FEBRUARY 2004 297U N D E R W O O D E T A L .

q 2004 American Meteorological Society

A Multiple-Case Analysis of Nocturnal Radiation-Fog Development in the CentralValley of California Utilizing the GOES Nighttime Fog Product

S. JEFFREY UNDERWOOD

Southern Illinois University, Carbondale, Illinois

GARY P. ELLROD

NOAA/NESDIS, Camp Springs, Maryland

AARON L. KUHNERT

Southern Illinois University, Carbondale, Illinois

(Manuscript received 22 January 2003, in final form 21 August 2003)

ABSTRACT

Radiation fog in the Central Valley of California has received very little attention in terms of climatologicalresearch. This study uses the Geostationary Operational Environmental Satellite (GOES) nighttime fog productto develop a sequence of images and datasets that reveal patterns of nocturnal radiation-fog development in theCentral Valley. Twenty long-lived, spatially extensive radiation-fog episodes, occurring from October throughJanuary, were selected for the period of 1997–2000. Mean hourly parameters for fog cover, fog developmentrate, and vertical development were calculated for the 20 episodes in the Central Valley. The study region isseparated into five analysis divisions oriented from south to north for spatial comparisons within the valley.Large-scale radiation fog begins developing before 1800 LST, and rates of development vary widely from southto north. Radiation fog develops earlier and covers a larger area of the southern valley as compared with thecentral and northern portions of the valley. The horizontal extent of radiation fog is maximized at 0600 LST inthe southern valley and near midnight in the central and northern parts of the valley. Vertical developmentreaches 300 m with regularity in the southern valley. Radiation-fog development of greater than 300 m occursprimarily in the early morning hours. Vertical development ‘‘bursts’’ are also observed in the southern valleyduring the morning hours. Climatologically important conditions for radiation-fog development in the CentralValley include cool 1600 LST surface temperatures, moisture availability as reflected by 1600 LST dewpointtemperatures, early evening surface cooling trends, the rapidity with which mean relative humidity reaches 90%,and the presence of cool, dry air aloft (700–500 hPa).

1. Introduction

Radiation fog routinely develops in various parts ofthe United States throughout the year (Carson and Hardy1963; Hardwick 1973; Ahrens 1994). These fog epi-sodes have profound implications for human activityand the physical environment. Hazardous ground trans-portation scenarios resulting from reduced visibility area major concern in fog-prone areas, and delays in airportschedules are common in areas with frequent radiationfog (Peace 1969; Baker et al. 2002; Swenson 2002).Long-lived spatially extensive radiation-fog episodesalso have the potential to deposit suspended and dis-solved pollutants, and these large-scale fogs influence

Corresponding author address: Dr. S. Jeffrey Underwood, De-partment of Geography, 4442 Faner Hall, Southern Illinois University,Carbondale, IL 62901-4514.E-mail: jeffreyu@siu.edu

the diurnal surface energy budget (McLaren et al. 1988;Oke 1988; Collet et al. 1999). In contrast to potentialhazards posed by dense fog, fog water intercepted byvegetation is a major component in the seasonal hydro-logical balance in regions that frequently experiencesuch episodes (Azevedo and Morgan 1974; Cavelier etal. 1996; Bruijnzeel and Veneklaas 1998).

An area of the United States where the occurrence oflong-lived, spatially extensive radiation fog is very com-mon is the Central Valley region of California (Sucklingand Mitchell 1988). National Climatic Data Center(NCDC 2002) daily observation records show that, fromOctober through March (for season), individual loca-tions across the Central Valley report upward of 25 fogdays per season. These radiation fogs occur primarilywith temperatures above 08C in the Central Valley sothat the majority of radiation-fog episodes in the valleyare composed of liquid droplets and few are ice fogs.Although radiation fog is the most common winter

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

298 VOLUME 43J O U R N A L O F A P P L I E D M E T E O R O L O G Y

weather hazard in central California, the phenomenonhas been inadequately investigated in a research context.Our limited understanding of the subject is reflected inthe small number of published works in the climato-logical and meteorological literature that focus exclu-sively on radiation fog in the inland valleys of California(Holets and Swanson 1981).

The purpose of this study is to provide a temporaland spatial framework for understanding radiation-fogdevelopment in California. The study will investigatenocturnal formation characteristics of radiation-fog ep-isodes that are both long lived and spatially extensiveacross the Central Valley. By looking exclusively atnocturnal development of these large episodes, the studyalso provides a context for using the 4-km spatial res-olution Geostationary Operational Environmental Sat-ellite (GOES) nighttime fog product (NFP) for clima-tological analysis. The GOES NFP is currently in useat National Weather Service field offices and has beencited in the literature primarily when the product is inforecast mode or when the product is undergoing fieldverification (Eyre et al. 1984; d’Entremont 1986;d’Entremont and Thompson 1987; Ellrod 1994; Wetzellet al. 1996; St. Jean 1997).

2. Background

a. Radiation-fog environment

Radiation-fog formation depends on a complex com-bination of boundary layer and synoptic-scale condi-tions that often have a diurnal and seasonal nature (Mey-er and Lala 1990; Meyer et al. 1986). Fitzjarrald andLala (1989) describe the fog environment in terms ofappropriate boundary layer temperature, humidity, windspeed, and wind direction, as well as near-surface ra-diative cooling profiles, advection currents, and char-acteristics of the underlying surface. Radiation-fog ini-tiation is modulated by surface radiative fluxes, verticalmixing of heat and moisture, vegetation interactions,and topographic effects (Duynkerke 1991). Radiationfog may also develop, dissipate, and redevelop duringthe same nocturnal cycle (Welch and Cox 1986). Theprocess of radiation-fog formation is described for 11fog episodes in the Chemung River Valley in New Yorkby Pilie et al. (1975b). The authors describe a low-leveltemperature inversion that develops just after sunset andfluctuates slightly in intensity until fog formation. Thisinversion is suggested to be most intense in the lowest0.1 m above the ground surface. The development andtiming of the low-level temperature inversion, the rateof fog growth, and valley wind patterns are importantfactors for fog formation and fog persistence in largemountain–valley climate systems (Moore et al. 1987).

Meteorological processes such as radiative flux di-vergence and surface dew formation have been modeledto gain insight into the temporal, often nocturnal, aspectsof fog onset (Fisher and Caplan 1963; Lala et al. 1975).

In addition, microphysical parameters have been usedto simulate selected physical interactions in the bound-ary layer that promote nocturnal fog development (Pilieet al. 1975a; Brown 1980; Musson-Genon 1987). Bottet al. (1990) used a one-dimensional approach to sim-ulate the timing of the fog life cycle and also estimatedfog-top height.

