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Adam J. O'Shay
and
T. N. Krishnamurti

Abstract

The main goal of this study is to investigate the relative contributions from the components of dynamics and physics of a forecast model, toward the understanding of the recurvature dynamics of hurricanes. A number of experiments were conducted using the Florida State University Global Spectral Model (FSU GSM), run at a global resolution of 126 waves. The method of physical initialization was used to “spin up” the model, 24 h prior to the 5-day forecast period to better define the initial water vapor, sensible heat fluxes, and rainfall rates.

The usage of the FSU GSM employed a partitioning of the dynamics and physics into separate components, that assumes a residue-free budget of the models' components. The model dynamics were broken down into a nonlinear advective component and also a linear dynamics (rest of the dynamics) partition. The model physics were partitioned into four components: deep convective heating, large-scale precipitation (nonconvective stable rain), total radiation, and shallow convection and surface fluxes. A total of four cases were examined, two each for Hurricanes Cindy and Dennis—1200 UTC 26 and 27 August, and 1200 UTC 28 and 29 August, occurring during the 1999 Atlantic hurricane season. The series of model runs were formulated to examine the tropical cyclone forecast tracks, suppressing one or more of the partitions for each time step, through day 5 of a forecast. Initial experiments coupling both the nonlinear advective and the linear dynamics (summed to equal the “total dynamics”) found that the total dynamics component resulted in a weakly recurving track for each of the storm cases. The addition of the physics components incrementally sharpened the recurving track through time.

While the full model dynamics was used as a baseline, the results of this study indicated that the deep convective heating (also referred to as deep convection) and total dynamics combined to produce a recurving track for both storms, for 50% of the four examined cases. The remaining cases required that the shallow convection and surface fluxes partition be included along with the deep convection and total dynamics. It was found that incremental improvements occurred with both the deep convective heating and shallow convection and surface fluxes partitions, however, the additions of the large-scale precipitation and radiation partitions did not significantly improve the forecast track relative to the full model, and their resulting magnitudes were significantly smaller than the rest.

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S. Pattnaik
,
C. Inglish
, and
T. N. Krishnamurti

Abstract

This study examines the impact of rain-rate initialization (RINIT), microphysical modifications, and cloud torques (in the context of angular momentum) on hurricane intensity forecasts using a mesoscale model [the Advanced Research Weather Research and Forecasting model (ARW-WRF)] at a cloud-resolving resolution of 2.7 km. The numerical simulations are performed in a triple-nested manner (25, 8.3, and 2.7 km) for Hurricane Dennis of 2005. Unless mentioned otherwise, all the results discussed are from the innermost grid with finest resolution (2.7 km). It is found that the model results obtained from the RINIT technique demonstrated robust improvement in hurricane structure, track, and intensity forecasts compared to the control experiment (CTRL; i.e., without RINIT). Thereafter, using RINIT initial conditions datasets three sensitive experiments are designed by modifying specific ice microphysical parameters (i.e., temperature-independent snow intercept parameter, doubling number of concentrations of ice, and ice crystal diameter) within the explicit parameterization scheme [i.e., the WRF Single-Moment 6-class (WSM6)]. It is shown that the experiment with enhanced ice mass concentration and temperature-independent snow intercept parameter produces the strongest and weakest storms, respectively. The results suggest that the distributions of hydrometeors are also impacted by the limited changes introduced in the microphysical scheme (e.g., the quantitative amount of snow drastically reduced to 0.1–0.2 g kg−1 when the intercept parameter of snow is made independent of temperature). It is noted that the model holds ice at a warmer temperature for a longer time with a temperature-independent intercept parameter. These variations in hydrometeor distribution in the eyewall region of the storm affect diabatic heating and vertical velocity structure and modulated the storm intensity. However, irrespective of the microphysical changes the quantitative amount of graupel hydrometeors remained nearly unaffected. Finally, the indirect effect of microphysical modifications on storm intensity through angular momentum and cloud torques is examined. A formulation to predict the short-term changes in the storm intensity using a parcel segment angular momentum budget method is developed. These results serve to elucidate the indirect impact of microphysical modifications on tropical cyclone intensity changes through modulation in cloud torque magnitude.

