scholarly journals The Effect of Soil Moisture Perturbations on Indian Monsoon Depressions in a Numerical Weather Prediction Model

2017 ◽  
Vol 30 (21) ◽  
pp. 8811-8823 ◽  
Author(s):  
Kieran M. R. Hunt ◽  
Andrew G. Turner

Indian monsoon depressions (MDs) are synoptic-scale cyclonic systems that propagate across peninsular India three or four times per monsoon season. They are responsible for the majority of rainfall in agrarian north India, so constraining precipitation estimates is of high importance. Here, a case study from August 2014 is used to explore the relationship between varying soil moisture and the resulting track and structure of an incident MD using the Met Office Unified Model. This case study is chosen with the view to increasing understanding of the general impact of soil moisture perturbations on monsoon depressions. It is found that increasing soil moisture in the monsoon trough region results in deeper inland penetration and a more developed structure—for example, a warmer core in the midtroposphere and a stronger bimodal potential vorticity core in the mid-to-lower troposphere—with more precipitation, and a structure that in general more closely resembles that found in depressions over the ocean, indicating that soil moisture may enhance the convective mechanism that drives depressions over land. This experiment also shows that these changes are most significant when the depression is deep and negligible when it is weakening. Increasing soil moisture in the sub-Himalayan arable zone, a region with large irrigation coverage, also caused deeper inland penetration and some feature enhancement in the upper troposphere, but no significant changes were found in the track heading or lower-tropospheric structure.

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 873
Author(s):  
Yakob Umer ◽  
Janneke Ettema ◽  
Victor Jetten ◽  
Gert-Jan Steeneveld ◽  
Reinder Ronda

Simulating high-intensity rainfall events that trigger local floods using a Numerical Weather Prediction model is challenging as rain-bearing systems are highly complex and localized. In this study, we analyze the performance of the Weather Research and Forecasting (WRF) model’s capability in simulating a high-intensity rainfall event using a variety of parameterization combinations over the Kampala catchment, Uganda. The study uses the high-intensity rainfall event that caused the local flood hazard on 25 June 2012 as a case study. The model capability to simulate the high-intensity rainfall event is performed for 24 simulations with a different combination of eight microphysics (MP), four cumulus (CP), and three planetary boundary layer (PBL) schemes. The model results are evaluated in terms of the total 24-h rainfall amount and its temporal and spatial distributions over the Kampala catchment using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) analysis. Rainfall observations from two gauging stations and the CHIRPS satellite product served as benchmark. Based on the TOPSIS analysis, we find that the most successful combination consists of complex microphysics such as the Morrison 2-moment scheme combined with Grell-Freitas (GF) and ACM2 PBL with a good TOPSIS score. However, the WRF performance to simulate a high-intensity rainfall event that has triggered the local flood in parts of the catchment seems weak (i.e., 0.5, where the ideal score is 1). Although there is high spatial variability of the event with the high-intensity rainfall event triggering the localized floods simulated only in a few pockets of the catchment, it is remarkable to see that WRF is capable of producing this kind of event in the neighborhood of Kampala. This study confirms that the capability of the WRF model in producing high-intensity tropical rain events depends on the proper choice of parametrization combinations.


2012 ◽  
Vol 12 (2) ◽  
pp. 403-413 ◽  
Author(s):  
S. Tajbakhsh ◽  
P. Ghafarian ◽  
F. Sahraian

Abstract. In this paper, one meteorological case study for two Iranian airports are presented. Attempts have been made to study the predefined threshold amounts of some instability indices such as vertical velocity and relative humidity. Two important output variables from a numerical weather prediction model have been used to survey thunderstorms. The climatological state of thunder days in Iran has been determined to aid in choosing the airports for the case studies. The synoptic pattern, atmospheric thermodynamics and output from a numerical weather prediction model have been studied to evaluate the occurrence of storms and to verify the threshold instability indices that are based on Gordon and Albert (2000) and Miller (1972). Using data from the Statistics and Data Center of the Iran Meteorological Organization, 195 synoptic stations were used to study the climatological pattern of thunderstorm days in Iran during a 15-yr period (1991–2005). Synoptic weather maps and thermodynamic diagrams have been drawn using data from synoptic stations and radiosonde data. A 15-km resolution version of the WRF numerical model has been implemented for the Middle East region with the assistance of global data from University Corporation for Atmospheric Research (UCAR). The Tabriz airport weather station has been selected for further study due to its high frequency of thunderstorms (more than 35 thunderstorm days per year) and the existence of an upper air station. Despite the fact that storms occur less often at the Tehran weather station, the station has been chosen as the second case study site due to its large amount of air traffic. Using these two case studies (Tehran at 00:00 UTC, 31 April 2009 and Tabriz at 12:00 UTC, 31 April 2009), the results of this research show that the threshold amounts of 30 °C for KI, −2 °C for LI and −3 °C for SI suggests the occurrence and non-occurrence of thunderstorms at the Tehran and Tabriz stations, respectively. The WRF model output of vertical velocity and relative humidity are the two most important indices for examining storm occurrence, and they have a numerical threshold of 1 m s−1 and 80%, respectively. These results are comparable to other studies that have examined thunderstorm occurrence.


