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Ge Chen and Hui Lin

Abstract

Previous research has shown that oceanic water vapor (OWV) is a useful quantity for studying the low-frequency variability of the atmosphere–ocean system. In this work, 10 years (1993–2002) of high-quality OWV data derived from the Ocean Topography Experiment (TOPEX) microwave radiometer are used to investigate the impact of El Niño/La Niña on the amplitude and phase of the annual cycle. These results suggest that El Niños (La Niñas) can weaken (strengthen) the seasonality of OWV by decreasing (increasing) the annual amplitude. The change of amplitude is usually slight but significant, especially for the five most dynamic seasonal belts across the major continents at midlatitudes. The El Niño–Southern Oscillation (ENSO) impact on the annual phase of OWV is seen to be fairly systematic and geographically correlated. The most striking feature is a large-scale advancing/delay of about 10 days (as estimated through empirical modeling) for the midlatitude oceans of the Northern Hemisphere in reaching their summer maxima during the El Niño/La Niña years. In addition, an alternative scheme for estimating the mean position of the intertropical convergence zone (ITCZ) based on the annual phase map of OWV is proposed. This ITCZ climatology favors 4°N in mean latitude, and agrees with existing results in that its position meanders from 2°S to 8°N oceanwide, and stays constantly north of the equator over the Atlantic and eastern Pacific.

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Hui-Ling Chang, Huiling Yuan, and Pay-Liam Lin

Abstract

This study pioneers the development of short-range (0–12 h) probabilistic quantitative precipitation forecasts (PQPFs) in Taiwan and aims to produce the PQPFs from time-lagged multimodel ensembles using the Local Analysis and Prediction System (LAPS). By doing so, the critical uncertainties in prediction processes can be captured and conveyed to the users. Since LAPS adopts diabatic data assimilation, it is utilized to mitigate the “spinup” problem and produce more accurate precipitation forecasts during the early prediction stage (0–6 h).

The LAPS ensemble prediction system (EPS) has a good spread–skill relationship and good discriminating ability. Therefore, though it is obviously wet biased, the forecast biases can be corrected to improve the skill of PQPFs through a linear regression (LR) calibration procedure. Sensitivity experiments for two important factors affecting calibration results are also conducted: the experiments on different training samples and the experiments on the accuracy of observation data. The first point reveals that the calibration results vary with training samples. Based on the statistical viewpoint, there should be enough samples for an effective calibration. Nevertheless, adopting more training samples does not necessarily produce better calibration results. It is essential to adopt training samples with similar forecast biases as validation samples to achieve better calibration results. The second factor indicates that as a result of the inconsistency of observation data accuracy in the sea and land areas, only separate calibration for these two areas can ensure better calibration results of the PQPFs.

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Lingcheng Li, Dunxian She, Hui Zheng, Peirong Lin, and Zong-Liang Yang

Abstract

This study elucidates drought characteristics in China during 1980–2015 using two commonly used meteorological drought indices: standardized precipitation index (SPI) and standardized precipitation–evapotranspiration index (SPEI). The results show that SPEI characterizes an overall increase in drought severity, area, and frequency during 1998–2015 compared with those during 1980–97, mainly due to the increasing potential evapotranspiration. By contrast, SPI does not reveal this phenomenon since precipitation does not exhibit a significant change overall. We further identify individual drought events using the three-dimensional (i.e., longitude, latitude, and time) clustering algorithm and apply the severity–area–duration (SAD) method to examine the drought spatiotemporal dynamics. Compared to SPI, SPEI identifies a lower drought frequency but with larger total drought areas overall. Additionally, SPEI identifies a greater number of severe drought events but a smaller number of slight drought events than the SPI. Approximately 30% of SPI-detected drought grids are not identified as drought by SPEI, and 40% of SPEI-detected drought grids are not recognized as drought by SPI. Both indices can roughly capture the major drought events, but SPEI-detected drought events are overall more severe than SPI. From the SAD analysis, SPI tends to identify drought as more severe over small areas within 1 million km2 and short durations less than 2 months, whereas SPEI tends to delineate drought as more severe across expansive areas larger than 3 million km2 and periods longer than 3 months. Given the fact that potential evapotranspiration increases in a warming climate, this study suggests SPEI may be more suitable than SPI in monitoring droughts under climate change.

