Showing papers on "Precipitation published in 1994"

A Statistical-Topographic Model for Mapping Climatological Precipitation over Mountainous Terrain

Abstract: The demand for climatological precipitation fields on a regular grid is growing dramatically as ecological and hydrological models become increasingly linked to geographic information systems that spatially represent and manipulate model output. This paper presents an analytical model that distributes point measurements of monthly and annual precipitation to regularly spaced grid cells in midlatitude regions. PRISM (Precipitation-elevation Regressions on Independent Slopes Model) brings a combination of climatological and statistical concepts to the analysis of orographic precipitation. Specifically, PRISM 1) uses a digital elevation model (DEM) to estimate the “orographic” elevations of precipitation stations; 2) uses the DEM and a windowing technique to group stations onto individual topographic facets; 3) estimates precipitation at a DEM grid cell through a regression of precipitation versus DEM elevation developed from stations on the cell's topographic facet; and 4) when possible, calculates...

A Double-Moment Multiple-Phase Four-Class Bulk Ice Scheme. Part I: Description

Abstract: A detailed ice-phase bulk microphysical scheme has been developed for simulating the hydrometeor distributions of convective and stratiform precipitation in different large-scale environmental conditions. The proposed scheme involves 90 distinct microphysical processes, which predict the mixing ratios and the number concentrations of small ice crystals, snow, graupel, and frozen drops/hail, as well as the mixing ratios of liquid water on wet precipitation ice (snow, graupel, frozen drops). The number of adjustable coefficients has been significantly reduced in comparison with other bulk schemes. Additional improvements have been made to the parameterization in the following areas: (1) representing small ice crystals with nonzero terminal fall velocities and dispersive size distributions, (2) accurate and computationally efficient calculations of precipitation collection processes, (3) reformulating the collection equation to prevent unrealistically large accretion rates, (4) more realistic conversion by riming between different classes of precipitation ice, (5) preventing unrealistically large rates of raindrop freezing and freezing of liquid water on ice, (6) detailed treatment of various rime-splintering ice multiplication mechanisms, (7) a simple representation of the Hobbs-Rangno ice enhancement process, (8) aggregation of small ice crystals and snow, and (9) allowing explicit competition between cloud water condensation and ice deposition rates rather than using saturation adjustment techniques. For the purposes of conserving the higher moments of the particle distributions, preserving the spectral widths (or slopes) of the particle spectra is shown to be more important than strict conservation of particle number concentration when parameterizing changes in ice-particle number concentrations due to melting, vapor transfer processes (sublimation of dry ice, evaporation from wet ice), and conversion between different hydrometeor species. The microphysical scheme is incorporated into a nonhydrostatic cloud model in Part 2 of this study. The model performed well in simulating the radar and microphysical structures of a midlatitude-continental squall lines and a tropical-maritime squall system with minimal tuning of the parameterization, even though the vertical profiles of radar reflectivity differed substantially between these storms.

Precipitation recycling in the Amazon basin

Abstract: Precipitation recycling is the contribution of evaporation within a region to precipitation in that same region. The recycling rate is a diagnostic measure of the potential for interactions between land surface hydrology and regional climate. In this paper we present a model for describing the seasonal and spatial variability of the recycling process. The precipitation recycling ratio, rho, is the basic variable in describing the recycling process. Rho is the fraction of precipitation at a certain location and time which is contributed by evaporation within the region under study. The recycling model is applied in studyiing the hydrologic cycle in the Amazon basin. It is estimated that about 25% of all the rain that falls in the Amazon basin is contributed by evaporation within the basin. This estimate is based on analysis of a data set supplied by the European Centre for Medium-range Weather Forecasts (ECMWF). The same analysis is repeated using a different data set from the Geophysical Fluid Dynamics Laboratory (GFDL). Based on this data set, the recycling ratio is estimated to be 35%. The seasonal variability of the recycling ratio is small compared with the yearly average. The new estimates of the recycling ratio are compared with results of previous studies, and the differences are explained.

