The use of earth observation techniques to improve catchment-scale pollution predictions

Remote sensing can potentially provide information useful in improving pollution transport modelling in agricultural catchments. Realisation of this potential will depend on the availability of the raw data, development of information extraction techniques, and the impact of the assimilation of the derived information into models. High spatial resolution hyperspectral imagery of a farm near Hereford, UK is analysed. A technique is described to automatically identify the soil and vegetation endmembers within a field, enabling vegetation fractional cover estimation. The aerially-acquired laser altimetry is used to produce digital elevation models of the site. At the subfield scale the hypothesis that higher resolution topography will make a substantial difference to contaminant transport is tested using the AGricultural Non-Point Source (AGNPS) model. Slope aspect and direction information are extracted from the topography at different resolutions to study the effects on soil erosion, deposition, runoff and nutrient losses. Field-scale models are often used to model drainage water, nitrate and runoff/sediment loss, but the demanding input data requirements make scaling up to catchment level difficult. By determining the input range of spatial variables gathered from EO data, and comparing the response of models to the range of variation measured, the critical model inputs can be identified. Response surfaces to variation in these inputs constrain uncertainty in model predictions and are presented. Although optical earth observation analysis can provide fractional vegetation cover, cloud cover and semi-random weather patterns can hinder data acquisition in Northern Europe. A Spring and Autumn cloud cover analysis is carried out over seven UK sites close to agricultural districts, using historic satellite image metadata, climate modelling and historic ground weather observations. Results are assessed in terms of probability of acquisition probability and implications for future earth observation missions. (C) 2003 Elsevier Ltd. All rights reserved.

Mesozoic climates: General circulation models and the rock record

General circulation models (GCMs) use the laws of physics and an understanding of past geography to simulate climatic responses. They are objective in character. However, they tend to require powerful computers to handle vast numbers of calculations. Nevertheless, it is now possible to compare results from different GCMs for a range of times and over a wide range of parameterisations for the past, present and future (e.g. in terms of predictions of surface air temperature, surface moisture, precipitation, etc.). GCMs are currently producing simulated climate predictions for the Mesozoic, which compare favourably with the distributions of climatically sensitive facies (e.g. coals, evaporites and palaeosols). They can be used effectively in the prediction of oceanic upwelling sites and the distribution of petroleum source rocks and phosphorites. Models also produce evaluations of other parameters that do not leave a geological record (e.g. cloud cover, snow cover) and equivocal phenomena such as storminess. Parameterisation of sub-grid scale processes is the main weakness in GCMs (e.g. land surfaces, convection, cloud behaviour) and model output for continental interiors is still too cold in winter by comparison with palaeontological data. The sedimentary and palaeontological record provides an important way that GCMs may themselves be evaluated and this is important because the same GCMs are being used currently to predict possible changes in future climate. The Mesozoic Earth was, by comparison with the present, an alien world, as we illustrate here by reference to late Triassic, late Jurassic and late Cretaceous simulations. Dense forests grew close to both poles but experienced months-long daylight in warm summers and months-long darkness in cold snowy winters. Ocean depths were warm (8 degrees C or more to the ocean floor) and reefs, with corals, grew 10 degrees of latitude further north and south than at the present time. The whole Earth was warmer than now by 6 degrees C or more, giving more atmospheric humidity and a greatly enhanced hydrological cycle. Much of the rainfall was predominantly convective in character, often focused over the oceans and leaving major desert expanses on the continental areas. Polar ice sheets are unlikely to have been present because of the high summer temperatures achieved. The model indicates extensive sea ice in the nearly enclosed Arctic seaway through a large portion of the year during the late Cretaceous, and the possibility of sea ice in adjacent parts of the Midwest Seaway over North America. The Triassic world was a predominantly warm world, the model output for evaporation and precipitation conforming well with the known distributions of evaporites, calcretes and other climatically sensitive facies for that time. The message from the geological record is clear. Through the Phanerozoic, Earth's climate has changed significantly, both on a variety of time scales and over a range of climatic states, usually baldly referred to as "greenhouse" and "icehouse", although these terms disguise more subtle states between these extremes. Any notion that the climate can remain constant for the convenience of one species of anthropoid is a delusion (although the recent rate of climatic change is exceptional). (c) 2006 Elsevier B.V. All rights reserved.

