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Haobo Tan
,
Jietai Mao
,
Huanhuan Chen
,
P. W. Chan
,
Dui Wu
,
Fei Li
, and
Tao Deng

Abstract

This paper discusses the application of principal component analysis and stepwise regression in the retrieval of vertical profiles of temperature and humidity based on the measurements of a 35-channel microwave radiometer. It uses the radiosonde data of 6 yr from Hong Kong, China, and the monochromatic radiative transfer model (MonoRTM) to calculate the brightness temperatures of the 35 channels of the radiometer. The retrieval of the atmospheric profile is then established based on principal component analysis and stepwise regression. The accuracy of the retrieval method is also analyzed. Using an independent sample, the root-mean-square error of the retrieved temperature is less than 1.5 K, on average, with better retrieval results in summer than in winter. Likewise, the root-mean-square error of the retrieved water vapor density reaches a maximum value of 1.4 g m−3 between 0.5 and 2 km, and is less than 1 g m−3 for all other heights. The retrieval method is then applied to the actual measured brightness temperatures by the 35-channel microwave radiometer at a station in Nansha, China. It is shown that the statistical model as developed in this paper has better retrieval results than the profiles obtained from the neural network as supplied with the radiometer. From numerical analysis, the error with the water vapor density retrieval is found to arise from the treatment of cloud liquid water. Finally, the retrieved profiles from the radiometer are studied for two typical weather phenomena during the observation period, and the retrieved profiles using the method discussed in the present paper is found to capture the evolution of the atmospheric condition very well.

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Iam-Fei Pun
,
I.-I. Lin
,
Chun-Chi Lien
, and
Chun-Chieh Wu

Abstract

Supertyphoon Megi (2010) left behind two very contrasting SST cold-wake cooling patterns between the Philippine Sea (1.5°C) and the South China Sea (7°C). Based on various radii of radial winds, the authors found that the size of Megi doubles over the South China Sea when it curves northward. On average, the radius of maximum wind (RMW) increased from 18.8 km over the Philippine Sea to 43.1 km over the South China Sea; the radius of 64-kt (33 m s−1) typhoon-force wind (R64) increased from 52.6 to 119.7 km; the radius of 50-kt (25.7 m s−1) damaging-force wind (R50) increased from 91.8 to 210 km; and the radius of 34-kt (17.5 m s−1) gale-force wind (R34) increased from 162.3 to 358.5 km. To investigate the typhoon size effect, the authors conduct a series of numerical experiments on Megi-induced SST cooling by keeping other factors unchanged, that is, typhoon translation speed and ocean subsurface thermal structure. The results show that if it were not for Megi’s size increase over the South China Sea, the during-Megi SST cooling magnitude would have been 52% less (reduced from 4° to 1.9°C), the right bias in cooling would have been 60% (or 30 km) less, and the width of the cooling would have been 61% (or 52 km) less, suggesting that typhoon size is as important as other well-known factors on SST cooling. Aside from the size effect, the authors also conduct a straight-track experiment and find that the curvature of Megi contributes up to 30% (or 1.2°C) of cooling over the South China Sea.

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I-I. Lin
,
Chun-Chieh Wu
,
Kerry A. Emanuel
,
I-Huan Lee
,
Chau-Ron Wu
, and
Iam-Fei Pun

Abstract

Understanding the interaction of ocean eddies with tropical cyclones is critical for improving the understanding and prediction of the tropical cyclone intensity change. Here an investigation is presented of the interaction between Supertyphoon Maemi, the most intense tropical cyclone in 2003, and a warm ocean eddy in the western North Pacific. In September 2003, Maemi passed directly over a prominent (700 km × 500 km) warm ocean eddy when passing over the 22°N eddy-rich zone in the northwest Pacific Ocean. Analyses of satellite altimetry and the best-track data from the Joint Typhoon Warning Center show that during the 36 h of the Maemi–eddy encounter, Maemi’s intensity (in 1-min sustained wind) shot up from 41 m s−1 to its peak of 77 m s−1. Maemi subsequently devastated the southern Korean peninsula. Based on results from the Coupled Hurricane Intensity Prediction System and satellite microwave sea surface temperature observations, it is suggested that the warm eddies act as an effective insulator between typhoons and the deeper ocean cold water. The typhoon’s self-induced sea surface temperature cooling is suppressed owing to the presence of the thicker upper-ocean mixed layer in the warm eddy, which prevents the deeper cold water from being entrained into the upper-ocean mixed layer. As simulated using the Coupled Hurricane Intensity Prediction System, the incorporation of the eddy information yields an evident improvement on Maemi’s intensity evolution, with its peak intensity increased by one category and maintained at category-5 strength for a longer period (36 h) of time. Without the presence of the warm ocean eddy, the intensification is less rapid. This study can serve as a starting point in the largely speculative and unexplored field of typhoon–warm ocean eddy interaction in the western North Pacific. Given the abundance of ocean eddies and intense typhoons in the western North Pacific, these results highlight the importance of a systematic and in-depth investigation of the interaction between typhoons and western North Pacific eddies.

