REGIONAL CLIMATE CHANGE SCENARIOS UNDER GLOBAL WARMING IN KAZAKHSTAN

The aim of this paper is to report on the development of regional climate change scenarios for Kazakhstan as the result of increasing of CO₂ concentration in the global atmosphere. These scenarios are used in the assessment of climate change impacts on the agricultural, forest and water resources of Kazakhstan. Climate change scenarios for Kazakhstan to assess both long-term (2× CO₂ in 2075) and short-term (2000, 2010 and 2030) impacts were prepared. The climate conditions under increasing CO₂ concentration were estimated from three General Circulation Models (GCM) outputs: the model of the Canadian Climate Center Model (CCCM), the model of the Geophysical Fluid Dynamics Laboratory (GFDL) and the 1% transient version of the GFDL model (GFDL-T). The near-term climate scenarios were obtained using the probabilistic forecast model (PFM) to the year 2010 and the results of GFDL-T for years 2000 and 2030. A baseline scenario representing the current climate conditions based on observations from 1951 to 1980 was developed. The assessment of climate change in Kazakhstan based on the analysis of 100-years observations is given too. As a result of comparisons of the current climate (based on observed climate) the 1× CO₂ output from GCMs showed that the GFDL model best matches the observed climate. The GFDL model suggests that the minimum increase in temperature is expected in winter, when most of the territory is expected to have temperatures 2.3–4.5 °C higher. The maximum (4.3 to 8.2 °C) is expected to be in spring. CCCM scenario estimates an extreme worming above 11 °C in spring months. GFDL-T outputs provide an intermediate scenario.     

Mechanisms for projected future changes in south Asian monsoon precipitation

Results are first presented from an analysis of a global coupled climate model regarding changes in future mean and variability of south Asian monsoon precipitation due to increased atmospheric CO₂ for doubled (2 × CO₂) and quadrupled (4 × CO₂) present-day amounts. Results from the coupled model show that, in agreement with previous studies, mean area-averaged south Asian monsoon precipitation increases with greater CO₂ concentrations, as does the interannual variability. Mechanisms producing these changes are then examined in a series of AMIP2-style sensitivity experiments using the atmospheric model (taken from the coupled model) run with specified SSTs. Three sets of ensemble experiments are run with SST anomalies superimposed on the AMIP2 SSTs from 1979–97: (1) anomalously warm Indian Ocean SSTs, (2) anomalously warm Pacific Ocean SSTs, and (3) anomalously warm Indian and Pacific Ocean SSTs. Results from these experiments show that the greater mean monsoon precipitation is due to increased moisture source from the warmer Indian Ocean. Increased south Asian monsoon interannual variability is primarily due to warmer Pacific Ocean SSTs with enhanced evaporation variability, with the warmer Indian Ocean SSTs a contributing but secondary factor. That is, for a given interannual tropical Pacific SST fluctuation with warmer mean SSTs in the future climate, there is enhanced evaporation and precipitation variability that is communicated via the Walker Circulation in the atmosphere to the south Asian monsoon to increase interannual precipitation variability there. This enhanced monsoon variability occurs even with no change in interannual SST variability in the tropical Pacific.     

An investigation of cloud cover change in response to thermal forcing

The role of cloud cover in determining the sensitivity of climate has been a source of great uncertainty. This article reviews the distributions of cloud cover change from several climate sensitivity experiments conducted at the Geophysical Fluid Dynamics Laboratory of NOAA (GFDL) and other institutions. Two of the sensitivity experiments conducted at GFDL used a general circulation model with a limited computational domain and idealized geography, whereas three other experiments were conducted by the use of a global model with realistic geography. A thermal forcing imposed was either a change of solar constant or that of the CO₂-concentration in the atmosphere. It was found that in all five cases, clouds were decreased in the moist, convectively active regions such as the tropical and middle latitude rainbelts, whereas they increased in the stable region near the model surface from middle to higher latitudes. In addition, cloud also increased in the lower model stratosphere and generally decreased in the middle and upper troposphere for practically all latitudes.A comparison of the cloud changes obtained from investigations carried out at other institutions reveals certain qualitative (but not necessarily quantitative) similarities to the GFDL results. These similarities include a general reduction of tropospheric cloud cover especially in the vicinity of the rainbelts, a general increase of lower stratospheric cloud cover for almost all latitudes and an increase of low stratiform cloud in high latitudes.     

