Contrasting interannual atmospheric CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; variabilities and their terrestrial mechanisms for two types of El Niños

Wang, Jun; Zeng, Ning; Wang, Meirong; Jiang, Fei; Chen, Jingming; Friedlingstein, Pierre; Jain, Atul K.; Jiang, Zhe; Ju, Weimin; Lienert, Sebastian; Nabel, Julia E. M. S.; Sitch, Stephen; Viovy, Nicolas; Wang, Hengmao; Wiltshire, Andrew J.

doi:10.5194/acp-18-10333-2018

Cited by 22 publications

(36 citation statements)

References 55 publications

(96 reference statements)

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“…Thus, the specifically-applied spatial averaging procedure to remap the finer RADOLAN grid data to the coarser GPM grid utilizes the first order conservative remapping scheme from Jones [64], comprised in the Climate Data Operators software (CDO), which applies the SCRIP algorithm (Spherical Coordinate Remapping and Interpolation Package) [65,66]. This technique is widely applied in other studies dealing with precipitation data [67][68][69]. The area-averaged precipitation quantityF k at the destination grid is calculated as follows:…”

Section: Preprocessing Of Datasetsmentioning

confidence: 99%

Comparison of the GPM IMERG Final Precipitation Product to RADOLAN Weather Radar Data over the Topographically and Climatically Diverse Germany

Ramsauer¹,

Weiß²,

Marzahn³

2018

Remote Sensing

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Precipitation measurements provide crucial information for hydrometeorological applications. In regions where typical precipitation measurement gauges are sparse, gridded products aim to provide alternative data sources. This study examines the performance of NASA’s Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement Mission (IMERG, GPM) satellite precipitation dataset in capturing the spatio-temporal variability of weather events compared to the German weather radar dataset RADOLAN RW. Besides quantity, also timing of rainfall is of very high importance when modeling or monitoring the hydrologic cycle. Therefore, detection metrics are evaluated along with standard statistical measures to test both datasets. Using indices like “probability of detection” allows a binary evaluation showing the basic categorical accordance of the radar and satellite data. Furthermore, a pixel-by-pixel comparison is performed to assess the ability to represent the spatial variability of rainfall and precipitation quantity. All calculations are additionally carried out for seasonal subsets of the data to assess potentially different behavior due to differences in precipitation schemes. The results indicate significant differences between the datasets. Overall, GPM IMERG overestimates the quantity of precipitation compared to RADOLAN, especially in the winter season. Moreover, shortcomings in detection performance arise in this season with significant erroneously-detected, yet also missed precipitation events compared to the weather radar data. Additionally, along secondary mountain ranges and the Alps, topographically-induced precipitation is not represented in GPM data, which generally shows a lack of spatial variability in rainfall and snowfall estimates due to lower resolution.

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Section: Preprocessing Of Datasetsmentioning

confidence: 99%

Comparison of the GPM IMERG Final Precipitation Product to RADOLAN Weather Radar Data over the Topographically and Climatically Diverse Germany

Ramsauer¹,

Weiß²,

Marzahn³

2018

Remote Sensing

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“…Yeh et al, 2009). Despite recent research finding that the expression of El Niño is important at interannual timescales (Wang et al, 2018;Chylek et al, 2018;Pan et al, 2018), it is not known how and where the recent trend towards more CP El Niño events would impact the terrestrial carbon cycle.…”

Section: Introductionmentioning

confidence: 98%

“…Scheiter and Higgins, 2009;Whitley et al, 2017). Recent studies have found that, depending on the expression of El Niño, different time lags, amplitudes and duration in the carbon cycle anomalies occur (Wang et al, 2018;Chylek et al, 2018). Wang et al (2018) and Chylek et al (2018) link the effects of different expressions of El Niño on the terrestrial carbon cycle to variability at interannual timescales, but the impact on longer timescales is not well understood.…”

