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Abstract
To characterize the effects of subgrid surface heterogeneity, the blending-height concept has been developed as a coupling strategy for surface parameterization schemes used in numerical weather prediction models. Previous modeling studies have tested this concept using stationary conditions with one-dimensional strips of surface roughness. Here, large-eddy simulations are used to examine the response of the blending height and effective surface roughness to tiled land-cover heterogeneity, or a two-dimensional chessboard pattern of alternating high and low vegetation given a diurnal cycle of solar irradiance in subarctic conditions. In each experiment, the length scale of the roughness elements is increased while the total domain fraction of each vegetation type is kept constant. The effective surface roughness was found to decrease with increasing length scale of surface cover heterogeneity, which is shown to have a significant impact on estimated wind turbine power calculated from logarithmic wind profiles. In stable conditions, the blending height in cases with large heterogeneity length scales was found to exist well above the surface layer. Because the behavior of the blending height has implications for coupled models, a simple model for the blending height as a function of heterogeneity length scale is introduced.
Abstract
To characterize the effects of subgrid surface heterogeneity, the blending-height concept has been developed as a coupling strategy for surface parameterization schemes used in numerical weather prediction models. Previous modeling studies have tested this concept using stationary conditions with one-dimensional strips of surface roughness. Here, large-eddy simulations are used to examine the response of the blending height and effective surface roughness to tiled land-cover heterogeneity, or a two-dimensional chessboard pattern of alternating high and low vegetation given a diurnal cycle of solar irradiance in subarctic conditions. In each experiment, the length scale of the roughness elements is increased while the total domain fraction of each vegetation type is kept constant. The effective surface roughness was found to decrease with increasing length scale of surface cover heterogeneity, which is shown to have a significant impact on estimated wind turbine power calculated from logarithmic wind profiles. In stable conditions, the blending height in cases with large heterogeneity length scales was found to exist well above the surface layer. Because the behavior of the blending height has implications for coupled models, a simple model for the blending height as a function of heterogeneity length scale is introduced.
Abstract
We use dual-polarization C-band data collected in the Southern Ocean to examine the properties of snow observed during a voyage in the austral summer of 2018. Using existing forward modeling formalisms based on an assumption of Rayleigh scattering by soft spheroids, an optimal estimation algorithm is implemented to infer snow properties from horizontally polarized radar reflectivity, the differential radar reflectivity, and the specific differential phase. From the dual-polarization observables, we estimate ice water content qi , the mass-mean particle size Dm , and the exponent of the mass–dimensional relationship bm that, with several assumptions, allow for evaluation of snow bulk density, and snow number concentration. Upon evaluating the uncertainties associated with measurement and forward model errors, we determine that the algorithm can retrieve qi , Dm , and bm within single-pixel uncertainties conservatively estimated in the range 120%, 60%, and 40%, respectively. Applying the algorithm to open-cellular convection in the Southern Ocean, we find evidence for secondary ice formation processes within multicellular complexes. In stratiform precipitation systems we find snow properties and infer processes that are distinctly different from the shallow convective systems with evidence for riming and aggregation being common. We also find that embedded convection within the frontal system produces precipitation properties consistent with graupel. Examining 5 weeks of data, we show that snow in open-cellular cumulus has higher overall bulk density than snow in stratiform precipitation systems with implications for interpreting measurements from space-based active remote sensors.
