Showing papers in "Journal of Hydrometeorology in 2003"

The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present)

Abstract: The Global Precipitation Climatology Project (GPCP) Version 2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5 degrees x 2.5 degrees latitude-longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit-satellite infrared data, and rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The data set is extended back into the premicrowave era (before 1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the raingauge analysis. This monthly analysis is the foundation for the GPCP suite of products including those at finer temporal resolution, satellite estimate, and error estimates for each field. The 23-year GPCP climatology is characterized, along with time and space variations of precipitation.

Explicit representation of subgrid heterogeneity in a GCM land surface scheme

Abstract: A land surface scheme that may be run with or without a tiled representation of subgrid heterogeneity and includes an implicit atmospheric coupling scheme is described. Simulated average surface air temperatures and diurnal temperature ranges in a GCM using this surface model are compared with climatology. Surface tiling is not found to give a clear improvement in the simulated climate but offers more flexibility in the representation of heterogeneous land surface processes. Using the same meteorological forcing in offline simulations using versions of the surface model with and without tiling, the tiled model gives slightly lower winter temperatures at high latitudes and higher summer temperatures at midlatitudes. When the surface model is coupled to a GCM, reduced evaporation in the tiled version leads to changes in cloud cover and radiation at the surface that enhance these differences.

Atmospheric Controls on Soil Moisture–Boundary Layer Interactions. Part I: Framework Development

Abstract: This paper investigates the influence of soil moisture on the development and triggering of convection in different early-morning atmospheric conditions. A one-dimensional model of the atmospheric boundary layer (BL) is initialized with atmospheric sounding data from Illinois and with the soil moisture set to either extremely wet (saturated) or extremely dry (20% of saturation) conditions. Two measures are developed to assess the lowlevel temperature and humidity structure of the early-morning atmosphere. These two measures are used to distinguish between four types of soundings, based on the likely outcome of the model: 1) those soundings favoring deep convection over dry soils, 2) those favoring deep convection over wet soils, 3) those unlikely to convect over any land surface, and 4) those likely to convect over any land surface. Examples of the first two cases are presented in detail. The early-morning atmosphere is characterized in this work by the newly developed convective triggering potential (CTP) and a low-level humidity index, HIlow. The CTP measures the departure from a moist adiabatic temperature lapse rate in the region between 100 and 300 mb (about 1‐3 km) above the ground surface (AGS). This region is the critical interface between the near-surface region, which is almost always incorporated into the growing BL, and free atmospheric air, which is almost never incorporated into the BL. Together, these two measures form the CTP-HIlow framework for analyzing atmospheric controls on soil moisture‐boundary layer interactions. Results show that in Illinois deep convection is trigged in the model 22% of the time over wet soils and only 13% of the time over dry soils. Additional testing varying the radiative conditions in Illinois and also using the 1D model with soundings from four additional stations confirm that the CTP-HI low framework is valid for regions far removed from Illinois.

Atmospheric Controls on Soil Moisture-Boundary Layer Interactions. Part II: Feedbacks within the Continental United States

Abstract: The CTP-HIlow framework for describing atmospheric controls on soil moisture‐boundary layer interactions is described in a companion paper, Part I. In this paper, the framework is applied to the continental United States to investigate how differing atmospheric regimes influence local feedbacks between the land surface and the atmosphere. The framework was developed with a one-dimensional boundary layer model and is based on two measures of atmospheric thermodynamic properties: the convective triggering potential (CTP), a measure of the temperature lapse rate between approximately 1 and 3 km above the ground surface, and a low-level humidity index, HIlow. These two measures are used to distinguish between three types of early-morning atmospheric conditions: those favoring moist convection over dry soils, those favoring moist convection over wet soils, and those that will allow or prevent deep convective activity, independent of the surface flux partitioning. Analyses of multiyear CTP-HIlow scatterplots from radiosonde stations across the contiguous 48 United States reveal that during the summer months (June, July, and August) positive feedbacks between soil moisture and moist convection are likely in much of the eastern half of the country. Over the western half of the country, atmospheric conditions and the likelihood of moist convection are largely determined by oceanic influences, and land surface conditions in the summer are unlikely to impact convective triggering. The only area showing a potential negative feedback is in the dryline and monsoon region of the arid Southwest. This potential arises because of the topography of this and surrounding regions. A relatively narrow band of stations lies in between the eastern and western portions of the country, in some years behaving like the stations to the west and in other years behaving like the stations to the east.

