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Gregory J. Tripoli
and
T. N. Krishnamurti

Abstract

An assimilation of satellite low-cloud vector data and conventional meteorological data is presented in this paper. The domain of the study is the GATE A-scale area. The period is the summer months of 1972. Objective analysis of the data for 93 individual days was carried out for this entire domain. One of the important climatological findings of this study is the presence of a velocity maximum in the southeast trades along the Brazilian coast. Mean speeds for three months exceed 10 m/s in this region; daily values occasionally are as large as 25 m/s. Besides showing the monthly mean motion field, we have examined in detail one-level barotropic energy exchanges and fluxes in the GATE A-scale domain. The number of conventional plus non-conventional wind observations are about 400 per day. This is more than has been used in most previous studies. Some of these results of the energetics, especially with regards to the period when Hurricane Agnes formed, are thus of considerable interest.

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Arindam Chakraborty
and
T. N. Krishnamurti

Abstract

This study addresses seasonal forecasts of rains over India using the following components: high-resolution rain gauge–based rainfall data covering the years 1987–2001, rain-rate initialization, four global atmosphere–ocean coupled models, a regional downscaling of the multimodel forecasts, and a multimodel superensemble that includes a training and a forecast phase at the high resolution over the internal India domain. The results of monthly and seasonal forecasts of rains for the member models and for the superensemble are presented here. The main findings, assessed via the use of RMS error, anomaly correlation, equitable threat score, and ranked probability skill score, are (i) high forecast skills for the downscaled superensemble-based seasonal forecasts compared to the forecasts from the direct use of large-scale model forecasts were possible; (ii) very high scores for rainfall forecasts have been noted separately for dry and wet years, for different regions over India and especially for heavier rains in excess of 15 mm day−1; and (iii) the superensemble forecast skills exceed that of the benchmark observed climatology. The availability of reliable measures of high-resolution rain gauge–based rainfall was central for this study. Overall, the proposed algorithms, added together, show very promising results for the prediction of monsoon rains on the seasonal time scale.

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Z. Zhang
and
T. N. Krishnamurti

Abstract

This study illustrates the capability of the ensemble technique to improve hurricane forecasts in the Florida State University Global Spectral Model. A perturbation method for hurricane ensemble prediction is proposed. The perturbation method consists of perturbing hurricane initial position and the large-scale environment in which the storm is embedded. The position perturbation is done by displacing the observed hurricane toward different directions by a small distance. The empirical orthogonal function (EOF) analysis is used to find fast-growing modes in the initial state. It is shown that the model forecasts, in terms of both hurricane track and other physical variables, are very sensitive to the hurricane initial position, intensity, and its large-scale environment. The results also show the EOF-based perturbations are the fast-growing modes and can be used to reduce the initial uncertainty in the analysis.

The hurricane forecast obtained from ensemble statistics lead to a large improvement in the track forecasts. For the intensity forecasts, the ensemble prediction provides several statistical methods to display the forecasts. The statistical mean from individual ensemble members provide an overview of the forecast. The spatial distribution of the probability of predicted variables make it possible to find the most likely weather pattern.

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David R. Bachiochi
and
T. N. Krishnamurti

Abstract

An empirical planetary boundary layer cloud parameterization has been developed for The Florida State University coupled ocean–atmosphere model to improve low-level clouds in the model. The scheme diagnoses the clouds by combining the PBL depth, ground wetness, and the relative humidity. Winter and summer simulations between 1987 and 1989 suggest an improvement in the low cloud representation compared to the International Satellite Cloud Climatology Project analysis. When implemented in the model, this parameterization results in positive impacts on shortwave fluxes and low-level circulation, particularly along the west coasts of the North and South American continents. Enhanced mechanical forcing at the ocean surface improves the SST representation in the eastern Pacific Ocean basin. Warm versus cold phase ENSO variability of the east Pacific SSTs are also improved during the seasonal simulations. Furthermore, the near-coast diurnal fluctuation of the low cloud is comparable to observations.

