Surface Wind Analysis Research Articles

Some Value-Added Met-Ocean Products to the RAMMB’s TC Surface Analysis for Marine Meteorological Applications

In the realm of air-sea interaction and marine meteorology, during a tropical cyclone (TC) worldwide since 2006, the Regional and Mesoscale Meteorological Branch (RAMMB) has issued surface wind analysis. Based on this TC’s isotach (line of equal wind speed) analysis, in this paper, much more meteorological-oceanographic (met-ocean) products are developed and value-added to these isotachs. They are, for marine meteorology, overwater friction velocity, wind stress, atmospheric vorticity and the mean vertical velocity, and for oceanography, significant wave height, drift-current velocity, wind-stress tide and wave set-up. Furthermore, in order to estimate the wind-stress induced storm surges, two case studies are presented. They are the Extremely Severe Cyclonic Storm<strong> </strong>Nargis which devastated Myanmar in May 2008 from the Bay of Bengal and in August 2023 Hurricane Idalia which impacted northeastern Gulf of Mexico coastal region of Florida.

Blending Sea Surface Winds from the HY-2 Satellite Scatterometers Based on a 2D-Var Method

The launch of the Haiyang-2 (HY-2) satellite constellation fosters the quick acquisition of global sea surface vector winds from the perspective of remote sensing. This study intends to develop a six-hourly mesoscale analysis of sea surface winds based on the microwave scatterometers onboard the HY-2 satellite series, with the objective of meeting the considerable demand for accurate and gap-free ocean wind forcing products. First, the accuracy of HY-2 scatterometers (HSCATs) in measuring wind is evaluated. In particular, the standard deviation (SD) errors of HSCATs data are assessed using the collocated buoy measurements with different temporal windows in order to account for the temporal representativeness errors in the blending analysis. Afterwards, a two-dimensional variational (2D-Var) method is implemented to blend the HSCATs measured winds and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis winds over the global ocean surface. This approach is different from existing methods in that it takes both wind error and background error correlation into account. The results show that the blended wind product is of a promising quality compared with independent wind references. Interestingly, the blended winds derived from 2D-Var in combination with an empirical background error correlation show smaller SD errors than those using a Gaussian error correlation function. Overall, the blended wind product should be valuable for forcing global ocean models or describing air-sea interaction processes on a scale close to the scatterometer measurements.

Estimating Met-Ocean Parameters during a Tropical Cyclone for Marine Science and Engineering

During a tropical cyclone (TC) worldwide, the Regional and Mesoscale Meteorological Branch (RAMMB) of NOAA/NESDIS (http://rammb.cira.colostate.edu/) issues real-time TC surface wind analyses. The purpose of this article is to provide value-added estimations of several meteorological and oceanographic (met-ocean) parameters including overwater friction velocity and turbulence intensity, variation of the wind speed with height, significant wave height, peak or dominant wave period, wind-driven currents and wind-stress tides. Since these proposed value-added parameters are also validated by other independent methods available from the literature, these met-ocean parameters may be used for marine science and engineering including offshore energy (such as oil, gas and wind power) research, development, operation and maintenance.

Physics-augmented Deep Learning to Improve Tropical Cyclone Intensity and Size Estimation from Satellite Imagery

AbstractA deep learning-based method augmented by prior knowledge of tropical cyclones (TCs), called DeepTCNet, is introduced to estimate TC intensity and wind radii from infrared (IR) imagery over the North Atlantic Ocean. While standard deep learning practices have many advantages over conventional analysis approaches and can produce reliable estimates of TCs, the data-driven models informed by machine-readable physical knowledge of TCs could achieve higher performance. To this end, two approaches are explored to develop the physics-augmented DeepTCNet: (i) infusing the auxiliary physical information of TCs into models for single-task learning; (ii) learning auxiliary physical tasks for multi-task learning. More specifically, augmented by auxiliary information of TC fullness (a measure of the radial decay of the TC wind field), the DeepTCNet yielded a 12% improvement in estimating TC intensity over the non-augmented one. By learning TC wind radii and auxiliary TC intensity task simultaneously, the model’s wind radii estimation skill is improved by 6% over only learning four wind radii tasks, and by 9% over separately learning a single wind radii task. The evaluation results showed that the DeepTCNet is in-line with the Satellite Consensus technique (SATCON) but systematically outperforms the Advanced Dvorak Technique (ADT) at all intensity scales with an averaged 39% enhancement in TC intensity estimation. The DeepTCNet also surpasses the Multi-platform Tropical Cyclone Surface Wind Analysis technique (MTCSWA) with an average improvement of 32% in wind radii estimation.

