H13D-0455 1340h
Soil Water Adsorption and Evaporation During the Dry Season in an Arid Zone
The purpose of this study was to describe the daily pattern of changes in water content in the upper soil layers of a bare loess soil in the Negev desert throughout the dry season and to assess the corresponding relative magnitude of latent heat flux density. The measurements were carried out in the Northern Negev, Israel, over a bare loess soil, during nine 24-h field campaigns throughout the dry season of 2002. In addition to a micrometeorological station that was set up in the research site, an improved micro-lysimeter was installed. During each campaign, the 100-mm topsoil was sampled hourly, and water content at ten mm increments was obtained. A clear discernible daily cycle of water content in the upper soil layers was observed due to direct adsorption of water vapor by the soil and consequent evaporation. Although the water content of the uppermost soil is significantly lower than the wilting point, for which most of the commonly used meteorological models would assume no latent heat flux, the latter was $\sim$20% of the net-radiation during the night and 10-15% during the day. It is, therefore, concluded that latent heat flux plays a major role in the dissipation of the net radiation during the dry season in the Negev desert.
H13D-0456 1340h
The Flooding-drying Cycle in Rain-fed Seasonal Meadows, Central California
Abstract. This paper presents a methodology to calculate the infiltration and ponding hydrographs in rain-fed wetlands with negligible overland drainage. The flooding cycle is made up of at most three phases. In the first, the rainfall rate equals the infiltration rate and there is no ponding. The second phase begins with the initiation of ponding and ends with the end of rainfall or of ponding, whichever comes first. The third, and last, phase, starts with the end of rainfall -provided that there is ponded water still extant- and ends with the extinction of ponding. The ponding and infiltration hydrographs are calculated by solving ordinary differential equations of water balance and soil-water flow. Two variables of special interest are the maximum ponding depth and the duration of ponding, which are valuable for assessing flooding potential and ecological functioning. Several computational examples quantify the infiltration and ponding hydrographs in seasonal meadows -underlain by soils with a wide range of hydraulic properties- using design storms with realistic flooding potential. The computational examples are supported with field-derived soil properties.
H13D-0457 1340h
Role of Land-Atmosphere Interactions on Convection Initiation and Precipitation over the Southern Great Plains
Numerical simulations using the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) examine the impact of land-vegetation processes on convective initiation for the International H2O Project 2002 case study period 24-25 May 2002. For the control run COAMPS is configured with the WRF (Weather Research and Forecasting model) version of the Noah land surface model (LSM) and initialized using a high-resolution land-surface data assimilation system (HRLDAS). Physically consistent surface fields are ensured by an 18-month spin-up time for HRLDAS, and physically consistent mesoscale fields are ensured by a 2-day data-assimilation spin-up for COAMPS. Partially because of the spin-up procedure, the control run replicates the major mesoscale features of the cold front that moved across Kansas and Oklahoma during the case study time and the dryline that moved across the Texas and Oklahoma Panhandles, albeit with a 2-3 hour delay in convective initiation. Three sensitivity simulations are performed to assess the impact of land-vegetative processes on the modeled pre- and post-storm environment by: (1) replacing the Noah LSM with a simple slab soil model, (2) adding a photosynthesis, canopy resistance/transpiration scheme (the Gas Exchange/photosynthesis-based evapotranspiration Model, GEM) to the Noah LSM, and (3) replacing the HRLDAS soil moisture with the National Centers for Environmental Prediction (NCEP) 40-km Eta Data Assimilation (EDAS) operational soil fields. The location and timing of the front and convection and the structure of the dryline prove to be sensitive to land-vegetative processes. For this case the control and GEM simulations agree best with observations. The GEM run provides the strongest coupling between the surface, vegetation and atmosphere, a reflection of the importance of evapotranspiration and soil moisture and its responsiveness to environmental characteristics. The sensitivity of the synoptically forced strong convection to land surface processes indicates that such enhancements are important and need to be included in weather forecasting models, particularly for severe storm forecasting where local scale information is important. Additional studies with different synoptic conditions, storm characteristics, as well as surface conditions are recommended.
H13D-0458 1340h
Steady-State Upward Flow Through Layered Soils Under Shallow Water Table Conditions
The maximum steady state upward movement of water from a shallow water table in response to evaporation is of interest to crop water supply, water budgeting, and the estimation of evapotranspiration. In practice, soil profiles are often assumed to be homogenous to simplify calculations. Under certain conditions this assumption can lead to serious error in determining the connectivity between the shallow water table and the evaporating surface. Herein we investigate the conditions under which the steady state upward movement of water through a two-layered soil profile deviates from that of a homogenous soil. The effect of layering sequence, layer thickness, and similarity of layer hydraulic properties are addressed. Under shallow water table depths the rate of upward water movement decreased below that of both homogenous soils as the thickness of the top coarse layer decreased for a soil profile composed of a fine layer overlain by a coarse layer. In contrast the rate of upward water movement increased above that of both homogenous soils under shallow water table depths for the alternate case of a fine soil on top of coarse soil as the top fine layer thickness decreased. Under deep water table conditions the upward flow approached that of the homogenous coarse soil for both layering sequences. At these deeper water table depths the case of the coarse soil over the fine soil approached that of the homogenous coarse soil much more rapidly than the case of the fine soil on top of the coarse.
