Variability Of Water Vapor Research Articles

Diurnal variability of lower and middle atmospheric water vapour over the Asian summer monsoon region: first results from COSMIC-1 and TIMED-SABER measurements

First observations on the vertical structure of diurnal variability of water vapour in the lower and middle atmosphere using 13 years of COSMIC-1 and 18 years of SABER observations over the Asian summer monsoon region are presented in this paper. The most significant and new observation is that the middle stratospheric water vapour (SWV) enhancement is observed between 9 and 18 LT, whereas it is between 6 and 15 LT near tropopause in all the seasons. The diurnal amplitude of water vapour near tropopause is between 0.3 and 0.4 ppmv. Bimodal peaks are found in the diurnal amplitude of SWV, maximizing between 25 and 30 km (~ 0.4 ppmv), and between 45 and 50 km (~ 0.6 ppmv). The analysis reveals that the diurnal variability in the lower SWV is controlled by the tropical tropopause temperature, whereas the middle and upper SWV is primarily controlled by methane oxidation. The results are presented and discussed in the light of present understanding.

First Observations of Mesospheric OH Emission Profiles from OMPS/LP

Abstract The hydroxyl radical (OH) is one of the most reactive trace species and plays several important roles in the photochemical equilibrium and energy balance in the mesosphere. Global observations of OH from satellite instruments have a role to play in the study of OH and water vapor variations. This study describes an advanced algorithm to detect mesospheric OH emission profiles from the Suomi NPP satellite Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP). A triplet technique has been adapted to the OMPS/LP radiance measurements for determining OH emission signatures and OH index (OHI) from the OH A2Σ+-X2Π 0-0 band near the 308.8-nm wavelength. The derived mesospheric profiles provide an overall picture of the vertical distribution of OHI between 55 and 84 km and seasonal and latitudinal variability of the strength and height of the OHI. The observed annual cycle is correlated with the water vapor cycle and anticorrelated with the mesospheric temperature cycle. The data show that the relationships persist during the period of April 2012–December 2020. The seasonal behavior of OHI may be associated with variations in solar illumination or mesospheric water vapor abundance. The influence of solar illumination is dominant in the midlatitudes, while the OHI pattern is dominated by water vapor photolysis and other influences in the tropics.

Improving VLBI analysis by tropospheric ties in GNSS and VLBI integrated processing

Tropospheric delay modeling is challenging in high-precision Very Long Baseline Interferometry (VLBI) analysis due to the rapid water vapor variation and imperfect observation geometry, where observations from Global Navigation Satellite Systems (GNSS) co-locations can enhance the VLBI analysis. We investigate the impact of tropospheric ties in the VLBI and GNSS integrated processing during the CONT05–CONT17 campaigns, and present a method that automatically handles the systematic tropospheric tie biases. Applying tropospheric ties at VLBI–GNSS co-locations enhances the observation geometry and improves the solution reliability. The VLBI network is stabilized, with station coordinate repeatability improved by 12% horizontally and by 28% vertically, and the network scale improved by 32%. The Earth Orientation Parameters (EOP) improve by up to 20%. Both zenith delay and gradient ties contribute to the improvement of EOP, whereas the gradient ties contribute mainly to the improvement of length of day and celestial pole offsets.

Monsoon Fringe Area Moisture Transportation Revealed by Water Stable Isotopes: A Lanzhou River Valley Case Study

Because of global warming, the water cycle has intensified and precipitation has changed, with monsoons evolving to become more complex, particularly in monsoon fringe areas. Therefore, it is important to use stable isotopes to trace moisture sources in monsoon fringe areas, such as semiarid areas. In this study, in situ measurements of water vapor isotopes were obtained in the monsoon fringe areas of Lanzhou (36.1° N, 103.7° E), between May and November 2019 with the aim of analyzing the stable isotope composition and atmospheric water vapor variation to improve our understanding of moisture transport. The following results were obtained: stable isotopic variation of atmospheric water vapor shows an alternation between west and southwest moisture with wind directions and sources of water vapor, with δ18O and δ2H varying from high to low. In the Lanzhou valley, water vapor isotopes show a distinct daily cycle of δ17O, δ18O, and δ2H and are consistent with temperature changes. Water vapor isotopes, particularly d-excess, are correlated with temperature and absolute humidity. With regard to the local atmospheric water vapor line (LAVL), we show that the slope and intercept of the LAVL are affected by sub-cloud secondary evaporation and topography.

