Origins of Heavy Precipitation Biases in the TRMM PR and TMI Products Assessed with CloudSat and Reanalysis Data

AbstractThis study aims to characterize the background physical processes in the development of those heavy precipitation clouds that contribute to the Tropical Rainfall Measuring Mission (TRMM) active and passive sensor differences. The combined global observation data from TRMM, CloudSat, and European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) from 2006 to 2014 were utilized to address this issue. Heavy rainfall events were extracted from the top 10% of the rain events from the Precipitation Radar (PR) and TRMM Microwave Imager (TMI) rain-rate climatology. Composite analyses of CloudSat and ERA-Interim were conducted to identify the detailed cloud structures and the background environmental conditions. Over tropical land, TMI tends to preferentially detect deep isolated precipitation clouds for relatively drier and unstable environments, while PR identifies more organized systems. Over the tropical ocean, TMI identifies heavy rainfall events with notable convective organization and clear regional gradients between the western and eastern Pacific Ocean, while PR fails to capture the eastward shallowing of convective systems. The PR–TMI differences for the moist and stable environments are reversed over tropical land.

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Impact of Radiance Data Assimilation on the Prediction of Heavy Rainfall in RMAPS: A Case Study

Remote Sensing ◽

10.3390/rs10091380 ◽

2018 ◽

Vol 10 (9) ◽

pp. 1380 ◽

Cited By ~ 4

Author(s):

Yanhui Xie ◽

Jiancheng Shi ◽

Shuiyong Fan ◽

Min Chen ◽

Youjun Dou ◽

...

Keyword(s):

Data Assimilation ◽

Heavy Rainfall ◽

Precipitation Forecast ◽

Observation Data ◽

Rainfall Events ◽

Satellite Radiance Data ◽

Radiance Data ◽

The Impact ◽

Heavy Rainfall Events

Herein, a case study on the impact of assimilating satellite radiance observation data into the rapid-refresh multi-scale analysis and prediction system (RMAPS) is presented. This case study targeted the 48 h period from 19–20 July 2016, which was characterized by the passage of a low pressure system that produced heavy rainfall over North China. Two experiments were performed and 24 h forecasts were produced every 3 h. The results indicated that the forecast prior to the satellite radiance data assimilation could not accurately predict heavy rainfall events over Beijing and the surrounding area. The assimilation of satellite radiance data from the advanced microwave sounding unit-A (AMSU-A) and microwave humidity sounding (MHS) improved the skills of the quantitative precipitation forecast to a certain extent. In comparison with the control experiment that only assimilated conventional observations, the experiment with the integrated satellite radiance data improved the rainfall forecast accuracy for 6 h accumulated precipitation after about 6 h, especially for rainfall amounts that were greater than 25 mm. The average rainfall score was improved by 14.2% for the 25 mm threshold and by 35.8% for 50 mm of rainfall. The results also indicated a positive impact of assimilating satellite radiances, which was primarily reflected by the improved performance of quantitative precipitation forecasting and higher spatial correlation in the forecast range of 6–12 h. Satellite radiance observations provided certain valuable information that was related to the temperature profile, which increased the scope of the prediction of heavy rainfall and led to an improvement in the rainfall scoring in the RMAPS. The inclusion of satellite radiance observations was found to have a small but beneficial impact on the prediction of heavy rainfall events as it relates to our case study conditions. These findings suggest that the assimilation of satellite radiance data in the RMAPS can provide an overall improvement in heavy rainfall forecasting.

