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2015 Vol. 32, No. 3

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Data Selection Using Support Vector Regression
Michael B. RICHMAN, Lance M. LESLIE, Theodore B. TRAFALIS, Hicham MANSOURI
2015, 32(3): 277-286. doi: 10.1007/s00376-014-4072-9
Geophysical data sets are growing at an ever-increasing rate, requiring computationally efficient data selection (thinning) methods to preserve essential information. Satellites, such as WindSat, provide large data sets for assessing the accuracy and computational efficiency of data selection techniques. A new data thinning technique, based on support vector regression (SVR), is developed and tested. To manage large on-line satellite data streams, observations from WindSat are formed into subsets by Voronoi tessellation and then each is thinned by SVR (TSVR). Three experiments are performed. The first confirms the viability of TSVR for a relatively small sample, comparing it to several commonly used data thinning methods (random selection, averaging and Barnes filtering), producing a 10% thinning rate (90% data reduction), low mean absolute errors (MAE) and large correlations with the original data. A second experiment, using a larger dataset, shows TSVR retrievals with MAE <1 m s-1 and correlations ≥0.98. TSVR was an order of magnitude faster than the commonly used thinning methods. A third experiment applies a two-stage pipeline to TSVR, to accommodate online data. The pipeline subsets reconstruct the wind field with the same accuracy as the second experiment, is an order of magnitude faster than the non-pipeline TSVR. Therefore, pipeline TSVR is two orders of magnitude faster than commonly used thinning methods that ingest the entire data set. This study demonstrates that TSVR pipeline thinning is an accurate and computationally efficient alternative to commonly used data selection techniques.
Assessment of the Biospheric Contribution to Surface Atmospheric CO2 Concentrations over East Asia with a Regional Chemical Transport Model
KOU Xingxia, ZHANG Meigen, PENG Zhen, WANG Yinghong
2015, 32(3): 287-300. doi: 10.1007/s00376-014-4059-6
A regional chemical transport model, RAMS-CMAQ, was employed to assess the impacts of biosphere-atmosphere CO2 exchange on seasonal variations in atmospheric CO2 concentrations over East Asia. Simulated CO2 concentrations were compared with observations at 12 surface stations and the comparison showed they were generally in good agreement. Both observations and simulations suggested that surface CO2 over East Asia features a summertime trough due to biospheric absorption, while in some urban areas surface CO2 has a distinct summer peak, which could be attributed to the strong impact from anthropogenic emissions. Analysis of the model results indicated that biospheric fluxes and fossil-fuel emissions are comparably important in shaping spatial distributions of CO2 near the surface over East Asia. Biospheric flux plays an important role in the prevailing spatial pattern of CO2 enhancement and reduction on the synoptic scale due to the strong seasonality of biospheric CO2 flux. The elevation of CO2 levels by the biosphere during winter was found to be larger than 5 ppm in North China and Southeast China, and during summertime a significant depletion (≥7 ppm) occurred in most areas, except for the Indo-China Peninsula where positive bioflux values were found.
A Hybrid Coupled Model for the Pacific Ocean-Atmosphere System. Part I: Description and Basic Performance
ZHANG Rong-Hua
2015, 32(3): 301-318. doi: 10.1007/s00376-014-3266-5
A hybrid coupled model (HCM) is constructed for El Niño-Southern Oscillation (ENSO)-related modeling studies over almost the entire Pacific basin. An ocean general circulation model is coupled to a statistical atmospheric model for interannual wind stress anomalies to represent their dominant coupling with sea surface temperatures. In addition, various relevant forcing and feedback processes exist in the region and can affect ENSO in a significant way; their effects are simply represented using historical data and are incorporated into the HCM, including stochastic forcing of atmospheric winds, and feedbacks associated with freshwater flux, ocean biology-induced heating (OBH), and tropical instability waves (TIWs). In addition to its computational efficiency, the advantages of making use of such an HCM enable these related forcing and feedback processes to be represented individually or collectively, allowing their modulating effects on ENSO to be examined in a clean and clear way. In this paper, examples are given to illustrate the ability of the HCM to depict the mean ocean state, the circulation pathways connecting the subtropics and tropics in the western Pacific, and interannual variability associated with ENSO. As satellite data are taken to parameterize processes that are not explicitly represented in the HCM, this work also demonstrates an innovative method of using remotely sensed data for climate modeling. Further model applications related with ENSO modulations by extratropical influences and by various forcings and feedbacks will be presented in Part II of this study.
