000861592 001__ 861592
000861592 005__ 20210131030916.0
000861592 0247_ $$2doi$$a10.1029/2018WR024072
000861592 0247_ $$2ISSN$$a0043-1397
000861592 0247_ $$2ISSN$$a0148-0227
000861592 0247_ $$2ISSN$$a1944-7973
000861592 0247_ $$2ISSN$$a2156-2202
000861592 0247_ $$2Handle$$a2128/22230
000861592 0247_ $$2WOS$$aWOS:000468597900022
000861592 0247_ $$2altmetric$$aaltmetric:61406446
000861592 037__ $$aFZJ-2019-02042
000861592 082__ $$a550
000861592 1001_ $$0P:(DE-Juel1)158034$$aGroh, J.$$b0$$eCorresponding author
000861592 245__ $$aQuantification and prediction of nighttime evapotranspiration for two distinct grassland ecosystems
000861592 260__ $$a[New York]$$bWiley$$c2019
000861592 3367_ $$2DRIVER$$aarticle
000861592 3367_ $$2DataCite$$aOutput Types/Journal article
000861592 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1559042299_31637
000861592 3367_ $$2BibTeX$$aARTICLE
000861592 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000861592 3367_ $$00$$2EndNote$$aJournal Article
000861592 520__ $$aEvapotranspiration (ET) is, after precipitation, the second largest flux at the land surface in the water cycle and occurs mainly during daytime. Less attention has been given to water fluxes from the land surface into the atmosphere during nighttime (i.e., between sunset and sunrise). The nighttime ET (ETN) may be estimated based on models that use meteorological data; however, due to missing experimental long‐term data, the verification of ETN estimates is limited. In this paper, the amount of ETN for two grassland ecosystems was determined from highly temporally resolved and precise weighing lysimeter data. We found that annual ETN ranged between 3.5% and 9.5% of daytime annual ET (ETD) and occurred mainly during wet soil and canopy surface conditions, which suggests that ETN is largely related to evaporation. ETN was positively correlated with wind speed. Dew formation, ranging from 4.8% to 6.4% of annual precipitation, was in absolute terms larger than ETN. The prediction of ETN with the Penman‐Monteith model improved if the aerodynamic and surface resistance parameters were based on vegetation height observations and the nighttime stomatal resistance parameter was assumed to be zero. The occurrence of hot days during the observation period showed to increase average ETN rates. Our results suggest that ETN can be observed with precision weighing lysimeters, was a not negligible component in the water balance of the grassland ecosystems, and thus needs more attention when simulating land surface hydrological processes.
000861592 536__ $$0G:(DE-HGF)POF3-255$$a255 - Terrestrial Systems: From Observation to Prediction (POF3-255)$$cPOF3-255$$fPOF III$$x0
000861592 588__ $$aDataset connected to CrossRef
000861592 7001_ $$0P:(DE-Juel1)129523$$aPütz, Thomas$$b1$$ufzj
000861592 7001_ $$00000-0002-6232-7688$$aGerke, H. H.$$b2
000861592 7001_ $$0P:(DE-Juel1)129548$$aVanderborght, J.$$b3
000861592 7001_ $$0P:(DE-Juel1)129549$$aVereecken, H.$$b4
000861592 773__ $$0PERI:(DE-600)2029553-4$$a10.1029/2018WR024072$$gp. 2018WR024072$$n4$$p2961-2975$$tWater resources research$$v55$$x1944-7973$$y2019
000861592 8564_ $$uhttps://juser.fz-juelich.de/record/861592/files/Groh_et_al-2019-Water_Resources_Research-1.pdf$$yPublished on 2019-03-21. Available in OpenAccess from 2019-09-21.
000861592 8564_ $$uhttps://juser.fz-juelich.de/record/861592/files/Groh_et_al-2019-Water_Resources_Research-1.pdf?subformat=pdfa$$xpdfa$$yPublished on 2019-03-21. Available in OpenAccess from 2019-09-21.
000861592 909CO $$ooai:juser.fz-juelich.de:861592$$pdnbdelivery$$pVDB$$pVDB:Earth_Environment$$pdriver$$popen_access$$popenaire
000861592 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)158034$$aForschungszentrum Jülich$$b0$$kFZJ
000861592 9101_ $$0I:(DE-HGF)0$$6P:(DE-Juel1)158034$$aLeibniz-Center for Agriculture Landscape Research (ZALF)$$b0
000861592 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129523$$aForschungszentrum Jülich$$b1$$kFZJ
000861592 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129548$$aForschungszentrum Jülich$$b3$$kFZJ
000861592 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129549$$aForschungszentrum Jülich$$b4$$kFZJ
000861592 9131_ $$0G:(DE-HGF)POF3-255$$1G:(DE-HGF)POF3-250$$2G:(DE-HGF)POF3-200$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bErde und Umwelt$$lTerrestrische Umwelt$$vTerrestrial Systems: From Observation to Prediction$$x0
000861592 9141_ $$y2019
000861592 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000861592 915__ $$0StatID:(DE-HGF)1160$$2StatID$$aDBCoverage$$bCurrent Contents - Engineering, Computing and Technology
000861592 915__ $$0StatID:(DE-HGF)0530$$2StatID$$aEmbargoed OpenAccess
000861592 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bWATER RESOUR RES : 2017
000861592 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000861592 915__ $$0StatID:(DE-HGF)0110$$2StatID$$aWoS$$bScience Citation Index
000861592 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000861592 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000861592 915__ $$0StatID:(DE-HGF)1060$$2StatID$$aDBCoverage$$bCurrent Contents - Agriculture, Biology and Environmental Sciences
000861592 915__ $$0StatID:(DE-HGF)0310$$2StatID$$aDBCoverage$$bNCBI Molecular Biology Database
000861592 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000861592 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List
000861592 920__ $$lyes
000861592 9201_ $$0I:(DE-Juel1)IBG-3-20101118$$kIBG-3$$lAgrosphäre$$x0
000861592 980__ $$ajournal
000861592 980__ $$aVDB
000861592 980__ $$aUNRESTRICTED
000861592 980__ $$aI:(DE-Juel1)IBG-3-20101118
000861592 9801_ $$aFullTexts