Section: Introductionmentioning

confidence: 99%

“…(Lund-Potsdam-Jena General Ecosystem Simulator;Smith et al, 2001Smith et al, , 2014) is a DGVM extensively used for climate-carbon studies (Smith et al, 2014;Sitch et al, 2003). LPJ-GUESS is used as the land surface scheme in the global Earth system model EC-Earth3 (Weiss et al, 2014;Alessandri et al, 2017) and in the regional Earth system model RCA-GUESS (Wramneby et al, 2010;Zhang et al, 2014). LPJ-GUESS dynamically simulates the exchange of water, carbon and nitrogen through the soilplant-atmosphere continuum (Smith et al, 2014), resolving the vegetation's resource competition for light and space.…”

Section: Introductionmentioning

confidence: 99%

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Examining the sensitivity of the terrestrial carbon cycle to the expression of El Niño

et al. 2021

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Abstract. The El Niño‐-Southern Oscillation (ENSO) influences the global climate and the variability in the terrestrial carbon cycle on interannual timescales. Two different expressions of El Niño have recently been identified: (i) central Pacific (CP) and (ii) eastern Pacific (EP). Both types of El Niño are characterised by above-average sea surface temperature anomalies at the respective locations. Studies exploring the impact of these expressions of El Niño on the carbon cycle have identified changes in the amplitude of the concentration of interannual atmospheric carbon dioxide (CO2) variability following increased tropical near-surface air temperature and decreased precipitation. We employ the dynamic global vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator) within a synthetic experimental framework to examine the sensitivity and potential long-term impacts of these two expressions of El Niño on the terrestrial carbon cycle. We manipulated the occurrence of CP and EP events in two climate reanalysis datasets during the latter half of the 20th and early 21st century by replacing all EP with CP and separately all CP with EP El Niño events. We found that the different expressions of El Niño affect interannual variability in the terrestrial carbon cycle. However, the effect on longer timescales was small for both climate reanalysis datasets. We conclude that capturing any future trends in the relative frequency of CP and EP El Niño events may not be critical for robust simulations of the terrestrial carbon cycle.

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“…Patterns of precipitation are correspondingly different. Depending on the types of ENSO events, their impacts on terrestrial carbon cycle can be quite different or even contrast (Wang et al ., ; ). In response to a specific ENSO event, precipitation over the three tropical continents can have different anomalies (Malhi and Wright, ; Liu et al ., ).…”

Section: Introductionmentioning

confidence: 99%

Linkage between tropical terrestrial carbon cycle and precipitation: The two anomalous years of 1979 and 1996

Zhu

Zhang

Zeng

2019

Atmospheric Science Letters

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Tropical terrestrial ecosystems are the critical driver of the land carbon cycle and climate change. Previous studies have reported strong response in the tropical land carbon cycle to precipitation anomalies in post‐La Niña years. We show that among the post‐La Niña years, 1979 and 1996 stand out strikingly different from other years. 1979 has one of the largest atmospheric CO2 growth rate (CGR) while 1996 has one of the smallest CGR, despite that their annual tropical precipitation anomalies are small. We show that these 2 years correspond to opposite seasonal precipitation anomalies over tropical vegetated lands in the wet‐to‐dry transition seasons in which negative correlation between precipitation and CGR is the strongest. 1979 has large dry anomaly during the transition season, inhibiting land carbon uptake, while 1996 has large wet anomaly during the transition season, favoring more carbon uptake by the tropical ecosystem. Results here highlight the importance of seasonality of climate anomalies and their timing of occurrences with the rhythm of the carbon–climate coupling.

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Contrasting interannual atmospheric CO<sub>2</sub> variabilities and their terrestrial mechanisms for two types of El Niños

Cited by 22 publications

References 55 publications

Comparison of the GPM IMERG Final Precipitation Product to RADOLAN Weather Radar Data over the Topographically and Climatically Diverse Germany

Comparison of the GPM IMERG Final Precipitation Product to RADOLAN Weather Radar Data over the Topographically and Climatically Diverse Germany

Examining the sensitivity of the terrestrial carbon cycle to the expression of El Niño

Linkage between tropical terrestrial carbon cycle and precipitation: The two anomalous years of 1979 and 1996

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