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Abstract
The central question discussed here is how the rate at which drifter positions are determined and the position errors affect the calculation of velocity, acceleration and velocity gradients such as divergence and vorticity. The analysis shows that the mean-square velocity and acceleration errors each are composed of two terms. One arises from the position uncertainty and the discrete sampling rate. The other term is an alias resulting from sampling a continuous velocity or acceleration spectrum discretely. Effects at low and high frequencies and sampling intervals are examined by asymptotic expansions of the spectra. Then optimum smoothing and derivative filters are obtained for the velocity and accelerations, respectively. The efficiency of these filters is determined by comparison with the errors previously established.
The calculation of divergence and vorticity from drifter clusters typically neglects the position error, in which case the errors in the velocity gradients are proportional to the velocity errors. Our analysis shows that this procedure produces estimates of the velocity gradients whose magnitudes are less than the true values. This bias is easily removed. The analysis is concluded with a derivation of formulas for unbiased estimates of the variance and covariance of the velocity gradients.
Abstract
The central question discussed here is how the rate at which drifter positions are determined and the position errors affect the calculation of velocity, acceleration and velocity gradients such as divergence and vorticity. The analysis shows that the mean-square velocity and acceleration errors each are composed of two terms. One arises from the position uncertainty and the discrete sampling rate. The other term is an alias resulting from sampling a continuous velocity or acceleration spectrum discretely. Effects at low and high frequencies and sampling intervals are examined by asymptotic expansions of the spectra. Then optimum smoothing and derivative filters are obtained for the velocity and accelerations, respectively. The efficiency of these filters is determined by comparison with the errors previously established.
The calculation of divergence and vorticity from drifter clusters typically neglects the position error, in which case the errors in the velocity gradients are proportional to the velocity errors. Our analysis shows that this procedure produces estimates of the velocity gradients whose magnitudes are less than the true values. This bias is easily removed. The analysis is concluded with a derivation of formulas for unbiased estimates of the variance and covariance of the velocity gradients.
Abstract
The NASA Quick Scatterometer (QuikSCAT) has revolutionized the analysis and short-term forecasting of winds over the oceans at the NOAA Ocean Prediction Center (OPC). The success of QuikSCAT in OPC operations is due to the wide 1800-km swath width, large retrievable wind speed range (0 to in excess of 30 m s−1), ability to view QuikSCAT winds in a comprehensive form in operational workstations, and reliable near-real-time delivery of data. Prior to QuikSCAT, marine forecasters at the OPC made warning and forecast decisions over vast ocean areas based on a limited number of conventional observations or on the satellite presentation of a storm system. Today, QuikSCAT winds are a heavily used tool by OPC forecasters. Approximately 10% of all short-term wind warning decisions by the OPC are based on QuikSCAT winds. When QuikSCAT is available, 50%–68% of all weather features on OPC surface analyses are placed using QuikSCAT. QuikSCAT is the first remote sensing instrument that can consistently distinguish extreme hurricane force conditions from less dangerous storm force conditions in extratropical cyclones. During each winter season (October–April) from 2001 to 2004, 15–23 extratropical cyclones reached hurricane force intensity over both the North Atlantic and North Pacific Oceans. Due to QuikSCAT, OPC forecasters are now more likely to anticipate the onset of hurricane force conditions. QuikSCAT has also revealed significant wind speed gradients in the vicinity of strong sea surface temperature (SST) differences near the Gulf Stream and shelfbreak front of the western North Atlantic. These wind speed gradients are most likely due to changes in low-level stability of the boundary layer across the SST gradients. OPC forecasters now use a variety of numerical guidance based tools to help predict boundary layer stability and the resultant near-surface winds.
