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Topics covered include: data systems and quality; analysis and assimilation techniques; impacts on forecasts; tropical forecasts; analysis intercomparisons; improvements in predictability; and heat sources and sinks.
The focus of this effort is the development of a global-scale model of aerosol backscatter for laser atmospheric wind sounder (LAWS) design and performance studies. Background parameters are derived from aerosol data sets with global-scale spatial and/or temporal coverage, using objective statistical decomposition and/or a priori stratification based on supplementary data. Backscatter coefficients at the LAWS design wavelength are derived from background aerosol physical, chemical, and optical data, or from direct backscatter measurements at other wavelengths, using background conversion factors. Direct measurements of aerosol backscatter at 10.6 microns from the Royal Signals and Radar Establishment (RSRE) and the Wave Propagation Laboratory (WPL) were selected. The RSRE backscatter data processing code were optimized under low backscatter conditions, performed detailed analyses of collocated intercomparisons between the two lidars, and assisted in the analysis of the long-term backscatter climatologies from the two lidars. Timely presentation of global backscattering experiment (GLOBE) research results to the global geophysical community is required.
Papers presented in this volume discuss a mechanism causing mesoscale organizations of precipitation in midlatitude cyclones, the spatial variability of summer Florida precipitation and its impact on microwave radiometer rainfall-measurement systems, the relation between the mean areal rainfall and the fractional area where it rains above a given threshold, and a possible explanation for low correlation dimension estimates for the atmosphere. Attention is also given to a physically based simulation of radar rainfall data using a space-time rainfall model, the predictability of mesoscale rainfall in the tropics, and an intercomparison of tree satellite infrared rainfall techniques over Japan and surrounding waters. Other papers are on an evaluation of sampling errors of precipitation from spaceborne and ground sensors, an approach to the estimation of the areal rain-rate distribution from spaceborne radar by the use of multiple thresholds, and a comparison of two satellite-based rainfall algorithms using Pacific atoll raingage data.
We review recent observations by the Yohkoh-SXT (Soft X-ray Telescope) in collaboration with other spacecraft and ground-based observatories of coronal loops and prominences. These new results point to problems that SoHO will be able to address. With a unique combination of rapid-cadence digital imaging (greater than or equal to 32 s full-disk and greater than or equal to 2 s partial-frame images), high spatial resolution (greater than or equal to 2.5 arcsec pixels), high sensitivity (EM less than or equal to 10(exp 42) cm(exp -3)), a low-scatter mirror, and large dynamic range, SXT can observe a vast range of targets on the Sun. Over the first 21 months of Yohkoh operations SXT has taken over one million images of the corona and so is building up an invaluable long-term database on the large-scale corona and loop geometry. The most striking thing about the SXT images is the range of loop sizes and shapes. The active regions are a bright tangle of magnetic field lines, surrounded by a network of large-scale quiet-Sun loops stretching over distances in excess of 105 km. The cross-section of most loops seems to be constant. Loops displaying significant Gamma's are the exception, not the rule, implying the presence of widespread currents in the corona. All magnetic structures show changes. Time scales range from seconds to months. The question of how these structures are formed, become filled with hot plasma, and are maintained is still open. While we see the propagation of brightenings along the length of active-region loops and in X-ray jets with velocities of several hundred km/s, much higher velocities are seen in the quiet Sun. In XBP flares, for example, velocities of over 1000 km/s are common. Active-region loops seem to be in constant motion, moving slowly outward, carrying plasma with them. During flares, loops often produce localized brightenings at the base and later at the apex of the loop. Quiescent filaments and prominences have been observed regularly. Their coronal manifestation seems to be an extended arcade of loops overlying the filament. Reliable alignment of the ground-based data with the X-ray images make it possible to make a detailed intercomparison of the hot and cold plasma structures over extended periods. Hence we are able to follow the long-term evolution of these structures and see how they become destabilized and erupt.
