Adaptive use of research aircraft data sets for hurricane forecasts

Summary This study uses an adaptive observational strategy for hurricane forecasting. It shows the impacts of Lidar Atmospheric Sensing Experiment (LASE) and dropsonde data sets from Convection and Moisture Experiment (CAMEX) field campaigns on hurricane track and intensity forecasts. The following cases are used in this study: Bonnie, Danielle and Georges of 1998 and Erin, Gabrielle and Humberto of 2001. A single model run for each storm is carried out using the Florida State University Global Spectral Model (FSUGSM) with the European Center for Medium Range Weather Forecasts (ECMWF) analysis as initial conditions, in addition to 50 other model runs where the analysis is randomly perturbed for each storm. The centers of maximum variance of the DLM heights are located from the forecast error variance fields at the 84-hr forecast. Back correlations are then performed using the centers of these maximum variances and the fields at the 36-hr forecast. The regions having the highest correlations in the vicinity of the hurricanes are indicative of regions from where the error growth emanates and suggests the need for additional observations. Data sets are next assimilated in those areas that contain high correlations. Forecasts are computed using the new initial conditions for the storm cases, and track and intensity skills are then examined with respect to the control forecast. The adaptive strategy is capable of identifying sensitive areas where additional observations can help in reducing the hurricane track forecast errors. A reduction of position error by approximately 52% for day 3 of forecast (averaged over 7 storm cases) over the control runs is observed. The intensity forecast shows only a slight positive impact due to the model’s coarse resolution. Corresponding author’s address: T. N. Krishnamurti, Department of Meteorology, Florida State University, Tallahassee, FL 32306-4520, USA     

Multi-year prediction model of North Atlantic hurricane activity

Summary An empirical prediction algorithm is developed to assess the potential of useful multi-season forecasts of North Atlantic hurricane activity. The algorithm is based on combining separate univariate autoregressive moving average (ARMA) models for each of three dominant components of hurricane activity. A Bayesian criterion is used to select the order of each model. In a single retroactive hindcast experiment, the algorithm is found to make better hindcasts than an ARMA model of the detrended series. A real-time forecast of hurricane activity for the 1997 North Atlantic hurricane season proves to be more accurate than two competitive single-season forecast models. It is expected that the routine use of the forecast algorithm in an operational setting will result in only marginal skill against climatology; it could however offer considerable forecast value as realized by benefits to decision makers in the reinsurance industry.With 4 Figures     

Increased hurricane intensities with CO2-induced warming as simulated using the GFDL hurricane prediction system

 The impact of CO₂-induced global warming on the intensities of strong hurricanes is investigated using the GFDL regional high-resolution hurricane prediction system. The large-scale initial conditions and boundary conditions for the regional model experiments, including SSTs, are derived from control and transient CO₂ increase experiments with the GFDL R30-resolution global coupled climate model. In a case study approach, 51 northwest Pacific storm cases derived from the global model under present-day climate conditions are simulated with the regional model, along with 51 storm cases for high CO₂ conditions. For each case, the regional model is integrated forward for five days without ocean coupling. The high CO₂ storms, with SSTs warmer by about 2.2 °C on average and higher environmental convective available potential energy (CAPE), are more intense than the control storms by about 3–7 m/s (5%–11%) for surface wind speed and 7 to 24 hPa for central surface pressure. The simulated intensity increases are statistically significant according to most of the statistical tests conducted and are robust to changes in storm initialization methods. Near-storm precipitation is 28% greater in the high CO₂ sample. In terms of storm tracks, the high CO₂ sample is quite similar to the control. The mean radius of hurricane force winds is 2 to 3% greater for the composite high CO₂ storm than for the control, and the high CO₂ storms penetrate slightly higher into the upper troposphere. More idealized experiments were also performed in which an initial storm disturbance was embedded in highly simplified flow fields using time mean temperature and moisture conditions from the global climate model. These idealized experiments support the case study results and suggest that, in terms of thermodynamic influences, the results for the NW Pacific basin are qualitatively applicable to other tropical storm basins. Received: 20 July 1998/Accepted: 24 December 1998     

Multi-year prediction skill of Atlantic hurricane activity in CMIP5 decadal hindcasts