Abstract
We use dual-polarization C-band data collected in the Southern Ocean to examine the properties of snow observed during a voyage in the austral summer of 2018. Using existing forward modeling formalisms based on an assumption of Rayleigh scattering by soft spheroids, an optimal estimation algorithm is implemented to infer snow properties from horizontally polarized radar reflectivity, the differential radar reflectivity, and the specific differential phase. From the dual-polarization observables, we estimate ice water content qi , the mass-mean particle size Dm , and the exponent of the mass–dimensional relationship bm that, with several assumptions, allow for evaluation of snow bulk density, and snow number concentration. Upon evaluating the uncertainties associated with measurement and forward model errors, we determine that the algorithm can retrieve qi , Dm , and bm within single-pixel uncertainties conservatively estimated in the range 120%, 60%, and 40%, respectively. Applying the algorithm to open-cellular convection in the Southern Ocean, we find evidence for secondary ice formation processes within multicellular complexes. In stratiform precipitation systems we find snow properties and infer processes that are distinctly different from the shallow convective systems with evidence for riming and aggregation being common. We also find that embedded convection within the frontal system produces precipitation properties consistent with graupel. Examining 5 weeks of data, we show that snow in open-cellular cumulus has higher overall bulk density than snow in stratiform precipitation systems with implications for interpreting measurements from space-based active remote sensors.
Abstract
This study evaluates an operational glaciogenic cloud-seeding program using ground-based generators of silver iodide (AgI), with a total of 190 seeded storms over 10 cold seasons, using the Weather Research and Forecasting Weather Modification (WRF-WxMod) scheme at 900-m grid spacing. This study examines both the quantitative change in precipitation and the ambient and cloud conditions impacting seeding efficacy. An ensemble approach is used, with differing model boundary conditions, ice nucleation physics, concentrations of cloud condensation nuclei, and boundary layer schemes. This is intended to provide an envelope of uncertainty of natural clouds and seeding impacts. The simulations are validated against radiosonde, snow gauge, and microwave radiometer observations, and the seeding impact is inferred from simulations with/without AgI seeding. The seeding-induced precipitation enhancement (“yield”) varies greatly between storms. A small portion of the cases produces the majority of the yield. Overall, the precipitation in the target area (the Wind River Range in Wyoming) increased by 1.10% ± 0.13% in the 10 years of operational seeding. This rather low fractional increase is related to the frequent seeding at unsuitable times, primarily because of low-level flow blocking. The flow and cloud structure for select cases are examined to provide better insight into the variability of yield. Cases with unblocked surface flow and abundant cloud liquid water tend to be the most productive. The technique presented here can be readily adapted to evaluate the seeding impact of other long-term glaciogenic seeding operations and to improve their operational efficiency.
Significance Statement
In the United States and elsewhere, there are several operational programs to enhance cold-season precipitation through glaciogenic seeding of orographic clouds. The impact of such activity on seasonal precipitation has always been difficult to quantify. Recent observational and numerical modeling studies indicate that orographic cloud seeding can increase precipitation, although the amounts and optimal seeding conditions remain uncertain. Operators lack guidance about the seeding efficacy and about the most suitable environmental conditions. In recent years a model parameterization, called Weather Research and Forecasting Weather Modification (WRF-WxMod), has been tested against detailed measurements. This sets the stage for our work, a well-designed numerical evaluation of 10 years of operational cloud seeding over the Wind River Range, a mountain range in Wyoming that feeds the Colorado River basin and other watersheds. The WRF-WxMod based simulation experiment presented here, one of the most computationally expensive numerical experiments on this subject to date, quantifies seeding impact and its uncertainty. It is demonstrated with a high degree of confidence that over this 10-yr period, suitable seeding conditions were rare over this mountain range, that most seeding events were unproductive, and that, as a result, the overall yield over 10 years was a mere 1.1%.
