Cyclone Cloud Research Articles

Revealing the Precipitation Characteristics of Tropical Cyclone Ockhi from Polarimetric Doppler Weather Radar in Conjunction with Disdrometer Observations

Abstract This paper describes the rainfall and microphysical structure of precipitation associated with Tropical Cyclone Ockhi using polarimetric Doppler weather radar (PDWR) products. The study reports the statistical analysis of precipitation types of tropical cyclone cloud systems over the north Indian Ocean, by combining the observations of the PDWR and disdrometer for the first time. There are few studies that mention initial DWR observations of TC over this low-latitude region below 23.5°N. We tried to further carry out a statistical analysis of precipitating clouds in a cyclone from its depression stage to severe cyclonic stage. This study tries to classify and quantify the contribution of convective and stratiform rain to the total TC rainfall. Precipitating clouds have been classified into convective and stratiform based on reflectivity measurements. The vertical profiles (VPRs) of the radar reflectivity Z and the differential reflectivity ZDR obtained for the stratiform and the convective events are compared. A study of the VPR of the convective events reveals that the Z and ZDR parameters tend to increase as the raindrops descend toward the ground owing to enhanced collision–coalescence processes. The VPR of stratiform rain shows signatures of the bright band (BB). The drop size distribution (DSD) parameters and rainfall rate pertaining to the two different precipitation regimes are estimated from the radar data and have been compared. The Joss–Waldvogel Disdrometer measurements have been used to derive DSD parameters and polarimetric rain-rate relation.

Cloud-Top Phase Characterization of Extratropical Cyclones over the Northeast and Midwest United States: Results from IMPACTS

Abstract Cloud-top phase (CTP) impacts cloud albedo and pathways for ice particle nucleation, growth, and fallout within extratropical cyclones. This study uses airborne lidar, radar, and Rapid Refresh analysis data to characterize CTP within extratropical cyclones as a function of cloud-top temperature (CTT). During the 2020, 2022, and 2023 Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign deployments, the Earth Resources 2 (ER-2) aircraft flew 26 research flights over the northeast and midwest United States to sample the cloud tops of a variety of extratropical cyclones. A training dataset was developed to create probabilistic phase classifications based on Cloud Physics Lidar measurements of known ice and liquid clouds. These classifications were then used to quantify dominant CTP in the top 150 m of clouds sampled by the Cloud Physics Lidar in storms during IMPACTS. Case studies are presented illustrating examples of supercooled liquid water at cloud top at different CTT ranges (−3° < CTTs < −35°C) within extratropical cyclones. During IMPACTS, 19.2% of clouds had supercooled liquid water present at cloud top. Supercooled liquid was the dominant phase in extratropical cyclone cloud tops when CTTs were >−20°C. Liquid-bearing cloud tops were found at CTTs as cold as −37°C. Significance Statement Identifying supercooled liquid cloud tops’ frequency is crucial for understanding ice nucleation mechanisms at cloud top, cloud radiative effects, and aircraft icing. In this study, airborne lidar, radar, and model temperature data from 26 research flights during the NASA IMPACTS campaign are used to characterize extratropical cyclone cloud-top phase (CTP) as a function of cloud-top temperature (CTT). The results show that liquid was the dominant CTP present in extratropical cyclone cloud tops when CTTs were >−20°C with decreasing supercooled liquid cloud-top frequency at temperatures < −20°C. Nevertheless, liquid was present at CTTs as cold as −37°C.

Automated Segmentation of Tropical Cyclone Clouds in Geostationary Infrared Images

Automated Segmentation of Tropical Cyclone Clouds in Geostationary Infrared Images

Microphysical Characteristics of Cyclonic Rainfall: A GPM‐DPR Based Study Over the Arabian Sea

