Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.

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Climate Change 2007: The Physical Science Basis.

The Intergovernmental Panel on Climate Change (IPCC) Technical Paper Climate Change and Water draws together and evaluates the information in IPCC Assessment and Special Reports concerning the impacts of climate change on hydrological processes and regimes, and on freshwater resources – their availability, quality, use and management. It takes into account current and projected regional key vulnerabilities, prospects for adaptation, and the relationships between climate change mitigation and water. Its objectives are:

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Climate change and water.

The construction of a 0.5° lat × 0.5° long surface climatology of global land areas, excluding Antarctica, is described. The climatology represents the period 1961–90 and comprises a suite of nine variables: precipitation, wet-day frequency, mean temperature, diurnal temperature range, vapor pressure, sunshine, cloud cover, ground frost frequency, and wind speed. The climate surfaces have been constructed from a new dataset of station 1961–90 climatological normals, numbering between 19 800 (precipitation) and 3615 (wind speed). The station data were interpolated as a function of latitude, longitude, and elevation using thin-plate splines. The accuracy of the interpolations are assessed using cross validation and by comparison with other climatologies. This new climatology represents an advance over earlier published global terrestrial climatologies in that it is strictly constrained to the period 1961–90, describes an extended suite of surface climate variables, explicitly incorporates elevation...

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Representing Twentieth-Century Space–Time Climate Variability. Part I: Development of a 1961–90 Mean Monthly Terrestrial Climatology

[1] Arctic amplification (AA) – the observed enhanced warming in high northern latitudes relative to the northern hemisphere – is evident in lower-tropospheric temperatures and in 1000-to-500 hPa thicknesses. Daily fields of 500 hPa heights from the National Centers for Environmental Prediction Reanalysis are analyzed over N. America and the N. Atlantic to assess changes in north-south (Rossby) wave characteristics associated with AA and the relaxation of poleward thickness gradients. Two effects are identified that each contribute to a slower eastward progression of Rossby waves in the upper-level flow: 1) weakened zonal winds, and 2) increased wave amplitude. These effects are particularly evident in autumn and winter consistent with sea-ice loss, but are also apparent in summer, possibly related to earlier snow melt on high-latitude land. Slower progression of upper-level waves would cause associated weather patterns in mid-latitudes to be more persistent, which may lead to an increased probability of extreme weather events that result from prolonged conditions, such as drought, flooding, cold spells, and heat waves.

Observations: Changes in Snow, Ice and Frozen Ground

Regional climate model runs using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesocale Model modified for use in polar regions (Polar MM5), calibrated by independent in situ observations, demonstrate coherent regional patterns of Greenland ice sheet surface mass balance (SMB) change over a 17-yr period characterized by warming (1988–2004). Both accumulation and melt rates increased, partly counteracting each other for an overall negligible SMB trend. However, a 30% increase in meltwater runoff over this period suggests that the overall ice sheet mass balance has been increasingly negative, given observed meltwater-induced flow acceleration. SMB temporal variability of the whole ice sheet is best represented by ablation zone variability, suggesting that increased melting dominates over increased accumulation in a warming scenario. The melt season grew in duration over nearly the entire ablation zone by up to 40 days, 10 days on average. Accumulation area ratio decreased by 3%. Albedo reductions are apparent in five years of the Moderate Resolution Imaging Spectroradiometer (MODIS) derived data (2000–04). The Advanced Very High Resolution Radiometer (AVHRR)-derived albedo changes (1988–99) were less consistent spatially. A conservative assumption as to glacier discharge and basal melting suggests an ice sheet mass loss over this period greater than 100 km 3 yr 1 , framing the Greenland ice sheet as the largest single glacial contributor to recent global sea level rise. Surface mass balance uncertainty, quantified from residual random error between model and independent observations, suggests two things: 1) changes smaller than approximately 200 km 3 yr 1 would not satisfy conservative statistical significance thresholds (i.e., two standard deviations) and 2) although natural variability and model uncertainty were separated in this analysis, the magnitude of each were roughly equivalent. Therefore, improvements in model accuracy and analysis of longer periods (assuming larger changes) are both needed for definitive mass balance change assessments.

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Greenland Ice Sheet Surface Mass Balance Variability (1988–2004) from Calibrated Polar MM5 Output

[1] The Polar Pennsylvania State University–National Center for Atmospheric Research Fifth-Generation Mesoscale Model (Polar MM5) regional climate model was run over the North Atlantic region for 1991–2000. We analyze 24-km output over the Greenland ice sheet to evaluate spatial and temporal variability of the surface mass balance and its subcomponents. The model output is compared with 3 years of automatic weather station (AWS) data from 17 sites to identify biases. Using the in situ data, we derive simple corrections for biases in melt energy and in water vapor fluxes from the surface and from blowing snow. The simulated accumulation rate is in agreement with AWS and snow pit observations. Estimates for runoff and the surface mass balance distribution over the ice sheet are produced using modeled melt volume and a meltwater retention scheme. From the decade investigated, the magnitude of interannual variability in surface mass balance components is tentatively established. The largest variability is concentrated along the ice sheet margin, where both accumulation and ablation rates are largest. The simulated interannual fluctuations suggest a large absolute variability, ±187 km3 yr−1 for total ice sheet surface mass balance. Variability in simulated equilibrium line altitude is suggestive of a dominance of thermal variability in the south with increasing importance of accumulation variability with increasing latitude. Empirical functions for the sensitivity of surface mass balance to temperature and precipitation anomalies are presented. The precise locations and regions of maximum and minimum surface energy and mass fluxes are suggested. Using an estimate for iceberg discharge and bottom melting, the total ice sheet mass balance is estimated be −78 km3 yr−1, producing 2.2 mm of eustatic sea level rise over the 1991–2000 decade and contributing 15% to the observed (1.5 mm yr−1) global sea level rise. The more negative mass balance is attributed to including blowing-snow sublimation loss and to regional warming in the 1990s.

