Browse
Abstract
The Dual-Frequency Precipitation Radar (DPR), which consists of a Ku-band precipitation radar (KuPR) and a Ka-band precipitation radar (KaPR) on board the GPM Core Observatory, cannot observe precipitation at low altitudes near the ground contaminated by surface clutter. This near-surface region is called the blind zone. DPR estimates the clutter-free bottom (CFB), which is the lowest altitude not included in the blind zone, and estimates precipitation at altitudes higher than the CFB. High CFBs, which are common over mountainous areas, represent obstacles to detection of shallow precipitation and estimation of low-level enhanced precipitation. We compared KuPR data with rain gauge data from Da-Tun Mountain of northern Taiwan acquired from March 2014 to February 2020. A total of 12 cases were identified in which the KuPR missed some rainfall with intensity of >10 mm h−1 that was observed by rain gauges. Comparison of KuPR profile and ground-based radar profile revealed that shallow precipitation in the KuPR blind zone was missed because the CFB was estimated to be higher than the lower bound of the range free from surface echoes. In the original operational algorithm, CFB was estimated using only the received power data of the KuPR. In this study, the CFB was identified by the sharp increase in the difference between the received powers of the KuPR and the KaPR at altitude affected by surface clutter. By lowering the CFB, the KuPR succeeded in detection and estimation of shallow precipitation.
Significance Statement
The Dual-Frequency Precipitation Radar (DPR) on board the GPM Core Observatory cannot capture precipitation in the low-altitude region near the ground contaminated by surface clutter. This region is called the blind zone. The DPR estimates the clutter-free bottom (CFB), which is the lower bound of the range free from surface echoes, and uses data higher than CFB. DPR consists of a Ku-band precipitation radar (KuPR) and a Ka-band precipitation radar (KaPR). KuPR missed some shallow precipitation more than 10 mm h−1 in the blind zone over Da-Tun Mountain of northern Taiwan because of misjudged CFB estimation. Using both the KuPR and the KaPR, we improved the CFB estimation algorithm, which lowered the CFB, narrowed the blind zone, and improved the capability to detect shallow precipitation.
Abstract
The Dual-Frequency Precipitation Radar (DPR), which consists of a Ku-band precipitation radar (KuPR) and a Ka-band precipitation radar (KaPR) on board the GPM Core Observatory, cannot observe precipitation at low altitudes near the ground contaminated by surface clutter. This near-surface region is called the blind zone. DPR estimates the clutter-free bottom (CFB), which is the lowest altitude not included in the blind zone, and estimates precipitation at altitudes higher than the CFB. High CFBs, which are common over mountainous areas, represent obstacles to detection of shallow precipitation and estimation of low-level enhanced precipitation. We compared KuPR data with rain gauge data from Da-Tun Mountain of northern Taiwan acquired from March 2014 to February 2020. A total of 12 cases were identified in which the KuPR missed some rainfall with intensity of >10 mm h−1 that was observed by rain gauges. Comparison of KuPR profile and ground-based radar profile revealed that shallow precipitation in the KuPR blind zone was missed because the CFB was estimated to be higher than the lower bound of the range free from surface echoes. In the original operational algorithm, CFB was estimated using only the received power data of the KuPR. In this study, the CFB was identified by the sharp increase in the difference between the received powers of the KuPR and the KaPR at altitude affected by surface clutter. By lowering the CFB, the KuPR succeeded in detection and estimation of shallow precipitation.
Significance Statement
The Dual-Frequency Precipitation Radar (DPR) on board the GPM Core Observatory cannot capture precipitation in the low-altitude region near the ground contaminated by surface clutter. This region is called the blind zone. The DPR estimates the clutter-free bottom (CFB), which is the lower bound of the range free from surface echoes, and uses data higher than CFB. DPR consists of a Ku-band precipitation radar (KuPR) and a Ka-band precipitation radar (KaPR). KuPR missed some shallow precipitation more than 10 mm h−1 in the blind zone over Da-Tun Mountain of northern Taiwan because of misjudged CFB estimation. Using both the KuPR and the KaPR, we improved the CFB estimation algorithm, which lowered the CFB, narrowed the blind zone, and improved the capability to detect shallow precipitation.
