scholarly journals COMPARISON OF GNSS PWV AND ERA5-DERIVED PWV BASED ON GNSS PWV IN HONG KONG, CHINA

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 987-993
Author(s):  
Z. W. Li ◽  
C. Z. Tang ◽  
S. H. Tang ◽  
Y. Zhang
Keyword(s):  
Hong Kong ◽  
Water Vapor ◽  
Hydrological Cycle ◽  
Precipitable Water ◽  
Weather Forecast ◽  
Reanalysis Data ◽  
Vital Role ◽  
Small Range ◽  
Data Set ◽  
Medium Range Weather Forecast

Abstract. Water vapor is the most abundant atmospheric gas, and it plays a vital role in the evolution of the Earth's climate. Precipitable water vapor (PWV) is a key factor in monitoring the climate and hydrological cycle. The use of GNSS to estimate PWV is a very effective method. This paper uses 17 satellite positioning reference stations in SatRef, Hong Kong, China, in 2017 to calculate the PWV and introduce the latest reanalysis data set of the European Medium Range Weather Forecast Ingenued Center (ECMWF) ERA5 into this study. The accuracy of THE PWV derived from ERA5 was evaluated using the GNSS-derived PWV. In Hong Kong, the annual bias and RMSE values of GNSS-derived ZTD and ERA5-derived ZTDs are 1.16 cm and 1.78 cm respectively, while the annual RMSE values of GNSS-derived PWV and ERA5-derived PWV are 0.51 cm and 0.57 cm, respectively. The daily changes of GNSS PWV in 2017 are analyzed, and the results show that the ZTD effect of THE ERA5 reanalysis data derived in the small range area is not very ideal, but the accuracy of the PWV derived from ERA5 is better.

scholarly journals Widespread polar stratospheric ice clouds in the 2015/2016 Arctic winter – Implications for ice nucleation

2017 ◽  
Author(s):  
Christiane Voigt ◽  
Andreas Dörnbrack ◽  
Martin Wirth ◽  
Silke M. Groß ◽  
Michael C. Pitts ◽  
...  
Keyword(s):  
Weather Forecast ◽  
Satellite Observation ◽  
Reanalysis Data ◽  
Ice Nucleation ◽  
The Arctic ◽  
Orthogonal Polarization ◽  
Data Set ◽  
Ice Clouds ◽  
Medium Range Weather Forecast ◽  
Cold Temperatures

Abstract. Low planetary wave activity led to a stable vortex with exceptionally cold temperatures in the 2015/2016 Arctic winter. Extended areas with temperatures below the ice frost point Tice persisted over weeks in the Arctic stratosphere as derived from the 36-years temperature climatology of the ERA-Interim reanalysis data set of the European Center for Medium Range Weather Forecast ECMWF. These extreme conditions promoted the formation of widespread polar stratospheric ice clouds (ice PSCs). The space-borne Cloud-Aerosol Lidar with Orthogonal Polarization CALIOP instrument onboard the CALIPSO satellite (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) continuously measured ice PSCs for about a month with maximum extensions of up to 2 × 106 km2 in the stratosphere. On 22 January 2016, the WALES (Water Vapor Lidar Experiment in Space – airborne demonstrator) lidar onboard the High Altitude and Long Range Research Aircraft HALO detected an ice PSC with a horizontal length of more than 1400 km. The ice PSC extended between 18 and 24 km altitude and was surrounded by nitric acid trihydrate (NAT) particles, supercooled ternary solution (STS) droplets and particle mixtures. The ice PSC occurrence in the backscatter ratio to depolarization optical space spanned by WALES observations is best matched by defining the inverse backscatter ratio of 0.3 as 1/Rice|NAT threshold between ice and NAT cloud regions. In addition, the histogram clearly shows two distinct branches in ice PSC occurrence, indicative for two ice formation pathways. In addition to ice nucleation in STSm with meteoric dust inclusions, ice nucleation on pre-existing NAT may play a role in the Arctic winter 2015/2016. This hypothesis is supported by differences in the ECMWF trajectory analysis for the two ice branches. The observation of widespread Arctic ice PSCs can advance our understanding of ice nucleation in cold polar and tropical latitudes. It further provides a new observational data base for the parameterization of ice nucleation schemes in atmospheric models.

