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The recent development of satellite products for observing precipitation based on different technologies (microwaves, infrared, etc.) allows for near-real-time meteorological studies. The purpose of this article is to evaluate 11 satellite products (GHE, PDIR, IMERG-Early v6, IMERG-Late v6, CMORPH v0.x, CMORPH-RT v0.x, GSMaP-NRT v7, GSMaP-NRT-GC v7, GSMaP-NOW v7, GSMaP-NOW-GC v7, and DATABOURG) currently available and compare them to 2 ground-based radar networks (PANTHERE and OPERA) and the French rain-gauge network RADOME. Two case studies of intense precipitation over France (22 to 25 April 2022 and 24 to 29 June 2022) were selected. The radar estimations are closer to the RADOME observations than the satellite-based estimations, which tend to globally underestimate the precipitation amounts over the areas of interest while OPERA tends to strongly overestimate precipitation amounts during the June case study. The PANTHERE radar product and the carrier-to-noise product DATABOURG shows promising results. Near-real-time satellite products tend to have closer precipitation amounts to the reference dataset than satellite products with a shorter latency. The use of these datasets for nowcasting developments is plausible but further analyses must be conducted beforehand. [ABSTRACT FROM AUTHOR]

The measurement of global precipitation is important for quantifying and understanding the Earth's systems. While gauges form the basis of conventional measurements, global measurements are only truly possible using satellite observations. Over the last 50–60 years, satellite systems have evolved to provide a comprehensive suite of observing systems, including many sensors that are capable of precipitation retrievals. While much progress has been made in developing and implementing precipitation retrieval schemes, many techniques have concentrated upon retrievals over regions with well-defined precipitation systems, such as the tropics. At higher latitudes, such retrieval schemes are less successful in providing accurate and consistent precipitation estimates, especially due to the large diversity of precipitation regimes. Furthermore, the increasing dominance of snowfall at higher latitudes imposes a number of challenges that require further, urgent work. This paper reviews the state of the current observations and retrieval schemes, highlighting the key factors that need to be addressed to improve the estimation and measurement of precipitation at mid-to-high latitudes. [ABSTRACT FROM AUTHOR]

Two approaches were designed to identify the echoes of clear air and precipitation when both coexist in the very-high-frequency (VHF) radar spectra: contour-based and peak-finding methods. The contour-based approach was used to model a 2D Doppler spectra to determine the locations of multiple spectral humps, and the peak-finding approach was used to find the spectral peaks on request. Grouping, sifting, and Gaussian fitting were performed further for such obtained contour centres and spectral peaks to yield Doppler velocities and spectral widths. In general, the two approaches resulted in corresponding outcomes and can be complementary to find the spectral peaks as fully as possible. The Doppler velocities retrieved from the two approaches were cooperatively used to develop an effective process of Doppler profiling for treating a great amount of radar data, which was validated with the radar data collected during a rainy and strongly convective atmosphere. As an application of Doppler profiling results, the hydrometeor parameters measured by a dual-polarized microwave radiometer were investigated jointly with radar observation, showing that a strong updraft air could bring the liquid water to a height above the melting layer and then the Bergeron effect and coalescence processes on formation of ice crystals and graupel particles occur accordingly. [ABSTRACT FROM AUTHOR]

Topography has an important role in shaping regional and global climate systems, as it acts as a mechanical barrier to the low-level moisture flow. Thus, a complex spatial pattern of rainfall can exist over the mountainous region. Moreover, it is critical to advance our understanding of the relationship between rainfall and topography in terms of rainfall timing, frequency, and magnitude. In this study, characteristics of austral summer (December–February) precipitation are analyzed using 17-year (1998–2014) high-spatial-resolution (0.05° × 0.05°) data obtained from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) over the Andean region focusing on topographic impact. We observe an interaction between precipitation patterns and topography, with clear precipitation–elevation relationships in the Andes regions. The rainfall maxima zone was observed over the higher terrain of the central and southern Andes, and the zone is attributed to frequency and intensity of rainfall, respectively. In the foothills of the central Andes, we find there was a persistent rain system when a moist, low-level flow was lifted due to topography. In contrast, steep mountain slopes and a relatively dry atmosphere modulate deep convection in the foothills of southern Andes.

