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The Pleim-Xiu land surface model (PX LSM) has been improved by the addition of a second indirect data assimilation scheme. The first, which was described previously, is a technique in which soil moisture is nudged according to the biases in 2-m air temperature and relative humidity between the model- and observationbased analyses. The new technique involves nudging the deep soil temperature in the soil temperature force-restore (FR) model according to model bias in 2-m air temperature only during nighttime. While the FR technique is computationally efficient and very accurate for the special conditions for which it was derived, it is very dependent on the deep soil temperature that drives the restoration term of the surface soil temperature equation. Thus, adjustment of the deep soil temperature to optimize the 2-m air temperature during the night, when surface forcing is minimal, provides significant advantages over other methods of deep soil moisture initialization. Simulations of the Weather Research and Forecasting Model (WRF) using the PX LSM with and without the new deep soil temperature nudging scheme demonstrate substantial benefits of the new scheme for reducing error and bias of the 2-m air temperature. The effects of the new nudging scheme are most pronounced in the winter (January 2006) during which the model's cold bias is greatly reduced. Air temperature error and bias are also reduced in a summer simulation (August 2006) with the greatest benefits in less vegetated and more arid regions. Thus, the deep temperature nudging scheme complements the soil moisture nudging scheme because it is most effective for conditions in which the soil moisture scheme is least effective, that is, when evapotranspiration is not important (winter and arid climates).

The heat pulse method enables estimation of soil thermal diffusivity (k), volumetric heat capacity (C), thermal conductivity, and water content. The heater needle and temperature-sensing needle may deflect during probe insertion into soils. The impact of needle deflection on estimates of C and k has not been fully studied theoretically or experimentally. We defined [theta] to be the polar angle of needle deviation from the z axis and [phi] to be the azimuthal angle in the x-y plane. Transient-state analytical solutions were derived for an inclined and pulsed finite line source in a parallelepiped sample with zero surface temperature and adiabatic boundary conditions. For a heat pulse sensor with 6-mm needle spacing and a heater needle of 4-cm length in a given parallelepiped (5 by 5 by 5 cm, assumed to be filled with air-dry sand), model errors in C and k were about -11.3 and 12.1%, respectively, for an inclined heater needle with [theta] = 1[degrees] and [phi] = 0[degrees]. Model errors in C and k were about -11.2 and 12.1%, respectively, for an inclined sensor needle with [theta] = 1[degrees] and [phi] = 180[degrees]. When -6 [less than or equal to] [theta] [less than or equal to] 6[degrees] for either the heater or the sensor needle, the temperature curves could be approximated rather well by a pulsed infinite line source model with a modified probe spacing that accounted for the inclination. For various heating durations and strengths, the errors in both k and C were relatively constant when all other parameters were fixed; however, the errors in both C and k decreased monotonically and slowly as k increased. The model errors in C and k were similar for four soil conditions with different thermal properties in the range -6 [less than or equal to] [theta] [less than or equal to] 2[degrees]. Abbreviations: ABC, adiabatic boundary condition; DPHP, dual-probe heat pulse; PILS, pulsed infinite line source; ZST, zero surface temperature.

Byline: Annett Wolf (1,2,5), Eleanor Blyth (3), Richard Harding (3), Daniela Jacob (4), Elke Keup-Thiel (4), Holger Goettel (4), Terry Callaghan (5,6) Abstract: We tested the sensitivity of a dynamic ecosystem model (LPJ-GUESS) to the representation of soil moisture and soil temperature and to uncertainties in the prediction of precipitation and air temperature. We linked the ecosystem model with an advanced hydrological model (JULES) and used its soil moisture and soil temperature as input into the ecosystem model. We analysed these sensitivities along a latitudinal gradient in northern Russia. Differences in soil temperature and soil moisture had only little influence on the vegetation carbon fluxes, whereas the soil carbon fluxes were very sensitive to the JULES soil estimations. The sensitivity changed with latitude, showing stronger influence in the more northern grid cell. The sensitivity of modelled responses of both soil carbon fluxes and vegetation carbon fluxes to uncertainties in soil temperature were high, as both soil and vegetation carbon fluxes were strongly impacted. In contrast, uncertainties in the estimation of the amount of precipitation had little influence on the soil or vegetation carbon fluxes. The high sensitivity of soil respiration to soil temperature and moisture suggests that we should strive for a better understanding and representation of soil processes in ecosystem models to improve the reliability of predictions of future ecosystem changes. Author Affiliation: (1) Department of Physical Geography and Ecosystem Analyses, Lund University, Lund, Sweden (2) Department of Environmental Science, Universitatsstr. 22, CH-8092, Zurich, Switzerland (3) Centre for Ecology and Hydrology, Wallingford, UK (4) Max-Planck-Institut fur Meteorologie (MPI-M), Hamburg, Germany (5) Abisko Scientific Research Station, Abisko, Sweden (6) Department of Animal and Plant Sciences, University of Sheffield, Sheffield, S10 2TN, UK Article History: Registration Date: 04/10/2007 Received Date: 06/07/2006 Accepted Date: 03/10/2007 Online Date: 27/11/2007