scholarly journals Two decades of in-situ temperature measurements in the upper troposphere and lowermost stratosphere from IAGOS long-term routine observation

2017 ◽  
Author(s):  
Florian Berkes ◽  
Patrick Neis ◽  
Martin G. Schultz ◽  
Ulrich Bundke ◽  
Susanne Rohs ◽  
...  
Keyword(s):  
Weather Forecast ◽  
Global Scale ◽  
Temperature Trend ◽  
Data Set ◽  
Medium Range Weather Forecast ◽  
Upper Troposphere ◽  
Temperature Trends ◽  
Geographical Regions

Abstract. Despite several studies on temperature trends in the tropopause region, a comprehensive understanding of the evolution of temperatures in this climate-sensitive region of the atmosphere remains elusive. Here we present a unique global-scale, long-term data set of high-resolution in-situ temperature data measured aboard passenger aircraft within the European Research Infrastructure IAGOS (In-service Aircraft for a Global Observing System, www.iagos.org). This data set is used to investigate temperature trends within the global upper troposphere and lowermost stratosphere (UTLS) for the period 1995 to 2012 in different geographical regions and vertical layers of the UTLS. The largest amount of observations is available over the North Atlantic. Here, a neutral temperature trend is found within the lowermost stratosphere. This contradicts the temperature trend in the European Centre for Medium Range Weather Forecast (ECMWF) ERA-Interim reanalysis, where a significant (95 % confidence) temperature increase of +0.56 K/decade is obtained. Differences between trends derived from observations and reanalysis data can be traced back to changes in the temperature bias between observation and model data over the studied period. This study demonstrates the value of the IAGOS temperature observations as anchor point for the evaluation of reanalyses and its suitability for independent trend analyses.

Estimation of the precipitable water and water vapor flux using MAX-DOAS in two typical  cities of China

2021 ◽  
Author(s):  
Hongmei Ren ◽  
Ang Li ◽  
Pinhua Xie ◽  
Zhaokun Hu ◽  
Jin Xu ◽  
...  
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Reanalysis Data ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
Optical Absorption Spectroscopy ◽  
Water Vapor Flux ◽  
Vapor Flux ◽  
The North ◽  
Two Cities

<p>      Water vapor transport affects regional precipitation and climate change. The measurement of precipitable water and water vapor flux is of great significance to the study of precipitation and water vapor transport. In the study, a new method of computing the precipitable water and estimating the water vapor transport flux using multi-axis differential optical absorption spectroscopy (MAX-DOAS) were presented. The calculated precipitable water and water vapor flux were compared to the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data and the correlation coefficient of the precipitable water, the zonal and meridional water vapor flux and ECMWF are r≥0.92, r=0.77 and r≥0.89, respectively. The seasonal and diurnal climatologies of precipitable water and water vapor flux in the coastal (Qingdao) and inland (Xi’an) cities of China using this method were analyzed from June 1, 2019 to May 31, 2020. The results indicated that the seasonal and diurnal variation characteristics of the precipitable water in the two cities were similar. The zonal fluxes of the two cities were mainly transported from west to east, Qingdao's meridional flux was mainly transported to the south, and Xi'an was mainly transported to the north. The results also indicated that the water vapor flux transmitting belts appear near 2km and 1.4km above the surface in Qingdao and appeared around 2.8km, 1.6km and 1.0km in Xi'an. </p>

scholarly journals A comparison between the GNSS tomography technique and the WRF model in retrieving 3D wet refractivity field in Hong Kong

2018 ◽  
Author(s):  
Zhaohui Xiong ◽  
Bao Zhang ◽  
Yibin Yao
Keyword(s):  
Hong Kong ◽  
Water Vapor ◽  
Weather Prediction ◽  
Wrf Model ◽  
Vertical Direction ◽  
Lower Troposphere ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Rainy Period ◽  
Lower Accuracy

