Showing papers on "Precipitation published in 2003"
TL;DR: In this article, precipitation intensity, duration, frequency, and phase are as much of concern as total amounts, as these factors determine the disposition of precipitation once it hits the ground and how much runs off.
Abstract: From a societal, weather, and climate perspective, precipitation intensity, duration, frequency, and phase are as much of concern as total amounts, as these factors determine the disposition of precipitation once it hits the ground and how much runs off. At the extremes of precipitation incidence are the events that give rise to floods and droughts, whose changes in occurrence and severity have an enormous impact on the environment and society. Hence, advancing understanding and the ability to model and predict the character of precipitation is vital but requires new approaches to examining data and models. Various mechanisms, storms and so forth, exist to bring about precipitation. Because the rate of precipitation, conditional on when it falls, greatly exceeds the rate of replenishment of moisture by surface evaporation, most precipitation comes from moisture already in the atmosphere at the time the storm begins, and transport of moisture by the storm-scale circulation into the storm is vital....
2,526 citations
TL;DR: The relationship between vegetation vigor and moisture availability, however, is complex and has not been adequately studied with satellite sensor data as mentioned in this paper, however, an analysis was conducted on time series of monthly NDVI (1989-2000) during the growing season in the north and central U.S. Great Plains.
723 citations
TL;DR: The authors presented a comprehensive analysis of the diurnal cycle of the observed precipitation features' rainfall amount, precipitation feature frequency, rainfall intensity, convective-stratiform rainfall portioning, and remotely sensed convective intensity, sampled Tropicswide from space.
Abstract: The Tropical Rainfall Measuring Mission (TRMM) satellite measurements from the precipitation radar and TRMM microwave imager have been combined to yield a comprehensive 3-yr database of precipitation features (PFs) throughout the global Tropics (±36° latitude). The PFs retrieved using this algorithm (which number nearly six million Tropicswide) have been sorted by size and intensity ranging from small shallow features greater than 75 km2 in area to large mesoscale convective systems (MCSs) according to their radar and ice scattering characteristics. This study presents a comprehensive analysis of the diurnal cycle of the observed precipitation features' rainfall amount, precipitation feature frequency, rainfall intensity, convective–stratiform rainfall portioning, and remotely sensed convective intensity, sampled Tropicswide from space. The observations are sorted regionally to examine the stark differences in the diurnal cycle of rainfall and convective intensity over land and ocean areas. Over ...
676 citations
TL;DR: Using a high-resolution climate model, the influence of greenhouse-gas-induced global warming upon heavy or extended precipitation episodes that inflict catastrophic flooding is quantified.
Abstract: Even as summers become drier, the incidence of severe precipitation could increase. Using a high-resolution climate model, we are able to quantify the influence of greenhouse-gas-induced global warming upon heavy or extended precipitation episodes that inflict catastrophic flooding. We find that an increase in the amount of precipitation that exceeds the 95th percentile is very likely in many areas of Europe, despite a possible reduction in average summer precipitation over a substantial part of the continent. Our results indicate that episodes of severe flooding may become more frequent, despite a general trend towards drier summer conditions.
667 citations
TL;DR: In this article, the application of polarimetric radar data to the retrieval of raindrop size distribution parameters and rain rate in samples of convective and stratiform rain types is presented.
Abstract: The application of polarimetric radar data to the retrieval of raindrop size distribution parameters and rain rate in samples of convective and stratiform rain types is presented. Data from the Colorado State University (CSU), CHILL, NCAR S-band polarimetric (S-Pol), and NASA Kwajalein radars are analyzed for the statistics and functional relation of these parameters with rain rate. Surface drop size distribution measurements using two different disdrometers (2D video and RD-69) from a number of climatic regimes are analyzed and compared with the radar retrievals in a statistical and functional approach. The composite statistics based on disdrometer and radar retrievals suggest that, on average, the two parameters (generalized intercept and median volume diameter) for stratiform rain distributions lie on a straight line with negative slope, which appears to be consistent with variations in the microphysics of stratiform precipitation (melting of larger, dry snow particles versus smaller, rimed ic...
565 citations
TL;DR: Observations from a meteorological network across the Greater Himalaya, Nepal, along with estimates of erosion rates at geologic timescales from low-temperature thermochronometry are combined to predict spatial variations in precipitation and slopes and correlate with gradients in both erosion rates and crustal strain.
