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Scattering Properties and Brightness Temperatures Associated with Solid Precipitation

In the past few years, early solid precipitation detection and retrieval algorithms have been developed and shown to be applicable for snowing clouds and blizzards. NOAA has an operational snow versus rain classifier based on AMSU-B observations. Solid precipitation retrieval algorithms reported in the literature over the past two years include those that rely on neural nets, statistics, or physical relationships. All of the algorithms require the use of millimeter-wave radiometer observations. The millimeter-wave frequencies are especially sensitive to the scattering and emission properties of frozen particles due to the ice particle refractive index. Passive radiometric channels respond to both the integrated particle mass throughout the volume and field of view, and to the amount, location, and size distribution of the frozen (and liquid) particles with the sensitivity varying for different frequencies and hydrometeor types. This investigation probes the sensitivity of scattering and absorption coefficients, and hence computed brightness temperatures, resulting from variations in solid precipitation cloud profiles. The first study compares the single scattering, absorption, and asymmetry parameters associated with snow particles in clouds. Several methodologies are used to convert the physical characteristics (e.g., shape, size distributions, ice-air-water ratios) of ice particles to electromagnetic properties (e.g., absorption, scattering, and asymmetry factors). These methodologies include: conversion to solid ice particles, homogeneous dielectric mixing, or discrete dipole approximation. Changes in the conversion methodology can produce computed brightness temperature differences greater than 50 Kelvin.

Skofronick-Jackson, Gail M.↗

Atmospheric Hydroperoxides in West Antarctica: Links to Stratospheric Ozone and Atmospheric Oxidation Capacity

The troposphere above the West Antarctic Ice Sheet (WAIS) was sampled for hydroperoxides at 21 locations during 2-month-long summer traverses from 2000 to 2002, as part of US ITASE (International Transantarctic Scientific Expedition). First time quantitative measurements using an HPLC method showed that methylhydroperoxide (MHP) is the only important organic hydroperoxide occurring in the Antarctic troposphere, and that it is found at levels ten times those previously predicted by photochemical models. During three field seasons, means and standard deviations for hydrogen peroxide (H2O2) were 321+/-158 pptv, 650+/-176 pptv and 330+/-147 pptv. While MHP was detected, but not quantified in December 2000, levels in summer 2001 and 2002 were 317+128 pptv and 304+/-172.2 pptv. Results from firn air experiments and diurnal variability of the two species showed that atmospheric H2O2 is significantly impacted by a physical snow pack source between 76 and 90degS, whereas MHP is not. We show strong evidence of a positive feedback between stratospheric ozone and H2O2 at the surface. Between November-27 and December-12 in 2001, when ozone column densities dropped below 220 DU (means in 2000 and 2001 were 318 DU and 334 DU, respectively), H2O2 was 1.7 times that observed in the same period in 2000 and 2002, while MHP was only 80% of the levels encountered in 2002. Photochemical box model runs suggest that NO and OH levels on WAIS are closer to coastal values, while Antarctic Plateau levels are higher, confirming that region to be a highly oxidizing environment. The modeled sensitivity of H2O2 and particularly MHP to NO offers the potential to use atmospheric hydroperoxides to constrain the NO background and thus estimate the past oxidation capacity of the remote atmosphere. Index Terms: 0365 Atmospheric Composition and Structure: Troposphere: composition and chemistry; 0322 Atmospheric Composition and Structure: Constituent sources and sinks; 1610 Global Change: Atmosphere (03 15,0325); 0736 Cryosphere: Snow (1827, 1863); 0724 Cryosphere: Ice Cores (4932) Keywords: hydrogen peroxide, methylhydroperoxide, Antarctica, air-snow exchange, stratospheric ozone, atmospheric oxidation capacity