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Maochong Shi, Changsheng Chen, Qichun Xu, Huichan Lin, Guimei Liu, Hui Wang, Fang Wang, and Jinhui Yan

Abstract

An analysis of the water level and current data taken in Qiongzhou Strait in the South China Sea (SCS) over the last 37 years (1963 to 1999) was made to examine the characteristics of tidal waves and residual flow through the strait and their roles in the seasonal variation of the SCS circulation. The observations reveal that Qiongzhou Strait is an area where opposing tidal waves interact and a source of water transport to the Gulf of Beibu (Gulf of Tonkin), SCS. A year-round westward mean flow with a maximum speed of 10–40 cm s−1 is found in Qiongzhou Strait. This accounts for water transport of 0.2–0.4 Sv and 0.1–0.2 Sv into the Gulf of Beibu in winter–spring and summer–autumn, respectively. The outflow from Qiongzhou Strait may cause up to 44% of the gulf water to be refreshed each season, suggesting that it has a significant impact on the seasonal circulation in the Gulf of Beibu. This finding is in contrast to our current understanding that the seasonal circulation patterns in the South China Sea are primarily driven by seasonal winds. Several numerical experiments were conducted to examine the physical mechanisms responsible for the formation of the westward mean flow in Qiongzhou Strait. The model provides a reasonable simulation of semidiurnal and diurnal tidal waves in the strait and the predicted residual flow generally agrees with the observed mean flow. An analysis of the momentum equations indicates that the strong westward flow is driven mainly by tidal rectification over variable bottom topography. Both observations and modeling suggest that the coastal physical processes associated with tidal rectification and buoyancy input must be taken into account when the mass balance of the SCS circulation is investigated, especially for the regional circulation in the Gulf of Beibu.

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Ming Li, Jiping Liu, Zhenzhan Wang, Hui Wang, Zhanhai Zhang, Lin Zhang, and Qinghua Yang

Abstract

Reanalysis projects and satellite data analysis have provided surface wind over the global ocean. To assess how well one can reconstruct the variations of surface wind in the data-sparse Southern Ocean, sea surface wind speed data from 1) the National Centers for Environmental Prediction–Department of Energy reanalysis (NCEP–DOE), 2) the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim), 3) National Climate Data Center (NCDC) blended sea winds, and 4) cross-calibrated multiplatform (CCMP) ocean surface velocity are evaluated. First, the accuracy of sea surface wind speed is validated with quality-controlled in situ measurements from research vessels. The results show that the CCMP value is closer to the ship observations than other products, whereas the NCEP–DOE value has the largest systematic positive bias. All four products show large positive biases under weak wind regimes, good agreement with the ship observations under moderate wind regimes, and large negative biases under high wind regimes. Second, the consistency and discrepancy of sea surface wind speed across different products is examined. The intercomparisons suggest that these products show encouraging agreement in the spatial distribution of the annual-mean sea surface wind speed. The largest across-data scatter is found in the central Indian sector of the Antarctic Circumpolar Current, which is comparable to its respective interannual variability. The monthly-mean correlations between pairs of products are high. However, differing from the decadal trends of NCEP–DOE, NCDC, and CCMP that show an increase of sea surface wind speed in the Antarctic Circumpolar region, ERA-Interim has an opposite sign there.

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Hui-Ling Chang, Shu-Chih Yang, Huiling Yuan, Pay-Liam Lin, and Yu-Chieng Liou

Abstract

Measurement of the usefulness of numerical weather prediction considers not only the forecast quality but also the possible economic value (EV) in the daily decision-making process of users. Discrimination ability of an ensemble prediction system (EPS) can be assessed by the relative operating characteristic (ROC), which is closely related to the EV provided by the same forecast system.

Focusing on short-range probabilistic quantitative precipitation forecasts (PQPFs) for typhoons, this study demonstrates the consistent and strongly related characteristics of ROC and EV based on the Local Analysis and Prediction System (LAPS) EPS operated at the Central Weather Bureau in Taiwan. Sensitivity experiments including the effect of terrain, calibration, and forecast uncertainties on ROC and EV show that the potential EV provided by a forecast system is mainly determined by the discrimination ability of the same system. The ROC and maximum EV (EVmax) of an EPS are insensitive to calibration, but the optimal probability threshold to achieve the EVmax becomes more reliable after calibration. In addition, the LAPS ensemble probabilistic forecasts outperform deterministic forecasts in respect to both ROC and EV, and such an advantage grows with increasing precipitation intensity. Also, even without explicitly knowing the cost–loss ratio, one can still optimize decision-making and obtain the EVmax by using ensemble probabilistic forecasts.

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Jeng-Lin Tsai, Ben-Jei Tsuang, Po-Sheng Lu, Ken-Hui Chang, Ming-Hwi Yao, and Yuan Shen

Abstract

The aerodynamic roughness, Bowen ratio, and friction velocity were measured over a rice paddy using tethersonde and eddy covariance (EC) systems. In addition, the height ranges of the atmospheric inertial sublayer (ISL) were derived using the tethersonde data. Comparison of the friction velocity, latent and sensible heat fluxes, and Bowen ratio estimated from these systems show their correlation coefficients to be >0.7. This difference between the observational systems can be associated with their respective footprint areas. The aerodynamic roughness was observed to be about 0.03 m for wind blowing from a paddy-dominated area (PDA) and about 0.37 m from a rice paddy interspersed with buildings (PIB) based on the ISL profile. Results are close to the effective roughness length model of Mason, having the same shear stresses at the blending height. In contrast, both the geometric mean model of Taylor and the arithmetic mean model of Tsai and Tsuang underestimate the effective roughness over the PIB. During daylight hours, the height range of the ISL ranged from a few meters to 25 m above ground level (AGL) for wind blowing from the PDA and 14–42 m for wind blowing from the PIB.

