Statistical Regression Scheme for Intensity Prediction of Tropical Cyclones in the Northwestern Pacific

Abstract This study proposes a statistical regression scheme to forecast tropical cyclone (TC) intensity at 12, 24, 36, 48, 60, and 72 h in the northwestern Pacific region. This study utilizes best track data from the Shanghai Typhoon Institute (STI), China, and the Joint Typhoon Warning Center (JTWC), United States, from 2000 to 2015. In addition to conventional factors involving climatology and persistence, this study pays close attention to the land effect on TC intensity change by considering a new factor involving the ratio of seawater area to land area (SL ratio) in the statistical regression model. TC intensity changes are investigated over the entire life-span, over the open ocean, near the coast, and after landfall. Data from 2000 to 2011 are used for model calibration, and data from 2012 to 2015 are used for model validation. The results show that the intensity change during the previous 12 h (DVMAX), the potential future intensity change (POT), and the area-averaged (200–800 km) wind shear at 1000–300 hPa (SHRD) are the most significant predictors of the intensity change for TCs over the open ocean and near the coast. Intensity forecasting for TCs near the coast and over land is improved with the addition of the SL ratio compared with that of the models that do not consider the SL ratio. As this study has considered the TC intensity change over the entire TC life-span, the proposed models are valuable and practical for forecasting TC intensity change over the open ocean, near the coast, and after landfall.

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Precipitation Properties Observed during Tropical Cyclone Intensity Change

Monthly Weather Review ◽

10.1175/mwr-d-15-0065.1 ◽

2015 ◽

Vol 143 (11) ◽

pp. 4476-4492 ◽

Cited By ~ 45

Author(s):

George R. Alvey III ◽

Jonathan Zawislak ◽

Edward Zipser

Keyword(s):

Tropical Cyclone ◽

Passive Microwave ◽

Intensity Change ◽

Rapid Intensification ◽

Relative Importance ◽

Tropical Cyclone Intensity ◽

Cyclone Intensity ◽

East Pacific ◽

Intensity Changes ◽

Strong Convection

Abstract Using a 15-yr (1998–2012) multiplatform dataset of passive microwave satellite data [tropical cyclone–passive microwave (TC-PMW)] for Atlantic and east Pacific storms, this study examines the relative importance of various precipitation properties, specifically convective intensity, symmetry, and area, to the spectrum of intensity changes observed in tropical cyclones. Analyses are presented not only spatially in shear-relative quadrants around the center, but also every 6 h during a 42-h period encompassing 18 h prior to onset of intensification to 24 h after. Compared to those with slower intensification rates, storms with higher intensification rates (including rapid intensification) have more symmetric distributions of precipitation prior to onset of intensification, as well as a greater overall areal coverage of precipitation. The rate of symmetrization prior to, and during, intensification increases with increasing intensity change as rapidly intensifying storms are more symmetric than slowly intensifying storms. While results also clearly show important contributions from strong convection, it is concluded that intensification is more closely related to the evolution of the areal, radial, and symmetric distribution of precipitation that is not necessarily intense.

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Tropical Cyclone Intensity Change Prediction Based on Surrounding Environmental Conditions with Deep Learning

Water ◽

10.3390/w12102685 ◽

2020 ◽

Vol 12 (10) ◽

pp. 2685

Author(s):

Xin Wang ◽

Wenke Wang ◽

Bing Yan

Keyword(s):

Deep Learning ◽

Tropical Cyclone ◽

Environmental Conditions ◽

Environmental Variables ◽

Intensity Change ◽

Prediction Algorithm ◽

Hybrid Features ◽

Distribution Features ◽

Intensity Changes ◽

Change Prediction

Tropical cyclone (TC) motion has an important impact on both human lives and infrastructure. Predicting TC intensity is crucial, especially within the 24 h warning time. TC intensity change prediction can be regarded as a problem of both regression and classification. Statistical forecasting methods based on empirical relationships and traditional numerical prediction methods based on dynamical equations still have difficulty in accurately predicting TC intensity. In this study, a prediction algorithm for TC intensity changes based on deep learning is proposed by exploring the joint spatial features of three-dimensional (3D) environmental conditions that contain the basic variables of the atmosphere and ocean. These features can also be interpreted as fused characteristics of the distributions and interactions of these 3D environmental variables. We adopt a 3D convolutional neural network (3D-CNN) for learning the implicit correlations between the spatial distribution features and TC intensity changes. Image processing technology is also used to enhance the data from a small number of TC samples to generate the training set. Considering the instantaneous 3D status of a TC, we extract deep hybrid features from TC image patterns to predict 24 h intensity changes. Compared to previous studies, the experimental results show that the mean absolute error (MAE) of TC intensity change predictions and the accuracy of the classification as either intensifying or weakening are both significantly improved. The results of combining features of high and low spatial layers confirm that considering the distributions and interactions of 3D environmental variables is conducive to predicting TC intensity changes, thus providing insight into the process of TC evolution.