Forecasting radiation fog is still somewhat problem-atic because local topography, moisture availability,vegetation, and soil conditions introduce spatial vari-ability into model results and forecast products (Golding1993; Meyer and Rao 1999). In addition, the analyticalprecision that is required to diagnose humidity levels,condensation rates, and radiative exchanges adequatelyis very demanding in a forecast context (Bergot andGuedalia 1994). A number of approaches, including de-velopment of local- and regional-scale fog climatolog-ical descriptions, have proven valuable for forecastingonset time and dissipation rates (Court and Gerston1966; Hardwick 1973; Croft et al. 1997). Numericalforecasting simulations carried out by Guedalia and Ber-got (1994) confirm the difficulty in radiation-fog pre-diction. The simulations emphasized the need for ac-curate initialization data and very precise nocturnalcooling information.

b. Satellite remote sensing of fog and low stratusclouds

Once fog has developed, remote observation andanalysis of cloud tops and cloud droplet parameters maybe made by using satelliteborne sensors and sounders(Arking and Childs 1985; Mead et al. 1989; Menzel andPurdom 1994; Wetzel et al. 1996; Lee et al. 1997). Atregional scales, images produced by a number of sen-sors, including The National Oceanic and AtmosphericAdministration GOES and the Advanced Very HighResolution Radiometer (AVHRR) imagers, are adequateto resolve fog development and to convey fog and lowstratus boundaries accurately (Gustafson and Wasser-man 1976; Bendix 2001).

Introductory meteorology texts routinely display sat-ellite images of radiation fog that extends across theCentral Valley of California (Aguado and Burt 2001).These images are used to illustrate both the spatial ex-tensiveness of radiation fog and the utility of spacebornesensors for viewing such phenomena. Lee (1987) ob-served Central Valley fog episodes using 4-km-spatial-resolution visible imagery and found variability in fogcoverage and fog dissipation characteristics amongevents and across a single event. Highlighting this var-iability, Lee (1987) described the ‘‘urban clear islandeffect,’’ in which fog was absent or dissipated morequickly from urban areas in the Central Valley duringwidespread fog episodes.

The GOES sensors have the spatial (1 and 4 km) andspectral (0.65, 3.9, and 10.7 mm) resolution to provideboth daytime and nighttime observations of cloud-top

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

FEBRUARY 2004 299U N D E R W O O D E T A L .

reflectivity and emission (Rao et al. 1990; Kidder andVonder Haar 1995). Analysis and forecasting of fog andstratiform-cloud development during daylight hours ispracticed using bands in the visible wavelengths (0.65mm) from the GOES imagers. The 3.9-mm near-infraredband can also be used during daylight hours if the ther-mal component of the radiance is removed (Arking andChilds 1985; Rawlings and Foot 1990; Kleespies 1995).

To view low stratus clouds and fog at night, two IRbands from the GOES or AVHRR imagers can be usedto produce the NFP (Putsay et al. 2001). The GOESNFP calculates the brightness temperature difference be-tween GOES band 4 (10.7 mm) and band 2 (3.9 mm)(Ellrod 1995, 2000). The brightness temperature valuesfor low clouds and fog differ between bands in partbecause of the emissivity differences induced by cloudthickness and droplet size distribution (Hunt 1973; Pin-nick et al. 1978; Arnott et al. 1997). The NFP exploitsthe lower cloud emissivity in the 3.9-mm band as com-pared with the 10.7-mm band and calculates a value thatnot only suggests the presence or absence of fog atsingle pixel resolution but also estimates the verticaldepth of the radiation fog (Ellrod 1994).

3. Study area

The study area for this project includes the traditionalboundaries of the San Joaquin and Sacramento Val-leys—together called the Central Valley region (Holetsand Swanson 1981; Lee 1987). The Central Valley isrelatively uniform in elevation through its center and isbounded by two large topographic barriers—the SierraNevada to the east, with elevations that can exceed 4000m, and the California Coast Range to the west, withelevations to 1500 m (Fig. 1). The Sacramento delta isthe largest break in the valley boundary and opens tothe west toward the San Francisco Bay. For analysispurposes, the valley is divided into five analysis divi-sions, each of which contain at least four CaliforniaIrrigation Management Information System (CIMIS2000) mesonetwork surface observation stations and aregional population center with a first-order meteoro-logical observation station.

4. Analysis procedures

a. Data acquisition

The data for this study are composed of surface ob-servations and GOES images. The NCDC surface datafor stations in the Central Valley were used to identifyfog events that appeared to be long lived and spatiallyextensive during fog seasons from 1997/98 through2001/02. The surface data include current weather re-ports and visibility estimates. For each fog episode,GOES imager data were acquired from the Space Sci-ence and Engineering Center at the University of Wis-consin—Madison. Additional surface meteorological

data were acquired from CIMIS. GOES images from1800 to 0600 LST represent the nocturnal cycle forpurposes of this analysis. Local sunset time does varyfrom October through March over the latitudes of thestudy area. However, for ease of analysis, the authorsused 1800 LST as local sunset and 0600 LST for localsunrise. It is likely that some variability was introducedinto the study by generalizing local sunrise and sunset.

The GOES data for each event were downloaded andarchived using the Man Computer Interactive Data Ac-cess System (McIDAS; Suomi et al. 1983). Image qual-ity control consisted of manual and digital tests for prop-er coverage and navigation, as well as inspections forimage disruptions. In addition to rejection for failure tomeet quality-control standards, images were also re-moved if extensive cirrus cloud cover was present dur-ing the nighttime hours. The primary data-quality andimage-usability issues consisted of cirrus interruptionand sensor malfunctions (no data). Because the GOES10.7-mm band is sensitive to dust (GOES dust identi-fication uses 10.7–12-mm product), it is reasonable toassume that on occasion the 10.7-mm channel may havebeen influenced by the dust that is commonly suspendedin the lower troposphere over the Central Valley. Forthis study, however, dust concentration was not consid-ered when using the 10.7- and 3.9-mm infrared images.

b. Identification of events

Hourly observations of current weather and visibilityconditions from Bakersfield (BFL), Fresno (FAT), Mer-ced (MER), Sacramento (SMF), and Chico (CIC), Cal-ifornia were used to identify long-lived, spatially ex-tensive radiation-fog episodes. These stations span theCentral Valley from south to north and represent areasof population concentration. The ‘‘current weather’’ re-ports were examined for these stations for fog seasonsfrom 1997/98 through 2001/02. An extensive fog epi-sode was identified when at least three of the five sta-tions simultaneously reported fog with visibility reduc-tion to 1 mile for three consecutive nocturnal hours.

c. Nighttime-fog-product calculation

Calculation of the GOES NFP is discussed in detailin Ellrod (1995). In the current study, the GOES NFPis processed using IR images that were calibrated to astandard navigation and projection (Mather 1999). Thetemporal pairs of 10.7- and 3.9-mm IR images producethe GOES NFP as follows:

DT 5 (T 2 T ),b10.7 b3.9 (1)

where Tb10.7 is the brightness temperature for GOES IRchannel 4, Tb3.9 is the brightness temperature for GOESIR channel 2, and DT represents the difference in bright-ness temperature between the two IR images.

Positive DT values represent pixels with the GOESNFP fog signature. Table 1 details the vertical-fog-de-

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

300 VOLUME 43J O U R N A L O F A P P L I E D M E T E O R O L O G Y

FIG. 1. Study area (Central Valley of California) including the five subunits (rectangles) used in theanalysis of the GOES NFP data.

TABLE 1. Estimates of radiation-fog depth associated with particularDT values. The estimates are based on the work of Ellrod (1994,2000) and have not been field verified in the Central Valley of Cal-ifornia.