Sub-Saharan Northern African climate at the end of the twenty-first century: forcing factors and climate change processes

A regional climate model, the Weather Research and Forecasting (WRF) Model, is forced with increased atmospheric CO₂ and anomalous SSTs and lateral boundary conditions derived from nine coupled atmosphere–ocean general circulation models to produce an ensemble set of nine future climate simulations for northern Africa at the end of the twenty-first century. A well validated control simulation, agreement among ensemble members, and a physical understanding of the future climate change enhance confidence in the predictions. The regional model ensembles produce consistent precipitation projections over much of northern tropical Africa. A moisture budget analysis is used to identify the circulation changes that support future precipitation anomalies. The projected midsummer drought over the Guinean Coast region is related partly to weakened monsoon flow. Since the rainfall maximum demonstrates a southward bias in the control simulation in July–August, this may be indicative of future summer drying over the Sahel. Wetter conditions in late summer over the Sahel are associated with enhanced moisture transport by the West African westerly jet, a strengthening of the jet itself, and moisture transport from the Mediterranean. Severe drought in East Africa during August and September is accompanied by a weakened Indian monsoon and Somali jet. Simulations with projected and idealized SST forcing suggest that overall SST warming in part supports this regional model ensemble agreement, although changes in SST gradients are important over West Africa in spring and fall. Simulations which isolate the role of individual climate forcings suggest that the spatial distribution of the rainfall predictions is controlled by the anomalous SST and lateral boundary conditions, while CO₂ forcing within the regional model domain plays an important secondary role and generally produces wetter conditions.     

Impact of ocean warm layer thickness on the intensity of hurricane Katrina in a regional coupled model

The effect of pre-storm subsurface thermal structure on the intensity of hurricane Katrina (2005) is examined using a regional coupled model. The Estimating Circulation and Climate of Ocean (ECCO) ocean state estimate is used to initialize the ocean component of the coupled model, and the source of deficiencies in the simulation of Katrina intensity is investigated in relation to the initial depth of 26 °C isotherm (D26). The model underestimates the intensity of Katrina partly due to shallow D26 in ECCO. Sensitivity tests with various ECCO initial fields indicate that the correct relationship between intensity and D26 cannot be derived because D26 variability is underestimated in ECCO. A series of idealized experiments is carried out by modifying initial ECCO D26 to match the observed range. A more reasonable relationship between Katrina’s intensity and pre-storm D26 emerges: the intensity is much more sensitive to D26 than to sea surface temperature (SST). Ocean mixed layer process plays a critical role in modulating inner-core SSTs when D26 is deep, reducing mixed layer cooling and lowering the center pressure of the Katrina. Our result lends strong support to the notion that accurate initialization of pre-storm subsurface thermal structure in prediction models is critical for a skillful forecast of intensity of Katrina and likely other intense storms.     

Changes in mixed layer depth under climate change projections in two CGCMs

Two coupled general circulation models, i.e., the Meteorological Research Institute (MRI) and Geophysical Fluid Dynamics Laboratory (GFDL) models, were chosen to examine changes in mixed layer depth (MLD) in the equatorial tropical Pacific and its relationship with ENSO under climate change projections. The control experiment used pre-industrial greenhouse gas concentrations whereas the 2 × CO₂ experiment used doubled CO₂ levels. In the control experiment, the MLD simulated in the MRI model was shallower than that in the GFDL model. This resulted in the tropical Pacific’s mean sea surface temperature (SST) increasing at different rates under global warming in the two models. The deeper the mean MLD simulated in the control simulation, the lesser the warming rate of the mean SST simulated in the 2 × CO₂ experiment. This demonstrates that the MLD is a key parameter for regulating the response of tropical mean SST to global warming. In particular, in the MRI model, increased stratification associated with global warming amplified wind-driven advection within the mixed layer, leading to greater ENSO variability. On the other hand, in the GFDL model, wind-driven currents were weak, which resulted in mixed-layer dynamics being less sensitive to global warming. The relationship between MLD and ENSO was also examined. Results indicated that the non-linearity between the MLD and ENSO is enhanced from the control run to the 2 × CO₂ run in the MRI model, in contrast, the linear relationship between the MLD index and ENSO is unchanged despite an increase in CO₂ concentrations in the GFDL model.     

