Sentences with phrase «large precipitation variability»

Understanding and modeling the fundamental processes that govern the large precipitation variability and extremes in the western U.S. is a critical test for the ability of climate models to predict the regional water cycle, including floods and droughts.

Not exact matches

Because of large natural variability, the first approach results in an outcome suggesting that it is appropriate to conclude that there is no increase in precipitation by human influences, although the correct interpretation is that there is simply not enough evidence (not a long enough time series).

On decadal time scales, annual streamflow variation and precipitation are driven by large - scale patterns of climate variability, such as the Pacific Decadal Oscillation (see teleconnections description in Climate chapter)(Pederson et al. 2011a; Seager and Hoerling 2014).

Holden, Z. A., Morgan, P., Crimmins, M. A., Steinhorst, R. K. & Smith, A. M. S. Fire season precipitation variability influences fire extent and severity in a large southwestern wilderness area, United States.

My experience with extremes and detection and attribution of an anthropogenic signal in those is that only by averaging the behavior of extremes (both temperature extremes and precipitation extremes) over large geographical areas (continental or barely sub-continental) we have been able to see something outside of natural variability.

In part because of large intrinsic variability, no evidence was found for changes in extreme precipitation attributable to climate change in the available observed record.»

So: The study finds a fingerprint of anthropogenic influences on large scale increase in precipitation extremes, with remaining uncertainties — namely that there is still a possibility that the widespread increase in heavy precipitation could be due to an unusual event of natural variability.The intensification of extreme rainfall is expected with warming, and there is a clear physical mechanism for it, but it is never possible to completely separate a signal of external forcing from climate variability — the separation will always be statistical in nature.

No changes in extreme precipitation attributable to climate change were found for the observational period, in large part because of significant year - to - year variability.

Its six chapters cover temperature assessment, precipitation assessment, large - scale climate variability modes and related oscillation indices, extreme events, climate and composition of the atmosphere and cryosphere and sea level.

«One of the major modes of climate variability is El Niño and when we're in El Niño there's a large area of warm sea surface temps in the Pacific,» this leads to more precipitation on the West Coast, Crouch said.

It is important to note that RMSE tends to increase with variability, as illustrated at some locations closer to the equator that tend to have higher precipitation magnitudes (and variability) and therefore larger differences between RMSE and MAE (Figure 1).

Precipitation has much larger spatial and temporal variability than temperature, and it is therefore more difficult to identify the impact it has on changes in many systems.

Importantly, the changes in cereal yield projected for the 2020s and 2080s are driven by GHG - induced climate change and likely do not fully capture interannual precipitation variability which can result in large yield reductions during dry periods, as the IPCC (Christensen et al., 2007) states: ``... there is less confidence in the ability of the AOGCMs (atmosphere - ocean general circulation models) to generate interannual variability in the SSTs (sea surface temperatures) of the type known to affect African rainfall, as evidenced by the fact that very few AOGCMs produce droughts comparable in magnitude to the Sahel droughts of the 1970s and 1980s.»

The climate and hence precipitation variability in northern Africa can be quite large.

The greater increases in erosion in the GGa1 scenario was attributed to greater variability in monthly precipitation and an increased frequency of large storms in the model simulation.

The robustly project increased moisture flux convergence and precipitation in the pan-Arctic region over the 21st century, as did their AR4 counterparts (Kattsov et al., 2007; Rawlins et al., 2010 Then we get: since nearly all models project a large precipitation increase rising above the variability year - round, it is likely the pan-Arctic region will experience a statistically - significant increase in precipitation by mid-century.

The large interannual to decadal hydroclimatic variability in winter precipitation is highly influenced by sea surface temperature (SST) anomalies in the tropical Pacific Ocean and associated changes in large - scale atmospheric circulation patterns [16].

Intraseasonal precipitation variability on Kilimanjaro and the East African region and its relationship to the large - scale circulation.

Instrumental records have shown that hydroclimatic variability across the American Southwest is mostly structured around cool - season precipitation regimes, with a few winter storms typically contributing a disproportionately large amount of the annual precipitation across this region [15].

These aspects of precipitation generally exhibit large natural variability, and El Niño and changes in atmospheric circulation patterns such as the North Atlantic Oscillation have a substantial influence.

But given what is known, he said «there is every reason to believe that the trend toward greater variability, larger anomalies, is true for precipitation as well as temperature.»