Impacts of large-scale climatic disturbances on the terrestrial carbon cycle

Background

The amount of carbon dioxide in the atmosphere steadily increases as a consequence of anthropogenic emissions but with large interannual variability caused by the terrestrial biosphere. These variations in the CO₂ growth rate are caused by large-scale climate anomalies but the relative contributions of vegetation growth and soil decomposition is uncertain. We use a biogeochemical model of the terrestrial biosphere to differentiate the effects of temperature and precipitation on net primary production (NPP) and heterotrophic respiration (Rh) during the two largest anomalies in atmospheric CO₂ increase during the last 25 years. One of these, the smallest atmospheric year-to-year increase (largest land carbon uptake) in that period, was caused by global cooling in 1992/93 after the Pinatubo volcanic eruption. The other, the largest atmospheric increase on record (largest land carbon release), was caused by the strong El Niño event of 1997/98.

Results

We find that the LPJ model correctly simulates the magnitude of terrestrial modulation of atmospheric carbon anomalies for these two extreme disturbances. The response of soil respiration to changes in temperature and precipitation explains most of the modelled anomalous CO₂ flux.

Conclusion

Observed and modelled NEE anomalies are in good agreement, therefore we suggest that the temporal variability of heterotrophic respiration produced by our model is reasonably realistic. We therefore conclude that during the last 25 years the two largest disturbances of the global carbon cycle were strongly controlled by soil processes rather then the response of vegetation to these large-scale climatic events.     

Influence of road network and population demand assumptions in evacuation modeling for distant tsunamis

Tsunami evacuation planning in coastal communities is typically focused on local events where at-risk individuals must move on foot in a matter of minutes to safety. Less attention has been placed on distant tsunamis, where evacuations unfold over several hours, are often dominated by vehicle use and are managed by public safety officials. Traditional traffic simulation models focus on estimating clearance times but often overlook the influence of varying population demand, alternative modes, background traffic, shadow evacuation, and traffic management alternatives. These factors are especially important for island communities with limited egress options to safety. We use the coastal community of Balboa Island, California (USA), as a case study to explore the range of potential clearance times prior to wave arrival for a distant tsunami scenario. We use a first-in–first-out queuing simulation environment to estimate variations in clearance times, given varying assumptions of the evacuating population (demand) and the road network over which they evacuate (supply). Results suggest clearance times are less than wave arrival times for a distant tsunami, except when we assume maximum vehicle usage for residents, employees, and tourists for a weekend scenario. A two-lane bridge to the mainland was the primary traffic bottleneck, thereby minimizing the effect of departure times, shadow evacuations, background traffic, boat-based evacuations, and traffic light timing on overall community clearance time. Reducing vehicular demand generally reduced clearance time, whereas improvements to road capacity had mixed results. Finally, failure to recognize non-residential employee and tourist populations in the vehicle demand substantially underestimated clearance time.     

Causes of the Intraseasonal SST Variability in the Tropical Indian Ocean

Satellite observations reveal a much stronger intraseasonal sea surface temperature (SST) variability in the southern Indian Ocean along 5-10oS in boreal winter than in boreal summer. The cause of this seasonal dependence is studied using a 2?-layer ocean model forced by ERA-40 reanalysis products during 1987-2001. The simulated winter-summer asymmetry of the SST variability is consistent with the observed. A mixed-layer heat budget is analyzed. Mean surface westerlies along the ITCZ (5-10oS) in December-January-February (DJF) leads to an increased (decreased) evaporation in the westerly (easterly) phase of the intraseasonal oscillation (ISO), during which convection is also enhanced (suppressed). Thus the anomalous shortwave radiation, latent heat flux and entrainment effects are all in phase and produce strong SST signals. During June-July-August (JJA), mean easterlies prevail south of the equator. Anomalies of the shortwave radiation tend to be out of phase to those of the latent heat flux and ocean entrainment. This mutual cancellation leads to a weak SST response in boreal summer. The resultant SST tendency is further diminished by a deeper mixed layer in JJA compared to that in DJF. The strong intraseasonal SST response in boreal winter may exert a delayed feedback to the subsequent opposite phase of ISO, implying a two-way air-sea interaction scenario on the intraseasonal timescale. Citation: Li, T., F. Tam, X. Fu, et al., 2008: Causes of the intraseasonal SST variability in the tropical Indian ocean, Atmos. Oceanic Sci. Lett., 1, 18-23     

The intraseasonal oscillations of precipitation and circulations from January to March in 2010 in East Asia