Assimilation of GNSS reflectometry delay‐Doppler maps with a two‐dimensional variational analysis of global ocean surface winds

AbstractDirect remote‐sensing observations (e.g., radar backscatter, radiometer brightness temperature, or radio occultation bending angle) are often more effective for use in data assimilation (DA) than the corresponding geophysical retrievals (e.g., ocean surface winds, soil moisture, or atmospheric water vapor). In the particular case of Global Navigation Satellite System Reflectometry (GNSS‐R), the lower‐level delay‐Doppler map (DDM) observable shows a complicated relationship with the ocean surface wind field. Prior studies have demonstrated DA using GNSS‐R wind retrievals inferred from DDMs. The complexity of the DDM dependence on winds, however, suggests that the alternative approach of ingesting DDM observables directly into DA systems, without performing a wind retrieval, may be beneficial. We demonstrate assimilation of DDM observables from the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission into global ocean surface wind analyses using a two‐dimensional variational analysis method. Bias correction and quality‐control methods are described. Several models for the required observation‐error covariance matrix are developed and evaluated, with the conclusion that a diagonal matrix performs as well as a fully populated matrix empirically tuned to a large ensemble of CYGNSS observation data. The 10‐m surface winds from the European Centre for Medium‐Range Weather Forecasts (ECMWF) operational forecast are used as the background (i.e., prior in the variational analysis). Results are compared with independent scatterometer (the advanced scatterometer (ASCAT), the oceansat‐2 Scatterometer (OSCAT)) winds. For one month (June 2017) of data, the root‐mean‐square difference (RMSD) was reduced from 1.17 to 1.07 m·s−1 and bias from −0.14 to −0.08 m·s−1 for the wind speed at the specular point. Within a 150‐km wide swath along the specular point track, the RMSD was reduced from 1.20 to 1.13 m·s−1. These RMSD and bias statistics are smaller than other CYGNSS wind products available at this time.

Evaluation of the Surface Wind Field over Land in WRF Simulations of Hurricane Wilma (2005). Part I: Model Initialization and Simulation Validation

AbstractAlthough global and regional dynamical models are used to predict the tracks and intensities of hurricanes over the ocean, these models are not currently used to predict the wind field and other impacts over land. This two-part study performs detailed evaluations of the near-surface, overland wind fields produced in simulations of Hurricane Wilma (2005) as it traveled across South Florida. This first part describes the production of two high-resolution simulations using the Weather Research and Forecasting (WRF) Model, using different boundary layer parameterizations available in WRF: the Mellor–Yamada–Janjić (MYJ) scheme and the Yonsei University (YSU) scheme. Initial conditions from the Global Forecasting System are manipulated with a vortex-bogusing technique to modify the initial intensity, size, and location of the cyclone. It is found possible through trial and error to successfully produce simulations using both the YSU and MYJ schemes that closely reproduce the track, intensity, and size of Wilma at landfall. For both schemes the storm size and structure also show good agreement with the wind fields diagnosed by H*WIND and the Tropical Cyclone Surface Wind Analysis. Both over water and over land, the YSU scheme has stronger winds over larger areas than does the MYJ, but the surface winds are more reduced in areas of greater surface roughness, particularly in urban areas. Both schemes produced very similar inflow angles over land and water. The overland wind fields are examined in more detail in the second part of this study.

