Abstract

Our success with environmental prediction could be considered among humankind’s most remarkable developments over the past 50 years. It protects lives and property, and helps us advance the well-being of society. Vast changes have occurred recently to the complexity and scope of our weather enterprise. Given its importance to society, there is reason to optimize our approaches for advancing its scope and capabilities. This essay highlights three points that may help facilitate this optimization, with an overarching suggestion to more overtly embrace a systems (engineering) approach. 1) Continued emphasis should be placed on advancing Earth system science as the foundational knowledge that advances weather prediction as well as the more holistic scope of environmental prediction (EP). 2) The complexity and coupling of the social, programmatic, observation, modeling, analytic, and interdisciplinary landscapes within the EP enterprise suggest adding a system engineering perspective/approach to further optimize outcomes and limit vulnerabilities. 3) The consideration of the enterprise as a data to information flow problem highlights opportunities and focal points to leverage that could help to advance the societal benefits derived from the EP enterprise. A generalized, highly simplified systems perspective on the advancement of Earth science and environmental prediction is offered by framing a simple equation involving the synthesis of observations, models, and programmatics that in turn yield science and applications benefits. Simplifications and derivatives of this equation are used to distill challenges and opportunities for further advancing enterprise benefits and to motivate considerations of scope and priorities related to our community’s decadal survey(s).

Abstract

The present study composites atmosphere and ocean conditions associated with ocean hot spots. Ocean hot spots are defined as regions where SST exceeds 29.75°C and that have an area greater than 1 × 10⁶ km². The composite atmosphere includes surface flux parameters, deep convection and cloud amounts, cloud radiative forcing, and analysis fields from the National Meteorological Center (NMC) and European Centre for Medium-Range Weather Forecasts weather forecasting systems. The composite ocean includes sea level height and the temperature and velocity structures down to 720 m from the NMC ocean forecasting system. These fields are composited for the months before, during, and after the appearance of hot spots in order to develop a four-dimensional picture of the atmosphere and ocean conditions that are associated with the formation and the decay of these very high ocean surface temperatures.

The analysis indicates that the formation of these hot spots is largely confined to the region within the 28°C isotherm of the long-term mean SST, with greatest concentrations occurring in the western Pacific warm pool. Extended analysis of the warm-pool hot spots (0°–10°S, 156°–176°W) indicates strong influences from interannual, annual, and 30–60 day timescales, with La Niña conditions appearing to inhibit formation, southern summer favoring formation, and the descending (ascending) phase of the Madden–Julian oscillation (MJO) favoring formation (decay). This interaction with the MJO indicates how internal, or remotely forced, atmospheric variability, in addition to local feedbacks, may he playing a role to help limit SST. Furthermore, the out-of-phase relationship between SST and deep convection associated with this variability suggests the possibility of a positive feedback mechanism for the MJO. With respect to the surface heat budget, the data indicate that during the hot spot evolution, the convective perturbations to the surface shortwave exceed those for evaporation by at least a factor of 2.

The composite ocean conditions indicate that the rapidly varying atmospheric conditions associated with the hot spot evolution induce significant changes below the surface layer of the ocean as well. These changes appear to be primarily linked to the onset of westerly wind bursts associated with the enhanced deep convection. Removing the El Niño time periods from the composites indicates that the composite mean is more dependent on the interannual state than the composite atmosphere. These results indicate that the ocean should not be rendered too simple with respect to understanding the limiting mechanisms of high SST.

Abstract

The objective of this study is to examine the impacts from satellite equatorial crossing time (ECT) changes on the outgoing longwave radiation (OLR) and highly reflective cloud (HRC) datasets and to design appropriate and robust methods to remove these satellite-dependent biases. The OLR record covers the period from June 1974 to July 1996 and is on a 2.5° grid extending from 30°S to 30°N over the global Tropics. The HRC record covers the period from January 1971 to December 1987 and is on a 2° grid extending from 25°S to 25°N over the global Tropics. Rotated empirical orthogonal function analysis (REOF) is performed on both the monthly OLR and HRC anomalies to help distinguish between artificial modes of variability and those associated with real variability.

