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Paul A. Dirmeyer, Yan Jin, Bohar Singh, and Xiaoqin Yan

Abstract

Data from 15 models of phase 5 of the Coupled Model Intercomparison Project (CMIP5) for preindustrial, historical, and future climate change experiments are examined for consensus changes in land surface variables, fluxes, and metrics relevant to land–atmosphere interactions. Consensus changes in soil moisture and latent heat fluxes for past-to-present and present-to-future periods are consistent with CMIP3 simulations, showing a general drying trend over land (less soil moisture, less evaporation) over most of the globe, with the notable exception of high northern latitudes during winter. Sensible heat flux and net radiation declined from preindustrial times to current conditions according to the multimodel consensus, mainly due to increasing aerosols, but that trend reverses abruptly in the future projection. No broad trends are found in soil moisture memory except for reductions during boreal winter associated with high-latitude warming and diminution of frozen soils. Land–atmosphere coupling is projected to increase in the future across most of the globe, meaning a greater control by soil moisture variations on surface fluxes and the lower troposphere. There is also a strong consensus for a deepening atmospheric boundary layer and diminished gradients across the entrainment zone at the top of the boundary layer, indicating that the land surface feedback on the atmosphere should become stronger both in absolute terms and relative to the influence of the conditions of the free atmosphere. Coupled with the trend toward greater hydrologic extremes such as severe droughts, the land surface seems likely to play a greater role in amplifying both extremes and trends in climate on subseasonal and longer time scales.

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Paul A. Dirmeyer, Yan Jin, Bohar Singh, and Xiaoqin Yan

Abstract

Long-term changes in land–atmosphere interactions during spring and summer are examined over North America. A suite of models from phase 5 of the Coupled Model Intercomparison Project simulating preindustrial, historical, and severe future climate change scenarios are examined for changes in soil moisture, surface fluxes, atmospheric boundary layer characteristics, and metrics of land–atmosphere coupling.

Simulations of changes from preindustrial to modern conditions show warming brings stronger surface fluxes at high latitudes, while subtropical regions of North America respond with drier conditions. There is a clear anthropogenic aerosol response in midlatitudes that reduces surface radiation and heat fluxes, leading to shallower boundary layers and lower cloud base. Over the Great Plains, the signal does not reflect a purely radiatively forced response, showing evidence that the expansion of agriculture may have offset the aerosol impacts on the surface energy and water cycle.

Future changes show soils are projected to dry across North America, even though precipitation increases north of a line that retreats poleward from spring to summer. Latent heat flux also has a north–south dipole of change, increasing north and decreasing south of a line that also moves northward with the changing season. Metrics of land–atmosphere feedback increase over most of the continent but are strongest where latent heat flux increases in the same location and season where precipitation decreases. Combined with broadly elevated cloud bases and deeper boundary layers, land–atmosphere interactions are projected to become more important in the future with possible consequences for seasonal climate prediction.

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Long Jin, Cai Yao, and Xiao-Yan Huang

Abstract

A new nonlinear artificial intelligence ensemble prediction (NAIEP) model has been developed for predicting typhoon intensity based on multiple neural networks with the same expected output and using an evolutionary genetic algorithm (GA). The model is validated with short-range forecasts of typhoon intensity in the South China Sea (SCS); results show that the NAIEP model is clearly better than the climatology and persistence (CLIPER) model for 24-h forecasts of typhoon intensity. Using identical predictors and sample cases, predictions of the genetic neural network (GNN) ensemble prediction (GNNEP) model are compared with the single-GNN prediction model, and it has been proven theoretically that the former is more accurate. Computation and analysis of the generalization capacity of GNNEP also demonstrate that the prediction of the ensemble model integrates predictions of its optimized ensemble members, so the generalization capacity of the ensemble prediction model is also enhanced. This model better addresses the “overfitting” problem that generally exists in the traditional neural network approach to practical weather prediction.

