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Peter J. Wetzel

Abstract

The purpose of this note is to compare several methods for predicting the onset and quantitative amount of cloud cover over heterogeneous land surfaces. Among the methods tested are that of Wilde et al. (1985) and a new, simple parcel approach. Model comparison is accomplished by running each model using a series of six initial conditions from the Wangara experiment. Case days were chosen because they had relatively quiet synoptic conditions, and exhibited the formation of cumulus clouds from an initially mostly clear sky during the period of solar heating. Each model contains two or three free parameters that were systematically varied until the optimum agreement was reached between observed and predicted cloud amount. The single best run for each method was chosen based on the RMSE and coefficient of determination. The best runs are compared and plotted against the observations for the six case days.

Results of these limited tests do not necessarily suggest the absolute degree of accuracy to which low cloud cover may be predicted. This is left for a future study. Rather, the focus is on the relative skill and flexibility of the various models. It is shown that parcel methods, in which surface air is lifted to its equilibrium level while being diluted by a defined amount of mixed layer air, produce substantially superior prediction of cloud amount, particularly during periods of rapid cloud onset when the mean boundary layer top is swiftly rising through a new-neutral layer. Pending, verification from independent datasets, it appears that an rms error in instantaneous cloud amount of ±10% may be achievable.

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Peter J. Wetzel

Abstract

The bulk Richardson number formula for the depth of the nocturnal boundary layer (NBL) is compared to the Wangara observational data. A correlation of 0.89 is found between the observed NBL depth and the depth calculated using a fixed value of bulk Richardson number. This observed NBL depth is defined as the top of a layer, found consistently in the observations, in which the virtual potential temperature varies linearly with height. The Richardson number expression is also found to be a better estimator of NBL depth, defined in a number of other ways.

Based on these findings, a simple three-layer parameterization of the NBL is developed and shown to compare favorably with observations. Within the framework of a prognostic equation for virtual potential temperature, the model diagnoses two important NBL heights, one corresponding to the top of the turbulent layer and the other to the inversion or cooling depth. The single prognostic equation, along with four accompanying diagnostic expressions, also describes the temperature structure of the entire NBL. The model is simple enough to be integrated on a programmable hand calculator.

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Peter J. Wetzel
and
Jy-Tai Chang

Abstract

Natural land surfaces are rarely homogeneous over the resolvable scales of numerical weather prediction models. Therefore, these models must somehow account for the subgrid variability in processes that are nonlinealy dependent on surface characteristics. Because of its complex dependence on soil moisture and vegetation, the flux of latent heat is an acutely nonlinear process, involving variables which can vary widely over very short distances. Thus, if the effects of subgrid-scale surface variability are significant, they should appear most prominently in the prediction of evapotranspiration.

In this paper, a simple, explicit model for the computation of grid-cell-average evapotranspiration is presented and tested. The model incorporates a statistical distribution of soil moisture on the subgrid scale, the variance of which is obtained from observed distributions of soil moisture and precipitation. Distributions are also assumed for other surface and vegetation characteristics Water-stressed and potential evapotranspiration from both bare soil and vegetation are allowed to occur simultaneously within the grid element. Comparisons with estimated regional evapotranspiration from two extensive micrometeorological field programs verify the model under a wide range of conditions.

Sensitivity tests are also conducted with the model using the field observations and using a one-dimensional atmospheric boundary layer model which allows the surface and atmosphere to adjust interactively to changes in evapotranspiration. Results comparing point evapotranspiration computations with grid-area-averaged values show a significant impact due to the unresolved variability. In fact, in some case, the size of the grid unit can be a dominant factor in determining the mean rate of evapotranspiration. This is because of the observed increased variability of soil moisture with grid size, and because of the highly nonlinear relationships between soil moisture and evapotranspiration at a point. Other factors found important in regional evapotranspiration are radiation, surface water, soil moisture, amount of vegetation coverage, and vegetation internal resistance to moisture flow. Two factors found relatively unimportant in determining the rate of regional evapotranspiration are soil type and surface roughness length.

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Jy-Tai Chang
and
Peter J. Wetzel

Abstract

To study the effects of spatial variations of soil moisture and coverage coverage on the evolution of a prestorm environment, the Goddard mesoscale model (GMASS) was modified to incorporate a simple evapo-transpiration model that requires them two parameters. Soil moisture was estimated from an antecedent precipitation index. Relative fractional vegetation coverage was estimated from a normalized difference vegetation index (NDVI). The case study, 3–4 June 1980, is of particular interest because of the development of a tornado producing convective complex near Grand Island, Nebraska during a period of relatively weak synoptic-scale forcing. Three model simulators are compared. The first had no spatial variations in either sail moisture or vegetation; the second had soil moisture variability but no vegetation; and in the third, the observed variabilities of both soil moisture and vegetation are simulated.

