scholarly journals Development of Precise Indices for Assessing the Potential Impacts of Climate Change

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1231
Author(s):  
Vinay Kumar
Keyword(s):  
Climate Change ◽  
Southern Oscillation ◽  
Diversity Index ◽  
Region Of Interest ◽  
Heavy Precipitation ◽  
Climate Index ◽  
Climate Indices ◽  
Special Issue ◽  
Indonesian Archipelago ◽  
Weather And Climate

The Special Issue on climate indices and climate change deals with various kinds of indices exits to assess weather and climate over a region. These indices might be based on local, regional, remote variables, which may affect and define the weather and climate of a region. Climate indices are the time series used to monitor the state of the climate and its relationship with other possible causes. With indices being myriad, it is challenging to choose which one is appropriate for a region of interest. However, the relationship between the indices and the climate of a region varies. El-Nino Southern Oscillation (Southern Oscillation Index, SOI/ENSO) is one of the most robust climate signals that stimulate rainfall, temperature, and hurricanes via teleconnections. SOI has a correlation of 0.5 over the Indonesian archipelago. Here, some of the well-known indices Holiday Climate Index (HCI), Tourism Climate Index (TCI), and Simple Diversity Index (SDI) are being reconnoitered to understand the holiday-tourism, end-of-the-day (EOD) judgment. The intrusion of dry air in the middle troposphere can create unstable weather, leading to heavy precipitation. The Special Issue seeks to encourage researchers to discover new indices in multidisciplinary department of atmospheric and physical sciences.

scholarly journals Evaluating the Tourist Climate Comfortable Period of China in a Changing Climate

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Dan-Dan Yu ◽  
Shan Li ◽  
Zhong-Yang Guo
Keyword(s):  
Climate Change ◽  
Global Climate ◽  
Scientific Evidence ◽  
Climatic Conditions ◽  
Climate Index ◽  
Climate Indices ◽  
Climate Data ◽  
Climate Conditions ◽  
Positive Effects ◽  
Changing Climate

The evaluation of climate comfort for tourism can provide information for tourists selecting destinations and tourism operators. Understanding how climate conditions for tourism evolve is increasingly important for strategic tourism planning, particularly in rapidly developing tourism markets like China in a changing climate. Multidimensional climate indices are needed to evaluate climate for tourism, and previous studies in China have used the much criticized “climate index” with low resolution climate data. This study uses the Holiday Climate Index (HCI) and daily data from 775 weather stations to examine interregional differences in the tourist climate comfortable period (TCCP) across China and summarizes the spatiotemporal evolution of TCCP from 1981 to 2010 in a changing climate. Overall, most areas in China have an “excellent” climate for tourism, such that tourists may visit anytime with many choices available. The TCCP in most regions shows an increasing trend, and China benefits more from positive effects of climate change in climatic conditions for tourism, especially in spring and autumn. These results can provide some scientific evidence for understanding human settlement environmental constructions and further contribute in improving local or regional resilience responding to global climate change.

scholarly journals USING GLOBAL CLIMATE INDICES TO PREDICT RAINFALL AND SUGARCANE PRODUCTIVITY IN DRYLANDS OF BANYUWANGI, EAST JAVA, INDONESIA

2020 ◽  
Vol 21 (2) ◽  
pp. 78
Author(s):  
Muhammad Rasyid Ridla Ranomahera ◽  
Bayu Dwi Apri Nugroho ◽  
Prima Diarini Riajaya ◽  
Rivandi Pranandita Putra
Keyword(s):  
Southern Oscillation ◽  
Global Climate ◽  
Saccharum Officinarum ◽  
Crop Productivity ◽  
Climate Index ◽  
Climate Indices ◽  
Sugar Mills ◽  
Index Rainfall ◽  
Using Data ◽  
Sugarcane Productivity

