scholarly journals Characteristics of Summer Precipitation around the Western Ghats and the Myanmar West Coast

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Dibas Shrestha ◽  
Rashila Deshar ◽  
Kenji Nakamura
Keyword(s):  
West Coast ◽  
Western Ghats ◽  
Large Scale ◽  
Summer Precipitation ◽  
Tropical Rainfall Measuring Mission ◽  
Precipitation Radar ◽  
Maximum Rainfall ◽  
Trmm Precipitation ◽  
The Western Ghats ◽  
Coastal Mountain

Characteristics of summer (June–August) precipitation over two coastal mountain regions in South Asia (Western Ghats: WG and Myanmar West Coast: MWC) with a focus on topographic impact are analyzed using the 13-year (1998–2010) high spatial resolution (0.05° × 0.05°) version 6 data obtained from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). A relationship between precipitation patterns and topography was observed in the coastal mountains. In both the WG and MWC, maximum rainfall along a tight line on the upwind side of the coastal mountains is primarily attributed to rain frequency. However, intense precipitation was observed over the offshore regions. Compared with the WG, deeper and large-scale precipitation systems develop over the MWC, producing more intense rainfall. It is suggested that insufficient humidity deters large-scale convection over the WG, and the atmosphere is sufficiently moist over the MWC.

scholarly journals Relationships between Rain Characteristics and Environment. Part I: TRMM Precipitation Features and the Large-Scale Environment over the Tropical Pacific

2012 ◽  
Vol 140 (9) ◽  
pp. 2831-2840 ◽  
Author(s):  
Chie Yokoyama ◽  
Yukari N. Takayabu
Keyword(s):  
Large Scale ◽  
Tropical Rainfall Measuring Mission ◽  
Warm Pool ◽  
Intertropical Convergence Zone ◽  
The Other ◽  
Precipitation Radar ◽  
Trmm Precipitation ◽  
Highly Correlated ◽  
The Western Pacific ◽  
The Tropical Pacific

Abstract Differences in the characteristics of rain systems in the eastern Pacific (EP) intertropical convergence zone (ITCZ) and the western Pacific (WP) warm pool are quantitatively examined in relation to the large-scale environment. This study mainly uses precipitation feature (PF) data observed by the precipitation radar (PR) on board the Tropical Rainfall Measuring Mission (TRMM). The PFs are classified into four types according to their areas and maximum heights. Rain from tall unorganized systems and very tall organized systems tends to be dominant in high-SST regions such as the WP. On the other hand, the EP has more rain from congestus and organized systems with moderate heights than the WP. It is shown that shallow rain from congestus and moderately deep rain from organized systems are highly correlated with shallow (1000–925 hPa) convergence fields with coefficients of 0.75 and 0.66, respectively. These relationships between characteristics of rain systems and the large-scale environment are robust through all seasons.

Precipitation modes over the Western Ghats orography during the summer monsoon season

2021 ◽  
Author(s):  
Jayesh Phadtare ◽  
Jennifer Fletcher ◽  
Andrew Ross ◽  
Andy Turner ◽  
Thorwald Stein ◽  
...  
Keyword(s):  
Summer Monsoon ◽  
West Coast ◽  
Western Ghats ◽  
Monsoon Season ◽  
Radiosonde Data ◽  
Summer Monsoon Season ◽  
The West ◽  
Radiosonde Station ◽  
Westerly Flow ◽  
The Western Ghats

<p>Precipitation distribution around an orographic barrier is controlled by the Froude Number (Fr) of the impinging flow. Fr is essentially a ratio of kinetic energy and stratification of winds around the orography. For Fr > 1 (Fr <1), the flow is unblocked (blocked) and precipitation occurs over the mountain peaks and the lee region (upwind region). While idealized modelling studies have robustly established this relationship, its widespread real-world application is hampered by the dearth of relevant observations. Nevertheless, the data collected in the field campaigns give us an opportunity to explore this relationship and provide a testbed for numerical models. A realistic distribution of precipitation over a mountainous region in these models is necessary for flash-flood and landslide forecasting. The Western Ghats region is a classic example where the orographically induced precipitation leads to floods and landslides during the summer monsoon season. In the recent INCOMPASS field campaign, it was shown that the precipitation over the west coast of India occurred in alternate offshore and onshore phases. The Western Ghats received precipitation predominantly during the onshore phase which was characterized by a stronger westerly flow. Here, using the radiosonde data from a station over the Indian west coast and IMERG precipitation product, we show that climatologically, these phases can be mapped over an Fr-based classification of the monsoonal westerly flow. Classifying the flow as 'High Fr' (Fr >1), 'Moderate Fr' ( 0.5 < Fr ≤ 1) and 'Low Fr' ( Fr ≤ 0.5 ) gives three topographical modes of precipitation -- 'Orographic', 'Coastal' and 'Offshore', respectively.  Moreover, these modes are not sensitive to the choice of radiosonde station over the west coast.</p>