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Relating Passive 37-GHz Scattering to Radar Profiles in Strong Convection

Journal of Applied Meteorology and Climatology ◽

10.1175/2010jamc2506.1 ◽

2011 ◽

Vol 50 (1) ◽

pp. 233-240 ◽

Cited By ~ 28

Author(s):

Daniel J. Cecil

Keyword(s):

Central Africa ◽

Tropical Rainfall Measuring Mission ◽

The United States ◽

Phase Layer ◽

Tropical Ocean ◽

Convective Systems ◽

Freezing Level ◽

Brightness Temperatures ◽

Microwave Imager ◽

Ice Water

Abstract Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and precipitation radar measurements are examined for strong convective systems. Storms having similar values of minimum 37-GHz polarization-corrected temperature (PCT) are grouped together, and their vertical profiles of maximum radar reflectivity are composited. Lower 37-GHz PCT corresponds to stronger radar profiles (high reflectivity through a deep layer), but characteristic profiles for a given 37-GHz PCT are different for deep tropical ocean, deep tropical land, subtropical ocean, and subtropical land regions. Tropical oceanic storms have a sharper decrease of reflectivity just above the freezing level than storms from other regions with the same brightness temperature. Storms from subtropical land regions have the slowest decrease of reflectivity with height and the greatest mixed-phase-layer ice water content (IWC). Linear fits of 37-GHz PCT versus IWC for each region are used to scale the brightness temperatures. Counts of storms with these scaled brightness temperatures below certain thresholds suggest that not as many of the strongest storms occur in central Africa as in subtropical parts of South America, the United States, and central Asia.

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Verification of Tropical Cyclone–Related Satellite Precipitation Estimates in Mainland China

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc2143.1 ◽

2009 ◽

Vol 48 (11) ◽

pp. 2227-2241 ◽

Cited By ~ 46

Author(s):

Zifeng Yu ◽

Hui Yu ◽

Peiyan Chen ◽

Chuanhai Qian ◽

Caijun Yue

Keyword(s):

Heavy Rainfall ◽

Rain Rate ◽

Mainland China ◽

Tropical Rainfall Measuring Mission ◽

Rain Gauge ◽

Horizontal Distribution ◽

Rainfall Events ◽

Light Rain ◽

Geostationary Meteorological Satellite ◽

Heavy Rainfall Events

Abstract To evaluate the abilities of satellite retrievals in reflecting precipitation features related to tropical cyclones (TCs) affecting mainland China, four years of 6- and 24-h precipitation retrievals from three datasets, namely the Tropical Rainfall Measuring Mission satellite algorithm 3B42, version 6 (3B42), Climate Prediction Center morphed (CMORPH) product, and one based on the Geostationary Meteorological Satellite-5 infrared brightness temperature (GMS5-TBB), are compared statistically with direct measurements from surface gauge rainfall data during the periods affected by TCs. The GMS5-TBB dataset was set up by a method of considering the GMS5-TBB characteristics, hourly precipitation intensity, and horizontal distribution for landfalling TCs. The results show that in a general sense, all three satellite-retrieved rainfall datasets give quite reasonable 6- and 24-h rainfall distributions, with skill decreasing with the increase in both latitude and rainfall amount. The 3B42 has a little bit better skill than CMORPH, which is likely related to the fact that the 3B42 product has a rain gauge adjustment and CMORPH does not. Further analyses show that both 3B42 and CMORPH considerably underestimate the moderate and heavy rainfall and overestimate the very light precipitation. The overestimation of the GMS5-TBB data for the light rain is larger than that for 3B42 and CMORPH, probably due to the fact that the GMS5-TBB method considers stratiform and convective rainfall separately with a fixed stratiform rain rate of 2 mm h−1. For the heavy rainfall events, the GMS5-TBB data perform much better than the 3B42 and CMORPH data with an almost halved bias, owing to the fact that the GMS5-TBB method adopted the adjustment of the convective rain rate by considering TBB characteristics of landfalling TCs and using hourly gauge rainfall in the setup process. Since the heavy rainfall events associated with landfalling TCs are of the most concern, the compared GMS5-TBB data could be useful as an operational/research reference.

