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A. H. CHRISTENSEN

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Peter A. G. Watson, H. M. Christensen, and T. N. Palmer

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Important questions concerning parameterization of tropical convection are how should subgrid-scale variability be represented and which large-scale variables should be used in the parameterizations? Here the statistics of observational data in Darwin, Australia, are compared with those of short-term forecasts of convection made by the European Centre for Medium-Range Weather Forecasts Integrated Forecast System. The forecasts use multiplicative-noise stochastic physics (MNSP) that has led to many improvements in weather forecast skill. However, doubts have recently been raised about whether MNSP is consistent with observations of tropical convection. It is shown that the model can reproduce the variability of convection intensity for a given large-scale state, both with and without MNSP. Therefore MNSP is not inconsistent with observations, and much of the modeled variability arises from nonlinearity of the deterministic part of the convection scheme. It is also shown that the model can reproduce the lack of correlation between convection intensity and large-scale CAPE and an entraining CAPE, even though the convection parameterization assumes that deep convection is more intense when the vertical temperature profile is more unstable, with entrainment taken into account. Relationships between convection and large-scale convective inhibition and vertical velocity are also correctly captured.

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Sebastian H. Mernild, Glen E. Liston, Christopher A. Hiemstra, and Jens H. Christensen

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Fluctuations in the Greenland ice sheet (GrIS) surface mass balance (SMB) and freshwater influx to the surrounding oceans closely follow climate fluctuations and are of considerable importance to the global eustatic sea level rise. A state-of-the-art snow-evolution modeling system (SnowModel) was used to simulate variations in the GrIS melt extent, surface water balance components, changes in SMB, and freshwater influx to the ocean. The simulations are based on the Intergovernmental Panel on Climate Change scenario A1B modeled by the HIRHAM4 regional climate model (RCM) using boundary conditions from the ECHAM5 atmosphere–ocean general circulation model (AOGCM) from 1950 through 2080. In situ meteorological station [Greenland Climate Network (GC-Net) and World Meteorological Organization (WMO) Danish Meteorological Institute (DMI)] observations from inside and outside the GrIS were used to validate and correct RCM output data before they were used as input for SnowModel. Satellite observations and independent SMB studies were used to validate the SnowModel output and confirm the model’s robustness. The authors simulated an ∼90% increase in end-of-summer surface melt extent (0.483 × 106 km2) from 1950 to 2080 and a melt index (above 2000-m elevation) increase of 138% (1.96 × 106 km2 × days). The greatest difference in melt extent occurred in the southern part of the GrIS, and the greatest changes in the number of melt days were seen in the eastern part of the GrIS (∼50%–70%) and were lowest in the west (∼20%–30%). The rate of SMB loss, largely tied to changes in ablation processes, leads to an enhanced average loss of 331 km3 from 1950 to 2080 and an average SMB level of −99 km3 for the period 2070–80. GrIS surface freshwater runoff yielded a eustatic rise in sea level from 0.8 ± 0.1 (1950–59) to 1.9 ± 0.1 mm (2070–80) sea level equivalent (SLE) yr−1. The accumulated GrIS freshwater runoff contribution from surface melting equaled 160-mm SLE from 1950 through 2080.

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Sebastian H. Mernild, Glen E. Liston, Christopher A. Hiemstra, Jens H. Christensen, Martin Stendel, and Bent Hasholt

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A regional atmospheric model, the HIRHAM4 regional climate model (RCM) using boundary conditions from the ECHAM5 atmosphere–ocean general circulation model (AOGCM), was downscaled to a 500-m gridcell increment using SnowModel to simulate 131 yr (1950–2080) of hydrologic cycle evolution in west Greenland’s Kangerlussuaq drainage. Projected changes in the Greenland Ice Sheet (GrIS) surface mass balance (SMB) and runoff are relevant for potential hydropower production and prediction of ecosystem changes in sensitive Kangerlussuaq Fjord systems. Mean annual surface air temperatures and precipitation in the Kangerlussuaq area were simulated to increase by 3.4°C and 95 mm water equivalent (w.eq.), respectively, between 1950 and 2080. The local Kangerlussuaq warming was less than the average warming of 4.8°C simulated for the entire GrIS. The Kangerlussuaq SMB loss increased by an average of 0.3 km3 because of a 0.4 km3 rise in precipitation, 0.1 km3 rise in evaporation and sublimation, and 0.6 km3 gain in runoff (1950–2080). By 2080, the spring runoff season begins approximately three weeks earlier. The average modeled SMB and runoff is approximately −0.1 and 1.2 km3 yr−1, respectively, indicating that ∼10% of the Kangerlussuaq runoff is explained by the GrIS SMB net loss. The cumulative net volume loss (1950–2080) from SMB was 15.9 km3, and runoff was 151.2 km3 w.eq. This runoff volume is expected to have important hydrodynamic and ecological impacts on the stratified salinity in the Kangerlussuaq Fjord and on the transport of freshwater to the ocean.

