The role of water vapor in climate. A strategic research plan for the proposed GEWEX water vapor project (GVaP)

The proposed GEWEX Water Vapor Project (GVaP) addresses fundamental deficiencies in the present understanding of moist atmospheric processes and the role of water vapor in the global hydrologic cycle and climate. Inadequate knowledge of the distribution of atmospheric water vapor and its transport is a major impediment to progress in achieving a fuller understanding of various hydrologic processes and a capability for reliable assessment of potential climatic change on global and regional scales. GVap will promote significant improvements in knowledge of atmospheric water vapor and moist processes as well as in present capabilities to model these processes on global and regional scales. GVaP complements a number of ongoing and planned programs focused on various aspects of the hydrologic cycle. The goal of GVaP is to improve understanding of the role of water vapor in meteorological, hydrological, and climatological processes through improved knowledge of water vapor and its variability on all scales. A detailed description of the GVaP is presented

Assessing the utility of geospatial technologies to investigate environmental change within lake systems

Over 50% of the world's population live within 3. km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future

Radiometric Correction of Observations from Microwave Humidity Sounders

The Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Humidity Sounder (MHS) are total power microwave radiometers operating at frequencies near the water vapor absorption line at 183 GHz. The measurements of these instruments are crucial for deriving a variety of climate and hydrological products such as water vapor, precipitation, and ice cloud parameters. However, these measurements are subject to several errors that can be classified into radiometric and geometric errors. The aim of this study is to quantify and correct the radiometric errors in these observations through intercalibration. Since the bias in the calibration of microwave instruments changes with scene temperature, a two-point intercalibration correction scheme was developed based on averages of measurements over the tropical oceans and nighttime polar regions. The intercalibration coefficients were calculated on a monthly basis using measurements averaged over each specified region and each orbit, then interpolated to estimate the daily coefficients. Since AMSU-B and MHS channels operate at different frequencies and polarizations, the measurements from the two instruments were not intercalibrated. Because of the negligible diurnal cycle of both temperature and humidity fields over the tropical oceans, the satellites with the most stable time series of brightness temperatures over the tropical oceans (NOAA-17 for AMSU-B and NOAA-18 for MHS) were selected as the reference satellites and other similar instruments were intercalibrated with respect to the reference instrument. The results show that channels 1, 3, 4, and 5 of AMSU-B on board NOAA-16 and channels 1 and 4 of AMSU-B on board NOAA-15 show a large drift over the period of operation. The MHS measurements from instruments on board NOAA-18, NOAA-19, and MetOp-A are generally consistent with each other. Because of the lack of reference measurements, radiometric correction of microwave instruments remain a challenge, as the intercalibration of these instruments largely depends on the stability of the reference instrument

Snow Cover Monitoring from Remote-Sensing Satellites: Possibilities for Drought Assessment

Snow cover is an important earth surface characteristic because it influences partitioning of the surface radiation, energy, and hydrologic budgets. Snow is also an important source of moisture for agricultural crops and water supply in many higher latitude or mountainous areas. For instance, snowmelt provides approximately 50%–80% of the annual runoff in the western United States (Pagano and Garen, 2006) and Canadian Prairies (Gray et al., 1989; Fang and Pomeroy, 2007), which substantially impacts warm season hydrology. Limited soil moisture reserves from the winter period can result in agricultural drought (i.e., severe early growing season vegetation stress if rainfall deficits occur during that period), which can be prolonged or intensified well into the growing season if relatively dry conditions persist. Snow cover deficits can also result in hydrological drought (i.e., severe deficits in surface and subsurface water reserves including soil moisture, streamflow, reservoir and lake levels, and groundwater) since snowmelt runoff is the primary source of moisture to recharge these reserves for a wide range of agricultural, commercial, ecological, and municipal purposes. Semiarid regions that rely on snowmelt are especially vulnerable to winter moisture shortfalls since these areas are more likely to experience frequent droughts. In the Canadian Prairies, more than half the years of three decades (1910–1920, 1930–1939, and 1980–1989) were in drought. Wheaton et al. (2005) reported exceptionally low precipitation and low snow cover in the winter of 2000–2001, with the greatest anomalies of precipitation in Alberta and western Saskatchewan along with near-normal temperature in most of southern Canada. The reduced snowfall led to lower snow accumulation. A loss in agricultural production over Canada by an estimated $3.6 billion in 2001–2002 was attributed to this drought. Fang and Pomeroy (2008) analyzed the impacts of the most recent and severe drought of 1999/2004–2005 for part of the Canadian Prairies on the water supply of a wetland basin by using a physically based cold region hydrologic modeling system. Simulation results showed that much lower winter precipitation, less snow accumulation, and shorter snow cover duration were associated with much lower discharge from snowmelt runoff to the wetland area during much of the drought period of 1999/2004–2005 than during the nondrought period of 2005/2006

