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.

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 Using Lomb–Scargle Analysis to Derive Empirical Orthogonal Functions from Gappy Meteorological Data

2018 ◽  
Vol 57 (10) ◽  
pp. 2217-2229
Author(s):  
Christopher Dupuis ◽  
Courtney Schumacher
Keyword(s):  
Time Series ◽  
Meteorological Data ◽  
Tropical Rainfall Measuring Mission ◽  
Empirical Orthogonal Functions ◽  
Eof Analysis ◽  
Complex Topography ◽  
Sampled Data ◽  
Orthogonal Functions ◽  
Hard Limit ◽  
Irregularly Sampled Data

AbstractThe Lomb–Scargle discrete Fourier transform (LSDFT) is a well-known technique for analyzing time series. In this study, a solution for empirical orthogonal functions (EOFs) based on irregularly sampled data is derived from the LSDFT. It is demonstrated that this particular algorithm has no hard limit on its accuracy and yields results comparable to those of complex Hilbert EOF analysis. Two LSDFT algorithms are compared in terms of their performance in evaluating EOFs for precipitation observations from the Tropical Rainfall Measuring Mission satellite. Both are shown to be able to capture the pattern of the diurnal cycle of rainfall over the complex topography and diverse land cover of South America, and both also show other consistent features in the 0–12-day frequency band.

Directional Extreme Current Profiles Based on Complex Empirical Orthogonal Functions (C-EOF) for Offshore Design

2009 ◽  
Author(s):  
Jose Antonio Moreira Lima ◽  
Eric Oliveira Ribeiro ◽  
Wellington Ceccopieri ◽  
Guisela Grossmann Matheson
Keyword(s):  
Goodness Of Fit ◽  
Structural Reliability ◽  
Current System ◽  
Correlation Coefficients ◽  
Current Data ◽  
Empirical Orthogonal Functions ◽  
Western Boundary ◽  
Boundary Current ◽  
Orthogonal Functions ◽  
Brazil Current

This paper presents a methodology to estimate deep water design current profiles using Complex Empirical Orthogonal Function (C-EOF) and a structural reliability response based model. The advantage of C-EOF is the capability of directly obtaining directional extreme current profiles. It is estimated that most of the variability of the southeast Brazil current system can be explained by the first two EOF modes. The first mode associated with the southwestward Brazil Current (BC) and the second mode with the northeastward Intermediate Western Boundary Current (IWBC). Thus, only two series of C-EOF amplitudes can be used in the response based technique to estimate the 100-y extreme current values. The methodology can also be used with more EOF modes if required to properly represent the current data. The probabilistic cumulative functions are based on extreme value distributions such as Gumbel or Weibull, and Lognormal for conditional distributions. The evaluation of estimated distribution parameters are carried out using Kolmogorov-Smirnov goodness-of-fit hypothesis tests and correlation coefficients for each directional sector.

Understanding the role of water vapor and temperature in easterly wave-related convection

2020 ◽  
Author(s):  
Rosa Vargas Martes ◽  
Angel Adames Corraliza
Keyword(s):  
Water Vapor ◽  
Rainfall Variability ◽  
Large Fraction ◽  
Deep Convection ◽  
Linear Regression Analysis ◽  
Empirical Orthogonal Functions ◽  
Specific Humidity ◽  
Coupling Mechanism ◽  
Orthogonal Functions ◽  
The Relationship

<p>Easterly Waves (EW) in the Pacific Ocean (PEW) and over Africa (AEW) account for a large fraction of rainfall variability in their respective regions. Although multiple studies have been conducted to better understand EWs, many questions remain regarding their structure, development, and coupling to deep convection. Recent studies have highlighted the relationship between water vapor and precipitation in tropical motion systems. However, EW have not been studied within this context. On the basis of Empirical Orthogonal Functions (EOFs) and a novel plume-buoyancy framework, the thermodynamic processes associated with EW-related convection are elucidated. A linear regression analysis reveals the relationship between temperature, moisture, and precipitation in EW. Temperature anomalies are found to be highly correlated in space and time with anomalies in specific humidity. However, this coupling between temperature and moisture is more robust in AEWs than PEWs. In PEWs moisture accounts for a larger fraction of precipitation variability. Results suggest that the convective coupling mechanism in AEW may differ from the coupling mechanism of PEWs.</p>

scholarly journals Geospatial Trends and Decadal Anomalies in Extreme Rainfall over Uganda, East Africa

