Ascribing potential causes of recent trends in free atmosphere temperatures

We use globally gridded radiosonde temperature datasets in a simple climate change study. Two climate models, when run with historical and, particularly, anthropogenic forcings, exhibit a degree of agreement with radiosonde temperature observations for 1958–1998.     

Optimal detection and attribution of climate change: sensitivity of results to climate model differences

Fingerprint techniques for the detection of anthropogenic climate change aim to distinguish the climate response to anthropogenic forcing from responses to other external influences and from internal climate variability. All these responses and the characteristics of internal variability are typically estimated from climate model data. We evaluate the sensitivity of detection and attribution results to the use of response and variability estimates from two different coupled ocean atmosphere general circulation models (HadCM2, developed at the Hadley Centre, and ECHAM3/LSG from the MPI für Meteorologie and Deutsches Klimarechenzentrum). The models differ in their response to greenhouse gas and direct sulfate aerosol forcing and also in the structure of their internal variability. This leads to differences in the estimated amplitude and the significance level of anthropogenic signals in observed 50-year summer (June, July, August) surface temperature trends. While the detection of anthropogenic influence on climate is robust to intermodel differences, our ability to discriminate between the greenhouse gas and the sulfate aerosol signals is not. An analysis of the recent warming, and the warming that occurred in the first half of the twentieth century, suggests that simulations forced with combined changes in natural (solar and volcanic) and anthropogenic (greenhouse gas and sulfate aerosol) forcings agree best with the observations.     

Comparison of free atmosphere temperature series from radiosonde and satellite data

The series ofair temperature anomalies inthe free atmosphere from radiosonde and satellite data are compared. Along with the well-known datasets of leading foreign centers, the datasets are considered of monthly temperature anomalies for isobaric surfaces and tropospheric and lower tropospheric layers obtained in the All-Russian Research Institute of Hydrometeoroiogical Information-World Data Center (RIHMI-WDC) from the data of the global network of radiosonde observations. Following numerous literature sources, the study corroborates that it is impossible to detect the so called tropospheric amplification of warming in observational data. The results of the comparison of statistical parameters for different series of air temperature anomalies prove that the RIHMI-WDC dataset is appropriate for solving the problems of climate monitoring on the assessment of air temperature in the free atmosphere. A doubtless advantage of these datasets for the preparation of the data of monitoring and diagnosis of the current climate is that their operational update is possible by processing new monthly portions of radiosonde data for the global network. The other advantage is that they do not depend on the modes of series update in the foreign sources.     

Avoiding Circular Logic in Climate Modeling

The current debate on climate change and its policy implications often hinges on the credibility of global climate models. In considering this topic, we point out the danger of circular logic if climate model inputs (specifically, climate forcings) are determined from the same temperature record against which climate model outputs are tested. We suggest specific guidelines for avoiding this danger.     

Vertical structure of recent arctic warming from observed data and reanalysis products

Spatiotemporal patterns of recent (1979–2008) air temperature trends are evaluated using three reanalysis datasets and radiosonde data. Our analysis demonstrates large discrepancies between the reanalysis datasets, possibly due to differences in the data assimilation procedures as well as sparseness and inhomogeneity of high-latitude observations. We test the robustness of arctic tropospheric warming based on the ERA-40 dataset. ERA-40 Arctic atmosphere temperatures tend to be closer to the observed ones in terms of root mean square error compared to other reanalysis products used in the article. However, changes in the ERA-40 data assimilation procedure produce unphysical jumps in atmospheric temperatures, which may be the likely reason for the elevated tropospheric warming trend in 1979–2002. NCEP/NCAR Reanalysis data show that the near-surface upward temperature trend over the same period is greater than the tropospheric trend, which is consistent with direct radiosonde observations and inconsistent with ERA-40 results. A change of sign in the winter temperature trend from negative to positive in the late 1980s is documented in the upper troposphere/lower stratosphere with a maximum over the Canadian Arctic, based on radiosonde data. This change from cooling to warming tendency is associated with weakening of the stratospheric polar vortex and shift of its center toward the Siberian coast and possibly can be explained by the changes in the dynamics of the Arctic Oscillation. This temporal pattern is consistent with multi-decadal variations of key arctic climate parameters like, for example, surface air temperature and oceanic freshwater content. Elucidating the mechanisms behind these changes will be critical to understanding the complex nature of high-latitude variability and its impact on global climate change.     

