Large scale climate oscillations and mesoscale surface meteorological variability in the Apalachicola-Chattahoochee-Flint River Basin
TL;DR: In this paper, the authors examined the relationship between available surface climatological variables connected to evapotranspiration and climatic oscillations using canonical correlation analysis (CCA).
About: This article is published in Journal of Hydrology.The article was published on 2014-09-19. It has received 13 citations till now. The article focuses on the topics: Climate oscillation & Pacific decadal oscillation.
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TL;DR: In this article, a nonstationary Gamma distribution with climate indices as covariates was developed for fitting precipitation data and then used for calculating a Nonstationary Standardized Precipitation Index (NSPI).
Abstract: Many drought indices were proposed to describe drought characteristics, but only few had considered environmental changes. In an attempt to incorporate climate change into meteorological drought index, a nonstationary Gamma distribution with climate indices as covariates was developed for fitting precipitation data and then used for calculating a Nonstationary Standardized Precipitation Index (NSPI) in this study. The performances of the NSPI were compared with those of the traditional Standardized Precipitation Index (SPI), showing that the NSPI capable of taking climate variations into account is more robust than the traditional SPI. Focusing on the Luanhe River basin, historical drought events were described and assessed based on the NSPI and traditional SPI. Moreover, drought characteristics, including drought frequency, peak, duration, and magnitude, were calculated by using the two indices. The results in this study indicated that NSPI using climate indices as covariates could capture drought characteristics in the Luanhe River basin, and this new drought index provides a new concept for constructing the drought index that can effectively adapt to a changing environment.
58 citations
TL;DR: In this article, a probabilistic analysis approach by means of a state-of-the-art Copula-based joint probability distribution is developed to characterize the aggregated behaviors for large-scale climate patterns and their connections to precipitation.
31 citations
TL;DR: In this paper, Wang et al. presented a new probabilistic analysis approach by means of a state-of-the-art Copula-based joint probability distribution to characterize the aggregated behaviors for large-scale climate patterns and their connections to precipitation.
Abstract: The interactions between a range of large-scale climate oscillations and their quantitative links with precipitation are basic prerequisites to understand the hydrologic cycle. Restricted by the current limited knowledge on underlying mechanisms, statistical methods (e.g. correlation methods) are often used rather than a physical-based model. However, available correlation methods generally fail to explain the interactions among a wide range of climate oscillations and associated effects on the water cycle. This study presents a new probabilistic analysis approach by means of a state-of-the-art Copula-based joint probability distribution to characterize the aggregated behaviors for large-scale climate patterns and their connections to precipitation. We applied this method to identify the complex connections between climate patterns (westerly circulation (WEC), El Nino-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO)) and seasonal precipitation over a typical endorheic region, the Tarim River Basin in central Asia. Results show that the interactions among multiple climate oscillations are non-uniform in most seasons and phases. Certain joint extreme phases can significantly trigger extremes (flood and drought) owing to the amplification effect among climate oscillations. We further find that the connection is mainly due to the complex effects of climatic and topographical factors.
17 citations
TL;DR: In this article, the influence of low-frequency oscillations on streamflow variability in small tropical coastal mountain rivers of the Sierra Nevada de Santa Marta, Colombia, was evaluated.
Abstract: . This study evaluated the influence of
low-frequency oscillations, that are linked to large-scale
oceanographic–atmospheric processes, on streamflow variability in small
tropical coastal mountain rivers of the Sierra Nevada de Santa Marta,
Colombia. We used data from six rivers that had > 32 years of
complete, continuous monthly streamflow records. This investigation employed
spectral analyses to (1) explore temporal characteristics of streamflow
variability, (2) estimate the net contribution to the energy spectrum of
low-frequency oscillations to streamflow anomalies, and (3) analyze the
linkages between streamflow anomalies and large-scale, low-frequency
oceanographic–atmospheric processes. Wavelet analyses indicate that the
8–12-year component exhibited a quasi-stationary state, with a peak of
maximum power between 1985 and 2005. These oscillations were nearly in phase
in all rivers. Maximum power peaks occurred for the Palomino and Rancheria
rivers in 1985 and 1995, respectively. The wavelet spectrum highlights a
change in river variability patterns between 1995 and 2015, characterized by
a shift towards the low-frequency oscillations' domain (8–12 years). The net
contribution of these oscillations to the energy spectrum was as high as
51 %, a value much larger than previously thought for rivers in
northwestern South America. The simultaneous occurrence of hydrologic
oscillations, as well as the increase in the amplitude of the 8–12-year
band, defined periods of extremely anomalous wet seasons during 1989–1990,
1998–2002 and 2010–2011, reflecting the role of low-frequency oscillations
in modulating streamflow variability in these rivers. Cross-wavelet transform
and wavelet coherence revealed high common powers and significant coherences
in low-frequency bands ( >96 months) between streamflow anomalies and
Atlantic Meridional Oscillation (AMO), Pacific Decadal Oscillation (PDO) and
the Tropical North Atlantic Index (TNA). These results show the role of
large-scale, low-frequency oceanographic–climate processes in modulating the
long-term hydrological variability of these rivers.
