Evaluation of the COSMO model (v5.1) in polarimetric radar space – impact of uncertainties in model microphysics, retrievals and forward operators

Sensitivity experiments with a numerical weather prediction (NWP) model and polarimetric radar forward operator (FO) are conducted for a long-duration stratiform event over northwestern Germany to evaluate uncertainties in the partitioning of the ice water content and assumptions of hydrometeor scattering properties in the NWP model and FO, respectively. Polarimetric observations from X-band radar and retrievals of hydrometeor classifications are used for comparison with the multiple experiments in radar and model space. Modifying the critical diameter of particles for ice-to-snow conversion by aggregation (Dice) and the threshold temperature responsible for graupel production by riming (Tgr), was found to improve the synthetic polarimetric moments and simulated hydrometeor population, while keeping the difference in surface precipitation statistically insignificant at model resolvable grid scales. However, the model still exhibited a low bias (lower magnitude than observation) in simulated polarimetric moments at lower levels above the melting layer (−3 to −13 ∘C) where snow was found to dominate. This necessitates further research into the missing microphysical processes in these lower levels (e.g. fragmentation due to ice–ice collisions) and use of more reliable snow-scattering models to draw valid conclusions.

Track, intensity and few dynamical aspects of ‘AILA’ as simulated by operational NWP model of the IAF

bl 'kks/k i= esa Hkkjrh; ok;q lsuk ds izpkyukRed ,u- MCY;w- ih- ekWMy dh {kerk dk ebZ 2009 esa caxky dh [kkM+h esa cus vkSj if’pe caxky dks izHkkfor djus okys izpaM pØokrh; rwQku ^vk;yk^ ds dqN xR;kRed igyqvksa] mlds ekxZ] rhozrk ,oa LFky izos’k ds iwokZuqeku dk fo’ys"k.k djus dk iz;kl fd;k x;k gSA bl ekWMy dks 6 fd- eh- ds NksVs Hkkx esa diklh izkpyhdj.k ;kstuk ds lkFk vkSj mlds fcuk bl ;kstuk dk iz;ksx djds ns[kk x;k gSA ckjh ckjh ls fd, x, nksuksa iz;ksxksa ds lsV esa Mh&2 ij rS;kj fd, x, iwokZuqeku dh rqyuk esa Mh&1 ds iwokZuqeku vis{kk—r csgrj vkSj vkf/kd lgh ik, x,A diklh izkpyhdj.k ds iSVUlZ foyac ls laogu iSnk djrs gSa ijUrq bl iSVUlZ ds fcuk rS;kj fd, ifj.kke dh rqyuk esa vf/kd lgh gSA 6 fd-eh- ds NksVs Hkkx esa diklh izkpyhdj.k ;kstuk ds fcuk jsMkj dh ijkofrZrk Mh- MCY;w- vkj- dksydkrk ds okLrfod ijkofrZrk le; vkSj LFkku nksuksa dh rqyuk esa vf/kdre ns[kh xbZ gSA An attempt has been made in this study to analyse the efficacy of operational NWP Model of the IAF in predicting the track, intensity, landfall and few dynamical aspects of ‘AILA’ a Severe Cyclonic Storm that formed over the Bay of Bengal and affected West Bengal during May 2009. Model runs were done with and without employment of cumulus parameterisation scheme in the finer domain of 6 km. The forecasts of D-1 were relatively better and more realistic in comparison to the one generated on D-2, in both sets of experiment, respectively. Patterns with cumulus parameterisation produced delayed convection but with finer details in comparison to the patterns generated without it. Maximum radar reflectivity without using cumulus parameterisation scheme in the finer domain of 6 km, compared well with the actual reflectivity of Kolkata DWR both in time and space.

Stratospheric gravity waves excited by a propagating Rossby wave train – A DEEPWAVE Case Study

Stratospheric gravity waves observed during the DEEPWAVE research flight RF25 over the Southern Ocean are analyzed and compared with numerical weather prediction (NWP) model results. The quantitative agreement of the NWP model output and the tropospheric and lower stratospheric observations is remarkable. The high-resolution NWP models are even able to reproduce qualitatively the observed upper stratospheric gravity waves detected by an airborne Rayleigh lidar. The usage of high-resolution ERA5 data – partially capturing the long internal gravity waves – enabled a thorough interpretation of the particular event. Here, the observed and modeled gravity waves are excited by the stratospheric flow past a deep tropopause depression belonging to an eastward propagating Rossby wave train. In the reference frame of the propagating Rossby wave, vertically propagating hydrostatic gravity waves appear stationary; in reality, of course, they are transient and propagate horizontally at the phase speed of the Rossby wave. The subsequent refraction of these transient gravity waves into the polar night jet explains their observed and modeled patchy stratospheric occurrence near 60°S. The combination of both unique airborne observations and high-resolution NWP output provides evidence for the one case investigated in this paper. As the excitation of such gravity waves persists during the quasi-linear propagation phase of the Rossby wave’s life cycle, a hypothesis is formulated that parts of the stratospheric gravity wave belt over the Southern Ocean might be generated by such Rossbywaves trains propagating along the mid-latitude wave guide.