The modeled of effects spatial variations of vegetation and soil moisture include the enhancement of a stationary front oriented northwest-southeast through Grand Island. Prior to sunset, the unstable boundary layer collapses over a zone of cool surface temperature aligned with the observed front and coincident with an observed dry/moist soil boundary. Following the boundary layer collapse, the evolution of the ageostrophic flow exhibits a horizontally differential acceleration that amplifies the isolated upward motion over the frontal boundary. It is shown that the observed stationary front was strongly enhanced by differential heating caused by observed gradients of soil moisture, as acted upon by the vegetation cover. Thus, the run with realistic vegetation and soil moisture produces the best forecast of storm precursor conditions.

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Peter J. Wetzel
and
Jy-Tai Chang

Abstract

Evapotranspiration observations have traditionally been scaled by potential evapotranspiration as a means of unifying the soil moisture-evapotranspiration relationship under a variety of meteorological conditions. However, this scaling alone does not unify the relationship during the drying. supply-limited phase. In this paper, a second scaling parameter is identified which applies to this phase of evapotranspiration. The parameter is a maximum sustainable, or threshold evapotranspiration, which occurs in vegetation-covered surfaces just before leaf stomata close, and occurs when surface tension begins to significantly restrict the moisture release from bare soil pores. Simple expressions for this parameter are presented for the cases of vegetation cover and bare soil. The number of input variables required in these expressions is rather small.

We examine the effect of natural soil heterogeneities on evapotranspiration as computed from the proposed model. It is shown that the observed natural variability in soil moisture resulting from these heterogeneities is large enough to seriously alter the relationship between regional evapotranspiration and the area average soil moisture when compared to the point or homogeneous relationship. The implications for remote sensing and grid point numerical models are discussed. As a consequence of these results, we propose some key elements of a very simple parameterization for regional evapotranspiration for use in numerical models.

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Peter J. Wetzel
and
Robert H. Woodward

Abstract

Five days of clear sky observations over Kansas and Nebraska are used to examine the statistical relationship between soil moisture and infrared surface temperature observations taken from a geosynchronous satellite. The approach relies on numerical model results to identify important variables other than soil moisture which have a significant effect on the surface temperature, and to define linear relationships between these variables and surface temperature. Linear regression is used to relate soil moisture to surface temperature and other variables that represent wind speed, vegetation cover, and low-level temperature advection. Results show good agreement between estimated and observed soil moisture features on each of the 5 days. The average coefficient of determination for five pseudo-independent tests in which the test day is held out of the regression is 0.71. When advection is neglected in these tests the average value of r 2 drops to 0.57.

It is shown that a depiction coefficient of 0.92, when used to compute antecedent precipitation index (API), produces the best correlation between API and soil moisture as interred from GOES thermal infrared data. By averaging daily predicted values over the 5-day rain-free case study period, 92% of the variance of the morning surface temperature change is explained by a simple multiple linear regression with all independent variables, or, alternatively, 85% of the observed variance in API is explained. It is concluded that this approach can distinguish at least four classes of soil wetness, but the necessity for measurement of surface advection may limit its usefulness in remote areas.

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Peter J. Wetzel
and
Aaron Boone

Abstract

This paper presents a general description of, and demonstrates the capabilities of, the Parameterization for Land–Atmosphere–Cloud Exchange (PLACE). The PLACE model is a detailed process model of the partly cloudy atmospheric boundary layer and underlying heterogeneous land surfaces. In its development, particular attention has been given to three of the model's subprocesses: the prediction of boundary layer cloud amount, the treatment of surface and soil subgrid heterogeneity, and the liquid water budget. The model includes a three-parameter nonprecipitating cumulus model that feeds back to the surface and boundary layer through radiative effects. Surface heterogeneity in the PLACE model is treated both statistically and by resolving explicit subgrid patches. The model maintains a vertical column of liquid water that is divided into seven reservoirs, from the surface interception store down to bedrock.

Five single-day demonstration cases are presented, in which the PLACE model was initialized, run, and compared to field observations from four diverse sites. The model is shown to predict cloud amount well in these while predicting the surface fluxes with similar accuracy. A slight tendency to underpredict boundary layer depth is noted in all cases.

Sensitivity tests were also run using anemometer-level forcing provided by the Project for Inter-comparison of Land-surface Parameterization Schemes (PILPS). The purpose is to demonstrate the relative impact of heterogeneity of surface parameters on the predicted annual mean surface fluxes. Significant sensitivity to subgrid variability of certain parameters is demonstrated, particularly to parameters related to soil moisture. A major result is that the PLACE-computed impact of total (homogeneous) deforestation of a rain forest is comparable in magnitude to the effect of imposing heterogeneity of certain surface variables, and is similarly comparable to the overall variance among the other PILPS participant models. Were this result to be bourne out by further analysis, it would suggest that today's average land surface parameterization has little credibility when applied to discriminating the local impacts of any plausible future climate change.