13 citations
References
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823 citations
TL;DR: The 2005 North Atlantic hurricane season (1 June to 30 November) was the most active on record by several measures, surpassing the very active season of 2004 and causing an unprecedented level of damage.
Abstract: [1] The 2005 North Atlantic hurricane season (1 June to 30 November) was the most active on record by several measures, surpassing the very active season of 2004 and causing an unprecedented level of damage. Sea surface temperatures (SSTs) in the tropical North Atlantic (TNA) region critical for hurricanes (10° to 20°N) were at record high levels in the extended summer (June to October) of 2005 at 0.9°C above the 1901-70 normal and were a major reason for the record hurricane season. Changes in TNA SSTs are associated with a pattern of natural variation known as the Atlantic Multi-decadal Oscillation (AMO). However, previous AMO indices are conflated with linear trends and a revised AMO index accounts for between 0 and 0.1°C of the 2005 SST anomaly. About 0.45°C of the SST anomaly is common to global SST and is thus linked to global warming and, based on regression, about 0.2°C stemmed from after-effects of the 2004-05 El Nino.
805 citations
TL;DR: In this article, the editors of the book Geophysical field theory and method, Part B, Electromagnetic Fields I were listed, including Beno Gutenberg, Joseph W. Chamberlain, S. Kondratyev, E. E. Runcorn, C. U. Newton, and many more people.
Abstract: Publisher Summary This chapter lists the names of the editors of the book Geophysical Field Theory and Method, Part B, Electromagnetic Fields I . These editors include Beno Gutenberg, Joseph W. Chamberlain, S. K. Runcorn, C. E. Junge, Robert G. Fleagle, Joost A. Businger. L. Dufour, R. Defay, H. U. Roll, Richard A. Craig, Willis L. Webb, Michele Caputo, S. Matsushita, Wallace H. Campbell, K. V. A. Kondratyev, E. Palmen, C. W. Newton, and many more people.
762 citations
TL;DR: The relationship between the three primary modes of Pacific sea surface temperature variability (SST) variability and U.S. warm season hydroclimate is examined in this article, where precipitation, drought and stream flow data are analyzed to provide a comprehensive picture of the lower-frequency components of hydrologic variability.
Abstract: The relationship between the three primary modes of Pacific sea surface temperature (SST) variability—the El Nino–Southern Oscillation (ENSO), the Pacific decadal oscillation, and the North Pacific mode—and U.S. warm season hydroclimate is examined. In addition to precipitation, drought and stream flow data are analyzed to provide a comprehensive picture of the lower-frequency components of hydrologic variability. ENSO and the two decadal modes are extracted from a single unfiltered analysis, allowing a direct intercomparison of the modal structures and continental linkages. Both decadal modes have signals in the North Pacific, but the North Pacific mode captures most of the local variability. A summertime U.S. hydroclimatic signal is associated with all three SST modes, with the linkages of the two decadal modes comparable in strength to that of ENSO. The three SST variability modes also appear to play a significant role in long-term U.S. drought events. In particular, the northeastern drought o...
445 citations
TL;DR: In this article, the ocean surface-atmosphere relationships in the North Atlantic area in northern winter are empirically examined by canonical correlation analysis (CCA) from two different points of view, in terms of monthly mean sea level pressure (SLP) and monthly standard deviation of SLP (αSLP), and sea surface temperature (SST) anomalies.
Abstract: The ocean surface-atmosphere relationships in the North Atlantic area in northern winter are empirically examined by canonical correlation analysis (CCA). This analysis is performed from two different points of view. First, the connection between atmospheric circulation anomalies, in terms of monthly mean sea level pressure (SLP) and monthly standard deviation of SLP (αSLP), and sea surface temperature (SST) anomalies of the Atlantic Ocean are directly examined. Second, the air-sea relationships are indirectly studied through their influence upon precipitation in an area likely to be influenced by the North Atlantic, the Iberian Peninsula. The canonical correlation analysis yields two pairs of patterns that describe the coherent variations of the combined SST-SLP fields; one pair of patterns for the SST-αSLP fields and one pair of patterns for the SLP-αSLP fields. All patterns are dominant in describing variance. A lag cross-correlation analysis of the time coefficients indicates that monthly mea...
329 citations