Utilization of surface meteorological data, Himawari-8 satellite data, and radar data to analyze landspout in Sumenep, East Java, Indonesia (case study of 20 November 2017)

One of the extreme weather that happened in Indonesia is landspout. Landspout is virtually a tornado that forms from a thunderstorm that is not a supercell. On November 20, 2017 at 08.00 UTC there was a landspout in the village of Kertasada, Kalianget District, Sumenep Regency of Madura, East Java, Indonesia which caused damage to dozens of houses and many shops and warehouses. The study was done to determine the differences condition of the atmosphere before, during, and after the phenomenon based on synoptic analysis, atmospheric instability analysis, satellite image analysis, and radar image analysis. The results of the synoptic analysis of two weather parameters, pressure and temperature, also supported the occurrence of landspout phenomenon. Pressure and air temperature for two days before the occurrence of the landspout had a relatively similar pattern, but the average pressure appeared higher on the day of the incident. Temperature patterns showed a decrease from one hour before the incident, which was 3.2°C. The surface wind analysis showed wind speed during the day of the incident was higher than the previous two days, with a difference of 6 m s-1. The analysis of atmospheric instability when the incidence of the Lifted-Index (LI) values indicates the ‘unstable atmosphere and possible thunderstorm criteria. K-Index (KI) shows the possible to become moderate convetive’ The total index (TT) showed a stronger convective, local lightning potential and a value were higher than the previous two days. Severe Weather Threat Index (SWEAT) showed the potential of lightweight thunderstorm with greater instability value than the previous day while the Convective Avalilable Potential Energy (CAPE) index showed a large and potentially stormy energy. Then, in this research used Himawari-8 satellite and Radar C-band to detected convective clouds. According to Satellite Animation and Interactive Diagnosis (SATAID) satellite data, there is a Cumulonimbus (cb) cloud clump in the Sumenep region of Madura, which is meant to be potentially a landspout.

Developing a Quality Index Associated with Rain for Hurricane Winds from SAR

Differences in synthetic aperture radar (SAR)-retrieved hurricane wind speeds from co-polarization and cross-polarization measurements are found to be correlated with rain rate. A quality index is proposed for the SAR-retrieved wind speed product to recognize heavy rain- affected areas by taking account of the different imaging mechanisms of the radar backscattering from the ocean surface via cross-polarization and co-polarization observations. A procedure is proposed to rectify wind retrievals in the rain-contaminated areas within the hurricane core, based on the theoretical physical profile for hurricanes. The effectiveness of the proposed methodology for heavy rain area recognition and wind speed reconstruction in the rain-affected areas is validated against step frequency microwave radiometer measurements from hurricane reconnaissance missions and the hurricane surface wind analysis product (HWIND). The quality flags provide confidence levels of hurricane surface winds from SAR, which together with the proposed method to correct wind retrievals in rain-contaminated areas, can contribute to improved operational applications of SAR-derived winds under hurricane conditions.

Using sentinel-1A SAR wind retrievals for enhancing scatterometer and radiometer regional wind analyses

ABSTRACTScatterometer surface wind speed and direction observations in combination with radiometer wind speeds allow to generate surface wind analyses with high space and time resolutions over global as well as at regional scales. Regarding scatterometer sampling schemes and physics, the resulting surface wind analyses suffer from lack of accuracy in areas near coasts. The use of the synthetic aperture radar (SAR) onboard the Sentinel-1A satellite attempts to address the enhancement of surface wind analyses issues. In this study, SAR wind speeds and directions retrieved from backscatter coefficients acquired in interferometric wide (IW) swath mode are used. Their accuracy is determined through comprehensive comparisons with moored buoy wind measurements. SAR and buoy winds agree well at offshore and nearshore locations. The statistics characterizing the comparison of SAR and buoy wind speeds and directions are of the same order as those obtained from scatterometer (Advanced SCATterometer (ASCAT) and RapidScat) and buoy wind comparisons. The main discrepancy between SAR and buoy data are found for high wind speeds. SAR wind speeds exceeding 10 m s–1 tend to be underestimated. A similar conclusion is drawn from SAR and scatterometer wind speed comparisons. It is based on the underestimation of SAR backscatter coefficient (σ°) with respect to σ° estimated from scatterometer winds and the geophysical model function (GMF) named CMOD-IFR2 (Ifremer C band MODel). New SAR wind speeds are retrieved using CMOD-IFR2. The corrected SAR retrievals allow better determination of the spatial characteristics of surface wind speeds and of the related wind components in near-coast areas. They are used for enhancing the determination of the spatial structure function required for the estimation of wind fields gridded in space and time at the regional scale. The resulting wind fields are only determined from scatterometer wind observations in combination with radiometer retrievals. Their qualities are determined through comparisons with SAR wind speeds and directions, and through their application for determination of wind power off Brittany coasts.

