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Jin Wu and Yi Wei

Abstract

An optical-electronic technique has been developed for simultaneous, remote measurements of the surface tension and wave attenuation over the water surface. The technique has been fully tested in a laboratory tank, and tried in the field. Sample results of measurements are presented to illustrate that the technique is an effective method for studying the surfactants on the air–sea interface.

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Yi Zhang and Wei-Chyung Wang

Abstract

Two 100-yr equilibrium simulations from the NCAR Community Climate Model coupled to a nondynamic slab ocean are used to investigate the activity of northern winter extratropical cyclones and anticyclones under a greenhouse warming scenario. The first simulation uses the 1990 observed CO2, CH4, N2O, CFC-11, and CFC-12 concentrations, and the second adopts the year 2050 concentrations according to the Intergovernmental Panel on Climate Change business-as-usual scenario. Variables that describe the characteristic properties of the cyclone-scale eddies, such as surface cyclone and anticyclone frequency and the bandpassed root-mean-square of 500-hPa geopotential height, along with the Eady growth rate maximum, form a framework for the analysis of the cyclone and anticyclone activity.

Objective criteria are developed for identifying cyclone and anticyclone occurrences based on the 1000-hPa geopotential height and vorticity fields and tested using ECMWF analyses. The potential changes of the eddy activity under the greenhouse warming climate are then examined. Results indicate that the activity of cyclone-scale eddies decreases under the greenhouse warming scenario. This is not only reflected in the surface cyclone and anticyclone frequency and in the bandpassed rms of 500-hPa geopotential height, but is also discerned from the Eady growth rate maximum. Based on the analysis, three different physical mechanisms responsible for the decreased eddy activity are discussed: 1) a decrease of the extratropical meridional temperature gradient from the surface to the midtroposphere, 2) a reduction in the land–sea thermal contrast in the east coastal regions of the Asian and North American continents, and 3) an increase in the eddy meridional latent heat fluxes. Uncertainties in the results related to the limitations of the model and the model equilibrium simulations are discussed.

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Qin Xu, Li Wei, Yi Jin, Qingyun Zhao, and Jie Cao

Abstract

This paper proposes a new method to properly define and accurately determine the vortex center of a model-predicted tropical cyclone (TC) from a dynamic perspective. Ideally, a dynamically determined TC vortex center should maximize the gradient wind balance or, equivalently, minimize the gradient wind imbalance measured by an energy norm over the TC vortex. In practice, however, such an energy norm cannot be used to easily and unambiguously determine the TC vortex center. An alternative yet practical approach is developed to dynamically and unambiguously define the TC vortex center. In this approach, the TC vortex core of near-solid-body rotation is modeled by a simple parametric vortex constrained by the gradient wind balance. Therefore, the modeled vortex can fit simultaneously the perturbation pressure and streamfunction of the TC vortex part (extracted from the model-predicted fields) over the TC vortex core area (within the radius of maximum tangential wind), while the misfit is measured by a properly defined cost function. Minimizing this cost function yields the desired dynamic optimality condition that can uniquely define the TC vortex center. Using this dynamic optimality condition, a new method is developed in the form of iterative least squares fit to accurately determine the TC vortex center. The new method is shown to be efficient and effective for finding the TC vortex center that accurately satisfies the dynamic optimality condition.

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Tuantuan Zhang, Xingwen Jiang, Junwen Chen, Song Yang, Yi Deng, Wei Wei, Peng Hu, and Peng Gao

Abstract

As a result of the high mountains to the west and north of the plateau and the control by westerly mean flow in spring, hot and dry conditions are often observed over the southeastern edge of the Tibetan Plateau (SETP), favoring occurrences of extreme heat events there. Indeed, maximum centers and remarkable increasing trends of extreme heat (EH) days in spring are found over the region. Springtime EH events over the SETP also exhibit strong interannual variability and are closely linked to a spring-type circumglobal teleconnection (SCGT) pattern, which is the second leading mode of 200-hPa meridional wind over the North Hemisphere in spring. This SCGT shows distinctive features from the traditional circumglobal teleconnection patterns found in boreal summer and winter. It manifests as a circumglobally navigated Rossby wave train along the mid–high latitudes, which splits to a north branch along the polar jet and a south branch along the subtropical jet over Eurasia after propagating through the North Atlantic Ocean. The two branches eventually reach the SETP, forming an anomalous anticyclonic circulation over the region. Hence, conditions in the SETP are controlled by significant anomalous subsidence and a clearer sky, resulting in below-normal rainfall and above-normal air temperature, favoring more EH events in the region. The SETP EH events are also closely linked to the spring-type CGT-like pattern in April and May but not in March. In addition, the influence of the foehn effect on the SETP EH is discussed.