Global climatic change,hurricanes, and a tropical forest

Most, if not all forests in the Caribbean are subject to occasional disturbances from hurricanes. If current general circulation model (GCM) predictions are correct, with doubled atmospheric CO₂ (2 × CO₂), the tropical Atlantic will be between 1 °C and 4 °C warmer than it is today. With such a warming, more than twice as many hurricanes per year could be expected in the Caribbean. Furthermore, Emanuael (1987) indicates that in a warmed world the destructive potential of Atlantic hurricanes could be increased by 40% to 60%. While speculative, these increases would dramatically change the disturbance regimes affecting tropical forests in the region and might alter forest structure and composition. Global warming impacts through increased hurricane damage on Caribbean forests are presented.An individual tree, gap dynamics forest ecosystem model was used to simulate the range of possible hurricane disturbance regimes which could affect the Luquillo Experimental Forest in Puerto Rico. Model storm frequency ranged from no storms at all up to one storm per year; model storm intensity varied from no damage up to 100% mortality of trees. The model does not consider the effects of changing temperature and rainfall patterns on the forest. Simulation results indicate that with the different hurricane regimes a range of forest types are possible, ranging from mature forest with large trees, to an area in which forest trees are never allowed to reach maturity.     

Impact of cloud microphysical processes on hurricane intensity, part 2: Sensitivity experiments

Summary Seven different microphysical sensitivity experiments were designed with an objective to evaluate their respective impacts in modulating hurricane intensity forecasts using mesoscale model MM5. Microphysical processes such as melting of graupel, snow and cloud ice hydrometeors, suppression of evaporation of falling rain, the intercept parameter and fall speed of snow and graupel hydrometeors are modified in the existing NASA Goddard Space Flight Center (GSFC) microphysical parameterization scheme. We studied the impacts of cloud microphysical processes by means of track, intensity, precipitation, propagation speed, kinematic and thermodynamic vertical structural characteristics of hurricane inner core. These results suggest that the set of experiments where (a) melting of snow, graupel and cloud ice were suppressed (b) melting of snow and graupel were suppressed and (c) where the evaporation of rain water was suppressed all produced most intense storms. The major findings of this study are the interconversion processes such as melting and evaporation among hydrometeors and associated feedback mechanism are significantly modulate the intensity of the hurricane. In particular an experiment where the melting of graupel, snow and cloud ice hydrometeors was eliminated from the model parameterization scheme produced the most explosively intensified storm. In the experiment where rain water evaporation was eliminated from the model, it produced a stronger storm as compared to the control run but it was not as strong as the storms produced from absence of melting processes. The impact on intensity due to variations made in intercept parameters of the hydrometeors (i.e., snow and graupel) were not that evident compared to other experiments. The weakest storm was noted in the experiment where the fall speeds of the snow hydrometeors were increased two fold. This study has isolated some of the factors that contributed to a stronger hurricane and concludes with a motivation that the findings from this study will help in further improvement in the design of sophisticated explicit microphysical parameterization for the mesoscale non-hydrostatic model for realistic hurricane intensity forecasts.     

Climate sensitivity due to increased CO2: experiments with a coupled atmosphere and ocean general circulation model

