The Coordinated Influence of Indian Ocean Sea Surface Temperature and Arctic Sea Ice on Anomalous Northeast China Cold Vortex Activities with Different Paths during Late Summer

The Northeast China cold vortex(NCCV)during late summer(from July to August)is identified and classified into three types in terms of its movement path using machine learning.The relationships of the three types of NCCV intensity with atmospheric circulations in late summer,the sea surface temperature(SST),and Arctic sea ice concentration(SIC)in the preceding months,are analyzed.The sensitivity tests by the Community Atmosphere Model version 5.3(CAM5.3)are used to verify the statistical results.The results show that the coordination pattern of East Asia-Pacific(EAP)and Lake Baikal high pressure forced by SST anomalies in the North Indian Ocean dipole mode(NIOD)during the preceding April and SIC anomalies in the Nansen Basin during the preceding June results in an intensity anomaly for the first type of NCCV.While the pattern of high pressure over the Urals and Okhotsk Sea and low pressure over Lake Baikal during late summer-which is forced by SST anomalies in the South Indian Ocean dipole mode(SIOD)in the preceding June and SIC anomalies in the Barents Sea in the preceding April-causes the intensity anomaly of the second type.The third type is atypical and is not analyzed in detail.Sensitivity tests,jointly forced by the SST and SIC in the preceding period,can well reproduce the observations.In contrast,the results forced separately by the SST and SIC are poor,indicating that the NCCV during late summer is likely influenced by the coordinated effects of both SST and SIC in the preceding months.

Multiple ocean surface temperature changes induced multi-decadal global warming rate

Subject Code:D05Under support of the National Natural Science Foundation of China,a concerted study by Dr.Huang Gang(黄刚)from the Institute of Atmospheric Physics,Chinese Academy of Sciences,climate scientist Jing-Jia Luo from the Australian Bureau of Meteorology,Dr.Yao Shuailei(姚帅磊)from the Institute

The effect of sea surface temperature increase on the potential habitat of Ommastrephes bartramii in the Northwest Pacific Ocean

In the Northwest Pacific Ocean, the squid jigging fisheries from China, Japan and other countries and regions have targeted the west winter-spring cohort of neon flying squid（Ommastrephes bartramii） from August to November since the 1970 s. This squid is a short-lived ecological opportunist with a life-span of about one year,and its population is labile and recruitment variability is driven by the environment or climate change. This variability provides a challenge for ones to forecast the key habitats affected by climate change. The catch data of O. bartramii from Chinese squid jigging fishery and the satellite-derived sea surface temperature（SST） data are used in the Northwest Pacific Ocean from August to November of 1998 to 2004, the SST preferences of O.bartramii corresponding to high values of catch per fishing day（CPUE） are determined and monthly potential habitats are predicted using a histogram analysis of the SST data. The possible changes in the potential habitats of O. bartramii in the Northwest Pacific Ocean are estimated under four climate change scenarios based on the Fourth Assessment Report（AR4） of the Intergovernmental Panel on Climate Change, i.e., 0.5, 1, 2 and 4°C increases in the SST because of the climate change. The results reveal an obvious poleward shift of the potential habitats of O. bartramii in the Northwest Pacific Ocean.

Applications of AMSR-E Measurements for Tropical Cyclone Predictions PartⅠ: Retrieval of Sea Surface Temperature and Wind Speed

Existing satellite microwave algorithms for retrieving Sea Surface Temperature （SST） and Wind （SSW） are applicable primarily for non-raining cloudy conditions. With the launch of the Earth Observing System （EOS） Aqua satellite in 2002, the Advanced Microwave Scanning Radiometer （AMSRoE） onboard provides some unique measurements at lower frequencies which are sensitive to ocean surface parameters under adverse weather conditions. In this study, a new algorithm is developed to derive SST and SSW for hurricane predictions such as hurricane vortex analysis from the AMSRoE measurements at 6.925 and 10.65 GHz. In the algorithm, the effects of precipitation emission and scattering on the measurements are properly taken into account. The algorithm performances are evaluated with buoy measurements and aircraft dropsonde data. It is found that the root mean square （RMS） errors for SST and SSW are about 1.8 K and 1.9 m s^- 1, respectively, when the results are compared with the buoy data over open oceans under precipitating clouds （e.g., its liquid water path is larger than 0.5 mm）, while they are 1.1 K for SST and 2.0 m s^-1 for SSW, respectively, when the retrievals are validated against the dropsonde measurements over warm oceans. These results indicate that our newly developed algorithm can provide some critical surface information for tropical cycle predictions. Currently, this newly developed algorithm has been implemented into the hybrid variational scheme for the hurricane vortex analysis to provide predictions of SST and SSW fields.

