Interannual Surface Temperature Variability Research Articles

An assessment of potential climate impact during 1948–2010 using historical land use land cover change maps

AbstractEarlier studies of land use land cover change (LULCC) normally used only a specified LULCC map with no interannual variations. In this study, using an Atmospheric General Circulation Model (AGCM) coupled with a land surface model, biophysical impacts of LULCC on global and regional climate are investigated by using a LULCC map which covers 63 years from 1948 to 2010 with interannual variation. A methodology has been developed to convert a recently developed LULCC fraction map with 1° × 1° resolution to the AGCM grid points in which only one dominant type is allowed. Comprehensive evaluations are conducted to ensure consistency of the trend of the original LULCC fraction change and the trend of the fraction of grid point changes over different regions. The model was integrated with a potential vegetation map (CTL) and the map with LULCC, in which a set of surface parameters such as leaf area index, albedo and other soil and vegetation parameters were accordingly changed with interannual variation. The results indicate that the interannual LULCC map simulation is able to reproduce better interannual variability of surface temperature and rainfall when compared to the control simulation. LULCC causes negative effect on global precipitation, with the strongest significant signals over degraded regions such as East Asia, West Africa and South America, and some of these changes are consistent with observed regional anomalies for certain time periods. LULCC causes reduction in net radiation and evapotranspiration which leads to changes in monsoon circulation and variation in magnitude and pattern of moisture flux convergence and subsequent reduction in precipitation. Meanwhile, LULCC enhances surface warming during the summer in the LULCC regions due to greatly reduced evapotranspiration. In contradiction to the surface, upper troposphere temperatures are cool because of less latent heat released into the upper troposphere, which leads to weaker circulation in LULCC regions.

RegCM4 simulation with AVHRR land use data towards temperature and precipitation climatology over Indian region

The Regional Climate Modeling system (RegCM) is being widely used for climate simulation at seasonal to multi-decadal scales over many regions across the world in recent decades. In this study, we conducted a 10 years simulation using RegCM4 by replacing the United States Geological Survey (USGS) land use data (the default land use data in RegCM) with the land use data from Advanced Very High Resolution Radiometer (AVHRR) satellite images to test the usefulness of AVHRR land use data in RegCM. We focused on the 10 years (1991–2000) of temperature and precipitation climatologies over Indian region from the model with AVHRR land use data and that of with USGS land use data. The results are compared with Climate Research Unit (CRU) observation through the model biases, standard error, the temporal and spatial correlation between the model and observation in two results (USGS vs. AVHRR). Results indicate that the annual and seasonal climatology of surface temperature and precipitation in both simulations (i.e. with USGS and AVHRR) are close to each other over Indian region. However, the simulation with AVHRR land use data improved up to ~2 °C in temperature field and ~1 mm/d in precipitation field over few regions. The inter-annual variability of surface temperature and precipitation in both simulations are also found almost same. Based on the results of this study, we conclude that the AVHRR land use data can be used in RegCM to conduct regional climate simulations over Indian region. Additionally this study suggests that, as AVHRR dataset is available for longer period in 15 days interval, so the impact of land use change on different climatic variables during a period can be studied by using RegCM.

Emergent Constraints in Climate Projections: A Case Study of Changes in High-Latitude Temperature Variability

Abstract Climate projections from phase 5 of the Coupled Model Intercomparison Project (CMIP5) ensemble show a decrease in interannual surface temperature variability over high latitudes with a large intermodel spread, in particular over the areas of sea ice retreat. Here relationships are found between the models’ present-day performance in sea ice–related metrics and future changes in temperature variability. These relations, so-called emergent constraints, can produce ensembles of models calibrated with present-day observations with a narrower spread across their members than across the full ensemble. The underlying assumption is that models in better agreement with observations or reanalyses in a carefully selected metric probably have a more realistic representation of local processes, and therefore are more reliable for projections. Thus, the reliability of this method depends on the availability of high-quality observations or reanalyses. This work represents a step toward formalization of the emergent constraints framework, as so far there is no consensus on how the constraints should be best implemented. The authors quantify the reduction in spread from emerging constraints for various metrics and their combinations, different emission scenarios, and seasons. Some of the general features of emerging constraints are discussed, and how to effectively aggregate information across metrics and seasons to achieve the largest reduction in model spread. It is demonstrated, based on the case of temperature variability, that a robust constraint can be obtained by combining relevant metrics across all seasons. Such a constraint results in a strongly reduced spread across model projections, which is consistent with a process understanding of variability changes due to sea ice retreat.

