Low Rain Rates Research Articles

Evaluation of IMERG Data over Open Ocean Using Observations of Tropical Cyclones

The IMERG data product is an optimal combination of precipitation estimates from the Global Precipitation Mission (GPM), making use of a variety of data types, primarily data from various spaceborne passive instruments. Previous versions of the IMERG product have been extensively validated by comparisons with gauge data and ground-based radars over land. However, IMERG rain rates, especially sub-daily, over open ocean are less validated due to the scarcity of comparison data, particularly with the relatively new Version 07. To address this issue, we consider IMERG V07 30-min data acquired in tropical cyclones over open ocean. We perform two tasks. The first is a straightforward comparison between IMERG precipitation rates and those retrieved from the GPM Dual-frequency Precipitation Radar (DPR). From this, we find that IMERG and DPR are close at low rain rates, while, at high rain rates, IMERG tends to be lower than DPR. The second task is the assessment of IMERG’s ability to represent or detect structures commonly seen in tropical cyclones, including the annular structure and concentric eyewalls. For this, we operate on IMERG data with many machine learning algorithms and are able to achieve a 96% classification accuracy, indicating that IMERG does indeed contain TC structural information.

Water isotopic characterisation of the cloud–circulation coupling in the North Atlantic trades – Part 1: A process-oriented evaluation of COSMOiso simulations with EUREC4A observations

Abstract. Naturally available, stable, and heavy water molecules such as HDO and H218O have a lower saturation vapour pressure than the most abundant light water molecule H216O; therefore, these heavy water molecules preferentially condense and rain out during cloud formation. Stable water isotope observations thus have the potential to provide information on cloud processes in the trade-wind region, in particular when combined with high-resolution model simulations. In order to evaluate this potential, nested COSMOiso (isotope-enabled Consortium for Small Scale Modelling; Steppeler et al., 2003; Pfahl et al., 2012) simulations with explicit convection and horizontal grid spacings of 10, 5, and 1 km were carried out in this study over the tropical Atlantic for the time period of the EUREC4A (Elucidating the role of clouds-circulation coupling in climate; Stevens et al., 2021) field experiment. The comparison to airborne in situ and remote sensing observations shows that the three simulations are able to distinguish between different mesoscale cloud organisation patterns as well as between periods with comparatively high and low rain rates. Cloud fraction and liquid water content show a better agreement with aircraft observations with higher spatial resolution, because they show strong spatial variations on the scale of a few kilometres. A low-level cold-dry bias, including too depleted vapour in the subcloud and cloud layer and too enriched vapour in the free troposphere, is found in all three simulations. Furthermore, the simulated secondary isotope variable d-excess in vapour is overestimated compared to observations. Special attention is given to the cloud base level, which is the formation altitude of shallow cumulus clouds. The temporal variability of the simulated isotope variables at cloud base agrees reasonably well with observations, with correlations of the flight-to-flight data as high as 0.7 for δ2H and d-excess. A close examination of isotopic characteristics under precipitating clouds, non-precipitating clouds, clear-sky and dry-warm patches at the altitude of cloud base shows that these different environments are represented faithfully in the model with similar frequencies of occurrence, isotope signals, and specific-humidity anomalies as found in the observations. Furthermore, it is shown that the δ2H of cloud base vapour at the hourly timescale is mainly controlled by mesoscale transport and not by local microphysical processes, while the d-excess is mainly controlled by large-scale drivers. Overall, this evaluation of COSMOiso, including the isotopic characterisation of different cloud base environments, suggests that the simulations can be used for investigating the role of atmospheric circulations on different scales for controlling the formation of shallow cumulus clouds in the trade-wind region, as will be done in part 2 of this study.