The Impact of AIRS Atmospheric Temperature and Moisture Profiles on Hurricane Forecasts: Ike (2008) and Irene (2011)
ZHENG Jing, Jun LI, Timothy J. SCHMIT, Jinlong LI, Zhiquan LIU
2015, 32(3): 319-335. doi: 10.1007/s00376-014-3162-z
Atmospheric InfraRed Sounder (AIRS) measurements are a valuable supplement to current observational data, especially over the oceans where conventional data are sparse. In this study, two types of AIRS-retrieved temperature and moisture profiles, the AIRS Science Team product (SciSup) and the single field-of-view (SFOV) research product, were evaluated with European Centre for Medium-Range Weather Forecasts (ECMWF) analysis data over the Atlantic Ocean during Hurricane Ike (2008) and Hurricane Irene (2011). The evaluation results showed that both types of AIRS profiles agreed well with the ECMWF analysis, especially between 200 hPa and 700 hPa. The average standard deviation of both temperature profiles was approximately 1 K under 200 hPa, where the mean AIRS temperature profile from the AIRS SciSup retrievals was slightly colder than that from the AIRS SFOV retrievals. The mean SciSup moisture profile was slightly drier than that from the SFOV in the mid troposphere. A series of data assimilation and forecast experiments was then conducted with the Advanced Research version of the Weather Research and Forecasting (WRF) model and its three-dimensional variational (3DVAR) data assimilation system for hurricanes Ike and Irene. The results showed an improvement in the hurricane track due to the assimilation of AIRS clear-sky temperature profiles in the hurricane environment. In terms of total precipitable water and rainfall forecasts, the hurricane moisture environment was found to be affected by the AIRS sounding assimilation. Meanwhile, improving hurricane intensity forecasts through assimilating AIRS profiles remains a challenge for further study.
Connections between the Eurasian Teleconnection and Concurrent Variation of Upper-level Jets over East Asia
WANG Ning, ZHANG Yaocun
2015, 32(3): 336-348. doi: 10.1007/s00376-014-4088-1
The variation of the East Asian jet stream (EAJS) associated with the Eurasian (EU) teleconnection pattern is investigated using 60-yr NCEP-NCAR daily reanalysis data over the period 1951-2010. The EAJS consists of three components: the polar front jet (PFJ); the plateau subtropical jet (PSJ); and the ocean subtropical jet (OSJ). Of these three jets over East Asia, the EU pattern exhibits a significant influence on the PFJ and OSJ. There is a simultaneous negative correlation between the EU pattern and the PFJ. A significant positive correlation is found between the EU pattern and the OSJ when the EU pattern leads the OSJ by about 5 days. There is no obvious correlation between the EU pattern and the PSJ. The positive EU phase is accompanied by a weakened and poleward-shifted PFJ, which coincides with an intensified OSJ. A possible mechanism for the variation of the EAJS during different EU phases is explored via analyzing the effects of 10-day high-and low-frequency eddy forcing. The zonal wind tendency due to high-frequency eddy forcing contributes to the simultaneous negative correlation between the EU pattern and the PFJ, as well as the northward/southward shift of the PFJ. High- and low-frequency eddy forcing are both responsible for the positive correlation between the EU pattern and the OSJ, but only high-frequency eddy forcing contributes to the lagged variation of the OSJ relative to the EU pattern. The negative correlation between the EU pattern and winter temperature and precipitation anomalies in China is maintained only when the PFJ and OSJ are out of phase with each other. Thus, the EAJS plays an important role in transmitting the EU signal to winter temperature and precipitation anomalies in China.