The Accuracy of United States Precipitation Data

Abstract: Precipitation measurements in the United States (as well as all other countries) are adversely affected by the gauge undercatch bias of point precipitation measurements. When these measurements are used to obtain areal averages, particularly in mountainous terrain, additional biases may be introduced because most stations are at lower elevations in exposed sites. Gauge measurements tend to be underestimates of the true precipitation, largely because of wind-induced turbulence at the gauge orifice and wetting losses on the internal walls of the gauge. These are not trivial as monthly estimates of this bias often vary from 5% to 40%. Biases are larger in winter than in summer and increase to the north in the United States due largely to the deleterious effect of the wind on snowfall. Simple spatial averaging of data from existing networks does not provide an accurate evaluation of the area-mean precipitation over mountainous terrain (e.g., over much of the western United States) since most stations are loca...

The contribution of evaporation from the Great Lakes to the continental atmosphere: estimate based on stable isotope data

Abstract: The isotopic composition of precipitation and river runoff in the vicinity of the North American Great Lakes is characterized by a higher deuterium-excess value than observed in the advecting air masses. It is suggested that this indicates that evaporated moisture from the surface waters is mixed with the atmosphere waters. A preliminary estimate of the atmospheric water balance during summer and autumn indicates that between 4.6%–15.7% of the atmospheric water content downwind from the Great Lakes is derived from lake evaporation during summer.

Variability and Trends of Total Precipitation and Snowfall over the United States and Canada

Abstract: The biases and large-scale inhomogeneities in the time series of measured precipitation and snowfall over the United States and Canada are discussed and analyzed. The spatial statistical characteristics of monthly and annual snowfall and total precipitation are investigated and parameterized. After adjustments and selection of the “best” network, reliable “first guess” estimates of North American snowfall and precipitation are obtained. Century-long time series of unbiased annual precipitation over the regions to the south of 55°N and 40-year time series of unbiased area-averaged annual precipitation and snowfall for all of North America are developed. The analysis of their trends shows the following. 1) During the last 100 years, annual precipitation has increased in southern Canada (south of 55°N) by 13% and in the contiguous United States by 4%; however, the main domain of this century-scale precipitation increase is eastern Canada and adjacent to it northern regions of the United States. 2) U...

Impact of Land-Surface Moisture Variability on Local Shallow Convective Cumulus and Precipitation in Large-Scale Models

Abstract: Numerical experiments using state-of-the-art high-resolution mesoscale cloud model showed that land-surface moisture significantly affects the timing of onset of clouds and the intensity and distribution of precipitation. In general, landscape discontinuity enhances shallow convective precipitation. Two mechanisms that are strongly modulated by land-surface moisture-namely, random turbulent thermal cells and organized sea-breeze-like mesoscale circulations-also determine the horizontal distribution of maximum precipitation. However, interactions between shallow cumulus and land-surface moisture are highly nonlinear and complicated by different factors, such as atmospheric thermodynamic structure and large-scale background wind. This analysis also showed that land-surface moisture discontinuities seem to play a more important role in a relatively dry atmsophere, and that the strongest precipitation is produced by a wavelength of land-surface forcing equivalent to the local Rossby radius of deformation. A general trend between the maximum precipitation and the normalized maximum latent heat flux was identified. In general, large values of mesoscale latent heat flux imply strongly developed mesoscale circulations and intense cloud activity, accompanied by large surface latent heat fluxes that transport more water vapor into the atmosphere.