Abstract. Water vapor plays an important role in various scales of weather processes. However, there are limited means to monitor its 3-dimensional (3D) dynamical changes. The Numerical Weather Prediction (NWP) model and the Global Navigation Satellite System (GNSS) tomography technique are two of the limited means. Here, we conduct an interesting comparison between the GNSS tomography technique and the Weather Research and Forecasting (WRF) model (a representative of the NWP models) in retrieving Wet Refractivity (WR) in Hong Kong area during a rainy period and a rainless period. The GNSS tomography technique is used to retrieve WR from the GNSS slant wet delay. The WRF Data Assimilation (WRFDA) model is used to assimilate GNSS Zenith Tropospheric Delay (ZTD) to improve the background data. The WRF model is used to generate reanalysis data using the WRFDA output as the initial values. The radiosonde data are used to validate the WR derived from the GNSS tomography and the reanalysis data. The Root Mean Square (RMS) of the tomographic WR, the reanalysis WR that assimilate GNSS ZTD, and the reanalysis WR that without assimilating GNSS ZTD are 6.50 mm/km, 4.31 mm/km and 4.15 mm/km in the rainy period. The RMS becomes 7.02 mm/km, 7.26 mm/km and 6.35 mm/km in the rainless period. The lower accuracy in the rainless period is mainy due to the sharp variation of WR in the vertical direction. The results also show that assimilating GNSS ZTD into the WRFDA model only slightly improves the accuracy of the reanalysis WR and that the reanalysis WR is better than the tomographic WR in most cases. However, in a special experimental period when the water vapor is highly concentrated in the lower troposphere, the tomographic WR outperforms the reanalysis WR in the lower troposphere. When we assimilate the tomographic WR in the lower troposphere into the WRFDA model, the reanalysis WR is improved.

scholarly journals Precipitable Water Vapor Retrieval and Analysis by Multiple Data Sources: Ground-Based GNSS, Radio Occultation, Radiosonde, Microwave Satellite, and NWP Reanalysis Data

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Qin Zhang ◽  
Junhua Ye ◽  
Shuangcheng Zhang ◽  
Fei Han
Keyword(s):  
Water Vapor ◽  
Radio Occultation ◽  
Weather Prediction ◽  
Precipitable Water ◽  
Reanalysis Data ◽  
Precipitable Water Vapor ◽  
Reanalysis Dataset ◽  
High Positive Correlation ◽  
Advantages And Disadvantages ◽  
Ecmwf Reanalysis

Precipitable water vapor (PWV) content detection is vital to heavy rain prediction; up to now, lots of different measuring methods and devices are developed to observe PWV. In general, these methods can be divided into two categories, ground-based or space-based. In this study, we analyze the advantages and disadvantages of these technologies, compare retrieved atmosphere parameters by different RO (radio occultation) observations, like FORMOSAT-3/COSMIC (Formosa Satellite-3 and Constellation Observing System for Meteorology, Ionosphere, and Climate) and FY3C (China Feng Yun 3C), and assess retrieved PWV precision with a radiosonde. Besides, we interpolate PWV from NWP (numerical weather prediction) reanalysis data for more comparison and analysis with RO. Specifically, ground-based GNSS is of high precision and continuous availability to monitor PWV distribution; in our paper, we show cases to validate and compare GNSS retrieving PWV with a radiosonde. Except GNSS PWV, we give two different radio occultation sounding results, COSMIC and FY3C, to validate the precision to monitor PWV from space in a global area. FY3C results containing Beidou (China Beidou Global Satellite Navigation System) radio occultation events need to be emphasized. So, in our study, we get the retrieved atmospheric profiles from GPS and Beidou radio occultation observations and derive atmosphere PWV by a variational retrieval method based on these data over a global area. Besides, other space-based methods, such as microwave satellite, are also useful in detecting PWV distribution situations in a global area from space; in this study, we present a case of retrieved PWV using microwave satellite observation. NWP reanalysis data ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-Interim and the new-generation reanalysis data ERA5 provide global grid atmosphere parameters, like surface temperature, different-level pressures, and precipitable water. We show cases of retrieved PWV and validate the precision with radiosonde results and compare new reanalysis dataset ERA5 with ERA-Interim, finding that ERA5 can get higher precision-retrieved atmosphere parameters and PWV. In the end, from our comparison, we find that the retrieved PWV from RO (FY3C and COSMIC) and ECMWF reanalysis data (ERA-Interim and ERA5) have a high positive correlation and that almost all R2 values exceed 0.9, compare retrieved PWV with a radiosonde, and find that whether it is RO and ECMWF reanalysis data, ground-based GNSS, or microwave satellite, they all show small biases.