Abstract: The hypothesis that abrupt spatial gradients in erosion can cause high strain rates in active orogens has been supported by numerical models that couple erosional processes with lithospheric deformation via gravitational feedbacks. Most such models invoke a 'stream-power' rule, in which either increased discharge or steeper channel slopes cause higher erosion rates. Spatial variations in precipitation and slopes are therefore predicted to correlate with gradients in both erosion rates and crustal strain. Here we combine observations from a meteorological network across the Greater Himalaya, Nepal, along with estimates of erosion rates at geologic timescales (greater than 100,000 yr) from low-temperature thermochronometry. Across a zone of about 20 km length spanning the Himalayan crest and encompassing a more than fivefold difference in monsoon precipitation, significant spatial variations in geologic erosion rates are not detectable. Decreased rainfall is not balanced by steeper channels. Instead, additional factors that influence river incision rates, such as channel width and sediment concentrations, must compensate for decreasing precipitation. Overall, spatially constant erosion is a response to uniform, upward tectonic transport of Greater Himalayan rock above a crustal ramp.
513 citations
Ludwig Maximilian University of Munich1, Naval Postgraduate School2, Meteorological Service of Canada3, State University of New York System4, Dartmouth College5, Pennsylvania State University6, Florida State University7, Bureau of Meteorology8, European Centre for Medium-Range Weather Forecasts9, Embry–Riddle Aeronautical University10
TL;DR: In this article, the challenges associated with forecasting extratropical transition are described in terms of the forecast variables (track, intensity, surface winds, precipitation) and their impacts (flooding, bush fires, ocean response).
Abstract: A significant number of tropical cyclones move into the midlatitudes and transform into extratropical cyclones. This process is generally referred to as extratropical transition (ET). During ET a cyclone frequently produces intense rainfall and strong winds and has increased forward motion, so that such systems pose a serious threat to land and maritime activities. Changes in the structure of a system as it evolves from a tropical to an extratropical cyclone during ET necessitate changes in forecast strategies. In this paper a brief climatology of ET is given and the challenges associated with forecasting extratropical transition are described in terms of the forecast variables (track, intensity, surface winds, precipitation) and their impacts (flooding, bush fires, ocean response). The problems associated with the numerical prediction of ET are discussed. A comprehensive review of the current understanding of the processes involved in ET is presented. Classifications of extratropical transition ...
481 citations
TL;DR: In this article, two 30-year simulations corresponding to 1960-1989 and 2070-2099 have been performed with a variable resolution atmospheric model, with a maximum horizontal resolution of 05° over the Mediterranean Sea.
Abstract: Two 30-year simulations corresponding to 1960–1989 and 2070–2099 have been performed with a variable resolution atmospheric model The model has a maximum horizontal resolution of 05° over the Mediterranean Sea Simulations are driven by IPCC-B2 scenario radiative forcing Sea surface temperatures (SSTs) are prescribed from monthly observations for the present climate simulation, and from a blend of observations and coupled simulations for the scenario Another pair of forced atmospheric simulations has been run under these forcings with the same uniform low resolution as the coupled model Comparisons with observations show that the variable resolution model realistically reproduces the main climate characteristics of the Mediterranean region At a global scale, changes in latitudinal temperature profiles are similar for the forced and coupled models, justifying the time-slice approach The 2 m temperature and precipitation responses predict a warming and drying of the Mediterranean region A comparison with the coupled simulation and forced low-resolution simulation shows that this pattern is robust The decrease in mean precipitation is associated with a significant decrease in soil wetness, and could involve considerable impact on water resources around the Mediterranean basin
455 citations
TL;DR: In this article, a 15-year evaluation of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps is performed. But the results show that the model errors are very similar between the two models with the same dynamical core (but different parameterizations).
Abstract: [1] An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km. The 15-year integrations were forced from reanalyses and observed sea surface temperature and sea ice (global model from sea surface only). The observational reference is based on 6400 rain gauge records (10–50 stations per grid box). Evaluation statistics encompass mean precipitation, wet-day frequency, precipitation intensity, and quantiles of the frequency distribution. For mean precipitation, the models reproduce the characteristics of the annual cycle and the spatial distribution. The domain mean bias varies between −23% and +3% in winter and between −27% and −5% in summer. Larger errors are found for other statistics. In summer, all models underestimate precipitation intensity (by 16–42%) and there is a too low frequency of heavy events. This bias reflects too dry summer mean conditions in three of the models, while it is partly compensated by too many low-intensity events in the other two models. Similar intermodel differences are found for other European subregions. Interestingly, the model errors are very similar between the two models with the same dynamical core (but different parameterizations) and they differ considerably between the two models with similar parameterizations (but different dynamics). Despite considerable biases, the models reproduce prominent mesoscale features of heavy precipitation, which is a promising result for their use in climate change downscaling over complex topography.