A version of the National Center for Atmospheric Research community climate model — a global, spectral (R15) general circulation model — is coupled to a coarse-grid (5° latitude-] longitude, four-layer) ocean general circulation model to study the response of the climate system to increases of atmospheric carbon dioxide (CO₂). Three simulations are run: one with an instantaneous doubling of atmospheric CO₂ (from 330 to 660 ppm), another with the CO₂ concentration starting at 330 ppm and increasing linearly at a rate of 1% per year, and a third with CO₂ held constant at 330 pm. Results at the end of 30 years of simulation indicate a globally averaged surface air temperature increase of 1.6° C for the instantaneous doubling case and 0.7°C for the transient forcing case. Inherent characteristics of the coarse-grid ocean model flow sea-surface temperatures (SSTs) in the tropics and higher-than-observed SSTs and reduced sea-ice extent at higher latitudes] produce lower sensitivity in this model after 30 years than in earlier simulations with the same atmosphere coupled to a 50-m, slab-ocean mixed layer. Within the limitations of the simulated meridional overturning, the thermohaline circulation weakens in the coupled model with doubled CO₂ as the high-latitude ocean-surface layer warms and freshens and westerly wind stress is decreased. In the transient forcing case with slowly increasing CO₂ (30% increase after 30 years), the zonal mean warming of the ocean is most evident in the surface layer near 30°–50° S. Geographical plots of surface air temperature change in the transient case show patterns of regional climate anomalies that differ from those in the instantaneous CO₂ doubling case, particularly in the North Atlantic and northern European regions. This suggests that differences in CO₂ forcing in the climate system are important in CO₂ response in regard to time-dependent climate anomaly regimes. This confirms earlier studies with simple climate models that instantaneous CO₂ doubling simulations may not be analogous in all respects to simulations with slowly increasing CO₂.A portion of this study is supported by the US Department of Energy as part of its Carbon Dioxide Research Program     

North Atlantic cyclones in CO2-induced warm climate simulations: frequency, intensity, and tracks

The effect of CO₂-induced climate change on the North Atlantic storm and cyclone tracks in winter is analysed using time slice experiments of the Hamburg atmospheric general circulation model (ECHAM3) with triangular truncation at wave number 42 (T42) and 19 levels. The sea surface temperature (SST) and sea ice boundary conditions for these experiments are taken from a transient Intergovernmental Panel on Climate Change (IPCC) scenario A run of ECHAM1/LSG at the times where the 1×CO₂ (control run), the 2×CO₂ and the 3×CO₂ concentrations are reached. Using a cyclone identification and tracking scheme, we detect the low pressure systems as relative minima in the 1000 hPa geopotential height field and connect them to cyclone tracks. The results of the Eulerian analysis of the storm track using filtered variances and the Lagrangian analysis of the cyclone trajectories from the three climate runs are discussed and compared with each other. In the 2×CO₂ experiment, the storm track shifts eastward, whereas the cyclone density shifts northeastward. In the 3×CO₂ experiment the storm track shows a southeastward shift, whereas the cyclone density shifts northward. The variability of the cyclone tracks is determined by a cluster analysis of their relative trajectories considering the first three days of the cyclones. The relative cyclone tracks are grouped into stationary, zonal and northeastward travelling cyclones. This analysis provides a method to assess the model quality and to detect changes of the cyclone trajectories in different climates. In the 2×CO₂ (but not in the 3×CO₂) run the occupation number of northeastward cyclones increases. Received: 27 January 1998 / Accepted: 19 May 1998     

Simulated changes in vegetation distribution, land carbon storage, and atmospheric CO2 in response to a collapse of the North Atlantic thermohaline circulation

It is investigated how abrupt changes in the North Atlantic (NA) thermohaline circulation (THC) affect the terrestrial carbon cycle. The Lund–Potsdam–Jena Dynamic Global Vegetation Model is forced with climate perturbations from glacial freshwater experiments with the ECBILT-CLIO ocean–atmosphere–sea ice model. A reorganisation of the marine carbon cycle is not addressed. Modelled NA THC collapses and recovers after about a millennium in response to prescribed freshwater forcing. The initial cooling of several Kelvin over Eurasia causes a reduction of extant boreal and temperate forests and a decrease in carbon storage in high northern latitudes, whereas improved growing conditions and slower soil decomposition rates lead to enhanced storage in mid-latitudes. The magnitude and evolution of global terrestrial carbon storage in response to abrupt THC changes depends sensitively on the initial climate conditions. These were varied using results from time slice simulations with the Hadley Centre model HadSM3 for different periods over the past 21 kyr. Changes in terrestrial storage vary between −67 and +50 PgC for the range of experiments with different initial conditions. Simulated peak-to-peak differences in atmospheric CO₂ are 6 and 13 ppmv for glacial and late Holocene conditions. Simulated changes in δ¹³C are between 0.15 and 0.25‰. These simulated carbon storage anomalies during a NA THC collapse depend on their magnitude on the CO₂ fertilisation feedback mechanism. The CO₂ changes simulated for glacial conditions are compatible with available evidence from marine studies and the ice core CO₂ record. The latter shows multi-millennial CO₂ variations of up to 20 ppmv broadly in parallel with the Antarctic warm events A1 to A4 in the South and cooling in the North.     