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Classification of Intense Rainfall Days in Southern West Africa and Associated Atmospheric Circulation

Atmosphere ◽

10.3390/atmos11020188 ◽

2020 ◽

Vol 11 (2) ◽

pp. 188

Author(s):

Pierre Camberlin ◽

Marc Kpanou ◽

Pascal Roucou

Keyword(s):

West Africa ◽

Atmospheric Circulation ◽

Daily Rainfall ◽

Tropical Rainfall Measuring Mission ◽

Heavy Precipitation ◽

Reanalysis Data ◽

Intense Rainfall ◽

Rainfall Events ◽

Easterly Waves ◽

Atmospheric Circulation Anomalies

Daily rainfall in southern West Africa (4–8° N, 7° W–3° E) is analyzed with the aim of documenting the intense rainfall events which occur in coastal Ivory Coast, Ghana, Togo, and Benin. The daily 99th percentile (P99) shows that the coastline experiences higher intensity rainfall than inland areas. Using Tropical Rainfall Measuring Mission (TRMM) rainfall data for 1998–2014, a novel way of classifying the intense events is proposed. We consider their space-time structure over a window of 8° latitude-longitude and five days centered on the event. A total 39,680 events (62 at each location) are classified into three major types, mainly found over the oceanic regions south of 5° N, the Bight of Benin, and the inland regions respectively. These types display quite distinct rainfall patterns, propagation features, and seasonal occurrence. Three inland subtypes are also defined. The atmospheric circulation anomalies associated with each type are examined from ERA-interim reanalysis data. Intense rainfall events over the continent are mainly a result of westward propagating disturbances. Over the Gulf of Guinea, many intense events occur as a combination of atmospheric disturbances propagating westward (mid-tropospheric easterly waves or cyclonic vortices) and eastward (lower tropospheric zonal wind and moisture anomalies hypothesized to reflect Kelvin waves). Along the coast, there is a mixture of different types of rainfall events, often associated with interacting eastward- and westward-moving disturbances, which complicates the monitoring of heavy precipitation.

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Spatio-temporal patterns and extremity assessment of heavy rainfall events in Germany, derived from a radar-based catalogue (CatRaRE, 2001-2020)

10.5194/ems2021-461 ◽

2021 ◽

Author(s):

Ewelina Walawender ◽

Katharina Lengfeld ◽

Tanja Winterrath ◽

Elmar Weigl ◽

Andreas Becker

Keyword(s):

Heavy Rainfall ◽

Open Data ◽

Heavy Precipitation ◽

Radar Data ◽

Rainfall Events ◽

Antecedent Precipitation ◽

Hourly Data ◽

Spatio Temporal ◽

Heavy Rainfall Events ◽

Precipitation Events

One of the predicted effects of climate change in Central Europe is a growing number and increasing extremity of heavy rainfalls. Thus, it is of a great importance not only to develop best possible nowcasting methods and long-term forecasting models, but also to look closer at the structure and detailed characteristics of extreme events that have already taken place.With this objective, the German Weather Service (DWD) has developed a Catalogue of Radar-based Heavy Rainfall Events (CatRaRE), derived from 20 years of climatological radar data for the area of Germany.Using hourly data of about 1 km spatial resolution, an object-oriented analysis is performed to classify spatially and timely independent rainfall events exceeding the official warning level for heavy precipitation. Events with duration between 1 and 72 hours are investigated and statistically analysed. Apart from various extremity attributes, like return period, heavy precipitation, and weather extremity indices, the catalogue is enriched with additional variables (e.g. weather type, antecedent precipitation index, population density, land cover, imperviousness degree, Topographic Position Index), providing the meteorological background and helping to estimate the possible impact, each event could provoke.The Catalogue is freely available via DWD&#8217;s Open Data Portal in both a tabular and spatial (GIS) format. In addition, a user friendly online Dashboard was developed to visualize the data and communicate our results to a broader audience.&#160;We will present the CatRaRE Catalogue and results of a comprehensive analysis of all classified heavy precipitation events that occurred in Germany between 2001 and 2020. Different time scales from diurnal to multi-annual, as well as identified spatial patterns in connection with event attributes will be illustrated. Most common weather types, favouring occurrence of detected events will be outlined. Finally, we will demonstrate selected application possibilities by combining the catalogue with other datasets (e.g. fire brigade operations).