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Neil J. Holbrook
,
Jianping Li
,
Matthew Collins
,
Emanuele Di Lorenzo
,
Fei-Fei Jin
,
Thomas Knutson
,
Mojib Latif
,
Chongyin Li
,
Scott B. Power
,
Rhonghui Huang
, and
Guoxiong Wu
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Xi Liang
,
Qinghua Yang
,
Lars Nerger
,
Svetlana N. Losa
,
Biao Zhao
,
Fei Zheng
,
Lin Zhang
, and
Lixin Wu

Abstract

Sea surface temperature (SST) data from the Copernicus Marine Environment Monitoring Service are assimilated into a pan-Arctic ice–ocean coupled model using the ensemble-based local singular evolutive interpolated Kalman (LSEIK) filter. This study found that the SST deviation between model hindcasts and independent SST observations is reduced by the assimilation. Compared with model results without data assimilation, the deviation between the model hindcasts and independent SST observations has decreased by up to 0.2°C at the end of summer. The strongest SST improvements are located in the Greenland Sea, the Beaufort Sea, and the Canadian Arctic Archipelago. The SST assimilation also changes the sea ice concentration (SIC). Improvements of the ice concentrations are found in the Canadian Arctic Archipelago, the Beaufort Sea, and the central Arctic basin, while negative effects occur in the west area of the eastern Siberian Sea and the Laptev Sea. Also, sea ice thickness (SIT) benefits from ensemble SST assimilation. A comparison with upward-looking sonar observations reveals that hindcasts of SIT are improved in the Beaufort Sea by assimilating reliable SST observations into light ice areas. This study illustrates the advantages of assimilating SST observations into an ice–ocean coupled model system and suggests that SST assimilation can improve SIT hindcasts regionally during the melting season.

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Lei Wang
,
Zhi-Jun Yao
,
Li-Guang Jiang
,
Rui Wang
,
Shan-Shan Wu
, and
Zhao-Fei Liu

Abstract

The spatiotemporal changes in 21 indices of extreme temperature and precipitation for the Mongolian Plateau from 1951 to 2012 were investigated on the basis of daily temperature and precipitation data from 70 meteorological stations. Changes in catastrophic events, such as droughts, floods, and snowstorms, were also investigated for the same period. The correlations between catastrophic events and the extreme indices were examined. The results show that the Mongolian Plateau experienced an asymmetric warming trend. Both the cold extremes and warm extremes showed greater warming at night than in the daytime. The spatial changes in significant trends showed a good homogeneity and consistency in Inner Mongolia. Changes in the precipitation extremes were not as obvious as those in the temperature extremes. The spatial distributions in changes of precipitation extremes were complex. A decreasing trend was shown for total precipitation from west to east as based on the spatial distribution of decadal trends. Drought was the most serious extreme disaster, and prolonged drought for longer than 3 yr occurred about every 7–11 yr. An increasing trend in the disaster area was apparent for flood events from 1951 to 2012. A decreasing trend was observed for the maximum depth of snowfall from 1951 to 2012, with a decreased average maximum depth of 10 mm from the 1990s.

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William Randel
,
Petra Udelhofen
,
Eric Fleming
,
Marvin Geller
,
Mel Gelman
,
Kevin Hamilton
,
David Karoly
,
Dave Ortland
,
Steve Pawson
,
Richard Swinbank
,
Fei Wu
,
Mark Baldwin
,
Marie-Lise Chanin
,
Philippe Keckhut
,
Karin Labitzke
,
Ellis Remsberg
,
Adrian Simmons
, and
Dong Wu

Abstract

An updated assessment of uncertainties in “observed” climatological winds and temperatures in the middle atmosphere (over altitudes ∼10–80 km) is provided by detailed intercomparisons of contemporary and historic datasets. These datasets include global meteorological analyses and assimilations, climatologies derived from research satellite measurements, historical reference atmosphere circulation statistics, rocketsonde wind and temperature data, and lidar temperature measurements. The comparisons focus on a few basic circulation statistics (temperatures and zonal winds), with special attention given to tropical variability. Notable differences are found between analyses for temperatures near the tropical tropopause and polar lower stratosphere, temperatures near the global stratopause, and zonal winds throughout the Tropics. Comparisons of historical reference atmosphere and rocketsonde temperatures with more recent global analyses show the influence of decadal-scale cooling of the stratosphere and mesosphere. Detailed comparisons of the tropical semiannual oscillation (SAO) and quasi- biennial oscillation (QBO) show large differences in amplitude between analyses; recent data assimilation schemes show the best agreement with equatorial radiosonde, rocket, and satellite data.

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