scholarly journals Cluster Analysis Applied to Spatiotemporal Variability of Monthly Precipitation over Paraíba State Using Tropical Rainfall Measuring Mission (TRMM) Data

2019 ◽  
Vol 11 (6) ◽  
pp. 637 ◽  
Author(s):  
Celso Santos ◽  
Reginaldo Brasil Neto ◽  
Richarde da Silva ◽  
Samir Costa
Keyword(s):  
Cluster Analysis ◽  
Tropical Rainfall Measuring Mission ◽  
Spatiotemporal Variability ◽  
Monthly Precipitation ◽  
Trade Winds ◽  
Tropical Rainfall ◽  
Wave Disturbances ◽  
Easterly Wave ◽  
Precipitation Variation ◽  
Climate Systems

In Paraíba state, precipitation is strongly affected by several climate systems, such as trade winds, the intertropical convergence zone (ITCZ), easterly wave disturbances (EWDs), and the South Atlantic subtropical high. Accordingly, the objective of this study was to analyze the spatiotemporal variability in precipitation to identify homogeneous trends of that variable and the effects of climate systems in Paraíba state by cluster analysis. The precipitation data used in this study derive from the Tropical Rainfall Measuring Mission (TRMM) satellite for the period from January 1998 to December 2015, and hierarchical clustering was used to classify the sites into different groups with similar trends. The findings show an uneven spatiotemporal precipitation distribution in all mesoregions of the state and considerable monthly precipitation variation in space. The estimated precipitation depth was highest in coastal regions and in high-altitude areas due to orographic precipitation. In general, the precipitation over Paraíba is characterized by strong gradients in the coastal zone towards the continent (Agreste, Borborema, and Sertão mesoregions) and from north to south due to the physiography of the region and the effects of climate systems with different time scales. Finally, the proposed clustering method using TRMM data was effective in characterizing climatic systems.

scholarly journals Assessment of IMERG-V06 Precipitation Product over Different Hydro-Climatic Regimes in the Tianshan Mountains, North-Western China

2019 ◽  
Vol 11 (19) ◽  
pp. 2314 ◽  
Author(s):  
Anjum ◽  
Ahmad ◽  
Ding ◽  
Shangguan ◽  
Zaman ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Tianshan Mountains ◽  
Western China ◽  
Spatiotemporal Variability ◽  
Eastern Region ◽  
Monthly Precipitation ◽  
Precipitation Measurement ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Precipitation Events

This study presents an assessment of the version-6 (V06) of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) product from June 2014 to December 2017 over different hydro-climatic regimes in the Tianshan Mountains. The performance of IMERG-V06 was compared with IMERG-V05 and the Tropical Rainfall Measuring Mission (TRMM) 3B42V7 precipitation products. The precipitation products were assessed against gauge-based daily and monthly precipitation observations over the entire spatial domain and five hydro-climatologically distinct sub-regions. Results showed that: (1) The spatiotemporal variability of average daily precipitation over the study domain was well represented by all products. (2) All products showed better correlations with the monthly gauge-based observations than the daily data. Compared to 3B42V7, both IMERG products presented a better agreement with gauge-based observations. (3) The estimation skills of all precipitation products showed significant spatial variations. Overall performance of all precipitation products was better in the Eastern region compared to the Middle and Western regions. (4) Satellite products were able to detect tiny precipitation events, but they were uncertain in capturing light and moderate precipitation events. (5) No significant improvements in the precipitation estimation skill of IMERG-V06 were found as compared to IMERG-V05. We deduce that the IMERG-V06 precipitation detection capability could not outperform the efficiency of IMERG-V05. This comparative evaluation of the research products of Global Precipitation Measurement (GPM) and TRMM products in the Tianshan Mountains is useful for data users and algorithm developers.

scholarly journals Altitudinal Precipitation Gradients in the Tropics from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar

2015 ◽  
Vol 16 (1) ◽  
pp. 441-448 ◽  
Author(s):  
Alison M. Anders ◽  
Stephen W. Nesbitt
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
High Elevation ◽  
Specific Humidity ◽  
Trade Winds ◽  
Tropical Rainfall ◽  
Surface Precipitation ◽  
Lower Elevation ◽  
Precipitation Regimes ◽  
Moisture Fluxes ◽  
The Tropics

