TY  - JOUR
A1  - Wuttke, Matthias
A1  - Li, Yong
A1  - Li, Man
A1  - Sieber, Karsten B.
A1  - Feitosa, Mary F.
A1  - Gorski, Mathias
A1  - Tin, Adrienne
A1  - Wang, Lihua
A1  - Chu, Audrey Y.
A1  - Hoppmann, Anselm
A1  - Kirsten, Holger
A1  - Giri, Ayush
A1  - Chai, Jin-Fang
A1  - Sveinbjornsson, Gardar
A1  - Tayo, Bamidele O.
A1  - Nutile, Teresa
A1  - Fuchsberger, Christian
A1  - Marten, Jonathan
A1  - Cocca, Massimiliano
A1  - Ghasemi, Sahar
A1  - Xu, Yizhe
A1  - Horn, Katrin
A1  - Noce, Damia
A1  - Van der Most, Peter J.
A1  - Sedaghat, Sanaz
A1  - Yu, Zhi
A1  - Akiyama, Masato
A1  - Afaq, Saima
A1  - Ahluwalia, Tarunveer Singh
A1  - Almgren, Peter
A1  - Amin, Najaf
A1  - Arnlov, Johan
A1  - Bakker, Stephan J. L.
A1  - Bansal, Nisha
A1  - Baptista, Daniela
A1  - Bergmann, Sven
A1  - Biggs, Mary L.
A1  - Biino, Ginevra
A1  - Boehnke, Michael
A1  - Boerwinkle, Eric
A1  - Boissel, Mathilde
A1  - Böttinger, Erwin
A1  - Boutin, Thibaud S.
A1  - Brenner, Hermann
A1  - Brumat, Marco
A1  - Burkhardt, Ralph
A1  - Butterworth, Adam S.
A1  - Campana, Eric
A1  - Campbell, Archie
A1  - Campbell, Harry
A1  - Canouil, Mickael
A1  - Carroll, Robert J.
A1  - Catamo, Eulalia
A1  - Chambers, John C.
A1  - Chee, Miao-Ling
A1  - Chee, Miao-Li
A1  - Chen, Xu
A1  - Cheng, Ching-Yu
A1  - Cheng, Yurong
A1  - Christensen, Kaare
A1  - Cifkova, Renata
A1  - Ciullo, Marina
A1  - Concas, Maria Pina
A1  - Cook, James P.
A1  - Coresh, Josef
A1  - Corre, Tanguy
A1  - Sala, Cinzia Felicita
A1  - Cusi, Daniele
A1  - Danesh, John
A1  - Daw, E. Warwick
A1  - De Borst, Martin H.
A1  - De Grandi, Alessandro
A1  - De Mutsert, Renee
A1  - De Vries, Aiko P. J.
A1  - Degenhardt, Frauke
A1  - Delgado, Graciela
A1  - Demirkan, Ayse
A1  - Di Angelantonio, Emanuele
A1  - Dittrich, Katalin
A1  - Divers, Jasmin
A1  - Dorajoo, Rajkumar
A1  - Eckardt, Kai-Uwe
A1  - Ehret, Georg
A1  - Elliott, Paul
A1  - Endlich, Karlhans
A1  - Evans, Michele K.
A1  - Felix, Janine F.
A1  - Foo, Valencia Hui Xian
A1  - Franco, Oscar H.
A1  - Franke, Andre
A1  - Freedman, Barry I.
A1  - Freitag-Wolf, Sandra
A1  - Friedlander, Yechiel
A1  - Froguel, Philippe
A1  - Gansevoort, Ron T.
A1  - Gao, He
A1  - Gasparini, Paolo
A1  - Gaziano, J. Michael
A1  - Giedraitis, Vilmantas
A1  - Gieger, Christian
A1  - Girotto, Giorgia
A1  - Giulianini, Franco
A1  - Gogele, Martin
A1  - Gordon, Scott D.
A1  - Gudbjartsson, Daniel F.
A1  - Gudnason, Vilmundur
A1  - Haller, Toomas
A1  - Hamet, Pavel
A1  - Harris, Tamara B.
A1  - Hartman, Catharina A.
A1  - Hayward, Caroline
A1  - Hellwege, Jacklyn N.
A1  - Heng, Chew-Kiat
A1  - Hicks, Andrew A.
