A comparison of cumulus parameterization schemes in a numerical weather prediction model for a monsoon rainfall event

In order to evaluate cumulus parameterization (CP) schemes for hydrological applications, the Pennsylvania State University–National Center for Atmospheric Research's fifth‐generation mesoscale model (MM5) was used to simulate a summer monsoon in east China. The performances of five CP schemes (Anthes–Kuo, Betts–Miller, Fritsch–Chappell, Kain–Fritsch, and Grell) were evaluated in terms of their ability to simulate amount of rainfall during the heavy, moderate, and light phases of the event. The Grell scheme was found to be the most robust, performing well at all rainfall intensity and spatial scales. The Betts–Miller scheme also performed well, particularly at larger scales, but its assumptions may make it inapplicable to non‐tropical environments and at smaller scales. The Kain–Fritsch scheme was the best at simulating moderate rainfall rates, and was found to be superior to the Fritsch–Chappell scheme on which it was based. The Anthes–Kuo scheme was found to underpredict precipitation consistently at the mesoscale. Simulation performance was found to improve when schemes that included downdrafts were used in conjunction with schemes that did not include downdrafts. Copyright © 2005 John Wiley & Sons, Ltd.     

Sensitivity of Mesoscale Model Forecast During a Satellite Launch to Different Cumulus Parameterization Schemes in MM5

The identification of the model discrepancy and skill is crucial when a forecast is issued. The characterization of the model errors for different cumulus parameterization schemes (CPSs) provides more confidence on the model outputs and qualifies which CPSs are to be used for better forecasts. Cases of good/bad skill scores can be isolated and clustered into weather systems to identify the atmospheric structures that cause difficulties to the forecasts. The objective of this work is to study the sensitivity of weather forecast, produced using the PSU-NCAR Mesoscale Model version 5 (MM5) during the launch of an Indian satellite on 5th May, 2005, to the way in which convective processes are parameterized in the model. The real-time MM5 simulations were made for providing the weather conditions near the launch station Sriharikota (SHAR). A total of 10 simulations (each of 48 h) for the period 25th April to 04th May, 2005 over the Indian region and surrounding oceans were made using different CPSs. The 24 h and 48 h model predicted wind, temperature and moisture fields for different CPSs, namely the Kuo, Grell, Kain-Fritsch and Betts-Miller, are statistically evaluated by calculating parameters such as mean bias, root-mean-squares error (RMSE), and correlation coefficients by comparison with radiosonde observation. The performance of the different CPSs, in simulating the area of rainfall is evaluated by calculating bias scores (BSs) and equitable threat scores (ETSs). In order to compute BSs and ETSs the model predicted rainfall is compared with Tropical Rainfall Measuring Mission (TRMM) observed rainfall. It was observed that model simulated wind and temperature fields by all the CPSs are in reasonable agreement with that of radiosonde observation. The RMSE of wind speed, temperature and relative humidity do not show significant differences among the four CPSs. Temperature and relative humidity were overestimated by all the CPSs, while wind speed is underestimated, except in the upper levels. The model predicted moisture fields by all CPSs show substantial disagreement when compared with observation. Grell scheme outperforms the other CPSs in simulating wind speed, temperature and relative humidity, particularly in the upper levels, which implies that representing entrainment/detrainment in the cloud column may not necessarily be a beneficial assumption in tropical atmospheres. It is observed that MM5 overestimates the area of light precipitation, while the area of heavy precipitation is underestimated. The least predictive skill shown by Kuo for light and moderate precipitation asserts that this scheme is more suitable for larger grid scale (>30 km). In the predictive skill for the area of light precipitation the Betts-Miller scheme has a clear edge over the other CPSs. The evaluation of the MM5 model for different CPSs conducted during this study is only for a particular synoptic situation. More detailed studies however, are required to assess the forecast skill of the CPSs for different synoptic situations.     

