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The Earth is experiencing unprecedented climate change. Vegetation phenology has already showed strong response to the global warming, which alters mass and energy fluxes on terrestrial ecosystems. With technology and method developments in remote sensing, computer science and citizen science, many recent phenology-related studies have been focused on macrophenology. In this perspective, we 1) rev
The magnitude, direction and cause of precipitation changes across the Indo-Pacific Warm Pool (IPWP) during the Last Glacial Maximum (LGM) remain elusive. In particular, it is still inconclusive whether tropical or extra-tropical factors controlled such precipitation changes. Determining the spatio-temporal distribution of precipitation in the IPWP during the LGM is a valid strategy to address thi
Future global temperature change will have significant effects on society and ecosystems. Earth system models (ESM) are the primary tools to explore future climate change. However, ESMs have great uncertainty and often run at a coarse spatial resolution (usually about 2°). Accurate high-spatial-resolution temperature dataset are needed to improve our understanding of temperature variations and for
Dissolved Organic Carbon (DOC) in inland waters plays an essential role in the global carbon cycle and has significant public health effects. Machine learning (ML) together with remote sensing has emerged as a powerful and promising combination to quantify water quality parameters from space. However, inland water sample data for DOC is limited. Hence, little is known about the potential to quanti
The atmospheric CO2 growth rate (CGR) variability is largely controlled by tropical temperature fluctuations. The sensitivity of CGR to tropical temperature (γCGRT) has strongly increased since 1960, but here we show that this trend has ceased. Here, we use the long-term CO2 records from Mauna Loa and the South Pole to compute CGR, and show that γCGRT increased by 200% from 1960–1979 to 1979–2000
Ground-level fine particulate matter (PM2.5) and ozone (O3) are air pollutants that can pose severe health risks. Surface PM2.5 and O3 concentrations can be monitored from satellites, but most retrieval methods retrieve PM2.5 or O3 separately and disregard the shared information between the two air pollutants, for example due to common emission sources. Using surface observations across China span
Accurate and timely mapping of inundation extents during flood periods is essential for disaster evaluation and development of rescue strategies. With unique advantages over the optical sensors (e.g., little effect of clouds, and observations at day and night), Synthetic aperture radar (SAR) sensors provide an important data source for mapping inundation, particularly during flood periods. Freely
To train well-performing generalizing neural networks, sufficiently large and diverse datasets are needed. Collecting data while adhering to privacy legislation becomes increasingly difficult and annotating these large datasets is both a resource-heavy and time-consuming task. An approach to overcome these difficulties is to use synthetic data since it is inherently scalable and can be automatical
BACKGROUND: To outline how the training program and work situation of residents in Obstetrics and Gynecology (OB-GYN) was affected by the pandemic and to illuminate how residents experienced these changes.METHODS: As part of the COVID-19 in Pregnancy and Early Childhood Staff (COPE Staff) cohort study, between January and May 2021, all participating residents were invited to answer a 28-question o
Autumn phenology plays a key role in regulating the terrestrial carbon and water balance and their feedbacks to the climate. However, the mechanisms underlying autumn phenology are still poorly understood, especially in subtropical forests. In this study, we extracted the autumn photosynthetic transition dates (APTD) in subtropical China over the period 2003–2017 based on a global, fine-resolution
Extracting speaker-dependent paralinguistic information out of a person's voice, provides an opportunity for adaptive behaviour related to speaker information in speech processing applications. For instance, in audio-based conversational applications, adapting responses to the attributes of the correspondent is an integral part in making the conversations effective. Two speaker attributes that hum
Lake ice loss has been detected worldwide due to recent climate warming, yet spatially and temporally detailed information on the changes in global ice phenology does not exist. Here, we build a global lake ice phenology database comprising three lake ice phenologies—freeze-up, break-up, and ice duration—for each year across two centuries (1900–2099). The timing of all three phenologies experience
The effects of insect herbivores on forest functioning are not well understood even though they can have important impacts on ecosystem processes by intercepting foliage before resorption and depositing nutrient-rich materials to the soil. In this thesis, I investigated the impact and drivers of insect folivores on carbon (C), nitrogen (N), phosphorus (P) and silica (Si) cycling in broadleaf fores
This study focused on improving the performance of the near real-time Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) Early Run (IMERG-E) product based on a newly developed bias-correction scheme, LSCDF. The LSCDF was established by integrating the mean-based Linear Scaling (LS) and quantile-mapping Cumulative Distribution Function (CDF) matching approaches. The
Agricultural ecosystem water use efficiency (WUE) is an important indicator reflecting carbon-water coupling, but its control mechanisms in managed fields remain unclear. In order to reveal the influencing factors of WUE in the agricultural field under mulched drip irrigation (DM), we carried out the 8-year continuous observations in a maize field from Northwestern China. The structural equation m
Multi-source merging is an established tool for improving large-scale precipitation estimates. Existing merging frameworks typically use gauge-based precipitation error statistics and neglect the inter-dependence of various precipitation products. However, gauge-observation uncertainties at daily and sub-daily time scales can bias merging weights and yield sub-optimal precipitation estimates, part
Glacio-hydrological modeling is a key task for assessing the influence of snow and glaciers on water resources, essential for water resources management. The present study aims to enhance a conceptual hydrological model (namely Glacial Snow Melt (GSM)) by data-driven and swarm computing for enhancing the accuracy of rainfall runoff prediction. The proposed framework combines the conceptual hydrolo
This work presents an assessment of the precipitation deficit in the São Francisco River Basin (SFRB) based on temporal, seasonal and regional analyses of two decades of precipitation data products derived from satellite missions launched since 1997. The temporal analyses were performed by means of three 3-month SPI time series, consisting of 250 values each derived from TRMM, CHIRPS and PERSIANN-