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Greenland ice sheet surface mass balance 1991–2000: Application of Polar MM5 mesoscale model and in situ data

Meteorological station records and regional climate model output are combined to develop a continuous 168-yr (1840-2007) spatial reconstruction of monthly, seasonal, and annual mean Greenland ice sheet near-surface air temperatures. Independent observations are used to assess and compensate for systematic errors in the model output. Uncertainty is quantified using residual nonsystematic error. Spatial and temporal temperature variability is investigated on seasonal and annual time scales. It is found that volcanic cooling episodes are concentrated in winter and along the western ice sheet slope. Interdecadal warming trends coincide with an absence of major volcanic eruptions. Year 2003 was the only year of 1840-2007 with a warm anomaly that exceeds three standard deviations from the 1951-80 base period. The annual whole ice sheet 1919-32 warming trend is 33% greater in magnitude than the 1994-2007 warming. The recent warming was, however, stronger along western Greenland in autumn and southern Greenland in winter. Spring trends marked the 1920s warming onset, while autumn leads the 1994-2007 warming. In contrast to the 1920s warming, the 1994-2007 warming has not surpassed the Northern Hemisphere anomaly. An additional 1.08-1.5 degrees C of annual mean warming would be needed for Greenland to be in phase with the Northern Hemispheric pattern. Thus, it is expected that the ice sheet melt rates and mass deficit will continue to grow in the early twenty-first century as Greenland's climate catches up with the Northern Hemisphere warming trend and the Arctic climate warms according to global climate model predictions.

Greenland Ice Sheet Surface Air Temperature Variability: 1840–2007*

[1] A version of the state-of-the-art Weather Research and Forecasting model (WRF) has been developed for polar applications. The model known as ‘‘Polar WRF’’ is tested over the Arctic Ocean with a western Arctic grid using 25-km resolution. The model is based upon WRF version 2.2, with improvements to the Noah land surface model and the snowpack treatment. The ocean surface treatment is modified to include fractional sea ice. Simulations consist of a series of 48-h integrations initialized daily at 0000 UTC. The initial 24 h are taken as model spin-up time for the atmospheric hydrology and boundary layer processes. Arctic conditions are simulated for the selected months: January 1998, June 1998, and August 1998 representing midwinter, early summer, and late summer conditions, respectively, from the Surface Heat Budget of the Arctic (SHEBA) study. The albedo of sea ice is specified as a function of time and latitude for June and as a function of time for August. Simulation results are compared with observations of the drifting ice station SHEBA in the Arctic ice pack. Polar WRF simulations show good agreement with observations for all three months. Some differences between the simulations and observation occur owing to apparent errors in the synoptic forecasts and the representation of clouds. Nevertheless, the biases in the simulated fields appear to be small, and Polar WRF appears to be a very good tool for studies of Arctic Ocean meteorology.

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Development and testing of Polar Weather Research and Forecasting model: 2. Arctic Ocean

A version of the state-of-the-art Weather Research and Forecasting model (WRF) has been developed for use in polar climates. The model known as “Polar WRF” is tested for land areas with a western Arctic grid that has 25-km resolution. This work serves as preparation for the high-resolution Arctic System Reanalysis of the years 2000–10. The model is based upon WRF version 3.0.1.1, with improvements to the Noah land surface model and snow/ice treatment. Simulations consist of a series of 48-h integrations initialized daily at 0000 UTC, with the initial 24 h taken as spinup for atmospheric hydrology and boundary layer processes. Soil temperature and moisture that have a much slower spinup than the atmosphere are cycled from 48-h output of earlier runs. Arctic conditions are simulated for a winter-to-summer seasonal cycle from 15 November 2006 to 1 August 2007. Simulation results are compared with a variety of observations from several Alaskan sites, with emphasis on the North Slope. Polar WRF simula...

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Lesheng Bai

Papers

Greenland Ice Sheet Surface Mass Balance Variability (1988–2004) from Calibrated Polar MM5 Output

Greenland ice sheet surface mass balance 1991–2000: Application of Polar MM5 mesoscale model and in situ data

Greenland Ice Sheet Surface Air Temperature Variability: 1840–2007*

Development and testing of Polar Weather Research and Forecasting model: 2. Arctic Ocean

Development and Testing of Polar WRF. Part III: Arctic Land*