Performance of IMD multi-model ensemble and WRF (ARW) model for sub-basin wise rainfall forecast during monsoon 2012

The Numerical Weather Prediction models, Multi-model Ensemble (MME) (27 km × 27 km) and WRF (ARW) (9 km × 9 km) operationally run by India Meteorological Department (IMD) have been utilized to estimate sub-basin wise rainfall forecast. The sub-basin wise operational Quantitative Precipitation Forecast (QPF) have been issued by 10 field offices named Flood Meteorological Offices (FMOs) of IMD located at different flood prone areas of the country. The daily sub-basin wise NWP model rainfall forecast for 122 sub basins under these 10 FMOs for the flood season 2012 have been estimated on operational basis which are used by forecasters at FMOs as a guidance for the issue of operational sub-basin QPF for flood forecasting purposes. The performance of the MME and WRF (ARW) models rainfall at the sub-basin level have been studied in detail. The performance of WRF (ARW) and MME models is compared in the heavy rainfall case over the river basins (Mahanadi etc.) falls under FMO, Bhubaneswar and it is found that WRF (ARW) model gives better result than MME. It is also found that performance of WRF (ARW) is little better than MME when compared over all the flood prone river sub basins of India. For high rainfall categories (51-100, >100 mm), generally these leads to floods, the success rate of model rainfall forecasts are less and false alarms are more. The NWP models are able to capture the rainfall events but there is difference in magnitudes of sub basin wise rainfall estimates.

An algorithm for detecting the Chesapeake Bay breeze from mesoscale NWP model output

A novel algorithm is developed for detecting and classifying the Chesapeake Bay breeze and similar water-body breezes in output from mesoscale numerical weather prediction models. To assess the generality of the new model-based detection algorithm (MBDA), it is tested on simulations from the Weather Research and Forecasting (WRF) model and on analyses and forecasts from the High Resolution Rapid Refresh (HRRR) model. The MBDA outperforms three observation-based detection algorithms (OBDAs) when applied to the same model output. Additionally, by defining the onshore wind directions based on model land-use data, not on the actual geography of the region of interest, performance of the OBDAs with model output can be improved. Although simulations by the WRF model were used to develop the new MBDA, it performed best when applied to HRRR analyses. The generality of the MBDA is promising, and additional tuning of its parameters might improve it further.

Utilisation of ‘Aerostat’ Doppler Weather Radar in nowcasting of convective phenomena

‘Aerostat’ system is a part of the air defence radar network, adopted by the Indian Air Force. Many meteorological instruments have been integrated with this system, including Doppler Weather Radar (DWR). The ground-based DWR has a maximum range of 300 NM, however, it generally uses 150 NM range on scan mode. The scan mode images are provided at half an hour interval, which are being utilised very effectively for nowcasting of thunderstorms at various IAF bases. In the present study, utilisation of DWR images for nowcasting of thunderstorms / dust storms is discussed over NW India with the help of a few case studies during pre-monsoon and SW monsoon seasons of 2008. Further, products generated through operational meso-scale NWP model runs have been studied in order to obtain indications / guidance for expected convective activity over the area at least 24-36 hours in advance. Thus, short-range weather forecasts through NWP models can be used as an advance indication for careful monitoring of DWR images in near real time. It has been found that the DWR is a very good tool to track the movement of significant weather echoes around the airfields, which can be very helpful in issuing appropriate warnings / advisories with sufficient lead time. Meso-scale NWP models are capable of generating reliable indications for expected convective activity at least 24-36 hours in advance. The integration of both the inputs can increase the accuracy and reliability of location and time specific prediction of convective activity.

Intercalibration of Backscatter Measurements among Ku-Band Scatterometers Onboard the Chinese HY-2 Satellite Constellation

The Chinese HY-2D satellite was launched on 19 May 2021, carrying a Ku-band scatterometer. Together with the operating scatterometers onboard the HY-2B and HY-2C satellites, the HY-2 series scatterometer constellation was built, constituting different satellite orbits and hence opportunity for mutual intercomparison and intercalibration. To achieve intercalibration of backscatter measurements for these scatterometers, this study presents and performs three methods including: (1) direct comparison using collocated measurements, in which the nonlinear calibrations can also be derived; (2) intercalibration over the Amazon rainforest; (3) and the double-difference technique based on backscatter simulations over the global oceans, in which a geophysical model function and numerical weather prediction (NWP) model winds are needed. The results obtained using the three methods are comparable, i.e., the differences among them are within 0.1 dB. The intercalibration results are validated by comparing the HY-2 series scatterometer wind speeds with NWP model wind speeds. The curves of wind speed bias for the HY-2 series scatterometers are quite similar, particularly in wind speeds ranging from 4 to 20 m/s. Based on the well-intercalibrated backscatter measurements, consistent sea surface wind products from HY-2 series scatterometers can be produced, and greatly benefit data applications.