Using a statistical relationship between simulated sea surface temperature and Atlantic hurricane activity, we estimate the skill of a CMIP5 multi-model ensemble at predicting multi-annual level of Atlantic hurricane activity. The series of yearly-initialized hindcasts show positive skill compared to simpler forecasts such as persistence and climatology as well as non-initialized forecasts and return anomaly correlation coefficients of ～0.6 and ～0.8 for five and nine year forecasts, respectively. Some skill is shown to remain in the later years and making use of those later years to create a lagged-ensemble yields, for individual models, results that approach that obtained by the multi-model ensemble. Some of the skill is shown to come from persisting rather than predicting the climate shift that occur in 1994–1995. After accounting for that shift, the anomaly correlation coefficient for five-year forecasts is estimated to drop to 0.4, but remains statistically significant up to lead years 3–7. Most of the skill is shown to come from the ability of the forecast systems at capturing change in Atlantic sea surface temperature, although the failure of most systems at reproducing the observed slow down in warming over the tropics in recent years leads to an underestimation of hurricane activity in the later period.     

利用卫星微波观测亮温与云辐射模拟亮温的台风定位分析

极轨气象卫星S-NPP、MetOp-A和FY-3B上搭载的微波湿度计观测资料可以反映出台风周围水汽和云雨结构。本文使用权重函数峰值在800 hPa附近的微波湿度计通道观测资料和ERA5再分析资料全天空模拟亮温,以飓风Sandy和Isaac为例,对用方位谱台风中心位置定位方法得到的观测和模拟中心位置进行了比较。利用下午星S-NPP搭载的先进技术微波探测仪(Advanced Technology Microwave Sounder, ATMS)和上午星MetOp-A搭载的微波湿度计(Microwave Humidity Sounder, MHS)观测亮温得到的飓风Sandy(Isaac)中心位置与最佳路径平均相差35.8 km(32.9 km),但用ERA5全天空模拟亮温得到的飓风Sandy(Isaac)中心位置与最佳路径平均相差73.3 km(82.1 km)。若按照热带风暴和台风等级来划分,ATMS和MHS观测和模拟亮温得到的台风中心位置与最佳路径的平均距离对热带风暴分别是36.5 km和105.9 km,对台风分别是25.8 km和56.4 km。若用FY-3B搭载的微波湿度计(以M...     

Spatial grids for hurricane climate research

The authors demonstrate a spatial framework for studying hurricane climatology. The framework consists of a spatial tessellation of the hurricane basin using equal-area hexagons. The hexagons are efficient at covering hurricane tracks and provide a scaffolding to combine attribute data from tropical cyclones with spatial climate data. The framework’s utility is demonstrated using examples from recent hurricane seasons. Seasons that have similar tracks are quantitatively assessed and grouped. Regional cyclone frequency and intensity variations are mapped. A geographically-weighted regression of cyclone intensity on sea-surface temperature emphasizes the importance of a warm ocean in the intensification of cyclones over regions where the heat content is greatest. The largest differences between model predictions and observations occur near the coast. The authors suggest the framework is ideally suited for comparing tropical cyclones generated from different numerical simulations.     

On hurricane energy

Warm seawater is the energy source for hurricanes. Interfacial sea-to-air heat transfer without spray ranges from 100?W?m^?2 in light wind to 1,000?W?m^?2 in hurricane force wind. Spray can increase sea-to-air heat transfer by two orders of magnitude and result in heat transfers of up to 100,000?W?m^?2. Drops of spray falling back in the sea can be 2–4?°C colder than the drops leaving the sea, thus transferring a large quantity of heat from sea to air. The heat of evaporation is taken from the sensible heat of the remainder of the drop; evaporating approximately 0.3?% of a drop is sufficient to reduce its temperature to the wet bulb temperature of the air. The heat required to evaporate hurricane precipitation is roughly equal to the heat removed from the sea indicating that sea cooling is due to heat removal from above and not to the mixing of cold water from below. The paper shows how case studies of ideal thermodynamic processes can help explain hurricane intensity.     

