Land surface sensitivity of monsoon depressions formed over Bay of Bengal using improved high-resolution land state

Rajesh, P. V.; Pattnaik, Sandeep; Mohanty, U. C.; Rai, Deepika; Baisya, Himadri; Pandey, P. C.

doi:10.1016/j.dynatmoce.2017.10.007

Cited by 7 publications

(10 citation statements)

References 43 publications

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“…As compared to LDAS systems, LSM spinups can further resolve spatial heterogeneity down to 1 km or less, and in coupled systems such as LIS/NU-WRF, will ensure identical LSM settings in both the offline spinup and coupled simulations. To date, LSM spinups have been employed in numerous regional (WRF) modeling studies, but are typically only employed by those in the land (LIS and HRLDAS) communities (Santanello et al 2013a,b;Case et al 2011Case et al , 2008Kumar et al 2008;Rajesh et al 2017;Hirsch et al 2014), while atmospheric modelers have been much less inclined to invest in this approach.…”

Section: Review Of Soil Moisture Initialization Approachesmentioning

confidence: 99%

“…However, recent studies have demonstrated the critical role of the land surface, and in particular soil moisture, in terms of impacts on precipitation (Welty and Zeng 2018;Ford et al 2015;Taylor et al 2012;Koster et al 2004;Findell and Eltahir 2003), temperature and humidity (Kala et al 2015;Seneviratne et al 2013;Mueller and Seneviratne 2012), and landatmosphere coupling as a whole including the planetary boundary layer (PBL) (Johnson and Hitchens 2018;Dirmeyer and Halder 2016;Santanello et al 2007Santanello et al , 2005. In particular, the initial condition (IC) of soil moisture has been shown to influence predictability on near-term (Dirmeyer and Halder 2016;Santanello et al 2016Santanello et al , 2013a and seasonal (Rajesh et al 2017;Xiang et al 2018;Hirsch et al 2014;Koster et al 2010) scales. Thus, quantification of the sensitivity of coupled models to the soil moisture initialization approach is an often overlooked, but potentially high-impact, exercise that should be performed by model evaluation and development communities.…”

Section: Introductionmentioning

confidence: 99%

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Understanding the Impacts of Soil Moisture Initial Conditions on NWP in the Context of Land–Atmosphere Coupling

Santanello

Lawston

Kumar

et al. 2019

Journal of Hydrometeorology

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The role of soil moisture in NWP has gained more attention in recent years, as studies have demonstrated impacts of land surface states on ambient weather from diurnal to seasonal scales. However, soil moisture initialization approaches in coupled models remain quite diverse in terms of their complexity and observational roots, while assessment using bulk forecast statistics can be simplistic and misleading. In this study, a suite of soil moisture initialization approaches is used to generate short-term coupled forecasts over the U.S. Southern Great Plains using NASA’s Land Information System (LIS) and NASA Unified WRF (NU-WRF) modeling systems. This includes a wide range of currently used initialization approaches, including soil moisture derived from “off the shelf” products such as atmospheric models and land data assimilation systems, high-resolution land surface model spinups, and satellite-based soil moisture products from SMAP. Results indicate that the spread across initialization approaches can be quite large in terms of soil moisture conditions and spatial resolution, and that SMAP performs well in terms of heterogeneity and temporal dynamics when compared against high-resolution land surface model and in situ soil moisture estimates. Case studies are analyzed using the local land–atmosphere coupling (LoCo) framework that relies on integrated assessment of soil moisture, surface flux, boundary layer, and ambient weather, with results highlighting the critical role of inherent model background biases. In addition, simultaneous assessment of land versus atmospheric initial conditions in an integrated, process-level fashion can help address the question of whether improvements in traditional NWP verification statistics are achieved for the right reasons.

