scholarly journals Evaluation of High-Resolution Satellite-Based Real-Time and Post-Real-Time Precipitation Estimates during 2010 Extreme Flood Event in Swat River Basin, Hindukush Region

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Muhammad Naveed Anjum ◽  
Yongjian Ding ◽  
Donghui Shangguan ◽  
Muhammad Wajid Ijaz ◽  
Shiqiang Zhang
Keyword(s):  
Real Time ◽  
Correlation Coefficient ◽  
Spatial Correlation ◽  
River Basin ◽  
Heavy Precipitation ◽  
Precipitation Event ◽  
Extreme Precipitation Events ◽  
Extreme Flood ◽  
Precipitation Estimates ◽  
Swat River

Satellite-based real-time and post-real-time precipitation estimates of Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA-3B42) were evaluated during an extreme heavy precipitation event (on 28–30 July 2010) over Swat River Basin and adjacent areas in Hindukush Region. Observations of 15 rain gauging stations were used for the evaluation of TMPA products. Results showed that the spatial pattern of precipitation in the event was generally captured by post-real-time product (3B42V7) but misplaced by real-time product (3B42RT), witnessed by a high spatial correlation coefficient for 3B42V7 (CC = 0.87) and low spatial correlation coefficient for 3B42RT (CC = 0.20). The temporal variation of the storm precipitation was not well captured by both TMPA products. 3B42V7 product underestimated the storm accumulated precipitation by 32.15%, while underestimation by 3B42RT was 66.73%. Based on the findings of this study, we suggest that the latest TMPA-based precipitation products, 3B42RT and 3B42V7, might not be able to perform well during extreme precipitation events, particularly in complex terrain regions like Hindukush Mountains. Therefore, cautions should be considered while using 3B42RT and 3B42V7 as input data source for the modelling, forecasting, and monitoring of floods and potential landslides in Hindukush Region.

scholarly journals Evaluation of Numerical Weather Model–Based Satellite Precipitation Adjustment in Tropical Mountainous Regions

2019 ◽  
Vol 20 (3) ◽  
pp. 431-445 ◽  
Author(s):  
Xinxuan Zhang ◽  
Emmanouil N. Anagnostou
Keyword(s):  
Real Time ◽  
Heavy Precipitation ◽  
Precipitation Event ◽  
Satellite Precipitation ◽  
Numerical Weather ◽  
Mountainous Regions ◽  
Numerical Weather Model ◽  
Weather Model ◽  
Precipitation Estimates ◽  
Daily Scale

Abstract The study evaluated a numerical weather model (WRF)-based satellite precipitation adjustment technique with 81 heavy precipitation events that occurred in three tropical mountainous regions (Colombia, Peru, and Taiwan). The technique was applied on two widely used near-real-time global satellite precipitation products—the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center morphing technique (CMORPH) and the Global Satellite Mapping of Precipitation project (GSMaP)—for each precipitation event. The WRF-adjusted satellite products along with the near-real-time and gauge-adjusted satellite products as well as the WRF simulation were evaluated by independent gauge networks at daily scale and event total scale. Results show that the near-real-time precipitation products exhibited severe underestimation relative to the gauge observations over the three tropical mountainous regions. The underestimation tended to be larger for higher rainfall accumulations. The WRF-based satellite adjustment provided considerable improvements to the near-real-time CMORPH and GSMaP products. Moreover, error metrics show that WRF-adjusted satellite products outperformed the gauge-adjusted counterparts for most of the events. The effectiveness of WRF-based satellite adjustment varied with events of different physical processes. Thus, the technique applied on satellite precipitation estimates of these events may exhibit inconsistencies in the bias correction.

Evaluation of GEOS Precipitation Flagging for SMAP Soil Moisture Retrieval Accuracy

2021 ◽  
Author(s):  
Maheshwari Neelam ◽  
Rajat Bindlish ◽  
Peggy O’Neill ◽  
George J. Huffman ◽  
Rolf Reichle ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Weather Prediction ◽  
Heavy Precipitation ◽  
Precipitation Event ◽  
Retrieval Accuracy ◽  
Accuracy Requirement ◽  
Earth Observing System ◽  
Precipitation Estimates ◽  
Global Precipitation Mission ◽  
Global Precipitation

