Climate impact studies often require the selection of a small number of climate scenarios. Ideally, a subset would have simulations that both (1) appropriately represent the range of possible futures for the variable/s most important to the impact under investigation and (2) come from global climate models (GCMs) that provide...
Climate impact studies often require the selection of a small number of climate scenarios. Ideally, a subset would have simulations that both (1) appropriately represent the range of possible futures for the variable/s most important to the impact under investigation and (2) come from global climate models (GCMs) that provide...
Monthly temperature and precipitation data from 41 global climate models (GCMs)
of the Coupled Model Intercomparison Project Phase 5 (CMIP5) were compared to
observations for the 20th century, with a focus on the United States Pacific Northwest
(PNW) and surrounding region. A suite of statistics, or metrics, was calculated, that...
Monthly temperature and precipitation data from 41 global climate models (GCMs)
of the Coupled Model Intercomparison Project Phase 5 (CMIP5) were compared to
observations for the 20th century, with a focus on the United States Pacific Northwest
(PNW) and surrounding region. A suite of statistics, or metrics, was calculated, that...
Monthly temperature and precipitation data from 41 global climate models (GCMs)
of the Coupled Model Intercomparison Project Phase 5 (CMIP5) were compared to
observations for the 20th century, with a focus on the United States Pacific Northwest
(PNW) and surrounding region. A suite of statistics, or metrics, was calculated, that...
Probabilistic event attribution (PEA) is an important tool for assessing the contribution of climate change to extreme weather events. Here, PEA is applied to explore the climate attribution of recent extreme heat events in California’s Central Valley. Heat waves have become progressively more severe due to increasing relative humidity and...
Computing resources donated by volunteers have generated the first superensemble of regional climate model results, in which the Hadley Centre Regional Model, version 3P (HadRM3P), and Hadley Centre Atmosphere Model, version 3P (HadAM3P), were implemented for the western United States at 25-km resolution. Over 136,000 valid and complete 1-yr runs...
Simulations from a regional climate model (RCM) as part of a superensemble experiment were compared with observations of surface meteorological variables over the western United States. The RCM is the Hadley Centre Regional Climate Model, version 3, with improved physics parameterizations (HadRM3P) run at 25-km resolution and nested within the...
Climate impact studies often require the selection of a small number of climate scenarios. Ideally, a subset would have simulations that both (1) appropriately represent the range of possible futures for the variable/s most important to the impact under investigation and (2) come from global climate models (GCMs) that provide...
This work advances a unified approach to process-based hydrologic modeling to enable controlled and systematic evaluation of multiple model representations (hypotheses) of hydrologic processes and scaling behavior. Our approach, which we term the Structure for Unifying Multiple Modeling Alternatives (SUMMA), formulates a general set of conservation equations, providing the flexibility...