Moisture Correction Research Articles

Comparison of manual and automated chambers for field measurements of N 2O, CH 4, CO 2 fluxes from cultivated land

Chamber techniques can easily be applied to field trials with multiple small plots measuring carbon- and nitrogen-trace gas fluxes. Nevertheless, such chamber measurements are usually made weekly and rarely more frequently than once daily. However, automatic chambers do allow flux measurements on sub-daily time scales. It has been hypothesized that sub-daily measurements provide more reliable results, as diurnal variations are captured better compared to manual measurements. To test this hypothesis we compared automatic and manual measurements of N 2O, CO 2 and CH 4 fluxes from tilled and non-tilled plots of a rice–wheat rotation ecosystem over a non-waterlogged period. Our results suggest that both techniques, i.e., either manual or automatic chambers of N 2O and CO 2 emissions resulted in biased fluxes. The manual measurements were adequate to capture either day-to-day or seasonal dynamics of N 2O, CO 2 and CH 4 exchanges, but overestimated the cumulative N 2O and CO 2 emissions by 18% and 31%, respectively. This was due to neglecting temperature-dependent diurnal variations of C and N trace gas fluxes. However, the automatic measurements underestimated the cumulative emissions of N 2O and CO 2 by 22% and 17%, respectively. This underestimation resulted from chamber effects upon soil moisture during rainfall processes. No significant difference was detected between the two methods in CH 4 exchanges over the non-waterlogged soils. The bias of manual chambers may be significant when pronounced diurnal variations occur. The bias of automatic measurements can only be avoided/minimized if chamber positions are frequently changed and/or if chambers are automatically opened during rainfall events. We therefore recommend using automatic chambers together with continuous measurements of soil chamber moisture to allow for soil moisture correction of fluxes or to correct flux estimates as derived by manual chambers for possible diurnal variations.

Basis for a Rainfall Estimation Technique Using IR–VIS Cloud Classification and Parameters over the Life Cycle of Mesoscale Convective Systems

Abstract This paper discusses the basis for a new rainfall estimation method using geostationary infrared and visible data. The precipitation radar on board the Tropical Rainfall Measuring Mission satellite is used to train the algorithm presented (which is the basis of the estimation method) and the further intercomparison. The algorithm uses daily Geostationary Operational Environmental Satellite infrared–visible (IR–VIS) cloud classifications together with radiative and evolution properties of clouds over the life cycle of mesoscale convective systems (MCSs) in different brightness temperature (Tb) ranges. Despite recognition of the importance of the relationship between the life cycle of MCSs and the rainfall rate they produce, this relationship has not previously been quantified precisely. An empirical relationship is found between the characteristics that describe the MCSs’ life cycle and the magnitude of rainfall rate they produce. Numerous earlier studies focus on this subject using cloud-patch or pixel-based techniques; this work combines the two techniques. The algorithm performs reasonably well in the case of convective systems and also for stratiform clouds, although it tends to overestimate rainfall rates. Despite only using satellite information to initialize the algorithm, satisfactory results were obtained relative to the hydroestimator technique, which in addition to the IR information uses extra satellite data such as moisture and orographic corrections. This shows that the use of IR–VIS cloud classification and MCS properties provides a robust basis for creating a future estimation method incorporating humidity Eta field outputs for a moisture correction, digital elevation models combined with low-level moisture advection for an orographic correction, and a nighttime cloud classification.

Evaluation of European Land Data Assimilation System (ELDAS) products using in situ observations

Three land-surface models with land-data assimilation scheme (DA) were evaluated for one growing season using in situ observations obtained across Europe. To avoid drifts in the land-surface state in the models, soil moisture corrections are derived from errors in screen-level atmospheric quantities.With the in situ data it is assessed whether these land-surface schemes produce adequate results regarding the annual range of the soil water content, the monthly mean soil moisture content in the root zone and evaporative fraction (the ratio of evapotranspiration to energy available at the surface). DA considerably reduced bias in net precipitation, while slightly reducing RMSE as well. Evaporative fraction was improved in dry conditions but was hardly affected in moist conditions. The amplitude of soil moisture variations tended to be underestimated. The impact of improved land-surface properties like Leaf Area Index, water holding capacity and rooting depth may be as large as corrections of the DA systems. Because soil moisture memorizes errors in the hydrological cycle of the models, DA will remain necessary in forecast mode. Model improvements should be balanced against improvements of DA per se. Model bias appearing from persistent analysis increments arising from DA systems should be addressed by model improvements.