A Long‐Lasting Precipitation Deficit in South China During Autumn‐Winter 2020/2021: Combined Effect of ENSO and Arctic Sea Ice

AbstractA severe persistent drought occurred in South China during autumn–winter 2020/2021, causing enormous economic losses and severe water shortage in South China. Focusing on this event, this study analyzed the climate anomalies associated with this event, and investigated the underlying mechanisms as well as their relationship with the leading modes of the autumn and winter precipitation in eastern China. The results suggest that the drought in South China during autumn 2020 is mainly attributed to the water vapor divergence anomalies induced by an anomalous anticyclone over eastern China and an anomalous cyclone over the South China Sea, which are caused by an anomalous Eurasian atmospheric wave‐train triggered by the negative sea ice anomalies in the Barents Sea‐Kara Sea region and a La Niña‐like condition in the tropical Pacific sea surface temperatures, respectively. The continued drought in South China during winter 2020/2021 is mainly attributed to the water vapor divergence anomalies induced by an anomalous cyclone over the western North Pacific, which is caused by the continued La Niña‐like condition. The mechanisms of the first two leading modes of autumn precipitation in eastern China both contributed to the drought in South China during autumn 2020, whereas the mechanisms of the first leading mode of winter precipitation in eastern China played an important role in causing the drought in South China during winter 2020/2021. Numerical experiments demonstrate important impact of the ENSO and Arctic sea ice anomalies on the East Asian climate anomalies during autumn–winter 2020/2021.

Global Spatiotemporal Variability of Integrated Water Vapor Derived from GPS, GOME/SCIAMACHY and ERA-Interim: Annual Cycle, Frequency Distribution and Linear Trends

Atmospheric water vapor plays a prominent role in climate change and atmospheric, meteorological, and hydrological processes. Because of its high spatiotemporal variability, precise quantification of water vapor is challenging. This study investigates Integrated Water Vapor (IWV) variability for the period 1995–2010 at 118 globally distributed Global Positioning System (GPS) sites, using additional UV/VIS satellite retrievals by GOME, SCIAMACHY, and GOME-2 (denoted as GOMESCIA below), plus ERA-Interim reanalysis output. Apart from spatial representativeness differences, particularly at coastal and island sites, all three IWV datasets correlate well with the lowest mean correlation coefficient of 0.878 (averaged over all the sites) between GPS and GOMESCIA. We confirm the dominance of standard lognormal distribution of the IWV time series, which can be explained by the combination of a lower mode (dry season characterized by a standard lognormal distribution with a low median value) and an upper mode (wet season characterized by a reverse lognormal distribution with high median value) in European, Western American, and subtropical sites. Despite the relatively short length of the time series, we found a good consistency in the sign of the continental IWV trends, not only between the different datasets, but also compared to temperature and precipitation trends.

The role of ENSO in atmospheric water vapor variability during cold months over Iran

The role of ENSO in atmospheric water vapor variability during cold months over Iran

Multi-Year Variations in Atmospheric Water Vapor in the Baikal Natural Territory According to GPS Observations

