Distribution Of Observed Data Research Articles

Spatial horizontal correlation characteristics in the land data assimilation of soil moisture

Abstract. Remote sensing images deliver important information about soil moisture, but often cover only part of an area, for example due to the presence of clouds or vegetation. This paper examines the potential of incorporating the spatial horizontal correlation characteristics of surface soil moisture observations in land data assimilation in order to obtain improved estimates of soil moisture at uncovered grid cells (i.e. grid cells without observations). Observing system simulation experiments were carried out to assimilate the synthetic surface soil moisture observations into the Community Land Model for the Babaohe River Basin in northwestern China. The estimation of soil moisture at the uncovered grid cells was improved when information about surrounding observations and their spatial correlation structure was included. Including an increasing number of observations for covered and uncovered grid cells in the assimilation procedure led to a better prediction of soil moisture with an upper limit of five observations. A further increase of the number of observations did not further improve the results for this specific case. High observational coverage resulted in a better assimilation performance, depending also on the spatial distribution of observation data. In summary, the spatial horizontal correlation structure of soil moisture was found to be helpful for improving the surface soil moisture data characterization, especially for uncovered grid cells.

The impact of observation systems on medium-range weather forecasting in a global forecast system

To investigate the impact of various types of data on medium-range forecasts, observing system experiments are performed using an assimilation algorithm based on the National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) reanalysis system. Data-denial experiments for radiosonde, satellite, aircraft, and sea surface observations, and selected data experiments for radiosonde and surface data, are conducted for the boreal summer of 1997 and the boreal winter of 1997/1998. The data assimilation system used in this study is remarkably dependent on radiosonde data, which provides information about the three-dimensional structure of the atmosphere. As expected, the impact of radiosonde observations on medium-range forecasts is strongly positive over the Northern Hemisphere and tropics, whereas the satellite system is most beneficial over the Southern Hemisphere. These results are also found in experiments simulating historical changes in observation systems. Over the tropics, assimilation without radiosonde observations generates unbalanced analyses resulting in unrealistic forecasts that must be corrected by the forecast model. Forecasts based on analysis from the observation data before the era of radiosonde observation are found to be less meaningful. In addition, the impacts on forecasts are closely related to the geographical distribution of observation data. The memory of observation data embedded in the analysis tends to persist throughout forecasts. However, cases exist where the effect of forecast error growth is more dominant than that of analysis error, e.g., over East Asia in summer, and where the deficiency in observations is supplemented or the imbalance in analysis is adjusted by the forecast model during the period of forecasts. Forecast error growth may be related to the synoptic correction performed by the data assimilation system. Over data-rich areas, analysis fields are corrected to a greater extent by the data assimilation system than are those over data-poor areas, which can cause the forecast model to produce more forecast errors in medium-range forecasts. It is found that even one month per season is sufficient for forecast skill verification in data impact experiments. Additionally, the use of upper-air observations is found to benefit areas that are downstream of observation data-rich areas.

Distribution of subjective assessments in a controlled aircraft environment

Within the project ICE (“Ideal Cabin Environment”, funded by the European Commission under contract no. AST4-CT-2005-516131), the impact of different environmental conditions on comfort was investigated by 1500 participants in total. The ICE consortium was made up of 15 members from eight countries. Simulated flights of 8 hours each with 1100 passengers on 29 days were conducted in a large-scale aircraft cabin environment facility near Munich, Germany in winter 2006/2007. During these tests, typical in-flight conditions for noise, vibration, temperature, humidity, and pressure were presented with different level combinations on different days in order to analyze possible effects of these parameters on participantsʼ comfort and well-being. The environmental conditions and passengersʼ physiological response were monitored by sensors, while psychological response was recorded using PDA-based questionnaires. For our share of evaluation, extensive statistical methods were used, applied on a flight-by-flight analysis.As one outcome, the possibility to describe a large class of responses by a function based on the Poisson distribution is shown. An approximation of observed data was performed using the dmax test criteria of the Kolmogorov–Smirnov goodness-of-fit test. In addition, R as the variance-to-mean ratio (VMR) was determined and compared to the quality of the predictions with a significant equality to the observed data. For subjective ratings on a unipolar scale and a calculated VMR of R⩾0.72 in raw distribution data, a success rate of nearly 95% in representing the observed data distribution with one single parameter was identified. This approach allows for a representation of an average participantʼs impression (answer distributions of questionnaire data) of a defined environmental condition and enables for a prediction of not measured, interim situations.

