Sentences with phrase «in spatial coverage»

* In February, 2006 NCDC transitioned to the use of an improved Global Land and Ocean data set (Smith and Reynolds analysis (2005)-RRB- which incorporates new algorithms that better account for factors such as changes in spatial coverage and evolving observing methods.

Last year, an analysis conducted by the UK Met Office demonstrated that the disagreement amongst groups arose primarily from the differences in spatial coverage, especially the inclusion or exclusion of polar regions.

The instrumental record before then is hideously insufficient in spatial coverage of the planet to establish a global average temperature.

The processing of these observations is straightforward, but large gaps in spatial coverage compromise the reliability of global averages, and changes in instrumentation can give rise to spurious trends.

Since 1900, the change in spatial coverage does not seem to have affected land records significantly.2 Before then, however, even careful analysis may lead to long - term averages that are either too warm or too cold by up to 0.1 C. 1 Records may be affected by changes in the way observations are made.

Not exact matches

SUVI replaces the GOES Solar X-ray Imager (SXI) instrument in previous GOES satellites and represents a change in both spectral coverage and spatial resolution over SXI.

However, the Hadley Centre SST data set60, 61 (HadSST3, v3.1.1.0) is not global in coverage: rather than interpolating over all space and time coordinates it consists of spatial means within 5 ° × 5 ° bins, leading to missing values in the absence of data.

Statisticians can advise on how best to combine data from different sources, how to identify and adjust for biases in different measurement systems, and how to deal with changes in the spatial and temporal coverage of measurements.

One approach is to develop empirical regional models that enable aragonite saturation state to be estimated from existing hydrographic measurements, for which greater spatial coverage and longer time series exist in addition to higher spatial and temporal resolution.

In this case, there has been an identification of a host of small issues (and, in truth, there are always small issues in any complex field) that have involved the fidelity of the observations (the spatial coverage, the corrections for known biases), the fidelity of the models (issues with the forcings, examinations of the variability in ocean vertical transports etc.), and the coherence of the model - data comparisonIn this case, there has been an identification of a host of small issues (and, in truth, there are always small issues in any complex field) that have involved the fidelity of the observations (the spatial coverage, the corrections for known biases), the fidelity of the models (issues with the forcings, examinations of the variability in ocean vertical transports etc.), and the coherence of the model - data comparisonin truth, there are always small issues in any complex field) that have involved the fidelity of the observations (the spatial coverage, the corrections for known biases), the fidelity of the models (issues with the forcings, examinations of the variability in ocean vertical transports etc.), and the coherence of the model - data comparisonin any complex field) that have involved the fidelity of the observations (the spatial coverage, the corrections for known biases), the fidelity of the models (issues with the forcings, examinations of the variability in ocean vertical transports etc.), and the coherence of the model - data comparisonin ocean vertical transports etc.), and the coherence of the model - data comparisons.

Moreover, few of the sondes are in the inner tropics, spatial coverage is spotty, and there are questions of instrumental and diurnal sampling errors that may have complicated detection of the trend in the past decade.

First impressions are that this has a number of artifacts in it likely due to inhomogeneities in the satellites (varying levels of spatial coverage through time as satellites drop in or out).

But the bias uncertainty is smaller than the errors which are not persistent in time (e.g. due to incomplete spatial coverage), so I don't think accounting for this would make much difference, as Victor suggests.

The figure to the left shows the spatial mean temperature over all grid boxes in the HadCRUT3 data set that have continuous monthly coverage over the 1901 - 2008 period.

This product is consistent with broad current knowledge about the surface sources and sinks of CO2, CH4 and N2O, but, to our knowledge, it is unique in its combination of temporal coverage, spatial resolution and inclusion of recent measurements.

Shifts and trends in plankton biomass have been observed for instance in the North Atlantic (Beaugrand and Reid, 2003), the North Pacific (Karl, 1999; Chavez et al., 2003) and in the Southern Indian Ocean (Hirawake et al., 2005), but the spatial and temporal coverage is limited.

