ABSTRACT
High‐resolution monthly temperature climatologies for Italy are presented. They are based on a dense and quality‐controlled observational dataset which includes 1484 stations and on three ...distinct approaches: multi‐linear regression with local improvements (MLRLI), an enhanced version of the model recently used for the Greater Alpine Region, regression kriging (RK), widely used in literature and, lastly, local weighted linear regression (LWLR) of temperature versus elevation, which may be considered more suitable for the complex orography characterizing the Italian territory.
Dataset and methods used both to check the station records and to get the 1961–1990 normals used for the climatologies are discussed. Advantages and shortcomings of the three approaches are investigated and the results are compared.
All three approaches lead to quite reasonable models of station temperature normals, with lowest errors in spring and autumn and highest errors in winter. The LWLR approach shows slightly better performances than the other two, with monthly leave‐one‐out estimated root mean square errors ranging from 0.74 °C (April and May) to 1.03 °C (December). Further evidence in its favour is the greater reliability of local approach in modelling the behaviour of the temperature‐elevation relationship in Italy's complex territory.
The comparison of the different climatologies is a very effective tool to understand the robustness of each approach. Moreover, the first two methods (MLRLI and RK) turn out to be important to tune the third one (LWLR), as they help not only to understand the relationship between temperature normals and some important physiographical variables (MLRLI) but also to study the decrease of station normals covariance with distance (RK).
Wheat is the third largest crop globally and an essential source of calories in human diets. Maintaining and increasing global wheat production is therefore strongly linked to food security. A large ...geographic variation in wheat yields across similar climates points to sizeable yield gaps in many nations, and indicates a regionally variable flexibility to increase wheat production. Wheat is particularly sensitive to a changing climate thus limiting management opportunities to enable (sustainable) intensification with potentially significant implications for future wheat production. We present a comprehensive global evaluation of future wheat yields and production under distinct Representative Concentration Pathways (RCPs) using the Environmental Policy Integrated Climate (EPIC) agro-ecosystem model. We project, in a geographically explicit manner, future wheat production pathways for rainfed and irrigated wheat systems. We explore agricultural management flexibility by quantifying the development of wheat yield potentials under current, rainfed, exploitable (given current irrigation infrastructure), and irrigated intensification levels. Globally, because of climate change, wheat production under conventional management (around the year 2000) would decrease across all RCPs by 37 to 52 and 54 to 103Mt in the 2050s and 2090s, respectively. However, the exploitable and potential production gap will stay above 350 and 580Mt, respectively, for all RCPs and time horizons, indicating that negative impacts of climate change can globally be offset by adequate intensification using currently existing irrigation infrastructure and nutrient additions. Future world wheat production on cropland already under cultivation can be increased by ~35% through intensified fertilization and ~50% through increased fertilization and extended irrigation, if sufficient water would be available. Significant potential can still be exploited, especially in rainfed wheat systems in Russia, Eastern Europe and North America.
•Assessment of global wheat production under Representative Concentration Pathways•Region-specific agricultural management flexibility to counteract climate impacts•Production with management as in 2000 would decrease by 54 to 103Mt in the 2090s.•Yet, the exploitable and potential production gap will stay above 350 and 580 Mt.
We compare the performance of several modes of variability across six US climate modeling groups, with a focus on identifying robust improvements in recent models (including those participating in ...the Coupled Model Intercomparison Project (CMIP) Phase 6) compared to previous versions. In particular, we examine the representation of the Madden-Julian Oscillation (MJO), the El Ni˜no/Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), the Quasi-Biennial Oscillation (QBO) in the tropical stratosphere and the dominant modes of extra-tropical variability, including the Southern Annular Mode (SAM), the Northern Annular Mode (NAM) (and the closely related North Atlantic Oscillation (NAO)), and the Pacific-North American Pattern (PNA). Where feasible, we explore the processes driving these improvements through the use of “intermediary” experiments that utilize model versions between CMIP3/5 and CMIP6 as well as targeted sensitivity experiments in which individual modeling parameters are altered. We find clear and systematic improvements in the MJO and QBO and in the teleconnection patterns associated with the PDO and ENSO. Some gains arise from better process representation, while others (e.g. the QBO) from higher resolution that allows for a greater range of interactions. Our results demonstrate that the incremental development processes in multiple climate model groups lead to more realistic simulations over time.
