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Middle and eastern routes of the South-North Water Diversion Project (SNWDP) of China, which are approximately located within the area 28°-42°N and 110°-122°E, are being constructed. This paper investigates the past climatic variations on various time scales using instrumental and proxy data. It is found that annual mean surface air temperature has increased significantly during the past 50-100 years, and winter and spring temperatures in the northern part of the region have undergone the most significant changes. A much more significant increase occurs for annual mean minimum temperature and extreme low temperature than for annual mean maximum temperature and extreme high temperature. No significant trend in annual precipitation is found for the region as a whole for the last 50 and 100 years, although obvious decadal and spatial variation is detectable. A seesaw pattern of annual and summer precipitation variability between the north and the south of the region is evident. Over the last 100 years, the Haihe River basin has witnessed a significant negative trend of annual precipitation, but no similar trend is detected for the Yangtze and Huaihe River basins. Pan evaporation has significantly decreased since the mid-1960s in the region in spite of the fact that the trend appears to have ended in the early 1990s. The negative trend of pan evaporation is very significant in the plain area between the Yangtze and Yellow Rivers. There was a notable series of dry intervals lasting decades in the north of the region. The northern drought of the past 30 years is not the most severe in view of the past 500 years; however, the southern drought during the period from the 1960s to the 1980s may have been unprecedented. The dryness-wetness index (DWI) shows significant oscillations with periodicities of 9.5 and 20 years in the south and 10.5 and 25 years in the north. Longer periodicities in the DWI series include 160-170- and 70-80-yr oscillations in the north, and 100-150-yr oscillations in the south. The observed climate change could have implications for the construction and management of the SNWDP. The official approval and start of the hydro project was catalyzed by the severe multiyear drought of 1997-2003 in the north, and the operation and management of the project in the future will also be influenced by climate change-in particular by precipitation variability. This paper provides a preliminary discussion of the potential implications of observed climate change for the SNWDP. [ABSTRACT FROM AUTHOR]

In simulations of deep convection with cloud-resolving models the turbulence is often rather poorly resolved, and the influence of the subfilter-scale parameterization used in such circumstances is probably greater than in better-resolved simulations. Therefore a study to investigate the influence of stochastic backscatter was performed and presented in two papers. This first paper focuses on a description of the stochastic backscatter model and its effect on a neutral and a dry convective boundary layer. The second paper then deals with two cases of deep convection. The dry convective boundary layer is typical of the subcloud layer in deep convection and this study allows for influences on this layer to be investigated separately. As a simple case of convection it also allows for general effects to be identified. The implementation of stochastic backscatter was improved to ensure an appropriate scale of backscatter that is independent of any mesh refinements and always spatially isotropic. It can also be applied in a deep atmosphere with use of the anelastic approximation. Generally the backscatter is found to affect the velocity and scalar variances as well as the spatial structure and time development of the simulations. An additional issue is the marked influence of both varying resolution and backscatter on the near-surface temperature differences. This is an element of the complex issue of surface transfers under free convection conditions. Overall, the investigations show that the backscatter gives some beneficial changes to the simulations, which tend to keep results in less well- resolved cases closer to those in better-resolved simulations. [ABSTRACT FROM AUTHOR]

A method for the extrapolation of vertical profiles of temperature (and/or steric heights) from measurements of sea surface elevation and sea surface temperature has been developed and is described here. The technique, called coupled pattern reconstruction (CPR), is based on a multivariate analysis of the coupled variability of vertical profiles from historical hydrographic data and on the hypothesis that only few modes are needed to explain most of the covariance of the fields. Through a linear regression between the amplitudes of the coupled modes it is possible to reconstruct the first two modes by solving a simple linear system written for the surface values, which are supposed to be known. The CPR method has been applied and tested on 9 yr of conductivity– temperature–depth (CTD) measurements collected in the northern Mediterranean Sea during the Dynamiques des Flux de Matière en Mediterranée (DYFAMED) program (1994–2002). The first 6 yr were used as a training dataset, while the last 3 were set aside as independent test measurements. Results have demonstrated a substantial improvement in terms of absolute error with respect to an ad hoc climatology, and slightly worse performances compared to the most advanced technique found in literature, which consists of the single empirical orthogonal function reconstruction (sEOF-R) through a multivariate regression of the amplitudes, except for the very first meters. However, CPR is demonstrated to be much more robust and better performing with respect to sEOF-R when considering the errors associated with real measurements of sea surface elevation. [ABSTRACT FROM AUTHOR]

A one-dimensional (1D) version of a blowing snow model, called PIEKTUK-D, has been incorporated into a snow-sea ice coupled system. Blowing snow results in sublimation of approximately 12 mm of snow water equivalent (SWE), which is equal to approximately 6%% of the annual precipitation over 324 days from 1997 to 1998. This effect leads to an average decrease of 9 cm in snow depth for an 11-month simulation of the Surface Heat Budget of the Arctic Ocean (SHEBA) dataset (from 31 October 1997 to 1 October 1998). Inclusion of blowing snow has a significant impact on snow evolution between February and June, during which it is responsible for a decrease in snow depth error by about 30%%. Between November and January, however, other factors such as regional surface topography or horizontal wind transport may have had a greater influence on the evolution of the snowpack and sea ice. During these few months the new system does not perform as well, with a snow depth percentage error of 39%%-much larger than the 12%% error found between February and June. The results also indicate a slight increase of 4 cm on average for ice thickness, and a decrease of 0.4 K for the temperature at the snow-ice interface. One of the main effects of blowing snow is to shorten the duration of snow cover above sea ice by approximately 4 days and to lead to earlier ice melt by approximately 6 days. Blowing snow also has a very small impact on internal characteristics of the snowpack, such as grain size and density, leading to a weaker snowpack. [ABSTRACT FROM AUTHOR]

