2017 was the warmest year on record for the global ocean according to an updated ocean analysis from Institute of Atmospheric Physics/Chinese Academy of Science. The oceans in the upper 2000 m were 1.51 × 1022 J warmer than the second warmest year of 2015 and 19.19 × 1022 J above the 1981–2010 climatological reference period.
The ecosystem of the Tibetan Plateau is highly susceptible to climate change. Currently, there is little discussion on the temporal changes in the link between climatic factors and vegetation dynamics in this region under the changing climate. By employing Normalized Difference Vegetation Index data, the Climatic Research Unit temperature and precipitation data, and the in-situ meteorological observations, we report the temporal and spatial variations in the relationships between the vegetation dynamics and climatic factors on the Plateau over the past three decades. The results show that from the early 1980s to the mid-1990s, vegetation dynamics in the central and southeastern part of the Plateau appears to show a closer relationship with precipitation prior to the growing season than that of temperature. From the mid-1990s, the temperature rise seems to be the key climatic factor correlating vegetation growth in this region. The effects of increasing temperature on vegetation are spatially variable across the Plateau: it has negative impacts on vegetation activity in the southwestern and northeastern part of the Plateau, and positive impacts in the central and southeastern Plateau. In the context of global warming, the changing climate condition (increasing precipitation and significant rising temperature) might be the potential contributor to the shift in the climatic controls on vegetation dynamics in the central and southeastern Plateau.
The influence of the Arctic atmosphere on Northern Hemisphere midlatitude tropospheric weather and climate is explored by comparing the skill of two sets of 14-day weather forecast experiments using the ECMWF model with and without relaxation of the Arctic atmosphere towards ERA-Interim reanalysis data during the integration. Two pathways are identified along which the Arctic influences midlatitude weather: a pronounced one over Asia and Eastern Europe, and a secondary one over North America. In general, linkages are found to be strongest (weakest) during boreal winter (summer) when the amplitude of stationary planetary waves over the Northern Hemisphere is strongest (weakest). No discernible Arctic impact is found over the North Atlantic and North Pacific region, which is consistent with predominantly southwesterly flow. An analysis of the flow-dependence of the linkages shows that anomalous northerly flow conditions increase the Arctic influence on midlatitude weather over the continents. Specifically, an anomalous northerly flow from the Kara Sea towards West Asia leads to cold surface temperature anomalies not only over West Asia but also over Eastern and Central Europe. Finally, the results of this study are discussed in the light of potential midlatitude benefits of improved Arctic prediction capabilities.
Conflicting results have been presented regarding the link between Arctic sea-ice loss and midlatitude cooling, particularly over Eurasia. This study analyzes uncoupled (atmosphere-only) and coupled (ocean-atmosphere) simulations by the Climate Forecast System, version 2 (CFSv2), to examine this linkage during the Northern Hemisphere winter, focusing on the simulation of the observed surface cooling trend over Eurasia during the last three decades. The uncoupled simulations are Atmospheric Model Intercomparison Project (AMIP) runs forced with mean seasonal cycles of sea surface temperature (SST) and sea ice, using combinations of SST and sea ice from different time periods to assess the role that each plays individually, and to assess the role of atmospheric internal variability. Coupled runs are used to further investigate the role of internal variability via the analysis of initialized predictions and the evolution of the forecast with lead time. The AMIP simulations show a mean warming response over Eurasia due to SST changes, but little response to changes in sea ice. Individual runs simulate cooler periods over Eurasia, and this is shown to be concurrent with a stronger Siberian high and warming over Greenland. No substantial differences in the variability of Eurasian surface temperatures are found between the different model configurations. In the coupled runs, the region of significant warming over Eurasia is small at short leads, but increases at longer leads. It is concluded that, although the models have some capability in highlighting the temperature variability over Eurasia, the observed cooling may still be a consequence of internal variability.
