Dynamical model skill in forecasting extratropical precipitation is limited beyond the medium-range (around 15 d), but such models are often more skilful at predicting atmospheric variables. We ...explore the potential benefits of using weather pattern (WP) predictions as an intermediary step in forecasting UK precipitation and meteorological drought on sub-seasonal timescales. Mean sea-level pressure forecasts from the European Centre for Medium-Range Weather Forecasts ensemble prediction system (ECMWF-EPS) are post-processed into probabilistic WP predictions. Then we derive precipitation estimates and dichotomous drought event probabilities by sampling from the conditional distributions of precipitation given the WPs. We compare this model to the direct precipitation and drought forecasts from the ECMWF-EPS and to a baseline
Markov chain WP method. A perfect-prognosis model is also tested to illustrate the potential of WPs in forecasting. Using a range of skill
diagnostics, we find that the Markov model is the least skilful, while the
dynamical WP model and direct precipitation forecasts have similar accuracy
independent of lead time and season. However, drought forecasts are more
reliable for the dynamical WP model. Forecast skill scores are generally
modest (rarely above 0.4), although those for the perfect-prognosis model
highlight the potential predictability of precipitation and drought using WPs, with certain situations yielding skill scores of almost 0.8 and
drought event hit and false alarm rates of 70 % and 30 %, respectively.
Weather‐pattern, or weather‐type, classifications are a valuable tool in many applications as they characterize the broad‐scale atmospheric circulation over a given region. A new precipitation and ...meteorological drought climatology for the UK is presented here based on an objectively defined weather‐pattern classification recently developed by the Met Office. Six weather patterns are associated with drought over the entire UK, with several others linked to regional drought. This data set offers a new opportunity for classification‐based analyses in the UK.
ABSTRACT
Weather‐pattern, or weather‐type, classifications are a valuable tool in many applications as they characterize the broad‐scale atmospheric circulation over a given region. This study analyses the aspects of regional UK precipitation and meteorological drought climatology with respect to a new set of objectively defined weather patterns. These new patterns are currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. Weather pattern definitions and daily occurrences are mapped to Lamb weather types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Standardized precipitation index (SPI) and drought severity index (DSI) series are calculated for a range of aggregation periods and seasons. Monthly weather‐pattern frequency anomalies are calculated for SPI wet and dry periods and for the 5% most intense DSI‐based drought months. The new weather‐pattern definitions and daily occurrences largely agree with their respective LWTs, allowing comparison between the two classifications. There is also broad agreement between weather pattern and LWT changes in frequencies. The new data set is shown to be adequate for precipitation‐based analyses in the UK, although a smaller set of clustered weather patterns is not. Furthermore, intra‐pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in this context. Six of the new weather patterns are associated with drought over the entire UK, with several other patterns linked to regional drought. It is demonstrated that the new data set of weather patterns offers a new opportunity for classification‐based analyses in the UK.
Persistence in time series of daily weather pattern (WP) classifications can provide useful information such as on the memory of broad‐scale atmospheric circulation. Despite this, research of WP ...persistence has lagged behind that exploring their frequencies of occurrence. We develop two methods for identifying persistence in a 167‐year time series of WPs defined over the North Atlantic–European domain. The first is an empirical counting technique used to find periods of persistence among sets of WPs, with the definition of persistence more relaxed than just consecutive occurrences. We then condition this method on the driest WPs to see if persistence can be used to identify historical drought. The second method uses a Markov model to assess if WP transition probabilities change when conditioned on information up to 20 days prior, without the need for estimating the large number of parameters usually required for high‐order Markov chains. Results are compared with a benchmark ensemble of synthetic time series generated using first‐order transition probabilities. We show that there were multi‐month periods when small sets of WPs dominated, and some of these periods coincided with notable meteorological events, including droughts and storms, such as the mid‐1990s drought in northern England and the Burn's Day Storm over southern Scotland in 1990. Some WPs also behave as “attractors,” showing increased probability of reoccurrence despite other WPs occurring in‐between. However, we find no link between the persistence statistics of each WP and their flow characteristics, except for those featuring an easterly flow over the United Kingdom, which are among the most persistent. The benchmark simulation ensemble is unable to reproduce many of the key persistence statistics of the observations, confirming that the persistence is a physical phenomenon. Finally, we discuss the potential processes underpinning WP persistence, such as the effects of large‐scale circulation patterns and land‐surface feedbacks.