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T. N. Krishnamurti
and
C. M. Kishtawal

Abstract

A pronounced continental-scale diurnal mode of the Asian summer monsoon is mapped using data from recent satellites Meteosat-5 and TRMM. These datasets were available at high temporal resolutions. A result that stands out is the diurnal divergent circulation that in the afternoon hours has an ascending lobe over north-central India and has a descending lobe that reaches out radially toward central China, the southern part of China, the equatorial Indian Ocean, and the western Arabian Sea. The reverse circulation is clearly seen during the early morning hours. This diurnal pulsation of continental-scale divergent circulation appears to be an integral part of the monsoon. Another finding relates to the diurnal slowing down and speeding up of the Tibetan high circulations, especially in the southern flanks where the tropical easterly jet resides and exhibits a pulsation of intensity. The amplitude of pulsation was found to reach up to 7 m s−1. Thus this continental-scale change appears to be a pronounced feature. The phase and amplitude of various satellite datasets derived from the 90-min datasets are also displayed to confirm this major mode, that is, the diurnal oscillation of monsoon.

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Arindam Chakraborty
and
T. N. Krishnamurti

Abstract

Several modeling studies have shown that the south Asian monsoon region has the lowest skill for seasonal forecasts compared with many other domains of the world. This paper demonstrates that a multimodel synthetic superensemble approach, when constructed with any set of coupled atmosphere–ocean models, can provide improved skill in seasonal climate prediction compared with single-member models or their ensemble mean for the south Asian summer monsoon region. However, performance of the superensemble tends to improve when a better set of input member models are used. As many as 13 state-of-the-art coupled atmosphere–ocean models were used in the synthetic superensemble algorithm. The merit of this technique lies in assigning differential weights to the member models. The rms errors, anomaly correlations, case studies of extreme events, and probabilistic skill scores are used here to assess these forecast skills. It was found that over the south Asian region the seasonal forecasts from the superensemble are, in general, superior to the forecasts of the individual member models, and their bias-removed ensemble mean at a significance level of 95% or more (based on a Student's t test) during the 13 yr of forecasts. Moreover, the skill of the superensemble was found to be better than those of the ensemble mean over smaller domains as well as during extreme events that were monitored, especially during the switch on and off of the Indian Ocean dipole, which seems to modulate the Indian monsoon rainfall. The results of this paper suggest that the superensemble provides somewhat consistent forecasts on the seasonal time scale. This methodology needs to be tested for real-time seasonal climate forecasting over the south Asian region.

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Robert S. Ross
and
T. N. Krishnamurti

Abstract

This paper provides new information on the low-level (850 hPa) structure and behavior of African easterly waves (AEWs) and relates this information to previous studies. Individual AEWs that occurred during June–September of 2001 are studied by a synoptic approach that employs Hovmöller diagrams, wave track maps, and case studies. The focus is on two AEW regimes in the lower troposphere over North Africa: a dry regime to the north of the African easterly jet (AEJ) coincident with the surface position of the monsoon trough near 20°N, and a wet regime to the south of the jet coincident with the near-equatorial rainbelt near 10°N. The following issues are addressed: the origin of the waves seen in the two wave regimes, relation of the wave activity to the mean positions of the surface monsoon trough and the 600–700-hPa AEJ, collocation of the tracks of the two wave regimes off the African coast, and diversity in low-level wave behavior that includes merging, splitting, and dissipation of the cyclonic vorticity centers associated with the wave troughs. The relationship between the waves following the two tracks is examined as well as the relationship between the low-level wave activity and Atlantic tropical cyclogenesis in 2001. It is shown that the two wave regimes can interact, and that both regimes were instrumental in Atlantic tropical cyclogenesis in 2001.

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T. N. Krishnamurti
,
D. Oosterhof
, and
Nancy Dignon

Abstract

A global spectral model is used to carry out a number of short to medium range prediction experiments with global datasets. The primary objective of these studies is to examine the formation and motion of the hurricanes/typhoons with a fairly comprehensive state-of-the-art global model. Ale spectral model utilizes the usual transform method for the calculations of the nonlinear and physical processes. The physical processes include parameterizations of the planetary boundary layer, deep and shallow cumulus convection, radiative processes (including cloud feedback processes, diurnal change and surface energy balance) and large-scale condensation. ‘Envelope orography’ is used to represent steep mountains globally. Ocean temperatures are prescribed from a Preceding 10 day averaged dataset for the storm periods under investigation.

Sensitivity of storm forecasts to horizontal and vertical resolutions, datasets and representation of physical processes are addressed in this paper.

