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Data Assimilation Experiments Using Quality Controlled AIRS Version 5 Temperature Soundings

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains a number of significant improvements over Version 4. Two very significant improvements are described briefly below. 1) The AIRS Science Team Radiative Transfer Algorithm (RTA) has now been upgraded to accurately account for effects of non-local thermodynamic equilibrium on the AIRS observations. This allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval algorithm during both day and night. Following theoretical considerations, tropospheric temperature profile information is obtained almost exclusively from clear column radiances in the 4.3 micron CO2 band in the AIRS Version 5 temperature profile retrieval step. These clear column radiances are a derived product that are indicative of radiances AIRS channels would have seen if the field of view were completely clear. Clear column radiances for all channels are determined using tropospheric sounding 15 micron CO2 observations. This approach allows for the generation of accurate values of clear column radiances and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by-channel clear column radiances. These error estimates are used for quality control of the retrieved products. Based on error estimate thresholds, each temperature profiles is assigned a characteristic pressure, pg, down to which the profile is characterized as good for use for data assimilation purposes. We have conducted forecast impact experiments assimilating AIRS quality controlled temperature profiles using the NASA GEOS-5 data assimilation system, consisting of the NCEP GSI analysis coupled with the NASA FVGCM, at a spatial resolution of 0.5 deg by 0.5 deg. Assimilation of Quality Controlled AIRS temperature profiles down to pg resulted in significantly improved forecast skill compared to that obtained from experiments when all data used operationally by NCEP, except for AIRS data, is assimilated. These forecasts were also significantly better than to those obtained when AIRS radiances (rather than temperature profiles) are assimilated, which is the way AIRS data is used operationally by NCEP and ECMWF.

Susskind, Joel↗

Improving Forecast Skill by Assimilation of Quality Controlled AIRS Version 5 Temperature Soundings

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains two significant improvements over Version 4: 1) Improved physics allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profile T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations are now used primarily in the generation of cloud cleared radiances R(sub i). This approach allows for the generation of accurate values of R(sub i) and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by-channel error estimates for R(sub i). These error estimates are used for Quality Control of the retrieved products. We have conducted forecast impact experiments assimilating AIRS temperature profiles with different levels of Quality Control using the NASA GEOS-5 data assimilation system. Assimilation of Quality Controlled T(p) resulted in significantly improved forecast skill compared to that obtained from analyses obtained when all data used operationally by NCEP, except for AIRS data, is assimilated. We also conducted an experiment assimilating AIRS radiances uncontaminated by clouds, as done operationally by ECMWF and NCEP. Forecast resulting from assimilated AIRS radiances were of poorer quality than those obtained assimilating AIRS temperatures.

Susskind, Joel↗

Radiative Forcing and Temperature Response to Changes in Urban Albedos and Associated CO2 Offsets

The two main forcings that can counteract to some extent the positive forcings from greenhouse gases from pre-industrial times to present-day are the aerosol and related aerosol-cloud forcings, and the radiative response to changes in surface albedo. Here, we quantify the change in radiative forcing and surface temperature that may be obtained by increasing the albedos of roofs and pavements in urban areas in temperate and tropical regions of the globe. Using the catchment land surface model (the land model coupled to the GEOS-5 Atmospheric General Circulation Model), we quantify the response of the total outgoing (outgoing shortwave+longwave) radiation to urban albedo changes. Globally, the total outgoing radiation increased by 0.5 W/square m and temperature decreased by -0.008 K for an average 0.003 increase in albedo. For the U.S. the total outgoing total radiation increased by 2.3 W/square meter, and temperature decreased by approximately 0.03 K for an average 0.01 increase in albedo. These values are for the boreal summer (Tune-July-August). Based on these forcings, the expected emitted CO2 offset for a plausible 0.25 and 0.15 increase in albedos of roofs and pavements, respectively, for all global urban areas, was found to be approximately 57 Gt CO2 . A more meaningful evaluation of the impacts of urban albedo increases on climate and the expected CO2 offsets would require simulations which better characterizes urban surfaces and represents the full annual cycle.