444 citations
TL;DR: In this article, a methodology for producing gridded mean monthly catch ratios (CRs) for the adjustment of wind-induced undercatch and wetting losses is developed, which is suitable for application to continental or global GRG-based precipitation products.
Abstract: [1] Systematic biases in gauge-based measurement of precipitation can be substantial. Of the sources of bias, wind-induced undercatch of solid precipitation is by far the largest. A methodology for producing gridded mean monthly catch ratios (CRs) for the adjustment of wind-induced undercatch and wetting losses is developed, which is suitable for application to continental or global gridded precipitation products. The adjustments for wind-induced solid precipitation were estimated using gauge type-specific regression equations from the recent World Meteorological Organization Solid Precipitation Measurement Intercomparison. Wind-induced undercatch of liquid precipitation and wetting losses were estimated using methods employed in previous global bias adjustment efforts. Due to the unique nature of Canada's precipitation measurement network, the Canadian adjustments were determined using more detailed information than for the rest of the domain, and are therefore expected to be more reliable. The gridded gauge adjustment products are designed to be applicable both to climatological estimates and to individual years during the 1979 through 1998 reference period. Application of the CRs to an existing precipitation product yielded an increase in mean annual global terrestrial precipitation of 11.7%. As compared with recent (but more localized) studies that used a similar method to account for wind-induced catch deficiencies, our estimates of wind-induced undercatch are 1.6–7.9% higher on a mean annual basis. Compared to a previous global precipitation bias adjustment effort, our adjusted data set results on average in slightly greater warm season and lower cold season precipitation increases, greater precipitation increases over North America, and lower precipitation increases over Eurasia.
406 citations
TL;DR: Light, rather than water, temperature, or leaf nitrogen, was the primary factor limiting CO2 uptake during the rainy season, and photosynthesis, vegetative growth, and reproduction increased significantly.
Abstract: Recent global-scale analyses indicate that climate variability affects net carbon storage but regard temperature and precipitation to be the main contributors. Seasonal and interannual variation in light availability may also limit CO(2) uptake. As an experimental test of light limitation by cloud cover during tropical rainy seasons and by the unusually heavy cloud cover associated with La Nina, we installed high-intensity lamps above the forest canopy to augment light for Luehea seemannii, a tropical canopy tree species, during cloudy periods of 1999-2000. Light augmentation only partially compensated for the reduction in photosynthetic photon flux density caused by clouds. Nonetheless, leaves acclimated to the augmented irradiance, and photosynthesis, vegetative growth, and reproduction increased significantly. Light, rather than water, temperature, or leaf nitrogen, was the primary factor limiting CO(2) uptake during the rainy season.
TL;DR: In this article, the authors sampled 16 soil profiles along an arid to humid climosequence on Kohala Mountain, Hawaii, and found that weathering and soil properties change in a nonlinear fashion with increased rainfall.
TL;DR: In this paper, observations of snow water equivalent (SWE) in the Pacific Northwest were examined and compared with variability and trends in temperature and precipitation at nearby climate stations at most locations, especially below about 1800 m.
Abstract: [1] Observations of snow water equivalent (SWE) in the Pacific Northwest are examined and compared with variability and trends in temperature and precipitation at nearby climate stations. At most locations, especially below about 1800 m, substantial declines in SWE coincide with significant increases in temperature, and occur in spite of increases in precipitation.
TL;DR: In this article, the expected precipitation percentiles during the monsoon season of El Nino (EN) events are calculated, as well as anomalies of surface temperature and thermodynamic parameters.
