Changes in Tropical Clouds and Atmospheric Circulation Associated with Rapid Adjustment Induced by Increased Atmospheric CO2 A Multiscale Modeling Framework Study

The radiative heating increase due to increased CO2 concentration is the primary source for the rapid adjustment of atmospheric circulation and clouds. In this study, we investigate the rapid adjustment resulting from doubling of CO2 and its physical mechanism using a multiscale modeling framework (MMF). The MMF includes an advanced higher-order turbulence closure in its cloud-resolving model component and simulates realistic shallow and deep cloud climatology and boundary layer turbulence. The rapid adjustment over the tropics is characterized by 1) reduced ascent and descent strengths over the ocean, 2) increased lower tropospheric stability (LTS) over the subsidence region, 3) shoaling of planetary boundary layers over the ocean, 4) increased deep convection over lands and shift of cloud coverage from the ocean to lands, and 5) reduced sensible (SH) and latent heat (LH) fluxes over the oceanic deep convective regions. Unlike conventional general circulation models and another MMF, a reduction in the global-mean shortwave cloud radiative cooling is not simulated, due to the increase in low clouds at lower altitudes over the ocean, resulting from reduced cloud-top entrainment due to strengthened inversion. Changes in regional circulation play a key role in cloud changes and shift of cloud coverage to lands. Weaker energy transport resulting from water vapor and cloud CO2 masking effects reduces the upward motion and convective clouds in the oceanic regions. The ocean-land transports are linked to the partitioning of surface SH and LH fluxes that increases humidity over lands and enhances deep convection over the tropical lands

Water-saving and pollution-reducing effects of different irri-gation modes in paddy fields: A case study in Pinghu, Zhejiang province

Objective To study the water-saving and pollution reduction effects of rice under different irrigation modes, and to explore the water-saving irrigation mode suitable for the plain river network area. Methods Three modes of conventional irrigation, thin dew irrigation and suitable rain irrigation were set up in Pinghu irrigation experimental station in Zhejiang Province. The irrigation amount, TN, TP, , NO-N and COD in drainage and leakage water samples were measured. Result Compared with conventional irrigation and thin dew irrigation, the irrigation amount of suitable rain irrigation was reduced by 67.4% and 43.4%, respectively, and the water-saving effect was the best. Compared with conventional irrigation and thin dew irrigation, rain-appropriate irrigation has the least drainage. TN emissions,  emissions, COD emissions and TP and  emissions are reduced by 86.9% and 90.7%, 96.7% and 98.3%, 61.5% and 62.5%, respectively. Conclusion Under the condition of this study, the water-saving and pollution reduction effect of rain irrigation is better

Radiative Effects of African Dust and Smoke Observed from CERES and CALIOP Data

Cloud and aerosol effects have a significant impact on the atmospheric radiation budget in the Tropical Atlantic because of the spatial and temporal extent of desert dust and smoke from biomass burning in the atmosphere. The influences of African dust and smoke aerosols on cloud radiative properties over the Tropical Atlantic Ocean were analyzed for the month of July for three years (2006-2008) using collocated data collected by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Clouds and the Earth s Radiant Energy System (CERES) instruments on the CALIPSO and Aqua satellites. Aerosol layer height and type can be more accurately determined using CALIOP data, through parameters such as cloud and aerosol layer height, optical depth and depolarization ratio, than data from atmospheric imagers used in previous cloud-aerosol interaction studies. On average, clouds below 5 km had a daytime instantaneous shortwave (SW) radiative flux of 270.2 +/- 16.9 W/sq m and thin cirrus clouds had a SW radiative flux of 208.0 +/- 12.7 W/sq m. When dust aerosols interacted with clouds below 5 km, as determined from CALIPSO, the SW radiative flux decreased to 205.4 +/- 13.0 W/sq m. Similarly, smoke aerosols decreased the SW radiative flux of low clouds to a value of 240.0 +/- 16.6 W/sq m. These decreases in SW radiative flux were likely attributed to the aerosol layer height and changes in cloud microphysics. CALIOP lidar observations, which more accurately identify aerosol layer height than passive instruments, appear essential for better understanding of cloud-aerosol interactions, a major uncertainty in predicting the climate system

Engineering two-dimensional metal oxides and chalcogenides for enhanced electro- and photocatalysis

Two-dimensional (2D) metal oxides and chalcogenides (MOs & MCs) have been regarded as a new class of promising electro- and photocatalysts for many important chemical reactions such as hydrogen evolution reaction, CO2 reduction reaction and N2 reduction reaction in virtue of their outstanding physicochemical properties. However, pristine 2D MOs & MCs generally show the relatively poor catalytic performances due to the low electrical conductivity, few active sites and fast charge recombination. Therefore, considerable efforts have been devoted to engineering 2D MOs & MCs by rational structural design and chemical modification to further improve the catalytic activities. Herein, we comprehensively review the recent advances for engineering technologies of 2D MOs & MCs, which are mainly focused on the intercalation, doping, defects creation, facet design and compositing with functional materials. Meanwhile, the relationship between morphological, physicochemical, electronic, and optical properties of 2D MOs & MCs and their electro- and photocatalytic performances is also systematically discussed. Finally, we further give the prospect and challenge of the field and possible future research directions, aiming to inspire more research for achieving high-performance 2D MOs & MCs catalysts in energy storage and conversion fields