Evaluation of Short-Range Forecasts from a Mesoscale Model Over the Indian Region During Monsoon 2006

This study examines the short-range forecast accuracy of the Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5) as applied to the July 2006 episode of the Indian summer monsoon (ISM) and the model's sensitivity to the choice of different cumulus parameterization schemes (CPSs), namely Betts-Miller, Grell (GR) and Kain-Fritsch (KF). The results showed that MM5 day 1 (0–24 h prediction) and day 2 (24–48 h prediction) forecasts using all three CPSs overpredicted monsoon rainfall over the Indian landmass, with the larger overprediction seen in the day 2 forecasts. Among the CPSs, the rainfall distribution over the Indian landmass was better simulated in forecasts using the KF scheme. The KF scheme showed better skill in predicting the area of rainfall for most of the rainfall thresholds. The root mean square error (RMSE) in day 1 and day 2 rainfall forecasts using different CPSs showed that rainfall simulated using the KF scheme agreed better with the observed rainfall. As compared to other CPSs, simulation using the GR scheme showed larger RMSE in wind speed prediction at 850 and 200 hPa over the Indian landmass. MM5 24-h temperature forecasts at 850 hPa with all the CPSs showed a warm bias of the order of 1 K over the Indian landmass and the bias doubled in 48-h model forecasts. The mean error in temperature prediction at 850 hPa over the Indian region using the KF scheme was comparatively smaller for all the forecast intervals. The model with all the CPSs overpredicted humidity at 850 hPa. The improved prediction by MM5 with the KF scheme is well complemented by the smaller error shown by the KF scheme in vertical distribution of heat and mean moist static energy in the lower troposphere. In this study, the KF scheme which explicitly resolve the downdrafts in the cloud column tended to produce more realistic precipitation forecasts as compared to other schemes which did not explicitly incorporate downdraft effects. This is an important result especially given that the area covered by monsoon-precipitating systems is largely from stratiform-type clouds which are associated with strong downdrafts in the lower levels. This result is useful for improving the treatment of cumulus convection in numerical models over the ISM region.     

A numerical study of the rainstorm characteristics of the June 2005 flash flood with WRF/GSI data assimilation system over south‐east China

The evolution and structure of rainstorms associated with a flash‐flood event are simulated by the Advanced Weather Research and Forecasting (WRF‐ARW) model of the National Center for Atmospheric Research and the Gridpoint Statistical Interpolation (GSI) data assimilation (DA) system of the National Oceanic and Atmospheric Administration (NOAA) of the United States. The event is based on a flash flood that occurred in the central Guangdong Province of south‐east China during 20–21 June 2005. Compared to an hourly mixed rain‐gauge and satellite‐retrieved precipitation data, the model shows the capability to reproduce the intensity and location of rainfall; however, the simulation depends on three conditions to a large extent: model resolution, physical processes schemes and initial condition. In this case, the Eta Ferrier microphysics scheme and the initialization with satellite radiance DA with a fine 4‐km grid spacing nested grid and coarse 12‐km grid spacing outer grid are the best options. The model‐predicted rain rates, however, are slightly overestimated, and the activities of the storms do not precisely correspond with those observed, although peak values are obtained. Abundant moisture brought by the south‐westerly winds with a mesoscale low‐level jet from the South China Sea or Bay of Bengal and trapped within the XingfengJiang region encompassed by northern Jiulian, southern Lianhua and eastern small mountains are apparently the primary elements responsible for the flood event. All simulated rainstorms were initiated over the southern slopes of the Jiulian Mountain and moved south or north‐eastward within the Xingfengjiang region. Meanwhile, the Skew‐T/Log‐P diagrams show that there is a fairly high convective available potential energy (CAPE) over the active areas of the rainstorms. The higher CAPE provides a beneficial thermodynamic condition for the development of rainstorms, but the higher convective inhibition near the northern, eastern and southern mountains prohibits the storms from moving out of the region and causes heavy rainfall that is trapped within the area. Copyright © 2010 John Wiley & Sons, Ltd.     