Abstract: The El Nino impact on Brazil's summer monsoon has not been adequately assessed through seasonal analysis because it shows significant subseasonal variations. In this study, the El Nino influence on the summer monsoon circulation, rainfall, and temperature is analyzed with monthly resolution, using data from a dense network of stations. The expected precipitation percentiles during the monsoon season of El Nino (EN) events are calculated, as well as anomalies of surface temperature and thermodynamic parameters. This information is analyzed jointly with anomaly composites of several circulation parameters. The analysis shows that some precipitation and circulation anomalies, which are consistent and important during part of the season, are smoothed out in a seasonal analysis. There are abrupt changes of anomalies within the summer monsoon season, suggesting the prevalence of regional processes over remote influences during part of the season. The probable role of remote influences and regional processes is assessed. The anomalous heat sources associated with El Nino perturb the Walker and Hadley circulations over South America and generate Rossby wave trains that produce important effects in the subtropics and extratropics. In the early summer monsoon season, remotely produced atmospheric perturbations prevail over Brazil. Anticyclonic low-level anomalies predominate over central-east Brazil, in the Tropics and subtropics, due to the subsidence over the Amazon and to Rossby waves in the subtropics. Easterly moisture inflow from the Atlantic is favored, but diverted toward northern South America (SA) and south Brazil. There are negative precipitation anomalies in north and central-east Brazil and positive ones in south Brazil. These precipitation anomalies are favored by the perturbation in the Walker and Hadley circulation over the east Pacific and South America, and by a Rossby wave train over southern SA that originates in the eastern Pacific. In January, with the enhancement of the continental subtropical heat low by anomalous surface heating during the spring, there is anomalous low-level convergence and cyclonic circulation over southeast Brazil, while at the upper levels anomalies of divergence and anticyclonic circulation prevail. This anomalous circulation directs moisture flux toward central-east Brazil, causing moisture convergence in this region. A favorable thermodynamic structure enhances precipitation over central-east Brazil, the dry anomalies in north Brazil are displaced northward, and the anomalies in south Brazil almost disappear. In February, after the above-normal precipitation of January, the surface temperature anomalies turn negative and the precipitation diminishes in central-east Brazil. There are negative rainfall anomalies in north Brazil and in the South Atlantic convergence zone (SACZ) and positive ones in south Brazil. Influence function analysis shows that while the anomalies of circulation over southeast Brazil in the spring of El Nino years are mostly due to remote influences from the tropical east Pacific, those in January are probably due to local influence. During this month the monsoonlike circulation is enhanced. Simultaneous and lagged correlation analysis of SST and rainfall in central-east Brazil shows that SST anomalies in the Atlantic Ocean off the southeastern coast of Brazil fluctuate on the same timescale as the circulation and precipitation anomalies.
TL;DR: Wang et al. as discussed by the authors analyzed the observed long-term variations of seasonal climate in China and then investigated the possible influence of increases in greenhouse gas concentrations on these variations by comparing the observations with the simulations of the second phase of the Coupled Model Intercomparison Project (CMIP2).
Abstract: [1] In this work, the authors analyze the observed long-term variations of seasonal climate in China and then investigate the possible influence of increases in greenhouse gas concentrations on these variations by comparing the observations with the simulations of the second phase of the Coupled Model Intercomparison Project (CMIP2). The long-term variations of precipitation and temperature in China are highly seasonally dependent. The main characteristic of summer precipitation in China is a drying trend in the north and a wetting trend in the central part. The precipitation in winter shows an increasing trend in southern and eastern-central China. Interesting features have also been found in the transitional seasons. In spring, precipitation variations are almost opposite to those in summer. In autumn the precipitation decreases in almost the whole country except for the middle and lower reaches of the Yangtze River Valley. In addition, the seasonality of precipitation has become slightly weaker in recent decades in southern and eastern China. Pronounced warming is observed in the entire country in winter, spring, and autumn, particularly in the northern part of China. In summer a cooling trend in central China is particularly interesting, and cooling (warming) trends generally coexist with wetting (drying) trends. The correlativity between precipitation and temperature variations is weak in spring, autumn, and winter. It has also been found that the long-term climate variations in winter and summer in China may be connected to the warming trend in the sea surface temperature of the Indian Ocean. A comparison between the observed seasonal climate variations and the CMIP2 simulations of 16 models indicates that the observed long-term variations of winter, spring, and autumn temperature in China may be associated with increases in greenhouse gas concentrations. However, such a connection is not found for the summer temperature. The tremendous uncertainties among the models in precipitation simulations make it difficult to link the precipitation variations to global warming. INDEX TERMS: 1620 Global Change: Climate dynamics (3309); 3319 Meteorology and Atmospheric Dynamics: General circulation; 3309 Meteorology and Atmospheric Dynamics: Climatology (1620); 4215 Oceanography: General: Climate and interannual variability (3309); 1610 Global Change: Atmosphere (0315, 0325); KEYWORDS: global warming signals, Chinese climate, CMIP2 simulation
TL;DR: In this article, the authors investigated whether GCM-simulated precipitation is a good predictor for regional precipitation over Washington and Oregon, using the NCEP-NCAR reanalysis, which nearly perfectly represents the historic pressure, temperature, and humidity, but calculates precipitation according to the model physics and parameterizations.
