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Abstract
A computationally simple cross-correlation model for multiple backscattering from a continuous wave (CW) noise radar is developed and verified with theoretical analysis and brute-force time-domain simulations. Based on this cross-correlation model, a modification of an existing numerical method originally developed by Holdsworth and Reid for spaced antenna (SA) pulsed radar is used to simulate the estimated cross correlation corresponding to atmospheric backscattering using a coherent CW noise radar. Subsequently, coherent radar imaging (CRI) processing comparisons between the CW noise radar and a conventional pulsed radar are presented that verify the potential of CW noise radar for atmospheric imaging.
Abstract
A computationally simple cross-correlation model for multiple backscattering from a continuous wave (CW) noise radar is developed and verified with theoretical analysis and brute-force time-domain simulations. Based on this cross-correlation model, a modification of an existing numerical method originally developed by Holdsworth and Reid for spaced antenna (SA) pulsed radar is used to simulate the estimated cross correlation corresponding to atmospheric backscattering using a coherent CW noise radar. Subsequently, coherent radar imaging (CRI) processing comparisons between the CW noise radar and a conventional pulsed radar are presented that verify the potential of CW noise radar for atmospheric imaging.
Abstract
This paper highlights recent results obtained with the Turbulent Eddy Profiler (TEP), which was developed by the University of Massachusetts. This unique 915-MHz radar has up to 64 spatially separated receiving elements, each with an independent receiver. The calibrated raw data provided by this array could be processed using sophisticated imaging algorithms to resolve the horizontal structures within each range gate. After collecting all of the closely spaced horizontal slices, the TEP radar can produce three-dimensional images of echo power, radial velocity, and spectral width. From the radial velocity measurements, it is possible to estimate the three-dimensional wind with high horizontal and vertical resolution. Given the flexibility of the TEP system, various array configurations are possible. In the present work exploitation of the flexibility of TEP is attempted to enhance the rejection of clutter from unwanted biological targets. From statistical studies, most biological clutter results from targets outside the main imaging field of view, that is, the sidelobes and grating lobes (if they exist) of the receiving beam. Because the TEP array's minimum receiver separation exceeds the spatial Nyquist sampling requirement, substantial possibilities for grating-lobe clutter exist and are observed in actual array data. When imaging over the transmit beam volume, the receiving array main lobe is scanned over a ±12.5° region. This scanning also sweeps the grating lobes over a wide angular region, virtually guaranteeing that a biological scatterer outside of the main beam will appear somewhere in the imaged volume. This paper focuses on suppressing pointlike targets in the grating-lobe regions. With a subtle change to the standard TEP array hardware configuration, it is shown via simulations and actual experimental observations (collected in June 2003) that adaptive beamforming methods can subsequently be used to significantly suppress the effects of point targets on the wind field estimates. These pointlike targets can be birds or planes with strong reflectivity. By pointlike the authors mean its appearance is a distinct point (up to the imaging resolution) in the images. The pointlike strong reflectivity signature exploits the capability of adaptive beamforming to suppress the interference using the new array configuration. It should be noted that this same array configuration does not exhibit this beneficial effect when standard Fourier beamforming is employed.
Abstract
This paper highlights recent results obtained with the Turbulent Eddy Profiler (TEP), which was developed by the University of Massachusetts. This unique 915-MHz radar has up to 64 spatially separated receiving elements, each with an independent receiver. The calibrated raw data provided by this array could be processed using sophisticated imaging algorithms to resolve the horizontal structures within each range gate. After collecting all of the closely spaced horizontal slices, the TEP radar can produce three-dimensional images of echo power, radial velocity, and spectral width. From the radial velocity measurements, it is possible to estimate the three-dimensional wind with high horizontal and vertical resolution. Given the flexibility of the TEP system, various array configurations are possible. In the present work exploitation of the flexibility of TEP is attempted to enhance the rejection of clutter from unwanted biological targets. From statistical studies, most biological clutter results from targets outside the main imaging field of view, that is, the sidelobes and grating lobes (if they exist) of the receiving beam. Because the TEP array's minimum receiver separation exceeds the spatial Nyquist sampling requirement, substantial possibilities for grating-lobe clutter exist and are observed in actual array data. When imaging over the transmit beam volume, the receiving array main lobe is scanned over a ±12.5° region. This scanning also sweeps the grating lobes over a wide angular region, virtually guaranteeing that a biological scatterer outside of the main beam will appear somewhere in the imaged volume. This paper focuses on suppressing pointlike targets in the grating-lobe regions. With a subtle change to the standard TEP array hardware configuration, it is shown via simulations and actual experimental observations (collected in June 2003) that adaptive beamforming methods can subsequently be used to significantly suppress the effects of point targets on the wind field estimates. These pointlike targets can be birds or planes with strong reflectivity. By pointlike the authors mean its appearance is a distinct point (up to the imaging resolution) in the images. The pointlike strong reflectivity signature exploits the capability of adaptive beamforming to suppress the interference using the new array configuration. It should be noted that this same array configuration does not exhibit this beneficial effect when standard Fourier beamforming is employed.
