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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Re-evaluating probable maximum precipitation estimates: sensitivity to transposition domains and storm rotation using modern datasets

This study examines the sensitivity of Probable Maximum Precipitation (PMP) estimates to key methodological decisions embedded in the legacy approach adopted in the U.S. National Weather Service Hydrometeorological Reports No. 51 and No. 52. Although widely used for infrastructure design and risk regulation, fundamental aspects of PMP estimation—such as storm sample size, transposition domain, maximization procedures, and storm rotation—remain poorly constrained and lack formal guidance. Using the Red Rock watershed in Iowa as a case study, and leveraging the 2002–2023 NOAA Analysis of Record for Calibration (AORC) precipitation dataset, we systematically evaluate how each methodological choice, individually and in combination, influences PMP estimates. Our findings demonstrate that PMP is not a fixed physical upper bound but rather a modeling construct shaped heavily by user-defined assumptions. Notably, PMP values derived from modern gridded rainfall datasets can be substantially higher than the legacy estimate used in the original spillway design for Red Rock Dam. Decisions regarding storm sample size, domain extent, climatological window, and particularly storm rotation all contributed to higher PMP estimates. Storm rotation alone—a loosely constrained element in the current PMP practice—can amplify PMP by more than 25%. These results reveal the lack of standardized bounds in current PMP workflows and the need for systematic sensitivity and uncertainty analysis. As PMP estimation shifts toward probabilistic approaches, incorporating physically meaningful storm attributes will be key to developing more transparent, defensible methods for dam safety and climate-resilient infrastructure.

Probable maximum precipitation↗
DOE OSTI2020

Application of Numerical Atmospheric Models

In this study, a numerical modeling framework for simulating extreme storm events was established using the Weather Research and Forecasting (WRF) model. Such a framework is necessary for the derivation of engineering parameters such as probable maximum precipitation that are the cornerstone of large water-management infrastructure design. Here, this framework was built based on a heavy storm that occurred in Nashville, Tennessee (U.S.), in 2010, and verified using two other extreme storms. To achieve the optimal setup, several combinations of model resolutions, initial/boundary conditions (IC/BC), cloud microphysics, and cumulus parameterization schemes were evaluated using multiple metrics of precipitation characteristics. The evaluation suggests that WRF is most sensitive to the IC/BC option. Simulation generally benefits from finer resolutions up to 5 km. At the 15 km level, NCEP2 IC/BC produces better results, whereas NAM IC/BC performs best at the 5 km level. The recommended model configuration from this study is: NAM or NCEP2 IC/BC (depending on data availability), 15 km or 15–5 km nested grids, Morrison microphysics, and Kain-Fritsch cumulus schemes. Validation of the optimal framework suggests that these options are good starting choices for modeling extreme events similar to the test cases. This optimal framework is proposed in response to emerging engineering demands of extreme storm event forecasting and analyses for design, operations, and risk assessment of large water infrastructures.

Chen, Xiaodong↗
DOE OSTI2020

Infrastructure-Relevant Storms of the Last Century

Historical extreme storm events are widely used to make Probable Maximum Precipitation (PMP) estimates, which form the cornerstone of large water management infrastructure safety. Past studies suggest that extreme precipitation processes can be sensitive to land surface feedback and the planetary warming trend, which makes the future safety of large infrastructures questionable given the projected changes in land cover and temperature in the coming decades. In this study, a numerical modeling framework was employed to reconstruct 10 extreme storms over CONUS that occurred during the past 100 years, which are used by the engineering profession for PMP estimation for large infrastructures such as dams. Results show that the correlation in daily rainfall for such reconstruction can range between 0.4 and 0.7, while the correlation for maximum 3-day accumulation (a standard period used in infrastructure design) is always above 0.5 for post-1948 storms. This suggests that current numerical modeling and reanalysis data allow us to reconstruct big storms after 1948 with acceptable accuracy. For storms prior to 1948, however, reconstruction of storms shows inconsistency with observations. Our study indicates that numerical modeling and data may not have advanced to a sufficient level to understand how such old storms (pre-1948) may behave in future warming and land cover conditions. However, the infrastructure community can certainly rely on the use of model reconstructed extreme storms of the 1948-present period to reassess safety of our large water infrastructures under assumed changes in temperature and land cover.