NFP calculated DT Vertical development (m)

DT 1

DT 2

DT 3

DT 4

DT 5

DT 6

,100100–200200–300300–400400–500

.500

velopment estimates associated with the GOES NFP DTvalues. Satellite-estimated fog and stratus depth havebeen compared with aircraft observations in areas out-side the Central Valley over the period of 1997–2001(Ellrod 2000). Results from a linear regression analysisusing 73 pairs of satellite estimates and aircraft obser-vations produced a statistically significant r2 value of0.625 for the relationship (DT vs cloud depth at 100-mintervals) as listed in Table 1 (Ellrod 2000).

d. Analysis of radiation-fog characteristics

A brief synoptic analysis was performed to determinethe general circulation patterns that exist during the noc-

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

FEBRUARY 2004 301U N D E R W O O D E T A L .

turnal fog-development cycle. The analysis was limitedto surface conditions, 850-hPa heights and wind, and500-hPa heights and wind for the eastern Pacific Oceanand the western United States for the dates of spatiallyextensive fog episodes (Yarnal 1994).

To illustrate the spatial and temporal character of ra-diation fog, the GOES NFP images for a representativefog event were sequenced from sunset to sunrise andwere displayed with fog-depth contours. The spatial ex-tent of each fog episode was measured using the ,100-m contour. The major and semimajor axes of continuousfog coverage were identified from the edges of the,100-m contour.

To describe further the spatial character of radiationfog in the Central Valley, the study area was partitionedinto five analysis divisions whose dimensions are 35 335 pixels (GOES 4-km pixels). The divisions were ar-ranged south–north. The fog cover percentage Cp wascalculated for each division as follows:

C 5 DT /DT ,p obs max (2)

where DTobs is the observed number of pixels with DTvalues greater than or equal to 1, and DTmax is the max-imum number of pixels, out of 1225 (35 3 35 pixels),that are covered with GOES NFP–identified fog for aparticular analysis division. Because the five analysisdivisions do not have equal distributions of foggy pixels,the Cp allows fog cover to be analyzed in each divisionbased on the observed maximum coverage in that di-vision, thus providing uniformity in analysis.

Time-relative mean fog-depth values were also cal-culated at the pixel scale for each of the five analysisdivisions. Mean fog-depth values were generated for theperiod of 1800–0600 LST. These values were used todescribe the coverage characteristics and rates of fogdevelopment. The vertical development characteristicswere addressed using the vertical development ratio,which estimates the proportion of pixels covered with‘‘deeper’’ fog as compared with pixels covered withmore ‘‘shallow’’ fog layers in an analysis division. Thevertical development ratio (DTR) takes the form of

DT 5 (DT 1 DT 1 DT )/(DT 1 DT 1 DT ),R 4 5 6 1 2 3

(3)

where DT1, DT2, and DT3 represent the frequency ofpixels with a GOES NFP fog signature for shallow ra-diation fog, and DT4, DT5, and DT6 represent the fre-quency of pixels with the GOES NFP signature for deep-er-developing radiation fog. A ratio value very close to0 represents an analysis in which shallow fog dominatesthe study area. A ratio of 1.0 represents a situation inwhich shallow fog and deep fog cover an equal portionof the study area, and ratio values greater than 1.0 rep-resent scenarios in which deeper radiation fog coversmore of the analysis division.

Last, mesoscale surface meteorological observationswere used to determine the nocturnal characteristics ofselected variables during extensive fog development.

The variables used in this portion of the analysis wereobtained from the CIMIS network. The meteorologicalvariables are surface temperature (8C), dewpoint tem-perature (8C), dewpoint depression (8C), wind direction(degrees from north), and wind speed (m s21). Hourlyobservations from four CIMIS stations per analysis di-vision were used to produce mean fog-episode meteo-rological values for each division. The trends in themean meteorological values act as surrogates for phys-ical processes that occur in the boundary layer. In thediscussion that follows, the meteorological observationsare used to suggest the processes that lead to fog onsetand maintenance across the study area.

5. Findings

a. Overview of the 20 radiation-fog episodes

Identification of long-lived spatially extensive fog ep-isodes, using the criteria set out above, produced 31events from the fog seasons of 1997–2002. Twenty ofthe 31 events met the requirements for spatial extentand image quality and had cirrus-free coverage from1800 through 0600 LST. It is likely that a number ofspatially extensive and long-lived episodes have beenomitted from this analysis using such restrictive criteria.However, 20 nocturnal fog episodes is a sufficient sam-ple for a detailed radiation-fog analysis, because pastradiation fog studies have included as few as one epi-sode (Fitzjarrald and Lala 1989).

Table 2 provides a brief description of each of the 20radiation-fog events. The mean south–north extent offog across the study area is 452 km, and the mean east–west extent is 155 km. For the 20 events that make upthe current study, the most prominent synoptic-scale sur-face feature during fog development is a high pressurecenter usually located near 42.38N, 117.88W. The av-erage surface pressure associated with this high pressurecenter is 1033 hPa, with a range from 1019 to 1045 hPaover the 20 episodes. The mean upper-air pattern, asdescribed by the 500-hPa flow, consists of a highly am-plified ridge with its axis located near 120.88W. Geo-potential heights at the 500-hPa level across the CentralValley are estimated from 5550 to 5850 gpm, with amean value of 5718 gpm during fog development.

b. Central Valley radiation-fog case study (25November 2000)

Figure 2a is the 1800 LST GOES NFP image for 24November 2000. This frame illustrates the initial stageof nocturnal radiation-fog development (near local sun-set). Fog development is spatially limited at this time,with fog west of FAT extending 227 km south–northand 147 km east–west. The fog is vertically developedto approximately 300 m. The contours around the mainbody of fog represent fog that is less than 100-m thick.

Late-afternoon temperatures on 24 November 2000

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

302 VOLUME 43J O U R N A L O F A P P L I E D M E T E O R O L O G Y

TABLE 2. General meteorological characteristics associated with the development of the 20 radiation-fog events analyzed in this study.The spatial extent of fog cover was estimated using GOES NFP images with contoured depth intervals.

Event date

Spatial extent(0600 LST)

South–north(km)

East–west(km)

500-hPa ridge axis(0400 LST)

500-hPa heights acrossvalley (0400 LST)

(gpm)Surface pressure analysis

(0400 LST)

31 Oct 2000 501 214 1248W (northeast tilt) 5600–5700 1024-hPa high at 488N, 1158W31 Oct 2001 258 147 1258W (north–south oriented) 5700–5750 1019-hPa high at 408N, 1208W12 Nov 1998 196 188 1268W (north–south oriented) 5700–5750 1030-hPa high at 428N, 1178W18 Nov 2001 510 186 1208W (north–south oriented) 5750–5800 1036-hPa high at 508N, 1178W20 Nov 1999 480 229 1028W (northeast tilt) 5650–5750 1025-hPa high at 378N, 1108W25 Nov 2000 630 175 1178W (northeast tilt) 5700–5750 1030-hPa high at 438N, 1158W