Snow Cover Monitoring from Remote-Sensing Satellites: Possibilities for Drought Assessment

Snow cover is an important earth surface characteristic because it influences partitioning of the surface radiation, energy, and hydrologic budgets. Snow is also an important source of moisture for agricultural crops and water supply in many higher latitude or mountainous areas. For instance, snowmelt provides approximately 50%–80% of the annual runoff in the western United States (Pagano and Garen, 2006) and Canadian Prairies (Gray et al., 1989; Fang and Pomeroy, 2007), which substantially impacts warm season hydrology. Limited soil moisture reserves from the winter period can result in agricultural drought (i.e., severe early growing season vegetation stress if rainfall deficits occur during that period), which can be prolonged or intensified well into the growing season if relatively dry conditions persist. Snow cover deficits can also result in hydrological drought (i.e., severe deficits in surface and subsurface water reserves including soil moisture, streamflow, reservoir and lake levels, and groundwater) since snowmelt runoff is the primary source of moisture to recharge these reserves for a wide range of agricultural, commercial, ecological, and municipal purposes. Semiarid regions that rely on snowmelt are especially vulnerable to winter moisture shortfalls since these areas are more likely to experience frequent droughts. In the Canadian Prairies, more than half the years of three decades (1910–1920, 1930–1939, and 1980–1989) were in drought. Wheaton et al. (2005) reported exceptionally low precipitation and low snow cover in the winter of 2000–2001, with the greatest anomalies of precipitation in Alberta and western Saskatchewan along with near-normal temperature in most of southern Canada. The reduced snowfall led to lower snow accumulation. A loss in agricultural production over Canada by an estimated $3.6 billion in 2001–2002 was attributed to this drought. Fang and Pomeroy (2008) analyzed the impacts of the most recent and severe drought of 1999/2004–2005 for part of the Canadian Prairies on the water supply of a wetland basin by using a physically based cold region hydrologic modeling system. Simulation results showed that much lower winter precipitation, less snow accumulation, and shorter snow cover duration were associated with much lower discharge from snowmelt runoff to the wetland area during much of the drought period of 1999/2004–2005 than during the nondrought period of 2005/2006

Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

Soil moisture is an important component of the hydrological cycle. In the framework of modern flood warning systems, the knowledge of soil moisture is crucial, due to the influence on the soil response in terms of infiltration-runoff. Precipitation-runoff processes, in fact, are related to catchment's hydrological conditions before the precipitation. Thus, an estimation of these conditions is of significant importance to improve the reliability of flood warning systems. Combining such information with other weather-related satellite products (i.e. rain rate estimation) might represent a useful exercise in order to improve our capability to handle (and possibly mitigate or prevent) hydro-geological hazards. <P style='line-height: 20px;'> Remote sensing, in the last few years, has supported several techniques for soil moisture/wetness monitoring. Most of the satellite-based techniques use microwave data, thanks to the all-weather and all-time capability of these data, as well as to their high sensitivity to water content in the soil. On the other hand, microwave data are unfortunately highly affected by the presence of surface roughness or vegetation coverage within the instantaneous satellite field of view (IFOV). Those problems, consequently, strongly limit the efficiency and the reliability of traditional satellite techniques. <P style='line-height: 20px;'> Recently, using data coming from AMSU (Advanced Microwave Sounding Unit), flying aboard NOAA (National Oceanic and Atmospheric Administration) satellites, a new methodology for soil wetness estimation has been proposed. The proposed index, called Soil Wetness Variation Index (<I>SWVI</I>), developed by a multi-temporal analysis of AMSU records, seems able to reduce the problems related to vegetation and/or roughness effects. Such an approach has been tested, with promising results, on the analysis of some flooding events which occurred in Europe in the past. <P style='line-height: 20px;'> In this study, results achieved for the HYDROPTIMET test cases will be analysed and discussed in detail. This analysis allows us to evaluate the reliability and the efficiency of the proposed technique in identifying different amounts of soil wetness variations in different observational conditions. In particular, the proposed indicator was able to document the actual effects of meteorological events, in terms of space-time evolution of soil wetness changes, for all the analysed HYDROPTIMET test cases. Moreover, in some circumstances, the <I>SWVI</I> was able to identify the presence of a sort of 'early' signal in terms of soil wetness variations, which may be regarded as a timely indication of an anomalous value of soil water content. This evidence suggests the opportunity to use such an index in the pre-operational phases of the modern flood warning systems, in order to improve their forecast capabilities and their reliability

The status of environmental satellites and availability of their data products

The latest available information about the status of unclassified environmental satellite (flown by the United States) and their data products is presented. The type of environmental satellites discussed include unmanned earth resource and meteorological satellites, and manned satellites which can act as a combination platform for instruments. The capabilities and data products of projected satellites are discussed along with those of currently operating systems

Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

International audienceSoil moisture is an important component of the hydrological cycle. In the framework of modern flood warning systems, the knowledge of soil moisture is crucial, due to the influence on the soil response in terms of infiltration-runoff. Precipitation-runoff processes, in fact, are related to catchment's hydrological conditions before the precipitation. Thus, an estimation of these conditions is of significant importance to improve the reliability of flood warning systems. Combining such information with other weather-related satellite products (i.e. rain rate estimation) might represent a useful exercise in order to improve our capability to handle (and possibly mitigate or prevent) hydro-geological hazards. Remote sensing, in the last few years, has supported several techniques for soil moisture/wetness monitoring. Most of the satellite-based techniques use microwave data, thanks to the all-weather and all-time capability of these data, as well as to their high sensitivity to water content in the soil. On the other hand, microwave data are unfortunately highly affected by the presence of surface roughness or vegetation coverage within the instantaneous satellite field of view (IFOV). Those problems, consequently, strongly limit the efficiency and the reliability of traditional satellite techniques. Recently, using data coming from AMSU (Advanced Microwave Sounding Unit), flying aboard NOAA (National Oceanic and Atmospheric Administration) satellites, a new methodology for soil wetness estimation has been proposed. The proposed index, called Soil Wetness Variation Index (SWVI), developed by a multi-temporal analysis of AMSU records, seems able to reduce the problems related to vegetation and/or roughness effects. Such an approach has been tested, with promising results, on the analysis of some flooding events which occurred in Europe in the past. In this study, results achieved for the HYDROPTIMET test cases will be analysed and discussed in detail. This analysis allows us to evaluate the reliability and the efficiency of the proposed technique in identifying different amounts of soil wetness variations in different observational conditions. In particular, the proposed indicator was able to document the actual effects of meteorological events, in terms of space-time evolution of soil wetness changes, for all the analysed HYDROPTIMET test cases. Moreover, in some circumstances, the SWVI was able to identify the presence of a sort of "early" signal in terms of soil wetness variations, which may be regarded as a timely indication of an anomalous value of soil water content. This evidence suggests the opportunity to use such an index in the pre-operational phases of the modern flood warning systems, in order to improve their forecast capabilities and their reliability