Influence of the Land Surface in the Asian Summer Monsoon: External Conditions versus Internal Feedbacks

Abstract: The basic concept of land-sea temperature contrast and the strength of the Asian summer monsoon is investigated here by comparing the relative contributions of external conditions (involving surface albedo) and internal feedbacks (involving soil moisture) in a number of atmospheric general circulation model (GCM) mean climate simulations and in a GCM sensitivity experiment. All models are run with the same long-term mean sea surface temperatures so that only land-surface conditions affect the land-sea temperature contrast. There is a surprising consistency among the various models such that stronger summer monsoons (defined as high area-averaged precipitation over south Asia) are associated with greater land-sea temperature contrast (i.e., higher land temperatures), lower sea level pressure over land, less snow cover, and greater soil moisture. In a sensitivity study with land albedos uniformly raised from 0. 13 to 0.20 in one of the models, the winter-spring-summer sequence over southern Asia sh...

Terrestrial Precipitation Analysis: Operational Method and Required Density of Point Measurements

Abstract: The Global Precipitation Climatology Centre (GPCC) has established a semi-automatic data processing system to obtain monthly precipitation analyses. This includes components for the collection, storage arui quality-control of all available gauge-measured data. The calculation of areal mean precipitation on a 2.5o grid by using an objective analysis method and the merging of these analyses with results from other sources to get complete global gridded data sets are a part of the routine system as well.

Deuterium and oxygen 18 in precipitation: Isotopic model, including mixed cloud processes

Abstract: Modeling the isotropic ratios of precipitation in cold regions meets the problem of `switching` from the vapor-liquid transition to the vapor-ice transition at the oneset of snow formation. The one-dimensional model (mixed cloud isotopic model (MCIM)) described in this paper focuses on the fractionation of water isotopes in mixed clouds, where both liquid droplets and ice crystals can coexist for a given range of temperatures. This feature is linked to the existence of specific saturation conditions within the cloud, allowing droplets to evaporate while the water vapor condensates onto ice crystals. The isotopic composition of the different airborne phases and the precipitation is calculated throughout the condensation history of an isolated air mass moving over the Antarctic ice sheet. The results of the MCIM are compared to surface snow data both for the isotopic ratios and the deuterium excesses. The sensitivity of the model is compared to previous one-dimensional models. Our main result is that accounting specifically for the microphysics of mixed stratiform clouds (Bergeron-Findesein process) does not invalidate the results of earlier modeling studies.

Sensitivity of the Global Water Cycle to the Water-Holding Capacity of Land

Abstract: The sensitivity of the global water cycle to the water-holding capacity of the plant-root zone of continental soils is estimated by simulations using a mathematical model of the general circulation of the atmosphere, with prescribed ocean surface temperatures and prescribed cloud. With an increase of the globally constant storage capacity, evaporation from the continents rises and runoff falls, because a high storage capacity enhances the ability of the soil to store water from periods of excess for later evaporation during periods of shortage. In addition to this direct effect, atmospheric feedbacks associated with the resulting higher precipitation and lower potential evaporation drive further changes in evaporation and runoff. Most of the changes in evaporation and runoff occur in the tropics and in the northern middle-latitude rain belts. Global evaporation from land increases by about 7 cm for each doubling of storage capacity in the range from less than 1 cm to almost 60 cm. Sensitivity is ...

Dynamic modeling of orographically induced precipitation

Abstract: Local orography governs the triggering of cloud formation and the enhancement of processes such as condensation and hydrometeor nucleation and growth in mountainous regions. Intense, lengthy precipitation events are typical upwind of the topographic divide, with sharply decreasing magnitude and duration on the lee side. Differences in mean annual precipitation of several hundred percent between windward slopes of orographic barriers and adjacent valleys or lee side slopes are not unusual. Because much of the streamflow in areas such as the western United States is derived from mountainous areas that are remote and often poorly instrumented, modeling of orographic precipitation has important implications for water resources management. Models of orographically induced precipitation differ by their treatment of atmospheric dynamics and by the extent to which they rely on bulk parameterization of cloud and precipitation physics. Adiabatic ascent and a direct proportionality between efficiency and orographically magnified updrafts are the most frequent assumptions in orographic precipitation modeling. Space-time discretization (i.e., resolution) is a major issue because of the high spatial variability of orographic precipitation. For a specific storm, relative errors as large as 50 to 100% are common in the forecast/hindcast of precipitation intensity and can be even larger in the case of catastrophic storms. When monthly or seasonal timescales are used to evaluate model performance, the magnitude of such errors decreases dramatically, reaching values as low as 10 to 15%. Current research is focusing on the development of data assimilation techniques to incorporate radar and satellite observations, and on the development of aggregation and disaggregation methodologies to address the implications of modeling a multiscale problem at restricted spatial and temporal resolutions.

