Abstract

We have taken an important first step in validating climate models by comparing model and satellite inferred clear sky TOA (top-of-atmosphere) albedos. Model albodos were computed on a 1° × 1° latitude-longitude grid, allowing for variations in surface vegetation type, solar zenith angle, orography, spectral absorption/scattering at surface and within the atmosphere. Observed albedos were inferred from GOES-2 minimum narrowband (0.55–0.75 μm) brightness for November 1978 over South America and most of North America and adjacent ocean regions. Comparisons of TOA albedos over ocean agree within ±1% (the unit for albedo is in percent and the differences in percent denote absolute differences), and thus lie within both theoretical uncertainties (due to water vapor and aerosol concentrations, and ocean surface spectral reflectivity), as well as observational uncertainties. The ocean comparisons also show significant latitudinal variations in both model and observations. Albedos over land mostly agree within ±2% for the entire range of significant geographical variation of albedo from 13% over the Amazon Basin to 24% over mountains of western North America. These agreements lie within both theoretical uncertainties (due to surface type and spectral/zenith angle dependencies), as well as observational uncertainties (due to spectral and angular conversions of observed brightness to broadband albedos).

Abstract

The spatiotemporal evolution of daily southern Africa precipitation characteristics, and associated atmospheric circulation, related to El Niño and La Niña is examined across the region’s November–April wet season. Precipitation characteristics are examined in terms of monthly changes in daily average precipitation, the number of precipitation days, and the number of heavy precipitation days in three independently constructed estimates of observed precipitation during 1983–2018. Mechanisms related to precipitation changes, including contributions from mass divergence, water vapor transports, and transient eddies, are diagnosed using the atmospheric moisture budget based on the ERA5 reanalysis. El Niño is related to precipitation anomalies that build during December–March, the core of the rainy season, culminating in significantly below average values stretching across a semiarid region from central Mozambique to southeastern Angola. A broad anticyclone centered over Botswana drives these precipitation anomalies primarily through anomalous mass divergence, with moisture advection and transient eddies playing secondary roles. La Niña is related to significantly above average daily precipitation characteristics over all Africa south of 20°S in February and much less so during the other five months. February precipitation anomalies are primarily driven through mass divergence due to a strong anomalous cyclonic circulation, whereas a similar circulation is more diffuse during the other months. The spatiotemporal evolutions of anomalies in daily precipitation characteristics across southern Africa related to El Niño and La Niña are not equal and opposite. The robustness of an asymmetric evolution, which could have implications for subseasonal forecasts, needs to be confirmed with analysis of additional empirical data and established with climate model experimentation.

Abstract

Westerly wind events (WWEs) have previously been shown to initiate equatorial Pacific waveguide warming. The relationship between WWEs and Madden–Julian oscillation (MJO) activity, as well as the role of MJO events in initiating waveguide warming, is reconsidered here over the 1986–2010 period. WWEs are identified in observations of near-surface zonal winds using an objective scheme. MJO events are defined using a widely used index, and 64 are identified that occur when the El Niño–Southern Oscillation (ENSO) is in its neutral state. Of these MJO events, 43 have one or more embedded WWEs and 21 do not. The evolution of sea surface temperature anomaly over the equatorial Pacific waveguide following the westerly surface wind phase of the MJO over the western equatorial Pacific is examined. Waveguide warming is found for the MJO with WWE events in similar magnitudes as following the WWEs not embedded in an MJO. There is very little statistically significant waveguide warming following MJO events that do not contain an embedded WWE. The observed SST anomaly changes are well reproduced in an ocean general circulation model forced with the respective composite wind stress anomalies. Further, it is found that the occurrence of an MJO event does not significantly affect the likelihood that a WWE will occur. These results extend and confirm the earlier results of Vecchi with a near doubling of the period of study. It is suggested that understanding the sources and predictability of tropical Pacific westerly wind events remains essential to improving predictions of the onset of El Niño events.

Abstract

Five different analyses of 1982–83 monthly average surface wind stress fields have been used to force an ocean general circulation model of the tropical Pacific, in a series of El Niño hindcast experiments, like the one reported by Philander and Seigel. Although there were prominent common departures from climatology in the surface wind stress field during 1982–83 according to each wind analysis, there are also very substantial differences between analyses. This study was done to investigate the sensitivity of such hindcasts to our uncertain knowledge of the surface wind stress field. We concentrate here on the behavior along the Pacific ship-of-opportunity tracks.

