality control, in NMHS networks.

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“…Greater density of weather measurement points may be achieved by reducing the costs of weather stations through the use of low-cost sensors [2]. Such sensors are installed in, for example, smartphones, but the relatively low trustworthiness of crowdsourcing data [3] makes the usefulness of such improvised weather stations limited. The problem of the inaccuracy of environmental low-cost sensors is solved by the use of additional sensor calibration that supports factory calibration.…”

Section: Introductionmentioning

confidence: 99%

Response Time and Intrinsic Information Quality as Criteria for the Selection of Low-Cost Sensors for Use in Mobile Weather Stations

Chodorek

Sitek

2022

Electronics

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Smart-city management systems use information about the environment, including the current values of weather factors. The specificity of the urban sites requires a high density of weather measurement points, which forces the use of low-cost sensors. A typical problem of devices using low-cost sensors is the lack of legalization of the sensors and the resulting inaccuracy and uncertainty of measurement, which one can attempt to solve by additional sensor calibration. In this paper, we propose a different approach to this problem, i.e., the two-stage selection of sensors, carried out on the basis of both the literature (pre-selection) and experiments (actual selection). We formulated the criteria of the sensor selection for the needs of the sources of weather information: the major one, which is the fast response time of a sensor in a cyber-physical subsystem and two minor ones, which are based on the intrinsic information quality dimensions related to measurement information. These criteria were tested by using a set of twelve weather sensors from different manufacturers. Results show that the two-stage sensor selection allows us to choose the least energy consuming (due to the major criterion) and the most accurate (due to the minor criteria) set of weather sensors, and is able to replace some methods of sensor selection reported in the literature. The proposed method is, however, more versatile and can be used to select any sensors with a response time comparable to electric ones, and for the application of low-cost sensors that are not related to weather stations.

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Trust me, my neighbors say it's raining outside

Cited by 9 publications

References 7 publications

The use of personal weather station observations to improve precipitation estimation and interpolation

The use of personal weather station observations to improve precipitation estimation and interpolation

Evaluation of Selected Amateur Rain Gauges with Hellmann Rain Gauge Measurements

Response Time and Intrinsic Information Quality as Criteria for the Selection of Low-Cost Sensors for Use in Mobile Weather Stations

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