Numerical weather prediction as a surrogate for climate observations in practical applications

Climate data is used in many practical applications including energy demand estimations for heating and cooling, agricultural applications, risk assessment, and many more. The required climate data is only available if meteorological observations exist at a given location. In this study, the possibility of replacing long observational records with a few years of numerical weather forecast data is investigated for practical applications requiring temperature data. Observational data from 1980–2010, measured at 700 weather stations in Central Europe are used together with model forecasts of the years 2008–2010. Depending on the station, forecast data capture 90–110% of the standard deviation observed for daily mean and maximum temperatures and slightly less for minimum temperature. Heating and cooling degree days can be estimated with an error of 5–15% in climates where they have a relevance. Based on model data, maps of heating and cooling degree days are computed and the regional uncertainties are quantified using the observational data. The results suggest that numerical weather forecast data can be used for certain practical applications, either as a surrogate of observational data or for quite reliable estimates in locations with no observations.     

Total energy equation method for calculating hurricane intensity

Summary Surface pressure reduction in hurricanes is calculated by applying the total energy equation (TEE) to ideal isentropic upflow in a vertical tube. The pressure reduction at the base of the tube, called the intensity, is calculated for three upflow processes: reversible upflow of air approaching equilibrium with the sea at the sea level pressure outside the tube; irreversible upflow of air approaching equilibrium with the sea at the sea-level pressure outside the tube; and upflow of air approaching equilibrium with the sea at the reduced surface pressure inside the tube. The sensitivity of intensity to the type of upflow process and to the sea surface temperature is investigated. Intensities calculated with the TEE are shown to be consistent with observations and to be close to intensities calculated with more complex methods. The TEE method is simple and can help understand the basic mechanism responsible for surface pressure reduction and for energy production. The method is used to show that approximately 20% of the heat taken from the sea during a hurricane is converted to mechanical energy. Received December 4, 2000/Revised March 29, 2001     

Surface pressure profiles, vortex structure and initialization for hurricane prediction. Part I: analysis of observed and synthetic structures

Without detailed reconnaissance, consistent representation of hurricane-like vortices in initial conditions for operational prediction and research simulations still remains elusive. It is thus often necessary, particularly for high-resolution intensity forecasting, to use synthetic tropical cyclone circulations to initialize forecast models. Variants on three commonly used surface pressure profiles are evaluated for possible use. Enhancements to the original profiles are proposed that allows definition of both the inner-core and outer circulation. The latter improvement creates a vortex more consistent with the estimated outer structure which sometimes appears to be crucial to the evolving intensity of the storm. It also allows smoother merging of the synthetic vortex with the environment. Comparisons of the profiles against (a) structure estimates, (b) each other, (c) structures obtained via conservation of angular momentum, and (d) observed vorticity structures, suggest that a new enhanced Fujita profile best represents real TC structures. Student-t tests indicate that improved fitting to the observations is statistically significant.     

Adaptive observations in the context of 4D-Var data assimilation

Summary The design of adaptive observations strategies must account for the particular properties of the data assimilation method. A new adjoint sensitivity approach to the targeted observations problem is proposed in the context of four-dimensional variational data assimilation (4D-Var). The method is based on a periodic update of the adjoint sensitivity field that takes into account the interaction between time distributed adaptive and routine observations. Information provided by all previously located observations is used to identify best locations for new targeted observations. Adaptive observations at distinct instants in time are selected in a sequential manner such that the method is only suboptimal. The selection algorithm proceeds backward in time and requires only one additional adjoint model integration in the assimilation window. Therefore, the method is very efficient and is suitable for practical applications. A comparative performance analysis is presented using the traditional adjoint sensitivity method as well as the total energy singular vectors technique as alternative adaptive strategies. Numerical experiments are performed in the twin experiments framework using a two-dimensional global shallow water model in spherical coordinates and an explicit Turkel-Zwas discretization scheme. Data from a NASA 500mb analysis valid for 00Z 16 Mar 2001 6h obtained with the GEOS-3 model was used to specify the geopotential height at the initial time and the initial velocities were obtained from a geostrophic balance. Numerical results show that the new adaptive observations approach is a promising method for targeted observations and its implementation is feasible for large scale atmospheric models.     