A1  - Hofer, Edith
A1  - Huang, Wei
A1  - Hutri-Kahonen, Nina
A1  - Hwang, Shih-Jen
A1  - Ikram, M. Arfan
A1  - Indridason, Olafur S.
A1  - Ingelsson, Erik
A1  - Ising, Marcus
A1  - Jaddoe, Vincent W. V.
A1  - Jakobsdottir, Johanna
A1  - Jonas, Jost B.
A1  - Joshi, Peter K.
A1  - Josyula, Navya Shilpa
A1  - Jung, Bettina
A1  - Kahonen, Mika
A1  - Kamatani, Yoichiro
A1  - Kammerer, Candace M.
A1  - Kanai, Masahiro
A1  - Kastarinen, Mika
A1  - Kerr, Shona M.
A1  - Khor, Chiea-Chuen
A1  - Kiess, Wieland
A1  - Kleber, Marcus E.
A1  - Koenig, Wolfgang
A1  - Kooner, Jaspal S.
A1  - Korner, Antje
A1  - Kovacs, Peter
A1  - Kraja, Aldi T.
A1  - Krajcoviechova, Alena
A1  - Kramer, Holly
A1  - Kramer, Bernhard K.
A1  - Kronenberg, Florian
A1  - Kubo, Michiaki
A1  - Kuhnel, Brigitte
A1  - Kuokkanen, Mikko
A1  - Kuusisto, Johanna
A1  - La Bianca, Martina
A1  - Laakso, Markku
A1  - Lange, Leslie A.
A1  - Langefeld, Carl D.
A1  - Lee, Jeannette Jen-Mai
A1  - Lehne, Benjamin
A1  - Lehtimaki, Terho
A1  - Lieb, Wolfgang
A1  - Lim, Su-Chi
A1  - Lind, Lars
A1  - Lindgren, Cecilia M.
A1  - Liu, Jun
A1  - Liu, Jianjun
A1  - Loeffler, Markus
A1  - Loos, Ruth J. F.
A1  - Lucae, Susanne
A1  - Lukas, Mary Ann
A1  - Lyytikainen, Leo-Pekka
A1  - Magi, Reedik
A1  - Magnusson, Patrik K. E.
A1  - Mahajan, Anubha
A1  - Martin, Nicholas G.
A1  - Martins, Jade
A1  - Marz, Winfried
A1  - Mascalzoni, Deborah
A1  - Matsuda, Koichi
A1  - Meisinger, Christa
A1  - Meitinger, Thomas
A1  - Melander, Olle
A1  - Metspalu, Andres
A1  - Mikaelsdottir, Evgenia K.
A1  - Milaneschi, Yuri
A1  - Miliku, Kozeta
A1  - Mishra, Pashupati P.
A1  - Program, V. A. Million Veteran
A1  - Mohlke, Karen L.
A1  - Mononen, Nina
A1  - Montgomery, Grant W.
A1  - Mook-Kanamori, Dennis O.
A1  - Mychaleckyj, Josyf C.
A1  - Nadkarni, Girish N.
A1  - Nalls, Mike A.
A1  - Nauck, Matthias
A1  - Nikus, Kjell
A1  - Ning, Boting
A1  - Nolte, Ilja M.
A1  - Noordam, Raymond
A1  - Olafsson, Isleifur
A1  - Oldehinkel, Albertine J.
A1  - Orho-Melander, Marju
A1  - Ouwehand, Willem H.
A1  - Padmanabhan, Sandosh
A1  - Palmer, Nicholette D.
A1  - Palsson, Runolfur
A1  - Penninx, Brenda W. J. H.
A1  - Perls, Thomas
A1  - Perola, Markus
A1  - Pirastu, Mario
A1  - Pirastu, Nicola
A1  - Pistis, Giorgio
A1  - Podgornaia, Anna I.
A1  - Polasek, Ozren
A1  - Ponte, Belen
A1  - Porteous, David J.
A1  - Poulain, Tanja
A1  - Pramstaller, Peter P.
A1  - Preuss, Michael H.
A1  - Prins, Bram P.
A1  - Province, Michael A.
A1  - Rabelink, Ton J.
A1  - Raffield, Laura M.
A1  - Raitakari, Olli T.
A1  - Reilly, Dermot F.
A1  - Rettig, Rainer
A1  - Rheinberger, Myriam
A1  - Rice, Kenneth M.
A1  - Ridker, Paul M.