But I suppose we can leave that to a study of the proper way of calculating a error due to spatial coverage, that error will be a function (at least in the math I've seen) involving the spatial correlation which varies considerably.

Two thermometers along the Atlantic coast of North America, three thermometers in central Europe, one in England, and one by the Great Lakes is not sufficient spatial coverage to make claims about the temperature of the Middle East, India, China, Japan, Mexico, etc..

In general, spatial and temporal coincidences offered by the Dobson and Brewer networks are sufficient to cover a wide geographical extent for the validation of a satellite sensor, however, with better coverage over land with respect to sea and over the Northern Hemisphere compared to the Southern Hemisphere.

The flux estimates presented in previous sections use available estimates from every reservoir where GHG emissions have been reported (and mean estimates from reservoirs where multiple studies or years of data have been collected), but it is important to note that the spatial and temporal coverage of these emission estimates are highly variable.

Precipitation and soil moisture are both presented using two different data records that are complementary in terms of spatial coverage and spatial resolution.

«Bias might be introduced in cases where the spatial coverage is not uniform (e.g., of the 24 original chronologies with data back to 1500, half are concentrated in eastern Siberia) but this can be reduced by prior averaging of the chronologies into regional series (as was done in the previous section)... Eight different methods have been used... They produce very similar results for the post-1700 period... They exhibit fairly dramatic differences, however, in the magnitude of multidecadal variability prior to 1700... highlighting the sensitivity of the reconstruction to the methodology used, once the number of regions with data, and the reliability of each regional reconstruction, begin to decrease.

«The addition of buoy data in recent decades has been particularly important as the spatial coverage from ship observations has decreased since the 1990's (cf. Fig. 1 (a) in (13)-RRB-.

The difference in the latter aspect is most likely due to improvement in the spatial — temporal coverage of the data used in this study, as well as the details of data processing procedures.

Beginning in 1979 we have the satellite record which is really the only sensor system I feel is adequate in accuracy, precision, and especially spatial coverage to measure global average trend to a precision of hundredths of degrees per decade.

Another avenue for monitoring is satellite measurements of column inventories of the gases, which provide much more detailed spatial coverage but no vertical resolution, in which air masses at different altitudes may carry gases that originated from different parts of the Earth's surface.

Spatial coverage is pitifully inadequate, misses the oceans which are the real climate drivers, no discipline in siting, calibration, no repeatibility, amateur volunteers doing all the heavy lifting... A fool's errand trying to make a silk purse from a sow's ear.

The challenges are finding a good enough measure of urbanity, dealing with uncertainty in station locations (a problem in many areas outside the U.S., where lat / lon coordinates aren't always accurate), and ensuring that your method doesn't suffer from spatial coverage biases between urban and rural sets (I tend to prefer station pair comparison methods for that reason).

But use enough weather stations, and your answer is not only better because you have better spatial coverage, but because errors — even pretty large errors — in one of the weather stations probably won't affect your result.

Key challenges, therefore, will be to increasingly: 1) interrogate extreme events in climate simulations; 2) use earth system models to disentangle the complex and multiple controls on proxies; 3) adopt multi-proxy approaches to constrain complex phenomena; and 4) increase the spatial coverage of such records, especially in arid regions, which are currently under - represented.

Because of their large spatial coverage, satellite data have proven useful in evaluating dust sources, transport and deposition in global models.

Prior to 1988, the satellite data that Trenberth uses is not available, but it is known that long term records in radiosondes contain large inhomogeneities due to improving observing systems, increasing spatial resolution (but still very little ocean coverage), and the NCEP data in particular contains large model biases.

To say that the pre-satellite humidity trends are correct, despite the many changes in instrumentation, despite the changes in spatial and temporal resolution (but still almost no ocean coverage), despite the known problems with NCEP model bias, and despite that it has been wrong throughout the satellite era... well, it's ludicrous.

However there are limited long - term air concentration datasets and significant gaps in the spatial and temporal coverage (Keeler et al., 2009).