跳到主要內容

GPS meterology


What is GPS meterology?

Global Positioning System (GPS) Meteorology is the application of GPS data to the monitoring and analyses of atmospheric conditions. Atmospheric monitoring can be done by both ground-based and space-based GPS applications.
GPS satellites transmit radio signals that can be inverted to measure atmospheric profiles of refractivity. The refractivity profile can be transformed to profiles of tropospheric humidity given a temperature profile.
Ground-based GPS receivers at fixed locations can be used to gather data that can be used to determine integrated Precipitable Water Vapor (PWV). Atmospheric scientists have shown that GPS-determined PWV observations can significantly improve weather forecasting accuracy.

Why is measurement of PWV important? 

The Global Positioning System (GPS) tracking network was established to provide high precision navigation and geodetic positioning. The system consists of satellites in orbit around the earth and a ground-based network of support stations to update the ephemeredes and clocks.
A constellation of GPS satellites transmit atomic-clock controlled L-band signals to receivers on the earth. Time delays of the signal travel paths from multiple satellites to a single receiver are used to establish the ground position of the receiver. Data recorded by GPS receivers at fixed locations will show signal path delays caused by a variety of effects.

One class of GPS-signal delays can be directly attributed to the passage of the signals through the Earth’s ionosphere and atmosphere.

The ionospheric delay is dispersive (frequency dependent) and can be determined by observing both of the frequencies transmitted by the GPS satellites (L1 & L2) using a dual-band GPS receiver. These ionospheric delays can be eliminated without reference to observations recorded by other GPS receivers ¹.
The remainder of the atmospheric delay, or neutral delay, is not dispersive and cannot be estimated from single station observations. However, it is possible to parameterize the neutral delays affecting each station in a network of GPS receivers and to estimate these parameters jointly as part of the overall geodetic inversion for the relative geometry of the network and the precise orbits of the satellites.² (Hoffman-Wellenhof et al., 1993). The physical basis for estimating the zenith delay parameters is that a GPS receiver is typically tracking 4 to 8 satellites simultaneously and over-determines the zenith delay parameters without regard to azimuth or elevation.
The neutral delay can be decomposed into a "hydrostatic delay" associated with the "dry" atmosphere and a "wet" delay associated with the permanent dipole moment of water vapor.

Accurate, frequent, and dense sampling of water vapor is needed for operational weather forecasting as well as for weather and climatic research. Given the present operational weather data system, inadequate resolution of the temporal and spatial variability of water vapor has been cited as the single greatest obstacle to improved short range precipitation forecasts. Mesoscale numerical model simulations have shown that when model-predicted precipitable water is relaxed toward an observed value, the model recovers the vertical structure of water vapor with an accuracy much greater than that from statistical retrieval based on climatology, leading to significantly improved short range precipitation forecasts. One can infer that GPS water vapor data will be similarly valuable to longer range and global numerical simulations.

For example, using the NCAR/PennState mesoscale weather model, Kuo et al., 1995, have shown that the combination of PWV and surface humidity data significantly benefits the numerical models. A 20% improvement in the numerical weather forecasting was achieved when PWV time-series constrained the model. An additional improvement was achieved when the surface humidity was included.

How is PWV estimated from GPS receiver data?

The zenith hydrostatic delay (ZHD) has a magnitude (equivalent GPS phase delay length) of about 2300 mm at sea level. It is possible to predict the ZHD to better than 1 mm given surface pressure measurements accurate to 0.3 hPa (millibar) or better.

The Zenith Wet Delay (ZWD) can vary from a few millimeters in desert conditions to more than 350 mm in very humid conditions. It is not possible to predict the wet delay with any useful degree of accuracy from surface measurements of pressure, temperature, and humidity. However, once the ZHD parameters have been estimated from the measured GPS neutral delay, it is possible to estimate ZWD by subtracting ZHD from the ZND where the ZHD is derived from the surface pressure readings.

The Zenith Wet Delay can then be transformed into an estimate of Precipitable Water Vapor by using either a numerical weather model or a statistical/analytical model of the vertical temperature distribution at the receiver site.





Calculation of PWV


The steps to estimate PWV from MET3/GPS measurements are:

1) Determine the total station delays (or zenith total delay integrated over all azimuths and elevations) from the GPS station network with each station tracking multiple GPS satellites.
Total Delay = Ionospheric Delay + Neutral Delay.

2) Measure the Ionospheric delay from comparison of the L1 and L2 GPS signals recorded with a dual-band GPS receiver, and calculate the Neutral Delay.
Neutral Delay = Total Delay - Ionospheric Delay.

