Earth System Model FGOALS-s2: Coupling a Dynamic Global Vegetation and Terrestrial Carbon Model with the Physical Climate System Model

Earth System Models （ESMs） are fundamental tools for understanding climate-carbon feedback. An ESM version of the Flexible Global Ocean-Atmosphere-Land System model （FGOALS） was recently developed within the IPCC AR5 Coupled Model Intercomparison Project Phase 5 （CMIP5） modeling framework, and we describe the development of this model through the coupling of a dynamic global vegetation and terrestrial carbon model with FGOALS-s2. The performance of the coupled model is evaluated as follows. The simulated global total terrestrial gross primary production （GPP） is 124.4 PgC yr-I and net pri- mary production （NPP） is 50.9 PgC yr-1. The entire terrestrial carbon pools contain about 2009.9 PgC, comprising 628.2 PgC and 1381.6 PgC in vegetation and soil pools, respectively. Spatially, in the tropics, the seasonal cycle of NPP and net ecosystem production （NEP） exhibits a dipole mode across the equator due to migration of the monsoon rainbelt, while the seasonal cycle is not so significant in Leaf Area Index （LAI）. In the subtropics, especially in the East Asian monsoon region, the seasonal cycle is obvious due to changes in temperature and precipitation from boreal winter to summer. Vegetation productivity in the northern mid-high latitudes is too low, possibly due to low soil moisture there. On the interannual timescale, the terrestrial ecosystem shows a strong response to ENSO. The model- simulated Nifio3.4 index and total terrestrial NEP are both characterized by a broad spectral peak in the range of 2-7 years. Further analysis indicates their correlation coefficient reaches -0.7 when NEP lags the Nifio3.4 index for about 1-2 months.

Temporal and Spatial Variations of Global Deep Cloud Systems Based on CloudSat and CALIPSO Satellite Observations

ABSTRACT The spatial and temporal global distribution of deep clouds was analyzed using a four-year dataset （2007-10） based on observations from CloudSat and CALIPSO. Results showed that in the Northern Hemisphere, the number of deep cloud systems （DCS） reached a maximum in summer and a minimum in winter. Seasonal variations in the number of DCS varied zonally in the Southern Hemisphere. DCS occurred most frequently over central Africa, the northern parts of South America and Australia, and Tibet. The mean cloud-top height of deep cloud cores （TDCC） decreased toward high latitudes in all seasons. DCS with the highest TDCC and deepest cores occurred over east and south Asian monsoon regions, west-central Africa and northern South America. The width of DCS （WDCS） increased toward high latitudes in all seasons. In general, DCS were more developed in the horizontal than in the vertical direction over high latitudes and vice versa over lower lat- itudes. Findings from this study show that different mechanisms are behind the development of DCS at different latitudes. Most DCS at low latitudes are deep convective clouds which are highly developed in the vertical direction but cover a rela tively small area in the horizontal direction; these DCS have the highest TDCC and smallest WDCS. The DCS at midlatitudes are more likely to be caused by cyclones, so they have less vertical development than DCS at low latitudes. DCS at high latitudes are mainly generated by large frontal systems, so they have the largest WDCS and the smallest TDCC.

Cloud-Aerosol-Radiation (CAR) Ensemble Modeling System: Overall Accuracy and Efficiency

The Cloud Aerosol- Radiation （CAR） ensemble modeling system has recently been built to better un- derstand cloud/aerosol/radiation processes and determine the uncertainties caused by different treatments of cloud/aerosol/radiation in climate models. The CAR system comprises a large scheme collection of cloud, aerosol, and radiation processes available in the literature, including those commonly used by the world＇s leading GCMs. In this study, detailed analyses of the overall accuracy and efficiency of the CAR system were performed. Despite the different observations used, the overall accuracies of the CAR ensemble means were found to be very good for both shortwave （SW） and longwave （LW） radiation calculations. Taking tile percentage errors for July 2004 compared to ISCCP （International Satellite Cloud Climatology Project） data over （60~N, 60~S） as an example, even among the 448 CAR members selected here, those errors of the CAR ensemble means were only about -0.67% （-0.6 W m-2） and -0.82% （-2.0 W m-2） for SW and LW upward fluxes at the top of atmosphere, and 0.06% （0.1 W m-2） and -2.12% （-7.8 W m 2） for SW and LW downward fluxes at the surface, respectively. Furthermore, model SW frequency distributions in July 2004 covered the observational ranges entirely, with ensemble means located in the middle of the ranges. Moreover, it was found that the accuracy of radiative transfer calculations can be significantly enhanced by＂ using certain combinations of cloud schemes for the cloud cover fraction, particle effective size, water path, and optical properties, along with better explicit treatments for unresolved cloud structures.

