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Jun Yang
,
Weitao Lu
,
Ying Ma
, and
Wen Yao

Abstract

Cloud detection is a basic research for achieving cloud-cover state and other cloud characteristics. Because of the influence of sunlight, the brightness of sky background on the ground-based cloud image is usually nonuniform, which increases the difficulty for cirrus cloud detection, and few detection methods perform well for thin cirrus clouds. This paper presents an effective background estimation method to eliminate the influence of variable illumination conditions and proposes a background subtraction adaptive threshold method (BSAT) to detect cirrus clouds in visible images for the small field of view and mixed clear–cloud scenes. The BSAT algorithm consists of red-to-blue band operation, background subtraction, adaptive threshold selection, and binarization. The experimental results show that the BSAT algorithm is robust for all types of cirrus clouds, and the quantitative evaluation results demonstrate that the BSAT algorithm outperforms the fixed threshold (FT) and adaptive threshold (AT) methods in cirrus cloud detection.

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Min Min
,
Lu Zhang
,
Peng Zhang
, and
Zhigang Yao

Abstract

The plane-parallel atmosphere as an underlying assumption in physics is appropriately used in the rigorous numerical simulation of the atmospheric radiative transfer model (RTM) with incident solar light. The solar irradiance is a constant with the plane-parallel assumption, which is attributed to the small difference in the distance between any point on Earth’s surface to the sun. However, at night, atmospheric RTMs use the moon as a unique incident light source in the sky. The Earth–moon distance is approximately 1/400 of the Earth–sun distance. Thus, the varying Earth–moon distance on Earth’s surface can influence the top of atmosphere (TOA) lunar irradiance for the plane-parallel atmosphere assumption. In this investigation, we observe that the maximum biases in Earth–moon distance and day/night band lunar irradiance at the TOA are ±1.7% and ±3.3%, respectively, with the plane-parallel assumption. According to our calculations, this bias effect on the Earth–moon distance and lunar irradiance shows a noticeable spatiotemporal variation on a global scale that can impact the computational accuracy of an RTM at night. In addition, we also developed a fast and portable correction algorithm for the Earth–moon distance within a maximum bias of 18 km or ±0.05%, because of the relatively low computational efficiency and the large storage space necessary for the standard ephemeris computational software. This novel correction algorithm can be easily used or integrated into the atmospheric RTM at night.

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Moran Zhuang
,
Anmin Duan
,
Riyu Lu
,
Puxi Li
, and
Jinglong Yao

Abstract

The Indochina Peninsula (ICP) has a critical effect in shaping the Asian summer monsoon (ASM). However, the seasonal responses of the ASM to the ICP are not fully understood. This study employs a 1° atmospheric general circulation model to examine the different contributions of the ICP’s orography and land–sea contrast to the ASM during the early and late summer. Results indicate that the orographic effect increases South Asian rainfall and reduces the rainfall over the South China Sea (SCS) and North China in early summer, but its influence on monsoonal circulation and rainfall is limited to East Asia in late summer. The impact of the ICP’s land–sea contrast is basically opposite in the two summer stages. With the presence of the ICP, SCS rainfall is enhanced but South Asian rainfall is weakened in early summer. In late summer, however, rainfall from the ICP to the northwestern Pacific is strikingly reduced, accompanied by intensified rainfall over South Asia. Relatively, the orographic effect seems to be more important in modulating the South Asian monsoon in early summer, while the land–sea contrast is dominant in strengthening the SCS monsoon and suppressing the northwest Pacific monsoon via the interaction between the induced local circulation and multilevel ASM subsystems. In late summer, the orographic effect on the ASM is much weaker compared to the land–sea contrast, which plays a critical role by shifting the subtropical high southwestward and through the “thermal adaption” feedback mechanism. Therefore, the orographic impact of the ICP on the ASM differs from that of the land–sea contrast in the two summer stages.