Satellite Rainfall Estimation Using Combined Passive Microwave and Infrared Algorithms

Abstract: The development of a combined infrared and passive microwave satellite rainfall estimation technique is outlined. Infrared data from geostationary satellites are combined with polar-orbiting passive microwave estimates to provide 30-min rainfall estimates. Collocated infrared and passive microwave values are used to generate a database, which is accessed by a cumulative histogram matching approach to generate an infrared temperature–rain-rate relationship. The technique produces initial estimates at 30-min and 12-km resolution ready to be aggregated to the user requirements. A 4-month case study over Africa has been chosen to compare the results from this technique with those of some existing rainfall techniques. The results indicate that the technique outlined here has statistical scores that are similar to other infrared/passive microwave combined algorithms. Comparison with the Geostationary Operational Environmental Satellite (GOES) precipitation index shows that while these algorithms result...

Operational Implementation of the ISBA Land Surface Scheme in the Canadian Regional Weather Forecast Model. Part II: Cold Season Results

Abstract: The performance of a modified version of the snow scheme included in the Interactions between Surface–Biosphere–Atmosphere (ISBA) land surface scheme, which was operationally implemented into the regional weather forecast system at the Canadian Meteorological Centre, is examined in this study. Stand-alone verification tests conducted prior to the operational implementation showed that ISBA's new snow package was able to realistically reproduce the main characteristics of a snow cover, such as snow water equivalent and density, for five winter datasets taken at Col de Porte, France, and at Goose Bay, Newfoundland, Canada. A number of modifications to ISBA's snow model (i.e., new liquid water reservoir in the snowpack, new formulation of snow density, and melting effect of incident rainfall on the snowpack) were found to improve the numerical representation of snow characteristics. Objective scores for the fully interactive preimplementation tests carried out with the Canadian regional weather fore...

ENSO and PDO Effects on Hydroclimatic Variations of the Upper Colorado River Basin

Abstract: Linkages between tropical Pacific Ocean monthly climatic variables and the Upper Colorado River basin (UCRB) hydroclimatic variations from 1909 to 1998 are analyzed at interseasonal timescales. A study of the changes in these linkages through the years and their relationship to the Pacific Decadal Oscillation (PDO) is also investigated. Tropical Pacific climate variations were represented by atmospheric/oceanic ENSO indicators. For the UCRB, warm season (April–September) streamflow totals at Lee's Ferry, Arizona, and precipitation averages at different periods (cold season: October–March; warm season: April–September; and annual: October–September) were used to study the UCRB's response to tropical Pacific climatic forcing. A basinwide ENSO signature was found in the significant correlations between warm season precipitation in the UCRB and warm season SST averages from the Nino-3 region in most of the stations around the UCRB. This link is more evident during the warm phase of ENSO (El Nino), wh...

Effects of frozen soil on soil temperature, spring infiltration, and runoff: Results from the PILPS 2(d) experiment at Valdai, Russia

Abstract: The Project for Intercomparison of Land-Surface Parameterization Schemes phase 2(d) experiment at Valdai, Russia, offers a unique opportunity to evaluate land surface schemes, especially snow and frozen soil parameterizations. Here, the ability of the 21 schemes that participated in the experiment to correctly simulate the thermal and hydrological properties of the soil on several different timescales was examined. Using observed vertical profiles of soil temperature and soil moisture, the impact of frozen soil schemes in the land surface models on the soil temperature and soil moisture simulations was evaluated. It was found that when soil-water freezing is explicitly included in a model, it improves the simulation of soil temperature and its variability at seasonal and interannual scales. Although change of thermal conductivity of the soil also affects soil temperature simulation, this effect is rather weak. The impact of frozen soil on soil moisture is inconclusive in this experiment due to the particular climate at Valdai, where the top 1mo fsoil is very close to saturation during winter and the range for soil moisture changes at the time of snowmelt is very limited. The results also imply that inclusion of explicit snow processes in the models would contribute to substantially improved simulations. More sophisticated snow models based on snow physics tend to produce better snow simulations, especially of snow ablation. Hysteresis of snowcover fraction as a function of snow depth is observed at the catchment but not in any of the models.