5 Nov 1998 200 195 1138W (north–south oriented) 5700–5750 1033-hPa high at 408N, 1408W18 Dec 2000 341 120 1248W (north–south oriented) 5800–5850 1043-hPa high at 458N, 1168W19 Dec 2001 375 124 1288W (north–south oriented) 5550–5700 1045-hPa high at 508N, 1168W22 Dec 1998 457 144 1298W (northeast tilt) 5500–5600 1039-hPa high at 438N, 1158W25 Dec 2000 393 118 1238W (north–south oriented) 5700–5750 1036-hPa high at 428N, 1188W26 Dec 2001 415 132 1158W (north–south oriented) 5700 1040-hPa high at 428N, 1148W

2 Jan 2000 642 200 1268W (north–south oriented) 5550–5650 1032-hPa high at 408N, 1308W10 Jan 1999 694 160 1258W (north–south oriented) 5800 1030-hPa high at 408N, 1188W11 Jan 2002 611 122 1228W (north–south oriented) 5800 1038-hPa high at 438N, 1158W16 Jan 1997 475 130 1228W (north–south oriented) 5650 1040-hPa high at 428N, 1148W21 Jan 1998 546 210 1238W (north–south oriented) 5550 1034-hPa high at 398N, 1188W25 Jan 1998 489 158 1238W (north–south oriented) 5700–5750 1034-hPa high at 418N, 1198W28 Jan 1999 342 51 1198W (northeast tilt) 5600–5650 1032-hPa high at 408N, 1178W

3 Jan 2002 490 115 1108W (north–south oriented) 5600–5650 1032-hPa high at 398N, 1128WMean value 452 155 120.88W 5718 1033.6-hPa high at 42.38N,

117.88WStd dev 139 43 6.68 76 6.4-hPa and 3.58, 6.58

→

FIG. 2. The (a) 1800 LST 24 Nov 2000, (b) 0000 LST 25 Nov 2000, and (c) 0600 LST 25 Nov 2000 GOES NFP images of developingradiation fog. The contour lines represent fog depth, and five Central Valley cities that lend their names to the analysis divisions are identified(see text for definitions).

at both FAT and MER are lower when compared withthe other valley divisions. At FAT 1400 LST temper-ature is 11.78C, and at MER it is 9.88C. The other sta-tions in the study report 1400 LST temperatures of 14.58(BFL), 15.48 (SMF), and 13.78C (CIC). The colder af-ternoon temperatures in the middle portion of the valley(FAT and MER) suggest that these areas should developradiation fog more rapidly with even marginal radiativecooling. With no sounding data available for the CentralValley proper, the Oakland, California (KOAK), sound-ing was used to assess the vertical profile of the lowertroposphere. The 0000 UTC (1600 LST) and 1200 UTC(0400 LST) soundings show westerly flow from the 850-through 500-hPa level (Fig. 3). The westerly flow aloftis very dry, with 700-hPa dewpoint depression at 108Cat 1600 LST. This dry air aloft was also observed onother western U.S. soundings [Deer Park, Washington(KDEW), and Mercury, Nevada (KDRA)] that are eastof the Central Valley. A large high pressure center withclosed isobars is located over the Great Basin at sunseton 24 November 2000 as well. The central surface pres-sure for this Great Basin high is 1030 hPa, and the highpressure dome extends prominently through the 850-hPa level. Wind speeds at 850 hPa were estimated at2.5 m s21 across California from 1600 to 0400 LST.

Figure 2b is the GOES NFP image for midnight dur-ing the 25 November 2000 fog episode. Radiation fogcovers a large portion of the San Joaquin Valley at thistime. The south–north extent is approximately 319 km,and the east–west coverage is 126 km. Fog has alsoformed near BFL at midnight, and there are patches offog extending northward from MER. Rapid radiativecooling from 1800 to 0000 LST at BFL produces surfacetemperatures of 2.18C at midnight. This temperature ob-servation is more similar to the 0000 LST temperatureof 2.28C at FAT. Temperatures at both SMF and CIC,however, do not cool substantially from sunset to mid-night. The SMF temperature at 0000 LST is 6.18C, andthe CIC temperature is 5.68C. The slower cooling trendsin the northern valley may in part explain the lack ofradiation-fog development during the evening hours.

Vertical development at 0000 LST is similar to thatexhibited at 1800 LST, with fog tops to 200 m acrossthe central portion of the valley. The fog cover extendingsouthward is vertically developed to less than 100 m,while the fog east of SMF has developed to 100 and200 m over limited areas. Also of note are the embeddedpixels that suggest vertical development to 300 m withinthe main body of fog from FAT to MER.

Figure 2c illustrates spatially extensive radiation fog

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

FEBRUARY 2004 303U N D E R W O O D E T A L .

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

304 VOLUME 43J O U R N A L O F A P P L I E D M E T E O R O L O G Y

FIG. 3. KOAK soundings for 1600 LST 24 Nov 2000 and 0400 LST 25 Nov 2000.

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

FEBRUARY 2004 305U N D E R W O O D E T A L .

across most of the Central Valley near sunrise (0600LST) on 25 November 2000. The south–north axis offog cover now measures 630 km, and the east–west spanis 175 km near SMF. This particular fog episode extendsacross the Sacramento delta and into the San FranciscoBay area. The fog in the bay area cannot be assumedto have formed under the same radiative conditions asthe valley fog to the east, and so this is treated as ahybrid fog episode west of SMF.

All five of the valley population centers are withinthe main body of fog at 0600 LST, and fog depth hasincreased since midnight. Extensive areas of 300-m de-velopment are indicated between BFL and FAT, and alsonorth of MER. The extreme northern portions of theSacramento Valley near CIC have vertical developmentindicated to 200 m with a smaller area to 300 m. Surfacecooling during the morning hours produces tempera-tures of 20.28C at BFL, 0.68C at FAT, 1.48C at MER,4.38C at SMF, and 5.88C at CIC at 0600 LST. The 1200UTC (0400 LST) KOAK sounding indicates a strongdrying profile from approximately 900 to 550 hPa. Thewinds through this level are very weak and are fromthe west-southwest. This profile, along with buildinghigh pressure over the Great Basin and weak surfacewinds, suggests that processes are in place that favormaintenance of the fog cover over the Central Valley.

c. Nocturnal characteristics of radiation fog—Meanspatial coverage

The area covered by radiation fog in each analysisdivision is represented by the coverage percentage (Cp)whose calculation is detailed in Eq. (2). The maximumobserved coverage, from which Cp is calculated, is 1196pixels for the BFL division, 1114 for FAT, 1085 forMER, 933 for SMF, and 790 for the CIC division.

Figure 4 shows the Cp calculated for each of the anal-ysis divisions. The BFL division reaches 50% meancoverage at 0300 LST and remains above this level forthe remainder of the nocturnal cycle, peaking in cov-erage at 0600 LST. The standard deviation around thehourly mean Cp at BFL is variable from 1800 to 0000LST but becomes more stable after midnight.

Maximum coverage at FAT is realized at 0600 LSTat 53%. Lower Cp standard deviations are realized dur-ing the morning hours when the areal coverage is great-est, suggesting that coverage variability is minimized ascoverage increases and meteorological conditions be-come more favorable for fog development and main-tenance.

The MER division peaks in Cp at 0000 LST and againbetween 0400 and 0500 LST. The standard deviationvalues suggest that the morning hours are less variablethan the evening hours in terms of radiation-fog cov-erage.

