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Theoretical studies of low frequency and seasonal weather variability; dynamical properties of observational and general circulation model (GCM)-generated records; effects of the hydrologic cycle and latent heat release on extratropical weather; and Earth-system science studies are summarized.
The framework for a model of travel demand which will be useful in predicting the total market for air travel between two cities is discussed. Variables to be used in determining the need for air transportation where none currently exists and the effect of changes in system characteristics on attracting latent demand are identified. Existing models are examined in order to provide insight into their strong points and shortcomings. Much of the existing behavioral research in travel demand is incorporated to allow the inclusion of non-economic factors, such as convenience. The model developed is characterized as a market segmentation model. This is a consequence of the strengths of disaggregation and its natural evolution to a usable aggregate formulation. The need for this approach both pedagogically and mathematically is discussed.
A newly developed, weakly coupled land and atmosphere data assimilation system for NASA’s Global Earth Observing System model is presented, and used to demonstrate the benefit of assimilating satellite soil moisture into an atmospheric reanalysis. Specifically, Advanced Scatterometer and Soil Moisture Ocean Salinity soil moisture retrievals are assimilated into a system that uses the same model, atmospheric assimilation system, and atmospheric observations as the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). The atmosphere is sensitive to soil moisture only under certain conditions. Hence, while the globally averaged model improvements were small, regionally, the soil moisture assimilation induced some substantial improvements. For example, in a large region spanning from western Europe across southern Russia, the soil moisture assimilation decreased the RMSE against independent station observations of daily maximum 2-m temperature (T(sup 2m, sub max)) by up to 0.4 K, and of 2-m specific humidity (q(exp 2m)) by up to 0.5 g/kg. Over all available stations, the mean T(sup 2m, sub max) RMSE was reduced from 2.82 to 2.79 K, while the mean q(exp 2m) RMSE was reduced from 1.25 to 1.20 g/kg. The soil moisture assimilation also reduced the mean RMSE across 29 flux tower sites from 34.2 to 32.6 Wm(exp −2) for latent heating, and from 37.7 to 36.5 Wm(exp −2) for sensible heating. For all variables evaluated, the soil moisture assimilation improved the model at monthly to seasonal, rather than daily, time scales. Based on the above experiments, it is recommended that satellite soil moisture be assimilated into future reanalyses, including the follow-on to MERRA-2.
Trend terms in models for wheat yield in the U.S. Great Plains for the years 1932 to 1976 are evaluated. The subset of meteorological variables yielding the largest adjusted R(2) is selected using the method of leaps and bounds. Latent root regression is used to eliminate multicollinearities, and generalized ridge regression is used to introduce bias to provide stability in the data matrix. The regression model used provides for two trends in each of two models: a dependent model in which the trend line is piece-wise continuous, and an independent model in which the trend line is discontinuous at the year of the slope change. It was found that the trend lines best describing the wheat yields consisted of combinations of increasing, decreasing, and constant trend: four combinations for the dependent model and seven for the independent model.
The present diurnal and seasonal thermal model for Mars, in which surface CO2 frost condensation and sublimation are determined by the net effects of radiation, latent heat, and heat conduction in subsurface soil layers, in order to simulate seasonal exchanges of CO2 between the polar caps and atmosphere, successfully reproduces the measured pressured variations at the Viking Lander 1 site. In the second part of this work, the year-to-year differences between measured surface pressures at Viking sites as a function of season are used as upper limits on the potential magnitudes of interannual variations in the Martian atmosphere's mass. Simulations indicate that the dust layers deposited onto the condensing north seasonal polar cap during dust storms can darken seasonal frost deposits upon their springtime uncovering, while having little effect on seasonal pressure variations.
The potential complexity of the feedback between global mean cloud amount and global mean surface temperature when variations of the vertical cloud distribution are included is illustrated. This is done by studying the behavior of a one-dimensional radiative-convective model with two types of cloud variation: (1) variable cloud cover with constant optical thickness and (2) variable optical thickness with constant cloud cover. The variable parameter is calculated on the assumption that a correlation exists between cloud amount and precipitation or the vertical flux convergence of latent heat. Since the vertical latent heat flux is taken to be a fraction of the total heat flux, modeled by convective adjustment, the sensitivity of the results to two different critical lapse rates is examined. These are a constant 6.5 K/km lapse rate and a temperature-dependent, moist adiabatic lapse rate. The effects of the vertical structure of climate perturbations on the nature of the cloud feedback are also examined. The model results reveal that changes in the vertical cloud distribution and mean cloud optical thickness can be as important to climate variations as are changes in the total cloud cover.
