Results 71 to 80 of about 41,752 (176)

Statistical Downscaling Method for Vegetation Optical Depth Based on NDVI

应用气象学报
The microwave vegetation index, known as vegetation optical depth (VOD), is a dimensionless vegetation index.VOD is an important parameter for retrieving soil moisture and surface biomass.
Wang Xinyu, Fang Shibo, Han Jiahao
doaj   +1 more source

Improving Precipitation Estimation Using Convolutional Neural Network [PDF]

, 2019
Precipitation process is generally considered to be poorly represented in numerical weather/climate models. Statistical downscaling (SD) methods, which relate precipitation with model resolved dynamics, often provide more accurate precipitation estimates
AghaKouchak, A, Hsu, K, Pan, B, Sorooshian, S   +3 more
core  

An Enhanced Archive Facilitating Climate Impacts and Adaptation Analysis [PDF]

, 2014
We describe the expansion of a publicly available archive of downscaled climate and hydrology projections for the United States. Those studying or planning to adapt to future climate impacts demand downscaled climate model output for local or regional ...
Arnold, James W., Brekke, Levi, Cayan, Daniel R., Dettinger, Michael D., Duffy, Philip B., Long, J., Maurer, Edwin P., Pruitt, Tom, Thrasher, Bridget   +8 more
core   +1 more source

The role of empirical space-weather models (in a world of physics-based numerical simulations) [PDF]

, 2018
Advanced forecasting of space weather requires prediction of near-Earth solar-wind conditions on the basis of remote solar observations. This is typically achieved using numerical magnetohydrodynamic models initiated by photospheric magnetic field ...
Barnard, Mathew J. Owens, Owens, Pete Riley, Siscoe, Tim Horbury   +5 more
core   +1 more source

Research on downscaling method of the enhanced TROPOMI solar-induced chlorophyll fluorescence data

Geocarto International
Solar-induced chlorophyll fluorescence (SIF) is the release of plant energy during photosynthesis, which is significantly superior to the vegetation index in the characterization of vegetation growth.
Xiaoping Lu, Guosheng Cai, Xiangjun Zhang, Haikun Yu, Qinggang Zhang, Xiaoxuan Wang, Yushi Zhou, Yingying Su   +7 more
doaj   +1 more source

Performance Evaluation of Downscaling Sentinel-2 Imagery for Land Use and Land Cover Classification by Spectral-Spatial Features

Remote Sensing, 2017
Land Use and Land Cover (LULC) classification is vital for environmental and ecological applications. Sentinel-2 is a new generation land monitoring satellite with the advantages of novel spectral capabilities, wide coverage and fine spatial and temporal
Hongrui Zheng, Peijun Du, Jike Chen, Junshi Xia, Erzhu Li, Zhigang Xu, Xiaojuan Li, Naoto Yokoya   +7 more
doaj   +1 more source

Temporal and spatial downscaling for solar radiation

35 pages, 14 ...
Bailey, Maggie, Nychka, Doug, Sengupta, Manajit, Yang, Jaemo, Bandyopadhyay, Soutir   +4 more
openaire   +2 more sources

A multiscale geographically weighted regression kriging method for spatial downscaling of satellite-based ozone datasets

Frontiers in Environmental Science
Accurate monitoring of ozone (O3) concentrations by remote sensing is essential for achieving pollution control and ecological protection. However, the existing O3 remote sensing data with a low spatial resolution do not facilitate fine-grained studies ...
Shuang Cheng, Guoqiao Zhang, Xuexi Yang, Bingfeng Lei   +3 more
doaj   +1 more source

Spatial and Temporal Downscaling of TRMM Precipitation with Novel Algorithms Spatial and Temporal Downscaling of TRMM Precipitation with Novel Algorithms [PDF]

, 2020
Abstract: Tropical Rainfall Measuring Mission (TRMM) satellite products constitute valuable precipitation datasets over regions with sparse rain gauge networks. Downscaling is an effective approach to estimating the precipitation over ungauged areas with high spatial resolution. However, a large bias and low resolution of original TRMM satellite images
Zhang, Huihui, Loáiciga, Hugo A, Ha, Da, Du, Qingyun   +3 more
openaire   +1 more source

Differences between Machine Learning and Traditional Downscaling Method in Processing Summer Meteorological Elements in the Yellow River Basin

Gaoyuan qixiang
Global Climate Models （GCMs） are the primary tools currently used to predict future climate change； however， their coarse spatial resolution limits their ability to assess localized impacts of climate change.To address this issue， statistical downscaling
Han CHEN, Xiaodan GUAN, Tingting MA
doaj   +1 more source