Mean Cp at SMF peaks at 2300 LST at 35%, and thefinal 4 h of the study period are nearly equal. Similarto the southern valley analysis, the SMF standard de-

viation around the hourly mean Cp suggests that fogdevelopment during the morning hours is less variablethan during the evening hours.

The most extensive coverage at CIC occurs at 2300LST at 32%. The hourly standard deviation analysissuggests that spatial coverage is variable at all hours,with no preference for evening or morning. This vari-ability in Cp reflects the mean surface meteorologicalobservations at CIC, where temperatures during the 20fog episodes did not cool as rapidly as they did in theother divisions (Fig. 5). In addition, mean relative hu-midity was lower than in the other divisions and themean wind speed was higher, remaining above 2.0 ms21 over the entire nocturnal cycle. The surface mixinginduced by higher wind speeds could offset radiativecooling and keep nocturnal temperatures and dewpointdepression values higher at CIC.

The Cp trends in the divisions other than CIC are mostlikely attributable to the dry, cool, and clear midtro-posphere, which promotes radiative cooling throughoutthe valley, and greater moisture availability in the south-ern valley. Figure 6 shows that late-afternoon dewpointtemperatures at both BFL and FAT (southern valley di-visions) are much higher than in the other analysis di-visions. The mean relative humidity trends are similaracross the study area from 1600 through 1900 LST butdiverge noticeably from 1900 through 0700 LST (Fig.7). The BFL and FAT analysis divisions rapidly reachmean relative humidity values of 90% while MER, SMF,and CIC are delayed in reaching 90% relative humidity.Radiation-fog development follows a similar trend asthe cooling and humidity trends across the divisions—forming more readily and maintaining coveragethroughout the nocturnal cycle across BFL and FAT anddeveloping more slowly and dissipating slightly duringthe morning hours across MER, SMF, and CIC.

d. Nocturnal characteristics of radiation fog—Meanrate of fog development

Figure 8 illustrates the hourly rates of fog-coverchange for each of the five analysis divisions. The di-visions are represented hourly from top to bottom onthe graphic in the following order: BFL, FAT, MER,SMF, and CIC. The hourly rate of coverage change forthe BFL division is positive for 10 of the 12 hourlyintervals. Radiation fog growth is less intense after mid-night, with only 1 h with a rate greater than 5%, ascompared with 2 h with rates greater than 7% from 1800to 0000 LST. The fog expansion rate is also less variableafter midnight, reflecting the stability of the environ-ment in terms of air temperature and dewpoint depres-sion (Figs. 5 and 9, respectively). Wind speeds are alsoat a nocturnal low during the morning hours at BFL(Fig. 10).

The FAT division has 10 h with positive rates (Fig.8). The two negative intervals are 0000–0100 and 0100–0200 LST. FAT experiences its greatest fog-cover ex-

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

306 VOLUME 43J O U R N A L O F A P P L I E D M E T E O R O L O G Y

FIG. 4. Areal coverage percentages (Cp) for each of the five analysisdivisions. The Cp values were calculated based on the maximumobserved coverage (pixels with GOES NFP fog signature) for eachdivision.

pansion from 1800 to 1900 LST, which coincides witha rapid temperature decline and increasing relative hu-midity levels. Even though the calculation of mean val-ues for the 20 episodes dilutes the finer details of eachepisode’s nocturnal cycle, the mean values do suggestthat FAT experiences increasing wind speeds between

0000 and 0200 LST (Fig. 10). This period also exhibitsa midcycle erosion of radiation fog at FAT, which sug-gests that some low-level mixing may be present duringthe early morning. This process ceases, however, andpositive fog-development rates recover from 0300 LSTto sunrise.

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

FEBRUARY 2004 307U N D E R W O O D E T A L .

FIG. 5. Mean hourly surface temperature (8C) trends for each ofthe analysis divisions. The mean values were calculated using fourCIMIS stations in each analysis division.

FIG. 7. Mean hourly relative humidity (%) trends for each of theanalysis divisions. The mean values were calculated using four CIMISstations in each analysis division.

FIG. 6. Mean hourly surface dewpoint temperature (8C) trends foreach of the analysis divisions. The mean values were calculated usingfour CIMIS stations in each analysis division.

FIG. 8. Radiation-fog development rates for each of the five analysisdivisions. The rates were calculated based on hourly changes in Cp.The divisions are represented from top to bottom (BFL, FAT, MER,SMF, CIC) for each hour.

The MER division has 8 of 12 intervals with positiverates of fog development. All four negative rates areduring morning intervals. MER is somewhat unique inthat the division’s mean relative humidity levels re-mained below 90% until 0300 LST. This observation isreflected in the dewpoint temperature trend, whichshows MER having the lowest mean dewpoint temper-ature for any division from midnight until 0600 LST(Fig. 6).

The SMF division has nine hourly intervals with pos-itive radiation-fog growth rates. The highest growth rateis 7.75% at 2100–2200 LST, and the most negative rateis 5.9%. Temperature and relative humidity trends atSMF are more similar to those in BFL and FAT, andthe fog growth rates also follow a trend more similarto the southern valley divisions.

The CIC division has positive radiation-fog growth

during 8 of the 12 hourly intervals. The highest positiverate at CIC is 4.4% at 2100–2200 LST. The lowestnegative growth is found during 2300–0000 LST at4.1%. The rates are comparable to the other divisions;however, the total maximum coverage at CIC is stillmuch less than the other divisions (790 pixels).

This analysis suggests that radiation-fog developmentrates are positive across all divisions during the eveninghours and that positive development rates are greatestin the southern divisions (BFL, FAT). Surface meteo-rological conditions in the southern valley, such as cool1600 LST surface temperatures and higher moisture lev-

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

308 VOLUME 43J O U R N A L O F A P P L I E D M E T E O R O L O G Y

FIG. 9. Mean hourly dewpoint depression (8C) trends for each ofthe analysis divisions. The mean values were calculated using fourCIMIS stations in each analysis division.

FIG. 10. Mean hourly surface wind speed (m s21) trends for eachof the analysis divisions. The mean values were calculated using fourCIMIS stations in each analysis division.

FIG. 11. Hourly vertical development ratio (DTR) for the five anal-ysis divisions. The DTR was calculated using pixels with deep de-veloping radiation fog (greater than 300 m) and pixels with moreshallow developing radiation fog (less than 300 m).

els (dewpoint temperatures), allow the BFL and FATdivisions to develop radiation fog very rapidly after sun-set, as revealed by the GOES NFP. Negative rates offog-cover change are most likely during the middle ofthe nocturnal cycle. Midcycle wind speed increases atFAT and MER suggest that in the larger east–west ex-panses of the Central Valley (nearer FAT and MER)low-level mixing is available to erode a portion of thefog cover.

e. Nocturnal characteristics of radiation fog—Vertical development

Figure 11 is a graphical summary of the mean verticaldevelopment ratio DTR for each of the five analysis di-visions from 1800 to 0600 LST. More shallow fog de-velopment dominates the spatial and temporal distri-bution in the 20 fog episodes; however, variability isevident in the DTR from south to north and from sunsetto sunrise.