Variational Analysis of Simulated Ocean Surface Winds from the Cyclone Global Navigation Satellite System (CYGNSS) and Evaluation Using a Regional OSSE

AbstractA positive impact of adding directional information to observations from the Cyclone Global Navigation Satellite System (CYNGSS) constellation of microsatellites is observed in simulation using a high-resolution nature run of an Atlantic hurricane for a 4-day period. Directional information is added using a two-dimensional variational analysis method (VAM) for near-surface vector winds that blends simulated CYGNSS wind speeds with an a priori background vector wind field at 6-h analysis times. The resulting wind vectors at CYGNSS data locations are more geophysically self-consistent when using high-resolution 6-h forecast backgrounds from a Hurricane Weather Research and Forecast Model (HWRF) control observing system simulation experiment (OSSE) compared to low-resolution 6-h forecasts from an associated Global Forecast System (GFS) model control OSSE. An important contributing factor is the large displacement error in the center of circulation in the GFS background wind fields that produces asymmetric circulations in the associated VAM analyses. Results of a limited OSSE indicate that CYGNSS winds reduce forecast error in hurricane intensity in 0–48-h forecasts compared to using no CYGNSS data. Assimilation of VAM-CYGNSS vector winds reduces maximum wind speed error by 2–5 kt (1 kt = 0.51 m s−1) and reduces minimum central pressure error by 2–5 hPa. The improvement in forecast intensity is notably larger and more consistent than the reduction in track error. The assimilation of VAM-CYGNSS wind vectors constrains analyses of surface wind field structures during OSSE more effectively than wind speeds alone. Because of incomplete sampling and the limitations of the data assimilation system used, CYGNSS scalar winds produce unwanted wind/pressure imbalances and asymmetries more often than the assimilation of VAM-CYGNSS data.

Integrated kinetic energy of Atlantic tropical cyclones in a global ocean surface wind analysis

The integrated kinetic energy (IKE) of a tropical cyclone (TC), a volume integration of the surface winds around the centre of the TC, is computed from a comprehensive surface wind (National Aeronautics and Space Administration’s (NASA) cross‐calibrated multi‐platform [CCMP]) analysis available over the global oceans to verify against IKE from wind radii estimates of extended best‐track data maintained by NOAA for the North Atlantic TCs. It is shown that CCMP surface wind analysis severely underestimates IKE largely from not resolving hurricane force winds for majority of the Atlantic TCs, under sampling short‐lived and small‐sized TCs. The seasonal cycle of the North Atlantic TC IKE also verifies poorly in the CCMP analysis. In this article we introduce proxy IKE (PIKE) based on the kinetic energy of the winds at the radius of the last closed isobar (ROCI), which shows promise for a wide range of TC sizes including the smaller‐sized TCs unresolved in the CCMP data set.

Position of the South Atlantic Anticyclone and Its Impact on Surface Conditions across Brazil

AbstractThis study examines the surface wind characteristics of Brazil on the basis of the location of the maximum high pressure center in the South Atlantic basin (SAB), known as the South Atlantic anticyclone (SAA), from three reanalysis datasets for the period of 1980–2014. Linear wind speed trends determined for Brazil are geographically related to surface and macroscale atmospheric conditions found in the SAB. The daily mean position of the SAA exhibited a latitudinal poleward shift for all seasons, and a longitudinal trend was dependent upon extratropical activity found in the SAB. Results also show that wind speed and sea level pressure for northern Brazil are dependent upon the latitudinal position of the SAA. Consequently, surface wind correlations for southern Brazil tend to be related to changes in the longitudinal position of the SAA, which result from transient anticyclones migrating over the SAB. An examination of positive and negative wind anomalies shows that shifts in the position of the SAA are coupled with changes in sea level pressure for northern Brazil and air temperature for southern Brazil. From these findings, a surface wind analysis was performed to demonstrate how the geographical location of the SAA affects wind speed anomalies across Brazil and the SAB. Results from this study can assist in understanding how atmospheric systems change within the SAB so that forthcoming socioeconomic and climate-related causes of wind for the country of Brazil can be known.

