Abstract

This paper addresses the anomaly correlation of the 500-hPa geopotential heights from a suite of global multimodels and from a model-weighted ensemble mean called the superensemble. This procedure follows a number of current studies on weather and seasonal climate forecasting that are being pursued. This study includes a slightly different procedure from that used in other current experimental forecasts for other variables. Here a superensemble for the ∇² of the geopotential based on the daily forecasts of the geopotential fields at the 500-hPa level is constructed. The geopotential of the superensemble is recovered from the solution of the Poisson equation. This procedure appears to improve the skill for those scales where the variance of the geopotential is large and contributes to a marked improvement in the skill of the anomaly correlation. Especially large improvements over the Southern Hemisphere are noted. Consistent day-6 forecast skill above 0.80 is achieved on a day to day basis. The superensemble skills are higher than those of the best model and the ensemble mean. For days 1–6 the percent improvement in anomaly correlations of the superensemble over the best model are 0.3, 0.8, 2.25, 4.75, 8.6, and 14.6, respectively, for the Northern Hemisphere. The corresponding numbers for the Southern Hemisphere are 1.12, 1.66, 2.69, 4.48, 7.11, and 12.17. Major improvement of anomaly correlation skills is realized by the superensemble at days 5 and 6 of forecasts. The collective regional strengths of the member models, which is reflected in the proposed superensemble, provide a useful consensus product that may be useful for future operational guidance.

Abstract

Many frost events over southeastern Brazil are accompanied by a large-amplitude upper trough of the middle latitudes that extends well into the Tropics. This paper first illustrates that a mechanism of downstream amplification across the Pacific into South America is generally accompanied in these situations. This is manifested by troughs and ridges that propagate eastward. An analysis of these situations during frost events shows that these features of downstream amplification, illustrated on a Hovmöller (x–t) plot, can be decomposed into a family of synoptic-scale waves that propagate eastward and a family of planetary-scale waves that acquire a quasi-stationary character during the freeze event. It is shown that a global model, at a resolution of 70 km, can be used to predict these features on the decomposition of scales during freeze events. It became apparent from these features that the growth of the long stationary waves during the freeze events may be due to scale interaction among wave components. This paper discusses the nature of these scale interactions, calculated from the energetics in the wavenumber domain, for periods before, during, and after the freeze events. The salient results are that nonlinear barotropic-scale interactions are an important source for the maintenance of the downstream amplification; however, the baroclinic (in scale) contributions dominate through the life cycle of the downstream amplitude where the large-amplitude troughs are indeed accompanied by baroclinic features. Finally, it is shown that a very high resolution regional spectral model can be used to handle the local aspects of the freeze events. This study offers the possibility for designing prediction experiments on the medium-range timescales for the forecast of these frost events.

Abstract

This study addresses observational and modeling sensitivity on the march of the onset isochrones of the Indian summer monsoon. The first 25 days of the passage of the isochrones of monsoon onset is of great scientific interest. Surface and satellite-based datasets are used for high-resolution modeling of the impact of the motion of the onset isochrones from Kerala to New Delhi. These include the asymmetries across the isochrone such as soil moisture and its temporal variability, moistening of the dry soil to the immediate north of the isochrone by nonconvective anvil rains, and formation of newly forming cloud elements to the immediate north of the isochrone. The region immediately north of the isochrone is shown to carry a spread of buoyancy elements. As these new elements grow, they are continually being steered by the divergent circulations of the parent isochrone to the north and eventually to the northwest. CloudSat was extremely useful for identifying the asymmetric cloud structures across the isochrone. In the modeling sensitivity studies, the authors used a mesoscale Advanced Research Weather Research and Forecasting Model (ARW-WRF) to examine days 1–25 of forecasts of the onset isochrone. Prediction experiments were first modeled during normal, dry, and wet Indian monsoons using default values of model parameters. This study was extended to determine the effects of changes in soil moisture and nonconvective rain parameterizations (the parameters suggested by the satellite observations). These sensitivity experiments show that the motion of the isochrones from Kerala to New Delhi are very sensitive to the parameterization of soil moisture and nonconvective anvil rains immediately north of the isochrone.

Abstract

In this paper the performance of a multimodel ensemble forecast analysis that shows superior forecast skills is illustrated and compared to all individual models used. The model comparisons include global weather, hurricane track and intensity forecasts, and seasonal climate simulations. The performance improvements are completely attributed to the collective information of all models used in the statistical algorithm.

The proposed concept is first illustrated for a low-order spectral model from which the multimodels and a “nature run” were constructed. Two hundred time units are divided into a training period (70 time units) and a forecast period (130 time units). The multimodel forecasts and the observed fields (the nature run) during the training period are subjected to a simple linear multiple regression to derive the statistical weights for the member models. The multimodel forecasts, generated for the next 130 forecast units, outperform all the individual models. This procedure was deployed for the multimodel forecasts of global weather, multiseasonal climate simulations, and hurricane track and intensity forecasts. For each type an improvement of the multimodel analysis is demonstrated and compared to the performance of the individual models. Seasonal and multiseasonal simulations demonstrate a major success of this approach for the atmospheric general circulation models where the sea surface temperatures and the sea ice are prescribed. In many instances, a major improvement in skill over the best models is noted.

