Sentences with phrase «coarse spatial resolution»

Their relatively good spectral resolution makes infrared sounders very useful for the determination of cloud properties (day and night), and their coarse spatial resolution has less effect on clouds with large spatial extents like cirrus clouds.

The coarse spatial resolution of GCMs presents an important limitation for simulating extreme ETCs, but Eady growth rate biases are likely just as relevant.

Thus, scientists often make climate projections at coarse spatial resolution where each projected data point is an average value of a grid cell that measures hundreds of miles (kilometers) across.

«Until the launch of the OCO - 2 satellite mission in 2014 we had global maps of SIF but at coarse spatial resolution, each pixel compromising areas of about 50 x 50 kilometres in the best case,» says Luis Guanter from GFZ.

Moreover, graph theory - based network analyses have also been applied to resting - state fMRI data, identifying similar RSNs, although typically at a coarser spatial resolution.

The intent of downscaling is to achieve accurate, higher spatial resolution of weather and other components of the climate system than is achievable with the coarser spatial resolution global model.

Not exact matches

The climate change impacts community has long bemoaned the inadequate spatial scale of climate scenarios produced from coarse resolution GCM output (Gates, 1985; Lamb, 1987; Robinson and Finkelstein, 1989; Smith and Tirpak, 1989; Cohen, 1990).

Unfortunately, the figure also confirms that the spatial resolution of theoutput from the GCMs used in the Mediterranean study is too coarse for constructing detailed regional scenarios.To develop more detailed regional scenarios, modelers can combine the GCM results with output from statistical models.3 This is done by constructing a statistical model to explain the observed temperature or precipitation at a meteorological station in terms of a range of regionally - averaged climate variables.

Because most AOGCMs have coarse resolution and large - scale systematic errors, and extreme events tend to be short lived and have smaller spatial scales, it is somewhat surprising how well the models simulate the statistics of extreme events in the current climate, including the trends during the 20th century (see Chapter 9 for more detail).

Finally, simulations having finer spatial detail (i.e., «downscaled» climate model projections) do not necessarily have greater accuracy than coarser - resolution simulations; they add contextual detail related to factors such as regional topography and coastlines but may still retain the same basic climatic features simulated at larger scales.

It contains a suite of routines for downscaling coarse scale global climate model (GCM) output to a fine spatial resolution.

While regional climate downscaling yields higher spatial resolution, the downscaling is strongly dependent on the lateral boundary conditions and the methods used to constrain the regional climate model variables to the coarser spatial scale information from the parent global models.

Land use and emissions of air pollutants and greenhouse gases are reported mostly at a 0.5 × 0.5 degree spatial resolution, with air pollutants also provided per sector (for well - mixed gases, a coarser resolution is used).

The ClimDown R package publishes the routines and techniques of the Pacific Climate Impacts Consortium (PCIC) for downscaling coarse scale Global Climate Models (GCMs) to fine scale spatial resolution.

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.

Impact studies rarely use GCM outputs directly because GCM biases are too great and because the spatial resolution is generally too coarse to satisfy the data requirements for estimating impacts.

The spatial resolution of current global climate models, roughly 200 km, is too coarse to simulate the impact of global change on most individual river basins.

Even the best proxy records contain far fewer observations than the worst periods of the observational record, and the spatial and temporal resolution of the resulting reconstructions is correspondingly coarse.