Results 161 to 170 of about 41,752 (176)

Statistical downscaling of GRACE products to improve spatial resolution

2021
<p>The satellite missions Gravity Recovery And Climate Experiment (GRACE) and GRACE Follow-On record the change in the gravity field, which is then related to water mass redistribution near the Earth's surface and disseminated as monthly fields of Total Water Storage Change (TWSC).
Nico Sneeuw, Bramha Dutt Vishwakarma, Jinwei Zhang   +2 more
openaire   +1 more source

Regression-based downscaling of spatial variability for hydrologic applications

Journal of Hydrology, 2005
There is an obvious imbalance between, on the one hand, the importance of spatio-temporal variability of precipitation for river flows and, on the other, their representation in current empirical downscaling models that are applied for climate scenarios. The imperfect variability results from incomplete forcing of the large scales. The last IPCC report
Bürger, G., Chen, Y.
openaire   +2 more sources

Towards spatially coherent statistical downscaling

2013
Towards spatially coherent statistical downscaling.
Radanovics, S., Vidal, Jean-Philippe, Sauquet, Eric, Bontron, G., Ben Daoud, A.   +4 more
openaire   +1 more source

Spatial downscaling of IMERG precipitation estimates using statistical techniques

2023
The aim of this study was to spatially downscale the Precipitation Estimates (PEs) from the Global Precipitation Measurement (GPM) mission, using the Integrated Multi-satellite Retrievals for GPM (IMERG), over a complex region in Greece. For this purpose, the Multivariate Linear Regression (MLR) and the Residual Correction (RC) techniques were utilized,
Stavros Stathopoulos, Alexandra Gemitzi
openaire   +1 more source

Spatially explicit downscaling and projection of population in mainland China

Science of The Total Environment
Spatially explicit population data is critical to investigating human-nature interactions, identifying at-risk populations, and informing sustainable management and policy decisions. Most long-term global population data have three main limitations: 1) they were estimated with simple scaling or trend extrapolation methods which are not able to capture ...
Xu, Wenru, Zhou, Yuyu, Taubenböck, Hannes, Stokes, Eleanor C., Zhu, Zhengyuan, Lai, Feilin, Li, Xuecao, Zhao, Xia   +7 more
openaire   +2 more sources

Stochastic weather generators for climate‐change downscaling, part II: multivariable and spatially coherent multisite downscaling

WIREs Climate Change, 2012
AbstractThis paper continues Part I (Wilks DS. Use of stochastic weather generators for precipitation downscaling. WIRES Clim Change 2010, 1(6):898–907) of a two‐part review on statistical downscaling of climate changes using parametric ‘weather generators’, which treated only precipitation downscaling at individual locations.
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Quantifying spatially explicit uncertainty in empirically downscaled climate data

International Journal of Climatology
AbstractEcological simulations including forest and vegetation growth models require climate inputs that match the resolution and extent of the process being modelled. Climate inputs are often derived at resolutions coarser than the scale of many ecosystem processes. Machine learning models can be trained to spatially downscale climate data to fine (30 
Nicole C. Inglis, Taylor R. Brown, Ashley B. Cale, Theodore Hartsook, Adriano Matos, Johanson Onyegbula, Jonathan A. Greenberg   +6 more
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A review of spatial downscaling of satellite precipitation products

2020
<p>Precipitation is an important component of the water cycle. Precipitation is characterized with high temporal and spatial variability. Accurate measurements of precipitation at high spatiotemporal resolution are essential for many applications in the fields of hydrology, meteorology and ecology.
Zheng Duan, Cheng Chen, Hongkai Gao, Jian Peng   +3 more
openaire   +1 more source

Downscaling spatial structure for the analysis of epidemiological data

Computers, Environment and Urban Systems, 2008
Abstract Many widely accessible forms of socio-economic and public health data have been subjected to some form of spatial aggregation. Polygonal units, such as US Census tabulation areas, political boundaries, transportation analysis zones and ZIP codes, are often used to represent the spatial extent of these data.
T.C. Matisziw, T.H. Grubesic, H. Wei
openaire   +1 more source

Coherent predictand areas for spatially coherent precipitation downscaling

2013
Statistical downscaling aims at finding relationships between local precipitation (predictand) and large-scale predictor fields, in various contexts, from medium-term forecasting to climate change impact studies. For distributed hydrological modelling the downscaled precipitation spatial fields have furthermore to be coherent over possibly large river ...
Radanovics, S., Vidal, Jean-Philippe, Sauquet, Eric, Ben Daoud, A., Bontron, G.   +4 more
openaire   +1 more source