Climate adaptation as a control problem: Review and perspectives on dynamic water resources planning under uncertainty
Climate change introduces substantial uncertainty to water resources planning and raises
the key question: when, or under what conditions, should adaptation occur? A number of …
the key question: when, or under what conditions, should adaptation occur? A number of …
[HTML][HTML] Use of the autoregressive integrated moving average (ARIMA) model to forecast near-term regional temperature and precipitation
Y Lai, DA Dzombak - Weather and Forecasting, 2020 - journals.ametsoc.org
A data-driven approach for obtaining near-term (2–20 years) regional temperature and
precipitation projections utilizing local historical observations was established in this study to …
precipitation projections utilizing local historical observations was established in this study to …
Statistical machine learning for power flow analysis considering the influence of weather factors on photovoltaic power generation
It is generally accepted that the impact of weather variation is gradually increasing in
modern distribution networks with the integration of high-proportion photovoltaic (PV) power …
modern distribution networks with the integration of high-proportion photovoltaic (PV) power …
A weather‐regime‐based stochastic weather generator for climate vulnerability assessments of water systems in the western United States
Vulnerability‐based frameworks are increasingly used to better understand water system
performance under climate change. This work advances the use of stochastic weather …
performance under climate change. This work advances the use of stochastic weather …
Climate-Agriculture-Modeling and Decision Tool (CAMDT): A software framework for climate risk management in agriculture
Seasonal climate forecasts (SCFs) have received a lot of attention for climate risk
management in agriculture. The question is, how can we use SCFs for informing decisions …
management in agriculture. The question is, how can we use SCFs for informing decisions …
The advanced meteorology explorer: a novel stochastic, gridded daily rainfall generator
Synthetic rainfall simulations from stochastic models are commonly used for water resource
management, as they are able to provide a wider range of meteorological conditions than …
management, as they are able to provide a wider range of meteorological conditions than …
Implementing generative adversarial network (GAN) as a data-driven multi-site stochastic weather generator for flood frequency estimation
Precipitation is a key driving factor of hydrologic modeling for impact studies. However, there
are challenges due to limited long-term data availability and complex parameterizations of …
are challenges due to limited long-term data availability and complex parameterizations of …
Assessing statistical downscaling in Argentina: Daily maximum and minimum temperatures
R Balmaceda‐Huarte, ML Bettolli - International Journal of …, 2022 - Wiley Online Library
Empirical statistical downscaling (ESD) under the perfect prognosis approach was carried
out to simulate daily maximum (Tx) and minimum temperatures (Tn) in 101 meteorological …
out to simulate daily maximum (Tx) and minimum temperatures (Tn) in 101 meteorological …
Energy performance of cool roofs under the impact of actual weather data
Weather conditions account for a major source of deviation between simulation results and
actual energy performance of buildings. Typical meteorological year (TMY) weather data are …
actual energy performance of buildings. Typical meteorological year (TMY) weather data are …
A linked modelling framework to explore interactions among climate, soil water, and land use decisions in the Argentine Pampas
In flat environments, groundwater is relatively shallow, tightly associated with surface water
and climate, and can have either positive and negative impacts on natural and human …
and climate, and can have either positive and negative impacts on natural and human …