The rainfall from January to March in 2010 in East Asia is positive anomaly and the temporal evolution characteristics present the cycle of 20–40 days. In the present paper, the low-frequency circulations and its formation mechanism are analyzed. The results show that during the peak rainfall phase, the upstream of the rainfall regions is controlled by low-frequency cyclone, and the downstream is controlled by low-frequency anticyclone in the middle and low troposphere. In the upper troposphere, the westerly jet presents the oscillation characteristics between the north and the south. Both the integrated (from the surface to 100 hPa) diabatic heating and the horizontal vorticity advection contribute to the vertical velocity. In addition, the vorticity vertical advection has effects on the vertical speed, which is a self-feedback process. The latent heating in the precipitation has influences on the westerly jet in the upper troposphere. The interactions between the precipitation and the westerly jet are mainly manifested as the intraseasonal oscillations.     

Evaluation of forecast strategies for seasonal and decadal forecasts in presence of systematic model errors

This study discusses and compares three different strategies used to deal with model error in seasonal and decadal forecasts. The strategies discussed are the so-called full initialisation, anomaly initialisation and flux correction. In the full initialisation the coupled model is initialised to a state close to the real-world attractor and after initialisation the model drifts towards its own attractor, giving rise to model bias. The anomaly initialisation aims to initialise the model close to its own attractor, by initialising only the anomalies. The flux correction strategy aims to keep the model trajectory close to the real-world attractor by adding empirical corrections. These three strategies have been implemented in the ECMWF coupled model, and are evaluated at seasonal and decadal time-scales. The practical implications of the different strategies are also discussed. Results show that full initialisation results in a clear model drift towards a colder climate. The anomaly initialisation is able to reduce the drift, by initialising around the model mean state. However, the erroneous model mean state results in degraded seasonal forecast skill. The best results on the seasonal time-scale are obtained using momentum-flux correction, mainly because it avoids the positive feedback responsible for a strong cold bias in the tropical Pacific. It is likely that these results are model dependent: the coupled model used here shows a strong cold bias in the Central Pacific, resulting from a positive coupled feedback between winds and SST. At decadal time-scales it is difficult to determine whether any of the strategies is superior to the others.     

耦合模式FGOALS_s 模拟的亚澳季风年际变率及ENSO

本文评估了中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室 (LASG/IAP) 新一代耦合气候模式FGOALS_s对亚澳季风和ENSO的模拟。结果表明, FGOALS_s可以模拟出亚澳季风的主要气候态特征。FGOALS_s模拟的ENSO事件振幅为观测值的70%, 同时它合理再现了ENSO周期的非规则性。FGOALS_s可以定性模拟出ENSO的主要空间特征。当赤道东太平洋SST升高时, 印度洋和西太平洋海表面气压升高, 而东太平洋海表面气压降低。FGOALS_s的主要缺陷在于模拟的ENSO峰值多出现在春季和夏季。与ENSO振幅偏小相反, FGOALS_s模拟的亚澳季风年际变率振幅大于观测。但是观测中亚澳季风年际变率与ENSO暖位相的显著负相关关系, 在模式中没有得到合理再现, 原因部分可归之于耦合模式在ENSO锁相模拟上的缺陷。由于模式模拟的ENSO峰值出现在北半球春季和夏季, Walker环流异常下沉支移动到西北太平洋, 其激发出的异常反气旋位置较之观测要偏东, 导致印度季风降水和El Niño的负相关关系不显著; 在北半球冬季, 由于模式中的赤道东太平洋SST暖异常较弱, 亚澳季风响应也偏弱。此外, 由于赤道东太平洋SST异常向西伸展, 观测中位于澳洲季风区的辐散中心向西偏移, 最终导致模式中澳洲季风降水与ENSO的负相关同样不显著。     

What controls early or late onset of tropical North Atlantic hurricane season?

The occurrence of first hurricane in early summer signifies the onset of an active Atlantic hurricane season. The interannual variation of this hurricane onset date is examined for the period 1979-2013. It is found that the onset date has a marked interannual variation. The standard deviation of the interannual variation of the onset day is 17.5 days, with the climatological mean onset happening on July 23.A diagnosis of tropical cyclone (TC) genesis potential index (GPI) indicates that the major difference between an early and a late onset group lies in the maximum potential intensity (MPI). A further diagnosis of the MPI shows that it is primarily controlled by the local SST anomaly (SSTA). Besides the SSTA, vertical shear and mid-tropospheric relative humidity anomalies also contribute significantly to the GPI difference between the early and late onset groups.It is found that the anomalous warm (cold) SST over the tropical Atlantic, while uncorrelated with the Niño3 index, persists from the preceding winter to concurrent summer in the early (late) onset group. The net surface heat flux anomaly always tends to damp the SSTA, which suggests that ocean dynamics may play a role in maintaining the SSTA in the tropical Atlantic. The SSTA pattern with a maximum center in northeastern tropical Atlantic appears responsible for generating the observed wind and moisture anomalies over the main TC development region. A further study is needed to understand the initiation mechanism of the SSTA in the Atlantic.     

