Zobrazeno 1 - 10
of 2 673
pro vyhledávání: '"Statistical Downscaling"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract In recent years, the uncertainty of weather conditions and the impact of future climate change on building energy assessment has received increasing attention. As an important part of these studies, several types of methods for generating st
Externí odkaz:
https://doaj.org/article/f63c831cfcca4da592de64586eccfffb
Publikováno v:
آب و توسعه پایدار, Vol 11, Iss 2, Pp 15-26 (2024)
The climate system is very complex and has made the modeling and predicting/projecting face many challenges. Although climate variability may be detected and identified through a time series of observations, it cannot express the interaction of vario
Externí odkaz:
https://doaj.org/article/7ff3ef14e9674ccb84c7b5b4798cb593
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 23, Pp n/a-n/a (2024)
Abstract While deep‐learning downscaling algorithms can generate fine‐scale climate projections cost‐effectively, it is unclear how effectively they extrapolate to unobserved climates. We assess the extrapolation capabilities of a deterministic
Externí odkaz:
https://doaj.org/article/108e438a842f41b5b5ec21281eaf6a33
Publikováno v:
Journal of Water and Climate Change, Vol 15, Iss 6, Pp 2628-2647 (2024)
Recognizing the differential impacts of climate change across geographical scales, this study emphasizes the importance of statistical downscaling. Using Gene Expression Programming (GEP) and Linear Genetic Programming (LGP), statistical downscaling
Externí odkaz:
https://doaj.org/article/73e6080fea0b4ed0a19cec973f3121cf
Publikováno v:
Journal of Water and Climate Change, Vol 15, Iss 4, Pp 1772-1796 (2024)
This study examines two downscaling techniques, convolutional neural networks (CNNs) and feedforward neural networks for predicting precipitation and temperature, alongside statistical downscaling as a benchmark model. The daily climate predictors we
Externí odkaz:
https://doaj.org/article/56bd63f7aa27486998d5ee30d09f006c
Publikováno v:
Journal of Agrometeorology, Vol 26, Iss 3 (2024)
Rainfall is a climate element with high variations in space and time scales, so it is not easy to predict. One way to predict rainfall is statistical downscaling (SD). SD can predict local rainfall based on Global Circulation Model (GCM) data. The De
Externí odkaz:
https://doaj.org/article/82e7d6273bbd455f83a7ec04cf9236d9
Autor:
Leila Rahimi, Mushfiqul Hoque, Ebrahim Ahmadisharaf, Nasrin Alamdari, Vasubandhu Misra, Ana Carolina Maran, Shih‐Chieh Kao, Amir AghaKouchak, Rocky Talchabhadel
Publikováno v:
Earth's Future, Vol 12, Iss 8, Pp n/a-n/a (2024)
Abstract Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these impacts is challenging due to the coarse spatial resolution of global climate models
Externí odkaz:
https://doaj.org/article/89e53a8803774db6b51e2bf414282361
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 4646-4662 (2024)
High-resolution bioclimatic data are crucial to providing fine-scaled insights into biodiversity assessment, forestry, and agricultural management. Existing global bioclimatic datasets often exhibit kilometer-level coarse resolution or have miss the
Externí odkaz:
https://doaj.org/article/4926cc321d3f4b468f3e19962050c74b
Publikováno v:
Remote Sensing, Vol 16, Iss 23, p 4367 (2024)
Soil moisture (SM) is a crucial factor in land-atmosphere interactions and climate systems, affecting surface energy, water budgets, and weather extremes. In the Three-River-Source Region (TRSR) of China, rapid climate change necessitates precise SM
Externí odkaz:
https://doaj.org/article/e2c869a64da64d6e91e93439f2cfcb69
Autor:
Marie-Dominique Leroux, François Bonnardot, Samuel Somot, Antoinette Alias, Stephason Kotomangazafy, Abdoul-Oikil Saïd Ridhoine, Philippe Veerabadren, Vincent Amélie
Publikováno v:
Climate Services, Vol 34, Iss , Pp 100491- (2024)
Climate change is a global challenge necessitating adaptation at the local level. Small island developing states (SIDS) in the southwest Indian Ocean (SWIO) basin are particularly vulnerable and already facing significant challenges due to climate va
Externí odkaz:
https://doaj.org/article/380f291dcb88453bb2abeb5acb0f4f21