Abstract

This study is based on a global coupled atmosphere–ocean model climate prediction that was designed to include 14 layers over the atmosphere and 17 layers within the ocean. In this model an 11-yr data assimilation includes physical initialization of the daily rainfall estimates. No flux corrections are included in the seasonal and annual forecasts of this coupled model. It is first shown that intraseasonal oscillation on the Madden–Julian timescale was an important feature during the onset of the El Niño of 1997. It is shown that this feature is retained in the model’s data assimilation and in the forecasts. The forecasts commence on 1 April 1997. The model forecasts showed an El Niño warming of the equatorial Pacific Ocean waters commencing with the excitation of a Kelvin wave. The Niño-3.4 region acquired above-normal sea surface temperature anomalies (SSTAs) by 15 May. The warm SSTs reached a peak by around January 1998. The El Niño made its demise by June 1998. The life cycle of the entire SSTA shows remarkable agreement to the observed anomalies over the Pacific Ocean. The subsurface temperature anomalies exhibit eastward propagating subsurface warm and cold water that are in phase with the El Niño and the La Niña features at the surface. Phenomenologically, this study is quite successful in showing the following.

• Velocity potential anomalies at the 200-hPa level are good indicators for long-lasting dry spells. In particular the authors have remarkable success in predicting the long-lasting dry spell over Florida (which resulted in major fires over Florida during June 1998, some 14 months into the forecast) and over Indonesia (which resulted in major fires over Indonesia during September and October 1997). This was by far the most promising result of the coupled modeling study. This study also enumerates several areas of the climate of 1997–98 that were not reasonably simulated at the present resolution of the coupled model. The model does not exhibit very high skill in prediction of precipitation anomalies over the Asian–Australian monsoon world, which is most likely due to the resolution and organization of convection issues.

• A realistic picture is shown of the North American monsoon system (the Mexico–Arizona monsoon) with wet conditions along 110°W, dry conditions along 95°W, and wet conditions along 80°W during the summers of 1997 and 1998. Furthermore, the model successfully shows a stronger North American monsoon system during the post–El Niño year 1998 compared to the El Niño year 1997. This is in accordance with the climatological and observational findings.

• California rainfall during January and February 1998, arising from the eastward passage of disturbances from the Pacific Ocean, was successfully simulated, although the rainfall amounts at the model resolution were roughly one-third of the observed peak estimates.

Abstract

Our collective understanding of azimuthally asymmetric features within the coherent structure of a tropical cyclone (TC) continues to improve with the availability of more detailed observations and high-resolution model outputs. However, a precise understanding of how these asymmetries impact TC intensity changes is lacking. Prior attempts at investigating the asymmetric impacts follow a mean–eddy partitioning that condenses the effect of all the asymmetries into one term and fails to highlight the differences in the role of asymmetries at different scales. In this study, we present a novel energetics-based approach to analyze the asymmetric impacts at multiple length scales during periods of rapid intensity changes. Using model outputs of TCs under low and high shear, we compute the different energy pathways that enhance/suppress the growth of multiscale asymmetries in the wavenumber (WN) domain. We then compare and contrast the energetics of the mean-flow field (WN 0) with that of the persistent, coherent vortex-scale asymmetric structures (WNs 1 and 2) and the more local, transient, sub-vortex-scale asymmetries (WNs ≥ 3). We find in our case studies that the dominant mechanisms of growth/decay of the asymmetries are the baroclinic conversion from available potential to kinetic energy at individual scales of asymmetries and the transactions of kinetic energy between the asymmetries of various length scales, rather than the barotropic mean–eddy transactions as is typically assumed. Our case study analysis further shows that the growth/decay of asymmetries is largely independent of the mean. Certain aspects of eddy energetics can potentially serve as early-warning indicators of TC rapid intensity changes.

Abstract

This paper addresses real-time precipitation forecasts from a multianalysis–multimodel superensemble. The methodology for the construction of the superensemble forecasts follows previous recent publications on this topic. This study includes forecasts from multimodels of a number of global operational centers. A multianalysis component based on the Florida State University (FSU) global spectral model that utilizes TRMM and SSM/I datasets and a number of rain-rate algorithms is also included. The difference in the analysis arises from the use of these rain rates within physical initialization that produces distinct differences among these components in the divergence, heating, moisture, and rain-rate descriptions. A total of 11 models, of which 5 represent global operational models and 6 represent multianalysis forecasts from the FSU model initialized by different rain-rate algorithms, are included in the multianalysis–multimodel system studied here. In this paper, “multimodel” refers to different models whose forecasts are being assimilated for the construction of the superensemble. “Multianalysis” refers to different initial analysis contributing to forecasts from the same model. The term superensemble is being used here to denote the bias-corrected forecasts based on the products derived from the multimodel and the multianalysis. The training period is covered by nearly 120 forecast experiments prior to 1 January 2000 for each of the multimodels. These are all 3-day forecasts. The statistical bias of the models is determined from multiple linear regression of these forecasts against a “best” rainfall analysis field that is based on TRMM and SSM/I datasets and using the rain-rate algorithms recently developed at NASA Goddard Space Flight Center. This paper discusses the results of real-time rainfall forecasts based on this system. The main results of this study are that the multianalysis–multimodel superensemble has a much higher skill than the participating member models. The skill of this system is higher than those of the ensemble mean that assigns a weight of 1.0 to all including the poorer models and the ensemble mean of bias-removed individual models. The selective weights for the entire multianalysis–multimodel superensemble forecast system make it superior to individual models and the above mean representations. The skill of precipitation forecasts is addressed in several ways. The skill of the superensemble-based rain rates is shown to be higher than the following: (a) individual model's skills with and without physical initialization, (b) skill of the ensemble mean, and (c) skill of the ensemble mean of individually bias-removed models.

