Abstract

This study addresses two aspects of the planetary albedo's diurnal cycle, the first of which refers to directional models of the planetary albodo. It is found that even for clear regions there appear to be deficiencies in our knowledge of how to model this quantity. Over land surfaces, for example, Nimbus-7 data for the directional planetary albedo compare best with model calculations for which a Lambertian surface is assumed, despite ample evidence that the albedo of land surfaces is dependent upon solar zenith angle. Similarly, over ocean surfaces both GOES and Nimbus-7 data produce a weaker dependence of the planetary albedo upon solar zenith angle than would be suggested by model calculations.

The second aspect of the study concerns a comparison of the diurnal amplitude factor, defined as the ratio of the diurnally averaged planetary albedo to that at noon, between two general circulation models (GCMs) and measurements made from a geostationary satellite (GOES). While these comparisons indicate reasonable consistency between the GCMs and the satellite measurements, this is due in part to compensating differences, such as an underestimate in cloud amount by a GCM being compensated for by a corresponding underestimate of the diurnal amplitude factor for overcast regions. The comparisons further underscore difficulties associated with converting local-time albedo measurements, as made from sun-synchronous satellites, to diurnally averaged albedos.

Abstract

We discuss the spatial character of mesoscale temperature variability as observed in six midlatitude multiship expendable bathythermograph (XBT) surveys, two from the North Pacific and four from the North Atlantic. These surveys sample mid-ocean regions as well as regions adjacent to the western boundary currents of both subtropical gyres. Mesoscale characteristics exhibit substantial changes between surveys, between ship tracks within each survey and between different portions of individual ship tracks. These results suggest that a single XBT section across a region is unlikely to represent the range of variability within that region satisfactorily.

Fluctuations below the mixed layer are strongly vertically correlated, but surface temperatures are not well correlated with those below the mixed layer. We concentrate on the horizontal variability of the temperature at 450 m, and present rms thermal variability values and zonal autocorrelation functions as conventional measures of the variability. We also discuss the utility of analysis perspectives that focus on the “event-like” character of much of the variability and describe the properties of the different features in the data. Using climatology rather than a linear trend to remove the large scale can result in markedly different feature characteristics and survey statistics. In particular, warm and cold features (defined relative to climatology) often have quite different scales. Assuming that the mesoscale temperature variability is a Guassian process with 150 km decorrelation length is acceptable at the 95% level in several surveys using linearly detrended data, but is generally unacceptable when climatology is removed.

Abstract

We present the results of a multi-level, constant depth, primitive equation general ocean numerical circulation simulation with mesoscale resolution. A single mid-latitude model gyre is driven by wind and heating. After 30 years of spin-up with a relatively coarse grid and large diffusion coefficients, the grid size and diffusion coefficients are reduced. The circulation then adjusts into a nonlinear and time-dependent flow with periods of tens of days and space scales of hundreds of kilometers. After a quasi-equilibrium state is achieved, two years of data are obtained which are separated into time-mean and time-dependent fluctuations, and analyzed. Dynamically distinct regions are intensified, momentum, heat and vorticity balances examined, and energy integrals calculated. Statistical measures of significance and of uncertainty are computed where possible. Eddy energy is produced primarily by Reynolds stress work (barotropic instability) on the mean circulation shear in the recirculation and near-field region of the northern current system. Mean fluctuation correlation terms are presented in some regions at order 1 in the mean heat and vorticity balance and can be the leading ageostrophic effect in the mean momentum balance. The flow is non-quasigeostrophic in some parts of the intense boundary currents.

Clouds and the Earth's Radiant Energy System (CERES) is an investigation to examine the role of cloud/radiation feedback in the Earth's climate system. The CERES broadband scanning radiometers are an improved version of the Earth Radiation Budget Experiment (ERBE) radiometers. The CERES instruments will fly on several National Aeronautics and Space Administration Earth Observing System (EOS) satellites starting in 1998 and extending over at least 15 years. The CERES science investigations will provide data to extend the ERBE climate record of top-of-atmosphere shortwave (SW) and longwave (LW) radiative fluxes. CERES will also combine simultaneous cloud property data derived using EOS narrowband imagers to provide a consistent set of cloud/radiation data, including SW and LW radiative fluxes at the surface and at several selected levels within the atmosphere. CERES data are expected to provide top-of-atmosphere radiative fluxes with a factor of 2 to 3 less error than the ERBE data. Estimates of radiative fluxes at the surface and especially within the atmosphere will be a much greater challenge but should also show significant improvements over current capabilities.