Two Notes on Ptolemy's Geography of India

1941 ◽  
Vol 73 (3) ◽  
pp. 208-222 ◽  
Author(s):  
E. H. Johnston
Keyword(s):  
West Coast ◽  
Western Ghats ◽  
The West ◽  
Market Town ◽  
The City ◽  
The Town ◽  
Good Access ◽  
The Western Ghats ◽  
Market Towns

The Periplus Marts Erythræ describes the seaports below Barygaza in the following way according to Schoff's translation: “The market-towns of this region are, in order, after Barygaza: Suppara, and the city of Calliena, which in the time of the elder Saraganus became a lawful market-town; but since it came into the possession of Sandares [an unjustified conjecture for the text's Sandanes] the port is much obstructed, and Greek ships landing there may chance to be taken to Barygaza under guard. Beyond Calliena there are other market-towns of this region; Semylla.…” Suppara is now Sopara on the coast above Bassein, Semylla is Cemūla of two inscriptions, now Chaul, and Calliena is Kalyāṇa. This last, situated at the foot of the two regular ascents of the Western Ghats leading towards Nasik and Poona respectively and with good access to the sea, was the natural outlet for the commerce of the Andhra dominions on the west coast, and the notice, just quoted, shows how its trade was stifled, as the Kṣaharātas extended their rule southwards from Broach. It is unnecessary here to consider who are the kings alluded to in this passage or in the earlier one mentioning Nambanus (a conjecture for the text's Mambarus), but clearly we are dealing with the rivalry of the Western Satraps and the Andhra kings. That the former were successful in their policy towards Kalyāṇa is shown by Ptolemy's omission of the town. The order he gives (taking Renou's text) is Souppara mouth of the River Goaris, Dounga, mouth of the River Bêndas, Semyla.

scholarly journals Impact of Misrepresentation of Freezing-Level Height by the TRMM Algorithm on Shallow Rain Statistics over India and Adjoining Oceans

2013 ◽  
Vol 52 (9) ◽  
pp. 2001-2008 ◽  
Author(s):  
K. Saikranthi ◽  
T. Narayana Rao ◽  
B. Radhakrishna ◽  
S. Vijaya Bhaskara Rao
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Precipitation Radar ◽  
Study Region ◽  
Freezing Level ◽  
Northwestern India ◽  
Trmm Precipitation ◽  
Radar Measurements ◽  
The Impact ◽  
The Himalaya ◽  
Level Height

AbstractThe estimation of freezing level-height (FLH) by the Tropical Rainfall Measuring Mission (TRMM) algorithm is evaluated, against several other data sources, over India and adjoining oceans. It is observed that the TRMM algorithm either underestimates or overestimates the FLH [relative to radiosonde- and ECMWF Interim Re-Analysis (ERA)-derived FLH] at latitudes > 20°N over India. The agreement between the FLHs obtained from ERA and radiosonde and the TRMM-derived brightband height suggests that usage of ERA-derived FLH may improve shallow rain statistics. The impact of misrepresentation of FLH by the TRMM algorithm on shallow rain statistics is assessed by using 13 yr of TRMM precipitation radar measurements. It is noted that the misidentification of FLH alone affects (mostly underestimates) the shallow rain occurrence and rain fraction by 3%–8% over the study region. The magnitude of underestimation is large over the southern slopes of the Himalaya, the northern plains, and in northwestern India. TRMM identifies most of the shallow rain (30%–50%) as cold rain in regions where the underestimation of FLH is high. This situation could introduce some error in the correction of reflectivity for attenuation and in the retrieval of latent heat profiles.