The data of GPS measurements at the permanent observation points IRKM (Irkutsk, 52°13′ N, 104°19′ E, h = 509 m), ULAZ (Ulan-Ude, 51°48′ N, 107°37′ E, h = 517 m) and BADG (Badary, 51°46′ N, 102°14′ E, h = 848 m) located within the Baikal natural area (Eastern Siberia) are considered. A comparison was made of the time series of the tropospheric moisture content levels obtained at the IRKM site from GPS observations and radiosonde data, and at the BADG site from GPS observations and measurements with a water vapor radiometer (WVR) during 2020. The average deviation of the difference in total moisture content data during 2020 in the form of precipitable water according to GPS and WVR observations was about 0.12 mm, or about 1.1% relative to the average value, and the cross-correlation coefficient between the data is very high (K = 0.92). The use of GPS observations to obtain continuous data on the moisture content of the troposphere is substantiated. A series of processed data on the total moisture content based on GPS measurements using surface meteorological data for the period 1999–2020 for the IRKM and ULAZ sites and for the period 2006–2020 for the BADG site were obtained. Linear trends of total moisture content were determined for observation points: IRKM (−0.35 mm per decade, –2.7%), ULAZ (+0.47 mm per decade, +3.9%) and BADG (+1.41 mm per decade, 13.4%). Moreover, at the IRKM and ULAZ points, the surface temperature trends in the same period were positive and amounted to +0.4 K and +0.7 K per decade, respectively. The article confirms the trends identified in the work of Ross and Elliott for the territory of Eastern Siberia.

Understanding the Present-Day Spatiotemporal Variability of Precipitable Water Vapor over Ethiopia: A Comparative Study between ERA5 and GPS

Atmospheric water vapor plays a crucial role in atmospheric, climate change, meteorological, and hydrological processes. In a country like Ethiopia, with its complex topography and synoptic-scale spatiotemporal circulation patterns, the analysis of the spatiotemporal variability of precipitable water vapor (PWV) is very challenging, and is hampered by the lack of long observational datasets. In this study, we process the PWV over eight Ethiopian global positioning system (GPS) sites and one close to the Ethiopian eastern border, for the available common period 2013–2020, and compare with the PWV retrieved from the state-of-the-art ERA5 reanalysis. Both PWV datasets agree very well at our sample, with correlation coefficients between 0.96 and 0.99, GPS-PWV show a moderate wet bias compared to ERA5-PWV for the majority of the sites, and an overall root mean square error of 3.4 mm. Seasonal and diurnal cycles are also well captured by these datasets. The seasonal variations of PWV and precipitation at the sites agree very well. Maximum diurnal PWV amplitudes are observed for stations near water bodies or dense vegetation, such as Arbaminch (ARMI) and Bahir Dar (BDMT). At those stations, the PWV behavior at heavy rainfall events has been investigated and an average 25% increase (resp. decrease) from 12 h before (resp. 12 h after) the start of the rainfall event, when the PWV peaks, has been observed.

Incremental Learning with Neural Network Algorithm for the Monitoring Pre-Convective Environments Using Geostationary Imager

Early warning of severe weather caused by intense convective weather systems is challenging. To help such activities, meteorological satellites with high temporal and spatial resolution have been utilized for the monitoring of instability trends along with water vapor variation. The current study proposes a retrieval algorithm based on an artificial neural network (ANN) model to quickly and efficiently derive total precipitable water (TPW) and convective available potential energy (CAPE) from Korea’s second geostationary satellite imagery measurements (GEO-KOMPSAT-2A/Advanced Meteorological Imager (AMI)). To overcome the limitations of the traditional static (ST) learning method such as exhaustive learning, impractical, and not matching in a sequence data, we applied an ANN model with incremental (INC) learning. The INC ANN uses a dynamic dataset that begins with the existing weight information transferred from a previously learned model when new samples emerge. To prevent sudden changes in the distribution of learning data, this method uses a sliding window that moves along the data with a window of a fixed size. Through an empirical test, the update cycle and the window size of the model are set to be one day and ten days, respectively. For the preparation of learning datasets, nine infrared brightness temperatures of AMI, six dual channel differences, temporal and geographic information, and a satellite zenith angle are used as input variables, and the TPW and CAPE from ECMWF model reanalysis (ERA5) data are used as the corresponding target values over the clear-sky conditions in the Northeast Asia region for about one year. Through the accuracy tests with radiosonde observation for one year, the INC NN results demonstrate improved performance (the accuracy of TPW and CAPE decreased by approximately 26% and 26% for bias and about 13% and 12% for RMSE, respectively) when compared to the ST learning. Evaluation results using ERA5 data also reveal more stable error statistics over time and overall reduced error distribution compared with ST ANN.