This paper reports results of NASA's Chemical Instrumentation and Test Evaluation (CITE 3) during which airborne measurements for carbonyl sulfide (COS), hydrogen sulfide (H2S), and carbon disulfide (CS2) were intercompared. Instrumentation included a gas chromatograph using flame photometric detection (COS, H2S, and CS2), a gas chromatograph using mass spectrometric detection (COS) and CS2), a gas chromatograph using fluorination and subsequent SF6 detection via electron capture (COS and CS2), and the Natusch technique (H2S). The measurements were made over the Atlantic Ocean east of North and South America during flights from NASA's Wallops Flight Center, Virginia, and Natal, Brazil, in August/September 1989. Most of the intercomparisons for H2S and CS2 were at mixing ratios less than 25 pptv and less than 10 pptv, respectively, with a maximum mixing ratio of about 100 pptv and 50 pptv, respectively. Carbonyl sulfide intercomparisons were at mixing ratios between 400 and 600 pptv. Measurements were intercompared from data bases constructed from time periods of simultaneous or overlapping measurements. Agreement among the COS techniques averaged about 5%, and individual measurements were generally within 10%. For H2S and at mixing ratio greater than 25 pptv, the instruments agreed on average to about 15%. At mixing ratios less than 25 pptv the agreement was about 5 pptv. For CS2 (mixing ratios less than 50 pptv), two techniques agreed on average to about 4 pptv, and the third exhibited a bias (relative to the other two) that varied in the range of 3-7 pptv. CS2 mixing ratios over the ocean east of Natal as measured by the gas chromatograph-mass spectrometer technique were only a few pptv and were below the detection limits of the other two techniques. The CITE 3 data are used to estimate the current uncertainty associated with aircraft measurements of COS, H2S, and CS2 in the remote troposphere.
It is recognized that the resolved tropical wave spectrum can vary considerably between general circulation models (GCMs) and that these differences can have an important impact on the simulated climate. A comprehensive comparison of the waves is presented for the December-January-February period using high-frequency (three-hourly) data archives from eight GCMs and one simple model participating in the GCM Reality Intercomparison Project for SPARC (GRIPS). Quantitative measures of the structure and causes of the wavenumber-frequency structure of resolved waves and their impacts on the climate are given. Space-time spectral analysis reveals that the wave spectrum throughout the middle atmosphere is linked to variability of convective precipitation, which is determined by the parameterized convection. The variability of the precipitation spectrum differs by more than an order of magnitude between the models, with additional changes in the spectral distribution (especially the frequency). These differences can be explained primarily by the choice of different, cumulus par amet erizations: quasi-equilibrium mass-flux schemes tend to produce small variability, while the moist-convective adjustment scheme is most active. Comparison with observational estimates of precipitation variability suggests that the model values are scattered around the truth. This result indicates that a significant portion of the forcing of the equatorial quasi-biennial oscillation (QBO) is provided by waves with scales that are not resolved in present-day GCMs, since only the moist convective adjustment scheme (which has the largest transient variability) can force a QBO in models that have no parameterization of non-stationary gravity waves. Parameterized cumulus convection also impacts the nonmigrating tides in the equatorial region. In most of the models, momentum transport by diurnal nonmigrating tides in the mesosphere is larger than that by Kelvin waves, being more significant than has been thought. It is shown that the equatorial semi-annual oscillation in the models examined is driven mainly by gravity waves with periods shorter than three days, with at least some contribution from parameterized gravity waves; the contribution from the ultra-fast zonal wavenumber-1 Kelvin waves is negligible.
Future changes in Earth system state will impact agricultural yields and, through these changed yields, can have profound impacts on the global economy. Global gridded crop models estimate the influence of these Earth system changes on future crop yields but are often too computationally intensive to dynamically couple into global multisector economic models, such as the Global Change Assessment Model (GCAM) and other similar-in-scale models. Yet, generalizing a faster site-specific crop model’s results to be used globally will introduce inaccuracies, and the question of which model to use is unclear given the wide variation in yield response across crop models. To examine the feedback loop among socioeconomics, Earth system changes, and crop yield changes, rapidly generated yield responses with some quantification of crop response uncertainty are desirable. The Persephone v1.0 response functions presented in this work are based on the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Climate-Crop Modeling Project (C3MP) sensitivity test data set and are focused on providing GCAM and similar models with a tractable number of rapid to evaluate dynamic yield response functions corresponding to a range of the yield response sensitivities seen in the C3MP data set. With the Persephone response functions, a new variety of agricultural impact experiments will be open to GCAM and other economic models: for example, examining the economic impacts of a multi-year drought in a key agricultural region and how economic changes in response to the drought can, in turn, impact the drought.