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Kun Yang, Jun Qin, Long Zhao, Yingying Chen, Wenjun Tang, Menglei Han, Lazhu, Zhuoqi Chen, Ning Lv, Baohong Ding, Hui Wu, and Changgui Lin

Multisphere interactions over the Tibetan Plateau directly impact its surrounding climate and environment at a variety of spatiotemporal scales. Remote sensing and modeling are expected to provide hydrometeorological data needed for these process studies, but in situ observations are required to support their calibration and validation. For this purpose, we have established a dense monitoring network on the central Tibetan Plateau to measure two state variables (soil moisture and temperature) at three spatial scales (1.0°, 0.3°, and 0.1°) and four soil depths (0–5, 10, 20, and 40 cm). The experimental area is characterized by low biomass, high soil moisture dynamic range, and typical freeze–thaw cycle. The network consists of 56 stations with their elevation varying over 4470–4950 m. As auxiliary parameters of this network, soil texture and soil organic carbon content are measured at each station to support further studies. To guarantee continuous and high-quality data, tremendous efforts have been made to protect the data-logger from soil water intrusion, to calibrate soil moisture sensors, and to upscale the point measurements.

As the highest soil moisture network above sea level in the world, our network meets the requirement for evaluating a variety of soil moisture products and for soil moisture scaling analyses. It also directly contributes to the soil–water–ice–air–ecosystem interaction studies on the third pole. The data will be publicized via the International Soil Moisture Network and the recent 2-yr data will become accessible soon.

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Yan Wang, Kun Yang, Zhengyang Pan, Jun Qin, Deliang Chen, Changgui Lin, Yingying Chen, Lazhu, Wenjun Tang, Menglei Han, Ning Lu, and Hui Wu

Abstract

The southern Tibetan Plateau (STP) is the region in which water vapor passes from South Asia into the Tibetan Plateau (TP). The accuracy of precipitable water vapor (PWV) modeling for this region depends strongly on the quality of the available estimates of water vapor advection and the parameterization of land evaporation models. While climate simulation is frequently improved by assimilating relevant satellite and reanalysis products, this requires an understanding of the accuracy of these products. In this study, PWV data from MODIS infrared and near-infrared measurements, AIRS Level-2 and Level-3, MERRA, ERA-Interim, JRA-55, and NCEP final reanalysis (NCEP-Final) are evaluated against ground-based GPS measurements at nine stations over the STP, which covers the summer monsoon season from 2007 to 2013. The MODIS infrared product is shown to underestimate water vapor levels by more than 20% (1.84 mm), while the MODIS near-infrared product overestimates them by over 40% (3.52 mm). The AIRS PWV product appears to be most useful for constructing high-resolution and high-quality PWV datasets over the TP; particularly the AIRS Level-2 product has a relatively low bias (0.48 mm) and RMSE (1.83 mm) and correlates strongly with the GPS measurements (R = 0.90). The four reanalysis datasets exhibit similar performance in terms of their correlation coefficients (R = 0.87–0.90), bias (0.72–1.49 mm), and RMSE (2.19–2.35 mm). The key finding is that all the reanalyses have positive biases along the PWV seasonal cycle, which is linked to the well-known wet bias over the TP of current climate models.

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Wenli Wang, Kun Yang, Long Zhao, Ziyan Zheng, Hui Lu, Ali Mamtimin, Baohong Ding, Xin Li, Lin Zhao, Hongyi Li, Tao Che, and John C. Moore

Abstract

Snow depth on the interior of Tibetan Plateau (TP) in state-of-the-art reanalysis products is almost an order of magnitude higher than observed. This huge bias stems primarily from excessive snowfall, but inappropriate process representation of shallow snow also causes excessive snow depth and snow cover. This study investigated the issue with respect to the parameterization of fresh snow albedo. The characteristics of TP snowfall were investigated using ground truth data. Snow in the interior of the TP is usually only some centimeters in depth. The albedo of fresh snow depends on snow depth, and is frequently less than 0.4. Such low albedo values contrast with the high values (~0.8) used in the existing snow schemes of land surface models. The SNICAR radiative transfer model can reproduce the observations that fresh shallow snow has a low albedo value, based on which a fresh snow albedo scheme was derived in this study. Finally, the impact of the fresh snow albedo on snow ablation was examined at 45 meteorological stations on TP using the land surface model Noah-MP which incorporated the new scheme. Allowing albedo to change with snow depth can produce quite realistic snow depths compared with observations. In contrast, the typically assumed fresh snow albedo of 0.82 leads to too large snow depths in the snow ablation period averaged across 45 stations. The shallow snow transparency impact on snow ablation is therefore particularly important in the TP interior, where snow is rather thin and radiation is strong.

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