Abstract
This study investigates the use of tornadic debris signature (TDS) parameters to estimate tornado damage severity using Norman, Oklahoma (KOUN), polarimetric radar data (polarimetric version of the Weather Surveillance Radar-1988 Doppler radar). Several TDS parameters are examined, including parameters based on the 10th or 90th percentiles of polarimetric variables (lowest tilt TDS parameters) and TDS parameters based on the TDS volumetric coverage (spatial TDS parameters). Two highly detailed National Weather Service (NWS) damage surveys are compared to TDS parameters. The TDS parameters tend to be correlated with the enhanced Fujita scale (EF) rating. The 90th percentile reflectivity, TDS height, and TDS volume increase during tornado intensification and decrease during tornado dissipation. For 14 tornado cases, the maximum or minimum TDS parameter values are compared to the tornado’s EF rating. For tornadoes with a higher EF rating, higher maximum values of the 90th percentile Z HH, TDS height, and volume, as well as lower minimum values of 10th percentile ρ HV and Z DR, are observed. Maxima in spatial TDS parameters are observed after periods of severe, widespread tornado damage for violent tornadoes. This paper discusses how forecasters could use TDS parameters to obtain near-real-time information about tornado damage severity and spatial extent.
Abstract
This study investigates the use of tornadic debris signature (TDS) parameters to estimate tornado damage severity using Norman, Oklahoma (KOUN), polarimetric radar data (polarimetric version of the Weather Surveillance Radar-1988 Doppler radar). Several TDS parameters are examined, including parameters based on the 10th or 90th percentiles of polarimetric variables (lowest tilt TDS parameters) and TDS parameters based on the TDS volumetric coverage (spatial TDS parameters). Two highly detailed National Weather Service (NWS) damage surveys are compared to TDS parameters. The TDS parameters tend to be correlated with the enhanced Fujita scale (EF) rating. The 90th percentile reflectivity, TDS height, and TDS volume increase during tornado intensification and decrease during tornado dissipation. For 14 tornado cases, the maximum or minimum TDS parameter values are compared to the tornado’s EF rating. For tornadoes with a higher EF rating, higher maximum values of the 90th percentile Z HH, TDS height, and volume, as well as lower minimum values of 10th percentile ρ HV and Z DR, are observed. Maxima in spatial TDS parameters are observed after periods of severe, widespread tornado damage for violent tornadoes. This paper discusses how forecasters could use TDS parameters to obtain near-real-time information about tornado damage severity and spatial extent.
Abstract
We present a method for deriving horizontal velocities, vertical velocities, and in-beam incidence angles from radar interferometer data. All parameters are calculated from the slope and intercept of straight lines fitted in a least-squares sense to the variation of the signal phase as a function of radial velocity for each pair of receiving antennas. Advantages of the method are that the calculations are computationally fast and simple, and the analysis leads to relatively simple expressions for the uncertainty in the velocity measurements.
Abstract
We present a method for deriving horizontal velocities, vertical velocities, and in-beam incidence angles from radar interferometer data. All parameters are calculated from the slope and intercept of straight lines fitted in a least-squares sense to the variation of the signal phase as a function of radial velocity for each pair of receiving antennas. Advantages of the method are that the calculations are computationally fast and simple, and the analysis leads to relatively simple expressions for the uncertainty in the velocity measurements.
