scholarly journals An Empirical Seasonal Rainfall Forecasting Model for the Northeast Region of Brazil

Water ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1613
Author(s):  
Rodrigo Lins da Rocha Júnior ◽  
David Duarte Cavalcante Pinto ◽  
Fabrício Daniel dos Santos Silva ◽  
Heliofábio Barros Gomes ◽  
Helber Barros Gomes ◽  
...  
Keyword(s):  
Time Series ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Northern Region ◽  
Empirical Orthogonal Functions ◽  
Rainfall Forecasting ◽  
Orthogonal Functions ◽  
Northeast Region ◽  
Teleconnection Patterns ◽  
The North

The Northeast region of Brazil (NEB) is characterized by large climate variability that causes extreme and long unseasonal wet and dry periods. Despite significant model developments to improve seasonal forecasting for the NEB, the achievement of a satisfactory accuracy often remains a challenge, and forecasting methods aimed at reducing uncertainties regarding future climate are needed. In this work, we implement and assess the performance of an empirical model (EmpM) based on a decomposition of historical data into dominant modes of precipitation and seasonal forecast applied to the NEB domain. We analyzed the model’s performance for the February-March-April quarter and compared its results with forecasts based on data from the North American Multi-model Ensemble (NMME) project for the same period. We found that the first three leading precipitation modes obtained by empirical orthogonal functions (EOF) explained most of the rainfall variability for the season of interest. Thereby, this study focuses on them for the forecast evaluations. A teleconnection analysis shows that most of the variability in precipitation comes from sea surface temperature (SST) anomalies in various areas of the Pacific and the tropical Atlantic. The modes exhibit different spatial patterns across the NEB, with the first being concentrated in the northern half of the region and presenting remarkable associations with the El Niño-Southern Oscillation (ENSO) and the Atlantic Meridional Mode (AMM), both linked to the latitudinal migration of the intertropical convergence zone (ITCZ). As for the second mode, the correlations with oceanic regions and its loading pattern point to the influence of the incursion of frontal systems in the southern NEB. The time series of the third mode implies the influence of a lower frequency mode of variability, probably related to the Interdecadal Pacific Oscillation (IPO). The teleconnection patterns found in the analysis allowed for a reliable forecast of the time series of each mode, which, combined, result in the final rainfall prediction outputted by the model. Overall, the EmpM outperformed the post-processed NMME for most of the NEB, except for some areas along the northern region, where the NMME showed superiority.

scholarly journals Linear Contributions of Different Time Scales to Teleconnectivity

2009 ◽  
Vol 22 (13) ◽  
pp. 3720-3728 ◽  
Author(s):  
Panos J. Athanasiadis ◽  
Maarten H. P. Ambaum
Keyword(s):  
Time Scales ◽  
Low Frequency ◽  
Reanalysis Data ◽  
Empirical Orthogonal Functions ◽  
Orthogonal Functions ◽  
Low Frequencies ◽  
Teleconnection Patterns ◽  
The North ◽  
The North Atlantic Oscillation ◽  
Different Time Scales

Abstract The contributions of different time scales to extratropical teleconnections are examined. By applying empirical orthogonal functions and correlation analyses to reanalysis data, it is shown that eddies with periods shorter than 10 days have no linear contribution to teleconnectivity. Instead, synoptic variability follows wavelike patterns along the storm tracks, interpreted as propagating baroclinic disturbances. In agreement with preceding studies, it is found that teleconnections such as the North Atlantic Oscillation (NAO) and the Pacific–North America (PNA) pattern occur only at low frequencies, typically for periods more than 20 days. Low-frequency potential vorticity variability is shown to follow patterns analogous to known teleconnections but with shapes that differ considerably from them. It is concluded that the role, if any, of synoptic eddies in determining and forcing teleconnections needs to be sought in nonlinear interactions with the slower transients. The present results demonstrate that daily variability of teleconnection indices cannot be interpreted in terms of the teleconnection patterns, only the slow part of the variability.

scholarly journals Predicting Critical Transitions in ENSO models. Part II: Spatially Dependent Models

2015 ◽  
Vol 28 (5) ◽  
pp. 1962-1976 ◽  
Author(s):  
Dmitry Mukhin ◽  
Dmitri Kondrashov ◽  
Evgeny Loskutov ◽  
Andrey Gavrilov ◽  
Alexander Feigin ◽  
...  
Keyword(s):  
Time Series ◽  
Southern Oscillation ◽  
Singular Spectrum Analysis ◽  
Coupled Model ◽  
Empirical Orthogonal Functions ◽  
Empirical Modeling ◽  
Orthogonal Functions ◽  
Critical Transitions ◽  
Spatially Distributed ◽  
Learning Set