This study examines pre-industrial control simulations from CMIP5 climate models in an effort to better understand the complex relationships between Arctic sea ice and the stratosphere, and between Arctic sea ice and cold winter temperatures over Eurasia. We present normalized regressions of Arctic sea-ice area against several atmospheric variables at extended lead and lag times. Statistically significant regressions are found at leads and lags, suggesting both atmospheric precursors of, and responses to, low sea ice; but generally, the regressions are stronger when the atmosphere leads sea ice, including a weaker polar stratospheric vortex indicated by positive polar cap height anomalies. Significant positive midlatitude eddy heat flux anomalies are also found to precede low sea ice. We argue that low sea ice and raised polar cap height are both a response to this enhanced midlatitude eddy heat flux. The so-called "warm Arctic, cold continents" anomaly pattern is present one to two months before low sea ice, but is absent in the months following low sea ice, suggesting that the Eurasian cooling and low sea ice are driven by similar processes. Lastly, our results suggest a dependence on the geographic region of low sea ice, with low Barents-Kara Sea ice correlated with a weakened polar stratospheric vortex, whilst low Sea of Okhotsk ice is correlated with a strengthened polar vortex. Overall, the results support a notion that the sea ice, polar stratospheric vortex and Eurasian surface temperatures collectively respond to large-scale changes in tropospheric circulation.
Using a set of numerical experiments from 39 CMIP5 climate models, we project the emergence time for 4°C global warming with respect to pre-industrial levels and associated climate changes under the RCP8.5 greenhouse gas concentration scenario. Results show that, according to the 39 models, the median year in which 4°C global warming will occur is 2084. Based on the median results of models that project a 4°C global warming by 2100, land areas will generally exhibit stronger warming than the oceans annually and seasonally, and the strongest enhancement occurs in the Arctic, with the exception of the summer season. Change signals for temperature go outside its natural internal variabilities globally, and the signal-to-noise ratio averages 9.6 for the annual mean and ranges from 6.3 to 7.2 for the seasonal mean over the globe, with the greatest values appearing at low latitudes because of low noise. Decreased precipitation generally occurs in the subtropics, whilst increased precipitation mainly appears at high latitudes. The precipitation changes in most of the high latitudes are greater than the background variability, and the global mean signal-to-noise ratio is 0.5 and ranges from 0.2 to 0.4 for the annual and seasonal means, respectively. Attention should be paid to limiting global warming to 1.5°C, in which case temperature and precipitation will experience a far more moderate change than the natural internal variability. Large inter-model disagreement appears at high latitudes for temperature changes and at mid and low latitudes for precipitation changes. Overall, the inter-model consistency is better for temperature than for precipitation.
The variation of the vegetation growing season in the Three-Rivers Headwater Region of the Tibetan Plateau has recently become a controversial topic. One issue is that the estimated local trend in the start of the vegetation growing season (SOS) based on remote sensing data is easily affected by outliers because this data series is short. In this study, we determine that the spring minimum temperature is the most influential factor for SOS. The significant negative linear relationship between the two variables in the region is evaluated using Moderate Resolution Imaging Spectroradiometer-Normalized Difference Vegetation Index data for 2000-13. We then reconstruct the SOS time series based on the temperature data for 1960-2013. The regional mean SOS shows an advancing trend of 1.42 d (10 yr)-1 during 1960-2013, with the SOS occurring on the 160th and 151st days in 1960 and 2013, respectively. The advancing trend enhances to 6.04 d (10 yr)-1 during the past 14 years. The spatiotemporal variations of the reconstructed SOS data are similar to those deduced from remote sensing data during the past 14 years. The latter exhibit an even larger regional mean trend of SOS [7.98 d (10 yr-1)] during 2000-13. The Arctic Oscillation is found to have significantly influenced the changing SOS, especially for the eastern part of the region, during 2000-13.
In contrast to previous studies that have tended to focus on the influence of the total Arctic sea-ice cover on the East Asian summer tripole rainfall pattern, the present study identifies the Barents Sea as the key region where the June sea-ice variability exerts the most significant impacts on the East Asian August tripole rainfall pattern, and explores the teleconnection mechanisms involved. The results reveal that a reduction in June sea ice excites anomalous upward air motion due to strong near-surface thermal forcing, which further triggers a meridional overturning wave-like pattern extending to midlatitudes. Anomalous downward motion therefore forms over the Caspian Sea, which in turn induces zonally oriented overturning circulation along the subtropical jet stream, exhibiting the east-west Rossby wave train known as the Silk Road pattern. It is suggested that the Bonin high, a subtropical anticyclone predominant near South Korea, shows a significant anomaly due to the eastward extension of the Silk Road pattern to East Asia. As a possible descending branch of the Hadley cell, the Bonin high anomaly ultimately triggers a meridional overturning, establishing the Pacific-Japan pattern. This in turn induces an anomalous anticyclone and cyclone pair over East Asia, and a tripole vertical convection anomaly meridionally oriented over East Asia. Consequently, a tripole rainfall anomaly pattern is observed over East Asia. Results from numerical experiments using version 5 of the Community Atmosphere Model support the interpretation of this chain of events.