The Sensitivity of Global Climate Model Simulations to the Representation of Soil Moisture Heterogeneity

Abstract: Improving the treatment of subgrid-scale soil moisture variations is recognized as a priority for the next generation of land surface schemes. Here, the impact of an improved representation of subgrid-scale soil moisture heterogeneity on global climate model (GCM) simulations of current and future climates is carried out using Version three of the Hadley Centre Atmospheric Climate Model (HadAM3) coupled to the Met Office Surface Exchange Scheme (MOSES). MOSES was adapted to make use of the rainfall runoff model TOPMODEL algorithms, which relate the local water table depth to the grid box mean water table depth, assuming that subgrid-scale topography is the primary cause of soil moisture heterogeneity. This approach was also applied to produce a novel model for wetland area, which can ultimately be used to interactively model methane emissions from wetlands. The modified scheme was validated offline by forcing with near-surface Global Soil Wetness Project (GSWP) data, and online within the HadAM3 global climate model. In both cases it was found to improve the present-day simulation of runoff and produce realistic distributions of global wetland area. (Precipitation was also improved in the online simulation.) The new scheme results in substantial differences in the modeled sensitivity of runoff to climate change, with implications for the modeling of hydrological impacts.

Sensitivity of Annual Evaporation to Soil and Root Properties in Two Models of Contrasting Complexity

Abstract: Simulations of soil water and evapotranspiration with physically based models at broad scales vary in both complexity of processes modeled and in parameterization of soil and root properties. Sensitivity of annual evaporation Eann to some of these processes and parameters was tested with both a model allowing multiple soil layers (BROOK90) and a single-layered water balance model (WBM). For nine widely scattered locations in North America Eann was controlled primarily by climate and cover type, but within a location–type combination, Eann was controlled primarily by the available water capacity Wac, which is the product of available water fraction and effective root depth. The definition of the upper limit of available water is important; it is precisely defined here as the water volume fraction at 30-cm depth after 48 h of drainage from an initially saturated, homogeneous profile with a fixed gravity potential gradient at 2-m depth. Specification of root depth was as important as specification o...

Variability of Raindrop Size Distributions in a Squall Line and Implications for Radar Rainfall Estimation

Abstract: The intrastorm variability of raindrop size distributions as a source of uncertainty in single-parameter and dual-parameter radar rainfall estimates is studied using time series analyses of disdrometer observations. Two rain-rate (R) estimators are considered: the traditional single-parameter estimator using only the radar reflectivity factor (Z) and a dual-polarization estimator using a combination of radar reflectivity at horizontal polarization (ZH) and differential reflectivity (ZDR). A case study for a squall-line system passing over the Goodwin Creek experimental watershed in northern Mississippi is presented. Microphysically, the leading convective line is characterized by large raindrop concentrations (>500 drops per cubic meter), large mean raindrop sizes (>1 mm), and wide raindrop size distributions (standard deviations >0.5 mm), as compared to the transition region and the trailing stratiform rain. The transition and stratiform phases have similar raindrop concentrations and mean raind...

Real-Time Variational Assimilation of Hydrologic and Hydrometeorological Data into Operational Hydrologic Forecasting

Abstract: Variational assimilation (VAR) of hydrologic and hydrometeorological data into operational hydrologic forecasting is explored. The data assimilated are the hourly real-time observations of streamflow and precipitation, and climatological estimates of potential evaporation (PE). The hydrologic system considered is a single headwater basin for which soil moisture accounting and routing are carried out in a lumped fashion via the Sacramento model (SAC) and the unit hydrograph (UH), respectively. The control variables in the VAR formulation are the fast-varying SAC soil moisture states at the beginning of the assimilation window and the multiplicative adjustment factors to the estimates of mean areal precipitation (MAP) and mean areal potential evaporation (MAPE) for each hour in the assimilation window. In a separate application of VAR as a parameter estimation tool, the estimation of empirical UH is also explored by treating its ordinates as the control variables. To evaluate the assimilation procedure thus developed, streamflow was forecast with and without the aid of VAR for three basins in the southern plains under the assumption of perfectly forecast future mean areal precipitation (FMAP). The streamflow forecasts were then compared with each other and with those based on persistence and the state space-based state-updating procedure, the state-space Sacramento model (SS-SAC). The results indicate that the VAR procedure significantly improves the accuracy of the basic forecast at short lead times and compares favorably with SS-SAC.