Abstract The present paper is the second part of a two-part study on empirical modeling and prediction of climate variability. This paper deals with spatially distributed data, as opposed to the univariate data of Part I. The choice of a basis for effective data compression becomes of the essence. In many applications, it is the set of spatial empirical orthogonal functions that provides the uncorrelated time series of principal components (PCs) used in the learning set. In this paper, the basis of the learning set is obtained instead by applying multichannel singular-spectrum analysis to climatic time series and using the leading spatiotemporal PCs to construct a reduced stochastic model. The effectiveness of this approach is illustrated by predicting the behavior of the Jin–Neelin–Ghil (JNG) hybrid seasonally forced coupled ocean–atmosphere model of El Niño–Southern Oscillation. The JNG model produces spatially distributed and weakly nonstationary time series to which the model reduction and prediction methodology is applied. Critical transitions in the hybrid periodically forced coupled model are successfully predicted on time scales that are substantially longer than the duration of the learning sample.

scholarly journals On the Differences in the Intraseasonal Rainfall Variability between Western and Eastern Central Africa: Case of 10–25-Day Oscillations

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Alain Tchakoutio Sandjon ◽  
Armand Nzeukou ◽  
Clément Tchawoua ◽  
Tengeleng Siddi
Keyword(s):  
Time Series ◽  
Rainfall Variability ◽  
Intraseasonal Variability ◽  
Central Africa ◽  
Power Spectra ◽  
Correlation Coefficients ◽  
Empirical Orthogonal Functions ◽  
Orthogonal Functions ◽  
Intraseasonal Oscillations ◽  
Cross Correlations

In this paper, we analyze the space-time structures of the 10–25 day intraseasonal variability of rainfall over Central Africa (CA) using 1DD GPCP rainfall product for the period 1996–2009, with an emphasis on the comparison between the western Central Africa (WCA) and the eastern Central Africa (ECA) with different climate features. The results of Empirical Orthogonal Functions (EOFs) analysis have shown that the amount of variance explained by the leading EOFs is greater in ECA than WCA (40.6% and 48.1%, for WCA and ECA, resp.). For the two subregions, the power spectra of the principal components (PCs) peak around 15 days, indicating a biweekly signal. The lagged cross-correlations computed between WCA and ECA PCs time series showed that most of the WCA PCs lead ECA PCs time series with a time scale of 5–8 days. The variations of Intraseasonal Oscillations (ISO) activity are weak in WCA, when compared with ECA where the signal exhibits large annual and interannual variations. Globally, the correlation coefficients computed between ECA and WCA annual mean ISO power time series are weak, revealing that the processes driving the interannual modulation of ISO signal should be different in nature or magnitude in the two subregions.

Interannual Tasmanian Rainfall Variability Associated with Large-Scale Climate Modes

2009 ◽  
Vol 22 (16) ◽  
pp. 4383-4397 ◽  
Author(s):  
Khalia J. Hill ◽  
Agus Santoso ◽  
Matthew H. England
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Southern Annular Mode ◽  
Reanalysis Data ◽  
Empirical Orthogonal Functions ◽  
Orthogonal Functions ◽  
Climate Modes ◽  
Interannual Rainfall Variability ◽  
East West

Abstract Interannual rainfall variability over Tasmania is examined using observations and reanalysis data. Tasmanian rainfall is dominated by an east–west gradient of mean rainfall and variability. The Pacific–South American mode (PSA), El Niño–Southern Oscillation (ENSO), and the southern annular mode (SAM) each show clear influences on the interannual variability of Tasmanian rainfall. Composites of rainfall during each phase of ENSO and the PSA suggest a notable islandwide influence of these climate modes on Tasmanian rainfall. In contrast, the positive phase of the SAM is associated with drier conditions over the west of the island. The PSA and the SAM project most prominently over the southwest of the island, whereas the ENSO signature is strongest in the north. Empirical orthogonal functions (EOFs) of rainfall over Tasmania show a leading mode (explaining 72% of total variance) of coherent islandwide in-phase anomalies with dominant periods of 2 and 5 yr. The second EOF accounts for ∼14% of total variation, characterized by out-of-phase east–west anomalies, which is likely a combination of all three modes. The EOF1 mode can be attributed to ENSO, the PSA, and to a lesser extent the SAM.

scholarly journals On the Nonlinearity of Winter Northern Hemisphere Atmospheric Variability

