The effects of annual precipitation and mean air temperature on annual runoff in global forest regions

Abstract Changing trends in runoff and water balance under a warming atmosphere are a major subject of interest in recent climatic and hydrological research. Forest basins represent the most complex systems including critical hydrological processes. In this study, we investigate the relationship between annual total runoff (Q), precipitation (P), and mean temperature (T) using observed data collected from 829 (forest) site years around the world. It is shown that the strong linear relationship between annual P and Q is a function of mean T. By empirically perturbing observed annual Q and P with T, a set of ΔQ-zero lines are derived for different mean T. To evaluate the extent to which the future changes in annual P and T alter Q, the future projections of ΔP and ΔT under a warming scenario (A1B) from five coupled AOGCMs (Atmosphere-Ocean General Circulation Models) are compared with the empirical ΔQ-zero lines derived in this study. It is found that five AOGCMs show different distributions with respect to the ΔQ-zero lines, which can be attributed to the contrasting dominant sensitivities of various influencing factors to water balance partitioning among models. The knowledge gained in this empirical study is helpful to predict water resources changes under changing climate as well as to interpret hydrologic simulations in AOGCM future projections. Climatic Chang

GLACE: the global land–atmosphere coupling experiment. Part I: overview

Permission to place copies of these works on this server has been provided by the American Meteorological Society (AMS). The AMS does not guarantee that the copies provided here are accurate copies of the published work. © Copyright 2006 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/AMS) or from the AMS at 617-227-2425 or [email protected] Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detail so that any interested modeling group can repeat them easily and thereby place their model’s coupling strength within the broad range of those documented here

Influence of “Realistic” Land Surface Wetness on Predictability of Seasonal Precipitation in Boreal Summer

Outputs from two ensembles of atmospheric model simulations for 1951–98 define the influence of “realistic” land surface wetness on seasonal precipitation predictability in boreal summer. The ensembles consist of one forced with observed sea surface temperatures (SSTs) and the other forced with realistic land surface wetness as well as SSTs. Predictability was determined from correlations between the time series of simulated and observed precipitation. The ratio of forced variance to total variance determined potential predictability. Predictability occurred over some land areas adjacent to tropical oceans without land wetness forcing. On the other hand, because of the chaotic nature of the atmosphere, considerable parts of the land areas of the globe did not even show potential predictability with both land wetness and SST forcings. The use of land wetness forcing enhanced predictability over semiarid regions. Such semiarid regions are generally characterized by a negative correlation between fluxes of latent heat and sensible heat from the land surface, and are “water-regulating” areas where soil moisture plays a governing role in land–atmosphere interactions. Actual seasonal prediction may be possible in these regions if slowly varying surface conditions can be estimated in advance. In contrast, some land regions (e.g., south of the Sahel, the Amazon, and Indochina) showed little predictability despite high potential predictability. These regions are mostly characterized by a positive correlation between the surface fluxes, and are “radiation-regulating” areas where the atmosphere plays a leading role. Improvements in predictability for these regions may require further improvements in model physics

Seasonal variation of land-atmosphere coupling strength over the West African monsoon region in an atmospheric general circulation model

The seasonal variation of land-atmosphere coupling strength has been examined using an extended series of atmospheric general circulation model (AGCM) simulations. In the Western Sahel of Africa, strong coupling strength for precipitation is found in April and May, just prior to and at the beginning of the monsoon season. At this time, heat and water fluxes from the surface are strongly controlled by land conditions, and the unstable conditions in the lower level of the troposphere, as induced by local land state, allow the surface fluxes to influence the variability of convective precipitationand thus the timing of monsoon onset

Estimation of Predictability with a Newly Derived Index to Quantify Similarity among Ensemble Members

This study reveals the mathematical structure of a statistical index, Ω, that quantifies similarity among ensemble members in a weather forecast. Previous approaches for quantifying predictability estimate separately the phase and shape characteristics of a forecast ensemble. The diagnostic Ω, on the other hand, characterizes the similarity (across ensemble members) of both aspects together with a simple expression. The diagnostic Ω is thus more mathematically versatile than previous indices

Climate Extremes, Disasters and Health

This chapter focuses on health and economic impacts of disasters, including climate extremes. The economic losses from weather- and climate-related disasters and the difference in disaster costs and deaths between developed and developing countries are described. The types of disasters (earthquakes, extreme temperature, floods, cyclones, tornadoes, hail, drought) and their health impacts are reviewed. The future trends of extreme events and adaptation, as well as conflicts in adaptation are discussed

Water Scarcity Footprints by Considering the Differences in Water Sources

Water resources have uneven distributions over time, space, and source; thus, potential impacts related to water use should be evaluated by determining the differences in water resources rather than by simply summing water use. We propose a model for weighting renewable water resources and present a case study assessing water scarcity footprints as indicators of the potential impacts of water use based on a life cycle impact assessment (LCIA). We assumed that the potential impact of a unit amount of water used is proportional to the land area or time required to obtain a unit of water from each water source. The water unavailability factor (fwua) was defined using a global hydrological modeling system with a global resolution of 0.5 × 0.5 degrees. This model can address the differences in water sources using an adjustable reference volume and temporal and spatial resolutions based on the flexible demands of users. The global virtual water flows were characterized using the fwua for each water source. Although nonrenewable and nonlocal blue water constituted only 3.8% of the total flow of the water footprint inventory, this increased to 29.7% of the total flow of the water scarcity footprint. We can estimate the potential impacts of water use that can be instinctively understood using fwua

Potential Impacts of Food Production on Freshwater Availability Considering Water Sources

We quantify the potential impacts of global food production on freshwater availability (water scarcity footprint; WSF) by applying the water unavailability factor (fwua) as a characterization factor and a global water resource model based on life cycle impact assessment (LCIA). Each water source, including rainfall, surface water, and groundwater, has a distinct fwua that is estimated based on the renewability rate of each geographical water cycle. The aggregated consumptive water use level for food production (water footprint inventory; WI) was found to be 4344 km3/year, and the calculated global total WSF was 18,031 km3 H2Oeq/year, when considering the difference in water sources. According to the fwua concept, which is based on the land area required to obtain a unit volume of water from each source, the calculated annual impact can also be represented as 98.5 × 106 km2. This value implies that current agricultural activities requires a land area that is over six times larger than global total cropland. We also present the net import of the WI and WSF, highlighting the importance of quantitative assessments for utilizing global water resources to achieve sustainable water use globally