The determination of a “regional” atmospheric background mixing ratio for anthropogenic greenhouse gases: A comparison of two independent methods

Halocarbons are powerful greenhouse gases capable of significantly influencing the radiative forcing of the Earth’s atmosphere. Halocarbons are monitored in several stations which are globally distributed in order to assess long term atmospheric trends and to identify source regions. However, to achieve these aims the definition of background mixing ratios, i.e. the mixing ratio in a given air mass when the recent contribution of local sources is absent, is necessary. This task can be accomplished using different methods. This paper presents a statistical methodology that has been devised specifically for a mountain site located in Continental Europe (Monte Cimone, Italy), characterised by the vicinity of strong sources. The method involves the decomposition of the observed data distribution into a Gaussian distribution, representative of background values, and a Gamma distribution, ascribable to contribution from stronger sources. The method has been applied to a time series from a European marine remote station (Mace Head, Ireland) as well as to time series from Monte Cimone. A comparison of the methodology described in this paper with a well-established meteorological filtering procedure at Mace Head has shown an excellent agreement. A comparison of the baselines at Mace Head, Mt. Cimone and the Swiss alpine station of the Jungfraujoch highlighted the occurrence of a specific background concentration. Although this paper presents the application of the method to three hydrofluorocarbons, the proposed methodology can be extended to any long lived atmospheric component for which a long term time series is available and at any location even if affected by strong source regions.

Characterization of Controls on High-Resolution Stratigraphic Architecture in Wave-Dominated Shoreface-Shelf Parasequences Using Inverse Numerical Modeling

Abstract A new inverse numerical modeling method is used to constrain the environmental parameters (e.g., relative-sea-level, sediment-supply, and wave climate histories) that control stratigraphic architecture in wave-dominated shallow-marine deposits. The method links a “process-response” forward stratigraphic model that simulates wave and storm processes (BARSIM) to a combination of inverse methods formulated in a Bayesian framework that allows full characterization of uncertainties. This method is applied for the first time to a real geologic dataset, collected at outcrop from two shoreface–shelf parasequences in the Aberdeen Member, Blackhawk Formation of the Book Cliffs, east-central Utah, USA. The environmental parameters that controlled the observed stratigraphic architecture are quantified, and key aspects of stratigraphic architecture are successfully predicted from limited data. Stratigraphic architecture at parasequence-stacking and intra-parasequence scales was driven principally by relative sea level (varying by up to about 55 m) and sediment supply (varying by up to 70 m2/yr), whose interplay determines the shoreline trajectory. Within zones of distinctive shoreline trajectory, variations in wave climate (of up to about 3 m in fairweather-wave height) controlled superimposed variations in sandstone and shale content (e.g., the development of upward-coarsening and upward-fining bedsets). The modeling results closely match the observed stratigraphic architecture, but their quality is limited by: (1) the formulation and assumptions of the forward-modeling algorithms, and (2) the observed data distribution and quality, which provide poor age constraint.

Estimation of atmospheric nutrient inputs to the Atlantic Ocean from 50°N to 50°S based on large‐scale field sampling: Fixed nitrogen and dry deposition of phosphorus

Atmospheric nitrogen inputs to the ocean are estimated to have increased by up to a factor of three as a result of increased anthropogenic emissions over the last 150 years, with further increases expected in the short‐ to mid‐term at least. Such estimates are largely based on emissions and atmospheric transport modeling, because, apart from a few island sites, there is very little observational data available for atmospheric nitrogen concentrations over the remote ocean. Here we use samples of rainwater and aerosol we obtained during 12 long‐transect cruises across the Atlantic Ocean between 50°N and 50°S as the basis for a climatological estimate of nitrogen inputs to the basin. The climatology is for the 5 years 2001–2005, during which almost all of the cruises took place, and includes dry and wet deposition of nitrate and ammonium explicitly, together with a more uncertain estimate of soluble organic nitrogen deposition. Our results indicate that nitrogen inputs into the region were ∼850–1420 Gmol (12–20 Tg) N yr−1, with ∼78–85% of this in the form of wet deposition. Inputs were greater in the Northern Hemisphere and in wet regions, and wet regions had a greater proportion of input via wet deposition. The largest uncertainty in our estimate of dry inputs is associated with variability in deposition velocities, while the largest uncertainty in our wet nitrogen input estimate is due to the limited amount and uneven geographic distribution of observational data. We also estimate a lower limit of dry deposition of phosphate to be ∼0.19 Gmol P yr−1, using data from the same cruises. We compare our results to several recent estimates of N and P deposition to the Atlantic and discuss the likely sources of uncertainty, such as the potential seasonal bias introduced by our sampling, on our climatology.