Chen, Xiaodong↗
DOE OSTI2020

Safety Design of Water Infrastructures in A Modern Era

In this chapter, we review the current practice of engineering safety design of large water management infrastructures. Those large infrastructures are designed using probable maximum precipitation (PMP) to withstand extreme conditions, but climate change has been posing challenges on the conventional PMP estimation approach. We discuss multiple limitations of the current approaches, and propose a few possible solutions based on the advancement of atmospheric modeling and statistical analysis of extreme precipitation mechanisms.

Chen, Xiaodong↗
NASA NTRSDate not supplied

Warming Reduces the Efficacy of Wet Conditions to Moderate Extreme Heat and Atmospheric Aridity Across the Central Plains

In the literature, dry land surface conditions possess a well-established association with extreme heat and high atmospheric aridity, especially in regions that experience strong land-atmosphere feedbacks. However, few studies have examined whether global warming will impact the ability of wet conditions to constrain high temperatures and atmospheric aridity occurrences. Here we investigate how wet conditions, which we define using precipitation and soil moisture, constrain high temperature and high vapor pressure deficit during the warm season over the Central Plains in North America at different global warming levels (0-3 degrees K). Using a CMIP6 multi-model ensemble, we show that absolute changes in the maximum temperature distribution outweigh the historical cooling effect of high precipitation or soil moisture conditions, reducing the probability of non-extreme maximum temperatures under global warming. Strikingly, the conditional likelihood of non-extreme maximum temperatures falls from 97-98% at baseline conditions to 50-58% at 1 degree of global warming. Once 2 degrees of warming is reached, there is very little probability of constraining extreme maximum temperatures. On the other hand, high precipitation and high soil moisture are able to better retain the ability to constrain concurrent high vapor pressure deficit conditions – moving from 99% at baseline conditions to 81-91% at 1 degree of warming and 26-42% at 2 degrees of warming. With our results, we find that the extent of this retention is dependent on how individual models represent relative changes in the VPD distribution as temperatures warm. Overall, our results highlight the growing vulnerability of the Central North American region to warmer temperatures and drier atmospheric conditions, even during periods of high precipitation and soil moisture.

Extreme heat↗
DOE OSTI2023

Assessment of WRF (v 4.2.1) dynamically downscaled precipitation on subdaily and daily timescales over CONUS

Abstract. This study analyzes the quality of simulated historical precipitation across the contiguous United States (CONUS) in a 12 km Weather Research and Forecasting model version 4.2.1 (WRF v 4.2.1)-based dynamical downscaling of the fifth-generation ECMWF atmospheric reanalysis (ERA5). This work addresses the following questions. First, how well are the 3 and 24 h precipitation characteristics (diurnal and annual cycles, precipitation frequency, annual and seasonal mean and maximum precipitation, and distribution of seasonal maximum precipitation) represented in the downscaled simulation, compared to ERA5? And second, how does the performance of the simulated WRF precipitation vary across seasons, regions, and timescales? Performance is measured against the National Centers for Environmental Prediction/Environmental Modeling Center (NCEP/EMC) 4 km Stage IV and Oregon State University Parameter-Elevation Regressions on Independent Slopes Model (PRISM) data on 3 and 24 h timescales, respectively. Our analysis suggests that the 12 km WRF exhibits biases typically found in other WRF simulations, including those at convection-permitting scales. In particular, WRF simulates both the timing and magnitude of the summer diurnal precipitation peak as well as ERA5 over most of the CONUS, except for a delayed diurnal peak over the Great Plains. As compared to ERA5, both the month and the magnitude of the precipitation peak annual cycle are remarkably improved in the downscaled WRF simulation. WRF slightly overestimates 3 and 24 h precipitation maximum over the CONUS, in contrast to ERA5, which generally underestimates these quantities mainly over the eastern half of the CONUS. Notably, WRF better captures the probability density distribution (PDF) of 3 and 24 h annual and seasonal maximum precipitation. WRF exhibits seasonally dependent precipitation biases across the CONUS, while ERA5's biases are relatively consistent year round over most of the CONUS. These results suggest that dynamical downscaling to a higher resolution improves upon some precipitation metrics but is susceptible to common regional climate model biases. Consequently, if used as input data for domain-specific models, we suggest moderate bias correction be applied to the dynamically downscaled product.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Distributions and characteristics of high-latitude field-aligned electron precipitation.

