Detection of a Human Influence on North American Climate
... data were obtained from quality-controlled instrumental observations and have been used in virtually all detection studies considering surface temperature changes. Observed diurnal temperature range data were obtained from a different data set (9). Annual means were constructed using seasonal averag ...
... data were obtained from quality-controlled instrumental observations and have been used in virtually all detection studies considering surface temperature changes. Observed diurnal temperature range data were obtained from a different data set (9). Annual means were constructed using seasonal averag ...
Modeling hydrological consequences of climate and land use change
... Large scale simulation experiments were begun by the Corps of Engineers of the United States in 1953 for reservoir management. The Stanford Watershed Model (SWM) (Crawford and Linsley, 1966) is another early model integrating many sub-models including storm water and basin chemical modeling. This le ...
... Large scale simulation experiments were begun by the Corps of Engineers of the United States in 1953 for reservoir management. The Stanford Watershed Model (SWM) (Crawford and Linsley, 1966) is another early model integrating many sub-models including storm water and basin chemical modeling. This le ...
Vol.5, No.2, 2005
... lower relative humidity, higher stability and vertical shear found in the warm-climate simulation over these areas. The results of this study demonstrate the utility of applying the IPRC–RegCM to the tropical cyclone climate sensitivity problem. By using a regional model forced by output from coarse ...
... lower relative humidity, higher stability and vertical shear found in the warm-climate simulation over these areas. The results of this study demonstrate the utility of applying the IPRC–RegCM to the tropical cyclone climate sensitivity problem. By using a regional model forced by output from coarse ...
univERsity oF copEnhAGEn
... part of the world. This representation is not, however, an exact replica of the system that the model represents instead the model represents only certain aspects of the system while ignoring others. Many representational models are analogue models which are based on certain similarities or analog ...
... part of the world. This representation is not, however, an exact replica of the system that the model represents instead the model represents only certain aspects of the system while ignoring others. Many representational models are analogue models which are based on certain similarities or analog ...
Please indicate if Student Paper Future changes in Extreme East
... occurs largely in winter. However, at this point there are no projections available for ECLs when explicitly identified through their synoptic features at the surface. The main impact ECLs have on the coastal areas is in producing rainfall, often extreme rainfall that leads to flooding. Climate chan ...
... occurs largely in winter. However, at this point there are no projections available for ECLs when explicitly identified through their synoptic features at the surface. The main impact ECLs have on the coastal areas is in producing rainfall, often extreme rainfall that leads to flooding. Climate chan ...
the wmo voluntary observing ship programme
... calibration or “ground-truthing” of satellite observations. Furthermore, reports from VOS continue to be used routinely in the preparation of weather forecasts, thus supplying a constant “reality check” on actual weather conditions, contributing directly to short-range prediction and providing impor ...
... calibration or “ground-truthing” of satellite observations. Furthermore, reports from VOS continue to be used routinely in the preparation of weather forecasts, thus supplying a constant “reality check” on actual weather conditions, contributing directly to short-range prediction and providing impor ...
IPCC Expert Meeting on Assessing and Combining Multi Model Climate Projections
... and in interpreting model spread in general. Formal statistical methods can be powerful tools to synthesize model results, but there is also a danger of overconfidence if the models are lacking important processes and if model error, uncertainties in observations, and the robustness of statistical a ...
... and in interpreting model spread in general. Formal statistical methods can be powerful tools to synthesize model results, but there is also a danger of overconfidence if the models are lacking important processes and if model error, uncertainties in observations, and the robustness of statistical a ...
User-driven downscaling: advances in data apportioning and
... Data accessed by users in all 50 States and 99 countries (last 11 months only) ...
... Data accessed by users in all 50 States and 99 countries (last 11 months only) ...
Annex 3: Strengths and weaknesses of climate models
... extends more into the north and over the UK, whereas in the multi-model ensemble the line of zero mean change cuts the UK. This is why it is so important to include information from other climate models in UKCP09. For some variables the response to climate change may be quite different in different ...
... extends more into the north and over the UK, whereas in the multi-model ensemble the line of zero mean change cuts the UK. This is why it is so important to include information from other climate models in UKCP09. For some variables the response to climate change may be quite different in different ...
Skill and reliability of climate model ensembles at the Last Glacial
... Hydrology and Earth System Much of the current concern over climate change is based on decadal to centennial forecasts Sciences from climate models forced ...
... Hydrology and Earth System Much of the current concern over climate change is based on decadal to centennial forecasts Sciences from climate models forced ...
Weather Maps and Weather Prediction
... What are some types of weather forecasts? • Short-range weather forecasts make predictions 0 to 3 days into the future. Medium-range forecasts predict conditions 3 to 7 days into the future. • Temperature, wind, cloud cover, and precipitation are predicted with different degrees of accuracy. • Weath ...
