Spatial and temporal characteristics of summer precipitation over Central Europe in a suite of high-resolution climate models

High-impact, localized intense rainfall episodes represent a major socio-economic problem for societies worldwide, and at the same time these events are notoriously difficult to simulate properly in climate models. Here, the authors investigate how horizontal resolution and model formulation influence this issue by applying the HARMONIE regional climate model (HCLIM) with three different setups; two using convection parameterization at 15 and 6.25 km horizontal resolution (the latter within the “grey-zone” scale), with lateral boundary conditions provided by ERA-Interim reanalysis and integrated over a pan-European domain, and one with explicit convection at 2 km resolution (HCLIM2) over the Alpine region driven by the 15 km model. Seven summer seasons were sampled and validated against two high-resolution observational data sets. All HCLIM versions underestimate the number of dry days and hours by 20-40%, and overestimate precipitation over the Alpine ridge. Also, only modest added value were found of “grey-zone” resolution. However, the single most important outcome is the substantial added value in HCLIM2 compared to the coarser model versions at sub-daily time scales. It better captures the local-to-regional spatial patterns of precipitation reflecting a more realistic representation of the local and meso-scale dynamics. Further, the duration and spatial frequency of precipitation events, as well as extremes, are closer to observations. These characteristics are key ingredients in heavy rainfall events and associated flash floods, and the outstanding results using HCLIM in convection-permitting setting are convincing and encourage further use of the model to study changes in such events in changing climates.

Regional climate change and harmful algal blooms in the northeast Atlantic

We investigated long-term spatial variability in a number of Harmful Algal Blooms (HABs) in the northeast Atlantic and North Sea using data from the Continuous Plankton Recorder. Over the last four decades. some dinoflagellate taxa showed pronounced variation in the south and east of the North Sea, with the most significant increases being restricted to the adjacent waters off Norway. There was also a general decrease along the eastern coast of the United Kingdom. The most prominent feature in the interannual bloom frequencies over the last four decades was the anomalously high values recorded in the late 1980s in the northern and central North Sea areas. The only mesoscale area in the northeast Atlantic to show a significant increase in bloom formation over the last decade was the Norwegian coastal region. The changing spatial patterns of HAB taxa and the frequency of bloom formation are discussed in relation to regional climate change, in particular, changes in temperature, salinity, and the North Atlantic Oscillation (NAO). Areas highly vulnerable to the effects of regional climate change on HABs are Norwegian coastal waters and the Skagerrak. Other vulnerable areas include Danish coastal waters, and to a lesser extent, the German and Dutch Bight and the northern Irish Sea. Quite apart from eutrophication, our results give a preview of what might happen to certain HAB genera under changing climatic conditions in temperate environments and their responses to variability of climate oscillations Such as the NAO.

Regional climate services illustrated with experiences from Northern Europe

In this article, we discuss the advisory capacity of climate science for political and societal decisions. To provide options, open up perspectives and enhance the understanding for the dynamics of climate is a task we name climate services. After a general discussion, experiences of providing these services on a regional and local scale – Northern Germany, the metropolitan area of Hamburg and the Baltic Sea Basin – during the last few years is reviewed.Key components of this regional climate service is the establishment of a regional climate office, of regional IPCC-like assessments of knowledge about regional and local climate change, and detailed homogeneous data sets describing changing weather statistics (i.e., climate) in past decades and in perspectives for the next several decades.

Regional climate change impacts on wild animals' living territory in Central Europe

In this paper the projected future impact of climate change has been analyzed for the quality of living conditions of the European terrestrial vertebrates (amphibians, reptiles, birds, mammals) in the Carpathian Basin. According to the climate scenarios, warmer and drier climatic conditions are likely to occur in the Carpathian Basin by end of this century. Simultaneous analysis of climate parameters, climate simulations and animal range datasets enables us to evaluate the vulnerability of different European species to regional warming and climate change. The spatial climate analogy technique is used to analyze the estimated rapid change of the wild animals’ habitats and their northward migration. For the reference climate data of Debrecen is considered, and three spatial analogue regions are compared. The results suggest that generally a significant decline in habitats is very likely for most of the analyzed animal groups by the end of the 21st century. The largest rate of decline is estimated for birds. However, living conditions for reptiles may improve in the future due to the warmer and drier climatic conditions, which are favourable for these species.

