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P. Alexander

Abstract

Wrong information may be extracted from balloon soundings if neither appropriate interpretation and processing nor evaluations of certain inevitable distortions or artifacts on atmospheric measurements are performed. A numerical code that finds solutions to the dynamical and thermal equations describing an open balloon in the atmosphere is used to develop flight simulations under diverse conditions. The results are then employed to point out that a valid determination of values for diverse variables is intrinsically difficult. It is shown that the distance between the balloon and gondola may be chosen to optimize the information to be obtained from observations obtained during ascent and descent, so that even without an accurate balloon-tracking system, it may be possible to reconstruct horizontal wind fluctuations from the measurements. Vertical air oscillations may be only grossly inferred in some cases. The propagation direction of gravity waves detected during a sounding may be inferred and vertical wavelengths may typically be determined with a 10% accuracy. Air velocity measurements performed during flotation may be used to find shears.

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Gen. E. P. Alexander

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No Abstract Available.

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Alexander P. Trishchenko

Abstract

Satellite observations in the shortwave infrared (SWIR) part of spectrum between 3.5 and 4.0 μm deliver critically important information for many applications. The satellite signal in this spectral band consists of solar-reflected radiation and thermal radiation emitted by surface, clouds, and atmosphere. Accurate retrievals require precise knowledge of solar irradiance values within a channel's bandwidth. The magnitudes of solar irradiance for shortwave infrared channels (3.7–3.9 μm) for the Advanced Very High Resolution Radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration-7 (NOAA-7) to NOAA-18 satellites and the Geostationary Operational Environmental Satellite-8 (GOES-8) to GOES-12 are considered in this paper. Four recent solar reference spectra [those of Kurucz, Gueymard, the American Society for Testing and Materials (ASTM), and Wehrli] are analyzed to determine uncertainties in the knowledge of solar irradiance values for SWIR channels of the listed sensors. Because thermal radiation is frequently converted to effective blackbody temperature for analysis, computations, and calibration purposes, it is proposed here to express band-limited solar irradiance values in terms of brightness temperature as well. It is shown that band-limited solar irradiance for AVHRR radiometers expressed in terms of blackbody equivalent brightness temperature correspond to the range 355–360 K, and vary around 345 K for the SWIR channels of the GOES imagers. The values of band-limited solar irradiance and brightness temperatures are provided for various reference solar spectra. The relative differences in band-limited solar irradiance computed for the considered reference solar spectra are between 0% and 2.5%. Differences expressed in terms of brightness temperatures may reach 0.8 K. The results for the ASTM and the Kurucz reference spectra agree within 0.1% relative difference. Parameters of linear fits relating effective brightness temperatures and spectral radiance equivalent temperatures are also determined for all sensors. They are required for precise radiance–temperature and temperature–radiance conversion through Planck's functions in the case of the finite spectral response of real sensors.

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Alexander Gershunov and Tim P. Barnett

Abstract

The signature of ENSO in the wintertime frequencies of heavy precipitation and temperature extremes is derived from both observations and atmospheric general circulation model output for the contiguous United States. ENSO signals in the frequency of occurrence of heavy rainfall are found in the Southeast, Gulf Coast, central Rockies, and the general area of the Mississippi–Ohio River valleys. Strong, nonlinear signals in extreme warm temperature frequencies are found in the southern and eastern United States. Extreme cold temperature frequencies are found to be less sensitive to ENSO forcing than extreme warm temperature frequencies. Observed ENSO signals in extreme temperature frequencies are not simply manifestations of shifts in mean seasonal temperature. These signals in the wintertime frequency of extreme rainfall and temperature events appear strong enough to be useful in long-range regional statistical prediction.

Comparisons of observational and model results show that the model climate is sensitive to ENSO on continental scales and provide some encouragement to modeling studies of intraseasonal sensitivity to low-frequency climatic forcing. However, large regional disagreements exist in all variables. Continental-scale El Niño signatures in intraseasonal temperature variability are not correctly modeled. Modeled signals in extreme temperature event frequencies are much more directly related to shifts in seasonal mean temperature than they are in nature.

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Simon P. Alexander and Toshitaka Tsuda

Abstract

The first campaign-based measurements of virtual temperature in the upper-troposphere and lower-stratosphere (UTLS) region were made with the middle- and upper-atmosphere (MU) radar radio acoustic sounding system (RASS) during 4 days in August 1995. This dataset was examined in order to study high-frequency changes in the stability below 20 km, but especially in the UTLS region. Calculations of the WMO tropopause and cold-point tropopause heights showed the latter to be (1.0 ± 0.6) km higher, where 0.6 km is the standard deviation. A diurnal cycle of temperature and wind dominated the spectra, which was identified as the diurnal solar tide. Its phase maximum occurred in the afternoon between 5 and 15 km and showed upward energy propagation above this height. Changes in the UTLS kinetic energy dissipation rate ε showed significant high-frequency fluctuations embedded within layers that persisted for at least 1 day. Relative to the WMO tropopause height, the median ε increased from (0.5 ± 0.1) × 10−3 m2 s−3 in the upper troposphere to (0.7 ± 0.1) × 10−3 m2 s−3 in the lower stratosphere.

