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Based on the daily precipitation forecast data of European Centre for Medium Range Weather Forecasts and National Center for Environmental Forecasting from May to August in 2017, combining with observation data during the same time period, the frequency matching technique is used to correct the model bias of summer precipitation forecast in Jianghuai River basin, and improvement to the scheme is also discussed. The following four conclusions are drawn from this study. (1) The model has significant false alarm forecast of light rain and missed forecast for heavy rain and above. (2) By lowering the precipitation with low intensity and raising the precipitation with high intensity, the intensity and area forecast skills in different precipitation magnitudes are improved to some extent. The correction effect is more obvious at both ends of precipitation magnitude, the accuracy of light rain and torrential rain forecast is significantly improved after the bias correction. (3) The improvement effect of rainstorm area forecast depends on the precipitation type. Typical case analysis shows that: for the large area Meiyu front rainstorms with more accurate forecast of rain belt location, the rainstorm TS score is significantly improved after bias correction. For rainstorms in a small area at the periphery of the subtropical high and the Meiyu front rainstorm or typhoon rainstorm with inaccurate forecast of rain belt location, the improvement of rainstorm TS score is not obvious or even lower after the bias correction. (4) To solve the above problems, the improvement ideas of dynamic coefficient adjustment and model integration are put forward, i.e., for small area rainstorm with average rainfall of 5 mm or less, the coefficient should be appropriately increased, while for large area rainstorm with average rainfall of 15 mm or above, the coefficient should be lowered appropriately. Model integration can effectively improve the rainstorm TS score.

Jianghuai region was hit by a torrential rainfall event on 18th-19th July, 2020. Numerical prediction models from ECMWF(hereinafter as EC model), East China Regional Meteorological Center/CMA(hereinafter as Huadong model), National Meteorological Center/CMA (3km resolution, hereinafter as G3 model) all present obvious northerly-offset in heavy rainfall area forecasts, and with weaker rainfall amounts as well. After detailed verification and analysis on models' wind fields and precipitation forecasts, it is founded that the performance of a model's synoptic situation forecasts are closely related to the model's precipitation forecast in most of times, especially for middle and low level wind fields which are easily affected by the model's precipitation latent heating process and thus would present wrong revision instruction to duty forecasters. Comparatively speaking, a model's forecast on high-level wind field is likely not affected by the model's precipitation latent heating process, which could be a reference deserving more attention during synoptic analysis. Furthermore, for a torrential rainfall caused by propagation of meso-or smaller scale weather systems, regional numerical model with higher resolution would be a better reference for forecast decision during similar heavy rainfall events.

ABSTRACT: In preparation for the Fourth International Workshop on Tropical Cyclone Landfall Processes (IWTCLP-IV), a summary of recent research studies and the forecasting challenges of tropical cyclone (TC) rainfall has been prepared. The extreme rainfall accumulations in Hurricane Harvey (2017) near Houston, Texas and Typhoon Damrey (2017) in southern Vietnam are examples of the TC rainfall forecasting challenges. Some progress is being made in understanding the internal rainfall dynamics via case studies. Environmental effects such as vertical wind shear and terrain-induced rainfall have been studied, as well as the rainfall relationships with TC intensity and structure. Numerical model predictions of TC-related rainfall have been improved via data assimilation, microphysics representation, improved resolution, and ensemble quantitative precipitation forecast techniques. Some attempts have been made to improve the verification techniques as well. A basic forecast challenge for TC-related rainfall is monitoring the existing rainfall distribution via satellite or coastal radars, or from over-land rain gauges. Forecasters also need assistance in understanding how seemingly similar landfall locations relative to the TC experience different rainfall distributions. In addition, forecasters must cope with anomalous TC activity and landfall distributions in response to various environmental effects. Keywords: tropical cyclone, landfall, rainfall, nowcast, forecast verification

ABSTRACT: Timely and relatively accurate detection of the center position of a near-landfalling typhoon is essential for weather forecasts, warning, disaster preparedness and data assimilation. Due to the vortex like nature of the flow near the typhoon center, the Zero Radial Velocity Line (ZRVL) of a Doppler radar extends through the typhoon center and the radar site. This paper proposes a method to detect the typhoon center by intersecting the ZRVLs of a dual-Doppler radar system. Simulation with Rankine Vortex model shows the validity of this method. This paper also evaluated the method by locating the centers of Typhoon FUNG-WONG (No. 201416) which impacted the east coastal regions of China from the afternoon of 22 September to the morning of 23 September, 2014 BST (Beijing Standard Time). During this period, the centers of the coastal typhoon were precisely positioned by intersecting the ZRVLs of two Doppler radars. The positioning accuracy of this method is comparable to that from Automatic Weather Stations (AWS) wind data. This method is suitable for areas where AWS data are unavailable, supposing radars are apart 100 km with a maximum unambiguous distance of 148km, this technique can cover most regions effectively. Keywords: dual radar, zero radial velocity line, typhoon positioning, coastal typhoon

ABSTRACT: By considering distance error and direction error, Tropical Cyclone (TC) track forecasts with abnormal forecast error (AFE) at lead time of 48 h by ECMWF-IFS are selected out from 2010 to 2013. Factors closely related to AFE cases are investigated. There are 7 factors which are closely related to AFE cases. The most common one is Landfall or Passing through big island (LP) which appears 21 times among all 55 AFE cases. But LP often coexists with other factors to cause AFE cases. The second in the list is Coexistence with other TC or cloud cluster (CO) which affects more than one third of all AFE cases. Besides those 7 factors, fault of TC-tracker also results in some AFE cases. There are no simple indicators for forecasters to anticipate a possible AFE case in advance. It seems that forecasters still have to anticipate AFE cases by their experiences and with synthetic analysis on all available data. Some possible ways to improve AFE cases are discussed and proposed to forecasters. That includes relying on products from ensemble prediction system or guidance from other models, simple translation process and manual analysis of TC track by forecasters under some circumstances. Keywords: track forecast, abnormal forecast error, tropical cyclone, ECMWF-IFS