Temporal distribution of weather catastrophes in the USA

The temporal distributions of the nation’s four major storm types during 1950–2005 were assessed, including those for thunderstorms, hurricanes, tornadoes, and winter storms. Storms are labeled as catastrophes, defined as events causing $1 million or more in property losses, based on time-adjusted data provided by the insurance industry. Most catastrophic storms occurred in the eastern half of the nation. Analysis of the regional and national storm frequencies revealed there was little time-related relationship between storm types, reflecting how storm types were reported. That is, when tornadoes occurred with thunderstorms, the type producing the greatest losses was the one identified by the insurance industry, not both. Temporal agreement was found in the timing of relatively high incidences of thunderstorms, hurricanes, and winter storms during 2002–2005. This resulted in upward time trends in the national losses of hurricane and thunderstorm catastrophes, The temporal increase in hurricanes is in agreement with upward trends in population density, wealth, and insurance coverage in Gulf and East coastal areas. The upward trends in thunderstorm catastrophes and losses result from increases in heavy rain days, floods, high winds, and hail days, revealing that atmospheric conditions conducive to strong convective activity have been increasing since the 1960s. Tornado catastrophes and their losses peaked in 1966–1973 and had no upward time trend. Temporal variability in tornado catastrophes was large, whereas the variability in hurricane and thunderstorm catastrophes was only moderate, and that for winter storms was low.     

Simulations of the Last Glacial Maximum climates using a general circulation model: prescribed versus computed sea surface temperatures

 The climate during the Last Glacial Maximum (LGM) has been simulated using the UK Universities Global Atmospheric Modelling Programme (UGAMP) general circulation model (GCM) with both prescribed sea surface temperatures (SSTs) based on the CLIMAP reconstruction and computed SSTs with a simple thermodynamic slab ocean. Consistent with the Paleoclimate Modelling Intercomparison Project (PMIP), the other boundary conditions include the large changes in ice-sheet topography and geography, a lower sea level, a lower concentration of CO₂ in the atmosphere, and a slightly different insolation pattern at the top of the atmosphere. The results are analysed in terms of changes in atmospheric circulation. Emphasis is given to the changes in surface temperatures, planetary waves, storm tracks and the associated changes in distribution of precipitation. The model responds in a similar manner to the changes in boundary conditions to previous studies in global mean statistics, but differs in its treatment of regional climates. Results also suggest that both the land ice sheets and sea ice introduce significant changes in planetary waves and transient eddy activity, which in turn affect regional climates. The computed SST simulations predict less sea ice and cooler tropical temperatures than those based on CLIMAP SSTs. It is unclear as to whether this is a model and/or a data problem, but the resulting changes in land temperatures and precipitation can be large. Snow mass budget analysis suggests that there is net ice loss along the southern edges of the Laurentide and Fennoscandian ice sheets and net ice gain over other parts of the two ice sheets. The net accumulation is mainly due to the decrease in ablation in the cold climate rather than to the changes in snowfall. The characteristics of the Greenland ice-sheet mass balance in the LGM simulations is also quite different from those in the present-day (PD) simulations. The ablation in the LGM simulations is negligible while it is a very important process in the ice mass budget in the PD simulations. Received: 10 January 1997 / Accepted: 11 December 1997     

Tropical storms: representation and diagnosis in climate models and the impacts of climate change