AbstractThe precipitation characteristics of tropical cyclone (TC) formed over the Arabian Sea during the onset phase of the Indian summer monsoon (i.e., late‐May and early‐June months) and in the post‐monsoon season were investigated during the period from 2014 to 2021 using the Global Precipitation Measurement (GPM) satellite level 2 V07 data. For the cyclonic precipitation, 2‐D frequency distribution between liquid water content (LWC) and non‐liquid water content, that is, ice water content (IWC) shows significant variation with the rain type and season. A large proportion of rain droplets are within the LWC (IWC) range of 0–800 (0–350) g/m2 for the stratiform precipitation of TCs in both seasons. The average value of the mass‐weighted mean diameter (Dm), for the stratiform and convective precipitation at 2 km above the mean sea level in the monsoon (post‐monsoon) season is 1.29 (1.27) mm and 1.47 (1.31) mm, respectively. A gradual decrease in the normalized intercept parameters (Nw) is found to occur with an increase in Dm, irrespective of cloud type and season. There is an enormously high concentration of supercooled liquid and ice particles observed above the melting layer during the convection precipitation in both seasons. In the stratiform cyclonic cloud, the contribution of the collision‐coalescence and breaking‐up process is about 36.62% (47.58%) and 52.52% (41.52%) during the monsoon (post‐monsoon) season. However, the collision‐coalescence process (63.45% in monsoon and 70.2% in post‐monsoon) is acting as dominating microphysical process in the convective precipitation as compared to the break‐up process.

The Quagmire of Arrested Development in Tropical Cyclones

Abstract The 48-h intensity forecasts for Hurricane Pamela (2021) from numerical weather prediction models, statistical–dynamical aids, and forecasters were a major forecast bust with Pamela making landfall as a minor rather than major hurricane. From the satellite presentation, Pamela exhibited a symmetric pattern referred to as central cold cover (CCC) in the subjective Dvorak intensity technique. Per the technique, the CCC pattern is accompanied by arrested development in intensity despite the seemingly favorable convective signature. To understand forecast uncertainty during occurrences, central cold cover frequency from 2011 to 2021 is documented. From these cases, composites of longwave infrared brightness temperatures from geostationary satellites for CCC cases are presented, and the surrounding tropical cyclone large-scale environment is quantified and compared with other tropical cyclones at similar latitudes and intensities. These composites show that central cold cover has a consistent presentation, but varies in the preceding hours for storms that eventually intensify or weaken. And, the synoptic-scale environment surrounding the tropical cyclone thermodynamically supports the vigorous deep convection associated with CCC. Finally, intensity forecast errors from numerical weather prediction models and statistical–dynamical aids are examined in comparison to similar tropical cyclones. This work shows that guidance struggles during CCC cases with intensity errors from these models being in the lowest percentiles of performance, particularly for 24- and 36-h forecasts. Significance Statement The appearance of symmetric cold clouds near the center of developing tropical cyclones is most often associated with future intensification. This simple relationship is widely used by statistical tropical cyclone intensity forecast models. Here, we reexamine and confirm that one subjectively determined nighttime cold cyclone cloud pattern termed the “central cold cover” pattern in Vern Dvorak’s seminal technique for estimating tropical cyclone intensity from infrared satellite images is indeed related to slow or arrested development, and represents a failure mode for these simple forecast models.

Quantifying the cooling effect of tropical cyclone clouds on the climate system

The net effect on the upwelling radiation caused by tropical cyclone clouds is calculated over a 20-year global data set, and the corresponding contribution to the earth energy balance is analyzed. Tropical cyclone clouds are shown on average to increase the upwelling radiation at the top of the atmosphere compared with the background non-tropical-cyclone-cloud climatology. This increase in upwelling radiation provides an overall cooling effect on the climate system because the increased reflected shortwave radiation (cooling) outweighs the decreased emitted longwave radiation (warming). While the effect neglects the (likely considerable) contribution due to tropical cyclone drying, the amount of cooling by clouds alone represents a considerable fraction of the excess warming energy in the climate system. Thus, any future change in tropical cyclone activity has the potential to impact the overall energy balance if it substantially alters this total. The seasonal and geographic distribution of warming and cooling effects, and the diurnal dynamics that impact whether any particular cyclone is net cooling or net warming are discussed in this study.

Strong surface winds in Storm Eunice. Part 1: storm overview and indications of sting jet activity from observations and model data

Strong surface winds in Storm <i>Eunice</i>. Part 1: storm overview and indications of sting jet activity from observations and model data

Impacts of the Saharan air layer on the physical properties of the Atlantic tropical cyclone cloud systems: 2003–2019

