scholarly journals Application of climate data to predict pasture production

2008 ◽  
pp. 145-151
Author(s):  
I.C. Blair
Keyword(s):  
Soil Moisture ◽  
Climate Variability ◽  
Pacific Decadal Oscillation ◽  
Southern Oscillation Index ◽  
Reliable Method ◽  
Southern Oscillation ◽  
Climate Data ◽  
Pasture Production ◽  
Production Models ◽  
Soil Moisture Status

With increasing climate variability, a reliable method of estimating pasture growth has eluded farmers. Rain, temperature, evapotranspiration, radiation and soil moisture status are components which interact and affect pasture production. In 1992, soil moisture monitoring in Marlborough vineyards was extended to pasture. Keywords: soil moisture, pasture production, models, Southern Oscillation Index, Pacific Decadal Oscillation

scholarly journals Impact of Indo-Pacific Climate Variability on Rice Productivity in Bihar, India

2020 ◽  
Vol 12 (17) ◽  
pp. 7023 ◽  
Author(s):  
Netrananda Sahu ◽  
Atul Saini ◽  
Swadhin Behera ◽  
Takahiro Sayama ◽  
Sridhara Nayak ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Climate Variability ◽  
Southern Oscillation Index ◽  
Partial Correlation ◽  
Southern Oscillation ◽  
Maximum Temperature ◽  
Climate Indices ◽  
Rice Productivity ◽  
Pacific Climate Variability ◽  
The Impact

The impact of Indo-Pacific climate variability in the South Asian region is very pronounced and their impact on agriculture is very important for the Indian subcontinent. In this study, rice productivity, climatic factors (Rainfall, Temperature and Soil Moisture) and associated major Indo-Pacific climate indices in Bihar were investigated. Bihar is one of the major rice-producing states of India and the role of climate variability and prevailing climate indices in six events (between 1991–2014) with severer than −10% rice productivity are analyzed. The Five-year moving average, Pearson’s Product Moment Correlation, Partial Correlation, Linear Regression Model, Mann Kendall Test, Sen’s Slope and some other important statistical techniques were used to understand the association between climatic variables and rice productivity. Pearson’s Product Moment Correlation provided an overview of the significant correlation between climate indices and rice productivity. Whereas, Partial Correlation provided the most refined results on it and among all the climate indices, Niño 3, Ocean Niño Index and Southern Oscillation Index are found highly associated with years having severer than −10% decline in rice productivity. Rainfall, temperature and soil moisture anomalies are analyzed to observe the importance of climate factors in rice productivity. Along with the lack of rainfall, lack of soil moisture and persistent above normal temperature (especially maximum temperature) are found to be the important factors in cases of severe loss in rice productivity. Observation of the dynamics of ocean-atmosphere coupling through the composite map shows the Pacific warming signals during the event years. The analysis revealed a negative (positive) correlation of rice productivity with the Niño 3 and Ocean Niño Index (Southern Oscillation Index).

VARIABILIDAD CLIMÁTICA, CAMBIO CLIMÁTICO Y PESQUERÍAS EN EL ECUADOR.

2012 ◽  
Vol 1 (1) ◽  
Author(s):  
Johnny Chavarría Viteri ◽  
Dennis Tomalá Solano
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Pacific Decadal Oscillation ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Current Action ◽  
Palabras Clave

La variabilidad climática es la norma que ha modulado la vida en el planeta. Este trabajo demuestra que las pesquerías y acuicultura costera ecuatorianas no son la excepción, puesto que tales actividades están fuertemente influenciadas por la variabilidad ENSO (El Niño-Oscilación del Sur) y PDO (Oscilación Decadal del Pacífico), planteándose que la señal del cambio climático debe contribuir a esta influencia. Se destaca también que, en el análisis de los efectos de la variabilidad climática sobre los recursos pesqueros, el esfuerzo extractivo también debe ser considerado. Por su parte, la acción actual de la PDO está afectando la señal del cambio climático, encontrándose actualmente en fases opuestas. Se espera que estas señales entren en fase a finales de esta década, y principalmente durante la década de los 20 y consecuentemente se evidencien con mayor fuerza los efectos del Cambio Climático. Palabras Clave: Variabilidad Climática, Cambio Climático, ENSO, PDO, Pesquerías, Ecuador. ABSTRACT Climate variability is the standard that has modulated life in the planet. This work shows that the Ecuadorian  fisheries and aquaculture are not the exception, since such activities are strongly influenced by ENSO variability (El Niño - Southern Oscillation) and PDO (Pacific Decadal Oscillation), considering that the signal of climate change should contribute to this influence. It also emphasizes that in the analysis of the effects of climate variability on the fishing resources, the extractive effort must also be considered. For its part, the current action of the PDO is affecting the signal of climate change, now found on opposite phases. It is hoped that these signals come into phase at the end of this decade, and especially during the decade of the 20’s and more strongly evidencing the effects of climate change. Keywords: Climate variability, climate change, ENSO (El Niño - Southern Oscillation) and PDO  (Pacific Decadal Oscillation); fisheries, Ecuador. Recibido: mayo, 2012Aprobado: agosto, 2012

scholarly journals Glacier annual balance measurement, forecasting and climate correlations, North Cascades, Washington 1984–2006