<p>In Indonesia, sugarcane (<em>Saccharum officinarum </em>L.) is mostly cultivated in drylands, thus depending on rainfall for crop growth and development. Rainfall is an essential factor affecting sugarcane productivity. The global climate indices can be used to investigate potential of rainfall within a given area and its relationship with crop productivity. This reserach aimed to analyze the relationship between the global climate index, rainfall, and sugarcane productivity in drylands near Glenmore sugar mill, i.e., Benculuk and Jolondoro, Banyuwangi, East Java, Indonesia. The global climate index data used were the Southern Oscillation Index (SOI) and Sea Surface Temperature (SST) between 1995 and 2014. Results of this research showed that SOI and SST can be used to predict the rainfall in both Benculuk and Jolondoro. Rainfall (y) can be predicted with SST data (x) using the equation of y = -352.49x + 7724.1 in Benculuk and y = -107.32 + 3443.4 in Jolondoro, as well as with SOI data (x) using the equation of y = 38.664x + 1555.1 in Benculuk and y = 10.541x + 1567.8 in Jolondoro. Sugarcane productivity (y) in Jolondoro can be predicted using data of total rainfall (x) between October and March with the following equation: y = -0.1672x + 1157.3. This equation can be used by sugar mills, sugarcane growers, and other sugarcane-relevant stakeholders for determining the appropriate growing season.</p>

scholarly journals Combined analysis of temperature and rainfall variability as they relate to climate indices in Northern Algeria over the 1972–2013 period

2016 ◽  
Vol 48 (2) ◽  
pp. 584-595 ◽  
Author(s):  
Ayoub Zeroual ◽  
Ali A. Assani ◽  
Mohamed Meddi
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Coastal Region ◽  
Western Mediterranean ◽  
Seasonal Rainfall ◽  
Climate Index ◽  
Climate Indices ◽  
Mean Values ◽  
Northern Algeria

Many studies have highlighted breaks in mean values of temperature and precipitation time series since the 1970s. Given that temperatures have continued to increase following that decade, the first question addressed in this study is whether other breaks in mean values have occurred since that time. The second question is to determine which climate indices influence temperature and rainfall in the coastal region of Northern Algeria. To address these two questions, we analyzed the temporal variability of temperature and annual and seasonal rainfall as they relate to four climate indices at seven coastal stations in Algeria during the 1972–2013 period using the Mann–Kendall, Lombard, and canonical correlation (CC) analysis methods.The annual and seasonal maximum, minimum and mean temperatures increased significantly over that time period. Most of these increases are gradual, implying a slow warming trend. In contrast, total annual and seasonal rainfall did not show any significant change. CC analysis revealed that annual and seasonal temperatures are negatively correlated with the Western Mediterranean Oscillation (WeMOI) climate index that characterizes atmospheric circulation over the Mediterranean basin. On the other hand, rainfall is positively correlated with a large-scale atmospheric index such as the Southern Oscillation Index.

scholarly journals The changing physical and ecological meanings of North Pacific Ocean climate indices

2020 ◽  
Vol 117 (14) ◽  
pp. 7665-7671 ◽  
Author(s):  
Michael A. Litzow ◽  
Mary E. Hunsicker ◽  
Nicholas A. Bond ◽  
Brian J. Burke ◽  
Curry J. Cunningham ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Historical Record ◽  
Climate Index ◽  
Climate Indices ◽  
Northeast Pacific ◽  
Temporal Variance ◽  
Basin Scale

Climate change is likely to change the relationships between commonly used climate indices and underlying patterns of climate variability, but this complexity is rarely considered in studies using climate indices. Here, we show that the physical and ecological conditions mapping onto the Pacific Decadal Oscillation (PDO) index and North Pacific Gyre Oscillation (NPGO) index have changed over multidecadal timescales. These changes apparently began around a 1988/1989 North Pacific climate shift that was marked by abrupt northeast Pacific warming, declining temporal variance in the Aleutian Low (a leading atmospheric driver of the PDO), and increasing correlation between the PDO and NPGO patterns. Sea level pressure and surface temperature patterns associated with each climate index changed after 1988/1989, indicating that identical index values reflect different states of basin-scale climate over time. The PDO and NPGO also show time-dependent skill as indices of regional northeast Pacific ecosystem variability. Since the late 1980s, both indices have become less relevant to physical–ecological variability in regional ecosystems from the Bering Sea to the southern California Current. Users of these climate indices should be aware of nonstationary relationships with underlying climate variability within the historical record, and the potential for further nonstationarity with ongoing climate change.

