JOYCE Julich Observatory for Cloud Evolution

被引:80
作者
Loehnert, U. [1 ]
Schween, J. H. [1 ]
Acquistapace, C. [1 ]
Ebell, K. [1 ]
Maahn, M. [1 ]
Barrera-Verdejo, M. [1 ]
Hirsikko, A. [2 ]
Bohn, B. [2 ]
Knaps, A. [3 ]
O'Connor, E. [4 ,5 ]
Simmer, C. [6 ]
Wahner, A. [2 ]
Crewell, S. [1 ]
机构
[1] Univ Cologne, Inst Geophys & Meteorol, D-50969 Cologne, Germany
[2] Forschungszentrum Julich, Inst Energie & Klimaforsch Troposphare IEK 8, D-52425 Julich, Germany
[3] Forschungszentrum Julich, Geshaftsbereich Sicherheit & Strahlenschutz S UM, D-52425 Julich, Germany
[4] Univ Reading, Dept Meteorol, Reading, Berks, England
[5] Finnish Meteorol Inst, FIN-00101 Helsinki, Finland
[6] Univ Bonn, Inst Meteorol, Bonn, Germany
关键词
EMITTED RADIANCE INTERFEROMETER; LIQUID WATER PATH; MICROWAVE RADIOMETRY; BOUNDARY-LAYER; PART II; RETRIEVAL; AEROSOL; TEMPERATURE; MODELS; RADAR;
D O I
10.1175/BAMS-D-14-00105.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The Julich Observatory for Cloud Evolution (JOYCE), located at Forschungszentrum Julich in the most western part of Germany, is a recently established platform for cloud research. The main objective of JOYCE is to provide observations, which improve our understanding of the cloudy boundary layer in a midlatitude environment. Continuous and temporally highly resolved measurements that are specifically suited to characterize the diurnal cycle of water vapor, stability, and turbulence in the lower troposphere are performed with a special focus on atmosphere-surface interaction. In addition, instruments are set up to measure the micro- and macrophysical properties of clouds in detail and how they interact with different boundary layer processes and the large-scale synoptic situation. For this, JOYCE is equipped with an array of state-of-the-art active and passive remote sensing and in situ instruments, which are briefly described in this scientific overview. As an example, a 24-h time series of the evolution of a typical cumulus cloud-topped boundary layer is analyzed with respect to stability, turbulence, and cloud properties. Additionally, we present longer-term statistics, which can be used to elucidate the diurnal cycle of water vapor, drizzle formation through autoconversion, and warm versus cold rain precipitation formation. Both case studies and long-term observations are important for improving the representation of clouds in climate and numerical weather prediction models.
引用
收藏
页码:1157 / 1174
页数:18
相关论文
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