Frey, Markus M.↗

Arctic Warming Signals from Satellite Observations

Global warming signals are expected to be amplified in the Arctic primarily because of ice-albedo feedback associated with the high reflectivity of ice and snow that blankets much of the region. The Arctic had been a poorly explored territory basically because of its general inaccessibility on account of extremely harsh weather conditions and the dominant presence of thick perennial ice in the region. The advent of satellite remote sensing systems since the 1960s, however, enabled the acquisition of synoptic data that depict in good spatial detail the temporal changes of many Arctic surface parameters. Among the surface parameters that have been studied using space based systems are surface temperature, sea ice concentration, snow cover, surface albedo and phytoplankton concentration. Associated atmospheric parameters, such as cloud cover, temperature profile, ozone concentration, and aerosol have also been derived. Recent observational and phenomenological studies have indeed revealed progressively changing conditions in the Arctic during the last few decades (e g , Walsh et al. 1996; Serreze et al 2000; Comiso and Parkinson 2004). The changes included declines in the extent and area of surfaces covered by sea ice and snow, increases in melt area over the Greenland ice sheets, thawing of the permafrost, warming in the troposphere, and retreat of the glaciers. These observations are consistent with the observed global warming that has been associated with the increasing concentration of greenhouse gases in the atmosphere (Karl and Trenberth 2003) and confirmed by modeling studies (Holland and Bitz, 2003). The Arctic system, however, is still not well understood complicated by a largely fluctuating wind circulation and atmospheric conditions (Proshutinsky and Johnson 1997) and controlled by what is now known as the Arctic Oscillation (AO) which provides a measure of the strength of atmospheric activities in the region (Thompson and Wallace 1998). Meanwhile, the observed Arctic conditions since the 1970s have been shown to exhibit a linear behavior that directly contradicts what has been expected from the A0 (Overland, 2005). The decade of the 1990s has been regarded as the warmest decade in the last century and current data indicates that the 2000s may be even a warmer decade than the 1990s further supporting the linear variability. In this paper, we use satellite data to gain insights into the warming Arctic and how the abnormally warm conditions during the last few years are reflected in the region.

Comiso, Josefino C.↗

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. , Over five years of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA s Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface s radiative characteristics. However, roughly 30% of the global land surface, on an annual equal-angle basis, is obscured due to persistent and transient cloud cover, while another 207% is obscured due to ephemeral and seasonal snow effects. This precludes the MOD43B3 albedo products from being directly used in some remote sensing and ground-based applications, climate models, and global change research projects. To provide researchers with the requisite spatially complete global snow-free land surface albedo dataset, an ecosystem-dependent temporal interpolation technique was developed to fill missing or lower quality data and snow covered values from the official MOD43B3 dataset with geophysically realistic values. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the MODIS MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data.

King, Michael D.↗

Percentage Contributions from Atmospheric and Surface Features to Computed Brightness Temperatures

Over the past few years, a few solid precipitation detection and retrieval algorithms have been developed and shown to be applicable for snowing clouds and blizzards. Current precipitating snow retrieval algorithms require the use of millimeter-wave radiometer observations. The millimeter-wave frequencies are especially sensitive to the scattering and emission properties of frozen particles due to the ice particle refractive index. These channels can also be used to discern information about the frozen particles above the melting layer. Passive radiometric channels respond to both the integrated particle mass throughout the volume and field of view, and to the amount, location, and size distribution of the frozen (and liquid) particles with the sensitivity varying for different frequencies and hydrometeor types. This work will show the percentage of the brightness temperature resulting from the liquid hydrometeor, frozen hydrometeor, relative humidity, and surface contributions. The focus will be on precipitating snow events and millimeter-wave frequencies however, other events and frequencies will be included in the analysis.

SkofronickJackson, Gail↗

Spatial Variability of Barrow-Area Shore-Fast Sea Ice and Its Relationships to Passive Microwave Emissivity

Aircraft-acquired passive microwave data, laser radar height observations, RADARSAT synthetic aperture radar imagery, and in situ measurements obtained during the AMSR-Ice03 experiment are used to investigate relationships between microwave emission and ice characteristics over several space scales. The data fusion allows delineation of the shore-fast ice and pack ice in the Barrow area, AK, into several ice classes. Results show good agreement between observed and Polarimetric Scanning Radiometer (PSR)-derived snow depths over relatively smooth ice, with larger differences over ridged and rubbled ice. The PSR results are consistent with the effects on snow depth of the spatial distribution and nature of ice roughness, ridging, and other factors such as ice age. Apparent relationships exist between ice roughness and the degree of depolarization of emission at 10,19, and 37 GHz. This depolarization .would yield overestimates of total ice concentration using polarization-based algorithms, with indications of this seen when the NT-2 algorithm is applied to the PSR data. Other characteristics of the microwave data, such as effects of grounding of sea ice and large contrast between sea ice and adjacent land, are also apparent in the PSR data. Overall, the results further demonstrate the importance of macroscale ice roughness conditions such as ridging and rubbling on snow depth and microwave emissivity.