Understanding the spatial and temporal variation in soil temperatures is important to classification, land use, and management. To that end, mean annual soil temperature (MAST) data for Wisconsin and Michigan were modeled to (i) determine the effects of the Great Lakes and their snowbelts on soil temperatures, and (ii) better estimate the location of the boundary between the mesic and frigid soil temperature regimes in this region. The location of the mesic-frigid (M-F) line is particularly difficult to determine where east-west gradients in air temperature cross north-south trends in snowfall due to Lake Michigan. Additionally, the soil temperature regime of several Great Lakes' peninsulas near the M-F line is in question. To determine the accuracy of our soil temperature model, soil temperature data output from it were compared with data derived from thermocouples implanted in soils at 39 sites in northern Michigan that had been collecting data several times daily for more than 6 yr. Error statistics for the model show that it has essentially no mean bias when examined on an annual basis or for winter, and only a bias of 0.1[degrees]C for the warm season. The M-F line in Wisconsin and Michigan is slightly north of most previously estimated locations, and is strongly influenced by the snowbelt in southern Michigan. Soils in deep snow areas stay warmer in winter than do soils inland, increasing their MAST and forcing the M-F line north of where air temperatures alone might have placed it. Lake-effect areas also stay cold longer into the spring season, and cool down more slowly in fall. Soil temperatures in these areas are, therefore, more moderated on an annual basis, as indicated by coefficients of variation.

Experimental evidence is produced using two soils that support the hypothesis that small-scale models frozen on a centrifuge for several hours can simulate correctly full-scale soil freezing response developing in the field over one or more winters. This is not the case in small 1g models. The conclusion is based on three observations: first, that model data produce self-consistent results from tests conducted at different scales; second, that model thin sections show general scaling of ice formation; and third, that heave developing in the field under broadly similar conditions shows broadly similar heave characteristics. A small series of tests to investigate effects on heave of various temperature regimes that might exist in the field also is included.

In general, the temperature field and the heat flow of bare soils are controlled by two coupled, first-order differential equations, with the boundary condition defined by the heat flow through the surface due to net radiation and the sensible and latent heat exchange between the soil and the atmosphere. Periodic diurnal temperature variations have previously been studied using Fourier modeling techniques. In this paper, it is shown how this method can he extended to nonperiodic diurnal temperature variations and heat flows due to changing weather conditions. The time interval covered can he selected from hours up to weeks or years. The calculations are speeded significantly using Fast Fourier Transform (FFT) processing. The algorithms are generalized to multiple soil layers as well. Index Terms - Agriculture, heat flow, meteorology, modeling, remote sensing, rock, soil, temperature.

The soil microwave effective temperature ([T.sub.e]) is an important parameter which improves the accuracy of the soil surface moisture derived from low frequency microwave radiometric observations. A new semi-empirical model of [T.sub.e] at L- and C-bands is proposed. The model is based on the following inputs: the air temperature ([T.sub.a]), a deep soil temperature ([T.sub.d]), and the microwave brightness temperature measured at X band ([Lambda] [congruent] 3 cm) and V polarization ([T.sub.BXV]). Unlike other approaches based on the surface temperature ([T.sub.s]), the proposed model can be implemented without being dependent on the clear sky conditions required to measure [T.sub.s] with a spaceborne infrared radiometer. However, the proposed model may also use [T.sub.s] when available. The model was designed from a large data set simulated by a physical model for smooth bare soil. The model of [T.sub.e] was then successfully validated with experimental data acquired during a ground based experiment with the multifrequency PORTOS radiometer. This model designed from smooth soil data was successfully tested on rough bare soil using experimental data.

We have developed physically based, diurnal, and annual models for freezing/thawing moist soils subject to annual insolation, radiant heating, and cooling, and sensible and latent heat exchanges with the atmosphere. Both models have the same weather forcing, numerical scheme, and soil constitutive properties. We find that surface temperature differences over a diurnal cycle between the annual and diurnal models are as much as -5 K in March, -7 K in June, -4 K in September, and 5 K in December for 38% (by volume fraction) moist soil. This difference occurs because the annual model includes the history of energy fluxes at the surface of the soil. The annual model is linked to microwave emission models for predictions of temporal radiobrightness signatures. The model predicts a relatively weak decrease in diurnal differences in soil temperature with increased moisture content, but a significant decrease in diurnal differences in radiobrightness. It also exhibits notable perturbations in radiobrightness when soils freeze and thaw. The moisture dependent, day-to-night radiobrightness difference is enhanced by as much as -42 K at 19.35 GHz horizontal polarization for frozen soil if daytime thawing occurs.

Minimum or no-tillage of agricultural soils promotes soil conservation and improves soil fertility at lower costs. The factors that contribute to the success of conservation-tillagepractices are surface energy balance and soil temperature. In turn, these conditions are affected by solar irradiances, air temperature, water vapor densities and wind speeds. Energy balance and soil temperature models were usedto measure radiation, heat transfers and evaporation between the mulch and barestrips using a strip tillage environemnt which combines bare soil and mulch practices. The soil temperature model conformed to theoretical solutions of heat-transfer problems.