Context of the added value in coupled atmosphere-land RegCM4–CLM4.5 in the simulation of Indian summer monsoon

Abstract

The potential of the RegCM4-CLM4.5 model for value addition over the MIROC5 GCM for Indian Summer Monsson (ISM) simulation for the present climate has been examined. The added value has been investigated in terms of the added value index (AV) and the Modified Brier Skill Score (MBSS). In general, a strong dry (wet) bias > 5 mm/day in the RegCM4 (MIROC5) dataset was prevalent over different parts of India. Additional precipitation statistics such as the area-averaged mean, standard deviation, correlation coefficient, and percentage bias over the homogeneous region of precipitation suggest that the RegCM4 occasionally improves over the MIROC5, depending upon the region and the metric under consideration. Further, a comparable tropospheric temperature gradient and the vertical wind shear have been found for both the dataset. However, this does not hold for the large-scale moisture transport as the RegCM4 shows an advantage in representing the magnitude and the location of the low-level jet. The dominant unrealistic moisture transport and associated stronger Bay of Bengal branch of circulation causes heavy precipitation (> 12 mm/day), thus leading to improved precipitation statistics for MIROC5. A quantifiable added value over the GCM in terms of the positive indices have been found in the RegCM4. The AV (MBSS) suggests positive values i.e. 0.6-0.8 (0.2-0.5) over major parts of India, signifying added information and/or the improvement upon the downscaling. The experiment certainly provides additional information in the precipitation simulation over the major part of India however the two indices do not necessarily agree over certain areas.

Impact of horizontal resolution on monsoon precipitation for CORDEX-South Asia: A regional earth system model assessment

“…However, the ROM 0.11 shows an increase of dry bias over the central part of the NEI, probably due to the limitation of using the hydrostatic version at a higher resolution over the region with a complex interaction between the convective system and large-scale dynamics (Maurya et al, 2018). The magnitude of bias reported in this study is considerably less than that of the bias reported in earlier studies using RCM (Lucas-Picher et al, 2011;Kumar et al, 2014a, 2014b, 2014c, Bhatla et al, 2020Kumar and Dimri, 2020) and coupled regional atmosphere-ocean model/RESM (Misra et al, 2017(Misra et al, , 2018Di Sante et al, 2019;Mishra et al, 2021).…”

Dynamic downscaling of climate simulations and projected changes in tropical South America using RegCM4.7

“…In this context, the added value (AV) is defined as a measure of the extent to which the reduced‐scale climate representation is closest to observation than the model that served as a lateral forcing (Di Luca et al, 2012, 2016; Falco et al, 2020; Lucas‐Picher et al, 2017). Although some works point to AV of the RCM, particularly in the representation of precipitation in terrain with complex topography (e.g., Feser et al, 2011; Fotso‐Nguemo et al, 2017; Kumar & Dimri, 2021; Rummukainen, 2016), other studies find deterioration (e.g., Coppola et al, 2014; Mishra et al, 2014; Singh et al, 2017). These results depend on many factors, that is, the regional model adopted, the study area, the hydrological regime, the configuration adopted in the experiment, the analysed variable, the temporal and spatial scale, the method used to analyse the experiment and the set of data used as LBC (Giorgi & Gutowski, 2015).…”

Hindcasts of Sea Surface Wind around the Korean Peninsula Using the WRF Model: Added Value Evaluation and Estimation of Extreme Wind Speeds

“…DASCAT is advantageous due to its consistent temporal coverage with ERA-Interim over the study period. Since modified BSS was introduced to evaluate the added value of sea surface wind hindcast [20], many studies used modified BSS to evaluate added value quantitatively [13,21,22,57,58].…”