Climatological features of future mesoscale convective systems in convection‐permitting climate models using CMIP6 and ERA5 in the central United States

AbstractMotivated by the limited understanding of future changes in mesoscale convective systems (MCSs), we investigated characteristics of warm‐season (June–August) MCSs in the central United States based on high‐resolution convection‐permitting Weather Research and Forecasting simulations. We examined two 15‐year simulations, which include current simulations (2004–2018) forced by European Centre for Medium‐Range Weather Forecasts Reanalysis version 5 (ERA5) and future simulations (2086–2100) forced by perturbed ERA5 (i.e., ERA5 plus climate change signal derived from 28 Coupled Intercomparison Projected Phase 6 models under the Shared Socioeconomic Pathway–Representative Concentration Pathway 8.5 emission scenario). The initiations and longevities of MCSs were determined using the object‐tracking algorithm MODE‐Time Domain (MTD) from observation, current simulations (ERA), and future simulations (pseudo‐global warming, PGW). Objects identified by MODE‐Time Domain were divided into short‐/long‐lived (based on 75th percentiles of longevity) and daytime (initiated during 0000–1100 UTC)/nighttime (initiated during 1200–2300 UTC). We found that ERA and observation have comparable occurrences of MCSs. MCSs in PGW are associated with intensified rain rates in New Mexico, Colorado, and Kansas and lower rain rates in Texas, Louisiana, and Arkansas than in ERA. Moreover, the statistical analysis based on 15 parameters before MCSs initiation indicates that short‐lived MCSs in PGW are characterized by prominent changes in precipitable water (PW) and the most unstable convective available potential energy. We also found that long‐lived MCSs in PGW are associated with prominent changes in PW, unstable convective available potential energy, and isentropic potential vorticity at 345 K. According to the statistical results, PW is the most important variable in determining the longevity of MCSs and in understanding future changes.

Performance analysis of innovative cleaning and soiling mitigation solutions in the semi-arid climate of Benguerir Morocco

The objective of this paper is to evaluate the performance of the hydrophobic coatings and detergent cleaning & antistatic protection for photovoltaic solar panels in semi-arid weather conditions in Benguerir Morocco. Various coating and cleaning strategies were tested on five photovoltaic (PV) systems with the same PV panels and electrical configurations. The first PV system (uncleaned) was not subject to any coatings or cleaning solutions. The second PV system (Water Cleaned) was periodically cleaned with raw water. The third PV system: solar wash protects (SWP) made use of a cleaning solution. The fourth:D solar defender (DSS) and fifth: industrial glass protect (IGP) PV systems each had a unique combination of the two hydrophobic coatings. The results demonstrated that after 9 months of operation, in the first 3 months (cleaning period) the average efficiency gain of the coated PV panels is around 10% compared to the reference system. Whereas in the non-cleaning period after 6 months of exposure, the efficiency gain is around 5%. After the outdoor exposure period, the cumulative energy gain of the coated systems compared to the water-cleaned reference reaches an average of 3%. It has been found that the SWP used 50% less water to clean the PV panels than the system cleaned without a cleaning solution, which made the panels harder to clean. The SWP is more successful at dust removal during the dry season (August–February) with low rain rates. However, during the rainy season (March–April), IGP outperformed SWP and DSD, with a small difference in PV performance. This study demonstrates the significance of using new cleaning strategies such as anti-soling coatings in dry areas to enhance the performance of photovoltaic systems, which may be useful for investors, researchers, and engineers interested in grid-connected photovoltaic and self-cleaning technology.

A study of rain drop size distributions and associated rain microphysical processes over a subtropical station in the Northeast India

A study of rain Drop Size Distributions (DSDs) and associated microphysical processes is carried out during the premonsoon and monsoon seasons at Kohima (25.67° N, 94.08° E) in the Patkai hill range of the Northeast India. The study is carried out with the help of Micro Rain Radar (24.1 GHz). The rainfall is classified in three categories namely, Bright Band (BB), No Bright Band Low rain rate (R) i.e. 0.10 mm h−1< R ≤ 10 mm h−1 (NBBL) and No Bright Band High rain rate i.e. 10 mm h−1 <R ≤ 20 mm h−1 (NBBH). During the premonsoon and monsoon, for R ≤ 20 mm h−1, rainfall occurrence time constitute around 96% and 98% respectively, whereas rainfall accumulation constitute around 51%. and 72% respectively. The BB height is found to be lower during the premonsoon (∼2.2 km from surface level) compared to monsoon (∼3.6 km from surface level) season. The observational results suggest that, during the premonsoon as well monsoon seasons, BB rain is predominantly associated with collision–coalescence–breakup process with varying proportion, whereas NBBL and NBBH rain are predominantly associated with collision–coalescence process with varying proportion. In each season, collision-coalescence process is most dominant for NBBH type of rain. Seasonally, collision-coalescence process is found to be stronger during the premonsoon season. For the falling rain drops, there is a transition in the microphysical process from number controlled (collision-coalescence-breakup) to size-controlled (collision-coalescence) process with varying proportion. For each season, for R ≤ 10 mm h−1, larger rain drops are found for BB type of rain compared to NBBL rain. Overall, relatively larger raindrops are found to be associated with NBBH rain. Seasonally, larger drops are found during the premonsoon compared to the monsoon season. The rain DSDs and associated microphysical processes during the premonsoon are found to be associated with stronger convection compared to the monsoon season.