Mitigating the effects of soil and residue water contents on remotely sensed estimates of crop residue cover

Crop residues on the soil surface decrease soil erosion and increase soil organic carbon and the management of crop residues is an integral part of many conservation tillage systems. Current methods of measuring residue cover are inadequate for characterizing the spatial variability of residue cover over large fields. The objectives of this research were to determine the effects of water content on the remotely sensed estimates of crop residue cover and to propose a method to mitigate the effects of water content on remotely sensed estimates of crop residue cover. Reflectance spectra of crop residues and soils were measured in the lab over the 400–2400 nm wavelength region. Reflectance of scenes with various residue cover fractions and water contents was simulated using a linear mixture model. Additional spectra of scenes with mixtures of crop residues and soil were also acquired in corn, soybean, and wheat fields with different tillage treatments and different water content conditions. Crop residue cover was linearly related to the cellulose absorption index (CAI), which was defined as the relative intensity of an absorption feature near 2100 nm. Water in the crop residue significantly attenuated CAI and changed the slope of the residue cover vs. CAI relationship. Without an appropriate correction, crop residue covers were underestimated as scene water content increased. Spectral vegetation water indices were poorly related to changes in the water contents of crop residues and soils. A new reflectance ratio water index that used the two bands located on the shoulders of the cellulose absorption feature to estimate scene water conditions was proposed and tested with data from corn, soybean, and wheat fields. The ratio water index was used to describe the changes in the slope of crop residue cover vs. CAI and improve the predictions of crop residue cover. These results indicate that spatial and temporal adjustments in the spectral estimates of crop residue cover are possible. Current mutispectral imaging systems will not provide reliable estimates of crop residue cover when scene water content varies. Hyperspectral data are not required, because the three narrow bands that are used for both CAI and the scene moisture correction could be incorporated in advanced multispectral sensors. Thus, regional surveys of soil conservation practices that affect soil carbon dynamics may be feasible using either advanced multispectral or hyperspectral imaging systems.

Extent of error in estimating nutrient intakes from food tables versus laboratory estimates of cooked foods.

Individual cooked foods (104) and composite meals (92) were examined for agreement between nutritive value estimated by indirect analysis (E) (Indian National database of nutrient composition of raw foods, adjusted for observed moisture contents of cooked recipes), and by chemical analysis in our laboratory (M). The extent of error incurred in using food table values with moisture correction for estimating macro as well as micronutrients at food level and daily intake level was quantified. Food samples were analyzed for contents of iron, zinc, copper, beta-carotene, riboflavin, thiamine, ascorbic acid, folic acid and also for macronutrients, phytate and dietary fiber. Mean percent difference in energy content between E and M was 3.07+/-0.6%, that for protein was 5.3+/-2.0%, for fat was 2.6+/-1.8% and for carbohydrates was 5.1+/-0.9%. Mean percent difference in vitamin contents between E and M ranged from 32 (vitamin C) to 45.5% (beta-carotene content); and that for minerals between 5.6 (copper) to 19.8% (zinc). Percent E/M were computed for daily nutrient intakes of 264 apparently healthy adults. These were observed to be 108, 112, 127 and 97 for energy, protein, fat and carbohydrates respectively. Percent E/M for their intakes of copper (102) and beta-carotene (114) were closer to 100 but these were very high in the case of zinc (186), iron (202), and vitamins C (170), thiamine (190), riboflavin (181) and folic acid (165). Estimates based on food composition table values with moisture correction show macronutrients for cooked foods to be within +/- 5% whereas at daily intake levels the error increased up to 27%. The lack of good agreement in the case of several micronutrients indicated that the use of Indian food tables for micronutrient intakes would be inappropriate.

