Jeff Ridley

The New Hadley Centre Climate Model (HadGEM1): Evaluation of Coupled Simulations

Abstract A new coupled general circulation climate model developed at the Met Offices Hadley Centre is presented, and aspects of its performance in climate simulations run for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) documented with reference to previous models. The Hadley Centre Global Environmental Model version 1 (HadGEM1) is built around a new atmospheric dynamical core; uses higher resolution than the previous Hadley Centre model, HadCM3; and contains several improvements in its formulation including interactive atmospheric aerosols (sulphate, black carbon, biomass burning, and sea salt) plus their direct and indirect effects. The ocean component also has higher resolution and incorporates a sea ice component more advanced than HadCM3 in terms of both dynamics and thermodynamics. HadGEM1 thus permits experiments including some interactive processes not feasible with HadCM3. The simulation of present-day mean climate in HadGEM1 is significantly better overall ...

Elimination of the greenland Ice sheet in a high CO2 climate

Projections of future global sea level depend on reliable estimates of changes in the size of polar ice sheets. Calculating this directly from global general circulation models (GCMs) is unreliable because the coarse resolution of 100 km or more is unable to capture narrow ablation zones, and ice dynamics is not usually taken into account in GCMs. To overcome these problems a high-resolution (20 km) dynamic ice sheet model has been coupled to the third Hadley Centre Coupled Ocean–Atmosphere GCM (HadCM3). A novel feature is the use of two-way coupling, so that climate changes in the GCM drive ice mass changes in the ice sheet model that, in turn, can alter the future climate through changes in orography, surface albedo, and freshwater input to the model ocean. At the start of the main experiment the atmospheric carbon dioxide concentration was increased to 4 times the preindustrial level and held constant for 3000 yr. By the end of this period the Greenland ice sheet is almost completely ablated and has made a direct contribution of approximatel y7mt oglobal average sea level, causing a peak rate of sea level rise of 5 mm yr 1 early in the simulation. The effect of ice sheet depletion on global and regional climate has been examined and it was found that apart from the sea level rise, the long-term effect on global climate is small. However, there are some significant regional climate changes that appear to have reduced the rate at which the ice sheet ablates.

Impact of model physics on estimating the surface mass balance of the Greenland ice sheet

Long-term predictions of sea level rise from increased Greenland ice sheet melting have been derived using Positive Degree Day models only. It is, however, unknown precisely what uncertainties are associated with applying this simple surface melt parameterization for future climate. We compare the behavior of a Positive Degree Day and Energy Balance/ Snowpack model for estimating the surface mass balance of the Greenland ice sheet under a warming climate. Both models were first tuned to give similar values for present-day mass balance using 10 years of ERA-40 climatology and were then run for 300 years, forced with the output of a GCM in which atmospheric CO2 increased to 4 times preindustrial levels. Results indicate that the Positive Degree Day model is more sensitive to climate warming than the Energy Balance model, generating annual runoff rates almost twice as large for a fixed ice sheet geometry. Roughly half of this difference was due to differences in the volume of melt generated and half was due to differences in refreezing rates in the snowpack. Our results indicate that the modeled snowpack properties evolve on a multidecadal timescale to changing climate, with a potentially large impact on the mass balance of the ice sheet; an evolution that was absent from the Positive Degree Day model. Copyright 2007 by the American Geophysical Union.

Western Disturbances: A review

Cyclonic storms associated with the midlatitude Subtropical Westerly Jet (SWJ), referred to as Western Disturbances (WDs), play a critical role in the meteorology of the Indian subcontinent. WDs embedded in the southward propagating SWJ produce extreme precipitation over northern India and are further enhanced over the Himalayas due to orographic land-atmosphere interactions. During December, January, and February, WD snowfall is the dominant precipitation input to establish and sustain regional snowpack, replenishing regional water resources. Spring melt is the major source of runoff to northern Indian rivers and can be linked to important hydrologic processes from aquifer recharge to flashfloods. Understanding the dynamical structure, evolution-decay, and interaction of WDs with the Himalayas is therefore necessary to improve knowledge which has wide ranging socioeconomic implications beyond short-term disaster response including cold season agricultural activities, management of water resources, and development of vulnerability-adaptive measures. In addition, WD wintertime precipitation provides critical mass input to existing glaciers and modulates the albedo characteristics of the Himalayas and Tibetan Plateau, affecting large-scale circulation and the onset of the succeeding Indian Summer Monsoon. Assessing the impacts of climate variability and change on the Indian subcontinent requires fundamental understanding of the dynamics of WDs. In particular, projected changes in the structure of the SWJ will influence evolution-decay processes of the WDs and impact Himalayan regional water availability. This review synthesizes past research on WDs with a perspective to provide a comprehensive assessment of the state of knowledge to assist both researchers and policymakers, and context for future research.

Evaluation of the sea ice simulation in a new coupled atmosphere‐ocean climate model (HadGEM1)

A rapid increase in the variety, quality, and quantity of observations in polar regions is leading to a significant improvement in the understanding of sea ice dynamic and thermodynamic processes and their representation in global climate models. We assess the simulation of sea ice in the new Hadley Centre Global Environmental Model (HadGEM1) against the latest available observations. The HadGEM1 sea ice component uses elastic-viscous-plastic dynamics, multiple ice thickness categories, and zero-layer thermodynamics. The model evaluation is focused on the mean state of the key variables of ice concentration, thickness, velocity, and albedo. The model shows good agreement with observational data sets. The variability of the ice forced by the North Atlantic Oscillation is also found to agree with observations.