scholarly journals Precipitation climatology over Mediterranean Basin from ten years of TRMM measurements

2008 ◽  
Vol 17 ◽  
pp. 87-91 ◽  
Author(s):  
A. V. Mehta ◽  
S. Yang
Keyword(s):  
Mediterranean Sea ◽  
Rainy Season ◽  
Mediterranean Region ◽  
Large Scale ◽  
Eastern Mediterranean ◽  
Tropical Rainfall Measuring Mission ◽  
Western Mediterranean ◽  
Sea Temperature ◽  
Maximum Rainfall ◽  
The Mediterranean

Abstract. Climatological features of mesoscale rain activities over the Mediterranean region between 5° W–40° E and 28° N–48° N are examined using the Tropical Rainfall Measuring Mission (TRMM) 3B42 and 2A25 rain products. The 3B42 rainrates at 3-hourly, 0.25°×0.25° spatial resolution for the last 10 years (January 1998 to July 2007) are used to form and analyze the 5-day mean and monthly mean climatology of rainfall. Results show considerable regional and seasonal differences of rainfall over the Mediterranean Region. The maximum rainfall (3–5 mm day−1) occurs over the mountain regions of Europe, while the minimum rainfall is observed over North Africa (~0.5 mm day−1). The main rainy season over the Mediterranean Sea extends from October to March, with maximum rainfall occurring during November–December. Over the Mediterranean Sea, an average rainrate of ~1–2 mm day−1 is observed, but during the rainy season there is 20% larger rainfall over the western Mediterranean Sea than that over the eastern Mediterranean Sea. During the rainy season, mesoscale rain systems generally propagate from west to east and from north to south over the Mediterranean region, likely to be associated with Mediterranean cyclonic disturbances resulting from interactions among large-scale circulation, orography, and land-sea temperature contrast.

scholarly journals Differences of Rainfall Estimates over Land by Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and TRMM Microwave Imager (TMI)—Dependence on Storm Height

2005 ◽  
Vol 44 (3) ◽  
pp. 367-383 ◽  
Author(s):  
Fumie A. Furuzawa ◽  
Kenji Nakamura
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Local Times ◽  
Precipitation Radar ◽  
Tropical Rainfall ◽  
Convective Rain ◽  
Brightness Temperatures ◽  
Trmm Precipitation ◽  
Microwave Imager ◽  
Trmm Microwave Imager ◽  
Orbit Data

Abstract It is well known that precipitation rate estimation is poor over land. Using the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and TRMM Microwave Imager (TMI), the performance of the TMI rain estimation was investigated. Their differences over land were checked by using the orbit-by-orbit data for June 1998, December 1998, January 1999, and February 1999, and the following results were obtained: 1) Rain rate (RR) near the surface for the TMI (TMI-RR) is smaller than that for the PR (PR-RR) in winter; it is also smaller from 0900 to 1800 LT. These dependencies show some variations at various latitudes or local times. 2) When the storm height is low (<5 km), the TMI-RR is smaller than the PR-RR; when it is high (>8 km), the PR-RR is smaller. These dependencies of the RR on the storm height do not depend on local time or latitude. The tendency for a TMI-RR to be smaller when the storm height is low is more noticeable in convective rain than in stratiform rain. 3) Rain with a low storm height predominates in winter or from 0600 to 1500 LT, and convective rain occurs frequently from 1200 to 2100 LT. Result 1 can be explained by results 2 and 3. It can be concluded that the TMI underestimates rain with low storm height over land because of the weakness of the TMI algorithm, especially for convective rain. On the other hand, it is speculated that TMI overestimates rain with high storm height because of the effect of anvil rain with low brightness temperatures at high frequencies without rain near the surface, and because of the effect of evaporation or tilting, which is indicated by a PR profile and does not appear in the TMI profile. Moreover, it was found that the PR rain for the cases with no TMI rain amounted to about 10%–30% of the total but that the TMI rain for the cases with no PR rain accounted for only a few percent of the TMI rain. This result can be explained by the difficulty of detecting shallow rain with the TMI.