Coincident Occurrences of Tropical Individual Cirrus Clouds and Deep Convective Systems Derived from TRMM Observations

Measurements of cloud properties and atmospheric radiation taken between January and August 1998 by the Tropical Rainfall Measuring Mission (TRMM) satellite were used to investigate the effect of spatial and temporal scales on the coincident occurrences of tropical individual cirrus clouds (ICCs) and deep convective systems (DCSs). It is found that there is little or even negative correlation between instantaneous occurrences of ICC and DCS in small areas, in which both types of clouds cannot grow and expand simultaneously. When spatial and temporal domains are increased, ICCs become more dependent on DCSs due to the origination of many ICCs from DCSs and moisture supply from the DCS in the upper troposphere for the ICCs to grow, resulting in significant positive correlation between the two types of tropical high clouds in large spatial and long temporal scales. This result may suggest that the decrease of tropical high clouds with SST from model simulations is likely caused by restricted spatial domains and limited temporal periods. Finally, the radiative feedback due to the change in tropical high cloud area coverage with sea surface temperature appears small and about -0.14 W/sq m per degree Kelvin

The Effect of Environmental Conditions on Tropical Deep Convective Systems Observed from the TRMM Satellite

This study uses measurements of radiation and cloud properties taken between January and August 1998 by three Tropical Rainfall Measuring Mission (TRMM) instruments, the Clouds and the Earth's Radiant Energy System (CERES) scanner, the TRMM Microwave Imager (TMI), and the Visible and InfraRed Scanner (VIRS), to evaluate the variations of tropical deep convective systems (DCS) with sea surface temperature (SST) and precipitation. This study finds that DCS precipitation efficiency increases with SST at a rate of approx. 2%/K. Despite increasing rainfall efficiency, the cloud areal coverage rises with SST at a rate of about 7%/K in the warm tropical seas. There, the boundary layer moisture supply for deep convection and the moisture transported to the upper troposphere for cirrus-anvil cloud formation increase by approx. 6.3%/K and approx. 4.0%/K, respectively. The changes in cloud formation efficiency, along with the increased transport of moisture available for cloud formation, likely contribute to the large rate of increasing DCS areal coverage. Although no direct observations are available, the increase of cloud formation efficiency with rising SST is deduced indirectly from measurements of changes in the ratio of DCS ice water path and boundary layer water vapor amount with SST. Besides the cloud areal coverage, DCS cluster effective sizes also increase with precipitation. Furthermore, other cloud properties, such as cloud total water and ice water paths, increase with SST. These changes in DCS properties will produce a negative radiative feedback for the earth's climate system due to strong reflection of shortwave radiation by the DCS. These results significantly differ from some previous hypothesized dehydration scenarios for warmer climates, and have great potential in testing current cloud-system resolving models and convective parameterizations of general circulation models

Analysis and Fault-Tolerant Control for Dual-Three-Phase PMSM Based on Virtual Healthy Model

Dual-three-phase permanent magnet synchronous machines (DTP-PMSMs) are famous for their fault-tolerant capability. However, the complex modeling, high copper loss, and torque ripple under postfault operation limit their further application. In this article, a fault-tolerant control (FTC) strategy is developed for DTP-PMSMs under the open-phase fault (OPF) with straightforward modeling and smooth output torque. The virtual healthy DTP-PMSM model, where the coordinate transformation, the modulation strategy, and the controller structure remain unchanged under OPF, is adopted in the proposed FTC scheme. And the current references are derived in sinusoidal waves with minimum copper loss. The inaccurate transmission of control signals under OPF is also focused on. Comprehensive theoretical analysis shows the relationship between the controller output voltage and the actual stator voltage should be considered in the proposed FTC strategy; otherwise, distortion in torque and current will be introduced. The voltage compensation is utilized to compensate for the voltage difference and ensure the smooth torque output. Besides, a quasi proportional resonance controller is designed to further suppress the residual torque ripple. The proposed strategy will not induce complex implementation and heavy computation burden. The simulation and experimental results prove the analysis and the effectiveness of the proposed strategy

A novel approach for prognosis of lithium-ion battery based on geometrical features and data-driven model

Lithium-ion (Li-ion) batteries are widely used in such devices as today’s electrical vehicles, consumer electronics, and unmanned aerial vehicles, and will play a key role in the future. Unexpected Li-ion battery abnormities may result in serious inconvenience and enormous replacement costs. Thus, the diagnostic and prognostic methods play important roles in battery replacement scheduling, maintenance strategy development, and battery failure precaution, However, many published methods are unsuitable for both battery capacity and end-of-discharge. In this paper, a hybrid ensemble approach, integrating k-fold cross validation (k-CV) and genetic algorithm with back-propagation neural network (GA-BPNN), is proposed for capacity and end-of-discharge of Li-ion battery prognostics combined with geometrical features. Geometrical features extracted from charge-discharge cycles of Li-ion batteries are set as the inputs of the neural network. K-fold cross validation is introduced to determine the number of BPNN hidden layer neurons, genetic algorithm is used to initialize and optimize the connection weights and thresholds of BPNN. By the critical geometrical feature extraction and the ensemble BPNN model with k-fold cross validation and genetic algorithm, accurate battery capacity and end-of discharge are accomplished, making the proposed model can potentially be used for real-time estimate for the conditions given in this article. The performance of the proposed approach is demonstrated by using actual Li-ion battery data, which is supplied by the NASA Ames Research Center database