The feasibility of using radio frequency receivers to collect data from automated weather stations to model fluxes of latent heat, sensible heat, and radiation using routine weather data collected by automated weather stations was tested and the estimated fluxes were compared with fluxes measured over wheat. The model Cupid was used to model the fluxes. Two or more automated weather stations, interrogated by radio frequency and other means, were utilized to examine some of the climatic variability of the First ISLSCP (International Satellite Land-Surface Climatology Project) Field Experiment (FIFE) site, to measure and model reflected and emitted radiation streams from various locations at the site and to compare modeled latent and sensible heat fluxes with measured values. Some bidirectional reflected and emitted radiation data were collected from 23 locations throughout the FIFE site. Analysis of these data along with analysis of the measured sensible and latent heat fluxes is just beginning.
The latest catastrophic earthquake in Japan (March 2011) has renewed interest in the important question of the existence of pre-earthquake anomalous signals related to strong earthquakes. Recent studies have shown that there were precursory atmospheric/ionospheric signals observed in space associated with major earthquakes. The critical question, still widely debated in the scientific community, is whether such ionospheric/atmospheric signals systematically precede large earthquakes. To address this problem we have started to investigate anomalous ionospheric / atmospheric signals occurring prior to large earthquakes. We are studying the Earth's atmospheric electromagnetic environment by developing a multisensor model for monitoring the signals related to active tectonic faulting and earthquake processes. The integrated satellite and terrestrial framework (ISTF) is our method for validation and is based on a joint analysis of several physical and environmental parameters (thermal infrared radiation, electron concentration in the ionosphere, lineament analysis, radon/ion activities, air temperature and seismicity) that were found to be associated with earthquakes. A physical link between these parameters and earthquake processes has been provided by the recent version of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model. Our experimental measurements have supported the new theoretical estimates of LAIC hypothesis for an increase in the surface latent heat flux, integrated variability of outgoing long wave radiation (OLR) and anomalous variations of the total electron content (TEC) registered over the epicenters. Some of the major earthquakes are accompanied by an intensification of gas migration to the surface, thermodynamic and hydrodynamic processes of transformation of latent heat into thermal energy and with vertical transport of charged aerosols in the lower atmosphere. These processes lead to the generation of external electric currents in specific regions of the atmosphere and the modifications, by dc electric fields, in the ionosphere-atmosphere electric circuit. We retrospectively analyzed temporal and spatial variations of four different physical parameters (gas/radon counting rate, lineaments change, long-wave radiation transitions and ionospheric electron density/plasma variations) characterizing the state of the lithosphere/atmosphere coupling several days before the onset of the earthquakes. Validation processes consist in two phases: A. Case studies for seven recent major earthquakes: Japan (M9.0, 2011), China (M7.9, 2008), Italy (M6.3, 2009), Samoa (M7, 2009), Haiti (M7.0, 2010) and, Chile (M8.8, 2010) and B. A continuous retrospective analysis was preformed over two different regions with high seismicity- Taiwan and Japan for 2003-2009. Satellite, ground surface, and troposphere data were obtained from Terra/ASTER, Aqua/AIRS, POES and ionospheric variations from DEMETER and COSMIC-I data. Radon and GPS/TEC were obtaining from monitoring sites in Taiwan, Japan and Italy and from global ionosphere maps (GIM) respectively. Our analysis of ground and satellite data during the occurrence of 7 global earthquakes has shown the presence of anomalies in the atmosphere. Our results for Tohoku M9.0 earthquake show that on March 7th, 2011 (4 days before the main shock and 1 day before the M7.2 foreshock of March 8, 2011) a rapid increase of emitted infrared radiation was observed by the satellite data and an anomaly was developed near the epicenter. The GPS/TEC data indicate an increase and variation in electron density reaching a maximum value on March 8. From March 3 to 11 a large increase in electron concentration was recorded at all four Japanese ground-based ionosondes, which returned to normal after the main earthquake. Similar approach for analyzing atmospheric and ionospheric parameters has been applied for China (M7.9, 2008), Italy (M6.3, 2009), Samoa (M7, 2009), Haiti (M7.0, 2010) and Chile (M8.8, 2010) eahquakes. Results have revealed the presence of related variations of these parameters implying their connection with the earthquake process. The second phase (B) of this validation included 102 major earthquakes (M>5.9) in Taiwan and Japan. We have found anomalous behavior before all of these events with no false negatives. False alarm ratio for false positives is less then 10% and has been calculated for the same month of the earthquake occurrence for the entire period of analysis (2003-2009). The commonalities for detecting atmospheric/ionospheric anomalies are: i.) Regularly appearance over regions of maximum stress (i.e., along plate boundaries); ii.) Anomaly existence over land and sea; and iii) association with M>5.9 earthquakes not deeper than 100km. Due to their long duration over the same region these anomalies are not consistent with a meteorological origin. Our initial results from the ISTF validation of multi-instrument space-borne and ground observations show a systematic appearance of atmospheric anomalies near the epicentral area, one to seven (average) days prior to the largest earthquakes, and suggest that it could be explained by a coupling process between the observed physical parameters and the pre-earthquake preparation processes.