Abstract: This study investigates whether GCM-simulated precipitation is a good predictor for regional precipitation over Washington and Oregon. In order to allow for a detailed comparison of the estimated precipitation with observations, the simulated precipitation is taken from the NCEP–NCAR reanalysis, which nearly perfectly represents the historic pressure, temperature, and humidity, but calculates precipitation according to the model physics and parameterizations. Three statistical downscaling methods are investigated: (i) local rescaling of the simulated precipitation, and two newly developed methods, namely, (ii) downscaling using singular value decomposition (SVD) with simulated precipitation as the predictor, and (iii) local rescaling with a dynamical correction. Both local scaling methods are straightforward to apply to GCMs that are used for climate change experiments and seasonal forecasts, since they only need control runs for model fitting. The SVD method requires for model fitting special re...
TL;DR: Meinzer et al. as discussed by the authors showed that the response of tropical forest carbon balance to global change is highly dependent on the factors limiting net primary productivity (NPP) in this biome.
Abstract: The response of tropical forest carbon balance to global change is highly dependent on the factors limiting net primary productivity (NPP) in this biome. Current empirical global NPP–climate relationships predict that the response of NPP to climate diminishes at higher levels of mean annual precipitation (MAP) and mean annual temperature (MAT), but data have been relatively scarce in warm and wet tropical ecosystems. By integrating data from a new comprehensive global survey of NPP from tropical forests and a climate gradient from Maui, Hawaii, along with data previously used to develop NPP–climate relationships, I show that there is a strong negative relationship between MAP and NPP in humid ecosystems. The relationships derived here clearly demonstrate that NPP in wet tropical forests is sensitive to climate, and that future forest growth may be limited by increased precipitation forecast by global climate models for the wet tropics. Corresponding Editor: F. C. Meinzer.
TL;DR: Oxygen-isotope ratios of a stalagmite from Socotra Island in the Indian Ocean provide a record of changes in monsoon precipitation and climate for the time period from 42 to 55 thousand years before the present, with increased tropical precipitation associated with warm periods in the high northern latitudes.
Abstract: Oxygen-isotope ratios of a stalagmite from Socotra Island in the Indian Ocean provide a record of changes in monsoon precipitation and climate for the time period from 42 to 55 thousand years before the present. The pattern of precipitation bears a striking resemblance to the oxygen-isotope record from Greenland ice cores, with increased tropical precipitation associated with warm periods in the high northern latitudes. The largest change, at the onset of interstadial 12, occurred very rapidly, in about 25 years. The chronology of the events found in our record requires a reevaluation of previously published time scales for climate events during this period.
TL;DR: In this paper, the first global, multiannual soil moisture data set (1992-2000) has been derived from active microwave data acquired by the European Remote Sensing Satellites (ERS) ERS-1/ERS-2 scatterometer (C-band) and the retrieval algorithm is based on a change detection approach that naturally accounts for surface roughness and heterogeneous land cover.
Abstract: [1] The lack of global soil moisture data has spurred research in the field of microwave remote sensing. Both passive (radiometers) and active (scatterometer) microwave data are very sensitive to the moisture content of the surface soil layer. To retrieve soil moisture, the effects of vegetation, surface roughness, and heterogeneous land cover must be taken into account. Field experiments have shown that passive microwave data at long wavelengths (L-band) are best suited for soil moisture retrieval. Nevertheless, the first global, multiannual soil moisture data set (1992–2000) has been derived from active microwave data acquired by the European Remote Sensing Satellites (ERS) ERS-1 and ERS-2 scatterometer (C-band). The retrieval algorithm is based on a change detection approach that naturally accounts for surface roughness and heterogeneous land cover. In this paper the scatterometer-derived soil moisture data are compared to gridded precipitation data and soil moisture modeled by a global vegetation and water balance model. The correlation between soil moisture and rainfall anomalies is observed to be best over areas with a dense rainfall gauge network. Also, the scatterometer-derived and modeled soil moisture agree reasonably well over tropical and temperate climates. The fact that the algorithm performs equally well for regions with summer rain and Mediterranean areas indicates that dynamic vegetation effects are correctly represented in the retrieval. More research is needed to better understand the backscattering behavior over dry (steppe, deserts) and cold (boreal zone, tundra) climatic regions. The scatterometer-derived soil moisture data are available to other research groups at http://www.ipf.tuwien.ac.at/radar/ers-scat/home.htm.
TL;DR: In this paper, the effect of different ice schemes (i.e., three-class ice scheme, four-class two-moment ice scheme) on precipitation processes is examined and compared.