3) Calculate the Zenith Hydrostatic Delay from the barometric pressure, temperature, and humidity as measured by the Paroscientific MET3.
Zenith Neutral Delay = Zenith Hydrostatic Delay + Zenith Wet Delay.

4) Calculate the Zenith Wet Delay.
Zenith Wet Delay = Zenith Neutral Delay - Zenith Hydrostatic Delay.

5) Estimate Precipitable Water Vapor from the Zenith Wet Delay. PWV can be estimated from either a numerical model or a statistical/analytical temperature model.




more on this from paroscientific



Estimation of atmospheric water vapour using GPS from HK poly u

3D distribution of Ionsopheric delay in Hong Kong







Precise estimation of ionsopheric delay in Hong Kong



thesis paper from HK poly u: Remote sensing of atmospheric water vapor using GPS data in the Hong Kong Region

typical setup of a GPS reference station with Met sensor in Lands department:









留言

這個網誌中的熱門文章

Scythians 斯泰基 塞種 西古提人

900 BC - 200 AD British museum   Tomb of scythe prince, Buktarma valley, 1200 masl, Google map Herodotus   絲路上的帝國 Biblegeography   哥羅西書 3:11  在此並不分希利尼人、猶太人、受割禮的、未受割禮的、化外人、 西古提人 、為奴的、自主的.惟有基督是包括一切、又住在各人之內。 塞種 塞迦  saka 史記漢書 西域傳: 塞種  ctext 昔匈奴破大月氏,大月氏西君大夏,而塞王南君罽賓。塞種分散,往往為數國。自疏勒以西北,休循、捐毒之屬,皆故 塞種 也。 匈奴列傳 Ctext :塞王 《史記》在《大宛列傳》與《匈奴列傳》中, 詳細 記錄了中亞至天山一帶的塞種(塞王、塞地)狀況。例如,文中記載了月氏西破走塞王,導致塞人南遷越過懸度(今帕米爾高原及克什米爾一帶) Baike Genetic history   Genetics  Nih griffin  ? Scytho-Siberian  world 塞迦 saka  wiki Disappeared? Sarmatians ( 薩爾馬泰 , 奄蔡 史記 ,  Aorsi )and goths YouTube  

calculate pH of phosphoric acid

Question: adding 1/4 teaspoon of 10% phosphoric acid  to 19 litres of water, what will be the pH? Let's go through the calculations step by step. Step 1. Convert mass ( or volume) of 10% phosphoric acid to mole per litre ( mol/L) The above calculation shows that 1/4 tsp of H3PO4 acid is 6.97e-5 mol/L Step 2. Input this value to BATE (or other app) to calculate pH The answer: pH = 4.16, ie too acidic !? If you use pipette instead of teaspoon,  1 drop = 0.05ml. So 1/4 TSP means roughly 25 drops If you actually aim for pH 5.6 (which is optimum pH for mashing), conc will be 2.51 e-6, or 1/100 tsp , 0.044 ml, roughly 1 drop Let's roll back a bit. From  recipes of   BarleyWine , summer rye , hefe Gordon Strong suggested to use 1/4 teaspoon of 10% phosphoric acid, which is targeting pH of 5.5..... Discussion on  homebrewtalk  forum. However using online BF water calc , Sparge pH would be 4.6. but he also added 1 tsp of CaCl2. 2H20. Mash pH change from 5.7 t...

ES8311 and ES8388 codec IC

ES8388 audio codec module is one of the audio codec modules available that is supported by ESP32 and official ESP-ADF releases. The ES8388 module lets you have: Stereo microphone and line input Stereo headphone and line out Up to 96 kHz 24 bpp high quality audio This module is compatible with all MCUs that have I2C and I2S ports (like ESP32, ESP8266, STM32, i.MX6, Raspberry Pi, etc) ES8311 Maxgerhardt github PCBartist twblogs ESP32-A1S  (limited stock)Audio codec AC101 or ES8388 built-in. NB the pinouts and firmware are different! Arduino - ESP31-A1S instructable Phil Schatzmann and his github   Simple A2DP thaaraak github on ESP32-A1S github of Yveaux and  Marcel-licence ESP ADF   example:  Logitech PiCorePlayer squeeze lite squeezebox forum   ESP32-Audio-kit  (from AI thinker) based on ESP32-A1S, is simple and small. But upgrade-ability seems limited  Alex John Talbert mixer equalizer: can this be used as simple equalizer? how about proces...