Abstract
This paper examines the controls on supercooled liquid water content (SLWC) and drop number concentrations (Nt ,CDP) over the Payette River basin during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE) campaign. During SNOWIE, 27.4% of 1-Hz in situ cloud droplet probe samples were in an environment containing supercooled liquid water (SLW). The interquartile range of SLWC, when present, was found to be 0.02–0.18 g m−3 and 13.3–37.2 cm−3 for Nt ,CDP, with the most extreme values reaching 0.40–1.75 g m−3 and 150–320 cm−3 in isolated regions of convection and strong shear-induced turbulence. SLWC and Nt ,CDP distributions are shown to be directly related to cloud-top temperature and ice particle concentrations, consistent with past research over other mountain ranges. Two classes of vertical motions were analyzed as potential controls on SLWC and Nt ,CDP, the first forced by the orography and fixed in space relative to the topography (stationary waves) and the second transient, triggered by vertical shear and instability within passing synoptic-scale cyclones. SLWC occurrence and magnitudes, and Nt ,CDP associated with fixed updrafts were found to be normally distributed about ridgelines when SLW was present. SLW was more likely to form at low altitudes near the terrain slope associated with fixed waves due to higher mixing ratios and larger vertical air parcel displacements at low altitudes. When considering transient updrafts, SLWC and Nt ,CDP appear more uniformly distributed over the flight track with little discernable terrain dependence as a result of time and spatially varying updrafts associated with passing weather systems. The implications for cloud seeding over the basin are discussed.
Abstract
This paper examines the controls on supercooled liquid water content (SLWC) and drop number concentrations (Nt ,CDP) over the Payette River basin during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE) campaign. During SNOWIE, 27.4% of 1-Hz in situ cloud droplet probe samples were in an environment containing supercooled liquid water (SLW). The interquartile range of SLWC, when present, was found to be 0.02–0.18 g m−3 and 13.3–37.2 cm−3 for Nt ,CDP, with the most extreme values reaching 0.40–1.75 g m−3 and 150–320 cm−3 in isolated regions of convection and strong shear-induced turbulence. SLWC and Nt ,CDP distributions are shown to be directly related to cloud-top temperature and ice particle concentrations, consistent with past research over other mountain ranges. Two classes of vertical motions were analyzed as potential controls on SLWC and Nt ,CDP, the first forced by the orography and fixed in space relative to the topography (stationary waves) and the second transient, triggered by vertical shear and instability within passing synoptic-scale cyclones. SLWC occurrence and magnitudes, and Nt ,CDP associated with fixed updrafts were found to be normally distributed about ridgelines when SLW was present. SLW was more likely to form at low altitudes near the terrain slope associated with fixed waves due to higher mixing ratios and larger vertical air parcel displacements at low altitudes. When considering transient updrafts, SLWC and Nt ,CDP appear more uniformly distributed over the flight track with little discernable terrain dependence as a result of time and spatially varying updrafts associated with passing weather systems. The implications for cloud seeding over the basin are discussed.
Abstract
Forecasting tornadogenesis remains a difficult problem in meteorology, especially for short-lived, predominantly nonsupercellular tornadic storms embedded within mesoscale convective systems (MCSs). This study compares populations of tornadic nonsupercellular MCS storm cells with their nontornadic counterparts, focusing on nontornadic storms that have similar radar characteristics to tornadic storms. Comparisons of single-polarization radar variables during storm lifetimes show that median values of low-level, midlevel, and column-maximum azimuthal shear, as well as low-level radial divergence, enable the highest degree of separation between tornadic and nontornadic storms. Focusing on low-level azimuthal shear values, null storms were randomly selected such that the distribution of null low-level azimuthal shear values matched the distribution of tornadic values. After isolating the null cases from the nontornadic population, signatures emerge in single-polarization data that enable discrimination between nontornadic and tornadic storms. In comparison, dual-polarization variables show little deviation between storm types. Tornadic storms both at tornadogenesis and at a 20-min lead time show collocation of the primary storm updraft with enhanced near-surface rotation and convergence, facilitating the nonmesocyclonic tornadogenesis processes.
Abstract
Forecasting tornadogenesis remains a difficult problem in meteorology, especially for short-lived, predominantly nonsupercellular tornadic storms embedded within mesoscale convective systems (MCSs). This study compares populations of tornadic nonsupercellular MCS storm cells with their nontornadic counterparts, focusing on nontornadic storms that have similar radar characteristics to tornadic storms. Comparisons of single-polarization radar variables during storm lifetimes show that median values of low-level, midlevel, and column-maximum azimuthal shear, as well as low-level radial divergence, enable the highest degree of separation between tornadic and nontornadic storms. Focusing on low-level azimuthal shear values, null storms were randomly selected such that the distribution of null low-level azimuthal shear values matched the distribution of tornadic values. After isolating the null cases from the nontornadic population, signatures emerge in single-polarization data that enable discrimination between nontornadic and tornadic storms. In comparison, dual-polarization variables show little deviation between storm types. Tornadic storms both at tornadogenesis and at a 20-min lead time show collocation of the primary storm updraft with enhanced near-surface rotation and convergence, facilitating the nonmesocyclonic tornadogenesis processes.