Satellite soil moisture observations are assimilated into NASA's Global Earth Observing System using a weakly coupled land/atmosphere data assimilation system. Specifically, Advanced Scatterometer and Soil Moisture Ocean Salinity soil moisture retrievals are assimilated with an Ensemble Kalman Filter into a system that uses the same model, atmospheric assimilation system (3DVar), and atmospheric observations as the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The first set of experiments investigate the impact of the soil moisture assimilation on the model states and fluxes within the cycling DA system. Comparison to independent ground-based observations from global networks of soil moisture, latent and sensible heating, and 2m temperature and specific humidity showed small, but positive, improvements in the global mean statistics. Additionally, in some regions, the soil moisture assimilation induced more substantial improvements. For all variables evaluated, the soil moisture assimilation improved the model at monthly to seasonal, rather than daily, time scales. Based on the above experiments, it is recommended that satellite soil moisture be assimilated into future reanalyses, including the follow-on to MERRA-2.
Thermal inertia of the earth's surface can be used in geologic mapping as a complement to surface reflectance data as provided by Landsat. Thermal inertia cannot be determined directly but must be inferred from radiation temperature measurements (by thermal IR sensors) made at various times in the diurnal cycle, combined with a model of the surface heating processes. A model is developed which differs from those created previously for this purpose, because it includes sensible and latent heating. Tests of this model using field data indicate that it accurately determines the surface heating. When the model is used with field measurements of meteorological variables and is combined with remotely sensed temperature data, a thermal inertia image can be produced.
The Tropical Rainfall Measuring Mission was a new concept of measuring rainfall over the global tropics using a combination of instruments, including the first weather radar to be flown in space. An important objective of the mission was to obtain profiles of latent heat in order to initialize large-scale circulation models and to understand the relationship between short-term climate changes in relation to rainfall variability. The idea originated in the early 1980's from scientists at the Goddard Space Flight Center/NASA who had been involved with attempts to measure rain with a passive microwave instrument on Nimbus 5 and had compared its results with rain falling in the area covered by the GATE1 radar ships. Using an imaginary satellite flying over the GATE ships, scientists showed that a satellite with an inclined orbit of 30-35 degrees could obtain monthly rainfalls with a sampling error of less than 10 percent over 5 degree by 5 degree areas. The Japanese proposed that they could build a nadir-scanning rain radar for the satellite. Vern Suomi was excited by this mission from the outset, since he recognized the great importance of adequate rainfall measurements over the tropical oceans. He was a charter member of the Science Steering Team and prepared a large part of the Report. While the mission attracted strong support in the science community, it was opposed by some of the high-level NASA management who feared its competition for funds with some much larger Earth Science satellites. Vern was able to overcome this opposition and to generate Congressional support, so that the Project finally got underway on both sides of the Pacific in 1991. The paper will discuss the design of the satellite, its data system and ground validation program. TP.NM was successfully launched in late 1997. Early results will be described. 1 GATE stands for GARP Atlantic Tropical Experiment and GARP stands for Global Atmospheric Research Program.