Signal analysis of the atmospheric mean 500/1000 hPa temperature north of 55°N between 1949 and 1994

 The lower tropospheric mean temperature 500/1000 hPa is examined in the Northern Hemisphere high-latitude region north of 55°N with regard to a climate change signal due to anthropogenic climate forcing as a supplement to previous studies which concentrated on near surface temperatures. An observational data set of the German Weather Service is compared with several model simulations including different scenarios of greenhouse gas and sulfate aerosol forcing derived from the two recent versions of the coupled climate model in Hamburg, ECHAM-3/LSG and ECHAM-4/OPYC. The signal analysis is based on the optimal fingerprint method, which supplies a detection variable with optimal signal-to-noise ratio. The natural variability measures are derived from the corresponding long-term control experiments. From 1970 onward, we find high trend pattern analogies between the observational data and the greenhouse-gas induced model simulations. The fingerprint of this common temperature signal consists of a predominate warming with maximum over Siberia and a weak cooling over the North Atlantic reaching an estimated significance level of about 1%. A non-optimized approach has also been examined, leading to even closer trend pattern correlations. The additional forcing by sulfate aerosols decreases the correlation of this climate change simulation with the observations. The natural variability constitutes about 50% of the conforming trend patterns. The signal-to-noise ratio is best over the oceans while the tropospheric temperatures over the land masses are contaminated by strong noise. The trend pattern correlations look the same for both model versions and several ensemble members with different noise realizations. Received: 4 January 1999 / Accepted: 11 April 2001     

Climatic effects of air pollutants over china: A review

Tropospheric ozone(O3) and aerosols are major air pollutants in the atmosphere. They have also made significant contributions to radiative forcing of climate since preindustrial times. With its rapid economic development, concentrations of air pollutants are relatively high in China; hence, quantifying the role of air pollutants in China in regional climate change is especially important. This review summarizes existing knowledge with regard to impacts of air pollutants on climate change in China and defines critical gaps needed to reduce the associated uncertainties. Measured monthly, seasonal, and annual mean surface-layer concentrations of O3 and aerosols over China are compiled in this work, with the aim to show the magnitude of concentrations of O3 and aerosols over China and to provide datasets for evaluation of model results in future studies. Ground-based and satellite measurements of O3 column burden and aerosol optical properties, as well as model estimates of radiative forcing by tropospheric O3 and aerosols are summarized. We also review regional and global modeling studies that have investigated climate change driven by tropospheric O3and/or aerosols in China; the predicted sign and magnitude of the responses in temperature and precipitation to O3/aerosol forcings are presented. Based on this review, key priorities for future research on the climatic effects of air pollutants in China are highlighted.     

Anthropogenic and natural causes of climate change

We test for causality between radiative forcing and temperature using multivariate time series models and Granger causality tests that are robust to the non-stationary (trending) nature of global climate data. We find that both natural and anthropogenic forcings cause temperature change and also that temperature causes greenhouse gas concentration changes. Although the effects of greenhouse gases and volcanic forcing are robust across model specifications, we cannot detect any effect of black carbon on temperature, the effect of changes in solar irradiance is weak, and the effect of anthropogenic sulfate aerosols may be only around half that usually attributed to them.     

Projecting future drought in Mediterranean forests: bias correction of climate models matters!

Global and regional climate models (GCM and RCM) are generally biased and cannot be used as forcing variables in ecological impact models without some form of prior bias correction. In this study, we investigated the influence of the bias correction method on drought projections in Mediterranean forests in southern France for the end of the twenty-first century (2071–2100). We used a water balance model with two different atmospheric climate forcings built from the same RCM simulations but using two different correction methods (quantile mapping or anomaly method). Drought, defined here as periods when vegetation functioning is affected by water deficit, was described in terms of intensity, duration and timing. Our results showed that the choice of the bias correction method had little effects on temperature and global radiation projections. However, although both methods led to similar predictions of precipitation amount, they induced strong differences in their temporal distribution, especially during summer. These differences were amplified when the climatic data were used to force the water balance model. On average, the choice of bias correction leads to 45 % uncertainty in the predicted anomalies in drought intensity along with discrepancies in the spatial pattern of the predicted changes and changes in the year-to-year variability in drought characteristics. We conclude that the choice of a bias correction method might have a significant impact on the projections of forest response to climate change.     

