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Aondover Tarhule and Peter J. Lamb

Beginning in response to the disastrous drought of 1968–73, considerable research and monitoring have focused on the characteristics, causes, predictability, and impacts of West African Soudano–Sahel (10°–18°N) rainfall variability and drought. While these efforts have generated substantial information on a range of these topics, very little is known of the extent to which communities, activities at risk, and policy makers are aware of, have access to, or use such information. This situation has prevailed despite Glantz's provocative BAMS paper on the use and value of seasonal forecasts for the Sahel more than a quarter century ago. We now provide a systematic reevaluation of these issues based on questionnaire responses of 566 participants (in 13 communities) and 26 organizations in Burkina Faso, Mali, Niger, and Nigeria. The results reveal that rural inhabitants have limited access to climate information, with nongovernmental organizations (NGOs) being the most important source. Moreover, the pathways for information flow are generally weakly connected and informal. As a result, utilization of the results of climate research is very low to nonexistent, even by organizations responsible for managing the effects of climate variability. Similarly, few people have access to seasonal climate forecasts, although the vast majority expressed a willingness to use such information when it becomes available. Those respondents with access expressed great enthusiasm and satisfaction with seasonal forecasts. The results suggest that inhabitants of the Soudano–Sahel savanna are keen for changes that improve their ability to cope with climate variability, but the lack of information on alternative courses of action is a major constraint. Our study, thus, essentially leaves unchanged both Glantz's negative “tentative conclusion” and more positive “preliminary assessment” of 25 years ago. Specifically, while many of the infrastructural deficiencies and socioeconomic impediments remain, the great yearning for climate information by Soudano–Sahalians suggests that the time is finally ripe for fostering increased use. Therefore, a simple model for improved dissemination of climate research and seasonal climate forecast information is proposed. The tragedy is that a quarter century has passed since Glantz's clarion call.

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Peter J. Webster and Carlos Hoyos

Most attempts at predicting south Asian monsoon variability have concentrated on seasonally averaged rainfall over the Indian subcontinent some months in advance using regional and remote boundary effects as predictors. Overall, about 30% of the variance of mean seasonal monsoon rainfall can be explained, but the statistics appear to be nonstationary and correlations vary strongly on interdecadal time scales. Model intercomparisons show that climate models have difficulty in simulating even gross-scale features of the monsoon such as mean summer rainfall, and there is little demonstrated skill when the models are used in predictive mode. Even if the statistics were stable and model predictions were skillful it is argued that the information is not readily downscalable because the mean rainfall does not define the timing or number of intraseasonal variations or even the spatial distributions of the seasonal mean rainfall. Based on these concerns, it is argued that skillful and timely forecasts of intraseasonal variability possess a greater potential utility for agriculture and water resource management and should be the highest priority for prediction within the monsoon regions.

A physically based empirical Bayesian prediction scheme is developed for forecasting regional intraseasonal variability of the monsoon. Ten predictors are chosen that depict the morphology of the monsoon intraseasonal mode. The scheme employs a wavelet-banding technique and linear regression to forecast 5-day average rainfall variability over regions of south Asia 15–30 days (i.e., six 5-day lags) in the future. Hindcasts conducted for the central Indian region for the period 1992–2002 show considerable skill out to 30 days in both the timing and amplitude of the intraseasonal oscillations. Skill, albeit reduced, is also found in smaller regions such as the Indian states of Rajasthan and Orissa. The use of wavelet analysis to sort time series and isolate each band from the noise generated in other bands, together with the careful choice of predictors, are the defining elements of the scheme. Anomaly correlations of rainfall in the 28–80-day band in central India are 0.88, 0.76, 0.73, 0.66, and 0.58 for 10,15, 20, 25, and 30 days, respectively. Similar skill is found for forecasting the discharge of the Ganges and Brahmaputra into Bangladesh. The potential utility of these forecasts for applications in agriculture and water resource management is discussed together with the possible use of the empirical scheme as a diagnostic tool and as a guide for the development of a new type of numerical model.