2008 ◽  
Vol 2 (1) ◽  
pp. 13-21 ◽  
Author(s):  
M. S. Pelto
Keyword(s):  
Pacific Decadal Oscillation ◽  
Water Resource Management ◽  
Southern Oscillation Index ◽  
Southern Oscillation ◽  
Significant Loss ◽  
Glacier Mass Balance ◽  
North Cascades ◽  
Entire Volume ◽  
Glacier Runoff ◽  
Annual Balance

Abstract. North Cascade glacier annual balance measured on 10 glaciers from 1984–2006 yielded mean annual balance (ba) of −0.54 m/a, and −12.38 m cumulatively. This is a significant loss for glaciers that average 30–60 m in thickness, 20–40% of their entire volume. Two observed glaciers, Lewis Glacier and Spider Glacier, no longer exist. The ba of North Cascade glaciers is reliably calculated, correlation coefficient 0.91, using 1 April snowpack water equivalent and ablation season temperature. Utilizing ba from 10 glaciers 1984–2006 and net balance (bn) from South Cascade 1960–2005, a set of forecast rules for glacier mass balance were derived utilizing October–April Pacific Decadal Oscillation and Multivariate El Nino Southern Oscillation index values. The forecast rules provide a correct assessment in 41 of the 46 years for South Cascade Glacier and 20 of 23 years for NCGCP glaciers. Glacier annual balance forecasting is an important step for summer water resource management in glacier runoff dominated stream systems. The forecast for North Cascade glaciers in 2007 is for a negative ba.

scholarly journals Comparing the climate experienced during the Cicerone farmlet experiment against the climatic record

2013 ◽  
Vol 53 (8) ◽  
pp. 658 ◽  
Author(s):  
K. Behrendt ◽  
J. M. Scott ◽  
D. F. Mackay ◽  
R. Murison
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Wavelet Transforms ◽  
Experimental Period ◽  
Moisture Stress ◽  
Climatic Conditions ◽  
Climate Data ◽  
Pasture Production ◽  
Systems Research ◽  
Climatic Record

Farming systems research conducted under dryland conditions is subject to the vagaries of the climate during the experimental period. Whether such an experiment experiences a representative series of climatic years must be examined in relation to the longer term climatic record. The Cicerone Project’s farmlet experiment was conducted on the Northern Tablelands of New South Wales, Australia, to investigate the profitability and sustainability of three different management systems: one managed under typical, moderate-input conditions (farmlet B); a second which employed a higher level of pasture inputs and soil fertility (farmlet A); and a third which focussed on the use of moderate inputs and intensive rotational grazing (farmlet C). The climate experienced during the 6.5-year experimental period was compared with the 118-year climatic record, using a biophysical simulation model of grazed systems. The model utilised the long-term daily climate data as inputs and provided outputs that allowed comparison of parameters known to affect grazed pastures. Modelled soil-available water, the number of soil moisture stress days (SMSDs) limiting pasture growth, and growth indices over the experimental period (2000–06) were compared with data over the climatic record from 1890 to 2007. SMSDs were defined as when the modelled available soil moisture to a depth of 300 mm was <17% of water-holding capacity. In addition, minimum temperatures and, in particular, the frequency of frosts, were compared with medium-term (1981–2011) temperature records. Wavelet transforms of rainfall and modelled available soil water data were used to separate profile features of these parameters from the noise components of the data. Over the experimental period, both rainfall and available soil water were more commonly significantly below than above the 95% confidence intervals of both parameters. In addition, there was an increased frequency of severe frosting during the dry winters experienced over the 6.5-year period. These dry and cold conditions were likely to have limited the responses to the pasture and grazing management treatments imposed on the three farmlets. In particular, lower than average levels of available soil water were likely to have constrained pasture production, threatened pasture persistence, and reduced the response of the pasture to available soil nutrients and, as a consequence, livestock production and economic outcomes. Ideally, dryland field experimentation should be conducted over a representative range of climatic conditions, including soil moisture conditions both drier and wetter than average. The drier than average conditions, combined with a higher than normal frequency of severe frosts, mean that the results from the Cicerone Project’s farmlet experiment need to be viewed in the context of the climate experienced over this 6.5-year period.