Results from the analysis show that significant errors are introduced by changes in the satellite ECT, and they appear differently in the two datasets. The primary satellite-related bias in the OLR appears as the fourth REOF mode, which accounts for 4.4% of the OLR anomaly variance. Its spatial pattern exhibits a strong surface signature over land, with the opposite sign over many of the deep convective regions of the ocean. During some periods, these biases result in widespread errors of over 10 W m⁻², which are sustained for several months to over a year. In other cases, the transition between satellites induces abrupt, artificial changes in the OLR as high as 16 W m⁻². In the HRC, the satellite-related bias appears as the leading two REOF modes, which account for 13.1% of the HRC anomaly variance. The spatial patterns of the HRC biases are indicative of an overall change in the mean climatological convection pattern. The above results can be understood by considering the sampling and radiometric characteristics of the OLR and HRC datasets.

To remove the satellite ECT biases, the REOF time series of the satellite-related modes are modified by using the detailed knowledge of the satellite ECTs so that only artificial variability related to the satellite changes is captured and the natural variability is excluded. These modified time series are used in conjunction with their associated spatial patterns to compute the satellite-related artificial variability, which is then removed from the two datasets. These datasets provide an improved resource to study intraseasonal and longer timescale regional climate variations, large-scale interannual variability, and global-scale climate trends. Analyses of the long-term trends in both datasets show that the satellite biases induce artificial trends in the data and that these artificial trends are reduced in the corrected datasets. Further, each of the corrected datasets exhibits a trend in the tropical western-central Pacific that appears spatially independent of the satellite biases and agrees with results of previous studies that indicate an increase in precipitation has occurred in this region over the period encompassed by these datasets.

Abstract

The Madden–Julian oscillation (MJO) is the dominant form of intraseasonal variability in the Tropics. In previous studies, intraseasonal variability has usually been characterized in terms of wind or convection anomalies, while the structure of MJO-related moisture variations has been greatly unexplored. This work focuses on the behavior of moisture and related hydrological fields associated with MJO events during Northern Hemisphere winter. Five-day averaged (1979–99) Television Infrared Observational Satellite (TIROS) Operational Vertical Sounder (TOVS) moisture soundings from the NASA Pathfinder data were used, providing global coverage at specific pressure levels. The TOVS moisture, as well as the International Satellite Cloud Climatology Project (ISCCP) cloud fraction anomaly data, were composited based on MJO events selected via an index constructed from Xie–Arkin bandpassed pentad rainfall data. Analysis of the three-dimensional structure and evolution of precipitation, water vapor, and clouds over the life cycle of the MJO shows a rich set of relationships between the variables.

The composite evolution of moisture shows markedly different vertical structures as a function of longitude. There is a clear westward tilt with the height of the moisture maximum associated with MJO disturbances propagating eastward across the Indian Ocean. These disturbances evolve into nearly vertically uniform moist anomalies as they reach the western Pacific. Near-surface (≥850 mb) water vapor leads precipitation by 1 pentad over the Indian Ocean and western Pacific. Upper-level water vapor lags the peak in precipitation by 1–2 pentads, as the upper troposphere is moistened following intense convection. In the eastern Pacific, the moisture variations then become confined to the lower levels (<∼700 mb), with upper-level water vapor nearly out of phase. ISCCP total cloud fraction is highly correlated with humidity, and also leads observed precipitation. There is a longitudinal displacement between the maxima in rainfall and the maxima in cloud fraction, with higher cloudiness at the (western) trailing edges of the rainfall maxima. The cloud-top heights also show consistent changes over the course of the composite MJO life cycle, with an increasing (decreasing) strength of middle (high) cloud variations as the disturbances propagate eastward to the western Pacific.