A1  - Rivadeneira, Fernando
A1  - Rizzi, Federica
A1  - Roberts, David J.
A1  - Robino, Antonietta
A1  - Rossing, Peter
A1  - Rudan, Igor
A1  - Rueedi, Rico
A1  - Ruggiero, Daniela
A1  - Ryan, Kathleen A.
A1  - Saba, Yasaman
A1  - Sabanayagam, Charumathi
A1  - Salomaa, Veikko
A1  - Salvi, Erika
A1  - Saum, Kai-Uwe
A1  - Schmidt, Helena
A1  - Schmidt, Reinhold
A1  - Ben Schottker, 
A1  - Schulz, Christina-Alexandra
A1  - Schupf, Nicole
A1  - Shaffer, Christian M.
A1  - Shi, Yuan
A1  - Smith, Albert V.
A1  - Smith, Blair H.
A1  - Soranzo, Nicole
A1  - Spracklen, Cassandra N.
A1  - Strauch, Konstantin
A1  - Stringham, Heather M.
A1  - Stumvoll, Michael
A1  - Svensson, Per O.
A1  - Szymczak, Silke
A1  - Tai, E-Shyong
A1  - Tajuddin, Salman M.
A1  - Tan, Nicholas Y. Q.
A1  - Taylor, Kent D.
A1  - Teren, Andrej
A1  - Tham, Yih-Chung
A1  - Thiery, Joachim
A1  - Thio, Chris H. L.
A1  - Thomsen, Hauke
A1  - Thorleifsson, Gudmar
A1  - Toniolo, Daniela
A1  - Tonjes, Anke
A1  - Tremblay, Johanne
A1  - Tzoulaki, Ioanna
A1  - Uitterlinden, Andre G.
A1  - Vaccargiu, Simona
A1  - Van Dam, Rob M.
A1  - Van der Harst, Pim
A1  - Van Duijn, Cornelia M.
A1  - Edward, Digna R. Velez
A1  - Verweij, Niek
A1  - Vogelezang, Suzanne
A1  - Volker, Uwe
A1  - Vollenweider, Peter
A1  - Waeber, Gerard
A1  - Waldenberger, Melanie
A1  - Wallentin, Lars
A1  - Wang, Ya Xing
A1  - Wang, Chaolong
A1  - Waterworth, Dawn M.
A1  - Bin Wei, Wen
A1  - White, Harvey
A1  - Whitfield, John B.
A1  - Wild, Sarah H.
A1  - Wilson, James F.
A1  - Wojczynski, Mary K.
A1  - Wong, Charlene
A1  - Wong, Tien-Yin
A1  - Xu, Liang
A1  - Yang, Qiong
A1  - Yasuda, Masayuki
A1  - Yerges-Armstrong, Laura M.
A1  - Zhang, Weihua
A1  - Zonderman, Alan B.
A1  - Rotter, Jerome I.
A1  - Bochud, Murielle
A1  - Psaty, Bruce M.
A1  - Vitart, Veronique
A1  - Wilson, James G.
A1  - Dehghan, Abbas
A1  - Parsa, Afshin
A1  - Chasman, Daniel I.
A1  - Ho, Kevin
A1  - Morris, Andrew P.
A1  - Devuyst, Olivier
A1  - Akilesh, Shreeram
A1  - Pendergrass, Sarah A.
A1  - Sim, Xueling
A1  - Boger, Carsten A.
A1  - Okada, Yukinori
A1  - Edwards, Todd L.
A1  - Snieder, Harold
A1  - Stefansson, Kari
A1  - Hung, Adriana M.
A1  - Heid, Iris M.
A1  - Scholz, Markus
A1  - Teumer, Alexander
A1  - Kottgen, Anna
A1  - Pattaro, Cristian
T1  - A catalog of genetic loci associated with kidney function from analyses of a million individuals
JF  - Nature genetics
N2  - Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through transancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these,147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.
Y1  - 2019
U6  - https://doi.org/10.1038/s41588-019-0407-x
SN  - 1061-4036
SN  - 1546-1718
VL  - 51
IS  - 6
SP  - 957
EP  - +
PB  - Nature Publ. Group
CY  - New York
ER  - 
TY  - JOUR
A1  - Prokhorov, Boris E.
A1  - Foerster, M.
A1  - He, M.
A1  - Namgaladze, Alexander A.