A targeted maximum likelihood estimator of a causal effect on a bounded continuous outcome.

Targeted maximum likelihood estimation of a parameter of a data generating distribution, known to be an element of a semi-parametric model, involves constructing a parametric model through an initial density estimator with parameter ɛ representing an amount of fluctuation of the initial density estimator, where the score of this fluctuation model at ɛ = 0 equals the efficient influence curve/canonical gradient. The latter constraint can be satisfied by many parametric fluctuation models since it represents only a local constraint of its behavior at zero fluctuation. However, it is very important that the fluctuations stay within the semi-parametric model for the observed data distribution, even if the parameter can be defined on fluctuations that fall outside the assumed observed data model. In particular, in the context of sparse data, by which we mean situations where the Fisher information is low, a violation of this property can heavily affect the performance of the estimator. This paper presents a fluctuation approach that guarantees the fluctuated density estimator remains inside the bounds of the data model. We demonstrate this in the context of estimation of a causal effect of a binary treatment on a continuous outcome that is bounded. It results in a targeted maximum likelihood estimator that inherently respects known bounds, and consequently is more robust in sparse data situations than the targeted MLE using a naive fluctuation model. When an estimation procedure incorporates weights, observations having large weights relative to the rest heavily influence the point estimate and inflate the variance. Truncating these weights is a common approach to reducing the variance, but it can also introduce bias into the estimate. We present an alternative targeted maximum likelihood estimation (TMLE) approach that dampens the effect of these heavily weighted observations. As a substitution estimator, TMLE respects the global constraints of the observed data model. For example, when outcomes are binary, a fluctuation of an initial density estimate on the logit scale constrains predicted probabilities to be between 0 and 1. This inherent enforcement of bounds has been extended to continuous outcomes. Simulation study results indicate that this approach is on a par with, and many times superior to, fluctuating on the linear scale, and in particular is more robust when there is sparsity in the data.

Surgical Treatment for Discogenic Low-Back Pain: Lumbar Arthroplasty Results in Superior Pain Reduction and Disability Level Improvement Compared With Lumbar Fusion

Background The US Food and Drug Administration approved the Charité artificial disc on October 26, 2004. This approval was based on an extensive analysis and review process; 20 years of disc usage worldwide; and the results of a prospective, randomized, controlled clinical trial that compared lumbar artificial disc replacement to fusion. The results of the investigational device exemption (IDE) study led to a conclusion that clinical outcomes following lumbar arthroplasty were at least as good as outcomes from fusion. Methods The author performed a new analysis of the Visual Analog Scale pain scores and the Oswestry Disability Index scores from the Charité artificial disc IDE study and used a nonparametric statistical test, because observed data distributions were not normal. The analysis included all of the enrolled subjects in both the nonrandomized and randomized phases of the study. Results Subjects from both the treatment and control groups improved from the baseline situation ( P < .001) at all follow-up times (6 weeks to 24 months). Additionally, these pain and disability levels with artificial disc replacement were superior ( P < .05) to the fusion treatment at all follow-up times including 2 years. Conclusions The a priori statistical plan for an IDE study may not adequately address the final distribution of the data. Therefore, statistical analyses more appropriate to the distribution may be necessary to develop meaningful statistical conclusions from the study. A nonparametric statistical analysis of the Charité artificial disc IDE outcomes scores demonstrates superiority for lumbar arthroplasty versus fusion at all follow-up time points to 24 months.

Surgical treatment for discogenic low-back pain: lumbar arthroplasty results in superior pain reduction and disability level improvement compared with lumbar fusion.

