Land surface waters play a primary role in the global water cycle and climate. As a consequence, there is a widespread demand for accurate and long‐term quantitative observations of their ...distribution over the whole globe. This study presents the first global data set that quantifies the monthly distribution of surface water extent at ∼25 km sampling intervals over 12 years (1993–2004). These estimates, generated from complementary multiple‐satellite observations, including passive (Special Sensor Microwave Imager) and active (ERS scatterometer) microwaves along with visible and near‐infrared imagery (advanced very high‐resolution radiometer; AVHRR), were first developed over 1993–2000. The ERS encountered technical problems in 2001 and the processing scheme had to be adapted to extend the time series. Here we investigate and discuss the adjustments of the methodology, compare the various options, and show that the data set can be extended with good confidence beyond 2000, using ERS and AVHRR mean monthly climatologies. In addition to a large seasonal and interannual variability, the new results show a slight overall decrease in global inundated area between 1993 and 2004, representing an ∼5.7% reduction of the mean annual maximum in 12 years. The decrease is mainly observed in the tropics during the 1990s. Over inland water bodies and large river basins, we assess the variability of the surface water extent against related variables such as in situ river discharges, altimeter‐derived and in situ river/floodplain water level heights, and precipitation estimates. This new 12 year data set of global surface water extent represents an unprecedented source of information for future hydrological or methane modeling.
Clouds cover about 70% of Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere ...over the entire globe and across the wide range of spatial and temporal scales that compose weather and climate variability. Satellite cloud data records now exceed more than 25 years; however, climate data records must be compiled from different satellite datasets and can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors and retrieval methods. The Global Energy and Water Cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel (GEWEX Data and Assessment Panel since 2011), provides the first coordinated intercomparison of publicly available, standard global cloud products (gridded monthly statistics) retrieved from measurements of multispectral imagers (some with multiangle view and polarization capabilities), IR sounders, and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature, or altitude), cloud thermodynamic phase, and cloud radiative and bulk microphysical properties (optical depth or emissivity, effective particle radius, and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. The monthly gridded database presented here facilitates further assessments, climate studies, and the evaluation of climate models.
Wetlands and surface waters are recognized to play important roles in climate, hydrologic and biogeochemical cycles, and availability of water resources. Until now, quantitative, global time series ...of spatial and temporal dynamics of inundation have been unavailable. This study presents the first global estimate of monthly inundated areas for 1993–2000. The data set is derived from a multisatellite method employing passive microwave land surface emissivities calculated from SSM/I and ISCCP observations, ERS scatterometer responses, and AVHRR visible and near‐infrared reflectances. The satellite data are used to calculate inundated fractions of equal area grid cells (0.25° × 0.25° at the equator), taking into account the contribution of vegetation to the passive microwave signal. Global inundated area varies from a maximum of 5.86 × 106 km2 (average for 1993–2000) to a mean minimum of 2.12 × 106 km2. These values are considered consistent with existing independent, static inventories. The new multisatellite estimates also show good agreement with regional high‐resolution SAR observations over the Amazon basin. The seasonal and interannual variations in inundation have been evaluated against rain rate estimates from the Global Precipitation Climatology Project (GPCP) and water levels in wetlands, lakes, and rivers measured with satellite altimeters. The inundation data base is now being used for hydrology modeling and methane studies in GCMs.
We developed a remote sensing approach based on multi‐satellite observations, which provides an unprecedented estimate of monthly distribution and area of land‐surface open water over the whole ...globe. Results for 1993 to 2007 exhibit a large seasonal and inter‐annual variability of the inundation extent with an overall decline in global average maximum inundated area of 6% during the fifteen‐year period, primarily in tropical and subtropical South America and South Asia. The largest declines of open water are found where large increases in population have occurred over the last two decades, suggesting a global scale effect of human activities on continental surface freshwater: denser population can impact local hydrology by reducing freshwater extent, by draining marshes and wetlands, and by increasing water withdrawals.