A Numerical Study of the Stratiform Region of a Fast-Moving Squall Line. Part I: General Description and Water and Heat Budgets

Abstract: A two-dimensional nonhydrostatic cloud model is applied to the simulation of a tropical squall line that occurred on 23 June during the COPT 81 experiment. Owing to the use of an ice parameterization scheme, the simulation reproduces many interesting features of the stratiform part observed with Doppler radars. In particular, this includes the dynamical, thermodynamical, and microphysical structures of the stratiform part. Different parts are clearly identified from the simulation and observations: a leading convective zone 40-km wide with large precipitation; a developed stratiform zone stretching over 150 km with moderate precipitation; between these two regions, a transition zone 20-km wide giving only light precipitation; and a forward anvil near 12 km. The mean horizontal circulation is characterized by two mean flows: the front-to-rear flow that represents upward and rearward injection of boundary-layer air and the underlying rear-to-front flow. The simulated vertical velocity, except in th...

Albedo as a modulator of climate response to tropical deforestation

Abstract: An atmospheric general circulation model with land surface properties represented by the simplified Simple Biosphere model is used to investigate the effects on local climate due to tropical deforestation for the Amazon basin. One control and three anomaly integrations of 4 years' duration are performed. In the anomaly integrations, rain forest in South America is replaced by degraded grassland. The anomaly integrations differ only in the optical properties of the grassland vegetation, with net surface albedos ranging from the same as to 0.09 lighter than that of rain forest. It is found that the change in climate, particularly rainfall, is strongly dependent on the change in surface albedo that accompanies deforestation. Replacement of forest by grass causes a reduction in transpiration and reduces frictional convergence by decreasing surface roughness. However, precipitation averaged over the deforested area is not necessarily reduced. Average precipitation decreases when the increase in albedo is greater than 0.03. If surface albedo is not increased appreciably as a result of deforestation, moisture flux convergence driven by the increase in surface temperature can offset the other effects, and average precipitation increases. As albedo is increased, surface temperature does not change, but surface latent and sensible heat flux decreases due to reduced radiational energy absorbed at the surface, resulting in a reduction in convection and precipitation. A change in the distribution of precipitation due to deforestation that appears to be independent of the albedo is observed.

Water stress and use of summer precipitation in a Great Basin shrub community

Abstract: Seasonal patterns of water stress (determined from predawn xylem pressure potentials) and relative use of summer precipitation (determined from hydrogen isotope composition) varied intraspecifically and interspecifically in a Great Basin shrub community. The development of water stress during the dry season from June to July was positively correlated with the use of summer precipitation in August. The smallest plants generally developed the greatest water stress and took up the most summer precipitation, presumably due to being more dependent on shallow roots. Among mature shrubs examined, moisture from summer precipitation was taken up by Chrysothamnus viscidiflorus and Artemisia tridentata, but not by C. nauseosus, Juniperus osteosperma and Tetradymia canescens (...)

