Inter annual, spatial, seasonal, and diurnal variability of precipitable water vapour over northeast India using GPS time series

2016 ◽  
Vol 38 (2) ◽  
pp. 391-411 ◽  
Author(s):  
Prakash Barman ◽  
Sridevi Jade ◽  
Ashok Kumar ◽  
Wangshimenla Jamir
Keyword(s):  
Time Series ◽  
Water Vapour ◽  
Precipitable Water ◽  
Northeast India ◽  
Precipitable Water Vapour ◽  
Diurnal Variability ◽  
Gps Time Series

scholarly journals Interannual variability of the GNSS derived precipitable water vapour in the light of tropical climate patterns

2021 ◽  
Author(s):  
Grzegorz Nykiel ◽  
Zofia Baldysz ◽  
Beata Latos ◽  
Mariusz Figurski
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Interannual Variability ◽  
Water Vapour ◽  
Precipitable Water ◽  
Precipitable Water Vapour ◽  
Climate Patterns ◽  
Non Linear ◽  
Linear Trends

<p>Among various greenhouse gases, water vapour is characterized by the single highest positive feedback on the surface temperature and dominates increasing of the Earth’s surface temperature. Hence, long-term changes in its concentration in the atmosphere are one of the indicators for the assessment of the global warming rate. Consequently, monitoring of water vapour interannual variability is an important element in climate observing system, especially considering limitations of the surface technology that is traditionally used for this purpose. In this work, we have used 18 years of global navigation satellite system (GNSS) observations derived from 43 International GNSS Service (IGS) stations located across the global tropics. Based on them, we have estimated zenith tropospheric delay (ZTD) time series by precise point positioning (PPP) approach, and in next step converted them to long-term and homogenous precipitable water vapour (PWV) time series. We have investigated their interannual variability through estimation of non-linear trends and assessment which climate phenomena affect GNSS PWV long-term variability the most. Results have shown that for most of the analysed stations, GNSS PWV time series present distinct analogies to the global and regional climate phenomena such as El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) or North Pacific Gyro Oscillation (NPGO). Comparative analysis between GNSS PWV non-linear trends and selected climate indices showed strong cross-correlation, that amounted to 0.78. Moreover small-scale weather phenomena, such as local droughts, were clearly distinguishable, thus showing how GNSS PWV time series are sensitive to the combined effect of various weather and climate patterns. </p>

scholarly journals On the inclusion of GPS precipitable water vapour in the nowcasting of rainfall

2015 ◽  
Vol 3 (6) ◽  
pp. 3861-3895 ◽  
Author(s):  
P. Benevides ◽  
J. Catalao ◽  
P. M. A. Miranda
Keyword(s):  
Water Vapour ◽  
Meteorological Data ◽  
Simple Algorithm ◽  
Precipitable Water ◽  
False Alarms ◽  
Precipitable Water Vapour ◽  
Temporal Behaviour ◽  
Nearby Region ◽  
Single Station ◽  
Rain Events

Abstract. The temporal behaviour of Precipitable Water Vapour (PWV) retrieved from GPS delay data is analysed in a number of case studies of intense precipitation in the Lisbon area, in the period 2010–2012, and in a continuous annual cycle of 2012 observations. Such behaviour is found to correlate positively with the probability of precipitation, especially in cases of severe rainfall. The evolution of the GPS PWV in a few stations is analysed by a least-squares fitting of a broken line tendency, made by a temporal sequence of ascents and descents over the data. It is found that most severe rainfall event occurs in descending trends after a long ascending period, and that the most intense events occur after steep ascents in PWV. A simple algorithm, forecasting rain in the 6 h after a steep ascent of the GPS PWV in a single station is found to produce reasonable forecasts of the occurrence of precipitation in the nearby region, without significant misses in what concerns larger rain events, but with a substantial amount of false alarms. It is suggested that this method could be improved by the analysis of 2-D or 3-D time varying GPS PWV fields, or by its joint use with other meteorological data relevant to nowcast precipitation.

scholarly journals Evaluation of MODIS Water Vapour Products over ALGERIA using Radiosonde Data