Persistence in time series of daily weather pattern classifications can provide useful information such as on the memory of broad‐scale atmospheric circulation. We develop two novel methods for identifying persistence in a 167‐year time series of weather patterns defined over the North Atlantic–European domain, showing that there were multi‐month periods when small sets of WPs dominated. Some of these periods coincided with notable meteorological events, such as the Burn's Day Storm over southern Scotland in 1990 (see image).
•The frequency of extreme daily precipitation occurrence displays a distinctive non-uniform seasonal pattern.•The seasonal distribution is simulated with Generalized Additive Models.•A strong ...dependence on atmospheric driving conditions is replicated.•Statistical simulations indicate a future shift toward more frequent autumnal extreme precipitation.
Floods pose multi-dimensional hazards to critical infrastructure and society and these hazards may increase under climate change. While flood conditions are dependent on catchment type and soil conditions, seasonal precipitation extremes also play an important role. The extreme precipitation events driving flood occurrence may arrive non-uniformly in time. In addition, their seasonal and inter-annual patterns may also cause sequences of several events and enhance likely flood responses.
Spatial and temporal patterns of extreme daily precipitation occurrence are characterized across the UK. Extreme and very heavy daily precipitation is not uniformly distributed throughout the year, but exhibits spatial differences, arising from the relative proximity to the North Atlantic Ocean or North Sea. Periods of weeks or months are identified during which extreme daily precipitation occurrences are most likely to occur, with some regions of the UK displaying multimodal seasonality.
A Generalized Additive Model is employed to simulate extreme daily precipitation occurrences over the UK from 1901 to 2010 and to allow robust statistical testing of temporal changes in the seasonal distribution. Simulations show that seasonality has the strongest correlation with intra-annual variations in extreme event occurrence, while Sea Surface Temperature (SST) and Mean Sea Level Pressure (MSLP) have the strongest correlation with inter-annual variations. The north and west of the UK are dominated by MSLP in the mid-North Atlantic and the south and east are dominated by local SST.
All regions now have a higher likelihood of autumnal extreme daily precipitation than earlier in the twentieth century. This equates to extreme daily precipitation occurring earlier in the autumn in the north and west, and later in the autumn in the south and east. The change in timing is accompanied by increases in the probability of extreme daily precipitation occurrences during the autumn, and in the number of days with a very high probability of an extreme event. These results indicate a higher probability of several extreme occurrences in succession and a potential increase in flooding.
Wrapt (Weather generator rainfall analysis processing tool) is a software tool created as part of a UK Water Industry Research project on the impact of climate change on sewer networks. It allows ...users to generate design storm change factors and select timeseries from output of the UKCP09 (UK climate projections 2009) weather generator without the need for manual processing or detailed knowledge of weather generators. Wrapt has been developed to assess changes in extremes of short-duration rainfall events – relevant to assessing the performance of sewer networks – but also has potential for applications elsewhere (e.g. water quality modelling).
The optimal use of bevacizumab in recurrent glioblastoma (GBM), including the choice of monotherapy or combination therapy, remains uncertain. The purpose of this study was to compare combination ...therapy with bevacizumab monotherapy.
This was a 2-part randomized phase 2 study. Eligibility criteria included recurrent GBM after radiotherapy and temozolomide, no other chemotherapy for GBM, and Eastern Cooperative Oncology Group performance status 0-2. The primary objective (Part 1) was to determine the effect of bevacizumab plus carboplatin versus bevacizumab monotherapy on progression-free survival (PFS) using modified Response Assessment in Neuro-Oncology criteria. Bevacizumab was given every 2 weeks, 10 mg/kg; and carboplatin every 4 weeks, (AUC 5). On progression, patients able to continue were randomized to continue or cease bevacizumab (Part 2). Secondary endpoints included objective radiological response rate (ORR), quality of life, toxicity, and overall survival (OS).
One hundred twenty-two patients (median age, 55y) were enrolled to Part 1 from 18 Australian sites. Median follow-up was 32 months, and median on-treatment time was 3.3 months. Median PFS was 3.5 months for each arm (hazard ratio HR: 0.92, 95% CI: 0.64-1.33, P = .66). ORR was 14% (combination) versus 6% (monotherapy) (P = .18). Median OS was 6.9 (combination) versus 7.5 months (monotherapy) (HR: 1.18, 95% CI: 0.82-1.69, P = .38). The incidence of bevacizumab-related adverse events was similar to prior literature, with no new toxicity signals. Toxicities were higher in the combination arm. Part 2 data (n = 48) will be reported separately.
Adding carboplatin resulted in more toxicity without additional clinical benefit. Clinical outcomes in patients with recurrent GBM treated with bevacizumab were inferior to those in previously reported studies.
ACTRN12610000915055.
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