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Shunlin Liang, Jie Cheng, Kun Jia, Bo Jiang, Qiang Liu, Zhiqiang Xiao, Yunjun Yao, Wenping Yuan, Xiaotong Zhang, Xiang Zhao, and Ji Zhou

Abstract:

The Global Land Surface Satellite (GLASS) product suite currently contains 12 products, including leaf area index, fraction of absorbed photosynthetically active radiation, fraction of green vegetation coverage, gross primary production, broadband albedo, broadband longwave emissivity, downward shortwave radiation and photosynthetically active radiation, land surface temperature, downward and upwelling thermal radiation, all-wave net radiation, and evapotranspiration. These products are generated from the Advanced Very High Resolution Radiometer and Moderate Resolution Imaging Spectroradiometer satellite data. Their unique features include long-term temporal coverage (many from 1981 to the present), high spatial resolutions of the surface radiation products (1 km and 0.05°), spatial continuities without missing pixels, and high quality and accuracy based on extensive validation using in situ measurements and intercomparisons with other existing satellite products. Moreover, the GLASS products are based on robust algorithms that have been published in peer-reviewed literature. Herein, we provide an overview of the algorithm development, product characteristics, and some preliminary applications of these products. We also describe the next steps, such as improving the existing GLASS products, generating more climate data records (CDRs), broadening product dissemination, and fostering their wider utilization. The GLASS products are freely available to the public.

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Xiang Li, Dongliang Yuan, Zheng Wang, Yao Li, Corry Corvianawatie, Dewi Surinati, Asep Sandra, Ahmad Bayhaqi, Praditya Avianto, Edi Kusmanto, Dirham Dirhamsyah, and Zainal Arifin

Abstract

The ocean currents in the Halmahera Sea are studied using a subsurface mooring deployed in the Jailolo Strait from November 2015 to October 2017. The subtidal currents of the mooring measurements are characterized by a two-layer system, with the current variability below about 200 m in opposite phases to that in the upper layer. The mean along-strait velocity (ASV) is toward the Indonesian seas in the whole water column, producing an estimated mean transport of 2.44 ± 0.42 Sv (1 Sv ≡ 106 m3 s−1). The errors of the transport calculation based on the single mooring measurements are estimated to be less than 15% using simulations of high-resolution ocean models. A weak current is observed to flow northward during 2017 at the bottom of the strait. The ASV variability is found to be dominated by an annual cycle both in the upper and lower layers. The total transport, however, is dominated by semiannual variability because of the cancelation of the annual transports in the upper and lower layers. The variability of the transport is suggested to be driven by the pressure difference between the Pacific Ocean and the Indonesian seas, as evidenced by the agreement between the satellite pressure gradient and the two-layer transports. The transport of the Jailolo Strait during the 2015/16 super El Niño is found to be nearly the same as that during the 2016 La Niña, suggesting that the interannual variability of the transport is much smaller than the seasonal cycle.

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Ke Huang, Dongxiao Wang, Ming Feng, Weiqing Han, Gengxin Chen, Chaojiao Sun, Xiaolin Zhang, Qiang Xie, Weiqiang Wang, Qinyan Liu, and Jinglong Yao

Abstract

The first baroclinic mode Rossby wave is known to be of critical importance to the annual sea level variability in the southern tropical Indian Ocean (STIO; 0°–20°S, 50°–115°E). In this study, an analysis of continuously stratified linear ocean model reveals that the second baroclinic mode also has significant contribution to the annual sea level variability (as high as 81% of the first baroclinic mode). The contributions of residual high-order modes (3 ≤ n ≤ 25) are much less. The superposition of low-order (first and second) baroclinic Rossby waves (BRWs) primarily contribute to the high energy center of sea level variability at ~10°S in the STIO and the vertical energy penetration below the seasonal thermocline. We have found that 1) the low-order BRWs, having longer zonal wavelengths and weaker damping, can couple more efficiently to the local large-scale wind forcing than the high-order modes and 2) the zonal coherency of the Ekman pumping results in the latitudinal energy maximum of low-order BRWs. Overall, this study extends the traditional analysis to suggest the characteristics of the second baroclinic mode need to be taken into account in interpreting the annual variability in the STIO.

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Shuwen Tan, Larry J. Pratt, Dongliang Yuan, Xiang Li, Zheng Wang, Yao Li, Corry Corvianawatie, Dewi Surinati, Asep S. Budiman, and Ahmad Bayhaqi

Abstract

Hydrographic measurements recently acquired along the thalweg of the Lifamatola Passage combined with historical moored velocity measurements immediately downstream of the sill are used to study the hydraulics, transport, mixing, and entrainment in the dense overflow. The observations suggest that the mean overflow is nearly critical at the mooring site, suggesting that a weir formula may be appropriate for estimating the overflow transport. Our assessment suggests that the weir formulas corresponding to a rectangular, triangular, or parabolic cross section all result in transports very close to the observation, suggesting their potential usage in long-term monitoring of the overflow transport or parameterizing the transport in numerical models. Analyses also suggest that deep signals within the overflow layer are blocked by the shear flow from propagating upstream, whereas the shallow wave modes of the full-depth continuously stratified flow are able to propagate upstream from the Banda Sea into the Maluku Sea. Strong mixing is found immediately downstream of the sill crest, with Thorpe-scale-based estimates of the mean dissipation rate within the overflow up to 1.1 × 10−7 W kg−1 and the region-averaged diapycnal diffusivity within the downstream overflow in the range of 2.3 × 10−3 to 10.1 × 10−3 m2 s−1. Mixing in the Lifamatola Passage results in 0.6–1.2-Sv (1 Sv ≡ 106 m3 s−1) entrainment transport added to the overflow, enhancing the deep-water renewal in the Banda Sea. A bulk diffusivity coefficient estimated in the deep Banda Sea yields 1.6 × 10−3 ± 5 × 10−4 m2 s−1, with an associated downward turbulent heat flux of 9 W m−2.

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Metcrax 2006

Meteorological Experiments in Arizona's Meteor Crater

C. David Whiteman, Andreas Muschinski, Sharon Zhong, David Fritts, Sebastian W. Hoch, Maura Hahnenberger, Wenqing Yao, Vincent Hohreiter, Mario Behn, Yonghun Cheon, Craig B. Clements, Thomas W. Horst, William O. J. Brown, and Steven P. Oncley

The Meteor Crater Experiment (METCRAX 2006) was conducted in October 2006 at Arizona's Meteor Crater to investigate stable boundary layer evolution in a topographically uncomplicated basin surrounded by the nearly homogeneous plain of the Colorado Plateau. The two goals of the experiment were 1) to investigate the microscale and mesoscale structure and evolution of the stable boundary layer in the crater and its surroundings and 2) to determine whether atmospheric seiches or standing waves are produced inside the crater. This article provides an overview of the scientific goals of the experiment; summarizes the research measurements, the crater topography, and the synoptic meteorology of the study period; and presents initial analysis results. Analyses show that nighttime temperature inversions form frequently in the crater and that they are often perturbed by internal wave motions. Nighttime cooling produces a shallow (15–30 m deep) surface-based inversion that is surmounted by a horizontally homogeneous near-isothermal layer that extends all the way to the rim, where a second inversion extends above rim level. Seiches are sometimes present on the crater floor. The diurnal propagation of shadows from the crater rim produces important spatial differences in the surface radiation budget and thus the timing of the slope flow transition, and the crater atmosphere is often perturbed during nighttime by a southwesterly mesoscale drainage flow.

