NOAA PSL OttDisdrometerStats KettlePonds for SLASH

Data Format for DisdrometerOTTParsivel Stats

Header: InstrumentModel (SN: SerialNumber) Time (YYJJJHH): StatsFileBeginTime[2-digit-Year;3-digit-DayOfYear;2-digit-Hour] UTC

Data Field 1: Begin time of the accumulation/averaging period in UTC

MM = minute
SS = second
mmm = millisecond

Data Field 2: End time of the accumulation/averaging period in UTC

MM = minute
SS = second
mmm = millisecond
Data Field 3-34: Partical distribution (count) binned by ClassNumber

ClassNumber according to volume-equivalent diameter:

ClassNumber ClassAverage(mm) ClassSpread(mm)
1 0.062 0.125
2 0.187 0.125
3 0.312 0.125
4 0.437 0.125
5 0.562 0.125
6 0.687 0.125
7 0.812 0.125
8 0.937 0.125
9 1.062 0.125
10 1.187 0.125
11 1.375 0.250
12 1.625 0.250
13 1.875 0.250
14 2.125 0.250
15 2.375 0.250
16 2.750 0.500
17 3.250 0.500
18 3.750 0.500
19 4.250 0.500
20 4.750 0.500
21 5.500 1.000
22 6.500 1.000
23 7.500 1.000
24 8.500 1.000
25 9.500 1.000
26 11.000 2.000
27 13.000 2.000
28 15.000 2.000
29 17.000 2.000
30 19.000 2.000
31 21.500 3.000
32 24.500 3.000

Note: Class 1 and Class 2 are limits and are not evaluated
at the current time in measurements using the Parsivel
since they are outside the measurement range of the
device.

Data Field 35-37: Data acquisition software quality control

Blackout = number of data samples excluded during PC clock synchronization
Good = number of samples that passed the quality control checks, as performed by the data acquisition software
Bad = number of samples that failed the quality control checks, as performed by the data acquisition software

Data Field 38-42: Precipitation statistics

NumParticle = total number of detected particles
Rate(mm/h) = rain rate; units: millimeter per hour
Amount(mm) = interval rain accumulation ; units: millimeter
AmountSum(mm) = event rain accumulation; units: millimeter
Z(dB) = radar refelctivity factor; units: decibel

Data Field 43-48: Laser status

NumError = number of sample instances that were reported as dirty, very dirty, or damaged
Dirty = laser protective glass is dirty, but measurements are still possible
VeryDirty = laser protective glass is dirty, partially covered; no further usable measurements are possible
Damaged = laser damaged
SignalAvg = average signal amplitude of the laser strip; unitless
SignalStdDev = standard deviation of the signal amplitude of the laser strip; unitless

Data Field 49-54: Sensor status

TempAvg(C) = average sensor temperature; units: Celsius
TempStdDev(C) = standard deviation of the sensor temperature; units: Celsius
VoltAvg(V) = sensor power supply voltage; units: Volts
VoltStdDev(V) = standard deviation of the sensor power supply voltage; units: Volts
HeatCurrentAvg(A) = average heating system current; units: Amps
HeatCurrentStdDev(A) = standard deviation of the heating system current; units: Amps

Data Field 55-58: Precipitation partitioning

NumRain = number of particles detected as rain
NumNoRain = number of particles detected not as rain
NumAmbig = number of particles detected as ambiguous
Type = precipitation type (1=rain; 2=mixed; 3=snow)

Note: NumRain, NumNoRain, and NumAmbig counts are determined based on size-velocity masking described in:

Yuter, S. E., D. E. Kingsmill, L. B. Nance, and M. Loffler-Mang, 2006: Observations of precipitation
size and fall speed characteristics within coexisting rain and wet snow. J. Appl. Meteor.,45, 1450-1464.

Precipitation type is determined by RainFraction thresholds, where

RainFraction = NumRain / (NumRain + NumNoRain), and

Type = 1 (rain) for RainFraction > 0.95
Type = 3 (snow) for RainFraction < 0.05
Type = 2 (mixed) for RainFraction >= 0.05 and RainFraction <= 0.95

Erroneous particle-size-velocity measurements (and thereby derived precipitation types) can occur at
higher wind speeds (as low as ~ 6 m/s), as documented in:

Neiman, P.J., D.J. Gottas, A.B. White, W.R. Schneider, and D. Bright, 2018: A Real-Time Online Data
Product that Automatically Detects Easterly Gap Flow Events and Precipitation Type in the Columbia
River Gorge. J. Atmos. Oceanic Technol., 35, 2037-2052.

Less conservative RainFraction thresholds for precipitation typing were also explored in Neiman et al.