Water vapor isotopes indicating rapid shift among multiple moisture sources for the 2018–2019 winter extreme precipitation events in southeastern China

Abstract. In the East Asian monsoon region, winter extreme precipitation events occasionally occur and bring great social and economic losses. From December 2018 to February 2019, southeastern China experienced a record-breaking number of extreme precipitation events. In this study, we analyzed the variation in water vapor isotopes and their controlling factors during the extreme precipitation events in Nanjing, southeastern China. The results show that the variations in water vapor isotopes are closely linked to the change in moisture sources. Using a water vapor d-excess-weighted trajectory model, we identified the following five most important moisture source regions: South China, the East China Sea, the South China Sea, the Bay of Bengal, and continental regions (northwestern China and Mongolia). Moreover, the variations in water vapor d excess during a precipitation event reflect rapid shifts in the moisture source regions. These results indicate that rapid shifts among multiple moisture sources are important conditions for sustaining wintertime extreme precipitation events over extended periods.

Evaluation of ERA5 reanalysis atmospheric water vapor variation in Algeria

In climate change context, the precipitable water vapour (PW) is key parameter of atmospheric process and dynamics and its variation is very high in space and time. It's accuracy is paramount for any geodetic or climatic study. The main objective of this study is to compute precipitable water vapour from ERA5 reanalysis for 4 stations in Algeria which have different types of climate. We opt for using integration method for different level of pressure with ERA5. The values of water vapour are also compared with radiosondes profiles. The results of this work shows good agreement with a correlation that is not less than not 0.95 and 0.70 compared as radiosondes profiles. The first results are encouraging, in particular for meteorological applications with good hope to introduce another dataset as GNSS to more understand the variation and behavior of water vapour over a long period of observation.

An Analysis of Spatio-Temporal Water Vapor Variation in the East Java using Ground Based GPS Receivers

Water vapor plays a critical role in the global/regional scale of weather and climate changes. Traditionally, the water vapor measurement uses radiosonde balloons which are very sparse in the distribution. The utilization of GPS as a new method for studying water vapor has been studied in several publications. This research analyzed the precipitable water vapor (PWV) based on ground-based GPS receivers in the East Java region. In the first part, the datasets are compared. The Zenith Total Delay (ZTD) from GPS processing will be compared with the Zenith Path Delay from the International GNSS Service (IGS) results. The comparison of ZTD and ZPD shows a good agreement. The comparison of GPS PWV and Radiosonde shows a good agreement. The spatio-temporal of GPS PWV is correlated with the Monsoon Asian-Australian cycles that affect weather and climate in Indonesia. The result indicates that GPS data provide valuable information in meteorology and climatology.

Interannual Variability of the GNSS Precipitable Water Vapor in the Global Tropics

This paper addresses the subject of inter-annual variability of the tropical precipitable water vapor (PWV) derived from 18 years of global navigation satellite system (GNSS) observations. Non-linear trends of retrieved GNSS PWV were investigated using the singular spectrum analysis (SSA) along with various climate indices. For most of the analyzed stations (~49%) the GNSS PWV anomaly was related to the El Niño Southern Oscillation (ENSO), although its influence on the PWV variability was not homogeneous. The cross-correlations coefficient values estimated between the Multivariate ENSO Index (MEI) and PWV were up to 0.78. A strong cross-correlation was also found for regional climate pattern expressed through CAR, DMI, HAW, NPGO, TNA and TSA indices. A distinct agreement was also found when instead of climate indices, the local sea surface temperature was examined (average correlation 0.60). The SSA method made it also possible to distinguish small-scale phenomena that affect PWV, such as local droughts or wetter rainy seasons. The overall nature of the investigated changes was also verified through linear trend analysis. In general, not a single station was characterized by a negative trend and its weighted mean value, calculated for all stations was equal to 0.08 ± 0.01 mm/year.