The Atmosphere Profiling Synthetic Observation System (APSOS) is the first ground-based facility for profiling atmospheric variables and multiple constituents in the whole (neutral) atmosphere from the surface up to the lower thermosphere. It enables simultaneous observations and extensive studies of the atmospheric vertical structure and constituent transport.
The program under which this new facility was developed, funded by the National Natural Science Foundation of China, was launched in 2012 for developing a cluster of state-of-the-art instruments to facilitate atmospheric studies over the Tibetan Plateau (TP). After a one-year test run in Anhui Province at the Huainan Division of the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS) (32.62°N, 116.98°E), APSOS was recently deployed at its final destination——Yangbajain (YBJ) International Cosmic Ray Observatory (30.21°N, 90.43°E; 4300 m MSL), located in YBJ valley, about 90 km northwest of the city of Lhasa, the Tibet Autonomous Region, China. Figure 1 shows an aerial view of the newly established observatory for APSOS in YBJ.
The Yangtze River has been subject to heavy flooding throughout history, and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods. Dams along the river help to manage flood waters, and are important sources of electricity for the region. Being able to forecast high-impact events at long lead times therefore has enormous potential benefit. Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services. The teleconnection from El Niño to Yangtze River basin rainfall meant that the strong El Niño in winter 2015/16 provided a valuable opportunity to test the application of a dynamical forecast system. This paper therefore presents a case study of a real-time seasonal forecast for the Yangtze River basin, building on previous work demonstrating the retrospective skill of such a forecast. A simple forecasting methodology is presented, in which the forecast probabilities are derived from the historical relationship between hindcast and observations. Its performance for 2016 is discussed. The heavy rainfall in the May-June-July period was correctly forecast well in advance. August saw anomalously low rainfall, and the forecasts for the June-July-August period correctly showed closer to average levels. The forecasts contributed to the confidence of decision-makers across the Yangtze River basin. Trials of climate services such as this help to promote appropriate use of seasonal forecasts, and highlight areas for future improvements.
In order to examine the response of the tropical Pacific Walker circulation (PWC) to strong tropical volcanic eruptions (SVEs), we analyzed a three-member long-term simulation performed with HadCM3, and carried out four additional CAM4 experiments. We found that the PWC shows a significant interannual weakening after SVEs. The cooling effect from SVEs is able to cool the entire tropics. However, cooling over the Maritime Continent is stronger than that over the central-eastern tropical Pacific. Thus, non-uniform zonal temperature anomalies can be seen following SVEs. As a result, the sea level pressure gradient between the tropical Pacific and the Maritime Continent is reduced, which weakens trade winds over the tropical Pacific. Therefore, the PWC is weakened during this period. At the same time, due to the cooling subtropical and midlatitude Pacific, the Intertropical Convergence Zone (ITCZ) and South Pacific convergence zone (SPCZ) are weakened and shift to the equator. These changes also contribute to the weakened PWC. Meanwhile, through the positive Bjerknes feedback, weakened trade winds cause El Niño-like SST anomalies over the tropical Pacific, which in turn further influence the PWC. Therefore, the PWC significantly weakens after SVEs. The CAM4 experiments further confirm the influences from surface cooling over the Maritime Continent and subtropical/midlatitude Pacific on the PWC. Moreover, they indicate that the stronger cooling over the Maritime Continent plays a dominant role in weakening the PWC after SVEs. In the observations, a weakened PWC and a related El Niño-like SST pattern can be found following SVEs.