A Validation of the Multivariate and Minimum Residual Method for Cloud Retrieval Using Radiance from Multiple Satellites
XU Dongmei, Thomas AULIGNÈ, Xiang-Yu HUANG
2015, 32(3): 349-362. doi: 10.1007/s00376-014-3258-5
The Multivariate and Minimum Residual (MMR) cloud detection and retrieval algorithm, previously developed and tested on simulated observations and Advanced Infrared Sounder radiance, was explored and validated using various radiances from multiple sensors. For validation, the cloud retrievals were compared to independent cloud products from CloudSat, MODIS (Moderate Resolution Imaging Spectroradiometer), and GOES (Geostationary Operational Environmental Satellites). We found good spatial agreement within a single instrument, although the cloud fraction on each pixel was estimated independently. The retrieved cloud properties showed good agreement using radiances from multiple satellites, especially for the vertically integrated cloud mask. The accuracy of the MMR scheme in detecting mid-level clouds was found to be higher than for higher and lower clouds. The accuracy in retrieving cloud top pressures and cloud profiles increased with more channels from observations. For observations with fewer channels, the MMR solution was an "overly smoothed" estimation of the true vertical profile, starting from a uniform clear guess. Additionally, the retrieval algorithm showed some meaningful skill in simulating the cloudy radiance as a linear observation operator, discriminating between numerical weather prediction (NWP) error and cloud effects. The retrieval scheme was also found to be robust when different radiative transfer models were used. The potential application of the MMR algorithm in NWP with multiple radiances is also discussed.
Role of the 10-20-Day Oscillation in Sustained Rainstorms over Hainan, China in October 2010
QIAO Yunting, ZHANG Chunhua, JIAN Maoqiu
2015, 32(3): 363-374. doi: 10.1007/s00376-014-3200-x
Hainan, an island province of China in the northern South China Sea, experienced two sustained rainstorms in October 2010, which were the most severe autumn rainstorms of the past 60 years. From August to October 2010, the most dominant signal of Hainan rainfall was the 10-20-day oscillation. This paper examines the roles of the 10-20-day oscillation in the convective activity and atmospheric circulation during the rainstorms of October 2010 over Hainan. During both rainstorms, Hainan was near the center of convective activity and under the influence of a lower-troposphere cyclonic circulation. The convective center was initiated in the west-central tropical Indian Ocean several days prior to the rainstorm in Hainan. The convective center first propagated eastward to the maritime continent, accompanied by the cyclonic circulation, and then moved northward to the northern South China Sea and South China, causing the rainstorms over Hainan. In addition, the westward propagation of convection from the tropical western Pacific to the southern South China Sea, as well as the propagation farther northward, intensified the convective activity over the northern South China Sea and South China during the first rainstorm.
Retrieval of Outgoing Longwave Radiation from COMS Narrowband Infrared Imagery
Myung-Sook PARK, Chang-Hoi HO, Heeje CHO, Yong-Sang CHOI
2015, 32(3): 375-388. doi: 10.1007/s00376-014-4013-7
Hourly outgoing longwave radiation (OLR) from the geostationary satellite Communication Oceanography Meteorological Satellite (COMS) has been retrieved since June 2010. The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels. This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm (OLR12.0 using the 12.0 μm channel) and three multiple-channel algorithms (OLR10.8+12.0 using the 10.8 and 12.0 μm channels; OLR6.7+10.8 using the 6.7 and 10.8 μm channels; and OLR All using the 6.7, 10.8, and 12.0 μm channels). The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth's Radiant Energy System (CERES) over the full COMS field of view [roughly (50°S-50°N, 70°-170°E)] during April 2011. Validation results show that the root-mean-square errors of COMS OLRs are 5-7 W m-2, which indicates good agreement with CERES OLR over the vast domain. OLR6.7+10.8 and OLR All have much smaller errors (∼6 W m-2) than OLR12.0 and OLR10.8+12.0 (∼8 W m-2). Moreover, the small errors of OLR6.7+10.8 and OLR All are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration. These results indicate a noteworthy role of the 6.7 μm water vapor absorption channel in improving the accuracy of the OLRs. The dependence of the accuracy of COMS OLRs on various surface, atmospheric, and observational conditions is also discussed.