Assimilating the LAI Data to the VEGAS Model Using the Local Ensemble Transform Kalman Filter: An Observing System Simulation Experiment

Information on the spatial and temporal patterns of surface carbon flux is crucial to understanding of source/sink mechanisms and projection of future atmospheric CO2 concentrations and climate. This study presents the construction and implementation of a terrestrial carbon cycle data assimilation system based on a dynamic vegetation and terrestrial carbon model Vegetation-Global-Atmosphere-Soil(VEGAS) with an advanced assimilation algorithm, the local ensemble transform Kalman filter(LETKF, hereafter LETKF-VEGAS). An observing system simulation experiment(OSSE) framework was designed to evaluate the reliability of this system, and numerical experiments conducted by the OSSE using leaf area index(LAI) observations suggest that the LETKF-VEGAS can improve the estimations of leaf carbon pool and LAI significantly, with reduced root mean square errors and increased correlation coefficients with true values, as compared to a control run without assimilation. Furthermore, the LETKF-VEGAS has the potential to provide more accurate estimations of the net primary productivity(NPP) and carbon flux to atmosphere(CFta).

June to October Aerosol Optical Depth over the Arctic at Various Spatial and Temporal Scales in MODIS, MAIAC, CALIOP and GOES Data

The accuracy of the cloud-aerosol lidar with orthogonal polarization (CALIOP), moderate resolution imaging spectroradiometer (MODIS), Multi-Angle Implementation of Atmospheric Correction (MAIAC), and Geostationary Operational Environmental Satellite (GOES) aerosol optical depth (AOD) products for the Arctic north of 59.75°N was examined by means of 35 aerosol robotic network (AERONET) AOD sites. The assessment for June to October 2006 to 2020 showed MAIAC AOD agreed the best with AERONET AOD;CALIOP AOD differed the strongest from the AERONET AOD. Cross-correlations of CALIOP AOD along the satellite path indicated that AOD-values 40 km up-and-down the path often failed to represent the AERONET AOD-values within ±30 min of the overpass in this region dominated by easterly winds. Typically, CALIOP AOD was lower than AERONET AOD and MAIAC AOD at the sites, especially, at sites with mean AOD below 0.1. Generally, MODIS AOD values exceeded those of MAIAC. Comparison of CALIOP, MAIAC, and MODIS products resampled on a 0.25° × 0.25° grid revealed differences among the products caused by their temporal and spatial resolution, sample habit and size. Typically, the MODIS AOD-product showed the most details in AOD distribution. Despite differences in AOD-values, all products provided similar temporal evolution of elevated and lower AOD.

Changes in Aerosol Optical Depth over the Arctic Ocean as Seen by CALIOP, MAIAC, and MODIS C6.1

Due to the recent increase in Arctic shipping, 2006-2020 June to October Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 (C6.1), and Multi-Angle Implementation of Atmospheric Correction (MAIAC) retrieved aerosol optical depth (AOD) data were examined for changes in AOD from period 1 (P1, 2006-2012) to period 2 (P2, 2014-2020 (P2). Herein, AOD was statistically analyzed on a 0.25° × 0.25° grid and in the airsheds over the various ocean basins over the Arctic north of 59.75°N. According to heatmaps of the correlation between AOD and ship traffic, and AOD and fire emissions for the airsheds, all three AOD products captured the observed inter-annual variability in wildfire occurrence well, and showed wildfire emissions over Siberia were more severe in P2 than P1. Except for the Atlantic, North, and Baltic Seas, Beaufort Sea, and Barents Sea, all three AOD products indicated that AOD was higher over the various basins in P2 than P1, but disagreed on the magnitude. This fact suggests that the detection of changes in the typical low AOD over the Arctic Ocean might be rather qualitative than quantitative. While all products captured increases in AOD due to ships at berth, only MODIS C6.1 caught the elevated AOD due to shipping on the Siberian rivers. Obviously, sub-daily resolutions are required to capture increased AOD due to short-term events like a traveling ship or short-interval fire.