Menon, Surabi↗

Representations of the Stratospheric Polar Vortices in Versions 1 and 2 of the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM)

This study will document the behavior of the polar vortices in two versions of the GEOS CCM. Both versions of the model include the same stratospheric chemistry, They differ in the underlying circulation model. Version 1 of the GEOS CCM is based on the Goddard Earth Observing System, Version 4, general circulation model which includes the finite-volume (Lin-Rood) dynamical core and physical parameterizations from Community Climate Model, Version 3. GEOS CCM Version 2 is based on the GEOS-5 GCM that includes a different tropospheric physics package. Baseline simulations of both models, performed at two-degree spatial resolution, show some improvements in Version 2, but also some degradation, In the Antarctic, both models show an over-persistent stratospheric polar vortex with late breakdown, but the year-to-year variations that are overestimated in Version I are more realistic in Version 2. The implications of this for the interactions with tropospheric climate, the Southern Annular Mode, will be discussed. In the Arctic both model versions show a dominant dynamically forced variabi;ity, but Version 2 has a persistent warm bias in the low stratosphere and there are seasonal differences in the simulations. These differences will be quantified in terms of climate change and ozone loss. Impacts of model resolution, using simulations at one-degree and half-degree, and changes in physical parameterizations (especially the gravity wave drag) will be discussed.

Pawson, S.↗

An Approach to Assess Observation Impact Based on Observation-Minus-Forecast Residuals

Langland and Baker (2004) introduced an approach to assess the impact of observations on the forecasts. In that, a state-space aspect of the forecast is defined and a procedure is derived that relates changes in the aspect with changes in the initial conditions associated with the assimilation of observations) ultimately providing information about the impact of individual observations on the forecast. Some features of the approach are to be noted. The typical choice of forecast aspect employed in related works is rather arbitrary and leads to an incomplete assessment of the observing system. Furthermore, the state-space forecast aspect requires availability of a verification state that should ideally be uncorrelated with the forecast but in practice is not. Lastly, the approach involves the adjoint operator of the entire data assimilation system and as such it is constrained by the validity of this operator. In this presentation, an observation-space metric is used that, for a relatively time-homogeneous observing system, allows inferring observation impact on the forecast without some of the limitations above. Specifically, using observation-minus-forecast residuals leads to an approach with the following features: (i) it suggests a rather natural choice of forecast aspect, directly linked to the analysis system and providing full assessment of the observations; (ii) it naturally avoids introducing undesirable correlations in the forecast aspect by verifying against the observations; and (iii) it does not involve linearization and use of adjoints; therefore being applicable to any length of forecast. The state and observation-space approaches might be complementary to some degree, and involve different limitations and complexities. Illustrations are given using the NASA GEOS-5 data.

Todling, Ricardo↗

Regional Precipitation Forecast with Atmospheric InfraRed Sounder (AIRS) Profile Assimilation

Advanced technology in hyperspectral sensors such as the Atmospheric InfraRed Sounder (AIRS; Aumann et al. 2003) on NASA's polar orbiting Aqua satellite retrieve higher vertical resolution thermodynamic profiles than their predecessors due to increased spectral resolution. Although these capabilities do not replace the robust vertical resolution provided by radiosondes, they can serve as a complement to radiosondes in both space and time. These retrieved soundings can have a significant impact on weather forecasts if properly assimilated into prediction models. Several recent studies have evaluated the performance of specific operational weather forecast models when AIRS data are included in the assimilation process. LeMarshall et al. (2006) concluded that AIRS radiances significantly improved 500 hPa anomaly correlations in medium-range forecasts of the Global Forecast System (GFS) model. McCarty et al. (2009) demonstrated similar forecast improvement in 0-48 hour forecasts in an offline version of the operational North American Mesoscale (NAM) model when AIRS radiances were assimilated at the regional scale. Reale et al. (2008) showed improvements to Northern Hemisphere 500 hPa height anomaly correlations in NASA's Goddard Earth Observing System Model, Version 5 (GEOS-5) global system with the inclusion of partly cloudy AIRS temperature profiles. Singh et al. (2008) assimilated AIRS temperature and moisture profiles into a regional modeling system for a study of a heavy rainfall event during the summer monsoon season in Mumbai, India. This paper describes an approach to assimilate AIRS temperature and moisture profiles into a regional configuration of the Advanced Research Weather Research and Forecasting (WRF-ARW) model using its three-dimensional variational (3DVAR) assimilation system (WRF-Var; Barker et al. 2004). Section 2 describes the AIRS instrument and how the quality indicators are used to intelligently select the highest-quality data for assimilation. Section 3 presents an overall precipitation improvement with AIRS assimilation during a 37-day case study period, and Section 4 focuses on a single case study to further investigate the meteorological impact of AIRS profiles on synoptic scale models. Finally, Section 5 provides a summary of the paper.

