C. M. Goodess

Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user

Precipitation downscaling improves the coarse resolution and poor representation of precipitation in global climate models and helps end users to assess the likely hydrological impacts of climate change. This paper integrates perspectives from meteorologists, climatologists, statisticians, and hydrologists to identify generic end user (in particular, impact modeler) needs and to discuss downscaling capabilities and gaps. End users need a reliable representation of precipitation intensities and temporal and spatial variability, as well as physical consistency, independent of region and season. In addition to presenting dynamical downscaling, we review perfect prognosis statistical downscaling, model output statistics, and weather generators, focusing on recent developments to improve the representation of space-time variability. Furthermore, evaluation techniques to assess downscaling skill are presented. Downscaling adds considerable value to projections from global climate models. Remaining gaps are uncertainties arising from sparse data; representation of extreme summer precipitation, subdaily precipitation, and full precipitation fields on fine scales; capturing changes in small-scale processes and their feedback on large scales; and errors inherited from the driving global climate model.

Changes in climate extremes and their impacts on the natural physical environment

This chapter addresses changes in weather and climate events relevant to extreme impacts and disasters. An extreme (weather or climate) event is generally defined as the occurrence of a value of a weather or climate variable above (or below) a threshold value near the upper (or lower) ends (‘tails’) of the range of observed values of the variable. Some climate extremes (e.g., droughts, floods) may be the result of an accumulation of weather or climate events that are, individually, not extreme themselves (though their accumulation is extreme). As well, weather or climate events, even if not extreme in a statistical sense, can still lead to extreme conditions or impacts, either by crossing a critical threshold in a social, ecological, or physical system, or by occurring simultaneously with other events. A weather system such as a tropical cyclone can have an extreme impact, depending on where and when it approaches landfall, even if the specific cyclone is not extreme relative to other tropical cyclones. Conversely, not all extremes necessarily lead to serious impacts. [3.1] Many weather and climate extremes are the result of natural climate variability (including phenomena such as El Nino), and natural decadal or multi-decadal variations in the climate provide the backdrop for anthropogenic climate changes. Even if there were no anthropogenic changes in climate, a wide variety of natural weather and climate extremes would still occur. [3.1] A changing climate leads to changes in the frequency, intensity, spatial extent, duration, and timing of weather and climate extremes, and can result in unprecedented extremes. Changes in extremes can also be directly related to changes in mean climate, because mean future conditions in some variables are projected to lie within the tails of present-day conditions. Nevertheless, changes in extremes of a climate or weather variable are not always related in a simple way to changes in the mean of the same variable, and in some cases can be of opposite sign to a change in the mean of the variable. Changes in phenomena such as the El Nino-Southern Oscillation or monsoons could affect the frequency and intensity of extremes in several regions simultaneously.

Precipitation fluctuations over northern hemisphere land areas since the mid-19th century

An extensive array of measurements extending back to the mid-19th century was used to investigate large-scale changes in precipitation over Northern Hemisphere land areas. Significant increases in mid-latitude precipitation and concurrent decreases in low-latitude precipitation have occurred over the last 30 to 40 years. Although these large-scale trends are consistent with general circulation model projections of precipitation changes associated with doubled concentrations of atmospheric carbon dioxide, they should be viewed as defining large-scale natural climatic variability. Additional work to refine regional variations and address potential network inhomogeneitics is needed. This study attempts to show secular precipitation fluctuations over hemispheric and continental-scale areas of the Northern Hemisphere.

Statistical and dynamical downscaling of precipitation: An evaluation and comparison of scenarios for the European Alps