Verification of an operational ocean circulation-surface wave coupled forecasting system for the China＇s seas

An operational ocean circulation-surface wave coupled forecasting system for the seas off China and adjacent areas（OCFS-C） is developed based on parallelized circulation and wave models. It has been in operation since November 1, 2007. In this paper we comprehensively present the simulation and verification of the system, whose distinguishing feature is that the wave-induced mixing is coupled in the circulation model. In particular, with nested technique the resolution in the China＇s seas has been updated to（1/24）° from the global model with（1/2）°resolution. Besides, daily remote sensing sea surface temperature（SST） data have been assimilated into the model to generate a hot restart field for OCFS-C. Moreover, inter-comparisons between forecasting and independent observational data are performed to evaluate the effectiveness of OCFS-C in upper-ocean quantities predictions, including SST, mixed layer depth（MLD） and subsurface temperature. Except in conventional statistical metrics, non-dimensional skill scores（SS） is also used to evaluate forecast skill. Observations from buoys and Argo profiles are used for lead time and real time validations, which give a large SS value（more than 0.90）. Besides, prediction skill for the seasonal variation of SST is confirmed. Comparisons of subsurface temperatures with Argo profiles data indicate that OCFS-C has low skill in predicting subsurface temperatures between 100 m and 150 m. Nevertheless, inter-comparisons of MLD reveal that the MLD from model is shallower than that from Argo profiles by about 12 m, i.e., OCFS-C is successful and steady in MLD predictions. Validation of 1-d, 2-d and 3-d forecasting SST shows that our operational ocean circulation-surface wave coupled forecasting model has reasonable accuracy in the upper ocean.

The regime shift in the 1960s and associated atmospheric change over the southern Indian Ocean

The change of sea surface temperature（SST） in the southern Indian Ocean（SIO） during the recent six decades has been analyzed based on oceanic reanalysis and model, as well as atmospheric data. The results show that a thermal regime shift in SIO during the 1960 s, which is not caught enough attentions, has been of equal magnitude to the linear warming since 1970. Empirical Orthogonal Function（EOF） analyses reveal that a thermal shift is combined with atmospheric changes such as the weakening of westerly during the period of 1960–1967. Inner dynamic connections can be defined that when the westerly winds turn weak, the anticyclonic wind circulation between westerly winds and the trade winds decreases, which further reduces the SST to a negative peak in this period. It is noted that the shifts in the 1960 s are also evident for Southern Hemisphere. For example, subtropical high and the entire westerly winds belt at high latitudes both change dramatically in the 1960 s. This large-scaled process maybe link to the change of southern annular mode（SAM）.

Contributions of internal climate variability in driving global and ocean temperature variations using multi-layer perceptron neural network

Roles of internal climate variabilities regulating global and ocean temperature changes is a hot but complex issue of scientific concern,infuencing the comprehensive policy-making in response to global and regional warming.In this study,the time series of monthly global and ocean mean surface temperature(GST and OST,respectively)since 1866 is successflly reconstructed via natural and anthropogenic forcing factors and internal climate variability by using a Multi-Layer Perceptron(MLP)neural network technique.The MLP demonstrates prominent monthly GST and OST reconstruction skills on both interannual and annual time scales.Most of the warming in GST and OST since 1866 is found to be attributable to anthropogenic forcing,while the multidecadal and interannual GST and OST variations are considerably dominated by Atlantic Multidecadal Oscillation(AMO).Internal climate variabilities like Interdecadal Pacific Oscillation(IPO)can amplify the GST and OST changes and explain the global warming slowdown since 1998.Southern Oscillation Index(SOI)performs a similar role as IPO but to a lesser extent.Changes in OST caused by solar forcing are more considerable than those in GST.Moreover,the"biased warmth"during the Second World War is successfully reconstructed in MLP.AMO and IPO can explain most annual and even sub-annual temperature variations during this period,offering an explanation for the existence of this abnormal warm period other than that it was entirely caused by instrumental errors.The generally high accuracy of reconstructions on interannual and annual time scales can enhance the ability to monitor the prompt feedback of specific external radiative forcings and internal variabilities to changes in climate.

The Analysis of Global Warming Patterns from 1970s to 2010s

While global warming is only one part of climate change effects, it poses the highest risk to our habitats and ecologies. It is alarming that global warming has heightened in multiple locations and is intensified since the early 1970s. Since then, there are certain global warming patterns that could guide us with an overview of what mitigation and adaptation strategies should be developed in the future decades. There are certain regions affected more than another, and there are certain patterns with adverse effects on regions, sub-regions, and even continents. This study provides an insightful analysis of recent global warming patterns, those that are affecting us the most with regional climate change of different types, upsurge in frequency and intensity of natural disasters, and drastic impacts on our ecosystems around the world. By analysing the global warming patterns of these last four decades, this research study sheds light on where these patterns are coming from, how they are developing, and what are their impacts. This study is conducted through grey literature and analysis of the recorded global warming data publicly available by the NASA-GISS data centre for global temperature. This brief—but comprehensive—analysis helps us to have a better understanding of what comes next for global warming impacts, and how we should ultimately react. The study contributes to the field by discovering three key points analysed based on available data and literature on recorded global temperature, including: differences between north and south hemispheres, specific patterns due to ocean surface temperature increase, and recent impacts on particular regions. The study concludes with the importance of global scale analysis to have a more realistic understanding of the global warming patterns and their impacts on all living habitats.

Possible Causes of the Interdecadal Transition of the Somali Jet Around the Late 1990s

This observational study demonstrates that the Somali jet（SMJ） experienced a notable interdecadal transition in not only its lower-level parts（〈 850 hP a） but also its higher-level parts（850-600 h Pa） in the late 1990 s. The results also show that the jet at higher level is more significantly related to East Asian monsoon rainfall than that at lower level. Thus, a new whole-layer SMJ（WSMJ） index which includes variations of the higher-level jet is defined based on the average meridional wind speed at five levels（1000-600 h Pa）. The interdecadal transition of the SMJ can be mainly attributed to the meridional thermal contrast anomalies near the equator which are associated with the three-pole pattern of the southern Indian Ocean.