scholarly journals Linking the atmospheric Pacific-South American mode with oceanic variability and predictability

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Jiale Lou ◽  
Terence J. O’Kane ◽  
Neil J. Holbrook
Keyword(s):  
Climate Variability ◽  
Pacific Decadal Oscillation ◽  
Southern Oscillation ◽  
South Pacific ◽  
Reanalysis Data ◽  
South American ◽  
The South ◽  
Climate Signal ◽  
Pacific Climate Variability ◽  
Oceanic Variability

AbstractWhile Pacific climate variability is largely understood based on El Niño-Southern Oscillation (ENSO), the North Pacific focused Pacific decadal oscillation and the basin-wide interdecadal Pacific oscillation, the role of the South Pacific, including atmospheric drivers and cross-scale interactions, has received less attention. Using reanalysis data and model outputs, here we propose a paradigm for South Pacific climate variability whereby the atmospheric Pacific-South American (PSA) mode acts to excite multiscale spatiotemporal responses in the upper South Pacific Ocean. We find the second mid-troposphere PSA pattern is fundamental to stochastically generate a mid-latitude sea surface temperature quadrupole pattern that represents the optimal precursor for the predictability and evolution of both the South Pacific decadal oscillation and ENSO several seasons in advance. We find that the PSA mode is the key driver of oceanic variability in the South Pacific subtropics that generates a potentially predictable climate signal linked to the tropics.

scholarly journals Combined Effects of the Southern Oscillation Index and the Pacific Decadal Oscillation on a Stochastic Daily Precipitation Model*

2008 ◽  
Vol 21 (5) ◽  
pp. 1139-1152 ◽  
Author(s):  
David A. Woolhiser
Keyword(s):  
Markov Chain ◽  
New Mexico ◽  
Pacific Decadal Oscillation ◽  
Southern Oscillation Index ◽  
Daily Precipitation ◽  
Transition Probabilities ◽  
Southern Oscillation ◽  
Combined Effects ◽  
The Pacific ◽  
The Mean

Abstract The combined effects of the Southern Oscillation index (SOI) and the Pacific decadal oscillation (PDO) on a second-order Markov chain mixed exponential daily precipitation model were determined for 15 stations in Nevada, Arizona, New Mexico, and Washington. The linkage between these monthly indices and daily precipitation was investigated by perturbing logits of Markov chain transition probabilities and the mean of the mixed exponential distribution by linear functions of a time-lagged SOI and concurrent PDO. The combination of linear coefficients and lags that resulted in the maximum log-likelihood functions was identified, and the Akaike information criterion (AIC) was used to determine the best model. The SOI effect was consistent with previous studies in that negative SOI (El Niño) leads to more frequent precipitation and greater amounts of precipitation given a wet day in Nevada and the Southwest, with the opposite effect in the northwest. SOI and PDO interactions were most significant for the Nevada stations where a positive PDO increases both the probability of a wet day for three transition probabilities and also increases the mean of wet-day precipitation. The PDO had little effect for the monsoonal (Arizona and New Mexico) stations except for Hobbs, New Mexico, where a positive PDO would increase the mean depth on a wet day. The Washington stations showed an increase in the frequency and mean depth of precipitation given a positive SOI, but PDO had little effect. Identification of combined SOI–PDO effects allows more realistic simulations of daily precipitation and provides insight into the reliability of short records.

LIME AND DAIRY PRODUCTION

1982 ◽  
pp. 93-103
Author(s):  
N.A. Thomson
Keyword(s):  
Soil Moisture ◽  
Dairy Cows ◽  
Milk Production ◽  
Soil Ph ◽  
Dairy Production ◽  
Pasture Production ◽  
The Third ◽  
One Year ◽  
Plasma Magnesium

In a four year grazing trial with dairy cows the application of 5000 kg lime/ ha (applied in two applications of 2500 kg/ha in winter of the first two years) significantly increased annual pasture production in two of the four years and dairy production in one year. In three of the four years lime significantly increased pasture growth over summer/autumn with concurrent increases in milk production. In the last year of the trial lime had little effect on pasture growth but a relatively large increase in milkfat production resulted. A higher incidence of grass staggers was recorded on the limed farmlets in spring for each of the four years. In the second spring immediately following the second application of lime significant depressions in both pasture and plasma magnesium levels were recorded. By the third spring differences in plasma magnesium levels were negligible but small depressions in herbage magnesium resulting from lime continued to the end of the trial. Lime significantly raised soil pH, Ca and Mg levels but had no effect on either soil K or P. As pH levels of the unlimed paddocks were low (5.2-5.4) in each autumn and soil moisture levels were increased by liming, these factors may suggest possible causes for the seasonality of the pasture response to lime

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.

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