scholarly journals Improved Drought Monitoring Index Using GNSS-Derived Precipitable Water Vapor over the Loess Plateau Area

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5566 ◽  
Author(s):  
Qingzhi Zhao ◽  
Xiongwei Ma ◽  
Wanqiang Yao ◽  
Yang Liu ◽  
Zheng Du ◽  
...  
Keyword(s):  
Water Vapor ◽  
Loess Plateau ◽  
Meteorological Data ◽  
Precipitable Water ◽  
Satellite System ◽  
Reanalysis Data ◽  
Precipitable Water Vapor ◽  
Drought Monitoring ◽  
The Loess Plateau ◽  
Monitoring Index

Standardized precipitation evapotranspiration index (SPEI) is an acknowledged drought monitoring index, and the evapotranspiration (ET) used to calculated SPEI is obtained based on the Thornthwaite (TH) model. However, the SPEI calculated based on the TH model is overestimated globally, whereas the more accurate ET derived from the Penman–Monteith (PM) model recommended by the Food and Agriculture Organization of the United Nations is unavailable due to the lack of a large amount of meteorological data at most places. Therefore, how to improve the accuracy of ET calculated by the TH model becomes the focus of this study. Here, a revised TH (RTH) model is proposed using the temperature (T) and precipitable water vapor (PWV) data. The T and PWV data are derived from the reanalysis data and the global navigation satellite system (GNSS) observation, respectively. The initial value of ET for the RTH model is calculated based on the TH model, and the time series of ET residual between the TH and PM models is then obtained. Analyzed results reveal that ET residual is highly correlated with PWV and T, and the correlate coefficient between PWV and ET is −0.66, while that between T and ET for cases of T larger or less than 0 °C are −0.54 and 0.59, respectively. Therefore, a linear model between ET residual and PWV/T is established, and the ET value of the RTH model can be obtained by combining the TH-derived ET and estimated ET residual. Finally, the SPEI calculated based on the RTH model can be obtained and compared with that derived using PM and TH models. Result in the Loess Plateau (LP) region reveals the good performance of the RTH-based SPEI when compared with the TH-based SPEI over the period of 1979–2016. A case analysis in April 2013 over the LP region also indicates the superiority of the RTH-based SPEI at 88 meteorological and 31 GNSS stations when the PM-based SPEI is considered as the reference.

The role of El Niño Southern Oscillation on the patterns of cycling rates observed over India during the monsoon season

2014 ◽  
Vol 5 (4) ◽  
pp. 696-706 ◽  
Author(s):  
T. V. Lakshmi Kumar ◽  
K. Koteswara Rao ◽  
R. Uma ◽  
K. Aruna
Keyword(s):  
Water Vapor ◽  
El Niño ◽  
Hydrological Cycle ◽  
El Nino ◽  
Southern Oscillation ◽  
Monsoon Season ◽  
Precipitable Water ◽  
Spatiotemporal Variability ◽  
Monsoon Period ◽  
Sw Monsoon