The major findings of this study are that improved results on the formation and motion of storms are achieved in several cases when (i) the surface layer fluxes are adequately resolved, (ii) the final FGGE analyzed datasets are used, (iii) very high resolution in the horizontal (106 waves triangular truncation) is used, and (iv) improved physical parameterization for the boundary layer, cumulus convection and radiative process are included.

The major limitation of this study is that in spite of the use of very high resolution the inner rain area (radius<150 km from the storm center) is not adequately represented to describe the central pressure, maximum wind and the warm core of hurricanes. Further studies to improve these areas are suggested.

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T. N. Krishnamurti
,
Simon Low-Nam
, and
Richard Pasch

Abstract

In the various formulations of Kuo (1965, 1974) type cumulus parameterization schemes, the moistening and heating by the cumulus are made proportional to the humidity and temperature differences between a model cloud and its environment. The constants of proportionality that differentiate the various versions of the Kuo's schemes are based on different closure assumptions. The proportion of available moisture supply that goes into the moistening by cumulus convection usually determines these constants. It is possible to diagnostically calculate the observed (or what might be called the exact) measures of these constants of proportionality. This enables one to define an ultimate Kuo scheme where the vertical integrals of the heating and moistening are exactly known but the vertical distributions are limited by the aforementioned structure functions. This ultimate Kuo scheme is not a prognostic scheme, but it serves as a benchmark in defining how far one can progress with this type of scheme in the prognostic sense. Using the final validated GATE B-scale data sets a comparison is made between the observed vertical distributions of the apparent heat source and apparent moisture sink (obtained from direct substitutions of observed data) with the ultimate Kuo scheme to assess its scope. Comparison of Kuo (1965, 1974) type schemes is next carried out with the ultimate Kuo scheme to address their limitations.

A proposal for a mesoscale convergence parameter η and a moistening parameter b is made to overcome some of the limitations of the above schemes. Here a multiple regression search of large-scale parameters, using 72 map times of data, is carried out to determine these parameters via least-square minimization of errors. These are next used to determine the vertical structure of moistening and heating, for a semi-prognostic formulation. The results show that by using the vertical average of the large-scale upward vertical motion and the lower tropospheric relative vorticity in the multiple regression, it is possible to attain an accuracy close to that prescribed by the ultimate Kuo scheme. Detailed results on the vertical distributions of the heating and moistening and the rainfall rates for the entire third phase of GATE are presented in this paper.

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

Abstract

Modeling the geographical distribution of the phase and amplitude of the diurnal change is a challenging problem. This paper addresses the issues of modeling the diurnal mode of precipitation over the Tropics. Largely an early morning precipitation maximum over the oceans and an afternoon rainfall maximum over land areas describe the first-order diurnal variability. However, large variability in phase and amplitude prevails even within the land and oceanic areas. This paper addresses the importance of a multimodel superensemble for much improved prediction of the diurnal mode as compared to what is possible from individual models. To begin this exercise, the skills of the member models, the ensemble mean of the member models, a unified cloud model, and the superensemble for the prediction of total rain as well as its day versus night distribution were examined. Here it is shown that the distributions of total rain over the earth (tropical belt) and over certain geographical regions are predicted reasonably well (RMSE less than 18%) from the construction of a multimodel superensemble. This dataset is well suited for addressing the diurnal change. The large errors in phase of the diurnal modes in individual models usually stem from numerous physical processes such as the cloud radiation, shallow and deep cumulus convection, and the physics of the planetary boundary layer. The multimodel superensemble is designed to reduce such systematic errors and provide meaningful forecasts. That application for the diurnal mode appears very promising. This paper examines some of the regions such as the Tibetan Plateau, the eastern foothills of the Himalayas, and the Amazon region of South America that are traditionally difficult for modeling the diurnal change. In nearly all of these regions, errors in phase and amplitude of the diurnal mode of precipitation increase with the increased length of forecasts. Model forecast errors on the order of 6–12 h for phase and 50% for the amplitude are often seen from the member models. The multimodel superensemble reduces these errors and provides a close match (RMSE < 6 h) to the observed phase. The percent of daily rain and their phases obtained from the multimodel superensemble at 3-hourly intervals for different regions of the Tropics showed a closer match (pattern correlation about 0.4) with the satellite estimates. This is another area where the individual member models conveyed a much lower skill.

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