Abstract
This study evaluates an operational glaciogenic cloud-seeding program using ground-based generators of silver iodide (AgI), with a total of 190 seeded storms over 10 cold seasons, using the Weather Research and Forecasting Weather Modification (WRF-WxMod) scheme at 900-m grid spacing. This study examines both the quantitative change in precipitation and the ambient and cloud conditions impacting seeding efficacy. An ensemble approach is used, with differing model boundary conditions, ice nucleation physics, concentrations of cloud condensation nuclei, and boundary layer schemes. This is intended to provide an envelope of uncertainty of natural clouds and seeding impacts. The simulations are validated against radiosonde, snow gauge, and microwave radiometer observations, and the seeding impact is inferred from simulations with/without AgI seeding. The seeding-induced precipitation enhancement (“yield”) varies greatly between storms. A small portion of the cases produces the majority of the yield. Overall, the precipitation in the target area (the Wind River Range in Wyoming) increased by 1.10% ± 0.13% in the 10 years of operational seeding. This rather low fractional increase is related to the frequent seeding at unsuitable times, primarily because of low-level flow blocking. The flow and cloud structure for select cases are examined to provide better insight into the variability of yield. Cases with unblocked surface flow and abundant cloud liquid water tend to be the most productive. The technique presented here can be readily adapted to evaluate the seeding impact of other long-term glaciogenic seeding operations and to improve their operational efficiency.
Significance Statement
In the United States and elsewhere, there are several operational programs to enhance cold-season precipitation through glaciogenic seeding of orographic clouds. The impact of such activity on seasonal precipitation has always been difficult to quantify. Recent observational and numerical modeling studies indicate that orographic cloud seeding can increase precipitation, although the amounts and optimal seeding conditions remain uncertain. Operators lack guidance about the seeding efficacy and about the most suitable environmental conditions. In recent years a model parameterization, called Weather Research and Forecasting Weather Modification (WRF-WxMod), has been tested against detailed measurements. This sets the stage for our work, a well-designed numerical evaluation of 10 years of operational cloud seeding over the Wind River Range, a mountain range in Wyoming that feeds the Colorado River basin and other watersheds. The WRF-WxMod based simulation experiment presented here, one of the most computationally expensive numerical experiments on this subject to date, quantifies seeding impact and its uncertainty. It is demonstrated with a high degree of confidence that over this 10-yr period, suitable seeding conditions were rare over this mountain range, that most seeding events were unproductive, and that, as a result, the overall yield over 10 years was a mere 1.1%.
Abstract
This paper investigates the surface-layer processes associated with the morning transition from nighttime downslope winds to daytime upslope winds over a semi-isolated massif. It provides an insight into the characteristics of the transition and its connection with the processes controlling the erosion of the temperature inversion at the foot of the slope. First, a criterion for the identification of days prone to the development of purely thermally driven slope winds is proposed and adopted to select five representative case studies. Then, the mechanisms leading to different patterns of erosion of the nocturnal temperature inversion at the foot of the slope are analyzed. Three main patterns of erosion are identified: the first is connected to the growth of the convective boundary layer at the surface, the second is connected to the descent of the inversion top, and the third is a combination of the previous two. The first pattern is linked to the initiation of the morning transition through surface heating, and the second pattern is connected to the top-down dilution mechanism and so to mixing with the above air. The discriminating factor in the determination of the erosion pattern is identified in the partitioning of turbulent sensible heat flux at the surface.
Significance Statement
The purpose of this study is to improve our understanding of the thermally driven slope circulations with a focus on the unsteady processes associated with the morning transition and the erosion patterns of the nocturnal temperature inversion, so far in the literature less investigated and understood than the evening transition. Understanding this diurnal process will advance our abilities to model it and to improve the accuracy of weather forecasting in complex terrain.
Abstract
This paper investigates the surface-layer processes associated with the morning transition from nighttime downslope winds to daytime upslope winds over a semi-isolated massif. It provides an insight into the characteristics of the transition and its connection with the processes controlling the erosion of the temperature inversion at the foot of the slope. First, a criterion for the identification of days prone to the development of purely thermally driven slope winds is proposed and adopted to select five representative case studies. Then, the mechanisms leading to different patterns of erosion of the nocturnal temperature inversion at the foot of the slope are analyzed. Three main patterns of erosion are identified: the first is connected to the growth of the convective boundary layer at the surface, the second is connected to the descent of the inversion top, and the third is a combination of the previous two. The first pattern is linked to the initiation of the morning transition through surface heating, and the second pattern is connected to the top-down dilution mechanism and so to mixing with the above air. The discriminating factor in the determination of the erosion pattern is identified in the partitioning of turbulent sensible heat flux at the surface.