The northernmost analysis areas vary little in theirratio of shallow to deeper fogs. Both the SMF and CICdivisions remain at or below a DTR value of 0.10 forthe entire nocturnal cycle. This result suggests that deepradiation fog rarely develops over large areas of thedivision. The lack of fog development is likely a resultof surface conditions such as lower dewpoint temper-atures and higher mean wind speeds. This peak in DTR

(0.20) is followed by a steep decline in the verticaldevelopment ratio. A minimum value of 0.08 is reachedat 0200 LST.

The BFL division is dominated by shallow fog coverfrom 1800 to 2100 LST when the ratio is minimized at0.03. From 2100 to 0100 LST the DTR increases to 0.30and then experiences another steep increase from 0400to 0600 LST. The 0600 LST peak ratio is 0.49.

The FAT division also begins the night with DTR

values near 0.11, but the ratio begins to increase between1900 and 0000 LST. FAT reaches one of its two peaksat midnight with a DTR of 0.30. Just after midnight, thedeeper fogs decrease as a proportion of total coverage,but they increase again to a second peak of 0.31 at 0600LST.

The surface conditions that help to explain the de-velopment of deeper fog in the southern portion of thestudy area have been discussed in some detail in thesections above. They include the south–north variationin 1600 LST temperature, 1600 LST relative humiditylevels, the steep temperature decline after sunset, andlow mean wind speeds at the surface. It is also verylikely that conditions in the midtroposphere play a crit-ical role in vertically developing radiation fog in theCentral Valley.

The KOAK soundings for the 20 episodes reveal that

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

FEBRUARY 2004 309U N D E R W O O D E T A L .

the atmosphere above 700 hPa was consistently dry andcooled slightly during radiation-fog development. Cool,dry air above the valley inversion, along with lightwinds aloft, promotes fog-top radiative cooling,strengthening the temperature inversion, and encour-aging further condensation at the fog top. The mean700-hPa dewpoint depression for the 20 fog episodeswas 14.58C at 1600 LST, and the mean 700-hPa dew-point depression at 0400 LST was 21.38C, suggestingsignificant drying of the air above the fog level in thevalley. The mean 500-hPa dewpoint depression valuewas 12.58C at 1600 LST and 18.98C at 0400 LST, con-firming that a deep layer of the midtroposphere expe-rienced substantial drying over the nocturnal cycle.Wind speeds at 700 hPa were generally weak (7.7–15.4m s21) and were out of the northwest most prominentlyat both 1600 and 0400 LST.

To summarize the relationship between vertical de-velopment parameters and horizontal fog cover, a Pear-son’s product moment correlation analysis was per-formed at the 0.05 significance level to compare thehourly vertical development ratio with hourly coveragepercentage and hourly fog growth rates. The analysissuggests that there is no significant relationship in termsof linear correlation between vertical fog developmentand hourly growth rates. This is the case over all fiveanalysis divisions. There are, however, significant cor-relation coefficients for the relationship between hourlyCp and the hourly DTR. For the BFL division, 13 of the20 fog episodes had significant positive correlations be-tween hourly Cp and the hourly DTR. The remainingseven fog episodes had no significant linear relationshipat the 0.05 level. The FAT division had 14 fog episodeswith positive correlations between the hourly Cp andhourly DTR. In the MER division there were 10 fogepisodes that had significant correlation coefficients, andeach was positive. The SMF division had 11 fog epi-sodes with significant positive correlation coefficients.The CIC division produced only 3 of 20 fog episodeswith significant correlations between the hourly Cp andhourly DTR. This result suggests that vertical devel-opment follows horizontal development more stronglyin the southern part of the valley (BFL and FAT), butthe relationship weakens in the central part of the studyarea (MER and SMF) and is nonexistent in the northernvalley (CIC).

6. Summary and conclusions

This study presents a framework for analyzing thenocturnal development of long-lived spatially extensiveradiation fog in the Central Valley of California. Bydividing the study area into five divisions and utilizingthe GOES NFP to analyze 20 fog episodes, the studyprovides insight into both the spatial and temporal char-acteristics of large-scale radiation-fog development.This analysis is the first to provide parameters for arealand vertical development of Central Valley radiation

fog. The study also links fog-development character-istics to surface and lower-tropospheric conditions dur-ing the nocturnal cycle.

Synoptic-scale conditions apparent during the 20 ra-diation-fog episodes are dominated by a large GreatBasin high pressure center. The mean location and cen-tral pressure for the omnipresent Great Basin high were42.38N, 117.88W and 1033.6 hPa, respectively. Themean position of the 500-hPa ridge axis associated withthis regime was approximately 120.88W, and 500-hPaheights across the Central Valley during radiation-fogepisodes ranged from 5550 to 5850 gpm.

The mean south–north extent of the 20 episodes wasfound to be 452 km, and the mean east–west extent ofradiation fog was 155 km. Even though these large-scalefog events may be perceived to be homogeneous incharacter, the spatial coverage, rate of development, andvertical extent were found to vary substantially fromsouth to north.

Fog cover as measured by Cp was greatest in the BFLand FAT divisions. Over the 20 episodes analyzed inthis study, areal coverage was more variable during theevening hours but became less variable from 0000 to0600 LST. This was the case for all divisions exceptCIC. Total radiation fog cover was maximized at 0600LST in the southern valley but was at its greatest arealextent between 2300 and 0000 LST for MER, SMF, andCIC. The FAT and MER divisions experienced slighterosion of their fog cover between 0000 and 0200 LST.This erosion coincided with an increase in mean windspeed in this area of the valley, which is the widestportion of the study region and, thus, may be subjectto circulation patterns influenced by the distance fromthe center of the valley to adjacent topographic barriers.

Vertical fog development was also variable fromsouth to north across the study area. The deepest fogdevelopment occurred in the southern valley, with max-imum depths that exceed 400 m. Vertical developmentwas most rapid in the south valley from 2100 to 0100LST and again between 0400 and 0600 LST. Verticaldevelopment was also strongly related (positively) toareal coverage in the southern valley, but this positiverelationship was weaker from MER to CIC.

Both the areal extent and the vertical development ofradiation fog in the southern valley closely followed thetemporal trends in surface temperature, dewpoint tem-peratures, and relative humidity. Divisions includingBFL and FAT also recorded much cooler 1600 LSTsurface temperatures in comparison with the other di-visions. BFL and FAT also had more vigorous radiationfog development in comparison with MER, SMF, andCIC. Vertical development was also influenced by cool,dry air aloft, which was observed during each of the 20episodes from 700 to 500 hPa. Though the height ofthe valley temperature inversion was not available fromthe KOAK sounding, the cool, dry northwesterly windsin the layer above 700 hPa likely strengthened the in-version and modulated condensation at the fog top. The

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

310 VOLUME 43J O U R N A L O F A P P L I E D M E T E O R O L O G Y

mean dewpoint temperature change from 1600 to 0400LST at 700 hPa was 6.88C, and drying at 500 hPa was6.48C during the same period.

This work confirms a number of conclusions fromradiation fog research carried out in other regions.Among these confirmations are the relationship of noc-turnal fog development to presunset temperature con-ditions, evening trends in relative humidity, and surfacewind speed (Fitzjarrald and Lala 1989; Guedalia andBergot 1994). Further work in the operational contextcan advance the use of the GOES NFP for both fore-casting and climatological analysis in the Central Valley.Foremost among the operational goals should be theverification of the GOES NFP vertical development es-timates using visual observations of known topographicfeatures, visibility reports, and GOES or AVHRR visibleimages.

