Sensitivity of land surface parameterization on Regional Spectral Model forecasts

Experiments were carried out to study the impact of different land surface schemes on a Regional Spectral Model (RSM) forecasts. RSM is based on the perturbation method of NCEP, where the dependent variables are the differences between the regional and global model fields called 'perturbations'. The perturbation method ensures the use of global model values as the base fields all over the domain and predicts the mesoscale features embedded in the base field forecasts. The first version of RSM has a land surface scheme with a single layer of soil moisture, which is the same as the operational global model with which it is nested. The second version of RSM has a land surface scheme with two layers of soil moisture and a more complex treatment of evaporation. The model was integrated for five days nested with the operational global spectral model during August 2001. The RSM with 2-layer soil moisture scheme was found to have slightly less easterly bias over north India. However, the two-layer scheme showed higher evaporation and precipitation over Andhra Pradesh region. Additionally, major differences were also observed in all the components of the surface energy balance over the same region

Cumulus convection and lateral boundary conditions in a limited area model

Three versions of Kuo's cumulus parameterization have been tested in a limited area model to investigate their comparative performances. Results show that the version of Anthes produces better forecasts than those produced by other versions. To identify a suitable scheme of lateral boundary conditions for the limited area model, impact of two time-invariant and two time-dependent boundary conditions have been examined. The forecasts suggest that the time-dependent tendency modification scheme, based on large-scale tendencies obtained from observed data, is a better boundary scheme for the model. Furthermore, the forecast produced with the revised version of the model incorporating improved versions of Kuo's scheme and lateral boundary conditions shows an overall improvement

Heavy rainfall episode over Mumbai on 26 July 2005: Assessment of NWP guidance

In the present work a qualitative assessment of guidance from NCMRWF operational global and regional Numerical Weather Prediction (NWP) systems in the episode of unprecedented rainfall over Mumbai has been attempted. This also consolidates and examines the predictions that were provided by some of the leading global operational centres. Some hindcast runs were also made with different initial conditions. It reveals that the use of very high resolution global and regional models with advanced data assimilation techniques (4D Var), that optimally utilizes information from satellite observations, could significantly enhance the usefulness of NWP guidance

Skills of different mesoscale models over Indian region during monsoon season: Forecast errors

Performance of four mesoscale models namely, the MM5, ETA, RSM and WRF, run at NCMRWF for short range weather forecasting has been examined during monsoon-2006. Evaluation is carried out based upon comparisons between observations and day-1 and day-3 forecasts of wind, temperature, speci.c humidity, geopotential height, rainfall, systematic errors, root mean square errors and specific events like the monsoon depressions. It is very difficult to address the question of which model performs best over the Indian region? An honest answer is 'none'. Perhaps an ensemble approach would be the best. However, if we must make a final verdict, it can be stated that in general, (i) the WRF is able to produce best All India rainfall prediction compared to observations in the day-1 forecast and, the MM5 is able to produce best All India rainfall forecasts in day-3, but ETA and RSM are able to depict the best distribution of rainfall maxima along the west coast of India, (ii) the MM5 is able to produce least RMSE of wind and geopotential fields at most of the time, and (iii) the RSM is able to produce least errors in the day-1 forecasts of the tracks, while the ETA model produces least errors in the day-3 forecasts

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Indian Ocean surface winds from NCMRWF analysis as compared to QuikSCAT and moored buoy winds

The quality of the surface wind analysis at the National Centre for Medium Range Weather Forecasts (NCMRWF), New Delhi over the tropical Indian Ocean and its improvement, in 2001 are examined by comparing it with in situ buoy measurements and satellite derived surface winds from NASA QuikSCAT satellite (QSCT) during 1999, 2000 and 2001. The NCMRWF surface winds suffered from easterly bias of 1.0-1.5 ms(-1) in the equatorial Indian Ocean (IO) and northerly bias of 2.0-3.0 ms(-1) in the south equatorial IO during 1999 and 2000 compared to QSCT winds. The amplitude of daily variability was also underestimated compared to that in QSCT. In particular, the amplitude of daily variability of NCMRWF winds in the eastern equatorial IO was only about 60% of that of QSCT during 1999 and 2000. The NCMRWF surface winds during 2001 have significantly improved with the bias of the mean analyzed winds considerably reduced everywhere bringing it to within 0.5 ms(-1) of QSCT winds in the equatorial IO. The amplitude and phase of daily and intraseasonal variability are very close to that in QSCT almost everywhere during 2001. It is shown that the weakness in the surface wind analysis during 1999 and 2000 and its improvement in 2001 are related to the weakness in simulation of precipitation by the forecast model in the equatorial IO and its improvement in 2001

A limited area model for monsoon prediction

A six level regional primitive equation model has been formulated and tested for monsoon prediction. The model uses dynamic normal mode initialization scheme for obtaining initial balance. The physical processes included are: the large scale condensation, the Kuo type of cumulus convection, the surface friction, the sensible heat supply and evaporation over the sea. The actual smooth orography is included. The model has been integrated for 48 hrs using input of 7 July and 8 August 1979 when the domain of integration was dominated by an intense monsoon depression. In order to investigate the model simulation of formative stage of the depression, the model was also integrated using input of 4 July 1979