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Since 1987, this paper has presented the yearly report of the meteorological observations at the Geophysical Observatory of Modena and Reggio Emilia University, which is located inside the eastern tower of the Dukes' Palace of Modena. The Observatory was founded the 26th January 1826 and ever since its instruments have regularly recorded data. For the year 2015, we present a summary of the annual average values, total and extreme weather of the main parameters, plots with annual and monthly trends of several parameters compared with average climatological values. In addition, "the extremes of 2015", i.e. the average and extreme values of all data collected by the Observatory and at the meteorological stations "Campus DIEF", located in the Department of Engineering in Modena, and at the Campus San Lazzaro in Reggio Emilia are presented. In 2015, there were also anomalies, in line with climate change taking place at a global scale. In particular, July 2015 with an average temperature of 29.4 °C, equals the hottest temperature record of August 2003 and was the hottest July ever recorded. The year 2015, with an average temperature of 16.1 °C, is the second warmest year on record. The amount of precipitation is close to climatic mean, but with some anomalies in monthly distribution. [ABSTRACT FROM AUTHOR]

This paper discusses the effects of vegetation cover and soil parameters on the climate change projections of a regional climate model over the Arctic domain. Different setups of the land surface model of the regional climate model HIRHAM were realized to analyze differences in the atmospheric circulation caused by (1) the incorporation of freezing/thawing of soil moisture, (2) the consideration of top organic soil horizons typical for the Arctic and (3) a vegetation shift due to a changing climate. The largest direct thermal effect in 2 m air temperature was found for the vegetation shift, which ranged between −1.5 K and 3 K. The inclusion of a freeze/thaw scheme for soil moisture shows equally large sensitivities in spring over cool areas with high soil moisture content. Although the sensitivity signal in 2 m air temperature for the experiments differs in amplitude, all experiments show changes in mean sea level pressure (mslp) and geopotential height (z) throughout the troposphere of similar magnitude (mslp: −2 hPa to 1.5 hPa, z: −15 gpm to 5 gpm). This points to the importance of dynamical feedbacks within the atmosphere-land system. Land and soil processes have a distinct remote influence on large scale atmospheric circulation patterns in addition to their direct, regional effects. The assessment of induced uncertainties due to the changed implementations of land surface processes discussed in this study demonstrates the need to take all those processes for future Arctic climate projections into account, and demonstrates a clear need to include similar implementations in regional and global climate models. [ABSTRACT FROM AUTHOR]

Meteorological and oceanographic data from ships of opportunity are the largest contributor to the world’s ocean surface database and thus are extensively used to estimate the change in climatic properties over the world’s oceans during the previous 150 years. The importance of these data for climate change studies underscores the need to fully understand the error associated with averages of these data. The sampling error problem is especially acute for ship data due to the fact that ships are moving platforms and, thus, report observations from constantly varying locations with time. This paper develops a theoretical framework for assessing the averaged sampling error associated with monthly, 1°×1° latitude-longitude box averaged ship data. It should be noted that the time-space distribution of ships within the averaging domain strongly affects the sampling error. This is shown in our derivation. The framework developed here can be used to improve upon existing methods for estimating the sampling error associated with three-dimensional box averages of meteorological and oceanographic data obtained from ship records. The framework is complimentary to existing methods of assessing biases and random error due to instrumentation, recording, etc. It is demonstrated mathematically that the uncertainty due to incomplete sampling is primarily a trade off between of the number of observations and their relative locations within the box as well as the inherent time-space correlation structure of the variable of interest. This work differs from other studies in that the three-dimensional interdependence of data is taken into account in deriving an expression for the sampling error. [ABSTRACT FROM AUTHOR]

The natural resources of the Okavango Delta, a large wetland in semi-arid Botswana, form the basis of livelihoods of the local population and support economically important high-end tourism. The hydro-ecological system is dynamic at various time scales, responding to climate variability, and both flood and drought conditions have in the past put pressure on the system's users. Human-induced climate change can potentially exacerbate the effects of existing climate variability. In this paper, we present simulated future hydro-ecological conditions in the Okavango Delta generated by a step-wise modelling procedure. The outputs of three different global climate models are used to drive a suite of hydrological models. Lastly, a rule-based dynamic model relates hydroperiod conditions to vegetation assemblages. The simulated future conditions vary from much drier to much wetter than those recorded in the past. Models indicate that climatic change would result in change in both extent and distribution of the major ecotopes of the Okavango Delta. Importantly, the different ecotopes will be affected to varying degrees. The projected changes will have consequences for the wildlife-based management of the system. They will affect, for example, available grazing and migration/movement patterns of large herbivores, as well as fish. Such consequences can have rapid up-trophic level effects, ultimately leading to potentially substantial impacts on the economy. The main conclusion to be drawn is that management planning and land-use systems should be as flexible as possible. [ABSTRACT FROM AUTHOR]