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Lu Li, Wei Shangguan, Yi Deng, Jiafu Mao, JinJing Pan, Nan Wei, Hua Yuan, Shupeng Zhang, Yonggen Zhang, and Yongjiu Dai

Abstract

Soil moisture influences precipitation mainly through its impact on land–atmosphere interactions. Understanding and correctly modeling soil moisture–precipitation (SM–P) coupling is crucial for improving weather forecasting and subseasonal to seasonal climate predictions, especially when predicting the persistence and magnitude of drought. However, the sign and spatial structure of SM–P feedback are still being debated in the climate research community, mainly due to the difficulty in establishing causal relationships and the high degree of nonlinearity in land–atmosphere processes. To this end, we developed a causal inference model based on the Granger causality analysis and a nonlinear machine learning model. This model includes three steps: nonlinear anomaly decomposition, nonlinear Granger causality analysis, and evaluation of the quality of SM–P feedback, which eliminates the nonlinear response of interannual and seasonal variability and the memory effects of climatic factors and isolates the causal relationship of local SM–P feedback. We applied this model by using National Climate Assessment–Land Data Assimilation System (NCA-LDAS) datasets over the United States. The results highlight the importance of nonlinear atmosphere responses in land–atmosphere interactions. In addition, the strong feedback over the southwestern United States and the Great Plains both highlight the impacts of topographic factors rather than only the sensitivity of evapotranspiration to soil moisture. Furthermore, the SM–P index defined by our framework is used to benchmark Earth system models (ESMs), which provides a new metric for efficiently identifying potential model biases in modeling local land–atmosphere interactions and may help the development of ESMs in improving simulations of water cycle variability and extremes.

Open access
Wei Na, John L. McBride, Xing-Hai Zhang, and Yi-Hong Duan

Abstract

The characteristics of 24-h official forecast errors (OFEs) of tropical cyclone (TC) intensity are analyzed over the North Atlantic, east Pacific, and western North Pacific. The OFE is demonstrated to be strongly anticorrelated with TC intensity change with correlation coefficients of −0.77, −0.77, and −0.68 for the three basins, respectively. The 24-h intensity change in the official forecast closely follows a Gaussian distribution with a standard deviation only ⅔ of that in nature, suggesting the current official forecasts estimate fewer cases of large intensity change. The intensifying systems tend to produce negative errors (underforecast), while weakening systems have consistent positive errors (overforecast). This asymmetrical bias is larger for extreme intensity change, including rapid intensification (RI) and rapid weakening (RW). To understand this behavior, the errors are analyzed in a simple objective model, the trend-persistence model (TPM). The TPM exhibits the same error-intensity change correlation. In the TPM, the error can be understood as it is exactly inversely proportional to the finite difference form of the concavity or second derivative of the intensity–time curve. The occurrence of large negative (positive) errors indicates the intensity–time curve is concave upward (downward) in nature during the TC’s rapid intensification (weakening) process. Thus, the fundamental feature of the OFE distribution is related to the shape of the intensity–time curve, governed by TC dynamics. All forecast systems have difficulty forecasting an accelerating rate of change, or a large second derivative of the intensity–time curve. TPM may also be useful as a baseline in evaluating the skill of official forecasts. According to this baseline, official forecasts are more skillful in RW than in RI.

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Jun-Jie Chang, Yi-Ming Wei, Xiao-Chen Yuan, Hua Liao, and Bi-Ying Yu

Abstract

China, the second largest economy in the world, covers a large area spanning multiple climate zones, with varying economic conditions across regions. Given this variety in climate and economic conditions, global warming is expected to have heterogeneous economic impacts across the country. This study uses annual average temperature to conduct an empirical research from a top-down perspective to evaluate the nonlinear impacts of temperature change on aggregate economic output in China. We find that there is an inverted U-shaped relationship between temperature and economic growth at the provincial level, with a turning point at 12.2°C. The regional and national economic impacts are projected under the shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs). As future temperature rises, the economic impacts are positive in the northeast, north, and northwest regions but negative in the south, east, central, and southwest regions. Based on SSP5, the decrement in the GDP per capita of China would reach 16.0% under RCP2.6 and 27.0% under RCP8.5.