The need for accurate wind measurement data in urban areas is a rising concern for advanced air mobility such as uncrewed aircraft systems (UAS) and urban air mobility. The lack of quality observations of wind fields and other parameters presents a challenge for operability. Urban areas provide additional difficulty because of the complex terrain and varying building geometry and their associated flow fields. This has led to an extensive knowledge gap when it comes to real-time urban measurements. This paper focuses on comparison of available systems and the types of measurements for urban wind field campaigns. LiDARs and SoDARs are two of many ground instruments capable of gathering the necessary wind field information. UAS is also a viable technique of obtaining aerial wind measurements. Each of these all have specific strengths that make their measurements more suitable than others. Ground based and airborne systems are evaluated and compared to provide a thorough look into which system or instrument might provide the most accurate and definitive results for urban wind field campaigns.
Abstract: Since 1998 the Southern Hemisphere ADditional OZonesondes (SHADOZ) project has collected more than 2000 ozone profiles from a dozen tropical and subtropical sites using balloon-borne electrochemical concentration cell (ECC) ozonesondes. The data (with accompanying pressure-temperature-humidity soundings) are archived. Analysis of ozonesonde imprecision within the SHADOZ dataset revealed that variations in ozonesonde technique could lead to station-to-station biases in the measurements. In this paper imprecisions and accuracy in the SHADOZ dataset are examined in light of new data. When SHADOZ total ozone column amounts are compared to version 8 TOMS (2004 release), discrepancies between sonde and satellite datasets decline 1-2 percentage points on average, compared to version 7 TOMS. Variability among stations is evaluated using total ozone normalized to TOMS and results of laboratory tests on ozonesondes (JOSE-2O00, Julich Ozonesonde Intercomparison Experiment). Ozone deviations from a standard instrument in the JOSE flight simulation chamber resemble those of SHADOZ station data relative to a SHADOZ-defined climatological reference. Certain systematic variations in SHADOZ ozone profiles are accounted for by differences in solution composition, data processing and instrument (manufacturer). Instrument bias leads to a greater ozone measurement above 25 km over Nairobi and to lower total column ozone at three Pacific sites compared to other SHADOZ stations at 0-20 deg.S.
Total ozone measurements with the Dobson No. 104 (D 104) have been performed at the Meteorological Observatory Hohenpeissenberg since 1967. A critical review of this time series and the comparison with other instruments like TOMS or Brewer spectrophotometer revealed some intervals with uncertainties. Especially in the early eighties a monthly mean bias of about minus 3 percent to TOMS-data with annual variations depending on the mean sun-height exists. An extreme amplitude of 5.6 percent occurs in 1980 with minus 0.76 percent (February) and minus 6.36 percent (July). Two different methods were applied to reprocess the Dobson data set. A comparison of the differently recalculated data showed, that the application of N-corrections by means of the standard-lamp tests starting from the reference values of the Arosa Intercomparison 1986 yields better results than the N-corrections based on a Langley-pilot of the Arosa Intercomparison 1978. The extreme amplitude of the year 1980 is now reduced to 3.02 percent. There is still a slight drift in the monthly and yearly mean differences between TOMS and revised Dobson data. It cannot be excluded, that the satellite data may be responsible for the trend.
One physically informative regularity of their otherwise heterogeneous ensemble, is that many Gamma-Ray Bursts consist of well defined pulses. To objectively quantify the temporal structure of BATSE bursts, we have developed an automatic modeling procedure that separates overlapping pulses and determines the energy-dependence of the pulse-shape parameters. No binning of photon arrival times is needed, so when applied to time-tagged events (TTE) the procedure captures variability information down to the shortest time scales present in the raw data. Maximizing the Bayesian likelihood function Pr(data/model) yields estimates of the model parameters, including the number of pulses present, and allows intercomparison of models of different forms. As with any nonlinear optimization, good initial guesses are crucial to avoid convergence to undesirable local minima. We find excellent initial pulse decompositions by wavelet-denoising a cumulative distribution of the raw photon arrival data; differentiation then gives a time profile mostly free of the systematic effects of degraded resolution (as in ordinary Fourier smoothing) and binning. We present statistical information on pulse rise-time, decay-time, peakedness, and amplitudes, plus their energy dependences - both within a single burst and for a large ensemble of bursts.