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A Comparison of Two Heavy Rainfall Events during the Terrain-Influenced Monsoon Rainfall Experiment (TiMREX) 2008

Monthly Weather Review ◽

10.1175/mwr-d-13-00293.1 ◽

2014 ◽

Vol 142 (7) ◽

pp. 2436-2463 ◽

Cited By ~ 23

Author(s):

Chuan-Chi Tu ◽

Yi-Leng Chen ◽

Ching-Sen Chen ◽

Pay-Liam Lin ◽

Po-Hsiung Lin

Keyword(s):

Rainy Season ◽

Heavy Rainfall ◽

Large Scale ◽

Sea Breeze ◽

Heavy Precipitation ◽

Early Summer ◽

Cold Pool ◽

Mountain Range ◽

Rainfall Events ◽

Heavy Rainfall Events

Abstract Two contrasting localized heavy rainfall events during Taiwan’s early summer rainy season with the daily rainfall maximum along the windward mountain range and coast were studied and compared using a combination of observations and numerical simulations. Both events occurred under favorable large-scale settings including the existence of a moisture tongue from the tropics. For the 31 May case, heavy rainfall occurred in the afternoon hours over the southwestern windward slopes after a shallow surface front passed central Taiwan. The orographic lifting of the prevailing warm, moist, west-southwesterly flow aloft, combined with a sea breeze–upslope flow at the surface provided the localized lifting needed for the development of heavy precipitation. On 16 June before sunrise, pronounced orographic blocking of the warm, moist, south-southwesterly flow occurred because of the presence of relatively cold air at low levels as a result of nocturnal and rain evaporative cooling. As a result, convective systems intensified as they moved toward the southwestern coast. During the daytime, the cold pool remained over southwestern Taiwan without the development of onshore/upslope flow. Furthermore, with a south-southwesterly flow aloft parallel to terrain contours, orographic lifting aloft was absent and preexisting rain cells offshore diminished after they moved inland. Over northern Taiwan on the lee side, a sea breeze/onshore flow developed in the afternoon hours, resulting in heavy thundershowers. These results demonstrate the importance of diurnal and local effects on determining the location and timing of the occurrences of localized heavy precipitation during the early summer rainy season over Taiwan.

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Anomalous Weather Patterns in Relation to Heavy Precipitation Events in Japan during the Baiu Season

Journal of Hydrometeorology ◽

10.1175/jhm-d-14-0124.1 ◽

2015 ◽

Vol 16 (2) ◽

pp. 688-701 ◽

Cited By ~ 35

Author(s):

Masamichi Ohba ◽

Shinji Kadokura ◽

Yoshikatsu Yoshida ◽

Daisuke Nohara ◽

Yasushi Toyoda

Keyword(s):

Time Scales ◽

Heavy Rainfall ◽

Southern Oscillation ◽

Potential Temperature ◽

Heavy Precipitation ◽

Rainfall Events ◽

Weather Patterns ◽

Extreme Precipitation Events ◽

Heavy Rainfall Events ◽

Precipitation Events

Abstract Anomalous weather patterns (WPs) in relation to heavy precipitation events during the baiu season in Japan are investigated using a nonlinear classification technique known as the self-organizing map (SOM). The analysis is performed on daily time scales using the Japanese 55-year Reanalysis Project (JRA-55) to determine the role of circulation and atmospheric moisture on extreme events and to investigate interannual and interdecadal variations for possible linkages with global-scale climate variability. SOM is simultaneously employed on four atmospheric variables over East Asia that are related to baiu front variability, whereby anomalous WPs that dominated during the 1958–2011 period are obtained. Our analysis extracts seven typical WPs, which are linked to frequent occurrences of heavy precipitation events. Each WP is associated with regional variations in the probability of extreme precipitation events. On interannual time scales, El Niño–Southern Oscillation (ENSO) affects the frequency of the WPs in relation to the heavy rainfall events. The warm phase of ENSO results in an increased frequency of a WP that provides a southwesterly intrusion of high equivalent potential temperature at low levels, while the cold phase provides southeastern intrusion. In addition, the results of this analysis suggest that interdecadal variability of frequency for heavy rainfall events corresponds to changes in frequency distributions of WPs and are not due to one particular WP.

