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The reduction of the runoff to lake has become a common phenomenon of the inland lakes in northwest China, and the quantitative calculation of the driving factors affecting the runoff change has always been a challenge in lake research. In this pursuit, the present study was performed on Lake Daihai as an example, based on the relevant data from 1960 to 2018. The quantitative calculations of the runoff driving factors of Lake Daihai from 1982 to 2004 and from 2004 to 2017 were based on the slope change ratio of cumulative quantity (SCRCQ). It was concluded that human activities were the main factors affecting runoff change after 1982. The SCRCQ method was improved, which could carry out the quantitative calculations on the driving factors affecting the runoff change of the Lake Daihai from 1961 to 2017 on a yearly basis. The results show that the dominant factor of runoff changes in Lake Daihai was found to be the climate change before 1975, and it changed into human activities after 1975. Finally, based on the comparative analysis of the results of SCRCQ and improved SCRCQ, the advantages of improved SCRCQ were discussed. In addition, the reasons for the variation of the runoff to lake dominated by different factors in different periods for Lake Daihai were analyzed. Key Points: This paper analyzes the influence of climate change and human activities on the change in runoff volume of Lake Daihai according to the slope change ratio of cumulative quantity (SCRCQ)The SCRCQ method was improved, which could carry out the quantitative calculations on the driving factors affecting the runoff change of the Lake Daihai from 1961 to 2017 on a yearly basisThe reasons for the variation of the runoff to lake dominated by different factors in different periods for Lake Daihai were analyzed [ABSTRACT FROM AUTHOR]

Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) is a multinational program initiated in 1997 in the tropical Atlantic to improve our understanding and ability to predict ocean‐atmosphere variability. PIRATA consists of a network of moored buoys providing meteorological and oceanographic data transmitted in real time to address fundamental scientific questions as well as societal needs. The network is maintained through dedicated yearly cruises, which allow for extensive complementary shipboard measurements and provide platforms for deployment of other components of the Tropical Atlantic Observing System. This paper describes network enhancements, scientific accomplishments and successes obtained from the last 10 years of observations, and additional results enabled by cooperation with other national and international programs. Capacity building activities and the role of PIRATA in a future Tropical Atlantic Observing System that is presently being optimized are also described. Plain Language Summary: Long data records are essential for improving our understanding of the weather and climate, their variability and predictability, and how the climate may change in the future in response to anthropogenic greenhouse gas emissions. Climate variability in the tropical Atlantic Ocean has strong impacts on the coastal climate in particular and, consequently, the economies of the surrounding regions. Since 1997, the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) program has maintained a network of moored buoys in the tropical Atlantic in order to provide instantaneous high‐quality data to research scientists and weather forecasters around the world. This paper describes PIRATA successes in terms of scientific discoveries and observing technology enhancements. Perspectives are also provided on PIRATA's role in the future Tropical Atlantic Observing System, currently under design, that will consist of a variety of coordinated measurements from satellites, ships, buoys, and other ocean technologies. Key Points: We describe the sustained tropical Atlantic observing system PIRATA maintained through a multinational cooperative program in ocean scienceMajor scientific results and accomplishments obtained from the last 10 years are presentedThe potential role of PIRATA in a future Tropical Atlantic Observing System is described [ABSTRACT FROM AUTHOR]

The variation of polar sea ice is an indicator of polar environmental change, which plays an important role in the study of regional and global climate change. In this paper, the latest sea ice data sets from the European Space Agency Climate Change Initiative were firstly combined to comprehensively analyze the spatial and temporal variation of Arctic sea ice concentration (SIC) and sea ice thickness (SIT) from 2002 to 2017. The results show that during this period, the SIC of the Kara Sea and the Barents Sea decreases the most significantly, reaching −1.11%·year−1. The Arctic annual average sea ice extent (SIE) and sea ice area (SIA) exhibit noticeable decreasing trends, reaching −0.0592 × 106 km·year−1 and −0.0628 × 106 km·year−1, respectively. Both of Arctic SIE and SIA vary seasonally, and they reach the minimum values of 4.97 × 106 km2 and 3.96 × 106 km2 in September and the maximum values of 14.58 × 106 km2 and 13.35 × 106 km2 in March, respectively. Moreover, the Arctic SIE and SIA anomaly series from 2002 to 2017 were analyzed based on the linear regression method. It is found the most noticeable decreasing trends of the Arctic SIE and SIA are from July to October. The maximum variation of the SIE is −1.06 × 106 km2(10a)−1, and the maximum variation of the SIA is −1.09 × 106 km2(10a)−1. The Arctic SIE and SIA present the smallest decreasing trends from April to May, which are −0.19 × 106 km2(10a)−1 and −0.2 × 106 km2(10a)−1, respectively. The Arctic SIT also displays a pronounced decreasing trend with −0.015 m·year−1 in autumn and −0.018 m·year−1 in winter. The annual average SIT reaches a minimum of 1.28 m in 2013 and a maximum of 1.66 m in 2005. Particularly, the SIT of the Hudson Bay decreases the most significantly, reaching −0.051 m·year−1. Finally, the Arctic average SIT was tested by the Mann‐Kendall method. It is found that the SIT has a sudden change in 2007, from a slight increase in 2003–2007 to a significant decrease in 2007–2017. Overall, the decreasing trend of the Arctic sea ice (both SIC and SIT) is significant in the past decade. These findings can contribute to future research on polar regions and global climate change. Key Points: We analyzed the whole and regional variation of Arctic sea ice by combining use of the latest sea ice concentration and sea ice thickness data sets from European Space AgencyThe sea ice concentration in the Barents Sea and the Kara Sea and the sea ice thickness in the Hudson Bay decreased the most obviouslyThe sea ice thickness has a sudden change in 2007 based on Mann‐Kendall mutation test [ABSTRACT FROM AUTHOR]