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Eugene M. Wilkins

Eastern Idaho's Snake River Plain and that portion of the Continental Divide bordering it to the north comprise a topographic feature that provides an interesting local wind phenomenon. A sloping discontinuity surface is produced in a zone of conflict between slope and valley winds. The incursions of the front at the National Reactor Testing Station have become the subject of investigation because of their effect on the dispersion of stack effluents

Photographs are presented showing the effect of the frontal shear on a stack plume, smoke released at the ground, and a debris cloud from an experimental explosion. These photographs give an indication of the circulation pattern in the vicinity of the front. In addition, data from a network of recording stations, instruments on a 250-ft tower, and low-level wind and temperature soundings have been used to establish the circulation model.

Information is presented to show seasonal and diurnal effects, and also the influence of major pressure systems on the front phenomenon.

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Andreas Stohl, Heini Wernli, Paul James, Michel Bourqui, Caroline Forster, Mark A. Liniger, Petra Seibert, and Michael Sprenger

Stratosphere–troposphere exchange (STE) is important for the chemical composition of both the stratosphere and troposphere. Modifications of STE in a changing climate may affect stratospheric ozone depletion and the oxidizing capacity of the troposphere significantly. However, STE is still poorly understood and inadequately quantified, due to the involvement of physical and dynamical processes on local to global scales and to conceptual problems. In this study, a presentday global climatology of STE is developed that is based, from a data standpoint, on 15 yr of global meteorological reanalyses, and, from a conceptual standpoint, on a Lagrangian perspective that considers the pathways of exchange air parcels and their residence times in the troposphere and lowermost stratosphere. To this end, two complementary Lagrangian models are used. Particular consideration is given to “deep” exchange events that, through fast ascent of tropospheric or fast descent of stratospheric air masses, bring into contact air from the (potentially polluted) boundary layer and lower stratosphere. It is shown that they have different characteristics (strongly preferred geographical locations and a pronounced seasonal cycle) from that of the full set of exchange events. This result is important for accurately characterizing the effects of STE. In particular, it can be inferred that the well-documented springtime maximum of surface ozone cannot be explained primarily by STE.

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F. A. Huff and S. A. Changnon Jr.

Historical weather records at eight American urban areas of varying size, type, and climate were studied for indications of inadvertent precipitation modification. The six largest cities all had experienced warm seasonal rainfall increases of 9 to 17% during the 1955–70 period. The increases in the Midwest cities occurred largely with cold frontal systems, but in the coastal cities they were largely during air mass (non-frontal) conditions. The Midwest increases also were found to occur as enhancement, not initiation, of moderate to heavy rain days. Significant increases in summer thunder-day frequencies (13 to 41%) and hail-day frequencies (90 to 450%) were found at the six largest cities, and the increases occurred largely in the morning hours. The typical locations of maxima in the Midwest cities were thunder over and near the city, and rain and hail 25 to 55 km downwind. The maxima of all events in coastal cities were in or near the city. Overall, the results suggest that urban precipitation enhancement is related to city size, industrial nuclei generation, and urban thermal effects. The alterations have considerable relevance to urban design, local area forecasting, local water supplies, agricultural production, hydrologic design, and to planned weather modification.

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T. P. Barnett, K. Hasselmann, M. Chelliah, T. Delworth, G. Hegerl, P. Jones, E. Rasmusson, E. Roeckner, C. Ropelewski, B. Santer, and S. Tett

This paper addresses the question of where we now stand with respect to detection and attribution of an anthropogenic climate signal. Our ability to estimate natural climate variability, against which claims of anthropogenic signal detection must be made, is reviewed. The current situation suggests control runs of global climate models may give the best estimates of natural variability on a global basis, estimates that appear to be accurate to within a factor of 2 or 3 at multidecadal timescales used in detection work.

Present uncertainties in both observations and model-simulated anthropogenic signals in near-surface air temperature are estimated. The uncertainty in model simulated signals is, in places, as large as the signal to be detected. Two different, but complementary, approaches to detection and attribution are discussed in the context of these uncertainties.

Applying one of the detection strategies, it is found that the change in near-surface, June through August air temperature field over the last 50 years is generally different at a significance level of 5% from that expected from model-based estimates of natural variability. Greenhouse gases alone cannot explain the observed change. Two of four climate models forced by greenhouse gases and direct sulfate aerosols produce results consistent with the current climate change observations, while the consistency of the other two depends on which model's anthropogenic fingerprints are used. A recent integration with additional anthropogenic forcings (the indirect effects of sulfate aerosols and tropospheric ozone) and more complete tropospheric chemistry produced results whose signal amplitude and pattern were consistent with current observations, provided the model's fingerprint is used and detection carried out over only the last 30 years of annually averaged data. This single integration currently cannot be corroborated and provides no opportunity to estimate the uncertainties inherent in the results, uncertainties that are thought to be large and poorly known. These results illustrate the current large uncertainty in the magnitude and spatial pattern of the direct and indirect sulfate forcing and climate response. They also show detection statements depend on model-specific fingerprints, time period, and seasonal character of the signal, dependencies that have not been well explored.