Influence of Drying Temperature and Duration on the Quantification of Particulate Organic Matter

Various drying conditions, temperatures (40 to 80°C) and durations (overnight to 72 hrs), for the particulate organic matter (POM) fraction after wet-sieving size fractionation have been applied for determination of POM contents in the weight loss-on-ignition method. In this study, we investigated the optimum drying condition for POM fraction in quantification of POM and/or mineral-associated organic matter (MOM; usually indirectly estimated). The influence of the drying conditions on quantifying POM was dependent upon soil properties, especially the amount of soil organic components. In relatively high organic soils (total carbon > 40 g/kg in this study), the POM values were significantly higher (overestimated) with drying at 55°C than those values at 105°C, which were, for example, 173.2 and 137.3 mg/kg, respectively, in a soil studied. However, drying at 55°C for longer than 48 hrs of periods produced consistent POM values even though the values were much higher than those at 105°C. Thus, indirect estimates of MOM (MOM = SOM POM) also tended to be significantly impacted by the dry conditions. Therefore, we suggest -- - POM fractions should be dried at 105°C for 24 hrs as determining POM and MOM contents. If the POM fraction is needed to be dried at a lower temperature (e.g. 55°C) with a specific reason, at least 48 hrs of drying period is necessary to obtain consistent POM values, and a moisture correction factor should be deter- mined to adjust the values back to a 105°C weight basis.

Thermal Kinetic Parameters of Thiamin in Wheat Flour at Temperatures Higher than 100°C

Kinetic parameters for thiamin degradation were obtained using 2 high-temperature heating methods: (1) atmospheric pressure (AP) with moisture correction and (2) controlled pressure (CP). At AP conditions, 33.3% dry basis(db) moisture wheat flour with 0.35% (db) thiamin was heated in thin steel cells isothermally at 145, 160, and 172 °C. To obtain the moisture correction factor, a constant-moisture study was conducted at 80 °C using 6 moisture contents (6.1% to 36.9%). At CP conditions, flour at 19%, 28.2%, and 33.3% (db) moisture in double-seamed cans was heated in a CP steam retort at 129 °C. For the AP method, the corrected activation energy for 33.3% moisture content was 129.5 kJ/g-mol and reaction rate at 80 °C was 3.48×10 - 4 min - 1 . Using the CP method, the activation energy and reaction rate were 121.0 kJ/g-mol and 9.69×10 - 5 min - 1 , respectively. Results obtained from 2 methods were not statistically different. These results illustrated that the correction method could be used as an alternative for researchers without access to controlled pressure equipment and transient heat transfer software.

Mathematical modelling of the composting process: A review

In this paper mathematical models of the composting process are examined and their performance evaluated. Mathematical models of the composting process have been derived from both energy and mass balance considerations, with solutions typically derived in time, and in some cases, spatially. Both lumped and distributed parameter models have been reported, with lumped parameter models presently predominating in the literature. Biological energy production functions within the models included first-order, Monod-type or empirical expressions, and these have predicted volatile solids degradation, oxygen consumption or carbon dioxide production, with heat generation derived using heat quotient factors. Rate coefficient correction functions for temperature, moisture, oxygen and/or free air space have been incorporated in a number of the first-order and Monod-type expressions. The most successful models in predicting temperature profiles were those which incorporated either empirical kinetic expressions for volatile solids degradation or CO 2 production, or which utilised a first-order model for volatile solids degradation, with empirical corrections for temperature and moisture variations. Models incorporating Monod-type kinetic expressions were less successful. No models were able to predict maximum, average and peak temperatures to within criteria of 5, 2 and 2 °C, respectively, or to predict the times to reach peak temperatures to within 8 h. Limitations included the modelling of forced aeration systems only and the generation of temperature validation data for relatively short time periods in relation to those used in full-scale composting practice. Moisture and solids profiles were well predicted by two models, but oxygen and carbon dioxide profiles were generally poorly modelled. Further research to obtain more extensive substrate degradation data, develop improved first-order biological heat production models, investigate mechanistically-based moisture correction factors, explore the role of moisture tension, investigate model performance over thermophilic composting time periods, provide more information on model sensitivity and incorporate natural ventilation aeration expressions into composting process models, is suggested.

