Global-scale intraseasonal and annual variation of divergent water-vapor flux

1990 ◽  
Vol 44 (1-4) ◽  
pp. 133-151 ◽  
Author(s):  
Tsing-Chang Chen ◽  
Ren-Yow Tzeng
Keyword(s):  
Water Vapor ◽  
Annual Variation ◽  
Global Scale ◽  
Water Vapor Flux ◽  
Vapor Flux

scholarly journals Annual Variation of Midlatitude Precipitation

2004 ◽  
Vol 17 (21) ◽  
pp. 4291-4298 ◽  
Author(s):  
Tsing-Chang Chen ◽  
Wan-Ru Huang ◽  
Eugene S. Takle
Keyword(s):  
Water Vapor ◽  
Annual Variation ◽  
Global Precipitation Climatology Project ◽  
Storm Tracks ◽  
Water Vapor Flux ◽  
Vapor Flux ◽  
Earth Observing System ◽  
Variation Patterns ◽  
Upper Level ◽  
Global Precipitation

Abstract Annual variation of midlatitude precipitation and its maintenance through divergent water vapor flux were explored by the use of hydrological variables from three reanalyses [(NCEP–NCAR, ECMWF Re-Analysis (ERA), and Goddard Earth Observing System (GEOS-1)] and two global precipitation datasets [Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and Global Precipitation Climatology Project (GPCP)]. Two annual variation patterns of midlatitude precipitation were identified:Tropical–midlatitude precipitation contrast: Midlatitude precipitation along storm tracks over the oceans attains its maximum in winter and its minimum in summer opposite to that over the tropical continents.Land–ocean precipitation contrast: The annual precipitation variation between the oceans and the continent masses exhibits a pronounced seesaw.The annual variation of precipitation along storm tracks of both hemispheres follows that of the convergence of transient water vapor flux. On the other hand, the land–ocean precipitation contrast in the Northern Hemisphere midlatitudes is primarily maintained by the annual seesaw between the divergence of stationary water vapor flux over the western oceans and the convergence of this water vapor flux over the eastern oceans during winter. The pattern is reversed during the summer. This divergence–convergence exchange of stationary water vapor flux is coupled with the annual evolution of upper-level ridges over continents and troughs over the oceans.

scholarly journals First-time lidar measurement of water vapor flux in a volcanic plume

2011 ◽  
Vol 284 (5) ◽  
pp. 1295-1298 ◽  
Author(s):  
Luca Fiorani ◽  
Francesco Colao ◽  
Antonio Palucci ◽  
Davod Poreh ◽  
Alessandro Aiuppa ◽  
...  
Keyword(s):  
Water Vapor ◽  
Volcanic Plume ◽  
Lidar Measurement ◽  
Water Vapor Flux ◽  
Vapor Flux ◽  
First Time

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 Rapid Cyclogenesis from a Mesoscale Frontal Wave on an Atmospheric River: Impacts on Forecast Skill and Predictability during Atmospheric River Landfall

2019 ◽  
Vol 20 (9) ◽  
pp. 1779-1794 ◽  
Author(s):  
Andrew C. Martin ◽  
F. Martin Ralph ◽  
Anna Wilson ◽  
Laurel DeHaan ◽  
Brian Kawzenuk
Keyword(s):  
Water Vapor ◽  
Lead Time ◽  
Forecast Skill ◽  
Vapor Transport ◽  
Lead Times ◽  
Forecast Uncertainty ◽  
Water Vapor Flux ◽  
Vapor Flux ◽  
Frontal Wave ◽  
Atmospheric River

Abstract Mesoscale frontal waves have the potential to modify the hydrometeorological impacts of atmospheric rivers (ARs). The small scale and rapid growth of these waves pose significant forecast challenges. We examined a frontal wave that developed a secondary cyclone during the landfall of an extreme AR in Northern California. We document rapid changes in significant storm features including integrated vapor transport and precipitation and connect these to high forecast uncertainty at 1–4-days’ lead time. We also analyze the skill of the Global Ensemble Forecast System in predicting secondary cyclogenesis and relate secondary cyclogenesis prediction skill to forecasts of AR intensity, AR duration, and upslope water vapor flux in the orographic controlling layer. Leveraging a measure of reference accuracy designed for cyclogenesis, we found forecasts were only able to skillfully predict secondary cyclogenesis for lead times less than 36 h. Forecast skill in predicting the large-scale pressure pattern and integrated vapor transport was lost by 96-h lead time. For lead times longer than 36 h, the failure to predict secondary cyclogenesis led to significant uncertainty in forecast AR intensity and to long bias in AR forecast duration. Failure to forecast a warm front associated with the secondary cyclone at lead times less than 36 h caused large overprediction of upslope water vapor flux, an important indicator of orographic precipitation forcing. This study highlights the need to identify offshore mesoscale frontal waves in real time and to characterize the forecast uncertainty inherent in these events when creating hydrometeorological forecasts.