Abstract. It is generally known that the tropical cyclone (TC) cloud systems (TCCSs) in the North Atlantic region frequently occur during boreal summer, while the Saharan dust outbreaks occur concurrently. The Sahara air layer (SAL), an elevated layer containing Saharan dry air and mineral dust, has crucial impacts on the generation and evolution of TCs. However, the effects of SAL on the physical (macro and micro) characteristics of the Atlantic TCCSs have not been well constrained, and the interaction mechanisms between them still need further investigation. In this study, our primary interest is to distinguish the various effects of SAL on different intensities of TCs and further find out the probable causes of the varied feedback mechanisms. Therefore, we attempt to identify whether and how the effects of the SAL play a positive or negative role on the TCCSs and to draw a qualitative conclusion on how SAL affects the various intensities of the TCs. This paper focuses on the 70 TC samples from July to September in the years of 2003–2019 to investigate the physical effects of SAL on three intensities of TCs, i.e., the tropical depression (TD), tropical storm (TS), and hurricane (HU). The results show that SAL has a positive impact on the macro properties of HU but significantly suppresses the TD. It appears that the SAL attributes little to the variation of the ice cloud effective radius (CERi) for TS, whereas CERi changes significantly and differentially for TD and HU. When affected by SAL, the probability density function (PDF) curve of CERi generally shifts to the smaller value for TD, whereas the PDF curve becomes flatter for HU. Our analysis indicates that the various responses of TCCSs to SAL are determined by the combined effects of dry air masses, the dust aerosols as ice nuclei, and the thermodynamic and moisture conditions. Based on the observation data analysis, a concept scheme description has been concluded to deepen our recognition of the effects of SAL on the TCCSs.

Intensity prediction of tropical cyclone using multilayer multi-block local binary pattern and tree-based classifiers over North Indian Ocean

Local binary pattern (LBP) is an extensively used method in image analysis and pattern recognition related works across various domains. In this paper, we explore cyclone cloud evolution patterns using a modified LBP. The multilayer multi-block local binary pattern (MMLBP) is an extended version of Completed LBP (CLBP) with multiple blocks and many layers. A tropical cyclone (TC) image is converted into 3 × 3 identical blocks to generate central pixels using CLBP magnitude descriptor block-wise (CLBP_MB). These central pixels are used to find the next layer, which is further divided into 3 × 3 blocks to generate central pixels by CLBP_MB descriptor. This technique will iterate until the dimension of the final layer reached to 1 × 1. These central pixels are extracted from each layer and gather in a vector called a feature vector. The proposed method is applied to 600 tropical cyclone (TC) images and each image generates one feature vector. Hence, 600 vectors are passed through tree-based classifiers to classify cyclone images of various classes. The proposed method of feature extraction and classification reaches a maximum of 84.66% accuracy using Random Forest (RF) classifier. The root mean squared error (RMSE) of the MMLBP method is 9.27 kt, which is better than the LBP and MBLBP approaches. Finally, the size of the original feature vector is reduced to 97.4% using correlation based feature subset selection method.

Tropical Cyclone Temperature Profiles and Cloud Macro-/Micro-Physical Properties Based on AIRS Data

We used the observations from Atmospheric Infrared Sounder (AIRS) onboard Aqua over the northwest Pacific Ocean from 2006–2015 to study the relationships between (i) tropical cyclone (TC) temperature structure and intensity and (ii) cloud macro-/micro-physical properties and TC intensity. TC intensity had a positive correlation with warm-core strength (correlation coefficient of 0.8556). The warm-core strength increased gradually from 1 K for tropical depression (TD) to &gt;15 K for super typhoon (Super TY). The vertical areas affected by the warm core expanded as TC intensity increased. The positive correlation between TC intensity and warm-core height was slightly weaker. The warm-core heights for TD, tropical storm (TS), and severe tropical storm (STS) were concentrated between 300 and 500 hPa, while those for typhoon (TY), severe typhoon (STY), and Super TY varied from 200 to 350 hPa. Analyses of the cloud macro-/micro-physical properties showed that the top of TC cloud systems mainly consisted of ice clouds. For TCs of all intensities, areas near the TC center showed lower cloud-top pressures and lower cloud-top temperatures, more cloud fractions, and larger ice-cloud effective diameters. With the increase in TC intensity, the levels of ice clouds around the TC center became higher and the spiral cloud-rain bands became larger. When a TC developed into a TY, STY, or Super TY, the convection in the clouds was stronger, releasing more heat, thus forming a much warmer warm core.