Understanding and forecasting hurricanes remains a challenge for the operational and research communities. To accurately predict the Tropical Cyclone (TC) evolution requires properly reflecting the storm’s inner core dynamics by using: (i) high-resolution models; (ii) realistic physical parameterizations. The microphysical processes and their representation in cloud-permitting models are of crucial importance. In particular, the assumed Particle Size Distribution (PSD) functions affect nearly all formulated microphysical processes and are among the most fundamental assumptions in the bulk microphysics schemes. This paper analyzes the impact of the PSD assumptions on simulated hurricanes and their synthetic radiometric signatures. It determines the most realistic, among the available set of assumptions, based on comparison to multi-parameter satellite observations. Here we simulated 2005′s category-5 Hurricane Rita using the cloud-permitting community Weather Research and Forecasting model (WRF) with two different microphysical schemes and with seven different modifications of the parametrized hydrometeor properties within one of the two schemes. We then used instrument simulators to produce satellite-like observations. The study consisted in evaluating the structure of the different simulated storms by comparing, for each storm, the calculated microwave signatures with actual satellite observations made by (a) the passive microwave radiometer that was carried by the Tropical Rainfall Measuring Mission (TRMM) satellite—the TRMM microwave imager TMI, (b) TRMM’s precipitation radar (PR) and (c) the ocean-wind-vector scatterometer carried by the QuikSCAT satellite. The analysis reveals that the different choices of microphysical parameters do produce significantly different microwave signatures, allowing an objective determination of a “best” parameter combination whose resulting signatures are collectively most consistent with the wind and precipitation observations obtained from the satellites. In particular, we find that assuming PSDs with larger number of smaller hydrometeors produces storms that compare best to observations.

The modern era of polarimetric radar begins with radiowave propagation research starting in the early 1970s with applications to measurement and modeling of wave attenuation in rain and depolarization due to ice particles along satellite−earth links. While there is a rich history of radar in meteorology after World War II, the impetus provided by radiowave propagation requirements led to high-quality antennas and feeds. Our journey starts by describing the key institutions and personnel responsible for development of weather radar polarimetry. The early period was dominated by circularly polarized radars for propagation research and at S band (frequency near 3 GHz) for hail detection. By the mid to late 70s, a paradigm shift occurred which led to the dominance of linear polarizations with applications to slant path attenuation prediction as well as estimation of rain rates and inferences of precipitation physics. The period from the early 1980s to 1995 can be considered as the “golden” period of rapid research that brought in meteorologists, cloud physicists, and hydrologists. This article describes the evolution of this technology from the vantage point of the authors. Their personal reflections and “behind the scenes” descriptions offer a glimpse into the inner workings at several key institutions which cannot be found elsewhere.

In the French Alps the quality of the radar Quantitative Precipitation Estimation (QPE) is limited by the topography and the vertical structure of precipitation. A previous study realized in all the French Alps, has shown a general bias between values of the national radar QPE composite and the rain gauge measurements: a radar QPE over-estimation at low altitude (+20% at 200 m a.s.l.), and an increasing underestimation at high altitudes (until −40% at 2100 m a.s.l.). This trend has been linked to altitudinal gradients of precipitation observed at ground level. This paper analyzes relative altitudinal gradients of precipitation estimated with rain gauges measurements in 2016 for three massifs around Grenoble, and for different temporal accumulations (yearly, seasonal, monthly, daily). Comparisons of radar and rain gauge accumulations confirm the bias previously observed. The parts of the current radar data processing affecting the bias value are pointed out. The analysis shows a coherency between the relative gradient values estimated at the different temporal accumulations. Vertical profiles of precipitation detected by a research radar installed at the bottom of the valley also show how the wide horizontal variability of precipitation inside the valley can affect the gradient estimation.