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Dongliang Yuan, Xiang Li, Zheng Wang, Yao Li, Jing Wang, Ya Yang, Xiaoyue Hu, Shuwen Tan, Hui Zhou, Adhitya Kusuma Wardana, Dewi Surinati, Adi Purwandana, Mochamad Furqon Azis Ismail, Praditya Avianto, Dirham Dirhamsyah, Zainal Arifin, and Jin-Song von Storch

Abstract

The Maluku Channel is a major opening of the eastern Indonesian Seas to the western Pacific Ocean, the upper-ocean currents of which have rarely been observed historically. During December 2012–November 2016, long time series of the upper Maluku Channel transport are measured successfully for the first time using subsurface oceanic moorings. The measurements show significant intraseasonal-to-interannual variability of over 14 Sv (1 Sv ≡ 106 m3 s−1) in the upper 300 m or so, with a mean transport of 1.04–1.31 Sv northward and a significant southward interannual change of over 3.5 Sv in the spring of 2014. Coincident with the interannual transport change is the Mindanao Current, choked at the entrance of the Indonesian Seas, which is significantly different from its climatological retroflection in fall–winter. A high-resolution numerical simulation suggests that the variations of the Maluku Channel currents are associated with the shifting of the Mindanao Current retroflection. It is suggested that the shifting of the Mindanao Current outside the Sulawesi Sea in the spring of 2014 elevates the sea level at the entrance of the Indonesian Seas, which drives the anomalous transport through the Maluku Channel. The results suggest the importance of the western boundary current nonlinearity in driving the transport variability of the Indonesian Throughflow.

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Sha Zhou, Junyi Liang, Xingjie Lu, Qianyu Li, Lifen Jiang, Yao Zhang, Christopher R. Schwalm, Joshua B. Fisher, Jerry Tjiputra, Stephen Sitch, Anders Ahlström, Deborah N. Huntzinger, Yuefei Huang, Guangqian Wang, and Yiqi Luo

Abstract

Terrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land–Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. In this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25 models in the three MIPs. First, terrestrial carbon storage dynamics were characterized by a three-dimensional (3D) model output space with coordinates of carbon residence time, net primary productivity (NPP), and carbon storage potential. The latter represents the potential of an ecosystem to lose or gain carbon. This space can be used to measure how and why model output differs. Models with a nitrogen cycle generally exhibit lower annual NPP in comparison with other models, and mostly negative carbon storage potential. Second, a transient traceability framework was used to decompose any given carbon cycle model into traceable components and identify the sources of model differences. The carbon residence time (or NPP) was traced to baseline carbon residence time (or baseline NPP related to the maximum carbon input), environmental scalars, and climate forcing. Third, by applying a variance decomposition method, the authors show that the intermodel differences in carbon storage can be mainly attributed to the baseline carbon residence time and baseline NPP (>90% in the three MIPs). The three techniques developed in this study offer a novel approach to gain more insight from existing MIPs and can point out directions for future MIPs. Since this study is conducted at the global scale for an overview on intermodel differences, future studies should focus more on regional analysis to identify the sources of uncertainties and improve models at the specified mechanism level.

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Dan Fu, Justin Small, Jaison Kurian, Yun Liu, Brian Kauffman, Abishek Gopal, Sanjiv Ramachandran, Zhi Shang, Ping Chang, Gokhan Danabasoglu, Katherine Thayer-Calder, Mariana Vertenstein, Xiaohui Ma, Hengkai Yao, Mingkui Li, Zhao Xu, Xiaopei Lin, Shaoqing Zhang, and Lixin Wu

Abstract

The development of high-resolution, fully-coupled, regional Earth system model systems is important for improving our understanding of climate variability, future projections, and extreme events at regional scales. Here we introduce and present an overview of the newly-developed Regional Community Earth System Model (R-CESM). Different from other existing regional climate models, R-CESM is based on the Community Earth System Model version 2 (CESM2) framework. We have incorporated the Weather Research and Forecasting (WRF) model and Regional Ocean Modeling System (ROMS) into CESM2 as additional components. As such, R-CESM can be conveniently used as a regional dynamical downscaling tool for the global CESM solutions or/and as a standalone high-resolution regional coupled model. The user interface of R-CESM follows that of CESM, making it readily accessible to the broader community. Among countless potential applications of R-CESM, we showcase here a few preliminary studies that illustrate its novel aspects and value. These include: 1) assessing the skill of R-CESM in a multi-year, high-resolution, regional coupled simulation of the Gulf of Mexico; 2) examining the impact of WRF and CESM ocean-atmosphere coupling physics on tropical cyclone simulations; and 3) a convection-permitting simulation of submesoscale ocean-atmosphere interactions. We also discuss capabilities under development such as i) regional refinement using a high-resolution ROMS nested within global CESM; and ii) “online” coupled data assimilation. Our open-source framework (publicly available at https://github.com/ihesp/rcesm1) can be easily adapted to a broad range of applications that are of interest to the users of CESM, WRF, and ROMS.