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Charles Onyutha
Keyword(s):  
North Atlantic Ocean ◽  
Rainfall Variability ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Empirical Orthogonal Functions ◽  
Orthogonal Functions ◽  
Indicator Method ◽  
Significance Level ◽  
Modes Of Variability ◽  
In Series

Trends and variability in series comprising the mean of fifteen highest daily rainfall intensities in each year were analyzed considering entire Uganda. The data were extracted from high-resolution (0.5° × 0.5°) gridded daily series of the Princeton Global Forcings covering the period 1948–2008. Variability was analyzed using nonparametric anomaly indicator method and empirical orthogonal functions. Possible drivers of the rainfall variability were investigated. Trends were analyzed using the cumulative rank difference approach. Generally, rainfall was above the long-term mean from the mid-1950s to the late 1960s and again in the 1990s. From around 1970 to the late 1980s, rainfall was characterized by a decrease. The first and second dominant modes of variability correspond with the variation in Indian Ocean Dipole and North Atlantic Ocean index, respectively. The influence of Niño 3 on the rainfall variability of some parts of the country was also evident. The southern and northern parts had positive and negative trends, respectively. The null hypothesisH0(no trend) was collectively rejected at the significance level of 5% in the series from 7 out of 168 grid points. The insights from the findings of this study are vital for planning and management of risk-based water resources applications.

scholarly journals The Influence of European Climate Variability Mechanism on Air Temperatures in Romania

2014 ◽  
Vol 8 (1) ◽  
pp. 5-16 ◽  
Author(s):  
Nicoleta Ionac ◽  
Monica Matei
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Large Scale ◽  
Empirical Orthogonal Functions ◽  
Spatial And Temporal Variability ◽  
Orthogonal Functions ◽  
Mean Values ◽  
European Climate ◽  
Air Temperatures ◽  
And Shifts

Abstract The present paper investigates on the spatial and temporal variability of maximum and minimum air-temperatures in Romania and their connection to the European climate variability. The European climate variability is expressed by large scale parameters, which are roughly represented by the geopotential height at 500 hPa (H500) and air temperature at 850 hPa (T850). The Romanian data are represented by the time series at 22 weather stations, evenly distributed over the entire country’s territory. The period that was taken into account was 1961-2010, for the summer and winter seasons. The method of empirical orthogonal functions (EOF) has been used, in order to analyze the connection between the temperature variability in Romania and the same variability at a larger scale, by taking into consideration the atmosphere circulation. The time series associated to the first two EOF patterns of local temperatures and large-scale anomalies were considered with regard to trends and shifts in their mean values. The non- Mann-Kendall and Pettitt parametric tests were used in this respect. The results showed a strong correlation between T850 parameter and minimum and maximum air temperatures in Romania. Also, the ample variance expressed by the first EOF configurations suggests a connection between local and large scale climate variability.

scholarly journals Daily to intraseasonal oscillations at Antarctic research station Neumayer

2013 ◽  
Vol 26 (2) ◽  
pp. 193-204 ◽  
Author(s):  
N. Rimbu ◽  
G. Lohmann ◽  
G. König-Langlo ◽  
C. Necula ◽  
M. Ionita
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Sea Level ◽  
Intraseasonal Variability ◽  
Research Station ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Intraseasonal Oscillations ◽  
Antarctic Research ◽  
And Sea Level

AbstractHigh temporal resolution (three hours) records of temperature, wind speed and sea level pressure recorded at Antarctic research station Neumayer (70°S, 8°W) during 1982–2011 are analysed to identify oscillations from daily to intraseasonal timescales. The diurnal cycle dominates the three-hourly time series of temperature during the Antarctic summer and is almost absent during winter. In contrast, the three-hourly time series of wind speed and sea level pressure show a weak diurnal cycle. The dominant pattern of the intraseasonal variability of these quantities, which captures the out-of-phase variation of temperature and wind speed with sea level pressure, shows enhanced variability at timescales of ∼ 40 days and ∼ 80 days, respectively. Correlation and composite analysis reveal that these oscillations may be related to tropical intraseasonal oscillations via large-scale eastward propagating atmospheric circulation wave-trains. The second pattern of intraseasonal variability, which captures in-phase variations of temperature, wind and sea level pressure, shows enhanced variability at timescales of ∼ 35, ∼ 60 and ∼ 120 days. These oscillations are attributed to the Southern Annular Mode/Antarctic Oscillation (SAM/AAO) which shows enhanced variability at these timescales. We argue that intraseasonal oscillations of tropical climate and SAM/AAO are related to distinct patterns of climate variables measured at Neumayer.