Significance Statement
The purpose of this study is to improve our understanding of the thermally driven slope circulations with a focus on the unsteady processes associated with the morning transition and the erosion patterns of the nocturnal temperature inversion, so far in the literature less investigated and understood than the evening transition. Understanding this diurnal process will advance our abilities to model it and to improve the accuracy of weather forecasting in complex terrain.
Abstract
This study quantifies the potential effect of the lee vortex on the fine particulate matter (PM2.5) pollution deterioration under the complex topography in Taiwan using observational data. We select the lee-vortex days that favor the development of the lee vortices in northwestern Taiwan under the southeasterly synoptic winds. We then define the enhancement index that discerns the areas with the high occurrence frequencies of the PM2.5 enhancement under the flow regime relative to the seasonal background concentrations. Under the lee-vortex days, the center of western Taiwan exhibits enhancement indices higher than 0.65. In addition, during the consecutive lee-vortex days, the index characterizes a northward shift in the PM2.5-enhanced areas under the subtle transition of the background wind directions. The areas with indices higher than 0.65 expand on the second day in northwestern Taiwan; the number of stations exhibiting indices higher than 0.8 increases by threefold from the first to the second day. The idealized numerical simulations using the Taiwan vector vorticity equation cloud-resolving model (TaiwanVVM) explicitly resolve the structures of leeside circulations and the associated pollutant transport, and their evolutions are highly sensitive to the background winds.
Significance Statement
Our study investigates the challenging question of local circulation patterns affected by mountain orography and the associated pollutant transport. We analyzed long-term balloon sounding and ground station observations to select the weather regime favoring the formation of lee vortices on Taiwan island. We then quantified the areas with a frequent enhancement of particulate pollutants. The long-term trend of the lee-vortex days exhibited a significant increase in the past decades. The pollution enhancement areas are highly consistent with the regions dominated by leeside local circulation. Together with the idealized high-resolution simulations, we identified that the detailed evolution of the lee vortices is highly sensitive to the subtle changes in background wind direction and hence the redistribution of local pollution.
Abstract
This study quantifies the potential effect of the lee vortex on the fine particulate matter (PM2.5) pollution deterioration under the complex topography in Taiwan using observational data. We select the lee-vortex days that favor the development of the lee vortices in northwestern Taiwan under the southeasterly synoptic winds. We then define the enhancement index that discerns the areas with the high occurrence frequencies of the PM2.5 enhancement under the flow regime relative to the seasonal background concentrations. Under the lee-vortex days, the center of western Taiwan exhibits enhancement indices higher than 0.65. In addition, during the consecutive lee-vortex days, the index characterizes a northward shift in the PM2.5-enhanced areas under the subtle transition of the background wind directions. The areas with indices higher than 0.65 expand on the second day in northwestern Taiwan; the number of stations exhibiting indices higher than 0.8 increases by threefold from the first to the second day. The idealized numerical simulations using the Taiwan vector vorticity equation cloud-resolving model (TaiwanVVM) explicitly resolve the structures of leeside circulations and the associated pollutant transport, and their evolutions are highly sensitive to the background winds.
Significance Statement
Our study investigates the challenging question of local circulation patterns affected by mountain orography and the associated pollutant transport. We analyzed long-term balloon sounding and ground station observations to select the weather regime favoring the formation of lee vortices on Taiwan island. We then quantified the areas with a frequent enhancement of particulate pollutants. The long-term trend of the lee-vortex days exhibited a significant increase in the past decades. The pollution enhancement areas are highly consistent with the regions dominated by leeside local circulation. Together with the idealized high-resolution simulations, we identified that the detailed evolution of the lee vortices is highly sensitive to the subtle changes in background wind direction and hence the redistribution of local pollution.