... What are some types of weather forecasts? • Short-range weather forecasts make predictions 0 to 3 days into the future. Medium-range forecasts predict conditions 3 to 7 days into the future. • Temperature, wind, cloud cover, and precipitation are predicted with different degrees of accuracy. • Weath ...
Weather Maps and Weather Prediction
... What are some types of weather forecasts? • Short-range weather forecasts make predictions 0 to 3 days into the future. Medium-range forecasts predict conditions 3 to 7 days into the future. • Temperature, wind, cloud cover, and precipitation are predicted with different degrees of accuracy. • Weath ...
... What are some types of weather forecasts? • Short-range weather forecasts make predictions 0 to 3 days into the future. Medium-range forecasts predict conditions 3 to 7 days into the future. • Temperature, wind, cloud cover, and precipitation are predicted with different degrees of accuracy. • Weath ...
Improving evaluation of climate change impacts on the water cycle
... predictions. In the present work, a robust methodology for building climate multimodel ensembles of meteorological data was presented. The final aim was to increase the reliability of both climatological and hydrological projections. The introduction of GIS has facilitated the spatial modelling of t ...
... predictions. In the present work, a robust methodology for building climate multimodel ensembles of meteorological data was presented. The final aim was to increase the reliability of both climatological and hydrological projections. The introduction of GIS has facilitated the spatial modelling of t ...
- Wiley Online Library
... [12] The total amount of clouds (Figure 3) is best defined, but changes in the low, middle and high cloud can also be estimated using definitions from the International Satellite Cloud Climatology Project (ISCCP) [Schiffer and Rossow, 1983]. The treatment of cloud overlap by radiation codes varies w ...
... [12] The total amount of clouds (Figure 3) is best defined, but changes in the low, middle and high cloud can also be estimated using definitions from the International Satellite Cloud Climatology Project (ISCCP) [Schiffer and Rossow, 1983]. The treatment of cloud overlap by radiation codes varies w ...
Weather Forecasting and Indigenous Knowledge Systems in
... It is a statement of weather expected to occur in a particular area during a stated time period [Buckle, 1996:218].Weather forecasting can either be subjective or numerical. Subjective forecasting is based on describing the current daily observation of the atmosphere and what has been happening in t ...
... It is a statement of weather expected to occur in a particular area during a stated time period [Buckle, 1996:218].Weather forecasting can either be subjective or numerical. Subjective forecasting is based on describing the current daily observation of the atmosphere and what has been happening in t ...
Probability Models for the NCAA Regional Basketball Tournaments
... of these chi-squares is given for each model. Twenty-six of the seed pairs had fewer than five games played, and the small expected numbers in these cells, being used as a divisor, may place too much emphasis on these cells and distort the chi-square values. Hence a second set of chisquare statistic ...
... of these chi-squares is given for each model. Twenty-six of the seed pairs had fewer than five games played, and the small expected numbers in these cells, being used as a divisor, may place too much emphasis on these cells and distort the chi-square values. Hence a second set of chisquare statistic ...
Document
... Mike Purucker, Anne Mee Thompson, Matthew Lazzara Over the past decades, satellite technologies and related sciences have advanced to provide observations on global scale on various parameters (temperature, clouds, snow/ice coverage, magnetic field, sea level, ocean colour, surface roughness) from w ...
... Mike Purucker, Anne Mee Thompson, Matthew Lazzara Over the past decades, satellite technologies and related sciences have advanced to provide observations on global scale on various parameters (temperature, clouds, snow/ice coverage, magnetic field, sea level, ocean colour, surface roughness) from w ...
Observing climate change trends in ocean
... example of ALOHA 20 years of data – are the observed trends due to climate change? Our analysis suggests that for SST need 13 years, chl 29 years, and PP 26 years of data to distinguish genuine climate trend from natural variability ...
... example of ALOHA 20 years of data – are the observed trends due to climate change? Our analysis suggests that for SST need 13 years, chl 29 years, and PP 26 years of data to distinguish genuine climate trend from natural variability ...
DRAFT by Baker 9 November 2003 Observing the Ocean
... (JGOFS) have raised the profile of the need for better and operational coastal and global observations. New technology from experimental satellites such as TOPEX/POSEIDON and autonomous floats, and greatly expanded modeling and data assimilation have laid the basis for an operational global ocean ob ...
... (JGOFS) have raised the profile of the need for better and operational coastal and global observations. New technology from experimental satellites such as TOPEX/POSEIDON and autonomous floats, and greatly expanded modeling and data assimilation have laid the basis for an operational global ocean ob ...
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.