Most, but not all, results suggest that recent changes in global climate inferred from surface air temperature are likely not due solely to natural causes. At present it is not possible to make a very confident statement about the relative contributions of specific natural and anthropogenic forcings to observed climate change. One of the main reasons is that fully realistic simulations of climate change due to the combined effects of all anthropogenic and natural forcings mechanisms have yet to be computed. A list of recommendations for reducing some of the uncertainties that currently hamper detection and attribution studies is presented.

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David K. Adams and Andrew C. Comrie

The North American monsoon is an important feature of the atmospheric circulation over the continent, with a research literature that dates back almost 100 years. The authors review the wide range of past and current research dealing with the meteorological and climatological aspects of the North American monsoon, highlighting historical development and major research themes. The domain of the North American monsoon is large, extending over much of the western United States from its region of greatest influence in northwestern Mexico. Regarding the debate over moisture source regions and water vapor advection into southwestern North America, there is general agreement that the bulk of monsoon moisture is advected at low levels from the eastern tropical Pacific Ocean and the Gulf of California, while the Gulf of Mexico may contribute some upper-level moisture (although mixing occurs over the Sierra Madre Occidental). Surges of low-level moisture from the Gulf of California are a significant part of intraseasonal monsoon variability, and they are associated with the configuration of upper-level midlatitude troughs and tropical easterly waves at the synoptic scale, as well as the presence of low-level jets, a thermal low, and associated dynamics (including the important effects of local topography) at the mesoscale. Seasonally, the gulf surges and the latitudinal position of the midtropospheric subtropical ridge over southwestern North America appear to be responsible for much spatial and temporal variability in precipitation. Interannual variability of the North American monsoon system is high, but it is not strongly linked to El Niño or other common sources of interannual circulation variability. Recent mesoscale field measurements gathered during the South-West Area Monsoon Project have highlighted the complex nature of the monsoon-related severe storm environment and associated difficulties in modeling and forecasting.

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Karen I. Mohr and Edward J. Zipser

Mesoscale convective systems are composed of numerous deep convective cells with varying amounts of large, convectively produced ice particles aloft. The magnitude of the 85-GHz brightness temperature depression resulting from scattering by large ice is believed to be related to the convective intensity and to the magnitude of the convective fluxes through a deep layer. The 85-GHz ice-scattering signature can be used to map the distribution of organized mesoscale regions of convectively produced large ice particles. The purpose of this article is to demonstrate the usefulness of the 85-GHz ice-scattering signature for describing the frequency, convective intensity, and geographic distribution of mesoscale convective systems.

Objective criteria were developed to identify mesoscale convective systems from raw data from January, April, July, and October 1993. To minimize the effects of background contamination and to ensure that bounded areas contained convective elements, a “mesoscale convective system” was defined as an area bounded by 250 K of at least 2000 km2 of 85 GHz, with a minimum brightness temperature ≤ 225 K. Mesoscale convective systems extracted from the raw data were sorted and plotted by their areas and by their minimum brightness temperatures. Four area and brightness temperature classes were used to account for a spectrum of organized convection ranging from small to very large and from less organized to highly organized. The populations of mesoscale convective systems by this study's definition were consistent with infrared-based climatologies and large-scale seasonal dynamics. Land/water differences were highlighted by the plots of minimum brightness temperature. Most of the intense mesoscale convective systems were located on or near land and seemed to occur most frequently in particular areas in North America, South America, Africa, and India.

