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Satoru Yokoi, Yukari N. Takayabu, Kazuaki Nishii, Hisashi Nakamura, Hirokazu Endo, Hiroki Ichikawa, Tomoshige Inoue, Masahide Kimoto, Yu Kosaka, Takafumi Miyasaka, Kazuhiro Oshima, Naoki Sato, Yoko Tsushima, and Masahiro Watanabe

Abstract

The overall performance of general circulation models is often investigated on the basis of the synthesis of a number of scalar performance metrics of individual models that measure the reproducibility of diverse aspects of the climate. Because of physical and dynamic constraints governing the climate, a model’s performance in simulating a certain aspect of the climate is sometimes related closely to that in simulating another aspect, which results in significant intermodel correlation between performance metrics. Numerous metrics and intermodel correlations may cause a problem in understanding the evaluation and synthesizing the metrics. One possible way to alleviate this problem is to group the correlated metrics beforehand. This study attempts to use simple cluster analysis to group 43 performance metrics. Two clustering methods, the K-means and the Ward methods, yield considerably similar clustering results, and several aspects of the results are found to be physically and dynamically reasonable. Furthermore, the intermodel correlation between the cluster averages is considerably lower than that between the metrics. These results suggest that the cluster analysis is helpful in obtaining the appropriate grouping. Applications of the clustering results are also discussed.

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Kunio Yoneyama, Yukio Masumoto, Yoshifumi Kuroda, Masaki Katsumata, Keisuke Mizuno, Yukari N. Takayabu, Masanori Yoshizaki, Ali Shareef, Yasushi Fujiyoshi, Michael J. McPhaden, V. S. N. Murty, Ryuichi Shirooka, Kazuaki Yasunaga, Hiroyuki Yamada, Naoki Sato, Tomoki Ushiyama, Qoosaku Moteki, Ayako Seiki, Mikiko Fujita, Kentaro Ando, Hideaki Hase, Iwao Ueki, Takanori Horii, Chie Yokoyama, and Tomoki Miyakawa

The Mirai Indian Ocean cruise for the Study of the Madden-Julian oscillation (MJO)-convection Onset (MISMO) was a field experiment that took place in the central equatorial Indian Ocean during October–December 2006, using the research vessel Mirai, a moored buoy array, and landbased sites at the Maldive Islands. The aim of MISMO was to capture atmospheric and oceanic features in the equatorial Indian Ocean when convection in the MJO was initiated. This article describes details of the experiment as well as some selected early results.

Intensive observations using Doppler radar, radiosonde, surface meteorological measurements, and other instruments were conducted at 0°, 80.5°E, after deploying an array of surface and subsurface moorings around this site. The Mirai stayed within this buoy array area from 24 October through 25 November. After a period of stationary observations, underway meteorological measurements were continued from the Maldives to the eastern Indian Ocean in early December.

All observations were collected during an El Nino and a positive Indian Ocean Dipole (IOD) event, which tended to suppress convection in the western Pacific and eastern Indian Ocean in throughout much of November 2006. However, as the IOD began to wane in mid-November, an abrupt change from westerly to easterly took place in upper tropospheric winds in the MISMO study region. By late November and early December, deep convection developed over the central Indian Ocean and eastward movement of large-scale cloud systems were observed. This article describes these variations in detail and how they advance our understanding of the onset of tropical deep convection on intraseasonal time scales.

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Gail Skofronick-Jackson, Walter A. Petersen, Wesley Berg, Chris Kidd, Erich F. Stocker, Dalia B. Kirschbaum, Ramesh Kakar, Scott A. Braun, George J. Huffman, Toshio Iguchi, Pierre E. Kirstetter, Christian Kummerow, Robert Meneghini, Riko Oki, William S. Olson, Yukari N. Takayabu, Kinji Furukawa, and Thomas Wilheit

Abstract

Precipitation is a key source of freshwater; therefore, observing global patterns of precipitation and its intensity is important for science, society, and understanding our planet in a changing climate. In 2014, the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA) launched the Global Precipitation Measurement (GPM) Core Observatory (CO) spacecraft. The GPM CO carries the most advanced precipitation sensors currently in space including a dual-frequency precipitation radar provided by JAXA for measuring the three-dimensional structures of precipitation and a well-calibrated, multifrequency passive microwave radiometer that provides wide-swath precipitation data. The GPM CO was designed to measure rain rates from 0.2 to 110.0 mm h−1 and to detect moderate to intense snow events. The GPM CO serves as a reference for unifying the data from a constellation of partner satellites to provide next-generation, merged precipitation estimates globally and with high spatial and temporal resolutions. Through improved measurements of rain and snow, precipitation data from GPM provides new information such as details on precipitation structure and intensity; observations of hurricanes and typhoons as they transition from the tropics to the midlatitudes; data to advance near-real-time hazard assessment for floods, landslides, and droughts; inputs to improve weather and climate models; and insights into agricultural productivity, famine, and public health. Since launch, GPM teams have calibrated satellite instruments, refined precipitation retrieval algorithms, expanded science investigations, and processed and disseminated precipitation data for a range of applications. The current status of GPM, its ongoing science, and its future plans are presented.

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