A new magnitude category disaggregation approach for temporal high‐resolution rainfall intensities

Simulation of quick runoff components such as surface runoff and associated soil erosion requires temporal high‐resolution rainfall intensities. However, these data are often not available because such measurements are costly and time consuming. Current rainfall disaggregation methods have shortcomings, especially in generating the distribution of storm events. The objectives of this study were to improve point rainfall disaggregation using a new magnitude category rainfall disaggregation approach. The procedure is introduced using a coupled disaggregation approach (Hyetos and cascade) for multisite rainfall disaggregation. The new procedure was tested with ten long‐term precipitation data sets of central Germany using summer and winter precipitation to determine seasonal variability. Results showed that dividing the rainfall amount into four daily rainfall magnitude categories (1–10, 11–25, 26–50, >50 mm) improves the simulation of high rainfall intensity (convective rainfall). The Hyetos model category approach (Hyetos_Cat) with seasonal variation performs representative to observed hourly rainfall compared with without categories on each month. The mean absolute percentage accuracy of standard deviation for hourly rainfall is 89.7% in winter and 95.6% in summer. The proposed magnitude category method applied with the coupled Hyetos_Cat–cascade approach reproduces successfully the statistical behaviour of local 10‐min rainfall intensities in terms of intermittency as well as variability. The root mean square error performance statistics for disaggregated 10‐min rainfall depth ranges from 0.20 to 2.38 mm for summer and from 0.12 to 2.82 mm for the winter season in all categories. The coupled stochastic approach preserves the statistical self‐similarity and intermittency at each magnitude category with a relatively low computational burden. Copyright © 2014 John Wiley & Sons, Ltd.     

Numerical Simulation of Andhra Severe Cyclone (2003): Model Sensitivity to the Boundary Layer and Convection Parameterization

The Andhra severe cyclonic storm (2003) is simulated to study its evolution, structure, intensity and movement using the Penn State/NCAR non-hydrostatic mesoscale atmospheric model MM5. The model is used with three interactive nested domains at 81, 27 and 9 km resolutions covering the Bay of Bengal and adjoining Indian Peninsula. The performance of the Planetary Boundary Layer (PBL) and convective parameterization on the simulated features of the cyclone is studied by conducting sensitivity experiments. Results indicate that while the boundary layer processes play a significant role in determining both the intensity and movement, the convective processes especially control the movement of the model storm. The Mellor-Yamada scheme is found to yield the most intensive cyclone. While the combination of Mellor-Yamada (MY) PBL and Kain-Fritsch 2 (KF2) convection schemes gives the most intensive storm, the MRF PBL with KF2 convection scheme produces the best simulation in terms of intensity and track. Results of the simulation with the combination of MRF scheme for PBL and KF2 for convection show the evolution and major features of a mature tropical storm. The model has very nearly simulated the intensity of the storm though slightly overpredicted. Simulated core vertical temperature structure, winds at different heights, vertical winds in and around the core, vorticity and divergence fields at the lower and upper levels—all support the characteristics of a mature storm. The model storm has moved towards the west of the observed track during the development phase although the location of the storm in the initial and final phases agreed with the observations. The simulated rainfall distribution associated with the storm agreed reasonably with observations.     

Regional differences in hydrological response to canopy interception schemes in a land surface model

Two different canopy interception schemes are applied to the parameterization of the hydrological processes in the Community Land Model version 3. One scheme treats rainfall and canopy water storage as spatially uniform within each model grid cell, and the other scheme considers sub‐grid variability of rainfall and water storage in the parameterization of canopy hydrological processes. The hydrological responses to differences between these two schemes in different regions are studied. It is found that the impact of the sub‐grid variability in the tropical regions is generally greater than the extra‐tropical regions. However, such impact can't be negligible for the extra‐tropical regions. Soil water in the total 3.4 m soil depth increases by 3% for Central‐South Europe, and vegetation temperature increases by 0.14 °C for Southeastern United States if the regional averages are considered. The magnitude of the impact is greater if the analysis focuses on the specific grid cells in these regions. The impact is tightly correlated with rainfall amount and vegetation density. The correlation coefficient between such impact and rainfall amount and vegetation density varies with regions and hydrological variables, with the largest value of 0.92 for interception loss in Amazonia. Our results indicate that the impact of the sub‐grid variability on hydrological processes in the extra‐tropical areas is also important, although rainfall amount and vegetation density in these areas are not as high as in the tropical areas. Copyright © 2013 John Wiley & Sons, Ltd.     