Importance of instantaneous radiative forcing for rapid tropospheric adjustment

To better understand CFMIP/CMIP inter-model differences in rapid low cloud responses to CO₂ increases and their associated effective radiative forcings, we examined the tropospheric adjustment of the lower tropospheric stability (LTS) in three general circulation models (GCMs): HadGEM2-A, MIROC3.2 medres, and MIROC5. MIROC3.2 medres showed a reduction in LTS over the sub-tropical ocean, in contrast to the other two models. This reduction was consistent with a temperature decrease in the mid-troposphere. The temperature decrease was mainly driven by instantaneous radiative forcing (RF) caused by an increase in CO₂. Reductions in radiative and latent heating, due to clouds, and in adiabatic and advective heating, also contribute to the temperature decrease. The instantaneous RF in the mid-troposphere in MIROC3.2 medres is inconsistent with the results of line-by-line (LBL) calculations, and thus it is considered questionable. These results illustrate the importance of evaluating the vertical profile of instantaneous RF with LBL calculations; improved future model performance in this regard should help to increase our confidence in the tropospheric adjustment in GCMs.     

Responses of Mean and Extreme Precipitation to Different Climate Forcing Under Radiative-Convective Equilibrium

Understanding the responses of mean and extreme precipitation to climate change is of great importance.Previous studies have mainly focused on the responses to prescribed sea surface warming or warming due to increases of CO2.This study uses a cloud-resolving model under the idealization of radiative-convective equilibrium to examine the responses of mean and extreme precipitation to a variety of climate forcings,including changes in prescribed sea surface temperature,CO2,solar insolation,surface albedo,stratospheric volcanic aerosols,and several tropospheric aerosols.The different responses of mean precipitation are understood by examining the changes in the surface energy budget.It is found that the cancellation between shortwave scattering and longwave radiation leads to a small dependence of the mean precipitation response on forcings.The responses of extreme precipitation are decomposed into three components(thermodynamic,dynamic,and precipitation efficiency).The thermodynamic components for all climate forcings are similar.The dynamic components and the precipitation-efficiency components,which have large spreads among the cases,are negatively correlated,leading to a small dependence of the extreme precipitation response on the forcings.     

对流层增暖热带放大现象：基于FGOALS-g3的模拟研究

热带地区的湿绝热过程会放大地表的增暖幅度,在约200 hPa高度上产生增暖峰值,该现象被称为“热带对流层放大”。热带对流层放大是气候变化的显著特征之一,是检验气候模式性能的重要指标。本文基于RSS4.0卫星数据和ERA5.1再分析资料,系统分析了FGOALS-g3模式对气温变化特别是热带对流层放大的模拟能力,并通过新旧版本模式（FGOALS-g3与FGOALS-g2）的比较指出了新版本模式模拟技巧的提升;通过比较FGOALS-g3历史模拟试验与GAMIL3单独大气模式AMIP试验结果,研究了海气耦合过程对模拟结果的影响。结果表明,FGOALS-g3能够合理再现观测中的全球对流层显著增温趋势,但模拟的增温趋势偏强,这与气候系统内部变率以及两代气候系统模式所使用的历史气候外强迫差异有关。其对于观测中热带平均增温廓线以及热带对流层放大的空间分布均表现出良好的模拟性能,模拟的热带对流层放大现象的量值大小存在正偏差,与模拟的对流层低层温度变化偏强有关。FGOALS-g3较FGOALS-g2在性能上有一定提升,主要表现为增加了对于火山气溶胶强迫的响应,并在热带对流层放大的空间分布及平均气温趋势廓线...     

Decadal prediction skill in a multi-model ensemble

Decadal climate predictions may have skill due to predictable components in boundary conditions (mainly greenhouse gas concentrations but also tropospheric and stratospheric aerosol distributions) and initial conditions (mainly the ocean state). We investigate the skill of temperature and precipitation hindcasts from a multi-model ensemble of four climate forecast systems based on coupled ocean-atmosphere models. Regional variations in skill with and without trend are compared with similarly analysed uninitialised experiments to separate the trend due to monotonically increasing forcings from fluctuations around the trend due to the ocean initial state and aerosol forcings. In temperature most of the skill in both multi-model ensembles comes from the externally forced trends. The rise of the global mean temperature is represented well in the initialised hindcasts, but variations around the trend show little skill beyond the first year due to the absence of volcanic aerosols in the hindcasts and the unpredictability of ENSO. The models have non-trivial skill in hindcasts of North Atlantic sea surface temperature beyond the trend. This skill is highest in the northern North Atlantic in initialised experiments and in the subtropical North Atlantic in uninitialised simulations. A similar result is found in the Pacific Ocean, although the signal is less clear. The uninitialised simulations have good skill beyond the trend in the western North Pacific. The initialised experiments show some skill in the decadal ENSO region in the eastern Pacific, in agreement with previous studies. However, the results in this study are not statistically significant (p?≈?0.1) by themselves. The initialised models also show some skill in forecasting 4-year mean Sahel rainfall at lead times of 1 and 5?years, in agreement with the observed teleconnection from the Atlantic Ocean. Again, the skill is not statistically significant (p?≈?0.2). Furthermore, uninitialised simulations that include volcanic aerosols have similar skill. It is therefore still an open question whether initialisation improves predictions of Sahel rainfall. We conclude that the main source of skill in forecasting temperature is the trend forced by rising greenhouse gas concentrations. The ocean initial state contributes to skill in some regions, but variations in boundary forcings such as aerosols are as important in decadal forecasting.     