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Anping Sun, Hye-Yeong Chun, Jong-Jin Baik, and Muhong Yan

Abstract

A new three-dimensional dynamics and electrification coupled model is developed to investigate the influence of electrification on microphysical and dynamical processes in thunderstorms. This model includes a four-class ice microphysics scheme, five electrification mechanisms, and lightning parameterization. Comparisons between model results and observations reveal that the dynamics and electrification coupled model is capable of reproducing many of the observed characteristics of the thunderstorm in dynamical, microphysical, and electrical aspects. The effects of electrification on microphysical and dynamical processes are examined by performing two numerical experiments, one with electrification processes and the other without them. Results show that when electrification processes are included the mass transfer among hydrometeors in microphysical processes, especially collection and coalescence processes, changes considerably as a result of significant modification of the terminal velocities of large precipitation particles. The change of mass transfer in microphysical processes affects cloud buoyancy by changing the amount and distribution of hydrometeors, and latent-heat release in the middle region of the thunderstorm increases. That is, convection strengthens by including electrification processes. The amount of solid precipitation and the diameter of solid precipitation particles at the surface increase because a stronger updraft sustains large precipitation particles and prevents them from falling out of the cloud earlier.

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Yan Jin, Zezong Chen, Lingang Fan, and Chen Zhao

Abstract

A new method is proposed to detect small targets embedded in sea clutter for land-based microwave coherent radar using spectral kurtosis as a signature from radar data. It is executed according to the following procedures. First, the echoes of radar from each range gate are processed by the technique of short-time Fourier transform. Then, the kurtosis of each Doppler channel is estimated from the time–Doppler spectra. Last, the spectral kurtosis is compared to a threshold to determine whether a target exists. The proposed method is applied to measured datasets of different sea conditions from slight to moderate. The signal from a small boat is detected successfully. Furthermore, the detection performance of the proposed method is analyzed by the way of Monte Carlo simulation. It demonstrates that the spectral kurtosis–based detector works well for weak target detection when the target’s Doppler frequency is beyond the strong clutter region.

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Chunhan Jin, Jian Liu, Bin Wang, Mi Yan, and Liang Ning

Abstract

Statistical evidence suggests that solar activity may affect the atmospheric circulation over East Asia (EA), but the way in which the 11-yr solar radiation cycle affects the East Asian summer monsoon (EASM) remains unexplained. Based on one control experiment and four solar-only forcing experiments performed during the Community Earth System Model–Last Millennium Ensemble (CESM-LME) model project, we explore the potential impacts of the 11-yr solar cycle on EASM variability and the physical processes through which solar forcing influences EASM decadal variability. The model results show that the warm season [May–September (MJJAS)] mean precipitation over EA exhibits significant decadal variation with a “northern wet–southern dry” pattern during peak years in the strong 11-yr solar cycle epoch (AD 900–1285), which is in contrast to the absence of decadal signals during the weak 11-yr solar cycle epoch (AD 1400–1535). For the four-member ensemble averaged solar-only forcing experiment, the summer mean precipitation over northern EA is significantly correlated with the solar forcing (r = 0.414, n = 68, p < 0.05) on a decadal time scale during the strong cycle epoch, whereas there is no statistical link between the EASM and solar activity during the weak cycle epoch (r = 0.002, n = 24). A strong, 11-yr solar cycle is also shown to excite an anomalous sea surface temperature (SST) pattern that resembles a cool Pacific decadal oscillation (PDO) phase, which has a significant 11-yr periodicity. The associated anomalous North Pacific anticyclone dominates the entire extratropical North Pacific and enhances the southerly monsoon over EA, which results in abundant rainfall over northern EA. We argue that the 11-yr solar cycle affects the EASM decadal variation through excitation of a coupled decadal mode in the Asia–North Pacific region.

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Liang Ning, Kefan Chen, Jian Liu, Zhengyu Liu, Mi Yan, Weiyi Sun, Chunhan Jin, and Zhengguo Shi

Abstract

The influence and mechanism of volcanic eruptions on decadal megadroughts over eastern China during the last millennium were investigated using a control (CTRL) and five volcanic eruption sensitivity experiments (VOLC) from the Community Earth System Model (CESM) Last Millennium Ensemble (LME) archive. The decadal megadroughts associated with the failures of the East Asian summer monsoon (EASM) are associated with a meridional tripole of sea surface temperature anomalies (SSTAs) in the western Pacific from the equator to high latitudes, suggestive of a decadal-scale internal mode of variability that emerges from empirical orthogonal function (EOF) analysis. Composite analyses further showed that, on interannual time scales, within a decade after an eruption the megadrought was first enhanced but then weakened, due to the change from an El Niño state to a La Niña state. The impacts of volcanic eruptions on the magnitudes of megadroughts are superposed on internal variability. Therefore, the evolution of decadal megadroughts coinciding with strong volcanic eruptions demonstrate that the impacts of internal variability and external forcing can combine to influence hydroclimate.