Abstract
In this work, the accuracy of the Doppler beam-swinging (DBS) technique for wind measurements is studied using an imaging radar—the turbulent eddy profiler (TEP) developed by the University of Massachusetts, with data collected in summer 2003. With up to 64 independent receivers, and using coherent radar imaging (CRI), several hundred partially independent beams can be formed simultaneously within the volume defined by the transmit beam. By selecting a subset of these beams, an unprecedented number of DBS configurations with varying zenith angle, azimuth angle, and number of beams can be investigated. The angular distributions of echo power and radial velocity obtained by CRI provide a unique opportunity to validate the inherent assumption in the DBS method of homogeneity across the region defined by the beam directions. Through comparison with a reference wind field, calculated as the optimal uniform wind field derived from all CRI beams with sufficient signal-to-noise ratio (SNR), the accuracy of the wind estimates for various DBS configurations is statistically analyzed. It is shown that for a three-beam DBS configuration, although the validity of the homogeneity assumption is enhanced at smaller zenith angles, the root-mean-square (RMS) error increases because of the ill-conditioned matrix in the DBS algorithm. As expected, inhomogeneities in the wind field produce large bias for the three-beam DBS configuration for large zenith angles. An optimal zenith angle, in terms of RMS error, of approximately 9°–10° was estimated. It is further shown that RMS error can be significantly reduced by increasing the number of off-vertical beams used for the DBS processing.
Abstract
In this work, the accuracy of the Doppler beam-swinging (DBS) technique for wind measurements is studied using an imaging radar—the turbulent eddy profiler (TEP) developed by the University of Massachusetts, with data collected in summer 2003. With up to 64 independent receivers, and using coherent radar imaging (CRI), several hundred partially independent beams can be formed simultaneously within the volume defined by the transmit beam. By selecting a subset of these beams, an unprecedented number of DBS configurations with varying zenith angle, azimuth angle, and number of beams can be investigated. The angular distributions of echo power and radial velocity obtained by CRI provide a unique opportunity to validate the inherent assumption in the DBS method of homogeneity across the region defined by the beam directions. Through comparison with a reference wind field, calculated as the optimal uniform wind field derived from all CRI beams with sufficient signal-to-noise ratio (SNR), the accuracy of the wind estimates for various DBS configurations is statistically analyzed. It is shown that for a three-beam DBS configuration, although the validity of the homogeneity assumption is enhanced at smaller zenith angles, the root-mean-square (RMS) error increases because of the ill-conditioned matrix in the DBS algorithm. As expected, inhomogeneities in the wind field produce large bias for the three-beam DBS configuration for large zenith angles. An optimal zenith angle, in terms of RMS error, of approximately 9°–10° was estimated. It is further shown that RMS error can be significantly reduced by increasing the number of off-vertical beams used for the DBS processing.
Abstract
Twentieth-century regional sea level changes are estimated from 12 climate models from phase 5 of the Climate Model Intercomparison Project (CMIP5). The output of the CMIP5 climate model simulations was used to calculate the global and regional sea level changes associated with dynamic sea level, atmospheric loading, glacier mass changes, and ice sheet surface mass balance contributions. The contribution from groundwater depletion, reservoir storage, and dynamic ice sheet mass changes are estimated from observations as they are not simulated by climate models. All contributions are summed, including the glacial isostatic adjustment (GIA) contribution, and compared to observational estimates from 27 tide gauge records over the twentieth century (1900–2015). A general agreement is found between the simulated sea level and tide gauge records in terms of interannual to multidecadal variability over 1900–2015. But climate models tend to systematically underestimate the observed sea level trends, particularly in the first half of the twentieth century. The corrections based on attributable biases between observations and models that have been identified in Part I of this two-part paper result in an improved explanation of the spatial variability in observed sea level trends by climate models. Climate models show that the spatial variability in sea level trends observed by tide gauge records is dominated by the GIA contribution and the steric contribution over 1900–2015. Climate models also show that it is important to include all contributions to sea level changes as they cause significant local deviations; note, for example, the groundwater depletion around India, which is responsible for the low twentieth-century sea level rise in the region.
Abstract
Twentieth-century regional sea level changes are estimated from 12 climate models from phase 5 of the Climate Model Intercomparison Project (CMIP5). The output of the CMIP5 climate model simulations was used to calculate the global and regional sea level changes associated with dynamic sea level, atmospheric loading, glacier mass changes, and ice sheet surface mass balance contributions. The contribution from groundwater depletion, reservoir storage, and dynamic ice sheet mass changes are estimated from observations as they are not simulated by climate models. All contributions are summed, including the glacial isostatic adjustment (GIA) contribution, and compared to observational estimates from 27 tide gauge records over the twentieth century (1900–2015). A general agreement is found between the simulated sea level and tide gauge records in terms of interannual to multidecadal variability over 1900–2015. But climate models tend to systematically underestimate the observed sea level trends, particularly in the first half of the twentieth century. The corrections based on attributable biases between observations and models that have been identified in Part I of this two-part paper result in an improved explanation of the spatial variability in observed sea level trends by climate models. Climate models show that the spatial variability in sea level trends observed by tide gauge records is dominated by the GIA contribution and the steric contribution over 1900–2015. Climate models also show that it is important to include all contributions to sea level changes as they cause significant local deviations; note, for example, the groundwater depletion around India, which is responsible for the low twentieth-century sea level rise in the region.