Regional climate gradients in precipitation and temperature in response to climate teleconnections in the Greater Everglades ecosystem of South Florida

Precipitation and temperature in Florida responds to climate teleconnections from both the Pacific and Atlantic regions. In this region south of Lake Okeechobee, encompassing NWS Climate Divisions 5, 6, and 7, modern movement of surface waters are managed by the South Florida Water Management District and the US Army Corps of Engineers for flood control, water supply, and Everglades restoration within the constraints of the climatic variability of precipitation and evaporation. Despite relatively narrow, low-relief, but multi-purposed land separating the Atlantic Ocean from the Gulf of Mexico, South Florida has patterns of precipitation and temperature that vary substantially on spatial scales of 101–102 km. Here we explore statistically significant linkages to precipitation and temperature that vary seasonally and over small spatial scales with El Niño-Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO), and the Pacific Decadal Oscillation (PDO). Over the period from 1952 to 2005, ENSO teleconnections exhibited the strongest influence on seasonal precipitation. The Multivariate ENSO Index was positively correlated with winter (dry season) precipitation and explained up to 34 % of dry season precipitation variability along the southwest Florida coast. The AMO was the most influential of these teleconnections during the summer (wet season), with significant positive correlations to South Florida precipitation. These relationships with modern climate parameters have implications for paleoclimatological and paleoecological reconstructions, and future climate predictions from the Greater Everglades system.

Diatom-based paleolimnological reconstruction of regional climate and local land-use change from a protected sinkhole lake in southern Florida, USA

Despite their sensitivity to climate variability, few of the abundant sinkhole lakes of Florida have been the subject of paleolimnological studies to discern patterns of change in aquatic communities and link them to climate drivers. However, deep sinkhole lakes can contain highly resolved paleolimnological records that can be used to track long-term climate variability and its interaction with effects of land-use change. In order to understand how limnological changes were regulated by regional climate variability and further modified by local land-use change in south Florida, we explored diatom assemblage variability over centennial and semi-decadal time scales in an ~11,000-yr and a ~150-yr sediment core extracted from a 21-m deep sinkhole lake, Lake Annie, on the protected property of Archbold Biological Station. We linked variance in diatom assemblage structure to changes in water total phosphorus, color, and pH using diatom-based transfer functions. Reconstructions suggest the sinkhole depression contained a small, acidic, oligotrophic pond ~11000–7000 cal yr BP that gradually deepened to form a humic lake by ~4000 cal yr BP, coinciding with the onset of modern precipitation regimes and the stabilization of sea-level indicated by corresponding palynological records. The lake then contained stable, acidophilous planktonic and benthic algal communities for several thousand years. In the early AD 1900s, that community shifted to one diagnostic of an even lower pH (~5.6), likely resulting from acid precipitation. Further transitions over the past 25 yr reflect recovery from acidification and intensified sensitivity to climate variability caused by enhanced watershed runoff from small drainage ditches dug during the mid-twentieth Century on the surrounding property.

