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D. LEE HARRIS and CHESTER P. JELESNIANSKI

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D. LEE HARRIS and CHESTER P. JELESNIANSKI

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The linearized two-dimensional hydrodynamic equations are presented in a manner which displays the principal assumptions involved. Several approximations are developed for the partial derivatives, and boundary conditions in finite difference form and the associated errors are discussed. The procedure for establishing a finite difference analog of the equations of motion and boundary conditions is illustrated, and computational stability for the solution of some simple problems is illustrated by means of examples.

The physical and computational problems associated with the introduction of friction in the computational model are discussed. It is concluded that friction should be neglected in many problems but that it must be considered in others.

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Sonja S. Folwell, Phil P. Harris, and Christopher M. Taylor

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Soil moisture plays a fundamental role in regulating the summertime surface energy balance across Europe. Understanding the spatial and temporal behavior in soil moisture and its control on evapotranspiration (ET) is critically important and influences heat wave events. Global climate models (GCMs) exhibit a broad range of land responses to soil moisture in regions that lie between wet and dry soil regimes. In situ observations of soil moisture and evaporation are limited in space, and given the spatial heterogeneity of the landscape, are unrepresentative of the GCM gridbox scale. On the other hand, satelliteborne observations of land surface temperature (LST) can provide important information at the larger scale. As a key component of the surface energy balance, LST is used to provide an indirect measure of surface drying across the landscape. To isolate soil moisture constraints on evaporation, time series of clear-sky LST are analyzed during dry spells lasting at least 10 days from March to October. Averaged over thousands of dry spell events across Europe, and accounting for atmospheric temperature variations, regional surface warming of between 0.5 and 0.8 K is observed over the first 10 days of a dry spell. Land surface temperatures are found to be sensitive to antecedent rainfall; stronger dry spell warming rates are observed following relatively wet months, indicative of soil moisture memory effects on the monthly time scale. Furthermore, clear differences in surface warming rate are found between cropland and forest, consistent with contrasting hydrological and aerodynamic properties.

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Gettys N. Harris Jr., Kenneth P. Bowman, and Dong-Bin Shin

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A global climatology of the altitude of the freezing level (0°C isotherm) is computed using 20 yr of 6-hourly output from the National Centers for Environmental Prediction (NCEP) reanalysis system. Mean statistics discussed include monthly means and climatological monthly means. Variance statistics include the standard deviation of the 6-hourly values with the month and the standard deviation of the monthly means. In the Tropics, freezing levels are highest (∼5000 m) and both intramonth and interannual variability is lowest. Freezing levels are lower and variability is higher in the subtropics and midlatitudes. In 1998 there are unusually high freezing levels in the eastern Pacific Ocean relative to the 20-yr climatology, consistent with elevated sea surface temperatures associated with the 1997–98 El Niño. Freezing levels return to near-climatological values during the last half of 1998. The individual monthly means for 1998 and the 20-yr climatology are compared with monthly means of the altitude of the bright band (melting layer) retrieved from Tropical Rainfall Measuring Mission (TRMM) precipitation radar data. Differences between TRMM and NCEP typically range from about −300 to −900 m. Differences are somewhat larger over landmasses and in zonal bands centered on ±20° latitude.

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Jonathan P. D. Mittaz, Andrew R. Harris, and Jerry T. Sullivan