Abstract
The NASA Quick Scatterometer (QuikSCAT) has revolutionized the analysis and short-term forecasting of winds over the oceans at the NOAA Ocean Prediction Center (OPC). The success of QuikSCAT in OPC operations is due to the wide 1800-km swath width, large retrievable wind speed range (0 to in excess of 30 m s−1), ability to view QuikSCAT winds in a comprehensive form in operational workstations, and reliable near-real-time delivery of data. Prior to QuikSCAT, marine forecasters at the OPC made warning and forecast decisions over vast ocean areas based on a limited number of conventional observations or on the satellite presentation of a storm system. Today, QuikSCAT winds are a heavily used tool by OPC forecasters. Approximately 10% of all short-term wind warning decisions by the OPC are based on QuikSCAT winds. When QuikSCAT is available, 50%–68% of all weather features on OPC surface analyses are placed using QuikSCAT. QuikSCAT is the first remote sensing instrument that can consistently distinguish extreme hurricane force conditions from less dangerous storm force conditions in extratropical cyclones. During each winter season (October–April) from 2001 to 2004, 15–23 extratropical cyclones reached hurricane force intensity over both the North Atlantic and North Pacific Oceans. Due to QuikSCAT, OPC forecasters are now more likely to anticipate the onset of hurricane force conditions. QuikSCAT has also revealed significant wind speed gradients in the vicinity of strong sea surface temperature (SST) differences near the Gulf Stream and shelfbreak front of the western North Atlantic. These wind speed gradients are most likely due to changes in low-level stability of the boundary layer across the SST gradients. OPC forecasters now use a variety of numerical guidance based tools to help predict boundary layer stability and the resultant near-surface winds.
Abstract
Data collected by the National Center for Atmospheric Research S-band polarimetric radar (S-Pol) during the Terrain-Influenced Monsoon Rainfall Experiment (TiMREX) in Taiwan are analyzed and used to infer storm microphysics in the ice phase of convective storms. Both simultaneous horizontal (H) and vertical (V) (SHV) transmit polarization data and fast-alternating H and V (FHV) transmit polarization data are used in the analysis. The SHV Z
dr (differential reflectivity) data show radial stripes of biased data in the ice phase that are likely caused by aligned and canted ice crystals. Similar radial streaks in the linear depolarization ratio (LDR) are presented that are also biased by the same mechanism. Dual-Doppler synthesis and sounding data characterize the storm environment and support the inferences concerning the ice particle types. Small convective cells were observed to have both large positive and large negative K
dp (specific differential phase) values. Negative K
dp regions suggest that ice crystals are vertically aligned by electric fields. Since high |K
dp| values of 0.8° km−1 in both negative and positive K
dp regions in the ice phase are accompanied by Z
dr values close to 0 dB, it is inferred that there are two types of ice crystals present: 1) smaller aligned ice crystals that cause the K
dp signatures and 2) larger aggregates or graupel that cause the Z
dr signatures. The inferences are supported with simulated ice particle scattering calculations. A radar scattering model is used to explain the anomalous radial streaks in SHV 
Abstract
Data collected by the National Center for Atmospheric Research S-band polarimetric radar (S-Pol) during the Terrain-Influenced Monsoon Rainfall Experiment (TiMREX) in Taiwan are analyzed and used to infer storm microphysics in the ice phase of convective storms. Both simultaneous horizontal (H) and vertical (V) (SHV) transmit polarization data and fast-alternating H and V (FHV) transmit polarization data are used in the analysis. The SHV Z
dr (differential reflectivity) data show radial stripes of biased data in the ice phase that are likely caused by aligned and canted ice crystals. Similar radial streaks in the linear depolarization ratio (LDR) are presented that are also biased by the same mechanism. Dual-Doppler synthesis and sounding data characterize the storm environment and support the inferences concerning the ice particle types. Small convective cells were observed to have both large positive and large negative K
dp (specific differential phase) values. Negative K
dp regions suggest that ice crystals are vertically aligned by electric fields. Since high |K
dp| values of 0.8° km−1 in both negative and positive K
dp regions in the ice phase are accompanied by Z
dr values close to 0 dB, it is inferred that there are two types of ice crystals present: 1) smaller aligned ice crystals that cause the K
dp signatures and 2) larger aggregates or graupel that cause the Z
dr signatures. The inferences are supported with simulated ice particle scattering calculations. A radar scattering model is used to explain the anomalous radial streaks in SHV
Abstract
An updated complete and comprehensive description of the land surface parameterization scheme in the Coupled Atmosphere–Plant–Soil (CAPS) model is presented. The CAPS model has been in development at Oregon State University and Phillips Laboratory since 1981. The CAPS model was originally designed for a global atmospheric model, but it has also been used as a stand-alone model for a variety of applications. The land surface scheme in the CAPS model is one of the two dozen schemes that participated in the Project for Intercomparison of Land Surface Parameterization Schemes (PILPS). Some unique features of the CAPS scheme are given in detail. A comprehensive dataset of one year (1987), including atmospheric forcing data and validation data from Cabauw, has been provided for PILPS by the Royal Netherlands Meteorological Institute. Using the Cabauw data, a validation study for the CAPS scheme has been carried out. The scheme’s self-consistencies in terms of surface energy balance and water budget are discussed. Finally, the results of this validation study with emphasis on the performance of surface momentum and heat fluxes are presented.
Abstract
An updated complete and comprehensive description of the land surface parameterization scheme in the Coupled Atmosphere–Plant–Soil (CAPS) model is presented. The CAPS model has been in development at Oregon State University and Phillips Laboratory since 1981. The CAPS model was originally designed for a global atmospheric model, but it has also been used as a stand-alone model for a variety of applications. The land surface scheme in the CAPS model is one of the two dozen schemes that participated in the Project for Intercomparison of Land Surface Parameterization Schemes (PILPS). Some unique features of the CAPS scheme are given in detail. A comprehensive dataset of one year (1987), including atmospheric forcing data and validation data from Cabauw, has been provided for PILPS by the Royal Netherlands Meteorological Institute. Using the Cabauw data, a validation study for the CAPS scheme has been carried out. The scheme’s self-consistencies in terms of surface energy balance and water budget are discussed. Finally, the results of this validation study with emphasis on the performance of surface momentum and heat fluxes are presented.
Abstract
The problem analysed here is the motion of a drifter acted on by wind, surface and subsurface currents. From the condition of static equilibrium of all drag forces acting on the drifter, the effects of wind and surface current of arbitrary direction and magnitude and drogue characteristics are examined parametrically. Specific application is made to a recently developed drifter with 9.2 and 11.85 m parachute drogues and a window shade drogue. The calculations show that for some environmental conditions the deviation between the magnitudes of the drifter velocity and the water parcel velocity may exceed 500%. Furthermore, the direction of velocity vectors may differ by as much as 45°. Drifter data from an experiment conducted by the Atlantic Oceanographic and Meteorological Laboratories and the NOAA Data Buoy Office in the Gulf of Mexico Loop Current are examined in light of the theoretical results. The wind effects predicted by the theory were observed in the field. Thus wind corrections to the drifter velocity records which are based on the theory can significantly improve the velocity records.
Abstract
The problem analysed here is the motion of a drifter acted on by wind, surface and subsurface currents. From the condition of static equilibrium of all drag forces acting on the drifter, the effects of wind and surface current of arbitrary direction and magnitude and drogue characteristics are examined parametrically. Specific application is made to a recently developed drifter with 9.2 and 11.85 m parachute drogues and a window shade drogue. The calculations show that for some environmental conditions the deviation between the magnitudes of the drifter velocity and the water parcel velocity may exceed 500%. Furthermore, the direction of velocity vectors may differ by as much as 45°. Drifter data from an experiment conducted by the Atlantic Oceanographic and Meteorological Laboratories and the NOAA Data Buoy Office in the Gulf of Mexico Loop Current are examined in light of the theoretical results. The wind effects predicted by the theory were observed in the field. Thus wind corrections to the drifter velocity records which are based on the theory can significantly improve the velocity records.