[1] This paper compares six statistical downscaling models (SDMs) and three regional climate models (RCMs) in their ability to downscale daily precipitation statistics in a region of complex topography. The six SDMs include regression methods, weather typing methods, a conditional weather generator, and a bias correction and spatial disaggregation approach. The comparison is carried out over the European Alps for current and future (2071–2100) climate. The evaluation of simulated precipitation for the current climate shows that the SDMs and RCMs tend to have similar biases but that they differ with respect to interannual variations. The SDMs strongly underestimate the magnitude of the year-to-year variations. Clear differences emerge also with respect to the year-to-year anomaly correlation skill: In winter, over complex terrain, the better RCMs achieve significantly higher skills than the SDMs. Over flat terrain and in summer, the differences are smaller. Scenario results using A2 emissions show that in winter mean precipitation tends to increase north of about 45N and insignificant or opposite changes are found to the south. There is good agreement between the downscaling models for most precipitation statistics. In summer, there is still good qualitative agreement between the RCMs but large differences between the SDMs and between the SDMs and the RCMs. According to the RCMs, there is a strong trend toward drier conditions including longer periods of drought. The SDMs, on the other hand, show mostly nonsignificant or even opposite changes. Overall, the present analysis suggests that downscaling does significantly contribute to the uncertainty in regional climate scenarios, especially for the summer precipitation climate.

Development of daily rainfall scenarios for southeast Spain using a circulation-type approach to downscaling

A method for downscaling from the relatively coarse General Circulation Model (GCM) spatial scale to the finer spatial scale required for impact assessment has been developed and tested in the Guadalentin Basin, southeast Spain. The method uses a circulation-type approach and relates large-scale patterns of a predictor variable, gridded sea level pressure, to local values of a surface climate variable (daily rainfall at six stations). The large-scale patterns are defined using an automated version of the Lamb Weather Type classification scheme, originally developed for the British Isles. It is demonstrated that this scheme can be successfully transferred to another region, southeast Spain. The 14 basic circulation types are combined into eight groups. These provide a legitimate basis for downscaling because each has a characteristic pressure pattern which produces the expected type and direction of flow over the study region. Furthermore, a set of consistent and distinct relationships is identified between these circulation types and daily rainfall in the Guadalentin Basin. The ability of the GCM to reproduce the observed circulation types is assessed before applying these relationships to control and perturbed-run GCM output using a statistical weather generator. The effects of the GCM’s failure to reproduce the observed frequency of the circulation types are detectable in the weather generator output. The GCM changes in SLP and circulation-type frequency between the control and perturbed-runs are generally small. Nonetheless the weather generator results indicate significant changes in the number of rain days in spring and summer. These scenarios are presented as illustrative results rather than as reliable predictions. It is concluded that the circulation-type based approach to downscaling offers great potential.

Future Climate Projections

In this chapter we show results from an innovative multi-model system used to produce climate simulations with a realistic representation of the Mediterranean Sea. The models (hereafter simply referred to as the “CIRCE models”) are a set of five coupled climate models composed by a high-resolution Mediterranean Sea coupled with a relatively high-resolution atmospheric component and a global ocean, which allow, for the first time, to explore and assess the role of the Mediterranean Sea and its complex, small-scale dynamics in the climate of the region. In particular, they make it possible to investigate the influence that local air-sea feedbacks might exert on the mechanisms responsible for climate variability and change in the European continent, Middle East and Northern Africa. In many regards, they represent a new and innovative approach to the problem of regionalization of climate projections in the Mediterranean region.

The Effect of Urban Warming on the Northern Hemisphere Temperature Average

Abstract The significance of the urban warming effect on large-scale and hemispheric mean temperature series is assessed using estimates of the urbanization bias for stations in the United States produced by Karl et al. It is concluded that the Northern Hemisphere landmass average recently compiled by Jones et al. may contain a spurious warming trend which is, at the maximum, 0.1°C over the first eight decades of the twentieth century. This is considerably less than the long-term warming trend observed over the same period.

The Simulation of Daily Temperature Time Series from GCM Output. Part I: Comparison of Model Data with Observations