Abstract

The response of ten atmospheric general circulation models to orbital forcing at 6 kyr BP has been investigated using the BIOME model, which predicts equilibrium vegetation distribution, as a diagnostic. Several common features emerge: (a) reduced tropical rain forest as a consequence of increased aridity in the equatorial zone, (b) expansion of moisture-demanding vegetation in the Old World subtropics as a consequence of the expansion of the Afro–Asian monsoon, (c) an increase in warm grass/shrub in the Northern Hemisphere continental interiors in response to warming and enhanced aridity, and (d) a northward shift in the tundra–forest boundary in response to a warmer growing season at high northern latitudes. These broadscale features are consistent from model to model, but there are differences in their expression at a regional scale. Vegetation changes associated with monsoon enhancement and high-latitude summer warming are consistent with palaeoenvironmental observations, but the simulated shifts in vegetation belts are too small in both cases. Vegetation changes due to warmer and more arid conditions in the midcontinents of the Northern Hemisphere are consistent with palaeoenvironmental data from North America, but data from Eurasia suggests conditions were wetter at 6 kyr BP than today. The models show quantitatively similar vegetation changes in the intertropical zone, and in the northern and southern extratropics. The small differences among models in the magnitude of the global vegetation response are not related to differences in global or zonal climate averages, but reflect differences in simulated regional features. Regional-scale analyses will therefore be necessary to identify the underlying causes of such differences among models.

Abstract

Providing advance warning for impending severe convective weather events (i.e., tornadoes, hail, wind) fundamentally requires an ability to predict and/or detect these hazards and subsequently communicate their potential threat in real time. The National Weather Service (NWS) provides advance warning for severe convective weather through the issuance of tornado and severe thunderstorm warnings, a system that has remained relatively unchanged for approximately the past 65 years. Forecasting a Continuum of Environmental Threats (FACETs) proposes a reinvention of this system, transitioning from a deterministic product-centric paradigm to one based on probabilistic hazard information (PHI) for hazardous weather events. Four years of iterative development and rapid prototyping in the National Oceanic and Atmospheric Administration (NOAA) Hazardous Weather Testbed (HWT) with NWS forecasters and partners has yielded insights into this new paradigm by discovering efficient ways to generate, inform, and utilize a continuous flow of information through the development of a human–machine mix. Forecasters conditionally used automated object-based guidance within four levels of automation to issue deterministic products containing PHI. Forecasters accomplished this task in a timely manner while focusing on communication and conveying forecast confidence, elements considered necessary by emergency managers. Observed annual increases in the usage of first-guess probabilistic guidance by forecasters were related to improvements made to the prototyped software, guidance, and techniques. However, increasing usage of automation requires improvements in guidance, data integration, and data visualization to garner trust more effectively. Additional opportunities exist to address limitations in procedures for motion derivation and geospatial mapping of subjective probability.

Abstract

Air quality and heat are strong health drivers, and their accurate assessment and forecast are important in densely populated urban areas. However, the sources and processes leading to high concentrations of main pollutants, such as ozone, nitrogen dioxide, and fine and coarse particulate matter, in complex urban areas are not fully understood, limiting our ability to forecast air quality accurately. This paper introduces the Clean Air for London (ClearfLo; www.clearflo.ac.uk) project’s interdisciplinary approach to investigate the processes leading to poor air quality and elevated temperatures.

Within ClearfLo, a large multi-institutional project funded by the U.K. Natural Environment Research Council (NERC), integrated measurements of meteorology and gaseous, and particulate composition/loading within the atmosphere of London, United Kingdom, were undertaken to understand the processes underlying poor air quality. Long-term measurement infrastructure installed at multiple levels (street and elevated), and at urban background, curbside, and rural locations were complemented with high-resolution numerical atmospheric simulations. Combining these (measurement–modeling) enhances understanding of seasonal variations in meteorology and composition together with the controlling processes. Two intensive observation periods (winter 2012 and the Summer Olympics of 2012) focus upon the vertical structure and evolution of the urban boundary layer; chemical controls on nitrogen dioxide and ozone production—in particular, the role of volatile organic compounds; and processes controlling the evolution, size, distribution, and composition of particulate matter. The paper shows that mixing heights are deeper over London than in the rural surroundings and that the seasonality of the urban boundary layer evolution controls when concentrations peak. The composition also reflects the seasonality of sources such as domestic burning and biogenic emissions.