Statistical Hypothesis Testing in Wavelet Analysis: Theoretical Developments and Applications to Indian Rainfall

Statistical hypothesis tests in wavelet analysis are methods that assess the degree to which a wavelet quantity(e.g., power and coherence) exceeds background noise. Commonly, a point-wise approach is adopted in which a wavelet quantity at every point in a wavelet spectrum is individually compared to the critical level of the point-wise test. However, because adjacent wavelet coefficients are correlated and wavelet spectra often contain many wavelet quantities, the point-wise test can produce many false positive results that occur in clusters or patches. To circumvent the point-wise test drawbacks, it is necessary to implement the recently developed area-wise, geometric, cumulative area-wise, and topological significance tests, which are reviewed and developed in this paper. To improve the computational efficiency of the cumulative area-wise test, a simplified version of the testing procedure is created based on the idea that its output is the mean of individual estimates of statistical significance calculated from the geometric test applied at a set of point-wise significance levels. Ideal examples are used to show that the geometric and cumulative area-wise tests are unable to differentiate wavelet spectral features arising from singularity-like structures from those associated with periodicities. A cumulative arc-wise test is therefore developed to strictly test for periodicities by using normalized arc length, which is defined as the number of points composing a cross section of a patch divided by the wavelet scale in question. A previously proposed topological significance test is formalized using persistent homology profiles (PHPs) measuring the number of patches and holes corresponding to the set of all point-wise significance values. Ideal examples show that the PHPs can be used to distinguish time series containing signal components from those that are purely noise. To demonstrate the practical uses of the existing and newly developed statistical methodologies, a first comprehensive wavelet analysis of Indian rainfall is also provided. An R software package has been written by the author to implement the various testing procedures

Evidence for solar cycles in a late Holocene speleothem record from Dongge Cave, China

The association between solar activity and Asian monsoon (AM) remains unclear. Here we evaluate the possible connection between them based on a precisely-dated, high-resolution speleothem oxygen isotope record from Dongge Cave, southwest China during the past 4.2 thousand years (ka). Without being adjusted chronologically to the solar signal, our record shows a distinct peak-to-peak correlation with cosmogenic nuclide 14C, total solar irradiance (TSI) and sunspot number (SN) at multi-decadal to centennial timescales. Further cross-wavelet analyses between our calcite δ18O and atmospheric 14C show statistically strong coherence at three typical periodicities of ~80, 200 and 340 years, suggesting important roles of solar activities in modulating AM changes at those timescales. Our result has further indicated a better correlation between our calcite δ18O record and atmospheric 14C than between our record and TSI. This better correlation may imply that the Sun–monsoon connection is dominated most likely by cosmic rays and oceanic circulation (both associated to atmospheric 14C), instead of the direct solar heating (TSI)

Quantifying the intra-regional precipitation variability in northwestern China over the past 1,400 years

There has been a surge of paleo-climatic/environmental studies of Northwestern China (NW China), a region characterized by a diverse assortment of hydro-climatic systems. Their common approach, however, focuses on "deducing regional resemblance" rather than "exploring regional variance." To date, efforts to produce a quantitative assessment of long-term intra-regional precipitation variability (IRPV) in NW China has been inadequate. In the present study, we base on historical flood/drought records to compile a decadal IRPV index for NW China spanned AD580-1979 and to find its major determinants via wavelet analysis. Results show that our IRPV index captures the footprints of internal hydro-climatic disparity in NW China. In addition, we find distinct similar to 120-200 year periodicities in the IRPV index over the Little Ice Age, which are attributable to the change of hydro-climatic influence of ocean-atmospheric modes during the period. Also, we offer statistical evidence of El Nino Southern Oscillation (Indo-Pacific warm pool sea surface temperature and China-wide land surface temperature) as the prominent multi-decadal to centennial (centennial to multi-centennial) determinant of the IRPV in NW China. The present study contributes to the quantitative validation of the long-term IRPV in NW China and its driving forces, covering the periods with and without instrumental records. It may help to comprehend the complex hydro-climatic regimes in the region.published_or_final_versio

THE ASIAN SUMMER PRECIPITATION OVER THE PAST FIVE CENTURIES

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2018

Intra-seasonal oscillations during monsoon 2002 and 2003

Features of the intra-seasonal oscillations during monsoon 2002, a drought year, and monsoon 2003, a normal year, have been examined by applying a frequency filter and the technique of wavelet analysis to rainfall data. Analysis reveals that while the faster 10-20 days mode dominated monsoon 2003, the slower 30-60 days mode dominated monsoon 2002

Summer seasonal predictability of warm days in Argentina: statistical model approach