H13D-0459 1340h
Observational Analyses of Hydrologic Scaling: the Role of Non-Local Interactions as Inferred From Soil Moisture and Precpitation Data
Using sparsely and infrequently measured soil moisture data, and a technique using conditional averaging of precipitation to estimate outflow, we investigate the effect of non-local interactions and moisture anomalies present in scaling local moisture-outflow relationships from points to larger areas. To investigate the presence of non-local interactions, locations are modeled as a set of independent columns and the moisture-outflow relationships are aggregated in such a way as to account for heterogeneity; this estimate is compared statistically to the large-scale response estimated from aggregate data. Significant differences would suggest the system is not well represented by the independence assumption, i.e. local outflow is dependent on local moisture and also is independently influenced by large-scale moisture. We applied these methods to data from three systems - a hillslope, an intermediate-sized watershed, and the state of Illinois, and found that heterogeneity coupled with non-linearity of the governing processes significantly affected scaling in all three. After accounting for these, significant differences remained between the aggregated point-scale estimates and the large-scale response. This difference is attributable to non-local influences on the local systems; in each area studied, the effect is to decrease (increase) local outflow during large-scale dry (wet) anomalies; evidence in Illinois points to a possible atmospheric pathway through an effect on wind speed. The apparent effect of the interactions is to prolong small spatial anomalies of moisture, and at the same time to decrease the temporal variability of the large-scale system. The results here suggest possible common dynamic and scaling effects in water balance at various scales, as well as large-scale dependencies of local climate on larger-scale soil moisture anomalies.
H13D-0460 1340h
Making Existing Surface Albedo Products Compatible with the Needs of Land Surface Models
Improving the estimates of the radiation fluxes in particular and energy budget in general over continental surfaces requires the assimilation of relevant and measurable variables responding to the various types of forcings that can be experienced by land-surfaces. Surface albedo is one such variable controlling the net radiation fluxes which can themselves also be estimated from space-borne sensors. Albedo products are nowadays delivered routinely by various space agencies. However, the word "surface albedo" covers various meanings depending on the level of sophistication adopted to account for the coupling between the bidirectional properties of the surface and the diffuse irradiance available at the bottom of the atmosphere. This state of affairs renders the use and intercomparison of these albedo products more difficult than would appear at first sight.This presentation will first describe albedo as a problem involving the radiative coupling of the surface and the atmosphere, and then illustrate the relationships linking the various albedo products currently available from various instruments. Once established, such relationships allow to intercompare surface albedo products from MODIS, MISR and Meteosat. Preliminary results in this direction will be shown. These efforts should prove useful to bridge the gap between the remote sensing derived products and the modeling needs of the climate and hydrology community.
H13D-0461 1340h
Climate Model Parameterization is a Form of Statistical Modeling - Application to Land Surface Representation and Treatment of Hydrological Cycling
The concept of parameterization was introduced in the early days of climate modeling to describe simple rules that were assumed to treat scales of motion not resolved by climate models. Such rules have generally neglected that there are multiple scales being neglected. What is done is best understood as a form of statistical modeling that is designed to optimally relate statistics of small scale processes to state parameters on the scale resolved by the model. It is not inevitable that such parameterization should forget about what are the spatial scales over which smaller scale processes occur. The land surface component of climate models is a nice example of this assertion. It is essentially all parameterization as it involves describing processes at a local site scale and then averaging them to model resolved scales. However, multiple scales of land can be distinguished that need to be separately addressed. Satellite data can now look at the land surface at a scale as fine as 1-m and this information can be used to calibrate other satellites providing global coverage. This paper works through the formalism whereas land at fine scales can be included computationally in a climate model by appropriate statistical modeling. Some of the important scaling issues are described. Examples are given from work with the CLM3 land model coupled to the CAM3 (Community Climate Model components supported by NCAR
H13D-0462 1340h
The Impact of Soil Moisture Initialization on Seasonal Precipitation in the West African Sahel Using the Regional Spectral Model
This study investigates the extent to which prior knowledge of soil moisture states can influence seasonal precipitation predictability in the West African Sahel. Model studies have suggested that the impact of land state initialization on precipitation may be most significant in transition (semi-arid) zones such as the Sahel. Results will be presented from (1) a preliminary sensitivity analysis that consists of a one-month integration to assess the atmospheric response to extreme dry and wet soil conditions, (2) a 22 year EOF analysis of May/June monthly Reanalysis-2 soil moisture data to identify the leading modes of soil moisture variability in the region and (3) a sensitivity analysis that consists of a seasonal integration (May-October) initialized with soil moisture patterns that are characteristic of the first two leading modes of soil moisture variability.