Dominant Cloud Microphysical Processes of a Torrential Rainfall Event in Sichuan, China
HUANG Yongjie, CUI Xiaopeng
2015, 32(3): 389-400. doi: 10.1007/s00376-014-4066-7
High-resolution numerical simulation data of a rainstorm triggering debris flow in Sichuan Province of China simulated by the Weather Research and Forecasting (WRF) Model were used to study the dominant cloud microphysical processes of the torrential rainfall. The results showed that: (2) In the strong precipitation period, particle sizes of all hydrometeors increased, and mean-mass diameters of graupel increased the most significantly, as compared with those in the weak precipitation period; (3) The terminal velocity of raindrops was the strongest among all hydrometeors, followed by graupel's, which was much smaller than that of raindrops. Differences between various hydrometeors' terminal velocities in the strong precipitation period were larger than those in the weak precipitation period, which favored relative motion, collection interaction and transformation between the particles. Absolute terminal velocity values of raindrops and graupel were significantly greater than those of air upward velocity, and the stronger the precipitation was, the greater the differences between them were; (4) The orders of magnitudes of the various hydrometeors' sources and sinks in the strong precipitation period were larger than those in the weak precipitation period, causing a difference in the intensity of precipitation. Water vapor, cloud water, raindrops, graupel and their exchange processes played a major role in the production of the torrential rainfall, and there were two main processes via which raindrops were generated: abundant water vapor condensed into cloud water and, on the one hand, accretion of cloud water by rain water formed rain water, while on the other hand, accretion of cloud water by graupel formed graupel, and then the melting of graupel formed rain water.
An Assessment of the Predictability of the East Asian Subtropical Westerly Jet Based on TIGGE Data
ZHOU Baiquan, NIU Ruoyun, ZHAI Panmao
2015, 32(3): 401-412. doi: 10.1007/s00376-014-4026-2
The predictability of the position, spatial coverage and intensity of the East Asian subtropical westerly jet (EASWJ) in the summers of 2010 to 2012 was examined for ensemble prediction systems (EPSs) from four representative TIGGE centers, including the ECMWF, the NCEP, the CMA, and the JMA. Results showed that each EPS predicted all EASWJ properties well, while the levels of skill of all EPSs declined as the lead time extended. Overall, improvements from the control to the ensemble mean forecasts for predicting the EASWJ were apparent. For the deterministic forecasts of all EPSs, the prediction of the average axis was better than the prediction of the spatial coverage and intensity of the EASWJ. ECMWF performed best, with a lead of approximately 0.5-1 day in predictability over the second-best EPS for all EASWJ properties throughout the forecast range. For probabilistic forecasts, differences in skills among the different EPSs were more evident in the earlier part of the forecast for the EASWJ axis and spatial coverage, while they departed obviously throughout the forecast range for the intensity. ECMWF led JMA by about 0.5-1 day for the EASWJ axis, and by about 1-2 days for the spatial coverage and intensity at almost all lead times. The largest lead of ECMWF over the relatively worse EPSs, such as NCEP and CMA, was approximately 3-4 days for all EASWJ properties. In summary, ECMWF showed the highest level of skill for predicting the EASWJ, followed by JMA.