A1  - Holschneider, Matthias
T1  - Using MFACE as input in the UAM to specify the MIT dynamics
JF  - Journal of geophysical research : Space physics
N2  - The magnetosphere-ionosphere-thermosphere (MIT) dynamic system significantly depends on the highly variable solar wind conditions, in particular, on changes of the strength and orientation of the interplanetary magnetic field (IMF). The solar wind and IMF interactions with the magnetosphere drive the MIT system via the magnetospheric field-aligned currents (FACs). The global modeling helps us to understand the physical background of this complex system. With the present study, we test the recently developed high-resolution empirical model of field-aligned currents MFACE (a high-resolution Model of Field-Aligned Currents through Empirical orthogonal functions analysis). These FAC distributions were used as input of the time-dependent, fully self-consistent global Upper Atmosphere Model (UAM) for different seasons and various solar wind and IMF conditions. The modeling results for neutral mass density and thermospheric wind are directly compared with the CHAMP satellite measurements. In addition, we perform comparisons with the global empirical models: the thermospheric wind model (HWM07) and the atmosphere density model (Naval Research Laboratory Mass Spectrometer and Incoherent Scatter Extended 2000). The theoretical model shows a good agreement with the satellite observations and an improved behavior compared with the empirical models at high latitudes. Using the MFACE model as input parameter of the UAM model, we obtain a realistic distribution of the upper atmosphere parameters for the Northern and Southern Hemispheres during stable IMF orientation as well as during dynamic situations. This variant of the UAM can therefore be used for modeling the MIT system and space weather predictions.
Y1  - 2014
U6  - https://doi.org/10.1002/2014JA019981
SN  - 2169-9380
SN  - 2169-9402
VL  - 119
IS  - 8
PB  - American Geophysical Union
CY  - Washington
ER  - 
TY  - JOUR
A1  - He, Zhihua
A1  - Unger-Shayesteh, Katy
A1  - Vorogushyn, Sergiy
A1  - Weise, Stephan M.
A1  - Kalashnikova, Olga
A1  - Gafurov, Abror
A1  - Duethmann, Doris
A1  - Barandun, Martina
A1  - Merz, Bruno
T1  - Constraining hydrological model parameters using water isotopic compositions in a glacierized basin, Central Asia
JF  - Journal of hydrology
N2  - Water stable isotope signatures can provide valuable insights into the catchment internal runoff processes. However, the ability of the water isotope data to constrain the internal apportionments of runoff components in hydrological models for glacierized basins is not well understood. This study developed an approach to simultaneously model the water stable isotopic compositions and runoff processes in a glacierized basin in Central Asia. The fractionation and mixing processes of water stable isotopes in and from the various water sources were integrated into a glacio-hydrological model. The model parameters were calibrated on discharge, snow cover and glacier mass balance data, and additionally isotopic composition of streamflow. We investigated the value of water isotopic compositions for the calibration of model parameters, in comparison to calibration methods without using such measurements. Results indicate that: (1) The proposed isotope-hydrological integrated modeling approach was able to reproduce the isotopic composition of streamflow, and improved the model performance in the evaluation period; (2) Involving water isotopic composition for model calibration reduced the model parameter uncertainty, and helped to reduce the uncertainty in the quantification of runoff components; (3) The isotope-hydrological integrated modeling approach quantified the contributions of runoff components comparably to a three-component tracer-based end-member mixing analysis method for summer peak flows, and required less water tracer data. Our findings demonstrate the value of water isotopic compositions to improve the quantification of runoff components using hydrological models in glacierized basins.
KW  - Water stable isotope
KW  - Isotope-hydrological integrated modeling
KW  - Quantification of runoff components
KW  - Glacierized basins
Y1  - 2019
U6  - https://doi.org/10.1016/j.jhydrol.2019.01.048
SN  - 0022-1694
SN  - 1879-2707
VL  - 571
SP  - 332
EP  - 348
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Wang, Enli
A1  - He, Di
A1  - Wang, Jing
A1  - Lilley, Julianne M.
A1  - Christy, Brendan
A1  - Hoffmann, Munir P.
A1  - O'Leary, Garry
A1  - Hatfield, Jerry L.
A1  - Ledda, Luigi
A1  - Deligios, Paola A.