A Parameter for Quantifying the Macroscale Asymmetry of Tropical Cyclone Cloud Clusters

AbstractA parameter to quantify macroscale (i.e., systemwide) asymmetry of tropical cyclones (TC) in infrared satellite images, galaxy asymmetry (GASYM), which is adopted from astronomy, is described. In addition, an alternative approach to identify TC cloud clusters that is based on a density-based spatial clustering algorithm, cluster identification (CI), is presented in this study. Although a commonly used approach in TC study, the predefined radius of calculation (ROC), can be used to identify the TC region in the calculation of GASYM, this approach is not optimal because the size of the TC cloud cluster is often unknown in the calculation. The area specified by the ROC often includes pixels that do not belong to the TC cloud cluster and excludes pixels that belong to the TC cloud cluster. The CI approach addresses this issue by identifying TC cloud clusters of any size with any shape, because it depends solely on the threshold brightness temperature that corresponds to the upper bound of the brightness temperature of the specific cloud types. This study shows that the CI approach can be integrated into the GASYM calculation as an objective measure of TC symmetry. Although GASYM-CI and intensity are correlated, the relationship between GASYM-CI and intensity depends on the size of the TC cloud cluster. Comparison between GASYM and an existing objective method to quantify symmetry of TCs, the deviation angle variance technique, is also presented.

Orographic effects on the propagation and rainfall modification associated with the 2007–08 Madden–Julian oscillation (MJO) past the New Guinea Highlands

Based on the tropical rainfall measuring mission (TRMM)-measured rainfall and estimated outgoing longwave radiation (OLR) fields, it is found that 2007–08 Madden–Julian Oscillation (MJO07-08) went through blocking, splitting, and merging stages when it passed over the New Guinea Highlands (NGH). The TRMM-estimated OLR fields fail to capture detailed TRMM rainfall field and thus is not suitable to serve as proxy for rainfall, as also found in previous studies. The mechanism of orographic blocking is explained by strong orographic blocking on the incoming, low-Froude number, and moist flow, which belonged to the flow-around regime. This is evidenced by estimating the Froude number by upstream soundings. The strong blocking forced the flow to go around the mountains on NGH, leading to the splitting of flow and MJO precipitating system and the merging at the southeast tip of New Guinea. Orographic, MJO, and cyclone clouds were shown in both observed and model-simulated results. The major differences of the model-simulated and TRMM-measured precipitation are as follows: (a) the model-simulated rainfall area is much larger than that covered by the observed rainfall and (b) even though they both show comparable maximum rainfall rate, the rainfall estimated by TRMM reveals more localized rainfall spots, which is unexpected since the WRF simulation uses a relatively fine resolution (5 km). In summary, during the blocking stage, the mountains have slowed down the MJO propagation and increased the rainfall amount upstream of the local mountains, while during the splitting and merging stages, the mountains have made significant impacts on the MJO rainfall distribution.

The Diurnal Cycle of Clouds in Tropical Cyclones over the Western North Pacific Basin

The Diurnal Cycle of Clouds in Tropical Cyclones over the Western North Pacific Basin

Extratropical Cyclone Clouds in the GFDL Climate Model: Diagnosing Biases and the Associated Causes

AbstractThe clouds in Southern Hemisphere extratropical cyclones generated by the GFDL climate model are analyzed against MODIS, CloudSat, and CALIPSO cloud and precipitation observations. Two model versions are used: one is a developmental version of “AM4,” a model GFDL that will utilize for CMIP6, and the other is the same model with a different parameterization of moist convection. Both model versions predict a realistic top-of-atmosphere cloud cover in the southern oceans, within 5% of the observations. However, an examination of cloud cover transects in extratropical cyclones reveals a tendency in the models to overestimate high-level clouds (by differing amounts) and underestimate cloud cover at low levels (again by differing amounts), especially in the post–cold frontal (PCF) region, when compared with observations. In focusing only on the models, it is seen that their differences in high and midlevel clouds are consistent with their differences in convective activity and relative humidity (RH), but the same is not true for the PCF region. In this region, RH is higher in the model with less cloud fraction. These seemingly contradictory cloud and RH differences can be explained by differences in the cloud-parameterization tuning parameters that ensure radiative balance. In the PCF region, the model cloud differences are smaller than either of the model biases with respect to observations, suggesting that other physics changes are needed to address the bias. The process-oriented analysis used to assess these model differences will soon be automated and shared.