Abstract A Tropical Rainfall Measuring Mission (TRMM) climatology shows variability in surface precipitation rate–elevation relationships across the tropics. Vertical profiles of radar reflectivity and profiles of specific humidity and cross-barrier moisture fluxes during precipitation events from the Interim European Centre for Medium-Range Weather Forecasts Re-Analysis reveal four precipitation regimes with distinct precipitation mechanisms: 1) a tropical regime with a broad precipitation maximum at ~1500 m where convection is triggered by orographic lifting; 2) a trade winds regime with a near–sea level precipitation maximum dominated by forced ascent due to prevailing winds and the presence of dry air aloft; 3) a wet monsoon regime with a low-elevation precipitation maximum driven by efficient precipitation generation, large low-level cross-barrier moisture fluxes, and multiple convective modes; and 4) a dry monsoon regime with a high-elevation precipitation maximum reflecting intense convection and stratiform rain with a strong evaporation signature. In general, surface precipitation–elevation relationships across the tropics feature lower-elevation precipitation maxima relative to typical midlatitude regimes.

scholarly journals Validation of CHIRPS Precipitation Estimates over Taiwan at Multiple Timescales

2021 ◽  
Vol 13 (2) ◽  
pp. 254 ◽  
Author(s):  
Jie Hsu ◽  
Wan-Ru Huang ◽  
Pin-Yi Liu ◽  
Xiuzhen Li
Keyword(s):  
Annual Cycle ◽  
Interannual Variation ◽  
Winter Precipitation ◽  
Monthly Precipitation ◽  
Precipitation Estimation ◽  
Precipitation Estimates ◽  
Precipitation Variation ◽  
Global Precipitation ◽  
Multiple Timescale ◽  
Better Than

The Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), which incorporates satellite imagery and in situ station information, is a new high-resolution long-term precipitation dataset available since 1981. This study aims to understand the performance of the latest version of CHIRPS in depicting the multiple timescale precipitation variation over Taiwan. The analysis is focused on examining whether CHIRPS is better than another satellite precipitation product—the Integrated Multi-satellitE Retrievals for Global Precipitation Mission (GPM) final run (hereafter IMERG)—which is known to effectively capture the precipitation variation over Taiwan. We carried out the evaluations made for annual cycle, seasonal cycle, interannual variation, and daily variation during 2001–2019. Our results show that IMERG is slightly better than CHIRPS considering most of the features examined; however, CHIRPS performs better than that of IMERG in representing the (1) magnitude of the annual cycle of monthly precipitation climatology, (2) spatial distribution of the seasonal mean precipitation for all four seasons, (3) quantitative precipitation estimation of the interannual variation of area-averaged winter precipitation in Taiwan, and (4) occurrence frequency of the non-rainy grids in winter. Notably, despite the fact that CHIRPS is not better than IMERG for many examined features, CHIRPS can depict the temporal variation in precipitation over Taiwan on annual, seasonal, and interannual timescales with 95% significance. This highlights the potential use of CHIRPS in studying the multiple timescale variation in precipitation over Taiwan during the years 1981–2000, for which there are no data available in the IMERG database.

Comparison Between Estimated Rainfall Estimated by the Tropical Rainfall Measuring Mission (TRMM) Satellite and Data Observed in the Lagoa Mirim/RS Basin, Brazil

INCREaSE 2019 ◽  
2019 ◽  
pp. 97-110
Author(s):  
Géri Eduardo Meneghello ◽  
Letícia Burkert Méllo ◽  
Ritâ De Cassia Fraga Damé ◽  
Francisco Amaral Villela ◽  
Maria Clotilde Carré Chagas Neta ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Tropical Rainfall

scholarly journals Global Evaluation of Seasonal Precipitation and Temperature Forecasts from NMME

2020 ◽  
Vol 21 (11) ◽  
pp. 2473-2486
Author(s):  
Tirthankar Roy ◽  
Xiaogang He ◽  
Peirong Lin ◽  
Hylke E. Beck ◽  
Christopher Castro ◽  
...  
Keyword(s):  
Phase 1 ◽  
Research Unit ◽  
Forecast Skill ◽  
Precipitation Forecast ◽  
Spatiotemporal Variability ◽  
Lead Times ◽  
Global Evaluation ◽  
Monthly Precipitation ◽  
Tropical Regions ◽  
Precipitation And Temperature