Chou, S.-H.↗

Modeling the Frozen-In Anticyclone in the 2005 Arctic Summer Stratosphere

Immediately following the breakup of the 2005 Arctic spring stratospheric vortex, a tropical air mass, characterized by low potential vorticity (PV) and high nitrous oxide (N2O), was advected poleward and became trapped in the easterly summer polar vortex. This feature, known as a "Frozen-In Anticyclone (FrIAC)", was observed in Earth Observing System (EOS) Aura Microwave Limb Sounder (MLS) data to span the potential temperature range from approximately 580 to 1100 K (approximately 25 to 40 km altitude) and to persist from late March to late August 2005. This study compares MLS N2O observations with simulations from the Global Modeling Initiative (GMI) chemistry and transport model, the GEOS-5/MERRA Replay model, and the VanLeer Icosahedral Triangular Advection isentropic transport model to elucidate the processes involved in the lifecycle of the FrIAC which is here divided into three distinct phases. During the "spin-up phase" (March to early April), strong poleward flow resulted in a tight isolated anticyclonic vortex at approximately 70-90 deg N, marked with elevated N2O. GMI, Replay, and VITA all reliably simulted the spin-up of the FrIAC, although the GMI and Replay peak N2O values were too low. The FrIAC became trapped in the developing summer easterly flow and circulated around the polar region during the "anticyclonic phase" (early April to the end of May). During this phase, the FrIAC crossed directly over the pole between the 7th and 14th of April. The VITA and Replay simulations transported the N2O anomaly intact during this crossing, in agreement with MLS, but unrealistic dispersion of the anomaly occurred in the GMI simulation due to excessive numerical mixing of the polar cap. The vortex associated with the FrIAC was apparently resistant to the weak vertical hear during the anticyclonic phase, and it thereby protected the embedded N20 anomaly from stretching. The vortex decayed in late May due to diabatic processes, leaving the N2O anomaly exposed to horizontal and vertical wind shears during the "shearing phase" (June to August). The observed lifetime of the FrIAC during this phase is consistent with time-scales calculated from the ambient horizontal and vertical wind shear. Replay maintained the horizontal structure of the N2O anomaly similar to NILS well into August. The VITA simulation also captured the horizontal structure of the FrIAC during this phase, but VITA eventually developed fine-scale N2O structure not observed in MLS data.

Allen, D. R.↗

Using MERRA Gridded Innovations for Quantifying Uncertainties in Analysis Fields and Diagnosing Observing System Inhomogeneities

MERRA is a NASA reanalysis for the satellite era using a major new version of the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5). The project focuses on historical analyses of the hydrological cycle on a broad range of weather and climate time scales and places the NASA EOS suite of observations in a climate context. The characterization of uncertainty in reanalysis fields is a commonly requested feature by users of such data. While intercomparison with reference data sets is common practice for ascertaining the realism of the datasets, such studies typically are restricted to long term climatological statistics and seldom provide state dependent measures of the uncertainties involved. In principle, variational data assimilation algorithms have the ability of producing error estimates for the analysis variables (typically surface pressure, winds, temperature, moisture and ozone) consistent with the assumed background and observation error statistics. However, these "perceived error estimates" are expensive to obtain and are limited by the somewhat simplistic errors assumed in the algorithm. The observation minus forecast residuals (innovations) by-product of any assimilation system constitutes a powerful tool for estimating the systematic and random errors in the analysis fields. Unfortunately, such data is usually not readily available with reanalysis products, often requiring the tedious decoding of large datasets and not so-user friendly file formats. With MERRA we have introduced a gridded version of the observations/innovations used in the assimilation process, using the same grid and data formats as the regular datasets. Such dataset empowers the user with the ability of conveniently performing observing system related analysis and error estimates. The scope of this dataset will be briefly described. We will present a systematic analysis of MERRA innovation time series for the conventional observing system, including maximum-likelihood estimates of background and observation errors, as well as global bias estimates. Starting with the joint PDF of innovations and analysis increments at observation locations we propose a technique for diagnosing bias among the observing systems, and document how these contextual biases have evolved during the satellite era covered by MERRA.

da Silva, Arlindo↗

Aerosol Observability and Predictability: From Research to Operations for Chemical Weather Forecasting. Lagrangian Displacement Ensembles for Aerosol Data Assimilation

A challenge common to many constituent data assimilation applications is the fact that one observes a much smaller fraction of the phase space that one wishes to estimate. For example, remotely sensed estimates of the column average concentrations are available, while one is faced with the problem of estimating 3D concentrations for initializing a prognostic model. This problem is exacerbated in the case of aerosols because the observable Aerosol Optical Depth (AOD) is not only a column integrated quantity, but it also sums over a large number of species (dust, sea-salt, carbonaceous and sulfate aerosols. An aerosol transport model when driven by high-resolution, state-of-the-art analysis of meteorological fields and realistic emissions can produce skillful forecasts even when no aerosol data is assimilated. The main task of aerosol data assimilation is to address the bias arising from inaccurate emissions, and Lagrangian misplacement of plumes induced by errors in the driving meteorological fields. As long as one decouples the meteorological and aerosol assimilation as we do here, the classic baroclinic growth of error is no longer the main order of business. We will describe an aerosol data assimilation scheme in which the analysis update step is conducted in observation space, using an adaptive maximum-likelihood scheme for estimating background errors in AOD space. This scheme includes e explicit sequential bias estimation as in Dee and da Silva. Unlikely existing aerosol data assimilation schemes we do not obtain analysis increments of the 3D concentrations by scaling the background profiles. Instead we explore the Lagrangian characteristics of the problem for generating local displacement ensembles. These high-resolution state-dependent ensembles are then used to parameterize the background errors and generate 3D aerosol increments. The algorithm has computational complexity running at a resolution of 1/4 degree, globally. We will present the result of assimilating AOD retrievals from MODIS (on both Aqua and TERRA satellites) from AERONET for validation. The impact on the GEOS-5 Aerosol Forecasting will be fully documented.

da Silva, Arlindo↗

New Insights in Tropospheric Ozone and its Variability

We have produced time-slice simulations using the Goddard Earth Observing System Version 5 (GEOS-5) coupled to a comprehensive stratospheric and tropospheric chemical mechanism. These simulations are forced with observed sea surface temperatures over the past 25 years and use constant specified surface emissions, thereby providing a measure of the dynamically controlled ozone response. We examine the model performance in simulating tropospheric ozone and its variability. Here we show targeted comparisons results from our simulations with a multi-decadal tropical tropospheric column ozone dataset obtained from satellite observations of total column ozone. We use SHADOZ ozonesondes to gain insight into the observed vertical response and compare with the simulated vertical structure. This work includes but is not limited to ENSO related variability.

Oman, Luke D.↗

Lessons Learned from Assimilating Altimeter Data into a Coupled General Circulation Model with the GMAO Augmented Ensemble Kalman Filter

Satellite altimetry measurements have provided global, evenly distributed observations of the ocean surface since 1993. However, the difficulties introduced by the presence of model biases and the requirement that data assimilation systems extrapolate the sea surface height (SSH) information to the subsurface in order to estimate the temperature, salinity and currents make it difficult to optimally exploit these measurements. This talk investigates the potential of the altimetry data assimilation once the biases are accounted for with an ad hoc bias estimation scheme. Either steady-state or state-dependent multivariate background-error covariances from an ensemble of model integrations are used to address the problem of extrapolating the information to the sub-surface. The GMAO ocean data assimilation system applied to an ensemble of coupled model instances using the GEOS-5 AGCM coupled to MOM4 is used in the investigation. To model the background error covariances, the system relies on a hybrid ensemble approach in which a small number of dynamically evolved model trajectories is augmented on the one hand with past instances of the state vector along each trajectory and, on the other, with a steady state ensemble of error estimates from a time series of short-term model forecasts. A state-dependent adaptive error-covariance localization and inflation algorithm controls how the SSH information is extrapolated to the sub-surface. A two-step predictor corrector approach is used to assimilate future information. Independent (not-assimilated) temperature and salinity observations from Argo floats are used to validate the assimilation. A two-step projection method in which the system first calculates a SSH increment and then projects this increment vertically onto the temperature, salt and current fields is found to be most effective in reconstructing the sub-surface information. The performance of the system in reconstructing the sub-surface fields is particularly impressive for temperature, but not as satisfactory for salt.