The Sensitivity of Precipitation and Snowpack Simulations to Model Resolution via Nesting in Regions of Complex Terrain

Abstract: This paper examines the sensitivity of regional climate simulations to increasing spatial resolution via nesting by means of a 20-yr simulation of the western United States at 40-km resolution and a 5-yr simulation at 13-km resolution for the Pacific Northwest and California. The regional simulation at 40-km resolution shows a lack of precipitation along coastal hills, good agreement with observations on the windward slopes of the Cascades and Sierra Nevada, but overprediction on the leeside and the basins beyond. Snowpack is grossly underpredicted throughout the western United States when compared against snowpack telemetry (snotel) observations. During winter, higher spatial resolution mainly improves the precipitation simulation in the coastal hills and basins. Along the Cascades and the Sierra Nevada range, precipitation is strongly amplified at the higher spatial resolution. Higher resolution generally improves the spatial distribution of precipitation to yield a higher spatial correlation b...

Variation in Surface Energetics during Snowmelt in a Subarctic Mountain Catchment

Abstract: Surface energetics and snow ablation were examined during the 1999 snowmelt season in a mountain subarctic tundra valley in the Yukon Territory of Canada. Considerations of melt energetics at small scales were made with respect to the frame of reference of the sloping surface snowpack. During relatively warm and sunny conditions early in melt, snow ablation rates were dramatically higher on the south-facing slope and strongly reduced on the north-facing slope, compared to the valley bottom. Negative spatial covariances developed between maximum snow accumulation and ablation rate during early and middle melt, with the highest ablation rates occurring on slopes with the shallowest snowpacks. Atmospheric conditions were sufficiently well mixed across the valley that reference level air temperatures and humidity among the slopes were close to levels of measurement accuracy. However, under high levels of April insolation, notable differences in incoming solar radiation to varying slopes/aspects caused relatively larger differences in net radiation and surface temperature, which were progressively magnified as shrubs and soil became exposed during snow ablation. Under cloudier conditions later in melt, the south-facing snowpack had mostly ablated, vegetation was exposed at all sites, and ablation rates were virtually identical between the valley bottom and north-facing slope. Driven primarily by initial differences in insolation and snow accumulation, surface energy fluxes changed sign and magnitude over space, not only with insolation, vegetation cover, slope, and aspect, but also with the snow cover state and ground/ vegetation exposure. Melt rate was, hence, controlled by both incoming energy and evolving and initial snow states. For these reasons, and because of the slope-based frame of reference necessary to precisely define the snowmelt energy balance, simple aggregate representations of melt in subarctic mountain environments that are based on averaged energy flux, snow state, and flat-plane conceptions may require substantive corrections that should be explored in modeling studies.

Assessing the Impact of Horizontal Error Correlations in Background Fields on Soil Moisture Estimation

Abstract: The importance of horizontal error correlations in background (i.e., model forecast) fields for large-scale soil moisture estimation is assessed by comparing the performance of one- and three-dimensional ensemble Kalman filters (EnKF) in a twin experiment. Over a domain centered on the U. S. Great Plains, gauge-based precipitation data is used to force the “true” model solution, and reanalysis data for the prior (or background) fields. The difference between the two precipitation datasets is thought to be representative of errors that might be encountered in a global land assimilation system. To ensure realistic conditions the synthetic observations of surface soil moisture match the spatiotemporal pattern and expected errors of retrievals from the Scanning Multichannel Microwave Radiometer (SMMR) on the Nimbus-7 satellite. After filter calibration, average actual estimation errors in the (volumetric) root zone moisture content are 0.015 m3 m−3 for the 3D-EnKF, 0.019 m3 m−3 for the 1D-EnKF, and 0...