H13D-0463 1340h
The effect of vegetation optical depth on temporal variation of soil moisture
Various remote sensing techniques have been evaluated and proven to be a valuable source of information for different hydrological applications. With the actual Earth observation satellites, we can observe the entire river basin rather than sparse points and provide unique information about properties of the surface or shallow layers of the earth. The actual remote sensing sensors offer the potential of measuring new hydrologic variables particularly valuable for flood forecasting and hydrological modeling. Soil moisture is one of those parameters, which plays a central role in a wide variety of hydrological system processes. Soil moisture is an important component of the hydrological cycle. The capability to observe soil moisture frequently and over large regions could significantly improve our ability to estimate some hydrological parameters such as infiltration, runoff, and soil wetness. The primary intent of this project was to map the spatial variability of soil moisture and to assess the effect of the vegetation optical depth on this variability. The outcome of this project will be used to better understand the effect of the vegetation optical depth on soil moisture variation. A rigorous assessment of this effect will help us to reduce the negative role of the vegetation on classification accuracy. The study area is located in Oklahoma (97d35'W, 36d15'N). The soil moisture data were collected over a 10,000 km2 using ESTAR Instrument (Electronically Scanned Thinned Array Radiometer) during the SGP97 campaign (operated by NASA). The SFP97 was a large, interdisciplinary experiment carried out over a month period in 1997. The derived soil moisture from different dates, with 800 m resolution, was analyzed and regrouped in different classes. The preliminary results showed that the vegetation optical depth has no significant effect on the temporal variation of soil moisture. This may partly be explained by the fact that the brightness temperature measured by ESTAR is more affected by the soil moisture than the vegetation wetness.
H13D-0464 1340h
Temporal variations in global simulated soil moisture
Soil moisture is a central term of the land surface water budget and is a key element in land-atmosphere coupling. It provides insight into drought occurrence and is an indicator of agricultural vigor and water resources potential. Soil moisture also provides opportunities for seasonal prediction of local and remote climate. Determining the temporal variation of soil moisture and how this varies globally will improve our understanding of these issues. In this study we analyse the temporal variability in global soil moisture fields, as derived from long-term simulations of the land surface water budget, and its potential predictability through climate teleconnections. The simulations use a hybrid meteorological forcing dataset, comprising high temporal resolution data from reanalysis combined with high spatial resolution data from monthly observation datasets, to drive the Variable Infiltration Capacity (VIC) hydrologic model. The resultant water and energy fluxes and states are available globally at 1 degree resolution for 1950-2000. We investigate the variability of the soil moisture fields over various time scales from daily to seasonal. From this we are able to make estimates of predictability of soil moisture at seasonal time scales. Potential predictability can be defined by the ratio of the magnitude of the seasonal variation of a variable to that of random variation due to the weather, which is basically a signal to noise problem. Statistical techniques are employed to quantify potential predictability for soil moisture and other water cycle components globally. The source of seasonal time scale signals in soil moisture may be from large-scale climate anomalies. We explore teleconnections with various climate indices such as ESNO and NAO and their role in seasonal prediction.
H13D-0465 1340h
Predictability of hydrological variables and their seasonal prediction in the GFDL climate model
A set of 22-year (1979-2000) AMIP-type integrations with multiple ensembles were performed with one recent version of the GFDL climate model to investigate the predictability of hydrological variables, especially precipitation, at seasonal timescale. The variability of the annual and seasonal precipitation are estimated with these integrations. Then a suite of integrations, all with a similar setup, were esigned and carried out as to decompose the total variability into different components, which are related to variations of the essential elements of the climate system, namely, the ocean, the land surface and the atmosphere. It is found that ocean (sea surface temperature) plays the dominant role in determining the precipitation variability at seasonal to interannual timescales in the tropics and much of the mid-latitudes. The land surface, has some contribution to the precipitation variability, and it contributes to the potential predictability of the hydrological cycle over the continents. Therefore, we speculate that a soil moisture initialization will also help improve the seasonal prediction of the hydrological cycle over land. This speculation is tested with seasonal hindcasts for several selected years using the GFDL climate model. Different land surface initial conditions are used to make different sets of ensemble forecast. We show that realistic soil moisture initial conditions are able to improve the skill of seasonal forecast.