scholarly journals Validation of the Moderate-Resolution Imaging Spectroradiometer precipitable water vapor product using measurements from GPS on the Tibetan Plateau

2006 ◽  
Vol 111 (D14) ◽  
Author(s):  
Jingmiao Liu ◽  
Hong Liang ◽  
Zhian Sun ◽  
Xiuji Zhou
Keyword(s):  
Water Vapor ◽  
Tibetan Plateau ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
The Tibetan Plateau ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Validation of the WRF Model for Estimating Precipitable Water Vapor at the Ali Observatory on the Tibetan Plateau

2020 ◽  
Vol 132 (1018) ◽  
pp. 125003
Author(s):  
Xuan Qian ◽  
Yongqiang Yao ◽  
Hongshuai Wang ◽  
Lei Zou ◽  
Yao Li ◽  
...  
Keyword(s):  
Water Vapor ◽  
Tibetan Plateau ◽  
Wrf Model ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
The Tibetan Plateau

An Empirical Model for Estimating Precipitable Water Vapor on the Tibetan Plateau

2019 ◽  
Vol 131 (1006) ◽  
pp. 125001 ◽  
Author(s):  
Xuan Qian ◽  
Yongqiang Yao ◽  
Lei Zou ◽  
Hongshuai Wang ◽  
Jia Yin
Keyword(s):  
Water Vapor ◽  
Tibetan Plateau ◽  
Empirical Model ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
The Tibetan Plateau

scholarly journals GPS Precipitable Water Vapor Estimations over Costa Rica: A Comparison against Atmospheric Sounding and Moderate Resolution Imaging Spectrometer (MODIS)

Climate ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 63 ◽  
Author(s):  
Polleth Campos-Arias ◽  
Germain Esquivel-Hernández ◽  
José Francisco Valverde-Calderón ◽  
Stephanie Rodríguez-Rosales ◽  
Jorge Moya-Zamora ◽  
...  
Keyword(s):  
Water Vapor ◽  
Costa Rica ◽  
Central America ◽  
Multiple Linear Regression Model ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Imaging Spectrometer ◽  
Atmospheric Sounding ◽  
Moderate Resolution ◽  
Resolution Imaging

The quantification of water vapor in tropical regions like Central America is necessary to estimate the influence of climate change on its distribution and the formation of precipitation. This work reports daily estimations of precipitable water vapor (PWV) using Global Positioning System (GPS) delay data over the Pacific region of Costa Rica during 2017. The GPS PWV measurements were compared against atmospheric sounding and Moderate Resolution Imaging Spectrometer (MODIS) data. When GPS PWV was calculated, relatively small biases between the mean atmospheric temperatures (Tm) from atmospheric sounding and the Bevis equation were found. The seasonal PWV fluctuations were controlled by two of the main circulation processes in Central America: the northeast trade winds and the latitudinal migration of the Intertropical Convergence Zone (ITCZ). No significant statistical differences were found for MODIS Terra during the dry season with respect GPS-based calculations (p > 0.05). A multiple linear regression model constructed based on surface meteorological variables can predict the GPS-based measurements with an average relative bias of −0.02 ± 0.19 mm/day (R2 = 0.597). These first results are promising for incorporating GPS-based meteorological applications in Central America where the prevailing climatic conditions offer a unique scenario to study the influence of maritime moisture inputs on the seasonal water vapor distribution.

scholarly journals Evaluation of Cloud Mask and Cloud Top Height from Fengyun-4A with MODIS Cloud Retrievals over the Tibetan Plateau

2021 ◽  
Vol 13 (8) ◽  
pp. 1418
Author(s):  
Wenjing Xu ◽  
Daren Lyu
Keyword(s):  
Tibetan Plateau ◽  
Climate Science ◽  
The Tibetan Plateau ◽  
Cloud Detection ◽  
Cloud Properties ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
New Generation ◽  
Cloud Mask

The Tibetan Plateau (TP) has profound thermal and dynamic influences on the atmospheric circulation, energy, and water cycles of the climate system, which make the clouds over the TP the forefront of atmospheric and climate science. However, the highest altitude and most complex terrain of the TP make the retrieval of cloud properties challenging. In order to understand the performance and limitations of cloud retrievals over the TP derived from the state-of-the-art Advanced Geosynchronous Radiation Imager (AGRI) onboard the new generation of Chinese Geostationary (GEO) meteorological satellites Fengyun-4 (FY-4), a three-month comparison was conducted between FY-4A/AGRI and the Moderate Resolution Imaging Spectroradiometer (MODIS) for both cloud detection and cloud top height (CTH) pixel-level retrievals. For cloud detection, the AGRI and MODIS cloud mask retrievals showed a fractional agreement of 0.93 for cloudy conditions and 0.73 for clear scenes. AGRI tended to miss lower CTH clouds due to the lack of thermal contrast between the clouds and the surface of the TP. For cloud top height retrievals, the comparison showed that on average, AGRI underestimated the CTH relative to MODIS by 1.366 ± 2.235 km, and their differences presented a trend of increasing with height.