The findings from this GOES NFP analysis of theCentral Valley may have implications for forecasters andpublic-safety officials in the region. The most promisingfindings that may make the transition to operational usefollow:

• More accurate timing of areal radiation-fog expansionmay prove beneficial, as assumptions of gradual de-velopment could lead to spurious forecasts. In thesouthern part of the valley, using Cp or hourly de-velopment rates at midnight to estimate sunrise cov-erage may underestimate the maximum coverage be-cause rapid development is evident during the morn-ing hours.

• The identification of a prominent midcycle disruptionin fog development in the valley region near FAT andMER may also benefit forecasters. This disruption infog development signals a retreat in areal coverageover the morning hours near MER and prevents fogdevelopment near FAT from reaching the extent offog episodes farther south near BFL.

• The rapid ‘‘bursts’’ of vertical fog development after0100 LST at BFL and after 0200 LST at FAT mayallow forecasters in the southern valley to delay anal-ysis of fog depth until later in the diurnal cycle so asnot to underestimate sunrise fog depth.

• The study’s confirmation of the importance of ana-lyzing surface temperatures and dewpoint tempera-tures before sunset (in this case 1600 LST) to estimatetime of onset and rapidity in radiation fog develop-ment may assist forecasters and planners in preparingaviation forecasts (especially calculating takeoff/land-ing cessation times at valley airports).

• In a climatological context (i.e., calculating mean val-ues over many episodes), forecasters may identify thehour at which mean surface relative humidity levelsreach 90% and use this hour as an indicator for fore-casting rapidly expanding or vertically developing ra-diation fog.

This study was one of the first to use GOES NFPimages for analysis of the climatological aspects of ra-

diation-fog development. The results of this study sug-gest that the GOES NFP can be a an effective data-generating tool and, in concert with surface and upper-air data, can assist in evaluating both horizontal andvertical development characteristics of radiation fog.The findings should lead to a number of questions thatcan be approached with similar methods as employedin this study. Among the most intriguing research ques-tions raised by this study is whether the GOES NFP–generated 0600 LST depth estimates can be used toforecast postsunrise time requirements for fog dissipa-tion in the Central Valley. By using the same five anal-ysis divisions and GOES 4- and 1-km visible imagery,this question could be tested with great accuracy.

Acknowledgments. This work was funded by the Na-tional Oceanic and Atmospheric Administration’s Na-tional Environmental Satellite Data and InformationService, Office of Research Applications (NOAA/NES-DIS/ORA) under Grant NA06EC0205. Special thanksare given to Kris Lynn (University of California, KearnyAgriculture Center) and the Geography Department atCalifornia State University, Fresno.

REFERENCES

Aguado, E., and J. E. Burt, 2001: Understanding Weather and Cli-mate. Prentice Hall, 505 pp.

Ahrens, D., 1994: Meteorology Today. 6th ed. Brooks-Cole, 535 pp.Arking, A., and J. D. Childs, 1985: Retrieval of cloud cover param-

eters from multispectral satellite images. J. Climate Appl. Me-teor., 24, 322–333.

Arnott, W. P., C. Schmitt, Y. Liu, and J. Hallett, 1997: Droplet sizespectra of water vapor concentration of laboratory water clouds:Inversion of Fourier transform infrared (500–5000 cm21) opti-cal-depth measurement. Appl. Opt., 36, 5205–5216.

Azevedo, J., and D. L. Morgan, 1974: Fog precipitation in coastalCalifornia forests. Ecology, 55, 1135–1141.

Baker, R., J. Cramer, and J. Peters, 2002: Radiation fog: UPS Airlinesconceptual models and forecast methods. Preprints, 10th Conf.on Aviation, Range, and Aerospace Meteorology, Portland, OR,Amer. Meteor. Soc., 154–159.

Bendix, J., 2001: A 10-years fog climatology of Germany and theAlpine region based on satellite data—Preliminary results. Proc.Second Int. Conf. on Fog and Fog Collection, St. John’s, NF,Canada, Canadian International Development Agency, CanadianMeteor. and Oceanogr. Soc., and Environment Canada. 357–360.

Bergot, T., and D. Guedalia, 1994: Numerical forecasting of radiationfog. Part I: Numerical model and sensitivity tests. Mon. Wea.Rev., 122, 1218–1230.

Bott, A., U. Sievers, and W. Zdunkowski, 1990: A radiation fog modelwith a detailed treatment of the interaction between radiativetransfer and fog microphysics. J. Atmos. Sci., 47, 2153–2166.

Brown, R., 1980: A numerical study of radiation fog with an explicitformulation of the microphysics. Quart. J. Roy. Meteor. Soc.,106, 781–802.

Bruijnzeel, L. A., and E. L. Veneklaas, 1998: Climatic conditions andtropical montane forest productivity: The fog has not lifted yet.Ecology, 79, 3–9.

Carson, R. B., and R. C. Hardy, 1963: On the forecasting of winterfog: A geographical approach. J. Appl. Meteor., 2, 351–357.

Cavelier, J., D. Solis, and M. A. Jaramillo, 1996: Fog interception inmontane forests across the central cordillera of Panama. J. Trop.Ecol., 12, 357–369.

CIMIS, cited 2002: California irrigation management and information

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC

FEBRUARY 2004 311U N D E R W O O D E T A L .

system—Data reports. California Department of Water Resourc-es. [Available online at http://www.cimis.water.ca.gov.]

Collet, J. L., K. J. Hoag, D. E. Sherman, A. Baton, and L. W. Richards,1999: Spatial and temporal variations in San Joaquin Valley fogchemistry. Atmos. Environ., 33, 129–140.

Court, A., and R. Gerston, 1966: Fog frequency in the United States.Geogr. Rev., 56, 543–550.

Croft, P. J., R. L. Pfost, J. M. Medlin, and G. A. Johnson, 1997: Fogforecasting for the southern region: A conceptual model ap-proach. Wea. Forecasting, 12, 545–556.

d’Entremont, R. P., 1986: Low and midlevel cloud analysis usingnighttime multispectral imagery. J. Climate Appl. Meteor., 25,1853–1869.

——, and L. W. Thompson, 1987: Interpreting meteorological sat-ellite images using a color-composite technique. Bull. Amer. Me-teor. Soc., 68, 762–768.

Duynkerke, P. G., 1991: Radiation fog: A comparison of model sim-ulation with detailed observations. Mon. Wea. Rev., 119, 324–341.

Ellrod, G., 1994: Detection and analysis of fog at night using GOESmultispectral infrared imagery. NOAA Tech. Rep. NESDIS-75,22 pp.

——, 1995: Advances in the detection and analysis of fog at nightusing GOES multispectral infrared imagery. Wea. Forecasting,10, 606–619.

——, 2000: Proposed improvements to the GOES nighttime fog prod-uct to provide ceiling and visibility information. Preprints, 10thConf. on Satellite Meteorology and Oceanography, Long Beach,CA, Amer. Meteor. Soc., 454–456.