BackgroundThe US Food and Drug Administration approved the Charité artificial disc on October 26, 2004. This approval was based on an extensive analysis and review process; 20 years of disc usage worldwide; and the results of a prospective, randomized, controlled clinical trial that compared lumbar artificial disc replacement to fusion. The results of the investigational device exemption (IDE) study led to a conclusion that clinical outcomes following lumbar arthroplasty were at least as good as outcomes from fusion.MethodsThe author performed a new analysis of the Visual Analog Scale pain scores and the Oswestry Disability Index scores from the Charité artificial disc IDE study and used a nonparametric statistical test, because observed data distributions were not normal. The analysis included all of the enrolled subjects in both the nonrandomized and randomized phases of the study.ResultsSubjects from both the treatment and control groups improved from the baseline situation (P < .001) at all follow-up times (6 weeks to 24 months). Additionally, these pain and disability levels with artificial disc replacement were superior (P < .05) to the fusion treatment at all follow-up times including 2 years.ConclusionsThe a priori statistical plan for an IDE study may not adequately address the final distribution of the data. Therefore, statistical analyses more appropriate to the distribution may be necessary to develop meaningful statistical conclusions from the study. A nonparametric statistical analysis of the Charité artificial disc IDE outcomes scores demonstrates superiority for lumbar arthroplasty versus fusion at all follow-up time points to 24 months.

Analysis of Web page image tag distribution characteristics

The authors investigate the frequency distribution of the use of image tags in Web pages. Using data sampled from top level Web pages across five top level domains and from sample pages within individual websites, the authors model observed patterns in the frequency of image tag usage by fitting collected data distributions to different theoretical models used in informetrics. Models tested include the modified power law (MPL), Mandelbrot (MDB), generalized waring (GW), generalized inverse Gaussian–Poisson (GIGP), and generalized negative binomial (GNB) distributions. The GIGP provided the best fit for data sets for top level pages across the top level domains tested. The poor fits of the models to the observed data distributions from specific websites were due to the multimodal nature of the observed data sets. Mixtures of the tested models for the data sets provided better fits. The ability to effectively model Web page attributes, such as the distribution of the number of image tags used per page, is needed for accurate simulation models of Web page content, and makes it possible to estimate the number of requests needed to display the complete content of Web pages.

Pattern–Mixture and Selection Models for Analysing Longitudinal Data with Monotone Missing Patterns

Summary We examine three pattern–mixture models for making inference about parameters of the distribution of an outcome of interest Y that is to be measured at the end of a longitudinal study when this outcome is missing in some subjects. We show that these pattern–mixture models also have an interpretation as selection models. Because these models make unverifiable assumptions, we recommend that inference about the distribution of Y be repeated under a range of plausible assumptions. We argue that, of the three models considered, only one admits a parameterization that facilitates the examination of departures from the assumption of sequential ignorability. The three models are nonparametric in the sense that they do not impose restrictions on the class of observed data distributions. Owing to the curse of dimensionality, the assumptions that are encoded in these models are sufficient for identification but not for inference. We describe additional flexible and easily interpretable assumptions under which it is possible to construct estimators that are well behaved with moderate sample sizes. These assumptions define semiparametric models for the distribution of the observed data. We describe a class of estimators which, up to asymptotic equivalence, comprise all the consistent and asymptotically normal estimators of the parameters of interest under the postulated semiparametric models. We illustrate our methods with the analysis of data from a randomized clinical trial of contracepting women.

Glacial isostatic adjustment in Fennoscandia with a three-dimensional viscosity structure as an inverse problem

Glacial isostatic adjustment data are commonly used to invert for the radial viscosity structure of the mantle. However, the effects of lateral variations in mantle viscosity in such inversions are not yet accounted for. Here we analysed synthetic sea-level data for the Fennoscandian region, which are derived from a three-dimensional (3D) earth model with realistic lateral and vertical viscosity variations deduced from seismological and geological information. The inversion of the 3D synthetic data for a best-fitting 1D viscosity profile reveals that (i) lateral lithospheric thickness variations can be detected with 1D model predictions, if the data are grouped into regional subsets, (ii) combined lateral variations in lithospheric thickness and asthenospheric viscosity are not properly resolved with 1D model predictions, and (iii) the spatial and temporal distribution of observational data strongly affects the resulting 1D viscosity profile.

Climate modelers meet in Switzerland

The ability to model climate at high spatial resolution is a relatively new scientific initiative. While significant progress has been made in climate modeling, in part as a result of increased spatial resolution, much is still unknown about these models. Climate modelers met in Wengen, Switzerland, last year to assess their progress and difficulties. The difficulties include deficiencies in physical parameterization schemes, inadequate simulations of feedback mechanisms between different elements of the climate system, and problems with the quality, representation, and spatial distribution of observational data for verification purposes.

