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- Author or Editor: Zhi Liang x
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Abstract
The National Aeronautics and Space Administration (NASA) and National Oceanic and Atmospheric Administration (NOAA) have a long and successful history of weather radar research. The NOAA ground-based radars—WSR-88D network—provide nationwide precipitation observations and estimates with advanced polarimetric capability. As a counterpart, the NASA–JAXA spaceborne radar—the Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM DPR)—has global coverage and higher vertical resolution than ground-based radars. While significant advances from both NOAA’s WSR-88D network and NASA–JAXA’s spaceborne radar DPR have been made, no systematic comparisons between the WSR-88D network and the DPR have been done. This study for the first time generates nationwide comprehensive comparisons at 136 WSR-88D radar sites from 2014 to 2020. Systematic differences in reflectivity are found, with ground radar reflectivity on average 2.4 dB smaller than that of the DPR (DPR version 6). This research found the discrepancies between WSR-88D and DPR arise from different calibration standards, signal attenuation correction, and differences in the ground and spaceborne scattering volumes. The recently updated DPR version 7 product improves rain detection and attenuation corrections, effectively reducing the overall average WSR-88D and DPR reflectivity differences to 1.0 dB. The goal of this study is to examine the systematic differences of radar reflectivity between the NOAA WSR-88D network and the NASA–JAXA DPR and to draw attention to radar-application users in recognizing their differences. Further investigation into understanding and alleviating the systematic bias between the two platforms is needed.
Abstract
The National Aeronautics and Space Administration (NASA) and National Oceanic and Atmospheric Administration (NOAA) have a long and successful history of weather radar research. The NOAA ground-based radars—WSR-88D network—provide nationwide precipitation observations and estimates with advanced polarimetric capability. As a counterpart, the NASA–JAXA spaceborne radar—the Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM DPR)—has global coverage and higher vertical resolution than ground-based radars. While significant advances from both NOAA’s WSR-88D network and NASA–JAXA’s spaceborne radar DPR have been made, no systematic comparisons between the WSR-88D network and the DPR have been done. This study for the first time generates nationwide comprehensive comparisons at 136 WSR-88D radar sites from 2014 to 2020. Systematic differences in reflectivity are found, with ground radar reflectivity on average 2.4 dB smaller than that of the DPR (DPR version 6). This research found the discrepancies between WSR-88D and DPR arise from different calibration standards, signal attenuation correction, and differences in the ground and spaceborne scattering volumes. The recently updated DPR version 7 product improves rain detection and attenuation corrections, effectively reducing the overall average WSR-88D and DPR reflectivity differences to 1.0 dB. The goal of this study is to examine the systematic differences of radar reflectivity between the NOAA WSR-88D network and the NASA–JAXA DPR and to draw attention to radar-application users in recognizing their differences. Further investigation into understanding and alleviating the systematic bias between the two platforms is needed.
Abstract
There is an ongoing debate as to whether the UHI intensity (UHII) is enhanced or dampened under heat waves (HWs). Using a comprehensive dataset including continuous surface energy flux data for three summers (2016–18) and automated weather station data for six summers (2013–18) in Shanghai, China, we find synergies between UHIs and HWs when either a coastal or an inland suburban site is used as the reference site. We further find that during HWs, the increase of net radiation at the urban site is larger than that at the suburban site. More importantly, the latent heat flux is slightly reduced at the urban site but is slightly increased at the suburban site, while the increase of the sensible heat flux is larger at the urban site. This change of surface energy partitioning, together with the increased anthropogenic heat flux during HWs, exacerbates the UHII. The change of surface energy partitioning is consistent with the observed decrease of relative humidity ratio between urban and suburban areas. The UHII is stronger when the regional wind speed is reduced and under sea breeze, both of which are found to be associated with HWs in our study region. This study suggests that there are multiple factors controlling the interactions between UHIs and HWs, which may explain why synergies between UHIs and HWs are only found in certain metropolitan regions and/or under certain HW events.