The precipitation flag in the Soil Moisture Active Passive (SMAP) Level 2 passive soil moisture (L2SMP) retrieval product indicates the presence or absence of heavy precipitation at the time of the SMAP overpass. The flag is based on precipitation estimates from the Goddard Earth Observing System (GEOS) Forward Processing numerical weather prediction system. An error in flagging during an active or recent precipitation event can either (1) produce an overestimation of soil moisture due to short-term surface wetting of vegetation and/or surface ponding (if soil moisture retrieval was attempted in the presence of rain), or (2) produce an unnecessary non-retrieval of soil moisture and loss of data (if retrieval is flagged due to an erroneous indication of rain). Satellite precipitation estimates from the Integrated Multi-satellite Retrievals for GPM (IMERG) Version 06 Early Run (latency of ~4 hrs) precipitationCal product are used here to evaluate the GEOS-based precipitation flag in the L2SMP product for both the 6 PM ascending and 6 AM descending SMAP overpasses over the first five years of the mission (2015-2020). Consisting of blended precipitation measurements from the GPM (Global Precipitation Mission) satellite constellation, IMERG is treated as the “truth” when comparing to the GEOS model forecasts of precipitation used by SMAP. Key results include: i) IMERG measurements generally show higher spatial variability than the GEOS forecast precipitation, ii) the IMERG product has a higher frequency of light precipitation amounts, and iii) the effect of incorporating IMERG rainfall measurements in lieu of GEOS precipitation forecasts are minimal on the L2SMP retrieval accuracy (determined vs. in situ soil moisture measurements at core validation sites). Our results indicate that L2SMP retrievals continue to meet the mission’s accuracy requirement (standard deviation of the ubRMSE less than 0.04 m3/m3).

On the use of Geostationary Lightning Mapper data as proxy for heavy precipitation

2020 ◽  
Author(s):  
Vandoir Bourscheidt ◽  
Maria-Helena Ramos
Keyword(s):  
Kernel Method ◽  
Heavy Precipitation ◽  
Comparison Method ◽  
Convective Precipitation ◽  
Gaussian Kernel ◽  
Climate Change Scenarios ◽  
Spatial And Temporal Scales ◽  
Extreme Precipitation Events ◽  
Precipitation Estimates ◽  
Total Lightning

<p>In view of the likely increase of thunderstorm and extreme precipitation events under climate change scenarios, alternatives to improve the estimates of rainfall and the understanding of the runoff response to extreme events are relevant, especially in areas with low or absent radar or raingauge coverage. Efforts in this direction have resulted, for example, on the Global Precipitation Measurement (GPM) products, which offer potentially useful estimates of precipitation over relatively fine spatial and temporal scales. With the launch of GOES 16 satellite, with its new Geostationary Lightning Mapper (GLM) instrument and improved visible and infrared imagery (with the Advanced Baseline Imager - ABI), new possibilities emerge in the analysis of (severe) convective precipitation and its impact on runoff. In this work, we analyze the relationship between lightning activity and rainfall, with the aim to estimate how total lightning data can be used as proxy of (heavy) precipitation estimates. GLM data is evaluated against weather radar in three different ways: (1) based on a Gaussian Kernel method; (2) using a simple dot-count approach, and (3) using the operational GLM gridded product, built on the ABI fixed grid (2 x 2 km). Two sample strategies are evaluated: a pixel-based comparison and a comparison method that extracts statistics inside polygons (using watersheds). For all cases, both group and flash data from GLM are used. The study area focuses on the southeastern and central-west regions of Brazil, where developments towards enhanced flood nowcasting and warning systems capabilities have been carried out in order to anticipate flash floods and prevent flood damages in the future.</p>

scholarly journals Tuning Extreme NEXRAD and CMORPH Precipitation Estimates

2014 ◽  
Vol 15 (3) ◽  
pp. 1070-1077 ◽  
Author(s):  
Jonathan Woody ◽  
Robert Lund ◽  
Mekonnen Gebremichael
Keyword(s):  
Pareto Distribution ◽  
Generalized Pareto Distribution ◽  
Heavy Precipitation ◽  
Generalized Pareto ◽  
Extreme Precipitation Events ◽  
Precipitation Estimates ◽  
Alternative Sources ◽  
Climate Prediction Center ◽  
Adequate Ground ◽  
Precipitation Events