海洋气溶胶多角度偏振辐射特性研究

海洋气溶胶是对流层气溶胶的重要组成部分,对全球的辐射收支平衡及气侯变化均有重要的影响。评价气溶胶的直接与间接辐射效应需要对气溶胶的性质进行深入的研究。多角度偏振为气溶胶光学物理性质研究提供了新的方法。在对可见光550nm和近红外860nm波段处海洋气溶胶的光学性质的研究基础上,采用矢量辐射传输模型模拟了TOA(top of atmosphere)反射率和偏振反射率与下垫面性质、观测方位角、气溶胶光学厚度之间的敏感性。模拟结果表明,海洋型气溶胶的多角度偏振信息可以有效地体现气溶胶的光学性质,可以利用多角度偏振遥感信息进行海洋气溶胶的反演,为利用多角度偏振遥感数据进行海洋气溶胶提供了理论基础。

一个改进的混合型海气耦合模式：ENSO模拟

通过在中国科学院大气物理研究所热带太平洋环流模式与一个统计大气模式所建立的混合型海气耦合模式中引入次表层上卷海温非局地参数化方案,对比分析了次表层上卷海温对耦合模式模拟结果的影响,表明在引入次表层上卷海温非局地参数化方案前耦合模式模拟的SSTA最大变率中心位于日界线附近赤道南北狭窄范围内,而在赤道东太平洋及南美沿岸一带变率过低,周期呈准2年振荡。改进后,耦合模式模拟结果的分布不论在东西方向亦或南北方向与观测更为相近,振荡周期为4年左右,而且还能模拟出观测中ENSO振荡的季节依赖性特征。进一步分析改进的耦合模式中海气耦合特征,表明"延迟振子"理论、"西太平洋振子"理论、"充电-放电振子"理论及"平流-反射"理论所揭示的一些规律在该模式中都能被不同程度地描述出来,这说明在实际的ENSO循环过程中,可能有多种机制在同时起作用。

卫星臭氧资料的发展与应用

随着卫星探测技术的进步、天气学和气候学理论的不断完善,以及高性能计算机广泛应用,卫星臭氧资料的种类得到极大丰富并被应用到多个研究领域中,取得了一系列重要成果。文中介绍了主要星载臭氧探测仪的发展概况,回顾了卫星臭氧资料在气象领域的应用研究成果,主要包括卫星臭氧资料在气旋或低压过程中、全球或区域臭氧的气候分布及变化特征、高原臭氧分布及变化特点、数值应用等方面的应用研究,并展望了卫星臭氧资料研究的未来发展趋势。

焉耆盆地不同植被下土壤有机碳库的特征研究

以新疆干旱区焉耆盆地不同植被下的土壤为研究对象，研究了干旱环境不同植被下土壤有机碳库累积特征，为进一步推动干旱区有机碳循环的研究提供基础。结果表明，不同植被土壤有机碳随土壤深度的增加而减少，农田植被土壤有机碳高于相同土壤剖面其他各荒漠植被；农田植被土壤有机碳库密度高于相同土壤剖面其他各荒漠植被，且农田植被土壤剖面有机碳库密度最大；O～5、5～15、15～30、50～100cm土壤剖面的农田植被土壤有机碳库密度分布较为均匀。而非豆科植被与豆科植被的土壤有机碳库密度分布不均匀。