Ice clouds and falling snow are ubiquitous globally and play important roles in the Earth’s radiation budget and precipitation processes. Ice particle microphysical properties (e.g., size, habit and ...orientation) are not only influenced by ambient environment’s dynamic and thermodynamic conditions, but also intimately connect to the cloud radiative effects and particle fall speeds, which therefore impact up to the future climate projection and down to the details of the surface precipitation (e.g., onset-time, location, type and strength). Our previous work revealed that high-frequency Polarimetric radiance Difference (PD) from passive microwave sensors is a good indicator of the bulk aspect ratio of horizontally oriented ice particles that are often occur inside anvil clouds and/or stratiform precipitations. In this current work, we further investigate the dynamic/thermodynamic mechanisms and cloud/precipitation structures associated with ice-phase microphysics corresponding to different PD signals. In order to do so, collocated CloudSat radar (W-band) and Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM-DPR, Ku/Ka bands) observations as well as European Centre for Medium-Range Weather Forecasts (ECMWF) atmosphere background profiles are grouped according to the magnitude of PD for only stratiform precipitation and/or anvil cloud scenes. We found that horizontally-oriented snow aggregates or large snow particles are likely the major contributor to the high-PD signals at 166 GHz, while low-PD magnitudes can be attributed to small cloud ice, randomly oriented snow aggregates, riming snow or super-cooled water. Further, high (low) PD scenes are found to be associated with stronger (weaker) wind shear and higher (lower) ambient humidity, both of which help promote (prohibit) the growth of frozen particles and the organization of convective systems. An ensemble of squall line cases is studied at the end to demonstrate that the PD asymmetry in the leading and trailing edges of the deep convection line is closely tied to the anvil cloud and stratiform precipitation layers respectively, suggesting the potential usefulness of PD as a proxy of stratiform/convective precipitation flag, as well as a proxy of convection life stage.
Evidence-based responses to climate change by society require operational and sustained information including biophysical indicator systems that provide up-to-date measures of trends and patterns ...against historical baselines. Two key components linking anthropogenic climate change to impacts on socio-ecological systems are the periodic inter- and intra-annual variations in physical climate systems (seasonality) and in plant and animal life cycles (phenology). We describe a set of national indicators that reflect sub-seasonal to seasonal drivers and responses of terrestrial physical and biological systems to climate change and variability at the national scale. Proposed indicators and metrics include seasonality of surface climate conditions (e.g., frost and freeze dates and durations), seasonality of freeze/thaw in freshwater systems (e.g., timing of stream runoff and durations of lake/river ice), seasonality in ecosystem disturbances (e.g., wildfire season timing and duration), seasonality in vegetated land surfaces (e.g., green-up and brown-down of landscapes), and seasonality of organismal life-history stages (e.g., timings of bird migration). Recommended indicators have strong linkages to variable and changing climates, include abiotic and biotic responses and feedback mechanisms, and are sufficiently simple to facilitate communication to broad audiences and stakeholders interested in understanding and adapting to climate change.
Supercooled clouds substantially impact polar surface energy budgets but large-scale models often underestimate their occurrence, which motivates accurately establishing metrics of basic processes. ...An analysis of long-term measurements at Utqiaġvik, Alaska, and McMurdo Station, Antarctica, combines lidar-validated use of soundings to identify supercooled cloud layers and colocated ground-based profiling radar measurements to quantify cloud base precipitation. We find that more than 85 % (75 %) of sampled supercooled layers are precipitating over the Arctic (Antarctic) site, with more than 75 % (50 %) precipitating continuously to the surface. Such high frequencies can be reconciled with substantially lesser spaceborne estimates by considering differences in radar hydrometeor detection sensitivity. While ice precipitation into supercooled clouds from aloft is common, we also find that the great majority of supercooled cloud layers without ice falling into them are themselves continuously generating precipitation. Such sustained primary ice formation is consistent with continuous activation of immersion-mode ice nucleating particles (INPs), suggesting that supercooled cloud formation is a principal gateway to ice formation at temperatures greater than ~ −38 °C over polar regions. The prevalence of weak precipitation fluxes is also consistent with supercooled cloud longevity, and with well-observed and widely simulated case studies. An analysis of colocated microwave radiometer retrievals suggests that weak precipitation fluxes can be nonetheless consequential to moisture budgets for supercooled clouds owing to small liquid water paths. Finally, we suggest that these ground-based precipitation rate statistics offer valuable guidance for improving the representation of polar cloud processes in large-scale models.