Carbon dioxide induced stomatal closure increases radiative forcing of climate via a rapid reduction in low cloud

We performed an ensemble of twelve five-year experiments using a coupled climate-carbon-cycle model with scenarios of prescribed atmospheric carbon dioxide concentration; CO2 was instantaneously doubled or quadrupled at the start of the experiments. Within these five years, climate feedback is not significantly influenced by the effects of climate change on the carbon system. However, rapid changes take place, within much less than a year, due to the physiological effect of CO2 on plant stomatal conductance, leading to adjustment in the shortwave cloud radiative effect over land, due to a reduction in low cloud cover. This causes a 10% enhancement to the radiative forcing due to CO2, which leads to an increase in the equilibrium warming of 0.4 and 0.7 K for doubling and quadrupling. The implications for calibration of energy-balance models are discussed.

Modelling monsoons: understanding and predicting current and future behaviour

The global monsoon system is so varied and complex that understanding and predicting its diverse behaviour remains a challenge that will occupy modellers for many years to come. Despite the difficult task ahead, an improved monsoon modelling capability has been realized through the inclusion of more detailed physics of the climate system and higher resolution in our numerical models. Perhaps the most crucial improvement to date has been the development of coupled ocean-atmosphere models. From subseasonal to interdecadal time scales, only through the inclusion of air-sea interaction can the proper phasing and teleconnections of convection be attained with respect to sea surface temperature variations. Even then, the response to slow variations in remote forcings (e.g., El Niño—Southern Oscillation) does not result in a robust solution, as there are a host of competing modes of variability that must be represented, including those that appear to be chaotic. Understanding the links between monsoons and land surface processes is not as mature as that explored regarding air-sea interactions. A land surface forcing signal appears to dominate the onset of wet season rainfall over the North American monsoon region, though the relative role of ocean versus land forcing remains a topic of investigation in all the monsoon systems. Also, improved forecasts have been made during periods in which additional sounding observations are available for data assimilation. Thus, there is untapped predictability that can only be attained through the development of a more comprehensive observing system for all monsoon regions. Additionally, improved parameterizations - for example, of convection, cloud, radiation, and boundary layer schemes as well as land surface processes - are essential to realize the full potential of monsoon predictability. A more comprehensive assessment is needed of the impact of black carbon aerosols, which may modulate that of other anthropogenic greenhouse gases. Dynamical considerations require ever increased horizontal resolution (probably to 0.5 degree or higher) in order to resolve many monsoon features including, but not limited to, the Mei-Yu/Baiu sudden onset and withdrawal, low-level jet orientation and variability, and orographic forced rainfall. Under anthropogenic climate change many competing factors complicate making robust projections of monsoon changes. Absent aerosol effects, increased land-sea temperature contrast suggests strengthened monsoon circulation due to climate change. However, increased aerosol emissions will reflect more solar radiation back to space, which may temper or even reduce the strength of monsoon circulations compared to the present day. Precipitation may behave independently from the circulation under warming conditions in which an increased atmospheric moisture loading, based purely on thermodynamic considerations, could result in increased monsoon rainfall under climate change. The challenge to improve model parameterizations and include more complex processes and feedbacks pushes computing resources to their limit, thus requiring continuous upgrades of computational infrastructure to ensure progress in understanding and predicting current and future behaviour of monsoons.

Orographic precipitation in the tropics: experiments in Dominica

The “natural laboratory” of mountainous Dominica (15°N) in the trade wind belt is used to study the physics of tropical orographic precipitation in its purest form, unforced by weather disturbances or by the diurnal cycle of solar heating. A cross-island line of rain gauges and 5-min radar scans from Guadeloupe reveal a large annual precipitation at high elevation (7 m yr^{−1}) and a large orographic enhancement factor (2 to 8) caused primarily by repetitive convective triggering over the windward slope. The triggering is caused by terrain-forced lifting of the conditionally unstable trade wind cloud layer. Ambient humidity fluctuations associated with open-ocean convection may play a key role. The convection transports moisture upward and causes frequent brief showers on the hilltops. The drying ratio of the full air column from precipitation is less than 1% whereas the surface air dries by about 17% from the east coast to the mountain top. On the lee side, a plunging trade wind inversion and reduced instability destroys convective clouds and creates an oceanic rain shadow.