Abstract
Sea level change is one of the major consequences of climate change and is projected to affect coastal communities around the world. Here, global mean sea level (GMSL) change estimated by 12 climate models from phase 5 of the World Climate Research Programme’s Climate Model Intercomparison Project (CMIP5) is compared to observational estimates for the period 1900–2015. Observed and simulated individual contributions to GMSL change (thermal expansion, glacier mass change, ice sheet mass change, landwater storage change) are analyzed and compared to observed GMSL change over the period 1900–2007 using tide gauge reconstructions, and over the period 1993–2015 using satellite altimetry estimates. The model-simulated contributions explain 50% ± 30% (uncertainties 1.65σ unless indicated otherwise) of the mean observed change from 1901–20 to 1988–2007. Based on attributable biases between observations and models, a number of corrections are proposed, which result in an improved explanation of 75% ± 38% of the observed change. For the satellite era (from 1993–97 to 2011–15) an improved budget closure of 102% ± 33% is found (105% ± 35% when including the proposed bias corrections). Simulated decadal trends increase over the twentieth century, both in the thermal expansion and the combined mass contributions (glaciers, ice sheets, and landwater storage). The mass components explain the majority of sea level rise over the twentieth century, but the thermal expansion has increasingly contributed to sea level rise, starting from 1910 onward and in 2015 accounting for 46% of the total simulated sea level change.
Abstract
Sea level change is one of the major consequences of climate change and is projected to affect coastal communities around the world. Here, global mean sea level (GMSL) change estimated by 12 climate models from phase 5 of the World Climate Research Programme’s Climate Model Intercomparison Project (CMIP5) is compared to observational estimates for the period 1900–2015. Observed and simulated individual contributions to GMSL change (thermal expansion, glacier mass change, ice sheet mass change, landwater storage change) are analyzed and compared to observed GMSL change over the period 1900–2007 using tide gauge reconstructions, and over the period 1993–2015 using satellite altimetry estimates. The model-simulated contributions explain 50% ± 30% (uncertainties 1.65σ unless indicated otherwise) of the mean observed change from 1901–20 to 1988–2007. Based on attributable biases between observations and models, a number of corrections are proposed, which result in an improved explanation of 75% ± 38% of the observed change. For the satellite era (from 1993–97 to 2011–15) an improved budget closure of 102% ± 33% is found (105% ± 35% when including the proposed bias corrections). Simulated decadal trends increase over the twentieth century, both in the thermal expansion and the combined mass contributions (glaciers, ice sheets, and landwater storage). The mass components explain the majority of sea level rise over the twentieth century, but the thermal expansion has increasingly contributed to sea level rise, starting from 1910 onward and in 2015 accounting for 46% of the total simulated sea level change.
The authors have developed a new extended-range flood forecasting system for large river basins that uses satellite data and statistically rendered probabilistic weather and climate predictions to initialize basin-scale hydrological models. The forecasting system overcomes the absence of upstreamflow data, a problem that is prevalent in the developing world. Forecasts of the Ganges and Brahmaputra discharge into Bangladesh were made in real time on 1–10-day time horizons for the period 2003–08. Serious flooding of the Brahmaputra occurred in 2004, 2007, and 2008. Detailed forecasts of the flood onset and withdrawal were made 10 days in advance for each of the flooding events with correlations at 10 days ≥0.8 and Brier scores <0.05. Extensions to 15 days show useable skill. Based on the 1–10-day forecasts of the 2007 and 2008 floods, emergency managers in Bangladesh were able to act preemptively, arrange the evacuation of populations in peril along the Brahmaputra, and minimize financial loss. The particular application of this forecast scheme in Bangladesh represents a “world is f lat” approach to emergency management through the collaboration of scientists in Europe (generating global ensemble meteorological and climate forecasts), the United States (developing and producing the integrated flood forecasts), and the developing world (integrating the flood forecasts into their disaster management decision-making protocol), all enabled by high-speed Internet connections. We also make suggestions of how scientific and technical collaborations between more developed and developing nations can be improved to increase their prospects for sustaining the technology adoption and transfer.