Trend and interannual variability of total integrated precipitable water vapor (PWV) has been studied over India for the period 1979–2004 using NCEP/National Centre for Atmospheric Research reanalysis data with 2.5° × 2.5° resolution. The spatiotemporal variability of cycling rates (CR; units: per day), obtained from the ratio of rainfall to the PWV were presented not only for the long term (1979–2004) but also during El Niño (EN) and La Niña (LN) years of the study period to understand the intensity of hydrological cycle. The paper then dwells on obtaining the monthly atmospheric residences times over India to infer the stay of water vapor before it precipitates. The results of the present study are: all India PWV shows decreasing trend in association with the increasing/decreasing trends of Niño 3 SST/Southern Oscillation Index (SOI) for the southwest (SW) monsoon period of 1979–2004; the spatial pattern of temporal correlations of CR with SOI and Niño 3 SST displayed the significant positive and negative values in peninsular and central Indian portions of India respectively; all India atmospheric residence times varied from 9 to 2 days from premonsoon/post monsoon to SW monsoon over India.

scholarly journals Climatology and Trend of Severe Drought Events in the State of Sao Paulo, Brazil, during the 20th Century

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 190 ◽  
Author(s):  
Luiz Gozzo ◽  
Doris Palma ◽  
Maria Custodio ◽  
Jeferson Machado
Keyword(s):  
20Th Century ◽  
Linear Trend ◽  
Weather Forecast ◽  
Reanalysis Data ◽  
Sao Paulo ◽  
The State ◽  
Economic Consequences ◽  
Severe Drought ◽  
São Paulo ◽  
Medium Range Weather Forecast

Drought is a natural hazard with critical societal and economic consequences to millions of people around the world. In this paper, we present the climatology of severe drought events that occurred during the 20th century in the region of Sao Paulo, Brazil. To account for the effects of rainfall deficit and changes in temperature at a climatic timescale, we chose the Standardized Precipitation Evapotranspiration Index (SPEI) to identify severe droughts over the city of Sao Paulo, and the eastern and central-western regions of the state. Events were identified using weather station data and European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis data, in order to assess the representation of drought periods in both datasets. Results show that the reanalysis seems suitable to represent the number of events and their mean duration, severity and intensity, but the timing and characteristics of individual events are not well reproduced. The correlation between observation and reanalysis SPEI time series is low to moderate in all cases. A linear trend analysis between 1901 and 2010 shows a tendency of increasing (decreasing) severe drought events in the central and western (eastern) Sao Paulo state, according to observational data. This is in agreement with previous findings, and the reanalysis presents this same signal. The weakened trend values in the reanalysis may be associated with issues in representing precipitation in this dataset.

Statistical Characteristics of Long-Term High-Resolution Precipitable Water Vapor Data at Darwin

2018 ◽  
Vol 10 (04) ◽  
pp. 1850010
Author(s):  
Kimberly Leung ◽  
Aneesh C. Subramanian ◽  
Samuel S. P. Shen
Keyword(s):  
Water Vapor ◽  
High Resolution ◽  
Southern Oscillation ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Statistical Characteristics ◽  
Convective Precipitation ◽  
Data Set ◽  
Best Estimates

This paper studies the statistical characteristics of a unique long-term high-resolution precipitable water vapor (PWV) data set at Darwin, Australia, from 12 March 2002 to 28 February 2011. To understand the convective precipitation processes for climate model development, the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) program made high-frequency radar observations of PWV at the Darwin ARM site and released the best estimates from the radar data retrievals for this time period. Based on the best estimates, we produced a PWV data set on a uniform 20-s time grid. The gridded data were sufficient to show the fractal behavior of precipitable water with Hausdorff dimension equal to 1.9. Fourier power spectral analysis revealed modulation instability due to two sideband frequencies near the diurnal cycle, which manifests as nonlinearity of an atmospheric system. The statistics of PWV extreme values and daily rainfall data show that Darwin’s PWV has El Nino Southern Oscillation (ENSO) signatures and has potential to be a predictor for weather forecasting. The right skewness of the PWV data was identified, which implies an important property of tropical atmosphere: ample capacity to hold water vapor. The statistical characteristics of this long-term high-resolution PWV data will facilitate the development and validation of climate models, particularly stochastic models.

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