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- Author or Editor: N. Balakrishnan x
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Abstract
Precipitation comprising rain and hail is studied. Specifically, techniques to identify and quantify such precipitation in terms of rain and hail fall rates using dual polarized radar data, are presented. Included for consideration are Z H, the reflectivity factor for horizontal polarization, Z DR, the differential reflectivity, and K DP, the differential propagation constant. A variety of simple models of mixed-phase precipitation are first examined. Electromagnetic scattering computations are performed to simulate and study the behavior of Z H, Z DR, and K DP. It is shown that it is possible to distinguish the mixed-phase precipitation from either rain or hail by using Z H, K DP pair and also to infer the thermodynamic phase and orientation from Z H, Z DR pair. On the basis of physical principles, it is shown that K DP senses primarily liquid water in the form of raindrops even when these are mixed with hailstones. The self-consistency Of Z H, Z DR, and K DP is then exploited to estimate both the rain and hail fall rates. The ability of the methods to estimate rain and hail fall rates is demonstrated with actual radar data from two Oklahoma storms.
Abstract
Precipitation comprising rain and hail is studied. Specifically, techniques to identify and quantify such precipitation in terms of rain and hail fall rates using dual polarized radar data, are presented. Included for consideration are Z H, the reflectivity factor for horizontal polarization, Z DR, the differential reflectivity, and K DP, the differential propagation constant. A variety of simple models of mixed-phase precipitation are first examined. Electromagnetic scattering computations are performed to simulate and study the behavior of Z H, Z DR, and K DP. It is shown that it is possible to distinguish the mixed-phase precipitation from either rain or hail by using Z H, K DP pair and also to infer the thermodynamic phase and orientation from Z H, Z DR pair. On the basis of physical principles, it is shown that K DP senses primarily liquid water in the form of raindrops even when these are mixed with hailstones. The self-consistency Of Z H, Z DR, and K DP is then exploited to estimate both the rain and hail fall rates. The ability of the methods to estimate rain and hail fall rates is demonstrated with actual radar data from two Oklahoma storms.
Abstract
We examine the utility of the correlation coefficient between linear orthogonally polarized echoes for determining precipitation type and gauging hail size. Models and measurements from pure rain coincide in predicting very high correlations (0.98); similar results are obtained with pure hail. Several mechanisms could cause the lowering of correlation but the behavior of the examined data is definitely attributed to a mixture of hydrometeor types. This decrease is an indicator of hail size; it is shown theoretically that in at least two other realistic situations the correlation would decrease with hail size. For the examined case a model of hail shape and orientation during fall is able to reproduce the essential features of polarimetric measurements. It suggests, together with our data and data from other investigators, that substantial negative differential reflectivity (about −1 dB) in a region of high reflectivity factor values is caused by hailstones larger than about 2 cm in diameter.
Abstract
We examine the utility of the correlation coefficient between linear orthogonally polarized echoes for determining precipitation type and gauging hail size. Models and measurements from pure rain coincide in predicting very high correlations (0.98); similar results are obtained with pure hail. Several mechanisms could cause the lowering of correlation but the behavior of the examined data is definitely attributed to a mixture of hydrometeor types. This decrease is an indicator of hail size; it is shown theoretically that in at least two other realistic situations the correlation would decrease with hail size. For the examined case a model of hail shape and orientation during fall is able to reproduce the essential features of polarimetric measurements. It suggests, together with our data and data from other investigators, that substantial negative differential reflectivity (about −1 dB) in a region of high reflectivity factor values is caused by hailstones larger than about 2 cm in diameter.
Abstract
The reflectivity factor (Z), rainfall rate (R) relationship for weather radars that probe precipitation at low elevation angles is sensitive to polarization. It is shown how to transform a relation that is valid with one polarization (vertical, horizontal or circular) to relations that are applicable to the other two polarizations. We present errors that occur if the transformations are not applied, and an example from literature in which two seemingly different Z, R relations are equivalent, tied by the polarization transformation.
