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1. Introduction The Geostationary Operational Environmental Satellite-R series (GOES-R) is due to launch in early 2016 as of this writing. In preparation for this launch and in order to optimize return on investment, many ongoing research activities are being carried out to explore and exploit the full information content of the GOES-R instrument data. One instrument on GOES-R is the Geostationary Lightning Mapper (GLM) described in Goodman et al. (2013) . The GLM will map the locations and
1. Introduction The Geostationary Operational Environmental Satellite-R series (GOES-R) is due to launch in early 2016 as of this writing. In preparation for this launch and in order to optimize return on investment, many ongoing research activities are being carried out to explore and exploit the full information content of the GOES-R instrument data. One instrument on GOES-R is the Geostationary Lightning Mapper (GLM) described in Goodman et al. (2013) . The GLM will map the locations and
DEPARTMENT OF COMMERCELEWISL. STRAWS, Secretary WEATHER BUREAU F. W. REICHELDERFER, ChiefMONTHLY WEATHER REVIEWJAMESE.CASKEY, JR., EditorVolume 87 Number 2 FEBRUARY 1959 Closed April 15, 1959 Issued May 15, 1959COMPARISON OF BAROTROPIC AND BAROCLINIC NUMERICALFORECASTS AND CONTRIBUTIONS OF VARIOUS EFFECTSMAJOR LLOYD W. VANDERMAN,' US. Air ForceWILLIAM J. DREWES, US. NavyandLEO E. HOPP, U.S. Weather BureauJoint Numerical Weather Prediction Unit, Suitland, Md.[Manuscript received November 7, 195B
DEPARTMENT OF COMMERCELEWISL. STRAWS, Secretary WEATHER BUREAU F. W. REICHELDERFER, ChiefMONTHLY WEATHER REVIEWJAMESE.CASKEY, JR., EditorVolume 87 Number 2 FEBRUARY 1959 Closed April 15, 1959 Issued May 15, 1959COMPARISON OF BAROTROPIC AND BAROCLINIC NUMERICALFORECASTS AND CONTRIBUTIONS OF VARIOUS EFFECTSMAJOR LLOYD W. VANDERMAN,' US. Air ForceWILLIAM J. DREWES, US. NavyandLEO E. HOPP, U.S. Weather BureauJoint Numerical Weather Prediction Unit, Suitland, Md.[Manuscript received November 7, 195B
engagements. The anticipated effects on HEL propagation performance are assessed at an operating wavelength of 1.0642 μ m across the world’s oceans and mapped onto a 1° × 1° worldwide grid. The scenario evaluated is near surface and nearly horizontal over a range of 5000 m in which anticipated clear-air maritime aerosols occur. Summer and winter scenarios are considered. In addition to realistic vertical profiles of molecular and aerosol absorption and scattering, correlated optical turbulence profiles
engagements. The anticipated effects on HEL propagation performance are assessed at an operating wavelength of 1.0642 μ m across the world’s oceans and mapped onto a 1° × 1° worldwide grid. The scenario evaluated is near surface and nearly horizontal over a range of 5000 m in which anticipated clear-air maritime aerosols occur. Summer and winter scenarios are considered. In addition to realistic vertical profiles of molecular and aerosol absorption and scattering, correlated optical turbulence profiles
1. Introduction Ray solutions are often expressed in spatial coordinates. Some examples for mountain waves are given in Gjevik and Marthinsen (1978) , Hines (1988) , Shutts (1998) , and Broad (1999) . Ray solutions can also be expressed in Fourier-transform coordinates and then mapped into a spatial solution by inverse Fourier transform. For waves in a height-dependent background, the use of Fourier transform coordinates simplifies important parts of the ray calculation, including the ray
1. Introduction Ray solutions are often expressed in spatial coordinates. Some examples for mountain waves are given in Gjevik and Marthinsen (1978) , Hines (1988) , Shutts (1998) , and Broad (1999) . Ray solutions can also be expressed in Fourier-transform coordinates and then mapped into a spatial solution by inverse Fourier transform. For waves in a height-dependent background, the use of Fourier transform coordinates simplifies important parts of the ray calculation, including the ray
properties. In section 4 , different time integration schemes are compared. 2. Volume conservation under numerical discretizations For this analysis, the discretization process is understood as split into two parts, namely spatial (e.g., finite differences) and temporal (e.g., implicit midpoint, leapfrog) discretization. This carries a partial differential equation (PDE) over to an ordinary differential equation (ODE) and to an algebraic equation. a. Volume
properties. In section 4 , different time integration schemes are compared. 2. Volume conservation under numerical discretizations For this analysis, the discretization process is understood as split into two parts, namely spatial (e.g., finite differences) and temporal (e.g., implicit midpoint, leapfrog) discretization. This carries a partial differential equation (PDE) over to an ordinary differential equation (ODE) and to an algebraic equation. a. Volume