Mixing due to sheared salt fingers is studied by means of direct numerical simulations (DNS) of a double-diffusively unstable shear layer. The focus is on the ''moderate shear'' case, where shear is strong enough to produce Kelvin--Helmholtz (KH) instability but not strong enough to produce the subharmonic pairing instability. This flow supports both KH and salt-sheet instabilities, and the objective is to see how the two mechanisms work together to flux heat, salt, and momentum across the layer. For observed values of the bulk Richardson number Ri and the density ratio Rρρ, the linear growth rates of KH and salt-sheet instabilities are similar. These mechanisms, as well as their associated secondary instabilities, lead the flow to a fully turbulent state. Depending on the values of Ri and Rρρ, the resulting turbulence may be driven mainly by shear or mainly by salt fingering. Turbulent mixing causes the profiles of temperature, salinity, and velocity to spread; however, in salt-sheet-dominated cases, the net density (or buoyancy) layer thins over time. This could be a factor in the maintenance of the staircase and is also an argument in favor of an eventual role for Holmboe instability. Fluxes are scaled using both laboratory scalings for a thin layer and an effective diffusivity. Fluxes are generally stronger in salt-sheet-dominated cases. Shear instability disrupts salt-sheet fluxes while adding little flux of its own. Shear therefore reduces mixing, despite providing an additional energy source. The dissipation ratio ΓΓ is near 0.2 for shear-dominated cases but is much larger when salt sheets are dominant, supporting the use of ΓΓ in the diagnosis of observed mixing phenomena. The profiler approximation ΓΓ z, however, appears to significantly overestimate the true dissipation ratio. [ABSTRACT FROM AUTHOR]

Prior efforts have produced a sea surface temperature (SST) optimum interpolation (OI) analysis that is widely used, especially for climate purposes. The analysis uses in situ (ship and buoy) and infrared (IR) satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Beginning in December 1997, “microwave” SSTs became available from the Tropical Rainfall Measuring Mission (TRMM) satellite Microwave Imager (TMI). Microwave SSTs have a significant coverage advantage over “IR” SSTs because microwave SSTs can be retrieved in cloud-covered regions while IR SSTs cannot. However, microwave SSTs are at a much lower spatial resolution than the IR SSTs. In this study, the impact of SSTs derived from TMI was tested from the perspective of the OI analysis. Six different versions of the OI were produced weekly from 10 December 1997 to 1 January 2003 using different combinations of AVHRR and TMI data and including versions with and without a bias correction of the satellite data. To make the results more objective, 20% of the buoys were randomly selected and the SSTs from these buoys were withheld from the OI for independent verification. The results of the intercomparisons show that both AVHRR and TMI data have biases that must be corrected for climate studies. These biases change with time as physical properties of the atmosphere change and as satellite instruments and the orbits of the satellites, themselves, change. It is critical to monitor differences between satellite and other products to quickly diagnose any of these changes. For the OI analyses with bias correction, it is difficult using the withheld buoys to clearly demonstrate that there is a significant advantage in adding TMI data. The advantage of TMI data is clearly shown in the OI analyses without bias correction. Because IR and microwave satellite algorithms are affected by different sources of error, biases may tend to cancel when both TMI and AVHRR data are used in the OI. Bias corrections cannot be made in regions where there are no in situ data. In these regions, the results of the analyses without bias corrections apply. Because there are areas of the ocean with limited in situ data and restricted AVHRR coverage due to cloud cover, the use of both TMI and AVHRR should improve the accuracy of the analysis in these regions. In addition, the use of more than one satellite product is helpful in diagnosing problems in these products. [ABSTRACT FROM AUTHOR]

Oceanographic datasets, which are arranged for standard depths, have many applications for various users. However, oceanic observations are not always conducted exactly at standard depths, especially in the case of historical bottle observations. Therefore, interpolation for density data is usually calculated from interpolated temperature and salinity data. However, in areas such as the Kuroshio–Oyashio mixed water region, east of Japan, the oceanic conditions are extremely complex, and pseudo-density inversions are often generated during the interpolation procedure. The authors have designed a new scheme based on parabolic or cubic interpolation, to avoid the generation of pseudo-density inversions, that uses temperature and density as independent variables. If the generation of a density inversion in the parabolic or cubic interpolation is found, it is replaced by a linear interpolation. The salinity calculated from interpolated temperature and density sometimes lies outside the range between the salinities at the observed levels above and below the standard depth; therefore, the scheme is designed so as to avoid the generation of such unacceptable salinity values. [ABSTRACT FROM AUTHOR]