Variations of surface air temperature (SAT) are key in affecting the hydrological cycle, ecosystems and agriculture in western China in summer. This study assesses the seasonal forecast skill and reliability of SAT in western China, using the GloSea5 operational forecast system from the UK Met Office. Useful predictions are demonstrated, with considerable skill over most regions of western China. The temporal correlation coefficients of SAT between model predictions and observations are larger than 0.6, in both northwestern China and the Tibetan Plateau. There are two important sources of skill for these predictions in western China: interannual variation of SST in the western Pacific and the SST trend in the tropical Pacific. The tropical SST change in the recent two decades, with a warming in the western Pacific and cooling in the eastern Pacific, which is reproduced well by the forecast system, provides a large contribution to the skill of SAT in northwestern China. Additionally, the interannual variation of SST in the western Pacific gives rise to the reliable prediction of SAT around the Tibetan Plateau. It modulates convection around the Maritime Continent and further modulates the variation of SAT on the Tibetan Plateau via the surrounding circulation. This process is evident irrespective of detrending both in observations and the model predictions, and acts as a source of skill in predictions for the Tibetan Plateau. The predictability and reliability demonstrated in this study is potentially useful for climate services providing early warning of extreme climate events and could imply useful economic benefits.
Using observational data and the pre-industrial simulations of 19 models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), the El Niño (EN) and La Niña (LN) events in positive and negative Pacific Decadal Oscillation (PDO) phases are examined. In the observational data, with EN (LN) events the positive (negative) SST anomaly in the equatorial eastern Pacific is much stronger in positive (negative) PDO phases than in negative (positive) phases. Meanwhile, the models cannot reasonably reproduce this difference. Besides, the modulation of ENSO frequency asymmetry by the PDO is explored. Results show that, in the observational data, EN is 300% more (58% less) frequent than LN in positive (negative) PDO phases, which is significant at the 99% confidence level using the Monte Carlo test. Most of the CMIP5 models exhibit results that are consistent with the observational data.
A modified hydrometeor classification algorithm (HCA) is developed in this study for Chinese polarimetric radars. This algorithm is based on the U.S. operational HCA. Meanwhile, the methodology of statistics-based optimization is proposed including calibration checking, datasets selection, membership functions modification, computation thresholds modification, and effect verification. Zhuhai radar, the first operational polarimetric radar in South China, applies these procedures. The systematic bias of calibration is corrected, the reliability of radar measurements deteriorates when the signal-to-noise ratio is low, and correlation coefficient within the melting layer is usually lower than that of the U.S. WSR-88D radar. Through modification based on statistical analysis of polarimetric variables, the localized HCA especially for Zhuhai is obtained, and it performs well over a one-month test through comparison with sounding and surface observations. The algorithm is then utilized for analysis of a squall line process on 11 May 2014 and is found to provide reasonable details with respect to horizontal and vertical structures, and the HCA results——especially in the mixed rain-hail region——can reflect the life cycle of the squall line. In addition, the kinematic and microphysical processes of cloud evolution and the differences between radar-detected hail and surface observations are also analyzed. The results of this study provide evidence for the improvement of this HCA developed specifically for China.
Particulate matter with diameters of 2.5 μm or smaller (PM2.5) and ozone (O3) are major pollutants in the urban atmosphere. PM2.5 can affect O3 by altering the photolysis rate and heterogeneous reactions. However, these two processes and their relative importance remain uncertain. In this paper, with Nanjing in China as the target city, we investigate the characteristics and mechanism of interactions between particles and O3 based on ground observations and numerical modeling. In 2008, the average concentrations of PM2.5 and O3 at Caochangmen station are 64.6 47.4 μg m-3 and 24.6 22.8 ppb, respectively, while at Pukou station they are 94.1 63.4 μg m-3 and 16.9 14.9 ppb. The correlation coefficient between PM2.5 and O3 is -0.46. In order to understand the reaction between PM2.5 and O3, we construct a box model, in which an aerosol optical property model, ultraviolet radiation model, gas phase chemistry model, and heterogeneous chemistry model, are coupled. The model is employed to investigate the relative contribution of the aforementioned two processes, which vary under different particle concentrations, scattering capability and VOCs/NO x ratios (VOCs: volatile organic compounds; NO x: nitric oxide and nitrogen dioxide). Generally, photolysis rate effect can cause a greater O3 reduction when the particle concentrations are higher, while heterogeneous reactions dominate O3 reduction with low-level particle concentrations. Moreover, in typical VOC-sensitive regions, O3 can even be increased by heterogeneous reactions. In Nanjing, both processes lead to O3 reduction, and photolysis rate effect is dominant. Our study underscores the importance of photolysis rate effect and heterogeneous reactions for O3, and such interaction processes should be fully considered in future atmospheric chemistry modeling.