Verification of National Weather Service Ensemble Streamflow Predictions for Water Supply Forecasting in the Colorado River Basin

Abstract: The Ensemble Streamflow Prediction (ESP) system, developed by the National Weather Service (NWS), uses conceptual hydrologic models and historical data to generate a set, or ensemble, of possible streamflow scenarios conditioned on the initial states of a given basin. Using this approach, simulated historical probabilistic forecasts were generated for 14 forecast points in the Colorado River basin, and the statistical properties of the ensembles were evaluated. The median forecast traces were analyzed using ‘‘traditional’’ verification measures; these forecasts represented ‘‘deterministic ESP forecasts.’’ The minimum-error and historical traces were examined to evaluate the median forecasts and the forecast system. Distribution-oriented verification measures were used to analyze the probabilistic information contained in the entire forecast ensemble. Using a single-trace prediction, for example, the median, resulted in a loss of valuable uncertainty information about predicted seasonal volumes that is provided by the entire ensemble. The minimum-error and historical traces revealed that there are errors in the data, calibration, and models, which are part of the uncertainty provided by the probabilistic forecasts, but are not considered in the median forecast. The simulated ESP forecasts more accurately predicted future streamflow than climatology forecasts and, on average, provided useful information about the likelihood of future streamflow magnitude with a lead time of up to 7 months. Overall, the forecast provided stronger probability statements and became more reliable at shorter lead times. The distribution-oriented verification approach was shown to be applicable to ESP outlooks and appropriate for extracting detailed performance information, although interpretation of the results is complicated by inadequate sample sizes.

Impact of Land Surface Initialization on Seasonal Precipitation and Temperature Prediction

Abstract: The potential role of land initialization in seasonal forecasting is illustrated through ensembles of simulations with the NASA Seasonal-to-Interannual Prediction Project (NSIPP) model. For each boreal summer during 1997–2001, two 16-member ensembles of 3-month simulations were generated. The first, “AMIP style” (Atmospheric Model Intercomparison Project) ensemble establishes the degree to which a perfect prediction of SSTs would contribute to the seasonal prediction of precipitation and temperature over continents. The second ensemble is identical to the first, except that the land surface is also initialized with “realistic” soil moisture contents through the continuous prior application (within GCM simulations leading up to the start of the forecast period) of a daily observational precipitation dataset and the associated avoidance of model drift through the scaling of all surface prognostic variables. A comparison of the two ensembles shows that land initialization has a statistically signifi...

Coastal Orographic Rainfall Processes Observed by Radar during the California Land-Falling Jets Experiment

Abstract: Radar and rain gauge observations collected in coastal mountains during the California Land-Falling Jets Experiment (CALJET) are used to diagnose the bulk physical properties of rainfall during a wet winter season (January–March 1998). Three rainfall types were clearly distinguishable by differences in their vertical profiles of radar reflectivity and Doppler vertical velocity: nonbright band, bright band, and hybrid (seeder–feeder). The contribution of each rainfall type to the total rainfall observed at the radar site (1841 mm) was determined by a new, objective algorithm. While hybrid rain occurred most often, nonbrightband rain (NBB rain) contributed significantly (28%) to the total. This paper focuses on characterizing NBB rain because of the need to document this key physical process and because of its impact on Weather Surveillance Radar-1988 Doppler (WSR-88D) precipitation surveillance capabilities. NBB rain is a quasi-steady, shallow rain process that does not exhibit a radar bright band...

Derivation of an Effective Height for Scintillometers: La Poza Experiment in Northwest Mexico

Abstract: The large-aperture scintillometer (LAS) is by now a generally accepted device for routinely obtaining the area-averaged sensible heat flux, H, on a scale of up to 10 km. It is an optical instrument that consists of a transmitter and receiver. In practice, the LAS beam height often varies along the path due to a variety of reasons. This study will explain what effective height to use in such situations, when analyzing scintillometer data to derive H. Several aspects are covered: a slanted path over flat terrain, structured terrain, and varying path height due to the curvature of the earth’s surface. To test the derived effective height formulation the authors present LAS data taken in September and October 1996 at a rangeland site in Sonora, Mexico. In experiment 1, the LAS was set up over a slant path, ranging roughly between 10 and 45 m above the surface over a 3200-m path. In experiment 2, a horizontal LAS path was used at approximately 30 m over a pathlength of 1100 m. The resulting sensible heat fluxes were compared with eddy-covariance data and show satisfactory results for both the full and one of the approximate formulations of the effective height.