scholarly journals Seasonal streamflow forecasting in the upper Indus Basin of Pakistan: an assessment of methods

2018 ◽  
Vol 22 (6) ◽  
pp. 3533-3549 ◽  
Author(s):  
Stephen P. Charles ◽  
Quan J. Wang ◽  
Mobin-ud-Din Ahmad ◽  
Danial Hashmi ◽  
Andrew Schepen ◽  
...  
Keyword(s):  
Southern Oscillation ◽  
Hybrid Approach ◽  
Indus Basin ◽  
Climate Index ◽  
Climate Indices ◽  
Streamflow Forecasting ◽  
Upper Indus Basin ◽  
Probabilistic Forecasts ◽  
Streamflow Forecasts ◽  
Seasonal Streamflow

Abstract. Timely and skilful seasonal streamflow forecasts are used by water managers in many regions of the world for seasonal water allocation outlooks for irrigators, reservoir operations, environmental flow management, water markets and drought response strategies. In Australia, the Bayesian joint probability (BJP) statistical approach has been deployed by the Australian Bureau of Meteorology to provide seasonal streamflow forecasts across the country since 2010. Here we assess the BJP approach, using antecedent conditions and climate indices as predictors, to produce Kharif season (April–September) streamflow forecasts for inflow to Pakistan's two largest upper Indus Basin (UIB) water supply dams, Tarbela (on the Indus) and Mangla (on the Jhelum). For Mangla, we compare these BJP forecasts to (i) ensemble streamflow predictions (ESPs) from the snowmelt runoff model (SRM) and (ii) a hybrid approach using the BJP with SRM–ESP forecast means as an additional predictor. For Tarbela, we only assess BJP forecasts using antecedent and climate predictors as we did not have access to SRM for this location. Cross validation of the streamflow forecasts shows that the BJP approach using two predictors (March flow and an El Niño Southern Oscillation, ENSO, climate index) provides skilful probabilistic forecasts that are reliable in uncertainty spread for both Mangla and Tarbela. For Mangla, the SRM approach leads to forecasts that exhibit some bias and are unreliable in uncertainty spread, and the hybrid approach does not result in better forecast skill. Skill levels for Kharif (April–September), early Kharif (April–June) and late Kharif (July–September) BJP forecasts vary between the two locations. Forecasts for Mangla show high skill for early Kharif and moderate skill for all Kharif and late Kharif, whereas forecasts for Tarbela also show moderate skill for all Kharif and late Kharif, but low skill for early Kharif. The BJP approach is simple to apply, with small input data requirements and automated calibration and forecast generation. It offers a tool for rapid deployment at many locations across the UIB to provide probabilistic seasonal streamflow forecasts that can inform Pakistan's basin water management.

scholarly journals Describing rainfall in northern Australia using multiple climate indices

2016 ◽  
Author(s):  
Cassandra Rogers ◽  
Jason Beringer
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Climate Index ◽  
Climate Indices ◽  
Human Populations ◽  
Wet Season ◽  
Australian Monsoon ◽  
The North

Abstract. Savanna landscapes are globally extensive and highly sensitive to climate change, yet the physical processes and climate phenomena which affect them remain poorly understood and therefore poorly represented in climate models. Both human populations and natural ecosystems are highly susceptible to precipitation variation in these regions due to the implications on water and food availability and atmosphere-biosphere energy fluxes. Here we quantify the relationship between climate phenomena and historical rainfall variability in Australian savannas, and in particular, how these relationships changed across a strong rainfall gradient, namely the North Australian Tropical Transect (NATT). Climate phenomena were described by 16 relevant climate indices and correlated against precipitation from 1900 to 2010 to determine the relative importance of each climate index on seasonal, inter-annual and decadal time scales. Precipitation trends, climate index trends, and wet season characteristics have also been investigated using linear statistical methods. In general, climate index-rainfall correlations were stronger in the north of the NATT where inter-annual rainfall variability was lower and a high proportion of rainfall fell during the wet season. This is consistent with a decreased influence of the Indian-Australian monsoon from the north to the south. Seasonal variation was most strongly correlated with the Australian Monsoon Index, whereas inter-annual variability was related to a greater number of climatic phenomena (predominately the El Niño-Southern Oscillation along with Tasman Sea and Indonesian sea surface temperatures). These findings highlight the importance of rainfall variability and the need to understand the climate processes driving variability, and subsequently being able to accurately represent these in climate models in order to project future rainfall patterns in the Northern Territory.