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R. A. Christensen, R. F. Eilbert, O. H. Lindgren, and L. L. Rans

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The Entropy Minimax technique from information theory has been applied to long-range, hydrologic forecasting in California. Based on 1852–1977 records, the technique exhibits a limited, but statistically significant, success for predictions one year ahead. A seven-station precipitation index having a 126 water-year base period was chosen as the dependent variable to represent the area's hydrologic status. Random division of the water years into training (model building) and test (reserved for verification only) halves was strictly enforced and a “one-try-only” constraint was placed on predictive runs. Predictions were formulated by an analog selection procedure based on patterns found in a 42-dimensional space of independent variables. These had been extracted by selection, compression and filtering from a data base containing over 100 000 time series. Wet/dry predictions (above or below median), validated on the test water years, demonstrated a 63% accuracy with a 94% confidence that this success is not due to chance. The accuracy rose to 78% when borderline SSPI years were omitted from the validation set, a result significant at the 0.4% level. By comparison, a predictor based on persistence alone is essentially random.

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W. J. Gutowski Jr., E. S. Takle, K. A. Kozak, J. C. Patton, R. W. Arritt, and J. H. Christensen

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Changes in daily precipitation versus intensity under a global warming scenario in two regional climate simulations of the United States show a well-recognized feature of more intense precipitation. More important, by resolving the precipitation intensity spectrum, the changes show a relatively simple pattern for nearly all regions and seasons examined whereby nearly all high-intensity daily precipitation contributes a larger fraction of the total precipitation, and nearly all low-intensity precipitation contributes a reduced fraction. The percentile separating relative decrease from relative increase occurs around the 70th percentile of cumulative precipitation, irrespective of the governing precipitation processes or which model produced the simulation. Changes in normalized distributions display these features much more consistently than distribution changes without normalization.

Further analysis suggests that this consistent response in precipitation intensity may be a consequence of the intensity spectrum’s adherence to a gamma distribution. Under the gamma distribution, when the total precipitation or number of precipitation days changes, there is a single transition between precipitation rates that contribute relatively more to the total and rates that contribute relatively less. The behavior is roughly the same as the results of the numerical models and is insensitive to characteristics of the baseline climate, such as average precipitation, frequency of rain days, and the shape parameter of the precipitation’s gamma distribution. Changes in the normalized precipitation distribution give a more consistent constraint on how precipitation intensity may change when climate changes than do changes in the nonnormalized distribution. The analysis does not apply to extreme precipitation for which the theory of statistical extremes more likely provides the appropriate description.

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K. Dethloff, M. Schwager, J. H. Christensen, S. Kiilsholm, A. Rinke, W. Dorn, F. Jung-Rothenhäusler, H. Fischer, S. Kipfstuhl, and H. Miller

Abstract

The accumulation defined as “precipitation minus evaporation” over Greenland has been simulated with the high-resolution limited-area regional climate model HIRHAM4 applied over an Arctic integration domain. This simulation is compared with a revised estimate of annual accumulation rate distribution over Greenland taking into account information from a new set of ice core analyses, based on surface sample collections from the North Greenland Traverse. The region with accumulation rates below 150 mm yr−1 in central-northwest Greenland is much larger than previously assumed and extends about 500 km farther to the south. It is demonstrated that good agreement between modeled and observed regional precipitation and accumulation patterns exists, particularly concerning the location and the values of very low accumulation in the middle of Greenland. The accumulation rates in the northern part of Greenland are reduced in comparison to previous estimates. These minima are connected with a prevailing blocking high over the Greenland ice sheet and katabatic wind systems preventing humidity transports to central Greenland. The model reasonably represents the synoptic situations that lead to precipitation. Maxima of precipitation and accumulation occur at the southwestern and southeastern coasts of Greenland and are connected with cyclonic activity and the main storm tracks around Greenland. The central region of the Greenland ice sheet acts as a blocking barrier on moving weather systems and prohibits cyclones moving from west to east across this region and, thus prevents moisture transports.

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P. L. Langen, R. H. Mottram, J. H. Christensen, F. Boberg, C. B. Rodehacke, M. Stendel, D. van As, A. P. Ahlstrøm, J. Mortensen, S. Rysgaard, D. Petersen, K. H. Svendsen, G. Aðalgeirsdóttir, and J. Cappelen

Abstract

Freshwater runoff to fjords with marine-terminating glaciers along the Greenland Ice Sheet margin has an impact on fjord circulation and potentially ice sheet mass balance through increasing heat transport to the glacier front. Here, the authors use the high-resolution (5.5 km) HIRHAM5 regional climate model, allowing high detail in topography and surface types, to estimate freshwater input to Godthåbsfjord in southwest Greenland. Model output is compared to hydrometeorological observations and, while simulated daily variability in temperature and downwelling radiation shows high correlation with observations (typically >0.9), there are biases that impact the results. In particular, overestimated albedo leads to underestimation of melt and runoff at low elevations.