Abstract
The outflow of warm, salty, and dense water from the Red Sea into the western Gulf of Aden is numerically simulated using the Hybrid Coordinate Ocean Model (HYCOM). The pathways of the modeled overflow, temperature, salinity, velocity profiles from stations and across sections, and transport estimates are compared to those observed during the 2001 Red Sea Outflow Experiment. As in nature, the simulated outflow is funneled into two narrow channels along the seafloor. The results from the three-dimensional simulations show a favorable agreement with the observed temperature and salinity profiles along the channels. The volume transport of the modeled overflow increases with the increasing distance from the southern exit of the Bab el Mandeb Strait due to entrainment of ambient fluid, such that the modeled transport shows a reasonable agreement with that estimated from the observations. The initial propagation speed of the outflow is found to be smaller than the estimated interfacial wave speed. The slow propagation is shown to result from the roughness of the bottom topography characterized by a number of depressions that take time to be filled with outflow water. Sensitivities of the results to the horizontal grid spacing, different entrainment parameterizations, and forcing at the source location are investigated. Because of the narrow widths of the approximately 5 km of the outflow channels, a horizontal grid spacing of 1 km or less is required for model simulations to achieve a reasonable agreement with the observations. Comparison of two entrainment parameterizations, namely, TPX and K-profile parameterization (KPP), show that similar results are obtained at 1-km resolution. Overall, the simulation of the Red Sea outflow appears to be more strongly affected by the details of bottom topography and grid spacing needed to adequately resolve them than by parameterizations of diapycnal mixing.
Abstract
The outflow of warm, salty, and dense water from the Red Sea into the western Gulf of Aden is numerically simulated using the Hybrid Coordinate Ocean Model (HYCOM). The pathways of the modeled overflow, temperature, salinity, velocity profiles from stations and across sections, and transport estimates are compared to those observed during the 2001 Red Sea Outflow Experiment. As in nature, the simulated outflow is funneled into two narrow channels along the seafloor. The results from the three-dimensional simulations show a favorable agreement with the observed temperature and salinity profiles along the channels. The volume transport of the modeled overflow increases with the increasing distance from the southern exit of the Bab el Mandeb Strait due to entrainment of ambient fluid, such that the modeled transport shows a reasonable agreement with that estimated from the observations. The initial propagation speed of the outflow is found to be smaller than the estimated interfacial wave speed. The slow propagation is shown to result from the roughness of the bottom topography characterized by a number of depressions that take time to be filled with outflow water. Sensitivities of the results to the horizontal grid spacing, different entrainment parameterizations, and forcing at the source location are investigated. Because of the narrow widths of the approximately 5 km of the outflow channels, a horizontal grid spacing of 1 km or less is required for model simulations to achieve a reasonable agreement with the observations. Comparison of two entrainment parameterizations, namely, TPX and K-profile parameterization (KPP), show that similar results are obtained at 1-km resolution. Overall, the simulation of the Red Sea outflow appears to be more strongly affected by the details of bottom topography and grid spacing needed to adequately resolve them than by parameterizations of diapycnal mixing.
Abstract
We outline a framework for identifying the geographical sources of biases in climate models. By forcing the model with time-averaged short-term analysis increments [tendency bias corrections (TBCs)] over well-defined regions, we can quantify how the associated reduced tendency errors in these regions manifest themselves both locally and remotely through large-scale teleconnections. Companion experiments in which the model is fully corrected [constrained to remain close to the analysis at each time step, termed replay (RPL)] in the various regions provide an upper bound to the local and remote TBC impacts. An example is given based on MERRA-2 and the NASA/GMAO GEOS AGCM used to generate MERRA-2. The results highlight the ability of the approach to isolate the geographical sources of some of the long-standing boreal summer biases of the GEOS model, including a stunted North Pacific summer jet, a dry bias in the U.S. Great Plains, and a warm bias over most of the Northern Hemisphere land. In particular, we show that the TBC over a region that encompasses Tibet has by far the largest impact (compared with all other regions) on the NH summer jets and related variables, leading to significant improvements in the simulation of North American temperature and, to a lesser degree, precipitation. It is further shown that the results of the regional TBC experiments are for the most part linear in the summer hemisphere, allowing a robust interpretation of the results.