Impact of Rainfall on Tropical Cyclone‐Induced Sea Surface Cooling

AbstractTropical cyclones (TCs) are often accompanied by strong winds and torrential rains. While the winds associated with TCs tend to enhance mixing in the upper ocean, the freshwater input from rain can stratify the water column and limit mixing. However, the extent to which the stabilizing effect of rainfall can compete with wind‐induced mixing and to what degree it modulates TC‐induced sea surface cooling remain unknown. Here we show, using a suite of observations, that heavy rains under weak TCs can significantly reduce the magnitude of cold wakes induced by them. When compared to storms with low rain rates, the ocean surface under TCs with high rain rates freshens significantly and cools less. High‐resolution climate model simulations and idealized experiments with an ocean mixed layer model support these results and reveal that oceanic mixing processes are primarily responsible for reduced cooling under TCs, with a lesser role for surface fluxes.

Simulating the Effects of Land Surface Characteristics on Planetary Boundary Layer Parameters for a Modeled Landfalling Tropical Cyclone

This study examined whether varying moisture availability and roughness length for the land surface under a simulated Tropical Cyclone (TC) could affect its production of precipitation. The TC moved over the heterogeneous land surface of the southeastern U.S. in the control simulation, while the other simulations featured homogeneous land surfaces that were wet rough, wet smooth, dry rough, and dry smooth. Results suggest that the near-surface atmosphere was modified by the changes to the land surface, where the wet cases have higher latent and lower sensible heat flux values, and rough cases exhibit higher values of friction velocity. The analysis of areal-averaged rain rates and the area receiving low and high rain rates shows that simulations having a moist land surface produce higher rain rates and larger areas of low rain rates in the TC’s inner core. The dry and rough land surfaces produced a higher coverage of high rain rates in the outer regions. Key differences among the simulations happened as the TC core moved over land, while the outer rainbands produced more rain when moving over the coastline. These findings support the assertion that the modifications of the land surface can influence precipitation production within a landfalling TC.

From TRMM to GPM, how do improvements of post/near-real-time satellite precipitation estimates manifest?

With the end of the Tropical Rainfall Measuring Mission (TRMM) era, its successor of Global Precipitation Measurement (GPM) aims to provide a new generation of satellite precipitation estimates (SPE) with higher spatiotemporal resolution and wider spatial coverage. As the representative precipitation retrieval algorithms for GPM and TRMM eras, it is necessary to compare the Integrated Multi-satellite Retrievals for GPM (IMERG) with the TRMM Multi-satellite Precipitation Analysis (TMPA) to investigate the improvements of SPEs from TRMM to GPM. This study analyzes the post/near-real-time SPEs from TMPA and IMERG over Mainland China from April 2014 to March 2018 at daily scale, using precipitation observations from 510 meteorological stations as reference. A very comprehensive evaluation system, which contains four indicators of continuous metrics, categorical metrics, error components, and systematic and random errors is adopted in this study. Besides, four patterns with spatial distribution, temporal pattern, precipitation intensity distribution, and overall metrics are applied to illustrate each indicator's performance. The results show that IMERG products have lower RB and RMSE and higher CC than TMPA and greatly reduce the three error components (hit bias, missed precipitation, and false precipitation). Furthermore, IMERG products present a higher capability to capture the precipitation events correctly and generally have lower systematic and random errors than TMPA products. However, there are still rooms for IMERG products to improve, such as higher false alarm ratio (FAR) and more false precipitation of IMERG products at relatively low rain rates, the 25% higher systematic error of IMERG-E (IMERG “Early Run” near-real-time SPE) compared to TMPA-RT (TMPA near-real-time SPE). In addition, we find the gauge adjustment from GPCC is not a very effective way to improve the detecting capability and reduce the systematic errors for near-real-time SPEs over Mainland China. This study provides some valuable information on the transition from TMPA to IMERG, which may advance the algorithm's development and the hydrometeorological applications.