Abstract
Removing nonweather echoes is a critical component of the quality control (QC) chain used in the context of radar data assimilation for numerical weather prediction, quantitative precipitation estimation, and nowcasting applications. Recent studies show that using a simple QC method based on the depolarization ratio (DR) performs remarkably well in many situations. Nonetheless, this method may misclassify echoes in regions affected by nonuniform beamfilling or melting particles. This study presents an updated version of this QC used to remove nonweather echoes that uses the DR-based classification together with a set of physically based rules for correcting misclassifications of hail, nonuniform beamfilling, and melting particles. The potential of the new QC is evaluated using a continental-scale monitoring framework that compares the radar observations after QC with the precipitation occurrence derived from aviation routine weather reports (METARs). For this evaluation, the study uses the radar data and the METARs available over North America during the summer of 2019 and winter of 2020. In addition, the study demonstrates the usefulness of the monitoring framework to determine the optimal QC configuration. Some practical limitations of using the METAR-derived precipitation to assess radar data quality are also discussed.
Abstract
Removing nonweather echoes is a critical component of the quality control (QC) chain used in the context of radar data assimilation for numerical weather prediction, quantitative precipitation estimation, and nowcasting applications. Recent studies show that using a simple QC method based on the depolarization ratio (DR) performs remarkably well in many situations. Nonetheless, this method may misclassify echoes in regions affected by nonuniform beamfilling or melting particles. This study presents an updated version of this QC used to remove nonweather echoes that uses the DR-based classification together with a set of physically based rules for correcting misclassifications of hail, nonuniform beamfilling, and melting particles. The potential of the new QC is evaluated using a continental-scale monitoring framework that compares the radar observations after QC with the precipitation occurrence derived from aviation routine weather reports (METARs). For this evaluation, the study uses the radar data and the METARs available over North America during the summer of 2019 and winter of 2020. In addition, the study demonstrates the usefulness of the monitoring framework to determine the optimal QC configuration. Some practical limitations of using the METAR-derived precipitation to assess radar data quality are also discussed.
Abstract
The southern Great Plains (SGP) is defined by hydrometeorological swings between dry and wet extremes. These swings exacerbate the climatological gradients of moisture (from east to west) and temperature (from south to north), which can impact the agricultural production of the region. Thus, it is key to understand extremes to sustainably maintain agricultural success in the region. This study investigates the wet extremes, or extreme precipitation events, that have become more prominent in the last two decades. Data from 108 U.S. Historical Climatology Network stations were analyzed for the 1950–2020 period to detect changes in the frequency and magnitude of extreme precipitation events. Results show that changes in the magnitude of extreme precipitation are isolated and scattered across the SGP, with only the winter season showing regional shifts in extreme precipitation magnitude. Changes in the frequency of extreme precipitation events were noted across the entire SGP, although the changes in frequency are more notable in the eastern SGP than in the western SGP. Analysis shows that the increased number of events detected is driven more, but not exclusively, by the increasing spatial extent of individual extreme precipitation events than by an increased number of events. Overall, these results depict the changing nature of extreme precipitation within the SGP and differences in extreme precipitation between the eastern and western SGP.
Abstract
The southern Great Plains (SGP) is defined by hydrometeorological swings between dry and wet extremes. These swings exacerbate the climatological gradients of moisture (from east to west) and temperature (from south to north), which can impact the agricultural production of the region. Thus, it is key to understand extremes to sustainably maintain agricultural success in the region. This study investigates the wet extremes, or extreme precipitation events, that have become more prominent in the last two decades. Data from 108 U.S. Historical Climatology Network stations were analyzed for the 1950–2020 period to detect changes in the frequency and magnitude of extreme precipitation events. Results show that changes in the magnitude of extreme precipitation are isolated and scattered across the SGP, with only the winter season showing regional shifts in extreme precipitation magnitude. Changes in the frequency of extreme precipitation events were noted across the entire SGP, although the changes in frequency are more notable in the eastern SGP than in the western SGP. Analysis shows that the increased number of events detected is driven more, but not exclusively, by the increasing spatial extent of individual extreme precipitation events than by an increased number of events. Overall, these results depict the changing nature of extreme precipitation within the SGP and differences in extreme precipitation between the eastern and western SGP.