Abstract High-resolution satellite precipitation estimates, such as the Climate Prediction Center morphing technique (CMORPH), provide alternative sources of precipitation data for hydrological applications, especially in regions where adequate ground-based instruments are unavailable. These estimates are, however, subject to large errors, especially at times of heavy precipitation. This paper presents a method to distributionally convert a set of CMORPH estimates into ground-based Next Generation Weather Radar (NEXRAD) estimates. As our concern lies with floods and extreme precipitation events, a peaks-over-threshold extreme value approach is adopted that fits a generalized Pareto distribution to the large precipitation estimates. A quantile matching transformation is then used to convert CMORPH values into NEXRAD values. The methods are applied in the analysis of 6 yr of precipitation observations from 625 pixels centered around eastern Oklahoma.

scholarly journals Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi)

2014 ◽  
Vol 11 (1) ◽  
pp. 1169-1201 ◽  
Author(s):  
D. Kneis ◽  
C. Chatterjee ◽  
R. Singh
Keyword(s):  
Real Time ◽  
River Basin ◽  
Stream Flow ◽  
Remotely Sensed ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Rain Gage ◽  
Precipitation Estimates ◽  
Rainfall Estimates

Abstract. The paper examines the quality of satellite-based precipitation estimates for the Lower Mahanadi River Basin (Eastern India). The considered data sets known as 3B42 and 3B42-RT (version 7/7A) are routinely produced by the tropical rainfall measuring mission (TRMM) from passive microwave and infrared recordings. While the 3B42-RT data are disseminated in real time, the gage-adjusted 3B42 data set is published with a delay of some months. The quality of the two products was assessed in a two-step procedure. First, the correspondence between the remotely sensed precipitation rates and rain gage data was evaluated at the sub-basin scale. Second, the quality of the rainfall estimates was assessed by analyzing their performance in the context of rainfall-runoff simulation. At sub-basin level (4000 to 16 000 km2) the satellite-based areal precipitation estimates were found to be moderately correlated with the gage-based counterparts (R2 of 0.64–0.74 for 3B42 and 0.59–0.72 for 3B42-RT). Significant discrepancies between TRMM data and ground observations were identified at high intensity levels. The rainfall depth derived from rain gage data is often not reflected by the TRMM estimates (hit rate < 0.6 for ground-based intensities > 80 mm day−1). At the same time, the remotely sensed rainfall rates frequently exceed the gage-based equivalents (false alarm ratios of 0.2–0.6). In addition, the real time product 3B42-RT was found to suffer from a spatially consistent negative bias. Since the regionalization of rain gage data is potentially associated with a number of errors, the above results are subject to uncertainty. Hence, a validation against independent information, such as stream flow, was essential. In this case study, the outcome of rainfall–runoff simulation experiments was consistent with the above-mentioned findings. The best fit between observed and simulated stream flow was obtained if rain gage data were used as model input (Nash–Sutcliffe Index of 0.76–0.88 at gages not affected by reservoir operation). This compares to the values of 0.71–0.78 for the gage-adjusted TRMM 3B42 data and 0.65–0.77 for the 3B42-RT real-time data. Whether the 3B42-RT data are useful in the context of operational runoff prediction in spite of the identified problems remains a question for further research.

Statistics of 20 years of heavy precipitation events in Germany from radar data

2021 ◽  
Author(s):  
Katharina Lengfeld ◽  
Ewelina Walawender ◽  
Tanja Winterrath ◽  
Elmar Weigl ◽  
Andreas Becker
Keyword(s):  
Temporal Structure ◽  
Heavy Precipitation ◽  
Radar Data ◽  
Easy Access ◽  
Data Set ◽  
Extreme Precipitation Events ◽  
Radar Networks ◽  
Temporal And Spatial Variability ◽  
Precipitation Estimates ◽  
Precipitation Events

&lt;p&gt;Extreme precipitation events are expected to occur more frequently in a warming climate. Understanding their structure and predicting the exact time and location of precipitation events still remains a challenge because of the high temporal and spatial variability of rainfall. Nationwide weather radar networks are a common tool for investigating precipitation events and their spatial and temporal structure. The German Weather Service (DWD) provides a nationwide climatological radar data set from 2001 to 2020. A reprocessing procedure has been applied to reflectivity measurements in order to obtain precipitation estimates as homogeneous as possible. With an object-oriented analysis, all precipitation events for 11 different durations from 1 to 72 hours exceeding DWD&amp;#8217;s official warning level for heavy precipitation have been detected and statistically analysed.&lt;/p&gt;&lt;p&gt;We will present a comprehensive analysis of all heavy precipitation events that occurred in Germany between 2001 and 2020. We examined their size, duration, location, spatial structure and distribution as well as regional and climatological differences and demonstrate how this information is collected in an online tool for easy access. An assessment of how well these heavy precipitation events were captured by DWD&amp;#8217;s network of precipitation stations will be given. Finally, we will present the possibility to use the event detection procedure as an operational tool for assessing and classifying heavy precipitation events and their potential impact in near real-time.&lt;/p&gt;