Exploring the Temporal Information From GEO Satellites for Estimating Precipitation With Convolutional Neural Networks

Temporal information from a geostationary satellite is explored for improved precipitation characterization and quantification. Temporal predictors are extracted from the Geostationary Operational Environmental Satellite (GOES)-16 Advanced Baseline Imager. A 1-Dimensional Convolutional Neural Network (CNN) architecture is proposed and compared to a Deep Neural Network (DNN) benchmark without temporal predictors. While the CNN detection (Rain/No-Rain separation) is on par with the DNN benchmark, promising results are obtained for both precipitation type classification and quantification, indicating the value of the temporal information for precipitation estimation. The identification of rapidly evolving convective systems is improved (accuracy improved from 49% to 58%), while false detections in Stratiform type precipitation are reduced. Rain rate quantification is improved by reducing the overestimation of low rain rates, which increases the correlation from 0.34 (DNN) to 0.41 (CNN). This study is an important first step toward better characterizing and quantifying precipitation using the very high temporal resolution of geostationary satellites.

Long-Term Impact of Continental and Maritime Airflow on Aerosol Environment and Rain Microstructure Near Land–Sea Boundary

The present study deals with the interplay of multiple atmospheric processes in changing the microphysical properties of precipitation during the pre-monsoon season (March–May) using the long-term experimental data of raindrop size distributions (DSDs) spanning over 15 years (2005–2019) obtained at an urban tropical location, Kolkata (22.57°N, 88.37°E), near the land–sea boundary. The changing pattern of air mass flows from the maritime and continental region, which contribute to the formation of precipitation processes, has been responsible for the varying characteristics of rain. Changes in raindrop sizes are related to aerosol properties, cloud features, temperature, and relative humidity that change mass-weighted mean drop diameter ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$D_{m}$ </tex-math></inline-formula> ) differently in low and high rain rate regimes. <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$D_{m}$ </tex-math></inline-formula> has shown an increasing trend over time for low rain rates (< 15 mm/h), but a decreasing trend for high rain rate regimes (≥15 mm/h). An increase (decrease) in mean temperature (relative humidity) below the atmospheric boundary layer (< 1.6 km) has enhanced the evaporation of small raindrops and altered rain microphysical features. Based on satellite observations, it has been found that the increasing aerosol optical depth (AOD) has been accompanied by an increase in cloud effective radius (CER), resulting in the anti-Twomey effect, which is due to the dominance of maritime influence over continental activities. Because of the predominant maritime activities, sea salt aerosols have a greater presence, causing an increase in CER, which consequently prevents raindrops from becoming large enough before they fall, thereby reducing <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$D_{m}$ </tex-math></inline-formula> at high rainfall rates.

Validation of Three Daily Satellite Rainfall Products in a Humid Tropic Watershed, Brantas, Indonesia: Implications to Land Characteristics and Hydrological Modelling

A total of three different satellite products, CHIRPS, GPM, and PERSIANN, with different spatial resolutions, were examined for their ability to estimate rainfall data at a pixel level, using 30-year-long observations from six locations. Quantitative and qualitative accuracy indicators, as well as R2 and NSE from hydrological estimates, were used as the performance measures. The results show that all of the satellite estimates are unsatisfactory, giving the NRMSE ranging from 6 to 30% at a daily level, with CC only 0.21–0.36. Limited number of gauges, coarse spatial data resolution, and physical terrain complexity were found to be linked with low accuracy. Accuracy was slightly better in dry seasons or low rain rate classes. The errors increased exponentially with the increase in rain rates. CHIPRS and PERSIANN tend to slightly underestimate at lower rain rates, but do show a consistently better performance, with an NRMSE of 6–12%. CHRIPS and PERSIANN also exhibit better estimates of monthly flow data and water balance components, namely runoff, groundwater, and water yield. GPM has a better ability for rainfall event detections, especially during high rainfall events or extremes (&gt;40 mm/day). The errors of the satellite products are generally linked to slope, wind, elevation, and evapotranspiration. Hydrologic simulations using SWAT modelling and the three satellite rainfall products show that CHIRPS slightly has the daily best performance, with R2 of 0.59 and 0.62, and NSE = 0.54, and the monthly aggregated improved at a monthly level. The water balance components generated at an annual level, using three satellite products, show that CHIRPS outperformed with a ration closer to one, though with a tendency to overestimate up to 3–4× times the data generated from the rainfall gauges. The findings of this study are beneficial in supporting efforts for improving satellite rainfall products and water resource implications.