Averaged over all phases of the MJO, dry anomalies dominate over moist anomalies that occur in the active phase of the disturbance. The bias toward dry anomalies is strongest between 15°N and 15°S in the Western Hemisphere and suggests a low-frequency rectification of intraseasonal variability onto the mean background moisture state of the atmosphere.

Abstract

This paper presents fundamental climatological characteristics of the intertropical convergence zone (ITCZ) in a simple concise manner using the highly reflective cloud (HRC) dataset. This satellite-derived dataset uses both visible and infrared observations to measure the frequency of occurrence of large-scale convective systems over the global tropics at a 1° spatial resolution. These dataset characteristics make the HRC particularly well suited for climatological analysis of the ITCZ because the dataset is based on estimates of organized deep convective cloud systems rather than observations of clouds as a whole, and it provides the spatial resolution needed to identify thew large-wale convective structures. Furthermore, the dataset covers a time period extending nearly two decades, which provides for a fairly robust climatology and the opportunity to examine seasonal and interannual variability of both the convection and the latitude of the ITCZ.

Abstract

In this study, evidence of the strong modulation of the convectively coupled Kelvin wave (CCKW) activity by the Madden–Julian oscillation (MJO) is presented, with a particular focus over the South America and tropical Atlantic region. The MJO impacts on CCKWs over this region, as noted in anomalous fields of rainfall as well as vertical profiles of wind, moisture, and temperature, are primarily through the modulation of Kelvin wave amplitude, with secondary effects on vertical structure, and little impact on wavenumber. CCKW activity is enhanced during MJO phases 8, 1, and 2 and damped during MJO phases 4, 5, and 6.

Further analyses reveal that the strong modulation of the MJO on the CCKW activity could be largely through two factors: namely, the vertical zonal wind shear and the lower- to middle-tropospheric specific humidity. The CCKW activity tends to be enhanced during MJO phases when the easterly vertical wind shear and positive low- to midtroposphere moisture anomalies are present and vice versa. These two physical processes associated with the MJO are found to have positively (negatively) reinforcing influences on the CCKW activity in phase 1 (4 and 5), while counteracting influences in phases 2, 3, 6, 7, and 8, leading to the observed MJO cycle of the CCKW activity anomalies in the study region. The results presented in this study may have important implications for extended-range prediction of tropical wave activity and might suggest possible roles of the upstream CCKWs in the initiation of the MJO in the western Indian Ocean.

Abstract

This study illustrates that observed modulations of tropical cyclone (TC) genesis over the eastern Pacific (EPAC) by large-scale intraseasonal variability (ISV) are well represented in a recently developed high-resolution atmospheric model (HiRAM) at the NOAA/Geophysical Fluid Dynamics Laboratory (GFDL) with a horizontal resolution of about 50 km. Considering the intrinsic predictability of the ISV of 2–4 weeks, this analysis thus has significant implications for dynamically based TC predictions on intraseasonal time scales. Analysis indicates that the genesis potential index (GPI) anomalies associated with the ISV can generally well depict ISV modulations of EPAC TC genesis in both observations and HiRAM simulations. Further investigation is conducted to explore the key factors associated with ISV modulation of TC activity based on an analysis of budget terms of the observed GPI during the ISV life cycle. It is found that, while relative roles of GPI factors are dependent on ISV phase and location, lower-level cyclonic vorticity, enhanced midlevel relative humidity, and reduced vertical wind shear can all contribute to the observed active TC genesis over the EPAC during particular ISV phases. In general, the observed anomalous ISV patterns of these large-scale GPI factors are well represented in HiRAM. Model deficiencies are also noted particularly in the anomalous midlevel relative humidity patterns and amplitude of vertical wind shear associated with the EPAC ISV.