Open access
Sheng Huang
,
Weijiang Li
,
Jiahong Wen
,
Mengru Zhu
,
Yao Lu
, and
Na Wu

Abstract

Driven by both climate change and urbanization, extreme rainfall events are becoming more frequent and having an increasing impact on urban commuting. Using hourly rainfall data and “metro” origin–destination (OD) flow data in Shanghai, China, this study uses the Prophet time series model to calculate the predicted commuting flows during rainfall events and then quantifies the spatiotemporal variations of commuting flows due to rainfall at station and OD levels. Our results show the following: 1) In general, inbound commuting flows at metro stations tend to decrease with hourly rainfall intensity, varying across station types. The departure time of commuters is usually delayed by rainfall, resulting in a significant stacking effect of inbound flows at metro stations, with a pattern of falling followed by rising. The sensitivity of inbound flows to rainfall varies at different times, high at 0700 and 1700 LT and low at 0800, 0900, 1800, and 1900 LT because of the different levels of flexibility of departure time. 2) Short commuting OD flows (≤15 min) are more affected by rainfall, with an average increase of 7.3% and a maximum increase of nearly 35%, whereas long OD flows (>15 min) decrease slightly. OD flows between residential and industrial areas are more affected by rainfall than those between residential and commercial (service) areas, exhibiting a greater fluctuation of falling followed by rising. The sensitivity of OD flows to rainfall varies across metro lines. The departure stations of rainfall-sensitive lines are mostly distributed in large residential areas that rely heavily on the metro in the morning peak hours and in large industrial parks and commercial centers in the evening peak hours. Our findings reveal the spatiotemporal patterns of commuting flows resulting from rainfall at a finer scale, which provides a sound basis for spatial and temporal response strategies. This study also suggests that attention should be paid to the surges and stacking effects of commuting flows at certain times and areas during rainfall events.

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Jun Yang
,
Weitao Lyu
,
Ying Ma
,
Yijun Zhang
,
Qingyong Li
,
Wen Yao
, and
Tianshu Lu

Abstract

The macroscopic characteristics of clouds in the Tibetan Plateau are crucial to understanding the local climatic conditions and their impact on the global climate and water vapor cycle. In this study, the variations of cloud cover and cloud types are analyzed by using total-sky images of two consecutive years in Shigatse, Tibetan Plateau. The results show that the cloud cover in Shigatse presents a distinct seasonal difference that is characterized by low cloud cover in autumn and winter and high cloud cover in summer and spring. July is the month with the largest cloud coverage, and its average cloud cover exceeds 75%. The probability of clouds in the sky is the lowest in November, with an average cloud cover of less than 20%. The diurnal variations of cloud cover in different months also have considerable differences. Specifically, cloud cover is higher in the afternoon than that in the morning in most months, whereas the cloud cover throughout the day varies little from July to September. The dominant cloud types in different months are also not the same. The proportion of clear sky is large in autumn and winter. Stratiform cloud occupies the highest percentage in March, April, July, and August. The probability of emergence of cirrus is highest in May and June. The Shigatse region has clear rainy and dry seasons, and correlation analysis between precipitation and clouds shows that the largest cumulative precipitation, the highest cloud cover, and the highest proportion of stratiform clouds occur simultaneously in July.

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Ning Lu
,
Kevin E. Trenberth
,
Jun Qin
,
Kun Yang
, and
Ling Yao