Abstract: The response of cloud systems to their environment is an important link in a chain of processes responsible for monsoons, frontal depression, El Nino-Southern Oscillation (ENSO) episodes and other climate variations (e.g., 30-60 day intra-seasonal oscillations). Numerical models of cloud properties provide essential insights into the interactions of clouds with each other, with their surroundings, and with land and ocean surfaces. Significant advances are currently being made in the modeling of rainfall and rain-related cloud processes, ranging in scales from the very small up to the simulation of an extensive population of raining cumulus clouds in a tropical- or midlatitude-storm environment. The Goddard Cumulus Ensemble (GCE) model is a multidimensional non-hydrostatic dynamic/microphysical cloud resolving model. It has been used to simulate many different mesoscale convective systems that occurred in various geographic locations. In this paper, recent GCE model improvements (microphysics, radiation and surface processes) will be described as well as their impact on the development of precipitation events from various geographic locations. The performance of these new physical processes will be examined by comparing the model results with observations. Specifically, the impact of different ice schemes (i.e., three-class ice scheme, four-class two-moment ice scheme) on precipitation processes are examined and compared. Spectral bin microphysics are used to investigate precipitation processes under clean and dirty environments. The coupled GCE-radiation model shows that the modulation of relative humidity by radiative processes is the main reason for the diurnal variation of precipitation in the tropics. The coupled GCE-land surface model is used to examine the impact of heterogeneous land surface characteristics (soil-vegetation) on precipitation processes. The effect of ocean flux algorithms (e.g., the TOGA COARE flux algorithm and a simple bulk aerodynamic method) on surface fluxes, environmental convective available potential energy (CAPE) and precipitation processes are compared. In addition, the coupled GCE-ocean mixed layer (OML) model is used to investigate the physical processes that affect the variation of sea surface temperature, mixed layer depth and salinity.
TL;DR: Erosion and precipitation rates inferred from apatite (U–Th)/He cooling ages across the Cascades mountains of Washington state closely track modern mean annual precipitation rates, demonstrating a strong coupling between precipitation and long-term erosion rates on the mountain-range scale.
Abstract: Past studies of tectonically active mountain ranges have suggested strong coupling and feedbacks between climate, tectonics and topography. For example, rock uplift generates topographic relief, thereby enhancing precipitation, which focuses erosion and in turn influences rates and spatial patterns of further rock uplift. Although theoretical links between climate, erosion and uplift have received much attention, few studies have shown convincing correlations between observable indices of these processes on mountain-range scales. Here we show that strongly varying long-term (>10(6)-10(7) yr) erosion rates inferred from apatite (U-Th)/He cooling ages across the Cascades mountains of Washington state closely track modern mean annual precipitation rates. Erosion and precipitation rates vary over an order of magnitude across the range with maxima of 0.33 mm yr(-1) and 3.5 m yr(-1), respectively, with both maxima located 50 km west (windward) of the topographic crest of the range. These data demonstrate a strong coupling between precipitation and long-term erosion rates on the mountain-range scale. If the range is currently in topographic steady state, rock uplift on the west flank is three to ten times faster than elsewhere in the range, possibly in response to climatically focused erosion.
TL;DR: In this article, a snow depth analysis scheme developed by Brasnett and employed at the Canadian Meteorological Centre (CMC) was applied to generate a 3° latitude/longitude grid of monthly mean snow depth and corresponding estimated water equivalent for North America to evaluate GCM snow cover simulations for the Atmospheric Model Intercomparison Project II (AMIP II) for the period 1979-96 Approximately 8000 snow depth observations per day were obtained from US cooperative stations and Canadian climate stations for input to the analysis.
Abstract: Evaluation of snow cover in GCMs has been hampered by a lack of reliable gridded estimates of snow water equivalent (SWE) at continental scales In order to address this gap, a snow depth analysis scheme developed by Brasnett (1999) and employed operationally at the Canadian Meteorological Centre (CMC), was applied to generate a 03° latitude/longitude grid of monthly mean snow depth and corresponding estimated water equivalent for North America to evaluate GCM snow cover simulations for the Atmospheric Model Intercomparison Project II (AMIP II) for the period 1979–96 Approximately 8000 snow depth observations per day were obtained from US cooperative stations and Canadian climate stations for input to the analysis The first‐guess field used a simple snow accumulation, aging and melt model driven by 6‐hourly values of air temperature and precipitation from the European Centre for Medium‐range Weather Forecasting (ECMWF) ERA‐15 Reanalysis with extensions from the Tropical Ocean Global Atmosphe
TL;DR: It is revealed that, in addition to temperature and SWC, rain plays a role in determining the total amount of carbon released from soils, even in a maritime climate.