Eurasian snow cover and seasonal forecast of Indian summer monsoon rainfall

Abstract

This paper presents the relationship between Indian summer monsoon total rainfall and two parameters from Eurasian snow cover, one being the winter snow cover extent and the other the area of spring snowmelt. Satellite-derived Eurasian snow cover extent and Indian monsoon rainfall data were obtained from the NOAA/NESDIS and the India Meteorological Department (IMD) for the period 1966–1985. Seasonal cyclic variations of snow cover showed a higher swing in both the winter and the spring seasons of the cycle as compared to the remaining seasons of the year in the lower region of the cycle. The established inverse relation between winter snow cover and monsoon rainfall during June to September is further extended. Winter snow cover is very strongly correlated with spring snowmelt over Eurasia. Spring snowmelt area is obtained by subtracting the May snow cover extent from that of the previous February. The variations of spring snowmelt were also compared with Indian total monsoon rainfall. The detected correlation is stronger between snowmelt and monsoon rainfall than between the winter snow cover and the monsoon rainfall. There is also a significant multiple correlation among winter snow cover, spring snowmelt and monsoon rainfall. Lastly, a significant multiple correlation suggested a multiple regression equation which might improve the climatic prediction of monsoon rainfall over India.     

Daily rainfall projections from general circulation models with a downscaling nonhomogeneous hidden Markov model (NHMM) for south‐eastern Australia

An ensemble of stochastic daily rainfall projections has been generated for 30 stations across south‐eastern Australia using the downscaling nonhomogeneous hidden Markov model, which was driven by atmospheric predictors from four climate models for three IPCC emissions scenarios (A1B, A2, and B1) and for two periods (2046–2065 and 2081–2100). The results indicate that the annual rainfall is projected to decrease for both periods for all scenarios and climate models, with the exception of a few scenarios of no statistically significant changes. However, there is a seasonal difference: two downscaled GCMs consistently project a decline of summer rainfall, and two an increase. In contrast, all four downscaled GCMs show a decrease of winter rainfall. Because winter rainfall accounts for two‐thirds of the annual rainfall and produces the majority of streamflow for this region, this decrease in winter rainfall would cause additional water availability concerns in the southern Murray–Darling basin, given that water shortage is already a critical problem in the region. In addition, the annual maximum daily rainfall is projected to intensify in the future, particularly by the end of the 21st century; the maximum length of consecutive dry days is projected to increase, and correspondingly, the maximum length of consecutive wet days is projected to decrease. These changes in daily sequencing, combined with fewer events of reduced amount, could lead to drier catchment soil profiles and further reduce runoff potential and, hence, also have streamflow and water availability implications. Copyright © 2012 John Wiley & Sons, Ltd.     

Regionality and seasonality of submesoscale and mesoscale turbulence in the North Pacific Ocean