For climate change impact analyses, local scenarios of surface variables at the daily scales are frequently required. Empirical transfer functions are a widely used technique to generate scenarios from GCM data at these scales. For successful downscaling, the impact analyst should take into account certain considerations. First, it must be demonstrated that the GCM simulations of the required variable are unrealistic and therefore that downscaling is required. Second, it must be shown that the GCM simulations of the selected predictor variables are realistic. Where errors occur, attempts must be made to compensate for their effect on the transfer function‐ generated predictions or, where this is not possible, the effect on the transfer function‐generated climate series must be understood. Third, the changes in the predictors between the control and perturbed simulation must be examined in the light of the implications for the change in the predicted variable. Finally, the effect of decisions made during the development of the transfer functions on the final result should be explored. This study, presented in two parts, addresses these considerations with respect to the development of local scenarios for daily maximum (TMAX) and minimum (TMIN) temperature for two sites, one in North America (Eau Claire, Michigan) and one in Europe (Alcantarilla, Spain). Part I confirms for a selected GCM that simulations of daily TMAX and TMIN, whether taken from the nearest land grid point, or obtained by interpolation to the site location, are inadequate. Differences between the GCM 1 3 CO2 and observed temperature series arise because of a 08C threshold in the model data. At both sites, variability is suppressed during periods affected by the threshold. The thresholds persist into the perturbed simulation, affecting not only GCM-predicted 2 3 CO2 temperatures but also, because the duration and timing of the threshold effect changes in the perturbed simulation, the magnitude and seasonal distribution of the 2 3 CO2 ‐1 3CO2 GCM differences. Comparison of modeled and observed 500-hPa geopotential height (Z500) and sea level pressure (SLP) shows that, although systematic errors of the type associated with the 08C threshold in the temperature data are absent, significant errors do occur in certain seasons at both sites. For example, SLP is poorly modeled at Alcantarilla, where the control and observed means differ significantly in every season. The worst results at both sites are in summer. These results will affect the performance of the transfer functions when initialized with model data. Whereas little change is found to occur in SLP at either site between the 1 3 CO2 and 2 3 CO2 simulation, there is a noticeable increase in Z500. Other things being equal, therefore, the temperature changes predicted by the transfer functions are likely to be greatest when Z500 contributes the most to the explained variances. In Part II, a range of transfer functions are developed from the free atmosphere variables and validated, using observations. The performance of these transfer functions when initialized with model data is evaluated in the light of the findings in Part I. The sensitivity of the perturbed climate scenarios to a range of user decisions is explored.

The Simulation of Daily Temperature Time Series from GCM Output. Part II: Sensitivity Analysis of an Empirical Transfer Function Methodology

Abstract Empirical transfer functions have been proposed as a means for “downscaling” simulations from general circulation models (GCMs) to the local scale. However, subjective decisions made during the development of these functions may influence the ensuing climate scenarios. This research evaluated the sensitivity of a selected empirical transfer function methodology to 1) the definition of the seasons for which separate specification equations are derived, 2) adjustments for known departures of the GCM simulations of the predictor variables from observations, 3) the length of the calibration period, 4) the choice of function form, and 5) the choice of predictor variables. A modified version of the Climatological Projection by Model Statistics method was employed to generate control (1 × CO2) and perturbed (2 × CO2) scenarios of daily maximum and minimum temperature for two locations with diverse climates (Alcantarilla, Spain, and Eau Claire, Michigan). The GCM simulations used in the scenario developm...

Generating Rainfall and Temperature Scenarios at Multiple Sites: Examples from the Mediterranean

A statistical downscaling methodology was implemented to generate daily time series of temperature and rainfall for point locations within a catchment, based on the output from general circulation models. The rainfall scenarios were constructed by a two-stage process. First, for a single station, a conditional first-order Markov chain was used to generate wet and dry day successions. Then, the multisite scenarios were constructed by sampling from a benchmark file containing a daily time series of multiple-site observations, classified by season, circulation weather type, and whether the day is wet or dry at the reference station. The temperature scenarios were constructed using deterministic transfer functions initialized by free atmosphere variables. The relationship between the temperature and rainfall scenarios is established in two ways. First, sea level pressure fields define the circulation weather types underpinning the rainfall scenarios and are used to construct predictor variables in the temperature scenarios. Second, separate temperature transfer functions are developed for wet and dry days. The methods were evaluated in two Mediterranean catchments. The rainfall scenarios were always too dry, despite the application of Monte Carlo techniques in an attempt to overcome the problem. The temperature scenarios were generally too cool. The scenarios were used to explore the occurrence of extreme events, and the changes predicted in response to climate change, taking the example of temperature. The nonlinear relationship between changes in the mean and changes at the extremes was clearly demonstrated.