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Anthony G. Barnston, Ants Leetmaa, Vernon E. Kousky, Robert E. Livezey, Edward A. O'Lenic, Huug Van den Dool, A. James Wagner, and David A. Unger

The strong El Niño of 1997–98 provided a unique opportunity for National Weather Service, National Centers for Environmental Prediction, Climate Prediction Center (CPC) forecasters to apply several years of accumulated new knowledge of the U.S. impacts of El Niño to their long-lead seasonal forecasts with more clarity and confidence than ever previously. This paper examines the performance of CPC's official forecasts, and its individual component forecast tools, during this event. Heavy winter precipitation across California and the southern plains–Gulf coast region was accurately forecast with at least six months of lead time. Dryness was also correctly forecast in Montana and in the southwestern Ohio Valley. The warmth across the northern half of the country was correctly forecast, but extended farther south and east than predicted. As the winter approached, forecaster confidence in the forecast pattern increased, and the probability anomalies that were assigned reached unprecedented levels in the months immediately preceding the winter. Verification scores for winter 1997/98 forecasts set a new record at CPC for precipitation.

Forecasts for the autumn preceding the El Niño winter were less skillful than those of winter, but skill for temperature was still higher than the average expected for autumn. The precipitation forecasts for autumn showed little skill. Forecasts for the spring following the El Niño were poor, as an unexpected circulation pattern emerged, giving the southern and southeastern United States a significant drought. This pattern, which differed from the historical El Niño pattern for spring, may have been related to a large pool of anomalously warm water that remained in the far eastern tropical Pacific through summer 1998 while the waters in the central Pacific cooled as the El Niño was replaced by a La Niña by the first week of June.

It is suggested that in addition to the obvious effects of the 1997–98 El Niño on 3-month mean climate in the United States, the El Niño (indeed, any strong El Niño or La Niña) may have provided a positive influence on the skill of medium-range forecasts of 5-day mean climate anomalies. This would reflect first the connection between the mean seasonal conditions and the individual contributing synoptic events, but also the possibly unexpected effect of the tropical boundary forcing unique to a given synoptic event. Circumstantial evidence suggests that the skill of medium-range forecasts is increased during lead times (and averaging periods) long enough that the boundary conditions have a noticeable effect, but not so long that the skill associated with the initial conditions disappears. Firmer evidence of a beneficial influence of ENSO on subclimate-scale forecast skill is needed, as the higher skill may be associated just with the higher amplitude of the forecasts, regardless of the reason for that amplitude.

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Garik Gutman, Dan Tarpley, Aleksandr Ignatov, and Steve Olson

Global mapped data of reflected radiation in the visible (0.63 μm) and near-infrared (0.85 μm) wavebands of the Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration satellites have been collected as the global vegetation index (GVI) dataset since 1982. Its primary objective has been vegetation studies (hence its title) using the normalized difference vegetation index (NDVI) calculated from the visible and near-IR data. The second-generation GVI, which started in April 1985, has also included brightness temperatures in the thermal IR (11 and 12 μm) and the associated observation–illumination geometry. This multiyear, multispectral, multisatellite dataset is a unique tool for global land studies. At the same time, it raises challenging remote sensing and data management problems with respect to uniformity in time, enhancement of signal-to-noise ratio, retrieval of geophysical parameters from satellite radiances, and large data volumes. The authors explored a four-level generic structure for processing AVHRR data—the first two levels being remote sensing oriented and the other two directed at environmental studies—and will describe the present status of each level. The uniformity of GVI data was improved by applying an updated calibration, and noise was reduced by applying a more accurate cloud-screening procedure. In addition to the enhanced weekly data (recalibrated with appended quality/cloud flags), the available land environmental products include monthly 0.15°-resolution global maps of top-of-theatmosphere visible and near-IR reflectances, NDVI, brightness temperatures, and a precipitable water index for April 1985–September 1994. For the first time, a 5-yr monthly climatology (means and standard deviations) of each quantity was produced. These products show strong potential for detecting and analyzing largescale spatial and seasonal land variability. The data can also be used for educational purposes to illustrate the annual global dynamics of vegetation cover, albedo, temperature, and water vapor. Development of the GVI data product contributes to the activities of the International Geosphere–Biosphere Programme and Global Energy and Water Cycle Experiment and, in particular, to the International Satellite Land Surface Climatology Project. Monthly standardized anomalies of the GVI variables have been calculated for April 1985–present and are routinely produced on UNIX workstations, thus providing a prototype land monitoring system. Standardized anomalies clearly indicate that strong signals at the land surface, such as droughts and floods and their teleconnections with such global environmental phenomena as El Niño–Southern Oscillation, can be detected and analyzed. The monitoring of relatively small year-to-year variability is, however, contingent on the removal of residual trends/noise in GVI data, which are of the order of the analyzed effects.

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