Optical Properties and Spatial Variation of Tropical Cyclone Cloud Systems From TRMM and MODIS in the East Asia Region: 2010–2014

AbstractThe tropical cyclone (TC) in East Asia varies strongly each year, indicating the different spectral characteristics of the TC cloud systems (TCCSs) with the distance from the center of TC. We report a new perspective of optical properties of TCCS by using the Moderate Resolution Imaging Spectroradiometer and Tropical Rainfall Measuring Mission data over the years from 2010 to 2014 for the 35 TCs in East Asia. We investigate the spatial distribution of the cloud‐top height, radar reflectivity, polarization corrected temperature in 85.5 GHz (PCT85.5), hydrometeor vertical profile, cloud water path, cloud optical thickness, and cloud particle effective radius of TCCS in the development, maturity, and decay stages of TC. The results indicate the significant differences of cloud characteristics in the maturity stage in comparison to other two stages, showing the higher radar reflectivity up to 30 dBZ and the PCT85.5 as low as 232.98 K in the TC eye wall. Meanwhile, the mean hydrometeor profile indicates more ice particles accumulating above the height of 10 km but less liquid droplets near 3 km. The peak of cloud water path and cloud optical thickness in the maturity stage can reach to 1,300 g/m2 and 75, respectively. The mean cloud particle effective radius and precipitation in the three stages could be influenced by aerosols. Based on these quantified results, several ideal fitting equations and the models are constructed to denote the properties of TCCS. Two cases are analyzed to examine the accuracy of the quantified mean state for different stages of TCCS and the relationship between aerosols and clouds.

Development and characterization of a high-efficiency, aircraft-based axial cyclone cloud water collector

A new aircraft-mounted probe for collecting samples of cloud water has been designed, fabricated, and extensively tested. Following previous designs, the probe uses inertial separation to remove cloud droplets from the airstream, which are subsequently collected and stored for offline analysis. We report details of the design, operation, and modelled and measured probe performance.Computational fluid dynamics (CFD) was used to understand the flow patterns around the complex interior geometrical features that were optimized to ensure efficient droplet capture. CFD simulations coupled with particle tracking and multiphase surface transport modelling provide detailed estimates of the probe performance across the entire range of flight operating conditions and sampling scenarios.Physical operation of the probe was tested on a Lockheed C-130 Hercules (fuselage mounted) and de Havilland Twin Otter (wing pylon mounted) during three airborne field campaigns. During C-130 flights on the final field campaign, the probe reflected the most developed version of the design and a median cloud water collection rate of 4.5 mL min−1 was achieved. This allowed samples to be collected over 1–2 min under optimal cloud conditions. Flights on the Twin Otter featured an inter-comparison of the new probe with a slotted-rod collector, which has an extensive airborne campaign legacy. Comparison of trace species concentrations showed good agreement between collection techniques, with absolute concentrations of most major ions agreeing within 30 %, over a range of several orders of magnitude.

Can CFMIP2 models reproduce the leading modes of cloud vertical structure in the CALIPSO-GOCCP observations?

Using principal component (PC) analysis, three leading modes of cloud vertical structure (CVS) are revealed by the GCM-Oriented CALIPSO Cloud Product (GOCCP), i.e. tropical high, subtropical anticyclonic and extratropical cyclonic cloud modes (THCM, SACM and ECCM, respectively). THCM mainly reflect the contrast between tropical high clouds and clouds in middle/high latitudes. SACM is closely associated with middle-high clouds in tropical convective cores, few-cloud regimes in subtropical anticyclonic clouds and stratocumulus over subtropical eastern oceans. ECCM mainly corresponds to clouds along extratropical cyclonic regions. Models of phase 2 of Cloud Feedback Model Intercomparison Project (CFMIP2) well reproduce the THCM, but SACM and ECCM are generally poorly simulated compared to GOCCP. Standardized PCs corresponding to CVS modes are generally captured, whereas original PCs (OPCs) are consistently underestimated (overestimated) for THCM (SACM and ECCM) by CFMIP2 models. The effects of CVS modes on relative cloud radiative forcing (RSCRF/RLCRF) (RSCRF being calculated at the surface while RLCRF at the top of atmosphere) are studied in terms of principal component regression method. Results show that CFMIP2 models tend to overestimate (underestimated or simulate the opposite sign) RSCRF/RLCRF radiative effects (REs) of ECCM (THCM and SACM) in unit global mean OPC compared to observations. These RE biases may be attributed to two factors, one of which is underestimation (overestimation) of low/middle clouds (high clouds) (also known as stronger (weaker) REs in unit low/middle (high) clouds) in simulated global mean cloud profiles, the other is eigenvector biases in CVS modes (especially for SACM and ECCM). It is suggested that much more attention should be paid on improvement of CVS, especially cloud parameterization associated with particular physical processes (e.g. downwelling regimes with the Hadley circulation, extratropical storm tracks and others), which may be crucial to reduce the CRF biases in current climate models.