scholarly journals Canopy Resistance and Estimation of Evapotranspiration above a Humid Cypress Forest

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Bau-Show Lin ◽  
Huimin Lei ◽  
Ming-Che Hu ◽  
Supattra Visessri ◽  
Cheng-I Hsieh
Keyword(s):  
Water Vapor ◽  
Seasonal Variations ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Canopy Resistance ◽  
Data Set ◽  
Water Vapor Flux ◽  
Vapor Flux ◽  
Evapotranspiration Estimation ◽  
Monteith Equation

This study presented a two-year data set of sensible heat and water vapor fluxes above a humid subtropical montane Cypress forest, located at 1650 m a.s.l. in northeastern Taiwan. The focuses of this study were to investigate (1) the diurnal and seasonal variations of canopy resistance and fluxes of sensible heat and water vapor above this forest; and (2) the mechanism of why a fixed canopy resistance could work when implementing the Penman–Monteith equation for diurnal hourly evapotranspiration estimation. Our results showed distinct seasonal variations in canopy resistance and water vapor flux, but on the contrary, the sensible heat flux did not change as much as the water vapor flux did with seasons. The seasonal variation patterns of the canopy resistance and water vapor flux were highly coupled with the meteorological factors. Also, the results demonstrated that a constant (fixed) canopy resistance was good enough for estimating the diurnal variation of evapotranspiration using Penman–Monteith equation. We observed a canopy resistance around 190 (s/m) for both the two warm seasons; and canopy resistances were around 670 and 320 (s/m) for the two cool seasons, respectively. In addition, our analytical analyses demonstrated that when the average canopy resistance is higher than 200 (s/m), the Penman–Monteith equation is less sensitive to the change of canopy resistance; hence, a fixed canopy resistance is suitable for the diurnal hourly evapotranspiration estimation. However, this is not the case when the average canopy resistance is less than 100 (s/m), and variable canopy resistances are needed. These two constraints (200 and 100) were obtained based on purely analytical analyses under a moderate meteorological condition (Rn = 600 W·m−2, RH = 60%, Ta = 20°C, U = 2 m·s−1) and a measurement height around two times of the canopy height.

scholarly journals Ocean Salinity as a Precursor of Summer Rainfall over the East Asian Monsoon Region

2019 ◽  
Vol 32 (17) ◽  
pp. 5659-5676 ◽  
Author(s):  
Biao Chen ◽  
Huiling Qin ◽  
Guixing Chen ◽  
Huijie Xue
Keyword(s):  
Water Vapor ◽  
Asian Monsoon ◽  
East Asian Monsoon ◽  
Summer Rainfall ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
Asian Monsoon Region ◽  
Water Vapor Flux ◽  
Vapor Flux ◽  
Land Water

Abstract The sea surface salinity (SSS) varies largely as a result of the evaporation–precipitation difference, indicating the source or sink of regional/global water vapor. This study identifies a relationship between the spring SSS in the tropical northwest Pacific (TNWP) and the summer rainfall of the East Asian monsoon region (EAMR) during 1980–2017. Analysis suggests that the SSS–rainfall link involves the coupled ocean–atmosphere–land processes with a multifacet evolution. In spring, evaporation and water vapor flux divergence were enhanced in some years over the TNWP where an anomalous atmospheric anticyclone was established and a high SSS was well observed. As a result, the convergence of water vapor flux and soil moisture over the EAMR was strengthened. This ocean-to-land water vapor transport pattern was sustained from spring to summer and played a leading role in the EAMR rainfall. Moreover, the change in local spring soil moisture helped to amplify the summer rainfall by modifying surface thermal conditions and precipitation systems over the EAMR. As the multifacet evolution is closely related to the large-scale ocean-to-land water vapor transport, it can be well represented by the spring SSS in the TNWP. A random forest regression algorithm was used to further evaluate the relative importance of spring SSS in predicting summer rainfall compared to other climate indices. As the SSS is now monitored routinely by satellite and the global Argo float array, it can serve as a good metric for measuring the water cycle and as a precursor for predicting the EAMR rainfall.

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