Sentences with phrase «spatial scale variability»

Analyses of tide gauge and altimetry data by Vinogradov and Ponte (2011), which indicated the presence of considerably small spatial scale variability in annual mean sea level over many coastal regions, are an important factor for understanding the uncertainties in regional sea - level simulations and projections at sub-decadal time scales in coarse - resolution climate models that are also discussed in Chapter 13.

Not exact matches

spatial variability in the thermal and nutritional riverscape at multiple spatial scales (patch, riverscape, reach, river segment)

Monitoring, understanding, and predicting oceanic variations associated with natural climate variability and human - induced changes, and assessing the related roles of the ocean on multiple spatial - temporal scales.

Figure 4 - Spatial variability of the sea surface temperature (SST) trends scaled with the global surface air temperature (SAT) trend for each simulation used in the study.

Variability with MJO characteristics (e.g., convection and wind anomalies of the correct spatial scale that propagate coherently eastward with realistic phase speeds) is simulated in many contemporary models (e.g., Sperber et al., 2005; Zhang, 2005), but this variability is typically not simulated to occur often enough or with sufficient strength so that the MJO stands out realistically above the broadband background variability (Lin et Variability with MJO characteristics (e.g., convection and wind anomalies of the correct spatial scale that propagate coherently eastward with realistic phase speeds) is simulated in many contemporary models (e.g., Sperber et al., 2005; Zhang, 2005), but this variability is typically not simulated to occur often enough or with sufficient strength so that the MJO stands out realistically above the broadband background variability (Lin et variability is typically not simulated to occur often enough or with sufficient strength so that the MJO stands out realistically above the broadband background variability (Lin et variability (Lin et al., 2006).

Figure 1.4 http://cybele.bu.edu/courses/gg312fall02/chap01/figures/figure1.4.gif shows the natural variability of the annual mean surface temperature on several different spatial scales from a climate model simulation for 200 years.

As you go to smaller spatial and shorter temporal scales the amount of internal variability increases markedly and so the number of diagnostics which will be different to the expected values from the models will increase (in both directions of course).

But isn't the UHI effect something other than this «microscale variability» that would be evident at a regional, spatial scale as a «hot spot» for instance (thus the urban heat island).

Uses analyses at national and state scales to examine a suite of climatic and intrinsic drivers of continental - scale West Nile virus epidemics, including an empirically derived mechanistic relationship between temperature and transmission potential that accounts for spatial variability in vectors

Although such approaches provide important spatial coverage of long - term trends, their accuracy will be difficult to assess unless seasonal and interannual time scales of pH variability can be adequately resolved.»

These estimates are generally model - based because of difficulties in obtaining reliable internal variability estimates from the observational record on the spatial and temporal scales considered in detection studies.

The goal is to provide the Arctic research community and other users of Arctic climate information with access to climate variability and change data on the smaller spatial scales that are needed for improved fundamental understanding and for decision support applications and assessment research.

These results contradict the notion that oceanic variability is mostly baroclinic at interannual periods, regardless of location or spatial scale.

This has been difficult to confirm observationally because of the high spatial variability of RS, inaccessibility of the soil medium and the inability of remote - sensing instruments to measure RS on large scales.

The results show that the effects of SAL physics lead to time - varying, non-uniform spatial patterns and are an important component of ocean mass variability on scales from months to years.

Moreover, we suggest that accounting for any spatial or seasonal biases in the stack would tend to reduce its variability because of the cancellation of noise in a large - scale mean and the opposing nature of seasonal insolation forcing over the Holocene, causing the Holocene temperature distribution to contract.

Actions occur at a very small spatial scale, where variability is huge and unpredictable.

«Climate variability refers to variations in the mean state and other statistics (such as standard deviations, the occurrence of extremes, etc.) of the climate on all temporal and spatial scales beyond that of individual weather events.

Additionally, circulation trends that are robust on large spatial scales may be much more difficult to detect on regional spatial scales due to the competing effects of internal climate variability (e.g., Deser et al., 2012a, 2012b).

We wanted to illustrate the potential of a long - term regional homogenized dataset mainly in three areas: (i) the high spatial density, which allows the study of small scale spatial variability patterns; (ii) the length of the series in the region which shows clear features concerning trends starting early in the pre-industrial period; and (iii) the vertical component in climate variability up to the 700 - hPa level.

The main drivers of spatial variability in net ecosystem production (NEP) on a global scale are, however, poorly known.

Modes or patterns of climate variability - Natural variability of the climate system, in particular on seasonal and longer time scales, predominantly occurs with preferred spatial patterns and time scales, through the dynamical characteristics of the atmospheric circulation and through interactions with the land and ocean surfaces.

Remember that the magnitude of annual, interannual and decadal variability increases substantially as spatial scales go from global, hemispheric, continental, regional to local.

«The response to anthropogenic changes in climate forcing occurs against a backdrop of natural internal and externally forced climate variability that can occur on similar temporal and spatial scales.

These range from simple averaging of regional data and scaling of the resulting series so that its mean and standard deviation match those of the observed record over some period of overlap (Jones et al., 1998; Crowley and Lowery, 2000), to complex climate field reconstruction, where large - scale modes of spatial climate variability are linked to patterns of variability in the proxy network via a multivariate transfer function that explicitly provides estimates of the spatio - temporal changes in past temperatures, and from which large - scale average temperature changes are derived by averaging the climate estimates across the required region (Mann et al., 1998; Rutherford et al., 2003, 2005).

We use the 250 km analysis because it is better - suited for illustrating variability on regional spatial scales.

However, regional variations are expected because of greater climate «noise» (unforced variability) on small scales, possible regional climate forcings, and known mechanisms that affect the large scale spatial variation of global warming.

Because natural fire regimes varied widely historically, and are complicated in many places by similar variability in logging practices and intensities, the effect of fire reductions on bark beetle outbreaks varies considerably and involves several issues of spatial and temporal scale variability.