Eyre, J. R., J. L. Brownscombe, and R. J. Allen, 1984: Detection offog at night using Advanced High Resolution Radiometer(AVHRR) imagery. Meteor. Mag., 113, 266–271.

Fisher, E. L., and P. Caplan, 1963: An experiment in numerical pre-diction of fog and stratus. J. Atmos. Sci., 20, 425–437.

Fitzjarrald, D. R., and G. G. Lala, 1989: Hudson Valley fog envi-ronments. J. Appl. Meteor., 28, 1303–1328.

Golding, B. W., 1993: A study of the influence of terrain on fogdevelopment. Mon. Wea. Rev., 121, 2529–2541.

Guedalia, D., and T. Bergot, 1994: Numerical forecasting of radiationfog. Part II: A comparison of model simulation with severalobserved fog events. Mon. Wea. Rev., 122, 1231–1246.

Gustafson, A. V., and S. E. Wasserman, 1976: Use of satellite in-formation in observing and forecasting for dissipation and cloudformation. Mon. Wea. Rev., 104, 323–324.

Hardwick, W. C., 1973: Monthly fog frequency in the continentalUnited States. Mon. Wea. Rev., 101, 763–766.

Holets, S., and R. N. Swanson, 1981: High-inversion fog episodesin central California. J. Appl. Meteor., 20, 890–899.

Hunt, G. E., 1973: Radiative properties of terrestrial clouds at visibleand infra-red thermal window wavelengths. Quart. J. Roy. Me-teor. Soc., 99, 346–369.

Kidder, S. Q., and T. H. Vonder Haar, 1995: Satellite Meteorology:An Introduction. Academic Press, 446 pp.

Kleespies, T. J., 1995: The retrievals of marine stratiform cloud prop-erties from multiple observations in the 3.9-mm window underconditions of varying solar illumination. J. Appl. Meteor., 34,1512–1524.

Lala, G. G., E. Mandel, and J. E. Jiusto, 1975: A numerical evaluationof radiation fog variables. J. Atmos. Sci., 32, 720–728.

Lee, T. F., 1987: Urban clear islands in California Central Valley fog.Mon. Wea. Rev., 115, 1794–1796.

——, F. J. Turk, and K. Richardson, 1997: Stratus and fog productsusing GOES-8–9 3.9-mm data. Wea. Forecasting, 12, 664–677.

Mather, P. M., 1999: Computer Processing of Remotely-Sensed Im-ages. 2d ed. John Wiley and Sons, 292 pp.

McLaren, S., E. McLaren, and M. Mariotti, 1988: Heterogeneous

processes in the Po Valley radiation fog. J. Geophys. Res., 93,11 141–11 151.

Mead, J. B., R. F. McIntosh, D. Vandemark, and C. T. Swift, 1989:Remote sensing of clouds and fog with a 1.4-mm radar. J. Atmos.Oceanic Technol., 6, 1090–1097.

Menzel, W. P., and J. F. W. Purdom, 1994: Introducing GOES-1: Thefirst of a new generation of geostationary operational environ-mental satellites. Bull. Amer. Meteor. Soc., 75, 757–782.

Meyer, M. B., and G. G. Lala, 1990: Climatological aspects of ra-diation fog occurrence at Albany, New York. J. Climate, 3, 577–586.

——, ——, and J. E. Jiusto, 1986: FOG-82: A cooperative field studyof radiation fog. Bull. Amer. Meteor. Soc., 67, 825–832.

Meyer, W. D., and G. V. Rao, 1999: Radiation fog prediction usinga simple numerical model. Pure Appl. Geophys., 155, 57–80.

Moore, G. E., C. Daly, and M. Liu, 1987: Modeling of mountain–valley wind fields in the southern San Joaquin Valley, California.J. Climate Appl. Meteor., 26, 1230–1242.

Musson-Genon, L., 1987: Numerical simulation of a fog event witha one-dimensional boundary layer model. Mon. Wea. Rev., 115,592–607.

NCDC, cited 2002: National virtual data system. National ClimaticData Center, NOAA, Department of Commerce, Asheville, NC.[Available online at http://nndc.noaa.gov/?home.shtml.]

Oke, T. R., 1988: Boundary Layer Climates. Routledge, 435 pp.Peace, R. L., 1969: Heavy-fog regions in the conterminous United

States. Mon. Wea. Rev., 97, 116–123.Pilie, R. J., E. J. Mack, W. C. Kocmond, W. J. Eadie, and C. W.

Rogers, 1975a: The life cycle of valley fog. Part II: Fog micro-physics. J. Appl. Meteor., 14, 364–374.

——, ——, ——, C. W. Rogers, and W. J. Eadie, 1975b: The lifecycle of valley fog. Part I: Micrometeorological characteristics.J. Appl. Meteor., 14, 347–363.

Pinnick, R. G., D. L. Hoihjelle, G. Fernandez, E. B. Stenmark, andJ. D. Lindberg, 1978: Vertical structure in atmospheric fog andhaze and its effects on visible and infrared extinctions. J. Atmos.Sci., 35, 2020–2032.

Putsay, M., J. Kerenyi, I. Sebok, P. Nemeth, and M. Dioszeghy, 2001:Nighttime fog and low cloud detection in NOAA-16 AVHRRimages and validation with ground observed SYNOP data andradar measurements. Preprints, The 2001 EUMETSAT Meteo-rological Satellite Data Users’ Conf., Ankura, Turkey, EuopeanOrganisation for the Exploitation of Meteorological Satellites,365–373.

Rao, P. K., S. J. Holmes, R. K. Anderson, J. S. Winston, and P. E.Lehr, Eds., 1990: Weather Satellites: Systems, Data, and Envi-ronmental Applications. Amer. Meteor. Soc., 503 pp.

Rawlings, F., and J. S. Foot, 1990: Remotely sensed measurementsof stratocumulus properties during FIRE using the C130 aircraftmulti-channel radiometer. J. Atmos. Sci., 47, 2488–2504.

St. Jean, D., 1997: Using varied enhancement curves to better eval-uate fog and status with RAMSDIS. U.S. Department of Com-merce, Western Region Tech. Attachment 97-40, 9 pp.

Suckling, P. W., and M. D. Mitchell, 1988: Fog climatology of theSacramento urban area. Prof. Geogr., 40, 186–194.

Suomi, V. E., R. Fox, S. S. Limaye, and W. L. Smith, 1983: McIDASIII: A modern interactive data access and analysis system. J.Climate Appl. Meteor., 22, 766–778.

Swenson, S. E., 2002: Crashes clog highways. Bakersfield Califor-nian, 3 January.

Welch, R. M., and S. K. Cox, 1986: Prediction of quasi-periodicoscillations in radiation fogs. Part I: Comparison of simple sim-ilarity approaches. J. Atmos. Sci., 43, 633–651.

Wetzel, M. A., R. D. Borys, and L. E. Xu, 1996: Satellite micro-physical retrievals for land-based fog with validation by balloonprofiling. J. Appl. Meteor., 35, 810–829.

Yarnal, B., 1994: Synoptic Climatology in Environmental Analysis:A Primer. John Wiley and Sons, 256 pp.

Unauthenticated | Downloaded 04/11/22 05:40 AM UTC