Cepheids in NGC 1866: a test for pulsational models

We present non-linear theoretical results concerning the predicted pulsational behaviour of stellar models suitable for the sample of Cepheids belonging to the Large Magellanic Cloud (LMC) star cluster NGC 1866. The blue and red edges of the instability strip, transformed into the observed plane (V, B — V) by adopting current values for the distance modulus (DM = 18.57 mag according to Welch et al.) and for the reddening [E(B — V) = 0.06 mag according to Arp and Walker], are in agreement with the observed distribution of Cepheids in the quoted cluster. Moreover, the distribution of observational data in the Bailey diagram (V amplitude versus period) appears to be in agreement with theoretical predictions derived by adopting the luminosity level predicted by canonical evolutionary models. The role played by the direct ab initio integration of the coupling between pulsation and convection and by the input physics on the smoothness of light and velocity curves is briefly discussed.

Data Management and Distribution of Earth Environment Observation Data

Data Management and Distribution of Earth Environment Observation Data

Contributions of frequency distribution analysis to the understanding of coronary restenosis. A reappraisal of the gaussian curve.

Clinical restenosis after balloon angioplasty can be categorized by use of dichotomous terms based on the presence or absence of recurrent myocardial ischemia. In contrast, recent investigations have concluded that late luminal renarrowing, documented through angiographic imaging, occurs to a variable extent in nearly all stenoses. This process has been characterized by a gaussian or normal frequency distribution, with restenosis simply representing an extreme form of this delayed remodeling. In the current study, frequency distribution analysis was used to examine the process of coronary restenosis in a large cohort of patients at risk. Quantitative coronary angiographic analysis was applied to 9279 cineangiograms obtained in 3093 patients before and immediately after angioplasty and after 6-month follow-up. Late loss, defined as the change in minimum lumen diameter of the target stenosis from postdilation to follow-up, did not statistically conform to a normal distribution (P<.0001 by both chi2 statistic and Kolmogorov-Smirnov test), even after the exclusion of the 236 stenoses that displayed total occlusions at follow-up angiography. Examination of deviation from a normal curve revealed an excessively high frequency of stenoses that experienced either little change (0.0+/-0.3 mm) or marked change (1.0 to 2.0 mm) in late loss, with a low frequency of stenoses with intermediate values (0.3 to 1.0 mm). Similarly, although the distribution of percent diameter stenosis of the target lesion was statistically normal immediately after dilation, this gaussian distribution disappeared during the follow-up period. Other angiographic indexes of restenosis also failed to approximate a normal curve. In an attempt to improve the goodness of fit, a probabilistic model of late loss was created on the basis of deconvolution of the observed data distribution. Two theoretical, discrete populations of stenoses were identified, one with and one without overall late luminal narrowing. Unlike the gaussian distribution, this model provided a good representation of the observed data (P=NS for lack of fit). The frequency distributions of angiographic indexes of restenosis often superficially resemble a gaussian curve, an appearance that is artifactually enhanced by the measurement imprecision of current quantitative techniques. Nevertheless, standard indexes of coronary restenosis fail to conform statistically to a normal distribution. The pattern of deviations observed supports the possible existence of discrete subpopulations of lesions, each with a different propensity toward the development of restenosis after coronary intervention.

Bootstrap statistics for velocity tomography: application of a new information criterion1

AbstractA new information criterion, the extended information criterion (EIC) was applied in order to determine an optimum solution in simultaneous iterative reconstruction technique (SIRT) P‐wave velocity tomography. The EIC is derived from information theory and statistics, and it measures the goodness‐of‐fit between the true (unknown) data distribution and the observed data distribution: the former gives the probability of data realization from the true (unknown) model, whereas the latter gives a probability of data realization calculated from a particular model of which parameters are estimated. The EIC is calculated using bootstrap statistics, a numerical technique for calculating statistical estimators. Bootstrap statistics enables us to obtain the bias between the log likelihood and the expected log likelihood, and then to obtain the expected log likelihood from the log likelihood. Since the EIC is obtained numerically, we can use it for most problems of model parameter estimation without employing the maximum likelihood method. Taking weak anisotropy into account, we reconstructed the P‐wave velocity structure of a rock sample during water infiltration under differential stress loading conditions. The results indicate that we can remove unrealistic solutions sometimes encountered when too many iterations are made. In spite of much computation time, the EIC is a promising technique for the near future, prompted by the rapid progress in current computer technology.