# DisdrometerOTTParsivel 统计数据格式

## 表头
仪器型号（SN：序列号） 时间（YYJJJHH）：统计文件开始时间[两位年份；三位一年中第几日；两位小时] 协调世界时（UTC）

## 数据字段1
累积/平均时段的协调世界时（UTC）开始时间

MM = 分钟
SS = 秒
mmm = 毫秒

## 数据字段2
累积/平均时段的协调世界时（UTC）结束时间

MM = 分钟
SS = 秒
mmm = 毫秒

## 数据字段3-34
按粒子体积等效直径分箱的粒子分布（计数）

类别编号对应体积等效直径：

| 类别编号 | 类别平均值(mm) | 类别跨度(mm) |
|----------|----------------|--------------|
| 1 | 0.062 | 0.125 |
| 2 | 0.187 | 0.125 |
| 3 | 0.312 | 0.125 |
| 4 | 0.437 | 0.125 |
| 5 | 0.562 | 0.125 |
| 6 | 0.687 | 0.125 |
| 7 | 0.812 | 0.125 |
| 8 | 0.937 | 0.125 |
| 9 | 1.062 | 0.125 |
| 10 | 1.187 | 0.125 |
| 11 | 1.375 | 0.250 |
| 12 | 1.625 | 0.250 |
| 13 | 1.875 | 0.250 |
| 14 | 2.125 | 0.250 |
| 15 | 2.375 | 0.250 |
| 16 | 2.750 | 0.500 |
| 17 | 3.250 | 0.500 |
| 18 | 3.750 | 0.500 |
| 19 | 4.250 | 0.500 |
| 20 | 4.750 | 0.500 |
| 21 | 5.500 | 1.000 |
| 22 | 6.500 | 1.000 |
| 23 | 7.500 | 1.000 |
| 24 | 8.500 | 1.000 |
| 25 | 9.500 | 1.000 |
| 26 | 11.000 | 2.000 |
| 27 | 13.000 | 2.000 |
| 28 | 15.000 | 2.000 |
| 29 | 17.000 | 2.000 |
| 30 | 19.000 | 2.000 |
| 31 | 21.500 | 3.000 |
| 32 | 24.500 | 3.000 |

备注：类别1与类别2为量程限值，当前使用Parsivel进行的测量中未对其进行评估，因其处于设备的测量量程之外。

## 数据字段35-37
数据采集软件质量控制

Blackout = PC时钟同步期间被排除的数据样本数
Good = 经数据采集软件质量控制检查通过的样本数
Bad = 经数据采集软件质量控制检查未通过的样本数

## 数据字段38-42
降水统计

NumParticle = 总检测粒子数
Rate(mm/h) = 降雨率；单位：毫米每小时
Amount(mm) = 时段降雨累积量；单位：毫米
AmountSum(mm) = 事件降雨累积量；单位：毫米
Z(dB) = 雷达反射率因子；单位：分贝

## 数据字段43-48
激光状态

NumError = 被报告为脏污、严重脏污或损坏的样本实例数
Dirty = 激光防护玻璃脏污，但仍可进行测量
VeryDirty = 激光防护玻璃脏污且部分被覆盖，无法进行有效测量
Damaged = 激光损坏
SignalAvg = 激光条平均信号幅度；无量纲
SignalStdDev = 激光条信号幅度的标准差；无量纲

## 数据字段49-54
传感器状态

TempAvg(℃) = 平均传感器温度；单位：摄氏度
TempStdDev(℃) = 传感器温度标准差；单位：摄氏度
VoltAvg(V) = 传感器供电电压平均值；单位：伏特
VoltStdDev(V) = 传感器供电电压标准差；单位：伏特
HeatCurrentAvg(A) = 加热系统平均电流；单位：安培
HeatCurrentStdDev(A) = 加热系统电流标准差；单位：安培

## 数据字段55-58
降水分区

NumRain = 被检测为降雨的粒子数
NumNoRain = 被检测为非降雨的粒子数
NumAmbig = 被检测为模糊类别的粒子数
Type = 降水类型（1=降雨；2=混合性降水；3=降雪）

备注：NumRain、NumNoRain与NumAmbig的计数基于Yuter等人2006年提出的尺寸-速度掩膜法确定，相关文献如下：

Yuter, S. E., D. E. Kingsmill, L. B. Nance, and M. Loffler-Mang, 2006: Observations of precipitation size and fall speed characteristics within coexisting rain and wet snow. J. Appl. Meteor.,45, 1450-1464.
（译：Yuter SE, Kingsmill DE, Nance LB, 等. 2006. 雨与湿雪共存条件下降水粒子尺寸与下落速度特征观测. 《应用气象学报》, 45: 1450-1464.）

降水类型由降雨分数（RainFraction）阈值确定，其中：

RainFraction = NumRain / (NumRain + NumNoRain)，且

Type = 1（降雨） 当 RainFraction > 0.95
Type = 3（降雪） 当 RainFraction < 0.05
Type = 2（混合性降水） 当 0.05 ≤ RainFraction ≤ 0.95

如Neiman等人2018年文献所述，当风速较高（低至约6 m/s）时，可能出现错误的粒子尺寸-速度测量结果，进而导致降水类型判断错误：

Neiman, P.J., D.J. Gottas, A.B. White, W.R. Schneider, and D. Bright, 2018: A Real-Time Online Data Product that Automatically Detects Easterly Gap Flow Events and Precipitation Type in the Columbia River Gorge. J. Atmos. Oceanic Technol., 35, 2037-2052.
（译：Neiman PJ, Gottas DJ, White AB, 等. 2018. 用于自动检测哥伦比亚河峡谷东风隙流事件与降水类型的实时在线数据产品. 《大气与海洋技术学报》, 35: 2037-2052.）

Neiman等人的研究中还探索了用于降水类型判定的更宽松的RainFraction阈值。