Effect of rainfall‐sampling errors on simulations of desert flash floods

Abstract: The effect of rainfall-sampling errors on distributed hydrologic simulations was evaluated in a study conducted with localized thunderstorms and a midsized (150 km2) semiarid watershed. Rainfall fields based on observations from a very dense rain gage network were compared to rainfall fields based on observations from a subset of the original gages. The rain gage density of the “sparse” network (1 gage per 20 km2) was selected to represent the typical gage density of a local evaluation in real time (ALERT) type flash flood warning system. Inadequate rain gage densities in the case of the sparse network produced errors in simulated peaks that, on the average, represented 58% of the observed peak flow. Approximately half of the difference between observed and simulated peaks was due to rainfall-sampling errors. Simulations were also conducted with rainfall that is similar to the next generation weather radar (NEXRAD) digital precipitation estimates in that it represents areal averages within 4 km × 4 km pixels. Spatial averaging of rainfall over 4 km × 4 km pixels led to consistent reductions in simulated peaks that, on the average, represented 50% of the observed peak flow. Hence it appears that the current spatial resolution of ALERT-type precipitation measurements and 4 km × 4 km radar precipitation estimates may not be sufficient to produce reliable rainfall-runoff simulations/forecasts in midsized watersheds of the southwestern United States subject to localized thunderstorms and large infiltration losses.

Climate controls on temporal variability of methane flux from a poor fen in southeastern New Hampshire: Measurement and modeling

Abstract: Three scales of temporal variability were present in methane (CH 4) flux data collected during a 2.5 year (mid-1990n1992) study at a small, poor fen in southeastern New Hampshire. (1) There was a strong seasonality to the fluxes (high in summer); monthly average fluxes range from 21.4 mg CH 4nm m2nd m1n(February 1992) to 639.0 mg CH 4nm m2d m1n(July 1991). Annual fluxes were 68.8 g CH 4nm m2n(1991) and 69.8 g CH 4nm m2n(1992). (2) There was interannual variability; distribution of flux intensity was very different from 1991 to 1992, particularly the timing and rapidity of the onset of higher fluxes in the spring. (3) There was a high degree of variability in CH 4nflux during the warm season; four successive weekly flux rates in July 1991 were 957, 1044, 170, and 491 mg CH 4nm m2nd m1. Fluxes were correlated with peat temperature (r 2=0.44) but only weakly with depth to water table (r 2n= 0.14 for warm season data). Warm season fluxes appeared to be suppressed by rainstorms. Along with methane flux data we present an analysis of this temporal variability in flux, using a peatland soil climate model developed for this site. The model was driven by daily air temperature, precipitation, and net radiation; it calculated daily soil temperature and moisture profiles, water table location, and ice layer thickness. Temperature profiles were generally in good agreement with field data. Depth to water table simulations were good in 1992, fair in 1990, and poor in the summer of 1991. Using model-simulated peat climate and correlations to methane flux developed from the field data, simulated methane fluxes exhibited the same three modes of temporal variability that were present in the field flux data, though the model underestimated peak fluxes in 1990 and 1991. We conclude that temporal variability in flux is significantly influenced by climate/weather variability at all three scales and that rainfall appears to suppress methane flux for at least several days at this site.

Large-Scale Aspects of the United States Hydrologic Cycle

Abstract: A large-scale, gridpoint, atmospheric, hydrologic climatology consisting of atmospheric precipitable water, precipitation, atmospheric moisture flux convergence, and a residual evaporation for the conterminous United States is described. A large-scale, basin, hydrologic climatology of the same atmospheric variables is also described, as well as residual surface water and streamflow divergence or runoff for various large-scale river basins terminating at the United States boundary. Climatologically, precipitation, which had a U.S. annual mean of more than 2.1 mm day−1, was largely balanced by evaporation; atmospheric moisture flux convergence was also an important contributor (∼0.5 mm day−1), especially during the wintertime, and especially along the U.S. west coast. At the surface, seasonal and anomalous surface water (including snow) variations on the order of 10 cm yr−1 were forced by seasonal variations of about 1 mm day−1 in atmospheric moisture flux convergence (precipitation minus evaporati...