ABSTRACT
High‐resolution monthly precipitation climatologies for Italy are presented. They are based on 1961–1990 precipitation normals obtained from a quality‐controlled dataset of 6134 stations ...covering the Italian territory and part of the Northern neighbouring regions. The climatologies are computed by means of two interpolation methods modelling the precipitation‐elevation relationship at a local level, more precisely a local weighted linear regression (LWLR) and a local regression kriging (RK) are performed. For both methods, local optimisations are also applied in order to improve model performance. Model results are compared with those provided by two other widely used interpolation methods which do not consider elevation in modelling precipitation distribution: ordinary kriging and inverse distance weighting. Even though all the four models produce quite reasonable results, LWLR and RK show the best agreement with the observed station normals and leave‐one‐out‐estimated mean absolute errors ranging from 5.1 mm (July) to 11 mm (November) for both models. Their better performances are even clearer when specific clusters of stations (e.g. high‐elevation sites) are considered. Even though LWLR and RK provide very similar results both at station and at grid point level, they show some peculiar features. In particular, LWLR is found to have a better extrapolation ability at high‐elevation sites when data density is high enough, while RK is more robust in performing extrapolation over areas with complex orography and scarce data coverage, where LWLR may provide unrealistic precipitation values. However, by means of prediction intervals, LWLR provides a more straightforward approach to quantify the model uncertainty at any point of the study domain, which helps to identify the areas mainly affected by model instability. LWLR and RK high‐resolution climatologies exhibit a very heterogeneous and seasonal‐dependent precipitation distribution throughout the domain and allow to identify the main climatic zones of Italy.
The paper presents high‐resolution monthly precipitation climatologies for Italy. They are computed by means of two interpolation methods modelling the precipitation‐elevation relationship at a local level: local weighted linear regression (LWLR) and regression kriging (RK). The monthly errors turn out to range from 5 mm to 11 mm for both models. LWLR shows a better extrapolation ability at high‐elevated sites, while RK is preferable over areas with complex orography and scarce data coverage, where LWLR may provide unrealistic precipitation values.
Over the last 20 years, developments in climatology have provided an amazing array of explanations for the pattern of world climates. This textbook, first published in 2006, examines the earth's ...climate systems in light of this incredible growth in data availability, data retrieval systems, and satellite and computer applications. It considers regional climate anomalies, developments in teleconnections, unusual sequences of recent climate change, and human impacts upon the climate system. The physical climate forms the main part of the book, but it also considers social and economic aspects of the global climate system. This textbook has been derived from the authors' extensive experience of teaching climatology and atmospheric science. Each chapter contains an essay by a specialist in the field to enhance the understanding of selected topics. An extensive bibliography is included and lists of websites for further study. This textbook will be invaluable to advanced students of climatology and atmospheric science.
A common feature of polar liquid-bearing clouds (LBCs) is radiatively-driven turbulence, which may variously alter cloud lifecycle via vertical mixing, droplet activation, and subsequent feedbacks. ...However, polar LBCs are commonly initiated under stable, non-turbulent conditions. Using long-term data from the North Slope of Alaska and McMurdo, Antarctica, we show that non-turbulent conditions prevail in ~25% of detected LBCs, surmised to be preferentially early in their lifecycle. We conclude that non-turbulent LBCs are likely common over the polar regions owing primarily to atmospheric temperature and stability. Such stable environments are known to support gravity wave activity. Using large-eddy simulations we find that short to intermediate period gravity waves may catalyze turbulence formation when aerosol particles available for activation are sufficiently small. We posit that the frequent occurrence of non-turbulent LBCs over the polar regions has implications for polar aerosol-cloud interactions and their parameterization in large-scale models.
Long and temporally consistent rainfall time series are essential in climate analyses and applications. Rainfall data from station observations are inadequate over many parts of the world due to ...sparse or non‐existent observation networks, or limited reporting of gauge observations. As a result, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. However, many satellite‐based rainfall products with long time series suffer from coarse spatial and temporal resolutions and inhomogeneities caused by variations in satellite inputs. There are some satellite rainfall products with reasonably consistent time series, but they are often limited to specific geographic areas. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite‐based rainfall products with relatively high spatial and temporal resolutions and quasi‐global coverage. In this study, CHIRP and CHIRPS were evaluated over East Africa at daily, dekadal (10‐day) and monthly time‐scales. The evaluation was done by comparing the satellite products with rain‐gauge data from about 1,200 stations. The CHIRP and CHIRPS products were also compared with two similar operational satellite rainfall products: the African Rainfall Climatology version 2 (ARC2) and the Tropical Applications of Meteorology using Satellite data (TAMSAT). The results show that both CHIRP and CHIRPS products are significantly better than ARC2 with higher skill and low or no bias. These products were also found to be slightly better than the latest version of the TAMSAT product at dekadal and monthly time‐scales, while TAMSAT performed better at the daily time‐scale. The performance of the different satellite products exhibits high spatial variability with weak performances over coastal and mountainous regions.
The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are evaluated over East Africa by comparing with rain‐gauge data from about 1,200 stations as well as with other similar satellite products (the African Rainfall Climatology version 2 (ARC2) and the Tropical Applications of Meteorology using Satellite data (TAMSAT)). The above figure compares the skill (Eff) for different satellite products. The grey scale in the background is elevations in metres.
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