Maslanik, J. A.↗

ARISE (Antarctic Remote Ice Sensing Experiment) in the East 2003: Validation of Satellite-derived Sea-ice Data Product

Preliminary results are presented from the first validation of geophysical data products (ice concentration, snow thickness on sea ice (h(sub s) and ice temperature (T(sub i))fr om the NASA EOS Aqua AMSR-E sensor, in East Antarctica (in September-October 2003). The challenge of collecting sufficient measurements with which to validate the coarse-resolution AMSR-E data products adequately was addressed by means of a hierarchical approach, using detailed in situ measurements, digital aerial photography and other satellite data. Initial results from a circumnavigation of the experimental site indicate that, at least under cold conditions with a dry snow cover, there is a reasonably close agreement between satellite- and aerial-photo-derived ice concentrations, i.e. 97.2+/-.6% for NT2 and 96.5+/-2.5% for BBA algorithms vs 94.3% for the aerial photos. In general, the AMSR-E concentration represents a slight overestimate of the actual concentration, with the largest discrepancies occurring in regions containing a relatively high proportion of thin ice. The AMSR-E concentrations from the NT2 and BBA algorithms are similar on average, although differences of up to 5% occur in places, again related to thin-ice distribution. The AMSR-E ice temperature (T(sub i)) product agrees with coincident surface measurements to approximately 0.5 C in the limited dataset analyzed. Regarding snow thickness, the AMSR h(sub s) retrieval is a significant underestimate compared to in situ measurements weighted by the percentage of thin ice (and open water) present. For the case study analyzed, the underestimate was 46% for the overall average, but 23% compared to smooth-ice measurements. The spatial distribution of the AMSR-E h(sub s) product follows an expected and consistent spatial pattern, suggesting that the observed difference may be an offset (at least under freezing conditions). Areas of discrepancy are identified, and the need for future work using the more extensive dataset is highlighted.

Massom, Robert A.↗

Analysis of Terrestrial Water Storage Changes from GRACE and GLDAS

Since March 2002, the Gravity Recovery and Climate Experiment (GRACE) has provided first estimates of land water storage variations by monitoring the time-variable component of Earth's gravity field. Here we characterize spatial-temporal variations in terrestrial water storage changes (TWSC) from GRACE and compare them to those simulated with the Global Land Data Assimilation System (GLDAS). Additionally, we use GLDAS simulations to infer how TWSC is partitioned into snow, canopy water and soil water components, and to understand how variations in the hydrologic fluxes act to enhance or dissipate the stores. Results quantify the range of GRACE-derived storage changes during the studied period and place them in the context of seasonal variations in global climate and hydrologic extremes including drought and flood, by impacting land memory processes. The role of the largest continental river basins as major locations for freshwater redistribution is highlighted. GRACE-based storage changes are in good agreement with those obtained from GLDAS simulations. Analysis of GLDAS-simulated TWSC illustrates several key characteristics of spatial and temporal land water storage variations. Global averages of TWSC were partitioned nearly equally between soil moisture and snow water equivalent, while zonal averages of TWSC revealed the importance of soil moisture storage at low latitudes and snow storage at high latitudes. Evapotranspiration plays a key role in dissipating globally averaged terrestrial water storage. Latitudinal averages showed how precipitation dominates TWSC variations in the tropics, evapotranspiration is most effective in the midlatitudes, and snowmelt runoff is a key dissipating flux at high latitudes. Results have implications for monitoring water storage response to climate variability and change, and for constraining land model hydrology simulations.

Syed, Tajdarul H.↗

An Improved Bulk Microphysical Scheme for Studying Precipitation Processes: Comparisons with Other Schemes

Cloud microphysical processes play an important role in non-hydrostatic high-resolution simulations. Over the past decade both research and operational numerical weather prediction models have started using more complex cloud microphysical schemes that were originally developed for high-resolution cloud-resolving models. An improved bulk microphysical parameterization (adopted from the Goddard microphysics schemes) has recently implemented into the Weather Research and Forecasting (WRF) model. This bulk microphysical scheme has three different options --- 2ICE (cloud ice & snow), 3ICE-graupel (cloud ice, snow & graupel) and 3ICE-hail (cloud ice, snow & hail). High-resolution model simulations are conducted to examine the impact of microphysical schemes on two different weather events (a midlatitude linear convective system and an Atlantic hurricane). In addition, this bulk microphysical parameterization is compared with WIRF's three other bulk microphysical schemes.