The simulated Indian monsoon: A GCM sensitivity study

Abstract: A series of sensitivity experiments are conducted in an attempt to understand and correct deficiencies in the simulation of the seasonal mean Indian monsoon with a global atmospheric general circulation model. The seasonal mean precipitation is less than half that observed. This poor simulation in seasonal integrations is independent of the choice of initial conditions and global sea surface temperature data used. Experiments are performed to test the sensitivity of the Indian monsoon simulation to changes in orography, vegetation, soil, wetness, and cloudiness. The authors find that the deficiency of the model precipitation simulation may be attributed to the use of an enhanced orography in the integrations. Replacement of this orography with a mean orography results in a much more realistic simulation of Indian monsoon circulation and rainfall. Experiments with a linear primitive equation model on the sphere suggest that this striking improvement is due to modulations of the orographically forced waves in the lower troposphere. This improvement in the monsoon simulation is due to the kinematic and dynamical effects of changing the topography, rather than the thermal effects, which were minimal. The magnitude of the impact on the Indian monsoon of the other sensitivity experiments varied considerably, but was consistently less than the impact of using the mean orography. However, results from the soil moisture sensitivity experiments suggest a possibly important role for soil moisture in simulating tropical precipitation, including that associated with the Indian monsoon.

Effects of surface conditions on rain identification using the DMSP‐SSM/I

Abstract: Accurate rain identification using satellite‐based microwave radiometers requires the identification of surfaces having signatures similar to that of rain. This is especially important over land since highly variable surface conditions (such as changing vegetation cover, soil moisture, and snow cover) can result in similar microwave characteristics to that of precipitation. The spectral characteristics of brightness temperature measured by the Special Sensor Microwave/Imager (SSM/I) form the basis of a rain classification scheme (Grody, 1991), which is detailed and improved upon in this paper.

Life Cycle and Precipitation Formation in a Hybrid-Type Hailstorm Revealed by Polarimetric and Doppler Radar Measurements

Abstract: Hailstorm processes are studied using multiparameter radar observations of thunderstorm evolution. The storm turned out to be of hybrid type, having both multicellular (oscillatory nature of hail production) and supercellular (quasi-steady state of basic dynamics) characteristics. Its reflectivity field showed a V-like pattern not yet described in the literature as a typical severe storm pattern. The flow was characterized by an updraft zone surrounding an embedded downdraft collocated with the main precipitation shaft. The precipitation mainly originated from graupel particles growing at the fringes of the main updraft zone, whereas an accumulation zone of big drops was not present. In the weaker parts of the updraft the falling graupel melted and reached the ground as rain, whereas in the main updraft region those raindrops could be recirculated and subsequently freeze or be captured by hailstones already present aloft. In this region of high liquid water content large hail could be grown; it f...

Atmospheric contribution to hydrologic variations in the Arctic

Abstract: High‐latitude rawinsonde data for 18 years (1973–1990) are used to compute the atmospheric moisture flux convergence over two regions: the Arctic Ocean and the Mackenzie River drainage basin. The primary objectives are to assess the interannual variability and to compare the macroscale hydrologie regimes of the two regions. The moisture flux convergence is positive in all months over the Arctic Ocean, but is occasionally negative during summer over the Mackenzie Basin. The climatological seasonal cycle of the moisture convergence contains a late‐summer (August‐September) maximum over the Arctic Ocean but a late‐summer minimum over the Mackenzie Basin. Evaporation, deduced from the moisture inflow and independent data on precipitation, makes a much greater contribution to the atmospheric moisture budget of the Mackenzie domain, especially during summer. The respective equivalent area averages of the 18‐year annual mean moisture flux convergence, precipitation and derived evaporation are 17.3, 19.5...