Abstract

There has been an accelerating interest in forecasting the weather and climate within the subseasonal time range. The Madden–Julian oscillation (MJO), an organized envelope of tropical convection, is recognized as one of the leading sources of subseasonal predictability. This review synthesizes the latest progress regarding the MJO predictability and prediction. During the past decade, the MJO prediction skill in dynamical prediction systems has exceeded the skill of empirical predictions. Such improvement has been mainly attributed to more observations and computer resources, advances in theoretical understanding, and improved numerical models aided in part by multinational efforts through field campaigns and multimodel experiments. The state-of-the-art dynamical forecasts have shown MJO prediction skill up to 5 weeks. Prediction skill can be extended by improving the ensemble generation approach tailored for MJO prediction and by averaging multiensembles or multimodels. MJO prediction skill can be influenced by the tropical mean state and low-frequency climate mode variations, as well as by the extratropical circulation. MJO prediction skill is proven to be sensitive to model physics, ocean–atmosphere coupling, and quality of initial conditions, while the impact of the model resolution seems to be marginal. Remaining challenges and recommendations on new research avenues to fully realize the predictability of the MJO are discussed.

Abstract

The latitude preference of the intertropical convergence zone (ITCZ) is examined on the basis of observations, theory, and a modeling analysis. Observations show that convection is enhanced at latitudes of about 4° to 10° relative to the equator, even in regions where the sea surface temperature (SST) is maximum on the equator. Both linear shallow-water theory and a moist primitive equation model suggest a new explanation for the off-equatorial latitude preference of the ITCZ that requires neither the existence of zonally propagating disturbances nor an off-equatorial maximum in SST. The shallow-water theory indicates that a finite-width, zonally oriented, midtropospheric heat source (i.e., an ITCZ) produces the greatest local low-level convergence when placed a finite distance away from the equator. This result suggests that an ITCZ is most likely to be supported via low-level convergence of moist energy when located at these “preferred” latitudes away from the equator. For a plausible range of heating widths and damping parameters, the theoretically predicted latitude is approximately equal to the observed position(s) of the ITCZ(s). Analysis with an axially symmetric, moist, primitive equation model indicates that when the latent heating field is allowed to be determined internally, a positive feedback develops between the midtropospheric latent heating and the low-level convergence, with the effect of enhancing the organization of convection at latitudes of about 4° to 12°. Numerical experiments show that 1) two peaks in convective precipitation develop straddling the equator when the SST maximum is located on the equator; 2) steady ITCZ-like structures form only when the SST maximum is located away from the equator; and 3) peaks in convection can develop away from the maximum in SST, with a particular preference for latitudes of about 4° to 12°, even in the (“cold”) hemisphere without the SST maximum. The relationship between this mechanism and earlier theories is discussed, as are implications for the coupled ocean-atmosphere system and the roles played by midlevel latent heating and SST gradients in forcing the low-level atmospheric circulation in the tropics.

Abstract

The relationship between a model’s performance in simulating the Madden–Julian oscillation (MJO) and convectively coupled equatorial wave (CCEW) activity during wintertime is examined by analyzing precipitation from 26 general circulation models (GCMs) participating in the MJO Task Force/Global Energy and Water Cycle Experiment (GEWEX) Atmospheric System Study (GASS) MJO model intercomparison project as well as observations based on the Tropical Rainfall Measuring Mission (TRMM). A model’s performance in simulating the MJO is determined by how faithfully it reproduces the eastward propagation of the large-scale intraseasonal variability (ISV) compared to TRMM observations. Results suggest that models that simulate a better MJO tend to 1) have higher fractional variances for various high-frequency wave modes (Kelvin, mixed Rossby–gravity, and westward and eastward inertio-gravity waves), which are defined by the ratios of wave variances of specific wave modes to the “total” variance, and 2) exhibit stronger CCEW variances in association with the eastward-propagating ISV precipitation anomalies for these high-frequency wave modes. The former result is illustrative of an alleviation in the good MJO models of the widely reported GCM deficiency in simulating the correct distribution of variance in tropical convection [i.e., typically too weak (strong) variance in the high- (low-) frequency spectrum of the precipitation]. The latter suggests better coherence and stronger interactions between these aforementioned high-frequency CCEWs and the ISV envelope in good MJO models. Both factors likely contribute to the improved simulation of the MJO in a GCM.