Influence of and correction for moisture in rocks, soils and sediments on in situ XRF analysis

AbstractThis paper discusses the influence of water contained in rocks, soils and sediments on in situ XRF analysis with a portable XRF analyzer. Water in natural rocks, soil and sediments absorbs the characteristic x‐rays from the elements and also causes the primary radiation from the excitation sources to scatter, which results in a decrease in the intensity of characteristic x‐rays and an increase in the intensity of scattered x‐rays in a fluorescence spectrum. A method for correcting for the influence of the water on the analysis of wet samples is proposed, based on the fact that the intensity of scattered radiation is directly proportional to the water content of wet samples. Tests on a set of wet soil samples showed that the method can effectively correct for the influence of the water in wet samples up to a 20% water content. The method was also applied to the analysis of soil with an IED‐2000P XRF analyzer in a copper prospecting area in Yunnan, China. The results show satisfactory agreement of the results for Cu, Zn and Sr analyses before and after rain. Copyright © 2004 John Wiley & Sons, Ltd.

CCQM-P13 pilot study. Metals in artificial food digest

The accuracy of elemental analyses in complex matrices is usually assessed by analysis of a suitable matrix reference material. The reference value is ascribed by consensus mean and by application of primary methods of analysis. However, the quality of this value will be affected by problems such as matrix-induced interferences, moisture corrections and heterogeneity.Pilot study CCQM-P13 was undertaken to assess the capabilities ofNational Metrology Institutes to analyse Ca, Cu and Cd in an acidic solution that simulates the digest of a food sample. This study filled the gap between the analysis of a gravimetrically prepared calibration solution and the analysis of an unknown in a complex matrix requiring extensive sample preparation. Having an independent reference value, with a small uncertainty, allowed a more rigorous estimation of the reliability of the institutes' analysis and uncertainty estimates, without including issues around sample digestion.The reference values were: 1.6617 ± 0.0020 µmol/g for Ca, 7.037 ± 0.012 nmol/g for Cu and 45.57 ± 0.10 pmol/g for Cd (expanded uncertainties are quoted with coverage factor of 2). The other elements in the matrix were: Na (~25 µg/g), K (~90 µg/g), Cl (~120 µg/g), Fe (~100 ng/g), Mg (~5 µg/g), P (~5 µg/g), Sn (~80 ng/g) and Zn (~200 ng/g).Twelve international laboratories, representing eight countries, determined the amount content of the analytes. A range of techniques that include ID-ICP-MS (high resolution and collision cell), ICP-MS, ICP-OES, AAS, voltametry and potentiometry were used. The results for this pilot study averaged: 1.654 ± 0.058 µmol/g for Ca (n = 10), 7.26 ± 0.53 nmol/g for Cu (n = 12) and 45.2 ± 5.1 pmol/g for Cd (n = 11) where the values associated with the averages are the standard deviations of n participants.Main text. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/.The final report has been peer-reviewed and approved for publication by theCCQM Working Group on Inorganic Analysis (IAWG), according to theprovisions of the Mutual Recognition Arrangement (MRA).

On Predicting Roller Milling Performance V: Effect of Moisture Content on the Particle Size Distribution from First Break Milling of Wheat

Extended breakage functions incorporating both single kernel size and moisture content were determined for First Break milling of hard and soft wheats under a sharp-to-sharp disposition. A moisture correction function was constructed by milling narrow size fractions of wheat tempered to different moisture contents, and subtracting the breakage function at a base moisture content of 16% from that at other moisture contents. The effect of adding moisture was to change an initially inverted U-shaped distribution at low moisture contents to a linear distribution at 16% moisture, then to a U-shaped distribution at higher moisture contents, reminiscent of the particle size distributions produced by dull-to-dull milling. The extended breakage functions were used to predict milling of unseparated feed samples at different roll gaps and moisture contents. In addition, mixtures of hard wheat at 14% moisture and soft wheat at 20% moisture, mixed in different proportions, were milled and the resulting particle size distributions compared with predictions. Excellent predictions were obtained in all cases. This confirms the independent breakage of kernels during First Break milling, and demonstrates the potential of the breakage function approach for interpreting single kernel data in terms of predictions of milling performance.