Abstract
We outline a framework for identifying the geographical sources of biases in climate models. By forcing the model with time-averaged short-term analysis increments [tendency bias corrections (TBCs)] over well-defined regions, we can quantify how the associated reduced tendency errors in these regions manifest themselves both locally and remotely through large-scale teleconnections. Companion experiments in which the model is fully corrected [constrained to remain close to the analysis at each time step, termed replay (RPL)] in the various regions provide an upper bound to the local and remote TBC impacts. An example is given based on MERRA-2 and the NASA/GMAO GEOS AGCM used to generate MERRA-2. The results highlight the ability of the approach to isolate the geographical sources of some of the long-standing boreal summer biases of the GEOS model, including a stunted North Pacific summer jet, a dry bias in the U.S. Great Plains, and a warm bias over most of the Northern Hemisphere land. In particular, we show that the TBC over a region that encompasses Tibet has by far the largest impact (compared with all other regions) on the NH summer jets and related variables, leading to significant improvements in the simulation of North American temperature and, to a lesser degree, precipitation. It is further shown that the results of the regional TBC experiments are for the most part linear in the summer hemisphere, allowing a robust interpretation of the results.
Abstract
We revisit the bias correction problem in current climate models, taking advantage of state-of-the-art atmospheric reanalysis data and new data assimilation tools that simplify the estimation of short-term (6 hourly) atmospheric tendency errors. The focus is on the extent to which correcting biases in atmospheric tendencies improves the model’s climatology, variability, and ultimately forecast skill at subseasonal and seasonal time scales. Results are presented for the NASA GMAO GEOS model in both uncoupled (atmosphere only) and coupled (atmosphere–ocean) modes. For the uncoupled model, the focus is on correcting a stunted North Pacific jet and a dry bias over the central United States during boreal summer—long-standing errors that are indeed common to many current AGCMs. The results show that the tendency bias correction (TBC) eliminates the jet bias and substantially increases the precipitation over the Great Plains. These changes are accompanied by much improved (increased) storm-track activity throughout the northern midlatitudes. For the coupled model, the atmospheric TBCs produce substantial improvements in the simulated mean climate and its variability, including a much reduced SST warm bias, more realistic ENSO-related SST variability and teleconnections, and much improved subtropical jets and related submonthly transient wave activity. Despite these improvements, the improvement in subseasonal and seasonal forecast skill over North America is only modest at best. The reasons for this, which are presumably relevant to any forecast system, involve the competing influences of predictability loss with time and the time it takes for climate drift to first have a significant impact on forecast skill.
Abstract
We revisit the bias correction problem in current climate models, taking advantage of state-of-the-art atmospheric reanalysis data and new data assimilation tools that simplify the estimation of short-term (6 hourly) atmospheric tendency errors. The focus is on the extent to which correcting biases in atmospheric tendencies improves the model’s climatology, variability, and ultimately forecast skill at subseasonal and seasonal time scales. Results are presented for the NASA GMAO GEOS model in both uncoupled (atmosphere only) and coupled (atmosphere–ocean) modes. For the uncoupled model, the focus is on correcting a stunted North Pacific jet and a dry bias over the central United States during boreal summer—long-standing errors that are indeed common to many current AGCMs. The results show that the tendency bias correction (TBC) eliminates the jet bias and substantially increases the precipitation over the Great Plains. These changes are accompanied by much improved (increased) storm-track activity throughout the northern midlatitudes. For the coupled model, the atmospheric TBCs produce substantial improvements in the simulated mean climate and its variability, including a much reduced SST warm bias, more realistic ENSO-related SST variability and teleconnections, and much improved subtropical jets and related submonthly transient wave activity. Despite these improvements, the improvement in subseasonal and seasonal forecast skill over North America is only modest at best. The reasons for this, which are presumably relevant to any forecast system, involve the competing influences of predictability loss with time and the time it takes for climate drift to first have a significant impact on forecast skill.