The triggering of orographic rainbands by small-scale topography

The triggering of convective orographic rainbands by small-scale topographic features is investigated through observations of a banded precipitation event over the Oregon Coastal Range and simulations using a cloud-resolving numerical model. A quasi-idealized simulation of the observed event reproduces the bands in the radar observations, indicating the model’s ability to capture the physics of the band-formation process. Additional idealized simulations reinforce that the bands are triggered by lee waves past small-scale topographic obstacles just upstream of the nominal leading edge of the orographic cloud. Whether a topographic obstacle in this region is able to trigger a strong rainband depends on the phase of its lee wave at cloud entry. Convective growth only occurs downstream of obstacles that give rise to lee-wave-induced displacements that create positive vertical velocity anomalies w_c and nearly zero buoyancy anomalies b_c as air parcels undergo saturation. This relationship is quantified through a simple analytic condition involving w_c, b_c, and the static stability N_m^2 of the cloud mass. Once convection is triggered, horizontal buoyancy gradients in the cross-flow direction generate circulations that align the bands parallel to the flow direction.

Sampling uncertainty properties of cloud fraction estimates from random transect observations

[1] Cloud cover is conventionally estimated from satellite images as the observed fraction of cloudy pixels. Active instruments such as radar and Lidar observe in narrow transects that sample only a small percentage of the area over which the cloud fraction is estimated. As a consequence, the fraction estimate has an associated sampling uncertainty, which usually remains unspecified. This paper extends a Bayesian method of cloud fraction estimation, which also provides an analytical estimate of the sampling error. This method is applied to test the sensitivity of this error to sampling characteristics, such as the number of observed transects and the variability of the underlying cloud field. The dependence of the uncertainty on these characteristics is investigated using synthetic data simulated to have properties closely resembling observations of the spaceborne Lidar NASA-LITE mission. Results suggest that the variance of the cloud fraction is greatest for medium cloud cover and least when conditions are mostly cloudy or clear. However, there is a bias in the estimation, which is greatest around 25% and 75% cloud cover. The sampling uncertainty is also affected by the mean lengths of clouds and of clear intervals; shorter lengths decrease uncertainty, primarily because there are more cloud observations in a transect of a given length. Uncertainty also falls with increasing number of transects. Therefore a sampling strategy aimed at minimizing the uncertainty in transect derived cloud fraction will have to take into account both the cloud and clear sky length distributions as well as the cloud fraction of the observed field. These conclusions have implications for the design of future satellite missions. This paper describes the first integrated methodology for the analytical assessment of sampling uncertainty in cloud fraction observations from forthcoming spaceborne radar and Lidar missions such as NASA's Calipso and CloudSat.

Cloud properties and their seasonal and diurnal variability from TOVS path-B

Eight years of cloud properties retrieved from Television Infrared Observation Satellite-N (TIROS-N) Observational Vertical Sounder (TOVS) observations aboard the NOAA polar orbiting satellites are presented. The relatively high spectral resolution of these instruments in the infrared allows especially reliable cirrus identification day and night. This dataset therefore provides complementary information to the International Satellite Cloud Climatology Project (ISCCP). According to this dataset, cirrus clouds cover about 27% of the earth and 45% of the Tropics, whereas ISCCP reports 19% and 25%, respectively. Both global datasets agree within 5% on the amount of single-layer low clouds, at 30%. From 1987 to 1995, global cloud amounts remained stable to within 2%. The seasonal cycle of cloud amount is in general stronger than its diurnal cycle and it is stronger than the one of effective cloud amount, the latter the relevant variable for radiative transfer. Maximum effective low cloud amount over ocean occurs in winter in SH subtropics in the early morning hours and in NH midlatitudes without diurnal cycle. Over land in winter the maximum is in the early afternoon, accompanied in the midlatitudes by thin cirrus. Over tropical land and in the other regions in summer, the maximum of mesoscale high opaque clouds occurs in the evening. Cirrus also increases during the afternoon and persists during night and early morning. The maximum of thin cirrus is in the early afternoon, then decreases slowly while cirrus and high opaque clouds increase. TOVS extends information of ISCCP during night, indicating that high cloudiness, increasing during the afternoon, persists longer during night in the Tropics and subtropics than in midlatitudes. A comparison of seasonal and diurnal cycle of high cloud amount between South America, Africa, and Indonesia during boreal winter has shown strong similarities between the two land regions, whereas the Indonesian islands show a seasonal and diurnal behavior strongly influenced by the surrounding ocean. Deeper precipitation systems over Africa than over South America do not seem to be directly reflected in the horizontal coverage and mesoscale effective emissivity of high clouds.