Abstract: Soil respiration (SR) was monitored periodically throughout 2001 in a Scots pine (Pinus sylvestris L.) stand located in the Belgian Campine region. As expected for a temperate maritime forest, temperature was the dominant control over SR during most of the year. However, during late spring and summer, when soil water content (SWC) was limiting, SR was insensitive to temperature (Q(10) = 1.24). We observed that during prolonged rain-free periods, when SWC was less than 15% (v/v), SR decreased dramatically (up to 50%) and SWC took over control of SR. During such drought periods, however, rain events sometimes stimulated SR and restored temperature control over SR, even though SWC in the mineral soil was low. We hypothesize that restoration of temperature control occurred only when rain events adequately rewetted the uppermost soil layers, where most of the respiratory activity occurred. To quantify the rewetting capacity of rain events, an index (I(w)) was designed that incorporated rainfall intensity, time elapsed since the last rain event, and atmospheric vapor pressure deficit (a proxy for evaporative water losses). To simulate SR fluxes, a model was developed that included the effects of soil temperature and, under drought and non-rewetting conditions (I(w) and SWC < threshold), an SWC response function. The model explained 95% of the temporal variability in SR observed during summer, whereas the temperature function alone explained only 73% of this variability. Our results revealed that, in addition to temperature and SWC, rain plays a role in determining the total amount of carbon released from soils, even in a maritime climate.
TL;DR: In this paper, two atmospheric general circulation models, the ECHAM-4 and the GISS II models, were used to analyze the interannual variability of δ18O in precipitation over the tropical Americas.
Abstract: [1] We use two atmospheric general circulation models (AGCMs), the ECHAM-4 and the GISS II models, to analyze the interannual variability of δ18O in precipitation over the tropical Americas. Several different simulations with isotopic tracers forced with observed global sea surface temperatures (SST) between 1950 and 1998 reveal the influence of varying temperature, precipitation amount, and moisture source contributions on the predicted δ18O distribution. Observational evidence from climatic (NCEP-NCAR) and sparse stable isotope (IAEA-GNIP) data is used to evaluate model performance. The models capture the essential features of surface climate over the tropical Americas in terms of both their spatial and temporal characteristics. Using a low-resolution model (GISS II), adjusted to provide a more realistic Andean topography, or a higher-resolution model (ECHAM-4 T106) leads to an improved δ18O distribution over the tropical Americas with an altitude effect comparable to observations. Water vapor transport and gradual rainout and increasingly depleted composition of water vapor along its trajectory are correctly simulated in both models, although the ECHAM model appears to underestimate the continentality effect over the Amazon basin. A significant dependence of δ18O on the precipitation amount is apparent in both models, in accordance with observations, while the influence of temperature seems to be less significant in most regions and is accurately reproduced by the ECHAM model only. Over most regions, however, the δ18O signal in precipitation is influenced by a combination of factors, such as precipitation amount, temperature, moisture source variability, and atmospheric circulation changes. Over parts of the tropical Americas, the δ18O signal is therefore also significantly correlated with ENSO because ENSO is an integrator of many factors affecting the δ18O composition of precipitation.
TL;DR: In this article, the authors investigated the interactions between a storm and its environmental flow through a numerical simulation of Hurricane Bonnie (1998) that focuses on the role of vertical wind shear in governing azimuthal variations of rainfall.
Abstract: Despite the significant impacts of torrential rainfall from tropical cyclones at landfall, quantitative precipitation forecasting (QPF) remains an unsolved problem A key task in improving tropical cyclone QPF is understanding the factors that affect the intensity and distribution of rainfall around the storm These include the storm motion, topography, and orientation of the coast, and interactions with the environmental flow The combination of these effects can produce rainfall distributions that may be nearly axisymmetric or highly asymmetric and rainfall amounts that range from 1 or 2 cm to >30 cm This study investigates the interactions between a storm and its environmental flow through a numerical simulation of Hurricane Bonnie (1998) that focuses on the role of vertical wind shear in governing azimuthal variations of rainfall The simulation uses the high-resolution nonhydrostatic fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) to simulate the storm between 0000
TL;DR: In this article, a pair of numerical experiments have shown that by altering the complex exchanges of water and energy from surface to atmosphere, the changes in land cover have brought about significant changes to the East Asian monsoon, including weakening of the summer monsoon and enhancement of winter monsoon over the region and a commensurate increase in anomalous northerly flow.
TL;DR: In this article, a 50-year observational precipitation dataset covering the United States was used to investigate the existence of land-atmosphere feedback, by which precipitation-induced soil moisture anomalies affect subsequent precipitation.