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Arindam Chakraborty
,
T. N. Krishnamurti
, and
C. Gnanaseelan

Abstract

This study addresses the issue of cloud parameterization in general circulation models utilizing a twofold approach. Four versions of the Florida State University (FSU) global spectral model (GSM) were used, including four different cloud parameterization schemes in order to construct ensemble forecasts of cloud covers. Next, a superensemble approach was used to combine these model forecasts based on their past performance. It was shown that it is possible to substantially reduce the 1–5-day forecast errors of phase and amplitude of the diurnal cycle of clouds from the use of a multimodel superensemble. Further, the statistical information generated in the construction of a superensemble was used to develop a unified cloud parameterization scheme for a single model. This new cloud scheme, when implemented in the FSU GSM, carried a higher forecast accuracy compared to those of the individual cloud schemes and their ensemble mean for the diurnal cycle of cloud cover up to day 5 of the forecasts. This results in a 5–10 W m−2 improvement in the root-mean-square error to the upward longwave and shortwave flux at the top of the atmosphere, especially over deep convective regions. It is shown that while the multimodel superensemble is still the best product in forecasting the diurnal cycle of clouds, a unified cloud parameterization scheme, implemented in a single model, also provides higher forecast accuracy compared to the individual cloud models. Moreover, since this unified scheme is an integral part of the model, the forecast accuracy of the single model improves in terms of radiative fluxes and thus has greater impacts on weather and climate time scales. This new cloud scheme will be tested in real-time simulations.

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T. N. Krishnamurti
,
H. S. Bedi
,
William Heckley
, and
Kevin Ingles

Abstract

A dynamic relaxation technique is examined to update a spectral model. The technique consists of constraining selected time dependent model variables towards their predetermined space–time estimates, while the remaining variables evolve unconstrained. The scheme involves gradual assimilation of data and thus is essentially free from data insertion shocks generally associated with data assimilation schemes. The scheme can also be used to update the model variables consistent with the observed estimates of diabatic forcings. The spectral formulation is particularly suited to relax the current estimates of model variables towards their observed estimates scale-by-scale.

The scheme has been applied to initialize model variables by relaxing vorticity, divergence and total mass (surface pressure) fields through one to three observation periods using an 11-layer model with T-42 spectral resolution. In addition, the moisture field and diabatic heating rates have been relaxed consistent with the observed estimates of precipitation rates. The explicit two-day Newtonian relaxation of the streamfunction, velocity potential (consistent with rainfall estimates) and the surface pressure and an implicit treatment of the humidity (again consistent with rainfall estimates) results in a realistic initialization. Tropical rainfall, humidity analysis and the divergence field show considerable consistency and improvement. The study addresses the model initialization by this scheme and its impact on medium range forecasts using FGGE IIIb data. The reduction of the spinup time is accomplished by this procedure at the initial time. Globally averaged evaporation and precipitation exhibit an equilibration by this procedure.

A major result of this study is the ability to initialize an observed rainfall field from the use of a reverse Kuo algorithm, the Newtonian relaxation and the overall physical initialization within this model.

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T. N. Krishnamurti
,
M. Subramaniam
,
Glenn Daughenbaugh
,
D. Oosterhof
, and
Jishan Xue

Abstract

This study follows a recent paper on the predictability of low-frequency modes on the time scale of 30–50 days. By filtering out the high-frequency modes, we are able to delay the contamination of low-frequency modes for periods of the order of 1 month in global forecasts. A multilevel global model forecast is carried out to predict a wet spell over central China. It is shown that an initial state consisting of time-mean state, a low-frequency mode, and a specification of the sea surface temperature anomaly provides useful forecasts for the occurrence of dry or wet spells. All of these tests are carried out with a global model; however, only the monsoon region is examined in some detail. This study includes the results of a number of experiments where the sensitivity to the definitions of the mean state, the sea surface temperatures, and initial datasets are explored. The main finding of this paper is that the prediction of monsoonal low-frequency modes and the related dry and wet spells can be extended beyond the usual numerical weather prediction (NWP) predictability limit of 6 or 7 days. It appears that if the contamination from high-frequency modes is suppressed by an initial filtering, then the prediction of low-frequency motion through one cycle, a period of roughly a month, is possible. The forecasts are shown to be quite sensitive to the definition of the initial time-mean state and the sea surface temperature anomaly.

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T. N. Krishnamurti
,
Philip Ardanuy
,
Y. Ramanathan
, and
Richard Pasch

Abstract

In this paper we examine the evolution of the low-level flow over the Arabian Sea during the onset of the summer monsoon. A detailed examination of the onset vortex that forms over the Arabian Sea just prior to the commencement of heavy rains over central India is carried out. The unique aspect of this study is the use of data sets from the Global Atmospheric Research Program (GARP) Monsoon Experiment (MONEX) from a variety of observing platforms. These include winds from geostationary satellites, constant level balloons, dropwindsonde aircraft and an enhanced World Weather Watch network. The data sets were analyzed for a 46-day period from 16 May through 30 June 1979. A number of calculations were performed with this analysis. Of major interest is a finding that the kinetic energy of the zonal flow over the central Arabian Sea increases by an order of magnitude one week prior to the commencement of monsoon rain over central India. This study provides a MONEX time-averaged analysis for the low-level flow which is an update on the well-known Findlater analysis.