Storm track sensitivity to sea surface temperature resolution in a regional atmosphere model

A high resolution regional atmosphere model is used to investigate the sensitivity of the North Atlantic storm track to the spatial and temporal resolution of the sea surface temperature (SST) data used as a lower boundary condition. The model is run over an unusually large domain covering all of the North Atlantic and Europe, and is shown to produce a very good simulation of the observed storm track structure. The model is forced at the lateral boundaries with 15–20 years of data from the ERA-40 reanalysis, and at the lower boundary by SST data of differing resolution. The impacts of increasing spatial and temporal resolution are assessed separately, and in both cases increasing the resolution leads to subtle, but significant changes in the storm track. In some, but not all cases these changes act to reduce the small storm track biases seen in the model when it is forced with low-resolution SSTs. In addition there are several clear mesoscale responses to increased spatial SST resolution, with surface heat fluxes and convective precipitation increasing by 10–20% along the Gulf Stream SST gradient.     

A new paradigm for the predominance of standing Central Pacific Warming after the late 1990s

Canonical El Niño has a warming center in the eastern Pacific (EP), but in recent decades, El Niño warming center tends to occur more frequently in the central Pacific (CP). The definitions and names of this new type of El Niño, however, have been notoriously diverse, which makes it difficult to understand why the warming center shifts. Here, we show that the new type of El Niño events is characterized by: 1) the maximum warming standing and persisting in the CP and 2) the warming extending to the EP only briefly during its peak phase. For this reason, we refer to it as standing CP warming (CPW). Global warming has been blamed for the westward shift of maximum warming as well as more frequent occurrence of CPW. However, we find that since the late 1990s the standing CPW becomes a dominant mode in the Pacific; meanwhile, the epochal mean trade winds have strengthened and the equatorial thermocline slope has increased, contrary to the global warming-induced weakening trades and flattening thermocline. We propose that the recent predominance of standing CPW arises from a dramatic decadal change characterized by a grand La Niña-like background pattern and strong divergence in the CP atmospheric boundary layer. After the late 1990s, the anomalous mean CP wind divergence tends to weaken the anomalous convection and shift it westward from the underlying SST warming due to the suppressed low-level convergence feedback. This leads to a westward shift of anomalous westerly response and thus a zonally in-phase SST tendency, preventing eastward propagation of the SST anomaly. We anticipate more CPW events will occur in the coming decade provided the grand La Niña-like background state persists.     

How Frequently Will the Persistent Heavy Rainfall over the Middle and Lower Yangtze River Basin in Summer 2020 Happen under Global Warming?

The middle and lower Yangtze River basin (MLYRB) suffered persistent heavy rainfall in summer 2020, with nearly continuous rainfall for about six consecutive weeks. How the likelihood of persistent heavy rainfall resembling that which occurred over the MLYRB in summer 2020 (hereafter 2020PHR-like event) would change under global warming is investigated. An index that reflects maximum accumulated precipitation during a consecutive five-week period in summer (Rx35day) is introduced. This accumulated precipitation index in summer 2020 is 60% stronger than the climatology, and a statistical analysis further shows that the 2020 event is a 1-in-70-year event. The model projection results derived from the 50-member ensemble of CanESM2 and the multimodel ensemble (MME) of the CMIP5 and CMIP6 models show that the occurrence probability of the 2020PHR-like event will dramatically increase under global warming. Based on the Kolmogorov–Smirnoff test, one-third of the CMIP5 and CMIP6 models that have reasonable performance in reproducing the 2020PHR-like event in their historical simulations are selected for the future projection study. The CMIP5 and CMIP6 MME results show that the occurrence probability of the 2020PHR-like event under the present-day climate will be double under lower-emission scenarios (CMIP5 RCP4.5, CMIP6 SSP1-2.6, and SSP2-4.5) and 3–5 times greater under higher-emission scenarios (3.0 times for CMIP5 RCP8.5, 2.9 times for CMIP6 SSP3-7.0, and 4.8 times for CMIP6 SSP5-8.5). The inter-model spread of the probability change is small, lending confidence to the projection results. The results provide a scientific reference for mitigation of and adaptation to future climate change.