Stable oxygen isotopes in irish oaks: potential for reconstructing local and regional climate

The long Irish oak tree-ring chronology, developed for archaeological dating and radiocarbon calibration, is the longest of any in northwest maritime Europe, spanning most of the Holocene (7,272 years). Unfortunately, the rings widths do not carry a strong climate signal and the record hasnever been satisfactorily applied for dendroclimatic reconstruction. This pilot study explores the potential for extracting a climate signal from Irish oaks by comparing the stable oxygen isotopes ratios from 10 oak tree cores (Quercus robur and Quercus petraea L.) collected across the Armagh region of NE Ireland with local and regional climatic and stable isotopic data. Statistically significant correlations between isotope ratios and the amount of summer precipitation (r = -0.44) point to the isotopic composition of summer rainfall as the dominant signal. Including the Armagh data into an extended regional oxygen isotope series did not reduce the correlation coefficient with regional precipitation (r = -0.68, p < 0.01). Correlations of this magnitude in dendro-hydroclimatology are typically restricted to trees growing at their ecological limits. This research suggests that there is considerable potential for including living trees and ancient timbers from Ireland into a regional composite to reconstruct the summer hydroclimate of Britain and Ireland.

Modeling and Mapping Golden-winged Warbler Abundance to Improve Regional Conservation Strategies

Conservation planning requires identifying pertinent habitat factors and locating geographic locations where land management may improve habitat conditions for high priority species. I derived habitat models and mapped predicted abundance for the Golden-winged Warbler (Vermivora chrysoptera), a species of high conservation concern, using bird counts, environmental variables, and hierarchical models applied at multiple spatial scales. My aim was to understand habitat associations at multiple spatial scales and create a predictive abundance map for purposes of conservation planning for the Golden-winged Warbler. My models indicated a substantial influence of landscape conditions, including strong positive associations with total forest composition within the landscape. However, many of the associations I observed were counter to reported associations at finer spatial extents; for instance, I found Golden-winged Warblers negatively associated with several measures of edge habitat. No single spatial scale dominated, indicating that this species is responding to factors at multiple spatial scales. I found Golden-winged Warbler abundance was negatively related with Blue-winged Warbler (Vermivora cyanoptera) abundance. I also observed a north-south spatial trend suggestive of a regional climate effect that was not previously noted for this species. The map of predicted abundance indicated a large area of concentrated abundance in west-central Wisconsin, with smaller areas of high abundance along the northern periphery of the Prairie Hardwood Transition. This map of predicted abundance compared favorably with independent evaluation data sets and can thus be used to inform regional planning efforts devoted to conserving this species.

Research priorities in observing and modeling urban weather and climate

In 2007, the world reached the unprecedented milestone of half of its people living in cities, and that proportion is projected to be 60% in 2030. The combined effect of global climate change and rapid urban growth, accompanied by economic and industrial development, will likely make city residents more vulnerable to a number of urban environmental problems, including extreme weather and climate conditions, sea-level rise, poor public health and air quality, atmospheric transport of accidental or intentional releases of toxic material, and limited water resources. One fundamental aspect of predicting the future risks and defining mitigation strategies is to understand the weather and regional climate affected by cities. For this reason, dozens of researchers from many disciplines and nations attended the Urban Weather and Climate Workshop.1 Twenty-five students from Chinese universities and institutes also took part. The presentations by the workshop's participants span a wide range of topics, from the interaction between the urban climate and energy consumption in climate-change environments to the impact of urban areas on storms and local circulations, and from the impact of urbanization on the hydrological cycle to air quality and weather prediction.

Modeling the Impacts of Climate Change on Phytogeographical Units. A Case Study of the Moesz Line

Regional climate models (RCMs) provide reliable climatic predictions for the next 90 years with high horizontal and temporal resolution. In the 21st century northward latitudinal and upward altitudinal shift of the distribution of plant species and phytogeographical units is expected. It is discussed how the modeling of phytogeographical unit can be reduced to modeling plant distributions. Predicted shift of the Moesz line is studied as case study (with three different modeling approaches) using 36 parameters of REMO regional climate data-set, ArcGIS geographic information software, and periods of 1961-1990 (reference period), 2011-2040, and 2041-2070. The disadvantages of this relatively simple climate envelope modeling (CEM) approach are then discussed and several ways of model improvement are suggested. Some statistical and artificial intelligence (AI) methods (logistic regression, cluster analysis and other clustering methods, decision tree, evolutionary algorithm, artificial neural network) are able to provide development of the model. Among them artificial neural networks (ANN) seems to be the most suitable algorithm for this purpose, which provides a black box method for distribution modeling.