scholarly journals Detecting Long-Term Trends in Precipitable Water over the Tibetan Plateau by Synthesis of Station and MODIS Observations*

2015 ◽  
Vol 28 (4) ◽  
pp. 1707-1722 ◽  
Author(s):  
Ning Lu ◽  
Kevin E. Trenberth ◽  
Jun Qin ◽  
Kun Yang ◽  
Ling Yao
Keyword(s):  
Tibetan Plateau ◽  
Bayesian Estimation ◽  
Precipitable Water ◽  
The Tibetan Plateau ◽  
Estimation Model ◽  
Spatial Coverage ◽  
Moderate Resolution ◽  
Long Term Trends ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Long-term trends in precipitable water (PW) are an important component of climate change assessments for the Tibetan Plateau (TP). PW products from Moderate Resolution Imaging Spectroradiometer (MODIS) are able to provide good spatial coverage of PW over the TP but limited in time coverage, while the meteorological stations in the TP can estimate long-term PW but unevenly distributed. To detect the decadal trend in PW over the TP, Bayesian inference theory is used to construct long-term and spatially continuous PW data for the TP based on the station and MODIS observations. The prior information on the monthly-mean PW from MODIS and the 63 stations over the TP for 2000–06 is used to get the posterior probability knowledge that is utilized to build a Bayesian estimation model. This model is then operated to estimate continuous monthly-mean PW for 1970–2011 and its performance is evaluated using the monthly MODIS PW anomalies (2007–11) and annual GPS PW anomalies (1995–2011), with RMSEs below 0.65 mm, to demonstrate that the model estimation can reproduce the PW variability over the TP in both space and time. Annual PW series show a significant increasing trend of 0.19 mm decade−1 for the TP during the 42 years. The most significant PW increase of 0.47 mm decade−1 occurs for 1986–99 and an insignificant decrease occurs for 2000–11. From the comparison of the PW data from JRA-55, ERA-40, ERA-Interim, MERRA, NCEP-2, and ISCCP, it is found that none of them are able to show the actual long-term trends and variability in PW for the TP as the Bayesian estimation.

scholarly journals Evaluation of Precipitable Water Vapor from Four Satellite Products and Four Reanalysis Datasets against GPS Measurements on the Southern Tibetan Plateau

2017 ◽  
Vol 30 (15) ◽  
pp. 5699-5713 ◽  
Author(s):  
Yan Wang ◽  
Kun Yang ◽  
Zhengyang Pan ◽  
Jun Qin ◽  
Deliang Chen ◽  
...  
Keyword(s):  
Water Vapor ◽  
Tibetan Plateau ◽  
Near Infrared ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
The Tibetan Plateau ◽  
Gps Measurements ◽  
Infrared Measurements ◽  
Southern Tibetan Plateau ◽  
Level 2

The southern Tibetan Plateau (STP) is the region in which water vapor passes from South Asia into the Tibetan Plateau (TP). The accuracy of precipitable water vapor (PWV) modeling for this region depends strongly on the quality of the available estimates of water vapor advection and the parameterization of land evaporation models. While climate simulation is frequently improved by assimilating relevant satellite and reanalysis products, this requires an understanding of the accuracy of these products. In this study, PWV data from MODIS infrared and near-infrared measurements, AIRS Level-2 and Level-3, MERRA, ERA-Interim, JRA-55, and NCEP final reanalysis (NCEP-Final) are evaluated against ground-based GPS measurements at nine stations over the STP, which covers the summer monsoon season from 2007 to 2013. The MODIS infrared product is shown to underestimate water vapor levels by more than 20% (1.84 mm), while the MODIS near-infrared product overestimates them by over 40% (3.52 mm). The AIRS PWV product appears to be most useful for constructing high-resolution and high-quality PWV datasets over the TP; particularly the AIRS Level-2 product has a relatively low bias (0.48 mm) and RMSE (1.83 mm) and correlates strongly with the GPS measurements ( R = 0.90). The four reanalysis datasets exhibit similar performance in terms of their correlation coefficients ( R = 0.87–0.90), bias (0.72–1.49 mm), and RMSE (2.19–2.35 mm). The key finding is that all the reanalyses have positive biases along the PWV seasonal cycle, which is linked to the well-known wet bias over the TP of current climate models.

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