Sentence examples for climatological variability from inspiring English sources

After inter-site correlations, differences in linear sedimentation rates, GRA densities, and other oceanographic and climatological variability and distribution can be examined for any combination of depth, latitudinal, and longitudinal transects.

Projecting this understanding to a field population under climatological variability results in a pattern coherent with in situ records.

The variability of the atmospheric circulation is the most important of these trends, with respect to changes in the spatial distribution and variability, not only for temperature and precipitation, but also for other climatological variables [4] [7].

The study of avifauna and climatological variables is not new in scientific literature.

The temporal variability and bio-climatological characteristics across Europe do not allow for a simple European classification of HNV farmland.

In this manner, Alken and Maus (2007) proposed an empirical model of EEJ climatological mean and day-to-day variability as a function of longitude, local time, season, and solar flux.

All types of UV radiation and climatological factors were included as independent variables separately in models.

The present study draws on a significant dataset of snow density and climate observations from the United States, Australia and the former Soviet Union and uses regression-based techniques to identify the dominant climatological drivers for snow densification rates, characterise densification rate variability and estimate spring snow densities from more readily available climate data.

Our climatological model is twofold: its first component describes the daily variability and is derived from a principal component analysis (PCA) which allows us to retrieve the main patterns of the time series.

A systematic study of the EEJ characteristics using all the data from the Oersted, CHAMP, and SAC-C satellites obtained during the years (1999 to 2006) was used to construct the equatorial electrojet climatological model (EEJM-2.0) to reflect the day-to-day variability of electrojet using the input parameters of longitude, local time, and season and solar flux.

This finding may result from considerable overlap among the optimal temperature range for transmission (18 32°C), the climatological range for extreme daily temperatures in Cali (15 35°C), the variability in this overlap on intraseasonal time scales, and its relation to other meteorological parameters (RHAVG and RRTOT) that influence vector populations and disease transmission.