Abstract
This study aims to characterize the shapes and fall speeds of ice pellets formed in various atmospheric conditions and to investigate the possibility to use a laser-optical disdrometer to distinguish between ice pellets and other types of precipitation. To do so, four ice pellet events were documented using manual observations, macro photography, and laser-optical disdrometer data. First, various ice pellet fall speeds, and shapes, including spherical, bulged, fractured, and irregular particles, were associated with distinct atmospheric conditions. A higher fraction of bulged and fractured ice pellets was observed when solid precipitation was completely melted aloft while more irregular particles were observed during partial melting. These characteristics affected the diameter-fall speed relations measured. Second, the measurements of particles’ fall speed and diameter show that ice pellets could be differentiated from rain or freezing rain. Ice pellets larger than 1.5 mm tend to fall > 0.5 m s−1 slower than raindrops of the same size. Additionally, the fall speed of a small fraction of ice pellets was < 2 m s−1 regardless of their size, compared to a fall speed > 3 m s−1 for ice pellets with diameter > 1.5 mm. Video analysis suggests that these slower particles could be ice pellets passing through the laser-optical disdrometer after colliding with the head of the instrument. Overall, these findings contribute to a better understanding of the microphysics of ice pellets and their measurement using a laser-optical disdrometer.
Abstract
This study aims to characterize the shapes and fall speeds of ice pellets formed in various atmospheric conditions and to investigate the possibility to use a laser-optical disdrometer to distinguish between ice pellets and other types of precipitation. To do so, four ice pellet events were documented using manual observations, macro photography, and laser-optical disdrometer data. First, various ice pellet fall speeds, and shapes, including spherical, bulged, fractured, and irregular particles, were associated with distinct atmospheric conditions. A higher fraction of bulged and fractured ice pellets was observed when solid precipitation was completely melted aloft while more irregular particles were observed during partial melting. These characteristics affected the diameter-fall speed relations measured. Second, the measurements of particles’ fall speed and diameter show that ice pellets could be differentiated from rain or freezing rain. Ice pellets larger than 1.5 mm tend to fall > 0.5 m s−1 slower than raindrops of the same size. Additionally, the fall speed of a small fraction of ice pellets was < 2 m s−1 regardless of their size, compared to a fall speed > 3 m s−1 for ice pellets with diameter > 1.5 mm. Video analysis suggests that these slower particles could be ice pellets passing through the laser-optical disdrometer after colliding with the head of the instrument. Overall, these findings contribute to a better understanding of the microphysics of ice pellets and their measurement using a laser-optical disdrometer.
Abstract
Recent studies from the Seeded and Natural Orographic Wintertime Clouds: the Idaho Experiment (SNOWIE) demonstrated definitive radar evidence of seeding signatures in winter orographic clouds during three intensive operation periods (IOPs) where the background signal from natural precipitation was weak and a radar signal attributable to seeding could be identified as traceable seeding lines. Except for the three IOPs where seeding was detected, background natural snowfall was present during seeding operations and no clear seeding signatures were detected. This paper provides a quantitative analysis to assess if orographic cloud seeding effects are detectable using radar when background precipitation is present. We show that a 5 dB change in equivalent reflectivity factor (Ze ) is required to stand out against background natural Ze variability. This analysis considers four radar wavelengths, a range of background ice water contents (IWC) from 0.012 g m−3 to 1.214 g m−3, and additional IWC introduced by seeding ranging from 0.012 g m−3 to 0.486 g m−3. The upper limit values of seeded IWC are based on measurements of IWC from the Nevzorov probe employed on the University of Wyoming King Air aircraft during SNOWIE. This analysis implies that seeding effects will be undetectable using radar within background snowfall unless the background IWC is small, and the seeding effects are large. It therefore remains uncertain whether seeding had no effect on cloud microstructure, and therefore produced no signature on radar, or whether seeding did have an effect, but that effect was undetectable against the background reflectivity associated with naturally-produced precipitation.