scholarly journals Describing rainfall in northern Australia using multiple climate indices

2017 ◽  
Vol 14 (3) ◽  
pp. 597-615 ◽  
Author(s):  
Cassandra Denise Wilks Rogers ◽  
Jason Beringer
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Climate Index ◽  
Climate Indices ◽  
Human Populations ◽  
Wet Season ◽  
Australian Monsoon ◽  
The North

Abstract. Savanna landscapes are globally extensive and highly sensitive to climate change, yet the physical processes and climate phenomena which affect them remain poorly understood and therefore poorly represented in climate models. Both human populations and natural ecosystems are highly susceptible to precipitation variation in these regions due to the effects on water and food availability and atmosphere–biosphere energy fluxes. Here we quantify the relationship between climate phenomena and historical rainfall variability in Australian savannas and, in particular, how these relationships changed across a strong rainfall gradient, namely the North Australian Tropical Transect (NATT). Climate phenomena were described by 16 relevant climate indices and correlated against precipitation from 1900 to 2010 to determine the relative importance of each climate index on seasonal, annual and decadal timescales. Precipitation trends, climate index trends and wet season characteristics have also been investigated using linear statistical methods. In general, climate index–rainfall correlations were stronger in the north of the NATT where annual rainfall variability was lower and a high proportion of rainfall fell during the wet season. This is consistent with a decreased influence of the Indian–Australian monsoon from the north to the south. Seasonal variation was most strongly correlated with the Australian Monsoon Index, whereas yearly variability was related to a greater number of climate indices, predominately the Tasman Sea and Indonesian sea surface temperature indices (both of which experienced a linear increase over the duration of the study) and the El Niño–Southern Oscillation indices. These findings highlight the importance of understanding the climatic processes driving variability and, subsequently, the importance of understanding the relationships between rainfall and climatic phenomena in the Northern Territory in order to project future rainfall patterns in the region.

scholarly journals Marine lake ecosystem dynamics illustrate ENSO variation in the tropical western Pacific

2005 ◽  
Vol 2 (1) ◽  
pp. 144-147 ◽  
Author(s):  
Laura E Martin ◽  
Michael N Dawson ◽  
Lori J Bell ◽  
Patrick L Colin
Keyword(s):  
Climate Change ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Ecosystem Dynamics ◽  
Western Pacific ◽  
Climate Index ◽  
Lake Ecosystem ◽  
Sediment Record ◽  
Tropical Western Pacific

Understanding El Niño/Southern Oscillation (ENSO) and its biological consequences is hindered by a lack of high-resolution, long-term data from the tropical western Pacific. We describe a preliminary, 6 year dataset that shows tightly coupled ENSO-related bio-physical dynamics in a seawater lake in Palau, Micronesia. The lake is more strongly stratified during La Niña than El Niño conditions, temperature anomalies in the lake co-vary strongly with the Niño 3.4 climate index, and the abundance of the dominant member of the pelagic community, an endemic subspecies of zooxanthellate jellyfish, is temperature associated. These results have broad relevance because the lake: (i) illustrates an ENSO signal that is partly obscured in surrounding semi-enclosed lagoon waters and, therefore, (ii) may provide a model system for studying the effects of climate change on community evolution and cnidarian–zooxanthellae symbioses, which (iii) should be traceable throughout the Holocene because the lake harbours a high quality sediment record; the sediment record should (iv) provide a sensitive and regionally unique record of Holocene climate relevant to predicting ENSO responses to future global climate change and, finally, (v) seawater lake ecosystems elsewhere in the Pacific may hold similar potential for past, present, and predictive measurements of climate variation and ecosystem response.