Abstract
The reflectivity factor (Z), rainfall rate (R) relationship for weather radars that probe precipitation at low elevation angles is sensitive to polarization. It is shown how to transform a relation that is valid with one polarization (vertical, horizontal or circular) to relations that are applicable to the other two polarizations. We present errors that occur if the transformations are not applied, and an example from literature in which two seemingly different Z, R relations are equivalent, tied by the polarization transformation.
Abstract
Parts I and II of this three part paper dealt with the error structure of differential reflectivity and X-band specific attenuation in rainfall as estimated by radar and surface disdrometers. In this Part III paper we focus on the error structure of the specific differential phase (K DP, °km−1) measurement in rainfall. This allows us to analyze three estimators of rainfall rate, the first based on the reflectivity factor Z H , the second based on combining reflectivity and Z DR, [R(Z H , Z DR)], and the third based on K DP alone, R(K DP). Simulations are used to model random errors in Z H , Z DR and K DP. Physical variations in the raindrop size distribution (RSD) are modeled by varying the gamma parameters (N 0, D 0, m) over a range typically found in natural rainfall. Thus, our simulations incorporate physical fluctuations onto which random measurement errors have been superimposed. Radar-derived estimates of R(Z H , Z DR) and R(K DP) have been intercompared using data obtained in convective rainfall with the NSSL Cimarron radar and the NCAR/CP-2 radar. As practical application of the analysis presented here, we have determined the range of applicability of the three rainfall rate estimators: R(Z H ), R(Z H , Z DR) and R(K DP). Our simulations show that when the rainfall rate exceeds about 70 mm h−1, R(K DP) performs better than R(Z H , Z DR). This result is valid over a 1 km propagation path. At intermediate rainfall rates around 20 ≲R ≲70 mm h−1, our simulations show that R(Z H , Z DR) gives the least error. However, there are other reasons which make R(K DP) useful; i.e., (i) its stability with respect to mixed phase precipitation, and (ii) the fact that it is a differential phase measurement and thus insensitive to system gain calibration. This last premise suggests an accurate method of system gain calibration based on the rain medium.
Abstract
Parts I and II of this three part paper dealt with the error structure of differential reflectivity and X-band specific attenuation in rainfall as estimated by radar and surface disdrometers. In this Part III paper we focus on the error structure of the specific differential phase (K DP, °km−1) measurement in rainfall. This allows us to analyze three estimators of rainfall rate, the first based on the reflectivity factor Z H , the second based on combining reflectivity and Z DR, [R(Z H , Z DR)], and the third based on K DP alone, R(K DP). Simulations are used to model random errors in Z H , Z DR and K DP. Physical variations in the raindrop size distribution (RSD) are modeled by varying the gamma parameters (N 0, D 0, m) over a range typically found in natural rainfall. Thus, our simulations incorporate physical fluctuations onto which random measurement errors have been superimposed. Radar-derived estimates of R(Z H , Z DR) and R(K DP) have been intercompared using data obtained in convective rainfall with the NSSL Cimarron radar and the NCAR/CP-2 radar. As practical application of the analysis presented here, we have determined the range of applicability of the three rainfall rate estimators: R(Z H ), R(Z H , Z DR) and R(K DP). Our simulations show that when the rainfall rate exceeds about 70 mm h−1, R(K DP) performs better than R(Z H , Z DR). This result is valid over a 1 km propagation path. At intermediate rainfall rates around 20 ≲R ≲70 mm h−1, our simulations show that R(Z H , Z DR) gives the least error. However, there are other reasons which make R(K DP) useful; i.e., (i) its stability with respect to mixed phase precipitation, and (ii) the fact that it is a differential phase measurement and thus insensitive to system gain calibration. This last premise suggests an accurate method of system gain calibration based on the rain medium.