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The absolute accuracy of the thermal infrared (IR) radiances and brightness temperatures derived from the Advanced Very High Resolution Radiometer (AVHRR) is still unknown, with major sources of error not yet fully understood. This is despite the fact that data from the AVHRR IR channels are widely used in deriving important atmospheric and surface parameters as well as in weather prediction, climate modeling, and other environmental studies. Central to the problem are possible errors introduced by the calibration test procedures and methodologies that can range up to approximately 0.5 K, much larger than the instrument electronic and detector noise characteristics. Further, there are known issues with the current calibration including a large mismatch of up to 0.7 K between the measured physical temperature of the internal calibration target (ICT) and its radiometric temperature estimated by using the AVHRR-observed counts. In an effort to improve this, a new approach to the calibration has been adopted that is dependent on physical instrument parameters. It is shown that this new calibration method can explain the ICT temperature mismatch as a combination of an incorrect assumption that the AVHRR was kept at a constant temperature during testing combined with the effect of scattered radiation from the test chamber and other sources. This new calibration also reduces the total biases and errors that exist when using the current operational calibration on the prelaunch data. Comparing the external calibration target temperatures to the temperatures derived using the AVHRR measurements, this new calibration can reduce an up to 0.7-K bias seen currently to an essentially zero bias with a scatter of less than 0.05 K in the SST regime. This marks an improvement of up to an order of magnitude in accuracy over the current operational calibration.

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Martin G. De Kauwe, Christopher M. Taylor, Philip P. Harris, Graham P. Weedon, and Richard. J. Ellis

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Land–atmosphere feedbacks play an important role in the weather and climate of many semiarid regions. These feedbacks are strongly controlled by how the surface responds to precipitation events, which regulate the return of heat and moisture to the atmosphere. Characteristics of the surface can result in both differing amplitudes and rates of warming following rain. Spectral analysis is used to quantify these surface responses to rainfall events using land surface temperature (LST) derived from Earth observations (EOs). The authors analyzed two mesoscale regions in the Sahel and identified distinct differences in the strength of the short-term (<5 days) spectral variance, notably, a shift toward lower-frequency variability in forest pixels relative to nonforest areas and an increase in amplitude with decreasing vegetation cover. Consistent with these spectral signatures, areas of forest and, to a lesser extent, grassland regions were found to warm up more slowly than sparsely vegetated or barren pixels. The authors applied the same spectral analysis method to simulated LST data from the Joint UK Land Environment Simulator (JULES) land surface model. A reasonable level of agreement was found with the EO spectral analysis for two contrasting land surface regions. However, JULES shows a significant underestimate in the magnitude of the observed response to rain compared to EOs. A sensitivity analysis of the JULES model highlights an unrealistically high level of soil water availability as a key deficiency, which dampens the models response to rainfall events.

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E. J. Barton, C. M. Taylor, C. Klein, P. P. Harris, and X. Meng

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Convection over the Tibetan Plateau (TP) has been linked to heavy rain and flooding in downstream parts of China. Understanding processes which influence the development of convection on the TP could contribute to better forecasting of these extreme events. TP scale (~1000 km) soil moisture gradients have been shown to influence formation of convective systems over the eastern TP. The importance of smaller-scale (~10 km) variability has been identified in other regions (including the Sahel and Mongolia) but has yet to be investigated for the TP. In addition, compared to studies over flat terrain, much less is known about soil moisture–convection feedbacks above complex topography. In this study we use satellite observations of cold cloud, land surface temperature, and soil moisture to analyze the effect of mesoscale soil moisture heterogeneity on the initiation of strong convection in the complex TP environment. We find that strong convection is favored over negative (positive) land surface temperature (soil moisture) gradients. The signal is strongest for less vegetation and low topographic complexity, though still significant up to a local standard deviation of 300 m in elevation, accounting for 65% of cases. In addition, the signal is dependent on background wind. Strong convective initiation is only sensitive to local (tens of kilometers) soil moisture heterogeneity for light wind speeds, though large-scale (hundreds of kilometers) gradients may still be important for strong wind speeds. Our results demonstrate that, even in the presence of complex topography, local soil moisture variability plays an important role in storm development.