The kinetic energy (KE) seasonality has been revealed by satellite altimeters in many oceanic regions. Question about the mechanisms that trigger this seasonality is still challenging. We address this question through the comparison of two numerical simulations. The first one, with a 1/10° horizontal grid spacing, 54 vertical levels, represents dynamics of physical scales larger than 50 km. The second one, with a 1/30° grid spacing, 100 vertical levels, takes into account the dynamics of physical scales down to 16 km. Comparison clearly emphasizes in the whole North Pacific Ocean, not only a significant KE increase by a factor up to three, but also the emergence of seasonal variability when the scale range 16–50 km (called submesoscales in this study) is taken into account. But the mechanisms explaining these KE changes display strong regional contrasts. In high KE regions, such the Kuroshio Extension and the western and eastern subtropics, frontal mixed-layer instabilities appear to be the main mechanism for the emergence of submesoscales in winter. Subsequent inverse kinetic energy cascade leads to the KE seasonality of larger scales. In other regions, in particular in subarctic regions, results suggest that the KE seasonality is principally produced by larger-scale instabilities with typical scales of 100 km and not so much by smaller-scale mixed-layer instabilities. Using arguments from geostrophic turbulence, the submesoscale impact in these regions is assumed to strengthen mesoscale eddies that become more coherent and not quickly dissipated, leading to a KE increase.     

Finite-difference modelling of S-wave splitting in anisotropic media

We have implemented a 3D finite‐difference scheme to simulate wave propagation in arbitrary anisotropic media. The anisotropic media up to orthorhombic symmetry were modelled using a standard staggered grid scheme and beyond (monoclinic and triclinic) using a rotated staggered grid scheme. The rationale of not using rotated staggered grid for all types of anisotropic media is that the rotated staggered grid schemes are more expensive than standard staggered grid schemes. For a 1D azimuthally anistropic medium, we show a comparison between the seismic data generated by our finite‐difference code and by the reflectivity algorithm; they are in excellent agreement. We conducted a study on zero‐offset shear‐wave splitting using the finite‐difference modelling algorithm using the rotated staggered grid scheme. Our S‐wave splitting study is mainly focused on fractured media. On the scale of seismic wavelenghts, small aligned fractures behave as an equivalent anisotropic medium. We computed the equivalent elastic properties of the fractures and the background in which the fractures were embedded, using low‐frequency equivalent media theories. Wave propagation was simulated for both rotationally invariant and corrugated fractures embedded in an isotropic background for one, or more than one, set of fluid‐filled and dry fractures. S‐wave splitting was studied for dipping fractures, two vertical non‐orthogonal fractures and corrugated fractures. Our modelling results confirm that S‐wave splitting can reveal the fracture infill in the case of dipping fractures. S‐wave splitting has the potential to reveal the angle between the two vertical fractures. We also notice that in the case of vertical corrugated fractures, S‐wave splitting is sensitive to the fracture infill.     

Evaluating the impacts of climate change and switchgrass production on a semiarid basin

Climate and land use changes greatly modify hydrologic regimes. In this paper, we modelled the impacts of biofuel cultivation in the US Great Plains on a 1061‐km² watershed using the Soil and Water Assessment Tool (SWAT) hydrologic model. The model was calibrated to monthly discharges spanning 2002–2010 and for the winter, spring, and summer seasons. SWAT was then run for a climate‐change‐only scenario using downscaled precipitation and a projected temperature for 16 general circulation model (GCM) runs associated with the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios A2 scenario spanning 2040–2050. SWAT was also run on a climate change plus land use change scenario in which Alamo switchgrass (Panicum virgatum L.) replaced native range grasses, winter wheat, and rye (89% of the basin). For the climate‐change‐only scenario, the GCMs agreed on a monthly temperature increase of 1–2 °C by the 2042–2050 period, but they disagreed on the direction of change in precipitation. For this scenario, decreases in surface runoff during all three seasons and increases in spring and summer evapotranspiration (eT) were driven predominantly by precipitation. Increased summer temperatures also significantly contributed to changes in eT. With the addition of switchgrass, changes in surface runoff are amplified during the winter and summer, and changes in eT are amplified during all three seasons. Depending on the GCM utilized, either climate change or land use change (switchgrass cultivation) was the dominant driver of change in surface runoff while switchgrass cultivation was the major driver of changes in eT. Copyright © 2014 John Wiley & Sons, Ltd.     