The CLIVAR C20C project: selected twentieth century climate events

We use a simple methodology to test whether a set of atmospheric climate models with prescribed radiative forcings and ocean surface conditions can reproduce twentieth century climate variability. Globally, rapid land surface warming since the 1970s is reproduced by some models but others warm too slowly. In the tropics, air-sea coupling allows models to reproduce the Southern Oscillation but its strength varies between models. We find a strong relationship between the Southern Oscillation in global temperature and the rate of global warming, which could in principle be used to identify models with realistic climate sensitivity. This relationship and a weak response to ENSO suggests weak sensitivity to changes in sea surface temperature in some of the models used here. In the tropics, most models reproduce part of the observed Sahel drought. In the extratropics, models do not reproduce the observed increase in the North Atlantic Oscillation in response to forcings, through internal variability, or as a combination of both.     

The impact of natural and anthropogenic forcings on climate and hydrology since 1550

A climate simulation of an ocean/atmosphere general circulation model driven with natural forcings alone (constant “pre-industrial” land-cover and well-mixed greenhouse gases, changing orbital, solar and volcanic forcing) has been carried out from 1492 to 2000. Another simulation driven with natural and anthropogenic forcings (changes in greenhouse gases, ozone, the direct and first indirect effect of anthropogenic sulphate aerosol and land-cover) from 1750 to 2000 has also been carried out. These simulations suggest that since 1550, in the absence of anthropogenic forcings, climate would have warmed by about 0.1 K. Simulated response is not in equilibrium with the external forcings suggesting that both climate sensitivity and the rate at which the ocean takes up heat determine the magnitude of the response to forcings since 1550. In the simulation with natural forcings climate sensitivity is similar to other simulations of HadCM3 driven with CO₂ alone. Climate sensitivity increases when anthropogenic forcings are included. The natural forcing used in our experiment increases decadal–centennial time-scale and large spatial scale climate variability, relative to internal variability, as diagnosed from a control simulation. Mean conditions in the natural simulation are cooler than in our control simulation reflecting the reduction in forcing. However, over certain regions there is significant warming, relative to control, due to an increase in forest cover. Comparing the simulation driven by anthropogenic and natural forcings with the natural-only simulation suggests that anthropogenic forcings have had a significant impact on, particularly tropical, climate since the early nineteenth century. Thus the entire instrumental temperature record may be “contaminated” by anthropogenic influences. Both the hydrological cycle and cryosphere are also affected by anthropogenic forcings. Changes in tree-cover appear to be responsible for some of the local and hydrological changes as well as an increase in northern hemisphere spring snow cover.

---

CLIMBER-2: a climate system model of intermediate complexity. Part II: model sensitivity

 A set of sensitivity experiments with the climate system model of intermediate complexity CLIMBER-2 was performed to compare its sensitivity to changes in different types of forcings and boundary conditions with the results of comprehensive models (GCMs). We investigated the climate system response to changes in freshwater flux into the Northern Atlantic, CO₂ concentration, solar insolation, and vegetation cover in the boreal zone and in the tropics. All these experiments were compared with the results of corresponding experiments performed with different GCMs. Qualitative, and in many respects, quantitative agreement between the results of CLIMBER-2 and GCMs demonstrate the ability of our climate system model of intermediate complexity to address diverse aspects of the climate change problem. In addition, we used our model for a series of experiments to assess the impact of some climate feedbacks and uncertainties in model parameters on the model sensitivity to different forcings. We studied the role of freshwater feedback and vertical ocean diffusivity for the stability properties of the thermohaline ocean circulation. We show that freshwater feedback plays a minor role, while changes of vertical diffusivity in the ocean considerably affect the circulation stability. In global warming experiments we analysed the impact of hydrological sensitivity and vertical diffusivity on the long-term evolution of the thermohaline circulation. In the boreal and tropical deforestation experiments we assessed the role of an interactive ocean and showed that for both types of deforestation scenarios, an interactive ocean leads to an additional cooling due to albedo and water vapour feedbacks. Received: 28 May 2000 / Accepted: 9 November 2000     