Key Points
The monthly extent of global land surface water is estimated by satellites
A large variability of the surface water extent is evidenced at global scale
The effect of human activities on continental surface water is observed
A global intercomparison of 12 monthly mean land surface heat flux products for the period 1993-1995 is presented. The intercomparison includes some of the first emerging global satellite-based ...products (developed at Paris Observatory, Max Planck Institute for Biogeochemistry, University of California Berkeley, University of Maryland, and Princeton University) and examples of fluxes produced by reanalyses (ERA-Interim, MERRA, NCEP-DOE) and off-line land surface models (GSWP-2, GLDAS CLM/ Mosaic/Noah). An intercomparison of the global latent heat flux (Q(sub le)) annual means shows a spread of approx 20 W/sq m (all-product global average of approx 45 W/sq m). A similar spread is observed for the sensible (Q(sub h)) and net radiative (R(sub n)) fluxes. In general, the products correlate well with each other, helped by the large seasonal variability and common forcing data for some of the products. Expected spatial distributions related to the major climatic regimes and geographical features are reproduced by all products. Nevertheless, large Q(sub le)and Q(sub h) absolute differences are also observed. The fluxes were spatially averaged for 10 vegetation classes. The larger Q(sub le) differences were observed for the rain forest but, when normalized by mean fluxes, the differences were comparable to other classes. In general, the correlations between Q(sub le) and R(sub n) were higher for the satellite-based products compared with the reanalyses and off-line models. The fluxes were also averaged for 10 selected basins. The seasonality was generally well captured by all products, but large differences in the flux partitioning were observed for some products and basins.
For the period 2003–2004 and for six large river basins, the present study compares monthly time series of multi‐satellite‐derived surface water extent with other independent global data sets related ...to land water dynamics, such as water mass variations monitored by GRACE, simulated surface and total water storage from WGHM, water levels from altimetry, and GPCP precipitation estimates. In general, the datasets show a strong agreement with each other at seasonal timescale. In particular, over the Amazon and the Ganges basins, analysis of seasonal phase differences and hysteresis behavior between surface water extent, water level and storage reveal the complex relations between water extent and storage variations and the different effects of water transport processes within large river basins. The results highlight the value of combining multi‐satellite techniques for retrieving surface water storage dynamics.
Tropical cirrus evolution and its relation to upper-tropospheric water vapor (UTWV) are examined in the paper by analyzing satellite-derived cloud data, UTWV data from infrared and microwave ...measurements, and the NCEP–NCAR reanalysis wind field. Building upon the existing International Satellite Cloud Climatology Project (ISCCP) data and the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) product, a global (except polar region), 6-hourly cirrus dataset is developed from two infrared radiance measurements at 11 and 12μm. The UTWV is obtained in both clear and cloudy locations by developing a combined satellite infrared and microwave-based retrieval. The analysis in this study is conducted in a Lagrangian framework. The Lagrangian trajectory analysis shows that the decay of deep convection is immediately followed by the growth of cirrostratus and cirrus, and then the decay of cirrostratus is followed by the continued growth of cirrus. Cirrus properties continuously evolve along the trajectories as they gradually thin out and move to the lower levels. Typical tropical cirrus systems last for 19–30 ± 16 h. This is much longer than cirrus particle lifetimes, suggesting that other processes (e.g., large-scale lifting) replenish the particles to maintain tropical cirrus. Consequently, tropical cirrus can advect over large distances, about 600–1000 km, during their lifetimes. For almost all current GCMs, this distance spans more than one grid box, requiring that the water vapor and cloud water budgets include an advection term. Based on their relationship to convective systems, detrainment cirrus are distinguished from in situ cirrus. It is found that more than half of the tropical cirrus are formed in situ well away from convection. The interaction between cirrus and UTWV is explored by comparing the evolution of the UTWV along composite clear trajectories and trajectories with cirrus. Cirrus are found to be associated with a moister upper troposphere and a slower rate of decrease of UTWV. Moreover, the elevated UTWV has a longer duration than cirrus. The amount of water in cirrus is too small for evaporation of cirrus ice particles to moisten the upper troposphere significantly (but cirrus may be an important water vapor sink). Rather, it is likely that the same transient motions that produce the cirrus also transport water vapor upward to maintain a larger UTWV.