中层大气重力波的全球分布特征

从2002年1月到2009年12月的SABER温度剖面数据提取了可以反映重力波活动的垂直尺度2～10 km的中尺度温度扰动,分析了全球中层大气重力波的分布.重力波扰动在夏季和冬季明显强于春季和秋季,而冬季与夏季相比,在70 km以下的高度夏季弱于冬季,在70 km以上夏季比冬季要强.从全球重力波分布来看,较大值分布在冬...     

Hydrological responses to climatic variability in a cold agricultural region

Extended severe dry and wet periods are frequently observed in the northern continental climate of the Canadian Prairies. Prairie streamflow is mainly driven by spring snowmelt of the winter snowpack, whilst summer rainfall is an important control on evapotranspiration and thus seasonality affects the hydrological response to drought and wet periods in complex ways. A field‐tested physically based model was used to investigate the influences of climatic variability on hydrological processes in this region. The model was set up to resolve agricultural fields and to include key cold regions processes. It was parameterized from local and regional measurements without calibration and run for the South Tobacco Creek basin in southern Manitoba, Canada. The model was tested against snow depth and streamflow observations at multiple scales and performed well enough to explore the impacts of wet and dry periods on hydrological processes governing the basin scale hydrological response. Four hydro‐climatic patterns with distinctive climatic seasonality and runoff responses were identified from differing combinations of wet/dry winter and summer seasons. Water balance analyses of these patterns identified substantive multiyear subsurface soil moisture storage depletion during drought (2001–2005) and recharge during a subsequent wet period (2009–2011). The fractional percentage of heavy rainfall days was a useful metric to explain the contrasting runoff volumes between dry and wet summers. Finally, a comparison of modeling approaches highlights the importance of antecedent fall soil moisture, ice lens formation during the snowmelt period, and peak snow water equivalent in simulating snowmelt runoff.     

Relations between rainfall–runoff‐induced erosion and aeolian deposition at archaeological sites in a semi‐arid dam‐controlled river corridor

Process dynamics in fluvial‐based dryland environments are highly complex with fluvial, aeolian, and alluvial processes all contributing to landscape change. When anthropogenic activities such as dam‐building affect fluvial processes, the complexity in local response can be further increased by flood‐ and sediment‐limiting flows. Understanding these complexities is key to predicting landscape behavior in drylands and has important scientific and management implications, including for studies related to paleoclimatology, landscape ecology evolution, and archaeological site context and preservation. Here we use multi‐temporal LiDAR surveys, local weather data, and geomorphological observations to identify trends in site change throughout the 446‐km‐long semi‐arid Colorado River corridor in Grand Canyon, Arizona, USA, where archaeological site degradation related to the effects of upstream dam operation is a concern. Using several site case studies, we show the range of landscape responses that might be expected from concomitant occurrence of dam‐controlled fluvial sand bar deposition, aeolian sand transport, and rainfall‐induced erosion. Empirical rainfall‐erosion threshold analyses coupled with a numerical rainfall–runoff–soil erosion model indicate that infiltration‐excess overland flow and gullying govern large‐scale (centimeter‐ to decimeter‐scale) landscape changes, but that aeolian deposition can in some cases mitigate gully erosion. Whereas threshold analyses identify the normalized rainfall intensity (defined as the ratio of rainfall intensity to hydraulic conductivity) as the primary factor governing hydrologic‐driven erosion, assessment of false positives and false negatives in the dataset highlight topographic slope as the next most important parameter governing site response. Analysis of 4+ years of high resolution (four‐minute) weather data and 75+ years of low resolution (daily) climate records indicates that dryland erosion is dependent on short‐term, storm‐driven rainfall intensity rather than cumulative rainfall, and that erosion can occur outside of wet seasons and even wet years. These results can apply to other similar semi‐arid landscapes where process complexity may not be fully understood. Published 2015. This article is a U.S. Government work and is in the public domain in the USA     

Sensitivity of the Weather Research and Forecasting (WRF) model to downscaling ratios and storm types in rainfall simulation