scholarly journals Effects of weather and climate on the dynamics of animal population time series

2010 ◽  
Vol 278 (1708) ◽  
pp. 985-992 ◽  
Author(s):  
Jonas Knape ◽  
Perry de Valpine
Keyword(s):  
Time Series ◽  
Population Dynamics ◽  
Population Change ◽  
A Priori ◽  
Randomization Test ◽  
Weather Data ◽  
Climate Index ◽  
Climate Indices ◽  
Animal Populations ◽  
Weather And Climate

Weather is one of the most basic factors impacting animal populations, but the typical strength of such impacts on population dynamics is unknown. We incorporate weather and climate index data into analysis of 492 time series of mammals, birds and insects from the global population dynamics database. A conundrum is that a multitude of weather data may a priori be considered potentially important and hence present a risk of statistical over-fitting. We find that model selection or averaging alone could spuriously indicate that weather provides strong improvements to short-term population prediction accuracy. However, a block randomization test reveals that most improvements result from over-fitting. Weather and climate variables do, in general, improve predictions, but improvements were barely detectable despite the large number of datasets considered. Climate indices such as North Atlantic Oscillation are not better predictors of population change than local weather variables. Insect time series are typically less predictable than bird or mammal time series, although all taxonomic classes display low predictability. Our results are in line with the view that population dynamics is often too complex to allow resolving mechanisms from time series, but we argue that time series analysis can still be useful for estimating net environmental effects.

scholarly journals What climate change means for farmers in Africa: A triptych review Left panel: Increasing climate variability and a response approach for African farmers

2014 ◽  
Vol 14 (61) ◽  
pp. 8445-8458
Author(s):  
CJ Stigter ◽  
◽  
E Ofori ◽  
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Climate Variability ◽  
Climate Models ◽  
Southern Oscillation ◽  
Climate Science ◽  
Direct Consequence ◽  
Sub Saharan Africa ◽  
Local Conditions ◽  
Weather And Climate

In this paper in three parts, climate change is approached by dealing with the three sides from which the danger comes: (i) global warming, (ii) increasing climate variability, (iii) more (and possibly more severe) meteorological and climatological extreme events. These are the three panels of this triptych review and this left panel is about (ii). This second panel starts with a compelling review of the present situation of food security, referring to African examples to improve the situation. Then the influence is discussed that the El Niño Southern Oscillation (ENSO) has on increasing climate variability as a consequence of climate change. It is indicated that, to date, climate models have been developed with little knowledge of agricultural systems dynamics. On the other hand one can illustrate that agricultural policy analysis has been conducted with little knowledge of climate dynamics. As a direct consequence of capricious behaviour of particularly rainfall in West Africa, the adaptation of its farmers has lagged behind enormously. This statement is valid for most farmers in sub-Saharan Africa. Within the climate science community there is an emerging effort to make findings more suitable for decision making, but as yet there is little consensus as to how data may be relied upon for decision making. Then a lot of attention is paid to how response farming, that is thoroughly defined, can play an important role in coping with the consequences of climate variability. Response farming is often limited envisaging rainfall events, but coping with weather and climate (and often soil) disasters as well as using windows of weather and climate (and often soil) opportunities are other forms of responding to weather and climate (and often soil) realities. Services such as in advice on design rules on above and below ground microclimate management or manipulation, with respect to any appreciable microclimatic improvement: shading, wind protection, mulching, other surface modification, drying, storage, frost protection and so on belong to such “response farming” agrometeorological services. Ideally, to get optimal preparations, farmers get advisories/services through extension intermediaries, backed by scientists, to properly understand decision options through discussions supported by economic analyses. Throughout the paper text boxes are used that illustrate local conditions that must be taken into account if one wants to understand the impacts/consequences of climate change for African farmers and how they may cope with them.

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