Results 51 to 60 of about 830 (198)

The Untapped Hydropower Potential of World's Cities

Earth's Future, Volume 14, Issue 5, May 2026.
Abstract Many large cities around the world experience frequent power outages and yet have an abundance of tall buildings and experience rainfall. This represents a unique and scalable opportunity for cities to capture the intermittent rainwater at high elevation and convert the potential energy into electricity for rechargeable batteries at street ...
Shahzaib Khan, Zarar N. Hossain, Sarath Suresh, Faisal Hossain   +3 more
wiley   +1 more source

Multiple Spatial and Temporal Scales Evaluation of Eight Satellite Precipitation Products in a Mountainous Catchment of South China

Remote Sensing, 2023
Satellite precipitation products (SPPs) have emerged as an important information source of precipitation with high spatio-temporal resolutions, with great potential to improve catchment water resource management and hydrologic modelling, especially in ...
Binbin Guo, Tingbao Xu, Qin Yang, Jing Zhang, Zhong Dai, Yunyuan Deng, Jun Zou   +6 more
doaj   +1 more source

Single‐Cell and Spatial Omics: Methods and Applications

MedComm, Volume 7, Issue 4, April 2026.
Systematically summarized the breakthrough sequencing technologies and computational methods for single‐cell and spatial omics across multiple omics layers, including genome, epigenome, transcriptome, proteome, and metabolome. State‐of‐the‐art methods for multi‐omics integration, cross‐modal integration, and cross‐scale integration were reviewed, with ...
Xiaoping Cen, Xiaolan Huang, Enjin Deng, Xue Gong, Na Tan, Jifeng Ye, Yin Wang, Roland Eils, Qun Luo, Yixue Li, Fangfang Qu   +10 more
wiley   +1 more source

Evaluation of TRMM/GPM Blended Daily Products over Brazil

Remote Sensing, 2018
The precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (named TMPA and TMPA-RT for the near real-time version) are widely used both in research and in operational forecasting.
José Roberto Rozante, Daniel A. Vila, Júlio Barboza Chiquetto, Alex de A. Fernandes, Débora Souza Alvim   +4 more
doaj   +1 more source

Urban Impacts on Precipitation in the Greater Ho Chi Minh City Metropolitan Area, Vietnam

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 6, 28 March 2026.
Abstract Urban impacts on precipitation have been extensively studied in mid‐latitude developed countries. However, despite the recent rapid urban development, such studies focusing on Southeast Asian cities remain limited. This study evaluated urban impacts on precipitation in the Greater Ho Chi Minh City Metropolitan area (GHCM) by multi‐case ...
Shun Hasebe, Hiroyuki Kusaka, Nobuyasu Suzuki, Thanh Ngo‐Duc   +3 more
wiley   +1 more source

Machine Learning‐Based Forecasting of Ice Water Path for Storm Detection and Tracking Using Geostationary Infrared and Passive Microwave Data

Earth and Space Science, Volume 13, Issue 3, March 2026.
Abstract This study presents a proof of concept for a storm Detection, Delineation, and Tracking (DDT) method based on the vertical integral of condensed water and ice content—namely the Ice Water Path (IWP). Traditional DDT methods rely solely on regularly sampled variables, such as brightness temperatures, which do not directly capture storm ...
Livia J. Leganés, Sai Prasanth, Andrés Navarro, Joe Turk, Gyuwon Lee, Ziad Haddad, Jennie Bukowski, Peter Marinescu, Itinderjot Singh, Susan C. van den Heever, Francisco J. Tapiador   +10 more
wiley   +1 more source

Evaluasi Satellite Precipitation Product (GSMaP, CHIRPS, dan IMERG) di Kabupaten Lampung Selatan

, 2022
The availability of rainfall data is an important requirement in various activities. The limitations of observational data make the satellit precipitation product (SPPs) as an alternative.
Oktaviana, Ade Ayu, Pratama, Alvin, Agiel, Hayim Muhammad   +2 more
core   +1 more source

A Machine Learning Approach for Improving the Accuracy of Gridded Precipitation With Uncertainty Quantification

International Journal of Climatology, Volume 46, Issue 1, January 2026.
A novel machine learning (ML) approach combining extreme gradient boosting with quantile regression is used to create Vietnam Precipitation with Uncertainty (VNpu). Our VNpu dataset outperforms individual input products, benchmark interpolation methods and an existing gauge‐based product, particularly for heavy and extreme rainfall events. ABSTRACT The
Vinh Ngoc Tran, Manh‐Hung Le, Tam V. Nguyen, Trong Dieu Hien Le, Hung T. T. Nguyen, Hong Xuan Do, Binh Quang Nguyen, Doan Van Binh, Tu Hoang Le, Hung Thanh Pham, Hoang Tran, Thanh Duc Dang, John D. Bolten, Tan Phan‐Van, Thanh Ngo‐Duc, Venkataraman Lakshmi   +15 more
wiley   +1 more source

Validation of Hourly GSMAP and Ground Base Estimate of Precipitation for Flood Monitoring in Kumamoto, Japan [PDF]

, 2017
GSMaP (Global Satellite Mapping Precipitation) satellite rainfall estimates are evaluated at the hourly time scale and spatial resolution 0.1 degree latitude x 0.1 degree longitude.
Aryastana, Putu, Setiawati, Martiwi Diah, Miura, Fusanori   +2 more
core  

GENERACIÓN DE UN PRODUCTO DE PRECIPITACIÓN DIARIA PARA LA CUENCA CHOQUEYAPU EN LA CIUDAD DE LA PAZ

Investigación & Desarrollo
En este estudio se ha generado un producto precipitación diaria para el periodo 2021 a 2023 como resultado de la combinación de estaciones locales e información de sensores remotos.
Jhonatan E. Ureña, Fedra V. Alcalá, Oliver C. Saavedra   +2 more
doaj   +1 more source