Influences of the interannual variability of vegetation LAI on surface temperature

AbstractThe influences of interannual variability of vegetation LAI on surface temperature are investigated via two ensemble simulations, applying the Community Earth System Model. The interannual LAI, derived from Global Inventory Modeling and Mapping Studies NDVI for the period 1982–2011, and its associated climatological LAI, are used in the two ensemble simulations, respectively. The results show that the signals of the influences, represented as ensemble-mean differences, are generally weaker than the noises of the atmospheric variability, represented as one standard deviation of the ensemble differences. Spatially, the signals are stronger over the tropics compared with the mid–high latitudes. Such stronger signals are contributed by the significant linearity between LAI and surface temperature, which is mainly caused via the influences of LAI on evapotranspiration. The maximum amplitudes of the influences on the interannual variability of surface temperature are high and thus deserve full considera...

Improved Representation of Tropical Pacific Ocean–Atmosphere Dynamics in an Intermediate Complexity Climate Model

Abstract A new anomaly coupling technique is introduced into a coarse-resolution dynamic climate model [the Liège Ocean Carbon Heteronomous model (LOCH)–Vegetation Continuous Description model (VECODE)–Earth System Models of Intermediate Complexity Climate deBilt (ECBILT)–Coupled Large-Scale Ice–Ocean model (CLIO)–Antarctic and Greenland Ice Sheet Model (AGISM) ensemble (LOVECLIM)], improving the model’s representation of eastern equatorial Pacific surface temperature variability. The anomaly coupling amplifies the surface diabatic atmospheric forcing within a Gaussian-shaped patch applied in the tropical Pacific Ocean. It is implemented with an improved predictive cloud scheme based on empirical relationships between cloud cover and key state variables. Results are presented from a perturbed physics ensemble systematically varying the parameters controlling the anomaly coupling patch size, location, and amplitude. The model’s optimal parameter combination is chosen through calibration against the observed power spectrum of monthly-mean surface temperature anomalies in the Niño-3 region. The calibrated model exhibits substantial improvement in equatorial Pacific interannual surface temperature variability and robustly reproduces El Niño–Southern Oscillation (ENSO)-like variability. The authors diagnose some of the key atmospheric and oceanic feedbacks in the model important for simulating ENSO-like variability, such as the positive Bjerknes feedback and the negative heat flux feedback, and analyze the recharge–discharge of the equatorial Pacific ocean heat content. They find LOVECLIM robustly captures important ocean dynamics related to thermocline adjustment and equatorial Kelvin waves. The calibrated model demonstrates some improvement in simulating atmospheric feedbacks, but the coupling between ocean and atmosphere is relatively weak. Because of the tractability of LOVECLIM and its consequent utility in exploring long-term climate variability and large ensemble perturbed physics experiments, improved representation of tropical Pacific ocean–atmosphere dynamics in the model may more readily allow for the investigation of the role of tropical Pacific ocean–atmosphere dynamics in past climate changes.

Vulnerability assessment of areas affected by Chinese cryospheric changes in future climate change scenarios

Using the definition of vulnerability provided by the Intergovernmental Panel on Climate Change, this paper assesses the vulnerability of areas affected by Chinese cryospheric changes from 2001 to 2020 and from 2001 to 2050 in A1 and B1scenarios. Seven indices are used in the vulnerability assessment: glacial area fraction, interannual variability of permafrost depth, interannual variability of surface snow area fraction, interannual variability of surface runoff, interannual variability of surface temperature, interannual variability of vegetation growth, and interannual variability of the human development index. Assessment results show that the overall vulnerability of the studied areas in China increases from east to west. The areas in the middle and eastern parts of China are less vulnerable compared with western parts and parts of the Tibetan Plateau. The highest vulnerability values are found from 1981 to 2000, and the least ones are found from 2001 to 2050. The vulnerable areas increase from the period of 1981 to 2000 to the period of 2001 to 2050, and the less vulnerable areas decrease. The highly vulnerable areas increase from the period of 1981 to 2000 to the period of 2001 to 2020 and then decrease from the period of 2001 to 2020 to the period of 2001 to 2050. This decrease in vulnerability is attributed to the decrease in exposure and sensitivity to Chinese cryospheric changes along with a concomitant increase in adaptation.