ANNUAL AND SEMI-ANNUAL VARIATIONS OF THE GPS-DERIVED PRECIPITABLE WATER VAPOR OVER SUMATRA ISLAND

<p align="justify"><em>We have utilized the Global Positioning System (GPS) data at 57 stations distributed over Sumatra Island to investigate spatio-temporal variations of the atmospheric precipitable water vapor (PWV). We focused on the annual and semi-annual cycles of the PWV. Our results show that Sumatra Island is divided into two distinct areas of annual and semi-annual cycles, where the boundary line between the areas is </em><em>approximately a</em><em>t</em><em> 2</em><em><sup>o</sup></em><em>S. While the annual cycle dominates the area over the southern side of 2</em><em><sup>o</sup></em><em>S, the semi-annual cycle is dominant over the northern side. Our results have further shown that</em><em> the maximum phase of annual cycle </em><em>occurs</em><em> between January-March with considerably large amplitudes (10-15 mm). On the other side, the maximum phase of the semi-annual cycle in general occurs around November and May, whose amplitude is approximately between 1-5 mm. Our results are consistent with other results using rainfall data.</em><em></em></p>

Precipitation Water Vapour Variation in the East Java Region from Data CORS Using GIPSY

The Global Navigation Satellite System is being developed as an atmospheric remote sensing system through the calculation of Zenith Total Delay. The development of the Continous Operating Reference Station encourages research investigations into Zenith Tropospheric Delay with continuous data and good spatial resolution. This research studies the characteristics of spatial and temporal variations of the Zenith Wet Delay in East Jawa. The case study in East Jawa Province uses 16 Continous Operating Reference Stations. As a comparison, meteorological data from the Badan Meteorologi, Klimatologi, and Geofisika stations are used.The Zenith Total Delay and Zenith Wet Delay values from the Continous Operating Reference Station data are calculated using GIPSY 6.4 Software. The Zenith Wet Delay values are gridded using the kriging method with the size of the grids being 0,25 x 0,25. The ZWD value comparison from the Continous Operating Reference Station and meteorology data has a strong correlation with a coefficient value of 0,712. The mean of Zenith Wet Delay’s trend is increasing by about 0,712 mm/yr. The characteristics of the spatial and temporal variations of the ZWD value are influenced by the monsoon of Asia-Australian, which causes dry and rainy seasons, global phenomena such as El Nino and La Nina, rainfall, local meteorological conditions such as temperature and humidity, weather, and the topography of the stations.

Decadal change of extreme consecutive dry days in spring over the middle and lower reaches of the Yangtze River around the early 2000s: The synergistic effect of mega-El Niño/Southern Oscillation, Atlantic Multidecadal Oscillation, and Arctic sea ice

Base on daily station precipitation data from 1960 to 2019, the variability of extreme consecutive dry days (extreme-CDDs) over the middle and lower reaches of the Yangtze River (MLRYR) during spring sowing time (March–April) is investigated. It is found that the extreme-CDDs over MLRYR experienced a significant decadal increase around the early 2000s. Associated with this decadal change, the Mongolian high and western North Pacific anticyclone (WNPA) are significantly intensified and weakened, respectively. The intensified Mongolian high and weakened WNPA lead to anomalous northerlies and water vapor divergence over MLRYR, providing favorable atmospheric conditions for more extreme-CDDs over the region. Further mechanism analyses suggest that the transition of mega-El Niño/Southern Oscillation (mega-ENSO) from negative-phase to positive-phase contributes to the decadal weakening of WNPA. And the phase transition of Atlantic Multidecadal Oscillation (AMO) and decadal decrease of sea ice over the Barents Sea lead to intensified Mongolian high through exciting atmospheric wave train. Multiple linear regression shows that there could be a synergistic role of mega-ENSO, AMO, and sea ice over the Barents Sea in the decadal change in extreme-CDDs over MLRYR around the early 2000s. Analysis on the simulation of 14 models in the Atmospheric Model Intercomparison Project (AMIP) experiment from phase 6 of the Coupled Model Intercomparison Project (CMIP6) shows that the models can reproduce the observed decadal intensification of the Mongolian high and weakening of WNPA around the early 2000s, which indicates the contribution of mega-ENSO, AMO, and sea ice over the Barents Sea to the decadal changes in Mongolian high, WNPA and extreme-CDDs over MLRYR.

Impact of a Mixed Ocean Layer and the Diurnal Cycle on Convective Aggregation.