Surface pressure profiles, vortex structure and initialization for hurricane prediction. Part II: numerical simulations of track, structure and intensity

In part 1 of this study, an assessment of commonly used surface pressure profiles to represent TC structures was made. Using the Australian tropical cyclone model, the profiles are tested in case studies of high-resolution prediction of track, structure and intensity. We demonstrate that: (1) track forecasts are mostly insensitive to the imposed structure; (2) in some cases [here Katrina (2005)], specification of vortex structure can have a large impact on prediction of structure and intensity; (3) the forecast model mostly preserves the characteristics of the initial structure and so correct structure at t?=?0 is a requirement for improved structure forecasting; and (4) skilful prediction of intensity does not guarantee skilful prediction of structure. It is shown that for Ivan (2004) the initial structure from each profile is preserved during the simulations, and that markedly different structures can have similar intensities. Evidence presented suggests that different initial profiles can sometimes change the timing of intensification. Thus, correct initial vortex structure is an essential ingredient for more accurate intensity and structure prediction.     

Dissipative heating and hurricane intensity

Summary Dissipative heating has not been accounted for in either numerical simulations of hurricanes or in theories for the maximum intensity of hurricanes. We argue that the bulk of dissipative heating occurs in the atmospheric boundary layer near the radius of maximum winds and, using both theory and numerical simulation, show that dissipative heating increases maximum wind speeds in tropical cyclones by about 20%.With 4 Figures     

Skill of synthetic superensemble hurricane forecasts for the Canadian maritime provinces

Summary From 1994 to 2003, fifty-five tropical cyclones entered the Canadian Hurricane Centre (CHC) Response Zone, or about 42% of all named Atlantic tropical cyclones in this ten-year period, and 2003 was the fourth consecutive year for a tropical cyclone to make landfall in Canada. The CHC forecasts all tropical cyclones that enter the CHC Response Zone and assumes the lead in forecasting once the cyclone enters its area of forecast responsibility. This study acknowledges the challenges of forecasting such tropical cyclones at extratropical latitudes. If a tropical cyclone has been declared extratropical, global models may no longer use vortex bogussing to carry the cyclone, and even if it is modeled, large model errors often result. The purpose of this study is to develop a new version of the Florida State University (FSU) hurricane superensemble with greater skill in tracking tropical cyclones, especially at extratropical latitudes. This has been achieved from the development of the synthetic superensemble, which is similar to the operational version of the multi-model superensemble that is used at FSU. The synthetic superensemble differs in that is has a larger set of member models consisting of regular member models, synthetic versions of these models, and the operational superensemble and its synthetic version. This synthetic superensemble is being used here to forecast hurricane tracks from the 2001, 2002, and 2003 hurricane seasons. The track forecasts from this method have generally less error than those of the member models, the operational superensemble, and the ensemble mean. This study shows that the synthetic superensemble performs consistently well and would be an asset to operational hurricane track forecasting.     

Development of a hurricane boundary-layer wind model

Summary Hurricanes cause a variety of damage due to high winds, heavy rains, and storm surges. This study focuses on hurricanes’ high winds. The most devastating effects of sustained high winds occur in the first few hours of landfall. During the short period, hurricanes’ rainfall often increases, while the low-level pressure gradients continue to weaken. Latent heating does not appear to strengthen the surface winds. The indicator is that dry mechanisms such as the boundary layer processes and terrain are responsible for the damaging winds in the coastal areas. In this study, the design of a dry hurricane boundary layer wind model is described. The goal is to develop a forecast tool with near-real time applications in expeditious wind damage assessment and disaster mitigation during a hurricane landfall event. Different surface roughness lengths and topographic features ranging from flat land to the mountainous terrain of Taiwan were used in the model simulation experiments to reveal how the coastal environment affected the hurricane surface winds. The model performed quite well in all cases. The experiments suggested that the downward transfer of high momentum aloft played a significant role in the maintenance of high wind speeds at the surface. The surface wind maximums were observed on the lee sides of high terrain. The surface streamline analyses showed that the high mountains tended to block the relatively weak flow and caused small eddies, while they forced the stronger flow to turn around the mountains. Due to great difficulty in data collection, the hurricane boundary layer over land remains one of the least understood parts of the system. The dry model proves to be an effective way to study many aspects of hurricane boundary layer winds over a wide range of terrain features and landfall sites. The model runs efficiently and can be run on a medium-size personal computer. Received March 16, 2001 Revised September 10, 2001     