基于MERIT DEM和DRT升尺度化算法的多分辨率全国河网数据集构建

相对较粗空间分辨率(>1 km)的水文网络或水文地理数据集是大尺度水文及陆面过程模型的基本输入数据,需要从数字高程模型中提取高分辨率河网并通过升尺度化获取。MERIT DEM是消除了复合误差的新版全球高分辨率(90 m)数字高程模型,提取的高分辨率河网信息更为精准。DRT是当前国际水文领域常用的高效河网自动升尺度化算法之一,可将高分辨率河网的结构特性完好地输出到粗分辨率河网。该文选取MERIT DEM的中国部分作为数据源,通过DRT升尺度化算法获取全国1°、1/2°、1/4°、1/8°、1/10°、1/16°分辨率的河网数据(流向、河网、流域面积、流距),并采用目视检验、流域面积一致性检验、流距评估等方法综合验证了DRT升尺度数据集的质量。结果表明,DRT算法性能优越,生产的大尺度数据集准确地保护了河道位置、流动方向和流域面积等在高分辨率DEM中描绘的水文特征,将有效降低我国境内流域水文模拟中由水文地形参数化引起的不确定性。

基于遥感与区域化方法的无资料流域水文模型参数优化方法

针对无资料流域径流预报的难点,探讨水文模型参数优化的共性问题,综述区域化方法和遥感方法的研究现状。首先从水文模型参数优化面临的共性问题,即水文地理数据生成、目标函数构建和优化方法选择等问题出发,分析其对参数优选结果的影响,并归纳出当前广泛认可的解决方案。然后结合区域化方法的技术原理和研究进展,着重论述测站密度对区域化方法性能的影响,并分析该方法在中国的适用性。接着从研究区域、水文模型结构、遥感资料以及率定目标等方面归纳总结遥感方法优化水文模型参数的最新研究进展。最后对区域化方法和遥感方法的优缺点及未来发展前景进行对比分析,为中国无资料或缺资料流域径流预报实践提供参考。

基于CWRF模式夏季日降水量的订正技术对比

误差订正是提高模式模拟和预报性能的有效方法。基于CWRF(regional Climate-Weather Research and Forecasting model)25套不同物理参数化方案的日降水量模拟资料,对比仅进行降水日数订正(OCD)、仅进行降水量订正(OCM)和先订正降水日数再订正降水量(COR)三种订正方法,先订正再等权重集成和先等权重集成再订正两种订正思路,重点对1997—2015年华中和华南地区夏季日降水进行订正效果的对比。结果表明:(1)降水日的订正是必要的,综合而言COR方法对CWRF模式日降水的订正效果更佳,尤其是小量级降水,但降水强度的表现不如OCM;(2)先集成后订正的效果更好;(3)CWRF模式不同参数化方案对日降水的模拟能力有显著差别,经过订正后模拟能力均有所提升,但对于不同的模拟方案,其订正效果也不同。表明,误差订正确实能有效提高模式模拟及预报性能,但其效果存在不确定性。提高模式的预报性能,关键还是提高模式对真实大气动力学的表述能力。

Light-absorbing Particles in Snow and Ice: Measurement and Modeling of Climatic and Hydrological impact

Light absorbing particles（LAP, e.g., black carbon, brown carbon, and dust） influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance（a.k.a., surface darkening）, which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice（LAPSI） has been identified as one of major forcings affecting climate change, e.g.in the fourth and fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, and climatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.

Improved ENSO Forecasts by Assimilating Sea Surface Temperature Observations into an Intermediate Coupled Model

A simple method for initializing intermediate coupled models （ICMs） using only sea surface temperature （SST） anomaly data is comprehensively tested in two sets of hindcasts with a new ICM. In the initialization scheme, both the magnitude of the nudging parameter and the duration of the assimilation are considered, and initial conditions for both atmosphere and ocean are generated by running the coupled model with SST anomalies nudged to the observations. A comparison with the observations indicates that the scheme can generate realistic thermal fields and surface dynamic fields in the equatorial Pacific through hindcast experiments. An ideal experiment is performed to get the optimal nudging parameters which include the nudging intensity and nudging time length. Twelve-month-long hindcast experiments are performed with the model over the period 1984-2003 and the period 1997-2003. Compared with the original prediction results, the model prediction skills are significantly improved by the nudging method especially beyond a 6-month lead time during the two different periods. Potential problems and further improvements are discussed regarding the new coupled assimilation system.