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G. Vaughan, C. Schiller, A. R. MacKenzie, K. Bower, T. Peter, H. Schlager, N. R. P. Harris, and P. T. May

During November and December 2005, two consortia of mainly European groups conducted an aircraft campaign in Darwin, Australia, to measure the composition of the tropical upper-troposphere and tropopause regions, between 12 and 20 km, in order to investigate the transport and transformation in deep convection of water vapor, aerosols, and trace chemicals. The campaign used two high-altitude aircraft—the Russian M55 Geophysica and the Australian Grob 520 Egrett, which can reach 20 and 15 km, respectively—complemented by upward-pointing lidar measurements from the DLR Falcon and low-level aerosol and chemical measurements from the U.K. Dornier-228. The meteorology during the campaign was characterized mainly by premonsoon conditions—isolated afternoon thunderstorms with more organized convective systems in the evening and overnight. At the beginning of November pronounced pollution resulting from widespread biomass burning was measured by the Dornier, giving way gradually to cleaner conditions by December, thus affording the opportunity to study the influence of aerosols on convection. The Egrett was used mainly to sample in and around the outflow from isolated thunderstorms, with a couple of survey missions near the end. The Geophysica–Falcon pair spent about 40% of their flight hours on survey legs, prioritizing remote sensing of water vapor, cirrus, and trace gases, and the remainder on close encounters with storm systems, prioritizing in situ measurements. Two joint missions with all four aircraft were conducted: on 16 November, during the polluted period, sampling a detached anvil from a single-cell storm, and on 30 November, around a much larger multicellular storm.

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Phil P. Harris, Sonja S. Folwell, Belen Gallego-Elvira, José Rodríguez, Sean Milton, and Christopher M. Taylor

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Soil moisture availability exerts control over the land surface energy partition in parts of Europe. However, determining the strength and variability of this control is impeded by the lack of reliable evaporation observations at the continental scale. This makes it difficult to refine the broad range of soil moisture–evaporation behaviors across global climate models (GCMs). Previous studies show that satellite observations of land surface temperature (LST) during rain-free dry spells can be used to diagnose evaporation regimes at the GCM gridbox scale. This relative warming rate (RWR) diagnostic quantifies the increase in dry spell LST relative to air temperature and is used here to evaluate a land surface model (JULES) both offline and coupled to a GCM (HadGEM3-A). It is shown that RWR can be calculated using outputs from an atmospheric GCM provided the satellite clear-sky sampling bias is incorporated. Both offline JULES and HadGEM3-A reproduce the observed seasonal and regional RWR variations, but with weak springtime RWRs in central Europe. This coincides with sustained bare soil evaporation (Ebs) during dry spells, reflecting previous site-level JULES studies in Europe. To assess whether RWR can discriminate between surface descriptions, the bare soil surface conductance and the vegetation root profile are revised to limit Ebs. This increases RWR by increasing the occurrence of soil moisture–limited dry spells, yielding more realistic springtime RWRs as a function of antecedent precipitation but poorer relationships in summer. This study demonstrates the potential for using satellite LST to assess evaporation regimes in climate models.

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C. J. Merchant, A. R. Harris, E. Maturi, O. Embury, S. N. MacCallum, J. Mittaz, and C. P. Old

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This paper describes the techniques used to obtain sea surface temperature (SST) retrievals from the Geostationary Operational Environmental Satellite 12 (GOES-12) at the National Oceanic and Atmospheric Administration’s Office of Satellite Data Processing and Distribution. Previous SST retrieval techniques relying on channels at 11 and 12 μm are not applicable because GOES-12 lacks the latter channel. Cloud detection is performed using a Bayesian method exploiting fast-forward modeling of prior clear-sky radiances using numerical weather predictions. The basic retrieval algorithm used at nighttime is based on a linear combination of brightness temperatures at 3.9 and 11 μm. In comparison with traditional split window SSTs (using 11- and 12-μm channels), simulations show that this combination has maximum scatter when observing drier colder scenes, with a comparable overall performance. For daytime retrieval, the same algorithm is applied after estimating and removing the contribution to brightness temperature in the 3.9-μm channel from solar irradiance. The correction is based on radiative transfer simulations and comprises a parameterization for atmospheric scattering and a calculation of ocean surface reflected radiance. Potential use of the 13-μm channel for SST is shown in a simulation study: in conjunction with the 3.9-μm channel, it can reduce the retrieval error by 30%. Some validation results are shown while a companion paper by Maturi et al. shows a detailed analysis of the validation results for the operational algorithms described in this present article.

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