2007 ◽  
Vol 20 (1) ◽  
pp. 3-20 ◽  
Author(s):  
V. Krishnamurthy ◽  
J. Shukla

Abstract The space–time structure of the active and break periods of the Indian monsoon has been studied using 70-yr-long high-resolution gridded daily rainfall data over India. The analysis of lagged composites of rainfall anomalies based on an objective categorization of active and break phases shows that the active (break) cycle, with an average life of 16 days, starts with positive (negative) rainfall anomalies over the Western Ghats and eastern part of central India and intensifies and expands to a region covering central India and parts of north India during the peak phase, while negative (positive) anomalies cover the sub-Himalayan region and southeast India. During the final stage of the active (break) period, the positive (negative) rainfall anomalies move toward the foothills of the Himalayas while peninsular India is covered with opposite sign anomalies. The number of days on which lows and depressions are present in the region during active and break periods is consistent with the rainfall analysis. The number of depressions during the active phase is about 7 times that during the break phase. Using multichannel singular spectrum analysis of the daily rainfall anomalies, the seasonal monsoon rainfall is found to consist of two dominant intraseasonal oscillations with periods of 45 and 20 days and three seasonally persisting components. The 45- and 20-day oscillations are manifestations of the active and break periods but contribute very little to the seasonal mean rainfall. The seasonally persisting components with anomalies of the same sign, and covering all of India, have a very high interannual correlation with the total seasonal mean rainfall. These results support a conceptual model of the interannual variability of the monsoon rainfall consisting of seasonal mean components and a statistical average of the intraseasonal variations. The success in the prediction of seasonal mean rainfall depends on the relative strengths of the seasonally persisting components and intraseasonal oscillations.


2020 ◽  
Author(s):  
Andreas Dörnbrack ◽  
Tyler Mixa ◽  
Bernd Kaifler ◽  
Markus Rapp

<p>At the end of the austral winter 2019, a sudden stratospheric warming led to an early breakdown of the polar vortex. The meteorological conditions during this event are documented and analysed by means of operational analyses of the Intgrated Forecast System (IFS) of the ECMWF and ERA5 data. Especially, we focus on the decline of stratospheric wave activity over the southern tip of South America. For this region, ground-based and airborne measurements are employed to compare selected diagnostics with fields from the ECMWF's numerical weather prediction model IFS. Furthmore, the meteorological conditions for one selected research flight during the SOUTHTRAC campaign are presented. This part serves as background information for a case study presented by Tyler Mixa.</p>


2009 ◽  
Vol 137 (12) ◽  
pp. 4276-4292 ◽  
Author(s):  
Thomas Pangaud ◽  
Nadia Fourrie ◽  
Vincent Guidard ◽  
Mohamed Dahoui ◽  
Florence Rabier

Abstract An approach to make use of Atmospheric Infrared Sounder (AIRS) cloud-affected infrared radiances has been developed at Météo-France in the context of the global numerical weather prediction model. The method is based on (i) the detection and the characterization of clouds by the CO2-slicing algorithm and (ii) the identification of clear–cloudy channels using the ECMWF cloud-detection scheme. Once a hypothetical cloud-affected pixel is detected by the CO2-slicing scheme, the cloud-top pressure and the effective cloud fraction are provided to the radiative transfer model simultaneously with other atmospheric variables to simulate cloud-affected radiances. Furthermore, the ECMWF scheme flags each channel of the pixel as clear or cloudy. In the current configuration of the assimilation scheme, channels affected by clouds whose cloud-top pressure ranges between 600 and 950 hPa are assimilated over sea in addition to clear channels. Results of assimilation experiments are presented. On average, 3.5% of additional pixels are assimilated over the globe but additional assimilated channels are much more numerous for mid- to high latitudes (10% of additional assimilated channels on average). Encouraging results are found in the quality of the analyses: background departures of AIRS observations are reduced, especially for surface channels, which are globally 4 times smaller, and the analysis better fits some conventional and satellite data. Global forecasts are slightly improved for the geopotential field. These improvements are significant up to the 72-h forecast range. Predictability improvements have been obtained for a case study: a low pressure system that affected the southeastern part of Italy in September 2006. The trajectory, intensity, and the whole development of the cyclogenesis are better predicted, whatever the forecast range, for this case study.


2012 ◽  
Vol 51 (10) ◽  
pp. 1811-1822 ◽  
Author(s):  
Kristopher M. Bedka ◽  
Richard Dworak ◽  
Jason Brunner ◽  
Wayne Feltz

AbstractTwo satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-μm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD > 0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.


2009 ◽  
Vol 9 (4) ◽  
pp. 16755-16810 ◽  
Author(s):  
K.-G. Karlsson ◽  
A. Dybbroe

Abstract. The performance of the three cloud products cloud fractional cover, cloud type and cloud top height, derived from NOAA AVHRR data and produced by the EUMETSAT Climate Monitoring Satellite Application Facility, has been evaluated in detail over the Arctic region for four months in 2007 using CALIPSO-CALIOP observations. The evaluation was based on 142 selected NOAA/Metop overpasses allowing almost 400 000 individual matchups between AVHRR pixels and CALIOP measurements distributed approximately equally over the studied months (June, July, August and December 2007). Results suggest that estimations of cloud amounts are very accurate during the polar summer season while a substantial loss of detected clouds occurs in the polar winter. Evaluation results for cloud type and cloud top products point at specific problems related to the existence of near isothermal conditions in the lower troposphere in the polar summer and the use of reference vertical temperature profiles from Numerical Weather Prediction model analyses. The latter are currently not detailed enough in describing true conditions relevant on the pixel scale. This concerns especially the description of near-surface temperature inversions which are often too weak leading to large errors in interpreted cloud top heights.


Sign in / Sign up

Export Citation Format

Share Document