Hubei Province Region (HPR), located in Central China, is a concentrated area of severe convective weather. Three severe convective processes occurred in HPR were selected, namely 14−15 May 2015 (Case 1), 6−7 July 2013 (Case 2), and 11−12 September 2014 (Case 3). In order to investigate the differences between the three cases, the temporal and spatial distribution characteristics of cloud−ground lightning (CG) flashes and precipitation, the distribution of radar parameters, and the evolution of cloud environment characteristics (including water vapor (VD), liquid water content (LWC), relative humidity (RH), and temperature) were compared and analyzed by using the data of lightning locator, S-band Doppler radar, ground-based microwave radiometer (MWR), and automatic weather stations (AWS) in this study. The results showed that 80% of the CG flashes had an inverse correlation with the spatial distribution of heavy rainfall, 28.6% of positive CG (+CG) flashes occurred at the center of precipitation (>30 mm), and the percentage was higher than that of negative CG (−CG) flashes (13%). Moreover, the quantity of thunderstorm cells in Case 1 was more than other cases, the peak time of +CG flashes was prior to that of total CG flashes in Case 2 and Case 3, and the time of +CG flashes’ peak in Case 2 was prior to that of precipitation at about 2 h. Based on the analysis of the cloud environment, there are three main reasons for the differences of CG flashes and precipitation. Firstly, the structure of the LWC vertical profile and the height of the LWC peak are different, and high LWC makes it difficult for the collision of ice particles to generate electricity. Secondly, the differences between convective available potential energy (CAPE), precipitation, and CG flashes is caused by the sudden increase of VD from 1.5 km to 3 km, and thirdly, the production of CG flashes is very sensitive to RH at the surface layer and the total CG flashes increase as the RH increasing.

Vertical variability in the raindrop size distribution (RSD) can disrupt the basic assumption of a constant rain profile that is customarily parameterized in radar-based quantitative precipitation estimation (QPE) techniques. This study investigates the utility of melting layer (ML) characteristics to help prescribe the RSD, in particular the mass-weighted mean diameter (Dm), of stratiform rainfall. We utilize ground-based polarimetric radar to map the ML and compare it with Dm observations from the ground upwards to the bottom of the ML. The results show definitive proof that a thickening, and to a lesser extent a lowering, of the ML causes an increase in raindrop diameter below the ML that extends to the surface. The connection between rainfall at the ground and the overlying microphysics in the column provide a means for improving radar QPE at far distances from a ground-based radar or close to the ground where satellite-based radar rainfall retrievals can be ill-defined.

Topography has an important role in shaping regional and global climate systems, as it acts as a mechanical barrier to the low-level moisture flow. Thus, a complex spatial pattern of rainfall can exist over the mountainous region. Moreover, it is critical to advance our understanding of the relationship between rainfall and topography in terms of rainfall timing, frequency, and magnitude. In this study, characteristics of austral summer (December–February) precipitation are analyzed using 17-year (1998–2014) high-spatial-resolution (0.05° × 0.05°) data obtained from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) over the Andean region focusing on topographic impact. We observe an interaction between precipitation patterns and topography, with clear precipitation–elevation relationships in the Andes regions. The rainfall maxima zone was observed over the higher terrain of the central and southern Andes, and the zone is attributed to frequency and intensity of rainfall, respectively. In the foothills of the central Andes, we find there was a persistent rain system when a moist, low-level flow was lifted due to topography. In contrast, steep mountain slopes and a relatively dry atmosphere modulate deep convection in the foothills of southern Andes. [ABSTRACT FROM AUTHOR]

In this study, an investigation of a new thunderstorm intensity index (TSII) derived from lightning data is performed, along with its relationship to rain, wind, hail and waterspouts as well as instability indices (CAPE, LI, KI, and DLS). The study area is located in the northeastern Adriatic and includes various terrain types in a relatively small area (coastal, flatlands, hills and valleys, and mountain regions). The investigated period covers 11 years (2008–2018). The mathematical algorithm standing behind the TSII is based on the well-established methodology of lightning jump, allowing us to recognize areas where intensification in thunderstorms occurred. Our results suggest that these areas (with a positive TSII) experience significantly higher rain intensities and have higher total amounts of precipitation compared with areas where thunderstorms did not generate a TSII. Moreover, 76% of thunderstorm hail cases were associated with the presence of a TSII within a 15 km distance. The maximum reported wind speed also has higher values on a day with a TSII. Out of 27 waterspout events associated with lightning, 77% were related to a TSII. Due to the good spatial (3 km × 3 km) and high temporal (2 min) resolution of lightning data, the TSII can recognize even a local and short-lived intense system that is often misread by radars and satellites due to their inferior temporal resolution. The TSII is designed to be used as a climatological and diagnostic variable that could serve in lieu of more established data sources (e.g., station measurements and observations, radar imagery, etc.) if they are unavailable. [ABSTRACT FROM AUTHOR]