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Bipolar Log-Intensity-Variance Histogram Method for Local Image Patch Intensity Change Measurements

Mathematical Problems in Engineering ◽

10.1155/2019/3651529 ◽

2019 ◽

Vol 2019 ◽

pp. 1-16

Author(s):

Han Wang ◽

Quan Shi ◽

Zhihuo Xu ◽

Ming Wei ◽

Hanseok Ko

Keyword(s):

Intensity Change ◽

Image Patch ◽

Fixed Position ◽

Histogram Method ◽

Probabilistic Measure ◽

Object Movement ◽

Image Patches ◽

Intensity Changes ◽

Sigmoid Functions ◽

Local Image

For a fixed-position camera, the intensity changes of an image pixel are often caused by object movement or illumination change. This paper focuses on such a problem: given two adjacent local image patches, how can the causes of intensity change be determined? A bipolar log-intensity-variance histogram is proposed to describe the intensity variations on the chaos phase plot subspace. This is combined with two sigmoid functions to construct a probabilistic measure function. Experimental results show that the proposed measurements are more effective and robust than conventional methods to the cause of variation in image intensity.

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Quantifying Environmental Control on Tropical Cyclone Intensity Change

Monthly Weather Review ◽

10.1175/2010mwr3185.1 ◽

2010 ◽

Vol 138 (8) ◽

pp. 3243-3271 ◽

Cited By ~ 118

Author(s):

Eric A. Hendricks ◽

Melinda S. Peng ◽

Bing Fu ◽

Tim Li

Keyword(s):

Environmental Control ◽

Global Analysis ◽

Tropical Rainfall Measuring Mission ◽

Initial Position ◽

Distribution Functions ◽

Cumulative Distribution ◽

Intensity Change ◽

Intensity Changes ◽

Real Atmosphere ◽

Microwave Imager

Abstract Composite analysis is used to examine environmental and climatology and persistence characteristics of tropical cyclones (TCs) undergoing different intensity changes in the western North Pacific (WPAC) and North Atlantic (ATL) ocean basins. Using the cumulative distribution functions of 24-h intensity changes from the 2003–08 best-track data, four intensity change bins are defined: rapidly intensifying (RI), intensifying, neutral, and weakening. The Navy Operational Global Atmospheric Prediction System daily 0000 and 1200 UTC global analysis and Tropical Rainfall Measuring Mission Microwave Imager data are then used as proxies for the real atmosphere, and composites of various environmental fields believed relevant to TC intensity change are made in the vicinity of the TCs. These composites give the average characteristics near the TC, prior to undergoing a given intensity change episode. For the environmental variables, statistically significant differences are examined between RI storms and the other groups. While some environmental differences were found between RI and weakening/neutral TCs in both basins, an interesting result from this study is that the environment of RI TCs and intensifying TCs is quite similar. This indicates that the rate of intensification is only weakly dependent on the environmental conditions, on average, provided the environment is favorable. Notable exceptions were that in the WPAC, RI events occurred in environments with significantly larger conditional instability than intensifying events. In the ATL, RI events occurred in environments with weaker deep-layer shear than intensifying events. An important finding of this work is that SSTs are similar between intensifying and rapidly intensifying TCs, indicating that the rate of intensification is not critically dependent on SST. The TCs in both basins were more intense prior to undergoing an RI episode than an intensifying or neutral episode. In the WPAC, the three groups had similar translational speeds and headings, and average initial position. In the ATL, RI storms were located farther south than intensifying and neutral storms, and had a larger translational speed and a more westward component to the heading.