Keppenne, Christian↗

Reactive Nitrogen, Ozone and Ozone Production in the Arctic Troposphere and the Impact of Stratosphere-Troposphere Exchange

We analyze the aircraft observations obtained during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellite (ARCTAS) mission together with the GEOS-5 CO simulation to examine O3 and NOy in the Arctic and sub-Arctic region and their source attribution. Using a number of marker tracers and their probability density distributions, we distinguish various air masses from the background troposphere and examine their contribution to NOx, O3, and O3 production in the Arctic troposphere. The background Arctic troposphere has mean O3 of approximately 60 ppbv and NOx of approximately 25 pptv throughout spring and summer with CO decreases from approximately 145 ppbv in spring to approximately 100 ppbv in summer. These observed CO, NOx and O3 mixing ratios are not notably different from the values measured during the 1988 ABLE-3A and the 2002 TOPSE field campaigns despite the significant changes in the past two decades in processes that could have changed the Arctic tropospheric composition. Air masses associated with stratosphere-troposphere exchange are present throughout the mid and upper troposphere during spring and summer. These air masses with mean O3 concentration of 140-160 ppbv are the most important direct sources of O3 in the Arctic troposphere. In addition, air of stratospheric origin is the only notable driver of net O3 formation in the Arctic due to its sustainable high NOx (75 pptv in spring and 110 pptv in summer) and NOy (approximately 800 pptv in spring and approximately 1100 pptv in summer) levels. The ARCTAS measurements present observational evidence suggesting significant conversion of nitrogen from HNO3 to NOx and then to PAN (a net formation of approximately 120 pptv PAN) in summer when air of stratospheric origin is mixed with tropospheric background during stratosphere-to-troposphere transport. These findings imply that an adequate representation of stratospheric O3 and NOy input are essential in accurately simulating O3 and NOx photochemistry as well as the atmospheric budget of PAN in tropospheric chemistry transport models of the Arctic. Anthropogenic and biomass burning pollution plumes observed during ARCTAS show highly elevated hydrocarbons and NOy (mostly in the form of NOx and PAN), but do not contribute significantly to O3 in the Arctic troposphere except in some of the aged biomass burning plumes sampled during spring. Convection and/or lightning influences are negligible sources of O3 in the Arctic troposphere but can have significant impacts in the upper troposphere in the continental sub-Arctic during summer.

Liang, Q.↗

AIRS Impact on Analysis and Forecast of an Extreme Rainfall Event (Indus River Valley 2010) with a Global Data Assimilation and Forecast System

A set of data assimilation and forecast experiments are performed with the NASA Global data assimilation and forecast system GEOS-5, to compare the impact of different approaches towards assimilation of Advanced Infrared Spectrometer (AIRS) data on the precipitation analysis and forecast skill. The event chosen is an extreme rainfall episode which occurred in late July 11 2010 in Pakistan, causing massive floods along the Indus River Valley. Results show that the assimilation of quality-controlled AIRS temperature retrievals obtained under partly cloudy conditions produce better precipitation analyses, and substantially better 7-day forecasts, than assimilation of clear-sky radiances. The improvement of precipitation forecast skill up to 7 day is very significant in the tropics, and is caused by an improved representation, attributed to cloudy retrieval assimilation, of two contributing mechanisms: the low-level moisture advection, and the concentration of moisture over the area in the days preceding the precipitation peak.

Reale, O.↗

Modeling and Observations of the Response of Tropical Tropospheric Ozone to ENSO

The El Nino-Southern Oscillation (ENSO) is the dominant mode of tropical variability on interannual time scales. ENSO appears to extend its influence into the chemical composition of the tropical troposphere, Recent results have revealed an ENSO induced wave-1 anomaly in observed tropical tropospheric column ozone, This results in a dipole over the western and eastern tropical Pacific, whereby differencing the two regions produces an ozone anomaly with an extremely high correlation to the Nino 3.4 Index. We have successfully reproduced this result using the Goddard Earth Observing System Version 5 (GEOS-5) general circulation model coupled to a comprehensive stratospheric and tropospheric chemical mechanism forced with observed sea surface temperatures over the past 25 years, An examination of the modeled ozone field reveals the vertical contributions of tropospheric ozone to the column over the western and eastern Pacific region, We will show targeted comparisons with SHADOZ ozonesondes over these regions to provide insight into the vertical structure. Also, comparisons with NASA's Aura satellite Microwave Limb Sounder (MLS) and Tropospheric Emissions Spectrometer (TES) instruments and other appropriate data sets will be shown. In addition, the water vapor response to ENSO will be compared to help illuminate its role relative to dynamics in impacting ozone concentrations. These results indicate that the tropospheric ozone response to ENSO is potentially a very useful chemistry-climate diagnostic and should be considered in future modeling assessments.