Although quality assurance and quality control procedures are routinely applied in most air quality networks, outliers can still occur due to instrument malfunctions, the influence of harsh environments and the limitation of measuring methods. Such outliers pose challenges for data-powered applications such as data assimilation, statistical analysis of pollution characteristics and ensemble forecasting. Here, a fully automatic outlier detection method was developed based on the probability of residuals, which are the discrepancies between the observed and the estimated concentration values. The estimation can be conducted using filtering——or regressions when appropriate——to discriminate four types of outliers characterized by temporal and spatial inconsistency, instrument-induced low variances, periodic calibration exceptions, and less PM10 than PM2.5 in concentration observations, respectively. This probabilistic method was applied to detect all four types of outliers in hourly surface measurements of six pollutants (PM2.5, PM10, SO2, NO2, CO and O3) from 1436 stations of the China National Environmental Monitoring Network during 2014-16. Among the measurements, 0.65%-5.68% are marked as outliers, with PM10 and CO more prone to outliers. Our method successfully identifies a trend of decreasing outliers from 2014 to 2016, which corresponds to known improvements in the quality assurance and quality control procedures of the China National Environmental Monitoring Network. The outliers can have a significant impact on the annual mean concentrations of PM2.5, with differences exceeding 10 μg m-3 at 66 sites.
Future changes in the 50-yr return level for temperature and precipitation extremes over mainland China are investigated based on a CMIP5 multi-model ensemble for RCP2.6, RCP4.5 and RCP8.5 scenarios. The following indices are analyzed: TXx and TNn (the annual maximum and minimum of daily maximum and minimum surface temperature), RX5day (the annual maximum consecutive 5-day precipitation) and CDD (maximum annual number of consecutive dry days). After first validating the model performance, future changes in the 50-yr return values and return periods for these indices are investigated along with the inter-model spread. Multi-model median changes show an increase in the 50-yr return values of TXx and a decrease for TNn, more specifically, by the end of the 21st century under RCP8.5, the present day 50-yr return period of warm events is reduced to 1.2 yr, while extreme cold events over the country are projected to essentially disappear. A general increase in RX5day 50-yr return values is found in the future. By the end of the 21st century under RCP8.5, events of the present RX5day 50-yr return period are projected to reduce to <10 yr over most of China. Changes in CDD-50 show a dipole pattern over China, with a decrease in the values and longer return periods in the north, and vice versa in the south. Our study also highlights the need for further improvements in the representation of extreme events in climate models to assess the future risks and engineering design related to large-scale infrastructure in China.
In this study, we investigate the influence of low-frequency solar forcing on the East Asian winter monsoon (EAWM) by analyzing a four-member ensemble of 600-year simulations performed with HadCM3 (Hadley Centre Coupled Model, version 3). We find that the EAWM is strengthened when total solar irradiance (TSI) increases on the multidecadal time scale. The model results indicate that positive TSI anomalies can result in the weakening of Atlantic meridional overturning circulation, causing negative sea surface temperature (SST) anomalies in the North Atlantic. Especially for the subtropical North Atlantic, the negative SST anomalies can excite an anomalous Rossby wave train that moves from the subtropical North Atlantic to the Greenland Sea and finally to Siberia. In this process, the positive sea-ice feedback over the Greenland Sea further enhances the Rossby wave. The wave train can reach the Siberian region, and strengthen the Siberian high. As a result, low-level East Asian winter circulation is strengthened and the surface air temperature in East Asia decreases. Overall, when solar forcing is stronger on the multidecadal time scale, the EAWM is typically stronger than normal. Finally, a similar linkage can be observed between the EAWM and solar forcing during the period 1850-1970.
This study demonstrates the two different Rossby wave train (RWT) patterns related to the developing/decaying upper atmospheric heat source over the Tibetan Plateau (TPUHS) in boreal summer. The results show that the summer TPUHS is dominated by quasi-biweekly variability, particularly from late July to mid-August when the subtropical jet steadily stays to the north of the TP. During the developing period of TPUHS events, the intensifying TPUHS corresponds to an anomalous upper-tropospheric high over the TP, which acts as the main source of a RWT that extends northeastward, via North China, the central Pacific and Alaska, to the northeastern Pacific region. This RWT breaks up while the anomalous high is temporarily replaced by an anomalous low due to the further deepened convective heating around the TPUHS peak. However, this anomalous low, though existing for only three to four days due to the counteracting dynamical effects of the persisting upper/lower divergence/convergence over the TP, acts as a new wave source to connect to an anomalous dynamical high over the Baikal region. Whilst the anomalous low is diminishing rapidly, this Baikal high becomes the main source of a new RWT, which develops eastward over the North Pacific region till around eight days after the TPUHS peak. Nevertheless, the anomaly centers along this decaying-TPUHS-related RWT mostly appear much weaker than those along the previous RWT. Therefore, their impacts on circulation and weather differ considerably from the developing to the decaying period of TPUHS events.
