Sentence examples for monthly climate data from inspiring English sources

Climate-growth relationships were calculated as bootstrapped correlation coefficients between site chronologies and monthly climate data, and identify climatic factors responsible for the observed growth variation.

As a starting point, a study that associates the region's monthly climate data with the thermal comfort has been developed.

For this purpose, the GROWEST model was comprehensively upgraded to run on weekly and monthly climate data, in point or grid form, to produce weekly and monthly outputs.

The first step in estimating Ea is to calculate E0 using monthly climate data from one representative weather station in the study area.

Simulations of variable initial conditions in which randomly generated monthly climate data (i.e., precipitation, temperature, and relative humidity) were used to force the model during the equilibration period (which precedes the application of instrumental climate data) demonstrate that Castor Lake and Scanlon Lake have a somewhat limited isotopic 'memory' of ∼10 years.

We then run the model with transient monthly climate data from 1900 to 2000.

These are 30 arc-second (~1 km) gridded climate surfaces for global land areas developed from monthly climate station data, which were spatially interpolated using elevation, distance to the coast and MODIS derived maximum and minimum land surface temperatures, and cloud cover as covariates (Fick and Hijmans 2017).

Monthly climatic data were obtained from worldwide climate maps generated by the interpolation of data from ground-based meteorologic stations with a monthly temporal resolution and 0.5° (latitude) by 0.5° (longitude) spatial resolution (Mitchell and Jones 2005).

Climate-growth analyses were performed in two ways: first, using correlation analysis between residual site-level chronologies and monthly and seasonal climate data, and second, using linear mixed effects models (LMM) with seasonal climate data and standardized chronologies for each individual.

Fig. 3 Results of the bootstrapped correlation analysis between tree-growth indices and monthly and seasonal climate data for (a) Schlossberg and (b) Eldena.

Auxiliary environmental data were extracted from GIS layers that included terrain attributes (Palmer 2008); environmental layers (Leathwick et al. 2003); and monthly and annual climate data (Mitchell 1991; Leathwick et al. 2002).