Toxic Metals in Ground Water of the Front Range, Colorado

ABSTRACTA study of toxic trace metal distribution in ground waters of the Front Range mineral belt, Colorado and adjacent areas was performed in order to determine the relationship of water quality to mineralization and the magnitude of potential health effects. A total of 149 samples were collected and analyzed for arsenic, cadmium, copper, iron, lead, manganese, mercury, silver and zinc. Field determinations of pH, Eh, and specific conductance were also made.The trace element data exhibited a lognormal distribution and are described utilizing the geometric mean and geometric deviation. Four populations were recognized in the samples: (1) samples in the mineral belt with plumbing contamination; (2) samples in the mineral belt without plumbing contamination, (3) samples outside the mineral belt with plumbing contamination, and (4) samples outside the mineral belt without plumbing contamination. Differences in these populations for several elements are observed utilizing the t test.Utilizing the observed data distributions, geochemical abundance estimates are made for the four recognized populations. The data distributions are corrected for analytical error, corrected for determinations below the detection limit and expressed as a predicted central 95% range for each element in each population. The corrected geometric mean, corrected geometric deviation, along with the U.S. Public Health Service limit for each element determined are used to determine the probability of ground water exceeding the specified limit for each constituent. Ground waters in the mineral belt are estimated to exceed the U.S. Public Health Service limit in 14% of the samples for Cd, 1% for Cu, 51% for Fe, 74% for Mn, 2% for Hg, and 9% for Zn. Ground waters outside the mineral belt have a similar probability of exceeding the limit for Hg and lesser probabilities for all other elements.

Outline of Weather and Wave Forecasting Techniques

Introduction Oil operators engaged in drilling on the Continental Shelf of Louisiana andTexas are in agreement that adverse weather and wave action are two of thegreatest hazards to the safety and efficiency of their work. It was anticipatedwhen the offshore operations commenced that such would be the case, andexperience to date has verified this assumption. Because atmospheric conditionsand wave action involve tremendous amounts of energy it is highly unlikely thatit will be possible to control any but the most localized weather and wavephenomena within the foreseeable future. Thus, as long as the offshoreoperations involve the movement of small craft and barges over exposed waters, and the transfer of personnel and heavy equipment from these craft to eitherfixed structures or larger craft at close quarters, the weather and waveproblem will remain. Taking into consideration the persistence of the wave and weather problemand the improbability of achieving a direct solution, the Humble Oil &amp; Refining Company, in planning its offshore campaign investigated thepossibility of forecasting wave and weather conditions in order to providewarnings of dangerous conditions and increase efficiency in day-to-day planningof work. It was recognized that predictions of wave and weather conditionsbased on meteorology and oceanography, both geophysical sciences, are not 100per cent accurate and application of forecasts in the offshore work wasdependent on whether they provided information which was sufficiently greaterin accuracy than the layman's guess to be worth the expenditure involved. During World War II, meteorology and oceanography were used with success inreducing danger resulting from environmental conditions and increasingefficiency of operations exposed to the elements. This success was partiallythe result of improvement in the scientific techniques involved and theprocurement and distribution of observational data, and partially due to thelarge scope of the military operations which meant that a reduction of lossesof a relatively small percentage of the total cost amounted to a large figureexpressed in terms of dollars. Since the offshore drilling involves anextremely large financial investment, it was considered that the experience ofthe Armed Services in successfully employing meteorology and oceanography mightbe duplicated in the oil industry. In addition, the oil industry's successfulexperience in utilizing seismology, geology, and terrestrial magnetism; allgeophysical sciences, indicated that meteorology and oceanography, also of thefamily of geophysical sciences and sharing their scientific assets andliabilities, might be profitably put to use. T.P. 2546

Results obtained from the analysis of Northern‐Hemisphere weather maps for 1936–1937

Since October 1, 1936, the analysis of a continuous series of charts of the Northern Hemisphere, once daily, has been carried on without interruption at Massachusetts Institute of Technology. The reports used for each region are those coinciding most nearly in time with the 8 p.m. (eastern standard time) observations in the United States. Most of the necessary observations have been received directly by radio. However, the western Pacific and eastern Asiatic observations have up to the present been delayed two days beyond the others, for direct radio reception of these reports has been found difficult, so that it has been necessary to depend upon observations for this area mailed to us each day from the United States Weather Bureau in Washington. It is hoped that in the near future it will be possible to receive the broadcast of these data directly from Honolulu. Unfortunately one bad gap in the circumpolar distribution of observational data still remains—that of central Asia. However, it is usually possible, between the European Russian stations in the west and the eastern Asiatic observations, at least to get some idea of the larger features of the intervening pressure‐distribution. Furthermore, it is hoped that in the near future it will be possible to receive directly the present broadcast from Moscow of central Asiatic reports.