The U.S. Geological Survey is examining effects of future sea-level rise on the coastal landscape from Maine to Virginia by producing spatially explicit, probabilistic predictions using sea-level projections, vertical land movement rates (due to isostacy), elevation data, and land-cover data. Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, including Coupled Model Intercomparison Project Phase 5 models following representative concentration pathways 4.5 and 8.5 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. A Bayesian network is used to develop a predictive coastal response model that integrates the sea-level, elevation, and land-cover data with assigned probabilities that account for interactions with coastal geomorphology as well as the corresponding ecological and societal systems it supports. The effects of sea-level rise are presented as (1) level of landscape submergence and (2) coastal response type characterized as either static (that is, inundation) or dynamic (that is, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades (the 2020s, 2030s, 2050s, and 2080s). The probabilistic predictions can be applied to landscape management decisions based on sea-level-rise effects as well as on assessments of the prediction uncertainty and need for improved data or fundamental understanding. This report describes the methods used to produce predictions, including information on input datasets; the modeling approach; model outputs; data-quality-control procedures; and information on how to access the data and metadata online.
The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the Suomi-NPP (SNPP) and NOAA-20 (N20) spacecrafts is a multi-spectral Earth-observing instrument with spectral channels ranging from the visible to the long-wave infrared. In addition to these spectral channels, the VIIRS instrument features a panchromatic Day/Night band (DNB) with 3 gain stages (low, mid, and high) which allows for Earth-view (EV) radiance retrievals over 7 orders of magnitude. The DNB is able to collect data ranging from dim city lights during nighttime up to reflected sunlight from cloud-tops during daytime. The DNB data collection is divided into 32 aggregation modes, where sub-pixel aggregation is used to maintain a nearly constant pixel footprint on ground during EV data collection throughout each scan. The DNB is also sensitive enough to observe bright stars through the instrument space-view (SV) port. Data from these bright stars can be used to track the temporal stability of the sensor gain and as a method of intercomparison between the two VIIRS instruments. In this work, we will present several sensor performance assessments of the VIIRS DNB using stars. In addition to the sensor gain trending, these assessments will include a comparison of the differences between the daytime and nighttime data due to the effects of stray-light, a comparison of the measured signal as a function of aggregation mode, a comparison between the two high-gain sub-stages, and half-angle mirror side for both the SNPP and N20 VIIRS DNB.
Advancements in both land surface models (LSM) and land surface data assimilation, especially over the last decade, have substantially advanced the ability of land data assimilation systems (LDAS) to estimate evapotranspiration (ET). This article provides a historical perspective on international LSM intercomparison efforts and the development of LDAS systems, both of which have improved LSM ET skill. In addition, an assessment of ET estimates for current LDAS systems is provided along with current research that demonstrates improvement in LSM ET estimates due to assimilating satellite-based soil moisture products. Using the Ensemble Kalman Filter in the Land Information System, we assimilate both NASA and Land Parameter Retrieval Model (LPRM) soil moisture products into the Noah LSM Version 3.2 with the North American LDAS phase 2 (NLDAS-2) forcing to mimic the NLDAS-2 configuration. Through comparisons with two global reference ET products, one based on interpolated flux tower data and one from a new satellite ET algorithm, over the NLDAS2 domain, we demonstrate improvement in ET estimates only when assimilating the LPRM soil moisture product.
Number-density data obtained at orbital 'crossover' points with the neutral-gas mass spectrometers aboard the Esro 4, Aeros A, AE-C, and Aeros B satellites are intercompared. All the mass spectrometers were designed to measure the ambient number densities of atomic oxygen, molecular nitrogen, helium, and argon. It is found that the agreement for N2 and O is satisfactory within the experimental errors and that the He measurements exhibit unexpectedly large discrepancies far outside the error range. Calibration and instrument sources of error are considered.