The research described in this chapter demonstrates a method for using Landsat Thematic Mapper data to estimate instantaneous regional-scale energy fluxes over an arid valley in eastern Nevada, U.S.A. Here point-based models of surface energy and water balance fluxes were applied to individual pixels of a Landsat Thematic Mapper scene over the study area. Although the method used to estimate these instantaneous fluxes requires certain assumptions be made about the spatial distribution of several physical parameters, the results from this analysis and modeling suggest that it is possible to scale from point measurements of environmental state variables (i.e., net radiation flux, surface heat flux, sensible heat flux, and latent heat flux) to regional estimates of energy exchange to obtain an understanding of the spatial relationship between these fluxes and landscape variables.
Astronauts often use promethazine (PMZ) to counteract space motion sickness; however PMZ may cause drowsiness, which might impair cognitive function. In a NASA ground study, subjects received PMZ and their cognitive performance was then monitored over time. Subjects also reported sleepiness using the Karolinska Sleepiness Score (KSS), which ranges from 1 - 9. A problem arises when using KSS to establish an association between true sleepiness and performance because KSS scores tend to overly concentrate on the values 3 (fairly awake) and 7 (moderately tired). Therefore, we defined a latent sleepiness measure as a continuous random variable describing a subject s actual, but unobserved true state of sleepiness through time. The latent sleepiness and observed KSS are associated through a conditional probability model, which when coupled with demographic factors, predicts performance.
The Tropical Ocean Global Atmosphere (TOGA) Program is a component of the World Meteorological Organization (WMO)/International Council of Scientific Unions (ICSU) World Climate Research Program (WCRP). One of the objectives of TOGA, which began in 1985, is to determine the limits of predictability of monthly mean sea surface temperature variations in tropical regions. The TOGA program created a raison d'etre for an explosive growth of the tropical ocean observing system and a substantial improvement in numerical simulations from atmospheric and oceanic general circulation models. Institutions located throughout the world are involved in the TOGA-distributed active data archive system. The diverse TOGA data sets for 1985 and 1986, including results from general circulation models, are included on a CD-ROM. Variables on the CD-ROM are barometric pressure, surface air temperature, dewpoint temperature Cartesian components of surface wind, surface sensible and latent heat fluxes,Cartesian components of surface wind stress and of an index of surface wind stress, sea level, sea surface temperature, and depth profiles of temperature and current in the upper ocean. Some data sets are global in extent, some are regional and cover portions of an ocean basin. Data on the CD-ROM can be extracted with an Apple Macintosh or an IBM PC.
The accuracy of the moist saturation adjustment scheme has been evaluated using a three-dimensional explicit microphysical cloud model. It was found that the error in saturation adjustment depends strongly on the Cloud Condensation Nucleii (CCN) concentration in the ambient atmosphere. The scheme provides rather accurate results in the case where a sufficiently large number of CCN (on the order of several hundred per cubic centimeter) is available. However, under conditions typical of marine stratocumulus cloud layers with low CCN concentration, the error in the amounts of condensed water vapor and released latent heat may be as large as 40%-50%. A revision of the saturation adjustment scheme is devised that employs the CCN concentration, dynamical supersaturation, and cloud water content as additional variables in the calculation of the condensation rate. The revised condensation model reduced the error in maximum updraft and cloud water content in the climatically significant case of marine stratocumulus cloud layers by an order of magnitude.
