Non-parametric short-term forecasts of the Great Salt Lake using atmospheric indices

Moon, Young‐Il; Lall, Upmanu; Kwon, Hyun‐Han

doi:10.1002/joc.1533

Cited by 10 publications

(11 citation statements)

References 30 publications

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“…Prior research has taken a statistical and systems dynamics approach to predicting the volume and level of the GSL [ Lall et al , 2006; Moon et al , 2008; Wang et al , 2010]. This approach exploits the idea that the GSL is a low‐frequency filter of climate inputs.…”

Section: Introductionmentioning

confidence: 99%

“… Moon et al [2008] and Moon and Lall [1996] studied the relationships between the time variability of the volume of GSL and selected atmospheric circulation indices. They developed and applied nonlinear measures of dependence between atmospheric circulation indices and the GSL volume at various lags (presuming that these indices are considered to lead the GSL volume) to develop forecasts of the volume of the GSL using selected atmospheric circulation indices.…”

Section: Introductionmentioning

confidence: 99%

“…The indices considered were the Southern Oscillation Index (SOI), the Pacific–North America (PNA) climatic pattern and the Central North Pacific (CNP) climatic pattern. Moon et al [2008] applied the local weighted polynomials methodology discussed by Lall et al [2006] to predict the volume of the GSL using both the above mentioned atmospheric indices and previous lake volumes and suggested that predictions of GSL volumes using the local polynomial regression approach can lead to significant improvements in the predictability of lake volume.…”

Section: Introductionmentioning

confidence: 99%

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An examination of the sensitivity of the Great Salt Lake to changes in inputs

Mohammed

Tarboton²

2012

Water Resources Research

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[1] The Great Salt Lake is a closed basin lake in which level and volume fluctuate due to differences between inflows and outflows. The only outflow is evaporation, which depends directly on lake area and salinity, both of which depend on lake volume. The lake's level, volume, and area adjust to balance, on average, precipitation and streamflow inflows by evaporation. In this paper, we examine the sensitivity of lake volume changes to precipitation, streamflow, and evaporation and the interactions among these processes and lake area and salinity related to volume. A mass balance model is developed to generate representative realizations of future lake level from climate and streamflow inputs simulated using the k-nearest-neighbor method. Climate and salinity are used to estimate evaporation from the lake using a Penman model adjusted for the salinity-dependent saturation vapor pressure. Our results show that fluctuation in streamflow is the dominant factor in lake level fluctuations, but fluctuations in lake area that modulate evaporation and precipitation directly on the lake are also important. The results also quantify the sensitivity of lake level to changes in streamflow and air temperature inputs. They predict that a 25% decrease in streamflow would reduce lake level by about 66 cm (2.2 feet), while a þ4 C air temperature increase would reduce lake level by about 34 cm (1.1 feet) on average. This sensitivity is important in evaluating the impacts of climate change or streamflow change due to increased consumptive water use on the level of the lake.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An examination of the sensitivity of the Great Salt Lake to changes in inputs

Mohammed

Tarboton²

2012

Water Resources Research

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“…Such features have challenged numerous attempts to forecast GSL volume variations; for example, by traditional Box-Jenkins methods (James et al 1984), nonparametric forecasting Lall et al 1996;Sangoyomi et al 1996), singular spectral analysis (Moon and Lall 1996), and locally weighted polynomial regression (Lall et al 2006). Such features have challenged numerous attempts to forecast GSL volume variations; for example, by traditional Box-Jenkins methods (James et al 1984), nonparametric forecasting Lall et al 1996;Sangoyomi et al 1996), singular spectral analysis (Moon and Lall 1996), and locally weighted polynomial regression (Lall et al 2006).…”

Section: Introductionmentioning

confidence: 99%

Incorporation of Pacific SSTs in a Time Series Model toward a Longer-Term Forecast for the Great Salt Lake Elevation

Gillies

Chung

Wang

et al. 2011

Journal of Hydrometeorology

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A recent study identified a pronounced lagged relationship between the Great Salt Lake's (GSL) elevation and the central tropical Pacific sea surface temperatures (SST) at the 10-15-year time scale. Using this relationship, a principal component analysis of historical time series of SST and local precipitation (P) was used in the construction of a lagged regression model to predict first the GSL elevation tendency and, from there, the GSL elevation. The combined principal component-lagged regression model was able to replicate and forecast turnarounds in the GSL elevation-that is, where prolonged increasing trends were followed by persistent decreases and vice versa. The coupling of the two time series is somewhat different from previous nonparametric, nonlinear time series methods developed for shorter-term (1-2 year) forecasts of the GSL volume. Moreover, by not accounting for interannual variability in the model, a forecast out to 6 years was feasible and was shown to intersect the 2009 and 2010 observations of the GSL elevation.

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“…The indices considered in his study were the Southern Oscillation index, The Pacific–North America (PNA) climatic pattern, and the central North Pacific climatic pattern. Moon et al [2008] improved Moon 's [1995] earlier GSL forecasts by including a local predictive risk measure to guide the forecast process.…”

Section: Introductionmentioning

confidence: 99%

On the interaction between bathymetry and climate in the system dynamics and preferred levels of the Great Salt Lake

Mohammed

Tarboton

2011

Water Resources Research

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The Great Salt Lake is a terminal lake whose level is determined by the balance between inflows and outflows. We examine the causes for multimodality in the distributions of lake level and hence volume and area that have previously been examined from a system dynamics perspective. We focus on the role of bathymetry in the dynamics of this system and show that some of the modes that are observed and that represent preferred system states are attributable to features of the bathymetry described using the topographic area‐volume relationship. Being a terminal lake, the only “outflow” is evaporation, which depends directly on lake area, which adjusts (with stochastic fluctuations) to balance inflows. Where the topographic side slopes are relatively flat and the lake goes through a large change in area for a given increase in level, the outflux evaporation will go through a corresponding large change, tending to stabilize the lake at that point. Conversely, where topographic side slopes are relatively steep, the stabilizing effect is diminished. This effect was quantified using the derivative of the lake area–lake volume function determined from U.S. Geological Survey topographic and bathymetric surveys. We show how some of the observed modes that represent preferred lake volume states are attributable to peaks in this area‐volume derivative, while a complete description of the observed distribution of lake volume requires combining the bathymetry represented by the area‐volume derivative with a multimodal lake area distribution that may be connected to multimodality in the aggregate hydrological forcing.

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Non-parametric short-term forecasts of the Great Salt Lake using atmospheric indices

Cited by 10 publications

References 30 publications

An examination of the sensitivity of the Great Salt Lake to changes in inputs

An examination of the sensitivity of the Great Salt Lake to changes in inputs

Incorporation of Pacific SSTs in a Time Series Model toward a Longer-Term Forecast for the Great Salt Lake Elevation

On the interaction between bathymetry and climate in the system dynamics and preferred levels of the Great Salt Lake

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