Abstract
Recent studies from the Seeded and Natural Orographic Wintertime Clouds: the Idaho Experiment (SNOWIE) demonstrated definitive radar evidence of seeding signatures in winter orographic clouds during three intensive operation periods (IOPs) where the background signal from natural precipitation was weak and a radar signal attributable to seeding could be identified as traceable seeding lines. Except for the three IOPs where seeding was detected, background natural snowfall was present during seeding operations and no clear seeding signatures were detected. This paper provides a quantitative analysis to assess if orographic cloud seeding effects are detectable using radar when background precipitation is present. We show that a 5 dB change in equivalent reflectivity factor (Ze ) is required to stand out against background natural Ze variability. This analysis considers four radar wavelengths, a range of background ice water contents (IWC) from 0.012 g m−3 to 1.214 g m−3, and additional IWC introduced by seeding ranging from 0.012 g m−3 to 0.486 g m−3. The upper limit values of seeded IWC are based on measurements of IWC from the Nevzorov probe employed on the University of Wyoming King Air aircraft during SNOWIE. This analysis implies that seeding effects will be undetectable using radar within background snowfall unless the background IWC is small, and the seeding effects are large. It therefore remains uncertain whether seeding had no effect on cloud microstructure, and therefore produced no signature on radar, or whether seeding did have an effect, but that effect was undetectable against the background reflectivity associated with naturally-produced precipitation.
Abstract
Phenological indicators (PI) are used to study changes to animal and plant behavior in response to seasonal cycles, and they can be useful to quantify the potential impacts of climate change on ecosystems. Here, multiple global climate models and emission scenarios are used to drive dynamically downscaled simulations using the WRF model over the CONUS. The wintertime dormancy of plants (chilling units or “CU”), timing of spring onset (Extended Spring Indices or “SI”), and frequency of proceeding false springs are calculated from regional climate simulations covering historical (1995–2005) and future periods (2025–2100). Southern parts of the CONUS show projected CU decreases (inhibiting some plants from flowering or fruiting), while the northern CONUS experiences an increase (possibly causing plants to break dormancy too early, becoming vulnerable to disease or freezing). Spring advancement (earlier SI dates) is projected, with decadal trends ranging from approximately 1 to 4 days per decade over the CONUS, comparable to or exceeding those found in observational studies. Projected changes in risk of false spring (hard freezes following spring onset) vary across members of the ensemble and regions of the CONUS, but generally western parts of the CONUS are projected to experience increased risk of false springs. These projected changes to PI connote significant effects on cycles of plants, animals, and ecosystems, highlighting the importance of examining temperature changes during transitional seasons.
Abstract
Phenological indicators (PI) are used to study changes to animal and plant behavior in response to seasonal cycles, and they can be useful to quantify the potential impacts of climate change on ecosystems. Here, multiple global climate models and emission scenarios are used to drive dynamically downscaled simulations using the WRF model over the CONUS. The wintertime dormancy of plants (chilling units or “CU”), timing of spring onset (Extended Spring Indices or “SI”), and frequency of proceeding false springs are calculated from regional climate simulations covering historical (1995–2005) and future periods (2025–2100). Southern parts of the CONUS show projected CU decreases (inhibiting some plants from flowering or fruiting), while the northern CONUS experiences an increase (possibly causing plants to break dormancy too early, becoming vulnerable to disease or freezing). Spring advancement (earlier SI dates) is projected, with decadal trends ranging from approximately 1 to 4 days per decade over the CONUS, comparable to or exceeding those found in observational studies. Projected changes in risk of false spring (hard freezes following spring onset) vary across members of the ensemble and regions of the CONUS, but generally western parts of the CONUS are projected to experience increased risk of false springs. These projected changes to PI connote significant effects on cycles of plants, animals, and ecosystems, highlighting the importance of examining temperature changes during transitional seasons.
Abstract
Vertical temperature profiles influence the wind power generation of large offshore wind farms through stability-dependent effects such as blockage and gravity waves. However, numerical tools that are used to model these effects are often computationally too expensive to cover the large variety of atmospheric states occurring over time. Generally, an informed decision about which representative non-idealized situations to simulate is missing because of the lack of easily available information on representative vertical profiles, taking into account their spatio-temporal variability. Therefore, we present a novel framework that allows a smart selection of vertical temperature profiles. The framework consists of an improved analytical temperature model for the atmospheric boundary layer and lower troposphere, a subsequent clustering of these profiles to identify representatives, and lastly, a determination of areas with similar spatio-temporal characteristics of vertical profiles. When applying this framework on European ERA5 data, physically realistic representatives were identified for Europe, excluding the Mediterranean. Two or three profiles were found to be dominant for the open ocean, whereas more profiles prevail for land. Over the open ocean, weak temperature gradients in the boundary layer and a clear capping inversions are widespread, and stable profiles are absent except in the region of the East Icelandic current. Interestingly, according to the ERA5 data, at its resolution, coastal areas and seas surrounded by land behave more similar to the land areas than to the open ocean, implying that a larger set of model integrations are needed for these areas to obtain representative results for offshore wind power assessments compared to the open ocean.