Abstract
Propagation effects in rainfall are examined at three microwave frequencies corresponding to S (3.0 GHz), C (5.5 GHz), and X (10.0 GHz) bands. Attenuation at horizontal polarization, as well as differential attenuation and differential propagation phase between horizontal (H) and vertical (V) polarizations are considered. It is shown that at the three frequencies both attenuation and differential attenuation are nearly linearly related to differential propagation phase (ϕDP). This is shown through simulation using (a) gamma raindrop size distributions (RSD) with three parameters (N 0, D 0, m) that are varied over a very wide range representing a variety of rainfall types, and (b) measured raindrop size distributions at a single location using a disdrometer. Measurements of X-band specific attenuation and S-band specific differential phase in convective rainshafts using the National Center for Atmospheric Research CP-2 radar are presented in order to experimentally demonstrate the linear relationship between attenuation and differential propagation phase. Correction procedures for reflectivity and differential reflectivity (Z DR) are developed assuming that differential propagation phase is measured using a radar that alternately transmits H and V polarized waves with copolar reception through the same receiver and processor system. The correction procedures are not dependent on the actual rainrate profile between the radar and the range location of interest. The accuracy of the procedure depends on, (a) RSD fluctuations, (b) variability in the estimate of differential propagation phase due to measurement fluctuations, and (c) nonzero values of the backscatter differential phase (δ) between H and V polarizations. Simulations are used to gauge the accuracy of correction procedures at S- and C-bands assuming δ is negligible. The correction accuracy for attentuation at S-band is estimated to be ∼0.05 dB while at C-band it is estimated to be within 1 dB if ϕDP≲60°. Simulations further indicate that C-band differential attenuations effects can be corrected to within ∼35% of the mean value.
Abstract
Propagation effects in rainfall are examined at three microwave frequencies corresponding to S (3.0 GHz), C (5.5 GHz), and X (10.0 GHz) bands. Attenuation at horizontal polarization, as well as differential attenuation and differential propagation phase between horizontal (H) and vertical (V) polarizations are considered. It is shown that at the three frequencies both attenuation and differential attenuation are nearly linearly related to differential propagation phase (ϕDP). This is shown through simulation using (a) gamma raindrop size distributions (RSD) with three parameters (N 0, D 0, m) that are varied over a very wide range representing a variety of rainfall types, and (b) measured raindrop size distributions at a single location using a disdrometer. Measurements of X-band specific attenuation and S-band specific differential phase in convective rainshafts using the National Center for Atmospheric Research CP-2 radar are presented in order to experimentally demonstrate the linear relationship between attenuation and differential propagation phase. Correction procedures for reflectivity and differential reflectivity (Z DR) are developed assuming that differential propagation phase is measured using a radar that alternately transmits H and V polarized waves with copolar reception through the same receiver and processor system. The correction procedures are not dependent on the actual rainrate profile between the radar and the range location of interest. The accuracy of the procedure depends on, (a) RSD fluctuations, (b) variability in the estimate of differential propagation phase due to measurement fluctuations, and (c) nonzero values of the backscatter differential phase (δ) between H and V polarizations. Simulations are used to gauge the accuracy of correction procedures at S- and C-bands assuming δ is negligible. The correction accuracy for attentuation at S-band is estimated to be ∼0.05 dB while at C-band it is estimated to be within 1 dB if ϕDP≲60°. Simulations further indicate that C-band differential attenuations effects can be corrected to within ∼35% of the mean value.
Abstract
Disdrometer data collected during three spring days, with moderate to heavy rain in the Norman, Oklahoma region are used with various polarimetric radar algorithms to simulate rain rates. It is assumed that available measurables are 1) reflectivity at horizontal polarization, Z H , 2) differential reflectivity, Z DR (ratio of horizontal to vertical reflectivity factors in dB), and 3) differential propagation constant, K DP . The accuracies of the simulated rain rates from Z H , Z DR , and K DP are evaluated and compared. A new algorithm that utilizes both reflectivity factor and differential propagation constant is also examined. In comparing the relative accuracies, the disdrometer-derived rain rates are assumed to be the “truth” measurements.
Abstract
Disdrometer data collected during three spring days, with moderate to heavy rain in the Norman, Oklahoma region are used with various polarimetric radar algorithms to simulate rain rates. It is assumed that available measurables are 1) reflectivity at horizontal polarization, Z H , 2) differential reflectivity, Z DR (ratio of horizontal to vertical reflectivity factors in dB), and 3) differential propagation constant, K DP . The accuracies of the simulated rain rates from Z H , Z DR , and K DP are evaluated and compared. A new algorithm that utilizes both reflectivity factor and differential propagation constant is also examined. In comparing the relative accuracies, the disdrometer-derived rain rates are assumed to be the “truth” measurements.
