Regional climate models (RCMs) primarily represent physical components of the climate system, omitting vegetation dynamics, ecosystem biogeochemistry and their associated feedbacks. To account for such feedbacks, we implemented a novel plant individual-based vegetation dynamics-ecosystem biogeochemistry scheme within the RCA3 RCM. Variations in leaf area index (LAI) of seven plant functional type (PFTs) in response to physical forcing and evolving vegetation state feed back to climate via adjustments in surface energy fluxes and surface properties. In an ERA-40-driven simulation over Europe, the model reproduces the recent past climate with comparable accuracy to the standard RCM. Large-scale patterns of LAI, net primary production and vegetation composition were comparable with observations, although winter LAI was systematically overestimated compared to satellite estimates. Analysis of the ERA-40 simulation and an A1B climate-change simulation revealed considerable covariation among dynamic variables of the physical climate and vegetation. At a Mediterranean site, periodic soil water limitation led to fluctuations in leaf cover and a likely positive feedback to near-surface temperature. At an alpine site, rising temperatures led to forest advance onto tundra areas, reducing albedo and effecting a likely positive feedback on temperature. Climate—vegetation coupling was less pronounced but still apparent at intermediate temperate and boreal sites.
The Rossby Centre Regional Climate Model (RCA3) and the hydrological model HBV were linked to assess climate change impacts on water resources in the Pungwe basin until 2050. RCA3 was capable of simulating the most important aspects of the climate for a control period at the regional scale. At the subbasin scale, additional scaling was needed. Three climate change experiments using ECHAM4-A2, B2 and CCSM3-B2 as input to RCA3 were carried out. According to the simulations annual rainfall in 2050 would be reduced by approximately 10% with increasing interannual variability of rainfall and dry season river flow and later onset of the rainy season. The ECHAM4-A2 driven experiment did also indicate a slight increase of high flows. If the results indeed reflect the future, they will worsen the already critical situation for water resources, regarding both floods and droughts. Uncertainties, however in the downscaled scenarios make it difficult to prioritize adaptation options. This calls for inclusion of more climate change experiments, in an ensemble of climate scenarios possibly by using a combination of dynamical and statistical downscaling of general circulation models, as well as extending the simulations to 2100 to further ensure robustness of the signal.
In order to assess the potential of regional climate models to be used to project future weather events, a first step is to study the regional model forced by actual weather, or more precisely by reanalysis of weather data. In this paper we investigate how well the Norwegian regional model HIRHAM, forced by ERA-40 reanalysis data, compares to observed precipitation data from the Norwegian Meteorological Institute over Norwegian mainland. This paper aims to show how standard methods of statistical testing may be used to assess dynamic downscaling. Methods considered are the Kolmogorov—Smirnov two-sample test, a Fisher exact test for equality of quantiles, an Extreme Value Theory test, where equality of the 1-yr return levels are tested, and equality of wet-day frequency. All tests are performed seasonally. The regional model is skillful in describing the lower quartile of the precipitation distribution, but underestimates higher levels of precipitation. Our results indicate that the regional model has too many but too small rain events for all seasons
The negative impacts of surface ozone (O-3) on vegetation are determined by external exposure, leaf gas exchange and plant antioxidant defence capacity, all dependent on climate and CO2 concentrations. In this study the influence of climate change on simulated stomatal O-3 uptake of a generic crop and a generic deciduous tree at ten European sites was investigated, using the LRTAP Mapping Manual stomatal flux model. O-3 concentrations are calculated by a chemistry transport model (MATCH) for three 30-yr time-windows (1961-1990, 2021-2050, 2071-2100), with constant precursor emissions and meteorology from a regional climate model (RCA3). Despite substantially increased modelled future O-3 concentrations in central and southern Europe, the flux-based risk for O-3 damage to vegetation is predicted to remain unchanged or decrease at most sites, mainly as a result of projected reductions in stomatal conductance under rising CO2 concentrations. Drier conditions in southern Europe are also important for this result. At northern latitudes, the current parameterisation of the stomatal conductance model suggest O-3 uptake to be mainly limited by temperature. This study demonstrates the importance of accounting for the influences by climate and CO2 on stomatal O-3 uptake, and of developing their representation in models, for risk assessment involving climate change.
