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a range of longitudes, which in turn could lead to the formation of the westerly duct even during the Northern Hemisphere summer months. Utilizing ECMWF analysis data, Magaña and Yanai (1995) documented how a midlatitude Rossby wave train can penetrate deeply into the tropics and project onto YM waves, especially in the western Hemisphere within a sufficiently wide equatorial westerly duct or even when the mean easterlies are weak (~2 m s −1 ) ( Fig. 3-11 ). Fig . 3-11. Linear regression
a range of longitudes, which in turn could lead to the formation of the westerly duct even during the Northern Hemisphere summer months. Utilizing ECMWF analysis data, Magaña and Yanai (1995) documented how a midlatitude Rossby wave train can penetrate deeply into the tropics and project onto YM waves, especially in the western Hemisphere within a sufficiently wide equatorial westerly duct or even when the mean easterlies are weak (~2 m s −1 ) ( Fig. 3-11 ). Fig . 3-11. Linear regression
. A key conclusion from the analysis of longwave ICRCCM results ( Ellingson et al. 1991 ) was that, although many fast radiation codes used within climate models had spectral errors that partially canceled out when fluxes over a wide spectral range were computed, line-by-line modelers did not have sufficient confidence in their own models to advocate using them as references. The participants in this study therefore recommended that “a program be organized to simultaneously measure the spectral
. A key conclusion from the analysis of longwave ICRCCM results ( Ellingson et al. 1991 ) was that, although many fast radiation codes used within climate models had spectral errors that partially canceled out when fluxes over a wide spectral range were computed, line-by-line modelers did not have sufficient confidence in their own models to advocate using them as references. The participants in this study therefore recommended that “a program be organized to simultaneously measure the spectral
insights through clustering and nonlinear analysis. This section looks to the future, but it also reverts to the past when science relied more on finding patterns in nature. Concluding thoughts and consideration of some prospects for the future appear in section 6 . This chapter is the final one of a three-part series on applied meteorology. In the first chapter, we considered some of the most basic and first-addressed application areas: weather modification, aviation applications, and security
insights through clustering and nonlinear analysis. This section looks to the future, but it also reverts to the past when science relied more on finding patterns in nature. Concluding thoughts and consideration of some prospects for the future appear in section 6 . This chapter is the final one of a three-part series on applied meteorology. In the first chapter, we considered some of the most basic and first-addressed application areas: weather modification, aviation applications, and security
horizontal eddy heat flux divergence, respectively. The horizontal divergence term is neglected when Eq. (2-2) is spatially averaged over an area suitable for diagnostic analysis. Figure 2-1 shows CRM-simulated time-domain mean profiles of heating/cooling due to the individual microphysical processes (i.e., condensation, evaporation, deposition, sublimation, melting, and freezing) in the convective and stratiform regions of a tropical MCS using the Goddard Cumulus Ensemble model (GCE; Tao and Simpson
horizontal eddy heat flux divergence, respectively. The horizontal divergence term is neglected when Eq. (2-2) is spatially averaged over an area suitable for diagnostic analysis. Figure 2-1 shows CRM-simulated time-domain mean profiles of heating/cooling due to the individual microphysical processes (i.e., condensation, evaporation, deposition, sublimation, melting, and freezing) in the convective and stratiform regions of a tropical MCS using the Goddard Cumulus Ensemble model (GCE; Tao and Simpson
wind vector. Precipitation data are from the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) 1979–2017 ( Xie and Arkin 1997a ), SST data are from Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) 1870–2017 ( Rayner et al. 2003 ), and wind data are from European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) 1979–2017 ( Dee et al. 2011 ). Fig . 8-2. Seasonal cycle along the equator (2°S–2°N) in (top) SST (contour interval
wind vector. Precipitation data are from the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) 1979–2017 ( Xie and Arkin 1997a ), SST data are from Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) 1870–2017 ( Rayner et al. 2003 ), and wind data are from European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) 1979–2017 ( Dee et al. 2011 ). Fig . 8-2. Seasonal cycle along the equator (2°S–2°N) in (top) SST (contour interval