Abstract
This study explores the utility of polarimetric measurements for discriminating between hydrometeor types with the emphasis on (a) hail detection and discrimination of its size, (b) measurement of heavy precipitation, (c) identification and quantification of mixed-phase hydrometeors, and (d) discrimination of ice forms. In particular, we examine the specific differential phase, the backscatter differential phase, the correlation coefficient between vertically and horizontally polarized waves, and the differential reflectivity, collected from a storm at close range. Three range–height cross sections are analyzed together with complementary data from a prototype WSR-88D radar. The case is interesting because it demonstrates the complementary nature of these polarimetric measurands. Self-consistency among them allows qualitative and some quantitative discrimination between hydrometeors.
Abstract
This study explores the utility of polarimetric measurements for discriminating between hydrometeor types with the emphasis on (a) hail detection and discrimination of its size, (b) measurement of heavy precipitation, (c) identification and quantification of mixed-phase hydrometeors, and (d) discrimination of ice forms. In particular, we examine the specific differential phase, the backscatter differential phase, the correlation coefficient between vertically and horizontally polarized waves, and the differential reflectivity, collected from a storm at close range. Three range–height cross sections are analyzed together with complementary data from a prototype WSR-88D radar. The case is interesting because it demonstrates the complementary nature of these polarimetric measurands. Self-consistency among them allows qualitative and some quantitative discrimination between hydrometeors.
Abstract
Four polarimetric measurands were collected in the stratiform region of a mesoscale convective system. The four are the reflectivity factor, the differential reflectivity, the correlation coefficient between orthogonal copolar echoes, and the differential propagation constant. Most striking is a signature of large aggregates (about 10 mm in size) seen in the differential phase through the melting layer. Another significant feature is an abrupt notch in the correlation coefficient that occurs towards the bottom of the bright band. Aircraft observations and a one-dimensional cloud model are used to explain some polarimetric measurements and to infer the presence of aggregates, graupel, and supercooled cloud water in the stratiform region. These unique observations and model data provide inferences concerning the presence of graupel and the growth of large aggregates in the melting layer.
Abstract
Four polarimetric measurands were collected in the stratiform region of a mesoscale convective system. The four are the reflectivity factor, the differential reflectivity, the correlation coefficient between orthogonal copolar echoes, and the differential propagation constant. Most striking is a signature of large aggregates (about 10 mm in size) seen in the differential phase through the melting layer. Another significant feature is an abrupt notch in the correlation coefficient that occurs towards the bottom of the bright band. Aircraft observations and a one-dimensional cloud model are used to explain some polarimetric measurements and to infer the presence of aggregates, graupel, and supercooled cloud water in the stratiform region. These unique observations and model data provide inferences concerning the presence of graupel and the growth of large aggregates in the melting layer.
Abstract
Ocean State Forecasts contribute to safe and sustainable fishing in India, but their usage among artisanal fishers is often limited. Our research in Thiruvananthapuram district in the southern Indian state of Kerala tested forecast quality and value and how fishers engage with forecasts. In two fishing villages, we verified forecast accuracy, skill, and reliability by comparing forecasts with observations during the 2018 monsoon season (June–September; n = 122). We assessed forecast value by analyzing fishers’ perceptions of weather and risks and the way they used forecasts based on 8 focus group discussions, 20 interviews, conversations, and logs of 10 fishing boats. We find that while forecasts are mostly accurate, inadequate forecasting of unusual events (e.g., wind >45 km h−1) and frequent fishing restrictions (n = 32) undermine their value. Fishers seek more localized and detailed forecasts, but they do not always use them. Weather forecasts are just one of the tools artisanal fishers deploy, used not simply to decide as to whether to go to sea but also to manage potential risks, allowing them to prepare for fishing under hazardous conditions. Their decisions are also based on the availability of fish and their economic needs. From our findings, we suggest that political, economic, and social marginality of south Indian fishers influences their perceptions and responses to weather-related risks. Therefore, improving forecast usage requires not only better forecast skill and wide dissemination of tailor-made weather information, but also better appreciation of risk cultures and the livelihood imperatives of artisanal fishing communities.