European summer climate variability in a heterogeneous multi-model ensemble

Recent results from an enhanced greenhouse-gas scenario over Europe suggest that climate change might not only imply a general mean warming at the surface, but also a pronounced increase in interannual surface temperature variability during the summer season (Schär et al., Nature 427:332–336, 2004). It has been proposed that the underlying physical mechanism is related to land surface-atmosphere interactions. In this study we expand the previous analysis by including results from a heterogeneous ensemble of 11 high-resolution climate models from the PRUDENCE project. All simulations considered comprise 30-year control and enhanced greenhouse-gas scenario periods. While there is considerable spread in the models’ ability to represent the observed summer variability, all models show some increase in variability for the scenario period, confirming the main result of the previous study. Averaged over a large-scale Central European domain, the models simulate an increase in the standard deviation of summer mean temperatures between 20 and 80%. The amplification occurs predominantly over land points and is particularly pronounced for surface temperature, but also evident for precipitation. It is also found that the simulated changes in Central European summer conditions are characterized by an emergence of dry and warm years, with early and intensified depletion of root-zone soil moisture. There is thus some evidence that the change in variability may be linked to the dynamics of soil-moisture storage and the associated feedbacks on the surface energy balance and precipitation.

Simulated Sea Surface Temperature and Heat Fluxes in Different Climates of the Baltic Sea

The physical state of the Baltic Sea in possible future climates is approached by numerical model experiments with a regional coupled ocean-atmosphere model driven by different global simulations. Scenarios and recent climate simulations are compared to estimate changes. The sea surface is clearly warmer by 2.9 degrees C in the ensemble mean. The horizontal pattern of average annual mean warming can largely be explained in terms of ice-cover reduction. The transfer of heat from the atmosphere to the Baltic Sea shows a changed seasonal cycle: a reduced heat loss in fall, increased heat uptake in spring, and reduced heat uptake in summer. The interannual variability of surface temperature is generally increased. This is associated with a smoothed frequency distribution in northern basins. The overall heat budget shows increased solar radiation to the sea surface, which is balanced by changes of the other heat flux components.

Seasonal and interannual variability of North American isoprene emissions as determined by formaldehyde column measurements from space

Formaldehyde (HCHO) columns measured from space by solar UV backscatter allow mapping of reactive hydrocarbon emissions. The principal contributor to these emissions during the growing season is the biogenic hydrocarbon isoprene, which is of great importance for driving regional and global tropospheric chemistry. We present seven years (1995–2001) of HCHO column data for North America from the Global Ozone Monitoring Experiment (GOME), and show that the general seasonal and interannual variability of these data is consistent with knowledge of isoprene emission. There are some significant regional discrepancies with the seasonal patterns predicted from current isoprene emission models, and we suggest that these may reflect flaws in the models. The interannual variability of HCHO columns observed by GOME appears to follow the interannual variability of surface temperature, as expected from current isoprene emission models.

Relationship between Temperature and Circulation in Southeastern South America and its Influence from El Nino and La Nina Events.

This paper explores the relationship between regional circulation anomalies and the interannual variability of surface temperature in Southern South America, east of the Andes (SSA). Two sets of monthly surface temperature for the 1963-1990 period were used; one was taken from the NCEP/NCAR reanalysis, and the other was built from the synoptic network records. Although these sets present some differences between them, the conclusions found are independent of the data set. Monthly and seasonal indices were developed to explore, through linear correlation, the connection between interannual temperature variability in SSA and some features of regional circulation. The intensification (reduction) of the west component of the wind at the upper troposphere over the subtropical latitudes of South America, and the northward (southward) shift of the maximum westerly wind over SSA tend to be associated with cold (warm) anomalies of surface temperature during practically every month throughout the year. At low levels, the enhancement (reduction) of the zonal geopotential gradient between the South Atlantic high and the Chaco low, representative of the northern component of the low-level flow, is generally associated with warm (cold) surface temperature anomalies. In SSA, monthly precipitation is positively correlated with the northern component of the geostrophic flow. Therefore the advection of temperature offsets the possible influence of precipitation, caused by the associated evaporation and cloudiness, on surface temperature. Hence, there are positive correlations between precipitation and temperature except for central Argentina in summer, and for southern Brazil in certain months. The fact that increased (decreased) precipitation accompanies enhanced (less) warm advection, contributes to moderate the interannual variability of surface temperature. The partial balance between the effects of warm advection and precipitation on surface temperature variability explains why, though ENSO phases have a considerable impact on precipitation and some influence on the regional circulation, their signals in the surface temperature are relatively modest. The exception is in JJA (0) in western SSA, for the most part a region with very scant precipitation during the austral winter, where the surface temperature anomalies are positive in El Ninno, and negative in La Ninna. The maximum anomalies coincide approximately with an enhancement (reduction) of the northern component of the flow, and of the warm advection at low levels in El Ninn o (La Ninna) events.