Abstract
Vertical temperature profiles influence the wind power generation of large offshore wind farms through stability-dependent effects such as blockage and gravity waves. However, numerical tools that are used to model these effects are often computationally too expensive to cover the large variety of atmospheric states occurring over time. Generally, an informed decision about which representative non-idealized situations to simulate is missing because of the lack of easily available information on representative vertical profiles, taking into account their spatio-temporal variability. Therefore, we present a novel framework that allows a smart selection of vertical temperature profiles. The framework consists of an improved analytical temperature model for the atmospheric boundary layer and lower troposphere, a subsequent clustering of these profiles to identify representatives, and lastly, a determination of areas with similar spatio-temporal characteristics of vertical profiles. When applying this framework on European ERA5 data, physically realistic representatives were identified for Europe, excluding the Mediterranean. Two or three profiles were found to be dominant for the open ocean, whereas more profiles prevail for land. Over the open ocean, weak temperature gradients in the boundary layer and a clear capping inversions are widespread, and stable profiles are absent except in the region of the East Icelandic current. Interestingly, according to the ERA5 data, at its resolution, coastal areas and seas surrounded by land behave more similar to the land areas than to the open ocean, implying that a larger set of model integrations are needed for these areas to obtain representative results for offshore wind power assessments compared to the open ocean.
Abstract
Measurements from the South Dakota School of Mines and Technology T-28 hail-penetrating aircraft are analyzed using recently developed data processing techniques with the goals of identifying where the large hail is found relative to vertical motion and improving the detection of hail microphysical properties from radar. Hail particle size distributions (PSD) and environmental conditions (temperature, relative humidity, liquid water content, air vertical velocity) were digitally collected by the T28 between 1995 and 2003 and synthesized by Detwiler et al. (2012). The PSD were forward-modeled by Cecchini et al. (2022) to simulate the radar reflectivity of the PSD at multiple radar wavelengths.
The T-28 penetrated temperatures primarily between 0 and −10 °C. The largest hailstones were sampled near the updraft/downdraft interface. Liquid water contents were highest in the updraft cores, whereas total (liquid + frozen) water contents were highest near the updraft/downdraft interface. The fitted properties of the PSD, intercept and slope, are directly related to each other, but do not show any dependence on the region of the hailstorm where sampled. The PSD measurements and the radar reflectivity calculations at multiple radar wavelengths facilitated the development of relationships between the PSD bulk properties—hail kinetic energy and kinetic energy flux—and the radar reflectivity. Rather than using the oft-assumed sphericity and solid ice physical properties, actual measurements of hail properties are used in the analysis. Results from the maximum estimated size of hail (MESH) and vertical integrated liquid water (VIL) algorithms are evaluated based on this analysis.
Abstract
Measurements from the South Dakota School of Mines and Technology T-28 hail-penetrating aircraft are analyzed using recently developed data processing techniques with the goals of identifying where the large hail is found relative to vertical motion and improving the detection of hail microphysical properties from radar. Hail particle size distributions (PSD) and environmental conditions (temperature, relative humidity, liquid water content, air vertical velocity) were digitally collected by the T28 between 1995 and 2003 and synthesized by Detwiler et al. (2012). The PSD were forward-modeled by Cecchini et al. (2022) to simulate the radar reflectivity of the PSD at multiple radar wavelengths.
The T-28 penetrated temperatures primarily between 0 and −10 °C. The largest hailstones were sampled near the updraft/downdraft interface. Liquid water contents were highest in the updraft cores, whereas total (liquid + frozen) water contents were highest near the updraft/downdraft interface. The fitted properties of the PSD, intercept and slope, are directly related to each other, but do not show any dependence on the region of the hailstorm where sampled. The PSD measurements and the radar reflectivity calculations at multiple radar wavelengths facilitated the development of relationships between the PSD bulk properties—hail kinetic energy and kinetic energy flux—and the radar reflectivity. Rather than using the oft-assumed sphericity and solid ice physical properties, actual measurements of hail properties are used in the analysis. Results from the maximum estimated size of hail (MESH) and vertical integrated liquid water (VIL) algorithms are evaluated based on this analysis.