2019 ◽  
Vol 76 (1) ◽  
pp. 333-356 ◽  
Author(s):  
A. Hannachi ◽  
W. Iqbal
Keyword(s):  
North Atlantic ◽  
Polar Vortex ◽  
Principal Component ◽  
Empirical Orthogonal Functions ◽  
The Arctic ◽  
Climate Change Signal ◽  
Two Dimensional ◽  
Orthogonal Functions ◽  
Local Flow ◽  
The North

Abstract Nonlinearity in the Northern Hemisphere’s wintertime atmospheric flow is investigated from both an intermediate-complexity model of the extratropics and reanalyses. A long simulation is obtained using a three-level quasigeostrophic model on the sphere. Kernel empirical orthogonal functions (EOFs), which help delineate complex structures, are used along with the local flow tendencies. Two fixed points are obtained, which are associated with strong bimodality in two-dimensional kernel principal component (PC) space, consistent with conceptual low-order dynamics. The regimes reflect zonal and blocked flows. The analysis is then extended to ERA-40 and JRA-55 using daily sea level pressure (SLP) and geopotential heights in the stratosphere (20 hPa) and troposphere (500 hPa). In the stratosphere, trimodality is obtained, representing disturbed, displaced, and undisturbed states of the winter polar vortex. In the troposphere, the probability density functions (PDFs), for both fields, within the two-dimensional (2D) kernel EOF space are strongly bimodal. The modes correspond broadly to opposite phases of the Arctic Oscillation with a signature of the negative North Atlantic Oscillation (NAO). Over the North Atlantic–European sector, a trimodal PDF is also obtained with two strong and one weak modes. The strong modes are associated, respectively, with the north (or +NAO) and south (or −NAO) positions of the eddy-driven jet stream. The third weak mode is interpreted as a transition path between the two positions. A climate change signal is also observed in the troposphere of the winter hemisphere, resulting in an increase (a decrease) in the frequency of the polar high (low), consistent with an increase of zonal flow frequency.

scholarly journals Climatology of Heavy Orographic Rainfall Induced by Tropical Cyclones over Madagascar: From Synoptic to Mesoscale Perspectives

2016 ◽  
Vol 5 (2) ◽  
pp. 132 ◽  
Author(s):  
Tatiana A. Arivelo ◽  
Yuh-Lang Lin
Keyword(s):  
Tropical Cyclones ◽  
Southern Oscillation Index ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Eastern Coast ◽  
Quasi Biennial Oscillation ◽  
Trade Winds ◽  
Southwest Indian Ocean ◽  
The North ◽  
Orographic Rainfall

Variability of and generation mechanisms for Madagascar rainfall are studied by conducting climatological, synoptic and mesoscale analyses. It is found the rainfall variability is highly sensitive to seasons with high variability in summer (Nov-Apr). The rainfall in summer is controlled by the Intertropical Convergence Zone (ITCZ) and orographic rainfall associated with tropical cyclones (TCs), while the rainfall in winter (May-Oct) is controlled by trade winds and local orographic rainfall along the eastern coast. Synoptic analysis reveals that major climate variations in summer are associated with ITCZ position, which is closely related to TC genesis locations and quasi-biennial oscillation (QBO). Linkages between El-Niño Southern Oscillation Index (ENSO) and Southern Oscillation Index (SOI) are identified as the cause of inconsistent dry or wet summers. Mesoscale analysis depicts the importance of the orographic effects on prevailing wind, which are controlled by the orography in both seasons. In winter, the prevailing trade winds over the Southwest Indian Ocean are from the east and are split to the north and south when it impinges on Malagasy Mountains. On the other hand, in summer the prevailing easterlies are weaker leading to the production of lee vortices, in addition to the flow splitting upstream of the mountain. Thus, the flow is classified into two regimes: (a) flow-over regime with no lee vortices under high Froude number (Fr=1.2-1.8) flow, and (b) flow-around regime with lee vortices under low Fr (=0.88-1.16) flow. A case study of TC Domoina (1984) indicates that the long-lasting heavy rainfall was induced by the strong orographic blocking of Madagascar. The shorter-term (e.g., 2 days) heavy orographic precipitation is characterized by large VH ∙Ñh which is composed by two common ingredients, namely a strong low-level wind normal to the mountain (VH) and a steep mountain slope (∇h).

scholarly journals Dynamic wavelet correlation analysis for multivariate climate time series

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Josué M. Polanco-Martínez ◽  
Javier Fernández-Macho ◽  
Martín Medina-Elizalde
Keyword(s):  
Time Series ◽  
Tropical Cyclone ◽  
North Atlantic ◽  
Large Scale ◽  
Southern Oscillation ◽  
Atlantic Multidecadal Oscillation ◽  
Last Millennium ◽  
Climate Data ◽  
The North ◽  
Climate Time Series

