scholarly journals Evaluating NA‐CORDEX historical performance and future change of western U.S. precipitation patterns and modes of variability

2021 ◽  
Author(s):  
Jonathan David Douglas Meyer ◽  
S.‐Y. Simon Wang ◽  
Robert R. Gillies ◽  
Yoon Jin‐Ho
Keyword(s):  
Future Change ◽  
Precipitation Patterns ◽  
Modes Of Variability ◽  
Historical Performance

Gravity Effect on the Formation of Periodic Precipitation Patterns

2000 ◽  
Vol 65 (9) ◽  
pp. 1438-1442 ◽  
Author(s):  
Vladislav Holba ◽  
Frederik Fusek
Keyword(s):  
Gravitational Field ◽  
Spatial Arrangement ◽  
Experimental Results ◽  
Single Sample ◽  
Gravity Effect ◽  
Periodic Precipitation ◽  
Precipitation Patterns ◽  
Liesegang Bands

The effect of gravity on the formation of Liesegang patterns of Ag2Cr2O7in gelatin and that of PbI2in agar was investigated. Spatial arrangement of Liesegang bands was measured in the parallel and antiparallel orientation to the gravitational field in a single sample with all other parameters kept fixed. The experimental results are discussed in terms of the prenucleation theory of periodic precipitation.

scholarly journals Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

2021 ◽  
Author(s):  
Mark D. Risser ◽  
Michael F. Wehner ◽  
John P. O’Brien ◽  
Christina M. Patricola ◽  
Travis A. O’Brien ◽  
...  
Keyword(s):  
Climate Variability ◽  
Extreme Precipitation ◽  
Southern Oscillation ◽  
Statistical Significance ◽  
In Situ Measurements ◽  
Climate Indices ◽  
Natural Climate Variability ◽  
Modes Of Variability ◽  
Natural Climate

AbstractWhile various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

scholarly journals Analysis and prediction of LUCC change in Huang-Huai-Hai river basin

2020 ◽  
Vol 12 (1) ◽  
pp. 1406-1420
Author(s):  
Jianwei Wang ◽  
Kun Wang ◽  
Tianling Qin ◽  
Hanjiang Nie ◽  
Zhenyu Lv ◽  
...  
Keyword(s):  
Land Use ◽  
River Basin ◽  
Land Use Planning ◽  
Climate Model ◽  
Dynamic Change ◽  
Cultivated Land ◽  
Emission Scenarios ◽  
Future Change ◽  
Land Use Types ◽  
Downstream Area

AbstractLand use/cover change plays an important role in human development and environmental health and stability. Markov chain and a future land use simulation model were used to predict future change and simulate the spatial distribution of land use in the Huang-Huai-Hai river basin. The results show that cultivated land and grassland are the main land-use types in the basin, accounting for about 40% and 30%, respectively. The area of cultivated land decreased and artificial surfaces increased from 1980 to 2010. The degree of dynamic change of land use after the 1990s was greater than that before the 1990s. There is a high probability of exchange among cultivate land, forest and grassland. The area of forest decreased before 2000 and increased after 2000. Under the three emission scenarios (RCP2.6, RCP4.5, and RCP8.5) of IPSL-CM5A-LR climate model, the area of cultivated land will decrease and that of grassland will increase in the upstream area while it will decrease in the downstream area. The above methods and rules will be of great help to future land use planning.

“Modes of Variability” and Climate Change

2009 ◽  
Vol 22 (10) ◽  
pp. 2639-2658 ◽  
Author(s):  
Grant Branstator ◽  
Frank Selten
Keyword(s):  
Climate Change ◽  
Stochastic Model ◽  
General Circulation ◽  
Climate Changes ◽  
Circulation Model ◽  
Meridional Wind ◽  
Model Atmosphere ◽  
Linear Pattern ◽  
Modes Of Variability ◽  
Mean State

Abstract A 62-member ensemble of coupled general circulation model (GCM) simulations of the years 1940–2080, including the effects of projected greenhouse gas increases, is examined. The focus is on the interplay between the trend in the Northern Hemisphere December–February (DJF) mean state and the intrinsic modes of variability of the model atmosphere as given by the upper-tropospheric meridional wind. The structure of the leading modes and the trend are similar. Two commonly proposed explanations for this similarity are considered. Several results suggest that this similarity in most respects is consistent with an explanation involving patterns that result from the model dynamics being well approximated by a linear system. Specifically, the leading intrinsic modes are similar to the leading modes of a stochastic model linearized about the mean state of the GCM atmosphere, trends in GCM tropical precipitation appear to excite the leading linear pattern, and the probability density functions (PDFs) of prominent circulation patterns are quasi-Gaussian. There are, on the other hand, some subtle indications that an explanation for the similarity involving preferred states (which necessarily result from nonlinear influences) has some relevance. For example, though unimodal, PDFs of prominent patterns have departures from Gaussianity that are suggestive of a mixture of two Gaussian components. And there is some evidence of a shift in probability between the two components as the climate changes. Interestingly, contrary to the most prominent theory of the influence of nonlinearly produced preferred states on climate change, the centroids of the components also change as the climate changes. This modification of the system’s preferred states corresponds to a change in the structure of its dominant patterns. The change in pattern structure is reproduced by the linear stochastic model when its basic state is modified to correspond to the trend in the general circulation model’s mean atmospheric state. Thus, there is a two-way interaction between the trend and the modes of variability.

scholarly journals Two major modes of variability of the East Asian summer monsoon

2010 ◽  
Vol 136 (649) ◽  
pp. 829-841 ◽  
Author(s):  
Xuguang Sun ◽  
Richard J. Greatbatch ◽  
Wonsun Park ◽  
Mojib Latif
Keyword(s):  
Summer Monsoon ◽  
East Asian Summer Monsoon ◽  
Asian Summer Monsoon ◽  
East Asian ◽  
Modes Of Variability ◽  
Asian Summer
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