Of mast and mean: differentialtemperature cue makes mast seeding
... fit (as is explicit in the DT model). One or both variables thus might be dropped from candidate models (e.g. Selas et al. 2002), consistent with their being rarely reported in the literature. In this article, we show that the DT model provides a much better fit to seedfall data across a range of di ...
... fit (as is explicit in the DT model). One or both variables thus might be dropped from candidate models (e.g. Selas et al. 2002), consistent with their being rarely reported in the literature. In this article, we show that the DT model provides a much better fit to seedfall data across a range of di ...
Uncertainties in future projections of extreme precipitation in the
... Whether such a relationship exists in other coupled GCMs under increased greenhouse warming has not so far been addressed. This paper aims to extend the work of Turner and Slingo (2009) using the CMIP3 multi-model database to test whether changes to the spatial pattern of subseasonal extremes can be ...
... Whether such a relationship exists in other coupled GCMs under increased greenhouse warming has not so far been addressed. This paper aims to extend the work of Turner and Slingo (2009) using the CMIP3 multi-model database to test whether changes to the spatial pattern of subseasonal extremes can be ...
Ensemble modeling, uncertainty and robust predictions
... the recognized uncertainty about future conditions. By the early 1990s, both the National Center for Environmental Prediction in the United States and the European Center for Medium Range Weather Forecasting in the United Kingdom were employing this ensemble approach operationally, developing distin ...
... the recognized uncertainty about future conditions. By the early 1990s, both the National Center for Environmental Prediction in the United States and the European Center for Medium Range Weather Forecasting in the United Kingdom were employing this ensemble approach operationally, developing distin ...
Odds ratios from logistic model results for a categorical predictor EXP
... PEONY model to predict risk of emergency admission to hospital over the next year Now implemented in NHS Tayside as part of Virtual Wards management of LTC ...
... PEONY model to predict risk of emergency admission to hospital over the next year Now implemented in NHS Tayside as part of Virtual Wards management of LTC ...
Projected 21st century decrease in marine productivity: a multi
... MPIM, and CSM1.4) of the four Earth System models used in this study. They provide detailed information on the performance of these three models under current climate conditions and compare modeled physical (temperature, salinity, mixed layer depth, meridional overturning, ENSO variability) and biol ...
... MPIM, and CSM1.4) of the four Earth System models used in this study. They provide detailed information on the performance of these three models under current climate conditions and compare modeled physical (temperature, salinity, mixed layer depth, meridional overturning, ENSO variability) and biol ...
Wind stress curl
... Influence of small scales on mean climate and variability • TIWs and impact on mean climate in tropical Pacific (may be partly model specific here) ...
... Influence of small scales on mean climate and variability • TIWs and impact on mean climate in tropical Pacific (may be partly model specific here) ...
Large-scale effects of climate change on water resources in Sweden
... Future changes in water resources Daily values of several modelled variables describing the water resources have been aggregated to average annual values and plotted on maps with high spatial resolution to analyse emerging geographical patterns for Europe and Sweden. The results for the reference ...
... Future changes in water resources Daily values of several modelled variables describing the water resources have been aggregated to average annual values and plotted on maps with high spatial resolution to analyse emerging geographical patterns for Europe and Sweden. The results for the reference ...
Ruti et al. BAMS - Med
... budget (2003 heat wave and relative Mediterranean warming is a good example), while long term ocean water mass formation and variability can influence the atmospheric water input (the relevance of this process has been highlighted for surrounding areas such as Sahel, see Fontaine et al., 2010). Here ...
... budget (2003 heat wave and relative Mediterranean warming is a good example), while long term ocean water mass formation and variability can influence the atmospheric water input (the relevance of this process has been highlighted for surrounding areas such as Sahel, see Fontaine et al., 2010). Here ...
Forecasting global climate change: A scientific approach Kesten C
... We found that the IPCC procedures violated all 19 of the Golden Rule guidelines that are relevant to long-term climate forecasting, including “be conservative when forecasting trends if the series is variable or unstable” and “be conservative when forecasting trends if the short and long-term trend ...
... We found that the IPCC procedures violated all 19 of the Golden Rule guidelines that are relevant to long-term climate forecasting, including “be conservative when forecasting trends if the series is variable or unstable” and “be conservative when forecasting trends if the short and long-term trend ...
Arctic sea ice decline: Faster than forecast
... show declining Arctic ice cover over this period. However, depending on the time window for analysis, none or very few individual model simulations show trends comparable to observations. If the multi-model ensemble mean time series provides a true representation of forced change by greenhouse gas ( ...