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Linking ENSO and heavy rainfall events over coastal British Columbia through a weather pattern classification

Hydrology and Earth System Sciences ◽

10.5194/hess-17-1455-2013 ◽

2013 ◽

Vol 17 (4) ◽

pp. 1455-1473 ◽

Cited By ~ 12

Author(s):

P. Brigode ◽

Z. Mićović ◽

P. Bernardara ◽

E. Paquet ◽

F. Garavaglia ◽

...

Keyword(s):

British Columbia ◽

Heavy Rainfall ◽

Weather Forecasting ◽

Coastal Region ◽

Circulation Model ◽

Heavy Precipitation ◽

Global Circulation Model ◽

Bottom Up ◽

Rainfall Events ◽

Heavy Rainfall Events

Abstract. Classifications of atmospheric weather patterns (WPs) are widely used for the description of the climate of a given region and are employed for many applications, such as weather forecasting, downscaling of global circulation model outputs and reconstruction of past climates. WP classifications were recently used to improve the statistical characterisation of heavy rainfall. In this context, bottom-up approaches, combining spatial distribution of heavy rainfall observations and geopotential height fields have been used to define WP classifications relevant for heavy rainfall statistical analysis. The definition of WPs at the synoptic scale creates an interesting variable which could be used as a link between the global scale of climate signals and the local scale of precipitation station measurements. We introduce here a new WP classification centred on the British Columbia (BC) coastal region (Canada) and based on a bottom-up approach. Five contrasted WPs composed this classification, four rainy WPs and one non-rainy WP, the anticyclonic pattern. The four rainy WPs are mainly observed in the winter months (October to March), which is the period of heavy precipitation events in coastal BC and is thus consistent with the local climatology. The combination of this WP classification with the seasonal description of rainfall is shown to be useful for splitting observed precipitation series into more homogeneous sub-samples (i.e. sub-samples constituted by days having similar atmospheric circulation patterns) and thus identifying, for each station, the synoptic situations that generate the highest hazard in terms of heavy rainfall events. El Niño-Southern Oscillations (ENSO) significantly influence the frequency of occurrence of two coastal BC WPs. Within each WP, ENSO seem to influence only the frequency of rainy events and not the magnitudes of heavy rainfall events. Consequently, heavy rainfall estimations do not show significant evolution of heavy rainfall behaviour between Niño and Niña winters. However, the WP approach captures the variability of the probability of occurrences of synoptic situations generating heavy rainfall depending on ENSO and opening interesting perspectives for the analysis of heavy rainfall distribution in a non-stationary context.

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Thermal Effects of the Surface Heat Flux on Cloud Systems over the Tibetan Plateau in Boreal Summer

Journal of Climate ◽

10.1175/jcli-d-18-0604.1 ◽

2019 ◽

Vol 32 (15) ◽

pp. 4699-4714 ◽

Cited By ~ 5

Author(s):

Jinghua Chen ◽

Xiaoqing Wu ◽

Yan Yin ◽

Chunsong Lu ◽

Hui Xiao ◽

...