Uncertainties in observed records of atmospheric temperature aloft remain poorly quantified. This has resulted in considerable controversy regarding signals of climate change over recent decades from temperature records of radiosondes and satellites. This work revisits the problems associated with the removal of inhomogeneities from the historical radiosonde temperature records, and provides a method for quantifying uncertainty in an adjusted radiosonde climate record due to the subjective choices made during the data homogenization. This paper presents an automated homogenization method designed to replicate the decisions made by manual judgment in the generation of an earlier radiosonde dataset [i.e., the Hadley Centre radiosonde temperature dataset (HadAT)]. A number of validation experiments have been conducted to test the system performance and impact on linear trends. Using climate model data to simulate biased radiosonde data, the authors show that limitations in the homogenization method are sufficiently large to explain much of the tropical trend discrepancy between HadAT and estimates from satellite platforms and climate models. This situation arises from the combination of systematic (unknown magnitude) and random uncertainties (of order 0.05 K decade-1) in the radiosonde data. Previous assessment of trends and uncertainty in HadAT is likely to have underestimated the systematic bias in tropical mean temperature trends. This objective assessment of radiosonde homogenization supports the conclusions of the synthesis report of the U.S. Climate Change Science Program (CCSP), and associated research, regarding potential bias in tropospheric temperature records from radiosondes. [ABSTRACT FROM AUTHOR]

The detection and attribution of climate change in the observed record play a central role in synthesizing knowledge of the climate system. Unfortunately, the traditional method for detecting and attributing changes due to multiple forcings requires large numbers of general circulation model (GCM) simulations incorporating different initial conditions and forcing scenarios, and these have only been performed with a small number of GCMs. This paper presents an extension to the fingerprinting technique that permits the inclusion of GCMs in the multisignal analysis of surface temperature even when the required families of ensembles have not been generated. This is achieved by fitting a series of energy balance models (EBMs) to the GCM output in order to estimate the temporal response patterns to the various forcings. This methodology is applied to the very large Challenge ensemble of 62 simulations of historical climate conducted with the NCAR Community Climate System Model version 1.4 (CCSM1.4) GCM, as well as some simulations from other GCMs. Considerable uncertainty exists in the estimates of the parameters in fitted EBMs. Nevertheless, temporal response patterns from these EBMs are more reliable and the combined EBM time series closely mimics the GCM in the context of transient forcing. In particular, detection and attribution results from this technique appear self-consistent and consistent with results from other methods provided that all major forcings are included in the analysis. Using this technique on the Challenge ensemble, the estimated responses to changes in greenhouse gases, tropospheric sulfate aerosols, and stratospheric volcanic aerosols are all detected in the observed record, and the responses to the greenhouse gases and tropospheric sulfate aerosols are both consistent with the observed record without a scaling of the amplitude being required. The result is that the temperature difference of the 1996–2005 decade relative to the 1940–49 decade can be attributed to greenhouse gas emissions, with a partially offsetting cooling from sulfate emissions and little contribution from natural sources. The results support the viability of the new methodology as an extension to current analysis tools for the detection and attribution of climate change, which will allow the inclusion of many more GCMs. Shortcomings remain, however, and so it should not be considered a replacement to traditional techniques. [ABSTRACT FROM AUTHOR]

The relative importance of the processes responsible for the annual cycle in the upper-ocean heat content in the Peru Current, in the southeastern tropical Pacific, was diagnosed from an oceanic analysis dataset. It was found that the annual cycle of heat content is forced mainly by insolation. However, the ocean dynamical processes play an important role in producing different regional budget characteristics. In a band 500 km from the coast of Peru, the annual heat content changes in this region are relatively large and can be approximated as sea surface temperature (SST) changes in a fixed-depth mixed layer. The annual cycle of the albedo associated with low-level clouds enhances the annual cycle in insolation, which explains the relatively strong annual cycle of heat content. These clouds, to a large extent, act as a feedback to SST, but a small additional forcing, which is proposed to be cold air advection in this paper, is needed to explain the fact that the maximum cloudiness leads the lowest SST by around a month. Ocean dynamics is important closer to the coast, where upwelling acts partly as damping of the heat content changes and forces it to peak earlier than farther offshore. In a band farther to the southwest, locally wind-forced thermocline motions, which become shallower (deeper) in the warm (cool) season, partially cancel the effect of net surface heat fluxes, whose annual cycle is comparable to that in the region previously mentioned, producing a relatively small annual cycle of heat content. The local forcing appears to be associated with the annual meridional displacements of the South Pacific anticyclone. The annual cycle in SST is also relatively small, which is probably due to the changes in the temperature of the water entrained into the mixed layer associated with the thermocline motions, but also to a mixed layer deeper than that closer to the coast. [ABSTRACT FROM AUTHOR]