... show declining Arctic ice cover over this period. However, depending on the time window for analysis, none or very few individual model simulations show trends comparable to observations. If the multi-model ensemble mean time series provides a true representation of forced change by greenhouse gas ( ...
Arctic sea ice decline: Faster than forecast
... show declining Arctic ice cover over this period. However, depending on the time window for analysis, none or very few individual model simulations show trends comparable to observations. If the multi-model ensemble mean time series provides a true representation of forced change by greenhouse gas ( ...
... show declining Arctic ice cover over this period. However, depending on the time window for analysis, none or very few individual model simulations show trends comparable to observations. If the multi-model ensemble mean time series provides a true representation of forced change by greenhouse gas ( ...
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Slide 1
... “Warming of the climate system is unequivocal” “The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen and concentrations of greenhouse gases have increased.” Intergovernmental Panel on Climate Change, AR5 WGI September 2013 ...
... “Warming of the climate system is unequivocal” “The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen and concentrations of greenhouse gases have increased.” Intergovernmental Panel on Climate Change, AR5 WGI September 2013 ...
Integrated Assessment Model of Climate Change: The AIM Approach Yuzuru M
... by chemical reactions, which are calculated within the AIM/climate. We divided these chemicals into two groups based on their reaction rates: long-life chemicals, such as CFCs and halons, and short-life chemicals such as ozone and OH radicals. Pseudo-equilibrium state is assumed for the latter group ...
... by chemical reactions, which are calculated within the AIM/climate. We divided these chemicals into two groups based on their reaction rates: long-life chemicals, such as CFCs and halons, and short-life chemicals such as ozone and OH radicals. Pseudo-equilibrium state is assumed for the latter group ...
numerical simulation dynamical model of three
... Introduction The current technological advance has made it possible for humans to disturb the environmental balance in nature that may cause immense damages, such as species extinction or starvation. Therefore, understanding the behaviour of the interaction between the species may help biologists an ...
... Introduction The current technological advance has made it possible for humans to disturb the environmental balance in nature that may cause immense damages, such as species extinction or starvation. Therefore, understanding the behaviour of the interaction between the species may help biologists an ...
Efficient Learning of Entity and Predicate Embeddings for Link
... in G, partitioning them into nb batches of the same size, and then iterating over such batches. A single pass over all triples in G is called an epoch. Then, for each triple y in the batch, the algorithm generates a corrupted triple ỹ uniformly sampled from CG (y): this leads to a set T of observed ...
... in G, partitioning them into nb batches of the same size, and then iterating over such batches. A single pass over all triples in G is called an epoch. Then, for each triple y in the batch, the algorithm generates a corrupted triple ỹ uniformly sampled from CG (y): this leads to a set T of observed ...
Numerical weather prediction
Numerical weather prediction uses mathematical models of the atmosphere and oceans to predict the weather based on current weather conditions. Though first attempted in the 1920s, it was not until the advent of computer simulation in the 1950s that numerical weather predictions produced realistic results. A number of global and regional forecast models are run in different countries worldwide, using current weather observations relayed from radiosondes, weather satellites and other observing systems as inputs.Mathematical models based on the same physical principles can be used to generate either short-term weather forecasts or longer-term climate predictions; the latter are widely applied for understanding and projecting climate change. The improvements made to regional models have allowed for significant improvements in tropical cyclone track and air quality forecasts; however, atmospheric models perform poorly at handling processes that occur in a relatively constricted area, such as wildfires.Manipulating the vast datasets and performing the complex calculations necessary to modern numerical weather prediction requires some of the most powerful supercomputers in the world. Even with the increasing power of supercomputers, the forecast skill of numerical weather models extends to about only six days. Factors affecting the accuracy of numerical predictions include the density and quality of observations used as input to the forecasts, along with deficiencies in the numerical models themselves. Post-processing techniques such as model output statistics (MOS) have been developed to improve the handling of errors in numerical predictions.A more fundamental problem lies in the chaotic nature of the partial differential equations that govern the atmosphere. It is impossible to solve these equations exactly, and small errors grow with time (doubling about every five days). Present understanding is that this chaotic behavior limits accurate forecasts to about 14 days even with perfectly accurate input data and a flawless model. In addition, the partial differential equations used in the model need to be supplemented with parameterizations for solar radiation, moist processes (clouds and precipitation), heat exchange, soil, vegetation, surface water, and the effects of terrain. In an effort to quantify the large amount of inherent uncertainty remaining in numerical predictions, ensemble forecasts have been used since the 1990s to help gauge the confidence in the forecast, and to obtain useful results farther into the future than otherwise possible. This approach analyzes multiple forecasts created with an individual forecast model or multiple models.