scholarly journals Precipitation Field from Rainfall Measurements and Rainfall Estimates from IPMet’s Radars Iuri Valério Graciano Borges

2019 ◽  
Vol 42 (4) ◽  
pp. 417-426
Author(s):  
I. V. G. BORGES ◽  
D. S. MOREIRA ◽  
J. R. ROZANTE
2019 ◽  
Vol 19 (4) ◽  
pp. 775-789 ◽  
Author(s):  
Elise Monsieurs ◽  
Olivier Dewitte ◽  
Alain Demoulin

Abstract. Rainfall threshold determination is a pressing issue in the landslide scientific community. While major improvements have been made towards more reproducible techniques for the identification of triggering conditions for landsliding, the now well-established rainfall intensity or event-duration thresholds for landsliding suffer from several limitations. Here, we propose a new approach of the frequentist method for threshold definition based on satellite-derived antecedent rainfall estimates directly coupled with landslide susceptibility data. Adopting a bootstrap statistical technique for the identification of threshold uncertainties at different exceedance probability levels, it results in thresholds expressed as AR = (α±Δα)⋅S(β±Δβ), where AR is antecedent rainfall (mm), S is landslide susceptibility, α and β are scaling parameters, and Δα and Δβ are their uncertainties. The main improvements of this approach consist in (1) using spatially continuous satellite rainfall data, (2) giving equal weight to rainfall characteristics and ground susceptibility factors in the definition of spatially varying rainfall thresholds, (3) proposing an exponential antecedent rainfall function that involves past daily rainfall in the exponent to account for the different lasting effect of large versus small rainfall, (4) quantitatively exploiting the lower parts of the cloud of data points, most meaningful for threshold estimation, and (5) merging the uncertainty on landslide date with the fit uncertainty in a single error estimation. We apply our approach in the western branch of the East African Rift based on landslides that occurred between 2001 and 2018, satellite rainfall estimates from the Tropical Rainfall Measurement Mission Multi-satellite Precipitation Analysis (TMPA 3B42 RT), and the continental-scale map of landslide susceptibility of Broeckx et al. (2018) and provide the first regional rainfall thresholds for landsliding in tropical Africa.


2021 ◽  
Author(s):  
Oluwatobi Aiyelokun ◽  
Quoc Bao Pham ◽  
Oluwafunbi Aiyelokun ◽  
Anurag Malik ◽  
S. Adarsh ◽  
...  

2008 ◽  
Vol 1 (2) ◽  
pp. 89-99 ◽  
Author(s):  
M.S. Shrestha ◽  
G.A. Artan ◽  
S.R. Bajracharya ◽  
R.R. Sharma
Keyword(s):  

2012 ◽  
Vol 15 (4) ◽  
pp. 1121-1136 ◽  
Author(s):  
N. K. Shrestha ◽  
T. Goormans ◽  
P. Willems

This paper investigates the accuracy of rainfall estimates from C- and X-band weather radars and their application for stream flow simulation. Different adjustment procedures are applied to raw radar estimates using gauge readings from a network of 12 raingauges. The stream flow is simulated for the 48.17 km2 Molenbeek/Parkbeek catchment located in the Flemish region of Belgium based on a lumped conceptual model. Results showed that raw radar estimates can be greatly improved using adjustment procedures. The gauge-radar residuals however, remain large even after adjustments. The adjusted X-band radar estimates are observed to be better estimates than corresponding C-band estimates. Their application for stream flow simulation showed that raingauges and radars can simulate spatially more uniform winter storms with almost the same accuracy, whereas differences are more evident on summer events.


2000 ◽  
Vol 239 (1-4) ◽  
pp. 19-32 ◽  
Author(s):  
R.P Ibbitt ◽  
R.D Henderson ◽  
J Copeland ◽  
D.S Wratt

2000 ◽  
Vol 1 (3) ◽  
pp. 222-240 ◽  
Author(s):  
Dong-Jun Seo ◽  
Jay Breidenbach ◽  
Richard Fulton ◽  
Dennis Miller ◽  
Timothy O’Bannon

2007 ◽  
Vol 46 (6) ◽  
pp. 742-756 ◽  
Author(s):  
Gyu Won Lee ◽  
Alan W. Seed ◽  
Isztar Zawadzki