超强台风\

利用欧洲中心ERA-Interim逐6 h再分析资料（水平分辨率0.125°×0.125°）、NOAA逐日海表温度资料（水平分辨率0.25°×0.25°）、日本HMW8卫星逐时黑体亮温TBB（水平分辨率0.05°×0.05°）资料对对流非对称台风\     

Forecasting hurricane winds in extratropical cyclones in Russia

In contrast to the common opinion, hurricane winds in extratropical cyclones are a quite frequent phenomenon followed by huge damage, especially in densely populated areas. This phenomenon has been poorly studied and is hardly predictable so far. The features of hurricane winds in extratropical cyclones, and the similarity and difference in their structure as compared to those in tropical cyclones are revealed.     

Systematic precipitation redistribution following a strong hurricane landfall

The 2017 and 2018 Atlantic hurricane seasons poignantly illustrated the dangers tropical cyclones pose to US, Central American, and Caribbean coastlines. In particular, Hurricane Maria inflicted widespread damage, including catastrophic defoliation, to Puerto Rico, altering surface heat fluxes and possibly modifying precipitation patterns. This study assesses whether defoliation-driven changes to surface energy fluxes redistribute precipitation in the months following a powerful hurricane landfall. Remote sensing analyses of Maria-related vegetation reduction and recovery from Puerto Rico were adapted to the Georgia coastline. In this novel methodology, the resulting landscape evolution, characterized by an instantaneous vegetation reduction with a gradual recovery, was assimilated into the Weather Research and Forecasting model at a convection-allowing a 3-km grid spacing for the 1 June–1 August 2017 period. The experiment revealed that Maria-scale defoliation reduced precipitation by 14% during the month following landfall within a 50 × 50 km zone containing the hypothetical landfall location. A maximum deficit of 20.0% was reached 4 weeks after landfall. For June 2017, the modeled 14% deficit would have shifted the precipitation total from the 61st to the 47th percentile for years 1981–2016. Meanwhile, precipitation totals were unchanged on the domain scale. The near-landfall drying was also evident in three less-severe defoliation simulations, suggesting that systematic precipitation redistribution near the landfall location is possible following storms considerably weaker than Hurricane Maria. Analyses of the temperature and wind fields suggest that coastal kinematic flow is altered by the introduction of a thermally driven pressure gradient in the defoliated zone.     

Sensitivity of hurricane intensity forecasts to physical initialization

Summary Intensity forecasts of a hurricane are shown to be quite sensitive to the initial meso-convective scale precipitation distributions. These are included within the data assimilation using a physical initialization that was developed at Florida State University. We show a case study of a hurricane forecast where the inclusion of the observed precipitation did provide reasonable intensity forecasts. Further experimentation with the inclusion or exclusion of individual meso-convective rainfall elements, around and over the storm, shows that the intensity forecasts were quite sensitive to these initial rainfall distributions. The exclusion of initial rain in the inner rain area of a hurricane leads to a much reduced intensity forecast, whereas that impact is less if the rainfall of an outer rain band was initially excluded.Intensity forecasts of hurricanes may be sensitive to a number of factors such as sea surface temperature anomalies, presence or absence of concentric eye walls, potential vorticity interactions in the upper troposphere and other environmental factors.This paper is a sequel to a recent study, Krishnamurti et al., 1997, on the prediction of hurricane OPAL of 1995 that was a category III storm over the Gulf of Mexico. In that study we showed successful forecasts of the storm intensity from the inclusion of observed rainfall distributions within physical initialization. In that paper we examined the issues of diabatic potential vorticity and the angular momentum in order to diagnose the storm intensity. All of the terms of the complete Ertel potential vorticity equation were evaluated and it was concluded that the diabatic contributions to the potential vorticity were quite important for the diagnosis of the storm's intensity. The present paper addresses some sensitivity issues related to the individual mesoconvective precipitating elements.With 4 Figures