Factors influencing the skill of synthesized satellite wind products in the tropical Pacific

Given the importance of tropical Pacific winds to global climate, it is interesting to examine differences in the mean and trend among various wind products, and their implications for ocean circulation. Past analysis has revealed that despite the assimilation of observational data, there remain large differences among reanalysis products. Thus, here we examine if satellite‐based synthesis products may provide more consistent estimate than reanalysis. Reanalysis product winds are, however, typically used as a background constraint in constructing the synthesis products to fill spatiotemporal gaps and to deal with satellite wind direction ambiguity. Our study identified two important factors that influence both the mean and trends from synthesized wind products. First, the choice of background wind product in synthesized satellite wind products affects the mean and long‐term trends, which has implications for simulations of ocean circulation, sea level, and presumably SST. Second, we identify a clear need for developing a better understanding of, and correcting differences between in situ observations of absolute winds with the satellite‐derived relative winds prior to synthesizing. This correction requires careful analysis of satellite surface winds with existing colocated in situ measurements of surface winds and currents, and will benefit from near‐surface current observations of the proposed Tropical Pacific Observing System. These results also illustrate the difficulty in independently evaluating the synthesis wind products because the in situ data have been utilized at numerous steps during their development. Addressing these identified issues effectively, will require enhanced collaborations among the wind observation (both satellite and in situ), reanalysis, and synthesis communities.

Two decades [1992–2012] of surface wind analyses based on satellite scatterometer observations

Surface winds (equivalent neutral wind velocities at 10m) from scatterometer missions since 1992 have been used to build up a 20-year climate series. Optimal interpolation and kriging methods have been applied to continuously provide surface wind speed and direction estimates over the global ocean on a regular grid in space and time. The use of other data sources such as radiometer data (SSM/I) and atmospheric wind reanalyses (ERA-Interim) has allowed building a blended product available at 1/4° spatial resolution and every 6h from 1992 to 2012. Sampling issues throughout the different missions (ERS-1, ERS-2, QuikSCAT, and ASCAT) and their possible impact on the homogeneity of the gridded product are discussed. In addition, we assess carefully the quality of the blended product in the absence of scatterometer data (1992 to 1999). Data selection experiments show that the description of the surface wind is significantly improved by including the scatterometer winds. The blended winds compare well with buoy winds (1992–2012) and they resolve finer spatial scales than atmospheric reanalyses, which make them suitable for studying air-sea interactions at mesoscale. The seasonal cycle and interannual variability of the product compare well with other long-term wind analyses. The product is used to calculate 20-year trends in wind speed, as well as in zonal and meridional wind components. These trends show an important asymmetry between the southern and northern hemispheres, which may be an important issue for climate studies.

Wind Structure Discrepancies between Two Best Track Datasets for Western North Pacific Tropical Cyclones

Abstract Symmetric and wavenumber-1 asymmetric characteristics of western North Pacific tropical cyclone (TC) outer wind structures are compared between best tracks from the Joint Typhoon Warning Center (JTWC) and the Japan Meteorological Agency (JMA) from 2004 to 2014 as well as the Multiplatform Tropical Cyclone Surface Wind Analysis (MTCSWA) product from 2007 to 2014. Significant linear relationships of averaged wind radii are obtained among datasets, in which both gale-force and storm-force wind radii are generally estimated slightly smaller (much larger) by JTWC (JMA) than by MTCSWA. These correlations are strongly related to TC intensity relationships discussed in earlier work. Moreover, JTWC (JMA) on average represents a smaller (greater) derived shape parameter than MTCSWA does, implying that JTWC (JMA) typically assesses a more compact (less compact) storm than MTCSWA. For the wavenumber-1 asymmetry, large differences among datasets are found regardless of the magnitude or the direction of the longest radius. JTWC estimates more asymmetric storms than JMA, and it provides greater wavenumber-1 asymmetry magnitudes on average. Asymmetric storms are most frequently oriented toward the east, northeast, and north in JTWC and MTCSWA, whereas they are most frequently oriented toward the southeast, east, and northeast in JMA. The direction of the longest gale-force (storm force) wind radius in JTWC is statistically rotated 18° (32°) clockwise to that in JMA. Although the wind radii in JTWC are of higher quality than those in JMA when using MTCSWA as a baseline, there remains a need to provide a consistent and reliable wind radii estimating process among operational centers.