AbstractThe wavelet local multiple correlation (WLMC) is introduced for the first time in the study of climate dynamics inferred from multivariate climate time series. To exemplify the use of WLMC with real climate data, we analyse Last Millennium (LM) relationships among several large-scale reconstructed climate variables characterizing North Atlantic: i.e. sea surface temperatures (SST) from the tropical cyclone main developmental region (MDR), the El Niño-Southern Oscillation (ENSO), the North Atlantic Multidecadal Oscillation (AMO), and tropical cyclone counts (TC). We examine the former three large-scale variables because they are known to influence North Atlantic tropical cyclone activity and because their underlying drivers are still under investigation. WLMC results obtained for these multivariate climate time series suggest that: (1) MDRSST and AMO show the highest correlation with each other and with respect to the TC record over the last millennium, and: (2) MDRSST is the dominant climate variable that explains TC temporal variability. WLMC results confirm that this method is able to capture the most fundamental information contained in multivariate climate time series and is suitable to investigate correlation among climate time series in a multivariate context.

scholarly journals A Hierarchy of Data-Based ENSO Models

2005 ◽  
Vol 18 (21) ◽  
pp. 4425-4444 ◽  
Author(s):  
D. Kondrashov ◽  
S. Kravtsov ◽  
A. W. Robertson ◽  
M. Ghil
Keyword(s):  
El Niño ◽  
Additive Noise ◽  
Polynomial Regression ◽  
El Nino ◽  
Southern Oscillation ◽  
Model Performance ◽  
Empirical Orthogonal Functions ◽  
Quadratic Model ◽  
Orthogonal Functions ◽  
Optimizing Model

Abstract Global sea surface temperature (SST) evolution is analyzed by constructing predictive models that best describe the dataset’s statistics. These inverse models assume that the system’s variability is driven by spatially coherent, additive noise that is white in time and are constructed in the phase space of the dataset’s leading empirical orthogonal functions. Multiple linear regression has been widely used to obtain inverse stochastic models; it is generalized here in two ways. First, the dynamics is allowed to be nonlinear by using polynomial regression. Second, a multilevel extension of classic regression allows the additive noise to be correlated in time; to do so, the residual stochastic forcing at a given level is modeled as a function of variables at this level and the preceding ones. The number of variables, as well as the order of nonlinearity, is determined by optimizing model performance. The two-level linear and quadratic models have a better El Niño–Southern Oscillation (ENSO) hindcast skill than their one-level counterparts. Estimates of skewness and kurtosis of the models’ simulated Niño-3 index reveal that the quadratic model reproduces better the observed asymmetry between the positive El Niño and negative La Niña events. The benefits of the quadratic model are less clear in terms of its overall, cross-validated hindcast skill; this model outperforms, however, the linear one in predicting the magnitude of extreme SST anomalies. Seasonal ENSO dependence is captured by incorporating additive, as well as multiplicative forcing with a 12-month period into the first level of each model. The quasi-quadrennial ENSO oscillatory mode is robustly simulated by all models. The “spring barrier” of ENSO forecast skill is explained by Floquet and singular vector analysis, which show that the leading ENSO mode becomes strongly damped in summer, while nonnormal optimum growth has a strong peak in December.

scholarly journals Eddy Trains and Striations in Quasigeostrophic Simulations and the Ocean

2016 ◽  
Vol 46 (9) ◽  
pp. 2807-2825 ◽  
Author(s):  
Changheng Chen ◽  
Igor Kamenkovich ◽  
Pavel Berloff
Keyword(s):  
North Pacific ◽  
Empirical Orthogonal Functions ◽  
Eof Analysis ◽  
Sea Level Anomaly ◽  
Orthogonal Functions ◽  
The North ◽  
Temporal Averaging ◽  
Low Pass ◽  
The Relationship ◽  
The North Pacific

AbstractThis study explores the relationship between coherent eddies and zonally elongated striations. The investigation involves an analysis of two baroclinic quasigeostrophic models of a zonal and double-gyre flow and a set of altimetry sea level anomaly data in the North Pacific. Striations are defined by either spatiotemporal filtering or empirical orthogonal functions (EOFs), with both approaches leading to consistent results. Coherent eddies, identified here by the modified Okubo–Weiss parameter, tend to propagate along well-defined paths, thus forming “eddy trains” that coincide with striations. The striations and eddy trains tend to drift away from the intergyre boundary at the same speed in both the model and observations. The EOF analysis further confirms that these striations in model simulations and altimetry are not an artifact of temporal averaging of random, spatially uncorrelated vortices. This study suggests instead that eddies organize into eddy trains, which manifest themselves as striations in low-pass filtered data and EOF modes.

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