# Disdrometer Performance Optimization for Use in Urban Settings Based on the Parameters that Affect the Measurements

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## Abstract

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## 1. Introduction

^{2}and collected during a certain time period, have been useful for meteorology and climatology and are of special interest to many sectors such as hydrology, agriculture, or vehicle traffic management systems [3]. However, although recording the amounts of precipitation of liquids and solids constitutes a knowledge base in several fields of study, the precipitation intensity (PI) has become a variable of the same importance at present.

- Catching instruments.
- Non-catching instruments.

- It should be a simple, low-cost system implemented with commercial materials.
- It should be capable of operating both at fixed stations in the road network and onboard a vehicle to provide information to the driver and activate the fog lights or windscreen wipers when required.

## 2. Materials and Methods

#### 2.1. Operating Principle

#### 2.2. Drop Size Measurement

#### 2.3. Signal Duration Measurement

#### 2.4. Data Processing

#### 2.5. Time Technique

#### 2.6. Counting Technique

#### 2.7. Precipitation Intensity Calculation

#### 2.8. Edge Effects

- Two small drops can be detected as a larger drop. In this case, a larger amount of water than the one that actually contains the two smaller drops is detected.
- The time of the transition detected as a consequence of the coincidence of two drops is larger than that corresponding to a drop of larger diameter, which simulates a greater probability of large drops and consequently an exaggerated contribution to the determination of the precipitation intensity.

- “The iterative procedure to compensate for the fringe effects is based on the assumption that these effects occur according to their mean statistics. The Monte Carlo studies are used to quantify the portion of the total error variance produced by the random occurrence of the fringe effects. This will be referred to in the following as (fringe effects).
- The Monte Carlo simulations also consider the inhomogeneity and anisotropy of the sensitive volume. The variance that is caused by this effect is therefore included in the variance obtained from the Monte Carlo model.
- The total error variance also includes a sampling error due to the fact that even at a constant rainfall the number of drops penetrating the sensitive volume varies from one measurement to another. This sampling error has not been considered in the Monte Carlo simulations. This variance that is only caused by the sampling error will be called. The value of was determined analytically”.

#### 2.9. Numerical Model

## 3. Results

- The drop distribution was obtained according to their size: maintaining a constant number of drops of each size, we randomly generated different spatial and temporal distributions (200 analyses) to estimate the variations that could arise in the determination of the measured as a function of the position of the drops at the initial time.
- The effect of considering different sampling times of 1−120 s was analyzed. To minimize the effect of the spatial and temporal distribution of the drops on the measurement, the average of 200 measurements with different distributions was analyzed.
- The effect of the type of gamma distribution applied was analyzed by comparing the results of the stratiform and convective distribution.
- The effect of the wind speed on the results of the counting and time estimation systems was analyzed. These measurements were performed for a PI of $5mm/h$ with measurement periods of 5 s, resolution of 0.1 milliseconds and an average of 20 measurements.
- The results were compared for 8- and 10-bit converters and an average of 20 measurements.

- Estimation of precipitation measurement error for different sampling times, measurement technique, and type of precipitation (Figure 10).

## 4. Discussion

- The use of the counting technique always results in an estimate of precipitation the time technique.
- The time technique usually overestimates of the precipitation values, except for precipitation intensities above 50 mm/h.
- The counting technique provides very close estimated PI values to the actual values, which are slightly below them.
- The PI measurement with 8-bit A/D converters provides better results with the time technique than with the counting technique. The latter usually underestimates the PI.
- The PI measurement with 10-bit A/D converters provides better results with the counting technique than with the time technique. In this case, the latter usually overestimates the PI values.
- For measurements using the time technique, the results show that it is better to work with 8-bit A/D converters.
- For measurements using the counting technique, the results show that it is better to work with 10-bit A/D converters.
- The edge effects have a smaller influence on the convective precipitation. The reason is that for a given precipitation intensity, the numerical density in the convective rain is less than that in the stratiform rainfall, and multiple occupations are less frequent.

## Author Contributions

## Funding

## Conflicts of Interest

## References

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**Figure 5.**Representation of the surface covered by the passage of a drop through the sensitive volume.

**Figure 6.**Signals generated by the passage of the droplets through the sensitive volume for 1 s with a precipitation intensity of 10 mm/h.

**Figure 7.**Superposition of several droplets simultaneously passing through the sensitive volume. (

**A**) Signals generated by the passage; (

**B**) A droplet that rubs the sensitive volume.

**Figure 8.**PI estimation for stratiform rainfall using the (

**A**) time technique and (

**B**) counting technique.

**Figure 9.**PI estimation for convective rainfall using the (

**A**) time technique and (

**B**) counting technique.

**Figure 10.**PI estimation errors of the counting and time techniques for different sampling times for (

**A**) stratiform rain and (

**B**) convective rain.

**Figure 11.**Estimated PI with 10-bit converters for stratiform rainfall, different precipitation intensities and different wind speeds: (

**A**) time technique and (

**B**) counting technique.

**Figure 12.**Estimated PI with 10-bit converters for convective rainfall, different precipitation intensities and different wind speeds: (

**A**) time technique and (

**B**) counting technique.

**Figure 13.**Estimated PI with 8-bit converters for stratiform rainfall, different precipitation intensities and different wind speeds: (

**A**) time technique and (

**B**) counting technique.

**Figure 14.**Estimated PI with 8-bit converters for convective rainfall, different precipitation intensities and different wind speeds: (

**A**) time technique and (

**B**) counting technique.

Full range | 0.02–2000 mm·h^{−1} |

Rainfall threshold detected | 0.02–0.2 mm·h^{−1} |

Output averaging time | One minute |

Uncertainty required in the measurement: | |

0.2–2 mm·h^{−1} | 0.1 mm·h^{−1} |

2–2000 mm·h^{−1} | 5% |

Type of Precipitation | N_{0} (m^{−3}cm^{−1−µ}) | µ |
---|---|---|

Convective | 7.54 × 10^{6} | 1.63 |

Stratified | 1.96 × 10^{5} | 0.18 |

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## Share and Cite

**MDPI and ACS Style**

Mocholí Belenguer, F.; Martínez-Millana, A.; Mocholí Salcedo, A.; Milián Sánchez, V.; Josefa Palomo Anaya, M.
Disdrometer Performance Optimization for Use in Urban Settings Based on the Parameters that Affect the Measurements. *Symmetry* **2020**, *12*, 303.
https://doi.org/10.3390/sym12020303

**AMA Style**

Mocholí Belenguer F, Martínez-Millana A, Mocholí Salcedo A, Milián Sánchez V, Josefa Palomo Anaya M.
Disdrometer Performance Optimization for Use in Urban Settings Based on the Parameters that Affect the Measurements. *Symmetry*. 2020; 12(2):303.
https://doi.org/10.3390/sym12020303

**Chicago/Turabian Style**

Mocholí Belenguer, Ferran, Antonio Martínez-Millana, Antonio Mocholí Salcedo, Víctor Milián Sánchez, and María Josefa Palomo Anaya.
2020. "Disdrometer Performance Optimization for Use in Urban Settings Based on the Parameters that Affect the Measurements" *Symmetry* 12, no. 2: 303.
https://doi.org/10.3390/sym12020303