Comets and climate

No connection between comets and climate has been proposed until now; here, we show that such a connection exists. We use a model to evaluate the shadowing effect due to cometary dust released by comet 1P/Halley in the inner solar system. We find that comet Halley has left a detectable fingerprint in the climate records of the last two millennia. The print shows up as a periodic cooling of the order of 0.08 °C. This temperature drop is comparable with other natural fluctuations. The finding will add a brick to our knowledge of the climate system and could allow to improve our predictive capacity of future climate.     

Simulations of LGM climate of East Asia by regional climate model

ClimateconditionsintheLastGlacialMaximum(LGM)wereremarkablydifferentfromthepresentones.LGMglobalmeantemperaturewas5℃-10℃dropbutprecipitationdecreasescommonly.LGMhasbecomethekeyphasetoreconstructtheearthenvironmentalfield,retrieveextremecoldclimatecondit…     

Homogenization of climate series:The basis for assessing climate changes

Long-term meteorological observation series are fundamental for reflecting climate changes.However,almost all meteorological stations inevitably undergo relocation or changes in observation instruments,rules,and methods,which can result in systematic biases in the observation series for corresponding periods.Homogenization is a technique for adjusting these biases in order to assess the true trends in the time series.In recent years,homogenization has shifted its focus from the adjustments to climate mean status to the adjustments to information about climate extremes or extreme weather.Using case analyses of ideal and actual climate series,here we demonstrate the basic idea of homogenization,introduce new understanding obtained from recent studies of homogenization of climate series in China,and raise issues for further studies in this field,especially with regards to climate extremes,uncertainty of the statistical adjustments,and biased physical relationships among different climate variables due to adjustments in single variable series.     

Using raw regional climate model outputs for quantifying climate change impacts on hydrology

General circulation model outputs are rarely used directly for quantifying climate change impacts on hydrology, due to their coarse resolution and inherent bias. Bias correction methods are usually applied to correct the statistical deviations of climate model outputs from the observed data. However, the use of bias correction methods for impact studies is often disputable, due to the lack of physical basis and the bias nonstationarity of climate model outputs. With the improvement in model resolution and reliability, it is now possible to investigate the direct use of regional climate model (RCM) outputs for impact studies. This study proposes an approach to use RCM simulations directly for quantifying the hydrological impacts of climate change over North America. With this method, a hydrological model (HSAMI) is specifically calibrated using the RCM simulations at the recent past period. The change in hydrological regimes for a future period (2041–2065) over the reference (1971–1995), simulated using bias‐corrected and nonbias‐corrected simulations, is compared using mean flow, spring high flow, and summer–autumn low flow as indicators. Three RCMs driven by three different general circulation models are used to investigate the uncertainty of hydrological simulations associated with the choice of a bias‐corrected or nonbias‐corrected RCM simulation. The results indicate that the uncertainty envelope is generally watershed and indicator dependent. It is difficult to draw a firm conclusion about whether one method is better than the other. In other words, the bias correction method could bring further uncertainty to future hydrological simulations, in addition to uncertainty related to the choice of a bias correction method. This implies that the nonbias‐corrected results should be provided to end users along with the bias‐corrected ones, along with a detailed explanation of the bias correction procedure. This information would be especially helpful to assist end users in making the most informed decisions.     

Land use effects on climate in China as simulated by a regional climate model

A regional climate model (RegCM3) nested within ERA40 re-analyzed data is used to investigate the climate effects of land use change over China. Two 15-year simulations (1987―2001), one with current land use and the other with potential vegetation cover without human intervention, are conducted for a domain encompassing China. The climate impacts of land use change are assessed from the difference between the two simulations. Results show that the current land use (modified by anthropogenic ac- tivities) influences local climate as simulated by the model through the reinforcement of the monsoon circulation in both the winter and summer seasons and through changes of the surface energy budget. In winter, land use change leads to reduced precipitation and decreased surface air temperature south of the Yangtze River, and increased precipitation north of the Yangtze River. Land use change signifi- cantly affects summer climate in southern China, yielding increased precipitation over the region, de- creased temperature along the Yangtze River and increased temperature in the South China area (south-end of China). In summer, a reduction of precipitation over northern China and a temperature rise over Northwest China are also simulated. Both daily maximum and minimum temperatures are affected in the simulations. In general, the current land use in China leads to enhanced mean annual precipitation and decreased annual temperature over south China along with decreased precipitation over North China.     

Space-time precipitation reflecting climate change

Abstract

A methodology has been developed and applied to an eastern Nebraska, USA, case study to estimate the space-time distribution of daily precipitation under climate change. The approach is based on the analysis both of the type and of the Markov properties of atmospheric circulation patterns (CPs), and a stochastic linkage between daily (here 500 hPa) CP types and daily precipitation events. Historical data and General Circulation Model (GCM) output of daily CPs corresponding to 1 × CO₂ and 2 × CO₂ are considered. Time series of both local and regional precipitation corresponding to each of those cases were simulated and their statistical properties were compared. Under the dry continental climate of eastern Nebraska, a highly variable spatial response to climate change was obtained. Most of the local and the regional average precipitation values reflect, under 2 × CO₂, a somewhat wetter and a more variable precipitation regime in eastern Nebraska. The sensitivity of the results to the GCM utilized should be considered.     

The value of climate forecasting

A short survey is given of the concepts associated with meteorological forecast verification and value. Apart from matters of mathematical detail the field has not advanced greatly over the last thirty years. If significant skill develops in long-range (i.e. climate) forecasting, it will be more than ever necessary for the general user to understand the possible consequences—in particular that there can be many circumstances where some forecast skill is worse than none at all. Some highly idealized agricultural examples are used to illustrate the point. It is emphasized that some numerical measure of confidence will have to be associated with (or be built into) probability precasts of climate.     