Land-atmosphere (L-A) interactions are important for understanding convective processes, climate feedbacks, the development and perpetuation of droughts, heatwaves, pluvials, and other land-centred climate anomalies. Local L-A coupling (LoCo) metrics capture relevant L-A processes, highlighting the impact of soil and vegetation states on surface flux partitioning, and the impact of surface fluxes on boundary layer (BL) growth, development, and entrainment of air above the BL. A primary goal of the Climate Process Team on Coupling Land and Atmospheric Subgrid Parameterizations (CLASP) is parameterizing and characterizing the impact of subgrid heterogeneity in global and regional earth system models (ESMs) to improve the connection between land and atmospheric states and processes. A critical step in achieving that aim is the incorporation of L-A metrics, especially LoCo metrics, into climate model diagnostic process streams. However, because land-atmosphere interactions span time scales of minutes (e.g., turbulent fluxes), hours (e.g., BL growth and decay), days (e.g., soil moisture memory), and seasons (e.g., variability of behavioural regimes between soil moisture and latent heat flux), with multiple processes of interest happening in different geographic regions at different times of year, there is not a single metric that captures all the modes, means, and methods of interaction between the land and the atmosphere. And while monthly means of most of the LoCo-relevant variables are routinely saved from ESM simulations, data storage constraints typically preclude routine archival of the hourly data that would enable the calculation of all LoCo metrics. Here we outline a reasonable data request that would allow for adequate characterization of sub-daily coupling processes between the land and the atmosphere, preserving enough sub-daily output to describe, analyse, and better understand L-A coupling in modern climate models. A secondary request involves embedding calculations within the models to determine mean properties in and above the BL to further improve characterization of model behaviour. Higher-frequency model output will (i) allow for more direct comparison with observational field campaigns on process-relevant time scales, (ii) enable demonstration of inter-model spread in L-A coupling processes, and (iii) aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Understanding climate variability over a wide range of space-time scales requires a comprehensive description of the earth system. Global analyses produced by a fixed assimilation system (i.e., re-analyses) - as their quality continues to improve - have the potential of providing a vital tool for meeting this challenge. But at the present time, the usefulness of re-analyses is limited by uncertainties in such basic fields as clouds, precipitation, and evaporation - especially in the tropics, where observations are relatively sparse. Analyses of the tropics have long been shown to be sensitive to. the treatment of cloud precipitation processes, which remains a major source of uncertainty in current models. Yet, for many climate studies it is crucial that analyses can accurately reproduce the observed rainfall intensity and variability since a small error of 1 mm/d in surface rain translates into an error of approx. 30 W/sq m in energy (latent heat) flux. Currently, discrepancies between the observed and analyzed monthly-mean rain rates averaged to 100 km x 100 km resolution can exceed 4 mm/d (or 120 W/sq m ), compared to uncertainties in surface radiative fluxes of approx. 10-20 W/sq m . Improving precipitation in analyses would reduce a major source of uncertainty in the global energy budget. Uncertainties in tropical precipitation have also been a major impediment in understanding how the tropics interact with other regions, including the remote response to El Nino/Southern Oscillation (ENSO) variability on interannual time scales, the influence of Madden-Julian Oscillation (MJO) and monsoons on intraseasonal time scales. A global analysis that can replicate the observed precipitation variability together with physically consistent estimates of other atmospheric variables provides the key to breaking this roadblock. NASA Goddard Space Flight Center has been exploring the use of satellite-based microwave rainfall measurements in improving global analyses and has recently produced a multi-year, 1 x 1 TRMM re-analysis , which assimilates 6-hourly TMI and SSM/I surface rain rates over tropical oceans using a ID variational continuous assimilation (VCA) procedure in the GEOS-3 global data assimilation system. The analysis period extends from 1 November 1997 through 3 1 December 2002. The goal is to produce a multi-year global analysis that is dynamically consistent with available tropical precipitation observations for the community to assess its utility in climate applications and identify areas for further improvements. A distinct feature of the GEOS-3RRMh4 re-analysis is that its precipitation analysis is not derived from a short-term forecast (as done in most operational systems) but is given by a time- continuous model integration constrained by precipitation observations within a 6-h analysis window, while the wind, temperature, and pressure fields are allowed to directly respond to the improved precipitation and associated latent heating structures within the same analysis window. In this talk, I will assess the impact VCA precipitation assimilation on analyses of climate signals ranging from a few weeks to interannual time scales and compare results against other operational and reanalysis products.
Aspects of the angular momentum cycle, energetics, and related diagnostics from a number of models, including some from the Goddard Laboratory for Atmospheres, and from the Atmospheric Model Intercomparison Project (AMIP) are examined. Torques that dynamically excite changes in angular momentum, including strong torques at mountains were studied. The measure of how atmospheric mass from a strong weather signal can notably change the angular momentum is studied. For AMIP, there is a spread in the angular momentum amongst models, while the GLA model does reasonably well compared to the other models in the diagnostics examined, namely angular momentum and water vapor. Trends and interannual variability in water vapor over a lengthy period was examined. The role of the diabatic heating components, especially latent heating, in the energy cycle and the terms converting available potential energy to kinetic energy, among other parts of the energy cycle, are studied. Modes of climate of the atmosphere, especially the Arctic and North Atlantic Oscillations, are analyzed as well.