Keyword(s):

Tibetan Plateau ◽

Heavy Rainfall ◽

Surface Heat ◽

Heat Fluxes ◽

Boreal Summer ◽

The Tibetan Plateau ◽

Tropical Ocean ◽

Rainfall Events ◽

Surface Heat Fluxes ◽

Heavy Rainfall Events

ABSTRACT The influence of surface heat fluxes on the generation and development of cloud and precipitation and its relative importance to the large-scale circulation patterns are investigated via cloud-resolving model (CRM) simulations over the Tibetan Plateau (TP) during boreal summer. Over the lowland (e.g., along the middle and lower reaches of the Yangtze River), the dynamical and thermal properties of the atmosphere take more responsibility than the surface heat fluxes for the triggering of heavy rainfall events. However, the surface thermal driving force is a necessary criterion for the triggering of heavy rainfall in the eastern and western TP (ETP and WTP). Strong surface heat fluxes can trigger shallow convections in the TP. Furthermore, moisture that is mainly transported from the southern tropical ocean has a greater influence on the heavy rainfall events of the WTP than those of the ETP. Cloud microphysical processes are substantially less active and heavy rainfall cannot be produced when surface heat fluxes are weakened by half in magnitude over the TP. In addition, surface heating effects are largely responsible for the high occurrence frequency of convection during the afternoon, and the cloud tops of convective systems show a positive relationship with the intensity of surface heat fluxes.

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Atmospheric Rivers in Association with Summer Heavy Rainfall over the Yangtze Plain on Sub-seasonal Time Scale

10.5194/egusphere-egu21-8107 ◽

2021 ◽

Author(s):

Ping Liang ◽

Guangtao Dong ◽

Huqiang Zhang ◽

Mei Zhao ◽

Yue Ma

Keyword(s):

Time Scales ◽

Lead Time ◽

Heavy Rainfall ◽

East Asian ◽

Heavy Precipitation ◽

Rainfall Events ◽

Atmospheric Rivers ◽

The Tropics ◽

Heavy Rainfall Events ◽

Precipitation Events

Atmospheric Rivers (ARs), referring to long and narrow bands of enhanced water vapor transport, mainly from the tropics into the mid-latitudes in the low atmosphere. They often contribute to heavy rainfall generations outside the tropics. However, there is a lack of such AR studies in East Asia and it is still unclear how ARs act on different time scales during the boreal summer when frequent heavy precipitation events take place over the region. In this study, climatological ARs and their evolutions on both synoptic and sub-seasonal time scales associated with heavy rainfall events over the Yangtze Plain in China are investigated. Furthermore, its predictability is assessed by examining hindcast skills from an operational coupled seasonal forecast model. Results show that ARs embedded within the South Asian monsoon and Somali cross-equatorial flow provide a favorable background for steady moisture supply of summer rainfall into East Asia. We can call this favorable background as a climatological East Asian AR which has close connections with seasonal cycle and climatological intra-seasonal oscillation (CISO) of rainfall in the Yangtze Plain during its Meiyu season. The East Asian AR is also influenced by anomalous anti-cyclonic circulations over the tropical West Pacific when heavy rainfall events occur over the Yangtze Plain. Different from orography-induced precipitation, ARs leading to heavy rainfall over the Yangtze Plain are linked with the intrusions of cold air from its north. The major source of ARs responsible for heavy precipitation events over the Yangtze Plain appears to originate from tropical West Pacific on both synoptic and sub-seasonal time scales. By analyzing 23-yr hindcasts for May-June-July with start date of 1 May, we show that the current operational coupled seasonal forecast system of the Australian Bureau of Meteorology (named as ACCESS-S1) has skillful rainfall forecasts at lead-time of 0 month (i.e. forecasting May monthly mean with initial conditions on 1 May), but the skill degrades significantly at longer lead time. Nevertheless, the model shows skills in predicting the variations of low-level moisture transport affecting the Yangtze River at longer lead time, suggesting that the ARs influencing summer monsoon rainfall in the East Asian region are likely to be more predictable than rainfall itself. This provides a potential of utilizing the skill from the coupled forecast system in predicting ARs to guide its rainfall forecasts in the East Asian summer season at longer lead time.

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