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Andrew J. Negri
,
Robert F. Adler
, and
Peter J. Wetzel

Abstract

The Griffith-Woodley Technique (GWT) is an approach to estimating precipitation using infrared observations of clouds from geosynchronous satellites. It is examined in three ways: an analysis of the terms in the GWT equations; a case study of infrared imagery portraying convective development over Florida; and the comparison of a simplified equation set and resultant rain maps to results using the GWT. The objective is to determine the dominant factors in the calculation of GWT rain estimates.

Analysis of a single day's convection over Florida produced a number of significant insights into various terms in the GWT rainfall equations. Due to the definition of clouds by a threshold isotherm (−20°C), the majority of clouds on this day did not go through an idealized life cycle before losing their identity through merger, splitting, etc. As a result, 82% of the clouds had a defined life of 1 h (two images) or less: 64% of the defined clouds were assessed no rain because the empirically derived ratio of radar echo area to cloud area was zero for 64% of the sampled clouds. For 76% of the sample, the temperature weighting term was identically 1.0. Terms not directly related to cloud area were essentially uncorrelated with GWT rain volume, but cloud area itself was highly correlated (r=0.93). Discriminating parameters in the GWT rain apportionment algorithm were the temperatures that define the coldest 50% and coldest 10% cloud areas. Further apportionment beyond these two thresholds was found to be unnecessary. Simplifying assumptions were made to the GWT such that the resultant equations were independent of cloud life history. Application of a simple algorithm incorporating these assumptions led to daily rainfall patterns on three days that were, to first order, the same as those calculated from the GWT. Daily totals in the FACE target area were actually closer to the gage determined rain depths than the GWT estimates. Correlations between half-hourly estimates from both techniques and the gage amounts were poor. We conclude that the GWT is unnecessarily complicated for use in estimating daily rainfall. A method in which the relationship between clouds and rain is simple and straightforward can, to first order, duplicate the results of the GWT.

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Peter J. Wetzel
,
William R. Cotton
, and
Ray L. McAnelly

Abstract

An eight-day episode in August 1977 is described, wherein 14 mesoscale convective complexes (MCCs) developed in the central United States, including one to the immediate Ice of the Rocky Mountains on each day of the episode. In Part I of this article, the daytime genesis of one of these systems was traced from its pre-convective roots in the mountains of central Colorado to its incipient MCC stage on the plains of eastern Colorado. In this paper, its continued nocturnal development into a large MCC over Kansas is followed. Satellite imagery shows that this system remained coherent for at least three days as it passed off the east coast and across the western Atlantic Ocean.

Analysis is focused on the mature stage of this and a second MCC in the episode in order to compare their major dynamic features to those of similar midlatitude systems reported in the literature, and also to previous studies of tropical mesoscale convective systems. Many of the important characteristics of midlatitude MCCs found by other authors are consistent with those studied here. In addition, significant similarities were found between the structure of these MCCs and developing tropical cloud clusters. It is concluded that the MCCs analyzed here are basically tropical in nature.

A number of previously unreported features are found common to the two MCCs studied here. Among thew are a 50 kPa divergence/convergence couplet, hypothesized to be an adjustment of the flow around an “obstacle,” and a ring of convergence at 20 kPa surrounding the large circular, divergent anvil region. Also, the high-speed upper-tropospheric outflow in the vicinity of the MCCs is shown to be shallow, indicating that the effect of these systems on the upper-tropospheric flow, in terms of changes in total kinetic energy, may not be as large as implied in previous work. Finally, computations show that while the two MCCs generated vertical velocities comparable to those associated with cyclogenesis, they transported virtually no heat meridionally, suggesting that MCCs are primarily driven by buoyant forces.

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Barry H. Lynn
,
Wei-Kuo Tao
, and
Peter J. Wetzel

Abstract

A two-dimensional version of a cloud-resolving model was used to study the generation of deep moist convection over heterogeneous landscapes. Alternating patches of dry and wet soil were simulated for various profiles of background wind. Results suggested a significant, systematic impact of patch length and background wind on moist convection. Rainfall occurred most intensely along sea-breeze-like fronts, which formed at patch boundaries. Total accumulated rainfall—as the average over simulations with the same patch size but with different background wind profiles—was largest for a patch length of 128 km. This patch length was similar in size to a local radius of deformation (r o = HN/ω). The deposition of rainfall generated a much different distribution of soil moisture after one day of model simulation. This new distribution, however, was far from equilibrium, as the landscape still consisted of a number of wet and dry soil patches. The cloud structure of moist convection was also examined using a cloud classification technique. The greatest percentage of rainfall that occurred from deep clouds (which had “roots” in the middle troposphere) was also obtained over patches with length similar to r o . The results suggest the need to account for the triggering of moist convection by land surface heterogeneity in regional- and global-scale atmospheric models. It is also necessary to include the impact of patch size on cloud type. Moreover, because the distribution of soil moisture patches evolves over time in response to background atmospheric conditions, further study is suggested to gain a more full understanding of local-scale feedbacks between moist convection and soil moisture.

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