AbstractWe present a comprehensive global evaluation of monthly precipitation and temperature forecasts from 16 seasonal forecasting models within the NMME Phase-1 system, using Multi-Source Weighted-Ensemble Precipitation version 2 (MSWEP-V2; precipitation) and Climate Research Unit TS4.01 (CRU-TS4.01; temperature) data as reference. We first assessed the forecast skill for lead times of 1–8 months using Kling–Gupta efficiency (KGE), an objective performance metric combining correlation, bias, and variability. Next, we carried out an empirical orthogonal function (EOF) analysis to compare the spatiotemporal variability structures of the forecasts. We found that, in most cases, precipitation skill was highest during the first lead time (i.e., forecast in the month of initialization) and rapidly dropped thereafter, while temperature skill was much higher overall and better retained at higher lead times, which is indicative of stronger temporal persistence. Based on a comprehensive assessment over 21 regions and four seasons, we found that the skill showed strong regional and seasonal dependencies. Some tropical regions, such as the Amazon and Southeast Asia, showed high skill even at longer lead times for both precipitation and temperature. Rainy seasons were generally associated with high precipitation skill, while during winter, temperature skill was low. Overall, precipitation forecast skill was highest for the NASA, NCEP, CMC, and GFDL models, and for temperature, the NASA, CFSv2, COLA, and CMC models performed the best. The spatiotemporal variability structures were better captured for precipitation than temperature. The simple forecast averaging did not produce noticeably better results, emphasizing the need for more advanced weight-based averaging schemes.

scholarly journals Spatiotemporal Variability of Lightning Flash Distribution over Sri Lanka

2019 ◽  
Vol 82 ◽  
pp. 1-13
Author(s):  
U.G.Dilaj Maduranga ◽  
Mahesh Edirisinghe ◽  
L. Vimukthi Gamage
Keyword(s):  
Sri Lanka ◽  
Monsoon Season ◽  
Tropical Rainfall Measuring Mission ◽  
Spatiotemporal Variability ◽  
Spatial And Temporal Variation ◽  
Lightning Flash ◽  
Northeast Monsoon ◽  
Time Period ◽  
Total Lightning ◽  
Imaging Sensor

The variation of the lightning activities over Sri Lanka and surrounded costal belt (5.750N-10.000N and 79.50E-89.000E) is studied using lightning flash data of Lightning Imaging Sensor (LIS) which was launched in November 1997 for NASA’s Tropical Rainfall Measuring Mission (TRMM). The LIS data for the period of 1998 to 2014 are considered for this study. The spatial and temporal variation of lightning activities is investigated and respective results are presented. The diurnal variation over the studied area presents that maximum and minimum flash count recorded at 1530-1630 Local Time (10-11UTC) and 0530-0630LT (00-01UTC) respectively. Maximum lightning activities over the observed area have occurred after the 1330LT (08UTC) in every year during the considered time period. The seasonal variation of the lightning activities shows that the maximum lightning activities happened in First inter monsoon season (March to April) with 30.90% total lightning flashes and minimum lightning activities recorded in Northeast monsoon season (December to February) with 8.51% of total lightning flashes. Maximum flash density of 14.37fl km-2year-1 was observed at 6.980N/80.160E in First inter monsoon season. These seasonal lighting activities are agree with seasonal convective activities and temperature variation base on propagation of Intra-Tropical Convection Zone over the studied particular area. Mean monthly flash count presents a maximum in the month of April with 29.12% of lightning flashes. Variation pattern of number of lightning activities in month of April shows a tiny increment during the time period of 1998 to 2014. Maximum annual flash density of 28.09fl km-2yr-1 was observed at 6.980N/80.170E. The latitudinal variation of the lightning flash density is depicted that extreme lightning activities have happened at the southern part of the county and results show that there is a noticeable lack of lightning activities over the surrounded costal belt relatively landmass.

Sign in / Sign up

Export Citation Format

Share Document