Large scale climate oscillations and mesoscale surface meteorological variability in the Apalachicola-Chattahoochee-Flint River Basin

Stevens, Kelly A.; Ruscher, Paul H.

doi:10.1016/j.jhydrol.2014.06.002

Cited by 17 publications

(28 citation statements)

References 37 publications

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“…In the southern part of the ACT–ACF the ENSO phase has the expected effect of increasing precipitation during El Niño; this effect is only statistically significant at a few southern stations and is reversed in the north of the ACT basin and is consistent with former studies (Kurtzman and Scanlon, ; Johnson et al ., ; Goly and Teegavarapu, ; Stevens and Ruscher, ). Several geographical effects likely lead to the north–south division of ENSO effects.…”

Section: Discussionmentioning

confidence: 99%

“…The effect of the AMO alone on precipitation was not statistically significant at individual stations; however, taking the mean precipitation anomaly across all stations, we found that the positive AMO is associated with decreased precipitation and the negative AMO to increased precipitation. This relation is consistent with previous studies (Enfield et al ., ; McCabe et al ., ; Tootle et al ., ; Johnson et al ., ; Goly and Teegavarapu, ; Stevens and Ruscher, ). The mechanism of the action of the AMO on the climate of North America is thought to be primarily by way of influencing the ridge trough pattern over North America; weakening the pattern during the AMO negative phase and strengthening the pattern during the AMO positive phase (Enfield et al ., ).…”

Section: Discussionmentioning

confidence: 99%

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Coupled impacts of ENSO AMO and PDO on temperature and precipitation in the Alabama–Coosa–Tallapoosa and Apalachicola–Chattahoochee–Flint river basins

Maleski

Martinez

2018

Intl Journal of Climatology

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Large‐scale patterns of ocean surface temperature can influence weather across the globe and understanding their interaction with the local climate can improve seasonal forecasting of local temperature and precipitation. Here we focus on the combined interactions of the El Niño‐Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO) in the Alabama–Coosa–Tallapoosa (ACT) and Apalachicola–Chattahoochee–Flint (ACF) river basins of the southeastern United States. Nonparametric ranks‐sum tests of individual and coupled impacts of these teleconnections on the annual study area climate (1895–2009) found significant impacts. A positive AMO phase was associated with decreased precipitation and increased mean temperature while the negative AMO phase was associated with increased precipitation and decreased temperature. While an El Niño event generally increases regional precipitation, El Niño during a positive AMO or PDO phase resulted in precipitation below the long‐term average in our study area. Because of many instances of El Niño being shared between AMO and PDO phase, the effects of the PDO and AMO on El Niño could not be distinguished. La Niña was associated with negative precipitation and increased temperature. The effects of La Niña on the temperature and precipitation anomaly were significantly increased during positive AMO and PDO phases. The coupled impacts of the aforementioned teleconnections demonstrate the necessity of including the effects of the AMO and the PDO when using ENSO‐based forecasts. The significant shifts on the effects of teleconnections on area climate from AMO negative phase to AMO positive phase cast doubt on seasonal prediction for the study area based on the recent history (i.e. the use of the period 1950–2000 to predict seasonal climate since 2000).

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Coupled impacts of ENSO AMO and PDO on temperature and precipitation in the Alabama–Coosa–Tallapoosa and Apalachicola–Chattahoochee–Flint river basins

Maleski

Martinez

2018

Intl Journal of Climatology

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“…This result is consistent with previous studies such as Stevens and Ruscher (2014), Wise et al (2015), and Ning and Bradley (2014). Stevens and Ruscher (2014) indicated that the sub-basins of the ACF are affected differently by multiple climatic oscillations, and no particular climatic oscillation can explain surface meteorological variation. Wise et al (2015) also emphasized the importance of considering multiple climatic oscillations when forecasting the seasonal rainfall variability.…”

Section: Discussionmentioning

confidence: 99%

“…The NAO index from 1901 to 2010 can be downloaded from the NOAA PSD website (http://www.esrl.noaa.gov/psd/ gcos_wgsp/Timeseries/NAO/). The AMO is a 60-85 year cycle of variable SSTs in the North Atlantic Ocean that has been shown to correlate with precipitation in the United States (Stevens and Ruscher, 2014). The AMO index is calculated using the Kaplan SST as the detrended time series of the area weighted averaged SST over the North Atlantic from 0 ∘ to 70 ∘ N (Enfield et al, 2001).…”

Section: Climatic Oscillationsmentioning

confidence: 99%

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Potential to improve precipitation forecasts in Texas through the incorporation of multiple teleconnections

Tian

Leasor

Quiring

2016

Intl Journal of Climatology

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Climate oscillations are one of the primary factors that influence precipitation. This study uses canonical correlation analysis (CCA) to examine how El Niño-Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation, North Atlantic Oscillation, Pacific Decadal Oscillation, and the Pacific-North American pattern influence precipitation in Texas. This study identifies the months, regions, and time lags where the relationships between climate oscillations and precipitation are strongest. Correlation results indicate that ENSO accounts for the greatest amount of precipitation variance in Texas. However, including all five climate oscillations is important and together they account for a greater amount of the variance in precipitation than any individual climate oscillation. Precipitation in southern Texas is more strongly influenced by climate oscillations than other regions in Texas. The CCA results demonstrate that there are statistically significant relationships between the climate oscillations and precipitation at time lags longer than 6 months during the summer and at time lags shorter than 6 months during the winter. Based on the CCA results, a precipitation forecast model was developed for the three climate regions that we defined. In the cases of January, the Heidke Skill Score (HSS) of our model is comparable or higher to those achieved by the Climate Prediction Center (CPC) in each region. For all of the 36 month/region cases (12 months × 3 regions), there are 50% cases that the HSS of our model is comparable or higher to those achieved by the CPC. The results of this study illustrate that including multiple teleconnections can increase forecast skill, and statistical methods are useful for precipitation forecasting at a 0-month lead time.

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A Nonstationary Standardized Precipitation Index incorporating climate indices as covariates

Wang

et al. 2015

JGR Atmospheres

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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.

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Large scale climate oscillations and mesoscale surface meteorological variability in the Apalachicola-Chattahoochee-Flint River Basin

Cited by 17 publications

References 37 publications

Coupled impacts of ENSO AMO and PDO on temperature and precipitation in the Alabama–Coosa–Tallapoosa and Apalachicola–Chattahoochee–Flint river basins

Coupled impacts of ENSO AMO and PDO on temperature and precipitation in the Alabama–Coosa–Tallapoosa and Apalachicola–Chattahoochee–Flint river basins

Potential to improve precipitation forecasts in Texas through the incorporation of multiple teleconnections

A Nonstationary Standardized Precipitation Index incorporating climate indices as covariates

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