Abstract
There is an ongoing debate as to whether the UHI intensity (UHII) is enhanced or dampened under heat waves (HWs). Using a comprehensive dataset including continuous surface energy flux data for three summers (2016–18) and automated weather station data for six summers (2013–18) in Shanghai, China, we find synergies between UHIs and HWs when either a coastal or an inland suburban site is used as the reference site. We further find that during HWs, the increase of net radiation at the urban site is larger than that at the suburban site. More importantly, the latent heat flux is slightly reduced at the urban site but is slightly increased at the suburban site, while the increase of the sensible heat flux is larger at the urban site. This change of surface energy partitioning, together with the increased anthropogenic heat flux during HWs, exacerbates the UHII. The change of surface energy partitioning is consistent with the observed decrease of relative humidity ratio between urban and suburban areas. The UHII is stronger when the regional wind speed is reduced and under sea breeze, both of which are found to be associated with HWs in our study region. This study suggests that there are multiple factors controlling the interactions between UHIs and HWs, which may explain why synergies between UHIs and HWs are only found in certain metropolitan regions and/or under certain HW events.
Abstract
LM3 is a new model of terrestrial water, energy, and carbon, intended for use in global hydrologic analyses and as a component of earth-system and physical-climate models. It is designed to improve upon the performance and to extend the scope of the predecessor Land Dynamics (LaD) and LM3V models by better quantifying the physical controls of climate and biogeochemistry and by relating more directly to components of the global water system that touch human concerns. LM3 includes multilayer representations of temperature, liquid water content, and ice content of both snowpack and macroporous soil–bedrock; topography-based description of saturated area and groundwater discharge; and transport of runoff to the ocean via a global river and lake network. Sensible heat transport by water mass is accounted throughout for a complete energy balance. Carbon and vegetation dynamics and biophysics are represented as in LM3V. In numerical experiments, LM3 avoids some of the limitations of the LaD model and provides qualitatively (though not always quantitatively) reasonable estimates, from a global perspective, of observed spatial and/or temporal variations of vegetation density, albedo, streamflow, water-table depth, permafrost, and lake levels. Amplitude and phase of annual cycle of total water storage are simulated well. Realism of modeled lake levels varies widely. The water table tends to be consistently too shallow in humid regions. Biophysical properties have an artificial stepwise spatial structure, and equilibrium vegetation is sensitive to initial conditions. Explicit resolution of thick (>100 m) unsaturated zones and permafrost is possible, but only at the cost of long (≫300 yr) model spinup times.
Abstract
LM3 is a new model of terrestrial water, energy, and carbon, intended for use in global hydrologic analyses and as a component of earth-system and physical-climate models. It is designed to improve upon the performance and to extend the scope of the predecessor Land Dynamics (LaD) and LM3V models by better quantifying the physical controls of climate and biogeochemistry and by relating more directly to components of the global water system that touch human concerns. LM3 includes multilayer representations of temperature, liquid water content, and ice content of both snowpack and macroporous soil–bedrock; topography-based description of saturated area and groundwater discharge; and transport of runoff to the ocean via a global river and lake network. Sensible heat transport by water mass is accounted throughout for a complete energy balance. Carbon and vegetation dynamics and biophysics are represented as in LM3V. In numerical experiments, LM3 avoids some of the limitations of the LaD model and provides qualitatively (though not always quantitatively) reasonable estimates, from a global perspective, of observed spatial and/or temporal variations of vegetation density, albedo, streamflow, water-table depth, permafrost, and lake levels. Amplitude and phase of annual cycle of total water storage are simulated well. Realism of modeled lake levels varies widely. The water table tends to be consistently too shallow in humid regions. Biophysical properties have an artificial stepwise spatial structure, and equilibrium vegetation is sensitive to initial conditions. Explicit resolution of thick (>100 m) unsaturated zones and permafrost is possible, but only at the cost of long (≫300 yr) model spinup times.