regional as well as global climate. Some of the results are summarized in this study, and can be considered as a complement to the review of Yanai and Wu (2006) . Both the diagnosis and numerical experiments are used to get new insights into our understanding. The remainder of this chapter is organized as follows. In section 2 , there is an analysis of the relative importance of mechanical and thermal forcing induced by large-scale mountains. The diabatic heating characteristics of atmosphere over TP
regional as well as global climate. Some of the results are summarized in this study, and can be considered as a complement to the review of Yanai and Wu (2006) . Both the diagnosis and numerical experiments are used to get new insights into our understanding. The remainder of this chapter is organized as follows. In section 2 , there is an analysis of the relative importance of mechanical and thermal forcing induced by large-scale mountains. The diabatic heating characteristics of atmosphere over TP
. While many of the fundamental instruments and analytical techniques predate the ARM Program, the program has contributed to significant advances along a number of pathways in instrument development and data analysis. a. Passive sensor systems Passive microwave measurements have long been used to derive properties of the atmosphere. Through its emphasis on long-term operational measurements, the ARM Program has contributed to specific advances in ensuring robust, automated calibration for these
. While many of the fundamental instruments and analytical techniques predate the ARM Program, the program has contributed to significant advances along a number of pathways in instrument development and data analysis. a. Passive sensor systems Passive microwave measurements have long been used to derive properties of the atmosphere. Through its emphasis on long-term operational measurements, the ARM Program has contributed to specific advances in ensuring robust, automated calibration for these
climate on extreme weather from Northern Hemisphere extratropical cyclones . Tellus , 63A , 893 – 906 , https://doi.org/10.1111/j.1600-0870.2011.00538.x . Chang , E. K. M. , 1993 : Downstream development of baroclinic waves as inferred from regression analysis . J. Atmos. Sci. , 50 , 2038 – 2053 , https://doi.org/10.1175/1520-0469(1993)050<2038:DDOBWA>2.0.CO;2 . Chang , E. K. M. , 2001 : The structure of baroclinic wave packets . J. Atmos. Sci. , 58 , 1694 – 1713 , https://doi.org/10
climate on extreme weather from Northern Hemisphere extratropical cyclones . Tellus , 63A , 893 – 906 , https://doi.org/10.1111/j.1600-0870.2011.00538.x . Chang , E. K. M. , 1993 : Downstream development of baroclinic waves as inferred from regression analysis . J. Atmos. Sci. , 50 , 2038 – 2053 , https://doi.org/10.1175/1520-0469(1993)050<2038:DDOBWA>2.0.CO;2 . Chang , E. K. M. , 2001 : The structure of baroclinic wave packets . J. Atmos. Sci. , 58 , 1694 – 1713 , https://doi.org/10
-emitted radiation. Raschke et al. (1973) used Nimbus-3 observations to estimate Earth’s annual global radiation budget, including planetary albedo, absorbed solar radiation, and infrared radiation loss to space at global, hemispheric, and zonal averages. They also presented global maps at a spatial resolution near synoptic scale. An analysis of data collected by the scanning bolometers aboard the Nimbus- 3 satellite in 1969 revealed that Earth’s planetary emitting temperature was approximately 254 K and it
-emitted radiation. Raschke et al. (1973) used Nimbus-3 observations to estimate Earth’s annual global radiation budget, including planetary albedo, absorbed solar radiation, and infrared radiation loss to space at global, hemispheric, and zonal averages. They also presented global maps at a spatial resolution near synoptic scale. An analysis of data collected by the scanning bolometers aboard the Nimbus- 3 satellite in 1969 revealed that Earth’s planetary emitting temperature was approximately 254 K and it
publications, ARM mounted a campaign called the ARM Enhanced Shortwave Experiment (ARESE; Valero et al. 1997a ) to measure radiation above and below clouds from aircraft flying in tandem and then to compare those measurements with radiation measurements when there were no clouds. The experiment, which was conducted in the fall of 1995, was marked by exceptionally clear weather; therefore, the analysis relied heavily on a single overcast day to estimate absorption in the clouds. Analyzing those data
publications, ARM mounted a campaign called the ARM Enhanced Shortwave Experiment (ARESE; Valero et al. 1997a ) to measure radiation above and below clouds from aircraft flying in tandem and then to compare those measurements with radiation measurements when there were no clouds. The experiment, which was conducted in the fall of 1995, was marked by exceptionally clear weather; therefore, the analysis relied heavily on a single overcast day to estimate absorption in the clouds. Analyzing those data