Trend turning (or trend change) is a type of structural change that is common in climate data, and methods for detecting it in time series with multiple turning‐points need to be developed. A recently developed method for this, the running slope difference (RSD) t‐test, examines trend differences in sub‐series of the sample time series to identify the trend turning‐points. In this paper, we use Monte Carlo simulation to evaluate this method's detection ability. Evaluation results show the method to be an effective tool for detecting trend turning time series and identify three major advantages of the RSD t‐test: ability to detect multiple turning‐points, capacity to detect all three types of trend turning, and great performance of reducing false alarm rate. Key Points: The RSD t‐test is a recently developed method for detecting trend turning in climate time seriesMonte Carlo simulation is designed to evaluate the detection ability of the RSD t‐test comprehensivelyThe RSD t‐test has capacity to detect multiple turning‐points of three turning types and great performance of reducing false alarm rate [ABSTRACT FROM AUTHOR]

Abstract: In the use of integrated assessment models to determine how the economy is affected by climate change, the bidirectional coupling of Earth system model with the integrated assessment model is needed. In the context of coupled problems in human‐Earth systems, two issues persist: spatial and temporal scale matching. For spatial scale matching, this paper proposes the area weight conversion method, a gridding method for calculations to accord with the grid of the Earth's system mode, where administrative data cells are transformed into grid data by “pregridding” and “postgridding.” For temporal scale matching, the temporal scale of the economic statistics was shortened to 1 year to render it consistent with the Earth system model. Using the area weight conversion method, grid processing was performed in terms of population and Gross Domestic Product for all provinces of China and every country of the world, respectively. The results showed that the characteristics of gridding population and Gross Domestic Product data were consistent with their actual distributions, that is, the credibility of gridding was high. The temporal matching treatment refined to the year and the spatial matching treatment following gridding met the overall requirements of coupling. Moreover, they provide a foundation for the coupling of the human‐Earth system model. [ABSTRACT FROM AUTHOR]

The Gao Fen 7 (GF‐7) satellite is China's first submeter, high‐resolution Earth observation and remote sensing satellite for natural resource monitoring, land surveying, and other industrial applications in China. The GF‐7 laser altimeter system is the successor of the ZiYuan3‐02 (ZY3‐02 satellite) laser altimeter. The key objective of the GF‐7 laser altimetry system is to provide high‐precision ground elevation control points that assist in optical imaging to achieve 1:10000 mapping in China. This paper introduces the GF‐7 laser altimeter system payload specifications, mission objectives, in‐orbit calibration plan, data products, and service policy. In the future, the GF‐7 laser altimeter system will also serve multidisciplinary and professional applications through its precise elevation measurement capabilities. In addition, it will play a vital role in Earth observation, climate change monitoring, and environmental protection. Plain Language Summary: Spaceborne laser altimeters are widely used for planet surface measurements due to their high range accuracy. This paper details the GF‐7 laser altimeter system, which is China's first formal spaceborne laser altimeter system for Earth observations. This laser altimeter system will be used in scientific experiments for the first time in China. GF‐7 laser altimeter system is the first to be equipped with laser footprint cameras and a laser optical axis surveillance camera. The GF‐7 satellite will be launched in October 2019, and the scientific experiments will begin in November. All the data it gets will be released globally. In the future, these data will help researchers from different disciplines around the world to conduct scientific experiments and monitor the Earth's resources. The GF‐7 laser altimeter system will play a vital role in global climate change monitoring, environmental protection, disaster warning, etc. The content presented in this article will help students, researchers, and engineers in the fields of geography, oceanography, and glaciology understand and use GF‐7 satellite laser data, which will be of great significance. Key Points: A new laser altimeter system design consisting of a laser altimeter, two laser footprint cameras, and a laser optical axis surveillance camera equipped with the Gao Fen 7 satellite is introducedThe application of the Gao Fen 7 laser altimeter system including ground control point measurement, polar ice sheet monitoring, and forest biomass estimation is presentedScientific experiments on the Gao Fen 7 laser altimeter system to be performed in November 2019 are given. Six levels of data products are listed and will be provided to users worldwide [ABSTRACT FROM AUTHOR]