According to the ship-of-opportunity XBT data, the ocean underwent major changes during this period. The vertical temperature gradients and mixed layer temperatures, as well as the depth of the thermocline, underwent substantial changes. There were also major changes in the geostrophic flow of the major current systems, as revealed by upper ocean dynamic height differences. Comparing the hindcasts with observations, we find that the gross large-scale changes of the ENSO event—surface warming in the second half of 1982, continued warmth into 1983 and cooling in mid-1983, together with major thermocline depth changes—are found in each hindcast. However, major quantitative differences exist between each hindcast and the observations in at least some region for some time and some variable.

Within the waveguide, dynamic height changes generally are hindcast with quantitative skill using each wind stress field and the best hindcasts differ from the observations by only a few dyn-cm more than the estimated uncertainty in the observations. Such hindcast skill is unlikely to be fortuitous: evidently the major elements of the waveguide variability are forced by the 1982–83 surface wind stress field rather than evolving out of some aspect of the state of the ocean during late 1981. Sea surface temperature changes are generally hindcast with qualitative skill, but rms errors of 2–3°C are frequent. Subsurface temperature variability skill varies with hindcast, location and depth; skill is greatest in the thermocline.

Outside the waveguide, hindcast skill tends to be reduced, and varies greatly with location and hindcast. Quantitative hindcast skill is found near 10°S and 10°N in some hindcasts in the WP, and near 10°S in most hindcasts in the CP, but there is never quantitative skill in the NECC region. The most striking inconsistency found involves the behavior of the NMC hindcast in the region of the North Equatorial Counter Current. Wind stress curl-forced Ekman pumping appears to be a significant factor in the variations in the more successful hindcasts.

In almost every comparison, the range of hindcast results brackets the observations, suggesting that the model physics is plausible. Overall, the special research effort wind fields produced better dynamic height results than did the operational wind product fields, but the operational fields produced generally better waveguide SST results. Improved knowledge of the surface wind stress field (and its curl) is a minimum requirement if we are to assess more critically model performance, and to identify needed model improvements.

Abstract

This paper presents a quantitative methodology for evaluating air–sea fluxes related to ENSO from different atmospheric products. A statistical model of the fluxes from each atmospheric product is coupled to an ocean general circulation model (GCM). Four different products are evaluated: reanalyses from the National Centers for Environmental Prediction (NCEP) and the European Centre for Medium-Range Weather Forecasts (ECMWF), satellite-derived data from the Special Sensor Microwave/Imaging (SSM/I) platform and the International Satellite Cloud Climatology Project (ISCCP), and an atmospheric GCM developed at the Geophysical Fluid Dynamics Laboratory (GFDL) as part of the Atmospheric Model Intercomparison Project (AMIP) II. For this study, comparisons between the datasets are restricted to the dominant air–sea mode.

The stability of a coupled model using only the dominant mode and the associated predictive skill of the model are strongly dependent on which atmospheric product is used. The model is unstable and oscillatory for the ECMWF product, damped and oscillatory for the NCEP and GFDL products, and unstable (nonoscillatory) for the satellite product. The ocean model is coupled with patterns of wind stress as well as heat fluxes. This distinguishes the present approach from the existing paradigm for ENSO models where surface heat fluxes are parameterized as a local damping term in the sea surface temperature (SST) equation.

Abstract

Impact forecasts and warnings (IFW) are key to resilience for hydrometeorological hazards. Communicating the potential social, economic, and environmental hazard impacts allows individuals and communities to adjust their plans and better prepare for the consequences of the hazard. IFW systems require additional knowledge about impacts and underlying vulnerability and exposure. Lack of data or knowledge about impacts, vulnerability, and exposure has been identified as a challenge for IFW implementation. In this study, we begin to address this challenge by developing an understanding of the data needs and uses for IFWs. Using the grounded theory method, we conducted a series of interviews with users and creators of hazard, impact, vulnerability, and exposure data (e.g., warning services, forecasters, meteorologists, hydrologists, emergency managers, data specialists, risk modelers) to understand where these data are needed and used in the warning value chain, a concept used to represent and understand the flow of information among actors in the warning chain. In support of existing research, we found a growing need for creating, gathering, and using impact, vulnerability, and exposure data for IFWs. Furthermore, we identified different approaches for impact forecasting and defining impact thresholds using objective models and subjective impact-oriented discussions depending on the data available. We also provided new insight into a growing need to identify, model, and warn for social and health impacts, which have typically taken a back seat to modeling and forecasting physical and infrastructure impacts. Our findings on the data needs and uses within IFW systems will help guide their development and provide a pathway for identifying specific relevant data sources.