In the model simulation (1991–2012), the ice sheet experiences increasing energy input from the surface turbulent heat flux (up to elevations of 2000 m) and shortwave radiation (at all elevations). Southerly wind anomalies and declining cloudiness due to an increase in atmospheric pressure over north Greenland contribute to increased summer melt. This results in declining surface mass balance (SMB), increasing surface runoff, and upward shift of the equilibrium line altitude.

SMB is reconstructed back to 1890 though regression between simulated SMB and observed temperature and precipitation, with added uncertainty in the period 1890–1952 because of possible inhomogeneity in the precipitation record. SMB as low as in recent years appears to have occurred before, most notably around 1930, 1950, and 1960. While previous low SMBs were mainly caused by low accumulation, those around 1930 and in the 2000s are mainly due to warming.

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Christopher J. Anderson, Raymond W. Arritt, Zaitao Pan, Eugene S. Takle, William J. Gutowski Jr., Francis O. Otieno, Renato da Silva, Daniel Caya, Jens H. Christensen, Daniel Lüthi, Miguel A. Gaertner, Clemente Gallardo, Filippo Giorgi, René Laprise, Song-You Hong, Colin Jones, H-M. H. Juang, J. J. Katzfey, John L. McGregor, William M. Lapenta, Jay W. Larson, John A. Taylor, Glen E. Liston, Roger A. Pielke Sr., and John O. Roads

Abstract

Thirteen regional climate model (RCM) simulations of June–July 1993 were compared with each other and observations. Water vapor conservation and precipitation characteristics in each RCM were examined for a 10° × 10° subregion of the upper Mississippi River basin, containing the region of maximum 60-day accumulated precipitation in all RCMs and station reports.

All RCMs produced positive precipitation minus evapotranspiration (PE > 0), though most RCMs produced PE below the observed range. RCM recycling ratios were within the range estimated from observations. No evidence of common errors of E was found. In contrast, common dry bias of P was found in the simulations.

Daily cycles of terms in the water vapor conservation equation were qualitatively similar in most RCMs. Nocturnal maximums of P and C (convergence) occurred in 9 of 13 RCMs, consistent with observations. Three of the four driest simulations failed to couple P and C overnight, producing afternoon maximum P. Further, dry simulations tended to produce a larger fraction of their 60-day accumulated precipitation from low 3-h totals.

In station reports, accumulation from high (low) 3-h totals had a nocturnal (early morning) maximum. This time lag occurred, in part, because many mesoscale convective systems had reached peak intensity overnight and had declined in intensity by early morning. None of the RCMs contained such a time lag. It is recommended that short-period experiments be performed to examine the ability of RCMs to simulate mesoscale convective systems prior to generating long-period simulations for hydroclimatology.

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Jonathan Spinoni, Paulo Barbosa, Edoardo Bucchignani, John Cassano, Tereza Cavazos, Jens H. Christensen, Ole B. Christensen, Erika Coppola, Jason Evans, Beate Geyer, Filippo Giorgi, Panos Hadjinicolaou, Daniela Jacob, Jack Katzfey, Torben Koenigk, René Laprise, Christopher J. Lennard, M. Levent Kurnaz, Delei Li, Marta Llopart, Niall McCormick, Gustavo Naumann, Grigory Nikulin, Tugba Ozturk, Hans-Juergen Panitz, Rosmeri Porfirio da Rocha, Burkhardt Rockel, Silvina A. Solman, Jozef Syktus, Fredolin Tangang, Claas Teichmann, Robert Vautard, Jürgen V. Vogt, Katja Winger, George Zittis, and Alessandro Dosio

Abstract

Two questions motivated this study: 1) Will meteorological droughts become more frequent and severe during the twenty-first century? 2) Given the projected global temperature rise, to what extent does the inclusion of temperature (in addition to precipitation) in drought indicators play a role in future meteorological droughts? To answer, we analyzed the changes in drought frequency, severity, and historically undocumented extreme droughts over 1981–2100, using the standardized precipitation index (SPI; including precipitation only) and standardized precipitation-evapotranspiration index (SPEI; indirectly including temperature), and under two representative concentration pathways (RCP4.5 and RCP8.5). As input data, we employed 103 high-resolution (0.44°) simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), based on a combination of 16 global circulation models (GCMs) and 20 regional circulation models (RCMs). This is the first study on global drought projections including RCMs based on such a large ensemble of RCMs. Based on precipitation only, ~15% of the global land is likely to experience more frequent and severe droughts during 2071–2100 versus 1981–2010 for both scenarios. This increase is larger (~47% under RCP4.5, ~49% under RCP8.5) when precipitation and temperature are used. Both SPI and SPEI project more frequent and severe droughts, especially under RCP8.5, over southern South America, the Mediterranean region, southern Africa, southeastern China, Japan, and southern Australia. A decrease in drought is projected for high latitudes in Northern Hemisphere and Southeast Asia. If temperature is included, drought characteristics are projected to increase over North America, Amazonia, central Europe and Asia, the Horn of Africa, India, and central Australia; if only precipitation is considered, they are found to decrease over those areas.

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