Oman, L. D.↗

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.↗

Dispersion of the Volcanic Sulfate Cloud from the Mount Pinatubo Eruption

We simulate the transport of the volcanic cloud from the 1991 eruption of Mount Pinatubo with the GEOS-5 general circulation model. Our simulations are in good agreement with observational data. We tested the importance of initial condition corresponding to the specific meteorological situation at the time of the eruption by employing reanalysis from MERRA. We found no significant difference in the transport of the cloud. We show how the inclusion of the interaction between volcanic sulfate aerosol and radiation is essential for a reliable simulation of the transport of the volcanic cloud. The absorption of long wave radiation by the volcanic sulfate induces a rising of the volcanic cloud up to the middle stratosphere, combined with divergent motion from the latitude of the eruption to the tropics. Our simulations indicate that the cloud diffuses to the northern hemisphere through a lower stratospheric pathway, and to mid- and high latitudes of the southern hemisphere through a middle stratospheric pathway, centered at about 30 hPa. The direction of the middle stratospheric pathway depends on the season. We did not detect any significant change of the mixing between tropics and mid- and high latitudes in the southern hemisphere.

Aquila, Valentina↗

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

The impacts of absorbing aerosol on melting of snowpack in the Hindu-Kush-Himalayas-Tibetan Plateau (HKHT) region are studied using in-situ, satellite observations, and GEOS-5 GCM. Based on atmospheric black carbon measurements from the Pyramid observation (~ 5 km elevation) in Mt. Everest, we estimate that deposition of black carbon on snow surface will give rise to a reduction in snow surface albedo of 2- 5 %, and an increased annual runoff of 12-34% for a typical Tibetan glacier. Examination of satellite reflectivity and re-analysis data reveals signals of possible impacts of dust and black carbon in darkening the snow surface, and accelerating spring melting of snowpack in the HKHT, following a build-up of absorbing aerosols in the Indo-Gangetic Plain. Results from GCM experiments show that 8-10% increase in the rate of melting of snowpack over the western Himalayas and Tibetan Plateau can be attributed to the elevated-heat-pump (EHP) feedback effect, initiated from the absorption of solar radiation by dust and black carbon accumulated to great height (~ 5 km) over the Indo-Gangetic Plain and Himalayas foothills in the pre-monsoon season (April-May). The accelerated melting of the snowpack is enabled by an EHP-induced atmosphere-land-snowpack positive feedback involving a) orographic forcing of the monsoon flow by the complex terrain, and thermal forcing of the HKHT region, leading to increased moisture, cloudiness and rainfall over the Himalayas foothills and northern India, b) warming of the upper troposphere over the Tibetan Plateau, and c) an snow albedo-temperature feedback initiated by a transfer of latent and sensible heat from a warmer atmosphere over the HKHT to the underlying snow surface. Results from ongoing modeling work to assess the relative roles of EHP vs. snow-darkening effects on accelerated melting of snowpack in HKHT region will also be discussed.

Lau, William K.↗

Teleconnection, Regime Shift, and Predictability of Climate Extremes: A Case Study for the Russian Heat Wave and Pakistan Flood in Summer 2010

In this talk, we present observational evidence showing that the two major extremes events of the summer of 2010, i.e., the Russian heat wave and the Pakistan flood were physically connected. We find that the Pakistan flood was contributed by a series of unusually heavy rain events over the upper Indus River Basin in July-August. The rainfall regimes shifted from an episodic heavy rain regime in mid-to-late July to a steady heavy rain regime in August. An atmospheric Rossby wave associated with the development of the Russian heat wave was instrumental in spurring the episodic rain events , drawing moisture from the Bay of Bengal and the northern Arabian Sea. The steady rain regime was maintained primarily by monsoon moisture surges from the deep tropics. From experiments with the GEOS-5 forecast system, we assess the predictability of the heavy rain events associated with the Pakistan flood. Preliminary results indicate that there are significantly higher skills in the rainfall forecasts during the episodic heavy rain events in July, compared to the steady rain period in early to mid-August. The change in rainfall predictability may be related to scale interactions between the extratropics and the tropics resulting in a modulation of rainfall predictability by the circulation regimes.

Lau, W. K.↗