Satellite measurements of field-aligned auroral electron precipitation have been analyzed using 16 months of data from the OGO 4 auroral particles experiment. As can be seen from the moving satellite, the anisotropies are of short duration and are most likely to occur when particle fluxes are high. Field-aligned 2.3-keV electron precipitation is found in an oval-shaped region primarily in the nighttime hours; maximum probability is at about 70 deg invariant latitude near midnight, congruent to and poleward of the auroral optical emissions in these hours. This precipitation is found to be associated with the high-latitude boundary of auroral electron precipitation during substorm expansion and is characterized by a slightly harder and considerably more intense energy spectrum than typical isotropic precipitation.-

Berko, F. W.↗
NASA NTRS1972

Distributions and characteristics of high-latitude field aligned electron precipitation

Satellite measurements of field-aligned auroral electron precipitation were analyzed using 16 months of data from the OGO-4 auroral particles experiment. It was observed that the anisotropies are of short time duration and are most likely to occur when particle fluxes are high. Field-aligned 2.3 keV electron precipitation is found in an oval shaped region primarily in the nighttime hours, with a maximum probability at approximately 70 deg invariant latitude near midnight, congruent to and poleward of the auroral optical emissions in these hours. This precipitation was found to be associated with the high latitude boundary of auroral electron precipitation during substorm expansion and is characterized by a harder and more intense energy spectrum than typical isotropic precipitation.

Berko, F. W.↗
NASA NTRS2016

Development and Evaluation of High-Resolution Climate Simulations Over the Mountainous Northeastern United States

The mountain regions of the northeastern United States are a critical socioeconomic resource for Vermont, New York State, New Hampshire, Maine, and southern Quebec. While global climate models (GCMs) are important tools for climate change risk assessment at regional scales, even the increased spatial resolution of statistically downscaled GCMs (commonly approximately 1/ 8 deg) is not sufficient for hydrologic, ecologic, and land-use modeling of small watersheds within the mountainous Northeast. To address this limitation, an ensemble of topographically downscaled, high-resolution (30"), daily 2-m maximum air temperature; 2-m minimum air temperature; and precipitation simulations are developed for the mountainous Northeast by applying an additional level of downscaling to intermediately downscaled (1/ 8 deg) data using high-resolution topography and station observations. First, observed relationships between 2-m air temperature and elevation and between precipitation and elevation are derived. Then, these relationships are combined with spatial interpolation to enhance the resolution of intermediately downscaled GCM simulations. The resulting topographically downscaled dataset is analyzed for its ability to reproduce station observations. Topographic downscaling adds value to intermediately downscaled maximum and minimum 2-m air temperature at high-elevation stations, as well as moderately improves domain-averaged maximum and minimum 2-m air temperature. Topographic downscaling also improves mean precipitation but not daily probability distributions of precipitation. Overall, the utility of topographic downscaling is dependent on the initial bias of the intermediately downscaled product and the magnitude of the elevation adjustment. As the initial bias or elevation adjustment increases, more value is added to the topographically downscaled product.

climatology↗
NASA NTRS2010

Characterization of Cloud Water-Content Distribution

The development of realistic cloud parameterizations for climate models requires accurate characterizations of subgrid distributions of thermodynamic variables. To this end, a software tool was developed to characterize cloud water-content distributions in climate-model sub-grid scales. This software characterizes distributions of cloud water content with respect to cloud phase, cloud type, precipitation occurrence, and geo-location using CloudSat radar measurements. It uses a statistical method called maximum likelihood estimation to estimate the probability density function of the cloud water content.

Lee, Seungwon↗
DOE OSTI2020

Future projections and uncertainty assessment of precipitation extremes in the Korean peninsula from the CMIP5 ensemble