Tao, W. K.↗

An Operational Assessment of the MODIS False Color Composite with the Great Falls, Montana National Weather Service

The close and productive collaborations between the NWS Warning and Forecast Office (WFO) in Great Falls, MT and the Short Term Prediction and Research Transition (SPORT) Center at NASA/Marshall Space Flight Center have provided a unique opportunity for science sharing and technology transfer. In particular, SPoRT has provided a false color composite product derived from MODIS data, which is part of NASA's Earth Observing System. This product is designed to delineate snow and ice covered ground, bare ground and clouds. The Great Falls WFO has been a test bed of the MODIS false color composite as a tool in operations to monitor the development and dissipation of snow cover In particular, preliminary applications have shown that the product can be used to monitor snow cover in remote locations as well as ice in rivers. This information can lead to improved assessments of flooding potential during post event conditions where rapid melting and runoff are anticipated. The potential of this product on future geostationary satellites may substantially contribute to the NWS mission by providing enhanced situational awareness. The operational use of this product has been transitioned at WFO Great Falls through a process of product implementation, discussions with the service hydrologist and forecasters, and post event analysis. A concentrated assessment period from January to March, 2008 was initiated to investigate the impact of the MODIS false color product on WFO Great Falls' operations. This presentation will emphasize the impact the MODIS false color product had in the WFO's situational awareness and how best this information can be used to influence operational decisions.

Loss, GIna↗

An Analytical Investigation of the Heat Losses from a U.S. Navy K-Type Airship

The heat losses from the envelope surface of a U.S. Navy K-type airship are evaluated to determine if the use of heat is a feasible means of preventing ice and snow accumulations on lighter-than-air craft during flight and when moored uncovered. Consideration is given to heat losses in clear air (no liquid water present in the atmosphere) and in probable conditions of icing and snow. The results of the analysis indicate that the amount of heat required in flight to raise the surface temperature of the entire envelope to the extent considered adequate for ice protection, based on experience with tests of heavier-than-air craft, is very large. Existing types of heating equipment which could be used to supply this quantity of heat would probably be too bulky and heavy to provide a practical flight installation. The heat requirements to provide protection for the nose and stern regions in assumed mild to moderate icing conditions appear to be within the range of the capacity of current types of heating equipment suitable for flight use. The amount of heat necessary to prevent snow accumulations on the upper surface of the airship envelope when moored uncovered under all conditions appear to be excessive for the heating equipment presently available for flight use, but could possibly be achieved with auxiliary ground heating equipment.

Hillendahl, Wesley H.↗

Remote Sensing of Terrestrial Water Storage and Application to Drought Monitoring

Terrestrial water storage (TWS) consists of groundwater, soil moisture and permafrost, surface water, snow and ice, and wet biomass. TWS variability tends to be dominated by snow and ice in polar and alpine regions, by soil moisture in mid-latitudes, and by surface water in wet, tropical regions such as the Amazon (Rodell and Famiglietti, 2001; Bates et al., 2007). Drought may be defined as a period of abnormally dry weather long enough to cause significant deficits in one or more of the TWS components. Thus, along with observations of the agricultural and socioeconomic impacts, measurements of TWS and its components enable quantification of drought severity. Each of the TWS components exhibits significant spatial variability, while installation and maintenance of sufficiently dense monitoring networks is costly and labor-intensive. Thus satellite remote sensing is an appealing alternative to traditional measurement techniques. Several current remote sensing instruments are able to detect variations in one or more TWS variables, including the Advanced Microwave Scanning Radiometer (AMSR) on NASA's Aqua satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra and Aqua. Future satellite missions have been proposed to improve this capability, including the European Space Agency's Soil Moisture Ocean Salinity mission (SMOS) and the Soil Moisture Active Passive (SMAP), Surface Water Ocean Topography (SWOT), and Snow and Cold Land Processes (SCLP) missions recommended by the US National Academy of Science's Decadal Survey for Earth Science (NRC, 2007). However, only one remote sensing technology is able to monitor changes in TWS from the land surface to the base of the deepest aquifer: satellite gravimetry. This paper focuses on NASA's Gravity Recovery and Climate Experiment mission (GRACE; http://www.csr.utexas.edu/grace/) and its potential as a tool for drought monitoring.