Low-Level Temperature Inversions and Their Effect on Aerosol Condensation Nuclei Concentrations under Different Large-Scale Synoptic Circulations

Knowledge of the statistical characteristics of inversions and their effects on aerosols under different large-scale synoptic circulations is important for studying and modeling the diffusion of pollutants in the boundary layer. Based on results gen- erated using the self-organizing map （SOM） weather classification method, this study compares the statistical characteristics of surface-based inversions （SBIs） and elevated inversions （EIs）, and quantitatively evaluates the effect of SBIs on aerosol condensation nuclei （CN） concentrations and the relationship between temperature gradients and aerosols for six prevailing synoptic patterns over the the Southern Great Plains （SGP） site during 2001-10. Large-scale synoptic patterns strongly influ- ence the statistical characteristics of inversions and the accumulation of aerosols in the low-level atmosphere. The activity, frequency, intensity, and vertical distribution of inversions are significantly different among these synoptic patterns. The verti- cal distribution of inversions varies diurnally and is significantly different among the different synoptic patterns. Anticyclonic patterns affect the accumulation of aerosols near the ground more strongly than cyclonic patterns. Mean aerosol CN con- centrations increase during SBIs compared to no inversion cases by 16.1%, 22.6%, 24.5%, 58.7%, 29.8% and 23.7% for the six synoptic patterns. This study confirms that there is a positive correlation between temperature gradients and aerosol CN concentrations near the ground at night under similar large-scale synoptic patterns. The relationship is different for different synoptic patterns and can be described by linear functions. These findings suggest that large-scale synoptic patterns change the static stability of the atmosphere and inversions in the lower atmosphere, thereby influencing the diffusion of aerosols near the ground.

Effects of Interannual Salinity Variability on the Barrier Layer in the Western-Central Equatorial Pacific:A Diagnostic Analysis from Argo

ABSTRACT In this paper, interannual variations in the barrier layer thickness （BLT） are analyzed using Argo three-dimensional temperature and salinity data, with a locus on the effects of interannually varying salinity on the evolution of the El Nifio Southern Oscillation （ENSO）. The interannually varying BLT exhibits a zonal seesaw pattern across the equatorial Pacific during ENSO cycles. This phenomenon has been attributed to two different physical processes. During E1 Nifio （La Nifia）, the barrier layer （BL） is anomalously thin （thick） west of about 160°E, and thick （thin） to the east. In the western equatorial Pacific （the western part： 130°-160°E）, interannual variations of the BLT indicate a lead of one year relative to those of the ENSO onset. The interannual variations of the BLT can be largely attributed to the interannual temperature variability, through its dominant effect on the isothermal layer depth （ILD）. However, in the central equatorial Pacific （the eastern part： 160~E- 170~W）, interannual variations of the BL almost synchronously vary with ENSO, with a lead of about two months relative to those of the local SST. In this region, the interannual variations of the BL are significantly affected by the interannually varying salinity, mainly through its modulation effect on the mixed layer depth （MLD）. As evaluated by a onedimensional boundary layer ocean model, the BL around the dateline induced by interannual salinity anomalies can significantly affect the temperature fields in the upper ocean, indicating a positive feedback that acts to enhance ENSO.

Processes Leading to Second-Year Cooling of the 2010–12 La Ni?a Event,Diagnosed Using GODAS

Isopycnal analyses were performed on the Global Ocean Data Assimilation System （GODAS） to determine the oceanic processes leading to so-called second-year cooling of the La Nina event.In 2010-12,a horseshoe-like pattern was seen,connecting negative temperature anomalies off and on the Equator,with a dominant influence from the South Pacific.During the 2010 La Nina event,warm waters piled up at subsurface depths in the western tropical Pacific.Beginning in early 2011,these warm subsurface anomalies propagated along the Equator toward the eastern basin,acting to reverse the sign of sea surface temperature （SST） anomalies （SSTAs） there and initiate a warm SSTA.However,throughout early 2011,pronounced negative anomalies persisted off the Equator in the subsurface depths of the South Pacific.As isopycnal surfaces outcropped in the central equatorial Pacific,negative anomalies from the subsurface spread upward along with mean circulation pathways,naturally initializing a cold SSTA.In the summer,a cold SSTA reappeared in the central basin,which subsequently strengthened due to the off-equatorial effects mostly in the South Pacific.These SSTAs acted to initiate local coupled air-sea interactions,generating atmospheric-oceanic anomalies that developed and evolved with the second-year cooling in the fall of 2011.However,the cooling tendency in mid-2012 did not develop into another La Nina event,since the cold anomalies in the South Pacific were not strong enough.An analysis of the 2007-09 La Nina event revealed similar processes to the 2010-12 La Nina event.