This study investigates the variations in the tropical ascending branches (TABs) of Hadley circulations (HCs) during past decades, using a variety of reanalysis datasets. The northern tropical ascending branch (NTAB) and the southern tropical ascending branch (STAB), which are defined as the ascending branches of the Northern Hemisphere HC and Southern Hemisphere HC, respectively, are identified and analyzed regarding their trends and variability. The reanalysis datasets consistently show a persistent increase in STAB during past decades, whereas they show less consistency in NTAB regarding its decadal- to multidecadal variability, which generally features a decreasing trend. These asymmetric trends in STAB and NTAB are attributed to asymmetric trends in the tropical SSTs. The relationship between STAB/NTAB and tropical SSTs is further examined regarding their interannual and decadal- to multidecadal variability. On the interannual time scale, the STAB and NTAB are essentially modulated by the eastern-Pacific type of ENSO, with a strengthened (weakened) STAB (NTAB) under an El Niño condition. On the decadal- to multidecadal time scale, the variability of STAB and NTAB is closely related to the southern tropical SSTs and the meridional asymmetry of global tropical SSTs, respectively. The tropical eastern Pacific SSTs (southern tropical SSTs) dominate the tropical SST-NTAB/STAB relationship on the interannual (decadal- to multidecadal) scale, whereas the NTAB is a passive factor in this relationship. Moreover, a cross-hemispheric relationship between the NTAB/STAB and the HC upper-level meridional winds is revealed.
Accurate atmospheric temperature and moisture information with high temporal/spatial resolutions are two of the key parameters needed in regional numerical weather prediction (NWP) models to reliably predict high-impact weather events such as local severe storms (LSSs). High spectral resolution or hyperspectral infrared (HIR) sounders from geostationary orbit (GEO) provide an unprecedented source of near time-continuous, three-dimensional information on the dynamic and thermodynamic atmospheric fields——an important benefit for nowcasting and NWP-based forecasting. In order to demonstrate the value of GEO HIR sounder radiances on LSS forecasts, a quick regional OSSE (Observing System Simulation Experiment) framework has been developed, including high-resolution nature run generation, synthetic observation simulation and validation, and impact study on LSS forecasts. Results show that, on top of the existing LEO (low earth orbit) sounders, a GEO HIR sounder may provide value-added impact [a reduction of 3.56% in normalized root-mean-square difference (RMSD)] on LSS forecasts due to large spatial coverage and high temporal resolution, even though the data are assimilated every 6 h with a thinning of 60 km. Additionally, more frequent assimilations and smaller thinning distances allow more observations to be assimilated, and may further increase the positive impact from a GEO HIR sounder. On the other hand, with denser and more frequent observations assimilated, it becomes more difficult to handle the spatial error correlation in observations and gravity waves due to the limitations of current assimilation and forecast systems (such as a static background error covariance). The peak reduction of 4.6% in normalized RMSD is found when observations are assimilated every 3 h with a thinning distance of 30 km.
Drylands are among those regions most sensitive to climate and environmental changes and human-induced perturbations. The most widely accepted definition of the term dryland is a ratio, called the Surface Wetness Index (SWI), of annual precipitation to potential evapotranspiration (PET) being below 0.65. PET is commonly estimated using the Thornthwaite (PET_Th) and Penman-Monteith equations (PET_PM). The present study compared spatiotemporal characteristics of global drylands based on the SWI with PET_Th and PET_PM. Results showed vast differences between PET_Th and PET_PM; however, the SWI derived from the two kinds of PET showed broadly similar characteristics in the interdecadal variability of global and continental drylands, except in North America, with high correlation coefficients ranging from 0.58 to 0.89. It was found that, during 1901-2014, global hyper-arid and semi-arid regions expanded, arid and dry sub-humid regions contracted, and drylands underwent interdecadal fluctuation. This was because precipitation variations made major contributions, whereas PET changes contributed to a much lesser degree. However, distinct differences in the interdecadal variability of semi-arid and dry sub-humid regions were found. This indicated that the influence of PET changes was comparable to that of precipitation variations in the global dry-wet transition zone. Additionally, the contribution of PET changes to the variations in global and continental drylands gradually enhanced with global warming, and the Thornthwaite method was found to be increasingly less applicable under climate change.