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Qin Zhang, Arun Kumar, Yan Xue, Wanqiu Wang, and Fei-Fei Jin

Abstract

Simulations from the National Centers for Environmental Prediction (NCEP) coupled model are analyzed to document and understand the behavior of the evolution of the El Niño–Southern Oscillation (ENSO) cycle. The analysis is of importance for two reasons: 1) the coupled model used in this study is also used operationally to provide model-based forecast guidance on a seasonal time scale, and therefore, an understanding of the ENSO mechanism in this particular coupled system could also lead to an understanding of possible biases in SST predictions; and 2) multiple theories for ENSO evolution have been proposed, and coupled model simulations are a useful test bed for understanding the relative importance of different ENSO mechanisms.

The analyses of coupled model simulations show that during the ENSO evolution the net surface heat flux acts as a damping mechanism for the mixed-layer temperature anomalies, and positive contribution from the advection terms to the ENSO evolution is dominated by the linear advective processes. The subsurface temperature–SST feedback, referred to as thermocline feedback in some theoretical literature, is found to be the primary positive feedback, whereas the advective feedback by anomalous zonal currents and the thermocline feedback are the primary sources responsible for the ENSO phase transition in the model simulation. The basic mechanisms for the model-simulated ENSO cycle are thus, to a large extent, consistent with those highlighted in the recharge oscillator. The atmospheric anticyclone (cyclone) over the western equatorial northern Pacific accompanied by a warm (cold) phase of the ENSO, as well as the oceanic Rossby waves outside of 15°S–15°N and the equatorial higher-order baroclinic modes, all appear to play minor roles in the model ENSO cycles.

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Lisan Yu, Xiangze Jin, Simon A. Josey, Tong Lee, Arun Kumar, Caihong Wen, and Yan Xue

Abstract

This study provides an assessment of the uncertainty in ocean surface (OS) freshwater budgets and variability using evaporation E and precipitation P from 10 atmospheric reanalyses, two combined satellite-based E − P products, and two observation-based salinity products. Three issues are examined: the uncertainty level in the OS freshwater budget in atmospheric reanalyses, the uncertainty structure and association with the global ocean wet/dry zones, and the potential of salinity in ascribing the uncertainty in E − P. The products agree on the global mean pattern but differ considerably in magnitude. The OS freshwater budgets are 129 ± 10 (8%) cm yr−1 for E, 118 ± 11 (9%) cm yr−1 for P, and 11 ± 4 (36%) cm yr−1 for E − P, where the mean and error represent the ensemble mean and one standard deviation of the ensemble spread. The E − P uncertainty exceeds the uncertainty in E and P by a factor of 4 or more. The large uncertainty is attributed to P in the tropical wet zone. Most reanalyses tend to produce a wider tropical rainband when compared to satellite products, with the exception of two recent reanalyses that implement an observation-based correction for the model-generated P over land. The disparity in the width and the extent of seasonal migrations of the tropical wet zone causes a large spread in P, implying that the tropical moist physics and the realism of tropical rainfall remain a key challenge. Satellite salinity appears feasible to evaluate the fidelity of E − P variability in three tropical areas, where the uncertainty diagnosis has a global indication.

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Kyoung-Ho Cho, Yan Li, Hui Wang, Kwang-Soon Park, Jin-Yong Choi, Kwang-Il Shin, and Jae-Il Kwon

Abstract

An operational search and rescue (SAR) modeling system was developed to forecast the tracks of victims or debris from marine accidents in the marginal seas of the northwestern Pacific Ocean. The system is directly linked to a real-time operational forecasting system that provides wind and surface current forecasts for the Yellow Sea and the East and South China Seas and is thus capable of immediately predicting the tracks and area to be searched for up to 72 h in the future. A stochastic trajectory model using a Monte Carlo ensemble technique is employed within the system to estimate the trajectories of drifting objects. It is able to consider leeway drift and to deal with uncertainties in the forcing fields obtained from the operational forecasting system. A circle assessment method was applied to evaluate the performance of the SAR model using comparisons in buoy and ship trajectories obtained from field drifter experiments. The method effectively analyzed the effects of the forcing fields and diagnosed the model’s performance. Results showed that accurate wind and current forcing fields play a significant role in improving the behavior of the SAR model. Operationally, the SAR modeling system is used to support the Korea Coast Guard during marine emergencies. Additionally, some sensitivity tests for model parameters and wave effect on the SAR model prediction are discussed.

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