Abstract
In this study, the possible climate change impacts on irrigated corn production in the lower Mississippi delta (LMD) region were analyzed. The observed daily maximum and minimum air temperature, wind speed, relative humidity (RH), and precipitation from 1960 to 2018 were used in the analysis. The length of the growing season, evapotranspiration (ET), and crop yield estimates from the precalibrated Root Zone Water Quality Model (RZWQM) were also used. Trend analyses were performed on growing-season averages for temperature, RH, and wind speed; growing-season totals for precipitation and ET; daily values of minimum and maximum temperature; and averages of RH and wind speed at critical corn growth stages. The last day of spring freezing (LDSF) and days with an average daily air temperature Ta of more than 35°C during corn silking were also included in the analysis. The trend analysis was performed using the modified Mann–Kendall test, Pettitt test, and Sen’s slope at a significance level of p ≤ 0.05. The results from our study pointed out increases in minimum Ta , increases in the number of days with Ta exceeding 35°C during the corn silking stage, increases in RH and decreases in ET, advancement of the LDSF by 2 weeks, and 8% reductions in corn yield that could be attributed to changes in climate. If the observed trends in climate (climate variability and change) and yield reductions continue in the region, it could be challenging to grow the corn crop in the LMD profitably.
Significance Statement
In recent years, growing corn and soybeans instead of cotton has been gaining popularity in the lower Mississippi delta (LMD) region. Our study is aimed to understand how climate change in the recent past (1960–2018) has affected irrigated corn production in LMD. This will help us to better understand the expected consequences of the future climate. We used observations of daily weather data from 1960 to 2018 and corn yield, water balance, and crop yield results from a computer model designed to simulate corn production. Tools were used to analyze trends and patterns in the data and results. Our analysis pointed out significant changes in weather, water balance, and yield decline for irrigated corn in the LMD.
Abstract
In this study, the possible climate change impacts on irrigated corn production in the lower Mississippi delta (LMD) region were analyzed. The observed daily maximum and minimum air temperature, wind speed, relative humidity (RH), and precipitation from 1960 to 2018 were used in the analysis. The length of the growing season, evapotranspiration (ET), and crop yield estimates from the precalibrated Root Zone Water Quality Model (RZWQM) were also used. Trend analyses were performed on growing-season averages for temperature, RH, and wind speed; growing-season totals for precipitation and ET; daily values of minimum and maximum temperature; and averages of RH and wind speed at critical corn growth stages. The last day of spring freezing (LDSF) and days with an average daily air temperature Ta of more than 35°C during corn silking were also included in the analysis. The trend analysis was performed using the modified Mann–Kendall test, Pettitt test, and Sen’s slope at a significance level of p ≤ 0.05. The results from our study pointed out increases in minimum Ta , increases in the number of days with Ta exceeding 35°C during the corn silking stage, increases in RH and decreases in ET, advancement of the LDSF by 2 weeks, and 8% reductions in corn yield that could be attributed to changes in climate. If the observed trends in climate (climate variability and change) and yield reductions continue in the region, it could be challenging to grow the corn crop in the LMD profitably.
Significance Statement
In recent years, growing corn and soybeans instead of cotton has been gaining popularity in the lower Mississippi delta (LMD) region. Our study is aimed to understand how climate change in the recent past (1960–2018) has affected irrigated corn production in LMD. This will help us to better understand the expected consequences of the future climate. We used observations of daily weather data from 1960 to 2018 and corn yield, water balance, and crop yield results from a computer model designed to simulate corn production. Tools were used to analyze trends and patterns in the data and results. Our analysis pointed out significant changes in weather, water balance, and yield decline for irrigated corn in the LMD.