Aerosol-cloud-radiation interactions represent one of the largest uncertainties in the current climate assessment. Much of the complexity arises from the non-monotonic responses of clouds, precipitation and radiative fluxes to aerosol perturbations under various meteorological conditions. In this study, an aerosol-aware WRF model is used to investigate the microphysical and radiative effects of aerosols in three weather systems during the March 2000 Cloud Intensive Observational Period campaign at the US Southern Great Plains. Three simulated cloud ensembles include a low-pressure deep convective cloud system, a collection of less-precipitating stratus and shallow cumulus, and a cold frontal passage. The WRF simulations are evaluated by several ground-based measurements. The microphysical properties of cloud hydrometeors, such as their mass and number concentrations, generally show monotonic trends as a function of cloud condensation nuclei concentrations. Aerosol radiative effects do not influence the trends of cloud microphysics, except for the stratus and shallow cumulus cases where aerosol semi-direct effects are identified. The precipitation changes by aerosols vary with the cloud types and their evolving stages, with a prominent aerosol invigoration effect and associated enhanced precipitation from the convective sources. The simulated aerosol direct effect suppresses precipitation in all three cases but does not overturn the aerosol indirect effect. Cloud fraction exhibits much smaller sensitivity (typically less than 2%) to aerosol perturbations, and the responses vary with aerosol concentrations and cloud regimes. The surface shortwave radiation shows a monotonic decrease by increasing aerosols, while the magnitude of the decrease depends on the cloud type.
Severe weather reports and composite radar reflectivity data from 2010-14 over North China were used to analyze the distribution of severe convective wind (SCW) events and their organizational modes of radar reflectivity. The six organizational modes for SCW events (and their proportions) were cluster cells (35.4%), squall lines (18.4%), nonlinear-shaped systems (17.8%), broken lines (11.6%), individual cells (1.2%), and bow echoes (0.5%). The peak month for both squall lines and broken lines was June, whereas it was July for the other four modes. The highest numbers of SCW events were over the mountains, which were generally associated with disorganized systems of cluster cells. In contrast, SCW associated with linear systems occurred mainly over the plains, where stations recorded an average of less than one SCW event per year. Regions with a high frequency of SCW associated with nonlinear-shaped systems also experienced many SCW events associated with squall lines. Values of convective available potential energy, precipitable water, 0-3-km shear, and 0-6-km shear, were demonstrably larger over the plains than over the mountains, which had an evident effect on the organizational modes of SCW events. Therefore, topography may be an important factor in the organizational modes for SCW events over North China.
The ECMWF has been assimilating Feng-Yun-3B (FY-3B) satellite microwave humidity sounder (MWHS) data over ocean in an operational forecasting system since 24 September 2014. It is more difficult, however, to assimilate microwave observations over land and sea ice than over the open ocean due to higher uncertainties in land surface temperature, surface emissivity and less effective cloud screening. We compare approaches in which the emissivity is retrieved dynamically from MWHS channel 1 [150 GHz (vertical polarization)] with the use of an evolving emissivity atlas from 89 GHz observations from the MWHS onboard NOAA and EUMETSAT satellites. The assimilation of the additional data over land improves the fit of short-range forecasts to other observations, notably ATMS (Advanced Technology Microwave Sounder) humidity channels, and the forecast impacts are mainly neutral to slightly positive over the first five days. The forecast impacts are better in boreal summer and the Southern Hemisphere. These results suggest that the techniques tested allow for effective assimilation of MWHS/FY-3B data over land.
We identify that the projected uncertainty of the pan-Arctic sea-ice concentration (SIC) is strongly coupled with the Eurasian circulation in the boreal winter (December-March; DJFM), based on a singular value decomposition (SVD) analysis of the forced response of 11 CMIP5 models. In the models showing a stronger sea-ice decline, the Polar cell becomes weaker and there is an anomalous increase in the sea level pressure (SLP) along 60°N, including the Urals-Siberia region and the Iceland low region. There is an accompanying weakening of both the midlatitude westerly winds and the Ferrell cell, where the SVD signals are also related to anomalous sea surface temperature warming in the midlatitude North Atlantic. In the Mediterranean region, the anomalous circulation response shows a decreasing SLP and increasing precipitation. The anomalous SLP responses over the Euro-Atlantic region project on to the negative North Atlantic Oscillation-like pattern. Altogether, pan-Arctic SIC decline could strongly impact the winter Eurasian climate, but we should be cautious about the causality of their linkage.