Ensemble Hindcasts of ENSO Events over the Past 120 Years Using a Large Number of Ensembles

Based on an intermediate coupled model （ICM）, a probabilistic ensemble prediction system （EPS） has been developed. The ensemble Kalman filter （EnKF） data assimilation approach is used for generating the initial ensemble conditions, and a linear, first-order Markov-Chain SST anomaly error model is embedded into the EPS to provide model-error perturbations. In this study, we perform ENSO retrospective forecasts over the 120 year period 1886-2005 using the EPS with 100 ensemble members and with initial conditions obtained by only assimilating historic SST anomaly observations. By examining the retrospective ensemble forecasts and available observations, the verification results show that the skill of the ensemble mean of the EPS is greater than that of a single deterministic forecast using the same ICM, with a distinct improvement of both the correlation and root mean square （RMS） error between the ensemble-mean hindcast and the deterministic scheme over the 12-month prediction period. The RMS error of the ensemble mean is almost 0.2℃ smaller than that of the deterministic forecast at a lead time of 12 months. The probabilistic skill of the EPS is also high with the predicted ensemble following the SST observations well, and the areas under the relative operating characteristic （ROC） curves for three different ENSO states （warm events, cold events, and neutral events） are all above 0.55 out to 12 months lead time. However, both deterministic and probabilistic prediction skills of the EPS show an interdecadal variation. For the deterministic skill, there is high skill in the late 19th century and in the middle-late 20th century （which includes some artificial skill due to the model training period）, and low skill during the period from 1906 to 1961. For probabilistic skill, for the three different ENSO states, there is still a similar interdecadal variation of ENSO probabilistic predictability during the period 1886~2005. There is high skill in the late 19th century from 1886 to 1905, and a decline to a minimum of skill around 1910-50s, beyond which skill rebounds and increases with time until the 2000s.

Modulation of El Nio-Southern Oscillation by Freshwater Flux and Salinity Variability in the Tropical Pacific

The E1 Nifio-Southern Oscillation （ENSO） is emphasized the roles of wind stress and heat flux environmental forcing to the ocean; its effect and modulated by many factors; most previous studies have in the tropical Pacific. Freshwater flux （FWF） is another the related ocean salinity variability in the ENSO region have been of increased interest recently. Currently, accurate quantifications of the FWF roles in the climate remain challenging; the related observations and coupled ocean-atmosphere modeling involve large elements of uncertainty. In this study, we utilized satellite-based data to represent FWF-induced feedback in the tropical Pacific climate system; we then incorporated these data into a hybrid coupled ocean-atmosphere model （HCM） to quantify its effects on ENSO. A new mechanism was revealed by which interannual FWF forcing modulates ENSO in a significant way. As a direct forcing, FWF exerts a significant influence on the ocean through sea surface salinity （SSS） and buoyancy flux （QB） in the western-central tropical Pacific. The SSS perturbations directly induced by ENSO-related interannual FWF variability affect the stability and mixing in the upper ocean. At the same time, the ENSO-induced FWF has a compensating effect on heat flux, acting to reduce interannual Qs variability during ENSO cycles. These FWF-induced processes in the ocean tend to modulate the vertical mixing and entrainment in the upper ocean, enhancing cooling during La Nifia and enhancing warming during E1 Nifio, respectively. The interannual FWF forcing-induced positive feedback acts to enhance ENSO amplitude and lengthen its time scales in the tropical Pacific coupled climate system.