New Estimates of 24-Hour Probable Maximum Precipitation (PMP) for the British Isles

Estimates of PMP are needed in order to estimate the spillway design flood for dams which must be capable of safely passing the probable maximum flood (PMF). For over forty years the standard estimates of the Flood Studies Report (FSR) have almost always been used. However, since then several studies have shown that these values are too low, and new estimates for South West England and then Britain were published. This paper extends these studies to include the whole of the British Isles. The study uses 6570 station years’ data in a new method of frequency analysis that identifies part of the data which represents the long term situation. Further analyses to support the results of this approach have been produced from the in situ maximisation of 12 historic storms using World Meteorological Organisation methods. The results are broadly consistent with those obtained from frequency analysis. Values of 24 hour PMP in Britain range from 600 mm in upland areas of the Lake District, to 400 mm in parts of East Anglia. This range of values is present in Wales and parts of South West England. For Ireland the highest values are over the upland areas, such as in the Wicklow Mountains (550 mm) and SW Ireland (600 mm), while in the lowlands values around 350 mm can be expected. The question of uncertainty in estimating PMP is considered, most of which is due to the temporal and spatial shortcomings of the data. The implications for the probable maximum flood (PMF) and spillway design flood mean that widespread reassessment of dam safety should be carried out at once.

Efficiency of Severe Recorded Rainstorms over Maharashtra State

12 severe rainstorms have been experienced by different meteorological sub-divisions of Maharashtra State during the last 100-year period from 1891-1990. For each of the rainstorms efficiency factors (i.e. P/ M ratios) were worked out for maximum one-day duration and for three standard areas of 1000, 5000, and 10,000 km2. Comparison of these ratios with the past has shown that the most efficient rainstorm over Maharashtra was the rainstorm of June, 1908 over the Vidarbha region whose full DAD data as well as isohyetal pattern have been given.

Predictability and skill of convection-permitting ensemble forecast systems in predicting the record-breaking“21·7”extreme rainfall event in Henan Province,China

During 19–21 July 2021,an extreme rainfall event occurred in Henan Province,China,during which a recordbreaking maximum hourly rainfall of 201.9 mm was recorded in Zhengzhou at 09 UTC July 20.In this study,the predictability of this extreme rainfall event is investigated using two convection-permitting ensemble forecast systems(CEFSs):one initialized from NCEP GEFS(named CEFS_GEFS)and the other initialized from time-lagged ERA5 data(named CEFS_ERA).Both are able to reproduce the daily heavy rainfall along the Taihang Mountains,but most members have significant position biases for the extreme rainfall in Zhengzhou.For the hourly rainfall,a few members are able to capture the evolution and propagation of extreme rainfall.However,all ensemble members underestimate the extreme hourly rainfall and have position errors of a few tens to a few hundreds of kilometers.Such results suggest that the predictability of the extreme hourly rainfall at the accuracy of city scale in Zhengzhou is low,especially by deterministic forecasting models,and the occurrence of the extreme requires many favorable conditions to happen simultaneously.In terms of the Brier score,CEFS_GEFS performs better than CEFS_ERA.The latter lacks spread,especially in regions with scarce rain,resulting in less dispersion in precipitation distributions and larger probability forecast error.When a neighborhood is applied,the probability of precipitation(POP)is significantly increased over Zhengzhou.While the traditional POP shows almost no skill for hourly rainfall≥25 mm h-1,the neighborhood POP significantly improves the forecast skill score,for both daily and hourly rainfall,suggesting higher predictability when spatial error among the ensemble members is allowed.