This paper describes the third full release of the Rossby Centre Regional Climate model (RCA3), with an emphasis on changes compared to earlier versions, in particular the introduction of a new tiled land-surface scheme. The model performance over Europe when driven at the boundaries by ERA40 reanalysis is discussed and systematic biases identified. This discussion is performed for key near-surface variables, such as temperature, precipitation, wind speed and snow amounts at both seasonal and daily timescales. An analysis of simulated clouds and surface turbulent and radiation fluxes is also made, to understand the causes of the identified biases. RCA3 shows equally good, or better, correspondence to observations than previous model versions at both analysed timescales. The primary model bias relates to an underestimate of the diurnal surface temperature range over Northern Europe, which maximizes in summer. This error is mainly linked to an overestimate of soil heat flux. It is shown that the introduction of an organic soil component reduces the error significantly. During the summer season, precipitation and surface evaporation are both overestimated over Northern Europe, whereas for most other regions and seasons precipitation and surface turbulent fluxes are well simulated.
The effect of a warmer climate on the properties of extratropical cyclones is investigated using simulations of the ECHAM5 global climate model at resolutions of T213 (60 km) and T319 (40 km). Two periods representative of the end of the 20th and 21st centuries are investigated using the IPCC A1B scenario. The focus of the paper is on precipitation for the NH summer and winter seasons, however results from vorticity and winds are also presented. Similar number of events are identified at both resolutions. There are, however, a greater number of extreme precipitation events in the higher resolution run. The difference between maximum intensity distributions is shown to be statistically significant using a Kolmogorov—Smirnov test. A generalized Pareto distribution is used to analyse changes in extreme precipitation and wind events. In both resolutions, there is an increase in the number of extreme precipitation events in a warmer climate for all seasons, together with a reduction in return period. This is not associated with any increased vertical velocity, or with any increase in wind intensity in the winter and spring. However, there is an increase in wind extremes in the summer and autumn associated with tropical cyclones migrating into the extratropics.
We study the feasibility of using the singular vector technique to create initial condition perturbations for shortrange ensemble prediction systems (SREPS) focussing on predictability of severe local storms and in particular deep convection. For this a newfinal time semi-norm based on the convective available potential energy (CAPE) is introduced. We compare singular vectors using the CAPE-norm with SVs using the more common total energy (TE) norm for a 2-week summer period in 2007, which includes a case of mesoscale extreme rainfall in the south west of Finland. The CAPE singular vectors perturb the CAPE field by increasing the specific humidity and temperature of the parcel and increase the lapse rate above the parcel in the lower troposphere consistent with physical considerations. The CAPE-SVs are situated in the lower troposphere. This in contrast to TE-SVs with short optimization times which predominantly remain in the high troposphere. By examining the time evolution of the CAPE singular values we observe that the convective event in the south west of Finland is clearly associated with high CAPE singular values.
Implementations of incremental variational data assimilation require the iterative minimization of a series of linear least-squares cost functions. The accuracy and speed with which these linear minimization problems can be solved is determined by the condition number of the Hessian of the problem. In this study, we examine how different components of the assimilation system influence this condition number. Theoretical bounds on the condition number for a single parameter system are presented and used to predict how the condition number is affected by the observation distribution and accuracy and by the specified lengthscales in the background error covariance matrix. The theoretical results are verified in the Met Office variational data assimilation system, using both pseudo-observations and real data.
A number of regional Arctic dynamical downscaling scenario experiments are performed with the Rossby Centre Atmosphere Ocean climate model. The simulations are based on IPCC AR4 scenario simulations with the global coupled models BCCR2.0 and ECHAM5/MPI-OM and differ in the surface salinity treatment and lateral boundary conditions.Compared to the global runs, the regional simulations show a warmer Arctic, which agrees better to ERA-40 reanalysis data in the 20th century, and a slightly smaller trend in the 21st century. The ECHAM-forced runs show several periods with rapid summer sea ice reductions and partial recovery thereafter. Summer sea ice disappears for the first time around 2040.The large-scale change patterns of sea level pressure (SLP) and air temperature in the regional simulations are mainly dominated by the forcing of the global models but locally significant modifications occur. Pressure is reduced by 1-3 hPa and air temperature increases by 2-4 K in most Arctic regions and up to 10 K where winter sea ice disappears.The largely reduced Arctic sea ice area leads to increased atmospheric variability and more extremes in winter SLP and summer air temperature.