Rodell, Matt↗

Contribution of Soil Moisture Information to Streamflow Prediction in the Snowmelt Season: A Continental-Scale Analysis

In areas dominated by winter snowcover, the prediction of streamflow during the snowmelt season may benefit from three pieces of information: (i) the accurate prediction of weather variability (precipitation, etc.) leading up to and during the snowmelt season, (ii) estimates of the amount of snow present during the winter season, and (iii) estimates of the amount of soil moisture underlying the snowpack during the winter season. The importance of accurate meteorological predictions and wintertime snow estimates is obvious. The contribution of soil moisture to streamflow prediction is more subtle yet potentially very important. If the soil is dry below the snowpack, a significant fraction of the snowmelt may be lost to streamflow and potential reservoir storage, since it may infiltrate the soil instead for later evaporation. Such evaporative losses are presumably smaller if the soil below the snowpack is wet. In this paper, we use a state-of-the-art land surface model to quantify the contribution of wintertime snow and soil moisture information -- both together and separately -- to skill in forecasting springtime streamflow. We find that soil moisture information indeed contributes significantly to streamflow prediction skill.

Reichle, Rolf↗

Compact Ku-Band T/R Module for High-Resolution Radar Imaging of Cold Land Processes

Global measurement of terrestrial snow cover is critical to two of the NASA Earth Science focus areas: (1) climate variability and change and (2) water and energy cycle. For radar backscatter measurements, Ku-band frequencies, scattered mainly within the volume of the snowpack, are most suitable for the SWE (snow-water equivalent) measurements. To isolate the complex effects of different snowpack (density and snowgrain size), and underlying soil properties and to distinctly determine SWE, the space-based synthetic aperture radar (SAR) system will require a dual-frequency (13.4 and 17.2 GHz) and dual polarization approach. A transmit/receive (T/R) module was developed operating at Ku-band frequencies to enable the use of active electronic scanning phased-array antenna for wide-swath, high-resolution SAR imaging of terrestrial snow cover. The T/R module has an integrated calibrator, which compensates for all environmental- and time-related changes, and results in very stable power and amplitude characteristics. The module was designed to operate over the full frequency range of 13 to 18 GHz, although only the two frequencies, 13.4 GHz and 17.2 GHz, will be used in this SAR radar application. Each channel of the transmit module produces > 4 W (35 dbm) over the operating bandwidth of 20 MHz. The stability requirements of <0.1 dB receive gain accuracy and <0.1 dB transmit power accuracy over a wide temperature range are achieved using a self-correction scheme, which does real-time amplitude calibration so that the module characteristics are continually corrected. All the calibration circuits are within the T/R module. The timing and calibration sequence is stored in a control FPGA (field-programmable gate array) while an internal 128K 8bit high-speed RAM (random access memory) stores all the calibration values. The module was designed using advanced components and packaging techniques to achieve integration of the electronics in a 2 x6.5x1-in. (5x17x2.5-cm) package. The module size allows 4 T/R modules to feed the 16 16-element subarray on an antenna panel. The T/R module contains four transmit channels and eight receive channels (horizontal and vertical polarizations).

Andricos, Constantine↗

CBSIT 2009: Airborne Validation of Envisat Radar Altimetry and In Situ Ice Camp Measurements Over Arctic Sea Ice