Tropical storms are located and tracked in an experiment in which a high-resolution atmosphere only model is forced with observed sea surface temperatures (SSTs) and sea ice. The structure, geographic distribution and seasonal variability of the model tropical storms show some similarities with observations. The simulation of tropical storms is better in this high-resolution experiment than in a parallel standard resolution experiment. In an anomaly experiment, sea ice, SSTs and greenhouse-gas forcing are changed to mimic the changes that occur in a coupled model as greenhouse-gases are increased. There are more tropical storms in this experiment than in the control experiment in the Northeast Pacific and Indian Ocean basins and fewer in the North Atlantic, Northwest Pacific and Southwest Pacific region. The changes in the North Atlantic and Northwest Pacific can be linked to El Niño-like behaviour. A comparison of the tracking results with two empirically derived tropical storm genesis parameters is carried out. The tracking technique and a convective genesis parameter give similar results, both in the global distribution and in the changes in the individual basins. The convective genesis parameter is also applied to parallel coupled model experiments that have a lower horizontal resolution. The changes in the global distribution of tropical storms in the coupled model experiments are consistent with the changes seen at higher resolution. This indicates that the convective genesis parameter may still provide useful information about tropical storm changes in experiments carried out with models that cannot resolve tropical storms.     

Adaptive use of research aircraft data sets for hurricane forecasts

Summary This study uses an adaptive observational strategy for hurricane forecasting. It shows the impacts of Lidar Atmospheric Sensing Experiment (LASE) and dropsonde data sets from Convection and Moisture Experiment (CAMEX) field campaigns on hurricane track and intensity forecasts. The following cases are used in this study: Bonnie, Danielle and Georges of 1998 and Erin, Gabrielle and Humberto of 2001. A single model run for each storm is carried out using the Florida State University Global Spectral Model (FSUGSM) with the European Center for Medium Range Weather Forecasts (ECMWF) analysis as initial conditions, in addition to 50 other model runs where the analysis is randomly perturbed for each storm. The centers of maximum variance of the DLM heights are located from the forecast error variance fields at the 84-hr forecast. Back correlations are then performed using the centers of these maximum variances and the fields at the 36-hr forecast. The regions having the highest correlations in the vicinity of the hurricanes are indicative of regions from where the error growth emanates and suggests the need for additional observations. Data sets are next assimilated in those areas that contain high correlations. Forecasts are computed using the new initial conditions for the storm cases, and track and intensity skills are then examined with respect to the control forecast. The adaptive strategy is capable of identifying sensitive areas where additional observations can help in reducing the hurricane track forecast errors. A reduction of position error by approximately 52% for day 3 of forecast (averaged over 7 storm cases) over the control runs is observed. The intensity forecast shows only a slight positive impact due to the model’s coarse resolution. Corresponding author’s address: T. N. Krishnamurti, Department of Meteorology, Florida State University, Tallahassee, FL 32306-4520, USA     

A simple model perturbed physics study of the simulated climate sensitivity uncertainty and its relation to control climate biases

In this study the relationship between climate model biases in the control climate and the simulated climate sensitivity are discussed on the basis of perturbed physics ensemble simulations with a globally resolved energy balance (GREB) model. It is illustrated that the uncertainties in the simulated climate sensitivity (estimated by the transient response to CO₂ forcing scenarios in the twenty first century or idealized 2 × CO₂ forcing experiments) can be conceptually split into two parts: a direct effect of the perturbed physics on the climate sensitivity independent of the control mean climate and an indirect effect of the perturbed physics by changing the control mean climate, which in turn changes the climate sensitivity, as the climate sensitivity itself is depending on the control climate. Biases in the control climate are negatively correlated with the climate sensitivity (colder climates have larger sensitivities), if no physics are perturbed. Perturbed physics that lead to warmer control climate, would in average also lead to larger climate sensitivities, if the control climate is held at the observed reference climate by flux corrections. Thus the effects of control biases and perturbed physics are opposing each other and are partially cancelling each other out. In the GREB model the biases in the control climate are the more important effect for the regional climate sensitivity uncertainties, but for the global mean climate sensitivity both, the biases in the control climate and the perturbed physics, are equally important.     