Tropical Storm Imelda struck the southeast coastal regions of Texas from 17–19 September, 2019, and delivered precipitation above 500 mm over about 6000 km2. The performance of the three IMERG (Early-, Late-, and Final-run) GPM satellite-based precipitation products was evaluated against Stage-IV radar precipitation estimates. Basic and probabilistic statistical metrics, such as CC, RSME, RBIAS, POD, FAR, CSI, and PSS were employed to assess the performance of the IMERG products. The products captured the event adequately, with a fairly high POD value of 0.9. The best product (Early-run) showed an average correlation coefficient of 0.60. The algorithm used to produce the Final-run improved the quality of the data by removing systematic errors that occurred in the near-real-time products. Less than 5 mm RMSE error was experienced in over three-quarters (ranging from 73% to 76%) of the area by all three IMERG products in estimating the Tropical Storm Imelda. The Early-run product showed a much better RBIAS relatively to the Final-run product. The overall performance was poor, as areas with an acceptable range of RBIAS (i.e., between −10% and 10%) in all the three IMERG products were only 16% to 17% of the total area. Overall, the Early-run product was found to be better than Late- and Final-run. [ABSTRACT FROM AUTHOR]

Understanding and forecasting hurricanes remains a challenge for the operational and research communities. To accurately predict the Tropical Cyclone (TC) evolution requires properly reflecting the storm's inner core dynamics by using: (i) high-resolution models; (ii) realistic physical parameterizations. The microphysical processes and their representation in cloud-permitting models are of crucial importance. In particular, the assumed Particle Size Distribution (PSD) functions affect nearly all formulated microphysical processes and are among the most fundamental assumptions in the bulk microphysics schemes. This paper analyzes the impact of the PSD assumptions on simulated hurricanes and their synthetic radiometric signatures. It determines the most realistic, among the available set of assumptions, based on comparison to multi-parameter satellite observations. Here we simulated 2005′s category-5 Hurricane Rita using the cloud-permitting community Weather Research and Forecasting model (WRF) with two different microphysical schemes and with seven different modifications of the parametrized hydrometeor properties within one of the two schemes. We then used instrument simulators to produce satellite-like observations. The study consisted in evaluating the structure of the different simulated storms by comparing, for each storm, the calculated microwave signatures with actual satellite observations made by (a) the passive microwave radiometer that was carried by the Tropical Rainfall Measuring Mission (TRMM) satellite—the TRMM microwave imager TMI, (b) TRMM's precipitation radar (PR) and (c) the ocean-wind-vector scatterometer carried by the QuikSCAT satellite. The analysis reveals that the different choices of microphysical parameters do produce significantly different microwave signatures, allowing an objective determination of a "best" parameter combination whose resulting signatures are collectively most consistent with the wind and precipitation observations obtained from the satellites. In particular, we find that assuming PSDs with larger number of smaller hydrometeors produces storms that compare best to observations. [ABSTRACT FROM AUTHOR]

The modern era of polarimetric radar begins with radiowave propagation research starting in the early 1970s with applications to measurement and modeling of wave attenuation in rain and depolarization due to ice particles along satellite–earth links. While there is a rich history of radar in meteorology after World War II, the impetus provided by radiowave propagation requirements led to high-quality antennas and feeds. Our journey starts by describing the key institutions and personnel responsible for development of weather radar polarimetry. The early period was dominated by circularly polarized radars for propagation research and at S band (frequency near 3 GHz) for hail detection. By the mid to late 70s, a paradigm shift occurred which led to the dominance of linear polarizations with applications to slant path attenuation prediction as well as estimation of rain rates and inferences of precipitation physics. The period from the early 1980s to 1995 can be considered as the "golden" period of rapid research that brought in meteorologists, cloud physicists, and hydrologists. This article describes the evolution of this technology from the vantage point of the authors. Their personal reflections and "behind the scenes" descriptions offer a glimpse into the inner workings at several key institutions which cannot be found elsewhere. [ABSTRACT FROM AUTHOR]