Abstract Projections of changes in extreme climate are sometimes predicted by multimodel ensemble methods that combine forecasts from individual simulation models using weighted averaging. One method to assign weight to each model is the Bayesian model averaging (BMA) in which posterior probability is used. For the cases of extreme climate, the generalized extreme value distribution (GEVD) is typically used. We applied the approach of GEV‐embedded BMA to a series of 35 years of the annual maximum daily precipitation data (both historical data and data gathered from simulation experiments for future periods) over the Korean peninsula as simulated by the models in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Simulation data under two Representative Concentration Pathway (RCP) scenarios, namely RCP4.5 and RCP8.5, were used. Observed data and 17 CMIP5 models for 12 gird cells in Korea have been examined to predict future changes in precipitation extremes. A simple regional frequency analysis of pooling observations from three stations in each cell was employed to reduce the estimation variance and local fluctuations. A bias correction technique using the regression‐type transfer function was applied to these simulation data. Return levels spanning over 20 and 50 years, as well as the return periods relative to the reference years (1971–2005), were estimated for two future periods, namely Period 1 (2021–2050) and Period 2 (2066–2095). From these analyses, relative increase observed in the spatially averaged 20‐year (50‐year) return level was approximately 23% (16%) and 45% (36%) in the RCP4.5 and RCP8.5 experiments, respectively, by the end of the 21st century. We concluded that extreme rainfalls will likely occur two times and four times more frequently in the RCP4.5 and RCP8.5 scenarios, respectively, as compared to in the reference years by the end of the 21st century.

Lee, Youngsaeng↗
NASA NTRS2017

The Effects of Vegetative Type, Edges, Fire History, Rainfall and Management in Fire-Maintained Ecosystems

The combined effects of repeated fires, climate, and landscape features (e.g., edges) need greater focus in fire ecology studies, which usually emphasize characteristics of the most recent fire and not fire history. Florida scrub-jays are an imperiled, territorial species that prefer medium (1.2-1.7 m) shrub heights. We measured short, medium, and tall habitat quality states annually within 10 ha grid cells that represented potential territories because frequent fires and vegetative recovery cause annual variation in habitat quality. We used multistate models and model selection to test competing hypotheses about how transition probabilities between states varied annually as functions of environmental covariates. Covariates included vegetative type, edges, precipitation, openings (gaps between shrubs), mechanical cutting, and fire characteristics. Fire characteristics not only included an annual presenceabsence of fire covariate, but also fire history covariates: time since the previous fire, the maximum fire-free interval, and the number of repeated fires. Statistical models with support included many covariates for each transition probability, often including fire history, interactions and nonlinear relationships. Tall territories resulted from 28 years of fire suppression and habitat fragmentation that reduced the spread of fires across landscapes. Despite 35 years of habitat restoration and prescribed fires, half the territories remained tall suggesting a regime shift to a less desirable habitat condition. Measuring territory quality states and environmental covariates each year combined with multistate modeling provided a useful empirical approach to quantify the effects of repeated fire in combinations with environmental variables on transition probabilities that drive management strategies and ecosystem change.

Breininger, David R.↗
DOE OSTI2022

Investigation on cloud vertical structures based on Ka-band cloud radar observations at Wuhan in Central China

Based on vertically pointing observations of Ka-band frequency-modulated continuous millimeter wave cloud radar (MMCR) in 2020, we investigate cloud vertical structures at Wuhan in central China. Case comparison indicates that the cloud top locations in the MMCR observation are largely consistent with those in satellite data. The precipitation has the occurrence frequency of 9.5% over the year, with the maximum value of 16.3% in July and the submaximal value of 14.7% in January, showing the significant influences of monsoons on precipitation at Wuhan. As the humid, cloudy and rainy climate, the probability of precipitation and non-precipitation clouds increases gradually from 53.9% in January to a large value of 71.5% in July. The non-precipitation clouds have the probability of 44.5% in the year, with two prominent peaks at the reflectivities of -35 to -30 dBZ around 12 km in summer and - 37– -32 dBZ around 10 km in spring. The cloud top can reach the heights of 14.49, 16.62, 13.38 and 11.73 km from spring to winter, respectively. The monthly mean cloud layer thickness is the largest (2.18 km) in May and September, and the smallest (1.36 km) in November. The seasonally averaged base and top heights and thickness of clouds have small diurnal variations. The high cloud is predominant in the warm months from May to September, and in the other cool months, the middle cloud has the most fraction. The quantitative investigation of clouds is helpful in improving the cloud parameterization in climate models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Development of ductile high-strength chromium alloys, phase 2