Diurnal variations of the areas and temperatures in tropical cyclone clouds

Diurnal variations of the areas and temperatures in tropical cyclone convective cloud systems in the western North Pacific were estimated using pixel‐resolution infrared (IR) brightness temperature (BT) and best‐track data for 2000–2013. The mean areal extent of very cold cloud cover (IR BTs &lt; 208 K) reached a maximum in the early morning (0000–0300 local solar time (LST)), then decreased after sunrise. This was followed by increasing cloud cover between 208 and 240 K, reaching its maximum areal extent in the afternoon (1500–1800 LST). The time at which cloud cover reached a maximum was sensitive to the temperature thresholds used over the ocean. IR BTs &lt; 240 K reached minima in the morning (0300–0600 LST), and IR BTs &gt; 240 K reached minima in the afternoon (1500–1800 LST). The out‐of‐phase relationships between IR BTs &lt; 240 K and IR BTs &gt; 240 K, and between the maximum coverage times of IR BTs &lt; 208 K and 208 K &lt; IR BTs &lt; 240 K, can both lead to the radius‐averaged IR temperature having two minima per day. The different diurnal evolutions under different cloud conditions suggest tropical cyclone convective cloud systems are best described in terms of both areal extent and cloud‐top temperature. Maximum occurrence of clouds with IR BTs &lt; 208 K in the morning and maximum occurrence of clouds with 208 K &lt; IR BTs &lt; 240 K in the afternoon suggest that two different mechanisms might be involved in causing diurnal variations under these two types of tropical cyclone cloud conditions.

Using satellite and reanalysis data to evaluate the representation of latent heating in extratropical cyclones in a climate model

Extratropical cyclones are a key feature of the weather in the extratropics, which climate models need to represent in order to provide reliable projections of future climate. Extratropical cyclones produce significant precipitation and the associated latent heat release can play a major role in their development. This study evaluates the ability of a climate model, HiGEM, to represent latent heating in extratropical cyclones. Remote sensing data is used to investigate the ability of both the climate model and ERA-Interim (ERAI) reanalysis to represent extratropical cyclone cloud features before latent heating itself is assessed. An offline radiance simulator, COSP, and the ISCCP and CloudSat datasets are used to evaluate comparable fields from HiGEM and ERAI. HiGEM is found to exhibit biases in the cloud structure of extratropical cyclones, with too much high cloud produced in the warm conveyor belt region compared to ISCCP. Significant latent heating occurs in this region, derived primarily from HiGEM’s convection scheme. ERAI is also found to exhibit biases in cloud structure, with more clouds at lower altitudes than those observed in ISCCP in the warm conveyor belt region. As a result, latent heat release in ERAI is concentrated at lower altitudes. CloudSat indicates that much precipitation may be produced at too low an altitude in both HiGEM and ERAI, particularly ERAI, and neither capture observed variability in precipitation intensity. The potential vorticity structure in composite extratropical cyclones in HiGEM and ERAI is also compared. A more pronounced tropopause ridge evolves in HiGEM on the leading edge of the composite as compared to ERAI. One future area of research to be addressed is what impact these biases in the representation of latent heating have on climate projections produced by HiGEM. The biases found in ERAI indicate caution is required when using reanalyses to study cloud features and precipitation processes in extratropical cyclones or using reanalysis to evaluate climate models’ ability to represent their structure.

An Algorithm for Pre-Processing of Satellite Images of Cyclone Clouds

advances in satellite imaging technologies have made it possible to obtain images of the atmosphere using different modalities and accordingly, make weather predictions. The progress of cyclone storms is one such area where cloud intensity images exhibit characteristic patterns at various stages of evolution. These patterns have been classified using Dvorak's technique, which is based on expert human judgment. Recent research efforts are being made to perform a computer analysis of these intensity patterns in order to make the classification process more objective. However, in order to perform an analysis of these image intensity patterns, the satellite images of different modalities need to be preprocessed to extract the dominant cyclone cloud patterns. This paper describes our algorithm to obtain cloud intensity contours to be used for pattern analysis. Results obtained using Visible (VIS) and Enhanced Infra-Red satellite images of cyclones have been found to be promising.