Evaluation of NASA’s NEX-GDDP-simulated summer monsoon rainfall over homogeneous monsoon regions of India

Kumar, Praveen; Kumar, Sunny; Barat, Archisman; Sarthi, P. Parth; Sinha, Asha

doi:10.1007/s00704-020-03188-2

Cited by 14 publications

(7 citation statements)

References 54 publications

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“…The method first extracts time series of daily precipitation from each of the 21 GCM ensemble members within the NASA Earth Exchange Global Daily Downscaled Projections (NEX‐GDDP, https://cds.nccs.nasa.gov/nex-gddp/). NEX‐GDDP comprises projections for RCP 4.5 and RCP 8.5 for the period from 1950 through to 2100 and is reported to have good skill in representing precipitation extremes (Chen et al., 2017; Kumar et al., 2020; Zhao et al., 2020). The spatial resolution of the dataset is 0.25° (∼25 km × 25 km) and the downscaling approach used is based on bias‐correction spatial disaggregation (Thrasher et al., 2012; Wood et al., 2004).…”

Section: Methodsmentioning

confidence: 99%

“…gov/nex-gddp/). NEX-GDDP comprises projections for RCP 4.5 and RCP 8.5 for the period from 1950 through to 2100 and is reported to have good skill in representing precipitation extremes (Chen et al, 2017;Kumar et al, 2020;Zhao et al, 2020). The spatial resolution of the dataset is 0.25° (∼25 km × 25 km) and the downscaling approach used is based on bias-correction spatial disaggregation (Thrasher et al, 2012;Wood et al, 2004).…”

Section: Pluvial Boundary Conditionsmentioning

confidence: 99%

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Combined Modeling of US Fluvial, Pluvial, and Coastal Flood Hazard Under Current and Future Climates

Bates

Quinn

Sampson

et al. 2021

Water Resources Research

200

165

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This study reports a new and significantly enhanced analysis of US flood hazard at 30 m spatial resolution. Specific improvements include updated hydrography data, new methods to determine channel depth, more rigorous flood frequency analysis, output downscaling to property tract level, and inclusion of the impact of local interventions in the flooding system. For the first time, we consider pluvial, fluvial, and coastal flood hazards within the same framework and provide projections for both current (rather than historic average) conditions and for future time periods centered on 2035 and 2050 under the RCP4.5 emissions pathway. Validation against high-quality local models and the entire catalog of FEMA 1% annual probability flood maps yielded Critical Success Index values in the range 0.69-0.82. Significant improvements over a previous pluvial/fluvial model version are shown for high-frequency events and coastal zones, along with minor improvements in areas where model performance was already good. The result is the first comprehensive and consistent national-scale analysis of flood hazard for the conterminous US for both current and future conditions. Even though we consider a stabilization emissions scenario and a near-future time horizon, we project clear patterns of changing flood hazard (3σ changes in 100 years inundated area of −3.8 to +16% at 1° scale), that are significant when considered as a proportion of the land area where human use is possible or in terms of the currently protected land area where the standard of flood defense protection may become compromised by this time. Plain Language Summary We develop a method to estimate past, present, and future flood risk for all properties in the conterminous United States whether affected by river, coastal or rainfall flooding. The analysis accounts for variability within environmental factors including changes in sea level rise, hurricane intensity and landfall locations, precipitation patterns, and river discharge. We show that even for a conservative climate change trajectory we can expect locally significant changes in the land area at risk from floods by 2050, and by this time defenses protecting 2,200 km 2 of land may be compromised. The complete dataset has been made available via a website (https://floodfactor.com/) created by the First Street Foundation in order to increase public awareness of the threat posed by flooding to safety and livelihoods. BATES ET AL.

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Section: Methodsmentioning

confidence: 99%

Section: Pluvial Boundary Conditionsmentioning

confidence: 99%

Combined Modeling of US Fluvial, Pluvial, and Coastal Flood Hazard Under Current and Future Climates

Bates

Quinn

Sampson

et al. 2021

Water Resources Research

200

165

View full text Add to dashboard Cite

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“…The NEX-GDDP data for all 21 GCMs (see in Appendix A the list of the GCMs) for the historical experiment and both future projections were used in the previous study [47]. Working with the complete set of 21 GCMs is a analogous to [41,45,61] and rather different approach than the one applied in [60], where only five models are used. The set of the considered EHEs-indicators is computed from the output tx for each model individually and from the tx extracted from E-OBS, which is used as a reference.…”

Section: Methodsmentioning

confidence: 99%

“…The primary goal of the NEX-GDDP developers and distributors is to assist the science community in conducting studies of climate change impacts at local to regional scales. Subsequently, it is used for many applications around the globe as an assessment of the Indian summer monsoon [41,59,60] and as general investigations on near-and long-term climate projections over China [61] and Southeast Asia [35]. The overall conclusion is that the NEX-GDDP product offers considerable improvements over CMIP5 GCM hindcasts and projections at regional-to-local scales, with an unchanged global long-term increment [61].…”

Section: Datamentioning

confidence: 99%

Extreme Heat Events over Southeast Europe Based on NEX-GDDP Ensemble: Present Climate Evaluation and Future Projections