Strength and ductility were evaluated for chromium alloys dispersion hardened with the putative TaC, TaB, CbC, and CbB compounds. TaC and TaB proved to be the most potent strengtheners, but when combined, their effect far outweighed that produced individually. Tests at 1422 K (2100 F) on an alloy containing these two compounds at the combined level of 0.5 m/o revealed a 495 MN/sq m (70 ksi) tensile strength for wrought material, and a 100 hour rupture strength of 208 MN/sq m (30 ksi) when solution annealed and aged to maximize creep resistance. These levels of high temperature strength greatly exceed that reported for any other chromium-base alloy. The ductile-to-brittle transition temperature (DBTT) of the two phase strengthened alloy occurred at approximately 588 K (600 F) when heat treated to optimize creep strength and was not improved by fabrication to produce a wrought and recovered microstructure. The lowest DBTT measured on any of the alloys investigated was 422 K (300 F). Strengthening phases actually formed in Cr-Ta-B and Cr-Cb-B compositions are probable M2CrB2 (M=Ta or Cb) compounds of tetragonal crystal structure. The likely habit relationship between these compounds and chromium is postulated. Cube habit coherency was identified for TaC precipitation in chromium by electron microscopy. In another study, the maximum solubility of carbon in chromium was indicated to lie between 3/4 and 1 a/o and that of boron to be 1/2 a/o.

Filippi, A. M.↗
NASA NTRS1980

Analysis of the origin of Aufeis feed-water on the arctic slope of Alaska

The origin of water feeding large aufeis fields (overflow river ice) on the Arctic Slope of Alaska is analyzed. Field measurements of two large aufeis fields on the eastern Arctic Slope were taken during July of 1978 and 1979. Measurements of aufeis extent and distribution were made using LANDSAT Multispectral Scanner Subsystem (MSS) satellite data from 1973 through 1979. In addition, ice cores were analyzed in the laboratory. Results of the field and laboratory studies indicate that the water derived from aufeis melt water has a chemical composition different from the adjacent upstream river water. Large aufeis fields are found in association with springs and faults thus indicating a subterranean origin of the feed water. In addition, the maximum extent of large aufeis fields was not found to follow meteorological patterns which would only be expected if the origin of the feed water were local. It is concluded that extent of large aufeis in a given river channel on the Arctic Slope is controlled by discharge from reservoirs of groundwater. It seems probable that precipitation passes into limestone aquifers in the Brooks Range, through an interconnecting system of subterranean fractures in calcareous rocks and ultimately discharges into alluvial sediments on the coastal plain to form aufeis. It is speculated that only small aufeis patches are affected by local meteorological parameters in the months just prior to aufeis formation.

Hall, D. K.↗
NASA NTRS2019

Evaluating Precipitation Features and Rainfall Characteristics in a Multi-scale Modeling Framework

Cloud and precipitation systems over the tropics and subtropics are simulated with a multi-scale modeling framework (MMF) and compared against the TRMM radar precipitation features (RPFs) product. A methodology, in close analogy to the TRMM RPFs, is developed to analyze simulated cloud precipitating structures from the embedded two-dimensional cloud-resolving models (CRMs) within an MMF. Despite the two-dimensionality of the CRMs, the simulated RPFs population distribution, and horizontal and vertical structure are in good agreement with TRMM observations. However, some deficits are also found in the model simulations. The model tends to overestimate mean convective precipitation rates for RPFs with a size less than 100 km, contributing to the excessive precipitation biases in the warm pool and western Pacific, western and northern India Ocean, and eastern Pacific commonly found in most MMFs. For large features with a size greater than 150 km, both convective and stratiform rain rates are underestimated. The distribution of maximum radar echo top heights as a function of RPF size is well simulated except the model tends to underestimate the occurrence frequency of maximum heights greater than 15 km. The maximum echo top heights for convective cells embedded within large RPFs with a size greater than 150 km are also underestimated. The cyclic lateral boundary with a limited model domain generates artificial occurrences for RPFs with a size close to the model domain size, producing a significant contribution to the total rainfall due to their sizes. This cyclic lateral boundary effect can be easily identified and quantified in both probability and cumulative distribution functions of RPFs. The geophysical distribution of the population of the largest RPFs in the control experiment shows they are mainly located in the Subtropics but also partially contribute to the common MMF biases of excessive precipitation in the Tropics. Sensitivity experiments using CRMs with different domain sizes and different grid spacings show larger domains (higher resolution) tend to shift the RPFs distribution to large (small) sizes. The cyclic lateral boundary biases increase as CRM domain size decreases. The impacts of model horizontal and vertical resolution on simulated convective systems are also investigated.