Evaluation of hurricane wind speed retrieval from cross-dual-pol SAR

ABSTRACTUnderstanding and forecasting hurricanes are important components of weather prediction and climate studies. A critical concern is accuracy in hurricane wind speed estimates, especially in areas over the ocean where in situ measurements are sparse. Moreover, for very intense hurricanes, remotely sensed ocean surface winds generally lack accuracy. Recent studies on cross-polarization RADARSAT-2 synthetic aperture radar (SAR) data show very promising capability for high wind speed retrieval. The monotonic increase of cross-pol radar backscattered intensity with wind speed, and less sensitive dependence on wind direction, makes it superior to co-pol SAR measurements for operational application. Before further application of the methodology, it is important to evaluate the capability of hurricane forced wind speed retrieval from the promising, simple cross-pol SAR data. In this study, we apply a newly developed wind retrieval model to hurricanes using VH polarization dual-pol mode (VH dual-pol) RADARSAT-2 ScanSAR images. Validation of SAR wind retrievals is via surface wind analysis data from the Hurricane Research Division (HRD) of the National Oceanic and Atmospheric Administration (NOAA) and airborne stepped frequency microwave radiometer (SFMR) measurements. We found that compared to the co-polarization RADARSAT-2 SAR measurements, retrieved wind speeds from cross-polarization mode SAR have better overall accuracy and are more consistent with expected hurricane structures. Moreover, the cross-polarization model for VH dual-pol-retrieved winds does not appear to exhibit the speed ambiguity problem, which is one of the main obstacles for co-polarization retrieval of hurricane winds. SAR-retrieved winds contain detailed wind structures of the hurricane eyewall which are potentially of value for ongoing improvements in numerical models of hurricanes, air–sea interactions, and climate change. Special attention must be paid to biases caused by precipitation in order to reduce remaining errors in SAR retrieval of hurricane winds; precipitation has not been explicitly considered by current geophysical model functions.

Impact of sea-land breezes on 210Pb in southern Iberian Peninsula – Feasibility study on using submicron-sized aerosol particles to analyze 210Pb hourly patterns

This work addresses the impact of mesoscale circulations on 210Pb concentrations in southwestern Iberian Peninsula by analysing the 210Pb database at El Arenosillo station during 2004–2011 (128 periods with a time scale of 48 h).The analysis of surface winds during each one of these periods has revealed the positive impact of the two sea-land breeze patterns (pure and non-pure), previously identified in this region, on 210Pb activity concentrations. An average value of 0.80 ± 0.09 mBq m−3 was obtained for the pure pattern (34 periods), 0.54 ± 0.09 mBq m−3 for the non-pure pattern (23 periods) and 0.46 ± 0.04 mBq m−3 for the rest (71 periods).The analysis of one representative period of each sea-land breeze patterns is also presented. To perform this analysis we have used: hourly surface wind observations, surface wind fields simulated by the WRF mesoscale model and the hourly database of sub-micron-particle size range in the accumulation mode (NACC). The use of this type of particles to investigate the hourly temporal variability of 210Pb is based on the high correlation, obtained in the present work, between 210Pb activity and particles in the accumulation mode (R = 0.90).The analysis reveals that the highest concentrations of NACC, and hence, 210Pb, are obtained when the sampling area is under the influence of the pure breeze, due to it favours the accumulation of particles previously transported by Mediterranean flows along the Guadalquivir valley. In the case of the non-pure pattern, the increase in the concentration of particles is related to the arrival of background synoptic winds from the continental areas of western Iberian Peninsula. In the latest, the increment of NACC is faster and around 400 particles cm−3, while in the case of the pure pattern, it is progressive up to 1400 particles cm−3.