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Alexander P. Trishchenko and Shusen Wang

Abstract

Snow and ice over land are important hydrological resources and sensitive indicators of climate change. The Moderate Resolution Imaging Spectroradiometer (MODIS) dataset at 250-m spatial resolution generated at the Canada Centre for Remote Sensing (CCRS) is used to derive the annual minimum snow and ice (MSI) extent over the Canadian Arctic landmass over a 17-yr time span (2000–16). The smallest MSI extent (1.53 × 105 km2) was observed in 2012, the largest (2.09 × 105 km2) was observed in 2013; the average value was 1.70 × 105 km2. Several reanalyses and observational datasets are assessed to explain the derived MSI variations: the ERA-Interim reanalysis, North American Regional Reanalysis (NARR), Clouds and the Earth’s Radiant Energy System (CERES) radiative fluxes, and European Space Agency’s GlobSnow dataset. Comparison with the Randolph Glacier Inventory (RGI) showed two important facts: 1) the semipermanent snowpack in the Canadian Arctic that persists through the entire melting season is a significant component relative to the ice caps and glacier-covered areas (up to 36% or 5.58 × 104 km2), and 2) the MSI variations are related to variations in the local climate dynamics such as warm season average temperature, energy fluxes, and snow cover. The correlation coefficients (absolute values) can be as high as 0.77. The reanalysis-based MSI estimates agree with satellite MSI results (average bias of 2.2 × 103 km2 or 1.3% of the mean value).

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Alexander Gershunov and Tim P. Barnett

Seasonal climate anomalies over North America exhibit rather large variability between years characterized by the same ENSO phase. This lack of consistency reduces potential statistically based ENSO-related climate predictability. The authors show that the North Pacific oscillation (NPO) exerts a modulating effect on ENSO teleconnections. Sea level pressure (SLP) data over the North Pacific, North America, and the North Atlantic and daily rainfall records in the contiguous United States are used to demonstrate that typical ENSO signals tend to be stronger and more stable during preferred phases of the NPO. Typical El Niño patterns (e.g., low pressure over the northeastern Pacific, dry northwest, and wet southwest, etc.) are strong and consistent only during the high phase of the NPO, which is associated with an anomalously cold northwestern Pacific. The generally reversed SLP and precipitation patterns during La Niña winters are consistent only during the low NPO phase. Climatic anomalies tend to be weak and spatially incoherent during low NPO–E1 Niño and high NPO–La Niña winters. These results suggest that confidence in ENSO-based long-range climate forecasts for North America should reflect interdecadal climatic anomalies in the North Pacific.

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Alexander P. Trishchenko and Calin Ungureanu

Capsule Summary

For the first time, time series of annual minimum snow/ice extent over the Northern landmass have been derived and used to assess the snow extent that survives the summer melt.

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Alexander P. Trishchenko and Louis Garand

Abstract

There has been a significant increase of interest in the building of a comprehensive Arctic observing system in recent years to properly and timely track the environmental and climate processes in this vast region. In this regard, a satellite observing system on highly elliptical orbit (HEO) with 12-h period (Molniya type) is of particular interest, because it enables continuous coverage of the entire Arctic region (58°–90°N) from a constellation of two satellites. Canada is currently proposing to operate such a constellation by 2017. Extending the pioneering study of S. Q. Kidder and T. H. Vonder Haar, this paper presents in-depth analysis of spatiotemporal sampling properties of the imagery from this system. This paper also discusses challenges and advantages of this orbit for various applications that require high temporal resolution and angular sampling.

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Zhanqing Li and Alexander P. Trishchenko

Abstract

The concept of cloud radiative forcing (CRF) has been widely employed in studying the effects of clouds on the earth’s radiation budget and climate. CRF denotes, in principle, the net influence of cloud alone on the radiation budget of a system. In practice, however, observational determination of CRF is fraught with uncertainties due to factors other than cloud that induce changes in atmospheric background conditions. The most notable variables include aerosol, water vapor, and the data sampling scheme. The impact of these factors on the derivation of CRF and cloud absorption is investigated here by means of modeling and analysis of multiple datasets. Improved estimation of CRF is attempted at the top of the atmosphere (TOA) and at the surface from spatially and temporally collocated ground and satellite measurements for broadband shortwave fluxes. Satellite data employed include pixel measurements from ERBE (1988–90), ScaRaB (1994–95), and CERES (1998), as well as surface data acquired across the Canadian radiation network, the ARM Central Facility site in Oklahoma, the US/NOAA SURFRAD networks, and the world BSRN (WMO) networks. It is found that surface CRF is much more susceptible to the variability in background conditions than TOA CRF. Selection of overly clear sky conditions often leads to significant overestimation of surface CRF, but TOA CRF remains intact or only slightly affected. As a result, the ratio of CRF at the surface and TOA is prone to overestimation. With careful treatments of these effects, the CRF ratio turns out to vary mostly between 0.9 and 1.1, implying approximately the same magnitude of atmospheric absorption under clear-sky and cloudy-sky conditions.

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