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Observations and Forecasts from the Landfall of Tropical Cyclones John, Lane, and Paul (2006) over Northwestern Mexico

Weather and Forecasting ◽

10.1175/waf-d-11-00108.1 ◽

2012 ◽

Vol 27 (6) ◽

pp. 1373-1393 ◽

Cited By ~ 4

Author(s):

Luis M. Farfán ◽

Rosario Romero-Centeno ◽

G. B. Raga

Keyword(s):

Tropical Cyclones ◽

Large Scale ◽

Regional Scale ◽

Rain Gauge ◽

Intensity Change ◽

Strong Wind ◽

Intensity Changes ◽

Radar Imagery ◽

Northwestern Mexico ◽

Rain Gauge Network

Abstract This study focuses on track and intensity changes of three tropical cyclones that, during the season of 2006, developed in the eastern North Pacific basin and made landfall over northwestern Mexico. Observational datasets, including satellite and radar imagery and a rain gauge network, are used to document regional-scale structures. Additionally, gridded fields are applied to determine the large-scale environment. John made landfall as a category-2 hurricane on the Saffir–Simpson scale and moved along the Baja California Peninsula during more than 40 h, resulting in total rainfall of up to 506 mm. The largest accumulations were located over mountains and set new records with respect to daily rates from the 1969–2005 period. Later in the season, Lane and Paul made landfall over the mainland and brought moderate rainfall over the coastal plains. Lane became a category-3 hurricane and was the third strongest hurricane to make landfall since 1969. In contrast, Paul followed a recurving track to reach the coastline as a weakening tropical depression. Strong wind shear, associated with a midlatitude trough, is found to be related to the intensity change. Examination of the official forecasts reveals that first inland positions were predicted several days before the actual landfall events. An assessment of the forecasts issued 1–3 days prior to landfall shows large track errors associated with some of the above tropical cyclones and this resulted in a westward bias. It is suggested that the track errors are due to an inadequate representation of the large-scale environment that steered the tropical cyclones.

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Satellite-Based Observations of Nonlinear Relationships between Vertical Wind Shear and Intensity Changes during the Life Cycle of Hurricane Joaquin (2015)

Weather and Forecasting ◽

10.1175/waf-d-19-0143.1 ◽

2020 ◽

Vol 35 (3) ◽

pp. 939-958 ◽

Cited By ~ 1

Author(s):

Russell L. Elsberry ◽

Natasha Buholzer ◽

Christopher S. Velden ◽

Mary S. Jordan

Keyword(s):

Life Cycle ◽

Negative Correlation ◽

Wind Shear ◽

Vertical Wind Shear ◽

Vertical Wind ◽

Intensity Change ◽

Intensity Increase ◽

Positive Correlation ◽

Peak Intensity ◽

Intensity Changes

Abstract A CIMSS vertical wind shear (VWS-C) dataset based on reprocessed GOES-East atmospheric motion vectors (AMVs) at 15-min intervals has a −0.36 correlation with the CIMSS Satellite Consensus (SATCON) intensity changes at 30-min intervals over the life cycle of Hurricane Joaquin (2015). Correlations are then calculated for four intensity change events including two rapid intensifications (RIs) and two decays, and four intensity change segments immediately before or after these events. During the first RI, the peak intensity increase of 16 kt (6 h)−1 (1 kt ≈ 0.51 m s−1) follows a small VWS-C decrease to a moderate 8 m s−1 value (negative correlation). A 30-h period of continued RI following the first peak RI occurred under moderate magnitude VWS-C (negative correlation), but with a rotation of the VWS-C direction to become more aligned with the southwestward heading of Joaquin. During the second RI, the peak intensity increase of 15 kt (6 h)−1 leads the rapid VWS-C increase (positive correlation), which the horizontal plots of VWS-C vectors demonstrate is related to an upper-tropospheric cyclone to the northeast of Joaquin. A conceptual model of ocean cooling within the anticyclonic track loop is proposed to explain a counterintuitive decreasing intensity when the VWS-C was also decreasing (positive correlation) during the Joaquin track reversal. These alternating negative and positive correlations during the four events and four segments of intensity change demonstrate the nonlinear relationships between the VWS-C and intensity changes during the life cycle of Joaquin that must be understood, analyzed, and modeled to improve tropical cyclone intensity forecasts, and especially RI events.