Chervenkov

Malcheva

2023

Atmosphere

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Southeast Europe is considered one of the most vulnerable regions in the context of climate change, and projected future summer warming is expected to exceed global rates significantly. Despite the importance of this problem, there have been few studies that utilized Coupled Model Intercomparison Project Phase 5 (CMIP5) Global Circulation Models (GCMs) and the multi-model ensemble approach to examine extreme heat events on a regional scale. Additionally, the NEX-GDDP dataset, successfully applied in other parts of the world to assess extreme heat, has not yet been utilized for Southeast Europe. This study aims to fill that gap, presenting the time evolution and spatial distribution of extreme heat events in Southeast Europe for the historical period 1950–2005 and for the expected future climate up to the end of the 21st century based on the NEX-GDDP dataset. In order to leverage the strengths of the multi-model ensemble approach, a set of purpose-tailored indicators, such as the annual number of hot days, the maximum number of consecutive hot days, and hot spell duration at different thresholds, is computed by the daily maximum temperature data from all datasets, produced by NEX-GDDP (21 for the historical period and 42 for the future period). The E-OBS dataset is used as a reference for evaluating the NEX-GDDP’s capability to simulate the features of the observed historical extreme heat events. The results show that the multi-model ensemble can satisfactorily capture the occurrence of extreme heat events in the historical period, and therefore it is reasonable to assume that the NEX-GDDP dataset has the potential to reproduce such extremes in the projected future. The study provides clear evidence that the persistence and spatial extent of extreme heat will increase significantly. Some indicators that were not relevant for the historical period due to the high-temperature threshold will become helpful in assessing extreme heat in Southeast Europe in the latter part of the century. Thus, under the RCP8.5 scenario, the area-averaged duration of hot spells at 32 °C and 34 °C will increase from near zero in 1976–2005 to 60 and 45 days, respectively, by the end of the century. The indicators used in the study may be helpful for decision-makers to implement climate change mitigation strategies and actions adequately. The findings are consistent with general tendencies in maximum temperatures considered in our previous works but also with the outcomes of recent studies dedicated to the future climate of the region.

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“…Lightning prediction is now a challenging area of research (Tiwari et al, 2014) examined the prediction skill of large-scale seasonal mean temperature variability in inter annual timescale over India using GCM products. The spatial characteristics and statistical scores are used to evaluate the performance of each model in simulating NASA's NEX-GDDP-simulated summer monsoon rainfall over homogeneous monsoon regions of India (Kumar et al, 2020) Using LIS satellite lightning data, Kandalgaonkar et al (2005) calculated that a 1-degree increase in temperature would increase lightning activity by 20-40%. As a result, several kinds of research have been conducted on South Asia to understand better the geographical and temporal variation of lightning and related variables using ground and satellite-based data.…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal variability of lightning climatology and its association with thunderstorm indices over India

Mondal

Panda

Das

et al. 2022

Theor Appl Climatol

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Lightning is an electrical discharge -a'spark' or 'flash' as charged regions in the atmosphere instantly balance themselves through this discharge. It is a beautiful and deadly naturally occurring phenomenon. In June 2020, more than a hundred people died in the state Bihar of India only in three days' span due to lightning events. In this work, Lightning Imaging Sensor (LIS) information from the Tropical Rainfall Measuring Mission (TRMM) satellite with a very high spatial resolution of 0.1 X 0.1 degree has been utilized to create the climatology of India for 16 years from 1998 to 2013. Diurnal, monthly, and seasonal variations in the occurrence of lightning flash rate density have also been analyzed. TRMM satellite low-resolution monthly time series (LRMTS) with 2.5-degree resolution datasets have been used for lightning trend analysis.The diurnal lightning event mainly occurs in the afternoon/evening (1400-1900 Hrs) time duration around 0.001 flashes/km 2 /hr. The highest lightning occurred in May (0.04 flashes/km 2 /day) and the least in December (0.005 flashes/km 2 /day). The distribution of lightning flash counts by season over India landmass is mainly in pre-monsoon (MAM) ranges from 0.248 -0.491 flashes/km 2 /day, and monsoon (JJA) ranges from 0.284 -0.451 flashes/km 2 /day and decreases afterward. Spatially, the distribution of lightning flashes mainly at North-Eastern region along with Bangladesh, Bihar, Jharkhand, Orissa, and Jammu& Kashmir region. The CAPE and K Index have positively correlated with the flash rate density seasonally but CAPE is more significantly correlated. This study also focused on finding of lightning hotspots region of India district wise and Rajouri district in Jammu and Kashmir got the highest lightning with 121 flashes/km 2 /yr.

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Evaluation of NASA’s NEX-GDDP-simulated summer monsoon rainfall over homogeneous monsoon regions of India

Cited by 14 publications

References 54 publications

Combined Modeling of US Fluvial, Pluvial, and Coastal Flood Hazard Under Current and Future Climates

Combined Modeling of US Fluvial, Pluvial, and Coastal Flood Hazard Under Current and Future Climates

Extreme Heat Events over Southeast Europe Based on NEX-GDDP Ensemble: Present Climate Evaluation and Future Projections

Spatio-temporal variability of lightning climatology and its association with thunderstorm indices over India

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