Abstract The information on the time variability of drop size distributions (DSDs) as seen by a disdrometer is used to illustrate the structure of uncertainty in radar estimates of precipitation. Based on this, a method to generate the space–time variability of the distributions of the size of raindrops is developed. The model generates one moment of DSDs that is conditioned on another moment of DSDs; in particular, radar reflectivity Z is used to obtain rainfall rate R. Based on the fact that two moments of the DSDs are sufficient to capture most of the DSD variability, the model can be used to calculate DSDs and other moments of interest of the DSD. A deterministic component of the precipitation field is obtained from a fixed R–Z relationship. Two different components of DSD variability are added to the deterministic precipitation field. The first represents the systematic departures from the fixed R–Z relationship that are expected from different regimes of precipitation. This is generated using a simple broken-line model. The second represents the fluctuations around the R–Z relationship for a particular regime and uses a space–time multiplicative cascade model. The temporal structure of the stochastic fluctuations is investigated using disdrometer data. Assuming Taylor hypothesis, the spatial structure of the fluctuations is obtained and a stochastic model of the spatial distribution of the DSD variability is constructed. The consistency of the model is validated using concurrent radar and disdrometer data.


2007 ◽  
Vol 20 (17) ◽  
pp. 4402-4424 ◽  
Author(s):  
Carlos D. Hoyos ◽  
Peter J. Webster

Abstract The structure of the mean precipitation of the south Asian monsoon is spatially complex. Embedded in a broad precipitation maximum extending eastward from 70°E to the northwest tropical Pacific Ocean are strong local maxima to the west of the Western Ghats mountain range of India, in Cambodia extending into the eastern China Sea, and over the eastern tropical Indian Ocean and the Bay of Bengal (BoB), where the strongest large-scale global maximum in precipitation is located. In general, the maximum precipitation occurs over the oceans and not over the land regions. Distinct temporal variability also exists with time scales ranging from days to decades. Neither the spatial nor temporal variability of the monsoon can be explained simply as the response to the cross-equatorial pressure gradient force between the continental regions of Asia and the oceans of the Southern Hemisphere, as suggested in classical descriptions of the monsoon. Monthly (1979–2005) and daily (1997–present) rainfall estimates from the Global Precipitation Climatology Project (GPCP), 3-hourly (1998–present) rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI) estimates of sea surface temperature (SST), reanalysis products, and satellite-determined outgoing longwave radiation (OLR) data were used as the basis of a detailed diagnostic study to explore the physical basis of the spatial and temporal nature of monsoon precipitation. Propagation characteristics of the monsoon intraseasonal oscillations (MISOs) and biweekly signals from the South China Sea, coupled with local and regional effects of orography and land–atmosphere feedbacks are found to modulate and determine the locations of the mean precipitation patterns. Long-term variability is found to be associated with remote climate forcing from phenomena such as El Niño–Southern Oscillation (ENSO), but with an impact that changes interdecadally, producing incoherent responses of regional rainfall. A proportion of the interannual modulation of monsoon rainfall is found to be the direct result of the cumulative effect of rainfall variability on intraseasonal (25–80 day) time scales over the Indian Ocean. MISOs are shown to be the main modulator of weather events and encompass most synoptic activity. Composite analysis shows that the cyclonic system associated with the northward propagation of a MISO event from the equatorial Indian Ocean tends to drive moist air toward the Burma mountain range and, in so doing, enhances rainfall considerably in the northeast corner of the bay, explaining much of the observed summer maximum oriented parallel to the mountains. Similar interplay occurs to the west of the Ghats. While orography does not seem to play a defining role in MISO evolution in any part of the basin, it directly influences the cumulative MISO-associated rainfall, thus defining the observed mean seasonal pattern. This is an important conclusion since it suggests that in order for the climate models to reproduce the observed seasonal monsoon rainfall structure, MISO activity needs to be well simulated and sharp mountain ranges well represented.


Author(s):  
Pablo Zurita-Gotor ◽  
Isaac M. Held

AbstractThis work investigates the characteristics of westward-propagating Rossby modes in idealized global general circulation models. Using a nonlinear smoothing algorithm to estimate the background spectrum and an objective method to extract the spectral peaks, the 4 leading meridional modes can be identified for each of the first 3 zonal wavenumbers, with frequencies close to the predictions from the Hough modes obtained by linearizing about a state of rest. Variations in peak amplitude for different modes, both within a simulation and across simulations, may be understood under the assumption that the forcing of the modes scales with the background spectrum. Surface friction affects the amplitude and width of the peaks but both remain finite as friction goes to zero, which implies that some other mechanism, arguably nonlinear, must also contribute to the damping of the modes. Although spectral peaks are also observed for the precipitation field with idealized moist physics, there is no evidence of mode enhancement by the convective heating. Subject to the same friction, the amplitude of the peaks are very similar in the dry and moist models when both are normalized by the background spectra.


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