Characteristics of surface wind structure of tropical cyclones over the north Indian Ocean

Tropical cyclone (TC) wind field monitoring and forecast are important for mariners, ships on sea and modelling group for creation of synthetic vortex, and storm surge and coastal inundation forecasting. Among others, a multi-platform satellite surface wind analysis developed by Co-operative Institute for Research in the Atmosphere (CIRA), USA for the TCs are referred by India Meteorological Department for surface wind field monitoring of TC. Hence, a study has been undertaken to analyze the characteristics of surface wind distribution and hence the structure of TC based on the real time data available from CIRA during 2007–2013. The study includes 19 TCs over the Bay of Bengal (BOB) and six over Arabian Sea (AS). The maximum radial extent of winds reaching threshold values of 34(17), 50(26) and 64(33) knot (ms−1) in each of the four geographical quadrants has been segregated with respect to season of formation, basin of formation and intensity of TC for analysis. The objective is to develop a reference surface wind structure of TC and examine its validity with respect to physical processes.The size of outer core (34(17) knot (ms−1) wind radial extension) as well as inner core (50(26) and 64(33) knot (ms−1) wind radial extension) increases significantly with increase in intensification of TC over BOB during both pre-monsoon and post-monsoon seasons and over AS during pre-monsoon season. The outer core of winds in TCs over the BOB is asymmetric in both pre-monsoon and post-monsoon seasons and for all categories of intensity of TCs. On the other hand, the asymmetry in inner core winds is significantly less. There is also no asymmetry in radial wind extension over the AS during both the seasons, except in case of outer core wind radial extension of VSCS during pre-monsoon season. The low level environment like enhanced cross equatorial flow, lower/middle level relative humidity, vertical wind shear and proximity of TC to the land surface are the determining factors for the size and asymmetry of TCs over the NIO.

Relation between the upper ocean heat content in the equatorial Atlantic during boreal spring and the Indian monsoon rainfall during June–September

ABSTRACTEarlier studies have identified a teleconnection between the Atlantic zonal mode (AZM) and Indian summer monsoon rainfall (ISMR), both of which are active during the boreal summer (AZM: June–August; ISMR: June–September). It is known that El Niño‐Southern Oscillation (ENSO)‐like coupled dynamics are operational in the tropical Atlantic during the AZM events. Our goal here is to extend this process understanding to seek a predictive relation between the tropical Atlantic and the ISMR based on these known teleconnections. Monthly composite analysis of the zonal surface winds, heat content, and sea surface temperature (SST) in the equatorial Atlantic tells us that signatures of a warm or cold AZM event begin to emerge as early as January of that year. We found significant correlations between the ISMR and the low level zonal winds in the western equatorial Atlantic and heat content in the eastern equatorial Atlantic in the boreal spring season. Tracking coherent changes in these winds and the evolution of the heat content in the deep tropical Atlantic in the boreal spring may offer the potential for skillful predictions of the ensuing summer monsoon anomalies, especially during non‐ENSO years when the predictability of ISMR tends to be low.

A new aircraft hurricane wind climatology and applications in assessing the predictive skill of tropical cyclone intensity using high‐resolution ensemble forecasts

AbstractHurricane surface wind is a key measure of storm intensity. However, a climatology of hurricane winds is lacking to date, largely because hurricanes are relatively rare events and difficult to observe over the open ocean. Here we present a new hurricane wind climatology based on objective surface wind analyses, which are derived from Stepped Frequency Microwave Radiometer measurements acquired by NOAA WP‐3D and U.S. Air Force WC‐130J hurricane hunter aircraft. The wind data were collected during 72 aircraft reconnaissance missions into 21 western Atlantic hurricanes from 1998 to 2012. This climatology provides an opportunity to validate hurricane intensity forecasts beyond the simplistic maximum wind speed metric and allows evaluating the predictive skill of probabilistic hurricane intensity forecasts using high‐resolution model ensembles. An example of application is presented here using a 1.3 km grid spacing Weather Research and Forecasting model ensemble forecast of Hurricane Earl (2010).