Linescan camera evaluation of SSM/I 85.5 GHz sea ice retrieval

Retrievals of total sea ice concentration from four algorithms using the 85.5 GHz vertically and horizontally polarized channels of the Special Sensor Microwave Imager (SSM/I) over the marginal ice zone in the Barents and Greenland Seas are compared with retrievals of total sea ice concentration from helicopter-borne linescan camera observations made during a cruise of the R/V Polarstern during May–June 1997. The goals are to evaluate (1) SSM/I 85.5 GHz retrievals of total sea ice concentration for climatological purposes, and (2) the ability of 85.5 GHz data to show the sea ice edge through cloud cover, for operational purposes. The SSM/I 85.5 GHz channels offer a spatial resolution of 12.5 km, which is sufficient to resolve ice edge features and small polynyas; however, there is generally more atmospheric contamination of the sea ice signal at 85.5 GHz than at the lower frequencies (19 and 37 GHz) traditionally used for sea ice remote sensing. A self-adjusting algorithm that performs a nonlinear correction for atmospheric moisture, without explicit atmospheric input data, yields the best accuracy over total sea ice concentrations greater than 30%. However, this algorithm can misclassify clouds over open water as sea ice, and is therefore unreliable for locating the sea ice edge. The best algorithm for locating the sea ice edge is found to be the SEA LION algorithm, which explicitly uses meteorological reanalysis data to correct for atmospheric contamination. For total sea ice concentrations in the range 20–70%, empirical 85.5 GHz hybrids of lower-frequency algorithms developed at the NASA Goddard Space Flight Center can improve the accuracy of these algorithms.

Deriving catchment-scale water and energy balance parameters using data assimilation based on extended Kalman filtering

Important catchment-scale water and energy balance parameters are derived for a small catchment in southeastern Australia by assimilation in a catchment-scale soil-vegetation-atmosphere transfer (SVAT) model of subcatchment-scale soil water content observations and land surface temperature measurements. In order to incorporate the subcatchment-scale soil moisture variability and its time evolution in a data assimilation scheme, an extended Kalman filter (EKF) method is used in combination with a cost function minimization approach to derive effective parameters for the catchment as a whole. These parameters are the minimum surface resistance to evaporation and the soil hydrodynamic parameters. This method provides a balanced assessment of all the uncertainties regarding the description of the catchment hydrological behaviour. Moreover, these uncertainties are propagated forward in time in a single framework, which combines soil moisture correction with effective parameter estimation. Two issues are addressed in this paper: (a) the applicability of the method for scaling purposes (effective parameterization) and (b) the relationship between effective parameters obtained by this method and parameters obtained by a classical minimization routine that ignores soil moisture correction and observation uncertainty. Effective parameters are found to be consistent with the available local parameter measurements. Derived parameter sets with and without EKF have been found to be very similar and this has been explained in a number of ways.