A1  - Grant, Brian
A1  - Jing, Qi
A1  - Nendel, Claas
A1  - Kage, Henning
A1  - Qian, Budong
A1  - Rezaei, Ehsan Eyshi
A1  - Smith, Ward
A1  - Weymann, Wiebke
A1  - Ewert, Frank
T1  - How reliable are current crop models for simulating growth and seed yield of canola across global sites and under future climate change?
JF  - Climatic change
N2  - To better understand how climate change might influence global canola production, scientists from six countries have completed the first inter-comparison of eight crop models for simulating growth and seed yield of canola, based on experimental data from six sites across five countries. A sensitivity analysis was conducted with a combination of five levels of atmospheric CO2 concentrations, seven temperature changes, five precipitation changes, together with five nitrogen application rates. Our results were in several aspects different from those of previous model inter-comparison studies for wheat, maize, rice, and potato crops. A partial model calibration only on phenology led to very poor simulation of aboveground biomass and seed yield of canola, even from the ensemble median or mean. A full calibration with additional data of leaf area index, biomass, and yield from one treatment at each site reduced simulation error of seed yield from 43.8 to 18.0%, but the uncertainty in simulation results remained large. Such calibration (with data from one treatment) was not able to constrain model parameters to reduce simulation uncertainty across the wide range of environments. Using a multi-model ensemble mean or median reduced the uncertainty of yield simulations, but the simulation error remained much larger than observation errors, indicating no guarantee that the ensemble mean/median would predict the correct responses. Using multi-model ensemble median, canola yield was projected to decline with rising temperature (2.5-5.7% per degrees C), but to increase with increasing CO2 concentration (4.6-8.3% per 100-ppm), rainfall (2.1-6.1% per 10% increase), and nitrogen rates (1.3-6.0% per 10% increase) depending on locations. Due to the large uncertainty, these results need to be treated with caution. We further discuss the need to collect new data to improve modelling of several key physiological processes of canola for increased confidence in future climate impact assessments.
KW  - AgMIP
KW  - Brassica napus L.
KW  - Model calibration
KW  - Model improvement;
KW  - Multimodel ensemble
KW  - Sensitivity analysis
Y1  - 2022
U6  - https://doi.org/10.1007/s10584-022-03375-2
SN  - 0165-0009
SN  - 1573-1480
VL  - 172
IS  - 1-2
PB  - Springer Nature
CY  - Dordrecht
ER  - 
TY  - JOUR
A1  - Frieler, Katja
A1  - Clark, Peter U.
A1  - He, Feng
A1  - Buizert, Christo
A1  - Reese, Ronja
A1  - Ligtenberg, Stefan R. M.
A1  - van den Broeke, Michiel R.
A1  - Winkelmann, Ricarda
A1  - Levermann, Anders
T1  - Consistent evidence of increasing Antarctic accumulation with warming
JF  - Nature climate change
N2  - Projections of changes in Antarctic Ice Sheet (AIS) surface mass balance indicate a negative contribution to sea level because of the expected increase in precipitation due to the higher moisture holding capacity of warmer air(1). Observations over the past decades, however, are unable to constrain the relation between temperature and accumulation changes because both are dominated by strong natural variability(2-5). Here we derive a consistent continental-scale increase in accumulation of approximately 5 +/- 1% K-1, through the assessment of ice-core data (spanning the large temperature change during the last deglaciation, 21,000 to 10,000 years ago), in combination with palaeo-simulations, future projections by 35 general circulation models (GCMs), and one high-resolution future simulation. The ice-core data and modelling results for the last deglaciation agree, showing uniform local sensitivities of similar to 6% K-1. The palaeo-simulation allows for a continental-scale aggregation of accumulation changes reaching 4.3% K-1. Despite the different timescales, these sensitivities agree with the multi-model mean of 6.1 +/- 2.6% K-1 (GCMprojections) and the continental-scale sensitivity of 4.9% K-1 (high-resolution future simulation). Because some of the mass gain of the AIS is offset by dynamical losses induced by accumulation(6,7), we provide a response function allowing projections of sea-level fall in terms of continental-scale accumulation changes that compete with surface melting and dynamical losses induced by other mechanisms(6,8,9).
Y1  - 2015
U6  - https://doi.org/10.1038/nclimate2574
SN  - 1758-678X
SN  - 1758-6798
VL  - 5
IS  - 4
SP  - 348
EP  - 352
PB  - Nature Publ. Group
CY  - London
ER  -