A localized precipitation network has been established over a 4000 sq km region of northern Alabama in support of local weather and climate research at the Global Hydrology and Climate Center (GHCC) in Huntsville. This Cooperative Huntsville-Area Rainfall Measurement (CHARM) network is comprised of over 80 volunteers who manually take daily rainfall measurements from 85 sites. The network also incorporates 20 automated gauges that report data at 1-5 minute intervals on a 24 h a day basis. The average spacing of the gauges in the network is about 6 kin, however coverage in some regions benefit from gauges every 1-2 km. The 24 h rainfall totals from the CHARM network have been used to validate Stage III rainfall estimates of daily and storm totals derived from the WSR-88D radars that cover northern Alabama. The Stage III rainfall product is produced by the Lower Mississippi River Forecast Center (LMRFC) in support of their daily forecast operations. The intercomparisons between the local rain gauge and the radar estimates have been useful to understand the accuracy and utility of the Stage III data. Recently, the Stage III and CHARM rainfall measurements have been combined to produce an hourly rainfall dataset at each CHARM observation site. The procedure matches each CHARM site with a time sequence of Stage III radar estimates of precipitation. Hourly stage III rainfall estimates were used to partition the rain gauge values to the time interval over which they occurred. The new hourly rain gauge dataset is validated at selected points where 1-5 minute rainfall measurements have been made. This procedure greatly enhances the utility of the CHARM data for local weather and hydrologic modeling studies. The conference paper will present highlights of the Stage III intercomparison and some examples of the combined radar / rain gauge product demonstrating its accuracy and utility in deriving an hourly rainfall product from the 24 h CHARM totals.
Upper ocean heat content (HC) is one of the key indicators of climate variability on many time-scales extending from seasonal to interannual to long-term climate trends. For example, HC in the tropical Pacific provides information on thermocline anomalies that is critical for the longlead forecast skill of ENSO. Since HC variability is also associated with SST variability, a better understanding and monitoring of HC variability can help us understand and forecast SST variability associated with ENSO and other modes such as Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), Tropical Atlantic Variability (TAV) and Atlantic Multidecadal Oscillation (AMO). An accurate ocean initialization of HC anomalies in coupled climate models could also contribute to skill in decadal climate prediction. Errors, and/or uncertainties, in the estimation of HC variability can be affected by many factors including uncertainties in surface forcings, ocean model biases, and deficiencies in data assimilation schemes. Changes in observing systems can also leave an imprint on the estimated variability. The availability of multiple operational ocean analyses (ORA) that are routinely produced by operational and research centers around the world provides an opportunity to assess uncertainties in HC analyses, to help identify gaps in observing systems as they impact the quality of ORAs and therefore climate model forecasts. A comparison of ORAs also gives an opportunity to identify deficiencies in data assimilation schemes, and can be used as a basis for development of real-time multi-model ensemble HC monitoring products. The OceanObs09 Conference called for an intercomparison of ORAs and use of ORAs for global ocean monitoring. As a follow up, we intercompared HC variations from ten ORAs -- two objective analyses based on in-situ data only and eight model analyses based on ocean data assimilation systems. The mean, annual cycle, interannual variability and longterm trend of HC have been analyzed
The NASA ER-2 aircraft is used as a platform for high altitude atmospheric missions. The Meteorological Measurement System (MMS) was designed specifically for atmospheric research to provide accurate, fast response, in situ measurements of pressure, temperature, and the three dimensional wind vector. The MMS consists of three subsystems: an air motion sensing system to measure the velocity of the air with respect to the aircraft, a high resolution Inertial Navigation System (INS) to measure the velocity of the aircraft with respect to the Earth, and a Data Acquisition System, to sample, process and record the measured quantities. Details of each of these systems are given. The location of the MMS instrumentation is illustrated. The calibration of the MMS is discussed and results on an intercomparison of MMS measurements, Vaisala radiosonde observation and radar tracking data are given. An illustration of the MMS measurement of vertical wind is given.