EVALUATION OF FIVE SENSORS TO ESTIMATE MASS–FLOW RATE AND MOISTURE OF GRASS IN A FORAGE HARVESTER

A forage harvester and a highdump wagon were instrumented to measure massflow rate during harvest of wiltedgrass, mainly timothy between 45 and 78% moisture. Five sensors were installed in the forage harvester: a transducer tomeasure feedroll displacement, two sensors to measure torque at the power takeoff (PTO) shaft and at the cutterhead, a loadcell to measure impact force against a hinged plate in the spout and a capacitancecontrolled oscillator placed at the endof the spout which exhibited a frequency change as a function of massflow rate. The highdump wagon was instrumentedwith four weighing sensors to measure the accumulated mass continuously. A total of 42 wagon loads, subdivided into133 harvest units corresponding to time intervals of 60 to 120 s each, provided massflow rates in the range of 1 to 15 kg/s(2 to 33 lb/s). Impact force in the spout produced a very good linear correlation with massflow rate (R 2 = 0.951) and astandard error of estimate (SE) of 0.7 kg/s (1.5 lb/s). Feedroll displacement produced the second best linear correlation withmassflow rate (R 2 = 0.863). Torque at the PTO shaft and at the cutterhead required a moisture correction to improvecorrelation with massflow rate. The capacitancecontrolled oscillator was poorly correlated with massflow rate butyielded the best correlation with moisture content (R 2 = 0.662). A prediction model based on two measurements (e.g. spoutimpact force and frequency drop of the oscillator) provided an improved estimation of massflow rate [SE = 0.3 kg/s (0.7 lb/s)]compared to a single measurement prediction model.

Modeling CO2 and water vapor turbulent flux distributions within a forest canopy

One‐dimensional multilayer biosphere‐atmosphere models (e.g., CANVEG) describe ecosystem carbon dioxide (CO2) and water vapor (H2O) fluxes well when cold temperatures or the hydrologic state of the ecosystem do not induce stomatal closure. To investigate the CANVEG model framework under such conditions, CO2, H2O, and sensible heat fluxes were measured with eddy‐covariance methods together with xylem sap flux and leaf‐level gas exchange in a 16‐year‐old (in 1999) southeastern loblolly pine forest. Leaf‐level gas exchange measurements, collected over a 3‐year period, provided all the necessary biochemical and physiological parameters for the CANVEG model. Using temperature‐induced reductions of the biochemical kinetic rate constants, the CANVEG approach closely captures the diurnal patterns of the CO2 and H2O fluxes for two different formulations of the maximum Rubisco catalytic capacity (Vc max) ‐ temperature function, suggesting that the CANVEG approach is not sensitive to Vc max variations for low temperatures. A soil moisture correction (wr) to the Ball‐Berry leaf‐conductance approach was also proposed and tested. The wr magnitude is consistent with values predicted by a root‐xylem hydraulic approach and with leaf‐level measurements. The wr correction significantly improves the model's ability to capture diurnal patterns of H2O fluxes for drought conditions. The modeled bulk canopy conductance (Gm) for pine foliage estimated from the CANVEG‐modeled multilevel resistance values agreed well with canopy conductance (Gc) independently estimated from pine sap flux measurements. Detailed sensitivity analysis suggests that the leaf‐level physiological parameters used in CANVEG are not static. The dynamic property of the conductance parameter, inferred from such sensitivity analysis, was further supported using 3 years of porometry measurements. The CANVEG model also reproduced basic biochemical processes as demonstrated by the agreement between modeled and leaf‐level measured Ci/Ca, where Ci and Ca are the intercellular and atmospheric CO2 concentration, respectively. The model estimated that vapor pressure deficit does not vary significantly within the canopy but that Ci/Ca varied by more than 15%. The broader implication of this variation is that “big‐leaf” approaches that compress physiological and biochemical parameters into bulk canopy stomatal properties may be suitable for estimating water vapor flux but biased for CO2 ecosystem fluxes.

Estimation of Sea Surface Temperatures UsingGOES-8/9Radiance Measurements

Abstract Sea surface temperatures (SSTs) are derived using measurements from the new generation of imaging instruments on the Geostationary Operational Environmental Satellites (GOES). The National Environmental Satellite, Data and Information Service has been producing hourly GOES SST estimates since December 1998. This paper presents the algorithm for cloud detection and atmospheric moisture correction and shows some initial results. Several advantages of GOES SST are evident in comparison with SST from polar orbiting satellites. Frequent sampling by GOES imagers results in a more complete map of SST as clouds move away. Changes in scene temperature over a short period of time help to detect the presence of clouds. The abundance of GOES observations enables stringent screening for cloud-free observations while maintaining good spatial coverage of clear-sky inferences of SST. Diurnal variations of SST over large areas are observed for the first time and their implications for numerical weather prediction...