The Operational Program on the Exchange of Weather Radar Information (OPERA) has co-ordinated radar co-operation among national weather services in Europe for more than 20 years. It has introduced its own, manufacturer-independent data model, runs its own data center, and produces Pan-European radar composites. The applications using this data vary from data assimilation to flood warnings and the monitoring of animal migration. It has used several approaches to provide a homogeneous combination of disparate raw data and to indicate the reliability of its products. In particular, if a pixel shows no precipitation, it is important to know if that pixel is dry or if the measurement was missing. [ABSTRACT FROM AUTHOR]

In the French Alps the quality of the radar Quantitative Precipitation Estimation (QPE) is limited by the topography and the vertical structure of precipitation. A previous study realized in all the French Alps, has shown a general bias between values of the national radar QPE composite and the rain gauge measurements: a radar QPE over-estimation at low altitude (+20% at 200 m a.s.l.), and an increasing underestimation at high altitudes (until −40% at 2100 m a.s.l.). This trend has been linked to altitudinal gradients of precipitation observed at ground level. This paper analyzes relative altitudinal gradients of precipitation estimated with rain gauges measurements in 2016 for three massifs around Grenoble, and for different temporal accumulations (yearly, seasonal, monthly, daily). Comparisons of radar and rain gauge accumulations confirm the bias previously observed. The parts of the current radar data processing affecting the bias value are pointed out. The analysis shows a coherency between the relative gradient values estimated at the different temporal accumulations. Vertical profiles of precipitation detected by a research radar installed at the bottom of the valley also show how the wide horizontal variability of precipitation inside the valley can affect the gradient estimation. [ABSTRACT FROM AUTHOR]

Hubei Province Region (HPR), located in Central China, is a concentrated area of severe convective weather. Three severe convective processes occurred in HPR were selected, namely 14–15 May 2015 (Case 1), 6–7 July 2013 (Case 2), and 11–12 September 2014 (Case 3). In order to investigate the differences between the three cases, the temporal and spatial distribution characteristics of cloud–ground lightning (CG) flashes and precipitation, the distribution of radar parameters, and the evolution of cloud environment characteristics (including water vapor (VD), liquid water content (LWC), relative humidity (RH), and temperature) were compared and analyzed by using the data of lightning locator, S-band Doppler radar, ground-based microwave radiometer (MWR), and automatic weather stations (AWS) in this study. The results showed that 80% of the CG flashes had an inverse correlation with the spatial distribution of heavy rainfall, 28.6% of positive CG (+CG) flashes occurred at the center of precipitation (>30 mm), and the percentage was higher than that of negative CG (−CG) flashes (13%). Moreover, the quantity of thunderstorm cells in Case 1 was more than other cases, the peak time of +CG flashes was prior to that of total CG flashes in Case 2 and Case 3, and the time of +CG flashes' peak in Case 2 was prior to that of precipitation at about 2 h. Based on the analysis of the cloud environment, there are three main reasons for the differences of CG flashes and precipitation. Firstly, the structure of the LWC vertical profile and the height of the LWC peak are different, and high LWC makes it difficult for the collision of ice particles to generate electricity. Secondly, the differences between convective available potential energy (CAPE), precipitation, and CG flashes is caused by the sudden increase of VD from 1.5 km to 3 km, and thirdly, the production of CG flashes is very sensitive to RH at the surface layer and the total CG flashes increase as the RH increasing. [ABSTRACT FROM AUTHOR]

Vertical variability in the raindrop size distribution (RSD) can disrupt the basic assumption of a constant rain profile that is customarily parameterized in radar-based quantitative precipitation estimation (QPE) techniques. This study investigates the utility of melting layer (ML) characteristics to help prescribe the RSD, in particular the mass-weighted mean diameter (Dm), of stratiform rainfall. We utilize ground-based polarimetric radar to map the ML and compare it with Dm observations from the ground upwards to the bottom of the ML. The results show definitive proof that a thickening, and to a lesser extent a lowering, of the ML causes an increase in raindrop diameter below the ML that extends to the surface. The connection between rainfall at the ground and the overlying microphysics in the column provide a means for improving radar QPE at far distances from a ground-based radar or close to the ground where satellite-based radar rainfall retrievals can be ill-defined. [ABSTRACT FROM AUTHOR]