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Yaohui Li, Xing Yuan, Hongsheng Zhang, Runyuan Wang, Chenghai Wang, Xianhong Meng, Zhiqiang Zhang, Shanshan Wang, Yang Yang, Bo Han, Kai Zhang, Xiaoping Wang, Hong Zhao, Guangsheng Zhou, Qiang Zhang, Qing He, Ni Guo, Wei Hou, Cunjie Zhang, Guoju Xiao, Xuying Sun, Ping Yue, Sha Sha, Heling Wang, Tiejun Zhang, Jinsong Wang, and Yubi Yao

Abstract

A major experimental drought research project entitled “Mechanisms and Early Warning of Drought Disasters over Northern China” (DroughtEX_China) was launched by the Ministry of Science and Technology of China in 2015. The objective of DroughtEX_China is to investigate drought disaster mechanisms and provide early-warning information via multisource observations and multiscale modeling. Since the implementation of DroughtEX_China, a comprehensive V-shape in situ observation network has been established to integrate different observational experiment systems for different landscapes, including crops in northern China. In this article, we introduce the experimental area, observational network configuration, ground- and air-based observing/testing facilities, implementation scheme, and data management procedures and sharing policy. The preliminary observational and numerical experimental results show that the following are important processes for understanding and modeling drought disasters over arid and semiarid regions: 1) the soil water vapor–heat interactions that affect surface soil moisture variability, 2) the effect of intermittent turbulence on boundary layer energy exchange, 3) the drought–albedo feedback, and 4) the transition from stomatal to nonstomatal control of plant photosynthesis with increasing drought severity. A prototype of a drought monitoring and forecasting system developed from coupled hydroclimate prediction models and an integrated multisource drought information platform is also briefly introduced. DroughtEX_China lasted for four years (i.e., 2015–18) and its implementation now provides regional drought monitoring and forecasting, risk assessment information, and a multisource data-sharing platform for drought adaptation over northern China, contributing to the global drought information system (GDIS).

Open access
William B. Willis, William E. Eichinger, John H. Prueger, Cathleen J. Hapeman, Hong Li, Michael D. Buser, Jerry L. Hatfield, John D. Wanjura, Gregory A. Holt, Alba Torrents, Sean J. Plenner, Warren Clarida, Stephen D. Browne, Peter M. Downey, and Qi Yao

Abstract

Pollutant emissions to the atmosphere commonly derive from nonpoint sources that are extended in space. Such sources may contain area, volume, line, or a combination of emission types. Currently, point measurements, often combined with models, are the primary means by which atmospheric emission rates are estimated from extended sources. Point measurement arrays often lack in spatial and temporal resolution and accuracy. In recent years, lidar has supplemented point measurements in agricultural research by sampling spatial ensembles nearly instantaneously. Here, a methodology using backscatter data from an elastic scanning lidar is presented to estimate emission rates from extended sources. To demonstrate the approach, a known amount of particulate matter was released upwind of a vegetative environmental buffer, a barrier designed to intercept emissions from animal production facilities. The emission rate was estimated downwind of the buffer, and the buffer capture efficiency (percentage of particles captured) was calculated. Efficiencies ranged from 21% to 74% and agree with the ranges previously published. A comprehensive uncertainty analysis of the lidar methodology was performed, revealing an uncertainty of 20% in the emission rate estimate; suggestions for significantly reducing this uncertainty in future studies are made. The methodology introduced here is demonstrated by estimating the efficiency of a vegetative buffer, but it can also be applied to any extended emission source for which point samples are inadequate, such as roads, animal feedlots, and cotton gin operations. It can also be applied to any pollutant for which a lidar system is configured, such as particulate matter, carbon dioxide, and ammonia.

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