Development of a hurricane boundary-layer wind model

Summary Hurricanes cause a variety of damage due to high winds, heavy rains, and storm surges. This study focuses on hurricanes’ high winds. The most devastating effects of sustained high winds occur in the first few hours of landfall. During the short period, hurricanes’ rainfall often increases, while the low-level pressure gradients continue to weaken. Latent heating does not appear to strengthen the surface winds. The indicator is that dry mechanisms such as the boundary layer processes and terrain are responsible for the damaging winds in the coastal areas. In this study, the design of a dry hurricane boundary layer wind model is described. The goal is to develop a forecast tool with near-real time applications in expeditious wind damage assessment and disaster mitigation during a hurricane landfall event. Different surface roughness lengths and topographic features ranging from flat land to the mountainous terrain of Taiwan were used in the model simulation experiments to reveal how the coastal environment affected the hurricane surface winds. The model performed quite well in all cases. The experiments suggested that the downward transfer of high momentum aloft played a significant role in the maintenance of high wind speeds at the surface. The surface wind maximums were observed on the lee sides of high terrain. The surface streamline analyses showed that the high mountains tended to block the relatively weak flow and caused small eddies, while they forced the stronger flow to turn around the mountains. Due to great difficulty in data collection, the hurricane boundary layer over land remains one of the least understood parts of the system. The dry model proves to be an effective way to study many aspects of hurricane boundary layer winds over a wide range of terrain features and landfall sites. The model runs efficiently and can be run on a medium-size personal computer. Received March 16, 2001 Revised September 10, 2001     

Radiative forcing and response of a GCM to ice age boundary conditions: cloud feedback and climate sensitivity

 A general circulation model is used to examine the effects of reduced atmospheric CO₂, insolation changes and an updated reconstruction of the continental ice sheets at the Last Glacial Maximum (LGM). A set of experiments is performed to estimate the radiative forcing from each of the boundary conditions. These calculations are used to estimate a total radiative forcing for the climate of the LGM. The response of the general circulation model to the forcing from each of the changed boundary conditions is then investigated. About two-thirds of the simulated glacial cooling is due to the presence of the continental ice sheets. The effect of the cloud feedback is substantially modified where there are large changes to surface albedo. Finally, the climate sensitivity is estimated based on the global mean LGM radiative forcing and temperature response, and is compared to the climate sensitivity calculated from equilibrium experiments with atmospheric CO₂ doubled from present day concentration. The calculations here using the model and palaeodata support a climate sensitivity of about 1 Wm^-2 K^-1 which is within the conventional range. Received: 8 February 1997 / Accepted: 4 June 1997     

Influence of dynamic vegetation on climate change arising from increasing CO<Subscript>2</Subscript>

A dynamic global vegetation model (DGVM) is coupled to an atmospheric general circulation model (AGCM) to investigate the influence of vegetation dynamics on climate change under conditions of global warming. The model results are largely in agreement with observations and the results of previous studies in terms of the present climate, present potential vegetation, present net primary productivity (NPP), and pre-industrial carbon budgets. The equilibrium state of climate properties are compared among pre-industrial, doubled, and quadrupled atmospheric CO₂ values using DGVM–AGCM and current AGCM with fixed vegetation to evaluate the influence of dynamic vegetation change. We also separated the contributions of temperature, precipitation and CO₂ fertilization on vegetation change. The results reveal an amplification of global warming climate sensitivity by 10% due to the inclusion of dynamic vegetation. The total effects of elevated CO₂ and climate change also lead to an increase in NPP and vegetation coverage globally. The reduction of albedo associated with this greening results in enhanced global warming. Our separation analysis indicates that temperature alters vegetation at high latitudes such as Siberia or Alaska, where there is a switch from tundra to forest. On the other hand, CO₂ fertilization provides the largest contribution to greening in arid/semi-arid region. Precipitation change did not cause any drastic vegetation shift.     

Sensitivity of transient eddies to climate change in the CCC general circulation model

Abstract

We use eddy life‐cycle simulations to evaluate the response of atmospheric transient eddies to a global warming caused by CO₂ doubling in the CCC general circulation model. In simulations using Northern Hemisphere winter conditions, transient waves attain larger kinetic energy and encompass a wider range of latitudes in the warmer climate. This behaviour contrasts with a previous investigation that used output from the NCAR and GFDL models. Our analysis indicates two primary factors for the difference between model responses: (1) a smaller change in the mid‐latitude temperature gradient in the CCC model, which allows (2) increased atmospheric water vapour in mid‐latitudes to catalyze a more rapidly evolving life‐cycle.