The tropical Pacific has begun to experience a new type of El Niño, which has occurred particularly frequently during the last decade, referred to as the central Pacific (CP) El Niño. Various coupled models with different degrees of complexity have been used to make real-time El Niño predictions, but high uncertainty still exists in their forecasts. It remains unknown as to how much of this uncertainty is specifically related to the new CP-type El Niño and how much is common to both this type and the conventional Eastern Pacific (EP)-type El Niño. In this study, the deterministic performance of an El Niño-Southern Oscillation (ENSO) ensemble prediction system is examined for the two types of El Niño. Ensemble hindcasts are run for the nine EP El Niño events and twelve CP El Niño events that have occurred since 1950. The results show that (1) the skill scores for the EP events are significantly better than those for the CP events, at all lead times; (2) the systematic forecast biases come mostly from the prediction of the CP events; and (3) the systematic error is characterized by an overly warm eastern Pacific during the spring season, indicating a stronger spring prediction barrier for the CP El Niño. Further improvements to coupled atmosphere-ocean models in terms of CP El Niño prediction should be recognized as a key and high-priority task for the climate prediction community.
Clouds are critical to the global radiation budget and hydrological cycle, but knowledge is still poor concerning the observed climatology of cloud-base height (CBH) in China. Based on fine-resolution sounding observations from the China Radiosonde Network (CRN), the method used to estimate CBH was modified, and uncertainty analyses indicated that the CBH is good enough. The accuracy of CBH estimation is verified by the comparison between the sounding-derived CBHs and those estimated from the micro-pulse lidar and millimeter-wave cloud radar. As such, the CBH climatology was compiled for the period 2006-16. Overall, the CBH exhibits large geographic variability across China, at both 0800 Local Standard Time (LST) and 2000 LST, irrespective of season. In addition, the summertime cloud base tends to be elevated to higher altitudes in dry regions [i.e., Inner Mongolia and the North China Plain (NCP)]. By comparison, the Tibetan Plateau (TP), Pearl River Delta (PRD) and Sichuan Basin (SCB) have relatively low CBHs (<2.4 km above ground level). In terms of seasonality, the CBH reaches its maximum in summer and minimum in winter. A low cloud base tends to occur frequently (>70%) over the TP, PRD and SCB. In contrast, at most sites over the Yangtze River Delta (YRD) and the NCP, about half the cloud belongs to the high-cloud category. The CBH does not exhibit marked diurnal variation in summer, throughout all CRN sites, probably due to the persistent cloud coverage caused by the East Asia Summer Monsson. To the best of our knowledge, this is the first CBH climatology produced from sounding measurements in China, and provides a useful reference for obtaining observational cloud base information.
The thermal forcing of the Tibetan Plateau (TP) during boreal spring, which involves surface sensible heating, latent heating released by convection and radiation flux heat, is critical for the seasonal and subseasonal variation of the East Asian summer monsoon. Distinct from the situation in March and April when the TP thermal forcing is modulated by the sea surface temperature anomaly (SSTA) in the North Atlantic, the present study shows that it is altered mainly by the SSTA in the Indian Ocean Basin Mode (IOBM) in May, according to in-situ observations over the TP and MERRA reanalysis data. In the positive phase of the IOBM, a local Hadley circulation is enhanced, with its ascending branch over the southwestern Indian Ocean and a descending one over the southeastern TP, leading to suppressed precipitation and weaker latent heat over the eastern TP. Meanwhile, stronger westerly flow and surface sensible heating emerges over much of the TP, along with slight variations in local net radiation flux due to cancellation between its components. The opposite trends occur in the negative phase of the IOBM. Moreover, the main associated physical processes can be validated by a series of sensitivity experiments based on an atmospheric general circulation model, FAMIL. Therefore, rather than influenced by the remote SSTAs of the northern Atlantic in the early spring, the thermal forcing of the TP is altered by the Indian Ocean SSTA in the late spring on an interannual timescale.