The effect of climate change on the potential distribution of the European Phlebotomus species and the parasite Leishmania infantum in 2011-2070. A climate envelope modeling approach

Aims: In the Mediterranean areas of Europe, leishmanisasis is one of the most emerging vector-borne diseases. Members of genus Phlebotomus are the primary vectors of the genus Leishmania. To track the human health effect of climate change it is a very important interdisciplinary question to study whether the climatic requirements and geographical distribution of the vectors of human pathogen organisms correlate with each other. Our study intended to explore the potential effects of ongoing climate change, in particular through a potential upward altitudinal and latitudinal shift of the distribution of the parasite Leishmania infantum, its vectors Phlebotomus ariasi, P. neglectus, P. perfiliewi, P. perniciosus, and P. tobbi, and some other sandfly species: P. papatasi, P. sergenti, and P. similis. Methods: By using a climate envelope modelling (CEM) method we modelled the current and future (2011-2070) potential distribution of 8 European sandfly species and L. infantum based on the current distribution using the REMO regional climate model. Results: We found that by the end of the 2060’s most parts of Western Europe can be colonized by sandfly species, mostly by P. ariasi and P. pernicosus. P. ariasi showed the greatest potential northward expansion. For all the studied vectors of L. infantum the entire Mediterranean Basin and South-Eastern Europe seemed to be suitable. L. infantum can affect the Eastern Mediterranean, without notable northward expansion. Our model resulted 1 to 2 months prolongation of the potentially active period of P. neglectus P. papatasi and P. perniciosus for the 2060’s in Southern Hungary. Conclusion: Our findings confirm the concerns that leishmanisais can become a real hazard for the major part of the European population to the end of the 21th century and the Carpathian Basin is a particularly vulnerable area.

Coupled atmosphere-biophysics-hydrology models for environmental modeling

The formulation and implementation of LEAF-2, the Land Ecosystem–Atmosphere Feedback model, which comprises the representation of land–surface processes in the Regional Atmospheric Modeling System (RAMS), is described. LEAF-2 is a prognostic model for the temperature and water content of soil, snow cover, vegetation, and canopy air, and includes turbulent and radiative exchanges between these components and with the atmosphere. Subdivision of a RAMS surface grid cell into multiple areas of distinct land-use types is allowed, with each subgrid area, or patch, containing its own LEAF-2 model, and each patch interacts with the overlying atmospheric column with a weight proportional to its fractional area in the grid cell. A description is also given of TOPMODEL, a land hydrology model that represents surface and subsurface downslope lateral transport of groundwater. Details of the incorporation of a modified form of TOPMODEL into LEAF-2 are presented. Sensitivity tests of the coupled system are presented that demonstrate the potential importance of the patch representation and of lateral water transport in idealized model simulations. Independent studies that have applied LEAF-2 and verified its performance against observational data are cited. Linkage of RAMS and TOPMODEL through LEAF-2 creates a modeling system that can be used to explore the coupled atmosphere–biophysical–hydrologic response to altered climate forcing at local watershed and regional basin scales.

Toward seamless prediction: calibration of climate change projections using seasonal forecasts

The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979– 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.

Sensitivity of simulated regional Arctic climate to the choice of coupled model domain

The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis). Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the North Pacific area into the coupled system drastically changes the Arctic climate variability to a point where the Arctic Oscillation becomes an ‘internal mode’ of variability and correlations of year-to-year variability with observational data vanish. In line with previous studies, our simulations provide evidence that Arctic sea ice export is mainly due to ‘internal variability’ within the Arctic region. We conclude that the choice of model domains should be based on physical knowledge of the atmospheric and oceanic processes and not on ‘geographic’ reasons. This is particularly the case for areas like the Arctic, which has very complex feedbacks between components of the regional climate system.