overestimation by the Edgeworth equation [ (26) ] of MI [ I ng(EF) ]. The map correlation between the two estimators is 0.98. By comparing the sorted values of I ng(ME) with the correspondent I ng(EI) values ( Fig. 5b ), we have an idea about the effect of Edgeworth truncation error in (23) . Their correlation is 0.76, while the correlation with I ng(EF) is expectedly lower: 0.69. By collecting all the 833 values, the I ng(EI) estimator exhibits a negative increasing bias in comparison with the
overestimation by the Edgeworth equation [ (26) ] of MI [ I ng(EF) ]. The map correlation between the two estimators is 0.98. By comparing the sorted values of I ng(ME) with the correspondent I ng(EI) values ( Fig. 5b ), we have an idea about the effect of Edgeworth truncation error in (23) . Their correlation is 0.76, while the correlation with I ng(EF) is expectedly lower: 0.69. By collecting all the 833 values, the I ng(EI) estimator exhibits a negative increasing bias in comparison with the
. Sea-level weather map; 1830 GCT 25 December 1950.JUNE 1953ERNEST M. RAMPEYFIG. 3. 850-mb chart; 1500 GCT 25 December 1950.culation at sea level, 850 and 700 mb, but not at500 mb. 500 mb.chosen for type I is 700 mb, while that for type I1 isThus, lows which appear on the sea-level map, butwhich are not closed at 850 mb, are not included.5. Type I : Evaluation of temperature advectionSimilarly, lows which are closed at 500 mb and higherhave been excluded from this investigation.As will be shown
. Sea-level weather map; 1830 GCT 25 December 1950.JUNE 1953ERNEST M. RAMPEYFIG. 3. 850-mb chart; 1500 GCT 25 December 1950.culation at sea level, 850 and 700 mb, but not at500 mb. 500 mb.chosen for type I is 700 mb, while that for type I1 isThus, lows which appear on the sea-level map, butwhich are not closed at 850 mb, are not included.5. Type I : Evaluation of temperature advectionSimilarly, lows which are closed at 500 mb and higherhave been excluded from this investigation.As will be shown
08 MONTHLY WEATHER REVIEW FEBRUARY, 1925to deterztline whether any particular phase of the temper- sture data is best adapted to indicate the degree of abnormality of the season. As a result of these trials itfas found that the order of magnitude of the abnsrmal-its W& practically the same whatever method wasused; hence in the interest of sim licity the method ofmonthly departures of December, January, and February be expressed by a+b+c, then the algebraic sum ofthese depmtures divided by 3
08 MONTHLY WEATHER REVIEW FEBRUARY, 1925to deterztline whether any particular phase of the temper- sture data is best adapted to indicate the degree of abnormality of the season. As a result of these trials itfas found that the order of magnitude of the abnsrmal-its W& practically the same whatever method wasused; hence in the interest of sim licity the method ofmonthly departures of December, January, and February be expressed by a+b+c, then the algebraic sum ofthese depmtures divided by 3
comparison of sea level rise estimates made from an ocean running with today’s climate with others made from transient fully coupled climate experiments in which the surface forcing is different. Maps of the spatial pattern of sea level rise can be made from the output of coupled GCMs using a simple inverse method. It is shown that the solution obtained using this inverse method is more accurate than the solution obtained by using a simpler technique for finding the spatial map of pressure at a certain
comparison of sea level rise estimates made from an ocean running with today’s climate with others made from transient fully coupled climate experiments in which the surface forcing is different. Maps of the spatial pattern of sea level rise can be made from the output of coupled GCMs using a simple inverse method. It is shown that the solution obtained using this inverse method is more accurate than the solution obtained by using a simpler technique for finding the spatial map of pressure at a certain
the vertical velocity in a hydrostatic model. We derive the elliptic equation for pressure from the second BDI dynamic constraint in Eq. (20) . To replace the time derivative terms, we substitute ∂ (1) /∂ x, ∂ (2) /∂ y, ∂ (21) /∂ z, and Eq. (21) into the constraint Eq. (20) . After algebra, we obtain the following second derivative equation for pressure where The variable ζ is the vorticity defined as ζ = υ x − u y , and β = ∂ f /∂ y. This equation is similar to the traditional
the vertical velocity in a hydrostatic model. We derive the elliptic equation for pressure from the second BDI dynamic constraint in Eq. (20) . To replace the time derivative terms, we substitute ∂ (1) /∂ x, ∂ (2) /∂ y, ∂ (21) /∂ z, and Eq. (21) into the constraint Eq. (20) . After algebra, we obtain the following second derivative equation for pressure where The variable ζ is the vorticity defined as ζ = υ x − u y , and β = ∂ f /∂ y. This equation is similar to the traditional