The preparation of perturbed initial conditions to initialize an ensemble of numerical weather forecasts is a crucial task in current ensemble prediction systems (EPSs). Perturbations are added in the places where they are expected to grow faster, in order to provide an envelope of uncertainty along with the deterministic forecast. This work analyses the influence of large-scale spatial patterns on the growth of small perturbations. Therefore, we compare Lyapunov vector (LV) definitions, used in the initialization of state-of-the-art EPSs, with the so-called characteristic LVs. We test the dynamical behaviour of these LVs in the two-scale Lorenz’96 system. We find that the commonly used definitions of LVs include non-intrinsic and spurious effects due to their mutual orthogonality. We also find that the spatial locations where the small-scale perturbations are growing are ‘quantized’ by the large-scale pattern. This ‘quantization’ enhances the artificial disposition of the LVs, which is only avoided using the characteristic LVs, an unambiguous basis which may also be of great use in realistic models for assessing or initializing EPSs.
Severe weather is frequently associated with polar lows over ice-free waters during Arctic winter. We propose a high-resolution, limited area ensemble prediction system (EPS) to enable early warnings of such events. The system (UMEPS) employs the UK Met Office non-hydrostatic Unified Model at 4-km resolution to downscale the 21 ensemble members of the HIRLAM-based LAMEPS run twice daily with 12-km resolution at met. no since February 2008. LAMEPS includes a 3DVar-based control forecast, although initial and boundary perturbations are taken from a version of EPS at ECMWF with perturbations targeted to Northern Europe (TEPS). The added value of UMEPS is evaluated for one polar low during the March 2008 IPY-THORPEX campaign. Forecast probabilities, pseudo-satellite pictures, polar low tracks and strike probability maps are compared with observational data. The forecast quality depends crucially on the size and location of the UMEPS domain. When sufficiently large, the influence from data imposed at the lateral boundaries can be reduced by a careful domain selection. The results are sensitive to the model's parameterizations of physical processes. Although preliminary, this study indicates that with a short-range, high-resolution UMEPS, potentially valuable warnings of extreme weather can be given up to 2 days in advance.
The common derivation of Rossby waves is based on the quasi-geostrophic approximation. A simple non-harmonic approximation for extratropical Rossby waves on the sphere is proposed, in which the meridional coordinate is a parameter instead of a continuous variable. It is shown that, in contrast to the quasi-geostrophic solution, to first order the meridional structure of these non-harmonic Rossby waves becomes irrelevant for determining the dispersion relation in this theory. The proposed approximation accurately reproduces numerical results obtained from runs of an ocean general circulation model initiated from several initial meridional structures and captures the latitudinal dependence of the phase speed of these waves. The proposed theory yields explicit expressions for the dispersion relation and for the meridional structure of the waves.
We obtained linear solutions for the frequency and amplitude modulations of the El Ni˜no-Southern Oscillation (ENSO) by the annual cycle using a modified harmonic oscillator equation. The frequency modulation by the annual cycle was capable of changing the ENSO phases and dominant frequency, but could not modify the ENSO amplitude. On the other hand, the amplitude modulation by the annual cycle intensifies the ENSO variability and also induces seasonal amplitude locking. The intensification rate of the ENSO amplitude with respect to the annual cycle becomes less sensitive in low-frequency regime of ENSO.
The ensemble Kalman filter (EnKF) is susceptible to losing track of observations, or ‘diverging’, when applied to large chaotic systems such as atmospheric and ocean models. Past studies have demonstrated the adverse impact of sampling error during the filter’s update step. We examine how system dynamics affect EnKF performance, and whether the absence of certain dynamic features in the ensemble may lead to divergence. The EnKF is applied to a simple chaotic model, and ensembles are checked against singular vectors of the tangent linear model, corresponding to short-term growth and Lyapunov vectors, corresponding to long-term growth. Results show that the ensemble strongly aligns itself with the subspace spanned by unstable Lyapunov vectors. Furthermore, the filter avoids divergence only if the full linearized long-term unstable subspace is spanned. However, short-term dynamics also become important as nonlinearity in the system increases. Non-linear movement prevents errors in the long-term stable subspace from decaying indefinitely. If these errors then undergo linear intermittent growth, a small ensemble may fail to properly represent all important modes, causing filter divergence. A combination of long and short-term growth dynamics are thus critical to EnKF performance. These findings can help in developing practical robust filters based on model dynamics.