Accurate information of rainfall is needed for sustainable water management and more reliable flood forecasting. The advances in mesoscale numerical weather modelling and modern computing technologies make it possible to provide rainfall simulations and forecasts at increasingly higher resolutions in space and time. However, being one of the most difficult variables to be modelled, the quality of the rainfall products from the numerical weather model remains unsatisfactory for hydrological applications. In this study, the sensitivity of the Weather Research and Forecasting (WRF) model is investigated using different domain settings and various storm types to improve the model performance of rainfall simulation. Eight 24‐h storm events are selected from the Brue catchment, southwest England, with different spatial and temporal distributions of the rainfall intensity. Five domain configuration scenarios designed with gradually changing downscaling ratios are used to run the WRF model with the ECMWF 40‐year reanalysis data for the periods of the eight events. A two‐dimensional verification scheme is proposed to evaluate the amounts and distributions of simulated rainfall in both spatial and temporal dimensions. The verification scheme consists of both categorical and continuous indices for a first‐level assessment and a more quantitative evaluation of the simulated rainfall. The results reveal a general improvement of the model performance as we downscale from the outermost to the innermost domain. Moderate downscaling ratios of 1:7, 1:5 and 1:3 are found to perform better with the WRF model in giving more reasonable results than smaller ratios. For the sensitivity study on different storm types, the model shows the best performance in reproducing the storm events with spatial and temporal evenness of the observed rainfall, whereas the type of events with highly concentrated rainfall in space and time are found to be the trickiest case for WRF to handle. Finally, the efficiencies of several variability indices are verified in categorising the storm events on the basis of the two‐dimensional rainfall evenness, which could provide a more quantitative way for the event classification that facilitates further studies. It is important that similar studies with various storm events are carried out in other catchments with different geographic and climatic conditions, so that more general error patterns can be found and further improvements can be made to the rainfall products from mesoscale numerical weather models. Copyright © 2011 John Wiley & Sons, Ltd.     

Vertical and off-diagonal eddy diffusivities in the Northern Hemispheric stratosphere and lower mesosphere

Meteorological rocket soundings, launched between 1968–74 at six locations representative of low, middle, and high latitudes in the northern hemisphere, are employed to determine the vertical, meridional and off-diagonal components of the eddy diffusivity in the northern hemispheric statosphere and lower mesosphere.It is shown that the distribution of the vertical and meridional components of the eddy diffusivity are similar in the northern hemisphere, although the magnitude of the former is 10⁷ smaller than that of the latter; the magnitude of the off-diagonal eddy diffusivity is about 10³ smaller than that of the meridional eddy diffusivity. In the troposphere, a maximum eddy diffusivity occurs in the mid-latitude at about 7 km above the mean sea level for both the summer and winter seasons. In the stratosphere, a maximum eddy diffusivity occurs in the mid-latitude at about 33 km in the winter, but no maximum in the summer.Paper presented at the World Meterological Organization Technical Conference on Global Observations of Atmospheric Pollution Relative to Climate, Boulder, Colorado, 20–24 August 1979.     

A high-resolution modeling study of the Western Iberian Margin mean and seasonal upper ocean circulation

The mean seasonal hydrography and circulation of the Western Iberian Margin (WIM) are studied by means of a high-resolution configuration of the Regional Oceanic Modeling System. A comparison of 5-year model averages for January and July with climatological datasets shows a general good agreement in the reproduction of the mean water mass properties and hydrographic distribution. We find that there is a prevailing tendency for slope poleward flow at about 80–100 km offshore at all latitudes from the surface to 1,500 m with strong vertical coupling. This northward flow, which is mainly along slope and amounts up to 8–10 cm s^?1, exhibits several mean flow recirculation regions on its way and evidences of an offshore pathway of poleward flow. Transports at different zonal sections further confirm the poleward flow tendency with two peaks of poleward transport in summer (3–10 Sv) and winter (2–7 Sv). The transport time series emphasize the seasonal character of the alongshore circulation and the interannual intrinsic variability of the circulation, since the forcing fields are climatological. As a conceptual essay with the purpose of assessing the Mediterranean Water flow influence on the WIM mean circulation, a second model configuration is setup, where the Mediterranean outflow into the study domain is removed. We find that there is an attenuation of the mesoscale field, but the slope poleward flow intensifies and remains as a mean dynamical feature closer to the upper slope.     