The past few years have seen the emergence of satellite altimetry as valuable tool for taking quantitative sea ice monitoring beyond the traditional surface extent measurements and into estimates of sea ice thickness and volume, parameters that arc fundamental to improved understanding of polar dynamics and climate modeling. Several studies have now demonstrated the use of both microwave (ERS, Envisat/RA-2) and laser (ICESat/GLAS) satellite altimeters for determining sea ice thickness. The complexity of polar environments, however, continues to make sea ice thickness determination a complicated remote sensing task and validation studies remain essential for successful monitoring of sea ice hy satellites. One such validation effort, the Arctic Aircraft Altimeter (AAA) campaign of2006. included underflights of Envisat and ICESat north of the Canadian Archipelago using NASA's P-3 aircraft. This campaign compared Envisat and ICESat sea ice elevation measurements with high-resolution airborne elevation measurements, revealing the impact of refrozen leads on radar altimetry and ice drift on laser altimetry. Continuing this research and validation effort, the Canada Basin Sea Ice Thickness (CBSIT) experiment was completed in April 2009. CBSIT was conducted by NOAA. and NASA as part of NASA's Operation Ice Bridge, a gap-filling mission intended to supplement sea and land ice monitoring until the launch of NASA's ICESat-2 mission. CBIST was flown on the NASA P-3, which was equipped with a scanning laser altimeter, a Ku-band snow radar, and un updated nadir looking photo-imaging system. The CB5IT campaign consisted of two flights: an under flight of Envisat along a 1000 km track similar to that flown in 2006, and a flight through the Nares Strait up to the Lincoln Sea that included an overflight of the Danish GreenArc Ice Camp off the coast of northern Greenland. We present an examination of data collected during this campaign, comparing airborne laser altimeter measurements with (1) Envisat RA-2 returns retracked optimally for sea ice and (2) in situ measurements of sea ice thickness and snow depth gathered from ice camp surveys. Particular attention is given to lead identification and classification using the continuous photo-imaging system along the Envisat underflight as well as the performance of the snow radar over the ice camp survey lines.

Connor, Laurence↗

Prediction of Hydrological Drought: What Can We Learn From Continental-Scale Offline Simulations?

Land surface model experiments are used to quantify, across the coterminous United States, the contributions (isolated and combined) of soil moisture and snowpack initialization to the skill of seasonal streamflow forecasts at multiple leads and for different start dates. Forecasted streamflows are compared to naturalized streamflow observations where available and to synthetic (model-generated) streamflow data elsewhere. We find that snow initialization has a major impact on skill in the mountainous western U.S. and in a portion of the northern Great Plains; a mid-winter (January 1) initialization of snow in these areas leads to significant skill in the spring melting season. Soil moisture initialization also contributes to skill, and although the maximum contributions are not as large as those seen for snow initialization, the soil moisture contributions extend across a much broader geographical area. Soil moisture initialization can contribute to skill at long leads (up to 5 or 6 months), particularly for forecasts issued during winter.

Koster, Randal↗

Enhancing Global Land Surface Hydrology Estimates from the NASA MERRA Reanalysis Using Precipitation Observations and Model Parameter Adjustments

The Modern-Era Retrospective analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis that provides. in addition to atmospheric fields. global estimates of soil moisture, latent heat flux. snow. and runoff for J 979-present. This study introduces a supplemental and improved set of land surface hydrological fields ('MERRA-Land') generated by replaying a revised version of the land component of the MERRA system. Specifically. the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameters in the rainfall interception model, changes that effectively correct for known limitations in the MERRA land surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ERA-Interim reanalysis. MERRA-Land and ERA-Interim root zone soil moisture skills (against in situ observations at 85 US stations) are comparable and significantly greater than that of MERRA. Throughout the northern hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 15 basins in the western US) of MERRA and MERRA-Land is typically higher than that of ERA-Interim. With a few exceptions. the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using '\-tERRA output for land surface hydrological studies.

Reichle, Rolf↗

Effects of Absorbing Aerosols on Accelerated Melting of Snowpack in the Tibetan-Himalayas Region

The impacts of absorbing aerosol on melting of snowpack in the Hindu-Kush-Tibetan-Himalayas (HKTH) region are studied using NASA satellite and GEOS-5 GCM. Results from GCM experiments shows that a 8-10% in the rate of melting of snowpack over the western Himalayas and Tibetan Plateau can be attributed to the aerosol elevated-heat-pump (EHP) feedback effect (Lau et al. 2008), initiated by the absorption of solar radiation by absorbing aerosols accumulated over the Indo-Gangetic Plain and Himalayas foothills. On the other hand, deposition of black carbon on snow surface was estimated to give rise to a reduction in snow surface albedo of 2 - 5%, and an increased annual runoff of 9-24%. From case studies using satellite observations and re-analysis data, we find consistent signals of possible impacts of dust and black carbon aerosol in blackening snow surface, in accelerating spring melting of snowpack in the HKHT, and consequentially in influencing shifts in long-term Asian summer monsoon rainfall pattern.

Lau, William K. M.↗