Vegetation stress as a feedback mechanism in midlatitude drought

Abstract: An atmospheric general circulation model with land surface properties represented by the Simplified Simple Biosphere Model is used to investigate the effect of soil moisture and vegetation stress on drought in the mid-latitudes. An idealized land-sea distribution with simple topography is used to remove as many external sources of climate variation as possible. The land consists of a single, flat, rectangular continent covered with prairie vegetation and centered on 44 deg N of an aqua planet. A control integration of 4 years is performed, and several sets of seasonal anomaly integrations are made to test the sensitivity of seasonal climate to low initial (1 April) soil moisture and dormant vegetation like what would occur during a severe drought. It is found that the inclusion of dormant vegetation during the spring and early summer greatly reduces evapotranspiration by eliminating transpiration. This affects local climate more strongly as summer progresses. Low initial soil moisture, combined with dormant vegetation, leads to a severe drought. The reduction in precipitation is much greater in magnitude than that due to low soil moisture alone, and greater than the sum of the effects computed separately. Although the short-term drought is more severe, the dormancy of the vegetation prevents further depletion of moisture in the root zone of the soil, so soil moisture begins to rebound toward the middle of summer.

Modeling the isotopic composition of precipitation

Abstract: The physics of the stable isotopes of water is incorporated into a two-dimensional, kinematic, bulk cloud microphysical model. The model is run for several idealized, classical stratiform and convective storm situations, and the resulting isotope ratios of precipitation and water vapor are diagnosed and compared to observations. For stratiform snow, the model produces low isotope ratios that decrease rapidly poleward of the warm front. The lowest isotope ratios occur when the atmosphere is cold and when the vertical velocity attains its maximum value high in the troposphere. For stratiform rains, the model produces much higher isotope ratios without a significant poleward gradient as a result of isotope exchange between the falling rain and the surrounding vapor. Isotope ratios of rain are lowest when the melting level is near the ground and isotope exchange is minimized. For air mass thunderstorms, isotope ratios are uniformly high in warm air, no matter what the cloud height, unless hail approaches or reaches the ground. The model also produces a significant amount effect for rain, in which isotope ratios decrease with increasing rainfall, totals. Isotope ratios are particularly low when the rain derives from a recirculation process in which air previously charged by vapor from falling rain subsequently rises. Under such conditions, the model sometimes produces isotope ratios that decrease from the periphery to the core of the precipitation shield. It is suggested that this recirculation process is responsible for extraordinarily low isotope ratios observed in some hurricanes and organized thunderstorms. The dominant cloud microphysical processes can sometimes be inferred from isotope ratios of precipitation. The model produces ice pellets with isotope ratios close to those of rain when the pellets are produced by homogeneous freezing of rain and close to those of snow when the pellets are produced by refreezing of partially melted snow. A climatology of isotope values that matches the main features of the observed global data set and of a seven-year record of storms at Mohonk Lake, New York is generated by running the model for a wide range of conditions. This includes the deuterium excess (d ≡ δD - 8*δ18O) for Antarctic snows that increases markedly as δD falls below −300‰ and the deuterium deficit observed for rain in warm, dry regions.

Estimating continental and terrestrial precipitation averages from rain-gauge networks

Abstract: © 1994 by the Royal Meteorological Society. Available from the publisher's website at http://dx.doi.org/10.1002/joc.3370140405

Incorporating Spatial Dependence and Atmospheric Data in a Model of Precipitation

Abstract: Nonhomogeneous hidden Markov models (NHMM) provide a method of relating synoptic atmospheric measurements to precipitation occurrence at a network of rain gauge stations. In previous work it was assumed that, conditional on the current atmospheric pattern (termed a “weather state”), rain gauge stations in a network could be considered spatially independent. For a spatially dense network, this assumption is not tenable. In the present work, the NHMM is extended to include the case of spatial dependence by postulating an autologistic model for the conditional probability of rainfall given the weather state. Methods for fitting the parameters, assessing the goodness of fit of the model, and generating rainfall simulations are presented. The model is applied to a network of 24 stations in the Puget Sound region of western Washington State.