Conditional non-linear optimal perturbation (CNOP), which is a natural extension of the linear singular vector into the non-linear regime, has been suggested to identify data-sensitive regions in the adaptive observation strategy. CNOP is the global maximum of a cost function, whereas, local CNOP is the local maximum of the cost function if the local maximum exists. The potential application of CNOPs to tropical cyclone adaptive observation is researched. The CNOPs and the first singular vector (FSV) are numerically obtained by a spectral projected gradient algorithm with the Weather Research Forecasting (WRF) model. This paper examines two tropical cyclone cases, a fast straight moving typhoon Matsa (2005) and a slow moving recurving typhoon Shanshan (2006). The CNOPs and FSVs are obtained using the norms of background error at initial time and total dry energy at final time with a 36-h optimization time interval. The spatial structures of CNOPs, their energies, non-linear evolutions and impacts on track simulations are compared with those of the FSVs. The results show that both the CNOPs and the FSVs are localized, and evolve into the verification area at the final time with the upscale growth of perturbations. However, the CNOPs are different from the FSVs in spatial patterns, wind maximum distribution, growth rate of energy and impact on track simulation. Compared to FSV, CNOP and local CNOP have greater impact on the forecast in the verification region at the final time in terms of total energy, and have larger, at least similar impact on track simulation too. This indicates the CNOP method with constraint of the norm of background error at initial time and total energy norm at final time is a reasonable candidate in tropical cyclone adaptive observation. Therefore, both CNOP and local CNOP are suggested to be considered in tropical cyclone adaptive observation.
We have examined the atmospheric water cycle of both Polar Regions, polewards of 60◦N and 60◦S, using the ERAInterim reanalysis and high-resolution simulations with the ECHAM5 model for both the present and future climate based on the IPCC, A1B scenario.The annual precipitation in ERA-Interim amounts to ∼17000 km3 and is more or less the same in the Arctic and the Antarctic, but it is composed differently. In the Arctic the annual evaporation is ∼8000 km3 but ∼3000 km3 less in the Antarctica where the net horizontal transport is correspondingly larger. The net water transport of the model is more intense than in ERA-Interim, in the Arctic the difference is 2.5% and in the Antarctic it is 6.2%. Precipitation and net horizontal transport in the Arctic has a maximum in August and September. Evaporation peaks in June and July. The seasonal cycle is similar in Antarctica with the highest precipitation in the austral autumn. The largest net transport occurs at the end of the major extra-tropical storm tracks in the Northern Hemisphere such as the eastern Pacific and eastern north Atlantic.The variability of themodel is virtually identical to that of the re-analysis and there are no changes in variability between the present climate and the climate at the end of the 21st century when normalized with the higher level of moisture. The changes from year to year are substantial with the 20- and 30-year records being generally too short to identify robust trends in the hydrological cycle.In the A1B climate scenario the strength of the water cycle increases by some 25% in the Arctic and by 19% in the Antarctica, as measured by annual precipitation. The increase in the net horizontal transport is 29% and 22%, respectively, and the increase in evaporation correspondingly less. The net transport follows closely the Clausius—Clapeyron relation. There is a minor change in the annual cycle of the Arctic atmospheric water cycle with the maximum transport and precipitation occurring later in the year.There is a small imbalance of some 4–6% between the net transport and precipitation minus evaporation. We suggest that this is mainly due to the fact that the transport is calculated from instantaneous six hourly data while precipitation and evaporation is accumulated over a 6-h period. The residual difference is proportionally similar for all experiments and hardly varies from year to year.
A forward operator for Global Positioning System (GPS) slant total delay (STD) data and its adjoint were implemented into the Mesoscale Model version 5 (MM5) 4DVAR system to investigate its impact on quantitative precipitation forecasting (QPF). An operational forecast system was set up providing two forecasts per day, one driven by ECMWF forecasts only and the other additionally by 4DVAR of GPS STD data.The investigation of statistics for August 2007 demonstrated a positive impact on the representation of the water-vapour field and the diurnal cycle of precipitation in southwest Germany. The spread of observation-minus-model departures was strongly reduced during the first 6 h of the simulations. As compared to the control simulation, the averaged diurnal cycle of precipitation in the 4DVAR integration was closer to observations in spite of the limitations of the 4DVAR system. Especially promising is the almost complete removal of the spin-up at the beginning of the simulation.This study not only demonstrates the potential of water vapour data assimilation for nowcasting and short-range QPF. It also suggests that improved GPS retrievals and extended networks are important to further improve the forecast performance and demonstrates the potential to apply observation operators for model verification.