An ERA‐5 Derived CONUS‐Wide High‐Resolution Precipitation Dataset Based on a Refined Parametric Statistical Downscaling Framework

AbstractThe spatiotemporal character of rainfall is particularly important for hydrologic modeling, as well as hydroclimatic risk estimation and impact assessment. Existing atmospheric reanalysis datasets offer extensive record lengths and global coverage, but usually their spatial resolution is coarse for distributed hydrologic simulations at small spatial scales. On the other hand, the temporal coverage of high‐resolution radar‐based rainfall estimates can be rather short for risk applications. To address these shortcomings, we simultaneously bias‐correct and downscale a state‐of‐the‐art atmospheric reanalysis (ERA5) rainfall dataset, using the radar‐based Stage IV precipitation product as fine resolution reference, to develop an hourly CONUS‐wide precipitation product over a 4‐km grid, which extends back to 1979. In this regard, we refine an existing parametric quantile mapping framework based on a two‐component theoretical distribution model, where we impose continuity of the parametric forms via optimal threshold selection to transition between higher and lower rain rates. An evaluation over the probability frequency and time domains, using NOAA’s raingauge measurements as benchmark, reveals that the developed product benefits from the strengths of the calibration datasets, demonstrating good performance and robust behavior over all studied time periods and Köppen climate classification zones, including snow‐prone regions or areas where mesoscale convective systems become dominant. The accuracy of the yielded high spatial‐resolution rain rates, especially in low probability events, shows that the developed product can be effectively used for hydroclimatic risk applications and frequency analysis, while its high temporal and spatial resolution makes it particularly useful for distributed hydrologic modeling.

English

Rain-based attenuation (RBA) is a major deteriorating factor affecting radio wave signals operating at microwave and millimetre wave bands for a typical Earth-Space Communication Link (ESCL). Although the international telecommunication union (ITU) recommended a standard model for predicting RBA along the terrestrial and ESCL, the technique underperforms in tropical environments. However, the model can be supported by appropriate modulation to enhance link performance. The present study assesses the performance of selected RBA models, namely the ITU, Moupfouma, and Garcἱa-Lὁpez models based on rain types for K-V frequency bands over some selected locations in Southwestern Nigeria. Link performance was further tested based on different modulation scaling to minimize signal degradation. The result shows that Garcίa-Lόpez and ITU models performed well at low rain rate R &le;2 mm/h but underestimated at higher rain rates (except thunderstorms rain type) at the high-frequency band. However, the Moupfouma model performed well for all the rain types irrespective of the selected frequency band, while the ITU model underestimated attenuation for R &lt; 5 mm/h (shower) and R &gt; 30 mm/h (thunderstorm) rain type from the K-V band frequency, Garcia Lopez underestimates the RBA value for R &lt; 5 mm/h and R &gt; 5 mm/h up to the Ka frequency band. Considering the modulation scaling on link performance shows that the bit-error-rate (BER) will severely degrade with a high rain rate compared to the low rain rate across different frequencies. The BER for 8-PPM outperforms the other types of modulation schemes that were used in this study. Overall results revealed that modulation technique DPSK with selective combining diversity gave a marginal improvement with the increase in link distance and operating frequency. Key words: ESCL, rain attenuation models, modulation techniques, K-V frequency bands.

Performance of the DBS Satellite Receiver under the Impact of Rainfall and Terrestrial Interference

This article presents a new study on the feasibility of operating a direct broadcasting satellite (DBS) system under the effect of both precipitation and interference from a fixed service (FS) at K‐band in a semiarid region. The carrier‐to‐noise plus interference ratio (CNIR) as a protection criterion has been adopted to make sure that the receiver of the DBS system operates with an acceptable performance under rainfall and interference from FS. Various measured data for rainfall in different areas have been utilized to investigate different rain rate exceedance percentages. Results have been shown that areas with high rain rates have a small CNIR at the DBS receiver and require large protection distances compared to low‐rain rate areas and vice versa. Some mitigation techniques have been suggested to alleviate the effect of rain and terrestrial interference on the DBS receiver performance.