Incorporation of Parameter Uncertainty into Spatial Interpolation Using Bayesian Trans-Gaussian Kriging
Joon Jin SONG, Soohyun KWON, GyuWon LEE
2015, 32(3): 413-423. doi: 10.1007/s00376-014-4040-4
Quantitative precipitation estimation (QPE) plays an important role in meteorological and hydrological applications. Ground-based telemetered rain gauges are widely used to collect precipitation measurements. Spatial interpolation methods are commonly employed to estimate precipitation fields covering non-observed locations. Kriging is a simple and popular geostatistical interpolation method, but it has two known problems: uncertainty underestimation and violation of assumptions. This paper tackles these problems and seeks an optimal spatial interpolation for QPE in order to enhance spatial interpolation through appropriately assessing prediction uncertainty and fulfilling the required assumptions. To this end, several methods are tested: transformation, detrending, multiple spatial correlation functions, and Bayesian kriging. In particular, we focus on a short-term and time-specific rather than a long-term and event-specific analysis. This paper analyzes a stratiform rain event with an embedded convection linked to the passing monsoon front on the 23 August 2012. Data from a total of 100 automatic weather stations are used, and the rainfall intensities are calculated from the difference of 15 minute accumulated rainfall observed every 1 minute. The one-hour average rainfall intensity is then calculated to minimize the measurement random error. Cross-validation is carried out for evaluating the interpolation methods at regional and local levels. As a result, transformation is found to play an important role in improving spatial interpolation and uncertainty assessment, and Bayesian methods generally outperform traditional ones in terms of the criteria.
Processes Leading to Second-Year Cooling of the 2010-12 La Niña Event, Diagnosed Using GODAS
FENG Licheng, ZHANG Rong-Hua, WANG Zhanggui, CHEN Xingrong
2015, 32(3): 424-438. doi: 10.1007/s00376-014-4012-8
Isopycnal analyses were performed on the Global Ocean Data Assimilation System (GODAS) to determine the oceanic processes leading to so-called second-year cooling of the La Niña event. In 2010-12, a horseshoe-like pattern was seen, connecting negative temperature anomalies off and on the Equator, with a dominant influence from the South Pacific. During the 2010 La Niña event, warm waters piled up at subsurface depths in the western tropical Pacific. Beginning in early 2011, these warm subsurface anomalies propagated along the Equator toward the eastern basin, acting to reverse the sign of sea surface temperature (SST) anomalies (SSTAs) there and initiate a warm SSTA. However, throughout early 2011, pronounced negative anomalies persisted off the Equator in the subsurface depths of the South Pacific. As isopycnal surfaces outcropped in the central equatorial Pacific, negative anomalies from the subsurface spread upward along with mean circulation pathways, naturally initializing a cold SSTA. In the summer, a cold SSTA reappeared in the central basin, which subsequently strengthened due to the off-equatorial effects mostly in the South Pacific. These SSTAs acted to initiate local coupled air-sea interactions, generating atmospheric-oceanic anomalies that developed and evolved with the second-year cooling in the fall of 2011. However, the cooling tendency in mid-2012 did not develop into another La Niña event, since the cold anomalies in the South Pacific were not strong enough. An analysis of the 2007-09 La Niña event revealed similar processes to the 2010-12 La Niña event.
Characterization and Source Apportionment of Volatile Organic Compounds in Urban and Suburban Tianjin, China
HAN Meng, LU Xueqiang, ZHAO Chunsheng, RAN Liang, HAN Suqin
2015, 32(3): 439-444. doi: 10.1007/s00376-014-4077-4
Tianjin is the third largest megacity and the fastest growth area in China, and consequently faces the problems of surface ozone and haze episodes. This study measures and characterizes volatile organic compounds (VOCs), which are ozone precursors, to identify their possible sources and evaluate their contribution to ozone formation in urban and suburban Tianjin, China during the HaChi (Haze in China) summer campaign in 2009. A total of 107 species of ambient VOCs were detected, and the average concentrations of VOCs at urban and suburban sites were 92 and 174 ppbv, respectively. Of those, 51 species of VOCs were extracted to analyze the possible VOC sources using positive matrix factorization. The identified sources of VOCs were significantly related to vehicular activities, which specifically contributed 60% to urban and 42% to suburban VOCs loadings in Tianjin. Industrial emission was the second most prominent source of ambient VOCs in both urban and suburban areas, although the contribution of industry in the suburban area (36%) was much higher than that at the urban area (16%). We conclude that controlling vehicle emissions should be a top priority for VOC reduction, and that fast industrialization and urbanization causes air pollution to be more complex due to the combined emission of VOCs from industry and daily life, especially in suburban areas.