Nonlinear analysis of rainfall dynamics in California's Sacramento Valley

This study investigates the dynamic nature of rainfall observed at the Sustainable Agriculture Farming Systems (SAFS) site in California's Sacramento Valley, which was established to study the benefits of winter cover cropping in Mediterranean irrigated‐arid systems. Rainfall data of four different temporal scales (i.e. daily, weekly, biweekly, and monthly) are analysed to determine the dynamic nature of precipitation in time. In an arid climate with seasonal precipitation this has large implications for land and water management, both in the short term and in the long term. A nonlinear dynamic technique (correlation dimension method) that uses the phase‐space reconstruction and dimension concepts is employed. Bearing in mind the possible effects of the presence of zeros (i.e. no rain) on the outcomes of this analysis, an attempt is also made to compare the dynamic nature of all‐year rainfall and winter rainfall. Analysis of 15 years of data suggests that rainfall dynamics at this site are dominated by a large number of variables, regardless of the scales and seasons studied. The dimension results also suggest that: (1) rainfall dynamics at coarser resolutions are more irregular than that at finer resolutions; (2) winter rainfall has a higher variability than all‐year rainfall. These results are indeed useful to gain information about the complexity of the rainfall process at this site with respect to (temporal) scales and seasons and, hence, the appropriate model (high‐dimensional) type. However, in view of the potential effects of certain rainfall data characteristics (e.g. zeros, measurement errors, scale effects) on the correlation dimension analysis, the discussion also emphasizes the need for further verification, and possibly confirmation, of these results. Copyright © 2005 John Wiley & Sons, Ltd.     

Winter rainfall interception by two mature open‐grown trees in Davis,California

A rainfall interception measuring system was developed and tested for open‐grown trees. The system includes direct measurements of gross precipitation, throughfall and stemflow, as well as continuous collection of micrometeorological data. The data were sampled every second and collected at 30‐s time steps using pressure transducers monitoring water depth in collection containers coupled to Campbell CR10 dataloggers. The system was tested on a 9‐year‐old broadleaf deciduous tree (pear, Pyrus calleryana ‘Bradford’) and an 8‐year‐old broadleaf evergreen tree (cork oak, Quercus suber) representing trees having divergent canopy distributions of foliage and stems. Partitioning of gross precipitation into throughfall, stemflow and canopy interception is presented for these two mature open‐grown trees during the 1996–1998 rainy seasons. Interception losses accounted for about 15% of gross precipitation for the pear tree and 27% for the oak tree. The fraction of gross precipitation reaching the ground included 8% by stemflow and 77% by throughfall for the pear tree, as compared with 15% and 58%, respectively, for the oak tree. The analysis of temporal patterns in interception indicates that it was greatest at the beginning of each rainfall event. Rainfall frequency is more significant than rainfall rate and duration in determining interception losses. Both stemflow and throughfall varied with rainfall intensity and wind speed. Increasing precipitation rates and wind speed increased stemflow but reduced throughfall. Analysis of rainfall interception processes at different time‐scales indicates that canopy interception varied from 100% at the beginning of the rain event to about 3% at the maximum rain intensity for the oak tree. These values reflected the canopy surface water storage changes during the rain event. The winter domain precipitation at our study site in the Central Valley of California limited our opportunities to collect interception data during non‐winter seasons. This precipitation pattern makes the results more specific to the Mediterranean climate region. Copyright © 2000 John Wiley & Sons, Ltd.