scholarly journals A Comparison Study of EOF Techniques: Analysis of Nonstationary Data with Periodic Statistics

1999 ◽  
Vol 12 (1) ◽  
pp. 185-199 ◽  
Author(s):  
Kwang-Y. Kim ◽  
Qigang Wu
Keyword(s):  
Time Series ◽  
Principal Component ◽  
Empirical Orthogonal Functions ◽  
Orthogonal Functions ◽  
Second Mode ◽  
Nonstationary Data ◽  
Cyclic Statistics ◽  
Surface Temperature Field ◽  
Climate Studies ◽  
Moving Patterns

Abstract Identification of independent physical/dynamical modes and corresponding principal component time series is an important aspect of climate studies for they serve as a tool for detecting and predicting climate changes. While there are a number of different eigen techniques their performance for identifying independent modes varies. Considered here are comparison tests of eight eigen techniques in identifying independent patterns from a dataset. A particular emphasis is given to cyclostationary processes such as deforming and moving patterns with cyclic statistics. Such processes are fairly common in climatology and geophysics. Two eigen techniques that are based on the cyclostationarity assumption—cyclostationary empirical orthogonal functions (EOFs) and periodically extended EOFs—perform better in identifying moving and deforming patterns than techniques based on the stationarity assumption. Application to a tropical Pacific surface temperature field indicates that the first dominant pattern and the corresponding principal component (PC) time series are consistent among different techniques. The second mode and the PC time series, however, are not very consistent from one another with hints of significant modal mixing and splitting in some of derived patterns. There also is a detailed difference of intraannual scale between PC time series of a stationary technique and those of a cyclostationary one. This may bear an important implication on the predictability of El Niño. Clearly there is a choice of eigen technique for improved predictability.

scholarly journals Rainfall variability and meteorological drought in the Horn of Africa

MAUSAM ◽  
2021 ◽  
Vol 68 (3) ◽  
pp. 463-474
Author(s):  
Y. WANG ◽  
Z. W. SHILENJE ◽  
P. O. SAGERO ◽  
A. M. NYONGESA ◽  
N. BANDA
Keyword(s):  
Rainfall Variability ◽  
Meteorological Drought ◽  
Research Unit ◽  
Dominant Mode ◽  
Empirical Orthogonal Functions ◽  
Seasonal Rainfall ◽  
Horn Of Africa ◽  
Standard Precipitation Index ◽  
Orthogonal Functions ◽  
Rainfall Characteristics

 Basic rainfall characteristics and drought over the Horn of Africa (HoA) is investigated, from 1901 to 2010. Standard Precipitation Index (SPI) is used to study drought variability, mainly focusing on 3-month SPI. The dominant mode of variability of seasonal rainfall was analyzed by performing Empirical orthogonal functions (EOF) analysis. Gridded data is sourced from Climate Research Unit (CRU), spanning from 1901 to 2010. The HoA experiences predominantly bimodal rainfall distribution in time; March to May (MAM) and October to December (OND). The spatial component of the first eigenvector (EOF1) shows that the MAM and OND seasonal rainfalls are dominated by negative and positive loadings, respectively. The EOF1 explain 34.5% and 58.9% variance of MAM and OND seasonal rainfall, respectively. The EOF2, 3 and 4 are predominantly positive, explaining less than 25% in total of the seasonal rainfall variance in the two seasons. The last two decades experienced the highest negative anomaly, with OND seasonal rainfall showing higher anomalies as compared to MAM season. The OND season recorded 9% more drought events as compared to MAM season. The frequency of occurrence of moderate, severe and extreme dryness was almost the same in the two seasons. These results give a good basis for regional model validation, as well as mapping out drought hotspots and projections studies in the HoA.

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