Abstract: Land-atmosphere feedback, by which precipitation-induced soil moisture anomalies affect subsequent precipitation, may be an important element of Earth's climate system, but its very existence has never been demonstrated conclusively at regional to continental scales. Evidence for the feedback is sought in a 50-year observational precipitation dataset covering the United States. The precipitation variance and autocorrelation fields are characterized by features that agree (in structure, though not in magnitude) with those produced by an atmospheric general circulation model (AGCM). Because the model-generated features are known to result from land-atmosphere feedback alone, the observed features are highly suggestive of the existence of feedback in nature.
TL;DR: In this paper, the authors describe an assessment of the implications of future climate change for river runoff across the entire world, using six climate models which have been driven by the SRES emissions scenarios.
Abstract: . This paper describes an assessment of the implications of future climate change for river runoff across the entire world, using six climate models which have been driven by the SRES emissions scenarios. Streamflow is simulated at a spatial resolution of 0.5°x0.5° using a macro-scale hydrological model, and summed to produce total runoff for almost 1200 catchments. The effects of climate change have been compared with the effects of natural multi-decadal climatic variability, as determined from a long unforced climate simulation using HadCM3. By the 2020s, change in runoff due to climate change in approximately a third of the catchments is less than that due to natural variability but, by the 2080s, this falls to between 10 and 30%. The climate models produce broadly similar changes in runoff, with increases in high latitudes, east Africa and south and east Asia, and decreases in southern and eastern Europe, western Russia, north Africa and the Middle East, central and southern Africa, much of North America, most of South America, and south and east Asia. The pattern of change in runoff is largely determined by simulated change in precipitation, offset by a general increase in evaporation. There is little difference in the pattern of change between different emissions scenarios (for a given model), and only by the 2080s is there evidence that the magnitudes of change in runoff vary, with emissions scenario A1FI producing the greatest change and B1 the smallest. The inter-annual variability in runoff increases in most catchments due to climate change — even though the inter-annual variability in precipitation is not changed — and the frequency of flow below the current 10-year return period minimum annual runoff increases by a factor of three in Europe and southern Africa and of two across North America. Across most of the world climate change does not alter the timing of flows through the year but, in the marginal zone between cool and mild climates, higher temperatures mean that peak streamflow moves from spring to winter as less winter precipitation falls as snow. The spatial pattern of changes in the 10-year return period maximum monthly runoff follows changes in annual runoff. Keywords: SRES emissions scenarios, climate change impacts on runoff, multi-decadal variability, macro-scale hydrological model, drought frequency, flood frequency
TL;DR: In this article, the authors show that changes in below ground temperatures can be influenced as much by temporal variations of snow cover as by changes in the near-surface air temperature, and that the recent changes in permafrost temperatures on the North Slope of Alaska are consistent with decadal scale variability in snow cover.
Abstract: [1] Air temperatures at high latitudes are expected to rise significantly as anthropogenic carbon builds up in the atmosphere. There is concern that warming of the ground in permafrost regions will result in additional release of carbon to the atmosphere. Recent emphasis has thus been on predicting the magnitude and spatial distribution of future warming at high latitudes. Modeling results show that changes in below ground temperatures can be influenced as much by temporal variations of snow cover as by changes in the near-surface air temperature. The recent (1983–1998) changes in permafrost temperatures on the North Slope of Alaska are consistent with decadal scale variability in snow cover. The implication of these results is that a better understanding of how winter precipitation patterns at high latitudes will change over the coming decades is needed to comprehend evolving permafrost temperatures.
TL;DR: In this article, the authors identified a mechanism that creates regional reductions in precipitation at the margins of convection zones during global warming, which is the leading cause of tropical drought in the global warming case and dominant in certain El Nino drought regions.
Abstract: [1] Climate model global warming simulations predict large regional changes in tropical rainfall, including regions of drought. Qualitatively similar changes occur during El Nino interannual variability. Using an intermediate climate model, we have identified a mechanism that creates regional reductions in precipitation at the margins of convection zones during warming. In this “upped-ante mechanism”, a warm troposphere increases the value of surface boundary layer moisture required for convection to occur. In regions of plentiful moisture supply, moisture simply rises to maintain precipitation, but this increases the moisture gradient relative to neighboring subsidence regions. Reductions in rainfall then result for those margins of convection zones that have strong inflow of air from the subsidence regions and less frequently meet the increased “ante” for convection. In simulations analyzed here, this new mechanism is the leading cause of tropical drought in the global warming case and is dominant in certain El Nino drought regions.