Radiometric Measurements of Atmospheric Attenuation Over a Tropical Location

AbstractThe information of atmospheric attenuation at Ka‐band is important during rain and clear air condition. In this paper, Ka‐band attenuation data obtained from radiometric measurements at Kolkata, India (22°034′E, 88°022′N) have been presented. The role of water vapor is examined in determining the behavior of atmospheric attenuation during and without rain condition at 22.24, 26.24, and 31.4 GHz frequencies. It has been observed that at lower rain rate (&lt;5 mm/hr), attenuation at 22.24 GHz is the highest among three frequencies due to water vapor absorption at this frequency. Millimeter Wave Propagation (MPM) model has been used to observe the contribution of rain and water vapor in determining atmospheric attenuation for different rain rates. It has been noted that at 22.24 GHz, water vapor attenuation is comparable to the rain attenuation up to 5 mm/hr. The measured attenuation from radiometer has been compared with ITU‐R model‐generated data and both the attenuation data match reasonably well up to rain rate 20 mm/hr. The attenuation obtained from radiometric measurements shows saturation with increasing rain rate due to the darkening effect. The ITU‐R frequency scaling model has been used to compare the measured and calculated attenuation at 31.4 GHz. This study gives some useful information about the radiometric measurements of atmospheric attenuation at a tropical location that shows that not only rain rate but also water vapor is an important cause of attenuation at Ka‐band.

Parameter estimation of a dual-pol radar rain rate estimator with truncated paired data

Abstract This study proposes a new method for estimating the parameters of a radar rain rate estimator, particularly of the dual-pol radar. The proposed method is similar to the probability matching method (PMM), except for being based on truncated data pairs. A truncation value is introduced to the log-transformed data in order to remove those in the low rain rate zone as well as to introduce Gaussian distribution. The parameters are then estimated by comparing the first- and second-order moments. The proposed method is applied to a total of six rainfall events observed by the Beaslesan Radar in Korea from 2014 to 2017. Summarizing the results, first, the truncation value should be applied to the horizontal reflectivity (dBZh) data. In this case only, the other two data, the rain rate (dBR) and the differential reflectivity (dBZdr), follow the Gaussian distribution well. It is also important to consider rather severe rainfall events for the parameter estimation. The parameters for only the severe rainfall events are all estimated rather reasonably. On the other hand, for the other moderate and light rainfall events, the parameters are estimated as being rather far from their normal ranges. This is mainly due to the relatively small variance of dBR compared to that of dBZh. That is, the variance of dBR is found to be greatly dependent on the peak rain rate, but the variance of dBZh remains almost unchanged, regardless of the peak rain rate. As a result, the peak rain rate plays a dominant role in the reasonable parameter estimation. These findings are also consistent with many previous studies.

Characterization of Ka-band Radar Observations for Different Rain Types over Akure, Nigeria

Radar is a unique tool that can measure precipitation parameters over a large aerial coverage. Its application spans over study of climate change and radiowave propagation. Inter-relation between the rain parameters can also be derived with the height of radar especially on vertical profiling or aloft ground level. Hence effect of precipitation parameters can be assessed along the satellite propagation path with the help of space-borne radar. Satellite communication links operating at frequencies above 10 GHz are usually affected by hydrometeors especially rainfall. These effects are expected to be quite severe in the tropical region like Akure due to the nature of precipitation which is mainly convective and stratiform rain type. Therefore, information on vertical rain structure is important for precise quantitative estimation of precipitation. Thus, the focus of this work is to characterize the vertical profile of rain structures using vertically-pointing Ka-band Micro Rain Radar (MRR) at Akure, Nigeria. This has been achieved by using 2-year (2013 and 2014) data of rain parameters namely: rain rate, reflectivity, liquid water content and fall velocity obtained from MRR to determine the bright band heights under different rain types and its implications on satellite and radio waves propagation in this region. Rain rate in this region has been categorized into four groups namely: 0.02- 0.2 mm/h, 0.2- 2 mm/h, 2-40 mm/h, and 40 - 200 mm/h. The very low rain rate group is related to the stratiform rain types whereas highest rain rate groups are for the convective rain type. Study shows that parameters that are much associated with rain attained peak value at different height depending on the period of the year. The vertical profile of Z shows peak around 3 to 4.2 km height. The peak region is associated with the bright band height and contribution to the melting layer. This study revealed that the occurrence of bright band heights varies with rain types. The overall results will be useful for determining rain height needed for the prediction of rain attenuation in this region.