We investigate how ocean feedbacks and the diurnal cycle impact convective aggregation using a slab ocean coupled to a cloud resolving model. With a 20 m mixed layer ocean, aggregation occurs after 25 days. Thinner ocean layers slow the onset of clustering, with a 1 m ocean layer needing around 43 days. The delay is due to anomalous solar radiation in clear sky regions, causing a relative surface warming balanced by a matching cooling in cloudy areas. The resulting gradient in surface heat fluxes opposes low level convergence into convecting regions. On aggregation, the convective regions are surrounded by moist, clear sky regions with the hottest SSTs, toward which convection migrates, while a cold SST patch forms under dry suppressed regions due to enhanced latent heat fluxes and longwave radiation. The next experiment allows a diurnal cycle of 2.5°C in the domain mean SST. This causes convective rainfall to shift from a weak morning maximum to a sharper evening peak, reminiscent of undisturbed tropical observations. However, convection reverts to a weak early morning maximum once aggregation starts due to spatially heterogeneous radiative forcing. This implies thin mixed ocean layers are a necessary but non‐sufficient condition for an afternoon maximum of convection; limited spatial water vapor variability is also necessary. The imposition of the mean diurnal cycle has no statistically significant impact on the mean timing of clustering onset.

Lag impacts of the anomalous July soil moisture over Southern China on the August rainfall over the Huang\u2013Huai River Basin

The effect of soil moisture (SM) on precipitation is an important issue in the land–atmosphere interaction and shows largely regional differences. In this study, the SM of the ERA-Interim reanalysis and precipitation data of the weather stations were used to investigate their relationship over eastern China during July and August. Moreover, the WRF model was applied to further validate the effect of SM on rainfall. In the observations, a significantly negative relationship was found that, when the soil over southern China is wet (dry) in July, the rainfall decreases (increases) over the Huang–Huai–River basin (hereafter HHR) in August. In the model results, the soil can “memorize” its wet anomaly over southern China from July to August. In August, the wet soil increases the latent heat flux at surface and the air moisture at lower levels of the atmosphere, which is generally unstable due to the summer monsoon. Thus, upward motion is prevailing over southern China in August, and the increased surface air moisture is transported upwards. After that, the condensation of water vapor is enhanced at the middle and upper levels, increasing the release of latent heat in the atmosphere. The heat release forms a cyclonic circulation at the lower levels over eastern China, and induces the transport and convergence of water vapor increased over southern China in August. This further strengthens the upward motion over southern China and the cyclonic circulation at the lower levels. Therefore, positive feedback appears between water vapor transport and atmospheric circulation. Meanwhile, the cyclonic circulation over southern China results in a response of water vapor divergence and a downward motion over HHR. Consequently, the negative anomalies of precipitation occur over HHR in August. When the July soil is dry over southern China, the opposite results can be found through the similar mechanism.

Spatio-Temporal Variations of Precipitable Water Vapor and Horizontal Tropospheric Gradients from GPS during Typhoon Lekima

GPS data during Typhoon Lekima at 700 stations in China were processed by the Precise Point Positioning (PPP) method. A refined regional Tm model was used to derive the precipitable water vapor (PWV) at these GPS stations. Spatio-temporal variations of PWV with the typhoon process were analyzed. As the typhoon approached, PWV at stations near the typhoon center increased sharply from about 50 mm to nearly 80 mm and then dropped back to about 40–50 mm as the typhoon left. Comparisons of GPS, radiosonde, the Global Data Assimilation System (GDAS) Global Forecast System (GFS) analysis products and ERA5 reanalysis products at four matched GPS-RS stations show overall overestimations of PWV from radiosonde, GFS and ERA5 compared with GPS in a statistical perspective. An empirical orthogonal functions (EOF) analysis of the PWV during the typhoon event revealed some different patterns of variability, with both the first EOF (~36.1% of variance) and second EOF (~30.3% of variance) showing distinctively large anomalies over the typhoon landing locations. The typhoon caused a large horizontal tropospheric gradient (HTG) with the magnitude reaching 5 mm and the direction pointing to the typhoon center when it made a landfall on mainland China. The magnitude and the consistency of the HTG direction decreased overall as the typhoon weakened.