The authors have developed a new extended-range flood forecasting system for large river basins that uses satellite data and statistically rendered probabilistic weather and climate predictions to initialize basin-scale hydrological models. The forecasting system overcomes the absence of upstreamflow data, a problem that is prevalent in the developing world. Forecasts of the Ganges and Brahmaputra discharge into Bangladesh were made in real time on 1–10-day time horizons for the period 2003–08. Serious flooding of the Brahmaputra occurred in 2004, 2007, and 2008. Detailed forecasts of the flood onset and withdrawal were made 10 days in advance for each of the flooding events with correlations at 10 days ≥0.8 and Brier scores <0.05. Extensions to 15 days show useable skill. Based on the 1–10-day forecasts of the 2007 and 2008 floods, emergency managers in Bangladesh were able to act preemptively, arrange the evacuation of populations in peril along the Brahmaputra, and minimize financial loss. The particular application of this forecast scheme in Bangladesh represents a “world is f lat” approach to emergency management through the collaboration of scientists in Europe (generating global ensemble meteorological and climate forecasts), the United States (developing and producing the integrated flood forecasts), and the developing world (integrating the flood forecasts into their disaster management decision-making protocol), all enabled by high-speed Internet connections. We also make suggestions of how scientific and technical collaborations between more developed and developing nations can be improved to increase their prospects for sustaining the technology adoption and transfer.
Abstract
The main field activities of the Coordinated Airborne Studies in the Tropics (CAST) campaign took place in the west Pacific during January–February 2014. The field campaign was based in Guam (13.5°N, 144.8°E), using the U.K. Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 atmospheric research aircraft, and was coordinated with the Airborne Tropical Tropopause Experiment (ATTREX) project with an unmanned Global Hawk and the Convective Transport of Active Species in the Tropics (CONTRAST) campaign with a Gulfstream V aircraft. Together, the three aircraft were able to make detailed measurements of atmospheric structure and composition from the ocean surface to 20 km. These measurements are providing new information about the processes influencing halogen and ozone levels in the tropical west Pacific, as well as the importance of trace-gas transport in convection for the upper troposphere and stratosphere. The FAAM aircraft made a total of 25 flights in the region between 1°S and 14°N and 130° and 155°E. It was used to sample at altitudes below 8 km, with much of the time spent in the marine boundary layer. It measured a range of chemical species and sampled extensively within the region of main inflow into the strong west Pacific convection. The CAST team also made ground-based measurements of a number of species (including daily ozonesondes) at the Atmospheric Radiation Measurement Program site on Manus Island, Papua New Guinea (2.1°S, 147.4°E). This article presents an overview of the CAST project, focusing on the design and operation of the west Pacific experiment. It additionally discusses some new developments in CAST, including flights of new instruments on board the Global Hawk in February–March 2015.
Abstract
The main field activities of the Coordinated Airborne Studies in the Tropics (CAST) campaign took place in the west Pacific during January–February 2014. The field campaign was based in Guam (13.5°N, 144.8°E), using the U.K. Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 atmospheric research aircraft, and was coordinated with the Airborne Tropical Tropopause Experiment (ATTREX) project with an unmanned Global Hawk and the Convective Transport of Active Species in the Tropics (CONTRAST) campaign with a Gulfstream V aircraft. Together, the three aircraft were able to make detailed measurements of atmospheric structure and composition from the ocean surface to 20 km. These measurements are providing new information about the processes influencing halogen and ozone levels in the tropical west Pacific, as well as the importance of trace-gas transport in convection for the upper troposphere and stratosphere. The FAAM aircraft made a total of 25 flights in the region between 1°S and 14°N and 130° and 155°E. It was used to sample at altitudes below 8 km, with much of the time spent in the marine boundary layer. It measured a range of chemical species and sampled extensively within the region of main inflow into the strong west Pacific convection. The CAST team also made ground-based measurements of a number of species (including daily ozonesondes) at the Atmospheric Radiation Measurement Program site on Manus Island, Papua New Guinea (2.1°S, 147.4°E). This article presents an overview of the CAST project, focusing on the design and operation of the west Pacific experiment. It additionally discusses some new developments in CAST, including flights of new instruments on board the Global Hawk in February–March 2015.
