CDQ-T1C Specifications
| Model |
CDQ-T1C200L |
CDQ-T1CXF500 |
CDQ-T1C500GL |
CDQ-T1C500SL |
| Measured Parameters |
Wind speed |
Temperature, |
Temperature, Humidity, |
Temperature, Humidity, |
|
Humidity, |
Air Pressure, |
Air pressure, |
| Wind direction |
Air Pressure, |
Wind Speed, |
Wind Speed, |
|
Wind Speed, |
WindDirection |
Wind Direction, |
|
Wind Direction |
lllumination |
Solar Radiation |
| Measuring Range |
0-40m/s |
-40-85℃ |
-40-85℃ |
-40-85℃ |
|
0-100%RH |
0-100%RH |
0-100%RH |
| 0-359.9° |
300-1100hPa |
300-1100hPa |
300-1100hPa |
|
0-40m/s |
0-40m/s |
0-40m/s |
|
0-359.9° |
0-359.9° |
0-359.9° |
|
|
0-200KLux |
0-2000W/m2 |
| Accuracy |
± (0.5+0.05V)m/s, |
≦ ± 0.3 ℃ |
≦ ± 0.3 ℃ |
≦ ± 0.3 ℃ |
| ±5° |
≦ + / - 3% RH |
≦ + / - 3% RH |
≦ + / - 3% RH |
| (wind speed <10m/s) |
≦ + / - 0.3 hPa |
≦ + / - 0.3 hPa |
≦ + / - 0.3 hPa |
|
(@ 25 ℃, ) |
(@ 25 ℃, ) |
(@ 25 ℃, ) |
|
± (0.5+0.05V) m/s |
± (0.5+0.05V) m/s |
± (0.5+0.05V) m/s |
|
±5° |
±5° |
±5° |
|
(wind speed < 10m/s) |
(wind speed < 10m/s) |
(wind speed < 10m/s) |
|
|
±1%F.S |
±5% |
| Resolution |
0.01m/s |
0.01℃ |
0.01℃ |
0.01℃ |
| 0.1° |
0.01%RH |
0.01%RH |
0.01%RH |
|
0.1hPa |
0.1hPa |
0.1hPa |
|
0.01m/s |
0.01m/s |
0.01m/s |
|
0.1° |
0.1° |
0.1° |
|
|
0.1° |
1W |
| Power Supply |
|
|
|
| Product Size(mm) |
116*147 |
116*217 |
116*217 |
116*217 |
| Model |
CDQ-T1CXF603 |
CDQ-T1C700L |
CDQ-T1C800L |
CDQ-T1C900L |
| Measured Parameters |
Temperature |
Temperature |
Temperature |
Temperature |
| Humidity |
Humidity |
Humidity |
Humidity |
| PM2.5 |
Air pressure |
Air pressure |
Air pressure |
| PM10 |
Wind speed |
Wind speed |
Wind speed |
| Noise |
Wind direction |
Wind direction |
Wind direction |
| lllumination |
Rainfall |
PM2.5 |
PM2.5 |
|
lllumination |
PM10 |
PM10 |
|
|
Noise |
Noise |
|
|
|
llluminance/Solar radiation |
|
|
|
Rainfall |
| Measuring Range |
-40-85℃ |
-40-85℃ |
-40-85℃ |
-40-85℃ |
| 0-100%RH |
0-100%RH |
0-100%RH |
0-100%RH |
| 0-100%RH |
300-1100hPa |
300-1100hPa |
300-1100hPa |
| 0-500ug/m³ ( 1000ug/m³) |
0-40m/s |
0-40m/s |
0-40m/s |
| 0-200klux |
0-359.9° |
0-359.9° |
0-359.9° |
| 30-130dB |
0-200mm/h |
0-500ug/m³ |
0-500ug/m³ |
|
0-200klux |
0-500ug/m³ |
0-500ug/m³ |
|
|
(1000ug/m³) |
(1000ug/m³) |
|
|
30-130dB |
30-130dB |
|
|
|
0-200klux/ |
|
|
|
0-2000W/m2 |
|
|
|
0-200mm/ |
CDQ-T1C Automatic Integrated Weather Station
CDQ-T1C automatic weather station is simultaneously measure the atmospheric temperature, atmospheric humidity, air pressure, wind speed, wind direction, solar radiation, Illuminance/UV, dust concentration and precipitation. Temperature, humidity and air pressure sensor is placed within the radiation shield. Wind speed and direction of ultrasonic principle.24G radar detection on rainfall, which can quickly detect rainfall and rainfall intensit.
Application
Meteorological monitoring and forecasting:
Automatic Integrated Weather stations can automatically and real-time collect a variety of meteorological elements data, including temperature, pressure, humidity, wind speed, wind direction, precipitation, sunshine hours, radiation intensity, etc. These data will be transmitted to the meteorological data center via wired (such as fiber optic, cable) or wireless (such as satellite communications, GPRS).
Agricultural field:
In modern agriculture, automatic integrated weather stations provide key data support for precision agriculture. Farmers can optimize planting decisions based on real-time and historical weather data provided by weather stations.
Data from automated integrated weather stations can also be used to optimize crop growth models. These models can simulate the growth process of crops under different meteorological conditions, including growth rate and yield prediction. By inputting the actual observation data of the weather station into the crop growth model, the model can be constantly revised and improved to reflect the actual local conditions more accurately.
Ecological environment research and protection:
Automatic integrated weather stations are important tools for ecosystem monitoring. It can provide data on long-term changes in meteorological elements in ecological environments, which are essential for studying structural and functional changes in ecosystems. For example, in forest ecosystems, temperature, humidity, and precipitation data from weather stations can affect tree growth, the forest’s water balance, and the distribution of vegetation beneath the forest.