Application of regional climate models to the Indian winter monsoon over the western Himalayas

The Himalayan region is characterized by pronounced topographic heterogeneity and land use variability from west to east, with a large variation in regional climate patterns. Over the western part of the region, almost one-third of the annual precipitation is received in winter during cyclonic storms embedded in westerlies, known locally as the western disturbance. In the present paper, the regional winter climate over the western Himalayas is analyzed from simulations produced by two regional climate models (RCMs) forced with large-scale fields from ERA-Interim. The analysis was conducted by the composition of contrasting (wet and dry) winter precipitation years. The findings showed that RCMs could simulate the regional climate of the western Himalayas and represent the atmospheric circulation during extreme precipitation years in accordance with observations. The results suggest the important role of topography in moisture fluxes, transport and vertical flows. Dynamical downscaling with RCMs represented regional climates at the mountain or even event scale. However, uncertainties of precipitation scale and liquid-solid precipitation ratios within RCMs are still large for the purposes of hydrological and glaciological studies.

Regional projections of North Indian climate for adaptation studies

Adaptation is increasingly important for regions around the world where large changes in climate could have an impact on populations and industry. The Brahmaputra-Ganges catchments have a large population, a main industry of agriculture and a growing hydro-power industry, making the region susceptible to changes in the Indian Summer Monsoon, annually the main water source. The HighNoon project has completed four regional climate model simulations for India and the Himalaya at high resolution (25km) from 1960 to 2100 to provide an ensemble of simulations for the region. In this paper we have assessed the ensemble for these catchments, comparing the simulations with observations, to give credence that the simulations provide a realistic representation of atmospheric processes and therefore future climate. We have illustrated how these simulations could be used to provide information on potential future climate impacts and therefore aid decision-making using climatology and threshold analysis. The ensemble analysis shows an increase in temperature between the baseline (1970-2000) and the 2050s (2040-2070) of between 2 and 4°C and an increase in the number of days with maximum temperatures above 28°C and 35°C. There is less certainty for precipitation and runoff which show considerable variability, even in this relatively small ensemble, spanning zero. The HighNoon ensemble is the most complete data for the region providing useful information on a wide range of variables for the regional climate of the Brahmaputra-Ganges region, however there are processes not yet included in the models that could have an impact on the simulations of future climate. We have discussed these processes and show that the range from the HighNoon ensemble is similar in magnitude to potential changes in projections where these processes are included. Therefore strategies for adaptation must be robust and flexible allowing for advances in the science and natural environmental changes.

Identifying uncertainties in Arctic climate change projections

Wide ranging climate changes are expected in the Arctic by the end of the 21st century, but projections of the size of these changes vary widely across current global climate models. This variation represents a large source of uncertainty in our understanding of the evolution of Arctic climate. Here we systematically quantify and assess the model uncertainty in Arctic climate changes in two CO2 doubling experiments: a multimodel ensemble (CMIP3) and an ensemble constructed using a single model (HadCM3) with multiple parameter perturbations (THC-QUMP). These two ensembles allow us to assess the contribution that both structural and parameter variations across models make to the total uncertainty and to begin to attribute sources of uncertainty in projected changes. We find that parameter uncertainty is an major source of uncertainty in certain aspects of Arctic climate. But also that uncertainties in the mean climate state in the 20th century, most notably in the northward Atlantic ocean heat transport and Arctic sea ice volume, are a significant source of uncertainty for projections of future Arctic change. We suggest that better observational constraints on these quantities will lead to significant improvements in the precision of projections of future Arctic climate change.

More frequent occurrence of westerly disturbances in Karakoram up to 2100.

The globally averaged mass balance of glaciers and ice caps is negative, but an anomalous gain of mass has been suggested for the Karakoram glaciers of the western Himalaya. Changes in the winter synoptic patterns can influence the amount and seasonality of Himalayan snowfall and consequently influence the mass balance of regional glaciers. We use a clustering method to analyse the sea level pressure patterns which most influence Karakorum snow fall and determine if the frequency of these synoptic patterns changes in future scenarios. A regional climate model is used to assess changes in severity and frequency of snowfall events. A number of weather patterns influence winter precipitation over the western Himalaya, including westerly disturbances, and indicate an increase in frequency of occurrence up to 2100. Thus, the Karakorum glaciers may continue to grow, or decline at a slower rate, compared with those across the rest of the Himalayas.

Changes in Global Ocean Bottom Properties and Volume Transports in CMIP5 Models under Climate Change Scenarios

AbstractChanges in bottom temperature, salinity, and density in the global ocean by 2100 for CMIP5 climate models are investigated for the climate change scenarios RCP4.5 and RCP8.5. The mean of 24 models shows a decrease in density in all deep basins, except the North Atlantic, which becomes denser. The individual model responses to climate change forcing are more complex: regarding temperature, the 24 models predict a warming of the bottom layer of the global ocean; in salinity, there is less agreement regarding the sign of the change, especially in the Southern Ocean. The magnitude and equatorward extent of these changes also vary strongly among models. The changes in properties can be linked with changes in the mean transport of key water masses. The Atlantic meridional overturning circulation weakens in most models and is directly linked to changes in bottom density in the North Atlantic. These changes are the result of the intrusion of modified Antarctic Bottom Water, made possible by the decrease i...