This paper describes the new global long-term International Satellite Cloud
Climatology Project (ISCCP) H-series climate data record (CDR). The H-series
data contain a suite of level 2 and 3 products ...for monitoring the
distribution and variation of cloud and surface properties to better
understand the effects of clouds on climate, the radiation budget, and the
global hydrologic cycle. This product is currently available for public use
and is derived from both geostationary and polar-orbiting satellite imaging
radiometers with common visible and infrared (IR) channels. The H-series data
currently span July 1983 to December 2009 with plans for continued
production to extend the record to the present with regular updates. The
H-series data are the longest combined geostationary and polar orbiter
satellite-based CDR of cloud properties. Access to the data is provided in
network common data form (netCDF) and archived by NOAA's National Centers for
Environmental Information (NCEI) under the satellite Climate Data Record
Program (https://doi.org/10.7289/V5QZ281S). The basic
characteristics, history, and evolution of the dataset are presented herein
with particular emphasis on and discussion of product changes between the
H-series and the widely used predecessor D-series product which also spans
from July 1983 through December 2009. Key refinements included in the ISCCP
H-series CDR are based on improved quality control measures, modified
ancillary inputs, higher spatial resolution input and output products,
calibration refinements, and updated documentation and metadata to bring the
H-series product into compliance with existing standards for climate data
records.
The analysis of microwave observations over land to determine atmospheric and surface parameters is still limited due to the complexity of the inverse problem. Neural network techniques have already ...proved successful as the basis of efficient retrieval methods for nonlinear cases; however, first guess estimates, which are used in variational assimilation methods to avoid problems of solution nonuniqueness or other forms of solution irregularity, have up to now not been used with neural network methods. In this study, a neural network approach is developed that uses a first guess. Conceptual bridges are established between the neural network and variational assimilation methods. The new neural method retrieves the surface skin temperature, the integrated water vapor content, the cloud liquid water path and the microwave surface emissivities between 19 and 85 GHz over land from Special Sensor Microwave Imager observations. The retrieval, in parallel, of all these quantities improves the results for consistancy reasons. A database to train the neural network is calculated with a radiative transfer model and a global collection of coincident surface and atmospheric parameters extracted from the National Center for Environmental Prediction reanalysis, from the International Satellite Cloud Climatology Project data, and from microwave emissivity atlases previously calculated. The results of the neural network inversion are very encouraging. The theoretical RMS error of the surface temperature retrieval over the globe is 1.3 K in clear‐sky conditions and 1.6 K in cloudy scenes. Water vapor is retrieved with a theoretical RMS error of 3.8 kg m−2 in clear conditions and 4.9 kg m−2 in cloudy situations. The theoretical RMS error in cloud liquid water path is 0.08 kg m−2. The surface emissivities are retrieved with an accuracy of better than 0.008 in clear conditions and 0.010 in cloudy conditions. Microwave land surface temperature retrieval presents a very attractive complement to the infrared estimates in cloudy areas: time record of land surface temperature will be produced.
Radiative flux changes induced by the occurrence of different cloud types are investigated using International Satellite Cloud Climatology Project cloud data and a refined radiative transfer model ...from National Aeronautics and Space Administration/Goddard Institute for Space Studies general circulation model. Cloud types are defined by their top height and optical thickness. Cloud-type variations are shown to be as important as cloud cover in modifying the radiation field of the earth–atmosphere system. Other variables, such as the solar insolation and atmospheric and surface properties, also play significant roles in determining regional cloud radiative effects. The largest “annual” mean (approximated by averaging the results of four particular days, one from each season) changes of the global top-of-atmosphere and surface shortwave radiative fluxes are produced by stratocumulus, altostratus, and cirrostratus clouds (i.e., clouds with moderate optical thicknesses). Cirrus, cirrostratus, and deep convective clouds (i.e., the highest-level clouds) cause most of the annual mean changes in the global top-of-atmosphere longwave radiative fluxes; whereas the largest annual mean changes of the global surface longwave radiative fluxes are caused by stratocumulus, cumulus, and altostratus.
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