Impacts of Including Rain-Evaporative Cooling in the Initial Conditions on the Prediction of a Coastal Heavy Rainfall Event during TiMREX

Abstract A cycling run, which began 36 h before the model forecast, was employed to assimilate special Terrain-influenced Monsoon Rainfall Experiment (TiMREX) soundings, Global Telecommunications System (GTS) data, and Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) global positioning system (GPS) radio occultation (RO) refractivity profiles to improve the model initial conditions provided by the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) to study a coastal, heavy rainfall event over southwestern Taiwan during 15–16 June 2008. The 36-h cycling run with data assimilation (DA_ALL_DATA run) has a positive impact on the depiction of subsynoptic flow in the model initial conditions at 1200 UTC 15 June, including the warm moist tongue and southwesterly monsoon flow over the open ocean. Furthermore, the cold pool caused by the evaporative cooling of antecedent rains and orographic blocking over southwestern Taiwan are better resolved in the nested high-resolution domain in the DA_ALL_DATA run as compared to the initial conditions provided by the NCEP GFS. As a result, the heavy rainfall along the southwestern coast and afternoon localized heavy rainfall over northern Taiwan are better predicted in the DA_ALL_DATA run. Model sensitivity tests are also performed to diagnose the effects of terrain and rain-evaporative cooling on the intensity and depth of the cold pool and degree of orographic blocking on the southwesterly flow over southwestern Taiwan. It is apparent that including rain-evaporative cooling from antecedent rains and orographic effects in the model initial conditions are important to account for the predicted rainfall distribution of this coastal rainfall event.

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Investigation of a heavy rainfall event over southwestern Taiwan associated with a subsynoptic cyclone during the 2003 Mei-Yu season

Atmospheric Research ◽

10.1016/j.atmosres.2009.10.003 ◽

2010 ◽

Vol 95 (2-3) ◽

pp. 235-254 ◽

Cited By ~ 25

Author(s):

Ching-Sen Chen ◽

Yuh-Lang Lin ◽

Wen-Chun Peng ◽

Che-Ling Liu

Keyword(s):

Heavy Rainfall ◽

Rainfall Event ◽

Heavy Rainfall Event ◽

Southwestern Taiwan

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Impact of radar data assimilation for the simulation of a heavy rainfall case in central Italy using WRF–3DVAR

Atmospheric Measurement Techniques ◽

10.5194/amt-7-2919-2014 ◽

2014 ◽

Vol 7 (9) ◽

pp. 2919-2935 ◽

Cited By ~ 12

Author(s):

I. Maiello ◽

R. Ferretti ◽

S. Gentile ◽

M. Montopoli ◽

E. Picciotti ◽

...

Keyword(s):

Heavy Rainfall ◽

Mesoscale Model ◽

Initial Conditions ◽

Positive Impact ◽

Central Italy ◽

Wrf Model ◽

Forecast Accuracy ◽

Radar Data ◽

Heavy Rainfall Event ◽

Dwr Data

Abstract. The aim of this study is to investigate the role of the assimilation of Doppler weather radar (DWR) data in a mesoscale model for the forecast of a heavy rainfall event that occurred in Italy in the urban area of Rome from 19 to 22 May 2008. For this purpose, radar reflectivity and radial velocity acquired from Monte Midia Doppler radar are assimilated into the Weather Research Forecasting (WRF) model, version 3.4.1. The general goal is to improve the quantitative precipitation forecasts (QPF): with this aim, several experiments are performed using the three-dimensional variational (3DVAR) technique. Moreover, sensitivity tests to outer loops are performed to include non-linearity in the observation operators. In order to identify the best initial conditions (ICs), statistical indicators such as forecast accuracy, frequency bias, false alarm rate and equitable threat score for the accumulated precipitation are used. The results show that the assimilation of DWR data has a large impact on both the position of convective cells and on the rainfall forecast of the analyzed event. A positive impact is also found if they are ingested together with conventional observations. Sensitivity to the use of two or three outer loops is also found if DWR data are assimilated together with conventional data.

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Understanding the Dynamics of a Heavy Rainfall Event using Multivariate Ensemble Sensitivity Analysis

10.5194/egusphere-egu21-11954 ◽

2021 ◽

Author(s):

Babitha George ◽

Govindan Kutty

Keyword(s):

Sensitivity Analysis ◽

Covariance Matrix ◽

Heavy Rainfall ◽

Initial Conditions ◽

Wrf Model ◽

Control Area ◽

Rainfall Event ◽

Heavy Rainfall Event ◽

Ensemble Forecasts ◽

The Impact

<p>Ensemble forecasts have proven useful for investigating the dynamics in a wide variety of atmospheric systems and they might be useful for diagnosing the source of forecast uncertainty in multi-scale flows. Ensemble Sensitivity Analysis (ESA) uses ensemble forecasts to evaluate the impact of changes in initial conditions on subsequent forecasts. ESA leads to a simple univariate regression by approximating the analysis covariance matrix with the corresponding diagonal matrix. On the contrary, the multivariate ensemble sensitivity computes sensitivity based on a more general multivariate regression that retains the full covariance matrix. The purpose of this study is to examine the performance of multivariate ensemble sensitivity over univariate by applying it to a heavy rainfall event that happened over the Himalayan foothills in June 2013. The ensemble forecasts and analyses are generated using the Advanced Research version of the Weather Research and Forecasting (WRF) model DART based Ensemble Kalman Filter. Initial results are promising and the sensitivity shows similar patterns for both univariate and multivariate methods. The reflectivity forecast for both methods are characterized by lower temperatures and increased moisture in the control area at 850 hPa level. Compared to multivariate, univariate ensemble sensitivity overestimates the magnitude of sensitivity for temperature. But the sensitivity for the moisture is the same in both methods.</p>

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The role of orographic effects on occurrence of the heavy rainfall event over Central Vietnam in November 1999

Tạp chí Khoa học và Công nghệ Biển ◽

10.15625/1859-3097/17/4b/12989 ◽

2017 ◽

Vol 17 (4B) ◽

pp. 31-36

Author(s):

Dang Hong Nhu ◽

Nguyen Xuan Anh ◽

Nguyen Binh Phong ◽

Nguyen Dang Quang ◽

Hiep Van Nguyen

Keyword(s):

Heavy Rainfall ◽

Wrf Model ◽

Rainfall Event ◽

Heavy Rainfall Event ◽

Monsoon Circulation ◽

Northeast Monsoon ◽

Strong Wind ◽

Orographic Effects ◽

Central Vietnam

In this study, the WRF model is used to investigate the role of Central Vietnam terrain on occurrence of the heavy rainfall event in November 1999 over Central Vietnam. Two model experiments with and without terrain were performed to examine the orographic blocking effects during the event. In the terrain experiment, the results from a three-day simulation show that the model reasonably well captures northeast monsoon circulation, tropical cyclones and the occurrence of heavy rainfall in Central Vietnam. The topography causes a high pressure anomaly intensifying northeast monsoon. When the terrain is removed, the three-day accumulated rainfall decreases approximately 75% in comparison with that in the terrain experiment. The terrain blocking and lifting effects in strong wind and moisture laden conditions combined with convergence circulation over open ocean are the main factors for occurrence of the heavy rainfall event.

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