Abstract
In this paper, experimental X-band polarimetric radar data from simultaneous transmission of horizontal (H) and vertical (V) polarizations (SHV) are shown, modeled, and microphysically interpreted. Both range–height indicator data and vertical-pointing X-band data from the Taiwan Experimental Atmospheric Mobile-Radar (TEAM-R) are presented. Some of the given X-band data are biased, which is very likely caused by cross coupling of the H and V transmitted waves as a result of aligned, canted ice crystals. Modeled SHV data are used to explain the observed polarimetric signatures. Coincident data from the National Center for Atmospheric Research S-band polarimetric radar (S-Pol) are presented to augment and support the X-band polarimetric observations and interpretations. The polarimetric S-Pol data are obtained via fast-alternating transmission of horizontal and vertical polarizations (FHV), and thus the S-band data are not contaminated by the cross coupling (except the linear depolarization ratio LDR) observed in the X-band data. The radar data reveal that there are regions in the ice phase where electric fields are apparently aligning ice crystals near vertically and thus causing negative specific differential phase K dp. The vertical-pointing data also indicate the presence of preferentially aligned ice crystals that cause differential reflectivity Z dr and differential phase ϕ dp to be strong functions of azimuth angle.
Abstract
In this paper, experimental X-band polarimetric radar data from simultaneous transmission of horizontal (H) and vertical (V) polarizations (SHV) are shown, modeled, and microphysically interpreted. Both range–height indicator data and vertical-pointing X-band data from the Taiwan Experimental Atmospheric Mobile-Radar (TEAM-R) are presented. Some of the given X-band data are biased, which is very likely caused by cross coupling of the H and V transmitted waves as a result of aligned, canted ice crystals. Modeled SHV data are used to explain the observed polarimetric signatures. Coincident data from the National Center for Atmospheric Research S-band polarimetric radar (S-Pol) are presented to augment and support the X-band polarimetric observations and interpretations. The polarimetric S-Pol data are obtained via fast-alternating transmission of horizontal and vertical polarizations (FHV), and thus the S-band data are not contaminated by the cross coupling (except the linear depolarization ratio LDR) observed in the X-band data. The radar data reveal that there are regions in the ice phase where electric fields are apparently aligning ice crystals near vertically and thus causing negative specific differential phase K dp. The vertical-pointing data also indicate the presence of preferentially aligned ice crystals that cause differential reflectivity Z dr and differential phase ϕ dp to be strong functions of azimuth angle.
Abstract
In winter, a branch of the China Coastal Current can turn in the Taiwan Strait to join the poleward-flowing Taiwan Coastal Current. The associated cross-strait flows have been inferred from hydrographic and satellite data, from observed abundances off northwestern Taiwan of cold-water copepod species Calanus sinicus and, in late March of 2012, also from debris found along the northwestern shore of Taiwan of a ship that broke two weeks earlier off the coast of China. The dynamics related to such cross flows have not been previously explained and are the focus of this study using analytical and numerical models. It is shown that the strait’s currents can be classified into three regimes depending on the strength of the winter monsoon: equatorward (poleward) for northeasterly winds stronger (weaker) than an upper (lower) bound and cross-strait flows for relaxing northeasterly winds between the two bounds. These regimes are related to the formation of the stationary Rossby wave over the Changyun Ridge off midwestern Taiwan. In the weak (strong) northeasterly wind regime, a weak (no) wave is produced. In the relaxing wind regime, cross-strait currents are triggered by an imbalance between the pressure gradient and wind and are amplified by the finite-amplitude meander downstream of the ridge where a strong cyclone develops.
Abstract
In winter, a branch of the China Coastal Current can turn in the Taiwan Strait to join the poleward-flowing Taiwan Coastal Current. The associated cross-strait flows have been inferred from hydrographic and satellite data, from observed abundances off northwestern Taiwan of cold-water copepod species Calanus sinicus and, in late March of 2012, also from debris found along the northwestern shore of Taiwan of a ship that broke two weeks earlier off the coast of China. The dynamics related to such cross flows have not been previously explained and are the focus of this study using analytical and numerical models. It is shown that the strait’s currents can be classified into three regimes depending on the strength of the winter monsoon: equatorward (poleward) for northeasterly winds stronger (weaker) than an upper (lower) bound and cross-strait flows for relaxing northeasterly winds between the two bounds. These regimes are related to the formation of the stationary Rossby wave over the Changyun Ridge off midwestern Taiwan. In the weak (strong) northeasterly wind regime, a weak (no) wave is produced. In the relaxing wind regime, cross-strait currents are triggered by an imbalance between the pressure gradient and wind and are amplified by the finite-amplitude meander downstream of the ridge where a strong cyclone develops.