Abstract
The current generation of coupled climate models run at the Geophysical Fluid Dynamics Laboratory (GFDL) as part of the Climate Change Science Program contains ocean components that differ in almost every respect from those contained in previous generations of GFDL climate models. This paper summarizes the new physical features of the models and examines the simulations that they produce. Of the two new coupled climate model versions 2.1 (CM2.1) and 2.0 (CM2.0), the CM2.1 model represents a major improvement over CM2.0 in most of the major oceanic features examined, with strikingly lower drifts in hydrographic fields such as temperature and salinity, more realistic ventilation of the deep ocean, and currents that are closer to their observed values. Regional analysis of the differences between the models highlights the importance of wind stress in determining the circulation, particularly in the Southern Ocean. At present, major errors in both models are associated with Northern Hemisphere Mode Waters and outflows from overflows, particularly the Mediterranean Sea and Red Sea.
Abstract
The current generation of coupled climate models run at the Geophysical Fluid Dynamics Laboratory (GFDL) as part of the Climate Change Science Program contains ocean components that differ in almost every respect from those contained in previous generations of GFDL climate models. This paper summarizes the new physical features of the models and examines the simulations that they produce. Of the two new coupled climate model versions 2.1 (CM2.1) and 2.0 (CM2.0), the CM2.1 model represents a major improvement over CM2.0 in most of the major oceanic features examined, with strikingly lower drifts in hydrographic fields such as temperature and salinity, more realistic ventilation of the deep ocean, and currents that are closer to their observed values. Regional analysis of the differences between the models highlights the importance of wind stress in determining the circulation, particularly in the Southern Ocean. At present, major errors in both models are associated with Northern Hemisphere Mode Waters and outflows from overflows, particularly the Mediterranean Sea and Red Sea.
Abstract
This paper documents time mean simulation characteristics from the ocean and sea ice components in a new coupled climate model developed at the NOAA Geophysical Fluid Dynamics Laboratory (GFDL). The GFDL Climate Model version 3 (CM3) is formulated with effectively the same ocean and sea ice components as the earlier CM2.1 yet with extensive developments made to the atmosphere and land model components. Both CM2.1 and CM3 show stable mean climate indices, such as large-scale circulation and sea surface temperatures (SSTs). There are notable improvements in the CM3 climate simulation relative to CM2.1, including a modified SST bias pattern and reduced biases in the Arctic sea ice cover. The authors anticipate SST differences between CM2.1 and CM3 in lower latitudes through analysis of the atmospheric fluxes at the ocean surface in corresponding Atmospheric Model Intercomparison Project (AMIP) simulations. In contrast, SST changes in the high latitudes are dominated by ocean and sea ice effects absent in AMIP simulations. The ocean interior simulation in CM3 is generally warmer than in CM2.1, which adversely impacts the interior biases.
Abstract
This paper documents time mean simulation characteristics from the ocean and sea ice components in a new coupled climate model developed at the NOAA Geophysical Fluid Dynamics Laboratory (GFDL). The GFDL Climate Model version 3 (CM3) is formulated with effectively the same ocean and sea ice components as the earlier CM2.1 yet with extensive developments made to the atmosphere and land model components. Both CM2.1 and CM3 show stable mean climate indices, such as large-scale circulation and sea surface temperatures (SSTs). There are notable improvements in the CM3 climate simulation relative to CM2.1, including a modified SST bias pattern and reduced biases in the Arctic sea ice cover. The authors anticipate SST differences between CM2.1 and CM3 in lower latitudes through analysis of the atmospheric fluxes at the ocean surface in corresponding Atmospheric Model Intercomparison Project (AMIP) simulations. In contrast, SST changes in the high latitudes are dominated by ocean and sea ice effects absent in AMIP simulations. The ocean interior simulation in CM3 is generally warmer than in CM2.1, which adversely impacts the interior biases.