Effects of a Subgrid-Scale Topography and Land Use Scheme on the Simulation of Surface Climate and Hydrology. Part I: Effects of Temperature and Water Vapor Disaggregation

Abstract: A mosaic-type parameterization of subgrid-scale topography and land use is implemented within the framework of a regional climate model, and its effects on a multiseasonal simulation over the European region are tested, with focus on the Alpine subregion. The parameterization adopts a regular finescale surface subgrid for each coarse model grid cell. Meteorological variables are disaggregated from the coarse grid to the fine grid, land surface calculations are then performed separately for each subgrid cell, and surface fluxes are reaggregated onto the coarse grid cell for input to the atmospheric model. The primary effects of the subgrid surface scheme are 1) an improvement of the finescale structure and overall simulation of surface air temperature over complex terrain, and 2) a more realistic simulation of snow as driven by the complex terrain features. The subgrid scheme also affects the warm season simulation through feedbacks between precipitation and the surface hydrology. The primary aspe...

Examination of the Surface Energy Budget: A Comparison of Eddy Correlation and Bowen Ratio Measurement Systems

Abstract: A reliable method for monitoring the surface energy budget is critical to the development and validation of numerical models and remote sensing algorithms. Unfortunately, closure of the energy budget remains difficult to achieve among measurement systems. Reasons for nonclosure still are not clearly understood, and, until recently, few long-term datasets were available to address this issue of nonclosure. This contribution examined 108 days of a year dataset collected from collocated eddy correlation (EC) and Bowen ratio (BR) systems. Differences between systems were examined across seasonal and diurnal cycles to better understand nonclosure of the energy budget. Closure by the EC system was observed to vary with season and with time of day, primarily as a function of latent heat flux. Furthermore, the EC and BR methods partitioned energy differently, with the EC system favoring latent heat flux and the BR system favoring sensible heat flux. Instrument error, surface heterogeneity, and the theore...

A Neural Network Approach to Real-Time Rainfall Estimation for Africa Using Satellite Data

Abstract: Operational, real-time rainfall estimation on a daily timescale is potentially of great benefit for hydrological forecasting in African river basins. Sparseness of ground-based observations often means that only methodologies based predominantly on satellite data are feasible. An approach is presented here in which Cold Cloud Duration (CCD) imagery derived from Meteosat thermal infrared imagery is used in conjunction with numerical weather model analysis data as the input to an artificial neural network. Novel features of this approach are the use of principal component analysis to reduce the data requirements for the weather model analyses and the use of a pruning technique to identify redundant input data. The methodology has been tested using 4 yr of daily rain gauge data from Zambia in central Africa. Calibration and validation were carried out using pixel area rainfall estimates derived from daily rain gauge data. When compared with a standard CCD approach using the same dataset, the neural ...

Interannual and Seasonal Variability of the Surface Energy Balance and Temperature of Central Great Slave Lake

Abstract: This paper addresses interannual and seasonal variability in the thermal regime and surface energy fluxes in central Great Slave Lake during three contiguous open-water periods, two of which overlap the Canadian Global Energy and Water Cycle Experiment (GEWEX) Enhanced Study (CAGES) water year. The specific objectives are to compare the air temperature regime in the midlake to coastal zones, detail patterns of air and water temperatures and atmospheric stability in the central lake, assess the role of the radiation balance in driving the sensible and latent heat fluxes on a daily and seasonal basis, quantify magnitudes and rates of the sensible and latent heat fluxes and evaporation, and present a comprehensive picture of the seasonal and interannual thermal and energy regimes, their variability, and their most important controls. Atmospheric and lake thermal regimes are closely linked. Temperature differences between midlake and the northern shore follow a seasonal linear change from 68C colder midlake in June, to 68C warmer in November‐December. These differences are a response to the surface energy budget of the lake. The surface radiation balance, and sensible and latent heat fluxes are not related on a day-to-day basis. Rather, from final lake ice melt in mid-June through to mid- to late August, the surface waters strongly absorb solar radiation. A stable atmosphere dominates this period, the latent heat flux is small and directed upward, and the sensible heat flux is small and directed downward into the lake. During this period, the net solar radiation is largely used in heating the lake. From mid- to late August to freeze up in December to early January, the absorbed solar radiation is small, the atmosphere over the lake becomes increasingly unstable, and the sensible and latent heat fluxes are directed into the atmosphere and grow in magnitude into the winter season. Comparing the period of stable atmospheric conditions with the period of unstable conditions, net radiation is 6 times larger during the period of stable atmosphere and the combined latent and sensible heat fluxes are 9 times larger during the unstable period. From 85% to 90% of total evaporation occurs after mid-August, and evaporation rates increase continuously as the season progresses. This rate of increase varies from year to year. The time of final ice melt exerts the largest single control on the seasonal thermal and energy regimes of this large northern lake.