Assimilation of GPM Rain Rate Products With GSI Data Assimilation System for Heavy and Light Precipitation Events

AbstractThe National Aeronautics and Space Administration‐Japan Aerospace Exploration Agency Global Precipitation Measurement (GPM) mission consists of a multisatellite constellation that provides real‐time or near‐real‐time global observations of rain and snow. In this study, GPM Level 3 Integrated Multi‐satellitE Retrievals for GPM (IMERG) and Level 2 GPM Microwave Imager Goddard Profiling rainfall products have been assimilated into the Weather Research and Forecasting model using the community Gridpoint Statistical Interpolation (GSI) data assimilation system. Experiments have been conducted and compared to demonstrate the impact of rain rate data assimilation on forecasts of heavy rainfall related to Hurricane Harvey (2017) and moderate to light rainfall observed during the GPM Integrated Precipitation and Hydrology Experiment field campaign. The results indicate that both GPM Microwave Imager Goddard Profiling and IMERG data could generate apparent increments in moisture, temperature, wind, and pressure fields for Hurricane Harvey, which led to significant improvement in the precipitation forecast. Frequent (every 3 hr) assimilation of IMERG data also positively impacted the short‐term precipitation forecast skill for the Integrated Precipitation and Hydrology Experiment moderate to light rain events. However, results also indicate that the impact of rain data assimilation was limited for a system that had a small horizontal dimension with low rain rates and within a relatively stable synoptic environment.

Global canopy rainfall interception loss derived from satellite earth observations

AbstractInformation on global canopy rainfall interception loss is essential for understanding the dynamics of land surface processes and the water cycle. In addition, large uncertainty remains regarding the global variation in this factor. The development of satellite earth observations has provided a great opportunity for the estimation of global rainfall interception loss to reveal the spatiotemporal variations. In the current study, the analytical Gash model was adapted and applied to estimate global rainfall interception loss from 2001 to 2015 on the basis of satellite remote‐sensing products, for example, gross rainfall amount and rate and leaf area index. The Dalton‐type equation was adopted to estimate the wet canopy evaporation rate in the revised Gash model. The estimation on the basis of the Dalton‐type equation showed better agreement with the ground observations than the classical Penman–Monteith equation in terms of estimated rainfall interception loss and its ratio to gross rainfall. Large spatial variations in global rainfall interception loss were found, and high values appeared in the regions with dense vegetation cover and high gross rainfall amounts, for example, tropical rainforests, whereas high rainfall interception to gross rainfall ratios occurred in the regions with low rain rates and high vegetation cover. This study constitutes a significant step forward in understanding global hydrological cycle on the basis of earth observation products.

Variable Raindrop Size Distributions in Different Rainbands Associated With Typhoon Fitow (2013)

AbstractThe microphysical characteristics of rain may vary in different rain regions of a tropical cyclone (TC), but few studies have demonstrated the differences in raindrop size distributions (RSDs) of convective rain in different rainbands of a specific TC. This study examines the RSD characteristics and evolution of convective rain within outer rainbands and a coastal‐front‐like rainband associated with Typhoon Fitow, based on observational data from a disdrometer at Shibo station in Shanghai, China, during 6–7 October 2013. Considering the fast passage of convective TC rainbands over the disdrometer and the low rain rate of stratiform rain in the outer area, this study proposes a modified rain‐type classification method based on the disdrometer data. This study indicates that convective outer‐rainband rain (ORR) and coastal‐front rain (CFR) have different rain parameters, three parameters of the gamma model, radar reflectivity–rain rate (Z‐R), and shape–slope (μ‐Λ) relationships. The convective ORR has higher concentrations at all drop sizes than the convective CFR as well as larger spectral width, leading to the greater rainfall rate. The different Z‐R relationships suggest the necessity of a variable relationship for quantitative precipitation estimation (QPE) in different rain regions of the TC. This study also demonstrates for the first time that the RSD evolution with increasing rain rate is different in various convective rainbands associated with Fitow, suggesting that different microphysical parameterization schemes may be required for different rainbands in TC models.