Abstract
Ocean State Forecasts contribute to safe and sustainable fishing in India, but their usage among artisanal fishers is often limited. Our research in Thiruvananthapuram district in the southern Indian state of Kerala tested forecast quality and value and how fishers engage with forecasts. In two fishing villages, we verified forecast accuracy, skill, and reliability by comparing forecasts with observations during the 2018 monsoon season (June–September; n = 122). We assessed forecast value by analyzing fishers’ perceptions of weather and risks and the way they used forecasts based on 8 focus group discussions, 20 interviews, conversations, and logs of 10 fishing boats. We find that while forecasts are mostly accurate, inadequate forecasting of unusual events (e.g., wind >45 km h−1) and frequent fishing restrictions (n = 32) undermine their value. Fishers seek more localized and detailed forecasts, but they do not always use them. Weather forecasts are just one of the tools artisanal fishers deploy, used not simply to decide as to whether to go to sea but also to manage potential risks, allowing them to prepare for fishing under hazardous conditions. Their decisions are also based on the availability of fish and their economic needs. From our findings, we suggest that political, economic, and social marginality of south Indian fishers influences their perceptions and responses to weather-related risks. Therefore, improving forecast usage requires not only better forecast skill and wide dissemination of tailor-made weather information, but also better appreciation of risk cultures and the livelihood imperatives of artisanal fishing communities.
Abstract
Ocean state forecast (OSF) along ship routes (OAS) is an advisory service of the Indian National Centre for Ocean Information Services (INCOIS) of the Earth System Science Organization (ESSO) that helps mariners to ensure safe navigation in the Indian Ocean in all seasons as well as in extreme conditions. As there are many users who solely depend on this service for their decision making, it is very important to ensure the reliability and accuracy of the service using the available in situ and satellite observations. This study evaluates the significant wave height (Hs) along the ship track in the Indian Ocean using the ship-mounted wave height meter (SWHM) on board the Oceanographic Research Vessel Sagar Nidhi, and the Cryosat-2 and Jason altimeters. Reliability of the SWHM is confirmed by comparing with collocated buoy and altimeter observations. The comparison along the ship routes using the SWHM shows very good agreement (correlation coefficient > 0.80) in all three oceanic regimes, [the tropical northern Indian Ocean (TNIO), the tropical southern Indian Ocean (TSIO), and extratropical southern Indian Ocean (ETSI)] with respect to the forecasts with a lead time of 48 h. However, the analysis shows ~10% overestimation of forecasted significant wave height in the low wave heights, especially in the TNIO. The forecast is found very reliable and accurate for the three regions during June–September with a higher correlation coefficient (average = 0.88) and a lower scatter index (average = 15%). During other months, overestimation (bias) of lower Hs is visible in the TNIO.
Abstract
Ocean state forecast (OSF) along ship routes (OAS) is an advisory service of the Indian National Centre for Ocean Information Services (INCOIS) of the Earth System Science Organization (ESSO) that helps mariners to ensure safe navigation in the Indian Ocean in all seasons as well as in extreme conditions. As there are many users who solely depend on this service for their decision making, it is very important to ensure the reliability and accuracy of the service using the available in situ and satellite observations. This study evaluates the significant wave height (Hs) along the ship track in the Indian Ocean using the ship-mounted wave height meter (SWHM) on board the Oceanographic Research Vessel Sagar Nidhi, and the Cryosat-2 and Jason altimeters. Reliability of the SWHM is confirmed by comparing with collocated buoy and altimeter observations. The comparison along the ship routes using the SWHM shows very good agreement (correlation coefficient > 0.80) in all three oceanic regimes, [the tropical northern Indian Ocean (TNIO), the tropical southern Indian Ocean (TSIO), and extratropical southern Indian Ocean (ETSI)] with respect to the forecasts with a lead time of 48 h. However, the analysis shows ~10% overestimation of forecasted significant wave height in the low wave heights, especially in the TNIO. The forecast is found very reliable and accurate for the three regions during June–September with a higher correlation coefficient (average = 0.88) and a lower scatter index (average = 15%). During other months, overestimation (bias) of lower Hs is visible in the TNIO.