Evaluation of the ERA-40 Surface Water Budget and Surface Temperature for the Mackenzie River Basin

Abstract: The systematic biases in temperature and precipitation, and the surface water budget of European Centre for Medium-Range Weather Forecasts (ECMWF) 40-yr reanalysis (ERA-40) for the Mackenzie River basin are assessed by comparing monthly averages from ERA-40 with basin averages of surface observations of temperature, precipitation, evaporation, and streamflow from the Mackenzie Global Energy and Water Cycle Experiment (GEWEX) Study (MAGS). The bias and spinup of precipitation in ERA-40 changes significantly over the analysis period. On an annual basis, both precipitation bias and spinup are correlated with the analysis increment of atmospheric total column water vapor. ERA-40 has, in addition, a high bias of precipitation in spring and a low bias in fall. The monthly precipitation analysis is best for the most recent decade, when the bias of the 0–12-h forecast precipitation is only a few percent higher than the MAGS observations, and ERA-40 represents rather well the variability of monthly precip...

The Impact of 200 Years of Land Cover Change on the Australian Near-Surface Climate

Abstract: The effect of land cover change on the Australian regional-scale climate is investigated using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5). Four ensemble simulations are performed consisting of January and July experiments for eight different years with a 50-km grid spacing using natural (1788) and current (1988) vegetation cover. The statistical significance of changes that occurred following the replacement of natural vegetation with current vegetation on air temperature, rainfall, latent heat flux, and other related quantities is explored. Results show that the impact of land cover change on local air temperature is statistically significant at a 99% confidence level. Furthermore, there are indications that the observed increase in local maximum air temperatures in certain regions of Australia can be partially attributed to land cover change. The results are evidence of statistically significant changes in rainfal...

Probable Maximum Precipitation Estimation Using Multifractals: Application in the Eastern United States

Abstract: Probable maximum precipitation (PMP) is the conceptual construct that defines the magnitude of extreme storms used in the design of dams and reservoirs. In this study, the value and utility of applying multifractal analysis techniques to systematically calculate physically meaningful estimates of maximum precipitation from observations in the eastern United States is assessed. The multifractal approach is advantageous because it provides a formal framework to infer the magnitude of extreme events independent of empirical adjustments, which is called the fractal maximum precipitation (FMP), as well as an objective estimate of the associated risk. Specifically, multifractal (multiscaling) behavior of maximum accumulated precipitation at daily (327 rain gauges) and monthly (1400 rain gauges) timescales, as well as maximum accumulated 6-hourly precipitable water fluxes for the period from 1950 to 1997 were characterized. Return periods for the 3-day FMP estimates in this study ranged from 5300 to 6200 yr. The multifractal parameters were used to infer the magnitude of extreme precipitation consistent with engineering design criterion (e.g., return periods of 10 6 yr), the design probable maximum precipitation (DPMP). The FMP and DPMP were compared against PMP estimates for small dams in Pennsylvania using the standard methodology in engineering practice (e.g., National Weather Service Hydrometeorological Reports 51 and 52). The FMP estimates were usually, but not always, found to be lower than the standard PMP (FMP/PMP ratios ranged from 0.5 to 1.0). Furthermore, a high degree of spatial variability in these ratios points to the importance of orographic effects locally, and the need for place-based FMP estimates. DMP/PMP ratios were usually greater than one (0.96 to 2.0), thus suggesting that DPMP estimates can provide a bound of known risk to the standard PMP.

