Blended probabilistic nowcasting with the IMPROVER post-processing system

Presentación realizada en la 3rd European Nowcasting Conference, celebrada en la sede central de AEMET en Madrid del 24 al 26 de abril de 2019

The potential use of the linear depolarization ratio to distinguish between convective and stratiform rainfall to improve radar rain-rate estimates

A major source of errors in radar-derived quantitative precipitation estimates is the inhomogeneous nature of the vertical reflectivity profile (VPR). Operational radars generally scan in azimuth at constant elevation (PPI mode) and provide limited VPR information, so predetermined VPR shapes with limited degrees of freedom are needed to correct for the VPR in real time. Typical stratiform VPRs have a sharp peak below the 0° isotherm, known as the “bright band,” caused by the presence of large melting snowflakes, but this feature is not present in convective cores where the melting ice is in the form of graupel or compact ice. Inappropriate correction assuming a brightband VPR can lead to underestimation of rain rates, with particular impacts in intense convective storms. This paper proposes the use of high values of linear depolarization ratio (LDR) measurements to confirm the presence of large melting snowflakes and lower values for melting graupel or high-density ice as a prerequisite to selecting a suitable profile shape for VPR correction. Using a climatologically representative dataset of short-range, high-resolution C-band vertical profiles, the peak value of the LDR in the melting layer is shown to have robust skill in identifying VPRs without bright band, with the “best” performance at a threshold of −20 dB. Further work is proposed to apply this result to improving corrections for VPR at longer range, where the limited effect of beam broadening on LDR peaks could provide advantages over other available methods

Improving local corrections for the radar vertical reflectivity profile using the linear depolarisation ratio

A major source of errors in radar-derived quantitative precipitation estimates (QPEs) is the vertical reflectivity profile (VPR). A feature of particular importance is the radar “bright band”: a reflectivity enhancement due to the melting of large snowflakes that occurs in the majority of high latitude rainfall, and which if misrepresented can cause order of magnitude errors in surface QPEs. Recent upgrades of several national weather radar networks to dual polarisation provide opportunities to refine the identification of bright band in operational radar measurements, and to improve subsequent determination and corrections for VPR. This thesis applies information from the linear depolarisation ratio (LDR) to improve classification of VPRs at the pixel scale. Using a unique dataset of high resolution vertical profiles, values of LDR in the melting layer are shown to provide a seven-fold increase in probability of detection of non-bright band reflectivity profiles over the current UK operational criterion. In the context of the Met Office local VPR correction scheme, an LDR-based classification step alone is shown to produce improvements in bias and RMSE of more than 1 mm h−1 for high rain rates in non-bright band conditions. The high resolution vertical profile dataset is then further used to improve the parameterisation of VPR shapes for correction at the local scale. Using a simulation method adapted from previous literature, three possible non-bright band VPR shapes are defined and their performance objectively compared to a control (no correction) profile. The most skilful profile is applied to a high intensity non-bright band case study in combination with LDR-based VPR classification, yielding further improvements to QPE bias and RMSE. Improvements to the stratiform profile are also investigated. The conclusions of this thesis indirectly support the use of local over global VPR corrections to maximise the accuracy of radar QPEs at the sub-kilometre scale

Clinical utility of PKD2 mutation testing in a polycystic kidney disease cohort attending a specialist nephrology out-patient clinic.

BACKGROUND: ADPKD affects approximately 1:1000 of the worldwide population. It is caused by mutations in two genes, PKD1 and PKD2. Although allelic variation has some influence on disease severity, genic effects are strong, with PKD2 mutations predicting later onset of ESRF by up to 20 years. We therefore screened a cohort of ADPKD patients attending a nephrology out-patient clinic for PKD2 mutations, to identify factors that can be used to offer targeted gene testing and to provide patients with improved prognostic information. METHODS: 142 consecutive individuals presenting to a hospital nephrology out-patient service with a diagnosis of ADPKD and CKD stage 4 or less were screened for mutations in PKD2, following clinical evaluation and provision of a detailed family history (FH). RESULTS: PKD2 mutations were identified in one fifth of cases. 12% of non-PKD2 patients progressed to ESRF during this study whilst none with a PKD2 mutation did (median 38.5 months of follow-up, range 16-88 months, p < 0.03). A significant difference was found in age at ESRF of affected family members (non-PKD2 vs. PKD2, 54 yrs vs. 65 yrs; p < 0.0001). No PKD2 mutations were identified in patients with a FH of ESRF occurring before age 50 yrs, whereas a PKD2 mutation was predicted by a positive FH without ESRF. CONCLUSIONS: PKD2 testing has a clinically significant detection rate in the pre-ESRF population. It did not accurately distinguish those individuals with milder renal disease defined by stage of CKD but did identify a group less likely to progress to ESRF. When used with detailed FH, it offers useful prognostic information for individuals and their families. It can therefore be offered to all but those whose relatives have developed ESRF before age 50

Prevalence and architecture of de novo mutations in developmental disorders.

The genomes of individuals with severe, undiagnosed developmental disorders are enriched in damaging de novo mutations (DNMs) in developmentally important genes. Here we have sequenced the exomes of 4,293 families containing individuals with developmental disorders, and meta-analysed these data with data from another 3,287 individuals with similar disorders. We show that the most important factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and the parental ages. We identified 94 genes enriched in damaging DNMs, including 14 that previously lacked compelling evidence of involvement in developmental disorders. We have also characterized the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences; approximately half of these DNMs disrupt gene function and the remainder result in altered protein function. We estimate that developmental disorders caused by DNMs have an average prevalence of 1 in 213 to 1 in 448 births, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year

International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways.

Primary biliary cirrhosis (PBC) is a classical autoimmune liver disease for which effective immunomodulatory therapy is lacking. Here we perform meta-analyses of discovery data sets from genome-wide association studies of European subjects (n=2,764 cases and 10,475 controls) followed by validation genotyping in an independent cohort (n=3,716 cases and 4,261 controls). We discover and validate six previously unknown risk loci for PBC (Pcombined<5 × 10(-8)) and used pathway analysis to identify JAK-STAT/IL12/IL27 signalling and cytokine-cytokine pathways, for which relevant therapies exist

Molecular mechanisms underlying variations in lung function: a systems genetics analysis

Lung function measures reflect the physiological state of the lung, and are essential to the diagnosis of chronic obstructive pulmonary disease (COPD). The SpiroMeta-CHARGE consortium undertook the largest genome-wide association study (GWAS) so far (n=48 201) for forced expiratory volume in 1 s (FEV1) and the ratio of FEV1 to forced vital capacity (FEV1/FVC) in the general population. The lung expression quantitative trait loci (eQTLs) study mapped the genetic architecture of gene expression in lung tissue from 1111 individuals. We used a systems genetics approach to identify single nucleotide polymorphisms (SNPs) associated with lung function that act as eQTLs and change the level of expression of their target genes in lung tissue; termed eSNPs

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands