A multiple regression model using variables related to season, mean daily air temperature, and a spatial influence factor (metric to account for groundwater influence) was a strong predictor of mean daily water temperature (r2 = 0.98; RMSE = 0.82). Data from two downscaled climate ...
whereas perception of local temperature change is the strongest predictor in many African and Asian countries. However, other key factors associated with public awareness and risk perceptions highlight the need to develop tailored climate communication strategies for individual nations. The results suggest...
Screening variables between predictand (such as maximum temperature, minimum temperature, evaporation, as well as precipitation on a local scale) and predictor (large-scale atmospheric conditions) is a core of the statistical downscaling process. SDSM combines the correlation matrix, partial correlation...
摘要: Previous research has identified the interaction between political orientation and education as an important predictor of climate change beliefs. Using data from the 2010 General Social Survey, this...关键词: Africa's Antelope Africa's habitats animal movement environmental gradients global climate...
This reduction of predictor variables resulted in the inclusion of six variables for models (Table 1). These variables included mean diurnal temperature range (Bio2), minimum temperature of coldest month (Bio6), annual precipitation (Bio12), precipitation of the driest month (Bio14), ...
We show that replacement of the traditional instantaneous and adjusted forcings, Fi and Fa, with an easily computed alternative, Fs, yields a better predictor of climate change, i.e., its efficacies are closer to unity. Fs is inferred from flux and temperature changes in a fixed-ocean model...
The Boland–Ridley model49 was used to calculate the direct and diffuse components of global solar irradiance. This method is a robust and straightforward predictor model that requires few inputs. The Italian National organization for standardization (UNI) has adopted this reliable method to split th...
The predictor variables, such as air temperature, zonal wind, meridional wind, and geo-potential height, are extracted from the National Centers for Environmental Prediction (NCEP) reanalysis data set for the period 1948-2000 and from the simulations using third-generation Canadian coupled global ...
Example (top) of time-varying April 1 SWE ‘predictor’ information (blue line) and target flow (black line) together with the statistical predictive model (red line) during a 30-year calibration. The subsequent 5-year application period shows the model prediction (purple line) from which pred...
Drought intensity was the most important predictor of fire occurrence, but land-cover type and degree of landowner absenteeism increased fire probability when conditions were dry enough. On the other hand, drought intensity did not stand out relative to other significant predictors in the fire size ...