Estimating Rainfall Intensities from Weather Radar Data: The Scale-Dependency Problem

Abstract: Meteorological radar is a remote sensing system that provides rainfall estimations at high spatial and temporal resolutions. The radar-based rainfall intensities ( R) are calculated from the observed radar reflectivities ( Z). Often, rain gauge rainfall observations are used in combination with the radar data to find the optimal parameters in the Z‐R transformation equation. The scale dependency of the power-law Z‐R parameters when estimated from radar reflectivity and rain gauge intensity data is explored herein. The multiplicative ( a) and exponent (b) parameters are said to be ‘‘scale dependent’’ if applying the observed and calculated rainfall intensities to objective function at different scale results in different ‘‘optimal’’ parameters. Radar and gauge data were analyzed from convective storms over a midsize, semiarid, and well-equipped watershed. Using the root-mean-square difference (rmsd) objective function, a significant scale dependency was observed. Increased time- and space scales resulted in a considerable increase of the a parameter and decrease of the b parameter. Two sources of uncertainties related to scale dependency were examined: 1) observational uncertainties, which were studied both experimentally and with simplified models that allow representation of observation errors; and 2) model uncertainties. It was found that observational errors are mainly (but not only) associated with positive bias of the b parameter that is reduced with integration, at least for small scales. Model errors also result in scale dependency, but the trend is less systematic, as in the case of observational errors. It is concluded that identification of optimal scale for Z‐R relationship determination requires further knowledge of reflectivity and rainintensity error structure.

Assessing the Influence of Soil Moisture on Seasonal Climate Variability with AGCMs

Abstract: Ensembles of boreal summer atmospheric simulations, spanning a 15-yr period (1979–93), are performed with the Action de Recherche Petite Echelle Grande Echelle (ARPEGE) climate model to investigate the possible influence of soil moisture (SM) on climate variability and predictability. All experiments are forced with observed sea surface temperatures. In addition to a control experiment using interactive SM boundary conditions, two sensitivity experiments are performed with a relaxation of total SM toward different monthly mean datasets: the ARPEGE climatology and the Global Soil Wetness Project climatology. Both sensitivity experiments indicate that damping the SM variability leads to a clear and robust reduction in low-level temperature variability over most areas in the Tropics and the summer extratropics. Variability in precipitation is not necessarily reduced because the effect of reduced evaporation variability can be offset by an increase in the mean precipitation. Such an increase is howev...

Sequential Assimilation of ERS-1 SAR Data into a Coupled Land Surface–Hydrological Model Using an Extended Kalman Filter

Abstract: A first attempt to sequentially assimilate European Space Agency (ESA) Remote Sensing Satellite (ERS) synthetic aperture radar (SAR) estimations of surface soil moisture in the production scheme of a lumped rainfall–runoff model has been conducted. The methodology developed is based on the use of an extended Kalman filter to assimilate the SAR retrievals in a land surface scheme (a two-layer hydrological model). This study was performed in the Orgeval agricultural river basin (104 km2), a subcatchment of the Marne River, 70 km east of Paris, France. Assimilation was tested over a 2-yr period (1996 and 1997), corresponding to 25 SAR measurements. The improvements observed in simulating flood events demonstrate the potential of sequential assimilation techniques for monitoring surface functioning models with remote sensing data. It was demonstrated that the method could correct for some errors or uncertainties in the input data (precipitation and evapotranspiration), provided that these errors are ...

The Impact of a Prominent Rain Shadow on Flooding in California's Santa Cruz Mountains: A CALJET Case Study and Sensitivity to the ENSO Cycle

Abstract: Data from the California Land-Falling Jets Experiment (CALJET) are used to explore the causes of variations in flood severity in adjacent coastal watersheds within the Santa Cruz Mountains on 2–3 February 1998. While Pescadero Creek (rural) experienced its flood of record, the adjacent San Lorenzo Creek (heavily populated), attained only its fourth-highest flow. This difference resulted from conditions present while the warm sector of the storm, with its associated low-level jet, high moisture content, and weak static stability, was overhead. Rainfall in the warm sector was dominated by orographic forcing. While the wind speed strongly modulated rain rates on windward slopes, the wind direction positioned the edge of a rain shadow cast by the Santa Lucia Mountains partially over the San Lorenzo basin, thus protecting the city of Santa Cruz from a more severe flood. Roughly 26% ± 9% of the streamflow at flood peak on Pescadero Creek resulted from the warm-sector rainfall. Without this rainfall, th...