往返式探空观测资料的质量控制及不确定性分析

为了推动新型探测资料在数值预报模式中的应用,本文进行了往返式探空资料同化应用前重要的基础性研究工作。基于国内首次往返式探空观测资料,首先建立了面向业务化应用的往返式探空资料质量控制方案,通过对比和分析质量控制前后观测样本的统计特征,论证了质量控制方案的合理性,质量控制后探测要素抽样分布更为合理,要素间一致性得到提高。进而以数值天气预报高时间分辨率的模式预报场和同站址业务常规探空观测资料为参考,分析质量控制后资料的不确定性,结果表明往返探空探测精度达到了世界气象组织WMO（World Meteorological Center）规定的突破目标,部分探测要素甚至实现了理想目标,探测资料具有可用性。最后结合数值模式背景场探讨往返探空资料的可同化性,研究表明往返探空的风场观测和夜间温度观测满足变分同化系统的高斯、无偏假定,可直接同化;气压、湿度和日间温度观测在资料同化前需要开展偏差订正工作,从而更有效的发挥资料价值。本文的研究工作为今后往返探空资料在模式中的同化应用奠定了基础。     

CMIP6检测归因模式比较计划（DAMIP）概况与评述

气候变化的检测归因是历次IPCC评估报告的重要组成部分。检测归因的目标是检测并量化由外强迫引起的变化,识别人为和自然强迫对气候变化的相对贡献。有助于全面评估气候系统是如何受人类活动影响的,所得结论对未来气候变化预估的信度而言至关重要。检测归因模式比较计划(DAMIP)是第六次国际耦合模式比较计划(CMIP6)的一个子计划,共包含3个级别、多达14组不同强迫驱动下的试验。文中概述其科学背景、试验设计、参与模式情况,并评述该计划的意义、期待的产出以及中国的机遇和贡献,以期使读者迅速了解相关要点和进展,为利用这些模式模拟试验数据开展检测归因研究提供必要的参考。     

近60年中国探空观测气温变化趋势及不确定性研究

基于118站探空资料研究了近60年中国850—100 hPa气温变化趋势及季节和区域特征,并通过与1979—2017年卫星微波气温的对比研究了中国探空气温均一化的不确定性。研究表明,1958—2017年中国平均对流层气温呈上升趋势,300 hPa升温最为显著,平流层下层（100 hPa）为降温趋势。冬季对流层上层升温趋势和夏季平流层下层降温趋势较强。1979—2017年较整个时段对流层升温趋势较强,平流层下层降温趋势较弱。青藏高原和西北地区对流层上层升温趋势较强。通过与卫星微波气温和邻近探空站探空气温的对比以及均一化前后日夜气温差值检测出中国探空均一化气温仍残存非均一性问题。由于参照序列的局限性,均一化未能完全去除21世纪最初10年中国探空系统变化造成的对流层中、上层至平流层下层气温系统性下降的影响,导致中国对流层上层升温趋势被低估和平流层下层降温趋势被高估。未来可通过参考卫星微波气温和邻近探空站序列调整非均一性订正顺序并增加合理性检验等方法改进中国探空气温均一化方案。      

Natural and anthropogenic climate change: incorporating historical land cover change,vegetation dynamics and the global carbon cycle

This study explores natural and anthropogenic influences on the climate system, with an emphasis on the biogeophysical and biogeochemical effects of historical land cover change. The biogeophysical effect of land cover change is first subjected to a detailed sensitivity analysis in the context of the UVic Earth System Climate Model, a global climate model of intermediate complexity. Results show a global cooling in the range of –0.06 to –0.22 °C, though this effect is not found to be detectable in observed temperature trends. We then include the effects of natural forcings (volcanic aerosols, solar insolation variability and orbital changes) and other anthropogenic forcings (greenhouse gases and sulfate aerosols). Transient model runs from the year 1700 to 2000 are presented for each forcing individually as well as for combinations of forcings. We find that the UVic Model reproduces well the global temperature data when all forcings are included. These transient experiments are repeated using a dynamic vegetation model coupled interactively to the UVic Model. We find that dynamic vegetation acts as a positive feedback in the climate system for both the all-forcings and land cover change only model runs. Finally, the biogeochemical effect of land cover change is explored using a dynamically coupled inorganic ocean and terrestrial carbon cycle model. The carbon emissions from land cover change are found to enhance global temperatures by an amount that exceeds the biogeophysical cooling. The net effect of historical land cover change over this period is to increase global temperature by 0.15 °C.