Estimation of Surface Heat Flux

Abstract The authors reconsider the problem of estimating the sensible heat transfer at the earth's surface from direct measurements of turbulent fluxes in the atmospheric boundary layer. For simplicity, only horizontally homogeneous conditions are considered for a thin atmospheric layer containing no liquid water, adjacent to the earth's ground surface. Applying the first law of thermodynamics to the thin interfacial layer, an expression is obtained for thermal conduction at the surface in terms of the traditionally defined sensible heat flux by turbulence and a set of correction terms including the so-called moisture correction term. A scale analysis is presented to suggest that the magnitudes of the miscellaneous correction terms are usually negligible. Previous literature on estimation of the sensible heat flux is critically reviewed in light of the new result.

Carbon-to-nitrogen ratios in agricultural residues

Agronomic crop residues produce greenhouse gas emissions. Crops that produce residues at harvest and during processing may vary from country to country. These residues, which can be in the form of peels, husks, stalks, or straw, are generally considered to be waste products. The carbon (C) and nitrogen (N) content of 19 different agronomic and grass crops common in Uganda were determined using standard laboratory methods. The C and N content of the samples were calculated from two separate equations containing a moisture correction factor. The crop residue C/N ratios were similar to UNEP/OECD/IEA/IPCC values.

The NESDIS Operational Convective Precipitation- Estimation Technique

Abstract This paper presents the NESDIS operational technique for estimating convective rainfall from GOES data. Estimates and 3-hour outlooks are computed on the Interactive Flash Flood Analyzer (IFFA) and transmitted via the Automation of Field Operations and Services (AFOS) computer systems to Weather Service Forecast Offices, Weather Service Offices, and River Forecast Centers. The technique consists of two steps: (1) locating the active portion of the convective system and (2) computing half-hourly rainfall estimates based on cloud-top temperature and cloud growth or divergence aloft, overshooting tops, mergers, saturated environment (stationary storms), and a moisture correction factor. A warm-top modification is used for cloud tops warmer than −62°C. Three-hour outlooks are based on persistence and extrapolation and trend and expectancy guidelines. Verification results show the average error of the rainfall estimates for a storm total precipitation event is about30%.

Measurement of elemental sulfur in soil and sediments - Field sampling, sample storage, pretreatment, extraction and analysis by high performance liquid chromatography

A rapid method for measuring elemental sulfur (S0) in soil and sediments is described that is accurate and precise down to a detection limit of 0.1 mg kg-l. Elemental sulfur is extracted into chloroform and measured by high-performance liquid chromatography. For moist samples, water is added to exceed their liquid limit. The method has been used to follow oxidation of both natural and fertilizer So in soil in the laboratory and field. Sediments analysed included some from lakes, and settling ponds containing coal mine wastes. Extraction within the plastic range was incomplete and recoveries as low as 5%-65% were found for five soils selected for a wide range of plastic limit. The plastic soil aggregates were not dispersed in the water-immiscible chloroform, preventing the dissolution of occluded S0; but at moisture levels above and below the plastic range, the soil was dispersed and extraction of S0 was quantitative. Extraction into a water-miscible solvent, chloroform-methanol (50 : 50), dispersed the soil at all moistures by dissolving the water thus preventing formation of plastic soil. This was less convenient because either volume correction for moisture was needed, or excess water added later to separate the chloroform. Measurement of total sulfur (S) in chloroform by inductively coupled plasma gave comparable results where samples contained S0 fertilizer, but at the lower natural levels they were much less precise and sometimes higher because of the additional S compounds extracted. Storage of moist soil below -10�C or air-dry soil at 20�C, gave no loss of S0 after one month. Moist soil at 20�C gave 40% loss after one week, but at 4�C the loss was only 5% after four weeks. Forced air-drying at 30�C, freeze-drying and microwave drying (under a narrow range of conditions) gave losses of about 5% for fertilizer S0 (<0.15 mm fraction), and of about 20% for smaller S0 crystals. In field trials with S0, sample variability was associated mostly with the difficulty of applying the S0 uniformly and with the small number of particles applied per unit area. For particles <0.25 mm, variability from mixing of cores and sub-sampling was not so great.