A number of calculations show that the horizontal shear of the monsoon current provides substantial energy during the evolution of the onset vortex. The flow satisfies the necessary condition for the existence of instability. Corresponding stability diagrams exhibit substantial growth rates around the period of the formation of the onset vortex. The scale of maximum growth rate is closely in correspondence with the scale of the onset vortex. Finally, the conversion from zonal to eddy kinetic energy is demonstrated via a simple prediction experiment with the conservation of absolute vorticity as a constraint. A reasonable simulation of the onset vortex is shown in this experiment.

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T. N. Krishnamurti
,
K. S. Yap
, and
D. K. Oosterhof

Abstract

This paper examines the medium-range forecast of a typhoon using a global model. The focus of this study is on a comparison of two longwave radiative transfer calculations, one is based on an emissivity formulation while the other utilizes a band model. A more realistic prediction of low clouds in the storm environment by the band model leads to stronger cooling rates and the resulting destabilization contributes to the maintenance of conditional instability. The inflowing air supplies this instability for the maintenance of a longer-lasting storm. The emissivity model fails to predict a sufficient abundance of low clouds resulting in weaker cooling rates hence the resulting destabilization is weak and leads to decay of the storm. The important role of radiatively active shallow clouds in maintaining the conditional instability of the storm environment is illustrated for a long-range integration. An analysis of these aspects of storm environment destabilization is presented in this paper.

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T. N. Krishnamurti
,
John Molinari
,
Hua-lu Pan
, and
Vince Wong

Abstract

In this paper we present many examples (based on 43 years of data) of a phenomenon of downstream amplification over the monsoonal belt. The specific finding here is the following sequence of events: 1) During northern summer pressure drops in the vicinity of the North Vietnam coast (near 20°N) as a typhoon or a tropical storm arrives; 2) during the ensuing week pressure rises over Indochina and Burma by some 5–7 mb; and 3) during the following week a monsoon disturbance forms near the northern part of the Bay of Bengal. On an x-t (or Hovmöller) diagram this sequence of low-high-low formation is similar to the downstream amplification phenomenon of the middle latitudes. The following are some interesting differences: over the middle latitudes the eastward propagating phase velocity is of the order of 10° longitude day−1, while the eastward propagating group velocity (the speed of propagation of the amplification) is around 30° longitude day−1. The tropical counterparts are westward propagating, and the phase and group velocity are, respectively, around 6° and 2° longitude day−1. In meteorological literature one frequently notes reference to in situ formation of monsoon depressions over the northern part of the Bay of Bengal. Our study illustrates the superposition of stationary long waves with progressive short waves, the latter arriving from the western Pacific. This result is contrary to this notion of in situ formation. In this paper we examine some aspects of this slowly westward propagating group velocity phenomenon.

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T. N. Krishnamurti
,
A. K. Mishra
,
A. Chakraborty
, and
M. Rajeevan

Abstract

The availability of daily observed rainfall estimates at a resolution of 0.5° × 0.5° latitude–longitude from a collection of over 2100 rain gauge sites over India provided the possibility for carrying out 5-day precipitation forecasts using a downscaling and a multimodel superensemble methodology. This paper addresses the forecast performances and regional distribution of predicted monsoon rains from the downscaling and from the addition of a multimodel superensemble. The extent of rainfall prediction improvements that arise above those of a current suite of operational models are discussed. The design of two algorithms one for downscaling and the other for the construction of multimodel superensembles are both based on the principle of least squares minimization of errors. That combination is shown to provide a robust forecast product through day 5 of the forecast for regional rains over the Indian monsoon region. The equitable threat scores from the downscaled superensemble over India well exceed those noted from the conventional superensemble and member models at current operational large-scale resolution.

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C. E. Williford
,
R. J. Correa-Torres
, and
T. N. Krishnamurti

Abstract

The Florida State University Global Spectral Model forecast skill is calculated for several tropical systems in the Atlantic and Pacific Ocean basins and is compared to operational forecast skill. The series of forecasts were initialized using global analyses and supplemental satellite data. Track forecast errors were calculated for the storm series for control runs, enhanced runs, and operational forecasts made for the same time periods. Cumulative results for all modeled 1995 hurricanes are summarized.

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