Abstract

Long-term trends in precipitable water (PW) are an important component of climate change assessments for the Tibetan Plateau (TP). PW products from Moderate Resolution Imaging Spectroradiometer (MODIS) are able to provide good spatial coverage of PW over the TP but limited in time coverage, while the meteorological stations in the TP can estimate long-term PW but unevenly distributed. To detect the decadal trend in PW over the TP, Bayesian inference theory is used to construct long-term and spatially continuous PW data for the TP based on the station and MODIS observations. The prior information on the monthly-mean PW from MODIS and the 63 stations over the TP for 2000–06 is used to get the posterior probability knowledge that is utilized to build a Bayesian estimation model. This model is then operated to estimate continuous monthly-mean PW for 1970–2011 and its performance is evaluated using the monthly MODIS PW anomalies (2007–11) and annual GPS PW anomalies (1995–2011), with RMSEs below 0.65 mm, to demonstrate that the model estimation can reproduce the PW variability over the TP in both space and time. Annual PW series show a significant increasing trend of 0.19 mm decade−1 for the TP during the 42 years. The most significant PW increase of 0.47 mm decade−1 occurs for 1986–99 and an insignificant decrease occurs for 2000–11. From the comparison of the PW data from JRA-55, ERA-40, ERA-Interim, MERRA, NCEP-2, and ISCCP, it is found that none of them are able to show the actual long-term trends and variability in PW for the TP as the Bayesian estimation.

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

Abstract

Many meteorological and air-quality models require land characteristics as inputs. A field experiment was conducted to study the surface energy budget of a rice paddy in Taiwan. During the day, the energy balance ratio measured by an eddy covariance (EC) system was found to be 95% after considering the photosynthetic and local advected heat fluxes. The observations by the EC system suggest that the Bowen ratio was about 0.18 during the daytime. The EC system also measured the daytime absorbed carbon dioxide flux. The equivalent photosynthetic energy flux was about 1% of the net solar radiation. A reference table describing the land characteristics of rice paddies for use in meteorological and air-quality models is listed that shows that the albedo and the Bowen ratio measured over rice paddies were lower than those listed in many state-of-the-art models. This study proposes simulating latent heat flux by assigning proper values for canopy resistance rather than by assigning constant values for Bowen ratio or surface moisture availability. The diurnal pattern of the canopy resistance of the rice paddy was found to be “U” shaped. Daytime canopy resistance was observed to be 87 s m−1, and a high canopy resistance (∼900 s m−1) should be assigned during nighttime periods.

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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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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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Fan Yang
,
Qing He
,
Jianping Huang
,
Ali Mamtimin
,
Xinghua Yang
,
Wen Huo
,
Chenglong Zhou
,
Xinchun Liu
,
Wenshou Wei
,
Caixia Cui
,
Minzhong Wang
,
Hongjun Li
,
Lianmei Yang
,
Hongsheng Zhang
,
Yuzhi Liu
,
Xinqian Zheng
,
Honglin Pan
,
Lili Jin
,
Han Zou
,
Libo Zhou
,
Yongqiang Liu
,
Jiantao Zhang
,
Lu Meng
,
Yu Wang
,
Xiaolin Qin
,
Yongjun Yao
,
Houyong Liu
,
Fumin Xue
, and
Wei Zheng

Abstract

As the second-largest shifting sand desert worldwide, the Taklimakan Desert (TD) represents the typical aeolian landforms in arid regions as an important source of global dust aerosols. It directly affects the ecological environment and human health across East Asia. Thus, establishing a comprehensive environment and climate observation network for field research in the TD region is essential to improve our understanding of the desert meteorology and environment, assess its impact, mitigate potential environmental issues, and promote sustainable development. With a nearly 20-yr effort under the extremely harsh conditions of the TD, the Desert Environment and Climate Observation Network (DECON) has been established completely covering the TD region. The core of DECON is the Tazhong station in the hinterland of the TD. Moreover, the network also includes 4 satellite stations located along the edge of the TD for synergistic observations, and 18 automatic weather stations interspersed between them. Thus, DECON marks a new chapter of environmental and meteorological observation capabilities over the TD, including dust storms, dust emission and transport mechanisms, desert land–atmosphere interactions, desert boundary layer structure, ground calibration for remote sensing monitoring, and desert carbon sinks. In addition, DECON promotes cooperation and communication within the research community in the field of desert environments and climate, which promotes a better understanding of the status and role of desert ecosystems. Finally, DECON is expected to provide the basic support necessary for coordinated environmental and meteorological monitoring and mitigation, joint construction of ecologically friendly communities, and sustainable development of central Asia.

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