Spectral analysis of climate data

The complexity of climate variability on all time scales requires the use of several refined tools to unravel its primary dynamics from observations. Indeed, ideas from the theory of dynamical systems have provided new ways of interpreting the information contained in climatic time series.We review the properties of several modern time series analysis methods. Those methods belong to four main classes: Fourier techniques (Blackman-Tukey and Multi-Taper), Maximum Entropy technique, Singular-spectrum techniques and wavelet analysis. Their respective advantages and limitations are illustrated by numerical experiments on synthetic time series. As climate data can be irregularly spaced in time, we also compare three interpolating methods on those time series. Those tests are aimed at showing the pitfalls of the blind use of mathematical or statistical techniques on climate data.We apply those methods to real climatic data from temperature variations over the last century, and the Vostok ice core deuterium record over the last glacial cycle. Then we show how interpretations on the dynamics of climate can be derived on those time scales.     

Plant phenology and climate change

<正>Plant phenology is regarded as an important natural indicator of climate change because plants are finely tuned to the seasonality of their climate.In response to the impacts of climate change,the observed shifting of phenophases at multiple scales since the 20th century,ranging from individual plants to whole ecosystems,is consistent with cli-     

Fluctuations in some climate parameters

There is argument as to the extent to which there has been an increase over the past few decades in the frequency of the extremes of climatic parameters, such as temperature, storminess, precipitation, etc, an obvious point being that Global Warming might be responsible. Here we report results on those parameters of which we have had experience during the last few years: Global surface temperature, Cloud Cover and the MODIS Liquid Cloud Fraction. In no case we have found indications that fluctuations of these parameters have increased with time.     

Assessing the effect of climate natural variability in water resources evaluation impacted by climate change

Water resource assessment on climate change is crucial in water resource planning and management. This issue is becoming more urgent with climate change intensifying. In the current research of climate change impact, climate natural variability (fluctuation) has seldom been studied separately. Many studies keep attributing all changes (e.g. runoff) to climate change, which may lead to wrong understanding of climate change impact assessment. Because of lack of long enough historical series, impacts of climate variability have been always avoided deliberately. Based on Latin hypercube sampling technique, a block sampling approach was proposed for climate variability simulation in this study. The widely used time horizon (1961–1991) was defined as baseline period, and the runoff variation probability affected by climate natural variability was analysed. Allowing for seven future climate projections in total of three GCMs (CSIRO, NCAR, and MPI) and three emission scenarios (A1B, A2, and B1), the impact of future climate change on water resources was estimated in terms of separating the contribution from climate natural variability. Based on the analysis of baseline period, for the future period from 2021 to 2051, the impact of climate natural variability may play a major part, whereas for the period from 2061 to 2091, climate change attributed to greenhouse gases may dominate the changing process. The results show that changes from climate variability possess a comparable magnitude, which highlights the importance to separate impacts of climate variability in assessing climate change, instead of attributing all changes to climate change solely. Copyright © 2012 John Wiley & Sons, Ltd.     

Design and testing of a global climate prediction system based on a coupled climate model

A global climate prediction system(PCCSM4) was developed based on the Community Climate System Model, version 4.0, developed by the National Center for Atmospheric Research(NCAR), and an initialization scheme was designed by our group. Thirty-year(1981–2010) one-month-lead retrospective summer climate ensemble predictions were carried out and analyzed. The results showed that PCCSM4 can efficiently capture the main characteristics of JJA mean sea surface temperature(SST), sea level pressure(SLP), and precipitation. The prediction skill for SST is high, especially over the central and eastern Pacific where the influence of El Ni?o-Southern Oscillation(ENSO) is dominant. Temporal correlation coefficients between the predicted Ni?o3.4 index and observed Ni?o3.4 index over the 30 years reach 0.7, exceeding the 99% statistical significance level. The prediction of 500-hPa geopotential height, 850-hPa zonal wind and SLP shows greater skill than for precipitation. Overall, the predictability in PCCSM4 is much higher in the tropics than in global terms, or over East Asia. Furthermore, PCCSM4 can simulate the summer climate in typical ENSO years and the interannual variability of the Asian summer monsoon well. These preliminary results suggest that PCCSM4 can be applied to real-time prediction after further testing and improvement.     

Martian oceans, valleys and climate

The new Mars Global Surveyor altimetry shows that the heavily cratered southern hemisphere of Mars is 5 km higher than the sparely cratered plains of the northern hemisphere. Previous suggestions that oceans formerly occupied the northern plains as evidenced by shorelines are partly supported by the new data. A previously identified outer boundary has a wide range of elevations and is unlikely to be a shoreline but an inner contact with a narrow range of elevations is a more likely candidate. No shorelines are visible in the newly acquired, 1.5 metre/pixel imaging. Newly imaged valleys provide strong support for sustained or episodic flow of water across the Martian surface. A major surprise, however, is the near absence of valleys less than 100 m across. Martian valleys seemingly do not divide into ever smaller valleys as terrestrial valleys commonly do. This could be due to lack of precipitation or lack of surface runoff because of high infiltration rates. High erosion rates and formation of valley networks supports warm climates and presence of large bodies of water during heavy bombardment. The climate history and fate of the water after heavy bombardment remain controversial.     

Effect of climate changes on groundwater

Predictive estimates of anticipated changes in groundwater resources in the territory of Russia as applied to global climate warming by 1, 2, and 3–4°C at different scenarios of changes in the regional distribution of atmospheric precipitation are given. Potential environmental and socio-economic consequences of changes in hydrogeological conditions are considered.