Abstract

The International Satellite Cloud Climatology Project (ISCCP) will provide a uniform global climatology of satellite-measured radiances and derive an experimental climatology of cloud radiative properties from these radiances. A pilot study to intercompare cloud analysis algorithms was initiated in 1981 to define a state-of-the-art algorithm for ISCCP. This study compared the results of applying six different algorithms to the same satellite radiance data. The results show that the performance of all current algorithms depends on how accurately the clear sky radiances are specified; much improvement in results is possible with better methods for obtaining these clear-sky radiances. A major difference between the algorithms is caused by their sensitivity to changes in the cloud size distribution and optical properties: all methods, which work well for some cloud types or climate regions, do poorly for other situations. Therefore, the ISCCP algorithm is composed of a series of steps, each of which is designed to detect some of the clouds present in the scene. This progressive analysis is used to retrieve an estimate of the clear sky radiances corresponding to each satellite image. Application of a bispectral threshold is then used as the last step to determine the cloud fraction. Cloudy radiances are interpreted in terms of a simplified model of cloud radiative effects to provide some measure of cloud radiative properties. Application of this experimental algorithm to produce a cloud climatology and field observation programs to validate the results will stimulate further research on cloud analysis techniques as part of ISCCP.

Abstract

One possible method of incorporating model sensitivities into ensemble forecasting systems is to combine ensembles run from two or more models. Furthermore, the use of more than one analysis, to which perturbations are added, may provide further unstable directions for error growth not present with a single analysis.

Results are presented from recent investigations into the potential benefit of combining ensembles from the systems of the European Centre for Medium-Range Weather Forecasts and The Met. Office of the United Kingdom. The multimodel and multianalysis ensemble significantly outperforms either individual system in many performance aspects, including deterministic and probabilistic forecast skill, spread–skill correlations, and breadth of synoptic information. It is demonstrated that these improvements are achieved through the combination of independent, useful information contained in the individual systems, and not through simple cancellation of biases that could occur when ensembles from two different forecast systems are combined. In addition, results indicate that model dependencies are at least comparable with analysis dependencies on medium-range timescales, and so in general both models and both analyses are required in the joint ensemble for the largest benefits.

Abstract

The highly temporally resolved time series from the Tropical Atmosphere-Ocean moored buoy array are used to evaluate the scales of thermal variability in the upper equatorial Pacific. The TAO array consists of nearly 70 deep-ocean moorings arranged nominally 15° longitude and 2°–3° latitude apart across the equatorial Pacific. The bulk of the data from the array consists of daily averages telemetered in real time, with some records up to 15 years long. However, at several sites more finely resolved data exist, in some cases with resolution of 1 minute. These data form the basis for spectral decomposition spanning virtually all scales of variability from the Brunt-Väiälä frequency to the El Niño-Southern Oscillation timescale. The spectra are used to define the signal to noise ratio as a function of sample rate and frequency, and to investigate the effects of aliasing that results from sparser sampling, such as ship-based observational techniques. The results show that the signal to noise ratio is larger in the east, mostly because the low-frequency signals are larger there. The noise level for SST varies by as much as a factor of 10 among the locations studied, while noise in thermocline depth is relatively more homogeneous over the region. In general, noise due to aliased high-frequency variability increases by roughly a factor of 10 as the sample rate decreases from daily to 100-day sampling. The highly resolved spectra suggest a somewhat more optimistic estimate of overall signal-to-noise ratios for typical ship of opportunity (VOS) XBT sampling (generally about 2) than had been found in previous studies using sparser data. Time scales were estimated for various filtered versions of the time series by integration of the autocorrelation functions. For high-passed data (periods longer than about 150 days removed), the timescale is about 5 days for both surface and subsurface temperatures everywhere in the region. Conversely, for low-passed data (the annual cycle and periods shorter than 150 days removed), the timescale is roughly 100 days. Horizontal space scales were estimated from cross-correlations among the buoys. Zonal scales of low-frequency SST variations along the equator were half the width of the Pacific, larger than those of thermocline depth (about 30°–40° longitude). In the cast, meridional scales of low-frequency SST were large (greater than about 15° latitude), associated with the coherent waxing and waning of the equatorial cold tongue, whereas in the west these scales were shorter. Thermocline depth variations had meridional scales associated with the equatorial waves, particularly in the east. Spatial scale estimates reported here are generally consistent with those found from the VOS datasets when the ENSO signals in the records of each dataset are taken into account. However, if signals with periods of 1 to 2 months are to be properly sampled, then sampling scales of 1°–2° latitude by 8°–10° longitude, with a 5-day timescale, are needed.

This paper describes the Earth Radiation Budget Experiment (ERBE) data products being made available to the community. The Science Team used ten validation criteria to judge the acceptability of the data for archival. We list these criteria and present uncertainty estimates based on them for four typical data products. A brief description of the radiation budget for April 1985 from the combined data of ERBE and NOAA-9 concludes this paper.