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Section: Review Of Soil Moisture Initialization Approachesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Understanding the Impacts of Soil Moisture Initial Conditions on NWP in the Context of Land–Atmosphere Coupling

Santanello

Lawston

Kumar

et al. 2019

Journal of Hydrometeorology

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“…Hunt and Turner (2017b) found similar improvements with resolution for a wider set of depression cases in an NWP model, at coarser scales ranging from 208 to 16 km, as did Johnson et al (2016) in a climate model at similar resolutions. Several recent studies have found that accurate land-surface initialisation and improved treatments of atmospheric boundary-layer processes also improve NWP forecasts of rainfall, for case-studies of monsoon depressions (Rajesh et al, 2017;Hunt and Turner, 2017a;Rai and Pattnaik, 2019).…”

Section: Introductionmentioning

confidence: 99%

The influence of air–sea coupling on forecasts of the 2016 Indian summer monsoon and its intraseasonal variability

Valdivieso

Peatman

Klingaman

2020

Quart J Royal Meteoro Soc

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Daily initialized coupled and uncoupled numerical weather prediction (NWP) forecasts from the global Met Office Unified Model (MetUM) are compared for the 2016 Indian summer monsoon. Three MetUM configurations are used: atmosphere only (ATM), coupled to a mixed-layer ocean model (KPP), and coupled to a dynamical ocean model (NEMO). The analysis focuses on the impact of air-sea coupling, particularly in the Bay of Bengal (BoB), on NWP for monsoon rainfall. Seasonal-mean biases in all three configurations are highly consistent and driven by errors in atmospheric processes. Rainfall is initially overestimated over India, but underestimated over the BoB, the latter associated with too much shortwave radiation and too little cloud cover in MetUM. The excess shortwave radiation (>40 W⋅m −2 over the northwest BoB) is partially compensated by additional latent cooling, primarily due to overestimated surface wind speeds. In NEMO and KPP, coupling improves the timing of intraseasonal active and break phases over India, primarily the end of these phases, which are systematically too late in ATM. NEMO and KPP show a more realistic intraseasonal local phase relationship between sea surface temperature (SST) and rainfall throughout the BoB, but no configuration reproduces the observed significant lagged relationship between BoB SST and Indian rainfall. The lack of this relationship may be partly attributed to weak heat flux feedbacks to northern BoB SST, with the forecast shortwave feedback having systematically the wrong sign (positive) compared to satellite radiation, and thus contributing to SST warming at all lead times. Based on these MetUM forecasts, there is a limited impact of coupling on NWP for monsoon rainfall, both for the mean rainfall and intraseasonal variability. Further research to improve NWP for monsoon rainfall should focus on reducing MetUM atmospheric systematical biases. K E Y W O R D S air-sea coupling, atmospheric convection, Bay of Bengal, Indian monsoon, intraseasonal variability, weather forecasting This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Monsoon depressions are synoptic-scale systems which form over the Bay of Bengal and move in a westward/north-westward direction and often make their entrance to central India through Odisha, thereby causing heavy rainfall there. It is found that moisture flux convergence is the main source of moisture for such systems, while local evaporation is of lesser importance (Rajesh et al, 2017;Hunt & Turner, 2017). Rajesh et al, (2017) have already demonstrated improvements in the prediction of rainfall and other convective parameters for monsoon depressions using high resolution land data assimilation techniques.…”

Section: Introductionmentioning

confidence: 99%

“…It is found that moisture flux convergence is the main source of moisture for such systems, while local evaporation is of lesser importance (Rajesh et al, 2017;Hunt & Turner, 2017). Rajesh et al, (2017) have already demonstrated improvements in the prediction of rainfall and other convective parameters for monsoon depressions using high resolution land data assimilation techniques.…”

Section: Introductionmentioning

confidence: 99%

Simulation of location-specific severe thunderstorm events using high resolution land data assimilation

Sisodiya

Pattnaik

Baisya

et al. 2019

Dynamics of Atmospheres and Oceans

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Land surface sensitivity of monsoon depressions formed over Bay of Bengal using improved high-resolution land state

Cited by 7 publications

References 43 publications

Understanding the Impacts of Soil Moisture Initial Conditions on NWP in the Context of Land–Atmosphere Coupling

Understanding the Impacts of Soil Moisture Initial Conditions on NWP in the Context of Land–Atmosphere Coupling

The influence of air–sea coupling on forecasts of the 2016 Indian summer monsoon and its intraseasonal variability

Simulation of location-specific severe thunderstorm events using high resolution land data assimilation

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