Predicting extreme temperature events can be very useful for different sectorsthat are strongly affected by their variability. The goal of this study is toanalyze the influence of the main atmospheric, oceanic, and soil moistureforcing on the occurrence of summer warm days and to predict extremetemperatures in Argentina northern of 40°S by fitting a statistical model. In apreliminary analysis, we studied trends and periodicities. Significant positivetrends, fundamentally in western Argentina, and two main periodicities ofsummer warm days were detected: 2?4 years and approximately 8 years.Lagged correlations allowed us to identify the key predictors: ElNiño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), andStandardized Precipitation Indices (SPI). We also noticed that the frequency ofwarm days in spring acts as a good predictor of summer warm days. Due to thecollinearity among many predictors, principal component regression was usedto simulate summer warm days. We obtained negative biases (i.e., the modeltends to underestimate the frequency of summer warm days), but the observedand simulated values of summer warm days were significantly correlated,except in northwest Argentina. Finally, we analyzed the predictability of thesummer warm days under ENSO neutral conditions, and we found newpredictors: the geopotential height gradient in 850 hPa (between the AtlanticAnticyclone and the Chaco Low) and the Atlantic Multidecadal Oscillation(AMO), while the PDO and SPI lost some relevance.Fil: Collazo, Soledad Maribel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; ArgentinaFil: Barrucand, Mariana Graciela. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; ArgentinaFil: Rusticucci, Matilde Monica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentin

Characteristic features of winter precipitation and its variability over northwest India

Northwestern parts of India receive considerable amount of precipitation during the winter months of December–March. Although, it is only about 15% of the annual precipitation, the precipitation is very important for rabi crops and to maintain the glaciers extend in the Himalaya, which melt and supply water to the rivers during other seasons. The precipitation is mainly associated with the sequence of synoptic systems known as ‘western disturbances’. The precipitation has considerable spatial and temporal variability, with maximum precipitation occurring particularly over northern hilly regions, with decreasing influence southwards. The spatially coherent winter precipitation series has been prepared for the largest possible area comprising nine meteorological subdivisions of northwest India, which constitute about 32% of the total area of the country, having similar precipitation characteristics. The precipitation series has been statistically analysed to understand its characteristics and variability. The seasonal precipitation series is found to be homogeneous, Gaussian (normal) distributed and free from persistence. The precipitation variability has increased during the most recent three decades with more excess and deficient years

Long-term regional precipitation disparity in northwestern China and its driving forces

published_or_final_versio

Variability and predictability of winter cold nights in Argentina

Extreme cold events can cause crop damage as well as an increase in energy demand and even in the mortality rate. Identifying the atmospheric processes associated with the occurrence of these extremes would allow decision-makers to implement preventive and mitigation actions. The goal of this study is to identify predictors of cold extremes of minimum temperature during winter in Argentina (north of 40 °S), and their modulation by the different El Ni~no-Southern Oscillation (ENSO) phases for the period 1970?2015. Lagged correlation analysis between winter cold nights and several global and regional climate indices identified ENSO, subtropical jet intensity, position and intensity of the South Pacific Anticyclone (SPA), and a blocking index as the dominating forcings. The El Niño phase is associated with a decrease in the occurrence of cold extremes. In addition, an increase in the number of blocking events together with a weaker subtropical jet and, a less intense and northward shift of the SPA also inhibit the occurrence of cold extremes of the minimum temperature. Our results indicate persistence in the winter cold nights series compared with the previous season in eastern Argentina. Twowinters with opposite extreme conditions (high and low frequency of cold nights) were selected as case studies. Since both cases occurred under ENSO neutral conditions, we also searched for cold nights predictors consideringonly neutral years. We detected the presence of an equivalent barotropic structure located in southeastern Pacific in both events, which confirmed the importance of the SPA intensity and blocking events as predictors in absenceof an active El Niño.Fil: Collazo, Soledad Maribel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Barrucand, Mariana Graciela. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rusticucci, Matilde Monica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

A comparative analysis of long-term variations of temperature and rainfall in rural and urban areas, and their effects on the estimation of design storms in Kenya

Philosophiae Doctor - PhD (Earth Science)My Thesis aimed at expanding the current knowledge on how variations of temperature characteristics including the possible existence of urban heat islands (UHI) over urban areas of Kenya could be influencing rainfall characteristics, and to examine if the stationary extreme value distributionis still suitable for modeling urban storm designs in view of the global climate change. My hypothesis was that the floodingoccurring frequently in major urban areas of Kenya are due to increased rainfall caused by global climate change, and the urban heat island (UHI) effect. To put this perception into perspective, temperature and rainfall characteristics and their inter-relationships, of four of the major urban areas in Kenya namely, Nairobi, Mombasa, Kisumu, and Nakuru, were investigated. I obtained data from meteorological stations in and around each urban area, which had at least thirty (30) years of continuous monthly (or daily) temperatures and rainfall values, from the Kenya Meteorological Department. I checked the datasets for quality and missing values and adjusted where necessary before commencing with analysis. I sourced other supporting global dataset from various websites' data banks.I used various methods of data analysis which included; i) exploratory data analysis techniques such as the continuous wavelet transform (CWT), geographical information system (GIS) maps, and visual time series plots. In particular and unique in my Thesis was the use of the CWT method as a diagnostic tool to examine non-stationaritiesand variability of temperature and rainfall time series