Morphology, Intensity, and Rainfall Production of MJO Convection: Observations from DYNAMO Shipborne Radar and TRMM

2015 ◽  
Vol 72 (2) ◽  
pp. 623-640 ◽  
Author(s):  
Weixin Xu ◽  
Steven A. Rutledge
Keyword(s):  
Mesoscale Convective System ◽  
Tropical Rainfall Measuring Mission ◽  
Radar Data ◽  
Convective System ◽  
Precipitation Radar ◽  
Convective Systems ◽  
Trmm Pr ◽  
Mesoscale Convective ◽  
Trmm Precipitation

Abstract This study uses Dynamics of the Madden–Julian Oscillation (DYNAMO) shipborne [Research Vessel (R/V) Roger Revelle] radar and Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) datasets to investigate MJO-associated convective systems in specific organizational modes [mesoscale convective system (MCS) versus sub-MCS and linear versus nonlinear]. The Revelle radar sampled many “climatological” aspects of MJO convection as indicated by comparison with the long-term TRMM PR statistics, including areal-mean rainfall (6–7 mm day−1), convective intensity, rainfall contributions from different morphologies, and their variations with MJO phase. Nonlinear sub-MCSs were present 70% of the time but contributed just around 20% of the total rainfall. In contrast, linear and nonlinear MCSs were present 10% of the time but contributed 20% and 50%, respectively. These distributions vary with MJO phase, with the largest sub-MCS rainfall fraction in suppressed phases (phases 5–7) and maximum MCS precipitation in active phases (phases 2 and 3). Similarly, convective–stratiform rainfall fractions also varied significantly with MJO phase, with the highest convective fractions (70%–80%) in suppressed phases and the largest stratiform fraction (40%–50%) in active phases. However, there are also discrepancies between the Revelle radar and TRMM PR. Revelle radar data indicated a mean convective rain fraction of 70% compared to 55% for TRMM PR. This difference is mainly due to the reduced resolution of the TRMM PR compared to the ship radar. There are also notable differences in the rainfall contributions as a function of convective intensity between the Revelle radar and TRMM PR. In addition, TRMM PR composites indicate linear MCS rainfall increases after MJO onset and produce similar rainfall contributions to nonlinear MCSs; however, the Revelle radar statistics show the clear dominance of nonlinear MCS rainfall.

scholarly journals A 0.01° Resolving TRMM PR Precipitation Climatology

2018 ◽  
Vol 57 (8) ◽  
pp. 1645-1661 ◽  
Author(s):  
M. Hirose ◽  
K. Okada
Keyword(s):  
High Resolution ◽  
Sampling Error ◽  
Tropical Rainfall Measuring Mission ◽  
Radar Data ◽  
Yakushima Island ◽  
Maximum Rainfall ◽  
High Resolution Data ◽  
Valley Side ◽  
Trmm Precipitation ◽  
Spaceborne Radar

AbstractIn this study, rainfall data are prepared at a 0.01° scale using 16-yr spaceborne radar data over the area of 36.13°S–36.13°N as provided by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). A spatial resolution that is finer than the field of view is obtained by assuming rainfall uniformity within an instantaneous footprint centered on the PR footprint geolocation. These ultra-high-resolution data reveal local rainfall concentrations over slope areas. A new estimate of the maximum rainfall at Cherrapunji, India, was observed on the valley side, approximately 5 km east of the gauge station, and is approximately 50% higher than the value indicated by the 0.1°-scale data. A case study of Yakushima Island, Japan, indicates that several percent of the sampling error arising from the spatial mismatch may be contained in conventional 0.05°-scale datasets generated without footprint areal information. The differences attributable to the enhancement in the resolution are significant in complex terrain such as the Himalayas. The differences in rainfall averaged for the 0.1° and 0.01° scales exceed 10 mm day−1 over specific slope areas. In the case of New Guinea, the mean rainfall on a mountain ridge can be 30 times smaller than that on an adjacent slope at a distance of 0.25°; this is not well represented by other high-resolution datasets based on gauges and infrared radiometers. The substantial nonuniformity of rainfall climatology highlights the need for a better understanding of kilometer-scale geographic constraints on rainfall and retrieval approaches.

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