2021 ◽  
Vol 44 ◽  
Author(s):  
Houaria Namaoui ◽  
Salem Kahlouche ◽  
Ahmed Hafidh Belbachir
Keyword(s):  
Water Vapour ◽  
Satellite Data ◽  
Correlation Coefficients ◽  
Precipitable Water ◽  
Radiosonde Data ◽  
Precipitable Water Vapour ◽  
Total Precipitable Water ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Remote sensing of atmospheric water vapour using GNSS and Satellite data has become an efficient tool in meteorology and climate research. Many satellite data have been increasingly used to measure the content of water vapour in the atmosphere and to characterize its temporal and spatial variations. In this paper, we have used observations from radiosonde data collected from three stations (Algiers, Bechar and Tamanrasset) in Algeria from January to December 2012 to evaluate Moderate Resolution Imaging Spectroradiometer (MODIS) total precipitable water vapour (PWV) products. Results show strong agreement between the total precipitable water contents estimated based on radiosondes observations and the ones measured by the sensor MODIS with the correlation coefficients in the range 0.69 to 0.95 and a mean bias, which does not exceed 1.5.  

scholarly journals Estimation of precipitable water vapour from GPS during winter season 2003

MAUSAM ◽  
2021 ◽  
Vol 57 (2) ◽  
pp. 323-328
Author(s):  
R. K. GIRI ◽  
B. R. LOE ◽  
N. PUVIARSON ◽  
S. S. BHANDARI ◽  
R. K. SHARMA
Keyword(s):  
Water Vapour ◽  
Winter Season ◽  
Precipitable Water ◽  
New Delhi ◽  
Total Delay ◽  
Precipitable Water Vapour ◽  
Integrated Water Vapour ◽  
Zenith Hydrostatic Delay ◽  
Indian Institute Of Science ◽  
Good Agreement

Lkkj & ok;qeaMy esa ty ok"i dk forj.k LFkkfud :i ls vkSj dkfyd rkSj ij cgqr vf/kd ifjorZu’khy gksrk gSA ty ok"i dk forj.k vusdksa ok;qeaMyh; izfØ;kvksa esa izeq[k Hkwfedk fuHkkrk gSA dqy lekdfyr ty ok"i vFkok le:ih o"kkZ ty ok"i dk vkdyu Xykscy iksft’kfuax flLVe ¼th- ih- ,l-½ tsfuFk VksVy fMys ¼tsM- Vh- Mh-½ ds vk¡dM+ksa dh lgk;rk ls fd;k tk ldrk gSA blesa tsfuFk nzoLFkSfrd fMys ds eku dks funf’kZr fd;k x;k gS vkSj bls tsM- Vh- Mh- ls fudkyus ij tsfuFk vknzZ fMys ds vk¡dM+s izkIr gksaxsA vr% bl izdkj vkdfyr fd, x, tsM- MCY;w- Mh- ds eku ls izk;% yxkrkj ,e- ,e-  esa o"kkZ  ty ok"i dk irk pysxkA bl 'kks/k&i= esa th- ih- ,l- ds vk¡dM+ksa dk mi;ksx djrs gq, ubZ fnYyh ds fy, o"kZ 2003 ds 'khrdkyhu _rq vkSj Hkkjrh; foKku laLFkku ifj"kn] caxykSj ds dsanzksa ds fy, ,e- ,e- esa ih- MCY;w- oh- dk vkdyu djus dk iz;kl fd;k x;k gSA buls izkIr gq, ifj.kkeksa dk jsfM;kslkSUnsa vk¡dM+ksa ds lkFk lgh rkyesy ik;k x;k gSA The distribution of water vapour in atmosphere is highly spatial and temporal variable. It plays a key role in many atmospheric processes. The total integrated water vapour or equivalent precipitable water vapour (PWV) can be estimated with the help of Global Positioning System (GPS) Zenith Total Delay (ZTD) data. The value of Zenith Hydrostatic Delay (ZHD) is modeled and subtracting from ZTD will give Zenith wet delay (ZWD). Consequently, the estimated ZWD values will provide PWV in mm almost in a continuous manner. In this paper an attempt has been made for the estimation of PWV in mm during winter season 2003 for New Delhi and Indian Institute of Science (IISC), Bangalore stations using GPS data. The result shows fairly good agreement with the radio-sonde data. 

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