Representation of Precipitation Characteristics and Extremes in Regional Reanalyses and Satellite- and Gauge-Based Estimates over Western and Central Europe

2019 ◽  
Vol 20 (6) ◽  
pp. 1123-1145 ◽  
Author(s):  
M. Lockhoff ◽  
O. Zolina ◽  
C. Simmer ◽  
J. Schulz
Keyword(s):  
Central Europe ◽  
Spatial Scales ◽  
Rain Gauge ◽  
Added Value ◽  
Precipitation Event ◽  
Precipitation Frequency ◽  
Frequency Distributions ◽  
Extreme Precipitation Events ◽  
Precipitation Regimes ◽  
Precipitation Estimates

Abstract This paper evaluates several daily precipitation products over western and central Europe, identifies and documents their respective strengths and shortcomings, and relates these to uncertainties associated with each of the products. We analyze one gauge-based, three satellite-based, and two reanalysis-based products using high-density rain gauge observations as reference. First, we assess spatial patterns and frequency distributions using aggregated statistics. Then, we determine the skill of precipitation event detection from these products with a focus on extremes, using temporally and spatially matched pairs of precipitation estimates. The results show that the quality of the datasets largely depends on the region, season, and precipitation characteristic addressed. The satellite and the reanalysis precipitation products are found to have difficulties in accurately representing precipitation frequency with local overestimations of more than 40%, which occur mostly in dry regions (all products) as well as along coastlines and over cold/frozen surfaces (satellite-based products). The frequency distributions of wet-day intensities are generally well reproduced by all products. Concerning the frequency distributions of wet-spell durations, the satellite-based products are found to have clear deficiencies for maritime-influenced precipitation regimes. Moreover, the analysis of the detection of extreme precipitation events reveals that none of the non-station-based datasets shows skill at the shortest temporal and spatial scales (1 day, 0.25°), but at and above the 3-day and 1.25° scale the products start to exhibit skill over large parts of the domain. Added value compared to coarser-resolution global benchmark products is found both for reanalysis and satellite-based products.

scholarly journals Disentangling the Forcing Mechanisms of a Heavy Precipitation Event along the Alpine South Side Using Potential Vorticity Inversion

2010 ◽  
Vol 138 (6) ◽  
pp. 2336-2353 ◽  
Author(s):  
Linda Schlemmer ◽  
Olivia Martius ◽  
Michael Sprenger ◽  
Cornelia Schwierz ◽  
Arwen Twitchett
Keyword(s):  
Potential Vorticity ◽  
Heavy Precipitation ◽  
Static Stability ◽  
Precipitation Event ◽  
Limited Area ◽  
South Side ◽  
Vertical Stability ◽  
Extreme Precipitation Events ◽  
The Alps ◽  
The Stability

Abstract Extreme precipitation events along the Alpine south side (AS) are often forced by upper-level positive potential vorticity (PV) anomalies over western Europe. These so-called PV streamers go along with a dynamical forcing for upward motion, a reduction of the static stability in the troposphere (hence facilitating convection), and are associated with low-level winds that transport moisture toward the Alps. A case of heavy precipitation is examined using the 40-yr ECMWF Re-Analysis data. Piecewise PV inversion (PPVI) and the limited-area Climate High Resolution Model (CHRM) are used to assess the influences of mesoscale parts of the streamer on the precipitation event. The impacts on the vertical stability are quantified by the convective available potential energy (CAPE) and an index of static stability. Very sensitive areas in terms of the stability are located beneath the southern tip of the streamer; smaller changes in the stability are observed in the Alpine region. The moisture transport toward the Alps is sensitive to the amplitude of the streamer, which influences the amount of water that can be transported along its eastern flank. The impacts of the topography on the flow are assessed by calculating an average inverse Froude number. Whether or not the air parcels are blocked by or lifted over the barrier (going along with suppressed and enhanced precipitation, respectively) depends on the vertical stability and the impinging wind velocity, two parameters that are inherently linked to the PV streamer and its substructure.

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