The equitable-threat scores at many thresholds of rain are also examined for the various models and noted that for days 1–3 of forecasts, the superensemble-based forecasts do have the highest skills. The training phase is a major component of the superensemble. Issues on optimizing the number of training days is addressed by examining training with days of high forecast skill versus training with low forecast skill, and training with the best available rain-rate datasets versus those from poor representations of rain. Finally the usefulness of superensemble forecasts of rain for providing possible guidance for flood events such as the one over Mozambique during February 2000 is shown.

The deployment of a space-based Doppler lidar would provide information that is fundamental to advancing the understanding and prediction of weather and climate.

This paper reviews the concepts of wind measurement by Doppler lidar, highlights the results of some observing system simulation experiments with lidar winds, and discusses the important advances in earth system science anticipated with lidar winds.

Observing system simulation experiments, conducted using two different general circulation models, have shown 1) that there is a significant improvement in the forecast accuracy over the Southern Hemisphere and tropical oceans resulting from the assimilation of simulated satellite wind data, and 2) that wind data are significantly more effective than temperature or moisture data in controlling analysis error. Because accurate wind observations are currently almost entirely unavailable for the vast majority of tropical cyclones worldwide, lidar winds have the potential to substantially improve tropical cyclone forecasts. Similarly, to improve water vapor flux divergence calculations, a direct measure of the ageostrophic wind is needed since the present level of uncertainty cannot be reduced with better temperature and moisture soundings alone.

Abstract

The Lidar Atmospheric Sensing Experiment (LASE) on board the NASA DC-8 measured high-resolution profiles of water vapor and aerosols, and cloud distributions in 14 flights over the eastern North Atlantic during the NASA African Monsoon Multidisciplinary Analyses (NAMMA) field experiment. These measurements were used to study African easterly waves (AEWs), tropical cyclones (TCs), and the Saharan air layer (SAL). These LASE measurements represent the first simultaneous water vapor and aerosol lidar measurements to study the SAL and its interactions with AEWs and TCs. Three case studies were selected for detailed analysis: (i) a stratified SAL, with fine structure and layering (unlike a well-mixed SAL), (ii) a SAL with high relative humidity (RH), and (iii) an AEW surrounded by SAL dry air intrusions. Profile measurements of aerosol scattering ratios, aerosol extinction coefficients, aerosol optical thickness, water vapor mixing ratios, RH, and temperature are presented to illustrate their characteristics in the SAL, convection, and clear air regions. LASE extinction-to-backscatter ratios for the dust layers varied from 35 ± 5 to 45 ± 5 sr, well within the range of values determined by other lidar systems. LASE aerosol extinction and water vapor profiles are validated by comparison with onboard in situ aerosol measurements and GPS dropsonde water vapor soundings, respectively. An analysis of LASE data suggests that the SAL suppresses low-altitude convection. Midlevel convection associated with the AEW and transport are likely responsible for high water vapor content observed in the southern regions of the SAL on 20 August 2008. This interaction is responsible for the transfer of about 7 × 10¹⁵ J (or 8 × 10³ J m⁻²) latent heat energy within a day to the SAL. Initial modeling studies that used LASE water vapor profiles show sensitivity to and improvements in model forecasts of an AEW.

Rainfall is a fundamental process within the Earth's hydrological cycle because it represents a principal forcing term in surface water budgets, while its energetics corollary, latent heating, is the principal source of atmospheric diabatic heating well into the middle latitudes. Latent heat production itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The properties of the vertical distribution of latent heat release modulate large-scale meridional and zonal circulations within the Tropics, as well as modify the energetic efficiencies of midlatitude weather systems.

This paper highlights the retrieval of latent heating from satellite measurements generated by the Tropical Rainfall Measuring Mission (TRMM) satellite observatory, which was launched in November 1997 as a joint American–Japanese space endeavor. Since then, TRMM measurements have been providing credible four-dimensional accounts of rainfall over the global Tropics and subtropics, information that can be used to estimate the space–time structure of latent heating across the Earth's low latitudes.

A set of algorithm methodologies for estimating latent heating based on precipitation-rate profile retrievals obtained from TRMM measurements has been under continuous development since the advent of the mission s research program. These algorithms are briefly described, followed by a discussion of the latent heating products that they generate. The paper then provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, concluding with remarks intended to stimulate further research on latent heating retrieval from satellites.