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The Application of Statistical Regression for Geographical Data Analysis

Forum Geografi ◽

10.23917/forgeo.v11i2.490 ◽

2004 ◽

Vol 11 (2) ◽

Author(s):

P Priyono

Keyword(s):

Regression Analysis ◽

Data Analysis ◽

Subject Matter ◽

Causal Relation ◽

Computer Software ◽

Statistical Technique ◽

Statistical Regression ◽

Close Attention ◽

Geographical Data ◽

The Relationship

Application of regression statistic to analyse geography data is getting familiar, as the reason that geography object is really wide, kwantitative approach of geography and availibilty computer software of regression analysis which is getting complete and refresentative. The way of making decision and prediction constitutes the superiority of regression analysis and constitutes the issue which is often met by geographer in the study of geography object. It not only phenomena of human geography, but phisycal geography phenomena is also able to be approtached by regression analysis. For user the attentions that ought to be noticed are 1) regression statistic ought to be appraised as a fool and not as a brain, so that researcher is the main important operator; 2) mastery of geography subject matter constitutes an essential basis; 3) statistic is able to work if there is a detum which is able to fulfill the term of requirements and preceded by a logic causal relation; 4) close attention of reasearcher is highly required; 5) when must, researcher use the statistic and the relationship between data type and statistical technique.

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Novel Fluorescence Sensing Methods for High Throughput Screening

CrossRef Listing of Deleted DOIs ◽

10.1177/108705710000500304 ◽

2000 ◽

Vol 5 (3) ◽

pp. 123-131 ◽

Cited By ~ 15

Author(s):

Joseph R. Lakowicz ◽

Ignacy Gryczynski ◽

Zygmunt Gryczynski

Keyword(s):

High Throughput ◽

Frequency Modulation ◽

High Throughput Screening ◽

Low Frequency ◽

Optical Component ◽

Intensity Change ◽

Fluorescence Sensing ◽

New Methods ◽

Intensity Changes ◽

Modulation Signal

We describe two new methods of fluorescence sensing for use in high throughput screening (HTS). Modulation sensing transforms analyte-dependent intensity changes into a change in the low-frequency modulation signal. Polarization sensing transforms an intensity change into a change in polarization. Both methods are internally calibrated by using a reference film immediately adjacent to the sample, which can be readily located on the HTS plate or on a nearby optical component and provides an intensity or polarization reference. Modulation sensing and polarization sensing were both shown useful for measurements of fluorophore concentrations, pH, or calcium concentrations in the wells of HTS plates. Sensing with a reference film provides the opportunity to internally reference HTS measurements without the need for additions to the sample. This approach can provide standardization for assays performed at different times.

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Future Changes in the Western North Pacific Tropical Cyclone Activity Projected by a Multidecadal Simulation with a 16-km Global Atmospheric GCM

Journal of Climate ◽

10.1175/jcli-d-13-00678.1 ◽

2014 ◽

Vol 27 (20) ◽

pp. 7622-7646 ◽

Cited By ~ 37

Author(s):

Julia V. Manganello ◽

Kevin I. Hodges ◽

Brandt Dirmeyer ◽

James L. Kinter ◽

Benjamin A. Cash ◽

...

Keyword(s):

Tropical Cyclone ◽

Southern Oscillation ◽

Atmospheric Model ◽

Future Climate ◽

Intensity Change ◽

Circulation System ◽

Northwestern Pacific ◽

Small Change ◽

Full Intensity ◽

Faster Development

Abstract How tropical cyclone (TC) activity in the northwestern Pacific might change in a future climate is assessed using multidecadal Atmospheric Model Intercomparison Project (AMIP)-style and time-slice simulations with the ECMWF Integrated Forecast System (IFS) at 16-km and 125-km global resolution. Both models reproduce many aspects of the present-day TC climatology and variability well, although the 16-km IFS is far more skillful in simulating the full intensity distribution and genesis locations, including their changes in response to El Niño–Southern Oscillation. Both IFS models project a small change in TC frequency at the end of the twenty-first century related to distinct shifts in genesis locations. In the 16-km IFS, this shift is southward and is likely driven by the southeastward penetration of the monsoon trough/subtropical high circulation system and the southward shift in activity of the synoptic-scale tropical disturbances in response to the strengthening of deep convective activity over the central equatorial Pacific in a future climate. The 16-km IFS also projects about a 50% increase in the power dissipation index, mainly due to significant increases in the frequency of the more intense storms, which is comparable to the natural variability in the model. Based on composite analysis of large samples of supertyphoons, both the development rate and the peak intensities of these storms increase in a future climate, which is consistent with their tendency to develop more to the south, within an environment that is thermodynamically more favorable for faster development and higher intensities. Coherent changes in the vertical structure of supertyphoon composites show system-scale amplification of the primary and secondary circulations with signs of contraction, a deeper warm core, and an upward shift in the outflow layer and the frequency of the most intense updrafts. Considering the large differences in the projections of TC intensity change between the 16-km and 125-km IFS, this study further emphasizes the need for high-resolution modeling in assessing potential changes in TC activity.

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