Chern, Jiun-Dar↗
NASA NTRS2008

Diversity and Physiology of Siderophilic Cyanobacteria: Implication for the Bioenergetics

Prior to 2.4 Ga, global oceans were likely significantly enriched in soluble iron (Rouxel, Bekker, Edwards, 2005), a condition that is not conducive to the growth of most contemporary mesophilic cyanobacteria (CB). Recent studies of the mechanisms of iron-deficiency stress in CB suggest that contemporary mesophilic freshwater and marine B underwent long-term adaptation to a permanent decrease in soluble iron in the ocean environment (Boyer, et al., 1987; Braun, Hantke, and Koster, 1998). Of all extant environments, iron-depositing hot springs may constitute the most appropriate natural models for analysis of the transition of ancestral cyanobacteria (CB) or protocyanobacteria (PCB) (Olson, 2001) from anoxygenic photosynthesis to oxygenic one and biogeochemical processes in the late Archean and early Paleoproterozoic eras. In particular, Olson (2001) proposed the definition for PCB and postulated that the common ancestor of PCB and CB might well have used Fe(OH)+ as the principal electron donor for CO2 fixation (Widdel, et al., 1993; Ehrenreich and Widdel, 1994; Pierson and Olson, 1989; Olson, 2006). Olson (2001) proposed that the driving force for the evolution of RC2, in addition to RC1, was the necessity to use Fe(OH)+ effectively for CO2 fixation in the absence of reduced sulfur compounds. The global decrease of dissolved environmental reduced iron could have been the driving force for the transition from anoxygenic to oxygenic photosynthesis (Brown et al., 2007). Despite the insights into the ecology, evolutionary biology, paleogeobiochemistry, and astrobiology the examination of iron depositing hot springs (IDHS) could potentially provide, very few studies dedicated to the diversity and physiology of cyanobacteria inhabiting IDHS have been conducted. Here we describe the phylogeny, physiology and ultrastructure and biogeochemical activity of several recent CB isolates from two different greater Yellowstone area IDHS, e.g. LaDuke and Chocolate Pots. Phylogenetic analysis of 16S rRNA genes indicated that 6 of 12 new isolates examined could not be placed within established CB genera. Some of the isolates exhibited pronounced requirements for elevated iron concentrations, with maximum growth rates observed when 0.4-1 mM Fe(3+) was present in the media. However, the pronounced effect of iron limitation on the proliferation of siderophilic CB can be observed only after several passages through iron "free" media. TEM studies of several species of siderophilic CB revealed that the cultures JSC-3 and -11 are probably capable of some sort of pinocytosis of precipitated iron. This phenomenon may explain high tolerance of siderophilic CB to iron deficit. We also found that the stimulation of the growth of siderophilic CB by oxidized iron is accompanied by the decrease of O2 evolution by some species after addition Fe(2+) in iron "free" medium.

Brown, Igor↗
NASA NTRS1994

Studies of African wave disturbances with the GISS GCM

Simulations made with the general circulation model of the NASA/Goddard Institute for Space Studies (GISS GCM) run at 4 deg latitude by 5 deg longitude horizontal resolution are analyzed to determine the model's representation of African wave disturbances. Waves detected in the model's lower troposphere over northern Africa during the summer monsoon season exhibit realistic wavelengths of about 2200 km. However, power spectra of the meridional wind show that the waves propagate westward too slowly, with periods of 5-10 days, about twice the observed values. This sluggishness is most pronounced during August, consistent with simulated 600-mb zonal winds that are only about half the observed speeds of the midtropospheric jet. The modeled wave amplitudes are strongest over West Africa during the first half of the summer but decrease dramatically by September, contrary to observational evidence. Maximum amplitudes occur at realistic latitudes, 12 deg - 20 deg N, but not as observed near the Atlantic coast. Spectral analyses suggest some wave modulation of precipitation in the 5-8 day band, and compositing shows that precipitation is slightly enhanced east of the wave trough, coincident with southerly winds. Extrema of low-level convergence west of the wave troughs, coinciding with northerly winds, were not preferred areas for simulated precipitation, probably because of the drying effect of this advection, as waves were generally north of the humid zone. The documentation of African wave disturbances in the GISS GCM is a first step toward considering wave influences in future GCM studies of Sahel drought.

Druyan, Leonard M.↗