Free access
Wei Chen, June-Yi Lee, Kyung-Ja Ha, Kyung-Sook Yun, and Riyu Lu

Abstract

Two types of El Niño evolution have been identified in terms of the lengths of their decaying phases: the first type is a short decaying El Niño that terminates in the following summer after the mature phase, and the second type is a long decaying one that persists until the subsequent winter. The responses of the western North Pacific anticyclone (WNPAC) anomaly to the two types of evolution are remarkably different. Using experiments from phase 5 of the Coupled Model Intercomparison Project (CMIP5), this study investigates how well climate models reproduce the two types of El Niño evolution and their impacts on the WNPAC in the historical period (1950–2005) and how they will change in the future under anthropogenic global warming. To reduce uncertainty in future projection, the nine best models are selected based on their performance in simulating El Niño evolution. In the historical run, the nine best models’ multimodel ensemble (B9MME) well reproduces the enhanced (weakened) WNPAC that is associated with the short (long) decaying El Niño. The comparison between results of the historical run for 1950–2005 and the representative concentration pathway 4.5 run for 2050–99 reveals that individual models and the B9MME tend to project no significant changes in the two types of El Niño evolution for the latter half of the twenty-first century. However, the WNPAC response to the short decaying El Niño is considerably intensified, being associated with the enhanced negative precipitation anomaly response over the equatorial central Pacific. This enhancement is attributable to the robust increase in mean and interannual variability of precipitation over the equatorial central Pacific under global warming.

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Yu-Chiao Liang, Matthew R. Mazloff, Isabella Rosso, Shih-Wei Fang, and Jin-Yi Yu

Abstract

The ability to construct nitrate maps in the Southern Ocean (SO) from sparse observations is important for marine biogeochemistry research, as it offers a geographical estimate of biological productivity. The goal of this study is to infer the skill of constructed SO nitrate maps using varying data sampling strategies. The mapping method uses multivariate empirical orthogonal functions (MEOFs) constructed from nitrate, salinity, and potential temperature (N-S-T) fields from a biogeochemical general circulation model simulation Synthetic N-S-T datasets are created by sampling modeled N-S-T fields in specific regions, determined either by random selection or by selecting regions over a certain threshold of nitrate temporal variances. The first 500 MEOF modes, determined by their capability to reconstruct the original N-S-T fields, are projected onto these synthetic N-S-T data to construct time-varying nitrate maps. Normalized root-mean-square errors (NRMSEs) are calculated between the constructed nitrate maps and the original modeled fields for different sampling strategies. The sampling strategy according to nitrate variances is shown to yield maps with lower NRMSEs than mapping adopting random sampling. A k-means cluster method that considers the N-S-T combined variances to identify key regions to insert data is most effective in reducing the mapping errors. These findings are further quantified by a series of mapping error analyses that also address the significance of data sampling density. The results provide a sampling framework to prioritize the deployment of biogeochemical Argo floats for constructing nitrate maps.

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Chu-Chun Chen, Min-Hui Lo, Eun-Soon Im, Jin-Yi Yu, Yu-Chiao Liang, Wei-Ting Chen, Iping Tang, Chia-Wei Lan, Ren-Jie Wu, and Rong-You Chien

Abstract

Tropical deforestation can result in substantial changes in local surface energy and water budgets, and thus in atmospheric stability. These effects may in turn yield changes in precipitation. The Maritime Continent (MC) has undergone severe deforestation during the past few decades but it has received less attention than the deforestation in the Amazon and Congo rain forests. In this study, numerical deforestation experiments are conducted with global (i.e., Community Earth System Model) and regional climate models (i.e., Regional Climate Model version 4.6) to investigate precipitation responses to MC deforestation. The results show that the deforestation in the MC region leads to increases in both surface temperature and local precipitation. Atmospheric moisture budget analysis reveals that the enhanced precipitation is associated more with the dynamic component than with the thermodynamic component of the vertical moisture advection term. Further analyses on the vertical profile of moist static energy indicate that the atmospheric instability over the deforested areas is increased as a result of anomalous moistening at approximately 800–850 hPa and anomalous warming extending from the surface to 750 hPa. This instability favors ascending air motions, which enhance low-level moisture convergence. Moreover, the vertical motion increases associated with the MC deforestation are comparable to those generated by La Niña events. These findings offer not only mechanisms to explain the local climatic responses to MC deforestation but also insights into the possible reasons for disagreements among climate models in simulating the precipitation responses.

Open access